nils-herrmann/clean_scirepeval huggingface dataset:
Heterozygous Mutation (Q459R) in the Calcium Sensing Receptor Gene Causes Familial Hypocalciuric Hypercalcemia 1 (FHH1)
Venue: The Journal of clinical endocrinology and metabolism
Year: 2020

Several heterozygous loss of function mutations in the calcium sensing receptor gene (CASR) leading to elevated ionized serum calcium and familial hypocalciuric hypercalcemia 1 (FHH1) have been characterized. Few mutations are not pathogenic, and previous studies suggested that the Q459R mutation does not result in an FHH1 phenotype.  We identified a family with a heterozygous CASR Q459R mutation and characterized their calcium homeostasis and the pathophysiological mechanisms of a homozygous and heterozygous Q459R mutation in vitro.  The index patient and her family had clinical, biochemical, and genetic analyses performed. In vitro functional characterization of homozygous and heterozygous (Q459R) mutations was conducted by determining CaSR cell surface expression and inositol monophosphate (IP1) signaling in transiently transfected human embryonic kidney 293A (HEK293A) cells.  All 3 heterozygous carriers had mild asymptomatic hypercalcemia, hypocalciuria, and 2 had elevated serum parathyroid hormone (PTH) In vitro characterization in HEK293A cells revealed that CASR Q459R is a loss of function mutation with no impact on cell surface expression. Cells with the homozygous Q459R genotype had significantly reduced calcium potency of IP1 signaling compared to wild type, whereas the heterozygous Q459R also had lower calcium potency albeit not significantly different from wild type.  A loss of function Q459R mutation in CASR in a family caused FHH1 characterized by elevated ionized calcium and PTH and low calcium excretion. The marked presence of CaSR at the membrane and inhibition of IP1 signaling in vitro suggest that calcimimetics may be functional in patients with this mutation, which seems to be a mild loss of function mutation associated with autosomal dominant transmission of FHH1.
Mineral Composition Physico chemical Properties and Fatty Acids Profile of Prunus armeniaca Apricot Seed Oil
Year: 2017

Edible oils are an important food source for humans because they supply essential fatty acids such as linoleic acid. Oils are also used in the cosmetics and pharmaceutical industries. The oils obtained from plant seeds can be both edible and non edible relating on the plant source. These oils are often available as raw materials for food industry usage. Because of the high request and economic aspects of these oils to the chemical industry, attention has been focused on the under utilized Prunus armeniaca L. kernel for possible development and use  Some studies have been conducted to assess the physical as well as chemical properties of the apricot seeds. Alpaslan and Hayta  have showed the physical and chemical composition of Turkish apricot kernels. Gezer et al.  has showed some physical properties of apricot pit and kernel of Turkish apricot kernels. Ozcan et al.  have reported the same physical properties of apricot kernel oil of Turkish Prunus armeniaca L. of oil. However, no study has been done about Iranian wild apricot kernel oil. Kernels of apricot, peach and plum are produced as byproducts by the food canning industry [4 8] This not only wastes a potentially economically valuable resource, but also aggravates an already serious disposal problem. For Mineral Composition, Physico chemical Properties and Fatty Acids Profile of Prunus armeniaca Apricot Seed Oil
The Neural Bases of Emotion Regulation: Reappraisal and Suppression of Negative Emotion
Venue: Biological Psychiatry
Year: 2008

Emotion regulation strategies are thought to differ in when and how they influence the emotion generative process. However, no study to date has directly probed the neural bases of two contrasting (e.g. cognitive versus behavioral) emotion regulation strategies. This study used functional magnetic resonance imaging (fMRI) to examine cognitive reappraisal (a cognitive strategy thought to have its impact early in the emotion generative process) and expressive suppression (a behavioral strategy thought to have its impact later in the emotion generative process) METHODS Seventeen women viewed 15 sec neutral and negative emotion eliciting films under four conditions watch neutral, watch negative, reappraise negative, and suppress negative while providing emotion experience ratings and having their facial expressions videotaped.  Reappraisal resulted in early (0 4.5 sec) prefrontal cortex (PFC) responses, decreased negative emotion experience, and decreased amygdala and insular responses. Suppression produced late (10.5 15 sec) PFC responses, decreased negative emotion behavior and experience, but increased amygdala and insular responses.  These findings demonstrate the differential efficacy of reappraisal and suppression on emotional experience, facial behavior, and neural response and highlight intriguing differences in the temporal dynamics of these two emotion regulation strategies.
Neural Unsigned Distance Fields for Implicit Function Learning
Venue: NeurIPS
Year: 2020

