nils-herrmann/clean_scirepeval huggingface dataset:
Phosphate solubilization by Trichoderma koningiopsis (NBRI PR5) under abiotic stress conditions
Year: 2020

solubilizing fungi contribute considerably in microbial phosphate mobilization. However, effects of different abiotic stresses on P solubilization mechanisms in Trichoderma are largely unexplored. In the present study we selected a P solubilizing Trichoderma to study the mechanism of P solubilization under alkaline and drought conditions. Among 33 Trichoderma isolates (NBRI PR1 NBRI PR33) NBRI PR5 was selected after screening for stress tolerance, antagonistic activity against phyto pathogens and P solubilization. The selected strain, Trichoderma koningiopsis (NBRI PR5) was characterized and identified using ITS and tef1 sequencing (Accession no. JN375992) Results show that NBRI PR5 uses different mechanisms of P solubilization under in vitro alkaline and drought conditions. NBRI PR5 produced organic acids for solubilizing insoluble tri calcium phosphate (TCP) at high pH stress. In drought conditions NBRI PR5 accumulated poly phosphate in its mycelia and produced alkaline phosphatase enzyme for P solubilization. The study concludes that T. koningiopsis employs different mechanisms of P solubilization in different stress conditions and therefore, it can be used in management of stressed soils.
Use of Ivermectin Is Associated With Lower Mortality in Hospitalized Patients With Coronavirus Disease 2019
Venue: Chest
Year: 2020

Ivermectin was shown to inhibit SARS CoV 2 replication in vitro, which has led to off label use, but clinical efficacy has not been previously described.  Does ivermectin benefit hospitalized COVID 19 patients?  Charts of consecutive patients hospitalized at four Broward Health hospitals in Florida with confirmed COVID 19 between March 15 through May 11, 2020 treated with or without ivermectin were reviewed. Hospital ivermectin dosing guidelines were provided but treatment decisions were per treating physician's discretion. The primary outcome was all cause in hospital mortality. Secondary outcomes included mortality in patients with severe pulmonary involvement, extubation rates for mechanically ventilated patients, and length of stay. Severe pulmonary involvement was defined as need for FiO2 =50% noninvasive ventilation, or invasive ventilation at study entry. Logistic regression and propensity score matching were used to adjust for confounders.  patients, 173 treated with ivermectin and 107 without ivermectin, were reviewed. Most patients in both groups also received hydroxychloroquine and/or azithromycin. Univariate analysis showed lower mortality in the ivermectin group (15.0% versus 25.2% OR 0.52, CI 0.29 0.96, P=0.03) Mortality was also lower among ivermectin treated patients with severe pulmonary involvement (38.8% vs 80.7% OR 0.15, CI 0.05 0.47, p=0.001) There were no significant differences in extubation rates (36.1% vs 15.4% OR 3.11 (0.88 11.00) p=0.07) or length of stay. After multivariate adjustment for confounders and mortality risks, the mortality difference remained significant (OR 0.27, CI 0.09 0.80, p=0.03) 196 patients were included in the propensity matched cohort. Mortality was significantly lower in the ivermectin group (13.3% vs 24.5% OR 0.47, CI 0.22 0.99, p<0.05) an 11.2% (CI 0.38% 22.1% absolute risk reduction, with a number needed to treat of 8.9 (CI 4.5 263)  Ivermectin treatment was associated with lower mortality during treatment of COVID 19, especially in patients with severe pulmonary involvement. Randomized controlled trials are needed to confirm these findings.
Recovery Experience as the Mediating Factor in the Relationship Between Sleep Disturbance and Depressive Symptoms Among Female Nurses in Chinese Public Hospitals: A Structural Equation Modeling Analysis
Venue: Psychology research and behavior management
Year: 2020

Nurses are suffering from considerable work related stress, which can result in disturbed sleep and depressive symptoms. Whereas, recovery experience can alleviate sleep disturbance and help maintain well being in the working environment. The aim of this study was to examine whether recovery experiences play a mediating role in the relationship between sleep disturbance and depressive symptoms of female nurses in Chinese public hospitals.  From December 2017 to May 2018, the study with proportional sampling of cross sectional design was carried out in the public tertiary hospitals from Shenyang of Liaoning Province in China. A total of 1500 female nurses who had been working for one or more years participated in this study. A structural equation model (SEM) was applied to test the assumption that recovery experiences might function as a mediator in the relationship between sleep disturbance and symptoms of depression.  Sleep disturbance contributed most to the variance (32.9% of depressive symptoms and had a significantly positive correlation with depressive symptoms (P<0.01) among nurses. Psychological detachment in recovery experience had a significantly positive correlation with sleep disturbance (P<0.01) and depressive symptoms (P<0.01) Whereas, relaxation, mastery experience, and control in recovery experience were significantly and negatively correlated with sleep disturbance (P<0.01) and depressive symptoms (P<0.01) Recovery experience served as a mediator between sleep disturbance and depressive symptoms (a b 0.066, BCa 95% CI: 0.045, 0.095)  Sleep disturbance was the predictor of depressive symptoms for female nurses. Moreover, recovery experience could combat the detrimental impacts of sleep disturbances on symptoms of depression. This study suggested that nurses might benefit from interventions on improving sleep quality to relieve depressive symptoms through mediating path of recovery experience.
CFD DEM study of biomass gasification in a fluidized bed reactor: Effects of key operating parameters
Year: 2020

