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The Internet of Things (IoT) revolutionises modern technology, offering unprecedented opportunities for connectivity and automation. However, the increased adoption of IoT devices introduces substantial security vulnerabilities, necessitating effective anomaly detection frameworks. This Paper proposes a secure IoT anomaly detection framework by utilising four machine learning algorithms such as: Logistic Regression (LR), Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), and Gaussian Naive Bayes (GNB). By generating synthetic datasets with induced anomalies, the framework employs AWS IoT Core infrastructure and Python-based analysis to identify irregularities in device performance. The proposed framework achieved a high detection accuracy ranging from 91 to 98% across the tested algorithms, with CART showing the best performance. Key performance metrics, including precision, recall, and F1-score, confirmed the model's reliability in distinguishing between normal and anomalous IoT data. Experimental results demonstrate superior detection accuracy across all methods, validating the robustness of the proposed approach. This research offers a scalable solution for IoT security, paving the way for improved anomaly detection and mitigation strategies in connected environments. The integration of machine learning algorithms with IoT infrastructure allows for real-time monitoring and proactive anomaly detection in diverse IoT applications. The proposed framework enhances security measures and contributes to the overall reliability and efficiency of connected systems. Article Highlights: A secure IoT framework uses ML models (LR, LDA, CART, GNB) to detect anomalies in sensor data. IoT security solution outperforms existing methods with an anomaly detection accuracy of 91–98%. The CART algorithm showed superior performance in anomaly detection among tested models. [ABSTRACT FROM AUTHOR]

This paper critically examines model compression techniques within the machine learning (ML) domain, emphasizing their role in enhancing model efficiency for deployment in resource-constrained environments, such as mobile devices, edge computing, and Internet of Things (IoT) systems. By systematically exploring compression techniques and lightweight design architectures, it is provided a comprehensive understanding of their operational contexts and effectiveness. The synthesis of these strategies reveals a dynamic interplay between model performance and computational demand, highlighting the balance required for optimal application. As machine learning (ML) models grow increasingly complex and data-intensive, the demand for computational resources and memory has surged accordingly. This escalation presents significant challenges for the deployment of artificial intelligence (AI) systems in real-world applications, particularly where hardware capabilities are limited. Therefore, model compression techniques are not merely advantageous but essential for ensuring that these models can be utilized across various domains, maintaining high performance without prohibitive resource requirements. Furthermore, this review underscores the importance of model compression in sustainable artificial intelligence (AI) development. The introduction of hybrid methods, which combine multiple compression techniques, promises to deliver superior performance and efficiency. Additionally, the development of intelligent frameworks capable of selecting the most appropriate compression strategy based on specific application needs is crucial for advancing the field. The practical examples and engineering applications discussed demonstrate the real-world impact of these techniques. By optimizing the balance between model complexity and computational efficiency, model compression ensures that the advancements in AI technology remain sustainable and widely applicable. This comprehensive review thus contributes to the academic discourse and guides innovative solutions for efficient and responsible machine learning practices, paving the way for future advancements in the field. [ABSTRACT FROM AUTHOR]

The environmental impact of trace metal contamination is a concern for Lake Small Abaya, Ethiopia, because of nearby agricultural and industrial activities. This study assessed the levels of trace metals (Pb, Zn, Cd, Cu, Fe, Mn, and Cr) in water, sediment, and fish samples, as well as the physicochemical parameters of the water. Samples were collected from five sites and analyzed via graphite furnace atomic absorption spectrometry (GFAAS). The mean concentrations in the water were Zn: 0.6971 mg/l, Fe: 0.5628 mg/l, Cu: 0.1168 mg/l, Mn: 0.2129 mg/l, Pb: 0.0057 mg/l, Cr: 0.0021 mg/l, and Cd: 0.0014 mg/l. In the sediments, the mean concentrations were as follows: Fe, 33.066 mg/kg; Zn, 18.263 mg/kg; Mn, 22.777 mg/kg; Cu, 7.5663 mg/kg; Pb, 0.0751 mg/kg; Cr, 0.0233 mg/kg; and Cd, 0.0183 mg/kg. The fish samples presented mean concentrations of Fe: 21.855 mg/kg, Zn: 12.686 mg/kg, Cu: 0.3185 mg/kg, Mn: 0.9181 mg/kg, Pb: 0.0089 mg/kg, Cd: 0.0075 mg/kg, and Cr: 0.0015 mg/kg. All the metal concentrations were generally below the World Health Organization (WHO) regulatory limits. The physicochemical parameters indicated slightly alkaline to neutral conditions, with electrical conductivity and total dissolved solids within acceptable ranges. These findings suggest that current agricultural and industrial activities do not significantly contribute to trace metal pollution. However, continued monitoring and pollution control measures are recommended to ensure the long-term health and sustainability of the lake. This study highlights the importance of effective environmental management strategies to safeguard this crucial aquatic resource. [ABSTRACT FROM AUTHOR]

High salinity presents a critical challenge in agriculture, leading to yearly crop losses. It affects crops by inducing both osmotic stresses, reducing water uptake, and ionic stress, causing harmful ion influx into the transpiration stream, leading to cellular damage. Salinity-induced stress results in the overproduction of reactive oxygen species (ROS), causing oxidative harm to cellular components and membranes and, in severe cases, plant and cell death. Plants defend against salt-induced oxidative damage by eliminating ROS and regulating ROS production through the antioxidant defense system. Recent studies have shown that various bioactive nanoparticles (NPs), with specific shapes, sizes, and concentrations, can effectively mitigate salt stress in various agricultural plants. These NPs also enhance growth parameters, seed germination, root morphology, productivity, and physio-biochemical composition. However, a significant knowledge gap exists regarding the molecular processes governing NP transport and plant absorption. To harness NPs for sustainable agriculture, gaining a comprehensive understanding of biological processes across multiple levels is essential. Furthermore, as the demand for detailed information on complex agricultural traits and crop responses to NP exposure increases, omics technologies have advanced in precision agriculture and nanotoxicity research. In this review article, we leverage significant advancements in multi-omics to introduce the "Nano-omics" approach for mitigating the effects of salt stress on plants and enhancing their productivity. [ABSTRACT FROM AUTHOR]

Groundwater is an essential source of drinking as well as irrigation water. It has recently become a significant challenge to maintain good and safe drinking water for all living beings. The continuous supply of arsenic detected in groundwater poses a severe health problem and has adverse effects on humans and the ecosystem. Researchers also identified arsenic contamination globally across various regions. However, a few studies also identified that the groundwater of Patna, Saran, and Vaishali districts of Bihar is intoxicated by arsenic. To assess the toxic level of arsenic in groundwater, samples from various GPS-based pointed locations were collected from the study area using a GARMIN GPS device. The total concentration of arsenic in drinking water (mostly traces of arsenic, level of μg L−1 or less) can be detected only by sophisticated analytical techniques such as ICP-MS, GF-AAS, and HG-AAS. The standard procedures were followed to determine quality attributes in groundwater. Arsenic contamination persists in most areas and exceeds the permissible limits prescribed by the World Health Organization (WHO), negatively impacting the health of more than 10 million people in the state. The 90.47% and 85.71% groundwater samples of the study area exceeded the permissible limit of the WHO (0.01 mg L−1) and Bureau of Indian Standards (BIS (0.05 mg L−1), respectively. The analyzed data was obtained, and variability was noticed in total arsenic concentrations ranging from 0.002 to 7.801 mg L−1, with a mean value of 0.87 mg L−1. Similarly, the water quality attribute like total dissolved solids were identified in 14.28% of samples, which crossed 201 to 1026 mg L−1, with a mean value of 375.33 mg L−1. [ABSTRACT FROM AUTHOR]

