Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of Defects in Aluminium using Large Scale Electronic Structure Calculations.

Defects in materials play an important role in determining their behavior. Defects, such as vacancies, dislocations, surfaces, dopants, interstitials, though present in small concentrations of the order of few parts per million (ppm), can influence properties of the materials at macroscopic scales. Various computational techniques have been used to model the influence of defects on the properties of materials. Density functional theory based electronic structure calculations have been very accurate in predicting material properties. Electronic structure calculations have provided various insights into the properties of materials such as bulk properties, surface energetics and phase transformations. But, their applicability in studying defect properties is restricted due to limitations on simulation cell-size, to the order of a few hundred to thousand atoms. Recently developed coarse graining technique Quasi Continuum orbital free density functional theory (QCOFDFT) addresses these issues using a real-space local variational formulation of the orbital free density functional theory, finite element discretization of the formulation and an adaptive coarse graining technique. Using this technique, multi-million atom simulations with arbitrary boundary conditions are accessible, which are instrumental in modeling defects in crystalline materials. In this thesis, we extend the QCOFDFT technique to the more accurate non-local kinetic energy functionals that describe materials systems whose electronic structure is close to that of a free electron gas. First, we present a local variational reformulation of the nonlocal functionals. The accuracy of this local formulation is validated with calculations on bulk properties of Aluminium and compared against plane-wave basis implementations. The coarse graining technique, QCOFDFT, is then used with this local reformulation to achieve multi-million atom simulations of vacancies in Aluminium. Cell-size studies are performed on mono and di-vacancies to underscore the need of large scale electronic structure calculations for an accurate understanding of the eneregtics of defects. The real-space formulation is then used to study an isolated edge dislocation to characterize the defect
Bisphenol A Alters n-6 Fatty Acid Composition and Decreases Antioxidant Enzyme Levels in Rat Testes: A LC-QTOF-Based Metabolomics Study

Background Male reproductive toxicity induced by exposure to bisphenol A (BPA) has been widely reported. The testes have proven to be a major target organ of BPA toxicity, so studying testicular metabolite variation holds promise for the discovery of mechanisms linked to the toxic effects of BPA on reproduction. Methodology/Principal Findings Male Sprague-Dawley rats were orally administered doses of BPA at the levels of 0, 50 mg/kg/d for 8 weeks. We used an unbiased liquid chromatography-quadrupole time-of-flight (LC-QTOF)-based metabolomics approach to discover, identify, and analyze the variation of testicular metabolites. Two n-6 fatty acids, linoleic acid (LA) and arachidonic acid (AA) were identified as potential testicular biomarkers. Decreased levels of LA and increased levels of AA as well as AA/LA ratio were observed in the testes of the exposed group. According to these suggestions, testicular antioxidant enzyme levels were detected. Testicular superoxide dismutase (SOD) declined significantly in the exposed group compared with that in the non-exposed group, and the glutathione peroxidase (GSH-Px) as well as catalase (CAT) also showed a decreasing trend in BPA treated group. Conclusions/Significance BPA caused testicular n-6 fatty acid composition variation and decreased antioxidant enzyme levels. This study emphasizes that metabolomics brings the promise of biomarkers identification for the discovery of mechanisms underlying reproductive toxicity.
Perception of Iterated Rippled Noise Periodicity in Cochlear Implant Users

Pitch perception is more challenging for individuals with cochlear implants (CIs) than normal-hearing subjects because the signal processing by CIs is restricted. Processing and perceiving the periodicity of signals may contribute to pitch perception. Whether individuals with CIs can discern pitch within an iterated rippled noise (IRN) signal is still unclear. In a prospective controlled psychoacoustic study with 34 CI users and 15 normal-hearing control subjects, the difference limen between IRN signals with different numbers of iterations was measured. In 7 CI users and 15 normal-hearing control listeners with single-sided deafness, pitch matching between IRN and harmonic complex tones was measured. The pitch onset response (POR) following signal changes from white noise to IRN was measured electrophysiologically. The CI users could discriminate different numbers of iteration in IRN signals, but worse than normal-hearing listeners. A POR was measured for both normal-hearing subjects and CI users increasing with the pitch salience of the IRN. This indicates that the POR could serve as an objective measure to monitor progress during audioverbal therapy after CI surgery.
Relationship between Two FCA Approaches on Heterogeneous Formal Contexts

