bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and characterization of a heat shock transcription factor in the marine red alga Neopyropia yezoensis (Rhodophyta)
Authors: Wi Jiwoong , Choi Dong-Woog 
Published: November 2024

Abstract

Heat shock transcription factors (HSFs), which play a pivotal role in the high-temperature response, are found in all organisms. Terrestrial plants, in particularly, possess a greater number of HSF genes, suggesting their necessity for adaptation to severe dry and extreme temperature environments. Red algae inhabit intertidal zones subject to periodic desiccation and extreme temperature changes. Despite this, HSF genes have not yet been reported in red algae. In this study, we identify an HSF gene, NyHSF, from the marine red algae Neopyropia yezoensis. NyHSF has a DNA binding domain, oligomerization domain, and motifs that are well-conserved in the HSFA family of angiosperms. Phylogenic analyses showed that HSFs from red algae were grouped into a distinctive clade separate from those of green plants. NyHSF is located in the nucleus. When the NyHSF gene was overexpressed in single-cell green algae, Chlamydomonas, the transcription levels of heat response genes including heat shock proteins increased under normal growth conditions without heat stress, demonstrating that NyHSF acts as a transcriptional activator of these heat response genes. Transgenic Chlamydomonas cells overexpressing NyHSF showed a higher growth rate compared to wild-type cells under heat-stress conditions. NyHSF responds to high temperatures and shows different expression patterns depending on the tissues in N. yezoensis. These results suggest that NyHSF has distinctive sequences compared to those of green plants and plays an important role in regulating the growth and life cycle of N. yezoensis, which are highly affected by temperature changes.
Quantum ensemble learning with a programmable superconducting processor
Authors: Song Chao , Chen Jiachen , Wu Yaozu , Yang Zhen , Xu Shibo , Ye Xuan , Wang Ke , Zhang Chuanyu , Jin Feitong , Zhu Xuhao , Gao Yu , Tan Ziqi , Cui Zhengyi , Zhang Aosai , Wang Ning , Zou Yiren , Li Tingting , Shen Fanhao , Zhong Jiarun , Bao Zehang , Zhu Zitian , Song Zixuan , Deng Jinfeng , Dong Hang , Zhang Pengfei , Li Daili , Zhang Wei , Li Hekang , Guo Qiujiang , Wang Zhen , Li Ying , Wang Xiaoting , Wang H. 
Published: November 2024

Abstract

Quantum machine learning is among the most exciting potential applications of quantum computing. However, the vulnerability of quantum information to environmental noises and the consequent high cost for realizing fault tolerance has impeded the quantum models from learning complex datasets. Here, we introduce Adaboost.Q, a quantum adaptation of the classical adaptive boosting (Adaboost) algorithm designed to enhance learning capabilities of quantum classifiers. Based on the probabilistic nature of quantum measurement, the algorithm improves the prediction accuracy by refining the attention mechanism during the adaptive training and combination of quantum classifiers. We experimentally demonstrate the versatility of our approach on a programmable superconducting processor, where we observe notable performance enhancements across various quantum machine learning models, including quantum neural networks and quantum convolutional neural networks. With Adaboost.Q, we achieve an accuracy above 86% for a ten-class classification task over 10,000 test samples, and an accuracy of 100% for a quantum feature recognition task over 1,564 test samples. Our results demonstrate a foundational tool for advancing quantum machine learning towards practical applications, which has broad applicability to both the current noisy and the future fault-tolerant quantum devices.
Studying the cases of heart and arteries nutrition for cardiac patients using bioinformatics tools
Authors: Alashoush Basma , Alkuddsi Yanal , Aleinikovas Marius , Silinskas Benas , Almogdad Mohammad , Skema Mindaugas , Almukdad Manal 
Published: November 2024

