LLukas22/scidocs huggingface dataset:
MOOCBuddy: a Chatbot for personalized learning with MOOCs

With the proliferation of MOOCs (Massive Open Online Courses) providers, like Coursera, edX, FutureLearn, UniCampus.ro, NOVAMOOC.uvt.ro or MOOC.ro, it’s a real challenge to find the best learning resource. MOOCBuddy – a MOOC recommender system as a chatbot for Facebook Messenger, based on user’s social media profile and interests, could be a solution. MOOCBuddy is looking like the big trend of 2016, based on the Messenger Platform launched by Facebook in the mid of April 2016. Author
cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination

Single-particle electron cryomicroscopy (cryo-EM) is a powerful method for determining the structures of biological macromolecules. With automated microscopes, cryo-EM data can often be obtained in a few days. However, processing cryo-EM image data to reveal heterogeneity in the protein structure and to refine 3D maps to high resolution frequently becomes a severe bottleneck, requiring expert intervention, prior structural knowledge, and weeks of calculations on expensive computer clusters. Here we show that stochastic gradient descent (SGD) and branch-and-bound maximum likelihood optimization algorithms permit the major steps in cryo-EM structure determination to be performed in hours or minutes on an inexpensive desktop computer. Furthermore, SGD with Bayesian marginalization allows ab initio 3D classification, enabling automated analysis and discovery of unexpected structures without bias from a reference map. These algorithms are combined in a user-friendly computer program named cryoSPARC (http://www.cryosparc.com).
Treatment Effects on Measures of Body Composition in the TODAY Clinical Trial

OBJECTIVE
The Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) trial showed superiority of metformin plus rosiglitazone (M+R) over metformin alone (M), with metformin plus lifestyle (M+L) intermediate in maintaining glycemic control. We report here treatment effects on measures of body composition and their relationships to demographic and metabolic variables including glycemia.


RESEARCH DESIGN AND METHODS
Measures of adiposity (BMI, waist circumference, abdominal height, percent and absolute fat, and bone mineral content [BMC] and density [BMD]) were analyzed as change from baseline at 6 and 24 months.


RESULTS
Measures of fat accumulation were greatest in subjects treated with M+R and least in M+L. Although fat measures in M+L were less than those of M+R and M at 6 months, differences from M were no longer apparent at 24 months, whereas differences from M+R persisted at 24 months. The only body composition measure differing by race and/or ethnicity was waist circumference, greater in M+R than either M or M+L at both 6 and 24 months in whites. BMD and BMC increased in all groups, but increased less in M+R compared with the other two groups by 24 months. Measures of adiposity (increases in BMI, waist circumference, abdominal height, and fat) were associated with reduced insulin sensitivity and increased hemoglobin A1c (HbA1c), although effects of adiposity on HbA1c were less evident in those treated with M+R.


CONCLUSIONS
Despite differential effects on measures of adiposity (with M+R resulting in the most and M+L in the least fat accumulation), group differences generally were small and unrelated to treatment effects in sustaining glycemic control.
Art therapy improved depression and influenced fatigue levels in cancer patients on chemotherapy.

INTRODUCTION
Cancer patients are particularly vulnerable to depression and anxiety, with fatigue as the most prevalent symptom of those undergoing treatment. The purpose of this study was to determine whether improvement in depression, anxiety or fatigue during chemotherapy following anthroposophy art therapy intervention is substantial enough to warrant a controlled trial.


MATERIAL AND METHODS
Sixty cancer patients on chemotherapy and willing to participate in once-weekly art therapy sessions (painting with water-based paints) were accrued for the study. Nineteen patients who participated in > or =4 sessions were evaluated as the intervention group, and 41 patients who participated in < or =2 sessions comprised the participant group. Hospital Anxiety and Depression Scale (HADS) and the Brief Fatigue Inventory (BFI) were completed before every session, relating to the previous week.


RESULTS
BFI scores were higher in the participant group (p=0.06). In the intervention group, the median HADS score for depression was 9 at the beginning and 7 after the fourth appointment (p=0.021). The median BFI score changed from 5.7 to 4.1 (p=0.24). The anxiety score was in the normal range from the beginning.


