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Nano-cellulose is a biodegradable polysaccharide which has multifunctional uses due to its fascinating properties (i.e., antibacterial, antifungal, anticarcinogenic activity) in wastewater treatment, drug design, food packaging, etc. CNC usually extracted from primary plant (such as jute, hemp, flax, cotton, etc.) which has other significant uses (for example preparation of yarn, rope, tissue paper, etc.). To reduce the pressure on primary plant the use of waste biomass of secondary plant could be an effective and economic route of CNC isolation. In this study a series of chemical treatment i.e. scouring (5% soap solution), alkali treatment (16% NaOH solution), bleaching (2% NaClO2 and 2% Na2S2O5 solution at pH = 4.0), acid hydrolysis (60% H2SO4) was conducted to isolate CNC from the waste maize cob. Characterization of the specimens were conducted by FTIR-ATR (Fourier Transform Infrared-Attenuated Total Reflection), FESEM (Field Emission Scanning Electron Microscopy), XRD (X-ray Diffraction), EDX (Energy Dispersive X-ray), DLS (Dynamic Light Scattering), Thermal analysis (TGA/DTG/DTA), and Zeta potential analysis. Different functional groups (>C=O, C≡C, C-O-C, C-O, -OH, etc.) were identified by FTIR-ATR. Crystal structure, crystallite size, and crystallinity index of CNC (around 84.63±0.03%) were observed by XRD analysis. Produced CNC showed enhanced thermal stabilities in TGA/DTG/DTA curves (about 40% residual mass at 600 °C) with the appearance of a peculiar 2D honey comb like void surface microstructure in FESEM micrographs and the surface charge (around -7.09mV) was measured by zeta potential. The newly produced CNC was perfectly nano sized (around 100 nm according to DLS analysis and FESEM micrograph). Hence, this newly produced CNC would be beneficially used to fabricate bio-nanocomposites for potential applications in various sectors such as biomedical, engineering, and industrial wastewater treatment as an appropriate substitute of the unsafe fossil based synthetic ones to develop legitimate environment.

The conjugation of environment and technology coerced the industry to combine these two instruments towards a sustainable and resilient future. Industry 5.0 is the most recent infrastructural revolution of industrial sector technology based on technologies like human–machine interaction, artificial intelligence, IoT, Big Data, collaborative robots, etc. This happened when the sector radically turned its global focus to sustainability and set many environmental goals to meet the requirements. In this research, the authors identified the synergy between Industry 5.0 and green supply chain management (GSCM) for achieving this target at RMG industries in Bangladesh. GSCM is well known for environmental concerns in traditional supply chain stages. For developing countries, the solution of a sustainable approach to counter waste and pollution-related issues is not adequate enough. A proper understanding of the digitalized industrial approach through Industry 5.0 will enable them to make efficient decisions regarding sustainable goal accomplishment and proper monitoring of the initiatives. This paper illustrates how I5.0 can integrate with GSCM. In this synergy, this study has identified 9 synergistic factors and analyzed the impact of each factor by using the interpretive structural modeling approach. By using level portioning, the factors are illustrated in 7 different levels, and MICMAC analysis is used to categorize them. This study offers a detailed exploration of the synergy between Industry 5.0 and GSCM, offering a practical framework that can guide industry stakeholders in implementing advanced technologies to achieve sustainable development in the RMG sector.

In recent years, research on Electric Vehicles (EVs) has gained considerable attention due to their potential to reduce reliance on fossil fuels and curb environmental pollution significantly. Various stakeholders play a pivotal role in the large-scale EV integration into the existing power grid by providing unique services, particularly in grid power management and charging of EV. This study provides a comprehensive analysis of the critical role played by key stakeholders in the large-scale integration of electric vehicles (EVs) into the power grid, with a particular focus on grid power management and charging infrastructure. It systematically examines the involvement of Distributed Network Operators (DNOs), EV Owners (EOs), and Charging Station Owners (CSOs), elucidating their respective objectives, responsibilities, and challenges. Furthermore, the paper delves into power management strategies, reactive power regulation, and advanced control methodologies aimed at enhancing grid stability. A case study on EV adoption in Western Australia is presented to contextualize current developments and future trajectories. The study concludes by identifying key challenges associated with EV-grid integration and providing strategic recommendations to facilitate a more resilient, efficient, and sustainable power system.

Rapid industrialization/urbanization has been marked as a responsible factor for the creation of bulky effluent which is loaded with several harmful toxicants resulting in a hursh damage to the ecosystem and public safety/secuerity. To mitigate this crucial issue, here a fixed-bed column adsorption technology were chosen due to its simplecity, cost-effectivity, reuseablity. Meanwhile, multifunctional biosorbent i.e functionallized rice husk biochar (FRHBC) was produced by EIPS technique from a beneficial source namely rice(Oriza sativa) waste shell. The experiments were conducted to optimize the effect of influential factors like concentration, flowrates, and bed height. To observe the bulk properties the samples were characterized by FESEM,EDX,BET, FTIR-ATR,XRD, and TGA analysis. The effluents were investigated by AAS and UV–vis-NIR techniques. As per the findings it has been stated that the synthesized FRHBC adsorbents have possessed a promizing 2D honeycomb-like well-oriented mesoporous surface microstructure with a larger surface area around 36.84 m2/g. Additionally holds substantial active binding sites, lower crystallinity nearly 23±0.03%, and higher thermal stability upto 700 °C. Noteworthy that the maximum adsorption performence was found 179.77 and 173.01 mg/g for Pb2+ and MB dye. Hence, the newly produced multifunctional FRHBC bioadsorbents would be benificially used to purify real-time industrial wastewater for sustainable environmental protection.

Cellulose nano crystal (CNC) has been considered as multifunctional biopolysaccharide due to its outstanding properties and biodegradable nature. CNC was derived from agro-waste namely maize shells by different treatment like soaping, alkali treatment, bleaching, and acid hydrolysis. Maize shells were chosen as it is considered a waste material that has no use rather burning. While burning of these releases exposes a considerable amount of environmentally airborne pollutants which are responsible for global warming. However, the properties of the extracted CNC were characterized by using FTIR-ATR, XRD,TGA,DTA,DTG, FESEM, DLS, UV–vis-NIR, and Zeta-potential analysis. The removal of hemicellulose and lignin were expelled from CNC asserted by FTIR-ATR. FESEM was used to capture microstructure and surface morphology. TGA/DTA/DTG was used for measurement of thermal stability. Phase composition, crystal structure/exact atomic position were analyzed by XRD measurement. The CNC was found more thermal stability (exposing 40 % residual mass at 600 °C), high crystallinity index (76.09±0.91 %) with good structural purity and smaller particle size around 100 nm along with negative zeta potential. Due to these outstanding properties the newly produced CNC could be beneficially used as a potential reinforcement in bionanocomposite fabrication for various uses in biomedical, industrial, and engineering sectors for the development of sustainable environment.

This study is to construct the solitary wave solutions to the nonlinear Fitzhugh-Nagumo (FN) model. The Fitzhugh-Nagumo(FN) model is a simplification form of the Hodgkin-Huxley model for nerve's impulse transmission through the nerve fibers, it also described the noise formations in circuit theory, the intercellular trigger waves and more. This is indubitably very important mathematical model in various neurobiological sciences and engineering applications. The generalized exponential rational function (GERF) technique is imposed to the considered model which accumulates different wave solutions in suitable form. In addition, we analyze the effects of wave velocity on the attained solutions, to realize the dynamical behavior of the related phenomenon. The attained results confirm the efficiency and consistency of the considered technique.

In this article, we present new exact soliton solutions for the space-time fractional higher-order nonlinear Schrödinger equation, which describes the propagation of ultra-short pulses in nonlinear optical fibers. We apply a traveling wave transformation with the Beta derivative to convert the nonlinear fractional differential equation into a standard nonlinear differential equation. To find the exact analytical solutions, we implement the extended Riccati equation method, which led to a variety of soliton and soliton-like solutions, including trigonometric, hyperbolic, and rational functions. The graphical representations of these solutions show different physical forms, such as kink, periodic, bright bell, and dark bell structures. Additionally, we used planar dynamical systems theory to investigate the bifurcation phenomena in the derived system. A detailed sensitivity analysis was also performed on the dynamical system utilizing the Runge-Kutta method. These exact solitons play a vital role in understanding wave propagation and are essential for validating both numerical simulations and experimental findings in areas such as quantum mechanics, nonlinear optics and engineering.

