bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the diabetes self-care behaviour in rural areas: Perspective of patients with type 2 diabetes mellitus and healthcare professionals
Authors: Gupta Saurabh Kumar , Lakshmi P.V.M. , Chakrapani Venkatesan , Rastogi Ashu , Kaur Manmeet 
Published: February 2024

Background
Diabetes self-care behaviour plays a crucial role in managing the diabetes effectively and preventing complications. Patients with type 2 diabetes mellitus (T2DM) and health care professionals (HCPs) of rural areas often face unique challenges when it comes to diabetes self-care practices (SCPs). Therefore, this study aim to explore the perspectives of patients with T2DM and HCPs on diabetes SCPs.

Methods
Eight focus group discussions (FGDs) among individuals with T2DM and In-depth interviews (IDIs) with 15 HCPs were conducted in rural areas of Punjab, North India. Capability, Opportunity, Motivation, and Behaviour model (COM-B) was employed for thematic framework analyses.

Results
The study participants perceived that a limited understanding of diabetes mellitus (DM), beliefs in alternative therapies, drug side effects, attitudes towards DM (psychological capability), comorbidities (physical capability), family support (social opportunity), financial and time constraints, and weather conditions (physical opportunity) contributed to lack of DM SCPs. Physicians’ guidance and support were motivating them to adhere to SCPs, especially when aligned with their sense of self-efficacy (reflective motivation). HCPs constraints in providing patient-centred care are due to training limitations (psychological capability) and a lack of essential resources (physical opportunities). Participants expressed need for comprehensive diabetes care (automatic motivation) through structured diabetes education intervention to improve diabetes SCPs.

Conclusions
The study findings indicate that various factors influence diabetes SCPs from the perspectives of both patients with T2DM and HCPs and emphasizes the need for a multi-faceted approach to improve diabetes SCPs in rural areas. Implementing a structured diabetes self-care intervention strategy in rural areas may help for preventing and mitigating the impact of diabetes-related complications in rural areas.
Japan-epiretinal membrane (J-ERM) registry: A prospective cohort study protocol investigating the surgical outcome of epiretinal membrane
Authors: Kanzaki Yuki , Matoba Ryo , Ishihara Kenji , Morita Tetsuro , Muraoka Yuki , Kimura Shuhei , Koto Takashi , Kawasaki Ryo , Baba Takayuki , Okamoto Fumiki , Inoue Makoto , Sakamoto Taiji , Tsujikawa Akitaka , Morizane Yuki 
Published: February 2024

Background
Epiretinal membrane (ERM) causes visual impairment such as reduction in visual acuity and metamorphopsia due to retinal traction. With the improvement of optical coherence tomography (OCT) and microincision vitrectomy surgery (MIVS), the surgery of ERM has significantly advanced. However, there have been no large-scale studies on the following: (1) how to evaluate visual impairment in ERM, (2) the relationship between OCT findings and visual function, (3) when is the optimal timing of surgery, and (4) the relationship between the surgical instruments as well as techniques and prognosis. The purpose of this study was to obtain evidence regarding these ERM surgeries.

Methods and design
This is a prospective, multicenter cohort study of ERM surgery in Japan from March 1, 2023, to March 31, 2027 (UMIN000048472, R-3468-2). Patients who underwent ERM surgery during the study period and agreed to participate in this study will be included. The goal is to have a total of 5,000 eyes surgically treated for ERM. The following data will be collected: age, gender, medical history, subjective symptoms, visual function before and 6 and 12 months after surgery, clinical findings, OCT data, surgical technique, instruments used in surgery, and complications.

