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Unmanned Aerial Vehicles (UAVs), commonly known as drones, show great potential in advancing the United Nations (UN) Sustainable Development Goals (SDGs), a collection of 17 worldwide targets outlined by the United Nations (UN) to tackle diverse social, economic, and environmental issues and foster sustainable development by 2030. As per the Federal Aviation Administration (FAA), UAVs can significantly improve areas of sustainability like wildlife and wildfire monitoring, precision agriculture, as well as healthcare. Furthermore, drones with communication capabilities are seen as key elements of non-terrestrial networks, and as enabling technologies for future 6G communication networks. This systematic literature review focuses on the role of UAV-enabled communications to achieve the SDGs. Our study is based on a thorough selection and analysis of scientific articles. Initially, we performed a broad search across three major databases: IEEE Xplore, Web of Science, and Scopus, yielding a set of 10,499 papers. Following a strict selection methodology (Preferred Reporting Items for Systematic Review and Meta-Analysis - PRISMA), we narrowed this set down to 28 key journal articles. Our analysis highlights six global targets that greatly benefit from UAV-enabled aerial communication. In order of impact, these are: “Sustainable Cities and Communities,” where UAVs improve security and disaster management; “Life on Land,” where drones help with wildlife monitoring and reforestation; “Industry, Innovation, and Infrastructure,” where UAVs (Unmanned Aerial Vehicles) aid in infrastructure inspection; “No Hunger,” where drones improve agricultural practices; “‘Good Health and Wellbeing,” where UAVs assist with disease prediction and monitoring; and “Clean water and sanitation,”where drones play a crucial role in efficiently monitoring water quality and distribution. In summary, this paper offers a detailed look at the applications of UAVs in achieving the SDGs through aerial communications. By identifying areas of major impact and spotting gaps and weaknesses in current research, this review article aims to guide future research and policy-making in sustainable drone applications.

This paper presents a geometry-based three-dimensional Probability of Line of Sight $(P_{\mathrm {LoS}})$ model for generic urban environments. The existing $P_{\mathrm {LoS}}$ models are mostly empirical, based on measurements or ray-tracing simulations at specific environments. To enable Unmanned Aerial Vehicle (UAV) communication in various environments, it is urgently necessary to develop an analytical model with high parameter scalability. Through introducing the ITU model that describes a built-up environment with three parameters, we derive a closed-form $P_{\mathrm {LoS}}$ model with the inputs of city built-up parameters, UAV altitude, elevation $\theta $ and azimuth $\varphi $ angles between UAV and User Equipment (UE). Furthermore, we develop a geometry-based simulator to validate the proposed analytical model. The results show good agreements between the simulated results, analytical results, and 3GPP $P_{\mathrm {LoS}}$ measurements. We demonstrate that the existing models provide less accurate results, which calls for re-evaluating the use cases and performance of UAV-mounted communication equipment in urban environments.

The process of developing of new drugs is greatly hampered by their inadequate physicochemical, pharmacokinetic, and intrinsic characteristics. In this regard, the selected chloro indolinone, (Z)-6-chloro-3-(2-chlorobenzylidene)indolin-2-one (C1), and nitro indolinone, (Z)-6-chloro-3-(2-nitrobenzylidene)indolin-2-one (C2), were subjected to SwissADME and density function theory (DFT) analysis. For compounds C1 and C2, the BOILED-Egg pharmacokinetic model predicted intestinal absorption, blood–brain barrier (BBB) penetration, and p-glycoprotein interaction. According to the physicochemical analysis, C1 has exceptional drug-like characteristics suitable for oral absorption. Despite only being substrates for some of the major CYP 450 isoforms, compounds C1 and C2 were anticipated to have strong plasma protein binding and efficient distribution and block these isoforms. The DFT study using the B3LYP/6-311G(d,p) approach with implicit water effects was performed to assess the structural features, electronic properties, and global reactivity parameters (GRP) of C1 and C2. The DFT results provided further support for other studies, implying that C2 is more water-soluble than C1 and that both compounds can form hydrogen bonds and (weak) dispersion interactions with other molecules, such as solvents and biomolecules. Furthermore, the GRP study suggested that C1 should be more stable and less reactive than C2. A concentration-dependent 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radical scavenging activity was shown by both C1 and C2. In brief, this finding has provided a strong foundation to explore further the therapeutic potential of these molecules against a variety of human disorders.

Cotton (Gossypium spp.) yield is reduced by stress. In this study, high temperature (HT) suppressed the expression of the jasmonic acid (JA) biosynthesis gene allene oxide cyclase 2 (GhAOC2), reducing JA content and causing male sterility in the cotton HT-sensitive line H05. Anther sterility was reversed by exogenous application of methyl jasmonate (MeJA) to early buds. To elucidate the role of GhAOC2 in JA biosynthesis and identify its putative contribution to the anther response to HT, we created gene knockout cotton plants using the CRISPR/Cas9 system. Ghaoc2 mutant lines showed male-sterile flowers with reduced JA content in the anthers at the tetrad stage (TS), tapetum degradation stage (TDS), and anther dehiscence stage (ADS). Exogenous application of MeJA to early mutant buds (containing TS or TDS anthers) rescued the sterile pollen and indehiscent anther phenotypes, while ROS signals were reduced in ADS anthers. We propose that HT downregulates the expression of GhAOC2 in anthers, reducing JA biosynthesis and causing excessive ROS accumulation in anthers, leading to male sterility. These findings suggest exogenous JA application as a strategy for increasing male fertility in cotton under HT.

