Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameterization of In‐Cloud Aerosol Scavenging Due to Atmospheric Ionization: Part 4. Effects of Varying Altitude

We have verified that the modified analytic solution (MAS) for aerosol scavenging designed in our previous work to parameterize in‐cloud collision rate coefficients between aerosol particles and droplets can be extended to altitudes ranging from 0 to 20.6 km, and droplet radii up to 100 μm. The MAS deals separately with the short‐range effects and long‐range effects involved in the collisions, with the short‐range effects including image electric forces, the intercept effect, and the weight effect; and the long‐range effects including Brownian diffusion, the Coulomb electric force, and phoretic forces. The effects of Brownian diffusion and Coulomb electric force increase as height increases, while the change of phoretic forces with altitude is complicated. The effects of image electric force and intercept change slightly with altitude, while the weight effect increases significantly at higher altitudes. When the short‐range effects include the irregular shape of particles, the MAS also works well. The calculations of collision rate coefficients by our Monte Carlo trajectory model for varying droplet radius, droplet charges, particle radius, particle charges, particle density, relative humidity, pressure and temperature have now been completed, and we parameterize them by the simple MAS method which makes the results user friendly and easily applicable for cloud models. Based on our results, it is now possible to build cloud models to investigate the hypothesized link between the downward current flow in the global electric circuit current and cloud microphysical changes affecting cloud development.
Individual Aircraft Noise Exposure Assessment for a Case-Crossover Study in Switzerland †

Accurate exposure assessment is essential in environmental epidemiological studies. This is especially true for aircraft noise, which is characterized by a high spatial and temporal variation. We propose a method to assess individual aircraft noise exposure for a case-crossover study investigating the acute effects of aircraft noise on cardiovascular deaths. We identified all cases of cardiovascular death (24,886) occurring near Zürich airport, Switzerland, over fifteen years from the Swiss National Cohort. Outdoor noise exposure at the home address was calculated for the night preceding death and control nights using flight operations information from Zürich airport and noise footprints calculated for major aircraft types and air routes. We estimated three different noise metrics: mean sound pressure level (LAeq), maximum sound pressure level (LAmax), and number above threshold 55 dB (NAT55) for different nighttime windows. Average nighttime aircraft noise levels were 45.2 dB, 64.6 dB, and 18.5 for LAeq, LAmax, and NAT55 respectively. In this paper, we present a method to estimate individual aircraft noise exposure with high spatio-temporal resolution and a flexible choice of exposure events and metrics. This exposure assessment will be used in a case-crossover study investigating the acute effects of noise on health.
On the Exact Distribution of Correlated Extremes in Hydrology

The analysis of hydrological hazards usually relies on asymptotic results of extreme value theory, which commonly deals with block maxima or peaks over threshold (POT) data series. However, data quality and quantity of block maxima and POT hydrological records do not usually fulfill the basic requirements of extreme value theory, thus making its application questionable and results prone to high uncertainty and low reliability. An alternative approach to better exploit the available information of continuous time series and nonextreme records is to build the exact distribution of maxima (i.e., nonasymptotic extreme value distributions) from a sequence of low‐threshold POT. Practical closed‐form results for this approach do exist only for independent high‐threshold POT series with Poisson occurrences. This study introduces new closed‐form equations of the exact distribution of maxima taken from low‐threshold POT with magnitudes characterized by an arbitrary marginal distribution and first‐order Markovian dependence, and negative binomial occurrences. The proposed model encompasses and generalizes the independent‐Poisson model and allows for analyses relying on significantly larger samples of low‐threshold POT values exhibiting dependence, temporal clustering, and overdispersion. To check the analytical results, we also introduce a new generator (called Gen2Mp) of proper first‐order Markov chains with arbitrary marginal distributions. An illustrative application to long‐term rainfall and streamflow data series shows that our model for the distribution of extreme maxima under dependence takes a step forward in developing more reliable data‐rich‐based analyses of extreme values.
Estimation of ionosphere state in AURORA online data analysis system

