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Abstract In this work, CsPb.625Zn.375IBr2-based perovskite solar cells (PSCs) are numerically simulated and optimized under ideal lighting conditions using the SCAPS-1D simulator. We investigate how various hole transport layers (HTL) including Zn3P2, PTAA, MoS2, MoO3, MEH-PPV, GaAs, CuAlO2, Cu2Te, ZnTe, MoTe2, CMTS, CNTS, CZTS, CZTSe and electron transport layers (ETL) such as CdS, SnS2, ZnSe, PC60BM interact with the devices’ functionality. Following HTL material optimization, a maximum power conversion efficiency (PCE) of 16.59% was observed for the FTO/SnS2/CsPb.625Zn.375IBr2/MoS2/Au structure, with MoS2 proving to be a more economical option. The remainder of the investigation is done following the HTL optimization. We study how the performance of the PSC is affected by varying the materials of the ETL and to improve the PCE of the device, we finally optimized the thickness, charge carrier densities, and defect densities of the absorber, ETL, and HTL. In the end, the optimized arrangement produced a VOC of 0.583 V, a JSC of 43.95 mA/cm2, an FF of 82.17%, and a PCE of 21.05% for the FTO/ZnSe/CsPb.625Zn.375IBr2/MoS2/Au structure. We also examine the effects of temperature, shunt resistance, series resistance, generation rate, recombination rate, current-voltage (JV) curve, and quantum efficiency (QE) properties to learn more about the performance of the optimized device. At 300 K, the optimized device provides the highest thermal stability. Our research shows the promise of CsPb.625Zn.375IBr2-based PSCs and offers insightful information for further development and improvement.

Abstract Jute endophyte Staphylococcus hominis strain MBL_AB63 was reported to produce a novel antimicrobial peptide, ‘homicorcin’. This exhibits potential activity against a broad spectrum of Gram-positive bacteria. Eight genes were predicted to be involved in the sequential maturation of this peptide antibiotic, which includes structural (homA), dehydratase (homB), cyclase (homC), peptidase (homP), immunity (homI), oxidoreductase (homO), ATP-binding cassette transporter (homT1), and permease (homT2), respectively. Among the modification enzymes, HomB, HomC, and HomP exhibit sequence similarities with class I lantibiotic dehydratase, cyclase, and leader peptidase, respectively. The current study investigated the sequential modifications and secretion of homicorcin by constructing robust computational protein models and analyzing their interaction patterns using protein-protein docking techniques. To enhance comprehension of the protein arrangement, their subcellular localization was also extrapolated. The findings demonstrate a network of proteins that works in a synchronized manner, where HomC functions as an intermediary between HomB and the transporter (HomT). Following its dehydration by HomB and cyclization by HomC, the pro-homicorcin is taken out of the cell by the transporter and processed by HomP, resulting in the production of matured, processed homicorcin. This biosynthesis model for homicorcin will lay the groundwork for the sustainable and efficient production of this peptide antibiotic.

Abstract Background Anaemia is a significant public health concern in Bangladesh, yet data on the prevalence of anaemia in pregnancy and the contribution of iron deficiency are limited. Given the reliance on groundwater for drinking, a better understanding of the role of drinking water iron in anaemia aetiology is also required to inform anaemia prevention strategies. Methods This cross-sectional study enrolled 1500 pregnant women from Narayanganj district, Bangladesh, during their second or third trimester. Anaemia and iron status were described and their relationship with drinking water iron assessed using regression analyses. Results The prevalence of anaemia was 38% (95% confidence interval, CI: 35%, 40%), with 10% (95% CI: 9%, 12%) experiencing moderate-to-severe anaemia. Iron deficiency affected 48% (95% CI: 45%, 50%) of participants. Although drinking water iron concentrations were generally low (median: 0 mg/L; interquartile range: 0–1), high concentrations (≥ 2 mg/L) were associated with increased ferritin levels but did not significantly impact iron deficiency (95% CI: 0·73, 1·02) or anaemia (95% CI: 0·79, 1·17) prevalence. Iron deficient women had a 1·86 (95% CI: 1·61, 2·15) adjusted prevalence ratio for anaemia and a 4·22 (95% CI: 2·89, 6·17) adjusted prevalence ratio for moderate-to-severe anaemia, compared to iron replete women. Conclusions Anaemia and iron deficiency are highly prevalent among pregnant women in Narayanganj. These findings challenge the assumption of low iron deficiency prevalence throughout Bangladesh and highlight iron deficiency in pregnancy as a potentially underrecognized public health problem, particularly in regions with low drinking water iron. Further research is needed to clarify the contribution of drinking water iron to iron deficiency and anaemia in Bangladesh. Trial registration The study is registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12621000982819, registered 26/07/2021)

