Acute Pancreatitis severity scoring index: Prospective study to identify determinants in Pakistan

Introduction: The purpose of the study was to compare different parameters used in Ranson’s Criteria, Bedside Index of Severity in Acute Pancreatitis (BISAP), Acute Physiology and Chronic Health Evaluation (APACHE-II), and modified computed tomography severity index (MCTSI) for predicting the severity of acute pancreatitis and formulate a new scoring system to assess the severity of acute pancreatitis based on their prognostic severity index in the local population. Materials and Methods: This prospective pilot study was conducted at Rawalpindi Medical University allied hospitals from August 2019 to December 2019. All patients with a diagnosis of acute pancreatitis were included in the study through non-probability convenient sampling. Different scoring parameters were entered into standardized proforma. Results: 100 patients were included in the pilot study with a mean age of 46.53 ± 15.324. Among 24 parameters from APACHE-II, Ranson’s, BISAP, and MCTSI, only 11 parameters, Pleural effusion (PE), Pancreatic necrosis (PN), LDH, serum Calcium (Sca++), Pulse, GCS, MCTS1, Base deficit, Po2, BUN-24, and BUN-48 were significantly related(at 10% level of significance) with the severity of acute pancreatitis. Similarly out of 24, 10 parameters AST, LDH, Sca++, Pulse, PE, PN, Base deficit, MCTS1, Po2, and BUN 48were significantly covered more than 50% of the area in AUC analysis. Our proposed criteria based on 9 parameters LDH, Sca++, Pulse, PE, PN, Base deficit, MCTS1, Po2, and BUN 48which were blowing by the two methods (ANOVA and ROC). The sensitivity and specificity were higher with our proposed criteria 93.1% and 60.6%respectively as compared to the Ranson’s, modified Ranson, BISAP, and APACHE-II criteria. Conclusion: The newly proposed criteria for the assessment of the severity of AP is superior as compared to old criteria

On Distribution Grid Optimal Power Flow Development and Integration

Due to changes in electric distribution grid operation, new operation regimes have been recommended. Distribution grid optimal power flow (DOPF) has received tremendous attention in the research community, yet it has not been fully adopted across the utility industry. Our paper recognizes this problem and suggests a development and integration procedure for DOPF. We propose development of DOPF as a three step procedure of 1) processing the grid, 2) obtaining a tractable solution, and 3) implementing multiple solution algorithms and benchmarking them to improve application reliability. For the integration of DOPF, we demonstrate how a DOPF federate may be developed that can be integrated in a co-simulation environment to mimic the real-world conditions and hence improve its practicality to be deployed in the field. To demonstrate the efficacy of the proposed methods, tests on IEEE 123-bus system are performed where the usage of tractable formulation in DOPF algorithm development and its comparison to the benchmark solution are demonstrated

A survey of machine learning applications in digital forensics

We address the role of machine learning in digital forensics in this paper, in order to have a better understanding of where machine learning stand in today’s cyber security domain when it comes to collecting digital evidence. We started by talking about Digital Forensics and its past. Then, to illustrate the fields of digital forensics where machine learning methods have been used to date, we recommend a brief literature review. The aim of this paper is to promote machine learning applications in digital forensics. We went through different applications of machine learning in different areas and analysed how machine learning can potentially be used in other areas by considering its current applications and we believe that the ideas presented here will provide promising directions in the pursuit of more powerful and successful digital forensics tools.</p

Pricing mechanism for flexible loads using distribution grid Hedging Rights

This paper proposes a new pricing mechanism for the integration of flexible loads in distribution grids. This price is calculated from an envisioned two-layer local distribution grid market, where flexible load aggregators are price takers and the distribution system operator (DSO) is the market operator. On a day-ahead basis, the DSO runs the local market and clears distribution locational marginal prices (DLMPs). Aggregators purchase energy based on these DLMPs. However, depending upon grid conditions (losses/congestion), the DLMP value increases, causing aggregators to bear high energy procurement cost. To mitigate this issue, a second layer is introduced to compute ex-ante scenario-based Hedging Rights. Through a combination of these two layers, the proposed mechanism 1) improves market competition among the involved entities, 2) maintain the congestion alleviation property of DLMPs, and 3) incorporate the intertemporal energy requirements of flexible loads. The proposed framework is tested on an IEEE benchmark distribution grid. The simulation results show that the proposed pricing mechanism allows aggregators to achieve higher cost-savings, while preserving physical power flow evaluation feature of DLMP.NRF (Natl Research Foundation, S’pore

