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Amar Vennapusa,Ramakanth Bhargav Panchangam,Charita Kesara,Nazneen Mallick 대한내시경복강경외과학회 2021 Journal of Minimally Invasive Surgery Vol.24 No.1
Purpose: Laparoscopic sleeve gastrectomy (SG) with loop duodenojejunal bypass (LDJB) is a combination of SG and one anastomosis gastric bypass surgeries. This study was intended to evaluate the safety and feasibility of SG-LDJB surgery. Methods: This was a retrospective study analyzing SG-LDJB surgery using 250-cm length biliopancreatic limbs that was performed between May 2013 and December 2017 in 113 Indians with obesity. All demographic, clinical, operative, and follow-up data were analyzed for weight loss and diabetes remission efficacy. Weight-loss success was defined as percentage of total weight loss (%TWL) ≥ 25%. Diabetes remission was defined as hemoglobin A1c < 6% without the need for antidiabetic medications. Safety and feasibility were analyzed in terms of intraoperative and postoperative complications and serum albumin, iron, and calcium levels. Results: The %TWL was 35.0% and 31.0% at the 1-year and 3-year follow-ups, respectively. The weight-loss success rate was 91.3% and 78.1% at the 1-year and 3-year follow-ups, respectively. Sixty-six out of 113 patients had type 2 diabetes. Diabetes remission was 80.0% and 75.4% at the 1-year and 3-year follow-ups, respectively. Major perioperative complications occurred in 0.9% of the patients. The 30-day mortality rate was zero. None of the patients had serum albumin levels of <3 g/dL at the 1-year and 3-year follow-ups or symptoms of hypoproteinemia. Conclusion: SG-LDJB surgery using a 250-cm biliopancreatic limb is a safe and effective procedure to treat obesity. It is technically complex but has the advantages of endoscopic access to the stomach and negligible postoperative complications or hypoproteinemia.
Articles : Tariffs and Income Distribution under Domestic Monopoly
( Amar K. Parai ) 세종대학교 경제통합연구소 1991 Journal of Economic Integration Vol.6 No.1
This paper investigates the impact of protective tariff on the distribution of income in a Ricardo-Viner model that admits product market monopoly. Monopolistic producer is assumed to own capital empolyed in the industry and therefore earn all nonwage income in the form of rental and superprofits. In this model, an increase in the relative price of importable good caused by an increase in tariff rate may raise the real wage of labor and the real income of the monopolist in terms of either good, and may thus lead to a possible resolution of the inter-group conflict of interests within the protected industry.
Amar ul Hassan Khawaja,Mirza Jhanzaib,Muhammad Munawar 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.22 No.6
The execution of sustainable manufacturing methods to make machining processes more eco-friendly is a difficult task that has attracted significant attention from the industrial area for a long time. As one of the leading manufacturing processes, machining can have a profound impact on the environment, society, and financial aspects. In a specific scenario, recognizing reasonable machining conditions to supply cutting fluids utilizing eco-friendly methods is at present a significant focal point of academic and industrial sector research. This study is to investigate the optimal operational parameters such as speed, feed rate, and cutting depth during high-speed machining of 15CDV6 HSLA steel under near-dry (green machining) and flood lubrication using response surface methodology and an artificial neural network that leads to better performance measures like tool-chip interface temperature, specific energy, yield strength, and percentage elongation. Initially, tensile samples were prepared on wire EDM, further high-speed machining has been carried out on CNC milling using a mechanical carbide cutter to improve performance. The results showed that an improvement in tool-chip interface temperature (0.9–12%), specific energy (0.8–12%), yield strength (1.8–3.2%), and percentage elongation (1.0–8.9%) using green machining has been witnessed and confirmed that green machining is an alternative of the flood to enhance the strength while reducing the specific energy in addition to eco-friendly. Moreover, the comparative analysis between RSM and ANN results determined that the ANN delivers more precise results and confirms its adequacy when its correlation coefficients are large, and root mean square errors are small compared to those obtained through the RSM.
Adaptability and Stability Analysis of Groundnut Genotypes Using AMMI Model and GGE-biplot
Amare Kebede B,Adisu Getahun 한국작물학회 2017 Journal of crop science and biotechnology Vol.20 No.5
Unpredictable rainfall, variations in farm inputs, crop-diseases, and the inherent potential of genotypes are among the major factors for low and variable crop yield. Fourteen elite groundnut genotypes were examined in 14 environments to analyze adaptability and stability of genotypes, and identify mega-environments if they exist. Additive main effect and multiplicative interaction (AMMI) model, cultivar-superiority measure, and genotype plus genotype-by-environment (GGE) biplot analysis were used for data analysis. The environment (69.8%) and genotype-by-environment interaction (GEI) effects (21.4%) were dominating the genotypic effect (8.8%). The GEI was significant (P < 0.01), and two distinct environments (mega-environments) were identified, suggesting separate national groundnut breeding strategies for Babile and Pawe. ICGV-94100 and ICGV-97156 were stable and had the highest-yield at Babile and Pawe, respectively. The higher heritability value was recorded in more homogeneous and favorable environments, indicating the genetic potential of groundnut genotypes were better attained in more homogeneous and favorable environments. AMMI model, cultivar-superiority measure, and GGE biplots were helpful methodologies and complemented each other to evaluate the adaptability and stability of groundnut genotypes in diverse environments.
Developing Data Mining Techniques for Intruder Detection in Network Traffic
Amar Agrawal,Sabah Mohammed,Jinan Fiaidhi 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.8
In this paper we have proposed a hybrid intrusion detection system consisting of a misuse detection model based upon a Binary Tree of Classifiers as the first stage and an anomaly detection model based upon SVM Classifier as the second stage. The Binary Tree consists of several best known classifiers specialized in detecting specific attacks at a high level of accuracy. Combination of a Binary Tree and specialized classifiers will increase accuracy of the misuse detection model. The misuse detection model will detect only known attacks. In-order to detect unknown attacks, we have an anomaly detection model as the second stage. SVM has been used, since it’s the best known classifier for anomaly detection which will detect patterns that deviate from normal behavior. The proposed hybrid intrusion detection has been tested and evaluated using KDD Cup ’99, NSL-KDD and UNSW-NB15 dataset.