nils-herrmann/clean_scirepeval huggingface dataset:
Meaningful Identifier Names: The Case of Single-Letter Variables

It is widely accepted that variable names in computer programs should be meaningful, and that this aids program comprehension. "Meaningful" is commonly interpreted as favoring long descriptive names. However, there is at least some use of short and even single-letter names: using 'i' in loops is very common, and we show (by extracting variable names from 1000 popular github projects in 5 languages) that some other letters are also widely used. In addition, controlled experiments with different versions of the same functions (specifically, different variable names) failed to show significant differences in ability to modify the code. Finally, an online survey showed that certain letters are strongly associated with certain types and meanings. This implies that a single letter can in fact convey meaning. The conclusion from all this is that single letter variables can indeed be used beneficially in certain cases, leading to more concise code.
An Improved Method on Static Binary Analysis to Enhance the Context-Sensitive CFI

Control Flow Integrity (CFI) is one of the most promising technique to defend Code-Reuse Attacks (CRAs). Traditional CFI Systems and recent Context-Sensitive CFI use coarse control flow graphs (CFGs) to analyze whether the control flow hijack occurs, left vast space for attackers at indirect call-sites. Coarse CFGs make it difficult to decide which target to execute at indirect control-flow transfers, and weaken the existing CFI systems actually. It is an unsolved problem to extract CFGs precisely and perfectly from binaries now. In this paper, we present an algorithm to get a more precise CFG from binaries. Parameters are analyzed at indirect call-sites and functions firstly. By comparing counts of parameters prepared before call-sites and consumed by functions, targets of indirect calls are reduced. Then the control flow would be more constrained at indirect call-sites in runtime. Combined with CCFI, we implement our policy. Experimental results on some popular programs show that our approach is efficient. Further analysis show that it can mitigate COOP and other advanced attacks. Contex-sensitive, CFI, binary analysis, code reuse attack.
Nanophotonics: Shrinking light-based technology

The study of light at the nanoscale has become a vibrant field of research, as researchers now master the flow of light at length scales far below the optical wavelength, largely surpassing the classical limits imposed by diffraction. Using metallic and dielectric nanostructures precisely sculpted into two-dimensional (2D) and 3D nanoarchitectures, light can be scattered, refracted, confined, filtered, and processed in fascinating new ways that are impossible to achieve with natural materials and in conventional geometries. This control over light at the nanoscale has not only unveiled a plethora of new phenomena but has also led to a variety of relevant applications, including new venues for integrated circuitry, optical computing, solar, and medical technologies, setting high expectations for many novel discoveries in the years to come.
SDCCN: A Novel Software Defined Content-Centric Networking Approach

Content Centric Networking (CCN) represents an important change in the current operation of the Internet, prioritizing content over the communication between end nodes. Routers play an essential role in CCN, since they receive the requests for a given content and provide content caching for the most popular ones. They have their own forwarding strategies and caching policies for the most popular contents. Despite the number of works on this field, experimental evaluation of different forwarding algorithms and caching policies yet demands a huge effort in routers programming. In this paper we propose SDCCN, a SDN approach to CCN that provides programmable forwarding strategy and caching policies. SDCCN allows fast prototyping and experimentation in CCN. Proofs of concept were performed to demonstrate the programmability of the cache replacement algorithms and the Strategy Layer. Experimental results, obtained through implementation in the Mininet environment, are presented and evaluated.
ANTECEDENTS AND DISTINCTIONS BETWEEN ONLINE TRUST AND DISTRUST : PREDICTING HIGH-AND LOW-RISK INTERNET BEHAVIORS

While previous studies have investigated the determinants and consequences of online trust, online distrust has seldom been studied. Assuming that the positive antecedents of online trust are necessarily negative antecedents of online distrust or that positive consequences of online trust are necessarily negatively affected by online distrust is inappropriate. This study examines the different antecedents of online trust and distrust in relation to consumer and website characteristics. Moreover, this study further examines whether online trust and distrust asymmetrically affect behaviors with different risk levels. A model is developed and tested using a survey of 1,153 online consumers. LISREL was employed to test the proposed model. Overall, different consumer and website characteristics influence online trust and distrust, and online trust engenders different behavioral outcomes to online distrust. The authors also discuss the theoretical and managerial implications of the study findings.
Optical magnetism and negative refraction in plasmonic metamaterials

In this review we describe the challenges and opportunities for creating magnetically active metamaterials in the optical part of the spectrum. The emphasis is on the sub-wavelength periodic metamaterials whose unit cell is much smaller than the optical wavelength. The conceptual differences between microwave and optical metamaterials are demonstrated. We also describe several theoretical techniques used for calculating the effective parameters of plasmonic metamaterials: the effective dielectric permittivity eff(ω) and magnetic permeability μeff(ω). Several examples of negative permittivity and negative permeability plasmonic metamaterials are used to illustrate the theory.
The Horseshoe Crab, Limulus polyphemus: 200 Million Years of Existence, 100 Years of Study

