bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting multi-parametric dynamics of an externally forced oscillator using reservoircomputing and minimal data
Authors: Yadav Manish , Chauhan Swati , Shrimali Manish , Stender Merten
Published: November 2024

Mechanical systems exhibit complex dynamical behavior from harmonic oscillations to chaotic motion. The dynamics undergo qualitative changes due to changes to internal system parameters like stiffness and changes to external forcing. Mapping out complete bifurcation diagrams numerically or experimentally is resource-consuming, or even infeasible. This study uses a data-driven approach to investigate how bifurcations can be learned from a few system response measurements. Particularly, the concept of reservoir computing (RC) is employed. As proof of concept, a minimal training dataset under the resource constraint problem of a Duffing oscillator with harmonic external forcing is provided as training data. Our results indicate that the RC not only learns to represent the system dynamics for the external forcing seen during training, but it also provides qualitatively accurate and robust system response predictions for completely unknown multi-parameter regimes outside the training data. Particularly, while being trained solely on regular period-2 cycle dynamics, the proposed framework correctly predicts higher-order periodic and even chaotic dynamics for out-of-distribution forcing signals.
Robotically assisted mitral valve repair using the butterfly technique in a patient with a narrow chest.
Authors: Tatsuki Suguru , Hashimoto Makoto , Koshima Ryuji
Published: November 2024

Background: Minimally invasive cardiac surgery for management of mitral regurgitation is challenging in patients with narrow chests due to limited thoracic space. The butterfly technique can prevent systolic anterior motion in patients with degenerative mitral regurgitation and redundant posterior leaflets, but it is difficult to perform via minimally invasive cardiac surgery. Few reports have described mitral valve repair using the butterfly technique or in a narrow chest. This case report demonstrates the feasibility and utility of robotically assisted mitral valve repair using the butterfly technique in a patient with a narrow chest, addressing the challenges involved through innovative port insertion and visualization.
Case Presentation: A 70-year-old woman with a narrow chest (58 mm from spine to sternum) presented with shortness of breath on exertion. Transesophageal echocardiography revealed severe mitral regurgitation with posterior leaflet prolapse. Robotically assisted mitral valve repair was performed. Skin incisions were made in the third, fourth, and sixth intercostal spaces on the right anterior axillary line. A port for the atrial retractor was placed slightly medial to the right mid-clavicular line in the fifth intercostal space, inserted more shallowly than usual to achieve mitral valve exposure. The P2 leaflet was resected and reconstructed using the butterfly technique. Mitral annuloplasty was performed with a semirigid partial band. The patient was discharged 6 days postoperatively with excellent valve function. One year later, she remained asymptomatic without obvious mitral regurgitation.
Conclusions: Robotically assisted mitral valve repair using the butterfly technique is feasible in patients with narrow chests. Robotic assistance facilitates mitral valve exposure and manipulation in challenging anatomical conditions through enhanced dexterity and visualization. Careful examination of the mitral valve, accurate resection, and assessment of the repair are key aspects of successful implementation. Further studies with larger sample sizes and longer follow-up periods are needed to confirm the effectiveness and durability of this approach. As robotically assisted surgery becomes more common, its applications to additional complex situations should be further explored.
Machine learning-guided evolution of pyrrolysyl-tRNA synthetase for improved incorporation efficiency of diverse noncanonical amino acids
Authors: Yu Haoran , Zhang Qunfeng , Cheng Jingxi , Ding Haote , Chen Binbin , Jiang Ling , Liu Ke , Ye Shilin , Yang Lirong , Wu Jianping , Xu Gang , Lin Jianping
Published: November 2024

The pyrrolysyl-tRNA synthetase (PylRS)/tRNACUA pair is one of the most widely used systems for the incorporation of noncanonical amino acids (ncAAs) into proteins at specific positions. Although directed evolution of PylRS have enabled over 300 ncAAs to be incorporated into proteins, most of the ncAA-containing proteins are expressed in a limited yield due to low activities of PylRS variants. Here, we applied machine learning (ML) to engineer the tRNA-binding domain of PylRS with a fast Fourier transform-partial least square regression (FFT-PLSR) model and three zero-shot prediction ML models. FFT-PLSR was first applied to explore a sequence space composed of pairwise combinations of 12 single mutations, and the best variant, Com1-IFRS, showed an 11-fold increase in activity compared to IFRS, a PylRS variant. The deep learning models ESM-1v, Mutcompute, and ProRefiner were then used to identify new mutation sites impacting the activity of Com1-IFRS. FFT-PLSR was used again to identify a variant, Com2-IFRS, from a sequence space containing 11520 mutations, which showed a 30-fold increase in activity. Com2-IFRS also enhanced enzyme activity against 12 other ncAAs by up to 3944.8-fold. Transplantation of the evolved mutations into 7 other PylRS-derived synthetases improved yields of proteins containing six types of ncAAs, including derivatives of Phe, Tyr, Trp, Cys, His and Lys, by up to 1149.7-fold. Molecular dynamics simulations revealed that mutations reshaped the hydrogen bond network between tRNA and protein, which increased tRNA binding affinity, shortened the reaction distance between tRNA and ncAA, and even enhanced the dynamics correlation network. This paper offers new PylRS variants that increase the utility of the orthogonal translation system and provide a machine learning framework for identifying optimized multiple-point combinatorial mutations in a vast sequence space.
Genome assembly and population analysis of tetraploid Tylosema esculentum (marama) reveal two district genomes.
Authors: LI JIN , Cullis Christopher
Published: November 2024

