MACHINE LEARNING-BASED FRAMEWORK FOR REMEDIAL CONTROL ACTION PREDICTION USING WIDE-AREA MEASUREMENTS IN INTERCONNECTED POWER SYSTEMS

Growing demand for power systems, economic, and environmental issues, lead to power systems operating close to their stability margin. Power systems are always exposed to disturbances, leading to either instability or cascading outages and blackouts in the worst cases. Although numerous methods have been proposed since 1920 to prevent disturbances, instability and blackout still exist. Among all the instabilities, the fastest occurring one is rotor angle instability or transient instability. Since this instability happens in a fraction of a second, time must be considered in designing remedial control actions (RCAs). Different types of remedial control actions have been proposed in the past, but due to the lack of time consideration in their design, they are not practical for those cases quickly lead to transient instability. Additionally, pre-planned remedial control actions have been employed to overcome time limitations, but they are not able to cover most of the possible scenarios that may occur in the power system. Based on the literature done for this research, predicting remedial control actions has not been implemented yet. This study presents an innovative idea to predict remedial control action schemes that are able to include time limitations and cover possible scenarios properly. There are numerous challenges to consider in performing such a method, such as remedial control actions selection, implementation, practical aspects, and wide-area measurement systems (WAMS). In this study, the different parts of the framework are discussed in detail and implemented. Based on the above discussion, first, an optimized artificial neural network (ANN) is implemented to make a comprehensive framework that can predict a proper remedial control action to prevent cascading outages and blackouts. The different steps of the framework are predicted using this comprehensive algorithm. A micro model strategy has been employed, which builds a model for each line separately. This micro model decreases prediction complexity and increases the prediction accuracies of the modules. The common RCAs, including controlled islanding, load shedding, and generator rejection, are implemented in this research project. To address controlled islanding prediction, in the first step, using voltage data, the stability status was predicted. In the second step, a new method to identify coherent groups of generators was developed, and based on that method; the coherency patterns have been predicted. In the third step, a combination of islanding and load shedding is selected as a control action, and a mixed-integer linear programming (MILP) method is designed to compute islands, the amount of load shedding, and load buses. Since the load shedding prediction has two aspects and it is a very challenging problem, a new concept called the specific set of loads (SSLs) had been proposed to simplify this issue. Finally, the islanding and load shedding patterns are predicted. The framework was tested via the IEEE 39 bus system and 74-bus Nordic power system, and the results show the effectiveness of the framework. To implement generator rejection prediction, the bus voltage data are used to predict the stability status. Next, the critical generators are predicted. Then, using the equal area criterion, the amount of generator rejection for each critical generator is calculated, and the patterns are extracted. Finally, the number of generator rejections is predicted using the dataset and designed ANN. The performance of the generator rejection prediction framework is tested via the IEEE 9-bus system and 74-Bus Nordic power network

Hyperactivation of NF-κB via the MEK signaling is indispensable for the inhibitory effect of cAMP on DNA damage-induced cell death

With cAMP signaling having a profound inhibitory effect on DNA damage-induced apoptosis in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) cells, understanding how this signaling pathway affects the survival capacity of the cell has important implications for cancer therapy. We have recently shown that p53 is critical for the inhibitory effect of cAMP on genotoxic agents-mediated apoptosis in BCP-ALLs. Here, we show that elevation of cAMP levels in cells exposed to DNA damage enhances the nuclear translocation and DNA binding of NF-κB by accelerating the phosphorylation of IKKβ and thereby phosphorylation and degradation of IκBα. Furthermore, we show that the ability of cAMP to potentiate the ionizing radiation-induced activation of NF-κB requires the activity of MEK. Importantly, pharmacological or genetic ablation of NF-κB reversed the inhibitory effect of cAMP on DNA damage-induced apoptosis, demonstrating that, in addition to p53, cAMP relies on the activity of NF-κB to provide cells with a survival advantage in the face of DNA damage. Collectively, our results uncover a novel and important interaction between the cAMP and NF-κB pathways that may have implications for the targeted treatment of lymphoid malignancies, such as BCP-ALL, in which aberrant NF-κB activity functions as a driving force for treatment resistance

A heuristic approach to solve the preventive health care problem with budget and congestion constraints

