Miracle-dz/UniFAR-FTUs huggingface dataset:
A Restoration Method of Infrared Image Based on Compressive Sampling

The deluge of big data is changing the operational environments of many sampling system. Modern technology is in the dangerous of submersion by big data. The paper investigated the present situation of infrared image processing techniques. An applied of compressive sampling to restoration of infrared image is given for denoising and deblurring tasks. In convex optimization stage, the fixed point continuation (FPC) is employed. Finally, the subjective and objective index is applied in the evaluation of proposed method. The PSNR (Peak Signal to Noise Ratio) and MSSIM (Mean Structural Similarity) are used to evaluate the performance of those methods. Experimental tests are executed by using infrared image of person in sand dune. Comparing with other existing methods, the proposed give the satisfying performance. It can provide a reference to practical engineering.
EFFICIENTLY SEARCHING NEAREST NEIGHBOR IN DOCUMENTS USING KEYWORDS

Conservative spatial queries, such as range search and nearest neighbor reclamation, involve only cond itions on objects’ numerical properties. Today, many modern applications call fo r novel forms of queries that aim to find objects s atisfying both a spatial predicate, and a predicate on their associated text s. For example, instead of considering all the rest aurants, a nearest neighbor query would instead ask for the restaurant that is the cl osest among those whose menus contain “steak, spagh etti, brandy” all at the same time. Currently the best solution to such queries ibased on the InformationRetrieval2-tree, which, h as a few deficiencies that seriously impact its efficiency. Motivated by this, there is a development of a new access method call ed the spatial inverted index that extends the conventional inverted index to cope wit h multidimensional data, and comes with algorithms that can answer nearest neighbor queries with keywords in real time. As ver ified by experiments, the proposed techniques outpe rform the InformationRetrieval2-tree in query response time soften by a factor of orders of magnit ude
The Reachability Query over Distributed Uncertain Graphs

Reachability, one of the most fundamental queries over uncertain graphs, which asks the probability that two given query vertices are reachable over an uncertain graph. Although this problem has been widely studied, the existing works are all processed in a single server. However, as graph data becomes larger, it usually cannot be stored in a single server. Moreover, processing probabilistic reachability queries is #P-complete, so the calculation is very expensive even on small graphs. Thus, in this paper, our purpose is to develop efficient distributed strategies to firstly pick out all the maximal subgraphs whose reachability probabilities can be calculated in polynomial time efficiently. After this step, only a small graph remains, and we provide an approximate method. Extensive experimental studies show that our distributed algorithms are efficient and have a low communication cost.
LACTATE – A MARKER FOR SEPSIS AND TRAUMA

It seems that each month, our journals publish the findings of a new study which describes the use of a certain marker or set of markers for the diagnosis, prognosis, or treatment of some emergency medical condition. Manuscripts and symposia discussing marker clearance, marker change, marker panels, and pointof-care markers reside in every issue and every meeting. In this newsletter, lactate, a serum marker older than any cardiac marker cousin, assumes center stage in two of the most difficult and resource intensive emergency medicine conditions – sepsis and trauma. This EMCREG-International newsletter aims to familiarize the emergency physician with lactate and its potential use the emergency department (ED).
Genetic Diversity and Abundance of Flavobacterial Proteorhodopsin in China Seas

ABSTRACT Proteorhodopsin (PR) genes related to Flavobacteria were found to be highly diverse in the East and South China seas and displayed a distinct geographic pattern, which appeared to reflect cold versus warm adaptation when Global Oceanic Sampling database metagenomic data were included. Flavobacterial PR genes were more abundant offshore than nearshore, implying that inheritance of the PR gene could be important for Flavobacteria living in the oligotrophic environment.
Improved performance and power consumption of three-dimensional FPGAs using Carbon Nanotube interconnects

