Up-gradation of the dielectric, physical & chemical properties of cottonseed-based, non-edible green nanofluids as sustainable alternatives for high-voltage equipment's insulation fluids.

The use of natural ester oils as electrically insulating fluids has gained significant attention from industries and electrical utilities as they aim to replace traditional mineral oils. However, most natural ester oils are derived from edible products, which has the potential to contribute to the food crisis. Therefore, nonedible green nanofluids made from cottonseed oil (CSO) have been targeted as a keen solution to this issue. However, Al2O3, TiO2, Fe2O3, SiO2, and graphene nanoparticles at (0.025, 0.05, and 0.075 wt/vol%) were used as additives, along with surfactant Olic Ac-id and Ethanol (1:5) due to their promising impact on the dielectric and thermal properties of the nanofluid. The nanofluid synthesis process was practically conducted in HV & Chemical Laboratories using one-step and two-step methods, and their breakdown voltage results and chemical properties (e.g., fire point, flash point, cloud point, pour point, viscosity, acidity, moisture content, resistivity, and dissipation factor) were compared. The physical mechanisms underlying these properties were also analyzed and tested. For the validation of the proposed vegetable oil the results have been compared with traditional mineral oil for high-voltage equipment's. The findings suggest that the proposed nonedible green nanofluids-based cottonseed oil (CSO) has a high potential to be used as electrically insulating fluids, providing a sustainable alternative to conventional mineral oils. Overall, this study provides insights into the use of non-edible green nanofluids as a solution to the potential contribution of natural ester oils to the food crisis. The findings highlight the importance of sustainable solutions in the energy industry and the need for further research in this area.

Development of a robust method for Cd(II) ions analysis using CeO2- and CeO2-Cu-BTC-based electrochemical sensors.

Simple and sensitive electrochemical sensors were fabricated from cerium oxide (CeO2) and copper-benzene tricarboxylic acid-modified cerium oxide (CeO2-Cu-BTC) materials for differential pulse voltammetric analysis of toxic cadmium (Cd) ions in aqueous solutions. The materials were prepared by hydrothermal method and structurally characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy with energy-dispersive X-ray (SEM-EDX), thermogravimetric analysis (TGA), and X-ray diffraction analysis (XRD). The CeO2-modified carbon paste electrode (CeCPE) and the CeO2-Cu-BTC-modified carbon paste electrode (CeBCPE) were electrochemically characterized by their cyclic voltammetry and electrochemical impedance study in standard K3[Fe(CN)6] single-electron redox process. Their electrochemical surface areas, electrode surface coverages, and charge transfer resistances were calculated to be 1.46 cm2, 2.338 × 10-5 mol∙cm-2, and 2790 Ω and 5.48 cm2, 2.476 × 10-5 mol∙cm-2, and 1254.65 Ω for CeCPE and CeBCPE, respectively. These fabricated electrodes were used as electrochemical sensors for cadmium ion estimation by optimizing the experimental parameters through differential pulse voltammetry. The optimized conditions included 10% modifier for CeCPE and 5% modifier for CeBCPE in 0.12 M HCl solution of pH 5 as supporting electrolyte at - 1.2 V deposition for 30 s in 0.01 to 10 mg L-1 linear cadmium solution range. Under these conditions, the limit of quantification (LOQ) of 0.368 mg L-1 and 0.005 mg L-1 was calculated for CeCPE and CeBCPE electrodes, respectively. The limit of detection (LOD) was calculated to be 0.121 mg L-1 and 0.002 mg L-1 for CeCPE and CeBCPE, respectively. All the experimental results indicated that electrodes fabricated from CeO2-Cu-BTC show better performance as compared to CeO2-based electrodes. Both these types of electrochemical sensors presented good repeatability and performance in the presence of interfering ions as well. From these findings, it can also be inferred that these electrochemical sensors can provide a simple and very sensitive method for approximation of toxic cadmium ions in aqueous solutions.

Disparities with global standards about growth references of mid-upper arm circumference-for-age for Pakistani children aged 6-60 months.

