Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of a slow H i bar in the dwarf irregular galaxy DDO 168

We examine the H i total intensity maps of the VLA LITTLE-THINGS galaxies and identify an H i bar in the dwarf irregular galaxy DDO 168 which has a dense and compact dark matter halo that dominates at all radii. This is only the third galaxy found to host an H i bar. Using the H i kinematic data, we apply the Tremaine–Weinberg method to estimate the pattern speed of the bar. The H i bar is found to have an average pattern speed of 23.3 ± 5.9 $\rm km \, s^{-1} \, kpc^{-1}$. Interestingly, for the first time, we find that the observed pattern speeds of the bar in the two kinematic halves are different. We identify the origin of this difference to be the kinematic asymmetry. This observed offset in the pattern speed serves to put a stringent constraint on the lifetime of the bar set by the winding time-scale. The lifetime of the bar is found to be 5.3 × 108 yr, which is two times the dynamical time-scale of the disc. We also find the H i bar in DDO 168 to be a weak bar with a strength of 0.2. If H i bar being weak can be easily disturbed, this could possibly explain why it is extremely rare to observe H i bars in galaxies. We estimate the bar radius to be 1 kpc and the dimensionless ratio, RL/Rb to be ≥2.1 indicating a ‘slow’ bar in DDO 168. Our results confirm the proposition that the dynamical friction with the halo slows down a rotating bar in a galaxy dominated by dark matter halo from inner radii.
Thermal conductivity of porous jennite by molecular dynamics method.

The thermal conductivity of porous jennite, as the major component of cement paste, and its porosity and temperature dependences are simulated by molecular dynamics methods using ClayFF force field. The porous jennite models with different porosities are created by removing atoms within the sphere from bulk jennite model. The thermal conductivity elements of bulk jennite calculated by equilibrium Green-Kubo method are almost identical to those by non-equilibrium Muller-Plathe (MP) method at 300 K. The volumetric thermal conductivity of porous jennite is found to decrease from 1.141 W/m$\cdot$K to 0.144 W/m$\cdot$K as increasing the porosity from 0\% to 72.22\% at 300 K, following the empirical coherent potential model when the pore is assumed to be filled with air. As increasing temperature, the thermal conductivity is observed to increase from 240 K to 560 K and gradually decrease until 1100 K for porous jennites with the porosities of 0\%, 15.99\% and 32.79\%.
Complexity of magnetic fields on red dwarfs

Context. Magnetic fields in cool stars can be investigated by measuring Zeeman line broadening and polarization in atomic and molecular lines. Similar to the Sun, these fields are complex and height-dependent. Many molecular lines dominating M-dwarf spectra (e.g., FeH, CaH, MgH, and TiO) are temperature- and Zeeman-sensitive and form at different atmospheric heights, which makes them excellent probes of magnetic fields on M dwarfs. Aims. Our goal is to analyze the complexity of magnetic fields in M dwarfs. We investigate how magnetic fields vary with the stellar temperature and how “surface” inhomogeneities are distributed in height – the dimension that is usually neglected in stellar magnetic studies. Methods. We have determined effective temperatures of the photosphere and of magnetic features, magnetic field strengths and filling factors for nine M dwarfs (M1–M7). Our χ2 analysis is based on a comparison of observed and synthetic intensity and circular polarization profiles. Stokes profiles were calculated by solving polarized radiative transfer equations. Results. Properties of magnetic structures depend on the analyzed atomic or molecular species and their formation heights. Two types of magnetic features similar to those on the Sun have been found: a cooler (starspots) and a hotter (network) one. The magnetic field strength in both starspots and network is within 3–6 kG, on average it is 5 kG. These fields occupy a large fraction of M dwarf atmospheres at all heights, up to 100%. The plasma β is less than one, implying highly magnetized stars. Conclusions. A combination of molecular and atomic species and a simultaneous analysis of intensity and circular polarization spectra have allowed us to better decipher the complexity of magnetic fields on M dwarfs, including their dependence on the atmospheric height. This work provides an opportunity to investigate a larger sample of M dwarfs and L-type brown dwarfs.
Dynamic Information Design with Diminishing Sensitivity Over News

