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The emergence of the underlying blockchain technology of bitcoin has gained extensive attention from researchers and practitioners. As distributed ledger technology, blockchain widely finds its applications in the supply chain to mitigate issues related to transparency, information sharing, process efficiency, and traceability. This study employed a knowledge-based visualization technique to create a vision beyond other review studies on the blockchain-based supply chain. We used bibliometric and network analysis to synthesize the previous literature. In total, 431 articles in the timespan of 2017 to April 2022 from Scopus and Web of Science (WOS) databases were analyzed after applying search string, inclusion, and exclusion criteria. Basic information was extracted from initial data screening; then, data was analyzed on the grounds of co-occurrence, bibliographic coupling, citation, co-authorship, and co-citation analysis. In addition, thematic analysis was performed to analyze the content of the previous studies, adopted research methods, and dynamic industries in the literature. Besides all these, we identified various research gaps and proposed research directions for future study. We believe that this study provides adequate knowledge to academic scholars and supply chain practitioners to fast-track the current research in the supply chain domain using blockchain technology.

The beneficial effects of biochar (BC) and plant growth-promoting bacteria (PGPR) to increase crop yields under harsh environments have been widely reported. However, the knowledge on the synergistic effects of BC and PGPR to induce drought tolerance in oilseeds is scant. In the present study, the effects of cotton sticks derived BC together with PGPR strains (Paraburkholderia phytofirmans and Bacillus sp.) were examined in water-stressed soybean plants. Initially, the BC application rates (1% and 2%) for soybean were optimized in a pilot experiment (experiment I), and the most effective level (1%) was selected for further studies together with PGPR in the second experiment. The soybean plants were raised in pots under semi-controlled conditions and were subjected to drought stress (25–30% water holding capacity) at pod formation stage. In comparison with control, the drought-mediated decrease in photosynthetic pigments and gas exchange characteristics was markedly lower in BC and PGPR-treated plants. However, the maximum increase in photosynthetic (12–30%) and the enzymatic antioxidant activities (5–20%) was recorded in plants treated with BC + P. phytofirmans, whereas no further significant increase was observed in plants treated with combined BC and Bacillus sp. under water deficit conditions. Similarly, the combined BC and P. phytofirmans application considerably increased the grain yield (14%) under drought stress conditions. We conclude that the combined application of BC + P. phytofirmans could be utilized as an effective strategy to improve soybean yield in dry arid regions.

A stochastic computing approach is implemented in the present work to solve the nonlinear nanofluidics system that occurs in the model of atomic physics. The process converts the partial differential nanofluidics system with suitable level of similarities transformation into nonlinear systems of differential equations. For the construction of datasets, finite difference scheme (Lobatto IIIA) is applied through different selection of collocation points for nonlinear nanofluidics system having accuracy of order four. Lobatto IIIA has a strong point to tackle extremely nonlinear systems of ordinary differential equations in smooth way. For different scenarios, datasets are well trained through computing scheme to investigate the heat transfer and thermal performance of nanofluidic transportation system of nanofluids and hybrid nanofluids toward stretching surfaces with variation of Biot number, Nusselt number and skin fraction. Furthermore, the reliability, accuracy and efficiency are endorsed through various statistical analysis and graphical illustrations of proposed computing scheme.

Fundamentals of Database Systems is a core course in computing disciplines as almost all small, medium, large, or enterprise systems essentially require data storage component. Database System Education (DSE) provides the foundation as well as advanced concepts in the area of data modeling and its implementation. The first course in DSE holds a pivotal role in developing students' interest in this area. Over the years, the researchers have devised several different tools and methods to teach this course effectively, and have also been revisiting the curricula for database systems education. In this study a Systematic Literature Review (SLR) is presented that distills the existing literature pertaining to the DSE to discuss these three perspectives for the first course in database systems. Whereby, this SLR also discusses how the developed teaching and learning assistant tools, teaching and assessment methods and database curricula have evolved over the years due to rapid change in database technology. To this end, more than 65 articles related to DSE published between 1995 and 2022 have been shortlisted through a structured mechanism and have been reviewed to find the answers of the aforementioned objectives. The article also provides useful guidelines to the instructors, and discusses ideas to extend this research from several perspectives. To the best of our knowledge, this is the first research work that presents a broader review about the research conducted in the area of DSE.

In this paper, we investigate the properties of a newly introduced class of functions, strongly reciprocally (p, h)-convex functions of higher order. We establish Hermite–Hadamard-type and Fejér-type inequalities for this class of functions. Additionally, we present fractional integral inequalities applicable to strongly reciprocally (p, h)-convex functions of higher order.

