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Next-generation consumer electronics and electric vehicle (EV) energy charging technology promise transformative advancements in the automotive industry. One of the main challenges that hinders consumers’ experience is range anxiety particularly relevant in locales where the installation of fixed charging stations (FCSs) is beset by logistical hurdles, notably in rural regions. With the advancement of consumer electronics especially in the design of Mobile Charging Stations (MCSs), EV drivers can now access these MCSs to exchange energy. However, concerns regarding data security and the best strategies to select an MCS to trade energy may negatively impact consumer experiences. This paper delves into the conception of intelligent remedies by proposing the integration of reinforcement learning and blockchain technology to empower EV drivers to access and securely exchange energy with MCSs. We design a Proof of MCSs (PoMCS) as a consensus protocol to select the winning MCSs as block miners in the blockchain. The results of our experiment show that the average gain for the MCSs increases when using the proposed model and therefore inclined to serve more EVs.

The study investigates the relationship between drought and vegetation variations in three main basins of western and southwestern of Iran, using the comprehensive approach of time-series analysis, Standardized Precipitation Index (SPI), and anomaly calculation. A total of 30 ground stations’ daily meteorological data and the MODIS 16-day composite NDVI products (2000–2017) were used in this case. The results showed that in the Great Karoun River (GKRW) and Karkheh River (KRW) sub-regions, the NDVI decreased slightly over the study period. Simultaneously, in the West Marginal (WMW) sub-region the NDVI slightly increased somewhat. Overall, the NDVI in the whole study area presented an insignificant decrease. Also the results found that there is a significant relationship (p< 0.02) between the NDVI (0.3–0.7) with spring drought and between NDVI (0.2–0.3) with fall drought (p< 0.01). There is a marginally significant relationship (R= 0.43, p= 0.07) between NDVI (0.3–0.4) with fall drought and a relatively high, but insignificant relationship between NDVI (0.7–0.8) with spring drought (R= 0.41, p= 0.09). Low temperature can play an important role in determining the relationship between SPI and NDVI, which evidenced that it can trade-off the effect of a very wet year. As well as a year with very wet condition can affect the NDVI of the coming years. Since summer is hot season in the study area and most of the vegetation consists of shrubs and grasslands, of which the NDVI ranges between 0.2 and 0.4, the vegetation cover can be significantly affected by a wet summer with abundant precipitation.

In this paper, we explore the problem of Weakly-supervised Temporal Action Localization (W-TAL), where the task is to localize the temporal boundaries of all action instances in an untrimmed video with only video-level supervision. The existing W-TAL methods achieve a good action localization performance by separating the discriminative action and background frames. However, there is still a large performance gap between the weakly and fully supervised methods. The main reason comes from that there are plenty of ambiguous action and background frames in addition to the discriminative action and background frames. Due to the lack of temporal annotations in W-TAL, the ambiguous background frames may be localized as foreground and the ambiguous action frames may be suppressed as background, which result in false positives and false negatives, respectively. In this paper, we introduce a novel collaborative Foreground, Background, and Action Modeling Network (FBA-Net) to suppress the background (i.e., both the discriminative and ambiguous background) frames, and localize the actual-action-related (i.e., both the discriminative and ambiguous action) frames as foreground, for the precise temporal action localization. We design our FBA-Net with three branches: the foreground modeling (FM) branch, the background modeling (BM) branch, and the class-specific action and background modeling (CM) branch. The CM branch learns to highlight the video frames related to $C$ action classes, and separate the action-related frames of $C$ action classes from the $(C+1)$ th background class. The collaboration between FM and CM regularizes the consistency between the FM and the $C$ action classes of CM, which reduces the false negative rate by localizing different actual-action-related (i.e., both the discriminative and ambiguous action) frames in a video as foreground. On the other hand, the collaboration between BM and CM regularizes the consistency between the BM and the $(C+1)$ th background class of CM, which reduces the false positive rate by suppressing both the discriminative and ambiguous background frames. Furthermore, the collaboration between FM and BM enforces more effective foreground-background separation. To evaluate the effectiveness of our FBA-Net, we perform extensive experiments on two challenging datasets, THUMOS14 and ActivityNet1.3. The experiments show that our FBA-Net attains superior results.

Reconstructing and predicting 3D human walking poses in unconstrained measurement environments have the potential to use for health monitoring systems for people with movement disabilities by assessing progression after treatments and providing information for assistive device controls. The latest pose estimation algorithms utilize motion capture systems, which capture data from IMU sensors and third-person view cameras. However, third-person views are not always possible for outpatients alone. Thus, we propose the wearable motion capture problem of reconstructing and predicting 3D human poses from the wearable IMU sensors and wearable cameras, which aids clinicians' diagnoses on patients out of clinics. To solve this problem, we introduce a novel Attention-Oriented Recurrent Neural Network (AttRNet) that contains a sensor-wise attention-oriented recurrent encoder, a reconstruction module, and a dynamic temporal attention-oriented recurrent decoder, to reconstruct the 3D human pose over time and predict the 3D human poses at the following time steps. To evaluate our approach, we collected a new WearableMotionCapture dataset using wearable IMUs and wearable video cameras, along with the musculoskeletal joint angle ground truth. The proposed AttRNet shows high accuracy on the new lower-limb WearableMotionCapture dataset, and it also outperforms the state-of-the-art methods on two public full-body pose datasets: DIP-IMU and TotalCaputre.

Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050.

Future action anticipation aims to infer future actions from the observation of a small set of past video frames. In this paper, we propose a novel Jointly-learnt Action Anticipation Network (J-AAN) via Self-Knowledge Distillation (Self-KD) and cycle consistency for future action anticipation. In contrast to the current state-of-the-art methods which anticipate the future actions either directly or recursively, our proposed J-AAN anticipates the future actions jointly in both direct and recursive ways. However, when dealing with future action anticipation, one important challenge to address is the future’s uncertainty since multiple action sequences may come from or be followed by the same action. Training an action anticipation model with one-hot-encoded hard labels that assign zero probabilities to incorrect yet semantically similar actions may not handle the uncertain future. To address this challenge, we design a Self-KD mechanism to train our J-AAN, where the J-AAN gradually distills its own knowledge during the training to soften the hard labels to model the uncertainty on future action anticipation. Furthermore, we design a forward and backward action anticipation framework with our proposed J-AAN based on a cyclic consistency constraint. The forward J-AAN anticipates the future actions from the observed past actions, and the backward J-AAN verifies the anticipation of the forward J-AAN by anticipating the past actions from the anticipated future actions. The proposed method outperforms all the latest state-of-the-art action anticipation methods on the Breakfast, 50Salads, and EPIC-Kitchens-55 datasets. This project will be publicly available on https://github.com/MoniruzzamanMd/J-AAN.

•Identify suitable site for livestock production is a paramount importance.•Locating best site for livestock production by using AHP based geospatial technique.•Final suitability map has been divided into 4 classes: low, medium, high, excellent.

Nanoparticle based permeation enhancers have the potential to improve the oral delivery of biologics. Recently, solid silica nanoparticles were discovered to improve the intestinal permeability of peptides and proteins viatransient opening of the gut epithelium. In this study, we have developed small-sized (∼60 nm) virus-like silica nanoparticles (VSNP) as a reversible and next generation non-toxic permeation enhancer for oral delivery of biologics. Our results show that the anionic VSNP showed a better permeation-enhancing effect than the same sized spherical Stöber silica nanoparticles (∼60 nm) by enhancing the apparent insulin permeability by 1.3-fold in the Caco-2 monolayer model and by 1.2-fold in the Caco-2/MTX-HT-29 co-culture model. In vivoexperiments in healthy mice demonstrated that anionic VSNP significantly enhanced the permeation of fluorescently labelled 4 kDa dextran after oral administration compared to Stöber nanoparticles and positively charged VSNP. The results indicated that the nanoscale surface roughness is an important consideration when designing nanoparticle-based permeation enhancers. Overall, our study shows for the first time that small-sized (∼60 nm) VSNP with nanoscale surface roughness can be used as a non-toxic permeation enhancer for oral delivery of therapeutic peptides and proteins.

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Over the past five years, significant strides have been made in the realm of supercapacitor materials, revolutionizing energy storage technologies. Supercapacitors have garnered widespread acclaim for their rapid energy transfer capabilities, enabling swift charge and discharge cycles within seconds. A pivotal focus has been the refinement of electrode materials to optimize capacitance and overall performance, driving innovation in the field. The latest advancements in supercapacitor electrode materials have underscored the importance of cyclic stability and extended lifespan, key factors in enhancing device reliability. Researchers have delved into a myriad of materials, including conductive polymers, metal oxides, carbon-derived nanomaterials, and their nanocomposites, leveraging their unique properties to push the boundaries of supercapacitor performance. This review uniquely integrates the exploration of cutting-edge materials such as covalent organic structures, metal-organic frameworks, MXenes, black phosphorus, and metal nitrides, highlighting their novel contributions to energy storage efficiency. Furthermore, the paper distinguishes itself by examining the integration of these materials into hybrid devices and advanced supercapacitor configurations, which has paved the way for transformative applications in various fields. Recent breakthroughs have seen the development of electrochromic supercapacitors, self-healing supercapacitors, thermally chargeable supercapacitors, micro-supercapacitors, and other cutting-edge devices, showcasing the dynamic evolution of supercapacitor technology. Additionally, significant efforts have been directed towards optimizing electrolytes to support high power and energy densities, further enhancing device performance and reliability. This review provides a comprehensive and unique overview of the latest research progress, materials, and advancements in supercapacitor electrode technology over the past five years. By elucidating current trends and future prospects, it offers valuable insights into the ongoing evolution of energy storage solutions and their potential impact on various industries. This distinctive focus on innovative materials and advanced device configurations sets this review apart from other publications in the field, offering a fresh perspective on the future of supercapacitor technology.

