Miracle-dz/UniFAR-FTUs huggingface dataset:
Using the user's point of view for interaction on mobile devices

We study interaction modalities for mobile devices (smartphones and tablets) that rely on a camera-based head tracking. This technique defines new possibilities for input and output interaction. For output, by computing the position of the device according to the user's head, it is for example possible to realistically control the viewpoint on a 3D scene (Head-Coupled Perspective, HCP). This technique improves the output interaction bandwidth by enhancing the depth perception and by allowing the visualization of large workspaces (virtual window). For input, head movement can be used as a means of interacting with a mobile device. Moreover such an input modality does not require any additional sensor except the built-in front-facing camera. In this paper, we classify the interaction possibilities offered by head tracking on smartphones and tablets. We then focus on the output interaction by introducing several applications of HCP on both smartphones and tablets and by presenting the results of a qualitative user experiment.
Sorting nexin 3 (SNX3) is disrupted in a patient with a translocation t(6;13)(q21;q12) and microcephaly, microphthalmia, ectrodactyly, prognathism (MMEP) phenotype

A patient with microcephaly, microphthalmia, ectrodactyly, and prognathism (MMEP) and mental retardation was previously reported to carry a de novo reciprocal t(6;13)(q21;q12) translocation. In an attempt to identify the presumed causative gene, we mapped the translocation breakpoints using fluorescence in situ hybridisation (FISH). Two overlapping genomic clones crossed the breakpoint on the der(6) chromosome, locating the breakpoint region between D6S1594 and D6S1250. Southern blot analysis allowed us to determine that the sorting nexin 3 gene (SNX3) was disrupted. Using Inverse PCR, we were able to amplify and sequence the der(6) breakpoint region, which exhibited homology to a BAC clone that contained marker D13S250. This clone allowed us to amplify and sequence the der(13) breakpoint region and to determine that no additional rearrangement was present at either breakpoint, nor was another gene disrupted on chromosome 13. Therefore, the translocation was balanced and SNX3 is probably the candidate gene for MMEP in the patient. However, mutation screening by dHPLC and Southern blot analysis of another sporadic case with MMEP failed to detect any point mutations or deletions in the SNX3 coding sequence. Considering the possibility of positional effect, another candidate gene in the vicinity of the der(6) chromosome breakpoint may be responsible for MMEP in the original patient or, just as likely, the MMEP phenotype in the two patients results from genetic heterogeneity.
Effectively Manifesting Concurrency Bugs in Android Apps

Smartphones are indispensable in people's daily lives. As smartphone apps are being increasingly concurrent, developers are increasingly unable to tackle the complexity and to avoid subtle concurrency bugs. To better address this issue, we propose a novel approach to manifesting concurrency bugs in Android apps based on the fact that one can simultaneously generate input events and their schedules for an app. We conduct static-dynamic hybrid analysis to find potentially conflicting resource accesses in an app. The app is then automatically pressure-tested by guided event and schedule generation. We implemented the prototype tool AATT and evaluated it over thirteen popular real-world open-source apps. AATT successfully found 9 concurrency bugs out of which 7 were previously unknown.
Self-Alignment of Patterned Wafers Using Capillary Forces at a Water–Air Interface

Precision alignment of features that are defined on separate substrates is an important step in fabricating a wide range of micrometer-scale sensors and actuators. In this paper, we describe the use of capillary forces resulting from menisci formed at a water‐air interface within lithographically defined patterns to automatically align features on two flat substrates with submicrometer accuracy. Capillary forces have been shown to be extremely powerful at the sub-millimeter scale. For example, the 30 year-old solder bump technology takes advantage of simple surface energy effects. [1] Solder is used to wet metal terminals on a chip before bringing this chip into contact with its complement. Self-alignment has been reported with this technique as the solder minimizes its surface area. Whitesides and coworkers have made extensive use of the “capillary bond” in their discussion of selfassembly of millimeter scale objects. [2] In a series of their experiments, polydimethylsiloxane objects were made to assemble into predetermined patterns at a liquid‐liquid interface by modifying their wall chemistries to generate attractive or repulsive menisci. This application of surface free energy showed that the minimization of the curvature of the menisci
Mathematical Modeling of Retinal Mosaic Formation by Mechanical Interactions and Dendritic Overlap