Biomass gasification in a fluidized bed reactor is a complex process involving intricately multi scale and multi physics processes and may be affected by many operating parameters. In this work, it is numerically investigated at particle scale using a coupled Computational Fluid Dynamics Discrete Element Method (CFD DEM) approach. The flow dynamics, turbulence, heat transfer via convective, conductive, and radiative paths, and heterogeneous and homogeneous reactions are considered. The effects of key operating parameters on gasification performance are studied in terms of biomass particle diameter, initial bed temperature, steam to biomass (S/B) ratio, inlet gas flow rate, and feed position. The simulation results show biomass particle diameter has an insignificant influence on the production of H2 and CH4 while it slightly affects the production of CO and CO2. Higher initial bed temperature leads to a larger decrease of gas temperature at bed exit and benefits the production of H2 and CO. Increasing S/B ratio increases H2 and CO2 production while decreases CH4 and CO production. Larger inlet gas flow rate leads to a shorter gas residence time and the decrease of S/B ratio. Biomass particles fed from the side wall give rise to higher temperature, lower H2 and CO2, and higher CO and CH4 than that fed from the center bottom. Changing feed positions on the side wall has a slight influence on gas temperature while it has an insignificant influence on product compositions.
Evaluating interventions to improve test, treat, and track (T3) malaria strategy among over the counter medicine sellers (OTCMS) in some rural communities of Fanteakwa North district, Ghana: study protocol for a cluster randomized controlled trial
Venue: Trials
Year: 2020

The World Health Organization initiated test, treat, and track (T3) malaria strategy to support malaria endemic countries in their efforts to achieve universal coverage with diagnostic testing, antimalarial treatment, and strengthening surveillance systems. Unfortunately, T3 is not adopted by over the counter medicine sellers (OTCMS) where many patients with malaria like symptoms first seek treatment. Sub Saharan African countries are considering introducing and scaling up RDTs in these outlets to reduce malaria burden. In this context, this study is aimed at improving implementation of the T3 among OTCMS using a number of intervention tools that could be scaled up easily at the national level.  The interventions will be evaluated using a two arm, cluster randomized trial across 8 rural communities (4 clusters per arm) in two adjacent districts (Fanteakwa North and Fanteakwa South districts) of Ghana. A total of 8 OTCMS in the intervention arm and 5 OTCMS in the control arm in the selected communities will participate in the study. In the intervention arm only, subsidized malaria rapid diagnostic test (mRDT) kits will be introduced after the OTCMS have been trained on how to use the kit appropriately. Supervision, technical assistance, feedbacks, and collection of data will be provided on a regular basis at the participating medicine stores. The primary outcome is the proportion of children under 10 years with fever or suspected to have malaria visiting OTCMS and tested (using mRDT) before treatment. Secondary outcomes will include adherence to national malaria treatment guidelines and recommended mRDT retail price. Outcomes will be measured using mainly a household survey supplemented by mystery client survey and a surveillance register on malaria tests conducted by the OTCMS during patient consultations. Data collected will be double entered and verified using Microsoft Access 2010 (Microsoft Inc. Redmond, Washington) and analyzed using STATA version 11.0.  The trial will provide evidence on the combined effectiveness of provider and community interventions in improving adherence to the T3 initiative among OTCMS in rural Ghana. Ethical clearance NMIMR IRB CPN 086/18 19 Trial registration ISRCTN registry ISRCTN77836926 Registered on 4 November 2019.
The Role of Youth Enterprise Development Fund (YEDF) in Job Creation: A Case of Dagoretti Constituency, Nairobi County, Kenya
Year: 2013

