Miracle-dz/UniFAR-FTUs huggingface dataset:
Differentiated Services: A New Direction for Distinguishing Congestion Losses from Wireless Losses

Currently, a TCP sender considers all losses as congestion signals and reacts to them by throttling the sending rate. With Internet becoming more heterogeneous with wireless error-prone links, a TCP connection may unduly throttle its sending rate and experience a poor performance over non congested paths. A closed form expression is developed for the expected improvement of TCP throughput if TCP can differentiate congestion losses and react appropriately. Differentiated Services (Diffserv) offer a new opportunity to enable a TCP sender to identify accurately wireless losses and react appropriately. A technique based on Diffserv is proposed to accurately differentiate congestion losses from other types of losses. This technique is supported by a simple probablistic argument and evaluated through simulations. Congestion losses are identified with an accuracy of 95%. Wireless losses are identified with an accuracy higher than 70%. We propose TCP-Casablanca which is TCP-Newreno endowed with our discriminator. With TCP-Casablanca, an improvement of up to 150% is observed on paths lightly congested with mild wireless error rates.
Action Recognition Using Convolutional Restricted Boltzmann Machines

In this work we study deep learning architectures for the problem of action recognition in image sequences focusing on generative neural networks, namely the convolutional extension of restricted Boltzmann machines (RBMs). We first use a stack of convolutional restricted Boltzmann machines to learn and extract features from sequences of images in an unsupervised way, and then use them for the task of action classification. We modify the energy function of the convolutional RBM in such a way that the training updates reported in the literature follow directly from the differentiation of the objective function, which we define in terms of the free energy function. This is in contrast to other works on convolutional RBMs in the literature whose update equations do not directly follow from a well defined energy function or optimization framework without any ad hoc normalizations. We show that the representations that are derived from unsupervised training of the RBMs have very similar or better descriptive power than hand-designed image descriptors and give competitive performance in the problem of action recognition.
Burkholderia mallei expresses a unique lipopolysaccharide mixture that is a potent activator of human Toll-like receptor 4 complexes

Burkholderia mallei, the aetiologic agent of glanders, causes a variety of illnesses in animals and humans ranging from occult infections to acute fulminating septicaemias. To better understand the role of lipopolysaccharide (LPS) in the pathogenesis of these diseases, studies were initiated to characterize the structural and biological properties of lipid A moieties expressed by this organism. Using a combination of chemical analyses and MALDI‐TOF mass spectrometry, B. mallei was shown to express a heterogeneous mixture of tetra‐ and penta‐acylated lipid A species that were non‐stoichiometrically substituted with 4‐amino‐4‐deoxy‐arabinose residues. The major penta‐acylated species consisted of bisphosphorylated d‐glucosamine disaccharide backbones possessing two amide linked 3‐hydroxyhexadecanoic acids, two ester linked 3‐hydroxytetradecanoic acids [C14:0(3‐OH)] and an acyloxyacyl linked tetradecanoic acid, whereas, the major tetra‐acylated species possessed all but the 3′‐linked C14:0(3‐OH) residues. In addition, although devoid of hexa‐acylated species, B. mallei LPS was shown to be a potent activator of human Toll‐like receptor 4 complexes and stimulated human macrophage‐like cells (THP‐1 and U‐937), monocyte‐derived macrophages and dendritic cells to produce high levels of TNF‐α, IL‐6 and RANTES. Based upon these results, it appears that B. mallei LPS is likely to play a significant role in the pathogenesis of human disease.
A realtime pattern generator for biped walking

For real-time walking control of a biped robot, we analyze the dynamics of a three-dimensional inverted pendulum whose motions are constrained onto an arbitrarily defined plane. This analysis leads us a simple linear dynamics, the Three-Dimensional Linear Inverted Pendulum Mode (3D-LIPM). Geometric nature of trajectories under the 3D-LIPM is discussed, and an algorithm for walking pattern generation is presented. Experimental results of real-time walking control of a 12-DOF biped robot HRP-2L using an input device such as a game pad are also shown.
A Framework for Understanding LSI Performance

In this paper we present a theoretical model for understanding the performance of LSI search and retrieval applications. Many models for understanding LSI have been proposed. Ours is the first to study the values produced by LSI in the term dimension vectors. The framework presented here is based on term co-occurrence data. We show a strong correlation between second order term co-occurrence and the values produced by the SVD algorithm that forms the foundation for LSI. We also present a mathematical proof that the SVD algorithm encapsulates term co-occurrence information.
Infrastructure for Virtual Counterparts of Real World Objects

