Performance analysis of massive MIMO receivers

We face now an exponential increase in wireless devices and to allow good user experience, it is imperative that the next generation of mobile (5G) communications ensures reliable connections, high data transfer rates and low latency. One way to increase the data transfer rate is to use massive Multiple-Input, Multiple-Output (MIMO) systems, that is, systems with multiple antennas to emit and multiple antennas to receive thus allowing spatial diversity. In these systems, to increase the battery life of the devices it is preferable to use the Single-Carrier with Frequency-Domain Equalization modulation in the uplink as this modulation reduces the complexity in the emitter, transferring it to the receiver, in this case the Base Staion, where it is quite acceptable. This dissertation studies the performance of massive MIMO receiver systems, comparing it to the performance achieved with the Matched Filter Bound (MFB). The Iterative Block Decision-Feedback Equalizer (IB-DFE) receiver presents a very similar performance to the MFB, however, the algorithm requires matrix inversions, which in the systems under study, where the size of the matrix is high, implies an increase of the associated operations increases. Thus it is very important that low complexity receivers, such as the Maximal-Ratio Combining (MRC) or Equal Gain Combining are used. In this dissertation, a simple receiver is proposed combining the IB-DFE receiver with the MRC receiver, thus creating a low complexity receiver with excellent performanceAtualmente, sente-se um aumento exponencial nos dispositivos wireless. De modo a permitir uma boa experiência por parte dos utilizadores é fundamental que a próxima geração de comunicações móveis (5G) assegure fiabilidade nas ligações, uma elevada taxa de transferência de dados e baixa latência. Uma maneira de elevar a taxa de transferência de dados é utilizar sistemas massive Multiple-Input, Multiple-Output (MIMO), ou seja, sistemas com múltiplas antenas a emitir e múltiplas antenas a receber permitindo assim diversidade espacial. Nestes sistemas, para aumentar a bateria dos dispositivos é preferível usar no uplink a modulação Single-Carrier with Frequency-Domain Equalization pois esta modulação reduz a complexidade no emissor transferindo-a para o recetor, neste caso na Base Station, onde isso é bastante aceitável. Esta dissertação estuda o desempenho dos recetores dos sistemas massive MIMO, comparando o desempenho alcançado com o desempenho do Matched Filter Bound (MFB). O recetor Iterative Block Decision-Feedback Equalizer (IBDFE) apresenta um desempenho muito semelhante ao do MFB no entanto, o algoritmo do receptor inverte matrizes, o que nos sistemas em estudo, onde o tamanho das matrizes é elevado, se reflecte no aumento da complexidade das operações associadas. Deste modo, é importante que sejam utilizados recetores de baixa complexidade tal como o Maximal-Ratio Combining (MRC) ou o Equal Gain Combining. Esta dissertação propõe um recetor simples que combina um recetor IB-DFE com um recetor MRC, criando desde modo um recetor de baixa complexidade e com excelente desempenho

Towards a new cloud-based planning and optimization methodology for mobile communication networks

The great concern of telecommunication operators to offer high-quality services to their customers requires a constant care with the state of the networks. These networks can present some problems that imply that the experience offered to customers is unsatisfactory. In order to monitor these situations, operators collect, on a fairly regular basis, data, like drive tests, that allow them to monitor and correct minor issues. This thesis takes advantage of the data collected and uses it in network planning in order to precisely obtain the coverage estimation of a network. In order to automate failure correction mechanisms, a totally automatic propagation model is presented, which precisely describes the state of the network, allowing it to be used for network planning and optimisation. After its implementation, the model was compared to a second model, generated through Artificial Intelligence, which is completely agnostic to all telecommunications knowledge. These models, for the considered scenarios, reached average absolute errors between estimated and actual values of 6.1 dB with a standard deviation of 4 dB. The existence of several real telecommunication network measures and their evolution to Multiple Input, Multiple Output (MIMO) systems motivated not only the investigation on the coverage impact with the change from a Single Input, Single Output (SISO) to a MIMO system, but also the investigation on the reduction of complexity of the receivers used in MIMO systems. The closer the Bit Error Rate performance of the receiver is to the Matched Filter Bound, the smaller will be the reduction in the coverage area with the transition from a SISO system to a MIMO system.A grande preocupação dos operadores de telecomunicações em oferecerem serviços de alta qualidade aos seus clientes leva a um constante cuidado com o estado das redes. Estas redes podem apresentar alguns problemas que implicam que a experiência oferecida aos clientes seja desagradável. De forma a monitorizar estas situações, os operadores recolhem, com bastante regularidade, dados, como "drive tests", que lhes permitem avaliar e corrigir pequenos problemas. Esta tese aproveita os dados recolhidos e utiliza-os no planeamento da rede de forma a obter fielmente a estimativa de cobertura de uma rede. De forma a automatizar mecanismos de correção de falhas, é apresentado um modelo de propagação completamente automático, que descreve de forma precisa o estado da rede permitindo que seja aplicado em algoritmos de planeamento e otimização da rede. Após a sua implementação, este modelo foi comparado com um segundo modelo, gerado através de inteligência artificial, que é completamente agnóstico a todo o conhecimento de telecomunicações. Estes modelos, para os cenários estudados, atingiram erros absolutos médios entre os valores estimados e os valores reais de 6.1 dB com um desvio padrão de 4 dB. A existência de diversos dados reais das redes de telecomunicações e a evolução para os sistemas "Multiple Input", "Multiple Output" (MIMO) motivou não só a investigação no impacto da cobertura com a mudança de um sistema "Single Input", "Single Output" (SISO) para um sistema MIMO, mas também a investigação na redução de complexidade dos recetores utilizados em sistemas MIMO. Quanto mais próxima a "Bit Error Rate performance" do recetor estiver do "Matched Filter Bound", menor será a redução na área de cobertura com a transição de um sistema SISO para um sistema MIMO

