bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forecasting of Solar Radiation for a Cleaner Environment using Robust Machine Learning Techniques
Authors: THANGAVELU MAGESH , Parthiban Vignesh Jayaraman , Kesavaraman Diwakar , Murugesan Thiyagesan 
Published: September 2022

Abstract

An intensified research is going on worldwide to increase renewable energy sources like solar and wind to reduce emissions and achieve the worldwide targets and also to address the depleting fossil fuels resources and meet the increasing energy demand of the population. The Solar Radiation (SR) is intermittent, forecasting the solar radiation beforehand is a must. The objective of this research is to use Modern Machine Techniques for different climatic conditions to forecast SR with higher accuracy.The required dataset is collected from National Solar Radiation Database having features as temperature, pressure, relative humidity, dew point, solar zenith angle, wind speed and direction, with respect to the y-parameter Global Horizontal Irradiance GHI (W/m2). The collected data is first split based on different types of climatic conditions. Each climatic model will be trained on various Machine Learning (ML) algorithms like Multiple Linear Regression(MLR), Support Vector Regression (SVR), Decision Tree Regression (DTR), Random Forest Regression (RFR), Gradient Boosting Regression(GBR), Lasso and Ridge Regression and Deep Learning Algorithm especially Long-short Term Memory (LSTM) using Google Colab Platform. From our analysis, LSTM has the least error approximation of 0.0040 loss at the 100th epoch and of all ML models, Gradient Boosting and RFR top high, when it comes to the Hot weather season – Gradient Boosting leads 2% than RFR and similarly for Cold weather, Autumn and monsoon climate –RFR has 1% higher accuracy than Gradient Boosting. This high accuracy model is deployed in a User Interface (UI) that will be more useful for real-time solar prediction, load operators for maintenance scheduling, stock commitment and load dispatch centers for engineers to decide on setting up solar panels, for household clients and future researchers.
Retrospective analysis of drug resistance characteristics and infection related risk factors of multidrug-resistant organisms (MDROs) isolated from the orthopedics department of a tertiary hospital
Authors: Yang Xiaowei , Guo Runsheng , Zhang Bi , Xie Banglin , Zhou Song , Zhang Bin , Lai Qi 
Published: September 2022

Abstract
Background: Patients infected with multidrug-resistant organisms (MDROs) are known to exhibit longer hospital stays and a significantly poorer prognosis. We performed a 6-year retrospective analysis of nosocomial infections reported in the orthopedics department of our institution, to gain valuable insights into antibiotic sensitivity and infectivity characteristics of MDROs, in order to deduce effective measures to control the occurrence of multidrug-resistant infections in clinical practice.
Methods: All relevant data, including basic patient information, cultivated bacterial strains, and antimicrobial resistance, was obtained from the Hospital Information Warehouse.
Results: A total of 1392 strains of pathogenic bacteria were isolated; 358 belonged to MDROs (detection rate=25.7%). All the isolated strains of MDROs were mostly from secretions (52.2%). The number of cases infected with MDROs were 144 (40.2%) and 129 (36.0%) in the trauma and spinal wards, respectively. MRSA showed high resistance to β lactam antibiotics, but was sensitive to quinolone antibiotics, linezolid and cotrimoxazole. ESBL-positive strains showed more sensitivity to carbapenem antibiotics (<10%). MDR nonfermenters showed high resistance to most antibiotics. Logistic multivariate analysis revealed age, open injury, and central nervous system injury as independent risk factors for multidrug resistant infections.
Conclusions: A high antibiotic resistance rate and an increasing prevalence of infections with MDROs was identified in the orthopedics department. Patients with open injury, central nervous system injury and those aged ≥60 years, were more prone to multidrug-resistant infections. Clinicians should pay more attention to such patients in order to actively prevent and control the occurrence of infections caused by MDROs.
The influence of commonly used non-surgical treatment modalities on control of intermittent exotropia: A meta-analysis of randomized clinical trials
Authors: Son Desheng , Qian Jing , chen Zhijun 
Published: September 2022

