bluuebunny/crossref_metadata_2025_split huggingface dataset:
New Wind-Wave Climate Records in the Western Mediterranean Sea
Authors: AMAROUCHE Khalid , Bingölbali Bilal , Akpinar Adem 
Published: July 2021

Abstract
This study presents a detailed analysis of changes in wind and wave climate in the Western Mediterranean Sea (WMed), based on 41 years of accurate wind and wave hindcasts. The purpose of this research is to assess the magnitude of recent changes in wave climate and to locate the coastal areas most affected by these changes. Starting from the Theil-Sen slope estimator and the Mann Kendall test, trends in mean and Max significant wave heights (SWH) and wind speed (WS) are analyzed simultaneously on seasonal and annual scales. Thus, the new wave records observed since 2010 have been located spatially and temporally using a simple spatial analysis method, while the increases in maximum wave heights over the last decade have been estimated and mapped. This work was motivated by evidence pointed out by several authors concerning the influence of global climate change on the local climate in the Mediterranean Sea and by the increase in the number and intensity of wave storm events over recent years. Several exceptional storms have recently been observed along the Mediterranean coasts, including storm Adrian in 2018 and storm Gloria in 2020, which resulted in enormous damage along the French and Spanish coasts. The results of the present study reflect a worrying situation in a large part of the WMed coasts. Most of the WMed basin experiences a significant increasing trend in the annual Max of SWH and WS with evident inter-seasonal variability that underlines the importance of multi-scale analysis to assess wind and wave trends. Since 2013, about half of the WMed coastline has experienced records in wave climate, not recorded at least since 1979, and several areas have experienced three successive records. Several WMed coasts are experiencing a worrying evolution of the wave climate, which requires a serious mobilization to prevent probable catastrophic wave storms and ensure sustainable and economic development.
Surgical Options for Localized Renal Cell Carcinoma, A Retrospective Clinical Study Based on Tumor Size
Authors: Li Jianyue , Li Xiang , Jiang Ziyu , Hu Canhong , Liu Jingbing , Liu Baorui , Huo Jiege 
Published: July 2021

Abstract
PurposeAlthough many studies have explored the options of radical nephrectomy (RN) and nephron sparing surgery (NSS) for localized renal cell carcinoma (RCC), the answer to this question remains unclear. This study aims to compare the long-term prognostic differences between RN and NSS among different sizes of localized RCC.MethodsThis study retrospectively included 80,439 T1-T4 N0 M0 patients who underwent RN or NSS based on the Surveillance, Epidemiology, and End Results database. We calculated the 10-year overall survival (OS) and cancer specific survival of patients with RCC. We also evaluated the risk of cardiovascular death in patients using competing risk models for RN and NSS.ResultsOur analysis showed that patients who underwent NSS had a more prolonged OS of 5 and 10 years when the tumor size was less than 8.5cm and 7.2cm. Compared to RN, NSS does not appear to improve OS in large (> 7.2cm) RCC patients. And stratified analysis showed that NSS for RCC less than 9.2cm may be more likely to benefit from long-term OS in younger patients (<60 years), while RCC above 7.3cm may be more suitable for RN in older patients (>=60 years). The gender-stratified results suggested male and female patients may be more suitable for NSS for RCC below 6.4 and 7.7cm, respectively. Besides, competing risk models showed patients receiving RN have higher cumulative cardiovascular mortality.Conclusions﻿For large RCC, NSS may be very carefully selected unless there are clear indications such as isolated congenital kidney and bilateral kidney cancer.
Is bone health of young atopic dermatitis patients a significant healthcare problem?
Authors: Kim Sooyoung , Choi Jimi , Cho Moon Kyun , Kim Nam Hoon , Kim Sin Gon , Kim Kyeong Jin 
Published: July 2021

