Miracle-dz/UniFAR-FTUs huggingface dataset:
Controlling Factors of Phytoplankton Productivity in Marshes in a Hot Climate with High Seasonal Variation

In this work the Auda marsh, which is part of a system of Iraqi marshes, was sampled to assess the seasonal dynamics and controlling factors of microalgae productivity. The marshes are situated in a hot climate with high seasonal variation near the Arabian Gulf. Physicochemical and biological measurements were taken for water in three areas. Bio-optical models were constructed to describe the primary productivity and chlorophyll-a concentrations in the wet and dry seasons separately and also for the entire area of the Iraqi marshes. The models, as well as almost all measurements, showed high seasonal variation. The mean water temperature was 16 °C in the wet season and 28 °C in the dry season. An almost twofold difference was measured for turbidity and the concentrations of dissolved oxygen and chlorophyll-a for the two seasons. Chlorophyll-a appeared to be a better indicator of ecosystem conditions than primary productivity or biological oxygen demand, according to the results obtained from canonical correlation analysis. Nitrogen or phosphorous did not explain primary productivity or chlorophyll-a to an appreciable extent. Biological variables were related most strongly to water temperature and turbidity, which were the factors most important for controlling phytoplankton productivity in the marshes.
Effects of Probability-Distributed Losses on Flood Estimates Using Event-Based Rainfall-Runoff Models

Probability distributions of initial losses are investigated using a large dataset of catchments throughout Australia. The variability in design flood estimates caused by probability-distributed initial losses and associated uncertainties are investigated. Based on historic data sets in Australia, the Gamma and Beta distributions are found to be suitable for describing initial loss data. It has also been found that the central tendency of probability-distributed initial loss is more important in design flood estimation than the form of the probability density function. Findings from this study have notable implications on the regionalization of initial loss data, which is required for the application of Monte Carlo methods for design flood estimation in ungauged catchments.
Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts

Heavy snowfall events can cause substantial transport disruption and exert a negative socioeconomic impact, particularly in low‐altitude and midlatitude regions, where it seldom snows. Such problems may be exacerbated if there are rapid transitions between different precipitation phases within the same event. Previous studies have addressed this issue using precipitation‐phase nowcasting techniques, often focusing on critical infrastructures such as airports. Very short‐range forecasts are usually based on trends of observations and numerical weather prediction models. Nowcasting schemes considering the precipitation phase generally merge extrapolated surface observations, modelled vertical temperature profiles, and extrapolated weather radar precipitation fields. In this study, a precipitation‐phase nowcasting scheme was developed and evaluated, initially using eight different algorithms to classify precipitation into rain, sleet or snow, together with a probabilistic weather radar data extrapolation technique. In addition, three combinations of the previous algorithms were also evaluated. The nowcasting scheme was applied to a midlatitude region in the Northwestern Mediterranean to assess its performance during eight snowfall events. Single and combined algorithms were compared to determine their suitability in conditions close to freezing point, when there is increased uncertainty about the precipitation phase. The results indicate that, although single and combined algorithms perform similarly, the latter can provide valuable information during event monitoring. Precipitation phase transitions were also analysed, finding that on average they can be forecast correctly with a lead time of 120 min. The proposed methodology can be readily applied to other regions where ground‐based observations, weather radar data, and model forecasts are available.
Genetic interrelationships of elite sorghum (Sorghum bicolor (L.) Moench) genotypes bred for Striga resistance and compatibility with Fusarium oxysporum f. sp. strigae (FOS) revealed by microsatellites

