Miracle-dz/UniFAR-FTUs huggingface dataset:
Assist-as-needed training paradigms for robotic rehabilitation of spinal cord injuries

This paper introduces a new "assist-as-needed" (AAN) training paradigm for rehabilitation of spinal cord injuries via robotic training devices. In the pilot study reported in this paper, nine female adult Swiss-Webster mice were divided into three groups, each experiencing a different robotic training control strategy: a fixed training trajectory (fixed group, A), an AAN training method without interlimb coordination (Band Group, B), and an AAN training method with bilateral hind-limb coordination (Window Group, C). Fourteen days after complete transection at the mid-thoracic level, the mice were robotically trained to step in the presence of an acutely administered serotonin agonist, quipazine, for a period of six weeks. The mice that received AAN training (Groups B and C) show higher levels of recovery than Group A mice, as measured by the number, consistency, and periodicity of steps realized during testing sessions. Group C displays a higher incidence of alternating stepping than Group B. These results indicate that this training approach may be more effective than fixed trajectory paradigms in promoting robust post-injury stepping behavior. Furthermore, the constraint of interlimb coordination appears to be an important contribution to successful training
Leveraging the OSM building data to enhance the localization of an urban vehicle

In this paper we present a technique that takes advantage of detected building façades and OpenStreetMaps data to improve the localization of an autonomous vehicle driving in an urban scenario. The proposed approach leverages images from a stereo rig mounted on the vehicle to produce a mathematical representation of the buildings' façades within the field of view. This representation is matched against the outlines of the surrounding buildings as they are available on OpenStreetMaps. The information is then fed into our probabilistic framework, called Road Layout Estimation, in order to produce an accurate lane-level localization of the vehicle. The experiments conducted on the well-known KITTI datasets prove the effectiveness of our approach.
DYNAMIC DISPLAY OF PERSONALIZED SOFTWARE FUNCTIONS

Generalized software packages endowed with a large spectrum of functionalities are often underutilized because users are not always aware of all the functionalities. It is hence desirable to display personalized information about the package. Though popular in web-based applications, personalization as a field of research in the design of generalized software packages is rare. This article develops a semi-Markov model of user navigation and an adaptive dynamic programming formulation to select high-utility software functions (states) for dynamically displaying them to a user. The personalization algorithm considers the interests of the software designers, the past users, and the current user. Frequency of visit to a state and the holding time in the state together determines the utility of the state. The personalization algorithm considers the interests of the software designers, the past users, and the current user. The algorithm is built in a demo package of ActiveX Servers and Controls. Graduate students tested the package. Pareto analysis and tests of hypothesis conducted on the test results indicate that the users did utilize the information on the displayed personalized software functions.
Extensibility verification of robust domain selection against out-of-grammar utterances in multi-domain spoken dialogue system

We developed a robust domain selection method and verified its extensibility. An issue in domain selection is its robustness against out-of-grammar utterances. It is essential to generate correct system responses because such utterances often cause domain selection errors. We therefore integrated the topic estimation results and the dialogue history to construct a robust domain classifier. Another issue is that domain selection should be performed within an extensible framework, because the system is often modified and extended. That is, the classifier should still have high performance without reconstructing it after adding new domains. The extensibility of our method was not experimentally verified yet, because it requires a lot of effort to collect new dialogue data after extending the system. Therefore, we verified extensibility without collecting new data. We constructed the classifier by leaving out some domains in the dialogue data and then evaluated its accuracy as the classifier for the data where the left-out domains were virtually added.
Decision Support System for research project duplication detection

Decision Support Systems are usually computer applications along with a human component that can sift through large amounts of data and pick between many choices. Among many challenges in front of research managers, checking of duplication of research efforts is a major challenge. Existing systems do provide simple keyword base search wherein one can find similar projects. These systems do not take care of the semantics or sense of the word into consideration. Also, these systems fail to provide results if synonyms of the keywords are used in other research projects. Moreover, if the keywords are matched and are not used in the same sense, it is very much likely that the projects may not be similar. The presented approach in this work uses WordNet Ontology for finding the semantics of the textual information available within the system. Two algorithms viz. Filtered Set and Preferential Coefficient are presented that also take care the structure of the research project proposal. The algorithms are implemented for the PIMS-ICAR database that contains more than 5000 research project documents.
Describing the issues of knowledge management in R&D: Towards a communication and analysis tool

