nils-herrmann/clean_scirepeval huggingface dataset:
Heart rate variability and functional outcome in ischemic stroke: a multiparameter approach.

Heart rate variability (HRV) as a measure of autonomic function might provide prognostic information in ischemic stroke. However, numerous difficulties are associated with HRV parameters assessment and interpretation, especially in short-term ECG recordings. For better understanding of derived HRV data and to avoid methodological bias we simultaneously recorded and analyzed heart rate, blood pressure and respiratory rate.



Seventy-five ischemic stroke patients underwent short-term ECG recordings. Linear and nonlinear parameters of HRV as well as beat-to-beat blood pressure and respiratory rate were assessed and compared in patients with different functional neurological outcomes at 7th and 90th days.



Values of Approximate, Sample and Fuzzy Entropy were significantly lower in patients with poor early neurological outcome. Patients with poor 90-day outcome had higher percentage of high frequency spectrum and normalized high frequency power, lower normalized low frequency power and lower low frequency/high frequency ratio. Low frequency/high frequency ratio correlated negatively with scores in the National Institutes of Health Stroke Scale and modified Rankin Scale (mRS) at the 7th and mRS at the 90th days. Mean RR interval, values of blood pressure as well as blood pressure variability did not differ between groups with good and poor outcomes. Respiratory frequency was significantly correlated with the functional neurological outcome at 7th and 90th days.



While HRV assessed by linear methods seems to have long-term prognostic value, complexity measures of HRV reflect the impact of the neurological state on distinct, temporary properties of heart rate dynamic. Respiratory rate during the first days of the stroke is associated with early and long-term neurological outcome and should be further investigated as a potential risk factor.
Meshworm: A Peristaltic Soft Robot With Antagonistic Nickel Titanium Coil Actuators

This paper presents the complete development and analysis of a soft robotic platform that exhibits peristaltic locomotion. The design principle is based on the antagonistic arrangement of circular and longitudinal muscle groups of Oligochaetes. Sequential antagonistic motion is achieved in a flexible braided mesh-tube structure using a nickel titanium (NiTi) coil actuators wrapped in a spiral pattern around the circumference. An enhanced theoretical model of the NiTi coil spring describes the combination of martensite deformation and spring elasticity as a function of geometry. A numerical model of the mesh structures reveals how peristaltic actuation induces robust locomotion and details the deformation by the contraction of circumferential NiTi actuators. Several peristaltic locomotion modes are modeled, tested, and compared on the basis of speed. Utilizing additional NiTi coils placed longitudinally, steering capabilities are incorporated. Proprioceptive potentiometers sense segment contraction, which enables the development of closed-loop controllers. Several appropriate control algorithms are designed and experimentally compared based on locomotion speed and energy consumption. The entire mechanical structure is made of flexible mesh materials and can withstand significant external impact during operation. This approach allows a completely soft robotic platform by employing a flexible control unit and energy sources.
SLC19: the folate/thiamine transporter family

The SLC19 gene family of solute carriers is a family of three transporter proteins with significant structural similarity, transporting, however, substrates with different structure and ionic charge. The three members of this gene family are expressed ubiquitously and mediate the transport of two important water-soluble vitamins, folate and thiamine. The concentrative transport of substrates mediated by the members of this gene family is energized by transcellular H+/OH− gradient. SLC19A1 is expressed at highest levels in absorptive cells where it is located in a polarized manner either in the apical or basal membrane, depending on the cell type. It mediates the transport of reduced folate and its analogs, such as methotrexate, which are anionic at physiological pH. SLC19A2 is expressed ubiquitously and mediates the transport of thiamine, a cation at physiological pH. SLC19A3 is also widely expressed and is capable of transporting thiamine. This review summarizes the current knowledge on the structural, functional, molecular and physiological aspects of the SLC19 gene family.
Landmarking Manifolds with Gaussian Processes

