bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis, physicochemical and quantum chemical studies of 7-azaindolinium-3,5-dinitrobenzoate single crystal for nonlinear optical applications
Authors: Anandhan Arivazhagan , Sivasankari Chandrasekaran , Siva Vadivel , Al-Sehemi Abdullah G. , Kim Ikhyun , Sivaprakash Paramasivam 
Published: February 2024

Abstract
A novel hydrogen bonded single crystal of 7-azaindolinium-3,5-dinitrobenzoate (7AIDNB) has been grown, and the structure of the crystal was determined by single-crystal XRD analysis. The results show that the grown crystal belongs to a triclinic crystal system with centrosymmetric space group P-1 and the unit cell parameters: a = 6.998(9) Å, b = 8.498(12) Å, c = 13.103(17) Å, V = 710.78(17) Å3, Z = 2. The presence of expected discrete functional groups in 7AIDNB has been identified by an FT-IR spectroscopic study. The thermal stability and decomposition of the title crystal have been studied by TG-DTA analysis. The optical property of the grown crystal has been analyzed by UV-Vis-NIR spectroscopy analysis. The DFT with 6-311++G(d, p) basis set has been used to examine optimization of molecular geometry, Mulliken charge, and HOMO-LUMO. As the frequency of the grown crystal increases, the dielectric loss and dielectric constant decrease. The third-order NLO parameters of 7AIDNB have been examined by a Z-scan technique.
Multi-attribute Feature Fusion Algorithm of IoT Communication Big Data Based on Ant Colony Neural Network
Authors: Li Ruihua , Feng Zhidong , Guo Hongbo 
Published: February 2024

Abstract
To address the issues of time-consuming and inaccurate feature fusion in traditional Internet of Things (IoT) communication big data multi-attribute fusion algorithms, a new algorithm based on the ant colony neural network is proposed. Modeling and feature decomposition processing is carried out on IoT communication big data, communication data information and data attribute characteristics are optimized into different data groups according to a data clustering algorithm, and a rough set calculation method is used to calculate information attribute characteristics. The genetic algorithm is used to improve the ant colony neural network, improve the search ability, extract the multi-attribute characteristics of IoT communication big data, filter the current big data’s characteristic attribute demand through the comparison method, and achieve multi-attribute feature fusion of IoT communication big data through the similarity measurement method. The experimental results show that the fusion error of the IoT communication big data multi-attribute feature fusion algorithm based on the ant colony neural network is small and relatively stable. During the 600 MB data fusion process, the data fusion processing time of the method in this paper is 150 ms, and the average energy consumption ratio is below 2 %, which reflects better IoT communication big data multi-attribute feature fusion performance.
A study Electronic structure of InSb: Experiment and Theory
Authors: Mohammed Sameen F. , Mohammed Mahmood A. 
Published: February 2024

The current study show the results related to investigating the Compton scattering(Cs) of Indium Antimonite (InSb). 241Am with 59.54 keV Gamm-radiations source Compton spectrometer is employed for the purpose of experimental measurement. The technique of linear combination of atomic orbitals (LCAO) is utilized within the framework of density functional theory (DFT),is used to assess the theoretical values of distributing the electron momentum density. A comparison was then made between the research findings and empirical data. Additionally, calculations employing the ionic model (IO) based on the 5p state of In and the 5p state of Sb atoms reveal that 0. 5 electrons of the state of 5pIn may have been transferred to the 5p state of Sb atoms in order to estimate the charge transfer in indium antimonite (InSb).
Children Don't Like Eating What They're Supposed to Eat… A Study of Public Catering for Children in Hungary from a Historical Perspective
Authors: Nickel Vira Réka 
Published: February 2024

