Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and evaluation of SURF descriptors for automatic 3D facial expression recognition using different classifiers

Emotion recognition plays a vital role in the field of Human-Computer Interaction (HCI). Among the visual human emotional cues, facial expressions are the most commonly used and understandable cues. Different machine learning techniques have been utilized to solve the expression recognition problem; however, their performance is still disputed. In this paper, we investigate the capability of several classification techniques to discriminate between the six universal facial expressions using Speed Up Robust Features (SURF). The evaluation were conducted using the BU-3DFE database with four classifiers, namely, Support Vector machine (SVM), Neural Network (NN), k-Nearest Neighbors (k-NN), and Naïve Bayes (NB). Experimental results show that the SVM was successful in discriminating between the six universal facial expressions with an overall recognition accuracy of 79.36%, which is significantly better than the nearest accuracy achieved by Naïve Bayes at significance level p <; 0.05.
Role of the Distal sarA Promoters in SarA Expression in Staphylococcus aureus

ABSTRACT The global regulatory locus sarA comprises a 375-bp open reading frame that is driven by three promoters, the proximal P1 and distal P3 and P2 promoters. We mutated the weaker P3 and P2 promoters to ascertain the effect of the change on SarA protein and target gene expression. Our results indicated that the solely active P1 promoter led to a lower SarA protein level, which has an effect on agr transcription and subsequently had corresponding effects on hla, sspA, and spa transcription, probably in both agr-independent and agr-dependent manners.
Selection Strategy of In Vivo Models for Ophthalmic Drug Development in Diabetic Retinopathy

Diabetic Retinopathy (DR) is the most common microvascular complication of diabetes and is one of the leading causes of visual impairment worldwide. DR is a chronic eye disease that eventually can result in legal blindness due to the evolution towards the major vision-threatening disorders diabetic macular edema (DME) and/or proliferative diabetic retinopathy (PDR). Current treatments with steroids, anti-VEGF compounds or retinal laser photocoagulation have shown a significant improvement in visual acuity in the advanced stage of the disease. However, main concerns are possible side effects and/or the relatively large number of clinical non-responders. A better understanding of the biological and molecular pathways not only in DR patients but also in the preclinical in vivo models would aid the development of novel and more efficient (personalized) therapeutic approaches for DR. This review aims to describe the pathways in a selection of diabetic, non-diabetic and surrogate rodent models of pathogenic neovascularization, vascular permeability, inflammation and neurodegeneration. None of these models can mimic the entire human pathophysiological progression but they all exhibit joint pathophysiological features with human DR pathogenesis. These combined features make these models very relevant in gaining a better understanding of the disease etiology and eventually improved strategies for drug screening. Through highlighting the most important biochemical and molecular pathways that these animal models have in common with DR patients, selection of the most suitable model for mechanistic studies and drug screening can be facilitated.
Citation for Published Item

'Dependence of domain-wall depinning threshold current on pinning prole. ', Physical review letters. , 102 (12). p. 127203. Use policy The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. Please consult the full DRO policy for further details.
Dictionary learning based multitask image restoration

In recent years, there have been increased interests in the study of dictionary learning (DL). Learned dictionaries lead to state-of-the-art results in image processing. Hence, many new DL methods were presented. This paper proposes a novel DL model and an algorithm to solve this model. We call the proposed algorithm problem-guided dictionary learning (PG-DL). PG-DL can deal with many problems in image processing. Taking noised image inpainting and removing mixed noise as examples, the experiments show that the PG-DL can describe the image content effectively and leads to valid performance.
Policy Targeting with Model-Consistent Expectations

Studies of inflation targeting make the distinction between strict and flexible inflation targeting. The problem of strict inflation targeting has so far been analysed by treating it as a special case of a standard optimal control problem and the algorithms used have not provided an exact solution. This paper presents a formal solution to the problem of strict inflation targeting in a economy with a forward-looking variable. It explains how the results can be applied with more than one forward-looking variable. It also draws on relevant control theory results. The results are illustrated on a small macro-economic model. It is shown that the use of a solution method which exploits the existence of a forward-looking variable delivers a solution which would not be easy to find by standard control methods.
Financial Analysis Extends Management of R&D

OVERVIEW: Research, development and acquisition (RDA) investments are susceptible to strategic financial analyses. RDA can be thought of as parts of a portfolio in which preserving some research will increase return per unit of risk. Specific optimum proportions of research versus development are calculated for realistic parameter values. In addition, the best mix of RDA is sensitive to changes in the cost of capital, as illustrated by U.S. Navy RDA expenditures over the past two decades. Finally, real options implicit in RDA are made explicit so that the value of options can be considered when making RDA decisions. Corporate financial analysis provides a framework for strategic RDA decisions.
Performance Analysis of OSTBC Over Keyhole Fading Channels

