Beidelita de la mina Dos Amigos, Los Menucos, prov. de Río Negro, Argentina

The presence of beidellite developed in veins from the core of the fluorite vein Dos Amigos (Prov. de Rio Negro) is cited. It was studied bv means of XRD, optical microscopy, SEM, TG, DTA, IR and Chemical analysis. The beidellite is associated to fluorite and quartz, with subordinated kaolinite. It has a good crystallinity. It is considered to have been formed in the latest stage of mineralization, from the fluids that give rise the fluorite vein

Perancangan Gedung Fakultas Teknik Unsrat Dengan Perspektif Animasi 3d

Model Gedung Fakultas Teknik yang biasanya hanya berbentuk gambar dibuat model berupa 3D dalam bentuk Animasi. Produksi Film Animasi Gedung Fakultas Teknik Universitas Sam Ratulangi dengan perspektif animasi 3D ini menggunakan teknik tracking camera. Tracking camera merupakan cara untuk melihat dari model 3D yang dibuat dengan pandangan camera yang berjalan sendiri. Pemodelan gedung berdasarkan gambar gedung hasil observasi yang dibuat menjadi model 3D. Hasil akhir dari pembuatan film animasi 3D dari gedung Fakultas Teknik Unsrat ini diharapkan dapat menjadikan gedung Fakultas Teknik Unsrat dalam bentuk animasi 3D yang dapat membantu user atau mahasiswa untuk lebih mengetahui daerah gedung Fakultas Teknik Unsrat ini. Selain itu melalui pembuatan film animasi 3D dari model gedung ini juga diharapkan dapat digunakan sebagai modul presentasi untuk memperkenalkan gedung Fakultas Teknik Unsrat kepada pihak luar

A possible rheological model of gum candies

An appropriate rheological model can be used in production of good quality gum candy required by consumers. For this purpose Creep-Recovery Test (CRT) curves were recorded with a Stable Micro System TA.XT-2 precision texture analyser with 75 mm diameter cylinder probe on gum candies purchased from the local market. The deformation speed was 0.2 mm s−1, the creeping- and recovering time was 60 s, while the loading force was set to 1 N, 2 N, 5 N, 7 N, and 10 N. The two-element Kelvin-Voigt-model, a three-element model, and the four-element Burgers-model were fitted on the recorded creep data, and then the parameters of the models were evaluated. The best fitting from the used models was given by the Burgers model

Previous SARS-CoV-2 Infection Increases B.1.1.7 Cross-Neutralization by Vaccinated Individuals

With the spread of new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is a need to assess the protection conferred by both previous infections and current vaccination. Here we tested the neutralizing activity of infected and/or vaccinated individuals against pseudoviruses expressing the spike of the original SARS-CoV-2 isolate Wuhan-Hu-1 (WH1), the D614G mutant and the B.1.1.7 variant. Our data show that parameters of natural infection (time from infection and nature of the infecting variant) determined cross-neutralization. Uninfected vaccinees showed a small reduction in neutralization against the B.1.1.7 variant compared to both the WH1 strain and the D614G mutant. Interestingly, upon vaccination, previously infected individuals developed more robust neutralizing responses against B.1.1.7, suggesting that vaccines can boost the neutralization breadth conferred by natural infection

KOBEsim: A Bayesian observing strategy algorithm for planet detection in radial velocity blind-search surveys

Context. Ground-based observing time is precious in the era of exoplanet follow-up and characterization, especially in high-precision radial velocity instruments. Blind-search radial velocity surveys thus require a dedicated observational strategy in order to optimize the observing time, which is particularly crucial for the detection of small rocky worlds at large orbital periods. Aims. We developed an algorithm with the purpose of improving the efficiency of radial velocity observations in the context of exoplanet searches, and we applied it to the K-dwarfs Orbited By habitable Exoplanets experiment. Our aim is to accelerate exoplanet confirmations or, alternatively, reject false signals as early as possible in order to save telescope time and increase the efficiency of both blind-search surveys and follow-up of transiting candidates. Methods. Once a minimum initial number of radial velocity datapoints is reached in such a way that a periodicity starts to emerge according to generalized Lomb-Scargle periodograms, that period is targeted with the proposed algorithm, named KOBEsim. The algorithm selects the next observing date that maximizes the Bayesian evidence for this periodicity in comparison with a model with no Keplerian orbits. Results. By means of simulated data, we proved that the algorithm accelerates the exoplanet detection, needing 29-33% fewer observations and a 41-47% smaller time span of the full dataset for low-mass planets (mp < 10 M⊕) in comparison with a conventional monotonic cadence strategy. For 20 M⊕ planets we found a 16% enhancement in the number of datapoints. We also tested KOBEsim with real data for a particular KOBE target and for the confirmed planet HD 102365 b. These two tests demonstrate that the strategy is capable of speeding up the detection by up to a factor of 2 (i.e., reducing both the time span and number of observations by half).14 página

