Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-term spatially defined coculture within three-dimensional photopatterned hydrogels.

Spatially controlled coculture in three-dimensional environments that appropriately mimic in vivo tissue architecture is a highly desirable goal in basic scientific studies of stem cell physiological processes (e.g., proliferation, matrix production, and tissue repair) and in enhancing the development of novel stem-cell-based clinical therapies for a variety of ailments. This study describes a novel fabrication system for photopatterning and assembling cell-laden oligo(polyethylene glycol)-fumarate:poly(ethylene glycol)-diacrylate hydrogels with high spatial fidelity and thickness using a controlled, inert nitrogen environment without the need for expensive precision equipment. Cross-linking was performed using Irgacure-2959 photoinitiator and 365-nm light (∼7 mW/cm²) to form gels ranging from 0.9 to 3 mm in width. Employing a nitrogen environment increased gel thickness up to 240%, generating gels > 1 mm thick before swelling. This technique was further applied for spatially controlled patterning of primary tendon/ligament fibroblasts and marrow stromal cells in a single 1.5-mm-thick laminated hydrogel construct. Cells encapsulated using this technique maintained viability over 14 days in culture. This system potentially enables better understanding of paracrine effects on a range of stem cell functions and therefore may be useful as an in vitro model system for a wide array of regenerative medicine applications.
A simple modified version of Edmonds' Branching algorithm for Minimum Weight Rooted Arborescence problem

We consider a general optimization problem regarding spanning trees in directed graphs (arborescence). We present an algorithm for solving such problem, which can be considered as a generalization of Edmonds' branching algorithm for the solution of the minimum weight rooted arborescence (MWRA) problem. This paper studies the problem of finding a minimum weight rooted arborescence in a rooted digraph with weights on edges. A method is developed for this problem, and computational results are reported.
Membrane Fusion Promoted by Increasing Surface Densities of the Paramyxovirus F and HN Proteins: Comparison of Fusion Reactions Mediated by Simian Virus 5 F, Human Parainfluenza Virus Type 3 F, and Influenza Virus HA

ABSTRACT The membrane fusion reaction promoted by the paramyxovirus simian virus 5 (SV5) and human parainfluenza virus type 3 (HPIV-3) fusion (F) proteins and hemagglutinin-neuraminidase (HN) proteins was characterized when the surface densities of F and HN were varied. Using a quantitative content mixing assay, it was found that the extent of SV5 F-mediated fusion was dependent on the surface density of the SV5 F protein but independent of the density of SV5 HN protein, indicating that HN serves only a binding function in the reaction. However, the extent of HPIV-3 F protein promoted fusion reaction was found to be dependent on surface density of HPIV-3 HN protein, suggesting that the HPIV-3 HN protein is a direct participant in the fusion reaction. Analysis of the kinetics of lipid mixing demonstrated that both initial rates and final extents of fusion increased with rising SV5 F protein surface densities, suggesting that multiple fusion pores can be active during SV5 F protein-promoted membrane fusion. Initial rates and extent of lipid mixing were also found to increase with increasing influenza virus hemagglutinin protein surface density, suggesting parallels between the mechanism of fusion promoted by these two viral fusion proteins.
Quantitative Expression and Co-Localization of Wnt Signalling Related Proteins in Feline Squamous Cell Carcinoma

