bluuebunny/crossref_metadata_2025_split huggingface dataset:
Women in STEM/SET: gender gap research review of the United Arab Emirates (UAE) – a meta-analysis
Authors: Patterson Louise , Varadarajan Damodharan Sowmya , Saji Salim Beena 
Published: December 2020

Purpose
The purpose of this paper is to conduct a meta-analysis of existing research on gender discrimination/gender gap and women in Science, Technology, Engineering and Mathematics (STEM) in the UAE, specifically, and Middle East and North Africa (MENA) and Gulf Cooperation Council (GCC) countries in general because of very limited number of articles published on the subject. It will give future researchers insights into the topics, methodologies and findings of such research from 1999–2019.

Design/methodology/approach
This study conducts a meta-analysis of 72 articles using the Wildcard operator search method and the Boolean operator to perform an integrative literature search related to gender discrimination studies done in relationship to or specific to the UAE.

Findings
In total, 88 papers related to the UAE and gender gap and women were identified. The articles were narrowed down to the ones published in high-ranked or Scopus journals (72). The findings suggest a decreasing trend in gender discrimination, but the issue still persists, requiring efforts from policy-makers, society and government to ensure gender parity is achieved. Academic research on women in STEM/SET workplace, specific to the UAE and the region, continue to slowly advance, with very few articles published in the same.

Practical implications
The study provides insights into gender gap research done in the past ten years specific to the UAE national women and gender gap in general and their career choices and prospects in the STEM/SET domain.

Social implications
There is a need to focus research on Emirati women in STEM careers to develop more insights into gender gap perceptions of Emirati women and identify challenges and methods to close the gender gap in STEM careers.

Originality/value
This paper brings a holistic perspective to the meta-analysis of research on the gender gap and women in the UAE’s STEM domain.
Corporate characteristics and leverage: evidence from Gulf countries
Authors: Al-Ahdal Waleed M. , Almaqtari Faozi A. , Zaid Dheya A. , Al-Homaidi Eissa A. , Farhan Najib H. 
Published: December 2020

Purpose
This study aims to investigate the impact of corporate characteristics on leverage in the Gulf Cooperation Council (GCC) non-financial listed firms.

Design/methodology/approach
A sample comprising a balanced panel for eight years from 2009–2016 for four Gulf countries is used. In total, 85 non-financial listed companies have been selected using a non-probability sampling technique. Corporate characteristics are represented by return on assets (ROA), return on equity, return on capital employed, market value-added, Tobin-Q, liquidity and firm size. The study used fixed and random effect models to estimate the results.

Findings
The findings of the study revealed that both ROA and FSIZE have a significant negative effect on leverage. However, market value-added, return on capital employed and Tobin-Q exhibited a statistically significant positive effect on leverage. Further, the results indicated that Qatar is better than kingdom of Saudi Arabia (KSA), Oman and the UAE. In addition, evidence noted that KSA is better than both UAE and Oman in terms of the overall impact of corporate characteristics on the leverage. However, this effect is not statistically significant.

Practical implications
This study provides an open insight for managers, bankers, financial analysts in the GCC countries and some other developing economies by highlighting the relationship between corporate characteristics and leverage in an emerging market.

Originality/value
The current study provides an important insight into corporate characteristics and leverage. By so doing, it provides an attempt to identify the factors influencing corporate financing behavior taking into consideration different issues such as different proxies of firms’ profitability, market capitalization, market value added and liquidity, which provides original evidence from Gulf countries emerging markets. These countries are characterized by low tax rates and high liquidity. High liquidity may reduce the cost of borrowing and debt financing may not be a huge burden on firms’ profits. This makes the investigation of leverage and corporate characteristics, particularly, firms’ profitability and liquidity, very important. Therefore, the study tries to bridge an existing gap in the body of literature of capital structure and debt financing in Gulf countries emerging markets.
Extraperitoneal high vaginal cuff suspension at the time of vaginal hysterectomy for advanced uterovaginal prolapse: Results of a modified McCall technique from a longitudinal clinical study
Authors: Zilberlicht Ariel , Dwyer Peter L. , Karmakar Debjyoti , Carswell Frida , Schierlitz Lore 
Published: December 2020

