bluuebunny/crossref_metadata_2025 huggingface dataset:
Data-Driven Optimization of Photocatalytic Water Splitting for Hydrogen Production
Authors: Cit Abi , Ahsun Abbas
Published: October 2024

Photocatalytic water splitting offers a promising route for sustainable hydrogen production, but its efficiency remains limited by complex interactions between material properties, operating conditions, and reaction mechanisms. This study presents a data-driven approach to optimize photocatalytic water splitting for enhanced hydrogen evolution. By integrating experimental data, density functional theory calculations, and machine learning algorithms, we identified key descriptors governing photocatalyst performance. A predictive model was developed to screen optimal catalyst compositions, morphologies, and operating conditions, leading to a significant increase in hydrogen production rates. The results demonstrate the potential of data-driven optimization to accelerate the discovery of high-performance photocatalysts, paving the way for scalable and efficient solar-driven hydrogen production.
Release of HMGB1 from Human-Derived Cancer and Normal Cells by Internal Targeted Radiotherapy with 131Iodine-Labeled m-Iodobenzylguanidine
Authors: Sato Kakeru , Handa Ririka , Yao Jianwei , Hirayama Yuka , Hamada Yuna , Yamagata Jundai , Watanabe Taiga , Mizutani Asuka , Kobayashi Masato , Nishii Ryuichi , Kawai Keiichi
Published: October 2024

The rare abscopal effect during radiotherapy is thought to be caused by the release of immune-stimulated damage-associated molecular patterns, such as high mobility group box-1 protein (HMGB1), from cancer cells. Although external irradiation of cancer cells increases HMGB1 release, it is not clear if HMGB1 is released from cells after administering 131I-labeled m-iodobenzylguanidine (131I-MIBG) as an internal targeted radiotherapeutic agent. This study aimed to determine if HMGB1 is released from human-derived cancer and normal cells after administering 131I-MIBG. Methods: Extracellular lactate dehydrogenase (LDH) and HMGB1 released from H441 (human-derived lung adenocarcinoma cell line) and HaCaT (human keratinocyte cell line) 1 day after 2- and 10-Gy X-ray irradiation were measured. Accumulations of 131I-MIBG in SH-SY5Y (human-derived neuroblastoma cell line) and HaCaT were measured 60 min after administering 131I-MIBG (0.37, 1.85, 3.7 MBq/well). Extracellular LDH and HMGB1 released from SH-SY5Y and HaCaT 1 day after administering 131I-MIBG were also measured. Results: The extracellular LDH and HMGB1 released from H441 after 10-Gy X-ray irradiation were significantly increased. However, the extracellular LDH and HMGB1 released from HaCaT after 2-Gy and 10-Gy X-ray irradiation were not increased. After administering 1.85 MBq and 3.7 MBq 131I-MIBG, the extracellular LDH and HMGB1 released from SH-SY5Y were both significantly increased, but only the extracellular LDH released from HaCaT was significantly increased. Conclusions: HMGB1 was released from neuroblastomas but not from normal cells after 131I-MIBG administration, suggesting that a combination of 131I-MIBG and immunotherapy may be feasible.
Plasma Functional Proteins: A Sustainable Solution to Reduce Postweaning Diarrhea Without Compromising Piglet Growth
Authors: Polo Javier , Shen Yanbin , Blavi Laia , Sobrevia Laia , Tibble Simon , Crenshaw Joe , Tous Núria , Torrallardona David
Published: October 2024

These studies address the challenge of post-weaning diarrhea (PWD) in piglets, a common and costly health issue exacerbated by the recent European Union ban on therapeutic zinc oxide. The research evaluates whether spray-dried plasma (SDP), a sustainable and highly digestible protein source, can mitigate PWD without compromising piglet growth. Two concurrent studies were conducted on farms using either low-protein or normal-protein diets, with SDP included in varying phases of early piglet feeding. Diets with SDP improved growth rates and feed intake during critical post-weaning phases, particularly under normal protein levels and enhanced feed efficiency and reduced medication needs, indicating its potential to support piglet health while reducing dependency on pharmaceutical interventions. In conclusion, SDP in post-weaning diets helps balance growth and health, even when using low protein diets and offers a viable and sustainable alternative to traditional methods for managing PWD. This work highlights the role of SDP in promoting a circular economy by upcycling animal by-products and aligning with environmentally friendly farming practices.
Obsessive-Compulsive Disorder with Religious Focus: A Observational Study
Authors: Ayoub Wissam Al Rida , Dib El Jalbout Jana , Maalouf Nancy , Ayache Samar S , Chalah Moussa A. , Abdel Rassoul Ronza
Published: October 2024