Artificial intelligence (AI)-based models have emerged as powerful tools in financial markets, capable of reducing investment risks and aiding in selecting highly profitable stocks by achieving precise predictions. This holds immense value for investors, as it empowers them to make data-driven decisions. Identifying current and future trends in multi-class forecasting techniques employed within financial markets, particularly profitability analysis as an evaluation metric is important. The review focuses on examining stud-ies conducted between 2018 and 2023, sourced from three prominent academic databases. A meticulous three-stage approach was employed, encompassing the systematic planning, conduct, and analysis of the se-lected studies. Specifically, the analysis emphasizes technical assessment, profitability analysis, hybrid mod-eling, and the type of results generated by models. Articles were shortlisted based on inclusion and exclusion criteria, while a rigorous quality assessment through ten quality criteria questions, utilizing a Likert-type scale was employed to ensure methodological robustness. We observed that ensemble and hybrid models with long short-term memory (LSTM) and support vector machines (SVM) are being more adopted for financial trends and price prediction. Moreover, hybrid models employing AI algorithms for feature engineering have great potential at par with ensemble techniques. Most studies only employ performance metrics and lack utilization of profitability metrics or investment or trading strategy (simulated or real-time). Similarly, research on multi-class or output is severely lacking in financial forecasting and can be a good avenue for future research.

Industrial applications of fibre-reinforced concrete (FRC) in structures require extensive experimental and analytical investigations of the FRC material properties. For design purposes and applications involving the flexural loading of the member, it is essential to have a predictive model for the flexural strength of the FRC material. In the present paper, a fracture mechanics approach based on Bridged Crack Model (BCM) is used to predict the flexural strength of steel fibre-reinforced concrete (SFRC) beams. The model assumes a quadratic tension-softening relationship (σ-δ) governing the bridging action of the steel fibres and a linear profile of the propagating crack. The proposed tension-softening relationship is considered valid for a wide range of fibre-reinforced concrete materials based on the knowledge of either the material micromechanical parameters (such as fibre volume fraction, fibre/matrix bond strength, fibre length, and fibre tensile strength) or an actual experimentally-measured σ-δ relationship. The flexural strength model thus obtained allows the prediction of the flexural strength of SFRC and study the variation of the latter as a function of the micromechanical parameters. An experimental program involving the flexural testing of 13 SFRC prism series was carried out to verify the prediction of the proposed model. The SFRC mixes incorporated two types of steel fibres (straight-end and hooked-end), four different concrete compressive strengths (40, 50, 60, and 70 MPa), three different fibre volume fractions (1, 1.5, and 2%), and three specimen depths (100, 150, and 200 mm). The experimental results were compared to the predictions of the proposed flexural strength model, and a reasonable agreement between the two has been observed. The model provided a useful physical explanation for the observed variation of flexural strength as a function of the test variables investigated in this study.

Sustainable food and nutrition security solutions demand integration and alignment in public policies, particularly in the post-COVID-19 scenarios. The introduction of integrated public policies to address the food and nutrition needs in Pakistan is an immediate requirement. This study has applied the Foster, Greer and Thorbecke (FGT) index to estimate food and nutrition security dimensions through primary and secondary data. This analysis reveals that food utilization and sustainability have destabilized and deteriorated in Pakistan in recent years. It shows that non-farmers are more food insecure (8 percent) than farmers (4 percent) and this ratio has increased from 2008 to 2018. Food insecurity in terms of food availability and food accessibility has decreased. A holistic approach in public policies toward food security is the clarion call of the time. Therefore, the paper recommends that more focus should be given to knowledge transmission about dietary diversity, provision of quality education, and health facilities in the formulation as well as execution of food security policies.

Objectives:The aim of this study was to investigate the prevalence of symptoms of computer vision syndrome (CVS) and identify its associated risk factors among computer-using bank workers in Pakistan.Materials and Methods:This cross-sectional study was conducted on computer-using bank workers. The data collection procedure included a self-administered questionnaire and comprehensive ocular health examination. The prevalence of CVS and its associated risk factors were investigated. The chi-square test was used to study the significance of the association of CVS with potential risk factors.Results:Of 127 participants, 95 (74.8%) were men. Most of the participants (n=53; 41.7%) were in the 30-40 years age group. A total of 101 participants (79.5%) reported any ocular symptom, with burning eyes being the most frequent ocular symptom (77.2%). General body fatigue was the most common non-ocular symptom of CVS (92.9%), followed by headache (83.5%). Out of 127 participants, 71 men and 30 women had some degree of CVS. Female participants had significantly higher risk of CVS than male participants (p=0.01). Total duration of computer use per day and duration of uninterrupted computer use were significantly associated with the occurrence of CVS (p=0.001 and p=0.008, respectively). No significant association was found between CVS and distance from computer screen (p=0.89), frequency of breaks (p=0.18), or font size (p=0.12).Conclusion:A high prevalence of CVS-related symptoms was observed among computer-using bank workers. Non-ocular symptoms associated with computer use were more common than ocular symptoms (92.9% vs. 77.2%).

Computational pharmacology and chemistry of drug-like properties along with pharmacokinetic studies have made it more amenable to decide or predict a potential drug candidate. 4-Hydroxyisoleucine is a pharmacologically active natural product with prominent antidiabetic properties. In this study, ADMETLab 2.0 was used to determine its important drug-related properties. 4-Hydroxyisoleucine is compliant with important drug-like physicochemical properties and pharma giants’ drug-ability rules like Lipinski’s, Pfizer, and GlaxoSmithKline (GSK) rules. Pharmacokinetically, it has been predicted to have satisfactory cell permeability. Blood–brain barrier permeation may add central nervous system (CNS) effects, while a very slight probability of being CYP2C9 substrate exists. None of the well-known toxicities were predicted in silico, being congruent with wet lab results, except for a “very slight risk” for respiratory toxicity predicted. The molecule is non ecotoxic as analyzed with common indicators such as bioconcentration and LC50 for fathead minnow and daphnia magna. The toxicity parameters identified 4-hydroxyisoleucine as non-toxic to androgen receptors, PPAR-γ, mitochondrial membrane receptor, heat shock element, and p53. However, out of seven parameters, not even a single toxicophore was found. The density functional theory (DFT) study provided support to the findings obtained from drug-like property predictions. Hence, it is a very logical approach to proceed further with a detailed pharmacokinetics and drug development process for 4-hydroxyisoleucine.

