bluuebunny/crossref_metadata_2025 huggingface dataset:
Population migration in the Russian Far East in the 1860s
Authors: Chzhen'hao Chzhan
Published: February 2025

Demographic studies can be categorized on the basis of demographic variables into studies of fertility, mortality, population migration, population structure, population distribution, population quality, and marriage and family in demography, while migration, along with births and deaths, determines the size of the population and its growth rate in the region, as well as determining the demographic characteristics of the region. The most important demographic problem of the Russian Far East is migration, which consists in the movement of people from the countryside to the towns, from one region of the country to another, from one’s own country to another. The past era could well be called the ‘age of migration’. Migration is often the result of economic and social development, which can contribute to the improvement of economic and social conditions or, on the contrary, lead to economic stagnation and social imbalances.
Influence of the internal demographic situation on the Russian Empire during the European Revolution of 1848
Authors: Sizhan' Tan
Published: February 2025

Population is the basis of global development and plays a key role both in the economic sphere and in social development, environmental impact and national policy. Therefore, studying the progress of population change is of great significance and research value for analyzing the history of certain periods and countries. The European Revolution of 1848 was an important period in the modern history of Europe, a period in which a series of events were based on demographic factors and which, at the same time, caused demographic changes, i. e. interacted with each other. Russia, as one of the main participants in the European revolution, with its vast territory and large population, is the best object for studying the demographic problems in this period. This paper will analyze the territorial development and factors of politics, economy, social environment and other areas in terms of demographic changes in Russia.
The number and location of serfs in the European North of Russia in the late 1850-s
Authors: Popov S.
Published: February 2025

In the process of implementing the 1861 reform, in a number of uyezds of the northern provinces, regional authorities encountered difficulties caused by the small number of landowners’ possessions, which were not only scattered over their territory at a considerable distance, but were also small-scale. In order to reflect the general picture of the settling of the serf population in the European North of Russia, the author turned to the analysis of the quantitative composition of the categories of serfs listed on the eve of the abolition of serfdom in the Arkhangelsk, Vologda and Olonets provinces and the specifics of their settlement. The study is based on statistical data contained in the published work of A. Troinitsky, as well as in the office documentation of the Ministry of Internal Affairs, the Vologda and Olonets governors. These materials were based on the results of the X People’s Census (revision) conducted in 1858. As a result, it was established that five groups of the serf population lived here, among which landowner peasants and household people significantly prevailed. It was revealed that the main concentration of serfs was observed in the Vologda province, while in the Arkhangelsk province they were practically absent. The highest percentage of them was concentrated in three southwestern uyezds of the Vologda province and in two southern uyezds of the Olonets province. The remaining part was scattered across six uyezds of the first and four uyezds of the second region.
Population dynamics of the Ancient Russian state (late IX – early XIII centuries)
Authors: Tkachev V.
Published: February 2025

The paper proposes and implements an approach to determining the secular dynamics of population growth in the Ancient Russian state from the late IX to the early XIII century. The basis for constructing the dy
namics are separate population estimates obtained in previous years by a number of domestic and foreign researchers. An analysis of these estimates and the assumptions used to obtain them made it possible to adjust the available results and obtain missing data for periods of time for which such estimates were not available. In particular, for the first time an attempt was made to determine the population size at the end of the IX - beginning of the X century. The results show that from the first century of its existence until the period preceding the Mongol invasion, the population of the Ancient Russian state increased (taking into account the increase in territory) by 3.1-3.8 times. The average growth rate over the centuries was: in the XII century - about 50%, in the XI century - about 30% and in the X century - about 70%. In the X century, the main population growth was due to the annexation of new territories. Directly, the demographic growth of the population in comparable territories during this period was 10-15%.
2021 All-Russian Population Census on the settling of the peoples of the Caucasus in the Komi Republic
Authors: Zherebcov I. , Fauzer V
Published: February 2025

Based on the materials of the 2021 All-Russian Population Census, the paper considers the settling of the peoples of the North Caucasus and Transcaucasia in the Komi Republic. Data are provided on the spatial distribution of representatives of the Caucasian peoples in the municipalities of the region and individual settlements. It is noted that the majority of representatives of the peoples of the North Caucasus and Transcaucasia settled in the northern part of the Komi Republic, but among the settlements, the city of Syktyvkar occupied the first place in the number of representatives of the Caucasian peoples.
Least squares estimation for reflected Ornstein-Uhlenbeck processes with one and two sided barriers
Authors: Merahi Fateh , Bibi Abdelouahab
Published: February 2025

Diffusion processes for modelling, among others, dataset for instance, (macro-) econometrics, mathematical finance, biology, queueing, and electrical engineering often involve reflecting one or two barriers. In this paper, we investigate the least squares estimation $\left(LSE\right)$ for a one dimensional continuous-time ergodic reflected Ornstein-Uhlenbeck $(ROU)$ processes that returns continuously and immediately to the interior of the state space when it attains one and/or two-sided barriers. Both the estimates based on continuously observed processes and discretely observed processes are considered. So, we derive explicit formulas for the estimates, and then we establish their consistency and asymptotic normality ($CAN$). We also illustrate the $CAN$ properties of the estimates through a Monte Carlo simulation and comparing with respect to maximum likelihood estimation ($LME$) as benchmark method showing the performance of the proposed estimators withmoderate sample sizes. The method is valid irrespective of the length of the time intervals between consecutive observations.
Some directs numerical methods for solving the nonlinear optimal control problem practical in aeronautic
Authors: Aliane Mohamed , Moussouni Nacima
Published: February 2025