Tylosema esculentum (marama bean), is an underutilized orphan legume with potential for domestication as a food crop to improve local food security. Thriving in the desert environments of southern Africa, it offers insights into plant adaptation to extreme conditions. In this study, 21.6 Gb PacBio HiFi data were assembled into a tetraploid genome of 1.24 Gb using Canu, achieving an N50 of 1.28 Mb and over 99% BUSCO completeness. Repeats constituted 27.35% of the genome. k-mer analysis suggested an autotetraploid or ancient allotetraploid genome for marama, with a compact haplotype genome size of 277 Mb. Phylogenetic analysis revealed a close relationship to Bauhinia variegata, diverging approximately 25.14 million years ago (MYA). Whole genome duplication (WGD) analysis indicated an ancient duplication event in marama. Enriched species-specific genes were involved in DNA processes, protein functions, and stress response pathways, highlighting their potential roles in marama’s adaption to diverse environments. The population study identified two distinct clusters, but additional phenotyping is required to assess whether these genomic differences are reflected in biological performance. This is the first high-quality genome assembly of marama, albeit unphased, represents a significant advancement in understanding marama's genomics.
Spatiotemporal Hybrid Asymptotic Framework for Human Motion Prediction
Authors: Li Xiaoshan , Gao Ang , Feng Kaixuan , Zhao Fengda , Jia Zhuolin
Published: November 2024

Skeleton-based human motion prediction involves predicting forthcoming human motion skeleton sequences by analyzing historical human motion skeleton sequences. Through extensive experiments, we found that integrating the methods of temporal asymptotic and spatial asymptotic into a multi-stage model reduces the severity of changes in action sequences during propagation between stages, thereby making it easier to predict future human action sequences and enhancing the accuracy of the multi-stage model's predictions. This paper proposes a spatiotemporal hybrid asymptotic framework that gradually approaches the target ground truth value from both temporal and spatial dimensions. To address the challenge of a single network inadequately capturing all relationships between human joints, we embed inter-joint correlation features into multiple feature extraction spaces during spatial feature extraction. This approach, named the Dynamic Scattering Method, allows for the independent training of graph attention matrices, effectively enhancing the framework's spatial feature extraction capability. We conducted extensive experiments on the Human3.6M, Carnegie Mellon University Motion Capture, and Three-Dimensional Human Pose in the Wild datasets, achieving optimal results.
Examination of Personality Traits and Their Relationship with Self-Control among Nurses Working in Emergency Departments of Hospitals in Kermanshah City
Authors: safavi safura , Jalali Amir , Veisimiankali Mohmmadjavad , Salari Nader , Mahvar Tayebeh
Published: November 2024

Background
Personality traits have a consistent influence on professional and occupational behaviors. Based on these traits, it is possible to predict an individual's specific behaviors in diverse work-related and occupational contexts. Furthermore, personality traits are essential contributing factors in the development of self-control. Therefore, the present study aimed to assess the prevalence of personality traits and their association with self-control among nurses employed in the emergency departments of hospitals in Kermanshah during
Methods
The study was a cross-sectional analytical investigation. The statistical sample comprised 154 nurses employed in the emergency department. Participants were selected using convenience sampling for the study. Data collection was conducted using questionnaires. Upon obtaining informed consent from the participants, the questionnaires were distributed to the study subjects. All participants filled out a demographic form, the Nikmanesh Self-control Questionnaire, and the NEO Five-Factor Inventory (NEO-FFI). The data were analyzed with SPSS software, version 25, utilizing suitable statistical tests.
Results
The research findings revealed a significant relationship between the components of personality traits and self-control among nurses. These personality traits can elucidate the levels of self-control in nurses employed in emergency departments. Furthermore, all sub-scales of self-control, except impulsivity and risk-taking behavior, demonstrated a significant negative correlation with personality traits.
Conclusion
The findings of this study suggest that personality traits significantly influence the self-control of nurses. Notably, stronger personality traits in all dimensions, barring neuroticism, are inversely related to the self-control scores of nurses. Consequently, to improve the performance and job quality of nurses, it is recommended that substantial revisions be implemented in the educational curriculum. Additionally, recruitment and employment processes for nurses should consider cultural factors, personality traits, and individual preferences.
Transposon mediated functional genomic screening for BRAF inhibitor resistance reveals convergent Hippo and MAPK pathway activation events
Authors: Chen Li , Pruteanu-Malinici Iulian , Dastur Anahita , Yin Xunqin , Frederick Dennie , Sadreyev Ruslan , Benes Cyril
Published: November 2024