Youth unemployment in Kenya is a serious development issue. The government conceived the Youth Enterprise Development Fund (YEDF) in June 2006 as a strategic move towards arresting the high rate of unemployment among the youth in the country. The overall objective of this study therefore was to investigate the role of the YEDF in job creation: A Case of Dagoretti Constituency, Nairobi County. The study population consisted of beneficiary youth groups at Dagoretti Constituency and YEDF management officials at the head office. The study adopted a descriptive survey design. To achieve this, two sets of questionnaires and one interview schedule were used to get information. Prior to data collection, authorization was sought from National Council of Science and Technology (NCST) The target population was 80 respondents and due to the small sample size, the researcher carried out a census. Out of the target population of 80 respondents, 70 responded translating to a response rate of 87.5% Data collected was analyzed using Statistical Program for Social Sciences (SPSS) and presented in the form of frequency tables, pie charts and bar charts. The research findings showed that majority of the respondents (85% felt that YEDF has helped reduce youth unemployment. A significant percentage of respondents (82% strongly agreed that lack of business and management skills is the greatest challenge entrepreneurs are facing and needed entrepreneurship training. The youth groups also suggest that the Fund should have a variety of structures to disburse funds also is should give loans to individuals since not all of them are in youth groups. They felt that YEDF should be exposed them capacity building programmes and life skills. Further it was found that the interest rate and repayment terms offered by YEDF were found to be the most appealing factor to beneficiaries. The youth groups suggested that the fund have more collaborations and strategic partnerships with financial intermediaries at grassroots to facilitate disbursement of funds to youth groups at the constituency. The main study recommendations include; YEDF funds be increased by the government and other financiers. For YEDF to be more effective in empowering the young entrepreneurs in the informal sector, more emphasis should be put in giving more training in entrepreneurship skills to youth before and after accessing the loan and credit should be given primarily for enterprise expansion, rather than start ups.  Youth enterprise Development Fund, Job Creation in Kenya
New and Old Sorts: Implications for Asset Pricing
Year: 2020

We study the returns to characteristic sorted portfolios up to five years after portfolio formation. Among a set of 56 characteristics, we find large pricing errors between the contemporaneous returns of new and old sorts, where new sorts use the most recent observations of firm characteristics. These relative pricing errors are not captured by existing asset pricing models and have been overlooked by standard tests using only returns to new sorts. Thus, pricing errors across horizons provide new and powerful information to test asset pricing models. Further, we show that these pricing errors are strongly related to a characteristic's market beta and connected to the difference in return between new and old stocks in the characteristic sorted portfolios.
Lightweight, Multi Stage, Compiler Assisted Application Specialization
Venue: ArXiv
Year: 2021

Program debloating aims to enhance the performance and reduce the attack surface of bloated applications. Several techniques have been recently proposed to specialize programs. These approaches are either based on unsound strategies or demanding techniques, leading to unsafe results or a highoverhead debloating process. In this paper, we address these limitations by applying partial evaluation principles to generate specialized applications. Our approach relies on a simple observation that an application typically consists of configuration logic, followed by the main logic of the program. The configuration logic specifies what functionality in the main logic should be executed. LMCAS performs partial interpretation to capture a precise program state of the configuration logic based on the supplied inputs. LMCAS then applies partial evaluation optimizations to generate a specialized program by propagating the constants in the captured partial state, eliminating unwanted code, and preserving the desired functionalities. Our evaluation of LMCAS on commonly used benchmarks and real world applications shows that it successfully removes unwanted features while preserving the functionality and robustness of the deblated programs, runs faster than prior tools, and reduces the attack surface of specialized programs. LMCAS runs 1500x, 4.6x, and 1.2x faster than the state of the art debloating tools CHISEL, RAZOR, and OCCAM, respectively; achieves 25% reduction in the binary size; reduces the attack surface of code reuse attacks by removing 51.7% of the total gadgets and eliminating 83% of known CVE vulnerabilities.
APID database: redefining protein protein interaction experimental evidences and binary interactomes
Venue: Database J. Biol. Databases Curation
Year: 2019

The collection and integration of all the known protein protein physical interactions within a proteome framework are critical to allow proper exploration of the protein interaction networks that drive biological processes in cells at molecular level. APID Interactomes is a public resource of biological data (http:/apid.dep.usal.es) that provides a comprehensive and curated collection of `protein interactomes' for more than 1100 organisms, including 30 species with more than 500 interactions, derived from the integration of experimentally detected protein to protein physical interactions (PPIs) We have performed an update of APID database including a redefinition of several key properties of the PPIs to provide a more precise data integration and to avoid false duplicated records. This includes the unification of all the PPIs from five primary databases of molecular interactions (BioGRID, DIP, HPRD, IntAct and MINT) plus the information from two original systematic sources of human data and from experimentally resolved 3D structures (i.e. PDBs, Protein Data Bank files, where more than two distinct proteins have been identified) Thus, APID provides PPIs reported in published research articles (with traceable PMIDs) and detected by valid experimental interaction methods that give evidences about such protein interactions (following the `ontology and controlled vocabulary' www.ebi.ac.uk/ols/ontologies/mi; developed by `HUPO PSI MI' Within this data mining framework, all interaction detection methods have been grouped into two main types: (i) `binary' physical direct detection methods and (ii) `indirect' methods. As a result of these redefinitions, APID provides unified protein interactomes including the specific `experimental evidences' that support each PPI, indicating whether the interactions can be considered `binary' (i.e. supported by at least one binary detection method) or not.
Identification of Candidate Growth Promoting Genes in Ovarian Cancer through Integrated Copy Number and Expression Analysis
Venue: PloS one
Year: 2010

