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Mesoporous materials are flourishing across every major research discipline, including carbon capture and conversion, energy storage, biomedical, photocatalysis, optics, and magnetics, and their promising potential has led to a flurry of publications. Among these applications, CO2 conversion using porous heterogeneous catalysts such as zeolites, clays, and mesoporous materials gained much attention in recent years as it has the potential to offer a solution for global warming. Although various porous catalysts have been used for CO2 conversion, mesoporous materials are particularly interesting owing to their large specific surface area, pore volume and pore diameter. These properties can be effectively utilized for creating unique catalytically active sites by loading metal or metal oxide species with high dispersion which are highly critical for efficient CO2 conversion. There have also been a significant number of reports on the direct use of mesoporous metal oxides, sulfides and/or phosphides, which exhibit appealing results for CO2 conversion as these inherently contain metal sites, and mesoporosity addition to them is an added advantage. Their continuous evolution warrants more sophisticated research to unveil their hidden properties by engaging in highly advanced characterization. The major emphasis of this review is to discuss various types of mesoporous materials mentioned above and their functionalized derivatives for CO2 conversion to mainly C1 products. The diverse range of mesoporous materials covered in this review will provide the readers with the opportunity to delve into their specific properties that control the efficiency of CO2 conversion.

ABSTRACTThe notion of the “complex dual hesitant fuzzy set (CDHFS)” is the combination of the “dual hesitant fuzzy set (DHFS)” and the “complex fuzzy set (CFS).” It is characterized by two degrees, namely the membership and nonmembership, in the form of a finite subset on a unit disc in the complex plane. CDHFS is useful for dealing with real-world problems involving uncertain or hard-to-predict information. Also, to approximate smoothly, the Einstein operators are well-known aggregation operators, while prioritized operators are effective tools for prioritization among criteria. Therefore, the goal of this study is to develop some prioritized aggregation operators under the CDHFS environment; namely the complex dual hesitant fuzzy prioritized averaging (CDHFPA) operator, the complex dual hesitant fuzzy prioritized geometric (CDHFPG) operator, the complex dual hesitant fuzzy Einstein prioritized averaging (CDHFEPA) operator, and complex dual hesitant fuzzy Einstein prioritized geometric (CDHFEPG) operator. Some properties of the proposed operators are investigated in detail. In addition, a multi-criteria decision-making (MCDM) method based on the proposed operators with the complex dual hesitant fuzzy setting is developed. Moreover, a numerical example is given for the application and effectiveness of the developed MCDM approach. A comparison study is also done with existing methods to show that the proposed MCDM method is better and more reliable. The study finds that if the expert’s preference is used to choose the right aggregation operators, the decision maker will have access to a wide range of compromise solutions.

IntroductionChile pepper (Capsicum annuum L.) mechanization is a promising alternative to traditional hand harvesting due to the costs associated with manual harvest, as well as the increasing unavailability of skilled manual chile harvesters. This study aimed to identify single nucleotide polymorphisms (SNPs) associated with mechanical harvestability (MH) and yield-related traits using multi-locus genome-wide association mapping approaches in a C. annuum association mapping population.MethodsA C. annuum association mapping panel for mechanical harvest was manually direct seeded in an augmented block design in two locations. After filtration, imputation, and quality control 27,291 single nucleotide polymorphism (SNP) markers were used for association analyses. Six multi-locus GWAS models were implemented to identify marker trait association.Results and DiscussionMulti-locus GWAS models identified 12 major SNP markers (R2 > 10) across nine chromosomes associated with plant architecture, easy destemming traits, and yield parameters. The presence of a major QTL in chromosome P2, dstem2.1, identified recently to be associated with destemming force, was confirmed. Mature green and mature red yield shared three SNP markers mapped on chromosome P3, P5, and P6 explaining 11.94% to 25.15% of the phenotypic variation. Candidate gene analysis for the significant loci identified 19 candidate genes regulating different phytohormone biosynthesis/signaling, metabolic processes, transcription, methylation, DNA repair/replication, and RNA splicing, with potential roles in controlling plant architecture and morphology. The diverse positions of the associated SNPs suggest the complex nature of these quantitative traits, involvement of multiple genetic factors, and novel significant marker-trait associations. Results from this study will be relevant for genetic improvement of mechanical harvestability traits in New Mexican chile pepper using molecular markerassisted breeding and selection.

Industrial and human activities contribute significantly to the environmental contamination of heavy metal ions (HMIs), which have detrimental effects on aquatic life, plants, and animals, causing major toxicological problems. The commercially available 4,4′-diamino-2,2′-stilbenedisulfonic acid (DSD) has been playing a vital role in the detection of heavy metal ions and has significantly inhibited a variety of cancer cells in numerous field of modern science. The current investigation aimed to ensure the detection of heavy metals ions from the environment and fluorescence imaging of DSD in the treatment of cancer cells. Fluorescence and UV–Visible spectroscopic analysis was performed to sense the selective behavior of the probe DSD with several heavy metal ions, including Fe2+, K1+, Co2+, Ni2+, Zn2+, Cd2+, Pb2+, Mn2+, Sn2+, and Cr3+. Furthermore, DSD was subjected to examine enzyme inhibition such as anti-Alzheimer, anti-inflammatory, antioxidant, anticancer, and antimicrobial activities in search of multifaceted drugs. Test compounds have demonstrated dose-dependent responses in the in-vitro enzyme inhibition assays for acetylcholinesterase (AChE), butyrylcholinesterase (BChE), cyclooxygenase (COX), and lipoxygenase (LOX), as well as antioxidant [DPPH = 2,2-diphenyl-1-picrylhydrazyl and ABTS = 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid]. The DSD were shown to be more effective than the conventional medication galantamine in inhibiting acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), with an IC50 value of 12.18 and 20.87 μM, which is equivalent to the standard drug. The results obtained has revealed that DSD has the potential to become an effective sensor for the detection of Sn2+ ions over competing metal ions due to the inhibition of photo-induced electron transfer pathway (PET). The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide tetrazolium) test, demonstrated that DSD had strong anticancer effects against the brain cancer cell line NIH/3T3, HeLa and MCF-7 with an IC50 value of 32.59, 15.31 and 96.46 μM respectively. The antimicrobial testing has shown that DSD outperforms the standard drug cefixime against Candida albicans and Pseudomonas aeruginosa, respectively. This study makes a substantial contribution to the ongoing search for efficient treatments for breast cancer.

The human brain is an incredible and wonderful organ that governs all body actions. Due to its great importance, any defect in the shape of its regions should be reported quickly to reduce the death rate. The abnormal region segmentation helps to plan and monitor the treatment. The most critical procedure is isolating normal and abnormal tissues from each other. So far, remarkable imaging modalities are being used to diagnose abnormalities at their early stages, and magnetic resonance imaging (MRI) is renowned and noninvasive among those modalities. This paper investigates the current landscape of brain tumor segmentation (BTS) by exploring emerging deep learning (DL) methods for brain MRI analysis. The findings offer a comprehensive comparison of recent DL approaches, emphasizing their effectiveness in handling diverse tumor types while addressing limitations associated with data scarcity and robust validation. DL has shown a vital improvement for BTS, so our primary focus is to include significant DL robust models to analyze the brain MRI. However, DL outperforms traditional methods; still, there are several limitations, especially related to the diverse tumor types, lack of datasets, and weak validations. The future perspectives of DL-based BTS present significant potential for revolutionizing the diagnosis and treatment of brain tumors.

