Search Results (4,302)

Polyvinyl alcohol (PVA), a versatile polymer, is extensively used across many industries, such as chemicals, food, healthcare, textiles, and packaging. However, research on applying PVA to triboelectric nanogenerators (TENGs) remains limited. Consequently, we chose PVA as the primary material to explore its contact electrification mechanisms at the molecular level, alongside materials like Polyethylene (PE), Polyvinylidene fluoride (PVDF), and Polytetrafluoroethylene (PTFE). Our findings show that PVA has the highest band gap, with the smallest band gap occurring between the HOMO of PVA and the LUMO of PTFE. During molecular contact, electron transfer primarily occurs in the outermost layers of the molecules, influenced by the functional groups of the polymers. The presence of fluorine atoms enhances the electron transfer between PVA and PTFE to maximum levels. Experimental validation confirmed that PVA and PTFE contact yields the highest triboelectric performance: V_OC of 128 V, I_SC of 2.83 µA, Q_SC of 82 nC, and an output power of 384 µW. Moreover, P-TENG, made of PVA and PTFE, was successfully applied in self-powered smart devices and monitored human respiration and bodily movements effectively. These findings offer valuable insights into using PVA in triboelectric nanogenerator technologies. Full article

This paper conducts an in-depth study of a wireless, hierarchical structure-based active balancing system for power batteries, aimed at addressing the rapid advancements in battery technology within the electric vehicle industry. The system is designed to enhance energy density and the reliability of the battery system, developing a balancing system capable of managing cells with significant disparities in characteristics, which is crucial for extending the lifespan of lithium-ion battery packs. The proposed system integrates wireless self-networking technology into the battery management system and adopts a more efficient active balancing approach, replacing traditional passive energy-consuming methods. In its design, inter-group balancing at the upper layer is achieved through a soft-switching LLC resonant converter, while intra-group balancing among individual cells at the lower layer is managed by an active balancing control IC and a bidirectional buck–boost converter. This configuration not only ensures precise control but also significantly enhances the speed and efficiency of balancing, effectively addressing the heat issues caused by energy dissipation. Key technologies involved include lithium-ion batteries, battery management systems, battery balancing systems, LLC resonant converters, and wireless self-networking technology. Tests have shown that this system not only reduces energy consumption but also significantly improves energy transfer efficiency and the overall balance of the battery pack, thereby extending battery life and optimizing vehicle performance, ensuring a safer and more reliable operation of electric vehicle battery systems. Full article

Aiming to explore the subtle connection between the number of nonlinear terms in Lorenz-like systems and hidden attractors, this paper introduces a new simple sub-quadratic four-thirds-degree Lorenz-like system, where $\dot{x}=a(y-x)$, $\dot{y}=cx-\sqrt[3]{x}z$, $\dot{z}=-bz+\sqrt[3]{x}y$, and uncovers the following property of these systems: decreasing the powers of the nonlinear terms in a quadratic Lorenz-like system where $\dot{x}=a(y-x)$, $\dot{y}=cx-xz$, $\dot{z}=-bz+xy$, may narrow, or even eliminate the range of the parameter c for hidden attractors, but enlarge it for self-excited attractors. By combining numerical simulation, stability and bifurcation theory, most of the important dynamics of the Lorenz system family are revealed, including self-excited Lorenz-like attractors, Hopf bifurcation and generic pitchfork bifurcation at the origin, singularly degenerate heteroclinic cycles, degenerate pitchfork bifurcation at non-isolated equilibria, invariant algebraic surface, heteroclinic orbits and so on. The obtained results may verify the generalization of the second part of the celebrated Hilbert’s sixteenth problem to some degree, showing that the number and mutual disposition of attractors and repellers may depend on the degree of chaotic multidimensional dynamical systems. Full article

