Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal Specifications of Component Based Systems with Polymorphic Dynamic Reconfiguration

In this chapter, we present a formal characterisation of component based systems with support for polymorphic dynamic reconfiguration. By dynamic reconfiguration we mean, as usual, changes in the system architecture at run time. By polymorphic reconfiguration we mean that reconfiguration operations may concern different types of components or connections, exploiting an inheritance relationship over components, as in object orientation. The formal characterisation of component based systems is based on a firstorder temporal logic. The logic is a variant of the Manna-Pnueli logic, expressive enough for straightforward specification of component types, connector types and dynamic amalgamations of components. On top of this logic, and in the form of a (rather low level) specification language, we build the necessary machinery for specifying components, connectors and amalgamations, together with inheritance and polymorphism.
Design, fabrication and characterization of a zinc oxide thin-film piezoelectric accelerometer

Conventionally manufactured accelerometers based on piezoelectric lead zirconate titanate (PZT) have been used for decades, but integration issues hinder their application in micro-electro-mechanical systems (MEMS). Compared to PZT, zinc oxide (ZnO) has lower piezoelectricity and is not an attractive material for use in traditional bulky accelerometers due to its low sensitivity. However, ZnO has excellent compatibility with MEMS processing techniques, and furthermore, sensitivity can be enhanced by MEMS miniaturization. In this paper, we report the development of a micromachined ZnO piezoelectric thin-film accelerometer that demonstrates the feasibility of both easy integration and high sensitivity.
Improving Education and Employment for Disadvantaged Young Men: Proven and Promising Strategies

Low high school graduation rates and sharply declining employment rates among disadvantaged youth have led to an increasing number of youths who are disconnected from both school and work. What programs and policies might prevent these disconnections and improve educational and employment outcomes, particularly among young men? The authors review the evidence base on youth development policies for adolescents and young teens; programs seeking to improve educational attainment and employment for in-school youths; and programs that try to “reconnect” those who are out of school and frequently out of work, including public employment programs. The authors identify a number of programmatic strategies that are promising or even proven, based on rigorous evaluations, for disadvantaged youths with different circumstances and conclude that policy efforts need to promote a range of approaches to engage and reconnect youths, along with ongoing evaluation efforts to improve our understanding of what works, including which program components, for whom.
TANSO: A componentized distributed service foundation in cloud environment

Along with the improvement of cloud technologies, we envision that thousands of web applications whether owned by individuals or enterprises will be migrated into cloud. These web applications share the cloud resources while require different quality of service guarantees and management policies. It is challenging while with abundant innovation opportunities given the easy and dynamic provisioning of cloud resources. In order to facilitate practitioners to evaluate, experiment, or enhance existing functionalities of distributed web application management in cloud environment, a componentized distributed service foundation named TANSO is proposed. TANSO targets serving as platform to manage thousands of web application server instances and provide plenty of interfaces for user to extend and experiment new ideas. TANSO has implemented framework components to enable fundamental management. It also provides interfaces to admit and foster user's innovative algorithms and designs for managing large-scale web applications.
Proteasome inhibitors attenuated cholesterol-induced cardiac hypertrophy in H9c2 cells

The Ubiquitin proteasome system (UPS) plays roles in protein degradation, cell cycle control, and growth and inflammatory cell signaling. Dysfunction of UPS in cardiac diseases has been seen in many studies. Cholesterol acts as an inducer of cardiac hypertrophy. In this study, the effect of proteasome inhibitors on the cholesterol-induced hypertrophic growth in H9c2 cells is examined in order to observe whether UPS is involved in cardiac hypertrophy. The treatment of proteasome inhibitors MG132 and Bortezomib markedly reduced cellular surface area and mRNA expression of β-MHC in cholesterol-induced cardiac hypertrophy. In addition, activated AKT and ERK were significantly attenuated by MG132 and Bortezomib in cholesterol-induced cardiac hypertrophy. We demonstrated that cholesterol-induced cardiac hypertrophy was suppressed by proteasome inhibitors. Thus, regulatory mechanism of cholesterol-induced cardiac hypertrophy by proteasome inhibitors may provide a new therapeutic strategy to prevent the progression of heart failure. [BMB Reports 2016; 49(5): 270-275]
DIRECTION FINDING FOR BISTATIC MIMO RADAR USING EM MAXIMUM LIKELIHOOD ALGORITHM

