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Search Results (1,065)

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31 pages, 8777 KiB  
Entry
State-of-the-Art Power Factor Correction: An Industry Perspective
by Claudio Adragna, Alberto Bianco, Giovanni Gritti and Matteo Sucameli
Encyclopedia 2024, 4(3), 1324-1354; https://doi.org/10.3390/encyclopedia4030087 (registering DOI) - 14 Sep 2024
Viewed by 280
Definition
On 1 January 2001, the IEC 61000-3-2 regulation became effective. Since then, mitigating current harmonics has been essential to ensure that electronic equipment connected to single-phase power distribution lines conforms to electromagnetic compatibility directives. Today, high-quality rectification, commonly known as power factor correction [...] Read more.
On 1 January 2001, the IEC 61000-3-2 regulation became effective. Since then, mitigating current harmonics has been essential to ensure that electronic equipment connected to single-phase power distribution lines conforms to electromagnetic compatibility directives. Today, high-quality rectification, commonly known as power factor correction (PFC), is a well-established technique widely adopted by the industry for powering various devices from the ac line. The topic has been studied by academia and industry since the mid-1980s; thus, an enormous amount of research has been published and countless solutions have been proposed since then. However, only a few of those solutions have encountered wide industrial usage. So, it is not the authors’ intention to provide a comprehensive review, but to take stock of the most used PFC techniques from an industry perspective. This paper will review the power factor theory with non-sinusoidal currents, the practical and regulatory aspects of using PFC, and the most common industry solutions for power factor correction in equipment operated from the single-phase, public, low-voltage supply system, with a special focus on boost PFC pre-regulators, their control methods, design procedures, and issues. Full article
(This article belongs to the Collection Encyclopedia of Engineering)
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Figure 1

Figure 1
<p>Front-end of a typical SMPS and related key waveforms.</p>
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<p>Ac circuit analysis with nonlinear loads: power triangles and general definitions of PF and THD of line current.</p>
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<p>Key waveforms of the low-frequency power processing in a PFC system.</p>
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<p>Block diagram summarizing PFC techniques.</p>
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<p>The special waveform envelope for class D equipment in IEC 61000-3-2:1995 [<a href="#B18-encyclopedia-04-00087" class="html-bibr">18</a>].</p>
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<p>An LC rectifier and related key waveforms.</p>
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<p>A Valley Fill circuit and related key waveforms.</p>
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<p>A line-frequency-commutated PFC system.</p>
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<p>Typical architectures of a power-factor-corrected SMPS: (<b>a</b>) with a non-isolated PFC; (<b>b</b>) with an isolated PFC.</p>
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<p>Single-stage power-factor-corrected SMPS for ripple-tolerant loads.</p>
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<p>Low-frequency power processing in a PFC stage with <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="bold-italic">C</mi> <mrow> <mi mathvariant="bold-italic">E</mi> <mi mathvariant="bold-italic">S</mi> </mrow> </msub> <mo>=</mo> <msub> <mi mathvariant="bold-italic">C</mi> <mrow> <mi mathvariant="bold-italic">o</mi> <mi mathvariant="bold-italic">u</mi> <mi mathvariant="bold-italic">t</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Single-stage power-factor-corrected SMPS with fast control loop.</p>
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<p>Basic schematic of a boost PFC pre-regulator.</p>
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<p>General control scheme of a boost PFC pre-regulator.</p>
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<p>Boost PFC pre-regulator with inrush limiting provisions.</p>
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<p>Boost PFC pre-regulator fundamental operating modes.</p>
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<p>FF-CCM Boost PFC pre-regulator with ACM control.</p>
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<p>FOT-CCM Boost PFC pre-regulator with PCM control.</p>
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<p>ZCD circuit and its operation.</p>
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<p>TM Boost PFC pre-regulator with PCM control.</p>
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<p>TM Boost PFC pre-regulator with VM control.</p>
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<p>Two-phase interleaved Boost PFC pre-regulator and inductor currents superposition with 180° out-of-phase operation.</p>
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<p>(<b>a</b>) Conventional boost PFC; (<b>b</b>) Dual boost bridgeless PFC; (<b>c</b>) Totem-pole bridgeless PFC.</p>
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<p>Typical architecture of a multi-string LED driver. Adapted with permission from [<a href="#B59-encyclopedia-04-00087" class="html-bibr">59</a>]. 2022 AEIT.</p>
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<p>TM-operated flyback PFC pre-regulator (<b>a</b>); key current waveforms (<b>b</b>). Adapted from [<a href="#B60-encyclopedia-04-00087" class="html-bibr">60</a>] and with permission from [<a href="#B61-encyclopedia-04-00087" class="html-bibr">61</a>]. 2003 STMicroelectronics.</p>
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<p>TM-operated SEPIC PFC pre-regulator (<b>a</b>); key current waveforms (<b>b</b>).</p>
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<p>TM-operated isolated SEPIC PFC pre-regulator.</p>
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<p>TM-operated buck-boost PFC pre-regulator. Adapted with permission from [<a href="#B65-encyclopedia-04-00087" class="html-bibr">65</a>]. 2003 STMicroelectronics.</p>
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13 pages, 4067 KiB  
Article
Tiny Security Hole: First-Order Vulnerability of Masked SEED and Its Countermeasure
by Ju-Hwan Kim and Dong-Guk Han
Sensors 2024, 24(18), 5894; https://doi.org/10.3390/s24185894 - 11 Sep 2024
Viewed by 215
Abstract
Side-channel analysis is a type of cryptanalysis that utilizes the physical leakage of a cryptographic device. An adversary exploits the relationship between a physical leakage and the secret intermediate value of an encryption algorithm. In order to prevent side-channel analysis, the masking method [...] Read more.
Side-channel analysis is a type of cryptanalysis that utilizes the physical leakage of a cryptographic device. An adversary exploits the relationship between a physical leakage and the secret intermediate value of an encryption algorithm. In order to prevent side-channel analysis, the masking method was proposed. Several masking methods of the ISO/IEC 18033-3 standard encryption algorithm SEED have been proposed, as the Korean financial IC (integrated circuit) card standard (CFIP.ST.FINIC-01-2021) mandates using a robust implementation of SEED as an encryption algorithm against side-channel analyses. However, vulnerabilities were reported, except for with only one masking method. This study proposes the first-order vulnerability of that masking method. That is, an adversary is able to perform a side-channel analysis with the same complexity as an unprotected implementation. In order to fix this vulnerability, we revise the masking method with negligible additional overhead. Its vulnerability and security are theoretically verified and experimentally demonstrated. The round key of the existing masking method is revealed with only 210 power consumption traces, while that of the proposed masking method is not disclosed with 10,000 traces. Full article
(This article belongs to the Special Issue Security, and Privacy in IoT and 6G Sensor Network)
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Figure 1
<p>Structure of the SEED Feistel function <span class="html-italic">F</span>. A rounded rectangle is an operation, and a sharp rectangle is an intermediate value.</p>
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<p>Masked function <span class="html-italic">G</span> of the existing masking scheme.</p>
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<p>Point-wise T-values and absolute correlation coefficients of the proposed intermediate value over 10,000 traces. The XOR part is the output byte-wise AND and XOR calculations. (Top: power consumption, middle: absolute T-value, bottom: absolute correlation coefficient of the correct key.)</p>
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<p>Absolute correlation coefficients of the correct key and incorrect keys according to the number of traces used.</p>
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<p>Guessed entropy and success rate derived from 10 CPAs.</p>
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<p>Masked function <span class="html-italic">G</span> of the proposed masking scheme.</p>
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<p>Point-wise T-values and absolute correlation coefficients of the proposed intermediate value over 10,000 traces. The XOR part is the output byte-wise AND and XOR calculations. The remask part changes the mask to <math display="inline"><semantics> <msub> <mi>M</mi> <mn>3</mn> </msub> </semantics></math> after XORing the four S-Box outputs. (Top: power consumption, middle: absolute T-value, bottom: absolute correlation coefficient of the correct key.)</p>
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<p>Absolute correlation coefficients of the correct key and incorrect keys according to the number of traces used.</p>
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<p>Guessed entropy and success rate derived from ten CPAs.</p>
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15 pages, 1625 KiB  
Article
The Relationship between HERV, Interleukin, and Transcription Factor Expression in ZIKV Infected versus Uninfected Trophoblastic Cells
by Anderson Luís da Costa, Paula Prieto-Oliveira, Márcia Duarte-Barbosa, Robert Andreata-Santos, Cristina M. Peter, Thamires Prolo de Brito, Fernando Antoneli, Ricardo Durães-Carvalho, Marcelo R. S. Briones, Juliana T. Maricato, Paolo M. A. Zanotto, Denis Jacob Machado and Luiz M. R. Janini
Cells 2024, 13(17), 1491; https://doi.org/10.3390/cells13171491 - 5 Sep 2024
Viewed by 420
Abstract
Zika virus (ZIKV) is an arbovirus with maternal, sexual, and TORCH-related transmission capabilities. After 2015, Brazil had the highest number of ZIVK-infected pregnant women who lost their babies or delivered them with Congenital ZIKV Syndrome (CZS). ZIKV triggers an immune defense in the [...] Read more.