In this paper, we first analyze the amount of fading (AF) of orthogonal space-time block codes (STBCs) over spatially uncorrelated keyhole channels. In order to investigate the diversity order of keyhole channels, we then derive an approximate expression for the average bit error rate (BER) at high signal-to-noise ratio (SNR). Finally we present the average capacity expression by applying the Gauss-Laguerre integration.
Coherent Stylized Lines for Mesh Surfaces by Contour Triangles

This paper presents a method to render smooth stylized contours of 3D meshes with temporal coherence. Contour triangles that contain countour curves perform two functions: they ensure that smooth contour curves are coherent and reconstructed faithfully during the motion of the viewpoint and they help to establish the corresponding relationship of contours which can propagate parameters on contours between frames against sliding effects. Our method can also deal with zig-zags and short segments for coarse meshes and nonuniform sampling meshes in a wide range of styles very well.
5G Software Defined Vehicular Networks

With the emergence of 5G mobile communication systems and software defined networks, not only could the performance of vehicular networks be improved, but also new applications of vehicular networks are required by future vehicles (e.g., pilotless vehicles). To meet requirements of intelligent transportation systems, a new vehicular network architecture integrated with 5G mobile communication technologies and software defined networking is proposed in this article. Moreover, fog cells have been proposed to flexibly cover vehicles and avoid frequent handover between vehicles and roadside units. Based on the proposed 5G software defined vehicular networks, the transmission delay and throughput are analyzed and compared. Simulation results indicate that there is a minimum transmission delay of 5G software defined vehicular networks considering different vehicle densities. Moreover, the throughput of fog cells in 5G software defined vehicular networks is better than the throughput of traditional transportation management systems.
Simplified Models of Evolution Lead to Improved Prediction of Functional Linkage from Correlated Gain and Loss of Genes among Eukaryotes

We have improved the accuracy of predictions of functional linkage from whole genomic gene content [1] by seeking not correlated presence and absence of genes, but rather correlated gains and losses of those genes on branches of a phylogenetic tree of species [2]. This may be modelled within a maximum likelihood (ML) framework [2,3]. As originally applied to gene content [2], this method involves estimation of rates of gene gain as well as rates of gene loss. We here simplify the ML models, by not estimating the initial rates of gain of genes but fixing them to constant, low values. The motivation for this novel approach is to better model gene content evolution, by preventing the modelling of multiple gains of the same gene in different parts of the phylogeny. A suitable low rate of gene gain is estimated using an initial training step with a grid search for the optimal rate, judged by specificity and sensitivity of predictions according to known test data. We compare our new method with the ML method of [2], the across-species method [1] and a method seeking correlated gain and loss of genes based on Dollo Parsimony. Dollo parsimony [4] provides a rapid, non-statistical method of reconstructing ancestral states on a phylogenetic tree. It allows zero or one gains of a trait, but any number of losses subject to the constraint that the total number of changes on the phylogenetic tree is minimized. The implied assumptions seem suitable for reconstructing gene content evolution in eukaryotes and it has been used for this purpose [5]. Using 21 species of fungi and animals, we test each method on large positive and negative test data derived from known protein complexes [6]. We compare the quality of methods according to sensitivity and specificity. We find that all three phylogenetic methods (using ML models or Dollo parsimony) give higher quality predictions than the across-species method. The ML approach with rates of gene gain constrained to a low value gives by far the best results. The specific value used for rates of gain is not critical, and values of half or double the optimum for the study are found to give results of almost equal quality. Thus the novel version of the ML phylogenetic method, using simpler ML models of gene gain/loss, will be able to give high quality predictions of functional linkage even for studies of species for which little training data is available.
Dissociated sequential activity and stimulus encoding in the dorsomedial striatum during spatial working memory

Several lines of evidence suggest that the striatum has an important role in spatial working memory. The neural dynamics in the striatum have been described in tasks with short delay periods (1–4 s), but remain largely uncharacterized for tasks with longer delay periods. We collected and analyzed single unit recordings from the dorsomedial striatum of rats performing a spatial working memory task with delays up to 10 s. We found that neurons were activated sequentially, with the sequences spanning the entire delay period. Surprisingly, this sequential activity was dissociated from stimulus encoding activity, which was present in the same neurons, but preferentially appeared towards the onset of the delay period. These observations contrast with descriptions of sequential dynamics during similar tasks in other brains areas, and clarify the contribution of the striatum to spatial working memory. DOI: http://dx.doi. org/10.7554/eLife.19507. 001
Interactions between the atmosphere and terrestrial ecosystems : influence on weather and climate