Multifunctional composites and smart textiles are an important advancement in material science, offering a variety of capabilities that extend well beyond traditional structural functions. These advanced materials are poised to revolutionize applications across a wide range of industries, including aerospace, healthcare, military, and consumer electronics, by embedding functionalities such as structural health monitoring, signal transmission, power transfer, self-healing, and environmental sensing. This review, which draws on insights from various disciplines, including material science, engineering, and technology, explores the manufacturing techniques employed in creating multifunctional composites, focusing on modifying textiles to incorporate conductive fibers, sensors, and functional coatings. The various multifunctional capabilities that result from these modifications and manufacturing techniques are examined in detail, including structural health monitoring, power conduction, power transfer, wireless communication, power storage, energy harvesting, and data transfer. The outlook and potential for future developments are also surveyed, emphasizing the need for improved durability, scalability, and energy efficiency. Key challenges are identified, such as ensuring material compatibility, optimizing fabrication techniques, achieving reliable performance under diverse conditions, and modeling multifunctional systems. By addressing these challenges through ongoing research and further innovation, we can significantly enhance the performance and utility of systems, driving advancements in technology and improving quality of life. Full article

Large language models (LLMs) are widely integrated into autonomous driving systems to enhance their operational intelligence and responsiveness and improve self-driving vehicles’ overall performance. Despite these advances, LLMs still struggle between hallucinations—when models either misinterpret the environment or generate imaginary parts for downstream use cases—and taxing computational overhead that relegates their performance to strictly non-real-time operations. These are essential problems to solve to make autonomous driving as safe and efficient as possible. This work is thus focused on symmetrical trade-offs between the reduction of hallucination and optimization, leading to a framework for these two combined and at least specifically motivated by these limitations. This framework intends to generate a symmetry of mapping between real and virtual worlds. It helps in minimizing hallucinations and optimizing computational resource consumption reasonably. In autonomous driving tasks, we use multimodal LLMs that combine an image-encoding Visual Transformer (ViT) and a decoding GPT-2 with responses generated by the powerful new sequence generator from OpenAI known as GPT4. Our hallucination reduction and optimization framework leverages iterative refinement loops, RLHF—reinforcement learning from human feedback (RLHF)—along with symmetric performance metrics, e.g., BLEU, ROUGE, and CIDEr similarity scores between machine-generated answers specific to other human reference answers. This ensures that improvements in model accuracy are not overused to the detriment of increased computational overhead. Experimental results show a twofold improvement in decision-maker error rate and processing efficiency, resulting in an overall decrease of 30% for the model and a 25% improvement in processing efficiency across diverse driving scenarios. Not only does this symmetrical approach reduce hallucination, but it also better aligns the virtual and real-world representations. Full article

As an essential component of the global economic crop, cotton is highly susceptible to the impact of diseases on its yield and quality. In recent years, artificial intelligence technology has been widely used in cotton crop disease recognition, but in complex backgrounds, existing technologies have certain limitations in accuracy and efficiency. To overcome these challenges, this study proposes an innovative cotton disease recognition method called CANnet, and we independently collected and constructed an image dataset containing multiple cotton diseases. Firstly, we introduced the innovatively designed Reception Field Space Channel (RFSC) module to replace traditional convolution kernels. This module combines dynamic receptive field features with traditional convolutional features to effectively utilize spatial channel attention, helping CANnet capture local and global features of images more comprehensively, thereby enhancing the expressive power of features. At the same time, the module also solves the problem of parameter sharing. To further optimize feature extraction and reduce the impact of spatial channel attention redundancy in the RFSC module, we connected a self-designed Precise Coordinate Attention (PCA) module after the RFSC module to achieve redundancy reduction. In the design of the classifier, CANnet abandoned the commonly used MLP in traditional models and instead adopted improved Kolmogorov Arnold Networks-s (KANs) for classification operations. KANs technology helps CANnet to more finely utilize extracted features for classification tasks through learnable activation functions. This is the first application of the KAN concept in crop disease recognition and has achieved excellent results. To comprehensively evaluate the performance of CANnet, we conducted extensive experiments on our cotton disease dataset and a publicly available cotton disease dataset. Numerous experimental results have shown that CANnet outperforms other advanced methods in the accuracy of cotton disease identification. Specifically, on the self-built dataset, the accuracy reached 96.3%; On the public dataset, the accuracy reached 98.6%. These results fully demonstrate the excellent performance of CANnet in cotton disease identification tasks. Full article