Zinc batteries offer distinct advantages owing to their notable safety profile, cost-effectiveness, and environmental friendliness. The zinc anode, in particular, stands out as a promising material for aqueous zinc batteries due to its array of benefits, including its lower potential, favorable cost, higher specific capacity, increased potential for hydrogen release, non-reactive properties, natural abundance, and ease of processing. However, the uncontrolled growth of zinc dendrites, electrolyte-induced damage, significant volume changes, and unstable interfaces have thus far impeded their commercial viability, posing obstacles to their further advancement. Recent efforts have focused on addressing these challenges through the utilization of structures derived from metals and their derivatives, resulting in significant progress regarding zinc anode issues. Strategies such as stabilization through metal-organic frameworks (MOFs) and their derivatives, solid-state electrolyte development, anode decoration, separator enhancement, and interface engineering have shown promise in stabilizing zinc anodes. The incorporation of these advancements could greatly benefit large-scale energy storage systems, capitalizing on zinc batteries' exceptional safety, high capacity, affordability, and sustainability. Moreover, the unique properties of MOFs, including their ability to facilitate zinc ion transportation, large specific surface area, and highly porous topology, have garnered increased attention for their application in zinc ion batteries. This review aims to comprehensively explore the structural components of zinc batteries based on previous research contributions, encompassing pure metal structures, metal oxides, porous carbon materials, and their compounds. In particular, the review delves into the utilization of MOFs-based materials as interfaces for solid electrolytes, separators, three-dimensional zinc architectures, and solid-state electrolytes to enhance the cyclic stability of zinc anodes. Additionally, it examines the role of conductive MOFs across various categories of zinc-based batteries, highlighting their functionality, efficacy, and existing challenges. Finally, the review offers insights into the potential future advancements in this field, outlining the prospects for further harnessing the capabilities of conductive MOFs.

Bangladesh is an agriculture-dependent country and very often this sector struggles a lot due to various natural hazards including drought and flood. Almost every year in kharif crop season, Bangladesh undergoes through drought which causes a lot of yield loss. So, this has become important to identify the drought-prone areas to reduce the risk of crops yield loss and for policymaking to suggest alternative drought-tolerant crops. The agricultural drought is related to soil properties because of having spatially dynamic in nature. In the present study, agricultural drought has been assessed comprising meteorological drought of kharif season and water holding capacity (WHC) in Geographic Information System (GIS) platform, as GIS is a widely used as a powerful tool to manage and model the spatial data. The metrological drought map has prepared by rainfall data with the calculation of Standardized Precipitation Index (SPI) using GIS and WHC of soil map has converted from soil texture map. Finally, the agricultural drought map has been derived by overlying metrological drought map and WHC of soil map. The study has found that the north-west and south-west region along with Barisal division of Bangladesh are more prone to agricultural drought area than the other parts. Some districts of the middle part of the country (Dhaka, Manikganj and Faridpur: 492 km2) also suffered in extreme agricultural drought during kharif season.

•A rectangular slot with inner circular ring patch and partial ground plane based broadband monopole patch antenna, with a microwave brain imaging system focused on nine antennas has been mentioned to identify an undesirable tumor in the brain.•The emanating part of an antenna is adjusted to increase the electrical length by chopping the slot from both the patch and the ground plane. At starting frequency of 1.9 GHz, the designed antenna has an electrical range of 0.253λ × 0.190λ × 0.010λ.•The antenna's FBW (% BW) estimated is 67.67%. The estimated max gains and efficiency respectively 5.2 dBi and >90%. The antenna includes a better response with respect to the group-delay (GD) and fidelity-factor (FF, 96.26%) for the time domain evaluation.•During the entire research, experimental and numerical results are reviewed, which show that the antenna proposed is ideal for imaging applications.•To evaluate the functionality of the one antenna and the array antenna, a 3D-realistic Hugo-head model is equipped with either a single antenna or a 9-antenna array setup and reviewed EM-field along with tumor-bearing and tumor-free head.

The high-power density enables rapid charging of energy storage devices. As technology advances, this is increasingly becoming a crucial method to evaluate these systems. Ionic hybrid capacitors are designed to provide more strength and higher energy storage capacity compared to electric double-layer capacitors. By fusing the best features of ionic batteries with electric double-layer capacitors, ionic hybrid capacitors expect to outperform both in terms of energy density as well as power density. Substituting lithium-ion capacitors with sodium-ion capacitors offers cost and material savings, among other advantages. The metal oxide electrodes possess a greater potential specific capacity compared to carbon-based electrodes due to their robust redox reaction. Therefore, they exhibit excellent compatibility with solid-state batteries, commonly referred to as sodium-ion capacitors. In the case of electric double-layer capacitors, the power output gap is reduced due to the high surface pseudocapacitance properties of metal oxide electrodes, which facilitate rapid ion movement. Metal oxides resolved the incompatibility between sodium-ion capacitor electrodes and electric double-layer capacitor counter electrodes. These issues were compounded by the reported drawbacks of metal oxides, such as poor electrical conductivity and significant expansion. To produce high-performance silicon carbides, it is crucial to adhere to appropriate modification techniques and electrode compatibility criteria. This item provides a concise summary of the study conducted on solid-state capacitor electrodes composed of various metal oxides, including the materials utilized. Additionally, there is a comprehensive discussion of the storage mechanism and construction of sodium-ion capacitors. Ultimately, this study provides an extensive understanding and more insights into enhancing the concert of metal oxide electrodes as well as exploring their potential applications, hence promoting further investigation in this field.

