nils-herrmann/clean_scirepeval huggingface dataset:
The effect of grounding the human body on mood.

Earthing (grounding) refers to bringing the body in contact with the Earth. Health benefits were previously reported, but no study exists about mood. This study was conducted to assess if Earthing improves mood. 40 adult participants were either grounded or sham-grounded (no grounding) for 1 hr. while relaxing in a comfortable recliner chair equipped with a conductive pillow, mat, and patches connecting them to the ground. This pilot project was double-blinded and the Brief Mood Introspection Scale (comprising 4 mood scales) was used. Pleasant and positive moods statistically significantly improved among grounded-but not sham-grounded-participants. It is concluded that the 1-hr. contact with the Earth improved mood more than expected by relaxation alone. More extensive studies are, therefore, warranted.
Bots increase exposure to negative and inflammatory content in online social systems

Societies are complex systems, which tend to polarize into subgroups of individuals with dramatically opposite perspectives. This phenomenon is reflected-and often amplified-in online social networks, where, however, humans are no longer the only players and coexist alongside with social bots-that is, software-controlled accounts. Analyzing large-scale social data collected during the Catalan referendum for independence on October 1, 2017, consisting of nearly 4 millions Twitter posts generated by almost 1 million users, we identify the two polarized groups of Independentists and Constitutionalists and quantify the structural and emotional roles played by social bots. We show that bots act from peripheral areas of the social system to target influential humans of both groups, bombarding Independentists with violent contents, increasing their exposure to negative and inflammatory narratives, and exacerbating social conflict online. Our findings stress the importance of developing countermeasures to unmask these forms of automated social manipulation.
Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures

We study the problem of alleviating the instability issue in the GAN training procedure via new architecture design. The discrepancy between the minimax and maximin objective values could serve as a proxy for the difficulties that the alternating gradient descent encounters in the optimization of GANs. In this work, we give new results on the benefits of multi-generator architecture of GANs. We show that the minimax gap shrinks to as the number of generators increases with rate Õ(1/ ). This improves over the best-known result of Õ(1/ ). At the core of our techniques is a novel application of Shapley-Folkman lemma to the generic minimax problem, where in the literature the technique was only known to work when the objective function is restricted to the Lagrangian function of a constraint optimization problem. Our proposed Stackelberg GAN performs well experimentally in both synthetic and real-world datasets, improving Fréchet Inception Distance by 14.61% over the previous multi-generator GANs on the benchmark datasets.
A novel data format for approximate arithmetic computing

Approximate computing has become one of the most popular computing paradigms in the era of the Internet of things and big data. It takes advantages of the error-tolerable feature of many applications, such as machine learning and image/signal processing, to reduce the resource required to deliver certain level of computation quality. In this paper, we propose an approximate integer format (AIF) and its associated arithmetic operations for energy minimization with controllable computation accuracy. In AIF, operands are segmented at run time such that the computation is performed only on part of operands by computing units (such as adders and multipliers) of smaller bit-width. The proposed AIF can be used for any arithmetic operation and can be extended to fixed point numbers. It can also be incorporated into higher level design such as architectural and programming language to give user the control of approximate computing. Experimental results show that our AIF based approximation computing approach can achieve high accuracy, incurs very little additional overhead, and save considerable energy.
Novel frequency selective surfaces designing by modification of Jerusalem cross slot

