Miracle-dz/UniFAR-FTUs huggingface dataset:
Analogue private communication based on hybrid chaotic systems with delays

Since most of private communication schemes based on chaotic synchronization are not robust again plain-texts attacks, the introduction of delays in the schemes can be regarded as an efficient method to improve the security degree with respect to such attack. As an extension of our recent work, this paper proposes a new analogue private communication scheme based on hybrid chaotic systems with delays. The proposed scheme is based on the notation of weakly left invertibility of switched systems, and an illustrative example is given for the purpose of highlighting the feasibility of the proposed method.
AKT inhibition overcomes rapamycin resistance by enhancing the repressive function of PRAS40 on mTORC1/4E-BP1 axis

The mTORC1 inhibitors, rapamycin and its analogs, are known to show only modest antitumor activity in clinic, but the underlying mechanisms remain largely elusive. Here, we found that activated AKT signaling is associated with rapamycin resistance in breast and colon cancers by sustained phosphorylation of the translational repressor 4E-BP1. Treatment of tumor cells with rapamycin or the AKT inhibitor MK2206 showed a limited activity in inhibiting 4E-BP1 phosphorylation, cap-dependent translation, cell growth and motility. However, treatment with both drugs resulted in profound effects in vitro and in vivo. Mechanistic investigation demonstrated that the combination treatment was required to effectively inhibit PRAS40 phosphorylation on both Ser183 and Thr246 mediated by mTORC1 and AKT respectively, and with the combined treatment, dephosphorylated PRAS40 binding to the raptor/mTOR complex was enhanced, leading to dramatic repression of mTORC1-regulated 4E-BP1 phosphorylation and translation. Knockdown of PRAS40 or 4E-BP1 expression markedly reduced the dependence of tumor cells on AKT/mTORC1 signaling for translation and survival. Together, these findings reveal a critical role of PRAS40 as an integrator of mTORC1 and AKT signaling for 4E-BP1-mediated translational regulation of tumor cell growth and motility, and highlight PRAS40 phosphorylation as a potential biomarker to evaluate the therapeutic response to mTOR/AKT inhibitors.
Visualization model validation via inline replication

Data visualizations typically show a representation of a data set with little to no focus on the repeatability or generalizability of the displayed trends and patterns. However, insights gleaned from these visualizations are often used as the basis for decisions about future events. Visualizations of retrospective data therefore often serve as “visual predictive models. ” However, this visual predictive model approach can lead to invalid inferences. In this article, we describe an approach to visual model validation called Inline Replication. Inline Replication is closely related to the statistical techniques of bootstrap sampling and cross-validation and, like those methods, provides a non-parametric and broadly applicable technique for assessing the variance of findings from visualizations. This article describes the overall Inline Replication process and outlines how it can be integrated into both traditional and emerging “big data” visualization pipelines. It also provides examples of how Inline Replication can be integrated into common visualization techniques such as bar charts and linear regression lines. Results from an empirical evaluation of the technique and two prototype Inline Replication–based visual analysis systems are also described. The empirical evaluation demonstrates the impact of Inline Replication under different conditions, showing that both (1) the level of partitioning and (2) the approach to aggregation have a major influence over its behavior. The results highlight the trade-offs in choosing Inline Replication parameters but suggest that using n = 5 partitions is a reasonable default.
Identification of differentially expressed genes regulated by transcription factors in glioblastomas by bioinformatics analysis

The present study aimed to identify differentially expressed genes (DEGs) regulated by transcription factors (TFs) in glioblastoma, by conducting a bioinformatics analysis. The results of the present study may provide potential therapeutic targets that are involved in the development of glioblastoma. The GSE4290 raw data set was downloaded from the Gene Expression Omnibus database, and consisted of 23 non-tumor samples and 77 glioblastoma (grade 4) tumor samples. Robust Multichip Averaging was used to identify DEGs between the glioblastoma and non-tumor samples. Functional enrichment analysis of the DEGs was also performed. Based on the TRANSFAC® database, TFs associated with the glioblastoma gene expression profile were used to construct a regulatory network. Furthermore, trimmed subnets were identified according to calculated Z-scores. A total of 676 DEGs were identified, of which 190 were upregulated and 496 were downregulated. Gene Ontology analysis demonstrated that the majority of these DEGs were functionally enriched in synaptic transmission, regulation of vesicle-mediated transport and ion-gated channel activity. In addition, the enriched Kyoto Encyclopedia of Genes and Genomes pathway included neuroactive ligand-receptor interaction, calcium signaling pathway, p53 signaling pathway and cell cycle. Based on the TRANSFAC® database, transcriptional regulatory networks with 2,246 nodes and 4,515 regulatory pairs were constructed. According to the Z-scores, the following candidate TFs were identified: TP53, SP1, JUN, STAT3 and SPI1; alongside their downstream DEGs. TP53 was the only differentially expressed TF. These candidate TFs and their downstream DEGs may have important roles in the progression of glioblastoma, and could be potential biomarkers for clinical treatment.
A Survey Paper on Task Scheduling Methods in Cluster Computing Environment for High Performance

