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The increasing number of IoT devices has led to more electronic waste production, which harms the environment and human health. Self-powered sensor systems are a solution, but they often use toxic materials. We propose using biocompatible peanut skin as the active material for a self-powered humidity sensor (PSP-SPHS) through integration with a peanut-skin-based triboelectric nanogenerator (PSP-TENG). The PSP-TENG was characterized electrically and showed promising results, including an open circuit voltage (162 V), short circuit current (0.2 µA), and instantaneous power (2.2 mW) at a loading resistance of 20 MΩ. Peanut skin is a great choice for the sensor due to its porous surface, large surface area, eco-friendliness, and affordability. PSP-TENG was further used as a power source for the PSP-humidity sensor. PSP-SPHS worked as a humidity-dependent resistor, whose resistance decreased with increasing relative humidity (%RH), which further resulted in decreasing voltage across the humidity sensor. This proposed PSP-SPHS exhibited a good sensitivity (0.8 V/RH%), fast response/recovery time (4/10 s), along with excellent stability and repeatability, making it a potential candidate for self-powered humidity sensor technology. [ABSTRACT FROM AUTHOR]

Background Aims and methods Results Conclusions The application of nanoparticles (NPs) in horticultural crops is in a tremendous increase. NPs help in the overcoming of stresses with positive impacts on plant growth and development. Silver NPs (AgNPs) have numerous pre‐ and postharvest applications in agriculture.This study aimed to evaluate the effect of AgNPs application (0, 50, 100, 150, and 200 ppm) at three spray intervals (5, 10, and 15 days) on the morphological and compositional traits, and defense system of strawberry.Results showed that AgNPs application enhanced the growth, yield, quality, and nutritional aspects of strawberry grown under field conditions. Shoot fresh weight (20.20 g) and leaf number/plant (41.53) were enhanced at 100 ppm AgNPs and 15 days interval. A stunted growth of strawberry plants was recorded at 200 ppm AgNPs. Moreover, a 15‐day‐spray interval was found optimum for the improvement of major morphological traits. Fruit size, yield, total soluble solids, acidity, and antioxidant capacity were improved at 50 and 100 ppm AgNPs. The activation of plant defense system, that is, superoxide dismutase, peroxidase, catalase, total soluble protein, and ascorbic acid was improved under AgNPs foliar application. The activation of stress indicating marker malondialdehyde outlined a high defense response of strawberry at 150 ppm AgNPs.Conclusively, AgNPs application at 50, 100, and 150 ppm can be considered effective for sustainable strawberry production. [ABSTRACT FROM AUTHOR]

Magnesium alloys are promising materials for bioresorbable implants that will improve patient life and reduce healthcare costs. However, their clinical use is prevented by the rapid degradation and corrosion of magnesium, which leads to a fast loss of mechanical strength and the formation of by-products that can trigger tissue inflammation. Here, a tannic acid coating is proposed to control the degradation of AZ31 and AZ91 alloys, starting from a previous study by the authors on AZ91. The coatings on the two materials were characterized both by the chemical (EDS, FTIR, XPS) and the morphological (SEM, confocal profilometry) point of view. Static degradation tests in PBS and electrochemical measurements in different solutions showed that the protective performances of the tannic acid coatings are strongly affected by the presence of cracks. The presence of fractures in the protective layer generates galvanic couples between the coating scales and the metal, worsening the corrosion resistance. Although degradation control was not achieved, useful insights on the degradation mechanisms of coated Mg surfaces were obtained, as well as key points for future studies: it resulted that the absence of cracks in protective coatings is of uttermost importance for novel biodegradable implants with proper degradation kinetics. [ABSTRACT FROM AUTHOR]

Machine learning (ML) analysis has gained huge importance among researchers for predicting multiple parameters and designing efficient donor and acceptor materials without experimentation. Data are collected from literature and subsequently used for predicting impactful properties of organic solar cells such as power conversion efficiency (PCE) and energy levels (HOMO/LUMO). Importantly, out of various tested models, hist gradient boosting (HGB) and the light gradient boosting (LGBM) regression models revealed better predictive capabilities. To achieve the prediction effectively, the selected (best) ML regression models are further tuned. For the prediction of PCE (test set), the LGBM shows the coefficient of determination (R2) value of 0.787, which is higher than HGB (R2 = 0.680). For the prediction of HOMO (test set), the LGBM shows R2 value of 0.566, which is higher than HGB (R2 = 0.563). However, for the prediction of LUMO (test set), the LGBM shows R2 value of 0.605, which is lower than HGB (R2 = 0.606). Among the three predicted properties, prediction ability is higher for PCE. These models help to predict the efficient acceptors in a short time and less computational cost. [ABSTRACT FROM AUTHOR]

Organic molecules have been extensively utilized in various applications including materials science, chemical, and biomedical fields. Traditionally, the design of organic molecules is achieved through experimental approaches, guided by conceptual insights, intuition, and experience. Although these experimental approaches have been successfully utilized to unveil various high‐performance materials, these methods show serious limitations due to vast design space and the ever‐increasing demand for organic molecules (new materials). Artificial intelligence with computer science is used by modern researchers to design materials with better performance and for predicting the properties of new materials. Herein, benzofuran‐based building blocks are used as a standard molecule to search for new building blocks. Similarity analysis is performed to screen/search potential candidates for photodetectors based on the chemical structural similarity. Extended‐connectivity fingerprints (ECFPs) are used for the similarity analysis. The virtual libraries of unique monomers are enumerated. The breaking retro‐synthetically interesting chemical substructures (BRICS) method is also used to design building blocks by automatically decomposing and combining monomers in enumerated libraries. Moreover, this work offers a potential way to identify new monomers for photodetectors cost‐effectively and rapidly. [ABSTRACT FROM AUTHOR]

Context: Selecting high performance polymer materials for organic solar cells (OSCs) remains a compelling goal to improve device morphology, stability, and efficiency. To achieve these goals, machine learning has been reported as a powerful set of algorithms/techniques to solve complex problems and help/guide exploratory researchers to screen, map, and develop high performance materials. In present work, we have applied machine learning tools to screen data from reported studies and designed new polymer acceptor materials, respectively. Quantitative structure-activity relationship (QSAR) models were generated using machine learning-assisted simulation techniques. For this purpose, 3000 molecular descriptors are generated. Consequently, molecular descriptors having key effect on power conversion efficiency (PCE) were identified. Moreover, numerous regression models (e.g., random forest and bagging regressor models) were developed to predict the PCE. In particular, new materials were designed based on the similarity analysis. The GDB17 chemical database consisting of 166 million organic molecules in an ordered form is used for performing similarity analysis. A similarity behavior between GDB17 materials and the materials reported in literature is studied using RDKit (a cheminformatics software). Noteworthily, 100 monomers proved to be unique and effective, and PCEs of these monomers are predicted. Among these monomers, four monomers exhibited PCE higher than 14%, which is better than various reported studies. Our methodology provides a unique, time- and cost-efficient approach to screening and designing new polymers for OSCs using similarity analysis without revisiting the reported studies. Methods: To perform machine learning analysis, data from reported studies and online databases was collected. Different molecular descriptors were generated for polymer materials utilizing Dragon software. 3D structures of studied molecules were applied as input (SDF; structure data file format). Importantly, about 3000 molecular descriptors were generated. Comma-separated value (.csv) file format was used to export these molecular descriptors. To shortlist best descriptors, univariate regression analysis was performed. These descriptors were further utilized for training machine learning models. Moreover, necessary packages of Python for data analysis and visualization were imported such as Matplotlib, Numpy, Pandas, Scikit-learn, Seaborn, and Scipy. Random forest and bagging regressor models were applied for performing machine learning analysis. A cheminformatics software, RDKit, was applied for similarity analysis. [ABSTRACT FROM AUTHOR]