Various derivatives of thiazolidine-2,4-dione (C1–C5) were designed and synthesized by chemical reaction with 4-nitrobenzaldehyde using Knoevenagel reaction conditions which results in the reduction of nitro group to amine and further modification results in target compounds. The chemical structures of all the 2,4-thiazolidinedione derivatives have been elucidated by 1H and 13C NMR spectroscopy. These compounds were further characterized by in silico ADME (absorption, distribution, metabolism, and excretion) studies. The pharmacokinetic properties were assessed by SwissADME software. The in silico ADME (absorption, distribution, metabolism, and excretion) assessment reveals that all derivatives (C1 to C5) have 5 to 7 rotatable bonds. Lipophilicity and water solubility showed that C1, C2, and C4 are water soluble except for C3 and C5 which are moderately soluble. All the compounds have high GI absorption except C3. None of the derivatives are blood-brain barrier permeant. Drug metabolism of TZDs derivatives showed that C3 was identified as an inhibitor of CYP2C9 and C5 as an inhibitor of CYP1A2 and CYP2C19. Drug likeness properties indicate that C1 has only one violation of the Ghose rule while C3 has violations in the Ghose and Egan rules. The in silico pharmacokinetic studies revealed high GI absorption and the inability to pass blood-brain barrier which can be further assessed by in vitro and in vivo antihyperglycemic activity. This study will contribute to providing TZDs derivatives with an improved pharmacokinetic profile and decreased toxicity.

Load Flow and Short Circuit Analyses have been performed on standard IEEE 9-Bus System. This paper is going to describe in detail how these analyses were performed and what were the results achieved. In addition to the performance of these two analyses on the standard test system, they were also performed by removing a voltage- controlled generator from the test system. It is revealed that by removal of a generator, the magnitude of short- circuit fault current in a system would reduce as compared to the case where all generators were present in the system

Abstract Zinc (Zn) deficiency can severely inhibit plant growth, yield, and enzymatic activities. Zn plays a vital role in various enzymatic activities in plants. Arbuscular mycorrhizal fungi (AMF) play a crucial role in improving the plant’s Zn nutrition and mitigating Zn stress effects on plants. The current study was conducted to compare the response of inoculated and non-inoculated maize (YH 1898) in the presence of different levels of zinc under greenhouse conditions under a Zn deficient condition. There were two mycorrhizal levels (i.e., M + with mycorrhizae, M- without mycorrhizae) and five Zn levels (i.e., 0, 1.5, 3, 6, and 12 mg kg-1), with three replicates following completely randomized design. At the vegetative stage (before tillering), biochemical, physiological, and agronomic attributes were measured. The results showed that maize plants previously inoculated with AMF had higher gaseous exchange traits, i.e., a higher stomatal conductance rate, favoring an increased photosynthetic rate. Improvement in antioxidant enzyme activity was also observed in inoculated compared to non-inoculated maize plants. Moreover, AMF inoculation also played a beneficial role in nutrients availability and its uptake by plants. Higher Zn12 (12 mg Zn kg-1 soil) treatment accumulated a higher Zn concentration in soil, root, and shoot in AMF-inoculated than in non-inoculated maize plants. These results are consistent with mycorrhizal symbiosis beneficial role for maize physiological functioning in Zn deficient soil conditions. Additionally, AMF inoculation mitigated the stress conditions and assisted nutrient uptake by maize.

Archeology deals with the common inheritance of human beings. Among those historical antiques, these are such records which remind us of those nations who were condemned due to their disobedience to Divine instructions. The purpose of preserving such sites as per Divine Scheme, was to make them lessons for the upcoming generations. More recently such trends have emerged where these sites have been made places of recreation. As a reaction to this trend, another approach within religious thought has emerged that instructs for complete elimination of such sites in order to discourage tourist activities at such places. This article takes a moderate path and tries to highlight the real teachings of Islam about such sites.

The Kumaraswamy distribution is one of the most popular probability distributions with applications to real life data. In this paper, an extension of this distribution called the Libby-Novick Kumaraswamy (LNK) distribution is presented which is believed to provide greater flexibility to model scenarios involving skew-normal data than original one. Analytical expressions for various mathematical properties including its cdf, quantile function, moments, factorial moments, conditional momennts, moment generating function, characteristic function, vitality function, information generating function, reliability measures, mean deviations, mean residual function, Bonferroni and Lorenz Curves are derived.The parameters’ estimation of LNK distribution is undertaken using the method of maximum likelihood estimation. A simulation study for different values of sample sizes, to assess the performance of the parameters of LNK distribution is provided. For illustration and performance evaluation of LNK distribution three real-life data sets from the field of engineering and science adapted from earlier studies are used. On comparing the results to previously used methods, LNK distribution shows that it can give consistently better fit than other existing important lifetime models. It is found that the LNK distribution is more suitable and useful to study lifetime data.

he acoustic emission technique has been applied successfully for the identification, characterization, and localization of deformations in civil engineering structures. Numerous localization techniques, such as Modal Acoustic Emission, Neural Networks, Beamforming, and Triangulation methods with or without prior knowledge of wave velocity, have been presented. Several authors have conducted in-depth research in the localization of AE sources. However, existing review papers do not focus on the performance evaluation of existing source localization techniques. This paper discusses these techniques based on the number of sensors used and the geometry of the structures of interest. Furthermore, it evaluates them on the basis of their performance. At the end of this paper, a comparative analysis of existing methods has been presented based on their basic principles, key strengths, and limitations. A deep learning circular sensor cluster-based solution has the potential to provide a low-cost reliable localization solution for acoustic emission sources.