Smartwatches with cutting-edge sensors are becoming commonplace in our daily lives. Despite their widespread use, it can be challenging to interpret accelerometer and gyroscope data efficiently for Human Activity Recognition (HAR). This study explores active learning integrated with machine learning, intending to maximize the use of smartwatch technology across a range of applications. The previous research on the HAR lacks promising performance, which could make it difficult to make highly accurate recognition. This paper proposes a novel approach to predict human activity from the Heterogeneity Human Activity Recognition (HHAR) dataset that integrates active learning with machine learning models: Random Forest (RF), Extreme Gradient Boosting (XGBoost), K-nearest Neighbors (KNN), Decision Tree (DT), Gradient Boosting (GB) and Light Gradient Boosting Machine (LGBM) classifier to predict heterogeneous activities accurately. We evaluated our approach to these models on the HHAR dataset that was generated using an accelerometer and gyroscope of smartwatches. The experiments are evaluated on 3 iterations where the results demonstrated that the proposed approach predicts human activities with the highest F1-Score of 99.99%. The results indicate that this approach is the most accurate and effective compared to the conventional approaches and baseline.

Numerous fuzzy structures have been created and studied up to this point in order to investigate objects under ambiguity. Among them, the structure of complex spherical fuzzy set is significant because it can define the four prospective aspects of an expert's viewpoint using the membership degree, non membership degree, abstinence, and rejection in a two-dimensional space. It is never easy to aggregate information, particularly when the input arguments are connected. In order to handle such situations, the goal of this study is to create the idea of the Hamy mean operator because it integrates data in ambiguous environments and takes into account the relationships between the input arguments. In this manuscript, we investigated the notion of Hamy mean and dual Hamy mean operators in the setup of complex spherical fuzzy sets and described their applications for engineering activities. We created the complex spherical fuzzy Hamy mean (CSFHM) and complex spherical fuzzy Dual Hamy mean (CSFDHM) operators and looked into the validity of each. To assess the effectiveness of the enterprise resource planning (ERP) systems using complex spherical fuzzy data, we created the multi attribute decision making technique based on the CSFHM and CSFDHM operators. The impacts of the related parameters are examined using a numerical example to assess the effectiveness of ERP systems. In comparison to conventional aggregation operators, the recommended aggregated results utilizing CSFHM and CSFDHM operators are observed to be reliable because they consider the interdependence of the input data. The suggested operators are compared in this study as well.

Rock-filled concrete (RFC) is an advanced construction material that integrates high-performance self-compacting concrete (HSCC) with large rocks exceeding 300 mm, providing advantages such as reduced hydration heat and increased construction processes. The elastic modulus of RFC is a critical parameter that directly influences its structural performance, making it vital for modern construction applications that require strength and stiffness. However, there is a scientific gap in understanding the effects of rock size, shape, arrangement, and volumetric ratio on this parameter. This study investigates these factors using mesoscale finite element models (FEMs) with spherical and polyhedral rocks. The results reveal that polyhedral rocks increase the elastic modulus compared to spherical rocks, enhancing RFC’s load-bearing capacity. Additionally, a 5% increase in the elastic modulus was observed when the rockfill ratio was increased from 50% to 60%, demonstrating a direct correlation between rock volume and mechanical performance. Furthermore, the elastic modulus rises significantly in the early stages of placement, followed by a gradual increase over time. Optimal rock sizes and a balanced mix of rock shapes allow for improved concrete flow and mechanical properties, making RFC a highly efficient material for construction. These findings offer valuable insights for designers and engineers looking to optimize RFC for structural applications.

Ammonia (NH3), a carbon-free hydrogen carrier, is an important commodity for the food supply chain owing to its high energy capacity and ease of storage and transport. The Haber–Bosch process is currently the favored industrial method for large-scale ammonia production but requires energy-intensive and sophisticated infrastructure which hampers its utilization in a sustainable and decentralized system of manufacture. The electrochemical nitrogen reduction reaction (eNRR) at ambient conditions holds great potential for sustainable production of ammonia using electricity generated from renewable energy sources such as solar and wind. However, this approach is limited by a low rate of ammonia production with high overpotential and the competing hydrogen evolution reaction (HER). For a better understanding and utilization of eNRR as a sustainable process, insight into rational catalyst design and mechanistic evaluations by a theoretically-directed experimental approach is imperative. Herein, recent insights into rational catalyst design and mechanisms, based on intrinsic and extrinsic catalytic activity are articulated. Following the elucidation of basic principles and mechanisms, a framework supplied by theoretical studies that lead to the optimal selection and development of eNRR catalysts is presented. Following a discussion of recently developed electrocatalysts for eNRR, we outline various recently-used theoretical and experimental methodologies to improve the intrinsic and extrinsic catalytic activity of advanced electrocatalysts. This review is anticipated to contribute to the development of active, selective, and efficient catalysts for nitrogen reduction.

Nanoparticles of molecularly imprinted polymers (nanoMIPs) combine the excellent recognition ability of imprinted polymers with specific properties related to the nanosize, such as a high surface-to-volume ratio, resulting in highly performing recognition elements with surface-exposed binding sites that promote the interaction with the target and, in turn, binding kinetics. Different synthetic strategies are currently available to produce nanoMIPs, with the possibility to select specific conditions in relation to the nature of monomers/templates and, importantly, to tune the nanoparticle size. The excellent sensing properties, combined with the size, tunability, and flexibility of synthetic protocols applicable to different targets, have enabled the widespread use of nanoMIPs in several applications, including sensors, imaging, and drug delivery. The present review summarizes nanoMIPs applications in sensors, specifically focusing on electrochemical detection, for which nanoMIPs have been mostly applied. After a general survey of the most widely adopted nanoMIP synthetic approaches, the integration of imprinted nanoparticles with electrochemical transducers will be discussed, representing a key step for enabling a reliable and stable sensor response. The mechanisms for electrochemical signal generation will also be compared, followed by an illustration of nanoMIP-based electrochemical sensor employment in several application fields. The high potentialities of nanoMIP-based electrochemical sensors are presented, and possible reasons that still limit their commercialization and issues to be resolved for coupling electrochemical sensing and nanoMIPs in an increasingly widespread daily-use technology are discussed.

Excessive and imbalance of free radicals within the body lead to inflammation. The objective of the current research work was to explore the anti-inflammatory and antioxidant potential of the isolated compounds from Habenaria digitata. In this study, the isolated phenolic compounds were investigated for in vitro and in vivo anti-inflammatory potential along with the antioxidant enzyme. The anti-inflammatory and antioxidant potential of the phenolic compounds was assayed via various enzymes like COX-1/2, 5-LOX and ABTS, DPPH, and H2O2 free radical enzyme inhibitory assay. These compounds were also explored for their in vivo antioxidant activity like examining SOD, CAT, GSH-Px, and MDA levels in the brain, heart, and liver. The anti-inflammatory potential was evaluated using the carrageenan-induced pleurisy model in mice. On the basis of initial screening of isolated compounds, the most potent compound was further evaluated for the anti-inflammatory mechanism. Furthermore, the molecular docking study was also performed for the potent compound. The phenolic compounds were isolated and identified by GC-MS/NMR analysis by comparing its spectra to the library spectra. The isolated phenolic compounds from H. digitata were 5-methylpyrimidine-24,4-diol (1), 3,5-dihydroxy-6-methyl-2,3-dihydropyran-4-one (2), 2-isopropyl-5-methylphenol (3), 3-methoxy-4-vinylphenol (4), and 2,6-dimethoxy-4-vinylphenol (5). In in vitro antioxidant assay, the most potent compound was compound 1 having IC50 values of 0.98, 0.90, and 5 μg/mL against ABTS, DPPH, and H2O2, respectively. Similarly, against COX1/2 and 5-LOX ,compound 1 was again the potent compound with IC50 values of 42.76, 10.70, and 7.40 μg/mL. Based on the in vitro results, compound 1 was further evaluated for in vivo antioxidant and anti-inflammatory potential. Findings of the study suggest that H. digitata contains active compounds with potential anti-inflammatory and antioxidant effects. These compounds could be screened as drug candidates for pharmaceutical research, targeting conditions associated with oxidative stress and inflammatory conditions in medicinal chemistry and support their ethnomedicinal use for inflammation and oxidative stress.

