Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimisation of plasma sprayed hydroxyapatite coatings

Hydroxyapatite, (HA), is a calcium phosphate bioceramic material which has an almost identical chemical composition to that of the mineral component of bone. Its biocompatibility and osteoconductivity have led to its use in a wide range of applications in both dentistry and orthopaedics. One such application is for the uncemented fixation of implants. The plasma spraying technique, a thermal spray process, is the most commonly used method for the production of HA coatings. This process is a complicated one, affected by a large number of parameters. Due to this complexity, the process – property – structure relationship is poorly understood. The present work aims to clarify this relationship and use the knowledge gained to develop a novel bi-layer coating. Statistically designed experiments (DOE) were used to determine the effect of five process parameters (factors), Current, Gas Flow Rate, Powder Feed Rate, Spray Distance and Carrier Gas Flow Rate, on the coating properties. A screening design was first carried out to gain an initial understanding of the process. This was followed by a detailed Response Surface Methodology (RSM) experiment. Five properties (responses) were examined, crystallinity, purity, roughness, porosity and thickness. Models describing the effects of the variables on these coating properties were then developed. The developed models were optimised using two separate optimisation criteria to develop a novel bi-layered coating, designed to provide improved in vivo performance over current HA coatings. The performance of this novel coating was evaluated using a cell culture experiment. Statistically significant models were developed in this work for each of the measured responses. All factors were found to have a significant effect on the measured coating responses. Current, Gas Flow Rate, Spray Distance and the Current * Spray Distance interaction were found to be the parameters with greatest effect on the coating properties. Analysis of the bi-layered coating produced indicates that improved biological performance has been achieved.
The Video Head Impulse Test and the Influence of Daily Use of Spectacles to Correct a Refractive Error

Objective To determine the influence of daily use of spectacles to correct a refractive error, on the vestibulo-ocular reflex (VOR) gain measured with the video head impulse test (vHIT). Study design This prospective study enrolled subjects between 18 and 80 years old with and without a refractive error. Subjects were classified into three groups: (1) contact lenses, (2) spectacles, and (3) control group without visual impairment. Exclusion criteria comprised ophthalmic pathology, history of vestibular disorders, and alternated use of spectacles and contact lenses in daily life. Corrective spectacles were removed seconds before testing. One examiner performed all vHIT’s under standardized circumstances using the EyeSeeCam system. This system calculated the horizontal VOR gain for rightward and leftward head rotations separately. Results No statistically significant difference was found in VOR gain between the control group (n = 16), spectacles group (n = 48), and contact lenses group (n = 15) (p = 0.111). Both the spectacles group and contact lenses group showed no statistically significant correlation between VOR gain and amount of refractive error, for rightwards (p = 0.071) and leftwards (p = 0.716) head rotations. There was no statistical significant difference in VOR gain between testing monocularly or binocularly (p = 0.132) and between testing with or without wearing contact lenses (p = 0.800). Conclusion In this study, VOR gain was not influenced by wearing corrective spectacles or contact lenses on a daily basis. Based on this study, no corrective measures are necessary when performing the vHIT on subjects with a refractive error, regardless of the way of correction.
Study on Glass Defect Inspection Based on Projecting Grating Method

An inspection method based on transmission-mode projecting grating for glass defects has been proposed and verified by experiments. Sinusoidal fringe on the glass is collected using a linear CCD. The fringe curve can be corrected through the Fourier series fitting method to eliminate the constant non-uniformity of the light intensity of a light-emitting diode. The one-dimensional Fourier transform is applied to the corrected fringe curve; the Gaussian band-reject filter is designed to attenuate the first-order spectrum, and a Gaussian band-pass filter having the opposite characteristic attenuates other frequencies (except those in the first-order spectrum). In this way, the defect image and the phase map are obtained. A double threshold segmentation algorithm is applied to get a ternary-value image of the defects, with judgment of the defects’ size and position based on the connected region. Based on the phase map, a calculation method of diopters is proposed. A method for defect type judgment is raised. The results show that the resolution of the real-time testing can reach 0.1 mm × 0.1 mm.
Capturing a black cat in shade: the past and present of Retinex color appearance models

As a part of the Symposium 'Retinex at 40', this paper recounts the research on capturing real-life scenes, calculating appearances and rendering sensations on film, and other limited dynamic-range media. It describes: the first patents, a hardware display used in Land's Ives Medal Address in 1968, the first computer simulations using 20 by 24 pixel arrays, psychophysical experiments and computational models of color constancy and dynamic range compression and the Frankle-McCann computationally efficient Retinex image processing of 512 by 512 images. It will include several modifications of the approach including recent modifications and gamut-mapping applications. This paper emphasizes the need for parallel studies of psychophysical measurements of human vision and computational models of imaging systems.
Transcripts of damaged genes in the brain during cerebral oxidative stress

