bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of the Pyrethroid Pesticide Fenpropathrin on the Cardiac Performance of Zebrafish and the Potential Mechanism of Toxicity
Authors: Saputra Ferry , Lai Yu-Heng , Roldan Marri Jmelou M. , Alos Honeymae C. , Aventurado Charlaine A. , Vasquez Ross D. , Hsiao Chung-Der
Published: September 2023

Fenpropathrin, a pyrethroid insecticide, has been widely used for many years in agricultural fields. It works by disturbing the voltage-gated sodium channel, leading to paralysis and the death of the target animal. While past studies have focused on neurodegeneration following fenpropathrin poisoning in humans, relatively few pieces of research have examined its effect on other peripheral organs. This study successfully investigated the potential toxicity of fenpropathrin on the cardiovascular system using zebrafish as an animal model. Zebrafish larvae exposed to varying doses of fenpropathrin underwent an evaluation of cardiac physiology by measuring the heart rate, stroke volume, cardiac output, and shortening fraction. The blood flow velocity and the dorsal aorta diameter were also measured to assess the impact of fenpropathrin exposure on the vascular system. Furthermore, molecular docking was performed to evaluate the pesticide binding affinity to various proteins associated with the cardiovascular system, revealing the potential mechanism of the fenpropathrin cardiotoxic effect. The findings demonstrated a significant dose-dependent increase in the heart rate stroke volume, cardiac output, shortening fraction, and ejection fraction of zebrafish larvae after 24 h of acute treatment with fenpropathrin. Additionally, zebrafish treated at a concentration of 1 ppm exhibited significantly larger blood vessels in diameter and an increased blood flow velocity compared to the control group. According to molecular docking, fenpropathrin showed a high affinity for various voltage-gated sodium channels like scn1lab, cacna1sb, and clcn3. Finally, from the results, we found that fenpropathrin caused cardiomegaly, which may have been induced by the voltage-gated sodium channel disruption. This study highlights the significant disruption of fenpropathrin in the cardiovascular system and emphasizes the need for further research on the health implications of this pesticide.
Focused Overview of Mycobacterium tuberculosis VapBC Toxin–Antitoxin Systems Regarding Their Structural and Functional Aspects: Including Insights on Biomimetic Peptides
Authors: Kang Sung-Min
Published: September 2023

Tuberculosis, caused by Mycobacterium tuberculosis, is a lethal infectious disease of significant public health concern. The rise of multidrug-resistant and drug-tolerant strains has necessitated novel approaches to combat the disease. Toxin–antitoxin (TA) systems, key players in bacterial adaptive responses, are prevalent in prokaryotic genomes and have been linked to tuberculosis. The genome of M. tuberculosis strains harbors an unusually high number of TA systems, prompting questions about their biological roles. The VapBC family, a representative type II TA system, is characterized by the VapC toxin, featuring a PilT N-terminal domain with nuclease activity. Its counterpart, VapB, functions as an antitoxin, inhibiting VapC’s activity. Additionally, we explore peptide mimics designed to replicate protein helical structures in this review. Investigating these synthetic peptides offers fresh insights into molecular interactions, potentially leading to therapeutic applications. These synthetic peptides show promise as versatile tools for modulating cellular processes and protein–protein interactions. We examine the rational design strategies employed to mimic helical motifs, their biophysical properties, and potential applications in drug development and bioengineering. This review aims to provide an in-depth understanding of TA systems by introducing known complex structures, with a focus on both structural aspects and functional and molecular details associated with each system.
Skin-Contact Triboelectric Nanogenerator for Energy Harvesting and Motion Sensing: Principles, Challenges, and Perspectives
Authors: Matin Nazar Ali , Mohsenian Reza , Rayegani Arash , Shadfar Mohammadamin , Jiao Pengcheng
Published: September 2023

Energy harvesting has become an increasingly important field of research as the demand for portable and wearable devices continues to grow. Skin-contact triboelectric nanogenerator (TENG) technology has emerged as a promising solution for energy harvesting and motion sensing. This review paper provides a detailed overview of skin-contact TENG technology, covering its principles, challenges, and perspectives. The introduction begins by defining skin-contact TENG and explaining the importance of energy harvesting and motion sensing. The principles of skin-contact TENG are explored, including the triboelectric effect and the materials used for energy harvesting. The working mechanism of skin-contact TENG is also discussed. This study then moves onto the applications of skin-contact TENG, focusing on energy harvesting for wearable devices and motion sensing for healthcare monitoring. Furthermore, the integration of skin-contact TENG technology with other technologies is discussed to highlight its versatility. The challenges in skin-contact TENG technology are then highlighted, which include sensitivity to environmental factors, such as humidity and temperature, biocompatibility and safety concerns, and durability and reliability issues. This section of the paper provides a comprehensive evaluation of the technological limitations that must be considered when designing skin-contact TENGs. In the Perspectives and Future Directions section, this review paper highlights various advancements in materials and design, as well as the potential for commercialization. Additionally, the potential impact of skin-contact TENG technology on the energy and healthcare industries is discussed.
Predicting Motor Imagery BCI Performance Based on EEG Microstate Analysis
Authors: Cui Yujie , Xie Songyun , Fu Yingxin , Xie Xinzhou
Published: September 2023

