bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of the Dose of African Swine Fever Virus Required to Establish Infection in Pigs Following Oral Uptake
Authors: Olesen Ann Sofie , Lazov Christina Marie , Accensi Francesc , Johnston Camille Melissa , Rasmussen Thomas Bruun , Bøtner Anette , Lohse Louise , Belsham Graham J.
Published: December 2024

African swine fever virus (ASFV) is known to be very stable within a protein-rich environment and indirect virus transmission can be mediated via oral uptake of different materials. However, experimental studies in pigs have shown that infection by ASFV via the oral route can be difficult to establish. Currently, there is a lack of studies using strict oral inoculations of pigs with different doses of ASFV. Therefore, we aimed to determine the dose of a European genotype II ASFV that is required to establish infection of pigs by the oral route. In this study, 24 pigs were divided into four groups of six. Three of the groups were fed with a low, medium or high dose of the ASFV POL/2015/Podlaskie virus. Pigs in the fourth group served as positive controls and were inoculated intranasally, just once, using the low dose of the virus. All pigs inoculated intranasally with ASFV succumbed to the infection, while only three of the six pigs that were fed the high dose of the virus became infected. None of the 12 pigs that were fed either with the medium or low doses of the virus became infected, despite receiving up to thirteen doses each. In two of the pigs infected by intranasal inoculation, the presence of a variant form of the ASFV genome was detected. The results obtained in this study underline that ASFV infection is more difficult to establish via the oral route when compared to the intranasal route. The high dose needed in order to establish oral infection could have implications for future strategies using baited vaccines containing infectious live-attenuated ASFV.
Impact of Reduced Dietary Crude Protein and Propionic Acid Preservation on Intestinal Health and Growth Performance in Post-Weaned Pigs
Authors: Connolly Kathryn Ruth , Sweeney Torres , Ryan Marion T. , Vigors Stafford , O’Doherty John V.
Published: December 2024

This study investigated whether organic acid (OA)-preserved grain could mitigate the negative effects of low crude protein (CP) diets on growth performance, intestinal health, and the coefficient of total tract digestibility (CATTD) of nutrients in weaned piglets. The grain was either conventionally dried or preserved post-harvest with 4 kg of OA per tonne. Ninety-six piglets (28 days old) were assigned to one of four diets in a 2 × 2 factorial design: (1) dried standard CP diet, (2) OA-preserved standard CP diet, (3) dried low CP diet, and (4) OA-preserved low CP diet. Standard and low CP diets contained 21% and 19% CP during the first 15 days, reducing to 19% and 17.5% CP thereafter. Faecal scores (FS) were assessed twice a day while microbial composition, inflammatory markers, colonic volatile fatty acid concentrations and intestinal morphology were measured on the 8th day post-weaning. Performance metrics were measured over the 35-day experimental period. Low CP diets consistently reduced FS (P<0.05) and increased colonic molar butyrate proportions (P<0.01) but increased duodenal IL1B expression compared to standard CP diets (P<0.05). The OA-preserved grain enhanced beneficial microbial populations (Lactobacillus, Roseburia) while lowering pro-inflammatory cytokines (IL1A, IL17) (P<0.05). While dried grain with low CP diets reduced average daily gain (ADG), colonic short-chain fatty acids (SCFA) concentrations, and nitrogen digestibility, OA-preserved grain with low CP maintained these parameters and improved final body weight (P<0.05). Overall, OA-preserved grain mitigated the performance decline associated with low CP diets by enhancing gut health, nutrient digestibility, and reducing inflammation, presenting a promising alternative nutritional strategy for post-weaned piglets.
Effect of Carotenoid Composition on Stability and Light-Induced Oxidative Damage of the LH2 Complexes Isolated from Ectothiorhodospira haloalkaliphila
Authors: Yanykin Denis V. , Paskhin Mark O. , Shumeyko Sergey A. , Ashikhmin Aleksandr A. , Bolshakov Maxim A.
Published: December 2024

Earlier, it has been shown that carotenoid-dependent singlet oxygen photogeneration in LH2 of Ectothiorhodospira haloalkaliphila leads to damage to pigments and protein. Present work continues this investigation using LH2 complexes with altered carotenoid composition: сarotenoid-less LH2, and LH2 complexes with incorporated neurosporene, spheroidene or rhodopin (LH2-Neu, LH2-Sph or LH2-Rho, respectively). It was shown that inhibition of carotenoid synthesis led to a decrease in LH2 thermal stability and reducing the light-induced oxidative damage to bacteriochlorophyll and protein. Re-incorporation of exogenous carotenoids did not return stability of the complexes but reduce tendency of complexes to aggregate, and (in the case of LH2-Rho) reactivated both photooxidation of bacteriochlorophyll and photoproduction of organic hydroperoxides. It was concluded that carotenoids play an important role in the complex stability and are capable of inducing oxidative damage to LH2 components through singlet oxygen photogeneration.
Risk Factors and Potential Treatments for Fatigue in Patients with Advanced CKD: A Narrative Review
Authors: Xia Ai , Meuleman Yvette , Dekker Friedo W. , Hoogeveen Ellen Karen
Published: December 2024

