nils-herrmann/clean_scirepeval huggingface dataset:
A population based cohort study of the effect of Caesarean section on subsequent fertility.
Venue: Human reproduction
Year: 2014

Is there an association between Caesarean section and subsequent fertility?  There is no or only a slight effect of Caesarean section on future fertility.  Previous studies have reported that delivery by a Caesarean section is associated with fewer subsequent pregnancies and longer inter pregnancy intervals. The interpretation of these findings is difficult because of significant weaknesses in study designs and analytical methods, notably the potential effect of the indication for Caesarean section on subsequent delivery.  Retrospective cohort study of 1 047 644 first births to low risk women using routinely collected, national administrative data of deliveries in English maternity units between 1 April 2000 and 31 March 2012.  Primiparous women aged 15 40 years who had a singleton, term, live birth in the English National Health Service were included. Women with high risk pregnancies involving placenta praevia, pre eclampsia, eclampsia (gestational or pre existing) hypertension or diabetes were excluded from the main analysis. Kaplan Meier analyses and Cox proportional hazard models were used to assess the effect of mode of delivery on time to subsequent birth, adjusted for age, ethnicity, socio economic deprivation and year of index delivery.  Among low risk primiparous women, 224 024 (21.4% were delivered by Caesarean section. The Kaplan Meier estimate of the subsequent birth rate at 10 years for the cohort was 74.7% Compared with vaginal delivery, subsequent birth rates were marginally lower after elective Caesarean for breech (adjusted hazard ratio, HR 0.96, 95% CI 0.94 0.98) Larger effects were observed after elective Caesarean for other indications (adjusted HR 0.81, 95% CI 0.78 0.83) and emergency Caesarean (adjusted HR 0.91, 95% CI 0.90 0.93) The effect was smallest for elective Caesarean for breech, and this was not statistically significant in women younger than 30 years of age (adjusted HR 0.98, 95% CI 0.96 1.01) LIMITATIONS,  We used birth cohorts from maternity units with good quality parity information. The data are likely to be nationally representative because the characteristics of the deliveries in included and omitted units were similar. There may be residual bias in our adjusted results due to unmeasured maternal factors such as obesity and voluntary absence of conception. Any residual bias would lead to an overestimate of the effect of Caesarean section on fertility, and the true effect is therefore likely to be smaller than the effect reported in our study.  Our results provide strong evidence that there is no or only a slight effect of Caesarean section on future fertility. The clinical and social circumstances leading to the Caesarean section have a greater effect on future fertility than the Caesarean section itself. This finding is important in light of rising Caesarean section rates.  IG U is supported by the Lindsay Stewart R&D Centre, Royal College of Obstetricians and Gynaecologists, UK. The authors have no conflicts of interest to declare.
Machine learning models for credit analysis improvements: Predicting low income families' default
Venue: Appl. Soft Comput.
Year: 2019

The main objective of this study is to investigate the behaviour of default prediction models based on credit scoring methods and computational techniques with machine learning algorithms. The predictive capabilities of the models were compared to identify default prediction mechanisms in the "My Home, My Life" Program (Programa "Minha Casa, Minha Vida" PMCMV) The PMCMV is one of the largest government initiatives in the world to finance home ownership in the low income population. Implemented by the Brazilian government, the programme has provided financing in excess of USD 84 billion and by 2016 had already contracted for the construction of over 4.5 million housing units, with 3.3 million units already delivered. The models developed in this study involve different time intervals for default prediction as well as analysis without the use of traditional discriminatory variables (gender, age, and marital status) Three measurements were used to evaluate the quality of the prediction models: area under the ROC curve, the Kolmogorov Smirnov index, and the Brier score. The results indicated that (1) the accuracy of the models improves as the number of days overdue used to define the default variable increases; (2) the best prediction results were obtained with traditional ensemble techniques in this case Bagging (BG) Random Forest (RF) and Boosting; and (3) there was a negative impact on all criteria when a smaller number of observations was used, especially on the type II error. It was also found that the discriminatory power of the credit risk rating system is preserved when removing discriminatory variables from the models. Applying the BG algorithm, which is the best prediction method, a default rate of 11.80% could be reduced to 2.95% which leads to a selection that would result in 197,905 fewer delinquent contracts in the PMCMV, thus representing a savings of approximately USD 3.0 billion in credit losses.
Employee Turnover Intention through Human Resource Management Practices: A Review of Literature
Year: 2020

