nils-herrmann/clean_scirepeval huggingface dataset:
Graph Coloring for class scheduling

The class scheduling problem can be modeled by a graph where the vertices and edges represent the courses and the common students, respectively. The problem is to assign the courses a given number of time slots (colors), where each time slot can be used for a given number of class rooms. The Vertex Coloring (VC) algorithm is a polynomial time algorithm which produces a conflict free solution using the least number of colors . However, the VC solution may not be implementable because it uses a number of time slots that exceed the available ones with unbalanced use of class rooms. We propose a heuristic approach VC* to (1) promote uniform distribution of courses over the colors and to (2) balance course load for each time slot over the available class rooms. The performance function represents the percentage of students in all courses that could not be mapped to time slots or to class rooms. A randomized simulation of registration of four departments with up to 1200 students is used to evaluate the performance of proposed heuristic.
Approaches for creating computer-interpretable guidelines that facilitate decision support

During the last decade, studies have shown the benefits of using clinical guidelines in the practice of medicine. Although the importance of these guidelines is widely recognized, health care organizations typically pay more attention to guideline development than to guideline implementation for routine use in daily care. However, studies have shown that clinicians are often not familiar with written guidelines and do not apply them appropriately during the actual care process. Implementing guidelines in computer-based decision support systems promises to improve the acceptance and application of guidelines in daily practice because the actions and observations of health care workers are monitored and advice is generated whenever a guideline is not followed. Such implementations are increasingly applied in diverse areas such as policy development, utilization management, education, clinical trials, and workflow facilitation. Many parties are developing computer-based guidelines as well as decision support systems that incorporate these guidelines. This paper reviews generic approaches for developing and implementing computer-based guidelines that facilitate decision support. It addresses guideline representation, acquisition, verification and execution aspects. The paper describes five approaches (the Arden Syntax, GuideLine Interchange Format (GLIF), PROforma, Asbru and EON), after the approaches are compared and discussed.
Enabling smart cities through a cognitive management framework for the internet of things

The Internet of Things (IoT) is expected to substantially support sustainable development of future smart cities. This article identifies the main issues that may prevent IoT from playing this crucial role, such as the heterogeneity among connected objects and the unreliable nature of associated services. To solve these issues, a cognitive management framework for IoT is proposed, in which dynamically changing real-world objects are represented in a virtualized environment, and where cognition and proximity are used to select the most relevant objects for the purpose of an application in an intelligent and autonomic way. Part of the framework is instantiated in terms of building blocks and demonstrated through a smart city scenario that horizontally spans several application domains. This preliminary proof of concept reveals the high potential that self-reconfigurable IoT can achieve in the context of smart cities.
Compile-time dynamic voltage scaling settings: opportunities and limits

With power-related concerns becoming dominant aspects of hardware and software design, significant research effort has been devoted towards system power minimization. Among run-time power-management techniques, dynamic voltage scaling (DVS) has emerged as an important approach, with the ability to provide significant power savings. DVS exploits the ability to control the power consumption by varying a processor's supply voltage (V) and clock frequency (f). DVS controls energy by scheduling different parts of the computation to different (V, f) pairs; the goal is to minimize energy while meeting performance needs. Although processors like the Intel XScale and Transmeta Crusoe allow software DVS control, such control has thus far largely been used at the process/task level under operating system control. This is mainly because the energy and time overhead for switching DVS modes is considered too large and difficult to manage within a single program.In this paper we explore the opportunities and limits of compile-time DVS scheduling. We derive an analytical model for the maximum energy savings that can be obtained using DVS given a few known program and processor parameters. We use this model to determine scenarios where energy consumption benefits from compile-time DVS and those where there is no benefit. The model helps us extrapolate the benefits of compile-time DVS into the future as processor parameters change. We then examine how much of these predicted benefits can actually be achieved through optimal settings of DVS modes. This is done by extending the existing Mixed-integer Linear Program (MILP) formulation for this problem by accurately accounting for DVS energy switching overhead, by providing finer-grained control on settings and by considering multiple data categories in the optimization. Overall, this research provides a comprehensive view of compile-time DVS management, providing both practical techniques for its immediate deployment as well theoretical bounds for use into the future.
Mining closed relational graphs with connectivity constraints

