4D Printing of Shape Memory Materials for Textiles: Mechanism,Mathematical Modeling,and Challenges

Shape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.     

Synergistic Effects of Polybenzimidazole and Aramide on Enhancing Flame-Retardancy and Solubility

Aromatic and functional polymers with processibility derived from biobased starting materials are prerequisite considering sustainable society. Poly(2,5-benzimidazole)s are rigid-rod polymers to show ultrahigh thermal stability such as flame retardance, while usually suffer from poor solubility. Here, poly(benzimidazole-co-amide)s are synthesized from two biobased monomers, 3,4-diaminobenzoic acid and a semirigid comonomer, 4-aminohydrocinnamic acid. The copolymers with an amide composition of 80 mol% and higher are soluble in widely used polar solvents to fabricate the films keeping high flame retardance, which is comparable with popular high-performance polymers such as aromatic polyimides, polyetheretherketone, polyphenylene sulfide, etc.     

Smart Edge Computing for 5 g/6 g Satellite IOT for Reducing Inter Transmission Delay

Mobile Networks and Applications - 5G/6G communication are first generation high speed wireless communication network which integrates the aerial data, terrestrial data and maritime data via...     

A Mobile Cloud-Based eHealth Scheme

Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace. Similarly, the field of health informatics is also considered as an extremely important field. This work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing analysis. The developed system has two front ends, the first dedicated for the user to perform the photographing of the trace report. Once the photographing is complete, mobile computing is used to extract the signal. Once the signal is extracted, it is uploaded into the server and further analysis is performed on the signal in the cloud. Once this is done, the second interface, intended for the use of the physician, can download and view the trace from the cloud. The data is securely held using a password-based authentication method. The system presented here is one of the first attempts at delivering the total solution, and after further upgrades, it will be possible to deploy the system in a commercial setting.     

Influence of HMTA ligand in MMA AGET ATRP emulsion polymerization

Interactions of hexamethylenetetramine ligand in atom transfer radical polymerization initiated by activator generated by electron transfer were studied. Polymerization of methyl methacrylate was done using two-step experimental procedure in 2 L emulsion batch reactor at 50, 60, and 80°C. The selection of reactant ratios was quite challenging for a reactor of this size. Replicate runs were conducted for data reproducibility purpose. Gravimetry method and gel permeation chromatography were used to determine monomer conversion, Mn, and PDI of polymer samples. PMMA produced was also characterized by means of dynamic light scattering, Fourier-transform infrared spectroscopy and nuclear Magnetic Resonance spectroscopy. Results showed high monomer conversion up to 93% and Mn ranging 243–274 kg/mol with PDI from 1.45 to 1.60. Besides, combining HMTA with sodium dodecyl sulfate, an anionic surfactant, a well-controlled polymer with a lower Mn of 201 kg/mol and PDI of 1.56 was obtained in 3 hr reaction time.     

Relevance feedback for CBIR: a new approach based on probabilistic feature weighting with positive and negative examples.

In content-based image retrieval, understanding the user's needs is a challenging task that requires integrating him in the process of retrieval. Relevance feedback (RF) has proven to be an effective tool for taking the user's judgement into account. In this paper, we present a new RF framework based on a feature selection algorithm that nicely combines the advantages of a probabilistic formulation with those of using both the positive example (PE) and the negative example (NE). Through interaction with the user, our algorithm learns the importance he assigns to image features, and then applies the results obtained to define similarity measures that correspond better to his judgement. The use of the NE allows images undesired by the user to be discarded, thereby improving retrieval accuracy. As for the probabilistic formulation of the problem, it presents a multitude of advantages and opens the door to more modeling possibilities that achieve a good feature selection. It makes it possible to cluster the query data into classes, choose the probability law that best models each class, model missing data, and support queries with multiple PE and/or NE classes. The basic principle of our algorithm is to assign more importance to features with a high likelihood and those which distinguish well between PE classes and NE classes. The proposed algorithm was validated separately and in image retrieval context, and the experiments show that it performs a good feature selection and contributes to improving retrieval effectiveness.     

A new approach to modelling of single droplet drying

A model was developed to predict the change in droplet mass and temperature when it is exposed to hot air, as in spray drying of droplets containing solids. The droplet was assumed first to undergo sensible rapid heating with no mass change. Then the droplet experiences some shrinkage, with no temperature change but rapid mass losses, followed by a period of crust formation with a significant change in droplet mass and temperature and finally a short period of sensible heating of the dried particle. The model, unlike previous models, accounts for shrinkage and for the temperature distribution in the droplet. It provided a good prediction for the change in droplet temperature and mass for some of the experimental measurements available in the literatures.