A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z). A wide plethora of methods have been developed, based either on ...template models fitting or on empirical explorations of the photometric parameter space. Machine-learning-based techniques are not explicitly dependent on the physical priors and able to produce accurate photo-z estimations within the photometric ranges derived from the spectroscopic training set. These estimates, however, are not easy to characterize in terms of a photo-z probability density function (PDF), due to the fact that the analytical relation mapping the photometric parameters on to the redshift space is virtually unknown. We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method designed to provide a reliable PDF of the error distribution for empirical techniques. The method is implemented as a modular workflow, whose internal engine for photo-z estimation makes use of the MLPQNA neural network (Multi Layer Perceptron with Quasi Newton learning rule), with the possibility to easily replace the specific machine-learning model chosen to predict photo-z. We present a summary of results on SDSS-DR9 galaxy data, used also to perform a direct comparison with PDFs obtained by the LE PHARE spectral energy distribution template fitting. We show that METAPHOR is capable to estimate the precision and reliability of photometric redshifts obtained with three different self-adaptive techniques, i.e. MLPQNA, Random Forest and the standard K-Nearest Neighbors models.
Abstract Introduction The aim of this study was to analyze and characterize root canal morphology of mandibular molars of the Brazilian population by using cone-beam computed tomography (CBCT). ...Methods Patients who required CBCT radiographic examinations as part of their routine examination, diagnosis, and treatment planning were enrolled in the study. A total of 460 healthy, untreated, fully developed mandibular first and second molars were included (234 first molars and 226 second molars). The following observations were recorded: (1) number of roots and their morphology, (2) number of canals per root, (3) C-shaped canals, and (4) primary variations in the morphology of the root canal systems. Results First molars showed a higher prevalence of 2 canals in the mesial root and 1 in the distal root with 2 separate roots (74%). In the mandibular second molars, the presence of 2 separate roots with 2 canals in the mesial root and 1 canal in the distal root represented 54% of the total. In 32% of the cases, 2 separate roots with 1 canal each in the mesial and distal roots were presented. The incidence of C-shaped canals was 1.7% of first molars and 3.5% of second molars. Conclusions A higher prevalence of 2 separate roots with 2 canals in the mesial root and 1 canal in the distal root was observed in mandibular first and second molars (74% and 54%, respectively). Also, a lower incidence of C-shaped canals and 3-rooted teeth was observed in a Brazilian population. CBCT is a clinically useful tool for endodontic diagnosis and treatment.
Current evidence and recent publications have led to the recognition that aerosol-borne transmission of COVID-19 is possible in indoor areas such as educational centers. A crucial measure to reduce ...the risk of infection in high occupancy indoors is ventilation. In this global pandemic context of SARS-CoV-2 virus infection, a study has been carried out with the main objective of analyzing the effects of natural ventilation conditions through windows on indoor air quality and thermal comfort during on-site examinations in higher education centers during the winter season, as this implies situations of unusual occupation and the impossibility in many cases of taking breaks or leaving classrooms, as well as the existence of unfavorable outdoor weather conditions in terms of low temperatures. For this purpose, in situ measurements of the environmental variables were taken during different evaluation tests. As the main results of the study, ventilation conditions were generally adequate in all the tests carried out, regardless of the ventilation strategy used, with average CO2 concentration levels of between 450 and 670 ppm. The maximum CO2 concentration value recorded in one of the tests was 808 ppm. On this basis, the limit for category IDA 2 buildings, corresponding to educational establishments, was not exceeded in any case. However, these measures affected the thermal comfort of the occupants, especially when the outside temperature was below 6 °C, with a dissatisfaction rate of between 25 and 72%. Examinations carried out with outside temperatures above 12 °C were conducted in acceptable comfort conditions regardless of outside air supply and classroom occupancy. In these cases, the dissatisfaction rate was less than 10%. The results obtained have made it possible to establish strategies for ventilation in the implementation of future exams, depending on the climatic conditions outside.
•Ventilation and capacity limitations ensure security during the on-site examinations.•If the outside temperature is low, it is not possible to combine comfort and security.•Periodic opening and closing of windows is the best strategy in low temperatures.•ACH is not a good indicator of air quality at low occupancy levels in classrooms.•Ventilation does not have a decisive influence on comfort above 12 °C.
Photometric redshifts (photo-z) are fundamental in galaxy surveys to address different topics, from gravitational lensing and dark matter distribution to galaxy evolution. The Kilo Degree Survey ...(KiDS), i.e. the European Southern Observatory (ESO) public survey on the VLT Survey Telescope (VST), provides the unprecedented opportunity to exploit a large galaxy data set with an exceptional image quality and depth in the optical wavebands. Using a KiDS subset of about 25000 galaxies with measured spectroscopic redshifts, we have derived photo-z using (i) three different empirical methods based on supervised machine learning; (ii) the Bayesian photometric redshift model (or BPZ); and (iii) a classical spectral energy distribution (SED) template fitting procedure (le phare). We confirm that, in the regions of the photometric parameter space properly sampled by the spectroscopic templates, machine learning methods provide better redshift estimates, with a lower scatter and a smaller fraction of outliers. SED fitting techniques, however, provide useful information on the galaxy spectral type, which can be effectively used to constrain systematic errors and to better characterize potential catastrophic outliers. Such classification is then used to specialize the training of regression machine learning models, by demonstrating that a hybrid approach, involving SED fitting and machine learning in a single collaborative framework, can be effectively used to improve the accuracy of photo-z estimates.
