nils-herrmann/clean_scirepeval huggingface dataset:
Pericapsular Nerve Group (PENG) Block for Hip Fracture.

Fascia iliaca block or femoral nerve block is used frequently in hip fracture patients because of their opioid-sparing effects and reduction in opioid-related adverse effects. A recent anatomical study on hip innervation led to the identification of relevant landmarks to target the hip articular branches of femoral nerve and accessory obturator nerve. Using this information, we developed a novel ultrasound-guided approach for blockade of these articular branches to the hip, the PENG (PEricapsular Nerve Group) block. In this report, we describe the technique and its application in 5 consecutive patients.
HadoopCL2: Motivating the Design of a Distributed, Heterogeneous Programming System With Machine-Learning Applications

Machine learning (ML) algorithms have garnered increased interest as they demonstrate improved ability to extract meaningful trends from large, diverse, and noisy data sets. While research is advancing the state-of-the-art in ML algorithms, it is difficult to drastically improve the real-world performance of these algorithms. Porting new and existing algorithms from single-node systems to multi-node clusters, or from architecturally homogeneous systems to heterogeneous systems, is a promising optimization technique. However, performing optimized ports is challenging for domain experts who may lack experience in distributed and heterogeneous software development. This work explores how challenges in ML application development on heterogeneous, distributed systems shaped the development of the HadoopCL2 (HCL2) programming system. ML applications guide this work because they exhibit features that make application development difficult: large & diverse datasets, complex algorithms, and the need for domain-specific knowledge. The goal of this work is a general, MapReduce programming system that outperforms existing programming systems. This work evaluates the performance and portability of HCL2 against five ML applications from the Mahout ML framework on two hardware platforms. HCL2 demonstrates speedups of greater than 20x relative to Mahout for three computationally heavy algorithms and maintains minor performance improvements for two I/O bound algorithms.
Towards a Verified , General-Purpose Operating System Kernel †

Operating system kernels are complex, critical, and difficult to test systems. The imperative nature of operating system implementations, the programming languages chosen, and the usually selected implementation style combine to make verification of a general-purpose operating system kernel impractical. While security policies have been verified against models of general-purpose operating systems, no verification has ever been accomplished for a general purpose operating system implementation. This paper summarizes how we are attempting to create a verified general purpose operating system implementation for Coyotos, the successor to the EROS system, and why we believe that there is a reasonable chance of success.
Top-down predictions in the cognitive brain

The human brain is not a passive organ simply waiting to be activated by external stimuli. Instead, we propose that the brain continuously employs memory of past experiences to interpret sensory information and predict the immediately relevant future. The basic elements of this proposal include analogical mapping, associative representations and the generation of predictions. This review concentrates on visual recognition as the model system for developing and testing ideas about the role and mechanisms of top-down predictions in the brain. We cover relevant behavioral, computational and neural aspects, explore links to emotion and action preparation, and consider clinical implications for schizophrenia and dyslexia. We then discuss the extension of the general principles of this proposal to other cognitive domains.
Autogeneration and Autotuning of 3D Stencil Codes on Homogeneous and Heterogeneous GPU Clusters

This paper develops and evaluates search and optimization techniques for autotuning 3D stencil (nearest neighbor) computations on GPUs. Observations indicate that parameter tuning is necessary for heterogeneous GPUs to achieve optimal performance with respect to a search space. Our proposed framework takes a most concise specification of stencil behavior from the user as a single formula, autogenerates tunable code from it, systematically searches for the best configuration and generates the code with optimal parameter configurations for different GPUs. This autotuning approach guarantees adaptive performance for different generations of GPUs while greatly enhancing programmer productivity. Experimental results show that the delivered floating point performance is very close to previous handcrafted work and outperforms other autotuned stencil codes by a large margin. Furthermore, heterogeneous GPU clusters are shown to exhibit the highest performance for dissimilar tuning parameters leveraging proportional partitioning relative to single-GPU performance.
MARS: A Personalised Mobile Activity Recognition System

Mobile activity recognition focuses on inferring the current activities of a mobile user by leveraging the sensory data that is available on today's smart phones. The state of the art in mobile activity recognition uses traditional classification techniques. Thus, the learning process typically involves: i) collection of labelled sensory data that is transferred and collated in a centralised repository, ii) model building where the classification model is trained and tested using the collected data, iii) a model deployment stage where the learnt model is deployed on-board a mobile device for identifying activities based on new sensory data. In this paper, we demonstrate the Mobile Activity Recognition System (MARS) where for the first time the model is built and continuously updated on-board the mobile device itself using data stream mining. The advantages of the on-board approach are that it allows model personalisation and increased privacy as the data is not sent to any external site. Furthermore, when the user or its activity profile changes MARS enables quick model adaptation. One of the stand out features of MARS is that training/updating the model takes less than 30 seconds per activity. MARS has been implemented on the Android platform to demonstrate that it can achieve accurate mobile activity recognition. Moreover, we can show in practice that MARS quickly adapts to user profile changes while at the same time being scalable and efficient in terms of consumption of the device resources.
Breastfeeding and the use of human milk.