This paper overviews the short-term (biophysical) and long-term (out to around 100 year timescales; biogeochemical and biogeographical) influences of the land surface on weather and climate. From our review of the literature, the evidence is convincing that terrestrial ecosystem dynamics on these timescales significantly influence atmospheric processes. In studies of past and possible future climate change, terrestrial ecosystem dynamics are as important as changes in atmospheric dynamics and composition, ocean circulation, ice sheet extent, and orbit perturbations.
Policies Bearing on Product Market Competition and Growth in Europe

The strength of product market competition plays an important role in economic growth as it affects economic efficiency and the allocation of resources, and can also lead to improved labour market performance. This paper examines product market competition and economic performance in the European Union. The Community’s competition rules, which apply whenever anti-competitive practices have an implication for cross-border trade, are enforced primarily by the Commission’s Directorate General for Competition, and complement national competition legislation. Reforms have been adopted recently to sharpen the toolkit and to increase the role of national authorities in the enforcement process. However, the toolkit could still be made more effective. Competition policy is complemented by, and partly overlapping with, the regulation of newly liberalised network industries. Despite the EU’s commendable efforts in this area, competition is still undermined by dominant incumbents in some . Politiques pour la concurrence et la croissance sur les marches de produits en Europe La vigueur de la concurrence sur les marches de produits joue un role important dans la croissance economique, influence l’efficience economique et l’allocation des ressources, et peut aussi induire de meilleurs resultats sur le marche du travail. Cette etude examine la concurrence sur les marches de produits et la performance economique dans l’Union Europeenne. Les regles de concurrence communautaires, qui s’appliquent chaque fois que des pratiques anticoncurrentielles ont une incidence sur les echanges transfrontieres, sont mises en œuvre principalement par la Direction generale de la concurrence de la Commission et viennent completer le droit national de la concurrence. Des reformes ont ete adoptees recemment pour affiner le dispositif et renforcer le role des autorites nationales dans le processus d’application. Toutefois, l’efficacite des instruments en place pourrait etre encore amelioree. La reglementation des industries de reseau recemment liberalisees complete la .
siRNA Efficiency: Structure or Sequence—That Is the Question

The triumphant success of RNA interference (RNAi) in life sciences is based on its high potency to silence genes in a sequence-specific manner. Nevertheless, the first task for successful RNAi approaches is the identification of highly active small interfering RNAs (siRNAs). Early on, it has been found that the potency of siRNAs can vary drastically. Great progress was made when thermodynamic properties that influence siRNA activity were discovered. Design algorithms based on these parameters enhance the chance to generate potent siRNAs. Still, many siRNAs designed accordingly fail to silence their targeted gene, whereas others are highly efficient despite the fact that they do not fulfil the recommended criteria. Therefore, the accessibility of the siRNA-binding site on the target RNA has been investigated as an additional parameter which is important for RNAi-mediated silencing. These and other factors which are crucial for successful RNAi approaches will be discussed in the present review.
The Open University ’ s repository of research publications and other research outputs Automatic Feature Set Selection for Merging Image

The image segmentation performance of clustering algorithms is highly dependent on the features used and the type of objects contained in the image, which limits the generalization ability of such algorithms. As a consequence, a fuzzy image segmentation using suppressed fuzzy c-means clustering (FSSC) algorithm was proposed that merged the initially segmented regions produced by a fuzzy clustering algorithm, using two different feature sets each comprising two features from pixel location, pixel intensity and a combination of both, which considered objects with similar surface variations (SSV), the arbitrariness of fuzzy c-means (FCM) algorithm using pixel location and the connectedness property of objects. The feature set selection for the initial segmentation in the merging technique was however, inaccurate because it did not consider all possible feature set combinations and also manually defined the threshold used to identify objects having SSV. To overcome these limitations, a new automatic feature set selection for merging image segmentation results using fuzzy clustering (AFMSF) algorithm is proposed, which considers the best feature set selection and also calculates the threshold based upon human visual perception. Both qualitative and quantitative analysis prove the superiority of AFMSF algorithm compared with other clustering techniques including FSSC, FCM, possibilistic c-means (PCM) and SFCM, for different image types. Keyword: Image Segmentation, Connectedness.
Query Replication in Distributed Information Systems with Autonomous Participants

