nils-herrmann/clean_scirepeval huggingface dataset:
Data services leveraging Bing's data assets
Venue: IEEE Data Eng. Bull.

Web search engines like Bing and Google have amassed a tremendous amount of data assets. These include query click logs, web crawl corpus, an entity knowledge graph and geographic/maps data. In the Data Management, Exploration and Mining (DMX) group at Microsoft Research, we investigate ways to mine the above data assets to derive new data that can provide new value to a wide variety of applications. We expose the new data as cloud data services that can be consumed by Microsoft products and services as well as third party applications. We describe two such data services we have built over the past few years: synonym service and web table service. These two data services have shipped in several Microsoft products and services including Bing, Office 365, Cortana, Bing synonyms API and Bing Knowledge API.
New developments in prostate cancer biomarkers
Venue: Current opinion in oncology

The initial management of localized prostate cancer is increasingly complex with the identification of a growing number of prognostic subgroups. Molecular and genetic biomarkers have been proposed to help clinicians and patients navigate treatment decisions. Recent findings Three commercially available tests, the Genomic Prostate score, Cell Cycle Progression score, and Genomic Classifier appear to currently have the most supporting data for their use in localized prostate cancer. All three have been shown to identify men at higher risk for poor outcome following radical prostatectomy in retrospective studies whereas the first two have also shown promise in addressing which men might be appropriate for active surveillance. Only the Genomic Classifier has data supporting its use as a predictive marker in addition to a prognostic marker.  Over the past several years, the management of localized prostate cancer has seen the development of several novel biomarkers aimed at improving decision making. Although a lack of prospective validation makes it challenging to know how best to change management based on the results from any of the tests, the growing body of retrospective data suggests significant promise in this arena.
Management of Postoperative Pain: A Clinical Practice Guideline From the American Pain Society, the American Society of Regional Anesthesia and Pain Medicine, and the American Society of Anesthesiologists' Committee on Regional Anesthesia, Executive Committee, and Administrative Council.
Venue: The journal of pain official journal of the American Pain Society

Most patients who undergo surgical procedures experience acute postoperative pain, but evidence suggests that less than half report adequate postoperative pain relief. Many preoperative, intraoperative, and postoperative interventions and management strategies are available for reducing and managing postoperative pain.  The guideline was subsequently approved by the American Society for Regional Anesthesia. As part of the guideline development process, a systematic review was commissioned on various aspects related to various interventions and management strategies for postoperative pain. After a review of the evidence, the expert panel formulated recommendations that addressed various aspects of postoperative pain management, including preoperative education, perioperative pain management planning, use of different pharmacological and nonpharmacological modalities, organizational policies, and transition to outpatient care. The recommendations are based on the underlying premise that optimal management begins in the preoperative period with an assessment of the patient and development of a plan of care tailored to the individual and the surgical procedure involved. The panel found that evidence supports the use of multimodal regimens in many situations, although the exact components of effective multimodal care will vary depending on the patient, setting, and surgical procedure. Although these guidelines are based on a systematic review of the evidence on management of postoperative pain, the panel identified numerous research gaps. Of 32 recommendations, 4 were assessed as being supported by high quality evidence, and 11 (in the areas of patient education and perioperative planning, patient assessment, organizational structures and policies, and transitioning to outpatient care) were made on the basis of low quality evidence.  This guideline, on the basis of a systematic review of the evidence on postoperative pain management, provides recommendations developed by a multidisciplinary expert panel. Safe and effective postoperative pain management should be on the basis of a plan of care tailored to the individual and the surgical procedure involved, and multimodal regimens are recommended in many situations.
Administrative Values and Public Personnel Management

Civil service reforms implemented over the past 35 years in many countries around the world have relaxed traditional merit system rules, decentralized the personnel function, and augmented agency and managerial discretion. One objective of these reforms has been to boost government productivity and increase the efficiency of core personnel management functions such as hiring and firing employees, but much of the available evidence suggests that reforms commonly implemented may serve political or ideological objectives better than performance related goals. We argue for a fuller appreciation of the political motivations for reforms and a broader understanding of their implications.
The Mediating Effect of Team Engagement between Team Cognitions and Team Outcomes in Service Management Teams

