nils-herrmann/clean_scirepeval huggingface dataset:
MANTIS-A ROBOT WITH ADVANCED LOCOMOTION AND MANIPULATION ABILITIES

We present in this paper the specifications and design of a multi-legged robot with manipulation abilities for extraterrestrial surface exploration activities. The paper contains a brief description of the project LIMES as well as the major goals therein. The underlying methods of identifying system requirements are then described , including the envisaged mission scenario, resulting requirement lists and semantic graphs depicting dependencies. Included in this is the evaluation of different concepts with respect to varying criteria. A description of the functional principles and components is provided with regard to the merits of chosen forms of actuation, planned sensors, electronic devices and structural materials. Finally, a brief overview of how the system is to be realized is given as well as a description of the most important key technologies and components.
A low-swing differential signalling scheme for on-chip global interconnects

The dense very deep submicron (VDSM) system on chips (SoC) face a serious limitation in performance due to reverse scaling of global interconnects. Interconnection techniques which decrease delay, delay variation and ensure signal integrity, play an important role in the growth of the semiconductor industry into future generations. Current-mode low-swing interconnection techniques provide an attractive alternative to conventional full-swing voltage mode signaling in terms of delay, power and noise immunity. In this paper, we present a new current-mode low-swing interconnection technique which reduces the delay and delay variations in global interconnects. Extensive simulations for performance of our circuit under crosstalk, supply voltage, process and temperature variations were performed. The results indicate significant savings in power, reduction in delay and increase in noise immunity compared to other techniques.
Neurophysiological evaluation of pain.

Neurophysiological techniques for the evaluation of pain in humans have made important advances in the last decade. A number of features of neuroanatomy and physiology of nociception qualifies pain as a multidimensional phenomenon which is rather unique among the sensory systems and which poses a number of technical and procedural requirements for its appropriate diagnostic assessment. Various stimulation techniques to induce defined pain in humans and used in combination with the methodology of evoked electrical brain potentials and magnetic fields are presented. Most recent knowledge gathered from scalp topography and dipole source analysis of pain-relevant evoked potentials and fields is discussed. Particular emphasis is put upon laser-evoked potentials and their application for diagnosis, pathophysiological description and monitoring of patients with neurological disorders and abnormal pain states. Future perspectives in this growing field of research are discussed briefly.
Do stack traces help developers fix bugs?

A widely shared belief in the software engineering community is that stack traces are much sought after by developers to support them in debugging. But limited empirical evidence is available to confirm the value of stack traces to developers. In this paper, we seek to provide such evidence by conducting an empirical study on the usage of stack traces by developers from the ECLIPSE project. Our results provide strong evidence to this effect and also throws light on some of the patterns in bug fixing using stack traces. We expect the findings of our study to further emphasize the importance of adding stack traces to bug reports and that in the future, software vendors will provide more support in their products to help general users make such information available when filing bug reports.
Risk Management in Software Development using Artificial Neural Networks

IT industry is one of the biggest industries around the world with several software projects being developed which vary in size, cost, complexity, etc. During development, many risks of different types arise such as lack of staff experience, new technologies, budgets, etc. These risks play a huge role in success or failure of a project. Most of the available risk management solutions are too costly and time consuming. There is a need for an efficient risk management technique. To assist the project manager in risk management, we have developed an application which will identify the risks involved during software development and predict the success or failure of the project using Artificial Neural Networks. The prediction will be done using historical data taking the important and common risk factors into account. After risk identification, the probability of success or failure will be determined and suggestions for risk mitigation will be provided for the
Model checking JAVA programs using JAVA PathFinder

This paper describes a translator called Java PathFinder (Jpf), which translates from Java to Promela, the modeling language of the Spin model checker. Jpf translates a given Java program into a Promela model, which then can be model checked using Spin. The Java program may contain assertions, which are translated into similar assertions in the Promela model. The Spin model checker will then look for deadlocks and violations of any stated assertions. Jpf generates a Promela model with the same state space characteristics as the Java program. Hence, the Java program must have a finite and tractable state space. This work should be seen in a broader attempt to make formal methods applicable within NASA’s areas such as space, aviation, and robotics. The work is a continuation of an effort to formally analyze, using Spin, a multi-threaded operating system for the Deep-Space 1 space craft, and of previous work in applying existing model checkers and theorem provers to real applications.
Software Defined Radio: Basic Principles and Applications Software Defined Radio: Principios y aplicaciones básicas Software Defined Radio: Princípios e Aplicações básicas

