Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Distributed Hydrological Analysis Tool for Future Climate Change Impacts Assessment of South Korea

The purpose of this paper is to develop a software tool, PGA-CC (Projection of hydrology via Grid-based Assessment for Climate Change) to evaluate the present hydrologic cycle and the future watershed hydrology by climate change. PGA-CC is composed of grid-based input data pre-processing module, hydrologic cycle calculation module, output analysis module, and output data post-processing module. The grid-based hydrological model was coded by Fortran and compiled using Compaq Fortran 6.6c, and the Graphic User Interface was developed by using Visual C#. Other most elements viz. Table and Graph, and GIS functions were implemented by MapWindow. The applicability of PGA-CC was tested by assessing the future hydrology of South Korea by HadCM3 SRES B1 and A2 climate change scenarios. For the whole country, the tool successfully assessed the future hydrological components including input data and evapotranspiration, soil moisture, surface runoff, lateral flow, base flow etc. From the spatial outputs, we could understand the hydrological changes both seasonally and regionally.
Reduction of location error in GPS collar tracking data of bovine cattle by using data screening

Global Positioning System (GPS) telemetry enables tracking of an individual animal over a long period of time and can provide researches with accurate information on animal movement. However, various environmental factors infl uence the satellite signals received by a GPS collar, potentially deteriorating accuracy of position. We tracked Caprivi Sanga cattle using Televilt Tellus Basic GPS collars in North-East Namibia in 2006 and 2007. Locations obtained during the night, when the cattle are gathered inside livestock enclosures, revealed that a signifi cant proportion of the locations are inaccurate. We used data of seven GPS collars for testing diff erent data screening options as a way to reduce location error. Basic analysis showed that simple measures of accuracy like dilution of precision (DOP) and fi gure of merit (FOM) are not suffi cient to remove erroneous locations from the data. We removed the inaccurate locations with the following condition: 2D location with DOP >6 or 0 1050 m or DOP ≥10 or FOM ≥10 or walking speed of the animal over 4.5 km/h. This data screening option eliminated 75% of the most erroneous locations (>300 m from the livestock enclosures) retaining 97.2% of the locations correctly located inside the livestock enclosures. Before data screening, 95% (1372) of the night-time locations that were located outside the livestock enclosures were located 71-406 m from the enclosures. The maximum error was over 10 km. After data screening, 95% (485) of the locations were 54-298 m from the enclosures; the maximum error was 4.4 km.
Age and provenance of basement metasediments from the Kubor and Bena Bena Blocks, central Highlands, Papua New Guinea: Constraints on the tectonic evolution of the northern Australian cratonic margin

Detrital zircon from two basement blocks (Kubor and Bena Bena) in the central Highlands of Papua New Guinea has an age signature that strongly suggests a northern Australian provenance. Samples of the Omung Metamorphics, southeastern Kubor Block, together yield principal zircon populations with ages of ca 1.8 Ga (∼10% of the total), ca 1.55 Ga (∼10%), 470–440 Ma (∼15%), ca 340 Ma (∼10%) and 290–260 Ma (∼40%). Two tonalite stocks of the Kubor Intrusive Complex, which intrude the Omung Metamorphics, yield indistinguishable ages of 244.8 ± 4.9 Ma and 239.1 ± 4.2 Ma.Therefore, the deposition and subsequent deformation of the Omung Metamorphics is Late Permian to Early Triassic. A sample of Goroka Formation (Bena Bena Block) contains detrital zircon of similar ages to the Omung Metamorphics, ca 1.8 Ga (5%), ca 1.55 Ga (∼45%), ca 430 Ma (∼5%) and ca 310 Ma (∼40%), suggesting that the Goroka Formation has a similar provenance and might be correlative. In contrast, a metapsammite from the Bena Bena Formation yielded only ages of 290–280 Ma (85%) and ca 240 Ma (15%). A tuff interbedded in the Bena Bena Formation yielded only igneous zircon with a Late Triassic age of 221 ± 3 Ma. Contrary to previous interpretations, the Bena Bena Formation is probably younger than the Goroka Formation. Ages of New Guinea detrital zircon closely match those of igneous and detrital zircon from the Coen Inlier, northeastern Queensland, but contrast with the ages of zircon from terranes further south, east and west. The Kubor and Bena Bena Blocks are not suspect terranes, but rather form part of the Australian craton. The craton margin, modified by rifting during the Mesozoic, was re‐inverted during Cenozoic compression. The Australian craton, in the eastern Highlands of Papua New Guinea, extends at least as far north as the Markham Valley, the northern edge of the Bena Bena terrane.
Refinamento estatístico das previsões horárias de temperatura a 2 m do modelo eta em estações do nordeste do Brasil