This research introduces an efficient method to obtain three novel frequency selective surface (FSS) slots. The method is based on the modification of Jerusalem cross (JC) slot which is called modified Jerusalem cross (MJC). The modifications of JC slot consist of the element type and geometry, the substrate and superstrate parameters, and inter-element spacing; however the FSSs have same dimension of unit cells and periodicity(Ltlambda). The array of slots which acts as a bandpass filter, were positioned normal to incidence plane wave. The array of metallic patches constitutes a capacitive surface and the inductive surface, which together act as a resonant structure in the path of an incident plane wave. The Si- parameters, resonance frequency, bandwidth and null between two adjacent resonance frequencies for each structure have been compared with the JC FSS. Three type of MJC have been designed and compared with JC slot. The result shows MJC1 has higher resonance frequency and higher bandwidth, MJC2 in the first resonance frequency works at higher resonance frequency and higher bandwidth but in second resonance frequency the bandwidth is lower and resonance frequency is higher than JC, and MJC3 has approximately same resonance frequency and higher band. This work provides new viewpoints to design novel structures for special purposes.
Low loss, 3.7GHz wideband BAW filters, using high power single crystal AlN-on-SiC resonators

Bulk acoustic wave (BAW) filters operating at center frequency of 3.7GHz, comprising of BAW resonators utilizing single crystal aluminum nitride (AlN) piezoelectric films epitaxially grown on silicon carbide (SiC) substrates, are reported. Metal-organic chemical vapor deposition (MOCVD) growth was used to obtain single crystal AlN films on 150-mm diameter c-plane semi-insulating SiC substrates with (0004) X-ray diffraction (XRD) rocking curve full-width half-maximum (FWHM) of 0.025°. The fabricated filters (1.25×0.9 sq.mm) had a center frequency of 3.71GHz and a 3dB bandwidth of 100MHz, an insertion loss of 2.0dB and narrow band rejection of 40dB and out-of-band rejection in excess of 37dB to 8GHz. Individual resonators on the same wafer show an electro-mechanical coupling as high as 7.63% and maximum quality-factors up to 1572. Insertion loss of 5ohm resonators configured as individual 2-port devices changed by 0.15dB after high power survival test at 10W. This is the first demonstration of single crystal AlN-on-SiC based BAW resonator and filter technology at 3.7GHz and illustrates the potential of a single crystal AlN-on-SiC based BAW technology platform enabling compact, high power and high performance filter solutions for high frequency mobile, Wi-Fi and infrastructure applications.
EFFECTS OF MANIPULATION OF DIETARY FATTY ACIDS ON CLINICAL MANIFESTATIONS OF RHEUMATOID ARTHRITIS

The effects of manipulation of dietary fatty acids in patients with rheumatoid arthritis were investigated in a 12-week, prospective, double-blind, controlled study. 17 patients took an experimental diet high in polyunsaturated fat and low in saturated fat, with a daily supplement (1.8 g) of eicosapentaenoic acid. 20 patients took a control diet with a lower polyunsaturated to saturated fat ratio and a placebo supplement. Compliance was monitored by plasma lipid gas-chromatographic analysis, Ivy bleeding time, and diet diaries. Results favoured the experimental group at 12 weeks for morning stiffness and number of tender joints. On follow-up evaluation 1-2 months after stopping the diet, the experimental group had deteriorated significantly in patient and physician global evaluation of disease activity, pain assessment, and number of tender joints. The control group had improved in morning stiffness and number of tender joints on follow-up.
Design of a miniature 3-DOF flexure-based mechanism for micro/nano manipulation

The work presented in this paper focuses on the design of a novel flexure-based mechanism capable of delivering planar motion with three degrees of freedom (3-DOF). Pseudo rigid body modeling (PRBM) and kinematic analysis of the mechanism are used to predict the motion of the mechanism in the X-, Y- and θ-directions. Lever based amplification is used to enhance the displacement of the mechanism. The presented design is small and compact in size (about 142mm by 110mm). The presented 3-DOF flexure-based miniature micro/nano mechanism delivers smooth motion in X, Y and θ, with maximum displacements of 142.09 μm in X-direction, 120.36 μm in Y-direction and 6.026 mrad in θ-rotation.
An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point Based Nondominated Sorting Approach, Part II: Handling Constraints and Extending to an Adaptive Approach

