nils-herrmann/clean_scirepeval huggingface dataset:
A Lyapunov-based Approach to Safe Reinforcement Learning

In many real-world reinforcement learning (RL) problems, besides optimizing the main objective function, an agent must concurrently avoid violating a number of constraints. In particular, besides optimizing performance, it is crucial to guarantee the safety of an agent during training as well as deployment (e.g., a robot should avoid taking actions exploratory or not which irrevocably harm its hardware). To incorporate safety in RL, we derive algorithms under the framework of constrained Markov decision processes (CMDPs), an extension of the standard Markov decision processes (MDPs) augmented with constraints on expected cumulative costs. Our approach hinges on a novel Lyapunov method. We define and present a method for constructing Lyapunov functions, which provide an effective way to guarantee the global safety of a behavior policy during training via a set of local linear constraints. Leveraging these theoretical underpinnings, we show how to use the Lyapunov approach to systematically transform dynamic programming (DP) and RL algorithms into their safe counterparts. To illustrate their effectiveness, we evaluate these algorithms in several CMDP planning and decision-making tasks on a safety benchmark domain. Our results show that our proposed method significantly outperforms existing baselines in balancing constraint satisfaction and performance.
Enterovirus 71 infection and vaccines

Hand, foot and mouth disease (HFMD) is a highly contagious viral infection affecting young children during the spring to fall seasons. Recently, serious outbreaks of HFMD were reported frequently in the Asia-Pacific region, including China and Korea. The symptoms of HFMD are usually mild, comprising fever, loss of appetite, and a rash with blisters, which do not need specific treatment. However, there are uncommon neurological or cardiac complications such as meningitis and acute flaccid paralysis that can be fatal. HFMD is most commonly caused by infection with coxsackievirus A16, and secondly by enterovirus 71 (EV71). Many other strains of coxsackievirus and enterovirus can also cause HFMD. Importantly, HFMD caused by EV71 tends to be associated with fatal complications. Therefore, there is an urgent need to protect against EV71 infection. Development of vaccines against EV71 would be the most effective approach to prevent EV71 outbreaks. Here, we summarize EV71 infection and development of vaccines, focusing on current scientific and clinical progress.
Bipolar Resistive Switching Characteristics of HfO2/TiO2/HfO2 Trilayer-Structure RRAM Devices on Pt and TiN-Coated Substrates Fabricated by Atomic Layer Deposition

The HfO2/TiO2/HfO2 trilayer-structure resistive random access memory (RRAM) devices have been fabricated on Pt- and TiN-coated Si substrates with Pt top electrodes by atomic layer deposition (ALD). The effect of the bottom electrodes of Pt and TiN on the resistive switching properties of trilayer-structure units has been investigated. Both Pt/HfO2/TiO2/HfO2/Pt and Pt/HfO2/TiO2/HfO2/TiN exhibit typical bipolar resistive switching behavior. The dominant conduction mechanisms in low and high resistance states (LRS and HRS) of both memory cells are Ohmic behavior and space-charge-limited current, respectively. It is found that the bottom electrodes of Pt and TiN have great influence on the electroforming polarity preference, ratio of high and low resistance, and dispersion of the operating voltages of trilayer-structure memory cells. Compared to using symmetric Pt top/bottom electrodes, the RRAM cells using asymmetric Pt top/TiN bottom electrodes show smaller negative forming voltage of -3.7 V, relatively narrow distribution of the set/reset voltages and lower ratio of high and low resistances of 102. The electrode-dependent electroforming polarity can be interpreted by considering electrodes' chemical activity with oxygen, the related reactions at anode, and the nonuniform distribution of oxygen vacancy concentration in trilayer-structure of HfO2/TiO2/HfO2 on Pt- and TiN-coated Si. Moreover, for Pt/HfO2/TiO2/HfO2/TiN devices, the TiN electrode as oxygen reservoir plays an important role in reducing forming voltage and improving uniformity of resistive switching parameters.
Cannabidiol attenuates seizures and social deficits in a mouse model of Dravet syndrome.