In this work we target a learnable output representation that allows continuous, high resolution outputs of arbitrary shape. Recent works represent 3D surfaces implicitly with a Neural Network, thereby breaking previous barriers in resolution, and ability to represent diverse topologies. However, neural implicit representations are limited to closed surfaces, which divide the space into inside and outside. Many real world objects such as walls of a scene scanned by a sensor, clothing, or a car with inner structures are not closed. This constitutes a significant barrier, in terms of data pre processing (objects need to be artificially closed creating artifacts) and the ability to output open surfaces. In this work, we propose Neural Distance Fields (NDF) a neural network based model which predicts the unsigned distance field for arbitrary 3D shapes given sparse point clouds. NDF represent surfaces at high resolutions as prior implicit models, but do not require closed surface data, and significantly broaden the class of representable shapes in the output. NDF allow to extract the surface as very dense point clouds and as meshes. We also show that NDF allow for surface normal calculation and can be rendered using a slight modification of sphere tracing. We find NDF can be used for multi target regression (multiple outputs for one input) with techniques that have been exclusively used for rendering in graphics. Experiments on ShapeNet show that NDF, while simple, is the state of the art, and allows to reconstruct shapes with inner structures, such as the chairs inside a bus. Notably, we show that NDF are not restricted to 3D shapes, and can approximate more general open surfaces such as curves, manifolds, and functions. Code is available for research at this https URL.
Effect of Chemical Pre treatments on Bioethanol Production from Chlorella minutissima.
Venue: Acta chimica Slovenica
Year: 2018

In recent years, algal bioethanol production comes into prominence as a trend towards sustainable development. Due to being sustainable energy source and environmental friendly, bioethanol production from algae is becoming increasingly popular all over the world. However, yield of bioethanol production from algae is lower than first generation feedstock's currently, and needs to be improved. In order to increase bioethanol yield, pre treatments should be performed as cell disruption process on algal biomass. For this reason, researchers investigate the most appropriate pre treatment method and its parameters for high yield bioethanol production from algae. In this study, cultivated Chlorella minutissima was utilized for bioethanol production. Effects of pre treatment method (dilute acid and alkaline) chemical concentration, pre treatment temperature and pre treatment time on bioethanol yield were investigated. It was found that, the highest bioethanol yield was obtained as 18.52% with acid pre treatment at pre treatment temperature of 100 degC and pre treatment time of 60 minutes.
Effects of dissolved oxygen on fungal morphology and process rheology during fed batch processing of Ganoderma lucidum.
Venue: Journal of microbiology and biotechnology
Year: 2010

Controlling the dissolved oxygen (DO) in the fed batch culture of the medicinal mushroom Ganoderma lucidum led to a two fold increase of the maximum biomass productivity compared to uncontrolled DO conditions. By contrast, extracellular polysaccharide (EPS) production was two times higher under oxygen limitation (uncontrolled DO) than under increased oxygen availability (controlled DO) Morphologically, dispersed mycelium was predominant under controlled DO conditions, with highly branched hyphae, consistent with the enhanced culture growth noted under these conditions. While in the uncontrolled DO processes mycelial clumps were the most common morphology throughout the culture. However, in both cultures clamp connections were found. This is an exciting new finding, which widens the applicability of this basidiomycete in submerged fermentation. In rheological terms, broths demonstrated shear thinning behaviour with a yield stress under both DO conditions. The flow curves were best described by the Herschel Bulkley model: flow index down to 0.6 and consistency coefficient up to 0.2 and 0.6 Pa sn in uncontrolled and controlled cultures DO, respectively. The pseudoplastic behaviour was entirely due to the fungal biomass, and not to the presence of EPS (rheological analysis of the filtered broth showed Newtonian behaviour) It is clear that dissolved oxygen tension is a critical process parameter that distinctly influences G. lucidum morphology and rheology, affecting the overall performance of the process. This study contributes to an improved understanding of the process physiology of submerged fermentation of G. lucidum.
The Relationship between Spiritual Well being and Anxiety Levels in the Students of School of Nursing and Midwifery in Rafsanjan University of Medical Sciences in 2015
Year: 2018

