Technologies, Volume 8, Issue 4 (December 2020) – 31 articles

Catharanthus roseus (C. roseus) is an important medicinal plant distributed in many countries. It has attracted increasing attention due to it being shown to possess a range of phytochemicals with various biological activities such as antioxidant, antibacterial, antifungal, antidiabetic and anticancer properties. Remarkably, vinblastine and vincristine isolated from this plant were the first plant-derived anticancer agents deployed for clinical use. Recently, new isolated indole alkaloids from this plant including catharoseumine, 14′,15′-didehydrocyclovinblastine, 17-deacetoxycyclovinblastine and 17-deacetoxyvinamidine effectively inhibited human cancer cell lines in vitro. Moreover, vindoline, vindolidine, vindolicine and vindolinine isolated from C. roseus leaf exhibited in vitro antidiabetic property. These findings strongly indicate that this plant is still a promising source of bioactive compounds, which should be further investigated. This paper provides an overview of the traditional use and phytochemical profiles of C. roseus, and summarises updated techniques of the preparation of dried material, extraction and isolation of bioactive compounds from this plant. In addition, purported health benefits of the extracts and bioactive compounds derived from this plant were also addressed to support their potential as therapeutic agents. Full article

In the field of information technology, information security technologies hold a special place. They ensure the security of the use of information technology. One of the urgent tasks is the protection of electronic documents during their transfer in information systems, including smart systems. This paper proposes a technology for protecting electronic documents containing digital images. The main idea is that the electronic document authorship can be protected by embedding digital watermarks in the images that are contained in this document. The paper considers three cases of using the proposed technology: full copying of an electronic document, copying of images contained in the document, and copying of text. It is shown that in all three cases, the authorship confirmation can be successfully implemented. Some areas of the proposed technology application are described, including augmented reality applications. Computational experiments are conducted with robust watermarking algorithms that can be used within the technology. A scenario of technology implementation is proposed which provides for the joint use of different class algorithms. Full article

A mathematical model employing the concept of energy-equivalent inhomogeneity is applied to analyze short cylindrical fiber composites with interfaces described by the Steigmann–Ogden material surface model. Real inhomogeneity consists of a cylindrical fiber of finite length, and its surface possessing different properties is replaced by a homogeneous, energy-equivalent cylinder. The properties of the energy-equivalent fiber, incorporating properties of the original fiber and its interface, are determined on the basis of Hill’s energy equivalence principle. Closed-form expressions for components of the stiffness tensor of equivalent fiber have been developed and, in the limit, shown to compare well with the results available in the literature for infinite fibers with the Steigmann–Ogden interface model. Dependence of those components on the radius, length of the cylindrical fiber, and surface parameters is included in these expressions. The effective stiffness tensor of the short-fiber composites with so-defined equivalent cylindrical fibers can be determined by any homogenization method developed without accounting for interface. Full article

Recently, the use of extended reality (XR) systems has been on the rise, to tackle various domains such as training, education, safety, etc. With the recent advances in augmented reality (AR), virtual reality (VR) and mixed reality (MR) technologies and ease of availability of high-end, commercially available hardware, the manufacturing industry has seen a rise in the use of advanced XR technologies to train its workforce. While several research publications exist on applications of XR in manufacturing training, a comprehensive review of recent works and applications is lacking to present a clear progress in using such advance technologies. To this end, we present a review of the current state-of-the-art of use of XR technologies in training personnel in the field of manufacturing. First, we put forth the need of XR in manufacturing. We then present several key application domains where XR is being currently applied, notably in maintenance training and in performing assembly task. We also reviewed the applications of XR in other vocational domains and how they can be leveraged in the manufacturing industry. We finally present some current barriers to XR adoption in manufacturing training and highlight the current limitations that should be considered when looking to develop and apply practical applications of XR. Full article

