Analysis of multi-agent activity using petri nets

This paper presents the use of place/transition petri nets (PNs) for the recognition and evaluation of complex multi-agent activities. The PNs were built automatically from the activity templates that are routinely used by experts to encode domain-specific knowledge. The PNs were built in such a way that they encoded the complex temporal relations between the individual activity actions. We extended the original PN formalism to handle the propagation of evidence using net tokens. The evaluation of the spatial and temporal properties of the actions was carried out using trajectory-based action detectors and probabilistic models of the action durations. The presented approach was evaluated using several examples of real basketball activities. The obtained experimental results suggest that this approach can be used to determine the type of activity that a team has performed as well as the stage at which the activity ended.     

Left-forbidding cooperating distributed grammar systems

A left-forbidding grammar, introduced in this paper, is a context-free grammar, where a set of nonterminal symbols is attached to each context-free production. Such a production can rewrite a nonterminal provided that no symbol from the attached set occurs to the left of the rewritten nonterminal in the current sentential form. The present paper discusses cooperating distributed grammar systems with left-forbidding grammars as components and gives some new characterizations of language families of the Chomsky hierarchy. In addition, it also proves that twelve nonterminals are enough for cooperating distributed grammar systems working in the terminal derivation mode with two left-forbidding components (including erasing productions) to characterize the family of recursively enumerable languages.     

Reactive scheduling in the multi-mode RCPSP

The multi-mode resource-constrained project scheduling problem (MRCPSP) involves the determination of a baseline schedule of the project activities, which can be executed in multiple modes, satisfying the precedence relations and resource constraints while minimizing the project duration. During the execution of the project, the baseline schedule may become infeasible due to activity duration and resource disruptions. We propose and evaluate a number of dedicated exact reactive scheduling procedures as well as a tabu search heuristic for repairing a disrupted schedule, under the assumption that no activity can be started before its baseline starting time. We report on promising computational results obtained on a set of benchmark problems.     

The Network as a Storage Device: Dynamic Routing with Bounded Buffers

We study dynamic routing in store-and-forward packet networks where each network link has bounded buffer capacity for receiving incoming packets and is capable of transmitting a fixed number of packets per unit of time. At any moment in time, packets are injected at various network nodes with each packet specifying its destination node. The goal is to maximize the throughput, defined as the number of packets delivered to their destinations. In this paper, we make some progress on throughput maximization in various network topologies. Let n and m denote the number of nodes and links in the network, respectively. For line networks, we show that Nearest-to-Go (NTG), a natural distributed greedy algorithm, is -competitive, essentially matching a known lower bound on the performance of any greedy algorithm. We also show that if we allow the online routing algorithm to make centralized decisions, there is a randomized polylog(n)-competitive algorithm for line networks as well as for rooted tree networks, where each packet is destined for the root of the tree. For grid graphs, we show that NTG has a competitive ratio of while no greedy algorithm can achieve a ratio better than . Finally, for arbitrary network topologies, we show that NTG is -competitive, improving upon an earlier bound of O(mn). An extended abstract appeared in the Proceedings of the 8th Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005, Berkeley, CA, USA, pp. 1–13, Lecture Notes in Computer Science, vol. 1741, Springer, Berlin. S. Angelov is supported in part by NSF Career Award CCR-0093117, NSF Award ITR 0205456 and NIGMS Award 1-P20-GM-6912-1. S. Khanna is supported in part by an NSF Career Award CCR-0093117, NSF Award CCF-0429836, and a US-Israel Binational Science Foundation Grant. K. Kunal is supported in part by an NSF Career Award CCR-0093117 and NSF Award CCF-0429836.     

Algorithm,software, and hardware optimizations for Delaunay mesh generation on simultaneous multithreaded architectures

This article focuses on the optimization of PCDM, a parallel, two-dimensional (2D) Delaunay mesh generation application, and its interaction with parallel architectures based on simultaneous multithreading (SMT) processors. We first present the step-by-step effect of a series of optimizations on performance. These optimizations improve the performance of PCDM by up to a factor of six. They target issues that very often limit the performance of scientific computing codes. We then evaluate the interaction of PCDM with a real SMT-based SMP system, using both high-level metrics, such as execution time, and low-level information from hardware performance counters.     