Soap is essentially used for various purposes. Therefore, it is important to determine the physico-chemical, antioxidant, and antimicrobial properties of soaps to evaluate their quality. The present research work focuses on 22 commercial soaps which include bar soaps (SN 1-SN 19) and liquid hand washes (SN 20-SN 22). The values of different parameters for commercial soaps are observed which are between 3.84–83.75 % for moisture content, 6.83–25.16 cm for foam height, 7.01–10.17 for pH, 62.47–91.39 % for total fatty matter, 0.20–1.17 % for total alkali content, zone of inhibition, 17.33–29.27 mm/100 % conc., antioxidant activity, 357.41–777.15 μg/mL. It is observed that all of the soaps have a foam height, and pH within the permitted limit (FH-above 1.5 cm, pH 7–10). All bar soap has a total fatty matter and a total alkali content within the accepted value. Moreover, 8 soaps show antimicrobial properties against Staphylococcus aureus, which were further tested for rapid efficacy and antioxidant properties. A survey report of 22 commercial branded soaps was done on 50 people in Bangladesh to get feedback from customers. Combining all the parameters, SN 3 has good results among bar soaps with mild moisturizing and cleansing properties (MC-8.30 ± 0.035 %, FH-22.33 ± 0.29 cm), is safe for the skin (pH-9.83 ± 0.02, TAC-0.99 ± 0.03), has good TFM values (72.89 %), has proficient bacteria growth-inhibiting properties (ZI-18.67 ± 0.29 mm/100 % conc.) and has the ability to remove free radicals (357.41 ± 2.07 μg/mL). Besides, SN-21 among liquid hand wash soaps possesses overall excellence as it moisturizes skin well (MC-83.75 ± 0.05 %), is almost safe for skin (pH-7.73 ± 0.02, TAC-0.98 ± 0.01 %), has TFM (11.35 %), has good cleansing capacity (FH-22.66 ± 0.58 cm) and bacteria growth inhibiting activity (29.27 ± 0.25 mm/100 % conc.), destroys selected bacteria (MIC – 1.2 × 107 CFU at 1 min and 5.5 × 107 CFU at 10 seconds), and wash away free radicals from skin (420.64 ± 3.62 μg/mL).

A photonic crystal fiber (PCF) with a hexahedron core has been introduced for usage in petrochemical sensing operations. The performance of the proposed sensor has been statistically analyzed in the frequency band of 1.0 to 3.0 THz. Pure petrol, kerosene, and diesel are poured into the hexahedron core hole. The Finite element Method (FEM) is handled for the simulation and precise calculation and investigation. The sensor utilizing PCF exhibits a relative sensitivity of about 97.80 %, 97.45 %, and 96.25 % and a confinement loss of approximately 1.88 × 10−8 dB/m, 1.90 × 10−8 dB/m, and 1.85 × 10−8 dB/m at 2.20 THz for all investigated Petrol, Kerosene, and Diesel petrochemicals. Moreover, effective areas are values of 7.75 × 10−8 m2, 7.80 × 10−8 m2, and 6.98 × 10−8 m2, and the effective material loss for Petrol, Kerosene, and Diesel of 0.0066168 cm−1, 0.0066955 cm−1 and 0.0066988 cm−1, respectively at 2.20 THz. Both 3D printing and extrusion can be used to create this photonic crystal fiber (PCF) sensor. In addition, this heptagonal photonic crystal fiber sensor will be used for biomedical sensing and various industry fields related to sensing sectors.

Glioblastoma (GBM) is one of the most aggressive cancers due to its high mortality rate in spite of intensive treatment. It may be happened because of drug resistance against their typical receptors, since these receptor genes are often mutated by environmental stress. So identifying mutated oncodriver genes which could be used as potential drug target is essential in order to develop effective new therapeutic drugs as well as better prognosis for GBM patients. In this study, we analyzed whole exome sequencing (WES) profiles of NCBI database on GBM and matched-normal (control) samples originated from astrocyte like neural stem cells (NSC) of subventricular zone (SVZ) to explore GBM-causing mutated oncodriver genes, since SVZ is considered as the origin of GBM development. We detected 16 mutated oncodriver genes. Then, filtering by differential co-expression analysis based on independent RNA-Seq profiles of CGGA database revealed 10 genes as dysregulated oncodriver genes. Following that, 3 significantly overexpressed oncodriver genes (MTCH2, VWF, and WDR89) were identified as potential drug targets. Then molecular mechanisms of GBM development were investigated by these three overexpressed driver genes through gene ontology (GO), KEGG-pathways, Gene regulatory network (GRN) and mutation analysis. Finally, overexpressed oncodriver genes guided top-ranked six drug agents (Irinotecan, Imatinib, etoposide, pazopanib, trametinib and cabozanitinib) were recommended against GBM through molecular docking study. Most of our findings received support by the literature review also. Therefore, the findings of this study might carry potential values to the wet-lab researchers for further investigation in terms of diagnosis and therapies of GBM.

Hydroxyapatite (HA) is frequently used in a variety of biomedical applications especially in orthopedics and dental because of its outstanding bioactivity and biocompatibility. On the other hand, HA lacks inherent antibacterial properties, shows poor mechanical strength, and infection issues are still one of the main causes of implant failure. Consequently, antibacterial HA may be a potential material for HA applications. For any potential uses of modified hydroxyapatite, such as in medicine or environmental protection, magnetite (Fe3O4) may be a crucial element because it has good mechanical properties and is preferred in biomedical systems. Moreover, Fe3O4 is biocompatible and basically nontoxic to humans. Therefore, the present study aims to find a novel approach that may improve the antibacterial activity of HA and HA-Fe3O4 nanocomposites and provide low toxicity to humans. The synthesized HA and HA -Fe3O4 nanocomposites were characterized by XRD, FTIR, SEM, EDX, and Zeta potential analyzer. Moreover, antibacterial activity tests confirmed that the utilization of Ocimum sanctum leaf extract as a reaction medium in HA and HA-Fe3O4 nanocomposites synthesis improved antibacterial activity against Escherichia coli and Staphylococcus aureus. This research demonstrates the green synthesis of HA and HA-Fe3O4 nanocomposites using Ocimum sanctum leaf extract by hydrothermal method, opening the door for potential applications in biomedical fields.

Objectives: Dengue emerged as a significant health threat in endemic regions in recent years. However, inconsistent diagnostic accuracy in sequential dengue infections necessitate improved testing methods to ensure effective management of dengue cases. Here, we evaluated a portable, rapid, and sensitive molecular assay—reverse transcriptase recombinase polymerase amplification assay (RT-RAA)—utilizing a mobile suitcase laboratory to detect infections in suspected dengue cases in Bangladesh. Methods: A total of 364 suspected patients with dengue were enrolled in the study. Dengue cases were confirmed by a positive result from any of the four tests: non-structural protein 1 (NS1) rapid diagnostic test (RDT), immunoglobulin (Ig) M RDT, quantitative reverse transcriptive-polymerase chain reaction (RT-PCR), and RT-RAA assay. IgG RDT was performed to differentiate between primary and secondary dengue infections. Results: Of 364 suspected cases, 320 were confirmed dengue cases, with 55.94% classified as primary and 44.06% as secondary infections. Laboratory results showed comparable positivity rates between RT-RAA (78.8%) and NS1 RDT (77.1%) in primary dengue, followed by quantitative RT-PCR (57.5%) and IgM RDT (12.8%). RT-RAA demonstrated superior positivity rates in secondary dengue (76.6%), surpassing RT-PCR (60.3%), NS1 RDT (27%), and IgM RDT (24.8%). Combining RT-RAA with NS1 RDT detected infections in 89.95% primary and 81.56% secondary dengue. Conclusions: The findings suggest that complementing RT-RAA with NS1 RDT could significantly improve dengue detection rate, particularly, for secondary infections.

