bluuebunny/crossref_metadata_2025_split huggingface dataset:
The influence of different storage conditions on Limnospira indica, a promising candidate for air revitalisation in Space
Authors: Leys Natalie , Fahrion Jana , Ellena Gabriele , Mastroleo Felice , Dussap Claude-Gilles 
Published: March 2024

Abstract

Limnospira indica is a cyanobacterium which is currently investigated as a candidate for life support systems in space. Transport to space starts with a storage phase, the time span between leaving the laboratory on Earth and the activation of the bioprocess in space. Here, the cells are kept in dormancy at 4°C, because energy is limited during the upload. This period can take up to two weeks and the influence on living biomass has not been extensively studied. This paper elucidates the influence of dark and cold storage on Limnospira indica growth and composition. The impact depends on gas availability, duration, nutrient availability during storage and initial cell density, pH and pigment content. Additionally, to simulate storage after the arrival of Limnospira indica onboard the ISS, a 14 days cold storage was performed using a dedicated simulated microgravity setup. No negative effect of simulated microgravity was found, when a healthy culture is used.
Quantum Computing Quantum Monte Carlo
Authors: Yuan Xiao , Zhang Yukun , Huang Yifei , Sun Jinzhao , Lv Dingshun 
Published: March 2024

Abstract
Quantum computing and quantum Monte Carlo (QMC) are respectively the state-of-the-art quantum and classical computing methods for understanding many-body quantum systems. Here, we propose a hybrid quantum-classical algorithm that integrates these two methods, inheriting their distinct features in efficient representation and manipulation of quantum states and overcoming their limitations. We first introduce non-stoquasticity indicators (NSIs) and their upper bounds, measuring the severity of the sign problem, the most notable limitation of QMC. Then we introduce the hybrid QC-QMC method by replacing the walkers with quantum states prepared by a shallow quantum circuit. We present an efficient and scalable approach to implement walker propagation in QC-QMC. We show that our algorithm could greatly mitigate the sign problem, which decreases NSIs with the assistance of quantum computing. Meanwhile, the use of quantum Monte Carlo also increases the expressivity of shallow quantum circuits, allowing more accurate computation that is conventionally achievable only with much deeper circuits. We numerically test and verify the method for the N$_2$ molecule (12 qubits) and the Hubbard model (16 qubits). Our work paves the way to solving practical problems with intermediate-scale and early-fault tolerant quantum computers, with potential applications in chemistry, condensed matter physics, materials, high energy physics, etc.
Attitudes and Beliefs About Gender Violence in Toledo University Students: a Cross-sectional Study
Authors: Gurrutxaga Mª Idoia Ugarte- , Molina-Gallego Brígida , de Corral Gonzalo Melgar , Mordillo-Mateos Laura , -García María Humanes , -Torres Juan Manuel Carmona 
Published: March 2024

Abstract

Aim
To analyse attitudes towards gender and violence and the sexist beliefs of the student body based on different sociodemographic variables and to study the relationship between attitudes towards gender and violence and the sexist beliefs that students show.
Design:
Descriptive cross-sectional study, following the Strengthening the Reporting of Observation Studies in Epidemiology (STROBE) checklist.
Methods
This study was carried out with undergraduate students from the University of one of the Campuses of the University of Castilla-La Mancha de enrolled in the 2022–2023 academic year. A total of 1176 students took an online survey. This survey included sociodemographic variables, the Questionnaire of Attitudes towards Gender and Violence (CAGV) and the variables of sexism (hostile and benevolent) reflected in the Ambivalent Sexism Inventory (ISA). A descriptive analysis, an inferential analysis and a Pearson correlation were performed for the scores of the two scales used, controlling for the influence of sex and age.
Results
Of the participants, 67.1% women and 32.0% were men. The average age was 20.13 years, with a deviation of 2,166, aged between 18 and 26 years. Being carried out in several Faculties of the Campus. The results highlight the significant differences between the group of men and women in both questionnaires, observing differences between the age groups. In general, men have higher scores than women, so they have higher sexist attitudes and beliefs. The correlations between both questionnaires are significant among all categories.
Conclusions
We believe that the data analysed call for the implementation of action plans to reduce sexist behaviour in university students. Universities must establish action plans against gender violence.
Cryptocurrency Price Prediction: A Comparative Sentiment Analysis Approach Using SVM, CNN-LSTM, and Pysentimento during Times of Crisis
Authors: Rateb Muhammad Nabil , Alansary Sameh , Elzouka Marwa Khamis , Galal Mohamad 
Published: March 2024