For the production of bioethanol, bamboo is quickly becoming recognized as a promising feedstock among other bio-based sources with enormous promise. The age of the culm when it is harvested is the most important factor that determines whether or not bamboo may be used as a renewable supply. In this study, the responsive enhancements of Beema bamboo were investigated based on the age of the stem. Beema bamboo is a superior hybrid clone of Bambusa balcooa. For this investigation, the bamboo was harvested at various stages of its development and then subjected to a two-step pretreatment process (step 1 acid treatment and step 2 alkali treatment). The amount of sugar that can be recovered and the amount of ethanol that can be produced from the treatment have both been estimated using enzymatic hydrolysis of the pretreated bamboo. According to the findings of the study, different age groups of bamboo exhibited significantly different chemical compositions (p-value < 0.05). The two-step pretreatment and enzymatic hydrolysis of bamboo resulted in a 95% recovery of fermentable sugar and a theoretical maximum ethanol output of 92.2%. Two-year-old bamboo had the highest ethanol output (321L/Ton) across all age categories. Therefore, 2 years of age was the optimal harvesting age for maximizing sugar recovery for bioethanol production. [ABSTRACT FROM AUTHOR]

Soil salinity is a major nutritional challenge with poor agriculture production characterized by high sodium (Na+) ions in the soil. Zinc oxide nanoparticles (ZnO NPs) and biochar have received attention as a sustainable strategy to reduce biotic and abiotic stress. However, there is a lack of information regarding the incorporation of ZnO NPs with biochar to ameliorate the salinity stress (0, 50,100 mM). Therefore, the current study aimed to investigate the potentials of ZnO NPs application (priming and foliar) alone and with a combination of biochar on the growth and nutrient availability of spinach plants under salinity stress. Results demonstrated that salinity stress at a higher rate (100 mM) showed maximum growth retardation by inducing oxidative stress, resulted in reduced photosynthetic rate and nutrient availability. ZnO NPs (priming and foliar) alone enhanced growth, chlorophyll contents and gas exchange parameters by improving the antioxidant enzymes activity of spinach under salinity stress. While, a significant and more pronounced effect was observed at combined treatments of ZnO NPs with biochar amendment. More importantly, ZnO NPs foliar application with biochar significantly reduced the Na+ contents in root 57.69%, and leaves 61.27% of spinach as compared to the respective control. Furthermore, higher nutrient contents were also found at the combined treatment of ZnO NPs foliar application with biochar. Overall, ZnO NPs combined application with biochar proved to be an efficient and sustainable strategy to alleviate salinity stress and improve crop nutritional quality under salinity stress. We inferred that ZnO NPs foliar application with a combination of biochar is more effectual in improving crop nutritional status and salinity mitigation than priming treatments with a combination of biochar. [ABSTRACT FROM AUTHOR]

A total of 21 surface sediment samples collected from Arasalar River are subjected to sediment texture (sand-silt-clay ratio), trace elements, organic matter, and CaCO3 studies to understand the accumulation dynamics of sediments. To assess the impact of metal pollution in estuarine sediments, the essential parameters should be done by checking the sediment characteristics, spatial distribution of heavy metal sources, sediment dynamics, and geochemical analysis. To evaluate the contamination level of metal pollution, a basic standard reference is required to decipher the values ranging from natural to anthropogenic contribution. From this research analysis, it is observed that the study area predominantly comprises silty sand and sand silty nature. The calcium carbonate content in the sediment is found to be proportional to the presence of shell fragments, whereas the organic matter (OM) is derived from riverine and coastal input which acts as a primary source. The obtained results confessed the average contents (mg/g) for the following selected eight elements in the order of Fe (35249–49068) > Mn (286–519) > Ni (107–279) > Cu (78.30–155.70) > Cr (50–99) > Zn (38.70–91.90) > Pb (39.90–62.40), and Co (12.6–29.1) by using an atomic absorption spectrophotometer (AAS) are utilized for this analysis. Multivariate analysis of heavy metals affirms geogenic sources (weathering of parent rocks) for Fe, Mn, Cr, Co, and Zn, whereas Cu, Ni, and Pb originated from anthropogenic activities (urban and industrial activities). The pollution load index, sediment pollution index, Igeo index, and PERI are categorized as under polluted, low to moderate polluted, and low potential environmental risk variety. Constant inspection and guidance are needed to prevent effluences from various agriculture and industrial activities in the nearby regions. The findings from this research may support and help the government to follow the suitable remediation on the better management of river and coastal areas. [ABSTRACT FROM AUTHOR]

Irritable bowel syndrome (IBS) is frequently linked with coexisting mental illnesses. Our previous study discovered that 32.1% of IBS patients had subthreshold depression (SD), placing them at higher risk of developing major depression. Gut microbiota modulation through psychobiotics was found to influence depression via the gut-brain axis. However, the efficacy of lessening depression among IBS patients remains ambiguous. The study’s aim was to investigate the roles of cultured milk drinks containing 109 cfu Lactobacillus acidophilus LA-5 and Lactobacillus paracasei L. CASEI-01 on depression and related variables among IBS participants with SD. A total of 110 IBS participants with normal mood (NM) and SD, were randomly assigned to one of four intervention groups: IBS-NM with placebo, IBS-NM with probiotic, IBS-SD with placebo, and IBS-SD with probiotic. Each participant was required to consume two bottles of cultured milk every day for a duration of 12 weeks. The following outcomes were assessed: depression risk, quality of life, the severity of IBS, and hormonal changes. The depression scores were significantly reduced in IBS-SD with probiotic and placebo from baseline (p < 0.001). Only IBS-SD with probiotic showed a significant rise in serotonin serum levels (p < 0.05). A significantly higher life quality measures were seen in IBS-SD with probiotic, IBS-SD with placebo, and IBS-NM with placebo (p < 0.05). All groups, both placebo and probiotic, reported significant improvement in IBS severity post-intervention with a higher prevalence of remission and mild IBS (p < 0.05). Dual strains lactobacillus-containing cultured milk drink via its regulation of relevant biomarkers, is a potential anti-depressive prophylactic agent for IBS patients at risk. [ABSTRACT FROM AUTHOR]

The soybean seeds were subjected to priming treatments using varying concentration of silicon dioxide (SiO2) nanoparticles in conjunction with water. The study assessed the effects of SiO2 nanoparticles on seed germination, seedling vigour, biochemical parameters, and osmotic adjustments in seeds that were primed with SiO2 nanoparticles, hydroprimed, and control seeds. These evaluations were conducted under conditions of moisture stress generated by PEG 6000 at -4 and -5 bars, as well as under non-drought stress condition. The findings of the study indicate that lower concentrations of SiO2 nanoparticles (NPs) had a positive impact on seed physiological and biochemical parameters. Conversely, higher concentrations of SiO2 NPs during priming resulted in reduced seed germination and antioxidant activity, both in drought stress and non stress conditions. Soybean seeds that were treated with silicon dioxide nanoparticles (SiO2 NPs) at a concentration of 500 mg/liter exhibited the highest rate of germination, germination percentage, and seedling vigour in non drought stress and in drought stress at -4 and -5 bars. The application of silicon dioxide nanoparticles (SiO2 NPs) at a concentration of 500 mg/liter during seed priming resulted in an enhancement in antioxidant enzyme activities, including catalase, peroxidase, and superoxide dismutase. Additionally, the seedlings exhibited increased levels of proline and relative water content, while experiencing a reduction in electrolyte leakage from the leaves under conditions of moisture stress generated by polyethylene glycol (PEG). [ABSTRACT FROM AUTHOR]

