Miracle-dz/UniFAR-FTUs huggingface dataset:
Impacts of non-plane waves on two-station measurements of phase velocities

SUMMARY To determine the regional shear wave velocities in the lithosphere it is frequently necessary to use two-station dispersion curves. We investigate the influence of non-plane wave energy on such dispersion curves, and compare them to two other better known sources of error: deviations from great-circle paths and uncorrelated noise. To study the influence of nonplane waves created from distant heterogeneities we create complex wavefields in a laterally homogeneous medium by adding interfering waves to a main plane wave. We then calculate the apparent phase velocity between two seismic stations located 100–400 km apart. Using realistic values for the sources of error, we conclude that the contribution of each is similar for 200-km-long profiles. Our conclusions on non-plane waves are made under the assumption that non-plane energy from distant heterogeneities varies randomly with hypocentre location. If this is correct, then only five to 10 events with different hypocentres are required to obtain a stable dispersion curve with less than 1 per cent error. The influence of uncorrelated noise and non-plane waves diminish for longer profiles, while the errors due to great-circle deviations are independent of profile length and systematically bias the dispersion curve to higher velocities. We recommend the inclusion of some off-profile broad-band stations for surface wave studies on a regional scale, because such supplementary stations make it possible to apply first-order corrections for off great-circle propagation. The strong influence from the different sources of error, combined with our lack of precise knowledge of the nature and amplitude of non-plane energy, implies that the interpretation of two-station measurements should be restricted to major changes in regional earth structure.
Impact of Social Media Usage on Financial and Non-Financial Performance of Organization through Social CRM

Social media usage improves Social Customer Relationship Management (CRM) is highly important for modern firms to create value for business after the rapid growth of technology adoption by customers. Studies on social media and organizational performance are limited so the present study has to extend this topic for a brief analysis of this domain. Hence, the current study aims to investigate further how social media usage benefits both financial and non-financial aspects of organizational performance through social CRM. A quantitative cross-sectional research design was carried out to collect the primary information using a structured questionnaire using two separate surveys; one was filled out by the top management of the organizations while the other was filled out by the respective customer of the organizations from different sectors of Pakistan which were also active on Facebook and lastly each 209 participants in both surveys were selected for data analysis. AMOS and Smart PLS were employed to test this proposed model. All findings of this study are found significantly positive and the social CRM acts as a positive mediator between the direct association of social media usage and organizational performance. Furthermore, the present study offers marketers and businessmen to explain the linkage of CRM with advancing social media technologies to improve organizational performance either financial or non-financial performance.
3-D Distribution of Sulphide Minerals in the Merensky Reef (Bushveld Complex, South Africa) and the J-M Reef (Stillwater Complex, USA) and their Relationship to Microstructures Using X-Ray Computed Tomography

Large mafic–ultramafic layered intrusions may contain layers enriched in platinum-group elements (PGE). In many cases, the PGE are hosted by disseminated sulphides. We have investigated the distribution of the sulphides in three dimensions in two oriented samples of the Merensky Reef and the J-M Reef. The aim of the study was to test the hypothesis that the sulphides crystallized from a base metal sulphide liquid that percolated through the cumulate pile during compaction. The distribution of sulphides was quantified using: (1) X-ray computed tomography; (2) microstructural analysis of polished thin sections oriented parallel to the paleovertical; (3) measurement of dihedral angles between sulphides and silicates or oxides. In the Merensky Reef and the J-M Reef, sulphides are connected in three dimensions and fill paleovertical dilatancies formed during compaction, which facilitated the downward migration of sulphide liquid in the cumulate. In the melanorite of the Merensky Reef, the sulphide content increases from top to bottom, reaching a maximum value above the underlying chromitite layer. In the chromitite layers sulphide melt connectivity is negligible. Thus, the chromitite may have acted as a filter, preventing extensive migration of sulphide melt downwards into the footwall. This could partially explain the enrichment in PGE of the chromitite layer and the observed paucity of sulphide in the footwall.
Emotional urgency predicts bipolar symptoms, severity, and suicide attempt better than non-emotional impulsivity: a cross-sectional study