Contamination by heavy metals has severely hampered agricultural productivity across the world. Cadmium (Cd) is one of the most dangerous heavy metals to plants. Melatonin (ME), a stress-relief hormone, has been extensively utilized to reduce phytotoxicity caused by heavy metals. In this work, we examined how ME reduced Cd damage in strawberry seedlings. The results revealed that Cd stress dramatically reduced growth characteristics (fresh and dry weight, root and shoot length), leaf gas exchange elements, and pigments content (chlorophyll a and chlorophyll b) in strawberry seedlings. In contrast, ME application efficiently enhanced growth and biomass production, increased net photosynthetic rate, and improved pigments molecules in strawberry seedling under Cd toxicity. Cadmium treatment effectively improved the level of malondialdehyde (MDA) and hydrogen peroxide (H 2 O 2), whereas ME strictly counterbalanced these oxidative stress markers. Furthermore, the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), were dominantly increased by ME. Additionally, ME supplementation significantly improved secondary metabolites (phenols, anthocyanin, and flavonoids) content, and these metabolites potentially restricted excess H 2 O 2 accumulation. In conclusion, our results revealed that ME might help to reduce Cd-induced phytotoxicity in strawberry seedlings by increasing growth, photosynthesis, redox homeostasis, and secondary metabolites. [Display omitted] • Melatonin enhanced cadmium stress tolerance in strawberry plants. • Melatonin stimulates antioxidant defense system in strawberry seedling under cadmium toxicity. • Melatonin increased photosynthesis apparatus in cadmium-stressed strawberry plants. • Melatonin as a supplement regulates defense mechanism in strawberry under cadmium stress. [ABSTRACT FROM AUTHOR]

Background: In arid and semiarid countries, grain yield of maize is increasingly impaired by soil salinity. Beside soil amelioration, the development of salt‐resistant cultivars is a possibility to enhance crop yield on salt‐affected soils. Aims: This study aimed at testing yield performance in the field of salt‐resistant maize hybrids on a salt‐affected soil. In addition, planting density was optimized under the saline conditions. Methods: Four salt‐resistant maize hybrids (Zea mays L. SR‐05, SR‐12, SR‐15, and SR‐16) were grown under control (EC = 2.0–2.5 dS m−1) and saline (EC = 10.0–12.0 dS m−1) field conditions and compared to the salt‐sensitive maize cv. Pioneer‐3906. Planting density (5, 8, or 11 plants m−2) was optimized for saline soil conditions for SR‐12 and the local hybrid EV‐78. Results: Yield of Pioneer‐3906 was significantly reduced under salinity because of inhibited kernel setting, whereas the SR hybrids showed no decrease in grain yield. Based on grain yield, the optimum planting density was 8 plants m−2 with no further increase with 11 plants m−2. In contrast to SR‐12, for cv. EV‐78 no increase of harvest index with 8 relative to 5 plants m−2 was observed. Conclusions: Vegetative growth of Pioneer‐3906 and the SR hybrids was decreased due to Phase‐I effects but neither due to water deficiency nor ion toxicity. The experiment corroborated the salt resistance of the SR hybrids under field conditions. Under saline conditions, optimum planting density of salt‐resistant cultivars may be higher than under nonsaline conditions when sufficient water supply by artificial irrigation is guaranteed. [ABSTRACT FROM AUTHOR]

Electrochemiluminescence (ECL) has emerged as a powerful tool in bioassays due to its unique versatility and controllability, but it is still a challenge to amplify ECL signals without utilizing complex synthetic processes, sophisticated nanomaterials, and catalysts. Herein, a new ECL system with high sensitivity and selectivity is reported for the detection of amisulpride (AMS). The AMS was beneficial for enhancing the weak ECL emission of luminol, wherein co‐reaction effect of AMS promoted the generation of superoxide anion radicals (O2⋅−), which significantly improved the ECL efficiency of luminol (emitter). Under the optimized experimental conditions, this anodic ECL system achieved AMS detection (a biphasic curve) with linear concentration ranges of 0.2–5.0 μm and 5.0–100.0 μm. Impressively, the developed system exhibited a low limit of detection (LOD) and quantification (LOQ) of 10.2 nm and 50.5 nm for AMS, respectively. This luminol‐based ECL system is further applied for sensitive AMS detection in real (bulk) drug and pharmaceutical tablet form. Moreover, statistical comparison between the developed and comparison method showed good precision and accuracy of the developed method. [ABSTRACT FROM AUTHOR]

The principle goal of the paper is to present proficient limited contrast finite difference schemes to execute on the nonlinear coupled partial differential system which emulate the overseeing differential framework. In this paper, more consideration is given to the exactness and security of the proposed numerical schemes by review consistency and union of the arrangement which can be seen from figures and information tables. For the nonlinear differential system, mesh independent results are expensive which are accommodated by the generation of block tridiagonal matrix structures (inherent properties of schemes) which are measured in terms of L 2 & L ∞ norms which lead to a superb concurrence with the investigative arrangement. [ABSTRACT FROM AUTHOR]

The probability model 'Power Lomax Geometric Distribution' proposed in this paper is derived from Power Lomax distribution through its compounding with the Geometric distribution. We present its various theoretical properties including hazard function, mean residual life and entropy. The family of this distribution constitutes heterogeneous characteristics, and is so classified into three distinguishable subfamilies. Each subfamily is unique in its importance with respect to theoretical and practical applications. The ML method is used for the estimation of four parameters of this distribution. To assess its adequacy we consider four real life data sets comparing it with other fitted models in literature. The model is flexible in its applicability to a large number of different situations. [ABSTRACT FROM AUTHOR]

Nitrogen is the most important and widely applied nutrient in sweet pepper production as it improves vegetative growth as well as fruit production. Therefore, the present research was aimed to evaluate promising sweet pepper cultivars as a function of different nitrogen fertilizer levels for semi-arid conditions of Pakistan during 2018 and 2019. Four nitrogen levels (75, 100, 125 and 150 kgha−1) and three sweet pepper cultivars (Ganga, Winner and Savio) were adopted in this study. Vegetative growth as well yield attributes were found highest during the cropping season of 2019 as compared with 2018. Plant height, stem diameter, canopy diameter, fresh and dry biomass of sweet pepper enhanced by the increased application of nitrogen from 75 to 125 kgha−1. All the yield contributing traits including number of fruits per plant, fruit fresh weight per plant and fruit yield per hectare were found the highest with nitrogen application of 150 kgha−1. In most of the crop traits, application of 125 kg Nha−1 and 150 kg Nha−1 produced statistically similar results. Cultivars respond differently to the nitrogen application. Ganga and Savio behaved similarly in response to nitrogen application. They had a quadratic response to nitrogen application; maximum growth and yield were at 125 kg Nha−1 and then decreased at 150 kg Nha−1. In contrast, Winner showed a somewhat linear response to nitrogen application and maximum growth, biomass and yield were recorded at 150 kg Nha−1. Planting a pepper cultivar with improved nitrogen use efficiency can result in maximum yield in a semi-arid region. [ABSTRACT FROM AUTHOR]

