Single mask fabrication process for movable MEMS devices

The current work reports on the realization of movable micromachining devices using self-aligned single-mask fabrication process. Only dry etching process utilizing inductively coupled plasma reactive ion etching was used to release 3D micro structures from single crystal silicon substrate. No wet etching process is required to release the structures as is the case with silicon on insulator (SOI) wafers. Also the developed process does not require an SOI substrate and accordingly dispensing with the application of a wet etching step, thus yielding uniform structures without stiction. The optimized process was applied to realize thermally actuated microgrippers. The article presents the development of the fabrication process and demonstrates the operation of the fabricated device. The optimized process provides an avenue for low cost fabrication of movable micromachining devices without the use of complicated wet etching steps typically associated with SOI substrates.     

Silhouette-based human action recognition using SAX-Shapes

Human action recognition is an important problem in Computer Vision. Although most of the existing solutions provide good accuracy results, the methods are often overly complex and computationally expensive, hindering practical applications. In this regard, we introduce the combination of time-series representation for the silhouette and Symbolic Aggregate approXimation (SAX), which we refer to as SAX-Shapes, to address the problem of human action recognition. Given an action sequence, the extracted silhouettes of an actor from every frame are transformed into time series. Each of these time series is then efficiently converted into the symbolic vector: SAX. The set of all these SAX vectors (SAX-Shape) represents the action. We propose a rotation invariant distance function to be used by a random forest algorithm to perform the human action recognition. Requiring only silhouettes of actors, the proposed method is validated on two public datasets. It has an accuracy comparable to the related works and it performs well even in varying rotation.     

A cross-layer approach for partition detection at overlay layer for structured P2P in MANETs

Due to limited radio range and mobility of nodes in mobile ad hoc networks (MANETs), the network partitioning and merging could occur frequently. When structured peer-to-peer (P2P) overlays are running over MANETs, then network partition in the physical network can also cause network partition at the overlay layer. Existing approaches for structured P2P overlay over MANETs do not detect network partition at the overlay layer. This paper proposes a cross-layer approach to detect network partition at the overlay layer for structured P2P overlay over MANETs. Simulation results show that the proposed approach is highly effective and efficient in terms of routing overhead, success ratio and false-negative ratio.     

Silicone oil emulsions: strategies to improve their stability and applications in hair care products

Silicone oils have wide range of applications in personal care products due to their unique properties of high lubricity, non‐toxicity, excessive spreading and film formation. They are usually employed in the form of emulsions due to their inert nature. Until now, different conventional emulsification techniques have been developed and applied to prepare silicone oil emulsions. The size and uniformity of emulsions showed important influence on stability of droplets, which further affect the application performance. Therefore, various strategies were developed to improve the stability as well as application performance of silicone oil emulsions. In this review, we highlight different factors influencing the stability of silicone oil emulsions and explain various strategies to overcome the stability problems. In addition, the silicone deposition on the surface of hair substrates and different approaches to increase their deposition are also discussed in detail.     

Graphene‐based ternary composites for supercapacitors

The research on electrode materials for supercapacitor application continues to evolve as the request of high‐energy storage system has increased globally due to the demand for energy consumption. Over the past decades, various types of carbon‐based materials have been employed as electrode materials for high‐performance supercapacitor application. Among them, graphene is 1 of the most widely used carbon‐based materials due to its excellent properties including high surface area and excellent conductivity. To exploit more of its interesting properties, graphene is tailored to produce graphene oxide and reduced graphene oxide to improve the dispersibility in water and easy to be incorporated with other materials to form binary composites or even ternary composites. Nowadays, ternary composites have attracted enormous interest as 2 materials (binary composites) cannot satisfy the requirement of the high‐performance supercapacitor. Thus, many approaches have been employed to fabricate ternary composites by combining 3 different types of electroactive materials for high‐performance supercapacitor application. This review focuses on the supercapacitive performance of graphene‐based ternary composites with different types of active materials, ie, conducting polymers, metal oxide, and other carbon‐based materials.     

Machine learning techniques for anti-money laundering (AML) solutions in suspicious transaction detection: a review

Money laundering has been affecting the global economy for many years. Large sums of money are laundered every year, posing a threat to the global economy and its security. Money laundering encompasses illegal activities that are used to make illegally acquired funds appear legal and legitimate. This paper aims to provide a comprehensive survey of machine learning algorithms and methods applied to detect suspicious transactions. In particular, solutions of anti-money laundering typologies, link analysis, behavioural modelling, risk scoring, anomaly detection, and geographic capability have been identified and analysed. Key steps of data preparation, data transformation, and data analytics techniques have been discussed; existing machine learning algorithms and methods described in the literature have been categorised, summarised, and compared. Finally, what techniques were lacking or under-addressed in the existing research has been elaborated with the purpose of pinpointing future research directions.     

Synthesis of amino-cosubstituted polyorganophosphazenes and fabrication of their nanoparticles for anticancer drug delivery

The development of safe drug carriers is cardinal in cancer therapy, which can target the cancer cells and release the loaded drug on-demand without damaging the healthy cells of the body. In our work, we synthesized three different biodegradable polymers, poly[(ethyl aminobezoate) (ethyl glycinato) phosphazenes] (PABGPs), in different mole ratio of side groups. The successful synthesis of these PABGPs was confirmed by ¹H NMR, ³¹P NMR, FT-IR, and gel permeation chromatography. These PABGPs were fabricated into drug (camptothecin, CPT, a hydrophobic anticancer drug) loaded nanoparticles. These drug-loaded nanoparticles showed good drug release behaviors under normal physiological conditions (pH 7.4 and temperature 37°C). These PABGPs-based nanoparticles may find their application as effective drug carriers for cancer therapy.     

Improvement of physical and mechanical properties of electrospun poly(lactic acid) nanofibrous structures

Iranian Polymer Journal - The electrospinning of stereocomplexed poly(lactic acid) (Sc-PLA) twisted yarns was our approach to produce PLA-based nanofibrous structures with improved physical and...     

Theoretical and experimental studies of a new aniline derivative corrosion inhibitor for mild steel in acid medium

4-Chloro-N-(pyridin-2-ylmethyl)aniline (CPYA) was synthesized by a simple and inexpensive method and tested as a corrosion inhibitor in acid medium for mild steel by using gravimetric studies and electrochemical measurements. An average maximum efficiency of 96.0% was achieved at 4.59 mmol/L. Corrosion kinetic and thermodynamic parameters were also analyzed. Surface analyses (atomic force microscopy and scanning electron microscopy) show that protection is enabled by adsorption on the metal, forming a film. Quantum chemical calculations were performed to access information regarding the molecular structure in the corrosive medium and to support interpretation of the results obtained by experimental methods.