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This paper examines agricultural financing and technological advances (fertilizer and irrigation) to mitigate the effect of climate change (temperature and rainfall) on Uttar Pradesh. Augmented Dickey–Fuller and P.P. test was used to identify variable unit roots test. Autoregressive distributed lag (ARDL) and Error correction model (E.C.M.) estimated long and short-run parameters for selected variables in Uttar Pradesh from 1990-91 to 2020-21. ARDL bounds testing indicated long-term co-integration between variables. This study revealed that In Uttar Pradesh, rainfall increased sugarcane output Increased, but temperature decreased. Long-term agricultural credit enhanced sugarcane output. The policy implication/recommendation or suggestion that it is used to invest in modern technology to production was maximum. The fertilizer improved and then increased sugarcane yield, showing that technology is crucial. This report recommends more comprehensive agricultural policies to suit the sector's financial demands and boost production technologies.

Objective: To compare the diagnostic accuracy of Computed Tomography and Ultrasonography in differentiating trans-dative and exudative pleural effusion. Study Design: Cross-sectional study. Place and Duration of Study: Radiology Department of Pakistan Institute of Medical Sciences, Islamabad Pakistan, from Jul to Oct 2021. Methodology: Patients suffering (n=80) from pleural effusion were involved, and all were assessed with ultrasound and computed Tomography along with diagnostic thoracocentesis. In addition, we investigated pleural thickening, pleural nodules, and loculations along with the USG signs and Computed Tomography attenuation values to detect transudate and exudate in individuals suffering from pleural effusion. Results: Participants had a mean age of 36.20±6.67 years, ranging from 25 to 49 years. Out of 80 patients, 50(62.5 %) were males, and 30(37.5%) were females. Of the eighty patients with pleural effusion, 29 were transudative 36(25%), and 51 were exudative 63(75%). Overall, USG showed better results for loculations, while CT showed better results for pleural thickeningand nodules. Conclusion: Attenuation values of Computed Tomography play an essential role in differentiating the type of pleural effusion. In addition, ultrasound is a supporting non-invasive imaging modality that helps define the characteristics of pleural effusion.

Objective: To evaluate the renal resistive index (RI) and serum creatinine correlation in patients with diabetic nephropathy. Study Design: Cross-sectional study Place and Duration of Study: Department of Radiology, Pakistan Institute of Medical Sciences, Islamabad Pakistan, from Nov 2020 to Apr 2021. Methodology: This study was conducted on 80 patients. Doppler renal artery sonography was carried out, and for all the individuals with controlled blood pressure, gender, age, urinary protein, serum creatinine and HBA1c were recorded. Results: In our study, 42(52%) patients were females, whereas the remaining 38(48%) were males. The mean age was observed to be 49.15±11.91 years. A significant positive correlation (r=0.53) was found between Resistive Index and Serum Creatinine.The correlation co-efficient values between Resistive Index and Serum Creatinine in female and male patients were r=0.58 and r=0.47, respectively. Conclusion: The present study concluded that RI had no significant statistical correlation with albuminuria, proteinuria and HbA1c levels. However, a statistical correlation between RI and creatinine level was reported.

Background: The diabetes mellitus is an old known disease and closely related to the renal impairment as a cause. The exact duration for any damage to renal functions is not known but early detection of any such happening is a requirement. Many measures explain the renal damage, proteinuria is one among them. Still it appears after some damage is done. Aim: To measure the RRI for renal arteries and find frequency of diabetic nephropathy among type II diabetic patients with normal albuminuria. Methods: It was a cross-sectional study performed at Shaikh Zayed hospital Lahore, in collaboration of Diabetes Clinic and Radiology Department during January 2020 to January 2021. Here 300 diabetic patients of type 2, with normal albumin creatinine ratio were selected. Both genders with age above 18 years with albuminuria below 30 mg/g and no known diabetic nephropathy were included. Pregnant women, patients with GFR 0.70. Conclusion: Renal resistive indexcan diagnose diabetic nephropathy at early stage. Keywords: Diabetic nephropathy, Renal resistivity index, Type II diabetes mellitus, Normal albuminuria

This study investigated wheat crop area, production, and yield in Uttar Pradesh. Wheat crop data from 1990-91 to 2019-20 were obtained. Compound growth rate and trend analysis show that wheat crop area has reduced due to shift of rabi crops. The growth in Uttar Pradesh's per-hectare yield boosted wheat production from 1990-91 to 2019-20. The methods were calculated indicate use of semi log trend function and Johansen cointegration results, which reveal that number of irrigations affects wheat production. The study founds that cropping intensity, fertilizer, and transportation positively affected wheat production.

