nils-herrmann/clean_scirepeval huggingface dataset:
Deep Learning Phase Segregation

Phase segregation, the process by which the components of a binary mixture spontaneously separate, is a key process in the evolution and design of many chemical, mechanical, and biological systems. In this work, we present a data-driven approach for the learning, modeling, and prediction of phase segregation. A direct mapping between an initially dispersed, immiscible binary fluid and the equilibrium concentration field is learned by conditional generative convolutional neural networks. Concentration field predictions by the deep learning model conserve phase fraction, correctly predict phase transition, and reproduce area, perimeter, and total free energy distributions up to 98% accuracy.
Liu Acupuncture Analgesia : I . The Scientific Basis

Paul White, PhD, MD§ Acupuncture has been used in China and other Asian countries for the past 3000 yr. Recently, this technique has been gaining increased popularity among physicians and patients in the United States. Even though acupuncture-induced analgesia is being used in many pain management programs in the United States, the mechanism of action remains unclear. Studies suggest that acupuncture and related techniques trigger a sequence of events that include the release of neurotransmitters, endogenous opioid-like substances, and activation of c-fos within the central nervous system. Recent developments in central nervous system imaging techniques allow scientists to better evaluate the chain of events that occur after acupuncture-induced stimulation. In this review article we examine current biophysiological and imaging studies that explore the mechanisms of acupuncture analgesia.
An Entropy Model for Loiterer Retrieval across Multiple Surveillance Cameras

Loitering is a suspicious behavior that often leads to criminal actions, such as pickpocketing and illegal entry. Tracking methods can determine suspicious behavior based on trajectory, but require continuous appearance and are difficult to scale up to multi-camera systems. Using the duration of appearance of features works on multiple cameras, but does not consider major aspects of loitering behavior, such as repeated appearance and trajectory of candidates. We introduce an entropy model that maps the location of a person's features on a heatmap. It can be used as an abstraction of trajectory tracking across multiple surveillance cameras. We evaluate our method over several datasets and compare it to other loitering detection methods. The results show that our approach has similar results to state of the art, but can provide additional interesting candidates.
Fake reviews detection based on LDA

It is necessary for potential consume to make decision based on online reviews. However, its usefulness brings forth a curse - deceptive opinion spam. The deceptive opinion spam mislead potential customers and organizations reshaping their businesses and prevent opinion-mining techniques from reaching accurate conclusions. Thus, the detection of fake reviews has become more and more fervent. In this work, we attempt to find out how to distinguish between fake reviews and non-fake reviews by using linguistic features in terms of Yelp Filter Dataset. To our surprise, the linguistic features performed well. Further, we proposed a method to extract features based on Latent Dirichlet Allocation. The result of experiment proved that the method is effective.
GUI Design for IDE Command Recommendations

This paper describes a novel design of a graphical user interface (GUI) to recommend useful command within an integrated development environment. The recommendation GUI contains a description of the suggested command, an explanation why the command is recommended, and a command usage example. The proposed design is based on the analysis of relevant guidelines identified in the literature. Its perceived usability and acceptance were evaluated in a live user study with 36 software developers. Our findings, partially contradicting existing literature, indicate that the presentation of the command-the description and the example-is perceived as more useful than the explanation of the rationale for the recommendation.
Improved thermal design of fin heat sink for high-power LED lamp cooling

The efficient cooling is very important for a light emitting diode (LED) module because both the energy efficiency and lifespan decrease significantly as the junction temperature increases. The fin heat sink is commonly used for cooling LED modules with natural convection conditions. This work proposed a new design method for high-power LED lamp cooling by combining plate fins with pin fins and oblique fins. Two new types of fin heat sinks called the pin-plate fin heat sink (PPF) and the oblique-plate fin heat sink (OPF) were designed and their heat dissipation performances were compared with three conventional fin heat sinks, the plate fin heat sink, the pin fin heat sink and the oblique fin heat sink. The LED module was assumed to be operated under 1 atmospheric pressure and its heat input is set to 4 watts. The PPF and OPF models show lower junction temperatures by about 6°C ~ 12°C than those of three conventional models. The PPF with 8 plate fins inside (PPF-8) and the OPF with 7 plate fins inside (OPF-7) showed the best thermal performance among all the PPF and OPF designs, respectively. The total thermal resistances of the PPF-8 and OPF-7 models decreased by 9.0% ~ 15.6% compared to those of three conventional models.
Vehicle Embedded Data Stream Processing Platform for Android Devices