Feline oral squamous cell carcinoma (FOSCC) is an aggressive neoplasm in cats. Little is known about the possible molecular mechanisms that may be involved in the initiation, maintenance and progression of FOSCC. Wnt signalling is critical in development and disease, including many mammalian cancers. In this study, we have investigated the expression of Wnt signalling related proteins using quantitative immunohistochemical techniques on tissue arrays. We constructed tissue arrays with 58 individual replicate tissue samples. We tested for the expression of four key Wnt/ß-catenin transcription targets, namely Cyclin D1 (CCND1 or CD1), FRA1, c-Myc and MMP7. All antibodies showed cross reactivity in feline tissue except MMP7. Quantitative immunohistochemical analysis of single proteins (expressed as area fraction / amount of tissue for normal vs tumor, mean ± SE) showed that the expression of CD1 (3.9 ± 0.5 vs 12.2 ± 0.9), FRA1 (5.5 ± 0.6 vs 16.8 ± 1.1) and c-Myc (5.4 ± 0.5 vs 12.5 ± 0.9) was increased in FOSCC tissue by 2.3 to 3 fold compared to normal controls (p<0.0001). By using a multilabel, quantitative fluorophore technique we further investigated if the co-localization of these proteins (all transcription factors) with each other and in the nucleus (stained with 4',6-diamidino-2-phenylindole, DAPI) was altered in FOSCC compared to normal tissue. The global intersection coefficients, a measure of the proximity of two fluorophore labeled entities, showed that there was a significant change (p < 0.01) in the co-localization for all permutations (e.g. CD1/FRA1 etc), except for the nuclear localization of CD1. Our results show that putative targets of Wnt signalling transcription are up-regulated in FOSCC with alterations in the co-localization of these proteins and could serve as a useful marker for the disease.
INVESTIGATION OF COAL-METHANOARCHAEAL ASSEMBLAGE IN DEEP SUBSURFACEUNDERGROUND USING ENRICHMENT CULTURE TECHNIQUE

Enrichment culture of coal samples from underground mines (Jitpur and Moonidih underground mines) located in Dhanbad region, the Indian state of Jharkhand was tested positive for the presence of living microbial lineage capable of producing methane from coal during energy metabolism under laboratory condition. Accordingly, two gram negative, mesophilic, penicillin G and streptomycin resistant strain (BC /C IMFR-ana-CH4-12 and 14) derived from preferred sites were produce methane from acetate. They assimilated complex proteinaceous substances (yeast extract, beef extract, tryptone, and peptone) and amino acids (alanine, cysteine, and methionine) for energy metabolism. The pH ranges for growth were 6.0-7.5 for strain BC /C IMFR-ana-CH4-12 and 6.5-8.5 for strain BC /C IMFR-ana-CH4-14, with the fastest growth at pH 7.5 for BC /C IMFR-ana-CH4-12 and pH 7.0 for strain BC /C IMFR-ana-CH4-14. During growth, doubling time was observed 13.702- 14.005 hours under the optimal condition, and specific growth rate was recorded 0.021/hour for both strains. Based on the study strains were belongs to Methanococcus spp. and Methanobacterium spp. , associated with numerous aerobic and anaerobic microbial community in deep subsurface coal deposits as suitable habitat. The ecological implication of their habitat also discussed. The study suggests that there is intense biogenic methane generation activity in a selected environment which may me enhance by stimulating the activity of existing methanoarchaeal consortia.
Uses and interpretations of non-word repetition tasks in children with and without specific language impairments (SLI).

BACKGROUND The non-word repetition task (NRT) has gained wide acceptance in describing language acquisition in both children with normal language development (NL) and children with specific language impairments (SLI). This task has gained wide acceptance because it so closely matches the phonological component of word learning, and correlates with measures of phonological working memory, a deficit in which is hypothesized to underlie SLI. AIMS/METHODS & PROCEDURES Recent uses of the NRT seem to accept it as a measure of phonological working memory capacity in spite of the fact that researchers have consistently acknowledged that the task taps many language processes, including speech perception, phonological encoding, phonological memory, phonological assembly and articulation. This paper reviews the literature on the use of the non-word repetition task (NRT) in children with NL and children with SLI, emphasizing the component skills necessary for successful repetition. MAIN CONTRIBUTION For children with NL, discussion has focused on (1) the relationship between non-word repetition ability and vocabulary, and (2) lexical and sublexical influences on repetition accuracy. For children with SLI, discussion has focused on these factors as well, but has also considered other component skills that support non-word repetition. Researchers have examined speech perception and discrimination, phonological encoding, phonological memory, phonological assembly, motor planning, and articulation, and have found evidence that children with SLI exhibit impairments in each of these supporting skills. CONCLUSIONS Because repetition accuracy depends on lexical and sublexical properties, the NRT can be used to examine the structural properties of the lexicon in both children with NL and with SLI. Further, because the task taps so many underlying skills, it is a powerful tool that can be used to identify children with language impairments.
Printed text and handwriting recognition