The integration of hydrogen in the primary energy mix requires a major technological shift in virtually every energy-related application. This study has attempted to investigate the techno-economic solar photovoltaic (PV) integrated water electrolysis and waste incineration system. Three different strategies, i.e., (i) PV + Battery(Hybrid mode with required batteries); (ii) auto-ignition (Direct coupling); and (iii) PV + Secondary-Electrolyzer(Direct coupling assisted with secondary electrolyzer), have been envisioned. The 'PV + Battery' consume 42.42 % and 15.07 % less energy than the auto-ignition and 'PV + Secondary-Electrolyzer' methods. However, the capital cost of 'PV + Battery' has been calculated to be 15.4 % and 11.8 % more than auto-ignition and 'PV + Secondary-Electrolyzer, respectively.The energy consumption relative to waste input, the 'PV + Battery' method used 80 % less energy, while auto-ignition and 'PV + Secondary-Electrolyzer' showed 70.5 % and 77.5 % less energy, respectively. Furthermore, these approaches showed a vast difference in cost-benefit for the longer run. 'PV + Battery' was forecasted to be 73.3 % and 23.3 % more expensive than auto-ignition and 'PV + Secondary-Electrolyzer' methods, respectively, for 30 years. Overall, this study can benefit from using either of these methods depending on the application, usage scale, and climatic conditions.

Growth analysis is commonly used throughout time to determine the trend of a certain variable and utilized in economic research to make policy choices. The exponential function predicted the compound increase in area, production, and yield of main food grains in Uttar Pradesh. Secondary data were gathered during a 70-year era, from 1950-51 to 2018-19. In Uttar Pradesh, growth in the area, production, and yield of main food grains such as rice and wheat were positive and substantial from 1950 to 2019. However, the rice area grew at a little negative pace. Wheat was discovered to be one of the most popular crops among major food grains, with the largest yearly growth in area, production, and yield. However, efforts should be made to rise the area under other major food grains (rice, wheat) with high-quality seeds of improved varieties, improved food grain production technology, price, marketing support, and effective extension mechanization to boost productivity of major food grains.

Mechanochromic, tough and healable polyurethane films are synthesized and their properties are thoroughly characterized. The optimum films are utilized to explore the potential applications of shape memory and flexible capacitor devices.

A Haar wavelet collocation method (HWCM) is presented for the solution of Riccati equation subject to the two-point and integral boundary condition. The qua?silinearization technique is applied to linearized the Riccati equation and then the linearized equation with boundary condition is solved by converting into system of algebraic equation with the help of Haar wavelets. We have considered three different form of Reccati equation, two having integral boundary condition and one with two-point boundary condition. The numerical results obtained by HWCM are stable, efficient and convergent.

Background: Coronary artery anomalies are infrequent findings during coronary angiography and may result in longer radiation time and increase the risk of complications. Insufficient knowledge of coronary anomaly may lead to accidental damage of vessels during cardiac surgery. This study aimed to estimate the prevalence of coronary artery anomalies among the patients underwent coronary angiography at our center. Methods: A retrospective study was conducted at Chitwan Medical College. Coronary angiography records of all patients from 1st April 2020 to 30th April 2022 were analyzed by two interventional cardiologists. Statistical analysis was done using Statistical package for social survey, Version 20.0 for windows. The categorical variables were presented as numbers or percentages (%) and continuous variables were presented as mean ± standard deviation. Results: A total of 1015 patients who underwent coronary angiography for various indication were included. Coronary artery anomalies were observed in 21 (2.1%) patients. Among anomalies most common was anomalies of origin 16 (76.2%) followed by anomalies of intrinsic coronary artery 5 (23.8%). Separate origin of the conus branch was the most common coronary artery variation 103 (10.1%). Conclusions: The prevalence of coronary artery anomalies in present study was similar to many large sample size previous studies from different geographical area. However present study reflects scenario of our population, which may be helpful for interventional cardiologist and cardiac surgeon during coronary angioplasty and cardiac surgery.