A benevolent sender communicates non-instrumental information over time to a Bayesian receiver who experiences gain-loss utility over changes in beliefs ("news utility"). We show how to inductively compute the optimal dynamic information structure for arbitrary news-utility functions. With diminishing sensitivity over the magnitude of news, unlike in piecewise-linear news-utility models, one-shot resolution of uncertainty is strictly suboptimal under commonly used functional forms. We identify additional conditions that imply the sender optimally releases good news in small pieces but bad news in one clump. By contrast, information structures that deliver bad news gradually are never optimal. When the sender lacks commitment power, good-news messages confront a credibility problem given the receiver's diminishing sensitivity. Without loss aversion, the babbling equilibrium is essentially unique. More loss-averse receivers may enjoy higher equilibrium news-utility, contrary to the commitment case.
Learning in brain-computer interface control evidenced by joint decomposition of brain and behavior

Objective. Motor imagery-based brain-computer interfaces (BCIs) use an individual’s ability to volitionally modulate localized brain activity, often as a therapy for motor dysfunction or to probe causal relations between brain activity and behavior. However, many individuals cannot learn to successfully modulate their brain activity, greatly limiting the efficacy of BCI for therapy and for basic scientific inquiry. Formal experiments designed to probe the nature of BCI learning have offered initial evidence that coherent activity across spatially distributed and functionally diverse cognitive systems is a hallmark of individuals who can successfully learn to control the BCI. However, little is known about how these distributed networks interact through time to support learning. Approach. Here, we address this gap in knowledge by constructing and applying a multimodal network approach to decipher brain-behavior relations in motor imagery-based brain-computer interface learning using magnetoencephalography. Specifically, we employ a minimally constrained matrix decomposition method – non-negative matrix factorization – to simultaneously identify regularized, covarying subgraphs of functional connectivity, to assess their similarity to task performance, and to detect their time-varying expression. Main results. We find that learning is marked by diffuse brain-behavior relations: good learners displayed many subgraphs whose temporal expression tracked performance. Individuals also displayed marked variation in the spatial properties of subgraphs such as the connectivity between the frontal lobe and the rest of the brain, and in the temporal properties of subgraphs such as the stage of learning at which they reached maximum expression. From these observations, we posit a conceptual model in which certain subgraphs support learning by modulating brain activity in sensors near regions important for sustaining attention. To test this model, we use tools that stipulate regional dynamics on a networked system (network control theory), and find that good learners display a single subgraph whose temporal expression tracked performance and whose architecture supports easy modulation of sensors located near brain regions important for attention. Significance. The nature of our contribution to the neuroscience of BCI learning is therefore both computational and theoretical; we first use a minimally-constrained, individual specific method of identifying mesoscale structure in dynamic brain activity to show how global connectivity and interactions between distributed networks supports BCI learning, and then we use a formal network model of control to lend theoretical support to the hypothesis that these identified subgraphs are well suited to modulate attention.
DIODE: A Dense Indoor and Outdoor DEpth Dataset

We introduce DIODE, a dataset that contains thousands of diverse high resolution color images with accurate, dense, long-range depth measurements. DIODE (Dense Indoor/Outdoor DEpth) is the first public dataset to include RGBD images of indoor and outdoor scenes obtained with one sensor suite. This is in contrast to existing datasets that focus on just one domain/scene type and employ different sensors, making generalization across domains difficult. The dataset is available for download at this http URL
On the extraction of the power-law parts of probability density functions in star-forming clouds

We present a new approach to extract the power-law part of a density/column-density probability density function (ρ-pdf/N-pdf) in star-forming clouds. This approach is based on the mathematical method bPlfit of Virkar & Clauset (2014, Annals of Applied Statistics, 8, 89) and it assesses the power-law part of an arbitrary distribution, without any assumptions about the other parts of this distribution. The slope and deviation point are derived as averaged values as the number of bins is varied. Neither parameter is sensitive to spikes and other local features of the tail. This adapted bPlfit method is applied to two different sets of data from numerical simulations of star-forming clouds at scales 0.5 and 500 pc, and it displays ρ-pdf and N-pdf evolution in agreement with a number of numerical and theoretical studies. Applied to Herschel data on the regions Aquila and Rosette, the method extracts pronounced power-law tails, consistent with those seen in simulations of evolved clouds.
Self-heating of relaxor and ferroelectric ceramics during electrocaloric field cycling

