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In the wake of policy, technology, and ideological disruptions in Western higher education, it is in universities’ interests to improve the quality of their learning and teaching to meet changed expectations. In some countries, particularly anglophone countries such as Australia, Canada, New Zealand, and the United Kingdom, the medium for this improvement is often professional development of academic staff provided through a Graduate Certificate in Higher Education (GCHE). This paper presents mixed methods research conducted at an Australian University. It addresses the questions of how a GCHE contributes to teaching quality and the Scholarship of Teaching and Learning (SoTL) from the perspective of course participants and their educators in the context of a university wide strategy to promote a culture of excellence in learning and teaching. Data and analysis indicate significant benefits to academic staff, their students, and the host institution from completion of a GCHE. However, tensions around academic workloads, compulsion, and some contradictions in espoused educational values and managerialist impositions emerge in these advancements. The educators in the GCHE (academic developers) were sometimes caught in the crossfire. Their reflections on this experience are included in the data and analysis.

China is the most productive seaweed farming country in the world and her seaweed imports and exports have a significant impact on global seaweed trade commodities and food security. Nevertheless, few studies had delved into the main characteristics and development of China's seaweed farming industry. This paper aims to narrow this research gap by analyzing trade patterns in China's seaweed products and the international competitiveness of seaweed product by using the international market share index (IMS), the trade competitiveness index (TC), and revealed comparative advantage index (RCA) from 2002 to 2017. The results showed that Japan, the Association of Southeast Asian Nations (ASEAN), Chile, Peru, and the Republic of Korea are China's main trade partners, the total trade value of China's seaweed products has grown rapidly, its imports have gradually exceeded exports, the trade deficit continues to expand, and its competitiveness keeps decreasing. The reasons for this trend may include the changing seaweed trade commodity structure, product differentiation, increased government support in competing countries, and trade barriers among the trade partners. We propose actively expanding international trade markets, establishing a strong seaweed product processing industry to develop high value-added seaweed products, optimizing the trade commodity structure, and differentiating of seaweed products to improve the competitiveness of China's seaweed products.

A computational analysis using Artificial Intelligence techniques has drawn its attention in Industrial Revolution 4.0. There are self-regulating and integrating processes involved. The commonly used control method involves single-loop feedback control. Embedding feedforward algorithm is aimed to improve the steady state response of the controlled process without affecting the performance of transient response. Apart of it, two optimal tunings are respectively applied to suit to the different control objectives. Correlation PID tunings are applied to respective objective somehow is very relying to the engineering experience and skills. This paper proposed using Genetic Algorithm for optimization analysis to search a trade-off optimized PI controller settings, which reduces dependency on skills as well as provide better insights to all practical engineers for commending effective PI tunings to the real control practices of plants. Initially, the respective process and disturbance models of LOOP-PRO software for both Jacketed-reactor and Pumped-tank were developed. Then, the simulation analysis of PI tunings was conducted to feedback control, feedforward and feedback and Genetic Algorithm scheme. Relative performance was compared in terms of graphs, performance index, and performance indicator. It is concluded that Genetic Algorithm has consistently provided a trade-off optimized PI controller settings for both Jacketed-reactor and Pumped-tank.

The conventional wisdom is that American universities transfer technologies more rapidly and more effectively than their European counterparts. While this appears to be true, it is important to note that there are substantial cultural, legal, and regulatory differences between the two regions, and even within Europe. We believe that European universities can enhance their effectiveness in technology transfer if this function is given more visibility and prestige, enhanced public support, and formal procedures are implemented to facilitate benchmarking. In this paper, we examine some of the differences in university technology transfer in Europe and the U.S., and discuss these new approaches, which have recently been fully supported by the European Commission.

The paper describes the results of a 3-year study of a social housing organization in England, tracing its transition from local authority-financed social agency into an ‘independent’ social business financed by lenders and following a merger its further transition into a complex business managing £200 million of assets. The study is concerned with the accountability to and by a quasi-public sector Board and how that Board was (or was not) able to exercise effective governance. It asks: Who is accountable? To whom are they accountable? For what are they accountable? The paper builds on the contrast made by Roberts [Acc. Organ. Society 16 (1991) 355; J. Roberts, From discipline to dialogue: individualizing and socializing forms of accountability, in: R. Munro, J. Mouritsen (Eds.), Accountability: Power, Ethos and the Technologies of Managing, International Thomson Business Press, London, 1996; Hum. Relat. 54 (2001) 1547] between a formal, hierarchical system of accountability based on a calculative accounting, and an informal, socializing form of accountability based on a sense-making narrative. The research identifies the limitations of accounting reports and the inadequacy of the narratives surrounding management/Board interaction. The paper identifies a space between the calculative and the narrative that is vacant and where governance is problematic and which impedes broader social accountabilities.

Aim: of this paper is to review the recent literature on the relationship between ectopic fat accumulation and cardiovascular disease. Data synthesis: Ectopic fat is an important predictor of metabolic (in particular insulin resistance) and cardiovascular disease, carrying more risk than general fat accumulation. Recent studies have shown a link between ectopic fat accumulation, as cardiac (epicardial or intra-myocardial fat) and/or visceral and/or hepatic fat, and development of atherosclerosis, coronary heart disease and hypertension. Conclusions: Ectopic fat accumulation is not only a marker of cardiometabolic disease, since through the release of adipocitokines, lipotoxic and glucotoxic agents, participates in the crosstalk with insulin-sensitive organs leading to metabolic, cardiac and vascular dysfunctions., This article version may be used for non-commercial purposes in accordance with CC BY-NC-ND license terms and conditions.

This is the unformatted version of the accepted review paper manuscript "Extended criteria grafts and emerging therapeutics strategy in liver transplantation. The unstable balance between damage and repair" published on Transplant Rev (Orlando)2021 Dec;35(4):100639. doi: 10.1016/j.trre.2021.100639., by Ghinolfi D, Melandro F, Torri F, Martinelli C, Cappello V, Babboni S, Silvestrini B, De Simone P, Basta G,Del Turco S. Due to increasing demand for donor organs, "extended criteria" donors are increasingly considered for liver transplantation, including elderly donors and donors after cardiac death. The grafts of this subgroup of donors share a major risk to develop significant features of ischemia reperfusion injury, that may eventually lead to graft failure. Ex-situ machine perfusion technology has gained much interest in liver transplantation, because represents both a useful tool for improving graft quality before transplantation and a platform for the delivery of therapeutics directly to the organ. In this review, we survey ongoing clinical evidences supporting the use of elderly and DCD donors in liver transplantation, and the underlying mechanistic aspects of liver aging and ischemia reperfusion injury that influence graft quality and transplant outcome. Finally, we highlight evidences in the field of new therapeutics to test in MP in the context of recent findings of basic and translational research.