Background: The virulent pathogen SARS-CoV-2 first appeared in the Chinese province of Hubei in December 2019. Pregnant women were a high-risk population in the pandemic because immune system alterations that occur during pregnancy make them more vulnerable to foreign infections. Late-pregnancy cholestasis is a dangerous liver condition that can cause the foetus to experience potentially fatal problems like early birth and stillbirth. In the present study we were testing the Bile acid level during pregnancy patients after covid pandemic. Objectives: To evaluate the prevalence of intrahepatic cholestasis in pregnant patients after Covid -19 pandemic. Materials and Methods: This cross-sectional study was conducted at department of Dr.fida painless and General Hospital Peshawar from jan 2022 to Dec 2022. We enrolled 186 pregnant patients after fulfilling the inclusion criteria. 5 ml blood sample were also taken from the patients. Serum was extracted and Bile acid test were performed in clinical laboratory. Data were collected in predesign questionnaire. Results: Total 186 patients were enrolled in the study with mean age of 37.18±6.39 years (Range 18-45 years). The mean value of all enrolled patients was 31.38±5.79 with minimum and maximum value of bile acids 20 micromol/L and 40.6.00 micromol/L. In our study 95 (56.5%) of patients belongs to 36 to 45 years of age group followed by age group of 26 to 35 years in which 60 (35.7%) patients and 13 (7.7%) patients were belongs to age group of 18 to 25 years. Practical implication: This study will help the clinical practitioner to take care of pregnant patients in order to avoid the prevalence of intrahepatic cholestasis. Conclusion: It is concluded from this research study that prevalence of intrahepatic cholestasis in pregnancy has increased after Covid-19 pandemic. Keywords: COVID-19, cholestasis, pregnancy, elevated Liver Enzyme, Bile Acids.

Aim: To examine the effect of elements of emotional distress like diminished quality of life, loss of enjoyment, cognitive changes, embarrassment, psychological trauma and loss of sleep on person’s perception towards illness and how these elements influence self-care management of patients and their adherence to treatment. Methodology: Four number of questionnaires were used to collect data having high reliability and validity from 1000 patients in different areas of Pakistan. Results: The results revealed a significant relationship of psychological distress, illness perception, self care management and adherence to medication. Conclusion: Based on these findings, the greater the psychological distress, the more would be the negative effects on illness perception, self-care management and adherence to medication. Keywords: Psychological distress, illness perception, self-care management and adherence to medication.

Background: The cancer antigen 125 “CA125” and Human Epididymis protein 4 “HE4” are among some well worked out markers for recognition of malignancy in ovarian tumors. Their different cutoffs are determined and reported by various studies and mostly used recommended cutoffs are 35.0 U/mL for CA125 and 140pmol/L for HE4. They are both reported to recognize the malignancy well, but how specific they are for benign gynecological diseases is still needed to be worked out. Aim: To determine and compare the performance of CA125 and HE4 for benign gynecological pathologies. Methodology: A cross-sectional study was performed at Gajju Khan Medical College in collaboration with Armed forces Institute of pathology (AFIP). A total of 76 women of age above 18 years age, with benign ovarian pathology, confirmed through histological evaluation were enrolled. All these were examined on both markers, i.e. CA125 and HE4. Standard cutoffs of CA125 >35.0 U/mL and HE4>140 pmol/L were used to see if the case was labeled malignant, incorrectly. SPSS 20.0 was used to manage and analyze the data. Performance of the two markers were compared by using some descriptive analysis and using chi-square test. P-value ≤0.05 was considered significant. Results: The median age of these women was 40 years ranging between 18 and 71. Majority (86.8%) was premenopausal, The CA125 had no difference between pre and post-menopausal women but HE4 had a significant difference with p-value 0.029. there were 10.5% incorrect labeling of malignancy when evaluated for CA125, while only 2.6% incorrect on HE4. This difference was found statistically significant between two markers with p-value 0.05. Conclusion: HE4 is better and more specific marker for benign gynecological pathologies as compared to CA125 Keywords:Benign Ovarian Epithelial, Human epididymisprotein (HE4), Cancer Antigen 125 (CA125), Specificity

Background: The prevalence of right bundle branch block (RBBB) is estimated in 0.2 to 1.3% of healthy people. RBBB had independent association with decreased right ventricle (RV) function, which is considered as predictor of adverse cardiovascular outcomes. The aim of this study is to evaluate RV structure and function in patients with isolated RBBB (without structural heart disease) using two-dimensional echocardiography. Methods: A cross-sectional study conducted at Chitwan Medical College, Bharatpur from 1st January 2022 to 30th June 2022. Consecutive adult patients aged ≥18 years with isolated RBBB classified into complete RBBB (CRBBB) and Incomplete RBBB (IRBBB) based on electrocardiographic findings. The echocardiographic evaluation was done to assess RV dimension and function. Results: A total of 52 patients with isolated RBBB were included with mean age of the study population was 45.3 ± 9.3 years, (28 ,53.8%) had CRBBB, whereas the remaining (24, 46.2%) had IRBBB. Among the parameters used to assess RV function; mean RV-Fractional area change (P