This study aimed to investigate the physicochemical properties, antioxidant activity, and organoleptic characteristics of vegan milk chocolate with various formulas. To achieve this objective, seven treatment formulas were used with different levels of OM and SPI, and ESE was added. The parameters analyzed included color, texture profile, particle size distribution, melting profiles, polymorphism, microstructure, fat content, protein content, total phenolics, total flavonoids, antioxidant activity, and organoleptic characteristics. The results showed that the combination of OM and SPI ratios, alongside the addition of ESE, significantly influenced the physicochemical and organoleptic characteristics of milk chocolate. During the reformulation of vegan milk chocolate, type VI (β1) polymorphic crystals were obtained, and no fat bloom was observed, signifying the success of the process. Through organoleptic testing, VC1, VC2, and VC5 received the highest preference from panelists. In particular, VC5 was observed to have the best physicochemical and organoleptic characteristics in this study; the reformulation of milk chocolate was suitable for vegan consumers as a non-dairy plant-based product option.

Numerous studies have explored pricing and lot-sizing strategies for various payment methods, but most have focused primarily on the buyer’s perspective. This study, however, approaches these strategies from a different perspective, incorporating key and relevant factors often overlooked. The volume of sales increases when a seller accepts a buyer’s credit. However, it reduces sales volume when a seller requests a buyer make a payment in advance. To boost sales and profitability, a vendor occasionally provides a price reduction in exchange for a down payment. Demanding a down payment from a customer earns interest and carries without any risk of default. When a vendor offers customers the option to pay with credit, a higher delay payment period facility plan may boost sales volume, but it also increases the risk of default. To maximize profit per unit of time, the vendor aims to simultaneously determine the optimal selling price, replenishment schedule, and payment method. This is achieved by comparing and calculating the vendor’s profit per time unit for credit, cash, and advance payment options. This is done by comparing and calculating the seller’s profit for each piece of time for credit, cash, and advance payments. The following managerial impacts are highlighted by means of numerical analyses: (1) A particular payment type, among the three available options, yields the seller’s highest profit under certain conditions. (2) It is vitally crucial for a vendor to provide a price reduction if an advance payment is required. (3) Advance payment results in higher profit than delayed payment if sales volume does not significantly fall while switching from credit to advance payments, or vice versa. To solve the optimization problem, a popular metaheuristic algorithm (viz., Grey Wolf Optimizer) is used and finally performed a post optimality analysis for making a fruitful conclusion.

During sprouting, significant chemical transformations frequently transpire, leading to variations in the concentrations of diverse bioactive compounds present in the seeds. Consequently, seeds and sprouts may have altered bioactivity. The current study aimed to evaluate the in vitro antioxidant activities of crude hydroalcoholic (70 % ethanol and 30 % distilled water) extracts of Momordica charantia seeds and sprouts and their antibacterial efficacies against morbific bacteria sourced from hospitalized patients. Utilizing three assays- DPPH (2,2-diphenyl-1-picrylhydrazyl), ABTS (2,2′-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid), and ferric ions reducing power), the antioxidant activities were evaluated. The results revealed that the sprout extract significantly outperformed the seed extract in terms of Fe3+ ions reducing power, DPPH radical scavenging activity (IC50 = 163.37 ± 23.91 μg/ml), and ABTS radical scavenging activity (IC50 = 30.56 ± 6.90 µg/ml). The antibacterial efficacies against five morbific bacteria (Enterobacter cloacae, Escherichia coli, Enterococcus faecalis, Pseudomonas aeruginosa, and Klebsiella oxytoca) isolated from hospitalized patients were evaluated by the agar disc diffusion method. The findings indicated that the extracts derived from both sprouts and seeds exerted potent antibacterial efficacy by suppressing the growth of several clinical isolates. Both extracts possessed statistically significant (p

Global efforts have been made to address environmental and health concerns by promoting and adopting renewable natural resources. This study investigated the role of bagasse-based wood vinegar to synthesize and stabilize silver nanoparticles. We present a simple bottom-up approach to produce silver nanoparticles using the green reducing agent. Wood vinegar has been used to create and stabilize nanoparticles as well as increase the biological activity of silver nanoparticles. In the WV-AgNPs aqueous dispersion's absorption spectra, a wide surface plasmon resonance (SPR) peak with a 395 nm wavelength center was visible. Wood vinegar has been utilized not only to synthesize and stabilize nanoparticles, but it also makes silver nanoparticles biologically more active. Prepared WV-AgNPs showed remarkable antibacterial activity against three pathogenic bacteria and satisfactory antiproliferative activity against human breast (MCF-7) cell line. The stability of the prepared nanoparticles has been confirmed by zeta potential value. The surface morphology and the particle size were investigated by scanning electron microscope and transmission electron microscope. The prepared particles are spherical in shape and particle size ranges from 20 to 40 nm. WV-AgNPs are further characterized by UV–Vis spectroscopy, X-ray diffraction (XRD), Thermogravimetric analysis (TGA), Dynamic Light Scattering (DLS), Energy-dispersive X-ray spectroscopy (EDX) and Fourier transform infrared (FTIR) spectroscopy. Based on the results, it can be concluded that silver nanoparticles mediated by wood vinegar showed promising properties and might find application in the biological domain.

Hearing loss has been identified as a risk factor for cognitive decline. The processing of auditory information relies on a well-connected neuronal network. Previous studies have found white matter abnormalities in individuals with hearing loss, but the structural connectivity and microstructural properties of white matter in individuals with moderate hearing loss remain unclear.To examine the integrity of white matter, identify vulnerable structural connectivity, and assess network topology, we examined major white matter tracts in elderly individuals with moderate hearing loss (MHL) (>30 dB) and compared them to age-matched controls with good hearing (GH).We observed that the fractional anisotropy of the right corticospinal tract and left superior longitudinal fasciculus – parietal was higher in subjects with MHL. Additionally, we identified a disrupted network centered on the left putamen in MHL, involving eight brain regions. Network topology analysis showed reduced betweenness centrality and small-world network in MHL. Interestingly, the fractional anisotropy of the forceps major tract and left uncinate tracts were correlated with hearing status.Our findings suggest that MHL is associated with putamen-centered disruptions in structural connectivity. The increased fractional anisotropy of the right corticospinal tract may be a compensatory mechanism, as it projects fibers to the right putamen. Overall, these results provide valuable insights into the impact of hearing loss on white matter integrity and may inform the development of new treatments to prevent its progression.

Marine algae have been visualized as fostering a prevalent actuation of bioactive substances that have noteworthy therapeutic effects. The current investigations deployed a trio of separate drying methods, i.e., oven drying, freeze drying, and sun drying, to quantify the total phenolic content (TPC), total flavonoid content (TFC), and dietary vitality of Ulva intestinalis and Padina tetrastromatica. By mining and scrutinizing it to the quercetin and gallic acid standards, TPC and TFC were derived. Among three drying techniques, freeze drying asserted higher TPC (12.59 ± 1.07 in U. intestinalis and 68.74 ± 1.95 mg of GA/g in P. tetrastromatica) and TFC (7.92 ± 0.97 in U. intestinalis and 58.15 ± 2.05 mg of quercetin/g in P. tetrastromatica) values. Ulva intestinalis and P. tetrastromatica also contain a high amount of protein (18.34% and 8.7%, respectively). The findings demonstrated that green seaweed possessed higher levels of potassium (2.20%) and molybdenum (2.41%) and brown seaweed showed higher amounts of potassium (2.41%) and calcium (1.11%). Where rapid drying methods are recommended to enhance constituent levels, freeze-drying could be an attractive alternative to oven and sun drying, as it addresses the drawbacks associated with prolonged drying periods.

Livestock production companies come under increasing responsibility to reduce their environmental impact, and thereby, the simultaneous decision-making of inventory replenishment and emissions reduction investment has become essential for ensuring sustainable development in the livestock farming business. This study investigates, for the first time, the best investment strategy for a livestock farming business under the carbon cap (CC) environmental legislation, taking into account both the edible and non-edible parts of slaughtering mature growing items (GIs) after procuring and feeding baby GIs. By fusing economic and environmental factors, this study aims to shed light on two crucial issues: (i) figuring out the appropriate level of investment needed for the farm to adhere to the CC environmental regulation; and (ii) evaluating the effect of the investment decision on the farm's expenses and emissions levels. To deal with these insights, a thorough analytical framework integrating mathematical modeling methodology, economic evaluation, and carbon accounting approaches is employed. By analyzing the interaction between the farm's emissions reduction investments and replenishment choices, the cost-effective investment level is determined that enables the farm to satisfy the carbon cap obligation while guaranteeing maximum operational efficiency. The results of this study have important ramifications for livestock farming businesses trying to make their way through the stringent CC emission law. The results indicate that in order to keep the business feasible when the cap of the CC guideline is low, the livestock-producing farm should give priority to investing in minimizing feed emissions and using cutting-edge manure treatment methods.