Based on our experience with a collection of prototypical ubiquitous computing applications, we have identified a number of common basic tasks which led to the design of some simple mechanisms that we have found useful for structuring and implementing such applications. Building upon these mechanisms, we have created a software infrastructure to support the development of tag-based ubiquitous computing applications. Our framework is targeted at applications where objects are tagged with Radio Frequency Identification tags (RFIDs), a simple but powerful means of bridging the gap between the physical and the virtual world. A central feature of our infrastructure are virtual counterparts. They form augmented representations of real world objects and encapsulate their state and behavior. This paper presents the rationale, design, and implementation of our prototype infrastructure.
Targeted Delivery Systems for Molecular Therapy in Skeletal Disorders

Abnormalities in the integral components of bone, including bone matrix, bone mineral and bone cells, give rise to complex disturbances of skeletal development, growth and homeostasis. Non-specific drug delivery using high-dose systemic administration may decrease therapeutic efficacy of drugs and increase the risk of toxic effects in non-skeletal tissues, which remain clinical challenges in the treatment of skeletal disorders. Thus, targeted delivery systems are urgently needed to achieve higher drug delivery efficiency, improve therapeutic efficacy in the targeted cells/tissues, and minimize toxicities in non-targeted cells/tissues. In this review, we summarize recent progress in the application of different targeting moieties and nanoparticles for targeted drug delivery in skeletal disorders, and also discuss the advantages, challenges and perspectives in their clinical translation.
The Implementation and Application of the Microarray Preprocessing Generalized PDNN Model

The preprocessing of the Microarray data is a hot topic in the bioinformatics research. The key point of a successful preprocessing method is to remove the noise of nonspecific binding and to keep the information of specific binding as much as possible. One way to solve these problems is to understand the principle of the binding between probes and target sequences, and to distinguish specific binding from nonspecific binding correctly. In this paper, we introduce MM probe intensities into position dependent nearest neighbor (PDNN) model, which contain much information of nonspecific binding.We use two-step model to estimate the parameters,which can simplify the computation. Based on the Wilcoxon rank test, we can determine whether a gene is present, with which we can obtain the training data set for the specific binding and non specific binding parameters. We also apply our model to gene expression data (HGU133plus2.0 and HGU133A) . We find that all these improvements increase the precision and stability, and show better result compared to the other four methods( Mas5.0, dChip, RMA and PDNN ).
MPEG-7 Audio Spectrum Basis as a signature of violin sound

The goal of the paper is to examine how robust MPEG-7 Audio Spectrum Basis features are as signatures of instruments from the same group. Instruments analyzed are contemporary concert violins competing in the international violinmaker competition. They have been recorded for research purposes, thus the set of sounds for each instrument and recording conditions are the same - 30 s long musical excerpts and a set of individual sounds. Audio Spectrum Basis captures the statistically most regular features of the sound feature space thus it has been expected to well characterize instruments. The results confirmed the expectations. Since violinmakers follow the same ideal model of instrument construction and use similar material for their creation, differences of their sound are tiny, Audio Spectrum Basis enabled discrimination of several instruments as more dissimilar then the others. However these outliers have been placed by jury musicians during competition on both boundaries of the ranking.
Increase of energy efficiency of alumina production on the basis of process modeling

The article examines a problem of searching for new energy-efficient technological solutions in alumina production, which is characterized by nonlinearity, inertia and closedness. It suggests a method to solve this problem on the basis of modeling of the production process and development of the optimizing function based on production cost and obtaining values of the process variables.
A topology optimisation based design of a compliant gripper for grasping objects with irregular shapes

Complex steel structures such as power transmission towers require regular inspection and maintenance during their lifetime. This work is currently completed by teams of human workers who climb the live structures. The exposure of these workers to the risks of climbing and completing work on towers provides motivation for developing a robotic substitute. There are many complex elements of climbing power transmission towers, such as the variation in beam shapes, sizes and orientations. To the best of our knowledge, there is no existing robotic grasping solution that can be directly used in this complex environment. This paper presents a topology optimisation based design of a compliant gripper for grasping objects with irregular shapes such as the beam members found in power transmission towers. The structure of the gripper is obtained through the use of a modified topology optimisation model where stiffness constraints are implemented in the optimisation to increase the strength of the gripper in desired areas. The stiffness constrained topology optimisation produces a novel gripper design which is validated through both simulations and physical testing of the manufactured gripper on a variety of physical objects.
Annexin V imaging of acute doxorubicin cardiotoxicity (apoptosis) in rats.