Simple Summary: An increase in the pulsatile release of gonadotropin-releasing hormone (GnRH) is essential for the onset of puberty. However, the mechanisms controlling pubertal increases in GnRH release are still unclear. In primates the GnRH neurosecretory system is active during the neonatal period but subsequently enters a dormant state in the juvenile period. The present study examined developmental changes in the gonadotropin inhibitory hormone (GnIH) neuronal system, an inhibitory neuropeptidergic system upstream of GnRH neurons, and the relationship among changes that were observed in GnRH and kisspeptin (Kiss1) gene expression during puberty. A significant inverse age-related relationship between GnRH, Kiss1, and GnIH was observed, suggesting GnIH's potential role in reproductive suppression prior to puberty, with this theoretical 'brake' during the pubertal transition. These findings underscore the need for further research on the role that is played by GnIH in reproductive transition to aid in the development of potential GnIH-based drugs to treat pubertal disorders and adult fertility. Modulation of pulsatile gonadotropin-releasing hormone (GnRH) secretion across postnatal development in higher primates is not fully understood. While gonadotropin-inhibitory hormone (GnIH) is reported to suppress reproductive axis activity in birds and rodents, little is known about the developmental trajectory of GnIH expression in rhesus monkeys throughout the pubertal transition. This study was aimed at examining the variation in GnIH immunoreactivity (-ir) and associated changes among GnIH, GnRH, and Kiss1 mRNA expression in the hypothalamus of infant, juvenile, prepubertal, and adult male rhesus monkeys. The brains from rhesus macaques were collected from infancy until adulthood and were examined using immunofluorescence and RT-qPCR. The mean GnIH-ir was found to be significantly higher in prepubertal animals (p < 0.01) compared to infants, and significantly reduced in adults (p < 0.001). Significantly higher (p < 0.001) GnRH and Kiss1 mRNA expression was noted in adults while GnIH mRNA expression was the highest at the prepubertal stage (p < 0.001). Significant negative correlations were seen between GnIH-GnRH (p < 0.01) and GnIH-Kiss1 (p < 0.001) expression. Our findings suggest a role for GnIH in the prepubertal suppression of the reproductive axis, with disinhibition of the adult reproductive axis occurring through decreases in GnIH. This pattern of expression suggests that GnIH may be a viable target for the development of novel therapeutics and contraceptives for humans. [ABSTRACT FROM AUTHOR]

Multilevel inverters are one of the important components of modern smart grids and the grid integration of renewable energy sources is not possible without them. In this paper, an asymmetrical switch ladder multilevel inverter (ASLMLI) topology is used to develop a 17-level inverter. The switching pulses for the proposed inverter are developed efficiently using a binary search algorithm based on the grid voltage as a reference. A graphical user interface (GUI) based power quality monitoring system is also developed that senses the grid signals accurately to serve them as a reference for grid integration purposes. The loss and efficiency analysis of the ASLMLI is carried out in the form of generic design equations. A comparative study shows the effectiveness of the proposed system in terms of the accuracy of power quality monitoring. The simulation of the ASLMLI is carried out in MATLAB/Simulink, and the power quality monitoring system is developed using a data acquisition card (DAC) and National Instruments (NI) LABVIEW GUI. [ABSTRACT FROM AUTHOR]

The potential of a partial differential equations model is to anticipate its computational behavior. The simulation of a transient 3D coupled convection–diffusion system using a numerical model is described. The main objective of this article is to offer effective limited contrast compact finite difference techniques for use with nonlinear coupled partial differential systems that mimic overseeing differential frameworks. The three-dimensional compact finite difference formulation serves as the model's foundation. An analytical model has been used to validate finite difference techniques that are numerically compact. By examining the consistency and union of the arrangement, which may be seen from figures and information tables, we can evaluate the model and the suggested numerical schemes. The schemes are unconditionally stable and accurate up to two orders in time and six orders in space, according to the results of the stability and accuracy tests. The implicit method used in the algorithm's design was examined for stability criteria. Because mesh-independent solutions for non-linear differential systems are expensive, block tridiagonal matrix structures, measured in terms of L2 and L∞ norms, which are inherent characteristics of schemes and have excellent agreement with the investigation arrangement, are created. [ABSTRACT FROM AUTHOR]

[Display omitted] • Machine learning assisted approach is used to design new organic semiconductors for organic photodetectors. • Machine learning tools are applied to predict the reorganization energy of organic semiconductors. • The chemical similarity analysis using clustering and heatmap is done for selected organic semiconductors. • Synthetic accessibility score is calculated and majority of semiconductors are easy to synthesize. Quantum chemical calculations have been widely utilized to design and explore organic semi-conductors for various photovoltaics applications. Photovoltaic devices such as photodetectors work on the principle of photo-electric-effect and widely used for optical communications. In recent years, machine learning has become famous in many research fields. In present study, we have predicted reorganization energy of organic semi-conductors with the aid of machine learning. Statistical analysis is used to select best molecular descriptors (features). About 10 machine learning models are tested for selecting the best one. Among various tested models, gradient forest regressor and random forest regressor are the top models. By using our new designing approach, easy to synthesize building blocks are connected to design new organic semiconductors. Their reorganization energies are predicted using fast machine learning method. For this purpose, already trained and hyper parameter optimized gradient boosting regressor is used. It is generally accepted that to obtain higher charge mobility molecules should have lower reorganization energy. Ten organic semi-conductors with lower reorganization energy are selected for density functional calculations and their energy levels are calculated. The chemical similarity analysis using clustering and heatmap is also done for selected organic semi-conductors. Synthetic accessibility score is calculated and majority of semi-conductors are easy to synthesize. These molecules are potential candidates for device fabrication. The proposed python-based pipeline has ability to select the molecules for organic photodetectors in fast and cheaper way. [ABSTRACT FROM AUTHOR]

The technology of modern power systems is revolutionizing as renewable energy sources are being integrated with electric power grids. In the form of inverters, power electronic converters are becoming an integral part of power systems due to their massive demand for grid integration of photovoltaic (PV) systems. Existing multilevel inverter topologies either require an output filter to get a sinusoidal voltage or generate a higher number of output voltage levels at the expense of many hardware resources. This paper presents a new single-phase 81-level inverter configuration with the name given as 'Modified W-Type Multilevel Inverter'. The proposed inverter configuration uses only eighteen power switches and four DC voltage sources to generate an 81-level output voltage approaching a sinusoidal waveform without an output filter. The general design equations are developed to calculate the number of switches, the number of voltage levels, and the number of DC sources for the proposed configuration. Loss and efficiency analysis is carried out that verifies a good practical efficiency of the proposed inverter configuration during the dynamic operation. A comparative analysis with the existing MLI topologies is also carried out that validates the effectiveness and novelty in reducing parts count and higher number of voltage levels. The proposed topology offers 1.04% total harmonic distortion of the output voltage which is within the benchmarks specified for grid integration without any filter requirements. The proposed inverter configuration is simulated in MATLAB/Simulink, and the results are validated by the design and development of a hardware prototype. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the metabolic status, stress and ovarian activity through progesterone profile in dairy buffalo as influenced by post‐partum days, body condition score (BCS) and lactation number. A total of 45 dairy buffaloes were involved and divided into three factors based on their BCS (2.5, 3.0 and 3.5, respectively), lactation number (1, 2 and 3, respectively), and post‐partum intervals (14, 28, 42 and 56, respectively). Based on findings, from day 14 to day 56 after parturition, blood glucose, cholesterol and triglyceride levels increased significantly (p <.01), while malondialdehyde (MDA) and cortisol levels decreased significantly (p <.05) on day 56 of the trial. With increased BCS levels, milk yield, blood metabolites and progesterone improved significantly (p <.05), whereas stress indicators decreased significantly (p <.01). Blood metabolites, progesterone and milk production were significantly (p <.01) higher and stress indicators (MDA and cortisol) were significantly (p <.01) lower in lactation stage. Buffaloes with a greater lactation stage and growing post‐partum stage had better blood metabolite and progesterone concentrations and less stress. It was concluded that better BCS and increased lactation stage have significant impact on milk yield, stress reduction and restoration of ovarian activity in buffaloes during post‐partum period. [ABSTRACT FROM AUTHOR]