Despite the high burden of fatigue in patients with advanced chronic kidney disease (CKD) stage 4-5 including dialysis, little is known about risk factors and treatments for fatigue. This paper provides an overview of measurement, associated risk factors and approaches to alleviate fatigue. Up to now, the 36-Item Short Form Health Survey (SF-36) is the most widely used tool to measure fatigue. Socio-demographic factors, including older age, female, white ethnicity, less education, unemployment and less social support, are risk factors for fatigue. More severe fatigue is related to anemia, protein energy wasting, inflammation, lactic acidosis, comorbidities (including diabetes, cardiovascular disease and chronic obstructive pulmonary disease), depression, anxiety, sleep disorders and uremic symptoms such as restless legs syndrome and pruritus. Dialysis treatment, dialysis-related low blood pressure and low dialysis adequacy, contribute to fatigue. Medication, such as β-blockers, antidepressant medication and medication for sleep disorders, are associated with fatigue, either as a result of the underlying condition treated or side effects. Currently, the principal treatments encompass pharmacological and nonpharmacological interventions. The utilization of erythropoiesis-stimulating agent (ESA) for anemia may alleviate fatigue. Physical exercise has been proved to be a promising therapeutic approach. Moreover, a recent clinical trial has confirmed the safety. Other potential treatments, such as L-carnitine, sodium bicarbonate, antidepressant medication (such as bupropion), psychological interventions and cold dialysis, require more research. In summary, further studies are recommended with more focus on the risk factors and underlying mechanisms, as well as potential treatments for patients with advanced CKD.
Can New Quality Productivity Promote the Carbon Emission Performance?—Empirical Evidence from China
Authors: Wang Shubin , Chen Feng
Published: December 2024

The new quality productivity(NQP) has the possibility to enhance carbon emission performance that will fortify the groundwork for long-term economic expansion even further. The research examines the panel data of 30 provinces spanning the years 2012 to 2022 for an evaluation framework for NQP and carbon emission performance at the provincial level. Employing fixed effect models, mediation effect analysis, and spatial econometrics, the study explores the effect of NQP on carbon emission performance, its mediating mechanisms, and the spatial spillover effects. The findings indicate that: (1) NQP significantly lowers carbon emissions for every unit of GDP and enhances carbon emission performance, the result holds up when the instrumental variable methods are used. (2) The NQP had a significant contribution on improving carbon emission performance via advancements in green innovation. (3) The NQP does more than directly enhances the regional carbon emission performance, in contrast, it additionally positively influences the carbon emission performance level of adjacent regions by spatial spillover effect. (4) The impact of NQP on carbon emission performance is particularly pronounced in eastern and innovative regions. On this basis, we should vigorously develop the NQP, strengthen cross-regional policy coordination, and promote green and sustainable development.
Detecting and Explaining Long-Term Trends in a Weed Community in a Biennial Cereal-Legume Rotation
Authors: Gonzalez-Andujar Jose L. , Gonzalez-Garcia Irene
Published: December 2024

The technique of Dynamic Factor Analysis (DFA), which aims to reduce the dimensionality of time series data, was utilized in order to model the changes over time in 8 different weed long-time series (26 years) growing in a biennial cereal-legume rotation. A common trend was extracted that captured the main signal of abundance over the time, indicating latent influences affecting all species. Canonical correlation analysis showed strong associations between the common trend and specific weed species, suggesting differential responses to this latent factor. Local (temperature and precipitations) and global weather factors (North Atlantic Oscillation (NAO)) were considered as explanatory variables to explain the common trend. The local weather variables considered did not play a significant role in explaining the common observed trend. Conversely, NAO showed a significant relationship with the weed community, indicating its potential role in shaping long-term weed dynamics. DFA was found to be useful for studying the variability in multivariate weed time series without the need for detailed a priori detailed information on the underlying mechanisms governing weed population dynamics. Overall, this study provides valuable insights into the long-term drivers of weed dynamics and sets the stage for future research in this area.
An Auto-Associative Unit Memory Network
Authors: Greer Kieran
Published: December 2024

This paper describes a new auto-associative network called a Unit Memory network. It is so-called because unit nodes in a network store binary input as integer values, representing binary words. The word size is critical and specific to the dataset and it also provides a first level of cohesion over the word values. A second cohesion network then links the unit network nodes, through layers of decreasing dimension, until the top layer contains only 1 node for any pattern. Thus, a pattern can be found using a search and compare technique through the two networks. The unit memory is compared to a Hopfield network and a Sparse Distributed Memory (SDM). It is shown that the memory requirements are not unreasonable and that it has a much larger capacity than a discrete Hopfield network, for example. It can also store dense or sparse data and can deal with maybe 30% noise. This is demonstrated with test results for 3 benchmark datasets. Apart from unit size, the rest of the configuration is automatic, and its simplistic design could make it attractive for some applications.
Assisted Reproduction: Impact of Mitochondrion (Dys)function and Antioxidant Therapy
Authors: Pereira Rosa Maria Lino Neto , Ferreira Filipa C , Teixeira José , Lidon Fernando , Cagide Fernando , Borges Fernanda
Published: December 2024