Worldwide medicinal use of cannabis is rapidly escalating, despite limited evidence of its efficacy from preclinical and clinical studies. Here we show that cannabidiol (CBD) effectively reduced seizures and autistic-like social deficits in a well-validated mouse genetic model of Dravet syndrome (DS), a severe childhood epilepsy disorder caused by loss-of-function mutations in the brain voltage-gated sodium channel NaV1.1. The duration and severity of thermally induced seizures and the frequency of spontaneous seizures were substantially decreased. Treatment with lower doses of CBD also improved autistic-like social interaction deficits in DS mice. Phenotypic rescue was associated with restoration of the excitability of inhibitory interneurons in the hippocampal dentate gyrus, an important area for seizure propagation. Reduced excitability of dentate granule neurons in response to strong depolarizing stimuli was also observed. The beneficial effects of CBD on inhibitory neurotransmission were mimicked and occluded by an antagonist of GPR55, suggesting that therapeutic effects of CBD are mediated through this lipid-activated G protein-coupled receptor. Our results provide critical preclinical evidence supporting treatment of epilepsy and autistic-like behaviors linked to DS with CBD. We also introduce antagonism of GPR55 as a potential therapeutic approach by illustrating its beneficial effects in DS mice. Our study provides essential preclinical evidence needed to build a sound scientific basis for increased medicinal use of CBD.
Epoch-Synchronous Overlap-Add (ESOLA) for Time- and Pitch-Scale Modification of Speech Signals

Timeand pitch-scale modifications of speech signals find important applications in speech synthesis, playback systems, voice conversion, learning/hearing aids, etc.. There is a requirement for computationally efficient and real-time implementable algorithms. In this paper, we propose a high quality and computationally efficient timeand pitch-scaling methodology based on the glottal closure instants (GCIs) or epochs in speech signals. The proposed algorithm, termed as epoch-synchronous overlapadd time/pitch-scaling (ESOLA-TS/PS), segments speech signals into overlapping short-time frames with the overlap between frames being dependent on the time-scaling factor. The adjacent frames are then aligned with respect to the epochs and the frames are overlap-added to synthesize time-scale modified speech. Pitch scaling is achieved by resampling the time-scaled speech by a desired sampling factor. We also propose a concept of epoch embedding into speech signals, which facilitates the identification and time-stamping of samples corresponding to epochs and using them for time/pitch-scaling to multiple scaling factors whenever desired, thereby contributing to faster and efficient implementation. The results of perceptual evaluation tests reported in this paper indicate the superiority of ESOLA over state-of-the-art techniques. The proposed ESOLA significantly outperforms the conventional pitch synchronous overlap-add (PSOLA) techniques in terms of perceptual quality and intelligibility of the modified speech. Unlike the waveform similarity overlap-add (WSOLA) or synchronous overlap-add (SOLA) techniques, the ESOLA technique has the capability to do exact time-scaling of speech with high quality to any desired modification factor within a range of 0.5 to 2. Compared to synchronous overlap-add with fixed synthesis (SOLAFS), the ESOLA is computationally advantageous and at least three times faster.
Grid synchronization of power converters using multiple second order generalized integrators

This paper presents a new frequency-adaptive synchronization method for grid-connected power converters which allows estimating not only the positive- and negative-sequence components of the power signal at the fundamental frequency, but also other sequence components at higher frequencies. The proposed system is called the MSOGI-FLL since it is based on a decoupled network consisting of multiple second order generalized integrators (MSOGI) which are frequency-adaptive by using a frequency-locked loop (FLL). In this paper, the MSOGI-FLL is analyzed and its performance is evaluated by both simulations and experiments.
Exploitation of the Macrophage Mannose Receptor (CD206) in Infectious Disease Diagnostics and Therapeutics.

