Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-layer transmission design in a class of delay-aware two-user interference networks

This paper investigates the transmission design problem in a class of two-user interference networks where each source sends two types of delay-sensitive message to its destination. The first type is generated periodically with a fixed rate and is desired to be delivered immediately with sufficiently high reliability. The second type, generated randomly, can be placed in queues but the average queueing delay should be finite. Each user applies point-to-point Gaussian random codes to transmit information, using constrained instantaneous and average powers. We utilise the Lyapunov optimisation theory to construct a cross-layer transmission strategy, which can adapt to both the channel state information (CSI) at the physical layer and the queue state information at the media access control layer. Our results show that the proposed strategy can achieve a better tradeoff among power consumption, transmission reliability, and queueing delay, compared with the conventional CSI-based transmission design.
Effect of rice plant on seasonal methane emission patterns

A greenhouse experiment was done to investigate the effect of the rice plant on seasonal methane emission patterns. The effect of the rice plant was separated from the effect of other factors by measuring methane emissions from rice plants with different ages at the same time. Soil was incubated at the same time. All the rice cultivars could at least cause one methane emission peak which is a maximum at the early growth stage. The easily decomposable soil carbon source resulted in the increase of methane concentration in soil solution. Rice plant mediated methane emission. The rice plants could cause a second maximum methane emission at the heading/filling stage if they could produce enough root exudates for methane production. Rice cultivars differed in their effect on seasonal methane emission pattern. In later growth stages, methane emissions through the rice plants decreased. This decreases in methane emission at the later growth stages were attributed to senescence of rice roots.
Comparison between 2D Shallow-Water Simulations and Energy-Momentum Computations for Transcritical Flow Past Channel Contractions

Multidimensional simulators of channel and river flow are widely used in industry and academia, raising the question about whether the classical one-dimensional theory of open-channel flow remains relevant in hydraulic engineering. Channel contractions that induce transcritical flow are interesting scenarios to test the classical 1D theory against multidimensional simulations, because supercritical flow in channels of variable width leads to multidimensional flow structures. Transcritical flows are important in practice, because the ensuing hydraulic jumps and regions of supercritical flow may damage hydraulic structures that otherwise operate under tranquil conditions. We compare well-resolved simulations of the 2D shallow-water Equations (SWE) with 1D energy-momentum calculations for flow past symmetric channel contractions. We analyze the accuracy of the classical energy-momentum gradually-varied flow theory to predict the onset of regime transitions and the location of hydraulic jumps. We test the relative performance of the 1D theory for different constriction geometries, and identify the flow mechanisms behind the discrepancies between the 1D and 2D predictions. The grid resolution used in the 2D SWE plays an important role in these predictions, because coarse-grid 2D simulations yield essentially quasi-1D results. Considering its simplicity and negligible computational cost compared with the 2D SWE simulations, the classical 1D theory performs remarkably well for a wide range of flow conditions and contraction geometries. In contrast, we observe large deviations between the 1D and 2D models in flow past abrupt contractions with a large width ratio, as expected. Only modified versions of the 1D theory, taking into account intense local head losses and the propagation of spatial flow structures downstream from the contraction, can succeed at describing these flow scenarios.
Shear Velocity Structure From Ambient Noise and Teleseismic Surface Wave Tomography in the Cascades Around Mount St. Helens

Mount St. Helens (MSH) lies in the forearc of the Cascades where conditions should be too cold for volcanism. To better understand thermal conditions and magma pathways beneath MSH, data from a dense broadband array are used to produce high‐resolution tomographic images of the crust and upper mantle. Rayleigh‐wave phase‐velocity maps and three‐dimensional images of shear velocity (Vs), generated from ambient noise and earthquake surface waves, show that west of MSH the middle‐lower crust is anomalously fast (3.95 ± 0.1 km/s), overlying an anomalously slow uppermost mantle (4.0–4.2 km/s). This combination renders the forearc Moho weak to invisible, with crustal velocity variations being a primary cause; fast crust is necessary to explain the absent Moho. Comparison with predicted rock velocities indicates that the fast crust likely consists of gabbros and basalts of the Siletzia terrane, an accreted oceanic plateau. East of MSH where magmatism is abundant, middle‐lower crust Vs is low (3.45–3.6 km/s), consistent with hot and potentially partly molten crust of more intermediate to felsic composition. This crust overlies mantle with more typical wave speeds, producing a strong Moho. The sharp boundary in crust and mantle Vs within a few kilometers of the MSH edifice correlates with a sharp boundary from low heat flow in the forearc to high arc heat flow and demonstrates that the crustal terrane boundary here couples with thermal structure to focus lateral melt transport from the lower crust westward to arc volcanoes.
Rifting of the northern margin of the Indian craton in the Early Cretaceous: Insight from the Aulis Trachyte of the Lesser Himalaya (Nepal)