BackgroundWomen with high‐grade uterovaginal prolapse have a greater risk of recurrent prolapse after pelvic organ prolapse surgery. Royal College of Obstetricians and Gynaecologists guidelines have recommended sacrospinous suspension (sacrospinous fixation) at the time of vaginal hysterectomy, whenever there is a marked uterovaginal prolapse. We have modified the McCall culdoplasty by placing sutures extraperitoneally, higher and more lateral into the uterosacral/cardinal ligaments to re‐support the vaginal cuff at the time of a vaginal hysterectomy.AimsTo evaluate the results of a modified technique of McCall high culdoplasty and native tissue repair at time of vaginal hysterectomy in women with advanced uterovaginal prolapse.Material and methodsLongitudinal clinical follow‐up conducted between 2000–2018, in a tertiary urogynaecology centre for patients presenting with stage 3–4 uterovaginal prolapse, who underwent vaginal hysterectomy and modified McCall vault suspension.ResultsThere were 176 cases meeting the inclusion criteria. Mean follow‐up was 19.35 months. There were 25 recurrences (14%) of ≥ stage 2 (76% not symptomatic). Twelve of these recurrences (48%) occurred in anterior compartment, six (25%) posterior, three (12%) combined anterior/posterior, two (8%) combined posterior/central and one case had recurrence in all compartments. Only six cases (3%) required another surgical procedure for symptomatic prolapse, all with an enterocele recurrence.ConclusionsOur described modified McCall technique incorporates high extraperitoneal approach to apical resuspension along with closure of any existing large hiatal defects of the levator plate at the time of vaginal hysterectomy for advanced uterine prolapse has excellent outcomes and extremely low complication rates and avoids the need for sacrospinous fixation.
A Questionnaire on Decolonization
Authors: Copeland Huey , Foster Hal , Joselit David , Lee Pamela M. 
Published: December 2020

The term decolonize has gained a new life in recent art activism, as a radical challenge to the Eurocentrism of museums (in light of Native, Indigenous, and other epistemological perspectives) as well as in the museum's structural relation to violence (either in its ties to oligarchic trustees or to corporations engaged in the business of war or environmental depredation). In calling forth the mid-twentieth-century period of decolonization as its historical point of reference, the word's emphatic return is rhetorically powerful, and it corresponds to a parallel interest among scholars in a plural field of postcolonial or global modernisms. The exhortation to decolonize, however, is not uncontroversial-some believe it still carries a Eurocentric bias. Indeed, it has been proposed that, for the West, de-imperialization is perhaps even more urgent than decolonization. What does the term decolonize mean to you in your work in activism, criticism, art, and/or scholarship? Why has it come to play such an urgent role in the neoliberal West? How can we link it historically with the political history of decolonization, and how does it work to translate postcolonial theory into a critique of the neocolonial contemporary art world? Respondents include Nana Adusei-Poku, Brook Andrew, Sampada Aranke, Ian Bethell-Bennett, Kader Attia, Andrea Carlson, Elise Y. Chagas, ISUMA, Iftikhar Dadi, Janet Dees, Nitasha Dhillon, Hannah Feldman, Josh T. Franco, David Garneau, Renee Green, Iman Issa, Arnold J. Kemp, Thomas Lax, Nancy Luxon, Nelson Maldonado-Torres, Saloni Mathur, Tiona Nekkia McClodden, Alan Michelson, Partha Mitter, Isabela Muci Barradas, Steven Nelson, Ugochukwu-Smooth C. Nzewi, Alessandro Petti, Paulina Pineda, Christopher Pinney, Elizabeth Povinelli, Ryan Rice, Andrew Ross, Paul Chaat Smith, Nancy Spector, Francoise Verges, Rocio Zambrana, and Joseph R. Zordan.
GLIOBLASTOMA MULTIFORME: THE UNIQUE AND FATAL BRAIN TUMOR
Authors: Nandi Amartya , Srivastava Sanjeeva 
Published: December 2020

