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Abstract Ferroelectric BaBi4Ti4O15 was prepared using solid-state calcination at 950 °C for four hours. X-ray diffraction, Raman spectroscopy, and X-ray photoelectron spectroscopy were utilized to understand its microstructure and other structural aspects. Particle size was around

Abstract Geospatial mapping and monitoring are crucial for designing slopes in opencast mining, as failure can result in significant economic and life loss. To overcome these issues, the present investigation evaluated the Digital Elevation Model (DEM) generated using high resolution Cartosat-1 satellite imagery. Simultaneously, mapping of shaded relief map, aspect map and slope maps was done for the monitoring of Shatabdi opencast coal mine of Jharia region, an eastern coalfield region of India. Shaded relief map was categorized in to low, moderate and high categories and maximum area was covered by moderate to high shades. The constructed aspect map encompasses the range between 0 and 360 degrees of direction, with categorization and representation through distinct colors. The slope map was classified into various categories based on degrees of slope, including very gentle, gentle, moderate, moderately steep, steep, and very steep slopes. The maps were ground validated using Differential Global Positioning System (DGPS) collected data points by field visit in the region. For opencast mines to operate safely and profitably, slope stability in different stages of mining must be mapped and monitored. The study synthesizes data from diverse sources, highlighting the role of geospatial technology in addressing multiple research gaps within the mining industries prior to leveraging Cartosat-1 satellite data. Slope mapping and monitoring of coalfield regions are crucial to reducing construction costs, mitigation of natural hazard risks like flooding and landslides, and effective conservation of natural resources such as soils, vegetation, and water systems. The present study benefits policymakers, environmental planners and government in formulating policies to ensure safety, reliability, and enhance the economic growth of workers and the country.

Data scarcity and unavailability of observed rainfalls in the northeastern states of India limit prediction of extreme hydro-climatological changes. To fill this gap, a data assimilation approach has been applied to re-construct accurate high-resolution gridded (5 km2) daily rainfall data (2001–2020), which include seasonality assessment, statistical evaluation, and bias correction. Random forest (RF) and support vector regression were used to predict rainfall time series, and a comparison between machine learning and data assimilation-based gridded rainfall data was performed. Five gridded rainfall datasets, namely, Indian Monsoon Data Assimilation and Analysis (IMDAA) (12 km2), APHRODITE (25 km2), India Meteorological Department (25 km2), PRINCETON (25 km2), and CHIRPS (25 and 5 km2), have been utilized. For re-constructed rainfall datasets (5 km2), the comparative seasonality and change assessment have been performed with respect to other rainfall datasets. CHIRPS and APHRODITE datasets have shown better similarities with IMDAA. The RF and assimilated rainfall (AR) have superiority based on bias and extremity, and AR data were recognized as the best accurate data (>0.8). Precipitation change analysis (2021–2100) performed utilizing the bias-corrected and downscaled CMIP6 datasets showed that the dry spells will be enhanced. Considering the CMIP6 moderate emission scenario, i.e., SSP245, the wet spell will be enhanced in future; however, when considering SSP585 (representing the extreme worst case), the wet spells will be decreased. HIGHLIGHTS A unique data assimilation approach is applied to construct an accurate high-resolution gridded (5 km2) daily rainfall time series.; Evaluation and bias correction of multisource gridded rainfall datasets were performed.; Random forest and support vector regression machine learning methods were applied for the prediction of rainfall.; Assessment of long-term rainfall changes was done in the wettest regions of the world.;

Abstract Textile industry dye effluent contains a mixture of different kinds of dyes. Many times, photocatalysis is targeted as a solution for the treatment of dye effluent from the textile industry. Many researches have been published related to the photocatalysis of single textile dyes but in the real-world scenario, effluent is a mixture of dyes. Magnesium oxide (MgO) is used as a photocatalyst to treat a mixture (binary solution) of Methylene blue (MB) and Methylene violet (MV) along with individual MB and MV dyes in this article. MgO shows remarkable photocatalytic activity at about 93 and 88% for MB and MV dye in binary solution within 135 min. Furthermore, to study the influence of process parameters, experiments are designed with the help of the central composite design (CCD), and Response surface methodology (RSM) is used to study the interactions between parameters. For this study, five parameters are selected i.e., Photocatalyst dosage, initial concentration of both dyes, time of exposure to the light source, and pH of the binary solution. The photocatalytic process is also optimized and finally optimization of process parameters is validated with an experiment. The result of the validation experiment is very close to the predicted photocatalytic activity.

Purpose: The main aim of this study was to evaluate the changes in quality of minimally processed litchi fruit during storage at low temperatures (5-7°C). Research method: The study attempts to report the efficacies of seven different anti-browning compounds at various concentrations namely methionine (0.1%), cysteine (0.1%), EDTA (0.1%), oxaloacetic acid (1%), ascorbic acid (1%), citric acid (1%), and potassium metabisulfite (0.5%) on quality and shelf-life extension of minimally processed litchi aril. Treated litchi aril kept in trays wrapped with plastic film and stored under refrigerated conditions. Changes in total soluble solids, titratable acidity, ascorbic acid, total phenolics, sensory attributes, colour, weight loss, microbial and activities of polyphenol oxidase and peroxidase enzymes were evaluated. Findings: Treatments reduce the weight loss and sensory attributes with higher contents of TSS, titratable acidity, ascorbic acid, total phenolics and suppressed the increase in activities of polyphenol oxidase and peroxidase. Therefore, a postharvest dip of peeled litchi into solutions of chemical preservatives could be suggested to maintain the postharvest quality under refrigeration storage. Treated litchi arils were acceptable (sensory score >7) up to 8 days as compared to 3 days for the control samples during refrigerated storage. Research limitations: No limitations were found. Originality/Value: Further, 1% ascorbic acid and 1% citric acid were recorded to be the best to preserve the quality of minimally processed ‘Mujaffarpur’ litchi during refrigeration storage.

Background: While short-term outcomes of total knee arthroplasty (TKA) have been extensively studied, there is a need for longstanding assessments to understand the enduring impact of the procedure on patient well-being. Methods: A retrospective cohort research to rate the longstanding functional outcomes and quality of life (QoL) in those undergoing primary TKA. Patient-reported outcomes, including SF-36 and EQ-5D scores, were collected at multiple time points postoperatively (1, 5, and 10 years). Objective assessments of functional parameters, i.e., range of motion, gait analysis, and quadriceps strength, were also recorded. Results: Current findings demonstrate significant improvements in functional outcomes post-TKA, with sustained benefits observed over a 10-year period. Range of motion, gait parameters, and quadriceps strength showed consistent enhancements postoperatively. Moreover, QoL measures, as reflected by SF-36 and EQ-5D scores, exhibited substantial improvements following TKA and remained elevated throughout the follow-up period. Conclusion: This research highlights the enduring effectiveness of TKA in improving both functional outcomes and QoL in patients with advanced knee arthritis.

