Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive video redundancy coding for scene and channel adaptation over error-prone network

In this paper, a new error-resilient video coding method with scene adaptation is proposed, which is based on video redundancy coding (VRC) of H.263 version 2, formerly known as H.263+. The proposed error-resilient mechanism adaptively changes the VRC coding parameters for multiple threads according to the channel status. Also, the scene-adaptation is incorporated into the network-aware error resilient method in order to reduce the motion-jerkiness occurred by an abrupt scene change. Simulation results show that the proposed adaptive VRC mechanism does not only react properly to the time-varying network status, but also reduce fluctuations of the video quality.
Responses of Leaf Photosynthesis, Plant Growth and Fruit Production to Periodic Alteration of Plant Density in Winter Produced Single-truss Tomatoes

Tomato plants in greenhouse production are often confronted with light insufficiency in the lower canopy, especially in the winter low irradiation season. In this study, periodic alteration of plant density (PD) was proposed to improve the light environment of plants’ lower canopies, leaf photosynthesis, plant growth, and fruit development. These were investigated with winter cultivated tomatoes in a single-truss production system. Seedlings were transplanted to either movable or fixed cultivation benches for treatments with fixed PDs of 14.3 plants·m−2 (F14.3), and 10 plants·m−2 (F10), and unfixed PDs in a movable bench (MB; 25 plants·m−2 after transplanting to anthesis, 16.6 plants·m−2 at anthesis to initial fruit set, 12.5 plants·m−2 at fruit set to mature green, and 11.1 plants·m−2 at mature green to red-ripe). The leaf photosynthesis rates in MB and F10 were generally significantly higher than in F14.3. F14.3 had the tallest stems, but the lowest leaf area and shoot dry weight at end of experiment, while MB and F10 were not significantly different. MB had significantly the highest total yield, while the lowest data were observed in F10. The soluble solids content was increased in MB and F10 compared with F14.3, but no significant differences in ascorbic acid content or fruit hardness were observed among treatments. Therefore, a high PD in the vegetative stage, but a relatively lower PD in the fruit development stage, was highly efficient in intensive tomato cultivation.
Synthesis of a new type poly(vinyl alcohol)/peat/bamboo charcoal/KNO3 composite bead used as biofilter material

A new type poly(vinyl alcohol) (PVA)/peat/bamboo charcoal (BC)/KNO3 composite bead was prepared, which has a diameter of 2.4–6.0 mm and a density of 1.133 g/cm3 and is a porous spherical particle. The biochemical kinetic behaviors of n-butyl acetate in PVA/peat/BC/KNO3 spherical composite bead biofilter (BC biofilter) and PVA/peat/granular activated carbon (GAC)/KNO3 spherical composite bead biofilter (GAC biofilter) were investigated. The values of half-saturation constant Ks for BC biofilter and GAC biofilter were 27.89 and 27.95 ppm, respectively. The values of maximum reaction rate Vm for BC biofilter and GAC biofilter were 13.49 and 13.65 ppm/s, respectively. Zero-order kinetic with the diffusion limitation was regarded as the most adequate biochemical reaction model for the two biofilters. The microbial growth rate and biochemical reaction rate for two biofilters were inhibited at higher inlet concentration, and the degree of inhibitive effect was more pronounced in the inlet concentration range of 100–800 ppm. The biochemical kinetic behaviors of the two biofilters were similar. The maximum elimination capacity of BC biofilter and GAC biofilter were 111.65 and 122.67 g C/h m3 bed volume, respectively. The PVA/peat/BC/KNO3 composite bead was suitable as a biofilter material. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011
Towards Real-Time Analytics in the Cloud

The data explosion and the tremendous growth in the volume of data generated from various IT services places an enormous demand on harnessing and smartly analyzing the generated data and enterprise contents. According to recent studies, it is predicted that the volume of such data will become 26 fold in the next five years. While there might be some existing technologies to support this, industry is frantically exploring new models that lead to more efficient and higher performance solutions. With the aid of cloud computing and high performance analytics such as scalable-parallel machine learning, big data could be the fuel to a smarter cloud-powered IT world. Through our work, we provide a state-of-the-art review of high-performance advanced cloud analytics in the literature in attempt to find the ideal real-time platform for distributed analytic computations.
OASIS: Self-tuning Storage for Applications