In the precursor paper, a many-objective optimization method (NSGA-III), based on the NSGA-II framework, was suggested and applied to a number of unconstrained test and practical problems with box constraints alone. In this paper, we extend NSGA-III to solve generic constrained many-objective optimization problems. In the process, we also suggest three types of constrained test problems that are scalable to any number of objectives and provide different types of challenges to a many-objective optimizer. A previously suggested MOEA/D algorithm is also extended to solve constrained problems. Results using constrained NSGA-III and constrained MOEA/D show an edge of the former, particularly in solving problems with a large number of objectives. Furthermore, the NSGA-III algorithm is made adaptive in updating and including new reference points on the fly. The resulting adaptive NSGA-III is shown to provide a denser representation of the Pareto-optimal front, compared to the original NSGA-III with an identical computational effort. This, and the original NSGA-III paper, together suggest and amply test a viable evolutionary many-objective optimization algorithm for handling constrained and unconstrained problems. These studies should encourage researchers to use and pay further attention in evolutionary many-objective optimization.
Micro note-taking on smartphone : the learner experience

Note-taking is considered as one of the main activities for students during lectures in the classroom. Indeed, many educators have suggested that note-taking can significantly improve students’ educational performance. Therefore, there are many systems available to capture what the teacher presents or explains during the lectures. However, less attention has been paid to the great potential of integrating Web 2.0 technologies with the learning process at universities for note-taking purposes so as to make it more effective. As such, the purpose of this paper is to extend understanding of learners’ experiences specifically when short text – the 140 characters, often used in social networks – was used for notetaking. The paper presents findings on learners’ experiences of using such a “micro” note-taking approach involving just 140 characters and suggests a feature list for a future note-taking system. The qualitative approach focuses on learners from one university in the UK. The learners were at postgraduate level, and data were collected through focus groups with the learners. Findings indicate that the use of a short text feature leads to a positive learning experience.  micro note-taking; smartphone; social media; UK.
Type-2 fuzzy logic systems for temperature evaluation in ladle furnace

This paper presents the implementation of the interval type-2 to control the process of production of High-strength low-alloy (HSLA) steel in a secondary metallurgy process in a simply way. The proposal evaluate fuzzy techniques to ensure the accuracy of the model, the most important advantage is that the systems do not need pretreatment of the historical data, it is used as it is. The system is a multiple input single output (MISO) and the main goal of this paper is the proposal of a system that optimizes the resources: computational, time, among others.
CNN-based pattern recognition on nonvolatile IoT platform for smart ultraviolet monitoring: (Invited paper)

Intelligent computing and maintenance-free powering are two desirable characteristics of wearable IoT devices. Energy harvesting nonvolatile intelligent processor (NIP) with neural network computation capability has the potential to advance these goals. Individual ultraviolet (UV) exposure monitoring progressively becomes one conspicuous application of wearable devices. In resource constrained wearable sensor nodes, we can alleviate the data transmission burden via convolutional neural networks (CNNs) based pattern recognition. Nevertheless, in spite of the substantially improved computing capability of NIP, typically computational and memory intensive CNNs are still too bulky for on-node implementation. We develop an CNN-based pattern recognition system for nonvolatile IoT platform for smart UV monitoring, and propose a optimization method to achieve extremely tiny and efficient CNNs. Experimental results show that the offline-trained CNN can recognize individual UV exposure patterns with accuracy of 85%, and the simplified on-node CNN can achieve 93.2% parameters reduction with only 5% accuracy loss.
Learning Programming at the Computational Thinking Level via Digital Game-Play

This paper outlines an innovative game model for learning computational thinking (CT) skills through digital game-play. We have designed a game framework where students can practice and develop their skills in CT with little or no programming knowledge. We analyze how this game supports various CT concepts and how these concepts can be mapped to programming constructs to facilitate learning introductory computer programming. Moreover, we discuss the potential benefits of our approach as a support tool to foster student motivation and abilities in problem solving. As initial evaluation, we provide some analysis of feedback from a survey response group of 25 students who have played our game as a voluntary exercise. Structured empirical evaluation will follow, and the plan for that is briefly described.
Non-verbal memory measured by Rey–Osterrieth Complex Figure B: normative data