Electrocaloric (EC) materials are prominent candidates for new generations of scalable and green refrigeration devices. While most often the research on EC materials has been focused on achieving high magnitudes of the EC temperature change, little is known about electrical losses and self-heating effects, despite playing a critical role in the cooling performance of these materials. Here, we analyzed the behavior of a set of ceramic materials under EC-device-like electric-field-driving conditions. The EC temperature response was studied focusing on the contributions to the self-heating in three different compositions: relaxor Pb(Mg1/3Nb2/3)O3 and two different (undoped and Nb-doped) rhombohedral ferroelectric Pb(Zr,Ti)O3 compositions. The specific relaxor and ferroelectric nature of the analyzed materials enabled us to separate the different contributions, such as domain switching and electrical conductivity, to their EC responses. We show that besides having a large EC temperature change, low electrical losses, leading to reduced self-heating effects, are another key parameter to be considered in the engineering of materials for future EC cooling devices.
Comparative evaluation of intrabony defect with platelet rich plasma alone and platelet rich plasma along with bioactive glass

Platelet-rich plasma (PRP) has been a breakthrough in the stimulation and acceleration of bone and soft tissue healing. It represents a relatively new biotechnology that is part of the growing interest in tissue engineering and cellular therapy today. Bioactive glass (BG) is a kind of bioactive ceramic consisting of SiO2, CaO, Na2O and P2O5 and results in the formation of a hydroxyapatite layer that has a stiffness closely matching the mineral phase of bone without forming fibrous tissue or promoting inflammation or toxicity. The purpose of this paper is to 1. To evaluate the role of Platelet Rich Plasma (PRP) in intrabony defects 2. ) To evaluate the role of combination of Platelet Rich Plasma along with Bioactive glass in intrabony defects. Keywords: Platelet rich plasma, Bioactive glass, Intrabony defect.
Insight into the Role of Water-Soluble Organic Solvents for the Cloud Condensation Nuclei Activation of Cholesterol

Organic aerosol is ubiquitous and partially soluble organic particles can uptake water, form droplets and act as Cloud Condensation Nuclei (CCN). Cholesterol is a well-known organic aerosol. Cholesterol is insoluble in water (<0.002 gram in 100 ml of H2O at 293°K) but readily dissolves in organic solvents. In this study, we examine the ability of cholesterol generated in 7.2%, 10.4% and 18.9% (by volume) dilutions of 3 water-soluble organic solvents (ethanol, isopropanol and acetone) to act as CCN. The measured apparent particle hygroscopicity, κ, can vary over two orders of magnitude, from ~ 0.001 to 0.1. We use statistical analysis of variance (ANOVA) to quantify experimental design factors, not explicitly addressed in traditional theory, that modify κ-values. Results show that i) particle sizes (electrical mobility and aerodynamic diameters) are important for apparent hygroscopicity κ-values and ii) atomized aerosol formed in the presence of organic solvents modifies particle size, droplet surface tens.
Liofilização como ferramenta de preservação de sêmen humano