Glioblastomas are the most aggressive and most founded type of common type of CNS cancer which are mainly classified into 2 major groups i.e. low grade gliomas (LGG) and high grade gliomas (HGG) and exhibits both intra and inter tumor heterogeny
LGG are showing low proliferation rate and further divided two sub types that are Grade I and Grade II which are commonly infiltrative and recur and they occur usually due to mutations in IDH-1 and IDH-2 genes.
Whereas, HGG are further divided two sub types Grade III and Grade IV showing nuclear atypia and most aggressive necrosis and high angiogenesis rate.
Exploration of differential methylation-driven genes to identify key epigenetic genes for prognosis of ovarian serous cystadenocarcinoma
Authors: Jiang Xingyu , Qiu Jiaqi , Chen Jueming , Li Han , Zhang Yanna 
Published: December 2020

Abstract
Background: Ovarian cancer is the leading cause of gynecological cancer-related mortality. The majority of patients have poor prognosis due to the lack of available biomarkers capable of predicting prognosis accurately and providing novel targeted therapy options.Methods: The methylation array data, gene expression profile and clinical information of 351 ovarian serous cystadenocarcinoma (OSC) samples as well as the methylation array data of another 10 normal ovarian epithelial tissues were accessed from The Cancer Genome Atlas (TCGA) and served as training dataset. An algorithm, MethylMix, was on the basis of a β mixture model to compare the DNA methylation status in tumor to normal DNA methylation status and then screened out hypo and hypermethylated genes of OSC, which were transcriptionally predictive. Gene Ontology (GO) enrichment and ConsensusPathDB pathway analysis of differential methylation-driven genes were further performed. A linear risk model was constructed through the univariate and multivariate COX regression with Akaike Information Criterion (AIC). Datasets of OSC from Gene Expression Omnibus (GEO) database were served as validation datasets to determine the prognostic value of the risk model. The Kaplan-Meier analysis was then used to evaluate the ability of the risk model to distinguish the survival in training dataset or validation dataset, even in subgroups of patients with different FIGO stage, histologic grade, residual tumor after surgery, and anatomic neoplasm subdivision. The receiver operating characteristic (ROC) curve was also applied to determine the value of risk model on predicting the prognostic survival of patients as well as compared with other 15 known prognostic biomarkers in OSC.Results: Totally 171 differential methylation-driven genes were identified between OSC and normal samples. Five of them, UBB, PLAT, TMOD1, KCNJ11, and CDSN, were selected to construct the prognostic risk model. The Kaplan-Meier analysis demonstrated that the survival rate in low-risk cohort was significantly higher than that in high-risk cohort in both training dataset and validation dataset (P<0.0001 for training dataset; P<0.05 for validation dataset). Further, the ROC analysis confirmed the prognosis-predict value of the risk model applicable not only in different group of patients but also more accurately when compared with other biomarkers.Conclusions: Our study successfully identified multiple methylation-driven genes in OSC and constructed a novel prognostic risk model to provide bioinformatic basis and an important tool for guiding subsequent OSC early diagnosis, prognosis assessment, and clinical treatment.
The Relationship Between Recommended and None Recommended Food Scores on Cardiovascular Risk Factors in Obese and Overweight Adult Women: A Cross Sectional Study
Authors: Sabbari Maryam , Mirzababaei Atieh , Shiraseb Farideh , Mirzaei Khadijeh 
Published: December 2020

