bluuebunny/crossref_metadata_2025 huggingface dataset:
ANALISIS GESTURE SISWA DALAM MENYELESAIKAN SOAL CERITA MATEMATIKA
Authors: Ayu Puspitasari Melinda , Kholifatul Mukaromah  , Hendra Herlambang Nugroho  , Siti Masitho Desinta Rizkia  , Nurhandayany  , Nuril Mumtaz  , Dwi Safitri  , Indah Setyo Wardhani
Published: November 2024

Menganalisis gesture siswa SD penting untuk dilakukan. Tujuan dari penelitian ini adalah menganalisis gesture siswa SD dalam menyelesaikan soal cerita matematika. Subjek penelitian adalah 39 siswa kelas V SDN Tunjung 1 Bangkalan. Metode penelitian berupa kualitatif deskriptif. Instru­men penelitian berupa tes materi luas bangun datar dan dokumentasi. Hasil penelitian berupa gesture yang dilakukan siswa berupa gesture representasi, menunjuk, dan menulis. Implementasi penelitian menjadi kajian guru dalam memahami gesture siswa Ketika menyelesaikan masalah matematika.
Analyzing elementary school students' gestures is important to do. The purpose of this study was to analyze elementary school students' gestures in solving mathematical story problems. The subjects of the study were 39 fifth grade students of SDN Tunjung 1 Bangkalan. The research method was descriptive qualitative. The research instrument was a test of the area of ​​data and documentation. The results of the study were gestures made by students in the form of gesture representation, pointing, and writing. The implementation of the research became a teacher's study in understanding students' body movements when solving mathematical problems.
ANALISIS KESULITAN SISWA DALAM MEMECAHKAN SOAL CERITA MATERI PERKALIAN BERDASARKAN TEORI NEWMAN
Authors: Fatimah Azzahroh  , Putri Aura Condrowati  , Uswatul Hasanah  , Saniyatus Safaah  , Indah Setyo Wardhani
Published: November 2024

Tujuan penelitian ini untuk menganalisis kesulitan siswa dalam memecahkan soal cerita materi perkalian berdasarkan teori Newman. Metode penelitian ini adalah penelitian kualitatif deskriptif. Teknik pengumpulan data melalui observasi, wawancara dan tes tertulis. Subjek penelitian ini adalah 5 siswa kelas III SDN Gili Timur 3 Bangkalan. Hasil penelitian menunjukkan bahwa: (1) 6% siswa kesulitan dalam membaca (reading), (2) 6% siswa kesulitan dalam memahami (comprehension), (3), 12% siswa kesulitan dalam transformasi (transformation), (4) 76% siswa kesulitan dalam keterampilan proses (process skill), dan (5) 62% siswa kesulitan dalam menulis jawaban (encoding). Faktor-faktor yang menjadi penyebabnya adalah siswa tidak lancar membaca soal, siswa melakukan kesalahan dalam menuliskan urutan pengerjaan secara lengkap, siswa melakukan kesalahan dalam peroses perhitungan, siswa melakukan kesalahan dalam menuliskan jawaban, serta siswa melakukan kesalahan dalam menuliskan bentuk satuan. Jadi dapat disimpulkan bahwa kesulitan siswa dalam memcahkan masalah matematika berbentuk soal cerita banyak dialami pada tahap keterampilan proses dan menulis jawaban.
The implementation of this research becomes material for teacher study in order to maximize students' habit of reading story questions, understanding story questions, carrying out story problem solving procedures and re-examining the results of solving story problems. The aim of this research is to analyze students' difficulties in solving multiplication story problems based on Newman's theory. This research method is descriptive qualitative research. Data collection techniques through observation, written tests and interviews. The research subjects were class III students at UPTD SDN Gili Timur 3 Bangkalan. The results showed that: (1) 6% of students had difficulty in reading, (2) 6% of students had difficulty in understanding, (3), 12% of students had difficulty in transformation, (4) 76% students have difficulty in process skills, and (5) 62% of students have difficulty in writing answers (encoding). Factors that cause this are that students are not fluent in reading the questions, students make errors in writing the complete order of work, students made mistakes in the calculation process, student made mistakes in writing the answer, and students made mistakes in writing the unit form. So it can be concluded that the difficulties student in solving mathematical problems are mostly experienced at the stage of process skills and writing answers. Experienced at the stage of process skills and writing answers.
Future Graduate Competencies: Perception of Lebanese Accounting Graduates, Academics, and Employers
Authors: Rkein Hassan I. , Hejase Hussin J. , Rkein Ali , Hamdar Bassam , Shehadeh Mohammad
Published: November 2024