Parallel computing perform concurrently execution tasks on distributed nodes. Large application split up into tasks and run on number on nodes for high performance computing. Cluster environment composed with heterogeneous devices and software components capable of cost effective and high performance computing on parallel application. In heterogeneous cluster environment proper scheduling of tasks and allocation to nodes is important for high performance computing. Many task scheduling algorithms proposed for achieving high performance computing on heterogeneous computing. We proposed swarm technique methodology for task scheduling on heterogeneous cluster environment, which can perform better results for minimize make span, high performance and resource utilization compared to others.
Alcohol dependence-related increase of glial cell density in the anterior cingulate cortex of suicide completers.

BACKGROUND Suicide is the most serious consequence of major depressive disorder (MDD). Although the anterior cingulate cortex (ACC; Brodmann area [BA] 24) has been increasingly investigated for its role in the etiology of MDD, there is surprisingly very little information about the possible implication of this brain region in suicide. We hypothesized that changes in BA24 cell densities occur in depressed individuals who commit suicide, possibly reflecting an altered state of cortical plasticity that is thought to occur in depression. METHODS We investigated cell densities and sizes in BA24 among suicide completers and matched sudden-death controls. We examined a 1-cm(3) tissue block from BA24a of the supracallosal ACC in 26 human postmortem brain specimens (13 depressed individuals who committed suicide and 13 controls). We assessed neuronal and glial cell densities as well as neuronal soma sizes in the upper and lower cortical layers using optical fractionator and nucleator 3-dimensional stereological probes. RESULTS Glial densities, neuronal densities and soma sizes measured in BA24a did not differ significantly between controls and suicide completers. Secondary analyses showed a significant and robust increase in glial cell densities in BA24a of alcohol-dependent depressed suicide completers compared with depressed suicide completers who were not alcohol-dependent (38%) and, to a lesser extent, controls (30%). LIMITATIONS Our study, conducted with tissue samples from men only, made use of a nonspecific stain that does not distinguish between neuronal or glial cell subtypes. Furthermore, the quantitative analysis concerned upper and lower cortical contours rather than individual cortical layers. CONCLUSION Our results indicate that in BA24, glial density, neuronal density and soma size are not affected in MDD and suicide. They also suggest that alcohol dependence has an important influence on glial densities in this key limbic structure.
Study of feature reconstruction algorithm for surface mesh

Algorithms for feature-based surface fitting in meshes were presented. Most algorithms for fitting surfaces to meshes do not provide information about high-level form features. Such features convey the designer's intent in the context of the expected application. This research addresses the problem by developing a framework to incorporate high-level freeform features in the solid model. As part of this framework, we have developed algorithms and demonstrated their capability to detect both simple analytical shapes and also freeform feature templates. A solid model is constructed using this parametric form feature information.
Automatic Reordering Rule Generation Based On Parallel Tagged Aligned Corpus for Myanmar-English Machine Translation

— Reordering is important problem to be considered when translating between language pairs with different word orders. Myanmar is a verb final language and reordering is needed when it is translated into other languages which are different from Myanmar word order. In this paper, automatic reordering rule generation for Myanmar-English machine machine translation is presented. In order to generate reordering rules; Myanmar-English parallel tagged aligned corpus is firstly created. Then reordering rules are generated automatically by using the linguistic information from this parallel tagged aligned corpus. In this paper, function tag and part-of-speech tag reordering rule extraction algorithms are proposed to generate reordering rules automatically. These algorithms can be used for other language pairs which need reordering because these rules generation is only depend on part-of-speech tags and function tags.
Predicting the performance of general task graphs with underlying queueing model

The Glamis methodology provides a framework for performance modelling of parallel applications, based on a combination of task graph models and queueing network models. This paper presents a new, moderately cheap algorithm which enables the analysis of arbitrary task graph models of parallel programs with general precedence relationships, given a queueing model of the underlying machine. The algorithm generalises over an earlier algorithm. An extension to this algorithm is proposed to allow for the analysis of a certain type of mutual exclusion at the task level. The features of the methodology are illustrated by means of a case study, modelling a task graph executor running on a distributed-memory parallel machine. Measurements carried out on the actual machine, as well as simulations, are used to validate the predictions.
Productive Security: A Scalable Methodology for Analysing Employee Security Behaviours

