bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving Online Security: A Deep Learning Model for Phishing URL Detection
Authors: bourigue rachid , OMAR Driss AIT , ZOUGAGH Hicham 
Published: November 2024

Abstract

Today, phishing attacks have become a sig-nificant threat to online security. These false fronts areused to mislead people and businesses into clicking onmalicious URLs, revealing their password, credit cardinformation, or personal data. Infiltrating fraudulentwebsites or fake apps: Cybercriminals are upping theirgame by creating more and more representative de-signs of what to the inexperienced user seems like a“trustworthy” site, where they can be misled to entertheir username and password. Various methods such asblacklist, whitelist, heuristic exchange features, and vi-sual similarity-based techniques are being proposed foranti-phishing. Modern browsers come to help and limitthe way users can be phished into a vicious agenda,but yet, users fall prey to these obvious attacks and re-veal their secret data. In earlier research, the authorsintroduced a machine-learning approach for detectingphishing websites, achieving an accuracy of 96.85% with87 features. In this paper, we present new phishingURL detection models based on a Deep Neural Net-work (DNN) using the same dataset and 87 featuresfrom the previous work. The proposed method achievesa higher accuracy of 99.43% with DNN. Additionally,cross-validation is employed to enhance robustness andimprove the speed of phishing detection
Synthesis and Molecular Modelling Studies of Some New Phthalonitriles And Their Inhibitory Potencies Against Cholinesterases (AChE/BChE)
Authors: Tekin Aşkın , Mercan Esra Özbek , Arslan Tayfun 
Published: November 2024

Abstract

This study presents the synthesis, characterization and evaluation of novel phthalonitrile derivatives for their inhibitory effects on acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), crucial enzymes in the pathogenesis of Alzheimer's disease (AD). Since the progression of AD is characterized by progressive memory loss, therapeutic strategies often target these cholinergic enzymes to alleviate symptoms. Using the Claisen-Schmidt condensation and the Debus-Radziszewski reaction, phthalonitriles with potential biological significance were synthesized in this study. Among the derivatives, compound B4 with an imidazole ring showed potent inhibitory activity against both AChE and BChE in the low nanomolar range, surpassing the efficacy of conventional inhibitors. Molecular docking confirmed the binding affinity of B4 to the active sites of the enzymes, suggesting that it is a leading compound for Alzheimer's therapy. This work contributes to the treatment of AD by presenting phthalonitrile derivatives as promising candidates for further therapeutic development.
A study of YangHe Decoction delaying the progression of osteoarthritis by inhibiting chondrocyte ferroptosis through the P53/SLC7A11/GPX4 signaling axis
Authors: Li Wenkai , Zhuang Chen , Ying Yuou , Zhou Xing , Wang Likang , Chen Yixuan , Su Hui , Yan Zechen , Liu Luyao , Zhu Kangxiang , Yan Yiqin , Pan Yu 
Published: November 2024

Abstract

Background and Objective: Osteoarthritis (OA) is a chronic degenerative disease characterized by damage and potential loss of articular cartilage for which there is no effective treatment. YangHe Decoction (YHD), a traditional Chinese herbal formula used for the treatment of OA, has been shown to have anti-inflammatory properties, which may be an effective strategy for the treatment of OA. The objective of this study is to investigate the potential mechanism of YHD and its main active ingredient for inhibiting ferroptosis in chondrocytes and for the treatment of OA. Methods: Possible targets and processes of YHD and OA were forecasted using network pharmacology, including relationships between cross-targets of YHD and OA, obtaining key potential targets through PPIs, and revealing possible mechanisms of YHD on OA through GO and KEGG pathway enhancement analyses. Subsequently, in vitro experiments confirmed the expected underlying process. Finally, an in vivo model of DMM-induced C57BL/6 mice model was constructed to validate that YHD ameliorates cartilage degradation and delays the progression of OA. Result: Utilizing a comprehensive approach encompassing network pharmacology, molecular docking, and experimental validation, we have demonstrated that YHD effectively mitigates cartilage degeneration and hinders OA progression in mice in vivo by suppressing IL-1β-mediated ferroptosis within chondrocytes. Conclusion: Our study revealed that YHD was able to slow down osteoarthritis (OA) progression by inhibiting ferroptosis in chondrocytes via the P53/SLC7A11/GPX4 axis.
Optimizing Quality Tolerance Limits Monitoring in Clinical Trials Through Machine Learning Methods
Authors: Yan Lei , Yu Ziji , Wu Liwen , Liu Rachael , Lin Jianchang 
Published: November 2024