Objective We aimed to describe clinical and laboratory characteristics and determine the predictors of outcome in patients with cerebral venous sinus thrombosis.Methods This prospective study was conducted over 2 years among hospitalized patients with cerebral venous sinus thrombosis. Patient outcome was assessed using the Modified Rankin Scale (mRS) score at 3 months. Outcome predictors were identified using logistic regression analysis.Results Eighty-one patients were included in this study. The median mRS outcome at 3 months was 1 (interquartile range 1–3). Poor outcomes were observed in 27.2% of patients, and the mortality rate was 9.8%. Factors associated with poor outcomes were age >60 years (relative risk [RR] 5.1), hemiparesis (RR 5.4), altered level of consciousness (RR 7.1), and transverse sinus involvement (RR 1.1). In general, mRS scores were not associated with D-dimer levels (RR 2.4). However, older patients with elevated D-dimer levels showed a significant association with poor outcomes (1.6) according to mRS scores.Conclusion Older age, hemiparesis, and altered consciousness levels were independent predictors of poor outcomes in patients with cerebral venous sinus thrombosis. High D-dimer level showed no association with functional disability, except in older patients.

Rainfall-induced landslide hazards have become a common phenomenon in the Rangamati Sadar area of the south-eastern folded part of Bangladesh. The area has experienced several landslides in 2017, which caused loss of life and enormous loss of the asset. The present study aims to map landslide vulnerability in the Rangamati Sadar area and the surroundings. The weighted overlay approach such as the knowledge-based empirical technique is commonly used for landslide vulnerability mapping. The susceptibility map has been derived using various parameters—geology, land use, DEM, slope, aspect, soil texture, and structure/lineament data taken from an open-source geospatial platform. Mapping procedural justification and authentication are confirmed based on past landslide locations and field visits. The landslide susceptibility map is categorized into very low (236.4 km2), low (196.8 km2), moderate (1076.2 km2), high (1613.8 km2), and very high (2615.7 km2) susceptible areas. The end map of the research area is validated using an image overlay on google earth-2021 and the area under the curve value of 52 landslides events. The weighted overlay approach has displayed an important presentation that the area under curve (AUC) value is 0.875. Statistical analysis has identified the most recent devastating landslides due to climate change along with other anthropogenic causes such as hill cutting, soil texture, and deforestation. The research outcome would help the stakeholders and policymakers reduce and mitigate the risks related to landslide hazards in the associated areas.

Upregulation of certain enzymes, such as collagenase, tyrosinase, and elastase, is triggered by several extrinsic environmental factors, such as temperature, UV radiation, humidity, and stress, and leads to elasticity loss and skin pigmentation. Herein, dual-emissive polyaromatic carbon quantum dots (CQDs) with abundant phenolic moieties, that is green and yellow CQDs (G-CQDs and Y-CQDs, respectively), were prepared using a three-fold symmetric molecule, 1,3,5-trihydroxybenzene. The significant inhibition efficacy of the fabricated CQDs against collagenase, elastase, and tyrosinase, which play important roles in skin aging, revealed their excellent antiaging potential. Y-CQDs with large polyphenolic–polyaromatic domains and abundant –OH groups exhibited high enzyme inhibitory efficacy against skin aging, and their collagenase, elastase, and tyrosinase inhibitory efficacies were ∼75 ± 4.2%, ∼52 ± 3.1%, and ∼35.3 ± 4.2%, respectively, at a concentration of 100 μg mL−1. The most critical factor that delays wound healing is oxidative stress, which is caused by the overproduction of free radicals around inflamed tissue. CQDs were effective in suppressing UV-induced reactive oxygen species at the cellular level and improved the cell viability. Subsequently, CQD-incorporated dual-emissive biocompatible gelatin–methacryloyl hydrogels were constructed as wound dressing materials to promote wound healing viainducing the proliferation of fibroblasts, enhancing cell migration and alleviating inflammation and to provide antiaging benefits. Our results demonstrated that the fabricated CQDs with remarkable optical features, low cytotoxicity, and excellent antioxidant and antiaging properties can be used as bio-imaging probes, antiaging agents, and wound dressing materials for oxidative stress-related diseases in the nanomedicine and cosmetics industries.