The paper presents the results of detection of ionospheric anomalies in online mode according to the ionosonde data at Paratunka station, Kamchatka peninsula (IKIR FEB RAS). The developed algorithms have been implemented in Aurora system for online geophysical data analysis (http://lsaoperanalysis.ikir.ru:9180/lsaoperanalysis.html). The algorithms allow us to detect sudden anomalous changes of varying intensity in the dynamics of ionospheric parameters, as well as to estimate their characteristics. The efficiency of the system and the possibility of its application in space weather forecast tasks have been shown on the examples of events occurred in 2019.
Robust Predictive Design of Field Measurements for Evapotranspiration Barriers Using Universal Multiple linear Regression

Surface barriers are commonly installed to reduce downward water movement into contaminated zones. Specifically, evapotranspiration (ET) barriers are used to store water and release it, via ET, before it can percolate into an underlying waste zone. To assess the effectiveness of a surface barrier, we used an existing data set, model‐simulated data, and a dimensionality reduction approach called universal multiple linear regression (uMLR) to optimize the required number of sensors in a 2‐m thick surface barrier. To understand the usefulness of implementing predictive uMLR to accommodate multiple monitoring objectives, we compare several network designs, selected based on down‐sampling of existing data, with a recommended sensor design based on model simulations performed without consideration of existing data. We also added consideration of “fuzzy” design, which allows more practical guidelines for field implementation of uMLR. We found that uMLR, combined with robust decision‐making, provides a simple, flexible, and high‐quality network design for monitoring the total water stored in a surface barrier across multiple uncertain conditions.
Water And Land Productivity of Lettuce (Lactuca sativa) Cultivation on Floating Pot in Wetland

The objective of this study was to determine the values of water productivity and land productivity at the floating pot on wetland and to find out whether the floating pots were optimal or not for agriculture in wetlands. The planting media used were mineral soil, and peat soil consisting of 0%, 30%, 50%, 70% and 100% each of which had hydraulic conductivity values respectively except the 100% was 36.07 cm/hour, 38.33 cm/hour, 51.23 cm/hour and 69.60 cm/hour. The water delivery used was legacy cloth which had hydraulic conductivity value was 158.4 cm/hour. The floating pots were applied to the experiment tank in the greenhouse. The decrease in water level in the experimental pool was total evapotranspiration for all plants in five types of planting media. Water level reduction during the 41-days planting period was 40.56 mm with a total water volume was 0.081 m 3 . The productivity values of land and water in the 0%, 30%, 50%, 70% and 100% peat planting media, respectively were 1.29, 1.25, 1.06, 0.8 dan 0 kg/m 2 dan 1.63, 1.63, 1.38, 1.04 dan 0 kg/m 3 . The objective of this study was to determine the values of water productivity and land productivity at the floating pot on wetland and to find out whether the floating pots were optimal or not for agriculture in wetlands . The planting media used were mineral soil, and peat soil consisting of 0%, 30%, 50%, 70% and 100% each of which had hydraulic conductivity values respectively except the 100% was 36.07 cm/hour, 38.33 cm/hour, 51.23 cm/hour and 69.60 cm/hour. The water delivery used was legacy cloth which had hydraulic conductivity value was 158.4 cm/hour. The floating pots were applied to the experiment tank in the greenhouse. The decrease in water level in the experimental pool was total evapotranspiration for all plants in five types of planting media. Water level reduction during the 41-days planting period was 40.56 mm with a total water volume was 0.081 m 3 . The productivity values of land and water in the 0%, 30%, 50%, 70% and 100% peat planting media, respectively were 1.29, 1.25, 1.06, 0.8 dan 0 kg/m 2 dan 1.63, 1.63, 1.38, 1.04 dan 0 kg/m 3 . Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-fareast-language:EN-US;}
Origin, Phylogeny and Natural Behavior of Mice: What is Their Influence on Welfare During their Maintenance in the House Facilities?