Biochar can be a good soil amendment to reduce the soil pH, increase crop growth rate, and improve the efficient use of fertilizer. Other than that, silicon fertilizer also would promote photosynthetic ability on plant development that would help to produce high yield. In this work, a series of experiments was conducted to observe the effect of rice husk biochar and silicon fertilizer on the maize growth rate and soil pH. A 45-day pot experiment in the greenhouse with three replicates of 9 experimental treatment combinations of RHB at two rates (5 and 2.5 t.ha-1) with silicon fertilizer at three rates (125%, 100%, 75%), sole biochar (10 t.ha-1), sole silicon fertilizer (100%) and control (NPK) to observe the best rate and combination to improve growth rate and change in soil chemical in acid soil. The result showed that the co-application of sole biochar and biochar with Silicon significantly improved growth development, increased photosynthesis rate, altered soil pH, and reduced Fe concentration compared to control. The plant height increased 88.35% from T4 (5 t.ha-1 RHB + 100% Si) compared to the control and the conductance was higher in T4 (0.53) followed by T8 (0.438) while T1 (0.071) recorded the lowest conductance. The shoot fresh weight was higher in T4 (127.83 g) followed by T8 (57.14 g). However, the weight increased by 343.7% at T4 followed by T8 (2.5 t.ha-1 RHB + 75% Si) at 98.33%. The highest pH increment of 1.24 units (T1 = 5.53, T4 = 6.77) of soil pH was noted from T4 (5 t.ha-1 RHB + 100% Si) compared to control (NPK), and the highest total Fe in soil was observed from T1 (442.30 mg.kg-1). The current study results showed that T4 (50% RHB + 100% Silicon) was the best treatment over the other rates of RHB and silicon increased plant height, photosynthetic rate, and biomass.

Abstract This research investigates the Circle of Willis, a critical vascular structure vital for cerebral blood supply. A modified novel dual‐pathway multi‐scale hierarchical upsampling network (HUNet) is presented, tailored explicitly for accurate segmentation of Circle of Willis anatomical components from medical imaging data. Evaluating both the multi‐label magnetic resonance angiography region of interest and the multi‐label magnetic resonance angiography whole brain‐case datasets, HUNet consistently outperforms the convolutional U‐net model, demonstrating superior capabilities and achieving higher accuracy across various classes. Additionally, the HUNet model achieves an exceptional dice similarity coefficient of 98.61 and 97.95, along with intersection over union scores of 73.32 and 85.76 in both the multi‐label magnetic resonance angiography region of interest and the multi‐label magnetic resonance angiography whole brain‐case datasets, respectively. These metrics highlight HUNet's exceptional performance in achieving precise and accurate segmentation of anatomical structures within the Circle of Willis, underscoring its robustness in medical image segmentation tasks. Visual representations substantiate HUNet's efficacy in delineating Circle of Willis structures, offering comprehensive insights into its superior performance.

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.