Background In the Himalayas, traditional knowledge and biodiversity are strongly linked due to the symbiotic interaction between plant and cultural diversity, as well as the support provided by cultural memories, ecological awareness, and social norms. Our study was focused on documenting the vanishing knowledge in the Kashmir Himalaya with the following main objectives: 1) to document the ethnomedical and cultural knowledge of the local flora, 2) to evaluate the cross-cultural use of the flora in the region, and, finally, 3) to identify the key indicator species utilized by each ethnic group using multivariate statistical analysis. Methods We used semi-structured questionnaires to conduct interviews with people of different ethnicity, gender, age, and occupational categories. The intercultural relationships of species utilization among ethnic groups were examined using a Venn diagram. The overall trends between the indicator values and the plant species used by diverse ethnic groups were illustrated using the linear regression model. Results We recorded 46 species belonging to 25 different families used by the local people of the Kashmir Valley belonging to four ethnic groups (Gujjar, Bakarwal, Pahari, and Kashmiri). The dominant families recorded were Asteraceae and Ranunculaceae followed by Caprifoliaceae. Rhizomes were the most utilized plant part, followed by leaves. A total of 33 ailments were treated with plants, and gastrointestinal disorders were treated with most species followed by musculoskeletal diseases and dermatological problems. Across cultural relationships, the Gujjar and Pahari showed greater similarity (17%). This may be due to the fact that both ethnic groups share a common geographical landscape and are exogamous to each other. We identified key indicator species used by different ethnic groups with significant (p ≤ 0.05) values. For instance, in the Gujjar ethnic group, Aconitum heterophyllum and Phytolacca acinosa had significant indicator value, which was due to the fact that these plants were easily accessible and also had a wide range of uses. In contrast, the Bakarwal ethnic group showed different indicator species, with Rheum spiciforme and Rhododendron campanulatum being highly significant (p ≤ 0.05), because this ethnic group spends the majority of their time in high-altitude pastures, using a particularly wide variety of plant species for medicine, food, and fuelwood. While indicator values and plant usage were positively correlated for the Gujjar, Kashmiri, and Pahari ethnic groups, they were negatively correlated for the Bakarwal. The positive correlation indicates cultural preferences for certain plant use and underlines the cultural significance of each species. The current study reported new uses for the following species: raw roots of Jurinea dolomiaea used for tooth cleaning, seeds of Verbascum thapsus applied for respiratory diseases, and flowers of Saussurea simpsoniana given to anyone as a good luck wish. Conclusion The current study highlights historical ethnic group stratifications and cultural standing while comparing reported taxa across cultures. Each ethnic group made extensive ethnomedical use of plants, and knowledge, originally transmitted verbally, is now available in writing for reference. This could pave the way for providing incentives to local communities to showcase their talents, celebrate them, and gain from potential development initiatives.

Although smartphones are equipped with accessibility functions, they still pose significant problems for visually impaired people. Sometimes these functions cannot fulfil the expectations of users. Early mobile devices had physical buttons and a keypad, and visually impaired users could navigate around the keypad using the tactile markers on the buttons. However, the lack of tactile markers makes it much more difficult to operate a touchscreen device. This paper describes an e-learning platform that is designed to improve the accessibility of smartphone applications for students who are visually impaired but have some useful vision. A User-Centered Design approach was used to develop an effective solution for visually impaired students. A study was conducted during the development of the described platform, and the results showed that our suggested design improves task completion time as compared to the initial version. Participants also expressed higher levels of satisfaction when using the improved design of this platform. The modified design was also assessed using the Mobile Application Rating Scale (MARS), and the results indicate that it is quite reliable and rated well among visually impaired children. Furthermore, developers can use our suggested design guidelines such as clear navigation, color contrast, immediate feedback, icon arrangements, button and text size in the development of new applications.

Background Mitochondrial transplantation (MTx) is an emerging but poorly understood technology with the potential to mitigate severe ischemia–reperfusion injuries after cardiac arrest (CA). To address critical gaps in the current knowledge, we test the hypothesis that MTx can improve outcomes after CA resuscitation. Methods This study consists of both in vitro and in vivo studies. We initially examined the migration of exogenous mitochondria into primary neural cell culture in vitro. Exogenous mitochondria extracted from the brain and muscle tissues of donor rats and endogenous mitochondria in the neural cells were separately labeled before co-culture. After a period of 24 h following co-culture, mitochondrial transfer was observed using microscopy. In vitro adenosine triphosphate (ATP) contents were assessed between freshly isolated and frozen-thawed mitochondria to compare their effects on survival. Our main study was an in vivo rat model of CA in which rats were subjected to 10 min of asphyxial CA followed by resuscitation. At the time of achieving successful resuscitation, rats were randomly assigned into one of three groups of intravenous injections: vehicle, frozen-thawed, or fresh viable mitochondria. During 72 h post-CA, the therapeutic efficacy of MTx was assessed by comparison of survival rates. The persistence of labeled donor mitochondria within critical organs of recipient animals 24 h post-CA was visualized via microscopy. Results The donated mitochondria were successfully taken up into cultured neural cells. Transferred exogenous mitochondria co-localized with endogenous mitochondria inside neural cells. ATP content in fresh mitochondria was approximately four times higher than in frozen-thawed mitochondria. In the in vivo survival study, freshly isolated functional mitochondria, but not frozen-thawed mitochondria, significantly increased 72-h survival from 55 to 91% (P = 0.048 vs. vehicle). The beneficial effects on survival were associated with improvements in rapid recovery of arterial lactate and glucose levels, cerebral microcirculation, lung edema, and neurological function. Labeled mitochondria were observed inside the vital organs of the surviving rats 24 h post-CA. Conclusions MTx performed immediately after resuscitation improved survival and neurological recovery in post-CA rats. These results provide a foundation for future studies to promote the development of MTx as a novel therapeutic strategy to save lives currently lost after CA.