Relational graphs are widely used in modeling large scale networks such as biological networks and social networks. In this kind of graph, connectivity becomes critical in identifying highly associated groups and clusters. In this paper, we investigate the issues of mining closed frequent graphs with connectivity constraints in massive relational graphs where each graph has around 10K nodes and 1M edges. We adopt the concept of edge connectivity and apply the results from graph theory, to speed up the mining process. Two approaches are developed to handle different mining requests: CloseCut, a pattern-growth approach, and splat, a pattern-reduction approach. We have applied these methods in biological datasets and found the discovered patterns interesting.
A Randomized, Clinical Trial of Frozen Versus Standard Nasogastric Tube Placement

Insertion of a nasogastric tube (NGT) in an anesthetized, paralyzed, and intubated patient is difficult, and many methods have been proposed to aid in the procedure. We present a simple insertion technique. A silicone NGT was made rigid by filling it with distilled water and freezing it. Patients were randomized into either the control or the frozen group, and an NGT was inserted after intubation. A total of 100 patients (50 in each group) were included in this study. The success rate increased significantly by making the tube more rigid (control:frozen = 58%:88%; p = 0.001). There was no difference between groups in the incidence of nasal bleeding. A simple method of freezing an NGT with distilled water increased the success rate of insertion for intubated patients.
Analysis of the Energy-Response Time Tradeoff for Mobile Cloud Offloading Using Combined Metrics

Mobile offloading migrates heavy computation from mobile devices to cloud servers using one or more communication network channels. Communication interfaces vary in speed, energy consumption and degree of availability. We assume two interfaces: WiFi, which is fast with low energy demand but not always present and cellular, which is slightly slower has higher energy consumption but is present at all times. We study two different communication strategies: one that selects the best available interface for each transmitted packet and the other multiplexes data across available communication channels. Since the latter may experience interrupts in the WiFi connection packets can be delayed. We call it interrupted strategy as opposed to the uninterrupted strategy that transmits packets only over currently available networks. Two key concerns of mobile offloading are the energy use of the mobile terminal and the response time experienced by the user of the mobile device. In this context, we investigate three different metrics that express the energy-performance tradeoff, the known Energy-Response time Weighted Sum (EWRS), the Energy-Response time Product (ERP) and the Energy-Response time Weighted Product (ERWP) metric. We apply the metrics to the two different offloading strategies and find that the conclusions drawn from the analysis depend on the considered metric. In particular, while an additive metric is not normalised, which implies that the term using smaller scale is always favoured, the ERWP metric, which is new in this paper, allows to assign importance to both aspects without being misled by different scales. It combines the advantages of an additive metric and a product. The interrupted strategy can save energy especially if the focus in the tradeoff metric lies on the energy aspect. In general one can say that the uninterrupted strategy is faster, while the interrupted strategy uses less energy. A fast connection improves the response time much more than the fast repair of a failed connection. In conclusion, a short down-time of the transmission channel can mostly be tolerated.
Automated planning and creation of simulation experiments with a domain specific ontology for semiconductor manufacturing AMHS

To successfully manufacture logic and power semiconductors in existing high mix semiconductor factories, fast ramp up phases and frequent product changes are necessary. Especially for power semiconductor production, new manufacturing and automation concepts are required, e.g. regarding the use of other substrates than silicon wafers. To allow a judgment on how an existing automated material handling system (AMHS) can cope with the new challenges or which alterations are required, a material flow simulation is essential. However, the planning and creation of such simulation experiments is difficult because of the systems complexity, the large amount of boundary conditions and the effort of manually modifying and testing many different variants, partially using currently unforeseen automation concepts. In order to assist in this process, the authors suggest a method for rapidly creating valid simulation experiments using an ontology that allows for the reuse of previous experiments and system experts knowledge.
Cognition ” and path planning Localization and map building Perception Motion control Environment Path Local map Position / Map Task /

Mobile robots are increasingly used in automated industrial environments. There are also other applications like planet exploration, surveillance, landmine detection, etc. In all these applications, in order that the mobile robots perform their tasks, collision-free path planning is a prerequisite. This article provides an overview of the research progress in path planning of a mobile robot for off-line as well as on-line environments. Commonly used classic and evolutionary approaches of path planning of mobile robots have been addressed. Review shows that evolutionary optimization algorithms are computationally efficient and hence are increasingly being used in tandem with classic approaches while handling Non-deterministic Polynomial time hard (NP-hard) problems. Also, challenges involved in developing a computationally efficient path planning algorithm are addressed.
The evolution of modern plate osteosynthesis.