Abstract
Background Atopic dermatitis (AD) incidence has increased over the past decades, especially among young adults. However, their bone health has not been clearly elucidated with discordant results. Objective We aimed to investigate the bone mineral density (BMD) measured by double energy X-ray absorptiometry and Z-score at the lumbar spine, femur neck, and total femur to evaluate the risk of osteoporosis in men aged <50 years and premenopausal women with AD.Methods The Korea National Health and Nutrition Examination Survey 2007-2009 data were used in this case-control cohort study. We included young AD patients (aged 19≤ and <50 years) diagnosed by a doctor and compared these patients with 1:5 propensity score weighting controls by age, sex, body mass index (BMI), vitamin D level, and alcohol/smoking status. Results We analyzed 311 (weighted n=817,014) AD patients and 1,555 (weighted n=4,155,855) controls. BMD at the lumbar spine was significantly lower in the male AD group than in the male control group (mean ± SE, 0.989 ± 0.002 vs. 0.954 ± 0.016, P = 0.03) while BMDs at the femur neck and total femur were comparable. For women, BMDs at the three sites were not significantly different between the AD and control groups. Low bone mass (defined by a Z-score of ≤2.0) was not significantly different between the AD and control groups in both sexes. Conclusions Bone health, especially BMD and Z-score, in young AD patients were comparable with those without AD. AD was not a risk factor for low BMD.
A Case of Primary CNS Embryonal Rhabdomyosarcoma with PAX3-NCOA2 Fusion and Systematic Meta-Review
Authors: Tanaka Ryuma , Inoue Kyohei , Yamada Yuji , Yoshida Masanori , Shima Haruko , Ito Jumpei , Okita Hajime , Miwa Tomoru , Kato Motohiro , Shimada Hiroyuki 
Published: July 2021

Abstract
Purpose: Primary central nervous system (CNS) rhabdomyosarcomais a rare mesenchymal tumor predominantly seen in children and associated with a poor outcome. We report a case of primary CNS rhabdomyosarcoma with PAX3-NCOA2 fusion and presenta systematic meta-review of primary CNS rhabdomyosarcoma to characterize this rare tumor.Methods: We present the case of a 6-year-old boy with primary CNS rhabdomyosarcoma in the posterior fossa. In a systematic meta-review, we compare the demographic data of primary CNS rhabdomyosarcoma with data of rhabdomyosarcoma at all sites from the SEER database and analyze clinical factors associated with survival outcome.Results: Our patient underwent gross total resectionand receivedvincristine, actinomycin-D, cyclophosphamide with early introduction of concurrent focal radiation and remained alive with no evidence of disease for 2 years after the end of therapy. Histopathological review revealed embryonal-type rhabdomyosarcoma, and whole-transcriptome analysis revealed PAX3 (EX6)-NCOA2 (EX12) fusion. In all, 77 cases of primary CNS rhabdomyosarcoma were identified through the meta-review. The demographic data of primary CNS rhabdomyosarcoma were similar to dataof rhabdomyosarcoma at all sites. Overall and event-free survival outcomes were available for 64 and 56 patients, respectively, with a 3-year OS of 29.5%and a 3-year EFS of 26.2%. The group that received trimodal treatment exhibited better survival outcomes, with a 3-year OS of 57.4%and a 3-year EFS of 46.3%.Conclusions: Primary CNS rhabdomyosarcoma shares common histological, molecular, and demographic features with non-CNS rhabdomyosarcoma. A trimodal treatment approach with early introduction of radiation therapy may result in favorable survival outcomes.
A Feedback-based Print Quality Improving Strategy for FDM 3D Printing: An Optimal Design Approach
Authors: Tamir Tariku Sinshaw , Xiong Gang , Fang Qihang , Dong Xisong , Shen Zhen , Wang Fei-Yue 
Published: July 2021

