Miracle-dz/UniFAR-FTUs huggingface dataset:
Inclusion and exclusion in the NHS : power, innovation and rejection in nursing

2 CHAPTER 1 Synopsis. 7 Introduction. 7 Brief synopsis of Projects 1-4.7 Research methodology. 9 Introduction. 9 Quantitative and qualitative research perspectives . 10 Brief overview of management research. 11 Research method and design. 14 My research method. 19 A complex responsive processes approach to research . 22 Reflexive methodology . 22 Generalisability and trustworthiness of my research . 28 Emergent themes from Projects 1–4 . 33 Targets and performance management . 34 The benefits of performance management . 44 The limitations of performance management . 47 The contribution of complex responsive processes perspectives. 51 The limitations of complex responsive processes perspectives . 57 Power . 60 Power in organisations . 68 Inclusion/exclusion and power. 75 Novelty and innovation . 78 The management of novelty and innovation.80 Complex responsive processes and novelty and innovation.88 An analysis of different perspectives.94 Different ways of understanding innovation in practice.97 Staff dissonances leading to feelings of rejection . 102 The psychological contract . 107 My original contribution to theory and professional practice . 122 Concluding remarks . 128 CHAPTER 2 Project 1: The influences and experiences that have made an impression on my working life. 129 Becoming a nurse. 129 The philosophy of child-centred care. 131
Euthyroid Nodular Disease in Relation to Insulin Resistance

Background: Nodular thyroid disease is a common endocrine problem. There is scarce information on the effect of hyperinsulinemia on the development of thyroid nodules. Objectives: to assess the frequency of insulin resistance (IR) in patients with euthyroid nodular thyroid disease, and to investigate any possible association between insulin resistance and thyroid functional and/or morphological changes within a sample of Egyptian patients. Research design and methods: This is a cross-sectional study including sixty subjects having euthyroid nodular thyroid disease, their ages ranged from 25 to 60 years old. They were purposively selected and evaluated for manifestations of IR. For all subjects, waist circumference (WC) and body mass index (BMI) were measured. Serum TSH, FreeT4, FreeT3, fasting plasma glucose, and fasting serum insulin (FI) were measured. Degree of IR was calculated using Homeostasis model Assessment-index (HOMA-index). Thyroid ultrasound (US) was performed and thyroid volume (TVml), nodule volume (NVmm), and nodular number (NN) were measured. Results: According to results of HOMA-Index, 56.70% of studied subjects had levels >2.7 denoting significant IR. No significant difference was found between subjects with and those without IR as regards thyroid profile. Subjects with IR had more frequent thyroid nodules besides greater TV and NV. Among the studied parameters, multivariate linear regression analysis revealed that, TV was mainly associated with FI and HOMA-index (p<0.000, p<0.002, respectively). The main predictors for developing more than one nodule were BMI, TV, HOMA-index, and FI. None of the studied parameters had an association with NV. Conclusions: IR is common among Egyptian patients with euthyroid nodular thyroid disease. Thyroid gland is a novel vulnerable tissue that may be affected by IR, in the form of increased thyroid volume and higher risk of nodule formation.
COCO-GAN: CONDITIONAL COORDINATE GENERA-

Recent advancements on Generative Adversarial Network (GAN) have inspired a wide range of works that generate synthetic images. However, current processes have to generate an entire image at once, and therefore resolutions are limited by memory or computational constraints. In this work, we propose COnditional COordinate GAN (COCO-GAN), which generates a specific patch of an image conditioned on a spatial position rather than the entire image at a time. The generated patches are later combined together to form a globally coherent full-image. With this process, we show that the generated image can achieve competitive quality to state-of-the-arts and the generated patches are locally smooth between consecutive neighbors. One direct implication of the COCO-GAN is that it can be applied onto any coordinate systems including the cylindrical systems which makes it feasible for generating panorama images. The fact that the patch generation process is independent to each other inspires a wide range of new applications: firstly, “Patch-Inspired Image Generation” enables us to generate the entire image based on a single patch. Secondly, “Partial-Scene Generation” allows us to generate images within a customized target region. Finally, thanks to COCO-GAN’s patch generation and massive parallelism, which enables combining patches for generating a full-image with higher resolution than state-of-the-arts.
Does Green Matter? A Study of Perception of Manufacturers and Consumers of a Developing Country about Green Supply Chains