CONCLUSION
Anthroposophical art therapy is worthy of further study in the treatment of cancer patients with depression or fatigue during chemotherapy treatment.
Agile Modeling with the UML

This paper discusses a model-based approach to software development. It argues that an approach using models as central development artifact needs to be added to the portfolio of software engineering techniques, to further increase efficiency and flexibility of the development as well as quality and reusability of the results. Two major and strongly related techniques are identified and discussed: Test case modeling and an evolutionary approach to model transformation.
N-terminal Pro-B-type natriuretic peptide and its correlation to haemodialysis-induced myocardial stunning.

BACKGROUND
Haemodialysis (HD) is able to induce recurrent myocardial ischemia and segmental left-ventricular dysfunction (myocardial stunning). The association of N-terminal Pro-B-type natriuretic peptide (NTpro-BNP) with HD-induced myocardial stunning is unclear.


METHODS
In 70 prevalent HD patients, HD-induced myocardial stunning was assessed echocardiographically at baseline and after 12 months. The extent to which pre-dialysis NTpro-BNP was associated with the occurrence of HD-induced myocardial stunning was assessed as the primary endpoint.


RESULTS
The median Ntpro-BNP concentration in this cohort was 2,154 pg/ml (IQR 1,224-3,014). Patients experiencing HD-induced myocardial stunning at either time point displayed elevated NTpro-BNP values (2,418 pg/ml, IQR, 1,583-3,474 vs. 1,751 pg/ml, IQR (536-2,029), p = 0.02). NTpro-BNP levels did not differ between patients showing HD-induced stunning at baseline and those developing stunning during the observational period (p = 0.8). NTpro-BNP levels drawn at the beginning of the dialysis session achieved a poor diagnostic accuracy for the detection of myocardial stunning (area under the ROC curve 0.61, 95% CI 0.45-0.77), but provided an accurate rule out for myocardial stunning during the subsequent year (AUC 0.85, 95% CI 0.70-0.99). The calculated cut-off of 1,570 pg/ml achieved a sensitivity of 66% and a specificity of 78% for the exclusion of myocardial stunning at any time point. In logistic regression analysis, only low NTpro-BNP levels (OR 0.92 for every additional 100 pg/ml, 95% CI 0.85-0.99, p = 0.03) were significantly associated with absence of myocardial stunning at any time point.


CONCLUSION
Predialytic NTpro-BNP levels fail to adequately diagnose current dialysis-induced myocardial stunning, but help to identify patients with a propensity to develop dialysis-induced myocardial stunning at any time during the next 12 months.
mm-Wave Silicon ICs: Challenges and Opportunities

Millimeter-waves offer promising opportunities and interesting challenges to silicon integrated circuit and system designers. These challenges go beyond standard circuit design questions and span a broader range of topics including wave propagation, antenna design, and communication channel capacity limits. It is only meaningful to evaluate the benefits and shortcoming of silicon-based mm-wave integrated circuits in this broader context. This paper reviews some of these issues and presents several solutions to them.
Provenance of Holocene beach sand in the Western Iberian margin: the use of the Kolmogorov–Smirnov test for the deciphering of sediment recycling in a modern coastal system