The author makes a review of the SDR (Software Defined Radio) technology, including hardware schemes and application fields. A low performance device is presented and several tests are executed with it using free software. With the acquired experience, SDR employment opportunities are identified for low-cost solutions that can solve significant problems. In addition, a list of the most important frameworks related to the technology developed in the last years is offered, recommending the use of three of them.
Recurrent Falls in Parkinson's Disease: A Systematic Review

Most people with Parkinson's disease (PD) fall and many experience recurrent falls. The aim of this review was to examine the scope of recurrent falls and to identify factors associated with recurrent fallers. A database search for journal articles which reported prospectively collected information concerning recurrent falls in people with PD identified 22 studies. In these studies, 60.5% (range 35 to 90%) of participants reported at least one fall, with 39% (range 18 to 65%) reporting recurrent falls. Recurrent fallers reported an average of 4.7 to 67.6 falls per person per year (overall average 20.8 falls). Factors associated with recurrent falls include: a positive fall history, increased disease severity and duration, increased motor impairment, treatment with dopamine agonists, increased levodopa dosage, cognitive impairment, fear of falling, freezing of gait, impaired mobility and reduced physical activity. The wide range in the frequency of recurrent falls experienced by people with PD suggests that it would be beneficial to classify recurrent fallers into sub-groups based on fall frequency. Given that there are several factors particularly associated with recurrent falls, fall management and prevention strategies specifically targeting recurrent fallers require urgent evaluation in order to inform clinical practice.
Optimal Control Theory

Optimal control theory is a mature mathematical discipline with numerous applications in both science and engineering. It is emerging as the computational framework of choice for studying the neural control of movement, in much the same way that probabilistic inference is emerging as the computational framework of choice for studying sensory information processing. Despite the growing popularity of optimal control models, however, the elaborate mathematical machinery behind them is rarely exposed and the big picture is hard to grasp without reading a few technical books on the subject. While this chapter cannot replace such books, it aims to provide a self-contained mathematical introduction to optimal control theory that is su¢ ciently broad and yet su¢ ciently detailed when it comes to key concepts. The text is not tailored to the eld of motor control (apart from the last section, and the overall emphasis on systems with continuous state) so it will hopefully be of interest to a wider audience. Of special interest in the context of this book is the material on the duality of optimal control and probabilistic inference; such duality suggests that neural information processing in sensory and motor areas may be more similar than currently thought. The chapter is organized in the following sections:
Conservative and operative treatment in cervical burst fractures

The aim of this study is to compare the results of non-operative and anterior operative treatment of cervical burst and flexion teardrop fractures. Sixty-nine consecutive patients treated during 1980 to 1995 were reviewed retrospectively. Thirty-four of them had been treated with skull traction or halo-vest and 35 with anterior decompression, bone grafting and fixation by an anterior Caspar plate. Neurological functioning on admission and at the end of the follow-up was assessed by using Frankel’s classification. Kyphosis and spinal canal encroachment by retropulsed fragments were measured radiographically. Operatively treated patients recovered more often with at least one Frankel grade (P = 0.027) and presented less narrowing of the spinal canal (P = 0.0006) and kyphotic deformity (P = 0.00003) at the end of the follow-up. In comparison with the conservative methods, the operative Caspar technique provided superior decompression and fixation as well as promoted the healing of cord injuries caused by burst and flexion teardrop fractures.
Articular cartilage repair: basic science and clinical progress. A review of the current status and prospects.

To review the basic scientific status of repair in articular cartilage tissue and to assess the efficiency of current clinical therapies instigated for the treatment of structural lesions generated therein as a result of trauma or during the course of various diseases, notably osteoarthritis (OA). Current scientific trends and possible directions for the future will also be discussed.



A systematic and critical analysis is undertaken, beginning with a description of the spontaneous repair responses in different types of lesion. Surgical interventions aimed at inducing repair without the use of active biologics will then be considered, followed by those involving active biologics and those drawing on autogenic and allogeneic tissue transplantation principles. Cell transplantation approaches, in particular novel tissue engineering concepts, will be critically presented. These will include growth-factor-based biological treatments and gene transfection protocols. A number of technical problems associated with repair interventions, such as tissue integration, tissue retention and the role of mechanical factors, will also be analysed.



A critical analysis of the literature reveals the existence of many novel and very promising biologically-based approaches for the induction of articular cartilage repair, the vast majority of which are still at an experimental phase of development. But prospective, double-blinded clinical trials comparing currently practiced surgical treatments have, unfortunately, not been undertaken.