To reconstruct the early tectonic history of the Himalayan orogen before final India-Asia collision, we carried out geochemical and geochronological studies on the Early Cretaceous Aulis Trachyte of the Lesser Himalaya. The trace-element geochemistry of the trachytic lava flows suggests formation in a rift setting, and zircon U-Pb ages indicate that volcanism occurred in Early Cretaceous time. The felsic volcanics show enrichment of more incompatible elements and rare earth elements, a pattern that is identical to the trachyte from the East African Rift (Kenya rift), with conspicuous negative anomalies of Nb, P, and Ti. Although much of the zircon age data are discordant, they strongly suggest an Early Cretaceous eruption age, which is in agreement with the fossil age of intravolcanic siltstones. The Aulis Trachyte provides the first corroboration of Cretaceous rifting in the Lesser Himalaya as suggested by paleomagnetic data associated with the concept that the northern margin of India separated as a microcontinent and drifted north in the Neo-Tethys before terminal collision of India with Asia.
Algal growth and weathering crust state drive variability in western Greenland Ice Sheet ice albedo

Abstract. One of the primary controls upon the melting of the Greenland Ice Sheet (GrIS) is albedo, a measure of how much solar radiation that hits a surface is reflected without being absorbed. Lower-albedo snow and ice surfaces therefore warm more quickly. There is a major difference in the albedo of snow-covered versus bare-ice surfaces, but observations also show that there is substantial spatio-temporal variability of up to ∼0.4 in bare-ice albedo. Variability in bare-ice albedo has been attributed to a number of processes including the accumulation of light-absorbing impurities (LAIs) and the changing physical properties of the near-surface ice. However, the combined impact of these processes upon albedo remains poorly constrained. Here we use field observations to show that pigmented glacier algae are ubiquitous and cause surface darkening both within and outside the south-west GrIS “dark zone” but that other factors including modification of the ice surface by algal bloom presence, surface topography and weathering crust state are also important in determining patterns of daily albedo variability. We further use observations from an unmanned aerial system (UAS) to examine the scale gap in albedo between ground versus remotely sensed measurements made by Sentinel-2 (S-2) and MODIS. S-2 observations provide a highly conservative estimate of algal bloom presence because algal blooms occur in patches much smaller than the ground resolution of S-2 data. Nevertheless, the bare-ice albedo distribution at the scale of 20 m×20 m S-2 pixels is generally unimodal and unskewed. Conversely, bare-ice surfaces have a left-skewed albedo distribution at MODIS MOD10A1 scales. Thus, when MOD10A1 observations are used as input to energy balance modelling, meltwater production can be underestimated by ∼2 %. Our study highlights that (1) the impact of the weathering crust state is of similar importance to the direct darkening role of light-absorbing impurities upon ice albedo and (2) there is a spatial-scale dependency in albedo measurement which reduces detection of real changes at coarser resolutions.
Cloud Masking for Landsat 8 and MODIS Terra Over Snow‐Covered Terrain: Error Analysis and Spectral Similarity Between Snow and Cloud

Automated, reliable cloud masks over snow‐covered terrain would improve the retrieval of snow properties from multispectral satellite sensors. The U.S. Geological Survey and NASA chose the currently operational cloud masks based on global performance across diverse land cover types. This study assesses errors in these cloud masks over snow‐covered, midlatitude mountains. We use 26 Landsat 8 scenes with manually delineated cloud, snow, and land cover to assess the performance of two cloud masks: CFMask for the Landsat 8 OLI and the cloud mask that ships with Moderate‐Resolution Imaging Spectroradiometer (MODIS) surface reflectance products MOD09GA and MYD09GA. The overall precision and recall of CFMask over snow‐covered terrain are 0.70 and 0.86; the MOD09GA cloud mask precision and recall are 0.17 and 0.72. A plausible reason for poorer performance of cloud masks over snow lies in the potential similarity between multispectral signatures of snow and cloud pixels in three situations: (1) Snow at high elevation is bright enough in the “cirrus” bands (Landsat band 9 or MODIS band 26) to be classified as cirrus. (2) Reflectances of “dark” clouds in shortwave infrared (SWIR) bands are bracketed by snow spectra in those wavelengths. (3) Snow as part of a fractional mixture in a pixel with soils sometimes produces “bright SWIR” pixels that look like clouds. Improvement in snow‐cloud discrimination in these cases will require more information than just the spectrum of the sensor's bands or will require deployment of a spaceborne imaging spectrometer, which could discriminate between snow and cloud under conditions where a multispectral sensor might not.
Leveraging Compression in In-Memory Databases