The CARMENES search for exoplanets around M dwarfs -- A deep learning approach to determine fundamental parameters of target stars

Existing and upcoming instrumentation is collecting large amounts of astrophysical data, which require efficient and fast analysis techniques. We present a deep neural network architecture to analyze high-resolution stellar spectra and predict stellar parameters such as effective temperature, surface gravity, metallicity, and rotational velocity. With this study, we firstly demonstrate the capability of deep neural networks to precisely recover stellar parameters from a synthetic training set. Secondly, we analyze the application of this method to observed spectra and the impact of the synthetic gap (i.e., the difference between observed and synthetic spectra) on the estimation of stellar parameters, their errors, and their precision. Our convolutional network is trained on synthetic PHOENIX-ACES spectra in different optical and near-infrared wavelength regions. For each of the four stellar parameters, $T_{\rm eff}$, $\log{g}$, [M/H], and $v \sin{i}$, we constructed a neural network model to estimate each parameter independently. We then applied this method to 50 M dwarfs with high-resolution spectra taken with CARMENES (Calar Alto high-Resolution search for M dwarfs with Exo-earths with Near-infrared and optical Echelle Spectrographs), which operates in the visible (520-960 nm) and near-infrared wavelength range (960-1710 nm) simultaneously. Our results are compared with literature values for these stars. They show mostly good agreement within the errors, but also exhibit large deviations in some cases, especially for [M/H], pointing out the importance of a better understanding of the synthetic gap

Perceptions or Actions? Grounding How Agents Interact Within a Software Architecture for Cognitive Robotics

One of the aims of cognitive robotics is to endow robots with the ability to plan solutions for complex goals and then to enact those plans. Additionally, robots should react properly upon encountering unexpected changes in their environment that are not part of their planned course of actions. This requires a close coupling between deliberative and reactive control flows. From the perspective of robotics, this coupling generally entails a tightly integrated perceptuomotor system, which is then loosely connected to some specific form of deliberative system such as a planner. From the high-level perspective of automated planning, the emphasis is on a highly functional system that, taken to its extreme, calls perceptual and motor modules as services when required. This paper proposes to join the perceptual and acting perspectives via a unique representation where the responses of all software modules in the architecture are generalized using the same set of tokens. The proposed representation integrates symbolic and metric information. The proposed approach has been successfully tested in CLARC, a robot that performs Comprehensive Geriatric Assessments of elderly patients. The robot was favourably appraised in a survey conducted to assess its behaviour. For instance, using a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree), patients reported an average of 4.86 when asked if they felt confident during the interaction with the robot. This paper proposes a mechanism for bringing the perceptual and acting perspectives closer within a distributed robotics architecture. The idea is built on top of the blackboard model and scene graphs. The modules in our proposal communicate using a short-term memory, writing the perceptual information they need to share with other agents and accessing the information they need for determining the next goals to address

Project goals, target selection, and stellar characterization

The detection of habitable worlds is one of humanitya-s greatest endeavors. Thus far, astrobiological studies have shown that one of the most critical components for allowing life to develop is liquid water. Its chemical properties and its capacity to dissolve and, hence, transport other substances makes this constituent a key piece in this regard. As a consequence, looking for life as we know it is directly related to the search for liquid water. For a remote detection of life in distant planetary systems, this essentially means looking for planets in the so-called habitable zone. In this sense, K-dwarf stars are the perfect hosts to search for planets in this range of distances. Contrary to G-dwarfs, the habitable zone is closer, thus making planet detection easier using transit or radial velocity techniques. Contrary to M-dwarfs, stellar activity is on a much smaller scale, hence, it has a smaller impact in terms of both the detectability and the true habitability of the planet. Also, K-dwarfs are the quietest in terms of oscillations, and granulation noise. In spite of this, there is a dearth of planets in the habitable zone of K-dwarfs due to a lack of observing programs devoted to this parameter space. In response to a call for legacy programs of the Calar Alto observatory, we have initiated the first dedicated and systematic search for habitable planets around these stars: K-dwarfs Orbited By habitable Exoplanets (KOBE). This survey is monitoring the radial velocity of 50 carefully pre-selected K-dwarfs with the CARMENES instrument over five semesters, with an average of 90 data points per target. Based on planet occurrence rates convolved with our detectability limits, we expect to find 1.68 ± 0.25 planets per star in the KOBE sample. Furthermore, in half of the sample, we expect to find one of those planets within the habitable zone. Here, we describe the motivations, goals, and target selection for the project as well as the preliminary stellar characterization. © 2022 EDP Sciences. All rights reserved