Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient simulation of large-scale p2p networks: packet-level vs. flow-level simulations

Peer-to-peer (P2P) networks can reduce the distribution cost of large media files for the original provider of the data significantly. Thereby, the BitTorrent protocol is widely used in the Internet today. Most research work studies the protocol analytically, by simulations at the flow-level or real world experiments. Thereby, for flow-level simulations the influence of neglecting packet-level characteristics is not yet quantified. Therefore, this paper compares packet-level simulation results with flow-level values and analytically derived bounds. Our findings show that BitTorrent is near to optimal at flow-level for different scenarios. Naturally, packet-level results deviate more from the optimal values but differences are at most around 30% in our simulations. Furthermore, we show that the propagation delay can significantly influence the download performance of BitTorrent.
Direction-Optimizing Breadth-First Search on CPU-GPU Heterogeneous Platforms

Breadth-First Search (BFS) is a basis for many graph traversal and analysis algorithms. In this paper, we present a direction-optimizing BFS implementation on CPU-GPU heterogeneous platforms to fully exploit the computing power of both the multi-core CPU and GPU. For each level of the BFS algorithm, we dynamically choose the best implementation from: a sequential top-down execution on CPU, a parallel top-down execution on CPU, and a cooperative bottom-up execution on CPU and GPU. By adapting to the runtime variability of vertex frontiers, such a hybrid approach provides the best performance for the exploration of each BFS level while avoiding poor worst case performance. Our implementation demonstrates speedups of 1.37 to 1.44 compared to the highest published performance for shared memory systems.
Optimization of Electric Field Parameters for HT29 Cell Line towards Wound Healing Application

Objective: The aim of this study is to optimize the electric field parameter for HT-29 cells line towards wound healing application. Methods: Cells were harvested when they reached 70% to 80% confluent. Afterward, 800 μl of the cells suspension were poured into a 4 mm cuvette and placed in the BTX ECM 830 Electroporator chamber. Voltages in the range of 80 V to 800 V and pulse durations in the range of 100 μs to 10 ms were used in electroporating the cells. After treatment, 300 μl of the cells suspension from each sample were seeded in a well of 6-wells plates each containing 2 ml of pre-warm complete growth medium and incubated at 37oC and 5% CO2 for 48 hours. Findings: The results obtained in this research quantitatively reveal the dependence of cell proliferation on electrical parameters. 200, 400, 600 and 800 V/cm electric field strengths at duration of 500 μs showed 42%, 63%, 86% and 36% increase in proliferation rate after 48 hours in culture as compared to initial plating densities, respectively. The control group and 1000 V/cm at 100 μs showed 48% and 33% increase in proliferation rate respectively as compared to initial seeding density. While electric field strengths of 1200-2000 V/cm at 200 V/cm interval and at 100 μs duration, revealed a decrease in proliferation rate by 4%, 15%, 18%, 23% and 26% respectively as compared to initial seeding density. Applications: It was found that 600 V/cm at 500 μs induced the highest proliferation rate (86%) as compared to initial seeding density after 48 hours of culture (that is 38% greater than the control group). This study can further be investigated for the use of the pulse electric field in facilitating drug-free wound healing process.
Foot-and-Mouth Disease Virus Induces Autophagosomes during Cell Entry via a Class III Phosphatidylinositol 3-Kinase-Independent Pathway

ABSTRACT Autophagy is an intracellular pathway that can contribute to innate antiviral immunity by delivering viruses to lysosomes for degradation or can be beneficial for viruses by providing specialized membranes for virus replication. Here, we show that the picornavirus foot-and-mouth disease virus (FMDV) induces the formation of autophagosomes. Induction was dependent on Atg5, involved processing of LC3 to LC3II, and led to a redistribution of LC3 from the cytosol to punctate vesicles indicative of authentic autophagosomes. Furthermore, FMDV yields were reduced in cells lacking Atg5, suggesting that autophagy may facilitate FMDV infection. However, induction of autophagosomes by FMDV appeared to differ from starvation, as the generation of LC3 punctae was not inhibited by wortmannin, implying that FMDV-induced autophagosome formation does not require the class III phosphatidylinositol 3-kinase (PI3-kinase) activity of vps34. Unlike other picornaviruses, for which there is strong evidence that autophagosome formation is linked to expression of viral nonstructural proteins, FMDV induced autophagosomes very early during infection. Furthermore, autophagosomes could be triggered by either UV-inactivated virus or empty FMDV capsids, suggesting that autophagosome formation was activated during cell entry. Unlike other picornaviruses, FMDV-induced autophagosomes did not colocalize with the viral 3A or 3D protein. In contrast, ∼50% of the autophagosomes induced by FMDV colocalized with VP1. LC3 and VP1 also colocalized with the cellular adaptor protein p62, which normally targets ubiquitinated proteins to autophagosomes. These results suggest that FMDV induces autophagosomes during cell entry to facilitate infection, but not to provide membranes for replication.
Reliability and sensitivity of visible liquid penetrant NDT for inspection of welded components

