Miracle-dz/UniFAR-FTUs huggingface dataset:
NEURO DIRECT TORQUE CONTROL OF PERMANENT MAGNET SYNCHRONOUS MOTOR WITH GENETIC ALGORITHM SPEED CONTROLLER

In recent years, permanent magnet synchronous motors (PMSM) have gained variety industrial applications, because of simple structures, high ef ficiency and ease of maintenance. But these motors have a nonlinear mathematical model. To resolve this pro blem several studies have suggested the application of vector control (VC) and direct torque control (DTC) with soft-computing (SC) technique. This paper presents neuro direct torque control (NDTC) of PMSM using genetic algorithm (GA) speed controller. The proposed method effectiveness has been verified by computer simulations using Matlab/Simulink®. These results are compared with the ones obtained with a classical DTC using PI speed controller.
An Evolutionary Algorithm for the Multi-objective shortest path problem

In this paper, a multi-objective shortest path evolutionary algorithm (MOSPEA) is presented for an undirected network. The algorithm differs from the others as it uses an external set to maintain nondominated solutions and different selection strategy. Property of MOSPEA about stochastic convergence is analyzed. Simulation experiments demonstrate the availability and efficiency of MOSPEA. The study shows that MOSPEA may hopefully be a feasible approach for multi-objective shortest path.
Discussion and Analysis of the Crowdsourcing Mode of Public Participation in Emergency Management

The crowdsourcing mode of public participation in emergency management is a new method that appears in recent years, and a comprehensive discussion and analysis of this new mode is helpful to its further improvement. This paper firstly presents a detailed analysis of the concept, components and processes of crowdsourcing, and discusses the background and origin reason of the combination of public participation in emergency management and crowdsourcing. Then, this study, using the case study method, deeply analyzes the successful application of a crowdsourcing platform named Ushahidi in the 2010 earthquake in Haiti from the aspects of source, processing and utilization of emergency information. Finally, this paper sums up some frontier topics that need a further research in the crowdsourcing mode of public participation in emergency management.
Do you see me now? Sparsity in passive observations of address liveness

Accurate information about address and block usage in the Internet has many applications in planning address allocation, topology studies, and simulations. Prior studies used active probing, sometimes augmented with passive observation, to study macroscopic phenomena, such as the overall usage of the IPv4 address space. This paper instead studies the completeness of passive sources: how well they can observe microscopic phenomena such as address usage within a given network. We define sparsity as the limitation of a given monitor to see a target, and we quantify the effects of interest, temporal, and coverage sparsity. To study sparsity, we introduce inverted analysis, a novel approach that uses complete passive observations of a few end networks (three campus networks in our case) to infer what of these networks would be seen by millions of virtual monitors near their traffic's destinations. Unsurprisingly, we find that monitors near popular content see many more targets and that visibility is strongly influenced by bipartite traffic between clients and servers. We are the first to quantify these effects and show their implications for the study of Internet liveness from passive observations. We find that visibility is heavy-tailed, with only 0.5% monitors seeing more than 10% of our targets' addresses, and is most affected by interest sparsity over temporal and coverage sparsity. Visibility is also strongly bipartite. Monitors of a different class than a target (e.g., a server monitor observing a client target) outperform monitors of the same class as a target in 82–99% of cases in our datasets. Finally, we find that adding active probing to passive observations greatly improves visibility of both server and client target addresses, but is not critical for visibility of target blocks. Our findings are valuable to understand limitations of existing measurement studies, and to develop methods to maximize microscopic completeness in future studies.
Load Balancing in IP Networks Using Generalized Destination-Based Multipath Routing

Intradomain traffic engineering (TE) has become an indispensable tool for Internet service providers (ISPs) to optimize network performance and utilize network resources efficiently. Various explicit routing TE methods were recently proposed and have been able to achieve high network performance. However, explicit routing has high complexity and requires large ternary content addressable memories (TCAMs) in the routers. Moreover, it is costly to deploy explicit routing in IP networks. In this paper, we present an approach, called generalized destination-based multipath routing (GDMR), to achieve the same high performance as explicit routing. The main contribution of this paper is that we prove that an arbitrary explicit routing can be converted to a loop-free destination-based routing without any performance penalty for a given traffic matrix. We present a systematic approach including a heuristic algorithm to realize GDMR. Extensive evaluation demonstrates the effectiveness and robustness of GDMR.
What We Know About Monetary Policy Transmission in the Czech Republic: Collection of Empirical Results