Green Supply Chain Management (GrSCM) has received increased attention from both academia and industry in recent years in the industrial nations. It focuses on reducing the adverse impact of business processes on the environment. These business processes include product design, material sourcing and selection, manufacturing processes, product delivery and end-of-life management of the product. The research studying interactions between environment and businesses in Pakistan has been scarce. This study is conducted to set a platform for GrSCM research in Pakistan as it aims to investigate the perceptions of the manufacturers and consumers regarding their understanding about GrSCM and green products. A qualitative research design including indepth interviews from senior managers of three manufacturing firms and a focus group of customers has been conducted for this purpose. A list of critical factors of GrSCM has been developed based on survey of the literature. The comparison between the GrSCM literature, manufacturer perception about GrSCM and consumer perception about green products lead towards the conclusions regarding; how consumers perceive green products? Do they really demand such products? Do the manufacturers think there is a need for GrSCM? How do they think GrSCM can lead to competitiveness and better economic performance? Basic understanding regarding these issues leads to the future direction for research and practice in this area.
Arbitrage-free bilateral counterparty risk valuation under collateralization and re-hypothecation with application to CDS ∗

We develop an arbitrage-free valuation framework for bilateral counterparty risk, where collateral is included with possible re-hypothecation. We show that the adjustment is given by the sum of two option payoff terms, where each term depends on the netted exposure, i.e. the difference between the on-default exposure and the pre-default collateral account. We then specialize our analysis to Credit Default Swaps (CDS) as underlying portfolios, and construct a numerical scheme to evaluate the adjustment under a doubly stochastic default framework. In particular, we show that for CDS contracts a perfect collateralization cannot be achieved, even under continuous collateralization, if the reference entity’s and counterparty’s default times are dependent. The impact of re-hypothecation, collateral margining frequency, and default correlation induced contagion is illustrated with numerical examples.
S rRNA Gene As A Marker For Bacteremia In Patients With Acute Pancreatitis

Background: 16S ribosomal RNA (rRNA) gene polymerase chain reaction (PCR) is used for detection of bacterial pathogens in the serum of patients with acute pancreatitis (AP). Acute pancreatitis is a frequent cause of hospital admission. Infection and septic complications are the major factors contributing to the poor outcome in acute severe pancreatitis. PCR makes it possible to identify the presence of bacterial DNA in culture-negative samples from patients with suspected infection. This molecular approach allows non-culture rapid confirmation of pancreatitis and septicemia, which leads to improved disease surveillance and provides guidance on appropriate antibiotic usage and patient management. The aim of the present study is to detect bacterial DNA accurately by PCR targeting 16s rRNA as a common bacterial primer in serum of patients with acute pancreatitis in order to augment the standardized use of prophylactic antibiotics in such cases. Methods: twenty patients with acute pancreatitis aged 44.5±13.9 years, 6(30%) male and 14(70%) female patients were included. Serum amylase and CRP were measured. All patients were undergone genotyping for 16S rRNA gene by polymerase chain reaction to detect bacterial DNA in serum and conventional microbial blood cultures analyzed by BACTEC system. 60 samples were collected (3 for each case collected in the first 3 days after admission). Results: Bacterial DNA was detected in 13/60 (21.67%) samples from 8 patients by PCR analysis. Regarding these 8 patients, bacterial DNA was detected in 3 (37.5 %) cases on day 1; 7 (87.5 %) cases on day 2; and 3 (37.5 %) cases on day 3. All the 15 (100 %) cases who received antibiotics had negative blood culture with significant correlation (p = 0.05), and negative PCR1 with highly significant correlation (P = 0.009). 12of the15 cases (80 %) had negative PCR2 with significant correlation (P = 0.03) and 14 (93.3 %) cases had negative PCR3 results with no significant correlation (P = 0.14). Out of the 20 patients, only 2 (10 %) cases had positive growth in blood culture analyzed by BACTEC system. Conclusion: The PCR assay with universal primers targeting 16S rRNA genes is more sensitive in detecting the sepsis secondary to acute severe pancreatitis. Early antibiotic treatment reduced septic complications and mortality. But it remains a therapeutic challenge in the clinical management of A.P.
Robust and Accurate Tracking of Free Surfaces : Stabilization and NURBS-Based Discretization Aspects