(1) Background: Obsessive-Compulsive Disorder (OCD) is a psychiatric disorder with poorly detailed subtypes/dimensions, such as religious OCD (ROCD). To date, little is known about ROCD characteristics. This work aimed to describe the sociodemographic and clinical characteristics, as well as the religiosity and spirituality among Lebanese Muslim citizens diagnosed with OCD and exhibiting religious symptoms. (2) Methods: Outpatients were enrolled according to the following inclusion criteria: 18 years of age or above, diagnosis of OCD, presence of religious symptoms, and ability to read and understand the questionnaire. Exclusion criteria were as follows: other psychiatric disorders, and cognitive or physical impairments preventing participation. They filled in a questionnaire including the 25-item Arabic Scale of Obsessions and Compulsions (10 questions addressing obsessions, 10 questions addressing compulsions and five filler items, all of which rated on a 4–point Likert scale; higher total scores indicating increasing severity), the 26-item Spiritual Involvement and Beliefs Scale (rated on a 5-point Likert scale; higher scores indicating higher spirituality), and questions assessing the sociodemographic, clinical, and religiosity variables. (3) Results: Fifty adults (62% females, 52% aged between 18-29 years) completed the study. They had mild (26%), moderate (48%) and severe (26%) OCD symptoms. The majority had a family history of psychiatric disorders (48% OCD) and reported traumatic life events (58%). The majority attended religious school at least at one point in their life and described moderate to very high degree of self-religiosity and parental religiosity. Group comparisons (patients with mild vs. moderate vs. severe OCD symptoms) showed significant differences with regards to family history of psychiatric disorders (p=0.043), frequency of self-questioning if praying correctly (p=0.005), higher rating of partial ablution repetition (p=0.006), and frequency of partial ablution repetitions (p=0.041). No significant groups differences were noted with regards to sociodemographic or spirituality outcomes (4) Conclusion: Some religiosity variables (thoughts and practices) seem to be associated with OCD severity. The current results support the need for further research pertaining to ROCD.
Data-driven Maturity Level Evaluation for Cardiomyocytes derived from Human Pluripotent Stem Cells (Invited Paper)
Authors: Hong Yan , Huang Xueqing , Li Fang , Huang Siqi , Weng Qibiao , Fraidenraich Diego , Voiculescu Ioana
Published: October 2024

Cardiovascular diseases are one of the leading causes of death in the world. The capability to direct the differentiation of human pluripotent stem cells (hPSCs) into functional cardiomyocytes (CMs) provides excellent opportunities for disease modeling and novel cell-based cardiac therapies. However, current hPSC-derived cardiomyocytes (hPSC-CMs) remain largely immature, limiting experimental and clinical uses. New insights into the maturation process of adult-like hPSC-CMs are critical. In this paper, we developed a data-driven pipeline to quantify cell maturity, based on gene expression input spanning different stages of cardiac development. First, we determined that culture time can serve as a proxy of the maturity level of hPSC-CMs. Second, we selected key heart-related genes whose expression varies with culture time, based on machine learning algorithms that are applied to accurately predict culture time. Our results demonstrate that the average discrepancy between the predicted culture time and the observed culture time can be reduced to 4.461 days. Furthermore, Gene CASQ2 (Calsequestrin 2), whose protein plays a role in the storage and transportation of calcium ions, has been identified as the most important cardiac gene that correlates with the culture duration.
Evaluating and Reforming India’s Educational System: Challenges and Solutions
Authors: satapathy Pradipta Kumar , Dash Bijayani , Satpathy Anshuman
Published: October 2024

The Indian educational system grapples with deep-rooted structural and systemic challenges that have hindered equitable access to quality education across all levels. Central issues include outdated curricula that fail to equip students with contemporary skills, significant socio-economic disparities limiting access and outcomes, and inadequate teacher training alongside deficient infrastructure, particularly in rural and economically disadvantaged areas. These challenges contribute to unequal educational opportunities and outcomes, with a stark divide between urban and rural, and between private and public institutions. This review delves into these pervasive issues, analyzing how they manifest from primary through tertiary education. In primary education, the focus often remains on rote learning, overlooking critical thinking and problem-solving skills. At the secondary and tertiary levels, curriculum relevance remains a concern, as courses frequently do not align with modern industry demands or technological advancements, creating a skills gap among graduates. Addressing these challenges, this review proposes a series of reforms aimed at building a more inclusive and effective system. Key reforms include curriculum modernization to incorporate skills for the 21st century, integrating digital learning tools to expand access and facilitate adaptive learning, and comprehensive teacher development programs that emphasize continuous professional growth. Together, these initiatives aim to create an educational environment that is not only inclusive but also adaptive to the evolving demands of a globalized world, thereby enhancing the quality and reach of education across India.
A PMBM Forward-Backward Smoother for Multiple Extended Targets
Authors: Xie Xingxiang , Tian Kai , Song Zhumei , Li Kening
Published: October 2024

This paper presents a Poisson multi-Bernoulli mixture (PMBM) forward-backward smoother for multiple extended target detection and tracking in the random finite sets (RFS) framework. The proposed method consists of forward filtering, achieved by the PMBM filter recursion, followed by backward smoothing, achieved by a parametric updated posterior PMBM density. The performance of the proposed method is evaluated in a simulation study.
Job stress, working capacity, professional performance and safety of shift workers at forest harvesting in the North
Authors: Korneeva Yana , Shadrina Nina , Simonova Natalia , Trofimova Anna
Published: October 2024

