Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloud Computing for Earth Surface Deformation Analysis via Spaceborne Radar Imaging: A Case Study

We present a case study on the migration to a Cloud Computing environment of the advanced differential synthetic aperture radar interferometry (DInSAR) technique, referred to as Small BAseline Subset (SBAS), which is widely used for the investigation of Earth surface deformation phenomena. In particular, we focus on the SBAS parallel algorithmic solution, namely P-SBAS, that allows the production of mean deformation velocity maps and the corresponding displacement time-series from a temporal sequence of radar images by exploiting distributed computing architectures. The Cloud migration is carried out by encapsulating the overall P-SBAS application in virtual machines running on the Cloud; moreover, the Cloud resources provisioning and configuration phases are implemented in an automatic way. Such an approach allows us to preserve the P-SBAS parallelization strategy and to straightforwardly evaluate its performance within a Cloud environment by comparing it with those achieved on a HPC in-house cluster. The results we present were achieved by using the Amazon Elastic Compute Cloud (EC2) of the Amazon Web Services (AWS) to process SAR datasets collected by the ENVISAT satellite and show that, thanks to the Cloud resources availability and flexibility, large DInSAR data volumes can be processed through the P-SBAS algorithm in short time frames and at reduced costs. As a case study, the mean deformation velocity map of the southern California area has been generated by processing 172 ENVISAT images. By exploiting 32 EC2 instances this processing took less than 17 hours to complete, with a cost of USD 850. Considering the available PB-scale archives of SAR data and the upcoming huge SAR data flow relevant to the recently launched (April 2014) Sentinel-1A and the forthcoming Sentinel-1B satellites, the exploitation of Cloud Computing solutions is particularly relevant because of the possibility to provide Cloud-based multi-user services allowing worldwide scientists to quickly process SAR data and to manage and access the achieved DInSAR results.
Presenting a Hybrid Method in Order to Predict the 2009 Pandemic Influenza A (H1N1)

By the emergence and rapid spread of 2009 pandemic influenza A (H1N1) virus through the world, several methods have been developed to predict and prevent this lethal disease. Although many efforts have been made by statistical and traditional intelligent methods to anticipate this disease, but none of them could satisfy the expectations of specialists. This paper aims to present an efficient hybrid method to predict H1N1 with a reliable sensitivity. In this way, three methods including Gaussian mixture model (GMM), neural network (NN), and fuzzy rule-based system (FRBS) have been fused in order to provide an accurate and reliable prediction scheme to anticipate presence of H1N1 influenza. In this study, 230 individuals were participated and their clinical data were collected. The proposed hybrid scheme was implicated and the results showed to be superior to using each of the decision components containing NN, FRBS, and GMM classifiers. The achieved results produced 95.83% sensitivity and 80.95% specificity on unseen data which support the effectiveness of the hybrid method to predict the influenza in its golden time.
The Production of Monokaryotic Hyphae by Cryptococcus neoformans Can Be Induced by High Temperature Arrest of the Cell Cycle and Is Independent of Same-Sex Mating

Cryptococcus neoformans is a heterothallic fungal pathogen of humans and animals. Although the fungus grows primarily as a yeast, hyphae are produced during the sexual phase and during a process called monokaryotic fruiting, which is also believed to involve sexual reproduction, but between cells of the same mating type. Here we report a novel monokaryotic fruiting mechanism that is dependent on the cell cycle and occurs in haploid cells in the absence of sexual reproduction. Cells grown at 37°C were found to rapidly produce hyphae (∼4 hrs) and at high frequency (∼40% of the population) after inoculation onto hyphae-inducing agar. Microscopic examination of the 37°C seed culture revealed a mixture of normal-sized and enlarged cells. Micromanipulation of single cells demonstrated that only enlarged cells were able to produce hyphae and genetic analysis confirmed that hyphae did not arise from α-α mating or endoduplication. Cell cycle analysis revealed that cells grown at 37°C had an increased population of cells in G2 arrest, with the proportion correlated with the frequency of monokaryotic fruiting. Cell sorting experiments demonstrated that enlarged cells were only found in the G2-arrested population and only this population contained cells able to produce hyphae. Treatment of cells at low temperature with the G2 cell cycle arrest agent, nocodazole, induced hyphal growth, confirming the role of the cell cycle in this process. Taken together, these results reveal a mating-independent mechanism for monokaryotic fruiting, which is dependent on the cell cycle for induction of hyphal competency.
Event‐related fMRI at 7T reveals overlapping cortical representations for adjacent fingertips in S1 of individual subjects

