bluuebunny/crossref_metadata_2025_split huggingface dataset:
La seguridad ciudadana como derecho esencial. El cambio de paradigma
Authors: Toledo Jerez Gustavo Ernesto 
Published: February 2025

Colombia tiene problemas de seguridad, desbordados en todas las modalidades existentes: un conflicto armado interno, delincuencia de cuello blanco, además de organizaciones criminales que operan desde las esferas cibernéticas, otras con fines de narcotráfico y control territorial, pero además delincuencia común, se encuentra que los gobiernos han mantenido una política criminal sin sustento, basados en la represión y la prevención general como símbolo y sustentados en la doctrina del enemigo interno (Suescún, 2014), y el devenir del conflicto armado. Actualmente, el país pasa por una transición del modelo político y económico que promete dar un enfoque distinto del manejo de la política criminal.
El presente trabajo pretende demostrar que la política de seguridad del Estado ha fracasado. Sostiene también que la criminología aplicada es la herramienta de tratamiento del crimen, el cual, permite explicar y establecer las causas, pero también los controles y tratamientos efectivos a los fenómenos criminógeno colombiano, del delincuente, de la víctima y del control social, para atender, de manera integral, los fines de la pena, y así el Estado pueda sustentar sus decisiones en materia de política y consecuente instrumentalización a través del Derecho Penal.
Para comenzar, se abordará el fenómeno de la seguridad desde una perspectiva histórica, con el objeto de exponer circunstancias y consecuentes acciones que han tomado los gobiernos colombianos. Acto seguido, se abordará el estado del arte de la política de seguridad, atendiendo a las conclusiones, opiniones y recomendaciones de los diferentes informes y estudios de las diferentes agencias privadas y públicas. Luego, con una mirada comparada entre la legislación de la unión europea y el colombiano, se evidenciaron las diferentes tendencias socio-políticas, con el objeto de concluir sobre la necesidad de la implementación de la criminología en el ordenamiento jurídico colombiano, como herramienta de fundamentación de la política criminal para atender la garantía de la seguridad ciudadana del Estado Colombiano.
Archaeal LOV domains from Lake Diamante: first functional characterization of a halo-adapted photoreceptor
Authors: Valle Lorena , Coronel Yonathan J. , Bravo Guillermina E. , Díaz Joaquín A. , Albarracín Virginia H. , Farías María E. , Abatedaga Inés 
Published: February 2025

Abstract

High-altitude Andean lakes (HAALs) represent polyextreme environments where diverse photoinduced processes have been documented. In this study, we investigated Light-Oxygen-Voltage (LOV) photoreceptors and identified 28 archaeal sequences from Lake Diamante, which were classified into two major groups (A and B), with three outliers showing unique structural features. Analysis of these sequences and their 3D models revealed hallmark adaptations to halophilic environments, including an abundance of surface acidic residues, an increased prevalence of arginine over lysine, and a greater density of salt bridges. The heterologous expression of a representative LOV domain, ALovD-1, demonstrated conserved photophysics between its dark- and light-adapted states, which was consistent with the slow cycling type. Importantly, ALovD-1 exhibited remarkable halophilic characteristics, maintaining photocycling functionality at salt concentrations as high as 3 M monovalent salts. This ability can be attributed to discrete structural changes, allowing adjustments in flavin interactions within its cavity under varying ionic strengths. Mutational studies of key residues (Y30F and Y48F) highlighted their roles in modulating flavin photophysic and revealed a stabilizing function for Y48 at low salt concentrations. These findings mark the first functional characterization of a canonical archaeal LOV domain, expanding our understanding of light sensing and protein adaptation in extremophiles.
Artificial Intelligence and Machine Learning-Based Prediction of Cardiovascular Disease Risk in Rural Elderly Women in North-East India: Insights into Women's Health, HDL, Metabolic Syndrome, and Key Biomarkers
Authors: Ghosh Joyeta , Chaudhuri Tinni , Taneja Jyoti , Kant Ravi 
Published: February 2025