This document is the Accepted Manuscript version of the following article: Soheil Davari, Kemal Kilic, and Siamak Naderi, ‘A heuristic approach to solve the preventive health care problem with budget and congestion constraints’, Applied Mathematics and Computation, Vol. 276, pp. 442-453, March 2016, doi: https://doi.org/10.1016/j.amc.2015.11.073. This manuscript version is made available under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License CC BY NC-ND 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.Preventive health care is of utmost importance to governments since they can make massive savings on health care expenditure and promote the well-being of the society. Preventive care includes many services such as cancer screenings, vaccinations, hepatitis screenings, and smoking cessation programs. Despite the benefits of these services, their uptake is not satisfactory in many countries in the world. This can be attributed to financial barriers, social issues., and other factors. One of the most important barriers for preventive care is accessibility to proper services, which is a function of various qualitative and quantitative factors such as the distance to travel, waiting time, vicinity of facilities to other attractive facilities (such as shopping malls), and even the cleanliness of the facilities. Statistics show that even a small improvement in people’s participation can save massive amounts of money for any government and improve the well-being of the people in a society. This paper addresses the problem of designing a preventive health care network considering impatient clients, and budget constraints. The objective is to maximize the accessibility of services to people. We model the problem as a mixed-integer programming problem with budget constraints, and congestion considerations. An efficient variable neighborhood search procedure is proposed and computational experiments are performed on a large set of instances.Peer reviewedFinal Accepted Versio

Comparison of Peripapillary Retinal Nerve Fiber Layer Thickness in Patients with MS and Normal Population

Purpose: To compare peripapillary retinal nerve fiber layer thickness (RNFLT) between patients with multiple sclerosis (MS) and healthy controls using optical coherence tomography (OCT).  Patients and Methods: In this prospective case control study, peripapillary RNFLT of 120 eyes from 60 patients with multiple sclerosis (MS)  was compared to 120 eyes from 60 age and sex matched healthy controls using OCT.  The RNFLT in 4 peripapillary quadrants and the mean RNFLT of all four quadrants were compared between the case and control groups. The relation between MS variables such as age of onset, type and duration of disease, history of optic neuritis (ON) and other non-ocular episodes with RNFLT was evaluated in the case group. Results: The mean RNFLT of all four quarters was significantly lower in patients with MS compared to the controls (P < 0.001). Also RNFLT was significantly lower in each of 4 quadrants (superior, temporal, inferior; P < 0.001, nasal P = 0.003). There was no significant relation between RNFLT, the age of onset of MS disease, and history of non-ocular episodes. RNFLT had a significant relation with duration of the disease (P < 0.001), the type of MS (P < 0.001), history of ON (P = 0.002), and the number of ON episodes (P = 0.021). Conclusion: We found that RNFLT decreases in MS patients and its reduction is related to the duration and type of disease as well as history and number of ON episodes. Therefore measuring RNFLT may help in estimating the progress of MS and can potentially be included as a part of patients’ follow up protocol.Keywords: Multiple sclerosis;  Tomography; Optical Coherence;;Optic Neuritis; Retinal; Nerve Fibers

Intracranial Aneurysm Rupture after SARS-CoV2 Infection : Case Report and Review of Literature

Background: SARS-CoV virus infection results in a dysbalanced and severe inflammatory response with hypercytokinemia and immunodepression. Viral infection triggers systemic inflammation and the virus itself can potentially cause vascular damage, including blood-brain barrier (BBB) disruption and alterations in the coagulation system, which may result in cardiovascular and neurovascular events. Here, we review the literature and present a case of COVID-19 infection leading to an aneurysmal subarachnoid haemorrhage (aSAH). Case Description: A 61-year-old woman presented with dyspnea, cough, and fever. She had a history of hypertension and was overweight with a body mass-index of 34. There was no history of subarachnoid hemorrhage in the family. Due to low oxygen saturation (89%) she was admitted into ICU. A chest CT showed a typical picture of COVID-19 pneumonia. The PCR-based test of an oropharyngeal swab was COVID-19-positive. In addition to oxygen support she was prescribed with favipiravir and hydroxychloroquine. She experienced a sudden headache and lost consciousness on the second day. Computer tomography (CT) with CT-angiography revealed a subarachnoid haemorrhage in the basal cisterns from a ruptured anterior communicating artery aneurysm. The aneurysm was clipped microsurgically through a left-sided standard pterional approach and the patient was admitted again to the intensive care unit for further intensive medical treatment. Post-operatively, the patient showed slight motor dysphasia. No other neurological deficits. Conclusion: Systemic inflammation and ventilator support-associated blood pressure fluctuations may trigger aneurysmal subarachnoid haemorrhage secondary to COVID-19 infection. COVID-19 infection could be considered as one of the possible risk factors leading to instability and rupture of intracranial aneurysm.Peer reviewe

Bone marrow stroma-derived PGE2 protects BCP-ALL cells from DNA damage-induced p53 accumulation and cell death