Plate osteosynthesis is still recognized as the treatment of choice for most articular fractures, many metaphyseal fractures, and certain diaphyseal fractures such as in the forearm. Since the 1960s, both the techniques and implants used for internal fixation with plates have evolved to provide for improved healing. Most recently, plating methods have focused on the principles of 'biological fixation'. These methods attempt to preserve the blood supply to improve the rate of fracture healing, decrease the need for bone grafting, and decrease the incidence of infection and re-fracture. The purpose of this article is to provide a brief overview of the history of plate osteosynthesis as it relates to the development of the latest minimally invasive surgical techniques.
Chapter LVIII The Design , Play , and Experience Framework

This chapter introduces a framework for the design of serious games for learning, called the design, play, and experience framework. The author argues that the great potential of serious games will not be realized without a formal design approach. To that end, the author presents and thoroughly explains the design, play, and experience framework which provides a formal approach to designing the learning, storytelling, game play, user experience, and technology components of a serious game. The author concludes by detailing how the framework provides a common language to discuss serious game design, a methodology to analyze a design, and a process to design a serious game for learning.
Analysis of eye-tracking experiments performed on a Tobii T60

Commercial eye-gaze trackers have the potential to be an important tool for quantifying the benefits of new visualization techniques. The expense of such trackers has made their use relatively infrequent in visualization studies. As such, it is difficult for researchers to compare multiple devices – obtaining several demonstration models is impractical in cost and time, and quantitative measures from real-world use are not readily available. In this paper, we present a sample protocol to determine the accuracy of a gaze-tacking device.
A High-Sensitivity and Low-Walk Error LADAR Receiver for Military Application

An integrated receiver with high sensitivity and low walk error for a military purpose pulsed time-of-flight (TOF) LADAR system is proposed. The proposed receiver adopts a dual-gain capacitive-feedback TIA (C-TIA) instead of widely used resistive-feedback TIA (R-TIA) to increase the sensitivity. In addition, a new walk-error improvement circuit based on a constant-delay detection method is proposed. Implemented in 0.35 μm CMOS technology, the receiver achieves an input-referred noise current of 1.36 pA/√Hz with bandwidth of 140 MHz and minimum detectable signal (MDS) of 10 nW with a 5 ns pulse at SNR=3.3, maximum walk-error of 2.8 ns, and a dynamic range of 1:12,000 over the operating temperature range of -40 °C to +85 °C.
RGB-D object pose estimation in unstructured environments

We present an object pose estimation approach exploiting both geometric depth and photometric color information available from an RGB-D sensor. In contrast to various efforts relying on object segmentation with a knownbackground structure, our approach does not depend on the segmentation and thus exhibits superior performance in unstructured environments. Inspired by a voting-based approach employing an oriented point pair feature, we present a voting-based approach which further incorporates color information from the RGB-D sensor and which exploits parallel power of the modern parallel computing architecture. The proposed approach is extensively evaluated with three state-of-the-art approaches on both synthetic and real datasets, and our approach outperforms the other approaches in terms of both computation time and accuracy.
Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression

Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C.
Chinese Language Processing Based on Stroke Representation and Multidimensional Representation

With the development of deep learning and artificial intelligence, deep neural networks are increasingly being applied for natural language processing tasks. However, the majority of research on natural language processing focuses on alphabetic languages. Few studies have paid attention to the characteristics of ideographic languages, such as the Chinese language. In addition, the existing Chinese processing algorithms typically regard Chinese words or Chinese characters as the basic units while ignoring the information contained within the deeper architecture of Chinese characters. In the Chinese language, each Chinese character can be split into several components, or strokes. This means that strokes are the basic units of a Chinese character, in a manner similar to the letters of an English word. Inspired by the success of character-level neural networks, we delve deeper into Chinese writing at the stroke level for Chinese language processing. We extract the basic features of strokes by considering similar Chinese characters to learn a continuous representation of Chinese characters. Furthermore, word embeddings trained at different granularities are not exactly the same. In this paper, we propose an algorithm for combining different representations of Chinese words within a single neural network to obtain a better word representation. We develop a Chinese word representation service for several natural language processing tasks, and cloud computing is introduced to deal with preprocessing challenges and the training of basic representations from different dimensions.
Systematic review of time trends in the prevalence of Helicobacter pylori infection in China and the USA.