One of the major problems that clinical neuropsychology has had in memory clinics is to apply ecological, easily administrable and sensitive tests that can make the diagnosis of dementia both precocious and reliable. Often the choice of the best neuropsychological test is hard because of a number of variables that can influence a subject’s performance. In this regard, tests originally devised to investigate cognitive functions in healthy adults are not often appropriate to analyze cognitive performance in old subjects with low education because of their intrinsically complex nature. In the present paper, we present normative values for the Rey–Osterrieth Complex Figure B Test (ROCF-B) a simple test that explores constructional praxis and visuospatial memory. We collected normative data of copy, immediate and delayed recall of the ROCF-B in a group of 346 normal Italian subjects above 40 years. A multiple regression analysis was performed to evaluate the potential effect of age, sex, and education on the three tasks administered to the subjects. Age and education had a significant effect on copying, immediate recall, and delayed recall as well as on the rate of forgetting. Correction grids and equivalent scores with cut-off values relative to each task are available. The availability of normative values can make the ROCF-B a valid instrument to assess non-verbal memory in adults and in the elderly for whom the commonly used ROCF-A is too demanding.
Hibiscus sabdariffa L. - a phytochemical and pharmacological review.

Hibiscus sabdariffa L. (Hs, roselle; Malvaceae) has been used traditionally as a food, in herbal drinks, in hot and cold beverages, as a flavouring agent in the food industry and as a herbal medicine. In vitro and in vivo studies as well as some clinical trials provide some evidence mostly for phytochemically poorly characterised Hs extracts. Extracts showed antibacterial, anti-oxidant, nephro- and hepato-protective, renal/diuretic effect, effects on lipid metabolism (anti-cholesterol), anti-diabetic and anti-hypertensive effects among others. This might be linked to strong antioxidant activities, inhibition of α-glucosidase and α-amylase, inhibition of angiotensin-converting enzymes (ACE), and direct vaso-relaxant effect or calcium channel modulation. Phenolic acids (esp. protocatechuic acid), organic acid (hydroxycitric acid and hibiscus acid) and anthocyanins (delphinidin-3-sambubioside and cyanidin-3-sambubioside) are likely to contribute to the reported effects. More well designed controlled clinical trials are needed which use phytochemically characterised preparations. Hs has an excellent safety and tolerability record.
A Formal Monitoring-Based Framework for Software Development and Analysis

A formal framework for software development and analysis is presented, which aims at reducing the gap between formal specification and implementation by integrating the two and allowing them together to form a system. It is called monitoring-oriented programming (MOP), since runtime monitoring is supported and encouraged as a fundamental principle. Monitors are automatically synthesized from formal specifications and integrated at appropriate places in the program, according to user-configurable attributes. Violations and/or validations of specifications can trigger user-defined code at any points in the program, in particular recovery code, outputting/sending messages, or raising exceptions. The major novelty of MOP is its generality w.r.t. logical formalisms: it allows users to insert their favorite or domain-specific specification formalisms via logic plug-in modules. A WWW repository has been created, allowing MOP users to download and upload logic plugins. An experimental prototype tool, called Java-MOP, is also discussed, which currently supports most but not all of the desired MOP features.
Unsupervised and Efficient Vocabulary Expansion for Recurrent Neural Network Language Models in ASR

