bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modelling the impact of COVID-19 on unemployment patterns across diverse sectors in the Valencian Community, Spain.
Authors: Saurina Laura Serra , Juan Pablo , Chaudhuri Sommath 
Published: October 2023

Abstract
The COVID-19 crisis has brought about a substantial and abrupt disruption to the economy of the EU27, leading to the need for unprecedented policy responses in the European Union (EU) nations. The aim of this research is to analyse the impact of the pandemic on unemployment within the Valencian Community, Spain. Specifically, it aims to examine and compare the effects on the major economic sectors in the region, namely industry, service, agriculture and construction. The study investigates the variation in unemployment rates across municipalities and in those economic sectors. To achieve this objective, we used a dataset comprising economic data collected at the municipal level from 2016 to 2021, including variables such as unemployment rates, the number of companies, government spending, budgetary data and debt levels. To explore these economic phenomena, we used spatio-temporal quantitative models that incorporate integrated nested Laplace approximation (INLA) and stochastic partial differential equation (SPDE) methodologies. These specialized methodologies are employed alongside three distinct approaches with various analytical strategies to effectively analyse and comprehend the dynamics of economic factors, allowing us to gain a deeper understanding of the impact of the pandemic on unemployment within the Valencian community. The study first examines the economic situation in the Valencian community by considering all municipalities, stratifying them by each of the economic sectors considered and separating them into three years: 2019, 2020 and 2021. The second approach categorizes municipalities by population size (small, medium, large) and considers political subsidies based on population and unemployment. The final approach uses temporal models to monitor changes from 2016 to 2021, capturing both political and social shifts. The results reveal a uniform impact of the lockdown on all four sectors. Upon closer examination of the three methodologies, it becomes evident that the initial approach, which did not account for temporal effects, emphasized the significance of spatial effects, and the best models are those that include all the elements, covariates, temporal effects and the spatial distributions of the municipalities.
Alanine transaminase is a risk factor for Acute pericarditis: A Mendelian Randomization study
Authors: Liu Ze-Yu , Chen Guan-Lin , He Ying-Zheng , Qiu Shi-Zhen , Lin Jun-Yuan , Lei Bing-Xi , Zhou Xue-Qiong 
Published: October 2023

Abstract
Background
As a kind of cardiovascular disease, the association between acute pericarditis and ALT has not been reported, and whether there is a causal relationship between ALT and acute pericarditis is still unclear. Therefore, we aimed to explore the potential causal relationship between ALT and the risk of acute pericarditis using a Mendelian randomization (MR) design.
Methods
We used large consortia of candidate gene summary data from a genome-wide association study (GWAS) to explore a causal association between levels of liver enzymes (alanine transaminase) and acute pericarditis. The IEU OPEN GWAS Project data were used for the GWAS of liver enzyme levels and included 437,267 participants. The IEU OPEN GWAS Project data, which included 437,267 participants, were utilized for investigating liver enzyme levels. Similarly, these data were also analyzed to assess the occurrence of acute pericarditis among 337,199 participants of mainly European ancestry from various countries. The main method used in this study is inverse-variance weighted (IVW), supplemented by the weighted median method and MR-Egger method.
Results
The results of IVW methods demonstrated that ALT was significantly associated with higher odds of acute pericarditis, with an odds ratio (OR) of 1.0016 (95%CI, 1.00004-1.00316; p<0.05). Furthermore, both funnel plots and MR-Egger results indicated no directional pleiotropic effects between ALT and acute pericarditis.
Conclusions
Our study provided potential evidence for a causal association between ALT and acute pericarditis, suggesting that enhanced screening for ALT allows for early detection of acute pericarditis.
Smartphones enabled up to 58 seconds strong-shaking warning in the M7.8 Türkiye earthquake
Authors: Finazzi Francesco , Bossu Remy , Cotton Fabrice 
Published: October 2023

