bluuebunny/crossref_metadata_2025 huggingface dataset:
Tailored treatment and clinical management for DPYD compound heterozygous: a multidisciplinary teamwork
Authors: Simone Laura , Maiorano Brigida Anna , Barbano Raffaela , Mazza Tommaso , Biagini Tommaso , Maggio Gabriele Di , Rodriquenz Maria Grazia , Nanni Luciano , Ciavarella Grazia , Rinaldi Antonio , Re Marzia Del , Carella Massimo , Fania Giuseppe , Maiello Evaristo , Miscio Giuseppe , Latiano Tiziana
Published: October 2024

Dihydropyrimidine dehydrogenase (DPD), encoded by the DPYD gene, is the rate-limiting enzyme governing fluoropyrimidines (FPs) catabolism. Impaired or abrogated DPD enzyme activity is often caused by genetic polymorphisms in the DPYD gene that are well-validated predictors of FP-associated toxicity. Presently, four DPYD variants are included in FP genetic-based dosing guidelines. Patient safety of FP treatment has been significantly improved by pre-emptive screening for DPYD genotype variants and dose adjustments in individuals carrying heterozygous DPYD variant alleles. Nonetheless, managing carriers of multiple DPYD gene variants remains still challenging We conducted a study involving patients undergoing standard-of-care fluoropyrimidine treatment who underwent preemptive DPYD genotyping for DPYD*2A, DPYD*13, D949V, and IVS10. Additionally, patients were screened for the DPYD*6. Adverse drug reactions (ADRs) were graded according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. Adverse events (AEs) ≥ grade 3 were considered severe. Herein, we report 4 cases of patients carrying double-site heterozygous variants of the DPYD gene (IVS10 and DPYD*6), diagnosed with either colon adenocarcinoma or breast cancer. These patients underwent pharmacogenetic-guided dose reduction of the standard by 25–50%, showing varying treatment responses. In conclusion, the management of patients carrying double-site heterozygous IVS10 and DPYD*6 variants should be performed by a multidisciplinary team due to the need for tailored treatment approaches including precision dosing, integrative deep analysis and therapeutic drug monitoring for early detection of AEs in order to maintain effectiveness and safety for each case.
Nonlinear analysis of groundwater levels: Investigating trends and the impact of El Niño on groundwater drought in a southern region of India
Authors: Poojitha Kondeti , Dodamani Basavanand M
Published: October 2024

The expansion of groundwater irrigation and the cultivation of water-intensive sugarcane crop, combined with low rainfall, has aggravated groundwater depletion and intensified droughts in a semi-arid region of the Upper Krishna basin, India. Consequently, assessing and managing groundwater resources in this region has become a priority for local authorities. However, this task is challenging due to the limited and inconsistent nature of historical observations, which complicates the balancing of temporal and spatial resolution in groundwater level data. The prevalence of missing values and the lack of sufficient information about their causes further complicate groundwater assessments, leading to potentially inaccurate interpretations. This study employs an iterative singular spectrum analysis (SSA) approach to impute missing groundwater level data from 25 monitoring wells. The reconstructed data is then used to identify nonlinear trends and investigate the impact of strong El Niño events on groundwater drought through cross wavelet transform (XWT) and wavelet coherence (WTC) analyses between 1983 and 2017. The SSA-extracted nonlinear trends revealed short-term deviations in groundwater levels during 1991–2000, 2002–2003, and 2015–2017, which were corroborated by significant cross wavelet power and high wavelet coherence between the Niño 3.4 SST Index and groundwater drought, particularly in low rainfall conditions, indicating stress on the groundwater system. Although the study effectively captures the nonlinear nature of groundwater levels and the influence of climate variability on drought, the complexity of the groundwater system in the region persists due to physical water scarcity and high groundwater extraction for irrigation. This study underscores the importance of imputing missing data and applying nonlinear trend and wavelet analysis to detect short-term deviations caused by severe droughts, driven by strong El Niño events and high irrigation demands.
Unraveling Predictors of Reading Difficulties in EFL 6th Graders: Insights from latent profile analysis and multinomial logistic regression
Authors: Kim EunJung
Published: October 2024

This study examines predictors of reading difficulties in 6th-grade EFL students via latent profile analysis (LPA) and multinomial logistic regression. Six profiles were identified, including the Disinterested in English Group, which faces severe reading challenges due to a poor home English environment (HEE), low parental support (PS), minimal English exposure, and low interest; the English Necessity Recognition Group, which struggles despite understanding English’s importance; the Excellent Parental Support Group, which experiences nonword reading issues despite strong PS and HEE; and the Excellent English Environment Group, which has the best reading outcomes. The key predictors of reduced reading difficulty are a robust HEE, high English exposure, and genuine interest. The study highlights the need for integrating supportive factors, such as improving HEE and PS, and emphasizing phonics education to enhance reading skills and motivation. Future research should explore additional variables and diverse populations.
Enhancing lettuce resilience to cadmium stress: Insights from raw vs. cystamine-modified biochar
Authors: Chen Rongqi , Duan XI , Xu Ruoxuan , Zhao Tao
Published: October 2024