Abstract

Background: This study aimed to leverage artificial intelligence and machine learning approaches to predict cardiovascular disease (CVD) risk among rural postmenopausal women in North-East India. The objectives included identifying critical risk factors and evaluating the performance of various machine learning models to enhance CVD prediction accuracy in rural populations.
Methods: The research was conducted in Singur Block (West Bengal) and Amdanga Block (North 24 Parganas District) over a span of four years, from March 2014 to August 2018. Key risk factors, including waist circumference, blood pressure, fasting blood glucose, and HDL cholesterol, were collected and analyzed. A correlation matrix was employed to assess the associations between these variables and CVD risk. Additionally, eight machine learning models were deployed to predict CVD risk, with performance comparisons to identify the most effective algorithm.
Results: The correlation analysis revealed strong associations between CVD risk and factors such as waist circumference, blood pressure, and fasting blood glucose, with HDL cholesterol playing a lesser yet relevant role. Among the machine learning models tested, the Random Forest algorithm achieved the highest accuracy of 98.91%, followed by Decision Tree and Support Vector Classifier (SVC), both of which achieved accuracies exceeding 95%. Feature important analysis highlighted waist circumference as the most significant predictor, with blood pressure and fasting blood glucose also contributing substantially to the prediction of CVD risk, while HDL cholesterol had a comparatively lower but still notable impact.
Conclusion: Machine learning techniques, particularly the Random Forest model, demonstrated remarkable efficacy in predicting CVD risk among rural postmenopausal women. This study identifies waist circumference, blood pressure, and fasting blood glucose as key predictors, emphasizing the potential of machine learning-based approaches as cost-effective, scalable solutions for early CVD detection. These findings provide a foundation for targeted preventive measures and improved health outcomes in underserved rural settings.
Impact of Living Arrangements on Burnout, Loneliness and Substance Use among Kazakhstan University Students
Authors: Mynbayeva Aigerim , Stelmakh Svetlana , Satkangulova Gulnara , Sarkisyan Liliya , Reznik Alexander , Isralowitz Richard 
Published: February 2025

Abstract

Kazakhstan is a large Central Asian country of the former Soviet republic with a population of 19 million, the majority being Muslim with moderate religious practices. Despite considerable economic growth, most university students remain pressed to address higher education and living costs. This cross-sectional study of 2,065 students examined living conditions and its association with burnout, loneliness and substance use. Female students, and those using harmful substances, were more likely to report burnout and loneliness. Gender status did not differentiate student substance use. However, students who live on or off campus evidence more substance use including alcohol binge drinking. Regardless of gender status and living conditions, religious students reported less substance use. Study findings contribute to usable information for promoting university student psychological well-being through policy and prevention practices associated with substance use over time and across locations in the country.
Molecular Docking Studies for the Evaluation of Cannabinoids as Multi-Target Inhibitors of Type 2 Diabetes
Authors: Takuissu Guy Roussel , Ambamba Dupon Bruno , Iqbal Shabnor , Olofinsan Kolowole , Tchinda Cedric Fossi , Ella Fils Armand , Ngnameko Corinne Raissa , Ngoumen Dany Joel , Motlalepula Matsabisa Gilbert 
Published: February 2025

Abstract

Type 2 Diabetes is due to dysregulation of glycemic control through multiple mechanisms. Cannabinoids from Cannabis sativa L. show promise as anti-diabetic agents, though currently their molecular mechanisms are unclear. This study carried out in silico molecular docking of cannabinoids (cannabidiol (CBD), tetrahydrocannabivarin (THCV), cannabichromene (CBC), cannabigerol (CBG), cannabinol (CBN), Δ9-tetrahydrocannabinol (THC)) against key diabetes drug targets namely: dipeptidyl peptidase-4 (DPP-4), α-glucosidase, α-amylase and invertase. Enzyme structures were obtained from the RCSB Protein Data Bank, while ligand structures were generated and optimized using ChemDraw. AutoDockTools-1.5.7 determined docking parameters, and Biovia Discovery Studio visualized interaction profiles. Normal mode analysis was performed for molecular dynamics simulations. Cannabinoids used in this study showed higher binding affinities (-5.02 to -7.85 kcal/mol) than reference drugs for the targets, with the exception of DPP-4. For DPP-4, CBN (-7.85 kcal/mol) showed best affinity followed by THC (-6.64 kcal/mol). All cannabinoids interacted with catalytic residues except cannabichromene. For α-amylase, THC (-7.14 kcal/mol) was strongest, with residues Asp197, Glu233, Asp300 involved. Against invertase, THC (-7.27 kcal/mol) had highest affinity interacting with Glu230. For α-glucosidase, THC (-7.86 kcal/mol) again dominated via key residues. Normal mode analysis revealed THC binding modulated complex dynamics differently for each enzyme. This study provides insights into cannabinoids' multi-target binding profiles against important T2D drug targets, supporting their potential as natural anti-diabetic agents requiring further research.
Unlocking Australia’s AI usage in Law enforcement from Human involvement perspective: A Systematic Literature Review
Authors: Dasgupta Rumpa , Mekala Sri Harsha , Jaigirdar Fariha Tasnim , Anwar Adnan , Chang Lennon 
Published: February 2025