Abstract

The traditional clinical trial monitoring process, which relies heavily on site visits and manual review of accumulative patient data reported through Electronic Data Capture system, is time-consuming and resource-intensive. The recently emerged risk-based monitoring (RBM) and quality tolerance limit (QTL) framework offers a more efficient alternative solution to traditional SDV (source data verification) based quality assurance. These frameworks aim at proactively identifying systematic issues that impact patient safety and data integrity. In this paper, we proposed a machine learning enabled approach to facilitate real-time, automated monitoring of clinical trial QTL risk assessment. Unlike the traditional quality assurance process, where QTLs are evaluated based on single-source data and arbitrary defined fixed threshold, we utilize the QTL-ML framework to integrate information from multiple clinical domains to predict the clinical QTL of variety types at program, study, site and patient level. Moreover, our approach is assumption-free, relying not on historical expectations but on dynamically accumulating trial data to predict quality tolerance limit risks in an automated manner. Embedded within ICH-E6 recommended RBM principles, this innovative machine learning solution for QTL monitoring has the potential to transform sponsors’ ability to protect patient safety, reduce trial duration, and lower trial costs.
Blockchain enabled Deep Learning Architectures to Secure IoT and Edge Computing in Supply Chain Management for Industry 4.0
Authors: Samriya Jitendra Kumar , Kumar Amit , Bhansali Ashok , Singh Virendra ,   5Deepak Kumar Mishra, Tripathi Pragati 
Published: November 2024

Abstract

Blockchain has been widely used in Internet of Things (IoT) applications to ensure data confidentiality, consistency and traceability. Integration of blockchain and edge computing improves the resource utilization across network, computation, storage, and security. This paper presents a novel method to address data transmission, communication overhead, security and privacy along with accuracy in IoT application integrating cloud edge environments using deep learning techniques. In addition, Blockchain technology has been incorporated to avoid the cyber-attacks in supply chain management and secure data transmission has been enhanced using Voxel Convolutional networks. The experiments are conducted to evaluate and analyse data transmission ratio, specificity, training accuracy, and validation accuracy. The computational results of our approach show a significant improvement in data privacy and communication security with data transmission ratio up to 89%, validation accuracy 89%, specificity of 75%, training accuracy 95%, and security analysis 91%.
Atomic-Level Insights into the Nanocluster to Quantum Dot Transition of CdSe from DNP-NMR
Authors: McDermott Ann , Xu Yunyao , Zhang Lichirui , Sergeyev Ivan , Greenberg Matthew , Saenz Natalie , Beecher Alexander , Friesner Richard , Owen Jonathan 
Published: November 2024

Abstract

Achieving control over quantum dot (QD) size is essential for their performance but remains difficult due to the limited atomic-level understanding of QD growth. Using signal-enhanced solid-state NMR (SSNMR), we examined structural features of intermediate CdSe clusters and mature QDs. The intermediates, with four distinct site types, pose a challenge in determining ligand distribution across their surface. By integrating quantum computation with experimental data, we assigned NMR peaks to specific Cd binding environments and found that ligand distribution is optimized through inter-ligand hydrogen bonds, which stabilize the ligand layer and counteract the steric constraints of ligand packing on planar facet. 113Cd NMR provided insights into local Cd environments, offering a framework for monitoring structural transitions and improving size control during QD growth.
Complementary competing risks for bivariate generalized Rayleigh distribution under maximum ranked set sampling
Authors: Alok Arvind Kumar , Singh Garib Nath , Chandra Prakash 
Published: November 2024