AbstractChildhood nutrition is an important element of lifestyle research, since the regularity and nutritional content of our meals as children, and the way in which they are eaten, determine our physical and mental health throughout our lives. Prior to 2018, there was no basic interdisciplinary research on this topic in Hungary, thus to fill the gap, an interdisciplinary research group was established in 2018 at the Institute of Ethnography, which carried out nationwide research. The present study is based on fieldwork undertaken by the author in two schools — the János Lenkey Primary School in Eger (formerly Primary School No. 1) and the Tamás Bolyki Primary School in Ózd — as well as a large amount of information gleaned from questionnaires and interviews. My research was also extended in terms of a historical and geographical perspective: I studied archival sources and expanded the field of my investigations by including Salgótarján, a research location familiar from my earlier research, which provided a vantage point alongside Ózd and Eger, as a third city typical of Northern Hungary. Public catering for children has undergone significant changes in the last six to seven years, although prior to this it had appeared relatively uniform, in line with the ingredients available at the time. The obligation to provide public catering and the general obligation to work, which began in the Rákosi era and culminated in the Kádár era, significantly changed family eating habits. Traditional elements typical of a particular locality disappeared as the globalization efforts of socialism were accomplished. The ever-decreasing amount of time devoted to preparing, cooking, and consuming food moved society in the direction of canteens, fast-food restaurants, and later, after the regime change, global fast-food chains. Education on proper nutrition is not currently part of academic teacher training, thus for want of a better alternative, teachers organize children's school meals based on their own experience and socialization or following the school's regulations (where they exist), without having a unified concept. The number of meals eaten at home has been reduced to light breakfasts, lunches, and dinners, with families mostly sitting down together at the table for dinner, when they often consume ready meals. Lack of contact with foodstuffs and with the person preparing the food has a negative impact on children's psychological development. Relying on extensive basic research and participant observation, and through the joint efforts of specialists from several fields of the social sciences, a significant improvement could be achieved in both public catering and education on healthy nutrition.
Gamma irradiation effects on microbial and qualitative properties of rosehip (Rosa canina L.) fresh fruit during storage
Authors: Berenji Ardestani S. , Ahmadi Z. , Esfandyari Ch. 
Published: February 2024

AbstractFruit of rosehip (Rosa canina L.) has high economic, medicinal, and nutritional values. Rosehip is rarely consumed fresh due to limitations of seasonality and short shelf life. They are usually processed, which affects the nutritional and sensory characteristics of rosehip products. Radiation processing along with storage at 4 °C is a way to increase safety and prolong fresh rosehip durability. Rosehip fruits were harvested at enough maturity stage, irradiated at doses of 0 (control), 0.5, 1, and 1.5 kGy, and stored at 25 and 4 °C for 60 days. Gamma irradiation at 1 kGy caused an increase in weight loss during storage for 60 days at 25 °C. Microbial counts, total phenolic contents (TPC), total anthocyanin contents (TAC), ascorbic acid contents (AAC), DPPH• scavenging activity, total colour difference (∆Eh), and sensory properties were acceptable in the sample irradiated at 1 kGy and preserved for 60 days at 4 °C. The amounts of acidity, pH, and total soluble solids (TSS) were not significantly different from the control. Gamma irradiation at 1 kGy and thereafter storage of the irradiated fruit at 4 °C are suggested as minimal processing and storage conditions of rosehip fresh fruit (RFF) for 60 days.
The Impact of Signaling on the 2022 to 2023 Orthopaedic Residency Application Cycle: A Survey of Incoming Residents
Authors: Tarapore Rae , Wieland Mark D. , Haislup Brett , Imbergamo Casey , McCormick Brian , Castillo Wilfrido , Boucher Henry 
Published: February 2024

Background:
During the 2022 to 2023 orthopaedic surgery residency application cycle, “signaling” was added, allowing applicants to communicate strong interest to 30 programs of their choosing. This study's purpose was to evaluate signaling's impact on the 2022 to 2023 application cycle.

Methods:
A cross-sectional survey was distributed to applicants who applied to a single residency program. We evaluated how many interviews the average applicant received, what proportion of interviews came from programs they had signaled, and what percentage of applicants matched at a program they had signaled. We stratified data by American Orthopaedic Association status, United States Medical Licensing Examination (USMLE) Step 1 and Step 2 scores, research items, sex, and race.

