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Abstract This paper proposes a new optimization technique to make an integration between the Optimal Reactive Power Dispatch (ORPD) problem and Electric Vehicles (EV). Here, a modified metaheuristic algorithm, called the Promoted Osprey Optimizer (POO) is used for this purpose. Inspired by the hunting behavior of ospreys, a predatory bird species, the POO algorithm employs various strategies like diving, soaring, and gliding to effectively explore the search space and avoid local optima. To evaluate its performance, the POO-based model has been applied to the IEEE 118-bus and IEEE 57-bus systems, considering different scenarios of EV penetration. The experimental findings demonstrate that the POO algorithm can effectively optimize the reactive power dispatch problem with EV integration, achieving significant reductions in active power losses and voltage deviations toward several existing metaheuristic optimization techniques in different terms. The POO algorithm demonstrates a significant reduction in power loss, achieving up to 22.2% and 16.2% in the 57-bus and 118-bus systems, respectively. This improvement is accompanied by reductions in voltage deviation of up to 20.6% and 15.7%. In the 57-bus system, power loss is reduced from 2.35 MW to 1.93 MW, while voltage deviation decreases from 0.034 p.u. to 0.027 p.u. For the 118-bus system, power loss is lowered from 4.21 MW to 3.53 MW, and voltage deviation is reduced from 0.051 p.u. to 0.043 p.u. Furthermore, the POO algorithm surpasses other optimization methods in minimizing voltage deviation, achieving reductions of up to 0.056 p.u. in the 57-bus system and up to 0.163 p.u. in the 118-bus system. Consequently, the POO algorithm holds great potential as a valuable tool for power system operators and planners to optimize reactive power dispatch and enhance power system performance with EV integration.

Abstract Wheat (Triticum aestivum L.) is a staple crop of immense economic importance, especially in the agronomic context of Dera Ismail Khan, Khyber Pakhtunkhwa (KPK), Pakistan. Understanding the effects of various agronomic practices, such as priming techniques, sowing methods, and seed rates, on wheat yield and growth is crucial for optimizing production and ensuring regional food security. To study the effects of priming and sowing techniques in combination with seed rates on short (Israr Shaheed) and long (Gomal) duration, three experiments were conducted at the agronomic research site of Gomal University, Dera Ismail Khan, Pakistan, wheat varieties. In the first experiment, various priming techniques were used. Among different techniques used Farmyard manure priming produced the tallest plants at 111.3 and 125.3 cm, the maximum number of tillers (335.7 and 345.0 m-2), longest spikes (8.6 and 7.6 cm), maximum spikelets (27.2 and 31.0 spike-1), maximum number of grains (45.5 and 48.7 spike-1), maximum grain yield (4.4 and 4.6 t ha-1) and maximum harvest index (38.7 and 41.5%) respectively for Israr Shaheed and Gomal. Conversely, compost manure produced heavier grains than other interactions (49.2 and 42.3 g) while sodium chloride showed the maximum biological yield (12.4 and 11.8 t ha-1) for Israr Shaheed and Gomal correspondingly. In 2nd experiment, different sowing methods were tested on two wheat varieties Israr Shaheed and Gomal. Dry sowing followed by flooding produced tallest plants measuring (105.5 and 101.7 cm), maximum number of tillers (398.2 and 406.7 m-2), longest spikes (8.3 and 7.2 cm), maximum spikelets (29.8 and 35.5 spike-1), maximum number of grains (54.3 and 51.6 spike-1) and maximum grain yield (4.3 and 4.6 t ha-1) respectively for Israr Shaheed and Gomal. Israr Shaheed and Gomal showed maximum 1000-grain weights (45.3 and 45.0 g) in sprouted seeding in flooded fields respectively. The highest biological yield (13.6 t ha-1) was in dry seed in the flooded field while the maximum harvest index (33.5 and 33.9%) was recorded in soaked seed followed by flooding for Israr Shaheed and Gomal. In the last experiment, different seed rates were studied. The results showed that plants grown with seed rate 150 kg ha-1 showed the tallest plants at 111.0 and 111.7 cm, maximum number of tillers (411.6 and 408.2 m-2), longest spikes (7.8 and 7.7 cm), maximum spikelets (34.3 and 34.3 spike-1), maximum number of grains (50.8 and 47.2 spike-1), maximum grain yield (4.6 and 4.5 t ha-1) and maximum harvest index (38.4 and 36.7%) respectively for Israr Shaheed and Gomal. The maximum number of 1000-grains weight (g) was found on 200 and 250 kg ha-1 for Israr Shaheed and Goma-8, respectively giving 45.2 g while biological yield was the highest in 175 kg ha-1 respectively. Conclusively, the results indicated that yield and yield attributes in wheat were enhanced up to 150 kg ha-1 seed rate when interacted with farmyard manure priming along with dry sowing of seed followed by flooding. Future research should explore the integration of advanced irrigation techniques and nutrient management practices to further enhance wheat productivity in the Dera Ismail Khan region.

