bluuebunny/crossref_metadata_2025_split huggingface dataset:
Usefulness of Vascular Clips in Surgery for Gynecologic Cancer
Authors: Nakanishi Kazuho , Yamada Takashi , Suzuki Shunji 
Published: September 2021

Abstract
In gynecological surgery for cervical cancer and endometrial cancer with lymphadenectomy, many lymph vessels are ligated to prevent postoperative lymph leakage and lymphocele, and many blood vessels leading to the pelvic floor are ligated. Therefore, the labors required for ligation are very large. However, no studies have examined ligation methods in gynecologic cancer surgery. Therefore, we retrospectively examined gynecologic cancer patients who had been treated at our hospital by dividing them into a group using absorbent threads and a group using titanium clips. In addition, the surgical procedure was classified into three groups: a group with only pelvic lymphadenectomy, a group with pelvic and para-aortic lymphadenectomy, and a group with radical hysterectomy with pelvic lymphadenectomy. As a result, analysis of all cases clearly showed less complications and less time for surgery in the clip group. Furthermore, the analysis of RH + PLN group showed that surgery time was clearly shorter and less complications tended to occur in the clip group. In conclusion, by using this easily usable device, surgery for gynecologic malignancies will be more comfortable and safer.
Dynamic experience of architectural forms affects arousal and valence perception in virtual environments
Authors: Presti Paolo , Ruzzon Davide , Avanzini Pietro , Caruana Fausto , Rizzolatti Giacomo , Vecchiato Giovanni 
Published: September 2021

Abstract
The built environment represents the stage surrounding our everyday life activities. To investigate the impact that architectural features have on individuals’ affective states, we measured their judgments of perceived valence (pleasant and unpleasant) and arousal after the dynamic experience of a progressive change of the environment within virtual decontextualized spaces. To this aim, we developed a parametric model which allowed to create 54 virtual architectural spaces characterized by a progressive change of side walls distance, ceiling and windows height as well as colour of the environment. Decreasing side walls distance, ceiling height variation as well as increasing windows height significantly affected the emotional state of the participants within virtual environments. Indeed, such architectural spaces generated high arousing and unpleasant states according to subjective judgement. Overall, we observed that valence and arousal scores are affected by all the dynamic form factors which modulated the spaciousness of the surrounding. Showing that virtual reality enables the possibility to measure the emotional impact of pure and decontextualized architectural features, we contribute to foster a human-centered approach to design where mental state of people is fundamental for the creation of novel spaces promoting wellbeing.
Automatic skin disease diagnosis using deep learning from clinical image and patient information
Authors: Muhaba Kedir Ali , Dese Kokeb , Aga Tadele Mola , Zewdu Feleke Tilahun , Simegn Gizeaddis Lamesgin 
Published: September 2021

Abstract
Background
Skin diseases are the fourth most common cause of human illness which results enormous non-fatal burden in daily life activities. They are caused by chemical, physical and biological factors. Visual assessment in combination with clinical information is the common diagnosis procedure for the diseases. However, these procedures are manual, time consuming, and require experience and excellent visual perception.
Methods
In this study, an automated system is proposed for diagnosis of five common skin diseases by using data from clinical images and patient information using deep learning pretrained mobilenet-v2 model. Clinical images were acquired using different smartphone cameras and patient’s information were collected during patient registration. Different data preprocessing and augmentation techniques were applied to boost the performance of the model prior to training.
Results
A multiclass classification accuracy of 97.5%, sensitivity of 97.7% and precision of 97.7% has been achieved using the proposed technique for the common five skin disease. The results demonstrate that, the developed system provides excellent diagnosis performance for the five skin diseases.
Conclusion
The system has been designed as a smartphone application and it has a potential to be used as a decision support system in low resource settings, where both the expert dermatologist and the means is limited.
The Relationship Between Body Composition, Glucose Metabolism, and Subtypes of Depressive Symptoms – Findings From the Helsinki Birth Cohort Study
Authors: Eriksson Mia D. , Eriksson Johan G. , Korhonen Päivi , Salonen Minna K. , Mikkola Tuija M. , Kajantie Eero , Wasenius Niko , Bonsdorff Mikaela , Kautiainen Hannu , Laine Merja K. 
Published: September 2021

