Miracle-dz/UniFAR-FTUs huggingface dataset:
Shedding and serologic responses following primary and secondary inoculation of house sparrows (Passer domesticus) and European starlings (Sturnus vulgaris) with low-pathogenicity avian influenza virus

Waterfowl and shorebirds are well-recognized natural reservoirs of low-pathogenicity avian influenza viruses (LPAIV); however, little is known about the role of passerines in avian influenza virus ecology. Passerines are abundant, widespread, and commonly come into contact with free-ranging birds as well as captive game birds and poultry. We inoculated and subsequently challenged house sparrows (Passer domesticus) and European starlings (Sturnus vulgaris) with wild-bird origin LPAIV H3N8 to evaluate their potential role in transmission. Oropharyngeal shedding was short lived, and was detected in more starlings (97.2%) than sparrows (47.2%; n=36 of each). Cloacal shedding was rare in both species (8.3%; n=36 of each) and no cage-mate transmission occurred. Infectious LPAIV was cultured from oropharyngeal and cloacal swabs and gastrointestinal and respiratory tissues from both species. Seroconversion was detected as early as 3 days post inoculation (d.p.i.) (16.7% of sparrows and 0% of starlings; n=6 each); 50% of these individuals seroconverted by 5 d.p.i. , and nearly all birds (97%; n=35) seroconverted by 28 d.p.i. In general, pre-existing homologous immunity led to reduced shedding and increased antibody levels within 7 days of challenge. Limited shedding and lack of cage-mate transmission suggest that passerines are not significant reservoirs of LPAIV, although species differences apparently exist. Passerines readily and consistently seroconverted to LPAIV, and therefore inclusion of passerines in epidemiological studies of influenza outbreaks in wildlife and domestic animals may provide further insight into the potential involvement of passerines in avian influenza virus transmission ecology.
The Economics of Futures Markets

Preface 1. Futures Markets: The Phenomena to be Explained 2. Market-Clearing Futures Prices and Hedging 3. Effects of Futures Markets upon Expected Output and Price Variance 4. Dynamic Stock-Flow Interactions in Futures Markets with Continuous Inventories 5. Anticipations, Hypotheses and Empirical Evidence 6. Futures Markets, Speculation and Welfare 7. The Effects of Interest Rate and Stock Index Futures upon the Rate of Capital Formation References Index.
Enable Knowledge Sharing in Intrusion Detection

Increasingly frequently and cleverly, intrusions are invading our hosts on the Internet. To address this, we see increasingly creative intrusion detection systems applying distinctive techniques, using different data structures for their underlying data, and reporting different kinds of intrusion status. Some are based on traffic patterns, others are based on signatures; some are centralized, others are distributed. Each of them has its own strengths and weaknesses. Despite the fact that attacks often affect multiple domains or organizations simultaneously, the tools used locally may not support effective collaboration across those boundaries. To date we do not have a way to integrate those techniques and create a comprehensive intrusion detection framework, so that intrusion detection systems widely distributed in the Internet can share information easily and worms be detected quickly. To unify those systems and make intrusion detection more effective in the Internet, we propose a unified, knowledge-based framework inspired by work on the knowledge plane (Clark et al., 2003).
Research the Data Analysis and Processing between MapReduce and Spark

Big Data can be defined as large data sets which are being generated from different sources like social media, audios, imaging, logging online websites etc. A need exists to process and analyze this huge amount of data to extract meaningful information. This can be a challenging task. Big data exceeds the processing capability of traditional databases to capture, manage, and process the voluminous amount of data. The use of the MapReduce and Spark frameworks are two common approaches that perform data analytics on Big Data. Both frameworks are open source and capable of cluster computing and fault-tolerance. We perform an experimental evaluation to study the performance differences between MapReduce and Spark. Given the conditions of our implementation, we found significant performance differences. We measured the execution times of the common WordCount program, and the PageRank algorithm, on a single node setup. Another metric of evaluation used is the CPU utilization when processing both batch and iterative jobs.
Enterprise Search with Development for Network Management System

Browsing and searching network information for observation, analysis and troubleshooting is an inherent part of using the features and functions of any Network Management System. Enterprise search has capabilities for handling various data types and sources and big data scalability, and is becoming an emerging technology for such network management functions development. In this paper, we give an overview on work done in our research and prototype team regarding an advanced search project. We provide a brief report on search fundamental knowledge and study of Solr search platform stack. It answers common questions from management and development teams regarding adopting search technology for production development, and gives a Solr reference card for developers. We also introduce two advanced search features, user experience based search recommendation and anomaly detection enhanced search ranking from our research work. Two features are developed to make network searches more efficient as it can help user quickly locate the most valuable search results, but the concept can be adopted for search applications in other domains.
Intellectual Property Rights, Technology and Economic Development