In this article, a comprehensive descriptive model of R&D knowledge management is presented and its use illustrated. Knowledge is defined as: information internalized by means of research, study or experience, that has value for the organization. First, the issue of knowledge management is placed in the context of R&D management, and set alongside what has been written in R&D management literature about topics such as information management, information technology in R&D, technology transfer, communication and organizational learning. Then, we present our descriptive model, and apply it in a case study concerning a Dutch multinational in the chemical industry. The model served as an aid to identify bottlenecks, and was a useful starting point for formulating improvement plans, some of which are presented. The paper concludes with an evaluation of the model as a communication and analysis tool, and ideas for further improvement.
Classification-Based Adaptive Filtering for Multiframe Blind Image Restoration

In this paper, the blind restoration of a scene is investigated, when multiple degraded (blurred and noisy) acquisitions are available. An adaptive filtering technique is proposed, where the distorted images are filtered, classified and then fused based upon the classification decisions. Finite normal-density mixture (FNM) models are used to model the filtered outputs at each iteration. For simplicity, fixed number of Gaussian components (classes) is, initially, considered for each degraded frame and the selection of the optimal number of classes is performed according to the global relative entropy criterion. However, there exist cases where dynamically varying FNM models should be considered, where the optimal number of classes is selected according to the Akaike information criterion. The iterative application of classification and fusion, followed by optimal adaptive filtering, converges to a global enhanced representation of the original scene in only a few iterations. The proposed restoration method does not require knowledge of the point-spread-function support size or exact alignment of the acquired frames. Simulation results on synthetic and real data, using both fixed and dynamically varying FNM models, demonstrate its efficiency under both noisy and noise-free conditions.
Hiding in plain sight: a closer look at posterior cortical atrophy

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome dominated by deterioration of higher visual function (particularly visuospatial and visuoperceptual abilities). It is most commonly due to Alzheimer's disease pathology, but may also be caused by dementia with Lewy bodies, corticobasal degeneration or Creutzfeldt-Jakob disease. Patients often present to optometrists, ophthalmologists and/or neurologists with non-specific visual complaints, and unless clinicians seek the specific symptoms and signs of PCA (beyond that of the ‘standard’ neurological examination), this infrequent disorder is easily missed, delaying its diagnosis and treatment. We review the clinical features of PCA, focusing on its visual manifestations, to help neurologists recognise this important syndrome.
Adipocyte Hypertrophy, Inflammation and Fibrosis Characterize Subcutaneous Adipose Tissue of Healthy, Non-Obese Subjects Predisposed to Type 2 Diabetes

Background The adipose tissue is important for development of insulin resistance and type 2 diabetes and adipose tissue dysfunction has been proposed as an underlying cause. In the present study we investigated presence of adipocyte hypertrophy, and gene expression pattern of adipose tissue dysfunction in the subcutaneous adipose tissue of healthy, non-obese subjects predisposed to type 2 diabetes compared to matched control subjects with no known genetic predisposition for type 2 diabetes. Method Seventeen healthy and non-obese subjects with known genetic predisposition for type 2 diabetes (first-degree relatives, FDRs) and 17 control subjects were recruited. The groups were matched for gender and BMI and had similar age. Glucose tolerance was determined by an oral glucose tolerance test and insulin sensitivity was calculated using HOMA-index. Blood samples were collected and subcutaneous abdominal adipose tissue biopsies obtained for gene expression analysis and adipocyte cell size measurement. Results Our findings show that, in spite of similar age, BMI and percent body fat, FDRs displayed adipocyte hypertrophy, as well as higher waist/hip ratio, fasting insulin levels, HOMA-IR and serum triglycerides. Adipocyte hypertrophy in the FDR group, but not among controls, was associated with measures of impaired insulin sensitivity. The adipocyte hypertrophy was accompanied by increased inflammation and Wnt-signal activation. In addition, signs of tissue remodeling and fibrosis were observed indicating presence of early alterations associated with adipose tissue dysfunction in the FDRs. Conclusion Genetic predisposition for type 2 diabetes is associated with impaired insulin sensitivity, adipocyte hypertrophy and other markers of adipose tissue dysfunction. A dysregulated subcutaneous adipose tissue may be a major susceptibility factor for later development of type 2 diabetes.
Immunoexpression of Ki-67, MCM2, and MCM3 in Ameloblastoma and Ameloblastic Carcinoma and Their Correlations with Clinical and Histopathological Patterns

