A Study on the Parallelization of Terrain-Covering Ant Robots Simulations

Agent-based simulation is used as a tool for supporting (time-critical) decision making in differentiated contexts. Hence, techniques for speeding up the execution of agent-based models, such as Parallel Discrete Event Simulation (PDES), are of great relevance/benefit. On the other hand, parallelism entails that the final output provided by the simulator should closely match the one provided by a traditional sequential run. This is not obvious given that, for performance and efficiency reasons, parallel simulation engines do not allow the evaluation of global predicates on the simulation model evolution with arbitrary time-granularity along the simulation time-Axis. In this article we present a study on the effects of parallelization of agent-based simulations, focusing on complementary aspects such as performance and reliability of the provided simulation output. We target Terrain Covering Ant Robots (TCAR) simulations, which are useful in rescue scenarios to determine how many agents (i.e., robots) should be used to completely explore a certain terrain for possible victims within a given time. © 2014 Springer-Verlag Berlin Heidelberg

Distributed Community Detection in Dynamic Graphs

Inspired by the increasing interest in self-organizing social opportunistic networks, we investigate the problem of distributed detection of unknown communities in dynamic random graphs. As a formal framework, we consider the dynamic version of the well-studied \emph{Planted Bisection Model} \sdG(n,p,q) where the node set $[n]$ of the network is partitioned into two unknown communities and, at every time step, each possible edge $(u,v)$ is active with probability $p$ if both nodes belong to the same community, while it is active with probability $q$ (with $q<<p$) otherwise. We also consider a time-Markovian generalization of this model. We propose a distributed protocol based on the popular \emph{Label Propagation Algorithm} and prove that, when the ratio $p/q$ is larger than $n^{b}$ (for an arbitrarily small constant $b>0$), the protocol finds the right "planted" partition in $O(\log n)$ time even when the snapshots of the dynamic graph are sparse and disconnected (i.e. in the case $p=\Theta(1/n)$).Comment: Version I

Emotional State Recognition Performance Improvement on a Handwriting and Drawing Task

In this work we combine time, spectral and cepstral features of the signal captured in a tablet to characterize depression, anxiety, and stress emotional state recognition on the EMOTHAW database. EMOTHAW contains the emotional states of users represented by capturing signals from sensors on the tablet and pen when the user is performing 3 specific handwriting and 4 drawing tasks, which had been categorized into depressed, anxious, stressed, and typical, according to the Depression, Anxiety and Stress Scale (DASS). Each user was characterized with six time-domain features, and the number of spectral-domain and cepstral-domain features for the horizontal and vertical displacement of the pen, the pressure on the paper, and the time spent on-air and off-air, depended on the configuration of the filterbank. As next step, we select the best features using the Fast Correlation-Based Filtering method. Since our dataset has 129 users, then as next step, we augmented the training data by randomly selecting a percentage of the training data and adding a small random Gaussian noise to the extracted features. We then train a radial basis SVM model using the Leave-One-Out (LOO) methodology. The experimental results show an average accuracy classification improvement ranging of 15%, and an accuracy classification improvement ranging from 4% to 34% compared with baseline (state of the art) for specific emotions such as depression, anxiety, stress, and typical emotional states

The dark side of AI in professional services

The introduction and widespread adoption of Artificial Intelligence in the professions has the potential to deliver a number of critical public goods, such as widening access to justice and healthcare through AI-powered professional services. Yet, the deployment of AI in the professions does not come without challenges, exemplified by the concerns about explainability, privacy, and human agency. In this paper, we explore how these issues may give rise to dark sides of AI in professional services and illustrate how an uncoordinated process of adoption and deployment can threaten the scope of AI-powered services. In particular, we illustrate how the adoption and deployment of AI in services may undermine the fiduciary duty between clients and professionals that, so far, has safeguarded the relationship between them, creating a ‘market for lemons’ of professional services. We conclude with a reflection on plausible ways forward to facilitate and smooth the transition to AI-powered services

A survey on parallel and distributed Multi-Agent Systems

International audienceSimulation has become an indispensable tool for researchers to explore systems without having recourse to real experiments. Depending on the characteristics of the modeled system, methods used to represent the system may vary. Multi-agent systems are, thus, often used to model and simulate complex systems. Whatever modeling type used, increasing the size and the precision of the model increases the amount of computation, requiring the use of parallel systems when it becomes too large. In this paper, we focus on parallel platforms that support multi-agent simulations. Our contribution is a survey on existing platforms and their evaluation in the context of high performance computing. We present a qualitative analysis, mainly based on platform properties, then a performance comparison using the same agent model implemented on each platform

OpenABL: A domain-specific language for parallel and distributed agent-based simulations

Agent-based simulations are becoming widespread among scientists from different areas, who use them to model increasingly complex problems. To cope with the growing computational complexity, parallel and distributed implementations have been developed for a wide range of platforms. However, it is difficult to have simulations that are portable to different platforms while still achieving high performance. We present OpenABL, a domain-specific language for portable, high-performance, parallel agent modeling. It comprises an easy-to-program language that relies on high-level abstractions for programmability and explicitly exploits agent parallelism to deliver high performance. A source-to-source compiler translates the input code to a high-level intermediate representation exposing parallelism, locality and synchronization, and, thanks to an architecture based on pluggable backends, generates target code for multi-core CPUs, GPUs, large clusters and cloud systems. OpenABL has been evaluated on six applications from various fields such as ecology, animation, and social sciences. The generated code scales to large clusters and performs similarly to hand-written target-specific code, while requiring significantly fewer lines of codes

FAK activity sustains intrinsic and acquired ovarian cancer resistance to platinum chemotherapy.