This paper discusses the digital automation workflows and co-design methods that made possible the comprehensive robotic prefabrication of the BUGA Wood Pavilion - a large-scale production case study of robotic timber construction. Latest research in architectural robotics often focuses on the advancement of singular aspects of integrated digital fabrication and computational design techniques. Few researchers discuss how a multitude of different robotic processes can come together into seamless, collaborative robotic fabrication workflows and how a high level of interaction within larger teams of computational design and robotic fabrication experts can be achieved. It will be increasingly important to discuss suitable methods for the management of robotics and computational design in construction for the successful implementation of robotic fabrication systems in the context of the industry. We present here how a co-design approach enabled the organization of computational design decisions in reciprocal feedback with the fabrication planning, simulation and robotic code generation. We demonstrate how this approach can implement direct and curated reciprocal feedback between all planning domains - paving the way for fast-paced integrative project development. Furthermore, we discuss how the modularization of computational routines simplify the management and computational control of complex robotic construction efforts on a per-project basis and open the door for the flexible reutilization of developed digital technologies across projects and building systems., European Regional Development Fund, Deutsche Forschungsgemeinschaft, Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg, Projekt DEAL, Bundesgartenschau Heilbronn 2019 GmbH, GETTYLAB

This research opinion paper advocates for a new system of treating viral infections and diseases, it lays more emphasis on the current virus called Covid -19 virus (Corona Virus), it is a new innovation different from the known methods of treating viral infections and diseases. Some of the known methods include use of vaccines, anti -viral medication, monoclonal, serology. Most recently, stem cells have proved to be very effective in solving complex medical diseases such as leukemia, cancer and a host of other medical diseases that pose difficult challenges to the medical field. This method could be used to cure covid-19 permanently and then simulated to solve and cure other viral infections such as HIV and AIDS, Ebola, Hanta Virus and a host of other diseases like Malaria, Chicken-Pox, Small Pox, Measles etc. It is worthy to note that viruses are always evolving by way of mutation and are developing intelligent and strategic ways to beat or avoid being detected by the immune system, this can be seen in HIV and AIDS virus which attacks CD4 cells and even goes as far as engaging and fighting to wear down the T-Cells. Also, Covid -19 tries to proofread the cells to counter anti-viral drugs such as Ribavirin. Although Remdesivir anti-viral medication which has proven to work on some covid-19 patients, cannot be proofread by the corona virus. More insight about this "Autologous stem cells trapping mechanism" is discussed under conceptual framework of this research paper and attention should also be given to the suggestions and recommendations as they hold potential methods to permanently stop the actions of viruses in invading the human cells.

All education systems, to a greater or lesser extent, are marked by educational inequalities. Nearly all education systems, again to a greater or lesser extent, have put in place a variety of ‘compensatory’ strategies to help reduce these educational inequalities. These strategies have gone through different phases and enjoyed different degrees of support, but have generally been as much a part of the education system as the inequalities they are designed to address. This paper explores the continuing reinvention and failure of compensatory education strategies. It looks, in particular, at the emergence and limits of recent moves to implement a ‘politics of recognition’ for schools in disadvantaged areas. It argues that children in disadvantaged schools need a ‘politics of redistribution’, but that the mechanisms of distribution and the nature of what it is that is to be redistributed are problematic. Drawing on theory and empirical research, the paper concludes by arguing that, until we have a clearer idea of what it is that we are compensating, compensatory education policies will be doomed to fail.

In this paper we present a new classification method based on Dictionary Learning (DL). The main contribution consists of a kernel version of incoherent DL, derived from its standard linear counterpart. We also propose an improvement of the AK-SVD algorithm concerning the representation update. Our algorithms are tested on several popular databases of classification problems.

Edge computing is projected to become the dominant form of cloud computing in the future because of the significant advantages it brings to both users (less latency, higher throughput) and telecom operators (less Internet traffic, more local management). However, to fully unlock its potential at scale, system designers and automated optimization systems alike will have to monitor closely the dynamics of both processing and communication facilities. Especially the latter is often neglected in current systems since network performance in cloud computing plays only a minor role. In this paper, we propose the architecture of MECPerf, which is a solution to collect network measurements in a live edge computing domain, to be collected for offline provisioning analysis and simulations, or to be provided in real-time for on-line system optimization. MECPerf has been validated in a realistic testbed funded by the European Commission (Fed4Fire+), and we describe here a summary of the results, which are fully available as open data and through a Python library to expedite their utilization. This is demonstrated via a use case involving the optimization of a system parameter for migrating clients in a federated edge computing system adopting the GSMA platform operator concept.

The wide availability of embedded sensor platforms and lowcost cameras—together with the developments in wireless communication—make it now possible the conception of pervasive intelligent systems based on vision. Such systems may be understood as distributed and collaborative sensor networks, able to produce, aggregate and process images in order to understand the observed scene and communicate the relevant information found about it. In this paper, we investigate the peculiarities of visual sensor networks with respect to standard vision systems and we identify possible strategies to accomplish image processing and analysis tasks over them. Although the rather strong constraints in computational and transmission power of embedded platforms that may prevent the use of state of the art computer vision and pattern recognition methods, we argue that multinode processing methods may be envisaged to decompose a complex task into a hierarchy of computationally simpler problems to be solved over the nodes of the network. These ideas are illustrated by describing an application of visual sensor network to infomobility. In particular, we consider an experimental setting in which several views of a parking lot are acquired by the sensor nodes in the network. By integrating the various views, the network is capable to provide a description of the scene in terms of the available spaces in the parking lot.