This paper focused on analysing the results of previous studies conducted by different researchers to examine the effect on turnover intention of HRM activities such as training and development, job security, performance appraisal and compensation. This research would also investigate the methods of human resource management as an independent variable and the intention of turnover as a dependent variable. A quantitative approach to assessing the effects of each variable has been implemented on the basis of these research objectives. The study therefore concluded that HRM activities can be applied as a method for the turnover intention of the employee.
Local binary pattern metric based multi focus image fusion
Venue: Optics Laser Technology
Year: 2019

Multi focus image fusion is to integrate the partially focused images into one single image which is focused everywhere. Nowadays, it has become an important research topic due to the applications in more and more scientific fields. However, preserving more information of the low contrast area in the focus area and maintaining the edge information are two challenges for existing approaches. In this paper, we address these two challenges with presenting a simple yet efficient multi focus fusion method based on local binary pattern (LBP) In our algorithm, we measure the clarity using the LBP metric and construct the initial weight map. And then we use the connected area judgment strategy (CAJS) to reduce the noise in the initial map. Afterwards, the two source images are fused together by weighted arranging. The experimental results validate that the proposed algorithm outperforms state of the art image fusion algorithms in both qualitative and quantitative evaluations, especially when dealing with low contrast regions and edge information.
Self Driving Car Acceptance and the Role of Ethics
Venue: IEEE Transactions on Engineering Management
Year: 2020

Mass availability of self driving cars is ante portas and independent of their sophistication, unavoidable fatal accidents will occur where the car will have to take life and death decisions. However, there is a knowledge gap, since the impact, that the ethical frameworks (used in the car's decision making process) have on the overall acceptance of self driving cars, is not well investigated. This paper addresses the key question: In the scope of unavoidable accidents, what is the effect of different ethical frameworks governing self driving car decision making, on their acceptance? This quantitative positivist research investigates the link of selected ethical frameworks, i.e. utilitarianism, deontology, relativism, absolutism (monism) and pluralism, to the acceptance of self driving cars. It is hypothesized that they have an impact on the acceptance of the self driving cars, and a model linking them to it is proposed and assessed. All five selected ethical frameworks investigated are found to have an effect on self driving car acceptance, which implies actions for several involved stakeholders as these may be a deciding factor for the success or failure of the self driving car market introduction.
Genistein ameliorates parathyroid hormone induced epithelial to mesenchymal transition and inhibits expression of connective tissue growth factor in human renal proximal tubular cells
Venue: Archives of medical science AMS
Year: 2013

Genistein, a soybean and soy based product, has been reported to inhibit the growth of a wide range of cancer cells, but there is no evidence concerning its treatment of chronic kidney disease. The aim was to investigate whether genistein has potential to inhibit parathyroid hormone (PTH) induced renal interstitial fibrosis.  Using human renal tubular epithelial HK 2 cells, a smooth muscle actin (a SMA) was assessed by using immunofluorescence detection. a Smooth muscle actin, E cadherin and connective tissue growth factor (CTGF) were measured by Western blot analysis. The promoter activity of the CTGF gene was examined by the luciferase reporter assay.  When cells were treated with PTH (0.1 nM) for 48 h, a SMA protein expression was induced significantly, the protein expression of E cadherin decreased substantially, and the promoter activity of the CTGF gene as well as its mRNA and protein expression levels increased (p 0.01) Interestingly, genistein effectively inhibited PTH induced a SMA expression, restored E cadherin expression, decreased mRNA and protein expression of CTGF, and suppressed the promoter activity of CTGF in a dose dependent manner.  Genistein has the ability to block the biomarker for renal transdifferentiation and epithelial to mesenchymal transition, a SMA, following PTH treatment and inhibit CTGF expression in human renal tubular epithelial cells; these might be important modes of actions that contribute to genistein anti fibrogenic effects and may have great implications for its potential in clinical treatment of renal interstitial fibrosis.
Forecasting Realized Volatility Matrix With Copula Based Models
Year: 2020

