Miracle-dz/UniFAR-FTUs huggingface dataset:
Certificateless Threshold Signature for Data Report Authentication in Mobile Ad Hoc Network

The focus of this paper is to design an efficient Certificateless Threshold Signature scheme (CLTHS) for data report authentication in mobile ad-hoc network, by which relatively small subsets of very large groups can report data that is aggregated and ``certified" by means of a signature. Examples include vehicular networks where cars report traffic conditions, sensor networks that report aggregate data such as temperature or radiation levels, military devices transmitting information to be reported to various commands, and more. We first define the security notion for Certificateless Threshold Signature. Different from the adversarial model defined by Wang et al., our definition considers Type I and Type II adversary separately. At the same time, we develop the simulatability and relationship between certificateless threshold signature and the underlying certificateless signature. We also propose the first CLTHS scheme which is proved existentially unforgeable against adaptively chosen message attack without random oracles. Compared with the previous scheme, our scheme is much more efficient.
Adaptive neural network tracking control of robot manipulators including motor dynamics: Dynamic surface backstepping methodology

To solve the trajectory tracking control problem for rigid-link robot manipulators including actuator dynamics, a novel neural network (NN)-based adaptive algorithm is discussed. In the proposed control algorithm, radial basis function neural network (RBFNN) is adopted to approximate the nonlinear dynamics of the robot manipulators' electromechanical system. Moreover, the key features are that, firstly, the unmatched & uncertainties of the system are overcame, secondly, the problem of “explosion of complexity” inherent in the conventional backstepping method is avoided due to combing with “dynamic surface control” (DSC) approach. Finally, simulation results are included to demonstrate the tracking performance and the effectiveness of proposed algorithm.
Enhancement of voltage-gated Ca2+ currents induced by daily stimulation of hippocampal neurons with glutamate

The regulation of calcium channel currents (ICa) induced by daily stimulation (1 hr) with 10 microM glutamate was studied in full differentiated hippocampal cells in culture. We report a specific enhancement of the high-voltage-activated current type (HVA ICa) ongoing over days. The density of HVA ICa increased about twofold after the second glutamate session, and this enhancement was still observed after the fifth day of treatment, while low-voltage-activated calcium currents (LVA ICa) remained unchanged. During glutamate application, a transient increase of intracellular calcium (Cai) was observed, followed by a slow decay within 2–3 min, and substantial recovery in about 10 min. Similarly, Cai transients induced by periodic membrane depolarization mimicked the long-term effect of glutamate on ICa. These results demonstrate for the first time an increase of ICa in a time frame of days. Since the effect of glutamate on ICa was prevented by cycloheximide, neosynthesis of channel proteins presumably supports this enhancement.
Energy Efficient Packet scheduling with Timing Constraints in Wireless Networks

Power efficiency is an important design issue in mobile devices with limited power supplies. Packet scheduling for wireless communication subsystem is one of the most important methods to achieve these issues. In this project, we identify the reward-based packet scheduling problem in wireless environments. A general scenario in which a transmitter communicates with multiple receivers periodically. To guarantee timely transmission of data, each packet is associated with a delay constraint. The periodic data streams have different importance levels, power functions, and levels of data sizes. The more data a transmitter delivers the more rewards it obtains. Objective is to develop schemes that selectively transmit data streams of different data sizes at different transmission rates so that the system reward can be maximized under given time and energy constraints. Index Terms Reward maximization, power-aware packet scheduling, wireless networks, embedded systems.
Leverages of Distributed MIMO Relaying : A Shannon-Theoretic Perspective

We consider a dense fading interference network with multiple active multi-antenna source-destination pair terminals communicating simultaneously through a large common set of multi-antenna relay terminals. We use Shannon-theoretic tools to analyze the tradeoff between energy efficiency and spectral efficiency (known as the power-bandwidth tradeoff) in meaningful asymptotic regimes of signal-to-noise ratio (SNR) and network size. We propose low-complexity distributed coordination schemes based on linear relay forwarding and characterize their power-bandwidth tradeoff under a system-wide power constraint on source and relay transmissions. The impact of multiple users, multiple relays and multiple antennas on the key performance measures of the high and low SNR regimes is investigated in order to shed new light on the possible reduction in power and bandwidth requirements through the usage of distributed relaying techniques. Our results indicate that point-to-point coded interference networks supported by linearbeamformer relays yield enhanced energy and spectral efficiency, and in certain cases, achieve asymptotically optimal powerbandwidth tradeoff for large number of relay terminals. Finally, we provide insights on energy efficient communication over dense power-limited relay networks considering jointly transmission and processing costs. 1
Uncertainties in Stellar Abundance Analyses