Abstract Welding, as an approach to join components, is used extensively by various industries. Generating several types of defects is one of the major weaknesses of the technique. Thus, inspection to detect the defects is normally considered as a stage of welding procedure. One of the main categories of the defects is surface cracks, which are found by nondestructive testing methods. However, visible liquid penetrant as a technique to reveal this kind of flaws is broadly used, the method capabilities in defect detection of welded components have not been comprehensively studied. In this paper, utilizing reliability and sensitivity concepts of nondestructive testing, its abilities in detecting of surface crack of welded joints are investigated. The results of the paper illustrate that the detection and missing rates are 52 % and 48 %. In addition, taking into account 95 % degree of confidence, probability of detection for defects with length equal to 3.73 mm is 90 %.
Improving efficiency of dynamic analysis with dynamic dependence summaries

Modern applications make heavy use of third-party libraries and components, which poses new challenges for efficient dynamic analysis. To perform such analyses, transitive dependent components at all layers of the call stack must be monitored and analyzed, and as such may be prohibitively expensive for systems with large libraries and components. As an approach to address such expenses, we record, summarize, and reuse dynamic dataflows between inputs and outputs of components, based on dynamic control and data traces. These summarized dataflows are computed at a fine-grained instruction level; the result of which, we call “dynamic dependence summaries. ” Although static summaries have been proposed, to the best of our knowledge, this work presents the first technique for dynamic dependence summaries. The benefits to efficiency of such summarization may be afforded with losses of accuracy. As such, we evaluate the degree of accuracy loss and the degree of efficiency gain when using dynamic dependence summaries of library methods. On five large programs from the DaCapo benchmark (for which no existing whole-program dynamic dependence analyses have been shown to scale) and 21 versions of NANOXML, the summarized dependence analysis provided 90% accuracy and a speed-up of 100% (i.e., ×2), on average, when compared to traditional exhaustive dynamic dependence analysis.
RNA Interference Therapies for an HIV-1 Functional Cure

HIV-1 drug therapies can prevent disease progression but cannot eliminate HIV-1 viruses from an infected individual. While there is hope that elimination of HIV-1 can be achieved, several approaches to reach a functional cure (control of HIV-1 replication in the absence of drug therapy) are also under investigation. One of these approaches is the transplant of HIV-1 resistant cells expressing anti-HIV-1 RNAs, proteins or peptides. Small RNAs that use RNA interference pathways to target HIV-1 replication have emerged as competitive candidates for cell transplant therapy and have been included in all gene combinations that have so far entered clinical trials. Here, we review RNA interference pathways in mammalian cells and the design of therapeutic small RNAs that use these pathways to target pathogenic RNA sequences. Studies that have been performed to identify anti-HIV-1 RNA interference therapeutics are also reviewed and perspectives on their use in combination gene therapy to functionally cure HIV-1 infection are provided.
The Case for an Internal Dynamics Model versus Equilibrium Point Control in Human Movement

The equilibrium point hypothesis (EPH) was conceived as a means whereby the central nervous system could control limb movements by a relatively simple shift in equilibrium position without the need to explicitly compensate for task dynamics. Many recent studies have questioned this view with results that suggest the formation of an internal dynamics model of the specific task. However, supporters of the EPH have argued that these results are not incompatible with the EPH and that there is no reason to abandon it. In this study, we have tested one of the fundamental predictions of the EPH, namely, equifinality. Subjects learned to perform goal‐directed wrist flexion movements while a motor provided assistance in proportion to the instantaneous velocity. It was found that the subjects stopped short of the target on the trials where the magnitude of the assistance was randomly decreased, compared to the preceding control trials (P= 0.003), i.e. equifinality was not achieved. This is contrary to the EPH, which predicts that final position should not be affected by external loads that depend purely on velocity. However, such effects are entirely consistent with predictions based on the formation of an internal dynamics model.
Limits to multiantenna capacity of spatially selective channels

In this paper we present a new upper bound on the mutual information of MIMO systems. By characterizing the fundamental communication modes between two physical regions, we develop an intrinsic capacity which is independent of antenna array geometries and array signal processing, and depends only on the size of the regions and the statistics of the scattering environment.
Governing the Global Commons with Local Institutions