Elastic Resource Allocation Algorithms for Collaboration Applications

Cloud technologies can provide elasticity to real-time audio and video (A/V) collaboration applications. However, cloud-based collaboration solutions generally operate on a best-effort basis, with neither delivery nor quality guarantees, and high-quality business focused solutions rely on dedicated infrastructure and hardware-based components. This article describes our 2-year of research in the EMD project, which targets to migrate a hardware-based and business focused A/V collaboration solution to a software-based platform hosted in the cloud, providing higher levels of elasticity and reliability. Our focus during this period was an educational collaboration scenario with teachers and students (locally present in the classroom or remotely following the classes). A model of collaboration streaming (e.g. network topology, codecs, stream, streaming workflow, software components) is defined as base for software deployment and preemptive VM allocation techniques. These heuristics are evaluated using a version of the CloudSim simulator extended to generate and simulate realistic collaboration scenarios, to manage network congestion and to monitor a.o. cost and session delay metrics. Our results show that the algorithms reduce costs when compared to previously designed approaches, having an effectiveness of 99% in meeting A/V collaboration setup deadlines, which is a stringent requirement for this collaboration application.     

Cluster formation in a time-varying multi-agent system

We introduce time-varying parameters in a multi-agent clustering model and we derive necessary and sufficient conditions for the occurrence of clustering behavior with respect to a given cluster structure. For periodically varying parameters the clustering conditions may be formulated in a similar way as for the time-invariant model. The results require the individual weights assigned to the agents to be constant. For time-varying weights we illustrate with an example that the obtained results can no longer be applied.     

Sodium Alginate—Natural Microencapsulation Material of Polymeric Microparticles

From the multitude of materials currently available on the market that can be used in the development of microparticles, sodium alginate has become one of the most studied natural anionic polymers that can be included in controlled-release pharmaceutical systems alongside other polymers due to its low cost, low toxicity, biocompatibility, biodegradability and gelatinous die-forming capacity in the presence of Ca²⁺ ions. In this review, we have shown that through coacervation, the particulate systems for the dispensing of drugs consisting of natural polymers are nontoxic, allowing the repeated administration of medicinal substances and the protection of better the medicinal substances from degradation, which can increase the capture capacity of the drug and extend its release from the pharmaceutical form.     

Biomarkers of Bladder Cancer: Cell-Free DNA,Epigenetic Modifications and Non-Coding RNAs

Bladder cancer (BC) is the 10th most frequent cancer in the world. The initial diagnosis and surveillance of BC require a combination of invasive and non-invasive methods, which are costly and suffer from several limitations. Cystoscopy with urine cytology and histological examination presents the standard diagnostic approach. Various biomarkers (e.g., proteins, genes, and RNAs) have been extensively studied in relation to BC. However, the new trend of liquid biopsy slowly proves to be almost equally effective. Cell-free DNA, non-coding RNA, and other subcellular structures are now being tested for the best predictive and diagnostic value. In this review, we focused on published gene mutations, especially in DNA fragments, but also epigenetic modifications, and non-coding RNA (ncRNA) molecules acquired by liquid biopsy. We performed an online search in PubMed/Medline, Scopus, and Web of Science databases using the terms “bladder cancer”, in combination with “markers” or “biomarkers” published until August 2022. If applicable, we set the sensitivity and specificity threshold to 80%. In the era of precision medicine, the development of complex laboratory techniques fuels the search and development of more sensitive and specific biomarkers for diagnosis, follow-up, and screening of BC. Future efforts will be focused on the validation of their sensitivity, specificity, predictive value, and their utility in everyday clinical practice.     

Activated Hepatic Stellate Cells in Hepatocellular Carcinoma: Their Role as a Potential Target for Future Therapies

Hepatocellular carcinoma (HCC) is a global healthcare challenge, which affects more than 815,000 new cases every year. Activated hepatic stellate cells (aHSCs) remain the principal cells that drive HCC onset and growth. aHSCs suppress the anti-tumor immune response through interaction with different immune cells. They also increase the deposition of the extracellular matrix proteins, challenging the reversion of fibrosis and increasing HCC growth and metastasis. Therapy for HCC was reported to activate HSCs, which could explain the low efficacy of current treatments. Conversely, recent studies aimed at the deactivation of HSCs show that they have been able to inhibit HCC growth. In this review article, we discuss the role of aHSCs in HCC pathophysiology and therapy. Finally, we provide suggestions for the experimental implementation of HSCs in HCC therapies.