Secure Self-healing Group Key Distribution Scheme with Constant Storage for SCADA Systems in Smart Grid

Wireless Personal Communications - Smart grid has a great advantage over the traditional power grid and it is a critical condition in people’s daily life. The security of data communication...     

War zone stress, personal resources, and PTSD in Persian Gulf War returnees.

Posttraumatic stress disorder (PTSD) can occur subsequent to war stress, but not all troops are negatively affected. A discriminant function model was used to study associations between personal and environmental resources and psychological outcomes subsequent to war zone stress. Among 775 Persian Gulf War exposed troops, 2 subsets were identified: 97 with PTSD diagnoses and 484 who had no psychological distress. A discriminant function, double cross-validated in random subsamples, classified 87% of troops, and demographic and stress severity variables did not alter results significantly. Personality hardiness commitment, avoidance coping, and perceived family cohesion emerged as consistent predictors of PTSD diagnosis. Findings suggest personal characteristics and environmental factors may alter vulnerability to negative war stress outcomes. Work is needed to identify mechanisms and causal pathways by which resource factors enhance or lower stress resistance. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

IoMT-Based Smart Monitoring Hierarchical Fuzzy Inference System for Diagnosis of COVID-19

The prediction of human diseases, particularly COVID-19, is an extremely challenging task not only for medical experts but also for the technologists supporting them in diagnosis and treatment. To deal with the prediction and diagnosis of COVID-19, we propose an Internet of Medical Things-based Smart Monitoring Hierarchical Mamdani Fuzzy Inference System (IoMTSM-HMFIS). The proposed system determines the various factors like fever, cough, complete blood count, respiratory rate, Ct-chest, Erythrocyte sedimentation rate and C-reactive protein, family history, and antibody detection (lgG) that are directly involved in COVID-19. The expert system has two input variables in layer 1, and seven input variables in layer 2. In layer 1, the initial identification for COVID-19 is considered, whereas in layer 2, the different factors involved are studied. Finally, advanced lab tests are conducted to identify the actual current status of the disease. The major focus of this study is to build an IoMT-based smart monitoring system that can be used by anyone exposed to COVID-19; the system would evaluate the user’s health condition and inform them if they need consultation with a specialist for quarantining. MATLAB-2019a tool is used to conduct the simulation. The COVID-19 IoMTSM-HMFIS system has an overall accuracy of approximately 83%. Finally, to achieve improved performance, the analysis results of the system were shared with experts of the Lahore General Hospital, Lahore, Pakistan.     

Prediction of Cloud Ranking in a Hyperconverged Cloud Ecosystem Using Machine Learning

Cloud computing is becoming popular technology due to its functional properties and variety of customer-oriented services over the Internet. The design of reliable and high-quality cloud applications requires a strong Quality of Service QoS parameter metric. In a hyperconverged cloud ecosystem environment, building high-reliability cloud applications is a challenging job. The selection of cloud services is based on the QoS parameters that play essential roles in optimizing and improving cloud rankings. The emergence of cloud computing is significantly reshaping the digital ecosystem, and the numerous services offered by cloud service providers are playing a vital role in this transformation. Hyperconverged software-based unified utilities combine storage virtualization, compute virtualization, and network virtualization. The availability of the latter has also raised the demand for QoS. Due to the diversity of services, the respective quality parameters are also in abundance and need a carefully designed mechanism to compare and identify the critical, common, and impactful parameters. It is also necessary to reconsider the market needs in terms of service requirements and the QoS provided by various CSPs. This research provides a machine learning-based mechanism to monitor the QoS in a hyperconverged environment with three core service parameters: service quality, downtime of servers, and outage of cloud services.     

Cloud-based efficient scheme for handwritten digit recognition

Multimedia Tools and Applications - Handwritten character recognition has been acknowledged and achieved more prominent attention in pattern recognition research community due to enormous...     

Characteristics of Retinitis Pigmentosa Associated with ADGRV1 and Comparison with USH2A in Patients from a Multicentric Usher Syndrome Study Treatrush

In contrast to USH2A, variants in ADGRV1 are a minor cause of Usher syndrome type 2, and the associated phenotype is less known. The purpose of the study was to characterize the retinal phenotype of 18 ADGRV1 patients (9 male, 9 female; median age 52 years) and compare it with that of 204 USH2A patients (111 male, 93 female; median age 43 years) in terms of nyctalopia onset, best corrected visual acuity (BCVA), fundus autofluorescence (FAF), and optical coherence tomography (OCT) features. There was no statistical difference in the median age at onset (30 and 18 years; Mann–Whitney U test, p = 0.13); the mean age when 50% of the patients reached legal blindness (≥1.0 log MAR) based on visual acuity (64 years for both groups; log-rank, p = 0.3); the risk of developing advanced retinal degeneration (patch or atrophy) with age (multiple logistic regression, p = 0.8); or the frequency of cystoid macular edema (31% vs. 26%, Fisher’s exact test, p = 0.4). ADGRV1 and USH2A retinopathy were indistinguishable in all major functional and structural characteristics, suggesting that the loss of function of the corresponding proteins produces similar effects in the retina. The results are important for counseling ADGRV1 patients, who represent the minor patient subgroup.     

