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As Moore’s law comes to a crawl, advanced package and integration techniques become increasingly crucial by allowing for the combination of fabricated silicon dies, so-called chiplet, to constitute system-in-package (SiP) achieving a much better yield and time-to-market. However, due to inherent security concerns within the convoluted semiconductor supply chain and in-field environment, hostile attacks targeting software and hardware applications can present a formidable challenge to ensuring the security of SiP. Even worse, the immanent black-box nature of product chiplets renders most conventional security inspection and testing solutions less useful. Therefore, we present our SiPGuard in this article to enable the security monitoring capability during run time to noninvasively track the application-level behaviors of target chiplets and detect any deviations potentially induced by underlying malicious intrusions. The security monitoring mechanism utilizes information-bearing system-level power noise variation and machine learning (ML) techniques. Specifically, we utilize a trusted field-programmable gate array (FPGA) chiplet as our trust anchor to implement the lightweight power sensor and on-chip ML inference engine for near-sensor analysis. We prototype our solution on a 2.5-D chiplet-based FPGA device and demonstrate the effectiveness against threats at software/hardware levels by identifying the consequent power anomalies of malicious activities.

In an age marked by environmental consciousness, ‘Sonali Bag’ has emerged as a promising substitute for single-use plastic bags, invented in Bangladesh. It is a jute cellulose-based, totally biodegradable, compostable, recyclable, and environment-friendly biopolymer. However, certain physical limitations have hindered its widespread consumer appeal. To address these challenges, this study pioneers the integration of jute cellulose nanocrystals (JCNCs) into Sonali Bag, with the objective of enhancing their physical properties. JCNC, obtained through a meticulous 64% concentrated sulfuric acid hydrolysis process, has been reinforced with Sonali Bag at varying loadings (0, 0.1, 0.2, 0.3, and 0.4 wt.%). The scanning electron microscopy (SEM) analysis showed spherical cellulose nanocrystals with high crystallinity and distinctive tear-like features on the nanoparticle’s surface. Furthermore, the SEM micrographs depicted that JCNC loading up to 0.2% helped reduce the pore formation of biocomposite. Moreover, the thermal properties increased significantly, and tensile strength increased by approximately 37% MPa after reinforcing JCNC with Sonali Bag. The water-resistant capacity of 0.2% CNC-reinforced film was about 30% better than other compositions. The JCNC-reinforced composite materials were found to moderate the degradation rate, contributing to the prolonged sustainability of these biodegradable solutions.

Black rice (Oryza sativaL.) is a rich source of phenolics and anthocyanins. It was aimed to investigate the effect of different extraction methods such as conventional solvent extraction, ultrasound-assisted extraction (UAE), and microwave-assisted extraction (MAE) on antioxidant activity and phenolic profiling of black rice free, esterified, and bound phenolics fractions. Spectrophotometric methods were used to evaluate antioxidant activity and HPTLC was used for phenolics profiling. The highest content of % yield, total anthocyanin (TAC), total phenolic (TPC), and total flavonoid (TFC) contents were detected in MAE. It was also observed that antioxidant activity based on DPPH, ABTS, superoxide radical-scavenging and ferric reducing antioxidant power (FRAP) assays showed highest activity in MAE. Eight phenolic compounds were identified and quantified by a validated HPTLC method. MAE showed most abundant phenolic compounds. A significant positive correlation was established between % yield, total phenolic content, and total flavonoid content (p< 0.05) where a significant negative correlation was established between % yield, TPC, and TFC with IC50of antioxidant activity (p< 0.05). Diverse phenolic contents and antioxidant activity were studied with different forms of phenolics with the different extraction methods. It designates that the extraction techniques had effects on the bioactive compounds as well biological properties.