Recent fMRI studies of the human primary somatosensory cortex have been able to differentiate the cortical representations of different fingertips at a single‐subject level. These studies did not, however, investigate the expected overlap in cortical activation due to the stimulation of different fingers. Here, we used an event‐related design in six subjects at 7 Tesla to explore the overlap in cortical responses elicited in S1 by vibrotactile stimulation of the five fingertips. We found that all parts of S1 show some degree of spatial overlap between the cortical representations of adjacent or even nonadjacent fingertips. In S1, the posterior bank of the central sulcus showed less overlap than regions in the post‐central gyrus, which responded to up to five fingertips. The functional properties of these two areas are consistent with the known layout of cytoarchitectonically defined subareas, and we speculate that they correspond to subarea 3b (S1 proper) and subarea 1, respectively. In contrast with previous fMRI studies, however, we did not observe discrete activation clusters that could unequivocally be attributed to different subareas of S1. Venous maps based on T2*‐weighted structural images suggest that the observed overlap is not driven by extra‐vascular contributions from large veins. Hum Brain Mapp 35:2027–2043, 2014. © 2013 The Authors Human Brain Mapping published by Wiley Periodicals, Inc.
Performance Analysis of Distributed Routing Protocol of Heterogeneous Wireless Sensor Networks

Wireless communication technologies continue to undergo rapid advancement. In recent years, there has been a steep growth in research in the area of wireless sensor networks (WSNs). Sensor nodes are small devices with sensing, computing and wireless communication capabilities. Such devices form a WSNs which can be used for many applications like gathering of environmental data and even monitoring enemy activity on a battlefield. In order to achieve this efficient routing protocols must be used. Such routing protocols are of prime research interest. There exist many different approaches most of which are studied through simulation only. At the same time real hardware platforms for this research become widely available and affordable. In this paper we will investigate the performance of distributed heterogeneous WSNs protocol: DDEEC, EDEEC and EDDEEC. I have analysed these protocol in terms of lifetime of the network and data transferred through each and every nodes of the network. The performance of these routing protocols is then measured and compared through simulation environment deployment of the WSNs.
Evaluating Gene Set Enrichment Analysis Via a Hybrid Data Model

Gene set enrichment analysis (GSA) methods have been widely adopted by biological labs to analyze data and generate hypotheses for validation. Most of the existing comparison studies focus on whether the existing GSA methods can produce accurate P-values; however, practitioners are often more concerned with the correct gene-set ranking generated by the methods. The ranking performance is closely related to two critical goals associated with GSA methods: the ability to reveal biological themes and ensuring reproducibility, especially for small-sample studies. We have conducted a comprehensive simulation study focusing on the ranking performance of seven representative GSA methods. We overcome the limitation on the availability of real data sets by creating hybrid data models from existing large data sets. To build the data model, we pick a master gene from the data set to form the ground truth and artificially generate the phenotype labels. Multiple hybrid data models can be constructed from one data set and multiple data sets of smaller sizes can be generated by resampling the original data set. This approach enables us to generate a large batch of data sets to check the ranking performance of GSA methods. Our simulation study reveals that for the proposed data model, the Q2 type GSA methods have in general better performance than other GSA methods and the global test has the most robust results. The properties of a data set play a critical role in the performance. For the data sets with highly connected genes, all GSA methods suffer significantly in performance.
Immobilization of Methyltrioxorhenium on Mesoporous Aluminosilicate Materials

The presented report focuses on an in-depth detailed characterization of immobilized methyltrioxorhenium (MTO), giving catalysts with a wide spectra of utilization. The range of mesoporous materials with different SiO2/Al2O3 ratios, namely mesoporous alumina (MA), aluminosilicates type Siral (with Al content 60%–90%) and MCM-41, were used as supports for immobilization of MTO. The tested support materials (aluminous/siliceous) exhibited high surface area, well-defined regular structure and narrow pore size distribution of mesopores, and therefore represent excellent supports for the active components. Some of the supports were modified by zinc chloride in order to obtain catalysts with higher activities for instance in metathesis reactions. The immobilization of MTO was optimized using these supports and it was successful using all supports. The success of the immobilization of MTO and the properties of the prepared heterogeneous catalysts were characterized using X-ray Fluorescence (XRF), atomic absorption spectroscopy (AAS), X-ray powder diffraction (XRD), scanning electron microscopy (SEM), physical adsorption of N2, ultraviolet-visible spectroscopy (UV-Vis), infrared spectroscopy (FTIR), Fourier Transform Infrared Spectroscopy (FTIR) using pyridine as a probe molecule and X-ray photoelectron spectroscopy (XPS). Furthermore, the catalytic activity of the immobilized MTO on the tested supports was demonstrated on metathesis reactions of various substrates.
Multilevel institutional analysis of accounting change in public management