Abstract
Objective: No studies have examined the relationship between recommended food score (RFS), none recommended food score (NRFS) and cardiovascular risk factors. This study was conducted to evaluate the association of RFS and NRFS with cardiovascular risk factors in overweight and obese women.Methods: This cross-sectional study was performed on 379 overweight and obese (BMI ≥25 kg/m2) women aged 18-48 years. Anthropometric measurements and body composition analysis were assessed in all participants. Dietary intake was assessed by a valid and reliable food frequency questionnaire (FFQ) containing 147 items and RFS and NRFS calculated. Biochemical assessments including TC, HDL, LDL, TG, FBS, insulin, HOMA-IR and hs-CRP were quantified by ELISA.Results: The mean age and BMI of participants were 36.73±9.21 (y) and 31.17±4.22 (kg/m²) respectively. Binary logistic analysis showed that participants in the highest quartile of the RFS compared to the lowest quartile had 82% lower risk for Hypertriglyceridemia [OR=0.18, 95%CI=0.06-0.53, P=0.002] and 91% lower risk for abdominal obesity [OR=0.09, 95%CI=0.008-1.04, P=0.05]. in addition, Participants who were in the highest quartile of the RFS compared to the lowest quartile had lower HOMA-IR [OR=0.29, 95%CI=0.08-1.00, P=0.05]. subjects with high adherence to the NRFS had lower HDL [OR=2.11, 95%CI=1.08-4.12, P=0.02] and higher risk for Hypertriglyceridemia [OR=2.95, 95%CI=1.47-5.94, P=0.002] compared to low adherence. Conclusions: There was an inverse significant association between adherence to RFS and risk of Hypertriglyceridemia, insulin resistance, and abdominal obesity. There was a significant association between NRFS and Hypertriglyceridemia, and also we found an inverse relationship between NRFS and HDL.
WITHDRAWN: Developing an Electronic Search Strategy Algorithm for Detecting Professional Interpreter Use among Patients with Limited English Proficiency: A Derivation and Validation Study
Authors: Soleimani Jalal , Marquez Alberto , Weister Timothy , Barwise Amelia 
Published: December 2020

Abstract
Background
Evidence exists that disparities occur for patients with Limited English Proficiency (LEP) that impact the quality of medical services, outcomes, and patient satisfaction. Using interpreter services can reduce these negative impacts; therefore optimizing our understanding of interpreter use during patient care is important. Manual chart review is time-consuming. The objective of this study was to develop and validate a search strategy algorithm to detect patients who used professional interpreter services during their hospitalization.
Methods
We identified all adults who were admitted to the hospital who had at least one Intensive Care Units (ICU) admission during the hospital stay across the Mayo Clinic Enterprise between January 1, 2015, and June 30, 2020. Three random subsets of 100 patients were extracted from 60,268 patients admitted to an ICU to develop the search strategy algorithm. A physician reviewer conducted the gold standard manual chart review and these results were compared with the search strategy algorithm each time it was refined. Iterative modification of the search strategy was performed and sensitivity and specificity were calculated by comparing the results to the reference standard for both derivation cohorts and the final validation cohort. Any uncertainties were resolved by a second physician researcher.
Results
The first search strategy resulted in a specificity of 95.7% and a sensitivity of 93.5%. The second revised search strategy achieved a specificity of 96.7% and a sensitivity of 92.3%. The final version of the search strategy was applied to the validation subset and specificity and sensitivity were 92.6% and 100% respectively.
Conclusion
We successfully derived and validated a search strategy algorithm to assess interpreter use among hospitalized patients. Developing a search strategy algorithm with a high sensitivity can reduce the time required to abstract data from the medical record compared to manual chart review. This can be used to examine and understand patient needs for research and quality improvement initiatives.
Neoantigen Load as a Prognostic and Predictive Marker for Stage II/III Non-Small Cell Lung Cancer&nbsp;in Chinese Patients
Authors: Li Hui , He Ronghui , Xu Yanjun , Luo Taobo , Jin Kaixiu , Yuan Wuzhou , Zheng Zengguang , Liu Lanxuan , Liang Zebin , Li Ao , Zheng Zhiguo , Fan Yun 
Published: December 2020