Abstract The demand for sustainable development goals and the absence of systematic development and organised exploration for gold has prompted this study to integrate magnetic and radiometric datasets with lithology to evaluate the gold mineralisation potential in the Ilesha schist belt. This study considers 3168.72 km2 of the Ilesha schist belt in southwestern Nigeria, a frontier belt for gold deposits. The high-resolution airborne magnetic and radiometric datasets were processed using enhancement techniques, including the analytical signal, lineament density, and K/Th ratio. CET grid analysis, Euler deconvolution, and analytical signal depth estimation methods were used to aid the interpretation. The spatial integration and interpolation were performed using the Analytical Hierarchy Process (AHP) and weighted overlay analytical tools within the ArcGIS environment. The dominant structural controls for potential mineralisation are ENE–WSW and ESE–WNW trends. The depth of the magnetic sources revealed by the analytical signal ranged from 63.17 to 629.47 m, while depths ranging from 47.32 to 457.22 m were obtained from Euler deconvolution. The delineated highly magnetic edge sources, dense lineaments, radiometrically highlighted alteration zones, and lithological hosts for gold mineralisation were integrated to establish the gold mineralisation potential map. The AHP deductions reveal that 10.52% of the study site is within the high mineralisation potential class, a remarkable 60.39% falls within the moderate class, a significant portion (28.86%) falls within the poor class, and 0.23% is considered unfavourable. The result was optimised by validation using known mines, with 94% (i.e., 15 out of 16 mining sites) plotting within the high mineralisation potential class. This assessment provides invaluable insight for stakeholders and policymakers to embark on gold exploration and exploitation and promote sustainable mineral development.

Abstract Recent studies indicate that Glypican 1 (GPC-1) is aberrantly expressed and plays a key role in certain cancers, but little is known in the hepatocellular carcinoma. Raw data from TCGA, GTEx and TIMER databases were utilized to comprehensively analyze GPC-1 expression landscape in pan-cancer, and the biological function of GPC-1 was investigated in liver cancer cells. The results revealed that GPC-1 is highly expressed in HCC, negatively correlated with survival, and also positively correlated with immune infiltration and clinical stage. Furthermore, GPC-1 promoted cell proliferation and inhibited apoptosis in the HCC cell lines. WGCNA analysis and HCCDB database revealed that Akt acted as a key molecule related to GPC-1, influencing biological functions and regulating cell malignant behaviors via the AKT signaling pathway. In conclusion, our findings provide a relatively comprehensive understanding of the oncogenic role of GPC-1 in HCC, implying that GPC-1 could serve as an innovative therapeutic target.