Considerable advances have occurred in recent years in the scientific knowledge of the benefits of breastfeeding, the mechanisms underlying these benefits, and in the clinical management of breastfeeding. This policy statement on breastfeeding replaces the 1997 policy statement of the American Academy of Pediatrics and reflects this newer knowledge and the supporting publications. The benefits of breastfeeding for the infant, the mother, and the community are summarized, and recommendations to guide the pediatrician and other health care professionals in assisting mothers in the initiation and maintenance of breastfeeding for healthy term infants and high-risk infants are presented. The policy statement delineates various ways in which pediatricians can promote, protect, and support breastfeeding not only in their individual practices but also in the hospital, medical school, community, and nation.
Beliefs , perceptions and expectations among acne patients

To evaluate the information, its source, beliefs an d perceptions of acne patients regarding acne and their expectations about treatment.  All acne patients visiting Dermatology outpatient c lini at WAPDA Teaching Hospital Complex, Lahore and at private practice fo r management were asked to fill a voluntary questionnaire containing information about patients ’ beliefs and perception about acne. Grading was done by a dermatologist. Result 449 patients completed the pro forma. Males were 37 % and females 63%. 54.1% of patients waited for one year to have treatment. More than 60 % thought acne as a curable disease and more than 50% expected it to clear in 2-4 weeks. Most of them decided themselves to visit the doctor or were influenced by their parents. Most of them gath ered information regarding acne from close relatives and friends. Infection and poor hygiene ( less washing of face with soap) was thought to be the most important cause. Facial masks and lotions were most commonly tried non-prescription acne products. 45% thought that acne had a severe i mpact on their self-image. Topical treatment was the most desired one. More than 40% of patients had grade IV acne and there was no significant difference between males and females re garding grade wise presentation.  Community-based health education program is require d to increase the awareness about acne and to resolve the misconceptions.
Power divider based on grounded dielectric slab waveguide operating in E11x mode

A novel low-loss planar dielectric waveguide is proposed. It is based on a high-permittivity dielectric slab parallel to a metal ground. The guiding channel is limited at the sides by a number of air holes which are lowering the effective permittivity. A mode with the electric field primarily parallel to the ground plane is used, similar to the E11x mode of an insulated image guide. A rather thick gap layer between the ground and the high-permittivity slab makes this mode to show the highest effective permittivity. The paper discusses the mode dispersion behaviour and presents measured characteristics of a power divider circuit operating at a frequency of about 8 GHz. Low leakage of about 14% is observed at the discontinuities forming the power divider. Using a compact dipole antenna structure, excitation efficiency of more than 90% is obtained.
New advances in the genetics of early onset obesity

Genes vs environment The rising prevalence of childhood obesity is largely driven by recent changes in diet and levels of physical activity; however, there is strong evidence to suggest that like height, weight is a highly heritable trait (40–70% heritability). It is very likely that the ability to store fat in times of nutritional abundance was a positive trait selected over thousands of years of evolution only to emerge recently on a large scale as a result of changes in our environment. There is increasing recognition that studies aimed at identifying these polygenic or oligogenic influences on weight gain in childhood are needed and a number of loci have been identified in genome-wide scans in different populations, although as yet few have been replicated. As well as a detectable shift in the mean BMI of children and adults in most populations, we are seeing a greater proportion of patients of all ages with severe obesity. It is clear that these individuals have a certain genetic propensity to store excessive caloric intake as fat and it is important to have a practical approach to the investigation and management of these vulnerable patients who have considerably increased morbidity and mortality. Although there is no accepted definition for severe or morbid obesity in childhood, a BMI s.d. 42.5 (weight off the chart) is often used in Specialist Centres and the crossing of major growth percentile lines upward is an early indication of risk of severe obesity.
Proposing 3SEMCS- Three Step Encryption Method for Cyber Security in Modern Cryptography

