The realization of truly unclonable identification and authentication tags is the key factor in protecting the global economy from an ever-increasing number of counterfeit attacks. Here, we report on the demonstration of nanoscale tags that exploit the electromechanical spectral signature as a fingerprint that is characterized by inherent randomness in fabrication processing. Benefiting from their ultraminiaturized size and transparent constituents, these clandestine nanoelectromechanical tags provide substantial immunity to physical tampering and cloning. Adaptive algorithms are developed for digital translation of the spectral signature into binary fingerprints. A large set of tags fabricated in the same batch is used to estimate the entropy of the corresponding fingerprints with high accuracy. The tags are also examined under repetitive measurements and temperature variations to verify the consistency of the fingerprints. These experiments highlight the potential of clandestine nanoelectromechanical tags for the realization of secure identification and authentication methodologies applicable to a wide range of products and consumer goods.

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Abstract-Cardiovascular disease is currently responsible for a major portion of all global deaths. Fortunately, early detection of its symptoms can greatly contribute to effective prevention. Hence, clinicians recommend routine cardiovascular check-ups. Even though various methods for cardiac diagnosis exist, most of them are clinic-based, and therefore time-consuming and costly. Therefore, it is not always possible for patients to go through these procedures on a regular basis. In this paper, we propose a novel wearable ultrasonic imaging assembly for routine, easy-to-use, and economical monitoring of the carotid arteries. The device monitors intima-media thickness (IMT), which is a proven clinically useful marker for diagnosis of cardiovascular disease and prediction of imminent cardiovascular events. It uses standard B-mode ultrasound, which is suitable for implementation within area-and power-constrained wearable form factors. We present design parameters and power requirements for all the essential hardware components of the proposed wearable imaging system. We also present an efficient algorithm for predicting IMT anomalies from ultrasound images.

In this paper, performance of a novel analytic model of direct sequence code division multiple accesses (DS-CDMA) using diversity with maximal ratio combining (MRC) scheme is observed under the influence of multipath Rayleigh fading and multi-access interference (MAI) varying different system parameters and properties of PN sequences. The analysis presents a mathematical expression for bit error rate (BER) of the novel DS-CDMA model using diversity with MRC when signal to interference plus noise ratio (SINR) per bit follows a chi-square distribution. Performance results are evaluated in terms of average bit error rate (BER) at the output of MRC receiver by averaging the conditional BER over the probability density function (pdf) of signal to interference plus noise ratio (SINR). In addition to that the receiver sensitivity of the model is observed for different transmit and receive diversity in a proposed multiple input multiple output (MIMO) system model varying Rayleigh fading co-efficient. Variants of simulation result at various cases are also analyzed.

Dyeing vegetables with harmful compounds has become an alarming public health issue over the past few years. Excessive consumption of these dyed vegetables can cause severe health hazards, including cancer. Copper sulfate, malachite green, and Sudan red are some of the non-food-grade dyes widely used on vegetables by untrusted entities in the food supply chain to make them look fresh and vibrant. In this study, the presence and quantity of dye-based adulteration in vegetables are determined by applying 1H-nuclear magnetic resonance (NMR) relaxometry. The proposed technique was validated by treating some vegetables in-house with different dyes and then soaking them in various solvents. The resulting solutions were collected and analyzed using NMR relaxometry. Specifically, the effective transverse relaxation time constant, T2,eff, of each solution was estimated using a Carr–Purcell–Meiboom–Gill (CPMG) pulse sequence. Finally, the estimated time constants (i.e., measured signatures) were compared with a library of existing T2,eff data to detect and quantify the presence of unwanted dyes. The latter consists of data-driven models of transverse decay times for various concentrations of each water-soluble dye. The time required to analyze each sample using the proposed approach is dye-dependent but typically no longer than a few minutes. The analysis results can be used to generate warning flags if the detected dye concentrations violate widely accepted standards for food dyes. The proposed low-cost detection approach can be used in various stages of a produce supply chain, including consumer household.