Search Results (8,867)

Energy poverty has impressive negative effects on people’s health. Alleviating energy poverty is crucial for a just and equitable transition. However, policies and attempts to reduce energy poverty present a challenge to researchers and policymakers due to its complexity. The lack of a clear definition, of a common set of metrics to assess its multiple dimensions, and of spatially explicit assessments represent serious shortcomings that hinder effective policy design. This paper aims to explore the relevance and spatial distribution of the determinants of vulnerability to energy poverty to support the design of effective responses at different scales. To this end, a principal component (PCA) and a geographically weighted principal component analysis (GWPCA) are conducted on more than 1300 municipalities in 15 Italian metropolitan areas, to identify the spatial patterns of vulnerability to energy poverty and its causes. The PCA highlights three main components of vulnerability to energy poverty in the study areas, respectively, related to the job condition and to individual and households’ socioeconomic factors, which provide relevant insights for policies at the national level, The GWPCA provides more detailed information to effectively support policies at the local level. The novelty of this work is the comparison of results from a PCA and a GWPCA of their different contributions to policy design at different scales. Full article

In this investigation, the efficacy of PCA-GLU, a polymer obtained by copolymerizing citric acid and glutamic acid, as a corrosion inhibitor for carbon steel was investigated in a 3.5wt% NaCl solution. Electrochemical impedance spectroscopy (EIS) techniques and potentiodynamic polarization (PDP) measurements were used to evaluate the corrosion inhibition. The findings demonstrate that PCA-GLU has a 96.73% corrosion inhibition efficiency. Additionally, when the inhibitor concentration rises, the corrosion inhibition efficiency rises as well, reaching an ideal concentration of 400 mg/L. Furthermore, PCA-GLU can create an adsorption layer on the surface of Q235. This paper verifies the adsorption mechanism of PCA-GLU through molecular dynamics simulations of the system and quantum chemical calculations of corrosion inhibitors in solution. Ultimately, our research findings validate that PCA-GLU is an efficient corrosion inhibitor in safeguarding carbon steel against corrosion in marine environments. Full article

The diagnosis of vibration faults in hydropower units is essential for ensuring the safe and stable operation of these systems. This paper proposes a fault diagnosis method for hydropower units that combines Dynamic Mode Decomposition (DMD) with an optimized Extreme Learning Machine (ELM) utilizing the Hiking Optimization Algorithm (HOA). To address the issue of noise interference in the vibration signals of hydropower units, this study employs DMD technology alongside a thresholding technique for noise reduction, demonstrating its effectiveness through comparative trials. Furthermore, to facilitate a thorough analysis of the operational status of hydropower units, this paper extracts multidimensional features from denoised signals. To improve the efficiency of model training, Principal Component Analysis (PCA) is applied to streamline the data. Given that the weights and biases of the ELM are generated randomly, which may impact the model’s stability and generalization capabilities, the HOA is introduced for optimization. The HOA-ELM model achieved a classification accuracy of 95.83%. A comparative analysis with alternative models substantiates the superior performance of the HOA-ELM model in the fault diagnosis of hydropower units. Full article

Purpose: This study investigates whether quantitative MRI and histology of the prostate reveal differences between races, specifically African Americans (AAs) and Caucasian Americans (CAs), that can affect diagnosis. Materials and Methods: Patients (98 CAs, 47 AAs) with known or suspected prostate cancer (PCa) underwent 3T MRI (T2W, DWI, and DCE-MRI) prior to biopsy or prostatectomy. Quantitative mpMRI metrics: ADC, T2, and DCE empirical mathematical model parameters were calculated. Results: AAs had a greater percentage of higher Gleason-grade lesions compared to CAs. There were no significant differences in the quantitative ADC and T2 values between AAs and CAs. The cancer signal enhancement rate (α) on DCE-MRI was significantly higher for AAs compared to CAs (AAs: 13.3 ± 9.3 vs. CAs: 6.1 ± 4.7 s⁻¹, p < 0.001). The DCE signal washout rate (β) was significantly lower in benign tissue of AAs (AAs: 0.01 ± 0.09 s⁻¹ vs. CAs: 0.07 ± 0.07 s⁻¹, p < 0.001) and significantly elevated in cancer tissue in AAs (AAs: 0.12 ± 0.07 s⁻¹ vs. CAs: 0.07 ± 0.08 s⁻¹, p = 0.02). DCE significantly improves the differentiation of PCa from benign in AAs (α: 52%, β: 62% more effective in AAs compared to CAs). Histologic analysis showed cancers have a greater proportion (p = 0.04) of epithelium (50.9 ± 12.3 vs. 44.7 ± 12.8%) and lower lumen (10.5 ± 6.9 vs. 16.2 ± 6.8%) in CAs compared to AAs. Conclusions: This study shows that AAs have different quantitative DCE-MRI values for benign prostate and prostate cancer and different histologic makeup in PCa compared to CAs. Quantitative DCE-MRI can significantly improve the performance of MRI for PCa diagnosis in African Americans but is much less effective for Caucasian Americans. Full article