In this study, we have implemented direct numerical methods to convert the continuous optimal control problem into a nonlinear optimization problem. We used three discretization techniques: the Euler method, the second-order Runge-Kutta method, and the fourth-order Runge-Kutta method. Subsequently, the resulting non-linear optimization problem was solved using MATLAB's fmincon function. To evaluate the efficiency and accuracy of the proposed approach, we modeled a nonlinear optimal control problem relevant to aeronautics. Our objective was to minimize the travel time of a rocket from an initial point to a final point at a specified altitude, considering aerodynamic forces and gravity, with the control variable being the rocket's heel angle. To compare the different methods, we developed a MATLAB implementation and showcased various simulation results.
A new power xgamma distribution: statistical properties, estimation methods and application
Authors: Boudjerda Khawla
Published: February 2025

This paper introduces a novel probability distribution called the power xgamma distribution. We investigate several statistical properties essential for its characterization, including moments, moment generating function, quantile function, and order statistics. Estimation methods are explored to determine the parameters and characteristic functions of this distribution through a comprehensive simulation study. To illustrate its practical applicability, a real-world data example is provided, which demonstrates the effectiveness and relevance of the proposed model in empirical contexts.
Estimating the Parameters of the Odd Lomax Exponential Distribution
Authors: Habeeb Ali Salman
Published: February 2025

In this study, we introduce two methods for estimation of the unknown parameters of the Odd Lomax Exponential $(OLE)$ distribution are Least Squares Estimation $(LSE)$ and Maximum Likelihood Estimation $(MLE)$. Some statistical functions and mathematical properties were derived for which investigated from distribution’s flexibility . Through Monte Carlo simulations we investigated the performance of the estimate for these parameters, and us comparison these estimations in terms of bias and mean squared error $(MSE)$ for various sample sizes and four different scenarios of initial parameter values for two methods. Our analysis revealed that least square estimation consistently outperformed on $MLE$, yielding lower MSE values. Additionally, both two methods demonstrated decreasing in criteria values with increasing sample size, indicating improved accuracy for larger datasets. To evaluate the applicability of the $OLE$ distribution, we applied it to two types of dataset in the reliability engineering field. All computational and graphics in this work were performed in a Matlab, 23b code.
On Rainbow Vertex Antimagic Coloring of Related Prism Graphs and Its Operations
Authors: Prihandini Rafiantika , Wulandari Evi Tri , Dafik  , Kristiana Arika Indah , Adawiyah Robiatul , Alfarisi Ridho
Published: February 2025

Let $G=(V,E)$ be a simple, connected and un-directed graph, for $f:E(G)\rightarrow\{1,2,\dots, |E(G)|\}$, the weight of a vertex $v\in V(G)$ under $f$ is $w_f(v)=\Sigma_{e \in E(v)} f(e)$, where $E(v)$ is the set of vertices incident to $v$. The function $f$ is called vertex antimagic edge labeling if every vertex has distinct weight. While, rainbow vertex coloring is a coloring of graph vertices where each vertex on the graph is connected by a path that all internal vertices on the $u-v$ path have different colors. We introduce a new notion, namely a rainbow vertex antimagic coloring, which is a combination of antimagic labeling and rainbow vertex coloring. The rainbow vertex antimagic connection number of $G$, denoted by $rvac(G)$, is the smallest number of colors taken over all rainbow colorings induced by rainbow vertex antimagic labelings of $G$.  In this paper we aim to discover some new lemmas or theorems regarding to $rvac(G)$.
A Structural Equation Modeling of Teachers’ Job Satisfaction: An Application in Saudi Arabia-TALIS 2018
Authors: Altaf Bothinah
Published: February 2025

Structural equation modeling (SEM) is one of the indispensable multivariate statistical techniques for analyzingcomplex relationships in many fields. The education field has emerged as an active area of SEM applications due to the inherent nature of its interacting variables. This research applies SEM to provide an in-depth analysis of the factors influencing teachers’ job satisfaction in Saudi Arabia. The study draws upon data collected from Saudi teachers who participated for the first time in the Teaching and Learning International Survey (TALIS-2018). For this purpose, 2744 teachers and 192 principals from the secondary school level were selected using a stratified sampling strategy. The results indicated school climate, professional practices, motivation and participation, and student-teacher interaction significantly impacted teacher job satisfaction (β=0.35,0.12,0.17 and 0.21) respectively p-value=0.000. Not surprisingly, the stress construct negatively impacted job satisfaction with (β=-0.30) with p-value=0.000. Based on the results, teacher satisfaction can be enhanced by focusing on variables that have a significant influence and avoiding stress causes.
Victims of (State) Terrorism
Authors: Prasetyo Hery
Published: February 2025