Purpose This paper aims to provide a multilevel institutional analysis of public sector accounting change. It seeks to explain the implementation of changes to state-sector budgeting systems, taking into account the complex of factors that drive and shape the cumulative processes of accounting change. Design/methodology/approach The study presents the results of an interpretive case study set in a Jordanian public organization, Jordan Customs. It uses triangulation of data collection methods including interviews, observations and documents and archival records. The study adopts a multilevel analysis of institutions to better understand the implications of public accounting changes for the re-engineering and improved delivery of public services in Jordan. Findings The paper concludes from its analysis of public sector organizations that change in their accounting systems has occurred on three institutional levels. New budgeting methodologies were produced and reproduced based on re-consideration and re-enacting of theoretical accounting bases and procedures. Through this process, accounting change was itself reformed and new accounting routines further embedded extant accounting institutions and norms. Budgeting change, as a fundamental accounting change, is in this conception generated by external pressures and institutionalized in accounting routines over time. Research limitations/implications The paper is subject to the limitations of the case study approach. The propositions presented from the case studied need to be confirmed in further research into accounting system changes in other public organizations. The authenticity of the conclusions of this study would be greatly enhanced if supported by findings from other studies. The study has significant implications for the ways in which the dynamics of accounting change emerge at three levels of institutional analysis. By explaining the interaction between the “external” sources of and “internal” responses to change, accounting practice is shown to be both formed by and formative of broader socioeconomic processes. This overall sensitivity to the nature of accounting has significant implications for how accounting change can be studied. Originality/value The paper presents an interpretive case study of the practical issues of organizational change in a multilevel analysis that considers the experience of institutional pressures from the perspective of organizational actors. The study contributes to both management accounting literature and institutional theory by providing further understanding of the dynamics of accounting change in a developing nation’s public sector.
People Re-Identification by Means of a Camera Network Using a Graph-Based Approach

The problem described in this paper consists in reidentifying moving people in different sites with nonoverlapping views. Our proposed framework relies on a spectral analysis of the appearance-based signatures extracted from a detected person in each sequence. First, we propose a new feature called “color-position” histogram combined with several illuminant invariant methods in order to characterize extracted silhouettes in static images. Then, a graph-based approach that characterizes the most useful information of video sequences is presented to compare sequences, two by two, and to make the final decision of re-identification. The global system is tested on a real and difficult data set composed of 40 individuals recorded in very different environments: indoors near windows and outdoors with very different lighting conditions. The experimental results show that our approach provides reliable results and is promising with regard to surveillance security applications.
A new fusion scheme for multi-focus images based on dynamic salient weights on discriminative edge points

In this paper, we propose a new fusion scheme for multi-focus images based on special edge information called discriminative edge points. A new focus measure is also proposed to identify which pixels in the source images can be included in the resultant image to achieve the best fusion result by evaluating the salient weights for the discriminative edge points within a dynamic focus-measuring window whose center is the location of the pixel under current consideration. Experimental results show that our fusion scheme outperforms other seven methods reported in the literature.
Arm rehabilitation with a robotic exoskeleleton in Virtual Reality

Several studies demonstrate the importance of an early, constant and intensive rehabilitation following cerebral accidents. This kind of therapy is an expensive procedure in terms of human resources and time, and the increase of both life expectance of world population and incidence of stroke is making the administration of such therapies more and more important. The development of new robotic devices for rehabilitation can help to reduce this cost and lead to new effective therapeutic procedures. In this paper we present an exoskeleton for the robotic-assisted rehabilitation of the upper limb. This article describes the main issues in the design of an exoskeletal robot with high performance, in terms of backdrivability, low inertia, large workspace isomorphic to the human arm and high payload to weight ratio. The implementation of three different robotic schemes of therapy in virtual reality with this exoskeleton, based on an impedance control architecture, are presented and discussed in detail. Finally the experimental results of a preliminary evaluation of functionality of the system carried out on one patient are presented, and compared with the performance in the execution of the exercise obtained with healthy volunteers. Moreover, other preliminary results from an extended pilot clinical study with the L-Exos are reported and discussed.
Effect of αlipoic acid and silymarin on bladder outlet obstruction

The aim of the present study was to determine whether the treatment of obstructed rat bladders with αlipoic acid (ALA) and silymarin reverses the biochemical and physiological responses to bladder outlet obstruction (BOO). A total of 32 adult Sprague Dawley rats were divided into four groups (n=8 per group): sham (placebo surgery) animals with no treatment (group 1); control animals with surgically induced BOO (group 2); obstructed rats treated with ALA (group 3); and obstructed rats treated with silymarin (group 4). Histological evaluation, bladder weights, collagen structure, TdT-mediated biotin nick end-labeling (TUNEL), inducible nitric oxide sentase (iNOS) mRNA levels, malondialdehyde (MDA) levels and tumor necrosis factor (TNF) levels were investigated. The ALA-treated group had similar bladder weights, collagen levels and TUNEL positivity and decreased iNOS levels compared with the control group, while the silymarin group exhibited further differences. Serum MDA and TNF-α levels were both decreased in the ALA and silymarin groups. ALA treatment reduced the increased oxidative stress and bladder inflammation caused by BOO and may contribute to the protection of bladder function.
Distributed Rate-Distortion With Common Components

