Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint-AL: Joint Discriminative and Generative Active Learning for Cross-Domain Semantic Concept Classification

As multimedia data come from a wide variety of domains, each having its distinctive data distributions, cross-domain video semantic concept classification becomes an important task in semantic computing. Its challenge arises from the different distribution (in feature space) of the concept between the source and the target domain, which makes a classifier trained on a source domain perform poorly on a target domain. Active learning can be employed to reuse the existing classifier in order to avoid expensively labeling target domain data for building a new classifier, which queries the labels for a number of most ambiguous samples in target domain and uses these samples to refine the source domain classifier. This discriminative query strategy, used by many traditional active learning methods, could fail if the difference in the feature space distribution of the concept is too large. A generative query strategy is proposed by us in this paper, to deal with large differences between two domains of one semantic concept, which queries samples that are most unlikely to be generated from current distribution. We then present a joint active learning method by adaptively combining the dis-criminative and the generative query strategies. This method dynamically adapts to the distribution differences and results a hybrid strategy that performs more robustly compared to either single strategy. We evaluate the proposed approaches in cross-domain semantic classification based on TRECVID corpora. The results show the effectiveness of our joint method.
PPARs in Liver Diseases and Cancer: Epigenetic Regulation by MicroRNAs

Peroxisome-proliferator-activated receptors (PPARs) are ligand-activated nuclear receptors that exert in the liver a transcriptional activity regulating a whole spectrum of physiological functions, including cholesterol and bile acid homeostasis, lipid/glucose metabolism, inflammatory responses, regenerative mechanisms, and cell differentiation/proliferation. Dysregulations of the expression, or activity, of specific PPAR isoforms in the liver are therefore believed to represent critical mechanisms contributing to the development of hepatic metabolic diseases, disorders induced by hepatic viral infections, and hepatocellular adenoma and carcinoma. In this regard, specific PPAR agonists have proven to be useful to treat these metabolic diseases, but for cancer therapies, the use of PPAR agonists is still debated. Interestingly, in addition to previously described mechanisms regulating PPARs expression and activity, microRNAs are emerging as new important regulators of PPAR expression and activity in pathophysiological conditions and therefore may represent future therapeutic targets to treat hepatic metabolic disorders and cancers. Here, we reviewed the current knowledge about the general roles of the different PPAR isoforms in common chronic metabolic and infectious liver diseases, as well as in the development of hepatic cancers. Recent works highlighting the regulation of PPARs by microRNAs in both physiological and pathological situations with a focus on the liver are also discussed.
How Software Developers Use Tagging to Support Reminding and Refinding

Developers frequently add annotations to source code to help them remember pertinent information and mark locations of interest for future investigation. Finding and refinding these notes is a form of navigation that is integral to software maintenance. Although there is some tool support in modern development environments for authoring and navigating these comments, we have observed that these annotations often fail to remind and are sometimes difficult to find by the programmer. To address these shortcomings, we have designed a new approach for software navigation called tags for software engineering activities (TagSEA). TagSEA combines the notion of waypointing (a mechanism for marking locations in spatial navigation) with social tagging to support programmers in defining semantically rich annotations to source code comments. The tool provides support for creating, editing, navigating, and managing these annotations. We present the results from two empirical studies, where we observed and then analyzed how professional programmers used source code annotations to support their development activities over 24 months. Our findings indicate that the addition of semantic information to annotations can improve their value. We also provide suggestions on how annotation tools in general may be improved.
Network Ties, Reputation, and the Financing of New Ventures

Explaining how entrepreneurs overcome information asymmetry between themselves and potential investors to obtain financing is an important issue for entrepreneurship research. Our premise is that economic explanations for venture finance, which do not consider how social ties influence this process, are undersocialized and incomplete. However, we also argue that organization theoretic arguments, which draw on the concept of social obligation, are oversocialized. Drawing on the organizational theory literature, and in-depth fieldwork with 50 high-technology ventures, we examine the effects of direct and indirect ties between entrepreneurs and 202 seed-stage investors on venture finance decisions. We show that these ties influence the selection of ventures to fund through a process of information transfer.
The empirics of agglomeration economies: the link with productivity

There is a large branch of literature providing empirical evidence on the positive effects of agglomeration economies on productivity. However, for policy makers it is important to understand the role of agglomeration economies at a more micro level, disentangling the effects across industries, firm-level characteristics and time. The present survey reviews this literature, outlining the econometric approaches and methodological challenges. In general, results show that the magnitude of agglomeration economies differ substantially across industries and point to the presence of non-linear effects, also depending on the industry and product life cycles. The channels through which these effects operate may also differ – resulting from specialization externalities (within industries in the same region) and/or urbanisation externalities (across industries in the same region). Overall, the evidence reviewed in this survey highlights the need for policy makers to follow tailor-made approaches and to complement existing evidence with national level studies, maximizing potential productivity gains.
Predicting Collision Detection with a Two-Layer Neural Network

