Miracle-dz/UniFAR-FTUs huggingface dataset:
DEVSML: automating DEVS execution over SOA towards transparent simulators

Discrete Event Specification (DEVS) formalism has been used to study dynamics of discrete event systems. DEVS environments are typically open architectures that have been extended to execute on various middleware such as CORBA, Grid computing, P2P networks, RMI and others. The present work aims to provide another development environment using the Service Oriented Architecture (SOA) framework. The proposed DEVS Modeling Language (DEVSML) is built on XML and provides model interoperability among DEVS models located at remote locations. The DEVSML environment is built on client-sever paradigm and the simulation is executed at the server's end. The proposed DEVS atomic and coupled DTDs are open to standardization from the community for successful model sharing and collaboration. The DEVSML framework provides the needed feature of run-time composability of coupled systems using the SOA framework. DEVSML also provides the capability to translate model to and from XML and JAVA programming language leading to model composability and validation. This paper will demonstrate the client application as well as the server architecture underlying the DEVSML framework.
A Model Checking Framework for Layered Command and Control Software

Most existing modular model checking techniques betray their hardware roots: they assume that modules compose in parallel. In contrast, layered software systems, which have proven successful in many domains, are really quasi-sequential compositions of parallel compositions. Most such systems demand and inspire new modular verification techniques. This paper presents algorithms that exploit a layered (or feature-based) decomposition to drive verification. Our technique can verify most properties locally within a layer; we also characterize when a global state space construction is unavoidable. This work is motivated by our efforts to verify a military fire simulation and support software system called FSATS.
A Quantitative Hydrological Climate Classification Evaluated With Independent Streamflow Data

Classification is essential in the study of natural systems, yet hydrology has no formal way to structure the climatic forcing that underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might need. This work presents a hydrologically informed way to quantify global climates, explicitly addressing the shortcomings in earlier climate classifications. In this work, causal factors (climate) and hydrologic response (streamflow) are separated, meaning that our classification scheme is based only on climatic information and can be evaluated with independent streamflow data. Using gridded global climate data, we calculate three dimensionless indices per grid cell, describing annual aridity, aridity seasonality, and precipitation‐as‐snow. We use these indices to create several climate groups and define the membership degree of 1,103 catchments to each of the climate groups, based on each catchment's climate. Streamflow patterns within each group tend to be similar, and tend to be different between groups. Visual comparison of flow regimes and Wilcoxon two‐sample statistical tests on 16 streamflow signatures show that this index‐based approach is more effective than the often‐used Köppen‐Geiger classification for grouping hydrologically similar catchments. Climate forcing exerts a strong control on typical hydrologic response and we show that at the global scale both change gradually in space. We argue that hydrologists should consider the hydroclimate as a continuous spectrum defined by the three climate indices, on which all catchments are positioned and show examples of this in a regionalization context.
Experimental Analysis of the Coupling Mechanisms Between a 4 GHz PPA and a 5–7 GHz $LC$-VCO

The coupling of the transmitted radio-frequency (RF) signal of the power amplifier (PA) in the sensitive voltage-controlled oscillator (VCO) remains a major problem for system-on-chip (SoC) design. Coupling between these two circuits may cause malfunctioning of the system. This paper analyzes the different coupling mechanisms between a 4 GHz prepower amplifier (PPA) and a 5-7 GHz LC-VCO designed in 0.13 mum technology. Different experiments are carried out to reveal the dominant coupling mechanisms. Insight into these mechanisms leads to the proposal of proper countermeasures.
Is Visual Selective Attention in Deaf Individuals Enhanced or Deficient? The Case of the Useful Field of View

Background Early deafness leads to enhanced attention in the visual periphery. Yet, whether this enhancement confers advantages in everyday life remains unknown, as deaf individuals have been shown to be more distracted by irrelevant information in the periphery than their hearing peers. Here, we show that, in a complex attentional task, a performance advantage results for deaf individuals. Methodology/Principal Findings We employed the Useful Field of View (UFOV) which requires central target identification concurrent with peripheral target localization in the presence of distractors – a divided, selective attention task. First, the comparison of deaf and hearing adults with or without sign language skills establishes that deafness and not sign language use drives UFOV enhancement. Second, UFOV performance was enhanced in deaf children, but only after 11 years of age. Conclusions/Significance This work demonstrates that, following early auditory deprivation, visual attention resources toward the periphery slowly get augmented to eventually result in a clear behavioral advantage by pre-adolescence on a selective visual attention task.
Adaptive Neural Control of Nonlinear MIMO Systems With Time-Varying Output Constraints