This study surveyed the existence of the Coxiella burnetii in ticks removed from camels in three different regions of the Punjab, Pakistan. A total of 325 ixodid ticks were analyzed for the occurrence of C. burnetii DNA by real-time polymerase chain reaction. Before analyses, all ticks were pooled into 30, 20 and 15 pools from Southern, Northern and Central Punjab, correspondingly. Each pool was comprised of five engorged or semi-engorged ticks according to species. Pooled based prevalence in Southern Punjab was eighteen from 30 pools (60%), leading to maximum-likelihood of true prevalence of 0.56% (95% CI 0.23-1.31), while pooled prevalence in Northern Punjab was eight from 20 pools (40%), leading to maximumlikelihood of the true prevalence of 0.44% (95% CI 0.31-0.89) and none of the pooled samples from Central Punjab were found positive for C. burnetii. During classification of tick pools based on species, infection was diagnosed in 75% (09/12) of H. dromedary, 42.8% (03/07) of H. anatolicum, 50% (01/02) of H. scupense, 60% (03/05) of R. microplus, and 50% (02/04) of R. annulatus in Southern Punjab. In comparison, infection was detected in 37.5% (03/08) of H. dromedary, 23% (01/04) of H. anatolicum, 0% of H. scupense, 66.7% (02/03) of R. microplus and 66.7% (02/03) of R. annulatus in Northern region. The detection of C. burnetii implies important role of ticks in the dissemination of this bacterium in Punjab, Pakistan and reveals that ticks have a major contribution to the epidemiology of coxiellosis in this ecological system. These judgments warrant further molecular investigations for better perception about C. burnetii epidemiology and its contributions to humans and animal disease in Pakistan. [ABSTRACT FROM AUTHOR]

Maritime surveillance is essential in understanding, predicting, and ensuring the security of events in the complex marine environment. In this context, we have used instance segmentation techniques, which provides an accurate and efficient method for segmenting objects (Ships) in maritime surveillance. However, prevalent two-stage algorithms have limitations, including complex models, extended training time, and high memory consumption, making them impractical for real-world application. To address these challenges, we present an efficient solution called Multiscale Attention for Single-Stage Ship Instance Segmentation, or MASSNet. MASSNet uses the power of attention mechanisms to enhance multiscale feature extraction across various dimensions, resulting in a more refined and contextually-aware representation. This approach significantly improves segmentation accuracy and overall performance. In our extensive experiments, we evaluate the effectiveness of MASSNet on three challenging datasets: MariboatS, ShipInsSeg, and ShipSG. Our proposed model achieves mask Average Precision (mask AP) scores of 55.4%, 55.5%, and 74.1% on MariboatS, ShipInsSeg, and ShipSG datasets and outperforms other models such as YOLACT, SOLO and SOLOv2 architectures. MASSNet offers a robust and efficient solution for Ship Instance Segmentation, making significant improvement in the capabilities of maritime surveillance. [ABSTRACT FROM AUTHOR]

In current study, six novel selenopheno-thiophene (ST) core-based chromophores (SePTD1- SePTD6) with A-D-A configuration were designed via structural tailoring with terminal acceptors of SePTR. The optoelectronic and photovoltaic properties of SePTD1-SePTD6 were explored through TDDFT/DFT approaches. The B3LYP/6–31 G(d,p) level was chose through benchmarked study with the help of DFT and experimental UV-Vis values of SePTR. All tailored chromophores exhibited a comparatively smaller band gap (2.144–2.003 eV), along with a significant bathochromic shift (676.8–724.2 nm) and an increased rate of charge transference then reference chromophore (2.119 eV and 686.6 nm). Among all derivatives, SePTD2 exhibited some unique characteristics such as, least HOMO/LUMO energy gap (2.003 eV), highest absorption values (665.4 nm in gas and 724.2 nm in solvent), least binding energy (0.291 eV) and also significant value of open circuit voltage (1.860 V). The aforementioned findings suggest that employing molecular engineering with extended acceptors enhances the photovoltaic performance of non-fullerene materials, thereby encouraging experimentalists to develop highly efficient photovoltaic devices. • Designing of selenopheno thiophene core-based chromophores for OSCs. • Structural modeling with π -spacer and acceptor moieties. • Exploration of photovoltaic behavior of designed chromophores. • Study of key electronic properties at B3LYP/6–31 G(d,p) functional. • Utilization of TD-DFT approach for FMOs and UV-Vis analyses. [ABSTRACT FROM AUTHOR]

Bandgap is a key parameter for selecting suitable materials for a broad range of applications. Organic solar cells (OSCs) are emerging as powerful devices due to their low-cost solution processing. Developing OSCs necessitates producing effective materials in a computationally cost-effective and rapid manner. Machine learning has become popular and well-recognized among researchers to screen and design high performance materials for OSCs. Machine learning models require data from the literature (reported studies or databases) to effectively predict targeted properties. To unveil the hidden dataset patterns, a thorough data visualization analysis is conducted. Importantly, multiple database mining is performed for designing low band gap organic semiconductors. Molecular descriptors are utilized to train machine learning models. Importantly, about 22 different machine learning models are tested. Among all models, extra trees regressor shows higher predictive capability. Residuals, learning curve and validation curve are also drawn for extra trees regressor. Feature importance analysis determines the significance of the features. Moreover, library enumeration and similarity analysis further facilitate designing of high-performance semiconductor materials. This work may help in screening and designing efficient semiconductors having low band gap for increasing the efficiency of OSCs. [Display omitted] • Machine learning is applied to design new low band gap organic semi-conductors for OSCs. • Data mining and property prediction strategies are applied to screen potential candidates for OSCs. • The chemical similarity analysis and library enumeration techniques are performed. • More than >20 different regression models are developed and used for better prediction. [ABSTRACT FROM AUTHOR]

• Abiotic stress significantly impaired growth of vegetable crops. • Nickel toxicity hindered mineral nutrient accumulation in pepper crop. • Melatonin regulated nickel stress tolerance in pepper. • Melatonin reduced nickel accumulation in shoot. The excessive accumulation of nickel (Ni) poses a significant threat to global agricultural productivity. In recent years, it has become clear that melatonin (ME) may play a significant role in protecting plants against heavy metal toxicity. This current study investigates the influence of exogenous ME on mitigating the adverse effects of Ni toxicity in pepper plants. The present results revealed that Ni toxicity significantly hindered pepper seedling growth, damaged the leaf photosynthetic system, impaired pigment concentration, and increased phenolic content. In contrast, ME supplementation efficiently restored seedling growth, protected the photosynthetic system, and further increased the phenolic concentration in pepper leaves. In addition, Ni toxicity considerably increased malondialdehyde (MDA) and hydrogen peroxide (H 2 O 2) production and increased antioxidant enzymes [SOD (superoxide dismutase), CAT (catalase), POD (peroxidase), GR (glutathione reductase), APX (ascorbate peroxidase), and GST (glutathione S-transferase)] activity in pepper leaves and roots. Conversely, ME inhibited MDA and H 2 O 2 accumulation and further increased the antioxidant enzyme activity in pepper leaves and roots. Furthermore, ME application restricted Ni accumulation from root to shoot. Collectively, the ME has shown the ability to mitigate the adverse effects of Ni toxicity in pepper plants. The findings of this study will contribute to the understanding and mitigation of the adverse impacts of Ni-induced stress on the growth and development of plants. [Display omitted] [ABSTRACT FROM AUTHOR]