Delineating a flood map is critical to perceive the potential risks of the event at diverse communities living both in urban and rural settings in Bangladesh. A timely generated flood map can help determine the losses of properties, calculate payment options from insurances, and set up mitigation measures when required. Application of satellite remote sensing (RS) and geographic information systems (GIS) are common these days to determine inundated areas, and to calculate possible losses of economies at scale. However, challenges remain while considering the available options for collecting satellite imageries obtained during the monsoon season with more than 70% cloud coverages found in the data. As a result, active synthetic aperture radar (SAR) sensors are a better choice to utilize the data in delineating the inundated areas. In doing so, this scientific paper sets up a few objectives to (1) prepare a flood map of Bangladesh using SAR remote-sensing data available from Sentinel-1 satellite; and (2) generate the inundated maps using cloud-based product, i.e., Google Earth Engine (GEE) in categorizing flood-affected districts of Bangladesh in 2020. Results have demonstrated that approximately 11% area of Bangladesh has been affected by the 2020 flood mainly located in the north-central and north-eastern part of the country. Moreover, the old Brahmaputra floodplain, Tista floodplain, lower Ganges-River floodplain, and Karataya-Bangali floodplain have been severely affected by the flood. Note that, the GEE-based automated processing systems adopted in this study have enhanced the computational time while obtaining freely available satellite data to generate mitigation strategies for the betterment of the communities suffered by the flood event.

Long-term dynamic tracking of cells with theranostic properties remains challenging due to the difficulty in preparing and delivering drugs by probes. Herein, we developed highly fluorescent one- and two-photon (OP and TP) excitable polyphenolic carbon quantum dots (CQDs) for excellent membrane-targeting and drug delivery properties for synergistic tumor therapy. The green-emissive CQDs (g-CQDs) were synthesized from a three-fold symmetric polyphenolic molecule, phloroglucinol (C3h; symmetry elements: E, C3, C32, σh, S3, and S3−1), in a sulfuric acid medium. Doxorubicin (Dox) was loaded onto the g-CQDs viaelectrostatic interaction, resulting in a loading efficiency and content of 54.62% and 323.25 μg mL−1, respectively. The g-CQDs@Dox complex exhibited a higher rate of cell killing efficiency at both pH 5.0 and 6.5, with higher reactive oxygen species (ROS) generation due to the greater Dox accumulation in the tumor cells. In addition, TP cell imaging displayed excellent membrane-targeting properties with less photobleaching ability in tumor cells. The in vivostudies confirmed that the g-CQDs@Dox complex has higher affinity towards tumor cells, better inhibitory effects, and an absence of systemic toxicity. Therefore, our developed nanocarrier exhibited better cell imaging, drug delivery, and tumor-targeting properties, and could be used as a “smart” probe for synergistic tumor therapy.

•The resonator is comprised of a square ring and double E shape resonator.•The resonator is constructed with tungsten and Quartz (Fused) as the substrate.•The absorption peaks of 99.8%, 99.9%, 99.92% and 99.92% is obtained.•The proposed structure shows polarization insensitivity in both TE and TM mode.•Large bandwidth, and low PCR, MTM absorber can be used as solar energy harvester.

Education develops human skills, raises human productivity and, consequently, enables them with higher monetary incentives and better jobs. But the realisation of benefits may differ across income groups due to various limiting factors to achieve it. This article estimates the impacts of education on income and consumption of rural households in Bangladesh, using mean differential approach and unconditional quantile regression approach. It utilises Bangladesh Integrated Household Survey (BIHS) data for the years 2012 and 2015 to estimate the impact of education on the income and consumption of rural households. To address the potential endogeneity problem in impact estimation, ‘total distance from school’ is used as an instrumental variable (IV) in the case of the fixed-effect regression model applied here. Though education affects mean differentials of income and consumption positively, the fixed-effect regression coefficients are surprisingly insignificant. However, quantile regression results suggest that education contributes to income and consumption of lower quantile households more than that of uppermost quantile households. Consequently, these indicate a decline in inequality in rural areas of Bangladesh. Interestingly, education has diminishing positive returns for lower quantiles, implying a declined inequality with an increase in education, but at a diminishing rate, confirming that the impact is non-linear in nature.

Research in the field of electrode materials for supercapacitors and batteries has significantly increased due to the rising demand for efficient energy storage solutions to facilitate the transition towards renewable energy sources. This enhances the effectiveness, cost-effectiveness, and safety of energy storage devices, ultimately encouraging the widespread adoption of clean energy technology. The advancements in electrode materials for batteries and supercapacitors hold the potential to revolutionize the energy storage industry by enabling enhanced efficiency, prolonged durability, accelerated charging and discharging rates, and increased power capabilities. These advancements can address the limitations of current electrode materials, such as limited storage capacities and insufficient durability during repeated cycling in conducting polymers. Scientists are working hard to overcome the restrictions and fully utilize the capabilities of energy storage devices by exploring other materials, such as activated carbon compounds and carbon materials with added impurities. Doping and surface modification enhance the pseudocapacitance, pore size, structure, conductivity, and several other properties of carbonaceous materials. Active carbons are most appropriate to be used as carbonaceous electrodes because they are easily available, low-cost, chemically inert, and highly conducting. Functionalization of nanoparticles is one of the attractive approaches for enhancing the performance of electrode materials that consists of modifying its characteristics on the surface and also improving its conductivity. The efficacy of both rechargeable batteries and supercapacitors in storing electrochemical energy is highly contingent on the properties of the electrode materials. Researchers are investigating combining carbon composites with nanomaterials, such as metal oxides and polymers, to create hybrid electrode materials that have complementary characteristics. This article provides valuable insights into the ever-changing landscape of carbon electrode materials and energy storage.

