High Number Of Agents Research Articles

Factors affecting the non-publication of clinical trials of prevalent urological cancer.

Clinical trials (CTs) are critical in understanding and managing cancer. However, despite being completed, CT results are often unpublished, compromising the ability to glean useful information from them. This study aimed to evaluate factors influencing the non-publication of urological oncology clinical trials. We conducted a comprehensive search of ClinicalTrials.gov to identify CTs focused on urological cancers completed between 2000 and 2020. We used the National Clinical Trial (NCT) identifier number to check whether the trial was published. 9,145 oncology CTs were conducted between 2000 and 2020, of which 8.39% (n = 767) focused on urological cancers, and 47.2% (n = 362) of these trials remained unpublished. Univariable analysis revealed that trials with a sample size of less than 50 and phase 4 were significantly associated with non-publication p < 0.001. In contrast, trials involving triple masking, a higher number of agents, and those conducted in High-Income Countries were associated with a higher likelihood of publication p < 0.05. Multivariable analysis demonstrated that trials enrolling more than 50 patients and employing three or more agents, along with triple and quadruple masking, had higher odds of being published (OR = 1.62; 95%CI (1.22-2.16), 1.89; 95%CI (1.10-3.27), 3.04; 95%CI (1.44-6.44), 5.62; 95%CI (1.72-18.37), and 5.41; 95%CI (1.76-16.67), p < 0.05, respectively). However, trials conducted in low-middle-income Countries had lower odds of publication (OR = 0.26; 95%CI (0.08-0.87), p = 0.02). We found that almost one-half (47.2%) of all completed urologic oncology clinical trials are not published in a PubMed-indexed journal. This non-publication rate represents a significant loss of scientific knowledge and progress. We identified several key variables including sample size.

MACA: Multi-Agent with Credit Assignment for Computation Offloading in Smart Parks Monitoring

Video monitoring has a wide range of applications in a variety of scenarios, especially in smart parks. How to improve the efficiency of video data processing and reduce resource consumption have become of increasing concern. The high complexity of traditional computation offloading algorithms makes it difficult to apply them to real-time decision-making scenarios. Thus, we propose a multi-agent deep reinforcement learning algorithm with credit assignment (MACA) for computation offloading in smart park monitoring. By making online decisions after offline training, the agent can give consideration to both decision time and accuracy in effectively solving the problem of the curse of dimensionality. Via simulation, we compare the performance of MACA with traditional deep Q-network reinforcement learning algorithm and other methods. Our results show that MACA performs better in scenarios where there are a higher number of agents and can minimize request delay and reduce task energy consumption. In addition, we also provide results from a generalization capability verified experiment and ablation study, which demonstrate the contribution of MACA algorithm to each component.

Bacterial superinfection in adults with COVID-19 hospitalized in two clinics in Medellín-Colombia, 2020.

COVID-19 represents high morbidity and mortality, its complications and lethality have increased due to bacterial superinfections. We aimed to determine the prevalence of bacterial superinfection in adults with COVID-19, hospitalized in two clinics in Medellín-Colombia during 2020, and its distribution according to sociodemographic and clinical conditions. A cross sectional study was made with 399 patients diagnosed with COVID-19 by RT-PCR. We determined the prevalence of bacterial superinfection and its factors associated with crude and adjusted prevalence ratios by a generalized linear model. The prevalence of superinfection was 49.6%, with 16 agents identified, the most frequent were Klebsiella (pneumoniae and oxytoca) and Staphylococcus aureus. In the multivariate adjustment, the variables with the strongest association with bacterial superinfection were lung disease, encephalopathy, mechanical ventilation, hospital stay, and steroid treatment. A high prevalence of bacterial superinfections, a high number of agents, and multiple associated factors were found. Among these stood out comorbidities, complications, days of hospitalization, mechanical ventilation, and steroid treatment. These results are vital to identifying priority clinical groups, improving the care of simultaneous infections with COVID-19 in people with the risk factors exposed in the population studied, and identifying bacteria of public health interest.

Majority Vote on Educational Standards

The direct democratic choice of an examination standard, i.e., a performance level required to graduate, is evaluated against a utilitarian welfare function. It is shown that the median preferred standard is inefficiently low if the marginal cost of reaching a higher performance reacts more sensitively to ability for high than for low abilities, and if the right tail of the ability distribution is longer than the left tail. Moreover, a high number of agents who choose not to graduate may imply that the median preferred standard is inefficiently low even if these conditions fail.

