nils-herrmann/clean_scirepeval huggingface dataset:
Ultralow thermal conductivity and high thermoelectric figure of merit in SnSe crystals

The thermoelectric effect enables direct and reversible conversion between thermal and electrical energy, and provides a viable route for power generation from waste heat. The efficiency of thermoelectric materials is dictated by the dimensionless figure of merit, ZT (where Z is the figure of merit and T is absolute temperature), which governs the Carnot efficiency for heat conversion. Enhancements above the generally high threshold value of 2.5 have important implications for commercial deployment, especially for compounds free of Pb and Te. Here we report an unprecedented ZT of 2.6 ± 0.3 at 923 K, realized in SnSe single crystals measured along the b axis of the room-temperature orthorhombic unit cell. This material also shows a high ZT of 2.3 ± 0.3 along the c axis but a significantly reduced ZT of 0.8 ± 0.2 along the a axis. We attribute the remarkably high ZT along the b axis to the intrinsically ultralow lattice thermal conductivity in SnSe. The layered structure of SnSe derives from a distorted rock-salt structure, and features anomalously high Grüneisen parameters, which reflect the anharmonic and anisotropic bonding. We attribute the exceptionally low lattice thermal conductivity (0.23 ± 0.03 W m−1 K−1 at 973 K) in SnSe to the anharmonicity. These findings highlight alternative strategies to nanostructuring for achieving high thermoelectric performance.
Analogy and Abstraction

A central question in human development is how young children gain knowledge so fast. We propose that analogical generalization drives much of this early learning and allows children to generate new abstractions from experience. In this paper, we review evidence for analogical generalization in both children and adults. We discuss how analogical processes interact with the child's changing knowledge base to predict the course of learning, from conservative to domain-general understanding. This line of research leads to challenges to existing assumptions about learning. It shows that (a) it is not enough to consider the distribution of examples given to learners; one must consider the processes learners are applying; (b) contrary to the general assumption, maximizing variability is not always the best route for maximizing generalization and transfer.
Cannabis and anxiety: a critical review of the evidence.

Anxiety reactions and panic attacks are the acute symptoms most frequently associated with cannabis use. Understanding the relationship between cannabis and anxiety may clarify the mechanism of action of cannabis and the pathophysiology of anxiety. Aims of the present study were to review the nature of the relationship between cannabis use and anxiety, as well as the possible clinical, diagnostic and causal implications.



Systematic review of the Medline, PsycLIT and EMBASE literature.



Frequent cannabis users consistently have a high prevalence of anxiety disorders and patients with anxiety disorders have relatively high rates of cannabis use. However, it is unclear if cannabis use increases the risk of developing long-lasting anxiety disorders. Many hypotheses have been proposed in an attempt to explain these relationships, including neurobiological, environmental and social influences.



The precise relationship between cannabis use and anxiety has yet to be established. Research is needed to fully clarify the mechanisms of such the association.
Low-Profile Circularly Polarized Cavity-Backed Antennas Using SIW Techniques

Two single fed low-profile cavity-backed slot antennas and an antenna array for circular polarization (CP) applications are introduced. By employing the substrate-integrated waveguide (SIW) and half-mode SIW (HMSIW) techniques in antenna designs, low-profile cavity-backed structures are realized using the low-cost standard printed circuit board process. First, a novel spoon-shaped slot antenna is proposed to realize CP radiation based on the SIW cavity. Then, to minimize the antenna size and achieve the impedance bandwidth enhancement, the HMSIW cavity is introduced to realize a cavity-backed semicircle slot antenna (SSA). The equivalence between the edge of the HMSIW cavity and the longitude slot curved on the surface of the SIW cavity is proposed to guide the design process of the SSA. In addition, two hybrid modes are used to improve the impedance bandwidth of the SSA. Furthermore, a sequential rotation antenna array is introduced to validate the feasibility of the SSA for antenna array application. Finally, the proposed antennas and the antenna array are designed and fabricated at 28 GHz. The measured and simulated results agree very well.
Lean On Me: Mining Internet Service Dependencies From Large-Scale DNS Data