Detrital zircons from Holocene beach sand and igneous zircons from the Cretaceous syenite forming Cape Sines (Western Iberian margin) were dated using laser ablation – inductively coupled plasma – mass spectrometry. The U–Pb ages obtained were used for comparison with previous radiometric data from Carboniferous greywacke, Pliocene–Pleistocene sand and Cretaceous syenite forming the sea cliff at Cape Sines and the contiguous coast. New U–Pb dating of igneous morphologically simple and complex zircons from the syenite of the Sines pluton suggests that the history of zircon crystallization was more extensive (ca 87 to 74 Ma), in contrast to the findings of previous geochronology studies (ca 76 to 74 Ma). The U–Pb ages obtained in Holocene sand revealed a wide interval, ranging from the Cretaceous to the Archean, with predominance of Cretaceous (37%), Palaeozoic (35%) and Neoproterozoic (19%) detrital-zircon ages. The paucity of round to subrounded grains seems to indicate a short transportation history for most of the Cretaceous zircons (ca 95 to 73 Ma) which are more abundant in the beach sand that was sampled south of Cape Sines. Comparative analysis using the Kolmogorov–Smirnov statistical method, analysing sub-populations separately, suggests that the zircon populations of the Carboniferous and Cretaceous rocks forming the sea cliff were reproduced faithfully in Quaternary sand, indicating sediment recycling. The similarity of the preCretaceous ages (>ca 280 Ma) of detrital zircons found in Holocene sand, as compared with Carboniferous greywacke and Pliocene–Pleistocene sand, provides support for the hypothesis that detritus was reworked into the beach from older sedimentary rocks exposed along the sea cliff. The largest percentage of Cretaceous zircons (<ca 95 Ma) found in Holocene sand, as compared with Pliocene–Pleistocene sand (secondary recycled source), suggests that the Sines pluton was the one of the primary sources that became progressively more exposed to erosion during Quaternary uplift. This work highlights the application of the Kolmogorov–Smirnov method in comparison of zircon age populations used to identify provenance and sediment recycling in modern and ancient detrital sedimentary sequences. 1 © 2015 The Authors. Sedimentology © 2015 International Association of Sedimentologists Sedimentology (2016) doi: 10.1111/sed.12254
Deep Learning-Based Recommendation: Current Issues and Challenges

Due to the revolutionary advances of deep learning achieved in the field of image processing, speech recognition and natural language processing, the deep learning gains much attention. The recommendation task is influenced by the deep learning trend which shows its significant effectiveness and the high-quality of recommendations. The deep learning based recommender models provide a better detention of user preferences, item features and users-items interactions history. In this paper, we provide a recent literature review of researches dealing with deep learning based recommendation approaches which are preceded by a presentation of the main lines of the recommendation approaches and the deep learning techniques. We propose also classification criteria of the different deep learning integration model. Then we finish by presenting the recommendation approach adopted by the most popular video recommendation platform YouTube which is based essentially on deep learning advances. Keywords—Recommender system; deep learning; neural network; YouTube recommendation
African American patients' perspectives on medical decision making.

BACKGROUND
The medical literature offers little information about how older African Americans view the medical decision-making process. We sought to describe the perspectives of older African American patients in a primary care clinic as they consider a medical decision.


METHODS
We interviewed 25 African American patients older than 50 years who had discussed flexible sigmoidoscopy with their primary care provider. Interviews were analyzed using qualitative methods.


RESULTS
Patients listed concerns about cancer and health, risks and benefits, their own understanding of the test, and the recommendation of the provider as the most important factors in their decision. Most patients wanted information about medical tests and procedures to increase their understanding and to provide reassurance rather than to guide decision making. Most patients explained that they wanted the provider to make medical decisions because of his or her training and experience. Despite this, many expressed a sense of ownership or control over one's own body. Patients thought trust was built by a health care provider's honesty, patience, kindness, interest, and continuity of care.


CONCLUSIONS
Although traditional models of informed consent have emphasized providing patients with information to guide autonomous decision making, patients may want this information for other reasons. Fully informing patients about their medical condition increases understanding and provides reassurance. Because many of these patients want their provider to participate in making medical decisions, he or she should not only provide information but should also provide guidance to the patient.
Crime Data Mining: An Overview and Case Studies

The concern about national security has increased significantly since the 9/11 attacks. However, information overload hinders the effective analysis of criminal and terrorist activities. Data mining applied in the context of law enforcement and intelligence analysis holds the promise of alleviating such problems. In this paper, we review crime data mining techniques and present four case studies done in our ongoing COPLINK project.
Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

