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Appendiceal neuroendocrine tumors (NET) although rare, but the most common tumors of the gastrointestinal tract in children and adolescents. NET of the appendix is typically undiagnosed preoperatively, are usually not associated with specific neuroendocrine symptoms, and a high percentage are initially identified by pathologists. For well-differentiated tumors of ＜1 cm and complete (R0) resection, no follow-up is required. Unlikely, tumor size ＞2 cm or tumor with high-risk features confer a relevant risk of recurrence and further imaging and surgical procedures are warranted. No consensus, clear recommendation or management guidelines are available for the management of appendiceal NET in children. Herein, current article will provide an overview of literature and suggested guidelines for evaluation and management of childhood neuroendocrine tumors of appendix.

Abstract We examine the cosmic evolution of the growth of perturbations with respect to matter content at early and recent past era of the Universe under the framework of non-zero torsion cosmology. Some cosmographic parameters are also discussed. To analyze this cosmic scenario, we formulate the cosmic models with two dark matter considerations and apply spherical collapse formalism. We explore that for model-1 (pressureless matter), the density contrast starts growing in early era of the Universe and with the Universe’s overall expansion, density contrast grows faster for different choices of torsion parameter. In model-2 (matter with non-zero pressure), the density contrast shows enormous growth as compared to overall expansion of the Universe for the perturbed region, which indicates the collapse of the perturbed region and formulation of new large scale matter or galaxy. Further, we analyze the behavior of the growth function for both models with different values of torsion parameter. For model-1, the growth function increases smoothly for different choices of torsion parameter but for the model-2 the behavior of the growth function with nonzero DM and torsion significantly deviates from pressureless DM with zero torsion ( $$\Lambda $$ Λ CDM). We also investigate different cosmographic parameters for both models and analyze their behavior with different choices of torsion parameter and $$\Lambda $$ Λ CDM. The results show the power-law expansion rate of the accelerating Universe with respect to redshift function.

Abstract Background Intellectual disability (ID) is a condition that varies widely in both its clinical presentation and its genetic underpinnings. It significantly impacts patients’ learning capacities and lowers their IQ below 70. The solute carrier (SLC) family is the most abundant class of transmembrane transporters and is responsible for the translocation of various substances across cell membranes, including nutrients, ions, metabolites, and medicines. The SLC13A3 gene encodes a plasma membrane-localized Na+/dicarboxylate cotransporter 3 (NaDC3) primarily expressed in the kidney, astrocytes, and the choroid plexus. In addition to three Na + ions, it brings four to six carbon dicarboxylates into the cytosol. Recently, it was discovered that patients with acute reversible leukoencephalopathy and a-ketoglutarate accumulation (ARLIAK) carry pathogenic mutations in the SLC13A3 gene, and the X-linked neurodevelopmental condition Christianson Syndrome is caused by mutations in the SLC9A6 gene, which encodes the recycling endosomal alkali cation/proton exchanger NHE6, also called sodium-hydrogen exchanger-6. As a result, there are severe impairments in the patient’s mental capacity, physical skills, and adaptive behavior. Methods and results Two Pakistani families (A and B) with autosomal recessive and X-linked intellectual disorders were clinically evaluated, and two novel disease-causing variants in the SLC13A3 gene (NM 022829.5) and the SLC9A6 gene (NM 001042537.2) were identified using whole exome sequencing. Family-A segregated a novel homozygous missense variant (c.1478 C > T; p. Pro493Leu) in the exon-11 of the SLC13A3 gene. At the same time, family-B segregated a novel missense variant (c.1342G > A; p.Gly448Arg) in the exon-10 of the SLC9A6 gene. By integrating computational approaches, our findings provided insights into the molecular mechanisms underlying the development of ID in individuals with SLC13A3 and SLC9A6 mutations. Conclusion We have utilized in-silico tools in the current study to examine the deleterious effects of the identified variants, which carry the potential to understand the genotype-phenotype relationships in neurodevelopmental disorders.

One-dimensional nanostructures are generally cited as nanowires, nanofibers, nanotubes, and so on. The foremost prominent feature of these materials is their electrical conductivity, which, unlike classical physics, doesn't increase their resistance because the diameter decreases. Numerous properties of these materials like electrical conductivity, optical, magnetic, biological, and environmental their sensory have created many applications for them altogether industries. nanowires (NWs) propose potential impact on electronics, computing, memory, data storage, communications, manufacturing, health, medicine, national security, and other economic sectors as well. NWs offer excellent surface-to-volume ratio (interface phenomena), low defect density, high optical output, and controllable n-type conductivity, making them more appropriate and sensitive for sensing applications. NWs with their ultra-sensitive and real-time detection capabilities lend their applications in nano biosensors, chemical sensors, gas sensors, and electrochemical sensors. NWs have been used in improving the optical absorption as well as for the collection efficacy in photovoltaic devices. NWs having small size, low weight, low cost for mass production, and are also compatible with commercial planar processes for large-scale circuitry. In the paper, the authors are focusing to summarize the recent advances in NWs with their potential applications in various fields such as research, health, security, education, entertainment, and power generation.

The bioavailability of heavy metals in soil is a crucial factor in determining their potential uptake by plants and their subsequent entry into the food chain. Various methods, including traditional chemical extractants and the diffusive gradients in thin films (DGT) technique, are employed to assess this bioavailability. The bioavailability of heavy metals, particularly cadmium (Cd) and lead (Pb), is also influenced by soil texture and their concentrations in the soil solution. The primary objectives of this experiment were to compare and correlate the assessment of the Cd and Pb bioavailability using the DGT technique and traditional extractants across two soil textural classes: sandy clay loam (SCL) and clay loam (CL) at two contamination levels: aged contaminated (NC) and artificially contaminated (AC). The specific objectives included assessing the bioavailability of Cd and Pb at different growth stages of the wheat plant and correlating the DGT-based bioassessments of Cd and Pb with their concentrations in various plant parts at different growth stages. This study also compared the effectiveness of the DGT method and traditional extraction techniques in assessing the bioavailable fractions of Cd and Pb in soil. The regression analysis demonstrated strong positive correlations between the DGT method and various extraction methods. The results showed that the wheat plants grown in the AC soils exhibited lower root, shoot, and grain weights compared to those grown in the NC soils, indicating that metal contamination negatively impacts plant performance. The concentrations of Cd and Pb in the wheat tissues varied across different growth stages, with the highest levels observed during the grain filling (S3) and maturity (S4) stages. It is concluded that the in situ assessment of Cd and Pb though DGT was strongly and positively correlated with the Cd and Pb concentration in wheat plant parts at the maturity stage. A correlation and regression analysis of the DGT assessment and traditional extractants showed that the DGT method provides a reliable tool for assessing the bioavailability of Cd and Pb in soils and helped in developing sustainable soil management strategies to ensure the safety of agricultural products for human consumption.