Background: This study provides us an opportunity to discuss about the development of a smartphone enabled Home based Self-management application for Chronic Obstructive Pulmonary Disease. Objective: To summarize the baseline characteristics of the Chronic Obstructive Pulmonary Disease patients recruited in present study. Methods: A single centered prospective non-randomized study has been conducted to implement the self-management application among 166 patients. Patients were matched based on gender and Global Initiative for Obstructive Lung Disease criteria. Smartphone application was provided to the intervention group and instructions were given to them. Results: The mean age of participants was 58.02 years in which more than half were male, more than 80% were married, almost one-third were educated up to class 10th, more than 65% have disease duration between 3 to 8 years, equally distributed for Grade 2 and 3 and two third were ex-smokers. The St. George's Respiratory Questionnaire score was 40.20 and 39.74, Clinical COPD Questionnaire score was 3.89 and 3.86, COPD Assessment Test score was 23.65 and 22.74 in intervention and control group respectively. There is no statistically significant difference between the group. Conclusion: The findings of present study provide a vital context for the follow-up results of the evaluation study.

Here we present a novel study of Calcium hydroxide and iron-nickel co-doped Calcium hydroxide nanoparticles. Calcium hydroxide (CH) and iron-nickel doped Calcium hydroxide (INCH) nanoparticles (NPs) were synthesized by a simple chemical precipitation method. XRD, FESEM-EDX, and FTIR were used to characterize the structural and morphological characteristics, while UV–Vis spectroscopy was used to study the optical alterations. The average crystallite size is estimated to be 63.75 nm and 66 nm for the CH and INCH nanoparticles, respectively. The FESEM analysis revealed that CHNPs form a hexagonal-like shape, whereas INCH NPs produce highly agglomerated dispersed particles. The UV–Vis spectroscopy revealed that the band gap changes with average crystallite size concurrently.

Emotion Recognition is a critical area of research including healthcare, human-computer interaction, and psychology. While traditional methods mainly rely on facial expressions and textual analysis, they also have inherent flaws and cannot be reliable. Facial expression-based emotion recognition assumes that it represents genuine internal emotions that may be inaccurate. Similarly, textual analysis depends on the available data and needs help accurately capturing subtle emotions in text. However, electroencephalography (EEG) has emerged as a rising alternative for objective and real-time emotion recognition. Unlike facial and textual methods, EEG directly measures brain activity and provides a reliable result. To address this researchers have used basic machine learning methods that need manual feature extraction, which might miss essential data and make the process slow and less accurate. In this study, we propose a comprehensive methodology for EEG-based emotion recognition that addresses the limitations of traditional methods and basic machine learning techniques. Our approach involves preprocessing EEG signals using a butter-worth bandpass filter to eliminate noise, followed by feature extraction techniques. We then employ Principal Component Analysis (PCA) for dimensionality reduction, ensuring efficient data representation. To further enhance the model performance we explore machine learning classifiers(GaussianNB, SVM, Random Forest) and proposed an EEG-LSTM and GRU model with an accuracy of 97% and 96% respectively, that gives better results than the basic machine learning models.

Introduction: Transurethral Resection of the Prostate (TURP) is a gold standard treatment for Benign Prostatic Hyperplasia (BPH). The Clavien classification system was proposed in 1992 to grade complications of general surgery, which was then modified in 2004 by Dindo. In 2017, the European Association of Urology (EAU) endorsed its use for reporting complications in urological procedures. However, the system relies on observers to grade complications, and different observers may assign different grades to the same negative outcome, highlighting the need for uniformity. Aim: To assess the inter-observer reliability and uniformity among urologists in reporting complications of TURP using the modified Clavien-Dindo classification system. Materials and Methods: A retrospective observational study was conducted at Department of Urology, Shyam Shah Medical College, Rewa, Madhya Pradesh, India, from January 2018 to May 2023. The study included symptomatic patients with BPH and prostate gland sizes greater than 40 cc. Negative outcomes were evaluated and complications were rated by nine different raters. Inter-observer reliability was tested using weighted kappa with Statistical Package for Social Sciences (SPSS) version 21.0 (Fleiss’s kappa test). Results: A total of 523 men with BPH who underwent TURP were evaluated, with a mean age of 66.7±5.2 years and a mean prostate volume of 62 cc. Adverse events occurred in 96 patients (18.36%), and these complications were classified according to the Clavien-Dindo System (CDS) by nine different blinded observers. The rating of these complications was then assessed for concordance. A concordance rate using weighted kappa of 0.847 was observed, indicating high inter-observer reliability for TURP. Conclusion: Clavien-Dindo’s system demonstrated good interobserver concordance and reliability. Some modifications to the grading system are needed, taking into account the impact of pre-existing co-morbidities and auxiliary procedures. Largescale prospective studies are recommended to further validate these findings.

This study developed and examined a new operational matrix approach utilizing the Vieta-Fibonacci polynomial for the numerical solution of generalized Caputo-type differential equations with fractal-fractional terms. Based on the proposed approach, the fractal-fractional differential equations with generalized Caputo-type derivatives were reduced into a system of algebraic equations, which was further solved to obtain the unknown solution. The convergence and error bounds are theoretically calculated. The results are quantitatively confirmed in various cases. To demonstrate the correctness and computational efficacy of this proposed technique, it is compared to other well-known methods.

Abstract Background In hexaploid wheat, quantitative trait loci (QTL) and meta-QTL (MQTL) analyses were conducted to identify genomic regions controlling resistance to cereal cyst nematode (CCN), Heterodera avenae. A mapping population comprising 149 RILs derived from the cross HUW 468 × C 306 was used for composite interval mapping (CIM) and inclusive composite interval mapping (ICIM). Results Eight main effect QTLs on three chromosomes (1B, 2A and 3A) were identified using two repeat experiments. One of these QTLs was co-localized with a previously reported wheat gene Cre5 for resistance to CCN. Seven important digenic epistatic interactions (PVE = 5% or more) were also identified, each involving one main effect QTL and another novel E-QTL. Using QTLs earlier reported in literature, two meta-QTLs were also identified, which were also used for identification of 57 candidate genes (CGs). Out of these, 29 CGs have high expression in roots and encoded the following proteins having a role in resistance to plant parasitic nematodes (PPNs): (i) NB-ARC,P-loop containing NTP hydrolase, (ii) Protein Kinase, (iii) serine-threonine/tyrosine-PK, (iv) protein with leucine-rich repeat, (v) virus X resistance protein-like, (vi) zinc finger protein, (vii) RING/FYVE/PHD-type, (viii) glycosyl transferase, family 8 (GT8), (ix) rubisco protein with small subunit domain, (x) protein with SANT/Myb domain and (xi) a protein with a homeobox. Conclusion Identification and selection of resistance loci with additive and epistatic effect along with two MQTL and associated CGs, identified in the present study may prove useful for understanding the molecular basis of resistance against H. avenae in wheat and for marker-assisted selection (MAS) for breeding CCN resistant wheat cultivars.

