bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-DRR NGOs coping strategies for livelihood development in the coastal communities of Bangladesh: a Case Study
Authors: Seddiky Assraf , Seddiky Assraf , Giggins Helen , Gajendran Thayaparan 
Published: July 2021

Abstract
This study aims to assess the effectiveness of non-DRR NGOs’ programs focusing on their contribution to the uplift livelihood of the disaster-affected coastal communities. Researchers conducted a field study in Satkhira, the most disaster-prone coastal district of Bangladesh, and interviewed 45 respondents, including NGO officials, local government bodies, and community beneficiaries, applying purposive sampling. For analyzing data, Researchers used thematic analysis methods with NVivo software's assistance. Study findings reveal that NGOs’ community-based awareness and advocacy, mobilization of local resources, and primary healthcare programs contributed to enhancing community livelihood by promoting their attitudes and capacities to cope with disasters. However, their microfinance and infrastructure-related programs reinforced community vulnerability and exposure to disaster by increasing poverty, exclusion, and disparities among them. In conclusion, the study signifies the value of integrating sustainable infrastructure, environmental impact assessment on health and agriculture for promoting effective livelihood strategies in coastal communities.
Intelligent IDS: Venus Fly-trap Optimization with Honeypot Approach for Intrusion Detection and Prevention
Authors: Chaithanya Movva Sai , Nikudiya Suresh , Basanaik Varsha S , Reddy Damodar , Bhukya Hanumanthu 
Published: July 2021

Abstract
Intrusion Detection Systems and Intrusion Prevention Systems are used to detect and prevent attacks/malware from entering the network/system. Honeypot is a type of Intrusion Detection System which is used to find the intruder, study the intruder and prevent the intruder to access the original system. It is necessary to build a strong honeypot because if it is compromised, the original system can be easily targeted by the attacker. To overcome such challenges an efficient honeypot is needed that can shut the attacker after extracting his attack technique and tools. In this paper, a Venus fly-trap optimization algorithm has been used for implementing the honeypot system along with Intrusion Detection System. Venus plants are a type of carnivorous plants that catch their prey intelligently. By adopting this feature we make an effective honeypot system that will intelligently interact with the attacker.

A new fitness function has been proposed to identify size of the attacker. The effectiveness of the proposed fitness function has been evaluated by comparing it with state of the art. For comparison, remote-to-local attacks, probing attacks and DOS attacks are performed on both proposed and existing models. The proposed model is significant to catch/block all the intruders which were caught by the art and also the proposed model reduces the time of interaction between the attacker and honeypot system thereby giving minimum information to the attacker.
How Do Natural Gas, Oil, and Coal Consumption Contribute to Environmental Degradation? An Empirical Investigation in Russia
Authors: Kanat Orazaliyev , Yan Zhijun , Asghar Muhammad Mansoor , Ahmed Zahoor , Mahmood Haider , Kirikkaleli Dervis , Murshed Muntasir 
Published: July 2021

Abstract
Environmental degradation sourced by conventional energy sources is not only a major factor behind climate change but also poses an adverse impact on human health. Undoubtedly, fossil fuels are major drivers of economic growth; however, their detrimental environmental impacts are of global scope, affecting the inhabitants of the whole world. In the literature, there is no comprehensive empirical evidence on the linkage between different energy sources and CO2 emissions in Russia which is among the top five CO2 emitting nations. Thus, this paper aims to quantify the relationships between oil consumption, natural gas consumption, coal consumption, and CO2 emission controlling economic growth in Russia. The findings indicate that CO2 emissions in Russia are cointegrated with oil, gas, coal, and economic growth. The long-run outcomes unfold that Russian economic growth is not directly harmful to environmental quality; however, the consumption of oil, gas, and coal upsurge the level of CO2 emissions. In addition, we conducted Granger causality tests for causal interaction analysis. The findings on the Russian data confirm the existence of both long and short-term causal connections with the country’s economic growth, disaggregated fossil fuel consumption, and CO2 emissions. In conclusion, we directed several policy recommendations to address the challenges and threats posed by energy-related emissions without adversely impacting economic growth in Russia. These policies could also be advantageous to other countries, especially those with close Russian links.
Convection-permitting Modeling Strategies for Simulating Extreme Rainfall Events Over Southeastern South America
Authors: Feijoó Martín , Solman Silvina 
Published: July 2021