Abstract

In this article, inference for a competing risk model is discussed when the cause of failures of units is dependent on using the maximum ranked set sampling (MaxRSS) approach. When the latent failure times follow the bivariate generalized Rayleigh distributions, inference for unknown parameters is obtained using frequentist and Bayesian approaches. Maximum likelihood estimators of the unknown parameter and its existence and uniqueness are also provided. Subsequently, approximate confidence intervals have also been constructed based on the observed Fisher information matrix. In competing risk, it is obvious that one risk is at a higher risk than the other, the MLE of the parameter has been discussed under re-parameterization of the parameter. Further, Bayes estimates have been discussed using informative and non-informative (Jeffrey's and reference) prior under the squared error loss function. Moreover, the associated highest posterior density credible interval is also developed. The performance of various estimators is evaluated based on extensive simulation study, and comments are obtained. Finally, two different real-life applications are also provided for illustrative purposes.
Modelling Home Range and Intraspecific Spatial Interaction in Wild Animal Populations
Authors: Bayisa Fekadu L. , Seals Christopher L. , Leeper Hannah J. , Steury Todd D. , Ceyhan Elvan 
Published: November 2024

Abstract

Interactions among individuals from the same-species of wild animals are an important component of population dynamics. An interaction can be either static (based on overlap of space use) or dynamic (based on movement). The goal of this work is to determine the level of static interactions between individuals from the same-species of wild animals using 95\% and 50\% home ranges, as well as to model their movement interactions, which could include attraction, avoidance (or repulsion), or lack of interaction, in order to gain new insights and improve our understanding of ecological processes. Home range estimation methods (minimum convex polygon, kernel density estimator, and autocorrelated kernel density estimator), inhomogeneous multitype (or cross-type) summary statistics, and envelope testing methods (pointwise and global envelope tests) were proposed to study the nature of the same-species wild-animal spatial interactions. Using GPS collar data, we applied the methods to quantify both static and dynamic interactions between black bears in southern Alabama, USA. In general, our findings suggest that the black bears in our dataset showed no significant preference to live together or apart, i.e., there was no significant deviation from independence toward association or avoidance (i.e., segregation) between the bears.
Predicting US Elections: A Machine Learning Approach
Authors: Gadde Nishant , Kumar Sanjit , Altaf Rayaan , Bharath Shreyas 
Published: November 2024

Abstract

This study introduces a cutting-edge machine learning framework specif- ically developed to forecast the results of highly competitive political races, focusing on the 2018 Texas Senate election between Senator Ted Cruz and Beto O’Rourke. By utilizing a comprehensive dataset compris- ing historical election results from 2008 to 2016, granular polling data, and the relative importance of key campaign issues across counties, we employ advanced machine learning techniques, including Random Forest and Gradient Boosting, to construct a highly accurate predictive model. This hybrid approach effectively captures complex voting behavior pat- terns, enabling the model to predict Cruz’s statewide vote share with a minimal error margin of just 0.89%. The model’s precision not only under- scores the potential of machine learning to revolutionize election forecast- ing but also offers actionable insights that can significantly impact strate- gic decision-making in political campaigns. For Cruz’s team, the ability to predict electoral outcomes with such accuracy provides a competitive advantage in resource allocation, voter outreach, and issue prioritization. The model identifies critical factors—such as the economy, immigration, and healthcare—driving voter preferences, allowing the campaign to tailor its messaging and mobilization efforts more effectively. Furthermore, this framework can be adapted for future campaigns, providing a dynamic, data-driven tool that enhances Cruz’s ability to anticipate shifts in voter sentiment and strategically respond to emerging challenges.
Smartphone-based Step Counts as an Independent
Digital Biomarker of Survival in ALS Patients
Authors: Matabuena Marcos , Straczkiewicz Marcin , Calcagno Narghes , Burke Katherine M. , Royse Timothy B. , Iyer Amrita , Carney Kendall T. , Hall Sydney , Berry James D. , Onnela Jukka-Pekka 
Published: November 2024

Abstract

Amyotrophic lateral sclerosis (ALS) is a progressive debilitating disease. Digital biomarkers obtained from smartphone data may allow for scalable, remote, unobtrusive, quantitative measurement of physical activity (PA) and could provide efficient outcome measures for ALS trials. Smartphone activity data may also have a role in predicting ALS prognosis. This study compares the effect of adding baseline smartphone PA variables for predicting ALS survival, which improves ALS survival prediction C-score by 20 percent after adjusting for traditional ALS baseline progression biomarkers. These results show that smartphone-based digital biomarkers are promising tools for ALS prognosis prediction.
Religia starożytnych Izraelitów w czasach podzielonej monarchii w świetle inskrypcji z Kuntillet ‘Ajrud i tradycji żydowskiej
Authors: Mączyński Tomasz 
Published: November 2024