Short-range wireless technologies will enable vehicles to communicate and coordinate their actions, thus improving people's safety and traffic efficiency. Whereas IEEE 802.11p (and related standards) had been the only practical solution for years, in 2016 a new option was introduced with Release of 14 long-term evolution (LTE), which includes new features to enable direct vehicle-to-vehicle (V2V) communications. LTE-V2V promises a more efficient use of the channel compared to IEEE 802.11p, thanks to an improved PHY layer and the use of orthogonal resources at the MAC layer. In LTE-V2V, a key role is played by the resource allocation algorithm and increasing efforts are being made to design new solutions to optimize the spatial reuse. In this context, an important aspect still little studied, is therefore that of identifying references that allow, first, to have a perception of the space in which the resource allocation algorithms move and, second, to verify the performance of new proposals. In this paper, we focus on a highway scenario and identify two algorithms to be used as a minimum and maximum reference in terms of the packet reception probability (PRP). The PRP is derived as a function of various parameters that describe the scenario and settings, from the application to the physical layer. Results, obtained both in a simplified Poisson point process scenario and with realistic traffic traces, show that the PRP varies considerably with different algorithms and that there is room for the improvement of current solutions.

none 12 si In this paper we present D.A.V.I.D.E. (Development for an Added Value Infrastructure Designed in Europe), an innovative and energy efficient High Performance Computing cluster designed by E4 Computer Engineering for PRACE (Partnership for Advanced Computing in Europe). D.A.V.I.D.E. is built using best-in-class components (IBM’s POWER8-NVLink CPUs, NVIDIA TESLA P100 GPUs, Mellanox InfiniBand EDR 100 Gb/s networking) plus custom hardware and an innovative system middleware software. D.A.V.I.D.E. features (i) a dedicated power monitor interface, built around the BeagleBone Black Board that allows high frequency sampling directly from the power backplane and scalable integration with the internal node telemetry and system level power management software; (ii) a custom-built chassis, based on OpenRack form factor, and liquid cooling that allows the system to be used in modern, energy efficient, datacenter; (iii) software components designed for enabling fine grain power monitoring, power management (i.e. power capping and energy aware job scheduling) and application power profiling, based on dedicated machine learning components. Software APIs are offered to developers and users to tune the computing node performance and power consumption around on the application requirements. The first pilot system that we will deploy at the beginning of 2017, will demonstrate key HPC applications from different fields ported and optimized for this innovative platform. open Abu Ahmad, Wissam; Bartolini, Andrea; Beneventi, Francesco; Benini, Luca; Borghesi, Andrea; Cicala, Marco; Forestieri, Privato; Gianfreda, Cosimo; Gregori, Daniele; Libri, Antonio; Spiga, Filippo; Tinti, Simone Abu Ahmad, Wissam; Bartolini, Andrea; Beneventi, Francesco; Benini, Luca; Borghesi, Andrea; Cicala, Marco; Forestieri, Privato; Gianfreda, Cosimo; Gregori, Daniele; Libri, Antonio; Spiga, Filippo; Tinti, Simone

Background Workplace absenteeism increases significantly during influenza epidemics. Sick leave records may facilitate more timely detection of influenza outbreaks, as trends in increased sick leave may precede alerts issued by sentinel surveillance systems by days or weeks. Sick leave data have not been comprehensively evaluated in comparison to traditional surveillance methods. The aim of this paper is to study the performance and the feasibility of using a detection system based on sick leave data to detect influenza outbreaks. Methods Sick leave records were extracted from private French health insurance data, covering on average 209,932 companies per year across a wide range of sizes and sectors. We used linear regression to estimate the weekly number of new sick leave spells between 2016 and 2017 in 12 French regions, adjusting for trend, seasonality and worker leaves on historical data from 2010 to 2015. Outbreaks were detected using a 95%-prediction interval. This method was compared to results from the French Sentinelles network, a gold-standard primary care surveillance system currently in place. Results Using sick leave data, we detected 92% of reported influenza outbreaks between 2016 and 2017, on average 5.88 weeks prior to outbreak peaks. Compared to the existing Sentinelles model, our method had high sensitivity (89%) and positive predictive value (86%), and detected outbreaks on average 2.5 weeks earlier. Conclusion Sick leave surveillance could be a sensitive, specific and timely tool for detection of influenza outbreaks.

This paper presents the results of cement-based mortars characterizations that were taken from rendered layers of military bunkers in the Rupnik Line. The Rupnik Line was conceived as a part of the fortified defence system protecting the Rapallo Border between the Kingdom of Italy and the Kingdom of Yugoslavia, established in 1920. The bunkers were built between 1938 and 1941, and the renders of various compositions were applied as a camouflage layer that merged the bunkers with the environment. Results of petrographic examination and microstructural and chemical analysis of the samples confirmed that locally available crushed dolomite or limestone sands were used as an aggregate in the mortars. As binders, pure Portland cement or a mixture of cement and ground granulated blast furnace slag were used. The selection of the aggregate and binder type in a particular mortar was based on the colour of the artificial stone produced. All samples with the dolomite aggregate show the presence of alkali-aggregate reactions, dedolomitization of the grains and secondary calcite formation in the cement binder, along with the Mg-Al, Mg-Si and Mg-Al-Si phase formations. In mortar compositions with a high Portland cement content, the presence of delayed ettringite formation was also confirmed.

Background: In a previous paper, we have demonstrated that: (1) local injection of corticosteroids for carpal tunnel syndrome (CTS) is as effective as decompressive surgery, at 1-year follow-up; and (2) surgery has an additional benefit in the 2-year follow-up. In this study, we assess the long-term outcomes of both therapies in an observational extension of the patients originally enrolled in our randomized clinical trial. Methods: Patients were included in an open, randomized clinical trial, comparing injections versus surgery in CTS. After the end of the clinical trial, patients received the treatment prescribed by their general practitioner or specialist. Therapeutic failure was defined as the need of any new therapeutic intervention on the involved wrist. Comparison between groups was made using Cox multiple regression analysis. Estimation of the accumulated incidence of new therapeutic failure was made considering the withdrawal as a competitive risk (Gooley’s test). Results: Of 163 randomized wrists at the beginning of the study, only 148 were available at the final follow-up. The mean follow-up was 6.3 and the median was 5.9 years. In the long-term follow-up, the accumulated incidence of therapeutic failure in the surgery group was 11.6% versus 41.8% in the injection group. The Cox multiple regression analysis showed a risk of failure associated with injection group of 4.5 (95% confidence interval [CI], 2.1-9.8; P < .0001). Conclusions: In long-term follow-up, surgery seems more effective than local corticosteroid injections in primary CTS. Nonetheless, about 58% of the patients in the injection group will not need further therapeutic interventions during the follow-up.