Motor imagery (MI) electroencephalography (EEG) is natural and comfortable for controllers, and has become a research hotspot in the field of the brain–computer interface (BCI). Exploring the inter-subject MI-BCI performance variation is one of the fundamental problems in MI-BCI application. EEG microstates with high spatiotemporal resolution and multichannel information can represent brain cognitive function. In this paper, four EEG microstates (MS1, MS2, MS3, MS4) were used in the analysis of the differences in the subjects’ MI-BCI performance, and the four microstate feature parameters (the mean duration, the occurrences per second, the time coverage ratio, and the transition probability) were calculated. The correlation between the resting-state EEG microstate feature parameters and the subjects’ MI-BCI performance was measured. Based on the negative correlation of the occurrence of MS1 and the positive correlation of the mean duration of MS3, a resting-state microstate predictor was proposed. Twenty-eight subjects were recruited to participate in our MI experiments to assess the performance of our resting-state microstate predictor. The experimental results show that the average area under curve (AUC) value of our resting-state microstate predictor was 0.83, and increased by 17.9% compared with the spectral entropy predictor, representing that the microstate feature parameters can better fit the subjects’ MI-BCI performance than spectral entropy predictor. Moreover, the AUC of microstate predictor is higher than that of spectral entropy predictor at both the single-session level and average level. Overall, our resting-state microstate predictor can help MI-BCI researchers better select subjects, save time, and promote MI-BCI development.
Resilience and Strategic Emotional Intelligence as Mediators between the Disconnection and Rejection Domain and Negative Parenting among Female Intimate Partner Violence Victims
Authors: Sójta Klaudia , Juraś-Darowny Małgorzata , Margulska Aleksandra , Jóźwiak-Majchrzak Wioletta , Grażka Anna , Strzelecki Dominik
Published: September 2023

(1) Background: The exposure of children to intimate partner violence (IPV) is associated with a wide range of negative effects on children’s development, where as parenting practice is considered to be one of the key factors mediating and mitigating this. Studies have found mixed results regarding the impact of female IPV victimization on maternal parenting practice; however, the most frequently tested hypothesis suggests that the cumulative stress of the IPV experience may emotionally deregulate the mother, contributing to an increased risk of neglected and abusive parenting practices. Little is still known about the factors determining the observed differences in maternal parenting practices among IPV victims. Thus, in our study, we use mediation models to provide preliminary results exploring the role of resilience and strategic emotional intelligence in the relationship between women’s disconnection and rejection (D/R) schema domain and maternal parenting practice among IPV victims. (2) Methods: A total of 48 female survivors of IPV and 48 age-matched women with no prior experience of IPV completed a set of tests examining parenting practices, the D/R domain, resilience and emotional intelligence. (3) Results: IPV victimization was associated with significantly higher rates of negative parenting practices. The D/R domain was found to be a significant predictor of parental autonomy attitude and level of parental competence, and these relationships were fully mediated by resilience with strategic emotional intelligence and resilience, respectively. (4) Conclusions: The results shed light on the under-researched relationship between early maladaptive schemas and parenting behavior in the context of IPV. The implications for clinical practice and further research can be drawn based on the study findings.
The Impact of the Perception of Primary Facial Emotions on Corticospinal Excitability
Authors: Fiori Francesca , Ciricugno Andrea , Cattaneo Zaira , Ferrari Chiara
Published: September 2023

The link between emotional experience and motor body responses has long been acknowledged. A well-established approach to exploring the effect of the perception of emotional stimuli on the motor system is measuring variations in the excitability of the corticospinal tract (CSE) through motor-evoked potentials (MEP) elicited via transcranial magnetic stimulation (TMS). Previous evidence has indicated a selective increase in MEP amplitude while participants view emotional stimuli, such as emotional facial expressions, compared to neutral cues. However, it is still not clear whether this effect depends on the specific emotional meaning conveyed by the stimulus. In the present study, we explored whether viewing faces expressing the primary emotions compared to faces with a neutral expression affects individuals’ CSE, measured using TMS-elicited MEPs. Specifically, we elicited MEPs from the left motor cortex (M1) while participants passively viewed the same faces expressing either anger, fear, disgust, happiness, sadness, surprise, and no emotion (in different blocks). We found that the observation of fearful, angry, disgusted, and happy facial expressions was associated with a significant increase in the MEPs’ amplitude compared to neutral facial expressions, with a comparable enhancement in the CSE occurring across these emotions. In turn, viewing sad and surprised faces did not modulate the CSE. Overall, our findings suggest that only facial expressions that signal (real or potential) danger or a rewarding stimulus, but not emotional facial expressions per se, are capable of activating action-related mechanisms.
To Take a Risk or Not? The Effect of Perceived Scarcity on Risky Choices
Authors: Liang Shujing , Fan Ping , Yang Guangyong
Published: September 2023