Introduction Emotional urgency is an emotion-based subdimension of trait impulsivity that is more clinically relevant to psychopathology and disorders of emotion dysfunction than non-emotional subdimensions (i.e., lack of perseverance, sensation seeking, lack of premeditation). However, few studies have examined the relative effects of emotional urgency in bipolar disorder. This cross-sectional study aimed to establish the clinical relevance of emotional urgency in bipolar disorders by (1) explicating clinically relevant correlates of emotional urgency and (2) comparing its effects against non-emotional impulsivity subdimensions. Methods and results A total of 150 individuals with bipolar disorder were recruited between October 2021 and January 2023. Zero-order correlations found that emotional urgency had the greatest effect on bipolar symptoms (r = 0.37 to 0.44). Multiple two-step hierarchical regression models showed that (1) positive urgency predicted past manic symptomology and dysfunction severity (b = 1.94, p < 0.001 and 0.35 p < 0.05, respectively), (2) negative urgency predicted current depression severity, and (3) non-emotional facets of impulsivity had smaller effects on bipolar symptoms and dysfunction by contrast, and were non-significant factors in the final step of all regression models (b < 0.30, ns); Those who had a history of attempted suicide had significantly greater levels of emotional urgency (Cohen’s d = –0.63). Discussion Notwithstanding the study’s limitations, our findings expand status quo knowledge beyond the perennial relationship between non-emotion-based impulsivity and bipolar disorder and its implications.
Noise generator by free FPGA technology

The IceStorm project by Clifford Wolf, which involved reverse engineering of an FPGA from Lattice, has sparked interest in developing open-source software and hardware within free FPGA communities. As a contribution to these communities, this paper presents the development of a block generator of random sequences with Gaussian distribution in the Icestudio environment. This block was used in the design and implementation of a Gaussian White Noise generator on the open-source FPGA of the Alhambra II board. Experimental tests demonstrated the similarity of the obtained distribution with the results from the simulation in Matlab and the Fast Fourier Transform (FFT) of the generated noise signal, verifying its limited bandwidth spectrum.
Spatiotemporally resolved emissions and concentrations of styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX) in the US Gulf region

Abstract. Styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX) are established neurotoxicants. SBTEX contains hazardous air pollutants (HAPs) that are released from the petrochemical industry, combustion process, transport emission, and solvent usage sources. Although several SBTEX toxic assessment studies have been conducted, they have mainly relied on ambient measurements to estimate exposure and limit their scope to specific locations and observational periods. To overcome these spatiotemporal limitations, an air quality modeling system over the US Gulf region was created, predicting the spatially and temporally enhanced SBTEX modeling concentrations from May to September 2012. Due to the incompleteness of SBTEX in the official US Environmental Protection Agency (EPA) National Emission Inventory (NEI), the Hazardous Air Pollutions Imputation (HAPI) program was used to identify and estimate the missing HAP emissions. The improved emission data were processed to generate the chemically speciated hourly gridded emission inputs for the Comprehensive Air Quality Model with Extensions (CAMx) chemical transport model to simulate the SBTEX concentrations over the Gulf modeling region. SBTEX pollutants were modeled using the Reactive Tracer feature in CAMx that accounts for their chemical and physical processes in the atmosphere. The data show that the major SBTEX emissions in this region are contributed by mobile emissions (45 %), wildfire (30 %), and industry (26 %). Most SBTEX emissions are emitted during daytime hours (local time 14:00–17:00), and the emission rate in the model domain is about 20–40 t h−1, which is about 4 times higher than that in the nighttime (local time 24:00–04:00, about 4–10 t h−1). High concentrations of SBTEX (above 1 ppb) occurred near the cities close to the I-10 interstate highway (Houston, Beaumont, Lake Charles, Lafayette, Baton Rouge, New Orleans, and Mobile) and other metropolitan cities (Shreveport and Dallas). High styrene concentrations were co-located with industrial sources, which contribute the most to the styrene emissions. The HAPI program successfully estimated missing emissions of styrene from the chemical industry. The change increased total styrene emissions by 22 %, resulting in maximum ambient concentrations increasing from 0.035 to 1.75 ppb across the model domain. The predicted SBTEX concentrations with imputed emissions present good agreement with observational data, with a correlation coefficient (R) of 0.75 (0.46 to 0.77 for individual SBTEX species) and a normalized mean bias (NMB) of −5.6 % (−24.9 % to 32.1 % for the individual SBTEX species), suggesting their value for supporting any SBTEX-related human health studies in the Gulf region. The SBTEX data were published at Zenodo (https://doi.org/10.5281/zenodo.7967541) (Wang et al., 2023), and the HAPI tool was also published at Zenodo (https://doi.org/10.5281/zenodo.7987106) (Wang and Baek, 2023).
Comparative bioinformatics analysis of transcriptomes between β-aminopropionitrile-induced aortic dissection murine model and human aortic dissection