The mouse is the species most used for didactic and scientific purposes. Given the ethical principles, Brazil´s legislation and normatives, it is recommended that the welfare of mice in the laboratory be linked to the promotion of conditions in which the animal can express its natural behavior. However, in the literature, information on the natural behavior of mice is limited. Thus, the objective of this work was to conduct a study on several genealogical and phylogenetic aspects. Origin of the mouse was 14 million years ago by rodents that inhabited the region between India and Pakistan and spawned the genus Mus, the subgenus Mus, the species Mus musculus and several subspecies. This speciation was probably related to its migration, colonization and commensal relationship with humans. Thus, a characteristic that stands out in the mouse is its adaptive capacity and social flexibility, always seeking reproductive success through the provision of food, territorialism, and formation of small groups, usually polygamous. Thus, we can say that the mouse kept in its genetics characteristics of its wild behavior, such as competition and interpersonal aggressiveness, as well close relationship with humans and its high adaptability to new environments, provided mainly food supply. In conclusion, we believe that its welfare is directed towards respecting the natural characteristics and biological evolution of the mouse, for example, stress is part of the animal’s physiology, its high adaptability and commensalism with humans. However, raising the welfare of mice in the house facilities should be accomplished by developing methodologies that enable the animal to demonstrate its preference (or choice) for space, food, floor, handling and other management procedures as animal reproduction or biological tests.
Accurate Detection of Built-Up Areas from High-Resolution Remote Sensing Imagery Using a Fully Convolutional Network

The analysis of built-up areas has always been a popular research topic for remote sensing applications. However, automatic extraction of built-up areas from a wide range of regions remains challenging. In this article, a fully convolutional network (FCN)–based strategy is proposed to address built-up area extraction. The proposed algorithm can be divided into two main steps. First, divide the remote sensing image into blocks and extract their deep features by a lightweight multi-branch convolutional neural network (LMB-CNN). Second, rearrange the deep features into feature maps that are fed into a well-designed FCN for image segmentation. Our FCN is integrated with multi-branch blocks and outputs multi-channel segmentation masks that are utilized to balance the false alarm and missing alarm. Experiments demonstrate that the overall classification accuracy of the proposed algorithm can achieve 98.75% in the test data set and that it has a faster processing compared with the existing state-of-the-art algorithms.
Effect of Urbanization on Ozone and Resultant Health Effects in the Pearl River Delta Region of China

The United Nations has reported that 55% of the global population resides in urban areas, and 68% of the population is expected to be urban dwellers by 2050. Urbanization has critical implications for global land cover. Relevant literature has provided evidence attributing climatic effects to urban expansion; however, few studies have investigated the effect on public health and pollutant sensitivity to emissions. This study aimed to characterize the effect of urbanization‐induced changes in regional climate on ozone (O3), to evaluate ozone sensitivity to nitrogen oxide (NOx) and volatile organic compound (VOC) emissions, and to estimate premature mortalities due to O3 exposure. We employed atmospheric models with the higher‐order decoupled direct method to simulate effects of urbanization on O3 and to determine O3 sensitivity to NOx and VOC emissions. China‐specific concentration response functions were utilized to estimate cardiovascular and respiratory mortalities due to ozone exposure. Urbanization increased O3, which translated to a 39.6% increase in O3‐induced premature mortality (1,100 deaths). Moreover, O3 has become less/more sensitive to unit changes in NOx and VOC emissions in various cities. Urban greening may reduce urban temperature, but it may increase O3 in some cities due to the additional VOC emissions of greening. These findings highlight the strong interactions between land use policies, urban climate adaptation strategies, and air quality policies, suggesting the need of cobeneficial strategies and policies. We proposed a precision environmental management concept that emphasizes the importance of considering the specific atmospheric condition and composition of a city when formulating its environmental policies.
From microstructures to macroscale carbon export : influences of marine snow composition on settling velocity and microbial colonization

