Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining the Strengths of Sparse Interest Point and Dense Image Registration for RGB-D Odometry

Visual odometry, i.e., estimating ego-motion from camera images, is frequently used as a building block in robot navigation systems. In this paper, we propose an efficient approach that provides robust and accurate visual odometry from RGB-D cameras in a wide range of settings. We seamlessly combine dense RGB-D image registration with the alignment of sparse interest points. While the former approach is robust and accurate when perceiving the depth towards structures well in less textured parts of an environment, the latter often performs better, if well textured but less structured parts are visible. Our formulation also integrates interest points with strongly uncertain or no depth to make best use of the available images. In experiments, we demonstrate advantages of our approach over methods that either are based on dense image or sparse interest point matching.
Current Insights into the Pathogenesis of Graves’ Ophthalmopathy

Abstract Environmental, genetic, and immune factors are at play in the development of the variable clinical manifestations of Graves’ ophthalmopathy (GO). Among the environmental contributions, smoking is the risk factor most consistently linked to the development or worsening of the disease. The close temporal relationship between the diagnoses of Graves’ hyperthyroidism and GO have long suggested that these 2 autoimmune conditions may share pathophysiologic features. The finding that the thyrotropin receptor (TSHR) is expressed in orbital fibroblasts, the target cells in GO, supported the notion of a common autoantigen. Both cellular and humeral immunity directed against TSHR expressed on orbital fibroblasts likely initiate the disease process. Activation of helper T cells recognizing TSHR peptides and ligation of TSHR by TRAb lead to the secretion of inflammatory cytokines and chemokines, and enhanced hyaluronic acid (HA) production and adipogenesis. The resulting connective tissue remodeling results in varying degrees extraocular muscle enlargement and orbital fat expansion. A subset of orbital fibroblasts express CD34, are bone-marrow derived, and circulate as fibrocytes that infiltrate connective tissues at sites of injury or inflammation. As these express high levels of TSHR and are capable of producing copious cytokines and chemokines, they may represent an orbital fibroblast population that plays a central role in GO development. In addition to TSHR, orbital fibroblasts from patients with GO express high levels of IGF-1R. Recent studies suggest that these receptors engage in cross-talk induced by TSHR ligation to synergistically enhance TSHR signaling, HA production, and the secretion of inflammatory mediators.
Bengali Named Entity Recognition Using Support Vector Machine

Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is nowadays considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali using Support Vector Machine (SVM). Though this state of the art machine learning method has been widely applied to NER in several well-studied languages, this is our first attempt to use this method to Indian languages (ILs) and particularly for Bengali. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the various named entity (NE) classes. A portion of a partially NE tagged Bengali news corpus, developed from the archive of a leading Bengali newspaper available in the web, has been used to develop the SVM-based NER system. The training set consists of approximately 150K words and has been manually annotated with the sixteen NE tags. Experimental results of the 10-fold cross validation test show the effectiveness of the proposed SVM based NER system with the overall average Recall, Precision and F-Score of 94.3%, 89.4% and 91.8%, respectively. It has been shown that this system outperforms other existing Bengali NER systems.
Construction of Keyword Extraction using Statistical Approaches and Document Clustering by Agglomerative method

Organize continuing growth of dynamic unstructured documents is the major challenge to the field experts. Handling of such unorganized documents causes more expensive. Clustering of such dynamic documents helps to reduce the cost. Document clustering by analysing the keywords of the documents is one the best method to organize the unstructured dynamic documents. Statistical analysis is the best adaptive method to extract the keywords from the documents. In this paper an algorithm was proposed to cluster the documents. It has two parts, first part extracts the keywords using statistical method and the second part construct the clusters by keyword using agglomerative method. This proposed algorithm gives more than 90% of accuracy. Keywords– Agglomerative Method, Co-occurrences Statistical Information (CSI), Document Clustering, Similarity Measures, TF-ISF
Pleckstrin Homology Domain-mediated Activation of the Rho-specific Guanine Nucleotide Exchange Factor Dbs by Rac1*

Dbs is a Rho-specific guanine nucleotide exchange factor that was identified in a screen for proteins whose expression causes deregulated growth in NIH 3T3 mouse fibroblasts. Although Rac1 has not been shown to be a substrate for Dbs in either in vitro or in vivo assays, the Rat ortholog of Dbs (Ost) has been shown to bind specifically to GTP·Rac1 in vitro. The dependence of the Rac1/Dbs interaction on GTP suggests that Dbs may in fact be an effector for Rac1. Here we show that the interaction between activated Rac1 and Dbs can be recapitulated in mammalian cells and that the Rac1 docking site resides within the pleckstrin homology domain of Dbs. This interaction is specific for Rac1 and is not observed between Rac1 and several other members of the Rho-specific guanine nucleotide exchange factor family. Co-expression of Dbs with activated Rac1 causes enhanced focus forming activity and elevated levels of GTP·RhoA in NIH 3T3 cells, indicating that Dbs is activated by the interaction. Consistent with this, activated Rac1 co-localizes with Dbs in NIH 3T3 cells, and natively expressed Rac1 relocalizes in response to Dbs expression. To summarize, we have characterized a surprisingly direct pleckstrin homology domain-mediated mechanism through which Rho GTPases can become functionally linked.
Time-regularized interrupting options