Cyber security is a critical issue now a days in various different domains in different disciplines. This paper presents a review analysis of cyber hacking attacks along with its experimental results and proposes a new methodology 3SEMCS named as three step encryption method for cyber security. By utilizing this new designed methodology, security at highest level will be easily provided especially on the time of request submission in the search engine as like google during client server communication. During its working a group of separate encryption algorithms are used. The benefit to utilize this three step encryption is to provide more tighten security by applying three separate encryption algorithms in each phase having different operations. And the additional benefit to utilize this methodology is to run over new designed private browser named as “RR” that is termed as Rim Rocks correspondingly this also help to check the authenticated sites or phishing sites by utilizing the strategy of passing URL address from phishing tank. This may help to block the phisher sites and user will relocate on previous page. The purpose to design this personnel browser is to enhance the level of security by
On Exploring the " Dark Figure " of Crime

the "dark figure" of crime&mdash;that is, about occurrences that by some criteria are called crime yet that are not registered in the statistics of whatever agency was the source of the data being used. Contending arguments arose about the dark figure between the "realists" who emphasized the virtues of completeness with which data represent the "real crime" that takes place and the "institutionalists" who emphasize that crime can have valid meaning only in terms of organized, legitimate social responses to it. This paper examines these arguments in the context of police and survey statistics as measures of crime in a population. It concludes that in exploring the dark figure of crime, the primary question is not how much of it
Julius Bernstein (1839–1917): pioneer neurobiologist and biophysicist

Bernstein belonged to the Berlin school of “organic physicists” who played a prominent role in creating modern physiology and biophysics during the second half of the nineteenth century. He trained under du Bois-Reymond in Berlin, worked with von Helmholtz in Heidelberg, and finally became Professor of Physiology at the University of Halle. Nowadays his name is primarily associated with two discoveries: (1) The first accurate description of the action potential in 1868. He developed a new instrument, a differential rheotome (= current slicer) that allowed him to resolve the exact time course of electrical activity in nerve and muscle and to measure its conduction velocity. (2) His ‘Membrane Theory of Electrical Potentials’ in biological cells and tissues. This theory, published by Bernstein in 1902, provided the first plausible physico-chemical model of bioelectric events; its fundamental concepts remain valid to this day. Bernstein pursued an intense and long-range program of research in which he achieved a new level of precision and refinement by formulating quantitative theories supported by exact measurements. The innovative design and application of his electromechanical instruments were milestones in the development of biomedical engineering techniques. His seminal work prepared the ground for hypotheses and experiments on the conduction of the nervous impulse and ultimately the transmission of information in the nervous system. Shortly after his retirement, Bernstein (1912) summarized his electrophysiological work and extended his theoretical concepts in a book Elektrobiologie that became a classic in its field. The Bernstein Centers for Computational Neuroscience recently established at several universities in Germany were named to honor the person and his work.
Acquiring and Exploiting Lexical Knowledge for Twitter Sentiment Analysis

The most popular sentiment analysis task in Twitter is the automatic classification of tweets into sentiment categories such as positive, negative, and neutral. State-ofthe-art solutions to this problem are based on supervised machine learning models trained from manually annotated examples. These models are affected by label sparsity, because the manual annotation of tweets is labour-intensive and time-consuming. This thesis addresses the label sparsity problem for Twitter polarity classification by automatically building two type of resources that can be exploited when labelled data is scarce: opinion lexicons, which are lists of words labelled by sentiment, and synthetically labelled tweets. In the first part of the thesis, we induce Twitter-specific opinion lexicons by training words level classifiers using representations that exploit different sources of information: (a) the morphological information conveyed by part-of-speech (POS) tags, (b) associations between words and the sentiment expressed in the tweets that contain them, and (c) distributional representations calculated from unlabelled tweets. Experimental results show that the induced lexicons produce significant improvements over existing manually annotated lexicons for tweet-level polarity classification. In the second part of the thesis, we develop distant supervision methods for generating synthetic training data for Twitter polarity classification by exploiting unlabelled tweets and prior lexical knowledge. Positive and negative training instances are generated by averaging unlabelled tweets annotated according to a given polarity lexicon. We study different mechanisms for selecting the candidate tweets to be averaged. Our experimental results show that the training data generated by the proposed models produce classifiers that perform significantly better than classifiers trained from tweets annotated with emoticons, a popular distant supervision approach for Twitter sentiment analysis.
Contingency Filtering Techniques for Preventive Security-Constrained Optimal Power Flow