Prior research has focused more on employee engagement than team engagement. The current work presents a theoretical framework proposing the antecedents and consequences of team engagement. Antecedents of team engagement include two types of team cognitions (shared mental models and transactive memory systems) Consequences of team engagement include team performance and team satisfaction. A longitudinal study was conducted with 27 service management teams involving 178 students in a restaurant setting. Hierarchical linear modeling results indicate the (a) direct relationships between team cognitions and team engagement, and between team engagement and team outcomes, and (b) mediation effects of team engagement.
Automatic aesthetic quality assessment of photographic images using deep convolutional neural network
Venue: 2016 International Conference on Information Science (ICIS)

Aesthetics can be defined as the study of various emotions related to the sense of beauty. Nowadays there is a fast growth in the use of digital images which is used for representing information. With the increase in the number of photos, it has become complicated to evaluate its quality. Image aesthetic evaluation methods depends on many aesthetic features. People give more attention to the photos which are visually satisfying. Evaluation of aesthetic quality is a challenging task which require knowledge about aesthetic features. Some low level features like contrast, sharpness, colorfulness etc are used to calculate aesthetic score of an image. This paper present a system for automatic aesthetic quality assessment of photographic images using deep convolutional neural network.
Hierarchical aesthetic quality assessment using deep convolutional neural networks
Venue: Signal Process. Image Commun.

Aesthetic image analysis has attracted much attention in recent years. However, assessing the aesthetic quality and assigning an aesthetic score are challenging problems. In this paper, we propose a novel framework for assessing the aesthetic quality of images. Firstly, we divide the images into three categories: "scene" "object" and "texture" Each category has an associated convolutional neural network (CNN) which learns the aesthetic features for the category in question. The object CNN is trained using the whole images and a salient region in each image. The texture CNN is trained using small regions in the original images. Furthermore, an A&C CNN is developed to simultaneously assess the aesthetic quality and identify the category for overall images. For each CNN, classification and regression models are developed separately to predict aesthetic class (high or low) and to assign an aesthetic score. Experimental results on a recently published large scale dataset show that the proposed method can outperform the state of the art methods for each category. HighlightsPropose an aesthetic quality assessment framework by dividing images into 3 categories.Three specific CNNs and an A&C CNN are constructed for aesthetic features learning.Different models for each CNN are developed to predict aesthetic class and score.
Numerical Modeling of 2 D and 3 D Flows using Artificial Compressibility Method and Collocated Mesh

In this paper, applications of a numerical model on simulation of two and three dimensional flows are presented. This model solves Navier Stokes equations using finite volume method and large eddy simulation (LES) in a collocated mesh. Artificial c ompressibility m ethod w ith d ual t ime stepping is used to solve the time dependent equations. Also a modified m omentum i nterpolation method (MIM) based on the unsteady flows i s deployed t o overcome t he non physical pressure oscillation. Capability of the presented numerical code for flow s imulation, i s assessed by application for twodimensional square and three dimensional lid driven cavity flows. Numerical results of cavity flow presents very good agreement with the numerical and experimental data of other existent researches.
Multiphysics analysis of an asymptotically correct piezoelectric sensor under static and dynamic load

This paper presents a versatile platform named V ariational A symptotic M ethod (VAM) to model and analyze a piezoelectric cantilever sensor under static and dynamic load. Variational asymptotic method is a mathematically rigorous dimentional reduction methodology and has been previously used to model different structures which can be defined by an energy functional having one or more small inherent parameters; but, it has never been explicitly applied to capture the multiphysics behavior of a sensor. Piezoelectric based sensing technology has seen an explosive growth in the last decade with its various applications in different domain, such as energy harvesters, aerospace application, soft robotics, wind turbine, biomechanics, etc. So, an efficient mathematical model is highly required to get a better insight of the multiphysics behavior of an electromechanical structure. The present study highlights the capability of the theory to effectively capture the electromechanical response of a piezo sensor under any static or dynamic load. The example problems considered in this present study include a single layer piezo sensor as well as a double layer piezo sensor bonded with aluminum. For static analysis, we have testified the model under a constant tip load. The discussed method effectively captures the voltage distribution across the thickness of the structure which is one of the fundamental parameter for a sensor model. The response accuracy obtained through variational asymptotic method is very good compared with the 3D simulation response performed in ABAQUS. For dynamic analysis a single layered piezo sensor has been studied under a tip harmonic force. The structure response is studied for both damped as well as undamped conditions. Displacement and corresponding voltage output for specific excitation frequency which is close to its first natural frequency has been studied. The model efficacy under dynamic load has been validated with the experimental study performed by Ly et al. (2011) The present model has numerous potential applications like in PZT cantilever design for chemo sensing, disease diagnostic, energy harvesting for self powered electronics, AFM higher harmonic imaging etc. The present theory along with the piezoelectric physics have been implemented in a modified version of VABS II (2004)
Elasticity measurement of Biological tissue using a Probe Type Instrument