High-level skills relieve planning algorithms from low-level details. But when the skills are poorly designed for the domain, the resulting plan may be severely suboptimal. Sutton et al. (1999) made an important step towards resolving this problem by introducing a rule that automatically improves a set of skills called options. This rule terminates an option early whenever switching to another option gives a higher value than continuing with the current option. However, they only analyzed the case where the improvement rule is applied once. We show conditions where this rule converges to the optimal set of options. A new interrupting Bellman operator that simultaneously improves the set of options is at the core of our analysis. One problem with the update rule is that it tends to favor lower-level skills. We introduce a regularization term that favors longer duration skills. Experimental results demonstrate that this approach can derive a good set of high-level skills even when the original set of skills cannot solve the problem.
Dead or alive: animal sampling during Ebola hemorrhagic fever outbreaks in humans

There are currently no widely accepted animal surveillance guidelines for human Ebola hemorrhagic fever (EHF) outbreak investigations to identify potential sources of Ebolavirus (EBOV) spillover into humans and other animals. Animal field surveillance during and following an outbreak has several purposes, from helping identify the specific animal source of a human case to guiding control activities by describing the spatial and temporal distribution of wild circulating EBOV, informing public health efforts, and contributing to broader EHF research questions. Since 1976, researchers have sampled over 10,000 individual vertebrates from areas associated with human EHF outbreaks and tested for EBOV or antibodies. Using field surveillance data associated with EHF outbreaks, this review provides guidance on animal sampling for resource-limited outbreak situations, target species, and in some cases which diagnostics should be prioritized to rapidly assess the presence of EBOV in animal reservoirs. In brief, EBOV detection was 32.7% (18/55) for carcasses (animals found dead) and 0.2% (13/5309) for live captured animals. Our review indicates that for the purposes of identifying potential sources of transmission from animals to humans and isolating suspected virus in an animal in outbreak situations, (1) surveillance of free-ranging non-human primate mortality and morbidity should be a priority, (2) any wildlife morbidity or mortality events should be investigated and may hold the most promise for locating virus or viral genome sequences, (3) surveillance of some bat species is worthwhile to isolate and detect evidence of exposure, and (4) morbidity, mortality, and serology studies of domestic animals should prioritize dogs and pigs and include testing for virus and previous exposure.
Optimal Resource Provisioning for Scaling Enterprise Applications on the Cloud

Over the past years organizations have been moving their enterprise applications to the cloud to take advantage of cloud's utility computing and elasticity. However, in enterprise applications or workflows, generally, different components/tasks will have different scaling requirements and finding an ideal deployment configuration and having the application to scale up and down based on the incoming requests is a difficult task. This paper presents a novel resource provisioning policy that can find the most cost optimal setup of variety of instances of cloud that can fulfill incoming workload. All major factors involved in resource amount estimation such as processing power, periodic cost and configuration cost of each instance type and capacity of clouds are considered in the model. Additionally, the model takes lifetime of each running instance into account while trying to find the optimal setup. Benchmark experiments were conducted on Amazon cloud, using a real load trace and through two main control flow components of enterprise applications, AND and XOR. In these experiments, our model could find the most cost-optimal setup for each component/task of the application within reasonable time, making it plausible for auto-scaling any web/services based enterprise workflow/application on the cloud.
Age is not a contraindication to home-based dialysis - Quality-of-Life outcomes favour older patients on peritoneal dialysis regimes relative to younger patients.