Discussion
The results of this study will support the surgical decisions and procedures in ERM practices.
The presence of enteropathy in HIV infected children on antiretroviral therapy in Malawi
Authors: Blaauw Julia , Chikwana Jessica , Chaima David , Khoswe Stanley , Samikwa Lyson , de Vries Isabelle , Voskuijl Wieger 
Published: February 2024

Background
Undernutrition and malnutrition in children in low- and middle-income countries contribute to high mortality rates. Stunting, a prevalent form of malnutrition, is associated with educational and productivity losses. Environmental enteric dysfunction (EED) and human immunodeficiency virus (HIV) infection worsen these conditions. This study seeks to investigate the presence of enteropathy using EED fecal biomarkers in HIV-infected children who are stable on antiretroviral therapy (ART) across various nutritional statuses. By understanding the interplay between EED, HIV, and nutritional status, this study aims to provide insights that can inform targeted interventions to optimize nutritional outcomes in HIV infected children.

Methods/Principal findings
This study evaluated the levels of alpha-1-antitrypsin, calprotectin and myeloperoxidase in frozen fecal samples from 61 HIV infected (mean age 9.16 ±3.08 years) and 31 HIV uninfected (6.65 ±3.41 years) children in Malawi. Anthropometric measurements and clinical data were collected. The height-for-age z-score (-1.66 vs -1.27, p = 0.040) and BMI-for-age z-score (-0.36 vs 0.01, p = 0.037) were lower in HIV infected children. Enzyme-linked immunosorbent assays were used to measure biomarker concentrations. Statistical tests were applied to compare biomarker levels based on HIV status and anthropometric parameters. Myeloperoxidase, alpha-1-antitrypsin, and calprotectin concentrations did not differ between HIV infected and HIV uninfected children of different age groups. In HIV infected children from 5–15 years, there is no difference in biomarker concentration between the stunted and non-stunted groups.

Conclusion/Significance
Our study found a higher prevalence of stunting in HIV infected children compared to uninfected children, but no significant differences in biomarker concentrations. This suggests no causal relationship between enteropathy and stunting in HIV infected children. These results contribute to the understanding of growth impairment in HIV infected children and emphasize the need for further research, particularly a longitudinal, biopsy-controlled study.
Feasibility of oropharyngeal and respiratory muscle training in individuals with OSA and spinal cord injury or disease: A pilot study
Authors: Sankari Abdulghani , Najjar Abed Alkader , Maresh Scott A. , Prowting Joel L. , Fung Constance H. , Knack Arthur , Yarandi Hossein , Badr M. Safwan 
Published: February 2024

AbstractObjectivesTo examine the feasibility of individuals with spinal cord injury or disease (SCI/D) to perform combined oropharyngeal and respiratory muscle training (RMT) and determine its impact on their respiratory function.MethodsA prospective study at a single Veterans Affairs (VA) Medical Center. Inclusion criteria included: 1) Veterans with chronic SCI/D (>6 months postinjury and American Spinal Injury Association (ASIA) classification A–D) and 2) evidence of OSA by apnea‐hypopnea index (AHI ≥5 events/h). Eligible participants were randomly assigned to either an experimental (exercise) group that involved performing daily inspiratory, expiratory (using POWERbreathe and Expiratory Muscle Strength Trainer 150 devices, respectively), and tongue strengthening exercises or a control (sham) group that involved using a sham device, for a 3‐month period. Spirometry, maximal expiratory pressure (MEP), maximal inspiratory pressure (MIP), polysomnography, and sleep questionnaires were assessed at baseline and at 3 months.ResultsTwenty‐four individuals were randomized (12 participants in each arm). A total of eight (67%) participants completed the exercise arm, and ten (83%) participants completed the sham arm. MIP was significantly increased (p < 0.05) in the exercise group compared with the baseline.ConclusionsCombined oropharyngeal and RMT are feasible for individuals with SCI/D. Future studies are needed to determine the clinical efficacy of these respiratory muscle exercises.
Implementierung von Alma & Primo VE an der Bayerischen Staatsbibliothek
Authors: Gillitzer Berthold , Kratzer Mathias , Moravetz-Kuhlmann Monika , Schäffler Hildegard , Schwarz Stephan 
Published: February 2024