Abstract

Cardiovascular diseases (CVD) are one of the most causes of death worldwide. Although of many habits like smoking and comorbidities are considered as a risk factors for developing CVD, poor eating habits should be taken into consideration. Bioinformatics tools provide powerful computational methods for analyzing CVD data. Therefore, the aim of this study was to develop a machine learning models to predict the deferent CVD to make the right decision in the protocol treatments of patients. The dataset was collected from Al-WATANI hospital in Sweida, Syria which included patients demographic, comorbidities, and dietary. The dataset was further split into training (60%) and test (40%) sets for building model and evaluating. Our study included 183 patients of which 111 patients were with hypertension, 33 patients with Infarction, 20 patients with congestive heart failure, and 19 patients with arrhythmia. Moreover, the accuracy of the algorithms varied, with support vector machine achieving the lowest accuracy of 71.62%, while it increased remarkably to 91.74% when applying the balanced weights. We also found that decision tree and random forest (tree depth = 5) achieved the same accuracies of 85.14%. However, when increasing the depth of the trees to 10, 15, or 20, the accuracy increased to 87.84% and remained steady. These models demonstrated high accuracy and reliability, making them valuable tools for clinical decision-making.
Prevalence, serotypes and antibiotic resistance patterns of Streptococcus agalactiae isolated from pregnant women in Khoy, Iran
Authors: Tabrizi Fatemeh Moghaddam , Najafinasab Elmira , Azarsa Mohammad 
Published: November 2024

Abstract

Background
Streptococcus agalactiae colonizes pregnant women and if transmitted to newborns during delivery, can lead to serious and fatal diseases such as sepsis, pneumonia, and meningitis. The aim of this study was to evaluate the frequency, serotypes, and antibiotic resistance patterns of Streptococcus agalactiae isolated from pregnant women’s vaginas.
Methods
In this cross-sectional study, 446 vaginal swab samples were collected from pregnant women. Suspected colonies were confirmed by conventional tests such as hemolytic activity, catalase, Gram staining, bile-esculin agar, CAMP, and hippurate hydrolysis. The antimicrobial susceptibility of Streptococcus agalactiae strains was determined via the Kirby-Bauer disk diffusion method. The presence of resistance genes (ermB, ermTR, mefA, and linB) was detected via Multiplex PCR method. The isolates were serotyped via the sequential multiplex-PCR method.
Results
A total of 42 strains were isolated from 446 vaginal swab samples. All the strains were sensitive to penicillin, ampicillin, and vancomycin, and 45.2% and 28.5% of the isolates were not susceptible to erythromycin or clindamycin, respectively. The ermTR, ermB, mefA, and linB genes were detected in 11(26.19%), 9(21.42%), 2 (4.76%), and 4 (9.52%) isolates, respectively. The most common serotype in this study was III (61.9%) followed by II (14.28%), Ia (11.9%), V (7.14%), and Ib (4.76%).
Conclusions
Serotype III is highly prevalent in Iran and due to its association with invasive diseases, screening of pregnant women and prophylactic treatment of carriers are necessary. The most important resistance mechanism for macrolides is the ermTR gene and the M phenotype.
Investigations on the additive manufacturing of structures made of copper-zinc alloys using wire and arc-based welding processes
Authors: Schop Malte , Schäfer Matthias , Ungethüm Tim , Schmale Hans Christian 
Published: November 2024

Abstract

There is a need in the industry for a highly productive and cost-effective additive manufacturing process that is capable of processing copper-zinc alloys in such a way that acceptable material properties are achieved. To develop technologies that fulfill the requirements, wire and arc-based additive manufacturing with copper-zinc alloys is investigated. As part of the technology development, experiments on tungsten inert gas (TIG) welding with CuZn37 filler wire on CuZn37 substrates are carried out. By varying the arc length, it is shown that with shorter arcs fewer lacks of fusion occur at the seam edges. With further welding experiments, preferred parameters for the manufacturing of higher wall structures are determined. The investigations demonstrate that the reproducible build-up of 20-layer wall structures and cylindrical blanks made of CuZn37 is possible with a TIG process. The cross-sections of selected welds and wall structures are analyzed and measured using an optical microscope. Some samples are scanned using a laser scanner to create height profiles. To investigate the mechanical properties within the additive manufacturing technology, tensile tests are carried out as well.
Effects of storage time and temperature on coagulation factor and natural anticoagulant activities
Authors: Nakanishi Ryosuke , Sakayori Tasuku , Matsui Daichi , Kono Mai , Maki Minase , Dunois Claire , Komiyama Yutaka , Morisaki Hiromi 
Published: November 2024