The study describes the features of manifestations and interrelationships of job stress, working capacity, professional performance and safety in loggers with shift work organization in the North. The study involved 402 loggers. The research methods include questionnaires and psychophysio-logical diagnostics of stress and working capacity, as well as questionnaires on the professional performance and safety of workers. The following statistical methods were used: correlation, mul-tivariate dispersion and multi-regression stepwise analysis. It was found that the severity of stress, speed, accuracy and operator working capacity, as well as well-being, activity and mood in logging equipment operators, timber truck drivers and maintenance specialists statistically differ signifi-cantly. Higher professional stress and more frequent decrease in professional performance are characteristic of truck drivers. Psychological and psychophysiological job stress and working ca-pacity parameters are associated with professional performance parameters of loggers. According to the results of a number of multi-regression analyses, reduced professional performance markers of loggers include the index of stress, satiety, monotony and fatigue, vegetative balance and stress (method of M. Luscher and coefficients of G.A. Aminev), operator working capacity and reaction speed (CVMR).
NAILS: Normalized Artificial Intelligence Labeling Sensor for Self-care Health
Authors: Tenze Livio , Canessa Enrique
Published: October 2024

Visual examination of nails can reflect the human health status. Diseases such as nutritive imbalances and skin diseases can be identified by looking the colors around the plate part of the nails. We present the AI-based NAILS method to detect fingernails through segmentation and labeling. We built a generalized model to identify single fingers, their fingernail plates and retrieve their color data. A pre-trained deep learning Neural Network algorithm containing different images of fingernails as reference frames is used to identify different fingernails edges and the color areas around them in real-time. The novel aspect of our NAILS sensor model is that it allows to analyze –via a GUI and the use of a HD webcam, the tiniest dynamical signals from changes in fingernail colors. This feature could be used to self-extract primary signs of diseases in humans.
Antimicrobial Resistance in Lactococcus spp. Isolated from Native Brazilian Fish Species: A Growing Challenge for Aquaculture
Authors: Rosário Angélica Emanuely Costa do , Barbanti Angelo Carlo Chaparro , Matos Helena Caldeira , Maia Cynthia Rafaela Monteiro da Silva , Trindade Júlia Miranda , Nogueira Luiz Fagner Ferreira , Pilarski Fabiana , Gallani Silvia Umeda , Leal Carlos Augusto Gomes , Figueiredo Henrique César Pereira , Tavares Guilherme Campos
Published: October 2024

Lactococcus spp. has emerged as a pathogen that is affecting global aquaculture, with L. garvieae, L. petauri, and L. formosensis causing piscine lactococcosis. While antimicrobials are commonly used to treat diseases in aquaculture, reports of antimicrobial resistance in fish isolates are increasing. However, little is known about the susceptibility patterns of Lactococcus spp. strains isolated from native fish species in Brazil. This study aimed to assess the antimicrobial susceptibility of these strains and establish a provisional epidemiological cut-off value for L. garvieae using the normalized resistance interpretation approach. A total of 47 isolates were tested: 17 L. garvieae, 24 L. petauri, and 6 L. formosensis. The isolates were classified as wild-type or non-wild-type (NWT) based on inhibition zone diameters. Isolates classified as NWT for three or more antimicrobial classes were considered multidrug-resistant, and the multiple antibiotic resistance (MAR) index was calculated. The results revealed heterogeneity in antimicrobial resistance profiles, with higher resistance to trimethoprim/sulfamethoxazole and norfloxacin. Resistance to other antimicrobials, including florfenicol and oxytetracycline (approved for use in Brazil), varied according to the bacterial species. Lactococcus petauri (87.5%) and L. formosensis (66.7%) showed the highest multidrug resistance, compared to L. garvieae (11.7%), along with higher MAR index values. These findings suggest that multidrug-resistant strains could pose future challenges in the production of native species, underscoring the need for ongoing monitoring of antimicrobial resistance and responsible use of antimicrobials in aquaculture.
Computational Fluid Dynamics-Driven Aerodynamic Enhancements for Miniature Car Design and Engineering

Authors: Chaturvedi Shlaghya , Bhatla Ryan , Mullick Aryash , Chandwani Manit
Published: October 2024

F1 in SchoolsTM is a STEM-focused educational program engaging students through the design and construction of a miniature F1 car. Developed with engineering expertise and endorsed by F1, it enhances STEM learning through immersive experiences. This study aims to optimize race car performance on a straight track by focusing on the aerodynamic efficiency of the front wing, car body, and sidepods. Key objectives include: minimizing drag coefficient and drag force; managing weight distribution; optimizing airflow. Using AutoCAD, each component was precisely designed, and Computational Fluid Dynamics tools were used to simulate and evaluate the car's aerodynamic performance. The final iteration of our F1 in SchoolsTM car focuses on optimizing overall airflow rather than relying on sharp aerodynamic components. This reduces turbulence, drag, and improves performance. Key features include a front wing redirecting airflow around the tires and a low-drag, backward-swept rear wing, which enhances aerodynamic efficiency.
Energy Saving in Wireless Sensor Networks via LEACH-based Energy Efficient Routing Protocols
Authors: Rountos Dimitris , Siamantas Georgios , Kandris Dionisis
Published: October 2024