Abstract Tuberculosis (TB), caused by Mycobacterium tuberculosis, ranks among the top causes of global human mortality, as reported by the World Health Organization’s 2022 TB report. The prevalence of M. tuberculosis strains that are multiple and extensive-drug resistant represents a significant barrier to TB eradication. Fortunately, having many completely sequenced M. tuberculosis genomes available has made it possible to investigate the species pangenome, conduct a pan-phylogenetic investigation, and find potential new drug targets. The 442 complete genome dataset was used to estimate the pangenome of M. tuberculosis. This study involved phylogenomic classification and in-depth analyses. Sequential filters were applied to the conserved core genome containing 2754 proteins. These filters assessed non-human homology, virulence, essentiality, physiochemical properties, and pathway analysis. Through these intensive filtering approaches, promising broad-spectrum therapeutic targets were identified. These targets were docked with FDA-approved compounds readily available on the ZINC database. Selected highly ranked ligands with inhibitory potential include dihydroergotamine and abiraterone acetate. The effectiveness of the ligands has been supported by molecular dynamics simulation of the ligand–protein complexes, instilling optimism that the identified lead compounds may serve as a robust basis for the development of safe and efficient drugs for TB treatment, subject to further lead optimization and subsequent experimental validation.

Abstract The relationship between ammonia and liver-related complications (LRCs) in acute-on-chronic liver failure (ACLF) patients is not clearly established. This study aimed to evaluate the association between ammonia levels and LRCs in patients with ACLF. The study also evaluated the ability of ammonia in predicting mortality and progression of LRCs. The study prospectively recruited ACLF patients based on the APASL definition from the ACLF Research Consortium (AARC) from 2009 to 2019. LRCs were a composite endpoint of bacterial infection, overt hepatic encephalopathy (HE), and ascites. A total of 3871 cases were screened. Of these, 701 ACLF patients were enrolled. Patients with LRCs had significantly higher ammonia levels than those without. Ammonia was significantly higher in patients with overt HE and ascites, but not in those with bacterial infection. Multivariate analysis found that ammonia was associated with LRCs. Additionally, baseline arterial ammonia was an independent predictor of 30-day mortality, but it was not associated with the development of new LRCs within 30 days. In summary, baseline arterial ammonia levels are associated with 30-day mortality and LRCs, mainly overt HE and ascites in ACLF patients.

Abstract The current study involves a synthesis of a composite of nickel oxide nanoparticles (NiONPs) with a chromium dopant to yield (Cr/NiONPs). Synthesis of nickel oxide was performed by the co-precipitation method. The synthesis of the composite was conducted by the impregnation method. FTIR, EDX, SEM, and XRD were used to characterize the synthesized materials. The synthesised materials’ point zero charges (PZC) were performed using the potentiometric titration method. The obtained results show that the PZC for neat nickel oxide was around 5, and it was around 8 for Cr/NiONPs. The adsorption action of the prepared materials was examined by applying them to remove Reactive Red 2 (RR2) and Crystal Violate (CV) dyes from solutions. The outcomes demonstrated that Cr/NiONPs were stronger in the removal of dyes than NiONPs. Cr/NiONPs achieved 99.9% removal of dyes after 1 h. Adsorption isotherms involving Freundlich and Langmuir adsorption isotherms were also conducted, and the outcomes indicated that the most accurate representation of the adsorption data was offered by Langmuir adsorption isotherms. Additionally, it was discovered that the adsorption characteristics of the NiONPs and Cr/NiONPs correspond well with the pseudo-second-order kinetic model. Each of the NiONPs and Cr/NiONPs was reused five times, and the results display that the effectiveness of the removal of RR2 dye slightly declined with the increase in reuse cycles; it lost only 5% of its original efficiency after the 5 cycles. Generally, Cr/NiONPs showed better reusability than NiONPs under the same conditions.

Abstract Patients receiving Medicaid often experience social risk factors for poor health and limited access to primary care, leading to high utilization of emergency departments and hospitals (acute care) for non-emergent conditions. As programs proactively outreach Medicaid patients to offer primary care, they rely on risk models historically limited by poor-quality data. Following initiatives to improve data quality and collect data on social risk, we tested alternative widely-debated strategies to improve Medicaid risk models. Among a sample of 10 million patients receiving Medicaid from 26 states and Washington DC, the best-performing model tripled the probability of prospectively identifying at-risk patients versus a standard model (sensitivity 11.3% [95% CI 10.5, 12.1%] vs 3.4% [95% CI 3.0, 4.0%]), without increasing “false positives” that reduce efficiency of outreach (specificity 99.8% [95% CI 99.6, 99.9%] vs 99.5% [95% CI 99.4, 99.7%]), and with a ~ tenfold improved coefficient of determination when predicting costs (R2: 0.195–0.412 among population subgroups vs 0.022–0.050). Our best-performing model also reversed the lower sensitivity of risk prediction for Black versus White patients, a bias present in the standard cost-based model. Our results demonstrate a modeling approach to substantially improve risk prediction performance and equity for patients receiving Medicaid.