Aims and Methods
Understanding the interactions among biochar, plants, soils, and microbial communities is essential for developing effective, eco-friendly soil remediation agents. This study investigates the mechanisms by which cystamine-modified biochar (Cys-BC) alleviates cadmium (Cd) toxicity in lettuce, comparing its effects to those of raw biochar across key parameters: plant growth, antioxidant enzyme activities, available Cd in root-sheet-soil, and shifts in microbial communities.
Results
Cys-BC significantly enhances biomass, increasing above-ground growth by 40.54–44.95% and root biomass by 37.54–47.44% compared to Cd-stressed controls. Photosynthetic parameters, including chlorophyll a content and net photosynthetic rate, improve by up to 91.02% and 37.93%, respectively. Cys-BC mitigates oxidative stress, enhancing antioxidant activities by 73.83–99.39%. Additionally, it reduces available soil Cd levels while promoting microbial diversity, as evidenced by increases in Shannon, Chao1, and ACE indices of 12.81%, 14.48%, and 17.15%, respectively.
Conclusions
Cys-BC enhances glutathione reductase activity and increase cysteine levels within the ascorbate-glutathione cycle, functioning through increased soil cation exchange for Cd passivation rather than through pH modifications. Significant shifts in microbial communities, particularly the increases in Deltaproteobacteria and Nitrospira, underscore their roles in sulfur and nitrogen metabolism. These findings provide new insights into how modified biochar, specifically Cys-BC, can effectively address Cd contamination, highlighting its potential for broader applications in soil remediation.
Impact of noradrenergic inhibition on neuroinflammation and pathophysiology in mouse models of Alzheimer's disease.
Authors: Evans Andrew K. , Park Heui Hye , Woods Claire E. , Lam Rachel K. , Rijsketic Daniel Ryskamp , Xu Christine , Chu Emily , Ciari Peter , Blumenfeld Sarah , Vidano Laura M. , Saw Nay L. , Heifets Boris D. , Shamloo Mehrdad
Published: October 2024

Norepinephrine (NE) modulates cognitive function, arousal, attention, and responses to novelty and stress, and also regulates neuroinflammation. We previously demonstrated behavioral and immunomodulatory effects of beta-adrenergic pharmacology in mouse models of Alzheimer's disease (AD). The current studies were designed to block noradrenergic signaling in 5XFAD mice through 1) chemogenetic inhibition of the locus coeruleus (LC), 2)pharmacologic blocking of β-adrenergic receptors, and 3) conditional deletion of β1- or β2-adrenergic receptors (adrb1 or adrb2) in microglia.
First, brain-wide AD pathology was mapped in 3D by imaging immunolabeled, cleared 5XFAD brains to assess the overlap between Aβ pathology, reactive microglia, and the loss of tyrosine hydroxylase (TH) expression in the catecholaminergic system. To examine the effects of inhibiting the LC NE system in the 5XFAD model, inhibitory (Gi) DREADD receptors were expressed specifically in LC NE neurons. LC NE neurons were chronically inhibited through the subcutaneous pump administration of the DREADD agonist clozapine-N-oxide (CNO). Plasma and brains were collected for assessment of neuroinflammation and pathology. A separate cohort of 5XFAD mice was chronically dosed with the beta-adrenergic antagonist propranolol or vehicle and evaluated for behavior, as well as post-mortem neuroinflammation and pathology. Finally, we used 5XFAD mice with conditional deletion of either adrb1 or adrb2 in microglia to assess neuroinflammation and pathology mediated by β-adrenergic signaling.
Using iDISCO, light sheet fluorescence microscopy, and novel analyses, we detected widespread microgliosis and amyloid pathology, along with modest TH downregulation in fibers across multiple brain regions, in contrast to the spatially limited TH downregulation observed in neurons. Both chemogenetic inhibition of LC adrenergic signaling and pharmacological inhibition of beta-adrenergic receptors potentiated neuroinflammation without altering amyloid beta pathology. Conditional deletion of adrb1 in microglia did not affect neuroinflammation. Conditional deletion of adrb2 in microglia attenuated inflammation and pathology in females but had no effect in males. Overall, these data support previous observations demonstrating the immunomodulatory effects of beta-adrenergic signaling in the pathophysiology of brain disorders and suggest that adrenergic receptors on cell types other than microglia, such as astrocytes, may predominantly mediate the disease-modifying effects of β-adrenergic agonists in the brain.
Antioxidant and antiplasmodial activities of Razafimandimbisonia minor (Baill.) Kainul. & B. Bremer leaves (Rubiaceae)
Authors: RAKOTOARIVELO Henintsoa , RAZAFINTSALAMA Vahinalahaja Eliane , RANDRIATSALAMA Angelo , RASOLOFOMANANA Jesuka , RANDRIAMIALINORO Faliarivony , RALAMBOMANANA Dimby Andrianina , RANARIVELO Lalasoa , RAZAFIMAHEFA Reine Dorothée RAMILISON , RASOARIVELO Tiana Sylvia RALAMBONIRINA
Published: October 2024

