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The Shillong Plateau, one of the most seismically active zones of South Asia, offers a unique setting for integrated assessment of multi-hazard interactions and local site effects. This study develops a geocartographic framework that combines detailed tectonic, geological, geomorphological, borehole and topographic information with resonance-frequency estimates from ambient noise and earthquake-based receiver-function analyses to derive spatially explicit hazard and site-effect maps for the Greater Shillong region. Using 10 deep borehole logs and two cross-sections (AB and CD), the subsurface stratigraphy is constrained up to depths exceeding 250 m and linked to lateral variations in fundamental frequency, which range from about 3–8 Hz. The hitherto geophysical profiles (AB and CD) provide contrasting impedance structure and amplification potential. Further, the resonance-frequency estimates are correlated with elevation and slope. This leads to delineation of zones where topographic amplification coherently reinforces, or decouples from, impedance-driven site response. In contrast to previous works, this work delivers an integrated, map-based characterization of sediment thickness, shear-wave velocity structure, resonance frequency and topographic modulation that refines the spatial pattern of seismic susceptibility and identifies pockets of potentially high vulnerability within the Shillong urban corridor. The results demonstrate considerable level of heterogeneity. Overall, the findings stemming from coupling multi-source geodata with passive and earthquake-based measurements for regional-scale seismic microzonation offer valuable information for guiding land-use planning and disaster risk reduction in tectonically active plateaus.

Microplastics have emerged as a significant environmental concern, particularly in marine ecosystems. The detection and quantification of microplastics pose considerable challenges due to their small size, diverse composition, and widespread distribution. In recent years, significant progress has been made in developing detection methods to enhance our understanding of microplastic pollution. This mini review provides an overview of the state-of-the-art detection methods for microplastics, including their principles, advantages, limitations, and applications. Finally, we explore emerging in situ monitoring technologies that hold promise for real-time detection of microplastics at sea.

Steganography, the hiding technique used to secure sensitive data (i.e., images, audio ) while communication takes place. In this paper, the message is embedded in color image in frequency domain exploiting Genetic Algorithm (GA) which provides the robustness i.e., the algorithm can withstand against any rigorous testing and brutal attack except destruction of the stego image. The fragmentation of 8-bit binary stream of each color component to 4-bit and applying Genetic Algorithm (GA) to increase the robustness of the scheme. Random Multiple bits are chosen to embed secret message which increases security along with the payload. The use of transform domain, hash function based random pixel and bit selections for data hiding, secrete data encryption and more over use of Genetic Algorithm (GA) for optimization is the novelty of the proposed work. Perspective and meticulous statistical analysis has been done to immune the algorithm from any attack. The algorithm proposed here is tested with benchmark tools like StirMark 4.0, Confusion Matrix (Receiver Operating Curve Characteristic (ROC) curve) along with steganalysis and statistical tools. Visual disturbance and distortion in stego image is also very insignificant here.

Advancement of information and communication techniques have led to share big amount of information which is increasing day by day through online activities and creating new added value over the internet services. At the same time threats to the security of cyber world has been increased with increasing number of heterogeneous connection points having powerful computational capacity. Internet being used to interact and control such automatic network devices connected to it. But hackers/crackers can exploit this network environment by putting malicious dummy node(s) or machine(s) called Botnet(s) to co-ordinate the attacks on security such as Denial of Service (DoS) or Distributed Denial of Service (DDoS). The proposed method attempts to identify those mallicious Botnet traffic from regular traffic using novel deep learning approaches like Artificial Neural Networks (ANN), Gatted Recurrent Units (GRU), Long or Short Term Memory (LSTM) model. The proposed model demonstrates significant improvement of all previous works. The testing dataset, Bot-IoT dataset is the latest and one of the largest public domain dataset used to justify improvement. Testing shows 99.7% classification accuracy which is precise and better than all previous works done. Results analysis and comparison shows the accuracy and supremacy over the latest work done on this field.

We report a volatile liquid detector by engaging metal oxide sensor, which is further assisted by an Arduino kit to develop a prototype of alcohol detection. We have used ethanol as the main volatile liquid to design the prototype. To verify the most selective nature of the metal oxide sensor towards alcohol, we have compared with Methanol, Isopropyl alcohol, Acetone and Ammonia along with Ethanol. The proposed sensing device has been found to be highly sensitive towards ethanol with an excellent linearity closing to unity. With a working domain of ~ 230–800 ppm, the probe renders good degree of reproducibility. Through a little up scaling, the proposed device can be used as a transducer to reduce the speed of a running car when the exhale of driver exceeds dangerous concentration of alcohol.

In recent years, the Kopili fault reported an increase in seismic activity. Coda-wave attenuation and its frequency dependency can be used to examine the seismo-tectonics. Here, we document the regional heterogeneity in the coda attenuation. Present data in this region report Q 0 (value of Q C at 1 Hz) variation from 63 (for 30 s window) to 213 (for 90 s window) and n from 1.330 (for 30 s window) to 0.913 (for 90 s window). These significant fluctuations in the attenuation parameter (Q 0 ) and frequency parameter (n), indicate a velocity inconsistency at depths of 230-270 km. This anomaly may be associated with the anisotropy originates in the asthenosphere-lithosphere transition or asthenospheric mantle at depths of 160-320 km. Accordingly, this concise work comprehensively analyzes reported implications, supported by observational evidences.