The rolling element skidding may lead to the failure of the rolling bearing. The skidding characteristics can be effectively analyzed by using dynamic response of the rolling bearing. A dynamic model is established to investigate the vibration response of the rolling bearing with local defect on inner/outer race in this paper. In the proposed model, the rolling element skidding, contact stiffness and displacement, the interaction force between ball and race, the interaction force between cage and race, elastohydrodynamic lubrication are taken into consideration. The dynamic responses of the rolling bearing with the rolling element skidding are solved by the proposed model in the time and frequency domains. The effects of defect size, rotational speed, external load, and compound factors on skidding characteristics are investigated. The proposed model is verified by the experiments. The results show that the rolling element skidding leads to the significant difference of dynamic characteristics in the time and frequency domains, which aggravates the failure of the rolling bearings.

Extant research suggests that the most significant elements of a family firm’s socioemotional wealth (SEW) can drive financial reporting decisions. This paper explores this empirically by analyzing corporate disclosures of a case organization – Guinness, a multinational family brewing firm – over an extended period. We identify the presence of the SEW dimensions in the firm’s corporate disclosures and explore the relationship between the most salient SEW dimension (family identity) and readability, measured by the Bog index. The analysis finds a positive association between family identity and readability in the period when the firm under study can be defined as a family firm. Other SEW dimensions do not appear to have an influence on readability. In addition, at the end of the period of study, when the firm under study ceased to be a family firm, the SEW dimensions failed to have an effect on readability.

With the imminent digitalisation of the manufacturing processes of gas turbine components, a large volume of geometric data of as-manufactured parts is being generated. This geometric data can be used in aerodynamic simulations to predict component performance. Both the cost and accuracy of these simulations increase with their fidelity. To efficiently exploit Digital Twin technology, one must therefore understand how realistic the aerodynamic simulations need to be to give useful performance predictions. This paper considers this issue for a sample of scrapped high-pressure turbine rotor blades from a civil aero engine. The measured geometric data was used to build aerodynamic models of varying degrees of realism, ranging from quasi-three-dimensional blade sections for an Euler solver to three-dimensional, multi-passage and multi-stage Reynolds-Averaged-Navier-Stokes models. The flow near the tip of these shrouded blades is sensitive to manufacturing variability and can switch between two quasi-stable horseshoe vortex modes. In general, capacity and exit flow angle can be adequately predicted by three-dimensional, single-passage calculations: averaging single-passage calculations gives a good prediction of the multi-passage behaviour. For efficiency and stage loading, the approach of averaging single-passage calculations is less accurate as the multi-passage behaviour requires an accurate prediction of the horseshoe vortex modes.

This paper examines ethics in international trade from several different ethical perspectives, including consequentialism, utilitarianism, virtue ethics and deontology. The views of Aristotle, Plato, Adam Smith, Bentham, Kant, Pareto, Rawls, Flew, Nozick, Bastiat and others are discussed and contrasted. Flow charts are provided to reflect the utilitarian and rights approaches to trade. Utilitarianism is shown to be structurally deficient for several reasons that cannot be overcome. Antidumping laws and sanctions are shown to be negative-sum games. Antidumping laws are seen for what they are, tools of rent-seeking in which some influential minority seeks to use the powers of government to protect them from competition, which harms the vast majority of the population. Any trade restrictions must necessarily violate someone’s property, contract and/or association rights. The only way to achieve a just trade policy is to allow individuals, and the corporations that represent them, to trade what they have for what they want without government interference. The view that trade deficits are bad and trade surpluses are good is dismantled. The present paper also includes a bibliography on trade, including links to more than 100 studies on trade.

Difference types of DC-DC converter are used in various electronic devices and applications for so many years. But conventional converter cannot afford in high voltage and high current applications. Many researchers have been tried to full-fill the requirements. In this paper, dual stage double boost DC-DC converter is used for data center, high voltage vehicles and renewable system. Many control methods are developed for the control of DC-DC converter. To obtain a control method has the best performance under any condition is always demand. The main objective of this paper is to study the voltage mode control of proposed converter based on fuzzy logic controller (FLC) under the response of different parameters of proposed converter using Matlab/Simulink Software. &nbsp

In this paper, we present SoDa, an irradiance-based synthetic Solar Data generation tool to generate realistic sub-minute solar photovoltaic (PV) output power time series, that emulate the weather pattern for a certain geographical location. Our tool relies on the National Solar Radiation Database (NSRDB) to obtain irradiance and weather data patterns for the site. Irradiance is mapped onto a PV model estimate of a solar plant’s 30-min power output, based on the configuration of the panel. The working hypothesis to generate high-resolution (e.g. 1 second) solar data is that the conditional distribution of the time series of solar power output given the cloud density is the same for different locations. We therefore propose a stochastic model with a switching behavior due to different weather regimes as provided by the cloud type label in the NSRDB, and train our stochastic model parameters for the cloudy states on the high-resolution solar power measurements from a Phasor Measurement Unit (PMU). In the paper we introduce the stochastic model, and the methodology used for the training of its parameters. The numerical results show that our tool creates synthetic solar time series at high resolutions that are statistically representative of the measured solar power and illustrate how to make use of the tool to create synthetic data for arbitrary sites in the footprint covered by the NSRDB.

International audience; The industrial internet of things (IIoT) known as industry 4.0, is the use of internet of things technologies, via the Wireless Sensor Network (WSN), to enhance manufacturing and industrial processes. It incorporates machine learning and big data technologies, to allow machine-to-machine communication that have existed for years in the industrial world. Therefore, it is necessary to propose a robust and functional communication architecture that is based on WSNs, inside factories, in order to show the great interest in the connectivity of things in the industrial environment. In such environment, propagation differs from other conventional indoor mediums, in its large dimensions, and the nature of objects and obstacles inside. Thus, the industrial medium is modeled as a fading channel affected by an impulsive and Gaussian noise. The objective of this paper is to improve robustness and performances of multi-user WSN architecture, based on Discrete Wavelet Transform, under an industrial environment using conventional channel coding and an optimal thresholding receiver.