Wireless Sensor Networks are at the center of scientific interest thanks to the ever growing range of their applications. The main weakness of Wireless Sensor Networks is the restricted lifetime of their sensor nodes due to limited energy capacity. The extension of the lifespan of sensor nodes is pursued in various ways. One of them, is the usage of protocols that achieve energy efficient routing. LEACH is one of the pioneering protocols of this type and has numerous descendants. This research article focuses on energy efficient routing protocols that are based on LEACH. Specifically, a study of LEACH along with many of its successors is provided. In addition, a novel protocol of this kind, named T-LEACHSAS is proposed. This protocol is actually an extension of T-LEACH, which is one of the most well-known descending protocols of LEACH. The performance of T-LEACHSAS is compared against that of T-LEACH via simulation tests that validate the protocols' strengths and weaknesses in various scenarios. Finally, concluding remarks are indicated.
SIT-Conversion: Transformer Spiking Neural Networks with Spiking-Softmax Function
Authors: Li Xuhang , Shen Qianzi , Wang Haitao , Wang Zijian
Published: October 2024

Studies on integrating Spiking Neural Networks (SNNs) with the Transformer architecture holds promise for enabling models to achieve ultra-low energy consumption while possessing the performance of the Transformer architecture. Currently, studies on ANN-to-SNN conversion of integrating Spiking Neural Networks (SNNs) with the Transformer architecture mainly focuses on simple activation functions in MLPs, and has not yet addressed the mismatch between the Softmax activation function in the self-attention mechanism and the computation rules of SNNs. Consequently, the ANN-to-SNN conversion efforts have consistently failed to make the Transformer architecture directly applicable to SNNs. To address this challenge, we propose the Spiking-Softmax method, which integrates Spiking Exponential Neuron (SI-exp) and Spiking Collaboration Normalized Neuron (SI-norm). The Spiking-Softmax method accurately simulates the Softmax activation function with only 12 time steps. Building upon this, we propose the Spike Integrated Transformer conversion (SIT-conversion) method, which enables the conversion of the Transformer architecture to SNNs. The SNNs generated by the SIT-conversion of Transformer models of various sizes achieve accuracy nearly identical to their ANNs counterparts, achieving nearly lossless and ultra-low-latency ANN-to-SNN conversion. This work represents the first implementation of simulating the Softmax activation function and fully converting the Transformer architecture into SNNs through spike firing.
Notes on Cooperstein Ovoids in Finite Geometries of Type E_{6,1}(q)
Authors: Van Maldeghem Hendrik
Published: October 2024

A Cooperstein ovoid is a set of q^8+q^4+1 pairwise non-collinear points in the Lie incidence geometry E_{6,1}(q). They were introduced by Cooperstein twenty-six years ago motivated by the fact that possible non-existence of them would imply non-existence of ovoids in hyperbolic quadrics of rank 5. Since then, no progress has been made on their existence question. We prove that Cooperstein ovoids do not exist under some natural additional conditions. In particular, Cooperstein ovoids intersecting every symplecton of E_{6,1}(q) do not exists, Cooperstein ovoids which are the fixed points of a collineation do not exist, and Cooperstein ovoids which are the absolute points of a polarity of E_{6,1}(q) do not exist.
Ethical Decision-Making in Artificial Intelligence: A Logic
Programming Approach
Authors: Machado José , Sousa Regina , Peixoto Hugo , Abelha António
Published: October 2024

This article proposes a framework for integrating ethical reasoning into AI systems through Continuous Logic Programming (CLP), emphasizing the improvement of transparency and accountability in automated decision-making. The study highlights requirements for AI that respects to human values and societal norms by examining concerns such as algorithmic bias, data privacy, and ethical dilemmas in fields like healthcare and autonomous systems. The proposed CLP-based methodology offers a systematic, elucidative framework for ethical decision-making, allowing AI systems to balance operational efficiency with ethical principles. Important contributions include strategies for the integration of ethical frameworks, stakeholder engagement, and transparency, as well as discussion on Artificial Moral Agents and their function in addressing ethical dilemmas in AI. The paper presents practical examples that illustrate the application of CLP in ethical reasoning, highlighting its ability to bring together AI performance with responsible AI practices.
The Impact of Sustainable Policies on Subjective Well-Being in a Developing Nation: The Case of Ecuador
Authors: Pacheco-Jaramillo W Alejandro , Zaldumbide David
Published: October 2024

Objective:
This study explores the impact of public policies that promote social equity and rights to nature on subjective well-being (SWB). The focus is on how sustainability policies, particularly on environmental protection and poverty reduction, have influenced life satisfaction in Ecuador.
Design/methodology/approach:
The research uses ordinal logistic regression models to analyze data from the National Survey of Employment, Unemployment and Underemployment of Ecuador. Life satisfaction is the dependent variable, while independent variables include income, education, job satisfaction, concern for the environment, and regional differences.
Findings:
The results indicate that the implementation of public social investment policies increases life satisfaction,
particularly in regions such as the Coast. After the implementation of the policy, income, higher education, job satisfaction, and concern for the environment were associated with higher levels of subjective well-being. However, disparities persist, with lower life satisfaction among indigenous groups, women, the elderly, and those living in poverty.
Originality/value:
This study provides valuable insights into the relationship between sustainable policies and subjective well-being, highlighting Ecuador's unique constitutional framework. It offers lessons for other developing nations seeking to balance social equity, economic growth, and environmental sustainability in pursuit of improving overall quality of life.
Breast Cancer Analysis Using Deep Learning Techniques a Survey
Authors: s koushalya , s Dr  Baulkani
Published: October 2024

