Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Deep Transfer Learning by Basic Probability Assignment

Transfer learning is a popular practice in deep neural networks, but fine-tuning of large number of parameters is a hard task due to the complex wiring of neurons between splitting layers and imbalance distributions of data in pretrained and transferred domains. The reconstruction of the original wiring for the target domain is a heavy burden due to the size of interconnections across neurons. We propose a distributed scheme that tunes the convolutional filters individually while backpropagates them jointly by means of basic probability assignment. Some of the most recent advances in evidence theory show that in a vast variety of the imbalanced regimes, optimizing of some proper objective functions derived from contingency matrices prevents biases towards high-prior class distributions. Therefore, the original filters get gradually transferred based on individual contributions to overall performance of the target domain. This largely reduces the expected complexity of transfer learning whilst highly improves precision. Our experiments on standard benchmarks and scenarios confirm the consistent improvement of our distributed deep transfer learning strategy.
Hierarchical Reasoning in Probabilistic CSP

Probabilistic CSP extends the language of CSP with an operator for probabilistic choice. However reasoning about an intricate combination of nondeterminism, communication and probabilistic behaviour can be complicated. In standard CSP, and in formal methods generally, such complication is overcome (when possible) by use of hierarchical reasoning. In this paper we provide a foundation for lifting such reasoning to the probabilistic setting. First we formalise the common observation that the standard models of CSP (traces, refusals and refusals/divergences) form a hierarchy, by showing that they are linked by embedding-projection pairs. Such structure underlies hierarchical reasoning in which complex process behaviour is reasoned about in terms of its simpler projections. Then we show how that hierarchy can be extended to a corresponding hierarchy between the probabilistic models, by using each of those three models of standard CSP as a basis for a probabilistic extension. Finally we show that there is a projection from the probabilistic models onto the standard models, which can be used to reason about nonprobabilistic properties of probabilistic processes.
Object-aware bundle adjustment for correcting monocular scale drift

Without knowledge of the absolute baseline between images, the scale of a map from single-camera simultaneous localization and mapping system is subject to calamitous drift over time. We describe a monocular approach that in addition to point measurements also considers object detections to resolve this scale ambiguity and drift. By placing a prior on the size of the objects, the scale estimation can be seamlessly integrated into a bundle adjustment. When object observations are available, the local scale of the map is then determined jointly with the camera pose in local adjustments. Unlike many previous visual odometry methods, our approach does not impose restrictions such as approximately constant camera height or planar roadways, and is therefore applicable to a much wider range of applications. We evaluate our approach on the KITTI dataset and show that it reduces scale drift over long-range outdoor sequences with a total length of 40 km. Qualitative evaluation is also performed on video footage from a hand-held camera.
Topological network alignment uncovers biological function and phylogeny

Sequence comparison and alignment has had an enormous impact on our understanding of evolution, biology and disease. Comparison and alignment of biological networks will probably have a similar impact. Existing network alignments use information external to the networks, such as sequence, because no good algorithm for purely topological alignment has yet been devised. In this paper, we present a novel algorithm based solely on network topology, that can be used to align any two networks. We apply it to biological networks to produce by far the most complete topological alignments of biological networks to date. We demonstrate that both species phylogeny and detailed biological function of individual proteins can be extracted from our alignments. Topology-based alignments have the potential to provide a completely new, independent source of phylogenetic information. Our alignment of the protein–protein interaction networks of two very different species—yeast and human—indicate that even distant species share a surprising amount of network topology, suggesting broad similarities in internal cellular wiring across all life on Earth.
In-Capture Mobile Video Distortions: A Study of Subjective Behavior and Objective Algorithms

Digital videos often contain visual distortions that are introduced by the camera’s hardware or processing software during the capture process. These distortions often detract from a viewer’s quality of experience. Understanding how human observers perceive the visual quality of digital videos is of great importance to camera designers. Thus, the development of automatic objective methods that accurately quantify the impact of visual distortions on perception has greatly accelerated. Video quality algorithm design and verification require realistic databases of distorted videos and human judgments of them. However, most current publicly available video quality databases have been created under highly controlled conditions using graded, simulated, and post-capture distortions (such as jitter and compression artifacts) on high-quality videos. The commercial plethora of hand-held mobile video capture devices produces videos often afflicted by a variety of complex distortions generated during the capturing process. These in-capture distortions are not well-modeled by the synthetic, post-capture distortions found in existing VQA databases. Toward overcoming this limitation, we designed and created a new database that we call the LIVE-Qualcomm mobile in-capture video quality database, comprising a total of 208 videos, which model six common in-capture distortions. We also conducted a subjective quality assessment study using this database, in which each video was assessed by 39 unique subjects. Furthermore, we evaluated several top-performing no-reference IQA and VQA algorithms on the new database and studied how real-world in-capture distortions challenge both human viewers as well as automatic perceptual quality prediction models. The new database is freely available at: http://live.ece. utexas.edu/research/incaptureDatabase/index.html.
Nur, a nickel‐responsive regulator of the Fur family, regulates superoxide dismutases and nickel transport in Streptomyces coelicolor