Abstract
BackgroundPrognosis of stage II/III non–small-cell lung cancer (NSCLC) is unsatisfactory even after complete tumor resection and adjuvant chemotherapy. Tumors with high immunogenicity were defined as “hot tumors” and associated with clinical benefits from immunotherapy. Here we assessed the prognostic and predictive value of immunogenomic signatures and gene mutation characters for stage II/III non-small cell lung cancer in Chinese patients. MethodsNinety-one paired resected stage II/III NSCLC and normal tissues and peripheral blood samples, including 47 squamous cell lung carcinomas (SCC) and 44 lung adenocarcinomas (ADC), were collected and analyzed using the whole exome sequencing (WES) to identify gene mutation and immunogenomic signatures for association with clinicopathological variables and disease-free survival (DFS). ResultsA high number of tumor mutation burden (TMB, > 4 mutations/Mb) was associated with better DFS of NSCLC patients, although there was no such an association in SCC and ADC subgroups. Moreover, higher neoantigen load (NAL, > 2 neoantigens/Mb) exhibited better DFS and survival benefit after adjuvant chemotherapy in a low NAL subgroup of SCC patients but not in ADC subgroup. A high DNA damage repair (DDR) index (gene mutations occurred in at least three different DNA repair pathways) was associated with high NAL numbers and favorable DFS of SCC, but not in ADC patients. However, mutations of individual gene, oncogene pathways, and antigen presentation machinery genes, and human leukocyte antigen (HLA)-I number and HLA-I loss of heterozygosity (LOH) had no prognostic or predictive value for DFS of SCC or ADC patients. ConclusionGiven the present information, NAL was a useful biomarker for lung SCC prognosis and prediction of chemotherapy responses in Chinese patients. Further study with a larger sample size from multiple institutions is needed to confirm these data.
LRIG1 Modulated Radioresistance of Glioma via Regulating CTLA-4/AKT Signaling Pathway
Authors: Cheng Shiqi , Huang Xiangqun , Yuan Raorao , Zhang Yan 
Published: December 2020

Abstract
Background: Radioresistance has a great impact on prognosis of glioma patients. However, the potential mechanism underlying the radioresistance of glioma cells remains largely unknown. Methods: LRIG1 overexpression model was firstly established by using Flag-LRIG1 plasmid. The expression of LRIG1, CTLA-4 proteins were detected by western blot and IHC in cells and human tissue. Real-time PCR was used for deterring mRNA expression. Cell viability and apoptosis were detected using CCK-8 and Annexin-V/propidium iodide (PI), respectively. Co-Immunoprecipitation was used for detecting the combination of LRIG1 and CTLA-4 proteins. Results: LRIG1 was significantly down-regulated in radioresistant glioma cells. Overexpressed LRIG1 could promote the radiosensitivity of glioma cells, meanwhile, inhibit the expression of p-AKT and CTLA-4 protein in radioresistant glioma cells. Furthermore, LRIG1 combined with CTLA-4 and promoted CTLA-4 degradation. In human glioma tissue, LRIG1 was down-regulated, while CTLA-4 was highly expressed in glioma tissue. Finally, correlation analysis showed that the expression of LRIG1 was negatively correlated with expression of CTLA-4 and radioresistance of glioma patients. Conclusion: Our findings demonstrated that LRIG1 facilitates radioresistance glioma cells by regulating CTLA4 /AKT signaling pathway.
Short Term and Long term Building Electricity Consumption Prediction
Using Extreme Gradient Boosting
Authors: Tyagi Sakshi , Singh Pratima 
Published: December 2020

Background:
Electricity is considered as the essential unit in today’s high-tech world.
The electricity demand has been increased very rapidly due to increased urbanization,(smart
buildings, and usage of smart devices to a large extent). Building a reliable and accurate electricity
consumption prediction model becomes necessary with the increase in demand for energy. From
recent studies, prediction models such as support vector regression (SVR), gradient boosting
decision tree (GBDT), artificial neural network (ANN), random forest (RF), and extreme gradient
boosting (XGBoost) have been compared for the prediction of electricity consumption and
XGBoost is found to be the most efficient method that leads to the motivation for the research.

Objective:
The objective of this research is to propose a model that performs future electricity
consumption prediction for different time horizons: short term prediction and long term prediction
using the extreme gradient boosting method and reduce prediction errors. Also, based on the
prediction of the electricity consumption, the best and worst predicted days are being recognized.

Methods:
The method used in this research is the extreme gradient boosting for future building
electricity consumption prediction. The extreme gradient boosting method performs predictions for
different time horizons(short term and long term) for different seasons(summer and winter). The
model was designed for a house building located in Paris.

Results:
The model has been trained and tested on the dataset and its prediction is accurate with
the low rate of errors compared to other machine learning techniques. The model predicts
accurately with RMSE of 140.45 and MAE of 28, which is the least value for errors when
compared to the baseline prediction models.

Conclusion:
A model that is robust to all the conditions should be built by enhancing the
prediction mechanism such that the model should be dependent on a few factors to make electricity
consumption prediction.