Universities continue to be concerned about employers’ demands for competent graduates who are job-ready. In response, universities have addressed this challenge by developing students' professional capabilities and skills that meet the job market expectations. Hence, universities have increasingly integrated various educational means throughout their curricula. These supporting means included adopting dynamic teaching and learning methods that foster critical thinking and enhance the analytical ability of the graduates. That was also in addition to incorporating work-integrated learning, facilitating employers’ visitations, and direct involvement in advising course development and review.This study aims to analyze the main stakeholders in the accounting education system, namely accounting students, teaching instructors, and employers, and compare their perspectives on the competencies required of accounting graduates. This research also seeks to identify the competency gap by analyzing the gap matrix and suggesting solutions based on comparing different viewpoints. To achieve the objectives necessitates a quantitative research approach using a survey questionnaire administered to 116 respondents, comprising 56 employers, 45 accounting students, and 15 accounting instructors. Participation in the survey is voluntary.The findings reveal significant differences between students' and employers’ perceptions of required accounting competencies compared to the instructors'. The most significant competencies identified include soft skills, accounting technical skills, problem-solving abilities, ethical considerations, and digital literacy. These findings provide valuable insights for policymakers in the workplace and universities to bridge differences and close competency gaps.
Effect of light intensity on removal of contaminants in tilapia residual effluents with mocroalgae
Authors: Sánchez-Sánchez Hilda Janet , Ortega-Clemente Luis Alfredo , Robledo-Narváez Paula Natalia , Pérez-Legaspi Ignacio Alejandro , Miranda-Medina Anilú
Published: November 2024

Residual aquaculture effluents are discarded into the environment, causing adverse effects on water bodies through eutrophication. Therefore, looking for a treatment that extracts the contaminants and adds benefits by cultivating microalgae in the effluents is necessary. In this research, Chlorella vulgaris and Nannochloropsis oculata were cultivated in aquaculture waste effluent using two lighting conditions (40.5 and 72.9 μmol m–2 s–1). The results show that the time the exponential and stationary phases are reached was not influenced by light, but cell growth, production, and biomass productivity were. The best results were for the condition of 72.9 μmol m–2 s–1 in stationary phase (4.62×107 ± 2.12×105 and 4.45×107 ± 2.33×106 cell mL–1; 0.684±0.124 and 0.718±0.122 g L–1; 0.043 ± 0.008 and 0.048 ±0.008 g L–1 d–1) with C. vulgaris and N. oculata, respectively. Cultures at 72.9 μmol m–2 s–1 and the stationary phase were better for removing nitrates, phosphates, and COD (80-97%, 25-50%, and 43-89%) in microalgae and growth phases. While for ammonium and nitrites, the highest removal efficiency was obtained with 40.5 μmol m–2 s–1 in the stationary phase. Therefore, light intensity is an essential factor to consider when there are high concentrations of contaminants On the other hand, the light intensity of 72.9 μmol m–2 s–1 was also the most suitable for the highest biomass production and productivity in the stationary phase.
Explanatory Depth and the Integration of Special Relativity and Quantum Mechanics
Authors: Kahan Dennis
Published: November 2024

Despite nearly a century of development, quantum theories that address the special relativity-quantum mechanics tension still struggle with limited explanatory depth. Given the fundamental differences between the two core theories, this is not surprising. Quantum theories that rely on mathematical constructs to explain particle or quantum state dynamics often struggle to reconcile with special relativity’s constraints in a physical 4D spacetime. This paper explores the explanatory depth of a tightly integrated, physically grounded approach to reconciling special relativity and quantum mechanics based on a dual ontology framework where a discrete 4D spacetime and an ultra-high-dimensional space are integrated facets of a physically unified universe. The approach provides a theoretical framework that adheres to special relativity’s laws, conforms with quantum experiments challenging special relativity’s constraints, and establishes a physical one-to-one correspondence between quantum phenomena across both dimensions. The strength of the analysis lies in its physical explanatory depth. Without relying on ad hoc, fine-tuning, or perturbative techniques, the model examines physical solutions for some of the most challenging special relativity-quantum mechanics problems, including (1) quantum entanglement and nonlocality, (2) the instantaneity of quantum collapse, (3) causality, (4) the nature of time, (5) quantum state localization, (6) ) quantum tunneling, (7) the relativity of simultaneity, (8) relativistic energy increase, and (9) the Born Rule's relationship to special relativity’s constraints.
Analyzing Forecasting Errors in 3PL Logistics: A Case Study on Pharmaceutical and Household Appliance Channels
Authors: Wolny Maciej , Kmiecik Mariusz
Published: November 2024

Purpose: The study aims to analyze forecast errors for various time series generated by a 3PL logistics operator across ten distribution channels managed by the operator.
Design/methodology/approach: The research focused on ten distribution channels served by a 3PL logistics operator utilizing the Google Cloud AI forecasting tool as part of the Google Cloud AI service. The R environment was used in the study. The research centered on analyzing forecast error series, particularly decomposition analysis of the series, to identify trends and seasonality in forecast errors.
Findings: The analysis of forecast errors reveals diverse patterns and characteristics of errors across individual channels. Statistical tests for various channels show significant differences in forecast error groups in some cases, suggesting that the forecasting tool may perform more accurately for certain channels than others. A systematic component was observed in all analyzed Household Appliance Channels (seasonality in all channels, and no significant trend identified only in Channel 10). In contrast, significant trends were identified in one Pharmaceutical Channel (Channel 02), while no systematic components were detected in the remaining channels within this group.
Research limitations: Logistics operations typically depend on numerous variables, which may affect forecast accuracy. Additionally, the lack of information on the forecasting models, mechanisms (black box), and input data limits a comprehensive understanding of the sources of errors.
Value of the paper: The study highlights the valuable insights that can be derived from analyzing forecast errors in time series within the context of logistics operations. The findings underscore the need for a tailored forecasting approach for each channel, the importance of enhancing the forecasting tool, and the potential for improving forecast accuracy by focusing on trends and seasonality. This analysis makes a significant contribution to the theory and practice of demand forecasting by logistics operators in distribution networks. The research offers valuable contributions to ongoing efforts in demand forecasting by logistics operators.
Keywords: time series of forecasting errors, 3PL, logistics operator, demand forecasting, distribution channels,
Redefining Roles: A Paradigm Shift in Tryptophan-Kynurenine Metabolism for Innovative Clinical Applications
Authors: Tanaka Masaru , Szabó Ágnes , Vécsei László
Published: November 2024

