nils-herrmann/clean_scirepeval huggingface dataset:
Physiological responses to humic substances as plant growth promoter

Humic substances (HS) have been widely recognized as a plant growth promoter mainly by changes on root architecture and growth dynamics, which result in increased root size, branching and/or greater density of root hair with larger surface area. Stimulation of the H+-ATPase activity in cell membrane suggests that modifications brought about by HS are not only restricted to root structure, but are also extended to the major biochemical pathways since the driving force for most nutrient uptake is the electrochemical gradient across the plasma membrane. Changes on root exudation profile, as well as primary and secondary metabolism were also observed, though strongly dependent on environment conditions, type of plant and its ontogeny. Proteomics and genomic approaches with diverse plant species subjected to HS treatment had often shown controversial patterns of protein and gene expression. This is a clear indication that HS effects of plants are complex and involve non-linear, cross-interrelated and dynamic processes that need be treated with an interdisciplinary view. Being the humic associations recalcitrant to microbiological attack, their use as vehicle to introduce beneficial selected microorganisms to crops has been proposed. This represents a perspective for a sort of new biofertilizer designed for a sustainable agriculture, whereby plants treated with HS become more susceptible to interact with bioinoculants, while HS may concomitantly modify the structure/activity of the microbial community in the rhizosphere compartment. An enhanced knowledge of the effects on plants physiology and biochemistry and interaction with rhizosphere and endophytic microbes should lead to achieve increased crop productivity through a better use of HS inputs in
Re-examining mechanic's hands as a characteristic skin finding in dermatomyositis.

Mechanic's hands is a poorly defined clinical finding that has been reported in a variety of rheumatologic diseases. Morphologic descriptions include hyperkeratosis on the sides of the digits that sometimes extends to the distal tips, diffuse palmar scale, and (more recently observed) linear discrete scaly papules in a similar lateral distribution. The association of mechanic's hands with dermatomyositis, although recognized, is still debatable. In this review, most studies have shown that mechanic's hands is commonly associated with dermatomyositis and displays histopathologic findings of interface dermatitis, colloid bodies, and interstitial mucin, which are consistent with a cutaneous connective tissue disease. A more specific definition of this entity would help to determine its usefulness in classifying and clinically identifying patients with dermatomyositis, with implications related to subsequent screening for associated comorbidities in this setting.
WIDE AWAKE Mediates the Circadian Timing of Sleep Onset

How the circadian clock regulates the timing of sleep is poorly understood. Here, we identify a Drosophila mutant, wide awake (wake), that exhibits a marked delay in sleep onset at dusk. Loss of WAKE in a set of arousal-promoting clock neurons, the large ventrolateral neurons (l-LNvs), impairs sleep onset. WAKE levels cycle, peaking near dusk, and the expression of WAKE in l-LNvs is Clock dependent. Strikingly, Clock and cycle mutants also exhibit a profound delay in sleep onset, which can be rescued by restoring WAKE expression in LNvs. WAKE interacts with the GABAA receptor Resistant to Dieldrin (RDL), upregulating its levels and promoting its localization to the plasma membrane. In wake mutant l-LNvs, GABA sensitivity is decreased and excitability is increased at dusk. We propose that WAKE acts as a clock output molecule specifically for sleep, inhibiting LNvs at dusk to promote the transition from wake to sleep.
GoalBaural: A Training Application for Goalball-related Aural Sense

Goalball, one of the official Paralympic events, is popular with visually impaired people all over the world. The purpose of goalball is to throw the specialized ball, with bells inside it, to the goal line of the opponents as many times as possible while defenders try to block the thrown ball with their bodies. Since goalball players cannot rely on visual information, they need to grasp the game situation using their auditory sense. However, it is hard, especially for beginners, to perceive the direction and distance of the thrown ball. In addition, they generally tend to be afraid of the approaching ball because, without visual information, they could be hit by a high-speed ball. In this paper, our goal is to develop an application called GoalBaural (Goalball + aural) that enables goalball players to improve the recognizability of the direction and distance of a thrown ball without going onto the court and playing goalball. The evaluation result indicated that our application would be efficient in improving the speed and the accuracy of locating the balls.
Glycerol ( Byproduct of Biodiesel Production ) as a Source for Fuels and Chemicals – Mini Review

Currently the large surplus of glycerol formed as a by-product during the production of biodiesel offered an abundant and low cost feedstock. Researchers showed a surge of interest in using glycerol as renewable feedstock to produce functional chemicals. This Minireview focuses on recent developments in the conversion of glycerol into valueadded products, including citric acid, lactic acid, 1,3-dihydroxyacetone (DHA), 1,3-propanediol (1,3-PD), dichloro-2propanol (DCP), acrolein, hydrogen, and ethanol etc. The versatile new applications of glycerol in the everyday life and chemical industry will improve the economic viability of the biodiesel industry.
The use of focused ultrasound for non-invasive body contouring in Asians.

