bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine Learning Methods for Predicting the Admissions and Hospitalisations in the Emergency Department of a Civil and Military Hospital
Authors: Álvarez-Chaves Hugo , Muñoz Pablo , R-Moreno María D. 
Published: December 2022

Abstract
The importance of the Emergency Department (ED) in hospitals was highlighted during the outbreak of the COVID-19 pandemic when ED overcrowding became a critical issue. The management of the service is critical for the effectiveness and efficient operation of the department. In this study, we present the results of the application of different algorithms for forecasting ED admissions (both seven days and four months ahead) and daily hospitalisations. To do this, we have employed the ED admissions and inpatients series from a Spanish civil and military hospital. The ED admissions have been aggregated on daily basis and on the official workers' shifts, meanwhile the hospitalisations series have been considered daily. Over that data we employ two algorithms types: time series (AR, H-W, SARIMA and Prophet models) and feature matrix (LR, EN, XGBoost and GLM models). In addition, we create all possible ensembles among the models in order to find the best forecasting method, even splitting the series by shifts. Our results show that time series algorithms achieve the best performance for almost all cases, but in the short term both time series and feature matrix perform similarly. In general, the ensembles slightly improve the predictions over the single models.
Asymmetric inter-specific competition between invasive Phytolacca americana and its native congener
Authors: Liu Yun-Shan , Chen Li , Zhou Yue , Xiao Feng , Liu Dan-Feng , Wang Yi 
Published: December 2022

Abstract
Interspecific competition is an essential factor affecting the invasiveness of alien plants. Phytolacca americana, one of the most destructive invasive plants in China, was introduced from North America into China in 1935. Its population expand, thereby causing the loss of the ecological niches of its native congener and a shrinking of Phytolacca acinosa population. In this study, we used the invasive plant P. americana and its native congener P. acinosa to assess their competitive interaction in response to different competition patterns and spray treatments in a pot experiment in a homogeneous garden at Yunnan University. The results indicate that an asymmetric competition occurred between P. americana and P. acinosa in inter-specific competition. Specifically, P. americana severely inhibits the growth and reproduction of P. acinosa, and it was superior to P. acinosa in terms of defense strategy on account of its stronger resistance against insects and bacteria. Our study provides some theoretical basis for assessing the invasive plant P. americana.
Identification and Experimental Validation of Autophagy-Related Genes in Abdominal aortic aneurysm: a bioinformatics analysis
Authors: Yuan Xiaoli , Song Yancheng , Xin Hai , Zhang Lu , Liu Bingyu , Ma Jianmin , Sun Ruicong , Guan Xiaomei , Jiang Zhirong 
Published: December 2022

Abstract
Aim
Autophagy plays essential roles in abdominal aortic aneurysm (AAA) happening and movement. The objective of this study was to verify the autophagy-related genes (ARGs) underlying AAA empirically and using bioinformatics analysis.
Methods
Two gene expression profile datasets (GSE98278 and GSE57691) were taken from the GEO database. These datasets were combined and then standardized. The underlying differential expression autophagy-related genes (DEARGs) of AAA were tested using R software. PPIs, associativity, GO enrichment and KEGG pathway functional analyses were used to identify the DEARGs. Finally, RT-qPCR was used to identify the RNA expression levels of the top five hub genes in clinical samples.
Results
In data from 97 AAA patients and 10 healthy controls, a total of 44 DEARGs (6 up-regulated expressed genes and 38 down-regulated expressed genes) were classified. PPI results showed that these ARGs interact. GO and KEGG enrichment analyses were directed to elucidate the bio-functional of DEARGs. RT-qPCR results presented that the expressed of IL6, PPARG, SOD1 and MAP1LC3B in AAA cases and negative control were in accordance with the bioinformatic analysis results.
Conclusion
Hub genes such as IL6, PPARG, SOD1 and MAP1LC3B may influence the happening of AAA by controlling autophagy. These findings enhance interpretation of AAA and may be helpful in its diagnosis and treatment.
To determine the frequency of carotid plaques on Doppler USG and associated presenting symptoms at a Tertiary Care Centre, Lahore
Authors: Sahrish Fariha , Naseer Madiha 
Published: December 2022