The ongoing attempt to harmonise and strengthen the intellectual property protection (IPP) regimes worldwide, as part of the TRIPs Agreement, appears to be adversely affecting technological activity in the developing countries by choking the knowledge spillovers from industrialised countries to developing countries. Furthermore, the implementation of the provisions of the TRIPs Agreement threatens poor peopleA¢Â? Â? s access to and affordability of life-saving drugs by pushing up their prices. This has been highlighted by the recent controversy regarding the availability of AIDS drugs in South Africa. In this context, this paper attempts to critically review the literature on the role of the IPP regime with particular reference to Asian countries and to draw out policy options.
Oral insulin delivery by means of solid lipid nanoparticles

The aim of this work was to produce and characterize cetyl palmitate-based solid lipid nanoparticles (SLN) containing insulin, and to evaluate the potential of these colloidal carriers for oral administration. SLN were prepared by a modified solvent emulsification-evaporation method based on a w/o/w double emulsion. The particle size, zeta potential and association efficiency of unloaded and insulin-loaded SLN were determined and were found to be around 350 nm, negatively charged and the insulin association efficiency was over 43%. After oral administration of insulin-loaded SLN to diabetic rats, a considerable hypoglycemic effect was observed during 24 hours. These results demonstrated that SLN promote the oral absorption of insulin.
Modelling confusion matrices to improve speech recognition accuracy, with an application to dysarthric speech

Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed for disordered speech, factors such as low intelligibility and limited vocabulary decrease speech recognition accuracy. In this paper, we introduce a technique that can increase recognition accuracy in speakers with low intelligibility by incorporating information from an estimate of the speaker's phoneme confusion matrix. The technique performs much better than standard speaker adaptation when the number of sentences available from a speaker for confusion matrix estimation or adaptation is low, and has similar performance for larger numbers of sentences.
Network Traffic Classification with Improved Random Forest

Accurate network traffic classification is significant to numerous network activities, such as QoS and network management etc. While port-based or payload-based classification methods are becoming more and more difficult, Machine Learning methods are promising in many aspects. In this paper, we improve the standard Random Forest by setting the variable selection probability according to the importance of the corresponding variable to classify network traffic. Our test results show that the Improved Random Forest has better classification performance. And it takes less time to build the model.
Automated unit testing of large industrial embedded software using concolic testing

Current testing practice in industry is often ineffective and slow to detect bugs, since most projects utilize manually generated test cases. Concolic testing alleviates this problem by automatically generating test cases that achieve high coverage. However, specialized execution platforms and resource constraints of embedded software hinder application of concolic testing to embedded software. To overcome these limitations, we have developed CONcrete and symBOLic (CONBOL) testing framework to unit test large size industrial embedded software automatically. To address the aforementioned limitations, CONBOL tests target units on a host PC platform by generating symbolic unit testing drivers/stubs automatically and applying heuristics to reduce false alarms caused by the imprecise drivers/stubs. We have applied CONBOL to four million lines long industrial embedded software and detected 24 new crash bugs. Furthermore, the development team of the target software adopted CONBOL to their development process to apply CONBOL to the revised target software regularly.
ESTIMATING THE HIDDEN COSTS OF ENVIRONMENTAL REGULATION

This paper examines whether accounting systems identify all the costs of environmental regulation. We estimate the relation between the “visible” cost of regulatory compliance, i.e., costs that are correctly classified in firms’ accounting systems, and “hidden” costs i.e., costs that are embedded in other accounts. We use plant-level data from 55 steel mills to estimate hidden costs, and we follow up with structured interviews of corporate-level managers and plant-level accountants. Empirical results show that a $1 increase in the visible cost of environmental regulation is associated with an increase in total cost (at the margin) of $10-11, of which $9-10 are hidden in other accounts. The findings suggest that inappropriate identification and accumulation of the costs of environmental compliance are likely to lead to distorted costs in firms subject to environmental regulation.
Process support for tools interoperability

Summary form only given. Our work seeks to build a platform that makes entities of various types (component, COTS, tools, etc.) interoperate in order to build a new application. We call this new kind of application a federation. Our federations use workflow as a support for application integration and interoperability. In this approach, the process is not defined in term of tools and their parameters; instead, the process is high level and describes only abstract steps without knowledge on how these steps will be carried out. Therefore, the federation offers a means to describe and control the synchronization between the abstract and executable process, and a set of concrete tools. The federation ensures that the execution of the abstract level involves a compatible real execution at the concrete level. Indeed, the real execution requires the collaboration of several tools. The description on how the abstract level is refined into the real execution satisfies consistency rules and interoperability paradigms. We think our work contributes by providing a high level view in which the application can be described, independently from the real tools specificities, and by providing the means to describe the application behavior and the tools can be used and modified flexibly and dynamically.
International Journal of Molecular Sciences the Significance of Epithelial-to-mesenchymal Transition for Circulating Tumor Cells

