Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing global dataset of salt pans and salt playas using Landsat-8 imagery: a case study of western North America

Monitoring salt pans is important especially for agricultural management in arid or semiarid regions because salt pans can negatively affect human life, wildlife, and ecology. Some of the harmful impacts of salt pans are accelerated desertification, cropland loss, economic downturn, wildlife loss, and forced migration of humans and animals due to salt storms. Spectral salt pan indices based upon remotely sensed data (using spectral properties of Landsat-8 imagery) suggested in previous studies vary by location. In other words, the spectral configuration of a salt index for a given location may not be readily applicable to another location due to spatial heterogeneity of salt components across the continental surface. Using Landsat-8 OLI imagery and climate data sets, this study aims to develop a mapping framework which can effectively extract salt pans and salt playas under various spectral conditions in different geographic locations. Based on training samples selected in eight major salt pans/playas in North America, Central Asia, Africa, and Australia, the mapping framework was designed to include the following steps: i) a conservative salt index to highlight potential salt-covered regions, ii) a calibrated support vector machine (SVM) to extract high-salinity areas in the mask regions, and iii) a posterior quality assurance/ quality control (QA/QC) with assistance of auxiliary datasets (e.g., surface slope and land covers) to eliminate commission errors and refine the extracted saltpan areas. The developed mapping framework was validated in the arid endorheic regions across the western United States, with a total area of 699 thousand square kilometers. Both qualitative and quantitative assessments of the results show reliability of the developed framework. The overall accuracy of the extracted salt pans prior to QA/QC is 97%. The final product after QA/QC achieves an overall accuracy of 99.95% and a Kappa statistic of 0.99. According to the results of salt pans areas and endorheic basins areas, it can be concluded that two aforementioned variables of this study are positively correlated to each other, and 1.10 percent of the entire case study area is covered by salt pans. The accuracy of the results suggests a potential that the mapping framework, together with the collected training sample and algorithms, may be applicable to identify salt pan and salt playa regions across the Earth’s land surface.
The Effect Of Land Fragmentation On Farm Performance: A Comprehensive Farm-Level Study From Denmark

This paper analyses the effect of land fragmentation on the performance of Danish farms based on a cross-sectional farm-level data set from 2014. Our measures of land fragmentation indicate the size and shape of the feild as well as inter feild distances and distances between farm buildings and feilds. Fragmented land is expected to increase costs and reduce production and, thus, decrease the performance of farms. Preliminary results based on two methodological approaches both indicate no statistically signifcant effect of the shape of the feils, while smaller feild sizes and longer distances signifcantly reduce performance.
Evaluation of the Inductive Coupling between Coplanar Concentric Coils in the Presence of the Ground

An analytical approach is presented that allows deriving an exact series-form representation for the flux linkage between two physically large concentric circular coils located on a lossy soil. The expression comes from a three-step analytical procedure. First, the integral expression for the flux linkage is converted into a double integral consisting of a finite and a semi-infinite integral. Next, the semi-infinite integral is recognized to be a well-known tabulated Sommerfeld integral, which may be analytically evaluated straightforwardly. Finally, applying Lommel’s expansion allows rewriting the remaining finite integral as a sum of elementary integrals amenable to analytical evaluation. As a result, the flux linkage between the two coils is given as a sum of spherical Hankel functions of the wavenumber in the air and in the ground, multiplied by a coefficient depending on the geometrical dimensions of the coils. The accuracy and robustness of the proposed formulation is tested by comparing its outcomes with those generated by numerical integration of the complete integral representation for the flux linkage and with the results provided by previous analytical approaches to the same problem. It is found that the use of the derived expression for the inductance makes it possible to obtain significant time savings as compared to numerical quadrature schemes.
Adding new evidence to the attribution puzzle of the recent water shortage over São Paulo (Brazil)