Recent studies using ischemia/reperfusion models of brain injury suggest that there is a period of time during which the formation of oxidative DNA lesions (ODLs) exceeds removal. This interval is a window of opportunity in which to study the effect of gene damage on gene expression in the brain, because the presence of excessive ODLs mimics a deficiency in gene repair, which has been shown to be associated with neurological disorders. Evidence from studies using similar models indicates that expression of faulty transcripts from ODL‐infested genes and non‐sense mutation in repaired genes occur before the process of cell death. Preventing the formation of ODLs and enhancing ODL repair are shown to increase the expression of intact transcripts and attenuate cell death. Understanding this mechanism could lead to the development of therapeutic techniques (physiologic, pharmacological, and/or genomic) that can enhance recovery. © 2002 Wiley‐Liss, Inc.
Learning ensemble of decision trees through multifactorial genetic programming

Genetic programming (GP) has received considerable successes in machine learning tasks such as prediction and classification. Ensemble learning enables the collaboration of multiple classifiers and effectively improves the classification accuracy. Learning an ensemble of classifiers with GP can simply be achieved by repeated runs of GP; however, the computational cost will be multiplied as well. Recently, multifactorial evolution was proposed to concurrently solve multiple problems with a single population. This study utilizes the multifactorial evolution and designs a multifactorial genetic programming (MFGP) for efficiently learning an ensemble of decision trees. In the MFGP, each task is associated with one run of GP. The multifactorial evolution enables MFGP to evolve multiple GP classifiers for an ensemble in a single run, which saves a substantial amount of computational cost at repeated runs of GP. The experimental results show that MFGP can learn an ensemble with comparable accuracy, precision, and recall to conventional ensemble learning methods, whereas MFGP requires much less computational resource. The satisfactory outcomes validate the advantages of MFGP in ensemble learning.
Molecular Memories Based on a CMOS Platform

Hybrid complementary metal oxide semiconductor (CMOS)/molecular memory devices are based on a dynamic random-access memory (DRAM) architecture, are fast, have high density, and exhibit low power consumption. These devices use a well-characterized charge storage mechanism to store information based on the intrinsic properties of molecules attached to a CMOS platform. The molecules are designed in a rational way to have known electrical properties and can be incorporated into CMOS devices with only minor modification of existing fabrication methods. Each memory element contains a monolayer of molecules (typically 100,000–1,000,000) to store charge; this process yields a structure that has many times the charge density of a typical DRAM capacitor, obviating the necessity for a trench or stacked capacitor geometry. The magnitude of voltage required to remove each electron is quantized (typically a few hundred millivolts per state), making it much easier to put molecules in a known state and to detect that state with low-power operation. Existing devices have charge retention times that are >1000 times that of semiconductors, and nonvolatile strategies based on simple modifications of existing systems are possible. All of these devices are ultimately scalable to molecular dimensions and will enable the production of memory products as small as state-of-the-art lithography will allow.
Conformational Changes during Pore Formation by the Perforin-Related Protein Pleurotolysin

Membrane attack complex/perforin-like (MACPF) proteins comprise the largest superfamily of pore-forming proteins, playing crucial roles in immunity and pathogenesis. Soluble monomers assemble into large transmembrane pores via conformational transitions that remain to be structurally and mechanistically characterised. Here we present an 11 Å resolution cryo-electron microscopy (cryo-EM) structure of the two-part, fungal toxin Pleurotolysin (Ply), together with crystal structures of both components (the lipid binding PlyA protein and the pore-forming MACPF component PlyB). These data reveal a 13-fold pore 80 Å in diameter and 100 Å in height, with each subunit comprised of a PlyB molecule atop a membrane bound dimer of PlyA. The resolution of the EM map, together with biophysical and computational experiments, allowed confident assignment of subdomains in a MACPF pore assembly. The major conformational changes in PlyB are a ∼70° opening of the bent and distorted central β-sheet of the MACPF domain, accompanied by extrusion and refolding of two α-helical regions into transmembrane β-hairpins (TMH1 and TMH2). We determined the structures of three different disulphide bond-trapped prepore intermediates. Analysis of these data by molecular modelling and flexible fitting allows us to generate a potential trajectory of β-sheet unbending. The results suggest that MACPF conformational change is triggered through disruption of the interface between a conserved helix-turn-helix motif and the top of TMH2. Following their release we propose that the transmembrane regions assemble into β-hairpins via top down zippering of backbone hydrogen bonds to form the membrane-inserted β-barrel. The intermediate structures of the MACPF domain during refolding into the β-barrel pore establish a structural paradigm for the transition from soluble monomer to pore, which may be conserved across the whole superfamily. The TMH2 region is critical for the release of both TMH clusters, suggesting why this region is targeted by endogenous inhibitors of MACPF function.
Shift-Reduce Constituent Parsing with Neural Lookahead Features