Multiphase Distribution Locational Marginal Prices: Approximation and Decomposition

We propose a multiphase distribution locational marginal price (DLMP) model. Compared to existing DLMP models in the literature, the proposed model has three distinctive features: i) It provides linear approximation of relevant DLMP components which captures global behavior of nonlinear functions; ii) it decomposes into most general components, i.e., energy, loss, congestion, voltage violations; and iii) it incorporates both wye and delta grid connections along with unbalanced loadings. The developed model is tested on a benchmark IEEE 13-bus unbalanced distribution system with the inclusion of distributed generators (DGs)

Modeling Environment for Testing a Distributed Energy Resource Management System (DERMS) Using GridAPPS-D Platform

The electric power system is currently undergoing a major transition due to growing numbers of distributed energy resources (DERs) and increased distribution automation. If optimally managed and operated, DERs could provide flexibility and highly valuable grid services such as restoration, peak shaving, voltage regulation, and frequency support to maintain grid reliability. Different applications and enterprises, such as distributed energy resources management systems (DERMS), are being developed for coordinated and optimal operation of DERs. However, to attract sufficient DER participation and achieve the coordinated operation of DERs, systems and components must be interoperable and information exchange must be secure. Along this line, the Portland State University power engineering group is developing Energy Grid of Things (EGoT) DERMS prototype. The proposed application requires the coordinated dispatch of large numbers of DERs and testing such a system presents a challenge; it is not practical to test system prototypes using thousands of real DERs. Hence, the modeling environment (ME) is designed as a co-simulation tool to model interactions between a DERMS and a mass of simulated DERs. The ME is expected to address the scalability issue inherent to hardware-in-the-loop DERMS simulation; many assets are needed to observe effects on the grid from deployment and dispatch of DERs. To enable the development and testing of such advanced applications for power distribution system planning and operations, the U.S Department of Energy developed GridAPPS-DTM, an open-source, standards-based platform at Pacific Northwest National Laboratory. This paper introduces the proposed ME for testing a DERMS application. The architecture of the ME is presented, and the GridAPPS-D features for a such simulation environment are discussed. Additionally, the procedure for developing the ME within the GridAPPS-D platform and use of different APIs for efficient and timely integration are discussed in detail

Connecting District Energy and Power Systems for Future Singaporean New Towns (CONCEPT): Final Report

Project CONCEPT (Connecting District Energy Systems in Future Singaporean New Towns) was undertaken as a joint project between the Singapore-ETH Centre (SEC) as well as TUMCREATE and has been successfully completed as of May 2019. The project has led to the development of a methodology for the integrated optimal planning of electric grids and operation of thermal building systems which has been implemented as a software framework and as such was included as an extension into the City Energy Analyst (CEA)1. Further, the project contributed to the development of a software framework for thermal building modelling, i.e., the Control-oriented Building Model (CoBMo)2. The work on the project has concluded with the submission of two journal papers (appendices C and D). The project outcomes have been discussed with the National Energy Transformation Office (NETO) of the Energy Market Authority (EMA) and were presented to the CREATE research community as part of the Future Cities Laboratory (FCL) Lunch Talk series (slides in appendix E)

Capacity Building for Vaccine Manufacturing Across Developing Countries: The Way Forward

Approved vaccines prevent 2 to 3 million deaths per year. There is a lack of equitable access to vaccines in the low- and middle-income developing nations. Challenges in the life cycle of vaccine production include process development, lead time, intellectual property, and local vaccine production. A robust and stable manufacturing process and constant raw material supplies over decades is critical. In a continuously evolving vaccine landscape, the need of the hour for developing nations is to manufacture their own vaccines besides having supply security, control over production scheduling and sustainability, control of costs, socio-economic development, and rapid response to local epidemics. There is a need for capacity building of workforce development, technology transfer, and financial support. Technology transfer has improved vaccine access and reduced prices of vaccines. Capacity building for the manufacturing of vaccines in developing countries has always been an area of paramount importance and more so in a pandemic situation