This paper concentrates on describing the available empirical findings on monetary policy transmission in the Czech Republic. Besides the overall impact of monetary policy on inflation and output, it is useful to study its individual channels, in particular the interest rate channel, the exchange rate channel, and the wealth channel. The results confirm that the transmission of monetary impulses to the real economy works in an intuitive direction and to an intuitive extent. Our analyses show, however, that the global financial and economic crisis might have somewhat slowed and weakened the transmission. We found an indication of such a change in the functioning of the interest rate channel, where elevated risk premiums played a major role.
Engineering secondary cell wall deposition in plants

Lignocellulosic biomass was used for thousands of years as animal feed and is now considered a great sugar source for biofuels production. It is composed mostly of secondary cell walls built with polysaccharide polymers that are embedded in lignin to reinforce the cell wall structure and maintain its integrity. Lignin is the primary material responsible for biomass recalcitrance to enzymatic hydrolysis. During plant development, deep reductions of lignin cause growth defects and often correlate with the loss of vessel integrity that adversely affects water and nutrient transport in plants. The work presented here describes a new approach to decrease lignin content while preventing vessel collapse and introduces a new strategy to boost transcription factor expression in native tissues. We used synthetic biology tools in Arabidopsis to rewire the secondary cell network by changing promoter-coding sequence associations. The result was a reduction in lignin and an increase in polysaccharide depositions in fibre cells. The promoter of a key lignin gene, C4H, was replaced by the vessel-specific promoter of transcription factor VND6. This rewired lignin biosynthesis specifically for vessel formation while disconnecting C4H expression from the fibre regulatory network. Secondly, the promoter of the IRX8 gene, secondary cell wall glycosyltransferase, was used to express a new copy of the fibre transcription factor NST1, and as the IRX8 promoter is induced by NST1, this also created an artificial positive feedback loop (APFL). The combination of strategies—lignin rewiring with APFL insertion—enhances polysaccharide deposition in stems without over-lignifying them, resulting in higher sugar yields after enzymatic hydrolysis.
Improving tests infrastructure through a model-based approach

Software tests have a high impact on the cost of software development. In practice, they are generally created at random and without any methodology, and do not have sufficient documentation. Commonly used approaches also perform the tests outside the application environment (e.g. web servers and containers). Besides, the test cases are usually restricted to target business components behavior, leaving a huge gap by not evaluating the presentation layer. Most of these practices can be explained by the overhead required to maintain manually the whole test artifacts. Applying a Model-based Approach (MBA), the creation and maintenance of test artifacts can be automated. This paper proposes a method that applies the Model-driven Architecture (MDA), a strategy of MBA, to determine the flow of test cases. The proposed method was based on the use of Unified Modeling Language (UML) activity diagrams. These diagrams allow determining the test flows and the objective of each activity, such as testing of business and presentation layers. Moreover, the generated test artifacts allow for performing the tests inside the application environment.
Analyzing intrusions using operating system level information flow

Computers continue to get broken into, so intrusion analysis is a part of most system administrators' job description. System administrators must answer two main questions when analyzing intrusions: "how did the attacker gain access to my system? ", and "what did the attacker do after they broke in? ". Current tools for analyzing intrusions fall short because they have insufficient information to fully track the intrusion and because they cannot separate the actions of attackers from the actions of legitimate users. We designed and implemented a system for analyzing intrusions by using OS-level information flow to highlight the activities of an attacker. OS-level information flow is a collection of causal events which connect operating system objects. These causal events can be linked to form an information-flow graph which highlights the events and objects that are part of an attack. Information flow graphs can be used to help system administrators determine how an intruder broke into a system and what they did after the compromise. We developed BackTracker to determine how an intruder broke into a system. BackTracker starts with a suspicious object (e.g., malicious process, trojaned executable file) and follows the attack back in time, using causal events, to highlight the sequence of events and objects that lead to the suspicious state. Showing a graph of these causally-connected events and objects provides a system-wide view of the attack and significantly reduces the amount of data an administrator must examine in order to determine which application was originally exploited. We also developed ForwardTracker to determine the attacker's actions after the compromise. ForwardTracker starts from the application which was exploited and tracks causal events forward in time to display the information flow graph of events and objects that result from the intrusion. Furthermore, we designed and implemented Bi-directional Distributed BackTracker (BDB) which continues the backward and forward information flow graphs across the network to highlight the set of computers on a local network which are likely to have been compromised by the attacker.
Socioeconomic factors, health behaviors, and mortality: results from a nationally representative prospective study of US adults.