Genotype-informed anticancer therapies such as BRAF inhibitors can show remarkable clinical efficacy in BRAF-mutant melanoma; however, drug resistance poses a major hurdle to successful cancer treatment. Many resistance events to targeted therapies have been identified, suggesting a complex path to improve therapeutics. Here, we showed the utility of a piggyBac transposon activation mutagenesis screen for the efficient identification of genes that are resistant to BRAF inhibition in melanoma. Although several forward genetic screens performed in the same context have identified a broad range of resistance genes that poorly overlap, an integrative analysis revealed a much smaller functional diversity of resistance mechanisms, including reactivation of the MAPK pathway, PI3K-AKT pathway, and Hippo pathway, suggesting that a relatively small number of therapeutic strategies might overcome resistance manifested by a large gene set. Moreover, we illustrated the pivotal role of the Hippo pathway effector WWTR1 (TAZ) in mediating BRAF inhibition resistance through transcriptional regulation of receptor tyrosine kinases and through interactions with the E3 ubiquitin ligase NEDD4L.
Investigating Africa Decarbonization Strategies: Evaluating the Pathway to Net-Zero by 2050-2060
Authors: Olatunde Dare Ebenezer , Hampo Chima Cyril , Akinlawon Abigail Pelumi , Odobulu Ogechukwu Benedicta , Afanwoubo Bamidele James
Published: November 2024

Climate change poses significant challenges to global stability, particularly for African nations, which, despite contributing minimally to global emissions, face disproportionate climate impacts. This study evaluates the effectiveness of the Long-Term Low Greenhouse Gas Emission Development Strategies (LT-LEDS) submitted by seven African countries, assessing their alignment with the Paris Agreement's goal of achieving net-zero emissions by mid-century. Utilizing a comprehensive methodology that includes both qualitative and quantitative measures, the study examines critical aspects such as strategy formulation, target setting, investment planning, and policy implementation. The findings reveal substantial variability in the quality and clarity of the submitted LT-LEDS, with only a minority of countries establishing clear and actionable goals. Additionally, the analysis highlights significant gaps in the setting of ambitious GHG reduction targets and the integration of socio-economic considerations into decarbonization plans. The study underscores the urgent need for increased commitment, enhanced legal frameworks, and stronger stakeholder engagement to ensure the successful implementation of LT-LEDS across the continent. By addressing these challenges, African nations can make meaningful progress toward sustainable development and contribute more effectively to global climate change mitigation efforts.
Evaluation in silico of the (pBthTX-I)2K Peptide as a SARS-CoV-2 PL proProtease inhibitor
Authors: Faria Marcus V. H , Silva Raphael S. F , Federico Leonardo B , Sant'Anna Carlos M R , Costa Luciano T
Published: November 2024

Context
Since 2019, the COVID-19 pandemic, caused by SARS-CoV-2, has resulted in millions of cases and deaths worldwide. The virus has various essential proteins for its replication and immune evasion, including non-structural protein 3 (nsp3), which encodes the papain-like protease (PLpro). PLpro plays a crucial role in processing the viral polyprotein pp1a and in interfering with the immune system through deubiquitination, making it a strategic target for antiviral development. Inhibiting PLpro is particularly relevant as it can block viral replication and modulate the immune response, interfering with the progression of the infection. In this context, our study investigated the inhibitory potential of a non-toxic dimeric peptide derived from Bothopstoxin-I, (pBthTX-I)2K, as an inhibitor of SARS-CoV-2 PLpro.
Methods
The investigation utilized molecular docking techniques and molecular dynamics (MD) simulations to analyze the interactions of the peptide (pBthTX-I)2K with SARS-CoV-2 PLpro. The structural model of PLpro was constructed based on crystallographic data and validated through homology modeling. Docking analysis was performed using the HPEPDOCK software, revealing a high binding affinity between (pBthTX-I)2K and PLpro, with binding scores of -197.6 kcal.mol-1 for the homology model (MPL) and − 197.0 kcal.mol-1 for the crystallographic model (CPL). The primary interactions between the peptide and PLpro were analyzed, highlighting the formation of hydrogen bonds and hydrophobic interactions with key enzyme residues. To assess the stability of the formed complexes, molecular dynamics simulations were conducted for 300 ns, utilizing the appropriate force field for proteins and peptides, confirming the reliability of the homology model (MPL) in comparison to the crystallographic model (CPL).
Evidence against a cortical module for processing communicative gaze
Authors: Görner Marius , Dicke Peter W , Thier Peter
Published: November 2024

Apart from language, our gaze is arguably the most important means of communication. Where we look lets others know what we are interested in and allows them to join our focus of attention. In several studies our group investigated the neuronal basis of gaze following behavior in humans and macaques and described a gaze following patch (GFP) in the posterior temporal cortex as being of central importance for this function. To our knowledge, this makes the GFP the most promising neurobiological correlate of Simon Baron-Cohen’s eye direction detector (EDD), an integral part of his influential mindreading system. With the latter, Baron-Cohen proposed a set of domain-specific neurocognitive modules implementing a functional framework he suggested to be necessary to establish a Theory of Mind - the attribution of mental states to others. The tenet of domain-specificity requires that the EDD processes only and exclusively eye-like stimuli with their typical contrast and movement properties. In this preregistered fMRI study, we aimed to critically test if the GFP fulfills this criterion. Specifically, we tested if it is equivalent to or different from the visual motion processing areas located in the same part of the brain. Contrary to previous studies, the present results clearly demonstrate that GFP activity is not exclusively correlated with the perception of other people’s gaze direction and thus does not fulfill the criterion of domain-specificity. Furthermore, we show that it cannot be functionally dissociated from the MT+ complex, with which it overlaps anatomically. Given that our experiments captured the full extent of gaze-following behavior and were specifically designed to reveal an EED, our results provide evidence against its existence, and therefore against Baron-Cohen's mindreading model as a set of domain-specific modules.
Synthesis, in-silico biochemical properities and in-vitro antibacterial activity of 3- (benzylimino)-1-((alkyl/cyclo amino) methyl)isoindolin-2-one Derivatives
Authors: Asif Mohammad , Abdulaziz Osama , Almehmadi Mazen , Aljuaid Abdulelah
Published: November 2024