Flexible piezoelectric devices have garnered a lot of attention for their potential as energy harvesters and transducers. In this work, Neodymium (Nd) doped Zinc Oxide (ZnO) based flexible piezoelectric energy harvester and sensory device has been developed. Nd-doped ZnO has been synthesized using wet chemical co-precipitation and incorporated in Polyvinylidene Difluoride (PVDF) polymer matrix along with Multiwalled Carbon Nanotubes (MWCNT) to produce flexible piezoelectric films. The piezoelectric output of the device is tested at variable tapping frequency (60 to 240 BPM) and pressure (10 to 40 psi). The device has also been tested with conventional electronics like bridge rectifiers, capacitors, resistors, LEDs to show its potential as an energy harvester. Compared to other modified ZnO-PVDF based unpoled piezoelectric energy harvesters, this device has shown the most open-circuit output voltage of 75.8 V and short circuit current of 28.8 µA. It has shown an optimum power density of 12.55 μwcm-2 at 1 MΩ load impedance. Energy harvesting capacity has been further tested by placing the device between the shoe soles during running and jogging. This study endorses the potential of Nd-ZnO/PVDF/MWCNT based piezoelectric energy harvester as the most efficient Piezoelectric Nanogenerator (PENG) which shows superior power generation along with self-powered sensory applications.

Modeling and simulating laser heating phenomena are crucial for optimizing manufacturing processes and ensuring high-quality final products. A major challenge in semiconductor manufacturing is achieving accurate, real-time temperature control during wafer heating. To reduce the computational burden of complex mathematical models, low-dimensional reduced models can be employed. In this paper, we develop a mathematical model for laser heating in silicon wafers. For model reduction, we use the balanced truncation method, considering both frequency-unrestricted and restricted cases. Additionally, the rational Krylov subspace method is applied to solve high-dimensional sparse matrix equations. To gain key physical insights, we use the COMSOL Multiphysics package. Finally, some numerical experiments are conducted using MATLAB to validate the proposed approach.

In engineering and applied sciences, several physical phenomena can be more precisely characterized by employing nonlinear fractional partial differential equations. The primary goal of this research is to examine the traveling wave solution in closed form for the nonlinear acoustic wave propagation model known as the time fractional simplified modified Camassa–Holm equation, which is used to explain the unidirectional propagation of shallow-water waves with non-hydrostatic pressure and explains the dispersion properties of numerous phenomena like fluid flow, control theory, liquid drop patterning in plasma, acoustics, fusion, and fission processes, etc. The utmost potential approach, namely the new auxiliary equation technique, is applied for analyzing the time nonlinear fractional simplified modified Camassa-Holm equation in the logic of the newest established truncated M-fractional derivative. The fractional partial differential equations have been transformed to the ordinary differential equation using the complex wave transformation in the sense of truncated M-fractional derivative. A variety of soliton solutions, including anti-kink, single soliton, anti-bell, bell, kink, multiple soliton, double soliton, singular-kink, compacton shape, periodic shape, and so many, are displayed in the diagram of 3D and contour plots by taking into account a number of various parameters. It is essential to point out that all derived outcomes are directly compared to the original solutions to certify their exactness. Results show that the used scheme is capable, simple, and straightforward and can be useful to a variety of complex phenomena. The acquired results are unique for the model equation and could be applied to the analysis of several nonlinear study fields.

This research delves into the obstacles and difficulties associated with predicting cryptocurrency movements in the volatile global financial market. This study develops and evaluates an advanced Deep Learning-Enhanced Temporal Fusion Transformer (ADE-TFT) model to estimate Bitcoin values more accurately. This research employs cutting-edge artificial intelligence (AI) and machine learning (ML) techniques to comprehensively examine various aspects of cryptocurrency forecasting, including geopolitical implications, market sentiment analysis, and pattern detection in transactional datasets. The study demonstrates that the ADE-TFT model outperforms its lower-layer counterparts in terms of forecasting accuracy, with reduced Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and Root Mean Square Error (RMSE) values, particularly when using a higher hidden layer configuration (h=8). The study emphasizes the importance of experimenting with different normalization strategies and utilizing various market-related data to enhance the model's performance. The results suggest that improving forecasting accuracy may require addressing these limitations and incorporating additional factors, such as market sentiment. By providing investors with more precise market predictions, the techniques and information presented in this research have the potential to significantly increase investor power in an unpredictable digital currency market, enabling wise investment choices.