Abstract
A set of six convection-permitting (CP) domain configurations were implemented to perform 72-hour long simulations of three extreme precipitation events over Southeastern South America (SESA). The goal of the study is to determine the most adequate configuration for reproducing not only the rainfall evolution and intensity, but also the synoptic triggering mechanisms that led to these extreme events, taking into account the trade-off between model performance and computational cost. This study assesses the impact of 1) the horizontal resolution in the CP domain, 2) the horizontal resolution of the driver domain, 3) the size of both CP and driver domains and 4) the nesting strategy (one-step versus two-step nesting). Each simulation was performed with the Weather Research and Forecasting model driven by the ERA-Interim reanalysis. For each event and domain configuration, a 6-member physics ensemble is built, making a total of 36 simulations for each event. No significant differences were found between the 4 km and 2.4 km CP ensembles. Increasing the horizontal resolution of the driver domain from 20 km to 12 km introduced only subtle differences. Increasing the size of the CP domain improved significantly the model performance, mainly because of better resolved topography and, hence, better resolved synoptic environment. The results in this study reveal that the one-step nesting CP ensemble at 4 km horizontal resolution covering an area of 21°x29° (lat-lon) arises as the optimal domain configuration to simulate extreme precipitation events over SESA.
Transcriptome wide association study of coronary artery disease identifies novel susceptibility genes
Authors: Schunkert Heribert , Li Ling , Chen Zhifen , Scheidt Moritz , Steiner Andrea , Güldener Ulrich , Koplev Simon , Ma Angela , Hao Ke , Pan Calvin , Lusis Aldons , Pang Shichao , Kessler Thorsten , Ermel Raili , Sukhavasi Katyayani , Ruusalepp Arno , Gagneur Julien , Erdmann Jeanette , Kovacic Jason , Bjorkegren Johan 
Published: July 2021

Abstract
Transcriptome-wide association studies (TWAS) explore genetic variants affecting gene expression for association with a trait. Here we studied coronary artery disease (CAD) using this approach by first determining genotype-regulated expression levels in nine CAD relevant tissues by EpiXcan in two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these data we next imputed gene expression in respective nine tissues from individual level genotype data on 37,997 CAD cases and 42,854 controls for a subsequent gene-trait association analysis. Transcriptome-wide significant association (P < 3.85e-6) was observed for 114 genes, which by genetic means were differentially expressed predominately in arterial, liver, and fat tissues. Of these, 96 resided within previously identified GWAS risk loci and 18 were novel (CAND1, EGFLAM, EZR, FAM114A1, FOCAD, GAS8, HOMER3, KPTN, MGP, NLRC4, RGS19, SDCCAG3, STX4, TSPAN11, TXNRD3, UFL1, WASF1, and WWP2). Gene set analyses showed that TWAS genes were strongly enriched in CAD-related pathways and risk traits. Associations with CAD or related traits were also observed for damaging mutations in 67 of these TWAS genes (11 novel) in whole-exome sequencing data of UK Biobank. Association studies in human genotype data of UK Biobank and expression-trait association statistics of atherosclerosis mouse models suggested that newly identified genes predominantly affect lipid metabolism, a classic risk factor for CAD. Finally, CRISPR/Cas9-based gene knockdown of RGS19 and KPTN in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Taken together, our TWAS approach was able to i) prioritize genes at known GWAS risk loci and ii) identify novel genes which are associated with CAD.
The Prevalence and Characters of Pressure Injuries in Hospital: A Hospital Study in Southeast China
Authors: Xu Jie , Deng Xiaofang , Sun Caixia , Pan Xiaoyun 
Published: July 2021

Abstract
Background and objective:

Hospital-acquired pressure injuries (HAPIs) carry many adverse consequences (such as pain, wound odors, long lengths of hospital stay), and are a concern internationally. The aim of this study was to describe the incidence, clinical and epidemiological features of HAPI in a tertiary hospital.
Methods