ABSTRACT Genetic diversity is key for breeding population development, hybrid breeding, heterotic grouping and genetic analysis, among others. The objective of this study was to examine genetic interrelationships among elite sorghum genotypes bred for resistance to Striga hermonthica Del. Benth and S. asiatica (L.) Kuntze and compatible with a biological control agent Fusarium oxysporum f. sp. strigae (FOS) against Striga using 22 polymorphic simple sequence repeat (SSR) or microsatellite markers. The number of alleles per locus detected by the markers varied from 2 to 7 with a mean value of 4.23. The polymorphic information content (PIC) of the SSR markers ranged from 0.15 to 0.84 with a mean of 0.57 showing moderate discriminatory power of the primers. The neighbour-joining clustering algorithm classified the genotypes into three main groups, revealing narrow to moderate variations existing among the test genotypes. Overall, the genetic diversity revealed by the study will be useful for designed crosses and pyramiding of broad-based resistance genes to control Striga for sustainable sorghum production.
Acidihalobacter: Novel Halotolerant Iron- and Sulfur-oxidizing Acidophiles with Potential for Saline Water Bioleaching

The principal genomic features of Acidihalobacter prosperus DSM 14174 (strain V6) are presented here. This is a mesophilic, halotolerant iron/sulfur oxidising acidophile that was isolated from seawater at Vulcano, Italy. It has potential for use in biomining applications in regions where high salinity exists in the source water and ores. Acidihalobacter prosperus (previously known as Thiobacillus prosperus) is a Gram-negative, halotolerant, acidophilic, mesophilic and chemolitho-autotrophic bacterium capable of oxidising both iron and reduced sulfur compounds (1). The type strain, A. prosperus DSM 5130, was isolated from a marine geothermal field in Italy. It requires a minimum of 0.04 M Cl− for growth and tolerates up to 0.6 M Cl− (1). A. prosperus DSM 14174 was isolated from a shallow acidic pool by the shore of Baia de Levant, Aeolion Islands of Vulcano, Italy (2). Like A. prosperus DSM 5130, it does not grow in the absence of salt (3). It has been used in saltrich systems for the active biomining of metal sulfide ores (4). Total DNA extracted from A. prosperus DSM 14174 was sequenced using Illumina MiSeq (204,485 paired-end 300 bp × 2 reads) and PacBio RS single-molecule real-time (SMRT) sequencing technologies (96,369 reads post-filter, 11,756 bp mean length). De novo hybrid assembly using SPAdes 3.9. 0 (5) produced a circular 162,484-bp plasmid (~32-fold coverage) and two chromosome fragments of 2,607,071 bp and 752,753 bp (~18-fold coverage). The
A Unifying Theory of Electronic Money and Payment Systems

We present a general theory of payment systems that is capable of describing both traditional and electronic forms of payment. Starting from the three basic functions of money and general non-functional requirements, we derive the necessary and sufficient properties of technical implementations of money and payments. We describe possible scalable implementations of e-money schemes based on a general description of their data structures (money distributions) and payments. We define the notion of bill scheme, in which the value units are bills with invariant values, and show that only the bill scheme allows for scalable and practically efficient implementations through decomposition, where the components have to process a considerably smaller amount of data and a number of payment requests, compared to the whole system.
Nickel Complexes Immobilized in Modified Ionic Liquids Anchored in Structured Materials for Ethylene Oligomerization

This work describes the study of ethylene oligomerization reactions catalyzed by nickel-β-diimine complexes immobilized on β-zeolite, [Si]-MCM-41 (Mobil Composition of Matter 41) and [Si,Al]-MCM-41 modified with an ionic liquid. XRD and N2 adsorption and desorption analyses were used to characterize the modified supports—namely, IL-Zeoβ, IL-MCM-41 and IL-Al-MCM-41—and the data showed that material organization remained intact even after incorporation of ionic liquid. N2 adsorption and desorption analyses suggested that ionic liquid can be confined in pores of support materials. Catalytic properties of synthesized materials were tested under different conditions. The following parameters were varied: Al/Ni molar ratio, temperature, pressure and catalyst loading. The homogeneous catalysts were more active but less selective in ethylene oligomerization, relative to heterogeneous ones, which can be attributed to the effect of confinement suffered by catalyst within channels of the support materials. NiIL-Zeoβ complexes were active, with activities greater than 23 s−1 and selectivities higher than 80% for butenes, including more than 85% of 1-butene. On the other hand, the NiIL-MCM-41 system was less active than NiIL-Zeoβ complexes, with activities above 1 s−1 with 100% selectivity for butenes (96% in 1-butene). NiIL-Al-MCM-41 system was more active than NiIL-MCM-41 system and showed an activity of 2.3 s−1 with 90% selectivity in 1-butenes.
Global compound floods from precipitation and storm surge: Hazards and the roles of cyclones

