Wireless sensors and IoT platform for intelligent HVAC control

Energy consumption of buildings (residential and non-residential) represents approximately 40% of total world electricity consumption, with half of this energy consumed by HVAC systems. Model-Based Predictive Control (MBPC) is perhaps the technique most often proposed for HVAC control, since it offers an enormous potential for energy savings. Despite the large number of papers on this topic during the last few years, there are only a few reported applications of the use of MBPC for existing buildings, under normal occupancy conditions and, to the best of our knowledge, no commercial solution yet. A marketable solution has been recently presented by the authors, coined the IMBPC HVAC system. This paper describes the design, prototyping and validation of two components of this integrated system, the Self-Powered Wireless Sensors and the IOT platform developed. Results for the use of IMBPC in a real building under normal occupation demonstrate savings in the electricity bill while maintaining thermal comfort during the whole occupation schedule.QREN SIDT [38798]; Portuguese Foundation for Science & Technology, through IDMEC, under LAETA [ID/EMS/50022/2013

Lifestyles and surveillance of sexual and reproductive women’s health

Abstract: Background: The epidemic increase of diseases is closely related to lifestyle changes. The low adhesion to breast self-examination and cervical cytology hinders prevention and early diagnosis during the asymptomatic state of two silent diseases, with nonspecific symptoms that are a major cause of death by cancer in the Portuguese female population. Objectives: To analyze the influence of sociodemographic variables and lifestyles in the surveillance of sexual and reproductive health of Portuguese women. Methods: Quantitative, non-experimental, correlational and cross-sectional study, conducted with a non-probabilistic convenience sample of 522 women aged between 18 and 67 years old, who applied the questionnaires about Breast self-examination, Knowledge about cervical cancer and the Inventory "My Lifestyle" (Ribeiro, 1993. Results: The average age of women is 38.89 years old. Women aged 31-37 years old (28.6%), Portuguese (99.1%), cohabiting with a partner and / or child (74.0%), with an active employment status (67 5%), residing in urban areas (55.8%) with higher education and attending family planning consultations have better lifestyles, without statistical significance (F = 0.016, p = 0.899). Conclusions: Healthy behaviors and lifestyles are crucial to good overall health. Adhesion to surveillance of sexual and reproductive women’s health is influenced by several factors, including the place of residence, employment status and lifestyles. These variables must be considered by health professionals when planning periodic screenings.info:eu-repo/semantics/publishedVersio

2HDM interpretations of the CMS diphoton excess at 95 GeV

In both Run 1 and Run 2 of the LHC, the CMS collaboration has observed an excess of events in the searches for low-mass Higgs bosons in the diphoton final state at a mass of about 95 GeV. After a recent update of the experimental analysis, in which the full Run 2 data collected at 13 TeV has been included and an improved experimental calibration has been applied, the local significance of the excess amounts to $2.9\sigma$. The presence of this diphoton excess is especially interesting in view of a further excess observed by CMS in ditau final states at a comparable mass and similar local significance. Moreover, an excess of events with about $2\sigma$ local significance and consistent with a mass of 95 GeV was observed in LEP searches for a Higgs boson decaying to pairs of bottom quarks. We interpret the CMS diphoton excess in combination with the ditau excess in terms of a pseudoscalar resonance in the CP-conserving two-Higgs-doublet model (2HDM). Furthermore, we discuss the possibility that, if CP-violation is taken into account, a CP-mixed scalar state can in addition describe the LEP result, thus accommodating all three excesses simultaneously. We find that the region of parameter space where both the CMS diphoton and ditau excesses can be fitted is in tension with current constraints from the flavour sector, potentially calling for other new-physics contributions to flavour-physics observables, most notably $b \to s\gamma$ transitions. We also comment on the compatibility with the recent ATLAS di-photon searches.Comment: 37 pages, 13 figure

Does cultural background influence the dissemination and severity of the COVID-19 pandemic?

The COVID-19 pandemic has spread throughout the globe affecting countries worldwide. However, several differences have been observed in the number of daily new cases, the COVID-19 reproduction rate, and the severity of the disease in different countries. Previous studies have mostly highlighted government restriction policies to mitigate the pandemic effects as reasons for such differences. This study focuses on 101 countries and proposes that each country’s cultural background is also accountable for such differences. We considered the six Hofstede’s cultural dimensions (power distance, individualism, masculinity, uncertainty avoidance, long term orientation, and indulgence) and statistically analyzed their correlation with several COVID-19 impact metrics in comparison to several restriction policies. Our results support our claim that national culture influences both acceptance and subsequent adoption of restriction policies and the implementation by each government of those policies. We highlight that the attitudes towards and trust in political institutions, policies and governance is influenced by the cultural background, which is reflected in the pandemic numbers. As a main takeaway from this study, we conclude that data-driven models which aim at predicting the pandemic impact evolution at a global scale should also include variables that reflect the cultural background of each nation.info:eu-repo/semantics/publishedVersio

Does Big Data Require Complex Systems? A Performance Comparison Between Spark and Unicage Shell Scripts