Abstract

Coagulation test results are influenced by many pre-analytical variables, including clinical sample storage conditions. This study investigated the effects of storage time and temperature on coagulation factor (FII, FV, FVII, FX, FVIII, FIX, FXI, FXII, and FXIII) and natural anticoagulant (antithrombin, protein C, and free protein S) activities. Blood samples from healthy individuals were centrifuged and plasma was tested after room temperature (18 to 25°C) or refrigerated (2 to 8°C) for 2, 3, 4, and 5 hours, or after frozen storage (-15 to -25°C) for 1, 2, 3, and 4 months. For all storage conditions, the mean percentage change from baseline in evaluated activities was < 15%, except for FV and FVIII. For FV activities after frozen storage at -15 to -25°C and FVIII activities at all storage conditions, the mean percentage change was > 15%. For FV and FVIII activities, the mean percentage change was < 15% after frozen storage at -75 to -85°C for 1, 2, 3, and 4 months. These labile factors are associated with rapid decreases in plasma levels in vitro. To ensure appropriate clinical testing results, especially for FV and FVIII activity, storage condition and time should be critically controlled.
Assessing the Spatial Demand for PCS for EVs Using Multi-source Big Data: An Example from Jinan City, China
Authors: Ren Qimeng , Sun Ming 
Published: November 2024

Abstract

Under the pressure of carbon pollution and resource scarcity, electric vehicles (EVs) have gradually replaced fuel vehicles as a new trend of low-carbon transformation. However, public charging stations (PCS) face problems such as insufficient quantity and unreasonable distribution. By using multi-source big data, this paper comprehensively analyzes the population distribution, traffic organization, infrastructure, land use and regional economy in the urban area of Jinan, China, and constructs evaluation indicators and spatial demand evaluation model for PCS. We analyse: 1) Distribution of population activity areas on weekday and rest days, high road network accessibility, high density area, high travel road network, commerce, public service facilities, parks, transportation facilities, residential area, high building coverage, high floor area ratio, economic development area and housing price level. 2) The impact of 14 evaluation indicators on space demand. 3) Demand level distribution of PCS in Jinan. 4) The distribution of current PCS and the comparison with the spatial demand model. The method recovers for the lack of comprehensive consideration of factors, intuitiveness of mathematical models, and urban geographic spatial research. This is of significance for predicting the use of PCS in the future and further promoting the whole popularization of EVs.
Charting spatial ligand-target activity using Renoir
Authors: Zafar Hamim , Rao Narein , Kumar Tanush , Pai Rhea , Mishra Archita , Ginhoux Florent , Chan Jerry , Sharma Ankur 
Published: November 2024

Abstract

The advancement of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics has enabled the inference of cellular interactions in a tissue microenvironment. Despite the development of cell-cell interaction inference methods, there is a lack of methods capable of mapping the influence of ligands on downstream target genes across a spatial topology with specific cell type composition, with the potential to shed light on niche-specific relationship between ligands and their downstream targets. Here we present Renoir for charting the ligand-target activities across a spatial topology and delineating spatial communication niches harboring specific ligand-target activities. Renoir also spatially maps pathway-level activity of ligand-target genesets and identifies domain-specific ligand-target activities. Across spatial datasets with varying resolution (spot to single-cell) ranging from development to disease, Renoir inferred cellular niches with distinct ligand-target interactions, spatially mapped pathway activities, and identified context-specific novel cell-cell interactions. Renoir uncovers biological insights and therapeutically-relevant cellular crosstalk from spatial transcriptomics data.
Flutter Control of Aircraft Wing using Auxetic Structures: Numerical Investigation
Authors: Rudresh M , Prashanth K P , V Praveen Kumar M , Ravikumar M , Sivambika S. 
Published: November 2024