In automatic speech recognition (ASR) systems, recurrent neural network language models (RNNLM) are used to rescore a word lattice or N-best hypotheses list. Due to the expensive training, the RNNLM’s vocabulary set accommodates only small shortlist of most frequent words. This leads to suboptimal performance if an input speech contains many out-of-shortlist (OOS) words. An effective solution is to increase the shortlist size and retrain the entire network which is highly inefficient. Therefore, we propose an efficient method to expand the shortlist set of a pretrained RNNLM without incurring expensive retraining and using additional training data. Our method exploits the structure of RNNLM which can be decoupled into three parts: input projection layer, middle layers, and output projection layer. Specifically, our method expands the word embedding matrices in projection layers and keeps the middle layers unchanged. In this approach, the functionality of the pretrained RNNLM will be correctly maintained as long as OOS words are properly modeled in two embedding spaces. We propose to model the OOS words by borrowing linguistic knowledge from appropriate in-shortlist words. Additionally, we propose to generate the list of OOS words to expand vocabulary in unsupervised manner by automatically extracting them from ASR output.
Joint channel estimation and feedback with low overhead for FDD massive MIMO systems

Accurate channel state information (CSI) is essential to realize the potential advantages of massive MIMO. However, the overhead required by conventional channel estimation and feedback schemes will be unaffordable, especially for frequency division duplex (FDD) massive MIMO. To solve this problem, we propose a structured compressive sensing (SCS) based spatio-temporal joint channel estimation and feedback scheme to reduce the required overhead. Particularly, we first propose the non-orthogonal pilots at the base station (BS) under the framework of CS theory. Then, an adaptive structured subspace pursuit (ASSP) algorithm is proposed to jointly estimate channels associated with multiple OFDM symbols at the receiver, whereby the spatio-temporal common sparsity of massive MIMO channels is exploited to improve the channel estimation accuracy. Moreover, we propose a parametric channel feedback scheme, which exploits the sparsity of channels to acquire accurate CSI at the BS with reduced feedback overhead. Simulation results show that the channel estimation performance approaches that of the oracle least squares (LS) channel estimator, and the parametric channel feedback scheme only suffers from a negligible performance loss compared with the complete channel feedback scheme.
Complex interaction between circadian rhythm and diet on bile acid homeostasis in male rats.

Desynchronization between the master clock in the brain, which is entrained by (day) light, and peripheral organ clocks, which are mainly entrained by food intake, may have negative effects on energy metabolism. Bile acid metabolism follows a clear day/night rhythm. We investigated whether in rats on a normal chow diet the daily rhythm of plasma bile acids and hepatic expression of bile acid metabolic genes is controlled by the light/dark cycle or the feeding/fasting rhythm. In addition, we investigated the effects of high caloric diets and time-restricted feeding on daily rhythms of plasma bile acids and hepatic genes involved in bile acid synthesis. In experiment 1 male Wistar rats were fed according to three different feeding paradigms: food was available ad libitum for 24 h (ad lib) or time-restricted for 10 h during the dark period (dark fed) or 10 h during the light period (light fed). To allow further metabolic phenotyping, we manipulated dietary macronutrient intake by providing rats with a chow diet, a free choice high-fat-high-sugar diet or a free choice high-fat (HF) diet. In experiment 2 rats were fed a normal chow diet, but food was either available in a 6-meals-a-day (6M) scheme or ad lib. During both experiments, we measured plasma bile acid levels and hepatic mRNA expression of genes involved in bile acid metabolism at eight different time points during 24 h. Time-restricted feeding enhanced the daily rhythm in plasma bile acid concentrations. Plasma bile acid concentrations are highest during fasting and dropped during the period of food intake with all diets. An HF-containing diet changed bile acid pool composition, but not the daily rhythmicity of plasma bile acid levels. Daily rhythms of hepatic Cyp7a1 and Cyp8b1 mRNA expression followed the hepatic molecular clock, whereas for Shp expression food intake was leading. Combining an HF diet with feeding in the light/inactive period annulled CYp7a1 and Cyp8b1 gene expression rhythms, whilst keeping that of Shp intact. In conclusion, plasma bile acids and key genes in bile acid biosynthesis are entrained by food intake as well as the hepatic molecular clock. Eating during the inactivity period induced changes in the plasma bile acid pool composition similar to those induced by HF feeding.