Most websites, services, and applications have come to rely on Internet services (e.g., DNS, CDN, email, WWW, etc.) offered by third parties. Although employing such services generally improves reliability and cost-effectiveness, it also creates dependencies on service providers, which may expose websites to additional risks, such as DDoS attacks or cascading failures. As cloud services are becoming more popular, an increasing percentage of the overall Internet ecosystem relies on a decreasing number of highly popular services. In our general effort to assess the security risk for a given entity, and motivated by the effects of recent service disruptions, we perform a large-scale analysis of passive and active DNS datasets including more than 2.5 trillion queries in order to discover the dependencies between websites and Internet services.
 In this paper, we present the findings of our DNS dataset analysis, and attempt to expose important insights about the ecosystem of dependencies. To further understand the nature of dependencies, we perform graph-theoretic analysis on the dependency graph and propose support power, a novel power measure that can quantify the amount of dependence websites and other services have on a particular service. Our DNS analysis findings reveal that the current service ecosystem is dominated by a handful of popular service providers---with Amazon being the leader, by far---whose popularity is steadily increasing. These findings are further supported by our graph analysis results, which also reveals a set of less-popular services that many (regional) websites depend on.
Invited Commentary: "Bedroom Light Exposure at Night and the Incidence of Depressive Symptoms: A Longitudinal Study of the HEIJO-KYO Cohort".

In modern society, we are increasingly disconnected from natural light/dark cycles and beset by round-the-clock exposure to artificial light. Light has powerful effects on physical and mental health, in part via the circadian system, and thus the timing of light exposure dictates whether it is helpful or harmful. In their compelling paper, Obayashi et al. ( offer evidence that light at night can prospectively predict an elevated incidence of depressive symptoms in older adults. Strengths of the study include the longitudinal design and direct, objective assessment of light levels, as well as accounting for multiple plausible confounders during analyses. Follow-up studies should address the study's limitations, including reliance on a global self-report of sleep quality and a 2-night assessment of light exposure that may not reliably represent typical light exposure. In addition, experimental studies including physiological circadian measures will be necessary to determine whether the light effects on depression are mediated through the circadian system or are so-called "direct" effects of light. In any case, these exciting findings could inform novel approaches to preventing depressive disorders in older adults.
BlocHIE: A BLOCkchain-Based Platform for Healthcare Information Exchange

Nowadays, a great number of healthcare data are generated every day from both medical institutions and individuals. Healthcare information exchange (HIE) has been proved to benefit the medical industry remarkably. To store and share such large amount of healthcare data is important while challenging. In this paper, we propose BlocHIE, a Blockchain-based platform for healthcare information exchange. First, we analyze the different requirements for sharing healthcare data from different sources. Based on the analysis, we employ two loosely-coupled Blockchains to handle different kinds of healthcare data. Second, we combine off-chain storage and on-chain verification to satisfy the requirements of both privacy and authenticability. Third, we propose two fairness-based packing algorithms to improve the system throughput and the fairness among users jointly. To demonstrate the practicability and effectiveness of BlocHIE, we implement BlocHIE in a minimal-viable-product way and evaluate the proposed packing algorithms extensively.
Heme oxygenase: function, multiplicity, regulatory mechanisms, and clinical applications.

In biological systems oxidation of heme is carried out by two isozymes of the microsomal heme oxygenase, HO-1 and HO-2. HO-1 is the commonly known heme oxygenase, the activity of which can be induced by up to 100-fold in response to a wide variety of stimuli (metals, heme, hormones, etc.). HO-2 was only recently discovered, and the isozyme appears to be uninducible. The two forms are products of two different genes and differ in their tissue expression. The primary structure of HO-1 and an HO-2 fragment of 91 amino acid residues show only 58% homology, but share a region with 100% secondary structure homology. This region is believed to be the catalytic site. Most likely, HO-1 gene is regulated in the same manner as metallothione in the gene. HO-1 has a heat shock regulatory element, and possibly many promoter elements, which bind to respective inducers and cause transcription of the gene. In vivo induction of HO-1 activity in the liver is accompanied by decreases in the total P-450 levels and, in a reconstituted system, cytochrome P-450b heme can be quantitatively converted to biliverdin by HO-1 and HO-2. The enzyme activity is inhibited in vivo for extended periods subsequent to binding of Zn- and Sn- protoporphyrins. This property appears useful for the suppression of bilirubin production. The metalloporphyrins, however, are not innocuous and cause major disruptions in cellular metabolism. In this review recent findings on heme oxygenase are highlighted.
Crime pattern detection, analysis & prediction