Moving-boundary flow simulations are an important design and analysis tool in many areas of engineering, including civil and marine engineering, as well as production engineering [1]. While interface-capturing offers unmatched flexibility for complex free-surface motion, the interface-tracking approach is very attractive due to its better mass conservation properties at low resolution. We focus on interface-tracking moving-boundary flow simulations based on stabilized discretizations of Navier-Stokes equations, spacetime formulations on moving grids, and mesh update mechanisms based on elasticity. The kinematic condition, which can be interpreted as an elevation equation, as well as its stabilized GLS formulation, has been derived for specific classes of problems, including cases where surface nodes move along prescribed directors or spines [2]. The need for implicit solution of such stabilized problem results in a coupled system of equations for a) the equation governing the generalized elevation, b) the interior mesh deformation equations and c) the flow equations. The coupling between these three systems is enforced iteratively within the nonlinear iteration loop, placing certain restrictions on the size of the time steps taken. In order to obtain accurate and smooth shape description of the free surface, as well as accurate flow approximation on coarse meshes, the approach of NURBS-enhanced finite elements (NEFEM) [3] is being applied to various aspects of free-surface flow computations. In NEFEM, certain parts of the boundary of the computational domain are represented using non-uniform rational B-splines (NURBS), therefore making it an effective technique to accurately treat curved boundaries, not only in terms of geometry representation, but also in terms of solution accuracy. As a step in the direction of NEFEM, the benefits of a purely geometrical NURBS representation of the free-surface could already be shown [4]. The first results with a full NEFEM approach for the flow variables in the vicinity of the moving free surface have also been obtained. The applications include both production engineering, i.e., die swell in plastics processing simulation, and safety engineering, i.e., sloshing phenomena in fluid tanks subjected to external excitation.
A Vector – based Method for Simulating Tailpiece to Rotated Texture Images

A vector–based method for making tailpiece is proposed to correct the image blank areas left by rotation. Using the image quality threshold δ to determine the degree of similarity γ of the vector image, an image is converted to vectors of cubic curve combination; after rotating vector-graph, we expand the curves to the blank area by adjusting the vector parameters, and grow texture accumulation areas. The texture gradient is used to fill the differences of the vector curves and the real texture gradient. Using wood texture images as samples, the experiments showed the repaired images are highly similar to real wood textures. Keywordsimage; vector curve; texture extension; tailpiece
EVALUATION OF INTRUSION DETECTION TECHNIQUES AND ALGORITHMS IN TERMS OF PERFORMANCE AND EFFICIENCY THROUGH DATA MINING

Data mining has been one of the approches used as a foundation then there is a érection of intrusion detection systems (IDS). Various algorithms and techniques have been développe to make out different types of vulnérabilités. These techniques help to recoder the performance of the detection of vulnerabilities, calculâtes the overheads, and to make Dataset efficient without redundancy. However there is no heuristic to corroborate the accuracy of their results. In this paper we study the techniques and algorithms of the detection of known and unknown attacks through data mining. The methods, metrics and datasets are used to find the known and unknown attacks through data mining. The various techniques like , Scoring Techniques, Attack generalization technique, Language model techniques, Novel hybrid technique, C4.5 decision algorithm, Nearest neighbour, Rough Set Theory(RST), Support Vector Machine(SVM) ,Statically Techniques, Ensemble boosted decision tree, apriori algorithm, Rule based techniques Association and Sequence techniques, are used to detect the vulnerabilities through Data mining. In this paper, we have described the outline of all the algorithms and techniques to identify their strengths and limitations.
Blood pressure measurement in the dog.

