Miracle-dz/UniFAR-FTUs huggingface dataset:
CompactKdt: Compact signatures for accurate large scale object recognition

We present a novel algorithm, Compact Kd-Trees (CompactKdt), that achieves state-of-the-art performance in searching large scale object image collections. The algorithm uses an order of magnitude less storage and computations by making use of both the full local features (e.g. SIFT) and their compact binary signatures to build and search the K-Tree. We compare classical PCA dimensionality reduction to three methods for generating compact binary representations for the features: Spectral Hashing, Locality Sensitive Hashing, and Locality Sensitive Binary Codes. CompactKdt achieves significant performance gain over using the binary signatures alone, and comparable performance to using the full features alone. Finally, our experiments show significantly better performance than the state-of-the-art Bag of Words (BoW) methods with equivalent or less storage and computational cost.
A homeobox gene, pnx, is involved in the formation of posterior neurons in zebrafish

A homeobox gene, pnx, is expressed in prospective posterior neurogenic regions and later in primary neurons. pnx expression was regulated by a signal from the non-axial mesendoderm and by Notch signaling. Pnx contains an Eh1 repressor domain, which interacted with Groucho and acted as a transcriptional repressor. Misexpression of pnx increased neural precursor cells and postmitotic neurons, which express neurogenin1 and elavl3/HuC, respectively. Expression of an antimorphic Pnx (VP16Pnx) or inhibition of Pnx by antisense morpholino oligonucleotide led to the reduction in the number of a subset of primary neurons. Misexpression of pnx promoted neurogenesis independent of Notch signaling. Epistatic analyses showed that Pnx also functions downstream of the Notch signal. These data indicate that pnx is a novel repressor-type homeobox gene that regulates posterior neurogenesis.
Evaluating performance degradation in NoSQL databases generated by virtualization

There are many services in Cloud Systems currently on the market for hosting servers with different purposes. These environments are IT infrastructures frequently deployed in large data centers using Virtual Machines. Moreover, an increasing number of users are using massive online application resources with hosted databases on virtual machines. In light of this, there is a critical need to evaluate databases performance in virtual environments. This work aims to evaluate overhead generated by virtualization in two common NoSQL databases, Cassandra and MongoDB, by different virtualization techniques - full virtualization and paravirtualization. For this, we used the YCSB benchmark (Yahoo! Cloud Serving Benchmark) to drive performance tests, with the results being evaluated through statistical analysis. As findings, the performed experiments in both virtualization techniques demonstrated that the experimental design comprises most of the factors in MongoDB, different from Cassandra which comprises of just a few. In paravirtualization scenarios the environment factor was more sensitive to experimental variations overcoming factors such as threads and numbers of transaction. Both databases in full virtualization scenarios reached significant variation, however the threads and transactions factors were more significant.
Convex Non-Negative Matrix Factorization for Brain Tumor Delimitation from MRSI Data

Background Pattern Recognition techniques can provide invaluable insights in the field of neuro-oncology. This is because the clinical analysis of brain tumors requires the use of non-invasive methods that generate complex data in electronic format. Magnetic Resonance (MR), in the modalities of spectroscopy (MRS) and spectroscopic imaging (MRSI), has been widely applied to this purpose. The heterogeneity of the tissue in the brain volumes analyzed by MR remains a challenge in terms of pathological area delimitation. Methodology/Principal Findings A pre-clinical study was carried out using seven brain tumor-bearing mice. Imaging and spectroscopy information was acquired from the brain tissue. A methodology is proposed to extract tissue type-specific sources from these signals by applying Convex Non-negative Matrix Factorization (Convex-NMF). Its suitability for the delimitation of pathological brain area from MRSI is experimentally confirmed by comparing the images obtained with its application to selected target regions, and to the gold standard of registered histopathology data. The former showed good accuracy for the solid tumor region (proliferation index (PI)>30%). The latter yielded (i) high sensitivity and specificity in most cases, (ii) acquisition conditions for safe thresholds in tumor and non-tumor regions (PI>30% for solid tumoral region; ≤5% for non-tumor), and (iii) fairly good results when borderline pixels were considered. Conclusions/Significance The unsupervised nature of Convex-NMF, which does not use prior information regarding the tumor area for its delimitation, places this approach one step ahead of classical label-requiring supervised methods for discrimination between tissue types, minimizing the negative effect of using mislabeled voxels. Convex-NMF also relaxes the non-negativity constraints on the observed data, which allows for a natural representation of the MRSI signal. This should help radiologists to accurately tackle one of the main sources of uncertainty in the clinical management of brain tumors, which is the difficulty of appropriately delimiting the pathological area.
Bringing the “self” into focus: conceptualising the role of self-experience for understanding and working with distressing voices