Abstract

Exploring human trust in Artificial Intelligence (AI) in Law Enforcement domain is paramount for its ethical and effective deployment. As AI systems become increasingly integrated into society, trust ensures transparency, accountability, and fairness in their deployment. Despite the rapid increase in discussion about AI usage in law enforcement in various sectors globally, no secondary research explores that for OCEANIA, specifically in Australia. Moreover, how humans are considered in AI law enforcement is an uninvestigated area in this region. This paper aims to investigate this gap by systematically exploring various applications used in this region and analysing how human perspectives are used, and to what extent. We conducted a systematic literature review (SLR) based on 56 qualitatively selected studies to i) classify the types, frequency, and demography of published research; ii) explore how AI is leveraged; iii) identify how and to what extent humans are considered in development and applications of AI in law enforcement; iv) understand the challenges and solutions reported in this domain and worldwide. In summary, our findings point to the need for solutions to address operational and ethical issues in integrating AI into law enforcement and for unified legislation or regulations to effectively design and utilize AI in this domain. Based on the findings that highlight the important concerns in this domain, we recommend a list of future research directions.
Effects of pulse period and frequency content of ground motion records on fragility curves of BRBFs
Authors: Yaghmaei-Sabegh Saman , Ranjbari Maryam 
Published: February 2025

Abstract

This study aims to estimate the fragility curves of buckling-restrained braced frames (BRBFs) subjected to pulse-like excitations at collapse prevention (CP) and immediate occupancy (IO) performance levels. To this end, 4, 8, 12, and 15-storey steel frames with mega configuration BRBs were modeled using a finite element approach, and fragility analyses were carried out for the records classified based on pulse period (TP) and the ratio of PGA/PGV (peak ground acceleration to peak ground velocity) as the indicator of frequency content. The result showed that for high-rise BRBFs, collapse probability differences between the records with TP<2s and TP>2s are at least 45% and 25% at the MCE and DBE levels, respectively, in which records with larger TP lead to severe damage. Also, analyses indicated that by increasing PGA/PGV ratio in TP<2s records, collapse probabilities for shorter BRBFs decrease where the highest collapse probabilities could be related to records with PGA/PGV<1g.s/cm.
Polymeric nanomicelles for piperine delivery: Preparation, characterization and evaluation of antioxidant and in-vivo anti-inflammatory properties
Authors: Zare Mahboobeh , Gavzan Hakime , Sarkati Malihe Noruzi , Mobaraki Mohammad Ali 
Published: February 2025

Abstract

Purpose Piperine, one of the bioactive alkaloids, exhibits restricted therapeutic effectiveness owing to its inadequate solubility and bioavailability. Nanomicelles hold great potential as drug delivery systems for drugs with low water solubility. This study aimed to create micelles that contain tragacanth gum, vitamin D, and folic acid to encapsulate piperine.Methods Piperine was isolated from black pepper and subsequently loaded on synthesized polymeric micelles. The antioxidant activity of piperine-loaded micelles was tested by DPPH⋅ radical method. Moreover, the peripheral anti-inflammatory activity of nanomicelles was assessed using the formalin-induced paw edema method.Results According to the results obtained from this investigation, the utilization of nanomicelles demonstrated an enhancement in the radical scavenging activity of piperine, consequently leading to a notable reduction in the required dosage of piperine for its anti-inflammatory effects.Conclusion The findings indicate that the utilization of synthesized micelle as an innovative targeted delivery system could potentially augment the therapeutic characteristics of piperine.
Exploring the anticancer potential of Vitex negundo L.: Cytotoxicity and gene regulation in PA1 ovarian cancer cells
Authors: Govindasamy Manivannan , Anbazhagan Ganesh Kumar , NCJ Packia Lekshmi , R Premkumar , Hirad Abdurahman Hajinur , Karuppiah Ponmurugan 
Published: February 2025

Abstract

Background Ovarian cancer is a commonly occurring and significant health concern among women worldwide. There is an ongoing search for effective and natural therapeutic agents to combat this disease.Objective The study aimed to analyze the cytotoxic effect and gene expression in ovarian cancer (PA1) cell lines treated with methanolic leaf extract of Vitex negundo.Methods The cytotoxic effect of the methanolic leaf extract of Vitex negundo on the ovarian cancer cell line (PA1) was determined using the MTT assay. The IC50 value was calculated to assess the concentration required to inhibit 50% of cell growth. Gene expression analysis was performed using RT-qPCR to evaluate the mRNA levels of significant targets including PLEKHH3, STIP1, and ATP5F1A.Results The IC50 value of the methanolic leaf extract of Vitex negundo on PA1 cells was determined as 53.332 ± 1.449 µg/mL compared to vehicle control cells. RT-qPCR analysis revealed that among the three target genes analyzed, two targets (PLEKHH3 and ATP5F1A) were downregulated, while STIP1 was upregulated upon treatment with the plant extract compared with untreated control cells.Conclusion This study indicates that the methanolic leaf extract of Vitex negundo exhibits cytotoxic effects against ovarian cancer cells and modulates gene expression of key targets involved in cellular processes. These findings suggest potential therapeutic applications of Vitex negundo in the treatment of ovarian cancer.
Comparison of the effectiveness of the common bean fly (Ophiomya spp.) control methods: Implications for resistance breeding: A meta-analysis
Authors: Tsekenedza Shylet , Shimelis Hussein , Nkhata Wilson , Mukankusi Clare M. , Dossa Emeline N. 
Published: February 2025