W latach 70. XX w. zespół archeologów z Uniwersytetu w Tel Awiwie prowadził badania na stanowisku w Kuntillet ‘Ajrud. Znaleziono tam pochodzące z VIII w. p.n.e. inskrypcje, spośród których część stanowiły błogosławieństwa „przez imię Jahwe i jego aszerę”. Te ostatnie słowa mogą stanowić dowód nie tylko na utrzymywanie się politeizmu wśród Izraelitów w okresie podzielonej monarchii, ale także na to, iż – według ich wierzeń – małżonką Jahwe była bogini Aszera. Analiza tekstu biblijnego i innych źródeł żydowskich pokazuje, że słowo aszera może odnosić się do obiektu kultowego, a nie bogini, co znacząco zmienia wydźwięk inskrypcji.
Oficjum Ave Gmma Claritatis w źródłach XIII-XVI wieku
Authors: Grajewski Czesław 
Published: November 2024

Autor analizuje oficjum Ave gemma claritatis o św. Katarzynie Aleksandryjskiej. Występuje ono w niewielu źródłach, głównie z terenu Francji i centralnej Europy (Polska, Węgry). Autor wydzielił sześć zasadniczych grup manuskryptów i starodruków, w których repertuar śpiewów jest zbliżony. Materiał analityczny pokazuje, że układ antyfon w oficjum był bardziej stabilny niż układ responsoriów. Najbardziej odpornymi na zmiany okazały się Laudesy.
Therapeutic Effectiveness of Prunus dulcis for Nephroprotective and Hepatoprotective in Albino Mice
Authors: Sharma Rajesh Kumar , Jha Nidhi , Mishra Anurag , Singh Gamdur , Sanwelka Madhvi , Gupta Ashish 
Published: November 2024

Background:
Nephrotoxicity caused by GM is a complicated occurrence that results in a variety of structural and functional changes, including lesions in the
glomerular region and proximal tubule damage, which leads to sudden kidney failure. The production of reactive oxygen species (ROS) has also
been linked to GM. Acute hepatic impairments caused by medication might lead to rapid deterioration of liver function.

Objective:
The purpose of this study was to evaluate the suspension of nuts of Prunus dulcis at a lower dose (800 mg/kg, b.w.) and a higher dose (1600
mg/kg, b.w.) for nephroprotective and hepatoprotective activities.

Materials and Methods:
Drug-induced nephrotoxicity and drug-induced hepatotoxicity models were used to evaluate the nephroprotective and hepatoprotective activity
using albino mice. A histopathological study was also performed.

Results:
Suspension of nuts Prunus dulcis exhibited significant nephroprotective and hepatoprotective activity. Suspension of nuts from Prunus dulcis at a
higher dose (1600 mg/kg b.w.) showed higher nephroprotective and hepatoprotective activity compared to the lower dose (800 mg/kg). The
nephroprotective activity was evident by decreased serum creatinine, uric acid, serum urea, and BUN, which were confirmed by histological study.
The hepatoprotective effect was confirmed by significantly decreased serum alanine transaminase (ALT), aspartate transaminase (AST), alkaline
phosphatase (ALP), total protein, and total bilirubin levels in treated groups, which were further confirmed by histopathological study.

Conclusion:
The result suggests that Prunus dulcis possesses nephroprotective and hepatoprotective activities.
Inclusión y exclusión en la escuela
Authors: Ferrada Hurtado Rocío , Otárola Cornejos Fabiola 
Published: November 2024

El artículo muestra las características que las y los docentes atribuyen a los estudiantes “incluidos” y “excluidos” en sus escuelas, obtenidas de un cuestionario aplicado a 180 docentes de establecimientos públicos de la región de Valparaíso y Metropolitana (Chile). Las respuestas revelan el predominio de características de tipo “escolar” para definir la cualidad de incluido de un estudiante (buen rendimiento, buen comportamiento, respeto a las normas), en detrimento de características que derivarían del modelo normativo de inclusión escolar. En complemento, se desprende de estas respuestas docentes una noción equívoca de inclusión, y su comprensión como un artificio, en el sentido de asociarla con acciones dirigidas a remediar la distancia de ciertos estudiantes respecto de las normas escolares. Se concluye la necesidad de estudiar el uso práctico que los docentes hacen de estas calificaciones y sus consecuencias en términos de inclusión escolar.
الكفاءة التربوية لمعلمي اللغة العربية في المدارس الثانوية ببندا أتشيه
Authors: Novita Bella Disa , Hayati Salma , Fadhilah Fadhilah 
Published: November 2024

