Intelligent Electromagnetic Sensors for Non-Invasive Trojan Detection.

Rapid growth of sensors and the Internet of Things is transforming society, the economy and the quality of life. Many devices at the extreme edge collect and transmit sensitive information wirelessly for remote computing. The device behavior can be monitored through side-channel emissions, including power consumption and electromagnetic (EM) emissions. This study presents a holistic self-testing approach incorporating nanoscale EM sensing devices and an energy-efficient learning module to detect security threats and malicious attacks directly at the front-end sensors. The built-in threat detection approach using the intelligent EM sensors distributed on the power lines is developed to detect abnormal data activities without degrading the performance while achieving good energy efficiency. The minimal usage of energy and space can allow the energy-constrained wireless devices to have an on-chip detection system to predict malicious attacks rapidly in the front line.

Husk of Agarwood Fruit-Based Hydrogel Beads for Adsorption of Cationic and Anionic Dyes in Aqueous Solutions.

Hydrogel beads based on the husk of agarwood fruit (HAF)/sodium alginate (SA), and based on the HAF/chitosan (CS) were developed for the removal of the dyes, crystal violet (CV) and reactive blue 4 (RB4), in aqueous solutions, respectively. The effects of the initial pH (2-10) of the dye solution, the adsorbent dosage (0.5-3.5 g/L), and contact time (0-540 min) were investigated in a batch system. The dynamic adsorption behavior of CV and RB4 can be represented well by the pseudo-second-order model and pseudo-first-order model, respectively. In addition, the adsorption isotherm data can be explained by the Langmuir isotherm model. Both hydrogel beads have acceptable adsorption selectivity and reusability for the study of selective adsorption and regeneration. Based on the effectiveness, selectivity, and reusability of these hydrogel beads, they can be treated as potential adsorbents for the removal of dyes in aqueous solutions.

Manipulating exchange bias by spin-orbit torque.

Exchange bias, a shift in the hysteresis loop of a ferromagnet arising from interfacial exchange coupling between adjacent ferromagnetic and antiferromagnetic layers, is an integral part of spintronic devices. Here, we show that spin-orbit torque generated from spin current, a promising approach to switch the ferromagnetic magnetization of next-generation magnetic random access memory, can also be used to manipulate the exchange bias. Applying current pulses to a Pt/Co/IrMn trilayer causes concurrent switching of ferromagnetic magnetization and exchange bias, but with different underlying mechanisms. This implies that the ferromagnetic magnetization and exchange bias can be manipulated independently. Our work demonstrates that spin-orbit torque in ferromagnet/antiferromagnet heterostructures facilitates independent manipulations of distinct magnetic properties, motivating innovative designs for future spintronics devices.

[The analysis and comparison of different edge detection algorithms in ultrasound B-scan images].

In this paper, some familiar algorithms of edge detection in ultrasound B-scan images are analyzed and studied. The results show that Sobel, Prewitt and Laplacian operators are sensitive to noise, Hough transform adapts to the whole detection, while LoG algorithm's average is zero and it couldn't change the whole dynamic area. Accordingly LoG algorithm is preferable.