Leadership in conflict management. The case of tourism versus territory conflict

Conflict occurs when the parties involved have divergent interests. Spatial planning involves a high number of agents who have conflicting characteristics (public/private, central/local government, the economy/environment) and divergent objectives or interests, and therefore, face the challenge of managing conflicts that are particularly difficult to resolve. A conflict management process that seeks to promote joint and constructive action amongst the stakeholders, and arrive at mutually beneficial solutions, requires a collaborative approach. In such an approach, leadership takes on a fundamental role. In this context, proceeding from a review of the literature on collaborative leadership, the aim of this paper is to answer the following question: what are the main leadership characteristics and functions that are necessary to carry out a collaborative conflict management process? In order to arrive to a conclusion, a tourism vs. territory conflict study was carried out, in which 26 public and private stakeholders were interviewed. These people are responsible for policies and interventions that have an impact on a territory that is subject to a high tourist development pressure and, at the same time, retains a high degree of natural value, in which the existence of intractable conflicts is a constant, namely the Troia‑Melides coastal region in Portugal. The results of this empirical research confirm the idea that implementing a collaborative process in Portugal is only possible if there is a leadership that has authority, legitimacy, impartiality, neutrality and the necessary communication and mobilization skills to involve the stakeholders in the process.

Competition with high number of agents and a major one

In the framework of mean field game theory, a new optimization problem is presented by adding an additional player, called the principal. After introducing a proper payoff for the principal, continuity and existence of minimum is proved. Some considerations about uniqueness and possible ways of continuing the analysis of this problem are given.

GAME THEORY AND PORT ECONOMICS: A SURVEY OF RECENT RESEARCH

AbstractThe last decade has seen a significant upsurge of studies seeking to examine the impacts of port agents’ strategic decisions. The outcome has been a wide range of results and conclusions. The aim of this work is to provide a review of this recent research in the port industry that uses strategic interaction approaches from industrial organization and game theory. The paper concentrates on five topics: ownership, relationship between ports and their hinterlands, port authorities and port operators’ relations, capacity investment decisions, and port specialization. We present the objectives, methodologies and results of the papers reviewed, with special emphasis on how models are developed. The results are not always consistent between the works analyzed. On the one hand, this could be due to the complexity of the port industry and the high number of agents that intervene. Researchers need to simplify reality to build their models by imposing restrictive assumptions. On the other hand, results could be very sensitive to the techniques used or to the differences on the port environment of the countries of study. However, some conclusions can be extracted and they present a good starting point to develop more sophisticated models. Finally, we also propose avenues for future research.

Exact and heuristic methods for solving Boolean games

Boolean games are a framework for reasoning about the rational behavior of agents whose goals are formalized using propositional formulas. Compared to normal form games, a well-studied and related game framework, Boolean games allow for an intuitive and more compact representation of the agents' goals. So far, Boolean games have been mainly studied in the literature from the Knowledge Representation perspective, and less attention has been paid on the algorithmic issues underlying the computation of solution concepts. Although some suggestions for solving specific classes of Boolean games have been made in the literature, there is currently no work available on the practical performance. In this paper, we propose the first technique to solve general Boolean games that does not require an exponential translation to normal-form games. Our method is based on disjunctive answer set programming and computes solutions (equilibria) of arbitrary Boolean games. It can be applied to a wide variety of solution concepts, and can naturally deal with extensions of Boolean games such as constraints and costs. We present detailed experimental results in which we compare the proposed method against a number of existing methods for solving specific classes of Boolean games, as well as adaptations of methods that were initially designed for normal-form games. We found that the heuristic methods that do not require all payoff matrix entries performed well for smaller Boolean games, while our ASP based technique is faster when the problem instances have a higher number of agents or action variables.

Biological Communities as Economic Subjects

When the natural resource management is considered by means of economics, biological associations are only regarded as the source of resources and the object of ownership from the part of economic agents (households, firms or the state). Such approach does not allow studying certain types of situations, like interaction of an economic agent and a natural ecosystem, property rights over which are not well defined, and does not account for system attributes of the environment. This study proposes to consider biological associations (populations or ecosystems) as specific economic subjects. It is shown that these associations regularly face the choice between various alternative uses of scarce means, which constitutes economic choice by definition. Different levels of organization in nature and economy are compared. It is defined at which level biological associations can be regarded as the subjects of economic choice in a way analogous to economic agents. A term «agent of evolutionary process»is coined for such associations. The main similarities between economic and ecological systems are listed, namely: spontaneous character of processes, crucial role of internal factors, expansion as the main criterion of determining winners and losers, high number of agents. Key differences between the two types of systems are indicated, which are: much higher number of alternatives treated by the economic agents and higher speed of reaction of the economic agents to the changes in the environment. The conclusion is made that the models where ecosystems are regarded as acting subjects are possible and useful.