In the last years, major changes in the biosystem related to the industrial development and envi-ronmental modifications have had a direct impact on human and animal fertility, as well as on biodiversity. It is widely demonstrated that all these changes impair in the reproductive function. Several studies have connected the increase of reactive oxygen species (ROS) generated in mito-chondria to the recently identified decline of fertility due to various factors, including heat stress. The study of antioxidants and especially of mitochondria targeted antioxidants, has been ad-dressed to identify more efficient and less toxic therapies that could circumvent the problem of in-fertility in mammals. These antioxidants can be obtained from natural compounds used in the diet and converted into more effective forms to mitochondria, which will be a much more natural therapy. The use of mitochondriotropic diet-based antioxidants in Assisted Reproductive Tech-nologies (ART) may be an important way to circumvent the low fertility, allowing the conserva-tion of biodiversity in animal species, including domestic breeds. This paper provides a concise re-view of the current state of the art on this topic, with a particular focus on antioxidants: Mitoqui-none, AntiOxBEN2, AntiOxCIN4, Urolithin A and the most recent Piperine.
Exploring Physicians and Patient Perspectives on Expectations and Role Models Towards Chronic Pain Treatment in General Practice: A Qualitative Cross-Sectional Study
Authors: Dupont Dominik , Brinkmöller Sabrina , Carter Sarina , Wensing Michel , Straßner Cornelia , Engeser Peter , Poß-Doering Regina
Published: December 2024

Background and Objective: Approximately 7.4% of the German population matched the criteria of impeding, chronic non-cancer-related pain in 2014. Guidelines emphasize the importance of a holistic treatment approach. The project RELIEF aims to develop and evaluate a multifaceted case-management intervention to foster holistic management of chronic pain in general practice. To inform intervention development, this study explored expectations and perceived role mod-els of General practitioners (GP) and patients regarding chronic non-cancer-related pain man-agement in general practice with a focus on patient expectations towards GPs and themselves, as well as GP expectations towards patients and their anticipation of patient’s expectations.
Methods: Data were collected via semi-structured guide-based interviews with general practi-tioners and patients. Pseudonymized verbatim transcripts were analyzed using an induc-tive-deductive approach with a structuring qualitative content analysis. The Theoretical Do-mains Framework served as analytical framework to explore behavioral aspects connotated with expectations and role perceptions.
Results: N=25 interviews were analyzed (GP: n=10, patient: n=15). Findings indicate that patients considered themselves as main actor in the therapy process yet expected guidance and care co-ordination from their GP. Role models indicated by GPs and some patients represent a care ide-al, which was also reflected in discussed expectations. GPs anticipated patients to put a high rel-evance on pharmacological options. Patients highlighted their preference of non-pharmacological and alternative treatment options.
Conclusions: Findings demonstrate the importance of holistic, individually tailored chronic pain management in general practice. Systematic, multifaceted case man agement, as planned in the RELIEF project, may contribute to high-quality primary care for affected individuals.
Social Understanding and Friendships in Children with Attention Deficit/Hyperactivity Disorder or Dyslexia
Authors: Kouvava Sofia , Antonopoulou Katerina , Kokkinos Constantinos M. , Ralli Asimina M.
Published: December 2024

Social understanding relies upon children’s experience of the world and the communicative interaction with others. Opportunities to engage in cooperative social interaction, such as friendships, can foster the development of social understanding. Children with Attention Deficit/Hyperactivity Disorder (ADHD) and dyslexia often have friendships of poorer quality. The present study examined relationships and differences in social understanding and friendship quality in children with ADHD or dyslexia, in comparison to neurotypically developing children (NTD). Participants were 192 primary-school students (Mage=9.77, sd=1.21) from Attica, Greece. Social understanding was measured with second-order and advanced theory of mind (ToM) tasks, and the Bryant’s Index of Empathy for Children and Adolescents, while friendships were examined with the Friendship Quality Questionnaire. Children with ADHD scored significantly lower across all positive characteristics of friendship quality, empathy and advanced ToM than those with dyslexia, who in turn, scored significantly lower than NTD children. Moreover, children with ADHD performed significantly worse in the second-order ToM tasks comparing to children with NTD or dyslexia, while NTD children scored significantly lower in the friendship conflict betrayal subscale compared to both ADHD and dyslexia groups. Multiple regression analyses controlling for learning disability status, gender, and age showed that ToM and perceived empathy predict friendship quality characteristics in all groups of children. Our findings contribute to a better understanding of children’s friendship relationships and give insight to parents and professionals involved in children’s education, provision, and mental health care.
Identification of Phytosphingosine-Based 1-O-Acylceramide in the Human Stratum Corneum and Investigation of Its Role in the Skin Barrier
Authors: Kang Bae-Gon , Choi Hyun Kyung , Liu Kwang-Hyeon , Hong Sung Kyu , Kim Jin Wook , LEE EUN OK , Park and Chang Seo
Published: December 2024

Phytosphingosine-based 1-O-acylceramide (CER 1-O-ENP) from the human stratum corneum (SC) has not been reported. A High-Resolution Mass Spectrometry was used to identify CER 1-O-ENP from the skin samples. A vehicle-controlled human study was performed to investigate the physiological interaction between CerNP and CER 1-O-ENP with respect to skin hydration, cohesion, and TEWL were measured. Twenty volunteers were treated with test creams containing CER 1-O-ENP together with CerNP, which significantly improved skin barrier parameters after four weeks of application: 1. Skin hydration was increased by 26% compared to that of CerNP alone and moisture retention was better than CerNP control. 2. SC cohesion was fostered significantly only formulated with CER 1-O-ENP. The results suggested a boosting effect of CER 1-O-ENP on the skin barrier functions exerted by CerNP since only a small amount is required, as low as 1/10 of CerNP. This is the first report on the identification of CER1-O-ENP in the human SC and its skin barrier activities in human skin. In conclusion, the combinatorial use of CER1-O-ENP and CerNP at an appropriate relative ratio could be a new normal in developing an ideal moisturizer for dry and atopic skin.
AI-Driven Personalized Learning: A Comprehensive Survey of Chatbot Applications in Education and Training
Authors: Krishna Akhil , Satheesh Aswin , PR Parthip , Thomas Blessen , Gopi Ajith
Published: December 2024

