pinecone/core-2020-05-10-deduplication huggingface dataset:
Heterogeneity in reporting on urinary outcome and cure after surgical interventions for stress urinary incontinence in adult neuro-urological patients: A systematic review

Aims: To describe all outcome parameters and definitions of cure used to report on outcome of surgical interventions for stress urinary incontinence (SUI) in neuro-urological (NU) patients. Methods: This systematic review was performed and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The study protocol was registered and published (CRD42016033303; http://www.crd.york.ac.uk/PROSPERO). Medline, Embase, Cochrane controlled trials databases, and clinicaltrial.gov were systematically searched for relevant publications until February 2017. Results: A total of 3168 abstracts were screened. Seventeen studies reporting on SUI surgeries in NU patients were included. Sixteen different outcome parameters and nine definitions of cure were used. Six studies reported on objective outcome parameters mainly derived from urodynamic investigations. All studies reported on one or more subjective outcome parameters. Patient-reported pad use (reported during interview) was the most commonly used outcome parameter. Only three of 17 studies used standardized questionnaires (two on impact of incontinence and one on quality of life). Overall, a high risk of bias was found. Conclusions: We found a considerable heterogeneity in outcome parameters and definitions of cure used to report on outcome of surgical interventions for SUI in NU patients. The results of this systematic review may begin the dialogue to a future consensus on this topic. Standardization of outcome parameters and definitions of cure would enable researchers and clinicians to consistently compare outcomes of different studies and therapies
Capsaicin-induced rapid neutrophil leukocyte activation in the rat urinary bladder microcirculatory bed

AIMS: This study was initiated to investigate the involvement of neutrophil leukocyte activation in neurogenic inflammation, a process also involved in human urinary pathologies, elicited in the rat urinary bladder by the local administration of capsaicin, the archetypal TRPV1 agonist. The contribution of afferent nerves and sensory neuropeptides to leukocyte activation in the urinary  bladder microcirculatory bed was examined. METHODS: Following a 15-min topical application of capsaicin (50 muM), leukocyte-endothelial interactions were examined for an observation period of 45 min with intravital microscopy. Expression of adhesion molecules E-selectin and ICAM-1 implicated in these interactions was assessed by immunohistochemistry. Selective sensory denervation  was performed by neonatal treatment with capsaicin. The role of the TRPV1 receptor and two sensory neuropeptides (CGRP and substance P [SP]) were studied using the selective antagonists capsazepine, CGRP8-37 and RP67580, respectively.  RESULTS: Capsaicin induced rapid increases in leukocyte rolling and adhesion and  increased the expression of E-selectin and ICAM-1 in the postcapillary venules. Sensory chemodenervation via capsaicin and also TRPV1 receptor antagonism effectively prevented these changes. A similar reduction was observed in leukocyte adhesion after topical application of CGRP8-34 or RP67580, but only CGRP8-34 reduced the capsaicin-evoked leukocyte rolling. CONCLUSIONS: Topical application of capsaicin induces early neurogenically mediated cellular microcirculatory inflammatory reactions via the activation of the TRPV1 receptor  and the release of CGRP and SP from sensory nerves in the bladder. Co-administration of SP and CGRP receptor antagonists may ameliorate microcirculatory inflammatory changes elicited by capsaicin in the urinary bladder
Three month clinical results with a rechargeable sacral neuromodulation system for the treatment of overactive bladder

Aims: The primary aim of the RELAX-OAB study is to confirm the safety and efficacy of the Axonics r-SNM System, a miniaturized, rechargeable SNM system. Methods: A total of 51 OAB patients were implanted in a single-stage implant procedure. These results represent the 3-month outcomes. Subject outcomes were evaluated using 3-day bladder diaries and quality of life questionnaires. Results: A total of 31 of 34 patients (91%) that responded during an initial trial period (“Test Responders”) continued to benefit from therapy with the Axonics r-SNM System at 3-months, defined as symptom improvement of ≥50% reduction in urinary voids or incontinence episodes or a return to <8 voids per day. Subjects who were Test Responders showed a statistically and clinically meaningful improvement in all aspects of quality of life (ICIQ-OABqol). No serious device-related adverse events (SADEs) occurred, and there were no unanticipated adverse events (UAEs). One subject was explanted due to an infection at the implant site and 19.6% of subjects experienced device related adverse events, most notably discomfort due to stimulation, which was resolved with reprogramming. Conclusions: The Axonics r-SNM System provides safe and effective SNM therapy with objective improvement in 91% of subjects. The data also demonstrates a significant improvement in all domains of quality of life. This miniaturized, rechargeable system is designed to last 15 or more years and is expected to provide clinical and cost benefits over current non-rechargeable systems by eliminating replacement surgeries
Suppression of enemy air defenses (SEAD) as an information duel