Abstract Background Statins are considered as standard drugs to control cholesterol levels, but their use is also associated with renal hypertrophy, hemorrhagic stroke, hepatomegaly, and myopathy. Murraya koenigii is an herb that is used in traditional cuisine and as a medicine in South Asia. Here we assessed the antidyslipidemic and antiatherosclerotic effects of this spice in repeated heated mix vegetable oils (RHMVO)-induced atherosclerotic models. Methods Aqueous extract of M. koenigii leaves (Mk LE) was prepared and its phytoconstituents were determined. Rabbits were divided into 5 groups (n = 10). Except for the control group, all the other four groups were treated with RHMVO for 16 weeks (dose = 2 ml/kg/day) to induce dyslipidemia and atherosclerosis. These groups were further treated for 10 weeks either with 300 and 500 mg/kg/day Mk LE, lovastatin, RHMVO, or left untreated. Body and organ weights were measured along with oxidative stress and tissue damage parameters. Lipid profile and hepatic function markers were studied. Atheroma measurement and histopathological examination were also performed in control and treated groups. Results Mk LE significantly (p

This paper explores the impact of fiscal spending on key macroeconomic indicators for Pakistan economy using an estimated open economy new Keynesian dynamic stochastic general equilibrium (DSGE) model. Results show that a positive shock to government consumption leads to fall in private consumption, private investment and exports owing to negative wealth effect, rise in interest rate and domestic currency appreciation, respectively. Imports and inflation also rise. Estimated values of present value fiscal multipliers are 0.54, 0.29 and 0.18 after 1 year, 5 years and 10 years, respectively. These results show that although positive in the short run, yet the magnitude of the fiscal multiplier is very low in the case of Pakistan. Sensitivity analysis shows that the value of the multiplier marginally rises with rise in degree of price stickiness. Transitory shocks have a substantially higher multiplier relative to persistent shocks.

Gait is the locomotion attained through the movement of limbs and gait analysis examines the patterns (normal/abnormal) depending on the gait cycle. It contributes to the development of various applications in the medical, security, sports, and fitness domains to improve the overall outcome. Among many available technologies, two emerging technologies that play a central role in modern day gait analysis are: A) wearable sensors which provide a convenient, efficient, and inexpensive way to collect data and B) Machine Learning Methods (MLMs) which enable high accuracy gait feature extraction for analysis. Given their prominent roles, this paper presents a review of the latest trends in gait analysis using wearable sensors and Machine Learning (ML). It explores the recent papers along with the publication details and key parameters such as sampling rates, MLMs, wearable sensors, number of sensors, and their locations. Furthermore, the paper provides recommendations for selecting a MLM, wearable sensor and its location for a specific application. Finally, it suggests some future directions for gait analysis and its applications.

Unlike straight web I-girders, the construction industry’s demand for corrugated web steel girders is increasing due to their high shear strength without needing transverse stiffeners. Although the corrugation fabrication cost could be high, savings on material, transportation, and erection costs can compensate for the expenditures needed to build flat-plated girders with stiffeners. This study investigates the shear behavior of straight and corrugated webs with different geometries and corrugation profiles (triangular and trapezoidal) through laboratory testing. Following a detailed parametric study, the results of the experimental program were used to formulate a reliability-based design optimization (RBDO) problem to achieve target reliability. When applied to two case studies related to girders of a building and a bridge, the RBDO demonstrated that it is possible to design girders with corrugated webs to achieve economic designs in terms of material volume in the range of 20% to 40% with thinner webs and without the need for transverse stiffeners.

This article presents experimental data and nonlinear finite element analysis (NLFEA) modeling for an innovative buckling restrained bracing (BRB) system. The data were collected from qualification testing of introduced BRBs per the AISC 341 test provision and finite element modeling. The BRB is made of three parts: core bar, restraining unit, and end units, in which duplicates of three different core bar cross sections (i.e., fully threaded, threaded notched, and smooth shaved) were tested. The BRBs introduced in this research come with innovative end parts, so-called fingers. These fingers provide the longitudinal gap required in every BRB system and simultaneously prevent buckling of the core bar at the end regions at both ends of the BRB sample, thus facilitating an easy core replacement if it gets damaged in the event of an earthquake. The measured parameters were the applied cyclic load and the corresponding displacement. Analysis of the acquired data illustrated an almost symmetric hysteric behavior with a little higher capacity under compression but a noticeable overall ductility of 4. Moreover, finite element modeling data for one type of core bar (fully threaded) were curated. The data presented in this paper will be valuable for fabricating BRBs in practice and further research on the topic considered.

Zinc (Zn) is a fundamental micronutrient required by all living organisms. Zn deficiency among children under 5 years, pregnant, and child-bearing women has been identified in developing countries such as Pakistan. Biofortified crops can increase micronutrient levels and decrease deficiencies. Meanwhile, consumer acceptance is essential, given that genetic alterations can occur during biofortification, resulting in changes in sensory traits and the quality of grains. Therefore, the present study focuses on the determining factors for consumer acceptance of Zn-biofortified wheat., an experimental survey was conducted to achieve the study's objectives. Qualitative and quantitative data were collected and analyzed from 203 respondents in the Punjab province. The results regarding sensory perceptions revealed that people attached great importance to the appearance of the chapati prepared with Zn-biofortified wheat. Therefore, they were willing to purchase Zn-biofortified wheat when asked to choose between the conventional wheat and the Zn-biofortified wheat. Moreover, the probit model illustrates that the level of education in the family and having young children aged under 5 years in the household positively impacted the acceptance of Zn-biofortified wheat among the participants. The findings suggest that there is significant scope for promoting Zn-biofortified wheat in the country. It is also imperative to ensure its availability across various regions so that households with weak purchasing power can buy and address their Zn deficiency. Furthermore, policymakers could introduce reforms targeting business communities for food management, keeping Zn-biofortified wheat in the priority stream.