Background
Razafimandimbisonia minor (Baill.) Kainul. & B. Bremer (Rubiaceae), a specie endemic to Madagascar, is traditionally used in Malagasy medicine. A decoction of the leaves is employed to treat liver disorders, fatigue and fever. The aim of this study was to assess the plant's antioxidant activity, determine the content of total phenolic compounds and flavonoids, and analyze the antiplasmodial potential.
Methods
The leaves were collected, shade dried and ground. The methanol extract obtained by maceration was partitioned by liquid-liquid to produce hexane, ethyl acetate and aqueous fractions. Phytochemical screening was carried out using standard methods, followed by analysis of phenol and flavonoid contents, as well as antioxidant and antiplasmodial activity tests. Quantification of total polyphenols and flavonoids was carried out by UV spectrophotometry, using colorimetry with 10% Folin-Ciocalteu reagent and 2% aluminum chloride respectively. Antioxidant activity was measured by the DPPH (2,2-diphenyl-1-picrylhydrazyl) free radical scavenging assay. Antimalaria activity was assessed by measuring fluorescence with the SYBR Green dye on the chloroquine-resistant Plasmodium falciparum strain FCM29. Results were analyzed by ANOVA with Tukey's test.
Results
The methanol extract had a high polyphenol and flavonoid content, with concentrations of 280.8 ± 4.6 mg EGA/g and 50.4 ± 2.3 mg ER/g respectively. Biological tests revealed a better antioxidant activity of this extract, with a 50% inhibitory concentration of free radicals measured at 21.58 ± 0.05 µg/mL. But, the hexane and ethyl acetate extracts showed moderate antiplasmodial activity with concentrations of 21.32 and 24.42 µg/mL respectively, while the aqueous and methanol extracts showed weaker activity with concentrations of 41.5 µg/mL and 50.71 µg/mL, respectively.
Conclusion
These results display the phenolic and flavonoid content of the methanol extract of Razafimandimbisonia minor leaves, which corroborates with antioxidant activity, but the antimalarial activity is rather weak. They underline the value of using this plant for phytomedicinal properties, confirming the important role in malagasy traditional medicine.
European Electricity Grids May Exhibit Heatwave-induced Capacity Bottlenecks
Authors: Keshav Srinivasan , Chen Minghua , Liang Enming
Published: October 2024

As climate change increases the frequency, intensity, and duration of heatwaves, understanding their impact on electricity grids is crucial for enhancing societal security and resilience. We study the effects of heatwaves on European electricity grids using several comprehensive real-world datasets. Moreover, noting that conventional modeling of temperature effects on grid operation limits is computationally challenging, we develop a novel temperature-dependent segment-based approach that is both efficient and accurate. We apply this method to evaluate the robustness of several European electricity grids for projected heatwave scenarios for the next 25 years. We find both concerning grid bottlenecks and national differences: for example, while the Spanish grid exhibits temperature-induced capacity bottlenecks that could jeopardize power supply during heatwaves, the German grid shows remarkable resilience. These findings emphasize the need for temperature-aware grid power flow analysis as well as the need for long-range planning to ensure energy security despite climate-change induced future heatwaves.
Investigating storage models for various types historical graphs
Authors: Spitalas Alexandros , Kosmatopoulos Andreas , Gounaris Anastasios , Tsichlas Kostas
Published: October 2024

Our focus in this study revolves around enhancing the storage strategies for evolving graphs, particularly emphasizing the preservation and querying of their complete history. In particular, we review previous research on historical graph databases and storage systems, we introduce a way to generate historical graph datasets and we propose an enhanced methodology for a space-optimal vertex-centric model with MongoDB. This approach prioritizes space optimizations while managing to achieve notable advancements in the execution time of global queries, known for their complexity within entity-centric frameworks. Extensive experimentation was done, employing snapshot-based and interval-based datasets generated with the use of LDBC SNB generator, in order to validate our claims of achieving significant speed enhancements. Consequently, our approach enables the execution of more resource-intensive queries with improved efficiency, reduced client involvement, and less memory requirements.
The effect of protocatechuic acid on nephrotoxicity induced by gentamicin in rats
Authors: Mert Handan , Çibuk Salih , Yıldırım Serkan , Mert Nihat
Published: October 2024

Gentamicin (GM) is an aminoglycoside antibiotic widely used in the treatment of gram-negative infections. It is known that oxidative stress plays an important role in gentamicin nephrotoxicity. Therefore, the aim of this study is to investigate the possible protective effect of protocatechuic acid (PCA), which is reported to have antioxidant properties, on GM-induced nephrotoxicity. For this purpose, 32 rats were randomly divided into four groups: Control (Physiological saline orally), PCA (20 mg/kg orally), GM (80 mg/kg/day/i.p), GM + PCA (GM 80 mg/kg/day/i.p and 20 mg/kg PCA orally). Trial period was eight days. Blood samples were taken for biochemical, kidneys were removed for immunohistochemistry and histopathological evaluations. Serum urea, creatinine, Na, K, Cl analyzes of the rats were performed in an autoanalyzer, and malondialdehyde (MDA), advanced oxidation protein products (AOPP), glutathione (GSH), superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) analyzes were performed in ELISA. While urea (p < 0.001), creatinine (p < 0.001), MDA (p < 0.05) and AOPP (p < 0.05) levels decreased in the GM + PCA group compared to the GM group, the GSH level (p < 0.05) and GPx activity (p < 0.05) levels increased. In conclusion; in GM-induced nephrotoxicity, PCA prevented lipid peroxidation and protein oxidation, increased GSH level and GPx activity, and according to histopathological and immunohistochemical findings, it prevented necrosis in tubular epithelium, atrophy in glomerulus and decreased 8-OHdG expression in kidney cells. With this study, it was emphasized once again that PCA is a good antioxidant agent and it can be said that PCA has a protective effect in nephrotoxicity induced by GM.
Impulse Buying in the Age of Algorithms: A Systematic Literature Review of Psychological Triggers Leading to Buyer's Remorse
Authors: Ofem
Published: October 2024

