Miracle-dz/UniFAR-FTUs huggingface dataset:
Empirical Research about Credit Risk on Neural Network Based Bp Algorithm

The paper combines theory with practice and applies neural network technology to establish a credit risk assessment model based on BP neural network technology. The assessment model, to some extent, improves the traditional credit risk analytical approaches in our country, overcoming the defects that subjectivity exists in credit risk measurement, expanding developing route for credit risk measurement and enriching measurement methods in our country’s credit risk system. Moreover, model establishment thinking, index selection as well as data choosing are not based on theoretical research, but instead the practical situation during our country’s commercial bank loan. As the empirical study indicates that BP neural network credit risk assessment model is effective in commercial banks’ credit risk management, and it is feasible in practical application.
Reduced persistence length and fluctuation-induced interactions of directed semiflexible polymers on fluctuating surfaces

We consider directed semiflexible polymers embedded in a fluctuating surface which is governed by either surface tension or bending rigidity. The attractive interactions induced by the fluctuations of the surface reduce the rigidity of the polymers. In particular, it is shown that for arbitrarily stiff parallel polymers, there is a characteristic separation below which they prefer to bend rather than stay linear. The out-of-plane fluctuations of the polymer screen out the long-range fluctuation-induced forces, resulting in only a short-ranged effective attraction.
A Mixed-Methods Study of Students’ Success and Persistence in Biology

Undergraduate success in Science Technology Engineering and Mathematics (STEM) fields is of critical importance to the United States (U.S.) maintenance of its position as the world leader in technological innovations. Research indicates that, there is need to promote success among the undergraduates undertaking STEM fields. In an effort to address this call, a majority of research has employed a variety of empirically validated instruction strategies designed to promote undergraduate success in biological sciences. Although of integral importance, such studies have often not extensively explored the impact of motivational and attitudinal factors in tandem with demographic and educational characteristics, especially in the field of biology. The purpose of the current research was to examine the predictors of students’ success in an introductory biology course based on motivational and attitudinal variables, considered alongside demographic and educational characteristics. In addition the study sought to explore to what extent do such factors differentially predict success among underrepresented minority and first generation students within the aforementioned cohort. A total of 882 undergraduate enrolled in a first year Principles of Biology course participated in this study through surveys. Quantitative methods were utilized in the study employing multiple linear regression for data analysis. Results revealed that motivational
The LEAD Roadmap : an Integrative Framework for Utilizing and Sharing Community Resources to Enhance Understanding and Impact of Weather

Linked Environments for Atmospheric Discovery (LEAD; Plale et al. 2004, 2006; Droegemeier et al. 2005, 2007; Droegemeier 2008) is a National Science Foundation (NSF) Large Information Technology Research (ITR) grant that has pioneered new approaches for integrating complex weather data, assimilation, modeling, mining, and cyberinfrastructure systems. LEAD empowers researchers and students with capabilities heretofore available at only a few major universities and research or operational centers around the world, and it does so using a service-oriented architecture similar in many respects to the familiar Amazon.com where storage and compute resources and services are “in the cloud”. By managing the complexity of inter-operative cyber tools and providing flexibility and ease in how they can be linked, LEAD allows users to focus their time on solving the science and engineering problems at hand, providing a means for more deeply understanding the tools and techniques being applied rather than the nuances of data formats, communication protocols, and job execution environments.
Pancreatic Fistula after Pancreatectomy: Definitions, Risk Factors, Preventive Measures, and Management—Review

Resection of pancreas, in particular pancreaticoduodenectomy, is a complex procedure, commonly performed in appropriately selected patients with benign and malignant disease of the pancreas and periampullary region. Despite significant improvements in the safety and efficacy of pancreatic surgery, pancreaticoenteric anastomosis continues to be the “Achilles heel” of pancreaticoduodenectomy, due to its association with a measurable risk of leakage or failure of healing, leading to pancreatic fistula. The morbidity rate after pancreaticoduodenectomy remains high in the range of 30% to 65%, although the mortality has significantly dropped to below 5%. Most of these complications are related to pancreatic fistula, with serious complications of intra-abdominal abscess, postoperative bleeding, and multiorgan failure. Several pharmacological and technical interventions have been suggested to decrease the pancreatic fistula rate, but the results have been controversial. This paper considers definition and classification of pancreatic fistula, risk factors, and preventive approach and offers management strategy when they do occur.
Few are Called, Fewer are Chosen: Elite Reproduction in U.S. Academic Accounting