—Fast and efﬁcient motion planning algorithms are critical for many state-of-the-art robotics applications, such as self-driving cars or rescue operations. Existing motion planning methods become less effective as the dimensionality of the robot and complexity of the workspace increases, e.g., the computational cost of collision detection routines increases. In this work, we present a framework to address the cost of expensive primitive operations in sampling-based motion planning. This framework determines the validity of a sample robot conﬁguration through a novel combination of a Con-tractive AutoEncoder (CAE), which captures a point cloud representation of the robot’s workspace, and a feed-forward neural network, which efﬁciently predicts the collision state of the robot from the CAE and the robot’s conﬁguration. We evaluate our framework on multiple planning problems with a variety of robotics in 2D and 3D workspaces. The results show that (1) the framework is computationally efﬁcient in all investigated problems, and (2) the framework generalizes well to previously un-encoded environments.
Arginase II Downregulates Nitric Oxide (NO) Production and Prevents NO-mediated Apoptosis in Murine Macrophage-derived RAW 264.7 Cells

Excess nitric oxide (NO) induces apoptosis of some cell types, including macrophages. As NO is synthesized by NO synthase (NOS) from arginine, a common substrate of arginase, these two enzymes compete for arginine. There are two known isoforms of arginase, types I and II. Using murine macrophage-like RAW 264.7 cells, we asked if the induction of arginase II would downregulate NO production and hence prevent apoptosis. When cells were exposed to lipopolysaccharide (LPS) and interferon-γ (IFN-γ), the inducible form of NOS (iNOS) was induced, production of NO was elevated, and apoptosis followed. When dexamethasone and cAMP were further added, both iNOS and arginase II were induced, NO production was much decreased, and apoptosis was prevented. When the cells were transfected with an arginase II expression plasmid and treated with LPS/IFN-γ, some cells were rescued from apoptosis. An arginase I expression plasmid was also effective. On the other hand, transfection with the arginase II plasmid did not prevent apoptosis when a NO donor SNAP or a high concentration (12 mM) of arginine was added. These results indicate that arginase II prevents NO-dependent apoptosis of RAW 264.7 cells by depleting intracellular arginine and by decreasing NO production.
Chaos , Solitons & Fractals Nonlinear Science , and Nonequilibrium and Complex Phenomena

Neutral evolutionary dynamics of replicators occurs on large and heterogeneous networks of genotypes. These networks, formed by all genotypes that yield the same phenotype, have a complex architecture that conditions the molecular composition of populations and their movements on genome spaces. Here we consider as an example the case of populations evolving on RNA secondary structure neutral networks and study the community structure of the network revealed through dynamical properties of the population at equilibrium and during adaptive transients. We unveil a rich hierarchical community structure that, eventually, can be traced back to the non-trivial relationship between RNA secondary structure and sequence composition. We demonstrate that usual measures of modularity that only take into account the static, topological structure of networks, cannot identify the community structure disclosed by population dynamics. 2014 Elsevier Ltd. All rights reserved.
Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes

AbstractIdentifying the spatio-temporal network structure of brain activity from multi-neuronal data streams is one ofthe biggest challenges in neuroscience. Repeating patterns of precisely timed activity across a group of neurons ispotentially indicative of a microcircuit in the underlying neural tissue. Frequent episode discovery, a temporal datamining framework, has recently been shown to be a computationally ecient method of counting the occurrences ofsuch patterns. In this paper, we propose a framework to determine when the counts are statistically signi cant bymodeling the counting process. Our model allows direct estimation of the strengths of functional connections be-tween neurons with improved resolution over previously published methods. It can also be used to rank the patternsdiscovered in a network of neurons according to their strengths and begin to reconstruct the graph structure of thenetwork that produced the spike data. We validate our methods on simulated data and present analysis of patternsdiscovered in data from cultures of cortical neurons.keywords: event sequences, spike trains, multi-electrode array, microcircuits, temporal data mining, frequentepisodes, non-overlapped occurrences, statistical inferences
Associations between work-related factors and specific disorders at the elbow: a systematic literature review.