The discussion of state power tends to elaborate on the problem of the legitimation of using force to deliver public goods. Seminal works by Machiavellian theoreticians stand on this argument and focus on developing a strong government that can control how the power works. There is a debate continuously elaborating on the nature of state power, mainly to present the humanist power relations; however, the problems of overuse of power and the fallen victims can not wait until academia makes a consensus. Moreover, with various governmental models, the state has a complex issue, such as the nexus between the plurality of social identity and other categories attributed to the citizens, which becomes essential to overcome the problems of unpredictable enemies with the most efficient strategist. Following these backgrounds, it is crucial to enhance knowledge about the variety of the implementation of state power to control, supervise, and docile the citizens. In doing so, first, figuring the concept of terrorism with multiple interpretations, in which states play their strategy to raise public awareness while elevating the regime of terror by creating a common enemy. Secondly, how has the technology to govern, with a technicalization of specific indicators, been used to count the risk and the possible number of victims. Lastly, concern about this condition leads to human rights fulfillment, particularly how the state's "conduct to conduct" can ensure citizens' well-being. As a point for reflection, this essay argues that state power has a paradox in delivering sovereignty; the challenge is how to construct social spaces that can reduce the overuse of power.
Peace agreement between ethics and aesthetics: the effects of the war on the art and culture of memory (case of Bosnia and Herzegovina)
Authors: Kreševljaković Nihad , Bajrović Hana
Published: February 2025

The siege of Sarajevo was the longest siege in contemporary human history. One of the characteristics of this period was an amazing response of artists to the situation they faced. As the result of that, artistic scene of Sarajevo in the period of 1992–1995 was one of the most interesting phenomena in all history of art in Bosnia and Herzegovina.
Letter to the Editor: “Aphasia Screening Test (TeRAp): Construction and Validation for European Portuguese”
Authors: Mourato Silva Cláudia
Published: February 2025

N/A
Mais de 20 pekenas suaves melodias feitas em formato pop pra serem tocadas com o sorriso do Ivon Cury e o vibrato do Monetário & Financeiro : para trompete, piano, violino e clarinete
Authors: Cozzella Levy Damiano , Taffarello Tadeu Moraes
Published: February 2025

O projeto Fomento, Editoração e Divulgação de Composições Musicais Brasileira, criado pela Profa. Dra. Sonia R. Albano de Lima e pelo Prof. Dr. Paulo Adriano Ronqui, em parceria com o CIDDIC – Centro de Integração, Documentação e Difusão Cultural da UNICAMP e CDMC – Coordenação de Documentação de Música Contemporânea (CDMC), tem a grata satisfação de publicar uma nova coletânea, contemplando as composições de Levy Damiano Cozzela, personalidade de extrema relevância para a produção musical paulista, seja como compositor, arranjador, maestro ou professor. O acervo de suas obras foi doado pela sua filha, Mariana Cozzella Carvalheira, e pela sua sobrinha, Flavia Lanna. Além da obra Mais de 20 pekenas suaves melodias feitas em formato pop pra serem tocadas com o sorriso do Ivon Cury e o vibrato do Monetário & Financeiro, idealizadas para trompete, piano, violino e clarinete, a publicação conta com parte da pesquisa realizada pelo Prof. Dr. Fernando de Oliveira Magre, que avaliou a vida e a obra do compositor. A organização da coletânea é de responsabilidade do Prof. Dr. Tadeu Moraes Taffarello, pesquisadores do Programa de Pós-Graduação em Música do IA-Unicamp e um dos criadores deste projeto.
On the Indian Tradition of Mathematical Names: A Scientific Analysis
Authors: Karn Ashish , Badoni Pankaj , Singh Raman Kumar
Published: February 2025

The current paper explores the potential interlink between names of individuals in a society and its collective social consciousness, particularly with reference to the pervasive occurrence of the ‘mathematical names’ in the current Hindu society in the Indian subcontinent and beyond. Initially, an attempt is made to put things into mathematical perspective by drawing a quick sketch of some of the stellar achievements of the Indian mathematicians. Under the six broad categories of geometry, trigonometry, numeration, arithmetic, algebra, and mathematics in the Vedic tradition, a concise simple description of these subdivisions is presented, underlining the names of the concepts and terms, sometimes by producing the textual references. Then, upon identification of such mathematical terms, an attempt is made to juxtapose these with the names current in the Indian Hindu society. By employing an extensive dataset of university student names in India and the directories of Facebook and LinkedIn, we produce both qualitative and quantitative evidence of the presence of such names in the Indian subcontinent. Evidently, these names reflect the impressions of the tremendously rich mathematical heritage left by the Hindu stalwart mathematicians. This hypothesis has also been examined by taking surveys of people bearing these mathematical names, as well as by documenting the ‘conscious procedures’ that go behind the naming of a Hindu Indian child. In trying to investigate if such a phenomenon is unique to the Indian tradition, a stark contrast with the ‘names in mathematics’ as prevalent in the European mathematical traditions is presented, as cultural roots of mathematics are explored. Further, we ascribe the presence of these names as the extant remains of the colossal impact of multifarious mathematical traditions existing in India. Interestingly, the present research also brings to the fore, certain unseen facets of the Indian Hindu society as regards the education of mathematics to women – through an indirect exploration of their names. We also show that the pervasive occurrence of these names is not merely the result of semantic chance events, but denotes the richness of the Indian mathematical legacy. Next, we also present cross-cultural comparisons to show the uniqueness of Indian mathematical and scientific traditions that led to the pervasiveness of ‘mathematical names’ in India. Finally, an attempt is made to clarify some subtle points on the associations between mathematics and religion in India and other cultures of the world. It is sincerely hoped that the present study may shed light on the cultural roots of mathematics and may furnish a new dimension in the study of mathematics, culture and civilizations across the world.
FlameViT: Wildfire Detection Through Vision Transformers for Enhanced Satellite Imagery Analysis
Authors: Makhija Aria
Published: February 2025

