A Systemic Approach for Evaluating Stakeholder Collaboration within Requirement Collection

The involvement of Stakeholders in requirement collection of software projects is essential, and that is evident in the diverse methodologies available that emphasise stakeholder collaboration. However these processes scarcely provide further understanding of the social interaction, and its effect into forming collaboration had not been sufficiently addressed by software development research. It is challenging to identify dominating factors that affect collaboration due to the complexity of stakeholder interaction. This thesis addresses such a challenge. It discusses a systems approach to the evaluation of stakeholder collaboration within requirement collection of software projects. A generic approach has been developed to contribute to our understanding of the problem and support stakeholders’ collaborative involvement. Based on understanding the nature of collaboration between stakeholders in requirement collection, and the concept of perception and its contribution into forming collaboration, the EStaC (Evaluation of Stakeholder Collaboration) approach is developed. EStaC is presented here to describe an integration of multi-methodologies that supports capturing stakeholders' perspectives, and therefore systemically it captures the essence of collaboration within its context. EStaC contributes to the crucial phase of requirement collection with the ultimate objective of extending it to include means of improvement of stakeholder collaboration. It promotes the development of two modes of analysis, the design and diagnosis, which both involves using the principles of the Viable System Model. The novelty of this work is specifically considered with the development of the EStaC approach because unlike other approaches, it focuses on the social act of interaction from a stakeholders viewpoint, by applying systemic strategies and cybernetic driven principles with concepts of fourth generation evaluation. The research recognises evaluation of stakeholder collaboration as an important aspect in the requirement collection process in any software development. It concludes and supports the incorporation of such activities throughout various phases of requirement collection

Spectrophotometric determination of nicradipine and isradipine in pharmaceutical formulations

A sensitive spectrophotometric method was developed for the determination of some 1,4-dihydropyridine compounds namely, nicardipine and isradipine either in pure form or in pharmaceutical preparations. The method is based on the reduction of nicardipine and isradipine with zinc powder and calcium chloride followed by further reduction with sodium pentacyanoaminoferrate (II) to give violet and red products having the absorbance maximum at 546 and 539 nm with nicardipine and isradipine, respectively. Beer’s law was obeyed over the concentration range 8.0–180 μg/ml with the detection limit of 1.67 μg/ml for nicardipine and 8.0–110 μg/ml with the detection limit of 1.748 μg/ml for isradipine. The analytical parameters and their effects on the reported methods were investigated. The molar absorptivity, quantization limit, standard deviation of intercept (Sa), standard deviation of slope (Sb) and standard deviation of the residuals (Sy/x) were calculated. The composition of the result compounds were found 1:1 for nicardipine and 1:2 for isradipine by Job’s method and the conditional stability constant (Kf) and the free energy changes (ΔG) were calculated for compounds formed. The proposed method was applied successfully for the determination of nicardipine and isradipine in their dosage forms. The results obtained were in good agreement with those obtained using the reference or official methods. A proposal of the reaction pathway was presented

Peptides as potent antimicrobials tethered to a solid surface: Implications for medical devices

Medical devices are an integral part of therapeutic management; despite their importance, they carry a significant risk of microbial infection. Bacterial attachment to a medical device is established by a single, multiplying organism, leading to subsequent biofilm formation. To date, no preventative measures have impacted the incidence of device-related infection. We report the bidirectional covalent coupling of an engineered cationic antimicrobial peptide (eCAP), WLBU2, to various biological surfaces is accomplished. These surfaces included (i) a carbohydrate-based gel matrix, (ii) a complex polymeric plastic bead, and (iii) a silica-calcium phosphate nanocomposite associated with bone reconstruction. WLBU2-conjugated surfaces are shown to retain potent antimicrobial activity related to bacterial surface adhesion. This study provides proof of principle that covalently coating laboratory and bone-regenerating materials with eCAPs has the potential for decreasing infection rates of implanted devices. These findings have important consequences to the patient management component of our current health care technology

The role of transcranial grayscale and Doppler ultrasound examination in diagnosis of neonatal hypoxic-ischemic encephalopathy