Tick infestation poses an important challenge to livestock in Pakistan. Farm management practices and environmental variables can influence tick infestation prevalence in animals. To this end, a cross-sectional survey of 96 farms in four different geographical districts (24 farms from each district) was conducted in Punjab, Pakistan, between October 2021 and January 2022. An epidemiological questionnaire was designed focusing on farm management practices and their impact on tick infestations at these farms. Data were collected via in-person interviews. Regional and farm-specific variables’ associations were evaluated using Pearson’s chi-square test and Fischer’s exact test, respectively. A multivariable logistic regression model was used to identify significant risk factors. This study identified that using soft bedding materials, e.g., wheat straw, leaf litter or plain soil posed a significant risk of tick infestation. Additionally, the absence of quarantine measures, open sheds and inadequate drainage were found as contributing factors in univariable analysis. Higher tick prevalence in the hotter seasons highlighted the influence of Punjab’s extreme weather on tick infestation. Despite regular veterinary visits and the use of acaricidal drugs, the prevalence of tick infestation at these farms suggested potential drug resistance in the ticks. The study recommended establishing quarantine practices, improving farms’ drainage systems and bedding and using a combination of chemical and traditional remedies to tackle drug resistance in ticks. Education and awareness programs on tick-borne diseases and control measures are advocated to reduce the tick infestation burden on animals. Further research on longitudinal studies to better understand tick population dynamics and develop effective acaricides is encouraged. This called for collaborative control efforts among farmers, veterinarians and research institutions.

Formulating a mix design for 3D concrete printing (3DCP) is challenging, as it involves an iterative approach, wasting a lot of resources, time, and effort to optimize the mix for strength and printability. A potential solution is mix formulation through artificial intelligence (AI); however, being a new and emerging field, the open-source availability of datasets is limited. Limited datasets significantly restrict the predictive performance of machine learning (ML) models. This research explores data augmentation techniques like deep generative adversarial network (DGAN) and bootstrap resampling (BR) to increase the available data to train three ML models, namely support vector machine (SVM), artificial neural network (ANN), and extreme gradient boosting regression (XGBoost). Their performance was evaluated using R2, MSE, RMSE, and MAE metrics. Models trained on BR-augmented data showed higher accuracy than those trained on the DGAN-augmented data. The BR-trained XGBoost exhibited the highest R2 scores of 0.982, 0.970, 0.972, 0.971, and 0.980 for cast compressive strength, printed compressive strength direction 1, 2, 3, and slump flow respectively. The proposed method of predicting the slump flow (mm), cast, and anisotropic compressive strength (MPa) can effectively predict the mix design for printable concrete, unlocking its full potential for application in the construction industry.

Arsenic, the 20th most common element in Earth’s crust and historically regarded as the King of Poisons, occurs naturally in two oxidation states, Arsenate (V) and Arsenite (III), and is prevalent worldwide through natural and anthropogenic means. The cations of the metalloid exhibit unique chemical behaviour in water and are found to be components of approximately 245 natural minerals, making its occurrence in drinking water a compelling challenge, especially in groundwater. This comprehensive review collates information regarding the prevalence of arsenic contamination in water worldwide and its impact on human health, its chemical behaviour, methods for detection and quantification, and treatment strategies. A comprehensive search was conducted, and the selection of eligible studies was carried out using the PRISMA (the preferred reporting items for systematic reviews and meta-analyses) guidelines. Essential characteristics of eligible research studies were extracted based on geographical areas, origins, concentration levels and the magnitude of populations vulnerable to arsenic contamination in groundwater sources. Arsenic contamination of water affects over 100 countries including Canada, the United States, Pakistan, China, India, Brazil and Bangladesh, where hydrogeological conditions favour prevalence and groundwater is the primary water source for food preparation, irrigation of food crops and drinking water. This leads to human exposure through absorption, ingestion and inhalation, causing numerous health disorders affecting nearly all systems within the human body, with acute and chronic toxicity including cancers. The presence of arsenic in water poses a considerable challenge to humanity, prompting scientists to devise diverse mitigation approaches categorized as (a) oxidation processes, (b) precipitation methods, (c) membrane technologies, (d) adsorption and ion exchange methods, and (e) social interventions. This comprehensive review is expected to be a valuable source for professionals in the water industry, public management, and policymaking, aiding their ongoing and future research and development efforts.

Electrically conductive membranes (ECMs) were prepared by coating porous ethylenediamine-modified polyacrylonitrile (PAN-EDA) UF membranes with an ultrathin layer of platinum (Pt) nanoparticles through magnetron sputtering. These ECMs were used in electrofiltration to study the removal of brilliant blue dye from an aqueous solution under positive electrical potentials (0–2.5 V). Negative electrical potentials (−1.0–−2.5 V) were also investigated to regenerate the membrane by desorbing the dye from the ECM surface. At +0 V, the EC PAN-EDA membrane adsorbed the dye due to its intrinsic positive charge. Application of −2.0 V resulted in a maximum of 39% desorption of the dye. A modified Poisson-Boltzmann (MPB) model showed that −2.0 V created a repulsive force within the first 24 nm of the membrane matrix, which had a minimal effect on dye ions adsorbed deeper within the membrane, thus limiting the electro-desorption efficiency to 39%. Moreover, increasing positive potentials from +0.5 V to +2.5 V led to increased dye electro-adsorption by 9.5 times, from 132 mg/m2 to 1112 mg/m2 at pH 8 (equivalent to the membrane’s isoelectric point). The MBP simulations demonstrated that increasing electro-adsorption loadings are related to increasing attractive force, indicating electro-adsorption induced by attractive force is the dominant mechanism and the role of other mechanisms (e.g., electrochemical oxidation) is excluded. At pH 5, electro-adsorption further increased to 1390 mg/m2, likely due to the additional positive charge of the membrane (zeta potential = 9.2 mV) compared to pH 8. At pH 8, complete desorption of the dye from the ECM surface was achieved with a significant repulsive force at −2.0 V. However, as pH decreased from 8 to 5, the desorption efficiency decreased by 3.9% due to the membrane’s positive charge. These findings help elucidate the mechanisms of electro-adsorption and desorption on ECMs using dye as a model for organic compounds like humic acids.

The emergence of drug-resistance-inducing mutations in Hepatitis C virus (HCV) coupled with genotypic heterogeneity has made targeting NS3/4A serine protease difficult. In this work, we investigated the mutagenic variations in the binding pocket of Genotype 3 (G3) HCV NS3/4A and evaluated ligands for efficacious inhibition. We report mutations at 14 positions within the ligand-binding residues of HCV NS3/4A, including H57R and S139P within the catalytic triad. We then modelled each mutational variant for pharmacophore-based virtual screening (PBVS) followed by covalent docking towards identifying a potential covalent inhibitor, i.e., cpd-217. The binding stability of cpd-217 was then supported by molecular dynamic simulation followed by MM/GBSA binding free energy calculation. The free energy decomposition analysis indicated that the resistant mutants alter the HCV NS3/4A–ligand interaction, resulting in unbalanced energy distribution within the binding site, leading to drug resistance. Cpd-217 was identified as interacting with all NS3/4A G3 variants with significant covalent docking scores. In conclusion, cpd-217 emerges as a potential inhibitor of HCV NS3/4A G3 variants that warrants further in vitro and in vivo studies. This study provides a theoretical foundation for drug design and development targeting HCV G3 NS3/4A.