—Recently, there has been a trend towards column-oriented databases, which in most cases apply lightweight compression techniques to improve read access. At the same time, in-memory databases become reality due to availability of huge amounts of main memory. In-memory databases achieve their optimal performance by building up cache-aware algorithms based on cost models for memory hierarchies. In this paper, we use a generic cost model for main memory access and show how lightweight compression schemes improve the cache behavior, which directly correlates with the performance of in-memory databases.
Groundwater Quality Assessment for Irrigation Purposes in the West of Minia, Governorate, South Egypt b

This investigation has been conducted to assess the suitability of ground waters in west Minia governorate for irrigation purposes. Thirty-three groundwater samples were collected from different sites, along Assiut the West Desert Road. These samples were analyzed for water quality criteria, namely electrical conductivity (EC), soluble cations (Ca2+, Mg2+, Na+ and K+), anions (HCO3-, CO32-, Cl- and SO42-). The chemical parameters that control water quality such as sodium adsorption ratio (SAR), soluble sodium percent (SSP%), residual sodium carbonated (RSC), Kelley’s ratio (KR), potential salinity (PS), permeability index (PI), total alkalinity, total hardness, magnesium ratio were also calculated using standard equations. Results revealed that anions contents in the studied ground waters followed the sequence: SO42->Cl-> HCO3- whereas CO-3ion was not detected. On the other hand, the cations contents of the water samples followed the sequence: Na+> Mg2+> Ca2+> K+. In addition, the pH values of the studied water samples ranged between 6.9 and 7. 9. The analytical results indicated that 94 % of the groundwater samples can be classified as good for irrigation on bases of EC, SAR, RSC and SSP%. Both SAR and RSC values indicated no liability for sodicity hazard. However, groundwater samples had high salinity levels and low sodicity (C3–S1). Some other parameters, which were generally used for assessing water quality e.g. Irrigation Water Quality Index (IWQI) and Relative Crop Yield Potential (RCYP), were calculated. GIS was used to create a water quality database including spatial distribution map for each parameter. The results obtained herein showed that about 21 % of the groundwater samples belong to No Restriction category (NR) while about 79 % from the total samples belong to the Low Restriction (LR) category. According to the RYPC values calculated for some crops that can be cultivated using the investigated waters, the following sequence is obtained: sugar beet (94) > wheat (74) > corn (33) > bean (13). Thus, it can be concluded that the studied groundwater can successfully be used for irrigation with special salinity control management i.e. leaching requirements and salt tolerant plants.
Shelf dense water transport in the Beaufort Sea

CTD data from the Beaufort Sea showed fresh surface water of 27 psu in August compared to 31 psu in April, which indicates a saline injection during the winter freezing season. Where and how those cold and salty dense water moves is very important to the halocline formation process. A coupled ice-ocean model is used to simulate the circulation and ice dynamics and thermodynamics in the Beaufort Sea. With 3.4km horizontal resolution and 16 vertical layers, this nested model obtains open boundary conditions from a similar model with large domain including Arctic and North Atlantic Oceans with 27.5km horizontal resolution. Numerical tracer studies revealed that the rate of dense shelf water penetrating the slope halocline in the Beaufort Sea is low which agrees with results from observations. Sensitivity studies with idealized model identified that salinity stratification is the main reason for the low rate. Wind is important for the position and shape of the horizontal front over the shelf break. Wind and geostrophic flow generated by horizontal salinity front over the shelf break are the two sources of shelf break transports, and among which, wind is the dominant factor. Eddy activities over shelf break generated by salinity front are evident while the shelf break flow along the same direction as the geostrophic flow generated by the front, but in case of reversal of this flow by wind, the eddy activities are also depressed.
The Impact of Radiosounding Observations on Numerical Weather Prediction Analyses in the Arctic

The radiosounding network in the Arctic, despite being sparse, is a crucial part of the atmospheric observing system for weather prediction and reanalysis. The spatial coverage of the network was evaluated using a numerical weather prediction model, comparing radiosonde observations from Arctic land stations and expeditions in the central Arctic Ocean with operational analyses and background fields (12‐hr forecasts) from European Centre for Medium‐Range Weather Forecasts for January 2016 to September 2018. The results show that the impact of radiosonde observations on analyses has large geographical variation. In data‐sparse areas, such as the central Arctic Ocean, high‐quality radiosonde observations substantially improve the analyses, while satellite observations are not able to compensate for the large spatial gap in the radiosounding network. In areas where the network is reasonably dense, the quality of background field is more related to how radiosonde observations are utilized in the assimilation and to the quality of those observations.
Validation of Satellite, Reanalysis and RCM Data of Monthly Rainfall in Calabria (Southern Italy)