Zusammenfassung
Dieser Bericht über die Implementierung der cloudbasierten Bibliotheksmanagement- und Discovery-Lösung Alma & Primo VE von Ex Libris an der Bayerischen Staatsbibliothek beleuchtet die für dieses Großprojekt spezifischen bis einzigartigen Aspekte. Sie ergeben sich aus der Größe und zum Teil besonderen Art des Bestands, der arbeitsteiligen Organisation von Geschäftsgängen, den überregionalen Aufgaben der Bibliothek und ihrer gemeinsamen Nutzerschaft mit der Universitätsbibliothek der Ludwig-Maximilians-Universität München.
Rechtsfragen zur generativen KI
Authors: Rack Fabian 
Published: February 2024

Zusammenfassung
Der Beitrag gibt einen Einstieg in ausgewählte Rechtsfragen der generativen KI. Der Blick richtet sich auf Betreiber, die fremde Materialien einsammeln, um ihre KI-Modelle zu trainieren. Die hierfür geltende gesetzliche Grundlage und ihre Grenzen werden dargestellt. Außerdem wird beleuchtet, was aus Nutzersicht im Hinblick auf fremde Urheberrechte zu beachten ist und wann eigene Urheberrechte beim Einsatz generativer KI entstehen. Auch datenschutzrechtliche Fragestellungen werden thematisiert.
20 Jahre Koordinationsstelle für die dauerhafte Archivierung elektronischer Unterlagen (KOST): Rückblick und Ausblick
Authors: Büchler Georg 
Published: February 2024

Zusammenfassung
Die Koordinationsstelle für die dauerhafte Archivierung elektronischer Unterlagen (KOST) unterstützt seit 20 Jahren öffentliche Archive in der Schweiz in allen Aspekten der digitalen Archivierung. Ihre Aktivitäten reichen von der Standardisierung über Forschung und Projektbegleitung bis zur individuellen Unterstützung ihrer Trägerarchive. Die neue Strategie der KOST fokussiert auf eine weitere Stärkung des Gemeinschaftsgedankens durch die Schaffung gemeinsamer Grundlagen, Werkzeuge und Weiterbildungsangebote.
Spatial and time-resolved properties of emission enhancement in polar/semi-polar InGaN/GaN by surface plasmon resonance
Authors: Ikeda Kento , Kawai Kanata , Kametani Jun , Matsuyama Tetsuya , Wada Kenji , Okada Narihito , Tadatomo Kazuyuki , Okamoto Koichi 
Published: February 2024

Abstract
Light-emitting diodes (LEDs) are widely used as next-generation light sources because of their various advantages. However, their luminous efficiency is remarkably low at the green-emission wavelength. The luminous efficiencies of InGaN/GaN quantum wells (QWs) significantly decrease with increasing indium content in the green wavelength region, mainly owing to the quantum-confined Stark effect (QCSE). This green gap problem can be solved using QWs grown on semi-polar GaN substrates, such as the {11–22} planes, to reduce the QCSE. We propose that the use of surface plasmons (SPs) is a promising way to improve the light emission efficiency of light-emitting materials such as InGaN/GaN QWs. SP resonance increases the spontaneous emission rates of the excited states, causes a relative reduction in non-radiative relaxation, and ultimately increases the internal quantum efficiencies. In this study, the light emissions of InGaN/GaN QWs grown on polar and semi-polar GaN were investigated using micro-photoluminescence (PL). We successfully enhanced the light emission of semi-polar GaN via SP resonance. The PL peak intensities and wavelengths were mapped and compared to determine the underlying mechanisms. We also measured the emission lifetimes by time-resolved PL and interpreted the detailed mechanism of SP-enhanced emissions. It was found that SP resonances can control not only the emission efficiency but also the exciton dynamics, such as exciton localization effects, QCSE screening, and defect level saturation. We conclude that the green gap problem can be solved by SP-enhanced light emission in semipolar InGaN/GaN.
Dual high-Q Fano resonances metasurfaces excited by asymmetric dielectric rods for refractive index sensing
Authors: Wang Tianyu , Liu Siqi , Zhang Jiahang , Xu Liang , Yang Mingyu , Ma Ding , Jiang Sijia , Jiao Qingbin , Tan Xin 
Published: February 2024