Abstract
Intermittent exotropia (IXT) is a relatively common childhood strabismus worldwide, non-surgical treatments are sometimes administered to prevent IXT from deteriorating, which has not been widely accepted by physicians. The objective of this study is to compare the effectiveness of commonly used non-surgical treatment modalities (overminus lens therapy and part-time occlusion therapy) and observation in the treatment of intermittent exotropia. An exhaustive search of the literature in Pubmed, EMBASE, Web of Science, and Cochrane Library databases was performed until July 2022. No language restrictions were used. The literature was rigorously screened according to eligibility criteria. Weighted mean differences (WMD) and 95% confidence intervals (CI) were calculated. A total of 7 articles with 1046 participants were included in this meta-analysis. Three studies compared the effects of OML and observation, three studies compared the effects of PTO and observation, and one study compared the effects of OML, PTO, and observation. Our pooled results showed that the commonly used non-surgical treatment modalities demonstrated superior outcomes compared with observation, with greater decreases in distance and near exodeviation control (OR, -0.51; 95% CI, -0.66 to -0.36, P < 0.001; OR, -0. 40; 95% CI, -0.54 to -0.25, P < 0.001). Patients who received the commonly used non-surgical treatment method had a greater decrease in the deviation at both distance and near (OR, -2.88; 95% CI, -3.75 to -2.01, P < 0.001; OR, -3.44; 95% CI, -5.34 to -1.55; P < 0.001). There was no statistical difference between the two groups in terms of post-treatment proximal stereopsis (OR=0.01, 95% CI: -0.04 to 0.05, P=0.83). Further analysis revealed that OML showed a better significant treatment effect than PTO. The present meta-analysis indicated that commonly used non-surgical treatment modalities (overminus lens therapy and part-time occlusion therapy) were effective in improving the control and decreasing exodeviation angle of intermittent exotropia, and overminus lens therapy was superior to part-time occlusion therapy.
Application of ML methods in identifying patients with asthma in primary care
Authors: Verma Jay , Natarajan Sukin , Khakshouri Sascha , Dhruva Bhuvana 
Published: September 2022

Abstract

Background:
Asthma is one of the most prevalent diseases, with approximately 5.4 million patients on prescribed medication in the UK. Poor asthma management is responsible for many preventable deaths in the UK, making the mortality rate the highest in Europe. Identifying asthma patients is time-consuming and requires detailed reviews of individual patients by GPs. In a previous study (awaiting publication), bespoke designed algorithms (Smart-Searches™) were used to identify patients who were not on the Quality Outcome Framework (QOF) asthma register but were likely to have asthma. GPs further reviewed these patients found by the searches to confirm their condition. This study aims to apply machine learning methods to real-world primary care electronic health records (EHRs) and compare their performance in identifying asthma patients with the previously used Smart-Searches™.
Methods:
This is a binary classification problem where patients are identified as asthmatic or non-asthmatic. Data from two practices used in this study comprised around 9000 patients, of whom around 600 were on the asthma register. A set of 40–45 features were extracted from the health records as inputs to the models. The models were trained and tested on datasets in several experiments. Both linear models such as Logistic Regression, Random Forest, Support Vector Model, Naïve Bayes, and deep learning models such as MLP and CNN were evaluated, and compared with the existing traditional methods.
Results:
ML models, on average, got a higher accuracy of about 70% compared to traditional methods at 54%. The Ensemble model obtained the highest accuracy at 77%, followed by MLP at 75%. In addition, the average positive predictive value for the ML methods was 82% compared to the search-based system at 54%. Finally, the Naïve Bayes model obtained the best positive predictive value at 100%.
Conclusions:
ML methods obtained high accuracy and positive predictive values, showing that the ML models could make better asthma identification predictions than the existing system. This also shows that the machine learning models could help clinicians identify more asthma patients in significantly less time while requiring less clinician input than the existing best methods leading to improved efficiency and better patient care.
Differential gene expression analysis under salinity stress in the selected turmeric (Curcuma longa L.) cultivars for curcuminoid biosynthesis.
Authors: SHANKAR BANDI ARPITHA , Yadav Manoj Kumar , Kumar Mukesh , Burman Vishakha 
Published: September 2022

