bluuebunny/crossref_metadata_2025_split huggingface dataset:
Використання методів аналізу ризику стосовно терористичних загроз на об’єктах критичної інфраструктури, що охороняються
Authors: Divizinyuk Mykhailo , Mirnenko Volodymyr , Polishchuk Vasyl 
Published: September 2022

Мета роботи: на основі дослідження трансформації поняття ризику (стосовно об’єкту критичної інфраструктури, що охороняється), характеристик терористичного акту та терористичних загроз, розглянути методи аналізу ризику стосовно терористичних загроз на об’єктах критичної інфраструктури, що охороняються.
Дизайн/Метод/Підхід дослідження: методи теорії ймовірностей та математичної статистики, теорії нечітких множин та інтервальної математики, теорії ризиків та моделювання динамічних процесів.
Результати дослідження: показано, що стосовно охоронюваного об’єкта критичної інфраструктури ризик – це міра кількісного багатокомпонентного виміру небезпеки з включенням величини шкоди від впливу загроз, що виявляються у формі технічних та технологічних, природних та екологічних, економічних та психологічних, соціальних та інших інцидентів. Вони проявляються як збої та відмови, пригоди та аварії, вибухи та пожежі, призводять до зупинки або обмеження функціонування цих об’єктів. Показано, що типовий сценарій теракту складається з десяти етапів, а терористичні загрози на об’єктах критичної інфраструктури, що охороняються, це можливі суспільно небезпечні наслідки зловмисних дій, які призводять до зупинення або обмеження функціонування цих об’єктів. Зроблено висновок, що для аналізу ризику стосовно терористичних загроз на об’єктах критичної інфраструктури, дефіцит статистичних даних при оцінці різних загроз забезпечив домінування імовірнісно-евристичних методів, що ґрунтуються на використанні суб’єктивних ймовірностей, одержуваних за допомогою експертного оцінювання.
Теоретична цінність дослідження: полягає в тому, що дефіцит статистичних даних при оцінці різних загроз на об’єктах критичної інфраструктури, що охороняються, забезпечує домінування імовірнісно-евристичних методів, що ґрунтуються на використанні суб’єктивних ймовірностей, одержуваних за допомогою експертного оцінювання.
Тип статті: науково-практичний.
Management of technological projects and economic profitability in the financial risk of banking institutions
Authors: Márquez Espinoza Armando , Pineda Domínguez Daniel , Torres Márquez María Amalia Clara 
Published: September 2022

This article analyzes the relationship between technology project management (GPT and economic profitability (RE) for the areas of financial risks with the aim of presenting a flexible model between both variables derived from performance indices and cognitive skills for the area of financial risks of a Mexican banking institution. This is through a quantitative method supported by a predictive econometric model of data obtained from 313 technological projects. The results show that the RE depends on the behavior of the dimensions of the GPT; considering the information taken for empirical verification based on the resulting sample and other data derived from the qualitative indicators.
Uso de um aplicativo para o acesso às políticas de assistência estudantil em um Instituto Federal do sul do Brasil
Authors: Oliveira Jaqueline Dutra de , Coutinho Renato Xavier 
Published: September 2022

Esse artigo tem como objetivo, verificar a efetividade do produto educacional, o aplicativo “CAE na rede”, junto algumas turmas do ensino médio integrado (EMI) de um Instituto Federal. O aplicativo tem como propósito centralizar alguns documentos referentes às políticas de assistência estudantil (PAE) desenvolvidas na instituição para facilitar o acesso a essas informações. Trata-se de um estudo quanti-qualitativo, para coleta de dados foi utilizado como instrumento um questionário desenvolvido para esse estudo. A análise dos dados foi desenvolvida por meio da estatística descritiva, organizada em aspectos positivos e negativos. Com o estudo, identificou-se que para os alunos o aplicativo “CAE na rede” está organizado, usariam com frequência e indicariam seu uso para colegas e nas reuniões de acolhimento e proporcionou maior conhecimento sobre as políticas desenvolvidas na instituição. E afirmam que essas políticas são importantes para sua permanência na instituição. Sobre a efetividade do aplicativo, os estudantes indicam que facilita o acesso aos documentos da assistência estudantil, diminuindo o tempo de pesquisa. Diante dos aspectos estudados, conclui-se que o aplicativo cumpriu seu objetivo de facilitar o acesso aos documentos das PAE, tornando a pesquisa mais prática e intuitiva, podendo assim, ser utilizado como uma ferramenta institucional na busca pela permanência dos estudantes, e no reconhecimento dessas ações como estratégias que visam a democratização do ensino e a redução das desigualdades sociais.
Alterações anatomopatológicas e parâmetros bioquímicos séricos e urinários em cães com diagnóstico de Dioctophyme renale
Authors: Valle Bruna dos Santos , Caye Pamela , Sapin Carolina da Fonseca , Silva Luisa Mariano Cerqueira da , Miranda Júlia Vargas , Boff Gustavo Antonio , Corrêa Luísa Grecco , Rappeti Josaine Cristina da Silva , Fernandes Cristina Geverh , Grecco Fabiane Borelli 
Published: September 2022