Cell proliferation assays are performed using antibodies against nuclear proteins associated with DNA replication. These nuclear proteins have gained special interest to predict the biological and clinical behaviors of various tumors. The aim of this study was to analyze the presence of Ki-67 protein and the minichromosome maintenance-2 (MCM2) and maintenance-3 (MCM3) proteins in ameloblastoma. Materials and Methods. Cell proliferation marker expression levels were assessed via immunohistochemistry in 111 ameloblastoma cases (72 unicystic ameloblastoma samples, 38 solid/multicystic ameloblastoma samples, and 1 ameloblastic carcinoma). The label index was performed as described previously. Results. MCM2 and MCM3 showed higher proliferation indexes in all variants of ameloblastoma compared to the classic marker Ki-67. No correlation between the proliferation index and the clinical and protein expression data was observed. Conclusion. The results suggest that clinical features do not directly affect tumor cell proliferation. Moreover, the high levels of cellular proliferation of MCM2 and MCM3 compared with Ki-67 may indicate that MCM2 and MCM3 are more sensitive markers for predicting the growth rate and eventually might be helpful as a tool for predicting aggressive and recurrent behaviors in these tumors.
Lane Detection of Curving Road for Structural Highway With Straight-Curve Model on Vision

Curve is the traffic accident-prone area in the traffic system of the structural road. How to effectively detect the lane-line and timely give the traffic information ahead for drivers is a difficult point for the assisted safe driving. The traditional lane detection technology is not very applicable in the curved road conditions. Thus, a curve detection algorithm which is based on straight-curve model is proposed in this paper and this method has good applicability for most curve road conditions. First, the method divides the road image into the region of interest and the road background region by analyzing the basic characteristics of the road image. The region of interest is further divided into the straight region and the curve region. At the same time, the straight-curve mathematical model is established. The mathematical equation of the straight model is obtained by using the improved Hough transform. The polynomial curve model is established according to the continuity of the road lane-line and the tangent relationship between the straight model and the curve model. Then, the parameters of the curve model equation are solved by the curve fitting method. Finally, the detection and identification of the straight and the curve are realized respectively and the road lane-line is reconstructed. Experiments show that this method can accurately identify the curve lane-line, provide effective traffic information, make early warning, and it also has certain universality.
Two Group A Streptococcal Peptide Pheromones Act through Opposing Rgg Regulators to Control Biofilm Development