We show a relationship between two theoretical approaches of Formal Concept Analysis working with so-called heterogeneous formal context i.e. such context in which each object and attribute can have own data-type. One of them is presented in (19); each value in a formal context is some Galois connection between the lattices corresponding to the appropriate object and attribute. Another approach is presented in our paper (1) and it is a unifying platform of approaches from (14) and (11), (12). In this paper, we prove that each of them can be derived from another.
Efficient Variational Inference for Gaussian Process Regression Networks

In multi-output regression applications the correlations between the response variables may vary with the input space and can be highly non-linear. Gaussian process regression networks (GPRNs) are flexible and effective models to represent such complex adaptive output dependencies. However, inference in GPRNs is intractable. In this paper we propose two efficient variational inference methods for GPRNs. The first method, gprn-mf, adopts a mean-field approach with full Gaussians over the GPRN’s parameters as its factorizing distributions. The second method, gprn-npv, uses a nonparametric variational inference approach. We derive analytical forms for the evidence lower bound on both methods, which we use to learn the variational parameters and the hyperparameters of the GPRN model. We obtain closed-form updates for the parameters of gprn-mf and show that, while having relatively complex approximate posterior distributions, our approximate methods require the estimation of O(N) variational parameters rather than O(N) for the parameters’ covariances. Our experiments on real data sets show that gprn-npv may give a better approximation to the posterior distribution compared to gprn-mf, in terms of both predictive performance and stability.
Long term restoration of peak torque, endurance and muscle activation post anterior cruciate ligament reconstruction

ht recent years, Accelerated Rehabilitation (A.R.) protocols have been used following Anterior Cruciate Ligament (A.C.L.) reconstructions, the longer tenn effects of these programs are seldom analysed. This study examined musculoskeletal mechartisms that might affect long tenn functional restoration, The control subjects (n = 19) of mixed age and gender, had no previous knee deliciences and were rocreationally lit The experimental subjects (n = 17) had undergone intraarticular A.C. L reconstruction, using bone patellar-tendon bone grafts perfonned by the same surgeon and had also participated in the A.R. protocol, similar to that described by Shelbourne and Nitz (1990). The experimental group attended Edith Cowan University (E.C.U.) research laboratory between 20-36 months post operation, where tl1ey participated in tests on a Cybex 6000 isoldnetic dynamometer. Isokinetic knee extensions and flexions at 90, 180 and 300 degrees per second were performed, with torque output recorded from the hamstring and quadricep muscle groups, in the involved leg (l.N.) and in the uninvolved leg (U.N.) . To examine quadriceps inhibition, maximal isometric contractions with twitch superimposition WC! re analysed for each leg. Functional endurance was examined during repeated isokinetic contractions at 90 degrees per second for a duration of two minutes. To study muscle activation and co-activation, surface electromyography (S.E.M.G.) of the quadricep and hamstring muscle groups was recorded during all isokinetic contractions .
MICROMORPHOGENESIS DURING DIATOM WALL FORMATION PRODUCES SILICEOUS NANOSTRUCTURES WITH DIFFERENT PROPERTIES 1

