Restructuring Primary Health Care Network to Maximize Utilization and Reduce Patient Out-of-pocket Expenses

Kaushal Kumar,Amit Kumar Bardhan 아시아기술혁신학회 2019 Asian Journal of Innovation and Policy Vol.8 No.1

Providing free primary care to everyone is an important goal pursued by many countries under universal health care programs. Countries like India need to efficiently utilize their limited capacities towards this purpose. Unfortunately, due to a variety of reasons, patients incur substantial travel and out-of-pocket expenses for getting primary care from publicly-funded facilities. We propose a set-covering optimization model to assist health policy-makers in managing existing capacity in a better way. Decision-making should consider upgrading centers with better potential to reduce patient expenses and reallocating capacities from less preferred facilities. A multinomial logit choice model is used to predict the preferences. In this article, a brief background and literature survey along with the mixed integer linear programming (MILP) optimization model are presented. The working of the model is illustrated with the help of numerical experiments.

Design and Investigation of the DM- PC-TFET-Based Biosensor for Breast Cancer Cell Detection

Mukesh Kumar Bind,Sajai Vir Singh,Kaushal Kumar Nigam 한국전기전자재료학회 2023 Transactions on Electrical and Electronic Material Vol.24 No.5

In this paper, a dielectric modulated polarity control tunnel field-effect transistor (DM-PC-TFET)- based biosensor has been proposed for the first time for breast cancer cells (BCCs) detection. The detection method is based on the signifi cant difference in dielectric constant between cancerous and healthy breast cell lines in the microwave frequency band.When BCCs with different dielectric constants are filled in the sensing region of the proposed DM-PC-TFET-based biosensor, the electrical characteristics of the device vary, allowing for early-stage breast cancer detection. The sensing ability of the proposed biosensor has been investigated in terms of variation in drain current, threshold voltage, subthreshold swing, ON/ OFF current ratio, and transconductance characteristics. The proposed bio-sensor demonstrates drain current sensitivity of 7.82 × 1010 , I ON /I OFF ratio sensitivity of 2 .01 × 109 , and trans-conductance sensitivity of 2.32 × 1012 for T47D (a breast cancer cell line). Additionally, the proposed biosensor’s selectivity, linearity, and noise characteristics are evaluated in this study too. Furthermore, the sensitivity of the DM-PC-TFET biosensor has also been investigated with variations in BCCs charge density, temperature, device geometry, and non-uniform arrangement of cancer cell lines within the nano-cavity region. The simulation results of the proposed biosensor are generated using a 2D technology computer-aided design tool. The results demonstrate that the proposed biosensor can be used as a suitable and effi cient nano-device for the early detection of breast cancer.

Restructuring Primary Health Care Network to Maximize Utilization and Reduce Patient Out-of-pocket Expenses

Bardhan, Amit Kumar,Kumar, Kaushal Asian Society for Innovation and Policy 2019 Asian Journal of Innovation and Policy Vol.8 No.1

Providing free primary care to everyone is an important goal pursued by many countries under universal health care programs. Countries like India need to efficiently utilize their limited capacities towards this purpose. Unfortunately, due to a variety of reasons, patients incur substantial travel and out-of-pocket expenses for getting primary care from publicly-funded facilities. We propose a set-covering optimization model to assist health policy-makers in managing existing capacity in a better way. Decision-making should consider upgrading centers with better potential to reduce patient expenses and reallocating capacities from less preferred facilities. A multinomial logit choice model is used to predict the preferences. In this article, a brief background and literature survey along with the mixed integer linear programming (MILP) optimization model are presented. The working of the model is illustrated with the help of numerical experiments.

Characterising the dynamic seals used in absorber rod drive mechanisms in Indian FBR

Kaushal, Nihal,Patri, Sudheer,Kumar, R. Suresh,Meikandamurthy, C.,Sreedhar, B.K.,Murugan, S.,Raghupathy, S. Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.10

Dynamic seals are one of the critical components of Absorber Rod Drive Mechanism of Fast Breeder Reactors, requiring separate experimental development. Their significance can't be overemphasized considering that the availability and re-usability of Control Rod Drive Mechanisms of Fast Breeder Test Reactor is governed by the failure rate of dynamic seals (bellows). For prototype and subsequent Fast Breeder Reactors in India, choice of the dynamic seal is changed to an in-house designed & developed labyrinth type V-ring seal. The present work is related to the numerical investigations carried out to gain insights into the sealing mechanism and the thermal behaviour of these seals. The results indicate that the seal geometry is very important for obtaining optimum performance. By changing the geometry of the present seal, performance enhancement by more than 50% in important indices is obtained. Further, the results point out that caution shall be exercised when the seal material & its operating temperature are changed. Also, the numerical model developed in this study will be useful for developing more robust dynamic seals in future.