A systematic investigation of the electrical characteristics of β-Ga2O3 Schottky barrier diodes (SBDs) has been conducted under high-dose 60Co gamma radiation, with total cumulative doses reaching up to 5 Mrad (Si). Initial exposure of the diodes to 1 Mrad resulted in a significant decrease in on-current and an increase in on-resistance compared to the pre-radiation condition, likely due to the generation of radiation-induced deep-level acceptor traps. However, upon exposure to higher gamma radiation doses of 3 and 5 Mrad, a partial recovery of the device performance occurred, attributed to a radiation annealing effect. Capacitance–voltage (C–V) measurements showed a decrease in net carrier concentration in the β-Ga2O3 drift layer, from ∼3.20 × 1016 to ∼3.05 × 1016 cm−3, after 5 Mrad irradiation. Temperature-dependent I–V characteristics showed that 5 Mrad irradiation leads to a reduction in both forward and reverse currents across all investigated temperatures ranging from 25 to 250 °C, accompanied by slight increases in on-resistance, ideality factors, and Schottky barrier heights. Additionally, a slight increase in reverse breakdown voltage was observed post-radiation. Overall, β-Ga2O3 SBDs exhibit high resilience to gamma irradiation, with performance degradation mitigated by radiation-induced self-recovery, highlighting its potential for radiation-hardened electronic applications in extreme environment. [ABSTRACT FROM AUTHOR]

Abstract In recent years, the proliferation of Massive Open Online Courses (MOOC) platforms on a global scale has been remarkable. Learners can now meet their learning demands with the help of MOOC. However, learners might not understand the course material well if they have access to a lot of information due to their inadequate expertise and cognitive ability. Personalized Recommender Systems (RSs), a cutting-edge technology, can assist in addressing this issue. It greatly increases resource acquisition through personalized availability for various people of all ages. Intelligent learning methods, such as machine learning and Reinforcement Learning (RL) can be used in RS challenges. However, machine learning needs supervised data and classical RL is not suitable for multi-task recommendations in online learning platforms. To address these challenges, the proposed framework integrates a Deep Reinforcement Learning (DRL) and multi-agent approach. This adaptive system personalizes the learning experience by considering key factors such as learner sentiments, learning style, preferences, competency, and adaptive difficulty levels. We formulate the interactive RS problem using a DRL-based Actor-Critic model named DRR, treating recommendations as a sequential decision-making process. The DRR enables the system to provide top-N course recommendations and personalized learning paths, enriching the student's experience. Extensive experiments on a MOOC dataset such as the 100 K Coursera course review validate the proposed DRR model, demonstrating its superiority over baseline models in major evaluation metrics for long-term recommendations. The outcomes of this research contribute to the field of e-learning technology, guiding the design and implementation of course RSs, to facilitate personalized and relevant recommendations for online learning students.

Nonlinear fractional partial differential equations can explain a vast scope of engineering and science, like atomic physics, wireless transmission, nonlinear optics, acoustics, economics, materials science, control theory, plasma physics, quantum plasma in mechanics, biological systems of nonlinear case and so on. In this study, the new generalized (G′/G)-expansion technique have been studied for examine the nonlinear fractional equations and built exact analytical traveling as well as solitary wave solutions namely space–time one-dimensional fractional wave equation used to simulate wave transmission in a nonlinear medium with blending and space–time fractional regularized long wave equation enables bore expansion and wave generating in nonlinear model of solitary waves, ion acoustic plasma waves, shallow waves in water, and nonlinear dispersive waves with the help of conformable derivatives. The creatable equations are transformed into ordinary differential equations by fractional complex transformation. Some dynamical wave shapes of multiple solitons, single soliton, periodic anti-kink, anti-kink, flat-kink type solitary wave models have been created, and 3D, and contour have been built to represent these solutions. The results are expressed using hyperbolic, rational functions, and trigonometric and Maple or Mathematica utilized to graphically represent the obtained solutions. It is essential to point out that all resultant solutions are directly compared to the original solutions to ensure their exactness. The new generalized (G′/G)-expansion method is an operative, compatible, and fruitful approach for analyzing nonlinear fractional traveling waves.