A retrospective, qualitative study was conducted from 2017 to 2018. A questionnaire was designed around the existing literature about HAPI, including general information, Braden Scale scores (on admission, the moment that patients developed HAPI, and discharge), and the assessment of HAPI.
Results

419 patients had HAPI, representing an incidence of 0.12%. On average, patients developed HAPI after 12 days. The intensive care unit (ICU; 79,18.9%) saw the largest number of patients with HAPI. HAPIs were most commonly at Stage 2 (71.4%) and of a sacral location (42.3%). Braden Scale scores at first development of HAPI were lower than those on admission or discharge (with a low score signifying high risk).
Conclusion

The incidence of HAPI in a tertiary hospital was lower than at other hospitals. Braden Scale scores predicted the highest HAPI risk occurring at the point where HAPI were first developed.
A Retrospective Study of the Factors Associated With Deterioration Severity of COVID-19 Illness at a Tertiary Hospital in Saudi Arabia
Authors: AlJabr Mohammad , AlDossary Areej , Alkanani Kanan , Zahrani Turky Al , Almulhim Sofian , Kheir Hatim , AlAbdulkader Assim , Mushcab Hayat , Alreshidi Yaser , Albalawi Nouf , Alabdullatif Wedyan , Almarzooq Abrar , Qahtani Saeed Al 
Published: July 2021

Abstract
Background: COVID-19 has rapidly progressed to a pandemic causing a severe burden on healthcare systems worldwide. It has proven to be a serious threat to certain populations such as elderly and chronically ill people. In this study we aim to determine risk factors contributing and affecting COVID-19 severity and deterioration during the course of illness. Methods: This is a retrospective cohort study for all hospitalized patients who were diagnosed with COVID-19 from March to July 2020.Results: A total of 639 patients were included in this study. The majority were Saudi patients (87.3%). 465 (76%) were symptomatic with abnormal x-ray imaging diagnosis (56.2%). Predetermined clinical risk factors were obesity (46.3%), hypertension (42.3%), diabetes mellitus (41.8%), dyslipidemia (39%), Ischemic heart disease (13.2%), chronic lung disease (11%), chronic kidney disease (10.3%), cancer (7.9%), congestive heart failure (6.1%), and immunocompromised patients (4.6%). It was also found that chest x-ray finding upon diagnosis, and presentation of symptoms had a significant impact on the pattern of deterioration.Conclusion: This study found that elderly and chronically ill patients are at higher risk for more severe COVID-19 infection and risk of deterioration, hospitalization, intensive care unit admission, and probably death when compared to younger and healthier patients.
Bacillus Thuringiensis Predominated in the Zombie Fungus Ophiocordyceps Unilateralis S. L.-Infected Ant Cadavers and Investigation of its Biological Properties
Authors: Tu Kai-Wen , Chiu Ming-Chung , Lin Wei-Jiun , Hsueh Yen-Ping , Lin Chung-Chi , Chou Jui-Yu 
Published: July 2021

Abstract
Animal hosts infected and killed by parasitoid fungi become a nutrient-rich cadaver for saprophytes. Bacteria adapted to colonization of parasitoid fungi can be selected and can predominate in the cadaver, actions that consequently impact the fitness of the parasitoid fungi. In Taiwan, the zombie fungus, Ophiocordyceps unilateralis sensu lato (Clavicipitaceae: Hypocreales), was found to parasitize eight ant species, with preference for a principal host, Polyrhachis moesta. In this study, ant cadavers grew a fungal stroma that was predominated by Bacillus thuringiensis. The bacterial diversity in the principal ant host was found to be lower than the bacterial diversity in alternative hosts, a situation that might enhance the impact of B. thuringiensis on the sympatric fungus. The B. thuringiensis isolates from fungal stroma displayed higher resistance to a specific naphthoquinone (plumbagin) than B. thuringiensis from the environment. Naphthoquinones are known to be produced by O. unilateralis s. l., and hence the resistance displayed by B. thuringiensis isolates to these compounds suggests an advantage to B. thuringiensis to grow in the ant cadaver. Bacteria proliferating in the ant cadaver inevitably compete for resources with the fungus. However, the B. thuringiensis isolates displayed in vitro capabilities of hemolysis, production of hydrolytic enzymes, and antagonistic effects to co-cultured nematodes and entomopathogenic fungi. Thus, co-infection with B. thuringiensis offers potential benefits to the zombie fungus in killing the host under favorable conditions for reproduction, digesting the host tissue, and protecting the cadaver from being taken over by other consumers. With these potential benefits, B. thuringiensis is not entirely a competitor but could also be a synergist in O. unilateralis s. l. infections under certain conditions.
The Lost Productivity Cost of Absenteeism Due to COVID-19 in Health Care Workers in Iran
Authors: Faramarzi Ahmad , Javan-Noughabi Javad , Tabatabaee Seyed Saeed , Najafpoor Ali Asghar , Rezapour Aziz 
Published: July 2021