Streptococcus pyogenes (Group A Streptococcus, GAS) is an important human commensal that occasionally causes localized infections and less frequently causes severe invasive disease with high mortality rates. How GAS regulates expression of factors used to colonize the host and avoid immune responses remains poorly understood. Intercellular communication is an important means by which bacteria coordinate gene expression to defend against host assaults and competing bacteria, yet no conserved cell-to-cell signaling system has been elucidated in GAS. Encoded within the GAS genome are four rgg-like genes, two of which (rgg2 and rgg3) have no previously described function. We tested the hypothesis that rgg2 or rgg3 rely on extracellular peptides to control target-gene regulation. We found that Rgg2 and Rgg3 together tightly regulate two linked genes encoding new peptide pheromones. Rgg2 activates transcription of and is required for full induction of the pheromone genes, while Rgg3 plays an antagonistic role and represses pheromone expression. The active pheromone signals, termed SHP2 and SHP3, are short and hydrophobic (DI[I/L]IIVGG), and, though highly similar in sequence, their ability to disrupt Rgg3-DNA complexes were observed to be different, indicating that specificity and differential activation of promoters are characteristics of the Rgg2/3 regulatory circuit. SHP-pheromone signaling requires an intact oligopeptide permease (opp) and a metalloprotease (eep), supporting the model that pro-peptides are secreted, processed to the mature form, and subsequently imported to the cytoplasm to interact directly with the Rgg receptors. At least one consequence of pheromone stimulation of the Rgg2/3 pathway is increased biogenesis of biofilms, which counteracts negative regulation of biofilms by RopB (Rgg1). These data provide the first demonstration that Rgg-dependent quorum sensing functions in GAS and substantiate the role that Rggs play as peptide receptors across the Firmicute phylum.
Understanding Consumer Recommendation Behavior in a Mobile Phone Service Context

Mobile service usage has become an important research topic in the field of MIS. In the past decade, research results have important implications for marketing managers with regard to the development of mobile services or advertising content employed to increase a consumer’s intentions to use. We consider that a customer is not only a service user, but also the partner of a firm. Therefore, we focus on two determinants of customer recommendation behavior, namely, overall satisfaction and flow experience. We also propose a number of hypotheses related to the constructs of overall satisfaction, and test them using data provided by 3G mobile service subscribers. The results contribute to our understanding of how customers are willing to make recommendations to others. Besides increasing customer satisfaction, we should consider a mediating factor—users’ flow experiences. Our findings provide empirical support for most of the hypotheses. The theoretical and practical implications of our findings are also discussed, and suggestions for further research are offered.
Presynaptic Adenosine Receptor-Mediated Regulation of Diverse Thalamocortical Short-Term Plasticity in the Mouse Whisker Pathway

Short-term synaptic plasticity (STP) sets the sensitivity of a synapse to incoming activity and determines the temporal patterns that it best transmits. In “driver” thalamocortical (TC) synaptic populations, STP is dominated by depression during stimulation from rest. However, during ongoing stimulation, lemniscal TC connections onto layer 4 neurons in mouse barrel cortex express variable STP. Each synapse responds to input trains with a distinct pattern of depression or facilitation around its mean steady-state response. As a result, in common with other synaptic populations, lemniscal TC synapses express diverse rather than uniform dynamics, allowing for a rich representation of temporally varying stimuli. Here, we show that this STP diversity is regulated presynaptically. Presynaptic adenosine receptors of the A1R type, but not kainate receptors (KARs), modulate STP behavior. Blocking the receptors does not eliminate diversity, indicating that diversity is related to heterogeneous expression of multiple mechanisms in the pathway from presynaptic calcium influx to neurotransmitter release.
Annotating regulatory DNA based on man-mouse genomic comparison

Non-coding DNA segments that are conserved between the human and mouse genomic sequence are good indicators of possible regulatory sequences. Here we report on a systematic approach to delineate such conserved elements from upstream regions of orthologous gene pairs from man and mouse. We focus on orthologous genes in order to maximize our chances to find functionally similar regulatory elements. The identification of conserved elements is effected using the Waterman-Eggert local suboptimal alignment algorithm. We have modified an implementation of this algorithm such that it integrates the determination of statistical significance for the local suboptimal alignments. This has the effect of outputting a dynamically determined number of suboptimal alignments that are deemed statistically significant. Comparison with experimentally determined annotation shows a striking enrichement of regulatory sites among the conserved regions. Furthermore, the conserved regions tend to cover the promotor region described in the EPD database.
On multiple solutions for a singular quasilinear elliptic system involving critical Hardy-Sobolev exponents