The synthesis of 3-(benzylimino)indolin-2-one or Schiff base (1) The 3-(benzylimino)-1-((alkyl/ cyclo sec. amino)methyl)isoindolin-2-one or Mannich bases (2a-e) derived from Indoline-2,3-dione and benzylimino by Mannich reaction and evaluated its and in-vitro antibacterial activity against B. subtilis, S. aureus, P. aeruginosa and E. coli bacteria by disc diffusion and well diffusion techniques and ciprofloxacin was used as a standard drug. The compound (1) was synthesized from Indoline-2,3-dione and benzylamine. The Mannich bases (2a-e) were synthesized by the reaction of compound (1) with appropriate secondary amines (dimethylamine, diethylamine, piperazine, 4-methyl-piperazine, and morpholine) in the presence of formaldehyde at room temperature. All the synthesized compounds were identified using FTIR, 1HNMR, mass spectroscopy, and elemental analytical studies. The in-vitro anti-bacterial activity, compounds 2a, and 2b exhibited good activity at a dose of 50 and 100 µg/0.1 ml. The synthesized Mannich bases (2a-e) showed varying degrees of antibacterial activity against the tested bacteria. All these synthesized compounds were tested in-silico for determine the biochemical properties and toxic profile. The findings imply that more research is necessary to maximize the efficacy of Mannich bases against pathogenic microbes.
Psychological Status of Mothers with Firstborns Diagnosed of Cerebral Palsy
Authors: Assibey Dennis , Quayson Leticia , Banini Sandra , Agyenkwa Seth Kwame , Mensa-Bonsu Ellen A. , Yarfi Cosmos , Ashigbi Evans Yayra
Published: November 2024

Background:Cerebral palsy (CP) is a non-progressive neurological disorder affecting motor functions, caused by permanent brain damage during the prenatal, perinatal, or early postnatal stages. Although research highlights heightened stress, anxiety, and depression among mothers of children with CP, little is known about these psychological challenges faced by mothers of firstborns diagnosed with the condition. Therefore, the study seeks to evaluate the psychological status of mothers whose firstborns have been diagnosed with Cerebral Palsy in Ghana.
Methodology: A cross-sectional study with proportion sampling technique was used to collect data on the psychological status of 75 mothers whose first child had been diagnosed with CP. The study was conducted at four physiotherapy units in Ghana, namely Korle Bu Teaching Hospital, 37 Military Hospital, Greater Accra Regional Hospital, and Princess Marie Louise Children's Hospital. The data was collected using Depression, Anxiety, and Stress Scale (DASS-42) tool.
Results: The mean age of the participants was 29.61(SD=6.35), with majority 42.7%(n=32) having one child and almost half of the participants 49.3%(n=37) having primary education and 13.3%(n=10) having no education. The study found significant psychological burdens among mothers, with severe levels of depression (mean=22.51 ± 8.648) and stress (mean=26.53 ± 7.987). Notably, 46.7%(n=35) of mothers experienced moderate depression, while 33.3%(n=25) faced severe stress. Anxiety levels were generally normal (mean=5.85 ± 2.481), with 82.7% (n=52) of mothers in the normal range. The results showed strong significant positive correlations between depression and anxiety (r =0.721, p < 0.001), depression and stress (r = 0.930, p < 0.001) and anxiety and stress (r = 0.738, p < 0.001). Significant variations in stress were observed across age groups (χ2 = 19.783, p = 0.028), and a notable correlation was found between the number of children and depression levels (χ2 = 21.77, p = 0.030).
Conclusion: The study emphasizes the importance of supportive psychological interventions that are crucial to address the unique burdens faced by these mothers in the Ghanaian context and also highlights the need for Health Professionals (Physiotherapists) to identify mothers who need psychological interventions and make appropriate referrals.
Clinical Trial Number: Not Applicable.
A widespread porin-cytochrome complex Om(abc)B kickstarts microbial respiration and nanowire formation
Authors: Erwin Joseph , Shen Cong , Saldivar Vanessa , Morales Aldo Salazar , Pentalic Vasilije , Samatey Fadel , Dahl Peter , Gu Yangqi , Yalcin Sibel Ebru , Malvankar Nikhil
Published: November 2024