We present an algorithm for finding landmarks along a manifold. These landmarks provide a small set of locations spaced out along the manifold such that they capture the low-dimensional nonlinear structure of the data embedded in the high-dimensional space. The approach does not select points directly from the dataset, but instead we optimize each landmark by moving along the continuous manifold space (as approximated by the data) according to the gradient of an objective function. We borrow ideas from active learning with Gaussian processes to define the objective, which has the property that a new landmark is “repelled” by those currently selected, allowing for exploration of the manifold. We derive a stochastic algorithm for learning with large datasets and show results on several datasets, including the Million Song Dataset and articles from the New York Times.
Body weight-supported bedside treadmill training facilitates ambulation in ICU patients: An interventional proof of concept study.

Early mobilisation is advocated to improve recovery of intensive care unit (ICU) survivors. However, severe weakness in combination with tubes, lines and machinery are practical barriers for the implementation of ambulation with critically ill patients. The aim of this study was to explore the feasibility of Body Weight-Supported Treadmill Training (BWSTT) in critically ill patients in the ICU.



A custom build bedside Body Weight-Supported Treadmill was used and evaluated in medical and surgical patients in the ICU. Feasibility was evaluated according to eligibility, successful number of BWSTT, number of staff needed, adverse events, number of patients that could not have walked without BWSTT, patient satisfaction and anxiety.



Twenty participants, underwent 54 sessions BWSTT. Two staff members executed the BWSTT and no adverse events occurred. Medical equipment did not have to be disconnected during all treatment sessions. In 74% of the sessions, the participants would not have been able to walk without the BWSTT. Patient satisfaction with BWSTT was high and anxiety low.



This proof of concept study demonstrated that BWSTT is safe, reduces staff resource, and facilitates the first time to ambulation in critically ill patients with severe muscle weakness in the ICU.
Multi-view Self-Paced Learning for Clustering

Exploiting the information from multiple views can improve clustering accuracy. However, most existing multi-view clustering algorithms are nonconvex and are thus prone to becoming stuck into bad local minima, especially when there are outliers and missing data. To overcome this problem, we present a new multi-view self-paced learning (MSPL) algorithm for clustering, that learns the multi-view model by not only progressing from ‘easy’ to ‘complex’ examples, but also from ‘easy’ to ‘complex’ views. Instead of binarily separating the examples or views into ‘easy’ and ‘complex’, we design a novel probabilistic smoothed weighting scheme. Employing multiple views for clustering and defining complexity across both examples and views are shown theoretically to be beneficial to optimal clustering. Experimental results on toy and real-world data demonstrate the efficacy of the proposed algorithm.
Natural Neural Networks

We introduce Natural Neural Networks, a novel family of algorithms that speed up convergence by adapting their internal representation during training to improve conditioning of the Fisher matrix. In particular, we show a specific example that employs a simple and efficient reparametrization of the neural network weights by implicitly whitening the representation obtained at each layer, while preserving the feed-forward computation of the network. Such networks can be trained efficiently via the proposed Projected Natural Gradient Descent algorithm (PRONG), which amortizes the cost of these reparametrizations over many parameter updates and is closely related to the Mirror Descent online learning algorithm. We highlight the benefits of our method on both unsupervised and supervised learning tasks, and showcase its scalability by training on the large-scale ImageNet Challenge dataset.
Architecture of field-programmable gate arrays

A survey of Field-Programmable Gate Array (FPGA) architectures and the programming technologies used to customize them is presented. Programming technologies are compared on the basis of their vola fility, size, parasitic capacitance, resistance, and process technology complexity. FPGA architectures are divided into two constituents: logic block architectures and routing architectures. A classijcation of logic blocks based on their granularity is proposed and several logic blocks used in commercially available FPGA ’s are described. A brief review of recent results on the effect of logic block granularity on logic density and pe$ormance of an FPGA is then presented. Several commercial routing architectures are described in the contest of a general routing architecture model. Finally, recent results on the tradeoff between the fleibility of an FPGA routing architecture its routability and density are reviewed.
Recurrent conditional random field for language understanding