Abstract

Aircraft Flutter is one of the significant concerns in achieving the required performance. These undesirable vibrations arising from interaction of aerodynamic and structural loads can be destructive. Trailing-edge wing morphing is one of the effective ways to tackle flutter. This work has been solely carried out to emphasis the concept of using integrated compliant mechanisms in the airfoil, being much efficient than using tradition wings, which is made up of flaps, ailerons separately which can cause problems like aileron reversal, etc. Re-entrant auxetic structures being one of the meta-materials, with negative Poisson's ratio to enable an effortless morphing mechanism as it has high flexibility along in-plane direction (chord-wise), at the same time combining with its torsional bending stiffness in out-of-plane direction (span-wise) results in finite weight reduction and delay in flutter, thereby increasing the flight performance characteristics. The 3D CAD Models were designed and numerical analysis is carried out. Modal analysis was done to compute the Eigen-frequencies of the Auxetic wing. Then, air-pressure was generated using CFD analysis. Finally, the fluid-structure interaction was done by importing the air-pressure and performing harmonic analysis. About 14.5% increase in resonant frequency was observed when Auxetic Structure was used also by reducing weight. This strongly indicates that, the Auxetic Wing is capable of withstanding higher frequencies before failure than regular wing, which can be used to delay flutter. This implies that the Auxetic Structure has the potential to be used as a structure with a passive morphing airfoil.
Seasonality of Rainfall in the Lake Victoria Basin is Controlled by the Large-Scale Circulation
Authors: Cook Kerry H , Andrews Patrick C. , Vizy Edward K. 
Published: November 2024

Abstract

Despite relatively constant surface temperatures, seasonally varying rainfall in the Lake Victoria Basin is bimodal, similar to much of East Africa. Precipitation maxima occur during the equinoctial seasons. Rainfall amounts are lower during boreal winter, and boreal summer is dry. Explanations involving movement of the intertropical convergence zone (ITCZ) are inadequate to explain this seasonal cycle since the ITCZ, with its low-level meridional moisture convergence, is not identifiable over the Lake Victoria Basin. The ERA5 reanalysis is evaluated and used to diagnose connections between the large-scale hydrodynamics of Lake Victoria Basin precipitation on seasonal time scales. A consideration of diurnal time scales is also included since averaging over the region’s pronounced diurnal cycles obscures physical processes. Primary analysis tools are a conservation of atmospheric water equation and moist static energy. Two large-scale circulation features are of primary importance for determining the seasonality of rainfall in the Lake Victoria Basin. One is the seasonality of the thermal low over the African continent, and the other is the seasonal formation and breakdown of the Somali jet. This basic understanding is needed for confident prediction on all time scales, and to assess the region’s vulnerability to anthropogenic climate change.
The role of Perception of Academic Stress and Emotion-focused Coping Style for International Medical Students’ Mental Health in China
Authors: Zhou Shisi 
Published: November 2024