Abstract In this article, we use coupled boundary conditions on a nonlinear system with ψ-Caputo fractional derivatives to derive new conclusions on the solution’s existence, uniqueness, and stability. We use the well-known tools of fixed-point theory to establish the proposed results. We give an example to verify the theoretical findings. The proposed existence, uniqueness, and stability analyses considering the ψ-Caputo fractional derivative are the novelty of this article.

Background: Peyronie’s disease (PD) is a localized fibrosis of tunica albuginea, which causes the anatomical and functional changes to the penis. Corporoplasty with grafting is indicated in severe (>60°) and complex curvature. Buccal mucosa is the most favored autologous graft material nowadays. The ventrolateral aspect of lingual mucosa has similar histological features to the rest of the oral cavity. Methods: This study aimed to test the efficacy, safety, durability, and reproducibility of corporoplasty with lingual mucosal graft (LMG) in the surgical treatment of PD in terms of surgical outcome, sexual function, and donor site complications. This prospective study included 19 patients of PD with severe and complex curvature, who underwent corporoplasty with LMG. Surgical and functional outcomes were assessed at follow-up planned at 2 weeks, 3 months, 6 months, 1 year, and 2 years. Results: The mean operative time was 126.31 ± 21.45 min. Additional Nesbit’s plication to correct the residual deformity was required in 26% (5 / 19) of patients. Straightening of the penis (curvature 1 cm) postoperatively was achieved in 63% (12 / 19) of patients and a shortening of penis occurred in 5% (1 / 19) of patients. Newer onset erectile dysfunction developed in 11% (2 / 19) of patients, and patient and partner satisfaction rates were 89% (17 / 19) and 84% (16 / 19), respectively, in a mean follow-up of 20.66 ± 5.37 months. Donor site complications were minimal and no patient had any salivary changes or speech disturbances. Conclusion: LMG provided excellent short-term results in terms of deformity correction, improved sexual function, and minimal donor site morbidity. The method is simple and reproducible, and multicenter studies with larger number of cases with longer follow-up are required to confirm these favorable results.

Abstract In wheat, genomic prediction accuracy (GPA) was assessed for three micronutrient traits (grain iron, grain zinc, and β‐carotenoid concentrations) using eight Bayesian regression models. For this purpose, data on 246 accessions, each genotyped with 17,937 DArT markers, were utilized. The phenotypic data on traits were available for 2013–2014 from Powerkheda (Madhya Pradesh) and for 2014–2015 from Meerut (Uttar Pradesh), India. The accuracy of the models was measured in terms of reliability, which was computed following a repeated cross‐validation approach. The predictions were obtained independently for each of the two environments after adjusting for the local effects and across environments after adjusting for the environmental effects. The Bayes ridge regression (BayesRR) model outperformed the other seven models, whereas BayesLASSO (BayesL) was the least efficient. The GPA increased with an increase in the size of the training set as well as with an increase in marker density. The GPA values differed for the three traits and were higher for the best linear unbiased estimate (BLUE) (obtained after adjusting for the environmental effects) relative to those for the two environments. The GPA also remained unaffected after accounting for the population structure. The results of the present study suggest that only the best model should be used for the estimations of genomic estimated breeding values (GEBVs) before their use for genomic selection to improve the grain micronutrient contents.

In this article, we derive some novel results of the existence, uniqueness, and stability of the solution of generalized Caputo-type fractional boundary value problems (FBVPs). The Banach contraction principle, along with necessary features of fixed point theory, is used to establish our results. An example is illustrated to justify the validity of the theoretical observations.

Thermal energy storage technology has evolved as one of the prominent methods of storing thermal energy when it is available and utilized as per the requirements. In recent years, thermal energy storage has found a variety of applications for thermal management, such as buildings, batteries, electronics, cold storage, textiles, and solar thermal systems. Phase Change Material (PCM) has taken the lead among all other thermal energy storage materials because of various merits such as high energy density, ease of use, low cost, low volume change, environmental friendliness, easy availability, and chemical stability. However, limitations such as poor thermal conductivity and leakage during phase transformation limit their applicability. In this study, Shape Stabilized Composite PCM (SSCPCM) was developed to overcome these drawbacks. Paraffin wax and soya wax were used as PCMs and multi-walled carbon nanotubes and graphene oxide were used as nano-additives. High-Density Polyethylene (HDPE) is used as a supporting matrix. Leakage test suggest maximum loading of 40 wt% and 35 wt% of paraffin wax and soya wax in HDPE without any leakage at elevated temperature. The prepared SSCPCM shows substantially better thermal energy storage capacity along with improved thermal conductivity. A maximum rise of 260.8% in thermal conductivity was observed in paraffin wax supported by HDPE and loaded with 3 wt% of multi-walled carbon nanotube nanoparticles. The heating and cooling performance suggests an improvement in the heating and cooling rate by adding nano-additives. The prepared SSCPCM are also thermally stable at elevated temperatures up to 150 °C.