Results:
This survey was distributed to 611 applicants, with 124 (20.3%) responding to the survey. Ninety-five respondents (76.6%) matched. The percentage of applicant interviews that came from signaled programs was 78.7%. Ninety-one percent of matched applicants matched at a program they signaled. Sixty-three percent of matched applicants performed an away rotation at their matched programs. Forty-five percent of applicants felt that signaling incentivized reducing the programs they applied to, and applicants gave signaling a high favorability rating of 4/5. Applicants with Alpha Omega Alpha status received more interviews per application (0.18 ± 0.11 vs. 0.10 ± 0.10, p < 0.001) and more interviews from programs they did not signal (74% of interviews from signaled programs vs. 90% of interviews from signaled programs, p < 0.001). Higher Step 1 and Step 2 scores were associated with more interviews per application (Step 1: 0.16 ± 0.12 vs. 0.12 ± 0.08, p = 0.032) (Step 2: 0.16 ± 0.11 vs. 0.12 ± 0.09, p = 0.032).

Conclusion:
Orthopaedic residency applicants received most of their interviews from programs that they signaled, with an overwhelming majority matching at signaled program. Alpha Omega Alpha status and high USMLE scores were associated with more interviews granted per application, regardless of signaling status. Signaling seems to be a favorable option for orthopaedic applicants. Data from future application cycles will help further evaluate signaling's impact on the orthopaedic match.
CryoTRANS: Quality Preserved Trajectory for Boosting Resolutions of Rare Conformations in cryo-EM
Authors: Bao Chenglong , Fan Xiao , Zhang Qi , Hu Mingxu , Zhang Hui , Zhu Jianying , Shi Zuoqiang 
Published: February 2024

Abstract

Cryo-electron microscopy (cryo-EM) single-particle analysis (SPA) has revolutionized structural biology, enabling the efficient determination of structures at atomic or near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of the vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. To address this limitation, we introduce CryoTRANS, a method that enhances the resolution of rare conformations. CryoTRANS constructs a quality-preserved trajectory between density maps of varying resolutions, utilizing an ordinary differential equation parameterized by a deep neural network. This ensures the retention of detailed structures from high-resolution density maps. Leveraging one high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations, demonstrating its potential through real-world cryo-EM cases and providing valuable insights into dynamic biological processes.
Abundance-Biased Codon Diversification prevents recombination
in AAV production and ensures robust in vivo expression of functional FRET sensors
Authors: Dernic Jan , Eleftheriou Afroditi , Rauch Melanie , Imseng Pascal , Zanker Henri , Looser Zoe , Meister Rachel , Moros Felipe Velasquez , Paterna Jean-Charles , Arand Michael , Saab Aiman , Weber Bruno , Ravotto Luca 
Published: February 2024

Abstract
The delivery of genetically encoded fluorescent sensors via adeno-associated viral vectors (AAVs) enables the quantification of biological analytes with high spatiotemporal resolution in living animals. In this study, we expose an unreported problem of the approach, in which the presence of repeated subsequences in the sensor’s DNA sequence triggers recombination during AAV production. In the case of Förster Resonance Energy Transfer (FRET) sensors, recombination leads to a mixture of fluorescent products, severely compromising in vivo functionality. To counter this phenomenon, we introduced Abundance-Biased Codon Diversification (ABCD), a computational method that prevents recombination without sacrificing codon optimization for a target organism. We demonstrate that ABCD greatly facilitates in vivo studies by restoring the functionality of FRET sensors and advanced inducible expression systems delivered via AAV vectors. We thereby offer a robust solution to a previously overlooked challenge for quantitative imaging and genetic manipulation in living animals using AAV-mediated strategies.
Watershed Hydrological Response in Developing Climate Change Resilience and Adaptation Strategies, case of Gilgal Gibe Watershed, Ethiopia
Authors: Namara Wana Geyisa , Rabba Zeinu Ahimed , Fanta Sewmehon Sisay , Hode Efrem Wakjira 
Published: February 2024