Abstract
Background There is an existing link between two of the most common diseases, obesity and depression. These are both of great public health concern, but little is known about the relationships between the subtypes of these conditions. We hypothesized that non-melancholic depressive symptoms have a stronger relationship with both body composition (lean mass and fat mass) and dysfunctional glucose metabolism than melancholic depression. Methods For this cross-sectional study 1 510 participants from the Helsinki Birth Cohort Study had their body composition evaluated as lean mass and fat mass (Lean Mass Index + Fat Mass Index = Body Mass Index). Participants were evaluated for depressive symptoms utilizing the Beck Depression Inventory, and had laboratory assessments including an oral glucose tolerance test. Results Higher than average Fat Mass Index (kg/m2) was associated with a higher percentage of participants scoring in the depressive range of the Beck Depression Inventory (p=0.048). Higher Fat Mass Index was associated with a higher likelihood of having depressive symptoms (OR per 1-SD Fat Mass Index=1.37, 95% CI: 1.13-1.65), whereas higher Lean Mass Index (kg/m2) was associated with a lower likelihood of having depressive symptoms (OR per 1-SD Lean Mass Index=0.76, 95% CI: 0.64-0.91). Participants with an above average Fat Mass Index more frequently had non-melancholic depressive symptoms (p=0.008) regardless of Lean Mass Index levels (p=0.38). There was no difference between the body composition groups in the likelihood of having melancholic depressive symptoms (Fat Mass Index p=0.83, Lean Mass Index p=0.93). The non-melancholic group had higher Fat Mass Index than either of the other groups (p<0.001), and a higher 2-hour glucose concentration than the non-depressed group (p=0.005). Conclusion As hypothesized, non-melancholic depressive symptoms are most closely related to high fat mass index and dysfunctional glucose metabolism.
Association Between Sleep Status and Myopia in Children and Adolescents: A Cross-sectional Study in Shenzhen
Authors: Zong Zhiqiang , Wang Renjie , Zhang Yi , Wu Xiaoyan , Xu Shaojun , Tao Fangbiao 
Published: September 2021

Abstract
Purpose: The aim of this cross-sectional study was to assess the association between sleep status and myopia in children and adolescents.Methods: Stratified cluster sampling a total of 30,188 schoolchildren from 14 schools located in 6 streets (Xinxiang, Songgang, Shiyan, Fuyong, Shajing and Xinan) of Baoan District in Shenzhen, China. The demographic characteristics of schoolchildren, information of self-reported myopia and their sleep status in the last 1 month were collected through using a standardized questionnaire. χ2-test was used to compare differences in myopia rates among children and adolescents in different sleep status. Logistic regression models were used to analyze the association of sleep status with myopia in children and adolescents.Results: The self-reported myopia rates was 49.8% among children and adolescents in Shenzhen. In primary, junior high and senior high students, the myopia rates were 25.6%, 62.4%, and 75.7%, respectively. After controlling for confounders, the results of multiple logistic analysis showed that night sleep duration < 7h/d (OR = 2.02, 95%CI: 1.87-2.19), falling asleep at a fixed time (no) (OR = 1.14, 95%CI: 1.08-1.20), getting up at a fixed time in the morning (no) (OR = 1.28, 95%CI: 1.19-1.37), putting off sleeping on weekends ≥ 2 h/d (OR = 1.28, 95%CI: 1.17-1.41) and Putting off getting up on weekends ≥ 2 h/d were risk factors (OR = 1.23, 95%CI: 1.13-1.34). After stratified by grade, social jet lag was not associated with myopia among senior high students.Conclusion: Insufficient sleep duration was positively associated with self-reported myopia, irregular patterns of sleep and social jet lag increased the risk of myopia among schoolchildren. Myopia prevention and control among children and adolescents should not only ensure adequate sleep, but also develop a habit of regular sleep.
AI - Based Framework for Private Cloud Computing
Authors: R DHAYA , R Kanthavel 
Published: September 2021

