nils-herrmann/clean_scirepeval huggingface dataset:
An Optimization Model for Human Activity Recognition Inspired by Information on Human-Object Interaction

Human activity categories can be mainly divided into two types: body motion (e.g. "dancing" and "jumping") and human-object interaction (e.g. "playing guitar" and "riding bike"). In this paper, we propose a model that uses this insight to combine spatiotemporal features with information on human-object interaction to predict human activity categories in realistic videos. In this paper, we (1) improve on prior work by proposing a model to provide long-term prediction based on spatiotemporal features extracted by a deep 3-dimensional convolutional network and (2) extend the spatiotemporal features by combining with information on human-object interaction generated from an object detection model. Our model achieves 92.5% accuracy on UCF101 dataset that outperforms any other state-of-the-art methods. In addition, our approach has high computing efficiency and achieves real-time processing.
Sustainability and Innovation in the Automotive Sector : A Structured Content Analysis

This study aims to analyse the scientific literature on sustainability and innovation in the automotive sector in the last 13 years. The research is classified as descriptive and exploratory. The process presented 31 articles in line with the research topic in the Scopus database. The bibliometric analysis identified the most relevant articles, authors, keywords, countries, research centers and journals for the subject from 2004 to 2016 in the Industrial Engineering domain. We concluded, through the systemic analysis, that the automotive sector is well structured on the issue of sustainability and process innovation. Innovations in the sector are of the incremental process type, due to the lower risk, lower costs and less complexity. However, the literature also points out that radical innovations are needed in order to fit the prevailing environmental standards. The selected studies show that environmental practices employed in the automotive sector are: the minimization of greenhouse gas emissions, life-cycle assessment, cleaner production, reverse logistics and eco-innovation. Thus, it displays the need for empirical studies in automotive companies on the environmental practices employed and how these practices impact innovation.
Relation path embedding in knowledge graphs

Large-scale knowledge graphs have currently reached impressive sizes; however, they are still far from complete. In addition, most existing methods for knowledge graph completion only consider the direct links between entities, ignoring the vital impact of the semantics of relation paths. In this paper, we study the problem of how to better embed entities and relations of knowledge graphs into different low-dimensional spaces by taking full advantage of the additional semantics of relation paths and propose a novel relation path embedding model named as RPE. Specifically, with the corresponding relation and path projections, RPE can simultaneously embed each entity into two types of latent spaces. Moreover, type constraints are extended from traditional relation-specific type constraints to the proposed path-specific type constraints and both of the two type constraints can be seamlessly incorporated into RPE. The proposed model is evaluated on the benchmark tasks of link prediction and triple classification. The results of experiments demonstrate our method outperforms all baselines on both tasks. They indicate that our model is capable of catching the semantics of relation paths, which is significant for knowledge representation learning.
Secure Key Distribution for the Smart Grid

To secure the network communication for the smart grid, it is important that a secure key management scheme is needed. The focus of this paper is on the secure key distribution for the smart grid. In this paper, we first overview the key management scheme recently proposed by Wu-Zhou and show it is vulnerable to the man-in-the-middle attack. Then we propose a new key distribution protocol and demonstrate it is secure and efficient for smart grid network. Applying traditional PKI to the smart grid requires significant work and maintenance of the public key. By using Kerberos to smart grid may lose authentication from the third party due to power outages. Therefore, we propose a scheme for a smart grid using a trusted third party which not only has no issue on key revocation, but also the third party can be easily duplicated in case power outages occur.
Arsenic removal from water/wastewater using adsorbents--A critical review.

Arsenic's history in science, medicine and technology has been overshadowed by its notoriety as a poison in homicides. Arsenic is viewed as being synonymous with toxicity. Dangerous arsenic concentrations in natural waters is now a worldwide problem and often referred to as a 20th-21st century calamity. High arsenic concentrations have been reported recently from the USA, China, Chile, Bangladesh, Taiwan, Mexico, Argentina, Poland, Canada, Hungary, Japan and India. Among 21 countries in different parts of the world affected by groundwater arsenic contamination, the largest population at risk is in Bangladesh followed by West Bengal in India. Existing overviews of arsenic removal include technologies that have traditionally been used (oxidation, precipitation/coagulation/membrane separation) with far less attention paid to adsorption. No previous review is available where readers can get an overview of the sorption capacities of both available and developed sorbents used for arsenic remediation together with the traditional remediation methods. We have incorporated most of the valuable available literature on arsenic remediation by adsorption ( approximately 600 references). Existing purification methods for drinking water; wastewater; industrial effluents, and technological solutions for arsenic have been listed. Arsenic sorption by commercially available carbons and other low-cost adsorbents are surveyed and critically reviewed and their sorption efficiencies are compared. Arsenic adsorption behavior in presence of other impurities has been discussed. Some commercially available adsorbents are also surveyed. An extensive table summarizes the sorption capacities of various adsorbents. Some low-cost adsorbents are superior including treated slags, carbons developed from agricultural waste (char carbons and coconut husk carbons), biosorbents (immobilized biomass, orange juice residue), goethite and some commercial adsorbents, which include resins, gels, silica, treated silica tested for arsenic removal come out to be superior. Immobilized biomass adsorbents offered outstanding performances. Desorption of arsenic followed by regeneration of sorbents has been discussed. Strong acids and bases seem to be the best desorbing agents to produce arsenic concentrates. Arsenic concentrate treatment and disposal obtained is briefly addressed. This issue is very important but much less discussed.
Pseudoangiomatous Stromal Hyperplasia of the Breast: Mammosonography and Elastography Findings with a Histopathological Correlation.