Abstract

Climate change is one of the most challenging and inevitable global environmental problems affecting mankind and its environment regardless of urban and rural areas. Its effect on watershed hydrology is challenging the sustainable water resources management and its availability across the globe. In order to develop a sustainable climate change adaptation strategy, understanding watershed hydrological response to the ever increasing climate change is highly important. Hence, the main objective of this study was investigating role of watershed hydrological response in developing climate resilience and adaptation strategy as a case study in Gilgal Gibe watershed, Omo Gibe river basin, Ethiopia. To achieve the main objective of the study, three regional climate models (RCM) derived from one global climate model (GCM) under two greenhouse gas emission scenarios (RCP4.5 & RCP8.5) were collected from CORDEX Africa. These data were analyzed against the 1986–2016 baseline data and projected for near future term (2020–2050) and for near future term (2051–2080). The climate dataset trend analysis over the specified period was conducted using Mann-Kendall test and the hydrological modeling was performed using the calibrated and validated HEC-HM model. From the analysis it was found that hydro-climate variability over the proposed time horizon was clearly observed from all RCM under both greenhouse gas emission scenarios. The stream flow revealed an oscillating trend over the course of the operation years under RCP4.5 and RCP8. Hence, this information is important for water resources manager, decision makers and policy makers to develop sustainable climate change resilience and adaptation.
Increased RNA transcription of energy source transporters in circulating white blood cells of aged individual with physical frailty
Authors: Okinaka Yuka , Suda Yoshihito , Matsumoto Tomoyuki , Kuroda Ryosuke , Shinagawa Yoshiyuki , Gul Sheraz , Claussen Carsten , Matsui Ikuko , Matsui Yutaka , Taguchi Akihiko 
Published: February 2024

Abstract

Background
Physical frailty is an age-related clinical condition that is accompanied by deterioration in physiological capacity. In aged mice, we had shown that changes in RNA expression of metabolism-related genes in circulating white blood cells significantly altered with muscle weakness.
Methods
In this explorative analysis, 20 elderly volunteers were enrolled and link between RNA expression profiles in circulating white blood cells and physical frailty was investigated.
Results
There were significant differences in RNA expression of metabolism-related genes, such as glucose transporter 1 (Glut1), Glut3, AMP-activated protein kinase A (AMPKa) and prolyl hydroxylase 3 (PHD3) between elderly individuals with and without swallowing dysfunction and masticatory disturbance. Furthermore, the level of metabolism-related RNA expression of circulating white blood cells was significantly different between the elderly with and without exercise habit. Subsequent mechanism of action studies in mice have revealed a direct link between circulating cells and endothelium/satellite cells in muscle tissue.
Conclusions
Our results indicate the level of metabolism-related RNA expression in circulating white blood cells can serve as a marker of physical frailty in the elderly and provide evidence of a significant role of direct cellular interaction between circulating white blood cells and cells in muscle tissue.
Trial registration:
jRCT1050210166、Feb. 02, 2022
Analyzing the Performance of Machine Learning Algorithms for Predicting Water Quality Index
Authors: Jemila V. Queen , Dhanalakshmi M. , Amutha M. 
Published: February 2024

Abstract
The aim of our research is to calculate the Water Quality Index of bore water in our surrounding educational institutions using three learning algorithms. Our research work differentiates from other work by choosing Decision Tree, K-Nearest Neighbor, and Naive Bayes and analyzing their performance with accuracy. We collected water samples from various resources and calculated the six important factors: salinity, total suspended solids (TDS), dissolved oxygen (DO), acidity and alkalinity (pH), and biochemical oxygen demand (BOD). Using efficient chemical methods, the quality parameters of water were examined. We created our dataset by utilizing these metrics, and the dataset is given as our chosen algorithm’s training and testing data. We implemented these machine learning algorithms using Google Colab. Finally, we got the WQI value with three different accuracies.
Convergent, discriminant, and known groups validity of the Behavioral Assessment Screening Tool (BAST) in chronic traumatic brain injury
Authors: Juengst Shannon B. , Wright Brittany , Vos Leia , Rodriguez Gabriel , Conley Michael , Terhorst Lauren 
Published: February 2024

