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AbstractNanoemulsions are nano-sized particles, typically ranging from tens to hundreds of nanometers. These nanoemulsions possess various appealing properties, making them highly promising for various applications in pharmaceutics, foods, and cosmetics. These properties include their small size, which allows for a high surface area per unit volume, and their ability to disperse hydrophobic components and enhance absorption effectively. In the pharmaceutical industry, nanoemulsions have been developed to enhance the delivery of hydrophobic active ingredients. Macromolecular surfactants offer enhanced emulsion stability compared to conventional low-molecular surfactants. Enhanced stability is due to their slower desorption kinetics at the droplet interface, which reduces the risk of toxicity and skin irritation associated with the latter. This article presents a comprehensive investigation into the role of nanoemulsions in drug delivery. It commences by delineating various emulsion types and subsequently explores techniques for nanoemulsion preparation. Surfactants serve as pivotal components in both the production and stabilization of nanoemulsions. The review provides an encompassing overview of diverse surfactant types, encompassing small molecule variants, particle surfactants, phospholipids, peptides, and protein-based surfactants tailored for nanoemulsions. Additionally, it addresses nanoemulsion instability, elucidating strategies to mitigate instability challenges, and highlights the utilization of nanoemulsions in nanomedicine for effective drug delivery. This comprehensive overview aims to offer insights for researchers engaged in nanoemulsion-related studies and associated interdisciplinary fields. [ABSTRACT FROM AUTHOR]

An experimental setup was developed for simulating the field conditions to determine the force and power required for cutting cumin crops in dynamic conditions. The effect of cutter bar speeds, forward speeds, and blade type on cutting force and power requirement for cutting cumin were also studied. Experiments were carried out at three levels: cutter bar speeds, forward speeds, and blade type. The results showed that all the factors significantly affected cutting force. The cutting force followed a decreasing trend with the increase in cutter bar speed. Whereas it followed an increasing trend with the increase in forward speed. The maximum cutting force for all three blades was observed at a cutter bar speed of 2.00 strokes.s-1 and forward speed of 0.46 m.s−1. The idle power and actual power required for cutting the cumin crop were also determined based on the cutting force. The results obtained were validated by the power drawn from the power source while operating the cutter bar blades. The R2 values for Blade-B1, Blade-B2, and Blade-B3 were 0.90, 0.82, and 0.88, respectively. The cutting force was primarily affected by the cutter bar speed, resulting in PCR values of 74.20%, 82.32%, and 81.75% for Blade-B1, Blade-B2, and Blade-B3, respectively, followed by the forward speed, which also had an impact on PCR values of 16.60%, 15.27%, and 18.25% for Blade-B1, Blade-B2, and Blade-B3, respectively. The cutting force for Blade-B1, Blade-B2, and Blade-B3 varied from 15.96 to 58.97 N, 21.08 to 76.64 N, and 30.22 to 85.31, respectively, for the selected range of cutter bar speed and forward speed. Blade-B1 had 18 and 30% less power consumption than Blade-B2 and Blade-B3, respectively. [ABSTRACT FROM AUTHOR]

Skin cancer is one of the most life-threatening diseases caused by the abnormal growth of the skin cells, when exposed to ultraviolet radiation. Early detection seems to be more crucial for reducing aberrant cell proliferation because the mortality rate is rapidly rising. Although multiple researches are available based on the skin cancer detection, there still exists challenges in improving the accuracy, reducing the computational time and so on. In this research, a novel skin cancer detection is performed using a modified falcon finch deep Convolutional neural network classifier (Modified Falcon finch deep CNN) that efficiently detects the disease with higher efficiency. The usage of modified falcon finch deep CNN classifier effectively analyzed the information relevant to the skin cancer and the errors are also minimized. The inclusion of the falcon finch optimization in the deep CNN classifier is necessary for efficient parameter tuning. This tuning enhanced the robustness and boosted the convergence of the classifier that detects the skin cancer in less stipulated time. The modified falcon finch deep CNN classifier achieved accuracy, sensitivity, and specificity values of 93.59%, 92.14%, and 95.22% regarding k-fold and 96.52%, 96.69%, and 96.54% regarding training percentage, proving more effective than literary works. [ABSTRACT FROM AUTHOR]

Chitosan, a versatile biopolymer derived from chitin, has garnered significant attention in various biomedical applications due to its unique properties, such as biocompatibility, biodegradability, and mucoadhesiveness. This review provides an overview of the diverse applications of chitosan and its derivatives in the antibacterial, anticancer, wound healing, and tissue engineering fields. In antibacterial applications, chitosan exhibits potent antimicrobial properties by disrupting microbial membranes and DNA, making it a promising natural preservative and agent against bacterial infections. Its role in cancer therapy involves the development of chitosan-based nanocarriers for targeted drug delivery, enhancing therapeutic efficacy while minimising side effects. Chitosan also plays a crucial role in wound healing by promoting cell proliferation, angiogenesis, and regulating inflammatory responses. Additionally, chitosan serves as a multifunctional scaffold in tissue engineering, facilitating the regeneration of diverse tissues such as cartilage, bone, and neural tissue by promoting cell adhesion and proliferation. The extensive range of applications for chitosan in pharmaceutical and biomedical sciences is not only highlighted by the comprehensive scope of this review, but it also establishes it as a fundamental component for forthcoming research in biomedicine. [ABSTRACT FROM AUTHOR]

Franz diffusion cell was primarily used to evaluate the permeability and stability of formulations such as topical (gels and creams) and transdermal (lipid nanoparticle formulations). Diffusion cell is a straightforward assay that can reliably measure the in-vitro and ex-vivo drug release from topical preparations such as creams, ointments, liposomes formulations, and gels. It offered crucial critical perspectives on skin, drug, and formulation relationships. In addition, it is also employed for toxicity testing and quality control. Currently, many medications are available in the market, administered through transdermal routes. To treat various skin conditions, medical professionals use a wide range of methods aimed at increasing the skin's permeability and drug absorption. The biggest challenge with transdermal drug delivery system is determining the amount of medication penetrating the skin. Today, there is a lot of research into creating new dermal dosage forms for pharmaceuticals. In this review, the authors discuss various evaluation methods to determine the amount of drug penetrating the skin. With their strengths and weaknesses, these models and assessment methods provide a valuable framework for investigating the dermato-pharmacokinetics of different transdermal formulations. The assessment techniques aid in assessing molecules that cause skin irritation by shedding light on the molecular mechanisms by which they penetrate the skin. These assessment tools and models provide a novel strategy for creating topical medicinal formulations for various skin infection disorders. The present review explores Franz diffusion cell application, its implication in pharmaceutical research, and the regulation related to pharmacopeia. [ABSTRACT FROM AUTHOR]