Abstract

The bean fly (Ophiomya spp.) is one of the most destructive field pests of the common bean (Phaseolus vulgaris L.), notably in Eastern and Southern Africa. Several studies have recommended a range of methods for bean fly control. Nevertheless, the effectiveness of management practices and their impact on grain yield is not fully understood to help prioritize and guide integrated management of the pest spearheaded by host plant resistance. A meta-analysis was conducted involving 18 studies on bean fly control methods. The highest achieved grain yield was 3761.00 kg/ha from the chemical control, and the lowest was 14.10 kg/ha from the genetic control, indicating a low level of bean fly-resistant lines in the current breeding stocks. The control methods had effect sizes ranging from small (0.19) to large (1.38). The chemical and integrated control methods had the highest ES values of 1.21 and 1.38, respectively, but had wide 95% confidence intervals. The metadata suggests variable efficacy of the control methods, and breeding for host resistance is yet to be up-scaled to control the bean fly and bolster grain yield effectively. No studies have reported the effectiveness of biological control against bean fly based on the grain yield of candidate common bean genotypes. Overall, the genetic control method with an ES (0.19) contributed to a relatively small effect, with CIs of -0.8 and 0.56 overlapping the null effect. This suggests that the level of bean fly resistance in the available genetic pool is still low, resulting in low yield potential, which requires concerted breeding.
Exploring the Therapeutic Potential of Momordica charantia in Targeting Protein Kinase C Delta (PRKCD) for Type 2 Diabetes Mellitus: Insights from Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulations
Authors: Yadav Ruchi , Nambiar Nidhi , Shah Manushi , Patel Bhumika 
Published: February 2025

Abstract

Type 2 diabetes mellitus (T2DM) is a chronic condition caused by decreased insulin production and increased insulin resistance, and its prevalence has increased by 49% since 1990. Current treatments for T2DM include pharmacological agents and lifestyle modifications, but they are limited by their side effects and cost. Herbal remedies and natural products have become popular alternative treatments for T2DM as they are associated with fewer side effects. Momordica charantia Linn. (bitter melon) is a member of the Cucurbitaceae family and has been used as a traditional anti-diabetic remedy in various countries for many years. The plant contains several biologically active compounds, including glycosides, saponins, alkaloids, triterpenes, proteins, and steroids. The hypoglycemic activity of Momordica charantia is primarily attributed to its saponins, which are collectively known as charantins, and alkaloids. Through network pharmacology, Molecular docking and MD simulation we found underlying, mechanism of karela in the treatment of T2DM. Through network pharmacology from 49 targets we found the Protein kinase C delta (PRKCD) as a hub gene. Various studies have also indicated the pathophysiological role of PRKCD in the development of T2DM. Gene expression analysis in 24 patients revealed an overexpression of PRKCD in both prediabetic and diabetic patients. Molecular docking data identified the top three active constituents of karela as Momordicoside C, Momorcharaside B, and Momordin I, with docking scores of -8.0 kcal/mol, -7.9 kcal/mol, and − 7.9 kcal/mol, respectively. Additionally,MD simulation was performed using the GROMACS software and we found that Momordicoside C and Momorcharaside B has good stability and also formed the H-bond at end of the 100ns of simulation. This study revelled new mechanism action of a well-known plant karela in the treatment of T2DM.
The Chain Mediation Effects Of Automatic Thoughts And Impulse Control On Growth Mindset And Cognitive Fusion Among Junior High School Students
Authors: Tao WeiDong , Wang BangCheng , Tao XiaoLi 
Published: February 2025

Abstract

Previous research has shown that having a growth mindset can directly or indirectly affect cognitive fusion in college students. Using the Cognitive Behavior Therapy (CBT) framework, this study explores the relationship between growth mindset and cognitive fusion in junior high school students, as well as how impulse control and automatic negative thoughts mediate this relationship.Participants were 520 junior high school students who completed a Growth Mindset scale, Cognitive Fusion questionnaire, self-control scale, and automatic-thought scale. We tested the mediation and chain-mediated models using PROCESS. The results revealed (1) a significant negative correlation between growth mindset and cognitive fusion, and (2) both impulse control and automatic negative thoughts were found to play a chain-mediating role in the relationship between growth mindset and cognitive fusion.These findings highlight the importance of supporting the development of a growth mindset in students while simultaneously addressing their impulse control abilities and patterns of automatic thinking.