A major drawback of nonlinear dimensionality reduction (DR) techniques is their inability to preserve some authentic information from the source domain, leading to projections that are often hard to interpret when it comes to observing anything other than the topological structure of the data. In this paper, we propose a nonlinear DR approach enforcing projection constraints resulting from an a priori knowledge about the structure of the data in multivariate periodical time series. We then propose several ways of exploiting this constrained projection to extract user-relevant information, such as the nominal behavior of a periodical dynamical system or the deviant behaviors which may occur at different time scales. The techniques are demonstrated on both a synthetic dataset composed of simulated multivariate data exhibiting a periodical behavior, and a real dataset corresponding to six months of sensor data acquisitions and recordings inside experimental buildings. 1 We would like to thank the Institut National de l'Energie Solaire (INES) and the CEA, LITEN, Laboratoire Energetique du Bâtiment for providing the data.

It is still not well understood how the media affect anti-immigrant party voting. In this paper, we argue and demonstrate empirically that mere exposure to immigration- and crime-related news is positively related to the likelihood that a voter casts a vote for an anti-immigrant party. On the basis of a media content analysis (N = 20,084 news items) in combination with a voter panel survey (N = 17,014 respondents) conducted in 11 European countries we find for several anti-immigrant parties that – ceteris paribus – exposure to news about immigration or crime increases voters' probabilities to vote for these parties. We discuss our findings in light of prior research on issue ownership, and their implications for the role of the mass media in established democracies.

The refrigerant after the expansion valve interchanges the heat at the evaporator. At this moment, the state of gas and liquid becomes two-phase flow and causes irregular noise. In order to avoid the noise, the two-phase flow pattern should be predicted. In this paper, the procedure to predict the two-phase flow patterns such as churn flow and annular flow was suggested using the CFD software. The experiments using refrigerant-supplying equipment was carried out and the noise levels according to the flow pattern were measured. The flow patterns predicted by this procedure showed good agreement with those by experiments. The churn flow is noisier than annular flow pattern.

Resilient suppliers can reduce supply chain risk, effectively avoid supply chain disruption, and bring profits to enterprises. However, there is no united measuring index system to evaluate the resilient supplier under supply chain environment, and the assessment language sets are usually crisp values. Therefore, in order to fill the research gap, this paper proposes a hybrid method, which combines triangular fuzzy number, the best-worst method (BWM), and the modular TOPSIS in random environments for group decision-making (GMo-RTOPSIS) to solve the above problem. Firstly, the weight of decision-maker is calculated by using fuzzy BWM which can deal with triangular fuzzy numbers. Secondly, triangular fuzzy number is introduced into GMo-RTOPSIS, and combined with fuzzy BWM, alternatives are sorted to select the best resilient supply chain partner. Finally, the feasibility and universality of this method are proved by illustrative examples.

Numerous technologies have been developed in the agricultural sector to facilitate its contribution to the livelihood of the people. However, the adoption of these technologies has been very low or non-existence at all. This paper determined the important factors/variables that determine adoption behaviour. A validated, pre-tested structured questionnaire was used to collect data from 113 respondents, equivalent to 5 percent of a population selected to represent maize growers in selected villages of Njombe District. The collected data were analyzed using the statistical package for social sciences (SPSS) and the linear regression model was used to investigate the influence of the study variables. The study findings show both independent and intervening factors investigated determined the adoption behaviour. However, in all the technologies investigated the intervening factors influenced highly the adoption behaviour. The results presented provide sufficient evidence in supporting the relevance of intervening variables as the most important determinants of the adoption behaviour. The study suggests that emphasis be put on these variables in agricultural extension programs in order to enhance the adoption of technologies by farmers.

Small-scale commercial farmers are regarded as the strategic avenue to achieve meaningful development in rural areas of South Africa. The government acknowledged that the inclusion of small-scale commercial farming in its development strategies. The paper aims to measure the efficiency of small-scale commercial farming enterprises in Vhembe District in Limpopo Province. Quantitative data were collected from 217 small-scale commercial farmers using structured questionnaires. The data were standardized using a farming enterprise budget system and analysed using the maximum likelihood and stochastic frontier analysis. The results revealed that aggregate output was positive and significantly influenced by age, education level, farm experience, farm labour, and government grants. However, the projected stochastic production frontier model combined with the efficiency parameters showed that labour and credit computed a negative effect on technical efficiency. The results indicated that the average level of technical efficiency ranged between 20% and 96% with a mean of 54%. This indicates that there is potential to increase production among small-scale commercial farmers in the study area by 46 % through efficient use of existing resources. As such, the local government should provide necessary supports such as formal agriculture training, access to credit and information to increase productivity.

This paper presents existing linkages within the spheres of government on plant health institutional and legislative framework and further identifies the existing limitations and risks on the current existing framework on the plant health system. A survey was conducted in South Africa with the relevant scientists from the National Department of Agriculture, Land Reform and Rural Development (DALRRD) formerly known as the Department of Agriculture, Forestry and Fisheries (DAFF) and Department of Environment, Forestry and Fisheries (DAFF) formerly known as Department of Environmental Affair (DEA) as well as extensionist and agricultural advisors from 7 Provincial Departments of Agriculture (PDAs). The sample size of the study was 60 government officials from both the national and provincial departments of agriculture. A semi-structured questionnaire was used to collect the data. The data were analysed statistically using the one-way frequency and Spearman’s Rank correlation coefficients. This paper revealed that there were no formal linkages between the relevant national government and PDAs in terms of legislative and policy prescripts on plant health issues. The study further revealed that there is a need to establish a plant health unit to coordinate plant health matters from the National Plant Protection Organisation of South Africa. On the aspect of biosecurity legislative framework affecting food production and security as well as trade, the study found that there is no cross-referencing amongst relevant legislation; therefore, there is a need for harmonisation of relevant legislation.

The study reported on in this paper investigated smallholder farmers’ access to extension services. The study sought to distinguish the varying degrees of access to services of smallholder farmers engaged in different production systems, that is, home gardening, field cropping, and livestock production. The study was conducted in Raymond Mhlaba Local Municipality in the Eastern Cape, specifically in two communities, namely Ngcabasa and Phathikhala villages. Research activities included a survey of 100 farmers as well as focus group discussions. Employing logistic regression analysis, the study aimed to understand what influences whether or not a smallholder farmer accesses extension. The study also used various types of comparative statistics (T-test) to assess the implications of access to extension support, for instance for production and farm income. The main findings of the study were that 68% of the farming households interviewed in Ngcabasa and 71% of those in Phathikhala had access to extension services. Farmers who had access to extension had more farm income in both enterprises compared to those who had no access to extension services. From the regression analysis, farmers who were more likely to receive extension support appeared to be those who were older, those with less education, and those farming with livestock.