Abstract
Objective
To determine the frequency of carotid plaques on Doppler USG and associated presenting symptoms at Tertiary Care Centre, Lahore
Methods
A cross-sectional study of 366 individuals was conducted from January 2020 to November 2020 at the Radiology Department of Shiekh Zayed Hospital, Lahore, Pakistan. A consultant radiologist scanned both sides of extra-cranial carotid artery tree. The DUS of carotid arteries was done with a GE Voluson Expert 730 Doppler ultrasound machine, using a linear probe with transducer frequency of 6-12.5MHz.
Results
A total of 366 patients underwent bilateral carotid Doppler ultrasound examinations. Our findings showed carotid plagues in 156 (42.62%) patients and majority were males 105(67.53). Mean age recorded was 61.17 ± 9.54 years and mean body mass index was 25.43 ± 3.40 Kg/m2. Highest number of plaques were noted in the left carotid artery 64 (41.03%), main location was common carotid artery 88 (56.41%) and majority were homogenous plagues 88 (56.41%).Majority patients presented with headache 177 (48.36%). Associated comorbidities were diabetes mellitus, hypertension and dyslipidemia.
Conclusion
The accuracy of diagnosing Carotid artery plagues has greatly increased over time due to radiological innovation. Carotid doppler ultrasound is a cheap noninvasive modality to detect carotid artery plagues due to its sensitivity, precision, and reliability. Since there is a high frequency of carotid plagues noted in middle age male adults, appropriate screening with prophylactic management can save a lot of disease burden from a lower middle income class country.
Forecasting Road Traffic Accident Using Deep Artificial Neural Network Approach in Case of Oromia Special Zone
Authors: Raja Kannaiya , Kaliyaperumal Karthikeyan , L. Velmurugan , Thanappan Subash 
Published: December 2022

Abstract
Millions of people are dying and billions of properties are damaged by road traffic accidents each year worldwide. In the case of our country Ethiopia, the effect of traffic accidents is even more by causing injuries, death, and property damage. Forecasting Road Traffic Accident and Predicting the severity of Road Traffic accident contributes a role indirectly in reducing road traffic accidents. This Study deals with forecasting the number of accident and prediction of the severity of an accident in the Oromia Special Zone using Deep Artificial Neural Network models. Around 6170 Road Traffic accidents data are collected from Oromia Police Commission Excel data and Oromia Special zone Traffic Police Department, the dataset consists of accidents in the Special Zone of Oromia Districts (Woredas) from 2005 to 2012 with 15 accidents attributes. 5928 or (80%) of the dataset was used for the training model and 1482 or (20%) of the dataset was used for the testing model. This study proposed Six different Neural Network architectures such as Backpropagation Neural Network (BPNN), Feed Forward Neural Network (FFNN), Multilayer Perceptron Neural Network (MLPNN), Recurrent Neural Networks (RNN), Radial Basis Function Neural Network (RBFNN) and Long Short-Term Memory (LSTM) models for accident severity prediction and The LSTM model for a time serious forecasting of number accidents within specified years. The models will take input data, classify accidents, predicts the severity of an accident. Accident predictor GUI has been created using Python Tkinter library for easy Accident Severity prediction. According to the model performance results RNN model showed the best prediction accuracy of 97.18% whereas MLP , LTSM, RBFNN, FFNN, and BPNN models showed the accuracy of 97.13%, 91.00%, 87.00%, 80.56%, 77.26%, respectively. LTSM model forecasted accident for Three years which is 3555 where the actual accident number is 3561. The prediction and forecast result obtained from the model will be helpful in planning and management of road traffic accidents.
Assessment of satellite precipitation products at different time scales over a cyclone prone coastal river basin in India
Authors: Setti Sridhara , Yumnam Karisma , Rathinasamy Maheswaran , Agarwal Ankit 
Published: December 2022