Abstract

Lots of previous researches had suggested that medical students are higher rates of mental health problems than other age-matched groups, however, there was little attention caring about international medical students’ mental health status and influential factors. The research aims to investigate the present mental health status of international medical students and assess the role of perception of academic stress, emotion-focused coping style in international medical students’ mental health in China. By using data of international medical students (17-27 years old) providing information on their demographics, Perception of Academic Stress, The Coping Style Questionnaire, Generalized Anxiety Disorder Assessment (GAD-7), the Center for Epidemiological Studies Depression Scale Revised (CESD-R10), the WHO Well-being Index Scale (WHO-5), this study found that the depression (mean score=13.55, SD=5.85) and anxiety (mean score=9.78 , SD=4.49) was high among international medical students, perception of academic stress was a significant positive predictor of depression (β=0.22) and anxiety (β=0.17) , the emotion-focused coping style was a significant negative predictor of depression (β=-0.90) and anxiety (β=-0.69) and have positive association with well-being (β=0.97).
Reduced Hair and Salivary Cortisol Concentrations Associated with Improved Emotional Well-Being Following Repeated Forest Walking: A Randomized Intervention Trial in Older Adults
Authors: Jezova Daniela , Hlavacova Natasa , Karailievova Lucia , Lamatungga Kiki Ekiawan , Halamova Julia , Tamatam Dhanalakshmi , Pichlerova Magdalena , Pichler Viliam 
Published: November 2024

Abstract

The main hypothesis of this study in older adults is that repeated walks in a forest but not an urban environment for one month lead to reduced chronic stress compared to the previous month without any intervention. This was achieved by the measurement of cumulative cortisol concentrations in hair. Older adults of both sexes (n=54; 71±6.2 years) participated in a randomized, parallel-group trial. They were randomly assigned to a forest or an urban walking group. They completed two 40-minute walking sessions per week over one month. Hair samples and morning, as well as afternoon salivary samples, were collected at baseline and following one month of walking interventions.
A significant reduction in cumulative hair cortisol was observed during the month of repeated forest but not urban walking compared to the previous month, indicating decreased chronic stress. Salivary cortisol concentrations decreased in the forest group only. No differences in salivary alpha-amylase activity and state anxiety scores were noticed. Walking activities had no negative impact on the diurnal rhythmicity of stress markers. Quality of life measures showed improvements in emotional well-being in the forest group. A negative correlation was found between hair cortisol and certain quality of life dimensions in urban but not forest groups. Repeated forest walks affect objective measures of chronic stress in older adults evidenced by lower cumulative hair cortisol concentrations and improved emotional well-being. These findings encourage incorporating forest-based interventions into mental health programs for older adults to enhance well-being, cognitive functions, and stress coping.
Preoperative serum Albumin and BMI as Predictors of Postoperative Morbidity and Mortality in Emergency Abdominal Surgeries.
Authors: Kamarsu Vishnupriya , Veerabhadrappa Bharath S , Rodrigues Gabriel S 
Published: November 2024

Abstract

Purpose: To evaluate how preoperative serum albumin levels and BMI correlate with surgical outcomes in emergency abdominal surgery patients and to identify reliable predictors of postoperative complications and mortality for enhanced risk stratification and patient care optimization.
Methods: This prospective observational study included patients undergoing emergency abdominal surgery at our tertiary care facility between January 2021 and November 2023. We measured each patient's body mass index (BMI) and serum albumin levels before surgery. We then tracked postoperative outcomes, including complications, duration of hospital stays, and mortality, analyzing their relationships with these preoperative measurements.
Results:Postoperative complications and mortality rates were highest in the underweight group (BMI < 18.5 kg/m²) and in patients with hypoalbuminemia (serum albumin < 3.5 g/dL). Surgical site infections, sepsis, and pneumonia were the most frequent complications observed. Patients with moderate hypoalbuminemia exhibited significantly higher rates of complications and more extended hospital stays. While trends relating BMI to outcomes were observed, these associations did not reach statistical significance in our cohort.
Conclusion: Our findings suggest that serum albumin is a valuable, readily available, and independent predictor of postoperative morbidity and mortality in emergency abdominal surgery patients. In contrast, BMI did not demonstrate statistically significant predictive value in this study. These results underscore the importance of preoperative nutritional assessment and serum albumin levels in risk stratification and clinical decision-making for emergency abdominal surgical patients.
Trial registration number: CTRI/2021/02/030891
Registered on: 01/02/2021