Exploration and exploitation of intelligent computing infrastructures are becoming of great interest for the research community to investigate different fields of science and engineering offering new improved versions of problem-solving soft computing-based methodologies. The current investigation presents a novel artificial neural network-based solution methodology for the presented problem addressing the properties of Hall current on magneto hydrodynamics (MHD) flow with Jeffery fluid towards a nonlinear stretchable sheet with thickness variation. Generalized heat flux characteristics employing Cattaneo–Christov heat flux model (CCHFM) along with modified Ohms law have been studied. The modelled PDEs are reduced into a dimensionless set of ODEs by introducing appropriate transformations. The temperature and velocity profiles of the fluid are examined numerically with the help of the Adam Bashforth method for different values of physical parameters to study the Hall current with Jeffrey fluid and CCHFM. The examination of the nonlinear input–output with neural network for numerical results is also conducted for the obtained dataset of the system by using Levenberg Marquardt backpropagated networks. The value of Skin friction coefficient, Reynold number, Deborah number, Nusselt number, local wall friction factors and local heat flux are calculated and interpreted for different parameters to have better insight into flow dynamics. The precision level is examined exhaustively by mean square error, error histograms, training states information, regression and fitting plots. Moreover, the performance of the designed solver is certified by mean square error-based learning curves, regression metrics and error histogram analysis. Several significant results for Deborah number, Hall parameters and magnetic field parameters have been presented in graphical and tabular form.

Cardiac arrest (CA) patients suffer from systemic ischemia–reperfusion (IR) injury leading to multiple organ failure; however, few studies have focused on tissue-specific pathophysiological responses to IR-induced oxidative stress. Herein, we investigated biological and physiological parameters of the brain and heart, and we particularly focused on the lung dysfunction that has not been well studied to date. We aimed to understand tissue-specific susceptibility to oxidative stress and tested how oxygen concentrations in the post-resuscitation setting would affect outcomes. Rats were resuscitated from 10 min of asphyxia CA. Mechanical ventilation was initiated at the beginning of cardiopulmonary resuscitation. We examined animals with or without CA, and those were further divided into the animals exposed to 100% oxygen (CA_Hypero) or those with 30% oxygen (CA_Normo) for 2 h after resuscitation. Biological and physiological parameters of the brain, heart, and lungs were assessed. The brain and lung functions were decreased after CA and resuscitation indicated by worse modified neurological score as compared to baseline (222 ± 33 vs. 500 ± 0, P P P P = 0.2886; fractional shortening, 24 h: 42.9 ± 3.1% vs. baseline: 45.7 ± 1.9%, P = 0.4658). Likewise, increases of superoxide production in the brain and lungs were remarkable, while those in the heart were moderate. mRNA gene expression analysis revealed that CA_Hypero group had increases in Il1b as compared to CA_Normo group significantly in the brain (P P P = 0.4848). Similarly, hyperoxia-induced increases in other inflammatory and apoptotic mRNA gene expression were observed in the brain, whereas no differences were found in the heart. Upon systemic IR injury initiated by asphyxia CA, hyperoxia-induced injury exacerbated inflammation/apoptosis signals in the brain and lungs but might not affect the heart. Hyperoxia following asphyxia CA is more damaging to the brain and lungs but not the heart.

In the present research, we introduce the notion of convex stochastic processes namely; strongly p-convex stochastic processes. We establish a generalized version of Ostrowski-type integral inequalities for strongly p-convex stochastic processes in the setting of a generalized k-fractional Hilfer–Katugampola derivative by using the Hölder and power-mean inequalities. By using our main results, we derived some known results as special cases and many well-known existing results are also recaptured. It is assumed that this research will offer new guidelines in fractional calculus.

The current investigation is related to the design of novel integrated neuroswarming heuristic paradigm using Gudermannian artificial neural networks (GANNs) optimized with particle swarm optimization (PSO) aid with active-set (AS) algorithm, i.e., GANN-PSOAS, for solving the nonlinear third-order Emden–Fowler model (NTO-EFM) involving single as well as multiple singularities. The Gudermannian activation function is exploited to construct the GANNs-based differential mapping for NTO-EFMs, and these networks are arbitrary integrated to formulate the fitness function of the system. An objective function is optimized using hybrid heuristics of PSO with AS, i.e., PSOAS, for finding the weights of GANN. The correctness, effectiveness and robustness of the designed GANN-PSOAS are verified through comparison with the exact solutions on three problems of NTO-EFMs. The assessments on statistical observations demonstrate the performance on different measures for the accuracy, consistency and stability of the proposed GANN-PSOAS solver.