In this paper, we explore the challenging 1-to-N map matching problem, which exploits a compact description of map data, to improve the scalability of map matching techniques used by various robot vision tasks. We propose a first method explicitly aimed at fast succinct map matching, which consists only of map-matching subtasks. These tasks include offline map matching attempts to find a compact part-based scene model that effectively explains each map using fewer larger parts. The tasks also include an online map matching attempt to efficiently find correspondence between the part-based maps. Our part-based scene modeling approach is unsupervised and uses common pattern discovery (CPD) between the input and known reference maps. This enables a robot to learn a compact map model without human intervention. We also present a practical implementation that uses the state-of-the-art CPD technique of randomized visual phrases (RVP) with a compact bounding box (BB) based part descriptor, which consists of keypoint and descriptor BBs. The results of our challenging map-matching experiments, which use a publicly available radish dataset, show that the proposed approach achieves successful map matching with significant speedup and a compact description of map data that is tens of times more compact. Although this paper focuses on the standard 2D point-set map and the BB-based part representation, we believe our approach is sufficiently general to be applicable to a broad range of map formats, such as the 3D point cloud map, as well as to general bounding volumes and other compact part representations., Offprint of IROS2013 paper

The aim of this paper is to analyse the impact of land access and livelihood strategies of rural households to well-being of households ' implications to extension agents in Mnquma, Eastern Cape. A cross-sectional research design was utilised to collect data from 105 randomly selected households. Descriptive statistics was then used to profile livelihood strategies and characteristics such as age, gender, years of farm experience, the availability of water and land for crop production and the income farmers generate from the sale of crops produced. Multinomial logistic regression results demonstrated that land size and location have a positive significant influence (p = 0.001) on household well-being. It is concluded that though land size has a positive influence on well-being, expanding farms through adding plots and distant farming hinders the attainment of well-being. Moreover, households with large number of dependents and those working in exclusive farming are disadvantaged in the attainment of well-being. There is therefore room to enhance progress in attainment of well-being through reducing the distance to farms and promoting diversification of livelihood strategies. The Eastern Cape department of Agriculture and Rural Development is advised to support distant farmers with settlements in their destinations. Furthermore, extension agents do play a significant role in promoting livelihoods of rural households and contribute towards improved land access. Keywords: Land access, livelihood strategy, rural households, South Africa

International audience Parsing facade images requires optimal handcrafted grammar for a given class of buildings. Such a handcrafted grammar is often designed manually by experts. In this paper, we present a novel framework to learn a compact grammar from a set of ground-truth images. To this end, parse trees of ground-truth annotated images are obtained running existing inference algorithms with a simple, very general grammar. From these parse trees, repeated subtrees are sought and merged together to share derivations and produce a grammar with fewer rules. Furthermore, unsupervised clustering is performed on these rules, so that, rules corresponding to the same complex pattern are grouped together leading to a rich compact grammar. Experimental validation and comparison with the state-of-the-art grammar-based methods on four diff erent datasets show that the learned grammar helps in much faster convergence while producing equal or more accurate parsing results compared to handcrafted grammars as well as grammars learned by other methods. Besides, we release a new dataset of facade images from Paris following the Art-deco style and demonstrate the general applicability and extreme potential of the proposed framework.

This article summarises a recent virtual meeting organised by the Oxford University Clinical Research Unit in Vietnam on the topic of climate change and health, bringing local partners, faculty and external collaborators together from across the Wellcome and Oxford networks. Attendees included invited local and global climate scientists, clinicians, modelers, epidemiologists and community engagement practitioners, with a view to setting priorities, identifying synergies and fostering collaborations to help define the regional climate and health research agenda. In this summary paper, we outline the major themes and topics that were identified and what will be needed to take forward this research for the next decade. We aim to take a broad, collaborative approach to including climate science in our current portfolio where it touches on infectious diseases now, and more broadly in our future research directions. We will focus on strengthening our research portfolio on climate-sensitive diseases, and supplement this with high quality data obtained from internal studies and external collaborations, obtained by multiple methods, ranging from traditional epidemiology to innovative technology and artificial intelligence and community-led research. Through timely agenda setting and involvement of local stakeholders, we aim to help support and shape research into global heating and health in the region.

Simultaneous occurrences of diabetic ketoacidosis (DKA) and thyroid storm have long been known, but only a few cases have been reported to date. Both these endocrine emergencies demand timely diagnosis and management to prevent adverse outcomes. Due to the similarities in their clinical presentation, DKA can mask the diagnosis of thyroid storm and vice versa. This case report describes a patient with Graves’ disease who presented to the emergency department with nausea, vomiting and abdominal pain. He was found to have severe DKA without an explicit history of diabetes mellitus. Further evaluation revealed that the patient also had a concomitant thyroid storm that was the likely cause of his DKA. Early recognition and appropriate management of both conditions resulted in a favourable outcome. This paper emphasises that a simultaneous thyroid storm diagnosis should be considered in patients with DKA, especially those with a known history of thyroid disorders.

Background: Three decades after the amyloid cascade hypothesis was first proposed, research into discovery of effective treatments for Alzheimer's disease has not yet produced any disease-modifying treatments. Aims: This review outlines the progress made by dementia research thus far, and provides a brief overview of the therapeutic approaches resulting from the amyloid cascade hypothesis. It then describes the shift in research focus to the early stages of the condition, the challenges it presents and potential consequences for care. Methods: A literature overview was undertaken by reviewing research papers, published protocols and policy guidelines. Findings: Past research has failed to produce effective treatments for dementia, yet the causes of this failure remain debated. Discovery of affordable, early biomarkers has emerged as a key target of investigation as the focus has shifted from treatment to prevention of the condition. Conclusions: Failures in identifying effective treatments for dementia have highlighted the importance of earlyidentification and intervention in patients as a way to prevent neurodegeneration and progression to dementia. Discovery of biomarkers is a key focus of current research. In the future, regular screening for dementia may be recommended for all older people in an effort to assess individual risk. Care may reflect a combination of early pharmacological interventions and lifestyle modification programmesbased on risk.