Abstract São Paulo, Brazil has experienced severe water shortages and record low levels of its water reservoirs in 2013–2014. We evaluate the contributions of Amazon deforestation and climate change to low precipitation levels using a modelling approach, and address whether similar precipitation anomalies might occur more frequently in a warming world. Precipitation records from INMET show that the dry anomaly extended over a fairly large region to the north of São Paulo. Unique features of this event were anomalous sea surface temperature (SST) patterns in the Southern Atlantic, an extension of the sub tropical high into the São Paulo region and moisture flux divergence over São Paulo. The SST anomalies were very similar in 2013/14 and 2014/15, suggesting they played a major role in forcing the dry conditions. The SST anomalies consisted of three zonal bands: a cold band in the tropics, a warm band to the south of São Paulo and another cold band poleward of 40 S. We performed ensemble climate simulations with observed SSTs prescribed, vegetation cover either fixed at 1870 levels or varying over time, and greenhouse gases (GHGs) either fixed at pre-industrial levels (280 ppm CO2) or varying over time. These simulations exhibit similar precipitation deficits over the São Paulo region in 2013/14. From this, we infer that SST patterns and the associated large-scale state of the atmosphere were important factors in determining the precipitation anomalies, while deforestation and increased GHGs only weakly modulated the signal. Finally, analyses of future climate simulations from CMIP5 models indicate that the frequency of such precipitation anomalies is not likely to change in a warmer climate.
Molecular Basis for the Involvement of Mammalian Serum Albumin in the AGE/RAGE Axis: A Comprehensive Computational Study

In mammals, glycated serum albumin (gSA) contributes to the pathogenesis of many metabolic diseases by activating the receptors (RAGE) for advanced glycation end products (AGEs). Many aspects of the gSA–RAGE interaction remain unknown. The purpose of the present paper was to study the interaction of glycated human albumin (gHSA) with RAGE using molecular modeling methods. Ten models of gHSA modified with different lysine residues to carboxymethyl-lysines were prepared. Complexes of gHSA–RAGE were obtained by the macromolecular docking method with subsequent molecular dynamics simulation (MD). According to the MD, the RAGE complexes with gHSA glycated at Lys233, Lys64, Lys525, Lys262 and Lys378 are the strongest. Three-dimensional models of the RAGE dimers with gHSA were proposed. Additional computational experiments showed that the binding of fatty acids (FAs) to HSA does not affect the ability of Lys525 (the most reactive lysine) to be glycated. In contrast, modification of Lys525 reduces the affinity of albumin for FA. The interspecies differences in the molecular structure of albumin that may affect the mechanism of the gSA–RAGE interaction were discussed. The obtained results will help us to learn more about the molecular basis for the involvement of serum albumin in the AGE/RAGE axis and improve the methodology for studying cellular signaling pathways involving RAGE.
Inter event times of fluid induced earthquakes suggest their Poisson nature

We analyze the inter event time distribution of fluid‐injection‐induced earthquakes for six catalogs collected at geothermal injection sites at Soultz‐sous‐Forêts and Basel. We find that the distribution of waiting times during phases of constant seismicity rate coincides with the exponential distribution of the homogeneous Poisson process (HPP). We analyze the waiting times for the complete event catalogs and find that, as for naturally occurring earthquakes, injection induced earthquakes are distributed according to a non homogeneous Poisson process in time. Moreover, the process of event occurrence in the injection volume domain is a HPP. These results indicate that fluid‐injection‐induced earthquakes are directly triggered by the loading induced by the fluid injection. We also consider the spatial distance between events and perform a nearest neighbor analysis in the time‐space‐magnitude domain. Our analysis including a comparison to a synthetic catalog created according to the ETAS model reveals no signs of causal relationships between events. Therefore, coupling effects between events are very weak. The Poisson model seems to be a very good approximation of fluid induced seismicity.
The High Rates of Comorbidity among Neurodevelopmental Disorders: Reconsidering the Clinical Utility of Distinct Diagnostic Categories