The strong ethnopharmacological utilization of Isodon rugosus Wall. Ex. Benth is evident in the treatment of several types of pain and inflammation, including toothache, earache, abdominal pain, gastric pain, and generalized body pain and inflammation. Based on this background, the antinociceptive effects of the crude extract, various fractions, and essential oil have been reported previously. In this research work, we isolate and characterize pure bioactive compounds from I. rugosus and evaluate possible mechanisms using various in vivo and in vitro models. The pure compounds were analyzed for analgesic and anti-inflammatory activities through various assays. The column chromatography of the chloroform fraction of I. rugosus led to the identification of two pure compounds, i.e., 1 and 2. Compound 1 demonstrated notable inhibition (62% writhing inhibition, 72.77% COX-2 inhibition, and 76.97% 5-LOX inhibition) and anti-inflammatory potential (>50% paw edema inhibition at various intervals). The possible mechanism involved in antinociception was considered primarily, a concept that has already been elucidated through the application of naloxone (an antagonist of opioid receptors). The involvement of adrenergic receptors was investigated using a hot plate model (an adrenergic receptor antagonist). The strong ethnomedicinal analgesic background of I. rugosus, supported by previous reports and current observations, leads to the conclusion that I. rugosus is a potential source of antinociceptive and anti-inflammatory bioactive compounds. It may be concluded from the results that the isolated analgesic compounds of I. rugosus may be a possible alternative remedy for pain and inflammation management with admirable efficacy and safety profiles.

The surging electricity demand in Pakistan has led to frequent blackouts, prompting government initiatives to expand power plant capacities and improve the national grid. The government prioritizes integrating large-scale renewable energy sources, such as wind and solar power, to reduce dependence on conventional power plants. However, the intermittency of renewables leads to forecasting errors, requiring extra power reserves from conventional units, thereby escalating operational costs and CO2 emissions. The country currently utilizes a manual mechanism for power balancing operations, overlooking critical grid constraints of the transmission line loadings. In such conditions, injecting large-scale power from renewables can lead to significant fluctuations in line power flows, risking transmission line loadings and compromising the system’s secure operation. Hence, this paper has developed an automatic generation control (AGC) model for the highly wind-integrated power system to alleviate line congestions in the network and enhance the economic operation of the system. The study utilizes the Pakistan power system as a case study to simulate the proposed model. The developed real-time power dispatch strategy for the AGC system considers the constraints of the transmission line to avoid congestion. It integrates wind energy as operating reserves to enhance the economic operation of the system. When managing line congestion, it identifies overloaded bus lines and adjusts power regulation accordingly while compensating for shortfalls by augmenting transmitted power from regional grid stations. However, it maintains a constant dispatch ratio without line overloads, aligned with generation capacities. Additionally, the strategy integrates reserve power from the wind power plant and traditional generating units to further improve economic operations. Simulations have been conducted using PowerFactory software, employing the eight-bus and five-machine models to replicate the characteristics of the Pakistan power system. The results demonstrate the effectiveness of the proposed AGC design in mitigating transmission line congestion of power systems that are heavily integrated with wind energy sources while simultaneously ensuring the economic operation of generating units.

This study inspects the impact of environmental deterioration and income on longevity and fertility in Asian countries, specifically the nations that are highly vulnerable to extreme weather. The study examines the data, covering two decades from 2000 to 2019. The empirical conclusions of the panel ARDL-PMG and the CS-ARDL econometric models indicate that environmental degradation leads to a decline in birth rate and life expectancy, while a rising income has a significant influence over longevity. However, increasing per capita income alone cannot solve the problem of population crisis in climatically susceptible countries. Therefore, the sample countries must prioritize climate action and formulate climate-resilient policies to add more years to the lives of their citizens. Similarly, for increasing childbirth the sample nations need to make peace with nature. The outcomes of this study are strong enough, as both the models support each other's findings, producing similar significant outcomes.

Green synthesis of nanoparticles (NPs) has attracted the researcher's attention due to its rapid, cost-effective, sustainable and eco-friendly nature. Current studies were carried out to perform and investigate the green synthesis of NiO NPs with aqueous (NiO(aqueous)) and ethanolic extracts (NiO(ethanolic)) of Acacia nilotica leaves, respectively. The NPs were characterized by spectroscopic, microscopic and thermometric techniques including FTIR, Raman, XRD, SEM, TGA and DSC. The electrochemical properties, antibacterial potential and haemolytic activities of the synthesized NPs were also examined. XRD patterns revealed the face-centred cubic structures of NiO NPs and a high degree of crystallinity. The average crystallite size of NiO(aqueous) NPs was significantly smaller (16 nm) than that of NiO(ethanolic) NPs (28 nm). SEM images show that NiO NPs are spherical. The synthesized NiO NPs demonstrate good electrochemical stability at an operating potential of −0.5-0.5 V. The inhibition effect of NiO NPs(ethanol) against B. subtilis, was comparable to the ciprofloxacin.

The growth of high-efficiency phase change material (PCM) nanocomposites with good heat conduction and substantial thermal capacity was of vital significance for practical matters in the sustainable utilization of energy. A novel leakage-proof n-heptadecane-graphene nanocomposite was prepared by a direct impregnation procedure from n-heptadacne as a PCM and nanographene as a skeleton. The creation of shape-stabilized nanocomposite was checked with X-ray diffraction (XRD), Raman, and Fourier transform infrared (FTIR) spectroscopy. The scanning electron microscopy (SEM) analysis illustrated that the n-heptadecane and graphene had favourable compatibility and there was no phase separation and graphene accumulation. Thermal analysis showed that the shape-stabilized nanocomposite not only had a good phase transition enthalpy (101.7 J/g) and n-heptadecane content (45.6 %) but also possessed appropriate thermal stability. The heat conduction of the obtained mesoporous nanocomposite was up to 1.527 W/mK, with a growth of 808 % compared to pure n-heptadecane. Furthermore, the optimized nanocomposite held auspicious thermal reliability, being exposed to 400 thermal cycles. Moreover, the thermoregulation tests demonstrated that the gypsum boards containing optimized nanocomposite showed a slow heat release rate and improved the building temperature profile over only the gypsum board. By virtue of the combination of n-heptadecane and thermal conductive nanographene, the obtained engineered nanocomposite might be regarded as a smart material for energy-conserving and temperature regulation in buildings.