Background Aortic dissection (AD) poses a great threat to the life of patients; however, there is currently no documentation of a clear pathogenic mechanism of this disease. In recent years, β-aminopropionitrile (BAPN)-induced AD in rodents has been widely used in basic research, which provides a good platform for exploring the pathogenesis of AD and drug modification. This study aimed to identify molecular markers and pathways for the diagnosis and treatment of AD by comparing a murine AD model and human AD transcriptome through a bioinformatics analysis. Methods We constructed a BAPN-induced mice model and performed high-throughput sequencing analysis. The GSE147026 dataset of patients was obtained from the Gene Expression Omnibus database. We performed a subsequent bioinformatics analysis of human AD and the murine AD model using R software. The DESeq software package was used to analyze the differentially expressed genes (DEGs). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to analyze the enrichment pathways. Protein-protein interaction network construction and hub gene selection were based on STRING software analysis. Stepwise identification of potential drugs was performed online, while hub genes were validated immunohistochemically. Results We compared the murine AD model and human AD transcriptome and found that both differentially expressed 463 genes. The cytokine-cytokine receptor interaction, tuberculosis, and phagosome pathways were significantly enriched. CDC20, CCNB2, and CCNB1 may be associated with AD development. Protein-drug interactions were also identified. Conclusions This study is the first to reveal transcriptional changes in a murine BAPN-induced AD model versus human AD transcriptome. Furthermore, we identified the important hub genes, related pathways, and potential drugs by analyzing the overlapping DEGs between human AD and the murine AD model. Our results provide a basis for the further identification of potential molecular markers for diagnosing and treating AD.
Enhancing Product Promotion in Social Networks: Leveraging Adaptive Discount-Offering and the Crowd Effect

Product promotion on social media platforms has revolutionized advertising, with the crowd effect playing a crucial role. This effect capitalizes on individuals’ exposure to product opinions shared online. People are more likely to make purchases when they see others endorsing the product through likes and positive feedback. In our study, we integrate this crowd effect into our modeling of information diffusion on social networks. Our goal is to optimize influence through adaptive discount offering to prospective customers. To achieve this, we develop a model based on two widely used diffusion models, namely the independent cascade and linear threshold models. We formulate our decision problem as a Markov decision process. Then, we demonstrate that our problem does not satisfy the adaptive submodular property due to an additional global state variable, rendering the greedy policy suboptimal without performance guarantees. To tackle this challenge, we propose a rolling horizon method with fluid approximation, utilizing an offline upper bound to guide our online decision-making process. We also conduct numerical experiments to evaluate our method on random and real networks. Our method outperforms benchmark methods by a significant margin, achieving up to double the performance on random graphs and up to 63.12% improvement on real networks.
Wind/Wave directional modelling: a compositional approach

M.I. Ortego, J.J. Egozcue, J. Gómez, C. Mösso and A. Sánchez-Arcilla ma.isabel. ortego@upc.edu (1) Departament de Matemàtica Aplicada III, Universitat Politècnica de Catalunya, Barcelona (Spain) (2) Laboratori d’Enginyeria Marítima, UPC (3) Centre Internacional d ’ Investigació dels Recursos Costaners (CIIRC), UPC The problem • One of the main parameters involved in wave impacts for coasts and harbours is the angle (α) between wave crests approaching to the coast and shoreline orientation • Regarding coastal dynamics: potential sediment transport rate (Ql), as well as magnitude of the wave-induced longshore currents (vl) are function of the wave angle in breaking conditions • Harbour breakwaters are designed to face the main wave crests direction, projecting the harbour entrance to prevent as much as possible the incoming wave energy into sheltered harbour areas and thus harbour agitation • Changes in wave angle may have a significant potential impact in sediment transport rates and beach evolution and in harbour operability • According to [2], a shift on the wave direction may induce a significant increase in harbour agitation in the nearby ports Data • Tortosa buoy: directional Datawell waverider with a sensor type heave-pitch-roll and accelerometers to record horizontal movements. • Located in the NW mediterranean, 8km front the Ebre delta at 60m depth. Recording data from 1990 until 2012 as part of the old XIOM oceanographic network. Figure 1: Bathymetric map of the Western Mediterranean with location of the Tortosa buoy.
The correlation between electron temperature and density in the topside ionosphere during 2006–2009

Detection of Electro‐Magnetic Emissions Transmitted from Earthquake Regions satellite data have been used to investigate the global relationship between electron density (Ne) and electron temperature (Te) in the topside ionosphere (~680 km) from 2006 to 2009. Te and Ne were negatively correlated in most of the low and middle latitude regions at ~10:30 solar local time (LT). In these regions, photoelectron heating of the electrons was balanced by cooling through collisions with the ions. The negative correlation became weaker at midlatitudes, due to the increasing influence of heat conduction. The correlation was negative in most seasons during the daytime except at high latitudes in the northern winter, where a positive correlation occurred. There were wave‐like longitudinal structures in Ne and Te around the geomagnetic equator, but they had different patterns in the day and the night. However, no obvious longitudinal variations in the correlation were associated with these structures. A positive correlation occurred near the magnetic equator at ~22:30 LT, which depended on thermal equilibrium between the electrons, ions, and neutrals. A negative correlation occurred at midlatitudes. Around the September equinox, at night around the magnetic equator, the positive correlation had a wider latitudinal range. At midlatitudes, a negative correlation occurred in smaller areas than it did around the March equinox. Around the December solstice the direct nighttime coupling between Ne and Te was weaker than it was around the June solstice. The negative correlation depends on the collisions between the electrons and the ions and the heating source.
Study of application of regression method based on support vector machine on Zhejiang drought and flood's forecast at flood season