In this paper, adaptive neural control is investigated for a class of unknown multiple-input multiple-output nonlinear systems with time-varying asymmetric output constraints. To ensure constraint satisfaction, we employ a system transformation technique to transform the original constrained (in the sense of the output restrictions) system into an equivalent unconstrained one, whose stability is sufficient to solve the output constraint problem. It is shown that output tracking is achieved without violation of the output constraint. More specifically, we can shape the system performance arbitrarily on transient and steady-state stages with the output evolving in predefined time-varying boundaries all the time. A single neural network, whose weights are tuned online, is used in our design to approximate the unknown functions in the system dynamics, while the singularity problem of the control coefficient matrix is avoided without assumption on the prior knowledge of control input's bound. All the signals in the closed-loop system are proved to be semiglobally uniformly ultimately bounded via Lyapunov synthesis. Finally, the merits of the proposed controller are verified in the simulation environment.
Persistence of Cardiac Remodeling in Preadolescents With Fetal Growth Restriction

Background— Fetal growth restriction (FGR) affects 5% to 10% of newborns and is associated with increased cardiovascular mortality in adulthood. We evaluated whether prenatal cardiovascular changes previously demonstrated in FGR persist into preadolescence. Methods and Results— A cohort study of 58 FGR (defined as birth weight below 10th centile) and 94 normally grown fetuses identified in utero and followed-up into preadolescence (8–12 years of age) by echocardiography and 3-dimensional shape computational analysis. Compared with controls, FGR preadolescents had a different cardiac shape, with more spherical and smaller hearts. Left ventricular ejection fraction was similar among groups, whereas FGR had decreased longitudinal motion (decreased mitral annular systolic peak velocities: control median, 0.11 m/s [interquartile range, 0.09–0.12] versus FGR median 0.09 m/s [interquartile range, 0.09–0.10]; P<0.01) and impaired relaxation (isovolumic relaxation time: control, 0.21 ms [interquartile range, 0.12–0.35] versus FGR, 0.35 ms [interquartile range, 0.20–0.46]; P=0.04). Global longitudinal strain was decreased (control mean, −22.4% [SD, 1.37] versus FGR mean, −21.5% [SD, 1.16]; P<0.001) compensated by an increased circumferential strain and with a higher prevalence of postsystolic shortening in FGR as compared with controls. These differences persisted after adjustment for parental ethnicity and smoking, prenatal glucocorticoid administration, preeclampsia, gestational age at delivery, days in intensive care unit, sex, age, and body surface area at evaluation. Conclusions— This study provides evidence that cardiac remodeling induced by FGR persists until preadolescence with findings similar to those reported in their prenatal life and childhood. The findings support the hypothesis of primary cardiac programming in FGR for explaining the association between low birth weight and cardiovascular risk in adulthood.
Compression of quantum multi-prover interactive proofs

We present a protocol that transforms any quantum multi-prover interactive proof into a nonlocal game in which questions consist of logarithmic number of bits and answers of constant number of bits. As a corollary, it follows that the promise problem corresponding to the approximation of the nonlocal value to inverse polynomial accuracy is complete for QMIP*, and therefore NEXP-hard. This establishes that nonlocal games are provably harder than classical games without any complexity theory assumptions. Our result also indicates that gap amplification for nonlocal games may be impossible in general and provides a negative evidence for the feasibility of the gap amplification approach to the multi-prover variant of the quantum PCP conjecture.
Purinergic receptor stimulation increases membrane trafficking in brown adipocytes

Stimulation of brown adipocytes by their sympathetic innervation plays a major role in body energy homeostasis by regulating the energy- wasting activity of the tissue. The norepinephrine released by sympathetic activity acts on adrenergic receptors to activate a variety of metabolic and membrane responses. Since sympathetic stimulation may also release vesicular ATP, we tested brown fat cells for ATP responses. We find that micromolar concentrations of extracellular ATP initiates profound changes in the membrane trafficking of brown adipocytes. ATP elicited substantial increases in total cell membrane capacitance, averaging approximately 30% over basal levels and occurring on a time scale of seconds to minutes. The membrane capacitance increase showed an agonist sensitivity of 2-methylthio-ATP > or = ATP > ADP > > adenosine, consistent with mediation by a P2r type purinergic receptor. Membrane capacitance increases were not seen when cytosolic calcium was increased by adrenergic stimulation, and capacitance responses to ATP were similar in the presence and absence of extracellular calcium. These results indicate that increases in cytosolic calcium alone do not mediate the membrane response to ATP. Photometric assessment of surface-accessible membrane using the dye FM1- 43 showed that ATP caused an approximate doubling of the amount of membrane actively trafficking with the cell surface. The discrepancy in the magnitudes of the capacitance and fluorescence changes suggests that ATP both activates exocytosis and alters other aspects of membrane handling. These findings suggest that secretion, mobilization of membrane transporters, and/or surface membrane expression of receptors may be regulated in brown adipocytes by P2r purinergic receptor activity.
Identification of Clinically Relevant Viridans Group Streptococci by Sequence Analysis of the 16S-23S Ribosomal DNA Spacer Region