Cloud computing is a rapidly growing paradigm which has evolved from having a monolithic to microservices architecture. The importance of cloud data centers has expanded dramatically in the previous decade, and they are now regarded as the backbone of the modern economy. Cloud-based microservices architecture is incorporated by firms such as Netflix, Twitter, eBay, Amazon, Hailo, Groupon, and Zalando. Such cloud computing arrangements deal with the parallel deployment of data-intensive workloads in real time. Moreover, commonly utilized cloud services such as the web and email require continuous operation without interruption. For that purpose, cloud service providers must optimize resource management, efficient energy usage, and carbon footprint reduction. This study presents a conceptual framework to manage the high amount of microservice execution while reducing response time, energy consumption, and execution costs. The proposed framework suggests four key agent services: (1) intelligent partitioning: responsible for microservice classification; (2) dynamic allocation: used for pre-execution distribution of microservices among containers and then makes decisions for dynamic allocation of microservices at runtime; (3) resource optimization: in charge of shifting workloads and ensuring optimal resource use; (4) mutation actions: these are based on procedures that will mutate the microservices based on cloud data center workloads. The suggested framework was partially evaluated using a custom-built simulation environment, which demonstrated its efficiency and potential for implementation in a cloud computing context. The findings show that the engrossment of suggested services can lead to a reduced number of network calls, lower energy consumption, and relatively reduced carbon dioxide emissions.

Cereals are the main source of human food on our planet. The ever-increasing food demand, continuously changing environment, and diseases of cereal crops have made adequate production a challenging task for feeding the ever-increasing population. Plant breeders are striving their hardest to increase production by manipulating conventional breeding methods based on the biology of plants, either self-pollinating or cross-pollinating. However, traditional approaches take a decade, space, and inputs in order to make crosses and release improved varieties. Recent advancements in genome editing tools (GETs) have increased the possibility of precise and rapid genome editing. New GETs such as CRISPR/Cas9, CRISPR/Cpf1, prime editing, base editing, dCas9 epigenetic modification, and several other transgene-free genome editing approaches are available to fill the lacuna of selection cycles and limited genetic diversity. Over the last few years, these technologies have led to revolutionary developments and researchers have quickly attained remarkable achievements. However, GETs are associated with various bottlenecks that prevent the scaling development of new varieties that can be dealt with by integrating the GETs with the improved conventional breeding methods such as speed breeding, which would take plant breeding to the next level. In this review, we have summarized all these traditional, molecular, and integrated approaches to speed up the breeding procedure of cereals.

Zinc (Zn) is an important micronutrient for plants, whose deficiency in alkaline soils creates hurdles in the achievement of optimum crop growth. Moreover, overuse of phosphorus (P) fertilizers often causes Zn immobilization in the soil. The employment of arbuscular mycorrhizal fungi (AMF) could be potentially environmentally friendly technology in this regard. Therefore, a pot experiment was conducted to assess the beneficial role of AMF (Glomus species) on maize under low and high P and Zn levels. Seven levels of Zn (0, 20, 40, 60, 80, 100 and 120 mg Zn kg−1 soil ZnSO4·7H2O) and three levels of P (0, 14.5, 29 and 58 kg ac−1 as single superphosphate) were applied with (M+) and without AMF (M−). The results showed that a high application rate of Zn (100 and 120 mg Zn kg−1 soil) restricted P translocation in plants and vice versa. Moreover, the nutritional status of mycorrhizal plants (AM) was better than non-mycorrhizal (NM) plants. AM plants showed a maximum positive response at 20 mg Zn kg−1 soil, or 29 kg P ac−1. In response to 20 mg Zn kg−1 soil, root colonization was maximum, which enhanced the maize nutrient concentration in shoots. In conclusion, AMF inoculation (M+) with P (29 kg ac−1) and Zn (20 mg kg−1) is efficacious for improving maize’s growth and nutrition. More investigations are suggested at the field level under different agroclimatic zones to ascertain whether P (29 kg ac−1) or Zn (20 mg kg−1) with AMF is the best treatment for maize growth optimization.

Innovation adoptions in agriculture sustain high total factor productivity (TFP) growth and overcome a potential production gap, which is beneficial for food security. Research and development (R&D) innovation adoption in agriculture sector is dependent on producers’ willingness to adopt, knowledge capital spillovers, and financial capacity. This research aims to investigate the impact of R&D innovation adoption and climate factors on agriculture TFP growth in Pakistan. The annual time series data were collected from different sources for the period of 1972–2020. For measuring the agriculture TFP, this study adopted the Cobb Douglas and Translog production functions. To analyze the impact of R&D innovation adoption and climate change on agricultural productivity, the dynamic autoregressive distributive lag (ARDL) and two-stage least square (TSLS) approaches were applied for regression analysis. The study outcomes highlight that the agricultural innovation adoption has a significantly positive impact on agriculture TFP growth in Pakistan with weak farmers’ absorptive ability. According to the results, agriculture tractors, innovative seed distribution, and fertilizer consumptions make a significantly positive contribution to agriculture TFP growth. Further, rainfall shows a positive and significant impact on agricultural productivity, where a moderate climate is beneficial for agricultural productivity. The estimation results contain policy suggestions for sustainable R&D adoption and agrarians’ absorptive ability. Based on the obtained results, it has been suggested that producers should focus on R&D innovation adoption to attain higher productivity. The government needs to emphasize innovative technology adoption, specifically to implement the extension services to increase farmers’ education, skills based training, and networking among the farmers to enhance their knowledge capital and absorptive ability. The farmers should also focus on the adoption of climate smart agriculture that can be achieved through the proper utilization of rainwater. For this purpose, the government needs to develop small community dams and large-scale dams for better use of rainwater harvesting.