Three dimensional stacking and some new materials such as Carbon Nanotube are two efficient techniques to alleviate the interconnect problems. In this paper, utilizing the Carbon Nanotube interconnects in three-dimensional FPGAs is explored and a CNT/Metal hybrid routing architecture corresponding with a CNT-based routing algorithm is proposed. In the presented architecture, Through-silicon Vias and enough-long 2D wire segments are realized by CNT and remained wires are implemented by metal. Our experimental results show that critical delay and power consumption are improved by the proposed approach by about 30% and 21% on average for attempted benchmarks.
ENERGY EFFICIENT CLUSTERING ALGORITHM IN MOBILE SENSOR NETWORKS

In this paper an energy efficient clustering algori thm is proposed under mobile sensor networks scenario. Clustering offers a kind of hier archical organization to provide scalability and basic performance guarantee by part itioning the network into disjoint groups of nodes. In the initial cluster formation phase, our proposed scheme features a simple execution process, which has a time and message com plexity of O(n), and eliminates the “frozen time” requirement by introducing some GPS-c apable mobile nodes. In the following cluster maintenance stage, the maintenance of clust ers is asynchronously and event driven so as to thoroughly avoid the “ripple effect”, thus be ing well suitable for the high mobility environment. Extensive simulations have been conduc te and the simulation results reveal that our proposed algorithm successfully achieves i ts target at incurring much less clustering overheads as well as maintaining much more stable c luster structure, as compared to HCC (High Connectivity Clustering) algorithm.
Footwear Cushioning: Relating Objective and Subjective Measurements

Footwear cushioning was evaluated objectively using an impact tester and related to perceived levels of cushioning (PLC). To evaluate the perceived levels of cushioning during standing, walking, and running, 3 experiments were conducted with 20 participants in each experiment. A 7-point subjective rating scale was used to rate the perceived levels of cushioning. At the end of the experiment, the subjective perceptions of cushioning were also recorded. During standing and running, the perceived level of cushioning can be predicted from the time to peak deceleration and/or stiffness (or compression). During walking, however, the magnitude of the peak deceleration on the impact tester appears to be a good predictor of PLC. Impact characterizations can reveal important differences between materials and how they are perceived during activity. In addition, the results seem to explain and link the differences that exist in the ergonomics and biomechanics literature on cushioning. Applications of this research include the design and selection of materials for footwear, floor mats, and other supporting surfaces.
A Chondroitin Sulfate Proteoglycan PTPζ/RPTPβ Regulates the Morphogenesis of Purkinje Cell Dendrites in the Developing Cerebellum

PTPζ/RPTPβ, a receptor-type protein tyrosine phosphatase synthesized as a chondroitin sulfate (CS) proteoglycan, uses a heparin-binding growth factor pleiotrophin (PTN) as a ligand, in which the CS portion plays an essential role in ligand binding. Using an organotypic slice culture system, we tested the hypothesis that PTN-PTPζ signaling is involved in the morphogenesis of Purkinje cell dendrites. An aberrant morphology of Purkinje cell dendrites such as multiple and disoriented primary dendrites was induced in slice cultures by (1) addition of a polyclonal antibody against the extracellular domain of PTPζ, (2) inhibition of protein tyrosine phosphatase activity, (3) enzymatic removal of the CS chains, (4) addition of exogenous CS chains, and (5) addition of exogenous PTN, all of which disturb PTN-PTPζ signaling. These treatments also reduced the immunoreactivity to GLAST, a glial glutamate transporter, on Bergmann glial processes. Furthermore, a glutamate transporter inhibitor also induced the abnormal morphogenesis of Purkinje cell dendrites. Altogether, these findings suggest that PTN-PTPζ signaling regulates the morphogenesis of Purkinje cell dendrites and that the mechanisms underlying that regulation involve the GLAST activity in Bergmann glial processes.
On the performance of average consensus in mobile wireless sensor networks