Puccinia spp. causing rust diseases in wheat and other cereals secrete several specialized effector proteins into host cells. Characterization of these proteins and their interaction with host’s R proteins could greatly help to limit crop losses due to diseases. Prediction of effector proteins by combining the transcriptome analysis and multiple in-silico approaches is gaining importance in revealing the pathogenic mechanism. The present study involved identification of 13 Puccinia triticina (Pt) coding sequences (CDSs), through transcriptome analysis, that were differentially expressed during wheat-leaf rust interaction; and prediction of their effector like features using different in-silico tools. NCBI-BLAST and pathogen-host interaction BLAST (PHI-BLAST) tools were used to annotate and classify these sequences based on their most closely matched counterpart in both the databases. Homology between CDSs and the annotated sequences in the NCBI database ranged from 79 to 94% and with putative effectors of other plant pathogens in PHI-BLAST from 24.46 to 54.35%. Nine of the 13 CDSs had effector-like features according to EffectorP 3.0 (≥0.546 probability of these sequences to be effector). The qRT-PCR expression analysis revealed that the relative expression of all CDSs in compatible interaction (HD2329) was maximum at 11 days post inoculation (dpi) and that in incompatible interactions (HD2329 + Lr28) was maximum at 3 dpi in seven and 9 dpi in five CDSs. These results suggest that six CDSs (>0.8 effector probability as per EffectorP 3.0) could be considered as putative Pt effectors. The molecular docking and MD simulation analysis of these six CDSs suggested that candidate Lr28 protein binds more strongly to candidate effector c14094_g1_i1 to form more stable complex than the remaining five. Further functional characterization of these six candidate effectors should prove useful for a better understanding of wheat-leaf rust interaction. In turn, this should facilitate effector-based leaf rust resistance breeding in wheat.

In this research article, we derive an optimal control problem for the mosaic disease model by using the Caputo fractional derivatives. The natural microbial biostimulants (MBs) are very useful to improve the plant performance and protect plants from mosaic infection. In the proposed model, we apply two extra optimal controls; spraying and roguing to investigate their roles in the control of mosaic spread. We perform a number of experimental results by using the algorithm of forward–backward sweep method at various fractional order values. The main goal of this article is to explore the role of spraying and roguing in the aforementioned availability of MBs. From our study, we notice that in the presence of MBs, only roguing is the effective control which can be used to stop the spread of mosaic.

In this digital, internet-based world, it is not new to face cyber attacks from time to time. A number of heavy viruses have been made by hackers, and they have successfully given big losses to our systems. In the family of these viruses, the Stuxnet virus is a well-known name. Stuxnet is a very dangerous virus that probably targets the control systems of our industry. The main source of this virus can be an infected USB drive or flash drive. In this research paper, we study a mathematical model to define the dynamical structure or the effects of the Stuxnet virus on our computer systems. To study the given dynamics, we use a modified version of the Caputo-type fractional derivative, which can be used as an old Caputo derivative by fixing some slight changes, which is an advantage of this study. We demonstrate that the given fractional Caputo-type dynamical model has a unique solution using fixed point theory. We derive the solution of the proposed non-linear non-classical model with the application of a recent version of the Predictor–Corrector scheme. We analyze various graphs at different values of the arrival rate of new computers, damage rate, virus transmission rate, and natural removal rate. In the graphical interpretations, we verify the values of fractional orders and simulate 2-D and 3-D graphics to understand the dynamics clearly. The major novelty of this study is that we formulate the optimal control problem and its important consequences both theoretically and mathematically, which can be further extended graphically. The main contribution of this research work is to provide some novel results on the Stuxnet virus dynamics and explore the uses of fractional derivatives in computer science. The given methodology is effective, fully novel, and very easy to understand.

In this research, we reformulate and analyze a co-infection model consisting of Chagas and HIV epidemics. The basic reproduction number $ R_0 $ of the proposed model is established along with the feasible region and disease-free equilibrium point $ E^0 $. We prove that $ E^0 $ is locally asymptotically stable when $ R_0 $ is less than one. Then, the model is fractionalized by using some important fractional derivatives in the Caputo sense. The analysis of the existence and uniqueness of the solution along with Ulam-Hyers stability is established. Finally, we solve the proposed epidemic model by using a novel numerical scheme, which is generated by Newton polynomials. The given model is numerically solved by considering some other fractional derivatives like Caputo, Caputo-Fabrizio and fractal-fractional with power law, exponential decay and Mittag-Leffler kernels.

Abstract The resistance to cereal cyst nematode (Heterodera avenae Woll.) in wheat (Triticum aestivum L.) was studied using 114 doubled haploid lines from a novel ITMI mapping population. These lines were screened for nematode infestation in a controlled environment for two years. QTL-mapping analyses were performed across two years (Y1 and Y2) as well as combining two years (CY) data. On the 114 lines that were screened, a total of 2,736 data points (genotype, batch or years, and replication combinations) were acquired. For QTL analysis, 12,093 markers (11,678 SNPs and 415 SSRs markers) were used, after filtering the genotypic data, for the QTL mapping. Composite interval mapping, using Haley-Knott regression (hk) method in R/QTL, was used for QTL analysis. In total, 19 QTLs were detected out of which 13 were novel and six were found to be colocalized or nearby to previously reported Cre genes, QTLs or MTAs for H. avenae or H. filipjevi. Nine QTLs were detected across all three groups (Y1, Y2 and CY) including a significant QTL "QCcn.ha-2D" on chromosome 2D that explains 23% of the variance. This QTL colocalized with a previously identified Cre3 locus. Novel QTL, QCcn.ha-2A, detected in the present study could be the possible unreported homeoloci to QCcn.ha-2D, QCcn.ha-2B.1 and QCcn.ha-2B.2. Six significant digenic epistatic interactions were also observed. In addition, 26 candidate genes were also identified including genes known for their involvement in PPNs (plant parasitic nematodes) resistance in different plant species. In-silico expression of putative candidate genes showed differential expression in roots during specific developmental stages. Results obtained in the present study are useful for wheat breeding to generate resistant genetic resources against H. avenae.

Five bacterial strains for biodegradation study were initially isolated from quinalphos exposed soil from cotton field of Indian Agricultural Research Institute, India by Serial dilution and enrichment technique. Amongst them, two strains Pantoea agglomerans and Acinetobacter sp. dcm5A were exposed to different concentrations (50-250 ppm, parts per million) of quinalphos to evaluate their tolerance and the optimum concentration of quinalphos supported growth. Growth kinetics of the isolates was studied by means of optical density of the culture media (150 rpm, rotation per minute) at 30oC for 15 days. The optimal concentration of quinalphos for the growth of Pantoea agglomerans was 100 ppm, while for Acinetobacter sp. dcm5A was 200 ppm. Bacterial strains Pantoea agglomerans and Acinetobacter sp. dcm5A degraded quinalphos 60% and 79.7% respectively in 7 days incubation and 100% degradation by both strains was observed after 13 days of incubation.