Adulteration of meat products is a delicate issue for people around the globe. The mixing of lard in meat causes a significant problem for end users who are sensitive to halal meat consumption. Due to the highly similar lipid profiles of meat species, the identification of adulteration becomes more difficult. Therefore, a comprehensive spectral detailing of meat species is required, which can boost the adulteration detection process. The experiment was conducted by distributing samples labeled as “Pure (80 samples)” and “Adulterated (90 samples)”. Lard was mixed with the ratio of 10–50% v/v with beef, lamb, and chicken samples to obtain adulterated samples. Functional groups were discovered for pure pork, and two regions of difference (RoD) at wavenumbers 1700–1800 cm−1 and 2800–3000 cm−1 were identified using absorbance values from the FTIR spectrum for all samples. The principal component analysis (PCA) described the studied adulteration using three principal components with an explained variance of 97.31%. The multiclass support vector machine (M-SVM) was trained to identify the sample class values as pure and adulterated clusters. The acquired overall classification accuracy for a cluster of pure samples was 81.25%, whereas when the adulteration ratio was above 10%, 71.21% overall accuracy was achieved for a group of adulterated samples. Beef and lamb samples for both adulterated and pure classes had the highest classification accuracy value of 85%, whereas chicken had the lowest value of 78% for each category. This paper introduces a comprehensive spectrum analysis for pure and adulterated samples of beef, chicken, lamb, and lard. Moreover, we present a rapid M-SVM model for an accurate classification of lard adulteration in different samples despite its low-level presence.

Falls are unusual actions that cause a significant health risk among older people. The growing percentage of people of old age requires urgent development of fall detection and prevention systems. The emerging technology focuses on developing such systems to improve quality of life, especially for the elderly. A fall prevention system tries to predict and reduce the risk of falls. In contrast, a fall detection system observes the fall and generates a help notification to minimize the consequences of falls. A plethora of technical and review papers exist in the literature with a primary focus on fall detection. Similarly, several studies are relatively old, with a focus on wearables only, and use statistical and threshold-based approaches with a high false alarm rate. Therefore, this paper presents the latest research trends in fall detection and prevention systems using Machine Learning (ML) algorithms. It uses recent studies and analyzes datasets, age groups, ML algorithms, sensors, and location. Additionally, it provides a detailed discussion of the current trends of fall detection and prevention systems with possible future directions. This overview can help researchers understand the current systems and propose new methodologies by improving the highlighted issues.

The rapid development in wireless technologies is positioning the Internet of Things (IoT) as an essential part of our daily lives. Localization is one of the most attractive applications related to IoT. In the past few years, localization has been gaining attention because of its applicability in safety, health monitoring, environment monitoring, and security. As a result, various localization-based wireless frameworks are being presented to improve such applications’ performances based on specific key performance indicators (KPIs). Therefore, this paper explores the recently proposed localization schemes in IoT. Initially, this paper explains the major KPIs of localization. After that, a thorough comparison of recently proposed localization schemes based on the KPIs is presented. The comparison includes an overview, architecture, network structure, performance parameters, and target KPIs. At the end, possible future directions are presented for the researchers working in this domain.

Brain-Computer Interfaces (BCIs) based on visual evoked potentials (VEPs) allow high communication speeds and accuracies. The fastest speeds can be achieved if targets are identified in a synchronous way (i.e., after a pre-set time period the system will produce a command output). The duration a target needs to be fixated on until the system classifies an output command affects the overall system performance. Hence, extracting a data window dedicated for the classification is of critical importance for VEP-based BCIs. Secondly, unintentional fixation on a target could easily lead to its selection. For the practical usability of BCI applications it is desirable to distinguish between intentional and unintentional fixations. This can be achieved by using threshold-based target identification methods. The study explores personalized dynamic classification time windows for threshold-based time synchronous VEP BCIs. The proposed techniques were tested employing the SSVEP and the c-VEP paradigm. Spelling performance was evaluated using an 8-target dictionary-supported BCI utilizing an n-gram word prediction model. The performance of twelve healthy participants was assessed with the information transfer rate (ITR) and accuracy. All participants completed sentence spelling tasks, reaching average accuracies of 94% and 96.3% for the c-VEP and the SSVEP paradigm, respectively. Average ITRs around 57 bpm were achieved for both paradigms.

A new twenty-first century skills framework and a 19-item scale was developed to bridge the gap between science and practice. A self-reporting 19-item scale was developed to measure twenty-first century skills of faculty and non-faculty staff of agri varsities. A total of 49 items were generated using deduction approach for four skills: communication and collaboration, leadership and responsibility, problem-solving and decision-making, and creativity and innovation. Two content validity techniques were used that reduced the number of items to 29. Exploratory factor analysis was conducted in Mplus and items with poor loadings and cross-loadings were removed in each round. After five rounds of EFA, a promising 19-item scale was identified that fit the data well based on multiple model fit indices. Confirmatory factor analysis further confirmed the construct validity of the items and a four construct scale was identified where creativity was the only skill that failed to load. The reliability of the scale was measured using Cronbach’s alpha which was above 0.70 for all the factors. Convergent and discriminant validity was analyzed using AVE, shared variance, and factor loadings. The implication and limitations of the scale were discussed.

Zinc (Zn) concentration in soil varies from deficient to toxic. Its deficiency, as well as toxicity, through imbalanced application and cropping in industrial sites can reduce maize growth and yield. Therefore, balanced Zn application is necessary to save resources and achieve optimum growth and yield in maize. Arbuscular mycorrhizal fungi (AMF) can provide tolerance to the host plant against Zn-induced stress. Inoculation with AMF helps in regulating the uptake of Zn and enhances the growth and yield of crops. Different application rates of Zn (0, 20, 40, 60, 80, 100, and 120 mg Zn kg−1) were applied with inoculation with AMF (AM) and without AMF (NM). Results showed that root colonization was 45% higher in AMF-inoculated plants than non-inoculated plants. A significant increase in plant height (15%), number of leaves (35.4%), cob weight (4.39%), 1000-grain weight (10.5%), and biological yield (42.2%) signified the efficacious functioning of Zn20 + AM over sole inoculation with AM. We also observed that AMF inoculation with Zn20 helped to improve photosynthesis, transpiration, and stomatal conductance. Furthermore, both Zn20 + AM and Zn20 + AM significantly increased total soluble protein compared with AM. Higher application rates of zinc, i.e., Zn80 and Zn120, induced Zn toxicity with (AM) and without (NM) AMF. In conclusion, Zn20 + AM is an effective treatment to achieve better growth and maize yield without Zn deficiency or toxicity.