The boundaries between neurodevelopmental disorders are often indistinct, even among specialists. But do these boundaries exist, or do experts struggle to distinguish and categorize symptoms in order to arrive at a dominant diagnosis while comorbidity continually leaves questions about where each disorder ends and begins? What should be reconsidered? The introduction of the term ‘spectrum of neurodevelopmental disorders’ could pave the way for a re-appraisal of the clinical continuum of neurodevelopmental disorders. This study aims to highlight the problems that emerge in the field of the differential diagnosis of neurodevelopmental disorders and propose a renegotiation of the distinctiveness criteria.
NEURAL NETWORK-BASED ADVERSE DRUG REACTION PREDICTION USING MOLECULAR SUBSTRUCTURE ANALYSES

Objective: This study aims to enhance early detection and prediction by exploiting drug molecular substructures, overcoming challenges posed by limited authentic patient data in the medical domain. Methods: The study implemented a neural network approach to optimize molecular fingerprint algorithms and employed various machine learning algorithms for predictions. Additionally, the study identified and extracted substructures associated with severe Adverse Drug Reactions (ADRs), validating their presence within drug structures through a comparison with a random set of drug structures. Predictions were made for specific molecular structures, and results were validated using clinical evidence from the literature. Results: Optimized molecular fingerprint algorithms and diverse machine-learning models yielded promising outcomes. The Area Under Curve (AUC) value for the fingerprint dataset was obtained at approximately 65%, and integrating it with patient data significantly improved the performance by about 30%. Substructure analysis pinpointed key components linked to severe ADRs, reinforcing the predictive prowess of the model. Predictions for specific molecular structures were corroborated using clinical evidence from the literature, fortifying the credibility of the proposed approach. Conclusion: In conclusion, this research effectively tackles challenges in the early detection and prediction of ADRs by leveraging machine learning algorithms, focusing on drug molecular substructures. The optimized model, incorporating both fingerprint and patient datasets, demonstrated significant improvements in predictive performance. Identifying and validating substructures linked to severe ADRs contribute to the model's reliability. The study's findings are vital for advancing drug safety and laying the groundwork for further strides in predictive modeling within the medical domain.
Socio-Cultural Potential for Low Delivery Assistance by Nakes in Working Area of the Bibida Health Center, Paniai Regency, Central Papua

One method that can reduce maternal and newborn mortality rates is delivery carried out by health workers. Most maternal and newborn complications and deaths occur during the labor period. This happens because the assistance is provided by health workers who do not have midwifery (professional) competence. This study aims to identify factors that contribute to the low level of delivery assistance by health workers in the Bibida Community Health Center working area. In 2021, 56.3 percent of births will be assisted by health workers, and 32% will be at the Bibida Community Health Center. Quantitative research was conducted using a cross-sectional analytical design. The research was conducted in the Bibida Community Health Center working area in Paniai Regency, Central Papua, from October 2023 to November 2023. This research involved all mothers who had just given birth who were in the Bibida Community Health Center working area during July, August and September. The total population technique was used to collect 35 samples. Use of computerization to process univariate and bivariate data. Research resultdelivery assistance by non-health workers 62.9% andculture does not support 51.4%. With p value=0.000, the results of statistical analysis show that there is a socio-cultural relationship. It is recommended that pregnant women give birth at health workers and in health facilities. In addition, it is important for midwives to work together with local community leaders and related sectors in encouraging people to give birth with health workers.
Traffic engineering and quality of service in hybrid software defined networks

For Future networks, many research projects have proposed different architectures around the globe; Software Defined Network (SDN) architectures, through separating Data and Control Layers, offer a crucial structure for it. With a worldwide view and centralized Control, the SDN network provides flexible and reliable network management that improves network throughput and increases link utilization. In addition, it supports an innovative flow scheduling system to help advance Traffic Engineering (TE). For Medium and large-scale networks migrating directly from a legacy network to an SDN Network seems more complicated & even impossible, as there are High potential challenges, including technical, financial, security, shortage of standards, and quality of service degradation challenges. These challenges cause the birth and pave the ground for Hybrid SDN networks, where SDN devices coexist with traditional network devices. This study explores a Hybrid SDN network's Traffic Engineering and Quality of Services Issues. Quality of service is described by network characteristics such as latency, jitter, loss, bandwidth, and network link utilization, using industry standards and mechanisms in a Hybrid SDN Network. We have organized the related studies in a way that the Quality of Service may gain the most benefit from the concept of Hybrid SDN networks using different algorithms and mechanisms: Deep Reinforcement Learning (DRL), Heuristic algorithm, K path partition algorithm, Genetic algorithm, SOTE algorithm, ROAR method, and Routing Optimization with different optimization mechanisms that help to ensure high-quality performance in a Hybrid SDN Network.
A Vibration Compensation Method for Pavement Depth Data Based on LightGBM with Bayesian Optimization