Abstract
Background:Curcuminoids are the phenolic compounds found exclusively in turmeric. The presence of these curcuminoids is known to increase immunity and resistance against certain cancers and neurological disorders in humans along with protecting the turmeric plant cells against salinity stress.
Methods:In this experiment, we studied the expression levels of MAPK1 and DCS genes with respect to curcuminoid biosynthesis under salinity stress so that the impact of individual genes can be understood using semi- quantitative PCR.
Results:The expressions of the genes with respect to curcuminoid biosynthesis showed fluctuations in their band intensity values due to the curcuminoid production, which is initiated first in the leaves followed by the rhizomes. Not all the genes responsible for the curcuminoid biosynthesis show positive regulation under salt stress conditions may be due to the severity of the stress imposed on the cultivars.
Conclusions:In our findings, both the genes MAPK1 and DCS genes are down-regulated for curcuminoid biosynthesis compared to the controls in both the cultivars Vallabh Sharad and New Selection 1.
CT-based Radiomics Nomogram for Differentiation of Adrenal Hyperplasia from Lipid-poor Adenoma: An exploratory study
Authors: Yuan Hongtao , Kang Bing , Sun Kui , Qin Songnan , Ji Congshan , Wang Ximing 
Published: September 2022

Abstract
Background
To establish and verify a radiomics nomogram for differentiating isolated micronodular adrenal hyperplasia (iMAD) from lipid-poor adenoma (LPA) based on computed tomography (CT)-extracted radiomic features.
Methods
A total of 148 patients with iMAD or LPA were divided into three cohorts: a training cohort (n = 72; 37 iMAD and 35 LPA), a validation cohort (n = 36; 22 iMAD and 14 LPA), and an external validation cohort (n = 40; 20 iMAD and 20 LPA). Radiomics features were extracted from contrast-enhanced and non-contrast CT images. The least absolute shrinkage and selection operator (LASSO) method was applied to develop a triphasic radiomics model and unenhanced radiomics model using reproducible radiomics features. A clinical model was constructed using certain laboratory variables and CT findings. Radiomics nomogram was established by selected radiomics signature and clinical factors. Nomogram performance was assessed by calibration curve, the areas under receiver operating characteristic curves (AUC), and decision curve analysis (DCA).
Results
Eleven and eight extracted features were finally selected to construct an unenhanced radiomics model and a triphasic radiomics model, respectively. There was no significant difference in AUC between the two models in the external validation cohort (0.838 vs. 0.843, p = 0.949). The radiomics nomogram inclusive of the unenhanced model, maximum diameter, and aldosterone showed the AUC of 0.951, 0.938, and 0.893 for the training, validation, and external validation cohorts, respectively. The nomogram showed good calibration, and the DCA demonstrated the superiority of the nomogram compared with the clinical factors model alone in terms of clinical usefulness.
Conclusions
A radiomics nomogram based on unenhanced CT images and clinical variables showed favorable performance for distinguishing iMAD from LPA. In addition, an efficient unenhanced model can help avoid extra contrast-enhanced scanning and radiation risk.
The Prevalence of Ocular Demodex folliculorum in 2253 Young Males
Authors: Ye Qian , Yan Weiming , Wang Yunpeng , Chen Meizhu 
Published: September 2022