Background: The role of transcranial grayscale ultrasound (TC-GSUS) and transcranial color Doppler (TCD) in the diagnosis and prognosis of neonatal hypoxic-ischemic encephalopathy (HIE) is still questionable.Objective: This study targeted to evaluate the role of TC-GSUS and TCD in diagnosis and prediction of the outcome of neonates with suspected HIE in comparison to Sarnat's clinical scoring.Patients and methods: 26 neonates with suspected HIE were clinically evaluated and the severity of HIE was categorized according to Sarnat's clinical staging. Then, all neonates underwent sonographic examinations. TC-GSUS was performed at levels of anterior, mastoid, and posterior fontanelles and the level of the temporal window.Results: Cranial biometry had negative and positive rates for HIE of 7.7% and 92.3%, respectively. Using TC-GSUS, periventricular leukomalacia, intraventricular hemorrhage, brain edema, and hydrocephalus were detected in 17, 19, 14, and 16 patients, respectively. According to the resistive index (RI) of intracranial vessels, TCD excluded HIE in 11 patients and assured diagnosis of HIE with varying severity in 15 patients. Five neonates died and four developed neurological affection during follow-up. The outcome was correlated with Sarnat’s scoring, ventricular-hemispheric ratio, and abnormalities of RI. Statistical analyses defined severity of HIE as judged by RI as the significant predictor for mortality and abnormal RI of anterior cerebral (ACA) and internal carotid arteries (ICA) are the most significant predictors of outcomes.Conclusion: TCD can diagnose HIE in neonates with high sensitivity and specificity and abnormal RI of ICA and ACA might be used as valuable diagnostic and prognostic tests

Le cancer du rein chez l’adulte. Etude rétrospective à propos de 155 cas

Objectif: Analyser les différents aspects épidémiologiques, cliniques, radiologiques, pathologiques et thérapeutiques du cancer du rein dans notre contexte. Patients et méthodes: Il s’agit d’une étude rétrospective à partir des dossiers des patients hospitalisés à notre service d’urologie pour tumeurs du rein entre 1990 et 2007. Sur les 155 dossiers consultés, 125 patients ont été traités chirurgicalement, et pour 30 patients, l’abstention a été justifiée par le stade évolué localement ou métastatique et/ou le mauvais état général. Les paramètres étudiés ont été : l’âge, la symptomatologie clinique, le bilan radiologique, le type d’intervention, les résultats anatomopathologiques et le stade histologique TNM. Tous les patients ont été revus avec un examen clinique, une échographie ou tomodensitométrie abdominale avec radiographie thoracique et une créatinémie. Résultats: Il s’agissait de 105 hommes et 50 femmes. L’âge moyen de découverte était de 60 ans (extrêmes : 18 et 85 ans). Le délai moyen entre l’apparition des symptômes et le diagnostic était d’environ 9 mois (extrêmes : 1 et 24 mois). L’hématurie était le signe révélateur le plus important noté chez 45,2% des cas. Le diagnostic a été basé sur le couple échographie – tomodensitométrie chez tous nos patients. La taille tumorale moyenne était de 10 cm (extrêmes 3 et 20 cm) lors du bilan initial. Le rein gauche était touché plus souvent que le rein droit (67% vs. 33%). Le bilan d’extension à distance était négatif chez 95 patients (61,3%), alors que 60 patients avaient des métastases viscérales et/ou ganglionnaires. Parmi ces derniers, 30 avaient un mauvais état général et/ou des métastases viscérales multiples ce qui a contre indiqué le geste opératoire. Les localisations métastatiques des 30 patients opérés étaient les suivantes: poumons (5 cas), ganglions (15 cas), os (2 cas), foie (8 cas). Plus de 80% des tumeurs étaient des carcinomes à cellules claires (carcinomes conventionnels). L’intervention a consisté à une néphrectomie totale élargie à ciel ouvert chez tous nos patients opérés. La médiane de suivi était de 62 mois (extrêmes: 6-72 mois). Trente patients ont été perdus de vue définitivement après l’intervention. Sur l’ensemble de la série, les taux respectifs de survie sans récidive à 3 ans et à 5 ans étaient de 78,4% et 47,2%. Conclusion: Le cancer du rein est une pathologie qui n’est pas rare. Sa symptomatologie est polymorphe. Le traitement de référence est la néphrectomie totale élargie. Les facteurs pronostiques les plus déterminants sont le stade (TNM) et le grade histologique de Fuhrman. Selon notre série, la néphrectomie élargie permet un taux de survie sans récidive supérieur à 85%, tous stades et types histologiques confondus.Mots clés: Cancer, rein, adulte

Modeling Surface Recombination at the p-Type Si/SiO

An integral model is proposed for recombination at the silicon/silicon dioxide (Si/SiO2) interface of thermally oxidized p-type silicon via Pb amphoteric centers associated with surface dangling bonds. The proposed model is a surface adaptation of a model developed for bulk recombination in amorphous silicon based on Sah-Shockley statistics which is more appropriate for amphoteric center recombination than classical Shockley-Read-Hall statistics. It is found that the surface recombination via amphoteric centers having capture cross-sections larger for charged centers than for neutral centers is distinguished from Shockley-Read-Hall recombination by exhibiting two peaks rather than one peak when plotted versus surface potential. Expressions are derived for the surface potentials at which the peaks occur. Such a finding provides a firm and plausible interpretation for the double peak surface recombination current measured in gated diodes or gated transistors. Successful fitting is possible between the results of the model and reported experimental curves showing two peaks for surface recombination velocity versus surface potential. On the other hand, if charged and neutral center capture cross-sections are equal or close to equal, surface recombination via amphoteric centers follows the same trend as Shockley-Read-Hall recombination and both models lead to comparable surface recombination velocities