In this paper, we investigate an expectation-maximization (EM) maximum likelihood (ML) algorithm of direction flnding (DF) for bistatic multiple-input multiple-output (MIMO) radar, where it is shown that the DF problem can be described as a special case of ML estimation with incomplete data. First, we introduce the signal and the noise models, and derive the ML estimations of the direction parameters. Considering the computational complexity, we make use of the EM algorithm to compute the ML algorithm, referred to EM ML algorithm, which can be applied to the arbitrary antenna geometry and realize the auto-pairing between direction-of-departures (DODs) and direction-of-arrivals (DOAs). Then the initialization is considered. In addition, both the convergence and the Cramer-Rao bound (CRB) analysis are derived. Finally, simulation results demonstrate the potential and asymptotic e-ciency of this approach for MIMO radar systems.
Mind wandering away from pain dynamically engages antinociceptive and default mode brain networks

Significance The mind easily wanders away from mundane tasks, but pain is presumed to automatically capture attention. We demonstrate that individuals differ in how often their minds spontaneously wander away from pain and that these differences are associated with the disruptive effect of pain on cognitive performance. Brain–behavior relationships underscore these individual differences. When people’s minds wander away from pain, there are increased activations of the default mode network (DMN) and strong interactions between the DMN and periaqueductal gray (PAG), an opiate-rich region mediating pain suppression. Individuals with greater tendencies to mind wander from pain have stronger anatomical links and dynamic functional communication between PAG and DMN. These findings provide clinically important clues about why some individuals cannot disengage from pain. Human minds often wander away from their immediate sensory environment. It remains unknown whether such mind wandering is unsystematic or whether it lawfully relates to an individual’s tendency to attend to salient stimuli such as pain and their associated brain structure/function. Studies of pain–cognition interactions typically examine explicit manipulation of attention rather than spontaneous mind wandering. Here we sought to better represent natural fluctuations in pain in daily life, so we assessed behavioral and neural aspects of spontaneous disengagement of attention from pain. We found that an individual’s tendency to attend to pain related to the disruptive effect of pain on his or her cognitive task performance. Next, we linked behavioral findings to neural networks with strikingly convergent evidence from functional magnetic resonance imaging during pain coupled with thought probes of mind wandering, dynamic resting state activity fluctuations, and diffusion MRI. We found that (i) pain-induced default mode network (DMN) deactivations were attenuated during mind wandering away from pain; (ii) functional connectivity fluctuations between the DMN and periaqueductal gray (PAG) dynamically tracked spontaneous attention away from pain; and (iii) across individuals, stronger PAG–DMN structural connectivity and more dynamic resting state PAG–DMN functional connectivity were associated with the tendency to mind wander away from pain. These data demonstrate that individual tendencies to mind wander away from pain, in the absence of explicit manipulation, are subserved by functional and structural connectivity within and between default mode and antinociceptive descending modulation networks.
A Comparative Study of IEEE 802 . 11 Standards for Non-Safety Applications on Vehicular Ad Hoc Networks : A Congestion Control Perspective

Vehicular Ad Hoc Networks (VANETs) is an important component within the intelligent transportation systems (ITS) that have been part of global strategy and advanced applications. The aim is to provide innovative services relating to various modes of transportation and traffic management. These systems enable users to reach their destinations better, safer and more coordinated. In order to make the system workable, several radio access technologies (RAT) such as UMTS, WiFi, WiMAX and radio spectrum at 5.9 GHz have been proposed for next generation ITS. In this survey, we investigate the IEEE wireless standards for non-safety applications in a distributed VANET. Furthermore, Inter vehicle communication requires the use of wireless standard which support high data rate along with better communication range in sparse as well as in dense situation. The paper provides study of different wireless standards supported by VANET and compare their parameters (range, data rate, and frequency band). Finally, the survey recommends the best suitable wireless standards for non-safety applications both real time and simulation time environment. Index Terms — Intelligent transportation systems (ITS ), nonsafety applications, radio access technologies (RAT).
What Do We Need to Know to Enhance the Environmental Sustainability of Agricultural Production? A Prioritisation of Knowledge Needs for the UK Food System

Increasing concerns about global environmental change and food security have focused attention on the need for environmentally sustainable agriculture. This is agriculture that makes efficient use of natural resources and does not degrade the environmental systems that underpin it, or deplete natural capital stocks. We convened a group of 29 ‘practitioners’ and 17 environmental scientists with direct involvement or expertise in the environmental sustainability of agriculture. The practitioners included representatives from UK industry, non-government organizations and government agencies. We collaboratively developed a long list of 264 knowledge needs to help enhance the environmental sustainability of agriculture within the UK or for the UK market. We refined and selected the most important knowledge needs through a three-stage process of voting, discussion and scoring. Scientists and practitioners identified similar priorities. We present the 26 highest priority knowledge needs. Many of them demand integration of knowledge from different disciplines to inform policy and practice. The top five are about sustainability of livestock feed, trade-offs between ecosystem services at farm or landscape scale, phosphorus recycling and metrics to measure sustainability. The outcomes will be used to guide on-going knowledge exchange work, future science policy and funding.
Spontaneous Slow Potential Fluctuations in the Limulus Photoreceptor