Customer Experience (CX) is monitored through market research surveys, based on metrics like the Net Promoter Score (NPS) and the customer satisfaction for certain experience attributes (e.g., call center, website, billing, service quality, tariff plan). The objective of companies is to maximize NPS through the improvement of the most important CX attributes. However, statistical analysis suggests that there is a lack of clear and accurate association between NPS and the CX attributes’ scores. In this paper, we address the aforementioned deficiency using a novel classification approach, which was developed based on logistic regression and tested with several state-of-the-art machine learning (ML) algorithms. The proposed method was applied on an extended data set from the telecommunication sector and the results were quite promising, showing a significant improvement in most statistical metrics. Full article

The aim of this study was to perform a content analysis of electronic activity monitors that also evaluates utility features, code behavior change techniques included in the monitoring systems, and align the results with intervention functions of the Behaviour Change Wheel program planning model to facilitate informed device selection. Devices were coded for the implemented behavior change techniques and device features. Three trained coders each wore a monitor for at least 1 week from December 2019–April 2020. Apple Watch Nike, Fitbit Versa 2, Fitbit Charge 3, Fitbit Ionic—Adidas Edition, Garmin Vivomove HR, Garmin Vivosmart 4, Amazfit Bip, Galaxy Watch Active, and Withings Steel HR were reviewed. The monitors all paired with a phone/tablet, tracked exercise sessions, and were wrist-worn. On average, the monitors implemented 27 behavior change techniques each. Fitbit devices implemented the most behavior change techniques, including techniques related to the intervention functions: education, enablement, environmental restructuring, coercion, incentivization, modeling, and persuasion. Garmin devices implemented the second highest number of behavior change techniques, including techniques related to enablement, environmental restructuring, and training. Researchers can use these results to guide selection of electronic activity monitors based on their research needs. Full article

Falls are the main cause of susceptibility to severe injuries in many humans, especially for older adults aged 65 and over. Typically, falls are being unnoticed and interpreted as a mere inevitable accident. Various wearable fall warning devices have been created recently for older people. However, most of these devices are dependent on local data processing. Various algorithms are used in wearable sensors to track a real-time fall effectively, which focuses on fall detection via fuzzy-as-a-service based on IEEE 1855–2016, Java Fuzzy Markup Language (FML) and service-oriented architecture. Moreover, several approaches are used to detect a fall using machine learning techniques via human movement positional data to avert any accidents. For fuzzy logic web services, analysis is performed using wearable accelerometer and gyroscope sensors, whereas in machine learning techniques, k-NN, decision tree, random forest and extreme gradient boost are used to differentiate between a fall and non-fall. This study aims to carry out a comparative analysis of real-time fall detection using fuzzy logic web services and machine learning techniques and aims to determine which one is better for real-time fall detection. Research findings exhibit that the proposed fuzzy-as-a-service could easily differentiate between fall and non-fall occurrences in a real-time environment with an accuracy, sensitivity and specificity of 90%, 88.89% and 91.67%, respectively, while the random forest algorithm of machine learning achieved 99.19%, 98.53% and 99.63%, respectively. Full article

The paper is devoted to the research of the effect of ultrasonic postprocessing—specifically, the effects of ultrasonic cavitation-abrasive finishing, ultrasonic plastic deformation, and vibration tumbling on surface quality, wear resistance, and the ability of real aircraft parts with complex geometries and with sizes less than and more than 100 mm to work in exploitation conditions. The parts were produced by laser powder bed fusion from two types of anticorrosion steels of austenitic and martensitic grades—20Kh13 (DIN 1.4021, X20Cr13, AISI 420) and 12Kh18N9T (DIN 1.4541, X10CrNiTi18-10, AISI 321). The finishing technologies based on mechanical action—plastic deformation, abrasive wear, and complex mechanolysis showed an effect on reducing the submicron surface roughness, removing the trapped powder granules from the manufactured functional surfaces and their wear resistance. The tests were completed by proving resistance of the produced parts to exploitation conditions—vibration fatigue and corrosion in salt fog. The roughness arithmetic mean deviation R_a was improved by 50–52% after cavitation-abrasive finishing, by 28–30% after ultrasonic plastic deformation, and by 65–70% after vibratory tumbling. The effect on wear resistance is correlated with the improved roughness. The effect of used techniques on resistance to abrasive wear was explained and grounded. Full article

