Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of Adult Retinal Precursor Cell Behaviour In Response To Soluble Factors And Varying Substrate Stiffness in Two and Three Dimensional Scaffolds

We have studied the factors that are important for producing functional retinal neurons from adult derived retinal stem and progenitor cells (RPCs) investigating the role of substrate stiffness or soluble factors in 2D and 3D culture on the differentiation and survival of RPCs. RPCs were cultured on agarose scaffolds modified with the adhesive peptides of varying stiffness. We observed that cell survival in the 0.75% matrix was greater in 3D than in 2D by a factor of 50% irrespective of the time in culture. We observed the presence of photoreceptors exclusively in 0.75% agarose, while the stiffer matrices (1.75%) led to retinal ganglion cell and glial cell differentiation with no significant difference in the differentiation profiles when cells were cultured in 2D vs. 3D. These data indicate that substrate stiffness, more than growth factors, has a significant impact on both the survival and differentiation profile of retinal precursor
Tensile properties of ag-EVOH electrospinning nanofiber mats for large muscle scaffolds

Abstract Large muscle defect negatively influences people’s life, the common treatment is muscle transplantation but limited by donor source, large area wound, etc. Therefore, a muscle tissue scaffold with superimposed vascular network was developed. For ensuring the performance of fascia layer which alternated by poly(ethylene-co-vinyl alcohol) (EVOH) nanofiber mats encapsulated with Ag, the mechanical properties and water vapor transmission of different samples (7.5%, 10%, 12.5% EVOH solution densities with 0.02, 0.05, 0.08 g/ml of Ag, respectively) were mainly discussed. Meanwhile, the main parameters (voltage, tip-to-collector distance, solution density, concentration of Ag) were compared to find their influence on fabricating nanofibers.
Olfactory Function Assessment of Blind Subjects Using the Sniffin’ Sticks Test

Objective In recent years, a growing number of studies have focused on the olfactory abilities of blind individuals as well as their tactile and auditory senses. In this study, we aimed to investigate possible alterations in the sense of smell in early- and late-blind subjects as compared with sighted controls, using a Sniffin’ Sticks test battery. Study Design Prospective clinical study. Setting Tertiary referral center. Subjects and Methods A total of 66 subjects were included in the study. The subjects were divided into 2 groups: blind subjects—who were then subgrouped as subjects with congenital blindness (n = 17) and those with acquired blindness (n = 16)—and sighted subjects (n = 33). We compared both congenitally and acquired blind subjects with sighted counterparts using the Sniffin’ Sticks test for odor threshold, odor discrimination, odor identification, and total odor scores. Results The blind subjects were more successful than their sighted counterparts in odor discrimination and odor threshold tasks. There was no statistically significant difference between the blind participants and the sighted individuals in terms of odor identification value. Another important finding was that the difference between individuals with congenital blindness and those with acquired blindness was not significant in any of the parameters. Conclusion This finding may suggest that odor discrimination and odor threshold in blind people were superior to those of controls. There was no difference in any of the results of tasks among congenital and acquired blind subjects.
Quaternion Gauss Maps and Optimal Framings of Curves and Surfaces

We propose a general paradigm for generating optimal coordinate frame fields that may be exploited to annotate and display curves and surfaces. Parallel-transport framings, which work well for open curves, generally fail to have desirable properties for cyclic curves and for surfaces. We suggest that minimal quaternion measure provides an appropriate generalization of parallel transport. Our fundamental tool is the “quaternion Gauss map,” a generalization to quaternion space of the tangent map for curves and of the Gauss map for surfaces. The quaternion Gauss map takes 3D coordinate frame fields for curves and surfaces into corresponding curves and surfaces constrained to the space of possible orientations in quaternion space. Standard optimization tools provide application-specific means of choosing optimal, e.g., lengthor area-minimizing, quaternion frame fields in this constrained space. We observe that some structures may have distinct classes of minimal quaternion framings, e.g, one disconnected from its quaternion reflection, and another that continuously includes its own quaternion reflection. We suggest an effective method for visualizing the geometry of quaternion maps that is used throughout. Quaternion derivations of the general moving-frame equations for both curves and surfaces are given; these equations are the quaternion analogs of the Frenet and Weingarten equations, respectively. We present examples of results of the suggested optimization procedures and the corresponding tubings of space curves and sets of frames for surfaces and surface patches.
Experiments on real-time 1-Gb/s packet transmission using MLD-based signal detection in MIMO-OFDM broadband radio access