Distributed averaging in wireless sensor networks is fundamental for advanced distributed algorithms. In this paper, we study the impact of node mobility on the well-known average consensus algorithm. More specifically, we study the MSE in mobile wireless sensor networks modeled via evolving random geometric graphs. We provide a closed-form lower bound for the MSE that shows that node mobility is beneficial. Numerical results involving various mobility models demonstrate that mobility can be traded against convergence time, transmit power, or node density.
The Covariance Transformation and the Instrumental Variables Estimator of the Fixed Effects Model

The covariance transformation is a useful and often necessary procedure to estimate the fixed effects model. When some explanatory variables are contemporaneously correlated with the disturbance term, the covariance transformation can be used in conjunction with an instrumental variables procedure to obtain a consistent estimator. This paper describes how to correctly compute the IV estimator as a two stage least squares estimator. In addition, I show that if the IV estimator is incorrectly computed using a two stage least squares approach where the covariance transformation is not applied until the second stage, the resulting estimator is not in general consistent.
Syringyl Methacrylate, a Hardwood Lignin-Based Monomer for High-Tg Polymeric Materials

As viable precursors to a diverse array of macromolecules, biomass-derived compounds must impart wide-ranging and precisely controllable properties to polymers. Herein, we report the synthesis and subsequent reversible addition–fragmentation chain-transfer polymerization of a new monomer, syringyl methacrylate (SM, 2,6-dimethoxyphenyl methacrylate), that can facilitate widespread property manipulations in macromolecules. Homopolymers and heteropolymers synthesized from SM and related monomers have broadly tunable and highly controllable glass transition temperatures ranging from 114 to 205 °C and zero-shear viscosities ranging from ∼0.2 kPa·s to ∼17,000 kPa·s at 220 °C, with consistent thermal stabilities. The tailorability of these properties is facilitated by the controlled polymerization kinetics of SM and the fact that one vs two o-methoxy groups negligibly affect monomer reactivity. Moreover, syringol, the precursor to SM, is an abundant component of depolymerized hardwood (e.g., oak) and graminaceous (e.g., switchgrass) lignins, making SM a potentially sustainable and low-cost candidate for tailoring macromolecular properties.
University of Ottawa's Participation in the CL-SR Task at CLEF 2006

This paper presents the second participation of the University of Ottawa group in CLEF, the Cross- Language Spoken Retrieval (CL-SR) task. We present the results of the submitted runs for the English collec- tion and very briefly for the Czech collection, followed by many additional experiments. We have used two Information Retrieval systems in our experiments: SMART and Terrier were tested with many different weighting schemes for indexing the documents and the queries and with several query expansion techniques (including a new method based on log-likelihood scores for collocations). Our experiments showed that query expansion methods do not help much for this collection. We tested whether the new Automatic Speech Recognition transcripts improve the retrieval results; we also tested combinations of different automatic tran- scripts (with different estimated word error rates). The retrieval results did not improve, probably because the speech recognition errors happened for the words that are important in retrieval, even in the newer ASR2006 transcripts. By using different system settings, we improved on our submitted result for the required run (English queries, title and description) on automatic transcripts plus automatic keywords. We present cross- language experiments, where the queries are automatically translated by combining the results of several online machine translation tools. Our experiments showed that high quality automatic translations (for French) led to results comparable with monolingual English, while the performance decreased for the other languages. Experiments on indexing the manual summaries and keywords gave the best retrieval results.
Rewriting Logic based Approach for the Formalization of Critical Systems based on Multi-Agent System

agent-oriented paradigm is an emerging technology, which has significant and growing interest, particularly through its ability to be used in the modeling of all types of systems and representation of knowledge. However, this potentiality should not hide the difficulties associated with them in the design and verification, which may cause the scientific credibility of multi-agent modeling field, especially for the case of embedded and critical systems. In this paper, we propose a new formal approach based on rewriting logic, in which we attempt to bridge the gap between agent based system analysis and its specification In addition, our approach includes a well-known and effective verification technique, model checking, and allows independent of the used formalism to verify an important number of properties deemed relevant on critical system based on agent paradigm.
Hepatitis B virus X protein disrupts the balance of the expression of circadian rhythm genes in hepatocellular carcinoma