A fall of an elderly person often leads to serious injuries or even death. Many falls occur in the home environment and remain unrecognized. Therefore, a reliable fall detection is absolutely necessary for a fast help. Wrist-worn accelerometer based fall detection systems are developed, but the accuracy and precision are not standardized, comparable, or sometimes even known. In this work, we present an overview about existing public databases with sensor based fall datasets and harmonize existing wrist-worn datasets for a broader and robust evaluation. Furthermore, we are analyzing the current possible recognition rate of fall detection using deep learning algorithms for mobile and embedded systems. The presented results and databases can be used for further research and optimizations in order to increase the recognition rate to enhance the independent life of the elderly. Furthermore, we give an outlook for a convenient application and wrist device. Full article

Modern drug delivery systems demand the development of targeted polymer-carriers with the set of obligatory requirements. Thus, such capsules must have total biocompatibility, biodegradability, and possess non-allergenic, and non-tumorigenic properties. Hyaluronic acid (HA), as a natural linear polysaccharide that is included in the pericellular and extracellular matrixes, satisfies all these demands in the best possible way. In this study, the biopolymer nanoparticles with an average diameter of 300 nm were successfully obtained from aqueous HA solutions by electrospraying technique and characterized. Due to the presence of active functional groups in the structure of HA, such polymer particles can incorporate various pharmaceutical agents. This finding expands the investigation and subsequent application of drug-loaded nanoparticles based on HA as challenging and advanced targeted delivery systems. Full article

The purpose of this review was to evaluate the current state of the literature and to identify the types of study designs, wearable devices, statistical tests, and exercise modes used in validation and reliability studies conducted in applied settings/outdoor environments. This was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We identified nine articles that fit our inclusion criteria, eight of which tested for validity and one tested for reliability. The studies tested 28 different devices with exercise modalities of running, walking, cycling, and hiking. While there were no universally common analytical techniques used to measure accuracy or validity, correlative measures were used in 88% of studies, mean absolute percentage error (MAPE) in 75%, and Bland–Altman plots in 63%. Intra-class correlation was used to determine reliability. There were not any universally common thresholds to determine validity, however, of the studies that used MAPE and correlation, there were only five devices that had a MAPE of < 10% and a correlation value of > 0.7. Overall, the current review establishes the need for greater testing in applied settings when validating wearables. Researchers should seek to incorporate multiple intensities, populations, and modalities into their study designs while utilizing appropriate analytical techniques to measure and determine validity and reliability. Full article

The rheology of liquids affects their ease of pouring. In this study, the subjects evaluated the feeling of pouring liquids with various viscosities. The situation was recorded with a high-speed camera and force plate. The score for ease of pouring water and 5 wt% thickened aqueous solution was 8.9 ± 1.5 and 2.1 ± 1.6 respectively, demonstrating that the score decreased with increasing viscosity. The three stages of the pouring process, namely the flowing state in which the liquid flows out vigorously (I), the yarning state in which the liquid flows out to stretch (II), and the dripping state in which the liquid flows out as droplets (III) were observed. The duration of state II extended as the viscosity increased. These findings can be useful for the development of characteristic containers and beverages. Full article