BACKGROUND
Deep learning (DL) is a representation learning approach ideally suited for image analysis challenges in digital pathology (DP). The variety of image analysis tasks in the context of DP includes detection and counting (e.g., mitotic events), segmentation (e.g., nuclei), and tissue classification (e.g., cancerous vs. non-cancerous). Unfortunately, issues with slide preparation, variations in staining and scanning across sites, and vendor platforms, as well as biological variance, such as the presentation of different grades of disease, make these image analysis tasks particularly challenging. Traditional approaches, wherein domain-specific cues are manually identified and developed into task-specific "handcrafted" features, can require extensive tuning to accommodate these variances. However, DL takes a more domain agnostic approach combining both feature discovery and implementation to maximally discriminate between the classes of interest. While DL approaches have performed well in a few DP related image analysis tasks, such as detection and tissue classification, the currently available open source tools and tutorials do not provide guidance on challenges such as (a) selecting appropriate magnification, (b) managing errors in annotations in the training (or learning) dataset, and (c) identifying a suitable training set containing information rich exemplars. These foundational concepts, which are needed to successfully translate the DL paradigm to DP tasks, are non-trivial for (i) DL experts with minimal digital histology experience, and (ii) DP and image processing experts with minimal DL experience, to derive on their own, thus meriting a dedicated tutorial.


AIMS
This paper investigates these concepts through seven unique DP tasks as use cases to elucidate techniques needed to produce comparable, and in many cases, superior to results from the state-of-the-art hand-crafted feature-based classification approaches.


RESULTS
Specifically, in this tutorial on DL for DP image analysis, we show how an open source framework (Caffe), with a singular network architecture, can be used to address: (a) nuclei segmentation (F-score of 0.83 across 12,000 nuclei), (b) epithelium segmentation (F-score of 0.84 across 1735 regions), (c) tubule segmentation (F-score of 0.83 from 795 tubules), (d) lymphocyte detection (F-score of 0.90 across 3064 lymphocytes), (e) mitosis detection (F-score of 0.53 across 550 mitotic events), (f) invasive ductal carcinoma detection (F-score of 0.7648 on 50 k testing patches), and (g) lymphoma classification (classification accuracy of 0.97 across 374 images).


CONCLUSION
This paper represents the largest comprehensive study of DL approaches in DP to date, with over 1200 DP images used during evaluation. The supplemental online material that accompanies this paper consists of step-by-step instructions for the usage of the supplied source code, trained models, and input data.
GPS Landslide Monitoring: Single Base vs. Network Solutions — A case study based on the Puerto Rico and Virgin Islands Permanent GPS Network

This study demonstrated an approach to using permanent GPS stations from a local continuous GPS network as no-cost references in conducting long-term millimeter-level landslide monitoring. Accuracy and outliers from a series of single-base and network GPS measurements of a creeping landslide were studied. The criterion for accuracy was the weighted root-mean-square (RMS) of residuals of GPS measurements with respect to true landslide displacements over a period of 14 months. This investigation indicated that the current Puerto Rico and Virgin Islands GPS network, as a reference frame, can provide accuracy of 1 to 2 mm horizontally and 6 mm vertically for local 24-hour continuous landslide monitoring with few outliers (<1%). The accuracy degraded by a factor of two for 6-hour sessions, and more for shorter sessions. This study indicated that adding a few reference stations to GPS data processing can reduce the number of outliers and increase the accuracy and robustness of landslide surveying, even if these references are far from the study site. This improvement was particularly significant for short sessions and vertical components. The accuracy of network solutions depended slightly on the number of reference stations, but the dependence on the distance and geometric distribution of the references was weak. For long-term landslide monitoring, accuracy under 5 mm horizontally and 15 mm vertically are often expected. Accuracy at this level can be stably achieved in the Puerto Rico and Virgin Islands region by performing field observations for 4 hours or longer, and applying 3 or more reference stations for solving a network solution. This study also indicated that rainfall events can play a crucial rule in high-precision GPS measurements. GPS data collected during heavy rainfall events should be cautiously analyzed in landslide studies.
Prevalence of attention-deficit/hyperactivity disorder: a systematic review and meta-analysis.