Virtual distillation using measurements of multiple copies of a quantum circuit have recently been proposed as a method of noise mitigation of expectation values. Circuit decompositions known as B gates were found only for 1-local Hamiltonians, however practical problems for chemistry require n-local Hamiltonians, which cannot be corrected with B gates. We discover low depth circuit decompositions for expectation values for n-local Pauli strings by combining multiple projections to recover the correct measurement statistics or expectation values. Our method adds linear entangling gates with the number of qubits, but it requires extra measurements. Furthermore, in applications to find ground states such as the variational quantum eigensolver (VQE) algorithm, the variational principle is required which states that the energy cannot go below the ground-state energy. We find that the variational principle is violated when using B gates and is preserved if we use our low depth decomposition on all expectation values. We perform a demonstration on real devices, and we show that our decomposition can mitigate real experimental noise in VQE for the H_{2} molecule with a two-qubit tapered mapping, H_{3} with three qubits, and H_{2} with four qubits. Our decomposition provides a way to perform duplicate circuit virtual distillation on real devices at significantly lower depth and for arbitrary observables.

Tissue engineering, a rapidly advancing field in medicine, has made significant strides with the development of artificial tissue substitutes to meet the growing need for organ transplants. Three-dimensional (3D) porous scaffolds are widely utilized in tissue engineering, especially in orthopedic surgery. This study investigated the fluidic properties of diamond and gyroid structures with varying porosity levels (50–80%) using Computational Fluid Dynamics (CFD) analysis. The pressure and velocity distributions were analyzed, and it was observed that the pressure decreased gradually, whereas the velocity increased in the central area of the surface structures. Specifically, the pressure drop ranged from 2.079 to 0.984 Pa for the diamond structure and from 1.669 to 0.943 Pa for the gyroid structure as the porosity increased from 50% to 80%. It was also found that the permeability increased as the porosity level increased, with values ranging from 2.424×10−9 to 5.122×10−9 m2 for the diamond structure and from 2.966×10−9 to 5.344×10−9 m2 for the gyroid structure. The wall shear stress (WSS) was also analyzed, showing a consistent decrease with increased porosity for both types of structures, with WSS values ranging from 9.903×10−2 to 9.840×10−1 Pa for the diamond structure and from 1.150×10−1 to 7.717×10−2 Pa for the gyroid structure. Overall, this study provides insights into the fluidic properties of diamond and gyroid structures, which can be useful in various applications such as tissue engineering.

Exploiting the power of quantum computation to realize superior machine learning algorithms has been a major research focus of recent years, but the prospects of quantum machine learning (QML) remain dampened by considerable technical challenges. A particularly significant issue is that generic QML models suffer from so-called barren plateaus in their training landscapes—large regions where cost function gradients vanish exponentially in the number of qubits employed, rendering large models effectively untrainable. A leading strategy for combating this effect is to build problem-specific models that take into account the symmetries of their data in order to focus on a smaller, relevant subset of Hilbert space. In this work, we introduce a family of rotationally equivariant QML models built upon the quantum Fourier transform, and leverage recent insights from the Lie-algebraic study of QML models to prove that (a subset of) our models do not exhibit barren plateaus. In addition to our analytical results we numerically test our rotationally equivariant models on a dataset of simulated scanning tunneling microscope images of phosphorus impurities in silicon, where rotational symmetry naturally arises, and find that they dramatically outperform their generic counterparts in practice.

Water pollution has become a great challenge today. To address this problem regarding wastewater treatment by removing toxic synthetic dyes from wastewater, this research focused on the synthesis of a novel starch-modified NiCrMn-layered double hydroxide composite through the coprecipitation method and applied it as a photocatalyst for the degradation of reactive orange 13 dye. The synthesized photocatalyst was characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), Brunauer–Emmett–Teller (BET), point of zero charges (PZC), dynamic light scattering (DLS), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and Zeta potential techniques. These techniques revealed different characteristics of photocatalysts, like surface and structural properties. According to BET analysis, the final composite had 2.5 × 102 m2/g BET-specific surface area with a 45.56 nm pore radius value, and the overall composite found as mesoporous. Similarly, in DLS analysis, bare NiCrMn-LDH had 404 nm hydrodynamic size, which increased for the final starch composite up to 667 nm. Zeta potential value changed from −14.56 mV to 0.95 mV after the incorporation of starch with NiCrMn-LDH. They confirmed the incorporation of starch with trimetallic NiCrMn-layered double hydroxide (2:1:2). Starch association improved the properties of the photocatalyst like surface area. Different parameters like pH value, initial dye concentration, photocatalyst dose, hydrogen peroxide concentration, effect of sacrificial reagent, and effect of inorganic anions were studied for degradation of RO13. Overall, the photocatalysis process for RO13 followed pseudo-first-order kinetics. Photocatalytic degradation reactions for reactive orange 13 were conducted with an initial dye concentration of 10 mg/L, photocatalyst dosage of 20 mg/50 mL, and pH value at 3 in the presence of sunlight, resulting in an impressive degradation removal rate of 86.68%. This remarkable degradation ability of the photocatalyst for reactive orange 13 proves this composite was highly efficient.

The extensive use of plastics has led to a significant environmental threat due to the generation of waste plastic, which has shown significant challenges during recycling. The catalytic hydrocracking route, however, is viewed as a key strategy to manage this fossil-fuel-derived waste into plastic-derived fuels with lower carbon emissions. Despite numerous efforts to identify an effective bi-functional catalyst, especially metal-loaded zeolites, the high-performing zeolite for hydrocracking plastics has yet to be synthesized. This is due to the microporous nature of zeolite, which results in the diffusional limitations of bulkier polymer molecules entering the structure and reducing the overall cracking of plastic and catalyst cycle time. These constraints can be overcome by developing hierarchical zeolites that feature shorter diffusion paths and larger pore sizes, facilitating the movement of bulky polymer molecules. However, if the hierarchical modification process of zeolites is not controlled, it can lead to the synthesis of hierarchical zeolites with compromised functionality or structural integrity, resulting in reduced conversion for the hydrocracking of plastics. Therefore, we provide an overview of various methods for synthesizing hierarchical zeolites, emphasizing significant advancements over the past two decades in developing innovative strategies to introduce additional pore systems. However, the objective of this review is to study the various synthesis approaches based on their effectiveness while developing a clear link between the optimized preparation methods and the structure-activity relationship of the resulting hierarchical zeolites used for the hydrocracking of plastics.