This thesis focuses on modifying the open source speech recognition toolkit, Kaldi, to work for the task of handwriting recognition, also called text recognition. Various methods were explored to improve the performance of the text recognition setup. Text recognition refers to the automatic transcription of handwritten or printed text inputs from sources such as text page images, personal digital assistants, electronic white-boards or other devices. Text recognition can be performed in both online and off-line scenarios. Offline recognition involves recognition of handwritten images whereas on-line recognition also stores the time trajectory information of each stroke. Handwriting recognition has long been an active area of research and uses many of the same models used to perform automatic speech recognition (ASR). One such model used in both tasks is the Hidden Markov Model (HMM). In handwriting recognition, the text line images are treated as observations generated by underlying states representing the transcription. In this thesis, a hybrid deep-neural-network-HMM (DNN-HMM) acoustic model used for ASR was adapted for text recognition. To overcome a major challenge of out of vocabulary (OOV) words, a new subword based algorithm was implemented for lexicon and language modeling. Different data augmentation
Views , Types and Viewtypes ∗

The need for direct memory manipulation through pointers is essential in many applications. However, it is also commonly understood that the use (or probably misuse) of pointers is a rich source for program errors. In this paper, we design and then formalize a type system that can effectively prevent dangling pointers from being ever accessed during the evaluation of a well-type program. In particular, we present an approach that makes novel use of linear types in support of the construction of memory-safe programs while allowing explicit pointer manipulation such as pointer arithmetic.
Majorization-minimization Algorithms for Convolutive NMF with the Beta-divergence

Nonnegative matrix factorization (NMF) has become a method of choice for spectrogram decomposition. However, its inability to capture dependencies across columns of the input motivated the introduction of a variant, convolutive NMF. While algorithms for solving the convolutive NMF problem were previously proposed, they rely on the use of a heuristic that does not insure the convergence of the algorithm (in particular in terms of objective function values). The goal of this work is to propose rigorous update rules, based on a majorization-minimization (MM) approach, for convolutive NMF with the β-divergence (a standard family of measures of fit). Specifically, we derive and study two variants of a convolutive NMF algorithm that are guaranteed to decrease the objective function value at each iteration. The complexity of the algorithms is studied, and the performance in terms of execution time and objective function are evaluated and compared in several numerical experiments using real-world audio data. Experiments show that the proposed MM algorithms consistently provide lower values of the objective function than the heuristic, at similar computational cost.
Problem Based Learning: A Student-Centered Approach

Problem-based learning is a teaching method in which students’ learn through the complex and open ended problems. These problems are real world problems and are used to encourage students’ learning through principles and concept. PBL is both a teaching method and approach to the curriculum. It can develop critical thinking skill, problem solving abilities, communication skills and lifelong learning. The purpose of this study is to give the general idea of PBL in the context of language learning, as PBL has expanded in the areas of law, education, economics, business, social studies, and engineering. It encourages students to develop skills that can be useful for their future and in practical life within a team environment. For the language classroom in Arab countries, where English is spoken as a foreign language PBL can be very useful. Trained teachers can design problems to meet the needs of the learners, that can be useful to improve English practically in social context.
Exploring the applicability of the Semantic Web for discovering and navigating Australian Indigenous knowledge resources