AIM: Growth reference values about mid-upper arm circumference (MUAC) are vital for assessing children's nutritional status. However, Pakistan lacks these reference values and growth charts. This study aims to develop these for children aged 6-60 months and compare them with global standards. METHODS: The data were acquired from the 2018 National Nutrition Survey of Pakistan, which was conducted by the United Nations Children's Fund (UNICEF) during 2018-2019. The final study cohort comprised 57 285 children, with 51% being boys. Percentile values and charts for MUAC-for-age were developed using generalised additive models for location, scale and shape with the Box-Cox power exponential distribution. RESULTS: The mean MUAC was 14.21 cm (±2.07 cm) and 14.13 cm (±2.12 cm) for the boys and girls, respectively. At 60 months of age, the P3 and P97 percentiles for girls were slightly higher than those for boys. The median percentiles of Pakistani children were smaller than the World Health Organisation 2007 standards and with international references. CONCLUSION: We observed disparities in MUAC-for-age growth references among Pakistani children compared to global standards, highlighting regional, age and gender variations. This underscores the need for developing countries like Pakistan to establish their growth references.

Unlock flow-type reversible aqueous Zn-CO2 batteries.

Metal-CO2 batteries, which use CO2 as the active species at cathodes, are particularly promising, but device design for mass-producible CO2 reduction and energetic power supply lag behind, limiting their potential benefits. In this study, an aqueous reversible flow-type Zn-CO2 battery using a Pd/SnO2@C cathode catalyst has been assembled and demonstrates an ultra-high discharge voltage of 1.38 V, a peak power density of 4.29 mW cm-2, high-energy efficiency of 95.64% and remarkable theoretical energy density (827.3 W h kg-1). In the meantime, this optimized system achieves a high formate faradaic efficiency of 95.86% during the discharge process at a high rate of 4.0 mA cm-2. This energy- and chemical-conversion technology could store and provide electricity, eliminate CO2 and produce valuable chemicals, addressing current energy and environment issues simultaneously.

Assessment of heavy metals level in chicken with indeterminate analysis in localities of Lahore, Pakistan.

The poultry industry is a significant source of animal protein, vitamins, and minerals, particularly through the consumption of chicken meat. In order to conduct the study, 100 samples of liver, chicken feed, and drinking water were collected in nearby areas of Lahore. The investigation aims to detect the presence of specific heavy metals in the collected samples. For this purpose, atomic absorption spectroscopy (AAS) was used to detect heavy metals after proper preparation of the samples. The experimentally observed data were analyzed through a novel statistical approach known as neutrosophic statistics. It was observed that copper (Cu), zinc (Zn), and cadmium (Cd) were the most prominent metals detected with contamination above the safe limits (for chicken drinking water (Zn = 23.09±13.67 mg/L, Cu = 3.84±3.04 mg/L, Cd = 0.805±0.645 mg/L, Pb = 0.275±0.095 mg/L, As = 0.982±0.978 mg/L), for chicken feed (Zn = 2.705±0.715 mg/kg, Cu = 1.85±0.53 mg/kg, Cd = 3.065±1.185 mg/kg, Pb = 0.215±0.175 mg/kg, As = 0.68±0.22 mg/kg), and chicken's liver (Zn = 3.93±0.66 mg/kg, Cu = 1.2±0.52 mg/kg, Cd = 0.07±0.05 mg/kg, Pb = 0.805±0.775 mg/kg, As = 1.05±0.8 mg/kg)). Similarly, the statistical analysis leads that the findings emphasize the importance of monitoring and mitigating heavy metal contamination in the poultry industry to ensure the safety and quality of poultry products.

Zinc oxide nanoparticles and Klebsiella sp. SBP-8 alleviates chromium toxicity in Brassica juncea by regulation of antioxidant capacity, osmolyte production, nutritional content and reduction in chromium adsorption.