Nowadays we are extremely dependent on various synthetic plastic materials to maintain the massive demand, therefore, both the industries and mankind have been generating a massive amount of plastic waste which is so hazardous for the total environment due to their nonbiodegradable nature. To solve this problem by replacing the fossil-based plastic materials with ecofriendly biopolymers in this current study we will be described a novel method for producing Crystalline Nano Cellulose (CNC) from the waste sugarcane leaf sheaths (SLSF) fibers as a green reinforcing agent. The waste-to-wealth approach aims to elevate agricultural residues, particularly SLSF, by transforming them into high-quality CNCs for use in a variety of sectors. SLSF was initially washed with detergent to remove impurities, followed by alkali treatment and bleaching operation before CNC manufacture using acid hydrolysis (60% H2SO4). The resulting materials were characterized using Fourier transform infrared (FTIR) spectroscopy, Scanning electron microscopy (SEM), X-ray diffraction (XRD), Thermogravimetric analysis (TGA), Differential thermogravimetry (DTG), and Differential thermal analysis (DTA). FTIR indicates the newly produced CNCs is very much rich with active sites like –OH, -NH, -COOH, -C-O-C-, etc., while SEM revealed the raw fiber surface was rough, whereas the surface of CNCs became smooth even after the removal of lignin, fatty, and waxy compounds. Overall, acid hydrolysis was shown to increase the crystallinity of bleached SLSF while reducing cellulose dimensions to the nanoscale. After analysis it was revealed that most CNC particle size was around 100 nm. The outstanding properties of CNCs, including as high strength, biodegradability, and low environmental impact, make them ideal candidates for reinforcing composites, improving medicine delivery systems, and aiding new electronics. Ongoing research and technology advancements in integrating CNCs into many applications have the potential to alter industries looking for sustainable and high-performance materials.

Summary: A poor maternal diet during pregnancy predisposes the infant to severe lower respiratory tract infections (sLRIs), which, in turn, increases childhood asthma risk; however, the underlying mechanisms remain poorly understood. Here, we show that the offspring of high-fat diet (HFD)-fed mothers (HFD-reared pups) developed an sLRI following pneumovirus inoculation in early life and subsequent asthma in later life upon allergen exposure. Prior to infection, HFD-reared pups developed microbial dysbiosis and low-grade systemic inflammation (LGSI), characterized by hyperneutropoiesis in the liver and elevated inflammatory cytokine expression, most notably granulocyte-colony stimulating factor (G-CSF), interleukin-17A (IL-17A), IL-6 and soluble IL-6 receptor (sIL-6R) (indicative of IL-6 trans-signaling) in the circulation and multiple organs but most prominently the liver. Inhibition of IL-6 trans-signaling using sgp130Fc transgenic mice or via specific genetic deletion of IL-6Ra on neutrophils conferred protection against both diseases. Taken together, our findings suggest that a maternal HFD induces neonatal LGSI that predisposes to sLRI and subsequent asthma via neutrophil-mediated IL-6 trans-signaling.

Smart grid is a transformative advancement that modernized the traditional power system for effective electricity management, and involves optimized energy distribution by load forecasting. Precise load forecasting provides the best utilization of energy resources and increases sustainability. Dynamic changes of several connected factors, such as temporal and geographical variability, pose challenges to accurate load prediction. Integrating Artificial Intelligence (AI) in the smart grid can enhance the performance of the forecasting process by capturing these changes. This study investigated load forecasting tasks on four different datasets. Several preprocessing and augmentation techniques are applied to increase the data quality. An attention-based 1D-CNN-GRU model is proposed to capture the temporal patterns from the time-series data, and the hyperparameters of the model are optimized using a particle swarm optimization (PSO) algorithm that also accelerates the convergence and results in an efficient training session. Empirical evaluations highlight that the proposed model substantially minimizes the loss, reflecting the ability to make accurate predictions. It obtains MAE values of 0.12, 0.8, 16.48, and 82.64 for the four datasets. Moreover, the explainable AI (XAI) technique is applied using Shapley Additive explanations (SHAP) to interpret the model prediction, providing the feature ranking based on their prediction score. Moreover, this study utilizes federated learning, enables collaborative training, maintains the privacy of the grid data, and secures the process comprehensively. The aggregation mechanism in federated learning is modified using pruning-based methods that reduce the parameters and computational cost, resulting in a more efficient framework. Integrating all these approaches provides valuable insights for developing a load forecasting model and outlines potential contributions in the smart grid domain.

Hybrid beamforming has gained popularity in recent years due to its ability to enhance the performance of massive multiple-input multiple-output (massive MIMO) systems and improve the efficiency of wireless communication. However, designing a hybrid precoder is a challenging task as it requires accurate channel state information (CSI) and needs to solve an optimization problem. This paper introduces an unsupervised hybrid deep learning technique, namely CNN-BiLSTM, for developing hybrid beamforming in massive MIMO systems based on received signal strength indicator (RSSI) without having prior knowledge of CSI. Additionally, incremental principal component analysis (Incremental PCA) is used to reduce the dataset's dimensionality. The results of our proposed model demonstrate a significant improvement in spectral efficiency. This technique reduces the training overhead significantly and is able to quickly serve all the users. The simulation results indicate that proposed model produces low side lobes when providing coverage to areas. As a result, the performance of our model has a noticeable advantage compared to other models. In addition, proposed method achieves 99.21% accuracy and 5.30 bps/Hz sum-rate that is close to optimal performance and outperforms the state-of-the-art method.

This study experimentally investigates the effect of peening treatment on the fatigue strength of welded joints of aged steel. Fatigue tests were conducted on T-shaped fillet welded joints made from three different types of aged steel under three-point bending loading conditions. To reveal fatigue strength improvement mechanism, residual stress measurement, hardness measurement, and metallographic analysis were performed at the weld toe for both as-weld and peened specimens. Fractured surfaces were examined to identify crack initiation sites and propagation. The findings reveal that peening treatment introduces compressive residual stress on the peened surface of welded joints of aged steel equal to or higher than conventional steel welded joints. Higher improvement of hardness was observed in the near surface of the peened welded joints of aged steel, and the improvement continued up to around the zero crossing points of the residual stress distribution. Additionally, peening treatment might refine near-surface grains of aged steel welded toe similar to conventional steel. The fatigue strength improvement effect of the peening treatment was the same for aged steel as conventional one. Cracks were observed on the peened surface of the aged steel due to over-peening treatment. However, it doesn't affect the fatigue strength improvement of the welded joints of aged steel. In summary, it can be said that peening treatment can improve fatigue strength of welded joints of aged steel in the same manner of conventional steel.

Multi-functional textiles have become a growing trend among smart customers who dream of having multiple functionalities in a single product. Thus, this study aimed to develop a multi-functional textile from a common textile substrate like cotton equipped with electrically conductive, anti-bacterial, and flame-retardant properties. Herein, a bunch of compounds from various sources like petro-based poly-aniline (PANI), phosphoric acid (H3PO4), inorganic silver nanoparticles (Ag-NPs), and biomass-sourced fish scale protein (FSP) were used. The coating was prepared via in-situ polymerization of PANI with the cotton substrate, followed by the dipping in AGNPs solution, layer-by-layer deposition of FSP and sodium alginate, and finally, a dip-dry-cure technique after immersing the modified cotton substrate into the H3PO4 and citric acid solution. The key results indicated that the fabric treated with PANI/Ag-NPs/FSP/P-compound exhibited a balanced improvement in all three desired properties as the electrical resistance was reduced by 44.44 % while showing superior bacterial inhibition against gram-positive bacteria (S. aureus) and gram-negative bacteria (E. coli), and produced dense-black carbonaceous char residues, indicating its flame retardant properties as well. Thus, such amicable developments made the cotton textile substrate a multi-functional textile, which showed potential to be used in medical textiles, wearable electronics, fire-fighter suits, etc.