CONTEXT A prominent hypothesis regarding social inequalities in mortality is that the elevated risk among the socioeconomically disadvantaged is largely due to the higher prevalence of health risk behaviors among those with lower levels of education and income. OBJECTIVE To investigate the degree to which 4 behavioral risk factors (cigarette smoking, alcohol drinking, sedentary lifestyle, and relative body weight) explain the observed association between socioeconomic characteristics and all-cause mortality. DESIGN Longitudinal survey study investigating the impact of education, income, and health behaviors on the risk of dying within the next 7.5 years. PARTICIPANTS A nationally representative sample of 3617 adult women and men participating in the Americans' Changing Lives survey. MAIN OUTCOME MEASURE All-cause mortality verified through the National Death Index and death certificate reviews. RESULTS Educational differences in mortality were explained in full by the strong association between education and income. Controlling for age, sex, race, urbanicity, and education, the hazard rate ratio of mortality was 3.22 (95% confidence interval [CI], 2.01-5.16) for those in the lowest-income group and 2.34 (95% CI, 1.49-3.67) for those in the middle-income group. When health risk behaviors were considered, the risk of dying was still significantly elevated for the lowest-income group (hazard rate ratio, 2.77; 95% CI, 1.74-4.42) and the middle-income group (hazard rate ratio, 2.14; 95% CI, 1.38-3.25). CONCLUSION Although reducing the prevalence of health risk behaviors in low-income populations is an important public health goal, socioeconomic differences in mortality are due to a wider array of factors and, therefore, would persist even with improved health behaviors among the disadvantaged.
Edge sharpening in grayscale images using modified Sobel technique

Edges of an image is characterised by a boundary that's why it has a significant importance in the field of image processing. This paper presents the modified Sobel edge detection technique which gives sharp thin and noise free edges. Canny edge detection can filter out the useless information than the remaining information defines the structural information of the image. First of all make the image smooth by using a mask than Sobel operator use gradient method to find edges in an image. Gradient method is very useful in camera processing technique. It is used to blend the colors in horizontal and in vertical direction.
Interplay of Interlocus Gene Conversion and Crossover in Segmental Duplications Under a Neutral Scenario

Interlocus gene conversion is a major evolutionary force that drives the concerted evolution of duplicated genomic regions. Theoretical models successfully have addressed the effects of interlocus gene conversion and the importance of crossover in the evolutionary fate of gene families and duplications but have not considered complex recombination scenarios, such as the presence of hotspots. To study the interplay between interlocus gene conversion and crossover, we have developed a forward-time simulator that allows the exploration of a wide range of interlocus gene conversion rates under different crossover models. Using it, we have analyzed patterns of nucleotide variation and linkage disequilibrium within and between duplicate regions, focusing on a neutral scenario with constant population size and validating our results with the existing theoretical models. We show that the interaction of gene conversion and crossover is nontrivial and that the location of crossover junctions is a fundamental determinant of levels of variation and linkage disequilibrium in duplicated regions. We also show that if crossover activity between duplications is strong enough, recurrent interlocus gene conversion events can break linkage disequilibrium within duplicates. Given the complex nature of interlocus gene conversion and crossover, we provide a framework to explore their interplay to help increase knowledge on molecular evolution within segmental duplications under more complex scenarios, such as demographic changes or natural selection.
Mobile Device-based Three-Dimension Coordinate Estimation Using Face Detection

In this paper, we propose a 3D coordinate estimation for 3D space using a mono camera in mobile devices. Generally, a marker is used for the detection of 3D movement in 2D images. However, this marker-based system has obvious defects since markers always need to be included in the image. To overcome this problem, we replaced the markers with a planar face by estimating the face detection. The experimental result indicates the feasibility of the proposed algorithm for face movement-based mobile user interfaces.
ZiFiT (Zinc Finger Targeter): an updated zinc finger engineering tool

ZiFiT (Zinc Finger Targeter) is a simple and intuitive web-based tool that provides an interface to identify potential binding sites for engineered zinc finger proteins (ZFPs) in user-supplied DNA sequences. In this updated version, ZiFiT identifies potential sites for ZFPs made by both the modular assembly and OPEN engineering methods. In addition, ZiFiT now integrates additional tools and resources including scoring schemes for modular assembly, an interface with the Zinc Finger Database (ZiFDB) of engineered ZFPs, and direct querying of NCBI BLAST servers for identifying potential off-target sites within a host genome. Taken together, these features facilitate design of ZFPs using reagents made available to the academic research community by the Zinc Finger Consortium. ZiFiT is freely available on the web without registration at http://bindr.gdcb. iastate.edu/ZiFiT/.
Semantic Mutation Analysis of Floating-Point Comparison