Microbial respiration via extracellular electron transfer (EET) drives several globally-important environmental processes and has applications in bioenergy, bioremediation, and bioelectronics. Geobacter sulfurreducens produce micrometer-long cytochrome nanowires for long-range (>10 µm) EET, but also require transmembrane porin-cytochrome complexes (PCCs), which can only perform EET on the cell surface. It was unknown why cells performing long-range EET need both PCCs and nanowires. Using Om(abc)B and OmcS as a model PCC and nanowire, respectively, for EET to Fe(III), we show that PCCs and nanowires form sequential, independent EET pathways where PCCs first kickstart EET and provide energy crucial for nanowire synthesis, and then nanowires perform long-range EET. Our model explains why both PCCs and nanowires are necessary. To understand the underlying EET mechanism, we purified native Om(ab)B and OmcB and found high excitonic coupling among hemes. Their midpoint reduction potentials (-182, -167 mV, respectively) are tuned for efficient electron transport. Additionally, OmcB transfers electrons to Fe(III) ~5 times more efficiently than OmcS. Our work suggests that the metabolic trade-off between PCCs and nanowires results from efficient proteome allocation. Notably, PCCs are widespread in environmentally-important bacteria and co-evolved with OmcS nanowires. This previously-undescribed nanowire synthesis strategy could accelerate EET in diverse microbes and environments.
Co-Infection of Human Papillomavirus Genotypes Exacerbates Symptomatic Risks and Transmission Dynamics
Authors: Tang Yue , Abudurusuli Guzainuer , Xu Jingwen , Tu Ruiqin , Hong Shishi , Ye Huiming , Chen Tianmu , Zhou Yulin , Lu Weihong
Published: November 2024

Background
The World Health Organization noted a significant rise in global human papillomavirus (HPV) prevalence among women, from 14\% (2019) to 24\% (2024), highlighting the need to understand the transmission dynamics and public health impact. Existing research focuses on single genotype infections and statistical methods, overlooking the effects of co-infection and multi-genotype interactions.
Methods
Data from HPV nucleic acid tests at two Xiamen hospitals were analyzed using cumulative link models to study symptom severity related to multi-genotype infections. An ordinary differential equation model estimated the reproduction numbers for different infection types.
Results
Increased risk of HPV-related diseases correlates with age (odds ratio, OR for ages 41–60: 37.07; over 60: 115.7). Multi-genotype infections correlate with greater disease severity (OR for two genotypes: 1.11; three genotypes: 1.21). Co-infections, especially involving high-risk genotypes, show higher transmissibility (median R0 for two high-risk genotypes: 6.82).
Conclusions
The findings urge a revision of HPV prevention strategies, focusing on the varying risks across age groups and the enhanced severity and transmissibility of multi-genotype infections. Enhanced surveillance and revised vaccination programs may be crucial to address these challenges.
Integrated Concept Engagement (ICE): An Intervention to Mitigate Neurophobia - A Pilot Study
Authors: Ismail Fatima Y. , Ljubisavljevic Milos R.
Published: November 2024

Background: The inherent complex nature of neuroscience teaching presents a unique challenge in medical education. Novel educational approaches are needed to address neurophobia in both undergraduate and postgraduate medical education. This pilot study investigated the feasibility of a novel educational approach, coined Integrated Concept Engagement (ICE), which merges the framework of the flipped classroom and blended learning to enhance learners' understanding of neuroscience and neurology.
Methods: The ICE model is a learner-centered intervention that utilizes important educational concepts, including the integration of subject-based knowledge via real-world clinical scenarios to foster critical thinking and problem-solving skills, spaced repetition, microlearning, anonymity and real-time feedback via an online interactive platform, within a safe learning environment.
Results: Our preliminary data suggest that the implementation of the ICE model is feasible and has enriched the learning experience by promoting self-identification of knowledge gaps, fostering collaborative learning, and improving the understanding of various neurological topics.
Conclusion: ICE has the potential to be a valuable teaching strategy in medical education. However, further research is needed to explore its scalability and applicability across different educational settings to assess its effectiveness in terms of knowledge retention and clinical reasoning skillsfully.
Fundamentals of occupational health and safety practices outside the workplace among health professionals in Ghana: An assessment of determinants of crash helmet use in the Tamale Teaching Hospital
Authors: Hussein Aziza , Opoku-Mensah Foster Abrampa , Amoafo Isaac Quansah , Saifu Kasim
Published: November 2024

Objectives
This study investigates the determinants of crash helmet use among healthcare professionals at Tamale Teaching Hospital (TTH) in Ghana. Grounded in the Health Belief Model, the Theory of Planned Behavior, and Social Cognitive Theory, the study emphasizes the roles of personal attitudes, perceived risks, and social influences in promoting safety behavior. By integrating these theoretical frameworks, the study highlights how individual beliefs and societal factors can impact the adoption of safety measures.
Methods
Employing a cross-sectional quantitative design, the study aimed to assess helmet usage among healthcare professionals. The target population consisted of approximately 4,000 staff members at TTH. Using the Krejcie and Morgan table, a sample size of 351 participants was determined. Stratified random sampling was implemented to ensure adequate representation across various job roles, including doctors, nurses, and paramedics. The dependent variable in this study was helmet usage, categorized as binary (uses/does not use), while the independent variables included job role, safety training (received/not received), years of experience, and attitudes towards safety. A structured questionnaire, incorporating closed and Likert-scale questions, was utilized to capture demographic data, helmet use habits, and safety attitudes. Statistical analyses were conducted using SPSS version 27, applying logistic regression, chi-square tests, and correlation analysis to assess the relationships between the variables.
Results
The findings indicated that safety training (β = 0.80, p < 0.001) and positive attitudes towards safety (β = 0.005, p = 0.005) significantly influenced helmet use. Medical doctors emerged as the most compliant group, demonstrating a higher likelihood of helmet usage (β = 0.43, p < 0.001). Years of experience exhibited varying effects on helmet compliance, with professionals at different career stages showing distinct usage patterns.
Conclusions
The study underscores the need for targeted interventions aimed at enhancing safety training and cultivating positive safety attitudes to improve helmet compliance among healthcare professionals. The study emphasizes that, to bolster helmet usage, healthcare institutions should expand safety training programs, promote a culture of safety, and develop tailored strategies to address the unique needs of various job roles within the healthcare setting.
Gamma-irradiation Induced Nonconventional Fluorescence Enhancement in Silicone Foams
Authors: Huang Zhendong , Liu Qiang , Jiang Binlian , Dou Ruiyang , Dai Bowen , Huang Wei , Chen Hongbing
Published: November 2024