Purpose: To estimate the volatility of exchange and stock markets and examine its spillover within and across the member countries of BRICS during COVID-19 and the conflict between Russia and Ukraine. Design/methodology/approach: The study utilizes the "dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH)" approach of Gabauer (2020). The volatility of the markets is calculated following the approach of Parkinson (1980). The sample dataset comprises the daily volatility of the stock and exchange markets for 35 months, from November 2019 to September 2022. Findings: The study confirms the existence of contagion effects among member countries. Volatility spillover between exchange and stock markets is low within the country but substantial across borders. Russian contribution increased significantly during the conflict with Ukraine, and other countries also witnessed a surge in the spillover index during the pandemic and war. Research limitations/implications: It adds to the body of literature by emphasizing the necessity of comprehending the economies' behavior and interdependence. Offers insightful information to decision-makers who must be more watchful regarding the financial crisis and its regional spillover. Originality/value: The study is the first to explore the contagion of volatility among the BRICS countries during the two biggest crisis periods of the decade. [ABSTRACT FROM AUTHOR]

The oral administration of donepezil hydrochloride has low brain targeting efficiency especially due to the presence of the blood–brain barrier leading to poor quality of treatment. Hence, this study aimed to systematically design chitosan nanoparticles for direct nose-to-brain delivery of donepezil hydrochloride using the Quality by Design approach for better transport to the brain avoiding the blood–brain barrier. The optimized formulation showed 180.2 nm average particle size and 0.282 polydispersity index, + 16.6 mV zeta potential, more than 90% drug release, and more than 70% drug permeation in 24 h. The studies on in-vitro drug release and ex-vivo permeation showed a sustained release pattern fulfilling Korsemeyer Peppa's model. The confocal laser scanning micrographs showed the spherical nature of nanoparticles. The intranasal administration of donepezil hydrochloride nanoparticles in Wistar rats showed approximately 2.6 times more drug than donepezil hydrochloride solution given intranasally and approximately 10 times more drug than donepezil hydrochloride solution given orally in the brain respectively after 6 h. Further, confocal micrographs using Rhodamine B (fluorescent dye) loaded nanoparticles confirmed the localization of nanoparticles in the brain post-intranasal administration. The obtained results suggested that the chitosan nanoparticles are promising drug carriers for the nose-to-brain delivery of donepezil hydrochloride for the treatment of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Utilization of organic wastewater for hydrogen production has dual advantages of clean energy generation and bioremediation, which is sustainable for a longer period. To maximize the energy recovery from starch rich wastewater, a two stage system comprising of thermophilic dark fermentation coupled with microbial fuel cell was employed. A single parameter optimization strategy was implemented for the operation of the batch system. The maximum cumulative hydrogen production obtained was 2.56 L L−1 with a 48% reduction in COD under the optimal conditions of 35 g L−1 initial substrate concentration (COD), temperature 60 °C, and pH 6.5. The H2 yield and H2 production rate were 6.8 mol H2/kg CODreduced and 731.3 mL L−1 h−1, respectively. The effect of the organic loading rate (OLR) on H2 production rate was studied in a continuous stirred tank reactor (CSTR). A maximum hydrogen production rate of 913 mL L−1 h−1 was observed at an OLR of 5.6 g L−1 h−1. Effluent recycle played an important role in the improvement of H2 production. A maximum H2 production rate of 1224 mL L−1 h−1 was observed at a recycle ratio of 0.6. Power density of 4.2 W m−3 was observed with MFC using the dark fermentative spent media neutralized with carbonate buffer at an optimal pH of 7. A total COD reduction of 86% was observed. [ABSTRACT FROM AUTHOR]

AbstractThe transungual drug delivery system refers to the administration of drugs through the nail plate to treat various nail disorders such as fungal infections, psoriasis, and nail dystrophies. The nail plate is a challenging barrier for drug penetration due to its highly keratinized and tightly packed structure, which limits the permeation of topically applied drugs. Owing to several problems associated with oral therapy, topical therapy remains a preferred treatment option for nail infections due to less side effects, and cost-effectiveness. On the other hand, the drugs that have low permeability across the nail plate highlight the need for further research in this area. Researchers working on various aspects to increase drug penetration across the nail plate, which include the use of chemical penetration enhancers, mechanical methods, and physical methods. Recent advances in transungual drug delivery systems have led to the development of antifungal nail lacquers that can penetrate the nail plate and effectively treat nail infections. Other transungual drug delivery systems under investigation include microneedles, ultrasound, and laser-assisted treatment, which can create micropores in the nail plate allowing higher drug delivery. This indicates the potential of research on transungual drug delivery systems. By understanding the anatomy of the nail, utilizing appropriate penetration-enhancing methods, and selecting appropriate drug formulations, the effectiveness of the system can be developed and utilized. [ABSTRACT FROM AUTHOR]

The laser wakefield acceleration (LWFA) scheme is now a superb and potent instrument for industry, medicine, fusion, and other uses. With the aid of this technique, high-quality electron beams can be generated, which might eventually be employed to create small, portable X-ray sources. Using a linearly polarized Gaussian laser pulse, the present work focuses on examining electron acceleration in an under-dense plasma having a ramp profile with different density-hill widths. Two-dimensional Fourier–Bessel Particle-In-Cell simulation (2D-FBPIC) code shows that optimizing the laser parameters and plasma density profile maximizes the energy gain and minimizes the normalized rms emittance in the x, y directions inside the plasma bubble. For 10 and 90 μ m density-hill widths, respectively, the optimal emittance value is reported to be ϵ x ∼ 3.10 mm.mrad in the x-direction and ϵ y ∼ 2.63 mm.mrad in the y-direction. At a density-hill width of 90 μ m , it is also observed that the charge trapped inside the bubble is 44.91 pC. With this density-hill width and a plasma channel length of 3.84 mm, our simulation findings show an energy gain of 0.38 GeV to the electron-bunch accelerated inside the bubble. [ABSTRACT FROM AUTHOR]

Background: Bovine tuberculosis (bTB) is a chronic disease that results from infection with any member of the Mycobacterium tuberculosis complex. Infected animals are typically diagnosed with tuberculin-based intradermal skin tests according to World Organization of Animal Health which are presently in use. However, tuberculin is not suitable for use in BCG-vaccinated animals due to a high rate of false-positive reactions. Peptide-based defined skin test (DST) antigens have been identified using antigens (ESAT-6, CFP-10 and Rv3615c) which are absent from BCG, but their performance in buffaloes remains unknown. To assess the comparative performance of DST with the tuberculin-based single intradermal test (SIT) and the single intradermal comparative cervical test (SICCT), we screened 543 female buffaloes from 49 organized dairy farms in two districts of Haryana state in India. Results: We found that 37 (7%), 4 (1%) and 18 (3%) buffaloes were reactors with the SIT, SICCT and DST tests, respectively. Of the 37 SIT reactors, four were positive with SICCT and 12 were positive with the DST. The results show that none of the animals tested positive with all three tests, and 6 DST positive animals were SIT negative. Together, a total of 43 animals were reactors with SIT, DST, or both, and the two assays showed moderate agreement (Cohen's Kappa 0.41; 95% Confidence Interval (CI): 0.23, 0.59). In contrast, only slight agreement (Cohen's Kappa 0.18; 95% CI: 0.02, 0.34) was observed between SIT and SICCT. Using a Bayesian latent class model, we estimated test specificities of 96.5% (95% CI, 92–99%), 99.7% (95% CI: 98–100%) and 99.0% (95% CI: 97–100%) for SIT, SICCT and DST, respectively, but considerably lower sensitivities of 58% (95% CI: 35–87%), 9% (95% CI: 3–21%), and 34% (95% CI: 18–55%) albeit with broad and overlapping credible intervals. Conclusion: Taken together, our investigation suggests that DST has a test specificity comparable with SICCT, and sensitivity intermediate between SIT and SICCT for the identification of buffaloes suspected of tuberculosis. Our study highlights an urgent need for future well-powered trials with detailed necropsy, with immunological and microbiological profiling of reactor and non-reactor animals to better define the underlying factors for the large observed discrepancies in assay performance, particularly between SIT and SICCT. [ABSTRACT FROM AUTHOR]