The tryptophan-kynurenine (KYN) pathway has long been recognized for its essential role in gen-erating metabolites that influence various physiological processes. Traditionally, these metabolites have been categorized into distinct, often opposing groups, such as pro-oxidant versus antioxidant, excitotoxic versus neuroprotective, or neurotoxic versus neuroprotective. This dichotomous framework has shaped much of the research on conditions like neurodegenerative and neuropsy-chiatric disorders, as well as cancer, where metabolic imbalances are a key feature. The effects are significantly influenced by various factors, including the concentration of metabolites and the par-ticular cellular milieu in which they are generated. A molecule that acts as neuroprotective at low concentrations may exhibit neurotoxic effects at elevated levels. The oxidative equilibrium of the surrounding environment can alter the function of KYN from an antioxidant to a pro-oxidant. This narrative review offers a comprehensive examination and analysis of the contemporary under-standing of KYN metabolites, emphasizing their multifaceted biological functions and their rele-vance in numerous physiological and pathological processes. This underscores the pressing ne-cessity for a paradigm shift in the comprehension of KYN metabolism. Understanding the con-text-dependent roles of KYN metabolites is vital for novel therapies in conditions like Alzheimer’s, multiple sclerosis, and cancer. Comprehensive pathway modulation, including balancing in-flammatory signals and enzyme regulation, offers promising avenues for targeted, effective treatments.
An Outdoor Air Quality at a Residential Environment in Lagos, Nigeria Using Airly Low-Cost Sensor
Authors: Akinnusotu Akinyinka , Abulude Francis Olawale , Oluwagbayide Samuel Dare , Arifalo Kikelomo Mabinuola , Sunday Acha
Published: November 2024

Human health is at risk when particulate matter levels reach a certain threshold, and determining these levels is crucial for mitigating environmental pollution. Since there is a lack of data in this field of study, it is anticipated that this work will provide stakeholders with data. On the basis of this supposition, an Airly sensor was used to assess the air quality at a location in Mafoluku, Lagos, Nigeria. Following the manufacturer's instructions, the installation was done at a height of 1.8 meters above the ground. Outdoor PM1, PM2.5, PM10, PM ratios, toxicity potentials (T/P), climatic factors, and their correlations were measured during a two-month period. The findings indicate that the levels of PM10, PM2.5, and PM1 were 36.12 μg/m3 (equivalent to 80.7% of the WHO annual limit), 34.83 μg/m3 (equivalent to 232.23% of the WHO annual limit), and 34.39 μg/m3 (no limit for the calculation), respectively. The corresponding average ratios were 0.98, 0.95, and 0.93. The majority of T/P values were greater than 1, which suggests that there are health risks to the area's most vulnerable residents. Winds from the southwestern desert influenced the air mass, and WHO limits are often exceeded. The study suggests stakeholders focus on problem reduction to mitigate air pollution risks.
Advances in Deep Brain Imaging with Quantum Dots: Structural, Functional, and Disease Specific Roles
Authors: Connor Tenesha , Weerasinghe Hemal , Lathia Justin , Burda Clemens , Yildirim Murat
Published: November 2024

Quantum dots (QDs) have emerged as promising tools in advancing multiphoton microscopy (MPM) for deep brain imaging, addressing long-standing challenges in resolution, penetration depth, and light-tissue interactions. MPM, which relies on nonlinear photon absorption, enables fluorescence imaging within defined volumes, effectively reducing background noise and photobleaching. However, achieving greater depths remains limited by light scattering and absorption, compounded by the need for balanced laser power to avoid tissue damage. QDs, nanoscale semiconductor particles with unique optical properties, offer substantial advantages over traditional fluorophores, including high quantum yields, large absorption cross-sections, superior photostability, and tunable emission spectra. These properties enhance signal to background ratio at increased depths and reduce scattering effects, making QDs ideal for imaging subcortical regions like the hippocampus without extensive microscope modifications. Studies have demonstrated the capability of QDs to achieve imaging depths up to 2100 μm, far exceeding that of conventional fluorophores. Beyond structural imaging, QDs facilitate functional imaging applications, such as high-resolution tracking of hemodynamic responses and neural activity, supporting investigations of neuronal dynamics and blood flow in vivo. Their stability enables long-term, targeted drug delivery and photodynamic therapy, presenting potential therapeutic applications in treating brain tumors, Alzheimer’s disease, and traumatic brain injury. This review highlights the impact of QDs on MPM, their effectiveness in overcoming light attenuation in deep tissue, and their expanding role in diagnosing and treating neurological disorders, positioning them as transformative agents for both brain imaging and intervention.
Metabolic Dysfunction-Associated Steatotic Liver Disease and Pancreaticoduodenectomy; a Narrative Review
Authors: Sotoudeheian Mohammadjavad
Published: November 2024