Over the past two decades, computer-aided detection and diagnosis have emerged as a field of research. The primary goal is to enhance the diagnostic and treatment procedures for radiologists and clinicians in medical image analysis. With the help of big data and advanced artificial intelligence (AI) technologies, such as machine learning and deep learning algorithms, the healthcare system can be made more convenient, active, efficient, and personalized. The primary goal of this literature survey was to present a thorough overview of the most important developments related to computer-aided diagnosis (CAD) systems in medical imaging. This survey is of considerable importance to researchers and professionals in both medical and computer sciences. Several reviews on the specific facets of CAD in medical imaging have been published.Nevertheless, the main emphasis of this study was to cover the complete range of capabilities of CAD systems in medical imaging. This review article introduces background concepts used in typical CAD systems in medical imaging by outlining and comparing several methods frequently employed in recent studies. This article also presents a comprehensive and well-structured survey of CAD in medicine, drawing on a meticulous selection of relevant publications. Moreover, it describes the process of handling medical images and introduces state-of-the-art AI-based CAD technologies in medical imaging, along with future directions of CAD. This study indicates that deep learning algorithms are the most effective method to diagnose and detect diseases.

Pure and Ag-doped Titanium dioxide (TiO2) thin films have been synthesized via the sol-gel spin coating method, and their structural, morphological, and optical properties have been investigated. X-ray diffraction analysis verifies that the polycrystalline anatase TiO2 phase is retained up to 2 % Ag doping. However, lattice expansion and grain refinement down to 25.345 nm are observed with increasing Ag content. Scanning electron microscopy (SEM) reveals the formation of large, isolated TiO2 aggregates separated by drying-induced cracks across the film surface. Optical studies show the undoped TiO2 films demonstrate excellent visible transparency (>75 % transmittance) that slightly decreases upon Ag doping, though it remains suitably high for device applications. Meanwhile, optical absorption and defect states improve with more Ag incorporation, narrowing the TiO2 bandgap from 3.83 eV (undoped) to 3.51 eV (2 % Ag-doping) due to the incorporation of Ag-induced electronic states just below the conduction band minimum. The capability to control optical and structural properties through Ag doping highlights the potential of these TiO2 films suitably tailored for photovoltaic devices or self-cleaning coatings.

Principal component analysis (PCA) can reduce the subjectivity of Water quality index (WQI) models by reducing parametric dimension and has gained immense attention in exploring water quality among researchers. Therefore, this study focuses on developing a novel WQI model for 4 Dhaka-based rivers namely Buriganga, Turag, Balu, and Shitalakhya following PCA as a method for selecting and weighting water quality parameters. The dataset includes 12 water quality parameters from 19 sites of these rivers sourced from the Department of Environment (DoE), Bangladesh. Correlation analysis followed by PCA, was conducted to decrease the parameter count from 12 to 7. The Measure of Sampling Adequacy (MSA) was found to be 0.853 in the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity was significant at an alpha level of 0.05 indicating the dataset was suitable for factor analysis. Sub-indexing was introduced with the quality rating curves provided by the National Sanitation Foundation (NSF)-WQI model and modified rating curves for specific parameters with statistical dispersion. The calculated WQI values for 209 samples ranged from 36 (Bad) to 82 (Good) on a scale of 100. More than 70 % of the samples were in the medium or bad, and the rest were in the good category. The trend in WQI across the rivers indicated higher values during the wet season, attributed to the dilation from local rainfall. By incorporating a well-distributed dataset spanning several years, this statistical approach effectively minimizes the subjectivity and bias in developing WQI models for rivers in Dhaka, contributing to more robust future model development. Moreover, this study introduces a modern approach for assessing the river water quality of Dhaka city that can be incorporated into the river pollution control strategies.

Water pollution is one of the major concerns due to rapid industrialization and urbanization. Wastewater treatment has been an area of great interest for the researchers and among many technologies developed for water treatment, adsorption is the most preferred due to its efficiency and ability of been economical method. In this research, eggshell powder (ESP) is converted into modified eggshell powder (MESP) through chemical and thermal treatment (at 550 °C for 2 h) to use it as an adsorbent to remediate Pb2+ and Methylene blue (MB) from water, then it is transferred into modified eggshell powder magnetic composite (MESPMC) with iron coating to resolve the separation challenges and to boost the MESP's adsorption efficiency. FTIR analysis identified the functional groups of ESP, MESP, and MESPMC. XRD analysis reveals a hexagonal crystal structure of calcite in MESP and a combination of the hexagonal crystal structure of calcite and the cubic crystal structure of iron in MESPMC. The Scherrer equation is used to determine the average crystallite sizes of MESP and MESPMC, which are 22.59 nm and 12.15 nm, respectively. The SEM image shows the irregular shape of the MESP and MESPMC particles, as well as the active coating layer in MESPMC. EDX analysis reveals that Ca (20.92 %), O (56.83 %), and Fe (41.03 %), O (48.83 %) are the most abundant elements in MESP and MESPMC respectively. TGA analysis points out that MESPMC outperforms MESP in terms of thermal stability between 600 and 750 °C. MESP and MESPMC were found to be very efficient adsorbent for lead and methylene blue in aqueous medium. At 40 mg/mL adsorbent dosage, ESP, MESP, and MESPMC had the highest yields of Pb2+ removal, with 46.996 %, 99.27 %, and 99.78 % respectively at 200 rpm for 60 min with 25 °C. Furthermore, at the 0.5 mg/mL adsorbent dosage, ESP, MESP, and MESPMC have the maximum removal efficiency of methylene blue, with 47.19 %, 90.1 %, and 92 %, respectively at 200 rpm for 30 min with 25 °C. In both cases, the removal efficiency of MESPMC is slightly higher than that of MESP and much higher than that of ESP. Additionally, the results confirm that MESP and MESPMC are potential environment-friendly bio sources to remediate heavy metal (Pb2+) and methylene blue dye from water.

The prevalence of brown carbon (BrC) in the atmosphere has experienced a notable upsurge owing to human activities of anthropogenic origin. This study aims to examine the optical characteristics of BrC in both deionized (DI) water and organic solvents (OS), alongside the identification of BrC chromophores within the ambient atmosphere of Dhaka, Bangladesh. Particulate matter (PM) samples were collected on quartz filters using a low-volume sampler from December 2021 to May 2022 at Mukarram Hussain Khundker Bhaban, University of Dhaka. The concentration of BrC was measured using soot analyzer, optical properties of BrC were determined using UV–Vis spectrometer, and BrC chromophores were identified with GC-MS. Average concentration of BrC was 19.13 ± 5.71 μgm−3. The average of absorption coefficient (babs_365), mass absorption efficiency (MAE), absorption angstrom exponent (AAE), and refractive index (kabs_365) of BrC_DI have been observed to be 38.75 ± 21.90 Mm−1, 2.16 ± 1.42 m2 g-1, 1.51 ± 0.08, 0.06 ± 0.04, respectively. The absorption coefficient and MAE of BrC_OS are 1.3 and 1.36 times, respectively higher than that of BrC_DI. Thirty chromophores of BrC have been identified, predominantly consisting of oxygenated compounds. Derivatives of Bisphenol A (C27H44O2Si2) were detected in all samples of oxygenated compounds, primarily originating from the combustion of plastic and the incineration of e-waste. Additionally, compounds containing nitrogen and sulfur, such as C14H26N2O, C31H55N, and C31H49NO3S, were identified, largely attributed to biomass combustion and traffic emissions. These chromophores play a significant role in the absorption of solar radiation, thus influencing atmospheric photochemistry.