ABSTRACT The feasibility of sequence analysis of the 16S-23S ribosomal DNA (rDNA) intergenic spacer (ITS) for the identification of clinically relevant viridans group streptococci (VS) was evaluated. The ITS regions of 29 reference strains (11 species) of VS were amplified by PCR and sequenced. These 11 species were Streptococcus anginosus, S. constellatus, S. gordonii, S. intermedius, S. mitis, S. mutans, S. oralis, S. parasanguinis, S. salivarius, S. sanguinis, and S. uberis. The ITS lengths (246 to 391 bp) and sequences were highly conserved among strains within a species. The intraspecies similarity scores for the ITS sequences ranged from 0.98 to 1.0, except for the score for S. gordonii strains. The interspecies similarity scores for the ITS sequences varied from 0.31 to 0.93. Phylogenetic analysis of the ITS regions revealed that evolution of the regions of some species of VS is not parallel to that of the 16S rRNA genes. One hundred six clinical isolates of VS were identified by the Rapid ID 32 STREP system (bioMérieux Vitek, Marcy l'Etoile, France) and by ITS sequencing, and the level of disagreement between the two methods was 18% (19 isolates). Most isolates producing discrepant results could be unambiguously assigned to a specific species by their ITS sequences. The accuracy of using ITS sequencing for identification of VS was verified by 16S rDNA sequencing for all strains except strains of S. oralis and S. mitis, which were difficult to differentiate by their 16S rDNA sequences. In conclusion, identification of species of VS by ITS sequencing is reliable and could be used as an alternative accurate method for identification of VS.
The use of environmental radionuclides in investigations of sediment sources and overbank sedimentation rates in the Himalaya Foreland, India

Abstract This paper presents some preliminary results from an investigation of overbank sedimentation rates on the flood plains of the Teesta and Brahmaputra Rivers in the Himalaya Foreland, India. The 210 Pb ex , 226 Ra and 137 Cs depth distributions in sediment cores have been used to derive estimates of overbank sedimentation rates. The estimated sedimentation rates for the flood plains of the Teesta River sites vary from 0.21 cm year -1 for the upper flood plain level at the site near Boogadong to 3.56 cm year -1 at the site near the confluence of the Teesta River with the Great Rangit River. Mass move-ments and channel and gully erosion are the dominant suspended sediment sources in the Teesta River basin. A similar accretion rate of 2.24 cm year -1 was documented for a site on the flood plain of the Brahmaputra River near Guwahati, where the river enters the Ganga-Brahmaputra Plain. Key words 137 Cs; 210 Pb ex ; Brahmaputra River; Ganga-Brahmaputra Plain, India; overbank sedimentation; sedimentation rate; sediment sources
Value Stream Map Simulator Using ExtendSim

Value Stream Mapping is a paper and pencil tool that captures the state of the system at the state it was drawn. Simulation can be combined with value stream mapping to give it power and flexibility in order to dynamically capture the state of the system. Component-based modeling divides a simulation model into a number of smaller simulation models resulting in a set of simulation building blocks. This paper introduces the Value Stream Map Simulator using ExtendSim ® (VSMSx) as a powerful tool designed to facilitate the implementation of lean manufacturing by simulating the value stream map. The VSMSx empowers the traditional value stream map by combining it with simulation and add the dimension of time making it a powerful analysis tool. The VSMSx is designed to have its own library of blocks that look identical to the icons of the traditional VSM. These blocks can be used for the purpose of developing value stream maps as they are designed to be generic, reusable, and appear exactly like the traditional VSM icons. Compared to traditional value stream mapping, this tool outputs more accurate quantitative performance measures of various scenarios that allow better decision making. Inputs to the VSMSx can be of a deterministic or a stochastic nature that would accurately represent the value stream map variables with any data distribution. A database is developed especially for manipulating the inputs/outputs to the VSMSx. As a conclusion, the VSMSx is a tool that can pave the way for successful lean manufacturing implementations.
An optimization approach to estimate and calibrate column water vapour for hyperspectral airborne data

ABSTRACT The article describes a novel approach to estimate and calibrate column water vapour (CWV), a key parameter for atmospheric correction of remote-sensing data. CWV is spatially and temporally variable, and image-based methods are used for its inference. This inference, however, is affected by methodological and numeric limitations, which likely propagate to reflectance estimates. In this article, a method is proposed to estimate CWV iteratively from target surface reflectances. The method is free from assumptions for at sensor radiance-based CWV estimation methods. We consider two cases: (a) CWV is incorrectly estimated in a processing chain and (b) CWV is not estimated in a processing chain. To solve (a) we use the incorrect estimations as initial values to the proposed method during calibration. In (b), CWV is estimated without initial information. Next, we combined the two scenarios, resulting in a generic method to calibrate and estimate CWV. We utilized the hyperspectral mapper (HyMap) and airborne prism experiment (APEX) instruments for the synthetic and real data experiments, respectively. Noise levels were added to the synthetic data to simulate real imaging conditions. The real data used in this research are cloud-free scenes acquired from the airborne campaigns. For performance assessment, we compared the proposed method with two state-of-the-art methods. Our method performed better as it minimizes the absolute error close to zero, only within 8–10 iterations. It thus suits existing operational chains where the number of iterations is considerable. Finally, the method is simple to implement and can be extended to address other atmospheric trace gases.
The Influence of Earnings Per Share and Interest Rate on Stock Prices in the Mediation of Firm Value (Study on Financial Companies Listed on the Indonesia Stock Exchange)