Studies suggest that resource scarcity leads to risky behaviors. From a cognitive perspective, a scarcity mindset affects the decision-making process. Does perceived scarcity therefore affect risk taking when making decisions? This study (N = 213) was conducted in western China to examine the effect of perceived scarcity on risky choices. Our results revealed that participants in the scarcity condition tended to be more risk averse than participants in the control condition when making a risky decision. Perceived scarcity increased the probability of choosing the safe option that offered a sure gain. The effect of psychological variables (emotion, risk attitude, personality, impulsivity, self-control and ego depletion) on risky choices was also tested. Risk attitude, urgency in impulsivity, and deliberate action in self-control also influence risky choices.
A Comprehensive Approach to Earthquake-Resilient Infrastructure: Integrating Maintenance with Seismic Fragility Curves
Authors: Urlainis Alon , Shohet Igal M.
Published: September 2023

A severe seismic event can cause significant damage to infrastructure systems, resulting in severe direct and indirect consequences. A comprehensive risk-management approach is required for earthquake-resilient infrastructure. This study presents an innovative approach to seismic risk assessment and aims to integrate maintenance considerations with seismic fragility curves. The proposed methodology uniquely quantifies the impact of maintenance conditions on seismic risk, presenting a dynamic perspective of risk changes attributable to maintenance and deterioration. The methodology hinges on the hypothesis that the maintenance condition of the infrastructure and the level of deterioration impacts the seismic resilience of the infrastructure. The methodology synergizes the Building Performance Index (BPI) and the deterioration over time to evaluate their cumulative effect on fragility curves to estimate the infrastructure’s total risk over the lifecycle (TRLC). This proposed methodology is demonstrated through a case study of a low-voltage substation in Bik’at HaYarden, Israel. A Monte Carlo simulation was carried out for the specific conditions of the analyzed substation. A comprehensive sensitivity analysis was performed to understand better the effect of maintenance conditions over time on the TRLC. Key insights reveal a statistically significant correlation between infrastructure performance and maintenance and their consequential impact on the TRLC. Notably, declining maintenance conditions intensify seismic risk uncertainties. The research proposes to researchers, stakeholders, and decision-makers a novel comprehensive perspective on the indispensability of maintenance for seismic risk management and mitigation.
Earlier Diagnosis of Pancreatic Cancer: Is It Possible?
Authors: Koltai Tomas
Published: September 2023

Pancreatic ductal adenocarcinoma has a very high mortality rate which has been only minimally improved in the last 30 years. This high mortality is closely related to late diagnosis, which is usually made when the tumor is large and has extensively infiltrated neighboring tissues or distant metastases are already present. This is a paradoxical situation for a tumor that requires nearly 15 years to develop since the first founding mutation. Response to chemotherapy under such late circumstances is poor, resistance is frequent, and prolongation of survival is almost negligible. Early surgery has been, and still is, the only approach with a slightly better outcome. Unfortunately, the relapse percentage after surgery is still very high. In fact, early surgery clearly requires early diagnosis. Despite all the advances in diagnostic methods, the available tools for improving these results are scarce. Serum tumor markers permit a late diagnosis, but their contribution to an improved therapeutic result is very limited. On the other hand, effective screening methods for high-risk populations have not been fully developed as yet. This paper discusses the difficulties of early diagnosis, evaluates whether the available diagnostic tools are adequate, and proposes some simple and not-so-simple measures to improve it.
T2-Weighted MRI Radiomic Features Predict Prostate Cancer Presence and Eventual Biochemical Recurrence
Authors: Duenweg Savannah R. , Bobholz Samuel A. , Barrett Michael J. , Lowman Allison K. , Winiarz Aleksandra , Nath Biprojit , Stebbins Margaret , Bukowy John , Iczkowski Kenneth A. , Jacobsohn Kenneth M. , Vincent-Sheldon Stephanie , LaViolette Peter S.
Published: September 2023

Prostate cancer (PCa) is the most diagnosed non-cutaneous cancer in men. Despite therapies such as radical prostatectomy, which is considered curative, distant metastases may form, resulting in biochemical recurrence (BCR). This study used radiomic features calculated from multi-parametric magnetic resonance imaging (MP-MRI) to evaluate their ability to predict BCR and PCa presence. Data from a total of 279 patients, of which 46 experienced BCR, undergoing MP-MRI prior to surgery were assessed for this study. After surgery, the prostate was sectioned using patient-specific 3D-printed slicing jigs modeled using the T2-weighted imaging (T2WI). Sectioned tissue was stained, digitized, and annotated by a GU-fellowship trained pathologist for cancer presence. Digitized slides and annotations were co-registered to the T2WI and radiomic features were calculated across the whole prostate and cancerous lesions. A tree regression model was fitted to assess the ability of radiomic features to predict BCR, and a tree classification model was fitted with the same radiomic features to classify regions of cancer. We found that 10 radiomic features predicted eventual BCR with an AUC of 0.97 and classified cancer at an accuracy of 89.9%. This study showcases the application of a radiomic feature-based tool to screen for the presence of prostate cancer and assess patient prognosis, as determined by biochemical recurrence.
Management of Small Bowel Neuroendocrine Tumours: 10 Years’ Experience at a Tertiary Referral Centre
Authors: Clift Ashley K. , Drymousis Panagiotis , von Roon Alexander , Humphries Adam , Goldin Robert , Bomanji Jamshed , Leaman Sydney , Wasan Harpreet , Habib Nagy , Frilling Andrea
Published: September 2023