Abstract
Public earthquake early warning systems (PEEWSs) have the potential to save lives by warning people of incoming seismic waves up to tens of seconds in advance. Given the scale and geographical extent of their impact, this potential is greatest for destructive earthquakes, such as the M7.8 Pazarcik (Türkiye) event of 6 February 2023, which killed almost 60,000 people. However, warning people of imminent strong shaking is particularly difficult for large-magnitude earthquakes because the warning must be given before the earthquake has reached its final size. Here, we show that the Earthquake Network (EQN), the first operational smartphone-based PEEWS and apparently the only one operating during this earthquake, issued a cross-border alert within 11 seconds of the beginning of the rupture. A comparison with accelerometer and macroseismic data reveals that, owing to the EQN alerting strategy, Turkish and Syrian EQN users exposed to intensity IX and above benefitted from a warning time of up to 58 seconds before the onset of strong ground shaking. If the alert had been extended to the entire population, approximately 2.7 million Turkish and Syrian people exposed to a life-threatening earthquake would have received a warning ranging from 30 seconds to 66 seconds in advance.
Intense laser interaction with micro-bars
Authors: Pomerantz Ishay , Elkind Michal , Cohen itamar , Blackman David , Meir Talia , Perelmutter Lior , Catabi Tomer , Levanon Assaf , Glenzer Siegfried , Arefiev Alexey 
Published: October 2023

Abstract
Intense laser fields interact very differently with micrometric rough surfaces than with flat objects. The interaction features high laser energy absorption and increased emission of MeV electrons, ions, and of hard x-rays. In this work, we irradiated isolated, translationally-symmetric objects in the form of micrometric Au bars. The interaction resulted in the emission of two forward-directed electron jets having a small opening angle, a narrow energy spread in the MeV range, and a positive angle to energy correlation. Our numerical simulations show that following ionization, those electrons that are pulled into vacuum near the object's edge, remain in-phase with the laser pulse for long enough so that the Lorentz force they experience drive them around the object's edge. After these electrons pass the object, they form attosecond duration bunches and interact with the laser field over large distances in vacuum in confined volumes that trap and accelerate them within a narrow range of momentum. The selectivity in energy of the interaction, its directionality, and the preservation of the attosecond duration of the electron bunches over large distances, offer new means for designing future laser-based light sources.
CCCD: A Deep Deterministic Policy Gradient based Data Augmentation Technique using Change Detection and Automatic Augmentation for Counting a Crowd
Authors: Sharma Ranjana , Dutt Sarthika , Dwivedi Rakesh Kumar , Kumari Neeraj 
Published: October 2023

Abstract
The necessity to address a difficult, significant, real-world image-based counting problem that cannot be adequately addressed with existing methodologies is what inspired this research. In order to overcome the difficulties mentioned above, we suggest a fresh method for teaching counting that builds on the earlier methods in several ways. A useful method for improving the performance of the counting model is data augmentation. The use of data augmentation can raise the amount and quality of training datasets, enhance model performance, and prevent the issue of data over-fitting. The phrase "data augmentation" refers to a collection of techniques used to increase the quantity and quality of training datasets so that Deep Learning models can be trained from them. Geometric transformations like color-space enhancement, kernel filters, combining pictures, and feature space augmentation are just a few of the image augmentation methods included in this examination. We propose a novel deep framework for counting, based on deep reinforcement learning. A pre-trained model with change detection is used before repeatedly attempting to build a Deep Deterministic Policy Gradient (DDPG)-based data augmentation strategy. After determining the optimum augmentation action for a given dataset, the augmented dataset is utilized to enhance the model. The outcomes of the experiment demonstrate that the automatic augmentation method may be utilized to produce adaptable augmentation strategies for counting models targeted at certain datasets.
Moving targets intelligent detection and tracking algorithm for that can restrain of local occlusion
Authors: YANG YueTing , Hu Shaolin , Zhang Jie , Ren Xinghua , Ke Ye 
Published: October 2023