This paper presents experimental results on real-time packet transmission of greater than 1 Gb/s using 4-by-4 multiple-input-multiple-output (MIMO) multiplexing and maximum-likelihood detection (MLD)-based signal detection with a decreased level of computational complexity in orthogonal frequency-division multiplexing (OFDM) radio access. We apply our previous algorithm called adaptive selection of surviving symbol replica candidates (ASESS) based on the maximum reliability in MLD employing QR decomposition and the M-algorithm (QRM-MLD) to reduce the extremely high level of computational complexity in the conventional MLD. The experimental results using multipath fading simulators are in good agreement with the computer simulation results. The loss in the required received signal energy per bit-to-background noise power spectrum density ratio (Eb/N0) is suppressed to within approximately 1-2 dB. Therefore, through experiments, we demonstrate that the QRM-MLD employing ASESS is very beneficial in reducing the influence of hardware implementation loss, as well as in decreasing the required received Eb/N0. We further show that the extremely high-speed real-time packet transmission of greater than 1 Gb/s in a 100-MHz channel bandwidth (i.e., 10 bit/s/Hz) is achieved at the average received Eb/N0 per receiver antenna of approximately 12 dB using 16QAM modulation and turbo coding with the coding rate of 8/9 in 4-by-4 MIMO multiplexing
Collaboration analysis: Joint resolution of problems in global supply networks

Many severe and costly supply network disruptions have been documented in the academic and business literatures, and the issue is receiving increased coverage and consideration by scholars and practitioners. It is widely acknowledged that recent trends in supply network management, such as greater global interconnectivity, make firms more susceptible to disruption risk than ever before. Further, research has demonstrated that firms are generally not able to quickly recover from the negative economic impacts associated with supply disruptions. Passive acceptance of disruptions is not a viable option; therefore, firms face a pressing need to develop superior disruption risk management capabilities. Supply network risk management has been defined as the management of external and supply network risk through a coordinated approach among supply network members to reduce vulnerability in the supply chain. Today's global manufacturing networks are complex socio-technical systems, which require socio-technical strategies for managing disruption risks. While the extant research heavily focuses on `hard' technical strategies such as second sourcing and inventory management, 'soft' socio strategies have received minimal attention. This chapter highlights socio factors such as relational closeness that are also crucial for supply partners to jointly resolve problems and contributes to the literature on disruption risk management by identifying associations between specific characteristics of relationships between partners, effective risk identification and joint problem resolution. Specifically, the chapter focuses on the dyadic relationships between a global manufacturing firm and its first tier suppliers. This dyad is the first key link in the supply network and the research conclusions may be applied to other dyadic links in the global network of suppliers.
A novel butyrolactone derivative inhibited smooth muscle cell migration and proliferation and maintained endothelial cell functions through selectively affecting Na, K‐ATPase activity and mitochondria membrane potential during in vitro angiogenesis