The space–time fractional Landau-Ginzburg-Higgs equation and coupled Boussinesq-Burger equation describe the behavior of nonlinear waves in the tropical and mid-latitude troposphere, exhibiting weak scattering, extended connections, arising from the interactions between equatorial and mid-latitude Rossby waves, fluid flow in dynamic systems, and depicting wave propagation in shallow water. The improved Bernoulli sub-equation function method has been used to achieve new and wide-ranging closed-form solitary wave solutions to the mentioned nonlinear fractional partial differential equations through beta-derivative. A wave transformation is applied to renovate the fractional-order equation into an ordinary differential equation. Some standard wave shapes of multiple soliton type, single soliton, kink shape, double soliton shape type, triple soliton shape, anti-kink shape, and other types of solitons have been established. The more updated software Python is used to display the solutions by using 3D and contour plotlines to describe the physical significances of attained solutions more clearly. The findings of this study are straightforward, adaptable, and quicker to simulate. It has been notable that the improved Bernoulli sub-equation function method is practical, effective, and offers more sophisticated solutions that can help to generate a large number of wave solutions for various models.

Bézier Generative Adversarial Networks (BézierGANs) is one of the most widely used Convolutional Neural Network (CNN) technique-based algorithms for generating smooth curves to analyze and optimize complex shapes and flow patterns, particularly aerodynamics. Airfoils, the basic cross-sectional shape to design air wings, are generated here by selecting the vital parameters wisely after alternating the typical BézierGANs algorithm instead of relying on pre-existing models. When these predicted airfoils are used to develop the physical structure of the adjacent air layer to observe the phenomena, they become the subject of computationally expensive simulations of turbulent airflow. Simulations of turbulent airflow that are computationally expensive are required when these anticipated airfoils are utilized to create the physical structure of the adjacent air layer to monitor the physical events. To prevail over this computational burden, the Model Order Reduction (MOR) technique is applied to develop the best-fitted lower-order model of the original turbulent air layer model around the airfoils by filtering the most effective system's singular values while preserving all the essential characteristics of the original large-scale model. As evidence of the effectiveness of the Reduced Order Model (ROM) of the turbulent air layer regarding the truncation of the design time and computational costs, the comparative analysis of the computational time is occupied by the original and prescribed system to ensure about 99.7660% of less time consumption by the ROM. The regeneration of the reduced-order physical model is also covered in this paper, which analyzes the physical behaviors regarding the air pressure and the velocity patterns of the airflow around the airfoils and compares the similarities to the physical characteristics of the Full Order Model (FOM). It was found that the ROM can be one of the best alternatives to FOM in real-life implementation.

The study investigated the feasibility of enzymatic extraction for guava juice and evaluated the effects of various preservatives on its shelf life. The crushed guava puree was undergone different pectinase enzyme concentrations over three incubation periods. The findings revealed that pectinase concentrations of 0.1 % and 0.2 %, when incubated for 1 and 2 h, were the most effective. Juice yields ranged from 65.24 % to 78.64 %, with Total Soluble Solids (TSS) varying from 9.12°Brix to 11.56°Brix. The physicochemical properties of the guava juice resulted 84.2 % moisture, 2.16 % protein, 0.77 % fat, 3.27 % fiber, 0.65 % acidity, 2.25 % reducing sugars, 8.27 % non-reducing sugars, 79.53 % antioxidant activity, 173.2 mg/100g of ascorbic acid, 10.52 TSS, 109.7 mg/100g of phenolic content, and a pH of 3.2. Eight juice samples were prepared as per formulation with sodium benzoate and potassium metabisulfite (KMS) at concentrations of 150 ppm, 200 ppm, and 250 ppm, in addition to one refrigerated sample and one control. The stability of these guava juice samples was monitored every 15 days over a 90-day period. Results showed that acidity, TSS, pH, reducing sugars, and non-reducing sugars changed over time. Samples with preservatives exhibited slower changes compared to the control. Phenolic compounds diminished more quickly at ambient temperature than in refrigerated or preservative-treated samples. Initially, phenolic content and antioxidant capacity were 44 mg GAE/100g and 44 %, respectively, but declined to 10–15 mg and 15–17 % by the end of the storage period. Color changes were more noticeable in samples stored at room temperature, whereas preservatives effectively reduced color degradation caused by enzymatic browning. Moreover, ascorbic acid retention was better in samples with preservatives and those stored under refrigeration. The ascorbic acid degradation rate was highest at room temperature (0.023 day^-1) and lowest with 250 ppm KMS (0.016 day^-1). Microbiological tests indicated that the juice remained safe for 40 days at room temperature, 90 days under refrigeration, and approximately 85 days with preservatives.