The major goal of this research is to adopt analytical hierarchy process (AHP) based geospatial technique to select suitable zone for the solar photovoltaic (PV) power plants. Nine thematic layers altogether—slope, global horizontal irradiation (GHI), relative humidity, direct normal irradiation (DNI), elevation, distance from major roads, distance from protected areas, rainfall, and land use/land cover (LULC)—are combined through overlay analysis in ArcGIS to create the final map of suitability for the placement of solar photovoltaic (PV) power plants in Bangladesh. This map has been classified into five categories namely, restricted zone, less suitable zone, moderate suitable zone, good suitable zone, and excellent suitable zone. These categories are covered by 7.28%, 16.61%, 28.51%, 27.77%, 21.83% land of total area in Bangladesh respectively. The findings of this research have been presented that ‘the excellent suitable’ and ‘good suitable’ areas for the construction of solar power plants are in the western and northwestern part (Rajshahi, Pabna, Sirajganj, Natore, Naogaon, Chapainawabganj, Bogura, Faridpur, Jessore, Jehenaidha, Magura, Kushtia, Choudanga, Meherpur) of the study area which contain a high value of global horizontal irradiation, direct normal irradiation, elevation and low value of slope, rainfall, temperature, relative humidity. Besides the restricted and less suitable zone for installing solar photovoltaic (PV) power plants indicates a high value of rainfall, slope, temperature, relative humidity and low value of global horizontal irradiation, direct normal irradiation, and elevation. Bangladesh's currently operational solar plants were taken into consideration for this study's validation purposes. The proposed framework may potentially be used in different locales on a national and worldwide scale. This study offers a consistent GIS process for the accurate, inexpensive implementation of a solar energy plan to achieve environmentally friendly goals.

Resveratrol (RES) is a nutraceutical with promising anti-inflammatory properties for the treatment of inflammatory bowel diseases (IBD). However, the clinical effectiveness of resveratrol as an oral anti-inflammatory agent is hindered by its extremely poor solubility and poor stability. In this study, we encapsulated resveratrol in β-lactoglobulin (BLG) nanospheres and systematically analyzed their formulation parameters in vitrofollowed by a thorough in vivoanti-inflammatory testing in a highly specialized spontaneous murine UC model (Winnie mice model). Complexation of resveratrol with BLG increased the aqueous solubility of resveratrol by ≈1.7 times with 10% w/w loading. Additionally, the in vitrodissolution of resveratrol from the particles was found to be higher compared to resveratrol alone, resulting in >90% resveratrol dissolution in ∼8 h. The anti-inflammatory activity of resveratrol was examined for the first time in Winnie mice, a mouse model that closely represents the clinical signs of IBD. At a 50 mg/kg oral dose for 2 weeks, BLG-RES significantly improved both % body weight and disease activity index (DAI), compared to free resveratrol in Winnie mice. Importantly, histological evaluations revealed a similar trend with striking improvement in the pathology of the colon via an increase in goblet cell numbers and recovery of colonic epithelium. BLG-RES significantly increased the expression level of cytokine interleukin-10 (Il10), which confirms the reduction in inflammation potentially because of the increased dissolution and stability of resveratrol by complexation with BLG. This comprehensive study demonstrates the effectiveness of biocompatible nanomaterials such as BLG in oral delivery of poorly soluble anti-inflammatory molecules such as resveratrol in the treatment of IBD.

Interleukin (IL)-22 is a multifunctional cytokine with a very short half-life that activates STAT3 and can elicit strong anti-inflammatory effects in the intestine but can induce inflammation in other sites. Several long-circulating IL-22 fusion proteins have been manufactured to date; however, those were associated with adverse effects in other organs limiting their utility for treating intestinal inflammation. Targeted delivery of IL-22 to the intestine could utilize its anti-inflammatory properties and overcome systemic toxicity. Therefore, this study aimed to synthesise large pore mesoporous silica nanoparticles (LPMSN), load recombinant (r)IL-22 in the LPMSN and test its bioactivity in the STAT3 reporter LS174T, wild type LS174T, Caco-2 intestinal epithelial cells, and healthy human colonic organoids. Our data showed one hundred percent loading capacity (w/w) of the synthesised LPMSN, which prolonged IL-22 induced STAT3 luciferase activities in LS174T and p-STAT3 immunofluorescence in Caco-2 cells. LPMSN also stabilized and increased the permeability of rIL-22 across Caco-2 monolayers. Moreover, LPMSN-IL-22 retained the functionality of the cytokine in human colonic organoids. Taken together, these data demonstrate the protection and effective delivery of IL-22 using bio-nanomaterials (LPMSN) that could enable targeted oral delivery of this IL-22.

