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.     

An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

Cubic–Quartic Optical Solitons with Differential Group Delay for Kudryashov’s Model by Extended Trial Function

Journal of Communications Technology and Electronics - This paper implements mathematically rigorous extended trial function algorithm to address cubic–quartic optical solitons in...     

Effect of 100 KeV Ar+ ion beam irradiation on ZnO thin films – Influence of morphology vis-a-vis electrode/electrolyte interface and its impact on photoelectrochemical water splitting

The present study attempts quantitative determination of changes in the morphological surface features viz. fractal dimension, lower and upper cut off length scale through Power Spectral Density analysis prior to and after irradiation of 100 KeV Ar⁺ ion beam at incidence angles of 0°, 40° and 60° on ZnO thin films. All the unirradiated and irradiated samples are subjected to photoelectrochemical characterization and a correlation between photoelectrochemical performance and morphological parameters is established. Sample irradiated at 40° angle at the fluence of 5 × 10¹⁶ ions/cm² is found to possess maximum fractal dimension of 2.72, lower and upper cut off length scale of 3.16 nm and 63.00 nm respectively. This sample exhibits maximum photocurrent density of 3.19 mA/cm² and applied bias photon-to-current efficiency of 1.12% at 1.23 V/RHE. Hydrogen gas collected for duration of 1 h for the same sample was ~4.83 mLcm^?2.     

Design and performance study of phase‐locked loop using fractional‐order loop filter

The present work reports the realization of an analog fractional‐order phase‐locked loop (FPLL) using a fractional capacitor. The expressions for bandwidth, capture range, and lock range of the FPLL have been derived analytically and then compared with the experimental observations using LM565 IC. It has been observed that bandwidth and capture range can be extended by using FPLL. It has also been found that FPLL can provide faster response and lower phase error at the time of switching compared to its integer‐order counterpart. Copyright © 2014 John Wiley & Sons, Ltd.     

Synthesis and characterization of a novel Ca-alginate-biochar composite as efficient zinc (Zn2+) adsorbent: Thermodynamics,process design,mass transfer and isotherm modeling

In this present work, Ca-alginate-biochar adsorbent has been synthesized, characterized and tested its effectiveness in the removal of aqueous phase Zn²⁺ metal. The removal efficiency was studied under various physicochemical process parameters. External mass transfer model, intraparticle diffusion model and pseudo-first-order and pseudo-second-order models were used to fit the experimental Zn²⁺ adoption kinetic results and to identify the mechanism of adsorption. The desorption studies indicate the possibilities of ion-exchange and physical–chemical adsorption of Zn^2+. The adsorption was best described by Langmuir isotherm model. Thermodynamic parameters suggested that the adsorption process becomes spontaneous, endothermic and irreversible in nature.     

Profile of Triacylglycerols,Phenols, and Vitamin E of Manjari Medika Grape Seed Oil and Cake: Introducing a Novel Indian Variety

The aim of the study is to investigate the biochemical composition of grapeseed oil and cake from an unexplored Indian grape‐juice cultivar, Manjari Medika (MM). The composition of oil and residual seed cake is evaluated using various chromatographic and spectroscopic techniques. The findings demonstrate that the vitamin E content of MM‐seed oil (1.15–1.35 g kg^?1) is distinctively higher than the Codex standard, suggesting its superior quality as an edible oil. The predominant triacylglycerols include trilinolein (LLL, 43%), dilinoleoyl‐stearylglycerol (LSL, 19%), and dilinoleoyl‐palmitoylglycerol (LLP, 11%), which are earlier recognized as natural antioxidants. The seed‐cake is rich in polyphenols including acylated anthocyanins (e.g., pelargonidin‐3‐O‐coumaroyl glucoside) and certain other flavonoids (e.g., catechin). The profile of phytonutrients in MM seed‐oil and cake is significantly superior to its seeded female parent and two other widely cultivated wine‐grape varieties. In brief, the studied by‐products of this new grape‐juice cultivar can be an important source of high‐value ingredients for use in food supplements, nutraceuticals, and functional foods. Practical applications: This study reports the phytochemical profile of the seed‐oil and seed cake derived from a newly developed grape variety, Manjari Medika. High contents of selective antioxidants: lipids, vitamin E, and phenols in the seed‐oil and cake with health benefits suggest their potential for use in nutraceutical and functional foods. These byproducts can be utilised as ingredients of functional foods and nutraceuticals (e.g., grape seed oil capsule) and also as raw materials in food supply chains (e.g., for production of grape cookies or cake). MM can also be utilized as a colorant in the food industry.     

Attribute Allocation and Retrieval Scheme for Large-Scale Sensor Networks

Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes.     

An assessment of the Spanish national hydrological plan

The paper is a comprehensive review of the Spanish National Hydrological Plan, which proposes to transfer water from the lower part of the Ebro River up to the Levante basins, around 912 km away. The National Hydrological Plan is a conventional, static plan, which focuses primarily on supply management. The plan is based on the explicit assumption that the world will change only incrementally during its entire economic life of 100-200 years. The analysis indicates that much of the increased water demands forecasted are unlikely to materialize due to increasing emphasis on demand management practices, major structural changes in the agricultural sector that will occur by 2020 and the requirements of the Water Directive of the European Union, which must be fulfilled by 2010. Even now, the cost per cubic metre of water delivered at the end of the transfer is nearly twice the cost of desalinated water. The National Hydrological Plan in its present form cannot be justified for economic, environmental and social reasons. In addition, the plan will not be necessary if demand management practices are implemented.