Automotive information services utilizing vehicle data are rapidly expanding. However, there is currently no data centric software architecture that takes into account the scale and complexity of data involving numerous sensors. To address this issue, the authors have developed an in-vehicle datastream management system for automotive embedded systems (eDSMS) as data centric software architecture. Providing the data stream functionalities to drivers and passengers are highly beneficial. This paper describes a vehicle embedded data stream processing platform for Android devices. The platform enables flexible query processing with a dataflow query language and extensible operator functions in the query language on the platform. The platform employs architecture independent of data stream schema in in-vehicle eDSMS to facilitate smoother Android application program development. This paper presents specifications and design of the query language and APIs of the platform, evaluate it, and discuss the results. Android, automotive, data stream management system
An investigation of the efficacy of oral myofunctional therapy as a precursor to articulation therapy for pre-first grade children.

This study investigated the assumption that oral myofunctional services might facilitate remediation of articulation disorders. Subjects were ten 6-year-old elementary school children who exhibited both tongue-thrust behaviors and articulation errors. All subjects had equal service time for a 14-week period, half receiving articulation services only and the other half receiving oral myofunctional services prior to and in conjunction with articulation services. Results showed that children in both programs made essentially equal progress in correcting placement of tongue-tip sounds, remediating /s/ and /z/ misarticulation, and remediating general articulation errors. Only children who received oral myofunctional services remediated tongue-thrust behaviors.
Risk management in Agile software development: A comparative study

The main goal of agile development methods is to reduce risk thereby resulting in more successful and effective information systems. Indeed, Finding out, analyzing, prioritising, and planning risks are important activities in all development approaches, including Agile development. However, while there is an extensive body of academic literature on risk management, few little researches have attempted to study risk management in Agile development projects. This paper discusses the Risk Management (RM) activities in Agile software development, and shows how using Agile can help with traditional RM process. Finally, the paper sheds light on the benefits and limitations of some Agile methodologies from a RM perspective and highlights directions for future work in this topic.
Design of Ethernet-CAN Protocol Conversion Module Based on STM32

CAN bus is ISO international standard serial communication protocol. It is one of the most widely used fieldbus in the world. It has become the standard bus of embedded industrial control LAN. Ethernet is the most common communication protocol standard that is applied in the existing LAN. Networked industrial control usually adopts fieldbus and Ethernet network, thus the protocol conversion problems of the heterogeneous network composed of Ethernet and CAN bus has become one of the research hotspots in the technology of the industrial control network. STM32F103RC ARM microprocessor was used in the design of the Ethernet-CAN protocol conversion module, the simplified TCP/IP communication protocol uIP protocol was adopted to improve the efficiency of the protocol conversion and guarantee the stability of the system communication. The results of the experiments show that the designed module can realize high-speed and transparent protocol conversion.
S-band dual circular polarized spherical conformal phased array antenna

In this paper, an S-band dual circular polarized (CP) spherical conformal phased array antenna (SPAA) is designed. It has the ability to scan a beam within the hemisphere coverage. There are 23 elements uniformly arranged on the hemispherical dome. The design process of the SPAA is presented in detail. Three different kinds of antenna elements are compared. The gain of the SPAA is more than 13 dBi and the gain flatness is less than 1 dB within the scanning range. The measured result is consistent well with the simulated one.
New approach with muller method for profit based unit commitment

This paper presents a new approach with Muller method for solving profit based unit commitment (PBUC). In deregulated environment, the generation companies (GENCOs) schedule their generators to maximize their profit rather than satisfying the power demand. While solving the PBUC problem, the information of forecasted price at the given predicted power demand is known. The PBUC problem is solved by the proposed approach in two stages. Initially, committed units table obtains information of the committed units and finally the non linear programming sub problem of economic dispatch is solved by Muller method. The proposed approach has been tested on a power system with 3 and 10 generating units. Simulation results of the proposed approach have been compared with existing methods and also with the traditional unit commitment. It is observed from the simulation results that the proposed algorithm provides maximum profit with less computational time compare to existing methods.
A Neural Architecture for Dialectal Arabic Segmentation

The automated processing of Arabic dialects is challenging due to the lack of spelling standards and the scarcity of annotated data and resources in general. Segmentation of words into their constituent tokens is an important processing step for natural language processing. In this paper, we show how a segmenter can be trained on only 350 annotated tweets using neural networks without any normalization or reliance on lexical features or linguistic resources. We deal with segmentation as a sequence labeling problem at the character level. We show experimentally that our model can rival state-of-the-art methods that heavily depend on additional resources.
Dialyzer reuse--part II: advantages and disadvantages.

