Miracle-dz/UniFAR-FTUs huggingface dataset:
Hard yet tough CrN/Si3N4 multilayer coatings deposited by the combined deep oscillation magnetron sputtering and pulsed dc magnetron sputtering

Hard yet tough coatings with simultaneously high hardness and toughness represent a new class of high-performance coatings, which are vital for tribological applications due to the enhanced surface/interface properties. In this work, CrN/Si3N4 multilayer coatings with various Si content were reactively deposited by the combined deep oscillation magnetron sputtering and pulsed dc magnetron sputtering. The as-deposited coatings exhibit smooth surface morphology, well-defined nc-CrN/a-Si3N4 interfaces, uniform thickness and highly dense architecture. Microstructure evolution is induced by Si content changing from scaly nanocolumnar to densely packed fibrous grains to tapered crystallites. These features allow the achievement of the increased properties in terms of high hardness of 30.6 GPa, H/E* of 0.099, H/E* of 0.387, elastic recover We of 58.5% and fracture toughness KIC of 3.69MPa·m. Hard yet tough CrN/Si3N4 multilayer coatings show excellent tribological properties by enhanced cooperative deformability through energy dissipation and stress relaxation at well-arranged nc-CrN/a-Si3N4 interfaces to reduce crack initiation and propagation, and adhesion failure, thanks to the enhanced H, H/E*, H/E*, We and KIC. Meanwhile, under limited normal load conditions, uniform tribolayers (Cr2O3, FeO(OH), Fe2O3 and Fe3O4) caused by tribochemical reaction on the worn surface also act to make contributions towards reducing friction and wear as a lubricant.
Development of Evolutionary Method for Optimizing a Roll Forming Process of Aluminum Parts

This paper presents the development of the knowledge-based neural network (KBNN) and genetic algorithm (GA) in modeling and optimization of the roll forming (RF) process of aluminum parts. The idea of a KBNN using multifidelity finite element (FE) models was developed to model the mechanical behaviors of the aluminum sheet. Initially, the less costly but less accurate FE model was used to build the response surface functions for the knowledge path of the KBNN. After that, a small number of the more accurate but expensive finite element analysis (FEA) of the high fidelity FE model were utilized in a multilayer perceptron (MLP) neural network with the prior knowledge to produce the KBNN prediction results. Two powerful optimization algorithms, the Levenberg― Marquadrt (LM) and GA, were applied to train the KBNN. The trained KBNN was used to perform the parametric study for investigating the effects of process parameters on the part quality. After that, the optimization of the process parameters was carried out by employing the combination of the GA and KBNN. The optimization objective was minimizing the overall damage in the aluminum part while keeping the longitudinal strain and spring back angle less than allowable limits to prevent the existence of defects. The modeling and optimization results by using the KBNN and GA were compared with the results from other methods to prove the advantages of the developed one against others.
The Effect of Glass Ceiling on Women Advancement: A Case Study of Financial Institutions in Bangladesh

Glass ceiling, a widely practiced but unrevealed obstacle for the development of women and minorities towards executive and upper level of managerial hierarchy in the organizations. At the present time this issue is drawing more attention from human resource practitioners around the globe. In developed and developing countries, women's empowerment is the burning issue as the economy can reach its peak through the participation of all genders. In Bangladesh also women are engaging more in jobs specifically in the financial sector and contributing to the economy at large volume. But the disparity between male and women participation at the decision-making level raises the question of the presence of a glass ceiling and the factors contributing to the glass ceiling in the financial sector of Bangladesh. Based on the survey by using structured questionnaires from the commercial banks of Dhaka City Corporation, this study explores organizational factors, explicitly the absence of human resource practices responsible for creating glass ceilings and its presence at the workplace. Using factor analysis and multiple regressions among the six factors, the study found five factors have a significant contribution to the presence of glass ceiling and thus creating barriers to women's advancement. The factors include recruitment practices, performance appraisal, promotion policy, maintenance issues and equal employment opportunities. Policy implications are discussed in light of the findings to minimize glass ceiling effect to contribute gender parity, women's advancement and reducing gender discrimination.
Patches Detection and Fusion for 3D Face Cloning.