OPTN recruitment to a Golgi-proximal compartment regulates immune signalling and cytokine secretion

Optineurin (OPTN) is a multifunctional protein involved in autophagy, secretion as well as NF-κB and IRF3 signalling and OPTN mutations are associated with several human diseases. Here we show that, in response to viral RNA, OPTN translocates to foci in the perinuclear region, where it negatively regulates NF-κB and IRF3 signalling pathways and downstream pro-inflammatory cytokine secretion. These OPTN foci consist of a tight cluster of small membrane vesicles, which are positive for ATG9A. Disease mutations linked to POAG cause aberrant foci formation in the absence of stimuli, which correlates with the ability of OPTN to inhibit signalling. Using proximity labelling proteomics, we identify the LUBAC complex, CYLD and TBK1 as part of the OPTN interactome and show that these proteins are recruited to this OPTN-positive perinuclear compartment. Our work uncovers a crucial role for OPTN in dampening NF-κB and IRF3 signalling through the sequestration of LUBAC and other positive regulators in this viral RNA-induced compartment leading to altered pro-inflammatory cytokine secretion

A cascaded classification-segmentation reversible system for computer-aided detection and cells counting in microscopic peripheral blood smear basophils and eosinophils images

Computer-aided image analysis has a pivotal role in automated counting and classification of white blood cells (WBCs) in peripheral blood images. Due to their different characteristics, our proposed approach is based on investigating the variations between the basophils and eosinophils in terms of their color histogram, size, and shape before performing the segmentation process. Accordingly, we proposed a cascaded system using a classification-based segmentation process, called classification-segmentation reversible system (CSRS). Prior to applying the CSRS system, a Histogram-based Object to Background Disparity (HOBD) metric was deduced to determine the most appropriate color plane for performing the initial WBC detection (first segmentation). Investigating the local histogram features of both classes resulted in a 92.4% initial classification accuracy using the third-degree polynomial support vector machine (SVM) method. Subsequently, in the proposed CSRS approach, transformation-based segmentation algorithms were developed to fit the specific requirements of each of the two predicted classes. The proposed CSRS system is used, where the images from an initial classification process are fed into a second segmentation process for each class separately. The segmentation results demonstrated a similarity index of 94.9% for basophils, and 94.1% for eosinophils. Moreover, an average counting accuracy of 97.4% for both classes was achieved. In addition, a second classification was carried out after applying the CSRS, achieving a 5.2% increase in accuracy compared to the initial classification process

Prediction of harvestable energy for self-powered wearable healthcare devices: filling a gap

Self-powered or autonomously driven wearable devices are touted to revolutionize the personalized healthcare industry, promising sustainable medical care for a large population of healthcare seekers. Current wearable devices rely on batteries for providing the necessary energy to the various electronic components. However, to ensure continuous and uninterrupted operation, these wearable devices need to scavenge energy from their surroundings. Different energy sources have been used to power wearable devices. These include predictable energy sources such as solar energy and radio frequency, as well as unpredictable energy from the human body. Nevertheless, these energy sources are either intermittent or deliver low power densities. Therefore, being able to predict or forecast the amount of harvestable energy over time enables the wearable to intelligently manage and plan its own energy resources more effectively. Several prediction approaches have been proposed in the context of energy harvesting wireless sensor network (EH-WSN) nodes. In their architectural design, these nodes are very similar to self-powered wearable devices. However, additional factors need to be considered to ensure a deeper market penetration of truly autonomous wearables for healthcare applications, which include low-cost, low-power, small-size, high-performance and lightweight. In this paper, we review the energy prediction approaches that were originally proposed for EH-WSN nodes and critique their application in wearable healthcare devices. Our comparison is based on their prediction accuracy, memory requirement, and execution time. We conclude that statistical techniques are better designed to meet the needs of short-term predictions, while long-term predictions require the hybridization of several linear and non-linear machine learning techniques. In addition to the recommendations, we discuss the challenges and future perspectives of these technique in our review

Perspectives of an Enterprise Integration Plug-in System Architecture for Networked Manufacturing Systems

This paper is a part of a research project funded by the Science and Technology Development Fund (STDF), to create a product serving the digital transformation of Egyptian manufacturing companies. It allows a manufacturing company to be a member of a distributed manufacturing network. The resulting system can be plugged into any ERP system. In this work, the limitation of a centralized integration entity to satisfy loosely coupling of distributed systems is overcome. The SOA framework and the remote method invocation (RMI) are applied using SOAP-XML technology. Enterprise integration patterns (EIP) were used in the architecture design