Trajectory and window width predictions for a cased hole sidetrack using a whipstock

The Trackmaster system manufactured by Smith Services consists of a multi-ramped whipstock and a trimill assembly used to perform a sidetrack from a cased well. Smith Services has observed evidence that the trimill assembly may prematurely leave the face of the whipstock and build excess inclination and dogleg severity or may fall into the original well immediately after leaving the end of the whipstock ramp thus creating a need to predict the borehole trajectory for sidetracking operations. The goal of this project was to predict the borehole trajectory and the window profile cut in the casing by the sidetracking equipment and the curvature that would result in tubular run through the sidetracked borehole, expressed as dogleg severity. A computer program was developed that predicts the sidetrack trajectory based on the BHA analysis method proposed by Jiazhi, and extended for calculating the side force on the mills. These side forces and a logical check on the feasibility of that force within the existing well geometry were used to predict the trajectory of each mill. A method was developed to calculate and plot the paths traversed by each mill and the width of the window subsequently cut by trimill assembly moving down the face of the whipstock. Results obtained from the simulator, for selected cases of tool geometries, hole sizes and resistance to sidetracking, indicate an overall dropping tendency of the mill assembly and no tendency to prematurely leave the face of the whipstock. Therefore premature departure of the trimill assembly from the whipstock is unlikely to be caused by BHA design but may be related to some other factor such as the interaction of the mill profile with the casing wall. Further, a method was developed to calculate the radius of curvature for a specific size pipe run in the predicted trajectory for a sidetracked borehole, based on pipe diameter and wellbore geometry. The curvature was expressed as dogleg severity in degrees of inclination change per 100 ft and provides a basis for determining whether the sidetracked borehole is suitable for its intended purpose

Investigation of Image Enhancement Techniques for Advancing Colon Cancer Diagnosis

Colorectal cancer continues to pose a substantial worldwide health challenge, necessitating the development of advanced imaging techniques for early and accurate diagnosis. In this study, we propose a novel hybrid image enhancement approach that combines Total Variation (TV) regularization and shift-invariant filtering to improve the visibility and diagnostic quality of colon cancer images. The Total Variation regularization technique is employed to effectively reduce noise and enhance the edges in the input images, thereby preserving important structural details. Simultaneously, shift-invariant filtering is utilized to address spatial variations and artifacts that often arise in medical images, ensuring consistent and reliable enhancements across the entire image. Our hybrid approach synergistically integrates the strengths of both TV regularization and shift-invariant filtering, resulting in enhanced colon cancer images that offer improved contrast, reduced noise, and enhanced fine structures. This improved image quality aids medical professionals in better identifying and characterizing cancerous lesions, ultimately leading to more accurate and timely diagnoses. To evaluate the effectiveness of the proposed approach, we conducted extensive experimentations on a diverse dataset of colon cancer images. Quantitative and qualitative assessments demonstrate that our hybrid approach outperforms existing enhancement methods, leading to superior image quality and diagnostic accuracy. In conclusion, the hybrid image enhancement approach presented in this study offers a promising solution for enhancing colon cancer images, contributing to the early detection and effective management of this life-threatening disease. These advancements hold significant potential for improving patient outcomes and reducing the burden of colon cancer on healthcare systems worldwide

Image Enhancement of Colon Cancer Images using a Two-Stage Hybrid Approach of TV and Shift-Invariant Filtering

Medical imaging holds a critical position in both disease diagnosis and treatment strategies, including colon cancer. However, the quality of medical images can often be compromised by noise and artifacts, making accurate interpretation challenging. Here, we suggest a innovative two-stage hybrid method aimed at enhancing colon cancer images, leveraging the strengths of Total Variation (TV) denoising and shift-invariant filtering techniques. The primary objective of this study is to increase visual superiority as well as diagnostic accurateness of colon cancer image while preserving crucial anatomical information.The first stage of our approach employs Total Variation (TV) denoising to reduce noise and enhance image contrast. TV regularization is known for its ability to preserve edges and fine details, making it well-suited for medical image enhancement. In the second stage, we apply shift-invariant filtering to further enhance the image quality. This technique is designed to address the limitations of traditional filtering methods and adapt to the specific characteristics of colon cancer images. To evaluate the effectiveness of our hybrid approach, we conducted a comprehensive set of experiments using a relevant dataset. We employed a range of quantitative metrics, including the Global Relative Error (EGRAS), Root Mean Squared Error (RMSE), Universal Image Quality Index (UQI), and Pixel-Based Visual Information Fidelity (VIFP), to assess the quality and fidelity of enhanced images. Our results demonstrate that the hybrid combination consistently outperforms existing methods, yielding superior image quality and diagnostic potential. This study makes a valuable contribution to the realm of medical imaging by introducing a robust and effective method to improve the quality of colon cancer images. Findings suggest that the proposed two-stage hybrid method holds promise for improving the accuracy of diagnosis and treatment planning. Further research in this direction may lead to advancements in medical image enhancement techniques, ultimately benefiting patient care and medical research

