bluuebunny/crossref_metadata_2025_split huggingface dataset:
Вимушені поперечні коливання магнітом'якої мікрострічки: Побудова частинних розв'язків
Authors: Сіжук Андрій , Жао Жендзіє , Чен Ксіаохонг , Сан Жуо , Донг Гуангдзіонг , Прокопенко Олександр , Третяк Аліна 
Published: May 2024

У роботі зроблена спроба опису низькочастотних коливань магнітом’якої прецизійної мікрострічки складу Fe73.5Cu1Nb3Si13.5B9 із закріпленим одним кінцем. У заданій області частот 15–80 Гц, для змінного магнітного поля знайдено резонансні частоти індукованих механічних коливань мікрострічок. Отримано коефіцієнт затухання, виміряний для механічних автоколивань відпаленого зразка. Коефіцієнт загасання, виміряний для механічних автоколивань відпаленого зразка за допомогою лазера, виявився значно меншим за відповідну напівширину амплітудно-частотної характеристики описаних вище вимушених коливань. Запропонована теоретична модель вимушених та вільних коливань мікрострічки скінченної товщини та ширини. Однією із властивостей побудованих частинних розв’язків є відносно широка резонансна крива, що підтверджується експериментально. Однак приведені приклади частинних розв’язків задовольняють здогад про форму лівого крила АЧХ при заданій частоті збудження та параметрах системи. Залежність механічного параметра, що характеризує момент сил при згинальній деформації, від напруженості прикладеного магнітного поля визначає механічні властивості м'яких магнітних кристаллінових матеріалів.
Оптимізація характеристик випромінювання лінійної фокусуючої решітки напівпрозорих дзеркал
Authors: Андрійчук Михайло Іванович , Ткачук Віктор 
Published: May 2024

Стаття присвячена оптимізації характеристик випромінювання лінійної фокусуючої решітки, яка складається із сукупності напівпрозорих похилих елементів (дзеркал), джерела збудження і кінцевого непрозорого дзеркала. Геометрія решітки задовольняє квазіоптичні умови, а нахил дзеркал задається таким чином, що решітка дозволяє фокусувати розсіяне поле в зоні Френзеля і в дальній зоні. Формування діаграми спрямованості (ДС), близької до заданої, чи забезпечення максимуму випромінювання в задану область кутових координат відбувається за рахунок вибору коефіцієнтів відбивання та проходження напівпрозорих елементів решітки. Для забезпечення цих вимог формулюється варіаційна постановка оптимізаційної задачі. Максимізація відповідних функціоналів відбувається чисельно методами послідовних наближень. Числові експерименти демонструють високу точність виконання вимог до характеристик випромінювання, це підтверджується також експериментальними даними.
identité juridique du vin nature(l)
Authors: Raffray Ronan 
Published: May 2024

Cet article porte sur l’identité juridique du vin nature(l). Il examine à son sujet le passage de la réalité matérielle à l’ordre juridique, des pratiques entourant la production de vin naturel à la reconnaissance normative singulière d’une méthode de production, à moins qu’il ne s’agisse de la singularité d’un produit. Cette publication reprend des éléments d’une communication présentée à la cité du vin lors d’un colloque intitulé « Des pratiques au droit, l’identité du vin nature(l) », dont les actes ont été publiés (Des pratiques au droit, l’identité des vins nature(l)s, dir. Chr. Pineau et R. Raffray, LEH, 2022).
Facilitating patient-oncologist communication in advanced treatment-resistant cancer: development and feasibility testing of a question prompt list.
Authors: Rault Aude , Dolbeault Sylvie , Terrasson Johanna , Bouleuc Carole , Cottu Paul , Piperno-Neumann Sophie , Rodrigues Manuel , Vaflard Pauline , Brédart Anne 
Published: May 2024