This study aimed to examine and analyse a company’s characteristic variables. Its earnings per share and interest rates were the macroeconomic variables, and their effect on stock prices was mediated by firm value. This study used quantitative methods and path analysis of 30 financial companies belonging to banks and non-banks that have been listed on the Indonesia Stock Exchange. The results showed that the direct effect of earnings per share on stock price had a positive and significant coefficient. Indirectly or through mediation (intervening) the firm value variable showed that the effect of the earning per share variable on the stock price was obtained by a positive and significant coefficient value. Furthermore, the results showed that the direct effect of interest rate on stock price had a positive direction coefficient and was not significant. The results of the research indirectly or through mediation (intervening) of firm value variable indicated that the effect of interest rate variable on stock price was obtained by positive and insignificant coefficient value. Meanwhile, the firm value directly on the stock price has a significant effect. Keywords: firm value, macroeconomic, Indonesia Stock Exchange
Evolving long-term dependency rules in lifelong learning models

Topic models are extensively used for text analysis to extract prominent concepts as topics in a large collection of documents about a subject domain. They are extended with different approaches to suit various application areas. Automatic knowledge-based topic models are recently introduced to specifically meet the processing needs of large-scale data having many subject domains. The model automatically learns rules across all domains and uses them to improve the results of the current domain by purposefully grouping words into topics to better represent the underlying concept. The existing models apply thresholds on evaluation criteria to learn rules; however, being automatic it may learn wrong, irrelevant or inconsistent rules as well. In this research article the proposed model learns rules and monitors their contributions towards the quality of results. As the model learns new rules, the existing rules undergo refinement and detachment procedures to retain reliable rules only. Experimental results on user reviews from Amazon.com shows improvement in the quality of topics by using fewer rules which advocates the quality of rules and help avoid performance bottleneck at high experience.
Fog Computing: Issues and Challenges in Security and Forensics

Although Fog Computing is defined as the extension of the Cloud Computing paradigm, its distinctive characteristics in the location sensitivity, wireless connectivity, and geographical accessibility create new security and forensics issues and challenges which have not been well studied in Cloud security and Cloud forensics. In this paper, through an extensive review of the motivation and advantages of the Fog Computing and its unique features as well as the comparison on various scenarios between the Fog Computing and Cloud Computing, the new issues and challenges in Fog security and Fog forensics are presented and discussed. The result of this study will encourage and promote more extensive research in this fascinating field, Fog security and Fog forensics.
Minimising cell transmit power: towards self-organized resource allocation in OFDMA femtocells

With the introduction of femtocells, cellular networks are moving from the conventional centralised architecture to a distributed one, where each network cell should make its own radio resource management decisions, while providing inter-cell interference mitigation. However, realising this distributed cellular network architecture is not a trivial task. In this paper, we first introduce a simple self-organisation rule under which a distributed cellular network is able to converge into an efficient resource allocation pattern, then propose a novel resource allocation model taking realistic resource allocation constraints into account, and finally evaluate the performance of the proposed self-organisation rule and resource allocation model using system-level simulations.
Research on Distributed Renewable Energy Power Measurement and Operation Control Based on Cloud-Edge Collaboration

This paper examines how we can combine two big trends in solar energy: the spread of solar panels and wind turbines to renew the power grid, and cloud and edge computing technology to improve the way the grid works. Our study introduces a new strategy that is based on a means to exploit the power of cloud computing’s big data handling ability, together with the capacity of edge computing to provide real-time data processing and decision making. The method is designed to address major challenges in renewables systems making the system bigger and more reliable, and cutting the time delays in deciding how the system should respond. These are the kinds of changes that will be necessary so that we can blend solar and wind power into our current power grid, whether we are ready to say goodbye to coal or natural gas power. Our paper presents a way in which we believe that renewables systems can work more smoothly and effectively. This includes making it easier to measure how much power is being generated, to control these systems so that they function much like traditional power plants, and hence, to allow renewable energy to be part of a reliable and efficient part of our electricity supply. These are all crucial steps in using technology to make more of the green power from the sun – which we must do for our energy usage to be more earth friendly.