Abstract
Fused deposition modelling (FDM) 3D printing, as a supporting technology in social manufacturing and cloud manufacturing, is a rapidly growing technology in the era of industry 4.0. It produces objects with the layer-by-layer material accumulation technique. However, qualitative uncertainties are the common challenges yet. In order to assure print quality, studying the error causing parameters and minimizing their effects is important. This paper presents a feedback-based error compensation strategy, which integrates fuzzy inference system and grey wolf optimization algorithm. The objectives are twofold. First, the possible errors in FDM 3D printing are discussed in detail and optimal error causing parameters are obtained in percentage. This is used to understand the effects of the printing errors in every phase of the 3D printing process. From the nine optimization configuration trials used, Config-6 that has 100 number of iterations and 60 wolves is selected due to its higher convergence speed and best fitness value. The integral absolute error (IAE) is used as an objective function and the global minimum is achieved in the iteration interval [86, 100]. The outputs of this optimization problem is used to achieve the next objective. Second, a closed-loop quality monitoring approach comprising of inner-loops and an outer-loop is utilized. The three inner-loops are used to monitor the errors during pre-printing, printing, and post-printing, respectively. The outer-loop, on the other hand, is responsible for monitoring the aggregated errors in all the three 3D printing phases. The error compensation system simulation in Matlab is run for 10 seconds, and the results show that the "normal" range deformation factors are reached within less than 2 seconds for the inner-loops, whereas the outer-loop deformation factor is achieved within 7 seconds. The responses are within the acceptable time range.
Quality of Indonesia’s Domestic Institutions and Export Performance in the Era of Global Value Chains
Authors: Bustaman Arief , Indiastuti Rina , Budiono B , Anas Titik 
Published: July 2021

Abstract
The focus of this research is on analysing the effects of institutional quality and trade agreements on Indonesia bilateral trade in four commodity groups in the era of global value chains (GVSs). Employing a panel data gravity model of Indonesian export of four commodities to Indonesia’s 18 trading partners from 2000 to 2018, and estimating the Feasible Generalized Least Squares (FGLS) and the Poisson Pseudo Maximum Likelihood Method (PPML), the results of this study find that institutional quality plays a different role in explaining Indonesia’s export performance of those four commodities, despite the fact that institutions contribute positively. Regarding raw material and capital goods export, trading partner institutions are significant factors for Indonesian export of the two commodities. On two commodities that are relevant to Indonesia participation in the global value chain, exported intermediates and consumer goods, we find that although both domestic institutions and trading partner institutions are significant to Indonesian export, but we argue that domestic institutions contribute more. This study also reveals that through tariff reductions, Indonesian trade agreements are significant regarding export of intermediate and consumer goods, but less so for raw material and capital goods.
Spontaneous Parasitic myoma with the omental vessel: A Case report and literature review
Authors: Sunder Amala , Varghese bessy , bahzad noora , darwish basma 
Published: July 2021

Abstract
Aim: The study is the Case Report of spontaneous parasitic myoma with omental vessel, and the management at Bahrain Defense Force Hospital. Case Report: A 35years old female was diagnosed, almost 20 cm, sub serous myoma with the pedicle of 2cm from the fundus of the uterus. There was a feeding vessel from the omentum. She underwent myomectomy after the resection of pedicle and omental vessel .Post-operative period was uneventful. Conclusion: Parasitic myoma is the type of subserous uterine myoma. Generally surgical management is required for the relief of symptoms and to avoid encroachment of nearby abdominal or pelvic structures which in turn leads to further complications.
Research on Data Collection and Analysis of Second Hand House in China Based on Python
Authors: Wu Hejing , Cui Ran 
Published: July 2021

Abstract
With the rapid development of domestic Internet, more and more people choose housing leasing activities through the Internet, however, the existing housing rental information website the quantity many, but because of various advertising, information is scattered, so to HOME LINK sites, according to the position provided by the customer, accurate demand such as rent or house type, vertical search related data from the rental information website and in accordance with the provisions, the structure of the storage, rent information data to provide data for subsequent analysis. Bring users a faster experience. At the same time, we should add the reminding of the houses we are interested in and the reminding of price reduction. For the users who cannot look at their mobile phones all the time, timely reminding can help them avoid missing many desirable houses. This system is committed to solving the current people to rent a request for the search of detailed provide the keywords needed. To help make it easier for everyone who needs to rent. The system is mainly composed of data cleaning, data access, algorithm design and implementation, Python implementation of the front and back end of the system, data formatting and auxiliary decision.
Design of Intelligent Warehouse Management System Based on MVC
Authors: Lu Ping , Liu Pingping , Xu Jiangtao 
Published: July 2021