Abstract
Sentiment analysis is a powerful tool for extracting valuable insights from social media data. In this paper, more than one million tweets spanning three months (March, June, and December 2022) regarding three cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), and Binance Coin (BNB) during the Russian-Ukrainian War are considered. Two models, a convolutional neural network with long short-term memory (CNN-LSTM) and a support vector machine (SVM) with GloVe and TF-IDF features, are trained on a labeled dataset of more than fifty thousand tweets about Bitcoin labeled as (positive, negative, and neutral). A pretrained model (Pysentimento) for sentiment analysis is also employed to compare the performances of the three models. The models are tested on the labeled dataset and then evaluated on the unlabeled tweets, revealing that Pysentimento's level of accuracy outperforms the other two models. Google Trends, along with the opening and closing prices, and the volume of the three cryptocurrencies, in addition to the results of Pysentimento sentiment classification, are employed to apply the Pearson correlation coefficient and conduct price prediction analysis using the SARIMA model. It is found that Bitcoin may appeal to those seeking stability and a known record of accomplishment, while Binance Coin and Ethereum may attract investors looking for more diverse opportunities. Sentiment analysis using machine learning is found to provide invaluable information for cryptocurrency price forecasting and trading strategies, especially in the context of geopolitical events and market volatility.
Preliminary Research on Tailored Fluid Therapy in Pigs: Comparing Customized Ionic Solutions with Hartmann's Solution
Authors: Lee Seongju , Lee Seung-Eun , Han Jae-Ik , Lee Sang Chul , Jeon Yubyeol 
Published: March 2024

Abstract
Background
Fluid therapy in veterinary medicine is pivotal for treating various conditions in pigs; however, standard solutions, such as Hartmann's solution, may not optimally align with pig physiology. This study explored the development and efficacy of a customized fluid therapy tailored to the ionic concentrations of pig blood, aiming to enhance treatment outcomes and safety in both healthy and diseased pigs.
Results
The study involved two experiments: the first to assess the safety and stability of customized fluids in healthy pigs, and the second to evaluate the efficacy in pigs with clinical symptoms of dehydration. In healthy pigs, the administration of customized fluids showed no adverse effects, with slight alterations observed in pO2, Hematocrit, and glucose levels in some groups. In symptomatic pigs, the customized fluid group did not show any improvement in clinical symptoms, with no significant changes in blood chemistry or metabolite levels compared to controls. The customized fluid group showed a mild increase in some values after administration, yet within normal physiological ranges. The study reported no significant improvements in clinical or dehydration status, attributing the observed variations in blood test results to the limited sample size and anaesthesia effects rather than fluid characteristics.
Conclusions
Customized fluid therapy, tailored to mimic the ionic concentrations of pig blood, appears to be a safe and potentially more effective alternative to conventional solutions such as Hartmann’s solution for treating pigs under various health conditions. Further research with larger sample sizes and controlled conditions is recommended to validate these findings and to explore the full potential of customized fluid therapy in veterinary practice.
Impact of long-term storage on mid-infrared spectral patterns of serum and synovial fluid samples of dogs with osteoarthritis
Authors: Malek Sarah , Marini Federico , McClure J T. 
Published: March 2024