In this study, we investigated the reactivity of γ-graphyne (Gp) and its derivatives, Gp-CH3, Gp-COOH, Gp-CN, Gp-NO2, and Gp-SOH, for the removal of toxic heavy metal ions (Hg+ 2, Pb+ 2, and Cd+ 2) from wastewater. From the analysis of the optimized structures, it was observed that all the compounds exhibited planar geometry. The dihedral angles (C9-C2-C1-C6 and C9-C2-C1-C6) were approximately 180.00°, indicating planarity in all molecular arrangements. To understand the electronic properties of the compounds, the HOMO (EH) and LUMO (EL) energies were calculated, and their energy gaps (Eg) were determined. The EH and EL values ranged between − 6.502 and − 8.192 eV and − 1.864 and − 3.773 eV, respectively, for all the compounds. Comparing the EH values, Gp-NO2 exhibited the most stable HOMO, while Gp-CH3 had the least stable structure. In terms of EL values, Gp-NO2 had the most stable LUMO, while Gp-CH3 was the least stable. The Eg values followed the order: Gp-NO2 < Gp-COOH < Gp-CN < Gp-SOH < Gp-CH3 < Gp, with Gp-NO2 (4.41 eV) having the smallest energy gap. The density of states (DOS) analysis showed that the shape and functional group modifications affected the energy levels. Functionalization with electron-withdrawing (CN, NO2, COOH, SOH) or electron-donating (CH3) groups reduced the energy gap. To specifically target the removal of heavy metal ions, the Gp-NO2 ligand was selected for its high binding energy. Complexes of Gp-NO2-Cd, Gp-NO2-Hg, and Gp-NO2-Pb were optimized, and their properties were analyzed. The complexes were found to be planar, with metal-ligand bond distances within the range of 2.092→3.442 Å. The Gp-NO2-Pb complex exhibited the shortest bond length, indicating a stronger interaction due to the smaller size of Pb+ 2. The computed adsorption energy values (Eads) indicated the stability of the complexes, with values ranging from − 0.035 to -4.199 eV. Non-covalent interaction (NCI) analysis was employed to investigate intermolecular interactions in Gp-NO2 complexes. The analysis revealed distinct patterns of attractive and repulsive interactions, providing valuable insights into the binding preferences and steric effects of heavy metals. [ABSTRACT FROM AUTHOR]

The study investigates residents' behavior towards reducing the use of single-use plastic (SUP), specifically in the context of food packaging. The widespread view holds that pro-environmental behavior (PB) results from a person's moral and rational deliberations. In reducing single-use plastic (SUP) consumption and waste, the relative roles of rationality and morality models in validating PB among rural and urban residents are not yet clear. In this empirical study, we compared the relative efficacy of two models for explaining people's SUP reduction behavior: the theory of planned behavior (TPB; rationality) and the value belief norm (VBN; morality). We investigated Thailand's rural (Sichang Island) and metropolitan (Nonthaburi city) areas. As a result, we surveyed people living on Sichang Island (n = 255) and in Nonthaburi city (n = 310). We employed structural equation modeling (SEM) for data analysis in this study. Findings showed that while morality better justified all the study participants' SUP reduction behavior, rationality underpinned behaviors of rural residents, while morality better explained the actions of city residents. We discussed future theoretical development and a policy roadmap based on these findings. [ABSTRACT FROM AUTHOR]

With the fast development of unmanned aerial vehicles (UAVs) and the user increasing demand of UAV video transmission, UAV video service is widely used in dynamic searching and reconnoitering applications. Video transmissions not only consider the complexity and instability of 3D UAV network topology but also ensure reliable quality of service (QoS) in flying ad hoc networks (FANETs). We propose hedge transfer learning routing (HTLR) for dynamic searching and reconnoitering applications to address this problem. Compared with the previous transfer learning framework, HTRL has the following innovations. First, hedge principle is introduced into transfer learning. Online model is continuously trained on the basis of offline model, and their weight factors are adjusted in real-time by transfer learning, so as to adapt to the complex 3D FANETs. Secondly, distributed multi-hop link state scheme is used to estimate multi-hop link states in the whole network, thus enhancing the stability of transmission links. Among them, we propose the multiplication rule of multi-hop link states, which is a new idea to evaluate link states. Finally, we use packet delivery rate (PDR) and energy efficiency rate (EER) as two main evaluation metrics. In the same NS3 experimental scenario, the PDR of HTLR is at least 5.11% higher and the EER is at least 1.17 lower than compared protocols. Besides, we use Wilcoxon test to compare HTLR with the simplified version of HTLR without hedge transfer learning (N-HTLR). The results show that HTRL is superior to N-HTRL, effectively ensuring QoS. [ABSTRACT FROM AUTHOR]

This study focuses on the design of new 2D membranes from connected Clar's Goblet as a potential sensor for pharmaceutical pollutants, specifically the painkiller drugs aspirin, paracetamol, ibuprofen, and diclofenac. The electronic, optical, and interaction properties are investigated using density functional theory calculations. The Clar's Goblet membranes (CGMs) that were chosen are semiconductors with an energy gap of around 1.5 eV, according to energy gap calculations and density of states. Molecular electrostatic potential (ESP) analysis shows that CGMs have electrophilic and nucleophilic sites, suggesting their suitability for interacting with pharmaceutical pollutants. The adsorption energies confirm the chemical adsorption of pharmaceutical pollutants with diclofenac showing the strongest adsorption. The UV–Vis absorption spectra of CGMs-drug complexes are analyzed, revealing a redshift compared to the absorption spectrum of CGMs alone, confirming the adsorption of these drugs. Further analysis using hole/electron examinations indicates that the type of excitation is local excitation rather than charge transfer excitation. This study quantitatively characterized hole and electron distribution in excited states using various indices. The analysis revealed local excitation transitions and significant charge transfer between the CGMs molecule and pharmaceutical pollutants. Additionally, non-covalent interaction analysis indicates the presence of van der Waals interactions, highlighting the adsorption behavior of the drugs. These results demonstrate the potential of CGMs as a highly sensitive sensor for pharmaceutical pollutants. [ABSTRACT FROM AUTHOR]

The current research was aimed to examine the NLO properties of novel benzodithiophene-based donor–acceptor (D-A)-type compounds (BDTD1–BDTD8) via structural modulation of reference compound (BDTR). Optimization of the reference compound (BDTR) along with eight derivatives was accomplished at M06/6-311G(d,p) level. Subsequently, the optimized geometries were further employed to execute additional analyses: UV–Vis absorption, natural population analysis (NPA), NLO, frontier molecular orbitals (FMOs) and natural bond orbital (NBO) properties at the above-mentioned functional. All the tailored compounds (BDTD1–BDTD8) were reported with less energy difference in comparison with BDTR. The descending order of compounds accordant to Egap values was found to be as BDTR > BDTD1 > BDTD8 > BDTD4 > BDTD2 > BDTD5 > BDTD7 > BDTD6 > BDTD3. Furthermore, assisted by FMOs analysis, density of states (DOS) computations demonstrated significant charge mobility from HOMO towards LUMO in the derivatives. Global reactivity descriptors correspond to Egap values, BDTD3 with least energy difference accompanied with less hardness (1.028 eV) and highest softness (0.486 eV) among all the derivatives. BDTD3 exhibited the highest value of λmax (717.211 nm) in all the designed compounds relative to BDTR (576.161 nm). For all fabricated chromophores, the βtot values are presented in the decreasing order: BDTD3 > BDTD7 > BDTD6 > BDTD5 > BDTD2 > BDTD4 > BDTD1 > BDTD8 > BDTR. Interestingly, the highest values as 2.324 × 10–27 and 4.302 × 10–32 esu of βtot and γtot, respectively, were indicated by BDTD3 compound. Valuable NLO findings explored that our derivatives might be significant candidates for nonlinear optics. [ABSTRACT FROM AUTHOR]

Heavy metals (HMs) are among the most harmful environmental constraints, threatening a wide range of life-forms, including plants. HMs significantly impair plant metabolism by interfering with the function of critical cellular biomolecules and ultimately lead to reduced crop yields. Various strategies were used to overcome the HM toxicity; among this use of nanoparticles (NPs) is a relatively new, effective, and efficient approach than the other conventional techniques. NPs decrease the mobility and bioavailability of HMs in soil, enhancing the proficiency of the apoplastic barrier within plants to restrict HM movement. NPs protect the plants' antioxidant system by increasing the activities of enzymatic and non-enzymatic antioxidants, collectively enhancing their role as stress mitigators. The current article discusses the role and mechanism of NPs to alleviate HM stress in soil and plants. The various factors affecting the interaction of NPs with HMs and toxicity raised by these materials in environment are also discussed. This article also discusses the future recommendations for utilization of NPs in plants to alleviate HM stress. [ABSTRACT FROM AUTHOR]