Microstructure, Tensile and Fatigue Behaviour of Resistance Spot Welded Zinc Coated Dual Phase and Interstitial Free Steel

Kaushal Kishore,Pankaj Kumar,Goutam Mukhopadhyay 대한금속·재료학회 2022 METALS AND MATERIALS International Vol.28 No.4

Galvannealed (hot dip galvanized and annealed) dual phase (DP600) steel and interstitial free (IF) steel are two of the widelyused materials in automotive industries owing to their high specific strength, toughness, formability and corrosion resistance. This inevitably requires their joining to form larger components. Resistance spot welding has emerged as the predominantwelding technique for joining of sheet metals in automotive industries. There are complexities regarding microstructuralvariation of the fusion zone and across heat affected zones during spot welding of fundamentally dissimilar steels. This isfurther aggravated by the prospect of zinc redistribution during the welding process. Current study presents the evolution ofmicrostructure in different zones of welding in IF and DP600 steel. Micro-hardness profiles and electron back scattered diffractionstudies were performed. Furthermore, redistribution of elements in different welding zones is studied using electronprobe micro analysis. The effect of welding current and time on the nugget size and the strength of the weld during tensile–shear is determined. It was observed that there was an increase in nugget diameter and maximum load bearing capacity ofthe joint with an increase in heat input, until the occurrence of expulsion. Furthermore, critical nugget diameter for pull-outfailure was determined and existing empirical models were verified for the applicability in this case. None of the existingempirical models could predict the critical nugget diameter correctly and thus a new empirical relationship between sheetthickness and critical nugget diameter for zinc coated dissimilar steels has been proposed. Failure behaviour of the spotweldedsheets were studied under tensile–shear configuration under quasi-static and fatigue mode of loading and it showedsubstantial difference in location of crack initiation and fractographic features. Tensile–shear specimen at optimum weldingparameter failed from the base metal of the IF steel side with dimples on the fracture surface, whereas fatigue specimenfailed from the heat affected zone of the IF steel side with transgranular striations on the fracture surface.

Fixed bed utilization for the isolation of xylene vapor: Kinetics and optimization using response surface methodology and artificial neural network

Kaushal Naresh Gupta,Rahul Kumar 대한환경공학회 2021 Environmental Engineering Research Vol.26 No.2

This paper discusses the isolation of xylene vapor through adsorption using granular activated carbon as an adsorbent. The operating parameters investigated were bed height, inlet xylene concentration and flow rate, their influence on the percentage utilization of the adsorbent bed up to the breakthrough was found out. Mathematical modeling of experimental data was then performed by employing a response surface methodology (RSM) technique to obtain a set of optimum operating conditions to achieve maximum percentage utilization of bed till breakthrough. A fairly high value of R² (0.993) asserted the proposed polynomial equation’s validity. ANOVA results indicated the model to be highly significant with respect to operating parameters studied. A maximum of 76.1% utilization of adsorbent bed was found out at a bed height of 0.025 m, inlet xylene concentration of 6,200 ppm and a gas flow rate of 25 mL.min<SUP>-1</SUP>. Furthermore, the artificial neural network (ANN) was also employed to compute the percentage utilization of the adsorbent bed. A comparison between RSM and ANN divulged the performance of the latter (R² = 0.99907) to be slightly better. Out of various kinetic models studied, the Yoon-Nelson model established its appropriateness in anticipating the breakthrough curves.