Animais acometidos por Dioctophyme renale geralmente são assintomáticos e o diagnóstico definitivo é o exame de imagem e o anatomopatológico. Desta forma, este estudo tem como objetivo descrever os parâmetros bioquímicos de sangue e urina e exames anatomopatológicos de 15 cães diagnosticados com D. renale na região de Pelotas-Rio Grande do Sul-RS. Foram obtidos dados de anamnese e exames laboratoriais sorológicos e urinários de protocolos de atendimento de animais no Hospital de Clínicas Veterinárias da Universidade Federal de Pelotas-UFPel, e análises anatomopatológicas pelo Serviço de oncologia SOVET/UFPEL. Foram observadas alterações macroscópicas em todas as amostras, sendo a atrofia do parênquima renal e espessamento da cápsula as mais frequentes. O exame histopatológico revelou substituição do tecido renal por fibrose, glomeruloesclerose e eventualmente presença de ovos do parasito. Em relação aos parâmetros sanguíneos e urinários, apenas um dos animais apresentou alteração nos valores de referência de ureia sérica e todos apresentaram creatinina dentro dos parâmetros considerados normais. Na urinálise havia presença de proteínas, sangue oculto, cilindros granulares, cristais e ovos do parasito. Os testes estatísticos mostraram correlação entre a evolução e grau das lesões renais com parâmetros alterados, porém mesmo em cães que apresentavam lesões de insuficiência renal aguda (IRA), haviam lesões concomitantes de insuficiência renal crônica (IRC). Como conclusão dos dados obtidos, parâmetros séricos e urinários isoladamente não refletem o real comprometimento do rim afetado, mas associados ao grau de lesão renal são aliados para um melhor estadiamento dos animais acometidos.
Application and mechanism of anti-VEGF drugs in age-related macular degeneration
Authors: Song Dawei , Liu Ping , Shang Kai , Ma YiBin 
Published: September 2022

Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly. The incidence rate increases with age in people over 50 years of age. With the advent of China’s aging society, the number of patients is increasing year by year. Although researchers have done a lot of basic research and clinical research on the pathogenesis and treatment of AMD in recent years, the pathogenesis of AMD is still controversialdue to the complexity of the disease itself. AMD is the primary cause of blindness in the elderly over 50 years old. It is characterized by the formation of choroidal neovascularization (CNV) and the over secretion of vascular endothelial growth factor (VEGF) as its main mechanism, which can eventually lead to vision loss or blindness. The occurrence and development of AMD is an extremely complex process, in which a large number of regulatory factors and cytokines are involved. Most of the existing treatments are for its concomitant CNV. Targeted VEGF drugs for neovascularization, such as Lucentis and Aflibercept, are the first-line drugs for AMD. Their application has greatly reduced the blinding rate of patients. However, there are still some patients who have no response to treatment or cannot maintain their vision after long-term treatment. Frequent injection also increases the risk of complications and economic burden. In order to further improve the quality of life and long-term prognosis of AMD patients, a variety of new treatmentshave been or will be applied in clinic, including combined treatment with the same or different targets to improve the curative effect, change or simplify the mode of medication, inhibit VEGF receptor tyrosine protein kinase and so on. This article provides a brief review of the research progress of anti-VEGF drugs and their mechanisms for the treatment of AMD, it is expected to provide a better treatment plan for AMD treatment.
Production of ultracold polyatomic molecules with strong polarity by laser cooling: A detailed theoretical study on CaNC and SrNC
Authors: Xia Wensha , Cao Jianwei , Lu Qing , Bian Wensheng 
Published: September 2022