Bosom disease remains a main source of death among women around the world. Early identification is significant for further developing endurance rates, accordingly making effective indicative strategies fundamental. This undertaking the malignant growth discovery utilizing mammography images (low dose x-ray), utilizing profound learning methods to robotize conclusions and upgrade exactness. The framework's center includes preprocessing the mammogram images, separating highlights, and arranging them utilizing Convolutional neural networks (CNNs) and other high-level profound learning models.
Neuroprotective Effects of Functionalized Hydrophilic Carbon Clusters: Targeted 1 Therapy of Traumatic Brain Injury in an Open Blast Rat Model
Authors: Padmanabhan Parasuraman , Lu JIa , Ng Kian Chye , Srinivasan Dinesh Kumar , Sundramurthy Kumar , Nilewski Lizanne G. , Sikkema William K. A. , Tour James M. , Kent Thomas A. , Gulyás Balázs , Carlstedt-Duke Jan
Published: October 2024

Traumatic brain injury (TBI) causes multiple cerebrovascular disruptions and oxidative stress, resulting in pathophysiological mechanisms. These are often accompanied by serious impairment in cerebral blood flow autoregulation, as well as neuronal and glial degeneration. Most currently available early antioxidant therapies lack sufficient efficacy. However, the application of a newly developed class of biologically compatible carbon-based nanoclusters, namely poly-ethylene-glycol-functionalized hydrophilic carbon clusters (PEG-HCCs), mitigate secondary injury after a TBI in early studies. In the present pilot study, we explore the efficacy of PEG-HCCs in an open blast rat model of TBI. Here we report on the neuroprotective efficacy of PEG-HCCs.
Sensory Health and Universal Health Coverage in Canada
Authors: Asheber Hanna , Minhas Renu , Hatolkar Ved , Jaiswal Atul , Wittich Walter
Published: October 2024

Background/Objectives: The World Federation of the Deafblind Global Report 2023 reports that many countries do not have a comprehensive identification, assessment, and referral system for persons with deafblindness, a combination of hearing and vision loss, across all age groups and geographic regions. The scan seeks to inform researchers, policymakers, and community-based organizations about the status of and gaps in sensory healthcare initiatives in Canada, with intent to raise awareness to enhance integration and coordination of eye and ear care services. Methods: We conducted an environmental scan of Canada’s healthcare system and current public health policies addressing vision and hearing care in Canada at federal and provincial levels. The scan was conducted using published literature searches from five scientific databases – Embase, Medline, PsycINFO, PubMed and CINAHL, in combination with the grey literature review of federal, provincial, and territorial government and non-profit organizations websites during April-October 2022. Out of 1257 articles screened, 82 studies included that met the inclusion/exclusion criteria. 13 reports were included in the grey literature search. Results: Thematic findings indicate stigma and discrimination towards individuals with disabilities and marginalized groups, including hearing, vision, or dual sensory loss, persist. Barriers to vision and hearing healthcare access include inadequate policies, underinvestment in vision and/or hearing services, limited collaboration and coordinated services between hearing and vision services, discrepancies in insurance coverages, and lack of health system support. Conclusions: This scan demonstrates the persistent barriers to vision and/or hearing services present in Canada, stemming from inadequate policy and limited-service coordination. Future work to address gaps, evaluate public education, and develop integrated sensory health care initiatives to enhance coordinate eye and ear care services as recommended in WHO Report on Hearing and Vision is imperative.
Dry Wipes for Hygiene in Hospitalized Patients: Economic and Environmental Impact, and Patient and Professional Satisfaction
Authors: Castellà Laia , Ricou Laura , Calderon Colldeforn Eduardo , López Seguí Francesc , Reina Sarrió Dina , Pons Calsapeu Arnau , Casas Irma , Subirana Milian Lluís , Giménez Montserrat , Sopena Nieves , Perpiñan Grogues Marina , Sanz Escudero Yolanda , Barberà Plà Angels , Estr Oriol , García Quesada Maria José
Published: October 2024