UNLABELLED Anthracyclines are widely used in chemotherapy regimens for several malignancies, with cardiotoxicity being the major limiting factor in high-dose schedules. Recently, it was reported that doxorubicin induces apoptosis in cardiac muscle cells in vivo and, as such, is expected to be involved in the genesis of doxorubicin-induced cardiomyopathy. The aim of this study was to validate an animal model for in vivo monitoring of doxorubicin cardiotoxicity by means of scintigraphic detection of apoptosis. METHODS Three groups of 5 male Wistar rats each were treated for 3, 4, and 5 times with a weekly intraperitoneal injection of doxorubicin at 2.5 mg/kg. At 24 h before and 24 h after the final treatment, (99m)Tc-annexin pinhole scintigraphy was performed. A control group of 5 rats was scanned without doxorubicin treatment. A cardiac uptake ratio was calculated from planar scintigraphy results with the following formula: (mediastinum - fat)/fat. After scintigraphy, the rats were sacrificed, and the heart was processed for histologic analysis. RESULTS Incremental general signs of illness were observed with increasing total cumulative doxorubicin dose. Rats treated for 3, 4, and 5 wk with doxorubicin showed significantly higher uptake ratios of, respectively, 4.0 +/- 0.52 (mean +/- SEM), 4.8 +/- 0.46, and 5.2 +/- 0.17 after the final treatment; the ratio for controls was 1.84 +/- 0.05 (P < 0.05). Histologic analysis confirmed cardiac stress in treated groups, with an increasing left ventricular atrial natriuretic factor messenger RNA expression level with increasing cumulative doxorubicin dose. Late apoptosis was confirmed by terminal deoxynucleotidyltransferase-mediated dUTP nick-end labeling in the rats treated for 5 wk. CONCLUSION Acute doxorubicin-induced cardiomyopathy based on early apoptosis can be assessed and imaged with annexin V scintigraphy in rats. This finding makes it possible to use this animal model for repetitive noninvasive evaluation of cardioprotective regimens for anthracycline cardiotoxicity.
Integrating PZB Model and TRIZ for Service Innovation of Tele-Healthcare

— Due to the rise of aging population, effective utilization of healthcare resources has become an important issue. With the advance of ICT technology, the application of tele-healthcare service has received more attention than ever. The main purpose of this research is to investigate how to conduct innovative design for tele-healthcare service based on user’s perspectives. First, the healthcare service blueprint was used to describe the processes of tele-healthcare service delivery, and then construct PZB service quality gap model based on the literature and practitioners’ interviews. Next, TRIZ theory is applied to implement service innovation. We found the proposed service innovation procedures can effectively improve the quality of service design.
A REGION VOID OF IRREGULAR SATELLITES AROUND JUPITER

An interesting feature of the giant planets of our solar system is the existence of regions around these objects where no irregular satellites are observed. Surveys have shown that, around Jupiter, such a region extends from the outermost regular satellite Callisto to the vicinity of Themisto, the innermost irregular satellite. To understand the reason for the existence of such a satellite–void region, we have studied the dynamical evolution of Jovian irregulars by numerically integrating the orbits of several hundred test particles, distributed in a region between 30 and 80 Jupiter-radii, for different values of their semimajor axes, orbital eccentricities, and inclinations. As expected, our simulations indicate that objects in or close to the influence zones of the Galilean satellites become unstable because of interactions with Ganymede and Callisto. However, these perturbations cannot account for the lack of irregular satellites in the entire region between Callisto and Themisto. It is suggested that at distances between 60 and 80 Jupiter-radii, Ganymede and Callisto may have long-term perturbative effects, which may require the integrations to be extended to times much longer than 10 Myr. The interactions of irregular satellites with protosatellites of Jupiter at the time of the formation of Jovian regulars may also be a destabilizing mechanism in this region. We present the results of our numerical simulations and discuss their applicability to similar satellite void-regions around other giant planets.
R-flurbiprofen attenuates experimental autoimmune encephalomyelitis in mice