OBJECTIVES To assess the exposure-response relationships between work-related physical and psychosocial factors and lateral epicondylitis, medial epicondylitis, cubital tunnel syndrome and radial tunnel syndrome in occupational populations. METHODS A systematic review of the literature was conducted on the associations between type of work, physical load and psychosocial aspects at work and the occurrence of specific elbow disorders. Associations between work factors and these elbow disorders were expressed in quantitative measures: odds ratio (OR) or relative risk (RR). RESULTS Handling tools >1 kg (ORs of 2.1-3.0), handling loads >20 kg at least 10 times/day (OR 2.6) and repetitive movements >2 h/day (ORs of 2.8-4.7) were associated with lateral epicondylitis. Psychosocial factors associated with lateral epicondylitis were low job control (OR 2.2) and low social support (OR 1.8). Handling loads >5 kg (2 times/min at minimum of 2 h/day), handling loads >20 kg at least 10 times/day, high hand grip forces for >1 h/day, repetitive movements for >2 h/day (ORs of 2.2-3.6) and working with vibrating tools >2 h/day (OR 2.2) were associated with medial epicondylitis. The occurrence of cubital tunnel syndrome was associated with the factor 'holding a tool in position' (OR 3.53). Handling loads >1 kg (OR 9.0; 95% CI 1.4, 56.9), static work of the hand during the majority of the cycle time (OR 5.9) and full extension (0-45 degrees ) of the elbow (OR 4.9) were associated with radial tunnel syndrome. CONCLUSIONS Several physical and psychosocial factors at work may result in an increased occurrence of specific disorders at the elbow.
A power-aware middleware for location & context aware mobile apps with cloud computing interaction

Nowadays mobile devices, represented mainly by smartphones, are used by million of people around the world. These smartphones include a large set of hardware capabilities and sensors which allow to improve the user interaction and content delivery. The sensors allow to gather extra information about the user situation and therefore to create location & context aware mobile apps. However, sensors usage involves energy consumption, which is also one of the smartphone's biggest limitations; in addition, these devices also have storage and memory constraints, and slow processors compared to a conventional computer. Recently, there is an emerging tendency consisting in lessen these limitations by implementing the complex computations and data storage in external entities such as cloud computing. This article presents the fundamentals for developing an energy-aware middleware for the support of context & location aware mobile apps with cloud computing interaction. This middleware can increase up to three times the smartphone battery performance when using the GPS receiver, and in the cloud can perform the extraction of places of interest from a list of GPS fixes uploaded by the smartphone.
A Regional Bio‐Economic Model of Nitrogen Use in Cropping

We develop a programming model of crop production to predict the effects of environmental policies on agriculture and the environment. The model is calibrated against acreages, yields, and exogenous supply elasticities following positive mathematical programming. In addition, crop production functions are calibrated to yield elasticities with respect to nitrogen and irrigation obtained from a biogeochemical model. We study the effects of a nitrogen tax in Yolo County, California, intended to mitigate nitrogen pollution from field crops. The behavioral and environmental responses to the tax are largely due to intensive margin adjustments. Sizable reductions in nitrate leaching are achieved at a low social cost.
Conditional XPath

XPath 1.0 is a variable free language designed to specify paths between nodes in XML documents. Such paths can alternatively be specified in first-order logic. The logical abstraction of XPath 1.0, usually called Navigational or Core XPath, is not powerful enough to express every first-order definable path. In this article, we show that there exists a natural expansion of Core XPath in which every first-order definable path in XML document trees is expressible. This expansion is called Conditional XPath. It contains additional axis relations of the form (child::n[F])+, denoting the transitive closure of the path expressed by child::n[F]. The difference with XPath's descendant::n[F] is that the path (child::n[F])+ is conditional on the fact that all nodes in between the start and end node of the path should also be labeled by n and should make the predicate F true. This result can be viewed as the XPath analogue of the expressive completeness of the relational algebra with respect to first-order logic.
Standards for Cooperative Intelligent Transportation Systems: a Proof of Concept

In recent years, a wide variety of stakeholders have been working for the development of Intelligent Transportation System solutions. Cooperation among the various actors of transportation (vehicles, but also pedestrians, roads and infrastructure, traffic control centers, etc.) is seen as promising to enhance the efficiency of transportation and reduce its negative impacts (e.g., fatalities). However, it means that all communicating entities have to talk the same language, hence the need for Cooperative Intelligent Transportation Systems standards. There are now lots of standards being produced by standardization organizations, e.g., International Standardization Organization (ISO) and European Telecommunications Standards Institute (ETSI) and there is a real need to understand how these standards can be implemented. This paper overviews the Intelligent Transportation System station reference architecture and presents a way of practical implementation of a toy Android application based on these standards as a proof of concept implementation. To our knowledge, this is the first implementation description compliant with these standards.
Principal Component and Neural Network Analyses of Face Images: Explorations into the Nature of Information Available for Classifying Faces by Sex