Microplastics influence the transport of organic matter from the ocean surface to the deep sea by altering the settling behavior of marine aggregates. We formed diatom aggregates with differing concentrations of microfibers and observed that microfiber addition stimulated aggregate formation, but decreased structural cohesion and caused them to break apart more readily, resulting in a smaller average size. Microfiber addition also reduced the settling velocity of diatom aggregates in laboratory simulations of particle export using roller tanks. Slower sinking extends aggregate retention time in the upper ocean, thereby increasing the time available for organic matter remineralization in the upper water column. Our laboratory experiments suggest that microfiber concentrations typical of those occurring in the ocean decrease potential export flux by 30-60%. If confirmed in situ, this means that present day microfiber concentrations in surface waters may substantially reduce the efficiency of the biological carbon pump relative to the preplastic era.
Complete Three‐Dimensional Coseismic Deformation Field of the 2016 Central Tottori Earthquake by Integrating Left‐ and Right‐Looking InSAR Observations With the Improved SM‐VCE Method

The three‐dimensional (3‐D) deformation field associated with the 2016 Central Tottori earthquake is retrieved from advanced land observing satellite 2 interferometric synthetic aperture radar (InSAR) observations with four different viewing geometries, that is, ascending/descending tracks and left‐/right‐looking modes. The strain model and variance component estimation (SM, VCE, SM‐VCE) method is exploited and improved to integrate the InSAR observations with different viewing geometries so that the 3‐D deformation field is not affected by the inconsistent coverage of SAR footprints or the gross errors in InSAR observations. The obtained results are consistent with GNSS observations, indicating that the improved SM‐VCE method, known as SM‐RVCE in this paper, is capable of retrieving an accurate and spatially complete 3‐D deformation field for this earthquake. In addition, the precision of the InSAR observations and the estimated 3‐D deformation are quantitatively assessed by the SM‐RVCE method. Finally, on the basis of the estimated 3‐D coseismic deformation, the source parameters of this event are inverted, revealing an asperity with a maximum strike‐parallel slip of ~1.1 m concentrated at depths between 2 and 10 km. The estimated seismic moment is 2.4 × 1018 Nm, which corresponds to a Mw 6.2 event.
Potential, production and utilization level of pelagic fish resource in Ambon City

In responsible and sustainable fisheries, marine resources should be exploited at optimum level in which potency, production and utilization level is known. This research was conducted to analysed potency, production and utilization level of pelagic fish in Ambon Island waters. Data for the analysis was obtained from the secondary data of Dinas Kelautan dan Perikanan Maluku province in the form of catch and effort for period 2005–2015 and then analysed by using Schaefer model. Estimated Maximum Sustainable Yield (MSY) was 103,513 tons with Total Allowable Catch (TAC) was 82,811 tons. Production of pelagic fish fluctuated but tended to increase due to increasing of fishing vessels and fishing gears. Catch per unit effort of purse seine and pole and line contributed more for the pelagic fish production than five other fishing gears. The utilization of pelagic fish resources in Ambon tended to increase with annual average 61.7% from TAC or 49.40% of MSY during the period of 2005-2015. In the last three years (2013-2015) the level of utilization increased significantly and has reached 98.31% from TAC or 78.65% of MSY which leads to fully exploitation. These results indicated that fishing effort should be maintained and monitored strictly to prevent over exploitation of pelagic fish resource.
Effect of Serpentinite Dehydration in Subducting Slabs on Isotopic Diversity in Recycled Oceanic Crust and Its Role in Isotopic Heterogeneity of the Mantle