Nickel serves as a cofactor for various microbial enzymes including superoxide dismutase (SOD) found in Streptomyces spp. In Streptomyces coelicolor, nickel represses and induces production of Fe‐containing and Ni‐containing SODs, respectively, primarily at the transcriptional level. We identified the nickel‐responsive regulator (Nur), a Fur (ferric‐uptake regulator) homologue, which binds to the promoter region of the sodF gene encoding FeSOD in the presence of nickel. Disruption of the nur gene caused constitutive expression of FeSOD and no induction of NiSOD in the presence of nickel. The intracellular level of nickel was higher in a Δnur mutant than in the wild type, suggesting that Nur also regulates nickel uptake in S. coelicolor. A putative nickel‐transporter gene cluster (nikABCDE) was identified in the genome database. Its transcription was negatively regulated by Nur in the presence of nickel. Purified Nur protein bound to the nikA promoter region in a nickel‐dependent way. These results support the action of Nur as a regulator of nickel homeostasis and antioxidative response in S. coelicolor, and add a novel nickel‐responsive member to the list of versatile metal‐specific regulators of the Fur family.
Endothelin receptor antagonists for pulmonary arterial hypertension.

BACKGROUND Pulmonary arterial hypertension (PAH) is a devastating disease, which leads to right heart failure and premature death. Pulmonary arterial hypertension can be classified into two categories: 1) sporadic primary pulmonary hypertension (PPH) or familial PPH and 2) PAH secondary to collagen vascular diseases, congenital systemic to pulmonary shunts, portal hypertension, HIV infection, drugs or toxins, and persistent pulmonary hypertension of the newborn. They have identical pathologic features, a similar clinical course. Endothelin receptor antagonists (ERAs) are a class of potent vasodilators, which could specifically dilate the pulmonary arterial system. OBJECTIVES To evaluate the efficacy of endothelin receptor antagonists in pulmonary arterial hypertension. SEARCH STRATEGY A search was carried out using the CENTRAL (Cochrane Central Register of Controlled Trials), MEDLINE, EMBASE, and the reference section of retrieved articles. Searches are current as of August 2004. SELECTION CRITERIA Randomised controlled trials (RCTs) or quasi-randomised controlled trials involving patients with pulmonary arterial hypertension (PAH) were selected by two reviewers. DATA COLLECTION AND ANALYSIS Two reviewers independently selected studies; assessed study quality; and extracted data. We analysed outcomes as continuous and dichotomous data. MAIN RESULTS We identified three RCTs of short duration (12-16 weeks), recruiting a total of 423 participants. Two studies compared a non-selective ERA (bosentan) with placebo and one compared a selective ERA (sitaxsentan) with placebo. Over a 12-16 week period ERAs improved exercise capacity, improve Borg dyspnoea score, some measures of cardiopulmonary haemodynamics (pulmonary artery pressure, pulmonary vascular resistance, and cardiac index) in symptomatic patients with PAH. The most severe side effect, hepatic toxicity, was not common. AUTHORS' CONCLUSIONS ERAs in conjunction with conventional therapy over 16 weeks can improve exercise capacity, Borg dyspnoea scores and several cardiopulmonary haemodynamics variables in PAH patients. Longer studies are required.
Comparative ecological transcriptomics and the contribution of gene expression to the evolutionary potential of a threatened fish