This paper introduces OASIS, a self-tuning storage management architecture that allows applications and the storage environment to negotiate resource allocations without requiring human intervention. The goal of OASIS is to maximize the utilization of all the storage resources in the storage area network subject to fairness in the allocation of resources to applications. To achieve this goal, OASIS continually inspects the application’s I/O behavior, and determines the application’s storage requirements automatically. Subsequently, OASIS communicates this information from the applications to a storage manager by means of a communication protocol that isolates the complexities of applications and storage from each other. The OASIS framework includes algorithms to dynamically and continuously map application requirements into appropriate low-level resource allocations. A key advantage of OASIS over best-effort systems is the ability to fairly share storage resources between workloads of varying characteristics. What distinguishes OASIS from other managed systems however, is its self-tuning nature. We implemented a prototype of the OASIS architecture and performed experiments on a set of competing synthetic workloads derived from traces. Our results show that OASIS is able to detect the bandwidth and latency requirements of the competing workloads and generate a fairer allocation of storage resources than a best-effort approach. More importantly, experience with a real-life database scenario, shows that OASIS is able to satisfy the bandwidth requirements of competing multi-threaded workloads without any storage administrator input. In particular, OASIS is able to identify an under-performing workload and ensure it receives a fair share of the overall storage system resources, resulting in a performance increase by as much as a factor of five for that workload over best-effort resource allocation.
A simple and expressive semantic framework for policy composition in access control

In defining large, complex access control policies, one would like to compose sub-policies, perhaps authored by different organizations, into a single global policy. Existing policy composition approaches tend to be ad-hoc, and do not explain whether too many or too few policy combinators have been defined. We define an access controlpolicy as a four-valued predicate that maps accesses to either grant, deny, conflict, or unspecified. These correspond to the four elements of the Belnap bilattice. Functions on this bilattice are then extended to policies to serve as policy combinators. We argue that this approach provides a simple andnatural semantic framework for policy composition, with a minimal but functionally complete set of policy combinators. We define derived, higher-level operators that are convenient for the specification of access control policies, and enable the decoupling of conflict resolution from policy composition. Finally, we propose a basic query language and show that it can reduce important analyses (e.g., conflict analysis) to checks of policy refinement.
Matricellular proteins as modulators of wound healing and the foreign body response

Summary Matricellular proteins form a group of extracellular matrix (ECM) proteins that do not subserve a primary structural role, but rather function as modulators of cell-matrix interactions (1). Members of the group, including thrombospondin (TSP) -1, TSP-2, SPARC, tenascin (TN)-C, and osteopontin (OPN), have been shown to participate in a number of processes related to tissue repair. Specifically, studies in knockout mice have indicated that a deficiency in one or more of these proteins can alter the course of wound healing. More recently, TSP1, TSP2, and SPARC have also been implicated in the foreign body response, an unusual reaction to injury that occurs after the implantation of biomaterials. This review will focus on the roles of these proteins in the response to injury in mice and will show how studies of this pathophysiological process can elucidate some of the intrinsic properties of these matricellular proteins.
Yolk testosterone reduces oxidative damages during postnatal development

Conditions experienced during early life can influence the development of an organism and several physiological traits, even in adulthood. An important factor is the level of oxidative stress experienced during early life. In birds, extra-genomic egg substances, such as the testosterone hormone, may exert a widespread influence over the offspring phenotype. Interestingly, testosterone can also upregulate the bioavailability of certain antioxidants but simultaneously increases the susceptibility to oxidative stress in adulthood. However, little is known about the effects of maternally derived yolk testosterone on oxidative stress in developing birds. Here, we investigated the role of yolk testosterone on oxidative stress of yellow-legged gull chicks during their early development by experimentally increasing yolk testosterone levels. Levels of antioxidants, reactive oxygen species and lipid oxidative damage were determined in plasma during nestlings' growth. Our results revealed that, contrary to control chicks, birds hatched from testosterone-treated eggs did not show an increase in the levels of oxidative damage during postnatal development. Moreover, the same birds showed a transient increase in plasma antioxidant levels. Our results suggest that yolk testosterone may shape the oxidative stress-resistance phenotype of the chicks during early development owing to an increase in antioxidant defences and repair processes.
TNF-α enhancement of CD62E mediates adhesion of non–small cell lung cancer cells to brain endothelium via CD15 in lung-brain metastasis

Background CD15, which is overexpressed on various cancers, has been reported as a cell adhesion molecule that plays a key role in non-CNS metastasis. However, the role of CD15 in brain metastasis is largely unexplored. This study provides a better understanding of CD15/CD62E interaction, enhanced by tumor necrosis factor-α (TNF-α), and its correlation with brain metastasis in non–small cell lung cancer (NSCLC). Methods CD15 and E-selectin (CD62E) expression was demonstrated in both human primary and metastatic NSCLC cells using flow cytometry, immunofluorescence, and Western blotting. The role of CD15 was investigated using an adhesion assay under static and physiological flow live-cell conditions. Human tissue sections were examined using immunohistochemistry. Results CD15, which was weakly expressed on hCMEC/D3 human brain endothelial cells, was expressed at high levels on metastatic NSCLC cells (NCI-H1299, SEBTA-001, and SEBTA-005) and at lower levels on primary NSCLC (COR-L105 and A549) cells (P < .001). The highest expression of CD62E was observed on hCMEC/D3 cells activated with TNF-α, with lower levels on metastatic NSCLC cells followed by primary NSCLC cells. Metastatic NSCLC cells adhered most strongly to hCMEC/D3 compared with primary NSCLC cells. CD15 immunoblocking decreased cancer cell adhesion to brain endothelium under static and shear stress conditions (P < .0001), confirming a correlation between CD15 and cerebral metastasis. Both CD15 and CD62E expression were detected in lung metastatic brain biopsies. Conclusion This study enhances the understanding of cancer cell-brain endothelial adhesion and confirms that CD15 plays a crucial role in adhesion in concert with TNF-α activation of its binding partner, CD62E.
Dynamic gesture recognition using neural networks: a fundament for advanced interaction construction