Naval Research Logistics 49 (2002) pp. 723-742.The article of record as published may be located at http://dx.doi.org/10.1002/nav.10046Blue strike aircraft enter region   to attack Red targets. In Case 1, Blue conducts
(preplanned) SEAD to establish air superiority. In the (reactive) SEAD scenario, which is Case
2, such superiority is already in place, but is jeopardized by prohibitive interference from Red,
which threatens Blue’s ability to conduct missions. We utilize both deterministic and stochastic
models to explore optimal tactics for Red in such engagements. Policies are developed which
will guide both Red’s determination of the modes of operation of his engagement radar, and his
choice of Blue opponent to target next. An index in the form of a simple transaction kill ratio
plays a major role throughout
Fitting Lanchester Equations to the Battles of Kursk and Ardennes

The article of record as published may be found at http://dx.doi.org/10.1002/nav.10101Lanchester equations and their extensions are widely used to calculate attrition in
models of warfare. This paper examines how Lanchester models fit detailed daily data on the
battles of Kursk and Ardennes. The data on Kursk, often called the greatest tank battle in history,
was only recently made available. A new approach is used to find the optimal parameter values
and gain an understanding of how well various parameter combinations explain the battles. It
turns out that a variety of Lanchester models fit the data about as well. This explains why
previous studies on Ardennes, using different minimization techniques and data formulations,
have found disparate optimal fits. We also find that none of the basic Lanchester laws (i.e.,
square, linear, and logarithmic) fit the data particularly well or consistently perform better than
the others. This means that it does not matter which of these laws you use, for with the right
coefficients you will get about the same result. Furthermore, no constant attrition coefficient
Lanchester law fits very well. The failure to find a good-fitting Lanchester model suggests that
it may be beneficial to look for new ways to model highly aggregated attrition
Flow shop scheduling with earliness, tardiness and intermediate inventory holding costs

We consider the problem of scheduling customer orders in a flow shop with the objective of minimizing the sum of tardiness, earliness (finished goods inventory holding) and intermediate (work-in-process) inventory holding costs. We formulate this problem as an integer program, and based on approximate solutions to two di erent, but closely related, Dantzig-Wolfe reformulations, we develop heuristics to minimize the total cost. We exploit the duality between Dantzig-Wolfe reformulation and Lagrangian relaxation to enhance our heuristics. This combined approach enables us to develop two di erent lower bounds on the optimal integer solution, together with intuitive approaches for obtaining near-optimal feasible integer solutions. To the best of our knowledge, this is the first paper that applies column generation to a scheduling problem with di erent types of strongly NP-hard pricing problems which are solved heuristically. The computational study demonstrates that our algorithms have a significant speed advantage over alternate methods, yield good lower bounds, and generate near-optimal feasible integer solutions for problem instances with many machines and a realistically large number of jobs
A Mathematical Programming Approach for Improving the Robustness of LAD Regression

This paper discusses a novel application of mathematical programming techniques to a regression problem. While least squares regression techniques have been used for
a long time, it is known that their robustness properties are not desirable. Specifically, the estimators are known to be too sensitive to data contamination. In this paper we examine regressions based on Least-sum of Absolute Deviations (LAD) and show that the robustness of the estimator can be improved significantly through a judicious choice of weights. The problem of finding optimum weights is formulated as a nonlinear mixed integer program, which is too difficult to solve exactly in general. We demonstrate
that our problem is equivalent to one similar to the knapsack problem and then solve
it for a special case. We then generalize this solution to general regression designs.
Furthermore, we provide an efficient algorithm to solve the general non-linear, mixed integer programming problem when the number of predictors is small. We show the
efficacy of the weighted LAD estimator using numerical examples.Statistics Working Papers Serie
A Sequential Bayesian Generalization of the Jelinski–Moranda Software Reliability Model

The article of record as published may be located at http://dx.doi.org/10.1002/nav.20148Includes supplemental material: Excel spreadsheetThe Jelinski–Moranda model of software reliability is generalized by introducing a negative-binomial prior distribution
for the number of faults remaining, together with a Gamma distribution for the rate at which each fault is exposed. This
model is well suited to sequential use, where a sequence of reliability forecasts is made in the process of testing or using the
software. We also investigate replacing the Gamma distribution with a worst-case assumption about failure rates (the worst-case
failure rate in models such as this is not infinite, since faults with large failure rates are immediately discovered and removed)
The Minmax Multidimensional Knapsack Problem with Application to a Chance-Constrained Problem

