Polyhydroxyalkanoates Production by Mixed Microbial Culture under High Salinity

PTDC/BTA-BTA/30902/2017 UIDP/04378/2020 UIDB/04378/2020 LA/P/0140/2020The fishing industry produces vast amounts of saline organic side streams that require adequate treatment and disposal. The bioconversion of saline resources into value-added products, such as biodegradable polyhydroxyalkanoates (PHAs), has not yet been fully explored. This study investigated PHA production by mixed microbial cultures under 30 gNaCl/L, the highest NaCl concentration reported for the acclimatization of a PHA-accumulating mixed microbial culture (MMC). The operational conditions used during the culture-selection stage resulted in an enriched PHA-accumulating culture dominated by the Rhodobacteraceae family (95.2%) and capable of storing PHAs up to 84.1% wt. (volatile suspended solids (VSS) basis) for the highest organic loading rate (OLR) applied (120 Cmmol/(L.d)). This culture presented a higher preference for the consumption of valeric acid (0.23 ± 0.03 CmolHVal/(CmolX.h)), and the 3HV monomer polymerization (0.33 ± 0.04 CmmolHV/(CmmolX.h) was higher as well. As result, a P(3HB-co-3HV)) with high HV content (63% wt.) was produced in the accumulation tests conducted at higher OLRs and with 30 gNaCl/L. A global volumetric PHA productivity of 0.77 gPHA/(L.h) and a specific PHA productivity of 0.21 gPHA/(gX.h) were achieved. These results suggested the significant potential of the bioconversion of saline resources into value-added products, such as PHAs.publishersversionpublishe

Data-driven approach for incident management in a smart city

Buildings in Lisbon are often the victim of several types of events (such as accidents, fires, collapses, etc.). This study aims to apply a data-driven approach towards knowledge extraction from past incident data, nowadays available in the context of a Smart City. We apply a Cross Industry Standard Process for Data Mining (CRISP-DM) approach to perform incident management of the city of Lisbon. From this data-driven process, a descriptive and predictive analysis of an events dataset provided by the Lisbon Municipality was possible, together with other data obtained from the public domain, such as the temperature and humidity on the day of the events. The dataset provided contains events from 2011 to 2018 for the municipality of Lisbon. This data mining approach over past data identified patterns that provide useful knowledge for city incident managers. Additionally, the forecasts can be used for better city planning, and data correlations of variables can provide information about the most important variables towards those incidents. This approach is fundamental in the context of smart cities, where sensors and data can be used to improve citizens’ quality of life. Smart Cities allow the collecting of data from different systems, and for the case of disruptive events, these data allow us to understand them and their cascading effects better.info:eu-repo/semantics/publishedVersio

Pilot-scale valorisation of salmon peptone into polyhydroxyalkanoates by mixed microbial cultures under conditions of high ammonia concentration

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Multidisciplinary Development and Initial Validation of a Clinical Knowledge Base on Chronic Respiratory Diseases for mHealth Decision Support Systems

Most mobile health (mHealth) decision support systems currently available for chronic obstructive respiratory diseases (CORDs) are not supported by clinical evidence or lack clinical validation. The development of the knowledge base that will feed the clinical decision support system is a crucial step that involves the collection and systematization of clinical knowledge from relevant scientific sources and its representation in a human-understandable and computer-interpretable way. This work describes the development and initial validation of a clinical knowledge base that can be integrated into mHealth decision support systems developed for patients with CORDs. A multidisciplinary team of health care professionals with clinical experience in respiratory diseases, together with data science and IT professionals, defined a new framework that can be used in other evidence-based systems. The knowledge base development began with a thorough review of the relevant scientific sources (eg, disease guidelines) to identify the recommendations to be implemented in the decision support system based on a consensus process. Recommendations were selected according to predefined inclusion criteria: (1) applicable to individuals with CORDs or to prevent CORDs, (2) directed toward patient self-management, (3) targeting adults, and (4) within the scope of the knowledge domains and subdomains defined. Then, the selected recommendations were prioritized according to (1) a harmonized level of evidence (reconciled from different sources); (2) the scope of the source document (international was preferred); (3) the entity that issued the source document; (4) the operability of the recommendation; and (5) health care professionals' perceptions of the relevance, potential impact, and reach of the recommendation. A total of 358 recommendations were selected. Next, the variables required to trigger those recommendations were defined (n=116) and operationalized into logical rules using Boolean logical operators (n=405). Finally, the knowledge base was implemented in an intelligent individualized coaching component and pretested with an asthma use case. Initial validation of the knowledge base was conducted internally using data from a population-based observational study of individuals with or without asthma or rhinitis. External validation of the appropriateness of the recommendations with the highest priority level was conducted independently by 4 physicians. In addition, a strategy for knowledge base updates, including an easy-to-use rules editor, was defined. Using this process, based on consensus and iterative improvement, we developed and conducted preliminary validation of a clinical knowledge base for CORDs that translates disease guidelines into personalized patient recommendations. The knowledge base can be used as part of mHealth decision support systems. This process could be replicated in other clinical areas.info:eu-repo/semantics/publishedVersio