3D face clones are used in many fields such as video games and Human-Computer Interaction. However, high-resolution sensors generating high quality clones are expensive and not accessible to all. In this paper, we propose to make a fully automated and accurate 3D reconstruction of a face with a low cost RGB-D camera. For each subject, we capture the depth and RGB data of their face in different positions while performing a rotational movement of the head. We fit a 3D Morphable Face Model on each frame to eliminate noise, increase resolution and provide a structured mesh. This type of mesh is a mesh which the semantic and topological structure is known. We propose to only keep the suitable parts of each mesh called Patch. This selection is performed using an error distance and the direction of the normal vectors. To create the 3D face clone, we merge the different patches of each mesh. These patches contain relevant information on the specificity of individuals and lead to the construction of a more accurate clone. We perform quantitative tests by comparing our clone to ground truth and qualitative tests by comparing visual features. These results show that our method outperforms the FaceWarehouse process of Cao et al [2]. This 3D face clone on a structured mesh can be used as pretreatment in applications such as emotion analysis [13] or facial animation.
Transgender Surgery: A Review Article

Gender dysphoria term was introduced in the Diagnostic and Statistical Manual of Mental Disorders-5 in 2013. It is estimated that 0.5-1.3% of the population in the United States of America has gender dysphoria (1). Although it may seem a very new concept, transgender surgery has been done for almost over a century. Surgical treatment of transgender patients is a series of consecutive operations supported with various treatment modalities. The content of these surgical techniques covers multiple complex and challenging operations. Before surgical treatment starts, a long period is necessary for physiological and endocrinological preoperative preparations. Therefore, many specialists perform these surgeries in universities or fully equipped complex utilities, which have all needed specialists. These kinds of surgeries are of interest to many specialties, such as plastic and reconstructive surgery, urology, obstetrics and gynecology, psychiatry, forensic medicine, genetic, and endocrinology. Many countries have authorized the decision to perform these operations in medical centers and committees that include several specialists. In the childhood period, congenital genital abnormalities can be reconstructed but in adulthood, other etiological problems, such as gender dysphoria or trauma, can be treated by these operations. Transgender operations contain two main groups: Male-to-female (MTF) and female-to-male (FTM) surgeries. According to literature, MTF transsexuals are four times more frequent than FTM (2,3). Transsexualism was described by Harry Benjamin in 1966 (4).
Combining Feature Correspondence With Parametric Chamfer Alignment: Hybrid Two-Stage Registration for Ultra-Widefield Retinal Images

We propose a novel hybrid framework for registering retinal images in the presence of extreme geometric distortions that are commonly encountered in ultra-widefield (UWF) fluorescein angiography. Our approach consists of two stages: a feature-based global registration and a vessel-based local refinement. For the global registration, we introduce a modified RANSAC (random sample and consensus) that jointly identifies robust matches between feature keypoints in reference and target images and estimates a polynomial geometric transformation consistent with the identified correspondences. Our RANSAC modification particularly improves feature point matching and the registration in peripheral regions that are most severely impacted by the geometric distortions. The second local refinement stage is formulated in our framework as a parametric chamfer alignment for vessel maps obtained using a deep neural network. Because the complete vessel maps contribute to the chamfer alignment, this approach not only improves registration accuracy but also aligns with clinical practice, where vessels are typically a key focus of examinations. We validate the effectiveness of the proposed framework on a new UWF fluorescein angiography (FA) dataset and on the existing narrow-field FIRE (fundus image registration) dataset and demonstrate that it significantly outperforms prior retinal image registration methods in accuracy. The proposed approach enhances the utility of large sets of longitudinal UWF images by enabling: (a) automatic computation of vessel change metrics such as vessel density and caliber, and (b) standardized and co-registered examination that can better highlight changes of clinical interest to physicians.
Introduction of the VITEK 2 Compact and Implementation of EUCAST Guidelines in a Microbiology Department

The aims of this project were to introduce the VITEK 2 Compact and to implement European Committee Antimicrobial Susceptibility Testing guidelines in a small microbiology department. The VITEK 2 Compact is an automated analyser for the identification and antimicrobial susceptibility testing of bacteria and has been associated with decreased sample turn-around-times, cost savings and improved detection of multi-drug resistant organisms. There are 10 different guidelines for the clinical interpretation of antimicrobial susceptibility data. A national decision was made in 2010 to harmonise susceptibility data reporting in Ireland, by adopting European Committee Antimicrobial Susceptibility Testing guidelines. This will enable the comparison of data between institutions at the patient, national and internationally level. The HSE Change Model was used to guide the change process. A vision for change, aligned with the organisations strong commitment to quality was created along with the key stakeholders. The vision was communicated along with the drivers for change. A plan was developed and implemented which included validation of the new processes and a training program. Mini-successes during the initial stages of the project were celebrated to ensure mainstreaming. Donabedian’s structure, process, outcome model was used for evaluation. Results demonstrated cost savings of €2.90-€10.28 per isolate and reduced turn-around-times of 1-20 hours, depending on organism complexity. Higher scores for external quality assurance samples were achieved in a direct comparison with historical procedures, demonstrating both trainee proficiency and process accuracy. Consumable costs and turn-around times were standardised irrespective of pathogen complexity and resistance. The turn-around-times for healthcare associated infections has been decreased by 20 hours, which has the potential to have a positive impact on infection control in the organisation. The implementation of the VITEK 2 Compact and European Committee Antimicrobial Susceptibility Testing guidelines will also facilitate the application of national guidelines for the control of multi-drug resistant organisms in the department.
A multi-helical ultrasonic imaging approach for the structural health monitoring of cylindrical structures