Antimony sulfide (Sb2S3) has garnered significant attention recently due to its remarkable photovoltaic properties and low toxicity. However, the conventional physical vapor deposition approach faces challenges in achieving high-quality films due to Sb2S3 having a quasi-one-dimensional nanoribbon structure. In contrast, solution-processed Sb2S3 thin films have shown improved photovoltaic behavior, offering a low-cost and scalable fabrication method. Nonetheless, the sensitivity of the solution process to the chemical composition of the precursor poses a challenge, often requiring noble gas protection to prevent exposure to toxic solvents or moisture-sensitive chemicals. Despite this, the impact of precursor fabrication conditions on film growth behavior remains unexplored. In our study, we investigate how different processing atmospheres of precursors, namely nitrogen (N2) and air, affect grain growth and the associated optical and electronic performance of Sb2S3 thin films. Our findings reveal that the presence of oxygen in the precursor can hinder grain growth by obstructing surface integration sites, resulting in undesired (hk0) orientation and even the formation of Sb2O3 on the surface of the Sb2S3 films, despite identical post-deposition conditions. This research sheds light on how the ambient conditions during precursor preparation can influence grain engineering, thereby providing valuable insights for controlling the grain size and producing high-quality Sb2S3 absorber films.

A proposal has been made to identify tuberculosis cells using a novel compact sensor based on photonic crystal fiber: PCF in accordance with hexagonal spectroscopy. This proposed structure, which consists of a closely packed hexagonal air hole in the cladding region and a hollow-core area, possesses a very low loss of 6.30 × 10−8 dB/m and an exceptionally high sensitivity of up to 91.75 % (tuberculosis cell for 1.345). Numerous optical parameters have been identified and assessed, comprised of the numerical aperture, the V-parameter, or normalized frequency (Veff), and the effective area (Aeff). The operational wavelength range is defined as 0.80–3.0 THz. The numerical investigation of the properties of the proposed TB sensors is performed within the environment of COMSOL Multiphysics (Version 5.3) using FV-FEM stands for the full vector finite element method. PCF sensors composed of hexagonal lattice in a circular form with ZEONEX as the backdrop material is intended to boost the sensitivity response in comparison to the earlier works. Additionally, the sensor that is being displayed achieves a single modality throughout its whole operational wavelength range. This proposed sensor may play a significant role in identifying tuberculosis thanks to its superior sensitivity response and extremely minimal confinement loss. So, it is clearly seen that this sensor could be used to bio-medical sectors with process of terahertz (THz) wave pulse.

Nowadays, artificial intelligence (AI) has been utilized in several domains of the healthcare sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited due to the transparency issue, which is considered a significant obstacle. To achieve the trust of end users, it is necessary to explain the AI models' output. Therefore, explainable AI (XAI) has become apparent as a potential solution by providing transparent explanations of the AI models' output. In this review paper, the primary aim is to review articles that are mainly related to machine learning (ML) or deep learning (DL) based human disease diagnoses, and the model's decision-making process is explained by XAI techniques. To do that, two journal databases (Scopus and the IEEE Xplore Digital Library) were thoroughly searched using a few predetermined relevant keywords. The PRISMA guidelines have been followed to determine the papers for the final analysis, where studies that did not meet the requirements were eliminated. Finally, 90 Q1 journal articles are selected for in-depth analysis, covering several XAI techniques. Then, the summarization of the several findings has been presented, and appropriate responses to the proposed research questions have been outlined. In addition, several challenges related to XAI in the case of human disease diagnosis and future research directions in this sector are presented.

This study analyses environmental sustainability indicators (ESIs) and explores their governance challenges in developing countries (Bangladesh and Thailand) and advances possible remedies in light of the practices of a developed country (Japan). A comparative analysis of countries' performance based on the ESIs could help identify useful practices from countries with high ESI to improve the poor ESI countries. While it is broadly understood that renewable energy and effective governance support environmental sustainability, our findings extend this knowledge by detailing how these factors interact specifically within the contexts of developed and developing nations. The analysis delineates the complex relationship between GDP growth, fossil fuel reliance, and sustainability efforts, offering a detailed examination of the variance in ESI performance across these countries. Beyond established notions, this study empirically validates the relationships between environmental sustainability (ES) and its influencing factors, providing a country-specific analysis that emphasizes the differential impact of renewable energy adoption, governance quality, and economic policies on environmental sustainability in Japan, Bangladesh, and Thailand. The results also revealed that Bangladesh's performance in terms of majority ESIs ranges from bad to worse, while Japan exhibits good performance in all its ESI indicators except for emissions. Thailand's ESI performance indicates its vulnerability to climate disasters and slow growth of renewable energy. The ESI measures of Thailand have shown its susceptibility to climate-related calamities and a slowdown in the rate of renewable energy implementation. A noticeable discrepancy in the execution of regulatory frameworks was noted between developing countries, such as Bangladesh, and industrialized ones, such as Japan. The outstanding results of Japan's ESI may be credited to the successful practices of its citizens and their strong devotion to the rule of law.

Jute (Corchorus sp.), a commercially important and eco-friendly crop, is widely cultivated in Bangladesh, India, and China. Some varieties of this tropical plant such as the Corchorus olitorius. Variety accession no. 2015 (acc. 2015) has been found to be low-temperature tolerant. The current study was designed to explore the genome-wide variations present in the tolerant plant acc. 2015 in comparison to the sensitive farmer popular variety Corchorus olitorius var. O9897 using the whole genome resequencing technique. Among different variations, intergenic Single Nucleotide Polymorphism (SNPs) and Insertion-Deletion (InDels) were found in the highest percentage whereas approximately 3% SNPs and 2% InDels were found in exonic regions in both plants. Gene enrichment analysis indicated the presence of acc. 2015 specific SNPs in the genes encoding peroxidase, ER lumen protein retaining receptor, and hexosyltransferase involved in stress response (GO:0006950) which were not present in sensitive variety O9897. Besides, distinctive copy number variation regions (CNVRs) comprising 120 gene loci were found in acc. 2015 with a gain of function from multiple copy numbers but absent in O9897. Gene ontology analysis revealed these gene loci to possess different receptors like kinases, helicases, phosphatases, transcription factors especially Myb transcription factors, regulatory proteins containing different binding domains, annexin, laccase, acyl carrier protein, potassium transporter, and vesicular transporter proteins that are responsible for low temperature induced adaptation pathways in plants. This work of identifying genomic variations linked to cold stress tolerance traits will help to develop successful markers that will pave the way to develop genetically modified cold-resistant jute lines for year-round cultivation to meet the demand for a sustainable fiber crop economy.

Objectives: This research was conducted to explore the patterns and behavior of panic purchasing, stockpiling, and use of drugs during COVID-19 in the Sylhet city, Bangladesh. Study design: The study adopted qualitative exploratory research design. Methods: 25 in-depth interviews with drug sellers and clients and 7 key informant interviews were conducted with pharmacists and medical representatives of pharmaceutical companies in Sylhet city in Bangladesh from October 2020 to March 2021. Thematic analysis was used to evaluate the primary data. Results: The findings revealed that individuals sought out, purchased, and stockpiled prescription-only drugs for self-medication purposes during the COVID-19 pandemic. News and rumor spread by social media, television, and everyday interactions concerning the severity of infections and the number of deaths caused an increase in self-medication as a preventive measure. The reason for this panic buying of drugs was identified as a fear of drug shortages, price hikes, the rise of infection, and the availability of medicines and home delivery services during the pandemic. Conclusion: The purchasing, stockpiling and use of drugs by pharmacies varied based on the person dispensing the drugs, the customer, and the COVID-19 pandemic situation. Furthermore, the role of social media in spreading rumor and (dis) misinformation about drug use, a greater tendency to self-medicate, and poor regulation, influenced the individual’s use of drugs. Therefore, the drug regulatory authorities and policymakers need to consider the real level of local drug use in order to encourage more rational use of drugs which will help to ensure that there is reliable access to safe, effective, and high-quality medicines and vaccines for all.