New organic dyes (H1-H6) for their promising applications as dye sensitized solar cell (DSSCs) were theoretically designed from 6,6′-di(thiophen-2-yl)-4,4′-bipyrimidine (TB) moiety in acceptor (A), π-spacer, and donor (D) type architecture to create A-π-D-π-D-π-A framework. After their benchmarking study against various exchange correlation (XC) and long-range corrected (LC) functional, the CAM-B3LYP produced accurate results so as selected for further density functional theory (DFT) and time dependent DFT (TD-DFT) studies. The frontier molecular orbitals (FMOs) were analyzed for their electron transfer properties, and their energies of the highest occupied molecular orbital (EHOMO) and the lowest unoccupied molecular orbital (ELUMO) were used to assess various electronic properties. Their energy differences (EH-L) ranged between 1.69 and 2.03 eV indicating their good responsiveness to electron injection (Ginj) being the values greater than 0.2 eV. The maximum absorbance of the dyes was reported around the 388–406 nm while their starting material (TB) had this value to be 371 nm. This redshift was significant with an intensification of electron-withdrawing groups on the dye structures. The dyes were evaluated for their device related parameters like their light harvesting efficiency, open circuit voltage, exciton binding energies, and exciton life times which were found in their promising values. The dyes were analyzed for their linear (α), first (βtotal), and second (γtotal) order nonlinear responses and were found to have significantly higher responses, not only against their starting materials but also those reported in literature for standard molecules (urea and p-nitric acid). Among the dyes under study, dye H4 exhibits the highest molecular polarizability (α) and hyperpolarizability (β and γ) values thanks to two CN substituted units on each ends. These dyes are most likely to have possible optical and photonic uses. Also, according to the results of the current theoretical research, all of these dyes may function as effective photosensitizer for their DSSC application. [ABSTRACT FROM AUTHOR]

In this work, we focused on the 3rd goal of the sustainable development plan: achieving good health and supporting well-being. Two redox-active hydrazo ligands namely, phenylcarbonohydrazonoyldicyanide (PCHD) and pyridin-4-ylcarbonohydrazonoyl-dicyanide (PyCHD), and their copper(I) complexes have been synthesized and characterized. The analytical data indicates the formation of copper(I) complexes despite starting with copper(II) perchlorate salt. The 1H-NMR and UV–visible spectral studies in DMSO revealed that PyCHD mainly exists in its azo-form, while PCHD exists in azo ↔ hydrazo equilibrium form, and confirmed the copper(I) oxidation state. XPS, spectral and electrochemistry data indicated the existence of copper(I) valence of both complexes. Cyclic voltammetry of PCHD and its copper(I) complex supported the reduction power of the ligand. The antimicrobial activity, cytotoxicity against the mammalian breast carcinoma cell line (MCF7), and DNA interaction of the compounds are investigated. All compounds showed high antimicrobial, and cytotoxic activities, relative to the standard drugs. Upon studying the wheat DNA binding, PCHD and PyCHD were found to bind through external contacts, while both [Cu(PCHD)2]ClO4.H2O and [Cu(PyCHD)2]ClO4.H2O were intercalated binding. In-silico molecular docking simulations against Estrogen Receptor Alpha Ligand Binding Domain (ID: 6CBZ) were performed on all produced compounds and confirmed the invitro experimentally best anticancer activity of [Cu(PyCHD)2]ClO4.H2O. The molecular docking tests against SARS-CoV-2 main protease (ID: 6 WTT) showed promising activity in the order of total binding energy values: [Cu(PCHD)2]ClO4.H2O > [Cu(PyCHD)2]ClO4.H2O > PCHD > PyCHD. [ABSTRACT FROM AUTHOR]

Internal exposure of public to radiation arising from ingestion of natural radionuclides in tuber crops of Ebonyi State origin was investigated in this study. Committed effective doses and lifetime cancer risk of 40K, 226Ra, and 232Th in cassava, cocoyam, water yam, and white yam were calculated. The average activity concentrations of 40K, 226Ra, and 232Th determined by gamma spectrometric Na (TI) detector were, respectively, 199.15 ± 23.51, 77.57 ± 7.98, and 118.20 ± 10.72 Bq/kg in cassava; 146.62 ± 40.69, 43.42 ± 7.63, and 75.61 ± 2.89 Bq/kg in cocoyam; 162.81 ± 20.43, 63.17 ± 11.36, and 81.50 ± 10.27 Bq/kg in water yam; and 184.50 ± 20.22, 80.23 ± 10.93, and 116.29 ± 5.93 Bq/kg in white yam. The total committed effective dose via ingestion aligned in this order of cassava (7.05 mSv/year) > white yam (4.38 mSv/year) > water yam (0.42 mSv/year) > cocoyam (0.21 mSv/year) with overall average dose of 3.12 mSv/year. The values of dose were higher than world average of 0.29 mSv/year given by United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). The lifetime cancer risk values were above tolerance level of >10−4 prescribed by United States Environmental Protection Agency (USEPA), suggesting probable evolvement of radiogenic cancer morbidity. The data presented in this study contributes to baseline information on radiological characteristics of tuber crops in Ebonyi, which would be valuable to WHO/FAO food safety policy in Nigeria and rest of the world. [ABSTRACT FROM AUTHOR]

Abiotic and biotic stresses hamper our agricultural productivity by reducing crop growth, leading to food crises all over the globe. At present, the main objective of environmentalists is to ensure food safety by improving crop production in stressful environment. To achieve this goal, nanotechnology is a promising tool to sustainably promote food production. Seed nano-priming has emerged as a successful method to activate not only seed germination and seedling establishment but also the growth of the plant. Here we are focusing on some important benefits of seed nano-priming, like rapid germination, better plant growth, and higher yield. Furthermore, an attempt has been made to explain seed priming technology, mechanism of seed germination along with molecular, biochemical, and physiological changes on nano-priming. The data presented in this review prove that nano-priming can mitigate abiotic and biotic stresses and provide an option to raise a resilient crop. This review has also highlighted the challenges and limitations in using seed nano-priming for sustainable agriculture. We have also discussed here future possibility of usage of endophytes due to their enormous benefits to host and non-host plants, as well in seed germination and in abiotic stress tolerance via seed priming, with different innovative seed coating techniques, which could be used as potential technology in advancing dynamic and sustainable agriculture. [ABSTRACT FROM AUTHOR]

Due to sessile, plants are unable to avoid unfavorable environmental conditions which leads to inducing serious negative effects on plant growth, crop yield, and food safety. Instead, various approaches were employed to mitigate the phytotoxicity of these emerging contaminants from the soil–plant system. However, recent studies based on the exogenous application of ZnO NPs approve of their important positive potential for alleviating abiotic stress-induced phytotoxicity leads to ensuring global food security. In this review, we have comprehensively discussed the promising role of ZnO NPs as alone or in synergistic interactions with other plant growth regulators (PGRs) in the mitigation of various abiotic stresses, i.e., heavy metals (HMs), drought, salinity, cold and high temperatures from different crops. ZnO NPs have stress-alleviating effects by regulating various functionalities by improving plant growth and development. ZnO NPs are reported to improve plant growth by stimulating diverse alterations at morphological, physiological, biochemical, and ultrastructural levels under abiotic stress factors. We have explained the recent advances and pointed out research gaps in studies conducted in earlier years with future recommendations. Thus, in this review, we have also addressed the opportunities and challenges together with aims to uplift future studies toward effective applications of ZnO NPs in stress management. [ABSTRACT FROM AUTHOR]