Recently, the destructive impact of wildfires has proliferated; for instance, the August Complex wildfire in 2020 burned around 4% of California's landmass. This has caused increased economic damage and risk to human life. Additionally, climate change is anticipated to increase the severity of wildfires, making it imperative for accurate and efficient detection of wildfires. Machine Learning approaches allow for the automatic detection of wildfires, simultaneously prioritizing accuracy and efficiency, with minimal human intervention, thus decreasing the likelihood of increased economic damage and increasing firefighting responses. Convolutional Neural Networks (CNNs), while showing promise, are often limited by their inability to learn and capture deep spatial dependencies in satellite imagery tasks. In this paper, we propose FlameViT, a novel wildfire detection architecture based on Vision Transformers (ViT). Satellite images are more efficient to obtain and can cover wide areas prone to wildfires. We obtain a dataset of 40K+ satellite images from Canada's Open Government Portal, allowing FlameViT to be optimized to detect wildfires in satellite imagery. FlameViT uses Patch Extractor and Patch Embedding layers, followed by multiple Transformer Encoder layers with Multi-Head Self-Attention and feed-forward neural networks. FlameViT is hyperparameter-tuned and achieves a validation accuracy of 95%, outperforming various baselines in the wildfire detection task. FlameViT shows the power of Vision Transformers for wildfire detection tasks, and in conjunction with the use of satellite imagery, can provide an efficient and accurate way of detecting wildfires.
Sixfold Discrete Symmetry of Fermion Fields as Explanation for Dark Matter
Authors: Nofech Avraham
Published: February 2025

We address the question, what is dark matter? The method used is the Pauli algebra form of the Dirac equation, equivalent to the standard one but allowing to use the multiplicative structure of the algebra. In this form discrete symmetries of fermion fields are the same as the automorphisms of the Pauli group. We construct the prototype Dirac equation in the Clifford algebra and then use its six representations by complex two by two matrices to construct the six symmetric versions, indexed by permutations of three letters. The solutions of symmetric equations form the six sectors of fermion fields. It is shown that the sectors are genuinely distinct, by proving that any fermion field belonging to two different sectors must have mass zero. Also shown is the lack of electromagnetic interaction between one sector and another, since each sector has its own matrix coupling the fermion field to the electromagnetic field. The key tool used is the mass inversion symmetry, introduced in []. The sixfold symmetry predicts the ratio of dark to ordinary matter of 5:1 which is close to the observed ratio of 5.2:1. However this symmetry is constructed only for interactions between fermion fields and the electromagnetic field, not yet taking into account the weak and strong interactions. So this article is an indication that maybe the complete answer can be found if the sixfold symmetry extends to these interactions.
Cardioprotective Activity of the Ethanolic Leaf Extract of Amaranthus viridis on Verapamil-Induced Heart Failure in Zebrafish (Danio rerio)
Authors: Rodriguez Leonel Paolo S. , Abalos Norielyn N.
Published: February 2025

Cardiovascular disease (CVD), a major global health concern, is characterized by cardiac complications that can lead to death. The commonly used treatments for this condition are synthetic drugs, but these often come with risky side effects. A potential alternative is the use of traditional medicinal plants, such as Amaranthus viridis, which is rich in bioactive compounds. This study aimed to determine the non-toxic concentration of A. viridis ethanolic extract, investigate its cardioprotective effects on zebrafish (Danio rerio) heart rate and cardiac phenotype, qualitatively assess the presence of phytochemicals, and assess its free radical scavenging activity using 2,2-diphenyl-1-picrylhydrazyl (DPPH). Zebrafish larvae at 72 hours post-fertilization (hpf) were used to evaluate mortality and optimize dosing. Physio-morphological screening was conducted by pre-treating zebrafish larvae with the extract 4 hours prior to administering a heart failure inducer, verapamil. The maximum non-toxic concentration was found to be 25 µg/mL, as all zebrafish survived after 24 hours. Mortality began at 50 µg/mL, and concentrations from 100 µg/mL to 400 µg/mL resulted in 100% mortality. All tested concentrations of A. viridis leaf extract showed cardioprotective activity in the physio-morphological analysis. Phytochemical analysis detected the presence of alkaloids, flavonoids, and saponins. Furthermore, A. viridis exhibited free radical scavenging activity from all tested concentrations. Based on the results, A. viridis exhibited cardioprotective effects against verapamil-induced cardiotoxicity, as evidenced by the recovery of heart rate and cardiac phenotype in the zebrafish model.
Bridging the Gap in ReID: A Fusion Approach to Integrating Motion Information in Static and Video Data
Authors: Tang Zhihao , Huang Guoqiang , Liu Hongye , Li Ling , Wu Hong
Published: February 2025

