nils-herrmann/clean_scirepeval huggingface dataset:
Antibacterial activity of oregano (Origanum vulgare Linn.) against gram positive bacteria.

The present investigation is focused on antibacterial potential of infusion, decoction and essential oil of oregano (Origanum vulgare) against 111 Gram-positive bacterial isolates belonging to 23 different species related to 3 genera. Infusion and essential oil exhibited antibacterial activity against Staphylococcus saprophyticus, S. aureus, Micrococcus roseus, M. kristinae, M. nishinomiyaensis, M. lylae, M. luteus, M. sedentarius, M. varians, Bacillus megaterium, B. thuringiensis, B. alvei, B. circulans, B. brevis, B. coagulans, B. pumilus, B. laterosporus, B. polymyxa, B. macerans, B. subtilis, B. firmus, B. cereus and B. lichiniformis. The infusion exhibited maximum activity against B. laterosporus (17.5 mm mean zone of inhibition+/-1.5 Standard deviation) followed by B. polymyxa (17.0 mm+/-2.0 SD) and essential oil of oregano exhibited maximum activity against S. saprophyticus (16.8 mm+/-1.8 SD) followed by B. circulans (14.5 mm+/-0.5 SD). While all these tested isolates were found resistant to decoction of oregano.
A User-Modeling Approach to Build User's Psycho-Physiological Maps of Emotions using Bio-Sensors

Near to real-time emotion recognition is a promising task for human-computer interaction (HCI) and human-robot interaction (HRI). Using knowledge about the user's emotions depends upon the possibility to extract information about users' emotions during HCI or HRI without explicitly asking users about the feelings they are experiencing. To be able to sense the user's emotions without interrupting the HCI, we present a new method applied to the emotional experience of the user for extracting semantic information from the autonomic nervous system (ANS) signals associated with emotions. We use the concepts of 1st person - where the subject consciously (and subjectively) extracts the semantic meaning of a given lived experience, (e.g. `I felt amused') - and 3rd person approach - where the experimenter interprets the semantic meaning of the subject's experience from a set of externally (and objectively) measured variables (e.g. galvanic skin response measures). Based on the 3rd person approach, our technique aims at psychologically interpreting physiological parameters (skin conductance and heart rate), and at producing a continuous extraction of the user's affective state during HCI or HRI. We also combine it with the 1st person approach measure which allows a tailored interpretation of the physiological measure closely related to the user own emotional experience
Joint Placement of Controllers and Gateways in SDN-Enabled 5G-Satellite Integrated Network

Leveraging the concept of software-defined network (SDN), the integration of terrestrial 5G and satellite networks brings us lots of benefits. The placement problem of controllers and satellite gateways is of fundamental importance for design of such SDN-enabled integrated network, especially, for the network reliability and latency, since different placement schemes would produce various network performances. To the best of our knowledge, it is an entirely new problem. Toward this end, in this paper, we first explore the satellite gateway placement problem to obtain the minimum average latency. A simulated annealing based approximate solution (SAA), is developed for this problem, which is able to achieve a near-optimal latency. Based on the analysis of latency, we further investigate a more challenging problem, i.e., the joint placement of controllers and gateways, for the maximum network reliability while satisfying the latency constraint. A simulated annealing and clustering hybrid algorithm (SACA) is proposed to solve this problem. Extensive experiments based on real world online network topologies have been conducted and as validated by our numerical results, enumeration algorithms are able to produce optimal results but having extremely long running time, while SAA and SACA can achieve approximate optimal performances with much lower computational complexity.
Parameterized unit tests

Parameterized unit tests extend the current industry practice of using closed unit tests defined as parameterless methods. Parameterized unit tests separate two concerns: 1) They specify the external behavior of the involved methods for all test arguments. 2) Test cases can be re-obtained as traditional closed unit tests by instantiating the parameterized unit tests. Symbolic execution and constraint solving can be used to automatically choose a minimal set of inputs that exercise a parameterized unit test with respect to possible code paths of the implementation. In addition, parameterized unit tests can be used as symbolic summaries which allows symbolic execution to scale for arbitrary abstraction levels. We have developed a prototype tool which computes test cases from parameterized unit tests. We report on its first use testing parts of the .NET base class library.
Multipath Ghosts in Radar Imaging: Physical Insight and Mitigation Strategies