The detection of hydrogen in the Earth's deep underground poses a major challenge due to the lack of oxygen and continuous changes in environmental conditions. An innovative class of hydrogen gas sensors based on AlGaN/GaN High Electron Mobility Transistors (HEMTs) with Platinum (Pt) gates as a functionalization layer, has been developed and optimized for geo-sensing. The study investigated the sensor characteristics using two carrier gases to simulate underground conditions, namely air (with 20 % O 2) and N 2 (with 0 % O 2), across a range of temperatures from 50 °C to 300 °C and with hydrogen concentrations varying from 25 ppm to 400 ppm. The detection limit was found to be approximately 1 ppm of hydrogen in the atmospheric air. The gas sensor transduction is based on the modification of the conductivity of a 2-Dimensional Electron Gas (2DEG). In this study, the principle was investigated using two gases, O 2 and H 2 , with different electronegativities relative to platinum. The adsorption competition between H 2 and O 2 on platinum was evaluated, and this allowed the calculation of the ratio of thermodynamic adsorption constants between these two gases. • Investigated the Pt-AlGaN/GaN HEMT-based sensor for detecting underground H 2 gas using N 2 and air as carrier gases. • Key parameters for hydrogen sensing included the effects of temperature and hydrogen concentration. • Demonstrated that hydrogen has 2000 times greater affinity than O 2 with the Pt-AlGaN/GaN sensor functional layer. • Presented and comprehensively explained the adsorption kinetics of hydrogen with the Pt functional layer. [ABSTRACT FROM AUTHOR]

In recent times, fibre reinforced polymer (FRP) composites have overtaken the huge market in the world replacing the old conventional materials due to its significant properties. The experimental work conducted to gather the mechanical properties takes alot of time as FRP composites comprises of various geometrical parameters. Therefore, to reduce the experimental encumbrance, the current work is focused on the numerical analysis using different failure criteria, to examine the bearing response of electron beam cured carbon fibre/epoxy (CF/E) composites joint and to get a suitable numerical model. In order to identify the failure of carbon-fibre/polymer composites joints, this work coupled progressive damage analysis (PDA) with the most appropriate failure criteria, namely the Hashin, Tsai-Wu and Maximum stress criteria. Results show that Hashin criterion gave the best suited bearing response predictions. Hashin criterion predicted the maximum bearing capacity in pristine joint specimens, in between 11 and 17% for greater values of W/D and E/D ratios. In multiwalled carbon nanotubes (MWCNTs) added joint specimens, the predicted values by Hashin criterion is in between 14 and 20%. [ABSTRACT FROM AUTHOR]

The flexoelectric phenomenon, which occurs when materials undergo mechanical deformation and cause strain gradients and a related spontaneous electric polarization field, can result in wide variety of energy‐ and cost‐saving mechano‐opto‐electronics, such as night vision, communication, and security. However, accurate sensing of weak intensities under self‐powered conditions with stable photocurrent and rapid temporal response remains essential despite the challenges related to having suitable band alignment and high junction quality. Taking use of the flexoelectric phenomena, it is shown that a centrosymmetric VO2‐based heterojunction exhibits a self‐powered (i.e., 0 V), infrared (λ = 940 nm) photoresponse. Specifically, the device shows giant current modulation (103%), good responsivity of >2.4 mA W−1, reasonable specific detectivity of ≈1010 Jones, and a fast response speed of 0.5 ms, even at the nanoscale modulation. Through manipulation of the applied inhomogeneous force, the sensitivity of the infrared response is enhanced (> 640%). Ultrafast night optical communication like Morse code distress (SOS) signal sensing and high‐performing obstacle sensors with potential impact alarms are created as proof‐of‐concept applications. These findings validate the potential of emerging mechanoelectrical coupling for a wide variety of novel applications, including mechanoptical switches, photovoltaics, sensors, and autonomous vehicles, which require tunable optoelectronic performance. [ABSTRACT FROM AUTHOR]

In the rapidly evolving digital landscape, secure communication is crucial, and polarization‐sensitive photodetectors offer a promising approach to enhance security and efficiency. However, conventional devices face limitations in encoding capacity due to material‐specific anisotropic properties and geometric factors. In this study, the critical role of the flexoelectric effect in detecting polarized light in silicon and its effective utilization in secure communication systems are demonstrated. The device shows self‐biased photoresponse, which is modulated by up to 320% with the application of force by a sharp probe, a phenomenon attributed to the flexoelectric effect. The polarization sensing behavior is confirmed through comprehensive scanning photocurrent mapping, which is further supported by rigorous finite element simulations. As a potential application, the device is implemented to sense Morse code and effectively modulate it using the flexoelectric effect and light polarization angle, offering more sophisticated encryption methods for secure communication. This research provides valuable insights for advancing secure communication technologies and overcoming the inherent challenges associated with silicon‐based photodetectors. [ABSTRACT FROM AUTHOR]

One of the most valuable practices for analyzing not-so-analytical-friendly analytes in complex, heterogenous matrices is derivatization. Availability of numerous derivatizing reagents (DRs) makes the modification of analyte more exploitable in terms of an analytical perspective. A wide array of derivatization techniques like pre or post-column, in-situ, enzymatic, ultrasound-assisted, microwave-assisted, photochemical derivatization has added much-needed methodological strength in analyzing intricate analytical matrices (food, water, and soil). In recent years, analytical chemistry has achieved greater heights through the development of new sensitive methods with simple conventional instruments like High-Performance Liquid Chromatography (HPLC) devoid of Mass detectors. The prompt availability of these straightforward instruments also makes it a favorable option for routine analysis in food, environmental, bioanalytical chemistry. Analyzing food, environmental or bioanalytical specimen has some of the most problematic aspects, like the low concentration of the analytes accompanied by not too suitable analytical properties. Even though conventional HPLC lacks the required sensitivity but merger with derivatization can lead to a remarkable increase in sensitivity. In recent years there has been a lot of application of diverse derivatizations to increase the sensitivity and selectivity of the analyte for available instruments, resulting in notable findings. Therefore, this review describes the application of derivatization principles in the analysis of analytes in food and additional matrices using conventional HPLC instruments such as HPLC-UV, HPLC-DAD, and HPLC-FD. In this article, we will briefly review the different modes and multiple types of derivatizing reagents with their mechanisms and importance for encouraging the use of established HPLC instruments. [ABSTRACT FROM AUTHOR]