Abstract

Background
Patients' expectations regarding medical information in advanced stages of cancer are still poorly understood in France. Tailoring information to advanced cancer patients is a subtle task. We have developed a question prompt list (QPL), serving as a patient-oncologist communication aid.
Methods
A four-step sequential mixed-method was followed, involving patients with luminal B/triple-negative metastatic breast cancer or metastatic uveal melanoma (N = 110), patients’ partners, oncologists and researchers (N = 18). In-depth interviews and questionnaires focused on information needed at disclosure of metastasis or resistance to treatment (step 1), formulation of questions and procedures for use in oncology visits (steps 2 and 3), and acceptability of final tool (stage 4).
Results
The QPL initial version consists of 17 questions covering 5 themes (disease, current treatment, other options, living with cancer, prognosis). In step 2, 13 questions were added, 2 merged and 5 deleted; a short form (4 questions) and recommendations for clinical use were proposed. At step 3, 2 questions were merged and 6 deleted. Four oncologists (27% of the target population) took part in step 4, and the QPL was discussed with 20 patients, revealing a positive appraisal.
Conclusion
We provide a rigorously developed, relevant, concise and acceptable question prompt list for clinical application in the advanced cancer care setting in France. Further research needs to assess whether this tool actually facilitates the oncologist-patient communication and improves satisfaction with care and health outcomes.
Trial registration:
The study is listed in ClinicalTrials.gov (NCT04118062) and registered under identification n° IRRID ‘International Registered Report Identifier’: DERR1-10.2196/26414.
Climate Change Transition and Physical Risks of Industrial Companies in Australia, Canada, the European Union and the United States
Authors: Erhart Szilard , Szabo Sandor , Erhart Kornel 
Published: May 2024

Abstract

We present a methodology to develop the integrated climate change transition and physical risk assessment of industrial plants in Europe, Northern America and Australia. There is an increasingly important need for effective large scale climate change risk assessment solutions with more governments aligning their company reporting regulations with the Task Force on Climate-related Financial Disclosures recommendations. In this paper we measure key aspects of climate change risks of industrial firms on the globe and vice-versa. The study provides valuable insights into climate risk exposure for companies, investors, and consumers, offering a pioneering approach by integrating data from major international registers. We analyse data from 70,000 companies and their 170,000 plants, which report to fragmented Pollutant Release and Transfer Registers and Greenhouse Gas Reporting Programs. For our assessment, transition risks are measured in terms of reported greenhouse gas emissions, while physical risks calculated for all company plant locations in terms of historical cooling energy needs, flood exposure and photovoltaic power potential. We show that climate change transition and physical risks are not correlated, therefore there are no winners and losers of climate change in general. The research contributes to the evolving landscape of climate risk management and highlights the need for standardized methodologies in the face of impending regulatory changes.
MonoViT-3D: Self-Supervised Monocular Depth Estimation from 3D Geometric Constraints using Point Cloud Projection
Authors: Wen Tian , Tang Haonan , Sun Gaofei , Zhang Lifeng 
Published: May 2024

Abstract

Self-supervised monocular depth estimation leverages geometric constraints to create pseudolabels, eliminating the need for ground-truth data during training. In the field of 3D geometric constraints, the optical flow and iterative closest point methods are widely used to extract geometric constraints. However, the application of the existing 3D geometric constraint methods in self-supervised learning tasks increases network complexity by introducing additional submodules and iterative loops. In this paper, we propose a point cloud projection method that replaces the iterative closest point algorithm. Following depth prediction, our method utilizes the difference of 3D gaussian measure to extract 3D point cloud structures and the difference of 2D gaussian measure for the 2D structures derived from synthesized multiview surfaces. By projecting a 3D structure onto a 2D image, the errors between the target point cloud image and the synthesized views are estimated to enhance the training process of self-supervised learning. 3D geometric constraints form a point cloud optimization problem in our approach, requiring deep prediction networks with strong receptive fields for global features. Benefiting from the global receptive field of transformers, we use a vision transformer for self-supervised learning. Furthermore, we propose an encoder block to more effectively learn the patterns of 3D geometric constraints. Experiments show that we achieve strong performance on the KITTI dataset, achieving 0.095, 0.691, 4.243, and 0.171 Abs Rel, Sq Rel, RMSE, and RMSE log values for monocular depth estimation, respectively. Moreover, the model outperforms the comparison models in 3D generation tasks conducted on the Make3D dataset. All code is available at https://github.com/weentiaan/MonoViT-3D.
Qualitative study on health self-management of patients with metabolic syndrome among bereaved population after earthquake
Authors: Ma Lihua , Yang Juandong , Yuan Wei , sun yanyan 
Published: May 2024