We have found that 3‐benzyl‐5‐((2‐nitrophenoxy) methyl)–dihydrofuran ‐2(3H)‐one (3BDO), could effectively suppress human umbilical vascular endothelial cell (HUVEC) apoptosis induced by deprivation of fibroblast growth factor‐2 and serum. Here, our purpose was to investigate whether 3BDO could modulate angiogenesis and its possible acting mechanism. The effect of 3BDO on angiogenesis was investigated by capillary‐like tubule formation and rat aortic ring assay. Proliferation and migration of cells were detected by counting living cell number and scraping cell monolayer, respectively. Na, K‐ATPase activity was measured spectrophotometrically. Mitochondrial membrane potential was analyzed using tetramethylrhodamine methylester fluorescence by confocal microscopy. Our results showed that 3BDO inhibited migration and proliferation of vascular smooth muscle cells (VSMCs), but maintained migration and tubule formation of HUVECs. In HUVECs, 3BDO inhibited Na, K‐ATPase activity, but had no effect on mitochondria membrane potential. In VSMCs, it did not affect Na, K‐ATPase activity, but depressed mitochondria membrane potential obviously. The data showed that 3BDO had selective effects on HUVECs and VSMCs, it might perform its role through the selective effects on the activity of Na, K‐ATPase and the mitochondria membrane potential in HUVECs and VSMCs. J. Cell. Biochem. 104: 2123–2130, 2008. © 2008 Wiley‐Liss, Inc.
Edward Jenner and the History of Smallpox and Vaccination

or many centuries, smallpox devastated mankind. In modern times we do not have to worry about it thanks to the remarkable work of Edward Jenner and later de-velopments from his endeavors. With the rapid pace of vaccine development in recent decades, the historic origins of immunization are often forgot-ten. Unfortunately, since the attack on the World Trade Center on September 11, 2001, the threat of biological warfare and bioterrorism has reemerged. Smallpox has been identified as a possible agent of bioter-rorism (1). It seems prudent to review the history of a disease known to few people in the 21st century. Edward Jenner (Figure 1) is well known around the world for his innovative contri-bution to immunization and the ultimate eradication of smallpox (2). Jenner’s work is widely regarded as the foundation of im-munology—despite the fact that he was neither the first to suggest that infection with cowpox conferred specific immunity to smallpox nor the first to attempt cowpox inoculation for this purpose.SMALLPOX: THE ORIGIN OF A DISEASEThe origin of smallpox as a natural dis-ease is lost in prehistory. It is believed to have appeared around 10,000
Characteristics of Ti6Al4V Powders Recycled from Turnings via the HDH Technique

The objective of this research is for Ti6Al4V alloy turnings, generated during the machining of implants, to produce powders for the fabrication of Ti base coating via the cold spray method. In order to decrease the cost of powder production and increase the recycling rate of the turnings, the hydrogenation-dehydrogenation (HDH) process has been utilised. The HDH process consists of the following sequence: surface conditioning of the turnings, hydrogenation, ball milling (for powder production), and dehydrogenation. Afterwards, the properties of the recycled powder were analysed via phase, chemical, and morphological examinations, and size and flowability measurements. Usability of the powder in additive manufacturing applications has been evaluated via examining the characteristics of the deposit produced from this powder by the cold spray method. In short, promising results were obtained regarding the potential of the recycled powders in additive manufacturing after making minor adjustments in the HDH process.
Importin-β Family Members Mediate Alpharetrovirus Gag Nuclear Entry via Interactions with Matrix and Nucleocapsid

ABSTRACT The retroviral Gag polyprotein orchestrates the assembly and release of virus particles from infected cells. We previously reported that nuclear transport of the Rous sarcoma virus (RSV) Gag protein is intrinsic to the virus assembly pathway. To identify cis- and trans-acting factors governing nucleocytoplasmic trafficking, we developed novel vectors to express regions of Gag in Saccharomyces cerevisiae. The localization of Gag proteins was examined in the wild type and in mutant strains deficient in members of the importin-β family. We confirmed the Crm1p dependence of the previously identified Gag p10 nuclear export signal. The known nuclear localization signal (NLS) in MA (matrix) was also functional in S. cerevisiae, and additionally we discovered a novel NLS within the NC (nucleocapsid) domain of Gag. MA utilizes Kap120p and Mtr10p import receptors while nuclear entry of NC involves the classical importin-α/β (Kap60p/95p) pathway. NC also possesses nuclear targeting activity in avian cells and contains the primary signal for the import of the Gag polyprotein. Thus, the nucleocytoplasmic dynamics of RSV Gag depend upon the counterbalance of Crm1p-mediated export with two independent NLSs, each interacting with distinct nuclear import factors.
Apolipoprotein E inhibition of vascular hyperplasia and neointima formation requires inducible nitric oxide synthase Published, JLR Papers in Press, August 1, 2005. DOI 10.1194/jlr.M500177-JLR200