Algorithmic marketing has become a powerful tool in e-commerce, significantly impacting consumer behavior by leveraging psychological triggers that foster impulse buying, often resulting in buyer’s remorse. This systematic literature review examines how algorithms employ scarcity, urgency, social proof, and personalization cues to encourage impulse purchases and explores the ensuing cognitive dissonance and buyer's remorse experienced by consumers. Adhering to PRISMA guidelines, the review assessed studies from databases including Scopus, Web of Science, PsycINFO, IEEE Xplore, and Google Scholar published between 2000 and 2024. Of the 1,200 initial articles, 50 high-quality studies were selected, encompassing methodologies such as experiments, surveys, case studies, and meta-analyses. Findings reveal that algorithm-driven marketing significantly increases impulse purchases and post-purchase regret, highlighting ethical tensions between consumer persuasion and manipulation. Framed by Cognitive Dissonance Theory, Nudge Theory, and Dual-Process Theory, the discussion underscores the ethical responsibility of marketers and the need for regulatory oversight to safeguard consumer autonomy. The study calls for further longitudinal research on the psychological impact of algorithmic marketing and suggests actionable strategies for consumers, ethical guidelines for marketers, and robust regulatory frameworks for policymakers. Conclusions: The findings underscore the profound influence of algorithms on consumer behavior and highlight the urgent need for ethical standards and regulatory policies to address potential manipulative practices in algorithmic marketing. Future studies should focus on the long-term effects of such marketing strategies and explore interventions to mitigate buyer's remorse.
Assessing Teacher Readiness for Online Teaching in Cambodian Higher Education using Structural Equation Modeling
Authors: Be Borey
Published: October 2024

This study examines Cambodian higher education teachers' readiness for online teaching and learning (OTL) using a structural equation modeling (SEM) approach. The framework centers around three key dimensions: teachers' self-efficacy in technological, pedagogical, and content knowledge (TPACK), their perceived online teaching presence, and the institutional support they receive. A quantitative survey was administered to 140 teachers at the university level. Teachers' online teaching experience positively influenced their TPACK self-efficacy. Online teaching experience also had a significant positive impact on teachers perceived online teaching presences. Furthermore, teachers' perceptions of institutional support were positively associated with their online teaching experience. These results highlight the critical role of teachers' online teaching experience in shaping their readiness for OTL. The findings suggest that targeted professional development programs and institutional support mechanisms can effectively enhance teachers' self-efficacy, online teaching presence, and perceptions of institutional support in Cambodian higher education.
Formation of Bachelor`s Skills in the Field of Machine Learning and Intelligent Data Analysis
Authors:   Ural State Pedagogical University, Lapenok Marina B. , Shestakova Lidia G. ,   Perm State University
Published: October 2024

The article presents the content of the educational disciplines “Workshop on Python Programming” and “Fundamentals of Artificial Intelligence”, included in the module “Data Analysis. Machine learning. Artificial Intelligence”, implemented in Ural universities. Modern teachers note that when preparing the next generation of teachers, the priority should be their acquisition of experience in using artificial intelligence tools in teaching. The objectives of mastering the module are developing students’ skills in the field of neural network mathematical modeling, developing knowledge about basic data analysis algorithms, development of skills in visualization and interpretation of data to solve applied problems using object-oriented programming technologies and artificial neural network technologies. As part of project activities, students gain experience in data mining by completing research projects (for example, a project on comparative assessment of the effectiveness of multilayer perceptron learning algorithms) and applied projects (for example, on the development of a neural network system for predicting the success of schoolchildren’s research work; on the development of a neural network system for predicting student attendance training sessions). At USPU, software systems have been developed in Python that implement the presented neural network prognostic systems. Educational and methodological materials for the disciplines of the module include video lectures and presentations for them, laboratory work (including those based on GoogleColab notebooks), datasets, test sets, theory questions and practical tasks for exams and tests. The effectiveness of the developed teaching methodology is confirmed by the results of a pedagogical experiment. Keywords: neural network technologies, data mining, predictive systems, machine learning, content of the academic discipline
Gamification Technology as a Tool for Improving Students’ Understanding of Text-Based Problem-Solving Techniques
Authors:   Ulaanbaatar Branch of Plekhanov Russian University of Economics, Yumova Tsyrenkhanda Zh. , Garmaeva Tuyana I. ,   Secondary School No. 60 for Social Adaptation of Disabled Children
Published: October 2024