Abstract
Precipitation is a fundamental input for many hydrological and water management studies. With the advancement in science, a variety of satellite precipitation products are available. In this study, the ability of three satellite precipitation products (TRMM-3B42v7, PERSIANN-CDR and GPM-IMERGv6) to capture rainfall were evaluated with ground-based Indian Meteorological Department (IMD) gridded data and also by driving the Soil Water Assessment Tool (SWAT) hydrological model for a cyclone prone coastal river basin in the southeast of India. Results indicate that among the three, GPM-IMERG v6 outperformed in all the statistical metrics, followed by TRMM-3B42 v7 at different temporal scales. GPM-IMERG v6 exhibited the highest correlation coefficient (0.48) and lowest root mean square error (9.52 mm/day), followed by TRMM-3B42 v7 (CC = 0.44, RMSE = 9.58 mm/day) at daily scale. In contrast to other studies in similar regions, IMERGV6 showed better performance than the PERSIANN CDR in detection skills of low, medium and high intensity rainfall events as well as False Alarm Ratio. Hydrological evaluation of the three products using the SWAT model over the study area showed satisfactory results at daily and monthly scale during the calibration and validation period. IMERGV6 is found to have better performance in hydrological evaluation as well.
Facile Synthesis of Organic Compounds in PEG, ScCO2 and H2O: A Review
Authors: Chandra Nath Arabinda , Borah Gongutri 
Published: December 2022

Abstract:
Green solvent is a topic of increasing attention in modern chemistry because of the consciousness of the effect of solvents on air quality, energy usage, pollution, and continuous climate change. Over the past few years, remarkable progress has been made to accomplish these goals by giving interest in sustainable synthesis. For sustainable development, continuous efforts have been put forward for addressing these issues and the chemical approaches are now analysed for the usage of solvents. Realizing solvent property is a crucial area of green chemistry, and therefore the solvents were categorized by their handling techniques, ecological, and healthiness (ESH) features. The focus of this ranking is to help the researchers in choosing their reaction solvent efficiently, keeping in mind the ESH values of the solvents and discouraging them from using environmentally harmful and toxic solvents which are commonly used in laboratories. In this review article, we are trying to consider various synthetic methodologies of the most protuberant sustainable solvents such as polyethylene glycol, supercritical CO2, and water. We herein examine not only the chemical reactions but also represent the mechanism and synthetic utility of each class of solvent inside the background of the reactions for which it is used, but also documented the widespread substrate scope of the reaction. A broad range of economic and environmental factors are also demonstrated, giving a wider display of the current status of sustainable solvent research and development.
Serotonergic 5-HT7 Receptors as Modulators of the Nociceptive System
Authors: Bardoni Rita 
Published: December 2022

Abstract:
The biogenic amine serotonin modulates pain perception by activating several types of serotonergic
receptors, including the 5-HT7 type. These receptors are widely expressed along the pain axis,
both peripherally, on primary nociceptors, and centrally, in the spinal cord and the brain. The role of
5-HT7 receptors in modulating pain has been explored in vivo in different models of inflammatory and
neuropathic pain. While most studies have reported an antinociceptive effect of 5-HT7 receptor activation,
some authors have suggested a pronociceptive action. Differences in pain models, animal species
and gender, receptor types, agonists, and route of administration could explain these discrepancies. In
this mini-review, some of the main findings concerning the function of 5-HT7 receptors in the pain
system have been presented. The expression patterns of the receptors at the different levels of the pain
axis, along with the cellular mechanisms involved in their activity, have been described. Alterations in
receptor expression and/or function in different pain models and the role of 5-HT7 receptors in controlling
pain transmission have also been discussed. Finally, some of the future perspectives in this field
have been outlined.
The Wistar Kyoto Rat: A Model of Depression Traits
Authors: Redei Eva E. , Udell Mallory E. , Solberg Woods Leah C. , Chen Hao 
Published: December 2022

Abstract:
There is an ongoing debate about the value of animal research in psychiatry with valid lines
of reasoning stating the limits of individual animal models compared to human psychiatric illnesses.
Human depression is not a homogenous disorder; therefore, one cannot expect a single animal model
to reflect depression heterogeneity. This limited review presents arguments that the Wistar Kyoto
(WKY) rats show intrinsic depression traits. The phenotypes of WKY do not completely mirror those
of human depression but clearly indicate characteristics that are common with it. WKYs present despair-
like behavior, passive coping with stress, comorbid anxiety, and enhanced drug use compared to
other routinely used inbred or outbred strains of rats. The commonly used tests identifying these phenotypes
reflect exploratory, escape-oriented, and withdrawal-like behaviors. The WKYs consistently
choose withdrawal or avoidance in novel environments and freezing behaviors in response to a challenge
in these tests. The physiological response to a stressful environment is exaggerated in WKYs.
Selective breeding generated two WKY substrains that are nearly isogenic but show clear behavioral
differences, including that of depression-like behavior. WKY and its substrains may share characteristics
of subgroups of depressed individuals with social withdrawal, low energy, weight loss, sleep disturbances,
and specific cognitive dysfunction. The genomes of the WKY and WKY substrains contain
variations that impact the function of many genes identified in recent human genetic studies of depression.
Thus, these strains of rats share characteristics of human depression at both phenotypic and genetic
levels, making them a model of depression traits.
Local Lung Fibroblast Autophagy in the Context of Lung Fibrosis Pathogenesis
Authors: Marzoog Basheer Abdullah 
Published: December 2022

