Miracle-dz/UniFAR-FTUs huggingface dataset:
On bias and noise in passive seismic data from finite circular array data processed using SPAC methods

The finite nature of typical small seismic arrays used in conjunction with spatial autocorrelation SPAC processing for observing the microtremor wavefield causes predictable perturbationsoftheSPACspectrumwhensourcesofseismic noiseareconfinedtoarestrictedrangeofazimuths.Suchperturbations are especially evident at higher frequencies where wavelengths are on the order of the array radius. The effects arereadilymodeledandshowthatthetriangulararraygeometries commonly used for microtremor studies require azimuthal distributions of wave energy on the order of 60° or greatertohaveahighprobabilityofbeingfreeofsuchperturbations. The imaginary component of the SPAC spectrum, which is ideally zero for a sufficiently dense circular array and/or a sufficiently isotropic wavefield, is in practice often nonzero and provides three quality-control indicators: 1 an indication of insufficient spatial averaging, 2 an empirical measure of the level of statistical uncertainty in SPAC spectralestimates,and3anindicationofdeparturesfromplanewavestationarityoftheseismicnoisewavefield.
Obstacle drag in stratified flow

This paper describes an experimental study of the drag of two- and three-dimensional bluff obstacles of various cross-stream shapes when towed through a fluid having a stable, linear density gradient with Brunt-Vaisala frequency, N. Drag measurements were made directly using a force balance, and effects of obstacle blockage (h/D, where h and D are the obstacle height and the fluid depth, respectively) and Reynolds number were effectively eliminated. It is shown that even in cases where the downstream lee waves and propagating columnar waves are of large amplitude, the variation of drag with the parameter K ( = ND/πU) is qualitatively close to that implied by linear theories, with drag minima existing at integral values of K. Under certain conditions large, steady, periodic variations in drag occur. Simultaneous drag measurements and video recordings of the wakes show that this unsteadiness is linked directly with time-variations in the lee and columnar wave amplitudes. It is argued that there are, therefore, situations where the inviscid flow is always unsteady even for large times; the consequent implications for atmospheric motions are discussed.
A Preliminary Survey and distribution of Land snails of Katana region, Southern Kivu, Democratic Republic of Congo

We investigated land snail fauna of Katana region, along the Lake Kivu and the Kahuzi-Biega National Park in Democratic Republic of Congo, using a combination of direct search and leaf litter sieving techniques. Four plots, in different habitats (Forest, wetland, cultivated area and fallow) were studied, covering low altitude (1400 - 1590 m), middle altitude (1600 - 1790 m) and high altitude (1800 - 2000 m). A total of 31 species and 2209 individual land snails belonging to 9 molluscan families and 23 genera were collected from all habitats. Species richness was ranged from 25 to 10 at different habitats and different altitudes. The wetland has high species richness (25) and the fallow has low species richness (10). Achatina achatina and Achatina fulica (Achatinidae) were recorded in all the habitats in the region (constant species), where Arion rufus (Arionidae), Homorus amputatus (Achatinidae) and Subulinuscus ruwenzorensis (Achatinidae) are found in one habitat (25 %) and are uncommon in Katana region (accidental species). The land snail species inventories will increase our knowledge of the molluscan fauna of the Katana region and assist in conservation management.
Low-shot Object Learning with Mutual Exclusivity Bias

This paper introduces Low-shot Object Learning with Mutual Exclusivity Bias (LSME), the first computational framing of mutual exclusivity bias, a phenomenon commonly observed in infants during word learning. We provide a novel dataset, comprehensive baselines, and a state-of-the-art method to enable the ML community to tackle this challenging learning task. The goal of LSME is to analyze an RGB image of a scene containing multiple objects and correctly associate a previously-unknown object instance with a provided category label. This association is then used to perform low-shot learning to test category generalization. We provide a data generation pipeline for the LSME problem and conduct a thorough analysis of the factors that contribute to its difficulty. Additionally, we evaluate the performance of multiple baselines, including state-of-the-art foundation models. Finally, we present a baseline approach that outperforms state-of-the-art models in terms of low-shot accuracy.
Electron Microprobe Analyses and Magnetic Properties of Non-Stoichiometric Titanomagnetites in Basaltic Rocks