The quest for novel synthesis method of silver nanoparticles (AgNPs) is still an active field of research due to their usefulness in different levels of therapeutic and sensing applications. Owing to the better biodegradability and biocompatibility, plant extract-assisted synthesis processes of AgNPs have gained considerable attention in recent years. Here, we report a novel synthesis approach for AgNPs using banana root bulb (BRB) extract. The BRB extract was used as solvent as well as reducing agent in this synthesis process. The nanoparticles obtained through this process possessed hydrodynamic size of the order of 40 nm and a broad surface plasmon resonance peak at ~ 411 nm. In order to validate this process, the properties of the product were compared with properties of the nanoparticles obtained from other two established approaches viz- chemical reduction method involving trisodium citrate as reducing agent and green synthesis method involving mixed fruit peel waste extract as solvent and reducing agent. It was observed that surface plasmon resonance peaks entitled to AgNPs prepared through all the three approaches were quite consistent with each other. Besides, the broad surface plasmon resonance peaks suggest that the nanoparticles obtained through all the approaches were polydispersed.

In today’s fast-paced world, people increasingly rely on a variety of processed foods due to their busy lifestyles. The enhanced flavors, vibrant colors, and ease of accessibility at reasonable prices have made ready-to-eat foods the easiest and simplest choice to satiate hunger, especially those that undergo thermal processing. However, these foods often contain an unsaturated amide called ‘Acrylamide’, known by its chemical name 2-propenamide, which is a contaminant formed when a carbohydrate- or protein-rich food product is thermally processed at more than 120 °C through methods like frying, baking, or roasting. Consuming foods with elevated levels of acrylamide can induce harmful toxicity such as neurotoxicity, hepatoxicity, cardiovascular toxicity, reproductive toxicity, and prenatal and postnatal toxicity. This review delves into the major pathways and factors influencing acrylamide formation in food, discusses its adverse effects on human health, and explores recent techniques for the detection and mitigation of acrylamide in food. This review could be of interest to a wide audience in the food industry that manufactures processed foods. A multi-faceted strategy is necessary to identify and resolve the factors responsible for the browning of food, ensure safety standards, and preserve essential food quality traits.

Lignocellulosic biomass resources especially agricultural and forests residues, perennial crops, farm wastes, and the organic fraction of municipal solid waste hold significant potential for the widespread production of sustainable fuels, chemicals, and bioproducts worldwide. For biochemical conversion processes, deconstruction of lignocellulosic biomass into its components (cellulose, hemicellulose, and lignin) for further microbial conversion has been a major challenge due to the recalcitrant nature of lignocellulose. Thus pretreatment is prerequisite for efficient hydrolysis of lignocellulose and cost for such treatment is currently about one third of the overall processing costs in a cellulosic biorefinery. Thus, the development of a more efficient and cost-effective pretreatment method is crucial for the commercialization of lignocellulosic biorefineries. Wet explosion (WEx), a thermochemical pretreatment method with additional features of oxygen addition and explosive decompression, can be adjusted to different biomass feedstock and to subsequent bio-catalytic and microbial processes. The WEx pretreatment method has been successfully applied in combination with both microbial fermentation and anaerobic digestion processes using both agricultural and forest residues as well as manure fibers. Steam explosion, represents a related process to WEx pretreatment where high pressure is used but no oxygen is added. This process has been tested in demonstration scale while WEx is on its way to commercialization. Presented here is a summary of the basic concepts and parameters involved in WEx pretreatment.

The development of materials with tunable structural and optical properties stands at the forefront of contemporary scientific research, given their broad applicability. In this study, we report the solvent-directed green synthesis of titanium dioxide nanoparticles (TiO 2 NPs) using Nyctanthes arbor-tristis (Night Jasmine) leaf extract as an eco-friendly reducing and capping agent. Synthesis was conducted employing both deionized (DI) water and ethanol as solvents to investigate their influence on the resulting nanoparticle properties. Comprehensive characterization using Field Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-ray Spectroscopy (EDX), Dynamic Light Scattering (DLS), X-ray Diffraction (XRD), UV-Vis spectroscopy, photoluminescence (PL), Fourier Transform Infrared (FTIR) spectroscopy, and Raman spectroscopy provided deep insight into structural, morphological, chemical, and optical variations imparted by solvent selection. FESEM analysis revealed solvent-dependent differences in nanoparticle size and morphology, while XRD patterns confirmed crystalline structures with solvent-induced changes in crystallinity and phase distribution. Optical analyses (UV-Vis, PL, and Raman) demonstrated notable shifts in band gap energy and emission behavior, attributable to the solvent medium. The non-linear optical (NLO) properties, evaluated by Z-scan technique, further underscored the effect of solvent choice on TiO 2 NP functionality. This study highlights solvent-mediated modulation of TiO 2 NP characteristics through a sustainable green synthesis approach, offering promising avenues for photocatalytic and environmental remediation applications.