In the construction industry, irregular schedules and long hours disrupt workers’ circadian rhythms, adversely affecting their safety and health. While studies have shown that sleep timing influences safety and health, they often overlook sleep quantity, work-shift start time, and a broad range of safety and health outcomes. To fill this gap, this study examines the relationship between circadian rhythm and safety health factors, including psychological issues, wellbeing, behavioral issues, altruistic behaviors, sleep quantity, starting hours at work, and parental care in 1,400 construction workers using a questionnaire. We investigated safety health using scales for psychological issues (0–34), wellbeing (0–24), behavioral issues (0–29), and altruistic behaviors (0–27). Midsleep time on weekends estimated circadian rhythm, with multilevel regressions adjusting for sleep quantity, work start time, and various characteristics. Results showed average midsleep at 04:11 h, with a 1 h delay associated with increased psychological issues (0.37), behavioral issues (3.0%), decreased wellbeing (0.19), and decreased altruistic behaviors (0.18). These findings highlight a correlation between early circadian rhythm and poor safety health, independent of sleep quantity and work-shift start time. Addressing circadian rhythm disruptions could be crucial for improving safety health outcomes, suggesting that work schedule adjustments and better sleep practices may mitigate adverse effects on workers’ health and wellbeing.

Rambutan (Nephelium lappaceum L.), an exotic non-climacteric tropical fruit in Bangladesh, has got wide acceptance to consumers as well as growers due to its attractive appearance, taste and nutrition, but the demerits of inadequate fruiting and yield as well as low edible properties at the farmers field requires to be addressed. Hence, an experiment was performed with gibberellic acid (GA3) and the obtained dataset demonstrates how GA3 application augmented the fruit set and retention, fruit yield and post-harvest biochemical properties of rambutan. Gibberellic acid was sprayed at seven various concentrations from 0 ppm (control) to 500 ppm at the mature panicles (inflorescence) during the pre-flowering and the early fruiting stages (three weeks after fruit set). The study was conducted in two sequential growing years (2020 and 2021) following a randomized complete block design (RCBD). Results revealed that 200–300 ppm doses had superiority over the lower (50–100 ppm) and higher (400–500 ppm) doses for promoting the fruit yield and quality. More specifically, fruit set and retention, fruit size and weight, pulp weight and thickness, pulp:peel ratio, edible portion and fruit yield as well as total soluble solids and total sugars contents in fruit were exhibited the best at 300 ppm being consonant with 200 ppm at majority cases, whereas GA3 doses from 200 ppm to 500 ppm performed similarly to enhance fruit physico-chemical qualities and shelf life of rambutan. Control treatment along with 50 ppm gibberellic acid dose demonstrated inferior results for yield and fruit quality promotion of rambutan. Thus, use of plant growth regulator at appropriate dose and time is imperative to rambutan improvement.