It has been suggested that the prevalence of Helicobacter pylori infection has stabilized in the USA and is decreasing in China. We conducted a systematic literature analysis to test this hypothesis. PubMed and Embase searches were conducted up to 19 January 2015. Trends in the prevalence of H. pylori infection over time were assessed by regression analysis using Microsoft Excel. Overall, 25 Chinese studies (contributing 28 datasets) and 11 US studies (contributing 11 datasets) were included. There was a significant decrease over time in the H. pylori infection prevalence for the Chinese studies overall (p = 0.00018) and when studies were limited to those that used serum immunoglobulin G (IgG) assays to detect H. pylori infection (p = 0.014; 20 datasets). The weighted mean prevalence of H. pylori infection was 66 % for rural Chinese populations and 47 % for urban Chinese populations. There was a significant trend towards a decreasing prevalence of H. pylori infection for studies that included only urban populations (p = 0.04; 9 datasets). This trend was no longer statistically significant when these studies were further restricted to those that used serum IgG assays to detect H. pylori infection, although this may have been because of low statistical power due to the small number of datasets available for this analysis (p = 0.28; 6 datasets). There were no significant trends in terms of changes in the prevalence of H. pylori infection over time for studies conducted in the USA. In conclusion, the prevalence of H. pylori infection is most likely decreasing in China, due to a combination of increasing urbanization, which we found to be associated with lower H. pylori infection rates, and possibly also decreasing rates of H. pylori infection within urban populations. This will probably result in a gradual decrease in peptic ulcer and gastric cancer rates in China over time.
Generalized Identity Based and Broadcast Encryption Schemes

We provide a general framework for constructing identitybased and broadcast encryption systems. In particular, we construct a general encryption system called spatial encryption from which many systems with a variety of properties follow. The ciphertext size in all these systems is independent of the number of users involved and is just three group elements. Private key size grows with the complexity of the system. One application of these results gives the first broadcast HIBE system with short ciphertexts. Broadcast HIBE solves a natural problem having to do with identity-based encrypted email.
Multimodal Mixed Reality Interfaces for Visualizing Digital Heritage

We have developed several digital heritage interfaces that utilize Web3D, virtual and augmented reality technologies for visualizing digital heritage in an interactive manner through the use of several different input devices. We propose in this paper an integration of these technologies to provide a novel multimodal mixed reality interface that facilitates the implementation of more interesting digital heritage exhibitions. With such exhibitions participants can switch dynamically between virtual web-based environments to indoor augmented reality environments as well as make use of various multimodal interaction techniques to better explore heritage information in the virtual museum. The museum visitor can potentially experience their digital heritage in the physical sense in the museum, then explore further through the web, visualize this heritage in the round (3D on the web), take that 3D artifact into the augmented reality domain (the real world) and explore it further using various multimodal interfaces.
A direct link between MITF, innate immunity, and hair graying

Melanocyte stem cells (McSCs) and mouse models of hair graying serve as useful systems to uncover mechanisms involved in stem cell self-renewal and the maintenance of regenerating tissues. Interested in assessing genetic variants that influence McSC maintenance, we found previously that heterozygosity for the melanogenesis associated transcription factor, Mitf, exacerbates McSC differentiation and hair graying in mice that are predisposed for this phenotype. Based on transcriptome and molecular analyses of Mitfmi-vga9/+ mice, we report a novel role for MITF in the regulation of systemic innate immune gene expression. We also demonstrate that the viral mimic poly(I:C) is sufficient to expose genetic susceptibility to hair graying. These observations point to a critical suppressor of innate immunity, the consequences of innate immune dysregulation on pigmentation, both of which may have implications in the autoimmune, depigmenting disease, vitiligo.