Multivariate volatility modeling and forecasting are crucial in financial economics. This paper develops a copula based approach to model and forecast realized volatility matrices. The proposed copula based time series models can capture the hidden dependence structure of realized volatility matrices. Also, this approach can automatically guarantee the positive definiteness of the forecasts through either Cholesky decomposition or matrix logarithm transformation. In this paper we consider both multivariate and bivariate copulas; the types of copulas include Student's t, Clayton and Gumbel copulas. In an empirical application, we find that for one day ahead volatility matrix forecasting, these copula based models can achieve significant performance both in terms of statistical precision as well as creating economically mean variance efficient portfolio. Among the copulas we considered, the multivariate t copula performs better in statistical precision, while bivariate t copula has better economical performance.
Travel cost analysis of an urban protected area and parks in Singapore: a mobile phone data application.
Venue: Journal of environmental management
Year: 2020

Big data have the potential to improve nonmarket valuation, but their application has been scarce. To test this potential, we apply mobile phone data to the zonal travel cost method and measure recreational ecosystem services from Bukit Timah (representing an urban protected area) and Jurong Lake Gardens (an urban recreational park) in Singapore. The study results show that the annual recreational benefits of the recreational park (S$54,698,761 to S$66,805,454) outweighed the benefits of the protected area (S$6,947,974 to S$9,068,027) The count data structure reduced the flexibility of the mobile phone data application. Compared to survey data, however, mobile phone data could prevent random errors and visitor memory biases; monitor impacts of site quality changes over time; count visitors from multiple entrances; and be cost efficient. Overall, these results highlight the potential of mobile phone data application to improve travel cost analysis.
UPAYA MEMPERBAIKI HASIL BELAJAR SERVIS FOREHAND TINGGI DALAM PEMBELAJARAN BULU TANGKIS DENGAN PENERAPAN GAYA MENGAJAR INKLUSI PADA SISWA KELAS IX SMP NEGERI 22 SURABAYA TAHUN PELAJARAN 2018 2019
Year: 2019

Penelitian ini bertujuan untuk memperbaiki dan meningkatkan hasil belajar bulutangkis servis forehand tinggi dengan menggunakan gaya mengajar inklusi. Jenis penelitian tindakan kelas, menggunakan pendekatan gaya mengajar iklusi. Objek penelitian adalah peserta didik kelas IX SMP Negeri 22 Surabaya. Rancangan penelitian mengunakan model Kemmis dan Mc. Taggart yang terdiri dari empat tahapan yaitu 1) Perencanaan tindakan, 2) Pelaksanaan tindakan, 3) observasi dan 4) refleksi. Berdasarkan analisis data menunjukkan hasil belajar bulutangkis servis forehand tinggi pada siklus I sebesar 38,46% (10 orang) kemudian pada siklus II meningkat sebesar 92.30% (24 orang) dinyatakan tuntas. Hasil belajar bulutangkis servis forehand tinggi peserta didik secara keseluruhan pada siklus I masih mencapai 0 KKM 75 dinyatakan belum tuntas belajar, kemudian meningkat pada siklus II menjadi 75 KKM 100 dinyatakan sudah tuntas belajar, sehingga capaian pada siklus II ada peningkatan 41.66% dan penuruan 12.50% Hasil analisis menunjukkan ketuntasan hasil belajar servis forehand tinggi dengan penerapan gaya mengajar inklusi tertuang pada siklus I ke siklus II mengalami perbaikan dan perubahan peningkatan ketuntasan secara individual maupun secara klasial. Kata Kunci servis forehand tinggi, gaya mengajar inklusi
Iconicity in the syntax and lexical semantics of sound symbolic words in Japanese
Year: 2015