Abstract
Aim: To determine the prevalence and influencing factors of Demodex folliculorum (DF) in the eyelashes of healthy young males.
Methods: An epidemiological cross-sectional prevalence study was conducted. A total of 2253 healthy young males (aged 17-24 years) were studied for the presence of DF within eyelash follicles. The presence of DF was analyzed according to various factors.
Results: The total prevalence of DF was 20.73% in our study. Subjects with history of myopia correction surgery had a statistically significant increase in the positive rate of DF (P<0.001). The positive rate was higher in subjects with ocular symptoms than in those without symptoms (P<0.05). Factors such as the educational level, long-term residence, annual household income, sleep time, time of using electronic products, smoke and drinking habits, had no significant correlation with the DF positive rate (all P>0.05). According to the multivariate logistic regression analysis, the history of myopic correction surgery was the risk factors of DF infection (P<0.001). There was no correlation between ocular discomfort and DF infection (P>0.05).
Conclusions: The prevalence of DF in eyelash follicles in healthy young men was relatively high. The history of myopic correction surgery was an important risk factor for the infection.
Dynamics of Temporal Immune Responses in Nonhuman Primates and Humans Immunized with COVID-19 Vaccines
Authors: Khan Imran , Ravindran Resmi , Kang Harsharonjit , McReynolds Cindy , Sanghar Gursharan Kaur , Chang William , Ramasamy Santhamani , Kolloli Afsal , Kumar Ranjeet , Subbian Selvakumar , Hammock Bruce , O’Connor Dennis J Hartigan , Ikram Aamer , Haczku Angela 
Published: September 2022

Abstract
We assessed the humoral immune responses to a COVID-19 vaccine in a well-controlled rhesus macaque model in comparison to humans immunized with two mRNA vaccines over several months post-second dose. The plasma IgG levels against seven coronaviruses (including SARS-CoV-2) and antibody subtypes (IgG1-4 and IgM) against SARS-CoV-2 were evaluated using multiplex assays. The neutralization capacity of plasma antibodies against original SAR-CoV-2 isolate and nine variants was evaluated in vaccinated humans and non-human primates. Immunization of macaques and humans with SARS-CoV-2 vaccines induced a robust neutralizing antibody response. In non-SIV infected adult macaques immunized with an adenoviral vector expressing S-RBD (n = 7) or N protein (n = 3), elevated levels of IgG and neutralizing antibodies were detected 2 weeks post-second dose. Immune responses to the S-RBD vaccine in SIV-infected adult macaques (n = 2) were similar to the non-SIV-infected animals. Adult humans immunized with Pfizer (n = 35) or Moderna (n = 18) vaccines developed IgG and neutralizing antibodies at 4 weeks post-second dose. In both vaccine groups, IgG 1 was the predominant subtype, followed by IgG 3. The IgG levels, including total and IgG1,2,3 elicited by Moderna vaccine, were significantly higher than the corresponding levels elicited by the Pfizer vaccine at 4 weeks post-second dose. A significant correlation was observed between the plasma total IgG antibody levels and neutralization titers in both macaques and humans. Furthermore, broad-spectrum neutralization antibodies against several variants of SARS-CoV-2 were detected in the plasma of both macaques and humans after two vaccinations.
Parity Violation Energy Difference calculation of atropisomers
Authors: Vadivel Dhanalakshmi , Dondi Daniele 
Published: September 2022

Abstract
Enantiomers have a different energy due to the parity violation effects. Up to now, these effects are difficult to calculate and their final effect on the choice of one enantiomer in the homochirality issue is still a matter of debate. Nevertheless, many scientists support the role of this tiny energy difference in the triggering of homochirality. In this work, we studied the energy difference in atropisomers, a class of stereoisomers in which the chirality is given by the block of rotation around one bond. Atropisomers might have a low energy barrier for the interconversion and this is interesting for the equilibration of the two enantiomers and the choice of the most stable enantiomer. Moreover, structures might be extended like in the case of polymers or crystals having helical framework and thus giving an additive effect on the parity violation energy of the whole structure. The parity violation energy difference here is discussed with the correlation on the general structure of the final molecule giving a qualitative model to predict the sign of local contributions of atoms.
Does employer involvement in primary health care enhance return to work for patients with stress-related mental disorders? a cluster randomized controlled trial
Authors: Beno Anja , Bertilsson Monica , Holmgren Kristina , Glise Kristina , Pousette Anders , Segerfelt Karin , Björk Lisa 
Published: September 2022