In order to study the effect of laser remelting on the properties of Q235 steel, WC-enhanced nickel-based remelted layers at different powers were prepared on the surface of Q235 steel using laser cladding technology. Their micro-morphologies were observed using scanning electron microscopy, and their hardness and corrosion resistance were tested using a Vickers hardness tester and an electrochemical workstation. The results show that when the laser power reached 1600 W, the number of WC particles was reduced, the fragments of the broken reinforcement particles were more evenly distributed, the fused layer had the highest uniformity, and the microhardness was more average. Additionally, the corrosion current density reached 2.397 × 10⁻⁵ A/cm², the self-corrosion potential E_corr of the remelted coatings was positive relative to the substrate, the corrosion resistance was the highest, the coating was uniformly flat, and its hardness was the highest. Full article

Objective: Understanding both the positive and negative psychological outcomes among cancer patients during the pandemic is critical for planning post-pandemic cancer care. This study (1) examined levels of psychological distress and post-traumatic growth (PTG) among Canadian cancer patients during the COVID-19 pandemic and (2) explored variables that were associated with psychological distress and PTG during the pandemic using a biopsychosocial framework. Method: A cross-section survey was undertaken of patients receiving ongoing care at a regional cancer centre in Ontario, Canada, between February and December 2021. Self-reported questionnaires assessing sociodemographic information, social difficulties, psychological distress (depression, anxiety fear of recurrence, and emotional distress), PTG, illness perceptions, and behavioural responses to the pandemic were administered. Disease-related information was extracted from patient health records. Results: Prevalences of moderate to severe levels of depression, anxiety, fear of recurrence and emotional distress were reported by 26.0%, 21.2%, 44.2%, and 50.0% of the sample (N = 104), respectively. Approximately 43% of the sample reported experiencing high PTG, and these positive experiences were not associated with levels of distress. Social factors, including social difficulties, being female, lower education, and unemployment status were prominent associative factors of patient distress. Perceptions of the pandemic as threatening, adopting more health safety behaviours, and not being on active treatment also increased patient likelihood to experience severe psychological distress. Younger age and adopting more health safety behaviours increased the likelihood of experiencing high PTG. The discriminatory power of the predictive models was strong, with a C-statistic > 0.80. Conclusions: Examining both the positive and negative psychological patient outcomes during the pandemic has highlighted the complex range of coping responses. Interventions that adopt a multi-pronged approach to screen and address social distress, as well as to leverage health safety behaviours, may improve the adjustments in the pandemic aftermath. Full article

In this article, I develop a critique of Chantal Mouffe’s leftist populism and its construction of ‘the people’ against an opposed ‘them’, from a perspective informed by the thought of Didier Eribon. I draw on both his public interventions and his theoretical work, employing his concepts of return, society as verdict, and his two principles of critical thinking to question the desirability of crafting ‘the people’ in the first place. I contend that Eribon’s critique renders Mouffe’s proposal problematic on three accounts. First, her approach is too politically volatile; its instability leaves it devoid of a critical analysis of the differences between concrete social positions, struggles, and subjectivities within ‘the people’. Consequently, the political becomes merely a function of the social. Yet, the social and its determining power remain mostly unaddressed by her framework. Second, its simplistic opposition of an overly generalised ‘the people’ against ‘the oligarchy’ is susceptible to right-wing populist appropriations. Third, for a shot at hegemony and a general appeal, it eclipses plurality and dissensus within ‘the people’. In contrast, Eribon encourages a connection between the social and the political by suggesting that a self-critical analysis be mutually intertwined with social analysis. Instead of merely mobilising affects, they must be critically interrogated. Instead of summoning ‘the people’, a return to their respective genesis must be attempted. Unless both principles of critical thinking, the insights of return, and societal verdicts are deployed to come to terms with the social determinisms at hand, the ‘people’s’ mobilisation against an opposed ‘them’ risks sacrificing pluralism and equality alike and neglecting the criteria of the desirability of specific changes in favour of a “whatever it costs” attempt at hegemony. Full article