A systemic review of randomized controlled studies about prevention with pharmacologic agents of adhesion formation in the rat uterine horn model.

IntroductionEvaluation of treatment attempts in postoperative adhesion formation is pivotal for the prevention of several morbidities including infertility, pelvic pain, bowel obstruction, and subsequent intraoperative complications. The purpose of this systemic review was to assess the literature on the rat uterine horn model for adhesion formation and treatment modalities to prevent adhesion in the most frequently used experimental animal model.Material and methodsWe performed a systemic review of publications from January 1st 2000 to December 31st 2013 via a PubMed search. A high number of agents were evaluated for the prevention of postoperative adhesion formation in the rat uterine horn model.ResultsAccording to most of the studies, adjuvants such as antiinflamatuars, antiestrogens, antioxidants were effective to prevent adhesion formation.ConclusionsPrevention of adhesion formation is pivotal and numerous types of agents were described in the literature were summarized in this review.

Combined environmental and economic dispatch of smart grids using distributed model predictive control

This paper presents an extended distributed model predictive control (DMPC) framework and its application to a smart grid case study. Specifically, a combined environmental and economic dispatch (EED) problem is formulated and solved, which is a non-trivial multi-objective optimization problem given the high number of agents, information exchanges and constraints associated to large-scale smart grids.In this line, the work proposed herein adopts a distributed Lagrange-based model predictive control with reduced computational demand making use of robust mixed-integer quadratic programming (MIQP) solvers. In addition, the model predictive control (MPC) nature of the framework accounts for renewable resource forecast while physical constraints are included in the formulation. The DMPC is herein extended to calculate market-based on-line energy pricing while minimizing the generation cost and emissions,and to include hard and soft constraints and ramp rate limits.The aforementioned control framework is applied to a smart grid composed of 11 consumer centers, 6 energy storages, 11 generation systems and 31 transmission lines. Simulation results show reductions of generation costs up to 40% when predictions are included in the formulation. Furthermore, the simulation of forecast errors results in up to 8% generation overcost. These results show that DMPC can be considered as an alternative versus other heuristic methods, which do not guarantee an optimal solution to the problem.

Differences in patterns of care and outcomes of elderly versus younger metastatic pancreatic cancer (mPC) patients.

9546 Background: Despite a median age at diagnosis of 72, elderly pancreatic cancer patients (pts) are poorly represented in clinical trials. We thus compared patterns of care and outcomes of mPC pts ≤ and &gt; 65 yrs of age. Methods: We retrospectively analyzed medical charts of 277 mPC pts treated at an academic center between 2000 and 2009. Age groups ≤ 65 yrs and &gt;65 yrs were compared with respect to gender, comorbidities, performance status (PS), tobacco/alcohol use, primary site, stage, histological grade, metastatic sites, treatment modalities, type and number of chemotherapeutic agents received, and survival after diagnosis of mPC (OS). Log-rank tests and Cox proportional hazards models were used to analyze survival endpoints and Fisher’s exact test to compare categorical variables. Results: 155 pts ≤65 yrs with median age of 58 and 122 pts &gt;65 yrs with median age of 73.5 were evaluated. The groups were well balanced with respect to sex (majority male), PS (majority ≤1), stage (majority 3, 4), and primary site (majority head). Cardiovascular (CV) disease was more prevalent among older pts (OR 1.7, p=0.04). Older pts were less likely to receive any chemotherapy for mPC (79% vs 92%; OR 0.33, p&lt; 0.001) and if treated were less likely to receive more than one agent (34% vs 52%; OR 0.48, p=0.003). Median OS was shorter in older pts (5m vs 6m, p=0.01). OS was longer with higher number of agents received (RR: 0.57 for young, 0.51 for old; p&lt; 0.001). CV and renal disease negatively impacted OS only in younger pts. The presence of lung metastases was associated with longer survival (10m vs 6m (p=0.01)) and liver metastases with decreased survival (5m vs 8m (p&lt;0.01)) only among younger pts. Conclusions: Elderly mPC pts have shorter OS, are less likely to receive chemotherapy, and if treated receive fewer agents compared to younger pts. These differences cannot be explained solely by PS or disease characteristics and warrant further study.