Management of the horseshoe crab, Limulus polyphemus, is currently surrounded by controversy. The species is considered a multiple-use resource, as it plays an important role as bait in a commercial fishery, as a source of an important biomedical product, as an important food source for multiple species of migratory shorebirds, as well as in several other minor, but important, uses. Concern has arisen that horseshoe crabs may be declining in number. However, traditional management historically data have not been kept for this species. In this review we discuss the general biology, ecology, and life history of the horseshoe crab. We discuss the role the horseshoe crab plays in the commercial fishery, in the biomedical industry, as well as for the shorebirds. We examine the economic impact the horseshoe crab has in the mid-Atlantic region and review the current developments of alternatives to the horseshoe crab resource. We discuss the management of horseshoe crabs by including a description of the Atlantic States Marine Fisheries Commission (ASMFC) and its management process. An account of the history of horseshoe crab management is included, as well as recent and current regulations and restrictions.
A semi-feature learning approach for tampered region localization across multi-format images

In multimedia security, it is an important task to localize the tampered image regions. In this work, deep learning is used to solve this problem and the approach can be applied to multi-format images. Concretely, we use Stack Autoencoder to obtain the tampered image block features so that the forgery can be identified in a semi-automatic manner. Contextual information of image block is further integrated to improve the localization accuracy. The approach is tested on a benchmark dataset, with a 92.84% localization accuracy and a 0.9375 Area Under Curve (AUC) score. Compared to the state-of-the-art solutions for multi-format images, our solution has an over 40% AUC improvement and 5.7 times F1 improvement. The results also out-perform several approaches which are designed specifically for JPEG images by 41.12%∼63.08% in AUC and with a 4∼8 times better F1.
Current opinion on auricular reconstruction.

To review the current practice in the field of auricular reconstruction and to highlight the recent advances reported in the medical literature.



The majority of surgeons who perform auricular reconstruction continue to employ the well-established techniques developed by Brent and Nagata. Surgery takes between two and four stages, with the initial stage being construction of a framework of autogenous rib cartilage which is implanted into a subcutaneous pocket. Several modifications of these techniques have been reported. More recently, synthetic frameworks have been employed instead of autogenous rib cartilage. For this procedure, the implant is generally covered with a temporoparietal flap and a skin graft at the first stage of surgery. Tissue engineering is a rapidly developing field, and there have been several articles related to the field of auricular reconstruction. These show great potential to offer a solution to the challenge associated with construction of a viable autogenous cartilage framework, whilst avoiding donor-site morbidity.



This article gives an overview of the current practice in the field of auricular reconstruction and summarizes the recent surgical developments and relevant tissue engineering research.
Learning Effective RGB-D Representations for Scene Recognition

Deep convolutional networks can achieve impressive results on RGB scene recognition thanks to large data sets such as places. In contrast, RGB-D scene recognition is still underdeveloped in comparison, due to two limitations of RGB-D data we address in this paper. The first limitation is the lack of depth data for training deep learning models. Rather than fine tuning or transferring RGB-specific features, we address this limitation by proposing an architecture and a two-step training approach that directly learns effective depth-specific features using weak supervision via patches. The resulting RGB-D model also benefits from more complementary multimodal features. Another limitation is the short range of depth sensors (typically 0.5 m to 5.5 m), resulting in depth images not capturing distant objects in the scenes that RGB images can. We show that this limitation can be addressed by using RGB-D videos, where more comprehensive depth information is accumulated as the camera travels across the scenes. Focusing on this scenario, we introduce the ISIA RGB-D video data set to evaluate RGB-D scene recognition with videos. Our video recognition architecture combines convolutional and recurrent neural networks that are trained in three steps with increasingly complex data to learn effective features (i.e., patches, frames, and sequences). Our approach obtains the state-of-the-art performances on RGB-D image (NYUD2 and SUN RGB-D) and video (ISIA RGB-D) scene recognition.
Personal Recommendation Engine of User Behavior Pattern and Analysis on Social Networks

In the age of information network explosion, Along with the popularity of the Internet, users can link to all kinds of social networking sites anytime and anywhere to interact and discuss with others. This phenomenon indicates that social networking sites have become a platform for interactions between companies and customers so far. Therefore, with the above through social science and technology development trend arising from current social phenomenon, research of this paper, mainly expectations for analysis by the information of interaction between people on the social network, such as: user clicked fans pages, user's graffiti wall message information, friend clicked fans pages etc. Three kinds of personal information for personal preference analysis, and from this huge amount of personal data to find out corresponding diverse group for personal preference category. We can by personal preference information for diversify personal advertising, product recommendation and other services. The paper at last through the actual business verification, the research can improve website browsing pages growth 11%, time on site growth 15%, site bounce rate dropped 13.8%, product click through rate growth 43%, more fully represents the results of this research fit the use's preference.
Potential uses of probiotics in clinical practice.

