Dynamic resource provisioning in cloud computing: A randomized auction approach

Abstract—This work studies resource allocation in a cloud market through the auction of Virtual Machine (VM) instances. It generalizes the existing literature by introducing combinatorial auctions of heterogeneous VMs, and models dynamic VM pro-visioning. Social welfare maximization under dynamic resource provisioning is proven NP-hard, and modeled with a linear inte-ger program. An efficient α-approximation algorithm is designed, with α ∼ 2.72 in typical scenarios. We then employ this algorithm as a building block for designing a randomized combinatorial auction that is computationally efficient, truthful in expectation, and guarantees the same social welfare approximation factor α. A key technique in the design is to utilize a pair of tailored primal and dual LPs for exploiting the underlying packing structure of the social welfare maximization problem, to decompose its fractional solution into a convex combination of integral solutions. Empirical studies driven by Google Cluster traces verify the efficacy of the randomized auction. I

Robotic approach together with an enhanced recovery programme improve the perioperative outcomes for complex hepatectomy

ObjectiveRobotic surgery has more advantages than traditional surgical approaches to complex liver resection; however, the robotic approach is invariably associated with increased cost. Enhanced recovery after surgery (ERAS) protocols are beneficial in conventional surgeries.MethodsThe present study investigated the effects of robotic surgery combined with an ERAS protocol on perioperative outcomes and hospitalization costs of patients undergoing complex hepatectomy. Clinical data from consecutive robotic and open liver resections (RLR and OLR, respectively) performed in our unit in the pre-ERAS (January 2019–June 2020) and ERAS (July 2020–December 2021) periods were collected. Multivariate logistic regression analysis was performed to determine the impact of ERAS and surgical approaches—alone or in combination—on LOS and costs.ResultsA total of 171 consecutive complex liver resections were analyzed. ERAS patients had a shorter median LOS and decreased total hospitalization cost, without a significant difference in the complication rate compared with the pre-ERAS cohort. RLR patients had a shorter median LOS and decreased major complications, but with increased total hospitalization cost, compared with OLR patients. Comparing the four combinations of perioperative management and surgical approaches, ERAS + RLR had the shortest LOS and the fewest major complications, whereas pre-ERAS + RLR had the highest hospitalization costs. Multivariate analysis found that the robotic approach was protective against prolonged LOS, whereas the ERAS pathway was protective against high costs.ConclusionsThe ERAS + RLR approach optimized postoperative complex liver resection outcomes and hospitalization costs compared with other combinations. The robotic approach combined with ERAS synergistically optimized outcome and overall cost compared with other strategies, and may be the best combination for optimizing perioperative outcomes for complex RLR

Special Section on Local and Distributed Electricity Markets

Driven by the Goals of Clean Energy and Zero Carbon Emissions, the Power Industry is Undergoing Significant Transformations. the Rapid Growth of Diverse Distributed Energy Resources (DERs) at Grid Edge Such as Rooftop Photovoltaics (PVs) and Electric Vehicles is Transforming the Traditional Centralized Power Grid Management to a Decentralized, Bottom-Up, and Localized Control Paradigm. Establishing Local and Distribution-Level Electricity Markets Provides an Effective Solution to Managing Large Amounts of Small-Scale DERs. New Regulations Such as the Recent FERC Order 2222 in the U.S. Open the Door to DERs in the Wholesale Markets. through Coordinating the Local and Distribution-Level Markets with the Transmission-Level Wholesale Market, the DERs and Prosumers Can Trade Energy and Flexibility Locally with Each Other and Meanwhile Provide Energy, Flexibility and Ancillary Services to the Bulk Power Grid. during This Transition, There Are Many New Technical Challenges to Address, Calling for Innovative Ideas and Interdisciplinary Research in This Promising Direction. Advanced Information and Communication Technologies (ICT) Are Needed, as a Key Enabler, for the Development and Practical Implementation of Local and Distribution Electricity Markets. Research into Local and Distribution Markets is Strongly Interdisciplinary, Involving the State of the Art in Power Engineering, Economics, and Digital/information Technology. a Broad Spectrum of Contributors from Universities, Industry, Research Laboratories and Policy Makers is Sought to Develop and Present Solutions and Technologies that Will Facilitate and Advance Practical Applications and Implementations of Local and Distribution-Level Electricity Markets to Uncover the Values of DERs

On decoder-only architecture for speech-to-text and large language model integration

Large language models (LLMs) have achieved remarkable success in the field of natural language processing, enabling better human-computer interaction using natural language. However, the seamless integration of speech signals into LLMs has not been explored well. The "decoder-only" architecture has also not been well studied for speech processing tasks. In this research, we introduce Speech-LLaMA, a novel approach that effectively incorporates acoustic information into text-based large language models. Our method leverages Connectionist Temporal Classification and a simple audio encoder to map the compressed acoustic features to the continuous semantic space of the LLM. In addition, we further probe the decoder-only architecture for speech-to-text tasks by training a smaller scale randomly initialized speech-LLaMA model from speech-text paired data alone. We conduct experiments on multilingual speech-to-text translation tasks and demonstrate a significant improvement over strong baselines, highlighting the potential advantages of decoder-only models for speech-to-text conversion