Previous studies have shown apolipoprotein E (apoE) recruitment to medial layers of carotid arteries after vascular injury in vivo and apoE activation of inducible nitric oxide synthase (iNOS) in smooth muscle cells in vitro. This investigation explored the relationship between medial apoE recruitment and iNOS activation in protection against neointimal hyperplasia. ApoE was present in both neointimal-resistant C57BL/6 mice and neointimal-susceptible FVB/N mice 24 h after carotid denudation, but iNOS expression was observed only in the neointimal-resistant C57BL/6 mice. However, iNOS was not observed in apoE-defective C57BL/6 mice. In contrast, overexpression of apoE in FVB/N mice activated iNOS expression in the injured vessels, resulting in protection against neointimal hyperplasia. ApoE and iNOS were colocalized in the medial layer of neointimal-resistant mouse strains. Endothelial denudation of carotid arteries in the iNOS-deficient NOS2−/− mice did not increase neointimal hyperplasia but significantly increased medial thickness and area. The iNOS-specific inhibitor also abrogated the apoE protective effects on vascular response to injury in apoE-overexpressing FVB/N mice. Thus, injury-induced activation of iNOS requires apoE recruitment. Moreover, both apoE and iNOS are necessary for the suppression of cell proliferation, and apoE recruitment without iNOS expression resulted in medial hyperplasia without cell migration to the intima.
Bayesian Perspective-plane (BPP) for Localization

The "perspective-plane" problem proposed in this paper is similar to the "perspective-n-point (PnP)" or "perspective-n-line (PnL)" problems, yet with broader applications and potentials, since planar scenes are more widely available than control points or lines in practice. We address this problem in the Bayesian framework and propose the "Bayesian perspective-plane (BPP)" algorithm, which can deal with more generalized constraints rather than type-specific ones to determine the plane for localization. Computation of the plane normal is formulated as a maximum likelihood problem, and is solved by using the Maximum Likelihood Searching Model (MLS-M). Two searching modes of 2D and 1D are presented. With the computed normal, the plane distance and the position of the object or camera can be computed readily. The BPP algorithm has been tested with real image data by using different types of scene constraints. The 2D and 1D searching modes were illustrated for plane normal computation. The results demonstrate that the algorithm is accurate and generalized for object localization.
Assembling Single-Cell Genomes and Mini-Metagenomes From Chimeric MDA Products

Recent advances in single-cell genomics provide an alternative to largely gene-centric metagenomics studies, enabling whole-genome sequencing of uncultivated bacteria. However, single-cell assembly projects are challenging due to (i) the highly nonuniform read coverage and (ii) a greatly elevated number of chimeric reads and read pairs. While recently developed single-cell assemblers have addressed the former challenge, methods for assembling highly chimeric reads remain poorly explored. We present algorithms for identifying chimeric edges and resolving complex bulges in de Bruijn graphs, which significantly improve single-cell assemblies. We further describe applications of the single-cell assembler SPAdes to a new approach for capturing and sequencing "microbial dark matter" that forms small pools of randomly selected single cells (called a mini-metagenome) and further sequences all genomes from the mini-metagenome at once. On single-cell bacterial datasets, SPAdes improves on the recently developed E+V-SC and IDBA-UD assemblers specifically designed for single-cell sequencing. For standard (cultivated monostrain) datasets, SPAdes also improves on A5, ABySS, CLC, EULER-SR, Ray, SOAPdenovo, and Velvet. Thus, recently developed single-cell assemblers not only enable single-cell sequencing, but also improve on conventional assemblers on their own turf. SPAdes is available for free online download under a GPLv2 license.
Preparation of Hippocampal Brain Slices

