Setting Parameters by Example

We introduce a class of "inverse parametric optimization" problems, in which one is given both a parametric optimization problem and a desired optimal solution; the task is to determine parameter values that lead to the given solution. We describe algorithms for solving such problems for minimum spanning trees, shortest paths, and other "optimal subgraph" problems, and discuss applications in multicast routing, vehicle path planning, resource allocation, and board game programming.Comment: 13 pages, 3 figures. To be presented at 40th IEEE Symp. Foundations of Computer Science (FOCS '99

Integer programming based solution approaches for the train dispatching problem

Railroads face the challenge of competing with the trucking industry in a fastpaced environment. In this respect, they are working toward running freight trains on schedule and reducing travel times. The planned train schedules consist of departure and arrival times at main stations on the rail network. A detailed timetable, on the other hand, consists of the departure and arrival times of each train in each track section of its route. The train dispatching problem aims to determine detailed timetables over a rail network in order to minimize deviations from the planned schedule. We provide a new integer programming formulation for this problem based on a spacetime network; we propose heuristic algorithms to solve it and present computational results of these algorithms. Our approach includes some realistic constraints that have not been previously considered as well as all the assumptions and practical issues considered by the earlier works

Gender inequalities in immunization of children in a rural population of Barabanki, Uttar Pradesh

Background: There is evidence of inequalities in immunization in India, despite the fact that childhood immunization has been an important part of maternal and child health services since the 1940s [1]. Objective: To evaluate the gender inequality in the missed opportunity for immunization in pre-school children in the rural population of Barabanki, Uttar Pradesh, India.  Methods: This was a cross-sectional study conducted in the rural areas of Barabanki district among the children of 1- 2 years of age. The information was collected on pre-designed questionnaire. A total of 15 villages were covered. A door to door survey was conducted in all the villages. There was 6% non-response due unavailability of mother/father of children.  A total of 447 children were included in the study. Results: Out of the total children, 50.6% (226/447) were males and 49.4% (221/447) were females. Overall, 49.7% were fully immunized and 20.4% partially immunized.  However, 5.8% were having contraindication for immunization.  The percentage of fully immunized children was higher among males (54.4%) compared with females (44.8%).  However, the percentage of partially immunized was found to be higher among females (21.3%) than males (19.5%).  The percentage of contraindication was similar among both male and female children. Conclusion: Missed opportunity for immunization can be brought down by creating awareness periodically once in 2 or 3 months for immunization among health personnel

Exact and Heuristic Methods for the Weapon Target Assignment Problem

The Weapon Target Assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research. This problem consists of optimally assigning n weapons to m targets so that the total expected survival value of the targets after all the engagements is minimum. The WTA problem can be formulated as a nonlinear integer programming problem and is known to be NP-complete. There do not exist any exact methods for the WTA problem which can solve even small size problems (for example, with 20 weapons and 20 targets). Though several heuristic methods have been proposed to solve the WTA problem, due to the absence of exact methods, no estimates are available on the quality of solutions produced by such heuristics. In this paper, we suggest linear programming, integer programming, and network flow based lower bounding methods using which we obtain several branch and bound algorithms for the WTA problem. We also propose a network flow based construction heuristic and a very large-scale neighborhood (VLSN) search algorithm. We present computational results of our algorithms which indicate that we can solve moderately large size instances (up to 80 weapons and 80 targets) of the WTA problem optimally and obtain almost optimal solutions of fairly large instances (up to 200 weapons and 200 targets) within a few second

Functionalized nanopore-embedded electrodes for rapid DNA sequencing

The determination of a patient's DNA sequence can, in principle, reveal an increased risk to fall ill with particular diseases [1,2] and help to design "personalized medicine" [3]. Moreover, statistical studies and comparison of genomes [4] of a large number of individuals are crucial for the analysis of mutations [5] and hereditary diseases, paving the way to preventive medicine [6]. DNA sequencing is, however, currently still a vastly time-consuming and very expensive task [4], consisting of pre-processing steps, the actual sequencing using the Sanger method, and post-processing in the form of data analysis [7]. Here we propose a new approach that relies on functionalized nanopore-embedded electrodes to achieve an unambiguous distinction of the four nucleic acid bases in the DNA sequencing process. This represents a significant improvement over previously studied designs [8,9] which cannot reliably distinguish all four bases of DNA. The transport properties of the setup investigated by us, employing state-of-the-art density functional theory together with the non-equilibrium Green's Function method, leads to current responses that differ by at least one order of magnitude for different bases and can thus provide a much more robust read-out of the base sequence. The implementation of our proposed setup could thus lead to a viable protocol for rapid DNA sequencing with significant consequences for the future of genome related research in particular and health care in general.Comment: 12 pages, 5 figure