Abstract Cryptosporidium is one of the most important protozoan parasitic pathogens, and it is a common cause of diarrhoea in humans, domestic animals, and wild vertebrates and has serious public health threats. A cross-sectional study was designed to determine the prevalence of Cryptosporidium oocysts in raw-eaten vegetables in Maiduguri Metropolitan Council (MMC) and Jere Local Government Areas (LGAs). A total of 400 samples were collected from four (4) different locations, namely Tashan Bama, Gomboru, and Monday Markets (n = 100), while fifty (n = 50) each from 202-Vegetable-Vendors and Unimaid Commercials. A total of 16 visits were conducted in all the sampling areas (twenty-five samples per visit). The Cryptosporidium oocysts were detected using the Modified Ziehl–Neelsen Staining Technique. The locations, sources, and types of raw-eaten vegetables were also assessed. The oocysts were confirmed (100×) as bright pink spherules. Data generated were analyzed using IBM-SPSS V23.0, and p ≤ 0.05 was considered significant. Out of the total samples (n = 400) analyzed, cabbage appeared to have the highest number of 10 (12.5%) of Cryptosporidium oocysts detected, while Tomato and garden egg had 9 (11.3%) and 1 (1.2%), respectively. There was a statistically significant association (χ2 = 12.5, P = 0.014) between the presence of Cryptosporidium oocysts in raw-eaten vegetables and vegetable types. Among the sources of the vegetables sampled, Alau had the highest number of Cryptosporidium oocysts, 15 (12.5%), followed by Kilari-Abdullahi and Zabarmari sources with 4 (10.0%) and 4 (5.0%), respectively. However, Jetete appeared to have the least number 2 (2.5%) of oocysts, and there was a statistically significant association (χ2= 10.4, P = 0.034) between the presence of Cryptosporidium oocysts and the sources of vegetables and fruits. The study concludes that the raw-eaten vegetables sampled from Maiduguri Metropolis were contaminated with Cryptosporidium oocysts. The study recommends that all raw-eaten vegetables should be from cleaned sources and washed before consumption. Consumers should be enlightened on the hygienic measures in the food chain in line with the Hazard Analysis and Critical Control Points (HACCP) principles.

Abstract Glycolate oxidase (GLO) is an FMN-containing enzyme localized in peroxisomes and performs in various molecular and biochemical mechanisms. It is a key player in plant glycolate and glyoxylate accumulation pathways. The role of GLO in disease and stress resistance is well-documented in various plant species. Although studies have been conducted regarding the role of GLO genes from spinach on a microbial level, the direct response of GLO genes to various stresses in short-season and leafy plants like lettuce has not been published yet. The genome of Lactuca sativa cultivar ‘Salinas’ (v8) was used to identify GLO gene members in lettuce by performing various computational analysis. Dual synteny, protein–protein interactions, and targeted miRNA analyses were conducted to understand the function of GLO genes. The identified GLO genes showed further clustering into two groups i.e., glycolate oxidase (GOX) and hydroxyacid oxidase (HAOX). Genes were observed to be distributed unevenly on three chromosomes, and syntenic analysis revealed that segmental duplication was prevalent. Thus, it might be the main reason for GLO gene diversity in lettuce. Almost all LsGLO genes showed syntenic blocks in respective plant genomes under study. Protein–protein interactions of LsGLO genes revealed various functional enrichments, mainly photorespiration, and lactate oxidation, and among biological processes oxidative photosynthetic carbon pathway was highly significant. Results of in-depth analyses disclosed the interaction of GLO genes with other members of the glycolate pathway and the activity of GLO genes in various organs and developmental stages in lettuce. The extensive genome evaluation of GLO gene family in garden lettuce is believed to be a reference for cloning and studying functional analyses of GLO genes and characterizing other members of glycolate/glyoxylate biosynthesis pathway in various plant species.