The human circadian rhythm is controlled by at least eight circadian clock genes and disruption of the circadian rhythm is associated with cancer development. The present study aims to elucidate the association between the expression of circadian clock genes and the development of hepatocellular carcinoma (HCC), and also to reveal whether the hepatitis B virus X protein (HBx) is the major regulator that contributes to the disturbance of circadian clock gene expression. The mRNA levels of circadian clock genes in 30 HCC and the paired peritumoral tissues were determined by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A stable HBx-expressing cell line, Bel-7404-HBx, was established through transfection of HBx plasmids. The mRNA level of circadian clock genes was also detected by RT-qPCR in these cells. Compared with the paired peritumoral tissues, the mRNA levels of the Per1, Per2, Per3 and Cry2 genes in HCC tissue were significantly lower (P<0.05), while no significant difference was observed in the expression levels of CLOCK, BMAL1, Cry1 and casein kinase 1ɛ (CK1ɛ; P>0.05). Compared with Bel-7404 cells, the mRNA levels of the CLOCK, Per1 and Per2 genes in Bel-7404-HBx cells were significantly increased, while the mRNA levels of the BMAL1, Per3, Cry1, Cry2 and CKIɛ genes were decreased (P<0.05). Thus, the present study identified that disturbance of the expression of circadian clock genes is common in HCC. HBx disrupts the expression of circadian clock genes and may, therefore, induce the development of HCC.
A Model-Based Soft Errors Risks Minimization Approach

Minimizing the risk of system failure in any computer structure requires identifying those components whose failure is likely to impact on system functionality. Clearly, the degree of protection or prevention required against faults is not the same for all components. Tolerating soft errors can be much improved if critical components can be identified at an early design phase and measures are taken to lower their criticalities at that stage. This improvement is achieved by presenting a criticality ranking (among the components) formed by combining a prediction of faults, consequences of them, and a propagation of errors at the system modeling phase; and pointing out ways to apply changes in the model to minimize the risk of degradation of desired functionalities. Case study results are given to validate the approach. Keywords-Criticality Analysis; Soft Errors; Reliability Risks, UML Model; Metrics
Review of: Culture and the Evolutionary Process by Robert Boyd and Peter J. Richerson

Similarly, Boyd and Richerson condense into a handful of pages all the theories of learning produced over the decades. Indeed, they distill them into a few general rules. One cannot expect a full explication of all learning theories; on the other hand, we need to ask when simplification and condensation go too far. The authors have done an excellent job of pulling together a highly diverse and complex set of theories and ideas. In the process, however, they may have lost some valuable insights.
Exploiting Psychological Factors for Interaction Style Recognition in Spoken Conversation

Determining how a speaker is engaged in a conversation is crucial for achieving harmonious interaction between computers and humans. In this study, a fusion approach was developed based on psychological factors to recognize Interaction Style ( IS) in spoken conversation, which plays a key role in creating natural dialogue agents. The proposed Fused Cross-Correlation Model (FCCM) provides a unified probabilistic framework to model the relationships among the psychological factors of emotion, personality trait ( PT), transient IS, and IS history, for recognizing IS. An emotional arousal-dependent speech recognizer was used to obtain the recognized spoken text for extracting linguistic features to estimate transient IS likelihood and recognize PT. A temporal course modeling approach and an emotional sub-state language model, based on the temporal phases of an emotional expression, were employed to obtain a better emotion recognition result. The experimental results indicate that the proposed FCCM yields satisfactory results in IS recognition and also demonstrate that combining psychological factors effectively improves IS recognition accuracy.
A high-performance parallel implementation of Sum of Absolute Differences algorithm for motion estimation using CUDA