Objectives: The study was designed to estimate daily salt intake, its discretionary use in healthy individuals and to validate three common methods for salt estimation in Pakistani population. Methodology: Information on demography and discretionary salt use was collected from healthy adults (>18 years) along with a blood sample, spot and 24 hour urine samples. Sodium, chloride, potassium levels and serum creatinine were measured using standard methods. For daily salt estimation, three common methods i.e. INTERSALT, Tanaka and Kawasaki were validated for their applicability in local settings. Results: Overall 24 h sodium excretion was 158 mmol/l indicating intake of 8.64 (±4.43) grams salt per day which was significantly associated with male gender (p. <0.004) and adding salt during cooking (p. <0.0001). Most (73%) of the participants know about hazardous effects of high salt intake, however, only 25% consider important to lower salt intake. None of three methods i.e. INTERSALT (bias: -19.64; CCC -0.79), Tanaka (bias: 167.35; CCC -0.37) and Kawasaki (bias: -42.49, CCC -0.79) showed any agreement between measured and estimated 24 hour sodium. Conclusion: Daily intake of salt was high which increases the risk for hypertension. Comparison of methods for estimation revealed that none of the three methods could be used for estimating daily intake of salt in local settings of Pakistan. [ABSTRACT FROM AUTHOR]

Background: Maturity onset diabetes of the young (MODY) is the genetic form of diabetes inherited in autosomal dominant pattern. The diagnosis of MODY is challenging and confirmed by genetic testing. The objective of this study was to investigate MODY in Pakistani patients using next-generation sequencing. Methods: The next-generation sequencing was performed to know the cause of disease in 07 patients phenotypically suspected for MODY from Pakistan. These patients were selected based on the high probability score through MODY probability calculator. Only those genetic variants were retained which were having low frequency as per available data bases and their potential effects on protein as assessed by bioinformatics prediction tools. Results: Four heterozygous variants were found among patients. This includes mutation in HNF1a gene (c.526+1G>A) that is already reported for causative for MODY type 3 which is most prevalent among all MODY sub-types. Other variants were identified in GCK (c.-45G>A), KLF11 (c.*96dupA), and CEL (c.1235C>T). Conclusion: This study was the first in Pakistan to investigate the MODY using next-generation sequencing for clinical applications. There is huge public health burden of diabetes in the country. The study identified mutation in one known MODY gene. More extensive studies involving large sample size are required in future. [ABSTRACT FROM AUTHOR]

Nonhomogeneous inviscid Burgers' equation arises in one‐dimensional inviscid flow in the presence of external force. Inter alia, its applications are in optics: nonlinear fibre and geometrical, for example. We study a generalized form of this equation from Lie symmetry stand point. Reductions and invariant solutions are presented using the similarity variables thus obtained. To account for modeling of diffusion process by fractional time derivative, Lie symmetries and reduction of time‐fractional inviscid Burgers' equation are also presented. [ABSTRACT FROM AUTHOR]

Sweet pepper (Capsicum annuum L.) is one of the most popular and high value vegetable crops grown for its immature fruits throughout the world. In Pakistan it is cultivated as warm season crop in open fields during summer and in plastic tunnels during winter. Optimum planting date in sweet pepper production is key to better yield as it determines the period of maximum crop potential, efficient use of resources, lesser competition of plants with weeds and insect pests. It is the need of time to understand the negative impact of climate change on phenological development of sweet pepper. Therefore, the current study was designed to mitigate the effect of climate on growth and yield of sweet pepper cultivars at agro-ecological area of Multan, Pakistan by adjusting planting date. Three transplanting dates (viz. February 15th, March 2nd and March 16th) were evaluated during year 1 whereas five transplanting dates (viz. February 1st, February 15th, March nd, March 16th and April 1st) were assessed during year 2. There were three sweet pepper cultivars (Ganga, Winner and Savio) under study. Overall plant growth (stem height, average canopy diameter, number of leaves per plant and fresh and dry mass of plant parts) was significantly higher in the earliest planting dates (viz. February 15th in year 1 and February 1st in year 2) and it reduced as the planting was delayed. Plant yield, number of fruits and average fruit weight were also significantly greater in the earliest planting dates, and significantly lesser in later planting dates. During year 1, the effect of cultivar was prominent, and Winner performed better regarding growth characteristics while the effect was non-significant on yield attributes except average fruit weight which was also significantly higher in Winner as compared with other two cultivars. During year 2, cv. Winner performed better in growth attributes, whereas significantly greater number of fruits was found in cv. Savio, average fruit diameter was greater in cv. Winner and average fruit length was higher in cv. Ganga. It is concluded that nursery of sweet pepper should be planted in 1st week of February to achieve maximum growth and yield of fruits. In cultivar selection, cv. Winner should be preferred among sweet pepper hybrids. [ABSTRACT FROM AUTHOR]

Introduction. Dental anxiety is a common occurrence in patients undergoing dental treatments, especially in children. The success in paedriatric dental treatments and patient comfort depends on controlling the level of patient's anxiety in clinical settings. This study is aimed at evaluating the efficacy of different techniques applied for the reduction of dental anxiety in paediatric patients. Material and Methods. One hundred and sixty participants were divided into 4 groups; each group having 40 patients as follows: group I: mobile application "little lovely dentist," group II: YouTube® "dental video songs," group III "tell-show-do," and group IV "control." Dental prophylaxis treatments were provided to all the participants. Initial anxiety levels were noted during the patient's education phase by measuring heart rate with pulse oximeter and distress level with facial image scale, at the same time in each group, respectively. The postoperative anxiety was noted later with the same methods, after the application of anxiety reduction techniques. The data obtained were entered in the statistical package for the social sciences software, version 25. One-way ANOVA and paired t -test for matched groups were used to compare mean values of the 4 groups, in this study to determine their effectiveness. A p value of ≤0.05 was considered as statistically significant. Results. The mean age of patients in group 1 was 6.8 ± 2.1 years, group 2: 8.15 ± 2.27 years, group 3: 7.5 ± 2.3 years, and group 4: 7.27 ± 1.68 years. The intragroup comparisons of heart rate and facial image scores have shown a significant difference in before and after dental treatment procedures. Marked reduction in heart rate and facial image scale scores were found in patients belonging to group 1 (mobile applications) and group 2 (dental video songs). An increase in heart rate and facial image scale scores was seen in group 3 (tell-show-do) and the control group. Conclusion. The paediatric dental anxiety is a common finding in dental clinics. Behavior modification techniques like smartphone applications, "little lovely dentist," and "dental songs" can alleviate dental anxiety experienced by paediatric patients. The "tell-show-do" technique although most commonly used did not prove to be beneficial in the reduction of the anxiety levels. [ABSTRACT FROM AUTHOR]

The colloidal suspension of nanometer-sized particles of Fe3O4 in traditional base fluids is referred to as Ferro-nanofluids. These fluids have many technological applications such as cell separation, drug delivery, magnetic resonance imaging, heat dissipation, damping, and dynamic sealing. Due to the massive applications of Ferro-nanofluids, the main objective of this study is to consider the MHD flow of water-based Ferro-nanofluid in the presence of thermal radiation, heat generation, and nanoparticle shape effect. The Caputo-Fabrizio time-fractional Brinkman type fluid model is utilized to demonstrate the proposed flow phenomenon with oscillating and ramped heating boundary conditions. The Laplace transform method is used to solve the model for both ramped and isothermal heating for exact solutions. The ramped and isothermal solutions are simultaneously plotted in the various figures to study the influence of pertinent flow parameters. The results revealed that the fractional parameter has a great impact on both temperature and velocity fields. In the case of ramped heating, both temperature and velocity fields decreasing with increasing fractional parameter. However, in the isothermal case, this trend reverses near the plate and gradually, ramped, and isothermal heating became alike away from the plate for the fractional parameter. Finally, the solutions for temperature and velocity fields are reduced to classical form and validated with already published results. [ABSTRACT FROM AUTHOR]