Semantic Mutation Testing (SMT) is a technique that aims to capture errors caused by possible misunderstandings of the semantics of a description language. This paper focuses on the use of SMT to represent possible problems caused by the use of Floating Point Comparison (FPC) since this feature of programming languages can lead to subtle errors. We describe six FPC semantic mutation operators that have been implemented in a C SMT tool. These operators mutate a C program by introducing tolerances using three different algorithms. The paper reports on the results of experiments that explored the proposed mutation operators. It was found that random test suites were not good at killing the resultant mutants, suggesting also that random test suites are poor at revealing FPC problems. We therefore devised a new approach to generate test data to kill these mutants. The manually generated test suites produced using the new approach were more effective in killing FPC mutants. In addition, the random test suites and manual test suites killed different sets of FPC mutants. The impact of using three different algorithms in FPC mutation was also investigated with no dominates relationships being found between the three types of FPC operators. Finally, we ran the same experiments on a computer with a different configuration. We found that slightly different sets of mutants were killed on the two computers, indicating that portability problems can be introduced by FPC.
Global Translational Responses to Oxidative Stress Impact upon Multiple Levels of Protein Synthesis*

Global inhibition of protein synthesis is a common response to stress conditions. We have analyzed the regulation of protein synthesis in response to oxidative stress induced by exposure to H2O2 in the yeast Saccharomyces cerevisiae. Our data show that H2O2 causes an inhibition of translation initiation dependent on the Gcn2 protein kinase, which phosphorylates the α-subunit of eukaryotic initiation factor-2. Additionally, our data indicate that translation is regulated in a Gcn2-independent manner because protein synthesis was still inhibited in response to H2O2 in a gcn2 mutant. Polysome analysis indicated that H2O2 causes a slower rate of ribosomal runoff, consistent with an inhibitory effect on translation elongation or termination. Furthermore, analysis of ribosomal transit times indicated that oxidative stress increases the average mRNA transit time, confirming a post-initiation inhibition of translation. Using microarray analysis of polysome- and monosome-associated mRNA pools, we demonstrate that certain mRNAs, including mRNAs encoding stress protective molecules, increase in association with ribosomes following H2O2 stress. For some candidate mRNAs, we show that a low concentration of H2O2 results in increased protein production. In contrast, a high concentration of H2O2 promotes polyribosome association but does not necessarily lead to increased protein production. We suggest that these mRNAs may represent an mRNA store that could become rapidly activated following relief of the stress condition. In summary, oxidative stress elicits complex translational reprogramming that is fundamental for adaptation to the stress.
Multiagent simulation of evolutive plate tectonics applied to the thermal evolution of the Earth

The feedback between plate tectonics and mantle convection controls the Earth's thermal evolution via the seafloor age distribution. We therefore designed the MACMA model to simulate time‐dependent plate tectonics in a 2D cylindrical geometry with evolutive plate boundaries, based on multiagent systems that express thermal and mechanical interactions. We compute plate velocities using a local force balance and use explicit parameterizations to treat tectonic processes such as trench migration, subduction initiation, continental breakup and plate suturing. These implementations allow the model to update its geometry and thermal state at all times. Our approach has two goals: (1) to test how empirically‐ and analytically‐determined rules for surface processes affect mantle and plate dynamics, and (2) to investigate how plate tectonics impact the thermal regime. Our predictions for driving forces, plate velocities and heat flux are in agreement with independent observations. Two time scales arise for the evolution of the heat flux: a linear long‐term decrease and high‐amplitude short‐term fluctuations due to surface tectonics. We also obtain a plausible thermal history, with mantle temperature decreasing by less than 200 K over the last 3 Gyr. In addition, we show that on the long term, mantle viscosity is less thermally influential than tectonic processes such as continental breakup or subduction initiation, because Earth's cooling rate depends mainly on its ability to replace old insulating seafloor by young thin oceanic lithosphere. We infer that simple convective considerations alone cannot account for the nature of mantle heat loss and that tectonic processes dictate the thermal evolution of the Earth.