Optimal design and augmentation of strongly attack-tolerant two-hop clusters in directed networks

We consider the problems of minimum-cost design and augmentation of directed network clusters that have diameter 2 and maintain the same diameter after the deletion of up to R elements (nodes or arcs) anywhere in the cluster. The property of a network to maintain not only the overall connectivity, but also the same diameter after the deletion of multiple nodes/arcs is referred to as strong attack tolerance. This paper presents the proof of NP-completeness of the decision version of the problem, derives tight theoretical bounds, as well as develops a heuristic algorithm for the considered problems, which are extremely challenging to solve to optimality even for small networks. Computational experiments suggest that the proposed heuristic algorithm does identify high-quality near-optimal solutions; moreover, in the special case of undirected networks with identical arc construction costs, the algorithm provably produces an exact optimal solution to strongly attack-tolerant two-hop network design problem, regardless of the network size.     

Mechanics of microelectrics examined by design of experiments techniques

We live in a world full of variations. We need to understand its sources and we need a scientific method for predicting it, for reducing it and for controlling it. Statistical thinking is the only way to deal with variations. Continuous improvement means continuously solving the variation problem. But this relies on a successful marriage of theory and practice; experience is insufficient without theory. The theory needs to be taught. There is no substitute for knowledge (Logothetis, 1991).     

Management of nature-based goods and services provisioning from the urban common: a pan-European perspective

The role of the urban common (i.e. shared space and resources) in sustainable provisioning of goods and services to city dwellers is discussed in this paper. Focusing on tree-based green infrastructure, the study scope includes three categories of provisioning (woody biomass, food/fibre, and non-timber forest products, i.e. NTFPs), alongside three categories of supporting services (fresh water replenishment, soil nutrient restoration, building preservation). As a first step, prospects of utilizing the urban common as facilitator of nature-based solution to the earmarked provisioning services are evaluated through dedicated literature survey and expert elicitation on perceived impact of environmental change triggers and management interventions (planning and/or governance). This is followed by a structured review of the state of affairs in four European cities (London, Amsterdam, Sofia, Ljubljana), representing different macro-geographical regions with distinct socio-economic drivers in managing these provisioning services. The pan-European expert elicitation exercise noted active management of the urban common as positively impacting on the performance of the majority of provisioning services, while environmental change impacts were found to be overriding and adversely influencing the provisioning of material resources (mainly NTFPs and woody biomass). The four-city case study highlighted some regional peculiarities in connecting the city dwellers to the urban common and identified the need to overcome socio-cultural barriers for enhancing pan-European best practice sharing in the management of goods and services provisioning. This is deemed essential to pave way for an emerging perspective on sustainable utilization of the urban common as an enabler for nature-based solution, making it fit for purpose in meeting the astronomical demands of future urban living.

     

Continuous event monitoring via a Bayesian predictive approach

In clinical trials, continuous monitoring of event incidence rate plays a critical role in making timely decisions affecting trial outcome. For example, continuous monitoring of adverse events protects the safety of trial participants, while continuous monitoring of efficacy events helps identify early signals of efficacy or futility. Because the endpoint of interest is often the event incidence associated with a given length of treatment duration (e.g., incidence proportion of an adverse event with 2 years of dosing), assessing the event proportion before reaching the intended treatment duration becomes challenging, especially when the event onset profile evolves over time with accumulated exposure. In particular, in the earlier part of the study, ignoring censored subjects may result in significant bias in estimating the cumulative event incidence rate. Such a problem is addressed using a predictive approach in the Bayesian framework. In the proposed approach, experts' prior knowledge about both the frequency and timing of the event occurrence is combined with observed data. More specifically, during any interim look, each event‐free subject will be counted with a probability that is derived using prior knowledge. The proposed approach is particularly useful in early stage studies for signal detection based on limited information. But it can also be used as a tool for safety monitoring (e.g., data monitoring committee) during later stage trials. Application of the approach is illustrated using a case study where the incidence rate of an adverse event is continuously monitored during an Alzheimer's disease clinical trial. The performance of the proposed approach is also assessed and compared with other Bayesian and frequentist methods via simulation. Copyright © 2015 John Wiley & Sons, Ltd.     

Robotic-Cell Scheduling: Special Polynomially Solvable Cases of the Traveling Salesman Problem on Permuted Monge Matrices

In this paper, we introduce the 1 − K robotic-cell scheduling problem, whose solution can be reduced to solving a TSP on specially structured permuted Monge matrices, we call b-decomposable matrices. We also review a number of other scheduling problems which all reduce to solving TSP-s on permuted Monge matrices. We present the important insight that the TSP on b-decomposable matrices can be solved in polynomial time by a special adaptation of the well-known subtour-patching technique. We discuss efficient implementations of this algorithm on newly defined subclasses of permuted Monge matrices.     

Stuck between Surplus and Shortage: Demand for Skills in Russian Industry

In order to remain competitive, firms need to keep the quantity and composition of jobs close to optimal for their given output. Since the beginning of the transition period, Russian industrial firms have been widely reporting that the quantity and composition of hired labour is far from being close to optimal. This paper discusses what kinds of firms in the Russian manufacturing sector are unable to optimize their employment and why. The main conclusion is that the key issue is an excess of non‐viable firms and a shortage of highly efficient firms because of weak selection mechanisms. The major solution is seen in creating institutional conditions that stimulate a more efficient reallocation of labour. The analysis presented in this paper is based on data from a large‐scale survey of Russian manufacturing firms.     

EXTREME TEMPERATURE AND EXTREME VIOLENCE: EVIDENCE FROM RUSSIA

We study the relationship between extreme temperatures and violent mortality, employing novel regional panel data from Russia. We find that extremely hot temperatures increase violent mortality, while extremely cold temperatures have no effect. The impact of hot temperature on violence is unequal across gender and age groups, rises noticeably during weekends, and leads to considerable social costs. Our findings also suggest that better job opportunities and lower vodka consumption may decrease this impact. The results underscore that economic policies need to target vulnerable population groups to mitigate the adverse impact of extreme temperatures. (JEL Q54, I14, K42)     

Could Refugees Have a Significant Impact on the Future Demographic Change of Serbia?

Serbia still hosts the largest number of forced migrants in Europe. The paper examines the impact of the refugee influx from newly formed states on the territory of the Socialist Federal Republic of Yugoslavia (SFRY) into Serbia on the future demographic trends of the country. Examination of the past population projections of Serbia confirmed that the process of predicting migration flows is related to the greatest source of uncertainty compared to all other components of demographic change. The results of our projection of Serbia’s population through 2050 show that the large influx of refugees during the last decade of the 20th century should not have a significant impact on the future demographic change of Serbia. Even in the case of substantial improvement of total fertility rate (2.35 in final projection year, comparing to current 1.55), no positive demographic effect should be experienced. Continuation of the decline in Serbia’s total population size cannot be offset by recent refugee influx for several reasons. The most important of them are: too small number of migrants comparing to the total population size of Serbia; similarity in fertility behaviour between refugee and indigenous population; the large‐scaled emigration during the same period; much older refugee population compared to emigrant population; and the processes of refugee repatriation and resettlement. A purely hypothetical projection variant assuming the migration required to maintain the size of current total population size of Serbia until 2050 points out the need for almost three times the amount of average annual migration surplus caused by the refugee influx.