Solving text problems to a greater extent than other mathematical topics in Grades 5–6 contributes to the development of erudition, thinking abilities, analytical reasoning skills, and the formation of mathematical knowledge. Problem-solving skills bring students closer to real-life situations that require them to develop strategies and search for optimal solutions. The article considers the necessity of using gamification technology to effectively achieve the main goal of the research – to improve students’ understanding of text problem solving methods. In order to achieve the goal, the authors have developed methodological recommendations to improve students’ understanding of the condition and solution of text problems. The authors note that the use of interactive tools, innovative teaching methods, such as online simulators and gamification, contributes to the attractiveness of the learning process. This helps to increase students’ activity, formation of motivation for understanding the conditions of the textual task, as well as stimulates their cognitive activity. The methods of analysis, synthesis, generalization, study of pedagogical experience, observation and survey have been used to conduct the research. The analysis of the research results showed that the novelty of using gamification technology will help, on the one hand, the teacher to adapt teaching methods depending on the level of understanding and the pace of learning of students and to present them with new material in an interactive form, and on the other hand - students to develop self-education, improve communication skills, learn to discuss the solution and work in a team. The author’s development of methodological recommendations in combination with game technologies will help teachers to apply gamification in the practice of solving text problems with schoolchildren. Keywords: text problem, formation of mathematical knowledge, gamification technology, motivation, game technology
Low Impact of Nitrogen Fertilization on Grafted Tomatoes under High-tunnel Production
Authors: Bonarota Maria-Sole , Barrios-Masias Felipe H.
Published: October 2024

High-tunnel systems can improve and prolong production under challenging climate, but research on nitrogen management and grafting is still needed. This study analyzes the effects of rootstock and two N fertilization levels in northern Nevada under high-tunnel commercial production. We report on tomato yield, growth, leaf nutrient profile, and spectral indices [i.e., soil plant analysis development (SPAD) and normalized difference vegetation index (NDVI)] correlation with leaf nitrogen. Although rootstock influenced yield and leaf nutrient profile depending on location, no clear effect from the nitrogen fertilization was observed in growth and yield. Moreover, the low accuracy of SPAD and NDVI indices in predicting leaf nitrogen status undermined the capacity to provide enough support for a sustainable nitrogen fertilization management.
Benefits of Irrigation or Fertigation on Early Growth and Yield of a High-density Apple Planting in a Humid Climate
Authors: Dominguez Leo I. , Robinson Terence L.
Published: October 2024

The success of a new high-density apple planting depends on how fast the grower can recoup the high investment that these systems require. The right balance between vegetative growth and cropping during the early life of the planting is where tree growth is sufficient to rapidly fill the allotted space while at the same time producing high early yields. In this study we evaluated irrigation or fertigation as strategies compared with the traditional nonirrigated control to improve growth and yield of five apple scion cultivars (Mutsu, Gala, Honeycrisp, Jonagold, and Macoun) on M.9 or B.9 rootstocks over the first 5 years at Geneva, NY. Calcium nitrate at the rate of 113 kg·ha−1 N was applied to all three irrigation treatments (dissolved in water for the fertigation treatment, broadcast dry with the irrigation treatment, or broadcast dry with the nonirrigated control). Our results showed that fertigation with dissolved N and irrigation with dry broadcast N increased yield and tree growth similarly and significantly over the first 5 years of orchard establishment compared with the nonirrigated treatment with dry broadcast N. There was a significant economic benefit of irrigation or fertigation in the humid climate of New York State.
Reducing Total Plate Count of Bacteria through Dark Sealed Storage for Plant Factory Nutrient Solution Sterilization
Authors: Chen Yu , Wang Teng , Cao Zhichao , Ke Haochun , Li Kun , Cheng Ruifeng
Published: October 2024

Plant factories are efficient systems for vegetable production under a clean and controlled environment. To improve the sterilization efficiency of nutrient solutions (NS) in plant factories, this study examined the changes in the number and composition of colonies from in-use and post-use stored NS. The sterilization effect under ultraviolet (UV) light-emitting diode light was also investigated. The results indicated that the total plate count of bacteria (TPC) of newly prepared NS was 3.99 lg CFU/mL (9870 CFU/mL); within 7 days of cultivation, this number sharply increased ∼7.8 times to 4.88 lg CFU/mL (76,000 CFU/mL), then remained stable. After dark sealed storage (DSS) of post-use NS, TPC dramatically decreased by 82.8% and reached its lowest point at 4.29 lg CFU/mL (19,566 CFU/mL) on day 3, equivalent to a log survival ratio of −0.76, then rapidly rebounded by 235.6% to 4.82 lg CFU/mL (65,666 CFU/mL) on day 4. During storage, bacterial community composition was also remarkably changed, and the relative abundance of heterotrophic bacteria such as Variovorax paradoxus and Pararhizobium giardinii and photosynthetic bacteria such as Pseudo-Nitzschia multiseries were greatly decreased. The log survival ratio for in-use and post-use stored NS under UV sterilization were −1.29 and −1.30, respectively, and was not significantly different. Coupled with the dramatic decrease in TPC during DSS, the overall log survival ratio of post-use NS UV sterilization was −2.06 and was the most effectively form of sterilization in our study. In short, TPC of in-use NS remained high for a long period, and DSS may serve as a low-cost NS sterilization method in plant factories.
تطبيق البيئة اللغوية بطريقة المفردات لترقية مهارة الكلام الطلاب
Authors: MAULIDIANA LAILI
Published: October 2024