The paradigm of big data is characterized by the need to collect and process data sets of great volume, arriving at the systems with great velocity, in a variety of formats. Spark is a widely used big data processing system that can be integrated with Hadoop to provide powerful abstractions to developers, such as distributed storage through HDFS and resource management through YARN. When all the required configurations are made, Spark can also provide quality attributes, such as scalability, fault tolerance, and security. However, all of these benefits come at the cost of complexity, with high memory requirements, and additional latency in processing. An alternative approach is to use a lean software stack, like Unicage, that delegates most control back to the developer. In this work we evaluated the performance of big data processing with Spark versus Unicage, in a cluster environment hosted in the IBM Cloud. Two sets of experiments were performed: batch processing of unstructured data sets, and query processing of structured data sets. The input data sets were of significant size, ranging from 64 GB to 8192 GB in volume. The results show that the performance of Unicage scripts is superior to Spark for search workloads like grep and select, but that the abstractions of distributed storage and resource management from the Hadoop stack enable Spark to execute workloads with inter-record dependencies, such as sort and join, with correct outputs.Comment: 10 pages, 14 figure

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8

BACKGROUND: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. OBJECTIVE: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). METHOD: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately - using standard univariate VBM - and simultaneously, with multivariate analyses. RESULTS: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. CONCLUSION: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities

Assessment and comparison of the Marennes-Oléron Bay (France) and Carlingford Lough (Ireland) carrying capacity with ecosystem models

Based on the individual growth, food limitation, population renewal through seeding, and individual marketable size, a theoretical model of the cultured species population dynamics was used to assess the carrying capacity of an ecosystem. It gave a domeshape curve relating the annual production and the standing stock under the assumption of individual growth limited by the available food in an ecosystem. It also showed the influence of mortality rate and marketable size on this curve and was introduced as a means to explore the global properties resulting from the interactions between the ecophysiology of the reared species and the environment at the ecosystem level. In a second step, an ecosystem model was built to assess the carrying capacity of MarennesOl ´eron bay, the most important shellfish culture site in France, with a standing stock of Crassostrea gigas around 100 000 tonnes fresh weight (FW) and an annual production of 30 000 tonnes FW. The ecosystem model focused on the oyster growth rate and considered the interaction between food availability, residence time of the water, oyster ecophysiology and number of individuals. It included a spatial discretization of the bay (box design) based on a hydrodynamicmodel, and the nitrogen or carbon cycling between phytoplankton, cultured oysters, and detritus. From simulations of the oyster growth with different seeding values, a curve relating the total annual production and the standing stock was obtained. This curve exhibited a dome shape with a maximum production corresponding to an optimum standing stock. The model predicted amaximum annual production of 45 000 tonnes FWfor a standing stock around 115 000 tonnes FW. The prediction confirmed some results obtained empirically in the case of MarennesOl ´eron bay and the results of the theoretical model. Results were compared with those obtained in Carlingford Lough (Ireland) using a similar ecosystem model. Carlingford Lough is a small intertidal bay where the same species is cultured at a reduced scale, with current biomass less than 500 tonnes FW. The model showed that the standing stock can be increased from 200 tonnes FW to approximately 1500 tonnes FW before any decrease of the production

Analysis of the deep chlorophyll maximum across the Azores Front

Physical, chemical and biological observations made in late July and August 1997 across the Azores Front (37ºN, 32ºW to 32ºN, 29ºW) are presented. The objectives of the study were: (1) to analyse horizontal and vertical profiles of temperature, salinity, density, nutrients and chlorophyll-a (Chl a) of the top 350 m; (2) to identify the main differences in the deep Chl a Maximum (DCM) and hydrographic structure between the water masses that pass north and south of the Azores Front; and (3) to estimate phytoplankton primary production in these water masses. Horizontal and vertical profiles of salinity, temperature, density, nutrients and phytoplankton pigments in the top 350 m were analysed. The Front separates two distinct water types: the 18 ºC ModeWater (18MW) of subtropical origin, and the 15 ºC ModeWater (15MW) of sub-polar origin. Differences in the DCM and hydrographic structure between 18 MW and 15 MW were observed in the contour plots of each section. The average Chl a concentration between 5 and 200 m depth decreased significantly from 15 MW to 18 MW. The same pattern was observed for the Chl a concentration at the DCM depth. A vertical one-dimensional model was used to estimate the phytoplankton primary production in the 15 MW and 18 MW and led to an estimated water column average gross primary productivity (GPP) between 1.08 and 2.71 mg C

Collaborative methodologies in island fishing communities of cape verde

Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Marine litter has been considered one of the most serious global challenges, requiring urgent action by governmental bodies, especially in African Small Island Developing States (SIDS), where resources and research are limited. In addition to this, waste management and environmental education and ocean literacy programs in schools are scarce, with islands suffering more seriously from these problems. Despite the amount of literature regarding causes and impacts of marine litter, there is still not enough research conducted concerning the public perceptions on both the problem and the potential solutions. This is even more noticeable in African developing countries, where resources and research are scarce. Perception plays a key role for ecosystem management and conservation policies. This study intends to explore the perceptions of local island fishing communities in Cape Verde regarding marine litter, in order to contribute for an improvement of marine ecosystem management and development of conservation policies. To achieve that, two participatory sessions were conducted in two communities in the island of Santiago—Porto Mosquito and Porto Gouveia—where brainstorming and active listening were used to create shared and authentic spaces for dialogue between the members of the community. Results show that the population of both communities were very aware of the marine litter problem. They were able to identify the lack of a proper waste management system in the island and the inappropriate behaviours of the population as the main causes of this problem. Equipment damages and the presence of plastic inside the fish were the most relevant impacts identified by the participants. These findings reinforce previous research on the importance of public engagement and environmental education to contribute to the conservation of marine ecosystems and to build a strong collaborative ocean governance.publishersversionpublishe