The retina is a complex assembly of neurons packed into a three-layer structure containing five classes of cells. Each class of retinal cells is regularly arranged within its layer in an orderly configuration called the retinal mosaic. We have set up a mathematical model of retinal mosaic formation focusing on the actions of local mechanical forces on the neuron's cytoskeleton. The cytoskeleton has been modeled according to two approaches, one based on the tensegrity concept (a structure made of elastic and rigid elements), and the other based on a simple model with viscoelastic features. We have assumed causing deformation of their cytoskeleton, overlap of dendritic areas and movement of the neuron. Simulations based on these two models indicate that a random distribution of neurons reaches an orderly configuration by local and mechanical neuron interaction in the case in which the cytoskeleton is modeled using the tensegrity approach, but not when the neuron is modeled as a purely viscoelastic system. Considering that the main structural difference between the Maxwell model and the tensegrity model is that the latter model contains rigid elements whereas the former does not, this suggests that the presence of rigid components in the cytoskeleton of retinal neurons plays a key role in the formation processes of the retinal mosaic.
In vitro analysis of mouse neural stem cells genetically modified to stably express human NGF by a novel multigenic viral expression system

Abstract Objectives: The purpose of this study was to characterize mouse neural stem cells (NSC) transduced by a multigenic lentiviral vector (LV) and stably express recombinant human nerve growth factor (rhNGF). We obtained NSC-derived cell lines which express human NGF in relevant amount to exploit their ability for therapeutic applications. Methods: We constructed advanced multigenic LV vectors which contain a tricistronic cassette to express simultaneously up to three independent genes: (1) rhNGF (β subunit); (2) EGFP (enhanced green fluorescent protein) and (3) NeoR (neomycin antibiotic resistance gene). Lentiviruses were obtained by transfecting LV constructs plus helper plasmids in human embryonic kidney (HEK)-293T packaging cells. Lentiviral virions were released in culture media and subsequent used to infect mouse NSC. Genetycin 418-resistant NSC were obtained after 1 month of selection in the presence of antibiotic (G418). Levels of human NGF secreted by rhNGF-NSC were determined by ELISA (enzyme-linked immunosorbent assay). Features of multipotentiality of engineered NSC-derived cell lines versus naive cells (control-NSC) were assessed by immunocytochemical analysis in differentiation conditions. Self-renewal of NSC was tested by neurospheres assay (NSA). Results: Levels of secreted human NGF, from conditioned media obtained by rhNGF-NSC cultures, were found to be elevated in either proliferation or differentiation conditions as compared with control cells. Moreover, released hNGF demonstrated biologic activity on PC12 cells by a functional test of neurite outgrowth. Immunocytochemical analysis revealed that engineered NSC showed to be all positives for EGFP. After thirty passages in vitro in the presence of G418, engineered cells versus naive NSC cultures maintained their multipotentiality to differentiate into neurons, astrocytes and oligodendrocytes. Furthermore, it was found that rhNGF-NSC-derived neurons expressed choline acetyltransferase (ChAT) and displayed an enhanced axonal growth. NSA showed an altered sphere forming frequency either in rhNGF-NSC or both group of control NSC. Discussion: Lentivirus-mediated rhNGF gene transfer into NSC was achieved using a new version of LV vectors. We obtained rhNGF-NSC-derived cell lines which released hNGF to high levels in the culture medium. The expression of neural differentiation markers, like microtubule associated protein 2 (MAP2) (a/b), glial fibrillary acidic protein (GFAP) and chondroitin sulphate proteoglycan (NG2), was not enhanced in rhNGF-NSC compared with control cells. Secreted hNGF increased axonal sprouting by rhNGF-NSC-derived neurons which was associated with ChAT expression. rhNGF-NSC may prospectively be good candidates for the treatment of either neurodegenerative diseases such as Alzheimer disease or central nervous system injuries.
Balanced network flows. VII. Primal‐dual algorithms