Abstract Millimeter wave (mm-Wave) wireless communication systems require high gain antennas to overcome path loss effects and thereby enhance system coverage. This paper presents the design and analysis of an antenna array for high gain performance of future mm-wave 5G communication systems. The proposed antenna is based on planar microstrip technology and fabricated on 0.254 mm thick dielectric substrate (Rogers-5880) having a relative permittivity of 2.2 and loss tangent of 0.0009. The single radiating element used to construct the antenna array is a microstrip patch that has a configuration resembling a two-pronged fork. The single radiator has a realized gain of 7.6 dBi. To achieve the gain required by 5G base stations, a 64-element array antenna design is proposed which has a bore side gain of 21.2 dBi at 37.2 GHz. The 8 × 8, 8 × 16, and 8 × 32 antenna array designs described here were simulated and optimized using CST Microwave Studio, which is a 3D full-wave electromagnetic solver. The overall characteristics of the array in terms of reflection-coefficient and radiation patterns makes the proposed design suitable for mm-Wave 5G and other communication systems.

Skin, largest organ of human, is directly exposed to environment and hence is prone to high rates of injuries and microbial infections. Over the passage of time these microbes have developed resistance to antibiotics making them ineffective especially in lower doses and hence, higher dosages or new drugs are required. The current study deals with designing of nano-emulsion (NE) formulations composed of garlic and ginger oils (0.1 %) with neomycin sulphate used in different ratios (0.001, 0.01 and 0.1 %) and combinations. The resulting NEs were characterized for droplet size (145–304 nm), zetapotential (-3.0–0.9 mV), refractive index (1.331–1.344), viscosity (1.10–1.23cP), transmittance (96–99 %), FT-IR and HPLC and found stable over a period of three months. All NEs were also found effective against both gram positive and negative bacterial strains i.e., B. spizizenii, S. aureus, E. coli and S. enterica as compared to pure neomycin sulphate (NS) used as control with highest activity recorded for NE-2 and NE-4 against all strains showing zone of inhibition in range of 22–30 mm and 21–19 mm, respectively. NEs were also tested using rabbit skin excision wound model which potentiates that all the NEs resulted in early recovery with 86–100 % wound healing achieved in 9 days as compared to NS ointment (71 %). The studies confirmed that essential oils when used in combination with traditional drug can lead to much higher efficacies as compared to pure drugs.

Abstract We evaluated root system architecture (RSA) of a set of 58 historical spring wheat cultivars from Pakistan representing 105 years of selection breeding. The evaluations were carried out under control and water-limited conditions using a high-throughput phenotyping system coupled with RhizoVision Explorer software. The cultivars were classified into three groups based on release year as cultivars released pre-1965, released between 1965 and 2000, and cultivars released post-2000. Under water-limited conditions a decline in 20 out of 25 RSA component traits was observed in pre-1965 cultivars group. Whereas cultivars released after the 1965, so-called green revolution period, showed a decline in 17 traits with significant increments in root length, depth, and steep angle frequency which are important root traits for resource-uptake under water-limited conditions. Similarly, cultivars released after 2000 indicated an increase in the number of roots, depth, diameter, surface area, and steep angle frequency. The coefficient of correlation analysis showed a positive correlation between root depth and yield-related traits under water-limited conditions. We also investigated the effects of green-revolution genes (Rht1) and some phenology-related genes such as DRO1, TaMOR, TaLTPs, TaSus-2B on RSA and identified significant associations of these genes with important root traits. There was strong selection pressure on DRO1 gene in cultivated wheat indicating the allele fixed in modern wheat cultivars is different from landraces. The expression of DRO1, and TaMOR were retrieved from an RNAseq experiment, and results were validated using qRT-PCR. The highest expression of DRO1 and TaMOR was found in Chakwal-50, a rainfed cultivar released in 2008, and MaxiPak-65 released in 1965. We conclude that there is a positive historic change in RSA after 1965 that might be attributed to genetic factors associated with favored RSA traits. Furthermore, we suggest root depth and steep angle as promising traits to withstand water-limited environments and may have implications in selection for breeding.

Pakistan is facing an annual electricity shortfall of 5000 MW since 2005 due to lack of effective planning on harnessing indigenous energy resources and dependence on imported fuels. In this regard, a qualitative analysis is presented to address the ongoing energy crises and to suggest the development of domestic energy assets and recommends a policy framework to meet electricity goals. Status of energy in Pakistan is presented in the context of energy supply and demand and discusses the major issues such as electricity theft and circular debt. The reasons are identified for power system degradation, energy crises and their potential impacts on the economy of Pakistan is discussed. Further, domestic energy assets are evaluated for their capacity of power production, including solar, wind, geothermal, biomass, tidal, hydro, coal, and natural gas. The main variables of Pakistan’s energy status are power system restructuring, power system planning and policies, electricity theft, energy crisis and circular debt. The key challenges for policy development are also addressed using possible approaches and used these approaches as input in making policy framework by considering the domestic energy resource through incorporating the policy actors, policy criteria, and policy tools. It is found that Pakistan has a renewable potential of 3425.796 GW and a non-renewable potential of 104.883 GW to meet the future energy demand. It is suggested to exploit domestic energy assets for power production, optimize energy planning and policy to find a secure and sustainable energy option for Pakistan.

The increase in root hair length and density is considered an effective way to deal with external phosphorous (P) limitation. The identification of useful loci for root hair traits is crucial for wheat breeding. Here, We employed a simple, cost-effective, and medium-throughput screening method using cigar rolls to assess P-responsive root hair length (RHL) and density (RHD) in bread wheat at the seedling stage. A set of 113 historical bread wheat cultivars was screened for root hair length and density (RHL/D) under low (0.005 mM KH2PO4) and high P-levels (0.25 mM KH2PO4). Significant variations (p

Chromium oxide (Cr2O3) nanoparticles (NPs) find applications in modern science and technology due to their chemical stabilities, high-density corners and magnetic/electrical/catalytic properties. Current studies were performed to produce the (Cr2O3)aq and (Cr2O3)et NPs by treating chromium acetate with the aqueous and ethanolic extracts, respectively of Cassia fistula leaves; the same reaction was also performed in the presence of NaOH to yield the (Cr2O3)aqNa and (Cr2O3)etNa NPs, respectively. The synthesized NPs were characterized by XRD, FTIR, Raman spectroscopy, UV–Vis spectroscopy, SEM, TGA and DSC analysis and examined for their electrochemical properties. Their antibacterial potential was tested by biofilm inhibition and agar well diffusion methods. XRD studies revealed that Cr2O3 NPs possessed hexagonal crystal structures with the crystallite sizes of 14.85 to 23.90 nm; the lowest size (14.85 nm) was possessed by (Cr2O3)et. FTIR and Raman spectroscopies verified the +3-oxidation state of chromium and corresponding Cr-O and Cr=O vibrations. Raman spectroscopy determined A1g vibration modes (540.50–557.07 cm−1) with rhombohedral Cr2O3 structure, high degree of crystallinity and existence of Cr3+ ions in octahedral coordination whereas Eg vibration modes were displayed at 306.04–350.87 cm−1 and 602.47–613.81 cm−1. UV–Visible spectroscopy has shown band gaps in the range of 4.06–4.40 eV. The SEM images demonstrated the spherical morphology with a high degree of agglomeration between fine particles. The synthesized NPs exhibited good thermal stabilities up to 600 °C. The CV curves displayed the oxidation–reduction peaks and reversible behavior whereas GCD curve indicated the possible energy storage applications of NPs. (Cr2O3)aqNa NPs showed the highest specific capacitance (234.35 mAhg−1) at 1 mA current density. The biofilm inhibitions of the investigated NPs were comparable to those of the standard antibacterial drug (ciprofloxacin); the activity of (Cr2O3)etNa was found even better than that of ciprofloxacin. The NPs were more active against Escherichia coli (Gram-negative) as compared to those against Staphylococcus aureus (Gram-positive).