Metabolic dysfunction-associated steatotic liver disease (MASLD) has become increasingly recognized as a postoperative complication in patients undergoing pancreatic surgeries, particularly pancreaticoduodenectomy (PD). Given MASLD’s prevalence and impact on liver function and postoperative outcomes, understanding its incidence, risk factors, and potential interventions is critical for patient care. This study reviewed the relation between MASLD and PD. Studies indicate that MASLD’s incidence ranges from 13.2% to 31% in post-PD patients, with notable variation influenced by factors such as sex, body mass index, and nutritional deficiencies. PD, performed to treat pancreatic or bile duct disease, is associated with considerable postoperative physiological changes. These include disruptions in pancreatic enzyme production, which can impair digestion, metabolism, and potentially contribute to MASLD in susceptible patients. Patients with MASLD post-PD show lower liver-to-spleen attenuation ratios on imaging and often require intensified pancreatic enzyme replacement. A scoring system based on risk factors has been developed to identify patients at higher risk of MASLD and guide preventive nutritional support. MASLD is a prevalent complication post-PD that impacts recovery and treatment continuity in cancer patients. Early risk stratification, tailored enzyme therapy, and ongoing monitoring may reduce MASLD-related liver impairment, enhancing patient outcomes.
The Assessment of Enterprise Risk Management Practices of Ethiopian Commercial Banks
Authors: Biresaw Tsega Meseret , Sibindi Athenia Bongani
Published: November 2024

The study aims to examine the enterprise risk management (ERM) practices of Ethiopian commercial banks. This approach is undertaken to examine the current approach to enterprise risk management within the Ethiopian banking context. Mixed methods research design is employed which comprises content analysis and survey. The study found that the prevailing emphasis of risk management functions in Ethiopian commercial banks revolves on ensuring compliance with regulatory reporting standards. A significant number of the banks have implemented ERM programs primarily to meet regulatory obligations, rather than leveraging ERM to generate firm value. The study identified several gaps in the risk management function of Ethiopian commercial banks, including: lack of integration of risk management with the banks' mission and core values, failure to assess the resources required for effective risk management and to prioritize resource allocation accordingly, inadequate coverage of relevant activities and functional areas by both risk management and internal audit activities, and limitations on the assignment of Chief Risk Officers (CROs) to oversee the risk management function within the banks. Overall, the maturity level of ERM implementation among Ethiopian commercial banks is moderate and requires further enhancement.
Development of an Analytical Model for Predicting the Tensile Modulus of Complex Polypropylene Compounds: A Comparative Study with Artificial Neural Networks
Authors: Seifert Lukas , Leuchtenberger-Engel Lisa , Hopmann Christian
Published: November 2024

The extensive use of polypropylene (PP) in various industries necessitates the development of efficient and reliable methods for predicting the mechanical properties of PP compounds. This study presents the development of an analytical model (AM) designed to predict the tensile modulus of PP compounds with various fillers and additives, including chalk, impact strength modifiers, and peroxide additives. The AM, incorporating both logarithmic and linear compo-nents, was benchmarked against an Artificial Neural Network (ANN) to evaluate its performance. The results demonstrate that the AM consistently outperforms the ANN, achieving lower Mean Absolute Error (MAE) and higher Coefficient of Determination (R²) values. The simplicity and robustness of the AM make it a useful tool for the plastics industry, providing a practical approach to optimising compound formulations with minimal empirical testing.
Resource Characterisation and Biogas Potential Determination of Cassava and Plantain Peels Using Theoretical and Hbt Based Experiments
Authors: Yankyera Kusi Joseph , Empl Florian , Müller Ralf , Pelz Stefan , Poetsch Jens , Sailer Gregor , Kirchhof Rainer , Agyemang Derkyi Nana Sarfo , Attiogbe Francis
Published: November 2024

This research aimed to evaluate the comparative biogas yields of waste (peels) of selected relevant fibrous materials from the West African region: Cassava, plantain, a mixture of cassava, plantain and yam. Three models: The Boyle model, the Modified Boyle’s model, and the Buswell and Müller model were used to determine the theoretical maximum biomethane potentials (TMBP), while the Hohenheim biogas yield test was used to undertake a batch test of anaerobic digestion. With an operating temperature of 37±0.5 ℃, the samples were co-digested with digested sewage sludge (DSS) for 39 days. Comparisons are drawn between the TBMPs and the experimental results, the experimental results of the different substrates and the experimental results and figures reported in literature. From the experimental results, plantain peels had the highest biogas yield (468±72 ml/g oTS), followed by a mixture of yam, cassava and plantain peels (362±31 ml/g oTS) and cassava peels obtained the least biogas yield (218±19 ml/g oTS). TMBPS of 204.04, 209.03 and 217.45 CH4 ml/g oTS were obtained for plantain peels, a mixture of yam, cassava and plantain peels and cassava peels respectively, evaluated using the Boyle’s model. For all the samples, the TMBPS (205.56, 209.03 and 218.45 CH4 ml/g oTS respectively) obtained using the Buswell and Mueller model were slightly higher than those obtained by both the Boyle and the modified Boyle’s model (163.23, 167.22 and 174.76 CH4 ml/g oTS respectively).
Research on GNSS/IMU/Visual Fusion Positioning Based on Adaptive Filtering
Authors: Liu Ao , Guo Hang , Yu Min , Xiong Jian , Liu Huiyang , Xie Pengfei
Published: November 2024