Spontaneous, subthreshold fluctuations of membrane potential are recorded in the eccentric cell body or dendrite of the dark-adapted Limulus ommatidium. These slow potential fluctuations (SPF's) are random in amplitude and in time of occurrence. The relation between average frequency of SPF's and light intensity is linear for low light intensities and becomes a non-linear saturation for higher intensities. The occurrences of SPF's have Poisson statistics in the dark but are non-Poisson with light stimuli. Light-adapting the ommatidium greatly decreases the SPF amplitude, and it increases the average frequency of SPF's in the dark and in response to light (facilitatory action). The shape (time course of response) of the SPF does not change at different light intensities and it is the result of a concurrent and conterminous change in membrane resistance. The functional properties of the SPF's are analyzed in terms of a stochastic model based on the summation of random events in time ("shot effect").
Energy Harvesting for Structural Health Monitoring Sensor Networks

This paper reviews the development of energy harvesting for low-power embedded structural health monitoring (SHM) sensing systems. A statistical pattern recognition paradigm for SHM is first presented and the concept of energy harvesting for embedded sensing systems is addressed with respect to the data acquisition portion of this paradigm. Next, various existing and emerging sensing modalities used for SHM and their respective power requirements are summarized followed by a discussion of SHM sensor network paradigms, power requirements for these networks, and power optimization strategies. Various approaches to energy harvesting and energy storage are discussed and limitations associated with the current technology are addressed. The paper concludes by defining some future research directions that are aimed at transitioning the concept of energy harvesting for embedded SHM sensing systems from laboratory research to field-deployed engineering prototypes. Finally, it is noted that many of the technologies discussed herein are applicable to powering any type of low-power embedded sensing system regardless of the application.
A New Construction of Massey-Omura Parallel Multiplier over GF(2m)

The Massey-Omura multiplier of GF(2/sup m/) uses a normal basis and its bit parallel version is usually implemented using m identical combinational logic blocks whose inputs are cyclically shifted from one another. In the past, it was shown that, for a class of finite fields defined by irreducible all-one polynomials, the parallel Massey-Omura multiplier had redundancy and a modified architecture of lower circuit complexity was proposed. In this article, it is shown that, not only does this type of multiplier contain redundancy in that special class of finite fields, but it also has redundancy in fields GF(2/sup m/) defined by any irreducible polynomial. By removing the redundancy, we propose a new architecture for the normal basis parallel multiplier, which is applicable to any arbitrary finite field and has significantly lower circuit complexity compared to the original Massey-Omura normal basis parallel multiplier. The proposed multiplier structure is also modular and, hence, suitable for VLSI realization. When applied to fields defined by the irreducible all-one polynomials, the multiplier's circuit complexity matches the best result available in the open literature.
Community Detection by Affinity Propagation

Community structure in networks indicates groups of vertices within which are dense connections and between which are sparse connections. Community detection, an important topic in data mining and social network analysis, has attracted considerable research interests in recent years. Motivated by the idea that community detection is in fact a clustering problem on graphs, we propose several similarity metrics of vertex to transform a community detection problem into a clustering problem, and further adopt a recently-proposed clustering method, namely ‘Affinity Propagation’, to extract communities from graphs. We demonstrate that the method achieves significant quality in detecting community structures in both computer-generated and real-world network data in near-linear time. Furthermore, the method could automatically determine the number of communities.
MERBIS - A Multi-Objective Evolutionary Rule Base Induction System

Classifier induction is a specific data-mining task that is pa rt of the knowledge discovery process. Its objectives are to extract ac urate, comprehensible and interesting knowledge. However, most classifier i nduction approaches focus only on one of these objectives. This paper introduces a Multi-Objective Evolutionary Rule Base Induction System (MERBIS) that is ca pable of optimising both, accuracy and comprehensibility objectives at the same time. We investigate different parameter sets for this approach and valid ate its performance on several benchmark data sets.
Self-employed Income Under-reporting and Estimates of the Black-Economy: Britain - 1987 & 1992