Actinidia arguta is a cold-resistant fruit tree but intolerant to waterlogging. Waterlogging stress is the major abiotic stress in A. arguta growth, and several pathways are involved in the response mechanisms. Fifteen physiological indices and transcriptome data of two A. arguta cultivars, which showed two forms under waterlogging, were used to identify the major factor following the leaf senescence in waterlogging. Through principal component analysis (PCA) of 15 physiological indices in ‘Kuilv’ and ‘Lvwang’, the hormone contents were selected as the most important principal component (PCA 2) out of four components in response to waterlogging stress. According to the analysis of transcriptome data, 21,750 differentially expressed genes were identified and 10 genes through WGCNA, including hormone metabolism and sucrose metabolism, were screened out on the 6th day of waterlogging. In particular, the ABA signal transduction pathway was found to be closely related to the response to waterlogging based on the correlation analysis between gene expression level and plant hormone content, which may have regulated physiological indicators and morphological changes together with other hormones. Overall, the phenomenon of leaves falling induced by ABA might be a protective mechanism. The results provided more insights into the response mechanism of coping with waterlogging stress in A. arguta. Full article

This study investigates the impact of adding varying concentrations (1%, 3%, 5%, 7%, and 9%) of chia seeds on the physicochemical and antioxidant properties of oat-based yogurt fortified with 2% honey. The research analyzed changes in pH, titratable acidity, water-holding capacity (WHC), dry matter content, total phenolic content (TPC), and antioxidant activity over a 7-day storage period. The pH values ranged from 4.33 ± 0.01 to 4.57 ± 0.01, with no significant impact observed due to chia seed addition. Titratable acidity increased most rapidly in the 9% chia seed sample, particularly between days 5 and 7. WHC significantly improved with higher chia seed concentrations, with the 9% chia sample reaching 99.9 ± 0.07% compared with 69.9 ± 0.12% in the control. Dry matter content showed a similar trend, with the highest increase observed in the 9% chia sample. TPC and antioxidant activity were positively correlated with chia seed concentration and storage time, with the 9% chia sample exhibiting the highest values on day 7. Sensory evaluation revealed that the 3% chia seed concentration was most preferred by panelists for its balanced texture and flavor. Principal Component Analysis (PCA) highlighted the clustering of higher chia concentrations with improved functional properties. This study presents novel insights into the impact of varying concentrations of chia seeds on the physicochemical properties and antioxidant potential of oat-based yogurt, specifically fortified with honey, contributing to the development of functional plant-based dairy alternatives. Full article