In this paper we present an overview of the major ndings of the principal component analysis (pca) approach to facial analysis. In a neural network or connectionist framework this approach is known as the linear autoassociator approach. Faces are represented as a weighted sum of macrofeatures (eigenvectors or eigenfaces) extracted from a cross-product matrix of face images. Using sex categorization as an illustration , we analyzed the robustness of this type of facial representation. We show that eigenvectors representing general categorical information can be estimated using a very small set of faces and that the information they convey is generalizable to new faces.
Optimized joystick control interface for electric powered wheelchairs

The main goal of this work is to develop a new smart joystick for electric wheelchair which provides an efficient and safe service for people with severe physical disabilities. These handicaps have difficulty to use the standard joystick because of their various levels of tremors. Based on neural networks, the new created joystick has good performances than the traditional one. These performances have been exposed by different experimental results.
Complexities of Assessing the Disease Burden Attributable to Leishmaniasis

Among parasitic diseases, morbidity and mortality caused by leishmaniasis are surpassed only by malaria and lymphatic filariasis. However, estimation of the leishmaniasis disease burden is challenging, due to clinical and epidemiological diversity, marked geographic clustering, and lack of reliable data on incidence, duration, and impact of the various disease syndromes. Non-health effects such as impoverishment, disfigurement, and stigma add to the burden, and introduce further complexities. Leishmaniasis occurs globally, but has disproportionate impact in the Horn of Africa, South Asia and Brazil (for visceral leishmaniasis), and Latin America, Central Asia, and southwestern Asia (for cutaneous leishmaniasis). Disease characteristics and challenges for control are reviewed for each of these foci. We recommend review of reliable secondary data sources and collection of baseline active survey data to improve current disease burden estimates, plus the improvement or establishment of effective surveillance systems to monitor the impact of control efforts.
The functional relationship of the interleukins

The mechanism of the lymphoproliferative effect of the macrophage product lymphocyte-activating factor [LAF(IL1] appears to be mediated by the stimulation of the release of T cell growth factor [TCGF(IL2)] by T cells. The magnitude of the resultant T cell proliferative clonal expansion is thus dependent upon the quantity of both LAF(IL1) and TCGF(IL2) induced by antigen or lectin stimulation. These observations, coupled with the ability to measure the production and actions of these hormone-like lymphokines, should allow for increased insight into the mode of action of immunoenhancing and immunosuppressive agents, as well as for new therapeutic approaches to disease states involving T lymphocytes.
Musicsim: integrating audio analysis and user feedback in an interactive music browsing ui

In music information retrieval (MIR), there are two main research directions, which are based either on a folder hierarchy and metadata, or on the actual acoustic content. We believe that both content-based and hierarchy-based retrieval have their respective strengths for browsing and organizing music collections, and that the integration of content analysis techniques in metadata-based media UIs can lead to more powerful UIs. In this paper we present a prototype, in which audio analysis techniques and user feedback are integrated into an interactive UI for browsing and organizing large music collections. We also provide visual assistance to support non-visual perception of music. We discussed our system with test users and received encouragement as well as valuable suggestions for future re-search.
Neuronal cell lineage in the vertebrate central nervous system

Fundamental, yet unresolved, issues in developmental neurobiology concern the relative influence of genetic vs. epigenetic factors in determining cell phenotype and establishing positional relationships among clonally related cells in the developing and mature vertebrate central nervous system (CNS). Advances in our understanding of how cells acquire their identity awaited a means to introduce lineage tracers into dividing cells of the developing CNS where the progenitor cells, which are situated in a neuroepithelial layer adjacent to the ventricles, generally are small and inaccessible. The technique of retroviral‐mediated gene transfer, whereby a heritable, easily detectable marker such as the gene for lacZ is integrated into the DNA of individual progenitor cells, has been used to analyze the lineage relationships of cells in the CNS and to derive the types of progenitor cells in the proliferative zones at different developmental stages. Collectively, these studies indicate that the CNS uses more than one strategy to achieve cell diversity. The analysis of the phenotypic composition of the cells within a clone indicates that there are predominantly separate progenitor cells for each of the main cell types comprising the cerebral cortex by the onset of cortical neurogenesis, although in other systems mostly multipotential progenitor cells persist throughout neurogenesis. Here I will compare and contrast the inferred role of cell lineage in the developing cerebral cortex and olfactory bulb, where postmitotic neurons migrate relatively long distances from their site of generation to their final destination, with that in other regions of the CNS in which the displacement of postmitotic neurons from their birthplace is significantly less. — Luskin, M. B. Neuronal cell lineage in the vertebrate central nervous system. FASEB J. 8: 722‐730; 1994.