Machine learning-based decision support systems bring relief and support to the decision-maker in many domains such as loan application acceptance, dating, hiring, granting parole, insurance coverage, and medical diagnoses. These support systems facilitate processing tremendous amounts of data to decipher the patterns embedded in them. However, these decisions can also absorb and amplify bias embedded in the data. To address this, the work presented in this paper introduces a new fairness measure as well as an enhanced, feature-rich representation derived from the temporal aspects in the data set that permits the selection of the lowest bias model among the set of models learned on various versions of the augmented feature set. Specifically, our approach uses neural networks to forecast recidivism from many unique feature-rich models created from the same raw offender dataset. We create multiple records from one summarizing criminal record per offender in the raw dataset. This is achieved by grouping each set of arrest to release information into a unique record. We use offenders’ criminal history, substance abuse, and treatments taken during imprisonment in different numbers of past arrests to enrich the input feature vectors for the prediction models generated. We propose a fairness measure called Bias Parity (BP) score to measure quantifiable decrease in bias in the prediction models. BP score leverages an existing intuition of bias awareness and summarizes it in a single measure. We demonstrate how BP score can be used to quantify bias for a variety of statistical quantities and how to associate disparate impact with this measure. By using our feature enrichment approach we could increase the accuracy of predicting recidivism for the same dataset from 77.8% in another study to 89.2% in the current study while achieving an improved BP score computed for average accuracy of 99.4, where a value of 100 means no bias for the two subpopulation groups compared. Moreover, an analysis of the accuracy and BP scores for various levels of our feature augmentation method shows consistent trends among scores for a range of fairness measures, illustrating the benefit of the method for picking fairer models without significant loss of accuracy. Full article

This paper scrutinized hydraulic fracturing applications mainly in the United States with regard to both groundwater and surface water contamination with the purpose of bringing forth objective analysis of research findings. Results from previous studies are often unconvincing due to the incomplete database of chemical additives; after and before well-founded water samples to define the change in parameters; and specific sources of water pollution in a particular region. Nonetheless, there is a superior chance of both surface and groundwater contamination induced by improper and less monitored wastewater disposal and management practices. This report has documented systematic evidence for total dissolved solids, salinity, and methane contamination regarding drinking water correlated with hydraulic fracturing. Methane concentrations were found on an average rate of 19.2 mg/L, which is 17 times higher than the acceptance rate and the maximum value was recorded as 64.2 mg/L near the active hydraulic fracturing drilling and extraction zones than that of the nonactive sites (1.1 mg/L). The concentration of total dissolved solids (350 g/L) was characterized as a voluminous amount of saline wastewater, which was quite unexpectedly high. The paper concludes with plausible solutions that should be implemented to avoid further contamination. Full article

The proliferation of Internet of Things devices and services and their integration in everyday environments led to the emergence of intelligent offices, classrooms, conference, and meeting rooms that adhere to the paradigm of Ambient Intelligence. Usually, the type of activities performed in such environments (i.e., presentations and lectures) can be enhanced by the use of large Interactive Boards that—among others—allow access to digital content, promote collaboration, enhance the process of exchanging ideas, and increase the engagement of the audience. Additionally, the board contents are expected to be plenty, in terms of quantity, and diverse, in terms of type (e.g., textual data, pictorial data, multimedia, figures, and charts), which unavoidably makes their manipulation over a large display tiring and cumbersome, especially when the interaction lasts for a considerable amount of time (e.g., during a class hour). Acknowledging both the shortcomings and potentials of Interactive Boards in intelligent conference rooms, meeting rooms, and classrooms, this work introduces a sophisticated framework named CognitOS Board, which takes advantage of (i) the intelligent facilities offered by the environment and (ii) the amenities offered by wall-to-wall displays, in order to enhance presentation-related activities. In this article, we describe the design process of CognitOS Board, elaborate on the available functionality, and discuss the results of a user-based evaluation study. Full article

Smartphones have become an essential part of our lives. Especially its computing power and its current specifications make a modern smartphone a powerful device for human activity recognition tasks. Equipped with various integrated sensors, a modern smartphone can be leveraged for lots of smart applications. We already investigated the possibility of using an unmodified commercial smartphone to recognize eight strength-based exercises. App-based workouts have become popular in the last few years. The advantage of using a mobile device is that you can practice anywhere at anytime. In our previous work, we proved the possibility of turning a commercial smartphone into an active sonar device to leverage the echo reflected from exercising movement close to the device. By conducting a test study with 14 participants, we showed the first results for cross person evaluation and the generalization ability of our inference models on disjoint participants. In this work, we extended another model to further improve the model generalizability and provided a thorough comparison of our proposed system to other existing state-of-the-art approaches. Finally, a concept of counting the repetitions is also provided in this study as a parallel task to classification. Full article

