The Domination Number of Grids

In this paper, we conclude the calculation of the domination number of all $n\times m$ grid graphs. Indeed, we prove Chang's conjecture saying that for every $16\le n\le m$, $\gamma(G_{n,m})=\lfloor\frac{(n+2)(m+2)}{5}\rfloor -4$.Comment: 12 pages, 4 figure

Urban traffic simulation using mobility patterns synthesized from real sensors

Data Availability Statement: The data presented in this study are openly available in Zenodo at 10.5281/zenodo.7997433 and were produced using the code available at https://github.com/fabio-r-goncalves/norte (accessed on 1 November 2023).Smart cities are an ongoing research topic with multiple sub-research areas, from traffic control to optimization and even safety. However, testing the new methodologies or technologies directly in the real world is an almost impossible feat that, inclusively, can result in disaster. Thus, there is the importance of simulation. Simulation enables testing new and complex methodologies and gauging their impact in a realistic context without adding any safety issues. Additionally, these can accurately map real-world conditions depending on the simulation configuration. One key aspect of the simulation is the traffic flows in the simulated region. These may be hard to find and, if ill-set, may introduce bias in the results. This work is on the characterization of the traffic in the city center of Guimarães, Portugal. An urban simulation scenario was established, using SUMO as the mobility traffic simulator, with traffic patterns derived from real-world data provided by Guimarães City Hall and using Eclipse MOSAIC for extended vehicular simulation. Apart from mobility patterns analysis, this work also provides publicly accessible datasets, simulations, and applications made available to future research works.Funding: This work has been supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020 by FEDER funds, through the North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020, within the Project Scope NORTE-01-0145-FEDER-000086

Uniformity of water distribution in a central pivot with the use of the Time Domain Reflectometry technique on surface and soil

The evaluation of the uniformity of water distribution in an irrigation system is done above the surface of the soil. The main objective of this work was to evaluate the uniformity of water distribution in a central pivot under field conditions, through the use of the CUD and CUC coefficients. On the surface, the uniformity was obtained with the use of the ABNT methodology, therefore placing two collector lines displaced three degrees from the initial pivot position. In order to obtain the uniformity in the soil, the water content was determined with the TDR (Time Domain Reflectometry), which is a simple and fast technique. The results demonstrated that uniformity in the soil was greater than on the surface and above the recommended range. The water arrangement in the soil promotes that condition. Therefore in the economic design of irrigation systems, the uniformity coefficients in the soil should be considered.A avaliação da uniformidade de distribuição de água de um sistema de irrigação é feita acima da superfície do solo. Tendo em vista a importância da uniformidade no interior do solo quando submetido a uma irrigação, desenvolveu-se o presente trabalho com o objetivo de se avaliar a uniformidade de distribuição de água, tanto acima como no interior do solo, através dos coeficientes CUD e CUC, com um pivô central operando em condições de campo. Acima da superfície, a uniformidade foi obtida seguindo-se a metodologia da Associação Brasileira de Normas Técnicas (ABNT) e se alocando duas linhas de coletores com abertura de 3º, a partir do ponto inicial do pivô. Propôs-se, para obtenção da uniformidade no interior do solo, a utilização da umidade determinada pelo TDR (Reflectometria no Domínio do Tempo) visto que é uma técnica simples e produz resultados imediatos. Os resultados encontrados demonstraram que a uniformidade no interior do solo foi maior que na superfície, ficando acima da faixa recomendada, mostrando que a redistribuição da água no interior do solo promove maior uniformidade de umidade no perfil do solo que a encontrada na lâmina aplicada; portanto, no dimensionamento econômico de sistemas de irrigação, os coeficientes de uniformidade obtidos no interior do solo devem ser considerados.18719

In the matter of the request of Liberty Mutual Fire Insurance Company, a Massachusetts domestic stock insurance company, to redomesticate to the state of Wisconsin