An unexpected fluorescence enhancement phenomenon in silicone foams induced by gamma-irradiation is reported. These materials contain no traditional luminophores. The fluorescence intensity increases with the absorbed dose (within 1000 Gy). Time-dependent density functional theory (TDDFT) calculations suggest that the mechanism is a crosslinking-enabled emission process, which is enhanced by gamma-irradiation. The fluorescence changes are visible and can even applied to distinguish irradiated silicone foam samples with absorbed doses less than 25 Gy, achieving sensitive visualization of gamma-irradiation damage. The potential applications for radiation damage self-reporting and information encryption are demonstrated. The fluorescence intensity shows similar trends with radiolysis gas products (typical aging parameter) in early-stage irradiation, which can represent radiation-induced crosslinking and radiolysis respectively to reveal the changes of materials after low dose irradiation from two aspects. This work could broaden the application of nonconventional fluorescent materials and help understand the effects of low-dose radiation on silicone materials.
Analysis of the determinants of agricultural income of rural households in a context of climate variability : the case of the community of Toulom in the Far North of Cameroon
Authors: Douswe Benoit , NYORE NYORE
Published: November 2024

Agriculture remains a major source of livelihood in most developing economies and Cameroon in particular, therefore improving agricultural income is one of the most effective means of welfare improvement in these economies. This study focuses on the analysis of the determinants of agricultural income of rural households in a context of climate variability in the locality of Touloum in the Far North of Cameroon. To do this, we used secondary data from the Care International database (2021), with a sample size of 100 households. Multiple regression and statistical analysis shows that 46.6% of household heads have access to inputs. However, 39.6% had a background in agriculture. The study revealss that the agricultural income of households in the locality is between 4000 and 160,000 FCFA, and a majority are those with an agricultural income above 160,000 FCFA. This indicates that a greater proporttion of households in the study area have a high level of agricultural income. However, through the empirical analysis, individuals between the age range of 30 to 55 years, have low levels of education, limited area of cultivation and poor access to agricultural inputs which positively influences the agricultural income of the households in the locality of Toulom. These determinants of income must be integrated into rural agricultural development policies in order to improve the purchasing power of households and their well-being.
Resilient and Secure Control Frameworks for Cyber-Physical Systems in Smart Grids using Anomaly-Graph Fusion Isolation Framework (AG-FIF)
Authors: Alkhorem Azan Hamad , Alghamdi Tami Abdulrahman , Almalki Sultan Ahmed
Published: November 2024

In the realm of addressing the primary unfeasible issue in the cybersecurity in smart grids to ensures protection of critical infrastructure, a novel “Anomaly-Graph Fusion Isolation Framework (AG-FIF)” was introduced. In the existing, unauthorized access to smart meter data due to weak encryption and poor authentication in smart grid systems, while scalability challenges hinder real-time processing. Hence a novel, Integrated Anomaly Detection Ensemble (IADE) was introduced in this approach, offers strong defence against manipulation of scalability problems in smart grid settings with Support Vector Machine (SVM) for classification purpose, Random Forest for integration purpose and Autoencoders for reconstruction purpose. Moreover, the smart grid information networks are being swamp with DDoS attacks due to bad management of resources, while standard methods have a difficulty in detection and relief in dynamic distributed environment. Thus, a novel Graph-Enhanced Isolation Tree Framework (GEITF) was invented, which controlling network resources and lessening the effects of dispersed and dynamic DDoS attacks with Graph Convolutional Networks (GCNs) for modelling purpose, Isolation Forest for detection purpose and Decision trees for classification purpose. The AG-FIF framework delivers 98.55% accuracy, 97.35% F1-Score, low FNR (1.01%), FPR (1.03%), and excels in resource management, robustness, and scalability.
Effect of shell layer thickness on low temperature SCR performance of FeMnOx@TiO2 core-shell catalysts
Authors: Ge Jiachen , Zhang Xinfeng , Miao Jianping , Ge jiaqi , Chen Hongping
Published: November 2024