This survey examines the use of AI-powered chat- bots in educational environments, focusing on their role in enhancing personalized learning experiences. By reviewing recent studies, this paper highlights the capabilities, benefits, and challenges of chatbot applications, including adaptive learning, student engagement, and language acquisition support. The findings show that chatbots can assist with personalized tutoring, provide real-time feedback, and streamline administrative tasks, significantly enhancing student engagement. However, challenges such as data privacy, ethical implications, and integration with existing educational systems remain. This survey provides in- sights into current trends and identifies critical areas for future research, aiming to guide educators and developers in optimizing AI-driven learning solutions. Index Terms—Artificial Intelligence (AI), Mobile Learning, En- glish Language Learning, Rural Education, Duolingo, Adaptive Learning, Student Engagement, User Experience, English as a Foreign Language (EFL), Classroom Integration, Blended Learn- ing, Vocabulary Retention, Learning Outcomes, AI-Enhanced Teaching, Innovation in Education.
A Rare Case of an Intracardial Ectopic Thyroid in the Right Ventricle
Authors: Wei Chuangwei , Zhao Ying , Song Yanting , Liu Dongting , Zhang Nan , Liu Jiayi , Sun Zhonghua , Wen Zhaoying , Xu Lei
Published: December 2024

The ectopic thyroid gland is an abnormal development of the embryo. Most of the ectopic thyroid occurs in the path around the thyroglossal duct or on the lateral side of the neck. However, ectopic thyroid occurs in the heart, which is rare. We report a case of right ventricular ectopic thyroid. This case highlights the imaging characteristics of computed tomography (CT) and cardiac magnetic resonance (CMR) and analyzes the underlying mechanisms for a timely diagnosis.
Analysis of Germinal Center Reaction in Competitive Bone Marrow Chimeric Rag2-/-gc-/- Mice
Authors: Datta Moumita
Published: December 2024

Germinal center (GC) reaction is crucial for the generation of high-affinity antibodies against any infection. To address the role of specific gene in GC, knock out mouse models are generally used. However, since GC is multicellular event, complete knock out models cannot pin point the cell intrinsic effect of certain genes in GC reaction. Here, we describe a detail protocol for the analysis of GC in competitive bone marrow chimeric mice generated by transplanting 1:1 mixture of CD45.1 and CD45.2 positive donor bone marrow (BM) cells in immunodeficient Rag2-/-gc-/- mice as recipient host. We describe the method of immunization using sheep red blood cells (SRBC), detection of successful immunization by the antigen specific antibody titer in the serum of the immunized mice and finally assessing the GC reaction in the spleen of the immunized mice by flow cytometry 10 days post-immunization. When the competitive chimera is made with wild type (WT) and a knock out (KO) donor BM, this method is suitable to address the cell type specific (for. e.g. B cell specific) role of the KO gene in GC.
Predictive Analysis of Binding Affinity among Human Cytomegalovirus (HCMV) Proteins and Class-I Major Histocompatibility Complex (MHC-I) Molecules
Authors: Biswas Balaka , Bhaduri Ankita , Saha Mousumi , Das Dipanwita , Sarkar Agniswar
Published: December 2024

Human Cytomegalovirus (HCMV) is a ubiquitous pathogen that establishes lifelong infections by evading the host immune system, particularly through targeting Class I Major Histocompatibility Complex (MHC-I) molecules. This immune evasion is mediated by a subset of viral proteins, including unique short (US) and unique long (UL) glycoproteins, which disrupt MHC-I antigen presentation and impair cytotoxic T-cell responses. In this study, we conducted an in-depth bioinformatics analysis of five key HCMV proteins (US2, US3, US6, US10, and US11) to investigate their structural and functional characteristics, focusing on their interactions with MHC-I molecules. Through homology modelling, binding affinity predictions, and structural comparisons, we identified unique features that enhance the ability of these viral proteins to inhibit immune recognition. Notably, structural adaptations in US6 and US10 suggest specialized roles in antigen processing interference. These findings provide new insights into the molecular mechanisms of HCMV immune evasion and offer potential avenues for developing targeted antiviral therapies.
Influence of Alkaline Treatment and Fiber Morphology on the Mechanical, Physical, and Thermal Properties of Polypropylene and Polylactic Acid Biocomposites Reinforced with Kenaf, Bagasse, and Hemp Fibers
Authors: Osman Zeinab , Elamin Mohammed , Ghorbel Elhem , Charrier Bertrand
Published: December 2024