AbstractPharmaceutical sciences are the exploration of the design, composition, action, and conveyance of drugs. It encompasses a wide range of research domains that seems to be fundamental for the discovery and development of new drugs and therapies. It is indeed categorized under many fractions with numerous specialized fields. New concepts in pharmaceutical research, a greater understanding of the properties of polymeric materials, fabricating innovation, and novel methodologies that assure high-quality dosage forms are being constantly pursued. The application of 3D printing technology in the area of drug delivery has brought new scope and opportunities. Various dosage forms like tablets, catheters, nanosuspensions, nanocomposites, multi-layered dosage forms, polypills, caplets, complex drug release dosage forms, and medical drug delivery devices have been explored in the recent past and detailed reviews of pharmaceuticals have also been studied. However, this technology has not been limited to the drug delivery or medical device field only. In this article, the authors highlighted the physiochemical properties of polymers that are utilized in the preparation of pharmaceutical dosage forms and also describes some of the new advancements and educational applications that have given a new dimension to this novel 3D-printing technology apart from the pharmaceutical and biomedical arena. [ABSTRACT FROM AUTHOR]

Aim: The aim of the present study was to assess the prevalence and types of anaemia in severe acute malnutrition children with age group from 6 months to 59 months. Methods: The Cross-Sectional study was conducted at Department of Pediatrics, Nutritional rehabilitation center of BRD Medical College, Gorakhpur for the period of one year (September 2021 to August 2022). 116 cases were included in the study. Permission for Ethical clearance was sought from the institutional human ethics committee of BRD Medical College. Results: Out of 98 anemic children 64 (65.3%) were mild anemic, 22 (22.4%) were moderate anemic. Out of 116 patients, 65 (56%) were classified as microcytic hypochromic blood picture while 26 (22.4%) were dimorphic blood picture, 18 (15.5%) were distributed as macrocytic blood picture and 7 (6%) were classified as normocytic normochromic blood picture. Out of 116 subjects, there were 62 (53.4%) males and 54 (46.6%) females. Out of 116 neonates, 97 (83.6%) were less than or equal to 2 years and 19 (16.4%) were more than 2 years. Out of 116 patients, 80 (69%) were moderately underweight while 19 (16.4%) were underweight and 17 (14.7%) were severe underweight. Out of 116 patients, 58 (69%) were moderately stunting while 38 (32.8%) were stunting and 20 (17.2%) were severe stunting. Conclusion: No significant odds of anaemic status were found when associated with the independent parameters. In addition, clinicians working in maternal and child health departments are recommended to strengthen the treatment of HIV infection before causing further damages. [ABSTRACT FROM AUTHOR]

The rise in demand for biomass as a renewable energy source is being seen as an alternative energy source to conventional fossil fuels. Blending of biodiesels and bioethanol in gasoline is the initial step towards complete utilization of biomass fuels. Glycerol is a byproduct generated in vast quantities during biodiesel production. Glycerol, on further oxidation, can produce several value-added products in conjunction with hydrogen (H2) through photo-/electrocatalysis (PEC/EC). Valuable products from glycerol include 1,3-dihydroxyacetone, glyceraldehyde, tartronic acid, formic acid, and glyceric acid. Glycerol can be used as a feedstock in PEC/EC cells along with water. An intriguing strategy unfolds by combining the oxidation of biomass-derived compounds at the anode with the hydrogen evolution reaction taking place at the cathode, all contained within a biomass electrolysis or photo-reforming reactor. This approach enables the simultaneous production of high-value chemicals and hydrogen, while minimizing energy consumption and reducing CO2 emissions. This review seeks to integrate essential insights into photo- and electro-assisted catalysis, with the objective of offering a holistic comprehension of the overall reaction mechanisms involved in the photo-/electrocatalytic oxidation of glycerol. At the same time, various transition metal-based photo-/electrocatalysts for glycerol valorization are reviewed and discussed in great detail. Moreover, this evaluation carefully examines the obstacles and possibilities for the advancement of photo-/electrocatalytic glycerol oxidation, aligning with future demands for sustainability in the global energy landscape. [ABSTRACT FROM AUTHOR]

COVID-19 has been shown to induce inflammatory disorders and CNS manifestations. Swift and efficient treatment strategies are urgently warranted for the management of COVID, inflammatory and neurological disorders. Hydrogen sulfide (H 2 S) has been associated with several clinical disorders due to its potential to influence a broad range of biological signalling pathways. According to recent clinical studies, COVID patients with lower physiological H 2 S had higher fatality rates. These findings clearly demonstrate an inverse correlation between H 2 S levels and the severity of COVID-19. H 2 S has been proposed as a protective molecule because of its antioxidant, anti-inflammatory, and antiviral properties. Various H 2 S-releasing prodrugs, hybrids and natural compounds have been tested for their therapeutic efficacy in viral infections and inflammatory disorders. In this review, I am highlighting the rationale for using H 2 S-based interventions for the management of COVID-19 and post-infection inflammatory disorders including neuroinflammation. I am also proposing therepurposing of existing H 2 S-releasing prodrugs, developing new NO-H 2 S-hybrids, targeting H 2 S metabolic pathways, and using H 2 S-producing dietary supplements as viable defensive strategies against SARS-CoV-2 infection and COVID-19 pathologies. • COVID patients had lower H 2 S bioavailability than healthy controls. • COVID survivors had higher H 2 S levels as compared to non-survivors. • H 2 S-based interventions may be relevant therapies for the management of COVID and inflammatory disorders. • Further investigation on efficacy, treatment time, dosage and delivery methods of H 2 S-releasing drugs is urgently needed. [ABSTRACT FROM AUTHOR]

Background: The green gram (Vigna radiata L.) is the major legume crop in India. Dry root rot (DRR) incited by M. phaseolina is a serious problem to the green gram production area in the world and India; Dry root rot has in recent years become a major obstacle to the successful and gainful growing of green gram, which can lead to significant losses in green gram production. The host plant resistance is the best alternative to management the DRR of the green gram, it is an economical and eco-friendly way to disease management. In the experiment, Twenty-five green gram germplasm has been tested for resistance to DRR, a serious disease caused by Macrophomina phaseolina. Methods: M. phaseolina sand maize meal inoculum was applied to the field in sufficient amounts to maintain the sick plot before planting green gram germplasm, each germplasm was planted in three rows of 5 m in length, maintaining a distance between plants of 10 cm, the incidence of DRR was recorded using a disease rating scale. Based on disease reaction, green gram germplasm was grouped into different categories. Result: From 25 green gram germplasm, four germplasm showed a resistant reaction to dry root rot, namely IPM-02-03, G-2, MH-2- 15, MUM-2, while this has been observed. Susceptibility of green gram germplasm to dry root rot such as RMG-26. [ABSTRACT FROM AUTHOR]