Social media has become very popular and important in people’s lives, as personal ideas, beliefs and opinions are expressed and shared through them. Unfortunately, social networks, and specifically Twitter, suffer from massive existence and perpetual creation of fake users. Their goal is to deceive other users employing various methods, or even create a stream of fake news and opinions in order to influence an idea upon a specific subject, thus impairing the platform’s integrity. As such, machine learning techniques have been widely used in social networks to address this type of threat by automatically identifying fake accounts. Nonetheless, threat actors update their arsenal and launch a range of sophisticated attacks to undermine this detection procedure, either during the training or test phase, rendering machine learning algorithms vulnerable to adversarial attacks. Our work examines the propagation of adversarial attacks in machine learning based detection for fake Twitter accounts, which is based on AdaBoost. Moreover, we propose and evaluate the use of k-NN as a countermeasure to remedy the effects of the adversarial attacks that we have implemented. Full article

Steady State Visual Evoked Potential (SSVEP) methods for brain–computer interfaces (BCI) are popular due to higher information transfer rate and easier setup with minimal training, compared to alternative methods. With precisely generated visual stimulus frequency, it is possible to translate brain signals into external actions or signals. Traditionally, SSVEP data is collected from the occipital region using electrodes with or without gel, normally mounted on a head cap. In this experimental study, we develop an in-ear electrode to collect SSVEP data for four different flicker frequencies and compare against occipital scalp electrode data. Data from five participants demonstrates the feasibility of in-ear electrode based SSVEP, significantly enhancing the practicability of wearable BCI applications. Full article

An environmental chamber is a specialistic device used for testing effects of given controlled conditions on a variety of objects. In case of plant growth chambers, the conditions are controlled usually for plant cultivation and propagation or botanical examination undertaken on living plant material. The aim of the project was to design and build a prototype of a desktop device with a control system capable of being used as a chamber supporting plant cultivation and propagation processes by the means of partial automation of environment control. The conditions controlled in the chamber are based on the environmental requirements of plant genera, such as Heliamphora, Drosera, Orectanthe, Cyrilla, Stegolepis, Maguireothamnus, or Utricularia. These plants occur naturally in the Guiana Highlands region of Venezuela, Brazil, and Guyana, especially around the upper parts of table-shaped mountain massifs called tepuis. The chamber was designed to simulate some of the peculiar natural factors and phenomena occurring in the high-tepui and surrounding mid-elevation wetland habitats, being the most significant for amateur-level plant cultivation, keeping the design as simple and low cost as possible. It was proven on the basis of the results of several tests made during the evaluation phase that the designed prototype of the chamber operates in a satisfying way, providing basic functionality matching the base assumptions. Full article

This work compares two design methodologies, emulating both AgCl electrode and skin tissue Cole models for testing and verification of electrical bio-impedance circuits and systems. The models are based on fractional-order elements, are implemented with active components, and capture bio-impedance behaviors up to 10 kHz. Contrary to passive-elements realizations, both architectures using analog filters coupled with adjustable transconductors offer tunability of the fractional capacitors’ parameters. The main objective is to build a tunable active integrated circuitry block that is able to approximate the models’ behavior and can be utilized as a Subject Under Test (SUT) and electrode equivalent in bio-impedance measurement applications. A tetrapolar impedance setup, typical in bio-impedance measurements, is used to demonstrate the performance and accuracy of the presented architectures via Spectre Monte-Carlo simulation. Circuit and post-layout simulations are carried out in 90-nm CMOS process, using the Cadence IC suite. Full article

Transdermal optical wireless (TOW) communication links have recently gained particular research and commercial attention as a viable alternative for establishing high speed and effective implantable data transmissions, which is vital for a variety of neuroprosthetic and other medical applications. However, the development of this optical telemetry modality with medical implanted devices (IMDs) is adversely affected by skin-induced photon absorption, scattering and pointing errors effects. Thus, in this work a minimum mean-square error (MMSE) criterion is proposed for the estimation of the optical signal intensity in a typical TOW link of varying path loss and misalignment-induced fading characteristics. In this context, the stochastic nature of the transmitter–receiver misalignment has been considered and jointly modeled with transdermal path loss. Additionally, the link is assumed to employ the suitable On–Off Keying (OOK) with intensity modulation and direct detection scheme as well as a PIN photodiode at the receiver side for signal detection. Under these assumptions the results demonstrate that the stochastic amount of pointing mismatch strongly affects the received irradiance estimation. Full article