Background: Neuroendocrine tumours (NET) arising from the small bowel are clinically challenging and are often diagnosed at advanced stages. Disease control with surgery alone can be demanding. Multimodal treatment concepts integrating surgery and non-surgical modalities could be of benefit. Method: Retrospective review of consecutive adult patients with SB NET treated at Imperial College Healthcare NHS Trust between 1 January 2010 and 31 December 2019. Data regarding clinicopathological characteristics, treatments, and disease trajectory were extracted and summarised. Overall and progression/recurrence-free survival were estimated at 5 and 10 years. Results: 154 patients were identified, with a median age of 64 years (range 33–87); 135/154 (87.7%) had stage III/IV disease at diagnosis. Surgery was used in 125 individuals (81.2%), typically with either segmental small bowel resection (60.8%) or right hemicolectomy (33.6%) and mesenteric lymphadenectomy for the primary tumour. Systemic and/or liver-directed therapies were used in 126 (81.8%); 60 (47.6%) had more than one line of non-surgical treatment. Median follow-up was 67.2 months (range 3.1–310.4); overall survival at 5 and 10 years was 91.0% (95% CI: 84.9–94.7%) and 82.5% (95% CI: 72.9–88.9%), respectively. Imaging-based median progression-free survival was 42.7 months (95% CI: 24.7 to 72.4); 5-year progression-free survival was 63.4% (95% CI: 55.0–70.6%); 10-year progression-free survival was 18.7% (95% CI: 12.4–26.1). Nineteen patients (12.3%) reached 10 years follow-up without disease recurrence and therefore were considered cured. Conclusions: Most patients with SB NET present in a metastasised stage. Multimodal treatment concepts may be associated with excellent clinical outcomes. Future work should explore optimal approaches to treatment sequencing and patient selection.
CAR Protects Females from Diet-Induced Steatosis and Associated Metabolic Disorders
Authors: Oliviero Fabiana , Klement Wendy , Mary Lucile , Dauwe Yannick , Lippi Yannick , Naylies Claire , Gayrard Véronique , Marchi Nicola , Mselli-Lakhal Laila
Published: September 2023

Non-Alcoholic Fatty Liver Disease (NAFLD) is the most common cause of chronic liver disease worldwide, affecting 70–90% of obese individuals. In humans, a lower NAFLD incidence is reported in pre-menopausal women, although the mechanisms affording this protection remain under-investigated. Here, we tested the hypothesis that the constitutive androstane nuclear receptor (CAR) plays a role in the pathogenesis of experimental NAFLD. Male and female wild-type (WT) and CAR knock-out (CAR−/−) mice were subjected to a high-fat diet (HFD) for 16 weeks. We examined the metabolic phenotype of mice through body weight follow-up, glucose tolerance tests, analysis of plasmatic metabolic markers, hepatic lipid accumulation, and hepatic transcriptome. Finally, we examined the potential impact of HFD and CAR deletion on specific brain regions, focusing on glial cells. HFD-induced weight gain and hepatic steatosis are more pronounced in WT males than females. CAR−/− females present a NASH-like hepatic transcriptomic signature suggesting a potential NAFLD to NASH transition. Transcriptomic correlation analysis highlighted a possible cross-talk between CAR and ERα receptors. The peripheral effects of CAR deletion in female mice were associated with astrogliosis in the hypothalamus. These findings prove that nuclear receptor CAR may be a potential mechanism entry-point and a therapeutic target for treating NAFLD/NASH.
Anodic Performance of Ni–BCZY and Ni–BCZY–GDC Films on BCZY Electrolytes
Authors: Itagaki Yoshiteru , Kumamoto Yota , Okayama Susumu , Aono Hiromichi
Published: September 2023

Cermet films consisting of Ni, BaCe0.4Zr0.4Y0.2O3−δ (BCZY), and Gd0.1Ce0.9Ox (GDC), specifically, 60 wt%Ni–BCZY, 60 wt%Ni–BCZY–GDC, and 60 wt%Ni–GDC, were formed on BCZY electrolyte supports as anodes of proton ceramic fuel cells (PCFCs). The Ni grain size in these films after sintering at 1450 °C was around 2 μm. The GDC addition did not affect the Ni grain size in the case of the BCZY matrix. The anodic properties greatly depended on the oxide phase composition and worsened with increasing the GDC content. This probably occurred because of the addition of GDC, which has low proton conductivity and inhibited the proton conduction path of BCZY, reducing three-phase boundaries in the anode bulk. Since BCZY has a lower grain growth rate during sintering than BaCe0.8Y0.2O3−δ, the Ni grain growth was likely suppressed by the surrounding Ni grains containing small BCZY grains.
Solid State Fabrication of Copper Nanoclusters and Supraparticles
Authors: Wang Rui , Zheng Yunyun , Xia Yunsheng
Published: September 2023