This paper focuses on contingency filtering to accelerate the iterative solution of preventive security-constrained optimal power flow (PSCOPF) problems. To this end, we propose two novel filtering techniques relying on the comparison at an intermediate PSCOPF solution of post-contingency constraint violations among postulated contingencies. We assess these techniques by comparing them with severity index-based filtering schemes, on a 60-and a 118-bus system. Our results show that the proposed contingency filtering techniques lead to faster solution of the PSCOPF, while being more robust and meaningful, than severity-index based ones.
Storage-Latency Trade-Off in Cache-Aided Fog Radio Access Networks

A fog radio access network (F-RAN) is studied, in which $K_T$ edge nodes (ENs) connected to a cloud server via orthogonal fronthaul links, serve $K_R$ users through a wireless Gaussian interference channel. Both the ENs and the users have finite-capacity cache memories, which are filled before the user demands are revealed. While a centralized placement phase is used for the ENs, which model static base stations, a decentralized placement is leveraged for the mobile users. An achievable transmission scheme is presented, which employs a combination of interference alignment, zero-forcing and interference cancellation techniques in the delivery phase, and the \textit{normalized delivery time} (NDT), which captures the worst-case latency, is analyzed.
1 Applications of Intelligent Agents

1.1  Intelligent agents are a new paradigm for developing software applications. More than this, agent-based computing has been hailed as 'the next significant breakthrough in software development' (Sargent, 1992), and 'the new revolution in software' (Ovum, 1994). Currently, agents are the focus of intense interest on the part of many sub-fields of computer science and artificial intelligence. Agents are being used in an increasingly wide variety of applications, ranging from comparatively small systems such as email filters to large, open, complex, mission critical systems such as air traffic control. At first sight, it may appear that such extremely different types of system can have little in common. And yet this is not the case: in both, the key abstraction used is that of an agent. Our aim in this article is to help the reader to understand why agent technology is seen as a fundamentally important new tool for building such a wide array of systems. More precisely, our aims are five-fold: • to introduce the reader to the concept of an agent and agent-based systems, • to help the reader to recognize the domain characteristics that indicate the appropriateness of an agent-based solution, • to introduce the main application areas in which agent technology has been successfully deployed to date, • to identify the main obstacles that lie in the way of the agent system developer, and finally • to provide a guide to the remainder of this book. We begin, in this section, by introducing some basic concepts (such as, perhaps most importantly, the notion of an agent). In Section 1.2, we give some general guidelines on the types of domain for which agent technology is appropriate. In Section 1.3, we survey the key application domains for intelligent agents. In Section 1.4, we discuss some issues in agent system development, and finally, in Section 1.5, we outline the structure of this book. Before we can discuss the development of agent-based systems in detail, we have to describe what we mean by such terms as 'agent' and 'agent-based system'. Unfortunately, we immediately run into difficulties, as some key concepts in agent-based computing lack universally accepted definitions. In particular, there is no real agreement even on the core question of exactly what an agent is (see Franklin and Graesser (1996) for a discussion). However, we believe that most researchers
Experiments in adjustable autonomy

Human-robotinteractionis becominganincreasinglyimportant researcharea. In this paper , we presentour work on designinga human-robotsystemwith adjustableautonomy anddescribenotonly theprototypeinterfacebut alsothecorrespondingrobot behaviors. In our approach,we grant the humanmeta-level control over the level of robot autonomy, but we allow the robot a varying amountof self-direction with eachlevel. Within this framework of adjustableautonomy, we explore appropriateinterfaceconceptsfor controlling multiple robotsfrom multiple platforms.
5G service requirements and operational use cases: Analysis and METIS II vision

One of the objectives of METIS-II project is to facilitate discussion on scenarios, use cases, KPIs and requirements for 5G, building upon the comprehensive work conducted in the METIS-I project and taking the work of other European projects as well as other bodies such as ITU-R, NGMN, etc. into account. This paper analyses the landscape of 5G use cases and presents METIS-II 5G use cases that cover the main 5G services, have stringent requirements and whose technical solutions are expected to serve other similar use cases as well. It also links these use cases to the business cases defined by 5G PPP so that requirements of vertical industries can be taken into account when designing the 5G Radio Access Network (RAN).
Insect chemical communication: Pheromones and exocrine glands of ants

Chemical communication plays a very important role in the lives of many social insects. Several different types of pheromones (species-specific chemical messengers) of ants have been described, particularly those involved in recruitment, recognition, territorial and alarm behaviours. Properties of pheromones include activity in minute quantities (thus requiring sensitive methods for chemical analysis) and specificity (which can have chemotaxonomic uses). Ants produce pheromones in various exocrine glands, such as the Dufour, poison, pygidial and mandibular glands. A wide range of substances have been identified from these glands.