Pseudoangiomatous stromal hyperplasia (PASH) is a rare benign mesenchymal proliferative lesion of the breast. In this study, we aimed to show a case of PASH with mammographic and sonographic features, which fulfill the criteria for benign lesions and to define its recently discovered elastography findings. A 49-year-old premenopausal female presented with breast pain in our outpatient surgery clinic. In ultrasound images, a hypoechoic solid mass located at the 3 o'clock position in the periareolar region of the right breast was observed. Due to it was not detected on earlier mammographies, the patient underwent a tru-cut biopsy, although the mass fulfilled the criteria for benign lesions on mammography, ultrasound, and elastography. Elastography is a new technique differentiating between benign and malignant lesions. It is also useful to determine whether a biopsy is necessary or follow-up is sufficient.
Fat tree encoder design for ultra-high speed flash A/D converters

The thermometer code-to-binary code encoder has become the bottleneck of the ultra-high speed flash ADCs. In this paper, the authors presented the fat tree thermometer codeto-binary code encoder that is highly suitable for the ultrahigh speed flash ADCs. The simulation and the implementation results show that the fat tree encoder outperforms the commonly used ROM encoder in terms of speed and power for the 6 bit CMOS flash ADC case. The speed is improved by almost a factor of 2 when using the fat tree encoder, which in fact demonstrates the fat tree encoder is an effective solution for the bottleneck problem in ultra-high speed ADCs.
Implementing a Dynamic Scaling of Web Applications in a Virtualized Cloud Computing Environment

Aljebreen, Mohammed, "Implementing a dynamic scaling of web applications in a virtualized cloud computing environment" (2013).  Cloud computing is becoming more essential day by day. The allure of the cloud is the significant value and benefits that people gain from it, such as reduced costs, increased storage, flexibility, and more mobility. Flexibility is one of the major benefits that cloud computing can provide in terms of scaling up and down the infrastructure of a network. Once traffic has increased on one server within the network, a load balancer instance will route incoming requests to a healthy instance, which is less busy and less burdened. When the full complement of instances cannot handle any more requests, past research has been done by Chieu et. al. that presented a scaling algorithm to address a dynamic scalability of web applications on a virtualized cloud computing environment based on relevant indicators that can increase or decrease servers, as needed. In this project, I implemented the proposed algorithm, but based on CPU Utilization threshold. In addition, two tests were run exploring the capabilities of different metrics when faced with ideal or challenging conditions. The results did find a superior metric that was able to perform successfully under both tests. 3 Dedication I lovingly dedicate this thesis to my gracious and devoted mother for her unwavering love and for always believing in me. 4 Acknowledgments This thesis would not have been possible without the support of many people. My wish is to express humble gratitude to the committee chair, Prof. Sharon Mason, who was perpetually generous in offering her invaluable assistance, support, and guidance. Deepest gratitude is also due to the members of my supervisory committee, Prof. Lawrence Hill and Prof. Jim Leone, without whose knowledge and direction this study would not have been successful. Special thanks also to Prof. Charles Border for his financial support of this thesis and priceless assistance. Profound gratitude to my mother, Moneerah, who has been there from the very beginning, for her support and endless love. I would also like to convey thanks to my wife for her patient and unending encouragement and support throughout the duration of my studies; without my wife's encouragement, I would not have completed this degree. I wish to express my gratitude to my beloved sister and brothers for their kind understanding throughout my studies. Special thanks to my friend, Mohammed Almathami, for his …
Effects of Aromatherapy on the Anxiety, Vital Signs, and Sleep Quality of Percutaneous Coronary Intervention Patients in Intensive Care Units