In order to develop machine learning and deep learning models that take into account the guidelines and principles of trustworthy AI, a novel information theoretic approach is introduced in this article. A unified approach to privacy-preserving interpretable and transferable learning is considered for studying and optimizing the trade-offs between the privacy, interpretability, and transferability aspects of trustworthy AI. A variational membership-mapping Bayesian model is used for the analytical approximation of the defined information theoretic measures for privacy leakage, interpretability, and transferability. The approach consists of approximating the information theoretic measures by maximizing a lower-bound using variational optimization. The approach is demonstrated through numerous experiments on benchmark datasets and a real-world biomedical application concerned with the detection of mental stress in individuals using heart rate variability analysis. [ABSTRACT FROM AUTHOR]

Litchi tree is planted in several countries of the world for its juicy fruit. For the estimated total annual global litchi production of ~ 2.7 million tons, around ~ 0.54 million tons of seeds as well as a sizeable amount of skin are generated as waste. This renewable waste biomass can be effectively used as the feedstock for recovering energy and obtaining several value-added products. In the present work, the fuel and thermochemical characteristics and thermal degradation behavior of acid- and alkali-treated litchi seed biomass were systematically investigated and compared for the first time. The average and maximum rate of mass losses, peak temperature and pyrolysis factor had been evaluated to assess the reactivity of the treated biomass. It had been observed that acid and alkali treatments improved the higher heating value and changed the thermal degradation behavior. The thermogravimetric (TG)/differential thermogravimetric analysis (DTG) data obtained at the heating rates of 20, 25 and 30 °C min−1 were used to evaluate the kinetic and thermodynamic parameters using iso-conversional models of Flynn–Wall–Ozawa, Kissinger–Akahira–Sunose, Tang and Starink. The Criado method had been used to elucidate the prevailing thermal degradation reaction mechanisms at different fractional conversions. The average activation energy of the acid-treated biomass increased, and that of the alkali-treated biomass decreased compared to that of the untreated biomass. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) is being used more widely because of the simplicity of the operating procedures. It decreases material consumption during part production and eliminates material waste. Fused deposition modeling (FDM), a well‐known AM process, uses thermoplastic polymer as a feedstock to manufacture the end design. Pure thermoplastic‐based products are still utilized as prototypes in several sectors due to their lack of strength and durability. This problem has been solved by strengthening the thermoplastics by adding a reinforcing element. Composites are made of polymers and various constituents known as reinforcing components. This article overviews natural reinforced polymer composites used in the FDM process. Mechanical and Thermal properties are presented based on natural filler percentage, and this article only considered natural composite filaments for the FDM process. [ABSTRACT FROM AUTHOR]

Caissons are rigid foundation systems with huge mass that support a large variety of load combinations. Most studies ignore the resistance provided by the periphery of a caisson in providing resistance to applied external loading. In this study, the variation of resistive stresses generated on the base and sides of a caisson under various loading, interface, and seismic conditions, obtained from numerical analysis, is explored using finite-element method–based computer program ABAQUS. The shear forces and resistive moments thus generated have been studied to identify the resistive forces required for stability for different input parameters. The percentage of resisting moment shared by the caisson sides (lateral soil pressure, horizontal and vertical skin friction) has then been compared with that due to the caisson base (base reaction and base friction). Empirical correlation has been obtained using multiple linear regression analysis for the load shared by the caisson sides. It is observed that, with an increase in the horizontal and vertical seismic acceleration coefficients, the percentage of resisting moment contributed by the caisson sides increases. [ABSTRACT FROM AUTHOR]

The use of IoT technology is rapidly increasing in healthcare development and smart healthcare system for fitness programs, monitoring, data analysis, etc. To improve the efficiency of monitoring, various studies have been conducted in this field to achieve improved precision. The architecture proposed herein is based on IoT integrated with a cloud system in which power absorption and accuracy are major concerns. We discuss and analyze development in this domain to improve the performance of IoT systems related to health care. Standards of communication for IoT data transmission and reception can help to understand the exact power absorption in different devices to achieve improved performance for healthcare development. We also systematically analyze the use of IoT in healthcare systems using cloud features, as well as the performance and limitations of IoT in this field. Furthermore, we discuss the design of an IoT system for efficient monitoring of various healthcare issues in elderly people and limitations of an existing system in terms of resources, power absorption and security when implemented in different devices as per requirements. Blood pressure and heartbeat monitoring in pregnant women are examples of high-intensity applications of NB-IoT (narrowband IoT), technology that supports widespread communication with a very low data cost and minimum processing complexity and battery lifespan. This article also focuses on analysis of the performance of narrowband IoT in terms of delay and throughput using single- and multinode approaches. We performed analysis using the message queuing telemetry transport protocol (MQTTP), which was found to be efficient compared to the limited application protocol (LAP) in sending information from sensors. [ABSTRACT FROM AUTHOR]

The determination of seismic passive earth pressure resistance is of utmost importance during the analysis of geotechnical structures. In the present study, seismic passive earth pressure coefficient for caisson embedded in n‐layered soil is computed using modified pseudo‐dynamic method. Limit equilibrium method of analysis considering poly‐planar failure wedge has been adopted in the study and parametric variation of geometry of failure wedge has also been studied. The current study proposes formulation for variation of horizontal and vertical seismic acceleration profile with depth through various layers and studies the effect of number of layers, relative depths of various layers and relative soil friction angle in those layers, soil‐wall friction angle, horizontal and vertical seismic acceleration coefficients and normalized width of caisson. The study has been extended for submerged soil and the effect of excess pore pressure has been investigated. The results of the present study have been compared with previous theoretical studies and found to be in good agreement. It is observed that the extent of failure wedge formed in front of caisson increases with increasing soil friction angle, soil‐wall friction angle, horizontal seismic acceleration coefficient and width of caisson. [ABSTRACT FROM AUTHOR]

Cardiac arrhythmia is a deadly disease that threatens the lives of millions of people, which shows the need for earlier detection and classification. An abnormal signal in the heart causing arrhythmia can be detected at an earlier stage when the health data from the patient are monitored using IoT technology. Arrhythmias may suddenly lead to death and the classification of arrhythmias is considered a complicated process. In this research, an effective classification model for the classification of heart disease is developed using flamingo optimization. Initially, the ECG signal from the heart is collected and then it is subjected to the preprocessing stage; to detect and control the electrical activity of the heart, the electrocardiogram (ECG) is used. The input signals collected using IoT nodes are collectively presented in the base station for the classification using flamingo-optimization-based deep convolutional networks, which effectively predict the disease. With the aid of communication technologies and the contribution of IoT, medical professionals can easily monitor the health condition of patients. The performance is analyzed in terms of accuracy, sensitivity, and specificity. [ABSTRACT FROM AUTHOR]