In an ESP (English for Specific Purposes) and ELP (English for Legal Purposes) perspective, this paper studies the construction of professional cultural competence through the cultural substrata woven into the narrative of specialised popular fiction, or FASP.After a brief overview of the theoretical framework retained and the functions of a coroner in England and Wales, the discussion focuses on a coronial FASP, M. R. Hall’s The Coroner (2009), to analyse three cultural strands which relate meaningfully to ELP learner objectives: culture specific to the Coroner’s Office, broader social commentary with regard to issues concerning the legal community as a whole and, finally, locus-related societal and national cultures.The paper concludes by addressing reservations expressed regarding such randomly acquired knowledge by highlighting the advantages of a heuristic and semasiological approach in exploring both target and source culture. Dans le cadre de la didactique des langues et cultures spécialisées du droit, cet article porte sur la construction d’une compétence de culture professionnelle à travers les substrats culturels tissés dans la fibre narrative de la fiction populaire spécialisée, la FASP.Après une brève présentation du cadrage théorique retenu, du professionnel de droit qu’est le coroner au Royaume Uni et de la FASP juridique qui constitue l’objet d’étude, The Coroner (2009) de M. R. Hall, l’analyse dégage trois domaines culturels en lien avec les objectifs de l’apprentissage : la culture spécifique à l’environnement spécialisé du professionnel qu’est le coroner, le commentaire social enchâssé dans le récit qui se rapporte à la communauté juridique dans son ensemble et, finalement, les cultures relatives aux lieux qui servent d’ancrage géographique au récit fictif.Pour conclure, l’auteur répond aux réserves souvent exprimées concernant la nature fragmentaire des connaissances acquises par l’intermédiaire de la FASP en mettant en avant les avantages d’une approche heuristique et sémasiologique dans l’exploration des cultures cible et source.

In this paper, the optimum linear/nonlinear spring and linear/nonlinear damper force versus displacement and force versus velocity characteristic functions, respectively, are determined using simple lumped parameter models of a quarter car front independent suspension and a half car rear solid axle suspension of a light commercial vehicle. The complexity of a nonlinear function optimisation problem is reduced by determining the shape a priori based on typical shapes supplied by the car manufacturer and then scaling it up or down in the optimisation process. The vehicle ride and handling responses are investigated considering models of increased complexity. The linear and nonlinear optimised spring characteristics are first obtained using lower complexity lumped parameter models. The commercial vehicle dynamics software Carmaker is then used in the optimisation as the higher complexity, more realistic model. The performance of the optimised suspension units are also verified using this more realistic Carmaker model.

RESUMO Introdução: Tendo em consideração que a atividade de investigação em Comunicação cresceu fortemente nos últimos anos, como indicado por estudos anteriores, o presente trabalho visa estabelecer uma pesquisa em termos de produção científica nessa área. Objetivos: Esse artigo analisa a produção científica na área da Comunicação, entre 2007 e 2017, em revistas indexadas no primeiro quartil (Q1) e no segundo quartil (Q2) da base de dados Web of Science, pertencentes a autores com afiliação em instituições brasileiras. Metodologia: Foram identificadas as revistas de comunicação no InCities (JCR) pertencentes aos dois primeiros quartis, em seguida foi realizada uma busca por título de periódico na WoS e posteriormente o tratamento e normalização dos dados obtidos. Resultados: Observa-se um crescimento na produção científica em Comunicação, na projeção internacional, alimentando uma tradição em coautoria com redes internacionais. No período de 2014 a 2017, tenderam a publicar principalmente em inglês, frente às colaborações usuais que vinham mantendo com países de língua espanhola até 2014. Conclusão: Conclui-se, entre outras coisas, que o sistema de avaliação da Capes, quadrienal, pode ter influenciado a produção científica em Comunicação no intervalo estudado. ABSTRACT Introduction: Taking into consideration that research activity in Communication has grown strongly in recent years, as indicated by previous studies, the present work aims to establish a survey in terms of scientific production in this area. Objectives: This paper analyzes the scientific production in the area of Communication, between 2007 and 2017, in journals indexed in the first quartile (Q1) and second quartile (Q2) of the Web of Science database, belonging to authors with affiliation in Brazilian institutions. Methodology: Communication journals in InCities (JCR) belonging to the first two quartiles were identified, then a search by journal title in WoSff was performed and subsequently the treatment and normalization of the data obtained. Results: A growth in scientific production in Communication is observed, in international projection, feeding a tradition in coauthorship with international networks. In the period from 2014 to 2017, they tended to publish mainly in English, against the usual collaborations that they had been maintaining with Spanish-speaking countries until 2014. Conclusion: We conclude, among other things, that the Capes evaluation system, quadrennial, may have influenced the scientific production in Communication in the studied interval.

In this paper we describe a cyberattack against 2 well-known wearable devices. The attacker presented in this paper is an “honest but curious” Internet Service Provider (ISP) sitting somewhere in the path between the device and the cloud. The ISP launches the attack when the smartbands try to synchronize their data with the permanent cloud storage. By launching its attack, this “honest but curious” ISP is able to learn much personal information about the users of the smartbands, including the frequency of measuring the users’ heart rate and weight; the number and duration of workouts; as well as whether (i) sleep or (ii) steps were recorded on a given day. We show that privacy leaks might occur even when the transferred data are fully encrypted, and the representative mobile application utilizes state-of-the-art security mechanisms: certificate pinning, and source code obfuscation.