Abstract The increase in global energy consumption and the related ecological problems have generated a constant demand for alternative energy sources superior to traditional ones. This is why unlimited photon-energy harnessing is important. A notable focus to address this concern is on advancing and producing cost-effective low-loss solar cells. For efficient light energy capture and conversion, we fabricated a ZnPC:PC70BM-based dye-sensitized solar cell (DSSC) and estimated its performance using a solar cell capacitance simulator (SCAPS-1D). We evaluated the output parameters of the ZnPC:PC70BM-based DSSC with different photoactive layer thicknesses, series and shunt resistances, and back-metal work function. Our analyses show that moderate thickness, minimum series resistance, high shunt resistance, and high metal-work function are favorable for better device performance due to low recombination losses, electrical losses, and better transport of charge carriers. In addition, in-depth research for clarifying the impact of factors, such as thickness variation, defect density, and doping density of charge transport layers, has been conducted. The best efficiency value found was 10.30% after tweaking the parameters. It also provides a realistic strategy for efficiently utilizing DSSC cells by altering features that are highly dependent on DSSC performance and output.

Abstract Vitis vinifera L., commonly known as grape is a major fruit crop in the world. Grapes seem to confer health benefits due to their chemical components, biological and antioxidant activities. The present study is conducted to evaluate the biochemical constituents, antioxidant, and antimicrobial potential of ethanolic grape peduncles (EGP) extract. The result of phytochemical analysis revealed the presence of various phytochemicals such as flavonoid, tannin, carbohydrates, alkaloids, cardiac glycoside, phenol, steroid, terpenoids, quinones and anthraquinones. Furthermore, total phenolic content (TPC) and total flavonoid contents (TFC) were 7.35 ± 0.25 mg GAE/g (Gallic Acid Equivalent per gram) and 29.67 ± 0.13 mg QE/g (Quercetin Equivalent per gram) respectively. DPPH (2, 2-diphenyl-1-picrylhydrazyl) free radical scavenging assay revealed IC50 = 159.3 μg/mL. The antibacterial and antifungal study disclosed that the extract was highly potent against Salmonella typhi with maximum zone of inhibition of 27.2 ± 1.60 mm and Epidermophyton floccosum with 74 ± 1.81% inhibition. The extract was analyzed for its cytotoxicity and antileishmanial activity and showed no activity against HeLa cell line and promastigotes of Leishmania major. Elements Fe, Mn, Ni, Pb and Cd were determined by atomic absorption spectroscopy and approximately 50 compounds were identified by Gas Chromatography-Mass Spectrometry (GC–MS). Current work suggest that grape peduncles can be a promising source of bioactive medicinal component.

Abstract The hormetic effect may cause disease control measures to fail due to inadequate treatment of human disease vectors such as houseflies. Age-stage, two-sex life table is used for accurate estimation of the hermetic impacts on insects as it allows to study sub-lethal or transgenerational effects. Pyrethroids insecticides are primarily used for the management of houseflies. This study used lambda-cyhalothrin (a pyrethroid insecticide) to quantify its transgenerational impacts on houseflies. Life table parameters of a progeny of adult houseflies exposed to LC10, LC30, and LC50 of lambda-cyhalothrin were computed. Statistically higher fecundity (71.31 per female) was observed in control treatment, while it was the adults exposed to LC50 recorded the lowest progeny. Significantly higher values for intrinsic rate of growth (r), limiting rate of growth (λ), and net reproductive rate (R o ) (0.16, 1.16, and 31.38 per day, respectively) were recorded for the control treatment of the study. Contrarily, lower values for λ, R o, and r were (0.10, 1.10, and 9.24 per day, respectively) were noted in the LC50 treatment. Decreased population parameters suggest that lambda-cyhalothrin can be successfully used in indoor environments to control houseflies.