Secure and reliable wireless communication systems are essential for the successful integration of smart grid-enabled wireless communications and Industry 5.0 applications. This work proposes a hybrid precoding design for secure smart-grid multiple-input multiple-output (MIMO) wireless communications in Industry 5.0 to maximize the average secrecy capacity of the system while minimizing user outages crucial for maintaining the security and privacy of sensitive data in critical infrastructure. To achieve this, we develop a mathematical model that considers the impact of various system parameters, such as eavesdropping and interference caused by the active eavesdropper and noise, on the secrecy capacity. To find an efficient solution to the optimization problem, we propose an algorithm that decouples the original optimization problem into a series of subproblems and uses iterative techniques to find the optimal values, thereby improving computational efficiency. The hybrid precoding scheme is an effective technique for optimizing the design parameters of MIMO-based secure wireless communication systems. Our proposed approach provides a practical solution for achieving this optimization. Our numerical results demonstrate that our proposed scheme outperforms traditional benchmark schemes, maximizing the average secrecy capacity while minimizing user outages. Our work highlights the importance of secure wireless communication systems in Industry 5.0 and smart grid applications. The proposed approach provides an efficient method for designing secure wireless communication systems that can effectively address the unique challenges posed by these critical infrastructure systems.

Heavy metal contamination of water has become a global environmental burden, which has stirred up agitation worldwide. Fabrication of adsorbents utilizing either low cost, environment friendly materials or waste products can be helpful in remediating environmental pollution. The current study evolved around the synthesis of nanocomposites derived from such raw precursors like spent tea waste biochar, hydroxyapatite, and clays. In this context, two nanocomposites, namely manganese ferrite doped hydroxyapatite/kaolinite/biochar (TK-NC) and manganese ferrite doped hydroxyapatite/vermiculite/biochar (TV-NC), were synthesized followed by their employment for decontamination of heavy metals from aqueous media. TK-NC and TV-NC exhibited the crystallite sizes in the range of 2.55-5.94 nm as obtained by Debye Scherrer Equation and Williamsons-Hall equation The fabricated nanocomposites were characterized using FT-IR, SEM-EDX, and powder XRD. Batch adsorption studies were performed, and influence of different adsorption parameters (contact time, reaction temperature, solution pH, adsorbent dose, and initial adsorbate concentration) on metal adsorption was examined. Thermodynamic studies revealed that the adsorption of Cr(VI), Ni(II) and Cu(II) on TK-NC and TV-NC was endothermic (+ΔH°) and indicates disorderness (+ΔS°) at the solid-liquid interface owing to the strong affinity of metal ions with adsorbent. The heavy metal uptake selectivity followed the following decreasing order; Cr(VI) > Cu(II) > Ni(II) by both nanocomposites, with adsorption capacities falling in the range of 204.68-343.05 mg g-1. Several adsorption kinetic and isotherm models were applied to experimentally calculated data, which suggest favorable adsorption of Cr(VI), Ni(II) and Cu(II) by TK-NC and TV-NC from the system while obeying general-order kinetics and R-P adsorption model, conferring the transition in adsorption kinetics order and involvement of multiple adsorption process.

Molecular imprinting is an attractive research area for synthesizing unique functional polymers with high selectivity due to template oriented active sites. Molecularly imprinted polymers (MIPs) have a wide range of applications in chemical and biological sensing, drug delivery, and solid-phase extraction owing to mechanical stability, reversibility, reproducibility, and cross-validity. MIPs are compatible with natural antibodies and are being used as antibody mimics/receptors in the biomedical field. Today, viral detection is the most popular research area due to emerging viral diseases with genetic variability and drug resistance. Therefore, there is a need to control viral infections by discriminative recognition of the viral pathogens. This review summarizes the literature on the detection of human viruses by using MIPs.

Objective: To compare negative pressure wound therapy with advanced moist wound therapy in managing early diabetic foot ulcer. Study Design: Quasi-experimental study. Place and Duration of Study: Surgical Department, Combined Military Hospital Rawalpindi, from Jul 2016 to Jun 2018. Methodology: A total of 100 patients of diabetic foot ulcer were randomly allocated into two equal groups for the treatment with negative pressure wound therapy (NPWT) and advanced moist wound therapy (AMWT). Ulcers were reassessed after 4 weeks for presence of granulation tissue covering entire ulcer base and reduction of 3 cm in largest diameter of ulcer. Results: Mean age of the study participants was 57.08 ± 9.99 years. 33 patients had Wagner grade-I ulcer, while remaining had Wagner grade-II ulcer. Mean ulcer size at presentation was 6.46 ± 1.71 cm. Both study groups were comparable in terms of mean age (p=0.968), wound size at presentation (p=1.000), age (p=0.695), gender (p=1.000) and Wagner ulcer grade (p=0.288). Mean ulcer size was found smaller with negative pressure wound therapy (3.46cm, p=0.061) at follow-up visits. Reduction in ulcer size ≥3cm was achieved frequently with negative pressure wound therapy technique (72.0% vs. 38.0%; p>0.01). Mean healing time was 4.11 ± 1.65 weeks which was lower with negative pressure wound therapy (3.66 weeks vs. 4.56 weeks; p>0.05). Treatment efficacy (healing in ≤4 weeks and ≥3cm reduction in ulcer) was significantly higher with negative pressure wound therapy (72.0% vs. 38.0%; p

Increasing global temperature has adverse effects on crop health and productivity at both seedling and reproductivity stages. It is paramount to develop heat tolerant wheat cultivars able to sustain under high and fluctuating temperature conditions. An experiment was conducted to characterize 194 historical wheat cultivars of Pakistan under high temperature at seedling stage to identify loci associated with heat tolerance using genome-wide association studies (GWAS). A quantitative trait locus, TaHST1, on chr4A was also characterized to identify the haplotypes at this locus associated with heat tolerance in wheat from Pakistan. Initially, the diversity panel was planted under control conditions (25°C/20°C day and night temperature) in a glass house. At three leaf stage, plants were subjected to heat stress (HS) by increasing temperature (40°C/35°C day and night), while one treatment was kept at control condition. After 7 days of HS, data were collected for seedling morphology. Heat stress reduced these traits by 25% (root weight) to 40% (shoot weight), and shoot biomass was largely affected by heat stress. A GWAS model, fixed and random model circulating probability unification (FarmCPU), identified 43 quantitative trait nucleotides (QTNs) on all chromosomes, except chr7B, were associated under both HS and control conditions. Thirteen QTNs were identified in control, while 30 QTNs were identified in HS condition. In total, 24 haplotypes were identified at TaHST1 locus, and most of the heat tolerant genotypes were assigned to Hap-20 and Hap-21. Eleven QTNs were identified within 0.3–3.1 Mb proximity of heat shock protein (HSP). Conclusively, this study provided a detailed genetic framework of heat tolerance in wheat at the seedling stage and identify potential genetic regions associated with heat tolerance which can be used for marker assisted selection (MAS) in breeding for heat stress tolerance.