This review explores the integration of graphene and liquid crystals to advance sensor technologies across multiple domains, with a focus on recent developments in thermal and infrared sensing, flexible actuators, chemical and biological detection, and environmental monitoring systems. The synergy between graphene’s exceptional electrical, optical, and thermal properties and the dynamic behavior of liquid crystals leads to sensors with significantly enhanced sensitivity, selectivity, and versatility. Notable contributions of this review include highlighting key advancements such as graphene-doped liquid crystal IR detectors, shape-memory polymers for flexible actuators, and composite hydrogels for environmental pollutant detection. Additionally, this review addresses ongoing challenges in scalability and integration, providing insights into current research efforts aimed at overcoming these obstacles. The potential for multi-modal sensing, self-powered devices, and AI integration is discussed, suggesting a transformative impact of these composite sensors on various sectors, including health, environmental monitoring, and technology. This review demonstrates how the fusion of graphene and liquid crystals is pushing the boundaries of sensor technology, offering more sensitive, adaptable, and innovative solutions to global challenges. Full article

Background and Objectives: The treatment of advanced and metastatic lung cancer is multimodal, and it is coordinated by a multidisciplinary team. Anxiety and depression occur frequently in patients with lung cancer, creating considerable discomfort in therapeutic management. At the same time, these psychoemotional symptoms affect the patients’ quality of life. Objective: This research seeks to identify correlations both between anxiety and depression and the patients’ performance statuses, as well as between anxiety and depression and the type of treatment: radiotherapy, chemotherapy, tyrosine kinase inhibitors (TKI), immunotherapy and palliative care. Materials and Methods: The study evaluated 105 patients with lung cancer from two oncologic centers. Patients were assessed for anxiety and depression using the questionnaire Hospital Anxiety and Depression Scale (HADS). The HADS is a self-report rating scale of 14 items. It measures anxiety and depression, and has two subscales. There are seven items for each subscale. There are 4-point Likert scale ranging from 0 to 3. For each subscale, the score is the sum of the seven items, ranging from 0 to 21. Results: The most powerful correlation with statistical significance was observed between the IT type of treatment (immunotherapy) and the normal level of anxiety, PC = 0.82 (p < 0.001) as well as the normal level of depression. Palliative treatment was correlated with anxiety and depression, both borderline and abnormal. For ECOG 3–4 performance status and abnormal anxiety, respectively, abnormal depression was significantly associated. Also, continuous hospitalization was associated with abnormal anxiety and depression. Conclusions: Early assessments of anxiety and depression are necessary in patients with advanced and metastatic lung cancer, with unfavorable performance status, who have been admitted to continuous hospitalization, and who require palliative care. Full article

This work aims to provide the hardware (HW) design of the optoelectronics interfaces for a visible-light communication (VLC) system that can be employed for several use cases. Potential applications include the transmission of ultra-high-definition (UHD) streaming video through existing reading lamps installed in passenger vans. In this use case, visible light is employed for the downlink, while infrared light is used for the uplink channel, acting as a remote controller. Two primary components -a Light Fidelity (LiFi) router and a USB dongle—were designed and implemented. The ‘LiFi Router’, handling the downlink channel, comprises components such as a visible Light-Emitting Diode (LED) and an infrared receiver. Operating at a supply voltage of 12 V and consuming current at 920 mA, it is compatible with standard voltage buses found in transport vehicles. The ‘USB dongle’, responsible for the uplink, incorporates an infrared LED and a receiver optimized for visible light. The USB dongle works at a supply voltage of 5 V and shows a current consumption of 1.12 A, making it well suited for direct connection to a universal serial bus (USB) port. The bandwidth achieved for the downlink is 11.66 MHz, while the uplink’s bandwidth is 12.27 MHz. A system competent at streaming UHD video with the feature of being single-input multiple-output (SIMO) was successfully implemented via the custom hardware design of the optical transceivers and optoelectronics interfaces. To ensure the system’s correct performance at a distance of 110 cm, the minimum signal-to-noise ratio (SNR_min) for both optical links was maintained at 10.74 dB. We conducted a proof-of-concept test of the VLC system in a passenger van and verified its optimal operation, effectively illustrating its performance in a real operating environment. Exemplifying potential implementations possible with the hardware system designed in this work, a bit rate of 15.2 Mbps was reached with On–Off Keying (OOK), and 11.25 Mbps was obtained with Quadrature Phase Shift Keying (QPSK) using Orthogonal Frequency-Division Multiplexing (OFDM) obtaining a bit-error rate (BER) of 3.3259 × 10⁻⁵ in a passenger van at a distance of 72.5 cm between the LiFi router and the USB dongle. As a final addition, a solar panel was installed on the passenger van’s roof to power the user’s laptop and the USB dongle via a power bank battery. It took 13.4 h to charge the battery, yielding a battery life of 22.3 h. This characteristic renders the user’s side of the system entirely self-powered. Full article