Abstract

The Behavioral Assessment Screening Tool (BAST) measures self-reported neurobehavioral symptoms commonly experienced by adults with traumatic brain injury (TBI). To assess the convergent, discriminant, and known-groups validity of the BAST among community-dwelling adults with chronic traumatic brain injury (TBI), we conducted correlation analyses and tests of group differences with previously validated symptom measures in two samples (n = 111, n = 134). Measures used for comparison were: Patient Health Questionnaire (depression), Generalized Anxiety Disorder-7 (anxiety), Positive and Negative Affect Schedule, Frontal Systems Behavior Scale (Executive Dysfunction, Apathy, Disinhibition), Modified Fatigue Impact Scale, PROMIS Fatigue, Aggression Questionnaire (anger, hostility, physical and verbal aggression), and Alcohol Use Disorders Test (alcohol misuse). BAST subscales had stronger correlations with measures of similar (|r|=.602-.828, p < .001) and related (|r|>.30, p < .001) constructs and weaker correlations (|r|<.300) with measures of dissimilar/unrelated constructs, supporting hypotheses of convergent and discriminant validity, respectively. Statistically significant group differences (p’s < .001) in BAST subscales were found, with large effect sizes (Cohen’s d = 1.2–1.9), for known-groups with moderate-severe depression, moderate-severe anxiety, clinically significant fatigue, problematic disinhibited and frontal-executive behaviors, and alcohol use. Conclusions: Results support the convergent and discriminant validity of the BAST subscales. The BAST was specifically developed as a self-reported measure for remote symptom reporting, supporting its incorporation into mobile health platforms to improve chronic symptom monitoring in community-dwelling adults with TBI. With further validation research, the BAST could be used for early identification of persons with TBI who could benefit from intervention.
Is increased life stress associated with similar changes in Big-Five Personality across Cognitive Impairment or Dementia (CI/D) and Non-CI/D cases?
Authors: Oi Katsuya 
Published: February 2024

Abstract

Objective: This study investigates how life stress correlates with changes in Big-Five personality factors among individuals with and without cognitive impairment or dementia (CI/D).
Methods: Utilizing data from 12,445 participants aged 50 or above in the Health and Retirement Study (2006-2020), we examined personality changes over an 8-year period. Participants were categorized into CI/D and Non-CI/D groups based on a cut-off score in the Telephone Interview for Cognitive Status-modified (TICS-m). Our analysis regresses estimated personality changes on baselines and variations of a Life Stress index during the same timeframe.
Results: Increased life stress is associated with heightened neuroticism and reduced conscientiousness, extraversion, and openness across both CI/D and Non-CI/D cases. These correlations persist irrespective of TICS-m score variations within each group.
Discussion: life stress as a significant factor in personality changes, cautioning against diagnostic interpretations of cognitive impairment that rely solely on personality assessments.
Non-parametric quantile regression-based modelling of additive effects to solar irradiation in Southern Africa
Authors: Masache Amon , Maposa Daniel , Mdlon Precious , Sigauke Caston 
Published: February 2024

Abstract

Modelling of solar irradiation is paramount to renewable energy management. This warrants the inclusion of additive effects to solar irradiation. To help develop the frameworks, this current study modelled solar irradiation using non-parametric quantile regression (QR). The approach applies quantile splines when finding the best relationships between covariates and the response variable. As a result, the method was very suitable because relationship structures between covariates and solar irradiation are unknown. However, some additive effects are perceived as linear. Thus, the study included the partially linear additive quantile regression model (PLAQR) in our quest to find how best the additive effects can be modelled. The PLAQR model compared very well on reliability analysis, but it was outperformed by the new quantile generalised additive model (QGAM) we proposed, on all other metrics. Modelling of solar irradiation using QGAM is new to renewable energy studies. The Winkler score is another metric where QGAM was inferior, however, an additive quantile regression model was the best. Even though the models had also approximately the same continuous rank probability score in all cases, the QGAM was the best in most metric evaluations. The three models performed differently in different locations, but the location was not a significant factor in their performances. In contrast, forecasting horizon and sample size influenced model performance differently in the three additive models. The performance variations also depended on the metric being evaluated. Therefore, the study has established the best forecasting horizons and sample sizes for the different metrics. It was finally concluded that a 20% forecasting horizon and a minimum sample size of 10000 data points are ideal when modelling additive effects of solar irradiation using non-parametric QR.