Ovarian cancer is a disease characterised by complex genomic rearrangements but the majority of the genes that are the target of these alterations remain unidentified. Cataloguing these target genes will provide useful insights into the disease etiology and may provide an opportunity to develop novel diagnostic and therapeutic interventions. High resolution genome wide copy number and matching expression data from 68 primary epithelial ovarian carcinomas of various histotypes was integrated to identify genes in regions of most frequent amplification with the strongest correlation with expression and copy number. Regions on chromosomes 3, 7, 8, and 20 were most frequently increased in copy number >40% of samples) Within these regions, 703/1370 (51% unique gene expression probesets were differentially expressed when samples with gain were compared to samples without gain. 30% of these differentially expressed probesets also showed a strong positive correlation (r>=0.6) between expression and copy number. We also identified 21 regions of high amplitude copy number gain, in which 32 known protein coding genes showed a strong positive correlation between expression and copy number. Overall, our data validates previously known ovarian cancer genes, such as ERBB2, and also identified novel potential drivers such as MYNN, PUF60 and TPX2.
Detecting Fake News with Sentiment Analysis and Network Metadata
Year: 2018

With the proliferation of the Internet and social media, there is now a voluminous amount of news, articles, and other text available online. These resources, while making communication and information flow easier and faster, have jeopardized the veracity of the news that is being distributed. The impact of fake news has been so deep rooted in society that it even affected the US election of 2016. This project used a combination of sentiment analysis and network metadata in a Machine Learning model to classify fake news. The study created a scraping tool to accumulate data related to the news and leveraged four different sub pipelines for feature engineering and feature extraction. The fake news model was trained on the Random Forest Classifier. Results show that the proposed model achieved a F1 score greater than 88% The study has also developed a web interface to take a URL of the news and display whether the news is fake.
Social Norms and Gender Differences in Labor Force Participation in China
Year: 2020

Since China's transition to a socialist market system, women's labor force participation has declined sharply. Using data from the Chinese General Social Survey (CGSS) 2010, the authors re examine China's gender gap in labor force participation with a focus on social norms. Probit model estimates of the gender gap in labor force participation probability confirm the contribution of conventional factors such as health and other human capital as important explanations for the resurgent gender gap in China. However, even after extensive controls for human capital differences, the gap remains mostly unexplained in the data. The Blinder Oaxaca decomposition analysis confirms that the gender gap in labor force participation is predominantly explained by behavioral differences between women and men. Gender related community social norms account for 41.4 percent of the unexplained gap. The study results are robust to alternative measures of social norms and additional controls for community characteristics.  Recent studies have examined why women's labor force participation has declined sharply in post economic reform China, but research on the effects of social norms has been limited. The gender gap in participation remains mostly unexplained by differences in human capital between women and men. Social norms account for almost half of the unexplained portion of the gender gap in labor force participation. Along with expanding women's access to education and improving their health, policies should promote favorable attitudes toward women's employment, particularly during times of economic crisis.
Understanding heterogeneity of treatment effect in prostate cancer
Venue: Current opinion in oncology
Year: 2015

In the era of personalized medicine, oncologists seek to tailor treatments for their patients based on indicators of differential response to treatment. We first provide a conceptual explanation of heterogeneity of treatment effect using prostate cancer as a case study and review studies that test whether Gleason score has a role in modifying the effectiveness of androgen deprivation therapy in men newly diagnosed with metastatic prostate cancer. Recent findings Depending on the study design, setting, and population, the median time to develop castration resistant prostate cancer ranges from 12 to 23 months among men with M1 disease on androgen deprivation therapy, and the median time from diagnosis to mortality in such patients ranges from 23 to 37 months. Patients with higher Gleason scores have a significantly shorter time to developing castration resistant prostate cancer compared with patients with lower Gleason scores. However, data suggest that Gleason score does not have a role in modifying the survival benefit associated with androgen deprivation therapy.  Androgen deprivation therapy has heterogeneous effects in men with metastatic prostate cancer related to the time of developing castration resistance. However, survival benefit from androgen deprivation therapy does not appear to depend on Gleason score.