Soft robotics is an emerging area of research due to its safe interaction with humans; it also has exciting applications, such as wearable soft medical devices for rehabilitation, prosthetics, etc. Soft robots require soft actuators for performing desired movements, including bending, expansion, contraction, and twisting. This work focuses on bending-type multi-chambered extra-soft actuators actuated by pneumatic pressure. The corrugated design of a multi-chambered soft pneumatic actuator (SPA) is analyzed experimentally to observe the radial, longitudinal, and lateral expansions of different chambers, i.e., ballooning of the chambers under the application of air pressure. From the experimental study, it is observed that the ballooning mainly occurs at the free end of the actuator in a cantilever-type boundary condition, which could not be demonstrated by the computational solution using the finite element analysis (FEA). Moreover, it is observed that the effect of ballooning also disturbs the constant curvature profile of SPA. Therefore, a chamber-reinforcement solution is provided for minimizing the ballooning and ensuring the uniform bending of a SPA.

In wheat, major yield losses are caused by a variety of diseases including rusts, spike diseases, leaf spot and root diseases. The genetics of resistance against all these diseases have been studied in great detail and utilized for breeding resistant cultivars. The resistance against leaf spot diseases caused by each individual necrotroph/hemi-biotroph involves a complex system involving resistance (R) genes, sensitivity (S) genes, small secreted protein (SSP) genes and quantitative resistance loci (QRLs). This review deals with resistance for the following four-leaf spot diseases: (i) Septoria nodorum blotch (SNB) caused by Parastagonospora nodorum; (ii) Tan spot (TS) caused by Pyrenophora tritici-repentis; (iii) Spot blotch (SB) caused by Bipolaris sorokiniana and (iv) Septoria tritici blotch (STB) caused by Zymoseptoria tritici.

Introduction: Vesical calculus accounts for nearly 5% of urinary system calculi and is commonly seen in patients with Bladder Outlet Obstruction (BOO), chronic infection, and neurogenic bladder. Open cystolithotomy is an invasive surgery with a long postoperative period and with a high wound infection rate, so only best recommended for large stones. With recent advancements in endourological instruments, cystolithotripsy either by Percutaneous Cystolithotripsy (PCCL) or Transurethral Cystolithotripsy (TUCL) approach has become a safer treatment for medium size stone (2-4 cm). Aim: To compare the outcome of PCCL and TUCL for medium size bladder stones in adult patients. Materials and Methods: This retrospective study was conducted between January 2019 to December 2021 in the Department of Urology, Superspeciality Hospital, Shyam Shah Medical College, Rewa, Madhya Pradesh, India. Group I was PCCL (n=32) and group II was TUCL (n=30). PCCL group was compared with TUCL group II for age, stone size, number of stones, operative time, mean urethral entries, postoperative hospital stays, peri and postoperative complications. Statistical analysis was performed using Chi-square and t-test. Differences were accepted to be statistically significant at p-value≤0.05. Results: A total of 168 were treated for bladder stones in the Institute and 62 patients were included in the study. No residual stone was observed in any of the two groups. Complete stone clearance was achieved in both groups of patients. Mean operative time and the number of urethral entries were 46.75±2.45 min and 1.06±0.25 min in in the PCCL group, and 59.67±3.84 min and 2.87±0.82 min in in the TUCL group. (p-value-

Abstract In this paper, we prove the existence and uniqueness of solutions for the nonlocal boundary value problem (BVP) using Caputo fractional derivative (CFD). We derive Green’s function and give some estimation for it to derive our main results. The main principles applied to investigate our results are based on the Banach contraction fixed point theorem and Schauder fixed point approach. We dwell in detail on some results concerning the Hyers-Ulam (H-U) type and generalized H-U (g-H-U) type stability also for problem we are considering. We justify our results with an illustrative example.

In this article, we studied the fractional dynamics of the most dangerous deathly disease which outbreaks have been recorded all over the world, called 2019-nCOV or COVID-19. We used the numerical values of the given parameters based on the real data of the 2019-nCOV cases in Spain for the time duration of 25 February to 9 October 2020. We performed our observations with the help of the Atangana-Baleanu (AB) non-integer order derivative. We analysed the optimal control problem in a fractional sense for giving the information on all necessary health care issues. We applied the Predictor-Corrector method to do the important graphical simulations. Also, we provided the analysis related to the existence of a unique solution and the stability of the proposed scheme. The aim and the main contribution of this research is to analyse the structure of novel coronavirus in Spain at different transmission rate and to indicate the danger of this deathly disease for future with the introduction of some optimal controls and health care measures.

In this article, we propose some novel results on the existence and uniqueness of generalized Caputo-type initial value problems with delay by using fixed point theory. The characteristics of space of continuous and measurable functions are the main basis of our results. The proposed results are very useful to prove the existence of a unique solution for the various types of fractional-order systems defined under the generalized Caputo fractional derivative consisting of delay terms.

An inbred strain limits the segregating variance and provides more power and requires fewer experimental animals to produce good reproducibility. This study was undertaken with the aim to assess the impact of sex of offsprings and sex specific microsatellite variants on performance and fitness traits in F4 inbred Swiss albino mice. The phenomics of different performance and fitness traits were estimated on 506 F4 inbred mice population. Two ‘X’ chromosome specific microsatellite loci (DXMit187 and DxMit172) were used for PCR-Microsatellite genotyping of 102 F4 inbred population. PIC estimates showed that both the loci were informative for the population. In the current population, with the increasing level of “F” a declining trend was observed for Body weight at birth (BWB), Body weight at weaning (BWW), Litter size at weaning (LSW) and Litter weight at weaning (LWW). In F4 inbred population, BWW and ABW for males (17.32±0.32g and 30.81±0.31g) were significantly (p

Abstract This study focuses on analyzing the poling effect of BaBi4Ti4O15 (BBT) on the basis of photo and piezo‐catalysis performance. BBT powder is prepared via a solid state reaction followed by calcination at 950 °C for 4 h. BBT is characterized by an X‐ray diffractometer, scanning electron microscopy, Raman spectroscopy, and X‐ray photoelectron spectroscopy. The optical bandgap of BBT is evaluated with the help of Tauc's plot and found to be 3.29 eV, which comes in the photon energy range of ultra‐violet radiation. BBT powder is poled by using Corona poling in the presence of 2 kV mm−1 of electric field. An aqueous solution of methyl blue (MB) dye in the presence of UV radiation is used to evaluate the photo/piezocatalysis performance. Photocatalysis, piezocatalysis, and photo–piezo catalysis degradation efficiencies of poled and unpoled BBT powder are tested for 120 min of UV light irradiation. Photo–piezocatalysis shows degradation efficiencies of 62% and 40% for poled and unpoled BBT powder, respectively. Poling of BBT powder shows significant enhancement in degradation performance of MB dye in aqueous solution. Scavenger tests are also performed to identify reactive species.