Heavy metals are one of the most damaging environmental toxins that hamper growth of plants. These noxious chemicals include lead (Pb), arsenic (As), nickel (Ni), cadmium (Cd) and chromium (Cr). Chromium is one of the toxic metal which induces various oxidative processes in plants. The emerging role of nanoparticles as pesticides, fertilizers and growth regulators have attracted the attention of various scientists. Current study was conducted to explore the potential of zinc oxide nanoparticles (ZnONPs) alone and in combination with plant growth promoting rhizobacteria (PGPR) Klebsiella sp. SBP-8 in Cr stress alleviation in Brassica juncea (L.). Chromium stress reduced shoot fresh weight (40%), root fresh weight (28%), shoot dry weight (28%) and root dry weight (34%) in B. juncea seedlings. Chromium stressed B. juncea plants showed enhanced levels of malondialdehyde (MDA), electrolyte leakage (EL), hydrogen peroxide (H2O2) and superoxide ion (O2• -). However, co-supplementation of ZnONPs and Klebsiella sp. SBP-8 escalated the activity of antioxidant enzymes i.e., superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX) in B. juncea grown in normal and Cr-toxic soil. It is further proposed that combined treatment of ZnONPs and Klebsiella sp. SBP-8 may be useful for alleviation of other abiotic stresses in plants.

Midurethral Sling with Concomitant Sacrocolpopexy: Does the Sequence Matter? A Retrospective Cohort Study.

The objective is to determine if the timing of midurethral sling (MUS) placement has an impact on the recurrence rate of stress urinary incontinence (SUI). We conducted a retrospective cohort study of patients that underwent robot sacrocolpopexy (RSC) with MUS placement at a large community hospital. Our data demonstrated that there was no significant difference in SUI recurrence when the MUS was placed before or after the RSC (15% vs. 11%, P = 0.41, respectively). We concluded that physician preference may dictate surgical approach to sequence of retropubic MUS placement at the time of RSC.

Role of telerehabilitation in the rehabilitation of children with cerebral palsy during COVID-19: A review.

Individuals with cerebral palsy (CP) have limited mobility and are unable to actively participate in tasks that are part of their daily living. Thus, continuous therapeutic sessions are required to keep such individuals active and engaged in the environment. Due to the coronavirus disease of 2019 (COVID-19) lockdowns, rehabilitation for children with CP was inhibited which consequently put them at risk of losing their functional gains which were obtained through previous in-person therapies. In order to avoid this, an alternate to conventional therapy was required and this rendered it necessary to review the role of telerehabilitation (TR) and its various modes for the rehabilitation of children with CP. This study aimed to explore the effectiveness of TR for children with CP during COVID-19 through the present literature and to determine if TR is an alternate to conventional physical therapy in children with CP during the coronavirus outbreak. This scoping review was conducted by searching different databases such as PubMed, Cochrane Collaboration, Medline, and Google Scholar on the basis of inclusion criteria. Screening was performed from January 2019 to June 2022 and the initial screening attempt returned 469 studies. After applying the aforementioned criteria, all impertinent studies were excluded which resulted in 28 studies being included for this review as they contained information about the effectiveness of TR on children with CP during COVID-19. These 28 articles included randomised controlled trials, surveys, reviews, clinical trials, case reports, prospective studies, editorials, and longitudinal studies. Three out of the 7 randomised controlled trial studies revealed that action observation treatment can be a useful approach for TR in child with CP during similar pandemics. The other 3 studies supported the use of computer-based games, robots, nonimmersive virtual reality, and wearable haptic devices as a significant means of TR in child with CP as an alternate to routine therapy during COVID-19. TR is an affable mode of rehabilitation specifically for the pediatric population. In the future, it can be an alternate to routine therapy for those who are unlikely to get daily access to in-person therapeutic sessions due to various reasons or circumstances.

Multi-Layer Palladium Diselenide as a Contact Material for Two-Dimensional Tungsten Diselenide Field-Effect Transistors.

Tungsten diselenide (WSe2) has emerged as a promising ambipolar semiconductor material for field-effect transistors (FETs) due to its unique electronic properties, including a sizeable band gap, high carrier mobility, and remarkable on-off ratio. However, engineering the contacts to WSe2 remains an issue, and high contact barriers prevent the utilization of the full performance in electronic applications. Furthermore, it could be possible to tune the contacts to WSe2 for effective electron or hole injection and consequently pin the threshold voltage to either conduction or valence band. This would be the way to achieve complementary metal-oxide-semiconductor devices without doping of the channel material.This study investigates the behaviour of two-dimensional WSe2 field-effect transistors with multi-layer palladium diselenide (PdSe2) as a contact material. We demonstrate that PdSe2 contacts favour hole injection while preserving the ambipolar nature of the channel material. This consequently yields high-performance p-type WSe2 devices with PdSe2 van der Waals contacts. Further, we explore the tunability of the contact interface by selective laser alteration of the WSe2 under the contacts, enabling pinning of the threshold voltage to the valence band of WSe2, yielding pure p-type operation of the devices.