Over the last half-century quantitative stellar spectroscopy has made great progress. However, most stellar abundance analyses today still employ rather simplified models, which can introduce severe systematic errors swamping the observational errors. Some of these uncertainties for late-type stars are briefly reviewed here: atomic and molecular data, stellar parameters, model atmospheres and spectral line formation.
Reliability and Validity Analysis on the Relationship between Learning Space, Student’s Satisfaction and Perceived Performance Using SMART-PLS

This pilot study aims to examine the possibility of the association between learning space attributes of the environmental, design & facilities with student’s satisfaction and perceived performance in an academic building. Hence, this pilot survey was conducted in Universiti Teknologi MARA (UiTM), Perak Branch, Seri Iskandar Campus, Malaysia. A pilot questionnaire was administrated and collected from 50 students, where respondents were asked to select their preferences based on a five-point Likert scale of agreement and satisfaction for Section B and multiple answer question for Section A. Results of the pilot survey indicated that there is a significant relationship between the learning space attributes of the environmental, design & facilities with student’s satisfaction and perceived performance in an academic building especially of all the independent variables of the study. These results highlighted the importance of the learning space attributes such as the environmental, design & facilities in perceiving student’s satisfaction and perceived performance. Analysis of this pilot study was conducted by using PLS-SEM: SMART-PLS Version 3.2 to examine the reliability and validity of the questionnaire, thus, determining the significance of every independent variables and dependent variable in the research. The result further confirmed that the instrument used in this pilot study fulfil the acceptable requirements of the reliability and validity ranged for main data collection purpose of the intended study.
Speaker perception and social behavior: Bridging social psychology and speech science

Increasingly in recent years, social psychologists have come to appreciate the role that language plays in social life. For the discipline, the consequences of this developing awareness have been salutary. Language is critically implicated in many of the core phenomena social psychologists study (e.g., causal attribution, social identity, status and intimacy, and interpersonal relations, to list but a few), and taking the role of language into account has greatly enhanced our understanding of them. Moreover, because stimulus and response in social psychology are so often verbal in form, many fundamental questions of methodology turn on issues that are implicitly linguistic. When social psychologists have considered language, they typically have focused on the semantic–pragmatic levels of linguistic analysis. Much less attention has been paid to the system of sound production that allows semantic representations to be transformed into the perceptually accessible form we call speech. This is unfortunate for many reasons, not the least of which is that speech, in addition to its semantic content, contains information that bears directly on phenomena that are the concern of social psychological theory. It is useful to distinguish between two related areas of investigation that involve speech processing: research on speech perception and speaker perception. Speech perception research studies the process by which listeners extract linguistically significant information from highly variable acoustic input. The process is complicated by the fact that spoken language is both highly variable
Book Reviews: Text Mining for Biology and Biomedicine, edited by Sophia Ananiadou and John McNaught

A battery separator material which is folded to form an envelope is heat sealed along at least two opposing edges thereof to form a battery separator. The separator material is comprised of discrete polyolefin pulp fibers in a sufficient amount to heat seal the separator along its edges. The fibers are bound by an organic polymeric binder. A process of forming the battery separator is also disclosed.
Large-Scale Reasoning with (Semantic) Data

In this paper, we discuss scalable methods for nonmonotonic rule-based reasoning over Semantic Web Data, using MapReduce. This work is motivated by the recent unparalleled explosion of available data coming from the Web, sensor readings, databases, ontologies and more. Such datasets could benefit from the introduction of rule sets encoding commonly accepted rules or facts, application or domain specific rules, commonsense knowledge etc. This raises the question of whether, how, and to what extent knowledge representation methods are capable of handling huge amounts of data for these applications. Our results indicate that our method shows good scalability properties and is able to handle a benchmark dataset of 1 billion triples, bringing it on par with state-of-the-art methods for monotonic reasoning on the semantic web.
Notice of RetractionStudy on multi-objective emergency service facilities probabilistic location

Traditional location models, when considering congested systems and facing numerous unforeseen matters, cannot fulfill with the requirements of the accessibility problem under busy fraction conditions. Besides that, we also did not take the marginal utility of the new added emergency service facilities into consideration. On the basis of the analysis of classic location models, this paper established a new comprehensive multi-objective probabilistic location model. This model meets the fairness of location by setting up the minimum accessibility, considering the new facilities marginal utility and cost, and then we come to find the emergency services location method. Finally the results of an example demonstrate the effectiveness of this model.
Approximation of biased Boolean functions of small total influence by DNFs