The application of SVM regression method on Zhejiang drought and flood's forecast at flood season was studied.By use of normalized Z-index calculated from 38 observatory stations' rainfalls,the grades of intensity of drought and flood were classified,and then corresponding index is obtained which reflects the whole state of drought and flood in Zhejiang province.Take the index as predictand,and atmospheric circulation and SST in the past,which exhibit high correlation with predictand,as predictor,the prediction model of Zhejiang drought and flood based on support vector machine and successive regression were built respectively.The comparisons of forecast results of two methods show that the SVM forecast model could make use of plentiful predictor's information,and show better performance of non-linear projection than successive regression method,which is confirmed by both training and testing samples.
Novel nomograms to predict risk and prognosis in hospitalized patients with severe fever with thrombocytopenia syndrome

Background Severe fever with thrombocytopenia syndrome (SFTS) is an emerging and life-threatening infectious disease caused by SFTS virus. Although recent studies have reported the use of nomograms based on demographic and laboratory data to predict the prognosis of SFTS, no study has included viral load, which is an important factor that influences the prognosis, when compared with other risk factors. Therefore, this study aimed to develop a model that predicts SFTS prognosis before it reaches the critical illness stage and to compare the predictive ability of groups with and without viral load. Methods Two hundred patients with SFTS were enrolled between June 2018 and August 2023. Data were sourced from the first laboratory results at admission, and two nomograms for mortality risk were developed using multivariate logistic regression to identify the risk variables for poor prognosis in these patients. We calculated the area under the receiver operating characteristic curve (AUC) for the two nomograms to assess their discrimination, and predictive abilities were compared using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results The multivariate logistic regression analysis identified four independent risk factors: age, bleeding manifestations, prolonged activated partial thromboplastin time, and viral load. Based on these factors, a final nomogram predicting mortality risk in patients with SFTS was constructed; in addition, a simplified nomogram was constructed excluding the viral load. The AUC [0.926, 95% confidence interval (CI): 0.882–0.970 vs. 0.882, 95% CI: 35 0.823–0.942], NRI (0.143, 95% CI, 0.036–0.285), and IDI (0.124, 95% CI, 0.061–0.186) were calculated and compared between the two models. The calibration curves of the two models showed excellent concordance, and decision curve analysis was used to quantify the net benefit at different threshold probabilities. Conclusion Two critical risk nomograms were developed based on the indicators for early prediction of mortality risk in patients with SFTS, and enhanced predictive accuracy was observed in the model that incorporated the viral load. The models developed will provide frontline clinicians with a convenient tool for early identification of critically ill patients and initiation of a better personalized treatment in a timely manner.
System-Scale Model of Aquifer, Vadose Zone, and River Interactions for the Hanford 300 Area - Application to Uranium Reactive Transport

This report represents a synthesis and integration of basic and applied research into a system-scale model of the Hanford 300 Area groundwater uranium plume, supported by the U.S. Department of Energy’s Richland Operations (DOE-RL) office. The report integrates research findings and data from DOE Office of Science (DOE-SC), Office of Environmental Management (DOE-EM), and DOE-RL projects, and from the site remediation and closure contractor, Washington Closure Hanford, LLC (WCH). The three-dimensional, system-scale model addresses water flow and reactive transport of uranium for the coupled vadose zone, unconfined aquifer, and Columbia River shoreline of the Hanford 300 Area. The system-scale model of the 300 Area was developed to be a decision-support tool to evaluate processes of the total system affecting the groundwater uranium plume. The model can also be used to address “what if” questions regarding different remediation endpoints, and to assist in design and evaluation of field remediation efforts. For example, the proposed cleanup plan for the Hanford 300 Area includes removal, treatment, and disposal of contaminated sediments from known waste sites, enhanced attenuation of uranium hot spots in the vadose and periodically rewetted zone, and continued monitoring of groundwater with institutional controls. Illustrative simulations of polyphosphate infiltration were performedmore » to demonstrate the ability of the system-scale model to address these types of questions. The use of this model in conjunction with continued field monitoring is expected to provide a rigorous basis for developing operational strategies for field remediation and for defining defensible remediation endpoints. « less