Open injury, robotic repair—moving ahead! Total robotic Roux-en-Y hepaticojejunostomy for post-open cholecystectomy Bismuth type 2 biliary stricture using indocyanine green dye

Kaushal Singh Rathore,Peeyush Varshney,Subhash Chandra Soni,Vaibhav Kumar Varshney,Selvakumar B,Lokesh Agarwal,Chhagan Lal Birda 대한내시경로봇외과학회 2023 Journal of Minimally Invasive Surgery Vol.26 No.3

Hepaticojejunostomy is currently the best treatment for post-cholecystectomy biliary strictures. Laparoscopic repair has not gained popularity due to difficult reconstruction. We present case of 43-year-old-female with Bismuth type 2 stricture following laparoscopic converted open cholecystectomy with bile duct injury done elsewhere. Position was modified Llyod-Davis position and four 8-mm robotic ports (including camera) and 12-mm assistant port were placed. The procedure included noticeable steps such as adhesiolysis, identification of gallbladder fossa, identification of common hepatic duct, lowering of hilar plate etc. Operating and console time were 420 and 350 minutes and blood loss was 100 mL. Patient was discharged on postoperative day 4. Robotic repair (hepaticojejunostomy) of biliary tract stricture after cholecystectomy is safe and feasible with good outcomes.

Distributed loads in modified couple stress thermoelastic diffusion with non-local and phase-lags

Kumar, Rajneesh,Kaushal, Sachin,Dahiya, Vikram Techno-Press 2021 Coupled systems mechanics Vol.10 No.5

Thermomechanical loading is considered to examine the non-local and phase-lags effects in a modified couple stress thermoelastic (MCT) half space. Governing equations are solved by using Laplace and Fourier transform techniques. Concentrated source in time and distributed sources with space variable are taken to demonstrate the application. Distributed sources are further classified as uniformly distributed source (UDS) and linearly distributed source (LDS) for mechanical, thermal and chemical potential sources. Numerical results are calculated for displacements, stresses, temperature distribution and chemical potential and are disucussed by displaying graphically. Some particular cases are deduced.

Multiparametric magnetic resonance imaging-transrectal ultrasound fusion biopsies increase the rate of cancer detection in populations with a low incidence of prostate cancer

Rohit Kaushal,Chandan J. Das,Prabhjot Singh,Prem Nath Dogra,Rajeev Kumar 대한비뇨의학회 2019 Investigative and Clinical Urology Vol.60 No.3

Purpose: To prospectively evaluate the diagnostic yield of multiparametric magnetic resonance imaging (mpMRI)-fusion, transrectal ultrasound (TRUS)-guided prostate biopsies for detection of prostate cancer in an Asian population with a low incidence of prostate cancer. Materials and Methods: A total of 131 males with suspected prostate cancer were recruited to undergo fusion biopsy with the Artemis prostate fusion biopsy device (Eigen, Grass Valley, CA, USA). All patients underwent standard 12-core systematic biopsies in addition to biopsies targeted at the mpMRI-identified abnormal regions. Yield from the standard cores was compared with that from the targeted cores. Gleason scores of 4+3 or higher were considered significant. Results: The mean age of the patients was 63.54±7.96 years and the mean prostate-specific antigen value was 9.75±5.35 ng/mL. A total of 36 patients had cancer, of which 3 (8.3%) were detected only on standard cores and 3 (8.3%) only on targeted cores. Of the clinically significant cancers (n=30), targeted biopsy detected a higher number (28/30, 93.3%) than standard biopsy (21/30, 70.0%). A total of 6 of 8 cancers (75.0%) that were insignificant on standard biopsy were upgraded to significant cancer on targeted cores. Conclusions: Eight percent of cancers were detected only on MRI-TRUS fusion-targeted biopsies, whereas the method upgraded more than two-thirds of insignificant cancers to significant cancers. Fusion biopsies thus provide incremental information over standard TRUS biopsies in the diagnosis of significant prostate cancer in populations with a low incidence of prostate cancer.

Scaling Up Face Masks Classification Using a Deep Neural Network and Classical Method Inspired Hybrid Technique

Akhil Kumar,Arvind Kalia,Kinshuk Verma,Akashdeep Sharma,Manisha Kaushal,Aayushi Kalia 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.11

Classification of persons wearing and not wearing face masks in images has emerged as a new computer vision problem during the COVID-19 pandemic. In order to address this problem and scale up the research in this domain, in this paper a hybrid technique by employing ResNet-101 and multi-layer perceptron (MLP) classifier has been proposed. The proposed technique is tested and validated on a self-created face masks classification dataset and a standard dataset. On self-created dataset, the proposed technique achieved a classification accuracy of 97.3%. To embrace the proposed technique, six other state-of-the-art CNN feature extractors with six other classical machine learning classifiers have been tested and compared with the proposed technique. The proposed technique achieved better classification accuracy and 1-6% higher precision, recall, and F1 score as compared to other tested deep feature extractors and machine learning classifiers.