To salve the issue of local distortion and feature distortion caused by vibration during the data acquisition process of 3D pavement detection vehicles, this research proposed a Bayesian optimization-based LightGBM method for compensating for vibration in pavement depth data. Firstly, the least squares method is used to remove trend of the acceleration data and interpolate missing values. Then, the pavement depth data and acceleration signals are matched using timestamps to obtain the dataset. Finally, the vibration compensation for pavement depth data is achieved through Bayesian optimization-based LightGBM. By comparing Bayesian optimization, genetic algorithm, and grid search parameter optimization methods, the results demonstrate the superiority of the Bayesian optimization-based LightGBM, with an R2Score reaching 0.84. Additionally, the proposed method is validated with real- scene pavement depth data, further demonstrating its feasibility, effectiveness, and generalizability.
DNA BARCODING OF Caranx senegallus FROM THREE WATER BODIES ADJOINING THE GULF OF GUINEA, NIGERIA

Fish species show astonishing phenotypic and genetic diversity in populations. The delimitation and recognition of fish species are not only of interest to taxonomists but also a requirement in studies of ecology. In this study, the genetic structure of Caranx senegallus collected from three water bodies adjoining the Gulf of Guinea, Nigeria was characterized using the cytochrome c oxidase I (COI) barcode gene region. Fish samples collected from Qua Iboe estuary, Escravos estuary, and Lagos lagoon were identified morphologically, and muscle tissues were used for DNA barcoding using Fish1 and Fish2 primers. Evolutionary analysis showed the formation of diverging clades in the neighbor-joining tree and indicated the presence of multiple species. The result also revealed that morphological identification was not entirely successful, as the Basic Local Alignment Search Tool (BLAST) prediction confirmed the presence of three specimens initially identified as C. senegallus but genetically matching C. fischeri and Trachinotus goreensis. This observation further emphasized the need for an integrative method for species identification.
State-Space Formulation for Buckling and Free Vibration of Axially Functionally Graded Graphene Reinforced Nanocomposite Microbeam under Axially Varying Loads

This paper focuses on the size-dependent free vibration and buckling behaviors of the axially functionally graded (AFG) graphene platelets (GPLs) reinforced nanocomposite microbeams subjected to axially varying loads (AVLs). With various axial grading patterns, the GPL nano-reinforcements are distributed throughout the polymer matrix against microbeam length, and the improved Halpin–Tsai micromechanics model and the rule of mixture are adopted to evaluate the effective material properties. Eigenvalue equations of the microbeams governing the static stability and vibration are derived based on the modified couple stress Euler–Bernoulli beam theory via the state-space method, and are analytically solved with the discrete equilong segment model. The effects of axial distribution patterns, weight fraction, and geometric parameters of GPLs, as well as different types of AVLs, on the size-dependent buckling load and natural frequency are scrutinized in detail. The results show that the synchronized axial distributions of GPLs and AVLs could improve the buckling resistance and natural frequency more powerfully.
Nanostructure and Optical Property Tailoring of Zinc Tin Nitride Thin Films through Phenomenological Decoupling: A Pathway to Enhanced Control