In this paper, the elastic properties of chicken and bovine livers were measured using a probe type instrument. The design of the instrument and the method for calculation the parameters were presented, followed by the experimental validation of the method using artificial material. The validated method was then used to measure the chicken and bovine livers. Good agreements in curve fitting were obtained using the proposed method. Experimental results showed that the chicken liver demonstrated stronger nonlinear behaviors comparing to the bovine liver.  Surgical simulation provides an good option for surgical training and optimal surgical planning before actual surgery. To this end, accurate computer model of human organs and tissues are required, which further requires accurate physical properties of these tissues. However, measuring such properties in vivo is a very challenging task due to the complex internal environment and limited space inside body. To take this challenge, in this research, a probe type device was proposed towards portable measuring system for calibrating tissue properties. II. M ETHOD Most of human organs and tissues are supposed to be incompressible and the Poisson's ratio g was considered to be close to 0.5. In this work, we set Poisson's ratio g as a constant of 0.49 and we are focusing on the calculation of elasticity, i.e. the Young's modulusE. According to Hertz contact mechanics, the contact forceF between a sphere and a flat elastic surface is given by: F 4 3 E 1 g2 R 1 2 d 3 2 (1) whereR denotes the radius of the sphere and d enotes the indentation depth. The relationship was further extended to Eq.
A multi modal parcellation of human cerebral cortex
Venue: Nature

Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century old objective in neuroscience. Using multi modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post mortem microscopy or other specialized study specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine learning classifier to recognize the multi modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.
Human resource management practices and organizational effectiveness: internal fit matters

The purpose of this paper is to test alternative conceptualizations of the relationship between systems of human resource management (HRM) practices and organizational effectiveness. The authors describe a framework suggesting a complex relationship between HRM practices and organizational effectiveness, test this approach empirically in a large sample of US motor carriers, and compare the results to those derived using other approaches prevalent in the strategic HRM literature.  The study used a large scale cross sectional survey design. In a sample of US motor carriers, questionnaires completed by senior HRM department staff were used as the primary data. The data were supplemented by organizational effectiveness data reported by motor carriers to the US Government.  The results support the general hypothesis that HRM practices enhance organizational effectiveness, provide some evidence that HRM practices can enhance each other's effectiveness, and unders.
Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

This paper addresses the challenge of 3D full body human pose estimation from a monocular image sequence. Here, two cases are considered: (i) the image locations of the human joints are provided and (ii) the image locations of joints are unknown. In the former case, a novel approach is introduced that integrates a sparsity driven 3D geometric prior and temporal smoothness. In the latter case, the former case is extended by treating the image locations of the joints as latent variables to take into account considerable uncertainties in 2D joint locations. A deep fully convolutional network is trained to predict the uncertainty maps of the 2D joint locations. The 3D pose estimates are realized via an Expectation Maximization algorithm over the entire sequence, where it is shown that the 2D joint location uncertainties can be conveniently marginalized out during inference. Empirical evaluation on the Human3.6M dataset shows that the proposed approaches achieve greater 3D pose estimation accuracy over state of the art baselines. Further, the proposed approach outperforms a publicly available 2D pose estimation baseline on the challenging PennAction dataset.
The First Law of Black Hole Mechanics for Fields with Internal Gauge Freedom