Docosahexaenoic acid (DHA) has attracted attention from researchers because of its pharmacological and nutritional importance. Currently, DHA production costs are high due to fermentation inefficiency; however, improving DHA yield by metabolic engineering in thraustochytrids is one approach to reduce these costs. In this study, a high-yielding (53.97% of total fatty acids) DHA production strain was constructed by disrupting polyunsaturated fatty acid beta-oxidation via knockout of the 2,4-dienyl-CoA reductase (DECR) gene (KO strain) in Aurantiochytrium sp. Slight differences in cell growth was observed in the wild-type and transformants (OE and KO), with cell concentrations in stationary of 2.65×106, 2.36×106 and 2.56×106 cells mL-1 respectively. Impressively, the KO strain yielded 21.62% more neutral lipids and 57.34% greater DHA production; moreover, the opposite was observed when overexpressing DECR (OE strain), with significant decreases of 30.49% and 64.61%, respectively. Furthermore, the KO strain showed a prolonged DHA production period with a sustainable increase from 63 to 90 h (170.03 to 203.27 mg g−1 DCW), while that of the wildtype strain decreased significantly from 150.58 to 140.10 mg g−1 DCW. This new approach provides an advanced proxy for the construction of sustainable DHA production strains for industrial purposes and deepens our understanding of the metabolic pathways of Aurantiochytrium sp.

Thar desert is located in south-east Pakistan carries 175 billion tons of coal and is the biggest coalfield in Asia. In this paper mathematical framework is developed for the accurate estimation of power production from the available Thar coal capacity. Annual TWh possible energy production the period 2020 to 2040 followed by detailed analysis of capacity factor and Maximizing the share percentage of coal in total energy mix at least 40% by 2040 is presented. The findings reveal that Thar coal has the capability of producing 100,000 MW power up to the next 250 years. The energy generation for the years 2020, 2032, and 2040 is calculated 744 TWh per year, 700 TWh per year, and 665 TWh per year respectively and it produces negligible negative impacts on the environment. The long-term energy planning presented in this paper would attract foreign investment and Pakistan's energy needs would be fulfilled for sustainable development of the country.

Alopecia has gradually become a problem that puzzles an increasing number of people. Dermal papilla cells (DPCs) play an important role in hair follicle (HF) growth; thus, exploring the effective chemicals or natural extracts that can remediate the growth of DPCs is vital. Our results showed that Schizochytrium sp.-extracted lipids (SEL) significantly promoted proliferation (up to 1.13 times) and survival ratio (up to 2.45 times) under oxidative stress. The treatment with SEL can protect DPCs against oxidative stress damage, reducing the reactive oxygen species (ROS) level by 90.7%. The relative gene transcription and translation were thoroughly analyzed using RNA-Seq, RT-qPCR, and Western blot to explore the mechanism. Results showed that SEL significantly inhibited the ferroptosis pathway and promoted the expression of antioxidant genes (up to 1.55–3.52 times). The in vivo application of SEL improved hair growth, with the length of new hair increasing by 16.7% and the length of new HF increasing by 92.6%, and the period of telogen shortening increased by 40.0%. This study proposes a novel therapeutic option for alopecia, with the effect and regulation mechanism of SEL on DPC systematically clarified.

The non-existing properties of the metamaterial surfaces can be utilized to improve the antenna radiation characteristics. In this article, a design and performance analysis of a Single Negative (SNG) metamaterial based antenna is imparted for LTE 46/WLAN and Ka-band (like in satellite communication for the receiving side) applications. The unit cell of the metamaterial surface exhibits negative permittivity and positive permeability; yielding a high magnitude positive refractive index, is used to improve and analyze the performance of the proposed monopole antenna element. The proposed SNG based antenna covers a −10 dB bandwidth from 5.35-5.69 GHz (LTE 46/WLAN) and 17.81-20.67 GHz (Ka-band). The total size of the proposed antenna element is $20.2\times 28$ .4 mm2 while a $2\times 3$ SNG metamaterial surface is used at the back of the antenna element which improves the gain from 4.52 dB to 9.13 dB for the desired Ka band and 1.17 to 5.04 dB for the LTE 46/WLAN band. Furthermore, for the LTE 46/WLAN frequency band, the impedance matching also gets better, resulting in the return loss improvement from −11 dB to −32.4 dB. Moreover, the radiation efficiency is also improved by more than 10 % for the Ka band after employing the SNG metamaterial surface. The measured results fall in good agreement with the simulated one and make the proposed SNG metamaterial based antenna design competent for the LTE 46/WLAN and Ka-band (like in satellite communication for the receiving side) applications.

Memristive crossbar Physical Unclonable Function (PUF) structures are emerging as strong security primitives for resource-constrained devices demanding good retention time, negligible standby power, small size, and ultra-low power operating requirements. Memristive PUF exploits the inherent high process variations of a memristor as a source of entropy to generate device-specific signatures. These PUFs need to be strong enough to deal with active and passive attacks as well as machine learning attacks, hence requires more device-to-device variability. Memristive PUF requires dense crossbar architecture to generate unique, uniform, and reliable device signatures. Dense memristive crossbars (Xbar) face the challenges of low noise margin, proper load resistance selection, scalability, and a precise sense circuitry at the load resistance side to read the resistive state of a memristor accurately. In this work, we have simulated and optimized the load resistance of memristive scaled up crossbar arrays. We have used two of our fabricated devices for memristive crossbar PUF simulation. The proposed crossbar PUF architecture satisfies the basic PUF evaluation metrics and improves noise margin (NM). The load resistance is optimized through MATLAB simulation. The impact of optimized load resistance on Xbar architecture is observed to be noticeable and around 18% improvement in the noise margin was observed when the crossbar is scaled up from $16\times 2$ to $128\times 2$ .

This paper presents a metasurface based multiple-input multiple-output (MIMO) antenna with a wideband operation for millimeter-wave 5G communication systems. The antenna system consists of four elements placed with a 90 degree shift in order to achieve a compact MIMO system while a $2\times 2$ non-uniform metasurface (total four elements) is placed at the back of the MIMO configuration to improve the radiation characteristics of it. The overall size of the MIMO antenna is $24\times 24$ mm2 while the operational bandwidth of the proposed antenna system ranges from 23.5-29.4 GHz. The peak gain achieved by the proposed MIMO antenna is almost 7dB which is further improved up to 10.44 dB by employing a $2\times 2$ metasurface. The total efficiency is also observed more than 80% across the operating band. Apart from this, the MIMO performance metrics such as envelope correlation coefficient (ECC), diversity gain (DG), and channel capacity loss (CCL) are analyzed which demonstrate good characteristics. All the simulations of the proposed design are carried out in computer simulation technology (CST) software, and measured results reveal good agreement with the simulated one which make it a potential contender for the upcoming 5G communication systems.

The emergence of coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2) has created a global alarming situation. Initially, diagnosis of the virus was conducted by a combination of different assays including; electron microscopy (EM), computed tomography (CT) scan and whole-genome sequencing. However, such time-consuming diagnosis has critically highlighted the need for a fast and specific testing approach for earlier detection. It is expected that the ongoing research advances and the continuing efforts for the fight against COVID-19 will soon bring a fruitful discovery in in vitro diagnostics techniques. Meanwhile, the efficiency and performance of any novel diagnostic approach should be censoriously analyzed before it comes into practice. The aims of this study were to evaluate and compare the different diagnostic tests recommended by the World Health Organization (WHO) for earlier detection of the novel SARSCoV-2. We found that the Clustered regularly interspaced short palindromic sequence (CRISPR/Cas) detection has relatively higher efficiency, compared to all the other tests. Therefore from this report, we concluded that the discovery of CRISPR/Cas based in vitro diagnostics will minimize the time limit as well as the cost for COVID19 detection.