In this study, we present solid state processes for the fabrication of copper nanoclusters (NCs) and hierarchical supraparticles (SPs). To achieve this, copper salt and thiols are mixed and are then grinded for 10–15 min, and the nano-products are thereby obtained. Interestingly, it was found in this study that the formation of the NCs or SPs is completely dependent on the grinding methods that are used: with mechanical grinding, the products are several nanometer-sized NCs, whereas manual grinding in an agate mortar can obtain Cu SPs with diameters as low as 10 nm all the way up to 200 nm. The photoluminescence emission wavelength of the nano-products is located at ~680 nm. The Stokes shift of the obtained nanomaterials is more than 300 nm. The emission quantum yields of the Cu NCs and SPs are as high as 47.5% and 63%, respectively. Due to their facile fabrication processes and their favorable optical properties, the two as-prepared types of copper nano-materials exhibit great potential for bio-imaging and bio-sensing applications.
Impact of Daily Choral Singing and Creative Writing Activities on the Cognitive Development of Second-, Third-, and Fourth-Grade French Children from Low Socioeconomic Backgrounds
Authors: Gutiérrez Cisneros Angélica , Roussey Juliette , Inbar Talya , Fratacci Althea , Frey Aline
Published: September 2023

In France, around one-fifth of children have reading difficulties, and school results are highly dependent on their socio-economic status. In this context, the need for alternative and innovative teaching techniques holds importance, and more artistic approaches are promising. The aim of this study was to assess the impact of a daily choral singing or creative writing practice on the cognitive and linguistic development of French children from disadvantaged backgrounds. Eighty children participated in this longitudinal study, for whom we measured several cognitive and linguistic skills at the beginning (pre-test) and end (post-test) of the school year. The results showed that children in “singing” classes improved both their reading skills and processing speed, while those in “writing” classes improved their reading skills and vocabulary. These results open up new avenues of learning support, specifically for children with difficulties.
Timing Matters: The Interplay between Early Mealtime, Circadian Rhythms, Gene Expression, Circadian Hormones, and Metabolism—A Narrative Review
Authors: BaHammam Ahmed S. , Pirzada Abdulrouf
Published: September 2023

Achieving synchronization between the central and peripheral body clocks is essential for ensuring optimal metabolic function. Meal timing is an emerging field of research that investigates the influence of eating patterns on our circadian rhythm, metabolism, and overall health. This narrative review examines the relationship between meal timing, circadian rhythm, clock genes, circadian hormones, and metabolic function. It analyzes the existing literature and experimental data to explore the connection between mealtime, circadian rhythms, and metabolic processes. The available evidence highlights the importance of aligning mealtime with the body’s natural rhythms to promote metabolic health and prevent metabolic disorders. Specifically, studies show that consuming meals later in the day is associated with an elevated prevalence of metabolic disorders, while early time-restricted eating, such as having an early breakfast and an earlier dinner, improves levels of glucose in the blood and substrate oxidation. Circadian hormones, including cortisol and melatonin, interact with mealtimes and play vital roles in regulating metabolic processes. Cortisol, aligned with dawn in diurnal mammals, activates energy reserves, stimulates appetite, influences clock gene expression, and synchronizes peripheral clocks. Consuming meals during periods of elevated melatonin levels, specifically during the circadian night, has been correlated with potential implications for glucose tolerance. Understanding the mechanisms of central and peripheral clock synchronization, including genetics, interactions with chronotype, sleep duration, and hormonal changes, provides valuable insights for optimizing dietary strategies and timing. This knowledge contributes to improved overall health and well-being by aligning mealtime with the body’s natural circadian rhythm.
Fabrication of Micron-Structured Heatable Graphene Hydrophobic Surfaces for Deicing and Anti-Icing by Laser Direct Writing
Authors: Li Shichen , Zhong Mian , Zou Yao , Xu Man , Liu Xinyi , Xing Xiaoqing , Zhang Huazhong , Jiang Yong , Qiu Chao , Qin Wenfeng , Li Meng , He Qiang , Zhou Chao
Published: September 2023

As a novel method to prepare graphene, the laser-induced graphene (LIG) technology has numerous outstanding properties and has been widely applied in various fields. Nevertheless, the challenge remains to easily and efficiently prepare multifunctional surfaces of graphene through laser microregulation and fine structure design. Here, we successfully fabricated a micron-structure gully graphene surface with hydrophobicity and electrothermal functionality under atmospheric conditions using a 10.6 μm CO2 laser to directly write on the surface of a polyimide film (PI). The impact of the laser scanning speed on the surface morphology and chemical composition of the product was investigated by analyzing the SEM (scanning electron microscope) observations and Raman spectra, respectively. The mechanical stability of the surface was studied by analyzing the contact angle of water droplets on the surface after mechanical circulation and the delayed icing effect after repeated icing. The deicing and anti-icing performance of the surface were analyzed based on its resistance to surface icing and electric deicing time. According to the experimental results, we first observed a linear negative correlation between the generated structure linewidth and the laser scanning speed. Additionally, we successfully achieved one-step preparation of primitive continuous graphene structures with a superhydrophobic capability (151°). Furthermore, our findings indicate that micron-structured graphene surfaces exhibit excellent mechanical stability, effectively delay icing formation, and demonstrate efficient electric deicing effects. These results demonstrate the potential application of CO2 laser-induced graphene technology in the field of surface preparation for deicing and anti-icing. This work offers a novel one-step approach for the fabrication of micron-structured heatable graphene surfaces with simultaneous superhydrophobicity, deicing, and anti-icing functionalities on polymer substrates.
Effects of Land Cover and Land Use Change on Nature’s Contributions to People of the Shade-Grown Coffee Agroecosystem: An Analysis of Cumbres de Huicicila, Nayarit, Mexico
Authors: Navidad Murrieta Diana Laura , Marceleño Flores Susana María Lorena , Nájera González Areli , Nájera González Oyolsi , Ramírez Silva Juan Pablo
Published: September 2023