Liofilizacao e um metodo alternativo de preservacao de espermatozoide, com vantagens sobre o criopreservado pelo baixo custo de armazenamento, facilidade no transporte pela nao necessidade de containers e baixas taxas de contaminacao. Esse estudo foi realizado no intuito e testar a eficacia de 5 acucares na protecao do material cromossomico (DNA) de espermatozoides humanos liofilizados apos reidratacao. Para isso foram utilizados espermatozoides de individuos classificados como normozooespermicos segundo OMS. Em eppendorfs foram colocados 1ml de semen que foram diluidos (1:1) em 1 ml de solucao de Glicose, Lactose, Maltose, Manitol e Sorbitol, separadamente, nas concentracoes 0.2M, 0.4M, 0.5M e 0.6M. Essas amostras foram analisadas em duas fases a primeira apos congelamento observando a porcentagem de celulas com danos de membrana e outra analise apos a liofilizacao, utilizando o Teste Cometa para detectar as taxas de fragmentacao de DNA dos espermatozoides recuperadas apos reidratacao. O processo de liofilizacao de espermatozoides nao foi capaz de recuperar a motilidade dos mesmos, mas foi capaz de manter 62.30 ± 13.76% de membrana plasmatica intacta na presenca de 0.6M manitol. As substâncias que melhor preservaram o DNA dessas celulas foram 0.2 lactose, 0.2M e 0.6M manitol e sorbitol, com apenas 4% de danos ao DNA. Esses resultados sugerem uma boa protecao ao DNA de espermatozoides humanos liofilizados, mas ainda requer testes adicionais para avaliar a fertilizacao e estudos que garantam a viabilidade da prole
The definition of exosome and extracellular vesicles (EV)

Membrane trafficking by exosomes has been the subject of intense investigation due to their diagnostic and therapeutic potential. However, although exosomes have been referred to by most authors as extracellular vesicles of endosomal origin, there are no extracellular vesicle-specific markers that can distinguish exosomes from other vesicle types. Moreover, the material isolated from different fluids such as cell culture conditioned media or plasma, generally contains a mixture of different vesicle subtypes. In this short article, we describe how the definition of the terms extracellular vesicles and exosomes varies in the literature, therefore prompting the need for a standardization of the terminology used to describe these membrane tracking particles. Such harmonization will ultimately help define the potential importance of specific vesicles as markers for various disease states. Keywords: Extracellular vesicles, exosomes, definition
Perceptions and Attitudes of Culinary Students Towards Food and Beverage Industry in Turkey

ABSTRACT In this study, a multi-dimensional and multi-item attitude scale was developed. The paper describes the scale development process. The new scale was used to investigate culinary students’ perceptions and attitudes towards working in the food and beverage industry. Culinary students of public universities were surveyed and 1055 usable questionnaires were analyzed. The results showed that students attitude towards food and beverage industry and perception of this sector is nine-dimensional: commitment to the F&B industry, co-workers, physical working conditions, nature of work, industry-person congeniality, social status, satisfaction, pay, and managers. Findings indicate that participants have negative attitudes towards physical working conditions, co-workers, pay, and managers in the food and beverage industry. On the other hand, the nature of work, industry-person congeniality and social status dimensions have a positive influence on the perceptions of students towards the food and beverage industry. Features such as using their skills, using creativity in sector satisfied students emotionally while low education level of coworkers, stressful work environment, low wages, and poor working conditions created dissatisfaction for the students. Implications for the industry and culinary departments are also discussed.
An aerosol dynamics model for simulating particle formation and growth in a mixed flow chamber

Abstract. In this work we model the aerosol size distribution dynamics in a mixed flow chamber in which new particles are formed via nucleation and subsequent condensation of oxidation products of VOCs emitted from Norway spruce seedlings. The microphysical processes included in the model are nucleation, condensation, deposition and coagulation. The aerosol dynamics in the chamber is a competition between aerosol growth and scavenging/deposition which results in a cyclic particle formation process. With a simple 1-product model, in which the formed gas is able to both condense to the particles and nucleate, we are able to catch both the oscillatory features of the particle formation process and the evolution of the number concentration in a reasonable way. The gas-phase chemistry was adjusted using pre-estimated reaction rate constant in the simulations and the particle deposition rate as a function of size was determined experimentally. Despite this, some of the essential features of the physical properties of the aerosol population could still be captured and investigated without the detailed knowledge of the physical processes underlying the problem by using the constructed model. The size dependency of the wall loss coefficient was investigated using a slightly modified measurement set-up.
Microstrip-line resonator with broadband, circularly polarized, uniform microwave field for nitrogen vacancy center ensembles in diamond