Micromorphogenesis within the silica deposition vesicle (SDV) of the diatom Pinnularia viridis (Nitzsh) Ehrenb. resulted in distinct silica nanostructures and layers within forming valves and girdle bands. These siliceous components were similarly disclosed following alkaline etching of mature valves/girdle bands, where their different susceptibilities to dissolution over time resulted from apparent differences in silica density and/or chemistry. The bulk of silica appeared to be deposited at the interface of the forming valve or girdle band with the silicalemma and occurred by the outward expansion of microfibrils of silica that aligned perpendicularly to the silicalemma. Microfibrils originated from both sides of the “silica lamella,” the first nanostructure formed within the SDV, and several silica species of distinct nanostructure and density resulted, including distinctive inner and outermost silica “coverings” of mature valves/girdle bands and the central and terminal nodules. Not all silica deposition and micromorphogenesis occurred in contact with the expanding silicalemma, but was somehow directed within the SDV cavity, and resulted in the distinct silica layers that lined the raphe fissures and poroids. Following alkaline etching, the inner surfaces of valves/girdle bands, as well as the silica layers lining the raphes, poroids, and slits, were determined to be significantly more resistant to alkaline etching than the exterior surfaces, while the outer silica coating and the nodules were quickly dissolved. The processes of micromorphogenesis must have exerted precise control over the chemical nature of the silica formed at different positions within the SDV and affected the overall structure and function of the diatom wall.
Least Committed basic belief density induced by a multivariate Gaussian pdf

We consider here the case where our knowledge is partial and based on a betting density function which is n-dimensional Gaussian. The explicit formulation of the least committed basic belief density (bbd) of the multivariate Gaussian pdf is provided. Beliefs are then assigned to hyperspheres and the bbd follows a chi2 distribution. An application to model based classification in the joint speed-acceleration feature space is presented
A hemispherical microfluidic channel for the trapping and passive dissipation of microbubbles

In this paper, we present that trapping and dissipating of bubbles in a microfluidic cell culture system can be simultaneously achieved by utilizing curved geometry principles. For this end, a simple and cost-effective method to fabricate a curved hemispherical microfluidic channel is presented. On the basis of an analytical model, the mechanism that the hemispherical well can trap various sizes of bubbles better than the cylindrical well is described, and we present a quantitative comparison of the trapping capabilities of the hemispherical versus conventional cylindrical wells through experiments. The surface tension is another important factor to trap bubbles, which was also verified through the analysis and experiments. In the hemispherical wells, the trapped bubbles were spontaneously dissipated under the flowing condition without using any active source, and we characterized the degassing process by measuring the area of bubbles occupied in the well over time. For an application to a biomedical system, a cell culture chamber was combined with the bubble trapping system, and the performance of the system was verified by culturing HeLa cells with the flowing bubbled culture media. Conclusively, the suggested method demonstrated excellent performance in trapping of microbubbles and dissipation without using any peripheral device, and will be broadly applied in biomedical microfluidic research.
Scalability of an Ad Hoc On-Demand Routing Protocol in Very Large-Scale Mobile Wireless Networks

This article focuses on the performance and scalability study of very large-scale wireless ad hoc networks. As wireless devices become more and more popular, ad hoc networks grow in the number of nodes as well as the complexity of communication among the large number of nodes. However, due to the limitation of simulation technologies, it is either impossible or very hard to investigate the scalability of ad hoc routing protocols in very large-scale wireless networks. In this article, a comprehensive simulation study is conducted of the performance of an on-demand routing protocol on a very large scale, with as many as 50,000 nodes in the network. The authors address the scalability analysis based on various network sizes, node density, traffic load, and mobility. The reasons for packet loss are analyzed and categorized at each network layer. Based on the observations, the authors optimize the parameter selection and try to exhaust the scalability boundary of the on-demand routing protocol for wireless ad hoc networks.
Feature-aware Label Space Dimension Reduction for Multi-label Classification

