Miracle-dz/UniFAR-FTUs huggingface dataset:
Outcomes in Economic Evaluations of Public Health Interventions in Low‐ and Middle‐Income Countries: Health, Capabilities and Subjective Wellbeing

Abstract Public health programmes tend to be complex and may combine social strategies with aspects of empowerment, capacity building and knowledge across sectors. The nature of the programmes means that some effects are likely to occur outside the healthcare sector; this breadth impacts on the choice of health and non‐health outcomes to measure and value in an economic evaluation. Employing conventional outcome measures in evaluations of public health has been questioned. There are concerns that such measures are too narrow, overlook important dimensions of programme effect and, thus, lead to such interventions being undervalued. This issue is of particular importance for low‐income and middle‐income countries, which face considerable budget constraints, yet deliver a large proportion of health activities within public health programmes. The need to develop outcome measures, which include broader measures of quality of life, has given impetus to the development of a variety of new, holistic approaches, including Sen's capability framework and measures of subjective wellbeing. Despite their promise, these approaches have not yet been widely applied, perhaps because they present significant methodological challenges. This paper outlines the methodological challenges for the identification and measurement of broader outcomes of public health interventions in economic evaluation in low‐income and middle‐income countries.
Collaborative Warning System for Dense Vehicular Networks Using MUSIC Algorithm DoA

The problem of providing a collaborative early warning system for multiple moving vehicles against a small size fast moving object like a motorbike. This approach consists of three stages: The first stage consists of detecting the incoming object using a highly directive antenna at 5.0 GHz in license free industrial, scientific and medical (ISM) band. The second stage consists of broadcasting the warning message using a low directivity broad beam antenna, third stage will be detected by receiving vehicles by using direction of arrival (DOA) estimation technique. The position of a fast arriving object can be estimated using the MUSIC algorithm for warning beam DOA estimation. This paper is intended to demonstrate the feasibility of an early detection and warning system using a collaborative vehicle to vehicle communication links. The simulation is performed to show the behavior of detecting and broadcasting antennas as well as performance of the detection algorithm. The process can be further expanded to implement commercial grade detection and warning system.
Stability and bifurcation analysis of a discrete predator-prey model with Holling type III functional response

The paper studies the dynamical behaviors of a discrete predator-prey system with Holling type III functional response. More precisely, we investigate the local stability of equilibriums, flip bifurcation and Neimark-Sacker bifurcation of the model by using the center manifold theorem and the bifurcation theory. And analyze the dynamic characteristics of the system in two-dimensional parameter-spaces, one can observe the ”cluster” phenomenon. Numerical simulations not only illustrate our results, but also exhibit the complex dynamical behaviors of the model. The results show that we can more clearly and directly observe the chaotic phenomenon, period-adding and Neimark-Sacker bifurcation from two-dimensional parameter-spaces and the optimal parameters matching interval can also be found easily. c ©2016 all rights reserved.
Integrating Data from The Preposition Project into FrameNet

In the course of The Preposition Project, FrameNet sentences are used as instances to characteize preposition behavior. FrameNet sentences containing prepositional phrases beginning with a given preposition are presented to a lexicographer, whereupon the given preposition is tagged with a sense from a sense inventory derived from the Oxford Dictionary of English. For the 34 prepositions used in the SemEval-2007 task on preposition disambiguation, over 25,000 instances were so tagged. Since each instance, i.e., a prepositional phrase, had already been tagged by the FrameNet lexicographers with a frame element for a particular frame, each sense in The Preposition Project has an associated set of (Frame, FrameElement) pairs. For the 25,641 instances, 18,470 instances are FrameNet core frame elements, 4,518 are FrameNet peripheral frame elements, and 1,676 are FrameNet extra-thematic frame elements. Since, in general, prepositions are not targets for the FrameNet project, data from The Preposition Project provide an opportunity to make a systematic attempt to expand the treatment of prepositions in FrameNet. This paper describes various analyses upon data from The Preposition Project and FrameNet to explore and develop steps that can be taken.
Cross-media cloud computing

Cross-media is the outstanding characteristics of the age of big data with large scale and complicated processing task. This article presents 5 issues and briefly summarizes the research progress of cross-media knowledge discovery. Furthermore, we propose a framework for cross-media semantic understanding which contains discriminative modeling, generative modeling and cognitive modeling. In cognitive modeling, a new model entitled CAM is proposed which is suitable for cross-media semantic understanding. Moreover, a Cross-Media Intelligent Retrieval System (CMIRS) will be illustrated. In the final, the research directions and problems encountered are presented.
Comparison of LEACH and PEGASIS Hierarchical Routing Protocols in Wireless Sensor Networks