Zika virus (ZIKV) is an arbovirus with maternal, sexual, and TORCH-related transmission capabilities. After 2015, Brazil had the highest number of ZIVK-infected pregnant women who lost their babies or delivered them with Congenital ZIKV Syndrome (CZS). ZIKV triggers an immune defense in the placenta. This immune response counts with the participation of interleukins and transcription factors. Additionally, it has the potential involvement of human endogenous retroviruses (HERVS). Interleukins are immune response regulators that aid immune tolerance and support syncytial structure development in the placenta, where syncytin receptors facilitate vital cell-to-cell fusion events. HERVs are remnants of ancient viral infections that integrate into the genome and produce syncytin proteins crucial for placental development. Since ZIKV can infect trophoblast cells, we analyzed the relationship between ZIKV infection, HERV, interleukin, and transcription factor modulations in the placenta. To investigate the impact of ZIKV on trophoblast cells, we examined two cell types (BeWo and HTR8) infected with ZIKV-MR766 (African) and ZIKV-IEC-Paraíba (Asian–Brazilian) using Taqman and RT2 Profiler PCR Array assays. Our results indicate that early ZIKV infection (24–72 h) does not induce differential interleukins, transcription factors, and HERV expression. However, we show that the expression of a few of these host defense genes appears to be linked independently of ZIKV infection. Future studies involving additional trophoblastic cell lineages and extended infection timelines will illuminate the dynamic interplay between ZIKV, HERVs, interleukins, and transcription factors in the placenta. Full article
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Figure 1
<p>Scatterplot. Differential expression in infected and non-infected cells by Log<sub>2</sub>(FC). Circles: BeWo cell lineage. Triangles: HTR8 cell lineage. Red: ZIKV MR766. Blue: ZIKV IEC. The dotted lines indicate the −1 and +1 intervals.</p>
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<p>Comparison of gene ∆CTs between infected and non-infected cells. Data from different cells were grouped by gene. The blue color represents the ∆CT of each gene in infected cells, and the pink color in non-infected cells. The <span class="html-italic">p</span>-values from Pearson’s tests are indicated right below the gene names.</p>
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<p>Pairwise ∆∆CT correlations. Cells contain the adjusted-R<sup>2</sup> values and are colored according to the <span class="html-italic">p</span>-value of each correlation test. Values in the X and Y axes correspond to the different gene names.</p>
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17 pages, 4156 KiB  
Article
Effect of METTL3 Gene on Lipopolysaccharide Induced Damage to Primary Small Intestinal Epithelial Cells in Sheep
by Yanjun Duan, Xiaoyang Lv, Xiukai Cao and Wei Sun
Int. J. Mol. Sci. 2024, 25(17), 9316; https://doi.org/10.3390/ijms25179316 - 28 Aug 2024
Viewed by 438
Abstract
Newborn lambs are susceptible to pathogenic bacterial infections leading to enteritis, which affects their growth and development and causes losses in sheep production. It has been reported that N6-methyladenosine (m6A) is closely related to innate immunity, but the effect of m6A on sheep [...] Read more.
Newborn lambs are susceptible to pathogenic bacterial infections leading to enteritis, which affects their growth and development and causes losses in sheep production. It has been reported that N6-methyladenosine (m6A) is closely related to innate immunity, but the effect of m6A on sheep small intestinal epithelial cells (IECs) and the mechanism involved have not been elucidated. Here, we investigated the effects of m6A on lipopolysaccharide (LPS)-induced inflammatory responses, apoptosis and oxidative stress in primary sheep IECs. First, the extracted IECs were identified by immunofluorescence using the epithelial cell signature protein cytokeratin 18 (CK18), and the cellular activity of IECs induced by different concentrations of LPS was determined by the CCK8 assay. Meanwhile, LPS could induce the upregulation of mRNA and protein levels of IECs cytokines IL1β, IL6 and TNFα and the apoptosis marker genes caspase-3, caspase-9, Bax, and apoptosis rate, reactive oxygen species (ROS) levels and mRNA levels of CAT, Mn-SOD and CuZn-SOD, and METTL3 were found to be upregulated during induction. It was hypothesized that METTL3 may have a potential effect on the induction of IECs by LPS. Overexpression and knockdown of METTL3 in IECs revealed that a low-level expression of METTL3 could reduce the inflammatory response, apoptosis and ROS levels in LPS-induced IECs to some extent. The results suggest that METTL3 may be a genetic marker for potential resistance to cellular damage. Full article
(This article belongs to the Special Issue The Twist and Turn of Lipids in Human Diseases 2.0)
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Figure 1
<p>Immunofluorescence analysis of the epithelial cell marker CK18 on IECs. (<b>A</b>) CCK8 detection results after 4 h of treatment with LPS at concentrations of 0 μg/mL, 0.5 μg/mL, 1 μg/mL, 2 μg/mL, 5 μg/mL, and 10 μg/mL on IECs (<b>B</b>). Protein expression of METTL3 in IECs after 4 h of treatment with the same LPS concentrations (<b>C</b>). The image scale is 200×. The data are presented as means ± SEM (standard error of the mean) (<span class="html-italic">n</span> = 3). The statistical significance was assessed using the unpaired Student’s <span class="html-italic">t</span>-test. (Unmarked: <span class="html-italic">p</span> &gt; 0.05; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>The mRNA levels of cytokines <span class="html-italic">IL1β</span>, <span class="html-italic">IL6</span>, and <span class="html-italic">TNFα</span> in IECs in the LPS group and control group (<b>A</b>–<b>C</b>). Protein levels of IL1β, IL6, and TNFα in IECs cell cultures stimulated by different concentrations of LPS (<b>D</b>–<b>F</b>). The mRNA levels of apoptosis marker genes <span class="html-italic">caspase-3</span>, <span class="html-italic">caspase-9</span>, and <span class="html-italic">Bax</span> in the LPS group and control group (<b>G</b>–<b>I</b>). Cells in different states in the LPS group and control group, with Q1, Q2, Q3, and Q4, respectively, representing necrotic or mechanically damaged cells, late apoptotic cells, living cells, and early apoptotic cells (<b>J</b>). Statistical analysis of the proportion of apoptotic cells in the LPS group and control group (<b>K</b>). ROS levels (<b>L</b>) and mRNA levels of antioxidant marker genes <span class="html-italic">CAT</span>, <span class="html-italic">Mn-SOD</span>, and <span class="html-italic">CuZn-SOD</span> in the LPS group and control group (<b>M</b>–<b>O</b>). The data are presented as means ± SEM (standard error of the mean) (<span class="html-italic">n</span> = 3). The statistical significance was assessed using the unpaired Student’s <span class="html-italic">t</span>-test. (Unmarked: <span class="html-italic">p</span> &gt; 0.05; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Legend for pcDNA3.1 empty vector (<b>A</b>). PCR identification of the <span class="html-italic">METTL3</span> overexpression vector (<b>B</b>). Sanger sequencing results of the <span class="html-italic">METTL3</span> overexpression vector (<b>C</b>).</p>
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<p>Fluorescence images of pcDNA3.1-EGFP fluorescent vector and FAM-labelled negative control in IECs. (<b>A</b>,<b>B</b>). The mRNA levels after <span class="html-italic">METTL3</span> overexpression and interference in IECs. (<b>C</b>,<b>D</b>). Expression of protein level after overexpression and interference of METTL3 in IECs. (<b>E</b>,<b>F</b>). The image scale is 100×. The data are presented as means ± SEM (standard error of the mean) (<span class="html-italic">n</span> = 3). The statistical significance was assessed using the unpaired Student’s <span class="html-italic">t</span>-test. (NS: <span class="html-italic">p</span> &gt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>The mRNA expression levels of cytokines <span class="html-italic">IL1β</span>, <span class="html-italic">IL6</span>, and <span class="html-italic">TNFα</span> in IECs after LPS induced overexpression of <span class="html-italic">METTL3</span> (<b>A</b>–<b>C</b>). Protein expression levels of cytokines IL1β, IL6, and TNFα in IECs after LPS induced overexpression of <span class="html-italic">METTL3</span> (<b>D</b>–<b>F</b>). The mRNA expression levels of cytokines IL1β, IL6, and TNFα in IECs after LPS induced interference with <span class="html-italic">METTL3</span> (<b>G</b>–<b>I</b>). Protein expression levels of cytokines IL1β, IL6, and TNFα in IECs after LPS induced interference with <span class="html-italic">METTL3</span> (<b>J</b>–<b>L</b>). The data are