Abstract Climate change, pesticide resistance, and the need for developing new plant varieties have galvanized biotechnologists to find new solutions in order to produce transgenic plants. Over the last decade scientists are working on green metallic nanoparticles to develop DNA delivery systems for plants. In the current study, green Iron nanoparticles were synthesized using leaf extract of Camellia sinensis (green tea) and Iron Chloride (FeCl3), the characterization and Confirmation was done using UV–VIS Spectroscopy, FTIR, SEM, and TEM. Using these nanoparticles, a novel method of gene transformation in okra plants was developed, with a combination of different Magnetofection factors. Maximum gene transformation efficiency was observed at the DNA to Iron-nanoparticles ratio of 1:20, by rotation of mixture (Plasmid DNA, Iron-nanoparticles, and seed embryo) at 800 rpm for 5 h. Using this approach, the transformation of the GFP (green fluorescent protein) gene was successfully carried out in Abelmoschus esculentus (Okra plant). The DNA transformation was confirmed by observing the expression of transgene GFP via Laser Scanning Confocal Microscope (LSCM) and PCR. This method is highly economical, adaptable, genotype independent, eco-friendly, and time-saving as well. We infer that this approach can be a potential solution to combat the yield and immunity challenges of plants against pathogens.

Abstract Coronary artery disease (CAD) is a prevalent disease with high morbidity and mortality rates. Invasive coronary angiography is the reference standard for diagnosing CAD but is costly and associated with risks. Noninvasive imaging like cardiac magnetic resonance (CMR) facilitates CAD assessment and can serve as a gatekeeper to downstream invasive testing. Machine learning methods are increasingly applied for automated interpretation of imaging and other clinical results for medical diagnosis. In this study, we proposed a novel CAD detection method based on CMR images by utilizing the feature extraction ability of deep neural networks and combining the features with the aid of a random forest for the very first time. It is necessary to convert image data to numeric features so that they can be used in the nodes of the decision trees. To this end, the predictions of multiple stand-alone convolutional neural networks (CNNs) were considered as input features for the decision trees. The capability of CNNs in representing image data renders our method a generic classification approach applicable to any image dataset. We named our method RF-CNN-F, which stands for Random Forest with CNN Features. We conducted experiments on a large CMR dataset that we have collected and made publicly accessible. Our method achieved excellent accuracy (99.18%) using Adam optimizer compared to a stand-alone CNN trained using fivefold cross validation (93.92%) tested on the same dataset.

Abstract As one of the important greenhouse gas, nitrous oxide (N2O) has attracted much attention globally under climate change context. Agricultural practices are the main sources of greenhouse gas emissions. Nevertheless, scarcity of literature is available on the effects of different tillage measures on soil N2O emission under spring wheat (Triticum aestivum L.) ecosystem in the semi-arid area of the Loess Plateau. The main objective of the experimental study was to explore the influence of conservation tillage techniques on soil physicochemical properties, nitrous oxide emission and yield in the Northern semi-arid Dingxi region of China. Four treatments viz., conventional tillage (CT), no tillage (NT), straw mulch with conventional tillage (TS) and stubble-return with no-till (NTS) were evaluated under randomized complete block design with three replications. Our results depicted that compared with conventional tillage, bulk density and water content of topsoil was increased and soil pH value was reduced under conservation tillage techniques. Conservation tillage NT, TS and NTS increased organic carbon, TN, MBN and NH4 +-N and reduced the accumulation of NO3 –N. Additionally, although the N2O emission under NT, TS and NTS was 8.95, 41.90 and 21.05% respectively higher than under T treatment, the corresponding wheat yield was 15.40, 31.97 and 63.21% higher than T treatment. Moreover, correlation analysis showed that soil moisture and temperature were the most significant factors affecting soil N2O emission. The NTS treatment pointedly increased crop yield without significantly increasing soil N2O emission. Consequently, based on economic and environmental benefits and considering N2O emission and crop yield, we suggest that NTS technique is the best conservation tillage strategy in the semi-arid environmental zone of the Loess Plateau of Dingxi China.

