Evaluation of Artificial Lift Methods to Increase Oil Production from Depleting Oil Wells in Gulf of Mexico

This paper summarizes the research work with reference to artificial lift methods to increase oil production form mature oil wells in Gulf of Mexico.  Increase oil production or oil recovery from oil reservoirs is very important. If the average worldwide recovery factor from hydrocarbon reservoirs can be increased beyond current limits, it will alleviate a number of issues related to global energy supply. Currently the daily oil production comes from mature or maturing oil fields and reserves replacement is not keeping pace with the growing energy demand.   This paper presents big picture overview of artificial lift methods for mature oil wells in Gulf of Mexico

Efficient procedure with new fused pyrido[2,3-d]pyrimidine derivatives as potent antimicrobial agents

502-508A four-step preparation of compounds containing a pyrimidine moiety is presented. This synthesis involves especially a Vilsmeier–Haack reaction and the synthesized compounds screened for their antibacterial activity against Gram-positive and Gram-negative organisms, as well as for antifungal activities. Structures of all the newly synthesized compounds were confirmed by their FTIR, 1H NMR, mass spectral and elemental analysis data. Some of the newly synthesized compounds show excellent antimicrobial activity and appear to be the most proficient members of the series

Innovation in small firms: Does family vs. non-family matter?

Small firms are the backbone of our economy. These firms need to innovate to thrive and compete. However, research on innovation in small firms, especially non-technology and less knowledge-intensive firms, is lacking. In this study, we explore antecedents of innovation in such firms. We build and test a theoretical model that links employee training, employee commitment, family employees, and emphasis on learning to innovation in small firms. We also argue that a small-firm owner’s perception about his firm being a family firm or a non-family firm will influence the relationship between predictors and firm innovation

Clinico-hematological profile of paediatric patient admitted with acute leukemia in tertiary care centre of central India

Background: Leukemia is the most prevalent childhood cancer. Acute lymphoblastic leukemia (ALL) constitutes 75% of allcases. Objective: To find out the most common clinical and hematological findings of pediatric patients with acute leukemia at atertiary care center of central India. Materials and Methods: This retrospective study was done on 30 pediatric patients diagnosedwith acute leukemia in the Department of Pediatrics and Oncology at Chirayu Medical College and Hospital, Bhopal. This studyincluded children aged from 6 months to 15 years, who were admitted from June 2014 to June 2015. Data were retrospectivelycollected by reviewing medical records of these patients. Clinical history, physical examination, hematological, and radiologicaldata were analyzed. Results: ALL was the most common hematological malignancy observed at our hospital. In addition, it wasfound to be more prevalent in males and fever was the most common presenting symptoms followed by fatigue and anorexia.Hepatosplenomegaly and pallor were the most common findings on clinical examination. Among patients with ALL, subtype L1was the most common type. Among patients with acute myeloid leukemia, M2 and M3 subtypes were most commonly documented

Explainable Brain Age Prediction using coVariance Neural Networks

In computational neuroscience, there has been an increased interest in developing machine learning algorithms that leverage brain imaging data to provide estimates of "brain age" for an individual. Importantly, the discordance between brain age and chronological age (referred to as "brain age gap") can capture accelerated aging due to adverse health conditions and therefore, can reflect increased vulnerability towards neurological disease or cognitive impairments. However, widespread adoption of brain age for clinical decision support has been hindered due to lack of transparency and methodological justifications in most existing brain age prediction algorithms. In this paper, we leverage coVariance neural networks (VNN) to propose an anatomically interpretable framework for brain age prediction using cortical thickness features. Specifically, our brain age prediction framework extends beyond the coarse metric of brain age gap in Alzheimer's disease (AD) and we make two important observations: (i) VNNs can assign anatomical interpretability to elevated brain age gap in AD by identifying contributing brain regions, (ii) the interpretability offered by VNNs is contingent on their ability to exploit specific eigenvectors of the anatomical covariance matrix. Together, these observations facilitate an explainable perspective to the task of brain age prediction.Comment: arXiv admin note: substantial text overlap with arXiv:2305.0180

Geo-Mechanical Modelling for Optimization of Rock Slope in an Opencast Coal Mine

Jharia Coalfield, in India, is a prime storehouse of the coking coal. It contains as many as thirty contiguous seams. Multiplicity of seams has contributed to a number of problems, fire, inundated workings, goaf out area and disturbed strata condition. However, due to various geotechnical problems, it was not possible to fully extract coal by underground mining method. Opencast mining is now planned for extraction of virgin coal seams upto an ultimate depth of 500 m for ensuring maximum resources recovery. There are various modeling methods to analyze the behaviour of slopes. To achieve the objective for ensuring the safe slopes with steepest possible angle, the prototype of one of the mine was simulated in physical model i.e. Equivalent material model (EM) incorporating all the pertinent characteristics of rock mass, mining method and geological discontinuities properties. The results of EM are corroborated by Numerical method using Computer code FLAC- 2D. It was observed that when slope reached near the bottom seam the resultant vector of various monitoring points showed toppling tendency of slopes whereas high stress concentration was observed in the toe region and decreases towards the surface

Equivalence Checking a Floating-point Unit against a High-level C Model

Semiconductor companies have increasingly adopted a methodology that starts with a system-level design specification in C/C++/SystemC. This model is extensively simulated to ensure correct functionality and performance. Later, a Register Transfer Level (RTL) implementation is created in Verilog, either manually by a designer or automatically by a high-level synthesis tool. It is essential to check that the C and Verilog programs are consistent. In this paper, we present a two-step approach, embodied in two equivalence checking tools, VERIFOX and HW-CBMC, to validate designs at the software and RTL levels, respectively. VERIFOX is used for equivalence checking of an untimed software model in C against a high-level reference model in C. HW-CBMC verifies the equivalence of a Verilog RTL implementation against an untimed software model in C. To evaluate our tools, we applied them to a commercial floating-point arithmetic unit (FPU) from ARM and an open-source dual-path floating-point adder