Abstract
Background
Stress-related disorders have become a major challenge for society and are associated with rising levels of sick leave. The provision of support to facilitate the return to work (RTW) for this patient group is of great importance. The aim of the present study was to evaluate whether a new systematic procedure with collaboration between general practitioners (GPs), rehabilitation coordinators (RCs) and employers could reduce sick leave days for this patient group.
Method
Employed patients with stress-related diagnoses seeking care at primary health care centres (PHCCs) were included in either the intervention group (n = 54), following the systematic intervention procedure, or the control group (n = 58), receiving treatment as usual (TAU). The intervention included a) a training day for participant GPs and RCs, b) a standardised procedure for GPs and RCs to follow after training, c) the opportunity to receive clinical advice from specialist physicians in the research group. Outcome measures for RTW were sick leave days.
Results
The control group had significantly fewer net sick leave days at three months (p = 0.03) at six months (p = 0.00) and at 12-months follow-up (p = 0.01). At 24 months, this difference was no longer significant.
Conclusions
The PRIMA intervention, which applied a standardized procedure for employer involvement in the rehabilitation process for patients with stress-related disorders, actually increased time to RTW compared to TAU. However, at 24 months, the benefit of TAU could no longer be confirmed.
Assessing the Radioactivity Level of Seawater and Sand Samples from the Baltic Sea Region
Authors: Jukna Artūras , Grigaliūnaitė-Vonsevičienė Gražina 
Published: September 2022

Abstract

Current work reports on a novel method for determining radionuclide concentration and radioactivity in seawater by comparing the gamma-ray spectra of water-free samples of seawater and foreshore sand flooded by waves. By applying the proposed method, it is possible to save time and effort that are used to monitor the quality of seawater in the Baltic Sea with its characteristic sandy shores. Foreshore sand filters seawater trapping insoluble sediments together with radionuclides brought by waves. Radiation spectra of natural and artificial radionuclides in samples of seawater, foreshore sand, and sand taken on top of the dune (reference sample) in the Juodkrante area in Lithuania, were recorded by a gamma-ray spectrometer utilizing a NaI detector. The analysis of radiation spectra in the energy range of 30–1670 keV and the identification of radionuclides were performed using computer software. The richest collection and the highest concentration of radionuclides, including Na-22, Ar-41, Sc-46, Fe-59, Y-91, Zr-97, Nb-94, and Te-132, found in the foreshore sand confirm that the sand traps them from seawater carried by waves. Simultaneous analysis of both seawater and foreshore sand spectra is a way of accurate estimation of the radionuclide concentration at the time of seawater sampling and prior to that. Using a reference sample, the NaI detector, operating at room temperature, can be exploited to make a qualitative determination of the concentration and radioactivity of radionuclides in water-free samples.
Signaling Game for Research Fund Allocation in Thailand
Authors: Duangsong Thiti , Paoprasert Naraphorn , Witchakul Suwitchaporn , Jaijit Sasarose 
Published: September 2022

Abstract
This study proposed a signaling game for a research grant allocation situation. A funding agency and a researcher whose type was kept secret from the funding agency were the players in the game. The agency decided the grant amount to fund the researcher. The results show that a pooling equilibrium existed when the difference between a large and small fund was sufficiently large, and the expected costs of failing the large-fund project for both types were small, whereas the expected costs of failing the small-fund project for both types were large. When the difference between the effort of putting up a project proposal between a large-fund project and a small-fund project was relatively small, pooling equilibrium occurred. Nevertheless, a separating equilibrium occurred in which the good researcher requested a large fund and the bad researcher requested a small fund when the expected cost of failing the large-fund project for the bad researcher was sufficiently large, whereas the expected cost of failing the large-fund project for the good researcher was sufficiently small. On the basis of the research impact assessment of previous studies, a case study was examined. According to the results, we were still in a pooling equilibrium. However, if some model parameters changed (e.g., when the estimated cost of a penalty to the bad researcher was increased), a separating equilibrium began to show.