Abstract
Artificial Intelligence (AI) systems are computational simulations that are "trained" using information and expert input to duplicate a professional's choice given the same data. Only using one private cloud storage service to store information can cause a variety of issues for the system administrator. Knowledge providers, scalability, efficiency, privacy, and the potential of vendor support are examples of such concerns. Distributing information across several cloud storage services, comparable to how data is dispersed between various physical disk drives to increase error detection and increase productivity, is a possible approach. Moreover, because multiple private cloud providers have varying pricing strategies and service quality, maximizing the efficiency and profitability of many cloud providers at the same time is difficult. Based on access permission behaviors, this study presents a methodology for dynamically modifying network management rules across several cloud providers. The goal of this research is to look into how to reduce both the estimated cost and delay periods for numerous cloud providers. The architecture was put into practice in a cloud storage systems emulator, which simulated the complexity and effectiveness of numerous cloud providers in a real-world context. In particular, the architecture was evaluated in a variety of cloud storage environments. The outcomes of the platform's testing revealed that many cloud methods were successful.
Title Page Predictive Value of Lymphocyte-to-Monocyte Ratio in Patients with Atrial Fibrillation: A Propensity Score Matching Analysis
Authors: Yu Yue , Wang Suyu , Wang Pei , Xu Qiumeng , Zhang Yufeng , Xiao Jian , Xue Xiaofei , Yang Qian , Xi Wang , Wang Junnan , Huang Renhong , Liu Meiyun , Wang Zhinong 
Published: September 2021

Abstract
Background

Inflammation plays a key role in the initiation and progression of atrial fibrillation (AF). Lymphocyte-to-monocyte ratio (LMR) has been proved to be a reliable predictor of many inflammation-associated diseases, but little data are available on the relationship between LMR and AF. The present study aimed to evaluate the predictive value of LMR in predicting all-cause mortality among AF patients.
Methods

Data of patients diagnosed with AF were retrieved from the Medical Information Mart for Intensive Care-III (MIMIC-III) database. X-tile analysis was used to calculate the optimal cutoff value for LMR. The Cox proportional-hazards regression model was used to assess the association of LMR and 28-day, 90-day and 1-year mortality. Additionally, a propensity score matching (PSM) method was performed to minimize the impact of potential confounders.
Results

A total of 3,567 patients hospitalized with AF were enrolled in this study. The X-tile software indicated that the optimal cutoff value of LMR was 2.67. A total of 1,127 pairs were generated and all the covariates were well balanced after PSM. The Cox proportional-hazards model showed that patients with the low LMR (≤ 2.67) had a higher 1-year all-cause mortality than those with the high LMR (> 2.67) in the study cohort before PSM (HR = 1.640, 95% CI: 1.437–1.872, P < 0.001) and after PSM (HR = 1.279, 95% CI: 1.094–1.495, P = 0.002). The multivariable Cox regression analysis for 28-day and 90-day mortality yielded similar results.
Conclusions

The lower LMR (≤ 2.67) was associated with a higher risk of 28-day, 90-day, and 1-year all-cause mortality, which might serve as an independent prognostic predictor in AF patients.
Transplantation of mesenchymal stem cells for prevention of acute myocardial infarction induced heart failure: Study protocol of a phase III randomized clinical trial
Authors: Attar Armin , Monabati Ahmad , Montaseri Mohammad , Vosough Massoud , Hosseini Seyed Ali , Kojouri Javad , Abdi-Ardekani Alireza , Izadpanah Peyman , Azarpira Negar , Pouladfar Gholamreza , Ramzi Mani 
Published: September 2021