A field experiment was performed at Research Farm of the University of Agriculture Peshawar, Pakistan to evaluate the effect of biochar on soil and plant nitrogen and yielding parameters of mung bean. The experiment was performed in randomize complete block design with split plot arrangement with four replications. Area of each experimental unit was 10.5 m2 and was applied with biochar at the rate of 0, 20, and 40 t ha-1 along with full and half levels of P and K i-e., (90 kg P, 60 kg K ha-1 and 45 kg P, 30 kg K ha-1). Nitrogen was applied to all the experimental units uniformly @ 25 kg N ha-1. The data showed that all of the analyzed parameters were significantly influenced with various biochar levels except fresh and dry weight of nodules. With full and half dose of P and K application, soil total N and soil organic matter were found significant with an increase of 16% and 7% as compared to half dose. With application of various levels of biochar, a significant increase was recorded in most of the parameters. Data regarding Soil N and soil O.M were found significantly enhanced at 40 t ha-1 with values of 0.15% and 2.64% which were 200% and 94% higher as compared to 0 t ha-1 biochar applications. Other parameters like 1000 grain weight, biological yield (fresh and dry), plant N and number of nodules were significantly affected with 20 t ha-1 biochar application which were increased by 20 %, 33%, 21% and 21% as compared to control. Combined application of P&K and biochar significantly affected soil total nitrogen i-e., 0.16% at (full×40 t ha-1) and nodulation number i-e., 36 at (half×20 t ha-1). It was concluded that biochar application @ 20 t ha-1 along with half levels of P and K, proved the best treatments combination for most of the plant parameters and hence they are recommended.

In paper, neutrosophic soft points with the concept of one point greater than the other and their properties, generalized neutrosophic soft open set known as soft b-open set, neutrosophic soft separation axioms theoretically with support of suitable examples with respect to soft points, neutrosophic soft 𝑏0 -space engagement with generalized neutrosophic soft closed set, neutrosophic soft 𝑏2 -space engagement with generalized neutrosophic soft open set are addressed. In continuation, neutrosophic soft 𝑏0 -space behave as neutrosophic soft 𝑏2 -space with the plantation of some extra condition on soft 𝑏0 -space, neutrosophic soft 𝑏3 -space and related theorems, neutrosophic soft 𝑏4 - space, monotonous behavior of neutrosophic soft function with connection of different neutrosophic soft separation axioms, monotonous behavior of neutrosophic soft function with connection of different neutrosophic soft close sets are reflected. Secondly, long touched has been given to neutrosophic soft countability connection with bases and sub-bases, neutrosophic soft product spaces and its engagement through different generalized neutrosophic soft open set and close sets, neutrosophic soft coordinate spaces and its engagement through different generalized neutrosophic soft open set and close sets, Finally, neutrosophic soft countability and its relationship with Bolzano Weirstrass Property through engagement of compactness, neutrosophic soft strongly spaces and its related theorems, neutrosophic soft sequences and its relation with neutrosophic soft compactness, neutrosophic soft Lindelof space and related theorems are supposed to address.

Background and purpose: New pressor protein (NPP) is a human plasma enzyme, which is structurally related to the beta-fragment of activated factor XII. The present study aimed to compare the effects of angiotensin converting enzyme inhibitors (captopril) and angiotensin type 1 receptor blocker (losartan) on the hypertension induced by NPP injection in normal (sham-2NX) and bilaterally nephrectomized rats (2NX). Experimental approach: In total, 60 male Wistar rats were sham operated or bilaterally nephrectomized under anesthesia. After 24 h of anesthesia with Inactin® (100 mg/kg), their systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) were measured before and after the intravenous administration of captopril, losartan, and NPP. Findings / Results: In the sham-2NX group, after NPP injection, changes were observed in SBP (145.99 ± 3.6 mmHg), DBP (93.9 ± 3.87 mmHg), and HR (400.29 ± 12.78 bpm). In the captopril group, SBP and DBP had no significant changes, while HR increased significantly (P = 0.001). In the losartan group, SBP and DBP decreased (P = 0.001 and P = 0.000, respectively), while HR had no significant changes. In the 2NX group, after NPP injection,changes were denoted in SBP (127.89 ± 9.03 mmHg), DBP (65.86 ± 5.69 mmHg), and HR (333.35 ± 11.47 bpm). In addition, captopril injection increased DBP(P = 0.016) and HR (P = 0.036) in response to NPP injection, while losartan injection had no significant effects in this regard. Conclusion and implications: It could be concluded that losartan could improve hypertension in normal rats, while captopril deteriorated hypertension in bilaterally nephrectomized rats in this hypertension model.

Pakistan has been in severe energy crises since the year 2004. Major reasons behind energy crises are lack of use of modeling tools in power planning and policy development, dependence on imported energy sources and poor governance. In this paper, electricity demand forecasting for Pakistan up to the year 2030 and a proposal for utilizing domestic energy resources, such as, coal, natural gas, and solar resources available in Baluchistan province of Pakistan for the electricity needs of the country are presented. Long-range Energy Alternative Planning (LEAP) software is used to develop energy demand model for Pakistan that forecasts energy demand under two scenarios, i.e., baseline scenario and energy conservation scenario for the period from 2018 to 2030. Electrical power generation capacity of coal, natural gas and solar resources is also calculated considering the capacity factor of each type of energy asset using MATLAB. This work suggests that Pakistan's energy demand forecast is 399 TWh under the baseline scenario and 312 TWh under the energy conservation scenario. The power generation potential of domestic energy assets available in Baluchistan is 500.041 TWh in total, which includes Natural Gas 392.768 TWh, Solar 84.935 TWh and Coal 22.338 TWh. This research would help relevant government departments in Pakistan for power capacity development as per the required energy demand and alleviate energy crises in Pakistan.

This study was conducted in a rice-based cropping scheme to investigate the impact of green manuring on soil health, considering soil physicochemical properties and sustainable crop production. A field experiment was started on 2 November 2015 and completed on 15 April 2018 under a rice–berseem (Trifolium alexandrinum) cropping system in calcareous soil. Two green manuring patterns, rice–berseem and rice–wheat–sesbania (rostrata), were compared with a commonly practiced rice–wheat (Oryza sativa-Triticumaestivum) cropping pattern. Green manuring of the berseem crop (last cutting) along with 50, 75, and 100% of the recommended fertilizer doses of nitrogen, phosphorus, and potassium (NPK) were compared with recommended NPK fertilization along with control (no fertilizer). The plant growth parameters of rice, including plant height, tillers per plant at maturity, and yield data, were recorded at harvest. The pre-sowing soil analysis revealed that the experimental soil was low in salts, and the nutrient (NPK) status was very low. The results indicated that green manuring substantially enhanced the grain and straw yield of rice crops. Green manuring combined with 75% of recommended NPK produced the highest grain yield (5.83 t ha−1 in year III) compared to the other treatments. The soil analysis showed that the bulk density was reduced while soil porosity, organic carbon, and N, K, and P contents were significantly improved. From the results of this study, it is recommended that under calcareous soil conditions, the regular use of green manuring can significantly improve crop growth, yield, and physicochemical properties of soil and, therefore, should be adopted by farmers.