Abstract Polyolefins are a widely accepted commodity polymer made from olefinic monomer consisting of carbon and hydrogen. This thermoplastic polymeric material is formed through reactive double bonds of olefins by the addition polymerization technique and it possesses a diverse range of unique features for a large variety of applications. Among the various types, polyethylene and polypropylene are the prominent classes of polyolefins that can be crafted and manipulated into diversified products for numerous applications. Research on polyolefins has boomed tremendously in recent times owing to the abundance of raw materials, low cost, lightweight, high chemical resistance, diverse functionalities, and outstanding physical characteristics. Polyolefins have also evidenced their potentiality as a fiber in micro to nanoscale and emerged as a fascinating material for widespread high-performance use. This review aims to provide an elucidation of the breakthroughs in polyolefins, namely as fibers, filaments, and yarns, and their applications in many domains such as medicine, body armor, and load-bearing industries. Moreover, the development of electrospun polyolefin nanofibers employing cutting-edge techniques and their prospective utilization in filtration, biomedical engineering, protective textiles, and lithium-ion batteries has been illustrated meticulously. Besides, this review delineates the challenges associated with the formation of polyolefin nanofiber using different techniques and critically analyzes overcoming the difficulties in forming functional nanofibers for the innovative field of applications. Graphical abstract

Background and objective: Hypertension is a potentially dangerous health condition that can be detected by measuring blood pressure (BP). Blood pressure monitoring and measurement are essential for preventing and treating cardiovascular diseases. Cuff-based devices, on the other hand, are uncomfortable and prevent continuous BP measurement. Methods: In this study, a new non-invasive and cuff-less method for estimating Systolic Blood Pressure (SBP), Mean Arterial Pressure (MAP), and Diastolic Blood Pressure (DBP) has been proposed using characteristic features of photoplethysmogram (PPG) signals and nonlinear regression algorithms. PPG signals were collected from 219 participants, which were then subjected to preprocessing and feature extraction steps. Analyzing PPG and its derivative signals, a total of 46 time, frequency, and time-frequency domain features were extracted. In addition, the age and gender of each subject were also included as features. Further, correlation-based feature selection (CFS) and Relief F feature selection (ReliefF) techniques were used to select the relevant features and reduce the possibility of over-fitting the models. Finally, support vector regression (SVR), K-nearest neighbour regression (KNR), decision tree regression (DTR), and random forest regression (RFR) were established to develop the BP estimation model. Regression models were trained and evaluated on all features as well as selected features. The best regression models for SBP, MAP, and DBP estimations were selected separately. Results: The SVR model, along with the ReliefF-based feature selection algorithm, outperforms other algorithms in estimating the SBP, MAP, and DBP with the mean absolute error of 2.49, 1.62 and 1.43 mmHg, respectively. The proposed method meets the Advancement of Medical Instrumentation standard for BP estimations. Based on the British Hypertension Society standard, the results also fall within Grade A for SBP, MAP, and DBP. Conclusion: The findings show that the method can be used to estimate blood pressure non-invasively, without using a cuff or calibration, and only by utilizing the PPG signal characteristic features.

Genetically engineered (GE) crops have the potential to contribute to agricultural sustainability, food security, and nutritional enrichment. However, these crops cannot be released for commercial cultivation without undergoing environmental risk assessments (ERA), thus biosafety evaluation. ERA assessments are performed comparatively with their natural non-GE counterparts. As Bangladesh is progressing with GE potato research, the present study aims to collect baseline information on non-GE potato cultivation with an emphasis on current agronomic practices focusing on fertilizer management and farmers’ knowledge base. The survey had three parts, including information on the farmers, information on potato cultivation practices, especially fertilizer use, and lastly, the farmer’s view on GE potato. From 2020 to 2021, data were collected through interviews with experienced growers in four potato-growing regions, the Central and Mid-East, North-West, Mid-West, and South-East regions (n = 1757) of the country. The study revealed that farmers of all regions used more than the recommended amounts of fertilizer; for instance, 67.1% more nitrogen fertilizer was applied as an extra dose during potato cultivation in Munshiganj (Central and Mid-East) than in the Dinajpur region (North-West). This overuse of nitrogen fertilizer can enhance plant vigor but makes the plants more susceptible to insect attraction and allows pests easier access to the plants. As a result, the excess dose of nitrogen fertilizer in Munshiganj may act as a catalyst to increase the probability of late blight. The findings also showed that 73.6% of farmers observed unexpected flowering in certain potato cultivars, which corresponded to the higher application of phosphate and potassium fertilizers aimed at late blight control. Furthermore, this study reported infestations of Solanaceous weeds, specifically Solanum torvum and Physalis heterophylla, in potato fields. Finally, our findings demonstrated that more than 68.7% of the potato growers intend to adopt disease-resistant GE potato as that may reduce the need for excess fertilizer use and thus reduce cultivation costs.