Inoculation of heavy metal resistant bacteria alleviated heavy metal-induced oxidative stress biomarkers in spinach (Spinacia oleracea L.).

Most vegetable crops are severely affected by the uptake of heavy metals from the soil. Heavy metals in vegetable bodies generate reactive oxygen species (ROS) that unbalance the antioxidant defense system. This study was initiated to determine the physiological and biochemical characteristics of spinach plants grown on soil contaminated with heavy metals and responding to Bacillus cereus and Bacillus aerius were isolated from soil contaminated with heavy metals. Heavy metal contamination led to a significant reduction in seed germination, seedling biomass, protein, and total nitrogen content of spinach plants grown in contaminated soils compared to control soils. In contrast, a significant increase in the content of metallothioneins and antioxidant enzymes was observed. Plants inoculated with B. cereus and B. aerius significantly reduced the oxidative stress induced by heavy metals by improving seed germination (%), seedling growth, nitrogen, and protein content. The content of metallothioneins and the activities of antioxidant enzymes were reduced in spinach plants grown from seeds inoculated with bacterial strains. In addition, plants inoculated with, B. cereus and B. aerius showed greater stomata opening than plants grown on soil contaminated with heavy metals, whose stomata were almost closed. These results suggested that both bacterial strains enhanced plant growth by reducing oxidative stress caused by metals.

Phytochemical screening, antioxidant, immunomodulatory and analgesic potential of aqueous-ethanolic extracts of Euphorbia prostrata ait. and Crotalaria burhia Buch-Ham.

Euphorbia prostrata (E. prostrata) and Crotalaria burhia (C. burhia) are widely found in flora of the Cholistan Desert of Bahawalpur, Pakistan and are traditionally used to treat pain and chronic disease. The current study aimed to evaluate their phytochemical screening, antioxidant activity, in-vivo phagocytic activity, and analgesic activity. Both the plant extracts were investigated for phytochemical screening, Fourier Transform Infrared (FTIR) analysis, in-vitro antioxidant by 2, 2-diphenyl-1-picrylhydrazyl (DPPH) method, in-vivo immunomodulatory activity by macrophages phagocytosis using carbon clearance rate assay and analgesic activity by acetic acid produced writhing method. Phytochemical screening showed the presence of carbohydrates, saponins, tannins, phenols, quinines, proteins, terpenes, glycosides, and alkaloids. FTIR analysis revealed the existence of different functional groups in both extracts. The DPPH method showed that E. prostrata exhibited a high antioxidant potential with an IC50 of 62.5 µg/ml whereas C. burhia showed a lower antioxidant potential. At the dose of 200 mg/kg body weight (b. wt), both the extracts showed a significant increase in the phagocytic index by 5.2 ± 0.2, and, 4.8 ± 0.1 (p < 0.001) respectively which was close to the 100 mg/kg b. wt of the standard drug (Levamisole) 5.4 ± 0.2. Both the extracts at the dose of 200 mg/kg b. wt also significantly reduced the writhing (abdominal contractions) count by 13.7 ± 0.3 and, 25.3 ± 1.5 (p < 0.001), showing 71.8% and 47.6% of reduced analgesic activity compared to the standard drug dicloran (diclofenac sodium), respectively. In conclusion, extracts of both plants indicate their role in the management of various disorders to relieve pain and modulate the immune system.

Neuro-computing solution for Lorenz differential equations through artificial neural networks integrated with PSO-NNA hybrid meta-heuristic algorithms: a comparative study.