We consider Distributed Information Systems with Autonomous Participants (DISAP), i.e., participants (consumers and providers) may have special interests towards queries and other participants. Recent applications of DISAP on the Internet have emerged to share data, services, or computing resources at an unprecedented scale (e.g. SETI@home). With autonomous participants, the only way to avoid a participant to voluntarily leave the system is to satisfy its interests when allocating queries. But, participants' satisfaction may also be badly affected by other participants' failures or comportment. In this context, replicating queries is useful to address two different problems: tolerate providers' failures and deal with Byzantine providers. In this paper, we make the following main contributions. First, we formalize the query allocation problem over faulty participants in the context of DISAP. Second, we deﬁne participant's satisfaction and deﬁne a notion of global satisfaction, which considers participants' satisfaction and their probability of failure. Third, we propose a query replication algorithm, SbQR, which deals with the participants' failures by deciding on-line whether a query should be replicated and at which rate. Fourth, we propose another query replication algorithm, called SbQR+, which generalizes SbQR with the goal of prioritizing critical queries. Finally, we implemented both algorithms and compared them to the popular baseline algorithm. The results demonstrate that our algorithms signiﬁcantly outperform the baseline algorithm from the performance and satisfaction points of view. In particular, Sb QR+ is excellent at choosing the queries that must be replicated to guarantee both participants' satisfaction and good system performance.
Characterization of the Skin Microbiota in Italian Stream Frogs (Rana italica) Infected and Uninfected by a Cutaneous Parasitic Disease

In human and wildlife populations, the natural microbiota plays an important role in health maintenance and the prevention of emerging infectious diseases. In amphibians, infectious diseases have been closely associated with population decline and extinction worldwide. Skin symbiont communities have been suggested as one of the factors driving the different susceptibilities of amphibians to diseases. The activity of the skin microbiota of amphibians against fungal pathogens, such as Batrachochytrium dendrobatidis, has been examined extensively, whereas its protective role towards the cutaneous infectious diseases caused by Amphibiocystidium parasites has not yet been elucidated in detail. In the present study, we investigated, for the first time, the cutaneous microbiota of the Italian stream frog (Rana italica) and characterized the microbial assemblages of frogs uninfected and infected by Amphibiocystidium using the Illumina next-generation sequencing of 16S rRNA gene fragments. A total of 629 different OTUs belonging to 16 different phyla were detected. Bacterial populations shared by all individuals represented only one fifth of all OTUs and were dominated by a small number of OTUs. Statistical analyses based on Bray-Curtis distances showed that uninfected and infected specimens had distinct cutaneous bacterial community structures. Phylotypes belonging to the genera Janthinobacterium, Pseudomonas, and Flavobacterium were more abundant, and sometimes almost exclusively present, in uninfected than in infected specimens. These bacterial populations, known to exhibit antifungal activity in amphibians, may also play a role in protection against cutaneous infectious diseases caused by Amphibiocystidium parasites.
Non-coding RNAs and HIV: viral manipulation of host dark matter to shape the cellular environment

On October 28th 1943 Winston Churchill said “we shape our buildings, and afterward our buildings shape us” (Humes, 1994). Churchill was pondering how and when to rebuild the British House of Commons, which had been destroyed by enemy bombs on May 10th 1941. The old House had been small and insufficient to hold all its members, but was restored to its original form in 1950 in order to recapture the “convenience and dignity” that the building had shaped into its parliamentary members. The circular loop whereby buildings or dwellings are shaped and go on to shape those that reside in them is also true of pathogens and their hosts. As obligate parasites, pathogens need to alter their cellular host environments to ensure survival. Typically pathogens modify cellular transcription profiles and in doing so, the pathogen in turn is affected, thereby closing the loop. As key orchestrators of gene expression, non-coding RNAs provide a vast and extremely precise set of tools for pathogens to target in order to shape the cellular environment. This review will focus on host non-coding RNAs that are manipulated by the infamous intracellular pathogen, the human immunodeficiency virus (HIV). We will briefly describe both short and long host non-coding RNAs and discuss how HIV gains control of these factors to ensure widespread dissemination throughout the host as well as the establishment of lifelong, chronic infection.
An authorization Framework for Grid Security using GT4

A Grid system is a Virtual Organization that is composed of several autonomous domains . It concerned with the sharing and coordinated use of diverse resources in distributed "virtual organizations. ” The dynamic and multiinstitutional nature of these environments introduces challenging security issues that demand new technical approaches. In particular, one must deal with diverse local mechanisms, support dynamic creation of services, and enable dynamic creation of trust domains. We review the Globus Toolkit version 2 (GT2) approach; then, Globus Toolkit version 3 (GT3), then, for authorization in such virtual organization a system needs to be flexible and scalable(reviewed the blacklist/whitelist authorization) to support multiple security policies. Basing on the Web Services security specifications such as XACML, SAML, and the special security needs of the Grid computing we review Globus Toolkit version 4 (GT4), provides a simple, open and efficient method for Grid service access control.