Understanding whether small populations with low genetic diversity can respond to rapid environmental change via phenotypic plasticity is an outstanding research question in biology. RNA sequencing (RNA‐seq) has recently provided the opportunity to examine variation in gene expression, a surrogate for phenotypic variation, in nonmodel species. We used a comparative RNA‐seq approach to assess expression variation within and among adaptively divergent populations of a threatened freshwater fish, Nannoperca australis, found across a steep hydroclimatic gradient in the Murray–Darling Basin, Australia. These populations evolved under contrasting selective environments (e.g., dry/hot lowland; wet/cold upland) and represent opposite ends of the species’ spectrum of genetic diversity and population size. We tested the hypothesis that environmental variation among isolated populations has driven the evolution of divergent expression at ecologically important genes using differential expression (DE) analysis and an anova‐based comparative phylogenetic expression variance and evolution model framework based on 27,425 de novo assembled transcripts. Additionally, we tested whether gene expression variance within populations was correlated with levels of standing genetic diversity. We identified 290 DE candidate transcripts, 33 transcripts with evidence for high expression plasticity, and 50 candidates for divergent selection on gene expression after accounting for phylogenetic structure. Variance in gene expression appeared unrelated to levels of genetic diversity. Functional annotation of the candidate transcripts revealed that variation in water quality is an important factor influencing expression variation for N. australis. Our findings suggest that gene expression variation can contribute to the evolutionary potential of small populations.
Ferroelectric Polymer Nanotubes with Large Dielectric Constants for Potential All‐Organic Electronic Devices

To fabricate ferroelectric ultrathin polymer films with large dielectric constants for potential all-organic electronic devices, ferroelectric polymer nanotubes and a composite of the nanotubes with a dispersed organic semiconductor have been fabricated by template-assisted methods. The ferroelectricity drops markedly in spin-coated ultrathin films less than 100 nm thick, whereas P(VDF-TrFE) nanotubes with a wall thickness of a few ten nm sustain ferroelectricity. The composite nanotubes exhibit a giant dielectric constant as a result of significantly enhanced interface polarization between the nanosized fillers and the polymer matrix. They could be of practical use in supercapacitors, optoelectronic devices, and sensors.
The Alpine file system

Alpine is a file system that supports atomic transactions and is designed to operate as a service on a computer network. Alpine's primary purpose is to store files that represent databases. An important secondary goal is to store ordinary files representing documents, program modules, and the like. Unlike other file servers described in the literature, Alpine uses a log-based technique to implement atomic file update. Another unusual aspect of Alpine is that it performs all communication via a general-purpose remote procedure call facility. Both of these decisions have worked out well. This paper describes Alpine's design and implementation, and evaluates the system in light of our experience to date. Alpine is written in Cedar, a strongly typed modular programming language that includes garbage-collected storage. We report on using the Cedar language and programming environment to develop Alpine.
Estimating friction using incipient slip sensing during a manipulation task

A scheme is presented by which a manipulator can use dynamic tactile sensing to detect when it is about to lose hold of a grasped object. By detecting localized slips on the gripping surface which precede gross slip, the controller can modify the grasp force to prevent the object from slipping. Also, by monitoring normal and tangential forces at the contact when these incipient slip signals occur, the controller obtains an accurate estimate of the friction coefficient which can then be used during the manipulation task. Accurate knowledge of the friction coefficient is essential when grasping fragile objects or manipulating with sliding. <<ETX>>
SECURITY SOLUTIONS BY DETECTING FRAUDULENT USAGE IN WIRELESS NETWORKS

Security research in to wired networks indicates that there are always some weak points in the systems that are hard to predict. This is particularly true for a wireless network, in which open wireless transmission media and low physical-security protection of mobile devices pose additional challenges for prevention-based approaches and detection-based approaches. Sensor network security mechanisms can be divided into two categories: communication protocols and key management architectures. Communication protocols deal with the cryptographic algorithms used to achieve availability, confidentiality, integrity, and authentication. Key management architectures handle the complexities of creating and distributing keys used by communication protocols. In this we explore Taxonomy of security solutions, Taxonomy of key distributing schemes, Detecting Computer and Network Misuse, Monitoring misuse through expert systems, Anomaly-based Intrusion Detection Using Mobility Profiles of Public Transportation Users, How to Increase Security in Mobile Networks by Anomaly Detection, The Baye’s Decision Rule.
Is it time for a new approach in cardiovascular risk assessment

Prospective epidemiologic studies have established risk factors for atherosclerotic cardiovascular diseases, including: advanced age, smoking, obesity, diabetes or glucose intolerance, elevated blood lipids, hypertension and sedentary life habits. Many of these factors are closely related to modern lifestyles and can be modified. They have been used for the risk estimation and the planning of preventive measures (1, 2).
Using Continuous Queries for Event Filtering and Routing in Sparse MANETs