Skills in reproducing monthly rainfall over Calabria (southern Italy) have been validated for the Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) satellite data, the E-OBS dataset and 13 Global Climate Model-Regional Climate Model (GCM-RCM) combinations, belonging to the ENSEMBLES project output set. To this aim, 73 rainfall series for the period 1951–1980 and 79 series for the period 1981–2010 have been selected from the database managed by Multi-Risk Functional Centre of the Regional Agency for Environmental Protection (Regione Calabria). The relative mean and standard deviation errors, and the Pearson correlation coefficient have been used as validation metrics. Results showed that CHIRPS satellite data (available only for the 1981–2010 validation period) and RCMs based on the ECHAM5 Global Climate performed better both in mean error and standard deviation error compared to other datasets. Moreover, a slight appreciable improvement in performance for all ECHAM5-based models and for the E-OBS dataset has been observed in the 1981–2010 time-period. The whole validation-and-assessment procedure applied in this work is general and easily applicable where ground data and gridded data are available. This procedure might help scientists and policy makers to select among available datasets those best suited for further applications, even in regions with complex orography and an inadequate amount of representative stations.
Correlation Analysis of Spatial Distribution, Temporal Seismotectonics, and Return Period of Earthquake in East Nusa Tenggara, Indonesia

This paper presents spatial distribution, temporal seismotectonics, and return period of earthquake in East Nusa Tenggara Province, Indonesia, using earthquake data and Maximum Likelihood methods. The data used are ISC, USGS/NEIC, and Indonesian Meteorology, Climatology and Geophysics Agency (IMCGA) earthquake catalog data for the period of 1918 to 2015. The results show that the a-value ranges from 5.0 to 8.5 and b-value ranges from 0.6 to 1.3. The pattern of spatial distribution of b-value is relatively low corresponding to the low of a-value, which means the high level of stress of rock in the area. The fractal dimension shows that the D value ranges from 1.384 to 1.874. The earthquake that occurred in East Nusa Tenggara Province was dominated by a small magnitude with great seismicity and the fastest return period is in Alor and Timor islands which is 44 days.
Leveraging the signature of heterotrophic respiration on atmospheric CO2 for model benchmarking

Abstract. Spatial and temporal variations in atmospheric carbon dioxide (CO2) reflect large-scale net carbon exchange between the atmosphere and terrestrial ecosystems. Soil heterotrophic respiration (HR) is one of the component fluxes that drive this net exchange, but, given observational limitations, it is difficult to quantify this flux or to evaluate global-scale model simulations thereof. Here, we show that atmospheric CO2 can provide a useful constraint on large-scale patterns of soil heterotrophic respiration. We analyze three soil model configurations (CASA-CNP, MIMICS, and CORPSE) that simulate HR fluxes within a biogeochemical test bed that provides each model with identical net primary productivity (NPP) and climate forcings. We subsequently quantify the effects of variation in simulated terrestrial carbon fluxes (NPP and HR from the three soil test-bed models) on atmospheric CO2 distributions using a three-dimensional atmospheric tracer transport model. Our results show that atmospheric CO2 observations can be used to identify deficiencies in model simulations of the seasonal cycle and interannual variability in HR relative to NPP. In particular, the two models that explicitly simulated microbial processes (MIMICS and CORPSE) were more variable than observations at interannual timescales and showed a stronger-than-observed temperature sensitivity. Our results prompt future research directions to use atmospheric CO2, in combination with additional constraints on terrestrial productivity or soil carbon stocks, for evaluating HR fluxes.
Execução e Gestão de Aplicações Conteinerizadas

Cloud computing, containerization technologies and containers management have recently gained considerable interest from organizations as a way to accelerate the development and delivery of software to their customers in addition to facilitate the management of such software in the production’s environment. This is a critical transformation necessary for the organizations that develop software so they remain competitive in the market. Adopting these new techniques is a complex task that reflects itself in several aspects of the organization, from software development and delivery processes to the necessary physical infrastructure. This work aims to introduce the applications’ contanerization into the software development process of the organizations, identifying the components needed to create a software development pipeline suitable for container concepts. In addition, the Kubernetes platform was evaluated to see if it is capable of performing the deployment of containerized applications as well as managing those applications during its life cycle. In order to perform this evaluation, an application with an architecture based on micro-services was containerized. This application meets a set of requirements capable of evaluating several points of the Kubernetes platform. Another key point on this dissertation is the introduction of elasticity at the node level of the Kubernetes cluster. As the cluster nodes in this work are supported by an OpenStack private cloud, we have manipulated the elasticity of the cloud so that we could automatically launch new nodes when the cluster is at its CPU load limit and thus continue to deploy new containers. This work leads us to realise that the Kubernetes’ plataform is able to carry out the deployment and to manage containers applications in an efficient and agile way. In addition, it demonstrates that Kubernetes is a very complete tool and that besides managing and realizing the deployment of containerized applications in a distributed environment, it has automatic mechanisms that help these applications during their life cycle. By introducing elasticity to the nodes of the Kubernetes cluster it was possible to make it more robust, without the need to manually introduce nodes when there is the necessity to allocate resources to the cluster.