This study aims to provide a thorough evaluation for the changes in the microstructure and evolution of strength of highly reactive clays that were treated with 7% lime over a period of curing time as a function of the mixing moisture content. Three series of testing were carried out on specimens with 100%, 85% and 75% of bentonite content and prepared with different moisture content of 10, 20, 30 and 40% above the corresponding optimum moisture content. Specimens of 100% bentonite were treated with 7% of lime, compacted to achieve a predetermined dry unit weight and cured at temperatures of 20 °C and 40 °C for up to 28 days whereas the specimens with 85% and 75% of bentonite content were prepared by the addition of sand and were cured at 20 °C for up to 7 days. Unconfined Compressive Strength tests and Scanning Electron Microscopy were conducted to observe the strength and the microstructural changes resulting from increasing mixing moisture content. California Bearing Ratio and Resilient Modulus were correspondingly determined based on correlations with the Unconfined Compressive Strength. The failure pattern was also studied to better understand the ultimate behaviour of lime stabilised clays. The results revealed that the strength of treated bentonite increased with the increase in the moisture content up to 30% above the corresponding optimum moisture content and with increasing the curing time and temperature. Nevertheless, substituting bentonite with sand on the specimen resulted in a significant reduction on the attained strength. Furthermore, the results of California Bearing Ratio and Resilient Modulus showed that values for both parameters are significantly enhanced with lime treatment. The microstructural analysis provided visual evidence to the improved strength in which the pozzolanic reaction was found to be significantly affected by the amount of moisture in the mixture. The results suggested that compacting lime treated expansive clays with moisture content moderately higher than the optimum moisture content would result in a significant enhancement to the attained strength over the period of curing.

Healthcare professionals consider predicting heart disease an essential task and deep learning has proven to be a promising approach for achieving this goal. This research paper introduces a novel method called the asynchronous federated deep learning approach for cardiac prediction (AFLCP), which combines a heart disease dataset and deep neural networks (DNNs) with an asynchronous learning technique. The proposed approach employs a method for asynchronously updating the parameters of DNNs and incorporates a temporally weighted aggregation technique to enhance the accuracy and convergence of the central model. To evaluate the effectiveness of the proposed AFLCP method, two datasets with various DNN architectures are tested, and the results demonstrate that the AFLCP approach outperforms the baseline method in terms of both communication cost and model accuracy.

Cancer, including the highly dangerous melanoma, is marked by uncontrolled cell growth and the possibility of spreading to other parts of the body. However, the conventional approach to machine learning relies on centralized training data, posing challenges for data privacy in healthcare systems driven by artificial intelligence. The collection of data from diverse sensors leads to increased computing costs, while privacy restrictions make it challenging to employ traditional machine learning methods. Researchers are currently confronted with the formidable task of developing a skin cancer prediction technique that takes privacy concerns into account while simultaneously improving accuracy. In this work, we aimed to propose a decentralized privacy-aware learning mechanism to accurately predict melanoma skin cancer. In this research we analyzed federated learning from the skin cancer database. The results from the study showed that 92% accuracy was achieved by the proposed method, which was higher than baseline algorithms.

This study aims to develop an efficient and accurate breast cancer classification model using meta-learning approaches and multiple convolutional neural networks. This Breast Ultrasound Images (BUSI) dataset contains various types of breast lesions. The goal is to classify these lesions as benign or malignant, which is crucial for the early detection and treatment of breast cancer. The problem is that traditional machine learning and deep learning approaches often fail to accurately classify these images due to their complex and diverse nature. In this research, to address this problem, the proposed model used several advanced techniques, including meta-learning ensemble technique, transfer learning, and data augmentation. Meta-learning will optimize the model’s learning process, allowing it to adapt to new and unseen datasets quickly. Transfer learning will leverage the pre-trained models such as Inception, ResNet50, and DenseNet121 to enhance the model’s feature extraction ability. Data augmentation techniques will be applied to artificially generate new training images, increasing the size and diversity of the dataset. Meta ensemble learning techniques will combine the outputs of multiple CNNs, improving the model’s classification accuracy. The proposed work will be investigated by pre-processing the BUSI dataset first, then training and evaluating multiple CNNs using different architectures and pre-trained models. Then, a meta-learning algorithm will be applied to optimize the learning process, and ensemble learning will be used to combine the outputs of multiple CNN. Additionally, the evaluation results indicate that the model is highly effective with high accuracy. Finally, the proposed model’s performance will be compared with state-of-the-art approaches in other existing systems’ accuracy, precision, recall, and F1 score.