Although single dialyzer use and reuse by chemical reprocessing are both associated with some complications, there is no definitive advantage to either in this respect. Some complications occur mainly at the first use of a dialyzer: a new cellophane or cuprophane membrane may activate the complement system, or a noxious agent may be introduced to the dialyzer during production or generated during storage. These agents may not be completely removed during the routine rinsing procedure. The reuse of dialyzers is associated with environmental contamination, allergic reactions, residual chemical infusion (rebound release), inadequate concentration of disinfectants, and pyrogen reactions. Bleach used during reprocessing causes a progressive increase in dialyzer permeability to larger molecules, including albumin. Reprocessing methods without the use of bleach are associated with progressive decreases in membrane permeability, particularly to larger molecules. Most comparative studies have not shown differences in mortality between centers reusing and those not reusing dialyzers, however, the largest cluster of dialysis-related deaths occurred with single-use dialyzers due to the presence of perfluorohydrocarbon introduced during the manufacturing process and not completely removed during preparation of the dialyzers before the dialysis procedure. The cost savings associated with reuse is substantial, especially with more expensive, high-flux synthetic membrane dialyzers. With reuse, some dialysis centers can afford to utilize more efficient dialyzers that are more expensive; consequently they provide a higher dose of dialysis and reduce mortality. Some studies have shown minimally higher morbidity with chemical reuse, depending on the method. Waste disposal is definitely decreased with the reuse of dialyzers, thus environmental impacts are lessened, particularly if reprocessing is done by heat disinfection. It is safe to predict that dialyzer reuse in dialysis centers will continue because it also saves money for the providers. Saving both time for the patient and money for the provider were the main motivations to design a new machine for daily home hemodialysis. The machine, developed in the 1990s, cleans and heat disinfects the dialyzer and lines in situ so they do not need to be changed for a month. In contrast, reuse of dialyzers in home hemodialysis patients treated with other hemodialysis machines is becoming less popular and is almost extinct.
Galaxy Zoo : morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey

In order to understand the formation and subsequent evolution of galaxies one must first distinguish between the two main morphological classes of massive systems: spirals and early-type systems. This paper introduces a project, Galaxy Zoo, which provides visual morphological classifications for nearly one million galaxies, extracted from the Sloan Digital Sky Survey (SDSS). This achievement was made possible by inviting the general public to visually inspect and classify these galaxies via the internet. The project has obtained more than 4 × 107 individual classifications made by ∼105 participants. We discuss the motivation and strategy for this project, and detail how the classifications were performed and processed. We find that Galaxy Zoo results are consistent with those for subsets of SDSS galaxies classified by professional astronomers, thus demonstrating that our data provide a robust morphological catalogue. Obtaining morphologies by direct visual inspection avoids introducing biases associated with proxies for morphology such as colour, concentration or structural parameters. In addition, this catalogue can be used to directly compare SDSS morphologies with older data sets. The colour–magnitude diagrams for each morphological class are shown, and we illustrate how these distributions differ from those inferred using colour alone as a proxy for
Combining Statistics-Based and CNN-Based Information for Sentence Classification

Sentence classification, serving as the foundation of the subsequent text-based processing, continues attracting researchers attentions. Recently, with the great success of deep learning, convolutional neural network (CNN), a kind of common architecture of deep learning, has been widely used to this filed and achieved excellent performance. However, most CNN-based studies focus on using complex architectures to extract more effective category information, requiring more time in training models. With the aim to get better performance with less time cost on classification, this paper proposes two simple and effective methods by fully combining information both extracted from statistics and CNN. The first method is S-SFCNN, which combines statistical features and CNN-based probabilistic features of classification to build feature vectors, and then the vectors are used to train the logistic regression classifiers. And the second method is C-SFCNN, which combines CNN-based features and statistics-based probabilistic features of classification to build feature vectors. In the two methods, the Naive Bayes log-count ratios are selected as the text statistical features and the single-layer and single channel CNN is used as our CNN architecture. The testing results executed on 7 tasks show that our methods can achieve better performance than many other complex CNN models with less time cost. In addition, we summarized the main factors influencing the performance of our methods though experiment.
Multiband MIMO antenna for 4G mobile terminal

A multiband MIMO antenna for a 4G mobile terminal is proposed. The antenna structure consists of a multiband main antenna element, a printed inverted-L subantenna element operating in the higher 2.5 GHz bands, and a wideband loop sub-antenna element working in lower 0.9 GHz band. In order to improve the isolation and ECC characteristics of the proposed MIMO antenna, each element is located at a different corner of the ground plane. In addition, the inductive coils are employed to reduce the antenna volume and realize the wideband property of the loop sub-antenna element. Finally, the proposed antenna covers LTE band 7/8, PCS, WiMAX, and WLAN service, simultaneously. The MIMO antenna has ECC lower than 0.15 and isolation higher than 12 dB in both lower and higher frequency bands.
Research Note - Investigating the Influence of the Functional Mechanisms of Online Product Presentations