Owing to the massive expansion and intermittent nature of renewable power, green hydrogen production, storage, and transportation technologies with improved economic returns need to be developed. Moreover, the slowness of the dehydrogenation reaction is a primary barrier to the commercialization of liquid organic hydrogen carrier (LOHC) technology. The present study focused on increasing the speed of dehydrogenation, resulting in the proposal of a triple-loop dehydrogenation system comprising reaction, heating, and chilling loops. The reactor has a rotating cage containing a packed bed of catalyst pellets, which is designed to enhance both heat and mass transfer by helping to detach precipitated hydrogen bubbles from the catalyst surface. In addition, the centrifugal force aids in isolating the gas phase from the LOHC liquid. A dehydrogenation experiment was conducted using the reaction and chilling loops, which revealed that the average hydrogen production rate during the first hour was 52.6 LPM (liter per minute) from 26.3 L of perhydro-dibenzyl-toluene with 1.5 kg of 0.5 wt% Pt/Al2O3 catalyst. This was approximately 48% more than the value predicted with the reaction kinetics measured with a small-scale plug flow dehydrogenation reactor with less than 1.0 g of 5.0 wt% Pt/Al2O3 catalyst. The concept, construction methods, and results of the preliminary gas infiltration, flow visualization, and reactor pumping experiments are also described in this paper.

Background: An amputation is a dramatic event that brings marked changes in an individual life which may affect the person physically and psychologically. Objective: To determine the frequency of non-specific low back pain and its effect on function and health-related quality of life across three levels of lower limb amputation. Methods: A cross-sectional study was conducted at the Pakistan Institute of Prosthetic and Orthotics Peshawar (PIPOS) from May 2020 to Sep 2020. The inclusion criteria were: both males and females ages 18-65 years, patients with unilateral transfemoral, knee disarticulation, and transtibial amputation. The data were collected via a self-administered questionnaire. The outcomes were measured by the Roland Morris disability questionnaire (RMDQ), The short form 36 health survey (SF-36), and questions about the prevalence of LBP. The data was analyzed by SPSS v.25. Results: A total of 264 amputees with a frequency of male 219 (83%) and female 45(17%) participated in this study. There was a significant association between pre and post-amputation back pain (P< 0.05) while no significant association was found between LBP and across the three levels of amputation (P> 0.05). There was no statistical difference between disability and level of amputation (P> 0.05). A statistical difference was found between low back pain and all domains of quality of life except mental and physical health with (P< 0.05) while no statistical difference was found in the quality of life and across the three levels of amputation (P> 0.05). Conclusion: This study found that LBP was prevalent after amputation. There was a significant association between low back pain before and after amputation while no significant association was found in low back pain across the three levels of amputation. The effect of low back pain on disability was found statistically significant and the effect of low back pain on quality of life was significant in some domains like Physical function, and social function.

The research article in hand provides a new mechanism that deals with the investigation of the triangular analytical fuzzy solutions (TAFS) of the two-dimensional fuzzy fractional order wave equation (2-D FFWE) through the Hukuhara conformable fractional derivative (HCFD) along with the concept of [gH] and [gH−p] differentiability. The mechanism consists of a fuzzy traveling wave method coupled with additive operating splitting (AOS). The procedure for the aforesaid mechanism starts with the extension of the HCFD to the fuzzy conformable fractional derivative (FCFD). Furthermore, some properties of FCFD that play a vital role in this study like, ([i−gH],[ii−gH],[i−p],[ii−p])-differentiability, switching point, fuzzy chain rule, and traveling wave method are discussed in detail. Further, fuzzy traveling wave method coupled with the procedure of the additive operating splitting (AOS) method is adopted to investigate the triangular analytical fuzzy solution of the Two-dimensional fuzzy wave equation (2-D FWE). Finally, some examples are provided that support our arguments.

The fungal endophytes are an understudied area of research with great potential for new bioactive compounds’ discovery. These are the fungal strains that live within the inner compartments of the host plant without causing it any kind of harm. These fungal endophytes, in combination with the host organisms, synthesize many compounds with a range of pharmaceutical values. Most recently, the discovery of fungal endophyte genes which are linked with the biosynthesis of plant metabolites has opened a new field of research. These plant partners assist plants against biotic stress and protect them from pathogenic attacks or diseases with the presence of some important gene families like WRKY and MYB. The bioactive metabolites from this group are known for their anticancer, antimicrobial, antioxidant, antidiabetic, and anti-tubercular properties. Therefore, these bioactive compounds offer new routes for discovering novel drugs, which can boost the pharmaceutical industry in times of great demand for novel drugs. Extracellular enzymes are also produced within the members of this distinct group which are crucial for several industrial sectors, including the biofuel production industry. Furthermore, fungal endophytes are capable of synthesizing silver nanoparticles, which exhibit significant potential in fields like biomedical imaging and water purification. This article aims to document all the available data on this group of fungi living in medicinal plants and the major compounds produced by members of this distinct group that are in use for the therapy of various ailments.

The limitations in the available reinforcing methods have accompanied the increasing popularity of 3D Concrete Printing (3DCP). Incorporating steel fibers as reinforcement is a promising approach to overcome these limitations. However, the impact of the printing process on the alignment of these fibers is not well understood. Therefore, the objective of this research is to quantitatively analyze the distribution of steel fiber alignment in 3D printed concrete. To achieve this, digital image analysis was employed to assess the influence of nozzle diameter, print speed, and fiber content on fiber alignment in both mold-cast and 3D-printed samples. UHPC matrix without fiber addition and fiber reinforced UHPC composites with brass-coated steel fiber contents of 1.5% and 3% by volume fraction were printed. Furthermore, Material nozzles ranging from 10 mm to 40 mm in size were employed and printing speeds of 15, 25, 35, and 45 mm/s were adjusted. Subsequently, the study examined the implications of fiber alignment on the hardened performance of printed specimens and compared them with conventionally mold-cast samples. The findings of the study demonstrated that increasing the fiber content and using smaller diameter nozzles during the printing procedure led to significant improvements in fiber orientation along the printing direction. As a result, the mechanical performance of the printed samples showed a substantial enhancement compared to the specimens produced through mold casting, primarily due to the improved fiber alignment.

Buckwheat is a globally recognized, nutritionally rich crop with robust adaptability, serving as a multi-purpose plant for its health benefits. Achieving precise and mechanized plot seed harvesting is a critical step in obtaining accurate results in breeding experiments. However, plot breeding requires no seed retention, no mixing, and ensures no accumulation of seed in the threshing unit. A self-cleaning technology was developed to prevent seed retention, mixing, and accumulation in the multistage tangential cylinder threshing unit. The newly designed cleaning system has five air inlets and a centrifugal fan for pneumatic cleaning. CFD simulations were conducted for each inlet position, coupled with four varying inlet velocities and the rotation speed of the main threshing cylinder. During the post-processing stage of the CFD modeling, a line consisting of fifty points was drawn beneath the threshing drums, and the air velocity at these points was recorded. The optimal configuration of inlet position, inlet air velocity, and main threshing drum rotation speed for efficient cleaning was identified based on the ratio of points beneath the drums where the airflow speed surpassed the suspension speed of buckwheat to the points where the airflow speed was lower than the suspension speed of buckwheat. The optimal configuration for ''inlet_1'' was identified based on the suspension velocity of buckwheat grain, with an inlet velocity of 4 m/s and a main threshing drum speed of 450 rpm.