Most algorithms commonly exploited for radar imaging are based on linear models that describe only direct scattering events from the targets in the investigated scene. This assumption is rarely verified in practical scenarios where the objects to be imaged interact with each other and with surrounding environment producing undesired multipath signals. These signals manifest in radar images as “ghosts" that usually impair the reliable identification of the targets. The recent literature in the field is attempting to provide suitable techniques for multipath suppression from one side and from the other side is focusing on the exploitation of the additional information conveyed by multipath to improve target detection and localization. This work addresses the first problem with a specific focus on multipath ghosts caused by target-to-target interactions. In particular, the study is performed with regard to metallic scatterers by means of the linearized inverse scattering approach based on the physical optics (PO) approximation. A simple model is proposed in the case of point-like targets to gain insight into the ghosts problem so as to devise possible measurement and processing strategies for their mitigation. Finally, the effectiveness of these methods is assessed by reconstruction results obtained from full-wave synthetic data.
Semi-proximal Mirror-Prox for Nonsmooth Composite Minimization

We propose a new first-order optimisation algorithm to solve high-dimensional non-smooth composite minimisation problems. Typical examples of such problems have an objective that decomposes into a non-smooth empirical risk part and a non-smooth regularisation penalty. The proposed algorithm, called Semi-Proximal Mirror-Prox, leverages the Fenchel-type representation of one part of the objective while handling the other part of the objective via linear minimization over the domain. The algorithm stands in contrast with more classical proximal gradient algorithms with smoothing, which require the computation of proximal operators at each iteration and can therefore be impractical for high-dimensional problems. We establish the theoretical convergence rate of Semi-Proximal Mirror-Prox, which exhibits the optimal complexity bounds, i.e. O(1/ ), for the number of calls to linear minimization oracle. We present promising experimental results showing the interest of the approach in comparison to competing methods.
A pilot study of omalizumab to facilitate rapid oral desensitization in high-risk peanut-allergic patients.

Peanut allergy is a major public health problem that affects 1% of the population and has no effective therapy.



To examine the safety and efficacy of oral desensitization in peanut-allergic children in combination with a brief course of anti-IgE mAb (omalizumab [Xolair]).



We performed oral peanut desensitization in peanut-allergic children at high risk for developing significant peanut-induced allergic reactions. Omalizumab was administered before and during oral peanut desensitization.



We enrolled 13 children (median age, 10 years), with a median peanut-specific IgE level of 229 kU(A)/L and a median total serum IgE level of 621 kU/L, who failed an initial double-blind placebo-controlled food challenge at peanut flour doses of 100 mg or less. After pretreatment with omalizumab, all 13 subjects tolerated the initial 11 desensitization doses given on the first day, including the maximum dose of 500 mg peanut flour (cumulative dose, 992 mg, equivalent to >2 peanuts), requiring minimal or no rescue therapy. Twelve subjects then reached the maximum maintenance dose of 4000 mg peanut flour per day in a median time of 8 weeks, at which point omalizumab was discontinued. All 12 subjects continued on 4000 mg peanut flour per day and subsequently tolerated a challenge with 8000 mg peanut flour (equivalent to about 20 peanuts), or 160 to 400 times the dose tolerated before desensitization. During the study, 6 of the 13 subjects experienced mild or no allergic reactions, 5 subjects had grade 2 reactions, and 2 subjects had grade 3 reactions, all of which responded rapidly to treatment.



Among children with high-risk peanut allergy, treatment with omalizumab may facilitate rapid oral desensitization and qualitatively improve the desensitization process.
Résumé automatique de texte avec un algorithme d'ordonnancement

Dans cet article, nous proposons une nouvelle approche pour le résumé automatique de textes utilisant un algorithme d'apprentissage numérique spécifique à la tâche d'ordonnancement. L'objectif est d'extraire les phrases d'un document qui sont les plus représentatives de son contenu. Pour se faire, chaque phrase d'un document est représentée par un vecteur de scores de pertinence, où chaque score est un score de similarité entre une requête particulière et la phrase considérée. L'algorithme d'ordonnancement effectue alors une combinaison linéaire de ces scores, avec pour but d'affecter aux phrases pertinentes d'un document des scores supérieurs à ceux des phrases non pertinentes du même document. Les algorithmes d'ordonnancement ont montré leur efficacité en particulier dans le domaine de la méta-recherche, et leur utilisation pour le résumé est motivée par une analogie peut être faite entre la méta-recherche et le résumé automatique qui consiste, dans notre cas, à considérer les similarités des phrases avec les différentes requêtes comme étant des sorties de différents moteurs de recherche. Nous montrons empiriquement que l'algorithme d'ordonnancement a de meilleures performances qu'une approche utilisant un algorithme de classification sur deux corpus distincts.
Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video