ملخص البحث: أهمّية فى البيئة اللغوية هي الإعتماد على النفس، التمرينات واستمرار بحسن التعلّم. من المفيد أن يتعلّم المسلمون اللغة العربية منذ الصغار و يجعله فى البيئة اللغوية اليومية بأن يكون اللغة إزدهرا كلغة الإتصال و مزدهرا فى قسم التكنولوجية. من المحسن أن يعرف المعلّم فعالية الخطوة فى صبّ البيئة اللغوية لأنها يعادله فى دراجة النجاح و عند تعامل المعلّم بهذه الفعالية يحسن به أن يراعى ما يلى: اِكثار مفردات التلاميذ، يبيّنُ المعلّم عن التفريق الجملة المفيدة و يَصْدرُ المعلّم شجاعة التلاميذ فى إعتبار فِكرتَهم باللغة العربية مع الغير. إذ يوجد الإعتماد فى النفوس التلاميذ عندما يصبّون البيئة اللغوية عسى أن يكون اثار خاصة فى نشر اللغة العربية و مَن الذى له كفائة فى اللغة العربية له مقام مرتفع بين الأخرين. إن أراد التلاميذ أن يجيد اللغة العربية واجب عليهم أن يفهموا معانى المفردات و أنماط التراكيب و الجمل أو العبارات. ففهم اللغة العربية يستطيع أن يحصل الطلاب بأي الطريقة مثلا بطريقة المفردات  “vocabulary methode”
مناهج البحث التي تتكون على مدخل البحث بإستعمال على مدخل البحث الكيفي, و تصميم البحث بإستعمال تصميم البحث الوصفي, و مكان البحث و هو باالمدرسة الإبتدائية الكونتورى و المدرسة الإبتدائية الإسلامية المنور، و طريقة جمع الحقائق المستعملة هنا هي: طريقة المشاهدة بأداة المشاهدة، طريقة المقابلة بأداة المقابلة، و طريقة الوثيقة بأداة إرشادة للواثيقة و طريقة تحليل الحقائق التي تستعمل بطريقة الإستقرائية و طريقة و صفة التحليلية، ثم تفتيش صحة البيانات بإستعمال تطويل أوقات الحضور و المناقشة مع بعض الإخوان و تثليث .حاصل البحث: 1. لمعرفة خطوة تطبيق البيئة اللغوية بطريقة المفردات فى ترقية مهارة الكلام الطلاب 2. لمعرفة ما المشكلات فى تطبيق البيئة اللغوية بطريقة المفردات لترقية مهارة الكلام الطلاب و لمعرفة طريقة فى انحلال تلك المشكلات، 3. لمعرفة ما تأثير فى تطبيق البيئة اللغوية بطريقة المفردات فى ترقية مهارة الكلام الطلاب
الكلمة المفتاحية: البيْئة لغوية, طريقة المفردات, مهارة الكلام.
CONCEPTUALIZATION OF THE CONNECTION BETWEEN FREEDOM AND CONTROL THROUGH THE PRISM OF DIGITAL TECHNOLOGIES
Authors: Obedkov Oleksandr
Published: October 2024

The article attempted to understand the meaning of the connection between the categories “Freedom” and “Control” in the modern conditions of digitalization and the active implementation of information and communication technologies. The definition of freedom is determined, in particular, its positive and negative forms are described. In addition, a retrospective analysis of the phenomenon of the totalitarian regime with its main components and characteristic features was carried out in order to draw an analogy with its updated form of the control “society”, where the place of human freedom and the meaning of control can be clearly traced. The proposed author's view on the meaning of freedom in the conditions of total digitalization, as well as opportunities to preserve it.
MODERN HUMAN: INFORMATION ASPECTS OF ANTHROPOSOCIOGENESIS
Authors: Danilyan Oleg , Dzoban Olexander
Published: October 2024

The article notes that the mechanisms for processing and storing information, formed as a result of humanity's long evolution, are currently undergoing significant transformations. There is a radical transformation of space and time, fundamental dimensions of human life. The use of new technologies generates new dangers, on the one hand, fostering individual self-development and social progress, and on the other hand, leading to an increased tendency towards negative activities by individuals. Dominant at the present stage, industrial and post-industrial technologies, characterized by both creative and significant destructive potential, can also pose threats to nature and humanity. It is emphasized that one of the modern forms of human dependence is computer dependence, associated with the attraction to computer games, which has the most destructive impact on human spirituality.
THE INFLUENCE OF THE TECHNOLOGICAL ATTITUDE TO KNOWLEDGE ON THE DEVELOPMENT OF LAW
Authors: Pavlenko Zhanna , Orlovsky Ilya
Published: October 2024

The article provides an understanding of the concept of technological relation to legal knowledge. It is shown that the methodology of the technological relationship to legal knowledge is a complex problem that can be solved on the basis of a constructive dialogue between developers of artificial intelligent systems and representatives of humanitarian sciences. It is substantiated that the use of knowledge as a material contributes to the transformation of law in the digital world.
ACTIVITIES OF STATE AND NON-STATE ENTITIES IN THE FUNCTIONING SYSTEM OF UKRAINE’S INFORMATION SECURITY
Authors: Prudnykova Olena
Published: October 2024

The essential characteristics of information security are analyzed through the activities of state and non-state entities. It is noted that the main task of the state is to create and maintain an institutional mechanism for ensuring information security. The leading role of non-state entities such as analytical centers and mass media in the functioning of the information security system of democratic countries is substantiated.
INTERNATIONALIZATION OF HIGHER EDUCATION AS THE MOST IMPORTANT FACTOR IN THE DEVELOPMENT OF INTERNATIONAL RELATIONS
Authors: Klimova Galina
Published: October 2024