Network Flows

Not Availabl

Faster algorithms for the shortest path problem

We investigate efficient implementations of Dijkstra\u27s shortest path algorithm. We propose a new data structure, called the redistributive heap, for use in this algorithm. On a network with n vertices, m edges, and nonnegative integer arc costs bounded by C, a one-level form of redistributive heap gives a time bound for Dijkstra\u27s algorithm of O(m + nlogC). A two-level form of redistributive heap gives a bound of O(m + nlogC/loglogC). A combination of a redistributive heap and a previously known data structure called a Fibonacci heap gives a bound of O(m+ nsqrt{log C}). The best previously known bounds are O(m + nlogn) using Fibonacci heaps alone and O(mloglogC) using the priority queue structure of Van Emde Boas, Kaas, and Zijlstra

Some Recent Advances in Network Flows

The literature on network flow problems is extensive, and over the past 40 years researchers have made continuous improvements to algorithms for solving several classes of problems. However, the surge of activity on the algorithmic aspects of network flow problems over the past few years has been particularly striking. Several techniques have proven to be very successful in permitting researchers to make these recent contributions: (i) scaling of the problem data; (ii) improved analysis of algorithms, especially amortized average case performance and the use of potential functions; and (iii) enhanced data structures. In this survey, we illustrate some of these techniques and their usefulness in developing faster network flow algorithms. Our discussion focuses on the design of faster algorithms from the worst case perspective and we limit our discussion to the following fundamental problems: the shortest path problem, the maximum flow problem, and the minimum cost flow problem. We consider several representative algorithms from each problem class including the radix heap algorithm for the shortest path problem, preflow push algorithms for the maximum flow problem, and the pseudoflow push algorithms for the minimum cost flow problem

Physisorption of Nucleobases on Graphene

We report the results of our first-principles investigation on the interaction of the nucleobases adenine (A), cytosine (C), guanine (G), thymine (T), and uracil (U) with graphene, carried out within the density functional theory framework, with additional calculations utilizing Hartree--Fock plus second-order Moeller-Plesset perturbation theory. The calculated binding energy of the nucleobases shows the following hierarchy: G > T ~ C ~ A > U, with the equilibrium configuration being very similar for all five of them. Our results clearly demonstrate that the nucleobases exhibit significantly different interaction strengths when physisorbed on graphene. The stabilizing factor in the interaction between the base molecule and graphene sheet is dominated by the molecular polarizability that allows a weakly attractive dispersion force to be induced between them. The present study represents a significant step towards a first-principles understanding of how the base sequence of DNA can affect its interaction with carbon nanotubes, as observed experimentally.Comment: 7 pages, 3 figure

Behavioural disorders amongst children of a rural community of Lucknow, India

Background: Behavioural disturbances are notable child health problem, the importance of which is increasingly recognized in most countries. A behaviour problem is nothing but a deviation from the accepted pattern of behavior on the part of the child when he is exposed to an inconsistent social and cultural environment. Aims & Objectives: To assess the prevalence of behavioural disorders in children of a rural community. Material & Methods: This was a village based cross-sectional study done among the children for the assessing the behavioural disorders. Results: Of the total 1157 children studied, 195 (16.9%) showed one or the other behavioural disorders. Various disorders elicited were bed wetting (11.6%), thumb sucking (3.1%), nail biting (1.6%) and food fad (0.5%). The disorders were more common in preschool children (34.2%) compared to school going age children (11.0%). Behavioural disorders were more frequent in children at extremes of birth orders (birth orders I & V) compared to others. The prevalence of disorders did not differ much in boys (16.2%) and girls (17.6%). Conclusions: The present study has reported a relatively higher prevalence of behavior disorders (16.9%) in children in a rural setting. The pattern of behavior problems was studied in terms of age, sex and birth order. In such children, there is a need for health education and counseling by psychiatrist/psychiatric social worker at the primary care level and must be worked ou