We proposed an annular microstrip-line resonator (AMLR) to provide a broadband, circularly polarized and uniform microwave field for state manipulation of negatively charged nitrogen-vacancy (NV–) center ensembles in order to achieve wide magnetic field detection range and large area microwave synchronous manipulation in miniaturized magnetic sensing devices. The bandwidth of the designed AMLR was 410 MHz when the input return losses was -10dB. With the designed bandwidth, a magnetic field detection range of 292 G was achieved based on the NV– center ensembles. The relationship between the direction of the magnetic field and the phase of the source signal indicated that the generated microwave field of AMLR was circularly polarized. Furthermore, the magnetic field magnitude homogeneity is higher than the parallel-microstrip-lines resonator (PMLR) and the intersected-microstrip-lines resonator (IMLR), and the magnetic field magnitude of AMLR had a difference of 0.012 G in the center of a 1×1 mm2 area. The AMLR has a great potential in magnetic field detection, temperature and pressure detection, which is useful for quantum applications with NV– center ensembles in diamond.
On the Reliability of the Probabilistic Worst-Case Execution Time Estimates

Probabilistic Worst-Case Execution Time estimates, through Measurement-Based Probabilistic Timing Analyses and statistical inference, desperately need for formal definition and reliability. The automatic DIAGnostic tool for applying the eXTReMe value theory within the Probabilistic Timing Analysis framework we are proposing defines a complete set of statistical tests for studying execution time traces, e.g., the real-time task average execution behavior, and estimating the extreme behavior of the task execution time, in particular the probabilistic Worst-Case Execution Time. The tool allows also defining and evaluating the reliability of the probabilistic Worst-Case Execution Time estimates with the Extreme Value Theory by applying a fuzzy logic approach. We apply the tool to traces of execution time measurements of a task running on a Commercial off-the-shelf real-time multi-core system under different execution conditions. Application of the diagnostic tool to the traces of execution time measurements particularly validates the hypothesis of using the Extreme Value Theory for estimating the probabilistic Worst-Case Execution Time for this kind of system.
Persistent growth of anthropogenic non-methane volatile organic compound (NMVOC) emissions in China during 1990–2017: drivers, speciation and ozone formation potential

Abstract. Non-methane volatile organic compounds (NMVOCs) are important ozone and secondary organic aerosol precursors and play important roles in tropospheric chemistry. In this work, we estimated the total and speciated NMVOC emissions from China's anthropogenic sources during 1990–2017 by using a bottom-up emission inventory framework and investigated the main drivers behind the trends. We found that anthropogenic NMVOC emissions in China have been increasing continuously since 1990 due to the dramatic growth in activity rates and absence of effective control measures. We estimated that anthropogenic NMVOC emissions in China increased from 9.76 Tg in 1990 to 28.5 Tg in 2017, mainly driven by the persistent growth from the industry sector and solvent use. Meanwhile, emissions from the residential and transportation sectors declined after 2005, partly offsetting the total emission increase. During 1990–2017, mass-based emissions of alkanes, alkenes, alkynes, aromatics, oxygenated volatile organic compounds (OVOCs) and other species increased by 274 %, 88 %, 4 %, 387 %, 91 % and 231 %, respectively. Following the growth in total NMVOC emissions, the corresponding ozone formation potential (OFP) increased from 38.2 Tg of O3 in 1990 to 99.7 Tg of O3 in 2017. We estimated that aromatics accounted for the largest share (43 %) of the total OFP, followed by alkenes (37 %) and OVOCs (10 %). Growth in China's NMVOC emissions was mainly driven by the transportation sector before 2000, while industry and solvent use dominated the emission growth during 2000–2010. Since 2010, although emissions from the industry sector and solvent use kept growing, strict control measures on transportation and fuel transition in residential stoves have successfully slowed down the increasing trend, especially after the implementation of China's clean air action since 2013. However, compared to large emission decreases in other major air pollutants in China (e.g., SO2, NOx and primary PM) during 2013–2017, the relatively flat trend in NMVOC emissions and OFP revealed the absence of effective control measures, which might have contributed to the increase in ozone during the same period. Given their high contributions to emissions and OFP, tailored control measures for solvent use and industrial sources should be developed, and multi-pollutant control strategies should be designed to mitigate both PM2.5 and ozone pollution simultaneously.