We present results of calibration-free laser-induced breakdown spectroscopy (CF-LIBS) and energy-dispersive X-ray (EDX) analysis of natural colorless topaz crystal of local Pakistani origin. Topaz plasma was produced in the ambient air using a nanosecond laser pulse of width 5 ns and wavelength 532 nm. For the purpose of detection of maximum possible constituent elements within the Topaz sample, the laser fluences were varied, ranging 19.6–37.6 J·cm−2 and optical emission from the plasma was recorded within the spectral range of 250–870 nm. The spectrum obtained has shown the presence of seven elements viz. Al, Si, F, O, H, Na and N. Results shows that the fluorine was detected at laser fluence higher than 35 J·cm−2 and plasma temperature of >1 eV. Al and Si were found as the major compositional elements in topaz crystals. The ratios of concentrations of Al and Si were found as 1.55 and 1.59 estimated by CF-LIBS and EDX, respectively. Furthermore, no impurity was found in the investigated colorless topaz samples.

The development in field of hybrid vehicles, telecommunication and energy sectors require dielectric materials having high-energy storage density with optimum thermal stability to operate in certain environment. To fulfil such requirement a new set of materials along the ternary solid solutions of 0.92Bi _0.5(1-x) -La _(x) Na _0.5 TiO _3 -0.06Ba(Zr _0.2 Ti _0.8 )O _3 -0.02NaNbO _3 (NB _1-x L _x T-BZT-NN) (x = 0, 0.03, 0.05, 0.07) were fabricated through solid-state mix oxide route. The XRD patterns analysis confirmed a structural phase transformation from rhombohedral to the tetragonal-P4bm phase when x content increased from 0 to 0.07. The SEM study revealed, dense microstructure for all ceramics accompanied by a decrease in the average grain from 1.66 μ m to 1.05 μ m leading to high densities for these materials with an increase in the x content. The dielectric breakdown field increased from ∼115 to 137 kV cm ^−1 resulting in an increase in recoverable energy density from ∼0.68 to 1.14 J cm ^−3 with the increase in x content. Furthermore, excellent temperature stability (±15%) in dielectric permittivity was observed in a wide temperature range for each ceramic. In the present study, a recoverable energy density of 1.14 J cm ^−3 along with an efficiency of 70.6% was obtained for the composition of x = 0.07.

In recent years, reproduction of human mechanical hand with upgraded abilities is one of the major concerns. This paper addresses the problems of underactuated robotic hand with low cost design as it avoids electromyogram (EMG) sensors. The main goal is to balance the hand in the way, like grabbing, speed, and power, and provide a more robust and cost effective solution. All fingers have some mechanical consistency for picking up objects in a better way. A Flex sensor is attached to all fingers and it is interfaced with a computer using Arduino UNO microcontroller. The sensor aids the arm in three different directions: at first it senses whether an object is grasped or not. In the second step, it determines the coefficient of friction between the objects. Finally it grasps the object and stops. One of the primary issues of prosthetic hand is to have the capacity to satisfy every detail of torque, speed, and latency. In this research, we have developed a model of robotic hand with some modifications. The adaptability of grasping is compared with the degree of freedom (DOF) along with the quantity of fingers. We are controlling our hands via sensors based signal controlling system. The idea is to design a robotic hand, which has low cost, is easy to use, and is light in weight, which helps the amputees to use it with ease in their daily lives. The efficacy of the proposed control is verified and validated using simulations.

The purpose of this study is to compare the sociability and its impact on learner’s personality traits, in classroom and E-Learning settings to provide an insight for HRM decisions. We proposed that student’s sociability level differ between classroom and e-learning environments. We also identify that sociability is a good predictor for extroversion and openness to experience. For this cross sectional explanatory research about 534 respondents are identified with purposive sampling method. Results point out that there is significant difference in learner’s sociability, extroversion and openness to experience, in classroom and E-Learning environments. The study also established that sociability has statistically significant and positive relationship with openness to experience and extroversion. As there is not even a single study so far that have compared educational environment by using aforementioned variables in reference with development of personality, so the study is unique and a valuable contribution both in educational psychology and for decision making in HRM as well. The study will assist managers to find suitable personal for job. It will also help for training and development plan formation

Liquid exfoliated molybdenum disulfide (MoS2) nanosheets and polyaniline (PANI) nanoparticles are dispersed in polystyrene (PS) matrix to fabricate hybrid polymer composites with high dielectric and electromagnetic interference (EMI) shielding behavior. A phase-separated morphology is formed when PANI and MoS2 are incorporated into polystyrene (PS) matrix. An increasing concentration of MoS2 nanoparticles inside PS/PANI (5 wt %) polymer blend forms an interconnected network, resulting in high electrical conductivity and dielectric behavior, making them a suitable candidate for EMI shielding application. An increment in dielectric constant and loss, up to four and five orders of magnitude, respectively, is recorded at a maximum concentration of 1 wt % of MoS2 in PS/PANI-5 polymer blend at 100 Hz. The enhanced dielectric characteristics for PS/PANI/MoS2 composites are then theoretically evaluated for the estimation of EMI shielding effectiveness in the frequency range of 100 Hz to 5 MHz. The maximum dielectric constant and loss achieved for PS/PANI-5 wt %/MoS2-1 wt % are responsible for estimated shielding effectiveness of around 92 dB at 100 Hz. The increase in dielectric behavior and shielding effectiveness is probably due to the increased number of charged dipoles accumulated at the insulator−conductor interface.