Gene copy number alterations, tumor cell stemness, and the development of platinum chemotherapy resistance contribute to high-grade serous ovarian cancer (HGSOC) recurrence. Stem phenotypes involving Wnt-β-catenin, aldehyde dehydrogenase activities, intrinsic platinum resistance, and tumorsphere formation are here associated with spontaneous gains in Kras, Myc and FAK (KMF) genes in a new aggressive murine model of ovarian cancer. Adhesion-independent FAK signaling sustained KMF and human tumorsphere proliferation as well as resistance to cisplatin cytotoxicity. Platinum-resistant tumorspheres can acquire a dependence on FAK for growth. Accordingly, increased FAK tyrosine phosphorylation was observed within HGSOC patient tumors surviving neo-adjuvant chemotherapy. Combining a FAK inhibitor with platinum overcame chemoresistance and triggered cell apoptosis. FAK transcriptomic analyses across knockout and reconstituted cells identified 135 targets, elevated in HGSOC, that were regulated by FAK activity and β-catenin including Myc, pluripotency and DNA repair genes. These studies reveal an oncogenic FAK signaling role supporting chemoresistance

The association of health literacy with adherence in older 2 adults, and its role in interventions: a systematic meta-review

Background: Low health literacy is a common problem among older adults. It is often suggested to be associated with poor adherence. This suggested association implies a need for effective adherence interventions in low health literate people. However, previous reviews show mixed results on the association between low health literacy and poor adherence. A systematic meta-review of systematic reviews was conducted to study the association between health literacy and adherence in adults above the age of 50. Evidence for the effectiveness of adherence interventions among adults in this older age group with low health literacy was also explored. Methods: Eight electronic databases (MEDLINE, ERIC, EMBASE, PsycINFO, CINAHL, DARE, the Cochrane Library, and Web of Knowledge) were searched using a variety of keywords regarding health literacy and adherence. Additionally, references of identified articles were checked. Systematic reviews were included if they assessed the association between health literacy and adherence or evaluated the effectiveness of interventions to improve adherence in adults with low health literacy. The AMSTAR tool was used to assess the quality of the included reviews. The selection procedure, data-extraction, and quality assessment were performed by two independent reviewers. Seventeen reviews were selected for inclusion. Results: Reviews varied widely in quality. Both reviews of high and low quality found only weak or mixed associations between health literacy and adherence among older adults. Reviews report on seven studies that assess the effectiveness of adherence interventions among low health literate older adults. The results suggest that some adherence interventions are effective for this group. The interventions described in the reviews focused mainly on education and on lowering the health literacy demands of adherence instructions. No conclusions could be drawn about which type of intervention could be most beneficial for this population. Conclusions: Evidence on the association between health literacy and adherence in older adults is relatively weak. Adherence interventions are potentially effective for the vulnerable population of older adults with low levels of health literacy, but the evidence on this topic is limited. Further research is needed on the association between health literacy and general health behavior, and on the effectiveness of interventions

English Language Proficiency and Geographical Proximity to a Safety Net Clinic as a Predictor of Health Care Access

Studies suggest that proximity to a safety net clinic (SNC) promotes access to care among the uninsured. Distance-based barriers to care may be greater for people with limited English proficiency (LEP), compared to those who are English proficient (EP), but this has not been explored. We assessed the relationship between distance to the nearest SNC and access in non-rural uninsured adults in California, and examined whether this relationship differs by language proficiency. Using the 2005 California Health Interview Survey and a list we compiled of California’s SNCs, we calculated distance between uninsured interviewee residence and the exact address of the nearest SNC. Using multivariate regression to adjust for other relevant characteristics, we examined associations between this distance and interviewee’s probability of having a usual source of health care (USOC) and having visited a physician in the prior 12 months. To examine differences by language proficiency, we included interactions between distance and language proficiency. Uninsured LEP adults living within 2 miles of a SNC were 9.3% less likely than their EP counterparts to have a USOC (P = 0.046). Further, distance to the nearest SNC was inversely associated with the probability of having a USOC among LEP, but not among EP; consequently, the difference between LEP and EP in the probability of having a USOC widened with increasing distance to the nearest SNC. There was no difference between LEP and EP adults living within 2 miles of a SNC in likelihood of having a physician visit; however, as with USOC, distance to the nearest SNC was inversely associated with the probability of having a physician visit among LEP but not EP. The effect sizes diminished, but remained significant, when we included county fixed effects in the models. Having LEP is a barrier to health care access, which compounds when combined with increased distance to the nearest SNC, among uninsured adults. Future studies should explore potential mechanisms so that appropriate interventions can be implemented