Recurrent neural networks (RNNs) have recently produced record setting performance in language modeling and word-labeling tasks. In the word-labeling task, the RNN is used analogously to the more traditional conditional random field (CRF) to assign a label to each word in an input sequence, and has been shown to significantly outperform CRFs. In contrast to CRFs, RNNs operate in an online fashion to assign labels as soon as a word is seen, rather than after seeing the whole word sequence. In this paper, we show that the performance of an RNN tagger can be significantly improved by incorporating elements of the CRF model; specifically, the explicit modeling of output-label dependencies with transition features, its global sequence-level objective function, and offline decoding. We term the resulting model a “recurrent conditional random field” and demonstrate its effectiveness on the ATIS travel domain dataset and a variety of web-search language understanding datasets.
Persuasive Systems Design: Key Issues, Process Model, and System Features

A growing number of information technology systems and services are being developed to change users’ attitudes or behavior or both. Despite the fact that attitudinal theories from social psychology have been quite extensively applied to the study of user intentions and behavior, these theories have been developed for predicting user acceptance of the information technology rather than for providing systematic analysis and design methods for developing persuasive software solutions. This article is conceptual and theory-creating by its nature, suggesting a framework for Persuasive Systems Design (PSD). It discusses the process of designing and evaluating persuasive systems and describes what kind of content and software functionality may be found in the final product. It also highlights seven underlying postulates behind persuasive systems and ways to analyze the persuasion context (the intent, the event, and the strategy). The article further lists 28 design principles for persuasive system content and functionality, describing example software requirements and implementations. Some of the design principles are novel. Moreover, a new categorization of these principles is proposed, consisting of the primary task, dialogue, system credibility, and social support categories.
The Hospitals / Residents Problem ( 1962 ; Gale , Shapley )

An instance I of the Hospitals / Residents problem (HR) [6, 7, 15] involves a set R = {r1, . . . , rn} of residents and a set H = {h1, . . . , hm} of hospitals. Each hospital hj ∈ H has a positive integral capacity, denoted by cj . Also, each resident ri ∈ R has a preference list in which he ranks in strict order a subset of H. A pair (ri, hj) ∈ R ×H is said to be acceptable if hj appears in ri’s preference list; in this case ri is said to find hj acceptable. Similarly each hospital hj ∈ H has a preference list in which it ranks in strict order those residents who find hj acceptable. Given any three agents x, y, z ∈ R ∪ H, x is said to prefer y to z if x finds each of y and z acceptable, and y precedes z on x’s preference list. Let C = ∑ hj∈H cj . Let A denote the set of acceptable pairs in I, and let L = |A|. An assignment M is a subset of A. If (ri, hj) ∈ M , ri is said to be assigned to hj , and hj is assigned ri. For each q ∈ R ∪ H, the set of assignees of q in M is denoted by M(q). If ri ∈ R and M(ri) = ∅, ri is said to be unassigned, otherwise ri is assigned. Similarly, any hospital hj ∈ H is under-subscribed, full or over-subscribed according as |M(hj)| is less than, equal to, or greater than cj , respectively. A matching M is an assignment such that |M(ri)| ≤ 1 for each ri ∈ R and |M(hj)| ≤ cj for each hj ∈ H (i.e., no resident is assigned to an unacceptable hospital, each resident is assigned to at most one hospital, and no hospital is over-subscribed). For notational convenience, given a matching M and a resident ri ∈ R such that M(ri) 6= ∅, where there is no ambiguity the notation M(ri) is also used to refer to the single member of M(ri). A pair (ri, hj) ∈ A\M blocks a matching M , or is a blocking pair for M , if the following conditions are satisfied relative to M :
Caring for agents and agents that care: building empathic relations with synthetic agents