: An indirect method of blood pressure measurement was evaluated in 169 dogs, including 114 that were hospitalized because of a variety of diseases, 10 clinically normal dogs presented for neutering, and 45 privately owned, clinically normal dogs. Measurements correlated well with values obtained by simultaneous direct arterial puncture. Normotension was considered to be 130 to 180 mm of Hg, systolic, and 60 to 95 mm of Hg, diastolic. As a group, 20 dogs with advanced renal disease had significant (P less than 0.001) hypertension, compared with the groups of clinically normal dogs. Of 94 dogs with a variety of diseases exclusive of renal disease, 10 had hypertension and 2 had hypotension.
Clinical Study The Obesity Paradox and Cardiorespiratory Fitness

1 Department of Human Performance and Sport Sciences, Winston-Salem State University, C024 Anderson, 601 S Martin Luther King Jr Drive, Winston-Salem, NC 27110, USA 2 Department of Physical Therapy, Winston-Salem State University, Winston-Salem, NC 27110, USA 3 Department of Cardiology, Division of Cardiovascular Medicine, Veterans Affairs Palo Alto Health Care System, Stanford University, Palo Alto, CA 94304, USA
Enhanced Pothole Detection Algorithm for Blurry Images

Recently, damaged pavement such as potholes are increasing owing to the climate change and poor road maintenance systems. Potholes can generate critical damages such as flat tire, wheel damage and impact on the lower part of a vehicle. Moreover, sudden braking and steering wheel operation due to the potholes can cause vehicle collision and major accidents. One of the solution to address these problems is to automatically detect potholes and store the information database systems for necessary corrective measures. In our previous studies, we proposed a pothole detection algorithm using various features in 2D images that improved the existing methods and accurately detected a pothole. However, our previous algorithm showed poor detection results with blurry pothole images because the feature information for distinguishing a pothole from road pavement was unclear. In this study, we redesign our previous algorithm in order to enhance the feature information from blurry images.
Multiple Features Fusion for Front-View Vehicle Detection

M.L. Men School of Science Xi’an University of Technology China F. Dai School of Science Xi’an University of Technology China Abstract-With the rapid increase of vehicle holdings, urban transport is facing a severe test. Driver-assistance systems (ADAS) can effectively avoid happening of traffic accidents. Real-time detection of moving vehicle based on vision has become a research focus of ADAS. A method of multiple features fusion for front-view vehicle detection is proposed in this paper. Firstly, in RGB color space, license plate position is located using color conversion and Otsu threshold segmentation method is improved to confirm the vehicle’s candidate area. Secondly, geometrical characteristics of the license plate is adopted to eliminate distraction regions and to verify the extracted license plate. Finally, rear lamps of vehicle are detected and matched in candidate license plate regions, so vehicle area is further determined. The experimental results show that the proposed method in this paper can be used to detect vehicle in real-time and false detection rate is low.
SZBC-HWSN : Stabilize Zone Balanced Cluster Head Selection Protocol for Heterogeneous Wireless Sensor Network

This paper presents a novel work to enhance stability of heterogeneous wireless sensor network (HWSN), with the protocol named as stabilize zone balanced Cluster head selection protocol (SZBC)-HWSN. SZBC-HWSN achieve better node connectivity in cluster and hence balancing energy consumption of the entire network. This work presents a solution to select high energy and low hop count node with base station from the zone to be cluster head (CH). In SZBC-HWSN Protocol, importance is given to initial energy, Residual energy and hop count for selecting cluster head based on regression analysis, with the nodes available from each zone of network. This approach gives better energy efficiency in HWSN compared to existing clustering protocol. For selecting cluster head towards the center of zone, boundary condition is also taken into consideration. The proposed method ensures that selected cluster head node is high energy or node near to base station. This approach reduces the possibility of selecting weak node to be cluster head, and to reduce the possibility of selecting cluster head at vicinity of network. The performance of the proposed protocol has been validated with 1164 Santosh Vishnu Purkar and Dr. R.S. Deshpande two renowned existing protocols through simulation. The result shows that the proposed scheme outperforms than the existing protocols in terms of stability, throughput and energy remain in the network.
Risk Assessment on Housing Segments in Stockholm From a bank ’ s perspective