Modern industries rapid expansion has heightened energy needs and accelerated fossil fuel depletion, contributing to global warming. Additionally, organic pollutants present substantial risks to aquatic ecosystems due to their stability, insolubility, and non-biodegradability. Scientists are currently researching high-performance materials to address these issues. LaFeO3 nanosheets (LFO-NS) were synthesized in this study using a solvothermal method with polyvinylpyrrolidone (PVP) as a soft template. The LFO-NS demonstrate superior performance, large surface area and charge separation than that of LaFeO3 nanoparticles (LFO-NP). The LFO-NS performance is further upgraded by incorporating ZIF-67. Our results confirmed the ZIF-67/LFO-NS nanocomposite have superior performances than pure LFO-NP and ZIF-67. The integration of ZIF-67 has enhanced the charge separation and promote the surface area of LFO-NSwhich was confirmed by various characterization techniques including TEM, HRTEM, DRS, EDX, XRD, FS, XPS, FT-IR, BET, PL, and RAMAN. The 5ZIF-67/LFO-NS sample showed significant activities for CO2 conversion, malachite green degradation, and antibiotics (cefazolin, oxacillin, and vancomycin) degradation. Furthermore, stability tests have confirmed that our optimal sample very active and stable. Furthermore, based on scavenger experiments and the photocatalytic degradation pathways, it has been established that H+ and •O2− are vital in the decomposition of MG and antibiotics. Our research work will open new gateways to prepare MOFs-Perovskites nanocatalysts for exceptional CO2 conversion, organic pollutants and antibiotics degradation.

Households in developing countries rely on traditional cooking methods despite low-efficiency and high risks of air pollution and health. Various improved biomass cookstove technologies have been developed to address this issue, but there is still room for improvement in biomass cooking technology. This research aims to enhance the biomass cookstove by investigating its performance under different air inlet conditions using computational fluid dynamics analysis. The impact of air flow rate and the position of the secondary air inlet on the thermal efficiency of the biomass cookstove is examined. The eddy dissipation combustion model and k-epsilon turbulence model are utilized in ANSYS Fluent to simulate the combustion process. The cookstove's performance is assessed at three different air flow rates (0.01, 0.02, and 0.03 kg/s) and at two different secondary air inlet positions. The highest thermal efficiency is observed at secondary air inlet located 50 mm below the outlet at a flow rate of 0.03 kg/s. The computational findings from this investigation show a significant connection between the air inlet conditions and the thermal efficiency of the biomass cookstove. Repositioning the secondary air inlet to a location with more available space for complete combustion improves thermal efficiency compared to traditional designs.

The multi-Fano interference, which is obtained through the simultaneous acquisition of bright and dark states in different phase transitions of Eu3+ : BiPO4 (7 : 1, 6 : 1, 1 : 1, and 0.5 : 1) and Eu3+ : NaYF4 (1 : 1/4) crystals, were reported in this work. Multidressed spontaneous four-wave mixing and multidressed fluorescence (multiorder) were adopted to optimize the strong photon–phonon nested dressing effect, which results in more obvious multi-Fano interference. Firstly, the multi-Fano is produced through interference in continuous and multibound states. Secondly, five multi-Fano dips are originated from the nested five dressings (one photon and four phonons) under symmetrical splitting of 7F1 energy level. It is found that the pure H-phase (0.5 : 1) sample exhibits the strongest photon–phonon dressed effect (five Fano dips). Further, high-order non-Hermitian exceptional points in multi-Fano interference were investigated by adjusting the ratio of Rabi frequency to dephase rate through nested photon and phonon dressing. The experimental results are validated by theoretical simulations, which may be applied to designing optoelectronic devices such as non-Hermitian multi-Fano interferences (multichannel) router.

In this article, the rheological effects of an Oldroyd 8-constant fluid model in the presence and absence of magnetic force (MHD) are investigated while traveling between the two rolls rotates in the same direction. The governing equations of the fluid flow have been simplified using the lubrication approximation theory (LAT). Analytical solutions in the presence and absence of MHD are presented using (i) Adomian’s decomposition method (ADM), (ii) Homotopy analysis method (HAM), and numerical simulations are performed by (iii) the finite difference method. We present the results of our findings through various graphs and validate the numerical and analytical methods through detailed tables of error comparisons. It has been found that non-Newtonian and magnetic parameters have a significant impact on the velocity profiles, pressure gradient, pressure distribution, separation points, and coating thickness. The material parameters α1 (dilatant parameter) and α2 (pseudoplastic parameter) notably affect the velocity profile of the fluid flow between two rolls. Increasing α1 causes shear thickening and decreases the velocity profile, while increasing α2 results in shear thinning and increases the velocity profile due to diminished internal resistance. A relationship exists between the MHD parameter m and the flow velocity. The greater the MHD force, the higher the resistance in fluid flow, resulting in lower velocity. A reasonable agreement has been found between Newtonian fluid and Oldroyd 8-constant fluid, assuming all the non-Newtonian parameters to be zero. The results provided a comprehensive methodology for regulating the coating thickness by adjusting the modified Capillary’s number in the industry.

The Lie group method stands as a significant, powerful, and straightforward mathematical tool for discovering precise invariant solutions and traveling wave solutions in prevalent nonlinear evolution equations across engineering, applied mathematics, and physics. The interplay of dispersive effects arising from material microstructure, combined with nonlinearities, results in the formation of solitary waves. In this article, we apply the Lie group method to derive invariant and comprehensive traveling wave solutions for the strain wave equation in microstructured solids. This yields a diverse array of exact solutions, including traveling wave solutions, solitons, shock waves, periodic, singular, and rational solutions, all of which bear potential significance in various engineering applications.

The propagation of elastic waves in hyperelastic materials is described by a nonlinear system of partial differential equations (PDEs) governing the material’s motion. Hyperelastic materials are characterized by a strain–energy density function that correlates material deformation with stored elastic energy. For simplicity, we focus on the one-dimensional case where the displacement field, denoted as ϕ(x,t), signifies material deformation along the x-direction at position x and time t. The governing equation for elastic wave propagation in hyperelastic materials is derived from the strain–energy density function and associated stress–strain relations. In this study, Lie symmetry analysis is used to examine a nonlinear system of such equations relevant to the propagation of elastic waves in hyperelastic materials. The resulting equations are solved by applying Lie’s invariance criterion, yielding a ten-dimensional Lie algebra. An optimal system is derived from this algebra, allowing for the identification of invariant solutions under certain conditions. Additionally, the multiplier approach and Ibragimov’s new conservation laws are utilized to obtain the conservation laws for this coupled system of elastic waves. The outcome presented here is innovative and suggests utilizing the Lie symmetry method for investigating hyperelastic materials.