Due to sessile, plants are unable to avoid unfavorable environmental conditions which leads to inducing serious negative effects on plant growth, crop yield, and food safety. Instead, various approaches were employed to mitigate the phytotoxicity of these emerging contaminants from the soil–plant system. However, recent studies based on the exogenous application of ZnO NPs approve of their important positive potential for alleviating abiotic stress-induced phytotoxicity leads to ensuring global food security. In this review, we have comprehensively discussed the promising role of ZnO NPs as alone or in synergistic interactions with other plant growth regulators (PGRs) in the mitigation of various abiotic stresses, i.e., heavy metals (HMs), drought, salinity, cold and high temperatures from different crops. ZnO NPs have stress-alleviating effects by regulating various functionalities by improving plant growth and development. ZnO NPs are reported to improve plant growth by stimulating diverse alterations at morphological, physiological, biochemical, and ultrastructural levels under abiotic stress factors. We have explained the recent advances and pointed out research gaps in studies conducted in earlier years with future recommendations. Thus, in this review, we have also addressed the opportunities and challenges together with aims to uplift future studies toward effective applications of ZnO NPs in stress management. [ABSTRACT FROM AUTHOR]

Pro-environmental behavior has a significant role to play in environmental sustainability. There has been little research done on environmental higher education-renewable energy consumption nexus. This study examines the impact of environmental higher education on renewable energy consumption in China from 1997 to 2021. The ARDL results show that higher environmental education enhances renewable energy consumption in long run. Findings also show that internet usage and economic development encourage renewable energy consumption in the long run. However, financial development and internet usage have a short-term impact on renewable energy consumption in China. The QARDL estimates are robust, and the finding shows that environmental higher education has a positive impact on renewable energy consumption in short and long run at higher quantiles. The empirical findings have environmental implications for China in terms of achieving long-term environmental sustainability by embracing patterns of pro-environmental behavior. [ABSTRACT FROM AUTHOR]

Cyber-physical systems (CPS) play an important role in our daily lives, such as automotive, medical monitoring, smart grid, industrial control systems and so on. CPS typically consists of three main components: sensors, aggregators and actuators. Recently, Software-Defined Networking (SDN) has been applied to CPS for achieving optimal resource allocation and Quality of Service, forming a type of SDN-assisted CPS. To protect such environment, collaborative intrusion detection system (CIDS) is a major security solution, but it is vulnerable to insider threat, where a cyber-attacker can behave maliciously within the network. In this work, we focus on this challenge and investigate the use of blockchain technology that can ensure immutable data sharing without the need of a trusted third party. We introduce a blockchain-enabled collaborative intrusion detection framework for SDN-assisted CPS. In particular, we use challenge-based CIDS in the study and evaluate the proposed framework under both external and internal attacks. The experimental results demonstrate the viability and effectiveness of our blockchain-enabled framework. [ABSTRACT FROM AUTHOR]

Imines are organic moieties associated with numerous frameworks and show applications in organic synthesis, medicine, chemical analysis, and new technologies. Schiff's base-associated materials are a boon for the advancement in the chemical sciences which enables dynamic and tunable properties to cater to science and technology demands as and when required. Schiff base reactions are facile to conduct in aqueous/organic solutions which incorporate and coordinate to form stable molecules. The review focuses on studying the coordination behaviour through structural variations by incorporating an azomethine ligand in the organic and inorganic frameworks, viz. dendrimers, inclusion complexes, and zeolites. The design and development of functionalized multifunctional azomethine (–C=N–) ligand owing to diversified structural entity offer a unified platform for the storage of gaseous molecules, material adsorption, optical sensors, catalysts, drug delivery channels, dyes, and pigments. The interaction of Schiff base with other substances tailoring desired characteristics that explore several dimensions of such assemblages and ordered metal-coordinated Schiff's base-derived complexes is necessary to offer a vast array of advanced materials. Graphical abstract of Azomethine Functionalized Organic-Inorganic Framework and their applications. [ABSTRACT FROM AUTHOR]

Introduction: Clinical Practice Guidelines (CPGs) development and implementation in the Kingdom of Saudi Arabia are suboptimal. The Kingdom's Vision 2030 envisages a transformational change to achieve an effective, integrated, value-based ecosystem focused on patient health. Objectives: This study aimed to develop a CPG appraisal tool that will support the realization of the Kingdom's Vision 2030 through the development of high-quality and highly implementable CPGs. To maximize its impact, all vital healthcare paradigms, such as systems thinking, value-based healthcare, and information technology, will robustly be incorporated in the tool. Methods: The Saudi Health Council through its National Center of Evidence-Based Medicine (NCEBM) embarked on a program to develop this appraisal tool. A taskforce of experts was selected based on their experience in evidence-based practice and training. The task force, through a methodology of extensive literature review, deliberation, outside experts' feedback, and Delphi and consensus voting, developed a prototype appraisal tool that was named the Holistic Appraisal Tool for CPGs (HAT-CPG). Results: The HAT-CPG was developed comprising three sections: an initial basic information section, an internal validity section, and an external validity section with a total of 13 section items and 73 reporting elements. Conclusion: It is envisaged that the Holistic Appraisal Tool will support CPG developers and users in Saudi Arabia in realizing the objectives for which it was developed. [ABSTRACT FROM AUTHOR]

Context: Heavy metals are highly noxious, and their presence can cause diverse effects on living organisms and the environment. Crown ether porphyrins and phthalocyanines are known to effectively extract these pollutants and are also used in photovoltaic devices. This study aims to evaluate various factors that govern intramolecular charge transfer (ICT) and photo-injection processes, including maximum absorption wavelength (λmax), density of states (DOS), charge transfer dipole (μCT), light harvesting efficiency (LHE), open-circuit voltage (Voc), and free energy change of electron injection (ΔGinj) in order to investigate the performance of different compounds designed from metalloporphyrins for bulk-heterojunction organic solar cell (BHJ-OSC) applications. The porphyrin complex showed the best optoelectronic properties, with remarkable LHE values and CT amounts compared to phthalocyanine derivatives. The central metal played a significant role in optimizing the optical properties of the materials for use in solar cells. HgPr4O and CdPr4O were found to have optimal Voc values, resulting in effective injection, high electron, and hole mobilities, making them ideal materials for highly efficient BHJ-OSC devices. Methods: Density functional theory (DFT) approach was employed with the B3LYP functional and the def2TZVP basis set as implemented in the Gaussian 16 revision C.01 program to investigate the designed complexes and to compute geometrical parameters, frontier molecular orbitals (FMOs), and natural bond orbital (NBO). Furthermore, the time-dependent density functional theory (TD-DFT) method was used to analyze the optical properties and photovoltaic characteristics of selected metalloporphyrins by examining the UV-Vis spectra. In summary, the study presents a thorough description of the structural and electronic properties of the investigated complexes and provides insights into their potential use in photovoltaic applications. [ABSTRACT FROM AUTHOR]

Objective: We aimed to examine the influence of sleep disturbances on the risk of oligo/astheno/teratozoospermia (OAT) in men attending an infertility clinic. Methods: We consecutively enrolled men attending an infertility clinic from July 2020 to June 2021. Semen parameters were obtained at initial presentation, and the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale score, and the STOP-BANG Questionnair were completed to assess sleep quality. Embryo outcomes were evaluated after infertility treatment. Results: Of 466 men enrolled, 119 had OAT (OAT group) and 347 had normozoospermia (NS group). There were no differences between the two groups regarding Epworth Sleepiness Scale and STOP-BANG Questionnaire scores. The prevalence of poor sleep quality (Pittsburgh Sleep Quality Index score ≥ 5) in the OAT group was significantly higher than that in the NS group (42% vs. 29%, p = 0.009). A higher rate of poor subjective sleep quality was observed in the OAT group compared with the NS group (p = 0.005) and Pearson's correlations revealed a negative relationship between subjective sleep quality and semen quality. Logistic regression found that subjective sleep quality was independently associated with an increased risk of OAT (adjusted odds ratio = 0.610, p = 0.007). Conclusions: Men with OAT attending an infertility clinic exhibited poor subjective sleep quality. Improving sleep disturbances may be a target intervention to reduce the risk of OAT. This possibility warrants further investigation. [ABSTRACT FROM AUTHOR]