We discuss an adaptation of the famous primal‐dual 1‐matching algorithm to balanced network flows which can be viewed as a network flow description of capacitated matching problems. This method is endowed with a sophisticated start‐up procedure which eventually makes the algorithm strongly polynomial. We apply the primal‐dual algorithm to the shortest valid path problem with arbitrary arc lengths, and so end up with a new complexity bound for this problem. © 2002 John Wiley & Sons, Inc.
Unique Translation Initiation at the Second AUG Codon Determines Mitochondrial Localization of the Phage-Type RNA Polymerases in the Moss Physcomitrella patens1

The nuclear genome of the moss Physcomitrella patens contains two genes encoding phage-type RNA polymerases (PpRPOT1 and PpRPOT2). Each of the PpRPOT1 and PpRPOT2 transcripts possesses two in-frame AUG codons at the 5′ terminus that could act as a translational initiation site. Observation of transient and stable Physcomitrella transformants expressing the 5′ terminus of each PpRPOT cDNA fused with the green fluorescent protein gene suggested that both PpRPOT1 and PpRPOT2 are not translated from the first (upstream) AUG codon in the natural context but translated from the second (downstream) one, and that these enzymes are targeted only to mitochondria, although they are potentially targeted to plastids when translation is forced to start from the first AUG codon. The influence of the 5′-upstream sequence on the translation efficiency of the two AUG codons in PpRPOT1 and PpRPOT2 was quantitatively assessed using a β-glucuronidase reporter. The results further supported that the second AUG codon is the sole translation initiation site in Physcomitrella cells. An Arabidopsis (Arabidopsis thaliana) RPOT homolog AtRpoT;2 that possesses two initiation AUG codons in its transcripts, as do the RPOTs of P. patens, has been regarded as a dually targeted protein. When the localization of AtRpoT;2 was tested using green fluorescent protein in a similar way, AtRpoT;2 was also observed only in mitochondria in many Arabidopsis tissues. These results suggest that, despite the presence of two in-frame AUGs at the 5′ termini of RPOTs in Physcomitrella and Arabidopsis, the second AUG is specifically recognized as the initiation site in these organisms, resulting in expression of a protein that is targeted to mitochondria. This finding may change the current framework of thinking about the transcription machinery of plastids in land plants.
Road Accidents Bigdata Mining and Visualization using Support Vector Machines

— Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the trafﬁc department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classiﬁers from the obtained trafﬁc data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.
Perceptual Factor Analysis for Speech Enhancement

This paper presents a new speech enhancement approach originated from factor analysis (FA) framework. FA is a data analysis model where the relevant common factors can be extracted from observations. A factor loading matrix is found and a resulting model error is introduced for each observation. Interestingly, FA is a subspace approach properly representing the noisy speech. This approach partitions the space of noisy speech into a principal subspace containing clean speech and a complimentary (minor) subspace containing the residual speech and noise. We show that FA is a generalized data model compared to signal subspace approach. To perform FA speech enhancement, we present a perceptual optimization procedure that minimizes the signal distortion subject to the energies of residual speech and noise under a specified level. Importantly, we present a hypothesis testing approach to optimally perform subspace decomposition. In the experiments, we implement perceptual FA speech enhancement using Aurora2 corpus. We find that proposed approach achieves desirable speech recognition rates especially when signal-to-noise ratio is lower than 5 dB.
Mathematical-Programming Approach to Matrix Games With Payoffs Represented by Atanassov's Interval-Valued Intuitionistic Fuzzy Sets