Probiotics are defined as live microorganisms that, when administered in adequate amounts, confer a health benefit on the host. There is now mounting evidence that selected probiotic strains can provide health benefits to their human hosts. Numerous clinical trials show that certain strains can improve the outcome of intestinal infections by reducing the duration of diarrhea. Further investigations have shown benefits in reducing the recurrence of urogenital infections in women, while promising studies in cancer and allergies require research into the mechanisms of activity for particular strains and better-designed trials. At present, only a small percentage of physicians either know of probiotics or understand their potential applicability to patient care. Thus, probiotics are not yet part of the clinical arsenal for prevention and treatment of disease or maintenance of health. The establishment of accepted standards and guidelines, proposed by the Food and Agriculture Organization of the United Nations and the World Health Organization, represents a key step in ensuring that reliable products with suitable, informative health claims become available. Based upon the evidence to date, future advances with single- and multiple-strain therapies are on the horizon for the management of a number of debilitating and even fatal conditions.
Blind Massive MIMO Base Stations: Downlink Transmission and Jamming

Massive  (Multiple-Input–Multiple-Output) is a wireless technology which aims to serve several different devices simultaneously in the same frequency band through spatial multiplexing, made possible by using a large number of antennas at the base station. e many antennas facilitates efficient beamforming, based on channel estimates acquired from uplink reference signals, which allows the base station to transmit signals exactly where they are needed. e multiplexing together with the array gain from the beamforming can increase the spectral efficiency over contemporary systems. One challenge of practical importance is how to transmit data in the downlink when no channel state information is available. When a device initially joins the network, prior to  uplink reference signals that enable beamforming, it needs system information—instructions on how to properly function within the network. It is transmission of system information that is the main focus of this thesis. In particular, the thesis analyzes how the reliability of the transmission of system information depends on the available amount of diversity. It is shown how downlink reference signals, space-time block codes, and power allocation can be used to improve the reliability of this transmission. In order to estimate the uplink and downlink channels from uplink reference signals, which is imperative to ensure scalability in the number of base station antennas, massive  relies on channel reciprocity. is thesis shows that the principles of channel reciprocity can also be exploited by a jammer, a malicious transmier, aiming to disrupt legitimate communication between two devices. A heuristic scheme is proposed in which the jammer estimates the channel to a target device blindly, without any knowledge of the transmied legitimate signals, and subsequently beamforms noise towards the target. Under the same power constraint, the proposed jammer can disrupt the legitimate link more effectively than a conventional omnidirectional jammer in many cases.
600 V Reverse Conducting (RC-)IGBT for Drives Applications in Ultra-Thin Wafer Technology

Reverse conducting IGBTs are fabricated in a large productive volume for soft switching applications, such as inductive heaters, microwave ovens or lamp ballast, since several years. To satisfy the requirements of hard switching applications, such as inverters in refrigerators, air conditioners or general purpose drives, the reverse recovery behavior of the integrated diode has to be optimized. Two promising concepts for such an optimization are based on a reduction of the charge- carrier lifetime or the anti-latch p+ implantation dose. It is shown that a combination of both concepts will lead to a device with a good reverse recovery behavior, low forward and reverse voltage drop and excellent over current turn- off capability of a trench field-stop IGBT.
Novel Variable Length Teager Energy Separation Based Instantaneous Frequency Features for Replay Detection

Replay attacks presents a great risk for Automatic Speaker Verification (ASV) system. In this paper, we propose a novel replay detector based on Variable length Teager Energy OperatorEnergy Separation Algorithm-Instantaneous Frequency Cosine Coefficients (VESA-IFCC) for the ASV spoof 2017 challenge. The key idea here is to exploit the contribution of IF in each subband energy via ESA to capture possible changes in spectral envelope (due to transmission and channel characteristics of replay device) of replayed speech. The IF is computed from narrowband components of speech signal, and DCT is applied in IF to get proposed feature set. We compare the performance of the proposed VESA-IFCC feature set with the features developed for detecting synthetic and voice converted speech. This includes the CQCC, CFCCIF and prosody-based features. On the development set, the proposed VESA-IFCC features when fused at score-level with a variant of CFCCIF and prosodybased features gave the least EER of 0.12 %. On the evaluation set, this combination gave an EER of 18.33 %. However, post-evaluation results of challenge indicate that VESA-IFCC features alone gave the relatively least EER of 14.06 % (i.e., relatively 16.11 % less compared to baseline CQCC) and hence, is a very useful countermeasure to detect replay attacks.
Flash flood mitigation : recommendations for research and applications

