Context.
The main goal of the CARMENES survey is to find Earth-mass planets around nearby M-dwarf stars. Seven M dwarfs included in the CARMENES sample had been observed before with HIRES and HARPS ...and either were reported to have one short period planetary companion (GJ 15 A, GJ 176, GJ 436, GJ 536 and GJ 1148) or are multiple planetary systems (GJ 581 and GJ 876).
Aims.
We aim to report new precise optical radial velocity measurements for these planet hosts and test the overall capabilities of CARMENES.
Methods.
We combined our CARMENES precise Doppler measurements with those available from HIRES and HARPS and derived new orbital parameters for the systems. Bona-fide single planet systems were fitted with a Keplerian model. The multiple planet systems were analyzed using a self-consistent dynamical model and their best fit orbits were tested for long-term stability.
Results.
We confirm or provide supportive arguments for planets around all the investigated stars except for GJ 15 A, for which we find that the post-discovery HIRES data and our CARMENES data do not show a signal at 11.4 days. Although we cannot confirm the super-Earth planet GJ 15 Ab, we show evidence for a possible long-period (
P
c
= 7030
-630
+970
d) Saturn-mass (
m
c
sin
i
= 51.8
-5.8
+5.5
M
⊕
) planet around GJ 15 A. In addition, based on our CARMENES and HIRES data we discover a second planet around GJ 1148, for which we estimate a period
P
c
= 532.6
-2.5
+4.1
days, eccentricity
e
c
= 0.342
-0.062
+0.050
and minimum mass
m
c
sin
i
= 68.1
-2.2
+4.9
M
⊕
.
Conclusions.
The CARMENES optical radial velocities have similar precision and overall scatter when compared to the Doppler measurements conducted with HARPS and HIRES. We conclude that CARMENES is an instrument that is up to the challenge of discovering rocky planets around low-mass stars.
Many alternatives for the proper disposal of horticultural plant wastes have been studied, and composting is one of the most attractive due to its insignificant environmental impact and low cost. The ...quality of compost for agronomical use is related to the degree of organic matter maturation and stabilization. Traditional parameters as well as temperature, ratio C/N, cationic exchange capacity, extractable carbon, or evolution of humificated substances have been successfully used to assess compost maturity and stability. However, microorganisms frequently isolated during composting release a wide range of hydrolytic enzymes, whose activity could apparently give interesting information on the rate of decomposition of organic matter and, therefore, on the product stability. The aim of this work was to study the evolution of some important enzymatic activities during composting of agricultural wastes and their comparison with other chemical parameters commonly employed as quality and maturity indexes, to establish a relationship between the degradation intensity of specific organic carbon fractions throughout the process. In this work, the chemical and biochemical parameters of plant wastes were studied along a composting process of 189 days to evaluate their importance as tools for compost characterization. Results showed an intense enzymatic activity during the first 2–3 weeks of composting (bio-oxidative phase), because of the availability of easily decomposable organic compounds. From a biological point of view, a less intense phase was observed between second and third month of composting (mesophilic or cooling phase). Finally, chemical humification parameters were more closely associated with the period between 119 and 189 days (maturation phase). Significant correlations between the enzymatic activities as well as between enzyme activities and other more traditional parameters were also highlighted, indicating that both kind of indexes can be a reliable tool to determine the degree of stability and maturation of horticultural plant wastes based-compost.
•Enzymatic and temperature patterns registered inside the pile are directly related.•Enzymatic activity reaches its peak during the first days of the composting process.•When piles begin to cool, the enzymatic activity decreases noticeably.•The intensity of the enzymatic activity indirectly affects the humification process.