This study investigates the effect of slight surface treatment of Kenaf (KBF), Bagasse, and Hemp fibers on the mechanical, morphological, physical, and thermal properties of biodegradable composites. The composites were prepared by extrusion using 25 wt% fibers to reinforce 75 wt% polypropylene (PP) and plasticized poly(lactic acid) (PLA), with softwood fibers as a control. Fi-bers were treated with 5% sodium hydroxide (NaOH) for one hour. Mechanical properties (ten-sile, young’s modulus, and impact), physical properties (fiber mapping, density, brightness), and thermal properties (heat deflection temperature (HDT), melting temperature, melt flow ratio (MFR), and melt flow index (MFI)) were evaluated using standard procedures. The biocomposites morphology was studied by scanning electronic microscopy (SEM). Results showed improved tensile and impact strength for PP composites with treated Bagasse (6.6% and 22%) and Hemp (7% and 44.7%), while Kenaf showed minimal change, indicating its high intrinsic strength. Fiber addition increased the HDT of PP from 55°C to 119°C for untreated KBF, 100°C for softwood, 86°C for Bagasse, and 79°C for Hemp. Treated fibers reinforced PP composites achieved higher HDT, with Kenaf (124°C) performing best, followed by Bagasse (93°C). PLA composites showed slight increases in HDT with fiber reinforcement. Differential Scanning Calorimetry (DSC) revealed a slight melting temperature decrease for PP and a slight increase for PLA. Overall, Kenaf and Bagasse yielded superior mechanical and thermal performance, comparable to softwood, while Hemp demonstrated moderate results. The differences among the fiber’s performance were at-tributed to variations in fiber mapping and the intrinsic properties of the polymer matrices.
The Total Entropic Quantity Framework: A Conceptual Foundation for Entropy, Time, and Cosmic Evolution
Authors: Sigtermans David
Published: December 2024

The Total Entropic Quantity (TEQ) framework provides a unified model for the interplaybetween entropy, time, and the thermodynamic evolution of the universe. By decomposing the totalnormalized entropy into three components–apparent entropy, entangled latent entropy, and non-entangled latent entropy–the TEQ framework reconciles the universe’s global quantum coherencewith the local emergence of thermodynamic disorder.A central result is the emergence of Universal Entropic Time (UET), a synchronized tem-poral framework defined by the monotonic growth of apparent entropy. UET naturally aligns withthe thermodynamic arrow of time, providing a robust link between decoherence processes and theobserved irreversibility of classical systems.TEQ integrates seamlessly with the Friedmann equations of General Relativity, ensuringconsistency with cosmic expansion and large-scale homogeneity. Moreover, speculative extensionsexplore the hypothesis that entanglement serves as the foundation for time and space, with deco-herence driving the transition from pre-geometric quantum states to classical spacetime.This framework not only unifies entropy growth, time, and causality but also connects theseprocesses to observable phenomena, including gravitational wave spectra, cosmic microwave back-ground anisotropies, and the large-scale structure of the universe. TEQ thus oﬀers novel insightsinto the thermodynamic arrow of time, the emergence of classical behavior, and the cosmologicalevolution of the universe.
XRF-Escape Scintillator Footprints for Nuclear Medicine Imaging and Gamma-Ray Spectrometry
Authors: Scafè Raffaele , Puccini Marco , Pellegrini Rosanna , Pani Roberto
Published: December 2024

The present paper introduces the so-called scintillators footprints, made of schemes showing XRF-escape peaks and their relative emission intensities in the energy range of interest for nuclear medicine SPECT and PET. A footprint describes the suitability of a scintillator for quantitative investigation with the best possible detectabilility. Sixteen scintillation materials have been identified in Literature, characterized by effective atomic number ranging between 22 to 75. The footprints of NaI:Tl and BGO, confirm the best suitability for quantitative spectral analisys at 140.5 keV and 511 keV, respectively. Moreover, for the low-Z eff scintillators like CaF 2 and CMSM, the XRF-escape effect is foresee irrelevant even at 140.5 keV, due to the small energy value of X-ray fluorescences.
The 3-30-300 Indicator, a Tool for Assessing Geographical Access and Inequalities Associated with Green Spaces: Demonstration Project for the Island of Montreal, Canada
Authors: Robitaille Éric , Douyon Cherlie
Published: December 2024

(1) Background: this study examines the effectiveness of the 3-30-300 indicator as a tool for assessing the accessibility of green spaces in the island of Montreal, Canada. The 3-30-300 framework defines three standards for urban vegetation: every resident should be able to see three trees from their home, live in a neighborhood that has 30% canopy cover, and have access to a park or green area within 300 meters. This study measures the distribution of these criteria across Montreal's neighborhoods using geospatial analysis and examines disparities linked to so-cio-economic factors. (2) Methods include spatial analysis using metrics like Getis-Ord G and Lee's L to identify patterns and correlations with socio-economic vulnerabilities. (3) The results show that there are inequalities in the distribution of green spaces: only a limited neighborhoods meet all the 3-30-300 criteria, while several outlying areas lag. (4) Conclusions: such results clearly show the need to have specific urban greening programs, particularly in neighborhoods that face so-cioeconomic challenges, to reduce inequalities in accessibility to green infrastructure for improved public health and urban resilience.
Text Classification: How Machine Learning is Revolutionizing Text Categorization
Authors: Allam Hesham , Makubvure Lisa , Gyamfi Benjamin , Kwadwo Graham , Akinwolere Kehinde
Published: December 2024