Abstract
Background: Human resources management plays an important role in social development and economic growth. Absence from work due to health problems can make obstacles to the growth of economy. This study conducted aimed to evaluate the absenteeism in healthcare workers during the COVID-19 pandemic.Methods: This cross-sectional study calculated the lost productivity cost of absenteeism among patients with COVID-19 between February 19, 2020, and September 21, 2020. The absenteeism costs were calculated using the human capital approach. Finally, we applied the linear regression to assess the impact of variables on the lost productivity of absenteeism due to COVID-19 on health care workers.Results: The results of this study showed that there were 1958 patients with COVID-19 among the staff of Mashhad University of Medical Sciences (MUMS) from February to September 2020. The absenteeism days in our study were 32,209 days. Total costs due to absenteeism were estimated to be nearly $1.3 million, with an average of $95.9 per patient in a month. The results of regression model showed that gender, age, employment type, job, experience and monthly income had a significant impact on the cost of absenteeism due to COVID-19.Conclusions: We calculated the absenteeism costs due to COVID-19 for the first time. Estimate costs and create evidence-based documentation can decrease the economic impacts of COVID-19 and improve human resources management during the COVID-19 pandemic.
Undergoing Multiple Red Blood Cell Transfusions is Associated With Poorer Outcomes in Very Low Birth Weight Infants
Authors: Fang Xiaohong , Huang Dali , Zeng Huibin , Xu Liping 
Published: July 2021

Abstract
Objective
This study was designed to assess red blood cell (RBC) transfusion frequency in very-low-birth-weight (VLBW)infants and to understand the relationships between the number of transfusions and the composite risk of bronchopulmonary dysplasia (BPD), retinopathy of prematurity (ROP), and mortality.
Method:
VLBW infants admitted from May 2017 – July 2019 were retrospectively analyzed. Relationships between gestational age (GA), birth weight (BW), numbers of transfusions, and comorbidities were evaluated through Pearson correlation analyses. The relationship between factors of interest (Model 1: GA, BW, comorbidities; Model 2: number of transfusions) and composite risk was assessed via a logistic regression approach.
Results
Overall,408 VLBW infants were enrolled, of whom 74% underwent at least one RBC transfusion. Infants with a GA < 30 weeks, a BW < 1,250 g, and comorbidities were more likely to require RBC transfusion. Number of transfusions was related to the risk of analyzed composite outcomes, with risk correlating with undergoing > 3 transfusions (OR: 3.275, 95% CI: 1.707–6.275).
Conclusion
We found that undergoing > 3 RBC transfusions was related to an increased risk of BPD, ROP, or death in VLBW infants.
Impaired CD8+ Mucosal-Associated Invariant T Cells and Myeloid-Derived Suppressor Cells Promote The Development of Polycystic Ovary Syndrome
Authors: Zhu Mengting , Xu Yuping , Li Caihua , Lu Zhimin , Bi Kaihuan , Wang Kangxia , Guo Peipei , Jiang Huanhuan , Cao Yunxia 
Published: July 2021