The article analyzes the concept of «internationalization of higher education» based on consideration of various theoretical and methodological approaches to defining its essence. An overview of a wide range of concepts that determine the features of the internationalization of higher education in international and national dimensions is offered. Institutional models of internationalization of higher education have been identified. Special attention is paid to the consideration of the conceptual foundations of the internationalization of higher education in Ukraine.The impact of the internationalization of higher education on the development of international relations in modern conditions is analyzed.
The Influence of Social Media Communication Towards Customer-Based Brand Equity on Netflix
Authors: Eka Putri Laila Febriyuni , Rufaidah Popy
Published: October 2024

This study aims to analyze how social media communication seen from user-generated content, firm-generated content, and distribution intensity affects customer-based brand equity on Netflix. Respondents in the study were 321 Netflix subscribers. This study uses a lower-order construct as a research model. Based on the results of research that has been conducted, show that firm-generated content (FGC), user-generated content (UGC), and distribution intensity (DI) affect customer-based brand equity (CBBE) at different levels. Although UGC has a smaller effect size compared to FGC, it still has significant relevance. Distribution intensity is important for increasing brand awareness and loyalty, although it has no direct impact on perceived quality. This in-depth understanding can guide marketing and brand management decisions to effectively utilize these components.
Determination of creep function coefficients of viscoelastic pipes using a transient-guided machine learning model
Authors: Sharififard Ebrahim , Azizipour Mohamad , Ahadiyan Javad , Haghighi Ali
Published: October 2024

This study introduces a novel framework for the estimation of creep function coefficients in viscoelastic pipelines, employing a combination of machine learning (ML) and transient hydraulics. Specifically, the efficacy of eXtreme Gradient Boosting (XGBoost) as an advanced regression method is evaluated within this framework. A transient simulation model, utilizing the method of characteristics, is formulated to create the reservoir-pipe-valve (RPV) scenarios under diverse boundary conditions. After conducting model calibration, the model is used to generate datasets with the transient hydraulic responses at the measurement points. The fast Fourier transform (FFT) is then applied to transform the generated samples into the frequency domain. Feature selection is accomplished through principal component analysis (PCA) to identify optimal input variables for XGBoost. In estimating the creep function, six coefficients are employed, with the feature selection analysis indicating that each coefficient is associated with a specific signal. Importantly, it is demonstrated that attempting to estimate all six coefficients using a single set of signals is unfeasible. The results affirm the accuracy of the proposed ML-based framework in determining creep function coefficients.
A parsimonious setup for streamflow forecasting using CNN-LSTM
Authors: Pokharel Sudan , Roy Tirthankar
Published: October 2024

Significant strides have been made in advancing streamflow predictions, notably with the introduction of cutting-edge machine-learning models. Predominantly, long short-term memories (LSTMs) and convolution neural networks (CNNs) have been widely employed in this domain. While LSTMs are applicable in both rainfall-runoff and time-series settings, CNN–LSTMs have primarily been utilized in rainfall-runoff scenarios. In this study, we extend the application of CNN–LSTMs to time-series settings, leveraging lagged streamflow data in conjunction with precipitation and temperature data to predict streamflow. Our results show a substantial improvement in predictive performance in 21 out of 32 HUC8 basins in Nebraska, showcasing noteworthy increases in the Kling–Gupta efficiency values. These results highlight the effectiveness of CNN–LSTMs in time-series settings, particularly for spatiotemporal hydrological modeling, for more accurate and robust streamflow predictions.
A metamodel for sensitivity and uncertainty analysis in the modeling of loss of life due to dam failures
Authors: Duarte Juliana Maia , Costa Veber Afonso Figueiredo
Published: October 2024

Estimating the loss of life (LOL) resulting from dam-failures is required for devising emergency action plans and strategies for alert issuance and evacuation. However, current models for simulating fatalities are computationally expensive, forced by highly uncertain variables and not readily interpretable, which may limit their use in engineering and research. For circumventing these problems, we utilize the Polynomial Chaos Expansion (PCE), technique for approximating the LOL, as obtained from the agent-based model LifeSim, and propagating uncertainty of inputs, namely, alerted population, mobilized population, alert issuance and hazard identification, to the model responses. We also benefit from the PCE spectral representation for assessing the effects of each input in the LOL associated with the dam-failure in an urban area in Brazil, considering efficient and inefficient scenarios for alert and evacuation, during the day and night. The PCE error ranged from 10−3 to 10−2, and the mean squared error between the metamodel output and LifeSim was between 1 and 2 fatalities. In global sensitivity analysis, the variables alert issuance and hazard identification contributed the most to the number of fatalities. These findings provide objective guidelines for implementing more effective safety measures, potentially reducing LOL resulting from a dam-break in the study area.
Discharge estimation using a rating curve developed for the Upper Erer River, Wabisheble River Basin, Ethiopia
Authors: Mummed Bedasa , Shiferaw Yilma Seleshi
Published: October 2024

The measurement of a stream flow is a vital component of water quality monitoring, geomorphology, and flooding investigations. However, the direct measurements of stream flow can be costly and challenging. To obtain a continuous record of discharge, typically the recorded stage and discharge are computed from the correlation of stage and discharge in the form of a rating curve. This study focused on the estimation of flow discharges using a rating curve equation based on data recorded at the Erer-Jijiga Bridge hydrometric station at the outlet of the upper Erer Sub-basin in Ethiopia for 2020–2021. The fitted rating curve was then used to estimate discharges from continuously recorded stages. The installation and operation of a gauging station in the Upper Erer Sub-basin will provide local and regional water sector administrators with more reliable estimates of discharge than would be available if the sub-basin was ungauged. This will also assist the local water sector to undertake water resource planning in the Upper Erer River Basin to better use the limited water resources in the region.
Insights into the Binding of Metadoxine with Bovine Serum Albumin: A Multi-Spectroscopic Investigation Combined with Molecular Docking
Authors: Kour Harman Deep , Pathania Apoorva , Pathania Anu Radha
Published: October 2024

Background:

Metadoxine, also known as pyruvate dehydrogenase activator, is a small
molecule drug that has been used in the treatment of various medical conditions. Bovine serum albumin is a commonly studied protein that serves as a plasmatic for understanding protein-drug interactions due to its abundance.