The fractional neuro-evolution-based intelligent computing has substantial potential to solve fractional order systems represented with Lane–Emden equation arising in astrophysics including Newtonian self-gravitating, spherically symmetric and polytropic fluid. The present study aimed to present a neuro-swarm-based intelligent computing solver for the solution of nonlinear fractional Lane–Emden system (NFLES) using by exploitation of fractional Meyer wavelet artificial neural networks (FMW-ANNs) and global optimization mechanism of particle swarm optimization (PSO) combined with rapid local search of sequential quadratic programming (SQP), i.e., FMW-ANN-PSO-SQP. The motivation for the design of FMW-ANN-PSO-SQP intelligent computing comes with an objective of presenting an accurate, reliable, and viable framworks to deal with stiff nonlinear singular models represented with NFLES involving both fractional and integer derivative terms. The designed algorithm is tested for six different variants of NFLESs. The obtained numerical outcomes obtained by the proposed FMW-ANN-PSO-SQP are compared with the exact results to authenticate the correctness, efficacy, and viability, and these aspects are further endorsed statistical observations.

This article discussed the influence of activation energy on MHD flow of third-grade nanofluid model (MHD-TGNFM) along with the convective conditions and used the technique of backpropagation in artificial neural network using Levenberg–Marquardt technique (BANN-LMT). The PDEs representing (MHD-TGNFM) transformed into the system of ODEs. The dataset for BANN-LMT is computed for the six scenarios by using the Adam numerical method by varying the local Hartman number (Ha), Prandtl number (Pr), local chemical reaction parameter (σ), Schmidt number (Sc), concentration Biot number (γ2) and thermal Biot number (γ1). By testing, validation and training process of (BANN-LMT), the estimated solutions are interpreted for (MHD-TGNFM). The validation of the performance of (BANN-LMT) is done through the MSE, error histogram and regression analysis. The concentration profile increases when there is an increase in Biot number and the local Hartmann number; meanwhile, it decreases for the higher values of Schmidt number and the local chemical reaction parameter.

Global warming and food security have led to increasing concern about agricultural crop production efficiency, especially wheat and rice farming. The purpose of the current study is to measure wheat and rice production efficiency scores with environmental quality in China, India, and Pakistan by using a data envelopment analysis (DEA) model. The DEA results show that China and India are more efficient in wheat and rice production but it is not efficient in the environment in the study period. The results also show that Pakistan has also relatively small wheat and rice efficiency compared with China and India and increased the efficiency with the passage of time. The practical outcomes also show that Pakistan has the most efficient and effective states from the periods 2008 to 2019 in terms of wheat and rice efficiency and also a small increase in carbon emission. Based on the findings, policymakers should pay attention to the role of green technology in reducing agricultural CO2 emissions.

Numerical treatment of the COVID-19 transposition and severity in Romania and Pakistan has been presented in this study, i.e., ANN-GA-SQP through artificial neural network genetic algorithms (ANN-GA) and sequential quadratic programming (SQP), a design of an integrated computational intelligent paradigm, COVID-19 is widely considered to be the greatest health threat humanity has ever faced. In terms of both health and economics, COVID-19 is a huge disaster. Many academics have looked at the COVID-19 model in their research papers, although they use different traditional techniques to represent it. The use of hybrid suggested solutions to solve this issue in the present article is significant, demonstrating the study's novelty. The SIR model of COVID-19 consists of a susceptible, infectious, and recovered class of population. The activation function for the construction of functions based on fitness in mean squared error sense is developed using nonlinear equations of the COVID-19 SIR model for the best performance of ANN-GA-SQP with the combined potential of GA and SQP of a network. While detailed refining is done with efficient local search with SQP, GAs operates as a global search. In addition, a neuron analysis will be presented to verify the effectiveness and complexity of the proposed method. Adam’s numerical methodology is applied to compare the sustainability and efficacy of the presented paradigm. Analytical evaluations of mean, median, and semi-interquartile range values, as well as Theil’s inequality coefficients, root mean squared error, and mean of absolute deviation) values have been observed. The convergence and correctness of the ANN-GA-SQP approach are further validated by statistical analyses.

Because the fluid-conveying piping system has a wide range of engineering applications such as mechanical, civil, astronautical and aeronautical engineering and so on, the vibration control is very necessary due to possible damage to the pipe system caused by vibration. This paper presents a vibration reduction scheme of pipeline conveying fluid which can reduce vibration effectively. By coupling the Bragg scattering bandgap mechanism with the inertia amplification mechanism, a strategy to enhance the bandgap properties of the periodic non-uniform pipes conveying fluid is proposed. The band structures for flexural waves in the fluid-conveying periodic non-uniform pipes with periodically distributed inertial amplification mechanisms are determined using the transfer matrix method, and the frequency ranges of the bandgaps and vibration reduction are analyzed. The vibration attenuation capacity of the periodic non-uniform pipes under different fluid velocities, amplification masses and amplification angles is investigated. The bandgaps of the non-uniform pipe conveying fluid with periodic inertial amplification mechanisms obtained by the numerical method are compared with the vibration experiments. The results show that the piping systems with the design of the periodic pipe structures can be effective in reducing vibration. The fluid velocity has slight effect on the band-gap properties of the non-uniform fluid-conveying pipes with periodic inertial amplification mechanisms. The band-gap properties and vibration attenuation performance of the non-uniform fluid-conveying pipes with periodic inertial amplification mechanisms can be enhanced more efficiently by a larger amplification angle and amplification mass.

