Practical Algorithms for Multicast Support in Input Queues Switches

Abstract — This paper deals with multicast flow support in N × N Input Queued switch architectures. A practical approach to support multicast traffic is presented, assuming that O(N) queues are available at each input port. The focus is on dynamic queueing policies, where, at each input port, multicast flows are assigned to one among the available queues when flows become active: flows are assigned to queues according to switch queue status and, possibly, to flow information. We discuss queueing assignments, scheduling algorithms and flow activity definition models. We explain why dynamic queueing disciplines may outperform static policies, and we show that, even in the most favorable conditions for static policies, they provide comparable performance. I

Mobility-Aware Edge Caching for Connected Cars

Content caching on the edge of 5G networks is an emerging and critical feature to support the thirst for content of future connected cars. Yet, the compactization of 5G cells, the finite edge storage capacity and the need for content availability while driving motivate the need to develop smart edge caching strategies adapted to the mobility characteristics of connected cars. In this paper, we propose a Mobility-Aware Probabilistic (MAP) scheme, which optimally caches content at edge nodes where connected vehicles mostly require it. Unlike blind popularity decisions, the probabilistic caching used by MAP considers vehicular trajectory predictions as well as content service time by edge nodes. We evaluate our approach on realistic mobility datasets and against popularity-based edge approaches. Our MAP edge caching scheme provides up to 40% enhanced content availability, 70% increased cache throughput, and 40% reduced backhaul overhead compared to popularity-based strategies

Enzymatic characterization of Vibrio alginolyticus strains isolated from bivalves harvested at Venice Lagoon (Italy) and Guanabara Bay (Brazil)

The aquatic ecosystem is the natural habitat of microorganisms including Vibrio and Aeromonas genus which are pathogenic to human and animals. In the present investigation the frequency of these bacteria and the enzymatic characteristics of 34 Vibrio alginolyticus strains isolated from bivalves harvested in Venice Lagoon (Italy) and Guanabara Bay (Brazil) were carried out from November 2003 to February 2004. The mussels' samples were submitted to enrichment in Alkaline Peptone Water (APW) added with 1% of sodium chloride (NaCl) and APW plus 3% NaCl incubated at 37 ºC for 18-24h. Following the samples were streaked onto TCBS Agar (Thiossulfate Citrate Bile Sucrose Agar) and the suspected colonies were submitted to biochemical characterization. Also, the Vibrio alginolyticus strains were evaluated to collagenase, elastase and chondroitinase production. The results showed the isolation of 127 microorganisms distributed as follows: 105 Vibrio strains such as V. alginolyticus (32.4%), V. harveyi (19%) and V. parahaemolyticus (7.6%), 20 Aeromonas strains and two Plesiomonas shigelloides were the main pathogens isolated. We observed the production of the three enzymes from V. alginolyticus strains considered as the main virulence factors of the bacteria, especially in cases of human dermatological infection

Prediction of outcome of non-small cell lung cancer patients treated with chemotherapy and bortezomib by time-course MALDI-TOF-MS serum peptide profiling

Background: Only a minority of patients with advanced non-small cell lung cancer (NSCLC) benefit from chemotherapy. Serum peptide profiling of NSCLC patients was performed to investigate patterns associated with treatment outcome. Using magnetic bead-assisted serum peptide capture coupled to matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry (MALDI-TOF-MS), serum peptide mass profiles of 27 NSCLC patients treated with cisplatin-gemcitabine chemotherapy and bortezomib were obtained. Support vector machine-based algorithms to predict clinical outcome were established based on differential pre-treatment peptide profiles and dynamic changes in peptide abundance during treatment. Results: A 6-peptide ion signature distinguished with 82% accuracy, sensitivity and specificity patients with a relatively short vs. long progression-free survival (PFS) upon treatment. Prediction of long PFS was associated with longer overall survival. Inclusion of 7 peptide ions showing differential changes in abundance during treatment led to a 13-peptide ion signature with 86% accuracy at 100% sensitivity and 73% specificity. A 5-peptide ion signature could separate patients with a partial response vs. non-responders with 89% accuracy at 100% sensitivity and 83% specificity. Differential peptide profiles were also found when comparing the NSCLC serum profiles to those from cancer-free control subjects. Conclusion: This study shows that serum peptidome profiling using MALDI-TOF-MS coupled to pattern diagnostics may aid in prediction of treatment outcome of advanced NSCLC patients treated with chemotherap

PI Loop Resonance Control for Dark Photon Experiment at 2 K Using a 2.6 GHz SRF Cavity

Two 2.6 GHz SRF cavities are being used for a dark photon search at the vertical test stand (VTS) in FNAL, for the second phase of the Dark SRF experiment. During testing at 2 K the cavities experience frequency detuning caused by microphonics and slow frequency drifts. The experiment requires that the two cavities have the same frequency within the cavity's bandwidth. These two cavities are equipped with frequency tuners consisting of three piezo actuators. The piezo actuators are used for fine-fast frequency tuning. A proportional-integral (PI) loop utilizing the three piezos on the emitter was used to stabilize the cavity frequency and match the receiver cavity frequency. The results from this implementation will be discussed. The integration time was also calculated via simulation.Comment: 21st International Conference on Radio-Frequency Superconductivity (SRF 2023