Breeding high-photosynthetic-efficiency wheat varieties is a crucial link in safeguarding national food security. Traditional identification methods necessitate laborious on-site observation and measurement, consuming time and effort. Leveraging unmanned aerial vehicle (UAV) remote sensing technology to forecast photosynthetic indices opens up the potential for swiftly discerning high-photosynthetic-efficiency wheat varieties. The objective of this research is to develop a multi-stage predictive model encompassing nine photosynthetic indicators at the field scale for wheat breeding. These indices include soil and plant analyzer development (SPAD), leaf area index (LAI), net photosynthetic rate (Pn), transpiration rate (Tr), intercellular CO₂ concentration (Ci), stomatal conductance (Gsw), photochemical quantum efficiency (PhiPS2), PSII reaction center excitation energy capture efficiency (Fv’/Fm’), and photochemical quenching coefficient (qP). The ultimate goal is to differentiate high-photosynthetic-efficiency wheat varieties through model-based predictions. This research gathered red, green, and blue spectrum (RGB) and multispectral (MS) images of eleven wheat varieties at the stages of jointing, heading, flowering, and filling. Vegetation indices (VIs) and texture features (TFs) were extracted as input variables. Three machine learning regression models (Support Vector Machine Regression (SVR), Random Forest (RF), and BP Neural Network (BPNN)) were employed to construct predictive models for nine photosynthetic indices across multiple growth stages. Furthermore, the research conducted principal component analysis (PCA) and membership function analysis on the predicted values of the optimal models for each indicator, established a comprehensive evaluation index for high photosynthetic efficiency, and employed cluster analysis to screen the test materials. The cluster analysis categorized the eleven varieties into three groups, with SH06144 and Yannong 188 demonstrating higher photosynthetic efficiency. The moderately efficient group comprises Liangxing 19, SH05604, SH06085, Chaomai 777, SH05292, Jimai 22, and Guigu 820, totaling seven varieties. Xinmai 916 and Jinong 114 fall into the category of lower photosynthetic efficiency, aligning closely with the results of the clustering analysis based on actual measurements. The findings suggest that employing UAV-based multi-source remote sensing technology to identify wheat varieties with high photosynthetic efficiency is feasible. The study results provide a theoretical basis for winter wheat phenotypic monitoring at the breeding field scale using UAV-based multi-source remote sensing, offering valuable insights for the advancement of smart breeding practices for high-photosynthetic-efficiency wheat varieties. Full article

Background/Objectives: Currently, the prediction of disease recurrence after radical prostatectomy (RP) in localized prostate cancer (PCa) relies on clinicopathological parameters, which lack accuracy in predicting clinical outcomes. This study focused on evaluating the utility of cfDNA levels and fragmentation patterns as prognostic biomarkers in progressive prostate-specific antigen (PSA) patients, including those with persistent PSA and biochemical recurrence (BR), after primary treatment in localized PCa patients. Methods: Twenty-nine high-risk localized PCa patients were enrolled in the study between February 2022 and May 2023. Blood samples were obtained before robotic RP. cfDNA concentration and fragment size were quantified using the Quant-it PicoGreen dsDNA Assay kit and Agilent 2200 TapeStation System, respectively. Results: The mean PSA value at diagnosis was 9.4 ng/mL. Seven patients (24.1%) had stage pT2 and 22 (75.9%) pT3. Nine patients (31%) had detectable PSA at the first PSA control six weeks after surgery, and four patients (20%) had BR during a mean follow-up of 18.4 months. No associations were found between cfDNA levels or fragmentation patterns and clinicopathological data. Although not statistically significant, patients with detectable PSA levels post-surgery exhibited higher cfDNA levels and shorter fragments compared with those with undetectable PSA. Conclusions: Our study indicated a tendency toward more fragmented cfDNA levels in PCa patients with persistent PSA. Strikingly, biochemical recurrent PCa patients exhibited similar cfDNA levels and fragmentation patterns compared to non-recurrent patients. Further studies exploring liquid biopsy-derived biomarkers in localized PCa patients are needed to elucidate their clinical utility in predicting PSA persistence. Full article

Objectives: Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) has gained a primary role in prostate cancer (PCa) imaging, overcoming conventional imaging and prostate-specific antigen (PSA) serum levels, and has recently emerged as a promising technique for monitoring therapy response in metastatic castration-resistant prostate cancer (mCRPC) patients treated with novel hormonal therapy, taxanes, and radioligand therapy (RLT). In this review, we aim to provide an overview of the most relevant aspects under study and future prospects related to the prognostic role of PSMA PET/CT in mCRPC. Methods: A systematic literature search was performed in the following databases: MEDLINE, PubMed, and EMBASE databases. The study focused exclusively on English-language studies, excluding papers not pertinent to the topic. Results: PSMA PET imaging offers a higher sensitivity and specificity than conventional imaging and provides accurate staging and efficient diagnosis of distant metastases. The data presented herein highlight the usefulness of PET in risk stratification, with a prognostic potential that can have a significant impact on clinical practice. Several prospective trials are ongoing and will shortly provide more evidence supporting the prognostic potential of PET PSMA data in this clinical scenario. Conclusions: Current evidence proves the prognostic role of PSMA PET/CT in different settings, with raising relevance also in the context of mCRPC. Full article