Studying geo-morphometric parameters using Remote Sensing (RS) and Geographic Information System (GIS) tools is crucial to routing runoff and remaining hydrological processes. A geo-spatial model and principal component analysis (PCA) approach are used in this study to prioritize sub-watersheds of the upper Beas river up to Pandoh dam. Dendritic drainage patterns throughout its sub-watersheds characterized the 6th-order Beas river. The sub-watersheds show a lithological uniformity that indicates that the entire watershed has structurally impermeable materials at both surface and sub-surface levels. Moreover, the aerial and relief aspects of the sub-watershed indicate fine drainage textures, steep slopes, immediate peak flows, a hydrograph with multiple peaks, and a low concentration time. In other words, the sub-watershed may not be able to manage flash floods during the storm period. Surface runoff and sediment production rates (SPR) were estimated in the present study ranged from 3.576–5.240 sq. km-cm/sq.km and 0.101–0.234 ha-m/100sq.km/year, respectively. Finally, the study concluded that the sub-watersheds in the upper regions produced high runoff and sediments, usually carried into the mainstream. Further, the PCA technique was applied to find the redundant morphometric parameters and then the same results were utilized to determine the effective way to prioritize the watershed. The present study will serve as a basis for developing appropriate policies and practices for peak flooding and promoting the sustainability of the watershed. [ABSTRACT FROM AUTHOR]

Industrial Internet of Things (IIoT) seeks more attention in attaining enormous opportunities in the field of Industry 4.0. But there exist severe challenges related to data privacy and security when processing the automatic and practical data collection and monitoring over industrial applications in IIoT. Traditional user authentication strategies in IIoT are affected by single factor authentication, which leads to poor adaptability along with the increasing users count and different user categories. For addressing such issue, this paper aims to implement the privacy preservation model in IIoT using the advancements of artificial intelligent techniques. The two major stages of the designed system are the sanitization and restoration of IIoT data. Data sanitization hides the sensitive information in IIoT for preventing it from leakage of information. Moreover, the designed sanitization procedure performs the optimal key generation by a new Grasshopper–Black Hole Optimization (G–BHO) algorithm. A multi-objective function involving the parameters like degree of modification, hiding rate, correlation coefficient between the actual data and restored data, and information preservation rate was derived and utilized for generating optimal key. The simulation result establishes the dominance of the proposed model over other state-of the-art models in terms of various performance metrics. In respect of privacy preservation, the proposed G–BHO algorithm has achieved 1%, 15.2%, 12.6%, and 1% enhanced result than JA, GWO, GOA, and BHO, respectively. [ABSTRACT FROM AUTHOR]

Drivers undergo a lot of stress that might cause distraction and might lead to an unfortunate incident. Emotional recognition via facial expressions is one of the most important field in the human–machine interface. The goal of this paper is to analyze the drivers' facial expressions in order to monitor their stress levels. In this paper, we propose FERNET — a hybrid deep convolutional neural network model for driver stress recognition through facial emotion recognition. FERNET is an integration of two DCNNs, pre-trained ResNet101V2 CNN and a custom CNN, ConvNet4. The experiments were carried out on the widely used public datasets CK + , FER2013 and AffectNet, achieving the accuracies of 99.70%, 74.86% and 70.46%, respectively, for facial emotion recognition. These results outperform the recent state-of-the-art methods. Furthermore, since a few specific isolated emotions lead to higher stress levels, we analyze the results for stress- and nonstress-related emotions for each individual dataset. FERNET achieves stress prediction accuracies of 98.17%, 90.16% and 84.49% for CK + , FER2013 and AffectNet datasets, respectively. [ABSTRACT FROM AUTHOR]

For many decades, uracil has been an antineoplastic agent used in combination with tegafur to treat various human cancers, including breast, prostate, and liver cancer. Therefore, it is necessary to explore the molecular features of uracil and its derivatives. Herein, the molecule's 5-hydroxymethyluracil has been thoroughly characterized by NMR, UV–Vis, and FT-IR spectroscopy by means of experimental and theoretical analysis. Density functional theory (DFT) using the B3LYP method at 6-311++G(d,p) was computed to achieve the optimized geometric parameters of the molecule in the ground state. For further investigation and computation of the NLO, NBO, NHO analysis, and FMO, the improved geometrical parameters were utilized. The potential energy distribution was used to allocate the vibrational frequencies using the VEDA 4 program. The NBO study determined the relationship between the donor and acceptor. The molecule's charge distribution and reactive regions were highlighted using the MEP and Fukui functions. Maps of the hole and electron density distribution in the excited state were generated using the TD-DFT method and PCM solvent model in order to reveal electronic characteristics. The energies and diagrams for the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO) were also provided. The HOMO–LUMO band gap estimated the charge transport within the molecule. When examining the intermolecular interactions in 5-HMU, Hirshfeld surface analysis was used, and fingerprint plots were also produced. The molecular docking investigation involved docking 5-HMU with six different protein receptors. Molecular dynamic simulation has given a better idea of the binding of the ligand with protein. [ABSTRACT FROM AUTHOR]

Unlike the structure‐specific piezoelectric effect, flexoelectricity is a universal phenomenon that can offer a wide range of energy‐efficient, cost‐effective, mechano‐opto‐electro‐coupled applications. Even though the flexoelectric effect has been extensively studied at nanoscale, a fundamental, yet unresolved, the issue is how it can be exploited at larger scales for potential applications. Herein, the long‐range (>millimeter) stimulated and regulated impact of the localized inhomogeneous strain‐induced flexoelectric potential on centrosymmetric metal/titanium oxide heterojunction with nanoscale precision (≈5.8 nm) is demonstrated. The noticed phenomenon is attributed to the long‐range interaction between flexoelectric and build‐in potentials, which is further utilized to develop mechanically regulated (enhancement > 104%), self‐powered (i.e., 0 V), ultrafast (>10 million bits per second), and broadband (λ = 365–1720 nm) pyro‐photosensors having high responsivity (≈1.18 mA W−1). As prospective applications, proof‐of‐concept ultrafast night movement monitors (>720 km h−1), high‐performing stationery, and dynamic obstacle sensors with possible impact alerts are developed. These findings lay the groundwork for the micro‐to‐millimeter‐range flexo‐opto‐electrical coupling in centrosymmetric materials, which can have a wide variety of practical applications. [ABSTRACT FROM AUTHOR]