Abstract
Aiming at the problems of single function, low service level and difficult to meet customers’ demand for warehousing business in warehouse management system, a collaborative filtering recommendation algorithm is proposed. The algorithm calculates the similarity between items by analyzing user’s consumption behavior records, finds similar items to ‘target user’s favorite items, recommends similar items to ‘target user’, and designs commodity recommendation function for customer preferences, so as to improve user satisfaction and commodity sales efficiency. In order to provide users with better service experience and make the system operators easy to use, it is proposed to use B / S architecture and MVC framework model to design four modules : user management, allocation management, warehouse information management and report management, and to establish the corresponding database for unified management. Finally, the intelligent warehouse management system with high user experience satisfaction and convenient background management operation is obtained.
The use of band similarity in urban water demand forecasting as a new method
Authors: Yılmaz V. 
Published: July 2021

Abstract
Water consumption and demand by persons vary from time to time and from location to location depending on countless factors, notably, population, socio-economic and climatic variables. Today, studies that create models of water consumption of persons, using numerous methods including artificial neural networks and regression models in this regard and ensure that ongoing projections are made. In this study, parameters affecting water consumption were examined within the scope of the study area, and the parameter reduction was realized with the help of Factor Analysis. Then, as a new method, the Band Similarity method was used together with the Artificial Bee Colony optimization algorithm, urban water demand models were produced and the temporal dependence of the relevant variables was examined. As a result of the study, it was seen that the Band Similarity method improved the results obtained with the optimization algorithm and helped to understand the temporal dependencies of the variables. The fact that the Band Similarity method, which was put forward for the first time in its field, worked successfully and produced results, can be said to be the main contribution of this study to existing knowledge.
Depresión, ansiedad y estrés durante la emergencia sanitaria por Covid-19, en jefes de hogar residentes en un Asentamiento Humano en Comas
Authors: Millones-Morales Patricia Elizabeth , Gonzales-Guevara Aylyn 
Published: July 2021

Objetivos: Determinar la depresión, ansiedad y estrés durante la emergencia sanitaria por COVID-19, en jefes de hogar residentes en un asentamiento humano en Comas. Materiales y métodos: Este estudio de enfoque cuantitativo, de diseño descriptivo-transversal. La población estuvo conformada por 115 jefes de hogar residentes. La técnica utilizada fue la encuesta y el instrumento de medición fue la Escala de Trastorno de Ansiedad Generalizada (TAG-7), que es conformada por 21 ítems y 3 dimensiones, las cuales son: depresión, ansiedad y estrés. Resultados: En cuanto a la edad, la mínima fue 17 y máxima 85, siendo la edad media 41,31. En relación al sexo, 59,1% (n=68) son femenino y 40,9% (n=47) masculino. En cuanto al impacto psicológico durante la emergencia sanitaria por COVID-19, en jefes de hogar residentes donde predomino extremadamente severo con 41,7% (n=48), seguido de moderado en un 20,9% (n=24), leve con 20% (n=23), normal y extremadamente severo en un 8,7% (n=10). En relación a las dimensiones, en depresión tuvo mayor predominio el nivel moderado con 27% (n=31), en ansiedad el nivel moderado con 17,4% (n=20) y en estrés el nivel severo con 25,2% (n=29). Conclusiones: En este estudio concluyen que el impacto psicológico predomino el nivel extremadamente severo, seguido de moderado, leve, normal y extremadamente severo. En cuanto a las dimensiones, todas predomino el nivel extremadamente severo y en estrés el nivel normal.
Fair value measurement and its impact on audit fees: evidence in the Brazilian market
Authors: Bastos Edson Vinícius Pontes , Holtz Luciana , Santos Odilanei Morais dos 
Published: July 2021