The macrophage mannose receptor (MR, CD206) is a C-type lectin expressed predominantly by most tissue macrophages, dendritic cells and specific lymphatic or endothelial cells. It functions in endocytosis and phagocytosis, and plays an important role in immune homeostasis by scavenging unwanted mannoglycoproteins. More attention is being paid to its particularly high expression in tissue pathology sites during disease such the tumor microenvironment. The MR recognizes a variety of microorganisms by their mannan-coated cell wall, which is exploited by adapted intracellular pathogens such as Mycobacterium tuberculosis, for their own survival. Despite the continued development of drug delivery technologies, the targeting of agents to immune cells, especially macrophages, for effective diagnosis and treatment of chronic infectious diseases has not been addressed adequately. In this regard, strategies that optimize MR-mediated uptake by macrophages in target tissues during infection are becoming an attractive approach. We review important progress in this area.
HOW RFID TECHNOLOGY BOOSTS WALMART ’ S SUPPLY CHAIN MANAGEMENT

The role of RFID technologies in supply chain management have gained significant interest in researchers and academics in recent years. Yet, very few studies conductedonhow this technologycould boost supply chains. So this study was to scrutinize how RFID technology boosts Wal-Mart’s supply chain management.  Exploratory research approachwas adopted to obtain an indepth understanding of RFID technology andsupply chain through related journals and literatures.Then the research was conducted in the form of case studies on RFID technology and Wal-Mart’s supply chain management practices. In general, the research is more descriptive and interpretive in nature. WalMart succeeded in adopting the RFID technology, reduced out-of-stocks and the bullwhip effect, reduction in manual orders resulting in a reduction of excess inventory, improved service levels and reduced administration costs.  The paper is original that provides empirical supportto RFID and SCM implementation, and creates value for retail stores on managing inventory. Keyword: RFID, SCM, Bullwhip Effect, VMI, CPFR
Understanding Human Behaviors in Crowds by Imitating the Decision-Making Process

Crowd behavior understanding is crucial yet challenging across a wide range of applications, since crowd behavior is inherently determined by a sequential decision-making process based on various factors, such as the pedestrians’ own destinations, interaction with nearby pedestrians and anticipation of upcoming events. In this paper, we propose a novel framework of Social-Aware Generative Adversarial Imitation Learning (SA-GAIL) to mimic the underlying decisionmaking process of pedestrians in crowds. Specifically, we infer the latent factors of human decision-making process in an unsupervised manner by extending the Generative Adversarial Imitation Learning framework to anticipate future paths of pedestrians. Different factors of human decision making are disentangled with mutual information maximization, with the process modeled by collision avoidance regularization and Social-Aware LSTMs. Experimental results demonstrate the potential of our framework in disentangling the latent decision-making factors of pedestrians and stronger abilities in predicting future trajectories.
UseLearn: A novel checklist and usability evaluation method for eLearning systems by criticality metric analysis

This paper proposes a new usability evaluation checklist, UseLearn, and a related method for eLearning systems. UseLearn is a comprehensive checklist which incorporates both quality and usability evaluation perspectives in eLearning systems. Structural equation modeling is deployed to validate the UseLearn checklist quantitatively. The experimental results show that the UseLearn method supports the determination of usability problems by criticality metric analysis and the definition of relevant improvement strategies. The main advantage of the UseLearn method is the adaptive selection of the most influential usability problems, and thus significant reduction of the time and effort for usability evaluation can be achieved. At the sketching and/or design stage of eLearning systems, it will provide an effective guidance to usability analysts as to what problems should be focused on in order to improve the usability perception of the end-users.  During the sketching or design stage of eLearning platforms, usability problems should be revealed and eradicated to create more usable and quality eLearning systems to satisfy the end-users. The UseLearn checklist along with its quantitative methodology proposed in this study would be helpful for usability experts to achieve this goal.
Outcomes of variation in technique and variation in accuracy of measurement in penile length measurement