FeMnOx@TiO2 core-shell catalysts with different shell layer thicknesses were prepared by co-precipitation method to investigate the effect of shell layer thickness on the activity and stability of the catalyst for low-temperature denitrification. It was found that the NOx removal efficiency of FeMnOx@TiO2 with 60% (FM@T60) shell layer content was above 98% between 160 and 320 °C. The physicochemical properties of the catalysts were investigated and analyzed by characterization means such as XRD, BET XPS, H2-TPR. The TiO2 shell layer in FM@T60 effectively mitigated the toxic effect of SO2, provided a large specific surface and a concentrated pore size distribution facilitated the adsorption-desorption reaction of the catalyst. The large number of acidic sites in FM@T60 improved the NH3 adsorption performance. The abundant active components Mn3+, Fe3+ and a high proportion of chemisorbed oxygen of FM@T60 promoted the electron migration and conversion between the core-shell interface, which enhanced the redox capacity of the catalyst. The synergistic interaction between the core and shell of FM@T60 catalyst improved its low-temperature NH3-SCR reaction efficiency and sulfur resistance.
Face Image-based Emotion Recognition using Fractal Dimension and Deep Convolutional Neural Network
Authors: Karnati Mohan , Seal Ayan , Krejcar Ondrej
Published: November 2024

Face images are the primary non-verbal, face-to-face communication method used in criminal detection, depression analysis, mental disease identication, health forecasting, and other applications. As a result, there has been a lot of study on emotion recognition using face images in recent years. However, it remains a big challenge, especially when intra-class variations are high. A novel deep convolutional neural network (DCNN) on textured images is suggested in this work for solving the emotion recognition task. Firstly, the texture of original face images is measured by dierential box-counting-based fractal dimension to obtain low-level features. Secondly, the novel proposed DCNN framework explores facial landmarks as a form of a curve that produces distinct local facets to distinguish two expressions. The suggested DCNN combines features from many scales. This fusion of multi-scale features allows the proposed DCNN to gather more reliable and noise-resistant characteristics from an image's multiple portions. Furthermore, the proposed framework can preserve spatial and structural information and focus on describing details in local regions of the textured face images. Five publicly accessible benchmark databases, namely Extended Cohn-Kanade, Japanese Female Facial Expressions, Real-World Aective Faces, Karolinska Directed Emotional Faces, and Facial Expression Recognition 2013, are considered in this work to compare the proposed method with some state-of-the-art (SOTA) approaches based on four classication evaluation metrics: f1-score, recall, accuracy, and precision. Practical results exemplify that the proposed method defeats some SOTA approaches, proving its eectiveness for vision-based industrial systems such as autonomous driving, virtual reality, medical rehabilitation, etc.
Socio-Demographic and Health Risk Factors Associated with Cardiovascular Health Among Urban Joggers in Dhaka: A Cross- Sectional Study
Authors: Rahman Md. Habibur , Ahmed Mohsin , Shiblee SA , Hassan Mir Khalid , Mozomder Md Iftekhar Mahmud
Published: November 2024

Background: Ischemic heart disease (IHD) poses a significant threat to sustainable growth in the 21st century. Regular exercise does, in fact, reduce the risk of ischemic heart disease.
Objective: The goal of this study is to identify and analyse the differences in Socio-Demographic and Health Risk Factors Associated with Cardiovascular Health Among Urban Joggers in Dhaka.
Methods: A cross-sectional study was conducted with 322 participants who participate in walking activities in the parks of Dhaka on a regular basis. We used a convenience sampling approach to gather data on demographic variables, health risk factors, and a history of ischemic heart disease.
Results: The study population had an average age of 51.13 years, with 82.6% males and 17.4% females. Significant differences were found between genders in terms of education, occupation, economic status, BMI, and health factors. Males had higher rates of smoking and stroke, while females had higher rates of dyslipidemia. Age-wise, seniors had a higher prevalence of hypertension, diabetes, and IHD compared to younger groups. Overall, 15.2% of participants had IHD, with significant associations found between IHD prevalence and age, education, occupation, and BMI.
Conclusion: This study highlights the importance of demographic and health risk factors in understanding the heart health of urban joggers in Dhaka.
CDOM Absorption Characteristics and DOC Concentrations in Remote Sensing Inversion Studies of Karst Plateau Reservoirs
Authors: Kong Jie , Zhou Zhongfa , Xie Rukai , Wang Yanbi , Ding Caixia , Li Rui
Published: November 2024

Colored dissolved organic matter (CDOM), which is a type of dissolved organic matter (DOM) in water bodies with color-carrying optical properties and is also the main component of dissolved organic carbon (DOC), is an important component of optically active substances in water bodies. Remote sensing monitoring of its concentration is scientifically important for understanding the carbon cycle of water bodies and understanding the distribution of organic matter. In this study, two field sampling and experimental analyses were conducted in April and July 2024 in the Pingzhai Reservoir, a karst reservoir in Southwest China, to study the CDOM concentration and absorption spectral characteristics. The inverse model of the CDOM concentration was established on the basis of Sentinel-2B/MSI remote sensing data and the machine learning random forest method, and the inverse model of the DOC concentration was developed by combining the strong correlations between the CDOM and DOC concentrations, after which the water body DOC concentration was estimated. The effects of water quality parameters and meteorological factors on CDOM and DOC concentrations were subsequently explored. The results revealed that (1) the CDOM of the Pingzhai Reservoir could be well inverted on the basis of measured data, Sentinel-2B/MSI remote sensing data and a random forest model; (2) the CDOM of the Pingzhai Reservoir had a good correlation with the DOC, and the accuracy of the inversion model of the DOC was high (R2 = 0.72, MAE = 0.33, RMSE = 0.44); (3) the Pingzhai Reservoir SUVA254 (ratio of the absorption coefficient of the CDOM at a wavelength of 254 nm to the DOC concentration) values were relatively high, and the M values (ratio of the absorption coefficient of the CDOM at wavelengths of 250 nm and 365 nm) were relatively small, which indicated that the CDOM of the Pingzhai Reservoir tended to be input from land-based sources and had a relatively high content of humus; and (4) the results of the redundancy analyses indicated that water quality parameters such as the chlorophyll a (Chl-a), total suspended matter (TSM), turbidity (Tur), and dissolved oxygen (DO) had important effects on the CDOM concentration. This study contributes to the understanding of the changes in CDOM and DOC concentrations in the Pingzhai Reservoir and provides a reference basis for water ecological environmental protection and water resource management.
Benzene-Hexane Separation by Room Temperature Ionic Liquid: A Molecular Dynamics Simulation Study
Authors: Kumar Praveen
Published: November 2024