Laser cooling molecules to the ultracold regime is the prerequisite for many novel science and technologies. It is desirable to take advantage of theoretical approaches to explore polyatomic molecular candidates, which are capable of being cooled to the ultracold regime. In this work, we explore two polyatomic candidates, CaNC and SrNC, which are suitable for laser cooling. These molecules possess impressively large permanent dipole moments (∼6 Debye), which is preferred for applications using an external electric field. High-level ab initio calculations are carried out to reveal electronic structures of these molecules, and the calculated spectroscopic constants agree very well with the available experimental data. For each molecule, the Franck-Condon factor matrix is calculated and shows a diagonal distribution. The radiative lifetimes for CaNC and SrNC are estimated to be 15.5 and 15.8 ns, respectively. Based upon the features of various electronic states and by choosing suitable spin-orbit states, we construct two feasible laser cooling schemes for the two molecules, each of which allows scattering nearly 10000 photons for direct laser cooling. These indicate that CaNC and SrNC are excellent ultracold polyatomic candidates with strong polarity.
Prevalence of latent tuberculosis infection and incidence of active tuberculosis in school close contacts in Shanghai, China: Baseline and follow-up results of a prospective cohort study
Authors: Xiao Xiao , Chen Jing , Jiang Yue , Li Peng , Li Jin , Lu Liping , Zhao Yameng , Tang Lihong , Zhang Tianyuan , Wu Zheyuan , Rao Lixin , Yuan Zheng’an , Pan Qichao , Shen Xin 
Published: September 2022

BackgroundThe management of latent tuberculosis infection (LTBI) is a key action for the realization of the “End tuberculosis (TB) Strategy” worldwide, and it is important to identify priority populations. In this prospective cohort study, we evaluated the prevalence of LTBI and incidence of active TB among close contacts and explored the suitable TB control strategy in schools.MethodsWe designed a cohort with 2 years of follow-up, recruiting freshman/sophomore TB patients’ close contacts from three administrative districts in Shanghai. These were chosen based on different levels of TB incidence reported in 2019. Questionnaires were included and all participants received both tuberculin skin test (TST) and QuantiFERON-TB Gold (QFT) at baseline, then tracked the outcomes of them during the follow-up period.ResultsThe prevalence of LTBI was 4.8% by QFT. Univariate analysis showed that the risk of LTBI was higher in those contacting bacteriologically confirmed patients or did not have BCG scars, including smokers. The risk increased with poor lighting and ventilation conditions at contact sites. Multivariate analysis showed that those contacting with bacteriologically confirmed patients (OR=4.180; 95%CI, 1.164-15.011) or who did not have BCG scars (OR=5.054; 95%CI, 2.278-11.214) had a higher risk of being LTBI, as did the current smokers (OR=3.916; 95%CI, 1.508-10.168) and those who had stopped smoking (OR=7.491; 95%CI, 2.222-25.249). During the 2-year follow-up period, three clinically diagnosed cases of TB were recorded, the 2-year cumulative incidence was 0.4% (95%CI 0.1-1.2), the median duration for TB occurrence was 1 year, the incidence rate of active TB was 2.0 per 1000 person-years with a total of 1497.3 observation person-years. For those LTBI, no one initiated preventive treatment, in the QFT (+) cohort, 1 TB case was observed, 71 person-years with an incidence rate of 14.1 14.1 (95%CI 2.5-75.6) per 1000 person-years, in the TST (+++) cohort, 2 TB cases were observed 91.5 person-years with an incidence rate of 21.9 (95%CI 6.0-76.3) per 1000 person-years.ConclusionsThe results suggest that school close contacts are one of the key populations for LTBI management. Measures should be taken to further reduce the prevalence of LTBI and the incidence of active TB among them.
Quantifying the Excess Risk of Adverse COVID-19 Outcomes in Unvaccinated Individuals With Diabetes Mellitus, Hypertension, Ischaemic Heart Disease or Myocardial Injury: A Meta-Analysis
Authors: Ng Sher May , Pan Jiliu , Mouyis Kyriacos , Kondapally Seshasai Sreenivasa Rao , Kapil Vikas , Rice Kenneth M. , Gupta Ajay K. 
Published: September 2022