presented as means ± SEM (standard error of the mean) (<span class="html-italic">n</span> = 3). The statistical significance was assessed using the unpaired Student’s <span class="html-italic">t</span>-test. (Unmarked: <span class="html-italic">p</span> &gt; 0.05; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>The mRNA levels of apoptosis marker genes <span class="html-italic">Caspase-3</span>, <span class="html-italic">Caspase-9</span>, and <span class="html-italic">Bax</span> in IECs after LPS-induced <span class="html-italic">METTL3</span> overexpression (<b>A</b>–<b>C</b>). The mRNA levels of apoptosis marker genes <span class="html-italic">Caspase-3</span>, <span class="html-italic">Caspase-9</span>, and <span class="html-italic">Bax</span> in IECs after LPS-induced interference with <span class="html-italic">METTL3</span> (<b>D</b>–<b>F</b>). Cells in different states of IECs after LPS-induced overexpression and interference of <span class="html-italic">METTL3</span>, with Q1, Q2, Q3, and Q4, respectively, representing necrotic or mechanically damaged cells, late apoptotic cells, living cells, and early apoptotic cells (<b>G</b>,<b>I</b>). Statistical analysis of apoptotic cells in IECs after LPS-induced overexpression and interference of <span class="html-italic">METTL3</span> (<b>H</b>,<b>J</b>). The data are presented as means ± SEM (standard error of the mean) (<span class="html-italic">n</span> = 3). The statistical significance was assessed using the unpaired Student’s <span class="html-italic">t</span>-test. (Unmarked: <span class="html-italic">p</span> &gt; 0.05; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>ROS levels in IECs after LPS-induced overexpression of <span class="html-italic">METTL3</span> (<b>A</b>) and ROS levels in IECs after LPS-induced interference with <span class="html-italic">METTL3</span> (<b>E</b>). The mRNA expression levels of antioxidant marker genes <span class="html-italic">CAT</span>, <span class="html-italic">Mn-SOD</span>, and <span class="html-italic">CuZn-SOD</span> in IECs after LPS-induced overexpression of <span class="html-italic">METTL3</span> (<b>B</b>–<b>D</b>) and the mRNA expression levels of antioxidant marker genes <span class="html-italic">CAT</span>, <span class="html-italic">Mn-SOD</span>, and <span class="html-italic">CuZn-SOD</span> in IECs after LPS-induced interference with METTL3 (<b>F</b>–<b>H</b>). The data are presented as means ± SEM (standard error of the mean) (<span class="html-italic">n</span> = 3). The statistical significance was assessed using the unpaired Student’s <span class="html-italic">t</span>-test. (Unmarked: <span class="html-italic">p</span> &gt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>(<b>A</b>–<b>C</b>) represent the standard curves for IL1β, IL6, and TNFα, respectively, with the X-axis representing the different concentrations of standards (pg/mL) and the Y-axis representing the OD values obtained for each concentration.</p>
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18 pages, 6368 KiB  
Article
The Current Harmonic Impact on Active Power Losses and Temperature Distribution in Power Cables
by Natalia Radwan-Pragłowska, Dominik Mamcarz, Paweł Albrechtowicz and Bartosz Rozegnał
Energies 2024, 17(16), 4170; https://doi.org/10.3390/en17164170 - 21 Aug 2024
Viewed by 464
Abstract
The active power losses are dependent on the flowing electric power value through overhead and cable lines. The current flow through the conductor causes negative phenomena to occur, such as released heat. The source of the current harmonics is the non-linear loads. Hence, [...] Read more.
The active power losses are dependent on the flowing electric power value through overhead and cable lines. The current flow through the conductor causes negative phenomena to occur, such as released heat. The source of the current harmonics is the non-linear loads. Hence, the skin effect occurs, and the current carrying capacity of cables is reduced. This results in the increase in and uneven distribution of the temperature inside the conductor. This paper presents a comparison of the temperature distribution inside a power cable for an ideal 50 Hz sine wave and highly distorted current (THDI=41%). The calculated active power losses for the IEC 60287-1-1:2006+A1:2014 standard and the method described in the literature were used as a basis for further calculations. The obtained results revealed the problem of the uneven distribution of the conductor temperature. Considering the skin effect, increasing the temperature in the outer layers leads to severe damage and faster insulation aging. The abovementioned phenomenon is a decrease in the permissible load capacity of the conductor. The table given in the IEC 60364-5-52 standard summarizes the percentage contribution of the third harmonic to the current waveform. For percentages between 15% and 33%, the current carrying capacity is reduced by up to 86% of the full-load current rating. In addition, consideration of thermal conditions forces the use of cables with larger cross-sections. This leads to their non-optimal use and makes the investment more expensive from an economic point of view. Full article
(This article belongs to the Special Issue Energy, Electrical and Power Engineering 2024)
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Figure 1
<p>The skin effect illustration.</p>
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<p>The frequency-dependent effective conductor cross-area.</p>
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<p>(<b>a</b>) Electrical cable construction; (<b>b</b>,<b>c</b>) cable arrangement: (<b>b</b>) flat formation; (<b>c</b>) trefoil formation.</p>
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<p>The excavation geometry.</p>
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<p>Unit active power losses for selected cross-sections of YKY-type cables.</p>
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<p>Current spectrum (THD<sub>I</sub> = 76%).</p>
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<p>Increases in power losses in relation to the ideal current waveform (THD = 0%).</p>
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<p>Increase in resistance, according to the fundamental harmonic resistance of a 35 mm<sup>2</sup> cable, for the analyzed methods (conductor/cable core temperature of 20 °C).</p>
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<p>Increase in resistance, according to the fundamental harmonic resistance of a 300 mm<sup>2</sup> cable, for the analyzed methods (conductor/cable core temperature of 20 °C).</p>
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<p>Increase in resistance, according to the fundamental harmonic resistance of a 35 mm<sup>2</sup> cable, for the analyzed methods (conductor/cable core temperature of ~90 °C).</p>
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<p>Increase in resistance, according to the fundamental harmonic resistance of a 300 mm<sup>2</sup> cable, for the analyzed methods (conductor/cable core temperature of ~85 °C).</p>
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<p>Active power losses for the fundamental frequency calculated using different methods.</p>
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<p>The temperature distribution for the cable YKY 1 × 150 mm<sup>2</sup> surrounded by air.</p>
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<p>The temperature distribution for the cable YKY 1 × 150 mm<sup>2</sup> surrounded by sand.</p>
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<p>The temperature changes along the cable (1 × 150 mm<sup>2</sup>) radius and for surrounding sand: (<b>a</b>) THD 76%; (<b>b</b>) 32%.</p>
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<p>The temperature changes along the cable (1 × 150 mm<sup>2</sup>) radius and for surrounding air: (<b>a</b>) THD 76%; (<b>b</b>) 32%.</p>
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<p>The temperature distribution at the boundary of two media air/sand for YKY 1 × 300 mm<sup>2</sup> cable (the hot-spot temperature was 53.91 °C).</p>
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<p>The temperature changes along the cable, taking into account two types of environment: A—CPD method, B—IEC method, C—AM method; (<b>a</b>) THD 76%; (<b>b</b>) 32%.</p>
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23 pages, 8470 KiB  
Article
Improved Control Technique for Enhancing Power System Stability in Out-of-Step Conditions
by Nande Fose, Senthil Krishnamurthy and Prathaban Moodley
Energies 2024, 17(16), 4086; https://doi.org/10.3390/en17164086 - 16 Aug 2024
Viewed by 634
Abstract
From time to time, a series of unpredictable and conflicting contingencies can lead to angular instability of the power system and even blackouts if not adequately handled by an out-of-step (OOS) protection system. The key contribution of this research work, to the theory [...] Read more.