BACKGROUND AND OBJECTIVE
Overdiagnosis and underdiagnosis of attention-deficit/hyperactivity disorder (ADHD) are widely debated, fueled by variations in prevalence estimates across countries, time, and broadening diagnostic criteria. We conducted a meta-analysis to: establish a benchmark pooled prevalence for ADHD; examine whether estimates have increased with publication of different editions of the Diagnostic and Statistical Manual of Mental Disorders (DSM); and explore the effect of study features on prevalence.


METHODS
Medline, PsycINFO, CINAHL, Embase, and Web of Science were searched for studies with point prevalence estimates of ADHD. We included studies of children that used the diagnostic criteria from DSM-III, DSM-III-R and DSM-IV in any language. Data were extracted on sampling procedure, sample characteristics, assessors, measures, and whether full or partial criteria were met.


RESULTS
The 175 eligible studies included 179 ADHD prevalence estimates with an overall pooled estimate of 7.2% (95% confidence interval: 6.7 to 7.8), and no statistically significant difference between DSM editions. In multivariable analyses, prevalence estimates for ADHD were lower when using the revised third edition of the DSM compared with the fourth edition (P = .03) and when studies were conducted in Europe compared with North America (P = .04). Few studies used population sampling with random selection. Most were from single towns or regions, thus limiting generalizability.


CONCLUSIONS
Our review provides a benchmark prevalence estimate for ADHD. If population estimates of ADHD diagnoses exceed our estimate, then overdiagnosis may have occurred for some children. If fewer, then underdiagnosis may have occurred.
Constacyclic codes over finite local Frobenius non-chain rings with nilpotency index 3

Article history: Received 9 January 2016 Received in revised form 15 June 2016 Accepted 25 August 2016 Available online xxxx Communicated by W. Cary Huffman
LibGuides: Finding the Visual History of the 1960s: Introduction to Primary Sources

This guide was created as a supplement to the 2014 library exhibition Conflict and Counterculture: Finding the Visual History of the Sixties.
Global Talent Management : How Leading Multinationals Build and Sustain Their Talent Pipeline

To determine how leading companies in North America, Europe, and Asia develop and sustain strong talent pipelines, this research investigates talent management processes and practices in a sample of 37 multinational corporations, selected on the basis of their international scope, reputation, and long-term performance. In-depth case studies and a Web-based survey of human resources professionals identify various effective practices that can help companies attract, select, develop, and retain talent. However, the results suggest that competitive advantage comes not primarily from designing and implementing best practices but rather from the proper internal alignment of various elements of a company’s talent management system, as well as their embeddedness in the value system of the firm, their links to business strategy, and their global coordination. Global Talent Management: How Leading Multinationals Build and Sustain Their Talent Pipeline Executives around the world seem to agree: One of the biggest challenges facing their companies is building and sustaining a strong talent pipeline. In a recent survey of 300 firms conducted by the Hay Group and Chief Executive magazine, participating companies ranked “finding the right number of leaders” as their top challenge, and every single firm indicated its belief that demand for leaders would increase in the future. Not only do companies have trouble filling their talent pipelines due to shifting demographics and workforce preferences, but they also must develop new capabilities and revitalize their organizations as they transform their businesses, invest in new technologies, enter into new partnerships, and globalize their operations. These challenges make the need to develop effective talent management processes and practices even more pressing for global companies. In response, a team of researchers from the universities of Cambridge, Cornell, Erasmus/Tilburg, and INSEAD has conducted a major research project on the global best practices in human capital management. The qualitative portion of this research examines 20 companies in-depth, using interviews with senior executives, line managers, and human resources (HR) professionals to identify how leading multinationals manage their human capital. These companies are renowned for their international scope, reputations, and long-term performance and provide results from 312 interviews with professionals at various levels (e.g., corporate, regional, country) in more than 20 countries. In addition, we conducted a Web-based survey of HR professionals of 20 multinational corporations, gaining input from 263 respondents from three major geographic regions (Americas, Asia-Pacific, and Europe/Middle East/Africa). In total, this study involves 37