Phospholamban (PLN) is a major regulator of cardiac contractility, and human mutations in this gene give rise to inherited cardiomyopathies. The deletion of Arginine 14 is the most-prevalent cardiomyopathy-related mutation, and it has been linked to arrhythmogenesis and early death. Studies in PLN-humanized mutant mice indicated an increased propensity to arrhythmias, but the underlying cellular mechanisms associated with R14del-PLN cardiac dysfunction in the absence of any apparent structural remodeling remain unclear. The present study addressed the specific role of myofilaments in the setting of R14del-PLN and the long-term effects of R14del-PLN in the heart. Maximal force was depressed in skinned cardiomyocytes from both left and right ventricles, but this effect was more pronounced in the right ventricle of R14del-PLN mice. In addition, the Ca2+ sensitivity of myofilaments was increased in both ventricles of mutant mice. However, the depressive effects of R14del-PLN on contractile parameters could be reversed with the positive inotropic drug omecamtiv mecarbil, a myosin activator. At 12 months of age, corresponding to the mean symptomatic age of R14del-PLN patients, contractile parameters and Ca2+ transients were significantly depressed in the right ventricular R14del-PLN cardiomyocytes. Echocardiography did not reveal any alterations in cardiac function or remodeling, although histological and electron microscopy analyses indicated subtle alterations in mutant hearts. These findings suggest that both aberrant myocyte calcium cycling and aberrant contractility remain specific to the right ventricle in the long term. In addition, altered myofilament activity is an early characteristic of R14del-PLN mutant hearts and the positive inotropic drug omecamtiv mecarbil may be beneficial in treating R14del-PLN cardiomyopathy. [ABSTRACT FROM AUTHOR]

Fractal interpolation is a contemporary technique to approximate numerous scientific experiments and natural phenomena. For data sets in ℝ 2 , the simplest and easy-to-handle fractal interpolation functions (FIFs) are linear. In this study, we estimate probability distributions of linear FIFs for data sets with various types of random noise. In order to evaluate the distribution of any linear FIF associated with a prescribed data set having Student's t-distributed noise, we develop a technique to approximate the distribution of a linear combination of independent generalized Student's t-distributed random variables. In addition, we provide some statistical properties and numerical approximations of these linear fractal functions. [ABSTRACT FROM AUTHOR]

The wearable healthcare equipment is primarily designed to alert patients of any specific health conditions or to act as a useful tool for treatment or follow-up. With the growth of technologies and connectivity, the security of these devices has become a growing concern. The lack of security awareness amongst novice users and the risk of several intermediary attacks for accessing health information severely endangers the use of IoT-enabled healthcare systems. In this paper, a blockchain-based secure data storage system is proposed along with a user authentication and health status prediction system. Firstly, this work utilizes reversed public-private keys combined Rivest–Shamir–Adleman (RP2-RSA) algorithm for providing security. Secondly, feature selection is completed by employing the correlation factor-induced salp swarm optimization algorithm (CF-SSOA). Finally, health status classification is performed using advanced weight initialization adapted SignReLU activation function-based artificial neural network (ASR-ANN) which classifies the status as normal and abnormal. Meanwhile, the abnormal measures are stored in the corresponding patient blockchain. Here, blockchain technology is used to store medical data securely for further analysis. The proposed model has achieved an accuracy of 95.893% and is validated by comparing it with other baseline techniques. On the security front, the proposed RP2-RSA attains a 96.123% security level. [ABSTRACT FROM AUTHOR]

Severe contrast degradation in an image result in a substantial loss of crucial visible information. A novel unsupervised image enhancement algorithm is proposed in this paper to unravel hidden visual details in perceptually invisible images. In this paper, new algorithms are designed to solve the range localization problem. The proposed algorithm intends to expand the image range to maximize its intensity level utilization. Outliers present in an image intensity range are truncated based on their power distribution. Based on the type of input image, maxima-minima, or frequency-based expansion of truncated levels, is exercised to avoid over-enhancement. Two novel parameters, namely the transmission map and zero-frequency spread, are coined. The visually enhanced result successfully exhibits the camouflaged information and avoids over-enhancement. Consumer gadgets, such as cameras, have difficulty taking pictures in very dark and cloudy settings. The suggested algorithm can improve low-contrast photos that are both very dark and severely attenuated. The unsupervised nature of the proposed algorithm makes it suitable for application in the field of consumer electronics like mobile phones and digital cameras. A consumer-focused, platform-independent app is created and made available to the general public for additional study. [ABSTRACT FROM AUTHOR]

Backgroud: Hyperhomocysteinemia (HHcy) is implicated in various neurovascular disorders including vascular dementia, subarachnoid hemorrhage and stroke. Elevated homocysteine (Hcy) levels are associated with increased oxidative stress and compromised blood–brain barrier (BBB) integrity. Hydrogen sulfide (H2S) has recently emerged as potent neuroprotective molecule in various neurological conditions including those associated with HHcy. The present study evaluates the protective effect of sodium hydrogen sulfide (NaHS; a source of H2S) on HHcy-induced BBB dysfunction and underpin molecular mechanisms. Materials and methods: Supplementation of NaHS restored the increased BBB permeability in the cortex and hippocampus of HHcy animals assessed in terms of diffused sodium fluorescein and Evans blue tracer dyes in the brain. Activity of matrix metalloproteinases (MMPs) assessed by gelatinase activity and in situ gelatinase assay was restored to the normal in the cortex and hippocampus of HHcy animals supplemented with NaHS. Results: Application of gelatin zymography revealed that specifically MMP-9 activity was increased in the cortex and hippocampus of HHcy animals, which was inhibited by NaHS supplementation. Real-time RT-PCR analysis showed that NaHS administration also decreased mRNA expression of MMP-9 in the hippocampus of HHcy animals. NaHS supplementation was further observed to reduce water retention in the brain regions of Hcy treated animals. Conclusion: Taken together, these findings suggest that NaHS supplementation ameliorates HHcy-induced BBB permeability and brain edema by inhibiting the mRNA expression and activity of MMP-9. Therefore, H2S and H2S releasing drugs may be used as a novel therapeutic approach to treat HHcy-associated neurovascular disorders. [ABSTRACT FROM AUTHOR]

Multi-feature based nano- (and micro-) materials are highly promising candidates for mechanical energy harvesting. The impregnation of the nanocrystals in a polymer matrix modifies the electrical characteristics of a composite film; in consequence, it becomes a multifunctional composite membrane. Herein, we report cuboctahedron zinc ferrite (ZnFe2O4) microparticles in a polydimethylsiloxane (PDMS) (ZnFe2O4@PDMS)-based composite film for mechanical energy harvesting. Several composite films are prepared at different thicknesses and weight percentages (wt%). The composite film having a thickness of 750 μm and 4 wt% generates a maximum open-circuit voltage (Voc), short-circuit current (Isc) and power of 60 V, 7.4 μA and 97 μW, respectively, by applying the contact-and-separation mode of a triboelectric nanogenerator. In addition, the film generates non-separation Voc of 800 mV and Isc of 580 nA. Eventually, the composite films were employed for tactile sensing applications. Versatile property-based ZnFe2O4@PDMS films can be further explored for hybrid device applications also. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to develop a computational approach to analyze the mechanical behavior, perfusion bioreactor test and degradation of the designed scaffolds. Five types of pore architecture scaffolds have been made using a computer-aided designed tool and fabricated through fused deposition modeling. Design/methodology/approach: Compressive structural analysis has been performed using the finite element method to forecast the mechanical performance of the scaffolds. Also, the experimental study was done to validate the simulation outcomes. A computational fluid dynamic analysis was performed to ascertain the fluid pressure distribution, velocity profile, wall shear stress, strain rate and permeability of scaffolds. The interconnected pore architecture of the scaffolds plays a crucial role in enhancing the mechanical properties and fluid flow characteristics. Findings: The scaffolds with continuous vertical support columns resulted in better strength because they provide better ways to transfer the load. The pore architecture of the scaffold plays a significant role in the path of fluid flow. Scaffolds with regular interconnected pore architecture showed better accessibility of the fluid. The degradation analysis showed that the degradation rate is dependent on the architecture of the scaffolds because of different surface area to volume ratios. Originality/value: The simulation results provide a straightforward prediction of the scaffold suitability in terms of mechanical strength, perfusion and degradation behavior. [ABSTRACT FROM AUTHOR]