Differential equations occur in many fields of science, engineering and social science as it is a natural way of modeling uncertain dynamical systems. A bipolar fuzzy set model is useful mathematical tool for addressing uncertainty which is an extension of fuzzy set model. In this paper, we study differential equations in bipolar fuzzy environment. We introduce the concept gH-derivative of bipolar fuzzy valued function. We present some properties of gH-differentiability of bipolar fuzzy valued function by considering different types of differentiability. We consider bipolar fuzzy Taylor expansion. By using Taylor expansion, Euler method is presented for solving bipolar fuzzy initial value problems. We discuss convergence analysis of proposed method. We describe some numerical examples to see the convergence and stability of the method and compute global truncation error. From numerical results, we see that for small step size Euler method converges to exact solution. [ABSTRACT FROM AUTHOR]

Salinity represents a medium with high soluble salts where as sodicity represents a medium with high exchangeable sodium, low calcium and highly alkaline pH. Salinity and sodicity commonly occur together in salt-affected soils however physiological studies have mostly considered salinity alone ending up in poor field success of the selected genetic resources. Similarly, the role of root-mediated acidification in salt resistance is not known in wheat. Here six wheat genotypes were exposed to salinity (NaCl: 125 mM), low calcium (25% of non-treated control) and salinity + low calcium in solution culture. There were significant differences among the wheat genotypes for growth and leaf ionic composition under salinity, low calcium and salinity + low calcium treatments. The wheat genotypes SARC-1, 25-SAWSN-42 and Pasban-90 accumulated higher K+ and Ca2+ and lower Na+ and Cl− and were resistant to the combined stress of low calcium and salinity. These genotypes also showed higher root-mediated acidification under stress conditions. The wheat genotypes resistant to salinity + low calcium supply in solution culture also performed better in the saline-sodic soil in a lysimeter study. A genotype resistant to salinity alone accumulated lower Ca2+ and showed lower rhizosphere acidification potential and did not perform good in saline-sodic soil conditions. Therefore, root-mediated acidification potential and resistance to low calcium supply improves resistance of wheat to saline-sodic conditions. It is further suggested that screening of the wheat germplasm for saline-sodic soils should be carried out at salinity + low calcium to better simulate saline-sodic field conditions. • Sodicity occurs with salinity in field but is ignored in physiological studies. • This study simulated saline sodic soil as salinity + low calcium in solution. • A genotype resistant to salinity + low calcium is resistant in saline sodic soil. • A resistant genotype accumulates higher Ca2+ and shows higher rhizosphere acification. • Screening for saline sodic soils should be done in salinity + low calcium solution. [ABSTRACT FROM AUTHOR]

The current study was carried out in order to assess the effects of micronutrients (B, Fe, Zn) on the yield and quality of Kinnow (Citrus reticulata Blanco). Citrus is an important fruit crop of Pakistan and micronutrients are not only important for yield and quality of citrus but also for the human health. This experiment consisted of different soil treatments and foliar applications of B, Zn and Fe either alone or in combinations. The results revealed that the highest concentrations of these three micronutrients in soil were found where 20 g B, 40 g Zn and 100 g Fe were applied per plant, respectively through soil application. The highest concentrations of these micronutrients in the leaves of Kinnow were found in the individual treatments of foliar spray of 0.03 % B, 0.1 % Zn and 0.25 % Fe, respectively, followed by the combined application of B, Zn and Fe with concentration of 0.03%, 0.1% and 0.25%. Soil that had combined treatment, B: 10 g plant-1, Zn: 20 g plant-1, Fe: 50 g plant-1 gave the highest yield of fruit and juice content. Fruit drop was the highest in control and the lowest for 20 g B soil application. Total sugars, reducing sugars and TSS were the highest for 40 g Zn as soil application, followed by the combined treatment of B:10 g plant-1, Zn:20 g plant-1, Fe:50 g plant-1 . The non-reducing sugars were the highest in the case of combined soil application of B, Zn and Fe. It is concluded that the micronutrients application is a suitable approach for increasing the quality and yield of Kinnow [ABSTRACT FROM AUTHOR]

Glanders is highly contagious and zoonotic bacterial disease of equines caused by Burkholderia mallei. Since many decades, glanders is endemic in eastern parts (Punjab) of Pakistan and has no information of disease in the north-western region (Khyber Pakhtunkhwa – KPK). Therefore, present study was aimed to determine the seroprevalence and associated risk factors in two draft equine populated districts (Charsada and Peshawar) of KPK. A total of 393 equine samples originating from different localities of study area were investigated for anti-B. mallei antibodies (glanders) using indirect enzyme linked immunosorbent assay (ID Vet, Grabels France). The overall seroprevalence was found to be 3.1% (95% CI: 1.6-5.3) which remained insignificantly (χ2 0.421, P=0.516) between the two districts. In Charsada, prevalence estimates varied significantly (χ2 11.986, P=0.017) among 5 localities and found insignificant (χ2 1.287, P=0.732) in different sampling areas of Peshawar district. Donkeys were more seropositive (4.1%; 4/195) than horses (2.1%; 8/194) which did not differ statistically (χ2 1.397, P=0.237) and all mules were tested negative. Prevalence slight increased with age of animals (>10 years) and with poor body conditions. Donkeys were more test positive (OR: 2.05, 95% CI: 0.61-6.94) than horses and similarly animals managed on communal feeding (OR: 1.84, 95% CI: 0.23-14.5) and water troughs (OR: 1.65, 95% CI: 0.21-13.04) had more chances of contracting glanders. Multivariable model indicated donkeys (OR: 4.58, 95% CI: 1.0, 20.9) and equines above 10 years of age (OR: 3.10, 95% CI: 0.7-13.3) were more likely to test positive for glanders. In conclusion, present study provides prevalence estimates of equine glanders in KPK regions, which appears to be an area of endemicity. Future large-scale investigations are seriously warranted in other equine populated districts before implementing an effective control plan for glanders. [ABSTRACT FROM AUTHOR]

A bipolar fuzzy set model is an extension of fuzzy set model. We develop new iterative methods: generalized Jacobi, generalized Gauss-Seidel, refined Jacobi, refined Gauss-seidel, refined generalized Jacobi and refined generalized Gauss-seidel methods, for solving bipolar fuzzy system of linear equations(BFSLEs). We decompose n × n BFSLEs into 4n × 4n symmetric crisp linear system. We present some results that give the convergence of proposed iterative methods. We solve some BFSLEs to check the validity, efficiency and stability of our proposed iterative schemes. Further, we compute Hausdorff distance between the exact solutions and approximate solution of our proposed schemes. The numerical examples show that some proposed methods converge for the BFSLEs, but Jacobi and Gauss-seidel iterative methods diverge for BFSLEs. Finally, comparison tables show the performance, validity and efficiency of our proposed iterative methods for BFSLEs. [ABSTRACT FROM AUTHOR]