From time to time, a series of unpredictable and conflicting contingencies can lead to angular instability of the power system and even blackouts if not adequately handled by an out-of-step (OOS) protection system. The key contribution of this research work, to the theory of out-of-step protection, is the identification and isolation after a given disruption of many unstable swings. This paper presents a proposed method to avoid false operation for distance function by out-of-step blocking to improve the system stability by using optimally placed PMUs for the fast detection of system analogue quantities. The studies were performed on a modified Eskom transmission network in the Western Cape with 765 kV and 400 kV voltage levels. The aim is to investigate the IEC 61850-90-5 standard for predictive dynamic stability maintaining systems using PMUs for out-of-step conditions of synchronous generators. The power system modelling and simulation are performed in the RSCAD-FX for the proposed multi-area power system network. An experimental lab-scale implementation is built to test the proposed out-of-step algorithm in a real-time digital simulator. Software-based PMU is incorporated to test and validate the IEC 61850-90-5 standard sampled values. Simulation and experimental results are presented. Full article
(This article belongs to the Topic Power System Protection)
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<p>Impedance-based OOS characteristic using concentric polygon.</p>
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<p>Flow chart for PMU algorithm execution.</p>
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<p>Equivalent phasor diagram generated from measured quantities and computed equivalent system impedances.</p>
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<p>PMU metering values received by the relay.</p>
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<p>GOOSE tripping circuit breaker control logic in RSCAD-FX draft.</p>
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<p>Modified Eskom 400kV western grid network.</p>
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<p>Hardware-in-the-loop test bench setup fully integrated with virtual PMU.</p>
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<p>Area 3 network with PMU integrated on RSCAD-FX draft interface.</p>
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<p>Resultant plots when a zone 1 fault is exhibited on the Palmiet_Pinotage 400 kV line. (<b>a</b>) Current and voltage signals with GOOSE digital outputs. (<b>b</b>) Rotor machine control variables during zone 1 fault.</p>
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<p>Palmiet generation supply and load profiles during zone 1 fault. (<b>a</b>) Palmiet generating unit supply with zone 1 fault cleared. (<b>b</b>) Palmiet transmission line load during the disturbance.</p>
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<p>Resultant graphs when a bus fault is employed on the system. (<b>a</b>) CT and PT analogues along with GOOSE data sets for out-of-step conditions. (<b>b</b>) Rotor control variables during this disturbance.</p>
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<p>System generating sources as Palmiet generators lose synchronism with the rest of the system due to OST being detected. (<b>a</b>) Palmiet generating supply during pole slipping. (<b>b</b>) System power transfer capabilities with Palmiet generating units losing synchronism with the rest of the system.</p>
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<p>RMS/EMT simulation for OOS tripping with a longer timestamp.</p>
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<p>Modified West Grid Transmission network system model in RSCAD-FX.</p>
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<p>OOS algorithm for the protection philosophy.</p>
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17 pages, 5381 KiB  
Article
Evaluation of the Antifibrotic Effects of Drugs Commonly Used in Inflammatory Intestinal Diseases on In Vitro Intestinal Cellular Models
by Serena Artone, Alessia Ciafarone, Francesca Rosaria Augello, Francesca Lombardi, Maria Grazia Cifone, Paola Palumbo, Benedetta Cinque and Giovanni Latella
Int. J. Mol. Sci. 2024, 25(16), 8862; https://doi.org/10.3390/ijms25168862 - 14 Aug 2024
Viewed by 580
Abstract
The mechanism underlying intestinal fibrosis, the main complication of inflammatory bowel disease (IBD), is not yet fully understood, and there is no therapy to prevent or reverse fibrosis. We evaluated, in in vitro cellular models, the ability of different classes of drugs currently [...] Read more.
The mechanism underlying intestinal fibrosis, the main complication of inflammatory bowel disease (IBD), is not yet fully understood, and there is no therapy to prevent or reverse fibrosis. We evaluated, in in vitro cellular models, the ability of different classes of drugs currently used in IBD to counteract two pivotal processes of intestinal fibrosis, the differentiation of intestinal fibroblasts to activated myofibroblasts using CCD-18Co cells, and the epithelial-to-mesenchymal transition (EMT) of intestinal epithelial cells using Caco-2 cells (IEC), both being processes induced by transforming growth factor-β1 (TGF-β1). The drugs tested included mesalamine, azathioprine, methotrexate, prednisone, methylprednisolone, budesonide, infliximab, and adalimumab. The expression of fibrosis and EMT markers (collagen-I, α-SMA, pSmad2/3, occludin) was assessed by Western blot analysis and by immunofluorescence. Of the drugs used, only prednisone, methylprednisolone, budesonide, and adalimumab were able to antagonize the pro-fibrotic effects induced by TGF-β1 on CCD-18Co cells, reducing the fibrosis marker expression. Methylprednisolone, budesonide, and adalimumab were also able to significantly counteract the TGF-β1-induced EMT process on Caco-2 IEC by increasing occludin and decreasing α-SMA expression. This is the first study that evaluates, using in vitro cellular models, the direct antifibrotic effects of drugs currently used in IBD, highlighting which drugs have potential antifibrotic effects. Full article
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<p>Cell viability of CCD-18Co and IEC Caco-2. (<b>A</b>) Cell viability of CCD-18Co cells incubated for 48 h with mesalamine (0.1–5 mM), azathioprine (5–20 µM), prednisone (10–100 µM), methylprednisolone (50–200 µM), budesonide (0.1–5 µM), methotrexate (0.1–1 µM), infliximab (10–50 µg/mL), and adalimumab (20–100 µg/mL). (<b>B</b>) IEC Caco-2 cells incubated up to 96 h with mesalamine (5–50 mM), azathioprine (1–20 µM), prednisone (10–200 µM), methylprednisolone (10–200 µM), budesonide (7–70 µM), methotrexate (1–50 µM), infliximab (25–200 µg/mL), and adalimumab (8–100 µg/mL). The data are from two independent experiments performed in triplicate, and values are expressed as mean ± SEM. For comparative analysis of data, a one-way ANOVA for CCD-18Co cells and two-way ANOVA for IEC Caco-2 cells followed by Dunnett’s post hoc test were performed. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Effect of tested drugs on TGB-β1-induced collagen I and α-SMA expression in CCD-18Co cells. Immunoblotting assay for collagen I and α-SMA was performed on CCD-18Co cells incubated for 48 h with TGF-β1 (10 ng/mL) in the presence or absence of (<b>A</b>) mesalamine (0.1–1 mM), (<b>B</b>) azathioprine (5–10 µM), (<b>C</b>) prednisone (10–50 µM), (<b>D</b>) methylprednisolone (50–100 µM), (<b>E</b>) budesonide (0.1–1 µM), (<b>F</b>) methotrexate (0.1–0.5 µM), (<b>G</b>) infliximab (10–25 µg/mL), and (<b>H</b>) adalimumab (20–50 µg/mL). Representative images of immunoblotting for collagen I (130 kDa), α-SMA (42 kDa), and GAPDH (37 kDa) are shown. The data are from three independent experiments, and values are expressed as mean ± SEM. For comparative analysis of data, a one-way analysis of variance (ANOVA) with Dunnett’s post hoc test was used. Densitometric analysis was performed by normalizing vs. GAPDH. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effect of drugs on TGB-β1-induced collagen I expression in CCD-18Co cells. Representative immunofluorescence images of untreated and treated CCD-18Co cells, as above described, stained with anti-collagen I antibody (green) and TRITC-phalloidin (red) to reveal F-actin. Nuclei were counterstained with DAPI (blue) (magnification 40×). The images are representative of three independent experiments in duplicate.</p>
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<p>Effect of drugs on TGB-β1-induced α-SMA expression in CCD-18Co cells. Representative immunofluorescence images of untreated and treated CCD-18Co cells, as described above, stained with anti-α-SMA antibody (green) and TRITC-phalloidin (red) to reveal F-actin. Nuclei were counterstained with DAPI (blue) (magnification 40×). The images are representative of three independent experiments performed in duplicate.</p>
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<p>Effect of tested drugs on TGB-β1-induced Smad signaling in CCD-18Co cells. Immunoblotting assay for pSmad 2/3 was performed on CCD-18Co cells incubated for 48 h with TGF-β1 (10 ng/mL) in the presence or absence of (<b>A</b>) mesalamine (0.1–1 mM), (<b>B</b>) azathioprine (5–10 µM), (<b>C</b>) prednisone (10–50 µM), (<b>D</b>) methylprednisolone (50–100 µM), (<b>E</b>) budesonide (0.1–1 µM), (<b>F</b>) methotrexate (0.1–0.5 µM), (<b>G</b>) infliximab (10–25 µg/mL), and (<b>H</b>) adalimumab (20–50 µg/mL). Representative images of immunoblotting pSmad2/3 (52 kDa) and GAPDH (37 kDa) are shown. The data are from three independent experiments, and values are expressed as mean ± SEM. For comparative analysis of data, a one-way analysis of variance (ANOVA) with Dunnett’s post hoc test was used. Densitometric analysis was performed by normalizing vs. GAPDH. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effect of tested drugs on EMT in Caco-2 IEC cells. Immunoblotting assay for occludin and α-SMA was performed on Caco-2 IEC cells incubated for 96 h with TGF-β1 (20 ng/mL) in the presence or absence of (<b>A</b>) mesalamine (5–20 mM), (<b>B</b>) azathioprine (1–10 µM), (<b>C</b>) prednisone (10–100 µM), (<b>D</b>) methylprednisolone (10–100 µM), (<b>E</b>) budesonide (7–45 µM), (<b>F</b>) methotrexate (1–20 µM), (<b>G</b>) infliximab (25–100 µg/mL), and (<b>H</b>) adalimumab (8–50 µg/mL). Representative images of immunoblotting for occludin (59 kDa), α-SMA (42 kDa), and GAPDH (37 kDa) are shown. The data are from three independent experiments, and values are expressed as mean ± SEM. For comparative analysis of data, a one-way analysis of variance (ANOVA) with Dunnett’s post hoc test was used. Densitometric analysis was performed by normalizing vs. GAPDH. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effect of drugs on EMT markers (occludin and α-SMA expression) in Caco-2 IEC cells. Representative immunofluorescence images of untreated and treated Caco-2 IEC cells, as described above, stained with anti-occludin and anti-α-SMA antibodies (green). Nuclei were counterstained with DAPI (blue) (magnification 40×). The images are representative of three independent experiments in duplicate.</p>
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<p>Graphical representation of the main results obtained on the two cell models used in this work.</p>
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29 pages, 9969 KiB  
Article
Calibration of a Class A Power Quality Analyser Connected to the Cloud in Real Time
by A. Cano-Ortega, F. Sanchez-Sutil, J. C. Hernandez, C. Gilabert-Torres and C. R. Baier
Electronics 2024, 13(16), 3209; https://doi.org/10.3390/electronics13163209 - 13 Aug 2024
Viewed by 619
Abstract
Power quality measurements are essential to monitor, analyse and control the operation of smart grids within power systems. This work aims to develop and calibrate a PQ network analyser. As the penetration of non-linear loads connected to power systems is increasing every day, [...] Read more.