This work addresses the need for precise control of thin film sputtering processes to enable thin film material tailoring on the example of zinc tin nitride (ZTN) thin films deposited via microwave plasma-assisted high power reactive magnetron sputtering (MAR-HiPIMS). The applied in situ diagnostic techniques (Langmuir probe and energy-resolved time-of-flight mass spectrometry) supported monitoring changes in the deposition environment with respect to microwave (MW) power. During MAR-HiPIMS, the presence of nitride ions in the gas phase (ZnN+, ZnN2+, SnN+, SnN2+) was detected. This indicates that the MW plasma facilitated their production, as opposed to pure R-HiPIMS. Additionally, MW plasma caused post-ionisation of sputtered atoms and reduced the overall energy-per-charge range of incoming charged species. By varying the MW power and substrate biasing, films with comparable chemical compositions (approximately Zn0.92Sn1.08N2) but different structures, ranging from polycrystalline to preferentially textured, were successfully produced. The application of density functional theory (DFT) further enabled the relationship between the lattice parameters and the optical properties of ZTN to be explored, where the material’s optical anisotropy nature was determined. It was found that despite considerable differences in crystallinity, the changes induced in the lattice parameters were subangstrom, causing only minor changes in the final optical properties of ZTN.
Laboratorio de Geocronología en el Servicio Geológico Colombiano: avances sobre datación U-Pb en circones mediante la técnica LA-ICP-MS

This paper presents the first results of the implementation of the U-Pb dating laboratory at the Servicio Geologico Colombiano (Colombian Geological Survey) using the LA-ICP-MS analytical technique for U-Pb dating. This geochronological method is based on the radioactive decay of the isotopes of Uranium (238U/206Pb and 235U/207Pb) in order to be used in the zircon age determinations. As part of the implementation process, we evaluated reference materials with different age ranges using analytical parameters similar to those used by other laboratories worldwide with the aim of obtaining results with optimal precision and accuracy for this analytical technique. In general, the results obtained show that for the majority of the reference materials, the precision as the coefficient of variation and the veracity as the difference between the expected age and the obtained age are less than 2 %. In addition, we evaluated the concordance of the U-Pb system using concordance diagrams and we found that the mean square weighted deviation (MSWD) in most standards were less than 2, implying that the results were obtained within the established statistical parameters.
Pemodelan Topik Menggunakan Metode Latent Dirichlet Allocation dan Gibbs Sampling

Pemodelan topik adalah suatu alat yang digunakan untuk menemukan topik laten pada sekelompok dokumen. Pada penelitian ini dilakukan pemodelan topik dengan menggunakan metode Latent Dirichlet Allocation dan Gibbs Sampling. Enam artikel berita Bahasa Indonesia telah dikumpulkan dari portal berita detiknews dengan menggunakan metode Web Scrapper. Artikel berita dibagi menjadi dua kategori utama yaitu, narkoba dan COVID-19. Analisis model LDA dilakukan dengan menggunakan metode koherensi topik pengukuran skor UCI dengan hasil penelitian menyebutkan diperoleh lima buah topik optimal pada kedua konfigurasi pengujian.
Ambient Air Pollution and Vision Disorder: A Systematic Review and Meta-Analysis

The effects of air pollution on physical health are well recognized, with many studies revealing air pollution’s effects on vision disorder, yet no relationship has been established. Therefore, a meta-analysis was carried out in this study to investigate the connection between vision disorder and ambient particles (diameter ≤ 2.5 µm (PM2.5), diameter ≤ 10 µm (PM10)) and gaseous pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), Ozone (O3)). Twelve relevant studies published by 26 February 2024 were identified in three databases. A pooled odds ratios (ORs) of 95% confidence intervals (CIs) were obtained using random-effects meta-analysis models. Meta-analysis results revealed that for every 10 µg/m3 increase in PM2.5 and NO2 exposure, a substantially higher incidence of vision disorder was observed (OR = 1.10; 95% CI: 1.01, 1.19; OR = 1.08, 95% CI: 1.00, 1.16). No significant correlation existed between exposure to PM10, SO2 and CO and vision disorder. However, O3 exposure was negatively associated with vision disorder. In addition, subgroup analyses revealed that PM2.5 exposure was significantly correlated with the risk of glaucoma and age-related macular degeneration and that children and adolescents were more susceptible to NO2 and PM2.5 than adults. Overall, exposure to air pollutants, especially PM2.5 and NO2, may increase the incidence of vision disorder.