Transition-based models can be fast and accurate for constituent parsing. Compared with chart-based models, they leverage richer features by extracting history information from a parser stack, which consists of a sequence of non-local constituents. On the other hand, during incremental parsing, constituent information on the right hand side of the current word is not utilized, which is a relative weakness of shift-reduce parsing. To address this limitation, we leverage a fast neural model to extract lookahead features. In particular, we build a bidirectional LSTM model, which leverages full sentence information to predict the hierarchy of constituents that each word starts and ends. The results are then passed to a strong transition-based constituent parser as lookahead features. The resulting parser gives 1.3% absolute improvement in WSJ and 2.3% in CTB compared to the baseline, giving the highest reported accuracies for fully-supervised parsing.
New Feature Subset Selection Algorithm Using Class Association Rules Mining

A new feature subset selection algorithm using class association rules mining is proposed in this paper. Firstly, the algorithm mines rules with features as antecedences and class attributes as consequences. Then, it selects the strongest rules one by one, and all the rules’ antecedences make up of the selected feature subset. Experimental results on 10 real data sets show that the proposed algorithm produces a remarkable advantage in enormously reducing the number of the features while keeping quite high classification accuracy compared with other existing seven algorithms. This algorithm can offer an available preprocess technique for pattern recognition, machine learning and data mining.
Emergency department management of mild traumatic brain injury in the USA

Objective: To describe the emergency department (ED) management of isolated mild traumatic brain injury (TBI) in the USA and to examine variation in care across age and insurance types. Methods: A secondary analysis of ED visits for isolated mild TBI in the National Hospital Ambulatory Medical Care Survey 1998–2000 was performed. Mild TBI was defined by International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9) codes for skull fracture, concussion, intracranial injury (unspecified), and head injury (unspecified). Available ED care variables were analysed by patient age and insurance categories using multivariate logistic regression. Results: The incidence of isolated mild TBI cases attending ED was 153 296 per year, or 56.4/100 000 people. Of the patients with isolated mild TBI, 44.3% underwent computed tomography, 23.9% underwent other non-extremity, non-chest x rays, 17.1% received wound care and 14.1% received intravenous fluids. However, only 43.8% had an assessment of pain. Of those with documented pain, only 45.5% received analgesics in the ED. Nearly 38% were discharged without recommendations for specific follow up. Several aspects of ED care varied by age but not by insurance type. Conclusion: Substantial ED resources are devoted to the care of isolated mild TBI. The present study identified deficiencies in and variation around several important aspects of ED care. The development of guidelines specific for mild TBI could reduce variation and improve emergency care for this injury.
Rice Prices and Income Distribution in Thailand: A Non-parametric Analysis

Rice is a staple crop in Thailand, significantly entering both household production and consumption. This paper examines the effect of rice prices on the distribution of real income across households, taking into account household characteristics and geographical location. The data set is a large-scale survey of 11,893 households. Simple nonparametric techniques for regression and density estimation are used. These methods depend on few assumptions and generate flexible graphical results that are directly informative about the problem at hand. The main results are that higher rice prices should benefit all rural households, but the largest benefits accrue to rural households in the middle of the income distribution. Copyright 1989 by Royal Economic Society.
The Design for the Wall Street Journal-based CSR Corpus

The DARPA Spoken Language System (SLS) community has long taken a leadership position in designing, implementing, and globally distributing significant speech corpora widely used for advancing speech recognition research. The Wall Street Journal (WSJ) CSR Corpus described here is the newest addition to this valuable set of resources. In contrast to previous corpora, the WSJ corpus will provide DARPA its first general-purpose English, large vocabulary, natural language, high perplexity, corpus containing significant quantities of both speech data (400 hrs.) and text data (47M words), thereby providing a means to integrate speech recognition and natural language processing in application domains with high potential practical value. This paper presents the motivating goals, acoustic data design, text processing steps, lexicons, and testing paradigms incorporated into the multi-faceted WSJ CSR Corpus.
Bin1 Interacts with and Restrains the DNA End-Binding Protein Complex Ku