This study offers a response to Akita (2013a) who proposes a relation between the lexical semantics of sound symbolic words and their realizations in a syntactic structure, drawing on a universal lexical hierarchy termed the Lexical Iconicity Hierarchy (LIH) This study examines Akita's proposal drawing on data from Japanese mimetics. It suggests the LIH based proposal may be difficult to maintain in its current format on the basis of (i) a frequency count of mimetics entered in a mid sized mimetic dictionary and (ii) the syntactic characteristics of phonomimes (e.g. bukubuku 'bubbling' working within the framework of Role and Reference Grammar.
Class Agnostic Weighted Normalization of Staining in Histopathology Images Using a Spatially Constrained Mixture Model
Venue: IEEE Transactions on Medical Imaging
Year: 2020

The colorless biopsied tissue samples are usually stained in order to visualize different microscopic structures for diagnostic purposes. But color variations associated with the process of sample preparation, usage of raw materials, diverse staining protocols, and using different slide scanners may adversely influence both visual inspection and computer aided image analysis. As a result, many methods are proposed for histopathology image stain normalization in recent years. In this study, we introduce a novel approach for stain normalization based on learning a mixture of multivariate skew normal distributions for stain clustering and parameter estimation alongside a stain transformation technique. The proposed method, labeled "Class Agnostic Weighted Normalization" (short CLAW normalization) has the ability to normalize a source image by learning the color distribution of both source and target images within an expectation maximization framework. The novelty of this approach is its flexibility to quantify the underlying both symmetric and nonsymmetric distributions of the different stain components while it is considering the spatial information. The performance of this new stain normalization scheme is tested on several publicly available digital pathology datasets to compare it against state of the art normalization algorithms in terms of ability to preserve the image structure and information. All in all, our proposed method performed superior more consistently in comparison with existing methods in terms of information preservation, visual quality enhancement, and boosting computer aided diagnosis algorithm performance.
The interplay of stress and mowing disturbance for the intensity and importance of plant interactions in dry calcareous grasslands.
Venue: Annals of botany
Year: 2012

There is still debate regarding the direction and strength of plant interactions under intermediate to high levels of stress. Furthermore, little is known on how disturbance may interact with physical stress in unproductive environments, although recent theory and models have shown that this interplay may induce a collapse of plant interactions and diversity. The few studies assessing such questions have considered the intensity of biotic interactions but not their importance, although this latter concept has been shown to be very useful for understanding the role of interactions in plant communities. The objective of this study was to assess the interplay between stress and disturbance for plant interactions in dry calcareous grasslands.  A field experiment was set up in the Dordogne, southern France, where the importance and intensity of biotic interactions undergone by four species were measured along a water stress gradient, and with and without mowing disturbance.  The importance and intensity of interactions varied in a very similar way along treatments. Under undisturbed conditions, plant interactions switched from competition to neutral with increasing water stress for three of the four species, whereas the fourth species was not subject to any significant biotic interaction along the gradient. Responses to disturbance were more species specific; for two species, competition disappeared with mowing in the wettest conditions, whereas for the two other species, competition switched to facilitation with mowing. Finally, there were no significant interactions for any species in the disturbed and driest conditions.  At very high levels of stress, plant performances become too weak to allow either competition or facilitation and disturbance may accelerate the collapse of interactions in dry conditions. The results suggest that the importance and direction of interactions are more likely to be positively related in stressful environments.
Supporting information retrieval from electronic health records: A report of University of Michigan's nine year experience in developing and using the Electronic Medical Record Search Engine (EMERSE)
Venue: J. Biomed. Informatics
Year: 2015