The efficiency of wireless sensor network largely depends on the routing protocol used. Routing is a major challenge for sensor networks as it presents a trade-off between responsiveness and efficiency. Hierarchical class of routing protocols introduces a structure on the network to achieve stability, energy efficiency and scalability. There are various protocols existing in this category. In this paper, we analyse Low Energy Adaptive Clustering Hierarchy (LEACH) and Power Efficient GAthering in Sensor Information System (PEGASIS) hierarchical protocols. This work analyzes these protocols on the basis of total enery consumed, overheads, and sensors lifetime and provides a comparison of LEACH and PEGASIS with simulation results.
Multi-Task low-rank and sparse matrix recovery for human motion segmentation

This paper proposes a new algorithm, named Multi-Task Robust Principal Component Analysis (MTRPCA), to collaboratively integrate multiple visual features and motion priors for human motion segmentation. Given the video data described by multiple features, the human motion part is obtained by jointly decomposing multiple feature matrices into pairs of low-rank and sparse matrices. The inference process is formulated as a convex optimization problem that minimizes a constrained combination of nuclear norm and ℓ2,1-norm, which can be solved efficiently with Augmented Lagrange Multiplier (ALM) method. Compared to previous methods, which usually make use of individual features, the proposed method seamlessly integrates multiple features and priors within a single inference step, and thus produces more accurate and reliable results. Experiments on the HumanEva human motion dataset show that the proposed MTRPCA is novel and promising.
Methods of Evaluation of Output Signals from Resonance Accelerometers

In this paper two novel modifications of Weighted Least Square Method (WLSM) of frequency estimation suitable for evaluation of rapid changes of frequency occurring in resonance sensors are introduced and experimentally verified. The efficiency of the WLSM methods is compared to the nano-counting approach representing a substantial improvement of well-known start-stop methods of frequency measurement and estimation. Copyright © 2014 IFSA Publishing, S. L.
Model of Knowledge Management Systems Adoption and Diffusion in Western Australia: Analysis by Partial Least Square Approach

This study investigates the factors influencing the adoption and diffusion of Knowledge Management Systems (KMS) in Western Australia. The study uses a mixed methodology approach. The research was carried out in three stages: field study, pilot survey, and state wide survey (top 300 companies). The data of the survey in Western Australia was analyzed through Partial Least Square Approach (PLS). Results indicate that “Individual factors”, “External Inspiring”, “Organizational Factors” and “Task complexity” are the significant factors which influence the “Perceived usefulness” of KMS, which in turn significantly influences the “Intention” to adopt KMS and its diffusion process. Some unexpected results are also revealed. The results provide practical suggestions to those companies who are embarking on the adoption and diffusion of knowledge management systems in Western Australia or elsewhere.
Application of the Hybrid Genetic Algorithm to Combinatorial Optimization Problems in Flow-shop Scheduling

Production scheduling has been recognized as common but challenging combinatorial problems. Because of their complexity, recent research has turned to genetic algorithms to address such problems. Although genetic algorithms have been proven to facilitate the entire space search, they lack in fine-tuning capability for obtaining the global optimum. Therefore, in this study a hybrid genetic algorithm was developed for optimization. Scheduling problems often involve more than one criterion and therefore require multicriteria analysis. Therefore a multicriteria flowshop scheduling problem with setup times is considered. The objective function of the problem is minimization of the weighted sum of total completion time, makespan, maximum tardiness and maximum earliness. An integer programming model is developed for the problem which belongs to NP-hard class. According to computational results, the hybrid genetic algorithm proposed is effective in finding problem solutions.
Attacks on feature-based affine-invariant watermarking methods

A class of attacks targeting at a feature-based affine-invariant digital watermarking technique is addressed in this paper. First, it is pointed out that the use of feature points to revert an affine transform operation is equivalent to the use of a known image size or boundary for image normalization. Therefore, any method based on feature points suffers from point shifting in much the same manner as how the image normalization scheme suffers from cropping or reframing. Some simple methods to perform a (feature) point shifting attack are next described. Although use of a sufficient large number of candidate feature points can solve the problem, the paper further points out that this solution, like any secure template-based watermarking method, results in high detection complexity. A two-stage search scheme is proposed to avoid the attack, while retaining the overall detection complexity to a reasonable level.
Neural classifier for larvae recognition

A new application of LIRA neural classifier is presented in this article. We adapt this neural classifier to recognize larvae. This problem has not been resolved but it is very important for agriculture. To reduce the pesticides that are used to protect the harvest, it is necessary to localize the larvae distribution. It is possible to do this by monitoring of plants with one robot that contains a vision system. We present the results of larvae recognition with the LIRA neural network that was developed for other recognition tasks.
Surface displacements in the September 2005 Afar rifting event from satellite image matching: Asymmetric uplift and faulting