Abstract Previous work on academic accounting in the U.S. has documented impressive concentrations in publications and labor market success by faculty with credentials from a relatively small number of prestigious universities. However, this work left open the pre-doctoral origins of people producing this work, and therefore could not rule out the operation of a meritocracy. Utilizing the theoretical contributions of Bourdieu, this paper argues that elite institutions constitute a unique positioning of symbolic capital that favors a particular type of candidate over equally able others. Through systematic personnel movements into doctoral programs, elites within the discipline are able to reproduce. A study of faculty cultural capital acquired from previous matriculation at elite universities offers empirical support for these ideas. The results suggest that previous studies of concentration in academic accounting are set in motion because of this systematic selection process.
Dynamic quality control in agile methodology for improving the quality

The advantages of software development using Agile methodology is a well researched and documented topic. However, testing in agile software methodologies is not as well researched. The four values and twelve principles of the Agile Manifesto say nothing concrete about testing or quality assurance. An agile approach such as Scrum also doesn't talk much about Quality Assurance. It's already proven that agile processes produce software fast, but does the software produced adhere to quality? Can we, in some way, improve the quality in agile methodology by focusing on Dynamic Quality Control? There is no notable evidence in existing literature that testing in agile methodologies improve the quality of software compared to other methodologies. We chose a real world project and employed three teams to work on the same project following three different methodologies (Waterfall, Agile and Agile with Dynamic Quality Control) and collected data to compare the effectiveness of testing in each methodology in real world project scenario. We concentrated on five metrics (Defect count, Test coverage, Team maturity, Resource utilization and Lean) to study and compare the change in quality of software when using different methodologies.
Pain detection from facial characteristics using supervised descent method

Current methods of assessing pain depend almost entirely on verbal report such as clinical interview or questionnaires of the patients. Pain being a symptom that can neither be felt nor seen, poses a major problem for the medical personnel involved in pain management since there are no accurate objective measures to establish the extent of pain the patient is suffering from when using a remote assistive medical system. The verbal report grading pain has obvious discrepancies, especially when it comes to children or people with limited ability to communicate (i.e. the mute, mentally impaired, or patients having assisted breathing). When designing a medical assistive system measuring pain in an efficient way is of great importance. In this paper we proposes an algorithm for both automatic pain recognition (i.e. pain/no pain presence in human) and continuous pain intensity estimation based on facial expression analysis. To locate specific landmarks in the face we used Supervised Descent Method (SDM) and then extract feature vectors using Scale Invariant Feature Transform (SIFT). For the recognition task we build a classier based on Support Vector Machines (SVM) and for the continuous pain intensity estimation task we trained linear regressor. The experiments with patients with shoulder pain show very good recognition rate (more than 95.7%). For the pain intensity estimation we reached an average Mean Squared Error of 1.28 and Correlation coefficient of 0.59. The recorded results demonstrate performance that exceeds state-of-the-art results on a standard data set.
Identifying Parenting Myths in the Sociocultural Context of Kermanshah Province, Iran: A Qualitative Study

Introduction: The aim of the present study was the identification and extraction of parenting myths in the sociocultural context of Kermanshah Province, Iran. Method: This qualitative research was conducted through the phenomenological approach. Therefore, 15 parents were selected through purposive sampling method. Data were collected through in-depth interviews. Results: The data analysis and coding led to 5 original themes of trait, effect, responsibility, relationship, and priority and 17 sub-themes in parent’s cognition system. Conclusion: Parenting myths are the criteria for parents’ performance. Thus, parents experience stressful parenting because they cannot fulfill these criteria. Parenting Myths the Sociocultural
A new genetic clustering based approach in aspect mining

Clustering is a division of data into groups of similar objects. Aspect mining is a process that tries to identify crosscutting concerns in existing software systems. The goal is to refactor the existing systems to use aspect oriented programming, in order to make them easier to maintain and to evolve. This paper aims at presenting a new genetic clustering based approach in aspect mining. Clustering is used in order to identify crosscutting concerns. We evaluate the obtained results from the aspect mining point of view based on two new quality measures. The proposed approach is compared with another clustering approach in aspect mining ([1]) and a case study is also reported.
A STUDY OF PROBLEM DRINKERS IN A GENERAL HOSPITAL

349 new admissions in the wards of Medicine, General Surgery & Orthopedics in a general hospital were screened with MAST & AUDIT for problem use of alcohol. Problem drinking was present in 14.6% of the inpatients. The severity and the need for additional treatment were measured with Addiction Severity Index (ASI). Majority of the patients had problems in more than one ar? a. Nevertheless, only one fourth of the patients were referred for psychiatric treatment. The findings indicate the need to develop services towards the recognition and referrals of the problem drinkers in general hospitals
An Introduction to Liquid Chromatography– Mass Spectrometry Instrumentation Applied in Plant Metabolomic Analyses † Untargeted Plant Metabolomics and the Potential of Liquid Chromatography Mass Spectrometry