The accuracy of satellite positioning results depends on the number of available satellites in the sky. In complex environments such as urban canyons, the effectiveness of satellite positioning is often compromised. To enhance the positioning accuracy of low-cost sensors, this paper combines the visual odometer data output by Xtion with the integrated navigation data output by the satellite receiver and MEMS IMU both in the mobile phone through adaptive Kalman filtering to improve positioning accuracy. Studies conducted in different experimental scenarios have found that in unobstructed environments, the RMSE accuracy of GNSS/IMU/visual fusion positioning improves by 50.4% compared to satellite positioning and by 24.4% compared to GNSS/IMU positioning. In obstructed environments, the RMSE accuracy of GNSS/IMU/visual fusion positioning improves by 57.8% compared to satellite positioning and by 36.8% compared to GNSS/IMU integrated positioning.
Leveraging ChatGPT for Enhancing Breast Cancer Detection Using Machine Learning
Authors: Singh Shreyansh
Published: November 2024

Breast cancer is one of the most common and life-threatening diseases affecting women globally. Early and accurate detection is crucial for improving patient outcomes and reducing mortality rates. Machine learning (ML) models have demonstrated remarkable potential in assisting with breast cancer diagnosis through data-driven approaches that can identify patterns in complex datasets more effectively than traditional methods. In this context, ChatGPT, an advanced language model, offers valuable assistance by enhancing several aspects of the breast cancer detection process, such as model development, data preprocessing, and troubleshooting. It supports researchers by providing real-time code generation, model optimization techniques, and detailed explanations of ML concepts, thereby streamlining the process of building accurate and robust models. This paper discusses the ways ChatGPT aids in breast cancer detection using machine learning, including technical guidance, code generation, and knowledge enhancement, making AI-driven healthcare research more accessible.
What Chat GPT Has to Say About Its Topological Structure: The Anyon Hypothesis
Authors: Planat Michel , Amaral Marcelo M
Published: November 2024

The large language model Chat GPT answers questions relative to its structure under the supervision of the authors. Then we postulate that modular tensor categories, alias the theory of anyons, are relevant for partially explaining the topological structure of large neural networks such as GPT. Mathematical details are summarized in an independent section.
A Symmetry and Conservation Framework for Photon Energy Interactions in Gravitational Fields
Authors: Thakur Soumendra Nath
Published: November 2024

This study extends the framework for photon energy interactions within gravitational fields by distinguishing between intrinsic photon energy (E) and gravitational-interaction energy (Eg). The investigation builds upon prior research concerning symmetrical energy and momentum exchanges, emphasizing how photons, while traversing gravitational wells, gain and expel Eg symmetrically, without altering their intrinsic energy (E). This distinction demonstrates that as photons move through gravitational fields, they acquire Eg from the field, which is expended as they exit the gravitational influence, preserving their inherent energy.We analyse the behaviour of photon and graviton dynamics to illustrate how Eg accumulates when photons approach gravitational wells and is symmetrically released as they move away. This results in curved photon trajectories reflecting balanced gravitational-interaction energy exchanges. The refined model bridges classical and relativistic perspectives on gravitational lensing and redshift, offering deeper insights into energy conservation and symmetry principles governing photon behaviour in gravitational fields.This framework clarifies the photon’s dual energy components—E and Eg—each with distinct interactions under gravitational influence. The study underscores the importance of distinguishing these energies to better understand the mechanics of gravitational redshift, energy conservation, and the overall behaviour of photons within varying gravitational potentials.
Spatially Modulated Plasma Profile for Turbulence and Instabilities Mitigation in Fusion Plasma
Authors: Shesterikov Ilya
Published: November 2024

This work explores a novel approach to mitigating turbulence in fusion plasmas through spatially modulated plasma profiles. By imposing a harmonic modulation on plasma parameters, we introduce conditions that alter the propagation characteristics of turbulent and MHD waves, a primary source of transport and instabilities in fusion devices. This modulation approach resembles bandgap formation in solid-state and photonic crystals, where spatial periodicity suppresses wave propagation within specific frequency bands. The mathematical framework developed here essentially resembles the parametric resonance of the harmonic oscillator. It reveals how a controlled spatial variation of turbulent wave phase velocity can effectively attenuate turbulence and instabilities. Several methods for implementing this modulation in plasma, including RF waves, static magnetic field perturbations, and modulated density profiles, are proposed as potential paths for achieving stable confinement. This concept could provide a versatile and potentially more controllable alternative to existing turbulence suppression techniques, with the goal of improving stability and confinement across a variety of magnetized fusion configurations.
Title: Efficacy of the Keratoconus Risk Investigative Survey (KRIS) in Detecting Keratoconus in a Secondary School Population
Authors: CHAURASIA NEHA D , Moodley Vanessa Raquel , Mashige Khathutshelo Percy
Published: November 2024