The automated classification of texts into predefined categories has become increasingly prominent, driven by the exponential growth of digital documents and the demand for efficient organization. This paper serves as an in-depth survey of text classification and machine learning, consolidating diverse aspects of the field into a single, comprehensive resource—a rarity in the current body of literature. Few studies have achieved such breadth, and this work claims to provide a unified perspective, offering a significant contribution to researchers and the academic community. The survey examines the evolution of machine learning in text categorization (TC), highlighting its transformative advantages over manual classification, such as enhanced accuracy, reduced labor, and adaptability across domains. It delves into various TC tasks and contrasts machine learning methodologies with knowledge engineering approaches, demonstrating the strengths and flexibility of data-driven techniques. Key applications of TC are explored, alongside an analysis of critical machine learning methods, including document representation techniques and dimensionality reduction strategies. Moreover, this study evaluates a range of text categorization models, identifies persistent challenges like class imbalance and overfitting, and investigates emerging trends shaping the future of the field. It discusses essential components such as document representation, classifier construction, and performance evaluation, offering a well-rounded understanding of the current state of TC. Importantly, this paper also provides clear research directions, emphasizing areas requiring further innovation, such as hybrid methodologies, explainable AI (XAI), and scalable approaches for low-resource languages. By bridging gaps in existing knowledge and suggesting actionable paths forward, this work positions itself as a vital resource for academics and industry practitioners, fostering deeper exploration and development in text classification.
Scalar Field Kantowski–Sachs Solutions in Teleparallel F(T) Gravity
Authors: Landry Alexandre
Published: December 2024

In this paper we investigate time-dependent Kantowski-Sachs spherically symmetric teleparallel $F(T)$ gravity with a scalar field source. We begin by setting the exact field equations to be solved and solve conservation laws for possible scalar field potential $V\left(\phi\right)$ solutions. Then we proceed to find new non-trivial teleparallel $F(T)$ solutions by using power-law and exponential ansatz for each potential cases arising from conservation laws such as linear, quadratic, logarithmic to name a few. We find a general formula allowing to compute all possible new teleparallel $F(T)$ solutions applicable for any scalar field potential and ansatz. Then we apply this formula and find a large number of exact and approximate new teleparallel $F(T)$ solutions for several types of cases. Some new $F(T)$ solution classes may be relevant for future cosmological applications, especially concerning the dark matter, the dark energy quintessence, phantom energy leading to the Big Rip event and quintom models of physical processes.
Quantifying Death Valence: A Thermometer Scale to Evaluate Explicit Expectations About One’s Own Mortality
Authors: Stiller Mel
Published: December 2024

This article introduces a thermometer scale to measure explicit death valence and explores its associations with death needs and death coping. While previous measures of a good death comprised interviews, surveys and implicit tests, no brief explicit measure for death valence seemed to exist. However, death positivity might affect personal well-being, end-of-life care and social encounters, due its relationship with life satisfaction and social prejudice. A repeated measures design indicated the sufficient reliability and validity. The scale should not be used as a single measure though, as implicit and explicit death attitudes show particular inconsistencies. Exploratory analyses revealed that people valued their own mortality more positively when they expected their death needs to be met, supporting the assumption of death needs constituting death valence. Five death need clusters were linked to death valence. Death positivity was furthermore associated with more acceptance coping, lmore active coping, reframing, humor, coping with religion, with the search for emotional support and with less death avoidance. Future research could examine the associations between death positivity, death needs and coping, as well as the thermometer scale's potential for health studies and social sciences.
Some Remarks on the Inverse Problem in the Variational Calculus Within the Functional and Antiexact Differential Forms Approach
Authors: Kycia Radosław , Bovdi Victor , Prykarpatski Anatolij
Published: December 2024

We present a slightly more broader framework of variational calculus to accommodate differential equations that are not variational as they stand. We discuss two approaches: The first one utilizes antiexact differential forms as obstruction to variationality, make them vanish that gives constraints for all possible variations. The spproach we discuss describe s of differential equations introducing new functions that make equations variational and then reduce them using a functional constraints. The latter approach incorporates via a not completely standard scheme the classical Dirac reduction approach.
The Role of Big Data Analytics in Strengthening Cyber Defense Mechanisms for Autonomous Vehicles
Authors: Dave Elevane , Segun Oluwaleye
Published: December 2024

The integration of autonomous vehicles (AVs) into modern transportation systems brings numerous benefits, including enhanced safety, efficiency, and convenience. However, their reliance on advanced software, interconnected systems, and real-time data processing exposes them to significant cybersecurity threats. Big Data Analytics (BDA) emerges as a critical tool in fortifying the cyber defense mechanisms of AVs, offering capabilities for real-time threat detection, predictive analysis, and system resilience. This article explores the intersection of BDA and AV cybersecurity, highlighting its role in identifying vulnerabilities, mitigating risks, and enabling adaptive responses to evolving cyber threats. It delves into practical applications such as anomaly detection, automated diagnostics, and predictive maintenance, while addressing challenges like data privacy and integration complexities. By examining case studies and future trends, this study underscores the necessity for a collaborative approach among industry stakeholders to harness BDA's full potential in safeguarding autonomous vehicles. The findings advocate for a proactive adoption of BDA-driven solutions as an essential pillar of AV cybersecurity.
Automated Detection of Pedestrian and Bicycle Lanes from High-Resolution Aerial Images by Integrating Image Processing and Artificial Intelligence (AI) Techniques
Authors: Antwi Richard Boadu , Lawson Prince Lartey , Kimollo Michael , Ozguven Eren Erman , Moses Ren , Dulebenets Maxim A , Sando Thobias
Published: December 2024