In recent times, there has been a substantial increase in the annual use of plastics, resulting in a major upward trend. As a result, recycling plastic waste has become a major global issue. The present research aims to explore the feasibility of utilizing Polyethylene terephthalate (PET) as a possible substitute for coarse aggregate in concrete. In addition, the integration of Graphene Nano-platelets (GNPs) into the concrete mixture was conducted using different quantities, aiming to improve its structural integrity. The study employed an experimental research design to carry out its examination. PET was included into concrete at varied ratios, namely 0 %, 5 %, 15 %, 20 %, and 25 %, serving as an additional ingredient alongside coarse aggregate. Additionally, GNPs were introduced into the mixture at various weight percentages, namely 0 %, 0.03 %, 0.05 %, 0.08 %, and 0.1 %. A series of mechanical tests were performed to evaluate various properties of the concrete, including compressive strength (CS), split tensile strength (STS), flexural strength (FS), modulus of elasticity (MoE), ultrasonic pulse velocity (UPV). In addition, an assessment of the concrete's environmental impact was conducted by analysing the carbon content and evaluating its eco-efficiency (ESE). The research study revealed that the incorporation of 5 % PET as a replacement for coarse aggregate, together with the inclusion of 0.1 % GNPs, resulted in the optimal enhancement of CS, STS, FS, MOE, UPV by 9 %, 12.21 %, 4.40 %, 4.40 % and 0.070 % respectively. The Response Surface Methodology (RSM) models were developed, and mathematical equations were generated in order to predict the expected results. The optimization process for all the models was carried out using a multi-objective optimization technique, followed by a subsequent validation process.

This study evaluates the earthquake-induced movement of geogrid earth-retaining (GER) walls. A thorough investigation was conducted on a GER wall model, utilizing a comprehensive finite element (FE) analysis. This research focuses on investigating and designing hollow prefabricated concrete panels and conventional gravity-type stone masonry GER walls. It also displays comparative studies such as the displacement of the wall, deflection of the wall, lateral pressure of the wall, settlement of the backfill reinforcement, vertical pressure of the backfill, lateral pressure of the backfill, vertical settlement of the foundation, and settlements of soil layers across the height and acceleration of the walls of the GER walls. The FE simulations used a three-dimensional (3D) nonlinear dynamic FE model of full-scale GER walls. The seismic performance of models has also been examined in terms of wall height. It was found that the seismic motion significantly impacts the height of the GER walls. In addition, the validity of the proposed study model was assessed by comparing it to the conventional reinforcement concrete and gravity-type GRE wall and ASSHTO guidelines using finite element (FE) simulation results. Based on the findings, the hollow prefabricated concrete panels were the most practical alternative due to their lower deflection and displacement. Based on the observation, it was also found that the hollow prefabricated GER wall is the most viable option, as the settlement and lateral pressure in the former type are high.

Nanotechnology offers promising applications in agriculture and horticulture. Specifically, nanofertilizers (NFs) have been investigated for enhancing growth, antioxidant defense, and productivity in fruit-bearing plants. These crops are vital for supplying essential nutrients and minerals to humans. However, their production and quality often face challenges from various stresses. Using nanoparticles (NPs) can potentially mitigate these challenges, thereby improving the productivity and quality of horticulture crops. NPs possess unique chemical and physical properties that benefit plant growth, development, and stress tolerance, making them valuable for fruit crop enhancement. This review highlights recent advancements in employing nanoparticles to bolster fruit crop growth. Various nanoparticle types, such as metal oxide, metallic, carbon-based, and organic NPs have been demonstrated positive effects on plant abiotic stress tolerance growth and fruit quality. They have been found to boost nutrient absorption, neutralize free radicals, and activate plant stress response pathways, leading to enhanced quality and yield of fruit. This review aims to elucidate significant insights into the utilization of nanoparticles as a promising strategy for bolstering the resilience of horticultural plants and safeguarding food security in the face of environmental alterations. Notwithstanding the favorable outcomes observed in ameliorating plant performance under abiotic stresses, the molecular mechanisms underlying the beneficial effects of NPs remain a subject of ongoing investigation. Further research is imperative to delve into the enduring implications, safety considerations, and optimal techniques for the application of NPs in horticultural plants.

Objective: To investigate the association between the tumour budding of colorectal carcinoma and its histological type, grade, lymph node metastasis, and pathological stage. Study Design: Cross-sectional study Place and Duration of Study: Histopathology Department, Armed Forces Institute of Pathology, Rawalpindi Pakistan, from Dec 2021 to Mar 2023. Methodology: One hundred and twenty colorectal carcinoma patients were examined for existence and severity using Hematoxylin and Eosin-stained sections. According to the number of tumour buds, cases were categorised as low grade (20/200X). These categories were related to lymph node involvement, histological type and grade, and pathological staging. In challenging cases, pan-cytokeratin immunohistochemistry labelling was conducted to confirm tumour budding. Results: The mean age of presentation was 55.78±12.47 years. The most common site of involvement was the ascending colon 66(55%), followed by the recto-sigmoid colon 29(24.2%). Most cases were conventional adenocarcinoma 80(67%), followed by mucinous carcinoma 31(26%). Most cases were moderately differentiated 62(52%) and were stage III 79(66%). Forty-two (35%) had low-grade, and thirty-four (28.3%) had intermediate-grade and high-grade tumour budding. Tumour budding significantly correlates with tumour size, histological grade, invasion extent, and lympho-vascular invasion (p-value

Background: Ulcerative colitis is a chronic immune-mediated inflammatory bowel disease that involves inflammation and ulcers of the colon and rectum. To date, no definite cure for this disease is available.Objective: The objective of the current study was to assess the effect of Calliandra haematocephala on inflammatory mediators and oxidative stress markers for the exploration of its anti-ulcerative colitis activity in rat models of acetic acid-induced ulcerative colitis.Methods: Methanolic and n-hexane extracts of areal parts of the plant were prepared by cold extraction method. Phytochemical analysis of both extracts was performed by qualitative analysis, quantitative methods, and high-performance liquid chromatography (HPLC). Prednisone at 2 mg/kg dose and plant extracts at 250, 500, and 750 mg/kg doses were given to Wistar rats for 11 days, which were given acetic acid on 8th day through the trans-rectal route for the induction of ulcerative colitis. A comparison of treatment groups was done with a normal control group and a colitis control group. To evaluate the anti-ulcerative colitis activity of Calliandra haematocephala, different parameters such as colon macroscopic damage, ulcer index, oxidative stress markers, histopathological examination, and mRNA expression of pro and anti-inflammatory mediators were evaluated. mRNA expression analysis was carried out by reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR).Results: The phytochemical evaluation revealed polyphenols, flavonoids, tannins, alkaloids, and sterols in both extracts of the plant. Results of the present study exhibited that both extracts attenuated the large bowel inflammation and prevented colon ulceration at all tested doses. Macroscopic damage and ulcer scoreswere significantly decreased by both extracts. Malondialdehyde (MDA) levels and nitrite/nitrate concentrations in colon tissues were returned to normal levels while superoxide dismutase (SOD) activity was significantly improved by all doses. Histopathological examination exhibited that both extracts prevented the inflammatory changes, cellular infiltration, and colon thickening. Gene expression analysis by RT-qPCR revealed the downregulation of pro-inflammatory markers such as tumor necrosis factor-alpha (TNF-α) and cyclooxygenase-2 (COX-2) whereas the anti-inflammatory cytokines including Interleukin-4 (IL-4) and Interleukin-10 (IL-10) were found to be upregulated in treated rats.Conclusion: It was concluded based on study outcomes that methanolic and n-hexane extracts of Calliandra haematocephala exhibited anti-ulcerative colitis activity through modulation of antioxidant defense mechanisms and the immune system. In this context, C. haematocephala can be considered as a potential therapeutic approach for cure of ulcerative colitis after bioassay-directed isolation of bioactive phytochemicals and clinical evaluation.