We describe a scheme for rate-distortion with distributed encoding in which the sources to be compressed contain a common component. We show that this scheme is optimal in some situations and that it strictly improves upon existing schemes, which do not make full use of common components. This establishes that independent quantization followed by independent binning is not optimal for the two-encoder problem with a distortion constraint on one source. We also show that independent quantization and binning is suboptimal for the three-encoder problem in which the goal is to reproduce one of the sources losslessly. This provides a counterexample that is fundamentally different from one provided earlier by Körner and Marton. The proofs rely on the binary analogue of the entropy power inequality and the existence of a rate loss for the binary symmetric Wyner-Ziv problem.
How Bayes tests of molecular phylogenies compare with frequentist approaches

MOTIVATION The desire to compare molecular phylogenies has stimulated the design of numerous tests. Most of these tests are formulated in a frequentist framework, and it is not known how they compare with Bayes procedures. I propose here two new Bayes tests that either compare pairs of trees (Bayes hypothesis test, BHT), or test each tree against an average of the trees included in the analysis (Bayes significance test, BST). RESULTS The algorithm, based on a standard Metropolis-Hastings sampler, integrates nuisance parameters out and estimates the probability of the data under each topology. These quantities are used to estimate Bayes factors for composite vs. composite hypotheses. Based on two data sets, the BHT and BST are shown to construct similar confidence sets to the bootstrap and the Shimodaira Hasegawa test, respectively. This suggests that the known difference among previous tests is mainly due to the null hypothesis considered.
Electromyography analysis and fatigue evaluation of rectus abdominis muscle during core exercise

Sedentary work is a common work style in modern society. Many studies show that sitting for a long time may diminish physical activity level and cause muscle pain, low back pain or even cardiovascular disease and high blood pressure. To improve the muscle strength of sedentary people, the study developed a training exercise for core muscles and lower limb muscles. Infrared sensors and electromyography (EMG) extracting circuit were used to record the subjects' EMG. Meanwhile, Median Frequency (MDF) and muscle Electromyographic Activity (EA) were applied to analyze the fatigue status of muscles and prevent muscle damage caused by excessive exercise.
How to detect fluctuating stripes in the high-temperature superconductors

We discuss fluctuating order in a quantum disordered phase proximate to a quantum critical point, with particular emphasis on fluctuating stripe order. Optimal strategies for extracting information concerning such local order from experiments are derived with emphasis on neutron scattering and scanning tunneling microscopy. These ideas are tested by application to two model systems - the exactly solvable one dimensional electron gas with an impurity, and a weakly-interacting 2D electron gas. We extensively review experiments on the cuprate high-temperature superconductors which can be analyzed using these strategies. We adduce evidence that stripe correlations are widespread in the cuprates. Finally, we compare and contrast the advantages of two limiting perspectives on the high-temperature superconductor: weak coupling, in which correlation effects are treated as a perturbation on an underlying metallic (although renormalized) Fermi liquid state, and strong coupling, in which the magnetism is associated with well defined localized spins, and stripes are viewed as a form of micro-phase separation. We present quantitative indicators that the latter view better accounts for the observed stripe phenomena in the cuprates.
TRUST EVALUATION IN UNSUPERVISED NETWORK: A FUZZY LOGIC APPROACH

Because of the possibility of anonymity and impersonation in social networks, trust plays an important role in these networks. In social networks, trust can have two aspects: trust of users to social network and trust of users to other users. Pear to pear networks, by eliminating the supervisor roles, besides its benefit in decreasing management costs, have problems in trust and security of users. In these networks, trust evaluation is only related to the trust of pear to other pear and because of the direct relation between pears; each user should know the trust level of other users. However, trust evaluation in pear-to-pear networks (as an unsupervised network), only can be done based on the past relation between pears or trust evaluation of other pears. This kind of trust evaluation cannot give a comprehensive view to pears. In other word, if any pear is not in the friend cycle of a user or friend cycle of user's friends, he will not be able to assign appropriate trust level to this pear. In this research, by using social networks as supervised networks, trust level of each user is evaluated, then by identifying these users in unsupervised networks, appropriate trust level is assigned to them.