AIM To compare Quality of Life, anxiety and depression between older (≥65 years) and younger (<65 years) patients across automated peritoneal dialysis and continuous ambulatory peritoneal dialysis. BACKGROUND There is a lack of studies as to whether the different peritoneal dialysis modalities confer similar outcomes in older and younger patients. DESIGN Cross-sectional. METHODS A total of 201 patients completed the Kidney Disease Quality of Life Short-Form, World Health Organization Quality of Life Instrument, Short Form and Hospital Anxiety and Depression Scale. Comorbidity and biochemical values were abstracted from medical records. RESULTS Older patients reported significantly better quality of life than younger patients in the Kidney Disease Quality of Life Short-Form effects of kidney disease and patient satisfaction and the World Health Organization Quality of Life Instrument overall Quality-of-Life/health despite worse clinical profile. Quality of life outcomes were comparable between automated peritoneal dialysis and continuous ambulatory peritoneal dialysis with the exception of the Kidney Disease Quality of Life Short-Form symptoms in favour of automated peritoneal dialysis. Levels of anxiety and depression were equivalent for older and younger patients across peritoneal dialysis modalities. The observed quality-of-life advantages for older patients persisted after case-mix adjustments and extended to more quality-of-life domains and depression and anxiety. CONCLUSION Our findings of superior quality of life in patients aged ≥ 65 support the expansion of peritoneal dialysis use in older patients. Patients across different age groups should be given non-biased information about both peritoneal dialysis modalities and individual preferences should be elicited and carefully considered by healthcare providers.
Instance-Based Question Answering: A Data-Driven Approach

Anticipating the availability of large questionanswer datasets, we propose a principled, datadriven Instance-Based approach to Question Answering. Most question answering systems incorporate three major steps: classify questions according to answer types, formulate queries for document retrieval, and extract actual answers. Under our approach, strategies for answering new questions are directly learned from training data. We learn models of answer type, query content, and answer extraction from clusters of similar questions. We view the answer type as a distribution, rather than a class in an ontology. In addition to query expansion, we learn general content features from training data and use them to enhance the queries. Finally, we treat answer extraction as a binary classification problem in which text snippets are labeled as correct or incorrect answers. We present a basic implementation of these concepts that achieves a good performance on TREC test data.
Bis(tetra-n-butylammonium) bis(5,6-dicyanopyrazine-2,3-dithiolato-κ2 S,S′)palladium(II)

In the title complex, (C16H36N)2[Pd(C6N4S2)2], the centrosymmetric dianion is planar, with an r.m.s. deviation of 0.034 (8) Å. The PdII atom, lying on an inversion center, has a square-planar coordination geometry, with Pd—S bond lengths of 2.276 (3) and 2.294 (3) Å.
Inverting Schema Mappings: Bridging the Gap between Theory and Practice

The inversion of schema mappings has been identified as one of the fundamental operators for the development of a general framework for metadata management. In fact, during the last years three alternative notions of inversion for schema mappings have been proposed (Fagin-inverse [10], quasi-inverse [14] and maximum recovery [2]). However, the procedures that have been developed for computing these operators have some features that limit their practical applicability. First, these algorithms work in exponential time and produce inverse mappings of exponential size. Second, these algorithms express inverses in some mappings languages which include features that are difficult to use in practice. A typical example is the use of disjunction in the conclusion of the mapping rules, which makes the process of exchanging data much more complicated. In this paper, we propose solutions for the two problems mentioned above. First, we provide a polynomial time algorithm that computes the three inverse operators mentioned above given a mapping specified by a set of tuple-generating dependencies (tgds). This algorithm uses an output mapping language that can express these three operators in a compact way and, in fact, can compute inverses for a much larger class of mappings. Unfortunately, it has already been proved that this type of mapping languages has to include some features that are difficult to use in practice and, hence, this is also the case for our output mapping language. Thus, as our second contribution, we propose a new and natural notion of inversion that overcomes this limitation. In particular, every mapping specified by a set of tgds admits an inverse under this new notion that can be expressed in a mapping language that slightly extends tgds, and that has the same good properties for data exchange as tgds. Finally, as our last contribution, we provide an algorithm for computing such inverses.
Design requirements of adaptive pilot-symbol patterns

Adaptive pilot patterns offer high throughput gains. However, their application requires additional feedback. In this paper, we investigate the feedback requirements for adaptive pilot patterns applied in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing systems. The main goal is to support a wide range of Doppler spreads and Root Mean Square (RMS) delay spreads while keeping the number of allowed pilot patterns at a minimum. Based on our simulation results, we show that only four bits of additional wide-band feedback per user are required in order to optimally support RMS delay spreads up to 800 ns and Doppler frequencies up to 1200 Hz.
Facial Action Unit recognition by relation modeling from both qualitative knowledge and quantitative data

In this paper, we propose to capture Action Unit (AU) relations existing in both qualitative knowledge and quantitative data through Credal Networks (CN). Each node of the CN represents an AU label, and the links and probability intervals capture the probabilistic dependencies among multiple AUs. The structure of CN is designed based on prior knowledge. The parameters of CN are learned from both knowledge and ground-truth AU labels. The AU preliminary estimations are obtained by an existing image-driven recognition method. With the learned credal network, we infer the true AU labels by combining the relationships among labels with the previous obtained estimations. Experimental results on the CK+ database and MMI database demonstrate that with complete AU labels, our CN model is slightly better than the Bayesian Network (BN) model, demonstrating that credal sets learned from data can capture uncertainty more reliably; With incomplete and error-prone AU annotations, our CN model outperforms the BN model, indicating that credal sets can successfully capture qualitative knowledge.
How many high-level concepts will fill the semantic gap in video retrieval ?