Naval Research Logistics (NRL) V. 54, No. 6, pp 656-666.http://dx.doi.org/10.1002/nav.20237In this paper we present a new combinatorial problem, called minmax multidimensional knapsack problem (MKP), motivated by a military logistics problem.  The logistics problem is a two-period, two-level, chance constrained problem with recourse.  We show that the MKP is NP-hard and develop a practically efficient combinatorial algorithm for solving it.  We also show that under some reasonable assumptions regarding the operational setting of the logistics problem, the chance-constrained optimization problem is decomposable into a series of MKPs that are solved separately
Optimizing the US Navy’s Combat Logistics Force

The article of record as published may be located at http://dx.doi.org/10.1002/nav.20318We study how changes to the composition and employment of the US Navy combat logistic force (CLF) influence
our ability to supply our navy worldwide. The CLF consists of about 30 special transport ships that carry ship and aircraft fuel,
ordnance, dry stores, and food, and deliver these to client combatant ships underway, making it possible for our naval forces to
operate at sea for extended periods.We have modeled CLF operations to evaluate a number of transforming initiatives that simplify
its operation while supporting an even larger number of client ships for a greater variety of missions. Our input is an employment
schedule for navy battle groups of ships operating worldwide, extending over a planning horizon of 90–180 days. We show how
we use optimization to advise how to sustain these ships. We have used this model to evaluate new CLF ship designs, advise what
number of ships in a new ship class would be needed, test concepts for forward at-sea logistics bases in lieu of conventional ports,
demonstrate the effects of changes to operating policy, and generally try to show whether and how the CLF can support planned
naval operations
Client-contractor bargaining on net present value in project scheduling\ud
with limited resources

The client-contractor bargaining problem addressed here is in the context of a multi-mode resource constrained project scheduling problem with discounted cash flows, which is formulated as a progress payments model.  In this model, the contractor receives payments from the client at predetermined regular time intervals. The last payment is paid at the first predetermined payment point right after project completion. The second payment model considered in this paper is the one with payments at activity completions. The project is represented on an Activity-on-Node (AON) project network. Activity durations are assumed to be deterministic. The project duration is bounded from above by a deadline imposed by the client, which constitutes a hard constraint. The bargaining objective is to maximize the bargaining objective function comprised of the objectives of both the client and the contractor. The bargaining objective function is expected to reflect the two-party nature of the problem environment and seeks a compromise between the client and the contractor. The bargaining power concept is introduced into the problem by the bargaining power weights used in the bargaining objective function. Simulated annealing algorithm and genetic algorithm approaches are proposed as solution procedures. The proposed solution methods are tested with respect to solution quality and solution times. Sensitivity analyses are conducted among different parameters used in the model, namely the profit margin, the discount rate, and the bargaining power weights
Consecutive k-within-m-out-of-n:F system with exchangeable components

As a generalization of k-out-of-n:F and consecutive k-out-of-n:F systems, the consecutive k-within-m-out-of-n:F system
consists of n linearly ordered components such that the system fails iff there are m consecutive components which include among them at least k failed components. In this article, the reliability properties of consecutive k-within-m-out-of-n:F systems with exchangeable components are studied. The bounds and approximations for the survival function are provided. A Monte Carlo estimator of system signature is obtained and used to approximate survival function. The results are illustrated and numerics are
provided for an exchangeable multivariate Pareto distribution.
Optimizing Assignment of Tomahawk Cruise Missile Missions to Firing Units

Naval Research Logistics, 58(3), pp.281-295.The article of record as published may be located at http://dx.doi.org/10.1002/nav.20377The Tomahawk land-attack cruise missile can be launched from a ship or submarine, and can deliver its warhead
precisely to a target at long range. There are several variants of the Tomahawk missile, each with specialized capabilities. For each
Tomahawk Missile Sequence Number (MSN) task (i.e., mission), the Tomahawk missile variants can be ranked with respect to
their ability and cost effectiveness to perform that task. A given land attack strike order may involve a large number of Tomahawk
missiles and numerous Tomahawk launch platforms. Operational planners select, in real time, feasible launch platforms to execute
Tomahawk taskings. The Tomahawk tasking in a strike order includes not only primary assignments but also backup assignments. On
board each launch platform, the precise allocation of speciﬁc Tomahawk missiles to the Tomahawk MSN task assigned is optimized
with a model described here. We help naval operational planners select, in real time, appropriate feasible launch platforms to fulﬁll
the Tomahawk tasking in a strike order
A Hybrid Method for Simulation Factor Screening