Summary Chemical analyses have been made of non-stoichiometric (i.e. slightly oxidized) titanomagnetites in basaltic rocks from Argentina, Turkey, the Azores, the Canary Islands, Japan, Bulgaria, Aden and the Pacific area. The compositions do not differ significantly from the average compositions of titanomagnetite grains which contain ilmenite lamellae (usually taken as evidence of deuteric oxidation) in other basalts from the same regions and also from Oregon. The shapes of the thermomagnetic curves are considered to provide a rapid and useful approximation to the degree of non-stoichiometry. This has been determined more precisely from observations that the measured Curie points are invariably higher than the compositional ones, calculated for stoichiometric titanomagnetites of the same composition. The degree of non-stoichiometry so obtained has been represented by plotting the estimated compositions of the grains studied on a triangular plot.
Length-Weight Relationships for Thirty Fish Species in Lake Niushan, a Shallow Macrophytic Yangtze Lake in China

Length-weight relationships are presented for 30 fish species captured from April 2002 to January 2004 in Lake Niushan, China. The values of the exponent b in the lengthweight relationships (W=aLb) ranged from 2.845 to 3.435 and the median of b was 3.103,whereas 50% of the values ranged between 3.032 and 3.203. In the eight examined species,sexual dimorphism did not affect the length-weight relationships, except in the cases of Siniperca chuatsi and Cultrichthys erythropterus. The application of the length-weight relationships presented here should be limited to the observed length ranges.
Earliest Records of the Genus Spiticeras Uhlig in the Neuquén Basin, Argentina: Systematic and Biostratigraphic Implications

Abstract. The earliest records of the genus Spiticeras Uhlig in Western Gondwana occur in the Upper Jurassic—Lower Cretaceous deposits of the Vaca Muerta Formation in the Neuquén Basin, Argentina. Those records involve two species, Spiticeras acutum Gerth and Spiticeras hauthali Gerth, which were firstly described from Arroyo Durazno, Mendoza. A systematic revision and reconsideration of the biostratigraphic distribution of both species was performed based on the study of type material and new bed-by-bed collections in the type locality and other southern Mendoza sections. S. acutum and S. hauthali display a succession of ornamentation stages that, together with other morphological characters, sustain their assignation to the genus Spiticeras. Addidionally, macroconchiate and microconchiate specimens were identified in both taxa. The record of S. acutum from the lowermost beds assigned to the Late Tithonian—Early Berrisian Substeueroceras koeneni Assemblage Biozone substantiates the downwards extension of the known range of the species in the Neuquén Basin. Given that the basal portion of the S. koeneni Biozone can be correlated with the Late Tithonian Standard “Durangites” Zone and that these early spiticeratins records have been found to be associated with a Late Tithonian secondary nannofossil bioevent (Raghodiscus asper (Stradner) first occurrence) in two of the studied sections, a Late Tithonian age is suggested for the earliest records of Spiticeras in Gondwana.
Polyglot or Not? Measuring Multilingual Encyclopedic Knowledge in Foundation Models

In this work, we assess the ability of foundation models to recall encyclopedic knowledge across a wide range of linguistic contexts. To support this, we: 1) produce a 20-language dataset that contains 303k factual associations paired with counterfactuals, 2) evaluate 5 models in a multilingual test, and 3) benchmark a diverse set of 24 models in an English-only test. Meta's LLaMA achieves the highest scores in both multilingual and English-only evaluations. Yet, an analysis of LLaMA's errors reveals significant limitations in its ability to recall facts in languages other than English, plus difficulties related to the location and gender of fact subjects. Overall, our findings suggest that today's foundation models are far from polyglots.
Large-Scale Variability of the Main Thermocline Excited by Stochastic Wind Stress Forcing