Abstract
Background: Immune dysfunction is one of the mechanisms to promote polycystic ovary syndrome (PCOS). Various immune cells have been reported to be involved in the development of PCOS. Meanwhile, the disturbance of metabolism is closely related to PCOS. This study is to explore the effect of mucosal-associated invariant T cells and myeloid-derived suppressor cells on the pathogenesis and the metabolic dysfunction of PCOS patients.Methods: 68 PCOS patients and 20 controls were recruited in this study and we collected the peripheral blood of participants’ during their follicular phase. The frequencies of MAIT cells and MDSCs were determined by flow cytometry after being stained with different monoclonal antibodies. And the concentrations of cytokines were determined by ELISA.Results: Compared to control group, the frequency of MDSCs, CD8+MAIT cells and CD38+CD8+MAIT cells were significantly decreased of PCOS patients with normal metabolism, however, proportion of CD4+MAIT cells exhibited a noticeable increase. PCOS patients with abnormal weight showed a lower level and activation of CD8+MAIT cells. On the contrary, they displayed an enrichment of CD4+MAIT cells. PCOS patients with glucose metabolic disorder displayed a remarkable dysregulation of MDSCs and Mo-MDSCs. MDSCs were positively correlated with MAIT cells. Negative correlations between the frequency of CD8+MAIT cells, CD38+CD8+MAIT cells and body mass index were revealed. CD4+MAIT cell was positively correlated with BMI. Mo-MDSCs were found to be negatively related to the levels of 2hour plasma glucose and HOMA-IR index.Conclusion: The MAIT cells subpopulations and MDSCs played distinct roles in the etiology and metabolic disorders of PCOS.
WITHDRAWN: Comparison The Effect of Single Daily Dose With 48 Hours Interval of Amikacin With Meropenem in Treatment With Urinary Tract Infection With E. Coli: A Clinical Trial Study
Authors: Mohsenpur Behzad , Azizzadeh Hero , Ghaderi Ebrahim , Ahmadi Amjad 
Published: July 2021

Abstract
Objective: Urinary tract infection is among the most prevalent infections in humans, and E. coli is the most frequent pathogen causing this disease. The production of Beta lactamase enzymes (ESBL) in this bacterium makes it resistant to many antibiotics. The aim of this study was to evaluate a novel method single daily dose of Amikacin at 48 h intervals in a clinical trial This was a double-blind clinical trial study.Material and Methods: The patients were divided into two groups of Intervention (Administration of single daily dose of Amikacin at 48 h intervals Intervals for 1 week 3 doses) and control (Prescription of Meropenem for 1 Week). Results: The mean age of the Intervention group was (46.64±3.89) and control group (46.03±2.38). The frequency of E. coli infection was 61(54%), and that of other infections was 52(46%).Conclusion: The results of our study show the therapeutic effect of single daily dose administration of Amikacin every 48 hours
Regionalization of Rainfall Intensity-Duration-Frequency (IDF) Curves With L-Moments Method Using Neural Gas Networks
Authors: Mahmoudi Mohammadreza , Eslamian Saeid , Soltani Saeid 
Published: July 2021

Abstract
Floods are one of the most frequent and destructive natural events which lead to lots of human and financial losses with damage to the houses, farms, roads, and other buildings. Intensity-duration-frequency (IDF) curves are the main and practical tools that have been used for flood control studies including the design of the water structures. In many cases, there is not any measuring device at the desired place or their information are not useful if there is any available. In this case, it is not possible to extract these curves through the conventional methods. Regionalizing the IDF curves is a method that has solved the issues mentioned in the common methods. In this research, the regionalized IDF curves are extracted in Khozestan province, Iran using 21 rain gauge stations through L-moments and neural gas networks. Clustering is one of the most effective steps and a prerequisite for regional frequency analysis (RFA) that divides the region and existing stations into hydrologically homogenous regions. In this study, clustering is done using two new models named neural gas (NG) and growing neural gas (GNG) network. Comparing the regional IDF curves with single site curves, it was found that neural gas network models had a more accurate performance and higher efficiency so that they had the lowest estimate error amount among other models. Also, due to the acceptable difference between regional and single site curves, the efficiency of L-Moments in RFA was evaluated as appropriate.