The challenge of accurately identifying individuals in different surveillance settings, particularly where obstructions occur, is significant in the field of person re-identification (ReID). We introduce a groundbreaking framework called the Motion-Aware FUsion (MAFU) network, crafted to utilize motion cues derived from static images to enhance the accuracy of ReID. This innovative network employs a dual-input mechanism that integrates the analysis of both still imagery and motion videos, improving the identification of crucial features. Key to our approach is the integration of a motion consistency task within the motion-aware transformer, facilitating precise detection and analysis of human movement dynamics. This development is vital for augmenting feature discernment in occlusion-heavy environments, thus advancing the ReID techniques. Rigorous evaluations across various ReID benchmarks, including tests tailored for occlusion, comprehensive, and video-based scenarios, demonstrate the superior performance of our MAFU network over existing models.
Towards Precision Psychiatry: An Advanced Machine Learning EEG Model for High‐Accuracy Schizophrenia Diagnosis
Authors: Montgomery Richard
Published: February 2025

Schizophrenia lacks clear biological diagnostic markers, but electroencephalography (EEG) has long been studied for distinguishing neural patterns of the disorder. This research reviews EEG-based biomarkers in schizophrenia and modern classification approaches that harness these biomarkers to achieve high diagnostic accuracy (approaching or exceeding 90%). We examine characteristic EEG signal abnormalities—including alterations in frequency band power (e.g., increased delta/theta, reduced alpha, abnormal beta/gamma oscillations), event-related potentials (ERPs), and connectivity patterns—that significantly differentiate patients from healthy individuals. Statistical and machine learning techniques (including support vector machines, random forests, and deep learning models) are discussed for their ability to recognize these patterns. Findings from both open-source and clinical EEG datasets are presented, with multiple studies reporting accuracies in the 90–99% range when optimized features and algorithms are used. Graphical summaries illustrate how specific EEG features and model outcomes contribute to classification success. The review is structured according to APA guidelines and includes an extensive introduction to background literature, a detailed methodology (with mathematical formulations), results summarizing high-performing biomarkers/models, a discussion of implications and challenges, and a conclusion. Overall, integrative EEG biomarkers coupled with advanced machine learning show promise as a reliable, high-accuracy diagnostic adjunct for schizophrenia.
Exogamy, Rites of Passage and Human Self-Domestication
Authors: Zhang Yan
Published: February 2025

Early scholars such as Darwin noted that a series of similar trait changes occurred between domesticated mammals and their wild counterparts, and that similar trait changes occurred in humans. Follow-up studies in recent years have further confirmed the findings of earlier scholars. These changes are known as domestication syndrome (DS). Human DS variation occurred over thecourse of two to three hundred thousand years before and after the formation of Homo sapiens, and is thought to be the result of human self-domestication. The main way to realize human self-domestication has been an important topic in recent years. And more than theoretical explanations have been proposed. In this paper, the main methods of previous research are briefly reviewed, and some related concepts are slightly revised. For example, the attributes and efficacy of selective reproduction in silver fox domestication experiments, the approximate correspondence between DS and the reduction of sexual dimorphism, and the correlation between DS causes and sexual selection.On this basis, this paper proposes a preliminary judgment on the causes of human DS that is different from the past : according to our present knowledge (empirical facts), there are two powerful drivers of DS variation, namely,exogamy and coming-of-age ceremony in tribal institutions. These two systems existed completely before the colonization of Australian tribes. This paper usesthe early classical ethnography of Australia by Fison, Howitt, Spencer, and Gillen to analyze and summarize the basic content of these two systems (reconstructing the original state of the system before colonization). Then, its domestication function and efficacy are discussed. Based on this, it is concluded that the joint effect of exogamy and coming-of-age ceremony is the main way for human beings to achieve self-domestication. We are very fortunate to have evidence about the Australian tribes in the early stages of civilization before colonization. We can trace their origins and examine their evolution accordingly. The alliance of two multimale-multifemale（mm-mf） groups through non-violent approach is the first step in the speciation of Homo sapiens.The tribal system formed in this historical link is the initial process of human civilization and an important foundation for human prosperity to this day.
Preclinical Validation of an Electrochemical Sensor for Alcoholism Monitoring in a Polydrug Self-Administration Animal Model
Authors: Garrido-Matilla Lucia , Maria Hormigo Roberto , Monago Maraña Olga , Marcos Alberto , Ambrosio Emilio , G. Crevillen Agustin
Published: February 2025

