Genetic Algorithm for Epidemic Mitigation by Removing Relationships

Min-SEIS-Cluster is an optimization problem which aims at minimizing the infection spreading in networks. In this problem, nodes can be susceptible to an infection, exposed to an infection, or infectious. One of the main features of this problem is the fact that nodes have different dynamics when interacting with other nodes from the same community. Thus, the problem is characterized by distinct probabilities of infecting nodes from both the same and from different communities. This paper presents a new genetic algorithm that solves the Min-SEIS-Cluster problem. This genetic algorithm surpassed the current heuristic of this problem significantly, reducing the number of infected nodes during the simulation of the epidemics. The results therefore suggest that our new genetic algorithm is the state-of-the-art heuristic to solve this problem.Comment: GECCO '17 - Proceedings of the Genetic and Evolutionary Computation Conferenc

Facility location optimization model for emergency humanitarian logistics

Since the 1950s, the number of natural and man-made disasters has increased exponentially and the facility location problem has become the preferred approach for dealing with emergency humanitarian logistical problems. To deal with this challenge, an exact algorithm and a heuristic algorithm have been combined as the main approach to solving this problem. Owing to the importance that an exact algorithm holds with regard to enhancing emergency humanitarian logistical facility location problems, this paper aims to conduct a survey on the facility location problems that are related to emergency humanitarian logistics based on both data modeling types and problem types and to examine the pre- and post-disaster situations with respect to facility location, such as the location of distribution centers, warehouses, shelters, debris removal sites and medical centers. The survey will examine the four main problems highlighted in the literature review: deterministic facility location problems, dynamic facility location problems, stochastic facility location problems, and robust facility location problems. For each problem, facility location type, data modeling type, disaster type, decisions, objectives, constraints, and solution methods will be evaluated and real-world applications and case studies will then be presented. Finally, research gaps will be identified and be addressed in further research studies to develop more effective disaster relief operations

J Gen Virol

We investigated the molecular epidemiology and population dynamics of HCV infection among indigenes of two semi-isolated communities in North-Central Nigeria. Despite remoteness and isolation, ~15% of the population had serological or molecular markers of hepatitis C virus (HCV) infection. Phylogenetic analysis of the NS5b sequences obtained from 60 HCV-infected residents showed that HCV variants belonged to genotype 1 (n=51; 85%) and genotype 2 (n=9; 15%). All sequences were unique and intermixed in the phylogenetic tree with HCV sequences from people infected from other West African countries. The high-throughput 454 pyrosequencing of the HCV hypervariable region 1 and an empirical threshold error correction algorithm were used to evaluate intra-host heterogeneity of HCV strains of genotype 1 (n=43) and genotype 2 (n=6) from residents of the communities. Analysis revealed a rare detectable intermixing of HCV intra-host variants among residents. Identification of genetically close HCV variants among all known groups of relatives suggests a common intra-familial HCV transmission in the communities. Applying Bayesian coalescent analysis to the NS5b sequences, the most recent common ancestors for genotype 1 and 2 variants were estimated to have existed 675 and 286 years ago, respectively. Bayesian skyline plots suggest that HCV lineages of both genotypes identified in the Nigerian communities experienced epidemic growth for 200-300 years until the mid-20th century. The data suggest a massive introduction of numerous HCV variants to the communities during the 20th century in the background of a dynamic evolutionary history of the hepatitis C epidemic in Nigeria over the past three centuries.20122015-10-01T00:00:00Z1000471177/Intramural CDC HHS/United States22456613PMC4591030664

Global Risks 2015, 10th Edition.