Abstract To investigate the role of stochastic forcing in generating decadal variability in the main thermocline circulation, an isopycnic numerical model is forced by the standard monthly climatological forcings plus daily wind stress anomalies. Two statistical models of daily wind stress anomalies are developed. The first one simulates both the temporal and spatial second moment statistics of the observations, whereby it produces realistic daily wind stress anomalies. The second model produces spatially uncorrelated wind stress anomalies that have the observed local variance at each grid point. The results show that a basinwide mode, characterized by a dipole structure in the heat content of the North Pacific, can be excited stochastically. The structure of the mode does not represent an imprint of the atmospheric forcing but is selected by the ocean itself.
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild

Diabetes encompasses a complex landscape of glycemic control that varies widely among individuals. However, current methods do not faithfully capture this variability at the meal level. On the one hand, expert-crafted features lack the flexibility of data-driven methods; on the other hand, learned representations tend to be uninterpretable which hampers clinical adoption. In this paper, we propose a hybrid variational autoencoder to learn interpretable representations of CGM and meal data. Our method grounds the latent space to the inputs of a mechanistic differential equation, producing embeddings that reflect physiological quantities, such as insulin sensitivity, glucose effectiveness, and basal glucose levels. Moreover, we introduce a novel method to infer the glucose appearance rate, making the mechanistic model robust to unreliable meal logs. On a dataset of CGM and self-reported meals from individuals with type-2 diabetes and pre-diabetes, our unsupervised representation discovers a separation between individuals proportional to their disease severity. Our embeddings produce clusters that are up to 4x better than naive, expert, black-box, and pure mechanistic features. Our method provides a nuanced, yet interpretable, embedding space to compare glycemic control within and across individuals, directly learnable from in-the-wild data.
Understanding and predicting ENSO

Throughout the 1960's and 1970's, oceanographers referred to the large-scale warming of the equatorial eastern and central Pacific as El Nino. This anomalous warming was later shown to be associated with anomalies in the upper ocean thermal structure throughout the equatorial Pacific Ocean. At about the same time, scientists realized that the Southern Oscillation was intimately related to the large-scale changes in the tropical Pacific Ocean. In brief, the Southern Oscillation represents the variability in the Indo-Pacific Walker circulation in the tropics, and is manifest as a displacement of the convection over the maritime continent, and is associated with large-scale anomalies in the surface wind and sea level pressure throughout the tropical Pacific (and into the Indian Ocean) basin.
Conﬁguring HRM Practices for Open Innovation: But Can It Deliver?

Though current scholarly interest generates a sustained growth of literature on open innovation, we need to learn more about human resource practices relating to open innovation. Building on the ability-motivation-opportunity (AMO) framework, we demonstrate the differential impact of human resources practice bundles on open innovation. We also find evidence that motivation-enhancing and competency-enhancing practices share a compensating effect on open innovation. Using firm-level data from 2540 Italian manufacturing firms, our study, if not first, contributes to the growing bodies of research on open innovation by bringing forth the human dimension to the forefront and offering a drilled-down practice-level view that needs to be addressed in the literature.
Thermotectonic history of SE China since the Late Mesozoic: insights from detailed thermochronological studies of Hong Kong

The late Mesozoic Yanshanian volcanic arc affected an extensive region of SE China, but the conclusion of magmatism and later evolution are not fully understood. Widespread Yanshanian ignimbrites and their contemporaneous granites exposed in Hong Kong represent a microcosm of this magmatic arc. To constrain the post-magmatic thermal history of the region, we present zircon and apatite fission-track analyses from these rocks. Double dating using laser ablation inductively coupled plasma mass spectrometry U–Pb and fission-track techniques on detrital zircons from post-volcanic Cretaceous sediments is used to further constrain the tectonothermal evolution. The resulting dataset and thermal modelling suggest that the igneous rocks and Cretaceous sediments together experienced post-emplacement or post-depositional heating to >250 °C, subsequently cooling through 120–60 °C after c. 80 Ma. The heating reflects the combined effects of an enhanced geothermal gradient and burial. We interpret the enhanced gradient to represent continuing Yanshanian magmatic activity until c. 100–80 Ma, much later than previously considered. Our data also indicate a long-term, slow cooling (c. 1 °C myr–1) since the early Cenozoic, linked to c. 2–3 km of erosion-driven exhumation. The thermotectonic history of Hong Kong reflects the mid-Cretaceous transition of SE China from an active to a passive margin bordered by marginal basins that formed in the early Cenozoic. Supplementary material: Descriptions of samples, operating conditions of the laser ablation inductively coupled plasma mass spectrometry system and the full dataset of U–Pb dating of detrital zircons are available at www.geolsoc. org.uk/SUP18750.
Occurrence and Formation of Water-Laid Placers

A placer is a deposit of residual or detrital mineral grains in which a valuable mineral has been concentrated by a mechanical agent. The agent is usually running water, and the valuable mineral is usually denser than quartz (for example, gold, diamond, cassiterite, ilmenite, or chromite). It is difficult to overemphasize the importance of placers as sources of mineral wealth; the Witwatersrand (South Africa) paleoplacers, discovered in 1886, alone have provided over half of all the gold ever mined in the world (Pretorius 1976), and alluvial placer deposits of cassiterite in southeast Asia presently are the world's major source of tin (Toh 1978). The earliest evidence of placer mining comes from stone carvings in Egypt dated at 2500 B.C. (MacDonald 1983), and as early as 7 B.C., Strabo pointed out that in Turdetania (Spain) more gold was procured from washing sand in the rivers than by digging in the mines. Given the economic importance of water-laid placers and the long history oftheir exploitation, it is remarkable that they have received so little attention in sedimentary research. Mining and exploration practices for the most part have been guided by empirical rules of thumb that are locally useful but lack any firm physical basis of understanding [see Bateman
Genome-Wide Identification, Evolution, and Expression Pattern Analysis of the GATA Gene Family in Tartary Buckwheat (Fagopyrum tataricum)

GATA is a transcription factor that exerts a vital function in plant growth and development, physiological metabolism, and environmental responses. However, the GATA gene family has rarely been studied in Tartary buckwheat since the completion of its genome. This study used bioinformatics methods to identify GATA genes of Tartary buckwheat and to analyze their subfamily classification, structural composition, and developmental evolution, as well as to discuss the expression patterns of FtGATA genes in different subfamilies. The twenty-eight identified FtGATA genes in the Tartary buckwheat genome were divided into four subfamilies and distributed on eight chromosomes. One pair of tandem repeat genes and eight pairs of fragments were found in chromosome mapping. Spatiotemporal expression patterns of eight FtGATA genes in different subfamilies indicated that the FtGATA gene family has regulatory roles in tissue specificity, fruit development, abiotic stress, and hormonal responses. This study creates a theoretical and scientific foundation for further research on the evolutionary relationship and biological function of FtGATA.
Localization, mapping, and planning in 3D environments

Building a map, localizing within the map, and planning using the map are fundamental problems for mobile robotics. Every mobile robotic system must incorporate some type of solution to all three problems. While the interdependency between mapping and localization is well known as the Simultaneous Localization and Mapping (SLAM) problem, there is a growing understanding in the research community that planning how the robot goes about mapping and exploring an environment (and operating in the environment afterwards) can avoid degenerate conditions and significantly reduce complexity of SLAM. Thus the task of exploring a new environment combines all three problems, since the robot must plan to find actions that reduce uncertainty in both mapping and localization. This combined problem is known as Active SLAM. Independently, SLAM and planning have been solved in small, two dimensional, structured domains. Robots need to move beyond these simple environments. The challenge is to develop real-time Active SLAM methods that allow robots to explore large, three dimensional, unstructured environments, and allow subsequent operation in these environments over long periods of time. But scaling up to truly large environments requires a second key insight beyond Active SLAM: to circumvent the scale limitations inherent in SLAM, the world can be divided up into more manageable pieces, or submaps. The SLAM problem then becomes a segmented SLAM problem, which represents the world with a combined metric and topological map, building metric submaps as necessary and refining the topological relationships between submaps. The contribution of this thesis is a real-time Active SLAM approach that combines a novel evidence grid-based volumetric representation, a robust Rao-Blackwellized particle-filter, a topologically flexible submap segmentation framework, and an integrated stochastic planning method for reducing SLAM uncertainty and predicting possible loop closures based on local map structure. We demonstrate our methods on several robotic platforms in both structured and unstructured large, three dimensional environments.
METAL FRACTIONATION ON FLUVIAL BED SEDIMENTS AND THE RISK ASSESSMENT FOR WATER SUPPLY (AMAZONIAN - BRAZIL)

Concentrations of metallic elements in sediment from Aura River basin between 2008 and 2012 were checked, with implementation of two environmental quality criteria for sediments: enrichment factor and degree of chemical and biological contamination. The results showed that the metals Al, Fe, Mn, Cr, Cu, Ni, Pb and Cd had concentrations very close to the limit safe for aquatic biota, and despite of seasonal fluctuations, some metals reached worrying levels with contamination risk for quality of life human resident near the basin. Near the Aura River mouth there is a pipeline company's state waters, pumping water for Metropolitan Region of Belem. The environmental assessment criteria applied indicated geological enrichment for Fe, Mn, Cr, Ni and Cu, and enrichment of Pb and Cd by the leachate from the landfill closed to drainage basin. According to the criteria of sediments quality used in this study, there is the presence of anthropogenic contamination and impairment of sediments by Pb and Cd.
Thermal imaging of Nisyros volcano (Aegean Sea) using ASTER data: estimation of radiative heat flux

A time series of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images (AST08) have been processed to allow radiative heat flux estimations of the Nisyros volcano. ASTER night-time images were acquired on four different dates: 7 April 2001, 13 June 2002, 26 October 2002 and 23 July 2005. The results show a steady state energy release with heat fluxes ranging from 15 to 30 W m−2 over the craters of Kaminakia, Polyvotis and Stefanos, respectively. It is suggested that this range of values indicates a background heat flux of this volcano following the unrest of 1995–1997, and that the volcano has entered again into the quiet phase. Also, on the basis of the average spatial extent of the thermal anomaly a total radiative heat flux of 36 MW was estimated at the moment of ASTER overpass. Heat flux values for Nisyros are in good agreement with other published estimates derived from low-temperature fumarolic volcanoes (Stromboli and Vulcano, Italy) using Landsat TM data. It is also evidenced that the ASTER radiometer can be used as an important imaging tool for the monitoring of geophysical properties associated to volcanic activity, as is the volcanic heat flux.
Estimation of 24 h continuous cloud cover using a ground-based imager with a convolutional neural network

In this study, we aimed to estimate cloud cover with high accuracy using images from a camera-based imager and a convolutional neural network (CNN) as a potential alternative to human-eye observation on the ground. Image data collected at 1 h intervals from 2019 to 2020 at a staffed weather station, where human-eye observations were performed, were used as input data. The 2019 dataset was used for training and validating the CNN model, whereas the 2020 dataset was used for testing the estimated cloud cover. Additionally, we compared satellite (SAT) and ceilometer (CEI) cloud cover to determine the method most suitable for cloud cover estimation at the ground level. The CNN model was optimized using a deep layer and detailed hyperparam-eter settings. Consequently, the model achieved an accuracy, bias, root mean square error (RMSE), and correlation coefﬁ-cient ( R ) of 0.92, − 0.13, 1.40 tenths, and 0.95, respectively, on the test dataset, and exhibited approximately 93 % high agreement at a difference within ± 2 tenths of the observed cloud cover. This result demonstrates an improvement over previous studies that used threshold, machine learning, and deep learning methods. In addition, compared with the SAT (with an accuracy, bias, RMSE, R , and agreement of 0.89, 0.33 tenths, 2.31 tenths, 0.87, and 83 %, respectively) and CEI (with an accuracy, bias, RMSE, R , agreement of 0.86, − 1.58 tenths, 3.34 tenths, 0.76, and 74 %, respectively), the camera-based imager with the CNN was found to be the most suitable method to replace ground cloud cover observation by humans.