An electrochemical sensor for identification and monitoring of chronic alcohol abuse and alcoholism was preclinically validated by the analysis of plasma from polydrug-consuming rats (alcohol and cocaine). The sensor measures the glycosylation level of transferrin as an electrochemical index of glycosylation (EIG). Three rat groups were designed: saline group, cocaine group and cocaine-alcohol group. Moreover, two periods of withdrawal were studied, after 2 days and 30 days. The alcohol-cocaine group after 2 days of withdrawal showed significantly lower EIG values (p<0.1) than the rest of groups (saline groups, cocaine groups and alcohol-cocaine group after 30 days of withdrawal), so the sensor was able to identify the alcohol abuse in rats and the recovery of glycosylation level after 30 days of withdrawal, even combined with cocaine. Furthermore, the effect of sex was also considered. Receiver operating characteristic (ROC) curves were developed for each sex and the corresponding cut-off values were determined. The sensor showed a clinical sensitivity of 70% for male and 75% for female, and a specificity of 67% for both sexes. This preclinical validation demonstrated the possibilities of this sensor for point of care testing of chronic alcohol abuse, even in cocaine addicts, making it a potential tool for diagnosis and monitoring of alcohol consumption in detox treatments for humans.
Assessing DWI Positivity in Clinically Diagnosed TIA: Insights from a Cohort Study in Cluj, Romania
Authors: Arif Khaled Abu , Florian Ioan Stefan , Florian Alexandru Stefan , Blesneag Alina , Maer Enola , Chereches Razvan
Published: February 2025

The updated definition of TIA emphasizes tissue characteristics rather than symptom duration, defining TIA as a transient neurological episode without ischemic lesions on brain imaging, including DWI. If imaging reveals a lesion, even in patients with transient symptoms, the event is reclassified as a minor ischemic stroke. This retrospective cross-sectional study aimed to determine the period prevalence of ischemic lesions on DWI in patients with TIA diagnosis. Adults aged 18–90 years, diagnosed with TIA by a neurologist, and who underwent MRI-DWI at CMT hospital within the first week after symptom onset (May 2023–July 2024) were included. Ethical approval was obtained. Descriptive statistics summarized patient demographics, clinical features, Fazekas scale grades, and imaging findings. Among the 26 patients clinically diagnosed with TIA, 7 (26.9%) exhibited ischemic lesions on DWI, reclassifying these cases as minor ischemic strokes under the updated definition. The prevalence of ischemic lesions was notably higher in patients with comorbidities such as hypertension and diabetes. The findings highlight the importance of early MRI-DWI in accurately distinguishing TIAs from minor ischemic strokes. Routine urgent DWI within the first week of TIA symptoms enhances diagnosis, risk stratification, and guides targeted stroke prevention strategies, particularly when combined with the ABCD2 score.
Enhancing Yarn Strength Through Fiber Blending: A Study on Cotton/Polyester Blended Yarns
Authors: Islam Rofi Rofiul
Published: February 2025

Strength, elongation, and uniformity are just a few of the mechanical qualities of yarns that can be greatly enhanced by blending several fibers. With an emphasis on cotton/polyester blends, this study investigates how fiber blending affects yarn performance. The study assesses the variations in yarn strength and other physical characteristics by altering the blending ratio and yarn structure (stiff, core-spun, and dual-core-spun). The findings show that while decreasing unevenness and flaws, raising the polyester blend ratio improves yarn strength and elongation. Because of their increased elasticity, core-spun and dual-core-spun yarns are appropriate for uses that call for both strength and flexibility.
Unveiling the Future: A Comprehensive Review of Machine Learning, Deep Learning, Multi-model Models and Explainable AI in Robotics
Authors: Ali Toqeer , Khan Sohaib , Ali) Asad , Ahmad Naveed , Ahmad Sadique
Published: February 2025

The rapid advancements in artificial intelligence (AI) have significantly transformed the fields of machine learning, deep learning, and robotics. This comprehensive review aims to provide an in-depth survey of the current state of AI models, focusing on machine learning, deep learning, large language models (LLMs), and multimodal models. Special emphasis is placed on explainable AI (XAI) techniques, which are crucial for fostering transparency, trust, and collaboration between humans and robots. We begin by categorizing and summarizing the various machine learning and deep learning models, including supervised, unsupervised, ensemble, and reinforcement learning approaches. We also explore the latest developments in LLMs and multimodal models, highlighting their applications and potential in various domains. The core of this review delves into XAI techniques, discussing both model-specific and model-agnostic methods. We examine global and local explainability, intrinsic and post-hoc explanations, and their relevance to different AI applications. Moreover, we extend our discussion to explainable AI in robotics, covering topics such as human-robot interaction, autonomous robot transparency, interpretable learning for robotic control, collaborative robotics, safety, adaptability, and ethical considerations. By integrating these diverse perspectives, this review aims to provide a holistic understanding of the interplay between advanced AI models and explainability. Our goal is to highlight the importance of transparent and interpretable AI systems in enhancing the functionality and reliability of robotic applications, ultimately contributing to the development of trustworthy AI technologies.
Parental Death and Premature Mortality in Individuals with Experience of Out-of-Home Care: A Nationwide Cohort Study
Authors: Rogne Sandra , Almquist Ylva B. , Brännström Lars
Published: February 2025