Crimes are a social irritation and cost our society deeply in several ways. Any research that can help in solving crimes quickly will pay for itself. About 10% of the criminals commit about 50% of the crimes . The system is trained by feeding previous years record of crimes taken from legitimate online portal of India listing various crimes such as murder, kidnapping and abduction, dacoits, robbery, burglary, rape and other such crimes. As per data of Indian statistics, which gives data of various crime of past 14 years (2001–2014) a regression model is created and the crime rate for the following years in various states can be predicted [8]. We have used supervised, semi-supervised and unsupervised learning technique [4] on the crime records for knowledge discovery and to help in increasing the predictive accuracy of the crime. This work will be helpful to the local police stations in crime suppression.
Evolution of Power Converter Topologies and Technical Considerations of Power Electronic Transformer-Based Rolling Stock Architectures

Power electronic transformer (PET) technology is one of the promising technology for medium/high power conversion systems. With the cutting-edge improvements in the power electronics and magnetics, makes it possible to substitute conventional line frequency transformer traction (LFTT) technology with the PET technology. Over the past years, research and field trial studies are conducted to explore the technical challenges associated with the operation, functionalities, and control of PET-based traction systems. This paper aims to review the essential requirements, technical challenges, and the existing state of the art of PET traction system architectures. Finally, this paper discusses technical considerations and introduces the new research possibilities especially in the power conversion stages, PET design, and the power switching devices.
Mathematical features of Whitehead ’ s point-free geometry

This paper is devoted to some mathematical considerations on the geometrical ideas contained in PNK, CN and, successively, in PR. Mainly, we will emphasize that these ideas give very promising suggestions for a modern point-free foundation of geometry. 1.  Recently the researches in point-free geometry received an increasing interest in different areas. As an example, we can quote computability theory, lattice theory, computer science. Now, the basic ideas of point-free geometry were firstly formulated by A. N. Whitehead in PNK and CN where the extension relation between events is proposed as a primitive. The points, the lines and all the " abstract " geometrical entities are defined by suitable abstraction processes. As a matter of fact, as observed in Casati and Varzi 1997, the approach proposed in these books is a basis for a "mereology" (i.e. an investigation about the part-whole relation) rather than for a point-free geometry. Indeed , the inclusion relation is set-theoretical and not topological in nature and this generates several difficulties. As an example, the definition of point is unsatisfactory (see Section 6). So, it is not surprising that some years later the publication of PNK and CN, Whitehead in PR proposed a different approach in which the primitive notion is the one of connection relation. This idea was suggested in de Laguna 1922. The aim of this paper is not to give a precise account of geometrical ideas contained in these books but only to emphasize their mathematical potentialities. So, we translate the analysis of Whitehead into suitable first order theories and we examine these theories from a logical point of view. Also, we argue that multi-valued logic is a promising tool to reformulate the approach in PNK and CN.
Understanding Student Perceptions of Game Elements to Develop Gamified Systems for Learning

As a precursor to the development of a gamified system to improve learning outcomes, we investigate the perception of important stakeholders, namely learners, on gamification in learning. However, as gamification is a relatively new approach/term, we neither assume that learners are knowledgeable about it nor do we attempt to explain the term in detail to them. Instead, we focus on common elements between gamification and learners’ gaming experience, to determine how learners perceive these game elements. This understanding of learners’ perception on the matter will aid in the later development of a gamified system for learning. In this work, we survey 51 undergraduate IT students to obtain their perceptions on game elements such as points, leader boards, player profiles, progress bars, and achievement badges. We then analyse the responses and suggest how these game elements can be used in a gamified system for education. It was found that undergraduate students have a positive perception of gamification and are interested in its use for learning. They expect that gamification will make classes more interesting and will improve the learning environment. Students also believed gamification would be beneficial by assisting them to improve their understanding of course material. Our results also indicate that points and leader boards promote competition, and that points and player profiles (which includes the tracking of performance statistics) can be used to provide users with performance feedback. Students perceive progress bars as motivators to complete tasks while achievement badges are perceived to motivate task mastery. Given these results, we recommend that gamified learning systems should have a strong focus providing different types of feedback to learners, especially feedback related to progression.
Scheduling strategies and throughput optimization for the Uplink for IEEE 802.11ax and IEEE 802.11ac based networks

