Unauthorized plucking of flowers, fruits, and vegetables from residential plant beds is a recurring concern in urban and semi-urban household, causing damage to gardening resources, economic loss and inconvenience to sustainable gardening. To address this issue, the present study proposes an IoT-enabled Smart Residential Plant Bed Protection System (SRPBPS), which is the integration of motion sensors, plant disturbance sensors, a video monitoring unit, a microcontroller, a communication module, and an alarm mechanism for real-time intrusion detection and monitoring. The behaviour of the proposed system is analyzed using a continuous-time Markov modelling approach by considering various operational and failed states of system components. Important reliability measures, including system reliability, mean time to system failure (MTTF), and the expected number of failures over time, are evaluated analytically. In addition, sensitivity analysis of reliability and MTTF are carried out to identify the critical components influencing overall system performance. The obtained results provide useful insights into component-level impact on system effectiveness and support reliability-oriented design enhancement. The proposed framework contributes toward the development of intelligent, secure, and sustainable residential plant bed protection systems for modern residential environments.

Environmental pollution is a global concern: currently, there is an increased spread of contaminants with heightened urbanization and industrialization. Such contaminants are pesticides, heavy metals (HMs), metalloids, including xenobiotics viz BPA, PVC, and freons. Currently, numerous HMs, such as cadmium, arsenic, and mercury, are interfering with health impacts people. About 17 HMs come under the category of highly risky and easily accessible. The present article represented the categorization of various HMs, their sources, and their impacts on plants, such as plant growth, health-hazardous impacts human health. Moreover, artificial intelligence (AI) has played a vital role in identifying screening as well as the mitigation of heavy metal and metalloid. AI-driven sensor systems, AI, along with the Internet of Things (IoT) can play pivotal role in monitoring the environment. Pollutant removal potential of plants can be examined in real-time using AI technologies, such as image analysis (IA) and growth pattern recognition (GPR). So that by technology improvement, AI can support efficiency of various remedial strategies to mitigate the adverse impact of toxicants, ensuring both environmental sustainability and human health. The present review highlighted about risk assessment of HMs in living organisms, including plants and humans. Moreover, AI can be a milestone to intensify the screening, mapping, and regulating toxic metals as well as metalloids in the environment. AI undoubtedly streamlines the environmental sustainability and public health.

This pioneering study reports the phytoconstituents of aerial organs of the vulnerable Stereospermum colais. These parts have been historically overlooked compared to root and bark exploitation in Ayurveda. This approach eliminates destructive root harvesting while staying within WHO elemental limits for multi-herb Ayurvedic formulations. The study proved leaves as the richest source of antioxidant phenolics and flavonoids, particularly rutin. The abscised petals stand out, containing a high level of the biomarker lignan cycloolivil (15.3 mg/g-DW), thus ideal for zero-impact, sustainable harvesting. Meanwhile, green stems are the best source of lapachol (1558 μg/g-DW in acetone). These highly significant profiles expand our understanding of the S. colais beyond previously identified compounds from roots and bark. This minimises expenses while maintaining tree health and bioactive yields for Ayurvedic applications. This study unlocks sustainable, eco-friendly sourcing for Ayurvedic and modern medicines, easing pressure on wild populations with non-destructive harvesting that can readily scale for commercial use.

A potentially genotoxic insecticide that is widely used in agriculture is dimethoate-30. This study focused on assessing the cyto-genotoxic impact of dimethoate-30 applying the Allium cepa bioassay, to understand its impact on biota. Roots were treated with 20, 40, 60, 80, and 100 mgl−1 dimethoate-30 concentrations for 24, 48, and 96 h, and root growth was measured using mitotic indices. The result showed a significant dose-dependent retardation in mitotic index over to control value, indicating cytotoxicity. Various cytological abnormalities were also observed, including c-metaphase, anaphase bridges, chromosome fragmentation, sticky metaphase and anaphase, and laggard chromosome. In addition, the frequency of micronuclei, aberrant cells percentage, and relative abnormality rate was increased, indicating genotoxicity. These findings indicate that dimethoate-30 may have cytotoxic and genotoxic effects, suggesting that it could be harmful and potentially carcinogenic. Therefore, it is not recommended to use higher concentrations of dimethoate-30 due to its cytogenotoxicity and potential to kill plants.