Organisational security policies are often written without sufficiently taking in to account the goals and capabilities of the employees that must follow them. Effective security management requires that security managers are able to assess the effectiveness of their policies, including their impact on employee behaviour. We present a methodology for gathering large scale data sets on employee behaviour and attitudes via scenario-based surveys. The survey questions are grounded in rich data drawn from interviews, and probe perceptions of security measures and their impact. Here we study employees of a large multinational company, demonstrating that our approach is capable of determining important differences between various population groups. We also report that our work has been used to set policy within the partner organisation, illustrating the real-world impact of our research.
Protection in the Hydra Operating System

This paper describes the capability based protection mechanisms provided by the Hydra Operating System Kernel. These mechanisms support the construction of user-defined protected subsystems, including file and directory subsystems, which do not therefore need to be supplied directly by Hydra. In addition, we discuss a number of well known protection problems, including Mutual Suspicion, Confinement and Revocation, and we present the mechanisms that Hydra supplies in order to solve them.
A sub-module capacitor voltage balancing scheme for the Alternate Arm Converter (AAC)

A per-phase sub-module capacitor voltage balancing scheme for the Alternate Arm Converter (AAC) is proposed. Leg balancing regulates the sum of sub-module capacitor voltages in a leg to its set-point. Arm balancing regulates each sub-module capacitor voltage to the nominal sub-module capacitor voltage. Additional converter control requirements and the modulation scheme are also discussed. The control and modulation scheme has been verified by simulation. The leg balancing control loop was designed to be critically damped to primarily limit oscillations in the output variable caused by changes in AC-side power demands; the simulation results indicated this specification was met.
Perfusion imaging with NMR contrast agents

Knowledge of regional hemodynamics has widespread application for both physiological research and clinical assessment. Here we review the use of MR contrast agents to measure tissue perfusion. Two primary mechanisms of image contrast are discussed: relaxivity and susceptibility effects. Relaxivity effects result from dipolar enhancement of T1 and T2 rates. Because tissue T1 rates are intrinsically smaller, the dominant effect is shortening of T1 relaxation times. The second mechanism of image contrast is the variation in tissue magnetic field produced by heterogeneous distribution of high magnetic susceptibility agents. Quantitation of tissue perfusion requires a detailed understanding of the relation between contrast agent concentration and associated MR signal changes. Studies to date show a linear relationship between contrast agent concentration and rate change in most organs. The exact nature of this relationship in the dynamic setting of rapid contrast agent passage through the microcirculatory bed is less well established. If this relationship is known, tracer kinetic modeling can be used to calculate regional blood flow and blood volume. Data are presented which indicate that this approach is feasible, and suggest the potential of contrast‐enhanced NMR for high resolution in vivo mapping of both physiology and anatomy. © 1990 Academic Press, Inc.
Improving Recommender System's Efficiency Using Time Context and Group Preferences

By the expanse of internet stores and products, recommender systems have emerged to increase store attractiveness and develop online customers. Recommender systems are systems which help customers to find product that they want. These systems recommend product to individual customer according to their preferences and interests. Recommender systems use several ways such as collaborative filtering and content-based filtering to create recommendation. In this study we proposed a recommender system based on collaborative filtering. In proposed model we endeavored to improve the customer profile in collaborative systems to enhance the recommender system efficiency. We do this improvement using time context and group preferences.
Power Consumption in Spatial Cognitive Scenarios

Multiple Input Multiple Output (MIMO) adds a new dimension to be exploited in Cognitive Radio (CR) by simultaneously serving several users. The spatial domain that is added through MIMO is another system resource that has to be optimized, and shared when possible. In the current paper, we present a spatial sharing that is carried out through Zero Forcing beamforming (ZFB). The power consumption in such a scenario is mathematically formulated and compared to single user case, to check the feasibility of employing spatial cognition from the power's perspective. Interesting conclusions are obtained about the utility of spatial cognition thanks to the derived closed form expressions for the data rate and consumed power. To provide a comprehensive measure of the expediency of spatial cognitive scenario, a joint power and rate metric is also proposed and analyzed.
Response time analysis of slotted WiDOM in noisy wireless channels