Epithelial to mesenchymal transition (EMT) is a process involved in embryonic development, but it also plays a role in remote metastasis formation in tumor diseases. During this process cells lose their epithelial features and adopt characteristics of mesenchymal cells. Thereby single tumor cells, which dissolve from the primary tumor, are enabled to invade the blood vessels and travel throughout the body as so called " circulating tumor cells " (CTCs). After leaving the blood stream the reverse process of EMT, the mesenchymal to epithelial transition (MET) helps the cells to seed in different tissues, thereby generating the bud of metastasis formation. As metastasis is the main reason for tumor-associated death, CTCs and the EMT process are in the focus of research in recent years. This review summarizes what was already found out about the molecular mechanisms driving EMT, the consequences of EMT for tumor cell detection, and suitable markers for the detection of CTCs which underwent EMT. The research work done in this field could open new roads towards combating cancer.
An Evaluation Model of Multimedia Composition Processes

Recent advances in developing smart devices, fast and reliable wireless communication, and mobile computing technologies offer rich information services to humans and machines by delivering multi-modal multimedia contents. As mobile contents are mostly composed of heterogeneous data delivered from multiple sources, these advances have significantly changed the way humans and machines interact from a content delivery perspective. How multiple devices communicate to provide useful content to users and how computing resources can be effectively exploited are critical issues in mobile computing. In this paper, a formal information composition process model is presented, and an analytical model based on a queueing theory approach is developed to address important challenges in the composition of multimedia information and the evaluation of content delivery in mobile computing. An illustrative application is also provided to demonstrate the effectiveness of the proposed model.
FPGA based TRNG using automatic calibration

This paper presents a new method to improve the quality of True Random Number Generators implemented on Field Programmable Gate Arrays. Traditionally implementations require an exact manual calibration to achieve the best performance. In this paper we are suggesting a method which uses modern clocking features to perform automatic calibration. This feature also enable the efficient use of some jitter sources previously unavailable to designers. The present design also uses one of these sources, the jitter available on the clock lines. The implementation has the advantage of a relatively high throughput in a small size. The quality of the generated stream is also high, passing multiple test suites. The implementation is also provided as a calibrating framework which can be easily reused for other designs.
Mobility Location Prediction : A review of Techniques used in Mobile Ad-Hoc Network

Mobility prognostication for individual way is a fascinating topic. Mobility foretelling in Mobile River advertizement -hoc meshing is a simpleton and effective dodging to predict when the exploiter will leave from the current emplacement and where he will move to next future position. The prediction of the mobility of node s in mobile ad hoc networks becomes a key solution for the delivery of data in real time operations; which enables the reclamation of the path s just prior to the modify of the topology which occurs a seamless and wellorganized data delivery that meet the expected value of the real time constraints. The mobility prediction is very significant for equally homogeneous networks and heterogeneous networks, determined by applications in mobility management, smooth handoffs, shout admission control, and resource reservation for improved timber of serving. One way to reference the truth of node mobility is devising proactive solvent that make use of mobility prediction algorithms to estimate the cause of the nodes. At the application level, drug user mobility prediction in combination with user’s profile may provide the user with enhanced location-based wireless services, such as route counsel, local traffic info and on-line advertising. In this newspaper we present the most significant mobility prediction techniques for Edouard Manet focusing on their major design rule and description. Keywords— MANET Networks, Mobility Prediction, Clustering, Mobility Models, Network Scalability.
FPGA realization of fuzzy temperature controller for industrial application

This paper describes FPGA realization of a Fuzzy Temperature Controller (FTC) using VHDL intended for industrial application. The system is built up with four major modules namely fuzzification, inference, implication and defuzzification. The composition method selected for the fuzzy model is the Max-Min composition while the Mamdani Min operator is chosen as the implication method. Each module is modeled individually using behavioral VHDL, and the combined using structural VHDL. Successful timing and functional simulations are carried out to verify the correct functionality of the algorithm. The verified VHDL model is synthesized using synthesis tool to get gate-level architecture of the FTC chip. The designed synthesized netlist is downloaded into FPGA board from Altera for verifying the functionality of the FTC chip. The operating frequency of the FTC chip is 5MHz with a critical path of 199.3ns.
LINK ADAPTATION FOR MIMO-OFDM SYSTEMS USING MAXIMUM LIKELIHOOD DETECTOR