Abstract
The metasurface refractive index sensor has a high degree of tunability and flexibility, providing excellent performance for high precision refractive index sensing applications. The metasurface absorber with metallic structure has been hindered in further sensor applications due to the inherent Ohmic loss of the metallic material. In this study, a dual nanorod metasurface structure based on semiconductor Si was designed, introducing a symmetry-breaking structure to excite dual ultra-narrow q-BIC resonance peaks with Fano line shapes. Both peaks are located in the near-infrared region, and multipole analysis shows that this strong field enhancement effect is induced by a magnetic dipole. Experimental results demonstrate the potential of this sensor to provide dual-channel detection while achieving high sensitivity and high Q-factor. We believe that this device exhibits outstanding performance and high practicality, providing a reference for the development and application of biological and environmental sensors.
Multi-wavelength structured light based on metasurfaces for 3D imaging
Authors: Lyu Baiying , Chen Chen , Wang Jian , Li Chang , Zhang Wei , Feng Yuxiang , Dong Fei , Zhang BaoShun , Zeng Zhongming , Wang Yiqun , Wu Dongmin 
Published: February 2024

Abstract
Structured light projection provides a promising approach to achieving fast and non-contact three-dimensional (3D) imaging. The resolution is a crucial index that represents security and accuracy in applications such as face recognition and robot vision. It depends on the density of dots in the projection. However, further improving the density of dots in the current system must be at the cost of speed or volume. Here, an all-dielectric ultra-thin metasurface is designed and fabricated to project a multi-wavelength dot array. The density of dots is improved because projected dots with different wavelengths fill the gaps with each other. The experimental results demonstrate that the multi-wavelength projection improves the resolution of 3D imaging. Furthermore, the multi-wavelength system is beneficial to measuring a surface with varying colors. The approach has the potential to achieve a new generation of high-resolution systems for tiny fluctuations and colorful 3D imaging in dark environments.
Experimental investigation of structural, morphological, and optical characteristics of SrTiO3 nanoparticles using a shock tube for photocatalytic applications
Authors: Sakthivel Surendhar , Paramasivam Sivaprakash , Velusamy Periyasamy , Jerries Infanta Joseph Anthony Doss , Ragavendran Venkatesan , Mayandi Jeyanthinath , Arumugam Sonachalam , Kim Ikhyun 
Published: February 2024

Abstract
We investigated the role of dynamic shock waves in perovskite SrTiO3 (STO) material. XRD, FE-SEM, EDAX, FTIR, UV-DRS, XPS, and Raman spectroscopy were all used to examine the title material. When perovskite sample was loaded with shocks, its diffraction pattern did not show any crystal structure changes. The FE-SEM results suggest that the grain size increased linearly with the number of shocks. We used energy-dispersive X-ray spectroscopy to perform elemental analysis; results confirmed that SrTiO3 NPs were indeed present. Although the impulse of the shock wave changed the optical characteristics, it did not affect the molecular structure. To find the optical band gap energies of untreated and shocked NPs, Tauc plot relationships were used. The band-gap energies got smaller as the shock pulse became more substantial. The impact of shock waves caused oxygen vacancies and surface defects, lowering band gap energy. The test for photocatalytic testing showed that SrTiO3 NPs that are loaded with shock waves worked much better when they were exposed to visible light. The characteristics, including stress, strain, and bond length, were found to significantly influence photocatalytic applications. In addition, attempts were made to provide a viewpoint for future study. Overall, the objective of this research was to provide valuable insights for experts engaged in the field of SrTiO3.
Analysis of Time-Based Public Transport Demand Prediction Using OPTUNA Framework
Authors: R. Thiagarajan Et al. 
Published: February 2024