Abstract

Objective
The study explore the influencing factors and healthy self-management of MS patients with bereaved relatives after Wenchuan and Yushu Earthquake of their real life; explore difficulties and challenges in the process of self-management; and supply information that could not be sought in quantitative studies.
Methods
Purposive sampling was used to recruit 36 MS patients who are bereavement population in two earthquakes, and those patients met the inclusion criteria for semi-structured focus group interview. The Nvivo11 software was used to collate and analyze the transcribed data.
Results
The main influencing factors of health self-management behavior for MS patients are as follows: the degree of understanding of disease prevention knowledge, emotion management induced by earthquake trauma, the source of disease-related information, access and identification are very limited; ethnic traditional culture, religious beliefs, and production activities and routines before and after the earthquake is an important factor in their healthy self-management behavior.The lack of health beliefs and self-efficacy of MS patients among bereaved families after Wenchuan and Yushu earthquake are key obstacle in their self-management.
Conclusion
The overall level of the knowledge of patients’ MS prevention, self-efficacy and self-management behaviors are still low. Some positive factors that can be changed including MS prevention knowledge, self-efficacy, social support, and family function. Some negative factors which can be improved afterwards, including negative coping style, traumatic life experiences from earthquake and smoking.
Mapping Indoor Radon Concentrations in Chungcheongbuk-do, South Korea: A Geospatial Analysis using Machine Learning Models
Authors: Widya Liadira Kusuma , Rezaie Fateemah , Lee Jungsub , Lee Jongchun , Yoo Juhee , Lee Woojin , Lee Saro 
Published: May 2024

Abstract

Radon is a naturally occurring radioactive gas found in many terrestrial materials. Due to the potential health risks linked to persistent exposure to high radon concentrations, it is essential to investigate indoor radon accumulation. This study generated indoor radon index maps for Chungcheongbuk-do, South Korea, selected factors with frequency ratios (FRs) and validated them using the FR, convolutional neural network, long short-term memory, and group method of data handling machine learning models. The establishment of a geospatial database provided a basis for the integration and analysis of indoor radon concentrations (IRCs), along with relevant geological, soil, topographical, and geochemical data. The study calculated the correlations between IRC and diverse factors statistically. The IRC potential was mapped for Chungcheongbuk-do by applying the above techniques, to assess the potential radon distribution. The robustness of the validated model was assessed using the area under the receiver operating curve.
Digital Speech Hearing Screening Using A Quick Novel Mobile Hearing Impairment Assessment
Authors: Banks Russell , Greene Barry , Morrow Isaiah , Ciesla Marissa , Woolever David , Tobyne Sean , Gomes-Osman Joyce , Jannati Ali , Showalter John , Bates David , Pascual-Leone Alvaro 
Published: May 2024

Abstract

Background
By 2050, 1 in 4 people worldwide will be living with hearing impairment by 2050. We propose a digital Speech Hearing Screener (dSHS) using short nonsense word recognition to measure speech-hearing ability. We compare dSHS outcomes with standardized pure-tone averages (PTA) and speech-recognition thresholds (SRT). 50 participants (aged 55 or older underwent pure-tone and speech-recognition thresholding.
Methods
One-way ANOVA was used to compare differences between hearing impaired and hearing not-impaired groups, by the dSHS, with a clinical threshold of moderately impaired hearing at 35dB and severe hearing impairment at 50dB.
Results
dSHS results significantly correlated with PTAs/SRTs. ANOVA results revealed the dSHS was significantly different (F(1,47) = 38.1, p < 0.001) between hearing impaired and unimpaired groups. Classification analysis using a 35dB threshold, yielded accuracy of 85.7% forPTA-based impairment and 81.6% forSRT-based impairment. At a 50dB threshold, dSHS classification accuracy was 79.6% for PTA-based impairment (NPV-93%) and 83.7% (NPV-100%) for SRT-based impairment.
Conclusions
The dSHS successfully differentiates between hearing impaired and unimpaired individuals in under 3 minutes. This hearing screener offers a time saving, in clinic hearing screening to streamline the triage of those with likely hearing impairment to the appropriate follow up assessment, thereby improving the quality of services. Additionally, this tool can help to rule out hearing impairment as a cause or confounder of cognitive impairment.
CCL5: a novel biomarker in a diagnostic model for bone metastasis in prostate cancer
Authors: Chen Chiwei , Zhan Dandan , Xiang Yuyang , Deng Wei , Huang Renlun , Wang Zhigang , Huang Mei , Hong Min , Wang Yuanzhao , Xiang Songtao 
Published: May 2024