During simultaneous or successive occurrences of precipitation and storm surges, the interplay of the two types of extremes can exacerbate the impact to a greater extent than either of them in isolation. The compound flood hazards from precipitation and storm surges vary across regions of the world because of the various weather conditions. By analyzing in-situ observations of precipitation and storm surges across the globe, we found that the return periods of compound floods with marginal values exceeding the 98.5th percentile (i.e., equivalent to a joint return period of 12 years if the marginal variables are independent) are < 2 years in most areas, while those in northern Europe are > 8 years due to weaker dependence. Our quantitative assessment shows that cyclones (i.e., tropical cyclones (TCs) and extratropical cyclones (ETCs)) are the major triggers of compound floods. More than 80% of compound floods in East Asia and > 50% of those in the Gulf of Mexico and northern Australia are associated with TCs, while in northern Europe and the higher latitude coast of North America, ETCs contribute to the majority of compound floods (i.e., 80%). Weather patterns characterized by deep low pressure, cyclonic wind, and abundant precipitable water content are conducive to the occurrence of compound floods. Extreme precipitation and extreme storm surges over Europe tend to occur in different months, which explains the relatively lower probability of compound floods in Europe. The comprehensive hazard assessment of global compound floods in this study serves as an important reference for flood risk management in coastal regions across the globe.
Contributors to social well-being from the perspective of older migrants in Australia

ABSTRACT This study investigates contributors to social well-being from the perspective of older migrants in Australia. Data were collected from semi-structured interviews with 33 participants in the 66–91-year age group, from Chinese, Vietnamese, Dutch, and German heritage backgrounds. At the time of the study, they were clients of a community service provider in Brisbane, Australia, and participated in the monthly social activities organised by the agency. Many of them also engaged in other social activities not organised by this agency. Thematic analysis of the interview transcripts identified three main contributors to participants’ social well-being: social integration through building strong connections with the ethnic community, social contribution through giving back to society, and social acceptance through assimilating into Australian society. However, the emphasis placed on these contributors was shaped by the participants’ age at migration, English language ability, and reasons for migration, as well as heritage cultural backgrounds. These findings highlight the need for tailored support to enhance social well-being among older people from diverse cultural backgrounds.
Evaluation of Mean State in NCEP Climate Forecast System (Version 2) Simulation Using a Stochastic Multicloud Model Calibrated With DYNAMO RADAR Data

Stochastic parameterizations are continuously providing promising simulations of unresolved atmospheric processes for global climate models (GCMs). One of the stochastic multi‐cloud model (SMCM) features is to mimic the life cycle of the three most common cloud types (congestus, deep, and stratiform) in tropical convective systems. To better represent organized convection in the Climate Forecast System version 2 (CFSv2), the SMCM parameterization is adopted in CFSv2 (SMCM‐CTRL) in lieu of the pre‐existing revised simplified Arakawa–Schubert (RSAS) cumulus scheme and has shown essential improvements in different large‐scale features of tropical convection. But the sensitivity of the SMCM parameterization from the observations is yet to be ascertained. Radar data during the Dynamics of the Madden‐Julian Oscillation (DYNAMO) field campaign is used to tune the SMCM in the present manuscript. The DYNAMO radar observations have been used to calibrate the SMCM using a Bayesian inference procedure to generate key time scale parameters for the transition probabilities of the underlying Markov chains of the SMCM as implemented in CFS (hereafter SMCM‐DYNAMO). SMCM‐DYNAMO improves many aspects of the mean state climate compared to RSAS, and SMCM‐CTRL. Significant improvement is noted in the rainfall probability distribution function over the global tropics. The global distribution of different types of clouds, particularly low‐level clouds, is also improved. The convective and large‐scale rainfall simulations are investigated in detail.
Aptis test review