The influence of the k th coordinate on a Boolean function f:{0,1}n→{0,1} is the probability (with respect to the uniform measure on {0,1}n ) that flipping xk changes the value f(x) . The total influence I(f) is the sum of influences of the coordinates. The well‐known ‘Junta theorem’ of Friedgut [Combinatorica 18 (1998) 27–35] asserts that if I(f)⩽M , then f can be ε ‐approximated by a function that depends on 2O(M/ε) coordinates. Friedgut's theorem has a wide variety of applications in mathematics and theoretical computer science.
Dense Non-rigid Structure from Motion

This paper shows how current sparse approaches to Non-Rigid Structure From Motion (NRSfM) can be extended to template-free dense reconstruction. Our contribution can be broken down into two components: (i) We provide asymptotic improvements to current optimisation approaches, allowing them to scale to the dense case. (ii) We remove the need to estimate an initial rest shape or a known 3d template. This both increases the robustness of the method, allowing it to be applied to arbitrary sequences, and further decreases the run-time of our approach. Extending the existing techniques of NRSfM to fullyautomatic and dense template-free reconstruction substantially increases the difficulty of the optimisation problems faced, and we provide novel approaches for avoiding local minima in both discrete and continuous sub-problems.
Motivating EFL Students with Conversation Data

Motivating learners of English as a Foreign Language (EFL) to improve their speaking fluency is challenging in environments where institutions emphasize reading and listening test performance. The focus tends to shift to strategic reading and listening first in order to attain acceptable test results, often at the expense of communicative competence. Computer Assisted Language Learning (CALL) is well positioned to assess and develop communicative competence for EFL learners, and to motivate them to speak. This article introduces the Objective Subjective (OS) Scoring system, a CALL system which sets clear immediate goals on the path to better communicative competence with data from videoed conversation sessions. It motivates learners to improve on their data in every consecutive conversation session, whereby an environment is created which facilitates conversation practice as well as individual error correction.
Human epicardium-derived cells fuse with high efficiency with skeletal myotubes and differentiate toward the skeletal muscle phenotype: a comparison study with stromal and endothelial cells

EPDCs fuse with skeletal myotubes with higher efficiency when compared to MSCs and endothelial cells. Independently from the cell origin, all nuclei recruited inside myotubes express muscle-specific genes. VCAM1 expression in nonmuscle cells is induced by soluble factors secreted by myotubes, and its function is required for fusion to occur.
The war room command console: shared visualizations for inclusive team coordination

Making the structure of software visible during system development helps (i) build a shared understanding of the context for each piece of work, (ii) identify progress with implementation, and (iii) highlight any conflict between individual development activities. Finding an adequate representation for such information is not straightforward, especially for large applications. This paper describes an implementation of such a visualization system designed to explore some of the issues involved. The approach is based on a `War Room Command Console' metaphor and uses a bank of eight linked consoles to present information. The tool was applied to several industrial software systems written in a mixture of Java, C++ and C, one of which was over a million lines of code in size.
Motivating physical activity at work: Using persuasive social media extensions for simple mobile devices

Powerful behaviour change programmes can be developed through a combination of very simple, accessible technology, and an understanding of the psychological processes that drive behaviour change. We present a study in which very basic digital pedometers were used to record the number of steps taken by participants over the course of a normal working day. A Facebook application, named Step Matron, was utilised to provide a social and competitive context for pedometer readings. We were particularly interested in whether interactions between users via the application more successfully motivated physical activity than simply recording daily step counts in a similar application. Ten participants (1 male), all nurses working in a UK hospital, used the application across two conditions over the course of the study. In the socially-enabled condition, participants could view each other‟s step data and make comparisons and comments. In the non-social condition, participants could only view their own personal step data. A significant increase in step activity was observed in the socially enabled condition. Our findings highlight the potential of social media as a means for generating positive behaviour change. They also suggest that simple mobile devices can function as an inexpensive, accessible and powerful trigger towards this behaviour change without necessitating the use of overly complex and expensive mobile applications or devices.
Automatic Labeling of Voiced Consonants for Morphological Analysis of Modern Japanese Literature