Abstract

Treating metastatic prostate cancer and bone metastasis is challenging, impacting both life quality and survival. CCL5 is known to promote prostate-cancer stem-cell activity, invasion, and metastasis. Here, we evaluated CCL5's role in a diagnostic model of bone metastasis in prostate cancer. Patient data from 2011 and 2022 formed the modelling dataset. Through logistic regression analyses, a classic diagnostic model ("classical model") for bone metastasis in prostate cancer was established. The Surveillance, Epidemiology, and End Results (SEER) database was utilized as the validation dataset. Immunohistochemistry evaluated CCL5 expression in prostate cancer tissues. Incorporating CCL5 as a clinical factor into the dataset yielded a novel diagnostic model. Its performance was assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). We collected clinical data from 160 patients with prostate cancer, establishing a modelling dataset for bone metastasis. Patients (2,215) originating from the SEER database were used to construct the validation dataset. T stage, PSA level, Gleason score, and CCL5 level emerged as significant risk factors for bone metastasis, indicating the classical model’s diagnostic significance. Furthermore, when CCL5 was included in the classical model, the CCL5 model exhibited superior discriminatory ability and clinical applicability. CCL5, as a novel biomarker, plays a significant role in the diagnosis of bone metastasis in prostate cancer.
Building Extraction on SegFormer Model and Post Processing from Remote Sensing Images
Authors: Li Deliang , Wang Haokun , Yan Long 
Published: May 2024

Abstract

Most of the traditional methods are based on remote sensing feature classification technology, which uses different classification methods to extract specific feature types, but the traditional classification process suffers from the problems of high threshold of use, cumbersome data processing process, slow recognition speed, and poor migration. Artificial intelligence, especially machine learning and deep learning, is constantly and deeply affecting our daily life and work, and the impact on intelligent extraction of remote sensing images is also very extensive. Classification and automatic extraction of geographic elements of remote sensing images is a popular research direction in the field of remote sensing. Remote sensing image building extraction has an important application value in the field of geographic information, especially in urban planning, resource management, and ecological protection. Deep learning convolutional neural network is used to recognize buildings in remote sensing images, and the current mainstream SegFormer network structure is selected for intelligent binary classification to extract buildings. The intelligent binary classification workflow ranges from data preparation, model construction, model release to application. Intelligent binary classification can intelligently decipher not only buildings, but also single land classes with obvious feature points such as roads and rivers. The development of deep learning algorithms, to a certain extent, to make up for some of the shortcomings of the traditional remote sensing image analysis methods, post-processing of the inference results, it greatly improves the presentation of the results, as well as the accuracy of the results, to provide a better technical basis for the analysis of remote sensing images.
Two novel DnaJ chaperone proteins CG5001 and P58IPK regulate the pathogenicity of Huntington’s Disease
Authors: Deo Ankita , Ghosh Rishita , Ahire Snehal , Marathe Sayali , BOSE Tania , Majumdar Amitabha 
Published: May 2024

Abstract

Huntington’s disease (HD) is a rare neurodegenerative disease caused due to aggregation of Huntingtin (HTT) protein. This study involves cloning of 40 DnaJ chaperones from Drosophila, and overexpressing them in yeasts and fly models of HD. Accordingly, DnaJ chaperones were catalogued as enhancers or suppressors based on their growth phenotypes and aggregation properties. 2 of the chaperones that came up as targets were CG5001 and P58IPK. Protein aggregation and slow growth phenotype was rescued in yeasts, S2 cells, and Drosophila transgenic lines of HTT103Q with these overexpressed chaperones. Since DnaJ chaperones have protein sequence similarity across species, they can be used as possible tools to combat the effects of neurodegenerative diseases.
Effect of ankle-foot orthosis on paretic gastrocnemius and tibialis anterior muscles contraction of stroke survivors during walking: a pilot study
Authors: Liu Wei , Wu Hui-Dong , Li Yu-Ying , Zhu Ringo Tang-Long , Luo Yu-Yan , Ling Yan To , Wang Li-Ke , Wang Jian-Fa , Zheng Yong-Ping , Ma Christina Zong-Hao 
Published: May 2024