ZnO/GO (Graphene Oxide) and SAN (Styrene Acrylonitrile)/PANI (Polyaniline)/FLG (Few Layers Graphene) nanocomposite coatings were produced by solution casting and sol-gel methods, respectively, to enhance corrosion resistance of ferrous based materials. Corrosive seawater and ‘produced crude oil water’ environments were selected as electrolytes for this study. Impedance and coating capacitance values obtained from Electrochemical Impedance Spectroscopy (EIS) Alternating Current (AC technique) showed enhanced corrosion resistance of nanocomposites coatings in the corrosive environments. Tafel scan Direct Current (DC technique) was used to find the corrosion rate of nanocomposite coating. SAN/PANI/FLG coating reduced the corrosion of bare metal up to 90% in seawater whereas ZnO/GO suppressed the corrosion up to 75% having the impedance value of 100 Ω. In produced water of crude oil, SAN/PANI/FLG reduced the corrosion up to 95% while ZnO/GO suppressed the corrosion up to 10%. Hybrid composites of SAN/PANI/FLG coatings have demonstrated better performances compared to ZnO/GO in the corrosive environments under investigation. This study provides fabrication of state-of-the-art novel anti corrosive nanocomposite coatings for a wide range of industrial applications. Reduced corrosion will result in increased service lifetime, durability and reliability of components and system and will in turn lead to significant cost savings.

A Brain–Computer Interface (BCI) provides a novel non-muscular communication method via brain signals. A BCI-speller can be considered as one of the first published BCI applications and has opened the gate for many advances in the field. Although many BCI-spellers have been developed during the last few decades, to our knowledge, no reviews have described the different spellers proposed and studied in this vital field. The presented speller systems are categorized according to major BCI paradigms: P300, steady-state visual evoked potential (SSVEP), and motor imagery (MI). Different BCI paradigms require specific electroencephalogram (EEG) signal features and lead to the development of appropriate Graphical User Interfaces (GUIs). The purpose of this review is to consolidate the most successful BCI-spellers published since 2010, while mentioning some other older systems which were built explicitly for spelling purposes. We aim to assist researchers and concerned individuals in the field by illustrating the highlights of different spellers and presenting them in one review. It is almost impossible to carry out an objective comparison between different spellers, as each has its variables, parameters, and conditions. However, the gathered information and the provided taxonomy about different BCI-spellers can be helpful, as it could identify suitable systems for first-hand users, as well as opportunities of development and learning from previous studies for BCI researchers.

The role of English in Afghanistan has always been contentious, but in 2001 English acquired symbolic capital that provided people with a motive to invest in learning the language. To better understand this investment, this study employed Darvin and Norton's Model of Investment along with the notion of Linguistic Entrepreneurship to investigate how dynamic shifts in the global era can influence people's willingness to invest in a new language, and how this investment is tied to issues of ideology, capital, and identity. Narrative data were collected via frames and interviews to present the experiences of people who had lived through a relatively prosperous time in Afghanistan's recent history, yet who also faced uncertainty due to the sudden shift in power that threatened the conditions which had allowed them to align themselves with more global ambitions. The study reveals how government and western support was influential in Afghans investing in English, which allowed them to accrue economic, cultural, and social capital, transforming them into linguistic entrepreneurs. However, recent events mean this support has been marginalized, diminishing the ability of Afghans to invest in English and leaving the participants in this study in a precarious position as new ideologies which promote opposition to western influence take hold of the country.

This study aimed to find out the distribution, destructions, developments, transformations, and processes of changes of mosques after WWII in Herat Old City, which is a medieval city still preserved and standing. One hundred and eight mosques were constructed, 2 of them were demolished, and 106 still exist. Twenty-eight are modern mosques, and 80 are traditional. Twenty-two out of 80 are preserved, 56 have been transformed, and 2 were damaged, or demolished. Modern mosques are mainly located in the second and fourth quarters, while traditional mosques are distributed in all four quarters. The transformation started in the 1950s after WWII, continued in the 1970s, 1990s, and 2000s, and has occurred in all four quarters, slightly higher in the second and fourth quarters. Through a field survey, data were collected, findings were combined, unified, and plotted on the map, and the mosques were categorized based on building material. [ABSTRACT FROM AUTHOR]

Purpose: To share our recent experience of the pattern and demography of endemic bladder calculi in children and the outcomes of current management strategies for the removal of bladder calculi in a peri-urban setting. Material and Methods: This retrospective longitudinal study was carried out at a dedicated urology centre. All patients with endemic bladder stones from January 2020 to December 2021 managed at our centre were included in this study. After discharge, each patient was followed up for 1 year. Data analysis was carried out with IBM SPSS v23. Mean and standard deviation were calculated for normally distributed continuous variables; for non-normally distributed continuous variables, median and IQR were calculated; frequency and percentage were calculated for categorical variables. Results: This study included 254 patients, with a male-to-female ratio of 10.5:1. The mean age of the patients was 4.80 ± 2.86 years. Ninety-one percent of the patients belonged to rural areas. Open cystolithotomy (OC) was performed in 11 (4.3%) patients, transurethral cystolithotripsy (TUCL) in 165 (65.0%), and percutaneous cysto- lithotomy (PCCL) in 78 (30.7%). The mean operative time was 48.8 ± 4.34 minutes for TUCL, 36.18 ± 7.4 minutes for open cystolithotomy, and 38.6 ± 5.2 minutes for PCCL. The most common stone composition was ammonium urate + calcium phosphate (33.1%). The complication rate was 4.8% in TUCL, 12.8% in PCCL, and 27.3% in open cystolithotomy. Stone clearance was 98.1% for TUCL and 100% for both PCCL and OC. Conclusion: Paediatric bladder calculus is still endemic in rural areas of Sindh with poor socioeconomic back- grounds. Timely diagnosis and early intervention with preventive measures can lead to better outcomes and fewer complications. Minimally invasive methods of cystolithotomy have a shorter hospital stay, are more cost-effective, and have fewer complications as compared to open cystolithotomy. [ABSTRACT FROM AUTHOR]