Since the present-day Japanese use of voiced consonant mark had established in the Meiji Era, modern Japanese literary text written in the Meiji Era often lacks compulsory voiced consonant marks. This deteriorates the performance of morphological analyzers using ordinary dictionary. In this paper, we propose an approach for automatic labeling of voiced consonant marks for modern literary Japanese. We formulate the task into a binary classification problem. Our pointwise prediction method uses as its feature set only surface information about the surrounding character strings. As a consequence, training corpus is easy to obtain and maintain because we can exploit a partially annotated corpus for learning. We compared our proposed method as a preprocessing step for morphological analysis with a dictionary-based approach, and confirmed that pointwise prediction outperforms dictionary-based approach by a large margin.
A Review of Data Intensive Computing

Data intensive computing is a common research problem in science, industry and computer academia. In recent twenty years, the explosive growth of science data has appeared all over the world. Typical data intensive computing applications include Internet text data processing, scientific research data processing, large scale graph computing, inverse and perspective problems. Data intensive computing research faces challenges of scalability of massive data management and processing, integrated data processing technology, system management, new transaction demand, unstructured data processing, service mode, good fault tolerance and high availability. Appropriate data intensive computing programming model needs to be suitable for large scale data sets parallel computing, multiple virtual machine task scheduling and constructing new data intensive computing applications. As a typical data intensive application, aerosol inverse computing I/O data volume is analyzed. Although industry and academia has brought some methods for data intensive applications, scientific discovery problems with both data intensive and computation intensive features are still no appropriate solution at present. Keywordsdata intensive computing, Big data, parallel
Risk Load and the Default Rate of Surplus

One of the biggest challenges facing the securitization of insurance risk is the translation of pricing techniques between the insurance and capital market worlds. At their heart the two worlds share similar purposes: assigning prices to uncertain future cash flow patterns. While the purposes are similar, historically the techniques and terminology have been somewhat disjoint. Widespread securitization of insurance results will require a manageable model to understand and price insurance risk in a capital market context. Ideally this model would also produce prices which were comparable to other securities available in the capital market. This paper introduces an insurance pricing model that translates aspects of corporate bond pricing – specifically default risk – to an insurance framework. It jointly addresses two favorite topics of casualty actuaries – allocated surplus and risk load, is well suited to DFA applications, and has been fully implemented in an Excel workbook that will be posted on the CAS Website.
An algorithm for dynamic optimal bandwidth allocation in communication networks

We study the problem of optimal bandwidth allocation in communication networks. We consider a queueing model with two queues to which traffic from different competing flows arrive. The queue length at the buffers is observed every T instants of time, on the basis of which a decision on the amount of bandwidth to be allocated to each buffer for the next T instants is made. We consider a class of closed-loop feedback policies for the system and use a twotimescale simultaneous perturbation stochastic approximation(SPSA) algorithm to find an optimal policy within the prescribed class. We study the performance of the proposed algorithm on a numerical setting. Our algorithm is found to exhibit good performance.
Does work influence women’s autonomy or does autonomy deliberate women to work?

Work, especially paid work, has been assumed to enhance women’s autonomy, particularly their household autonomy. However, this assumption does not work in one causal direction. The causality relationship works both ways, that women work due to their high level of autonomy, but also because their employment status will increase their autonomy. The aim of this study is to understand the relationship between women’s work status and their household autonomy. This study used data from the Indonesian Demography and Health Survey 2012, together with a multinomial logistic regression analysis on married women’s work status and autonomy as dependent and independent variables, respectively. It was found that work status influences married women’s household autonomy and vice versa. However, the direction and strength of the influence depend on the type of work status and autonomy.
Reliable Distribution of Data Using Replicated Web Servers

In this paper we describe an algorithm for accessing files over replicated Web servers. The algorithm breaks the request for a document W, which is assumed to be replicated among N different servers, into N requests such that any K replies are sufficient to reconstruct the whole page. In this way, the document is downloaded from the K fastest servers. The algorithm is feedback-free and does not require any computation to be performed on client or server sides. Thus, it may be implemented on devices with limited computing capabilities. Analytical evaluation of the proposed algorithm shows that, under the model's assumptions, a correctly tuned value for K significantly improves the probability of completing earlier the transfer of W
Genome Sequence of Anaerobacillus macyae JMM-4T (DSM 16346), the First Genomic Information of the Newly Established Genus Anaerobacillus

ABSTRACT Anaerobacillus macyae JMM-4T (DSM 16346) is a Gram-positive, spore-forming, strictly anaerobic, and arsenate-respiring bacterium. Here, we report the 4.26-Mb genome sequence of A. macyae JMM-4T, which is the first genome information of the newly established genus Anaerobacillus.