In the past few years, several efforts have been made to combine guided ultrasonic waves and imaging algorithms such as tomography for detecting and locating damage in complex structures. In this article, we introduce a multi-helical ultrasonic imaging approach for the structural health monitoring of cylindrical structures. An array of permanently installed piezoelectric transducers is used to generate and receive high-order helical guided waves around the cylindrical structure to artificially increase the ray density/resolution without increasing the number of sensors. A probabilistic-based imaging algorithm is used to identify metal loss defects. Experimental tests are carried out on a steel pipe instrumented with six piezoelectric transducers to validate the proposed approach. Three thickness recesses simulating corrosion are considered. Results demonstrate the efficacy of the proposed approach by identifying the simulated damage at the correct locations and qualitatively monitoring damage growth. No attempt is made in this study to quantify the extent of thinning.
Discovering gene regulatory networks of multiple phenotypic groups using dynamic Bayesian networks

Dynamic Bayesian networks (DBNs) can be used for the discovery of gene regulatory networks from time series gene expression data. Here, we suggest a strategy for learning DBNs from gene expression data by employing a Bayesian approach that is scalable to large networks and is targeted at learning models with high predictive accuracy. Our framework can be used to learn DBNs for multiple groups of samples and highlight differences and similarities in their gene regulatory networks. We learn these DBN models based on different structural and parametric assumptions and select the optimal model based on the cross-validated predictive accuracy. We show in simulation studies that our approach is better equipped to prevent overfitting than techniques used in previous studies. We applied the proposed DBN-based classification approach to two time series transcriptomic datasets from the Gene Expression Omnibus database, each comprising data from distinct phenotypic groups of the same tissue type. In the first case, we used DBNs to characterize responders and non-responders to anti-cancer therapy. In the second case, we compared normal to tumor cells of colorectal tissue. The classification accuracy reached by the DBN-based classifier for both datasets was higher than reported previously. For the colorectal cancer dataset, our analysis suggested that GRNs for cancer and normal tissues have a lot of differences, which are most pronounced in the neighborhoods of oncogenes and known cancer tissue markers. The identified differences in gene networks of cancer and normal cells may be used for the discovery of targeted therapies.
Completion methods in thick, multilayered tight gas sands

Completion Methods in Thick Multilayered Tight Gas Sands. (December 2007) Obinna Stavely Ogueri, B.Eng., Federal University of Technology, Owerri Chair of Advisory Committee: Dr. Stephen A. Holditch Tight gas sands, coal-bed methane, and gas shales are commonly called unconventional reservoirs. Tight gas sands (TGS) are often described as formations with an expected average permeability of 0.1mD or less. Gas production rates from TGS reservoirs are usually low due to poor permeability. As such, state-of-the-art technology must be used to economically develop the resource. TGS formations need to be hydraulically fractured in order to enhance the gas production rates. A majority of these reservoirs can be described as thick, multilayered gas systems. Many reservoirs are hundreds of feet thick and some are thousands of feet thick. The technology used to complete and stimulate thick, tight gas reservoirs is quite complex. It is often difficult to determine the optimum completion and stimulating techniques in thick reservoirs. The optimum methods are functions of many parameters, such as depth, pressure, temperature, in-situ stress and the number of layers. In multilayered reservoirs, it is important to include several sand layers in a single completion.
Lightweight ironless-stator PM generators for direct-drive wind turbines.

A permanent-magnet electrical machine that employs lightweight spoked structures for both rotor and stator is described. The stator is ironless so that there is no direct magnetic attraction between rotor and stator. The lightweight structures are sufficient to carry the small forces due to the interaction of the permanent magnet field with the stator winding current. Despite the absence of stator iron and a large airgap, rare-earth magnets are able to create a working flux density of about 0.25 T at the winding. This is sufficient for an effective generator design because the lightweight structures offer the opportunity to build generators of unprecedented diameter. The outcome is a generator that has a mass typically 20-30% of equivalent designs based on iron-cored magnetic circuits, and with efficiency greater than 90%.
Distributed photovoltaic generation in Argentina