An equilibrium problem of the Kirchhoff–Love plate containing a nonhomogeneous inclusion is considered. It is assumed that elastic properties of the inclusion depend on a small parameter characterizing the width of the inclusion $\epsilon$ as ${\epsilon }^N$ with $N<1$. The passage to the limit as the parameter $\epsilon$ tends to zero is justified, and an asymptotic model of a plate containing a thin inhomogeneous hard inclusion is constructed. It is shown that there exists two types of thin inclusions: rigid inclusion ($N<-1$) and elastic inclusion ($N=-1$). The inhomogeneity disappears in the case of $N\in (-1,1)$. Full article

Nowadays, our mobile devices have become smart computing platforms, incorporating a wide number of embedded sensors such as accelerometers, gyroscopes, barometers, GPS receivers, and magnetometers. Smartphones are valuable devices for gathering user-related data and transforming it into value-added information for the user. In this study, a novel mechanism to process sensor data from mobile devices in order to detect the type of area the user is crossing while walking in an urban setting is presented. The method is based on combining outlier data analysis and classification techniques from data collected by several pedestrians while traversing an urban environment. A theoretical framework, composed of methods for detecting multivariate outliers combined with supervised classification techniques, has been proposed in order to identify different situations and physical barriers while walking. Each type of element to be detected is characterized by using a feature vector computed based on the outliers detected. Finally, a radial SVM is used for the classification task. The classifier is trained in a supervised way with data from 20 different segments containing several physical barriers and used later to assign a class to new un-labelled data. The results obtained with this approach are very promising with an average accuracy around 95% when detecting different types of physical barriers. Full article

Older Greek adults make use of web technologies much less than the majority of their peers in Europe. Based on the fact that psychosocial attributes can also affect technology usage, this exploratory quantitative research is an attempt to focus on the implicit factors related to older Greek adults’ perceived usability, learnability, and ease-of-use of web technologies. For this aim, a web 2.0 storytelling prototype has been demonstrated to 112 participants and an online questionnaire was applied for data collection. According to the results, distinct correlations emerged between older adults’ characteristics (chronological age, loneliness, future time perspective) and the perceived usability, learnability, and ease-of-use of the presented prototype. These outcomes contribute to the limited literature in the field by probing the connections between older people’s implicit attributes and their evaluative perceptions of online technologies. Full article

Nonlinear free vibrations of functionally graded porous Bernoulli–Euler nano-beams resting on an elastic foundation through a stress-driven nonlocal elasticity model are studied taking into account von Kármán type nonlinearity and initial geometric imperfection. By using the Galerkin method, the governing equations are reduced to a nonlinear ordinary differential equation. The closed form analytical solution of the nonlinear natural flexural frequency is then established using the Hamiltonian approach to nonlinear oscillators. Several comparisons with existing models in the literature are performed to validate the accuracy and reliability of the proposed approach. Finally, a numerical investigation is developed in order to analyze the effects of the gradient index coefficient, porosity volume fraction, initial geometric imperfection, and the Winkler elastic foundation coefficient, on the nonlinear flexural vibrations of metal–ceramic FG porous Bernoulli–Euler nano-beams. Full article

Recent advances in big data systems and databases have made it possible to gather raw unlabeled data at unprecedented rates. However, labeling such data constitutes a costly and timely process. This is especially true for video data, and in particular for human activity recognition (HAR) tasks. For this reason, methods for reducing the need of labeled data for HAR applications have drawn significant attention from the research community. In particular, two popular approaches developed to address the above issue are data augmentation and domain adaptation. The former attempts to leverage problem-specific, hand-crafted data synthesizers to augment the training dataset with artificial labeled data instances. The latter attempts to extract knowledge from distinct but related supervised learning tasks for which labeled data is more abundant than the problem at hand. Both methods have been extensively studied and used successfully on various tasks, but a comprehensive comparison of the two has not been carried out in the context of video data HAR. In this work, we fill this gap by providing ample experimental results comparing data augmentation and domain adaptation techniques on a cross-viewpoint, human activity recognition task from pose information. Full article