The shade-grown coffee agroecosystem is rich in ecosystem services (ES). In recent years, pests and the decrease in coffee prices have caused producers to change their agricultural activities. These changes in land use have resulted in alterations in the vegetation cover that lead to the loss of ES. The objective of this research was to analyze the effects of land cover and land use changes on the ES associated with coffee production in Cumbres de Huicicila, a coffee-growing region in western Mexico. For this purpose, we analyzed land cover and land use maps for the period 2007–2019, calculated the annual rate of change and estimated the future rate of change to 2030. We used a literature review through the SALSA method to identify and estimate the impact of the ES of coffee plantations under the approach of nature’s contributions to people. As a result, we found alterations with a decreasing trend in agroecosystem cover and loss of ES related to biodiversity. We hope that this research will serve to consolidate efforts for the conservation and sustainable use of the ES of the shade-grown coffee plantations.
Reseek-Arrhythmia: Empirical Evaluation of ResNet Architecture for Detection of Arrhythmia
Authors: Haq Shams Ul , Bazai Sibghat Ullah , Fatima Ali , Marjan Shah , Yang Jing , Por Lip Yee , Anjum Mohd , Shahab Sana , Ku Chin Soon
Published: September 2023

Arrhythmia is a cardiac condition characterized by an irregular heart rhythm that hinders the proper circulation of blood, posing a severe risk to individuals’ lives. Globally, arrhythmias are recognized as a significant health concern, accounting for nearly 12 percent of all deaths. As a result, there has been a growing focus on utilizing artificial intelligence for the detection and classification of abnormal heartbeats. In recent years, self-operated heartbeat detection research has gained popularity due to its cost-effectiveness and potential for expediting therapy for individuals at risk of arrhythmias. However, building an efficient automatic heartbeat monitoring approach for arrhythmia identification and classification comes with several significant challenges. These challenges include addressing issues related to data quality, determining the range for heart rate segmentation, managing data imbalance difficulties, handling intra- and inter-patient variations, distinguishing supraventricular irregular heartbeats from regular heartbeats, and ensuring model interpretability. In this study, we propose the Reseek-Arrhythmia model, which leverages deep learning techniques to automatically detect and classify heart arrhythmia diseases. The model combines different convolutional blocks and identity blocks, along with essential components such as convolution layers, batch normalization layers, and activation layers. To train and evaluate the model, we utilized the MIT-BIH and PTB datasets. Remarkably, the proposed model achieves outstanding performance with an accuracy of 99.35% and 93.50% and an acceptable loss of 0.688 and 0.2564, respectively.
Arrhythmic Mitral Valve Prolapse: A Comprehensive Review
Authors: Deng Yuyan , Liu Jinfeng , Wu Shan , Li Xiaoming , Yu Huimei , Tang Lili , Xie Meng , Zhang Chun
Published: September 2023

Mitral valve prolapse (MVP) is a prevalent cardiac disorder that impacts approximately 2% to 3% of the overall population. While most patients experience a benign clinical course, there is evidence suggesting that a subgroup of MVP patients face an increased risk of sudden cardiac death (SCD). Although a conclusive causal link between MVP and SCD remains to be firmly established, various factors have been associated with arrhythmic mitral valve prolapse (AMVP). This study aims to provide a comprehensive review encompassing the historical background, epidemiology, pathology, clinical manifestations, electrocardiogram (ECG) findings, and treatment of AMVP patients. A key focus is on utilizing multimodal imaging techniques to accurately diagnose AMVP and to highlight the role of mitral annular disjunction (MAD) in AMVP.
Examining the Relationships between the Incidence of Infectious Diseases and Mood Disorders: An Analysis of Data from the Global Burden of Disease Studies, 1990–2019
Authors: Rajkumar Ravi Philip
Published: September 2023

Mood disorders are among the commonest mental disorders worldwide. Epidemiological and clinical evidence suggests that there are close links between infectious diseases and mood disorders, but the strength and direction of these association remain largely unknown. Theoretical models have attempted to explain this link based on evolutionary or immune-related factors, but these have not been empirically verified. The current study examined cross-sectional and longitudinal associations between the incidence of infectious diseases and mood disorders, while correcting for climate and economic factors, based on data from the Global Burden of Disease Studies, 1990–2019. It was found that major depressive disorder was positively associated with lower respiratory infections, while bipolar disorder was positively associated with upper respiratory infections and negatively associated with enteric and tropical infections, both cross-sectionally and over a period of 30 years. These results suggest that a complex, bidirectional relationship exists between these disorders. This relationship may be mediated through the immune system as well as through the gut–brain and lung–brain axes. Understanding the mechanisms that link these groups of disorders could lead to advances in the prevention and treatment of both.
Assessing Massive Open Online Courses for Developing Digital Competences among Higher Education Teachers
Authors: Bitakou Effrosyni , Ntaliani Maria , Demestichas Konstantinos , Costopoulou Constantina
Published: September 2023