A number of researchers have been building high-level seman tic concept detectors such as outdoors, face, building, etc., t o help with semantic video retrieval. Using the TRECVID video collecti on and LSCOM truth annotations from 300 concepts, we simulate perf ormance of video retrieval under different assumptions of con cept detection accuracy. Even low detection accuracy provides g ood retrieval results, when sufficiently many concepts are used. C onsidering this extrapolation under reasonable assumptions, th is paper arrives at the conclusion that “concept-based” video retri eval with fewer than 5000 concepts, detected with minimal accuracy of 10% mean average precision is likely to provide high accuracy re sults, comparable to text retrieval on the web, in a typical broadca st news collection. We also derive evidence that it should be feasib le to find sufficiently many new, useful concepts that would be help ful for retrieval.
Energy distribution in formant bands for arabic vowels

The acoustic cues play a major role in speech segmentation phase; the extraction of these indexes facilitates the characterization of the speech signal. In this work, we aim to study Arabic vowels (/a/, /a:/, /i/, /i:/, /u/ and /u:/), especially the long ones. We are interested in characterizing this type of vowels in terms of time, frequency and energy. The cues extracted and analyzed in this work are: segment length, voicing degree and formants values.
Detailed study of IP/ reconfigurable optical networks

IP over reconfigurable optical network architectures have been extensively discussed within the research literature over the past few years. However, although reconfigurable optical networks have been deployed and signaling protocols between IP routers and optical networks have been standardized, large IP backbones are typically deployed using the reconfigurable optical networks. One of the most important criteria in determining whether an IP backbone should be carried over a reconfigurable optical network is economic viability - which necessitates a detailed, accurate economic study of IP backbone over reconfigurable optical network architectures. In this paper, we analyze and explore four IP over optical network architectures for a typical large ISP backbone. In contrast with other published claims, our results suggest that an IP over opaque reconfigurable optical network architecture is not economically attractive with current equipment and IP backbone network design requirements. However, for ISPs also carrying large volumes of transport network private line services, our proposed integrated IP over re-configurable optical network architecture may provide an attractive alternative for providing rapid, cost effective failure recovery.
Playback-Adaptive Multi-Source Video Streaming

The best-effort nature of the Internet poses significant challenges to guaranteeing performance of video streaming applications. In particular, the available bandwidth between a sender and a receiver is often unpredictable and can vary substantially from time to time, causing buffer underflows and consequently playback starvations. This work tackles this problem by proposing a novel video playback adaptation and rebuffering algorithm for multi-source streaming. Unlike single-source streaming, the aggregate bandwidth of multiple senders closely follows the normal distribution when the number of senders exceeds four. Based on this discovery this paper presents a video playback rate adaptation and rebuffering algorithm that can significantly reduce playback starvations. This adaptive multi-source streaming scheme is simple to implement, does not require complex media adaptation processing at the servers, and can be applied to the vast amount of video content already available in the Internet.
Improving the quality factor estimation for differentially driven RF CMOS inductor

The quality factor of on-chip differentially driven RF CMOS inductors is derived using energy based formulas from an equivalent differential one-port model for the inductor, taking into account the influence of signal leakage to ground at high frequencies. The quality factor is calculated for various load conditions and compared to published results based on existing definitions of the quality factor. Results suggest that both differential and common mode signals have to be taken into account for an accurate estimation of the quality factor.
Anarchic Urban Expansion Detection and Monitoring with Integration of Expert Knowledge

With the advent of very high spatial, spectral, and temporal resolution satellites, Satellite Image Time Series (SITS) analysis and interpretation become even more challenging than before. Besides, several conventional techniques for controlling and monitoring anarchic urban expansion have been initiated but they remain not sufficient to overcome this issue.This paper proposes an automatic method of detection and monitoring of anarchic urban expansions starting from multi-sources and multi-temporal data (VHR satellite images and geographic information data). First, the illegal urban areas are extracted using an original SVM based technique integrating expert knowledge and auxiliary data by means of ontology construction. This leads to the formalization of the expert semantic information and the urban construction rules (often in sentences form) and their confrontation with the classification results.Secondly, the SITS classified images are modeled using Spatial-Object Temporal Adjacency Graphs (SOTAG) constructed for each region of the first image. These graphs are then classified using a Marginalized Graph Kernel (MGK) SVM based classification in order to extract regions with similar temporal evolution. We are focusing mainly on monitoring legal and illegal urban expansions. The resulted spatio-temporal map describes urban areas types and their changes over time.