The Aptis Testing System (O’Sullivan & Dunlea, 2015; O’Sullivan et al., 2020) is a suite of five English language proficiency tests developed by the British Council. The tests’ broad purpose is to examine the English language proficiency of English as a second or foreign language users (ESL/EFL) on the scale of the Common European Framework of Reference for Languages (CEFR) (North, 2000); however, the selection of a variant (i.e., version) or skill component allows institutions to test targeted groups of language learners or different combinations of subskills. Aptis General is the most commonly selected variant, designed to test the general English language proficiency of candidates who are 16 years of age or older, and whose English language proficiency ranges from CEFR A1 to C1 (Assessment Research Group, 2016). Institutions may also select domain-specific or proficiency-specific variants: Aptis Advanced (targeted at CEFR B1 to C2), Aptis American (standard American English), Aptis for Teens (adapted for a core age group of 13–17 years in secondary
Potential Crash Rate Benchmarks for Automated Vehicles

Most automobile manufacturers and several technology companies are testing automated vehicles (AVs) on public roads. While automation of the driving task is expected to reduce crashes, there is no consensus as to how safe an AV must be before it can be deployed. An AV should be at least as safe as the average driver, but national crash rates include drunk and distracted driving, meaning that an AV that crashes at the average rate is somewhere between drunk and sober. In this paper, safety benchmarks for AVs are explored from three perspectives. First, crash rates from naturalistic driving studies are used to determine the crash risk of the model (i.e., sober, rested, attentive, cautious) driver. Second, stated preference surveys in the literature are reviewed to estimate the AV risk acceptable to the public. Third, crash, injury, and fatality rates from other transportation modes are compared as baseline safety levels. A range of potential safety targets is presented as a guide for policymakers, regulators, and AV developers to assist in evaluating the safety of automated driving technologies for public use.
Osteoblasts-derived Exosomes as Novel Communicators in Particle Induced Periprosthetic Osteolysis

BackgroundThe inflammatory response to titanium implant-derived wear particles is considered as the hallmark of periprosthetic osteolysis, an event that cause pain, reduce patient motility, ultimately leading to the need of a revision surgery. Although macrophages are major cell players, other cell types such as bone cells can indirectly contribute to periprosthetic osteolysis, however the mechanisms are not fully understood. Exosomes (Exos) has been related with several bone pathologies, with growing body of literature recognizing them as actively shuttle molecules through the body, with their cargo being completely dependent of external stimuli (e.g. chemicals and metals ions and particles). Till the moment, the role of wear debris on osteoblasts exosomes biogenesis is absent and the possible contribution of Exos to osteoimmune communication and periprosthetic osteolysis is still in its infancy. Taking that in consideration, in this work we investigate the effect of wear debris on Exo biogenesis, where two bone cell models were exposed to titanium dioxide nanoparticles (TiO2 NPs) similar in size and composition to wear debris associated with prosthetic implants. The contribution of Exos to periprosthetic osteolysis was evaluated performing functional tests stimulating primary human macrophages with bone-derived Exos.ResultsFor the first time, we report that TiO2 NPs enter in multivesicular bodies, the nascent of Exos and altered osteoblasts derived exosomes secretion and cargo. No significant differences were observed in Exos morphology and size, however mass spectrometry analysis identified urokinase-type plasminogen activator (uPA), specifically enriched in Exos derived from bone cells pre-incubated with TiO2 NPs. Functional tests confirmed the activation of human macrophages towards a mixed phenotype with consequent secretion of pro and anti-inflammatory cytokines. ConclusionsThe external stimuli of osteoblasts to TiO2 NPs induced a dose dependent secretion of Exos, suggesting alterations in their biogenesis as well as in their cargo. Functional tests reveal that enriched uPA exosomal cargo is stimulating macrophages towards a mixed M1 and M2 phenotype inducing the release of pro-and anti-inflammatory signals that are characteristic of periprosthetic osteolysis. Interestingly, uPA may be proposed, in the future, as a possible candidate biomarker to early diagnose particle induced periprosthetic osteolysis, since uPA was also detected in the pseudocapsular interface around implants of patients with loosening of total hip prosthesis and joint replacement surgery, suggesting their active role in disease progression.
Limits on Diffuse Dark Matter with HAWC