The outstanding growth in digital technologies has raised higher education teachers’ attention towards developing digital competences for effectively fulfilling students’ learning requirements and keeping up with the rapidly evolving global education system. Nowadays, higher education teachers can find a plethora of online courses provided by educational organizations, universities, and businesses for reskilling and upskilling. The objective of this paper is to provide results from the assessment of existing massive open online courses regarding their potential to cover a large range of digital competences that higher education teachers should possess. A total of one hundred and sixty-two (162) online courses from three prominent international digital platforms, offering massive open online courses, were subjected to evaluation using a model incorporating six categories of attributes aligned with pertinent digital competences. The results indicate that the majority of the existing online courses lack sufficient coverage of key digital competences required by higher education teachers. Notably, these inadequately addressed competences regard evaluating students’ performance in the digital environment and ensuring positive online student experiences through collaborative engagement and self-reflection. The findings of this study offer valuable insights not only to higher education teachers, but also to online course developers and education policy-makers. The identified gaps in digital competences underscore the pressing need for substantial improvements in existing online courses or the development of new courses to effectively bridge these competence gaps. By addressing these shortcomings, higher education institutions can better equip their teachers to navigate the digital realm and elevate the overall quality of education in the digital era.
A New Approach for Implementing Finite State Machines with Input Multiplexing
Authors: Garcia-Vargas Ignacio , Senhadji-Navarro Raouf
Published: September 2023

The model called Finite State Machine with Input Multiplexing (FSMIM) was proposed as a mechanism for implementing Finite State Machines (FSMs) using ROM memory. This paper presents a novel approach for achieving more efficient FSMIM implementations in Field Programmable Gate Array (FPGA) devices. The aim of the proposed approach is to obtain further reductions in the use of Embedded Memory Blocks (EMBs). Unlike previous works, the proposed approach reduces the depth of the ROM by grouping states before simplifying the input selectors of the FSMIM. For this purpose, a new strategy for grouping states is proposed, and its optimality is proven. In addition, a new variant of the Minimum Maximal k-Partial Matching (MMKPM) problem and its corresponding Integer Linear Programming (ILP) formulation are proposed for simplifying input selectors. The proposed approach requires a significantly smaller number of EMBs than the approaches proposed previously.
A Secure Cooperative Transmission of Image Super-Resolution in Wireless Relay Networks
Authors: Duong Hien-Thuan , Phan Ca V. , Vien Quoc-Tuan , Nguyen Tuan T.
Published: September 2023

The image transmission over wireless media experiences not only unavailable performance loss caused by the environment and hardware issues, but also information leakage to eavesdroppers who can overhear and attempt to recover the images. This paper proposes a secure cooperative relaying (SCR) protocol for the image communications in wireless relay networks (WRNs) where Alice sends high-resolution (HR) images to Bob with the assistance of a relaying user named Relay, and in the presence of an eavesdropper named Eve. In order to enhance the security of the image communications, random linear network coding (RLNC) is employed at both Alice and Relay to conceal the original images from Eve with RLNC coefficient matrices and reference images in the shared image datastore. Furthermore, the original HR images are downscaled at Alice to save transmission bandwidth and image super-resolution (ISR) is adopted at Bob due to its capability to recover the HR images from their low-resolution (LR) version, while still maintaining the image quality. In the proposed SCR protocol, Bob can decode both the original images transmitted from Alice over the direct link and the images forwarded by Relay over the relaying links. Simulation results show that the SCR protocol achieves a considerably higher performance at Bob than at Eve since Eve does not know the coefficient matrices and reference images used at Alice and Relay for the RLNC. The SCR protocol is also shown to outperform the counterpart secure direct transmission protocol without the relaying links and secure relaying transmission without the direct link. Additionally, an increased scaling factor can save the transmission bandwidth for a slight change in the image quality. Moreover, the impacts of direct, relaying and wiretap links are evaluated, verifying the effectiveness of the SCR protocol with the employment of Relay to assist the image communications between Alice and Bob in the WRNs.
Differential Privacy-Based Spatial-Temporal Trajectory Clustering Scheme for LBSNs
Authors: Zhu Liang , Lei Tingting , Mu Jinqiao , Mu Jingzhe , Cai Zengyu , Zhang Jianwei
Published: September 2023