Genetic architecture of resistance to spot blotch in wheat was examined using a Genome-Wide Association Study (GWAS) involving an association panel comprising 303 diverse genotypes. The association panel was evaluated at two different locations in India including Banaras Hindu University (BHU), Varanasi (Uttar Pradesh), and Borlaug Institute for South Asia (BISA), Pusa, Samastipur (Bihar) for two consecutive years (2017-2018 and 2018-2019), thus making four environments (E1, BHU 2017-18; E2, BHU 2018-19; E3, PUSA, 2017-18; E4, PUSA, 2018-19). The panel was genotyped for 12,196 SNPs based on DArT-seq (outsourced to DArT Ltd by CIMMYT); these SNPs included 5,400 SNPs, which could not be assigned to individual chromosomes and were therefore, described as unassigned by the vendor. Phenotypic data was recorded on the following three disease-related traits: (i) Area Under Disease Progress Curve (AUDPC), (ii) Incubation Period (IP), and (iii) Lesion Number (LN). GWAS was conducted using each of five different models, which included two single-locus models (CMLM and SUPER) and three multi-locus models (MLMM, FarmCPU, and BLINK). This exercise gave 306 MTAs, but only 89 MTAs (33 for AUDPC, 30 for IP and 26 for LN) including a solitary MTA detected using all the five models and 88 identified using four of the five models (barring SUPER) were considered to be important. These were used for further analysis, which included identification of candidate genes (CGs) and their annotation. A majority of these MTAs were novel. Only 70 of the 89 MTAs were assigned to individual chromosomes; the remaining 19 MTAs belonged to unassigned SNPs, for which chromosomes were not known. Seven MTAs were selected on the basis of minimum P value, number of models, number of environments and location on chromosomes with respect to QTLs reported earlier. These 7 MTAs, which included five main effect MTAs and two for epistatic interactions, were considered to be important for marker-assisted selection (MAS). The present study thus improved our understanding of the genetics of resistance against spot blotch in wheat and provided seven MTAs, which may be used for MAS after due validation.

A rising amount of research demonstrates that artificial intelligence and machine learning approaches can provide an essential basis for the drug design and discovery process. Deep learning algorithms are being developed in response to recent advances in computer technology as part of the creation of therapeutically relevant medications for the treatment of a variety of ailments. In this review, we focus on the most recent advances in the areas of drug design and discovery research employing generative deep learning methodologies such as generative adversarial network (GAN) frameworks. To begin, we examine drug design and discovery studies that use several GAN methodologies to evaluate one key application, such as molecular de novo design in drug design and discovery. Furthermore, we discuss many GAN models for dimension reduction of single-cell data at the preclinical stage of the drug development pipeline. We also show various experiments in de novo peptide and protein creation utilizing GAN frameworks. Furthermore, we discuss the limits of past drug design and discovery research employing GAN models. Finally, we give a discussion on future research prospects and obstacles.

Abstract In bread wheat, meta-QTL analysis was conducted using 353 QTLs that were available from earlier studies. When projected onto a dense consensus map comprising 76,753 markers, only 184 QTLs with the required information, could be utilized leading to identification of 61 MQTLs spread over 18 of the 21 chromosomes (barring 5D, 6D and 7D). The range for mean R2 (PVE %) was 1.9% to 48.1%, and that of CI was 0.02 to 11.47 cM; these CIs also carried 37 Yr genes. Using these MQTLs, 385 candidate genes (CGs) were also identified. Out of these CGs, 241 encoded known R proteins and 120 showed differential expression due to stripe rust infection at the seedling stage; the remaining 24 CGs were common in the sense that they encoded R proteins as well as showed differential expression. The proteins encoded by CGs carried the following widely known domains: NBS-LRR domain, WRKY domains, ankyrin repeat domains, sugar transport domains, etc. Thirteen breeders’ MQTLs (PVE > 20%) including four pairs of closely linked MQTLs are recommended for use in wheat molecular breeding, for future studies to understand the molecular mechanism of stripe rust resistance and for gene cloning.

Background: Numerous plants and plant isolates have been widely reported for the treatment of arthritis. Berberine, a cationic flavonoid, obtained from Berberis aristata DC. (Berberidaceae) has been well reported for the treatment of arthritis. The lipid-based vesicular system including invasomes overcome the stratum corneum barrier and can effectively deliver drugs beneath the skin. Methods: The aim of the present study is to prepare berberine-loaded invasomes by the thin film hydration method. Prepared berberine-loaded invasomes were characterised for particle size and shape, zeta potential, entrapment efficiency, and skin permeation studies. These prepared berberine-loaded invasomes were further utilizesd for the preparation of gel containing carbomer for transdermal delivery. Prepared berberine-loaded invasomal gel was evaluated for homogeneity, viscosity, pH, speradability, extrudability, drug content, skin irritant and stability studies. Results: The in vivo analgesic activity of prepared berberine-loaded invasomal gel using the tail-flick hotwater immersion method, revealed potential analgesic activity for a prolonged period of time. Furthermore, the anti-arthritic activity of berberine-loaded invasomal gel was evaluated in CFA-induced arthritis rat model by measuring paw diameter, which showed a considerable reduction after treatment, as compared to standard gel (omnilgel, 0.1%). Topical application of berberine-loaded invasomal gel improves haematological factors and normalizes proinflammatory biomarkers. The radiographical analysis of hind paw rats in CFA model showed bone resorption, definite joint gap reduction, and considerable connective tissue expansion after treatment with prepared berberine-loaded invasomal gel. Histopathological examination of ankle joints also confirms the deeper penetration ability of invasomes through berberine-loaded invasomal gel and produces profound effects. Conclusion: The results revealed that the berberine-loaded invasomal gel has significant arthritic activity in the CFA rat model.

Metal-matrix nanocomposites have a separate variety of objectives under provisions of their enhanced properties. Ion irradiation with low energy is a curious contrivance to achieve the bulk variations of distinct materials. The effect of low energy ion irradiation is explored on Cu-C60 nanocomposite thin films grown by the thermal co-deposition method. The Cu concentration in the as-deposited sample is found to be ∼ 45 at.% by Rutherford Backscattering Spectrometry (RBS). Owing to high metal concentration, a Surface Plasmon Resonance (SPR) peak is found at 616 nm in the as-deposited sample and the average size of Cu nanoparticles is determined to be ∼7.8 nm, with a broad size distribution. The as-deposited samples are irradiated with a beam of 220 keV Ag ions using an ion accelerator, which leads to moderate variations in the structural, electrical, and optical properties of nanocomposite thin film. The SPR peak is effectively red-shifted by ∼16 nm at a highest dose. The outcomes of Raman spectroscopy disclose the gradual transformation of fullerene C60 into amorphous carbon with increasing doses. High-Resolution Transmission Electron Microscopy (HRTEM) images demonstrate the minor growth of copper nanoparticles with ion irradiation. A growth in surface grains with ion dose is confirmed by Field Emission Scanning Electron Microscope (FESEM) and Atomic Force Microscopy (AFM). The X-ray Photoelectron Spectroscopy (XPS) measurements have been used for the chemical state evaluation of the nanocomposite films. The I-V measurements show the conversion of fullerene into amorphous carbon with a loss in the resistivity of the film.