Statistical downscaling of 2 m air temperature forecasts from the Eta Model at 40 km resolution were carried out for 7 sites located in Northeast Brazil. The downscaling method was the Model Output Calibration (MOC), which is based on the linear regression between the forecast error and model output variables. One feature of the scheme is the use of short training period, in this work only 28 days was the chosen period. The model output variables with correlation higher than 0.6 were selected as predictors of the regression equation. The scheme was tested for one-month hourly forecasts in September 2003. Model systematic errors were strongly reduced to values below |0.5| °C on average. The root mean square errors, which initially were of the order of 2 °C, were reduced to about 1 °C. The linear correlation between the observations and Eta forecasts were generally kept the same after applying the downscaling scheme. Temperature forecasts with greatest errors in the amplitude of the diurnal cycle were corrected accordingly.
The REEP5/TRAM1 complex binds SARS-CoV-2 NSP3 and promotes virus replication

ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), like other coronaviruses, replicates their genome in virus-induced cytosolic membrane-bound replication organelles (ROs). SARS-CoV-2 promotes the biogenesis of ROs by inducing the rearrangement of endoplasmic reticulum (ER) membranes. NSP3, NSP4, and NSP6 are transmembrane viral non-structural proteins (NSPs) and essential players in the formation of ROs. To understand how these three NSPs work synergistically with host-binding proteins, we performed affinity purifications followed by mass spectrometry analyses to study the host-viral protein-protein interactome of NSP3, NSP4, and NSP6 expressed individually and in combination. Through this analysis, we identified two host transmembrane proteins, REEP5 and TRAM1, as critical interacting partners of NSP3 that localize at the membrane of the RO. REEP5 interacts with TRAM1 endogenously and binds NSP3 during SARS-CoV-2 infection. REEP5 knockout reduces ER membrane rearrangements and inhibits SARS-CoV-2 replication. Collectively, our study shows that the host REEP5/TRAM1 complex binds NSP3, promoting RO biogenesis and viral replication. IMPORTANCE Generation of virus-host protein–protein interactions (PPIs) maps may provide clues to uncover SARS-CoV-2-hijacked cellular processes. However, these PPIs maps were created by expressing each viral protein singularly, which does not reflect the life situation in which certain viral proteins synergistically interact with host proteins. Our results reveal the host-viral protein-protein interactome of SARS-CoV-2 NSP3, NSP4, and NSP6 expressed individually or in combination. Furthermore, REEP5/TRAM1 complex interacts with NSP3 at ROs and promotes viral replication. The significance of our research is identifying virus-host interactions that may be targeted for therapeutic intervention. Generation of virus-host protein–protein interactions (PPIs) maps may provide clues to uncover SARS-CoV-2-hijacked cellular processes. However, these PPIs maps were created by expressing each viral protein singularly, which does not reflect the life situation in which certain viral proteins synergistically interact with host proteins. Our results reveal the host-viral protein-protein interactome of SARS-CoV-2 NSP3, NSP4, and NSP6 expressed individually or in combination. Furthermore, REEP5/TRAM1 complex interacts with NSP3 at ROs and promotes viral replication. The significance of our research is identifying virus-host interactions that may be targeted for therapeutic intervention.
Cloud effects from boreal forest fire smoke: evidence for ice nucleation from polarization lidar data and cloud model simulations