The purpose of this paper is to develop the concept and mathematical-programming methodology of matrix games with payoffs represented by Atanassov's interval-valued intuitionistic fuzzy (IVIF) sets. In this methodology, the concept of solutions of matrix games with payoffs represented by Atanassov's IVIF sets is defined, and some important properties are studied using multiobjective-programming and duality-programming theory. It is proven that each matrix game with payoffs represented by Atanassov's IVIF sets has a solution, which can be obtained through solving a pair of auxiliary linear/nonlinear-programming models derived from a pair of nonlinear biobjective interval-programming models. Validity and applicability of the proposed methodology are illustrated with a numerical example.
Empirical Comparison of Evaluation Methods for Unsupervised Learning of Morphology

Unsupervised and semi-supervised learning of morphology provide p ractical solu- tions for processing morphologically rich languages with less human labor th the traditional rule-based analyzers. Direct evaluation of the learning methods using lin guistic reference anal- yses is important for their development, as evaluation through the final app lications is often time consuming. However, even linguistic evaluation is not straightforward for fu ll morphological analysis, because the morpheme labels generated by the learning method can be arbitrary. We review the previous evaluation methods for the learning tasks and propose new variations. In order to compare the methods, we perform an extensive meta-evaluation u sing the large collec- tion of results from the Morpho Challenge competitions. RESUME. L'apprentissage non supervise et semi-supervise de la morphologie fo urnit des so- lutions pratiques pour le traitement des langues morphologiquement riche s et requiert une intervention humaine reduite comparee aux analyseurs traditionnels base s sur des regles. L'evaluation directe des methodes d'apprentissage utilisant des analyse s de reference linguis- tique est importante pour leur developpement, puisque l'evaluation par lesapplications fi- nales prend generalement beaucoup de temps. Cependant, meme l'ev aluation linguistique n'est pas simple pour l'analyse morphologique complete, car les identifiants de m orphemes gene- res par la methode d'apprentissage peuvent se reveler arbitraires. N ous passons en revue les methodes d'evaluation existantes pour les tâches d'apprentissage et pr oposons de nouvelles va- riations. Afin de comparer les methodes, nous effectuons une vaste meta -evaluation a l'aide de l'importante base de resultats provenant des competitions Morpho Challen ge.
Structural controllability analysis of complex networks

How to exactly acquire link weights and high complexity of calculating eigenvalues of large-scale matrices are two inevitable problems in applying exact controllability framework to controllability of complex networks. To achieve complete regulation of arbitrary networks of general configurations, we here introduce a new structural controllability analysis approach based on the reachability matrix to identify the minimum set of driver nodes. Furthermore, we investigate the impact of network topology on controllability by means of robustness measure of network against random failures and malicious attacks, which could further deepen our understanding of controlling complex networks.
An embedded ReRAM using a small-offset sense amplifier for low-voltage operations

This paper presents a Contact Resistive Random Access Memory (CRRAM) macro with an offset-compensated Sense amplifier for low-voltage operation. The proposed circuit aims to solve the variation and speed issues during low-voltage operations. A 256Kb test-chip was fabricated in TSMC 65nm technology. An improvement of 1.78x in read speed and 85.7% in offset was measured compared to conventional sensing methods, and the minimum operating voltage was as low as 0.3V.
RRDD: Reliable Route Based Data Dissemination Technique in VANETs

In the vehicular Ad Hoc Network (VANETs) data dissemination is very important issue among the researchers and efficient data dissemination is very critical for some applications. In this paper we are presenting reliable route based data dissemination technique which sends the packet using exact route to destination to achieve efficient data delivery ratio and minimum packet drop. It also reduces the total number of packet that are moving in the network in comparison to the flooding based data dissemination. Simulation results demonstrates that the proposed protocol reduces congestion in the dense traffic region and efficiently utilizes the bandwidth in stressful road scenarios.
Covalent Small Ubiquitin-like Modifier (SUMO) Modification of Maf1 Protein Controls RNA Polymerase III-dependent Transcription Repression*