Abstract This study presents a simple, miniaturized, and low-profile multiple-input multiple-output (MIMO) antenna operating at 29 GHz with reduced mutual coupling between the antenna elements for futuristic 5G communication. The proposed design employs two radiating elements with slits in the radiators to produce high isolation among the antenna radiators. The MIMO antenna maintains a compact structure of 11.4 × 5.3 mm2, which is the smallest size compared to previous 5G antennas. Roger’s 4350B laminate was employed as a substrate material. At 29 GHz, low mutual coupling of − 36 dB, low envelope correlation coefficient (ECC 9.8 dB) are achieved. The proposed design is examined in terms of the S-parameters, diversity gain, radiation pattern, and envelope correlation. Compared to the straight antenna element, an improvement of − 20 dB is observed in the isolation for both the simulated and measured results.

Abstract This work investigated reasons and factors that cause the failure due to mechanical wear (Erosion) for the inside surface of elbows and pipes used in cement transportation which manufactures from low carbon steel and finds out a method for reducing this failure. The technique of Nano-coating layers is used to coat the surface of samples with layers of nanoparticles of tungsten carbides of different thicknesses of (30, 40, and 50 μm). The test was done for these samples by placing them inside the elbow under the same operating conditions, pin on disc test. The results of the test under the same operation condition showed a decrease in erosion rate by 71% for the sample coated with 50 μm of layer, while the results of the pin on disc test showed a decrease in erosion rate by 97% for the thickness of 50 μm as this test is done under ideal testing conditions. The decrease in wear rate for elbow and pipes will increase their life work two times at least and that reduces the cost of maintenance by about 75%. The numerical simulation was also implemented to simulate the erosion profile inside the elbow, and the agreement with experimental results was 90%.

Abstract Several polymers like ethylene glycol exhibit non-Newtonian rheological behavior. Ethylene glycol is a world-widely used engine coolant and therefore, investigation of thermal enhancement by dispersing mono and hybrid nanoparticles in ethylene glycol is worthful. Since ethylene glycol has shear rate-dependent viscosity and it obeys the power-law rheological model. Therefore, based on these facts, the power-law rheological model with thermophysical properties is augmented with basic law of heat transfer in fluid for the modeling of the considered physical situation. $$Mo{S}_{2}$$ M o S 2 are taken as mono-nanoparticles where $$Mo{S}_{2}$$ M o S 2 and $$Si{O}_{2}$$ S i O 2 are taken as hybrid nanoparticles. Comparative study for the enhancement of thermal performance of MoS2 ethylene glycol and $$Mo{S}_{2}$$ M o S 2 − $$Si{O}_{2}$$ S i O 2 – ethylene glycol is done. For energy conservation, non-Fourier’s law of Cattaneo–Christov is used. The power-law fluid becomes more heat generative due to the dispersion of $$Mo{S}_{2}$$ M o S 2 and $$Si{O}_{2}$$ S i O 2 . However, $$Mo{S}_{2}$$ M o S 2 −power-law fluid is less heat generative relative to $$Mo{S}_{2}$$ M o S 2 − $$Si{O}_{2}$$ S i O 2 -nanofluid. Thermal relaxation time is found proportional to the ability of the fluid to restore its thermal equilibrium.

Abstract Epidemiological studies have shown that head and neck cancer (HNC) is a complex multistage process that in part involves exposure to a combination of carcinogens and the capacity of certain drug-metabolising enzymes including cytochrome P450 (CYP) to detoxify or activate such carcinogens. In this study, CYP1A1, CYP1B1 and CYP2W1 expression in HNC was correlated with potential as target for duocarmycin prodrug activation and selective therapy. In the HNC cell lines, elevated expression was shown at the gene level for CYP1A1 and CYP1B1 whereas CYP2W1 was hardly detected. However, CYP2W1 was expressed in FaDu and Detroit-562 xenografts and in a cohort of human HNC samples. Functional activity was measured in Fadu and Detroit-562 cells using P450-Glo™ assay. Antiproliferative results of duocarmycin prodrugs ICT2700 and ICT2706 revealed FaDu and Detroit-562 as the most sensitive HNC cell lines. Administration of ICT2700 in vivo using a single dose of ICT2700 (150 mg/kg) showed preferential inhibition of small tumour growth (mean size of 60 mm3) in mice bearing FaDu xenografts. Significantly, our findings suggest a potential targeted therapeutic approach to manage HNCs by exploiting intratumoural CYP expression for metabolic activation of duocarmycin-based prodrugs such as ICT2700.