Proyecto de Fortalecimiento Institucional – Desarrollo de Políticas de Internacionalización de la Educación Superioren en la UNCUYO

O CONGRESSO DE INTERNACIONALIZAÇÃO DA EDUCAÇÃO SUPERIOR – CIES 2019 é um evento in- ternacional, que reúne professores, pesquisadores e estudantes de graduação e pós-graduação para divulgar a produção científica no campo da Internacionalização do Ensino Superior e fortalecer a cooperação internacional entre diferentes instituições de ensino e grupos de pesquisa no âmbito do MERCOSUL. A iniciativa é fruto de uma parceria entre pesquisadores da Universidade Federal da Integra- ção Latino-Americana (UNILA - Brasil), a Universidad Nacional del Litoral (UNL - Argentina), a Uni- versidad Nacional de Asunción (UNA - Paraguay) e a Universidad de la República (UDeLaR - Uru- guay), que atuam em projetos vinculados ao Setor Educacional do MERCOSUL, no Núcleo de Estudos e Investigações em Educação Superior. O evento será realizado nos dias 4, 5 e 6 de Setembro de 2019 no campus PTI da UNILA, dentro do Parque Tecnológico da Usina Hidrelétrica de Itaipu, na cidade de Foz do Iguaçu, Paraná, Brasil. A UNILA, sede do evento, é uma universidade temática criada em 2010 pelo governo federal do Brasil com a missão institucional de formar recursos humanos aptos a contribuir com a integra- ção latino-americana, com o desenvolvimento regional e com o intercâmbio cultural, científico e educacional da América Latina, especialmente no MERCOSUL. Sua finalidade, portanto, é conver- ter-se em um espaço de encontros, de trocas e de aprendizagem mútua, que reforçam o compro- misso em prol da pertinência, da excelência e da construção sustentável de um mundo melhor.La Universidad Nacional de Cuyo es una de las instituciones latinoamericanas que participan del Proyecto DHIP (Desarrollo de Políticas de Internacionalización de la Educación Superior, por sus siglas en inglés). Este proyecto, que también incluye a universidades de Argentina, Colombia, Paraguay, España, Italia y Portugal, se encuentra enmarcado en el programa ERASMUS+, y es cofinanciado por la Comisión Europea, dentro de las acciones de “Capacity building in the field of higher education” (Fortalecimiento institucional en el campo de la educación superior). El proyecto comenzó en octubre de 2018 y durará hasta 2020. Actualmente y a nivel global, las Instituciones de Educación Superior (IES) se proponen poner en marcha distintas iniciativas internacionales, manifestando su compromiso con la idea de convertirse en "instituciones educativas globales". Una mirada más cercana a lo que realmente está sucediendo muestra que con frecuencia estas iniciativas tienen un impacto marginal. En los últimos años, muchas universidades de América Latina han emprendido programas ambiciosos de internacionalización, que en muchos casos han dado resultados por debajo de lo esperado. El proyecto parte de la hipótesis de que existe por tanto una brecha significativa entre los esfuerzos de internacionalización de nuestras instituciones y los resultados concretos.Núcleo de Estudios e Investigaciones en Educación Superior del Mercosur - NUCLEO Grupo Interdisciplinar de Pesquisa em Educação na América Latina – EducAL/UNILA Instituto Mercosul de Estudos Avançados – IMEA/UNILA Pró-Reitoria de Relações Institucionais e Internacionais – PROINT/UNIL

Cloning and functional analysis of the naphthomycin biosynthetic gene cluster in Streptomyces sp CS

Naphthomycins (NATs) are 29-membered naphthalenic ansamacrolactam antibiotics with antimicrobial and antineoplastic activities. Their biosynthesis starts from 3-amino-5-hydroxy-benzoic acid (AHBA). By PCR amplification with primers for AHBA synthase and amino-dehydroquinate (aDHQ) synthase, a genomic region containing orthologs of these genes was identified in Streptomyces sp. CS. It was confirmed to be involved in naphthomycin biosynthesis by deletion of a large DNA fragment, resulting in abolishment of naphthomycin production. A 106 kb region was sequenced, and 32 complete ORFs were identified, including five polyketide synthase genes, eight genes for AHBA synthesis, and putative genes for modification, regulation, transport or resistance. Targeted inactivation and complementation experiments proved that the halogenase gene nat1 is responsible for the chlorination of C-30 of NATs. The nat1 mutant could also be complemented with asm12, the halogenase gene of ansamitocin biosynthesis. Likewise, an asm12 mutant could be complemented with nat1, suggesting a similar catalytic mechanism for both halogenases. A putative hydroxylase gene, nat2, was also inactivated, whereupon the biosynthesis of NATs was completely abolished with a tetraketide desacetyl-SY4b accumulated, indicating the participation of nat2 in the formation of the naphthalene ring. The information presented here expands our understanding of the biosynthesis of naphthalenic ansamycins, and may pave the way for engineering ansamacrolactams with improved pharmaceutical properties.National Natural Science Foundation of China; Ministry of Science and Technology[973, 863]; Ministry of Education; Shanghai Municipal Council of Science and Technolog