Lipid nanoparticles (LNPs) are spherical vesicles composed of ionizable lipids that are neutral at physiological pH. Despite their benefits, unmodified LNP drug delivery systems have substantial drawbacks, including a lack of targeted selectivity, a short blood circulation period, and in vivo instability. lipid–polymer hybrid nanoparticles (LPHNPs) are the next generation of nanoparticles, having the combined benefits of polymeric nanoparticles and liposomes. LPHNPs are being prepared from both natural and synthetic polymers with various techniques, including one- or two-step methods, emulsification solvent evaporation (ESE) method, and the nanoprecipitation method. Varieties of LPHNPs, including monolithic hybrid nanoparticles, core–shell nanoparticles, hollow core–shell nanoparticles, biomimetic lipid–polymer hybrid nanoparticles, and polymer-caged liposomes, have been investigated for various drug delivery applications. However, core–shell nanoparticles having a polymeric core surrounded by a highly biocompatible lipid shell are the most commonly explored LPHNPs for the treatment of various diseases. In this review, we will shed light on the composition, methods of preparation, classification, surface functionalization, release mechanism, advantages and disadvantages, patents, and clinical trials of LPHNPs, with an emphasis on core–shell-structured LPHNPs.

Abstract In this study, our aim is to explore the dynamics of COVID-19 or 2019-nCOV in Argentina considering the parameter values based on the real data of this virus from March 03, 2020 to March 29, 2021 which is a data range of more than one complete year. We propose a Atangana–Baleanu type fractional-order model and simulate it by using predictor–corrector (P-C) method. First we introduce the biological nature of this virus in theoretical way and then formulate a mathematical model to define its dynamics. We use a well-known effective optimization scheme based on the renowned trust-region-reflective (TRR) method to perform the model calibration. We have plotted the real cases of COVID-19 and compared our integer-order model with the simulated data along with the calculation of basic reproductive number. Concerning fractional-order simulations, first we prove the existence and uniqueness of solution and then write the solution along with the stability of the given P-C method. A number of graphs at various fractional-order values are simulated to predict the future dynamics of the virus in Argentina which is the main contribution of this paper.

The first reported case of coronavirus disease (COVID-19) in Brazil was confirmed on 25 February 2020 and then the number of symptomatic cases produced day by day. In this manuscript, we studied the epidemic peaks of the novel coronavirus (COVID-19) in Brazil by the successful application of Predictor–Corrector (P-C) scheme. For the proposed model of COVID-19, the numerical solutions are performed by a model framework of the recent generalized Caputo type non-classical derivative. Existence of unique solution of the given non-linear problem is presented in terms of theorems. A new analysis of epidemic peaks in Brazil with the help of parameter values cited from a real data is effectuated. Graphical simulations show the obtained results to classify the importance of the classes of projected model. We observed that the proposed fractional technique is smoothly work in the coding and very easy to implement for the model of non-linear equations. By this study we tried to exemplify the roll of newly proposed fractional derivatives in mathematical epidemiology. The main purpose of this paper is to predict the epidemic peak of COVID-19 in Brazil at different transmission rates. We have also attempted to give the stability analysis of the proposed numerical technique by the reminder of some important lemmas. At last we concluded that when the infection rate increases then the nature of the diseases changes by becoming more deathly to the population.

Fungicides are consumed to foreclose or slow the epidemics of disease germ by fungi. Crop cultivation is a favorable business platform for farmers, but it is also very common for them to have losses. These losses happen by attacking pathogens, such as fungi, oomycetes (water fungi), viruses, bacteria, nematodes, and viroid that spread the infection into the plants. In this article, we derive a fractional mathematical model for simulating the dynamics of fungicide application via Caputo-Fabrizio fractional derivative. Caputo-Fabrizio operator is defined with non-singular type kernel which is better than singular kernel. We give some important proofs related to the existence of a unique solution of the given model. We derive the solution of the model by using the Adams-Bashforth algorithm and also mentioned the stability of the method. We plotted the number of graphs at different fungicide application rate, fungicide decay rate, fungicide effectiveness, curatives rate of fungicide, growth rate of the host, and removal rate. A complete structure of the given problem can be understood by this paper. The main novelty of this work is to understand the role of fungicide application in the disease caused by fungi with the help of fractional derivatives consisting memory effects.

The main purpose of this paper is to provide new vaccinated models of COVID-19 in the sense of Caputo-Fabrizio and new generalized Caputo-type fractional derivatives. The formulation of the given models is presented including an exhaustive study of the model dynamics such as positivity, boundedness of the solutions, and local stability analysis. Furthermore, the unique solution existence for the proposed fractional-order models is discussed via fixed point theory. Numerical solutions are also derived by using two-steps Adams-Bashforth algorithm for Caputo-Fabrizio operator, and modified Predictor-Corrector method for generalised Caputo fractional derivative. Our analysis allows to show that the given fractional-order models exemplify the dynamics of COVID-19 much better than the classical ones. Also, the analysis on the convergence and stability for the proposed methods are performed. By this study, we see that how vaccine availability plays an important role in the control of COVID-19 infection.