ABSTRACT Semantic Web ontology files can be flexibly programmed to delineate metadata relationships in machine-readable formats to create relational pathways for discovering resources both on and off the Internet. There is a global community of Semantic Web developers and users across a broad multi-disciplinary range of interests who create and share extensible open-source ontologies. In this article, the author will explore the functionality of Semantic Web techniques for representing the ontologies of relatedness through kinship that typically underpin Australian Indigenous knowledge systems, and investigate their potentials for meeting persistent demands among leading Australian Indigenous collections creators and users to be able to search and discover their hereditary knowledge resources in ways that reflect and reinforce their enduring cultural values, ways of knowing and rights-management concerns.
A Deep Architecture for Non-Projective Dependency Parsing

Graph-based dependency parsing algorithms commonly employ features up to third order in an attempt to capture richer syntactic relations. However, each level and each feature combination must be defined manually. Besides that, input features are usually represented as huge, sparse binary vectors, offering limited generalization. In this work, we present a deep architecture for dependency parsing based on a convolutional neural network. It can examine the whole sentence structure before scoring each head/modifier candidate pair, and uses dense embeddings as input. Our model is still under ongoing work, achieving 91.6% unlabeled attachment score in the Penn Treebank.
Sticking to the text: a corpus linguist's view of language

Corpus Linguistics is the study of large, computer‐held bodies of text, or ‘corpora’. In the last five years, this approach to language study has become increasingly popular among linguists, and developments in computing technology and software and in storage mechanisms like CD are making it possible even for the individual PC user. The aim of the linguist is to describe the language, and corpus linguistics reflects the shift in academic focus from the brain to the text as the appropriate source of information. A description derived by introspection will tend to be idiosyncratic and partial, since no individual has total awareness of how they or others use language. A description based on the observation of appropriate corpus data, on the other hand, can provide a broader view of language use, including statements about the relative typicality of individual features based on their frequency of occurrence in the corpus.
Harmonic to subharmonic transition of the Faraday instability in miscible fluids

When a stable stratification between two miscible fluids is excited by a vertical and periodic forcing, a turbulent mixing zone can develop, triggered by the Faraday instability. The mixing zone grows and saturates to a recently predicted final value L sat [Grea and Ebo Adou, J. Fluid Mech. 837, 293 (2018)] when resonance conditions are no longer fulfilled. Notably, it is expected from the Mathieu stability diagram that the instability may evolve from a harmonic to a subharmonic regime for particular initial conditions. This transition is evidenced here in the full inhomogeneous system using direct numerical simulations with 1024 3 points: the analysis of one-point statistics and spectra reveals that turbulence is greatly enhanced after the transition, while the global anisotropy of both the velocity and concentration fields is significantly reduced. Furthermore, using the concept of sorted density field, we compute the background potential energy e b p of the flow, which increases only after the transition as a signature of irreversible mixing. While the gain in e b p strongly depends on the control parameters of the instability, the cumulative mixing efficiency is more robust. At saturation of the instability, available potential energy is partially released in the flow as background potential energy. Finally, it is shown numerically that for fixed parameters, a multiple-frequency forcing can modify the duration of the harmonic regime without significantly altering the asymptotic state.
Document transformation system from papers to XML data based on pivot XML document method

This paper proposes a new method for document transformation using OCR to generate various XML documents from printed documents. The proposed method adopts a hierarchical transformation strategy based on a pivot XML document. Firstly, document elements such as title, authors, abstract, headings, paragraphs, lists, captions, tables and figures are extracted from document images. Secondly, the hierarchical structure of document elements is extracted and is described using a DOM tree. Thirdly, this document structure is converted into a pivot XML document described as an XHTML document by an XML parser. Finally, this pivot XML document is transformed into the target XML document by the XML parser with XSLT scripts or specific programs. Experimental results show the method is effective in transforming printed documents to various XML documents.
SVD and Error Control Coding Based Digital Image Watermarking