Steady-state fluorescence measurements were used to examine the fluorescence quenching of 1, 4-bis [-(2-benzothiazolyl) vinyl benzene (BVB) by sodium salt of meso-tetrakis (4-sulfonatophenyl) porphyrin (TPPS) in the presence and absence of silver nanoparticles (Ag NPs). The energy transfer (ET) process's emission intensities and Stern–Volmer constants (KSV) showed that Ag NP's presence increased ET's efficiency. The molecular structures of TPPS, TPPS, and BVB/TPPS were optimized using the DFT/B3LYP/6-311G (d) technique to elucidate the mechanism. The discovered optimized molecular structure proved that whereas TPPS and BVB/TPPS MSs are not planar because the porphyrin group in TPPS is rotated out by phenyl sodium sulphate, the BVB MS is planer. All of the theoretical BVB results and the acquired experimental optical results were very similar. [ABSTRACT FROM AUTHOR]

Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare field. Traditionally, the healthcare system works based on centralized agents sharing their raw data. Therefore, huge vulnerabilities and challenges are still existing in this system. However, integrating with AI, the system would be multiple agent collaborators who are capable of communicating with their desired host efficiently. Again, FL is another interesting feature, which works decentralized manner; it maintains the communication based on a model in the preferred system without transferring the raw data. The combination of FL, AI, and XAI techniques can be capable of minimizing several limitations and challenges in the healthcare system. This paper presents a complete analysis of FL using AI for smart healthcare applications. Initially, we discuss contemporary concepts of emerging technologies such as FL, AI, XAI, and the healthcare system. We integrate and classify the FL-AI with healthcare technologies in different domains. Further, we address the existing problems, including security, privacy, stability, and reliability in the healthcare field. In addition, we guide the readers to solving strategies of healthcare using FL and AI. Finally, we address extensive research areas as well as future potential prospects regarding FL-based AI research in the healthcare management system. [ABSTRACT FROM AUTHOR]

Metallic antitumor drugs with heterocyclic ligands, such as novel AMI (amino methyl imidazole) complexes [Pd(AMI)Cl2](1), [Cu(AMI)L1](2), and [Cu(AMI)L2·2H2O](3) where L1 = oxalate and L2 = malonate, were synthesized and characterized. Assessments included elemental analyses, mass spectrometry, Fourier transform-infrared spectroscopy, ultraviolet–visible spectroscopy, and thermal analysis. The cytotoxicity of AMI complexes compared to cisplatin was assessed using MTT (3-[4,5-dimethylthiazol-2-yl] 2,5diphenyl tetrazolium bromide) assay with breast (MCF-7) and cervical (HeLa) cancer cell lines. After treating these cells with the AMI complexes' IC50 values for 48 h, malondialdehyde levels and catalase activity were used to assess oxidative stress, antioxidant activity was evaluated with DPPH radical scavenging method, comet assays assessed DNA damage, and DNA fragmentation was evaluated using the gel electrophoresis. In vitro, antimicrobial activity was assessed using a disc diffusion method. The anticancer activity results showed that IC50 (half-maximal inhibitory concentration) values of complex one, two, and three against MCF-7 and HeLa cancer cells are 0.156 ± 0.0006, 0.125 ± 0.001, 0.277 ± 0.002 μM respectively for MCF-7 cells and 0.222 ± 0.0005, 0.126 ± 0.0009, 0.152 ± 0.001 μM respectively for HeLa cells. Complex two demonstrated strong anticancer activity against MCF-7 and Hela cells. The study of oxidative stress parameters revealed that Malondialdehyde levels increased in cancer cell lines treated with complexes compared to untreated cells. Catalase activity decreased in cells treated with palladium chelate. The DPPH radical scavenging assay results identified that complex one was a more potent antioxidant in MCF-7 and Hela cells than other complexes with SC50 values of 227.5 ± 0.28 and 361 ± 1.2 μL/mL, respectively. The comet assay results showed that complex two caused significant DNA damage in MCF-7 and HeLa cancer cells treated. Antimicrobial assays identified complex three as the most effective. Copper complexes give better antifungal activity against A. flavus than the palladium complex. We conclude that complex two is the most active in both cell types and might be assessed as a clinically useful drug for breast cancer treatment. The significance of the current study is the synthesis of antitumor drugs containing heterocyclic ligands, such as novel AMI complexes, and the study of their biological activities. [ABSTRACT FROM AUTHOR]

In the current study, tetranuclear Ni complex [Ni4(LH)4]·CH3CN (1) (LH3=(E)-2-(hydroxymethyl)-6-(((2-hydroxyphenyl)imino)methyl)phenol) was prepared and incorporated in sulfonic acid functionalized MCM-48 material. This composite nanoporous material was investigated for the adsorption of toxic cationic water pollutant dyes like crystal violet (CV) and methylene blue (MB) from the water solution. Thorough characterization was carried out using a variety of techniques, including NMR, ICP, powder XRD, TGA, SEM, BET, and FT-IR, to verify the phase purity, existence of guest moiety, material morphology, and other crucial variables. The adsorption property was increased with the metal complex immobilization on the porous support. The effect of various parameters on the adsorption process was discussed, including adsorbent dosage, temperature, pH, NaCl concentration, and contact time. Maximum dye adsorption was found at 0.2 mg/ml adsorbent dosage, 10 ppm dye concentration, 6-7 pH, 25 °C temperature, and 15 minutes of contact time. The adsorption of MB (methylene blue) and CV (crystal violet) dyes by Ni complex integrated MCM-48 was effective, with over 99% adsorption achieved in 15 minutes. A recyclability test was also performed, and the material is reusable up to the third cycle, with no notable decline in adsorption found. From the previous literature survey, it is clear that very high adsorption efficiency was achieved using MCM-48-SO3-Ni in considerably short contact time which proves the novelty and effectiveness of the modified material. [ABSTRACT FROM AUTHOR]

Aquatic ecosystems are exceedingly contrived due to industrial dispenses, as a huge amount of toxicants especially heavy metals are released, causing drastic effects on aquatic lives and the human body. This study was performed to assess the quality of point-source industrial wastewater at varying percentage levels and their subsequent hazardous effect on fish (Anabas cobojius) and human health. The perceived value revealed that water quality parameters declined with the increase of wastewater concentration and trace metal evaluation index (TEI) ascertained a high level of water pollution due to Cr, Mn, Fe, Co, Ni, Cu, Zn, and As content for all percentages of wastewater. Concentration of wastewater and culture treatment duration largely impacted on fish mortality rate, body dis-pigmentation, mucus secretion rate, coagulation of mucus all over the body, and accumulation of heavy metals by fish samples. Metal pollution index (MPI) indicated low contamination of fish by the measured elements. Zn and Hg exceeded the threshold limit of target hazard quotient (THQ > 1) and contributed significantly to non-carcinogenic health implications for both the population group. Maximum hazard index in adults and children was observed to be 10.638 and 16.548 for 100% effluent at 96-h exposure period and the overall HI value manifested a very high to medium significant health effects regardless of age. Carcinogen Pb showed insignificant risk but Cr and Ni showed extremely high to medium–high risk for both the population group, and children were found more vulnerable receptors than adults. However, source of heavy metals in wastewater and fish samples stipulated anthropogenic sources. [ABSTRACT FROM AUTHOR]

