Insulin Gene Therapy for Type 1 Diabetes Mellitus: Unique Challenges Require Innovative Solutions

Type 1 diabetes mellitus (T1DM) is a disease characterized by chronically elevated blood glucose levels that results from the autoimmune destruction of the insulin-producing β cells of the pancreas. While treatment options exist, they all possess serious limitations. Insulin gene therapy provides a promising alternative aimed at replacing insulin production in native non-β cells. For insulin gene therapy applications to be successful in treating T1DM, a glucose-sensitive organ must be targeted for insulin expression, insulin production must be responsive to ever-changing blood glucose levels, and insulin expression must persist long term. In addition, the amount of insulin production is critical, as too little insulin would lead to poor glucose regulation and too much insulin would induce hypoglycemia, a potentially life-threatening state. Together, insulin gene therapy provides challenges that are absent with other gene therapy applications. In this chapter, we examine the challenges of insulin gene therapy and discuss how the two key components of insulin gene therapy—the insulin expression cassette and the delivery vehicle—can be tailored for the successful treatment of T1DM

A study on Stress among University Students, Bangladesh

Abstract: This cross sectional study was conducted with the purpose to find out the causes of stress among university students. This study was carried out in Jahangirnagar University, Savar, Dhaka, Bangladesh during the period of November 2017 to January 2018. Convenience sampling technique was adapted for the selection of respondents for data collection. A quantitative method was used in gathering and analyzing the data. For this purpose, structured questionnaires were distributed to the students of Jahangirnagar University. The results obtained show the different factors that cause stress among the students of Jahangirnagar University. According to 86% of 200 respondents, future worry was the most effective factor causing stress. 70.5% respondents thought examination tension as a major cause of stress. According to 61% respondents, working with news people also was a source of stress. 61% respondents said that, lots of group work caused stress among them. Relationship conflict was admitted as a major source of stress by 59.5% respondents. 55.5% respondents felt stressed due to financial crisis and also for failure in combing job with study. Misunderstanding class lectures, bad living condition, lower academic grade were also major causes of stress among respondents. This study also identified the level of stress among the respondents. It revealed that, among 200 respondents, 61.5% were moderately stressed, 18.5% were stressed with low level and 20% respondents had high level of stress

FINITE ELEMENT ANALYSIS OF HELICAL COIL COMPRESSION SPRING FOR THREE WHEELER AUTOMOTIVE FRONT SUSPENSION

The current paper deals with the stress analysis of a helical coil compression spring, which is employed in three wheeler’s auto-rickshaw belonging to the medium segment of the Indian automotive market. In the design of this kind of spring both the elastic characteristics and the fatigue strength have to be considered as significant aspects. In addition to this particular elastic property, as a consequence of the research effort in reducing the mass of components typical of the automotive industry, these springs have to face very high working stresses. The structural reliability of the spring must therefore be ensured. So for this purpose the static stress analysis using finite element method has been done in order to find out the detailed stress distribution of the spring

New Development of Anodic Electro-catalyst for Chlor-alkali Industry

Anodic electro catalysts are developed by using a titanium substrate coated with different compositions of mixed oxides, as it follows: ruthenium-titanium mixed oxides; ruthenium-titanium-tin mixed oxides; and ruthenium-titanium-iridium mixed oxides. The performance of electro catalysts was further evaluated by measuring coating thickness, studying coating morphology with microscope, identifying the presence of RuO2, TiO2, IrO2 and SnO2 in coating film, analyzing shape of individual crystal by XRD, performing accelerated life test and current efficiency test of the selected anode. The coating composition of 15% RuO2, 15% IrO2 and 70% TiO2 exhibited premium properties among the studied anodes

Surface Coatings and Treatments for Controlled Hydrate Formation: A Mini Review

LA/P/0008/2020Gas hydrates (GHs) are known to pose serious flow assurance challenges for the oil and gas industry. Neverthless, over the last few decades, gas hydrates-based technology has been explored for various energy- and environmentally related applications. For both applications, a controlled formation of GHs is desired. Management of hydrate formation by allowing them to form within the pipelines in a controlled form over their complete mitigation is preferred. Moreover, environmental, benign, non-chemical methods to accelerate the rate of hydrate formation are in demand. This review focused on the progress made in the last decade on the use of various surface coatings and treatments to control the hydrate formation at atmospheric pressure and in realistic conditions of high pressure. It can be inferred that both surface chemistry (hydrophobicity/hydrophilicity) and surface morphology play a significant role in deciding the hydrate adhesion on a given surface.publishersversionpublishe