Polarization lidar observations from the interior of Alaska have revealed unusual supercooled altocumulus cloud conditions in the presence of boreal forest fire smoke from local and regional fires. At temperatures of about −15 °C, the lidar data show ice nucleation prior to liquid cloud formation (i.e. below water saturation), as well as the occasional glaciation of the liquid layer. Thus the smoke aerosol appears to act as ice nuclei that become activated in updrafts before the liquid cloud forms, as the concentrated aqueous organic solutions are diluted sufficiently to allow them to freeze heterogeneously. This haze particle freezing process is similar to the production of cirrus ice crystals homogeneously at much colder temperatures. To test this hypothesis, cloud microphysical model simulations constrained by the measurements were performed. They indicate that this heterogeneous ice nucleation scenario can be supported by the cloud model. Although ice formation in this manner may generally act in the atmosphere, the boreal smoke particles produce an unusually dramatic effect in the lidar data. We conclude that smoke-induced ice nucleation occurs at moderate supercooled temperatures either through the effects of raised soil/dust particles embedded in the smoke droplets, coated soot aerosol or through the nucleation via certain organic solutions.
Optimized Artificial Intelligence Model for DDoS Detection in SDN Environment

Distributed denial of service (DDoS) attacks continue to be a major security concern, threatening the availability and reliability of network services. Software-defined networking (SDN) has emerged as a promising solution to address this issue, enabling centralized network control and management. However, conventional SDN-based DDoS mitigation techniques often struggle to detect and mitigate sophisticated attacks due to their limited ability to analyze complex traffic patterns. This paper proposes an innovative and optimized approach that effectively combines mininet, Ryu controller, and one dimensional-convolutional neural network (1D-CNN) to detect and mitigate DDoS attacks in SDN environments. The proposed approach involves training the 1D-CNN model with labeled network traffic data to effectively identify abnormal patterns associated with DDoS attacks. Furthermore, seven hyperparameters of the trained 1D-CNN model were tuned using non-dominated sorting genetic algorithm II (NSGA-II) to achieve the best accuracy with minimum training time. Once the optimized 1D-CNN model detects an attack, the Ryu controller dynamically adapts the network policies and employs appropriate mitigation techniques to protect the network infrastructure. To evaluate the effectiveness of the optimized 1D-CNN model, extensive experiments were conducted using a simulated SDN environment with a realistic DDoS attack dataset. The experimental results demonstrate that the developed approach achieves significantly improved detection accuracy of 99.99% compared to other machine learning (ML) models. The NSGA-II enhances the optimized model accuracy with an improvement rate of 9.5%, 8%, 5.4%, and 2.6% when it is compared to logistic regression (LR), random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) optimized models respectively. This research paves the way for future developments in leveraging deep learning (DL) driven techniques and SDN architectures to address evolving cybersecurity challenges.
In situ LA-ICPMS U-Pb dating of detrital zircons from the Cercadinho Formation, Minas Supergroup.

In this paper, new geochronological data obtained for the detrital rocks of the Cercadinho Formation, basal unit of the Piracicaba Group, Minas Supergroup, are presented. U-Pb Laser Ablation Induced Coupled Mass Spectrometer (LA-ICPMS) analysis in detrital zircon from quartzite samples provided a new maximum depositional age for the Cercadinho Formation. The youngest zircon population, among the dated samples, provided an average age of 2680 ± 24 Ma. These rocks have an expressive contribution of Meso- to Neoarchean zircons, with ages between 2812 ± 19 and 2909 ± 19 Ma, and older populations between 3212 ± 18 and 3272 ± 16 Ma, which occur mainly in the core of younger zircon grains. Comparing the U-Pb ages obtained in this work with previously published geochronological data for the basal units of the Minas Supergroup (Moeda Formation) an aging of the source for the detrital rocks of Cercadinho Formation can be observed, with a major contribution of zircons from TTG rocks crystallized between the Meso- and Neoarchean.
Nitrogen Journey in Plants: From Uptake to Metabolism, Stress Response, and Microbe Interaction