This study presents a sustainable approach to synthesizing gold nanoparticles (AuNPs) using Piper betle metabolites and investigates their potential to enhance growth and productivity in Vigna mungo (black gram). Betel-mediated AuNPs (B-AuNPs) were characterized by several biophysical techniques such as Fourier Transform Infrared (FTIR) analysis, which confirmed the roles of phenolic and flavonoid compounds in reducing and stabilizing AuNPs. Seed priming with B-AuNPs at optimized concentrations (100 µM) significantly boosted germination, morphological traits, crop yield, and antioxidant activity, showcasing a notable reduction in reactive oxygen species (ROS) and oxidative stress markers. The concentration-dependent response expressed the manifestation of cytotoxic effects. Thus, B-AuNPs promoted plant growth, seed yield and resilience of V. mungo. The findings advocate sustainable nanotechnology applications in agriculture and setting a foundation for eco-friendly yield enhancement strategies in global food systems.

Non-steroidal anti-inflammatory drugs (NSAIDs) are recommended to treat moderate-to-severe pain. Previous studies suggest that NSAIDs can suppress cellular proliferation and elevate apoptosis in different cancer cells. Ketorolac is an NSAID and can reduce the cancer cells' viability. However, molecular mechanisms by which Ketorolac can induce apoptosis and be helpful as an anti-tumor agent against carcinogenesis are unclear. Here, we observed treatment with Ketorolac disturbs proteasome functions, which induces aggregation of aberrant ubiquitinated proteins. Ketorolac exposure also induced the aggregation of expanded polyglutamine proteins, results cellular proteostasis disturbance. We found that the treatment of Ketorolac aggravates the accumulation of various cell cycle-linked proteins, which results in pro-apoptotic induction in cells. Ketorolac-mediated proteasome disturbance leads to mitochondrial abnormalities. Finally, we have observed that Ketorolac treatment depolarized mitochondrial membrane potential, released cytochrome c into cytoplasm, and induced apoptosis in cells, which could be due to proteasome functional depletion. Perhaps more in-depth research is required to understand the details of NSAID-based anti-proliferative molecular mechanisms that can elevate apoptosis in cancer cells and generate anti-tumor potential with the combination of putative cancer drugs.

The genotoxic effects of organophosphate insecticides Profenofos 50% EC in meiotic behaviour of chromosome were studied. The rooted onion bulbs were treated with different concentration of insecticides (0.2%, 0.4%, 0.6%, 0.8% and 1.0%) for varying treatments periods (24 hrs., 48 hrs. and 72 hrs.) respectively. The rooted onion bulbs were planted to obtained for M1 generation for meiotic analysis. Meiotic division of PMC of Allium cepa L. anthers were examined cytologically. This insecticide enhances the chromosome abnormality and statistically increase (p ? 0.05) in dose and duration dependent manner in addition to pollen sterility. Numerous cytological abnormalities were observed such as stickiness, micronuclei, lagging, univalent, quadrivalent, chromatin bridge and break such anomalies in plants have the potential to affect genetic makeup by ingestion exhibited chromosomal abnormalities at lower concentration. The scientists suggest avoiding large concentration dosages.

Gait is an imperative pointer that is used in behavioural biometrics to identify a person over a long distance without direct contact. This paper presents a novel LSTMbased framework for modelling the temporal dynamics of human gait for person identification. We propose an end-toend architecture that encodes short-term spatial features from silhouette and key point inputs and aggregates them over time using stacked Long Short-Term Memory (LSTM) layers with attention and temporal pooling. To improve robustness to view, speed, and clothing variations, we introduce a temporal augmentation pipeline and a triplet-loss-based training strategy that encourages discriminative sequence embeddings. Experiments on standard gait datasets demonstrate that our approach outperforms classical handcrafted descriptors and competitive deep baselines, particularly under cross-view and limited-length sequence conditions. We also provide ablation studies that quantify the contribution of temporal depth, attention, and augmentation. The proposed method is lightweight enough for near-real-time deployment and shows promise for fusion with face and other biometrics in multimodal systems.