Objectives: To evaluate the quality of sleep in patients hospitalised with coronavirus disease-2019, and its impact on hospitalisation duration, need for intensive care unit admission and mortality. Methods: The cross-sectional study was conducted at the Pakistan Institute of Medical Sciences, Islamabad, Pakistan, from May 2, 2021 to April 30, 2022, and comprised hospitalised coronavirus disease-2019 patients. Data was gathered using the Pittsburgh Sleep Quality Index questionnaire, including demographics, comorbidities, length of hospital stay, need for intensive care unit admission, C-reactive protein and D-dimer values at admission, and the outcome. The patients were divided into group A having good sleep quality score >5 and group B having poor sleep quality score 0.05). The difference was significant with respect to gender, comorbid conditions, education status as well C-reactive protein and D-dimer levels (p

Nanomaterials (NMs) have garnered significant attention in recent decades due to their versatile applications in a wide range of fields. Thanks to their tiny size, enhanced surface modifications, impressive volume-to-surface area ratio, magnetic properties, and customized optical dispersion. NMs experienced an incredible upsurge in biomedical applications including diagnostics, therapeutics, and drug delivery. This minireview will focus on notable examples of NMs that tackle important issues, demonstrating various aspects such as their design, synthesis, morphology, classification, and use in cutting-edge applications. Furthermore, we have classified and outlined the distinctive characteristics of the advanced NMs as nanoscale particles and hybrid NMs. Meanwhile, we emphasize the incredible potential of metal-organic frameworks (MOFs), a highly versatile group of NMs. These MOFs have gained recognition as promising candidates for a wide range of bio-applications, including bioimaging, biosensing, antiviral therapy, anticancer therapy, nanomedicines, theranostics, immunotherapy, photodynamic therapy, photothermal therapy, gene therapy, and drug delivery. Although advanced NMs have shown great potential in the biomedical field, their use in clinical applications is still limited by issues such as stability, cytotoxicity, biocompatibility, and health concerns. This review article provides a thorough analysis offering valuable insights for researchers investigating to explore new design, development, and expansion opportunities. Remarkably, we ponder the prospects of NMs and nanocomposites in conjunction with current technology.

The contamination of farm soils with heavy metals (HMs) has raised significant concerns due to the increased bioavailability and accumulation of HMs in agricultural food crops. To address this issue, a survey experiment was conducted in the suburbs of Multan and Faisalabad to investigate the spatial distribution, bioaccumulation, translocation, and health risks of cadmium (Cd) and lead (Pb) in agricultural crops. The results show a considerable concentration of Cd and Pb in soils irrigated with wastewater, even though these levels were below the permissible limits in water and soil matrices. The pollution index for Cd was mostly greater than 1 at the selected sites, indicating its accumulation in soil over time due to wastewater irrigation. Conversely, the pollution index for Pb was below 1 at all sites. Among the plants, Zea mays accumulated the highest concentration of Cd and Pb. The translocation factor from soil to root was highest for Brassica olearecea (7.037 for Cd) and Zea mays (6.383 for Pb). The target hazard quotient (THQ) value of Cd exceeded the non-carcinogenic limit for most vegetables. The highest value was found in Allium cepa (5.256) and the lowest in Allium sativum (0.040). In contrast, the THQ level of Pb was below the non-carcinogenic limit for most vegetables, except for Allium cepa (1.479), Solanum lycopersicum (1.367), and Solanum tuberosum (1.326). The study highlights that Allium cepa poses the highest health risk for humans, while Medicago sativa poses the highest risk for animals due to Cd and Pb contamination. These results underscore the urgent need for effective measures to mitigate the health risks associated with HM contamination in crops and soils.

Unmanned aerial vehicles (UAV) rely on a variety of sensors to perceive and navigate their airborne environment with precision. The autopilot software interprets this sensory data, acting as the control mechanism for autonomous flights. As UAVs are exposed to physical environment, they are vulnerable to potential impairments in their sensory mechanism. Their real-time interactions with the actual atmosphere make them susceptible to cyber exploitations as well, where sensory data alterations through counterfeit wireless signals pose a significant threat. In this context, sensor failures can result into unsafe flight conditions, as the fault handling logic may fail to anticipate the context of the issue, allowing autopilot to execute operations without necessary adjustments. Untimely control of sensor failures can result in mid-air collisions or crashes. To address these challenges, we created Biomisa Arducopter Sensory Critique (BASiC) dataset, a state-of-the-art resource for UAV sensor failure analysis. The BASiC dataset comprises 70 autonomous flight data, spanning over 7 hours. It encompasses 3+ hours of (each) pre-failure and post-failure data, along with 1+ hour of no-failure data. We selected the ArduPilot platform as our demonstration aerial vehicle to conduct the experiments. By engineering Software in the Loop (SITL) parameters, we effectively executed sensor failure test simulations. Our dataset incorporates six representative sensors failures which are critical to UAV operations: global positioning system (GPS) for precise aerial positioning, remote control for communication with the ground control station (GCS), accelerometer for measuring linear acceleration, gyroscope for rotational acceleration measurement, compass providing heading information, and barometer for maintaining flight height based on atmospheric pressure data. The availability of the BASiC dataset will benefit the research community, empowering researchers to explore and experiment with state-of-the-art deep learning models by tailoring them for time series signal analysis. It may also contribute in enhancing the safety and reliability of mission-critical autonomous UAV flights.

Amino acid ionic liquids (AAILs) have gained significant attention as green solvents that are biocompatible, biodegradable, and useful in various applications, including catalysts, absorbents, and solvents. This study investigates the detailed interactions of three amino acid anions (glycine [Gly]-, histidine [His]-, and arginine [Arg]-) with the cation 1-methoxylbutyl-3-methylimidazolium [MOBMIM]+ and their role in CO2 absorption using quantum mechanical calculations and molecular dynamics (MD) simulations. The Density Functional Theory (DFT) calculations elucidate the reaction mechanisms underlying CO2 absorption and cycloaddition, and facilitate a comparative analysis of the impact of different amino acids on these reactions, and the synergies between them. Notably, arginine displays superior CO2 absorption capacity in comparison to glycine and histidine. Additionally, the cycloaddition reaction with CO2 exhibits a lower energy barrier when arginine is involved. Insights from the MD simulations highlight the higher level of electrostatic interaction between [MOBMIM]+[Arg]- and CO2, relative to the other studied molecules. Moreover, the Lennard Jones interaction emerges as the dominant type of interaction in these systems. The diffusion coefficient for CO2 was highest when interacting with [MOBMIM]+[Gly]-, followed by [MOBMIM]+[Arg]-. Consequently, both MD and DFT investigations converge to suggest that [MOBMIM]+[Arg]- followed by [MOBMIM]+[Gly]- may serve as advantageous choices for CO2 fixation and cycloaddition. The findings from this study underscore the considerable potential of the investigated AAILs as materials conducive to CO2 capture and utilization, thus paving the way for the integration of CO2 capture into valuable chemical products.