In modern societies, anxiety is one of the most common mental health problems. Nowadays, the attention of many religious psychologists has been drawn to the role of spiritual well being in reducing mental disorders, including anxiety. The present study was designed to investigate the spiritual wellbeing and anxiety among the students in the School of Nursing and Midwifery at Rafsanjan University of Medical Sciences.  This research was a cross sectional and descriptive analytic study in which 233 nursing, midwifery, and medical students of Rafsanjan University of Medical Sciences participated. The instruments were the Palutzian&Ellison'sSpiritualWell Being Scale and Beck Anxiety Inventory. The obtained data were analyzed in the SPSS 20, using Pearson correlation coefficient and two sample t test statistical analysis.  The average spiritual well being of nursing and midwifery students is moderate (98.97 14.7) and their average anxiety was low (24.58 13.7) Moreover, there was a negative correlation between spiritual health and anxiety (r= 0.398)  According to the results, it is important to pay attention to spiritual health in nursing, midwifery, and medical emergency students. The spiritual health well being causes anxiety decrement; thus, to promote spiritual health and reduce anxiety in students, it is necessary to make proper plans.  Spiritual Health, Anxiety, Students, Nursing, Midwifery Received: 25 March 2017  24 Jun 2017 Instructor, Dept. of Nursing, Nursing and Midwifery School, Rafsanjan University of Medical Sciences, Rafsanjan, Iran. Corresponding Author) Tel:0344256961 Email:nedarahimi90@yahoo.com Instructor, Dept. of statistical, Rafsanjan University of Medical Sciences, Rafsanjan, Kerman, Iran. BS in Nursing, Jiroft University of Medical Sciences, Jiroft Rafsanjan, Kerman, Iran. D ow nl oa de d fr om ij n. iu m s. ac .ir a t 6 :3 1 IR D T o n S at ur da y A pr il 25 th 2 02 0 D O I: 10 .2 92 52 /ij n. 30 .1 06 .7 8
Barriers to Sustainable Business Model Innovation in Swedish Agriculture
Year: 2018

Sweden's agriculture industry has faced many challenges in recent years. Among the most severe challenges are the decrease in the number of small and medium sized farms, the decrease in the number of people employed in agricultural actvites, and the increase in governmental regulatons and legislaton governing such actvites. At the same tme, the demand that agriculture contributes to sustainable social and ecological development has increased. Although research shows that sustainable business model innovaton (SBMI) contributes to the creaton of sustainable businesses and to the development of a sustainable society, Swedish agriculture has not been at the forefront in the use of SBMI. The purpose of this paper is to examine the barriers to SBMI in Swedish agriculture in order to understand why farmers seldom engage in SBMI. This qualitatve study follows the Gioia methodology and data for the analysis were acquired in semi structured interviews with entrepreneurs at six family farms in Sweden. The paper makes a theoretcal contributon to the research on SBMI with its focus on sustainable entrepreneurship in the Swedish agricultural industry. The paper concludes that the barriers to SBMI are external, internal, and contextual.
Insights from an observational assessment of park based physical activity in Nanchang, China
Venue: Preventive medicine reports
Year: 2015