Limited water availability is one of the important abiotic factor affecting yield of wheat crop. Exogenous application of osmolytes is an important factor in reducing the stress due to water shortage. Keeping in view the role of proline and L-tryptophan (L-TRP) in stress alleviation, a study was carried out at the agricultural research area of the University College of Agriculture and Environmental Sciences, The Islamia University of Bahawalpur, Pakistan, during winter 2015-2016 to evaluate the impact of foliar applied proline and L-TRP on growth and photosynthetic efficiency of wheat grown under limited moisture supply. Drought stress was applied in three levels (I1 = control, I2 = drought stress at tillering stage and I3 = drought stress at grain filling stage) while, foliar application of proline and L-TRP was done in six levels [T1 = control; T2 = proline (10 mM); T3 = proline (20 mM); T4 = L-TRP (10-4 M); T5 = L-TRP (10-4 M) + proline (10 mM) and T6 = L-TRP (10-4 M) + proline (20 mM)]. The experimental results revealed that growth and photosynthetic efficiency of wheat were decreased due to reduced water supply. However, exogenously applied proline and L-TRP considerably ameliorated the effect of drought stress. Combined application of L-TRP (10-4 M) and proline (20 mM) showed better results and induced tolerance to drought stress, in comparison with other treatments. Foliar application of proline and L-TRP also enhanced the photosynthetic rate which might be related with the improved photosynthetic pigments. Overall, exogenously applied proline and L-TRP mitigated the adverse effects of moisture deficit on growth and photosynthetic efficiency of wheat crop. [ABSTRACT FROM AUTHOR]

Objective  Pentavalent vaccine has been introduced in Pakistan against tetanus, diphtheria, Haemophilus influenzae type B (HiB), pertussis, and hepatitis B virus. Methods  This study was designed to determine protection against diphtheria, tetanus, and HiB in children of age 18 to 24 months from community which had received all three doses of pentavalent vaccine. Results  Overall, 97% were having immunity against HiB, 97% against tetanus, and 88% against diphtheria. Our study showed that children aged 18 to 24 months in Pakistan have high level of protection against HiB and tetanus. However, the protection for diphtheria was low in 40% of children which could be improved by adding a booster dose of diphtheria. Conclusion  By increasing the vaccine coverage among children, the burden of these diseases can be reduced in the future. [ABSTRACT FROM AUTHOR]

In this work, we present the temperature-sensing responses of poly (vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)], a ferroelectric material. This P(VDF-TrFE) was used to investigate its response within the temperature range of 30 to 60 °C. The impedance and capacitance responses were recorded for different temperature values using an LCR meter at variable frequencies, and the resulting measurements proved the high sensitivity of the proposed device. A comparative study was performed to find the best responsive P(VDF-TrFE) weight-percent solution for different temperature ranges. The sensor responded continuously and linearly with high sensitivity. [ABSTRACT FROM AUTHOR]

Anaplasmosisis a disease of circulatory cells that might impose drastic effects on different blood parameters and thereby camel's health. The present study describes the hemato-biochemical changes in camels naturally infected with subclinical anaplasmosis. The study comprisedof2 groups viz., group-I(15 Anaplasma positive camels identified by PCR)and group-II (15 healthy- PCR negative camels) which served as negative control. The student t-test as statistical tool revealed significant (p<0.05) decrease in hemogram [red blood cells (2.78±1.08), HGBconc. (7.41±2.78), HCT(11.22±3.52)] with accelerated (p<0.05)leukocytes count(20.29±6.08) in infected animals. Remarkable serum biochemical alterations were increased liver enzymes (GGT 18.0±1.0; LDH 68.67±27.024) with significantly low iron. The study concluded significant alterationsin blood parameters of camels naturally infected with subclinical anaplasmosis thatrequired further studies to be conducted in order to set a reference guide of blood parameters for the diagnosis of anaplasmosis in camels. [ABSTRACT FROM AUTHOR]

Children of all ages have been reported to be susceptible to COVID-19 with no significant gender difference. Clinical manifestations of paediatric patients are generally less severe than those of adult patients except for the children with co-morbidities. We report a case of a COVID-19 positive child, 13 months old, with both parents positive and managed conservatively for symptoms of cough and loss of appetite. Continuous monitoring and close follow-up in intensive care is the key to successful recovery in patients with Coronavirus infection without co-morbidities. [ABSTRACT FROM AUTHOR]

A new and efficient anodic Ru(bpy)32+ ECL system by using acridine orange (3,6-Bis(dimethylamino)acridine, AO) as a coreactant was reported in a neutral medium. The developed Ru(bpy)32+–AO system displayed a higher ECL intensity than that of the classic Ru(bpy)32+– oxalate ECL system, and was further exploited for the ECL detection of thiourea for the first time. [ABSTRACT FROM AUTHOR]

We detected Crimean-Congo hemorrhagic fever virus infections in 4 provinces of Pakistan during 2017-2018. Overall, seroprevalence was 2.7% in humans and 36.2% in domestic livestock. Antibody prevalence in humans was highest in rural areas, where increased contact with animals is likely. [ABSTRACT FROM AUTHOR]

N-Hydroxysuccinimide (NHS) and N-hydroxysulfosuccinimide (NHSS) were exploited as efficient coreactants for cathodic Ru(bpy)32+ electrochemiluminescence (ECL) in neutral medium. The developed systems showed stronger ECL signals than that of the classic Ru(bpy)32+–H2O2 system and have been exploited for sensitive "turn-on" type ECL detections of methyl blue and Hg2+. [ABSTRACT FROM AUTHOR]

• Magnetic blood flow with MPD in a cylindrical tube is considered. • The two-phase Brinkman type fluid model is considered. • The fractional problem with physical condition is formulated. • Joint Laplace and Hankel transform are used for exact solutions. • Magnetic field influenced significantly blood and MPD velocities. This article deals with the magnetic blood flow in a cylindrical tube with uniformly distributed magnetite dusty particles (MDP). The two-phase Brinkman type fluid model is considered. The fractional governing equations are model in the cylindrical coordinate system taking into consideration the magnetization of the fluid due to the applied magnetic field. The fractional governing equations are subjected to physical initial and boundary conditions. The joint Laplace and Hankel transform are employed to develop exact analytical solutions. The obtained solutions are computed numerically and plotted in different graphs. It is noticed that for a long time τ = 0.4 the blood and MDP velocities increase with increasing values of the fractional parameter. In contrast, this effect reverses for a shorter time τ = 0.02. The magnetic field significantly influences the blood and MPD velocities due to Lorentz forces. Both velocities are decreased with increasing values of the magnetic parameter. [ABSTRACT FROM AUTHOR]

[Display omitted] • Machine learning-based approach is presented for virtual mining of polymer monomers for photodetectors. • DFT computations are used to predict the reorganization energy of >500 organic molecules. • Similarity analysis is applied to screen easily synthesizable polymer monomers for designing high-performance photodetectors. • Numerous regression models are developed and tested/selected their predictive capability. • Library enumeration and fitness score strategies are used. • SYnthetic BAyesian classifier (SYBA) is used to test the synthetic accessibility of designed monomers. Predicting and understanding the charge transport properties of organic semiconductors is a crucial target for constructing efficient electronic devices such as photodetectors. To this end, reorganization energy (Re) is a key parameter for molecular design, which provides quantitative strength of electron-photon coupling process (charge transport parameter). Although modern density functional theory-based approaches can accurately simulate intramolecular RE trends, such computations are time-consuming and costly. In this study, we present machine-learning tools for the accurate and fast prediction of intramolecular Re. These tools are effectively used for screening of new compounds with low internal Re. Moreover, virtual mining of polymer monomers is performed for photodetector applications. Machine learning models are developed with molecular descriptors (features). Regression analysis is used to show how two or more variables are related. The dependent variable yields the best outcomes and helps to predict Re. This research shows that chemical designs can accurately predict the REs of organic semiconductor materials. Out of five different regressions models, gradient booster regression gives the best prediction capability (R2 = 0.761). Moreover, chemical similarity analysis (CSA) is used to search for a new group of molecules with high performance. Library enumeration is used for structure determination and for studying the properties of these small molecules. The fitness score of newly designed quinoxaline is more than 0.9, which shows best outcome. The new strategy holds immense potential for the virtual mining of polymer monomers for photodetectors applications and regression-aided reorganization energy predictions. [ABSTRACT FROM AUTHOR]