BackgroundMore than 80% of individuals in low and middle-income countries (LMICs) are unvaccinated against coronavirus disease 2019 (COVID-19). In contrast, the greatest burden of cardiovascular disease is seen in LMIC populations. Hypertension (HTN), diabetes mellitus (DM), ischaemic heart disease (IHD) and myocardial injury have been variably associated with adverse COVID-19 outcomes. A systematic comparison of their impact on specific COVID-19 outcomes is lacking. We quantified the impact of DM, HTN, IHD and myocardial injury on six adverse COVID-19 outcomes: death, acute respiratory distress syndrome (ARDS), invasive mechanical ventilation (IMV), admission to intensive care (ITUadm), acute kidney injury (AKI) and severe COVID-19 disease (SCov), in an unvaccinated population.MethodologyWe included studies published between 1st December 2019 and 16th July 2020 with extractable data on patients ≥18 years of age with suspected or confirmed SARS-CoV-2 infection. Odds ratios (OR) for the association between DM, HTN, IHD and myocardial injury with each of six COVID-19 outcomes were measured.ResultsWe included 110 studies comprising 48,809 COVID-19 patients. Myocardial injury had the strongest association for all six adverse COVID-19 outcomes [death: OR 8.85 95% CI (8.08–9.68), ARDS: 5.70 (4.48–7.24), IMV: 3.42 (2.92–4.01), ITUadm: 4.85 (3.94–6.05), AKI: 10.49 (6.55–16.78), SCov: 5.10 (4.26–6.05)]. HTN and DM were also significantly associated with death, ARDS, ITUadm, AKI and SCov. There was substantial heterogeneity in the results, partly explained by differences in age, gender, geographical region and recruitment period.ConclusionCOVID-19 patients with myocardial injury are at substantially greater risk of death, severe disease and other adverse outcomes. Weaker, yet significant associations are present in patients with HTN, DM and IHD. Quantifying these associations is important for risk stratification, resource allocation and urgency in vaccinating these populations.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/, registration no: CRD42020201435 and CRD42020201443.
Development and validation of prediction models for hypertension risks: A cross-sectional study based on 4,287,407 participants
Authors: Ji Weidong , Zhang Yushan , Cheng Yinlin , Wang Yushan , Zhou Yi 
Published: September 2022

ObjectiveTo develop an optimal screening model to identify the individuals with a high risk of hypertension in China by comparing tree-based machine learning models, such as classification and regression tree, random forest, adaboost with a decision tree, extreme gradient boosting decision tree, and other machine learning models like an artificial neural network, naive Bayes, and traditional logistic regression models.MethodsA total of 4,287,407 adults participating in the national physical examination were included in the study. Features were selected using the least absolute shrinkage and selection operator regression. The Borderline synthetic minority over-sampling technique was used for data balance. Non-laboratory and semi-laboratory analyses were carried out in combination with the selected features. The tree-based machine learning models, other machine learning models, and traditional logistic regression models were constructed to identify individuals with hypertension, respectively. Top features selected using the best algorithm and the corresponding variable importance score were visualized.ResultsA total of 24 variables were finally included for analyses after the least absolute shrinkage and selection operator regression model. The sample size of hypertensive patients in the training set was expanded from 689,025 to 2,312,160 using the borderline synthetic minority over-sampling technique algorithm. The extreme gradient boosting decision tree algorithm showed the best results (area under the receiver operating characteristic curve of non-laboratory: 0.893 and area under the receiver operating characteristic curve of semi-laboratory: 0.894). This study found that age, systolic blood pressure, waist circumference, diastolic blood pressure, albumin, drinking frequency, electrocardiogram, ethnicity (uyghur, hui, and other), body mass index, sex (female), exercise frequency, diabetes mellitus, and total bilirubin are important factors reflecting hypertension. Besides, some algorithms included in the semi-laboratory analyses showed less improvement in the predictive performance compared to the non-laboratory analyses.ConclusionUsing multiple methods, a more significant prediction model can be built, which discovers risk factors and provides new insights into the prediction and prevention of hypertension.
Multiple experimental studies of pore structure and mineral grain sizes of the Woodford shale in southern Oklahoma, USA
Authors: Zhao Chen , Hu Qinhong , Wang Qiming , Ilavsky Jan , Wang Min , Zhang Xiaobei , Yan Jianping 
Published: September 2022