Combining sub‐pixel analysis of SPOT4 images with InSAR measurements, we generate 3D surface displacements for the September 2005 rifting event on the Dabbahu Segment in the Afar valley. The axis of rifting in the event is shifted to the east of the geomorphic rift. The horizontal displacements reveal 6 m of extension, and vertical displacements show asymmetric uplift of the flanks of the dike. Simple forward modelling indicates this asymmetry is due to the dike dipping 80° to the west towards the geomorphic rift. The boundary between eastward and westward displacements aligns with the transition between uplift and subsidence on the east in the north part of the segment, but on the west in the south. Normal faulting is not required on both sides of the instantaneous rift. East‐dipping normal faulting on the west side of the instantaneous rift aligns with a west‐dipping normal fault in the topography.
control of a 65m yacht in the Mediterranean Sea . II

An attacker’s ability to covertly control a maritime surface vessel by broadcasting counterfeit civil Global Positioning System (GPS) signals is analyzed and demonstrated. The aim of this work is to explore civil maritime transportation’s vulnerability to deceptive GPS signals. It is shown that, despite access to a variety of high-quality navigation and surveillance sensors, modern maritime navigation depends crucially on satellite navigation. A simple innovations-based detection framework for GPS deception is developed, and given real-world environmental and attack parameters, the probability of hazardously misleading information (HMI) is minimized within the framework. A covert attack is designed to have a high probability of HMI and is possible because attacker-induced deviations in the vessel’s crosstrack dynamics can be disguised as the effects of slowly-changing ocean currents. A field experiment confirms the analysis by demonstrating covert control of a 65-m yacht in the Mediterranean Sea.
Vulnerability ranking based on exploitation and defense graph

Network security analysis based on attack graphs has been applied extensively in recent years. The ranking of nodes in an attack graph is an important step towards analyzing network security, which can distill the overwhelming amount of information into a list of priorities that will help network administrators to efficiently utilize scarce resources. In this paper, we propose a new methodology called DBRank for ranking vulnerabilities to patch in computing networks. DBRank prioritizes vulnerabilities based on the diffusibility and benefit of vulnerability exploitation. Different from other approaches, DBRank takes into account the network topology and exploitation benefit in calculating their relative risk and priority. The experiments yielded promising results that this method can be used in hardening network security.
Relay based Clustering Protocol for WSN

Energy minimization and increase in lifetime have become the key factors for data transmission in a wireless sensor network. An energy efficient protocol called Energy Efficient Relay Based Multi-hop Clustering (EEMRC) that balances the energy consumption in clusters is implemented with the help of relay nodes. Comparison of the proposed protocol with the standard LEACH protocol yielded results which showed a large improvement in network lifetime.
Transdermal Rotigotine Improves Sleep Fragmentation in Parkinson's Disease: Results of the Multicenter, Prospective SLEEP-FRAM Study

Sleep disturbances occur frequently in patients with Parkinson's disease (PD). The aim of this study was to investigate the effects of rotigotine on sleep fluctuations in a sample of PD patients with self-reported complaints of nocturnal awakenings. This prospective, open-label, observational, and multicenter study enrolled consecutive outpatients with PD and administered rotigotine (mean dose 8.9 mg/day) for 3 months. The primary endpoint was the change from baseline in sleep fragmentation, assessed using the sleep maintenance subscale score of the Parkinson's Disease Sleep Scale (PDSS). The newly designed Parkinson's Disease Sleep Fragmentation Questionnaire (PD-SFQ) was used to measure other sleep parameters. A total of 62 patients were enrolled (mean age 70.2 years; 66% male). At 3 months, rotigotine significantly improved sleep fragmentation from baseline on the PDSS-2 sleep maintenance subscale (from 3.4 ± 0.9 to 1.9 ± 1.4; P < 0.0001). Rotigotine also significantly improved nocturnal motor symptoms (P < 0.0001), restless legs-like symptoms (P < 0.005), and nocturia (P = 0.004). Rotigotine significantly improved self-reported complaints of sleep fragmentation in PD patients and could be a useful treatment to improve this specific sleep problem in PD. However, these results are based on a small and clinically heterogeneous sample so they must be taken cautiously.
An illusion of control modulates the reluctance to tempt fate