Regulators’ increasingly stringent carbon rules to protect the environment are encouraging practitioners to modify their operational activities that are accountable for releasing emissions into the atmosphere. Thereby, practitioners dealing with product inventory planning are seeking proper management strategies not only to increase profits but also to reduce released carbons from operations. In addition, increasing uncertainty in supply operations has motivated suppliers to impose prepayment mechanisms in recent decades. This study examines the best prepayment installment policy for a practitioner for the first time, where the consumption behavior of consumers changes as a result of the combined effects of unit selling price and storage time. Moreover, to make the present inventory planning more realistic, the unit holding cost function is adopted as a power function of the inventory unit's storage period. The goal of this study is to provide the best combined installment for advance payment, price, and replenishment strategies for a practitioner under cap-and-price, cap-and-trade, and carbon tax environmental guidelines by ensuring maximum profit. For this purpose, an algorithm is created by combining all derived theoretical results from the analytical study, whereas the efficacy of the algorithm is assessed through the examination of five illustrative numerical instances. A plethora of noteworthy management insights for the practitioner are obtained by investigating the dynamic shifts in optimal strategies resulting from fluctuations in system parameters. The results reveal that if the demand is low in the nascent phases of the business cycle, then the prudent approach for the practitioner entails procuring a comparatively smaller lot-size using a modest number of payment frequencies and then setting a relatively small unit selling price to increase profits.

Nano-scale interactions between pure metal or metal-oxide components within an oxide matrix can improve functional performance over basic metal oxides. This study reports on the synthesis of monometallic (CuO), bimetallic (CuO–NiO) and trimetallic (CuO–NiO–ZnO) oxide nanoparticles (NPs) via the co-precipitation method and investigation of morphostructural properties. All of the synthesized metal oxide NPs were calcined at 550 °C temperature and annealed under vacuum. In this work, we applied Scherrer formula, modified Scherrer equation, Williamson-Hall plots, and Halder-Wagner plots to calculate the average crystallite size. The XRD data analysis showed that average crystallite sizes of the as-synthesized metal oxide phases were between 4 nm and 76 nm and average diameters calculated from SEM image were between 15 nm and 83 nm. The XRD studies also disclosed that average crystallite size and lattice microstrain of the CuO phases remain almost same (43 nm–46 nm and 2.074×10−3 to 2.665×10−3) for pure CuO and mixed CuO–NiO; but in case of mixed CuO–NiO–ZnO it is found to decrease in size to 11 nm where lattice microstrain increases to 9.653×10−3. Line broadening of diffraction peaks from microstrain contribution was between 0.02 and 0.01. Degree of crystallinity (%) of CuO phases found to decrease from 81 to 71. Dislocation density of CuO phases found to increase from 6.63×10−4nm−2 to 12.68×10−3nm−2. X-ray density of CuO phases increased from 6.48 to 6.53 g/cm3. Where this calculated small dislocation density well agreed with the high crystallinity. Crystal structure and specific surface area were determined from lattice constants and X-ray density. These synthesized nanopowders showed the existence of monoclinic, cubic, and hexagonal phases. The obtained NPs of multi-metal oxide explained more than one phases with different size, shape, and morphology at nano scale.

Rural transformation plays a crucial role in enhancing the income and employment prospects of the rural labor force. We investigate the effects of rural transformation on rural income inequality at the district level in Bangladesh using data from five years of nationally representative Household Income and Expenditure Surveys. The Gini coefficient is used to measure rural income inequality. In contrast, the share of high-value agricultural outputs and the share of rural non-farm employment are used as indicators of rural transformation. We find that rural income inequality is positively associated with the share of high-value agricultural outputs and the share of rural non-farm employment. The non-linear regression result shows an inverted U-shaped relationship between rural transformation and income inequality, which indicates that income inequality initially increases with rural transformation but decreases in the long run. Additionally, we find that rural income inequality is positively correlated with the proportion of household education expenditures, agricultural rental activity, and the share of remittances. This study also reveals that income inequality in rural areas of Bangladesh has a significant negative correlation with the government's social safety net program.

This study develops a hybrid model to investigate the factors affecting transnational e-commerce supply chain resilience (TNSCRE) by integrating the Entropy Weight Method (EWM), Simple Additive Weighting (SAW), and Interpretive Structural Modeling (ISM). The study identifies 36 critical factors categorized under supply chain adaptability, supply chain efficiency, and supply chain evolution, and five criteria are used to rank these factors. The EWM is used to calculate the relative weights of the criteria, and the SAW method is used to rank the factors based on their weighted scores. The ISM is then used to evaluate the interrelationships among the key factors. The research highlights the significance of several factors, such as the speed of supply chain disruption recovery, interactive collaboration, and response time to supply chain disruption. Sensitivity analysis was performed to assess the robustness of the findings. Finally, a SWOT analysis is conducted to develop a strategic action plan for addressing these significant factors. The study provides a comprehensive understanding of the factors that impact TNSCRE from the perspective of multiple stakeholders. The findings can help e-commerce business owners improve their existing supply chain resilience and achieve sustainable growth in the context of globalization.

The global environment is experiencing increasingly rapid pollution due to the presence of harmful products generated by human activities, the emissions from vehicular traffic, and the release of carbon dioxide from industrial sources. To save this beautiful earth as well as human beings, it is necessary to reduce pollution by producing eco-friendly products and reducing reckless carbon emissions from industry. Furthermore, advertising serves as a very efficacious strategy for promoting sustainable green products and encouraging customer engagement. In response to the current circumstances, a supply chain model including a manufacturer, a retailer, and customers is devised, incorporating investments in green practices and advertising. This study examines the relationship between client demand and three key factors: marketing effort, the product's green level, and the selling price. In addition, a sharing contract policy between the manufacturer and the retailer on green investment costs is applied in this model. The main focus of this study is to find the optimal values of advertisement effort, the product's green level, the manufacturer's wholesale price, the retailer's selling price and the sharing percentage of green investment that maximize the profits of the retailer and manufacturer, as well as the integrated supply chain system of the proposed model. In order to demonstrate the practical significance of the concept, a numerical example is solved and then a comparative analysis is conducted. Moreover, sensitivity studies are performed to assess the impact of different model parameters on decision factors and profitability. In conclusion, this study provides management insights and offers some closing observations, along with suggestions for future research directions. The findings indicate that the implementation of a sharing contract policy yields more earnings to the participants in the supply chain compared to a decentralized situation. The centralized strategy in supply chain management (SCM) results in higher joint earnings for the manufacturer and the retailer compared to the decentralized and sharing contract policies.

Mycoplasma genitalium is a pathogenic microorganism linked to a variety of severe health conditions including ovarian cancer, prostate cancer, HIV transmission, and sexually transmitted diseases. A more effective approach to address the challenges posed by this pathogen, given its high antibiotic resistance rates, could be the development of a peptide vaccine. In this study, we used experimentally validated 13 membrane proteins and their immunogenicity to identify suitable vaccine candidates. Thus, based on immunogenic properties and high conservation among other Mycoplasma genitalium sub-strains, the P110 surface protein is considered for further investigation. Later on, we identified T-cell epitopes and B-cell epitopes from the P110 protein to construct a multiepitope-based vaccine. As a result, the ‘NIAPISFSFTPFTAA’ T-cell epitope and ‘KVKYESSGSNNISFDS’ B-cell epitope have shown 99.53% and 87.50% population coverage along with 100% conservancy among the subspecies, and both epitopes were found to be non-allergenic. Furthermore, focusing on molecular docking analysis showed the lowest binding energy for MHC-I (−137.5 kcal/mol) and MHC-II (−183.3 kcal/mol), leading to a satisfactory binding strength between the T-cell epitopes and the MHC molecules. However, the constructed multiepitope vaccine (MEV) consisting of 54 amino acids demonstrates favorable characteristics for a vaccine candidate, including a theoretical pI of 4.25 with a scaled solubility of 0.812 and high antigenicity probabilities. Additionally, structural analyses reveal that the MEV displays substantial alpha helices and extended strands, vital for its immunogenicity. Molecular docking with the human Toll-like receptors TLR1/2 heterodimer shows strong binding affinity, reinforcing its potential to elicit an immune response. Our immune simulation analysis demonstrates immune memory development and robust immunity, while codon adaptation suggests optimal expression in E. coli using the pET-28a(+) vector. These findings collectively highlight the MEV's potential as a valuable vaccine candidate against M. genitalium.