Both theoretical predictions and observations of the very nearby Universe suggest that low-mass galaxies(log...M*/M... < 9.5) are likely to remain star-forming unless they are affected by their local ...environment. To test this premise, we compare and contrast the local environment of both passive and star-forming galaxies as a function of stellar mass, using the Galaxy and Mass Assembly survey. We find that passive fractions are higher in both interacting pair and group galaxies than the field at all stellar masses, and that this effect is most apparent in the lowest mass galaxies. We also find that essentially all passive log...M*/M... < 8.5 galaxies are found in pair/group environments, suggesting that local interactions with a more massive neighbour cause them to cease forming new stars. We find that the effects of immediate environment (local galaxy-galaxy interactions) in forming passive systems increase with decreasing stellar mass, and highlight that this is potentially due to increasing interaction time-scales giving sufficient time for the galaxy to become passive via starvation. We then present a simplistic model to test this premise, and show that given our speculative assumptions, it is consistent with our observed results. (ProQuest: ... denotes formulae/symbols omitted.)
Composting has been traditionally considered a process in which a succession of mesophilic and thermophilic microbial populations occurs due to temperature changes. In order to deepen in this model, ...1380 bacterial and fungal strains (the entire culturable microbiota isolated from a composting process) were investigated for their ability to grow across a wide range of temperatures (20 to 60 °C). First, qualitative tests were performed to establish a thermal profile for each strain. Then, quantitative tests allowed ascertaining the extent of growth for each strain at each of the tested temperatures. The identity of the isolates enabled to position them taxonomically and permitted tracking the strains throughout the process. Results showed that 90% of the isolates were classified as thermotolerant (they grew at all tested temperatures). Only 9% and 1% of the studied strains showed to be strictly mesophilic or thermophilic, respectively. Firmicutes exhibited the greatest thermal plasticity, followed by Actinobacteria and Ascomycota. Most of the Proteobacteria and all Basidiomycota strains were also able to grow at all the assayed temperatures. Thermotolerance was clearly demonstrated among the composting microbiota, suggesting that the idea of the succession of mesophilic and thermophilic populations throughout the process might need a reassessment.
Display omitted
•The temperature-driven succession of the composting microbial populations was revisited.•Thermotolerance was demonstrated for a vast majority of the composting microbiota.•Thermotolerant strains were repeatedly identified in most of the composting stages.•Firmicutes and Ascomycota accounted for the best represented thermotolerant phyla.•Thermal plasticity is a microbial reply to the ever changing composting conditions.
Avoiding vehicle-to-pedestrian crashes is a critical requirement for nowadays advanced driver assistant systems (ADAS) and future self-driving vehicles. Accordingly, detecting pedestrians from raw ...sensor data has a history of more than 15 years of research, with vision playing a central role. During the last years, deep learning has boosted the accuracy of image-based pedestrian detectors. However, detection is just the first step towards answering the core question, namely
Therefore, knowing as soon as possible if a detected pedestrian has the intention of crossing the road ahead of the vehicle is essential for performing safe and comfortable maneuvers that prevent a crash. However, compared to pedestrian detection, there is relatively little literature on detecting pedestrian intentions. This paper aims to contribute along this line by presenting a new vision-based approach which analyzes the pose of a pedestrian along several frames to determine if he or she is going to enter the road or not. We present experiments showing 750 ms of anticipation for pedestrians crossing the road, which at a typical urban driving speed of 50 km/h can provide 15 additional meters (compared to a pure pedestrian detector) for vehicle automatic reactions or to warn the driver. Moreover, in contrast with state-of-the-art methods, our approach is monocular, neither requiring stereo nor optical flow information.
Ferrimagnetic A2BB′O6 double perovskites, such as Sr2FeMoO6, are important spin‐polarized conductors. Introducing transition metals at the A‐sites offers new possibilities to increase magnetization ...and tune magnetoresistance. Herein we report a ferrimagnetic double perovskite, Mn2FeReO6, synthesized at high pressure which has a high Curie temperature of 520 K and magnetizations of up to 5.0 μB which greatly exceed those for other double perovskite ferrimagnets. A novel switching transition is discovered at 75 K where magnetoresistance changes from conventional negative tunneling behavior to large positive values, up to 265 % at 7 T and 20 K. Neutron diffraction shows that the switch is driven by magnetic frustration from antiferromagnetic Mn2+ spin ordering which cants Fe3+ and Re5+ spins and reduces spin‐polarization. Ferrimagnetic double perovskites based on A‐site Mn2+ thus offer new opportunities to enhance magnetization and control magnetoresistance in spintronic materials.