Copper (Cu), which is produced in cyclotrons or reactors, is a significant tracer in the human body. Bayesian regularized artificial neural networks (ANNs) algorithm, which is one of the ANN approaches, was used in analyzing the production cross sections of 61Cu, 64Cu, and 67Cu radioisotopes in p , α reactions in the present study. The production cross sections of 61Cu, 64Cu, and 67Cu radioisotopes in p , α reactions were assessed by making use of the ANN algorithm and TALYS 1.95 codes. The estimated cross section data were then compared to the data found in the TALYS-Based Evaluated Nuclear Reaction Library 2019 (TENDL) and Experimental Nuclear Reaction Data (EXFOR) Library. ANN results were shown to yield successful correlation coefficients of 0.99477, 0.98665, and 0.99313 for training, testing, and all processes, respectively. Furthermore, the mean square error (MSE) results of ANN prediction were calculated to be 3.6 (training) and 11.84 (testing) mb for all the (p, α .) reactions. It was concluded that the ANN algorithm yielded successful results since ANN estimations were suitable for experimental data, TALYS 1.95 calculations, and TENDL data. [ABSTRACT FROM AUTHOR]

COVID-19 is a virus that causes upper respiratory tract and lung infections. The number of cases and deaths increased daily during the pandemic. Once it is vital to diagnose such a disease in a timely manner, the researchers have focused on computer-aided diagnosis systems. Chest X-rays have helped monitor various lung diseases consisting COVID-19. In this study, we proposed a deep transfer learning approach with novel fine-tuning mechanisms to classify COVID-19 from chest X-ray images. We presented one classical and two new fine-tuning mechanisms to increase the model's performance. Two publicly available databases were combined and used for the study, which included 3616 COVID-19 and 1576 normal (healthy) and 4265 pneumonia X-ray images. The models achieved average accuracy rates of 95.62%, 96.10%, and 97.61%, respectively, for 3-class cases with fivefold cross-validation. Numerical results show that the third model reduced 81.92% of the total fine-tuning operations and achieved better results. The proposed approach is quite efficient compared with other state-of-the-art methods of detecting COVID-19. [ABSTRACT FROM AUTHOR]

A novel azo dye compound, Ethyl (E)-4-((5-hydroxy-3,4-bis(hydroxyl methyl)-6-methyl. pyridin-2-yl)diazenyl)benzoate (EAB), have been synthesized by the coupling reaction and characterized by FT-IR, 1H-and 13C-NMR, Mass, and UV–visible spectroscopies. The nonlinear optical (NLO) properties of the EAB compound via the finding of the nonlinear refractive index (NRI) using continuous wave (cw), low power 473 nm, TEM00 mode laser beam have been studied via the diffraction patterns (DPs) and the Z-scan. Effect of power input of the laser beam, types of beam wavefront and temporal variation of the DPs are discussed. The all-optical switching (AOS) using two laser beams is proved to occur in this compound. [ABSTRACT FROM AUTHOR]

Floating debris is a prominent indicator in measuring water quality. However, traditional object detection algorithms cannot meet the requirement of high accuracy due to the complexity of the environment. It is difficult for some deep learning-based object detection algorithms to achieve fast detection due to the limited performance of embedded devices. To address the above issues, this paper proposes TC-YOLOv5, which improves the detection accuracy by integrating the convolutional block attention module and vision transformer. To ensure the efficiency and low resource consumption of the algorithm, we selectively remove some convolutional layers and reduce some redundant calculations. We evaluated the performance of TC-YOLOv5 on a dataset with multiple species of floating debris, which can process an image in an average of 1.18 s on a Raspberry Pi 4B and achieve the mean average precision (mAP@0.5) of 84.2%. The detection accuracy, speed, and floating-point operations (FLOPs) of TC-YOLOv5 are better than some algorithms of the YOLOv5 series, such as YOLOv5n, YOLOv5s, and YOLOv5m. The above data show that TC-YOLOv5 realizes high-precision, low resource consumption, and rapid detection. [ABSTRACT FROM AUTHOR]

There is an increase in cyberattacks directed at the network behind firewalls. An all-inclusive approach is proposed in this assessment to deal with the problem of identifying new, complicated threats and the appropriate countermeasures. In particular, zero-day attacks and multi-step assaults, which are made up of a number of different phases, some malicious and others benign, illustrate this problem well. In this paper, we propose a highly Boosted Neural Network to detect the multi-stageattack scenario. This paper demonstrated the results of executing various machine learning algorithms and proposed an enormously boosted neural network. The accuracy level achieved in the prediction of multi-stage cyber attacks is 94.09% (Quest Model), 97.29% (Bayesian Network), and 99.09% (Neural Network). The evaluation results of the Multi-Step Cyber-Attack Dataset (MSCAD) show that the proposed Extremely Boosted Neural Network can predict the multi-stage cyber attack with 99.72% accuracy. Such accurate prediction plays a vital role in managing cyber attacks in real-time communication. [ABSTRACT FROM AUTHOR]

There is an increase in cyberattacks directed at the network behind firewalls. An all-inclusive approach is proposed in this assessment to deal with the problem of identifying new, complicated threats and the appropriate countermeasures. In particular, zero-day attacks and multi-step assaults, which are made up of a number of different phases, some malicious and others benign, illustrate this problem well. In this paper, we propose a highly Boosted Neural Network to detect the multi-stageattack scenario. This paper demonstrated the results of executing various machine learning algorithms and proposed an enormously boosted neural network. The accuracy level achieved in the prediction of multi-stage cyber attacks is 94.09% (Quest Model), 97.29% (Bayesian Network), and 99.09% (Neural Network). The evaluation results of the Multi-Step Cyber-Attack Dataset (MSCAD) show that the proposed Extremely Boosted Neural Network can predict the multi-stage cyber attack with 99.72% accuracy. Such accurate prediction plays a vital role in managing cyber attacks in real-time communication. [ABSTRACT FROM AUTHOR]

The use of algal biomass as a renewable source of energy is potentially promising. The literature on biofuels derived from Sargassum is limited compared to other macroalgae. The unusual seaweed bloom of Sargassum from 2011 to date can be caused by the following factors: eutrophication of the sea, climate change, and other oceanographic patterns. The atypical invasion has had great ecological and economic effects in the affected regions. Traditionally, Sargassum has been recovered from coasts and beaches for use as fertilizer, but new markets need to be found to exploit the large volumes produced by the seaweed influx and mitigate its impact. The biochemical composition of Sargassum biomass defines it as a potential feedstock for biofuel production. However, the high moisture and ash content constitute the limitations for the development of some energy extraction methods. On the other hand, the costs associated with the removal of high volumes of accumulated Sargassum from coasts and beaches, transportation, cleaning, and storage are relatively high. Therefore, the production of biofuels from Sargassum seaweed is still a technical, economic, and energy challenge. This review proposes a multifactorial approach to the potential use of Sargassum biomass as feedstock for energy production, especially by thermochemical conversion (combustion, gasification, pyrolysis, and hydrothermal liquefaction). The survey analyses the chemical composition, biomass productivity and coastal impact, energy output, thermochemical conversion processes, techno-economic challenges, and future perspectives. In addition, a Sargassum biomass biorefinery approach with a circular bioeconomy approach is proposed. [ABSTRACT FROM AUTHOR]

Controlling photophysical properties is critical for the continued development of electroluminescent devices and luminescent materials. The preparation and study of novel molecules suitable as luminescent for the development of optoelectrical devices have recently received a lot of attention. Even though the as-triazine unit is a good building block for organic active substances, it is rarely used in this context. We created here novel bis-triazine derivative dyes in the far UV–Vis range by alkylation of triazine-thione derivatives with appropriate dibromo compounds. At the B3LYP/6-311**G(d,p) basis set, their optimal molecular structures were obtained. DFT technique confirmed that the new triazine derivatives are in noncoplanar with one of the two phenyl rings and the triazine plane rotating out by 102.09. Also, depending on the energy gap difference between HOMO and LUMO, some important parameters including chemical potential (π), electronegativity (χ), and chemical hardness (η) were calculated. The compounds may be readily polarized and have significant NLO characteristics, as seen by the tiny HOMO–LUMO energy gap. The calculated values for the polarizability (α) of the two new triazine derivatives have the range 6.09–10.75 × 10–24 (esu). The emission peaks seemed to move to the long-wavelength (redshift), with a rise in the fluorescence band, suggesting that the singlet excited state is more polar than the ground state. The influence of solvent polarity and the intermolecular charge transfer (ICT) processes are reflected in the photophysical properties of new fused triazine derivatives. These properties such as extinction coefficient, absorption and emission cross-sections, fluorescence quantum yield, fluorescence lifetime, oscillator strength, the dipole moment, radiative decay rate constant, the energy yield of fluorescence, and the attenuation length were assessed and discussed. [ABSTRACT FROM AUTHOR]