When building agents and synthetic characters, and in order to achieve believability, we must consider the emotional relations established between users and characters, that is, we must consider the issue of "empathy". Defined in broad terms as "An observer reacting emotionally because he perceives that another is experiencing or about to experience an emotion", empathy is an important element to consider in the creation of relations between humans and agents. In this paper we will focus on the role of empathy in the construction of synthetic characters, providing some requirements for such construction and illustrating the presented concepts with a specific system called FearNot!. FearNot! was developed to address the difficult and often devastating problem of bullying in schools. By using role playing and empathic synthetic characters in a 3D environment, FearNot! allows children from 8 to 12 to experience a virtual scenario where they can witness (in a third-person perspective) bullying situations. To build empathy into FearNot! we have considered the following components: agentýs architecture; the charactersý embodiment and emotional expression; proximity with the user and emotionally charged situations.We will describe how these were implemented in FearNot! and report on the preliminary results we have with it.
A Secure Mechanism for Big Data Collection in Large Scale Internet of Vehicle

As an extension for Internet of Things (IoT), Internet of Vehicles (IoV) achieves unified management in smart transportation area. With the development of IoV, an increasing number of vehicles are connected to the network. Large scale IoV collects data from different places and various attributes, which conform with heterogeneous nature of big data in size, volume, and dimensionality. Big data collection between vehicle and application platform becomes more and more frequent through various communication technologies, which causes evolving security attack. However, the existing protocols in IoT cannot be directly applied in big data collection in large scale IoV. The dynamic network structure and growing amount of vehicle nodes increases the complexity and necessary of the secure mechanism. In this paper, a secure mechanism for big data collection in large scale IoV is proposed for improved security performance and efficiency. To begin with, vehicles need to register in the big data center to connect into the network. Afterward, vehicles associate with big data center via mutual authentication and single sign-on algorithm. Two different secure protocols are proposed for business data and confidential data collection. The collected big data is stored securely using distributed storage. The discussion and performance evaluation result shows the security and efficiency of the proposed secure mechanism.
Coexistence of Cheilitis Glandularis and Lichen Planus: Remarkable Response to Anti-inflammatory Treatments

A 36‐year‐old female patient presented with gradually enlarging and painful bleeding of her lower lip within 20 years. The patient did not define mechanical irritation, smoking, atopic state, chronic sun exposure, or photosensitivity. She was on oral antidiabetic treatment for Type 1 diabetes mellitus for 5 years. She did not have xerophthalmia, xerostomia, or arthritis. Organomegaly, lymphadenopathy, or palpable mass or any glandular involvement such as submandibular, sublingual, lacrimal, and parotid glands were not detected. Dermatological examination revealed fine desquamation, lacy white streaks, dilated and erythematous multiple milimetric ductal openings, and mild serous discharge by palpation . There was no vermilion or adjacent skin involvement. A wedge resection biopsy of the lower lip showed epidermal keratinization, granular layer, apoptotic cells lined in the basal layer, and lichenoid inflammation. Chronic lymphocytic inflammation of the minor salivary glands, periductal dense lymphocytic inflammation, and mild ductal ectasia were detected in the dermis . The inflammatory infiltrate in the tissue did not contain any plasma cells staining with CD138. Periodic acid Schiff/alcian blue (PAS/AB) staining did not show any dermal mucin or thick basal membrane. Fibrosis and obliterative phlebitis within the tissue were not present.
Improving medical diagnosis performance using hybrid feature selection via relieff and entropy based genetic search (RF-EGA) approach: application to breast cancer prediction

In this research a new hybrid prediction algorithm for breast cancer has been made from a breast cancer data set. Many approaches are available in diagnosing the medical diseases like genetic algorithm, ant colony optimization, particle swarm optimization, cuckoo search algorithm, etc., The proposed algorithm uses a ReliefF attribute reduction with entropy based genetic algorithm for breast cancer detection. The hybrid combination of these techniques is used to handle the dataset with high dimension and uncertainties. The data are obtained from the Wisconsin breast cancer dataset; these data have been categorized based on different properties. The performance of the proposed method is evaluated and the results are compared with other well known feature selection methods. The obtained result shows that the proposed method has a remarkable ability to generate reduced-size subset of salient features while yielding significant classification accuracy for large datasets.
“ Real Time Automated Control using PLC-VB Communication ” Prof .