The rapid advancement of computer vision technology is transforming how transportation agencies collect roadway characteristics inventory (RCI) data, yielding substantial savings in resources and time. Traditionally, capturing roadway data through image processing was seen as both difficult and error-prone. However, considering the recent improvements in computational power and image recognition techniques, there are now reliable methods to identify and map various roadway elements from multiple imagery sources. Notably, comprehensive geospatial data for pedestrian and bicycle lanes is still lacking across many state and local roadways, including those in the State of Florida, despite the essential role this information plays in optimizing traffic efficiency and reducing crashes. Developing fast, efficient methods to gather this data is essential for transportation agencies as it also supports objectives like identifying outdated or obscured markings, analyzing pedestrian and bicycle lane placements relative to crosswalks, turning lanes, and school zones, and assessing crash patterns in the associated areas. This study introduces an innovative approach using deep neural network models in image processing and computer vision to detect and extract pedestrian and bicycle lane features from very high-resolution aerial imagery, with a focus on public roadways in Florida. When tested against Leon County, Florida, ground truth data, the models demonstrated accuracy rates of 73% for pedestrian lanes and 89% for bicycle lanes. This initiative is vital for transportation agencies, enhancing infrastructure management by enabling timely identification of aging or obscured lane markings, which are crucial for maintaining safe transportation networks.
The Fire Safety Framework for the Buildings in the Emirate of Sharjah, UAE
Authors: Omar Musab , Mahmoud Abdelgadir
Published: December 2024

The purpose of this study is to assess the effectiveness of the current fire management system for residential buildings in the Emirate of Sharjah, propose a framework to reduce fire accidents in these buildings, evaluate the current implemented practices, and identify the necessary changes to transform the fire management system from reactive to proactive. The careful identification of the research objective informs the design of the proposed framework. Identify the factors affecting the performance of the Fire Management System for the residential buildings in the Emirate of Sharjah. Evaluate the factors affecting the performance of the Fire Management System. Develop an im-proved framework that enhances the performance of the Fire Management System in the Emirate of Sharjah and validate it through the subject matter experts. The results of the evaluation of the current fire management system in the Emirate of Sharjah revealed that it consists of two main elements: protection and response. Comparing with the best practices that include four elements: prevention, protection, response, and resilience, the two elements added to the proposed improved frameworks to fill the gap.
AI-Based Clustering of Numerical Flow Fields for Accelerating the Optimization of an Axial Turbine
Authors: Eyselein Simon , Tismer Alexander , Raj Rohit , Rentschler Tobias , Riedelbauch Stefan
Published: December 2024

The growing amount of Renewable Energy Sources has led to the demand of innovative and high performing turbine designs. Due to the increase of computing resources over the last years, the numerical optimization with use of Evolutionary Algorithms (EAs) has become established. Nevertheless, EAs require a high number of expensive computational fluid dynamic (CFD) simulations and with an increasing number of design parameters, more computational resources are required. In this work, an adapted optimization algorithm is introduced. By employing an Artificial Intelligence (AI)-based design assistant, turbines with a similar flow field are clustered into groups and provide a dataset to train AI-models. These AI-models are able to predict the flow field’s clustering before a CFD simulation is performed. By analyzing the turbines properties inside the predicted clustering group, the turbine’s efficiency and cavitation volume are predicted. Turbines with properties below a certain threshold are not CFD simulated but estimated by the design assistant. By this procedure, currently more than 30% of the CFD simulations are avoided, significantly reducing computational costs and accelerating the overall optimization workflow.
Pengaruh Pemilihan Lokasi Usaha Terhadap Pendapatan Usaha Mikro Kedai Kopi di Kecamatan Kebon Jeruk
Authors: Ninda Ainin Alifio  , Hardi Ode Sofyan , Hijrawady Sony Nugratama
Published: December 2024

The purpose of this study is to find out "How do business location selection factors affect coffee shop micro businesses in Kebon Jeruk District". The methodology used in this study is a quantitative research with a causal associative research design that seeks relationships between two or more variables. Likewise, in this study, we are looking for a relationship between independent variables and bound variables. The data collection technique in this study was carried out through literature studies, documentation and questionnaires aimed at 35 (thirty-five) coffee shop micro business managers in Kebon Jeruk District. The analysis technique used in this study is multiple regression analysis which is useful to test the strength of the relationship between independent variables (variable X); accessibility (X1), visibility (X2), business environment (X3), business land (X4) with bound variables (Y); coffee shop micro business income (Y). The results of the study show that of the 5 (five) variables of location selection factors, there are three factors that have a partial influence on income, namely accessibility variables, business environment and competition. Then that all independent variables, namely accessibility, visibility, business environment, competition, and business land have a significant effect simultaneously (together) on the income of coffee shop micro businesses in Kebon Jeruk District.
Glicerina cruda, restricción alimenticia y suplementación con aminogut® en pollos de engorde
Authors: Avellaneda Y. , Afanador G. , Ariza-Nieto C.
Published: December 2024