Submitted by Nuzia Santos ([email protected]) on 2018-08-24T16:36:28Z No. of bitstreams: 1 Phosphatidyl Inositol 3 Kinase-Gamma Balances.pdf: 10035595 bytes, checksum: 5a61fb2c618990d4314d36db3868ee2e (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2018-08-24T16:44:27Z (GMT) No. of bitstreams: 1 Phosphatidyl Inositol 3 Kinase-Gamma Balances.pdf: 10035595 bytes, checksum: 5a61fb2c618990d4314d36db3868ee2e (MD5)Made available in DSpace on 2018-08-24T16:44:27Z (GMT). No. of bitstreams: 1 Phosphatidyl Inositol 3 Kinase-Gamma Balances.pdf: 10035595 bytes, checksum: 5a61fb2c618990d4314d36db3868ee2e (MD5) Previous issue date: 2018Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Vírus Respiratórios e do Sarampo. Rio de Janeiro, RJ, Brazil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Fisiologia e Biofísica. Laboratório de Imunologia e Mecânica Pulmonar. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ, Brazil / UNIFRANZ. Coordinación Nacional de Investigación. La Paz, Bolivia.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Morfologia. Belo Horizonte, MG, BrazilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil / Universidade de São Paulo. Departamento de Farmacologia. Laboratório de Inflamação e Dor. Universidade de São Paulo. Ribeirão Preto, SP, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Vírus Respiratórios e do Sarampo. Rio de Janeiro, RJ, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil / Fundação Oswaldo Cruz. Instituto René Rachou. Laboratório de Imunologia de Doenças Virais. Belo Horizonte, MG, BrazilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de RNA de Interferência Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Vírus Respiratórios e do Sarampo. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto René Rachou. Laboratório de Imunologia de Doenças Virais. Belo Horizonte, MG, BrazilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil / Universidade Federal de Minas Gerais. Faculdade de Farmácia. Departamento de Análises Clínicas e Toxicológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Fisiologia e Biofísica. Laboratório de Imunologia e Mecânica Pulmonar. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Laboratório de Imunofarmacologia. Belo Horizonte, MG, Brazil.Influenza A virus (IAV) infection causes severe pulmonary disease characterized by intense leukocyte infiltration. Phosphoinositide-3 kinases (PI3Ks) are central signaling enzymes, involved in cell growth, survival, and migration. Class IB PI3K or phosphatidyl inositol 3 kinase-gamma (PI3Kγ), mainly expressed by leukocytes, is involved in cell migration during inflammation. Here, we investigated the contribution of PI3Kγ for the inflammatory and antiviral responses to IAV. PI3Kγ knockout (KO) mice were highly susceptible to lethality following infection with influenza A/WSN/33 H1N1. In the early time points of infection, infiltration of neutrophils was higher than WT mice whereas type-I and type-III IFN expression and p38 activation were reduced in PI3Kγ KO mice resulting in higher viral loads when compared with WT mice. Blockade of p38 in WT macrophages infected with IAV reduced levels of interferon-stimulated gene 15 protein to those induced in PI3Kγ KO macrophages, suggesting that p38 is downstream of antiviral responses mediated by PI3Kγ. PI3Kγ KO-derived fibroblasts or macrophages showed reduced type-I IFN transcription and altered pro-inflammatory cytokines suggesting a cell autonomous imbalance between inflammatory and antiviral responses. Seven days after IAV infection, there were reduced infiltration of natural killer cells and CD8+ T lymphocytes, increased concentration of inflammatory cytokines in bronchoalveolar fluid, reduced numbers of resolving macrophages, and IL-10 levels in PI3Kγ KO. This imbalanced environment in PI3Kγ KO-infected mice culminated in enhanced lung neutrophil infiltration, reactive oxygen species release, and lung damage that together with the increased viral loads, contributed to higher mortality in PI3Kγ KO mice compared with WT mice. In humans, we tested the genetic association of disease severity in influenza A/H1N1pdm09-infected patients with three potentially functional PIK3CG single-nucleotide polymorphisms (SNPs), rs1129293, rs17847825, and rs2230460. We observed that SNPs rs17847825 and rs2230460 (A and T alleles, respectively) were significantly associated with protection from severe disease using the recessive model in patients infected with influenza A(H1N1)pdm09. Altogether, our results suggest that PI3Kγ is crucial in balancing antiviral and inflammatory responses to IAV infection

Safeguarding human–wildlife cooperation

Human–wildlife cooperation occurs when humans and free-living wild animals actively coordinate their behavior to achieve a mutually beneficial outcome. These interactions provide important benefits to both the human and wildlife communities involved, have wider impacts on the local ecosystem, and represent a unique intersection of human and animal cultures. The remaining active forms are human–honeyguide and human–dolphin cooperation, but these are at risk of joining several inactive forms (including human–wolf and human–orca cooperation). Human–wildlife cooperation faces a unique set of conservation challenges, as it requires multiple components—a motivated human and wildlife partner, a suitable environment, and compatible interspecies knowledge—which face threats from ecological and cultural changes. To safeguard human–wildlife cooperation, we recommend: (i) establishing ethically sound conservation strategies together with the participating human communities; (ii) conserving opportunities for human and wildlife participation; (iii) protecting suitable environments; (iv) facilitating cultural transmission of traditional knowledge; (v) accessibly archiving Indigenous and scientific knowledge; and (vi) conducting long-term empirical studies to better understand these interactions and identify threats. Tailored safeguarding plans are therefore necessary to protect these diverse and irreplaceable interactions. Broadly, our review highlights that efforts to conserve biological and cultural diversity should carefully consider interactions between human and animal cultures