This paper describes the University of Michigan's nine year experience in developing and using a full text search engine designed to facilitate information retrieval (IR) from narrative documents stored in electronic health records (EHRs) The system, called the Electronic Medical Record Search Engine (EMERSE) functions similar to Google but is equipped with special functionalities for handling challenges unique to retrieving information from medical text.  Key features that distinguish EMERSE from general purpose search engines are discussed, with an emphasis on functions crucial to (1) improving medical IR performance and (2) assuring search quality and results consistency regardless of users' medical background, stage of training, or level of technical expertise.  Since its initial deployment, EMERSE has been enthusiastically embraced by clinicians, administrators, and clinical and translational researchers. To date, the system has been used in supporting more than 750 research projects yielding 80 peer reviewed publications. In several evaluation studies, EMERSE demonstrated very high levels of sensitivity and specificity in addition to greatly improved chart review efficiency.  Increased availability of electronic data in healthcare does not automatically warrant increased availability of information. The success of EMERSE at our institution illustrates that free text EHR search engines can be a valuable tool to help practitioners and researchers retrieve information from EHRs more effectively and efficiently, enabling critical tasks such as patient case synthesis and research data abstraction.  EMERSE, available free of charge for academic use, represents a state of the art medical IR tool with proven effectiveness and user acceptance.
Does Gamification Improve the Training of Software Testers? A Preliminary Study from the Industry Perspective*
Venue: SBQS
Year: 2020

Software testing is an essential activity in software companies to ensure the quality of their systems. Nevertheless, the most recent studies demonstrate that there is a lack of qualified professionals in this area.  To check whether the gamification contributes to the training of software testers in the industry, analyzing their motivation and test cases designed by them.  For this, we conducted an experimental study with junior testers in a software company to compare gamified training against non gamified training.  We observed significant contributions from gamification in the training of software testers, especially in their motivation and quality of the test cases. We noted that non gamified training still offers contributions to software testing training. This result intensified when we embedded gamified elements in the training since we noticed a difference between groups at scenario coverage analysis.  Our results should encourage software companies to emphasize training in software testing and adopt gamified elements because software testers are more motivated in training and design better test cases from the theories of software testing.
Risk factors for acute nerve injury after total knee arthroplasty
Venue: Muscle nerve
Year: 2018

In this we study identified potential risk factors for post total knee arthroplasty (TKA) nerve injury, a catastrophic complication with a reported incidence of 0.3% 1.3%  Patients who developed post TKA nerve injury from 1998 to 2013 were identified, and each was matched with 2 controls. A multivariable logistic regression model was built to calculate odds ratios (ORs)  Sixty five nerve injury cases were identified in 39,990 TKAs (0.16% Females (OR 3.28, P 0.003) and patients with history of lumbar pathology (OR 6.12, P 0.026) were associated with increased risk of nerve injury. Tourniquet pressure 300 mm Hg and longer duration of anesthesia may also be risk factors.  Surgical planning for females and patients with lumbar pathology should be modified to mitigate their higher risk of neurologic complications after TKA. Our finding that lower tourniquet pressure was associated with higher risk of nerve injury was unexpected and requires further investigation. Muscle Nerve 57: 946 950, 2018
The development and control of late blight (Phytophtora infestans) in Europe in 2009
Year: 2010

JENS GRONBECH HANSEN (DENMARk)1, BJORN ANDERSSON (SwEDEN) RUAIRIDH BAIN ALISON LEES (SCOTLAND) RICCARDO BUGIANO (ITALy) FAyE RITCHIE (ENGLAND wALES) LINDA BUCENA (LATvIA) STEvEN kILDEA (IRELAND) LOUISE COOkE (NORTHERN IRELAND) LUDOvIC DUBOIS (FRANCE) ALEXEy FILIPPOv (RUSSIA) ASkO HANNUkkALA (FINLAND) HANS HAUSLADEN (GERMANy) ERvIN HAUSvATER (CzECH REPUBLIC) JAN HELDAk (SLOvAkIA) ARNE HERMANSEN RAGNHILD NAERSTAD (NORwAy) JOzEFA kAPSA (POLAND) MATI kOPPEL (ESTONIA) TOMkE MUSA (SwITzERLAND) ANTANAS RONIS (LITHUANIA) HUUB SCHEPERS kEES vOGELAAR (THE NETHERLANDS) PIETER vANHAvERBEkE (BELGIUM)