A primary goal of cognitive behavior therapy for psychosis (CBTp) is to reduce distress and disability, not to change the positive symptoms of psychosis, such as hearing voices. Despite demonstrated associations between beliefs about voices and distress, the effects of CBTp on reducing voice distress are disappointing. Research has begun to explore the role that the psychological construct of “self” (which includes numerous facets such as self-reflection, self-schema and self-concept) might play in causing and maintaining distress and disability in voice hearers. However, attempts to clarify and integrate these different perspectives within the voice hearing literature, or to explore their clinical implications, are still in their infancy. This paper outlines how the self has been conceptualised in the psychosis and CBT literatures, followed by a review of the evidence regarding the proposed role of this construct in the etiology of and adaptation to voice hearing experiences. We go on to discuss some of the specific intervention methods that aim to target these aspects of self-experience and end by identifying key research questions in this area. Notably, we suggest that interventions specifically targeting aspects of self-experience, including self-affection, self-reflection, self-schema and self-concept, may be sufficient to reduce distress and disruption in the context of hearing voices, a suggestion that now requires further empirical investigation.
Fuzzy-Contextual Contrast Enhancement

This paper presents contrast enhancement algorithms based on fuzzy contextual information of the images. We introduce fuzzy similarity index and fuzzy contrast factor to capture the neighborhood characteristics of a pixel. A new histogram, using fuzzy contrast factor of each pixel is developed, and termed the fuzzy dissimilarity histogram (FDH). A cumulative distribution function is formed with normalized values of an FDH and used as a transfer function to obtain the contrast enhanced image. The algorithm gives good contrast enhancement and preserves the natural characteristic of the image. In order to develop a contextual intensity transfer function, we introduce a fuzzy membership function based on fuzzy similarity index and coefficient of variation of the image. The contextual intensity transfer function is designed using the fuzzy membership function to achieve final contrast enhanced image. The overall algorithm is referred as the fuzzy contextual contrast-enhancement algorithm. The proposed algorithms are compared with the conventional and the state-of-the-art contrast enhancement algorithms. The quantitative and visual assessment of the results is performed. The results of quantitative measures are statistically analyzed using t-test. The exhaustive experimentation and analysis show the proposed algorithm efficiently enhances contrast and yields in natural visual quality images.
Influence of Parenting Styles toward Achievement of Theory of Mind in the Late Childhood

The ability to understand the intention, beliefs, wishes or motives of others (theory of mind) is very important to be developed for the children. Caregiving is possible to contribute to the achievement of the theory of mind in children. The aims of this study are to examine the parenting influence on the achievement of the theory of mind and differences in authoritative, authoritarian and permissive parenting towards the achievement of the theory of mind in the last childhood period. The total of the students in this elementary school is 150 students in grade IV V was involved in this study. The instrument used in this study is the PAQ (Parental Authority Questionnaire) to determine the tendency of parents' parenting and higher order tasks to determine the level of the ToM. The results showed that there was a difference in the level of theory of mind performance in terms
Virulent Synergistic Effect between Enterococcus faecalis and Escherichia coli Assayed by Using the Caenorhabditis elegans Model

Background The role of enterococci in the pathogenesis of polymicrobial infections is still debated. The purpose of this study was to evaluate the effect of virulent enterococci in the presence or absence of Escherichia coli strains in the in vivo Caenorhabditis elegans model. Principal Findings This study demonstrated that there was a synergistic effect on virulence when an association of enterococci and E. coli (LT50 = 1.6 days±0.1 according to the tested strains and death of nematodes in 4 days±0.5) was tested in comparison with enterococci alone (LT50 = 4.6 days±0.1 and death in 10.4 days±0.6) or E. coli alone (LT50 = 2.1±0.9 and deaths 6.6±0.6) (p<0.001). In addition, there was a relation between the virulence of E. faecalis strains alone and the virulence potential of the association with E. coli strains. Finally, in the presence of avirulent E. coli strains, enterococci have no effect (LT50 = 4.3±0.5 and deaths in 10.8±0.8), independently of the level of their own virulence, demonstrating that the ‘enterococci effect’ only occurred in the presence of virulent E. coli strains. Conclusion This study allows a better understanding of a bacterial cooperation. Moreover, it could help to optimize the antibiotic regimen during polymicrobial infections.
Nimble Protein Sequence Alignment in Grid (NPSAG)