We conducted geochemical modeling of the isotopic evolution of subducted oceanic crust that takes into account the chemical variation produced at mid‐ocean ridges and in subduction zones, and examined the suitability of our model for generating the high‐μ (HIMU), focal zone (FOZO), and prevalent mantle (PREMA) mantle components. Chemical variation produced at mid‐ocean ridges was represented by the chemical compositions of two groups of mid‐ocean ridge basalts (depleted and enriched). Chemical variation produced in subduction zones was investigated with pressure‐temperature paths of slabs of different ages (governing the physicochemical conditions of element exchanges), as determined using representative subduction zones involving young (hot), intermediate, and old (cold) slabs. The results suggest that dehydration of oceanic crust cannot alone produce isotopic variation beyond the bounds of PREMA compositions. Producing the wider range of isotopic diversity from PREMA to FOZO requires various degrees of element partitioning between subducted oceanic crust and fluids (aqueous or supercritical) released by dehydration of slab serpentinite. The extremely radiogenic Pb isotopic signature of HIMU can only be produced by extensive reaction between subducted oceanic crust and fluids derived from slab serpentinite along the specific geothermal gradient resulting from the relatively slow descent of moderately old slabs. The rarity of such tectonic conditions explains the scarcity of HIMU.
Nonequilibrium quantum phase transition in a spinor quantum gas in a lattice coupled to a membrane

Recently, a novel kind of hybrid atom-optomechanical system, consisting of atoms in a lattice coupled to a membrane, has been experimentally realized [A. Vochezer et al., Phys. Rev. Lett. 120, 073602 (2018)], which promises a viable contender in the competitive field of simulating nonequilibrium many-body physics. Here we are motivated to investigate a spinor Bose gas coupled to a vibrational mode of a nanomembrane, focusing on analyzing the role of the spinor degrees of freedom therein. Through an adiabatic elimination of the degrees of freedom of the quantum oscillator, we derive an effective Hamiltonian which reveals a competition between the force localizing the atoms and the membrane displacement. We analyze the dynamical stability of the steady state using the Bogoliubov--de Gennes approach and derive the stationary phase diagram in the parameter space. Then, we investigate the first-order nonequilibrium quantum phase transition (NQPT) from a localized symmetric state of the atom cloud to a shifted symmetry-broken state, characterized by the occurrence of a hysteresis. Moreover we present a detailed analysis of the effects of the spin degree of freedom on NQPT. Our work presents a simple way to study the effects of the spinor degree of freedom on the nonequilibrium nonlinear phenomena that is complementary to ongoing experiments on the hybrid atom-optomechanical system.
Path Design for Cellular-Connected UAV with Reinforcement Learning

This paper studies the path design problem for cellular-connected unmanned aerial vehicle (UAV), which aims to minimize its mission completion time while maintaining good connectivity with the cellular network. We first argue that the conventional path design approach via formulating and solving optimization problems faces several practical challenges, and then propose a new reinforcement learning-based UAV path design algorithm by applying temporal-difference method to directly learn the state-value function of the corresponding Markov Decision Process. The proposed algorithm is further extended by using linear function approximation with tile coding to deal with large state space. The proposed algorithms only require the raw measured or simulation-generated signal samples as the input and are suitable for both online and offline implementations. Numerical results show that the proposed path designs can successfully avoid the coverage holes of cellular networks even in the complex urban environment.
α-attractor dark energy in view of next-generation cosmological surveys

The α-attractor inflationary models are nowadays favored by CMB Planck observations. Their similarity with canonical quintessence models motivates the exploration of a common framework that explains both inflation and dark energy. We study the expected constraints that next-generation cosmological experiments will be able to impose for the dark energy α-attractor model. We systematically account for the constraining power of SNIa from WFIRST, BAO from DESI and WFIRST, galaxy clustering and shear from LSST and Stage-4 CMB experiments. We assume a tensor-to-scalar ratio, 10−3 < r < 10−2, which permits to explore the wide regime sufficiently close, but distinct, to a cosmological constant, without need of fine tunning the initial value of the field. We find that the combination S4CMB + LSST + SNIa will achieve the best results, improving the FoM by almost an order of magnitude; respect to the S4CMB + BAO + SNIa case. We find this is also true for the FoM of the w0 − wa parameters. Therefore, future surveys will be uniquely able to probe models connecting early and late cosmic acceleration.