The present investigations are related to design an integrated computing numerical approach through Levenberg–Marquardt backpropagation (LMB) neural networks (NNs), i.e., LMB-NNs. The designed LMB-NNs approach is presented to solve the fourth-order nonlinear system of Emden–Fowler model (FO-SEFM). The solution of six different examples based on the FO-SEFM using the designed methodology LMB-NNs is numerically treated along with the discussion of singular point and shape factor. The comparison of the obtained results from the LMB-NNs and the exact solutions of each example has been presented. To evaluate the approximate results of the FO-SEFM for different problems, the testing, training, and authentication procedures are accompanied to adapt the NNs by reducing the functions of mean square error (MSE) through the LMB. The proportional investigations and performance studies based on the results of error histograms, MSE, regression, and correlation establish the effectiveness and correctness of the designed LMB-NNs approach.

The objective was to develop a reservoir-type nimesulide gel patch for controlled drug delivery and avoid the gastrointestinal adverse effects associated with the oral delivery of nimesulide. Six patch formulations of nimesulide gel comprising of 20–40% for ethanol and 20–40% for propylene glycol as permeation enhancers were constructed. Carbopol 934 was used as a gelling agent. The reservoir compartment of transdermal patch was filled with the gel. The in vitro release and skin permeation were assessed using USP apparatus V. The optimized formulation was obtained on the basis of the in vitro drug release and permeation results. The surface area of optimized formulation (F3) was reduced to 1 cm2, and permeation of drug was determined through Franz diffusion cell using Strat-M transdermal diffusional membrane. The nimesulide reservoir patch was placed in the donor compartment. The receptor compartment was filled with 5 mL of permeation medium [normal saline containing 20% v/v PEG-400 was used as dissolution media (pH 7.4)] stirred by magnetic stirrer. The skin sensitivity reaction of the optimized patch was evaluated by Draize method. The formulation F3 comprising of 40% ethyl alcohol and 20% propylene glycol was considered optimized due to maximum % of drug release (86.3 ± 2.73%) and permeation of (3048.84 ± 17.23 µg/cm2), having flux of 449.92 µg/cm2 h and lag time of 0.197 h with no visible skin sensitivity reaction. The study demonstrates that the reservoir-type transdermal patch of nimesulide gel has the potential of delivering drug across the skin in a controlled release manner.

Research on cancer treatment is always of great importance because of the extensive and difficult treatment options and side effects of chemotherapeutic agents. Due to this, novel techniques for cancer treatment are the need of the day. Nowadays, nanotechnology is of great interest for its applications as diagnostic tools, theragnostic, contrasting agents, and vehicles for delivering drugs. Nanoparticles (NPs) are made up of biocompatible and biodegradable polymers that improve the pharmacokinetic and pharmacodynamic properties of drugs, reduce side effects, improve stability, prolong the release of drug, and reduce the dosing frequency. Poly (lactic-co-glycolic acid) (PLGA) is FDA-approved synthetic polymer which can be used to formulate NPs that can be targeted to a specific site for the safe and effective delivery of drugs. PLGA-based NPs can be used for a variety of cancer therapies including tumor-targeted drug delivery, gene therapy, hyperthermia, and photodynamic therapy. This article discusses the method of preparation, characterization, encapsulation of chemotherapeutic drugs, effect of physicochemical properties of PLGA- based NPs, and how we can exploit these aspects through various methods of preparation for drug loading, biodistribution, target specificity, and their use in cancer treatment. Along with these targeting strategies, gene therapy, cancer immunotherapy, and various applications have also been discussed. This article also aims to discuss the incorporation of diagnostic tools and therapeutic moiety in one versatile formulation of PLGA-NPs and the difficulties faced in translating this promising tool to clinical use.

Background Vagus nerve stimulation (VNS) has shown therapeutic potential in a variety of different diseases with many ongoing clinical trials. The role of VNS in reducing ischemic injury in the brain requires further evaluation. Cardiac arrest (CA) causes global ischemia and leads to the injury of vital organs, especially the brain. In this study, we investigated the protective effects of customized threshold-adjusted VNS (tVNS) in a rat model of CA and resuscitation. Methods Sprague-Dawley rats underwent 12 min asphyxia-CA followed by resuscitation. Rats were assigned to either post-resuscitation tVNS for 2 h or no-tVNS (control). tVNS was applied by electrode placement in the left cervical vagus nerve. To optimize a threshold, we used animal’s heart rate and determined a 15–20% drop from baseline levels as the effective and physiological threshold for each animal. The primary endpoint was 72 h survival; secondary endpoints included neurological functional recovery, reduction in brain cellular injury (histopathology), cardiac and renal injury parameters (troponin I and creatinine levels, respectively). Results In comparison to the control group, tVNS significantly improved 72 h survival and brain functional recovery after 12 minutes of CA. The tVNS group demonstrated significantly reduced numbers of damaged neurons in the CA1 hippocampal region of the brain as compared to the control group. Similarly, the tVNS group showed decreased trend in plasma troponin I and creatinine levels as compared to the control group. Conclusions Our findings suggest that using tVNS for 2 h after 12 minutes of CA attenuates ischemia neuronal cell death, heart and kidney damage, and improves 72 h survival with improved neurological recovery.