Abstract
The optical imaging of the target motion process is susceptible to occlusion, resulting in detection failure and tracking loss. Aiming at the problems of low detection accuracy and poor robustness of existing multi-target tracking algorithms, this paper improves the YOLOv8 detection algorithm and DeepSort tracking algorithm, and constructs a YOLOv8 + DeepSort multi-target detection and tracking joint algorithm. In order to enhance the feature extraction ability of the model, the CBAM module is introduced into the YOLOv8 detection algorithm to retain more feature information. In order to further improve the tracking performance of the DeepSort algorithm, the Hungarian algorithm is selected to achieve the optimal matching of the detection box and the prediction box. The Euclidean distance is used to replace the IOU for the second matching of the failed detection box. The improved YOLOv8 and DeepSort joint algorithm is verified by experiments. The experimental results show that the average accuracy of the detection algorithm based on the improved YOLOv8 reaches 99.5 %, and the comprehensive detection and evaluation data are better than YOLOv4-tiny, YOLOv5, and YOLOv7 algorithms., The moving target is tracked in combined with the improved DeepSort, such that the Multiple Object Tracking Accuracy (MOTA) and Multiple Object Tracking Precision (MOTP) can reach 66.1 % and 84.3 % respectively, and the count of ID conversion is reduced by 16, verifying the effectiveness of the algorithm.
Topographical heterogeneity governs species distribution and regeneration potential by mediating soil attributes in Western Himalayan forests
Authors: Singh Shipra , Verma Abhishek , Hofhansl Florian 
Published: October 2023

Abstract
The present study is an attempt to understand variation in species composition and diversity and soil properties along topographic gradients in Western Himalayan reserve forests (400-3000m asl). To analyze changes in floristic composition, diversity, and regeneration status, we measured woody vegetation in forest plots at different altitudinal levels and contrasting aspects (North and south). Trees (diameter at breast height (DBH) > 10cm) and saplings (3-10cm DBH) were sampled in 10m×10m plots, shrubs were sampled in 5m×5m plots and seedlings (0-3cm DBH) were sampled in 1m×1m plots. To study variation in soil properties, samples were collected from each forest stand in five replicates from layers of 0-10cm, 10-20cm, and 20-30cm in soil depths. Canonical Correspondence Analysis (CCA) was applied to identify important factors that govern species distribution. Variance partitioning was conducted to quantify the relative contribution of elevation, slope aspect, vegetation attributes, and soil properties on regeneration potential of tree species. We found that environmental filtering shapes local species composition and associated edaphic factors in the region. Species richness and diversity were found to decrease with elevation. Soil properties (Organic Carbon, pH, and texture) and associated vegetation parameters did not vary significantly between the aspects. CCA confirmed that species composition was positively related to moisture content and available phosphorous at higher elevations, while reduced weathering rates and bulk density at lower elevations might have caused relatively lower nutrient turnover rates. Our study concludes that topographical variation and increased sum of soil nutrients are highly favorable for growth and development of plant species.
Soliton solutions of DSW and Burgers equations by generalized (G'/G) -expansion method
Authors: Hossain A. K. M. Kazi Sazzad , Akter Halida , Akbar M. Ali 
Published: October 2023

Abstract
Nonlinear evolution equations play a significant role in applied mathematics, including ordinary and partial differential equations, which are frequently used in many disciplines of applied sciences such as condensed matter physics, biophysics, atomic chains, optical fiber, chemical kinematics, molecular crystals and mathematical biology. The new generalized (G'/G)-expansion method provides an effective and more powerful mathematical tool for solving NLEEs arising in applied mathematics and mathematical physics for their easy calculation procedure. In this paper, two nonlinear evolution equations named the Drinfeld-Sokolov-Wilson equation and the Burgers equation are considered to find more new exact solutions by executing the new generalized (G'/G)-expansion method. Each of the derived solutions includes an explicit function of the variables in the equations under consideration. It has been established that the suggested techniques are more potential and successful at obtaining soliton solutions for nonlinear evolution equations. We provide some 3D plots to realize characteristics of the solutions.
Historical Assessment and Mapping of Human Plague in Kazakhstan: a Meta-analysis of Plague Epidemiology
Authors: Rametov Nurkuisa , Abdel Ziyat , Zhumadilova Zauresh , Yessimseit Duman , Abdeliyev Beck , Mussagaliyeva Raikhan , Issaeva Svetlana , AlThuwaynee Omar F. , Baygurin Zhaksybek , Tabynov Kairat 
Published: October 2023