The purpose of this study was to investigate the effects of aromatherapy on the anxiety, sleep, and blood pressure (BP) of percutaneous coronary intervention (PCI) patients in an intensive care unit (ICU). Fifty-six patients with PCI in ICU were evenly allocated to either the aromatherapy or conventional nursing care. Aromatherapy essential oils were blended with lavender, roman chamomile, and neroli with a 6 : 2 : 0.5 ratio. Participants received 10 times treatment before PCI, and the same essential oils were inhaled another 10 times after PCI. Outcome measures patients' state anxiety, sleeping quality, and BP. An aromatherapy group showed significantly low anxiety (t = 5.99, P < .001) and improving sleep quality (t = -3.65, P = .001) compared with conventional nursing intervention. The systolic BP of both groups did not show a significant difference by time or in a group-by-time interaction; however, a significant difference was observed between groups (F = 4.63, P = .036). The diastolic BP did not show any significant difference by time or by a group-by-time interaction; however, a significant difference was observed between groups (F = 6.93, P = .011). In conclusion, the aromatherapy effectively reduced the anxiety levels and increased the sleep quality of PCI patients admitted to the ICU. Aromatherapy may be used as an independent nursing intervention for reducing the anxiety levels and improving the sleep quality of PCI patients.
Memory enhancement for emotional words: are emotional words more vividly remembered than neutral words?

Individuals are more likely to remember negative information than neutral information. In the experiments reported here, we examined whether individuals were also more likely to remember details of the presentation of negative words, as compared with neutral words. In Experiment 1, the remember-know procedure was used to examine the effect of emotion on the vividness of an individual's memory, showing that remember responses were more frequently assigned to negative words than neutral words. In Experiment 2, a source memory paradigm was used, and again, evidence that individuals' memories were more detailed for negative than for neutral words was found. In Experiments 3-6, we examined the relative contribution of valence and arousal, finding that both dimensions increased the vividness of remembered information (i.e., items with valence only and those that elicited arousal were better remembered than neutral information) but that the effect was greater for words that evoked arousal than for those with valence only. The results support a qualitative, as well as a quantitative, memory benefit for emotional, as compared with neutral, words.
Design and Implementation of Broadband MEMS RHCP/LHCP Reconfigurable Arrays Using Rotated E-Shaped Patch Elements

A novel broadband RHCP/LHCP reconfigurable patch antenna array using an E-shaped patch antenna element is investigated. By applying particle swarm optimization (PSO), a challenging, combined S11-AR bandwidth of 17% was achieved and verified through measurement for the isolated element using MEMS switches at an overall substrate thickness of 0.092λ0. The achieved bandwidth is significantly higher than the current state-of-the-art in single-layer, single-feed circularly polarized (CP) patch element designs with similar substrate thickness. A small percentage of the upper frequency band experiences a pronounced beam squint similar to other thick substrate CP patch antennas. To overcome the beam squint, a novel rotated-element configuration is implemented to force pattern symmetry. Derivations of pattern symmetry and network effects are also shown. The final design prototype using rotated elements provides a measured 20% S11-AR bandwidth with good radiation pattern stability.
Agile Software Process and Its Experience

Agile processes focus on facilitating early and fast production of working code, and are based on software development process models that support iterative, incremental development of software. Although agile methods have existed for a number of years now, answers to questions concerning the suitability of agile processes to particular software development environments are still often based on anecdotal accounts of experiences. An appreciation of the (often unstated) assumptions underlying agile processes can lead to a better understanding of the applicability of agile processes to particular situations. Agile processes are less likely to be applicable in situations in which core assumptions do not hold. This paper examines the principles and advocated practices of agile processes to identify underlying assumptions. The paper also identifies limitations that may arise from these assumptions and outlines how the limitations can be addresses by incorporating other software development techniques and practices into agile development environments.
"Thanks for sharing" - Identifying users' roles based on knowledge contribution in Enterprise Social Networks

While ever more companies use Enterprise Social Networks for knowledge management, there is still a lack of understanding of users’ knowledge exchanging behavior. In this context, it is important to be able to identify and characterize users who contribute and communicate their knowledge in the network and help others to get their work done. In this paper, we propose a new methodological approach consisting of three steps, namely ―message classification‖, ―identification of users’ roles‖ as well as ―characterization of users’ roles‖. We apply the approach to a dataset from a multinational consulting company, which allows us to identify three user roles based on their knowledge contribution in messages: givers, takers, and matchers. Going beyond this categorization, our data shows that whereas the majority of messages aims to share knowledge, matchers, that means people that give and take, are a central element of the network. In conclusion, the development and application of a new methodological approach allows us to contribute to a more refined understanding of users’ knowledge exchanging behavior in Enterprise Social Networks which can ultimately help companies to take measures to improve their knowledge management.
BATS : The Blind Audio Tactile Mapping System