Over the past decade the application of non-targeted high-throughput metabolomic analysis within the plant sciences has gained ever increasing interest and has truly established itself as a valuable tool for plant functional genomics and studies of plant biochemical composition. Whilst proton nuclear magnetic resonance (1 H-NMR) spectroscopy is particularly appropriate for the analysis of bulk metabolites and gas chromatography mass spectrometry (GC-MS) to the analysis of volatile organic compounds (VOC's) and derivatised primary metabolites, liquid chromatography (LC)-MS is highly applicable to the analysis of a wide range of semi-polar compounds including many secondary metabolites of interest to plant researchers and nutritionists. In view of the recent developments in the separation sciences, leading to the advent of ultra high performance liquid chromatography (UHPLC) and MS based technology showing the ever improving resolution of metabolite species and precision of mass measurements (sub-ppm accuracy now being achievable), this review sets out to introduce the background and update the reader upon LC, high performance (HP)LC and UHPLC, as well as the large range of MS instruments that are being applied in current plant metabolomic studies. As well as covering the theory behind modern day LC-MS, the review also discusses the most relevant metabolomics applications for the wide range of MS instruments that are currently being applied to LC. Metabolomics has proven to be a valuable tool for the comprehensive profi ling of plant derived samples for the study of plant systems (Fiehn et al. Plants provide a great challenge in metabolomics due to the rich chemical diversity of metabolites that they possess across a huge range of concentrations ; estimates of 100000–200000 metabolites have been made for the plant kingdom (Oksman-Caldentey and Inzé, 2004). Currently no single analytical method or combination of analytical methods (i.e. chromatography combined with mass spec-trometry (MS) or nuclear magnetic resonance (NMR) spectroscopy is capable of detecting all metabolites within a given biological sample (Sumner et al., 2003; Hall, 2006; Allwood et al., 2008). Over the past decade many methods for the high-throughput metab-olomic analysis of plant derived samples have been established for gas chromatography combined with MS (GC-MS; Fiehn et al. 1 H-NMR has proven to be an appropriate tool for untargeted plant metabolomics, especially where studies focus upon samples that contain highly abundant bulk metabolite species, for example sugars in fruits (Biais et al., 2009). 1 H-NMR has the advantage that it produces signals that correlate directly and …
Time-travel Translator: Automatically Contextualizing News Articles

Fully understanding an older news article requires context knowledge from the time of article creation. Finding information about such context is a tedious and time-consuming task, which distracts the reader. Simple contextualization via Wikification is not sufficient here. The retrieved context information has to be time-aware, concise (not full Wikipages) and focused on the coherence of the article topic. In this paper, we present Contextualizer, a web-based system that acquires additional information for supporting interpretations of a news article of interest that requires a mapping, in this case, a kind of time-travel translation between present context knowledge and context knowledge at time of text creation. For a given article, the system provides a GUI that allows users to highlight their interested keywords which are then used to construct appropriate queries for retrieving contextualization candidates. Contextualizer exploits different kinds of information such as temporal similarity and textual complementarity to re-rank the candidates and presents to users in a friendly and interactive web-based interface.
Computed tomographic findings of radiation-induced acute adrenal injury with associated radiation nephropathy: a case report

Radiation nephropathy was first recognized in 1906. The kidney is a radiosensitive organ with a tolerance dose (5% complications in 5 years) of 20 Gray. The imaging findings of acute and chronic radiation induced renal injury are previously described. Radiation-induced adrenal injury, to our knowledge, has not been described in the literature. Unlike the kidneys and other upper abdominal organs, the adrenal glands are traditionally thought to be radio-resistant, protected from radiation-induced injury by proximity to adjacent organs and by the adrenal medulla which reportedly has increased radio-resistance. We present the computed tomographic imaging findings of a patient with acute radiation induced adrenal injury which resulted in adrenal insufficiency following radiotherapy of an adjacent thecal metastasis.
From a single discipline risk management approach to an interdisciplinary one: adaptation of FMEA to software needs

Risk management has been identified as a vitally important project management task. Hence, many risk management approaches have been developed. Unfortunately, most of them deal with the risks of a single discipline only, meaning disciplines in which either software or non-software products are developed. In contrast, nowadays many projects are highly interdisciplinary undertakings in the sense that newly developed conventional non-software products are enhanced by software. With the advent of software, many additional risks have emerged. In this paper, the differences between software and non-software products are investigated. From these differences, consequences for interdisciplinary projects are derived. It is indicated how an interdisciplinary risk management approach can cope with the consequences. An answer is given to the question of how to achieve such an interdisciplinary approach. One possible solution is presented here as an adaptation of the failure modes and effects analysis, a single discipline approach, to the needs of software. This paper is an extension of a position paper presented at the STEP2003 Workshop of Interdisciplinary Software Engineering.
A Comparison of the American Society of Cataract and Refractive Surgery post-myopic LASI K/PRK Intraocular Lens (IOL) calculator and the Ocular MD IOL calculator