To examine the rain-fed Aman rice yield fluctuation due to climatic anomalies overtimes in Bangladesh, we used climate-induced yield index (CIYI), ensemble empirical mode decomposition (EEMD), step-wise multiple regression, isotopic signature, wavelet transform coherence (WTC) and random forest (RF) model. In this work, daily multiple source climatic data which were collected between 1980 and 2017, from 18 weather stations and five atmospheric circulation indices were used for this purpose. The key findings were as follows; by employing principal component analysis (PCA), six temporal variability modes were identified as six corresponding sub-regions with various Aman rice CIYI fluctuations. The Aman rice CIYI in different sub-regions represented a noteworthy 3–4-year quasi-oscillation using the EEMD. The key climate variables (KCVs) including the potential evapotranspiration and cloud cover in September, the minimum temperature in August, and precipitation in July, August, and October were the best rice yield prediction signals in these sub-regions. The results suggest that Aman rice yield could likely decline by 33.59%, and 3.37% in the southwestern and southeastern regions, respectively, if KCV increased by 1 °C or 1%. The RF model suggests that the Indian Ocean Dipole (IOD) significantly influenced the rice yield. Isotopic signatures were employed to confirm the fluctuation and anti-amount effect during the Aman rice-growing period in Bangladesh. The results obtained in this study could be used as a guideline for sustainable mitigation and adaptation measures in managing agro-meteorological hazards in Bangladesh.

The study contributes towards modelling and estimating an endogenous growth model of an economy burgeoning with young working population and declining agricultural land. The model explores the long-run impact of physical capital stock, human capital augmented labour and production index augmented agricultural land on Gross Domestic Product of Bangladesh. Theoretically and empirically the model indicates that per capita income will be rising as long as the growth and share of human capital and the growth of agricultural productivity outweigh the dragging effect of the growth of declining agricultural land and the population growth. Vector error correction model (VECM), autoregressive distributive lag (ARDL) and dynamic ordinary least square (DOLS) techniques are employed to observe the robustness of the results. The underlying production relations exhibit constant returns to scale. DOLS estimates are found more robust and significant as compared to the results in ARDL. Agricultural productivity and human capital are found as very crucial determinants of growth. Government should give more focus on creating human capital through higher spending on education and take necessary measures to increase the utilization rate of scarce agricultural land. Formulation of land zoning policy and land reclamation policy may be instrumental for effective use and protection of declining agricultural land and adverse environmental impacts.

The quest for efficient energy storage solutions has ignited substantial interest in the development of advanced emerging materials with superior energy storage capabilities. Ceramic materials, renowned for their exceptional mechanical, thermal, and chemical stability, as well as their improved dielectric and electrical properties, have emerged as frontrunners in energy storage applications. Their potential to provide high energy densities, enhance capacitance, and extend cycle lifetimes has garnered attention. Incorporating nanotechnology into ceramic composites further boosts their performance by customizing their properties at the nanoscale. This concise overview delves into the burgeoning field of ceramic-ceramic nanocomposite materials for energy storage applications. It outlines synthesis methods, key properties such as dielectric and electrochemical properties, and potential applications of these materials for the advancement of more efficient, durable, and environmentally friendly energy storage devices, including batteries and capacitors. For instance, the NGC/MnO2-2 h fiber electrode-based Supercapacitor exhibited a remarkable specific capacitance of 367.7 F cm−3at 0.5 A cm−3current density, alongside the highest power density of 1066.1 mWh cm−3and energy density of 5.9 mWh cm−3achieved at current densities of 0.5 A cm−3and 3 A cm−3, respectively. Similarly, LiO2-containing cells demonstrated an impressive energy density of 320 Wh kg−1, a capacity of 2.46 Ah, and an 80 % capacity retention after 300 cycles. Recent advancements in the field of ceramic/ceramic materials at the nanoscale along with identified flaws in the field of energy storage are explored.

Lactoferricin B (LfcinB) and shorter versions of this peptide have antimicrobial activity. However, the elementary processes of interactions of these peptides with lipid membranes and bacteria are still not well understood. To elucidate the mechanism of their antimicrobial activity, we investigated the interactions of LfcinB (4–9) (its sequence of RRWQWR) with Escherichia colicells and giant unilamellar vesicles (GUVs). LfcinB (4–9) and lissamine rhodamine B red-labeled LfcinB (4–9) (Rh-LfcinB (4–9)) did not induce an influx of a membrane-impermeant fluorescent probe, SYTOX green, from the outside of E. colicells into their cytoplasm, indicating that no damage occurred in their plasma membrane. To examine the activity of LfcinB (4–9) to enter E. colicytoplasm, we investigated the interaction of Rh-LfcinB (4–9) with single cells of E. colicontaining calcein using confocal microscopy. We found that Rh-LfcinB (4–9) entered the cytoplasm without leakage of calcein. Next, we investigated the interactions of Rh-LfcinB (4–9) with single GUVs of dioleoylphosphatidylglycerol (DOPG) and dioleoylphosphatidylcholine (DOPC) mixtures containing a fluorescent probe, Alexa Fluor 647 hydrazide (AF647), using the single GUV method. The results indicate that Rh-LfcinB (4–9) outside the GUV translocated through the GUV membrane and entered its lumen without leakage of AF647. Interaction of Rh-LfcinB (4–9) with DNA increased its fluorescence intensity greatly. Therefore, we can conclude that Rh-LfcinB (4–9) can translocate across lipid membrane regions of the plasma membrane of E. colicells to enter their cytoplasm without leakage of calcein and its antimicrobial activity is not due to damage of their plasma membranes.