Electric tractors have many advantages, including high torque, excellent controllability, energy efficiency, a simple structure, and an electric interface for expansion. However, a significant limitation lies in their endurance. This study presents the design of an extended-range power supply system to ensure continuous endurance for an electric tractor. The objective is to provide a continuous power source for our self-developed electric tractor while preserving the benefits of electric propulsion. Extended-range power systems utilize a primary mover, typically an oil-fueled internal combustion engine, to drive the generator for electricity generation, and the generated AC-form electricity is subsequently converted into stable DC bus voltage by a power electronic converter. The hardware and control design of an extended-range power supply system are finalized and validated through experimental trials. The results demonstrate the system’s capability to sustain stable DC bus voltage amidst disruptions such as sudden load shifts and fluctuations in the prime mover’s speed. Even with a 50% sudden load change, the voltage drop is within 12% and can recover to ±3% within 4 s. The extended-range can be used alone without a battery to power the electric tractor, or it can used in parallel with other extended ranges or batteries for power sharing thanks to the droop control ability. Full article

Service-learning is a community-based learning approach that bridges academic knowledge with practical application through purposeful exploration, action, and reflection. In addition to enhancing academic learning in various disciplines, service-learning cultivates students’ self-awareness, personal values, and social responsibility, preparing them with essential skills for life beyond the classroom. However, due to its experiential nature, service-learning presents challenges for effective assessment. This study provides a concrete example of student reflections structured by the Objective, Reflective, Interpretive, and Decisional (ORID) model in practice. Content analysis was implemented by examining undergraduate students’ end-of-semester reflection papers while volunteering during the 2022 FIFA World Cup in Qatar. The results showed that the model provided a guided and structured format for students to reflect on their service-learning, going beyond reporting on factual details to engaging in profound reflections on the emotional, cognitive, and prospective aspects. Moreover, with the solution aspect added to the model, students could express their creativity, articulating on innovative solutions they proposed to overcome challenges and how they turned the challenges into favorable outcomes. Clearly, the model stands as a powerful tool for educators, offering deeper insights into students’ authentic experiences, fostering comprehensive, critical, and insightful reflection, and thereby facilitating the effective assessment of experiential learning. Full article

This paper studies the development of piezoelectric energy harvesting for self-powered leadless intracardiac pacemakers. The energy harvester fit inside the battery compartment, assuming that the energy harvester would replace the battery with a smaller rechargeable battery capacity. The power output analysis was derived from the three-dimensional finite element analysis and in vivo heart measurements. A Doppler laser at the anterior basal in the right ventricle directly measured the heart’s kinetic motion. Piezoceramics in the cantilevered configuration were studied. The heart motion was periodic but not harmonic and shock-based. This study found that energy can be harvested by applying periodic bio-movements (cardiac motion). The results also showed that the energy harvester can generate 1.1 V voltage. The effect of various geometrical parameters on power generation was studied. This approach offers potential for self-powered implantable medical devices, with the harvested energy used to power devices such as pacemakers. Full article