The existence of many new and encouraging biological approaches to cartilage repair justifies the future investment of time and money in this research area, particularly given the extremely high socio-economic importance of such therapeutic strategies in the prevention and treatment of these common joint diseases and traumas. Clinical epidemiological and prospective trials are, moreover, urgently needed for an objective, scientific appraisal of current therapies and future novel approaches.
Forgetting and Uniform Interpolation in Large-Scale Description Logic Terminologies

There have been many proposals for first-order belief networks but these typically only let us reason about the individuals that we know about. There are many instances where we have to quantify over all of the individuals in a population. When we do this the population size often matters and we need to reason about all of the members of the population (but not necessarily individually). This paper presents an algorithm to reason about multiple individuals, where we may know particular facts about some of them, but want to treat the others as a group. Combining unification with variable elimination lets us reason about classes of individuals without needed to ground out the theory.
Visualisation of latent fingermarks on polymer banknotes using copper vacuum metal deposition: A preliminary study.

The UK's recent move to polymer banknotes has seen some of the currently used fingermark enhancement techniques for currency potentially become redundant, due to the surface characteristics of the polymer substrates. Possessing a non-porous surface with some semi-porous properties, alternate processes are required for polymer banknotes. This preliminary investigation explored the recovery of fingermarks from polymer notes via vacuum metal deposition using elemental copper. The study successfully demonstrated that fresh latent fingermarks, from an individual donor, could be clearly developed and imaged in the near infrared. By varying the deposition thickness of the copper, the contrast between the fingermark minutiae and the substrate could be readily optimised. Where the deposition thickness was thin enough to be visually indistinguishable, forensic gelatin lifters could be used to lift the fingermarks. These lifts could then be treated with rubeanic acid to produce a visually distinguishable mark. The technique has shown enough promise that it could be effectively utilised on other semi- and non-porous substrates.
Review : Support Vector Machines in Pattern Recognition

SVM is extensively used in pattern recognition because of its capability to classify future unseen data and its’ good generalization performance. Several algorithms and models have been proposed for pattern recognition that uses SVM for classification. These models proved the efficiency of SVM in pattern recognition. Researchers have compared their results for SVM with other traditional empirical risk minimization techniques, such as Artificial Neural Network, Decision tree, etc. Comparison results show that SVM is superior to these techniques. Also, different variants of SVM are developed for enhancing the performance. In this paper, SVM is briefed and some of the pattern recognition applications of SVM are surveyed and briefly summarized. Keyword Hyperplane, Pattern Recognition, Quadratic Programming Problem, Support Vector Machines.
Burning With Envy? Dispositional and Situational Influences on Envy in Grandiose and Vulnerable Narcissism.

Research on narcissism and envy suggests a variable relationship that may reflect differences between how vulnerable and grandiose narcissism relate to precursors of envy. Accordingly, we proposed a model in which dispositional envy and relative deprivation differentially mediate envy's association with narcissistic vulnerability, grandiosity, and entitlement. To test the model, 330 young adults completed dispositional measures of narcissism, entitlement, and envy; one week later, participants reported on deprivation and envy feelings toward a peer who outperformed others on an intelligence test for a cash prize (Study 1) or earned higher monetary payouts in a betting game (Study 2). In both studies, structural equation modeling broadly supported the proposed model. Vulnerable narcissism robustly predicted episodic envy via dispositional envy. Entitlement-a narcissistic facet common to grandiosity and vulnerability-was a significant indirect predictor via relative deprivation. Study 2 also found that (a) the grandiose leadership/authority facet indirectly curbed envy feelings via dispositional envy, and (b) episodic envy contributed to schadenfreude feelings, which promoted efforts to sabotage a successful rival. Whereas vulnerable narcissists appear dispositionally envy-prone, grandiose narcissists may be dispositionally protected. Both, however, are susceptible to envy through entitlement when relative deprivation is encountered.
Modeling Cyber-Insurance: Towards a Unifying Framework

We propose a comprehensive formal framework to classify all market models of cyber-insurance we are aware of. The framework features a common terminology and deals with the specific properties of cyber-risk in a unified way: interdependent security, correlated risk, and information asymmetries. A survey of existing models, tabulated according to our framework, reveals a discrepancy between informal arguments in favor of cyber-insurance as a tool to align incentives for better network security, and analytical results questioning the viability of a market for cyber-insurance. Using our framework, we show which parameters should be considered and endogenized in future models to close this gap.
Split hardware transactions: true nesting of transactions using best-effort hardware transactional memory