Genetic and microenvironmental intra-tumor heterogeneity impacts colorectal cancer evolution and metastatic development

© The Author(s) 2022 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Colorectal cancer (CRC) is a highly diverse disease, where different genomic instability pathways shape genetic clonal diversity and tumor microenvironment. Although intra-tumor heterogeneity has been characterized in primary tumors, its origin and consequences in CRC outcome is not fully understood. Therefore, we assessed intra- and inter-tumor heterogeneity of a prospective cohort of 136 CRC samples. We demonstrate that CRC diversity is forged by asynchronous forms of molecular alterations, where mutational and chromosomal instability collectively boost CRC genetic and microenvironment intra-tumor heterogeneity. We were able to depict predictor signatures of cancer-related genes that can foresee heterogeneity levels across the different tumor consensus molecular subtypes (CMS) and primary tumor location. Finally, we show that high genetic and microenvironment heterogeneity are associated with lower metastatic potential, whereas late-emerging copy number variations favor metastasis development and polyclonal seeding. This study provides an exhaustive portrait of the interplay between genetic and microenvironment intra-tumor heterogeneity across CMS subtypes, depicting molecular events with predictive value of CRC progression and metastasis development.This work was financed by national funds from FCT - Fundação para a Ciência e a Tecnologia, I.P., in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences - UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy - i4HB. This research was also funded by: PTDC/MED-ONC/28660/2017 from Fundação para a Ciência e Tecnologia (FCT) to A.R.G. A.R.G is recipient of Researcher Grant CEECIND/02699/2017 from FCT. The biobanking of CRC samples from Hospital Santa Maria, Lisbon, Portugal was supported by FCT research grant PIC/IC/82821/2007. This work was produced with the support of INCD funded by FCT and FEDER under the project 22153-01/SAICT/2016.info:eu-repo/semantics/publishedVersio

Viral genetic clustering and transmission dynamics of the 2022 mpox outbreak in Portugal

Pathogen genome sequencing during epidemics enhances our ability to identify and understand suspected clusters and investigate their relationships. Here, we combine genomic and epidemiological data of the 2022 mpox outbreak to better understand early viral spread, diversification and transmission dynamics. By sequencing 52% of the confirmed cases in Portugal, we identified the mpox virus sublineages with the highest impact on case numbers and fitted them into a global context, finding evidence that several international sublineages probably emerged or spread early in Portugal. We estimated a 62% infection reporting rate and that 1.3% of the population of men who have sex with men in Portugal were infected. We infer the critical role played by sexual networks and superspreader gatherings, such as sauna attendance, in the dissemination of mpox virus. Overall, our findings highlight genomic epidemiology as a tool for the real-time monitoring and control of mpox epidemics, and can guide future vaccine policy in a highly susceptible population.info:eu-repo/semantics/publishedVersio

A list of land plants of Parque Nacional do Caparaó, Brazil, highlights the presence of sampling gaps within this protected area

Brazilian protected areas are essential for plant conservation in the Atlantic Forest domain, one of the 36 global biodiversity hotspots. A major challenge for improving conservation actions is to know the plant richness, protected by these areas. Online databases offer an accessible way to build plant species lists and to provide relevant information about biodiversity. A list of land plants of “Parque Nacional do Caparaó” (PNC) was previously built using online databases and published on the website "Catálogo de Plantas das Unidades de Conservação do Brasil." Here, we provide and discuss additional information about plant species richness, endemism and conservation in the PNC that could not be included in the List. We documented 1,791 species of land plants as occurring in PNC, of which 63 are cited as threatened (CR, EN or VU) by the Brazilian National Red List, seven as data deficient (DD) and five as priorities for conservation. Fifity-one species were possible new ocurrences for ES and MG states