Aims: To compare traditional versus dry wipes hygiene in hospitalized, bedridden patients with regard to economic and environmental impact and patient and professional satisfaction. Background: Evidence shows that dry hygiene with disposable wipes can reduce the risk of infection compared to traditional hygiene with soap and water. However, there is a need to compare the costs and environmental impact (waste) between the two methods. Design: Environmental impact and patient and user satisfaction were assessed through an ad hoc survey and cost minimization analysis in accordance with the Consolidated Health Economic Evaluation Reporting Standards. Methods: The environmental impact and costs associated with traditional versus dry hygiene were compared in an observational analysis. A single-center, randomized controlled trial was performed in a tertiary hospital to assess patient and professional satisfaction in patients with a urinary catheter recovering from heart surgery between January 2019 and February 2020. Results: Direct hygiene costs were similar using traditional (€15.82) and dry (€14.35) methods. However, the analysis of indirect costs, including those related to the probability of contracting catheter-associated urinary tract infections, showed that the total cost per hygiene session was €1345 higher with the traditional method. When using a high-efficiency energy system from a guaranteed renewable source, dry hygiene does not lead to a higher environmental impact (220.07 g CO2 traditional vs. 215.17g CO2 dry). However, emissions from conventional energy systems are 840.14 g CO2 higher when using traditional hygiene. Both patients and professionals express greater satisfaction with the dry method. Conclusion: Dry hygiene is not inferior to traditional hygiene in terms of satisfaction, and it can provide environmental benefits at a significantly lower cost. Implications for the profession and/or patient care: This study provides evidence supporting the introduction of the dry hygiene method, with is associated with higher user and professional satisfaction, lower economic cost, and similar or lower environmental impact compared to soap and water.
Simulating Fractional Stride Decrease in Binary Artificial Neural Networks for Autonomous Spacecraft Systems Using Exponential and Logarithmic Decay: A Comparative Experiment in Energy-Efficient ANN Design
Authors: Lancelot Jonathan Fitzgerald
Published: October 2024

This paper takes a novel approach to simulating fractional stride decreases in binary artificial neural networks (ANNs), addressing the limitations of fixed integer strides typically used in traditional convolutional neural networks (CNNs). By introducing a dynamic stride adjustment mechanism that reduces stride over time using either exponential or logarithmic decay functions, the network can simulate fractional strides, enabling the capture of increasingly fine-grained spatial details at deeper layers. This method improves output resolution, feature extraction without increasing network complexity, and possible solutions for binary ANN architectures where computational efficiency is critical. Using synthetic data, we analyze how both decay functions impact output resolution in a comparative experiment. Exponential decay produces a rapid initial stride decrease, leading to early significant resolution gains, while logarithmic decay offers a more gradual and controlled resolution increase. Both methods are enhanced by an attention mechanism that selectively emphasizes important regions in feature maps, improving spatial feature extraction efficiency. Our findings demonstrate that dynamic, asymptotic stride adjustment provides an effective method for simulating fractional strides in binary ANNs, with potential applications in areas such as object detection, segmentation, super-resolution, and autonomous systems, including spacecraft navigation and hazard detection. We also examine the trade-offs between the two decay methods in terms of resolution growth and computational overhead, contributing to ongoing research in adaptive ANN architectures and binary neural network design.
Path Planning for Robot Combined with Zero-Shot and Hierarchical Reinforcement Learning in Inexperienced Environments
Authors: Mei Liwei , Xu Pengjie
Published: October 2024

Path planning for robots based on reinforcement learning encounters challenges in integrating semantic information about environments into the training process. In those unseen or complex environmental information, agents often perform sub-optimally and require more training time. In response to these challenges, this manuscript pioneers a framework integrating zero-shot learning combined with hierarchical reinforcement learning to enhance agent decision-making in complex environments. Zero-shot learning enables agents to infer correct actions for previously unseen objects or situations based on learned semantic associations. Subsequently, the path planning component utilizes hierarchical reinforcement learning with adaptive replay buffer, directed by the insights gained from zero-shot learning, to make decisions effectively. Two parts are trained separately, so zero-shot learning is available in different and unseen environments. Through simulation experiments, the proposed method proves that this structure can make full use of environmental information to generalize across unseen environments and plan collision-free paths.
Effects of Various Greenhouse Treatments on Plant Growth and Flowering Characteristics of Oncidesa Cultivar
Authors: Chang Chia-Man , Lin Kuan-Hung , Huang Meng-Yuan , Chen Chung-I , Huang Wen-Hung , Wang Ching-Wen
Published: October 2024

The aim of this study was to evaluate the growth and flowering characteristics of three Oncidesa cultivars under four distinct canopy treatments in a greenhouse environment. The control canopy treatment (canopy D) involved covering the greenhouse with black shade nets to reduce natural light penetration. Canopy B included black shade nets in combination with a transparent plastic screen on the sides to further modify light conditions. Additionally, two other treatments were applied: black shade nets with (canopy A) or without (canopy C) plastic sheeting, supplemented with daily lighting from high-pressure sodium lamps. Ten horticultural traits were measured to assess the impact of these canopy treatments on different genotypes at various growth stages. The results showed that canopy treatments significantly affected all measured traits of the Oncidesa cultivars, except for leaf width. Apollo plants treated under canopy A exhibited longer and thicker pseudobulbs, wider leaves, higher chlorophyll content, and a greater number of branches and florets compared to Honey Angel and Golden Star. Plants under canopy C showed superior growth traits across all cultivars, while those under canopies A and D exhibited better flowering quality. These findings suggest that different canopy treatments had varying effects on the growth and flowering traits of Oncidesa cultivars, with each cultivar showing distinct adaptability to specific canopy conditions.
Coffee: Fuel for Your Day or Foe for Your Arteries
Authors: Buelna-Chontal Mabel
Published: October 2024