In this article, examine the performance of a physics informed neural networks (PINN) intelligent approach for predicting the solution of non-linear Lorenz differential equations. The main focus resides in the realm of leveraging unsupervised machine learning for the prediction of the Lorenz differential equation associated particle swarm optimization (PSO) hybridization with the neural networks algorithm (NNA) as ANN-PSO-NNA. In particular embark on a comprehensive comparative analysis employing the Lorenz differential equation for proposed approach as test case. The nonlinear Lorenz differential equations stand as a quintessential chaotic system, widely utilized in scientific investigations and behavior of dynamics system. The validation of physics informed neural network (PINN) methodology expands to via multiple independent runs, allowing evaluating the performance of the proposed ANN-PSO-NNA algorithms. Additionally, explore into a comprehensive statistical analysis inclusive metrics including minimum (min), maximum (max), average, standard deviation (S.D) values, and mean squared error (MSE). This evaluation provides found observation into the adeptness of proposed AN-PSO-NNA hybridization approach across multiple runs, ultimately improving the understanding of its utility and efficiency.

Life truncated multiple dependent state plan for imprecise Weibull distributed data.

This paper aims to provide a multiple dependent state (MDS) sampling technique for light-emitting diode luminous intensities under indeterminacy by employing time truncated sampling schemes and the Weibull distribution. This indicates that ASN is significantly impacted by the indeterminacy parameter. Furthermore, a comparison is shown between the existing, indeterminate sampling plans and the recommended sample designs. The projected sampling technique is illustrated by calculating the luminous intensities of LEDs using the Weibull distribution. Based on the findings and practical example, we conclude that the suggested strategy needs a smaller sample size than SSP and the current MDS sampling plan.

A redescending M-estimator approach for outlier-resilient modeling.

The OLS model is built on the assumption of normality in the distribution of error terms. However, this assumption can be easily violated, especially when there are outliers in the data. A single outlier can disrupt the normality assumption of error terms, making the OLS model less effective. In such situations, M-estimators (MEs) come into play to obtain reliable estimates. We introduce a redescending M-estimators (RME) for robust regression to handle datasets with outliers. The proposed RME produces more robust estimates by effectively managing the influence of outliers, even at lower values of the tuning constant. We compared the performance of this estimator with existing RMEs using real-life data examples and an extensive simulation study. The results show that our suggested RME is more efficient than the compared ME in various situations.

Nonparametric mixed exponentially weighted moving average-moving average control chart.

This research designed a distribution-free mixed exponentially weighted moving average-moving average (EWMA-MA) control chart based on signed-rank statistic to effectively identify changes in the process location. The EWMA-MA charting statistic assigns more weight to information obtained from the recent w samples and exponentially decreasing weights to information accumulated from all other past samples. The run-length profile of the proposed chart is obtained by employing Monte Carlo simulation techniques. The effectiveness of the proposed chart is evaluated under symmetrical distributions using a variety of individual and overall performance measures. The analysis of the run-length profile indicates that the proposed chart performs better than the existing control charts discussed in the literature. Additionally, an application from a gas turbine is provided to demonstrate how the proposed chart can be used in practice.

Birnbaum Saunders distribution for imprecise data: statistical properties, estimation methods, and real life applications.

A neutrosophic statistic is a random variable and it has a neutrosophic probability distribution. So, in this paper, we introduce the new neutrosophic Birnbaum-Saunders distribution. Some statistical properties are derived, using Mathematica 13.1.1 and R-Studio Software. Two different estimation methods for parameters estimation are introduced for new distribution: maximum likelihood estimation method and Bayesian estimation method. A Monte-Carlo simulation study is used to investigate the behavior of parameters estimates of new distribution, compare the performance of different estimates, and compare between our distribution and the classical version of Birnbaum-Saunders. Finally, study the validity of our new distribution in real life.

Comparing the efficacy of coefficient of variation control charts using generalized multiple dependent state sampling with various run-rule control charts.

This paper aimed to develop a coefficient of variation (CV) control chart utilizing the generalized multiple dependent state (GMDS) sampling approach for CV monitoring. We conducted a comprehensive examination of this designed control chart in comparison to existing control charts based on multiple dependent state sampling (MDS) and the Shewhart-type CV control chart, with a focus on average run lengths. The results were then compared to run-rule control charts available in the existing literature. Additionally, we elucidated the implementation of the proposed control chart through concrete examples and a simulation study. The findings clearly demonstrated that the GMDS sampling control chart shows significantly superior accuracy in detecting process shifts when compared to the MDS sampling control chart. As a result, the control chart approach presented in this paper holds significant potential for applications in textile and medical industries, particularly when researchers seek to identify minor to moderate shifts in the CV, contributing to enhanced quality control and process monitoring in these domains.