Abstract:
The current molecular advances in lung fibrosis pathogenesis distend beyond the cellular to involve subcellular and molecular levels. Lung fibrogenesis and autophagy impairment are tight-ly associated. Autophagy is involved in cell cycle control and regulation of the intracellular micro-environment. Degradation of impaired intracellular organelles and biproducts is crucial to maintain-ing a healthy cell and preventing its metaplasia / transdifferentiation to a pathological cell. Autoph-agy modifies the metabolism of alveolar epithelial cells, endothelial cells, and lung fibroblasts. Au-tophagy upregulation induces local lung fibroblast hyperactivity and fibrosis. Several molecular triggers were found to induce lung fibroblast autophagy including TGFβ by inhibition of the PI3K/AKT/mTOR. However, physiologically, a balance is retained between autophagy inducers and inhibitors. Each type of autophagy plays its role in the initiation and progression of lung fibro-sis. The pathogenesis of pulmonary fibrosis is multifactorial and involves dysfunction / dysregula-tion of alveolar epithelial cells, fibroblasts, monocyte-derived macrophages, and endothelial cells. The deposition of extracellular matrix proteins, the remodeling of the lung architecture and the mo-lecular changes include impaired glycolysis, mitochondrial oxidation, gene expression modification, altered phospholipid and sphingolipid metabolism, and dysregulated protein folding lead to repro-gramming of lung fibroblast into myofibroblast and their activation. The paper thoroughly addresses the molecular triggers and inhibitors of lung fibroblast autophagy in lung fibrosis.
Circulatory and Placental Expression of Soluble Fms-like Tyrosine Kinase-
1 and Placental Growth Factor in HIV-infected Preeclampsia
Authors: Mlambo Zinhle P. , Khaliq Olive P. , Moodley Jagidesa , Naicker Thajasvarie 
Published: December 2022

Abstract:
An imbalance between angiogenic and anti-angiogenic factors plays a fundamental role in
the pathogenesis of preeclampsia (PE). Studies have shown a dysregulation of sFlt-1 and placental
growth factor (PlGF) in PE. However, there are differing reports on the levels of these pro-/antiangiogenic
factors in HIV-infected preeclamptic and normotensive pregnancies, possibly due to
highly active antiretroviral therapy (HAART) and its immune reconstitution effect. The study aimed
to investigate the effect of hypertension and ARVs on circulating and placental pro- and antiangiogenic
factors in HIV-infected PE. The level of sFlt-1 expression is elevated in PE compared to
normal pregnancies. PlGF was altered by placental dysfunction. Antiretroviral therapy does not impact
the angiogenic shift in PE development. The angiogenic imbalance evident in the circulatory
system by higher sFlt-1 compared to PlGF levels is replicated in the placenta by reduced expression
of PlGF receptors in comparison to sFlt-1 receptors. However, there is a lack of data that explore the
relationship between HAART and anti-angiogenic factors in the placenta and the circulation of PE
comorbid with HIV infection.

Results:
The level of sFlt-1 expression is elevated in PE compared to normal pregnancies. PlGF was altered by placental dysfunction. Antiretroviral therapy does not impact the angiogenic shift in PE development.