Power quality measurements are essential to monitor, analyse and control the operation of smart grids within power systems. This work aims to develop and calibrate a PQ network analyser. As the penetration of non-linear loads connected to power systems is increasing every day, it is essential to measure power quality. In this sense, a power quality (PQ) analyser is based on the high-speed sampling of electrical signals in single-phase and three-phase electrical installations, which are available in real time for analysis using wireless Wi-Fi (Wireless-Fidelity) networks. The PQAE (Power Quality Analyser Embedded) power quality analyser has met the calibration standards for Class A devices from IEC 61000-4-30, IEC 61000-4-7 and IEC 62586-2. In this paper, a complete guide to the tests included in this standard has been provided. The Fast Fourier Transform (FFT) obtains the harmonic components from the measured signals and the window functions used reduce spectral leakage. The window size depends on the fundamental frequency of, intensity of and changes in the signal. Harmonic measurements from the 2nd to 50th harmonics for each phase of the voltage and each phase and neutral of the current have been performed, using the Fast Fourier transform algorithm with various window functions and their comparisons. PQAE is developed on an open-source platform that allows you to adapt its programming to the measurement needs of the users. Full article
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<p>Diagram circuit PQAE.</p>
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<p>Power quality measurement flowchart based on IEC standards.</p>
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<p>Sampling time to read the magnitudes.</p>
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<p>Signal sampling flowchart.</p>
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<p>Harmonic smoothing with digital low-pass filtering.</p>
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<p>Summary of calibration tests.</p>
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<p>Test equipment in the laboratory at the University of Jaen.</p>
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<p>Wiring diagram for the test.</p>
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<p>Window functions to current and voltage (Rectangular, FlatTop, Hann, Hamming). (<b>a</b>) Voltage 50 Hz. (<b>b</b>) Voltage 100-2500 Hz. (<b>c</b>) Current 50 Hz. (<b>d</b>) Current 0.1–2.5 kHz.</p>
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<p>Frequency tests. (<b>a</b>) Test point F1-1 (42.5 Hz); (<b>b</b>) Test point F1-2 (50.05 Hz); (<b>c</b>) Test point F1-3 (57.5 Hz); (<b>d</b>) Test point F2-1 (10% <span class="html-italic">V<sub>nom</sub></span>); and (<b>e</b>) Test point F2-2 (Harmonics).</p>
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<p>Frequency tests. (<b>a</b>) Test point F1-1 (42.5 Hz); (<b>b</b>) Test point F1-2 (50.05 Hz); (<b>c</b>) Test point F1-3 (57.5 Hz); (<b>d</b>) Test point F2-1 (10% <span class="html-italic">V<sub>nom</sub></span>); and (<b>e</b>) Test point F2-2 (Harmonics).</p>
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<p>Voltage tests. (<b>a</b>) Test point V1-1 (10% <span class="html-italic">V<sub>nom</sub></span>); (<b>b</b>) Test point V1-2 (80% <span class="html-italic">V<sub>nom</sub></span>) (<b>c</b>) Test point V1-3 (150% <span class="html-italic">V<sub>nom</sub></span>); (<b>d</b>) Test point V2-1 (42.5 Hz); (<b>e</b>) Test point V2-1 (50 Hz); (<b>e</b>) Test point V2-2 (57.5 Hz); (<b>f</b>) Test point V3-1 (Harmonics).</p>
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<p>Current tests. (<b>a</b>) Test point I1-1 (10% <span class="html-italic">I<sub>nom</sub></span>); (<b>b</b>) Test point I1-2 (80% <span class="html-italic">I<sub>nom</sub></span>) (<b>c</b>) Test point I1-3 (100% <span class="html-italic">I<sub>nom</sub></span>; (<b>d</b>) Test point I2-1 (42.5 Hz); (<b>e</b>) Test point I2-2 (57.5 Hz); (<b>f</b>) Test point I3-1 (Harmonics).</p>
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<p>Current tests. (<b>a</b>) Test point I1-1 (10% <span class="html-italic">I<sub>nom</sub></span>); (<b>b</b>) Test point I1-2 (80% <span class="html-italic">I<sub>nom</sub></span>) (<b>c</b>) Test point I1-3 (100% <span class="html-italic">I<sub>nom</sub></span>; (<b>d</b>) Test point I2-1 (42.5 Hz); (<b>e</b>) Test point I2-2 (57.5 Hz); (<b>f</b>) Test point I3-1 (Harmonics).</p>
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<p>Harmonics voltage tests. (<b>a</b>) Test point HV1-1 (2nd H 5% <span class="html-italic">V<sub>nom</sub></span>); (<b>b</b>) Test point HV1-2 (3rd H 10% <span class="html-italic">V<sub>nom</sub></span>); (<b>c</b>) Test point HV1-3 (50th H 1% <span class="html-italic">V<sub>nom</sub></span>); (<b>d</b>) Test point HV1-4 ((2–50th) H 10% of class 3 levels); (<b>e</b>) Test point HV1-5 ((2–50th) H 10% of class 3 levels); (<b>f</b>) Test point HV2-1 (42.5 Hz); (<b>g</b>) Test point HV2-2 (57.5 Hz); (<b>h</b>) Test point HV3-1 (10% <span class="html-italic">V<sub>nom</sub></span>); (<b>i</b>) Test point HV3-2 (100% <span class="html-italic">V<sub>nom</sub></span>).</p>
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<p>Harmonics voltage tests. (<b>a</b>) Test point HV1-1 (2nd H 5% <span class="html-italic">V<sub>nom</sub></span>); (<b>b</b>) Test point HV1-2 (3rd H 10% <span class="html-italic">V<sub>nom</sub></span>); (<b>c</b>) Test point HV1-3 (50th H 1% <span class="html-italic">V<sub>nom</sub></span>); (<b>d</b>) Test point HV1-4 ((2–50th) H 10% of class 3 levels); (<b>e</b>) Test point HV1-5 ((2–50th) H 10% of class 3 levels); (<b>f</b>) Test point HV2-1 (42.5 Hz); (<b>g</b>) Test point HV2-2 (57.5 Hz); (<b>h</b>) Test point HV3-1 (10% <span class="html-italic">V<sub>nom</sub></span>); (<b>i</b>) Test point HV3-2 (100% <span class="html-italic">V<sub>nom</sub></span>).</p>
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<p>Harmonics current tests. (<b>a</b>) Test point HI1-1 (2nd H 5% <span class="html-italic">I<sub>nom</sub></span>); (<b>b</b>) Test point HI1-2 (3rd H 10% <span class="html-italic">I<sub>nom</sub></span>); (<b>c</b>) Test point HI1-3 (50th H 1% <span class="html-italic">I<sub>nom</sub></span>); (<b>d</b>) Test point HI1-4 ((2–50th) H 10% of class 3 levels from IEC 61000-2-4); (<b>e</b>) Test point HI1-5 ((2–50th) H 10% of class 3 levels from IEC 61000-2-4); (<b>f</b>) Test point HI2-1 (42.5 Hz); (<b>g</b>) Test point HI2-2 (57.5 Hz); (<b>h</b>) Test point HI3-1 (10% <span class="html-italic">I<sub>nom</sub></span>); (<b>i</b>) Test point HI3-2 (100% <span class="html-italic">I<sub>nom</sub></span>).</p>
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<p>Harmonics current tests. (<b>a</b>) Test point HI1-1 (2nd H 5% <span class="html-italic">I<sub>nom</sub></span>); (<b>b</b>) Test point HI1-2 (3rd H 10% <span class="html-italic">I<sub>nom</sub></span>); (<b>c</b>) Test point HI1-3 (50th H 1% <span class="html-italic">I<sub>nom</sub></span>); (<b>d</b>) Test point HI1-4 ((2–50th) H 10% of class 3 levels from IEC 61000-2-4); (<b>e</b>) Test point HI1-5 ((2–50th) H 10% of class 3 levels from IEC 61000-2-4); (<b>f</b>) Test point HI2-1 (42.5 Hz); (<b>g</b>) Test point HI2-2 (57.5 Hz); (<b>h</b>) Test point HI3-1 (10% <span class="html-italic">I<sub>nom</sub></span>); (<b>i</b>) Test point HI3-2 (100% <span class="html-italic">I<sub>nom</sub></span>).</p>
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<p>Data visualisation in the PQAE app.</p>
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12 pages, 2259 KiB  
Article
Charge Variants Characterization of Co-Formulated Antibodies by Three-Dimensional Liquid Chromatography–Mass Spectrometry
by Xiaoqing Jin, Luna Chen, Jianlin Chu and Bingfang He
Biomolecules 2024, 14(8), 999; https://doi.org/10.3390/biom14080999 - 13 Aug 2024
Viewed by 433
Abstract
Co-formulated antibodies can bring clinical benefits to patients by combining two or more antibodies in a single dosage form. However, the quality analysis of co-formulated antibodies raises additional challenges, compared to individual antibodies, due to the need for accurate analysis of multiple antibodies [...] Read more.