Buses are the most popular and easy mode of transportation in all over the world. The state government operates bus service in all routes with low-cost fare. Traffic congestion has risen at an alarming rate due to an increase in the number of automobiles. Travel time have increased as a result, while accessibility and mobility have worsened. The primary challenge encountered by passengers is the absence of information regarding bus numbers that are accessible on a certain route and the approximate time of bus departure. The delay in bus operations, could have several reasons which are inclement weather, traffic jam, and breakdowns. Neither the arrival time of the bus nor the delay are known to the people waiting at the bus stop. In order to address this problem, encouraging the usage of public transportation seems to be a feasible way. Over the past ten years, prediction of bus arrival time has become a fascinating subject around the world. In the transportation sector, Machine Learning (ML) technologies have already shown great promise and have additionally shown to yield a larger return on investment than traditional methods. In this research work , authors propose and develop predictive models to predict public transport demand for passenger transit based on bus arrival time. The dataset shows the proportion of buses operated by the Rochester-Genesee Regional Transportation Authority (RGRTA) that arrive on time. Initially, lazy predict classifier is used for solving regression-based dataset for predicting the bus demand in On-time based passenger transit. Based on the examination of lazy classifiers, the Decision Tree Regressor (DTR) has been identified as the best model. It is assessed using the most advanced hyperparameter optimization framework (OPTUNA). The proposed OPTUNA based DTR which is utilized to identify On-time performance of bus services-based passenger transit. Using OPTUNA for search is an efficient and beneficial approach considering the search speed and the improvement in model accuracy. According to the experimental data, the proposed approach performs better where the R-squared score is 0.9878 with best hyperparameter to be optimized.
Survey on Cloud Computing Integrated with Artificial Intelligence
Authors: Sadargari Viharika Et al. 
Published: February 2024

The combination of cloud computing with Artificial Intelligence (AI) has become a viable approach in recent years to handle the increasing processing needs of AI applications. This article offers a thorough analysis of distributed and scalable artificial intelligence frameworks that use cloud computing to improve the effectiveness and performance of Deep Learning (DL). First, we provide a summary of common cloud services and AI frameworks, emphasizing the advantages and disadvantages of each. The important topics of data management and storage in cloud-based AI systems are then covered in detail, including feature engineering, data pretreatment, privacy, and security. Next, we investigate the distributed and parallel training methods for AI models, with particular emphasis on cloud-based training topologies, communication mechanisms, and model splitting. On the next chapters, we examine auto-scaling, load balancing, resource allocation, and performance benchmarking as optimization methodologies for AI workloads on the cloud. We also cover serverless deployment alternatives, containerization, best practices for monitoring, and the deployment and servicing of AI models on the cloud. We give a comprehensive study of costs, optimization methodologies, and case studies exhibiting successful installations to guarantee the cost-effectiveness of cloud-based AI systems. In conclusion, we provide an overview of the study's main conclusions, go through the difficulties and restrictions associated with cloud-based artificial intelligence, and point out new directions for future research in this area. For academics and practitioners trying to use cloud computing to create scalable, effective, and affordable artificial intelligence systems, this article will be a great resource.
Challenges in Policy Developments for Automated Vehicles
Authors: Neeta Maitre Neeta Maitre 
Published: February 2024

Innovation is the driving factor in autonomous vehicles (AV). AVs are creating a buzz all around due to the reaction perception time required while driving the vehicles. AV technology will lead to the increased highway capacity and also the speed of the vehicles. The caution to utilize the benefits of the AVs lead to the proper planning and implementation. This calls for systematic policy developments. The policies governing various facets of AVs such as mobility, connectivity, social and environmental impact and adherence to the sustainability principles. This paper aims to discuss the guiding strategies governing AVs and the principles associated with them.
The policies to be followed for AVs face various challenges and require effective planning. The challenges in context with the law, safety , security and economies will lead to various policy recommendations. The paper discusses the policy considerations in the state enabled legislation, cross sector partnerships and fiscal implications of AVs at different levels.