El efecto de la suplementación con glutamina y glutamato (aminogut®) durante un periodo de restricción energética en la fase de iniciación y el uso de dietas formuladas con glicerina cruda durante la fase de engorde fue evaluado en pollos de engorde. Se utilizaron 880 pollos de engorde de la estirpe Ross, que fueron sorteados a uno de los siguientes tratamientos: alimentación a voluntad o restricción energética del 15%, del día 4 al 21 de edad, usando dietas con o sin inclusión de aminogut®. Al día 21 de edad se evaluó el desarrollo de la microestructura intestinal. Al día 22 de edad, los pollos fueron nuevamente aleatorizados a uno de los siguientes tratamientos 0, 2.5, 5.0 o 7.5% de glicerina cruda. Semanalmente se midió el peso corporal y los residuales de alimento para calcular el consumo y la conversión alimenticia. La información hasta el día 21 de edad se analizó como un diseño factorial 2x2 y la información de la fase de engorde como un diseño de parcelas divididas. La utilización de aminogut® incremento (P
Efecto de la fuente de fibra en la digestibilidad y la retención de nitrógeno en cerdos
Authors: González A. , Figueroa V. , Bentancur O. , Astigarraga L.
Published: December 2024

Se evaluó el efecto de la inclusión de dos forrajes con diferente contenido en fibra soluble (FS) sobre la digestibilidad aparente (DA) de los nutrientes y la retención del nitrógeno (RN) de dietas para cerdos en tres estados fisiológicos. Para ello se utilizó nueve animales, machos castrados en una secuencia de tres pruebas de digestibilidad in vivo, cada prueba correspondiente a una fase de peso. Los tratamientos fueron: dieta base testigo (T0) formulada en base a maíz y harina de soja; dieta base con alfalfa (T1) (Medicago sativa var. Chaná) o con achicoria (T2) (Cichorium intybus var. Lacerta) para las fases (F) de recría I (F1, 40-60 kg de PV), recría II (F2, 60-80 kg de PV) y terminación (F3, 80 a 100 kg de PV). El diseño fue de medidas repetidas utilizando Ar (1) y un nivel de significancia del 5%. La inclusión de forraje redujo CMO en T1 para F1, mientras que en F2 y F3 fueron similar a T0. La DA de la materia orgánica fue menor en las dietas con forraje para todas las fases mientras que la DA de la fibra no se redujo con el incremento del nivel de forraje. No hubo reducción en la utilización digestiva de la fibra cuando el forraje se ofreció en forma continua hasta el nivel de inclusión 30% para animales en terminación, con un mejor registro en el CMO en animales que recibieron T2. Los datos obtenidos apoyan la afirmación de que puede ser económicamente factible para los criadores de cerdos de pequeña escala utilizar ingredientes alimenticios ricos en fibra disponibles y de bajo costo.
Estimación in vitro de metano y dióxido de carbono en dietas para engorda de bovinos
Authors: Pereyra C. , Pinto R. , Ramírez R. , Hernández D. , Guevara F. , Venegas J.
Published: December 2024

El objetivo del presente trabajo fue evaluar las características de fermentación de una dieta reformulada en comparación a la usada comúnmente en la engorda de bovinos en el estado de Chiapas, México y estimar la producción de GEI utilizando para ello la técnica de producción de gas in vitro. Se analizaron dos dietas (tratamientos) utilizando la prueba de T, una dieta convencional (D1), obtenida a través de un diagnóstico realizado a productores de la región de estudio y una dieta propuesta (D2). Se usaron ocho toretes mismos que fueron adaptados al consumo de las dietas. A las dietas se les analizó materia seca (MS), proteína cruda (PC), cenizas (Ce) y materia orgánica (MO). Los parámetros y fracciones de fermentación, degradación y estimación de metano y dióxido de carbono se obtuvieron por medio de la técnica in vitro. La D1 presentó mayor (P
Avaliação da Produtividade e Qualidade do Leite de Rebanhos da Raça Jersey do Rio Grande Do Sul
Authors: Batista L.S. , Haertel S.L.C. , Silva V.R. , Lima H.G.
Published: December 2024

O presente estudo buscou avaliar a capacidade produtiva dos animais da raça Jersey em três regiões do estado do Rio Grande do Sul (RS), Brasil: Metade Sul (MS); Serra Gaúcha (SG); e Região da Campanha Gaúcha (RC). Mensurou-se a quantidade de leite produzida individualmente pelos animais de cada região, em kg de leite/animal/dia e avaliou-se a qualidade do leite, a fim de verificar possíveis diferenças entre as regiões, e compara-las com a média geral do RS. Utilizaram-se dados obtidos do Serviço de Controle Leiteiro Oficial (SCL) da Associação de Criadores de Gado Jersey do Rio Grande do Sul (ACGJRS) de todos os animais lactantes de seis rebanhos de genética similar, dois rebanhos de cada região, pelo período total de três anos, divididos em seis períodos de um semestre cada período, com início no segundo semestre de 2016, e término no primeiro semestre de 2019. Os parâmetros de qualidade do leite utilizados foram: contagem de células somáticas (ccs); gordura (%G); proteína (%P); lactose (%L); e sólidos totais (%ST). A SG apresentou os maiores valores para produção média individual dos animais. A %G foi o parâmetro de qualidade que mais oscilou, e %P não registrou variações significativas. Ao final concluiu-se que há diferenças significativas entre as regiões, onde destaca-se positivamente a SG. Conclui-se também que %G oscila significativamente com as diferenças regionais.