I interactive multimedia technologies enable online firms to employ a variety of formats to present and promote their products: They can use pictures, videos, and sounds to depict products, as well as give consumers the opportunity to try out products virtually. Despite the several previous endeavors that studied the effects of different product presentation formats, the functional mechanisms underlying these presentation methods have not been investigated in a comprehensive way. This paper investigates a model showing how these functional mechanisms (namely, vividness and interactivity) influence consumers’ intentions to return to a website and their intentions to purchase products. A study conducted to test this model has largely confirmed our expectations: (1) both vividness and interactivity of product presentations are the primary design features that influence the efficacy of the presentations; (2) consumers’ perceptions of the diagnosticity of websites, their perceptions of the compatibility between online shopping and physical shopping, and their shopping enjoyment derived from a particular online shopping experience jointly influence consumers’ attitudes toward shopping at a website; and (3) both consumers’ attitudes toward products and their attitudes toward shopping at a website contribute to their intentions to purchase the products displayed on the website.
The management of bee communities by intercropping with flowering basil (Ocimum basilicum) enhances pollination and yield of bell pepper (Capsicum annuum)

Enhancements of floral resources in surrounding landscape and in local crop fields are expected to mitigate adverse human impacts on pollinator diversity and pollination services. We evaluated whether intercropping with flowering basil (Ocimum basilicum) increases the local abundance and richness of bees and improves fruit and seed production of bell pepper (Capsicum annuum). Fields of bell pepper were divided into intercropping (basil mixed with pepper) and single-cropping plots (only pepper). We also grew bell peppers in protected greenhouse in the presence and absence of beehives. The richness and abundance of visiting bees to pepper flowers were greater in the intercropped plots than the single-cropping plots. The increase in the number of bees visiting the peppers was due to the stronger attraction of Paratrigona lineata, Apis mellifera and Tetragonisca angustula to basil in the intercropping plots. The pepper fruits produced in the intercropping were wider, longer, and heavier and developed more seeds than the fruits produced by single-cropping. The same differences were observed between the fruits grown in greenhouse with and without beehives of P. lineata. We demonstrate that agricultural systems designed to attract and retain pollinators are more productive than growing pure stands. Our results also highlight the role of provisioning floral resources to enhance bee conservation and management in anthropogenic ecosystems.
LTP may trigger addiction.

Differing classes of abused drugs utilize different mechanisms of molecular pharmacological action yet the overuse of these same drugs frequently leads to the same outcome: addiction. Similarly, episodes of stress can lead to drug-seeking behaviors and relapse in recovering addicts. To overcome the labor-intensive headache of having to design a specific addiction-breaking intervention tailored to each drug it would be expedient to attack the cycle of addiction at targets common to such seemingly disparate classes of drugs of abuse. Recently, encouraging observations were made whereby stressful conditions and differing classes of drugs of abuse were found to impinge upon the same excitatory synapses on dopamine neurons in the midbrain. These findings will increase our understanding of the intricacies of addiction and LTP, and may lead to new interventions for breaking addiction.
Evaluation of processed green and ripe mango peel and pulp flours (Mangifera indica var. Chokanan) in terms of chemical composition, antioxidant compounds and functional properties.

Mango is a highly perishable seasonal fruit and large quantities are wasted during the peak season as a result of poor postharvest handling procedures. Processing surplus mango fruits into flour to be used as a functional ingredient appears to be a good preservation method to ensure its extended consumption.



In the present study, the chemical composition, bioactive/antioxidant compounds and functional properties of green and ripe mango (Mangifera indica var. Chokanan) peel and pulp flours were evaluated. Compared to commercial wheat flour, mango flours were significantly low in moisture and protein, but were high in crude fiber, fat and ash content. Mango flour showed a balance between soluble and insoluble dietary fiber proportions, with total dietary fiber content ranging from 3.2 to 5.94 g kg⁻¹. Mango flours exhibited high values for bioactive/antioxidant compounds compared to wheat flour. The water absorption capacity and oil absorption capacity of mango flours ranged from 0.36 to 0.87 g kg⁻¹ and from 0.18 to 0.22 g kg⁻¹, respectively.



Results of this study showed mango peel flour to be a rich source of dietary fiber with good antioxidant and functional properties, which could be a useful ingredient for new functional food formulations.