This study aims to determine the level of pedagogic competence of Arabic language teachers in MTs throughout Banda Aceh. This research is quantitative research with the research method taken is the survey method. The research instrument used was a questionnaire distributed to a number of 21 Arabic teachers at MTs throughout Banda Aceh City. Data analysis used descriptive statistics (Mean, Percentage, Standard deviation, and Frequency). The results showed that the level of pedagogic competence of Arabic language teachers in MTs throughout Banda Aceh was in the high category. This research implies that the pedagogical competence of teachers is very good in carrying out Arabic language learning.
MTsS Darul Ulum Banda Aceh وتطبيقها لترقية على مهارة القراءة بـ Rolling Ball وسيلة
Authors: Fajriah Fajriah , Kautsara Zulfina 
Published: November 2024

Based on the result of the observation in grade 2 (2) students at MTsS Darul Ulum Banda Aceh, there had some difficulties for the students in reading skiil, the students unable to understand the text well. The aim of this study is to know the effectiveness of the rolling ball media used to increase students’reading skiil. In this study, the researcher applied the pre-experimental method through one group pre -test post –test design. Samples of this research are 22 students in grade 2 (2) students at MTsS Darul Ulum Banda Aceh. To collect the data, the researcher used the test. The result of this research is the using of rolling ball media is effective to increase students’reading skiil in grade 2 (2) students at MTsS Darul Ulum Banda Aceh . Furthermore, it was found that the result of the T-Test is a significance level (2- tailed) 0.00<0.05.
Haroldo de Campos: diálogos intersemióticos na transcriação da poesia chinesa
Authors: Batista André Luis , Faria Alexandre Graça 
Published: November 2024

Entre os mais diversos horizontes de possibilidades que os trabalhos do poeta, teórico e tradutor Haroldo de Campos sinalizam, este artigo propõe analisar o fenômeno de tradução da poesia chinesa, configurado por Campos em seu livro escrito sobre jade: poesia clássica chinesa reimaginada por Haroldo de Campos, como modelo de transcriação intersemiótica. É a partir de sua incursão nos estudos sobre a língua e a arte literária chinesa que Haroldo propõe um distanciamento do percurso da tradução segundo o processo comum de literalidade dos significados linguísticos, para sinalizar a formação de um modelo tradutório de reconstituição dos elementos simbólicos culturais. Conceituado como “tradução-tradição”, a transcriação haroldiana busca um processo de reimaginação, cujo objetivo é o da recriação da tradição da poesia chinesa, a partir de uma nova moldura que possibilite o reconhecimento dessa tradição. Esse caminho aponta para uma possível recognição de signos linguísticos visuais como tradutores da presença da língua e da cultura chinesa, processo de diálogo que se daria a nível semiótico, possibilitado pela transcriação. No que concerne a proposta de Haroldo, trata-se então, assim se entende, da configuração da ação tradutória como percursos intersemióticos, cujos potenciais de leitura abrem-se para o exame das imagens poéticas como elementos vivos de uma tradição cultural.
Os Estudos da Tradução Literária no Brasil: história, teoria e crítica
Authors: Assis Roberto Carlos de , Pereira Germana Henriques 
Published: November 2024

Os Estudos da Tradução, em especial os Estudos da Tradução Literária, que é o foco deste dossiê, encontraram solo fértil no Brasil e em outros países, e assim, o Dossiê Tradução Literária: história, teoria e crítica abriu espaço para pesquisas que buscam entender como a tradução de textos literários e os Estudos da Tradução Literária têm se organizado bem como aquelas que identificam as correntes críticas e teóricas da tradução literária, os agentes – sejam eles, pesquisadores, teóricos, tradutores, editores, agências de fomento – , as normas que regem a tradução literária bem como a circulação de obras literárias traduzidas. Enfim, buscou-se reunir mapeamentos que contribuem para a construção da história da tradução literária no Brasil a fim de orientar pesquisas e passos futuros.