Supercapacitors, also known as electrochemical capacitors, have gained significant prominence in past few years due to their high energy and power density compared to traditional capacitors and batteries. Electrolyte materials have a significant impact on the performance and longevity of supercapacitors. This review article provides an overview of the recent advancements in electrolyte materials for supercapacitor applications, including ionic liquids, solid-state electrolytes, and gel electrolytes. The properties, such as conductivity, stability, and electrochemical window, are discussed in detail, along with their impact on the performance of supercapacitors. The article also highlights the challenges and future directions in the development of advanced electrolyte materials for supercapacitors. The aim of this review is to provide a comprehensive understanding of the electrolyte materials for supercapacitor applications and their potential for various energy storage applications.

MXenes are rapidly emerging as a class of two-dimensional (2D) materials with a wide range of applications in energy storage. MXenes are 2D layered structures, making them the most sought-after material among the 2D family. MXenes are regarded as one of the best electrode materials due to exceptional characteristics, including flexibility, high conductivity, and tunable surface functional groups for advanced energy storage technologies. The demand for high-capacity energy storage devices that are durable, versatile, and cost-effective has grown in tandem with the advancement of technology. MXenes and their composites have significantly improved the performance of energy storage devices. Researchers are continuously exploring new ways to improve MXene's unique properties further. This review article summarizes recent developments in MXene-based electrochemical energy storage devices powered by supercapacitors, which are robust, flexible, and highly efficient. The article also focuses on MXene's structure, synthesis strategies, and how various factors such as electrode architecture design and electrolyte composition affect the charge storage mechanism and electrochemical efficiency of MXene-based supercapacitors.

Major histocompatibility complex (MHC) II is dynamically expressed on mucosal epithelial cells and is induced in response to inflammation and parasitic infections, upon exposure to microbiota, and is increased in chronic inflammatory diseases. However, the regulation of epithelial cell–specific MHC II during homeostasis is yet to be explored. We discovered a novel role for IL-22 in suppressing epithelial cell MHC II partially via the regulation of endoplasmic reticulum (ER) stress, using animals lacking the interleukin-22-receptor (IL-22RA1), primary human and murine intestinal and respiratory organoids, and murine models of respiratory virus infection or with intestinal epithelial cell defects. IL-22 directly downregulated interferon-γ–induced MHC II on primary epithelial cells by modulating the expression of MHC II antigen A α (H2-Aα) and Class II transactivator (Ciita), a master regulator of MHC II gene expression. IL-22RA1-knockouts have significantly higher MHC II expression on mucosal epithelial cells. Thus, while IL-22–based therapeutics improve pathology in chronic disease, their use may increase susceptibility to viral infections.

Lassa virus (LASV) is responsible for an acute viral hemorrhagic fever known as Lassa fever. Sequence analyses of LASV proteome identified the most immunogenic protein that led to predict both T-cell and B-cell epitopes and further target and binding site depiction could allow novel drug findings for drug discovery field against this virus. To induce both humoral and cell-mediated immunity peptide sequence SSNLYKGVY, conserved region 41–49 amino acids were found as the most potential B-cell and T-cell epitopes, respectively. The peptide sequence might intermingle with 17 HLA-I and 16 HLA-II molecules, also cover 49.15–96.82% population coverage within the common people of different countries where Lassa virus is endemic. To ensure the binding affinity to both HLA-I and HLA-II molecules were employed in docking simulation with suggested epitope sequence. Further the predicted 3D structure of the most immunogenic protein was analyzed to reveal out the binding site for the drug design against Lassa Virus. Herein, sequence analyses of proteome identified the most immunogenic protein that led to predict both T-cell and B-cell epitopes and further target and binding site depiction could allow novel drug findings for drug discovery field against this virus.

A total of 21 water samples were collected from surface water (ponds and river) and groundwater samples from shallow tube well (STW) and deep tube well (DTW) from Gopalganj Sadar Upazila to evaluate the salinity hazard and suitability for irrigation purposes. Both surface and groundwater of the study area maintained the trend of Cl−> SO42−> PO43−. The cation trend in both surface and groundwater of the study area was Na+> K+> Ca2+> Mg2+> Fe. Correlation matrices and principal component analysis (PCA) confirmed the stress of salinity from elevated electrical conductivity and total dissolved solids (TDS) with Na+, K+, Cl−and total hardness (TH) in relation to Ca2+, Mg2+, PO43−and SO42−. Salinity hazard classification and Wilcox diagram for irrigation water classification demonstrate that shallow tube wells containing low alkali and low sodium hazard are an excellent source of irrigation waters and fall under good to fair class of water (55 % samples). Higher TH, sodium adsorption ratio (SAR), soluble sodium percentage (SSP) and other important analysis indicated that most of the surface water and DTW were not suitable for irrigation. Therefore, the best irrigation water quality was from STW. Nevertheless, to sustainably and efficiently utilize the existing water resources, cyclic conjunctive uses of river water, STW and DTW as well as excavation of pond to store rainwater were suggested.