Molybdenum (Mo) is an essential element for the growth and development of higher plants. Its deficiency leads to a decrease in wheat (Triticum aestivum L.) growth and reduces nutritional quality of grain. However, little is known about macro- and micro-nutrient contents or their allocation within organs of wheat under Mo sufficient and deficient conditions. The objective of this study was to gain a better understanding of how Mo application affects mineral nutrient uptake and allocations among various organs of wheat. A pot experiment was conducted to explore these effects in wheat with Mo-deficiency (–Mo) and Mo supply (+ Mo) treatment. The results revealed that Mo application increased plant dry biomass, grain yield, allocations of macro-nutrients (nitrogen (N), phosphorus (P), and potassium (K)), and micro-nutrients (copper (Cu), iron (Fe), manganese (Mn), zinc (Zn), and molybdenum (Mo)) among different wheat organs except for Fe. Nutrient allocation to plant tissues also varied between different organs. A high allocation of N, P, and Zn was observed in grain, K and Cu higher allocation was found in the stem, while flag leaf and glumes accumulated higher content of Mn and Mo, under Mo application as compared with Mo deficiency treatment. Mo application increased the uptake of N, P, K, Cu, Fe, Mn, Zn, and Mo in wheat organs compared to –Mo treatment. The relative increase of N, P, K, Cu, Fe, Mn, Zn and Mo uptake in the wheat grains was 58.5%, 13.0%, 29.7%, 20.2%, 31.5%, 12.7%, 52.8% and 621%, while in the flag leaf was 199.1%, 198.5%, 203.4%, 713.7%, 281.0%, 179.1%, 128.6% and 431.5%, respectively. The research findings suggest the supportive role of Mo application in increasing macro- and micro-nutrient uptake among wheat organs and grain yield through improving macro–micro-nutrient allocations.

Road safety guidelines are not properly implemented and are not diverse enough to counter an annual increase in traffic volume. The mitigation techniques of road regulating bodies have failed in minimizing road accidents with the increase in road users. Therefore, the purpose of this study is to provide valuable insight to the facilitators and decision-making stakeholders by predicting the number of accidents because it is an existential hurdle toward the prevention of accidents. Therefore, this study aims to create temporal patterns to forecast the accident rates in Pakistan by utilizing univariate time series analysis such as seasonal autoregressive integrated moving average (SARIMA) and exponential smoothing (ES) models. The results indicate that the ES model fitted better on accident data over the SARIMA model after calculating the lowest mean absolute error, root mean square error, mean absolute percentage error and normalized Bayesian information criterion. The study provides the guiding principles to implement the forecasted accident rates in the designing of roads to ensure the safety of end users which is a prime interest for accident rate collection agencies, decision-makers, design consultants and accident prevention departments.

Soil fertility plays a key role in citrus productivity. Therefore, it is necessary to explore the effects of soil amendments on soil fertility and citrus productivity and estimate carbon fractions’ suitability, which response to soil fertility and citrus productivity. A field experiment in a citrus orchard was conducted containing five treatments: local habit fertilization (LF), special fertilizer [25% lower NPK than LF, (SF)], special fertilizer, and rice straw mulching [0%, 12.5%, and 25% NPK higher than LF (SFRS25, SFRS37.5, and SFRS50, respectively)]. Total organic carbon (TOC), microbial biomass carbon (MBC), water-soluble organic carbon (WSOC), permanganate oxidizable carbon (ROC), available N, P, K, fruit yield, and quality were analyzed. Straw mulching and special fertilizer significantly increased soil carbon fractions, such as MBC and ROC. Such treatments also enhanced the soil available N, P, and K, subsequently elevated the fruit yield. MBC, available K, and available P showed a significantly positive correlation with citrus yield. Redundancy analysis indicated that MBC and ROC significantly explained 61.87% of the variation for available nutrients, suggesting that the increase of organic carbon fractions and microbial biomass could accelerate nutrient cycling for the plant. It proved that decrement application of special compound fertilizer with straw mulching raised fruit yield by altering soil carbon fractions to improve soil available nutrients or fertility. The MBC of soil labile carbon responded more sensitively to not only soil fertility but also citrus fruit yield.