It is well known that risk factors can influence how an investment portfolio can perform from a bank’s perspective; therefore, a thorough risk assessment is vital to such big investments like in housing market. The thesis is aimed to analyze the risks from housing apartments in different division parameters in Stockholm, Sweden. By applying quantitative and systems engineering methods, it is expected to establish the relation between overall housing market and several housing segments in pricing indexes, analyze result from the quantitative model and finally provide a feasible portfolio regarding risk control based on given data. The goal of the thesis is trying to pinpoint how different housing segment factors in same parameter can reveal risk towards overall market and offer better outlook for risk management when it comes to housing apartments in Stockholm, Sweden.
Acute atrial arrhythmogenicity and altered Ca 2 1 homeostasis in murine RyR 2P 2328 S hearts

Acute atrial arrhythmogenicity and altered Ca homeostasis in murine RyR2-P2328S hearts
Why Monitor Violent Websites? A Justification *

The authors argue that the international community should continue working together to devise rules for monitoring specific Internet sites, as human lives are at stake. Preemptive measures could prevent the translation of murderous thoughts into murderous actions. Designated monitoring mechanisms for certain websites that promote violence and seek adherents for the actualization of murderous thoughts could potentially prevent such unfortunate events. Our intention is to draw the attention of the international community’s multi-agents (law-enforcement agencies, governments, the business sector, including Internet Service Providers, websites administrators and owners, civil society groups) to the urgent need of developing monitoring schemes for certain websites, in order to prevent violent crimes.
Monitoring for the presence of parasitic protozoa and free-living amoebae in drinking water plants

Received 26.03. 2012 Accepted 04.06. 2012 Published 09.07. 2012 Contamination of drinking water by microorganisms represents a major human health hazard in many parts of the world. The main objective of drinking water treatment is to provide microbiologically safe drinking water. The conventional drinking water treatment and disinfection has proved to be one of the major public health advances in modern times. A number of processes; namely water treatment, disinfection and changes influence the quality of drinking water delivered to the customer’s tap during transport of treated water via the distribution system. At least 325 water-associated outbreaks of parasitic protozoan disease have reported. In this study, drinking water from treatment plants evaluated for the presence of parasitic protozoa. Water samples collected from two main points: (a) outlet of the water treatment plants (b) distribution system at different distances from the water treatment plants. Protozoa were concentrated from each water sample by adsorption and accumulation on the nitrocellulose membrane filters (0.45 μm pore size) and detected by conventional staining methods. Keywords
Phylogeny of canine coronavirus ( CCoV ) from Brazilian dogs based on membrane protein partial sequences

Recebido em 4 de fevereiro de 2013 Aceito em 1 de agosto de 2013 *Autor para correspondência (corresponding author) E-mail: paulo7926@usp.br Twenty-two fecal samples were collected from dogs with ages ranging from 1 to 6 months, all of them non-vaccinated against CCoV. Sampling was by convenience, without statistical methods, and the presence or absence of diarrhea was not taken into account at that moment.
Algorithm 1 : Attribute Selection Algorithm Based on Mutual Dependency Input

The text categorization is a core technique in knowledge mining field. Most of categorization methods are based on VSM in the current research, of which the widely-used method is kNN. But most of them are highly complicated on computation, and could hardly be used for classifying large-scale sample. Moreover, to them, the classifier must be rebuilt when adding or deleting the training samples, which make them poor in scalability. In this paper, based on Mutual Dependence and Equivalent Radius, a new categorization method (called MDER) is proposed. MDER can be used to classify large-scale sample and has good scalability. After a series of experiments of classifying Chinese texts, the conclusion are drawn that MDER outperforms kNN and CCC method, and can be used online to classify large-scale sample while keeping higher precision and recall. Key-Words: Text categorization, Mutual dependence, Equivalent radius, VSM