This study examined patterns of service use and payment methods for HIV/AIDS treatment using evidence from two data sources. The paper also compares the convergence of evidence from a household and exit survey among persons living with HIV/AIDS. The study was undertaken in Akwa Ibom, Anambra and Adamawa states in south-south, south-east and north-east geopolitical zones of Nigeria respectively. Using a household survey and an exit interview, questionnaires were administered to persons living with HIV who were 18 years and above. The health seeking patterns and payment methods were analysed. The findings showed some differences and similarities. In the exit survey, elicited check-up appointments were predominantly three monthly (35.5%) while about half (49.2%) of respondents from the household survey were on two monthly visits. During actual hospital visits, almost all respondents from exit (96.9%) and household survey (95.1%) received routine drugs for HIV/AIDS as appropriate. Out-of-pocket spending was the main method of payment in the two surveys. Variations exist across states in the patterns of treatment seeking and payment methods for HIV/AIDS but the overall findings from household and exit survey yield similar patterns. Hence, either of the methods may be used in a similar setting to obtain valid responses. However, innovative interventions are needed to reduce the incidence of opportunistic infections to limit the additional burden of hospitalization to patients.&nbsp

Today's blockchains suffer from low throughput and high latency, which impedes their widespread adoption of more complex applications like smart contracts. In this paper, we propose a novel paradigm for smart contract execution. It distinguishes between consensus nodes and execution nodes: different groups of execution nodes can execute transactions in parallel; meanwhile, consensus nodes can asynchronously order transactions and process execution results. Moreover, it requires no coordination among execution nodes and can effectively prevent livelocks. We show two ways of applying this paradigm to blockchains. First, we show how we can make Ethereum support parallel and asynchronous contract execution \emph{without hard-forks}. Then, we propose a new public, permissionless blockchain. Our benchmark shows that, with a fast consensus layer, it can provide a high throughput even for complex transactions like Cryptokitties gene mixing. It can also protect simple transactions from being starved by complex transactions.

This paper presents a collaboratively adaptive vibration monitoring system that captures high-fidelity structural vibration signals induced by pedestrians. These signals can be used for various human activities’ monitoring by inferring information about the impact sources, such as pedestrian footsteps, door opening and closing, and dragging objects. Such applications often require high-fidelity (high resolution and low distortion) signals. Traditionally, expensive high resolution and high dynamic range sensors are adopted to ensure sufficient resolution. However, for sensing systems that use low-cost sensing devices, the resolution and dynamic range are often limited; hence this type of sensing methods is not well explored ubiquitously. We propose a low-cost sensing system that utilizes (1) a heuristic model of the investigating excitations and (2) shared information through networked devices to adapt hardware configurations and obtain high-fidelity structural vibration signals. To further explain the system, we use indoor pedestrian footstep sensing through ambient structural vibration as an example to demonstrate the system performance. We evaluate the application with three metrics that measure the signal quality from different aspects: the sufficient resolution rate to present signal resolution improvement without clipping, the clipping rate to measure the distortion of the footstep signal, and the signal magnitude to quantify the detailed resolution of the detected footstep signal. In experiments conducted in a school building, our system demonstrated up to 2× increase on the sufficient resolution rate and 2× less error rate when used to locate the pedestrians as they walk along the hallway, compared to a fixed sensing setting.

As the development of autonomous vehicles rapidly advances, the use of convoying/platooning becomes a more widely explored technology option for saving fuel and increasing the efficiency of traffic. In cooperative adaptive cruise control (CACC), the vehicles in a convoy follow each other under adaptive cruise control (ACC) that is augmented by the sharing of preceding vehicle acceleration through the vehicle to vehicle communication in a feedforward control path. In general, the desired velocity optimization for vehicles in the convoy is based on fuel economy optimization, rather than driveability. This paper is a preliminary study on the impact of the desired velocity profile on the driveability characteristics of a convoy of vehicles and the controller gain impact on the driveability. A simple low-level longitudinal model of the vehicle has been used along with a PD type cruise controller and a generic spacing policy for ACC/CACC. The acceleration of the previous vehicle is available to the next vehicle as input, and the simulations are performed as Cooperative Adaptive Cruise Control of a convoy of vehicles. Individual vehicle acceleration profiles have been analyzed for driveability for two different velocity profiles that are followed in a stretch of 720 m between stop signs. The controller gains have been re-tuned based on the parameter space robust control PID approach for driveability and compared with the original gains. The US06 SFTP drive cycle has also been used for the comparison of the two different controller gain sets.

In this paper, a new approach in Bacterial Foraging Optimization algorithm is proposed to reduce the total power loss and to improve the voltage profile of the radial distribution systems, in the presence of Distributed Generation unit. The proposed method aims to modify the performance of the Bacterial Foraging Optimization algorithm. The test results obtained from Modified Bacterial Foraging Optimization algorithm are also compared and found to be better and in close agreement with the Bacterial Foraging Optimization algorithm. The achievability and convenience of the optimization methods proposed have been demonstrated on 12-bus, 34-bus, and 69-bus radial distribution system consisting of 11, 33, and 68 sections, respectively. MATLAB, Version 7.10 software is used for simulation.

In this article, we intend to draw attention on the new Similarity measure for Fuzzy sets based on the extended definition of complementation. The old existing measures are based on traditional Zadehian Theory of Fuzzy sets where it is believed that there is no difference between Fuzzy membership function and Fuzzy membership value for the complement of a Fuzzy set which is already proved to be wrong. As a result, the previous Similarity measures have been proved illogical from the standpoints of new defi nition of complementation of Fuzzy set based on the fact that Fuzzy membership function and Fuzzy membership value for the complement of a Fuzzy set are two different things. Accordingly, we have already established a new Similarity measure with the help of exte nded definition of complementation using reference function. In this paper, an effort has been put forward to show the validity of the results obtained from our proposed measure with the help of traditional Hamming distance and Euclidean distance measures.

Magnetic circuit components have long been the largest and most difficult components to miniaturize. Printed circuit board (PCB) fabrication methods cannot achieve small diameter, high aspect-ratio vias for high winding turn numbers to achieve high inductance, and microelectronics methods cannot achieve the high-quality and thick ferrite core materials. In this paper, we present an alternative breakthrough method of printed circuit fabrication to significantly reduce the effective via diameter for embedded magnetic devices, boosting the inductance per unit area. To reduce the effective via diameter, high-density via plugs are ex-situ fabricated and shaped, and then embedded into PCB substrate in the same process as standard magnetic core embedding. The structure of the plug is such that precise placement within the substrate, or alignment to the plug with the winding pattern, is not necessary. Devices presented in this paper use via plugs with an effective diameter of 40 μm and a theoretically unlimited aspect ratio, though refinements in the plug fabrication process are expected to reduce the via diameter down to 10μm. The process is experimentally demonstrated with a 14-turn racetrack shaped transformer; novel diagnostic methods using magneto-optic garnet films to image current paths are also demonstrated.