We derive the first law of black hole mechanics for physical theories based on a local, covariant and gauge invariant Lagrangian where the dynamical fields transform non trivially under the action of internal gauge transformations. The theories of interest include General Relativity formulated in terms of tetrads, Einstein Yang Mills theory and Einstein Dirac theory. Since the dynamical fields of these theories have gauge freedom, we argue that there is no group action of diffeomorphisms of spacetime on such dynamical fields. In general, such fields cannot even be represented as smooth, globally well defined tensor fields on spacetime. Consequently the derivation of the first law by Iyer Wald cannot be used directly. We show how such theories can be formulated on a principal bundle and that there is a natural action of automorphisms of the bundle on the fields. These bundle automorphisms encode both spacetime diffeomorphisms and gauge transformations. Using this reformulation we define the Noether charge associated to an infinitesimal automorphism and the corresponding notion of stationarity and axisymmetry of the dynamical fields. We define certain potentials and charges at the horizon of a black hole so that the potentials are constant on the bifurcate Killing horizon, giving a generalised zeroth law for bifurcate Killing horizons. We identify the gravitational potential and perturbed charge as the temperature and perturbed entropy of the black hole which gives an explicit formula for the perturbed entropy analogous to the Wald entropy formula. We obtain a general first law of black hole mechanics for such theories. The first law relates the perturbed Hamiltonians at spatial infinity and the horizon, and the horizon contributions take the form of a potential times perturbed charge term. We also comment on the ambiguities in defining a prescription for the total entropy for black holes.
Toxoplasmosis Detection of Serum Immunoglobulin by ELISA and Placenta DNA by PCR A Comparative Study

The prenatal diagnosis of congenital toxoplasmosis is important to prevent unnecessary termination of pregnancy. Thus, there is a need for application of laboratory test that is sensitive and specific for the diagnosis of toxoplasmosis .The objective of the present study was to check the validity of determination of serum specific IgG and IgM anti toxoplasma antibodies in comparison to PCR method for detecting toxoplasmosis DNA in placenta samples twenty one women suffered from abortion were included in this study. Their ages ranged from 20 35 years Cases of abortion due to other causes were excluded Sera and placentae were collected from all participants. Specific IgM and IgG antitoxoplasma antibodies were determined using capture ELISA technique according to the manufacturer's instructions. Nested primer sets were used for amplifying fragments of the B1 gen. Specific IgG anti toxoplasmosis antibodies were detected by ELISA in 17 (77.2% women out of 21 while specific IgM anti toxoplasmosis antibodies were detected in 8 (36.3) women out 0f the 21 examined sample However PCR detected toxoplasmosis DNA in 20 (95.4% out of 21 placental samples. Nested PCR amplification of the B1 gene of T. gondii is a rapid, sensitive and specific diagnostic procedure and considered a valuable tool for the diagnosis of T. gondii infection in adults females Detection of specific IgG and IgM anti toxoplasma antibodies in serum of women with abortion was with higher specificity .However their sensitivities were 85% and 40% for serum IgG and IgM respectively
Relative contribution of health related behaviours and chronic diseases to the socioeconomic patterning of low grade inflammation
Venue: International Journal of Public Health

ObjectivesTo test the association of low grade inflammation with socioeconomic status (SES) and determine the relative contribution of prevalent chronic diseases and health related behaviours in explaining such association.MethodsCross sectional analysis on 19,867 subjects (age =35, 48.1% men) recruited within the Moli sani study from 2005 to 2010 (Italy) A score of low grade inflammation, including platelet and leukocyte counts, the granulocyte to lymphocyte ratio, and C reactive protein was applied. SES was measured by education, household income, and occupational social class.ResultsLow SES was associated with elevated levels of low grade inflammation. Health behaviours (including adiposity, smoking, physical activity, and Mediterranean diet adherence) explained 53.5, 53.9, and 84.9% of the association between social class, income, and education with low grade inflammation, respectively. Adiposity and body mass index showed a prominent role, while prevalent chronic diseases and conditions only marginally attenuated SES inequalities in inflammation.ConclusionsLow grade inflammation was socioeconomically patterned in a large Mediterranean population. Potentially modifiable behavioural factors explained the greatest part of this association with a leading contribution of adiposity, body mass index, and physical activity.
QR code based chipless RFID system for unique identification
Venue: 2016 IEEE International Conference on RFID Technology and Applications (RFID TA)

A fully passive printable Quick Response (QR) code embedded chipless RFID (Radio Frequency Identification) technique is presented for secure identification of alive and nonalive amenity. A series of QR codes are printed in the form of a resonator in passive RFID tag, and the coded information is retrieved through frequency domain reflectometry method for identification. The design is demonstrated over the 3 10 GHz band with embedded multiple QR code resonators on a single RFID tag. The tag comprises of QR Code resonators, cross polarized transmitting and receiving ultra wide band (UWB) monopole antennas. As a proof of concept, a 42mm x 42mm size standard QR code resonator is designed and later the design is compressed to 10.5mm x 10.5mm size on a single sided FR4 PCB. The proposed method proved the tag read by reader from 2 meters of distance.