Accurate data regarding the size of the erect penis is of great importance to several disciplines working with male patients, but little data exists on the best technique to measure penile length. While some previous small studies have suggested good correlation between stretched penile length, others have shown significant variability. Penile girth has been less well studied, and little data exist on the possible errors induced by differing observers and different techniques. Much of the published data report penile length measured from the penopubic skin junction-to-glans tip (STT) rather than pubic bone-to-tip (BTT). We wished to assess the accuracy of different techniques of penile measurements with multiple observers. Men who achieved full erection using dynamic penile Doppler ultrasound for the diagnosis of sexual dysfunction or a desire for objective penile measurement were included in the study. Exclusion criteria were penile scarring, curvature, or congenital abnormality. In each case, the penis was measured by one of the seven andrology specialists in a private air-conditioned (21 °C) environment. Each patient had three parameters measured: circumference (girth) of the penile shaft, length from suprapubic skin-to-distal glans (STT), and pubis-to-distal glans (BTT). The three measurements were recorded in the stretched flaccid state, and the same three measurements were then repeated in the fully erect state, following induction of full erection with intracavernosal injection. We analyzed the accuracy of each flaccid measurement using the erect measurements as a reference, for the overall patient population and for each observer. In total, 201 adult men (mean age 49.4 years) were included in this study. Assessing the penis in the stretched and flaccid state gave a mean underestimate of the erect measurement of ~20% (STT length 23.39%, BTT length 19.86%, and circumference 21.38%). In this large, multicenter, multi-observer study of penis size, flaccid measurements were only moderately accurate in predicting erect size. They were also significantly observer dependent. Measuring penile length from pubic bone to tip of glans is more accurate and reliable, the discrepancy being most notable in overweight patients.
Antibiotic resistance of bacterial biofilms.

A biofilm is a structured consortium of bacteria embedded in a self-produced polymer matrix consisting of polysaccharide, protein and DNA. Bacterial biofilms cause chronic infections because they show increased tolerance to antibiotics and disinfectant chemicals as well as resisting phagocytosis and other components of the body's defence system. The persistence of, for example, staphylococcal infections related to foreign bodies is due to biofilm formation. Likewise, chronic Pseudomonas aeruginosa lung infection in cystic fibrosis patients is caused by biofilm-growing mucoid strains. Characteristically, gradients of nutrients and oxygen exist from the top to the bottom of biofilms and these gradients are associated with decreased bacterial metabolic activity and increased doubling times of the bacterial cells; it is these more or less dormant cells that are responsible for some of the tolerance to antibiotics. Biofilm growth is associated with an increased level of mutations as well as with quorum-sensing-regulated mechanisms. Conventional resistance mechanisms such as chromosomal beta-lactamase, upregulated efflux pumps and mutations in antibiotic target molecules in bacteria also contribute to the survival of biofilms. Biofilms can be prevented by early aggressive antibiotic prophylaxis or therapy and they can be treated by chronic suppressive therapy. A promising strategy may be the use of enzymes that can dissolve the biofilm matrix (e.g. DNase and alginate lyase) as well as quorum-sensing inhibitors that increase biofilm susceptibility to antibiotics.
Real-time fMRI brain computer interfaces: Self-regulation of single brain regions to networks

With the advent of brain computer interfaces based on real-time fMRI (rtfMRI-BCI), the possibility of performing neurofeedback based on brain hemodynamics has become a reality. In the early stage of the development of this field, studies have focused on the volitional control of activity in circumscribed brain regions. However, based on the understanding that the brain functions by coordinated activity of spatially distributed regions, there have recently been further developments to incorporate real-time feedback of functional connectivity and spatio-temporal patterns of brain activity. The present article reviews the principles of rtfMRI neurofeedback, its applications, benefits and limitations. A special emphasis is given to the discussion of novel developments that have enabled the use of this methodology to achieve self-regulation of the functional connectivity between different brain areas and of distributed brain networks, anticipating new and exciting applications for cognitive neuroscience and for the potential alleviation of neuropsychiatric disorders.
Looking Forward to Sociable Robots