In Argentina, renewable energies are promoted as a way of decarbonising the electricity mix and providing reliable energy services. The national goal is to generate 20% of electricity from renewable sources by 2025. However, despite significant natural potential, solar photovoltaic still represents only a small share of Argentina’s total electricity generation. Although this picture may look bleak, a wide range of market segments relating to decentralised photovoltaic generation in Argentina have developed. The general objective of this study is to examine the dynamics that currently enable or constrain the diffusion of distributed photovoltaic systems in Argentina. By applying the Technical Innovation System (TIS) approach, the aim is to understand which functions of the system are strong/weak and how these are influenced by endogenous/exogenous system strengths and weaknesses. To that end, a mixed method research strategy is applied. The exploratory sequential research design allows first to explore system strengths and weaknesses based on qualitative approaches, and then to further analyse the contextual embeddedness and the level of importance of the identified variables using quantitative survey instruments. Thereby, this study provides an important analytical method that contributes to a more nuanced understanding of the interdependencies of the TIS. The empirical results indicate that system weaknesses are shaped to a large extent by the overall contextual dynamics – such as political instability, energy subsidies and high inflation rates. System strengths relate to both the TIS itself (particularly knowledge development through pilot projects and market formation through provincial and national support programmes), to contextual relationships (linked to the availability of educational institutions that enable the rapid diffusion of knowledge) and to the importance of rural areas as protected spaces for the application of photovoltaic systems. Consequently, the study highlights the challenges to overcome for the broader diffusion of distributed photovoltaic generation.
Evaluation Of Efficacy And Biomechanical Characteristics Of Two Spinal Orthoses Manufactured By DeRoyal

ABSTRACT The purposes for this study were to examine efficacy of two spinal orthoses in altering spinal kinematics and to compare their effectiveness. Prolign is a lumbar orthosis (LO) and Ultralign is a lumbosacral orthosis (LSO) and both are made by the DeRoyal Industries, Inc. Seventeen healthy male subjects with no impairments to their trunk at the time of the data collection and no previous history of major spinal pathology participated in the study. A digital video camera (60 Hz) was used to obtain kinematic data from the right sagittal and posterior views of the subject. For the sagittal view, three retroreflective markers were placed on the right side of the body at the mid-trunk, the hip (greater trochanter), and the knee (lateral femoral epicondyle) and three customized marker wands were placed on the spinal process at the 1 st thoracic vertebra (T1), and the 1 st (L1) and 5 th (L5) lumbar vertebrae. For the posterior view, three flat retroreflective markers were placed on the spinal process of T1, L1 and L5. The subjects were instructed to perform three forward flexion trials, three backward extension trials, and three lateral (right) bending trials in each of the two braces and in an un-braced condition in nine test conditions. Selected variables were evaluated using a one-way analysis of variance with post hoc comparisons. The data from this study suggested that both orthoses are effective in restricting lumbar segmental intervertebral movement in flexion, extension and lateral flexion of trunk. The UltraLign provided more significant spinal immobilization and restricted more gross range of motion in all three types of trunk movement. The Prolign LO offered less support for the lumbar spine and restriction on the movements compared to the Ultralign LSO, but was effective in the reduction of lumbar intervertebral segmental mobility.
Etch-stop technique for patterning of tunnel junctions for a magnetic field sensor

Spin-dependent tunnelling devices, e.g. magnetic random access memories and highly sensitive tunnelling magnetoresistance (TMR) sensors, often consist of a large number of magnetic tunnel junctions (MTJs) of uniform quality over the whole device. The uniformity and yield of the fabrication of such a device are therefore very important. A major source of yield loss is the short-circuiting of junctions by redeposition of etch residues. This can be prevented by terminating of the etch in the typically 1 nm thick tunnelling barrier. Here, electron spectroscopy for chemical analysis for monitoring the etching semi-continuously is proposed. The fabrication scheme employs Ar ion milling for etching the MTJs, and photoelectron spectroscopy for analysing the composition of the etched surface in situ. Junctions etched either to or through the barrier were used for this. The quality of the etch stop was investigated using transmission electron microscopy (TEM), and it was confirmed that the etch could be stopped in the MgO barrier. The TEM imaging also showed clear signs of redeposition. Such redeposition was attributed to being partly caused by the reduction of the TMR ratio of the junctions etched through the barrier, which was only 15% as compared with 150% for junctions etched to the barrier. Also, the latter junctions exhibited 2.7 times less noise in the low-frequency regime, resulting in a 27 times improvement of the signal-to-noise ratio with the etch stop. The barrier also proved effective in protecting the bottom contact from oxidation during the capping and contacting of the junctions.
Influence of Windfarms on Power System Dynamic and Transient Stability

The interaction between bulk windfarm generation and conventional generation and its influence on network dynamic characteristics are investigated. A simple three-generator system having characteristics that may be considered representative of the major areas of the UK network is used for the dynamic studies. Time response simulation and eigenvalue analysis are used to establish basic transient and dynamic stability characteristics. The wind generation is provided either by windfarms based on Fixed Speed Induction Generators (FSIGs) or Doubly Fed Induction Generators (DFIGs). In addition, in order to provide a base-line, against which windfarm influence on network dynamics can be judged, the case where the power is provided only by conventional synchronous generation is also considered.