Trustee: A Trust Management System for Fog-enabled Cyber Physical Systems

In this paper, we propose a lightweight trust management system (TMS) for fog-enabled cyber physical systems (Fog-CPS). Trust computation is based on multi-factor and multi-dimensional parameters, and formulated as a statistical regression problem which is solved by employing random forest regression model. Additionally, as the Fog-CPS systems could be deployed in open and unprotected environments, the CPS devices and fog nodes are vulnerable to numerous attacks namely, collusion, self-promotion, badmouthing, ballot-stuffing, and opportunistic service. The compromised entities can impact the accuracy of trust computation model by increasing/decreasing the trust of other nodes. These challenges are addressed by designing a generic trust credibility model which can countermeasures the compromise of both CPS devices and fog nodes. The credibility of each newly computed trust value is evaluated and subsequently adjusted by correlating it with a standard deviation threshold. The standard deviation is quantified by computing the trust in two configurations of hostile environments and subsequently comparing it with the trust value in a legitimate/normal environment. Our results demonstrate that credibility model successfully countermeasures the malicious behaviour of all Fog-CPS entities i.e. CPS devices and fog nodes. The multi-factor trust assessment and credibility evaluation enable accurate and precise trust computation and guarantee a dependable Fog-CPS system

Clinical expression of plakophilin-2 mutations in familial arrhythmogenic right ventricular cardiomyopathy

Background - Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiac disorder characterized by loss of cardiomyocytes and their replacement by adipose and fibrous tissue. It is considered a disease of cell adhesion because mutations in desmosomal genes, desmoplakin and plakoglobin, have been implicated in the pathogenesis of ARVC. In a recent report, mutations in plakophilin-2, a gene highly expressed in cardiac desmosomes, have been shown to cause ARVC.Methods and Results - We investigated 100 white patients with ARVC for mutations in plakophilin-2. Nine different mutations were identified by direct sequencing in 11 cases. Five of these mutations are novel (A733fsX740, L586fsX658, V570fsX576, R413X, and P533fsX561) and predicted to cause a premature truncation of the plakophilin-2 protein. Family studies showed incomplete disease expression in mutation carriers and identified a number of individuals who would be misdiagnosed with the existing International Task Force and modified diagnostic criteria for ARVC.Conclusions - In this study, we provide new evidence that mutations in the desmosomal plakophilin-2 gene can cause ARVC. A systematic clinical evaluation of mutation carriers within families demonstrated variable phenotypic expression, even among individuals with the same mutation, and highlighted the need for a more accurate set of diagnostic criteria for ARVC

Effect of l-proline and l-tryptophan on somatic embryogenesis and plantlet regeneration of rice (Oryza sativa L. cv. Pusa 169)

This article does not have an abstract

An Overview of Chitosan-Xanthan Gum Matrices as Controlled Release Drug Carriers

Naturally occurring polysaccharides and/or their chemically modified derivatives have been widely investigated in relation to their use as components of controlled release systems for drug delivery. The aforementioned is due, in part, to their distinct properties such as abundant availability and biocompatibility as well as environmental and economic advantages. Chitosan (CS) and xanthan gum (XG) based matrices have received growing scientific/pharmaceutical interest as oral controlled release drug carriers. Herein, recent advances spanning the last two decades in CS-XG based drug delivery systems are reviewed with the emphasis being on oral tablet formulations, due to their versatility as pharmaceutical dosage forms. The mechanism of interaction between CS and XG, by means of computational and experimental approaches, is scrutinized. Results obtained from the literature establish the possibility of fabricating a controlled release drug delivery system based on CS and XG matrices. This can be achieved by monitoring and manipulating the physiochemical properties of the two polymers as well as the experimental variables affecting their drug retardation efficiency, without the need to employ special equipment or sophisticated experimental techniques/methodologies

Investigation of single beam near-infrared free space optical communication under different weather anomalies

The Free space optics (FSO) is a wireless optical communication system that connects directly to the atmosphere, where the connection is established between transmitter and receiver within in the line of sight. The FSO poses a high-speed broadband, which is the last mile wireless optical communication, deployed relatively fast. However, there are some weather factors may affect the performance of FSO transmission. In this paper, we analyzed the performance of Non-Return to Zero (NRZ) modulation schemes, which is used in FSO communication under extreme weather conditions over a range of 2Km. The performance has been analyzed under 980nm wavelength, Bit Error Rate (BER), and Q-factor using Opt system. The largest attenuation measured is 340dB/Km, correlate to the visibility of 50m. In addition the visibility exceeding about 50m, The Kruse formula provides a good measurement of optical attenuation over long distances under the clear weather and haze conditions respectively

Thermal studies of L, D and β-alanine

α-Amino acids are generally studied by spectroscopic techniques, to determine their structure and distinguish between L and D forms (Caroline et al., 2009). Their study via thermal analysis is usually combined with other analytical techniques such as FT-IR, MS, HPLC, GC or NMR to identify the products of thermal decomposition (Kumar et al., 2006, Rodante and Marrosu, 1990). It is intriguing to ascertain whether thermal analytical techniques alone can provide useful information about amino acids, in terms of their physicochemical properties, and their techniques ability to distinguish between L and D forms

Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique

Condition monitoring of wind turbines is progressively increasing to maintain the continuity of clean energy supply to power grids. This issue is of great importance since it prevents wind turbines from failing and overheating, as most wind turbines with doubly fed induction generators (DFIG) are overheated due to faults in generator bearings. Bearing fault detection has become a main topic targeting the optimum operation, unscheduled downtime, and maintenance cost of turbine generators. Wind turbines are equipped with condition monitoring devices. However, effective and reliable fault detection still faces significant difficulties. As the majority of health monitoring techniques are primarily focused on a single operating condition, they are unable to effectively determine the health condition of turbines, which results in unwanted downtimes. New and reliable strategies for data analysis were incorporated into this research, given the large amount and variety of data. The development of a new model of the temperature of the DFIG bearing versus wind speed to identify false alarms is the key innovation of this work. This research aims to analyze the parameters for condition monitoring of DFIG bearings using SCADA data for k-means clustering training. The variables of k are obtained by the elbow method that revealed three classes of k (k = 0, 1, and 2). Box plot visualization is used to quantify data points. The average rotation speed and average temperature measurement of the DFIG bearings are found to be primary indicators to characterize normal or irregular operating conditions. In order to evaluate the performance of the clustering model, an analysis of the assessment indices is also executed. The ultimate goal of the study is to be able to use SCADA-recorded data to provide advance warning of failures or performance issues

Continuous manufacturing of high quality pharmaceutical cocrystals integrated with process analytical tools for in-line process control

A continuous manufacturing process for pharmaceutical indomethacin–saccharine cocrystals was achieved by extrusion processing with high throughput. Down-stream milling and blending of the extrudates was followed by feeding the formulated cocrystals in a capsule-filling machine. By applying a quality by design approach, the process was optimized and scaled up to produce 3000 capsules/h of pharmaceutical cocrystals. Process analytical tools such as near infrared reflectance and spatial filter velocimetry probes were coupled at various process stages for in-line monitoring and quality control. Further physicochemical characterization of extruded batches confirmed the manufacturing of high quality cocrystals. A fully integrated continuous process starting from raw materials to produce a finished product was assembled with only six unit operations and a small footprint. The study is a paradigm of continuous manufacturing of pharmaceutical cocrystals