Quantum machine learning (QML) is emerging as an application of quantum computing with the potential to deliver quantum advantage, but its realization for practical applications remains impeded by challenges. Among these, a key barrier is the computationally expensive task of encoding classical data into a quantum state, which could erase any prospective speedups over classical algorithms. In this study, we implement methods for the efficient preparation of quantum states representing encoded image data using variational, genetic, and matrix product state algorithms. Our results show that these methods can approximately prepare states to a level suitable for QML using circuits 2 orders of magnitude shallower than a standard state preparation implementation, thus drastically reducing circuit depth and gate count without unduly sacrificing classification accuracy. Additionally, the QML models trained and evaluated on approximately encoded data displayed an increased robustness to adversarially generated input data perturbations. This partial alleviation of adversarial vulnerability, made possible by the retention of the meaningful large-scale features of the data despite the “drowning out” of adversarial perturbations, constitutes a considerable benefit for approximate state preparation in addition to lessening the requirements of the quantum hardware. Our results, based on simulations and experiments on IBM quantum devices, highlight a promising pathway for the future implementation of accurate and robust QML models on complex datasets relevant for practical applications, bringing the possibility of NISQ-era QML advantage closer to reality.

In this current study, hydrothermal method was employed to synthesize distinct nanostructures: pure nickel oxide (NiO), Zn-doped NiO, and NiO/ZnO composites. X-ray diffraction (XRD) results confirmed NiO’s cubic structure, with sizes of 17.01 nm for pure NiO and 30.87 nm for composites. Scanning electron microscope (SEM) images revealed flowerlike morphologies, energy-dispersive X-ray spectroscopy (EDX) authenticated the elemental composition without any impurities. Ultraviolet–visible (UV-Vis) spectroscopy demonstrated heightened absorption in doped and nanocomposite samples. The bandgap energy calculated using Tauc’s plot reduced from 2.95 to 2.55 eV with increase in zinc (Zn) content. In Fourier-transform infrared (FTIR) characterization, the Ni–O stretching vibration appeared at 666.7 cm−1 in doped samples, while Zn–O stretching was evident at 586.03 cm−1. Photoluminescence analysis unveiled a strong peak at 470 nm (near band edge) and another at 665 nm (indicative of defects), exhibiting intensified signals in doped and nanocomposite samples due to a higher defect density. The dielectric constant showed increased values at low frequencies attributed to real and space charge polarization. Notably, the conductivity of Zn-doped and nanocomposite samples displayed an upward trend with frequency due to a higher defect density. This study unveils insights into the intricate optical and electrical properties of these novel nanostructures, showcasing their potential in advanced energy storage applications.

Energy demand is continuously increasing around the globe, and the building sector contributes 40% of the total energy consumption, as per the studies. Fossil fuels are the primary cause of harmful gas emissions, thus causing environmental pollution. There is a dire need to introduce innovative techniques to fulfill energy demands while reducing environmental pollution. Phase change materials (PCMs) are the latent thermal storage materials that store thermal energy during phase change from solid to liquid state and vice versa. Thus, using PCMs in structural engineering offers one of the best options for rapidly developing energy-saving materials. To do so, ascaled model, concrete walls room, encapsulating locally available PCMs, was constructed in this study. Three locally available PCMs (glycerin, vegetable ghee, and ferric chloride hexahydrate) have been tested in a controlled environment. The model response is then evaluated for the energy-storing capacity of each PCM while considering the human comfort zone. From the test results, it is concluded that PCMs have a significant effect on improving the thermal energy efficiency of the model without any notable adverse effects. Over the completion of the test, after 12 hr, all the incorporated PCM showed positive results, and a maximum temperature loss of 2.25 K was observed. Among different PCMs, the optimal performance was observed for vegetable ghee, which showed a drop in temperature for all the points at the inner side of the wall, i.e., T3, T4, and T5.

Ivermectin (IVM) is an anti-parasitic drug which is used for treating parasitic infestations. It has been used in humans for treating intestinal strongyloidiasis and onchocerciasis however, currently researchers are investigating its potential for treating coronavirus SARS-CoV-2. Due to its broad-spectrum activities, IVM is being used excessively in animals which has generated an interest for researchers to investigate its toxic effects. Cytotoxic and genotoxic effects have been reported in animals due to excessive usage of IVM. Therefore, this study aims to evaluate the cytotoxic and genotoxic effects of IVM on the Madin-Darby-Bovine-Kidney (MDBK) cell line by examining the expression of a DNA damage-responsive gene (OGG1). Cytotoxicity of IVM was tested using an assay (MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide), whereas the genotoxicity was evaluated using comet assay along with micronucleus assay. Moreover, the gene expression of DNA damage response gene (OGG1) was measured by qRT-PCR, after extraction of RNA from the MDBK cell line using the TRIzol method and its conversion to cDNA by reverse-transcriptase PCR. During the experiment, cell viability percentage was measured at different doses of IVM i.e., 25%, 50%, 75%, along with LC50/2, LC50 and LC50*2. It was observed that the gene expression of OGG1 increased as the concentration of IVM increased. It was concluded that IVM has both cytotoxic and genotoxic effects on the MDBK cell line. Furthermore, it is recommended that studies related to the toxic effects of IVM at molecular level and on other model organisms should be conducted to combat its hazardous effects.

Musca domestica L. (Muscidae: Diptera) is a human and livestock pest especially in tropical and sub-tropical areas. Different insecticides have been used to control this pest that pose serious harmful effects on humans and the environment. The current study was planned to investigate the effects of two concentrations (LC25 and LC50) of pyriproxyfen on biological and population parameters of a field strain of M. domestica. The exposed parents (F0) and their progeny (F1) were studied to examine the transgenerational effects. The results indicated that preadult duration was higher in control (13.68 days) compared to LC50 treated individuals (12.44 days). The male and female longevity was relatively lower in the LC25 treated population i.e. 24.62 and 26.62 days, respectively. The adult pre-oviposition period (APOP) and total pre-oviposition period (TPOP) values were higher in the LC25 treated individuals than those of control. Moreover, oviposition days and fecundity were reduced in the treated individuals as compared to the control treatment. A gradual decrease in the net reproductive rate (R0) was observed (8.46-14.07 per day) while the value of R0 was significantly higher in control. The results suggested that pyriproxyfen can be effectively utilized and incorporated in the management programs of M. domestica.