The BATS project focuses on helping students with visual impairments access and explore spatial information using standard computer hardware and open source software. Our work is largely based on prior techniques used in presenting maps to the blind such as text-to-speech synthesis, auditory icons, and tactile feedback. We add spatial sound to position auditory icons and speech callouts in three dimensions, and use consumer-grade haptic feedback devices to provide additional map information through tactile vibrations and textures. Two prototypes have been developed for use in educational settings and have undergone minimal assessment. A system for public release and plans for more rigorous evaluation are in development.
Learning Robust Bed Making using Deep Imitation Learning with DART

Bed-making is a universal home task that can be challenging for senior citizens due to reaching motions. Automating bed-making has multiple technical challenges such as perception in an unstructured environments, deformable object manipulation, obstacle avoidance and sequential decision making. We explore how DART, an LfD algorithm for learning robust policies, can be applied to automating bed making without fiducial markers with a Toyota Human Support Robot (HSR). By gathering human demonstrations for grasping the sheet and failure detection, we can learn deep neural network policies that leverage pre-trained YOLO features to automate the task. Experiments with a scale bed and distractors placed on the bed, suggest policies learned on 50 demonstrations with DART achieve 96% sheet coverage, which is over 200% better than a corner detector baseline using contour detection.
Mechanisms of vascular hyporesponsiveness in septic shock.

To define some of the most common characteristics of vascular hyporesponsiveness to catecholamines during septic shock and outline current therapeutic approaches and future perspectives.



Source data were obtained from a PubMed search of the medical literature with the following MeSH terms: Muscle, smooth, vascular/physiopathology; hypotension/etiology; shock/physiopathology; vasodilation/physiology; shock/therapy; vasoconstrictor agents.



NO and peroxynitrite are mainly responsible for vasoplegia and vascular hyporeactivity while COX 2 enzyme is responsible for the increase in PGI2, which also contributes to hyporeactivity. Moreover, K+ATP and BKCa channels are over-activated during septic shock and participate in hypotension. Finally, other mechanisms are involved in vascular hyporesponsiveness such as critical illness-related corticosteroid insufficiency, vasopressin depletion, dysfunction and desensitization of adrenoreceptors as well as inactivation of catecholamines by oxidation.



In animal models, several therapeutic approaches, targeted on one particular compound have proven their efficacy in preventing or reversing vascular hyporesponsiveness to catecholamines. Unfortunately, none have been successfully tested in clinical trials. Nevertheless, very high doses of catecholamines ( > 5 μg/kg/min), hydrocortisone, terlipressin or vasopressin could represent an alternative for the treatment of refractory septic shock.
Design of a Novel Portable ECG Monitor for Heart Health

Using the ECG analog front-end and ARM Cortex-M3 processor to develop a portable ECG monitor. The STM32 as the core unit, the ADS1292 as the acquisition analog front-end, it also includes a touch screen display module, an SD card storage module and a voltage conversion module. Automatic ECG analysis algorithms including QRS complex detection, QRS width detection and ST segment detection. ECG can be divided into four kinds of heart beat and eight kinds of arrhythmia rhythm using the extracted ECG parameters. The results have been evaluated on the MIT-BIH Arrhythmia Database, the sensitivity of QRS complex detection was 99% and the sensitivity of heart beat classification was above 95%. The monitor can display the real-time ECG waveform and the current heart rate, to make recommendations for the subjects, and it stored the abnormal ECG waveform that provided to physicians for further analysis and diagnosis. Ultimately the monitor gives a composite score based on heart rate, arrhythmia and ST segment to facilitate subjects for heart health.
Interactive Urban Synthesis: Computational Methods for Fast Prototyping of Urban Design Proposals

In this paper, we present a method for generating fast conceptual urban design prototypes. We synthesize spatial configurations for street networks, parcels and building volumes. Therefore, we address the problem of implementing custom data structures for these configurations and how the generation process can be controlled and parameterized. We exemplify our method by the development of new components for Grasshopper/Rhino3D and their application in the scope of selected case studies. By means of these components, we show use case applications of the synthesis algorithms. In the conclusion, we reflect on the advantages of being able to generate fast urban design prototypes, but we also discuss the disadvantages of the concept and the usage of Grasshopper as a user interface.
Redundancy on Demand—Extending the Coverage Area of Terrestrial Broadcast via Broadband Networks

Nowadays more and more TV terminal devices for digital terrestrial broadcast are also equipped with broadband network interfaces. In view of this fact, we developed a novel redundancy on demand (RoD) system to improve the reception of terrestrial broadcast signals with the help of additional redundancy data transmitted via broadband networks. We propose various forms of redundancy, which can be provided on request by the receiving terminal in case of reception errors. RoD does not require any changes of the current broadcast network structure and is compatible with conventional receivers. Simulation results show that a small portion of additional redundancy data provided by the broadband network leads to significant performance improvements of the reception, making high data rate broadcasting feasible in a realistic environment. RoD introduces a new degree of freedom for network planning helping to reduce transmission cost and network energy consumption.