Freshness Detection and Classification of Chicken Eggs using Spectroscopy

The poultry industry plays a pivotal role in India's economy, with particular emphasis on egg production. India ranks as the world's third-largest producer of chicken eggs. Eggs are a delicate component of the human diet, and their quality can undergo substantial changes during storage. This has implications for egg quality and the classification of chicken eggs, both of which are critical factors affecting the poultry sector. Globally, numerous chicken breeds are being developed, necessitating the classification of eggs based on breed due to varying atmospheric conditions required for their storage. However, in India, there is a lack of technical methods for classifying eggs from different chicken breeds. The primary challenges faced by the poultry industry in India revolve around maintaining egg freshness and accurately classifying eggs by breed. While developed countries employ grading systems for eggs, this practice is less common in developing nations like India. To address these challenges, this study aims to propose a model that utilizes spectroscopy as a non-destructive method for assessing egg quality and freshness. The model seeks to establish a link between spectral data, collected using a handheld SCiO NIR spectrometer with wavelengths ranging from 740nm to 1070nm at a spectral resolution of 1 nm, and established destructive methods, particularly Haugh Units, to determine egg freshness based on storage duration

FORMULATION AND CHARACTERIZATION OF CYCLODEXTRIN BASED CURCUMIN LOADED NANOSPONGE

Objective: The aim of proposed work is to develop and screen cyclodextrin based Nanosponge loaded with poorly soluble anticancer drug and to optimize most suitable Nanosystem with increased solubility and dissolution rate. Methods: Cyclodextrinnanosponge (CDNS) was prepared using pyromelliticdianhydride as a crosslinker for beta cyclodextrin monomer. Cyclodextrinnanosponge and curcumin were taken in 1:1 w/w proportion. The resultant curcumin loaded nanosponges were dried at 50±0.5 °C for 24 h. Results: The absorbance maxima for Curcumin was seen at 424.0 nm and for cyclodextrin was seen at 290.0 nm, The average melting point of pure drug is 181 °C which is complies with Stander melting point of drug and the aspect ratio of the nanosponge was found 1.037. Zeta potential noticed for CUR-CD-NS were more negative contrasted with separate plain CUR (−20.1±1.57) demonstrating solidness of the nanodispersion. Curcumin release from CUR-CDNS was upgraded to very nearly 10 folds toward the finish of 8 hour. Treatment with a combination of CUR-CDNS at 1:1 and 1:3 ratios resulted in an IC50 value was found 14.98 μg/ml. Conclusion: In vitro cytotoxicity study and combination index analysis showed the synergistic effect of CUR-CDNS against MCF-7 cells. The present study reveals that the combination of curcumin results in higher cytotoxicity against breast cancer cells

PHARMACEUTICAL ANALYTICAL STUDY OF KAMPAVATARI RASA - AN AYURVEDIC HERBO MINERAL FORMULATION

Kampavatari Rasa (KVR) is a unique Ayurvedic herbo- mineral formulation mentioned in the classics Rasa Raj Sundar in Vata vyadhi and indicated mainly in Kampavata which resembles Parkinson's disease. The line of treatment in Ayurveda is to combat Vata dosha and to sustain neuronutrition by Rasayana remedies, which can be achieved by Kamapavatari Rasa with its properties like Tridosh shamaka and Rasayana. The present study was executed to establish a finger print for this unique formulation which can be used further for drug standardization. Kampavatari rasa is prepared by triturating Tamra bhasma and Rasa Sindura in equal quantity with Katuki swaras (Picrohiza kurroa) for 21 times. Each ingredient was prepared according to the norms of Ayurvedic classical texts. Raw drugs were selected on bases of Grahya lakshana and its percentage. To ensure the proper preparation of Tamra bhasma, standard tests (Bhasma Pariksha), XRD, NPST and SEM were carried and for Rasa sindura NPST test and XRD were employed. After been complied these tests KVR was prepared and subjected for physico chemical analysis and quantitative analysis of Mercury, Sulphur and Copper by ICPAES. The study of Kampavatari Rasa revealed that its Loss on Drying - 3.4%, Total Ash - 48 %, Acid insoluble ash -13%, water soluble ash - 9.5%, Hardness test was 7kg/cm2 and Tablet disintegration test 14/min which are within the normal limits and ICP – AES shows the percentage of Copper 20.51, Sulphur 8.9, and Mercury 20.43. This is the first study to establish the characterization of Kampavatari rasa