New technologies promise reduced flash flood losses. However, real-time observations with vast multi-sensor networks, more precise mapping capabilities using remote sensing and GIS, quicker hydrological and meteorological models, and increasing forecast lead times have not reduced losses. In November, 1999, 35 researchers from nine countries met in Ravello, Italy at a NATO sponsored Advanced Study Institute, to discuss these issues and to develop a research agenda that incorporates the various components required to cope with flash floods. The key recommendations from the Institute were: (1) greater emphasis on increasing understanding of the social processes involved in flash flood warning, particularly in the response phases, and (2) the need to reduce vulnerability in sustainable ways compatible with long-term economic and social goals. The relationship between hydrometeorology and social science is seen as critical to advancing our abilities to cope with flash floods.
A logical formalization of the OCC theory of emotions

In this paper, we provide a logical formalization of the emotion triggering process and of its relationship with mental attitudes, as described in Ortony, Clore, and Collins’s theory. We argue that modal logics are particularly adapted to represent agents’ mental attitudes and to reason about them, and use a specific modal logic that we call Logic of Emotions in order to provide logical definitions of all but two of their 22 emotions. While these definitions may be subject to debate, we show that they allow to reason about emotions and to draw interesting conclusions from the theory.
Comparison of LIFI and WIFI and study of smart meter-survey

Li-Fi stands for Light-Fidelity. Li-Fi innovation, which was suggested by Harald Haas, a German physicist, gives conduction of information over brightening through distribution of information via a LED light which changes in force quicker when compared to the vision of human beings which could take after. Wi-Fi is extraordinary for overall remote scope inside structures, while Li-Fi has been perfect for high thickness remote information scope in limited range besides for calming wireless impedance concerns. Smart meters are electronic devices which are used for recording consumption of electrical energy on a regular basis at an interval of an hour or less. In this paper, we motivate the need to learn and understand about the various new technologies like LiFi and its advantages. Further, we will understand the comparison between LiFi and Wi-Fi and learn about the advantages of using LiFi over WiFi. In addition to that we will also learn about the working of smart meters and its communication of the recorded information on a daily basis to the utility for monitoring and billing purposes.
Introducing the Human Brain Project

The Human Brain Project (HBP) is a candidate project in the European Union’s FET Flagship Program, funded by the ICT Program in the Seventh Framework Program. The project will develop a new integrated strategy for understanding the human brain and a novel research platform that will integrate all the data and knowledge we can acquire about the structure and function of the brain and use it to build unifying models that can be validated by simulations running on supercomputers. The project will drive the development of supercomputing for the life sciences, generate new neuroscientific data as a benchmark for modeling, develop radically new tools for informatics, modeling and simulation, and build virtual laboratories for collaborative basic and clinical studies, drug simulation and virtual prototyping of neuroprosthetic, neuromorphic, and robotic devices.
Surface passivation engineering strategy to fully-inorganic cubic CsPbI3 perovskites for high-performance solar cells

Owing to inevitable thermal/moisture instability for organic–inorganic hybrid perovskites, pure inorganic perovskite cesium lead halides with both inherent stability and prominent photovoltaic performance have become research hotspots as a promising candidate for commercial perovskite solar cells. However, it is still a serious challenge to synthesize desired cubic cesium lead iodides (CsPbI3) with superior photovoltaic performance for its thermodynamically metastable characteristics. Herein, polymer poly-vinylpyrrolidone (PVP)-induced surface passivation engineering is reported to synthesize extra-long-term stable cubic CsPbI3. It is revealed that acylamino groups of PVP induce electron cloud density enhancement on the surface of CsPbI3, thus lowering surface energy, conducive to stabilize cubic CsPbI3 even in micrometer scale. The cubic-CsPbI3 PSCs exhibit extra-long carrier diffusion length (over 1.5 μm), highest power conversion efficiency of 10.74% and excellent thermal/moisture stability. This result provides important progress towards understanding of phase stability in realization of large-scale preparations of efficient and stable inorganic PSCs. Inorganic cesium lead iodide perovskite is inherently more stable than the hybrid perovskites but it undergoes phase transition that degrades the solar cell performance. Here Li et al. stabilize it with poly-vinylpyrrolidone and obtain high efficiency of 10.74% with excellent thermal and moisture stability.