In addition to dense regions of dark matter, such as galaxy clusters and dwarf galaxies, dark matter annihilation and decay are also expected to have a nearly isotropic distribution across the sky. This isotropic component is less model-dependent than the flux from isolated dark matter targets, and would produce galactic contributions to the Diffuse Gamma-Ray Background (DGRB). With its continuous monitoring of the gamma-ray sky from a few hundred GeV to several hundred TeV and its wide field-of-view, the High AltitudeWater Cherenkov (HAWC) observatory is well-suited to search for dark matter contributions in the DGRB. In this work, 535 days of HAWC data and Monte Carlo simulations were studied to set limits on annihilating or decaying diffuse dark matter at TeV energies. With this data, we consider both leptonic and hadronic dark matter channels and are able to constrain dark matter up to masses >100 TeV.
Selective Noncatalytic Reduction of NOx Using Ammonium Sulfate

Ammonium sulfate (AS) is of interest as an additive in stationary combustion plants for the simultaneous control of NO x (through selective non-catalytic reduction, SNCR) and deposition and corrosion (through sulfation of alkali chlorides). The SNCR performance of ammonium sulfate was evaluated through experiments in a laboratory-scale (cid:29)ow reactor. Experiments with 5 and 10 wt. % aqueous ammonium sulfate solutions, corresponding to AS/NO ratios above one, yielded NO reductions up to 95% in a temperature interval of 1025 to 1075 o C. The results indicated that sulfur from ammonium sulfate is mainly released as SO 3 , even though SO 2 is detected in increasing concentrations at temperatures above 1000 o C. Addition of KCl to the SNCR process was shown to promote reaction at lower temperatures,
Distributed Adaptive Subgradient Algorithms for Online Learning Over Time-Varying Networks

Adaptive gradient algorithms have recently become extremely popular because they have been applied successfully in training deep neural networks, such as Adam, AMSGrad, and AdaBound. Despite their success, however, the distributed variant of the adaptive method, which is expected to possess a rapid training speed at the beginning and a good generalization capacity at the end, is rarely studied. To fill the gap, a distributed adaptive subgradient algorithm is presented, called D-AdaBound, where the learning rates are dynamically bounded by clipping the learning rates. Moreover, we obtain the regret bound of D-AdaBound, in which the objective functions are convex. Finally, we confirm the effectiveness of D-AdaBound by simulation experiments on different datasets. The results show the performance improvement of D-AdaBound relative to existing distributed online learning algorithms.
Unmanned Aerial Vehicle with Thermal Imaging for Automating Water Status in Vineyard

Thermal imaging is utilized as a technique in agricultural crop water management due to its efficiency in estimating canopy surface temperature and the ability to predict crop water levels. Thermal imaging was considered as a beneficial integration in Unmanned Aerial Vehicle (UAV) for agricultural and civil engineering purposes with the reduced weight of thermal imaging systems and increased resolution. When implemented on-site, this technique was able to address a number of difficulties, including estimation of water in the plant in farms or fields, while considering officially induced variability or naturally existing water level. The proposed effort aims to determine the amount of water content in a vineyard using the high-resolution thermal imaging. This research work has developed an unmanned aerial vehicle (UAV) that is particularly intended to display high-resolution images. This approach will be able to generate crop water stress index (CWSI) by utilizing a thermal imaging system on a clear-sky day. The measured values were compared to the estimated stomatal conductance (sg) and stem water (s) potential along the Vineyard at the same time. To evaluate the performance of the proposed work, special modelling approach was used to identify the pattern of variation in water level. Based on the observation, it was concluded that both ‘sg’ and ‘s’ value have correlated well with the CWSI value by indicating a great potential to monitor instantaneous changes in water level. However, based on seasonal changes in water status, it was discovered that the recorded thermal images did not correspond to seasonal variations in water status.