In this study, benzene extraction from benzene-hexane mixture in room temperature [Emim][NTf2] ionic liquid (IL) has been studied by employing molecular dynamics simulation. We observed that [Emim][NTf2] IL can extract benzene from benzene-hexane mixture efficiently and effectively even if it is present at < 10 wt%. The extraction of benzene from the benzene-hexane mixture is characterized from calculation of distribution coefficient (β) and selectivity (S). An important rational behind the benzene extraction by IL is observed that benzene-cation interactions are stronger than benzene-anion interactions, which is also supported by the DFT calculations.
Environmental awareness and sustainable behaviors of healthcare professionals: validation of the Healthcare Environmental Awareness Tool (HEAT)
Authors: Olivieri Romina Patricia. , Álvarez-Nieto Carmen , López-Medina Isabel María
Published: November 2024

Background Climate change poses a significant challenge to public health, requiring healthcare personnel to recognize their responsibility and adopt environmentally responsible behaviors. The aim of this study was to conduct a cultural adaptation and psychometric validation of the Healthcare Environmental Awareness Tool (HEAT) to assess the level of environmental awareness, sustainable behaviors, and their relationship to healthcare professionals' health in Spain.Methods A cross-sectional observational study was conducted to translate, adapt, and validate the HEAT questionnaire for the Spanish context. The sample comprised 450 healthcare professionals from 9 Spanish hospitals. The HEAT questionnaire was validated using item response theory, specifically through the polytomous Rasch model. It is organized into three main scales: HAS (Healthcare Awareness Scale), HPEB (Healthcare Professional Ecological Behavior Scale), and PEB (Personal Ecological Behavior Scale). Each scale includes two dimensions per item derived from paired questions. The first dimension addresses the specific topic of the scale, while the second focuses on the respondent’s belief about how environmental impacts affect human health.Results The HEAT questionnaire, initially comprising 62 items, was refined to a final version of 50 items. This version demonstrated robust reliability and validity, with satisfactory fit for both items and persons. Reliability indices were: HAS-1 (0.76 for persons, 0.98 for items), HAS-2 (0.82, 0.96), HPEB-1 (0.77, 0.99), HPEB-2 (0.79, 0.94), PEB-1 (0.83, 0.99), and PEB-2 (0.87, 0.97). Internal consistency, measured using Cronbach’s α and McDonald’s ω, yielded strong results: HAS-1 (0.79), HAS-2 (0.90), HPEB-1 (0.75), HPEB-2 (0.87), PEB-1 (0.81), and PEB-2 (0.92). No significant group differences were observed, confirming the instrument’s fairness in differential item analysis.Conclusions The HEAT questionnaire is a useful and accurate tool for measuring environmental awareness, sustainable behaviors, and perceived health impacts among healthcare professionals.
Transient protein structure guides surface diffusion pathways for electron transport in membrane supercomplexes
Authors: Singharoy Abhishek
Published: November 2024

The biological significance of protein supercomplexes have remained contentious, particularly how they tune the shuttling of charge-carrier redox proteins across cell membranes during biological energy conversion. We employ multiscale modeling and single particle cryo-electron microscopy (cryo-EM) to determine the mechanisms of diffusive electron transfer in mitochondrial supercomplexes, composed of respiratory complexes III and IV (CIII and CIV). Using a combination of bioinformatic and entropy maximization tools, we model an ensemble of structures representing the conformational space of CIII’s disordered QCR6 ‘hinge’ within the yeast CIII2CIV2 supercomplex. Molecular and Brownian Dynamics simulations of the entire supercomplex reveal a mechanism for electrostatic coupling between these negatively charged hinge conformations, and binding and directional diffusion of the redox proteins on the mitochondrial membrane, which is simulated over the millisecond timescale. We find that the disorder actually reduces the diffusive barrier to charge shuttling within the confined supercomplex. Anionic lipids reinforce this conformationally-coupled recognition of the supercomplex by retaining a pool of the redox proteins in the vicinity of the membrane when the hinges are of a critical length. Cryo-EM models reveal a large-scale rearrangement of the Δ QCR6 supercomplex, which retains a surprisingly robust electrostatic environment for recognition of the redox protein despite compromise in the supercomplex’s negative charge, still enabling a surface-mediated electron transfer in this CIII2CIV2 variant. Altogether, the evolutionary need of confining electron carriers on the surface of bioenergetic membranes is found to give rise to a refolding-guided diffusion model of the redox proteins, which improves the energy conversion efficiency within the supercomplex by nearly 30%.