Arbuscular mycorrhizae fungi (AMF) are a big player of the ecosystem which shows a major concern over plant nutrition by providing access to the soil-derived nutrients. Naturally, an intimate association between plant roots and AMF is observed. AMF are involved in improvement on the soil water regime and nutrient uptake both in the biotic and abiotic stress situations such as drought, temperature extreme, heavy metals, salinity, pathogen and metal pollution. This kind of symbiotic relationship between plant roots and fungal hyphae is observed to be 80% of the terrestrial plant species worldwide. In plant AMF association fungal hyphae are benefitted by obtaining sugar from the host plants root and host plants root are ameliorated by improved uptake of water and nutrients from soil surface. AMF have a dual role to manage the Zn nutrition in soil. For example below a critical Zn concentration, Zn uptake is enhanced by AMF application and above the critical level, Zn translocation to plant shoots is restricted. Synergistic association between Zn and AMF is important for sustainable yield and quality. It is observed that grain Zn content in the field is increased with applying AMF. AMF help in the plant growth, development and reproduction, as the Zn is essential for pollen tube formation. By AMF application there is an increment in the content of lycopene, vitamin C, vitamin A and antioxidant activities than non AMF plants in tomato. In traditional driven agriculture, inherent soil fertility is the major source of P with an occasional supply of manure for the crops. But after modernization in agriculture results in overexploitation of the P and results in low crop yield and farm income. Rock phosphate is the major source of the phosphatic fertilizer and is non-renewable which could be exhausted in the next 50–100 years. Moreover, the stimulation of secondary metabolites synthesis results in the improvement of crop quality by sustainable use of phosphatic fertilizers. So P application techniques which can also ameliorate AMF are widely promising. This is how AMF play a pivotal role in developing present era farming practices towards sustainable agriculture. Phytoremediation of heavy metals from different soil types has potential benefit of using AMF in soil. Mycorrhizae disrupt the uptake of the different heavy metals from the rhizosphere and movement from the root to the aerial parts. The major role of AMF in plant growth and development during stressful environments is to translocate important immovable nutrients like Cu, Zn and P and reducing metal toxicity in the host plant.

Accurate forecasting of key hydrological processes, such as rainfall, generally requires the use of auxiliary predictive hydrological variables. Data requirements can be reduced by using artificial intelligence models that are able to successfully capture the information contained in the historic observations of the target variable of interest. In this study, a novel Wavelet-coupled Multi-order Time Lagged Neural Network (WMTLNN) model is developed to accurately forecast rainfall by using previous rainfall records only. The study is conducted using daily rainfall data recorded in the period 2015–2017 at three meteorological stations (Astore, Chillas, and Gilgit) located in Upper Indus Basin (UIB), Pakistan. WMTLNN models are developed by introducing time lags up to ten days, Symlets 4 (sym4) wavelets and Daubechies wavelets with three vanishing moments (db3), and Maximal Overlap Discrete Wavelet Transformation (MODWT) to account for boundary effects in the forecasting mode. The performance of WMTLNN models is compared with that of Time Lagged Neural Network (TLNN) models, Wavelet-coupled Time Lagged Neural Network (WTLNN), and deep learning Long Short-Term Memory (LSTM) models. Comparative analysis indicates that WMTLNN models overcome the other models, with more than 80% forecasting accuracy for most of the cases, and a typical range of 0.85–0.95 accuracy in terms of NSE. The highest NSE value is 0.97 at Astore with LSTM model, 0.96 at Chillas with WMTLNN model, and 0.95 at Gilgit with WMTLNN model. Overall, wavelet transformation of time series data enhances efficiency and accuracy of rainfall forecast.

This analysis explores stagnation point in Jeffery liquid flow over a stretchable cylinder. Heat and mass transfer are investigated through Cattaneo–Christov model with double stratification, heat source and thermal relaxation. Moreover, the flow of liquid is caused by stretchable cylinder. Cylindrical coordinates are used for mathematical formulations. The acquired boundary layer problems for stretchable cylinder are dealt through homotopy analysis method. Results of variables appeared in governing equations are disclosed through graphs for flow, temperature, concentration and skin friction. The findings of the study show that higher values of ratio parameter and Deborah number in terms of relaxation time reduce magnitude of drag coefficient while reverse trend is noted for larger Deborah number in terms of retardation time and curvature parameter. Comparison of present work with previous published date is presented.

Global warming, energy consumption (EC), and food safety have caused an increase of focus regarding agricultural crop productivity with a principal focus on CEs from crop farming. This study analyzes Pakistan, India, and China's rice and wheat production rating through the CCR and SBM DEA framework. The recorded rice (0.60) and wheat (1.00) production, through the CCR approach, can be considered the highest productivity. The rating productivity of the parallel DMUs for the CCR (or BCC) framework average degree of technical productivity of SBM model of wheat and rice production, which does not adhere to the degree of 100% amongst all countries. Keeping the area's efficiency in mind, the average technical productivity rating recorded through CCR is 0.87, and SBM is 0.86 and is significantly lower than the ideal rating in the original DEA. By decreasing tomato output through farmers' productive operations, energy can be conserved by 21.4% compared to its current level by enhancing the utilization of essential resources, chemical fertilizers, farmyard manure, and water bear comparatively greater trading weights. It is eminent to decrease energy usage and carbon discharge in rice production. Similarly, the high yield and adequate rice plantation methods should be encouraged in the given region.