Abstract

The aim of this study was to evaluate the impact of short versus long-term storage on mid-infrared (MIR) spectral patterns of serum and synovial fluid (SF) of dogs with knee osteoarthritis (OA) and controls. Serum (52 OA and 49 control) and SF (51 OA and 51 control) samples from dogs that had been in short-term (<3 years) frozen state (-80°C) had their MIR spectra obtained. The remaining aliquots were maintained in long-term (>5 years) frozen state before having MIR spectra acquired under the same testing conditions. Spectra from the two time points were significantly different (P<0.0001), however, sample aging accounted for only 1.61% and 2.98% of serum and SF profiles’ variability, respectively. Predictive models for discriminating serum of OA from controls for short-term storage showed 87.3±3.7% sensitivity, 88.9±2.4% specificity and 88.1±2.3% accuracy, while, for long-term storage, values of the same figures of merit were 92.5±2.6%, 97.1±1.7% and 94.8±1.4%, respectively. Predictive models based on short-term stored SF spectra had 97.3±1.6% sensitivity, 89.4±2.6% specificity and 93.4±1.6% accuracy, while the values for long-term storage 95.7±2.1%, 95.7±0.8% and 95.8±1.1%, respectively. Long-term storage of serum and does not significantly alter the performance of predictive algorithms for discriminating OA samples from controls.
Impact of COVID-19 pandemic on specialty training in Obstetrics and Gynaecology in Hong Kong: what is the future prospect?
Authors: LEUNG Janice Tsz Ching , LI Yan Yu , KONG Choi Wah , TO William Wing Kee 
Published: March 2024

Abstract

Introduction
The COVID-19 pandemic in the past few years have led to major adjustments in the provision of healthcare. This study aimed to investigate the impact of the pandemic on specialty training in Obstetrics & Gynaecology (O&G) in Hong Kong.
Methods
A cross-sectional questionnaire survey was performed on all the O&G trainees and the young fellows of the Hong Kong College of Obstetricians and Gynaecologists (HKCOG). The questionnaires included 5 parts: demographic data, impact on clinical activities, redeployment, educational activities and career progression.
Results
A total of 104 questionnaires (92.9%) were received for final analysis. The majority of the participants had reductions in elective and emergency operations, as well as exposure to in-patient admissions and out-patient clinics in both obstetrics and gynaecology. The reduction was most significant in elective gynaecology operations. One-third (34.6%) of the participants had been redeployed to other departments, and educational activities were reduced during the pandemic. Around 58% of the trainees were concerned with the reduction in clinical exposure, and 78% worried they would not be able to log sufficient number of surgical procedures. Basic trainees were significantly more worried than higher trainees. Around half of the trainees had doubts or regrets about choosing to undergo O&G specialty training.
Conclusion
The COVID-19 pandemic had significant negative impacts on O&G training in Hong Kong. Many trainees were worried they would not be able to attain the required level of competence when they complete their specialist training.
Integrated operation of water resources in climate change conditions, considering uncertainty based on coupled dynamic models of surface water and groundwater
Authors: Azizi Kamran , Azari Arash , Bansouleh Bahman Farhadi 
Published: March 2024