Plants uptake and assimilate nitrogen from the soil in the form of nitrate, ammonium ions, and available amino acids from organic sources. Plant nitrate and ammonium transporters are responsible for nitrate and ammonium translocation from the soil into the roots. The unique structure of these transporters determines the specificity of each transporter, and structural analyses reveal the mechanisms by which these transporters function. Following absorption, the nitrogen metabolism pathway incorporates the nitrogen into organic compounds via glutamine synthetase and glutamate synthase that convert ammonium ions into glutamine and glutamate. Different isoforms of glutamine synthetase and glutamate synthase exist, enabling plants to fine-tune nitrogen metabolism based on environmental cues. Under stressful conditions, nitric oxide has been found to enhance plant survival under drought stress. Furthermore, the interaction between salinity stress and nitrogen availability in plants has been studied, with nitric oxide identified as a potential mediator of responses to salt stress. Conversely, excessive use of nitrate fertilizers can lead to health and environmental issues. Therefore, alternative strategies, such as establishing nitrogen fixation in plants through diazotrophic microbiota, have been explored to reduce reliance on synthetic fertilizers. Ultimately, genomics can identify new genes related to nitrogen fixation, which could be harnessed to improve plant productivity.
ExtSpecR: An R Package and Tool for Extracting Tree Spectra from UAV-Based Remote Sensing

The development of unmanned aerial vehicle (UAV) remote sensing has been increasingly applied in forestry for high-throughput and rapid acquisition of tree phenomics traits for various research areas. However, the detection of individual trees and the extraction of their spectral data remain a challenge, often requiring manual annotation. Although several software-based solutions have been developed, they are far from being widely adopted. This paper presents ExtSpecR, an open-source tool for spectral extraction of a single tree in forestry with an easy-to-use interactive web application. ExtSpecR reduces the time required for single tree detection and annotation and simplifies the entire process of spectral and spatial feature extraction from UAV-based imagery. In addition, ExtSpecR provides several functionalities with interactive dashboards that allow users to maximize the quality of information extracted from UAV data. ExtSpecR can promote the practical use of UAV remote sensing data among forest ecology and tree breeding researchers and help them to further understand the relationships between tree growth and its physiological traits.
Role of the Microbiota in Skin Neoplasms: New Therapeutic Horizons

The skin and the gut are regularly colonized by a variety of microorganisms capable of interacting with the immune system through their metabolites and influencing the balance between immune tolerance and inflammation. Alterations in the composition and diversity of the skin microbiota have been described in various cutaneous diseases, including skin cancer, and the actual function of the human microbiota in skin carcinogenesis, such as in progression and metastasis, is currently an active area of research. The role of Human Papilloma Virus (HPV) in the pathogenesis of squamous cell carcinoma is well consolidated, especially in chronically immunosuppressed patients. Furthermore, an imbalance between Staphylococcus spp. , such as Staphylococcus epidermidis and aureus, has been found to be strongly related to the progression from actinic keratosis to squamous cell carcinoma and differently associated with various stages of the diseases in cutaneous T-cell lymphoma patients. Also, in melanoma patients, differences in microbiota have been related to dissimilar disease course and prognosis and may affect the effectiveness and tolerability of immune checkpoint inhibitors, which currently represent one of the best chances of a cure. From this point of view, acting on microbiota can be considered a possible therapeutic option for patients with advanced skin cancers, even if several issues are still open.
Physicochemical properties and microbial qualities of honey produced by a stingless bee (Meliponula beccarii L.) in the Oromia region, Ethiopia

Abstract This study is aimed at determining the physicochemical and microbiological quality of stingless bee honey (Meliponula beccarii) collected in potential areas in the Oromia region of Ethiopia. Thirty-nine honey samples from underground soils were collected. The findings of the investigation indicated that the mean values of physicochemical properties for stingless bee honey samples were: moisture content (30.69 ± 0.29%), pH value (3.30 ± 0.03), free acidity (92.39 ± 4.45 meq/kg), ash content (0.16 ± 0.01%), electrical conductivity (0.44 ± 0.2 mS/cm), HMF (6.58 ± 0.36 mg/kg), fructose (36.48 ± 0.54%), glucose (27.67 ± 0.43%), reducing sugar (64.15 ± 0.75%) sucrose (1.24 ± 0.18%) and maltose content (1.2 ± 0.18%). The honey sample studied from Meliponulla beccarii was mostly characterized as having a light amber color (50%). Honey produced by stingless bees is distinguished from Apis mellifera honey by having a lower level of sugar, a higher amount of moisture, and free acidity. There were 2.55 × 104 to 1.9 × 103 CFU/mL of Aerobic Mesophiles, 1.68 × 104 to 9 × 102 CFU/mL of yeast, and 1.8 × 103 to 2 × 102 CFU/mL of mold in the Meliponulla beccarii honey sample. Staphylococcus species could only be detected in a sample taken from the Guduru area; however, an aerobic spore-forming bacteria was undetectable in all stingless bee samples. This suggested that there may have been cross-contamination from primary and secondary sources during pre-harvesting and post-harvest handling. Specific quality specifications must be established to promote commercialization since the physicochemical and microbiological characteristics of stingless bee honey differ from those of A. mellifera.
Application Of BASINS/HSPF In TheKoycegiz–Dalyan Watershed In Turkey:A Developing Country Case Study InWatershed Modeling