Digital media is a craze these days. With the present day internet connectivity the world has become smaller. The copyright protections of intellectual properties have become a necessity for prevention of illegal copying and content integrity verification. Newer data hiding techniques that satisfy the requirements of imperceptibility, robustness, capacity, or data hiding rate and security of the hidden data etc. are being developed. Therefore the preference to go for digital image watermarking, to show resiliency against various unintentional or deliberate attacks has increased. Watermarking is a method of data authentication by embedding a watermark in image characteristics with expectation. Here in this work, this is done using a mathematical tool called the singular value decomposition (SVD). Earlier SVD had been used individually, as a tool for watermarking of digital media, but this work incorporates error control coding to it, by a novel zig-zag scan operation on pixels done before coding, thereby increasing the robustness. This work here by focuses on using both of them together to provide a robust technique developed for protection of the intellectual property against the popular malicious attacks. The algorithm is later applied and tested on the standard checkmark techniques practically by attacking the watermarked image against standard simulated attacks and recovering the watermarked logo from it.
H∞ disturbance attenuation of fuzzy large-scale systems

This paper is concerned with the disturbance attenuation problem of fuzzy large-scale systems which consist of N interconnected subsystems which are represented by Takagi-Sugeno fuzzy models. Using Lyapunov function and linear matrix inequalities (LMIs), a criterion is proposed to have a prescribed level of disturbance attenuation. A numerical example is given to illustrate the control design procedure and its effectiveness.
Towards the Mo Piu tonal system: first results on an undocumented south-asian language

This paper presents the first results on the Mo Piu tonal system. This language is undocumented, unwritten and moreover in great danger. As the tasks of labeling phonetics and tones is hard to carry out when references on the language are lacking, this paper aims at presenting our method to try to build reliable data in order to understand the tonal system, and the main findings concerning the Mo Piu tonal system and finally at leading a comparison between these first results and the White Hmong tonal system.
Activation of the Pseudomonas aeruginosa Type III Secretion System Requires an Intact Pyruvate Dehydrogenase aceAB Operon

ABSTRACT Pseudomonas aeruginosa clinical cystic fibrosis isolate CHA was mutagenized with Tn5Tc to identify new genes involved in type III secretion system (TTSS)-dependent cytotoxicity toward human polymorphonuclear neutrophils. Among 25 mutants affected in TTSS function, 14 contained the insertion at different positions in the aceAB operon encoding the PDH-E1 and -E2 subunits of pyruvate dehydrogenase. In PDH mutants, no transcriptional activation of TTSS genes in response to calcium depletion occurred. Expression in trans of ExsA restored TTSS function and cytotoxicity.
Direct triggering of the type I interferon system by virus infection: activation of a transcription factor complex containing IRF‐3 and CBP/p300

It has been hypothesized that certain viral infections directly activate a transcription factor(s) which is responsible for the activation of genes encoding type I interferons (IFNs) and interferon‐stimulated genes (ISGs) via interferon regulatory factor (IRF) motifs present in their respective promoters. These events trigger the activation of defense machinery against viruses. Here we demonstrate that IRF‐3 transmits a virus‐induced signal from the cytoplasm to the nucleus. In unstimulated cells, IRF‐3 is present in its inactive form, restricted to the cytoplasm due to a continuous nuclear export mediated by nuclear export signal, and it exhibits few DNA‐binding properties. Virus infection but not IFN treatment induces phosphorylation of IRF‐3 on specific serine residues, thereby allowing it to complex with the co‐activator CBP/p300 with simultaneous nuclear translocation and its specific DNA binding. We also show that a dominant‐negative mutant of IRF‐3 could inhibit virus‐induced activation of chromosomal type I IFN genes and ISGs. These findings suggest that IRF‐3 plays an important role in the virus‐inducible primary activation of type I IFN and IFN‐responsive genes.
On first-order discrete boundary value problems

This article analyzes a nonlinear system of first-order difference equations with periodic and non-periodic boundary conditions. Some sufficient conditions are presented under which: potential solutions to the equations will satisfy certain a priori bounds; and the equations will admit at least one solution. The methods involve new dynamic inequalities and use of Brouwer degree theory. The new results are compared with those featuring in the theory of solutions to boundary value problems for differential equations.