This work examines humanoid social robots in Japan and the North America with a view to comparing and contrasting the projects cross culturally. In North America, I look at the work of Cynthia Breazeal at the Massachusetts Institute of Technology and her sociable robot project: Kismet. In Japan, at the Osaka University, I consider the project of Hiroshi Ishiguro: Repliée-Q2. I first distinguish between utilitarian and affective social robots. Then, drawing on published works of Breazeal and Ishiguro I examine the proposed vision of each project. Next, I examine specific characteristics (embodied and social intelligence, morphology and aesthetics, and moral equivalence) of Kismet and Repliée with a view to comparing the underlying concepts associated with each. These features are in turn connected to the societal preconditions of robots generally. Specifically, the role that history of robots, theology/spirituality, and popular culture plays in the reception and attitude toward robots is considered.
Modeling Learners' Social Centrality and Performance through Language and Discourse

There is an emerging trend in higher education for the adoption of massive open online courses (MOOCs). However, despite this interest in learning at scale, there has been limited work investigating the impact MOOCs can play on student learning. In this study, we adopt a novel approach, using language and discourse as a tool to explore its association with two established measures related to learning: traditional academic performance and social centrality. We demonstrate how characteristics of language diagnostically reveal the performance and social position of learners as they interact in a MOOC. We use CohMetrix, a theoretically grounded, computational linguistic modeling tool, to explore students’ forum postings across five potent discourse dimensions. Using a Social Network Analysis (SNA) methodology, we determine learners’ social centrality. Linear mixed-effect modeling is used for all other analyses to control for individual learner and text characteristics. The results indicate that learners performed significantly better when they engaged in more expository style discourse, with surface and deep level cohesive integration, abstract language, and simple syntactic structures. However, measures of social centrality revealed a different picture. Learners garnered a more significant and central position in their social network when they engaged with more narrative style discourse with less overlap between words and ideas, simpler syntactic structures and abstract words. Implications for further research and practice are discussed regarding the misalignment between these two learning-related outcomes.
Embedded FIR filter design for real-time refocusing using a standard plenoptic video camera

A novel and low-cost embedded hardware architecture for real-time refocusing based on a standard plenoptic camera is presented in this study. The proposed layout design synthesizes refocusing slices directly from micro images by omitting the process for the commonly used sub-aperture extraction. Therefore, intellectual property cores, containing switch controlled Finite Impulse Response (FIR) filters, are developed and applied to the Field Programmable Gate Array (FPGA) XC6SLX45 from Xilinx. Enabling the hardware design to work economically, the FIR filters are composed of stored product as well as upsampling and interpolation techniques in order to achieve an ideal relation between image resolution, delay time, power consumption and the demand of logic gates. The video output is transmitted via High-Definition Multimedia Interface (HDMI) with a resolution of 720p at a frame rate of 60 fps conforming to the HD ready standard. Examples of the synthesized refocusing slices are presented.
Uncovering the Spatio-Temporal Dynamics of Memes in the Presence of Incomplete Information

Modeling, understanding, and predicting the spatio-temporal dynamics of online memes are important tasks, with ramifications on location-based services, social media search, targeted advertising and content delivery networks. However, the raw data revealing these dynamics are often incomplete and error-prone; for example, API limitations and data sampling policies can lead to an incomplete (and often biased) perspective on these dynamics. Hence, in this paper, we investigate new methods for uncovering the full (underlying) distribution through a novel spatio-temporal dynamics recovery framework which models the latent relationships among locations, memes, and times. By integrating these hidden relationships into a tensor-based recovery framework -- called AirCP -- we find that high-quality models of meme spread can be built with access to only a fraction of the full data. Experimental results on both synthetic and real-world Twitter hashtag data demonstrate the promising performance of the proposed framework: an average improvement of over 27% in recovering the spatio-temporal dynamics of hashtags versus five state-of-the-art alternatives.