This paper investigates adaptive modulation and coding (AMC) in 2-Tx multiple-input and multiple output (MIMO)orthogonal frequency division multiplexing (OFDM) spatial multiplexing systems using non-iterative maximum likelihood detector (MLD). We derive an approximate postprocessing signal to interference-plus-noise ratio (SINR) for MLD, which is computed as post minimum mean-squared error (MMSE) SINR plus gain value, where the gain value is calculated by symbol error rate of the interfering stream. The post-MLD SINR is then applied to perform link adaptation for AMC. Simulation results show that the proposed link adaptation strategy achieves throughput performance close to that of the optimum approach.
Estimates of the Returns to Scale for US Manufacturing

This paper estimates the degree of the returns to scale for 2-digit U.S. manufacturing industries from the output-based primal and price-based dual equations implied by firms' cost-minimization problems. It seeks to reconcile the cyclical behavior of the primal and dual productivity residuals by allowing for nonconstant returns to scale and imperfect competition. We find significant differences between the estimates of the returns to scale parameter derived from the primal versus the dual equations. The existence of time-varying markups reduces the incidence of significant differences in the primal versus dual returns to scale estimates for the durable goods industries but not for the non-durable goods industries. Likewise, the presence of the quasi-fixity of capital helps to reconcile the behavior of the primal and dual productivity residuals for the durable but not for the non-durable goods industries.
Grasp, motion, view planning on dual-arm humanoid for manipulating in-hand object

It is certainly important to get 3D geometric shape models of unknown objects. We try throughout this paper to make humanoid robots construct such models themselves. To reach this objective, we propose a method consisting in observing objects from multiple view points with re-grasping in order to get non-occluded model. In this paper, we especially focus on the selection algorithm of the next grasp position from computed candidates. This problem is expressed through a graph search problem. The nodes represent grasp positions, and they are connected when robots can re-grasp from one grasp position to the other. Of cource when the shape of an object is unknown, it is difficult to solve this problem. This is why we propose a heuristic method to select next grasp position only using grasp position information, so to be able to adapt to objects which 3D shape information is updated online. We compare the result with this method with the optimal solution available when 3D shape information is given. Finally we show the validity of this heuristic method in real time observation by comparison between these two solutions from the standpoint of the acquired 3D shape percentage and the number of regrasping.
Inverted Pendulum Standing Apparatus for Investigating Closed-Loop Control of Ankle Joint Muscle Contractions during Functional Electrical Stimulation

The restoration of arm-free standing in individuals with paraplegia can be facilitated via functional electrical stimulation (FES). In developing adequate control strategies for FES systems, it remains challenging to test the performance of a particular control scheme on human subjects. In this study, we propose a testing platform for developing effective control strategies for a closed-loop FES system for standing. The Inverted Pendulum Standing Apparatus (IPSA) is a mechanical inverted pendulum, whose angular position is determined by the subject's ankle joint angle as controlled by the FES system while having the subject's body fixed in a standing frame. This approach provides a setup that is safe, prevents falling, and enables a research and design team to rigorously test various closed-loop controlled FES systems applied to the ankle joints. To demonstrate the feasibility of using the IPSA, we conducted a case series that employed the device for studying FES closed-loop controllers for regulating ankle joint kinematics during standing. The utilized FES system stimulated, in able-bodied volunteers, the plantarflexors as they prevent toppling during standing. Four different conditions were compared, and we were able to show unique performance of each condition using the IPSA. We concluded that the IPSA is a useful tool for developing and testing closed-loop controlled FES systems for regulating ankle joint position during standing.
A stochastic model for the spatial structure of annular patterns of variability and the North Atlant

Abstract Meridional dipoles of zonal wind and geopotential height are found extensively in empirical orthogonal function (EOF) analysis and single-point correlation maps of observations and models. Notable examples are the North Atlantic Oscillation and the so-called annular modes (or the Arctic Oscillation). Minimal stochastic models are developed to explain the origin of such structure. In particular, highly idealized, analytic, purely stochastic models of the barotropic, zonally averaged zonal wind and of the zonally averaged surface pressure are constructed, and it is found that the meridional dipole pattern is a natural consequence of the conservation of zonal momentum and mass by fluid motions. Extension of the one-dimensional zonal wind model to two-dimensional flow illustrates the manner in which a local meridional dipole structure may become zonally elongated in EOF analysis, producing a zonally uniform EOF even when the dynamics is not particularly zonally coherent on hemispheric length scales.