Background B cell precursor acute lymphoblastic leukaemia (BCP-ALL) is the most common paediatric cancer. BCP-ALL blasts typically retain wild type p53, and are therefore assumed to rely on indirect measures to suppress transformation-induced p53 activity. We have recently demonstrated that the second messenger cyclic adenosine monophosphate (cAMP) through activation of protein kinase A (PKA) has the ability to inhibit DNA damage-induced p53 accumulation and thereby promote survival of the leukaemic blasts. Development of BCP-ALL in the bone marrow (BM) is supported by resident BM-derived mesenchymal stromal cells (MSCs). MSCs are known to produce prostaglandin E2 (PGE2) which upon binding to its receptors is able to elicit a cAMP response in target cells. We hypothesized that PGE2 produced by stromal cells in the BM microenvironment could stimulate cAMP production and PKA activation in BCP-ALL cells, thereby suppressing p53 accumulation and promoting survival of the malignant cells. Methods Primary BCP-ALL cells isolated from BM aspirates at diagnosis were cocultivated with BM-derived MSCs, and effects on DNA damage-induced p53 accumulation and cell death were monitored by SDS-PAGE/immunoblotting and flow cytometry-based methods, respectively. Effects of intervention of signalling along the PGE2-cAMP-PKA axis were assessed by inhibition of PGE2 production or PKA activity. Statistical significance was tested by Wilcoxon signed-rank test or paired samples t test. Results We demonstrate that BM-derived MSCs produce PGE2 and protect primary BCP-ALL cells from p53 accumulation and apoptotic cell death. The MSC-mediated protection of DNA damage-mediated cell death is reversible upon inhibition of PGE2 synthesis or PKA activity. Furthermore our results indicate differences in the sensitivity to variations in p53 levels between common cytogenetic subgroups of BCP-ALL. Conclusions Our findings support our hypothesis that BM-derived PGE2, through activation of cAMP-PKA signalling in BCP-ALL blasts, can inhibit the tumour suppressive activity of wild type p53, thereby promoting leukaemogenesis and protecting against therapy-induced leukaemic cell death. These novel findings identify the PGE2-cAMP-PKA signalling pathway as a possible target for pharmacological intervention with potential relevance for treatment of BCP-ALL

Risk of stroke in hospitalized SARS-CoV-2 infected patients : A multinational study

Background: There is an increased attention to stroke following SARS-CoV-2. The goal of this study was to better depict the short-term risk of stroke and its associated factors among SARS-CoV-2 hospitalized patients. Methods: This multicentre, multinational observational study includes hospitalized SARS-CoV-2 patients from North and South America (United States, Canada, and Brazil), Europe (Greece, Italy, Finland, and Turkey), Asia (Lebanon, Iran, and India), and Oceania (New Zealand). The outcome was the risk of subsequent stroke. Centres were included by non-probability sampling. The counts and clinical characteristics including laboratory findings and imaging of the patients with and without a subsequent stroke were recorded according to a predefined protocol. Quality, risk of bias, and heterogeneity assessments were conducted according to ROBINS-E and Cochrane Q-test. The risk of subsequent stroke was estimated through meta-analyses with random effect models. Bivariate logistic regression was used to determine the parameters with predictive outcome value. The study was reported according to the STROBE, MOOSE, and EQUATOR guidelines. Findings: We received data from 26,175 hospitalized SARS-CoV-2 patients from 99 tertiary centres in 65 regions of 11 countries until May 1st, 2020. A total of 17,799 patients were included in meta-analyses. Among them, 156(0.9%) patients had a stroke-123(79%) ischaemic stroke, 27(17%) intracerebral/subarachnoid hemorrhage, and 6(4%) cerebral sinus thrombosis. Subsequent stroke risks calculated with meta-analyses, under low to moderate heterogeneity, were 0.5% among all centres in all countries, and 0.7% among countries with higher health expenditures. The need for mechanical ventilation (OR: 1.9, 95% CI:1.1-3.5, p = 0.03) and the presence of ischaemic heart disease (OR: 2.5, 95% CI:1.4-4.7, p = 0.006) were predictive of stroke. Interpretation: The results of this multi-national study on hospitalized patients with SARS-CoV-2 infection indicated an overall stroke risk of 0.5%(pooled risk: 0.9%). The need for mechanical ventilation and the history of ischaemic heart disease are the independent predictors of stroke among SARS-CoV-2 patients. (C) 2020 The Authors. Published by Elsevier B.V.Peer reviewe

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18 : a modelling study

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2 ·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676· 5 (513· 6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique, had the highest estimated HIV incidence (4661·7 [2544·8–8120·3]) cases per 100000 people in 2018 and Inhassunge District, Zambezia Province, Mozambique, had the highest estimated HIV mortality rate (1163·0 [679·0–1866·8]) deaths per 100 000 people. Further, the rate of reduction in HIV incidence and mortality from 2000 to 2018, as well as the ratio of new infections to the number of people living with HIV was highly variable. Although most second-level administrative units had declines in the number of new cases (3316 [81· 1%] of 4087 units) and number of deaths (3325 [81·4%]), nearly all appeared well short of the targeted 75% reduction in new cases and deaths between 2010 and 2020. Interpretation: Our estimates suggest that most second-level administrative units in sub-Saharan Africa are falling short of the targeted 75% reduction in new cases and deaths by 2020, which is further compounded by substantial within-country variability. These estimates will help decision makers and programme implementers expand access to ART and better target health resources to higher burden subnational areas