Previous studies demonstrated that multiple treatments using focused ultrasound can be effective as an non-invasive method for reducing unwanted localized fat deposits. The objective of the study is to investigate the safety and efficacy of this focused ultrasound device in body contouring in Asians.



Fifty-three (51 females and 2 males) patients were enrolled into the study. Subjects had up to three treatment sessions with approximately 1-month interval in between treatment. Efficacy was assessed by changes in abdominal circumference, ultrasound fat thickness, and caliper fat thickness. Weight change was monitored to distinguish weight loss induced changes in these measurements. Patient questionnaire was completed after each treatment. The level of pain or discomfort, improvement in body contour and overall satisfaction were graded with a score of 1-5 (1 being the least). Any adverse effects such as erythema, pain during treatment or blistering were recorded.



The overall satisfaction amongst subjects was poor. Objective measurements by ultrasound, abdominal circumference, and caliper did not show significant difference after treatment. There is a negative correlation between the abdominal fat thickness and number of shots per treatment session.



Focused ultrasound is not effective for non-invasive body contouring among Southern Asians as compared with Caucasian. Such observation is likely due to smaller body figures. Design modifications can overcome this problem and in doing so, improve clinical outcome.
Information system end-user satisfaction and continuance intention: A unified modeling approach

Permanent evaluation of end-user satisfaction and continuance intention is a critical issue at each phase of a clinical information system (CIS) project, but most validation studies are concerned with the pre- or early post-adoption phases.



The purpose of this study was twofold: to validate at the Pompidou University Hospital (HEGP) an information technology late post-adoption model built from four validated models and to propose a unified metamodel of evaluation that could be adapted to each context or deployment phase of a CIS project.



Five dimensions, i.e., CIS quality (CISQ), perceived usefulness (PU), confirmation of expectations (CE), user satisfaction (SAT), and continuance intention (CI) were selected to constitute the CI evaluation model. The validity of the model was tested using the combined answers to four surveys performed between 2011 and 2015, i.e., more than ten years after the opening of HEGP in July 2000. Structural equation modeling was used to test the eight model-associated hypotheses.



The multi-professional study group of 571 responders consisted of 158 doctors, 282 nurses, and 131 secretaries. The evaluation model accounted for 84% of variance of satisfaction and 53% of CI variance for the period 2011-2015 and for 92% and 69% for the period 2014-2015. In very late post adoption, CISQ appears to be the major determinant of satisfaction and CI. Combining the results obtained at various phases of CIS deployment, a Unified Model of Information System Continuance (UMISC) is proposed.



In a meaningful CIS use situation at HEGP, this study confirms the importance of CISQ in explaining satisfaction and CI. The proposed UMISC model that can be adapted to each phase of CIS deployment could facilitate the necessary efforts of permanent CIS acceptance and continuance evaluation.
Immediate dentin sealing of onlay preparations: thickness of pre-cured Dentin Bonding Agent and effect of surface cleaning.

This study evaluated the thickness of Dentin Bonding Agent (DBA) used for "immediate dentin sealing" of onlay preparations prior to final impression making for indirect restorations. In addition, the amount of DBA that is removed when the adhesive surface is cleaned with polishing or air abrasion prior to final cementation was evaluated. For this purpose, a standardized onlay preparation was prepared in 12 extracted molars, and either OptiBond FL (Kerr) or Syntac Classic (Vivadent) was applied to half of the teeth and cured in the absence of oxygen (air blocking). Each tooth was bisected in a bucco-lingual direction into two sections, and the thickness of the DBA was measured under SEM on gold sputtered epoxy resin replicas at 11 positions. The DBA layer of each half tooth was treated with either air abrasion or polishing. The thickness of the DBAs was then re-measured on the replicas at the same positions. The results were statistically analyzed with non-parametric statistics (Mann-Whitney U test and Kruskal-Wallis test) at a confidence level of 95% (p=0.05). The film thickness of the DBA was not uniform across the adhesive interface (121.13 +/- 107.64 microm), and a great range of values was recorded (0 to 500 microm). Statistically significant differences (p<0.05) were noted, which were both material (OptiBond FL or Syntac Classic) and position (1 to 11) dependent. Syntac Classic presented a higher thickness of DBA (142.34 +/- 125.10 microm) than OptiBond FL (87.99 +/- 73.76 microm). The higher film thickness of both DBAs was at the deepest part of the isthmus (the most concave part of the preparation), while the lowest was at the line angles of the dentinal crest (the most convex part of the preparation). OptiBond FL presented a more uniform thickness around the dentinal crest of preparation; Syntac Classic pooled at the lower parts of the preparation. The amount of DBA that was removed with air abrasion or polishing was not uniform (11.94 +/- 16.46 microm), and a great range of values was recorded (0 to 145 microm). No statistically significant differences (p<0.05) were found either between different DBAs (OptiBond FL or Syntac Classic) or between different treatments (air abrasion or polishing). As far as the effect of different treatments at different positions, polishing removed more DBA from the top of the dentinal crest, but the difference was not statistically significant. Air abrasion removed less DBA from the corners of the dentinal crest (Positions 4 and 6) than the outer buccal part of the preparation (Positions 1 and 2). Neither air abrasion nor polishing removed the entire layer thickness of the DBA in the majority of the cases.
Resolving Lexical Ambiguity in Tensor Regression Models of Meaning