(1) Background: Keratoconus (KC) is a progressive corneal disorder that begins in adolescence and can lead to significant vision loss if undetected. Early identification of at -risk individuals through efficient screening tools like Keratoconus Risk Investigative Survey (KRIS) is critical, especially in large populations with limited access to comprehensive eyecare (2) Methods: A stratified random sample of 2,042 children, aged 9 to 17, completed a modified 20-item KRIS. Those identified with three or more risk factors underwent ophthalmic evaluations, including visual acuity, auto-keratorefractometry, and topographical screening. The analysis was conducted using SPSS version 25, focusing on sensitivity and specificity (3) Results: KRIS identified 36% (n=728) as at risk for KC, with a mean age of 12.09 years. Most were female (73%) and Muslim (72%). Significant correlations were found between demographic variables and clinical findings (p<0.001). Consanguinity showed a weaker association (Spearman: -0.09). Logistic regression indicated a strong likelihood of KC diagnosis in at-risk children (OR: 4.23, p<0.001). KRIS demonstrated moderate sensitivity (69%), specificity (66%), and overall accuracy (66%). The kappa coefficient (0.1) indicated slight agreement with clinical assessments, while the AUC of 0.57 suggested moderate screening ability. (4) Conclusions: KRIS is an effective screening tool for identifying children at risk of KC, aiding in targeted clinical assessments and reducing the need for mass screening.
Genome Wide Analysis of ROP GTPase Gene Family of Strawberry and Functional Validation of FveROP4 in Fruit Resistance to Grey Mold
Authors: Zhao Shuai , Zou Zhijun , Zhai Yushan , Liao Sufeng , Xu Ming , Li Kunyang , Mehmood Nasir , Zhu Baode , Liao Xiong
Published: November 2024

ROP small GTPases function as signaling hubs that mediate various physiological processes, including plant defense. Their specific roles in strawberry resistance against gray mold remain uncharacterized. In this study, we identified 53 ROP genes across the genomes of six Rosaceae species. Based on sequence homology, they were classified into three distinct phylogenetic clades. Detailed analysis of FveROP proteins revealed the presence of highly conserved catalytic-G-domains, which are essential for their GTPase activity. By conducting transient overexpression experiments in strawberry fruits challenged with the gray mold pathogen Botrytis cinerea, we investigated the impact of the FveROP4 gene on disease resistance. The overexpression of both wild-type and constitutively active forms of FveROP4 enhanced resistance against B. cinerea infection. Subsequent analysis revealed that the overexpression of FveROP4 and FveCAROP4 genes led to increased accumulation of reactive oxygen species. Moreover, FveROP4 was localized on the plasma membrane, where it interacts directly with FveRBOHF1, corroborating the results obtained through yeast two-hybrid and luciferase complementation imaging assays. The study findings may provide valuable insights for investigating the mechanisms of ROP signaling in regulating the immune response in strawberry and can be used to enhance plant traits for extended fruit shelf-life.
Radiosurgery for Intracranial Meningiomas: A Review of Anatomical Challenges and an Update on The Evidence
Authors: Goldman Matthew J , Teh Bin S , Lo Simon S , Butler Edward B , Baskin David S
Published: November 2024

Radiation has been used to treat meningiomas since the mid-1970s. Traditionally, radiation was reserved for patients unfit for major surgery or those with surgically inaccessible tumors. With an increased quantity and quality of imaging and an aging population, there has been a rise in incidentally diagnosed meningiomas in patients with smaller tumors at the time of diagnosis. Deciding if, how, and when to intervene must be determined on a case-by-case basis. Anatomical location and adjacent vital structures are crucial for decision-making. Prior review articles have detailed outcomes of radiosurgery in broad anatomical regions such as the skull base, but there has been a deluge of recent research on increasingly specific anatomical subregions. This review synthesizes information regarding specific anatomical subregions, including anatomical challenges, radiosurgical outcomes, and unique considerations. We utilized the highest levels of evidence available for each region, discuss details of published research, and explore future directions. Meningioma management remains individualized based on patient comorbidities, tumor location/characteristics, symptomatic burden, and patient age. In addition to SRS’s established role for surgically inaccessible, recurrent, and high-grade meningiomas, the use of SRS as upfront management for small asymptomatic meningiomas is increasingly investigated. For all sub-regions reported, radiosurgical intervention resulted in high tumor control rates and acceptably low adverse radiation events.
Modulating Amyloid-β Toxicity: In Vitro Analysis of Aβ42(G37V) Variant Impact on Aβ42 Aggregation and Cytotoxicity
Authors: Huang Shu-Hsiang , Fang Shang-Ting , Yang Chin-Hao , Liou Je-Wen , Chen Yi-Cheng
Published: November 2024