Internationally, parks have been shown to be an important community asset for physical activity (PA) but little is known about the relationship between park usage and physical activity in China. The purpose of this study was to determine the association between park user characteristics and PA in Nanchang, China. In June 2014, 75,678 people were observed in eight parks over 12 days using SOPARC, a validated systematic observation tool. A logistic regression analysis was used to determine the association between PA and park user characteristics. Most park users were older adults (53.5% or adults (34.6% Overall, 55% of park users engaged in moderate to vigorous physical activity (MVPA) Fewer women were observed in parks than men, but were 66% more likely to be engaged in MVPA than men. Park users were more likely to be observed in MVPA between 6 9 am and when the temperature was below 30 degC. Chinese park users were more active (55% than US studies in Tampa (30% Chicago (49% and Los Angeles (34% More research is necessary to identify features of parks that are associated with greater PA so that effective interventions can be developed to promote active park use in Chinese citizens.
Bayesian Reanalyses From Summary Statistics: A Guide for Academic Consumers
Year: 2018

Across the social sciences, researchers have overwhelmingly used the classical statistical paradigm to draw conclusions from data, often focusing heavily on a single number: p. Recent years, however, have witnessed a surge of interest in an alternative statistical paradigm: Bayesian inference, in which probabilities are attached to parameters and models. We feel it is informative to provide statistical conclusions that go beyond a single number, and regardless of one's statistical preference it can be prudent to report the results from both the classical and the Bayesian paradigms. In order to promote a more inclusive and insightful approach to statistical inference, we show how the Summary Stats module in the open source software program JASP (https:/jasp stats.org) can provide comprehensive Bayesian reanalyses from just a few commonly reported summary statistics, such as t and N. These Bayesian reanalyses allow researchers and also editors, reviewers, readers, and reporters to (a) quantify evidence on a continuous scale using Bayes factors, (b) assess the robustness of that evidence to changes in the prior distribution, and (c) gauge which posterior parameter ranges are more credible than others by examining the posterior distribution of the effect size. The procedure is illustrated using Festinger and Carlsmith's (1959) seminal study on cognitive dissonance.
SnO2 quantum dots and quantum wires: controllable synthesis, self assembled 2D architectures, and gas sensing properties.
Venue: Journal of the American Chemical Society
Year: 2008

SnO2 quantum dots (QDs) and ultrathin nanowires (NWs) with diameters of approximately 0.5 2.5 and approximately 1.5 4.5 nm, respectively, were controllably synthesized in a simple solution system. They are supposed to be ideal models for studying the continuous evolution of the quantum confinement effect in SnO2 1D 0D systems. The observed transition from strong to weak quantum confinement in SnO2 QDs and ultrathin NWs is interpreted through the use of the Brus effective mass approximation and the Nosaka finite depth well model. Photoluminescence properties that were coinfluenced by size effects, defects (oxygen vacancies) and surface capping are discussed in detail. With the SnO2 QDs as building blocks, various 2D porous structures with ordered hexagonal, distorted hexagonal, and square patterns were prepared on silicon wafer surfaces and exhibited optical features of 2D photonic crystals and enhanced gas sensitivity.
Correcting Covariate Shift with the Frank Wolfe Algorithm
Venue: IJCAI
Year: 2015

Covariate shift is a fundamental problem for learning in non stationary environments where the conditional distribution p(y|x) is the same between training and test data while their marginal distributions ptrpxq and ptr(x) are different. Although many covariate shift correction techniques remain effective for real world problems, most do not scale well in practice. In this paper, using inspiration from recent optimization techniques, we apply the Frank Wolfe algorithm to two well known covariate shift correction techniques, Kernel Mean Matching (KMM) and Kullback Leibler Importance Estimation Procedure (KLIEP) and identify an important connection between kernel herding and KMM. Our complexity analysis shows the benefits of the Frank Wolfe approach over projected gradient methods in solving KMM and KLIEP. An empirical study then demonstrates the effectiveness and efficiency of the Frank Wolfe algorithm for correcting covariate shift in practice.
Long Term On board Prediction of People in Traffic Scenes Under Uncertainty
Venue: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Year: 2018