Braking conditions are a fundamental issue for the railway and have been a limiting factor in network capacity and timetabling. Leaf fall, especially during the autumn season, creates low-adhesion problems on railways, causing braking problems for trains. To address the requirements of the novel plasma industrial applications towards environmental applications, this work developed and tested a 2.45 GHz microwave atmospheric pressure plasma system for in situ removal of the third body layer deposited onto the railway so as to improve braking. The plasma reactor consisted of a 15 kW, 2.45 GHz magnetron-based microwave generator and a plasma reactor (dielectric tube placed in a TE01 monomode microwave cavity); the atmospheric plasma ignited and sustained at different power levels (2–15 kW) in different gases (nitrogen, argon) as well as mixtures of these gases with reactive molecules (water, oxygen) was jetted directly onto the railhead as to change the conditions for the wheel–rail interface. This technology is hoped to be a game-changer in enabling predictable and optimized braking on the railway network. Challenges encountered during the demonstration phase are discussed. Subsequent work should validate the results on a working railway line during the autumn season. Full article

A reversible gelation–release system was developed for safe storage of toxic hydrazine solution based on gelation at lower critical solution temperature (LCST). Poly(N-isopropylacrylamide) (PNIPAM) and its copolymer could form gels of 35wt% hydrazine by dissolution under low temperature and storage at ambient temperatures. For example, PNIPAM gelled a 63 fold heavier amount of 35wt% hydrazine. Aqueous hydrazine was released from the gels by compression or heating, and the gelation–release cycles proceeded quantitatively (> 95%). The high gelation ability and recyclability are suitable for rechargeable systems for safe storage of hydrazine fuels. Full article

Since polybenzimidazole (PBI) is often used in the aerospace industry, high-temperature fuel cells, and in redox flow batteries, this research investigated the surface modification of PBI film with 253.7 and 184.9 nm UV photo-oxidation. As observed by X-ray photoelectron spectroscopy (XPS), the oxygen concentration on the surface increased up to a saturation level of 20.2 ± 0.7 at %. With increasing treatment time, there were significant decreases in the concentrations of C-C sp² and C=N groups and increases in the concentrations of C=O, O-C=O, O-(C=O)-O, C-N, and N-C=O containing moieties due to 253.7 nm photo-oxidation of the aromatic groups of PBI and reaction with ozone produced by 184. 9 nm photo-dissociation of oxygen. Because no significant changes in surface topography were detected by Atomic Force Microscopy (AFM) and SEM measurements, the observed decrease in the water contact angle down to ca. 44°, i.e., increase in hydrophilic, was due to the chemical changes on the surface. Full article

Three-dimensional printing (3DP) is at the forefront of the disruptive innovations adding a new dimension in the material fabrication process with numerous design flexibilities. Especially, the ability to reinforce the plastic matrix with nanofiber, microfiber, chopped fiber and continuous fiber has put the technology beyond imagination in terms of multidimensional applications. In this technical paper, fiber and polymer filaments used by the commercial 3D printers to develop fiber-reinforced composites are characterized to discover the unknown manufacturing specifications such as fiber–polymer distribution and fiber volume fraction that have direct practical implications in determining and tuning composites’ properties and their applications. Additionally, the capabilities and limitations of 3D printing software to process materials and control print parameters in relation to print quality, structural integrity and properties of printed composites are discussed. The work in this paper aims to present constructive evaluation and criticism of the current technology along with its pros and cons in order to guide prospective users and 3D printing equipment manufacturers on improvements, as well as identify the potential avenues of development of the next generation 3D printed fiber-reinforced composites. Full article