Experiences of out-of-home care (placement in foster-family care or residential care) and parental death in childhood are known risk factors for premature all-cause mortality. However, it remains unclear whether parental death during placement moderates the association between out-of-home care and mortality, particularly when considering the timing and duration of placement. Longitudinal register data from 10 Swedish birth cohorts (n=948,483) were analyzed. Around 2.5% (n= 23,628) had out-of-home care experience during ages 0–19. Sex-specific Cox proportional hazard regression models assessed associations between experience of out-of-home care (categorized by timing and duration), parental death, and premature all-cause mortality (ages 20–47). Both men and women with out-of-home care experience displayed increased risk of premature all-cause mortality, as did those who experienced parental death before age 20. However, statistical interaction analyses revealed no moderating effect of parental death on the association between placement and premature all-cause mortality. Compared to non-placed individuals, parental death during placement in out-of-home care did not further increase the risk of premature mortality across placement groups. Possible reasons include strong attachments within the out-of-home care setting or reduced stress towards biological parents. Further research is needed to explore the complex dynamics of parental loss within out-of-home care populations.
Optimized Strategy for Energy Management in an EV Fast-Charging Microgrid Considering Storage Degradation
Authors: Paixão Joelson Lopes da , Abaide Alzenira da Rosa , Danielsson Gabriel Henrique , Sausen Jordan Passinato , da Silva Leonardo Nogueira Fontoura , Neto Nelson Knak
Published: February 2025

The current environmental challenges demand immediate actions, especially in the transport sector, one of the largest CO2 emitters. Vehicle electrification is considered an essential strategy for emission mitigation and combating global warming. This study presents methodologies for modeling and energy management of microgrids (MG), designed as charging stations for electric vehicles (EVs). Algorithms were developed to estimate daily energy generation and charging events in the MG. These data feed an energy management algorithm aimed at minimizing the costs associated with energy trading operations as well as the charging and discharging cycles of the battery energy storage system (BESS). The problem constraints ensure the safe operation of the system, availability of backup energy for off-grid conditions, preference for reduced tariffs, and optimized management of BESS charge and discharge rates, considering battery wear. The grid-connected MG used in the case study consists of a wind turbine (WT), photovoltaic system (PVS), battery energy storage system (BESS), and an electric vehicle fast-charging station (EVFCS). Located on a highway, the MG was designed to provide fast charging, extending the range of EVs and reducing drivers’ range anxiety. The study results demonstrated the effectiveness of the proposed energy management approach, with the optimization algorithm efficiently managing energy flows within the MG while prioritizing lower operational costs. The inclusion of the battery wear model makes the optimizer more selective in battery usage, operating it in cycles that minimize BESS wear and effectively prolong its lifespan.
From Grammont to a New 135° Short-Stem Design: Intraoperative 2-Hand-Lever-Test & Early Superior-Lateral Dislocations Reveal Critical Role of Liner Stability Ratio and Stem Alignment
Authors: Bauer Stefan , Mahlouly Jaad , Tolosano Luca , Blakeney William G , Shao Wei
Published: February 2025

Background: In reverse shoulder arthroplasty (RSA), the neck-shaft angle (NSA) has trended downward from 155° to 135° to reduce scapular notching, but concerns about instability persist. To assess superior-lateral stability, we developed the intra-operative 2-hand-lever-test (2HLT). This study evaluates the 2HLT's effectiveness, the learning curve with a new implant, and compares liner characteristics of 155° and 135° systems. Methods: In a single-surgeon learning curve study, 81 RSA procedures with the new Perform stem (Stryker) were included. Outcomes included the 2HLT test applied in 65 cases, early dislocations, stem alignment, stem length, liner type/thickness, and complications. The early dislocation rate was compared to 167 prior Ascend Flex RSA procedures (Stryker). Liner characteristics of three 135° systems (Perform/Stryker; Univers/Arthrex; Altivate/Enovis) were compared to traditional 155° Grammont systems (Delta Xtend/DePuy; Affinis Metal/Mathys; SMR 150/Lima, Aequalis Reversed/Stryker), focusing on jump height (JH) and liner stability ratio (LSR). Results: In 75% (49/65) of cases, the 2HLT detected superior-lateral instability, influencing implant selection. The early dislocation rate in the Perform cohort was 4.9% (0% with retentive liners, 8% with standard liners) versus 0% in the Ascend Flex cohort. The mean effective NSA was 133° (127°-144°) for short Perform stems and 135° (129°-143°) for long stems. Long Perform stems significantly reduced varus outlier density below 132° and 130° (p=0.006, p=0.002). The 36mm Perform 135° standard liner has a JH of 8.1mm and LSR of 152%, markedly lower than the Altivate (10.0mm/202%) and Univers (9.7mm/193%) and similar to traditional 155° Grammont liners (8.1-8.9mm/ 147%-152%). Perform retentive liners have LSR values of 185%-219%, comparable to established 135° design standard liners (195%-202%). In the Perform cohort, early complications included 4 superior-lateral dislocations (all standard liners, LSR 147%-152%) requiring 4 revisions. Conclusions: The 2HLT effectively identified superior-lateral instability and guided implant selection. Perform standard liners have a lower LSR and JH than established 135° designs, contributing to superior-lateral instability, particularly with an effective NSA < 135°. Retentive Perform liners with an LSR > 184% have a similar LSR compared to standard liners of established 135° designs and effectively mitigated instability. We recommend discontinuing the use of non-retentive Perform RSA liners (LSR <158%).
Molten Salt Electrolyte for Na-ZnCl2 All Liquid Battery for Grid Storage
Authors: Ding Wenjin , Hoffmann Ralf , Kjos Ole S. , Weber Norbert , Weier Tom , Bauer Thomas
Published: February 2025