Hydrogen production through solar-driven water splitting is a promising approach and an alternative to the conventional steam reforming of natural gas and coal gasification. The growing energy demand and environmental degradation through carbon-emitting fossil fuels urge a transition in the usage of non-renewable to renewable sources of energy. The photocathodes in a photoelectrochemical (PEC) water-splitting cell are essential for the direct evolution of hydrogen. Among the known photocathodes, Cu-based p-type semiconducting materials are the most promising photo-absorber materials owing to their low-cost, low toxicity, natural abundance, suitable bandgaps, and favorable band edges for reduction. Moreover, the chemical stability and the rate of recombination significantly limit the longevity, the PEC performance, and practical applicability of Cu-based photocathodes. To overcome these problems, it is critical to have a thorough understanding of the constraints, improvement strategies, and an assessment of current developments in order to construct and design highly stable and efficient photocathodes. Here, in this review we have summarized the development of Cu-based metal oxide and sulfide photocathodes with the significant operational challenges and strategies that have successfully been employed to enhance the PEC performance. Furthermore, the emphasis is placed on recent reports and future perspectives regarding emerging challenges. [ABSTRACT FROM AUTHOR]

The development of efficient and novel p-n heterojunctions for photoelectrochemical (PEC) water splitting is still a challenging problem. We have demonstrated the complementary nature of (p-type) BiSbS3 as a sensitizer when coupled with (n-type) TiO2/CdS to improve the photocatalytic activity and solar to hydrogen conversion efficiency. The as-prepared p-n heterojunction TiO2/CdS/BiSbS3 exhibits good visible light harvesting capacity and high charge separation over the binary heterojunction, which are confirmed by photoluminescence (PL) and electrical impedance spectroscopy (EIS). The ternary heterojunction produces higher H2 than the binary systems TiO2/CdS and TiO2/BiSbS3. This ternary heterojunction system displayed the highest photocurrent density of 5 mA·cm−2 at 1.23 V vs. reversible hydrogen electrode (RHE) in neutral conditions, and STH of 3.8% at 0.52 V vs. RHE is observed. The improved photocatalytic response was due to the favorable energy band positions of CdS and BiSbS3. This study highlights the p-n junction made up of TiO2/CdS/BiSbS3, which promises efficient charge formation, separation, and suppression of charge recombination for improved PEC water splitting efficiency. Further, no appreciable loss of activity was observed for the photoanode over 2500 s. Band alignment and interfaces mechanisms have been studied as well. [ABSTRACT FROM AUTHOR]

In the last few years, many controllability results have been developed for different semilinear control systems of fractional order. In this article. a set of new sufficient conditions is established for the existence of solutions and controllability for a class of fractional order semilinear integrodifferential (FOSI) control systems involve nonlocal initial conditions. The main advantage of the present study is that. the assumption of compactness on semigroup is to be relaxed in order to obtain the required results. The feasibility of these abstract results is illustrated by an example. [ABSTRACT FROM AUTHOR]

Nonparametric approaches are a good choice for function approximation as they are flexible, robust to overfitting, and provide well calibrated predictive uncertainty. The nonparametric form of fuzzy modeling can be promising, however, not analytically studied to compete with the Gaussian processes-based Bayesian framework in statistics and machine learning. In this work, a fuzzy modeling framework is built for data analysis of both supervised and unsupervised learning task, as a deterministic fuzzy analogous against the probabilistic Gaussian process, which defines a fuzzy membership over possible membership functions and is updated in light of data via the rules of variational inference. A fast variational inference framework has been suggested to study the propagation of the uncertainty through the layers of the deep model which can jointly infers the inducing inputs and the hyperparameters. The maximization problem is analytically solved using variational optimization with derived lower bound. We provide the sufficient number of experiments to support our argument that the proposed approach works well in practice for the problem which has the requirements to update the model dynamically. In addition, the application potential of the proposed methodology in data representation learning is also investigated, the "auxiliary inducing points" are used to express general features of tasks with smaller datasets. Nevertheless, this study offers new contents to the theory of nonparametric model and presents the potential for the design of practical fuzzy machine learning method. [ABSTRACT FROM AUTHOR]

The aim of this work is to develop Merkfree—a mercury-free sphygmomanometer that looks, feels, and operates just like a traditional mercury sphygmomanometer (MS). For this we use Galinstan as a substitute for mercury, which is a non-toxic alloy of Gallium, Indium and Tin. Galinstan is nearly half as dense as mercury and sticks to class. To work with the lower density, we designed an enclosure and scale that is nearly double the length of MS. The issue of stickiness with glass was resolved by maintaining a small meniscus of a reducing agent in the measuring tube and tank of Merkfree. Clinical trials to validate the accuracy of Merkfree against MS and oscillometric sphygmomanometer (OS) were conducted over 252 patients. The results show a good correlation of the systolic and diastolic BP measurements from Merkfree with respect to MS and the OS. The mean absolute percentage error is less than 10% for both SBP and DBP. We also found that Merkfree has lower rounding-off errors compared to MS. Merkfree can be a viable alternative to mercury sphygmomanometer that can help achieve the goal of WHO in eliminating mercury from healthcare, while simultaneously making sure that gold standard technique of sphygmomanometry continues to be available to the clinicians. [ABSTRACT FROM AUTHOR]

Let R be a commutative ring with identity and let I be a proper ideal of R. In this paper, we study the ideal based extended zero-divisor graph Γ′I(R) and prove that Γ′I(R) is connected with diameter at most two and if Γ′I(R) contains a cycle, then girth is at most four girth at most four. Furthermore, we study affinity the connection between the ideal based extended zero-divisor graph Γ′I(R) and the ideal-based zero-divisor graph ΓI (R) associated with the ideal I of R. Among the other things, for a radical ideal of a ring R, we show that the ideal-based extended zero-divisor graph Γ′I(R) is identical to the ideal-based zero-divisor graph ΓI (R) if and only if R has exactly two minimal prime-ideals which contain I. [ABSTRACT FROM AUTHOR]