This paper provides a method for improving tensor-based compositional distributional models of meaning by the addition of an explicit disambiguation step prior to composition. In contrast with previous research where this hypothesis has been successfully tested against relatively simple compositional models, in our work we use a robust model trained with linear regression. The results we get in two experiments show the superiority of the prior disambiguation method and suggest that the effectiveness of this approach is modelindependent.
QnDReview: read 100 CHI papers in 7 hours

In 2013, 392 research papers and notes were published in the CHI conference (The ACM CHI Conference on Human Factors in Computing Systems) and even more papers in the domain of Human-Computer Interaction (HCI) are constantly published in various conferences and journals. It is quite arduous, if not impossible, to read all of these papers. One approach to deal with this information deluge is to focus on skimming through lots of papers in a short period of time, so that one can more wisely choose what to read before investing time in them. In order to teach such a skimming technique, I have taught a technique, called "Quick and Dirty Review (QnDReview)," in a graduate-level HCI course. The method has been employed in the course for five semesters, and students' responses were collected and analyzed. Results showed that students spent, on average, 4.3 minutes per paper and believed that they got the gist of each paper. However, the largest benefit I noticed is that students get the overall pictures of the fields while exposing themselves to various new ideas through this approach.
Real-time reverse transcriptase-polymerase chain reaction (RT-PCR) for measurement of cytokine and growth factor mRNA expression with fluorogenic probes or SYBR Green I.

Real-time quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) is the method of choice for rapid and reproducible measurements of cytokine or growth factor expression in small samples. Fluorescence detection methods for monitoring real-time PCR include fluorogenic probes labelled with reporter and quencher dyes, such as Taqman probes or Molecular Beacons and the dsDNA-binding dye SYBR Green I. Fluorogenic (Taqman) probes for a range of human and rat cytokines and growth factors were tested for sensitivity and compared with an assay for SYBR Green I quantification using real-time fluorescence monitoring (PE Applied Biosystems Model 7700 sequence detector). SYBR Green I detection involved analysis of the melting temperature of the PCR product and measurement of fluorescence at the optimum temperature. Fluorogenic probes provided sensitive and reproducible detection of targets that ranged from low (<10 copies/reaction) to high (>107 copies/ reaction) expression. SYBR Green I gave reproducible quantification when the target gene was expressed at moderate to high levels (> or =1000 copies/reaction), but did not give consistently reproducible quantification when the target gene was expressed at low levels. Although optimization of melting temperature improved the specificity of SYBR Green I detection, in our hands it did not equal the reproducible sensitivity and specificity of fluorogenic probes. The latter method is the first choice for measurement of low-level gene expression, although SYBR Green I is a simple and reproducible means to quantify genes that are expressed at moderate to high levels.
Contributing Knowledge to Electronic Knowledge Repositories: An Empirical Investigation

Organizations are attempting to leverage their knowledge resources by employing knowledge management (KM) systems, a key form of which are electronic knowledge repositories (EKRs). A large number of KM initiatives fail due to reluctance of employees to share knowledge through these systems. Motivated by such concerns, this study formulates and tests a theoretical model to explain EKR usage by knowledge contributors. The model employs social exchange theory to identify cost and benefit factors affecting EKR usage, and social capital theory to account for the moderating influence of contextual factors. The model is validated through a large-scale survey of public sector organizations. The results reveal that knowledge self-efficacy and enjoyment in helping others significantly impact EKR usage by knowledge contributors. Contextual factors (generalized trust, pro-sharing norms, and identification) moderate the impact of codification effort, reciprocity, and organizational reward on EKR usage, respectively. It can be seen that extrinsic benefits (reciprocity and organizational reward) impact EKR usage contingent on particular contextual factors whereas the effects of intrinsic benefits (knowledge self-efficacy and enjoyment in helping others) on EKR usage are not moderated by contextual factors. The loss of knowledge power and image do not appear to impact EKR usage by knowledge contributors. Besides contributing to theory building in KM, the results of this study inform KM practice.
Incremental Semantic Construction in a Dialogue System

