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Introduction Mesomelic dysplasias are a group of skeletal disorders characterised by shortness of the middle limb segments (mesomelia). They are divided into 11 different categories. Among those without known molecular basis is mesomelic dysplasia Savarirayan type, characterised by severe shortness of the middle segment of the lower limb. Objective To identify the molecular cause of mesomelic dysplasia Savarirayan type. Methods and results We performed array comparative genomic hybridisation in three unrelated patients with mesomelic dysplasia Savarirayan type and identified 2 Mb overlapping de novo microdeletions on chromosome 6p22.3. The deletions encompass four known genes: MBOAT1, E2F3, CDKAL1 and SOX4. All patients showed mesomelia of the lower limbs with hypoplastic tibiae and fibulae. We identified a fourth patient with intellectual disability and an overlapping slightly larger do novo deletion also encompassing the flanking gene ID4. Given the fact that the fourth patient had no skeletal abnormalities and none of the genes in the deleted interval are known to be associated with abnormalities in skeletal development, other mutational mechanisms than loss of function of the deleted genes have to be considered. Analysis of the genomic region showed that the deletion removes two regulatory boundaries and brings several potential limb enhancers into close proximity of ID4. Thus, the deletion could result in the aberrant activation and misexpression of ID4 in the limb bud, thereby causing the mesomelic dysplasia. Conclusions Our data indicate that the distinct deletion 6p22.3 is associated with mesomelic dysplasia Savarirayan type featuring hypoplastic, triangular-shaped tibiae and abnormally shaped or hypoplastic fibulae. [ABSTRACT FROM AUTHOR]

Purpose – In the recent scenario, there are various issues related to wireless sensor networks such as clustering, routing, packet loss, network strength. The core functionality of primarily wireless sensor networks is sensor nodes that are randomly scattered over a specific area. The sensor senses the data and sends it to the base station. Energy consumption is an important issue in wireless sensor networks. Clustering and cluster head selection is an important method used to extend the lifetime of wireless sensor networks. The main goal of this research article is to reduce energy consumption using a clustering process such as CH determination, cluster formation, and data dissemination. Methodology/approach/design – The simulation in this paper was finished utilizing MATLAB programming methodology and the proposed technique is contrasted with the LEACH and MOD-LEACH protocols. Findings – The simulation results of this research show that the energy consumption and dead node ratio are improved of wireless sensor networks as compared to the LEACH and MOD-LEACH algorithms. Originality/value – In the wireless sensor network there are various constraints energy is one of them. In order to solve this problem use CH selection algorithms to reduce energy consumption and consequently increase network lifetime.

Purpose – If the two or more than two antennas are present in the antenna array, the mutual coupling between them becomes a critical issue to deal with. At microwave frequency, microstrip design is often used as a transmission line because of its good performance in transferring the energy and microwave signals. Most commonly used microstrip antenna has similar structure as that of the microstrip line. On one side of dielectric substrate layer, is an extremely thin layer of conductor that forms the radiating elements and on bottom side is the ground plane made up of metallic material. Our main motive is to maintain mutual coupling suppressing structure to its simplest form. Methodology/approach/design – We therefore use a Defected Ground Structure (DGS), which greatly decreases the mutual coupling between the two antennas, thus enhancing the performance of the antenna array. Findings – The introduction of the DGS does not affect the characteristics of antenna array system. The Simulation is done using CST (Computer Simulation Technology) software and the results are tested using Vector Network Analyzer. Both the simulated and measured results are in good agreement. The coupling has been reduced from -22 to -37 dB. The recent boom in wireless industry has led to the demand for the multiband antennas.

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.