Most problems faced by modern human society have two characteristics in common - they are tragedy-of-the-commons type of problems, and they are global problems. Tragedy-of-the-commons type of problems are those where a commonly shared resource is overexploited by free riders at the expense of everyone sharing the resource. The exploitation of global resources such as clean air and water, political stability and peace, etc. underlies many of the most pressing human problems. Punishment of free riding behavior is one of the most frequently used strategies to combat the problem, but the spatial reach of sanctioning institutions is often more limited than the spatial effects of overexploitation. Here, we analyze a general game theoretical model to assess under what circumstances sanctioning institutions with limited reach can maintain the larger commons. We find that the effect of the spatial reach has a strong effect on whether and how the commons can be maintained, and that the transitions between those outcomes are characterized by phase transitions. The latter indicates that a small change in the reach of sanctioning systems can profoundly change the way the global commons can be managed.
The Effect of the Neurogranin Schizophrenia Risk Variant rs12807809 on Brain Structure and Function

A single nucleotide polymorphism rs12807809 located upstream of the neurogranin (NRGN) gene has been identified as a risk variant for schizophrenia in recent genome-wide association studies. To date, there has been little investigation of the endophenotypic consequences of this variant, and our own investigations have suggested that the effects of this gene are not apparent at the level of cognitive function in patients or controls. Because the impact of risk variants may be more apparent at the level of brain, the aim of this investigation was to delineate whether NRGN genotype predicted variability in brain structure and/or function. Healthy individuals participated in structural (N = 140) and/or functional (N = 36) magnetic resonance imaging (s/fMRI). Voxel-based morphometry was used to compare gray and white matter volumes between carriers of the non-risk C allele (i.e., CC/CT) and those who were homozygous for the risk T allele. Functional imaging data were acquired during the performance of a spatial working memory task, and were also analyzed with respect to the difference between C carriers and T homozygotes. There was no effect of the NRGN variant rs12807809 on behavioral performance or brain structure. However, there was a main effect of genotype on brain activity during performance of the working memory task, such that while C carriers exhibited a load-independent decrease in left superior frontal gyrus/BA10, TT individuals failed to show a similar decrease in activity. The failure to disengage this ventromedial prefrontal region, despite preserved performance, may be indicative of a reduction in processing efficiency in healthy TT carriers. Although it remains to be established whether this holds true in larger samples and in patient cohorts, if valid, this suggests a potential mechanism by which NRGN variability might contribute to schizophrenia risk.
Recognition and Localization of a Flat Symmetric Object from a Single Perspective Image

ABSTRACT A flat symmetric object viewed under perspective (orthographic) projectiorl yields a conver- gent (skew) symmetry. Unlike skew symmetry where the axes constrain the orientation of the underlying object to lie on a hyperbola in the gradient space, for convergent symme- try the object orientation can be uniquely determined from the axis and convergent point except for some special cases. However, detection of the axis and convergent point of a convergent symmetry has not yet received much attention. We present a technique which can detect the axis and convergent point of a convergent symmetric contmour in an image using distinguished points such as bitangents, corners, and inflection points on the contour. In addition to recovering the orientation of an object directly from the axis and convergent point of its convergent symmetry, when a model database is available, our technique is also able to recognize and locate the object by using the cross ratio as an indexing function. The orientation information is also used for verification purposes. Our technique is simple, efficient, and accurate. It is also robust to noise and partial occlusion. Experimental results on real images are shown.
A fabrication process to make CNT/EP composite strain sensors

Carbon nanotube (CNT)/epoxy resin (EP) conductive composite can be obtained by solidifying the mixture of CNT and EP at specific temperature. The conductivity of the CNT/EP composite rises as the CNT content increases. It has been proven that the electrical resistance of a CNT/EP film varies when it experiences tension or compression. Therefore, the current research focuses on the design of strain sensors, based on the piezoresistivity of CNT/EP composite. In this article, an efficient method used to fabricate CNT/EP sensors is introduced in detail. One main novelty of the present method is that it provides an easy process to install metal electrodes for each piece of CNT/EP film. Another importance of the method is that it tackles the obstacles on the way to bulk production. A cantilever beam system was used to test the sensors fabricated through the self-developed process. The experimental results show that the sensors have consistent properties, and their gauge factors are much higher than that of typical foil strain gauges.
Optimized Heart Failure Therapy and Complete Anemia Correction on Left-Ventricular Hypertrophy in Nondiabetic and Diabetic Patients Undergoing Hemodialysis