Co-formulated antibodies can bring clinical benefits to patients by combining two or more antibodies in a single dosage form. However, the quality analysis of co-formulated antibodies raises additional challenges, compared to individual antibodies, due to the need for accurate analysis of multiple antibodies in one solution. It is extremely difficult to effectively separate the charge variants of the two co-formulated antibodies using one ion exchange chromatography (IEC) method because of their similar characteristics. In this study, a novel method was developed for the charge variants characterization of co-formulated antibodies using three-dimensional liquid chromatography–mass spectrometry (3D-LC-MS). Hydrophobic interaction chromatography (HIC) was used as the first dimension to separate and collect the two co-formulated antibodies. The two collections were then injected into the second-dimension IEC separately for charge variants separation and analysis. Subsequently, the separated charge variants underwent on-line desalting in the third-dimension reverse-phase chromatography (RPC) and subsequent mass spectroscopy analysis. The novel method could simultaneously provide a charge variants ratio and post-translational modification (PTM) data for the two co-formulated antibodies. Therefore, it could be used for release testing and stability studies of co-formulated antibodies, making up for the shortcomings of the existing approaches. It was the first time that charge variants of co-formulated antibodies were characterized by the 3D-LC-MS method, to the best of our knowledge. Full article
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<p>Schematic diagram of the 3D-LC-MS method for the charge variants characterization of co-formulated antibodies.</p>
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<p>Chromatography of mAb A and mAb B in the HIC optimization. (<b>A1</b>) mAb A under the conditions of optimization 1; (<b>A2</b>) mAb B under the conditions of optimization 1; (<b>B1</b>) mAb A under the conditions of optimization 2; (<b>B2</b>) mAb B under the conditions of optimization 2; (<b>C1</b>) mAb A under the conditions of optimization 3; and (<b>C2</b>) mAb B under the conditions of optimization 3.</p>
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<p>Chromatography overlay in optimized HIC. (<b>A</b>) Individual mAb A, individual mAb B, and co-formulated antibodies in optimized HIC; (<b>B</b>) co-formulated antibodies in optimized HIC in triplicate. The difference in the retention time was due to the different columns and HPLCs, but there was no detrimental effect on the resolutions of the mAb A peak and the mAb B peak.</p>
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<p>Raw MS spectra and deconvoluted MS spectra of charge variants of mAb A in co-formulated antibodies using the 3D-LC-MS method. (<b>A1</b>) Raw MS spectra of acidic peak 1; (<b>A2</b>) deconvoluted MS spectra of acidic peak 1; (<b>B1</b>) raw MS spectra of acidic peak 2; (<b>B2</b>) deconvoluted MS spectra of acidic peak 2; (<b>C1</b>) raw MS spectra of main peak 3; (<b>C2</b>) deconvoluted MS spectra of main peak 3; (<b>D1</b>) raw MS spectra of basic peak 4; (<b>D2</b>) deconvoluted MS spectra of basic peak 4; (<b>E1</b>) raw MS spectra of basic peak 5; and (<b>E2</b>) deconvoluted MS spectra of basic peak 5. There were some species with +98 Da in the deconvoluted MS spectra, which arose from the attachment of phosphoric acid. Phosphoric acid adducts were very common in MS [<a href="#B19-biomolecules-14-00999" class="html-bibr">19</a>] when phosphoric acid was used in the mobile phase, even though the desalting step was utilized before MS.</p>
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<p>Raw MS spectra and deconvoluted MS spectra of charge variants of mAb B in co-formulated antibodies using the 3D-LC-MS method. (<b>A1</b>) Raw MS spectra of acidic peak 1; (<b>A2</b>) deconvoluted MS spectra of acidic peak 1; (<b>B1</b>) raw MS spectra of acidic peak 2; (<b>B2</b>) deconvoluted MS spectra of acidic peak 2; (<b>C1</b>) raw MS spectra of main peak 3; (<b>C2</b>) deconvoluted MS spectra of main peak 3; (<b>D1</b>) raw MS spectra of basic peak 4; (<b>D2</b>) deconvoluted MS spectra of basic peak 4; (<b>E1</b>) raw MS spectra of basic peak 5; and (<b>E2</b>) deconvoluted MS spectra of basic peak 5. There were some species with +98 Da in the deconvoluted MS spectra, which arose from the attachment of phosphoric acid. Phosphoric acid adducts were very common in MS [<a href="#B19-biomolecules-14-00999" class="html-bibr">19</a>] when phosphoric acid was used in the mobile phase, even though the desalting step was utilized before MS.</p>
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14 pages, 2115 KiB  
Article
IV-SSIM—The Structural Similarity Metric for Immersive Video
by Adrian Dziembowski, Weronika Nowak and Jakub Stankowski
Appl. Sci. 2024, 14(16), 7090; https://doi.org/10.3390/app14167090 - 13 Aug 2024
Viewed by 535
Abstract
In this paper, we present a new objective quality metric designed for immersive video applications—IV-SSIM. The proposed IV-SSIM metric is an evolution of our previous work—IV-PSNR (immersive video peak signal-to-noise ratio)—which became a commonly used metric in research and ISO/IEC MPEG standardization activities [...] Read more.
In this paper, we present a new objective quality metric designed for immersive video applications—IV-SSIM. The proposed IV-SSIM metric is an evolution of our previous work—IV-PSNR (immersive video peak signal-to-noise ratio)—which became a commonly used metric in research and ISO/IEC MPEG standardization activities on immersive video. IV-SSIM combines the advantages of IV-PSNR and metrics based on the structural similarity of images, being able to properly mimic the subjective quality perception of immersive video with its characteristic distortions induced by the reprojection of pixels between multiple views. The effectiveness of IV-SSIM was compared with 16 state-of-the-art quality metrics (including other metrics designed for immersive video). Tested metrics were evaluated in an immersive video coding scenario and against a commonly used image quality database—TID2013—showing their performance in both immersive and typical, non-immersive use cases. As presented, the proposed IV-SSIM metric clearly outperforms other metrics in immersive video applications, while also being highly competitive for 2D image quality assessment. The authors of this paper have provided a publicly accessible, efficient implementation of the proposed IV-SSIM metric, which is used by ISO/IEC MPEG video coding experts in the development of the forthcoming second edition of the MPEG immersive video (MIV) coding standard. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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<p>Idea of an immersive video system; blue—real (input) cameras, orange—virtual camera; position of the virtual camera may be arbitrarily changed by the viewer.</p>
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<p>Noticeability of pixel shift in a rendered view: (<b>A</b>) correct position of the dancer, (<b>B</b>) dancer shifted by two pixels to the right, (<b>C</b>) dancer shifted significantly. Sequence Choreo [<a href="#B38-applsci-14-07090" class="html-bibr">38</a>].</p>
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<p>Fragment of a virtual view rendered using views captured by cameras with different color characteristics (<b>B</b>) and color-corrected views (<b>C</b>), vs. reference input view (<b>A</b>); brightness increased by 40% to emphasize differences. Sequence Carpark [<a href="#B39-applsci-14-07090" class="html-bibr">39</a>].</p>
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<p>SROCC and PLCC values for all considered metrics; immersive video coding scenario.</p>
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<p>SROCC and PLCC values for all considered metrics; TID2013 database.</p>
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<p>SROCC and computational time for all considered metrics; immersive video coding scenario. Calculations were performed on AMD Ryzen 9 3900XT (12 cores).</p>
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15 pages, 549 KiB  
Article
Math for Everybody: A Sonification Module for Computer Algebra Systems Aimed at Visually Impaired People
by Ana M. Zambrano, Mateo N. Salvador, Felipe Grijalva, Henry Carvajal Mora and Nathaly Orozco Garzón
Technologies 2024, 12(8), 133; https://doi.org/10.3390/technologies12080133 - 12 Aug 2024
Viewed by 1082
Abstract
Computer Algebra Systems (CAS) currently lack an effective auditory representation, with most existing solutions relying on screen readers that provide limited functionality. This limitation prevents blind users from fully understanding and interpreting mathematical expressions, leading to confusion and self-doubt. This paper addresses the [...] Read more.