Background To compare the average values of the American Society of Cataract and Refractive Surgery (ASCRS) and Ocular MD intraocular lens (IOL) calculators to assess their accuracy in predicting IOL power in patients with prior laser-in-situ keratomileusis (LASIK) or photorefractive keratectomy. Methods In this retrospective study, data from 21 eyes with previous LASIK or photorefractive keratectomy for myopia and subsequent cataract surgery was used in an IOL calculator comparison. The predicted IOL powers of the Ocular MD SRK/T, Ocular MD Haigis, and ASCRS averages were compared. The Ocular MD average (composed of an average of Ocular MD SRK/T and Ocular MD Haigis) and the all calculator average (composed of an average of Ocular MD SRK/T, Ocular MD Haigis, and ASCRS) were also compared. Primary outcome measures were mean arithmetic and absolute IOL prediction error, variance in mean arithmetic IOL prediction error, and the percentage of eyes within ±0.50 and ±1.00 D. Results The Ocular MD SRK/T and Ocular MD Haigis averages produced mean arithmetic IOL prediction errors of 0.57 and −0.61 diopters (D), respectively, which were significantly larger than errors from the ASCRS, Ocular MD, and all calculator averages (0.11, −0.02, and 0.02 D, respectively, all P < 0.05). There was no statistically significant difference between the methods in absolute IOL prediction error, variance, or the percentage of eyes with outcomes within ±0.50 and ±1.00 D. Conclusion The ASCRS average was more accurate in predicting IOL power than the Ocular MD SRK/T and Ocular MD Haigis averages alone. Our methods using combinations of these averages which, when compared with the individual averages, showed a trend of decreased mean arithmetic IOL prediction error, mean absolute upper limit of IOL prediction error, and variance, while increasing the percentage of outcomes within ±0.50 D.
Developmental perspectives in written language and literacy: In honor of Ludo Verhoeven

Research on the development on written language and literacy is inherently multidisciplinary. In this book, leading researchers studying brain, cognition and behavior, come together in revealing how children develop written language and literacy, why they may experience difficulties, and which interventions may help those who struggle. Each chapter provides an overview of a specific area of expertise, focusing on typical and atypical development, providing steps for future research, and discussing practical implications of the work. The book covers areas of bilingualism, dyslexia, reading comprehension, learning to read, atypical populations, intervention, and new media. Thus, the book presents a comprehensive overview of the current state of affairs in this field of research. The various book chapters have been written by researchers who all have collaborated at some point in their careers with Ludo Verhoeven, whose research sets the example for the importance of crossing disciplinary borders to research to take the next, important steps. The combination of the research in this book sets the stage for future research that connects various fields, and hopes to inspire anyone interested in the development of written language and literacy.
Sewing the Seams of Sensemaking: A Practical Interface for Tagging and Organizing Saved Search Results

This paper presents a usability-tested interface design that enables time-constrained analysts to organize their search results in a lightweight manner during and immediately following their search sessions. The research literature suggests that users want to lay out search results spatially in overlapping "piles," but a pilot study with a flexible canvas tool revealed that this design requires too much manipulation and has other drawbacks. This finding led to a novel hybrid design that combines structure with a flexible visual layout and which allows the analysts to quickly triage documents first and organize them later, or interweave these two processes. Two usability studies comparing the new design against a legacy tool found overwhelming preference for the new tool for saving and organizing search results. Design guidelines derived from this work could improve sensemaking interfaces for other search applications.
Elements of the B Cell Signalosome Are Differentially Affected by Mercury Intoxication

It has been suggested that environmental exposures to mercury contribute to autoimmune disease. Disruption of BCR signaling is associated with failure of central tolerance and autoimmunity, and we have previously shown that low levels of Hg2+ interfere with BCR signaling. In this report we have employed multiparametric phosphoflow cytometry, as well as a novel generalization of the Overton algorithm from one- to two-dimensional unimodal distributions to simultaneously monitor the effect of low level Hg2+ intoxication on activation of ERK and several upstream elements of the BCR signaling pathway in WEHI-231 B cells. We have found that, after exposure to low levels of Hg2+, only about a third of the cells are sensitive to the metal. For those cells which are sensitive, we confirm our earlier work that activation of ERK is attenuated but now report that Hg2+ has little upstream effect on the Btk tyrosine kinase. On the other hand, we find that signaling upstream through the Syk tyrosine kinase is actually augmented, as is upstream activation of the B cell signalosome scaffolding protein BLNK.