In our project, we design middleware services for emergency and rescue scenarios in sparse mobile ad-hoc networks (SMANETs). One of these services is a distributed event notification service (DENS) for asynchronous communication. The DENS architecture allows several subscription languages for different kinds of subscriptions. To support complex subscriptions, we use a data stream management system (DSMS) for filtering of the data streams and matching of filtered events and subscriptions. We have designed a simple rescue scenario to investigate the possibilities of using a DSMS together with the DENS middleware layer. In this paper we discuss the design of our implementation and first experimental results of our ongoing work
Endogenous Rational Bubbles

Tests on simulated data from an asset pricing model with heterogeneous forecasts show excess variance in the price and ARCH effects in the returns, features not explained by the strong version of the efficient markets hypothesis. An evolutionary game theory dynamic describes how agents switch between a fundamental forecast, a rational bubble forecast and the reflective forecast, which is a weighted average of the former two. Conditions determining the frequency and duration of episodes where a significant fraction of agents adopt the rational bubble forecast leading to large deviations in the price-dividend ratio are discussed.
Mixture-based bone segmentation and its application in computer aided diagnosis and treatment planning

The developmental dysplasia of the hip (DDH) is a congenital malformation of the acetabulum with different degrees. Leaving it partially treated or untreated is a major cause of disability. In this paper, we implemented a computer-aided system for the diagnosis and treatment planning of DDH. Instead of labeling each voxel with a unique label or tissue type, the percentage of different tissues within each voxel, which we call a mixture, was considered in establishing a maximum a posterior probability (MAP) framework for more accurate segmentation. A graphical module displayed the segmented bone in a 3D view to show the spatial relationship between acetabulum and femurs. This virtual image, together with quantitative measurement indexes, helps physicians make diagnosis. The system also provides physicians a virtual treatment planning on screen for acetabular and femoral osteotomy. It is currently under clinical trial on patient datasets.
An Interactive Two-Dimensional Approach to Query Aspects Rewriting in Systematic Reviews. IMS Unipd At CLEF eHealth Task 2

In this paper, we describe the participation of the Information Management Systems (IMS) group at CLEF eHealth 2017 Task 2. This task focuses on the problem of systematic reviews, that is articles that summarise all evidence that is published regarding a certain medical topic. This task, known in Information Retrieval as the total recall problem, requires long and tedious search sessions by experts in the field of medicine. Automatic (or semi-automatic) approaches are essential to support these type of searches when the amount of data exceed the limits of users, i.e. in terms of attention or patience. We present the two-dimensional probabilistic version of BM25 with explicit relevance feedback together with a query aspect rewriting approach for both the simple evaluation and the cost-effective evaluation.
Learning Activity Patterns Performed With Emotion

This paper is a preliminary work towards the design of a model able to generate realistic motion sequences conditioned on a number of contextual variables like age, morphology, emotion etc. We focus in a first step on the design of contextual markovian models able to perform recognition of activities performed under various emotions even in the case no training samples are available for a particular (activity, emotion) pair, a zero shot learning setting.
Reordering rules for English-Hindi SMT

Reordering is pre-processing stage for Statistical Machine Translation (SMT) system where the words of the source sentence are reordered as per the syntax of the target language. We are proposing a rich set of rules for better reordering. The idea is to facilitate the training process by better alignments and parallel phrase extraction for a phrase based SMT system. Reordering also helps the decoding process and hence improving the machine translation quality. We have observed significant improvements in the translation quality by using our approach over the baseline SMT. We have used BLEU, NIST, multi-reference word error rate, multi-reference position independent error rate for judging the improvements. We have exploited open source SMT toolkit MOSES to develop the system.
A generic off-line approach for dealing with uncertainty in production systems optimisation

This paper addresses production systems optimisation in uncertain context. A standard framework for solving such type of problems is depicted in a 3-step approach. The two first steps are addressed in this paper. They consist of off-line characterisation of the problem and calculation of solutions with some desired performance. A generic approach to implement these off-line steps is introduced in this paper. This approach relies on calculation of robust off-line solutions. A generic framework of robustness is defined. Then five standard optimisation problems are derived and related to the so called stability and sensitivity analysis. This generic approach is then applied to a multi-purpose machines problem.