Alzheimer's disease (AD) is primarily driven by the formation of toxic amyloid-β (Aβ) aggregates, with Aβ42 being a pivotal contributor to disease pathology. This study investigates a novel approach to mitigating Aβ42-induced toxicity by co-assembling Aβ42 with its G37V variant (Aβ42(G37V)), where Gly at position 37 is substituted with Valine. Using a combination of Thioflavin-T (Th-T) fluorescence assays, Western blot analysis, atomic force microscopy (AFM)/transmission electron microscopy (TEM) and biochemical assays, we demonstrated that adding Aβ42(G37V) significantly accelerates Aβ42 aggregation rate and mass while altering the morphology of the resulting aggregates. Consequently, adding Aβ42(G37V) reduces the Aβ42 aggregates-induced cytotoxicity, as evidenced by improved cell viability assays. The possible mechanism for this effect is that adding Aβ42(G37V) reduces the production of reactive oxygen species (ROS) and lipid peroxidation, typically elevated in Aβ42, indicating its protective effects against oxidative stress. These findings suggest that Aβ42(G37V) could be a promising candidate for modulating Aβ42 aggregation dynamics and reducing its neurotoxic effects, providing a new avenue for potential therapeutic interventions in AD.
An Analytical Solution to Rectangular Isotropic Kirchhoff Plates Having Two Adjacent Edges Free Using Two Single Series and the Boundary Collocation Method
Authors: Fogang Valentin
Published: November 2024

An analytical solution to arbitrarily loaded isotropic rectangular Kirchhoff plates supported at three corner points, having two adjacent edges free and the other edges being simply supported, clamped or free, was presented. Analytical methods such as the single trigonometric series of Lévy or the double trigonometric series of Navier are not applicable here because of the adjacent free edges. In this paper the deflection surface was approximated with the sum of a particular solution to the governing differential equation (GDE) and two single series. The terms of the single series were the product of an unknown function of an independent variable and a trigonometric function of the other independent variable, whereby the trigonometric functions were consistent with the deflection-related boundary conditions (zero deflection or not along an edge). On the one hand the terms of the series were required to satisfy the homogeneous GDE, leading to two uncoupled differential equations, one for each unknown function, and so the approximate solution satisﬁed exactly the GDE. On the other hand the boundary conditions were satisﬁed only at selected collocation points along the boundary, the number of collocation points in each direction corresponding to the number of terms of the associated series. The results obtained showed a reasonable agreement with the exact results, the accuracy increasing the more terms of series were considered. So a powerful computation tool is needed to consider higher number of terms of the series and so to approach the exact results. Cantilevered plates will be analyzed using this approach in future research.
Minimum Night Flow estimation in District Metered Areas
Authors: Tricarico Carla , Cappello Cristian , de Marinis Giovanni , Leopardi Angelo
Published: November 2024

The residential minimum water demand characterization is of fundamental importance for water distribution systems management. During the minimum consumption, indeed, maximum pressures are on network pipes and at the same time tank levels rise. The legitimate water consumption analysis during period of low demand and high pressure is thus of great interest for leakages estimation due to the increase of the water loss with the pressure. Previous studies have tackled this issue with deterministic approaches, by considering the legitimate consumption as a percentage of the night measured inflow. In order to contributing to the legitimate minimum residential water demand characterization, probabilistic models have been developed to study and forecast the daily minimum residential water demand. Some probability distributions have been tested by means of statistical inferences on data set collected from different District Metering Areas (DMAs), showing the stochastic minimum flow demand is described by the log-Normal (LN), Gumbel (Gu) and Log-Logistic (LL) distributions, as an extreme minimum value. The latter is of particular interest being the LL probability density function analytically integrated. With reference to the analysed DMAs, parameters of such statistical distributions have been estimated and relationship are provided in function only of the supplied users for different DMAs. Data have been analysed with 1 h interval time of discretization, with the aim of providing an useful guide to the Water Utilities which usually are managing water distribution systems data with such resolution time. Indeed, once the legitimate minimum residential flow consumption at 1h interval time is estimated in function of the users number, by subtracting it to the inflow measured, it is possible to estimate leakages rate at the DMA.
Hyperoside Attenuates the Toxic Effect of Cisplatin on the Human Ovarian Granulosa Cells: Invitro Model Study
Authors: Elmorsy Ekramy M. , Doghaither Huda A. Al , Al-Ghafari Ayat B. , Ebrahim Neven A , Amer Saad
Published: November 2024

Cisplatin (cis-diamminedichloroplatinum II) (CDDP) is an FDA approved anticancer therapy that is commonly used in women’s cancer treatment protocols, such as breast, cervical, endometrial, and gestational trophoblastic cancers. Premature ovarian insufficiency/failure is a well-known long-term risk of chemotherapy including CDDP in women. Granulosa cells (GCs) are an essen-tial ovarian cell type that promotes oocyte growth and is crucial for ovarian reproductive function. Many types of chemotherapeutic agents, such as CDDP, could induce GCs apoptosis, which could result in ovarian failure. Hyperoside (HYP) is a flavonoid known for its beneficial phar-macological properties, including anti-inflammatory and antiapoptotic effects. Hence the current work aimed to evaluate the potential cytoprotective impact of HYP on CDDP-induced cytotoxicity in a human ovarian GCs cell line model. Forty-eight-hour exposure to 5-10µM CPPD resulted in reduction of GCs viability in a dose-dependent manner. HYP (40µM) was found to ameliorate this CPPD-induced effect on GCs viability. CPPD in a concentration-dependent way, dramatically reduced cellular ATP, mitochondrial activities, cellular progesterone, and estradiol secretion. It also increased oxidative stress markers, Akt kinase activity, cytochrome c levels, caspase -3.-8.-9, and Bax/Bcl2 ratio. These cytotoxic effects of CDDP on the treated GCs, were mitigated to varying degrees by HYP (40 µM). In conclusion, CDDP-induced cytotoxic effects on GCs seem to be the possible underlying cellular and molecular mechanisms of CDDP-induced ovarian insufficien-cy/failure. The study also demonstrated the therapeutic potential of HYP in mitigating CDDP-induced ovarian injury. Further studies are warranted to investigate the potential benefit of HYP as an adjuvant to CDDP treatment protocols to avoid adverse ovarian effects.
Driving Profile Optimization for Energy Management in the Formula Student Técnico Prototype
Authors: Pires Tomás R. , Fernandes João F.P. , Branco P. J. Costa
Published: November 2024