In Bio-Informatics application, the analysis of protein sequence is a kind of computation driven science which has rapidly and quickly growing biological data. Also databases used in these applications are heterogeneous in nature and alignment of protein sequence using physical techniques is expensive, slow and results are not always guaranteed/accurate. So this application requires cross-platform, cost-effective and more computing power algorithm for sequence matching and searching a sequence in database. Grid is one of the most emerging technologies of cost effective computing paradigm for large class of data and compute intensive application which enables large-scale aggregation and sharing of computational data and other resources across institutional boundaries. We proposed the Grid architecture for searching of distributed, heterogeneous genomic databases which contained protein sequences to speed up the analysis of large scale sequence data and performed sequence alignment for residues match.
A Novel Approach to Random Pattern Testing of Sequential Circuits

Random pattern testing methods are known to result in poor fault coverage for most sequential circuits unless costly circuit modifications are made. In this paper, we propose a novel approach to improve the random pattern testability of sequential circuits. We introduce the concept of holding signals at primary inputs and scan flipflops of a partially scanned sequential circuit for a certain length of time, instead of applying a new random vector at each clock cycle. When a random vector is held at the primary inputs of the circuit under test or at the scan flip-flops, the system clock is applied and the primary outputs of the circuit are observed. Information obtained from a testability analysis or test generator is used to determine the number of clock cycles for which each random vector is to be held constant. The method is low cost and the results of our experiment on the benchmark circuits show that it is very effective in providing fault coverage close to the maximum obtainable fault coverage using random patterns with full scan.
THE PASSAGE OF FLUID AND PROTEIN THROUGH THE HUMAN CAPILLARY WALL DURING VENOUS CONGESTION.

It has been demonstrated in normal human subjects by several methods that during venous congestion fluid is filtered from the blood into the tissue spaces. This passage of fluid through the capillary wall has been identified by comparing blood samples removed during normal circulation and during venous congestion It has been observed also that when the venous pressure in the legs is increased by quiet standing, fluid is filtered from the blood stream with a consequent reduction in circulating blood volume (Thompson, Thompson and Dailey (1928); Waterfield (1931)). The filtration produced by measured grades of venous congestion has been measured also by plethysmographic methods in which the accumulation of fluid in the tissue spaces was estimated by measuring the increase in from Thompson, Thompson and Dailey in finding that during standing the blood lost not only fluid but also a significant amount of protein. Drinker and his co-workers (1931) have called attention to the high concentration of protein often found in lymph. Maintaining that tissue fluid and lymph are identical, they regard the capillary wall as everywhere quite permeable to protein even under normal conditions. A retrograde movement of protein from the tissue spaces through the capillary wall into the blood during venous stasis has been described by Plass and Rourke (1927). They found that during venous congestion the blood proteins were always increased by a greater percentage than was cell volume. This was believed to indicate that during venous congestion proteins must pass from the tissue spaces into the blood stream. It will be shown below that the direct comparison of percentage increase in cell volume with the percentage increase in plasma proteins is unjusti-Woodward Fellow in Physiological Chemistry. 717 CAPILLARY WALL DURING CONGESTION fied. Actually their figures show loss of both fluid and protein from the blood stream. The amount of tissue fluid accumulating in the arm during mild venous congestion (Krogh, Landis and Turner (1932)) seemed great enough to produce measurable changes in the fluid content of the blood. Assuming that the fluid is lost chiefly from the plasma, the amount of capillary filtrate per 100 cc. of blood can be calculated from the cell volume of normal blood and the apparent increase in the cell volume of the blood after passage through the congested vessels. If the capillary wall were totally impermeable to colloids the protein content of the blood would be increased in proportion to …
Joint channel decoding of spatially and temporally correlated data in wireless sensor networks

In densely deployed wireless sensor networks, sensor observations are spatially correlated. Furthermore, the nature of physical phenomena constitutes a temporal correlation between transmitted observations of an individual sensor node. In this paper, we propose a joint iterative channel decoding scheme using turbo codes. The proposed decoder exploits the spatial and temporal correlations of two binary data sequences to achieve additional coding gain. Simultaneously exploiting the spatial and temporal correlation, the proposed decoder achieves large performance gain.
Distance learning for categorical attribute based on context information

In this paper, we propose a novel method to measure the dissimilarity of categorical data. Our approach is based on two steps, in the first step we select a relevant subset of the whole attributes set that we use as the context for a given attribute and in the second step computes dissimilarity between pair of values of the same attribute using the context defined in the previous step. Dissimilarity between two categorical values of an attribute compute as a combination of dissimilarities between the conditional probability distributions of context attributes given these two values. Experiments with real data show that our dissimilarity estimation method improves the accuracy of the popular nearest neighbor classifier.
Interactive Gesture-based Authentication for Tabletop Devices