In this paper, we present a probabilistic multi-task learning approach for visual saliency estimation in video. In our approach, the problem of visual saliency estimation is modeled by simultaneously considering the stimulus-driven and task-related factors in a probabilistic framework. In this framework, a stimulus-driven component simulates the low-level processes in human vision system using multi-scale wavelet decomposition and unbiased feature competition; while a task-related component simulates the high-level processes to bias the competition of the input features. Different from existing approaches, we propose a multi-task learning algorithm to learn the task-related “stimulus-saliency” mapping functions for each scene. The algorithm also learns various fusion strategies, which are used to integrate the stimulus-driven and task-related components to obtain the visual saliency. Extensive experiments were carried out on two public eye-fixation datasets and one regional saliency dataset. Experimental results show that our approach outperforms eight state-of-the-art approaches remarkably.
Using Scrum to guide the execution of software process improvement in small organizations

For software process improvement -SPIthere are few small organizations using models that guide the management and deployment of their improvement initiatives. This is largely because a lot of these models do not consider the special characteristics of small businesses, nor the appropriate strategies for deploying an SPI initiative in this type of organization. It should also be noted that the models which direct improvement implementation for small settings do not present an explicit process with which to organize and guide the internal work of the employees involved in the implementation of the improvement opportunities. In this paper we propose a lightweight process, which takes into account appropriate strategies for this type of organization. Our proposal, known as a “Lightweight process to incorporate improvements” uses the philosophy of the Scrum agile
Classical PID versus predictive control solutions for a galvanometer-based scanner

The galvanometer-based scanners (GS) are oscillatory optical systems utilized in high-end biomedical technologies. From a control point-of-view the GSs are mechatronic systems (mainly positioning servo-systems) built usually in a close loop structure and controlled by different control algorithms. The paper presents a Model based Predictive Control (MPC) solution for the mobile equipment (moving magnet and galvomirror) of a GS. The development of a high-performance control solution is based to a basic closed loop GS which consists of a PD-L1 controller and a servomotor. The mathematical model (MM) and the parameters of the basic construction are identified using a theoretical approach followed by an experimental identification. The equipment is used in our laboratory for better dynamical performances for biomedical imaging systems. The control solutions proposed are supported by simulations carried out in Matlab/Simulink.
PLDA: Parallel Latent Dirichlet Allocation for Large-Scale Applications

This paper presents PLDA, our parallel implementation of Latent Dirichlet Allocation on MPI and MapReduce. PLDA smooths out storage and computation bottlenecks and provides fault recovery for lengthy distributed computations. We show that PLDA can be applied to large, real-world applications and achieves good scalability. We have released MPI-PLDA to open source at http://code.google.com/p/plda under the Apache License.
Practice Paper of the Academy of Nutrition and Dietetics : Nutrition assessment is an essential component of the Nutrition Care

Nutrition assessment is an essential component of the Nutrition Care Process and Model (NCPM), as it is the initial step in developing a comprehensive evaluation of the client’s nutrition history. A comprehensive nutrition assessment requires the ability to observe, interpret, analyze, and infer data to diagnose nutrition problems. This practice paper provides insight into the process by which critical thinking skills are utilized by both registered dietitian nutritionists (RDNs) and dietetic technicians, registered (DTRs).
Agree or Cancel ? Research and Terms of Service Compliance

Christian Sandvig University of Michigan Room 5385 North Quad 105 South State Street Ann Arbor, MI 48109 csandvig@umich.edu Abstract We address the ACM Code of Ethics and discuss the stipulation that researchers follow terms of service. While the reasons for following terms of service are clear, we argue that there are hidden costs. Using the example of research into algorithm awareness and algorithm transparency, we argue that for some research problems the benefits to society outweigh the harm of violating terms of service. We draw attention to current strategies that researchers use to adapt to the ACM prohibition on research violating terms of service and some results of those approaches. We conclude with recommendations for determining researchers’ current understanding of the ACM Code of Ethics and terms of service restrictions and updating the existing guidelines.
Spondyloarthropathies in Japan: nationwide questionnaire survey performed by the Japan Ankylosing Spondylitis Society.

The Japan Ankylosing Spondylitis Society conducted a nationwide questionnaire survey of spondyloarthropathies (SpA) in 1990 and 1997, (1) to estimate the prevalence and incidence, and (2) to validate the criteria of Amor and the European Spondylarthropathy Study Group (ESSG) in Japan.



Japan was divided into 9 districts, to each of which a survey supervisor was assigned. According to unified criteria, each supervisor selected all the clinics and hospitals with potential for SpA patients in the district. The study population consisted of all patients with SpA seen at these institutes during a 5 year period (1985-89) for the 1st survey and a 7 year period (1990-96) for the 2nd survey.



The 1st survey recruited 426 and the 2nd survey 638 cases, 74 of which were registered in both studies. The total number of patients with SpA identified 1985-96 was 990 (760 men, 227 women). They consisted of patients with ankylosing spondylitis (68.3%), psoriatic arthritis (12.7%), reactive arthritis (4.0%), undifferentiated SpA (5.4%), inflammatory bowel disease (2.2%), pustulosis palmaris et plantaris (4.7%), and others (polyenthesitis, etc.) (0.8%). The maximum onset number per year was 49. With the assumption that at least one-tenth of the Japanese population with SpA was recruited, incidence and prevalence were estimated not to exceed 0.48/100,000 and 9.5/100,000 person-years, respectively. The sensitivity was 84.0% for Amor criteria and 84.6 for ESSG criteria.