Atherosclerosis, a major risk factor for cardiovascular diseases is influenced by modifiable factors such as adiposity and blood cholesterol. Diet is crucial in these areas, particularly regarding antioxidant, inflammatory, and obesity effects. Coffee, a globally popular stimulant beverage has garnered significant attention for its potential impact on cardiovascular diseases. Recent insights reinforce the need to re-examine the relationship between coffee consumption and atherosclerosis progression. Coffee’s complex composition includes polyphenols, renowned for their antioxidant and anti-inflammatory properties, as well as potential weight-reducing effects. In addition, studies have demonstrated that certain coffee compounds such as chlorogenic acid, caffeic, p-coumaric, and ferulic acid can prevent atherogenesis by preventing oxidation of low-density lipoproteins. Conversely, diterpenes, found in some coffee brews, can elevate cholesterol levels posing risk to coronary health. Notably, coffee intake has been shown to influence gut microbiota diversity, potentially contributing to anti-obesity effects. This review explores the insights from preclinical and clinical studies investigating the potential mechanisms through which coffee consumption may reduce the risk of atherosclerosis. Highlighting the potential benefits of moderate filtered-coffee consumption, as well as the potential risks associated with excessive coffee consumption. Understanding this relationship is crucial for informing public health recommendations and guiding future research.
Evolutionary Ensembles of Artificial Agents for Enhanced Mineralogical Analysis
Authors: Dell'Aversana Paolo
Published: October 2024

This paper presents a novel machine learning framework that applies evolutionary ensembles of artificial agents to mineralogical analysis and classification. The approach is based on hybridiza-tion techniques that combine diverse machine learning algorithms, creating large and effective communities of agents. These progressively mute and improve through crossover, hybridization, and selection, addressing the challenges of mineral recognition and classification from thin section images. By combining multiple machine learning techniques, the ensemble of agents autono-mously improves by evolving to adapt and enhance its ability to identify mineral species and classify different types of alterations. We detail the method, provide examples using synthetic and real data, and explore the potential to improve mineralogical analysis workflows through this dynamic, self-improving system.
Blockchain-based Infrastructure Private Financing in the Least Developed Countries: A Conceptual Framework
Authors: Moayyed Erfan , Nourzad Hossein Hosseini , Shirazi Danial
Published: October 2024

Infrastructure financing in least-developed countries (LDCs) faces various obstacles, including fragile economic conditions, inadequate regulatory frameworks, and concerns over transparency and investor security. This deters private sector involvement, impeding vital infrastructure development and long-term economic progress. Blockchain technology, on the other hand, has demonstrated its ability to enhance transparency and improve operational efficiency. To bridge this gap, this study presents a novel blockchain-based framework for private financing governance in such projects. The proposed framework was built on three components: a foundational blockchain layer for secure transactions, a DAO layer for governance, and a node layer for user interaction. Moreover, a decentralized decision-making structure was outlined, which allocates voting power according to roles and reputations. The framework also introduces well-defined entry and exit criteria to ensure commitment and transparency. Further, it incorporates a member-driven proposal process and a reputation-based compensation system to encourage active involvement. Finally, a real-world case study was used to assess the framework's practicality and efficiency. According to the findings, the proposed framework has the potential to address and improve the identified gaps. The results of this study provide conceptual insights for LDC infrastructure project stakeholders to enhance the efficiency of infrastructure development in these nations.
Non-invasive Monitoring of Cerebral Edema Using Ultrasonic Echo Signal Features and Machine Learning
Authors: Yang Shuang , Yang Yuanbo , Zhou Yufeng
Published: October 2024

Objectives: Cerebral edema, a prevalent consequence of brain injury, is associated with significant mortality and disability. Timely diagnosis and monitoring are crucial for patient prognosis. There is a pressing clinical demand for a real-time, non-invasive cerebral edema monitoring method. Ultrasound methods are prime candidates for such investigations due to their non-invasiveness nature; Methods: Acute cerebral edema by permanently occluding the left middle cerebral artery (MCA) was introduced in rats. Ultrasonic echo signals were collected at nine time points over a 24-hour period to extract features from both the time and frequency domains. Concurrently, histomorphological changes were examined. We utilized support vector machine (SVM), logistic regression (LR), decision tree (DT), and random forest (RF) algorithms for classifying cerebral edema types, and SVM, RF, and feedforward neural network (FNN) for predicting the cerebral infarction volume ratio; Results: The integration of 16 ultrasonic features associated with cerebral edema development with the RF model enabled effective classification of cerebral edema types with a high accuracy rate of 97.9%. Additionally, it provided an accurate prediction of the cerebral infarction volume ratio, with an R2 value of 0.8814; Conclusions: Our proposed strategy classifies cerebral edema and predicts the cerebral infarction volume ratio with satisfactory precision. The fusion of ultrasound echo features with machine learning presents a promising non-invasive approach for the monitoring of cerebral edema.
Involvement of Oxidative Stress in Decreased Number and Motility of Sperm in Men without Obvious Causes for Male Infertility
Authors: Chen Linji , Mori Yusaku , Nishii Shogo , Sakamoto Miwa , Ohara Makoto , Yamagishi Shoichi , Sekizawa Akihiko
Published: October 2024