This paper is to enable the Delta PLC (Programmable Logic Control) DVP14SS to communicate with the Visual Basic 6.0. The communication between DVP14SS and Visual Basic 6.0 is via Modbus Serial Protocol. Computers are used as a link between humans and PLC systems as they have more graphics and visual capabilities. These are nothing but SCADA systems widely used for determining plant setups and displaying plant status on high quality screens. They also record/log the system data for long period .The SCADA software's are the software packages needs to be purchased from vendors and the cost depends on tag count. Visual Basic 6.0 platform can be used develop the SCADA application effectively. Using VB 6.0 we integrate software and hardware across spectrum of vendors easily. Here we show simple approach to communicate Delta PLC with visual Basic using MSComm control in visual basic. By means of Visual Basic cost effective solution is possible as Visual Basic we do not need to purchase licenses and is cheaper than SCADA packages. It also has the advantages like flexibility. MSComm control and PLC, plc, communication between PLC and VB 6.0, DVP14SS.
Intelligent Security Measures for Smart Cyber Physical Systems

The exponential growth of cyber-physical systems (CPS), especially in safety-critical applications, has imposed several security threats (like manipulation of communication channels, hardware components, and associated software) due to complex cybernetics and the interaction among (independent) CPS domains. These security threats have led to the development of different static as well as adaptive detection and protection techniques on different layers of the CPS stack, e.g., cross-layer and intra-layer connectivity. This paper first presents a brief overview of various security threats at different CPS layers, their respective threat models and associated research challenges to develop robust security measures. Moreover, this paper provides a brief yet comprehensive survey of the state-of-the-art static and adaptive techniques for detection and prevention, and their inherent limitations, i.e., incapability to capture the dormant or uncertainty-based runtime security attacks. To address these challenges, this paper also discusses the intelligent security measures (using machine learning-based techniques) against several characterized attacks on different layers of the CPS stack. Furthermore, we identify the associated challenges and open research problems in developing intelligent security measures for CPS. Towards the end, we provide an overview of our project on security for smart CPS along with important analyses.
Integrins in cancer: biological implications and therapeutic opportunities

The integrin family of cell adhesion receptors regulates a diverse array of cellular functions crucial to the initiation, progression and metastasis of solid tumours. The importance of integrins in several cell types that affect tumour progression has made them an appealing target for cancer therapy. Integrin antagonists, including the αvβ3 and αvβ5 inhibitor cilengitide, have shown encouraging activity in Phase II clinical trials and cilengitide is currently being tested in a Phase III trial in patients with glioblastoma. These exciting clinical developments emphasize the need to identify how integrin antagonists influence the tumour and its microenvironment.
Loughborough University Institutional Repository Domestic electricity use : a high-resolution energy demand model

The pattern of electricity use in an individual domestic dwelling is highly dependent upon the activities of the occupants and their associated use of electrical appliances. This paper presents a high-resolution model of domestic electricity use, that is based upon a combination of patterns of active occupancy (i.e. when people are at home and awake), and daily activity profiles that characterise how people spend their time performing certain activities. One-minute resolution synthetic electricity demand data is created through the simulation of appliance use; the model covers all major appliances commonly found in the domestic environment. In order to validate the model, electricity demand was recorded over the period of a year within 22 dwellings in the East Midlands, UK. A thorough quantitative comparison is made between the synthetic and measured data sets, showing them to have similar statistical characteristics. A freely downloadable example of the model is made available and may be configured to the particular requirements of users or incorporated into other models.