Abstract
In regions with arid and semi-arid climates, groundwater serves as one of the main sources of agricultural, industrial, and drinking water supply, constantly interacting with surface waters. The purpose of this study is to investigate changes in the level and volume of aquifer storage in Kermanshah by simulating the interaction of surface and groundwaters, using a coupling dynamic model WEAP-MODFLOW. This model is capable of calling and automatically running climate change scenarios and displaying their effects on the entire system. In this method, data and results between the MODFLOW and WEAP models are exchanged on a monthly basis, and the impacts of implementing each of the CMIP5 climate scenarios can be observed in both surface water and groundwater sections. The values of recharge, extraction, runoff, river levels, and water supply from the WEAP model are input into the MODFLOW model to calculate groundwater levels and changes in aquifer storage, with results fed back to the WEAP model. To apply model uncertainties and climate scenarios was developed a hybrid model based on the combination of predictions from 5 different AR5 models. The results showed that over a base period of 27 years (October 1991 to September 2018), the average groundwater level at the end of the period decreased by 4.3 meters, with a reservoir volume reduction of 253 million cubic meters. In the event of aquifer operation, based on the predicted climatic parameters derived from the hybrid model during the 81 years (October 2018 to September 2099), the level of reduction and volume of aquifer storage was predicted under the optimistic scenario of RCP2.6 in order of 2.52m and 251.51MCM and the pessimistic scenario RCP8.5, respectively 8.88m and 769.04 MCM. The results demonstrated that employing an integrated operation model in a dynamic link mode is an effective strategy for better river and aquifer management under climate change conditions. The effects of each climate scenario on the entire system are observable in this model, aiding decision-makers in implementing effective adaptation strategies to climate change.
Challenges in Neurosurgery During Armed Conflict in Sudan
Authors: Ibrahim Honida Ali M. , Elabdin Moayad Moawia Z. , Ali Mukashfi Elnaiem A. , SalahEldin Azza , Alameen Sayda Babekir M. , Kongar Abdalhadi Andal A. , Elazrag Tarig , Ahmed Asim ShamsEldein M. , Mohamedahmed Mohaned Abdelrhman , Essa Faisal Ali , Gassoum Alsadig , Aldeaf Sawsan A. H. 
Published: March 2024

Abstract
Introduction:
Sudan armed conflict between rapid support force (RSF) and Sudanese army was one of the wicked wars, the conflict has had terrible physical, emotional, and economic costs for Sudanese, this war caused great traumatic injuries among civilians despite the number of affected persons, during the period of this armed conflict, there is no data or reports regarding affected civilians.
Material and methods:
This is descriptive experience based and cross sectional study done at Almubarak hospital, kassala town from July 2023 to March 2024. In fact, the study was designed to reflect our neurosurgical experience during the period of armed conflict between rapid supporting force (RSF) and Sudanese army, hence the war is still going on, also, this paper describe the neurosurgical circumstances in Sudan throughout the war compared with other war that occurring in the middle East and worldwide . Modification and replacement in neuro-anesthia, showed that, isoflorane was replaced by low Minimal Alveolar Concentration (MAC) halothane<0.6%, or total intravenous anesthesia (TIVA) (propofol continuous infusion). Instead of Nitrous oxide and medical air, 100% oxygen 4 litter flows was used.
Results:
During the period of this study, we made some changes in techniques and treatment strategies for treating patients with neurosurgical problems. Our data revealed, 18 patients were presented with extra-dural haemorrhage (EDH), depressed fracture was detected in 42 of the patients, and hydrocephalus 12, abscess 5, tumor were 8, and sub-dural haemorrhage (SDH) was encountered in 41 patients.
Design of LED constant current driving circuit
Authors: Cheng， Mengzhang , Yu Xinyu 
Published: March 2024

Abstract
A 3W series LED constant current drive integrated circuit is designed in this paper. The driver can provide a constant current of 350mA for LED devices with over temperature and over voltage protection. When the power supply voltage fluctuates within ± 10%, the output driving current changes less than 5%; When the temperature of chip varies between 0 º C and 120 º C, the change in output driving current is less than 5%. The chip includes constant current drive, over temperature, and over voltage control circuits, as well as high-power driving NMOS devices. The control circuit consists of a bandgap voltage reference, an error amplifier, a sampling circuit. The bandgap voltage reference provides three reference voltages that are independent of temperature and power supply voltage; The sampling circuit and operational amplifier form a negative feedback circuit, allowing the sampling NMOS and power NMOS to operate at the same temperature and current density, so that the sampling current can more accurately reflect the changes in the output driving current of the power NMOS, and improve the control accuracy of the output driving current. By using a feedback control circuit, the sampling current tends to be constant, thereby achieving the goal of controlling the output driving current. The automatic adjustment of output current is achieved through over temperature and overvoltage circuits, which not only ensures the continuity of output current but also effectively ensures the safety of LED devices.
PL-NCC: A Novel Approach for Fake News Detection through Data Augmentation
Authors: Arunthavachelvan Keshopan , Hasan Emrul , Ding Cherie , Raza Shaina 
Published: March 2024