The article of record as published may be located at http://dx.doi.org/10.1002/nav.20382Factor screening is performed to eliminate unimportant factors so that the remaining important factors can be more
thoroughly studied in later experiments. Controlled sequential bifurcation (CSB) and controlled sequential factorial design (CSFD)
are two new screening methods for discrete-event simulations. Both methods use hypothesis testing procedures to control the Type
I Error and power of the screening results. The scenarios for which each method is most efficient are complementary. This study
proposes a two-stage hybrid approach that combines CSFD and an improved CSB called CSB-X. In Phase 1, a prescreening procedure
will estimate each effect and determine whether CSB-X or CSFD will be used for further screening. In Phase 2, CSB-X and
CSFD are performed separately based on the assignment of Phase 1. The new method usually has the same error control as CSB-X
and CSFD. The efficiency, on the other hand, is usually much better than either component method
Distribution network design on the battlefield

Cataloged from PDF version of article.Ammunition, whether it be an arrow in the middle ages, a lead bullet in the 1800s, or a laser guided smart bomb today, has been the most prominent factor in determining the outcome of combat. Failing to supply the required amount of ammunition properly may lead to defeat. Our main objective in this study is to provide a decision support tool that can help plan ammunition distribution on the battlefield. We demonstrate through an extensive literature review that the existing models are not capable of handling the specifics of the problem in this study. To this end, we propose a novel three-layer commodity-flow location routing formulation that distributes multiple products, respects hard time windows, allows demand points to be supplied by more than one vehicle or depot, and locates facilities at two different layers. We derive several valid inequalities to speed up the solution time of our model, illustrate the performance of the model in several realistically sized scenarios, and report encouraging results. Finally, we introduce a dynamic model that designs the distribution system in consecutive time periods for the entire combat duration. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 58: 188–209, 201
Analytic solution for the nucleolus of a three-player cooperative game

The nucleolus solution for cooperative games in characteristic function form is usually computed numerically by solving a sequence of linear programing (LP) problems, or by solving a single, but very large-scale, LP problem. This article proposes an algebraic method to compute the nucleolus solution analytically (i.e., in closed-form) for a three-player cooperative game in characteristic function form. We first consider cooperative games with empty core and derive a formula to compute the nucleolus solution. Next, we examine cooperative games with nonempty core and calculate the nucleolus solution analytically for five possible cases arising from the relationship among the value functions of different coalitions
The reset disambiguation policy for navigating stochastic obstacle fields

The problem we consider is a stochastic shortest path problem in the presence of a dynamic learning capability. Specifically, a spatial arrangement of possible obstacles needs to be traversed as swiftly as possible, and the status of the obstacles may be disambiguated (at a cost) en route. No efficiently computable optimal policy is known, and many similar problems have been proven intractable. In this article, we adapt a policy which is optimal for a related problem and prove that this policy is indeed also optimal for a restricted class of instances of our problem. Otherwise, this policy is generally suboptimal but, nonetheless, it is both effective and efficiently computable. Examples/simulations are provided in a mine countermeasures application. Of central use is the Tangent Arc Graph, a polynomially sized topological superimposition of exponentially many visibility graphs
Resource Allocation in an Asymmetric Technology Race with Temporary Advantages

Naval Research Logistics, V. 59, No. 2, pp 128-145.http://dx.doi.org/10.1002/nav.21477We consider two opponents that compete in developing aeymmetric technologies where each party's technology is aimed at damaging (or neutralizing) the other's technology.  The situation we consider is different than the classical problem of commercial R&D races in two ways: First, while in sommercial R&D races the competitors compete over the control of market share, in our case the comprtition is about the effectiveness of technologies with respect to certain capabilities.  Second, in contrast with the "winner-takes-all" assumption that characterizes much of the literature on this field in the commercial world, we assume that the party that wins gains a temporary advantage that expires when the other party develops a superior technology.  We formulate a variety of models that apply to a one-sided situation, where one of the two parties has to determine how much to invest in developing a technology to counter another technology employed by the other party.  The decision problems are expressed as (convex) nonlinear optimization problems.  We present an application that provides some operational insights regarding optimal resource allocation.  We also consider a two-sided situation and develop a Nash equilibrium solution that sets investment values, so that both parties have no incentive to change their investments
Equilibrium analysis of capacity allocation with demand competition

This article examines the capacity allocation decisions in a supply chain in which a supplier sells a common product to two retailers at a fixed wholesale price. The retailers order the supplier's product subject to an allocation mechanism preannounced by the supplier, and compete for the customer demand. We perform an equilibrium analysis of the retailers' ordering decisions under uniform and individually responsive allocations. Uniform allocation guarantees equilibrium orders, but is not necessarily truth inducing in the presence of demand competition. Further, we find that (1) neither the supplier nor either one of the retailers sees its profits necessarily increasing with the supplier's capacity, and the supplier may sell more with a lower capacity level, and (2) capacity allocation may not only affect the supply chain members' profits but also change the supply chain structure by driving a retailer out of the market. This article provides managerial insights on the capacity and ordering decisions for the supplier, the retailers, and the supply chain. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 201