Abstract
Background: Results from recent clinical trials on bone marrow mononuclear cell (BM-MNC) transplantation show that this intervention can help reduce the incidence of heart failure (HF) after acute myocardial infarction (AMI). However, no study has evaluated the effect of the transplantation of mesenchymal stem cells (MSCs) on a clinical endpoint such as HF.Methods: This single-blinded, randomized, multicenter trial aims to establish whether the intracoronary infusion of umbilical cord-derived Wharton’s jelly MSCs (WJ-MSCs) helps prevent HF development after AMI. The study will enroll 360 patients 3 to 7 days following AMI. Only patients aged below 65 years with impaired LV function (LVEF < 40%) will be included. They will be randomized (2:1 ratio) to either receive standard care or a single intracoronary infusion of 107 WJ-MSCs. The primary outcome of this study is the assessment of HF development during long-term follow-up (3 years).Results: Data will be collected until Nov 2024. Thereafter, the analysis will be conducted. Results are expected to be ready by Dec 2024. We will prepare and submit the related manuscript in accordance with the SPIRIT guidelines. Conclusions: This study will help determine whether or not the infusion of intracoronary WJ-MSCs in patients with AMI will reduce the incidence of AMI-induced HF.Trial Registration: ClinicalTrials.gov, NCT05043610, Registered 14 September 2021 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT05043610
The genomic landscape of canine diffuse large B-cell lymphoma identifies distinct subtypes with clinical and therapeutic implications
Authors: Giannuzzi Diana , Marconato Laura , Fanelli Antonella , Licenziato Luca , De Maria Raffaella , Rinaldi Andrea , Rotta Luca , Rouquet Nicole , Birolo Giovanni , Fariselli Piero , Mensah Afua , Bertoni Francesco , Aresu Luca 
Published: September 2021

Abstract
Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoid neoplasm in dogs, being characterized by a remarkable degree of clinical heterogeneity not completely explained by molecular data. This poses a major barrier to understanding the disease and response to therapy or when using dogs with DLBCL in clinical trials. We performed an integrated analysis of genome, exome and RNA sequencing in a cohort of 77 canine DLBCL to define the genetic landscape of this tumor. A wide range of signaling pathways and cellular processes were found in common with human DLBCL, but the frequencies of the most recurrently mutated genes were different overall. We developed a prognostic model integrating clinical, exonic variants and transcriptomic features to predict outcome in dogs with DLBCL. These results comprehensively define the genetic drivers of canine DLBCL and can be prospectively utilized to identify new therapeutic opportunities.
Multivariate meta-analysis of multiple outcomes: characteristics and predictors of borrowing of strength from Cochrane reviews
Authors: Hattle Miriam , Burke Danielle L. , Trikalinos Thomas , Schmid Christopher H. , Chen Yong , Jackson Dan , Riley Richard D. 
Published: September 2021

Abstract
Objectives

Multivariate meta-analysis allows the joint synthesis of multiple outcomes accounting for their correlation. This enables borrowing of strength (BoS) across outcomes, which may lead to greater efficiency and even different conclusions compared to separate univariate meta-analyses. However, multivariate meta-analysis is complex to apply, so guidance is needed to flag (in advance of analysis) when the approach is most useful.
Study design and setting

We use 43 Cochrane intervention reviews to empirically investigate the characteristics of meta-analysis datasets that are associated with a larger BoS statistic (from 0 to 100%) when applying a bivariate meta-analysis of binary outcomes.
Results

Four characteristics were identified as strongly associated with BoS: the total number of studies, the number of studies with the outcome of interest, the percentage of studies missing the outcome of interest, and the largest absolute within-study correlation. Using these characteristics, we then develop a model for predicting BoS in a new dataset, which is shown to have good performance (an adjusted R2 of 50%). Applied examples are used to illustrate the use of the BoS prediction model.
Conclusions

Cochrane reviewers currently use univariate meta-analysis methods, but our prediction model for BoS helps to flag when a multivariate meta-analysis may also be beneficial in Cochrane reviews with multiple binary outcomes. Extension to non-Cochrane reviews and other outcome types is still required.
Coral-inspired hierarchical structures for sunlight harvesting
Authors: Torres Juan Felipe , Tsuda Kaoru , Murakami Yasushi , Guo Yifan , Hosseini Sahar , Asselineau Charles-Alexis , Taheri Mahdiar , Drewes Kurt , Tricoli Antonio , Lipiński Wojciech , Coventry Joe 
Published: September 2021