Objective: The purpose is to verify the impact of using the measurement at fair value on the audit fees, differentiating even the period before and after the adoption of IFRS 13 (CPC 46).
Methodology: The research is quantitative, for testing the hypothesis raised, the multiple regression technique was used, with data available from companies listed in B3 for the period between 2010 and 2016.
Results: The evidence indicates that the complexity and subjectivity of fair value is recognized by the audit firms, that is, audit firms recognize that fair value measurement implies more effort and that the associated audit risk rises, leading firms to charge of a risk premium for the provision of the service. However, it was not possible to confirm that auditors' fees increased after the adoption of IFRS13 (CPC 46).
Contributions of study: Theoretical/methodological - The study contributes to understanding the impacts of adopting international accounting standards, in this specific case on audit fees. Social/management - Given the evidence that there is a higher audit cost associated with the greater complexity of information in a fair value environment, companies can develop mechanisms to minimize the uncertainty of the information to be audited.
Exploring CNS Effects of American Traditional Medicines using Zebrafish
Models
Authors: Kalueff Allan V. , de Abreu Murilo S. , Costa Fabiano , Giacomini Ana C.V.V. , Demin Konstantin A. , Petersen Elena V. , Rosemberg Denis B. 
Published: July 2021

:
Although American traditional medicine (ATM) has been practiced for millennia, its
complex multi-target mechanisms of therapeutic action remain poorly understood. Animal models
are widely used to elucidate the therapeutic effects of various ATMs, including their modulation of
brain and behavior. Complementing rodent models, the zebrafish (Danio rerio) is a promising novel
organism in translational neuroscience and neuropharmacology research. Here, we emphasize the
growing value of zebrafish for testing neurotropic effects of ATMs and outline future directions of
research in this field. We also demonstrate the developing utility of zebrafish as complementary
models for probing CNS mechanisms of ATM action and their potential to treat brain disorders.
Comparative Study of Valency-Based Topological Indices for Tetrahedral Sheets of Clay Minerals
Authors: Raza Hassan , Nadeem Muhammad Faisal , Ahmad Ali , Asim Muhammad Ahsan , Azeem Muhammad 
Published: July 2021

Introduction:
Intercapillary research in mathematics and other pure sciences areas has always helped
humanity quantify natural phenomena.

Materials & Method:
This article also contributes to which valency-based topological indices are implemented
on tetrahedral sheets of clay minerals. These indices have been used for a long time and are considered the most
powerful tools to quantify chemical graphs.

Results:
The atoms in the chemical compound and the bonds between the atoms are depicted as the graph’s
vertices and edges, respectively.

Conclusion:
The valency (or degree) of a vertex in a graph is the number of edges incident to that vertex. In this
article, various degree-based indices and their modifications are determined to check each types’ significance.
Prediction of lncRNA-disease Associations Based on Robust Multi-label Learning
Authors: Zhang Jiaxin , Sun Quanmeng , Liang Cheng 
Published: July 2021

Background:
Long non-coding RNAs (lncRNAs) are nonprotein-coding transcripts of more
than 200 nucleotides in length. In recent years, studies have shown that long non-coding RNAs
(lncRNA) play a vital role in various biological processes, complex disease diagnosis, prognosis, and
treatment.

Objective:
Analysis of known lncRNA-disease associations and the prediction of potential lncRNA-disease associations are necessary to provide the most probable candidates for subsequent experimental validation.

Methods:
: In this paper, we present a novel robust computational framework for lncRNA-disease association
prediction by combining the ℓ1-norm graph with multi-label learning. Specifically, we first construct
a set of similarity matrices for lncRNAs and diseases using known associations. Then, both
lncRNA and disease similarity matrices are adaptively re-weighted to enhance the robustness via the ℓ1-
norm graph. Lastly, the association matrix is updated with a graph-based multi-label learning framework
to uncover the underlying consistency between the lncRNA space and the disease space.

Results:
: We compared the proposed method with the four latest methods on five widely used data sets.
The experimental results show that our method can achieve comparable performance in both five-fold
cross-validation and leave-one-disease-out cross-validation prediction tasks. The case study of prostate
cancer further confirms the practicability of our approach in identifying lncRNAs as potential prognostic
biomarkers.

Conclusion:
Our method can serve as a useful tool for the prediction of novel lncRNA-disease associations.