Arsenic (As) contamination in rice poses a significant threat to human health due to its toxicity and widespread consumption. Identifying and manipulating key genes governing As accumulation in rice is crucial for reducing this threat. The large NIP gene family of aquaporins in rice presents a promising target due to functional redundancy, potentially allowing for gene manipulation without compromising plant growth. This study aimed to utilize genome editing to generate knock-out (KO) lines of genes of NIP family ( OsLsi1, OsNIP3;1) ) and an anion transporter family ( OsLsi2 ), in order to assess their impact on As accumulation and stress tolerance in rice. KO lines were created using CRISPR/Cas9 technology, and the As accumulation patterns, physiological performance, and grain yield were compared against wild-type (WT) under As-treated conditions. KO lines exhibited significantly reduced As accumulation in grain compared to WT. Notably, Osnip3;1 KO line displayed reduced As in xylem sap (71-74%) and grain (32-46%) upon treatment. Additionally, these lines demonstrated improved silicon (23%) uptake, photosynthetic pigment concentrations (Chl a: 77%; Chl b: 79%, Total Chl: 79% & Carotenoid: 49%) overall physiological and agronomical performance under As stress compared to WT. This study successfully utilized genome editing for the first time to identify OsNIP3;1 as a potential target for manipulating As accumulation in rice without compromising grain yield or plant vigor.

Face and Human walking style is plays important role to recognize a person. This paper is a brief assessment of various machine learning algorithms for solving multi-biometric recognition, their limitations and their applications. Face and Gait taken as two different inputs for recognize a person from captured video by camera. Here captured both inputs not need to inform to a person. Here Analyze Face and gait as Uni-Bio metric model and find their results then after applying Fusion technique as a multi bio metric model (face +gait features), conclude their results in different machine learning algorithms in different data sets and different environments. Here also focus some different Fusion techniques that are applicable in different machine learning algorithms. Index Terms-Multi-biometric, Face and Gait features, Machine Learning algorithms.

Increasing incidences of fungal infections and prevailing antifungal resistance in healthcare settings has given rise to an antifungal crisis on a global scale. The members of the genus Candida, owing to their ability to acquire sessile growth, are primarily associated with superficial to invasive fungal infections, including the implant-associated infections. The present study introduces a novel approach to combat the sessile/biofilm growth of Candida by fabricating nanofibers using a nanoencapsulation approach. This technique involves the synthesis of tyrosol (TYS) functionalized chitosan gold nanocomposite, which is then encapsulated into PVA/AG polymeric matrix using electrospinning. The FESEM, FTIR analysis of prepared TYS-AuNP@PVA/AG NF suggested the successful encapsulation of TYS into the nanofibers. Further, the sustained and long-term stability of TYS in the medium was confirmed by drug release and storage stability studies. The prepared nanomats can absorb the fluid, as evidenced by the swelling index of the nanofibers. The growth and biofilm inhibition, as well as the disintegration studies against Candida, showed 60-70 % biofilm disintegration when 10 mg of TYS-AuNP@PVA/AG NF was used, hence confirming its biological effectiveness. Subsequently, the nanofibers considerably reduced the hydrophobicity index and ergosterol content of the treated cells. Considering the challenges associated with the inhibition/disruption of fungal biofilm, the fabricated nanofibers prove their effectiveness against Candida biofilm. Therefore, nanocomposite-loaded nanofibers have emerged as potential materials that can control fungal colonization and could also promote healing.

Proteostasis is essential for normal function of proteins and vital for cellular health and survival. Proteostasis encompasses all stages in the "life" of a protein, that is, from translation to functional performance and, ultimately, to degradation. Proteins need native conformations for function and in the presence of multiple types of stress, their misfolding and aggregation can occur. A coordinated network of proteins is at the core of proteostasis in cells. Among these, chaperones are required for maintaining the integrity of protein conformations by preventing misfolding and aggregation and guide those with abnormal conformation to degradation. The ubiquitin-proteasome system (UPS) and autophagy are major cellular pathways for degrading proteins. Although failure or decreased functioning of components of this network can lead to proteotoxicity and disease, like neuron degenerative diseases, underlying factors are not completely understood. Accumulating misfolded and aggregated proteins are considered major pathomechanisms of neurodegeneration. In this chapter, we have described the components of three major branches required for proteostasis-chaperones, UPS and autophagy, the mechanistic basis of their function, and their potential for protection against various neurodegenerative conditions, like Alzheimer's, Parkinson's, and Huntington's disease. The modulation of various proteostasis network proteins, like chaperones, E3 ubiquitin ligases, proteasome, and autophagy-associated proteins as therapeutic targets by small molecules as well as new and unconventional approaches, shows promise.