Label space dimension reduction (LSDR) is an efficient and effective paradigm for multi-label classification with many classes. Existing approaches to LSDR, such as compressive sensing and principal label space transformation, exploit only the label part of the dataset, but not the feature part. In this paper, we propose a novel approach to LSDR that considers both the label and the feature parts. The approach, called conditional principal label space transformation, is based on minimizing an upper bound of the popular Hamming loss. The minimization step of the approach can be carried out efficiently by a simple use of singular value decomposition. In addition, the approach can be extended to a kernelized version that allows the use of sophisticated feature combinations to assist LSDR. The experimental results verify that the proposed approach is more effective than existing ones to LSDR across many real-world datasets.
Tissue engineering with glial cells and a novel biodegradable matrix to promote functional repair following experimental spinal cord injuries

s (presented on major international scientific meetings): Moellers, S. ; Noth, J; Brook, GA: „Assessement of the Biocompatibility of type I Collagen Matrices with Olfactory Nerve Ensheathing cells“, Abstracts of the 6th European Meeting on Glial Cell Function in Health and Disease. Berlin, Germany, September 3-6, 2003, Glia. 2003 Sep;Supp 2:1-84. Poster. Moellers, S; Heschel, I; Lassner, F; Noth, J; Brook, GA: „Three Dimensional type I Collagen Matrices with Olfactory Nerve Ensheathing Cells in Spinal Cord Injury“, Abstracts from the First World Congress on Regenerative Medicine. Leipzig, Germany. October 22-24, 2003. Int J Artif Organs. 2003 Sep;26(9):813-878. Poster + Oral Presentation. Moellers, S; Heschel, I; Noth, J; Brook, GA: „A newly developed orientated collagen type 1 scaffold for use in acute spinal cord injury – cytocompatability and orientated nerve regeneration“, Abstracts from the 7th International Neurotrauma Symposium in Adelaide 12-16 Sept. 2004. Restorative Neurology and Neuroscience. Volume 23, Number 3-4 / 2005. Oral Presentation. Students Travel Grant Award. Moellers, S; Altinova, H; Heschel, I; Noth, J; Brook, G: “Orientated axonal regeneration and functional recovery in acute spinal cord injury using collagen scaffolds and olfactory ensheathing cells”. VII European Meeting on Glial Cell Function in Health and Disease EUROGLIA 2005. Amsterdam, The Netherlands. May 2005. (Oral Presentation)
Yeast One-Hybrid Gγ Recruitment System for Identification of Protein Lipidation Motifs

Fatty acids and isoprenoids can be covalently attached to a variety of proteins. These lipid modifications regulate protein structure, localization and function. Here, we describe a yeast one-hybrid approach based on the Gγ recruitment system that is useful for identifying sequence motifs those influence lipid modification to recruit proteins to the plasma membrane. Our approach facilitates the isolation of yeast cells expressing lipid-modified proteins via a simple and easy growth selection assay utilizing G-protein signaling that induces diploid formation. In the current study, we selected the N-terminal sequence of Gα subunits as a model case to investigate dual lipid modification, i.e., myristoylation and palmitoylation, a modification that is widely conserved from yeast to higher eukaryotes. Our results suggest that both lipid modifications are required for restoration of G-protein signaling. Although we could not differentiate between myristoylation and palmitoylation, N-terminal position 7 and 8 play some critical role. Moreover, we tested the preference for specific amino-acid residues at position 7 and 8 using library-based screening. This new approach will be useful to explore protein-lipid associations and to determine the corresponding sequence motifs.
Sparse Online Learning via Truncated Gradient

We propose a general method called truncated gradient to induce sparsity in the weights of online-learning algorithms with convex loss. This method has several essential properties. First, the degree of sparsity is continuous—a parameter controls the rate of sparsification from no sparsification to total sparsification. Second, the approach is theoretically motivated, and an instance of it can be regarded as an online counterpart of the popular L1-regularization method in the batch setting. We prove small rates of sparsification result in only small additional regret with respect to typical online-learning guarantees. Finally, the approach works well empirically. We apply it to several datasets and find for datasets with large numbers of features, substantial sparsity is discoverable.
Approach for Arabic Handwritten Image Processing: Case of Text Detection in Degraded Documents