The tempting fate effect is that the probability of a fateful outcome is deemed higher following an action that “tempts” the outcome than in the absence of such an action. In this paper we evaluate the hypothesis that the effect is due to an illusion of control induced by a causal framing of the situation. Causal frames require that the action make a difference to an outcome and that the action precedes the outcome. If an illusion of control modulates the reluctance to tempt fate, then actions that make a difference to well-being and that occur prior to the outcome should tempt fate most strongly. In Experiments 1–3 we varied whether the action makes a difference and the temporal order of action and outcome. In Experiment 4 we tested whether an action can tempt fate if all outcomes are negative. The results of all four experiments supported our hypothesis that the tempting fate effect depends on a causal construal that gives rise to a false sense of control.
Spray Dried Extract of Phormidium valderianum as a Promising Source of Natural Antioxidant

Microencapsulation of antioxidant-rich fraction obtained by supercritical carbon dioxide extraction (at 50°C, 500 bar with extraction time of 90 min, and flow rate of CO2 at 2 L/min) of lyophilized biomass of Phormidium valderianum was carried out in a spray dryer using maltodextrin and gum arabic. Microencapsulation conditions that provided the best combination of phytochemical properties such as antioxidant activity, phenolic content, and reducing power with reasonable powder yield were an inlet temperature of 130°C and wall material composition as maltodextrin: gum arabic = 70 : 30. Toxicological study reported that the Anatoxin-a content of this encapsulated powder was below the limit of detection of HPLC. Storage study established that encapsulation of this antioxidant-rich algal extract resulted in eight times enhancement of half-life (T 1/2) values. The release profile of microencapsulated antioxidant-rich fraction from the encapsulated powder was found to follow first order anomalous transport kinetics. Therefore, this microencapsulated algal extract with minimum toxicity is a source of natural antioxidant and could have promising use as novel dietary supplement.
The high throughput and low memory access design of sub-pixel interpolation for H.264/AVC HDTV decoder

In this paper, we proposed a parallel and pipeline architecture for the sub-pixel interpolation filter in H.264/AVC conformed HDTV decoder. To efficiently use the bus bandwidth, we bring forward two memory access optimization strategies to avoid redundant data transfer and improve data bus utilization. To improve the processing throughput, we use parallel and multi-stage pipeline architecture for conducting data transmission and interpolation filtering in parallel. As compared to the traditional designs, our scheme offers 60% reduced memory data transfer. While clocking at 66 MHz, our design can support 1280/spl times/720 at 30 Hz processing throughput. The proposed design is suitable for system-on-chip design.
ECONOMIC THEORIES OF ORGANIZATION : CAUSAL MODES AND STRATEGIES FOR EMPIRICAL RESEARCH

Structural contingency theory, transaction cost theory and agency theory share a common interest in organizational forms as efficient solutions to situational factors. These three components – organizational form, situational factors and efficiency – characterize a class of theories that could properly be labeled economic theories of organization. Empirical investigations of these theories have regarded organizational form as well as efficiency as the dependent variable. Causal models which take organizational form as the result of situational factors are based on the assumption that existing organizational forms are the most efficient (given the situational factors). Thus two hypothetical mechanisms are involved: One mechanism causes variations in the level of efficiency for different organizational forms given specific situational factors. A second mechanism ensures that the more efficient organizational forms are selected. Only the first of these is actually related to core theoretical propositions. A number of unobserved variables may give rise to spurious correlations between organizational form and situational factors. Organizational form and situational factors may be uncorrelated even if some organizational forms are in fact more efficient than others given situational factors. We consequently argue that studies of the direct effect of situational factors (e.g., asset specificity) on organizational form (e.g., vertical integration) do not produce critical tests of theoretical propositions. Empirical testing that investigates situational factors as moderators of the relation between organizational form and efficiency, is both a more accurate representation of the theoretical mechanisms and approaches proper critical testing. This moderated model captures the essential and common features of economic theories of organization. We speculate whether the moderated model should indeed be adopted as a paradigm for theory building in organization science. We further argue that an explicit classification of the individual components in these theories as well as related theories into general categories (organizational form, situational factors and efficiency) may reveal if variables are interchangeable across theories for the benefit of future theory construction.
A performance evaluation of TopHat RNA sequences alignment tool on openstack-based cloud environments

Despite its great promises, current Cloud offering has not been fully exploited for the management of Next-Generation Sequencing technologies. In fact, while dynamic resource allocation is typically required to ensure efficient and effective usage of the Cloud resources, Cloud providers have to deal with complex services, usually treated as black-boxes; hence, the estimation of the maximum number of resources that could improve service execution is a big challenge. This paper proposes and explores the benefits of Cloud deployment when operating a processor-hungry RNA alignment tool. The goal is to show the advantages of the virtualized and Cloud-aware approach compared to a typical bare-metal deployment. Extensive results demonstrate that our approach is as a viable first step toward easing the deployment and improving run-time service scaling.