Abstract
Understanding the historical assessment of plague in Kazakhstan is essential for early warning and decision support for effective health disaster management. For this purpose, this study evaluated historical data on plague from 1926 to 2003 in Kazakhstan using descriptive-analytical methods. The results of the study showed that between 1926 and 2003, there were 565 human plague cases in 82 different outbreaks. Cases that occurred in different regions include Almaty (32.22%), Aktobe (1.59%), Atyrau (4.42%), Mangistau (21.24%), Kyzylorda (40.53%) oblasts. The study showed that a higher percentage of cases were recorded before public health in Kazakhstan began using antibiotics and prophylactic measures against plague (1947-1948). Large outbreaks were found to have occurred in 1926, 1929, 1945, 1947 and 1948, accounting for about 80.7% of human-to-human transmission. Other forms of plague transmission include flea bites, cutting and skinning camels, wild animals, aerosolization, and rodent bites. The study also showed that the age range of patients affected by plague ranged from 0 to 86 years and was divided into two genders, including 49.9% males and 50.1% females, respectively. During the study period, there were bubonic (12.57%), bubonic septicemia (5.84%), bubonic pneumonia (1.06%), pulmonary (72.4%), secondary pneumonia (0.35%), septic (2.83%), cutaneous (0.18%), cutaneous bubonic (0.88%), tonsillar (0.35%), tonsillar bubonic (0.18%) forms and no clinical form (3.36%) data cases. There were cases of plague infection from person to person. The incidence was 0.29 per 10,000 people. The risk of human infection with plague is likely to increase with the expansion of anthropogenic areas in areas where plague foci exist in Kazakhstan. Increased awareness is needed for rapid diagnosis and treatment.
Environmental conditions predetermine innate antioxidants pool in sea oat (Uniola paniculata L.) seeds
Authors: Egesa Andrew Ogolla , Pérez Héctor E. , Begcy Kevin 
Published: October 2023

Abstract
Secondary metabolites such as antioxidants are critical components that protect seeds from stress damage during seed development, desiccation, and ex-situ storage. Antioxidants are essential determinants of seed quality, longevity, and persistence. Understanding the environmental factors that regulate the accumulation, content, and function of antioxidant pools in sea oat seeds is critical for gene banking and understanding the environmental impacts on seed quality. Germination, viability, and Trolox Equivalent Antioxidant Capacity (TEAC) were analyzed on seeds from 18 sea oat populations from the US Atlantic and Gulf of Mexico coasts. We first assessed baseline TEAC, followed by TEAC performed on imbibed seeds for 36 hours at 35/25 °C during the day and night, respectively. Then, we analyzed the relationship of the antioxidant pools from these 18 sea oat populations to sampling site environmental classifications. Higher baseline antioxidants were common in regions with extreme environmental conditions corresponding to sea oat populations growing at latitudinal extremes characterized by warmer and colder temperatures. Baseline antioxidants did not correlate with prevailing seed germination. However, higher concentrations of antioxidants following imbibition were associated with poor seed germination in warmer conditions. Our results indicate that climatic conditions and environmental components associated with temperatures and precipitation may largely influence the innate pool of antioxidants in sea oat seeds. Also, a high amount of antioxidants following sea oat seeds imbibition suggest seed damage or poor viability influenced by environmental stress conditions during seed development.
Ionospheric EM tests in solar eclipses days caused abnormal pendulum and gravimeter behavior at very remote scattered sites for many years.
Authors: Iovane Antonio 
Published: October 2023

