A new focus on risk reduction: An ad hoc decision support system for humanitarian relief logistics

Particularly in the early phases of a disaster, logistical decisions are needed to be made quickly and under high pressure for the decision‐makers, knowing that their decisions may have direct consequences on the affected society and all future decisions. Proactive risk reduction may be helpful in providing decision‐makers with optimal strategies in advance. However, disasters are characterized by severe uncertainty and complexity, limited knowledge about the causes of the disaster, and continuous change of the situation in unpredicted ways. Following these assumptions, we believe that adequate proactive risk reduction measures are not practical. We propose strengthening the focus on ad hoc decision support to capture information in almost real time and to process information efficiently to reveal uncertainties that had not been previously predicted. Therefore, we present an ad hoc decision support system that uses scenario techniques to capture uncertainty by future developments of a situation and an optimization model to compute promising decision options. By combining these aspects in a dynamic manner and integrating new information continuously, it can be ensured that a decision is always based on the best currently available and processed information. And finally, to identify a robust decision option that is provided as a decision recommendation to the decision‐makers, methods of multi‐attribute decision making (MADM) are applied. Our approach is illustrated for a facility location decision problem arising in humanitarian relief logistics where the objective is to identify robust locations for tent hospitals to serve injured people in the immediate aftermath of the Haiti Earthquake 2010.Frank Schätter, Marcus Wiens and Frank Schultman

New Species of Phoradendron (Viscaceae) from Mexico and Guatemala and a Synopsis of Species in Section Pauciflorae

As presently interpreted Phoradendron section Paucifiorae consists of 15 species. These mistletoes parasitize primarily conifers. We describe seven new species, make status changes for four species, and provide information on the hosts and distribution of all members of the section. New species described are: Phoradendron abietinurn Wiens, on Abies durangensi s in Chihuahua, Durango, and Jalisco, Mexico; P. acuminatum Wiens, on Cupressus lusitanica in Guatemala; P. flavomarginatum Wiens, on Juniperus fiaccida in Nuevo León, Mexico; P. lta wksworthii Wiens, on Juniperus in New Mexico, west Texas, and Coahuila, Mexico; P. olivae Wiens, on Cupressus lusitanica in Colima and Jalisco, Mexico; P. rufescens Wiens, on Juniperus spp . in San Luis Potosí, Mexico; and P. sedifolium Wiens on Cupressus lusitanica in Chiapas, and Hidalgo, Mexico. Three taxa previously recognized as subspecies are raised to specific rank: P. densum Torr. ex Trel., P. paucifiorum Torr., and P. libocedri (Engelm.) Howell. Also P. saltillense Trel., which had been placed in synonymy under P. botleanum subsp. densum, is accorded species status. In addition, three new epiparastic species of Phoradendron are described. Epiparastic mistletoes are known to parasitize only other species of mistletoes—in this instance Phoradendron or Cladocolea (Loranthaceae)

Risk Differentiation for Critical Infrastructure Protection

Critical infrastructures, e.g., electricity transmission / distribution, public transport and health care systems, need to be protected against various internal and external risks which can be safety- and / or security-relevant. Predominately probability-based methods are hitherto used for analysing the whole spectrum of risks. We think this is an insufficient approach, presumably leading to inefficient resource allocation and biased risk perception, as it does not consider the different natures of risk. This paper looks at the key difference between safety- and security-relevant risks, highlights resulting implications for critical infrastructure protection and describes a possible approach for handling these different types of risk

A single ion as a shot noise limited magnetic field gradient probe

It is expected that ion trap quantum computing can be made scalable through protocols that make use of transport of ion qubits between sub-regions within the ion trap. In this scenario, any magnetic field inhomogeneity the ion experiences during the transport, may lead to dephasing and loss of fidelity. Here we demonstrate how to measure, and compensate for, magnetic field gradients inside a segmented ion trap, by transporting a single ion over variable distances. We attain a relative magnetic field sensitivity of \Delta B/B_0 ~ 5*10^{-7} over a test distance of 140 \micro m, which can be extended to the mm range, still with sub \micro m resolution. A fast experimental sequence is presented, facilitating its use as a magnetic field gradient calibration routine, and it is demonstrated that the main limitation is the quantum shot noise.Comment: 5 pages, 3 figure

Use of digital healthcare solutions for care delivery during a pandemic-chances and (cyber) risks referring to the example of the COVID-19 pandemic

During pandemics, regular service provisioning processes in medical care may be disrupted. Digital health promises many opportunities for service provisioning during a pandemic. However, a broad penetration of medical processes with information technology also has drawbacks. Within this work, the authors use the COVID-19 pandemic to analyze the chances and the risks that may come with using digital health solutions for medical care during a pandemic. Therefore, a multi-methods approach is used. First we use a systematic literature review for reviewing the state of the art of digital health applications in healthcare. Furthermore, the usage of digital health applications is mapped to the different processes in care delivery. Here we provide an exemplary process model of oncological care delivery. The analysis shows that including digital health solutions may be helpful for care delivery in most processes of medical care provisioning. However, research on digital health solutions focuses strongly on some few processes and specific disciplines while other processes and medical disciplines are underrepresented in literature. Last, we highlight the necessity of a comprehensive risk-related debate around the effects that come with the use of digital healthcare solutions

Motivation-based Attacker Modelling for Cyber Risk Management: A Quantitative Content Analysis and a Natural Experiment

Cyber-attacks have a tremendous impact on worldwide economic performance. Hence, it is vitally important to implement effective risk management for different cyber-attacks, which calls for profound attacker models. However, cyber risk modelling based on attacker models seems to be restricted to overly simplified models. This hinders the understanding of cyber risks and represents a heavy burden for efficient cyber risk management. This work aims to forward scientific research in this field by employing a multi-method approach based on a quantitative content analysis of scientific literature and a natural experiment. Our work gives evidence for the oversimplified modelling of attacker motivational patterns. The quantitative content analysis gives evidence for a broad and established misunderstanding of attackers as being illicitly malicious. The results of the natural ex- periment substantiate the findings of the content analysis. We thereby contribute to the improvement of attacker modelling, which can be considered a necessary prerequisite for effective cyber risk management