The 2015 edition of the Global Risks report completes a decade of highlighting the most significant long-term risks worldwide, drawing on the perspectives of experts and global decision-makers. Over that time, analysis has moved from risk identification to thinking through risk interconnections and the potentially cascading effects that result. Taking this effort one step further, this year's report underscores potential causes as well as solutions to global risks. Not only do we set out a view on 28 global risks in the report's traditional categories (economic, environmental, societal, geopolitical and technological) but also we consider the drivers of those risks in the form of 13 trends. In addition, we have selected initiatives for addressing significant challenges, which we hope will inspire collaboration among business, government and civil society communitie

Cell fate reprogramming by control of intracellular network dynamics

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Here we develop a novel network control framework that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our approach drives any initial state to the target state with 100% effectiveness and needs to be applied only transiently for the network to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of helper T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments.Comment: 61 pages (main text, 15 pages; supporting information, 46 pages) and 12 figures (main text, 6 figures; supporting information, 6 figures). In revie

Earthquake Early Warning System (EEWs) for the New Madrid Seismic Zone

Part 1: Research in the last decade on Earthquake Early Warning Systems (EEWSs) has undergone rapid development in terms of theoretical and methodological advances in real time data analysis, improved telemetry, and computer technology and is becoming a useful tool for practical real time seismic hazard mitigation. The main focus of this study is to undertake a feasibility study of an EEWS for the New Madrid Seismic Zone (NMSZ) from the standpoint of source location. Magnitude determination is addressed in a separate paper. The NMSZ covers a wide area with several heavily populated cities, vital infrastructures, and facilities located within a radius of less than 70 km from the epicenters of the 1811-1812 earthquakes. One of the challenges associated with the NMSZ is that while low to moderate levels of seismic activity are common, larger earthquakes are rare (i.e. there are no instrumentally recorded data for earthquakes with magnitudes greater than M5.5 in the NMSZ). We also recognize that it may not be realistic to provide early warning for all possible sources as is done on the west coast U.S. and we therefore focus on a specific source zone. We examine the stations within the NMSZ in order to answer the question What changes should be applied to the NMSZ network to make it suitable for earthquake early warning (EEW). We also explore needed changes to the Advanced National Seismic System (ANSS) Earthquake Monitoring System Real Time (AQMS RT) data acquisition system to make it useful for EEW. Our results show that EEW is feasible, though several technical challenges remain in incorporating its use with the present network.Part 2: Increasing vulnerability of metropolitan areas within stable continental regions (SCR), such as Memphis, TN and St. Louis, MO near the New Madrid Seismic Zone (NMSZ), to earthquakes and the very low probability level at which short term earthquake forecasting is possible make an earthquake early warning system (EEWS) a viable alternative for effective real-time risk reduction in these cities. In this study, we explore practical approaches to earthquake early warning (EEWS), and test the adaptability and potential of the real-time monitoring system in the NMSZ. We determine empirical relations based on amplitude and frequency magnitude proxies from the initial four seconds of the P-waveform records available from the Cooperative New Madrid Seismic Network (CNMSN) database for magnitude ????\u3e2.1. The amplitude-based proxies include low pass filtered peak displacement (Pd), peak velocity (Pv), and integral of the velocity squared (IV2), whereas the frequency-based proxies include predominant period (????????), characteristic period (????????), and log average period (????????????????). Very few studies have considered areas with lower magnitude events. With an active EEW system in the NMSZ, damage resulting from the catastrophic event, as witnessed in 1811-1812, may be mitigated in real-time

Stress Propagation in Human-Robot Teams Based on Computational Logic Model

Mission teams are exposed to the emotional toll of life and death decisions. These are small groups of specially trained people supported by intelligent machines for dealing with stressful environments and scenarios. We developed a composite model for stress monitoring in such teams of human and autonomous machines. This modelling aims to identify the conditions that may contribute to mission failure. The proposed model is composed of three parts: 1) a computational logic part that statically describes the stress states of teammates; 2) a decision part that manifests the mission status at any time; 3) a stress propagation part based on standard Susceptible-Infected-Susceptible (SIS) paradigm. In contrast to the approaches such as agent-based, random-walk and game models, the proposed model combines various mechanisms to satisfy the conditions of stress propagation in small groups. Our core approach involves data structures such as decision tables and decision diagrams. These tools are adaptable to human-machine teaming as well.Comment: Submitted to IEEE Aerospace 2023 conferenc