Transactional Memory (TM) is on its way to becoming the programming API of choice for writing correct, concurrent, and scalable programs. Hardware TM (HTM) implementations are expected to be significantly faster than pure software TM (STM); however, full hardware support for true closed and open nested transactions is unlikely to be practical.
 This paper presents a novel mechanism, the split hardware transaction (SpHT), that uses minimal software support to combine multiple segments of an atomic block, each executed using a separate hardware transaction, into one atomic operation. The idea of segmenting transactions can be used for many purposes, including nesting, local retry, orElse, and user-level thread scheduling; in this paper we focus on how it allows linear closed and open nesting of transactions. SpHT overcomes the limited expressive power of best-effort HTM while imposing overheads dramatically lower than STM and preserving useful guarantees such as strong atomicity provided by the underlying HTM.
Panniculus, giant hernias and surgical problems in patients with morbid obesity

Prevalence of morbid obesity is rising. Along with it, the adipose associated co-morbidities increase - included panniculus morbidus, the end stage of obesity of the abdominal wall. In the course of time panniculus often develop a herniation of bowel. An incarcerated hernia and acute exacerbation of a chronic inflammation of the panniculus must be treated immediately and presents a surgical challenge. The resection of such massive abdominal panniculus presents several technical problems to the surgeon. Preparation of long standing or fixed hernias may require demanding adhesiolysis. The wound created is huge and difficult to manage, and accompanied by considerable complications at the outset. We provide a comprehensive overview of a possible approach for panniculectomy and hernia repair and overlook of the existing literature.
Automatically improve software architecture models for performance, reliability, and cost using evolutionary algorithms

Quantitative prediction of quality properties (i.e. extra-functional properties such as performance, reliability, and cost) of software architectures during design supports a systematic software engineering approach. Designing architectures that exhibit a good trade-off between multiple quality criteria is hard, because even after a functional design has been created, many remaining degrees of freedom in the software architecture span a large, discontinuous design space. In current practice, software architects try to find solutions manually, which is time-consuming, can be error-prone and can lead to suboptimal designs. We propose an automated approach to search the design space for good solutions. Starting with a given initial architectural model, the approach iteratively modifies and evaluates architectural models. Our approach applies a multi-criteria genetic algorithm to software architectures modelled with the Palladio Component Model. It supports quantitative performance, reliability, and cost prediction and can be extended to other quantitative quality criteria of software architectures. We validate the applicability of our approach by applying it to an architecture model of a component-based business information system and analyse its quality criteria trade-offs by automatically investigating more than 1200 alternative design candidates.
Leimu : Gloveless Music Interaction Using a Wrist Mounted Leap Motion

Camera-based motion tracking has become a popular enabling technology for gestural human-computer interaction. However, the approach suffers from several limitations, which have been shown to be particularly problematic when employed within musical contexts. This paper presents Leimu, a wrist mount that couples a Leap Motion optical sensor with an inertial measurement unit to combine the benefits of wearable and camera-based motion tracking. Leimu is designed, developed and then evaluated using discourse and statistical analysis methods. Qualitative results indicate that users consider Leimu to be an effective interface for gestural music interaction and the quantitative results demonstrate that the interface offers improved tracking precision over a Leap Motion positioned on a table top.
Nudges for Privacy and Security: Understanding and Assisting Users' Choices Online

Advancements in information technology often task users with complex and consequential privacy and security decisions. A growing body of research has investigated individuals’ choices in the presence of privacy and information security tradeoffs, the decision-making hurdles affecting those choices, and ways to mitigate such hurdles. This article provides a multi-disciplinary assessment of the literature pertaining to privacy and security decision making. It focuses on research on assisting individuals’ privacy and security choices with soft paternalistic interventions that nudge users toward more beneficial choices. The article discusses potential benefits of those interventions, highlights their shortcomings, and identifies key ethical, design, and research challenges.
Comparison of Different Data Mining Techniques to Predict Hospital Length of Stay

In this paper we present the performance analysis of different data mining techniques to predict the inpatient hospital length of stay in a super specialty hospital. Data set used for the analysis is real time data taken from super specialty hospital. Pre-processed data set is generated from the electronic discharge summaries obtained from the hospital. This data set consists of 401 records with 16 parameters. In this paper we have investigated four data mining techniques: Multilayer back propagation NN, Naive Bayes Classifier, K-NN method, J48 class of C4.5 decision tree. We found from the analysis that Neural Network has achieved better performance compared to the other three techniques.