Because of their simple design structure, end-to-end deep learning (E2E-DL) models have gained a lot of attention for speech enhancement. A number of DL models have achieved excellent results in eliminating the background noise and enhancing the quality as well as the intelligibility of noisy speech. Designing resource-efficient and compact models during real-time processing is still a key challenge. In order to enhance the accomplishment of E2E models, the sequential and local characteristics of speech signal should be efficiently taken into consideration while modeling. In this paper, we present resource-efficient and compact neural models for end-to-end noise-robust waveform-based speech enhancement. Combining the Convolutional Encode-Decoder (CED) and Recurrent Neural Networks (RNNs) in the Convolutional Recurrent Network (CRN) framework, we have aimed at different speech enhancement systems. Different noise types and speakers are used to train and test the proposed models. With LibriSpeech and the DEMAND dataset, the experiments show that the proposed models lead to improved quality and intelligibility with fewer trainable parameters, notably reduced model complexity, and inference time than existing recurrent and convolutional models. The quality and intelligibility are improved by 31.61% and 17.18% over the noisy speech. We further performed cross corpus analysis to demonstrate the generalization of the proposed E2E SE models across different speech datasets.

The main purpose of this planned manuscript is to establish an algorithm for the solution of multiattribute decision-making (MADM) issues, where the experts utilizing linguistic variables provide the information about attributes in the form of picture hesitant fuzzy numbers. So, for the solution of these kinds of issues, we develop the TOPSIS algorithm under picture hesitant fuzzy environment using linguistic variables, which plays a vital role in practical applications, notably MADM issues, where the decision information is arranged by the decision-makers (DMs) in the form of picture hesitant fuzzy numbers. Finally, a sample example is given as an application and appropriateness of the planned method. At the end, we conduct comparison analysis of the planned method with picture fuzzy TOPSIS method and intuitionistic fuzzy TOPSIS method.

Data caching has emerged as a promising technique to handle growing data traffic and backhaul congestion of wireless networks. However, there is a concern regarding how and where to place contents to optimize data access by the users. Data caching can be exploited close to users by deploying cache entities at Small Base Stations (SBSs). In this approach, SBSs cache contents through the core network during off-peak traffic hours. Then, SBSs provide cached contents to content-demanding users during peak traffic hours with low latency. In this paper, we exploit the potential of data caching at the SBS level to minimize data access delay. We propose an intelligence-based data caching mechanism inspired by an artificial intelligence approach known as Reinforcement Learning (RL). Our proposed RL-based data caching mechanism is adaptive to dynamic learning and tracks network states to capture users’ diverse and varying data demands. Our proposed approach optimizes data caching at the SBS level by observing users’ data demands and locations to efficiently utilize the limited cache resources of SBS. Extensive simulations are performed to evaluate the performance of proposed caching mechanism based on various factors such as caching capacity, data library size, etc. The obtained results demonstrate that our proposed caching mechanism achieves 4% performance gain in terms of delay vs. contents, 3.5% performance gain in terms of delay vs. users, 2.6% performance gain in terms of delay vs. cache capacity, 18% performance gain in terms of percentage traffic offloading vs. popularity skewness (γ), and 6% performance gain in terms of backhaul saving vs. cache capacity.

Objective: To synthesize and isolate silver and gold nanoparticles from Litchi chinensis leaf methanolic extract, and to evaluate its comparative biological activities including muscles relaxant, analgesic, anti-inflammatory and antidiarrheal. Methods: The gold and silver nanoparticles were synthesized by dissolving methanolic extract in gold chloride and silver nitrate solution separately which were confirmed by colour change and UV-Vis spectroscopy, and pellets were collected through centrifugation. Biological activities of the extract were conducted on BALB/c mice through various standard methods and the data were subjected to One-way ANOVA. Results: The colorless gold chloride solution changed to purple soon after the addition of plant extract, demonstrating that the reaction took place and gold ions were reduced to gold nanoparticles, while colorless silver nitrate solution changed to light and dark brown that was indicative of silver nanoparticles. The muscles relaxant activity showed that silver nanoparticles were more effective than gold nanoparticles and methanolic extract in traction test. The analgesic activity showed that silver and gold nanoparticles showed highest percentage decrease in acetic acid induced writhing at the doses of 50, 100 and 150 mg/kg b.w. The highest anti-inflammatory activity was produced by gold nanoparticles followed by silver nanoparticles, while low activity was observed in methanolic leaf extract. Only the crude methanolic extract showed significant antidiarrheal activity as compared to the standard drug atropine sulphate, while antidiarrheal activities of gold and silver nanoparticles were non-significant. Conclusions: The present work concludes that isolated silver and gold nanoparticles from leaf methanolic extract shows strong muscles relaxant, analgesic and anti-inflammatory activities while crude methanolic extract possesses good antidiarrheal activity.

All human beings are susceptible to numerous problems in life however the elderly population is much more vulnerable to such issues. The number of elderly population is increasing particularly in the developing countries. In 2050, it is estimated that the world will have more aged people than the children less than 15 years (Muhammad, 2013). Although elderly have better contributed in the development during their productive time, however, their contribution has not been acknowledged. They are not properly cared by their family members rather they are abused mentally and physically. They have weak economic status due to their weak physical and mental health. They are not allowed to be involved in decision making. These deprivations and deplorable condition have led them to be dependent on others. In Pakistan till now, no social policy has been devised which could have been influential in the solution of the elderly problem. This literature based study highlights the problems of the senior citizens of Pakistan.

This paper proposed a new technique to compressed image blockiness/blurriness in frequency domain through edge detection method by applying Fourier transform. In image processing, boundaries are characterized by edges and thus, edges are the problems of fundamental importance. The edges have to be identified and computed thoroughly in order to retrieve the complete illustration of the image. Our novel edge detection scheme for blockiness and blurriness shows improvement of 60 and 100 blocks for high frequency components respectively than any other detection technique.

Here, the structure-dependent electronic, thermal, and transport properties of nanostructured thallium telluride (Tl _8 Pb _x Sb _2− _x Te _6 ) through controlled variation in Pb and Sb (x = 1.96, 1.97, 1.98, 1.99) concentrations have been investigated. In the temperature and concentration-dependent electrical conductivity measurements, the highest electrical conductivity 131.96 × 10 ^3 ${{\rm{\Omega }}}^{-1}{m}^{-1}$ at 300 K was measured for x = 1.99 and the maximum observed Seebeck value for the optimized Tl _8 Pb _1.96 Sb _0.04 Te _6 nanoparticles was 110.7 μ V/K at 550 K. Such an increased value of the Seebeck coefficient led to the achievement of a significantly improved high-power factor, which was found to be increasing with temperature and decreasing with the increase of Pb concentration. The density functional theory calculations performed for Pb and Sb co-doped Tl _5 Te _3 resulted in the enhanced σ _e and S with a significant reduction in electronic thermal conductivity ( κ _e ) and is found consistent with experimentally measured κ _e . The highest ZT = 0.35 and 0.18 were recorded experimentally and theoretically for Pb and Sb co-doped in Tl _5 Te _3 nanoparticles.

The composition of the essential oil from leaves of Skimmia laureola was determined by GC and GC-MS. Twenty-eight components were identified, accounting for 93.9% of the total oil. The oil is mainly composed of monoterpenes (93.5%), of which monoterpene hydrocarbons and oxygenated monoterpenes represent 11.0% and 82.5%, respectively. Sesquiterpenes constitute only 0.3% of the total oil. Linalyl acetate is the main component (50.5%), with linalool (13.1%), geranyl acetate (8.5%) and cis-p-menth-2-en-1-ol (6.2%) as other principal constituents. The essential oil showed a significant antispasmodic activity, in a dose range of 0.03–10 mg/mL. The essential oil also possesses antibacterial and antifungal activities against some pathogenic strains. The phytotoxic and cytotoxic activities were also assessed.