study presents a new approach for processing of Arabic handwritten documents based on the extraction of characteristics and mechanisms involved in the process of human visual perception. The architecture which has been developed is based on the concept of multi-agent systems, allowing the integration of different stages of character recognition process in a cooperative way. This is illustrated using as example the prepossessing of binary noisy document. Therefore, a method was proposed, in order to distinguish between text and non-text components, using a new geometric primitives extracted from the analysis of the characteristics of Arabic script. Results show pixel-level precision and recall respectively of 98% and 93% for noise removal. This proves the effectiveness of the proposed approach in processing degraded documents and, consequently, improving the recognition performance.
DeepDive: Transparently Identifying and Managing Performance Interference in Virtualized Environments

We describe the design and implementation of Deep-Dive, a system for transparently identifying and managing performance interference between virtual machines (VMs) co-located on the same physical machine in Infrastructure-as-a-Service cloud environments. DeepDive successfully addresses several important challenges, including the lack of performance information from applications, and the large overhead of detailed interference analysis. We first show that it is possible to use easily-obtainable, low-level metrics to clearly discern when interference is occurring and what resource is causing it. Next, using realistic workloads, we show that DeepDive quickly learns about interference across co-located VMs. Finally, we show DeepDive's ability to deal efficiently with interference when it is detected, by using a low-overhead approach to identifying a VM placement that alleviates interference.
Modular components for network address translation

We present a general-purpose toolkit for network address translation in Click, a modular, component-based networking system. Network address translation, or NAT, was designed to allow disparate address realms to communicate. The components of our toolkit can be combined in a variety of ways to implement this task and many others, including some that, superficially, have nothing to do with address translation. Our NAT components are more flexible than monolithic alternatives. They concern themselves solely with address translation; separate components handle related functions, such as classification. The user can choose where network address translation takes place in relation to other router functions; combine multiple translators in a single configuration; and use NAT in unintended, surprising ways. We describe our design approach, demonstrate its flexibility by presenting a range of examples of its use, and evaluate its performance. Our components have been in use in a production environment for over eighteen months.
POTENTIAL APPLICATIONS OF NONWOVEN POLYMER MATS – REVIEW

Nonwoven polymer mats with fibre diameters in the nanometer and micrometer range are distinguished for their high porosity with very small pore size, interconnectivity and controllable mesh thickness. These characteristics associated to the easy way to obtain the polymer nanofibres and a large surface area to volume ratio make the nonwoven fiber mats a suitable material for different applications, such as biosensor, electronic materials and filters. Polymer nanofibers mats are being considered for use in biomedical applications, including the production of artificial blood vessels, scaffolds for engineered tissues, wound dressings.
MST50 is involved in multiple MAP kinase signaling pathways in Magnaporthe oryzae

Appressorium formation plays a critical role in Magnaporthe oryzae. Mst50 is an adapter protein of the Mst11-Mst7-Pmk1 cascade that is essential for appressorium formation. To further characterize its functions, affinity purification was used to identify Mst50-interacting proteins (MIPs) in this study. Two of the MIPs are Mst11 and Mst7 that are known to interact with Mst50 for Pmk1 activation. Surprisingly, two other MIPs are Mck1 and Mkk2 that are the upstream kinases of the Mps1 pathway. Domain deletion analysis showed that the sterile alpha-motif of Mst50 but not the Ras-association domain was important for its interaction with Mck1 and responses to cell wall and oxidative stresses. The mst50 mutant was reduced in Mps1 activation under stress conditions. MIP11 encodes a RACK1 protein that also interacted with Mck1. Deletion of MIP11 resulted in defects in cell wall integrity, Mps1 phosphorylation and plant infection. Furthermore, Mst50 interacted with histidine kinase Hik1, and the mst50 mutant was reduced in Osm1 phosphorylation. These results indicated that Mst50 is involved in all three MAPK pathways in M. oryzae although its functions differ in each pathway. Several MIPs are conserved hypothetical proteins and may be involved in responses to various signals and crosstalk among signaling pathways.