Computer Algebra Systems (CAS) currently lack an effective auditory representation, with most existing solutions relying on screen readers that provide limited functionality. This limitation prevents blind users from fully understanding and interpreting mathematical expressions, leading to confusion and self-doubt. This paper addresses the challenges blind individuals face when comprehending mathematical expressions within a CAS environment. We propose “Math for Everybody” (Math4e, version 1.0), a software module to reduce barriers for blind users in education. Math4e is a Sonification Module for CAS that generates a series of auditory tones, prosodic cues, and variations in audio parameters such as volume and speed. These resources are designed to eliminate ambiguity and facilitate the interpretation and understanding of mathematical expressions for blind users. To assess the effectiveness of Math4e, we conducted standardized tests employing the methodologies outlined in the Software Engineering Body of Knowledge (SWEBOK), International Software Testing Qualifications Board (ISTBQ), and ISO/IEC/IEEE 29119. The evaluation encompassed two scenarios: one involving simulated blind users and another with real blind users associated with the “Asociación de Invidentes Milton Vedado” foundation in Ecuador. Through the SAM methodology and verbal surveys (given the condition of the evaluated user), results are obtained, such as 90.56% for pleasure, 90.78% for arousal, and 91.56% for dominance, which demonstrates significant acceptance of the systems by the users. The outcomes underscored the users’ commendable ability to identify mathematical expressions accurately. Full article
(This article belongs to the Section Assistive Technologies)
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<p>Ambiguity reading on screen readers.</p>
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<p>Sonification workflow of Math4e.</p>
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<p>LaTex structuring and processing to generate a descriptive reading format.</p>
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<p>Transformation of a math expression description into fragments.</p>
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15 pages, 2170 KiB  
Article
Estimation of Effective Length of Type-A Grounding System According to IEC 62305-3 Using a Machine Learning Regression Model
by Dino Lovrić, Ivan Krolo and Ivica Jurić-Grgić
Appl. Sci. 2024, 14(16), 6945; https://doi.org/10.3390/app14166945 - 8 Aug 2024
Viewed by 421
Abstract
Two types of grounding systems are recommended for use in the international standard IEC 62305-3, Part 3: Physical damage to structures and life hazard. One of these is a radial-based grounding system (type-A), which is used in soil resistivities of up to 3000 [...] Read more.
Two types of grounding systems are recommended for use in the international standard IEC 62305-3, Part 3: Physical damage to structures and life hazard. One of these is a radial-based grounding system (type-A), which is used in soil resistivities of up to 3000 Ωm and is considered in this paper. It is a well-known fact that during lightning strikes, only a part of the grounding wire contributes to dissipating the lightning current into the surrounding soil. This effective part of the grounding system depends on several features, such as soil resistivity, burial depth, and rise time of the dissipated lightning current. The effect of all of these features on the effective length of the type-A grounding system is explored in this paper. A suitable supervised machine learning regression model is developed, which will enable readers to accurately approximate the effective length of the type-A grounding system for realistic values of input features. The trained model in the paper yielded an R2 value of 0.99998 on the test set. In addition, two simple mathematical formulas are also provided, which produce similar but less accurate results (R2 values of 0.989883 and 0.998557, respectively). Full article
(This article belongs to the Special Issue Lightning Electromagnetic Fields Research)
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<p>Observed type-A grounding system as prescribed in [<a href="#B16-applsci-14-06945" class="html-bibr">16</a>].</p>
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<p>Methodology of obtaining the effective length dataset.</p>
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<p>Visualization of the dataset for a burial depth of 0.5 m.</p>
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<p>Feature importance scores sorted using the MRMR algorithm.</p>
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<p>Actual vs. predicted values obtained using Equation (<a href="#FD2-applsci-14-06945" class="html-disp-formula">2</a>): (<b>a</b>) Training set, (<b>b</b>) Test set.</p>
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<p>Residuals vs. predicted values obtained using Equation (<a href="#FD2-applsci-14-06945" class="html-disp-formula">2</a>): (<b>a</b>) Training set, (<b>b</b>) Test set.</p>
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<p>Actual vs. predicted values obtained using Equation (<a href="#FD3-applsci-14-06945" class="html-disp-formula">3</a>): (<b>a</b>) Training set, (<b>b</b>) Test set.</p>
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<p>Residuals vs. predicted values obtained using Equation (<a href="#FD3-applsci-14-06945" class="html-disp-formula">3</a>): (<b>a</b>) Training set, (<b>b</b>) Test set.</p>
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<p>Actual vs. predicted values obtained using the GP regression model: (<b>a</b>) Training set, (<b>b</b>) Test set.</p>
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<p>Residuals vs. predicted values obtained using the GP regression model: (<b>a</b>) Training set, (<b>b</b>) Test set.</p>
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30 pages, 2658 KiB  
Article
SecuriDN: A Modeling Tool Supporting the Early Detection of Cyberattacks to Smart Energy Systems
by Davide Cerotti, Daniele Codetta Raiteri, Giovanna Dondossola, Lavinia Egidi, Giuliana Franceschinis, Luigi Portinale, Davide Savarro and Roberta Terruggia
Energies 2024, 17(16), 3882; https://doi.org/10.3390/en17163882 - 6 Aug 2024
Viewed by 712
Abstract
SecuriDN v. 0.1 is a tool for the representation of the assets composing the IT and the OT subsystems of Distributed Energy Resources (DERs) control networks and the possible cyberattacks that can threaten them. It is part of a platform that allows the [...] Read more.
SecuriDN v. 0.1 is a tool for the representation of the assets composing the IT and the OT subsystems of Distributed Energy Resources (DERs) control networks and the possible cyberattacks that can threaten them. It is part of a platform that allows the evaluation of the security risks of DER control systems. SecuriDN is a multi-formalism tool, meaning that it manages several types of models: architecture graph, attack graphs and Dynamic Bayesian Networks (DBNs). In particular, each asset in the architecture is characterized by an attack graph showing the combinations of attack techniques that may affect the asset. By merging the attack graphs according to the asset associations in the architecture, a DBN is generated. Then, the evidence-based and time-driven probabilistic analysis of the DBN permits the quantification of the system security level. Indeed, the DBN probabilistic graphical model can be analyzed through inference algorithms, suitable for forward and backward assessment of the system’s belief state. In this paper, the features and the main goals of SecuriDN are described and illustrated through a simplified but realistic case study. Full article
(This article belongs to the Special Issue Model Predictive Control-Based Approach for Microgrids)
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<p>General ICS reference architecture [<a href="#B28-energies-17-03882" class="html-bibr">28</a>].</p>
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<p>DMS general architecture.</p>
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<p>Case study architecture.</p>
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<p>SecuriDN’s GUI, showing the ArchG graph of our case study. Notice the drawing area to the left and the panels to select nodes and edges to the right.</p>
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<p>The lAG of the historian server (the red node will be merged with the corresponding red node in <a href="#energies-17-03882-f006" class="html-fig">Figure 6</a> during the construction of the gAG). If the attackers have the ability to run a <span class="html-italic">shell</span> on the machine, they can install an SSH key. With an SSH key installed, they can connect also remotely (<span class="html-italic">remoteShell</span>). Notice the two analytics <span class="html-small-caps">shellExecution</span> and <span class="html-small-caps">rmtShellSession</span>. From this asset, the attackers can try <span class="html-italic">bruteForce</span> on a remote device reachable via a network connection.</p>
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<p>The lAG of the Tomcat web server shows that initial access can be obtained through <span class="html-italic">bruteForce</span>, after which an <span class="html-italic">escapeHost</span> can be carried out on the virtual environment on which the server is running. The analytic <span class="html-small-caps">loginFrequency</span> exposes a <span class="html-italic">bruteForce</span> attempt. The red node will be merged with the corresponding red node in <a href="#energies-17-03882-f005" class="html-fig">Figure 5</a> during the construction of the gAG.</p>
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<p>The lAG of the MMS client is more articulated (the green node will be merged with the corresponding green node in <a href="#energies-17-03882-f008" class="html-fig">Figure 8</a> during the construction of the gAG). If attackers can steal credentials and manipulate trust (<span class="html-italic">unsecCred</span> and <span class="html-italic">modAuthProc</span>), they can then carry out an <span class="html-italic">AITM</span> on the communication channel. Or, if they manage to spoof reporting messages, they can induce the MMS client to cause a <span class="html-italic">DERfailure</span>.</p>
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<p>The lAG of the MMS over the TLS channel describes the fact that, in case an <span class="html-italic">AITM</span> is carried out on the channel, attackers can then send crafted reporting messages to the client (<span class="html-italic">spoofRepMsg</span>) or send unauthorized command messages (<span class="html-italic">unauthCmdMsg</span>) directly to the server to cause a <span class="html-italic">DERfailure</span>. The green node will be merged with the corresponding green node in <a href="#energies-17-03882-f007" class="html-fig">Figure 7</a> during the construction of the gAG.</p>