The Sum of Absolute Differences (SAD) algorithm for motion estimation constitutes one of the most time consuming and compute intensive part of image registration in Automated Video Surveillance (AVS) using non-stationary cameras and H.264 video compression. Many present solutions, implemented by use of dedicated hardware for video surveillance are incapable of delivering image registration for larger sized video streams in real-time. In this paper, we present a novel, high performance implementation of SAD on the general purpose GPU architecture, which is available in many laptops and PCs, using NVIDIA’s CUDA. The proposed implementation contains innovative and efficient optimizations to overcome the bottlenecks that limit the achievable speedup and outperforms the other parallel implementations not only in terms of speed but also accuracy. The use of threshold in the SAD computation prevents detection of false motion caused due to noise. The proper choice of macro block size for SAD computation provides more accurate results with significant reduction in execution times. This makes the motion estimation real-time which scales well for larger image sizes. The wide range of memories offered by the GPU architecture has been exploited to a large extent and a significant speedup of 204X for an image size of 1024×768 was achieved for SAD on the GeForce GTX 280 as compared to the serial implementation. The use of texture memory for accessing the periphery of the reference frame prevents the out of bound references and contributes to the speedup achieved.
Holomorphic selection rules, the origin of the μ term, and thermal inflation

When an abelian gauge theory with integer charges is spontaneously broken by the expectation value of a charge Q field, there remains a ZQ discrete symmetry. In a supersymmetric theory, holomorphy adds additional constraints on the operators that can appear in the effective superpotential. As a result, operators with the same mass dimension but opposite sign charges can have very different coupling strengths. In the present work we characterize the operator hierarchies in the effective theory due to holomorphy, and show that there exist simple relationships between the size of an operator and its mass dimension and charge. Using such holomorphy-induced operator hierarchies, we construct a simple model with a naturally small supersymmetric µ term. This model also provides a concrete realization of late-time thermal inflation, which has the ability to solve the gravitino and moduli problems of weak-scale supersymmetry.
Presence of a loner strain maintains cooperation and diversity in well-mixed bacterial communities

Cooperation and diversity abound in nature despite cooperators risking exploitation from defectors and superior competitors displacing weaker ones. Understanding the persistence of cooperation and diversity is therefore a major problem for evolutionary ecology, especially in the context of well-mixed populations, where the potential for exploitation and displacement is greatest. Here, we demonstrate that a ‘loner effect’, described by economic game theorists, can maintain cooperation and diversity in real-world biological settings. We use mathematical models of public-good-producing bacteria to show that the presence of a loner strain, which produces an independent but relatively inefficient good, can lead to rock–paper–scissor dynamics, whereby cooperators outcompete loners, defectors outcompete cooperators and loners outcompete defectors. These model predictions are supported by our observations of evolutionary dynamics in well-mixed experimental communities of the bacterium Pseudomonas aeruginosa. We find that the coexistence of cooperators and defectors that produce and exploit, respectively, the iron-scavenging siderophore pyoverdine, is stabilized by the presence of loners with an independent iron-uptake mechanism. Our results establish the loner effect as a simple and general driver of cooperation and diversity in environments that would otherwise favour defection and the erosion of diversity.
Improving Object-Oriented Analysis with Roles

Object-oriented analysis (OOA) has been proposed and applied in software engineering for more than fifteen years. Many researchers and practitioners have published many articles and books to discuss this methodology. Many companies and organizations have also published many standards in software development. However, there is one critical problem that is becoming the bottle neck affecting the efficiency and correctness of OOA, i.e., the gap between customers, analysts and designers is too large to obtain a satisfactory requirement analysis report. Role-based analysis is one possible way to alleviate this symptom. It can at least improve the quality of the requirement analysis report. This paper gives a retrospect to the past OOA methodology, analyzes the weakness of it, proposes how to practice a new method for system analysis, i.e., role-based analysis, and demonstrates the benefits of this method.