Multi-touch tablets allow users to interact with computers through intuitive, natural gestures and direct manipulation of digital objects. One advantage of these devices is that they can offer a large, collaborative space where several users can work on a task at the same time. However the lack of privacy in these situations makes standard password-based authentication easily compromised. We therefore propose a new gesture-based authentication system based on each users’ unique signature of touch motion. Our technique has two key features. First, at each step in authentication the system prompts the user to make a specific gesture selected to maximize the expected long-term information gain. Hence the order of gestures can be different every time, and does not require the user to memorize a specific pattern. Second, each gesture is integrated using a novel hierarchical probabilistic model, allowing the system to accept or reject a user after a variable number of gestures, often in as few as five gestures. This touch-based approach allows the user to accurately authenticate without the need to cover their hand or look over their shoulder. It also allows the system to adapt to the diversity in touch styles for any particular user population. We tested this method using a set of samples were collected under realworld conditions in a business office, using a touch tablet that was used on a near daily basis by users familiar with the device. Despite the lack of sophisticated, high-precision equipment or noise suppression techniques, our system is able to achieve extremely high user recognition accuracy with relatively few gestures, demonstrating that human touch patterns have a distinctive “signature” can be used as a powerful biometric measure for user recognition and personalization.
Situation-aware decision making for autonomous driving on urban road using online POMDP

As autonomous vehicles begin venturing on the urban road, rational decision making is essential for driving safety and efficiency. This paper presents a situation-aware decision making algorithm for autonomous driving on urban road. Specifically, an urban road situation model is proposed first for proper environment representation, thereafter the situation-aware decision making problem is modeled as a Partially Observable Markov Decision Process (POMDP) and solved in an online manner. The proposed algorithm has been extensively evaluated, which is general enough for autonomous driving in various urban road scenarios, including leader following, collision avoidance and traffic negotiation at both T-junction and roundabout.
The Design of an Orchestrated Execution Environment Based on JBI

Many applications are exposed as Web Services deployed in web servers. We use BPEL to orchestrate these services to provide new services. This way works very well if there are only Internet services. But if there are telegraphic services it becomes slower. In this paper we present a detailed analysis of an enhanced JBI architecture in which a JAIN/SLEE service engine has been seamlessly integrated. With BPEL engine and JAIN/SLEE service engine we are capable to orchestrate service entities from both telecom and IT domains. JAIN/SLEE service engine which is driven by events, contains all the atomic business services. To orchestrate these atomic services, we design a business BPEL process and deploy it to BPEL execution engine. The orchestrated execution environment is capable of integrating the business in both Internet field and Telecommunication field.
Receiver Design for MIMO Radar Range Sidelobes Suppression

Multiple-input multiple-output (MIMO) radar transmits multiple-coded signals. In matched filter receiver, coded signals are required to have very good auto- and cross-correlation properties. These conditions are difficult to fulfill simultaneously when the lengths of the codes are short and there are many transmit antennas. In this correspondence, a receive filter matrix is designed using quadratic optimization method. The integrated correlations between the transmitted codes and the receive filter matrix in the area around zero shift are constrained under a prescribed level and the output noise power is minimized. A closed form solution is obtained. This integrated sidelobe level (ISL) method is computationally more efficient compared with the peak sidelobe level (PSL) method.
The Effects of Competition and Costs on Demonstration Strategies in the Software Industry

In the software industry, the need to provide a mechanism that enables the prospective customer to experience the product before the final purchase increases as a result of the increase in competition and the technical complexity of the product. As a result a demonstration offer is becoming an integrated part of any software sales effort. Software demonstrations vary in length (duration) and personalization level. With the increase in the popularity of the Internet, the tendency to use it as a vehicle for providing information about the product also increases. This includes a demonstration provided via the Internet. The special characteristics of the Internet dictate the demonstration(cid:146)s character, i
Stronger selection can slow down evolution driven by recombination on a smooth fitness landscape

Stronger selection implies faster evolution—that is, the greater the force, the faster the change. This apparently self-evident proposition, however, is derived under the assumption that genetic variation within a population is primarily supplied by mutation (i.e. mutation-driven evolution). Here, we show that this proposition does not actually hold for recombination-driven evolution, i.e. evolution in which genetic variation is primarily created by recombination rather than mutation. By numerically investigating population genetics models of recombination, migration and selection, we demonstrate that stronger selection can slow down evolution on a perfectly smooth fitness landscape. Through simple analytical calculation, this apparently counter-intuitive result is shown to stem from two opposing effects of natural selection on the rate of evolution. On the one hand, natural selection tends to increase the rate of evolution by increasing the fixation probability of fitter genotypes. On the other hand, natural selection tends to decrease the rate of evolution by decreasing the chance of recombination between immigrants and resident individuals. As a consequence of these opposing effects, there is a finite selection pressure maximizing the rate of evolution. Hence, stronger selection can imply slower evolution if genetic variation is primarily supplied by recombination.