Summary: Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B∗15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B∗15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the United States (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B∗15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified.

Prostate cancer is a prevalent and life-threatening disease characterized by abnormal cell growth within the prostate gland. Early and accurate diagnosis of prostate cancer is crucial for effective treatment planning. Magnetic Resonance Imaging (MRI) is valuable for diagnosing and assessing prostate cancer. Medical professionals use MRI to create segmentation for detecting prostate cancer. However, existing segmentation methods are limited in accurately delineating anatomical structures and tumor regions within the prostate. This research proposes an innovative methodology for advancing MRI-based prostate segmentation. The objective is to encompass anatomical and tumor zones within the prostate, facilitating precise diagnosis and treatment planning. The proposed dual-pathway multi-scale hierarchical upsampling network introduces significant modifications compared to the traditional UNet-based architecture. It outperforms previous studies, demonstrating superior performance in anatomical segmentation on both the ProstateX and Prostate158 datasets. It achieves an intersection over union of 0.8449 and a dice similarity coefficient of 0.9872 on ProstateX, as well as an intersection over union of 0.8065 and a dice similarity coefficient of 0.9831 on Prostate158, suppressing previous research by a significant margin. These results highlight the potential of this approach to advance the utility of MRI in diagnosing and planning the treatment of prostate-related pathologies, benefiting both patients and healthcare practitioners.

Perovskite materials are getting attention day by day due to their numerous optoelectronic properties. Lead-free perovskites are well-known for various applications in photovoltaic devices due to their non-toxicity which has no impacts on both the environment and health. Cs2PtI6, a lead-free halide perovskite, is renowned for its broad-spectrum light absorption and remarkably high absorption coefficient. Its stability under ambient conditions surpasses that of numerous other halide perovskites, rendering it exceptionally appealing for photovoltaic applications. The device configuration with FTO/ETL/Cs2PtI6/HTL/Au is used in this study where 4 different ETLs and 10 HTLs are used to investigate the best device configuration. The impact of different device parameters like thickness, acceptor density, donor density, and defect density are optimized to attain the best efficient device configuration. SCAPS-1D simulator is used to perform numerical analysis under light intensity of AM 1.5 light spectrum (100 mW/cm2). After the optimization of different device parameters, the device configured with FTO/SnS2/Cs2PtI6/MoTe2/Au shows the best performance among four devices where PCE is 32.98 %, VOC is 1.11 V, JSC is 33.19 mA/cm2, FF is 88.89 %. This suggested Cs2PtI6-based perovskite solar cells demonstrate superior performance compared to numerous lead perovskite-based solar cells, highlighting Cs2PtI6 as a promising alternative for photovoltaic applications while mitigating toxicity concerns.

In applied physics and engineering, non-linear fractional types of partial differential equations become increasingly prominent as an estimation technique to explain a wide variety of non-linear phenomena. Throughout this study, we choose to use an adaptable extended tanh-function scheme over a conformable derivative in order to construct a comprehensive closed-form traveling wave solution of the time fractional Cahn–Hilliard and modified Kawahara equations. The mentioned equations, have been used as frameworks for various phenomena such as quantum theory, geosciences, water wave mechanics, and solitary waves in shallow water in the porous medium. The different values of the fractional order of the model can be employed successfully to organize the wave velocity. We recognized numerous forms of solutions by using the computational software, namely solitons type, bell types, kink types, periodic types, multiple periodic, single soliton, singular kink, and other types of solutions that are illustrated using 3D, contour, and spherical. The attained results have effectively handled the previously stated phenomena in various fields of engineering and mathematical physics. The results originating in this study were confirmed by the computational software, which was used to rewrite them as non-linear fractional partial differential equations. We ensure that the technique is revised to make it more effective, pragmatic, and credible, and we pursue more comprehensive exact results for traveling waves, and then for solitary waves.