The incidence and prevalence of SpA in Japanese were estimated to be less than 1/10 and 1/200, respectively, of those among Caucasians. The adaptability of the Amor and ESSG criteria was validated for the Japanese population.
Speech-Driven Facial Reenactment Using Conditional Generative Adversarial Networks

We present a novel approach to generating photo-realistic images of a face with accurate lip sync, given an audio input. By using a recurrent neural network, we achieved mouth landmarks based on audio features. We exploited the power of conditional generative adversarial networks to produce highly-realistic face conditioned on a set of landmarks. These two networks together are capable of producing sequence of natural faces in sync with an input audio track.
Comparative simulation study between n-type and p-type Silicon Solar Cells and the variation of efficiency of n-type Solar Cell by the application of passivation layer with different thickness using

In this paper, comparative study of p type and n type solar cells are described using two popular solar cell analyzing software AFORS HET and PC1D. We use SiNx layer as Antireflection Coating and a passivated layer Al2O3 .The variation of reflection, absorption, I-V characteristics, and internal and external quantum efficiency have been done by changing the thickness of passivated layer and ARC layer, and front and back surface recombination velocities. The same analysis is taken by imposing surface charge at front of n-type solar Cell and we get 20.13%-20.15% conversion efficiency.
Generalized Self-Driven AC–DC Synchronous Rectification Techniques for Single- and Multiphase Systems

This paper extends the single-phase self-driven synchronous rectification (SDSR) technique to multiphase ac-dc systems. Power MOSFETs with either voltage- or current-sensing self-driven gate drives are used to replace the diodes in the rectifier circuits. The generalized methodology allows multiphase SDSRs to be designed to replace the multiphase diode rectifiers. Unlike the traditional SR that is designed for high-frequency power converters, the SDSR proposed here can be a direct replacement of the power diode bridges for both low- and high-frequency operations. The SDSR utilizes its output dc voltage to supply power to its control circuit. No start-up control is needed because the body diodes of the power MOSFETs provide the diode rectifier for the initial start-up stage. The generalized method is demonstrated in 2-kW one-phase and three-phase SDSRs for inductive, capacitive, and resistive loads. Power loss reduction in the range of 50%-69% has been achieved for the resistive load.
Association study of stuttering candidate genes GNPTAB, GNPTG and NAGPA with dyslexia in Chinese population

Dyslexia is a polygenic speech and language disorder characterized by an unexpected difficulty in reading in children and adults despite normal intelligence and schooling. Increasing evidence reveals that different speech and language disorders could share common genetic factors. As previous study reported association of GNPTAB, GNPTG and NAGPA with stuttering, we investigated these genes with dyslexia through association analysis. The study was carried out in an unrelated Chinese cohort with 502 dyslexic individuals and 522 healthy controls. In all, 21 Tag SNPs covering GNPTAB, GNPTG and NAGPA were subjected to genotyping. Association analysis was performed on all SNPs. Significant association of rs17031962 in GNPTAB and rs882294 in NAGPA with developmental dyslexia was identified after FDR correction for multiple comparisons. Our results revealed that the stuttering risk genes GNPTAB and NAGPA might also associate with developmental dyslexia in the Chinese population.
Succeeding through Disruption : Exploring the Factors Influencing the Adoption of Disruptive Technologies in the Mobile Telecommunications Industry in Zimbabwe Africa Makasi

The research explored factors influencing the adoption of disruptive technologies in the mobile telecommunications industry in Zimbabwe. Data was gathered from the second biggest competitor in the industry with over 3 million subscribers. A survey was conducted by purposively selecting 70 respondents from a population of 3,000,000 (three million) active subscribers from the company’s database. A skip interval of 42,857 was used to randomly select the sample. Customer representatives were selected from the company’s five regional offices using a two-stage cluster sampling technique. Employee participants were purposively selected from the company’s head office. A pilot test was conducted to assess the reliability of the research instrument used. Self-administered questionnaires were used in the research. Research results were collected, recorded and analyzed. All T-tests conducted produced results with p= 0.001 (which was less than 0.05 at which the tests were conducted) indicating that internal company influences such as staff competence, availability of funding and the type of infrastructure help impede or accelerate the rate of adoption of disruptive technologies in companies. Future research should however look at organizational ambidexterity as well as exploitation and exploration paradigms in organizations in the telecommunications industry and their impact on the adoption of disruptive technologies.