Heat treatment significantly increases the sharpness of silcrete stone tools

Humans were regularly heat-treating stone tool raw materials as early as 130,000 years ago. The late Middle Stone Age (MSA) and Late Stone Age (LSA) of South Africa's Western Cape region provides some of the earliest and most pervasive archaeological evidence for this behaviour. While archaeologists are beginning to understand the flaking implications of raw material heat treatment, its potential functional benefits remain unanswered. Using silcrete from the Western Cape region, we investigate the impact of heat treatment on stone tool cutting performance. We quantify the sharpness of silcrete in its natural, unheated form, before comparing it with silcrete heated in three different conditions. Results show that heat-treated silcrete can be significantly sharper than unheated alternatives, with cutting forces halving and energy requirements reducing by approximately two-thirds. The data suggest that silcrete may have been heat treated during the South African MSA and LSA to increase the sharpness and performance of stone cutting edges. This early example of material engineering has implications for understanding Stone Age populations’ technological capabilities, inventiveness and raw material choices. We predict that heat-treatment behaviours in other prehistoric and ethnographic contexts may also be linked to increases in edge sharpness and concerns about functional performance

Levantamento da ocorrência de populações do nematoide-das-galhas-do-cafeeiro (Meloidogyne sp.) em Rondônia: primeira atualização.

Objetivou-se neste trabalho determinar a ocorrência das principais espécies Meloidogyne em lavouras de café rondonienses por meio da caracterização das mesmas, a partir de análises morfológicas e isoenzimáticas de fêmeas do nematoide, coletadas de raízes e solo.bitstream/item/141377/1/COT-397-Levantamento-da-ocorrencia-de-populacoes-do-nematoides-das-galhas-do-cafeeiro-Meloidogyne-sp.-em-Rondonia-primeira-atualizacao.pd

Alternativas para o manejo integrado de nematoide-das-galhas do cafeeiro.

A publicação aborda, especialmente, os métodos genéticos, químicos e culturais para para o manejo de nematoide-das-galhas do cafeeiro.bitstream/item/146079/1/Doc-160-cafeeiro-HNC.pd

Structural and Functional insights into the catalytic mechanism of the Type II NADH:quinone oxidoreductase family

Type II NADH:quinone oxidoreductases (NDH-2s) are membrane proteins involved in respiratory chains. These proteins contribute indirectly to the establishment of the transmembrane difference of electrochemical potential by catalyzing the reduction of quinone by oxidation of NAD(P)H. NDH-2s are widespread enzymes being present in the three domains of life. In this work, we explored the catalytic mechanism of NDH-2 by investigating the common elements of all NDH-2s, based on the rationale that conservation of such elements reflects their structural/functional importance. We observed conserved sequence motifs and structural elements among 1762 NDH-2s. We identified two proton pathways possibly involved in the protonation of the quinone. Our results led us to propose the first catalytic mechanism for NDH-2 family, in which a conserved glutamate residue, E(172) (in NDH-2 from Staphylococcus aureus) plays a key role in proton transfer to the quinone pocket. This catalytic mechanism may also be extended to the other members of the two-Dinucleotide Binding Domains Flavoprotein (tDBDF) superfamily, such as sulfide:quinone oxidoreductases

Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. \noindent The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. \noindent The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.Comment: 25 pages (including references and appendices); 12 figures uploaded as separate file