Conclusion:
The angiogenic imbalance evident in the circulatory system by higher sFlt-1 compared to PlGF levels is replicated in the placenta by reduced expression of PlGF receptors in comparison to sFlt-1 receptors. However, there is a lack of data that explore the relationship between HAART and anti-angiogenic factors in the placenta and the circulation of PE comorbid with HIV infection.
Adaptive Training: A New Method to Improve the Image Quality of
Abdominal Magnetic Resonance Imaging
Authors: Letian Zhang , Huan Xie , Kun Fu , Qisheng Ran , Guang-Kuo Guo 
Published: December 2022

Background:
In abdominal magnetic resonance imaging (MRI), the late hepatic arterial
phase is particularly important for the diagnosis of hepatocellular carcinoma (HCC). However, poor
patient compliance with breath-hold imaging acquisition protocols and the administration of the liverspecific
contrast agent gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)
increases the motion artifacts that degrade the quality of the images making it more difficult to interpret
the images.

Objective:
This study aimed to evaluate the role of adaptive respiratory training in improving the quality
of the MRI by reducing the motion artifacts and improving the signal intensity from the regions of
interest (ROI) in the late hepatic arterial phase.

Methods:
A total of 120 patients who underwent an abdominal MRI between 2021 to 2022 to assess
for the liver disease were included in the study. These patients were divided into two groups: the experimental
group and the control group. The patients in the experimental group received adaptive training.
The incidence of motion artifacts and the signal intensity in the late hepatic arterial phase within
the abdominal aorta, hepatic artery, splenic artery, and hepatic parenchyma between the experimental
group and the control group were compared.

Results:
The incidence of motion artifacts in the experimental group was significantly reduced by
28.3% (p = 0.001, Chi-square value = 12.079). In the late hepatic arterial phase, the signal intensity of
the abdominal aorta, the hepatic artery, the splenic artery, and the hepatic parenchyma increased by
7.3%, 27.4%, 29.5%, and 6.9%, respectively.

Conclusion:
Adaptive respiratory training reduced the incidence of motion artifacts and improved the
signal intensity for various ROI. The improved image quality could potentially facilitate image interpretation
and reduce the number of repeat MRI scans.
Spatial Association Between Sociodemographic, Environmental Factors and Prevalence of Stroke Among Diabetes and Hypertension Patients in Thailand
Authors: Thammasarn Krittiyanee , Loahasiriwong Wongsa , Mahato Roshan Kumar , Sornlom Kittipong 
Published: December 2022

Background:
Stroke is one of the top leading causes of death and disability among adults and the elderly worldwide. Hypertension (HT) and Diabetes Mellitus (DM) are the most common contributory risk factors of stroke, accounting for up to 75% of all cases. This study aimed to investigate the spatial association between sociodemographic and environmental factors and the prevalence of stroke among DM and HT patients in Thailand.

Methods:
This spatial study applied global Moran’s I, the local indicators of spatial association (LISA) and spatial regression to examine the localised associations of sociodemographic and environmental factors and the prevalence of stroke among DM and HT patients in Thailand.

Results:
The univariate Moran’s I scatter plot of the annual prevalence of stroke in Thailand’s provinces observed significant positive spatial autocorrelation with the Moran’s I value of 0.454 (p < 0.05). The High-High clusters of strokes were mostly located in the center. The Bivariate Moran’s I indicated a spatial association between various factors and the prevalence of stroke in which the LISA analysis indicated; 16 Hot-spots or High-High clusters (HH) and 4 Cold-spot or low-low clusters (LL) with alcohol store density, 17 HH and 4 LL clusters with tobacco store density, 9 HH and 9 LL clusters with elderly population density, 5 HH and 3 LL clusters of primary care per population ratio, 16 HH and 3 LL clusters with LST, and 10 HH and 5 LL clusters with NTL. The Spatial Error Model (SEM) of spatial regression analysis has been observed to be the best model that could predict the variation in the prevalence of stroke by 50.80% (R2=0.508). SEM indicated tobacco store density (coefficient=0.065, P<0.05), elderly population density (coefficient=0.013, P<0.001, LST (day) (coefficient=1.417, P<0.05), and NTL (coefficient=0.021, P<0.05) were statistically significant associated with the prevalence of stroke among DM and HT patients in Thailand.

Conclusion:
Our study observed that the distribution of alcohol stores, density of tobacco stores, concentration of older adults, increasing day temperature and density of NTL were likely to be associated with enhancing the prevalence of stroke in the cluster and neighboring provinces of Thailand. The findings of this study will benefit public sectors or related organizations to develop efficient measures to control stroke.