Zeolite Battery Research Africa (ZEBRA) batteries (Na-NiCl2 solid electrolyte batteries, SEBs) have commercial applications in, e.g., energy storage due to their low costs and recyclability, long lifetime and high safety. In commercial ZEBRA batteries, Ni electrode and beta’’-alumina solid electrolyte (BASE) have a > 70% share of the cell material costs. Na-ZnCl2 all liquid batteries (ALBs), which replace Ni with abundant and low-cost Zn and BASE electrolyte with molten salt electrolyte, could have lower costs, longer lifetime and higher safety, are therefore promising as grid storage. However, compared to SEBs, ALBs are in an early development stage, particularly on their molten salt electrolytes, which have significant effect on the battery performance. The physical and chemical properties of the salt electrolyte like melting temperatures and solubilities of electrode materials (i.e., Na and Zn metal) are vital for the molten salt electrolyte selection, battery cell design and optimization. In this work, the binary and ternary phase diagrams of salt mixtures containing NaCl, CaCl2, BaCl2, SrCl2, KCl, obtained via FactSage simulation and DSC measurements and the solubilities of electrode materials are presented and used for the selection of the molten salt electrolyte. There are multiple criteria for the selection of the molten salt electrolyte, including high electromotive force (EMF) for suitable electrochemical properties, low melting temperature for large charge/discharge range, low solubilities of electrode materials for low self-discharge, low material costs and high material abundance for easy scale-up. According to these criteria, the NaCl-CaCl2-BaCl2 and NaCl-SrCl2-KCl salt mixtures are selected as the two most promising ALB molten salt electrolytes, which are suggested to be tested in the ALB demonstrators under development.
SAAS-Net: Self-supervised Sparse SAR Imaging Network with Azimuth Ambiguity Suppression
Authors: Jin Zhiyi , Pan Zhouhao , Zhang Zhe , Qiu Xiaolan
Published: February 2025

Sparse Synthetic Aperture Radar (SAR) imaging has garnered significant attention due to its ability to suppress azimuth ambiguity in under-sampled conditions, making it particularly useful for high-resolution wide-swath (HRWS) SAR systems. Traditional compressed sensing -based sparse SAR imaging algorithms are hindered by range-azimuth coupling induced by range cell migration (RCM), which results in high computational cost and limits their applicability to large-scale imaging scenarios. To address this challenge, the approximated observation-based sparse SAR imaging algorithm was developed, which decouples the range and azimuth directions, significantly reducing computational and temporal complexities to match the performance of conventional matched filtering algorithms. However, this method requires iterative processing and manual adjustment of parameters. In this paper, we propose a novel deep neural network-based sparse SAR imaging method, namely Self-supervised Azimuth Ambiguity Suppression Network (SAAS-Net). Unlike traditional iterative algorithms, SAAS-Net directly learns the parameters from data, eliminating the need for manual tuning. This approach not only improves imaging quality but also accelerates the imaging process. Additionally, SAAS-Net retains the core advantage of sparse SAR imaging—azimuth ambiguity suppression in under-sampling conditions. The method introduces self-supervision to achieve orientation ambiguity suppression without altering the hardware architecture. Simulations and real data experiments using Gaofen-3 validate the effectiveness and superiority of the proposed approach.
Spatial Analysis of the Determinants of HIV/AIDS Among Females Aged 15–34 in KwaZulu Natal, South Africa Using a Bayesian Spatial Logistic Regression Model
Authors: Chireshe Exaverio , Chifurira Retius , Chinhamu Knowledge , Batidzirai Jesca Mercy , Kharsany Ayesha B.M.
Published: February 2025

HIV remains a major public health challenge in sub-Saharan Africa, with South Africa bearing the highest burden. KwaZulu-Natal (KZN) has been identified as a hotspot, particularly among females aged 15–34. This study aimed to investigate the spatial distribution and key socio-demographic, behavioural, and economic factors associated with HIV prevalence among females in this age group using a Bayesian spatial logistic regression model. We analysed secondary data from 3324 females who participated in the HIV Incidence Provincial Surveillance System (HIPSS) from June 2014 to July 2015 in uMgungundlovu District, KZN. Bayesian spatial models were fitted using the Integrated Nested Laplace Approximation (INLA) to identify key predictors and spatial clusters of HIV prevalence. Results revealed that age, education, marital status, in-come, alcohol use, condom use, and number of sexual partners significantly influenced HIV prevalence. Higher age groups (20–34 years) had increased odds of HIV infection compared to those aged 15–19. Alcohol use, multiple partners, and STI/TB diagnosis elevated risk, whereas tertiary education and condom use were protective. Two HIV hotspots were identified, with one near Greater Edendale being statistically significant. Findings highlight the need for targeted, context-specific interventions to reduce HIV transmission among young females in KZN.