Identification of biomarkers predictive of metastasis development in early-stage colorectal cancer using network-based regularization

Abstract Colorectal cancer (CRC) is the third most common cancer and the second most deathly worldwide. It is a very heterogeneous disease that can develop via distinct pathways where metastasis is the primary cause of death. Therefore, it is crucial to understand the molecular mechanisms underlying metastasis. RNA-sequencing is an essential tool used for studying the transcriptional landscape. However, the high-dimensionality of gene expression data makes selecting novel metastatic biomarkers problematic. To distinguish early-stage CRC patients at risk of developing metastasis from those that are not, three types of binary classification approaches were used: (1) classification methods (decision trees, linear and radial kernel support vector machines, logistic regression, and random forest) using differentially expressed genes (DEGs) as input features; (2) regularized logistic regression based on the Elastic Net penalty and the proposed iTwiner—a network-based regularizer accounting for gene correlation information; and (3) classification methods based on the genes pre-selected using regularized logistic regression. Classifiers using the DEGs as features showed similar results, with random forest showing the highest accuracy. Using regularized logistic regression on the full dataset yielded no improvement in the methods’ accuracy. Further classification using the pre-selected genes found by different penalty factors, instead of the DEGs, significantly improved the accuracy of the binary classifiers. Moreover, the use of network-based correlation information (iTwiner) for gene selection produced the best classification results and the identification of more stable and robust gene sets. Some are known to be tumor suppressor genes (OPCML-IT2), to be related to resistance to cancer therapies (RAC1P3), or to be involved in several cancer processes such as genome stability (XRCC6P2), tumor growth and metastasis (MIR602) and regulation of gene transcription (NME2P2). We show that the classification of CRC patients based on pre-selected features by regularized logistic regression is a valuable alternative to using DEGs, significantly increasing the models’ predictive performance. Moreover, the use of correlation-based penalization for biomarker selection stands as a promising strategy for predicting patients’ groups based on RNA-seq data

Viral genetic clustering and transmission dynamics of the 2022 mpox outbreak in Portugal.

Acknowledgements: We gratefully acknowledge the engagement and willingness of all participants to share information critical to the investigation. We are grateful to the authors and laboratories that originated and submitted the genetic sequences released in GenBank. The acquisition of equipment associated with whole-genome sequencing used in this study (including the Illumina NextSeq 2000) was funded by the HERA (Human and Environmental Risk Assessment) project (Grant/2021/PHF/23776), supported by the European Commission through the European Centre for Disease Prevention and Control (ECDC), and partially funded by the GenomePT project (POCI-01-0145-FEDER-022184), supported by COMPETE 2020 (Operational Programme for Competitiveness and Internationalisation (POCI)), Lisboa Portugal Regional Operational Programme (Lisboa2020), Algarve Portugal Regional Operational Programme (CRESC Algarve2020) under the PORTUGAL 2020 Partnership Agreement through the European Regional Development Fund (ERDF), and by the Portuguese Science and Technology Foundation (FCT). This study was also supported by the ERINHA-Advance project (funded by the European Union’s Horizon 2020 Research & Innovation program, grant agreement no. 824061) and benefited from co-funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement no. 773830 (One Health European Joint Programme), in particular by the co-funding of the post-doctoral fellowships of J.S.D. and V.M. and the development of INSaFLU. We also thank M. Pinheiro (iBiMED at the Universidade de Aveiro) for his continuous support in updating the INSaFLU platform and the Infraestrutura Nacional de Computação Distribuída (INCD) for providing computational resources for testing it. INCD was funded by the FCT and FEDER under the project 22153-01/SAICT/2016. M.P.D. is funded by the Gates Cambridge Scholarship (no. OPP1144). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The GAT-Intendente team also thanks A. Vasques, L. Fortuna, J. Moreira, I. Correia and Á. Baginha.Pathogen genome sequencing during epidemics enhances our ability to identify and understand suspected clusters and investigate their relationships. Here, we combine genomic and epidemiological data of the 2022 mpox outbreak to better understand early viral spread, diversification and transmission dynamics. By sequencing 52% of the confirmed cases in Portugal, we identified the mpox virus sublineages with the highest impact on case numbers and fitted them into a global context, finding evidence that several international sublineages probably emerged or spread early in Portugal. We estimated a 62% infection reporting rate and that 1.3% of the population of men who have sex with men in Portugal were infected. We infer the critical role played by sexual networks and superspreader gatherings, such as sauna attendance, in the dissemination of mpox virus. Overall, our findings highlight genomic epidemiology as a tool for the real-time monitoring and control of mpox epidemics, and can guide future vaccine policy in a highly susceptible population

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data