Abstract

Ankle-foot orthosis (AFO) is commonly prescribed for stroke survivors with foot drop to aid in foot clearance while walking and reduce fall risk. However, its impact on the contraction patterns of paretic ankle muscles remains inconclusive. This pilot study investigated the contraction of paretic tibialis anterior (TA) and medial gastrocnemius (MG) muscles in twenty sub-acute stroke patients wearing AFO during walking using a wearable dynamic ultrasound imaging and motion sensors. Results showed an increase in TA muscle thickness throughout a gait cycle (p > 0.05) and a significant increase in TA muscle surface mechanomyography (sMMG) signal during pre- and initial swing phases (p < 0.05) when using AFO. MG muscle thickness generally decreased with AFO (p > 0.05), aligning more closely with healthy adults' trends throughout a gait cycle. MG sEMG signal significantly decreased during the initial and mid-swing phases when wearing AFO (p < 0.05). The TA-MG co-contraction index notably decreased during initial and mid-swing phases with AFO (p < 0.05). These findings suggest that AFO can promptly influence the contraction patterns of paretic ankle muscles during walking in stroke patients, but further research is needed to understand its long-term effects.
Photocatalytic product-selective reduction of CO2, CO and carbonates
Authors: Borbas Eszter , Bhimpuria Rohan , Tomar Monika , Thapper Anders 
Published: May 2024

Abstract

CO2 conversion to value-added chemicals is a crucial technology towards carbon-neutral fuels.1 Photocatalysis using sunlight is an energy-efficient alternative to electrochemical and thermal CO2 reduction.1 Photocatalysts usually yield either CO or HCO2H with varying degrees of selectivity.1 Herein, a lanthanide-based photocatalytic platform producing CO, HCO2H, CH4 or CH3OH is reported. The catalyst consists of a pendant amine for CO2 capture and a light-harvesting sensitiser that generates the reactive divalent lanthanide centre. CO2 reduction to CO or formate was possible with >99% selectivity and with the highest turnover number reported for a photocatalyst by virtue of a distinct mechanistic pathway. Attractive (bi)carbonate CO2 feedstocks were efficiently converted to CO, and CO could be reduced to the secondary products methane and methanol, demonstrating the wide utility of the platform.
Exploring Stress and Recovery among Students: Implications for Well-being and Academic Performance
Authors: Stang Philipp , Weiss Maren , Jaensch Peter , Scholz Stefanie 
Published: May 2024

Abstract

Understanding stress and recovery dynamics among students is essential for promoting their well-being and academic success. This study delves into the complex interplay of stressors and coping mechanisms among university students. Drawing upon health psychology and resilience research, we investigate the experiences of stress and recovery among both full-time and part-time students, considering factors such as gender and age. Our findings reveal significant differences between full-time and part-time students in various aspects of stress, including emotional stress, conflicts, and lack of energy. Full-time students reported higher levels of stress in these dimensions, which could indicate possible effects on their academic performance and general well-being. Moreover, gender-specific differences in stress experiences were observed, with female students exhibiting higher levels of stress compared to their male counterparts, particularly in terms of emotional stress and lack of energy. Interestingly, while age did not significantly impact stress and recovery experiences, other variables such as workload and coping strategies appeared to play crucial roles. Our study underscores the importance of tailored interventions and support mechanisms to address the diverse needs of students, including mindfulness-based approaches, social support networks, and academic accommodations. Overall, this research sheds light on the intricate relationship between stress, resilience, and academic outcomes among students, offering valuable insights for educators, policymakers, and mental health practitioners seeking to enhance student well-being and academic success in higher education settings.