Abstract
A meticulous study lasting 20 years, aimed at explaining reported mysterious anomalies in pendulum and gravimeter experiments in solar eclipse days, has revealed that the phenomenon was produced by an undisclosed campaign of EM tests by a very remote radio facility. Such anomalies had been reported in mainstream peer reviewed journals as per some cited references, but the articles substantially failed to propose any credible explanation. References have been found suggesting that the source was a facility 10000 Km away from scattered observation sites in Europe, very far apart. We examined experiments from 1999 to 2007.
Literature reports that, in solar eclipse days, some instruments had detected unexplainable anomalies which, despite Newton’s well-established gravity, fueled speculation about possible unknown features of gravity. The tiny temporal resolution of our own observations provided the key to solving the long-standing mystery. It took us 20 years to understand.
For the record, the root of these experiments is in that the French physicist Maurice Allais first reported pendulum anomalies during a solar eclipse in 1954. Referring to that work, NASA wanted to investigate the matter as per the cited reference, and promoted a worldwide test for the solar eclipse of August 11, 1999. We were recruited in July 1999, following our proposal for an unusual experiment (pendulum at rest). The participating stations were 16 as per the cited reference. (NASA has never released any reports). We have since conducted two campaigns of tests with stationary pendulums of our own design, actually detecting anomalies. After years of mystery we understood that their cause was not natural and matched the timing scheme of anomalies observed by others here and there in Europe. We report our results in detail with extensive control data, and a limited number of similar anomalies observed by others, some already published but still not as of artificial origin. In the examined experiments we found abnormal instrumental behaviors (sudden sharp micro-deviations) that obey a precise structure of equally spaced time markers. The timing scheme was always the same in all of said experiments. Subsequent research revealed that the scheme matched the one used by a very distant source of high-power, man-made, controlled radio signals. We conclude that the gravity-oriented instruments tracked by chance a long-lasting campaign of RF-based eclipse experiments.
СОНОГРАФІЧНІ ОЗНАКИ ЗМІН ЛЕГЕНЬ ТА НИРОК ПРИ НОВІЙ КОРОНАВІРУСНІЙ ХВОРОБІ-2019 У ВАГІТНИХ З ФЕТОПЛАЦЕНТАРНОЮ НЕДОСТАТНІСТЮ
Authors: Мацькевич Вікторія , Х. М. Ільницька  , О. Я. Царук  , І. С. Головчак  , О. Г. Бойчук  , Т. Л. Ленчук  , Л. В. Глушко  
Published: October 2023

Ультразвукове дослідження є основним методом діагностики змін легень і нирок у вагітних пацієнток з новою коронавірусною хворобою-2019. Метою дослідження є підвищення діагностичних можливостей виявлення змін легень та нирок, спричинених вірусом SARS-CoV-2 у вагітних з фетоплацентарною недостатністю у другому триместрі вагітності на підставі клінічних та ультразвукових ознак. У групу дослідження увійшли 42 пацієнтки віком 31-41 років, а у контрольну групу - 40 вагітних віком 29-40 років. Методи дослідження включали сонографічне обстеження легень та нирок, а також аналіз клініко-інструментальних даних. У 24 вагітних (57,1%) з фетоплацентарною недостатністю ультразвукові зміни легеневої тканини при коронавірусній хворобі-2019 представлені потовщенням і деформацією плевральної лінії, зливними В-лініями, транслобарною консолідацією з переважним ураженням нижніх долей легень. При сонографічному обстеженні нирок структурних змін паренхіми не виявлено, порожниста система не поширена.
Ключові слова: вагітність, фетоплацентарна недостатність, доплерографія, ультразвукове дослідження, коронавірусна хвороба-19, вірус SARS-CoV-2, пневмонія, легеневі хвороби.