Location privacy preserving for location-based social networks (LBSNs) has been attracting a great deal of attention. Existing location privacy protection methods are disadvantaged by issues such as information leakage and low data availability, which are no longer suitable for the current diverse and personalized location-based services. To address these issues, we propose a differential privacy-based spatial-temporal trajectory clustering (DP-STTC) scheme, which mainly transforms the existing location privacy protection mechanism into a spatial-temporal trajectory protection mechanism by adjusting the privacy parameters. Then, the trajectories were clustered to uncover users with similar trajectory characteristics. Finally, experiments were conducted on two real datasets. The experimental results show that our DP-STTC scheme can not only achieve better accuracy in trajectory clustering, but also protect user privacy.
Droop-Free Sliding-Mode Control for Active-Power Sharing and Frequency Regulation in Inverter-Based Islanded Microgrids
Authors: Rosero Carlos Xavier , Gavilánez Milton , Mejía-Echeverría Cosme
Published: September 2023

This paper introduces a simple decentralized sliding-mode (SM) approach to control active power sharing by regulating the local frequency in inverter-based islanded microgrids (MGs). Its sliding surface arises from the frequency correction term introduced in the droop-free technique; it relates local active power to neighboring MGs’ active power by considering available communications among voltage source inverters. Then, this schema allows one to avoid hierarchical control just as the droop-free method does, and the benefits associated are twofold. First, it reduces the steady-state frequency error while providing accurate active power distribution. Second, the system stays reliable, withstands uncertainties, and provides a fast transient response. A Lyapunov analysis confirms stability, and simulations on a realistic four-inverter MG platform substantiate the control scheme’s effectiveness. Its performance regards frequency regulation while achieving active power sharing, stability, and robustness against clock drifts and load steps.
Multidimensional Feature-Based Graph Attention Networks and Dynamic Learning for Electricity Load Forecasting
Authors: Huang Chaokai , Du Ning , He Jiahan , Li Na , Feng Yifan , Cai Weihong
Published: September 2023

Electricity load forecasting is of great significance for the overall operation of the power system and the orderly use of electricity at a later stage. However, traditional load forecasting does not consider the change in load quantity at each time point, while the information on the time difference of the load data can reflect the dynamic evolution information of the load data, which is a very important factor for load forecasting. In addition, the research topics in recent years mainly focus on the learning of the complex relationships of load sequences in time latitude by graph neural networks. The relationships between different variables of load sequences are not explicitly captured. In this paper, we propose a model that combines a differential learning network and a multidimensional feature graph attention layer, it can model the time dependence and dynamic evolution of load sequences by learning the amount of load variation at different time points, while representing the correlation of different variable features of load sequences through the graph attention layer. Comparative experiments show that the prediction errors of the proposed model have decreased by 5–26% compared to other advanced methods in the UC Irvine Machine Learning Repository Electricity Load Chart public dataset.
Numerical Investigation of Heat Transfer and Flow Characteristics of Supercritical CO2 in Solar Tower Microchannel Receivers at High Temperature
Authors: Zhuang Xiaoru , Wang Haitao , Lu Haoran , Yang Zhi , Guo Hao
Published: September 2023

Using supercritical CO2 as a heat transfer fluid in microchannel receivers is a promising alternative for tower concentrating solar power plants. In this paper, the heat transfer and flow characteristics of supercritical CO2 in microchannels at high temperature are investigated by numerical simulations. The effects of microchannel structure, mass flow rate, heat flux, pressure, inlet temperature and radiation are analyzed and discussed. The results show that higher mass flow rate obtains poorer heat transfer performance with larger flow resistance of supercritical CO2 in microchannels at high temperature. The fluid and wall temperatures, average heat transfer coefficient and pressure drop all increase nearly linearly with the increases in heat flux and inlet temperature in the high-temperature region. Moreover, high pressure contributes to great hydraulic performance with approximate thermal performance. The effect of radiation on thermal performance is more pronounced than that on hydraulic performance. Furthermore, the optimized structures of inlet and outlet headers, as well as those of the multichannel in the microchannels, are proposed to obtain good temperature uniformity in the microchannels with relatively low pressure drop. The results given in the current study can be conducive to the design and application of microchannel receivers with supercritical CO2 as a heat transfer fluid in the third generation of concentrating solar power plants.
Real-Time Implementation and Control of Multi-Source Electric Vehicle Traction Motor under Various Drive Conditions
Authors: Prasanthi Achikkulath , Shareef Hussain , Errouissi Rachid , Asna Madathodika , Wahyudie Addy
Published: September 2023

The hybridization of multiple energy sources is crucial for electric vehicles to deliver the same performance as modern fossil fuel-based automobiles. This paper presents a torque and speed control strategy for an electric vehicle DC traction motor by regulating the power flow from two energy sources, namely battery and supercapacitor systems, to resist unpredictable disturbances. A control system with three control loops is applied to regulate the speed of the traction motor. The outer speed control loop is a nonlinear state feedback controller with a disturbance observer, which is capable of handling non-linear systems with unpredictable disturbances. The inner voltage and current control loop are precisely tuned PI controllers. Using an adaptive energy management method that varies depending on the state of charge of the source, the total reference current needed to support the load demand is split between two sources. A laboratory prototype system model is generated, and the performance is analyzed under motoring and regenerative braking conditions. For monitoring and controlling the system, the dSPACE DS1202 real-time simulator is employed. The performance of the proposed control system is evaluated and it is found that the settling time to settle within a tolerance band of 1% is 0.75 s.