UNESCO declared world cultural landscape heritage to an ancient rice terraces system with a diverse of sustainability values and practices in the Bali Island, called the subak system, to be a World Heritage in 2012. This study examines the views of educated Balinese communities toward the subak ecological system, in response to the lack references regarding public perceptions of the Subak World Heritage in Bali. Participants (n = 912) completed a questionnaire based on a modification of the new ecological paradigm scale. Their views of subak were neutral with respect to human nor environmental orientation. An exploratory factor analysis failed to differentiate between ecocentrism and egocentrism dimensions, indicating a conflict in the perception of the educated Balinese people between preservation and utilization of the subak system. Since this study has its own limitations, which are carefully examined, further research is suggested. [ABSTRACT FROM AUTHOR]

A new series of 13 pyrazole-derivative compounds with potential antifungal activity were synthetized with good yields. The series have the (E)-2-((1-(R)-3,5-dimethyl-1H-pyrazol-4-yl)diazenyl)phenol general structure and were characterized by means of X-ray diffraction, UV–Vis, FTIR, 1H-NMR, 13C-NMR, and two-dimensional NMR experiments. This experimental characterization was complemented by DFT simulations. A deep insight regarding molecular reactivity was accomplished employing a conceptual DFT approach. In this sense, dual descriptors were calculated at HF and DFT level of theory and GGV spin-density Fukui functions. The main reactive region within the molecules was mapped through isosurface and condensed representations. Finally, chemical descriptors that have previously shown to be close related to biological activity were compared within the series. Thus, higher values of chemical potential ω and electrophilicity χ obtained for compounds 10, 9, 8, 6 and 7, in this order, suggest that these molecules are the better candidates as biological agents. [ABSTRACT FROM AUTHOR]

In our everyday lives, we communicate with each other using several means and channels of communication, as communication is crucial in the lives of humans. Listening and speaking are the primary forms of communication. For listening and speaking, the human voice is indispensable. Voice communication is the simplest type of communication. The Automatic Speaker Verification (ASV) system verifies users with their voices. These systems are susceptible to voice spoofing attacks - logical and physical access attacks. Recently, there has been a notable development in the detection of these attacks. Attackers use enhanced gadgets to record users' voices, replay them for the ASV system, and be granted access for harmful purposes. In this work, we propose a secure voice spoofing countermeasure to detect voice replay attacks. We enhanced the ASV system security by building a spoofing countermeasure dependent on the decomposed signals that consist of prominent information. We used two main features— the Gammatone Cepstral Coefficients and Mel-Frequency Cepstral Coefficients— for the audio representation. For the classification of the features, we used Bi-directional Long-Short Term Memory Network in the cloud, a deep learning classifier. We investigated numerous audio features and examined each feature's capability to obtain the most vital details from the audio for it to be labelled genuine or a spoof speech. Furthermore, we use various machine learning algorithms to illustrate the superiority of our system compared to the traditional classifiers. The results of the experiments were classified according to the parameters of accuracy, precision rate, recall, F1-score, and Equal Error Rate (EER). The results were 97%, 100%, 90.19% and 94.84%, and 2.95%, respectively. [ABSTRACT FROM AUTHOR]

Advances in the availability of multi-sensor, remote sensing-derived datasets, and machine learning algorithms can now provide an unprecedented possibility to predict flood events and risk. Therefore, this study was undertaken to develop a flood vulnerability map and to assess the exposure of buildings to flood risk in Warsaw, the capital of Poland. This goal was pursued in four research phases. The thirteen flood predictors were evaluated using information gain ratio (IGR), and finally reduced to eight of the most causative ones and used for flood vulnerability mapping with three machine learning algorithms, Artificial Neural Network Multi-Layer Perceptron (ANN/MLP), Deep Learning Neural Network based approach—DL4j (DLNN-DL4j) and Bayesian Logistic Regression (BLR). These algorithms show a good predictive performance with the receiver operating curve (ROC) value of 0.851, 0.877 and 0.697, respectively. The buildings' exposure to flood was assessed in line with criteria established in European and national legal regulations. The introduced new buildings' flood hazard index (BFH) revealed a significant similarity of potential flood risk for both models, highlighting the greatest risk in zones with high vulnerability to flooding. Depending on the method used, the BFH value was 0.54 (ANN), 0.52 (DLNNs) or 0.64 (BLR). The holistic approach proposed in this study could assist local authorities in improving flood management. [ABSTRACT FROM AUTHOR]

By exploiting the carrier frequency offset (CFO) between a transmitter-receiver pair, this paper proposes a CFO-based physical layer authentication scheme for dynamic multiple-input-multiple-output (MIMO) systems. We first provide analytical modeling of dynamic CFO in such MIMO systems by jointly taking into account the intrinsic oscillator mismatch and Doppler frequency shift caused by node mobility, and employ the self-correlating and extended Kalman filtering techniques for the CFO estimation and prediction. By quantizing the difference between the estimated CFO and predicted one, we then apply the statistical signal processing techniques to develop a CFO-based physical layer authentication scheme for transmitter identity verification. With the help of tools from stochastic process and hypothesis testing theories, we further derive the analytical expressions for false alarm rate as well as detection rate to evaluate the performance of the proposed scheme. Finally, we provide extensive numerical results to demonstrate the efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

Purpose of Review: The study aims to verify the advantages of nonsteroidal mineralocorticoid receptor blockers (MRBs) in the management of hypertension and cardiovascular and renal diseases, comparing with conventional MRBs. Recent Findings: Based on the unique structures, the nonsteroidal MRBs have higher selectivity for mineralocorticoid receptors (MRs) and show no agonist activity for major steroid hormone receptors in contrast to steroidal MRBs. Today, there are two nonsteroidal MRBs, esaxerenone and finerenone, which completed phase 3 clinical trials. Series of clinical trials have shown that both agents achieve similar MR blockade with smaller doses as compared with steroidal MRBs, but have no off-target side effect such as gynecomastia. Esaxerenone has persistent blood pressure-lowering effects in various hypertensive populations, including essential hypertension and those with diabetes and/or chronic kidney disease, while finerenone has demonstrated reduction of the cardiovascular risk rather than blood pressure in patients with diabetes and chronic kidney disease. Summary: Nonsteroidal MRBs are a more refined agent which contributes to appropriate MR blocking with minimized unpleasant adverse effects. [ABSTRACT FROM AUTHOR]

A high-accuracy analytical method is broadly required to obtain reliable research results. Thus, prompt γ-ray analysis (PGA), one of the most accurate non-destructive analytical methods, has been employed in various fields. However, the measurement accuracy of PGA is also known to degrade in hydrogenous samples. The degradation is caused by variation in the measurement sensitivity (counts per milligram) following the change in neutron energy due to scattering with hydrogen nucleus. Number of scatterings is well known to depend on the hydrogen content in a sample. However, considering multiple scatterings, hydrogen density, which has not been taken into account as yet, may also lead to the accuracy degradation. Here, we show the effect of the hydrogen density in PGA by evaluating the measurement sensitivity of samples with the same hydrogen content and different densities. We find that the measurement sensitivity varies by more than 30% depending on the hydrogen density even at the same hydrogen content. The variation is a particularly serious problem for PGA requiring a few percent accuracy in most cases. Additionally, although the variation is apparently observed in hydrogenous samples, the similar phenomenon can occur in other nuclides with a large scattering cross section; it may affect nuclear cross-section measurements using neutrons in such fields as astrophysics and nuclear energy. [ABSTRACT FROM AUTHOR]