Effect of Fibre Type on Mechanical Properties of Nonwoven Reinforced TPU Composites

Nonwoven-reinforced composites were produced using both low modulus fibres (lyocell, polyethylene terephthalate, and polyamide) and high modulus aramid fibres (polyphenylene terephthalamide) in thermoplastic polyurethane (TPU) matrix. Preferentially oriented web preforms were prepared by carding and pre-needling before impregnating the nonwovens in a thermoplastic polyurethane resin matrix. Composites were prepared by compression moulding and mechanical properties were evaluated. Scanning Electron Microscopy was employed to study the fibre-to-matrix interface in the nonwoven-reinforced composites. It was found that nonwoven reinforcement provided a range of mechanical properties, mainly linked to fibre properties and orientation of fibres in the web, apparently unaffected by the mechanical properties of the web. Furthermore, all studies fibres were thoroughly embedded in the matrix

Investigation of ring, airjet and rotor spun yarn structures on the fragmented fibers (microplastics) released from polyester textiles during laundering

The release of fragmented fibers (FFs), including microplastics from textiles, during their service life is considered an established source of environmental pollution. The yarn structure is identified to affect the amount and length distribution profile of shed FFs from textiles. In the present work, the impact of yarn structures spun from 100% polyester staple fibers, using commercially relevant spun yarn technologies in the textile industry, on the release of FFs from textiles is studied. The bespoke woven fabric samples produced from three types of spun yarns, which include ring, airjet (air vortex) and rotor yarns, were subjected to an accelerated washing process, for up to five washes, to quantify shed FFs and their length distribution profile. The morphological shapes of FF ends associated with the nature of fiber damage were also investigated. The results demonstrated that airjet and rotor yarn structures had released 28% and 33% less mass of FFs, respectively, as compared to the ring yarn structure during the whole washing process. The length distribution profile identified that the ring yarn structure shed longer length FFs as compared to both airjet and rotor ones. The damaged ends highlight the importance of textile manufacturing processes on the generation of FFs. The results of this study give a better understanding of the yarn structural effect of commercially relevant technologies on shedding of FFs, which are released as a pollutant to the environment

Bandstop Filter Design for GSM Shielding Using Frequency Selective Surfaces

In this paper, the performance of bandstop Frequency Selective Surface (FSS) is presented which can be used to provide wireless security on airports and other sensitive places, where a mobile phone can be used to set-off an explosive device. It can also be used to block the mobile signals at the places of worship, hospitals and cinemas where the annoying voice of a mobile phone may irritate the masses. The FSS unit cell consists of two metallic square-loop elements printed on FR-4 substrate with different periodicities. The outer and inner square-loop elements are tuned to 900 MHz and 1800 MHz, respectively. It has a stable frequency response at oblique incidences for both perpendicular (TE) and parallel (TM) polarizations. Simulation results are presented to give an overview for the performance of proposed FSS design.DOI:http://dx.doi.org/10.11591/ijece.v2i6.182

Ensemble learning based defect detection of laser sintering

In rapid development, Selective Laser Sintering (SLS) creates prototypes by processing industrial materials, for example, polymers. Such materials are usually in powder form and fused by a laser beam. The manufacturing quality depends on the interaction between a high-energy laser beam and the powdered material. However, in-homogeneous temperature distribution, unstable laser powder, and inconsistent powder densities can cause defects in the final product, for example, Powder Bed Defects. Such factors can lead to irregularities, for example, warping, distortion, and inadequate powder bed fusion. These irregularities may affect the profitable SLS production. Consequently, detecting powder bed defects requires automation. An ensemble learning-based approach is proposed for detecting defects in SLS powder bed images from this perceptive. The proposed approach first pre-processes the images to reduce the computational complexity. Then, the Convolutional Neural Network (CNN) based ensembled models (off-the-shelf CNN, bagged CNN, and boosted CNN) are implemented and compared. The ensemble learning CNN (bagged and boosted CNN) is good for powder bed detection. The evaluation results indicate that the performance of bagged CNN is significant. It also indicates that preprocessing of the images, mainly cropping to the region of interest, improves the performance of the proposed approach. The training and testing accuracy of the bagged CNN is 96.1% and 95.1%, respectively.© 2023The Authors. IET Optoelectronics published by John Wiley& Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License,which permits use, distribution and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed