Miracle-dz/UniFAR-FTUs huggingface dataset:
Vertebrate biogeographic evidence for connections of the east and southeast Asian blocks with Gondwana

A review of the fossil‐vertebrate literature indicates fluctuating affinities between aquatic faunas of China and Australia during the Devonian Period. Within the South China Block, the close similarity of the highly endemic freshwater fish faunas located on the Yangtze and Huanan terranes demonstrate that these must have been juxtaposed in the mid‐Palaeozoic. Analysis of the Triassic tetrapods suggests the faunas of Australia were quite distinct from those of China and Thailand. Although this evidence points to the Permo‐Carboniferous as the time of separation between Australia and the various plates of southeastern Asia, unfortunately the vertebrate fossil record in these regions during those periods is so poor as to shed no direct light on the matter. One of the problems of plate motion where fossil vertebrate evidence has contributed the most is the Mesozoic position of India. Because the relevant data are of a positive nature rather than dependent on the absence of taxa, the inference from them that .
Characterization of iron oxides in mineral dust aerosols: Implications for light absorption

[1] We report on measurements that were specifically designed to determine iron oxides in mineral dust aerosols needed for improved optical modeling. Atmospheric dust samples as well as samples generated in a wind tunnel from soils were analyzed by a number of analytical techniques for their total and free iron content (bulk and size resolved), hematite and goethite, mineralogy, and size distribution. These samples are representative of several important dust sources in East Asia and northern Africa. A novel data set generated from these measurements enables us to perform an in-depth modeling study of dust optical properties in the solar spectrum. We modeled the iron oxide–clay aggregates, which are the key light-absorbing species, as well as their mixtures with nonabsorbing minerals. A volume fraction of iron oxide in aggregates was determined from measurements. Significant differences in the single-scattering albedo, ω0, were found between hematite- and goethite-clay aggregates, although these calculations involved several important assumptions about the partition of hematite and goethite in size-resolved aggregates. Furthermore, we found that variability of the free iron content is large enough to cause important differences in ω0 of mineral dust originating from different sources. In contrast, this variability has little effect on the extinction coefficient and optical depth. We demonstrate that for the same size distribution, ω0 calculated from data obtained for Chinese and Tunisian samples show higher values and more distinct wavelength dependence than those of Niger dust. All the above ω0 differ from ones calculated using the refractive indices of Patterson et al. (1977) or the OPAC model (Hess et al., 1998), which are often used in radiative transfer studies. We conclude that information on a size-resolved content of free iron and a fraction of hematite and goethite in aggregates will need to be known on a regional basis to improve the prediction of the single-scattering albedo at solar wavelengths and hence the radiative impact of atmospheric mineral dust.
Modeling the paleocirculation of the Mediterranean: The Last Glacial Maximum and the Holocene with emphasis on the formation of sapropel S 1

An ocean general circulation model is used to simulate the thermohaline circulation in the Mediterranean sea during the last glacial maximum and the Holocene, when the sapropel S1 was deposited. The model is forced by prescribed surface temperatures and salinities, where present-day values lead to very realistic surface buoyancy fluxes. Different paleoreconstructions for the surface salinity and temperature distributions during these periods are tested. In both periods, under all reconstructions, antiestuarine flow is maintained at Gibraltar and Sicily. The Holocene circulation has fresh intermediate water produced in the Adriatic and an upward salt flux from the old waters below help maintain its outflow at Sicily. The depth of ventilation around the basin is broadly consistent with the shallowest sapropel layers observed. Shoaling of the eastern pycnocline occurs in all experiments in both periods, possibly indicating enhanced productivity, although the reasons for this are different in each case.
Using DeepWalk to Link Prediction in Subgraph

This research presents an innovative application of the DeepWalk algorithm in conjunction with k-Nearest Neighbors (k-NN) for link prediction tasks, using the Amazon dataset as a case study. The DeepWalk algorithm, designed to learn latent representations of vertices within a network, leverages randomized path traversing to reveal localized structures within networks. This is achieved by employing random paths as sequences to train a Skip-Gram Language Model. This approach allows us to extract insights from a part of the graph and extend it to the entire network, enhancing computational efficiency. In this study, the dataset was preprocessed to handle duplicates and missing values. A graph representation of the dataset was constructed based on product similarities, with DeepWalk used to generate graph embeddings. A k-NN model was trained on these embeddings to predict product links. The performance of the approach was assessed using various evaluation metrics, with particularly high AUC and Recall values indicating strong predictive accuracy. Two feature selection techniques, LASSO regression and Recursive Feature Elimination (RFE), were employed to improve the model's performance. The results highlighted ‘Price’, ‘Offers’, ‘Stock Availability’, ‘Category’, and ‘MRP’ as the most impactful features.
Estimation of variables explaining urbanization concomitant with land-use change: a spatial approach

Urbanization in India is rapidly increasing. Dispersed development along highways or surrounding cities and in rural areas is resulting in serious loss of agricultural land, open space, waterbodies, and ecologically sensitive habitats. The management and monitoring of such resources require an understanding of change in land use and land cover. Vadodara City in Gujarat, India, has been chosen as the study area because it is a rapidly developing city with increasing urbanization and industrialization. Rapid growth of the population and haphazard expansion of local planning has led to substantial loss of agricultural land, resulting in several land-use changes. Such changes have been analysed using remotely sensed data in conjunction with conventional data. This study was carried out to detect the changes that have occurred in the study area over a period of 129 years (1880–2009) at the Vadodara Mahanagar Seva Sadan (VMSS) level, i.e. the inner city level, and for 126 years (1880–2006) at the Vadodara Urban Development Authority (VUDA) level, i.e. the greater city area. The results reveal that the city expanded from 9.14 km2 in 1880 to 136.68 km2 in 2006, exhibiting a high rate of urbanization. Estimation of various variables, such as Shannon's entropy (SE), the urban sprawl index (USI), land consumption rate (LCR), and land absorption coefficient (LAC) related to urbanization, brought out interesting facts about the city. The results show that sprawl is high. This sprawl has evenly dispersed distribution across the space with absorption of land increasing over a period of time, but at the same time the absorbed land requires more planning and proper utilization as evident from lower LCR values. Such an understanding is a prerequisite for the sustainable planning required to counteract the perceived negative social, economic, and environmental impacts of urban sprawl.
Mapping coral reef benthic cover with fused IKONOS imagery

In this article, we present some experiments on coral reef benthic cover mapping with fused IKONOS image. The objective of our study is to establish an efficient approach for the classification task on hand. Four scenarios are designed and in each scenario two classification methods (Maximum Likelihood and Decision Tree) are implemented. Ground truth data is obtained through visual interpretation and manual digitization, against which accuracy of classification map is calculated. Results indicate that mining spectral information deeply (scenario III and IV) can increase classification accuracy dramatically. Compared with conventional utilization of spectral data (scenarioI), classification accuracy of ML and DT respectively increases by 3.94% and 5.15% under scenario IV. However, when spectral and spatial information is combined together (scenario II), accuracy of ML and DT is respectively reduced by 8.02% and 2.31%. It can be concluded from our study that when classify benthic cover with high-resolution remote sensing data in pixel-based pattern, utilization of spatial information should not be excessively emphasized. Fully exploiting spectral information may bring more benefits. Moreover, DT is more robust and can produce more accurate classification results than ML. Our results help scientists and managers in applying IKONOS-class data for coral reef mapping applications.
Detection and Location of Electricity Theft via Convolutional Neural Network in Distribution System

One of the common types of electricity theft occurs by tampering with smart meters (SMs) to pay less than the actual consumption. This paper proposes a convolutional neural network (CNN)-based method for detection and location of electricity theft (DLET) in smart distribution systems. The proposed method combines SMs and observer meters (OMs) data to reflect both spatial information of the grid bus connection and daily temporal data, simultaneously. The spatial information becomes the spatial axis and the daily data becomes the temporal axis of the input 2D image for the CNN. Furthermore, the spatial information of SMs and OMs is conserved by matching the kernel size of CNN with the spatial axis of the input image. The proposed method is evaluated by SimBench dataset, which includes bus connection and temporal data. As a result, the proposed method outperforms traditional methods for detection of electricity theft.
Aliphatic and Polycyclic Aromatic Hydrocarbons and Sulfur/Oxygen Derivatives in Northwestern Mediterranean Sediments: Spatial and Temporal Variability, Fluxes, and Budgets

The spatial and temporal distribution of aliphatic and polycyclic aromatic hydrocarbons (PAHs) and sulfur/oxygen derivatives in sediments from the NW Mediterranean basin were investigated. Along the Continental Shelf and slope, an unresolved complex mixture (UCM) of aliphatic hydrocarbons and alkylated PAHs, indicative of petrogenic inputs, were predominant. Long-chain n-alkanes derived from terrestrial plant waxes (n-C27, n-C29, and n-C31) and parent PAHs, which are typical of high-temperature combustion processes, were evenly distributed in the whole basin and largely prevailing in the deepest areas. Perylene, a geochemically derived PAH, was found highly abundant in the areas influenced by river discharges. The highest anthropogenic hydrocarbon inputs were found near the cities of Marseille and Barcelona, being the contribution of the Rhone River ca. 25 times higher than that of the Ebro. Fluxes of PAHs in the deep basin were consistent with a predominant atmospheric input. These results account for an.
Climate of East Africa 6000 14C Yr B.P. as Inferred from Pollen Data

This paper presents a spatial reconstruction of climate in East Africa at 6000 14C yr B.P. Two different approaches using pollen data have been used, the standard “best modern analogues” method and the new “plant functional type” method, based on groups of pollen taxa. Both methods have been applied to 32 fossil pollen spectra dated at 6000 14C yr B.P. For each site, we have estimated two climatic parameters (annual precipitation and mean annual temperature), three bioclimatic parameters (ratio of actual to potential evapotranspiration, and the mean temperature of the coldest and warmest months). Results show that the temperature lapse rate was less steep at 6000 14C yr B.P. than it is today. The climate was wetter north of 3°S (precipitation anomalies >+50 mm/yr) and slightly drier farther south (precipitation anomalies ≤+50 mm/yr). The ratio of actual to potential evapotranspiration also indicates conditions similar to or wetter than today north of 3°S (anomalies >10%). The climate was warmer than today by 2°C north of the equator and was cooler southward (≤−1°C). Although both methods indicate similar climatic patterns, the plant functional type method provides more consistent results.
Aerosol indirect effect over the Indian Ocean

We analyze the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data over the seas adjacent to the Indian sub‐continent to investigate the effect of aerosols on the size distribution of cloud droplets and ice crystals (indirect aerosol effect). During the winter months of increased anthropogenic pollution we observe smaller sizes of cloud droplets in water clouds in agreement with the expected aerosol indirect effect. However, contrary to our expectations, we find that during episodes of increased pollution the effective radius of ice crystals is shifted toward the larger rather than smaller sizes. We propose a combination of natural seasonal variability of meteorological conditions and an “inverse aerosol indirect effect” caused by heterogeneous ice nucleation as a possible explanation of observed ice crystal growth. The ECHAM4 (European Center for Medium‐Range Weather Forecast Hamburg version 4th generation GCM) results with heterogeneous ice nucleation reproduce the observed increase in ice crystal size during the enhanced pollution episodes.
Spatiotemporal characteristics of cusp latitude spectra

In this study we analyze the spatiotemporal characteristics of spectra generated from 754 days of cusp latitude magnetometer data (Longyearbyen and selected Magnetometer Array for Cusp and Cleft Studies (MACCS) stations). In order to distinguish between the presence of spatial (fixed in magnetic local time) and temporal (fixed in universal time) signatures in cusp latitude spectra we develop a simple test using trace power, polarization, and ellipticity spectra. On the basis of this test we find evidence for both spatial and temporal signatures in cusp latitude spectra. We find that the trace power spectrum is dominated by temporal information; however, the polarization and ellipticity spectra contain unambiguous spatial structure. Temporal information in cusp latitude spectra is carried primarily by broadband Pc3 (10–50 mHz) noise, while spatial information is carried by polarized Pc3 (1–10 mHz) pulsations. Additionally, we establish a state-space measure as a quantitative means of discriminating the spatial passage of the cusp and boundary regions by ground-based magnetic means. The measure is based on the difference between daily polarization spectra (centered on local magnetic noon) and the mean polarization spectra for a given station. This procedure replaces previous determinations which were made from spectra “by-eye”.
Application of Stochastic Averaging to Vibrating Electro-mechanical Systems for Piezoelectric Energy Harvesting

Electro-mechanical systems are ubiquitous in engineering. For example, they are used in energy harvesting systems to convert random mechanical excitations into usable electrical power. The analysis and design of these electro-mechanical systems is particularly challenging, because concepts and methods of stochastic analysis and nonlinear dynamics are required. In this work we present a methodology for the analysis of nonlinear electro-mechanical systems with small internal friction, and subject to random external mechanical excitations. The method is based on the combined application of a model order reduction technique, to reduce the number of dynamical variables, thus reducing the complexity, and of stochastic averaging, to calculate statistical relevant quantities, and in particular expectations of the output electrical variables. As an example, we apply the proposed technique to the analysis of a piezoelectric energy harvesting system.
Parameterization of shortwave radiation fluxes for nonuniform vegetation canopies in land surface models

Net solar radiation (Q * ) and the partitioning of Q * between vegetation (Q veg * ) and the substrate (Q soil * ) are important quantities computed by soil-vegetation-atmosphere-transfer (SVAT) models. Commonly, two-stream models of canopy radiative transfer are used for this purpose. We examine the validity of this approach for nonuniform canopies and compare estimates of Q * , Q veg * , and Q soil * computed using a two-stream model with estimates computed using a model that accounts for the effects of three-dimensional (3-D) structure in vegetation on radiative transfer. To accomplish these goals, a sensitivity analysis is conducted for the key input parameters to two-stream canopy radiative transfer models. The parameters examined include leaf area index (L), leaf optical properties, solar zenith angle, leaf orientation, and background albedo. Sensitivity analyses are also conducted using a Geometric-Optical Radiative Transfer (GORT) model. The GORT model treats vegetation canopies as being composed of 3-D crowns and allows for both vertical variation in leaf area and horizontal variation in stem density. Results show that Q * computed by the two-stream model varies by up to 10% relative to the GORT model. Further, the partitioning of Q * between the vegetation canopy and substrate computed by the two-stream model can vary by up to 30% relative to the more realistic GORT model, even for relatively dense canopies (L=6). These differences arise because two-stream models use parameterizations for gap probabilities that are not realistic in discontinuous canopies. Based on this conclusion, a parameterization is proposed to include the effects of canopy heterogeneity in two-stream models. Results from the original two-stream model, a parameterized two-stream model, and the GORT model are compared using data from the Boreal Ecosystem-Atmosphere Study. These results show that the proposed parameterization captures the effect of 3-D structure in vegetation on radiation regimes and is therefore suitable for inclusion in SVAT models. Inclusion of improved treatment for radiative fluxes in land surface parameterizations should improve modeled estimates for other flux quantities computed by SVAT models.
Toward Real-World Implementation of Deep Learning for Smartphone-Crowdsourced Pavement Condition Assessment

In recent years, acrlong MCS has emerged as an effective way of collecting essential information about our urban infrastructure integrity conditions. As such, smartphone sensor data obtained while driving vehicles has been widely investigated for road condition monitoring, hoping it can be used as a cost-effective alternative to conventional methods which uses high-cost system, including inertial profilers. However, currently available smartphone methods require expensive signal processing to address various practical uncertainty issues, such as unknown mechanical characteristics of vehicles, variable driving speed, and sensor location. Hence, only a precisely calibrated setup of the vehicle and smartphone could be used for road condition monitoring under a limited environment. The authors’ prior study has developed a deep-learning-based road roughness monitoring method that estimates the international roughness index (IRI) from the anonymous vehicles’ vibrations at any driving speeds, measured by smartphones. The feasibility of the proposed method has been numerically validated. Building on prior efforts, this study investigates its full-scale experimental validation under a real-world environment, addressing associated critical challenges in the real-world implementation of the proposed method. A fully convolutional neural network (CNN) architecture, called IRI-Net, is developed in this study. A new data management strategy is proposed to deal with the low-resolution characteristics of crowdsourced smartphone GPS data. A large-scale data set is collected with total 29 different vehicles under a real-world uncertain environment. The performance of the proposed method is validated by comparing to the reference IRI data obtained from a conventional inertial profiler, showing a great step toward real-world practical applications.
Volume changes of Vatnajökull ice cap, Iceland, due to surface mass balance, ice flow, and subglacial melting at geothermal areas

We present observed changes in the geometry of western Vatnajökull over a period of about ten years which are caused by the surface mass balance, ice flow (both during surges and quiescent periods), and basal melting due to geothermal and volcanic activity. Comparison of two digital elevation models shows that from 1985 to 1998 the outlet glaciers have lost 14 ± 5 km3, on the average 1 m yr−1 evenly distributed over the area of 1360 km2. However, the marginal areas of four outlets have gained up to 80 m in elevation and the uppermost parts have subsided similarly during surges. Altogether 26 ± 3 km3 were transported from the accumulation areas to the ablation areas of which 19 ± 3 km3 are attributed to surges. Comparison of DEM's from August 1997 and August 1998 revealed 10 ice cauldrons produced by subglacial geothermal activity, of which some were previously unknown.
Research on Green Supply Chain’s Coordination Based on Knowledge Spillover Effect

GSCM and its members of sharing resources generate knowledge spillover phenomenon within innovation activities.Considering the scarcity and publicity characteristics of knowledge,it puts forwards the driving factors including knowledge sharing cognition,technology gap, the economy and geography space, spill risk control and spill achievements’compensation.According to supply chain benefit coordination problem,it adds members’ participation and contribution factor for Shapley amendment model.Then it verifies rationality of the model by empirical analysis,which would be helpful for further knowledge spillovers benefit evaluation and compensation mechanism research.
Geochemical characteristics of the metapelites from the Xingxingxia group in the Eastern Segment of the Central Tianshan: Implications for the provenance and paleoweathering

Metapelites from the Mesoproterozoic Xingxingxia group in the Eastern Segment of the Central Tianshan, Northwestern China, were analyzed for major and trace elements, including rare earth elements. Compared with post-Archean shales, the metapelites are enriched in Sr, Hf and Zr. The other elements are similar to the compositions of the Phanerozoic North American Shale Composite and the Post-Archean Australian average Shale (PAAS). The characteristics of Al 2 O 3 /TiO 2 , Cr/Zr, Cr/Th, Th/Sc and high Zr concentration suggest that these pelites could be derived from a significant proportion of felsic and a few proportion of participation of mafic materials in nature. These rocks display highly fractionated REE patterns, and average (La/Yb) n = 18.6. Several samples have slightly negative Eu anomalies (Eu/Eu* = 0.7―0.84) in comparison with PAAS (Eu/Eu* = 0.65), indicating contribution from young immature materials. The low K 2 O/Al 2 O 3 values of these metapelites suggest that their source materials could contain minimal alkali feldspar. In the A-CN-K triangular diagram, the sample data array intersects the feldspar join, indicating that the source had a plagioclase: K-feldspar ratio of approximately 5:1, representing weathered products from components that could approximately correspond to granodiorites and tonalites. The low Chemical Index of Alteration (CIA) and high Index of Compositional Variability (ICV) values suggest low degrees of weathering of the source and low compositional maturity of the sediments, respectively. The geochemical characteristics of the metapelites from the Xingxingxia group also demonstrate that these sediments were deposited in a back-arc background within a continental-arc system.