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<p>The final gAG obtained merging lAGs and pruning the nodes not leading to the goal node. The red and green nodes are examples of merged nodes (see <a href="#energies-17-03882-f005" class="html-fig">Figure 5</a>, <a href="#energies-17-03882-f006" class="html-fig">Figure 6</a>, <a href="#energies-17-03882-f007" class="html-fig">Figure 7</a> and <a href="#energies-17-03882-f008" class="html-fig">Figure 8</a>). The yellow nodes indicate the initial technique and the final technique. Note that the figure shows precisely the output of SecuriDN (the graphical aspects will be improved in a later version of the prototype).</p>
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<p>The DBN derived from the final gAG. The nodes containing the symbol “2” are binary random variables representing techniques, analytics, or defenses, all characterized by two possible states (not occurred, occurred). The logic nodes (AND, OR) contain the corresponding Boolean operator (∧, ∨). The oriented black arcs indicate that a node influences another node. Finally the blue loops represent the temporal arcs to model probabilistic evolution over time.</p>
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<p><span class="html-italic">Experiment 1.</span> Probabilities of successful technique exploitation with no evidence (all analytics disabled).</p>
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<p><span class="html-italic">Experiment 2–part 1.</span> Probabilities of successful technique exploitation with fully implemented monitoring system, and partial execution of the attack process. Alerts: <span class="html-small-caps">HS_shellExec</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>9</mn> </mrow> </semantics></math>, <span class="html-small-caps">WS_loginFrequency</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>10</mn> </mrow> </semantics></math>, <span class="html-small-caps">VE_suspCmd</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>56</mn> </mrow> </semantics></math>. All other analytics raise no alerts.</p>
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<p><span class="html-italic">Experiment 2–part 2.</span> Probabilities of successful technique exploitation, when the observed attack process starts with a remote connection to the historian server. Analytic <span class="html-small-caps">HS_shellExec</span> not active. Alerts: <span class="html-small-caps">HS_rmtShell</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math>, <span class="html-small-caps">WS_loginFrequency</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>10</mn> </mrow> </semantics></math>. All other analytics are implemented but raise no alerts.</p>
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<p><span class="html-italic">Experiment 3 part 1.</span> Probabilities of successful technique exploitation with observations until time <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math> and predictions after <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>. Analytics <span class="html-small-caps">HS_shellExec</span>, <span class="html-small-caps">SC_shellExec</span>, <span class="html-small-caps">cli_fileAccess</span> and <span class="html-small-caps">MMS_cmdCoher</span> not active. Analytics Alerts: <span class="html-small-caps">HS_rmtShell</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math>, <span class="html-small-caps">WS_loginFrequency</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>10</mn> </mrow> </semantics></math>. Analytics <span class="html-small-caps">VE_suspCmd</span>, <span class="html-small-caps">cli_integrity</span>, <span class="html-small-caps">cli_measCoher</span> detect no suspicious activity. After <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>30</mn> </mrow> </semantics></math>, all analytics undefined.</p>
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<p><span class="html-italic">Experiment 3–part 2.</span> Probabilities of successful technique exploitation with observations until time <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>85</mn> </mrow> </semantics></math>. Analytics <span class="html-small-caps">HS_shellExec</span>, <span class="html-small-caps">SC_shellExec</span>, <span class="html-small-caps">cli_fileAccess</span> and <span class="html-small-caps">MMS_cmdCoher</span> not active. Alerts: <span class="html-small-caps">HS_rmtShell</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math>, <span class="html-small-caps">WS_loginFrequency</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>10</mn> </mrow> </semantics></math>, <span class="html-small-caps">VE_suspCmd</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>55</mn> </mrow> </semantics></math>, <span class="html-small-caps">cli_integrity</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>59</mn> </mrow> </semantics></math> and <span class="html-small-caps">cli_measCoher</span> at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>77</mn> </mrow> </semantics></math>.</p>
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24 pages, 2188 KiB  
Article
Investigation into PV Inverter Topologies from the Standards Compliance Viewpoint
by Muhammad Asif Hasan, Naresh Kumar Vemula, Ramesh Devarapalli and Łukasz Knypiński
Energies 2024, 17(16), 3879; https://doi.org/10.3390/en17163879 - 6 Aug 2024
Viewed by 634
Abstract
Numerous reviews are available in the literature on PV inverter topologies. These reviews have intensively investigated the available PV inverter topologies from their modulation techniques, control strategies, cost, and performance aspects. However, their compliance with industrial standards has not been investigated in detail [...] Read more.
Numerous reviews are available in the literature on PV inverter topologies. These reviews have intensively investigated the available PV inverter topologies from their modulation techniques, control strategies, cost, and performance aspects. However, their compliance with industrial standards has not been investigated in detail so far in the literature. There are various standards such as North American standards (UL1741, IEEE1547, and CSA 22.2) and Australian and European safety standards and grid codes, which include IEC 62109 and VDE. These standards provide detailed guidelines and expectations to be fulfilled by a PV inverter topology. Adherence to these standards is essential and crucial for the successful operation of PV inverters, be it a standalone or grid-tied mode of operation. This paper investigates different PV inverter topologies from the aspect of their adherence to different standards. Both standalone and grid-tied mode of operation-linked conditions have been checked for different topologies. This investigation will help power engineers in selecting suitable PV inverter topology for their specific applications. Full article
(This article belongs to the Special Issue Experimental and Numerical Analysis of Photovoltaic Inverters)
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<p>Salient features of standard UL1741.</p>
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<p>Salient features of standard IEEE 1547.</p>
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<p>Salient features of standard CSA 22.2.</p>
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<p>Salient features of standard IEC 62109.</p>
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<p>A comparative representation of different standards for PV inverter topologies.</p>
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<p>Multi-stage pv inverter topology.</p>
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<p>Line frequency pv inverter topology.</p>
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<p>High switching frequency pv inverter topology.</p>
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<p>Resonant frequency PV inverter topologies.</p>
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<p>Compliance status of individual PV inverter topology, with respect to industry standards.</p>
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15 pages, 1310 KiB  
Article
Prevalence of Selected Immune Evasion Genes and Clonal Diversity in Methicillin-Susceptible Staphylococcus aureus Isolated from Nasal Carriers and Outpatients with Cut Wound Infections
by Gabriela Jura, Helena Masiuk, Agata Pruss, Mateusz Kurzawski, Monika Sienkiewicz, Iwona Wojciechowska-Koszko and Paweł Kwiatkowski
Antibiotics 2024, 13(8), 730; https://doi.org/10.3390/antibiotics13080730 - 3 Aug 2024
Viewed by 552
Abstract
Staphylococcus aureus, being one of the most common human pathogens, is responsible for infections in both hospital and community settings. Its virulence is attributed to its ability to evade the immune system by producing immune evasion (IE) proteins. The aim of this [...] Read more.
Staphylococcus aureus, being one of the most common human pathogens, is responsible for infections in both hospital and community settings. Its virulence is attributed to its ability to evade the immune system by producing immune evasion (IE) proteins. The aim of this study was to detect the frequency of selected IE genes (spin, sbi, sea, sak, chp, scin, sep, ecb), belonging to the immune evasion cluster (IEC), and IEC types in 86 methicillin-susceptible S. aureus (MSSA) strains isolated from unrelated outpatients. In order to determine the diversity of analyzed strains, the phylogenetic relatedness was also determined. All strains were examined for the presence of IE genes using polymerase chain reaction assay. To analyze the clonal relatedness of S. aureus, pulsed-field gel electrophoresis (PFGE) was performed. All analyzed strains harbored the scn gene, followed by sbi (95.4%), ecb (91.7%), spin (89.5%), sak (83.7%), chp (67.4%), sep (67.4%) and sea (5.8%). Seventy-three (84.9%) S. aureus strains were classified into IEC types, of which, IEC type F was most commonly observed. IEC type A was not detected. PFGE results showed no association between clonal relatedness and the presence of IE genes/IEC types. In conclusion, the abundant and so diverse repertoire of genes determining invasion in analyzed strains may prove the fact that these strains are highly advanced and adapted to evade the host immune response. Full article
(This article belongs to the Special Issue Staphylococcal Biology and Pathogenesis)
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<p>Dendrogram presenting pulsed-field gel electrophoresis (PFGE) profiles of 86 methicillin-susceptible <span class="html-italic">S. aureus</span> isolated from nasal carriers and outpatients with cut wound infections (DH—dorsal hand wound infection; F—finger infection; PH—palmary hand wound infection). PFGE profiles were clustered into 19 genotypes (A to S) and 5 unique (Un) patterns (Un1 to Un5), on the basis of a similarity threshold ≥63%.</p>
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<p>Correlation between pulsed-field gel electrophoresis (PFGE) profiles and the number of methicillin-susceptible <span class="html-italic">Staphylococcus aureus</span> strains harboring immune evasion (IE) genes (<b>a</b>) or immune evasion cluster (IEC) types (<b>b</b>).</p>
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