R‐flurbiprofen is the non‐cyclooxygenase inhibiting R‐enantiomer of the non‐steroidal anti‐inflammatory drug flurbiprofen, which was assessed as a remedy for Alzheimer's disease. Because of its anti‐inflammatory, endocannabinoid‐modulating and antioxidative properties, combined with low toxicity, the present study assessed R‐flurbiprofen in experimental autoimmune encephalomyelitis (EAE) models of multiple sclerosis in mice. Oral R‐flurbiprofen prevented and attenuated primary progressive EAE in C57BL6/J mice and relapsing‐remitting EAE in SJL mice, even if the treatment was initiated on or after the first flare of the disease. R‐flurbiprofen reduced immune cell infiltration and microglia activation and inflammation in the spinal cord, brain and optic nerve and attenuated myelin destruction and EAE‐evoked hyperalgesia. R‐flurbiprofen treatment increased CD4+CD25+FoxP3+ regulatory T cells, CTLA4+ inhibitory T cells and interleukin‐10, whereas the EAE‐evoked upregulation of pro‐inflammatory genes in the spinal cord was strongly reduced. The effects were associated with an increase of plasma and cortical endocannabinoids but decreased spinal prostaglandins, the latter likely due to R to S inversion. The promising results suggest potential efficacy of R‐flurbiprofen in human MS, and its low toxicity may justify a clinical trial.
Integrated event recognition from multiple sources

Proposes a system architecture for event recognition that integrates information from multiple sources (e.g., gesture and speech recognition from distributed sensors in the real world). The proposed system consists of multiple recognizers named continuous state machines (CSMs). Each CSM has a state transition rule in a continuous state space and classifies time-varying patterns from a single source. Since the rule is defined as a simplification of Kalman filter (i.e., the next state is deduced from the trade-off scheme between input data and model's prediction), CSMs support dynamic time warping and robustness against noise. We then introduce an interaction method among CSMs to classify events from multiple sources. A continuous state space (i.e., vector space) allows us to design interaction as recursively minimizing an energy function. This interaction enables the system to dynamically focus over the multiple sources, and improves reliability and accuracy of classifying events in dynamically changing situations (e.g., the object is temporally occluded from one of multiple cameras in a gesture recognition task). Experimental results on gesture recognition by two cameras show the effectiveness of our proposed system.
MAX-MIN ANT OPTIMIZER FOR PROBLEM OF UNCERTAINITY

The real life problems deal with imperfectly specified knowledge and some degree of imprecision, uncertainty or inconsistency is embedded in the problem specification. The well-founded theory of fuzzy sets is a special way to model the uncertainty. The rules in a fuzzy model contain a set of propositions, each of which restricts a fuzzy variable to a single fuzzy value by means of the predicate equivalency. That way, each rule covers a single fuzzy region of the fuzzy grid. The proposed system of this thesis extends this structure to provide more general fuzzy rules, covering the input space as much as possible. In order to do this, new predicates are considered and a Max-Min Ant System is proposed to learn such fuzzy rules. Ant system is a general purpose algorithm inspired by the study of behavior of ant colonies. It is based on cooperative search paradigm that is applicable to the solution of combinatorial optimization problem. In this thesis we consider the combinatorial optimization issue of Travelling salesman problem (TSP) which evaluates more generic Fuzzy rules provided by Max-Min Ant System (MMAS). The existing ant colony system (ACS) was a distributed algorithm applied to the travelling salesman problem (TSP). In ACS, a set of cooperating agents called ants cooperate to find good solutions for TSPs (but here, Ants search their path randomly). Ants cooperate using an indirect form of communication mediated by pheromone they deposit on the edges of the TSP problem in symmetric instances. However most of the TSP issues carry both symmetric and asymmetric instances.
Investigation of Yersinia pestis Laboratory Adaptation through a Combined Genomics and Proteomics Approach

The bacterial pathogen Yersinia pestis, the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a parallel serial passage experiment (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing, LC-MS/MS proteomic analysis, and GC/MS metabolomics. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail, pepA, and zwf, suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS/MS proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism and cell envelope biogenesis. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement.
Web Knowledge Management for Small and Medium-Size Enterprises - WebTour: A Case Study from the Tourism Sector

Keywords: Value-Added Services, Web-Based Services, Web Knowledge Management, Decision Support System, Data Warehousing, On-Line Analysis Processing. Abstract: The current enterprise world has become global and complex. Knowledge management is a key to have a competitive advantage as it allows detecting in advance customer trends and market evolution. While knowledge management systems are usually unaffordable for small or even medium-size enterprises, a tool to be shared between them is a more realistic solution. The system, based on client/server architecture with a web interface, is able to provide top Information Technology (IT) solutions for a low cost so that small and medium business can also use these systems to acquire competitive advantage. We have developed a solution for a IT enterprise providing an on-line reservation system for small tourist lodgings and travel agencies. It consists of a Data Warehouse (DW) and a Decision Support System (DSS) which is currently being offered as a value-added service for providers and customers. The DSS is also used by the Acquisition Component of a Knowledge Management System (KMS).