This paper is concerned with the existence of nontrivial solutions for a class of degenerate quasilinear elliptic systems involving critical Hardy-Sobolev type exponents. The lack of compactness is overcame by using the Brezis-Nirenberg approach, and the multiplicity result is obtained by combining a version of the Ekeland's variational principle due to Mizoguchi with the Ambrosetti-Rabinowitz mountain pass theorem
Endothelial Growth Factor-A Mediated by Neutrophil-Derived Vascular Protein-2-Induced Angiogenesis In Vivo Is CXCL1/Macrophage Inflammatory

The angiogenic activity of CXC-ELR (cid:1) chemokines, including CXCL8/IL-8, CXCL1/macrophage inﬂammatory protein-2 (MIP-2), and CXCL1/growth-related oncogene- (cid:2) in the Matrigel sponge angiogenesis assay in vivo, is strictly neutrophil dependent, as neutrophil depletion of the animals completely abrogates the angiogenic response. In this study, we demonstrate that mice deﬁcient in the src family kinases, Hck and Fgr ( hck (cid:3) / (cid:3) fgr (cid:3) / (cid:3) ), are unable to develop an angiogenic response to CXCL1/MIP-2, although they respond normally to vascular endothelial growth factor-A (VEGF-A). Histological examination of the CXCL1/MIP-2-containing Matrigel implants isolated from wild-type or hck (cid:3) / (cid:3) fgr (cid:3) / (cid:3) mice showed the presence of an extensive neutrophil inﬁltrate, excluding a defective neutrophil recruitment into the Matrigel sponges. Accordingly, neutrophils from hck (cid:3) / (cid:3) fgr (cid:3) / (cid:3) mice normally migrated and released gelatinase B in response to CXCL1/MIP-2 in vitro, similarly to wild-type neutrophils. However, unlike wild-type neutrophils, those from hck (cid:3) / (cid:3) fgr (cid:3) / (cid:3) mice were completely unable to release VEGF-A upon stimulation with CXCL1/MIP-2. Furthermore, neutralizing anti-VEGF-A Abs abrogated the angiogenic response to CXCL1/MIP-2 in wild-type mice and CXCL1/MIP-2 induced angiogenesis in the chick embryo chorioallantoic membrane assay, indicating that neutrophil-derived VEGF-A is a major mediator of CXCL1/MIP-2-induced angiogenesis. Finally, in vitro kinase assays conﬁrmed that CXCL1/MIP-2 activates Hck and Fgr in murine neutrophils. Taken together, these data demonstrate that CXCL1/MIP-2 leads to recruitment of neutrophils that, in turn, release biologically active VEGF-A, resulting in angiogenesis in vivo. Our observations delineate a novel mechanism by which CXCL1/MIP-2 induces neutrophil-dependent angiogenesis in vivo. The Journal of Immunology, 2004, 172: 5034–5040.
A Pull Based Energy Efficient Data Aggregation Scheme for Wireless Sensor Networks

In case of wireless routing in sensor networks, data aggregation has been proposed as a predominantly constructive prototype. Most of the routing algorithms for traditional networks are address centric, and the ad hoc nature of wireless sensor network makes them unsuitable for practical applications. Data-centric technologies that carry out in-network aggregation of data to capitulate energyefficient dissemination are essential. In this paper, we propose a Pull based Energy Efficient Data Aggregation (PEEDA) approach, to effectively deliver the data to the sink. In this approach, the sink will broadcast an interest message containing its required data model, to all the nodes. We form an cost effective aggregation tree towards the sink based on the ToD structure. When the aggregator receives the data from the sources, it aggregates the data depending on the interest message using spatial and temporal convergence. To achieve energy efficient aggregation, the MAC protocol uses the partially overlapped channels. By simulation results, we show that the proposed scheme consumes less energy and reduces the overhead and delay. C. Kavitha Assistant Professor, R.V. College of Engineering Visvesvaraya Technological University, Karnataka, India Dr.K. V.Viswanatha Professor, Department of CSE, R.V. College of Engineering Visvesvaraya Technological University, Karnataka, India The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at editor@ijcaonline.org