Background: According to new guidelines, diabetes mellitus per se can be considered as stage I chronic heart failure (CHF). Available evidence suggests that patients suffering from both diabetes mellitus and renal insufficiency have disproportionately high rates of left-ventricular hypertrophy (LVH). Methods: Optimized heart failure therapy, including β-blockers, ACE-inhibitors and AT II-type-1-receptor-blockers, was prescribed in combination with complete anemia correction using epoetin beta (target hemoglobin: 13.5 g/dl for women; 14.5 g/dl for men) to 230 patients (55% male) with ambulatory hemodialysis, including 60 patients (52% male) with diabetes. Echocardiographic follow-up examinations were performed over a mean period of 4.4 ± 1.2 years. Results: Mean hemoglobin levels at the study end significantly increased to target levels in the entire study population and in patients with diabetes (both p < 0.001). Compared with baseline, significant improvements were seen in hemodialysis patients – both without and with diabetes – in left-ventricular mass index (–28.8 g/m2 [p < 0.001] and 29.0 g/m2 [p < 0.005], respectively), left-ventricular ejection fraction (+7.0% [p < 0.001] and +8.3% [p < 0.01], respectively) and in NYHA class (–0.84 [p < 0.01] and –1.12 [p < 0.01], respectively). Similar to the results in the overall population, a highly significant reduction in LVH (p < 0.005) and significant improvements in LVEF (p < 0.01) and NYHA class (p < 0.01) were seen in the high-risk subgroup of diabetic patients. Conclusions: Patients undergoing hemodialysis, with or without concomitant diabetes, benefit considerably from optimized, multifactorial heart failure therapy combined with complete anemia correction.
The role of the striatum in aversive learning and aversive prediction errors

Neuroeconomic studies of decision making have emphasized reward learning as critical in the representation of value-driven choice behaviour. However, it is readily apparent that punishment and aversive learning are also significant factors in motivating decisions and actions. In this paper, we review the role of the striatum and amygdala in affective learning and the coding of aversive prediction errors (PEs). We present neuroimaging results showing aversive PE-related signals in the striatum in fear conditioning paradigms with both primary (shock) and secondary (monetary loss) reinforcers. These results and others point to the general role for the striatum in coding PEs across a broad range of learning paradigms and reinforcer types.
Implementing Improved Algorithm Over APRIORI Data Mining Association Rule Algorithm

In this paper we present new scheme for extracting association rules that considers the time, number of database scans, memory consumption, and the interestingness of the rules. Discover a FIS data mining association algorithm that removes the disadvantages of APRIORI algorithm and is efficient in terms of number of database scan and time. The frequent patterns algorithm without candidate generation eliminates the costly candidate generation. It also avoids scanning the database again and again. So, we use Frequent Pattern (FP) Growth ARM algorithm that is more efficient structure to mine patterns when database grows. I. Introduction Data mining is the core process of " KNOWLEDGE DISCOVERY IN DATABASE ". It is the process of extraction of useful patterns from the large database. To analyze the large amounts of collected information, the area of Knowledge Discovery in Databases (KDD) provides techniques which extract interesting patterns in a reasonable amount of time. Therefore, KDD employs methods at the cross point of machine learning, statistics and database systems. Data mining is the application of efficient algorithms to detect the desired patterns contained within the given data.
AN IMPROVED ENDMEMBER EXTRACTION ALGORITHM BY INVERSING LINEAR MIXING MODEL

In hyperspectral imagery there are some cases when no pure pixels present due to the limitation of the sensors’ space resolution and the complexity of the ground components, and then the endmembers extracted by traditional algorithms are usually mixing ones still. In order to solve this problem, this paper proposes an endmember extraction algorithm based on the re-analysis of preliminary endmembers extracted by volume calculating concept under the linear mixing model. After extracting the pixels which are most approximated to the pure pixels from the image, using the convex polyhedron’s geometric characters to search out the boundary pixels which are around the preliminary endmembers and on the edge of the convex polyhedron formed by the pure pixels. Calculating the abundance fractions of every endmember in these pixels by the laws of sins, thus, with these coefficients the endmembers could be obtained using the inversion of linear mixing model. Hyperspectral scenes are simulated by the real spectra to investigate the performance of the algorithm. Preliminary results indicate the effectiveness of the algorithm. Applying the algorithm to a real Hyperion scene it also gets a better result.
Achievable Sum-Rates in MIMO Broadcast Channels with Vector Precoding Techniques Using Coded Modulation

In this paper we establish end-to-end achievable sum-rates of different linear and non-linear pre-processing techniques employing amplitude-shift keying (ASK)-modulation in a flat-fading multiple input multiple output (MIMO) broadcast system with single antenna terminals. The obtained results reveal that the minimum mean square error vector precoding (MMSE-VP) technique achieve close to capacity performance in various system settings. Thus it achieves a loss of merely 2-3 dB compared to the sum-capacity in the mid to high SNR range including the effects of practical system implementations, such as a non-ideal modulation set and a sub-optimal solver at the transmitter. When the SNR is low or when the system experience a small load, simpler pure linear techniques achieve similar performance.
Fast information sharing in networks of autonomous agents

A new nonlinear protocol is proposed for state consensus of multi-agent systems in this paper. It is shown that this protocol can provide faster convergence rate than the typical linear protocol, presented by Olfati-Saber and Murray, and furthermore guarantees the states of agents reach a consensus in finite time, provided that the interaction topology, represented by a directed graph, has a spanning tree.