Sustainable development is significantly contributing the environmental degradation due to improvements in financial sector in One Belt and Road Initiative (BRI) region. Thus, the present research work constructs the sustainable development index for BRI. Afterwards, it unfolds the nexus of sustainable development-environmental degradation and also evaluates the role of financial development indicators in BRI economies. By utilizing the robust mean group, the present study quantifies the long-run marginal impacts of sustainable development, financial development indicators, energy consumption, and urban sprawl on environmental degradation, respectively. The marginal impacts infer an inverted U-shaped sustainable development environmental Kuznets curve in BRI region. The sustainable development, energy consumption, and urban sprawl are enriching the environmental degradation, whereas the financial development indicators have an adverse impact on environmental degradation by induction of interaction of sustainable development-financial development. Therefore, the improvements in financial development indicators will help to achieve the sustainable development. Note: + and _ depict the significant positive and negative impact respectively while illustrates ⇒ causal direction.

Burns are caused by various external factors, such as radiation, chemicals, electricity, hot surfaces or liquids, which can seriously damage the integrity of the skin. Due to the lack of blood vessel formation, immunosuppression, and sensitivity to various infections, third-degree burns can damage the entire skin layer and delay the healing process. Therefore, this study was planned to evaluate the therapeutic effects of nano ZnO, nano CUR alone and in the composite form in third-degree burns. Topical 1% w/w skin ointments of nano ZnO, Curcuma longa (C. longa) nanoparticles (nano-CUR) and a composite of ZnO and C. longa nanoparticles (nano ZnO/CUR composite) were formulated for the treatment of burn wounds after characterization. A total of 25 rabbits from the animal house were grouped in 4 treatment (nano ZnO, nano CUR, nano ZnO/CUR and positive control) groups with 5 rabbits in each, while 5th group as a negative control group. These rabbits of four treatment groups were branded with the red-hot iron bar having a diameter of 10 mm for 15 seconds to create two burn wounds on each rabbit after induction of anesthesia. Healing time and wound contraction rate were conducted at 7th, 14th, 21st and 28th day after wound infliction while histopathological examination was conducted at 28th day after woud infliction. The statistical evaluation showed that nano ZnO/CUR composite group took less time to heal wound (avg, 24.25D ± 0.5) as compared to other groups of nano ZnO (26.25D ± 0.5), nano CUR (28D ± 0.82) and positive control (36.25D ± 0.5) with a similar pattern as observed for contraction rate of the wound. Histopathological analysis showed higher collagen deposition, vascularization, angiogenesis and fibrosis by nano ZnO/CUR composite treated group as compared to other groups. The study concluded that the application of nano ZnO/CUR composite ointment will heal third-degree burn wounds rapidly as compared to solus alone application.

The objective was to design and develop a drug-in-adhesive-type transdermal patch formulation of metoclopramide HCl, which is used as an effective antiemetic, dopaminergic antagonist agent. In DIA patches, drug is directly embedded in the polymeric adhesive layer and permeates through the skin to provide systemic effect, avoiding gastrointestinal tract complications, including the first-pass metabolism. Six different patch formulations were prepared by a solvent evaporation method using varying metoclopramide HCl concentrations using acrylate polymer DURO-TAK® 387/2510 for adhesive support. In vitro permeation profiles and parameters were obtained by using the skin of hairless albino Wistar rats. The influence of drug content on the rate of permeation was investigated, and patch formulation was optimized based on Q12, flux, and lag time. The effect of permeation enhancers (EO and PG) on the permeation rate of metoclopramide HCl was also studied. The skin irritation study was performed to observe the hypersensitivity against the patch component. Stability studies of the optimized formulation of a transdermal patch for three months at three different temperatures were investigated. The transdermal patch formulation containing 10% w/w metoclopramide HCl was capable of effectively delivering metoclopramide HCl for systemic effect without any skin irritation. It has Q12 of 3.892 ± 0.0043 mg/cm2, flux rate of 0.2501 mg/cm2 h, and the coefficient of permeability of 6.25E−02 cm/h with a lag time of 0.442 h. The stability data revealed that the optimized patch formulation could be stored at 4 °C in the refrigerator with a shelf life of 3.53 months. This newly developed metoclopramide transdermal DIA patch is an effective alternative to oral delivery with desirable antiemetic activity.

Information on wind speed and wind power distribution is significant for a few reasons, for example, surveying wind assets, arranging wind cultivates, and limiting the liabilities for wind power improvement. This study provided an application of a new generalization of two-parameter generalized inverse Lindley distribution using the Marshall–Olkin family for analyzing wind speed and wind power characteristics. Some mathematical properties of the new distribution were studied. We had observed the suitability of new distribution as compared to the other well-known wind speed distributions such as Weibull, inverse exponential, inverted Kumaraswamy, inverse Weibull, inverse Lindley, and generalized inverse Lindley distribution. For this purpose, the time-based wind speed data is taken from the four stations of Pakistan as a case study. We conclude based on certain goodness of fit criteria that the newly developed distribution has a better fit as compared to the other wind speed distributions. Therefore, the new model can be used as an alternative distribution for the assessment of wind speed energy potential.