Double‐perovskite magnetism: The double perovskite Mn2FeReO6 synthesized at high pressure has magnetic transition‐metal cations at all sites. High‐spin Mn2+ cations lead to record magnetizations for double‐perovskite ferrimagnets and their frustrated magnetic order at 75 K switches magnetoresistance from negative to large positive values at low temperatures.
Anion‐(π)n‐π Catalytic Micelles Tan, Mei‐Ling; Ángeles Gutiérrez López, M.; Sakai, Naomi ...
Angewandte Chemie International Edition,
October 2, 2023, Volume:
62, Issue:
40
Journal Article
Peer reviewed
Open access
Anion‐π catalysis operates by stabilizing anionic transition states on π‐acidic aromatic surfaces. In anion‐(π)n‐π catalysis, π stacks add polarizability to strengthen interactions. In search of ...synthetic methods to extend π stacks beyond the limits of foldamers, the self‐assembly of micelles from amphiphilic naphthalenediimides (NDIs) is introduced. To interface substrates and catalysts, charge‐transfer complexes with dialkoxynaphthalenes (DANs), a classic in supramolecular chemistry, are installed. In π‐stacked micelles, the rates of bioinspired ether cyclizations exceed rates on monomers in organic solvents by far. This is particularly impressive considering that anion‐π catalysis in water has been elusive so far. Increasing rates with increasing π acidity of the micelles evince operational anion‐(π)n‐π catalysis. At maximal π acidity, autocatalytic behavior emerges. Dependence on position and order in confined micellar space promises access to emergent properties. Anion‐(π)n‐π catalytic micelles in water thus expand supramolecular systems catalysis accessible with anion‐π interactions with an inspiring topic of general interest and great perspectives.
Anion‐(π)n‐π catalytic micelles are introduced to expand the collection of systems catalysts compatible with anion‐π catalysis with a rich topic of general importance. They are of interest to realize anion‐π catalysis, anion‐(π)n‐π catalysis and anion‐(π)n‐π autocatalysis in water. Classics in supramolecular chemistry are installed to control substrate binding and positioning within the confined micellar space for access to emergent properties.
Handling missing values is a crucial step in preprocessing data in Machine Learning. Most available algorithms for analyzing datasets in the feature selection process and classification or estimation ...process analyze complete datasets. Consequently, in many cases, the strategy for dealing with missing values is to use only instances with full data or to replace missing values with a mean, mode, median, or a constant value. Usually, discarding missing samples or replacing missing values by means of fundamental techniques causes bias in subsequent analyzes on datasets.
Demonstrate the positive impact of multivariate imputation in the feature selection process on datasets with missing values.
We compared the effects of the feature selection process using complete datasets, incomplete datasets with missingness rates between 5 and 50%, and imputed datasets by basic techniques and multivariate imputation. The feature selection algorithms used are well-known methods. The results showed that the datasets imputed by multivariate imputation obtained the best results in feature selection compared to datasets imputed by basic techniques or non-imputed incomplete datasets.
Considering the results obtained in the evaluation, applying multivariate imputation by MICE reduces bias in the feature selection process.
Variability in the way organisms reproduce raises numerous, and still unsolved, questions in evolutionary biology. In this study, we emphasize that fungi deserve a much greater emphasis in efforts to ...address these questions because of their multiple advantages as model eukaryotes. A tremendous diversity of reproductive modes and mating systems can be found in fungi, with many evolutionary transitions among closely related species. In addition, fungi show some peculiarities in their mating systems that have received little attention so far, despite the potential for providing insights into important evolutionary questions. In particular, selfing can occur at the haploid stage in addition to the diploid stage in many fungi, which is generally not possible in animals and plants but has a dramatic influence upon the structure of genetic systems. Fungi also present several advantages that make them tractable models for studies in experimental evolution. Here, we briefly review the unsolved questions and extant hypotheses about the evolution and maintenance of asexual vs. sexual reproduction and of selfing vs. outcrossing, focusing on fungal life cycles. We then propose how fungi can be used to address these long‐standing questions and advance our understanding of sexual reproduction and mating systems across all eukaryotes.
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