Surface-enhanced Raman spectroscopy for the characterization of bacterial pellets of Staphylococcus aureus infected by bacteriophage.

Drug-resistant pathogenic bacteria are a major cause of infectious diseases in the world and they have become a major threat through the reduced efficacy of developed antibiotics. This issue can be addressed by using bacteriophages, which can kill lethal bacteria and prevent them from causing infections. Surface-enhanced Raman spectroscopy (SERS) is a promising technique for studying the degradation of infectious bacteria by the interaction of bacteriophages to break the vicious cycle of drug-resistant bacteria and help to develop chemotherapy-independent remedial strategies. The phage (viruses)-sensitive Staphylococcus aureus (S. aureus) bacteria are exposed to bacteriophages (Siphoviridae family) in the time frame from 0 min (control) to 50 minutes with intervals of 5 minutes and characterized by SERS using silver nanoparticles as SERS substrate. This allows us to explore the effects of the bacteriophages against lethal bacteria (S. aureus) at different time intervals. The differentiating SERS bands are observed at 575 (C-C skeletal mode), 620 (phenylalanine), 649 (tyrosine, guanine (ring breathing)), 657 (guanine (COO deformation)), 728-735 (adenine, glycosidic ring mode), 796 (tyrosine (C-N stretching)), 957 (C-N stretching (amide lipopolysaccharides)), 1096 (PO2 (nucleic acid)), 1113 (phenylalanine), 1249 (CH2 of amide III, N-H bending and C-O stretching (amide III)), 1273 (CH2, N-H, C-N, amide III), 1331 (C-N stretching mode of adenine), 1373 (in nucleic acids (ring breathing modes of the DNA/RNA bases)) and 1454 cm-1 (CH2 deformation of saturated lipids), indicating the degradation of bacteria and replication of bacteriophages. Multivariate data analysis was performed by employing principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) to study the biochemical differences in the S. aureus bacteria infected by the bacteriophage. The SERS spectral data sets were successfully differentiated by PLS-DA with 94.47% sensitivity, 98.61% specificity, 94.44% precision, 98.88% accuracy and 81.06% area under the curve (AUC), which shows that at 50 min interval S. aureus bacteria is degraded by the replicating bacteriophages.

Surface-enhanced Raman spectroscopy for comparison of biochemical profile of bacteriophage sensitive and resistant methicillin-resistant Staphylococcus aureus (MRSA) strains.

Methicillin-resistant Staphylococcus aureus (MRSA) is gram positive bacteria and leading cause of a wide variety of diseases. It is a common cause of hospitalized and community-acquired infections. Development of increasing antibiotic-resistance by methicillin-resistant S. aureus (MRSA) strains demand to develop alternate novel therapies. Bacteriophages are now widely used as antibacterial therapies against antibiotic-resistant gram-positive pathogens. So, there is an urgent need to find fast detection techniques to point out phage susceptible and resistant strains of methicillin-resistant S. aureus (MRSA) bacteria. Samples of two separate strains of bacteria, S. aureus, in form of pellets and supernatant, were used for this purpose. Strain-I was resistant to phage, while the other (strain-II) was sensitive. Surface Enhanced Raman Spectroscopy (SERS) has detected significant biochemical changes in these bacterial strains of pellets and supernatants in the form of SERS spectral features. The protein portion of these two types of strains of methicillin-resistant S. aureus (MRSA) in their relevant pellets and supernatants is major distinguishing biomolecule as shown by their representative SERS spectral features. In addition, multivariate data analysis techniques such as principal component analysis (PCA) and a partial least squares-discriminant analysis (PLS-DA) were found to be helpful in identifying and characterizing various strains of S. aureus which are sensitive and resistant to bacteriophage with 100% specificity, 100% accuracy, and 99.8% sensitivity in case of SERS spectral data sets of bacterial cell pellets. Moreover, in case of supernatant samples, the results of PLS-DA model including 95.5% specificity, 96% sensitivity, and 96.5% accuracy are obtained.