This study addresses the challenge of optimizing energy management in the electric vehicle industry, specifically focusing on motorsport. It particularly targets optimizing energy management during an endurance event at the Formula Student competition. The research involves detailed simulation of a complete endurance event, including developing precise track and vehicle models and their application in real-time energy management of our motorsport vehicle. The primary objective is to develop an energy reference profile that optimizes point scoring following the event’s specific rules. The energy reference profile serves as a strategic guideline for energy consumption and its regeneration throughout the endurance event. What sets this study apart is its emphasis on the real-time feedback controller’s implementation in the Formula Student prototype, FST12, specifically during the Endurance event. This controller dynamically regulates the inverter’s power output, ensuring the vehicle follows the pre-established energy reference profile closely. This real-time energy management approach enhances overall performance by optimizing energy utilization for maximum scoring potential. The Formula Student prototype, FST12, undergoes experimental validation on a real 20 km closed-loop track.
Efficiency of Photobioreactor with Microalgae Strains Monoraphidium griffithi and Desmodesmus sp. for Biogas Upgrading
Authors: Drazdienė Loreta , Zagorskis Alvydas , Vasarevičius Saulius
Published: November 2024

Monoraphidium griffithii and Desmodesmus sp. microalgae cultures were exploited to examine the CO2 fixation efficiency in a bubble column photobioreactor (PBR). Two medium were used as the control groups to compare the effect of CO2 solubility in modified woods hole (MWH) medium and distilled water. Experiments were performed indoors using experimental apparatus consisting of 4 vertical bubble columns in total and injecting real biogas with 36% of CO2 and 56% of CH4 taken from wastewater treatment plant. As a result, system using Monoraphidium griffithii and Desmodesmus sp. cultures improved CO2 removal efficiency by 11.2% and 5.5% compared to MWH medium, respectively. In addition, 86.1% of the CO2 in the biogas could be captured by the Monoraphidium griffithii culture and 80.4% - by the Desmodesmus sp. culture. CH4 content in the effluent biogas increased from 56.1% to 66.4% using Monoraphidium griffithii culture. CH4 concentration in distilled water increased from 56.1% to 63.2% because CO2 is soluble in water, whereas CH4 has low solubility. Consequently, the volume of CH4 increased. After 32-36 hours, all media reached their saturation point, and the CO2 concentration returned to its starting value. The established microalgae culture system with intermittent operation could be efficiently used as a CO2 capture technology for biogas upgrading.
Climate Change Impact on the Populations of Goldcrest Regulus regulus and Firecrest Regulus Ingicapilla Migrating Through the Southern Baltic Coast
Authors: Maciag Tomasz , Remisiewicz Magdalena
Published: November 2024

Since about 2000, we observed the decline in the numbers of Goldcrests and increase in the numbers of Firecrests caught during autumn migration at two bird ringing stations, Bukowo-Kopań and Mierzeja Wiślana, on the Polish coast of the Baltic Sea over 1976–2023 . These two closely related forest bird species share similar biotopes but differ in foraging behavior and migration strategy. The changes in migrating bird abundance in autumn we observed at both ringing stations were correlated with the Pan-European breeding population trends over 1982–2022 from PECBMS project. This suggested that some Europe-wide factors are responsible for these changes. The snow cover in October decreased abundance and delayed autumn migration of Goldcrests on the Baltic coast, probably by exposing them to cold and impeding their feeding and fueling for migration. In Firecrests, the response to October snow was similar but much weaker. Firecrests, in turn, have shifted their migration earlier since late 1980’s, alleviating the effect of early winter. The warmer was October, the larger were the numbers of Firecrests on autumn migration at both stations, which suggest their good breeding success likely due to improved survival of chicks from late broods during warm autumns. Additionally, the increased number of broadleaf trees at the breeding grounds in Fennoscandia can favor the population of Firecrest, which prefers mixed forests and larger prey like spiders, over Goldcrest, which are bound to more coniferous forests, where they feed on smaller insects. If this trend continues, we expect a decline in the number of the currently numerous Goldcrest, but farther expansion of the breeding range to north-east and increase in numbers of the Firecrest, the less abundant of the two species. The change of forest management policy in Scandinavia by planting more broadleaf trees, is aimed at increasing biodiversity and can have a large impact on the forest environment, thus it is imperative to have methods for early detection of such changes. The results we presented show that monitoring the number of migrating birds can serve as a good indicator of environmental changes.