The Bin1 gene encodes a BAR adapter protein that suppresses cancer by poorly defined mechanisms. In an effort to gain insights, we identified cellular proteins that formed biochemical complexes with Bin1 protein. Here we report that Bin1 physically binds to Ku, a DNA end-binding protein that functions in telomere maintenance, apoptosis, and DNA repair after genotoxic stress. Both Ku70 and Ku80 were purified from human and murine cell extracts using the Bin1 BAR domain as an affinity matrix. A BAR domain mutation which destroys antioncogenic activity completely abolished Ku binding, supporting functional relevance. To further evaluate its meaning, we investigated interactions between the Bin1 homolog hob1+ and the Ku homologs pku70+ and pku80+ in fission yeast. Notably, deleting pku70+ or pku80+ relieved the survival defect displayed by hob1Δ cells after treatment with the DNA damaging agent phleomycin, suggesting that hob1+ may restrain Ku. Consistent with this notion, telomere length was altered in hob1Δ cells. The potential relevance of Bin1-Ku interaction to cancer are discussed in light of these findings.
On deriving unknown vulnerabilities from zero-day polymorphic and metamorphic worm exploits

Vulnerabilities that allow worms to hijack the control flow of each host that they spread to are typically discovered months before the worm outbreak, but are also typically discovered by third party researchers. A determined attacker could discover vulnerabilities as easily and create zero-day worms for vulnerabilities unknown to network defenses. It is important for an analysis tool to be able to generalize from a new exploit observed and derive protection for the vulnerability.Many researchers have observed that certain predicates of the exploit vector must be present for the exploit to work and that therefore these predicates place a limit on the amount of polymorphism and metamorphism available to the attacker. We formalize this idea and subject it to quantitative analysis with a symbolic execution tool called DACODA. Using DACODA we provide an empirical analysis of 14 exploits (seven of them actual worms or attacks from the Internet, caught by Minos with no prior knowledge of the vulnerabilities and no false positives observed over a period of six months) for four operating systems.Evaluation of our results in the light of these two models leads us to conclude that 1) single contiguous byte string signatures are not effective for content filtering, and token-based byte string signatures composed of smaller substrings are only semantically rich enough to be effective for content filtering if the vulnerability lies in a part of a protocol that is not commonly used, and that 2) practical exploit analysis must account for multiple processes, multithreading, and kernel processing of network data necessitating a focus on primitives instead of vulnerabilities.
Role of exogenous arginine vasopressin in the management of catecholamine-refractory septic shock.

CRITICALCARENURSE Vol 26, No. 6, DECEMBER 2006 17 Christopher S. Lee is a doctoral student at the University of Pennsylvania School of Nursing in Philadelphia. In this article, I examine the role of exogenous arginine vasopressin in catecholamine-refractory septic shock. I review normal physiological mechanisms of endogenous vasopressin, describe clinical benefits and adverse reactions associated with use of exogenous arginine vasopressin, and provide recommendations for nursing care of patients who require the exogenous form.
Developing a Bayesian Network Model Based on a State and Transition Model for Software Defect Detection

This paper describes a Bayesian Network model-to diagnose the causes-effect of software defect detection in the process of software testing. The aim is to use the BN model to identify defective software modules for efficient software test in order to improve the quality of a software system. It can also be used as a decision tool to assist software developers to determine defect priority levels for each phase of a software development project. The BN tool can provide a cause-effect relationship between the software defects found in each phase and other factors affecting software defect detection in software testing. First, we build a State and Transition Model that is used to provide a simple framework for integrating knowledge about software defect detection and various factors. Second, we convert the State and Transition Model into a Bayesian Network model. Third, the probabilities for the BN model are determined through the knowledge of software experts and previous software development projects or phases. Last, we observe the interactions among the variables and allow for prediction of effects of external manipulation. We believe that both STM and BN models can be used as very practical tools for predicting software defects and reliability in varying software development lifecycles.
Proximity and duration in temporary organisations

This study focuses on the effects of duration and proximity on collaborative outcomes in temporary organisations. With regard to proximity, it distinguishes between geographical and organisational proximity. The study is based on a regression analysis of an original dataset of 147 temporary organisations in the Netherlands. The results indicate that face-to face contact has a positive impact on the collaborative outcome, whereas the geographical distance between organisations does not seem to matter. Organisations with a high level of organisational proximity are also likely to achieve their goals better than organisations that are rather dissimilar. Furthermore, duration positively influences the relation between face-to-face contacts and goal attainment. However, it appears that duration as such has a negative influence on performance. This study shows that there are important differences between IORs that have to be taken into account since they matter for the level of goal achievement of a collaborative effort.