Abstract COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus is highly desired. Convolutional neural networks (CNNs) have shown outstanding classification performance on image datasets. To date, it appears that COVID computer-aided diagnosis systems based on CNNs and clinical information have not yet been analysed or explored. We propose a novel method, named the CNN-AE, to predict the survival chance of COVID-19 patients using a CNN trained with clinical information. Notably, the required resources to prepare CT images are expensive and limited compared to those required to collect clinical data, such as blood pressure, liver disease, etc. We evaluated our method using a publicly available clinical dataset that we collected. The dataset properties were carefully analysed to extract important features and compute the correlations of features. A data augmentation procedure based on autoencoders (AEs) was proposed to balance the dataset. The experimental results revealed that the average accuracy of the CNN-AE (96.05%) was higher than that of the CNN (92.49%). To demonstrate the generality of our augmentation method, we trained some existing mortality risk prediction methods on our dataset (with and without data augmentation) and compared their performances. We also evaluated our method using another dataset for further generality verification. To show that clinical data can be used for COVID-19 survival chance prediction, the CNN-AE was compared with multiple pre-trained deep models that were tuned based on CT images.

Abstract In a recent revision of the genus Agaricus, A. section Xanthodermatei was split into two sections A. sect. Hondenses and A. sect. Xanthodermatei. Our objectives were to investigate the species diversity of both sections in Pakistan and to give an overview of the major clades. Phylogenetic analyses based on the combined nucLSU, ITS and TEF1 dataset from 35 specimens of both sections revealed three major clades. Analyses based on ITS dataset and 106 specimens, including 33 from Pakistan, reveal eight new species and one new record species. These nine species are described in detail. It is noteworthy that intraspecific variability as well as interspecific variability between closely related species were very low in ITS sequences in many cases. In the case of the two new species A. xanthochromaticus and A. griseovariegatus, TEF1 sequence data were much more efficient than ITS to distinguish these species from each other. The other new species are A. atroumbonatus, A. fumidicolor, A. macropeplus, A. parviniveus, A. swaticus and A. bambusetorum. The latter is the only new species of A. sect. Hondenses in which it is morphologically atypical and also the unique (sub)tropical species. Agaricus gregariomyces is recorded for the first time in Pakistan. In addition, brief descriptions are provided not only for A. bisporiticus, A. endoxanthus and A. punjabensis, which are reported again in Pakistan, but also for A. californicus, which is reported for the first time in Spain and outside North America. In total 12 species of both sections were reported in Pakistan and half of them were from subtropical climatic areas, underlining the contribution of the climatic diversity to the high species richness in this country.

Abstract Flood early warning systems (FLEWSs) contribute remarkably to reducing economic and life losses during a flood. The theory of critical slowing down (CSD) has been successfully used as a generic indicator of early warning signals in various fields. A new tool called persistent homology (PH) was recently introduced for data analysis. PH employs a qualitative approach to assess a data set and provide new information on the topological features of the data set. In the present paper, we propose the use of PH as a preprocessing step to achieve a FLEWS through CSD. We test our proposal on water level data of the Kelantan River, which tends to flood nearly every year. The results suggest that the new information obtained by PH exhibits CSD and, therefore, can be used as a signal for a FLEWS. Further analysis of the signal, we manage to establish an early warning signal for ten of the twelve flood events recorded in the river; the two other events are detected on the first day of the flood. Finally, we compare our results with those of a FLEWS constructed directly from water level data and find that FLEWS via PH creates fewer false alarms than the conventional technique.