Interaction in virtual reality environments is still a challenging task. Static hand posture recognition is currently the most common and widely used method for interaction using glove input devices. In order to improve the naturalness of interaction, and thereby decrease the user-interface learning time, there is a need to be able to recognize dynamic gestures. In this paper we describe our approach to overcoming the difficulties of dynamic gesture recognition (DGR) using neural networks. Backpropagation neural networks have already proven themselves to be appropriate and efficient for posture recognition. However, the extensive amount of data involved in DGR requires a different approach. Because of features such as topology preservation and automatic-learning, Kohonen Feature Maps are particularly suitable for the reduction of the high dimensional data space that is the result of a dynamic gesture, and are thus implemented for this task.
Complementary limb motion estimation for the control of active knee prostheses

Abstract To restore walking after transfemoral amputation, various actuated exoprostheses have been developed, which control the knee torque actively or via variable damping. In both cases, an important issue is to find the appropriate control that enables user-dominated gait. Recently, we suggested a generic method to deduce intended motion of impaired or amputated limbs from residual human body motion. Based on interjoint coordination in physiological gait, statistical regression is used to estimate missing motion. In a pilot study, this complementary limb motion estimation (CLME) strategy is applied to control an active knee exoprosthesis. A motor-driven prosthetic knee with one degree of freedom has been realized, and one above-knee amputee has used it with CLME. Performed tasks are walking on a treadmill and alternating stair ascent and descent. The subject was able to walk on the treadmill at varying speeds, but needed assistance with the stairs, especially to descend. The promising results with CLME are compared with the subject's performance with her own prosthesis, the C-Leg from Otto Bock.
Comparing word, character, and phoneme n-grams for subjective utterance recognition

In this paper, we compare the performance of classifiers trained using word n-grams, character n-grams, and phoneme n-grams for recognizing subjective utterances in multiparty conversation. We show that there is value in using very shallow linguistic representations, such as character n-grams, for recognizing subjective utterances, in particular, gains in the recall of subjective utterances. Copyright © 2008 ISCA.
Improving Image Quality in Remote Sensing Satellites using Channel Coding

Among other factors that characterize satellite commu- nication channels is their high bit error rate. We present a system for still image transmission over noisy satellite channels. The system couples image compression together with error control codes to improve the received image quality while maintaining its bandwidth requirements. The proposed system is tested using a high resolution satellite imagery simulated over the Rician fading channel. Evaluation results show improvement in overall system including image quality and bandwidth requirements compared to similar systems with dif- ferent coding schemes.
Total Jitter of Delay-Locked Loops Due to Four Main Jitter Sources

There are four main sources of jitter in delay-locked loops (DLLs). In this paper, DLL's jitter due to uncertainties in these sources of jitter is calculated. Time domain equations of DLL are introduced, which are the key parameters to obtain a closed-form equation related to jitter of DLL in the presence of noisy phase-frequency detector, charge pump, delay cells, and reference clock. First, DLL's jitter at the output of each delay cells due to each sources of the jitter will be calculated. Then, the obtained equations are used to calculate the total jitter at the output of all stages. Finally, a DLL is designed in the 0.18-μm CMOS technology to validate the obtained equations.
Clinical classification of psychogenic non-epileptic seizures based on video-EEG analysis and automatic clustering