Graphene (GR) composites have great potential for the determination of carbamates pesticides (CPs) by electrochemical methods. Since the beginning of the 20th century, GR has shown remarkable promise as electrode material for various sensors. The contamination of food products with harmful CPs is a major problem as they do not always damage human health immediately, but can be harmful after prolonged exposure. A range of advantages can be gained from their electrochemical determination, such as high sensitivity, reasonably selectivity, rapid detection, low limit of detection, and easy electrode fabrication. Furthermore, these electrochemical techniques are robust, reproducible, user-friendly, and conform to both "green" and "white" analytical chemistry. This review is focused on results published in the last ten years in the field of electrochemical determination of CPs in food products using GR and its derivatives. [Display omitted] • Graphene-based electrochemical detection of carbamate pesticides in food is reviewed. • Characterization of graphene and its derivatives using instrumental methods is discussed. • Analytical characteristics of carbamate pesticides determination by electrochemical methods are discussed. • Graphene electrodes modified by enzymes, nanoparticles, and polymers are discussed. [ABSTRACT FROM AUTHOR]

Mastitis in goats, analogous to dairy cattle, is among the momentous diseases of economic value in all parts of the world. Local information of epidemiology of goat mastitis is scanty. In the present study, considering geographical distribution of Beetal goat, 172 flocks were randomly pulled out by “Survey tool box” to reduce biased sampling from perie-urban and urban areas of six districts of Punjab. By following the proportionate sampling strategy and assuming the highest population (70%) of Beetal all over the Punjab, Beetal strains were screened for the prevalence of mastitis from Faisalabad, Jhang, Chiniot, Bahawalpur, Muzzafargarh and Rajanpur districts. Screening of the flocks with surf field mastitis test indicated that overall prevalence of caprine mastitis in Beetal breed was 17.39% while in Beetal Faisalabadi strain 16.53% from 116 flocks, in Beetal Makhicheeni 18.06% from 32 flocks and in Beetal Nuqri 19.33% from 24 flocks. Microbiological examination of milk samples showed various types of mastitic microorganisms. The predominant isolates included Staphylococcus (S). hyicus (45%), S. xylosus (19%), S. simulans (16%), S. aureus (9%) and unidentifiable Staphyloccocal species (11%). Antibiotic sensitivity test was conducted on the most prevalent isolates. S. aureus and S. hyicus showed sensitivity to eight antibiotics: amoxicillin, ampicilin, lincomycin, sulfamethoxazole+trimethoprim, novobiocin, enrofloxacin, amoxicillin+ clavulanic acid and oxytetracycline while S. xylosus was sensitive to all antibiotics except novobiocin and S. simulans was sensitive to lincomycin, sulfamethoxazole+ trimethoprim, enrofloxacin and resistant to all other antibiotics. The study found over all 16.74% mastitis in different strains of Beetal. The most important parameters as; type of housing, farm hygiene, age, stage of lactation, parity, color, body condition score, teat ends, SFMT score and decreased milk yield were found pertinent risk factors so that prompt attention required for mastitis control in goats. [ABSTRACT FROM AUTHOR]

The present study was conducted to determine the sero-prevalence of Q fever and associated risk factors in institutional dairy farms in Punjab, Pakistan. A total 11 dairy farms were investigated from different areas of Punjab province. Out of these farms, a total of 827 animals (cows n=419 and buffaloes n=408) were investigated. Presence of anti-Coxiella burnetii antibodies was determined by indirect ELISA. The overall prevalence in dairy animals (cattle and buffaloes) was 6.1% (95% CI: 4.5-7.9). In cattle prevalence was higher (7.6%; 95% CI: 5.3-10.6) than in buffaloes (4.4%; 95% CI: 2.6-6.9). The probability of occurrence of disease in cattle was higher (7.63%; OR=1.9, 95% CI: 0.99-3.25) than in buffalo (1.00%; OR=1.00) The difference in sero-prevalence between the two-dairy species was significant (p=0.052, x² = 3.786). Stratification of Q fever as per the breed of cattle indicated that the sero-prevalence was the highest (13%) in Cholistani followed by Sahiwal (7.5%) and cross bred (2.6%). Animals age between 2.1 to 5 year (OR=2.56, 95% CI 1.05, 6.20), contact with small ruminants (OR=1.43, 95% CI 0.63, 3.25), tick infestations (OR=4.91, 95% CI 2.40, 10.00), dry-dusty environment (OR=1.55, 95% CI 0.54, 4.43), retained fetal membranes (OR=1.68, 95% CI 0.94, 5.73) and abortion history (OR=2.17, 95% CI 0.88, 5.35) were risk factors for the seropositivity of Q fever. The results of the study indicated that Q fever is prevalent in cattle and buffalo managed at institutional dairy farms in Punjab. [ABSTRACT FROM AUTHOR]

This article aims to study the flow of ethylene glycol-based molybdenum disulfide generalized nanofluid over an isothermal vertical plate. A fractional model with non-singular and non-local kernel, namely Atangana-Baleanu fractional derivatives, is developed for Casson nanofluid in the form of partial differential equations along with appropriate initial and boundary conditions. Molybdenum disulfide nanoparticles of spherical shape are suspended in ethylene glycol taken as conventional base fluid. The exact solutions are developed for velocity and temperature via the Laplace transform technique. In limiting sense, the obtained solutions are reduced to fractional Newtonian (β→∞), classical Casson fluid (α→1) and classical Newtonian nanofluid. The influence of various pertinent parameters is analyzed in various plots with the useful physical discussion. [ABSTRACT FROM AUTHOR]

The study of classical nanofluid is limited to partial differential equations with integer-order neglecting memory effect. Fractionalized nanofluids, modeled by partial differential equations with Caputo time-fractional derivative, have the capability to address the memory effect. This article deals with the flow and entropy generation of electrically conducting different types of fractionalized nanofluids passing over an infinite vertical plate embedded in porous medium. The governing equations are transformed into dimensionless form, and then, a time-fractional model is generated using the Caputo approach. Two different nanoparticles (molybdenum disulfide and graphene oxide) are dispersed in three different base fluids (water, kerosene oil and methanol). The problem is solved for the exact solutions using the Laplace transformation technique. The impacts of fractional parameter α and volume fraction of nanoparticles φ on velocity profile, entropy generation, Bejan number and the rate of heat transfer are exhibited in tabular form. Finally, the graphs are plotted for different types of nanoparticles and base fluids and discussed physically. Moreover, from present solutions, the well-known published results are recovered to validate the obtained results. [ABSTRACT FROM AUTHOR]

This paper explores a model predictive control (MPC) strategy with constraints satisfaction for a high power induction heating load. The MPC predicts the state variables and future control sequence of the system in advance and achieves on-line-optimization with a reduced error. The state-space model of the system with a parallel resonant load is developed and then MPC is applied. The proposed approach controls the DC link current at the rectifier output and reactive component of the supply current. The DC current is used to regulate the power of the heating load and the reactive component of input current is kept at zero to attain the unity power factor. The results show that the proposed strategy regulates the power of the heating load, achieves unity power factor at input of the system and handles the variables within the defined constraints effectively. [ABSTRACT FROM AUTHOR]