A dynamic simulation model, HSPF (Hydrological Simulation ProgramFORTRAN), is used for the simulation of hydrology and diffuse pollution in the Namnam sub basin of Koycegiz-Dalyan watershed in Turkey using a minimum amount of data required for model application. The resulting correlation coefficients for the mean daily and monthly flows for the Namnam stream were found to be 0.634 and 0.847 for calibration, and 0.761 and 0.843 for validation, respectively, using the Expert System for the calibration of HSPF (HSPEXP). HSPEXP criteria for calibration of HSPF based on the comparison of statistics between simulated and observed flows varied from fair to very good, except for the summer flow volume and total of the lowest 50% flows. Sediment, nitrate-N, orthophosphate-P, and BOD loads were determined for different land uses in the Namnam watershed. Agricultural activity was identified as the major source of sediments, and pastures with livestock grazing produced the highest NPS fluxes. The results emphasize the importance of advanced modeling tools even in the absence of high quality, continuous and consistent data.
Impact of Isopycnal Diffusion on Heat Fluxes and the Transient Response of a Two-Dimensional Ocean Model

Abstract A two-dimensional (latitude–depth) ocean–climate model is used to assess the impact of calculating diffusive heat and salinity fluxes along and across isopycnal surfaces rather than in a vertical–horizontal coordinate system. Differences between the two model versions are small and are overwhelmed by uncertainties in the appropriate value of the diapycnal/vertical diffusion coefficient Kv. Isopycnal diffusion is important only if convection is not explicitly included and Kv is fixed rather than parameterized as N−1 (where N is the Brunt–Vaisala frequency). When convection is present, the switch to diffusion in isopycnal coordinates causes large changes in the convective heat flux that are largely offset by diffusion along isopycnal surfaces, with little change in the diapycnal heat flux. The effective vertical diffusion coefficient due to combined mixing across and along isopycnal surfaces is negative in some regions due to upward heat diffusion along sloping isopycnal surfaces combined with temp.
Leaf area index of boreal forests: theory, techniques, and measurements

Leaf area index (LAI) is a key structural characteristic of forest ecosystems because of the role of green leaves in controlling many biological and physical processes in plant canopies. Accurate LAI estimates are required in studies of ecophysiology, atmosphere-ecosystem interactions, and global change. The objective of this paper is to evaluate LAI values obtained by several research teams using different methods for a broad spectrum of boreal forest types in support of the international Boreal Ecosystem-Atmosphere Study (BOREAS). These methods include destructive sampling and optical instruments: the tracing radiation and architecture of canopies (TRAC), the LAI-2000 plant canopy analyzer, hemispherical photography, and the Sunfleck Ceptometer. The latter three calculate LAI from measured radiation transmittance (gap fraction) using inversion models that assume a random spatial distribution of leaves. It is shown that these instruments underestimate LAI of boreal forest stands where the foliage is clumped. The TRAC quantifies the clumping effect by measuring the canopy gap size distribution. For deciduous stands the clumping index measured from TRAC includes the clumping effect at all scales, but for conifer stands it only resolves the clumping effect at scales larger than the shoot (the basic collection of needles). To determine foliage clumping within conifer shoots, a video camera and rotational light table system was used. The major difficulties in determining the surface area of small conifer needles have been largely overcome by the use of an accurate volume displacement method. Hemispherical photography has the advantage that it also provides a permanent image record of the canopies. Typically, LAI falls in the range from 1 to 4 for jack pine and aspen forests and from 1 to 6 for black spruce. Our comparative studies provide the most comprehensive set of LAI estimates available for boreal forests and demonstrate that optical techniques, combined with limited direct foliage sampling, can be used to obtain quick and accurate LAI measurements.