STUDY OF RATIONAL PRESCRIBING AND DISPENSING OF PRESCRIPTIONS WITH NONSTEROIDAL ANTI-INFLAMMATORY DRUGS IN ORTHOPEDIC OUTPATIENT DEPARTMENT

ABSTRACTObjective: To study the prescribing pattern of non-steroidal anti-inflammatory drugs (NSAIDs) in outpatient orthopedic hospitals from a rural areaof Maharashtra, India.Methods: A total of 237 prescriptions containing NSAIDs evaluated for their distribution according to the classification of NSAIDs and World HealthOrganization core indicators for prescribing practices and patient care.Results: The average number of drugs per prescription was 3.5. The average number of NSAIDs per prescription found to be 1.12. The incidenceof generic prescribing was very low. The overall average consultation time and dispensing time found to be 4.5 and 1.9 minutes respectively.The percentage of drugs adequately labeled was 61.44%. Out of the 843 drugs, 267 were systemic NSAIDs, of which 50.56% and 49.43% usedas monotherapy and fixed dose combinations respectively. The prescriptions are containing either one or two NSAIDs. Non-selective NSAIDs mostcommonly prescribed than selective cyclooxygenase-2 (COX2) inhibitors and highly selective COX2 inhibitors. The ratio of non-selective to selectiveNSAID usage pattern was 1:1.28.Conclusion: The study shows more use of traditional NSAIDs and underutilization of COX2 inhibitors. The study suggests that there is the immensescope of improvement for prescribing in the hospitals.Keywords: Prescribing pattern of non-steroidal anti-inflammatory drugs, Rational use of non-steroidal anti-inflammatory drugs, World HealthOrganization core drug use indicators

Role of triple phase computed tomography findings for evaluation of hepatic lesions

Background: Liver is prone to various diseases including benign and malignant because of its major function of digestion, detoxification and rich blood supply by hepatic artery and portal vein. Objectives of the study were to study the characteristic features of various hepatic lesions using triple phase CT as diagnostic modality, differentiating benign hepatic lesions from malignant and correlating findings of triple phase CT with clinical, histopathology or post-operative findings for calculation of its efficacy.Methods: A total of 100 patients were enrolled in this cross-sectional study done in Department of Radiodiagnosis, Gandhi Medical College, Bhopal, Madhya Pradesh, India. All patients underwent triple phase CECT examination and its accuracy, sensitivity and specificity was calculated.Results: Triple phase CT  be excellent diagnostic modality for characterisation and better evaluation of hepatic masses with sensitivity of 91.3% , specificity 97.8% , PPV 91.3% and NPV 97.8% (p value<0.001 , kappa value 0.847). Malignant hepatic lesions can be diagnosed by triphasic CT with accuracy of 93 %, sensitivity and specificity of 93.3% and 92.5% respectively and with PPV and NPV of 94.9% and 90.2% respectivelyConclusions: Triple phase CT with high accuracy is helpful in confident diagnosis of a hepatic lesion. It has an indispensible role in characterizing, evaluating and differentiating benign and malignant hepatic lesions which helps in guiding appropriate management plan with proper surgical triage. It is also helpful in reaching primary malignancy diagnosis in cases of multiple liver metastases from unknown primary.

Self-learning mechanical circuits

Computation, mechanics and materials merge in biological systems, which can continually self-optimize through internal adaptivity across length scales, from cytoplasm and biofilms to animal herds. Recent interest in such material-based computation uses the principles of energy minimization, inertia and dissipation to solve optimization problems. Although specific computations can be performed using dynamical systems, current implementations of material computation lack the ability to self-learn. In particular, the inverse problem of designing self-learning mechanical systems which can use physical computations to continuously self-optimize remains poorly understood. Here we introduce the concept of self-learning mechanical circuits, capable of taking mechanical inputs from changing environments and constantly updating their internal state in response, thus representing an entirely mechanical information processing unit. Our circuits are composed of a new mechanical construct: an adaptive directed spring (ADS), which changes its stiffness in a directional manner, enabling neural network-like computations. We provide both a theoretical foundation and experimental realization of these elastic learning units and demonstrate their ability to autonomously uncover patterns hidden in environmental inputs. By implementing computations in an embodied physical manner, the system directly interfaces with its environment, thus broadening the scope of its learning behavior. Our results pave the way towards the construction of energy-harvesting, adaptive materials which can autonomously and continuously sense and self-optimize to gain function in different environments