The genus Zephyranthes is widely represented in Mexico, with 37 species of ornamental and medical importance. However, basic aspects of the genus, such as the environmental variables that determine its presence in certain sites, have not yet been addressed, which limits the knowledge of its ecology, potential applications and possible conservation strategies. Potential distribution models were generated with data on the presence of 13 species of the genus Zephyranthes, using 28 bioclimatic and edaphic variables with the maximum entropy method (Maxent). Of these variables, the most important and least correlated for each species were chosen by principal component analysis (PCA); the occurrence data were obtained from digital platforms and filtered to reduce spatial autocorrelation. The resulting models, had AUC values > 0.90 and Kappa index values > 0.6, in addition to being significant according to the results of the binomial test applied (p < 0.05). Maximum temperatures and humidity, as well as annual precipitation, are relevant environmental variables for the niche models. Most species are distributed in the biogeographic province of the Transmexican Volcanic Belt. Zephyranthes concolor and Zephyranthes lindleyana were the species with the largest potential range. The species with the most restricted potential distribution were Zephyranthes citrina and Zephyranthes sessilis. The most determinant variables for species with neotropical affinity are different from those identified for Nearctic species, reflecting niche differentiation, congruent with the evolutionary history of Zephyranthes. Full article

We investigated the feasibility of magnetic resonance elastography (MRE) using a pelvic acoustic driver for the detection and classification of prostate cancer (PCa). A total of 75 consecutive patients (mean age, 70; range, 56–86) suspected of having PCa and who underwent multi-parametric MRI including MRE and subsequent surgical resection were included. The analyzed regions consisted of cancer (n = 69), benign prostatic hyperplasia (BPH) (n = 70), and normal parenchyma (n = 70). A histopathologic topographic map served as the reference standard for each region. One radiologist and one pathologist performed radiologic–pathologic correlation, and the radiologist measured stiffness values in each region of interest on elastograms automatically generated by dedicated software. Paired t-tests were used to compare stiffness values between two regions. ROC curve analysis was also used to extract a cutoff value between two regions. The stiffness value of PCa (unit, kilopascal (kPa); 4.9 ± 1.1) was significantly different to that of normal parenchyma (3.6 ± 0.3, p < 0.0001) and BPH (4.5 ± 1.4, p = 0.0454). Under a cutoff value of 4.2 kPa, a maximum accuracy of 87% was estimated, with a sensitivity of 73%, a specificity of 99%, and an AUC of 0.839 for discriminating PCa from normal parenchyma. Between PCa and BPH, a maximum accuracy of 62%, a sensitivity of 70%, a specificity of 56%, and an AUC of 0.598 were estimated at a 4.5 kPa cutoff. The stiffness values tended to increase as the ISUP grade increased. In conclusion, it is feasible to detect and classify PCa using pelvic MRE. Our observations suggest that MRE could be a supplement to multi-parametric MRI for PCa detection. Full article

Background/Objectives: Prostate cancer is a prevalent malignancy often presenting without early symptoms. Advanced imaging technologies have revolutionized its diagnosis and management. This review discusses the principles, benefits, and clinical applications of multiparametric magnetic resonance imaging (mpMRI), micro-ultrasound (microUS), and prostate-specific membrane antigen positron emission tomography–computed tomography (PSMA PET/CT) in localized prostate cancer. Methods: We conducted a comprehensive literature review of recent studies and guidelines on mpMRI, microUS, and PSMA PET/CT in prostate cancer diagnosis, focusing on their applications in biopsy-naïve patients, those with previous negative biopsies, and patients under active surveillance. Results: MpMRI has demonstrated high sensitivity and negative predictive value in detecting clinically significant prostate cancer (csPCa). MicroUS, a newer technology, has shown promising results in early studies, with sensitivity and specificity comparable to mpMRI. PSMA PET/CT has emerged as a highly sensitive and specific imaging modality, particularly valuable for staging and detecting metastatic disease. All three technologies have been incorporated into urologic practice for prostate cancer diagnosis and management, with each offering unique advantages in different clinical scenarios. Conclusions: Advanced imaging techniques, including mpMRI, microUS, and PSMA PET/CT, have significantly improved the accuracy of prostate cancer diagnosis, staging, and management. These technologies enable more precise targeting of suspicious lesions during biopsy and therapy planning. However, further research, especially randomized controlled trials, is needed to fully establish the optimal use and inclusion of these imaging modalities in various stages of prostate cancer care. Full article