Thermal comfort in educational buildings affects not only the well-being of students but also their academic performance. Over time, various methods have been developed to assess it. However, none of ...them takes into account the adaptation of students of different ages, which is an important issue. In recent years, the study of thermal comfort has become very important due to energy-saving measures and ventilation protocols to combat the spread of the SARS-CoV-2 coronavirus. Therefore, it is necessary to gather all the information to guide future research. Thus, this paper presents a comprehensive review of field studies on thermal comfort in classrooms at different educational levels. The focus is on those conducted during the global pandemic of COVID-19. It has been observed that students from climates with a higher degree of variation have shown a better adaptation. Children also tended to feel less affected by changing temperatures. High school and university students showed a greater range of dissatisfaction with heat than with cold. The adaptive approach is more suitable for recognising the comfort needs of all age groups. However, by using this approach together with the Fanger method, more reliable results have been reported. In most of the studies, comfort levels were found to be lower than those indicated by the standards, highlighting the need for guidelines adapted to the thermal comfort conditions of all students. Finally, the various natural ventilation measures to avoid COVID-19 infection have led to a decrease in comfort levels, especially in winter.
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•Through the 3-D homology modelling it was possible to predict the atomic structural arrangement of AlkB enzyme in the cytoplasmic region.•We detected the preferred position of the ...octane molecule in Cytosolic Binding Pocket, namely the AlkB_P1one.•Ala53, Trp55, Val15 and Tyr339 of AlkBenzyme are involved with the octane/uptake, octanol/exit, and the 1-octyne/up take molecule.
Many species of bacteria involved in degradation of n-alkanes have an important constitutional metabolic enzyme, the alkane hydroxylase called AlkB, specialized in the conversion of hydrocarbons molecules that can be used as carbon and/or energy source. This enzyme plays an important role in the microbial degradation of oil, chlorinated hydrocarbons, fuel additives, and many other compounds. A number of these enzymes has been biochemically characterized in detail because the potential of alkane hydroxylases to catalyse high added-value reactions is widely recognized. Nevertheless, the industrial and process bioremediation application of them is restricted, owing to their complex biochemistry, challenging process requirements, and the limited number of their three-dimensional structures. Furthermore, AlkB has great potential as biocatalysts for selective transformation of a wide range of chemically inert unreactive alkanes into reactive chemical precursors that can be used as tools for bioremediation and bioprocesses. Aiming to understand the possible ways the AlkB enzyme Pseudomonas putida P1 interacts with octane, octanol and 1-octyne, we consider its suitable biochemical structure taking into account a 3-D homology modelling. Besides, by using a quantum chemistry computational model based on the density functional theory (DFT), we determine possible protein-substrate interaction regions measured by means of its binding energy simulated throughout the Molecular Fractionation with Conjugated Caps (MFCC) approach.
O âmago da teoria de Luhmann é a comunicação. Toda comunicação no interior de um sistema opera pela seleção e processamento de apenas uma quantidade limitada de informações disponíveis de fora. Cada ...sistema trabalha estritamente em seus próprios códigos e sem acordo sobre os modos como outros sistemas percebem seu entorno. Niklas Luhmann desen- volve um programa teórico para exame desta questão. Sua premissa é que o conceito de risco projeta, no presente, aspectos essenciais de nossa descrição do futuro. Risco é concebido como a possibilidade de uma decisão desencadeadora de consequências improváveis, inesperadas e prejudiciais, ser atribuída aos tomadores de decisão. Assentados nessa teoria, discutimos uma abordagem para explorar a complexidade do sistema urbano.
We present a machine-learning photometric redshift (ML photo-z) analysis of the Kilo-Degree Survey Data Release 3 (KiDS DR3), using two neural-network based techniques: ANNz2 and MLPQNA. Despite ...limited coverage of spectroscopic training sets, these ML codes provide photo-zs of quality comparable to, if not better than, those from the Bayesian Photometric Redshift (BPZ) code, at least up to zphot ≲ 0.9 and r ≲ 23.5. At the bright end of r ≲ 20, where very complete spectroscopic data overlapping with KiDS are available, the performance of the ML photo-zs clearly surpasses that of BPZ, currently the primary photo-z method for KiDS. Using the Galaxy And Mass Assembly (GAMA) spectroscopic survey as calibration, we furthermore study how photo-zs improve for bright sources when photometric parameters additional to magnitudes are included in the photo-z derivation, as well as when VIKING and WISE infrared (IR) bands are added. While the fiducial four-band ugri setup gives a photo-z bias 〈δz/(1 + z)〉 = −2 × 10−4 and scatter σδz/(1+z) < 0.022 at mean 〈z〉 = 0.23, combining magnitudes, colours, and galaxy sizes reduces the scatter by ~7% and the bias by an order of magnitude. Once the ugri and IR magnitudes are joined into 12-band photometry spanning up to 12 μm, the scatter decreases by more than 10% over the fiducial case. Finally, using the 12 bands together with optical colours and linear sizes gives 〈δz/(1 + z)〉 < 4 × 10−5 and σδz/(1+z) < 0.019. This paper also serves as a reference for two public photo-z catalogues accompanying KiDS DR3, both obtained using the ANNz2 code. The first one, of general purpose, includes all the 39 million KiDS sources with four-band ugri measurements in DR3. The second dataset, optimised for low-redshift studies such as galaxy-galaxy lensing, is limited to r ≲ 20, and provides photo-zs of much better quality than in the full-depth case thanks to incorporating optical magnitudes, colours, and sizes in the GAMA-calibrated photo-z derivation.
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