Background: Male factors contribute to approximately 50% of infertile couples. However, obvious causes remain unknown in many cases. This observational study aimed to investigate the associations of clinical and lifestyle parameters with sperm parameters.
Materials and Methods: This study enrolled 41 men of infertile couples without obvious causes for male infertility from July 2023 to April 2024. Semen samples were evaluated for sperm number, motility, DNA fragmentation, and oxidative stress (OS) marker oxidation-reduction potential (ORP). Blood samples were analyzed for biochemical parameters, including advanced glycation end products (AGEs) and systemic OS marker diacron-reactive oxygen metabolites (d-ROMs). Skin-accumulated AGEs levels were identified with an autofluorescence method. Lifestyle factors were assessed with a lifestyle questionnaire.
Results: Most of the participants were under 40 years old and non-obese with normal clinical and sperm parameters. Multiple regression analyses revealed that body mass index, serum d-ROMs, and semen ORP levels were independently associated with decreased sperm number. Additionally, serum zinc and semen ORP levels were associated with sperm motility. Furthermore, serum zinc and high-density lipoprotein-cholesterol levels were associated with sperm progressive motility and DNA fragmentation, respectively. The rest of the clinical and lifestyle factors, including skin-accumulated and serum AGE levels were not correlated with any sperm parameters. Furthermore, serum d-ROMs and semen ORP levels were not correlated with each other or any of the clinical and lifestyle factors.
Conclusions: Our present study indicates that both systemic and local OS may be independently involved in sperm abnormality of healthy men without obvious causes for male infertility.
The Temperature Dependence of the Divergence Pressure
Authors: Bair Scott
Published: October 2024

The so-called controversy in elastohydrodynamic lubrication (EHL) regarding the nature of the shear dependence of viscosity, Eyring versus Carreau, is truly a controversy regarding the pressure and temperature dependence of the low-shear viscosity. The Roelands hoax became acceptable in EHL because ignoring the universal previtreous piezoviscous response made the traction calculated with the Eyring assumption appear to be reasonable. Traction and minimum film thickness calculations sometimes require the description of viscosity at pressures up to the glass transition pressure. There have been few measurements of viscosity at pressures up to the glass pressure. Therefore, a need exists for a piezoviscous model that extrapolates accurately and the Hybrid model fills that need. Here, an improved relation for the temperature dependence of the divergence pressure is offered and extrapolation is demonstrated for a polyalphaolefin.
Tennis Game Dynamic Prediction Model Based on Players’ Momentum
Authors: Wang Lechuan , Chen Puning
Published: October 2024

Psychological momentum dynamics in tennis have triggered interest for a long time, but measuring their impact presents substantial obstacles. In this paper, we present an approach to quantify momentum that combines real-time winning probabilities, leverage, and an exponentially weighted moving average (EWMA). We test the method on a high-profile match between Carlos Alcaraz and Novak Djokovic, demonstrating how changes in leverage affect momentum. Furthermore, we use feature extraction methods from time series analysis to derive momentum-related characteristics, which are critical inputs for creating an eXtreme Gradient Boosting (XGBoost) binary classification model to predict game winners. The algorithm has an average accuracy of 84% and provides real-time predictions of each player’s chances of winning the match. Our findings indicate that momentum is a somewhat relevant element in forecasting match outcomes, highlighting its potential value in improving match prediction systems.
Effects of Biological Nitrogen Fixation and Nitrogen Deposition on Soil Microbial Communities in Karst Grassland Ecosystems
Authors: Liu Xin , Yang Rong , Zhao Jie , Xiao Dan , He Xunyang , Zhang Wei , Wang Kelin , Chen Hongsong
Published: October 2024

Diverse exogenous nitrogen (N) sources have a considerable impact on microbial community structure in terrestrial ecosystems. Legume plants and N deposition can relieve N limitations and increase net primary productivity. However, the differences in their effects on soil microbial communities remain unclear. Here, the responses of the soil microbial community to a legume-planting system and simulated N deposition were examined in karst grasslands in Southwest China over five years by analyzing soil microbial phospholipid fatty acids (PLFAs). The experiment included three treatments—legume plant introduction (NL, Indigofera atropurpurea), N deposition (ND, NH4NO3:10 g N m−2 yr−1), and a control with no treatment. The effects of NL and ND on soil microbial community composition were significantly different. ND significantly reduced the biomass of bacteria, Actinobacteria, and arbuscular mycorrhizal fungi. NL insignificantly increased the biomass of all microbial groups. However, the total amounts of PLFAs and fungal biomass were significantly higher in NL than in ND. The effect of legume plant introduction on soil microbial community composition was more powerful than that of ND. Overall, the introduction of legume plants is beneficial for increasing the biomass of the soil microbial community and stabilizing the soil microbial community structure in karst grassland ecosystems.
A note on alternating weighted sums of Fibonacci numbers
Authors: Prabha Sivaraman Nair
Published: October 2024

In this note, we introduce a new convolution identity for the difference between classical Fibonacci numbers Fk and the alternating powers of k. We then apply this identity to develop a direct formula for the alternating convolution of Fibonacci numbers Fk and powers of k. Finally, we obtain an explicit formula for the alternating weighted Brousseau sums of the Fibonacci numbers using this alternating convolution identity. Furthermore, we generalize these identities to the Gibonacci numbers Gk with arbitrary initial values.