Progress towards advanced systems for assisted and autonomous driving is leveraging recent advances in recognition and segmentation methods. Yet, we are still facing challenges in bringing reliable driving to inner cities, as those are composed of highly dynamic scenes observed from a moving platform at considerable speeds. Anticipation becomes a key element in order to react timely and prevent accidents. In this paper we argue that it is necessary to predict at least 1 second and we thus propose a new model that jointly predicts ego motion and people trajectories over such large time horizons. We pay particular attention to modeling the uncertainty of our estimates arising from the non deterministic nature of natural traffic scenes. Our experimental results show that it is indeed possible to predict people trajectories at the desired time horizons and that our uncertainty estimates are informative of the prediction error. We also show that both sequence modeling of trajectories as well as our novel method of long term odometry prediction are essential for best performance.
Artificial Intelligence and Soft Computing: 14th International Conference, ICAISC 2015, Zakopane, Poland, June 14 28, 2015, Proceedings, Part II
Year: 2015

The two volume set LNAI 9119 and LNAI 9120 constitutes the refereed proceedings of the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2015, held in Zakopane, Poland in June 2015. The 142 revised full papers presented in the volumes, were carefully reviewed and selected from 322 submissions. These proceedings present both traditional artificial intelligence methods and soft computing techniques. The goal is to bring together scientists representing both areas of research. The first volume covers topics as follows neural networks and their applications, fuzzy systems and their applications, evolutionary algorithms and their applications, classification and estimation, computer vision, image and speech analysis and the workshop: large scale visual recognition and machine learning. The second volume has the focus on the following subjects: data mining, bioinformatics, biometrics and medical applications, concurrent and parallel processing, agent systems, robotics and control, artificial intelligence in modeling and simulation and various problems of artificial intelligence.
Effects of Sublingual Duster Mite Drops on Lung Function and Exhaled Nitric Oxide in Children with Multiple and Single Allergic Respiratory Diseases
Venue: Canadian respiratory journal
Year: 2020

To evaluate the efficiency of sublingual immunotherapy with Dermatophagoides Farinae Drops in children with single and multiple respiratory allergic diseases.  Seventy one children with allergic respiratory diseases who had been treated with Dermatophagoides Farinae Drops for one year or more were divided into a single allergic group (12 cases) and multiple allergic group (59 cases) The rhinitis score, daytime and night symptom score of asthma, VAS score, drug score, pulmonary function, and FeNO level before and after treatment were evaluated and compared between the two groups.  The rhinitis score, night symptom score, VAS score, and drug score in the single allergic group after treatment were significantly lower than those before treatment (p 0.05) but there was no significant difference in the daytime symptom score before and after treatment (p 0.05) The rhinitis score, VAS score, and drug score in the multiple allergic group after treatment were significantly lower than those before treatment (p 0.05) but there was no significant difference in the scores of daytime symptoms and nighttime symptoms before and after treatment (p 0.05) In both the single allergic group and multiple allergic group, the pulmonary function indexes of the patients were significantly improved after treatment, and the FeNO after treatment was significantly lower than that before treatment (p 0.05) There was no significant difference in scores, pulmonary function, and FeNO between the two groups (p 0.05)  Sublingual specific immunotherapy is effective in treating multiple and single allergic respiratory diseases in children.
Description of the Minimizers of Least Squares Regularized with pweb0 norm. Uniqueness of the Global Minimizer
Venue: SIAM J. Imaging Sci.
Year: 2013

We have an \sf{M}\times\sf{N} real valued arbitrary matrix $A$ (e.g. a dictionary) with \sf{M} 0$ For several decades, this objective has attracted a ceaseless effort to conceive algorithms approaching a good minimizer. Our theoretical contributions, summarized below, shed new light on the existing algorithms and can help in the conception of innovative numerical schemes. Solving the normal equation associated with any \sf{M} row submatrix of $A$ is equivalent to computing a local minimizer \hat u$ of \mathcal{F}}_d$ (Local) minimizers \hat u$ of \mathcal{F}}_d$ are strict if and only if the submatrix, composed of those columns of $A$ wh.