This paper describes recent work on the DynDial project ∗ towards incremental semantic interpretation in dialogue. We outline our domain-general gramm r-based approach, using a variant of Dynamic Syntax integrated with Type Theory with Records and Davidsonian event-based semantics. We describe a Java-based implementation of the parser , u d within the Jindigo framework to produce an incremental dialogue system capable of handling inherently incremental phenomena such as split utterances, adjuncts, and mid-sentence clarificat ion requests or backchannels.
Fast estimation of Gaussian mixture models for image segmentation

The expectation maximization algorithm has been classically used to find the maximum likelihood estimates of parameters in probabilistic models with unobserved data, for instance, mixture models. A key issue in such problems is the choice of the model complexity. The higher the number of components in the mixture, the higher will be the data likelihood, but also the higher will be the computational burden and data overfitting. In this work, we propose a clustering method based on the expectation maximization algorithm that adapts online the number of components of a finite Gaussian mixture model from multivariate data or method estimates the number of components and their means and covariances sequentially, without requiring any careful initialization. Our methodology starts from a single mixture component covering the whole data set and sequentially splits it incrementally during expectation maximization steps. The coarse to fine nature of the algorithm reduce the overall number of computations to achieve a solution, which makes the method particularly suited to image segmentation applications whenever computational time is an issue. We show the effectiveness of the method in a series of experiments and compare it with a state-of-the-art alternative technique both with synthetic data and real images, including experiments with images acquired from the iCub humanoid robot.
Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data

It is crucial for cancer diagnosis and treatment to accurately identify the site of origin of a tumor. With the emergence and rapid advancement of DNA microarray technologies, constructing gene expression profiles for different cancer types has already become a promising means for cancer classification. In addition to research on binary classification such as normal versus tumor samples, which attracts numerous efforts from a variety of disciplines, the discrimination of multiple tumor types is also important. Meanwhile, the selection of genes which are relevant to a certain cancer type not only improves the performance of the classifiers, but also provides molecular insights for treatment and drug development. Here, we use semisupervised ellipsoid ARTMAP (ssEAM) for multiclass cancer discrimination and particle swarm optimization for informative gene selection. ssEAM is a neural network architecture rooted in adaptive resonance theory and suitable for classification tasks. ssEAM features fast, stable, and finite learning and creates hyperellipsoidal clusters, inducing complex nonlinear decision boundaries. PSO is an evolutionary algorithm-based technique for global optimization. A discrete binary version of PSO is employed to indicate whether genes are chosen or not. The effectiveness of ssEAM/PSO for multiclass cancer diagnosis is demonstrated by testing it on three publicly available multiple-class cancer data sets. ssEAM/PSO achieves competitive performance on all these data sets, with results comparable to or better than those obtained by other classifiers
Convolutional Neural Network Classification loss MultiTask Loss Similarity Loss y Feature Embedding Sentiment Constraint

Affective image understanding has been extensively studied in the last decade since more and more users express emotion via visual contents. While current algorithms based on convolutional neural networks aim to distinguish emotional categories in a discrete label space, the task is inherently ambiguous. This is mainly because emotional labels with the same polarity (i.e., positive or negative) are highly related, which is different from concrete object concepts such as cat, dog and bird. To the best of our knowledge, few methods focus on leveraging such characteristic of emotions for affective image understanding. In this work, we address the problem of understanding affective images via deep metric learning and propose a multi-task deep framework to optimize both retrieval and classification goals. We propose the sentiment constraints adapted from the triplet constraints, which are able to explore the hierarchical relation of emotion labels. We further exploit the sentiment vector as an effective representation to distinguish affective images utilizing the texture representation derived from convolutional layers. Extensive evaluations on four widely-used affective datasets, i.e., Flickr and Instagram, IAPSa, Art Photo, and Abstract Paintings, demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods on both affective image retrieval and classification tasks.
Workload Management in Dynamic IT Service Delivery Organizations

Enterprises and service providers are increasingly looking to global service delivery as a means for containing costs while improving the quality of service delivery. However, it is often difficult to effectively manage the conflicting needs associated with dynamic customer workload, strict service level constraints, and efficient service personnel organization. In this paper we propose a dynamic approach for workload and personnel management, where organization of personnel is dynamically adjusted based upon differences between observed and target service level metrics. Our approach consists of constructing a dynamic service delivery organization and developing a feedback control mechanism for dynamic workload management. We demonstrate the effectiveness of the proposed approach in an IT incident management example designed based on a large service delivery environment handling more than ten thousand service requests over a period of six months.