This paper presents a volume measurement system based on image processing. The suggested plan offers reasonable costs, good accuracy, and convenience of manpower. The extra specifications like item alignment during measurement and putting the objects at a specific Place in the measurement area. Instead of using a single cell phone for the measurement, two cameras will be used, each of which will be positioned on a different plane to increase precision. To speed up processing, the application will be created on an Android platform and only be available on mobile devices. For precise measurement, images will be taken from two distinct perspectives (one from a top view and the other from a side view). First, a calibration procedure tailored to the problem at hand was carried out, and after that, the Hough transform was used throughout the image processing stage. The proposed method gives a rough volume measurement for objects with random shape even though it was originally designed to assess the volume of box-type objects. The system will yield satisfactory results when tested with different external disturbances.

Introduction: Information on the cardiac manifestations of coronavirus disease 2019 (COVID-19) is scarce. In this study we assessed the echocardiogram of consecutive patients with COVID-19 infection to assess the frequency of cardiac abnormalities. Materials and Methods: This retrospective descriptive study examined the echocardiographic study of 43 patients with severe and critical COVID-19 infection admitted at the ICU of Chitwan Medical College from May 16, 2021 to June 05, 2021. The study focused on left ventricle (LV) and right ventricle (RV) function. The results were then compared between severe and critical infections to examine if any differences exist between them. Results: The mean age of the study population was 54 years and predominately males. One-third were classified as critical COVID-19 while the remaining were severe COVID-19. Majority(83.7%) had a normal echocardiogram. Among the patients with abnormal reports, the distribution of echocardiographic pattern were biventricular dilation with biventricular dysfunction in two patients (4.6%), LV dialtion with LV dysfunction in two patients (4.6%) and isolated LV dysfunction (diastolic and systolic) in three patients (6.9%). None of the echocardiographic parameters were significantly different between the severe and the critical infection. Conclusion: COVID-19 in primarily a respiratory disease and the cardiac complications is largely attributed to the critical nature of the illness than the specific infection. Considering the risk of infection spread, routine echocardiography for all patients with COVID-19 infection is not advisable.

In this article, we study the dynamics of Norovirus infection by developing a stochastic epidemic model having Levy noise. The study shows that Levy noise and informative interventions have more influence on the said dynamics. Firstly, we show that the model has a unique global positive solution. After this, we formulated a stochastic threshold value as a necessary condition for the extinction and persistence in the mean of the proposed epidemic model. Finally, numerical simulation are drawn to verify our obtained results of the dynamics. The perturbed stochastic approach may affect the dynamical properties of the model and large noises will be greatly significant to minimize its transmission.

India is second most densely country in the world having 125.08 crore of population (census 2011) and about 60% population engage in agriculture both directly or indirectly. With the improvement of technology to feed the population and growth of economy cropping pattern affect change over period of time. Changing cropping pattern shows need and desire of population and for the sake of country’s Economy. Cropping patterns in the Chandauli district of Uttar Pradesh and their changes through time are the key topics of discussion in this study (2010 to 2020). Cropping is a fluid idea that evolves throughout time. However, the study also identified the elements that influence changes in cropping patterns in the study area over time, including technological advancements, farmer rationality, educational attainment, and government intervention in the agriculture sector. The data for the study was gathered from secondary sources and taken from the Statical Handbook. Rice and wheat are the most important crops, accounting for over 90% of net seeded area from 2010 to 2020