Background: Maf1 is a central repressor of genes that promote oncogenesis, yet little is known about how Maf1 is regulated. Results: Maf1K35 SUMO modification is controlled by SENP1, affecting its ability to repress transcription and suppress cell growth. Conclusion: SUMOylation of Maf1 is implicated as a regulatory mechanism for RNA pol III transcription. Significance: A link between SENP1, Maf1, and RNA pol III-mediated transcription in oncogenesis is revealed. RNA polymerase (pol) III transcribes genes that determine biosynthetic capacity. Induction of these genes is required for oncogenic transformation. The transcriptional repressor, Maf1, plays a central role in the repression of these and other genes that promote oncogenesis. Our studies identify an important new role for SUMOylation in repressing RNA pol III-dependent transcription. We show that a key mechanism by which this occurs is through small ubiquitin-like modifier (SUMO) modification of Maf1 by both SUMO1 and SUMO2. Mutation of each lysine residue revealed that Lys-35 is the major SUMOylation site on Maf1 and that the deSUMOylase, SENP1, is responsible for controlling Maf1K35 SUMOylation. SUMOylation of Maf1 is unaffected by rapamycin inhibition of mammalian target of rapamycin (mTOR) and mTOR-dependent Maf1 phosphorylation. By preventing SUMOylation at Lys-35, Maf1 is impaired in its ability to both repress transcription and suppress colony growth. Although SUMOylation does not alter Maf1 subcellular localization, Maf1K35R is defective in its ability to associate with RNA pol III. This impairs Maf1 recruitment to tRNA gene promoters and its ability to facilitate the dissociation of RNA pol III from these promoters. These studies identify a novel role for SUMOylation in controlling Maf1 and RNA pol III-mediated transcription. Given the emerging roles of SENP1, Maf1, and RNA pol III transcription in oncogenesis, our studies support the idea that deSUMOylation of Maf1 and induction of its gene targets play a critical role in cancer development.
Algorithmic Information Theory-Based Analysis of Earth Observation Images: An Assessment

Earth observation image-understanding methodologies may be hindered by the assumed data models and the estimated parameters on which they are often heavily dependent. First, the definition of the parameters may negatively affect the quality of the analysis. The parameters could not be captured in all aspects, and those resulting superfluous or not accurately tuned may introduce nuisance in the data. Furthermore, the diversity of the data, as regards sensor type, spatial, spectral, and radiometric resolution, and the variety and regularity of the observed scenes make it difficult to establish enough valid and robust statistical models to describe them. This letter proposes algorithmic information theory-based analysis as a valid solution to overcome these limitations. We will present different applications on satellite images, i.e., clustering, classification, artifact detection, and image time series mining, showing the generalization power of these parameter-free data-driven methods based on the computational complexity analysis.
Cyber Security Approach in Web Application using SVM

Internet is open source for web access like for the purpose of railway reservation, online banking, online fees submission etc. Security concern is the most threatening topic for users about their confidential information’s storage. various security designing and algorithms has been designed to impose secure environment for user but still malicious activities , codes, algorithms, design are acting on web application to create abnormal behavior for web usage or to steal confidential, secure information for the intension of unauthorized access ,illegitimate access , access for destroying or altering the contents. Attacker’s performs Site phishing, Dos attacks, pattern recognition for brute force attack etc, by using several hit and trial or input capturing methods, or by providing capturing codes or IP packets into web contents. Here in the proposed work a technique of detecting malicious Socket address (IP Address and port no.) has been presented, which detects and blocks if any suspicious cases are found and passes the contents to concern user. Here we use SVM technique for classification, detection and prediction of Blacklisted IP addresses and blacklisted port’s addresses. The proposed algorithm provides accuracy of 96.99% and which is the best among the present systems. It is light weight system and easy to implement on existing applications.