Abstract Background Urothelial bladder carcinoma accounts for around 3.9% cases of all the male cancers in India. Non-muscle-invasive bladder carcinoma (NMIBC) is predominant group which constitute approximately three fourth of the urothelial bladder cancer. Intravesical BCG immunotherapy is the corner stone of today’s NMIBC management. However, as with any other therapy it has its own complications and its interruption due to these adverse effects is a major cause of suboptimal efficacy. The aim of this study was to assess the complications of intravesical BCG therapy and their management in NMIBC patients. Methods This was a retrospective descriptive study conducted between October 2016 and November 2019; a backward review of 149 patients with diagnosis of NMIBC that undergone intravesicle BCG therapy was performed. Patient’s demographical, clinical, diagnostic and procedural data regarding bladder tumour, BCG therapy, its complications and management were collected and analysed. Results Total 149 patients were analysed, comprising 116 males and 33 females. The mean age was of 57.2 ± 6.7 years. Total 85.23% were primary and 14.76% were recurrent tumours. Total 96 patients (64.42%) completed the planned course, while 53 (35.57%) interrupted. The reasons for BCG interruption includes adverse effects (15.4%), progression of disease (6.7%), disease refractory to BCG (4.6%) and disease recurrence during BCG (3.3%). Most of the adverse events occurred in first 6 months and most interruptions occurred after the induction period. Cystitis was the most common observed adverse effect seen in 39.6% patients. Frequency, urgency, haematuria were common presentation. Radical cystectomy was the most common (16.10%) further treatment with patients whose treatment was interrupted. Conclusion BCG is an indispensable therapy available for NMIBC, but it is associated with array of adverse effects and complications, which are the main reasons for poor compliance to BCG therapy. Although BCG-related complications can affect any organ in the body, potentially life-threatening systemic BCG-related infections are encountered in only

Higher yield and broad adaptation to drought-prone environments are key targets of wheat breeding programs. This can be achieved through a complete knowledge of the genetic architecture of yield and its related traits. This brief article provides analysed mean data used in the research article entitled “QTL mapping for nine drought-responsive agronomic traits in bread wheat under irrigated and rain-fed environments” (Gahlaut et al., 2017). Phenotypic data were recorded on nine important agronomic traits on a doubled haploid (DH) mapping population derived from the cross Kukri/Excalibur. For recording this data, the mapping population was grown during three crop seasons (2010–11 to 2012–13) at four separate locations in India, both under irrigated and rain-fed environments. This dataset is valuable for wheat breeders to better understand the genetic basis of drought tolerance in wheat.

Introduction: Penile fracture is rupture of corpora cavernosa which occurs when the rigid penis is forcibly bent against resistance, leading to the disruption of tunica albuginea. There is classical history and physical examination before reaching upon this diagnosis. Aim: To study the aetiology, clinical presentation and share the experience in evaluation and treatment of penile fracture. Materials and Methods: The retrospective study was carried out on 26 patients, admitted in surgical facility in SS Medical College and associated SGM Hospital, Rewa, Madhya Pradesh, India from January 2014 to December 2018. Patient details like, age, marital status, aetiology, clinical presentation, time interval from injury to presentation, investigation done, treatment given and intraoperative findings were assessed from the hospital records. Results: The main cause of penile fractures was sexual intercourse (65.38%) followed by manual manipulation (26.92%). Ultrasonography (USG) was used for confirmation of diagnosis with sensitivity and specificity of 87.5% and 100%, respectively. Surgical exploration and repair of injury was done in all patients. The unilateral corporal injuries were the most common finding (76.92%). Urethral injuries were found in 11.53%. Conclusion: Most of the time diagnosis of penile fracture can be made reliably by history and physical examination. USG can be useful adjunct in confirmation of diagnosis and planning of incision. Early surgical intervention is standard of care, because it is associated with a good outcome, regardless of the timing of presentation.

In the present study, effect of chitosan coating on storage quality of plum fruit (Prunus salicina Lindley. cv. Santa Rosa) was investigated under supermarket conditions during 2013 at ICAR-IARI. After coating the plum fruits with 2% chitosan and water, they were stored at 20±1°C and 90±2% RH for 15 days. Fruit firmness, colour characteristics (hue and chroma), respiration and ethylene evolution rate, physiological loss in weight, antioxidant activity and total phenols were measured along with the activities for pectin methylesterase and malondialdehyde content. Chitosan application resulted in better firmness of fruits, retarded ethylene evolution and respiration rates and least colour changes as compared with the control. Reduction of total phenolics and antioxidant activity were also significantly inhibited by chitosan. Furthermore, fruits coated with chitosan also exhibited a significantly lower pectin methylesterase activity throughout the storage period. Moreover, the production of malondialdehyde was significantly reduced in the coated samples. The results clearly demonstrate that dip treatment of fruits in 2% chitosan could be an effective means to enhance the shelf-life and maintain postharvest quality of Santa Rosa plums during storage.

This study is devoted to constructing an approximate analytic solution of the fractional form of a strongly nonlinear boundary value problem with multi-fractional derivatives that comes in chemical reactor theory. We construct the solution algorithm based on the generalized differential transform technique in four simple steps. The fractional derivative is defined in the sense of Caputo. We also mathematically prove the convergence of the algorithm. The applicability and effectiveness of the given scheme are justified by simulating the equation for given parameter values presented in the system and compared with existing published results in the case of standard derivatives. In addition, residual error computation is used to check the algorithm’s correctness. The results are presented in several tables and figures. The goal of this study is to justify the effects and importance of the proposed fractional derivative on the given nonlinear problem. The generalization of the adopted integer-order problem into a fractional-order sense which includes the memory in the system is the main novelty of this research.

Hopfield neural network (HNN) is considered as an artificial model derived from the brain structures and it is an important model that admits an adequate performance in neurocomputing. In this article, we solve a dynamical model of 3D HNNs via Atangana–Baleanu (AB) fractional derivatives. To find the numerical solution of the considered dynamical model, the well-known Predictor-Corrector (PC) method is used. A number of cases are taken by using two different sets of values of the activation gradient of the neurons as well as six different initial conditions. The given results have been perfectly established using the different fractional-order values on the given derivative operator. The objective of this research is to investigate the dynamics of the proposed HNN model at various values of fractional orders. Nonlocal characteristic of the AB derivative contains the memory in the system which is the main motivation behind the proposal of this research.

Here, we report the synthesis of the WS2 nanorods (NRs) using an eco-friendly and facile hydrothermal method for an acetone-sensing application. This study explores the acetone gas-sensing characteristics of the WS2 nanorod sensor for 5, 10, and 15 ppm concentrations at 25 °C, 50 °C, 75 °C, and 100 °C. The WS2 nanorod sensor shows the highest sensitivity of 94.5% at 100 °C for the 15 ppm acetone concentration. The WS2 nanorod sensor also reveals the outstanding selectivity of acetone compared to other gases, such as ammonia, ethanol, acetaldehyde, methanol, and xylene at 100 °C with a 15 ppm concentration. The estimated selectivity coefficient indicates that the selectivity of the WS2 nanorod acetone sensor is 7.1, 4.5, 3.7, 2.9, and 2.0 times higher than xylene, acetaldehyde, ammonia, methanol, and ethanol, respectively. In addition, the WS2 nanorod sensor also divulges remarkable stability of 98.5% during the 20 days of study. Therefore, it is concluded that the WS2 nanorod can be an excellent nanomaterial for developing acetone sensors for monitoring work/public places.