Background Psychogenic non-epileptic seizures (PNES) or attacks consist of paroxysmal behavioural changes that resemble an epileptic seizure but are not associated with electrophysiological epileptic changes. They are caused by a psychopathological process and are primarily diagnosed on history and video-EEG. Clinical presentation comprises a wide range of symptoms and signs, which are individually neither totally specific nor sensitive, making positive diagnosis of PNES difficult. Consequently, PNES are often misdiagnosed as epilepsy. The aim of this study was to identify homogeneous groups of PNES based on specific combinations of clinical signs with a view to improving timely diagnosis. Methods The authors first retrospectively analysed 22 clinical signs of 145 PNES recorded by video-EEG in 52 patients and then conducted a multiple correspondence analysis and hierarchical cluster analysis. Results Five clusters of signs were identified and named according to their main clinical features: dystonic attack with primitive gestural activity (31.6%); pauci-kinetic attack with preserved responsiveness (23.4%); pseudosyncope (16.9%); hyperkinetic prolonged attack with hyperventilation and auras (11.7%); axial dystonic prolonged attack (16.4%). When several attacks were recorded in the same patient, they were automatically classified in the same subtype in 61.5% of patients. Conclusion This study proposes an objective clinical classification of PNES based on automatic clustering of clinical signs observed on video-EEG. It also suggests that PNES are stereotyped in the same patient. Application of these findings could help provide an objective diagnosis of patients with PNES.
Strain of experimental animals and modulation of nitric oxide pathway: their influence on development of renal failure in an experimental model of hepatorenal syndrome

Introduction Pathomechanism of HRS is still poorly understood. The aim of our study was: (1) to test whether different strains of rats could develop typical HRS, and (2) to estimate the influence of activation and inhibition of nitric oxide for development of renal failure in course of HRS. Material and methods First, we used 16 of Wistar and 16 of Sprague-Dawley rats in galactosamine model of HRS. Next, we used 48 of SDR rats, which received saline, N-nitro-L-arginine or L-arginine before and after liver damage. Twenty four hours urine and blood samples were collected 48 h after saline or Ga1N injection. Biochemical parameters were determined in serum or urine and then creatinine clearance and osmolality clearance were calculated. Liver and kidney tissues were collected for histopathological examination. Results Liver failure developed in all tested groups with significant increase of bilirubin (p < 0.001), ALT (p < 0.001) and ammonia (p < 0.001). Nevertheless we did not achieve any evidence of renal failure in Wistar, but we found typical renal failure in Sprague-Dawley group with significant decrease in creatinine clearance (p < 0.0012) and increase in concentration of creatinine and urea (p < 0.001) and (p < 0.001) respectively. Inhibition of NOS prevented development of renal failure with significant improvement of GFR both before (p < 0.0017) and after (p < 0.003) Ga1N injection. Injection of L-arginine after Ga1N injection did not caused significant improvement of GFR. Conclusions Our study showed, that genetic factors might be responsible for development of renal failure in course of HRS and nitric oxide play important role in acute model of this syndrome.
Adaptive CSMA Under the SINR Model: Efficient Approximation Algorithms for Throughput and Utility Maximization

We consider a carrier sense multiple access (CSMA)-based scheduling algorithm for a single-hop wireless network under a realistic signal-to-interference-plus-noise ratio model for the interference. We propose two local optimization-based approximation algorithms to efficiently estimate certain attempt rate parameters of CSMA called fugacities. It is known that adaptive CSMA can achieve throughput optimality by sampling feasible schedules from a Gibbs distribution, with appropriate fugacities. Unfortunately, obtaining these optimal fugacities is an NP-hard problem. Furthermore, the existing adaptive CSMA algorithms use a stochastic gradient descent-based method, which usually entails an impractically slow (exponential in the size of the network) convergence to the optimal fugacities. To address this issue, we first propose an algorithm to estimate the fugacities, that can support a given set of desired service rates. The convergence rate and the complexity of this algorithm are independent of the network size, and depend only on the neighborhood size of a link. Furthermore, we show that the proposed algorithm corresponds exactly to performing the well-known Bethe approximation to the underlying Gibbs distribution. Then, we propose another local algorithm to estimate the optimal fugacities under a utility maximization framework, and characterize its accuracy. Numerical results indicate that the proposed methods have a good degree of accuracy, and achieve extremely fast convergence to near-optimal fugacities, and often outperform the convergence rate of the stochastic gradient descent by a few orders of magnitude.
Flow behaviour and microstructure evolution in novel SiO2/PP/LCP ternary composites: effects of filler properties and mixing sequence

When silica (SiO2) fillers were introduced into the polypropylene (PP) and liquid-crystalline polymer (LCP) blend, it was found that the mixing sequence, the filler size, and the filler surface nature affected the rheology of the composites and the morphology of the LCP phase in the ternary composite. In particular, the compatibility between the filler and the PP matrix was found to exert a strong influence on the droplet-fibril transition. The incorporation of the hydrophobic silica to the LCP/PP blend facilitated the fibrillation of LCP because the hydrophobic filler demonstrated affinity towards the hydrophobic PP matrix. The preferential residence of the hydrophobic silica in the PP phase would minimise the LCP domain disruption leading to the formation of LCP fibrils with high aspect ratios. The use of fine filler and in situ blending, which promoted the filler–LCP interaction, could prevent coalescence, inhibit deformation and hinder fibril development as well. © 2003 Society of Chemical Industry