Successful utilization of lyophilized lipoprotein(a) as a biological reagent

Lipoprotein(a) [Lp(a)] represents a class of lipoprotein particles having as a protein moiety apoB-100 linked by a single disulfide bond to apolipoprotein(a) [apo(a)], a multikringle structure with a high degree of homology with plasminogen. A recognized feature of Lp(a) is its instability on storage caused by attendant protein and lipid modifications that affect the structural, functional, and immunological properties of this lipoprotein. Here we present data showing that, under appropriate conditions of cryopreservation, Lp(a) retains the properties of the freshly isolated product, and we provide examples supporting the stability of this cryopreserved product as a primary standard in immunoassay settings and in cell culture systems.     

The Interaction Between Lipoxygenase‐Catalyzed Oxidation and Autoxidation in Dry‐Cured Bacon and a Model System

A model system was conducted to characterize the interaction between lipid autoxidation and enzyme‐catalyzed oxidation in dry‐cured bacon. This involved the use of a hydroxyl radical (HO?) generating system and the extraction and purification of lipoxygenases (LOX) from pork belly. The results showed that LOX activity rapidly (P < 0.05) increased during the curing of dry‐cured bacon. This may be because of the hydroxyl‐radical‐mediated oxidation from LOX‐Fe²⁺ to LOX‐Fe³⁺, which activates LOX. In addition, experiments of the model system also showed that LOX activity could be inhibited by increasing the substrate concentration, although substrate type and concentration had no effect on autoxidation. Moreover, LOX enzyme‐catalyzed oxidation and autoxidation could act synergistically to promote lipid oxidation irrespective of the substrate (linoleic or arachidonic acid). These results provide useful information for regulating lipid oxidation during the production of dry‐cured pork products.     

IS-CORDIC: a fixed-point inverse recoded single iteration CORDIC architecture

This paper presents a novel modified Coordinate Rotation Digital Computer (CORDIC) architecture that computes values of sine and cosine in a single cycle. The proposed method utilises angle-recoding technique to design a modified CORDIC algorithm. Multiple iterations are merged in the modified algorithm using memory storage for initial iterations and employing inverse recoding to generate constant multiplication factors for the remaining iterations. Scale factor of the algorithm remains constant, as these factors are independent of intermediate directions of rotation. In addition, the architecture is mapped onto a single CORDIC computation element that requires only a single cycle to compute the result. These multiplications are implemented using dedicated hardware multipliers in Field Programmable Gate Arrays and customised fixed-point multiplication techniques for Application Specific Integrated Circuits. Implementation results show that the proposed IS-CORDIC architecture is 7.9 times more efficient than basic CORDIC and has reduced area-delay product than current state of the art implementations.     

The pH-Dependent Controlled Release of Encapsulated Vitamin B1 from Liposomal Nanocarrier

In this work, we firstly presented a simple encapsulation method to prepare thiamine hydrochloride (vitamin B₁)-loaded asolectin-based liposomes with average hydrodynamic diameter of ca. 225 and 245 nm under physiological and acidic conditions, respectively. In addition to the optimization of the sonication and magnetic stirring times used for size regulation, the effect of the concentrations of both asolectin carrier and initial vitamin B₁ on the entrapment efficiency (EE %) was also investigated. Thermoanalytical measurements clearly demonstrated that after the successful encapsulation, only weak interactions were discovered between the carriers and the drug molecules. Moreover, the dissolution profiles under physiological (pH = 7.40) and gastric conditions (pH = 1.50) were also registered and the release profiles of our liposomal B₁ system were compared with the dissolution profile of the pure drug solution and a manufactured tablet containing thiamin hydrochloride as active ingredient. The release curves were evaluated by nonlinear fitting of six different kinetic models. The best goodness of fit, where the correlation coefficients in the case of all three systems were larger than 0.98, was reached by application of the well-known second-order kinetic model. Based on the evaluation, it was estimated that our liposomal nanocarrier system shows 4.5-fold and 1.5-fold larger drug retention compared to the unpackaged vitamin B₁ under physiological conditions and in artificial gastric juice, respectively.