Objective:

This research suggests that metadoxine can bind to bovine serum albumin with moderate
affinity, leading to an alteration in the secondary structure of the protein, which may also influence
the protein's stability and function, which could provide a comprehensive understanding of the interaction at a molecular level. In this study, a variety of methodologies wereused to determine various thermodynamic parameters.

Methods:

The study uses UV-visible, Fluorescence, Fourier-transform infrared, Circular dichroism
spectroscopy, and Molecular docking to analyze the interaction between bovine serum albumin and
metadoxine, providing thermodynamic parameters for understanding the protein structure and its
binding

Result:

The binding of metadoxine with bovine serum albumin, causes a hyperchromic shift. In
fluorescence spectroscopy, the value of the Stern Volmer increases constantly with an increase in
temperature, suggesting a stronger interaction between the Metadoxine and the Bovine serum albumin, leading to dynamic quenching. Additionally, Fourier-transform infrared and circular dichroism indicated a reduction in the secondary structure of Bovine serum albumin.

Conclusion:

The interactions between metadoxine and bovine serum albumin, cause hyperchromic
shift revealed by UV-visible spectroscopy, whereas in Fluorescence spectroscopy, the value of the
Stern Volmer constant increases with an increase in temperature, suggesting a stronger interaction
between the MD and the BSA, leading to dynamic quenching. Additionally, Fourier-transform infrared and circular dichroism spectroscopy indicated a reduction in the secondary structure of the
protein, as evidenced by the shifting of the amide II band and leading to a slight decrease in the αhelix content. The molecular docking shows that metadoxine was docked in the subdomain IIA
binding pocket of BSA.
Trends of Artificial Intelligence (AI) Use in Drug Targets, Discovery and Development: Current Status and Future Perspectives
Authors: Mohapatra Manmayee , Sahu Chittaranjan , Mohapatra Snehamayee
Published: October 2024

The applications of artificial intelligence (AI) in pharmaceutical sectors have advanced
drug discovery and development methods. AI has been applied in virtual drug design, molecule
synthesis, advanced research, various screening methods, and decision-making processes. In the
fourth industrial revolution, when medical discoveries are happening swiftly, AI technology is essential
to reduce the costs, effort, and time in the pharmaceutical industry. Further, it will aid
“genome-based medicine” and “drug discovery.” AI may prepare proactive databases according to
diseases, disorders, and appropriate usage of drugs which will facilitate the required data for the
process of drug development. The application of AI has improved clinical trials on patient selection
in a population, stratification, and sample assessment such as biomarkers, effectiveness measures,
dosage selection, and trial length. Various studies suggest AI could be perform better compared
to conventional techniques in drug discovery. The present review focused on the positive impact
of AI in drug discovery and development processes in the pharmaceutical industry and beneficial
usage in health sectors as well.
Characterization of the Cytotoxic Effect of Naphthalenacetamides Hydrochlorides on Cervical Cancer-Derived Cells
Authors: Martinez-Nava Cristina , Perez-Gonzalez Cuauhtemoc , Zavala-Sanchez Miguel Ángel , Perez-Montiel Erick Cuauhtemoc , Lopez-Munoz Francisco Javier , Mendez-Cuesta Carlos Alberto
Published: October 2024

Introduction:

Cervical cancer is a global health problem due to its high incidence and
prevalence in women, mainly in third-world countries. For the treatment of this disease, there are
different therapeutic options, but these are not always effective, which gives rise to the search for
new compounds using cheminformatics tools.

Objective:

The objective of this study was to design, synthesize, and biologically evaluate N-(2-
morpholinoethyl)-2-(naphthalen-2-yloxy)acetamide hydrochloride (1) and 2-(naphthalen-2-yloxy)-
N-(2-(piperidin-1-yl)ethyl)acetamide hydrochloride (2) on the HeLa cell line in vitro. The referenced
cell line from the American Type Culture Collection (ATCC®CCL-2™) was used, and the
effect on cell viability was determined by MTT metabolic reduction-based assay at 24, 48, and 72
h.

Methods:

Therapies directed at the σ1 receptor may be a treatment alternative since this receptor
modulates the processes of cell proliferation and angiogenesis, producing cytoprotective or cytotoxic
actions depending on the ligand with which it is coupled.

Results:

The analysis showed that compounds 1 and 2 presented activity on HeLa cancer cells and
viability at micromolar concentrations (1.923 μmol/mL and 0.374 μmol/mL, respectively). Moreover,
the effect was maintained for 72 h.

Conclusion:

Naphthaleneacetamide derivatives exhibited an inhibitory effect on the HeLa cell line,
and the OSIRIS program predicted less toxicity than cisplatin.