This unit presents a procedure for the preparation of acute mammalian hippocampal slices for electrophysiological recording. Although this protocol should not be taken as the only means of making brain slices, it is a widely‐used typical procedure. It is simple and straightforward. It can be used on a variety of mammalian species, though it is discussed here for use in rats.
Applications of the Non-Dominated Sorting Genetic Algorithm (NSGA) in Chemical Reaction Engineering

Abstract Most of the chemical reaction engineering optimization problems encounters more than one objective functions. A considerable amount of research has been reported on the multiobjective optimization of various chemical reactors using various non-dominated sorting genetic algorithms. This is reviewed in this paper. The introduction of the topic is given at the beginning, followed by the description of multi-objective optimization and Pareto set. We have then discussed various non-dominated sorting genetic algorithms and its applications in chemical reaction engineering. Some comments are also made on the future research direction in this area.
A Component-Based Diffusion Model With Structural Diversity for Social Networks

Diffusion on social networks refers to the process where opinions are spread via the connected nodes. Given a set of observed information cascades, one can infer the underlying diffusion process for social network analysis. The independent cascade model (IC model) is a widely adopted diffusion model where a node is assumed to be activated independently by any one of its neighbors. In reality, how a node will be activated also depends on how its neighbors are connected and activated. For instance, the opinions from the neighbors of the same social group are often similar and thus redundant. In this paper, we extend the IC model by considering that: 1) the information coming from the connected neighbors are similar and 2) the underlying redundancy can be modeled using a dynamic structural diversity measure of the neighbors. Our proposed model assumes each node to be activated independently by different communities (or components) of its parent nodes, each weighted by its effective size. An expectation maximization algorithm is derived to infer the model parameters. We compare the performance of the proposed model with the basic IC model and its variants using both synthetic data sets and a real-world data set containing news stories and Web blogs. Our empirical results show that incorporating the community structure of neighbors and the structural diversity measure into the diffusion model significantly improves the accuracy of the model, at the expense of only a reasonable increase in run-time.
Sparsity in machine learning: theory and practice

The thesis explores sparse machine learning algorithms for supervised (classification and regression) and unsupervised (subspace methods) learning. For classification, we review the set covering machine (SCM) and propose new algorithms that directly minimise the SCMs sample compression generalisation error bounds during the training phase. Two of the resulting algorithms are proved to produce optimal or near-optimal solutions with respect to the loss bounds they minimise. One of the SCM loss bounds is shown to be incorrect and a corrected derivation of the sample compression bound is given along with a framework for allowing asymmetrical loss in sample compression risk bounds. In regression, we analyse the kernel matching pursuit (KMP) algorithm and derive a loss bound that takes into account the dual sparse basis vectors. We make connections to a sparse kernel principal components analysis (sparse KPCA) algorithm and bound its future loss using a sample compression argument. This investigation suggests a similar argument for kernel canonical correlation analysis (KCCA) and so the application of a similar sparsity algorithm gives rise to the sparse KCCA algorithm. We also propose a loss bound for sparse KCCA using the novel technique developed for KMP. All of the algorithms and bounds proposed in the thesis are elucidated with experiments.
Preparation and characterisation of ZnO/HAP bioceramics with excellent antibacterial property

ABSTRACT Ultra-long hydroxyapatite (HAP) nanowires have been hydrothermally synthesised using calcium chloride and phosphate sodium as the starting materials, and then, an antimicrobial bioceramics is successfully fabricated using the HAP-based ceramics by a simple interfacial ZnO adhesion procedure. The bioceramics is characterised by X-ray powder diffraction, scanning electron microscopy, and Fourier-transform infrared spectroscopy. The effect of the concentration of alkaline on the crystal phase and morphology of the HAP nanowires as well as sintering temperature on the crystal phase and morphology of the as-prepared bioceramics is investigated. Antimicrobial properties of the bioceramics are also carefully examined. The results show that the length-to-diameter ratio of the HAP nanowires can be well monitored by the alkalinity, and the ZnO@HAP bioceramics exhibited excellent antibacterial activity. Its antibacterial activity can be well controlled by ZnO nanoparticle content packed in the interspace of the ZnO@HAP bioceramics with different porosities obtained at different temperatures.