Timely delivery of critical traffic is a major challenge in industrial applications. The Wireless Dominance (WiDOM) medium access control protocol offers a very large number of priority levels to suit time sensitive application requirements. In particular, assuming that its overhead is properly modeled, WiDOM enables an accurate evaluation of the network response time in the wireless domain, through the power of the schedulability analysis, based on non-preemptive and static-priority scheduling. Recent research proposed a new version of WiDOM (dubbed Slotted WiDOM), which offers a lower overhead as compared to the original version. In this paper, we propose a new schedulability analysis for Slotted WiDOM and extend it to handle message streams with release jitter. In order to provide a more accurate timing analysis, the effect of transmission faults must be taken into account. Therefore, in our novel analysis we consider the case where messages are transmitted in a realistic wireless channel, affected by noise and interference. Evaluation is performed on a real test-bed and the results from experiments provide a firm validation of our findings.
Epigenetic and Therapeutic Analysis of various Neurological Disorders

Neurological disorders are diseases of the central and peripheral nervous system. In this Review, It has been analysed epigenetic changes present in neurological diseases and discussed its therapeutic potential. The article has reviewed advances and considers approaches that may provide hope for alleviation of the disorders. This also reviews in this supplement focus on the neurobiology of a variety of these diseases of the central nervous system (CNS), including epilepsy, Alzheimer’s disease (AD), Parkinson’s disease (PD) and multiple sclerosis (MS).
A Survey of Capital Budgeting Techniques in the Public and Private Sectors of a Less Developed Country (LDC)

ABSTRACT This study surveys the capital budgeting practice in private and commercially-oriented public sector enterprises in the Sudan, an African Less Developed Country (LDC). The study attempts to fill a gap in the existing literature by documenting the capital budgeting practice in an LDC where the economic environment is different than the developed and developing counterparts and where public sector still plays a major role in the economy. The study found a sizable number of commercially-oriented public corporations that do not use capital budgeting techniques in their capital investment decisions while the majority of private sector companies use these methods. Among the corporations that use capital budgeting methods, both in the public and private sector, the payback method (PB) is the most widely used method, followed by the Internal Rate of Return (IRR) and Net Present Value (NPV) in the private sector and the public sector respectively. The study also revealed additional factors such as cost, size, quality, experience and hard currency requirements that affect the capital budgeting process in both sectors. However, there are differences in the level of importance of these factors between the two sectors.
Robust Statistical Model-Based Cell Image Interpretation

A robust and adaptable model-based scheme for cell image interpretation is presented that can accommodate the wide natural variation in the appearance of cells. This is achieved using multiple models and an interpretation process that permits a smooth transition between the models. Boundaries are represented using trainable statistical models that are invariant to transformatio ns of scaling, shift, rotation and contrast; a Gaussian and a circular autoregressive model (CAR) are investigated. The interpretation process optimises the match between models and data using a Bayesian distance measure. We demonstrate how objects that vary in both shape and grey-level pattern can be reliably segmented. The results presented show that the overall performance is comparable with that of manual segmentation; the area within the automatically detected and the manually selected cell boundaries that is not common to both is less than 5% in 96% of the cases tested. The results also show that the computationally simpler Gaussian boundary model is at least as effective as the CAR model.
Repeated Split-Belt Treadmill Training Improves Poststroke Step Length Asymmetry

Background and objective. Previous studies suggest that error augmentation may be used as a strategy to achieve longer-term changes in gait deficits after stroke. The purpose of this study was to determine whether longer-term improvements in step length asymmetry could be achieved with repeated split-belt treadmill walking practice using an error augmentation strategy. Methods. 13 persons with chronic stroke (>6 months) participated in testing: (1) prior to 12 sessions of split-belt treadmill training, (2) after the training, and (3) in follow-up testing at 1 and 3 months. Step length asymmetry was the target of training, so belt speeds were set to augment step length asymmetry such that aftereffects resulted in reduced step length asymmetry during overground walking practice. Each individual was classified as a “responder” or “nonresponder” based on whether their reduction in step length asymmetry exceeded day-to-day variability. Results. For the group and for the responders (7 individuals), step length asymmetry improved from baseline to posttesting (P < .05) through an increased step length on both legs but a relatively larger change on the shorter step side (P < .05). Other parameters that were not targeted (eg, stance time asymmetry) did not change over the intervention. Conclusions. This study demonstrates that short-term adaptations can be capitalized on through repetitive practice and can lead to longer-term improvements in gait deficits poststroke. The error augmentation strategy, which promotes stride-by-stride adjustment to reduce asymmetry and results in improved asymmetry during overground walking practice, appears to be critical for obtaining the improvements observed.
Behind the Scene of Solvers Competitions: the "evaluation" Experience

In principle, running a competition of solvers is easy: one just needs to collect solvers and benchmarks, run the experiments and publish the results. In practice, there are a number of issues that must be dealt with. This paper attempts to summarize the experience accumulated during the organization of several competitions: pseudo-Boolean, SAT and CSP/MaxCSP competitions.