Abstract

Concentrating solar thermal (CST) is an efficient renewable energy technology with low-cost thermal energy storage. CST relies on wide-spectrum solar thermal absorbers that must withstand high temperatures (> 700°C) for many years, but state-of-the-art coatings have poor optical stability. Here, we show that the largely overlooked macro-scale morphology is key to enhancing both optical resilience and light trapping. Inspired by stony-coral morphology, we developed a hierarchical coating with three tuneable length-scale morphologies: nano- (~ 120 nm), micro- (~ 3 µm) and macro-scales (> 50 µm). Our coating exhibits outstanding, stable solar-weighted absorptance of > 97.75 ± 0.04% after ageing at 850°C for more than 2,000 hours. The scalability of our coating is demonstrated on a commercial solar thermal receiver, paving the way for more reliable high-performance solar thermal systems.
Past and future trends of civil airport emissions in China, from 2010 to 2030
Authors: Wang Kai , Wang Xiaoqi , Cheng Shuiyuan , Cheng Long , Wang Ruipeng 
Published: September 2021

Abstract
This paper aims to study the trend of aircraft emission in China. The multiyear emission inventories of HC, CO, NOX, SO2 and PM2.5 in the period 2010–2030 were developed. Results show that the total amount of all targeted pollutants from China's civil airports climbed from approximately 82407 tons in 2010 to 164275 tons in 2019. It is expected that the total amount of pollutants will reach 400845 tons by 2030. Pollutant emissions had the lowest growth rate in 2019 and the highest growth rate in 2013 (4.1% and 13.3%, respectively). From 2013 to 2019, the rate of increase in airport pollutant emissions began to decline. In 2019, the emissions of HC, CO, NOX, SO2 and PM2.5 are 6251, 53614, 97059, 6248 and 1102 tons, respectively. COVID-19 had a significant impact on airport emissions. By comparing the statistical value and the predicted value of airport emissions in 2020, we found that COVID-19 reduced the emissions of ZHHH and national by 46.33% and 30.45% respectively. In 2019, the East has the highest contribution rate of 27.6%, and Xinjiang has the lowest contribution rate of 3.6%. The emissions of the seven aviation regions were in the order of east > central south > southwest > north > northeast > northwest > Xinjiang.
Contribution of the Banking Sector for Economic Growth, Case of Ethiopian Banks
Authors: ALEMU ABIYOT , G. abebe 
Published: September 2021

Abstract
Financial institutions, especially the banking sector plays a crucial role in models of economic growth. It is an essential component of investments; bank Profit/Loss, banks deposits, banks advances and Interest Earning have considerable effect on economic activity and long-term economic growth. The view that, strong financial sector performance has the key to economic growth was reflected in the development strategies and plans in many countries. In Ethiopia, the development of the financial sector is limited, the contribution to GDP is also very low, and most of the banks attention to is on similar services and commercial activities in the domestic banking areas rather than diversified and international banking services. After selection of the study variables the researchers were described the economic growth function of the nation using the GDP Model to show the contribution of deposits, investments, advances, profitability and interest earning on GDP. This study is important to the practitioners, policy makers, and potential researchers by providing recommendable solutions those mitigate the obstacles in banking sector and providing conducive financial and economic theories and models important for the banking institutions and other concerned parties. The general objective of this study is to evaluate the contribution of the banking sector for the growth of GDP of the nation, more specifically it evaluate or measure the contribution of deposits, investments, advances, profitability, and interest earning on GDP of the nation. The appropriate research design adopted for this study was descriptive. From the total of 19 private and public banks in Ethiopia 5 banks were purposely selected (1 public and 4 private) for this study. Secondary sources of data were used for the analysis. All secondary data were collected from the different official publications of respected banks, annual reports and National bank of Ethiopia for five years (2009-2013 GC). The collected data were analyzed with the use of the SPSS (statistical package for the social sciences) program 20v. The percentage, mean, standard deviation, coefficient of variation, correlation and multiple regressions were utilized. The finding shows that Deposit, Investment, Advances, profitability, and Interest earned by Banks have significant effect on the GDP growth of the Nation. The percentage share to GDP in the sector was increased from time to time with an average of 22%, 11%, 18%, 0.86%, and 1.2% respectively.