Perishable products in Europe, the United States, and Canada typically have expiration dates or maximum lifetimes assigned to them. As these products approach their predetermined lifetimes , there is a gradual increase in the rate of decay, leading to a reduction in their freshness. To examine the impact of these two distinct attributes on a perishable product with a predetermined expiration date, we introduce two inventory models that utilize a demand function incorporating a linearly decreasing price dependence and a nonlinear increase that is influenced by advertising. These models consist of: (i) a zero-ending stock scenario and (ii) a partially backlogged shortage situation. Under certain conditions, the optimal cycle length for the stock zero-ending model and the optimal period with positive inventory for the model with shortages are obtained. The frequency of advertisement is a discrete and integer decision variable, we devise two algorithms for both models to determine the optimal frequency of advertisement that maximizes the profit. Finally, we suggest some strategies in order to increase the profit by studying marginal insights from a sensitivity analysis. It is recommended that the manager focuses on creating more impactful advertisements that are affordable to promote the product’s information through popular media channels.

Irritable Bowel Syndrome (IBS) is a common disorder affecting around 20% of the populations worldwide. Treatment of IBS typically focuses on managing predominant symptoms and the pathophysiology, such as the visceral hypersensitivity. This study was conducted to assess community pharmacist knowledge, attitude and practice of Irritable Bowel Syndrome in Khartoum locality.A descriptive cross-sectional study was done. The study was performed among all community pharmacist working at the pharmacies in the study area. Ethical approval from the Ministry of health was first granted (NUSU2021/3-5), then approvals was obtained from each of pharmacy administration. Pharmacists that were registered by Sudan medical counsel, while pharmacy technician and other staff were excluded. Association among variables was assessed through chi-square test, all tests were considered significant when p

The Bogoyavlenskii and the simplified modified Camassa-Holm (SMCH) models are studied through the recent technique namely auxiliary equation method in this paper. The Bogoyavlenskii model is more significant in shallow water wave, solitary wave and one dimension lattices. And the SMCH model is explained the Riemann waves along two spatial dimensions, periodic solitary and cross-solitary wave, and more. The novelty of this article is to examine the sufficient, adequate broad-ranging, and further general soliton solutions of the models by utilizing the auxiliary equation approach processing complex wave transformation which are not exist in the recent literature. The finding of this study demonstrates that the examined solutions exhibit that the employed technique is compatible, functional, straightforward and more effective. The accuracy of the acquired solutions is confirmed by reintroducing them into the original models and also the wave structures of the solutions are explained by depicting figures by means of the Wolfram Mathematica program.

Uncertainty refers to a lack of precise knowledge or information about a particular event, situation, or outcome. It is an inherent characteristic of many real-world phenomena and is often associated with the presence of risk or ambiguity. Uncertainty can arise due to various factors, such as incomplete information, unpredictability, complexity, or variability of a system or process. In many cases, uncertainty can lead to difficulties in decision-making and pose challenges in planning, forecasting, and managing risks. There are different types of uncertainty, including epistemic uncertainty, which arises from the inherent randomness or variability of a system or process. This study encompasses the inclusion of all inventory parameters as uncertainty parameters, which are expressed in the form of intervals. Furthermore, demand for the product is taken into account in interval form. The conversion of the differential equation into an interval differential equation is carried out in order to account for the variability in demand within a certain interval. The utilisation of the centre-radius technique leads to the derivation of the related optimisation problem under a ‘buy now, pay later’ (BNPL) payment scheme. In order to demonstrate the concept, a numerical case is selected and solved with the MATHEMATICA software and interval order relations. In the end, a comprehensive sensitivity analysis has been conducted to derive insightful conclusions pertaining to this study.

316L steel employed in biomedical applications has experienced mechanical failure triggered by insufficient biological reactions, a high corrosion rate, and surface impurities. Furthermore, the attenuated surface induced by corrosion and wear releases toxic elements, causing inflammatory effects. The prime aim of this research is to evaluate the carbon nanotube (CNT) based coating for enhancing surface integrity, corrosion resistance, and biological responses. This research also aims to comprehend the relationship between electric discharge machining (EDM) process variables and material properties. Several characterisation techniques, including scanning electron microscope (SEM), field emission scanning electron microscope (FESEM), atomic force microscope (AFM), electron dispersive X-ray (EDX), MTT assays, powder X-ray diffraction (XRD) and potentiodynamic polarisation are utilised. The addition of CNT forms a nanoporous and thin coating of 10.3 μm, resulting in a crack-free surface with an adhesion strength of 23.77 MPa. A low corrosion rate (0.0012 mm/year) and almost 85 % of alive cells are observed on the coated surface of 316L steel. This research shows a method to form carbide and oxide-based coating for biomedical applications.

PCF denotes photonic crystal fiber which is utilized for terahertz (THz) waveguides and cladding in the shape of a hexagon with two elliptical air apertures (AHs), which are discussed. Such differentiation is made: When the frequency is 1 THz, effective material loss (EML) to a minimum of 0.028 cm−1 has been achieved. Making use of the heptagonal photonic crystal fiber (He-PCF) architecture, every simulation result utilizing COMSOL Multiphysics software implements the perfectly match layer (PML) and finite element method (FEM) boundary conditions. The He-PCF fiber demonstrates an effective mode loss (EML) of 0.028 cm−1 that is negligible, a substantial effective area (EA) measuring 7.31 × 10−8 m2 and an 80 % power concentration encompassing the central area at 1 THz frequency. Furthermore, regarding crucial optical guiding aspects like confinement loss, dispersion, and modality, a small study with respect to power fraction along with effective mode area (EMA) has again been conducted. Here, He-PCF THz waveguide is anticipated to provide a notable improvement in the current design for the communication field. Moreover, our suggested the PCF demonstrates perception by a solitary mode, as indicated through the utilization of the V-parameter, across a range in frequency spanning among 0.80 and 3 THz. Thus, it is anticipated that the layout of He-PCF fibers will facilitate efficient transmission of terahertz (THz) signals in a variety of communication applications.

Given the advances in technology, Fintech is an invaluable tool which allows unbanked people to access financial services when social, cultural, economic and technological factors affect their user intentions (UI). Despite the great importance of the role of social and facilitating influences in the adoption of Fintech services, little research has been conducted on how and what influences affect Fintech user intention (FUI) and whether there is a gender gap in FUI. Therefore, this study aims to help formulate effective Fintech policies and close the gender gap by investigating the role of social and facilitating influences and sociodemographic variables in FUI. The study sample comprised 237 participants, and the data were collected through interviews with the use of a structured questionnaire in Chattogram, Bangladesh. The collected data were analysed employing exploratory factor analysis and an ordered logistic regression model. The study also examined the Fintech gender gap by applying the Blinder Oaxaca decomposition model. The results reveal that image, compatibility and the experiences of Fintech use are the positive and significant predictors of FUI, with the perceived social norm for adopting Fintech being non-informative for users. There is a significant interaction between user compatibility and experience of use in relation to Fintech. Interestingly, perceived behavioural control negatively influenced females to adopt Fintech. Furthermore, the study found a gender gap in FUI. The findings have managerial implications.

Breast cancer is a common disease that employs chemotherapeutic drugs as a treatment approach. However, these drugs have several adverse effects, prompting the development of new drugs. Hence, this study aimed to synthesize a series of hybrid heterocyclic bis-chalcone compounds using the Claisen-Schmidt reaction and evaluate their cytotoxicity in breast cancer Michigan Cancer Foundation-7 (MCF-7) cells. The selected compounds were then evaluated for molecular docking; molecular dynamics (MD) simulations; and absorption, distribution, metabolism, and excretion (ADME), pharmacokinetic, and drug-likeness property analyses. Among the synthesized heterocyclic bis-chalcone compounds, compounds 1d and 2d induced strong antiproliferative effects against MCF-7 cells with half-maximal inhibitory concentrations (IC50) of 32.51 ± 4.02 µM and 22.69 ± 6.95 µM, respectively. Molecular docking analysis showed that compound 2d had good binding affinity (-8.40 kcal/mol) when docked with the estrogen receptor alpha (ERα) receptor compared to compound 1d, which had a binding affinity of −8.10 kcal/mol. MD simulations revealed that these compounds were consistently stable throughout the 100 ns, with additional hydrogen-bond interactions. Moreover, the compounds satisfied the predicted ADME, pharmacokinetic, and drug-likeness requirements. This study demonstrated that compound 2d is a potent heterocyclic bis-chalcone compound with the potential to be used as an anti-breast cancer agent.