Abstract

Fake news has become rampant with the prominence of social media, jeopardizing information integrity and the reliability of news. It becomes imperative for media platforms to develop robust and efficient strategies to mitigate the spread of fake news. We make two contributions to fake news research in this work. Firstly, we propose the Psycho-Linguistic News Content and Comments (PL-NCC) dataset, a consolidated dataset of two leading fake news datasets, NELA-GT and Faked-dit, which leverages linguistic and psychological characteristics from the news articles and user comments to improve the classification accuracy of benchmark models. Secondly, we propose the News Content and Comments (NCC) classification model to leverage the psychological features extracted from our PL-NCC dataset, which introduces a feed-forward layer to a deep learning model, enhancing the efficacy of the extracted psychological features to better identify fake news. Our approach achieves a classification accuracy of over ninety percent, exceeding baseline results.
Research on the Impact of Population Agglomeration on Carbon Emission Efficiency: Empirical evidence from 284 cities in China
Authors: Zhou Fan , Zhou Zhou 
Published: March 2024

Abstract
It is of great theoretical and practical significance to explore the impact of population concentration on the efficiency of urban carbon emissions in order to build a long-term mechanism of green development in China. Based on the panel data of 284 prefecture-level cities in China from 2003 to 2019, this paper uses the super-efficient SBM model to measure the urban carbon emission efficiency, and depicts the upgrading of urban industrial structure with the upgrading and rationalization of industrial structure, and then makes quantitative analysis on this basis. The results show that population concentration can significantly improve the efficiency of urban carbon emissions. The conclusion is still valid after dealing with endogenous problems and robustness testing. Population concentration can improve carbon emission efficiency by stimulating regional technological innovation level; The upgrading and rationalization of industrial structure have a threshold effect on the urban carbon emission efficiency. The impact of the upgrading of industrial structure on the carbon emission efficiency before and after the threshold value presents a trend of "first restraining and then promoting", while the rationalization of industrial structure presents a more obvious promoting effect after crossing the threshold; Spatial measurement shows that urban carbon emission efficiency has a significant positive spillover effect, and also has a significant promotion effect on the carbon emission efficiency of neighboring cities, and the intensity is higher than the local level. Finally, based on the empirical conclusion, the corresponding policy recommendations are put forward from the perspective of the government.
A Novel Application of Filtration for the Collection of Microplastics in Waterways
Authors: Isahaku Ziddane 
Published: March 2024

Abstract
Since their invention, plastics have become ubiquitous in modern societies all around the world, and their impact on the environment has, in recent years, become nearly as well-known. Plastics produced by humans have reached nearly every corner of the world, and throughout their centuries-long lifetimes, plastics continually break down into smaller and smaller particles due to the physical stresses which they are subjected to. These stresses eventually, inevitably, break these plastics down into microplastics –pieces of plastic small enough to be consumed by organisms in bodies of water throughout the globe. These microplastics can very easily bioaccumulate, and have been found everywhere from the Great Lakes to the bloodstreams of humans. The effects of these plastics are poorly understood, however, they have been linked to infertility, halted growth, and a host of other maladies in aquatic organisms. Currently, removal of these plastics has been neglected, with no governmental action to remove them from marine environments, and this project aims to begin prototyping a solution to this issue. A significant percentage of microplastics are found at the surface of waterways, thus trawling in surface waters using an autonomously propelled net is proposed as a way to solve this seemingly intractable issue. By attaching motors and a guidance system to a manta trawl, a device currently used for collecting microorganisms, the process of collecting microplastics in open water can be automated, and thus the work of removing plastics from the environment on a large scale can begin.