The new IEEE 802.11 standard, IEEE 802.11ax, has the challenging goal of serving more Uplink (UL) traffic and users as compared with his predecessor IEEE 802.11ac, enabling consistent and reliable streams of data (average throughput) per station. In this paper we explore several new IEEE 802.11ax UL scheduling mechanisms and compare between the maximum throughputs of unidirectional UDP Multi Users (MU) triadic. The evaluation is conducted based on Multiple-Input-Multiple-Output (MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) transmission multiplexing format in IEEE 802.11ax vs. the CSMA/CA MAC in IEEE 802.11ac in the Single User (SU) and MU modes for 1, 4, 8, 16, 32 and 64 stations scenario in reliable and unreliable channels. The comparison is conducted as a function of the Modulation and Coding Schemes (MCS) in use. In IEEE 802.11ax we consider two new flavors of acknowledgment operation settings, where the maximum acknowledgment windows are 64 or 256 respectively. In SU scenario the throughputs of IEEE 802.11ax are larger than those of IEEE 802.11ac by 64% and 85% in reliable and unreliable channels respectively. In MU-MIMO scenario the throughputs of IEEE 802.11ax are larger than those of IEEE 802.11ac by 263% and 270% in reliable and unreliable channels respectively. Also, as the number of stations increases, the advantage of IEEE 802.11ax in terms of the access delay also increases.
Spatially Transformed Adversarial Examples

Recent studies show that widely used deep neural networks (DNNs) are vulnerable to carefully crafted adversarial examples. Many advanced algorithms have been proposed to generate adversarial examples by leveraging the Lp distance for penalizing perturbations. Researchers have explored different defense methods to defend against such adversarial attacks. While the effectiveness of Lp distance as a metric of perceptual quality remains an active research area, in this paper we will instead focus on a different type of perturbation, namely spatial transformation, as opposed to manipulating the pixel values directly as in prior works. Perturbations generated through spatial transformation could result in large Lp distance measures, but our extensive experiments show that such spatially transformed adversarial examples are perceptually realistic and more difficult to defend against with existing defense systems. This potentially provides a new direction in adversarial example generation and the design of corresponding defenses. We visualize the spatial transformation based perturbation for different examples and show that our technique can produce realistic adversarial examples with smooth image deformation. Finally, we visualize the attention of deep networks with different types of adversarial examples to better understand how these examples are interpreted.
Decoding the neural representation of story meanings across languages.

Drawing from a common lexicon of semantic units, humans fashion narratives whose meaning transcends that of their individual utterances. However, while brain regions that represent lower-level semantic units, such as words and sentences, have been identified, questions remain about the neural representation of narrative comprehension, which involves inferring cumulative meaning. To address these questions, we exposed English, Mandarin, and Farsi native speakers to native language translations of the same stories during fMRI scanning. Using a new technique in natural language processing, we calculated the distributed representations of these stories (capturing the meaning of the stories in high-dimensional semantic space), and demonstrate that using these representations we can identify the specific story a participant was reading from the neural data. Notably, this was possible even when the distributed representations were calculated using stories in a different language than the participant was reading. Our results reveal that identification relied on a collection of brain regions most prominently located in the default mode network. These results demonstrate that neuro-semantic encoding of narratives happens at levels higher than individual semantic units and that this encoding is systematic across both individuals and languages.
A research framework of smart education

The development of new technologies enables learners to learn more effectively, efficiently, flexibly and comfortably. Learners utilize smart devices to access digital resources through wireless network and to immerse in both personalized and seamless learning. Smart education, a concept that describes learning in digital age, has gained increased attention. This paper discusses the definition of smart education and presents a conceptual framework. A four-tier framework of smart pedagogies and ten key features of smart learning environments are proposed for foster smart learners who need master knowledge and skills of the 21st century learning. The smart pedagogy framework includes class-based differentiated instruction, group-based collaborative learning, individual-based personalized learning and mass-based generative learning. Furthermore, a technological architecture of smart education, which emphasizes the role of smart computing, is proposed. The tri-tier architecture and key functions are all presented. Finally, challenges of smart education are discussed.
40 years of cognitive architectures: core cognitive abilities and practical applications

In this paper we present a broad overview of the last 40 years of research on cognitive architectures. To date, the number of existing architectures has reached several hundred, but most of the existing surveys do not reflect this growth and instead focus on a handful of well-established architectures. In this survey we aim to provide a more inclusive and high-level overview of the research on cognitive architectures. Our final set of 84 architectures includes 49 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience. To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, action selection, memory, learning, reasoning and metareasoning. In order to assess the breadth of practical applications of cognitive architectures we present information on over 900 practical projects implemented using the cognitive architectures in our list. We use various visualization techniques to highlight the overall trends in the development of the field. In addition to summarizing the current state-of-the-art in the cognitive architecture research, this survey describes a variety of methods and ideas that have been tried and their relative success in modeling human cognitive abilities, as well as which aspects of cognitive behavior need more research with respect to their mechanistic counterparts and thus can further inform how cognitive science might progress.