This paper seeks to present some upper and lower bound estimates of the extent of self-employed income under-reporting in Britain in 1987 and 1992, and hence to infer an approximate estimate for the size of Britain's black economy. The methodology to be utilized is taken from Pissarides and Weber (1989), and seeks to analyze discrepancies between the expenditures and incomes reported by employee and self-employed households in a Family Expenditure Survey. The fundamental approach is to estimate food expenditure functions for both income groups which are then inverted to obtain our estimates. Various econometric caveats need to be addressed in the estimations.
Assessing contention effects of all-to-all communications on clusters and grids

One of the most important collective com- munication patterns used in scientific applications is the complete exchange, also called All-to-All. Although ecient algorithms have been studied for specific net- works, general solutions like those available in well- known MPI distributions (e.g. the MPI_Alltoall op- eration) are strongly influenced by the congestion of network resources. In this paper we present an inte- grated approach to model the performance of the All- to-All collective operation, which consists in identifying a contention signature that characterizes a given net- work environment, using it to augment a contention- free communication model. This approach, assessed by experimental results, allows an accurate prediction of the performance of the All-to-All operation over dierent network architectures with a small overhead. We also discuss the problem of network contention in a grid environment, studying some strategies to minimize the impact of contention on the performance of an All- to-All operation.
Analysis and Reflection on the Security of Biometrics System

On the basis of security analysis on biometrics mechanism and realization, in the view of system security, this paper studies and discusses the security of biometrics completely and deeply, especially to make a deep analysis on biometrics unity, uniqueness and across-system replay attack, so as to put forward a biometrics security model.
Mixed Criticality Systems - A Review

This review covers research on the topic of mixed criticality systems that has been published since Vestal’s 2007 paper. It covers the period up to and including December 2015. The review is organised into the following topics: introduction and motivation, models, single processor analysis (including job-based, hard and soft tasks, fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, related topics, realistic models, formal treatments, and systems issues. An appendix lists funded projects in the area of mixed criticality.
2016 Ieee International Conference on Big Data (big Data) Automated Port Traffic Statistics: from Raw Data to Visualisation

—We describe how we leveraged best practices in big data processing pipeline design and visual analytics to prototype the Maritime Patterns-of-Life Information Service (MPoLIS), an information product currently under development at the NATO Centre for Maritime Research and Experimentation (CMRE). MPoLIS supports the maritime industry, governments, and international organizations with visual analytics on vessel traffic in seaports. It addresses three main requirements: a) storing and processing large amounts of data; b) on-demand availability of statistical summaries of vessel traffic in ports; c) intuitive and interactive interface for subject matter experts (SMEs) in the maritime domain. MPoLIS has contributed to building a data-driven, self-service analytics culture within NATO and has been sanctioned for use in support of maritime situational awareness (MSA) in ongoing NATO operations. Readers outside of the maritime shipping industry often do not realize the fundamental role of maritime trade in the global economy: 80% of global trade is by sea, far and away the most dominant method for transporting goods globally. Given its importance, maritime commerce stakeholders are diverse, and include national government, international organizations , policy advisors, security and safety agencies, vessel operators, port authorities, and trade analysts just to name a few. In the past, a stakeholder seeking to understand maritime patterns could rely on few sources of information, which limited the achievable analyses, but also kept the analyst's daily workflow to manageable levels. Today, this is not the case any more. Big maritime data are now the norm, generated from the Automatic Identification System [1], radar, port visit and vessel registries, and ever-more connected databases and more accessible repositories. We argue that the maritime domain is undergoing a transformation akin to the nascent Internet of Things. The abundance and availability of maritime data afford the promise of more sophisticated analyses and more timely, actionable insights than previously possible. However, huge amounts of data overwhelm the end user and challenge the established analysis workflows. To make sense of, and gain advantage from big maritime data, stakeholders must rely on summary statistics and representative Patterns of Life (PoLs) to understand the organic behavior of maritime traffic, infer general trends, and extract the key indicators related to trade, safety, regulatory compliance, and day-today vessel and port operations. Examples of such indicators are cargo throughput, fishing activity, types of goods transported , piracy and suspicious activity risk assessments, and connectivity measures between ports at local, regional, and global scales. …
Understanding and Predicting Online Food Recipe Production Patterns

Studying online food patterns has recently become an active field of research. While there are a growing body of studies that investigate how online food in consumed, little effort has been devoted yet to understand how online food recipes are being created. To contribute to this lack of knowledge in the area, we present in this paper the results of a large-scale study that aims at understanding how historical, social and temporal factors impact on the online food creation process. Several experiments reveal the extent to which various factors are useful in predicting future recipe production.