Dlmp-based quantification and analysis method of operational flexibility in flexible distribution networks

With high penetration of flexible resources, operational flexibility of flexible distribution networks (FDNs) is important to ensure high-quality electricity services. This paper proposes a value quantification and analysis method for operational flexibility in FDNs based on distribution locational marginal pricing (DLMP). First, flexibility constraints are formulated from the perspective of node integration, branch transfer, and network aggregation of flexibility. Then, a unified analytical framework for quantifying the operational flexibility is established, in which spatial-temporal transfer of flexibility is modeled with the derivation of flexibility sensitivity factors. Further, a DLMP-based flexibility value quantification model is proposed with nodal net power as the unit for flexibility pricing. The obtained flexibility price can not only quantify flexibility value but also be used to guide the flexible resources. Finally, the effectiveness of the proposed method is validated on a modified IEEE 33-node distribution system and a modified IEEE 123-node distribution system. Results verify that the proposed method can quantify the impact of nodal net power on operational flexibility and effectively improve the overall flexibility performance through the guide of flexibility price

Interactive visual cluster analysis by contrastive dimensionality reduction

We propose a contrastive dimensionality reduction approach (CDR) for interactive visual cluster analysis. Although dimensionality reduction of high-dimensional data is widely used in visual cluster analysis in conjunction with scatterplots, there are several limitations on effective visual cluster analysis. First, it is non-trivial for an embedding to present clear visual cluster separation when keeping neighborhood structures. Second, as cluster analysis is a subjective task, user steering is required. However, it is also non-trivial to enable interactions in dimensionality reduction. To tackle these problems, we introduce contrastive learning into dimensionality reduction for high-quality embedding. We then redefine the gradient of the loss function to the negative pairs to enhance the visual cluster separation of embedding results. Based on the contrastive learning scheme, we employ link-based interactions to steer embeddings. After that, we implement a prototype visual interface that integrates the proposed algorithms and a set of visualizations. Quantitative experiments demonstrate that CDR outperforms existing techniques in terms of preserving correct neighborhood structures and improving visual cluster separation. The ablation experiment demonstrates the effectiveness of gradient redefinition. The user study verifies that CDR outperforms t-SNE and UMAP in the task of cluster identification. We also showcase two use cases on real-world datasets to present the effectiveness of link-based interactions

Identification of M2-like macrophage-related signature for predicting the prognosis, ecosystem and immunotherapy response in hepatocellular carcinoma.

BackgroundHepatocellular carcinoma is one of the most common malignancies worldwide, representing a big health-care challenge globally. M2-like macrophages are significantly correlated with tumor progression, metastasis and treatment resistance.MethodsIntegrative 10 machine learning algorithms were performed to developed a M2-like macrophage related prognostic signature (MRPS). Single-cell RNA-sequencing analysis was performed to dissect the ecosystem of HCC. Several approaches, including TIDE score, immunophenoscore, TMB score and tumor escape score were used to evaluate the predictive role of MRPS in immunology response.ResultsThe optimal MRPS constructed by the combination of stepCox + superPC algorithm served as an independent risk factor and showed stable and powerful performances in predicting the overall survival rate of HCC patients with 2-, 3-, and 4-year AUCs of 0. 763, 0.751, and 0.699 in TCGA cohort. HCC patients with low risk score possessed a more interaction of immunoactivated cells, including NK, CD8+ cytotoxic T, and activated B, and a less interaction of immunosuppressive cells, including Treg, CD4+ exhauster T, and M2-like macrophage. Low risk score indicated a higher PD1&CTLA4 immunophenoscore, higher TMB score, lower TIDE score and lower tumor escape score in HCC, suggesting a better immunotherapy response. The IC50 value of docetaxel, gemcitabine, crizotinib and Osimertinib in HCC with high risk score were lower versus that with low risk score. HCC patients with high risk score had a higher score of cancer-related hallmarks, including angiogenesis, DNA repair, EMT, glycolysis, and NOTCH signaling.ConclusionOur study proposed a novel MRPS for predicting the prognosis, ecosystem and immunotherapy response in HCC