Pore structure study is an important part of unconventional shale reservoir characterization, since the pore system provides the primary petroleum storage space and fluid flow pathways. Previous studies have suggested that the pore structure is related to the total organic carbon (TOC) content, mineral compositions, and the maturity of the organic matter (OM). However, few studies have focused on the mineral grains, the primary grains being deposited but before cementation, which are the building blocks of shale. Eight Woodford Shale outcrop samples from southern Oklahoma were chosen to study the effects of mineral grain size on the pore structure characterization, using multiple and complementary experimental approaches, including laser diffraction, mineralogy, TOC, pyrolysis, liquid immersion porosimetry, mercury intrusion porosimetry, gas physisorption, (ultra) small angle X-ray scattering, scanning electron microscopy, and spontaneous imbibition. The results from different experiments of eight samples show that the Woodford Shale has the mean mineral grain diameters at 3–6 μm, a wide range of porosity at 3–40% and pore diameters at 50–1,000 nm, and various pore connectivity. Grain size variation was probably caused by the sea-level fluctuation during its deposition, which affect the porosity, pore size distribution, and pore connectivity. With decreasing mineral grain sizes, the porosity tends to increase while the pore connectivity worsens. The results also indicate that OM and carbonates in this low-maturity Woodford Shale could block the pores and decrease the porosity. Coupling with the grain size analyses, the control of depositional environment on grain sizes and subsequent effects on pore structure is identified. The pore structure characteristics over a wide pore-diameter range provided by multiple experiments could improve the understanding of storage space and fluid flow in the Woodford Shale to further increase its petroleum production.
Impact of radiative forcing of spatially varying CO2 concentrations on net primary production
Authors: Peng Jing , Dan Li , Tang Xiba , Yang Fuqiang 
Published: September 2022

The radiative forcing of spatially varying carbon dioxide (CO2) concentrations has modified the climate by altering surface energy, the water budget, and carbon cycling. Over the past several decades, due to anthropogenic emissions, atmospheric CO2 concentrations in the whole terrestrial ecosystem have become greater than the global mean. The relationship between climatic variables and net primary production (NPP) can be regulated by the radiative forcing of this spatial variation. The present results show that owing to the radiative forcing of spatially varying CO2 concentrations, NPP has reduced globally by −0.6 Pg C yr−1. Region 2, with increased CO2 and decreased NPP, shows the greatest reductions, by −0.7 Pg C yr−1. Variations of both NPP and CO2 concentrations are distributed asymmetrically. As human activities are mainly located in the Northern Hemisphere, increased CO2 has mainly manifested in these regions. Especially in region 2, with increased CO2 and decreased NPP, increasing downward longwave radiation has heated the ground surface by 2.2 W m−2 and raised surface temperatures by 0.23°C. At the same time, due to the radiative forcing of spatial variations in CO2 concentrations, local dependence of NPP on soil moisture has increased due to enhanced temperature and evapotranspiration coupling, which may improve negative NPP anomalies locally, especially in region 2. With continued increasing CO2 concentrations, its spatial variation due to radiative forcing is likely to amplify warming and have a negative impact on NPP in the terrestrial ecosystem.
Experiment with the dynamical–statistical–analog ensemble forecast model for landfalling typhoon gale over South China
Authors: Li Lifang , Chen Yuxu , Ren Fumin , Liu Chunxia , Ma Yunqi , Wan Qilin 
Published: September 2022

In this study, an experiment based on the Dynamical-Statistical-Analog Ensemble Forecast model for Landfalling Typhoon Gale (DSAEF_LTG model) was conducted to predict tropical cyclone (TC)-induced potential maximum gales in South China for the first time. A total of 21 TCs with maximum gales greater than or equal to 17.2 m/s (at least one station) during 2011–2018 were selected for this experiment. Among them, 16 TCs in 2011–2015 were selected as the training samples aimed at identifying the best forecast scheme, while 5 TCs in 2016–2018 were selected as the independent samples to verify the best forecast scheme. Finally, the forecast results were compared with four numerical weather prediction (NWP) models (i.e., CMA, ECMWF, JMA and NCEP) based on four forecasting skill scores (Threat Score, False Alarm Ratio, Missing Ratio and Bias Score) at thresholds above Beaufort Scale 7 and 10, and two more indicators (Mean Absolute Error and pearson correlation coefficient). The results revealed encouraging forecasting ability in South China for the DSAEF_LTG model. In general, the DSAEF_LTG model showed higher forecasting skill than the NWP models above the critical thresholds. While the DSAEF_LTG model was prone to false alarms, the NWP models were prone to missing alarms, especially for an intense scale (≥Beaufort Scale 10). In addition, the DSAEF_LTG model also performed best with the smallest forecasting error. Furthermore, the DSAEF_LTG model had distinct advantages in predicting target TCs with typical tracks and widespread gales, both in terms of the wind field pattern and the magnitude of central wind speeds. However, for sideswiping TCs with small-scale gales, the DSAEF_LTG model tended to over-predict and held no advantage over the NWP models, which could perhaps be improved by introducing more reasonable ensemble forecast schemes in further research.