Prostate cancer (PCa) remains a significant health threat, with chemoresistance and recurrence posing major challenges despite advances in treatment. The epithelial to mesenchymal transition (EMT), a biochemical process where cells lose epithelial features and gain mesenchymal traits, is linked to chemoresistance and metastasis. Electrical impedance spectroscopy (EIS), a novel label-free electrokinetic technique, offers promise in detecting cell phenotype changes. In this study, we employed EIS to detect EMT in prostate cancer cells (PCCs). PC3, DU145, and LNCaP cells were treated with EMT induction media for five days. EIS characterization revealed unique impedance spectra correlating with metastatic potential, distinguishing DU145 EMT+ and EMT− cells, and LNCaP EMT+ and EMT− cells (in combination with dielectrophoresis), with comparisons made to epithelial and mesenchymal controls. These changes were supported by shifts in electrical signatures, morphologies, and protein expression, including the downregulation of E-cadherin and upregulation of vimentin. No phenotype change was observed in PC3 cells, which maintained a mesenchymal phenotype. EMT+ cells were also distinguishable from mixtures of EMT+ and EMT− cells. This study demonstrates key advancements: the application of EIS and dielectrophoresis for label-free EMT detection in PCCs, characterization of cell electrical signatures after EMT, and EIS sensitivity to EMT transitions. Detecting EMT in PCa is important to the development of more effective treatments and overcoming the challenges of chemoresistance. Full article

In the field of thermal non-destructive testing and evaluation (TNDT&E), active thermography gained popularity due to its fast wide-area monitoring and remote inspection capability to assess materials without compromising their future usability. Among the various active thermographic methods, pulse compression-favorable frequency-modulated thermal wave imaging stands out for its enhanced detectability and depth resolution. In this study, an experimental investigation has been carried out on a hardened steel sample used in the ship building industry with a flat-bottom-hole-simulated defect using the frequency-modulated thermal wave imaging (FMTWI) technique. The defect detection capabilities of FMTWI have been investigated from various statistical post-processing approaches and compared by taking the signal-to-noise ratio (SNR) as a figure of merit. Among various adopted statistical post-processing techniques, pulse compression has been carried out using different methods, namely the offset removal with polynomial curve fitting and principal component analysis (PCA), which is an unsupervised learning approach for data reduction and offset removal with median centering for data standardization. The performance of these techniques was assessed through experimental investigations on hardened steel specimens used in ship building to provide valuable insights into their effectiveness in defect detection capabilities. Full article

The palm Euterpe precatoria holds great social, cultural, and environmental importance. The heart of palm and the fruit are the main products used for industrialization due to their energetic properties. Thus, the aim of this study was to establish a suspension cultivation protocol for the species using different explant sources. For this, eight lineages of E. precatoria embryogenic calluses were tested, with five in liquid medium Murashige and Skoog (MS) with 5 μM Picloram and three for comparison in semisolid medium MS with 20 μM Picloram and 5 μM 2iP. The growth curve was obtained by weighing the calli from 60 to 180 days of cultivation. The Gompertz model was applied, and growth kinetics were evaluated. At 100 days, the contents of total soluble sugars (TSSs) and total soluble proteins (TSPs) were determined. Principal components (PCA) were measured. According to the analysis of the data, the cultivation of E. precatoria lineages in liquid medium was successfully carried out, and the establishment was achieved. The model can be considered adequate since the R² values found describe more than 90% of the growth kinetics of the lineages. In the liquid system, lineages L1 (from leaf explants and multiplied in semisolid medium—SM), L2 (from leaf explants and multiplied in SM), and L6 (from zygotic embryo explants and multiplied in liquid medium—LM) showed the shortest time to double the biomass accumulation. Multivariate analysis reveals a significant increase in masses in liquid cultures, represented by lineages L6 and L2. There was statistical difference in the amount of TSSs extracted; the highest TSS levels were observed in lineages cultivated in LM. The protein content found was very low, showing statistical differences among the lineages. In this work, the establishment and multiplication of embryogenic calli of E. precatoria are described for the first time, and they emerge as viable alternatives for the vegetative propagation of the species. Full article