To assess the use of intraoperative IV ketorolac (Toradol) on the peri-operative total morphine milligram equivalent (MME) requirements of patients undergoing ureteroscopy for nephrolithiasis.Patients undergoing ambulatory ureteroscopy for nephrolithiasis were randomized to receive ketorolac at time of anesthesia induction. Patients and surgeons were blinded to treatment. Intraoperative, postoperative and combined MME were calculated. Multivariable regression was used to identify independent predictors of MME requirement. Complications were recorded.A total of 94 patients were analyzed following randomization. There were 46 patients in the treatment arm and 48 patients in the control arm. There were no statistically significant differences in gender, age, BMI, operative length or baseline pain medication use between groups (P.05). Patients in the treatment arm required lower intraoperative MME when compared to the control arm (17.1 vs 24, P.01). There were no statistically significant differences in the postoperative MME requirements between groups. The combined peri-operative MME was lower in the treatment arm compared to the control arm (22.2 vs 30.4, P.02). Ketorolac use was an independent predictor of lower MME use on multivariable analysis (beta coefficient -5.1, P.01). There was no statistically significant difference with regards to complication numbers between the treatment arms.Ketorolac during ureteroscopy is associated with a 37% reduction in narcotic requirement and is an independent predictor of decreased peri-operative narcotic needs. These findings show that intra-operative use of ketorolac effectively reduces narcotic requirements and should be considered independently or as part of a multimodal pain control protocol, unless otherwise contraindicated.

PurposeTo provide human judgment input for computer algorithm development, this study examines the relative importance of source, content, and style cues in predicting the truthfulness ratings of two common types of online health information: news stories and institutional news releases.Design/methodology/approachThis study employed a multi-method approach using (1) a manual content analysis of 400 randomly selected online health news stories and news releases from HealthNewsReview.org and (2) an online experiment comparing truthfulness ratings between news stories and news releases.FindingsUsing content analysis, the authors found significant differences in the importance of source, content, and style cues in predicting truthfulness ratings of news stories and news releases: source and style cues predicted truthfulness ratings better than content cues. In the experiment, source credibility was the most important predictor of truthfulness ratings, controlling for individual differences. Experts have higher ratings for news media stories than news releases and lay people have no differences in rating the two news formats.Practical implicationsIt is important for health educators to curb consumer trust in misinformation and increase health information literacy. Rather than solely reporting scientific evidence, educators should focus on addressing cues people use to judge the truthfulness of health information.Originality/valueThis is the first study that directly compares human judgments of health news stories and news releases. Using both the breadth of content analysis and experimental causality testing, the authors evaluate the relative importance of source, content, and style cues in predicting truthfulness ratings.

After more than 4 Earth years of operation on the martian surface monitoring the planet’s ground vibrations, the InSight’s seismometer is now retired. Throughout the mission, analyses of body waves from marsquakes and impacts have led to important discoveries about the martian interior structure of the crust, mantle, and core. Recent detection of surface waves, together with gravimetric modeling enabled the characterization of crustal structure variations away from the InSight landing site and showed that average crustal velocity and density structure is similar between the northern lowlands and the southern highlands. Especially for the observed overtones and multi-orbiting surface waves in S1222a, we find the depth sensitivity expands down to the uppermost mantle close to 90 km. Furthermore, our 3D wavefield simulations show significantly broadened volumetric sensitivity of the higher-orbit surface waves. These new constraints obtained by our surface wave analyses provide an important opportunity not only to refine and verify our previous radially symmetric models of the planet’s interior structure but also to improve understanding of seismo-tectonic environments on Mars. Here, we summarize our recent effort in the analyses of surface waves on Mars and discuss the inferred crustal property and its global implications.

Contamination of water resources by industrial effluents containing heavy metal ions and management of solid waste from agricultural and food industries is a serious issue. This study presents the valorization of waste walnut shells as an effective and environment-friendly biosorbent for sequestrating Cr(VI) from aqueous media. The native walnut shell powder (NWP) was chemically modified with alkali (AWP) and citric acid (CWP) to obtain modified biosorbents with abundant availability of pores as active centers, as confirmed by BET analysis. During batch adsorption studies, the process parameters for Cr(VI) adsorption were optimized at pH 2.0. The adsorption data were fitted to isotherm and kinetic models to compute various adsorption parameters. The adsorption pattern of Cr(VI) was well explained by the Langmuir model suggesting the adsorbate monolayer formation on the surface of the biosorbents. The maximum adsorption capacity, qm, for Cr(VI) was achieved for CWP (75.26 mg/g), followed by AWP (69.56 mg/g) and NWP (64.82 mg/g). Treatment with sodium hydroxide and citric acid improved the adsorption efficiency of the biosorbent by 4.5 and 8.2%, respectively. The endothermic and spontaneous adsorption was observed to trail the pseudo-second-order kinetics under optimized process parameters. Thus, the chemically modified walnut shell powder can be an eco-friendly adsorbent for Cr(VI) from aqueous solutions.