Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalisation of physical habitat-discharge relationships

Physical habitat is increasingly used worldwide as a measure of river ecosystem health when assessing changes to river flows, such as those caused by abstraction. The major drawback with this approach is that defining precisely the relationships between physical habitat and flow for a given river reach requires considerable data collection and analysis. Consequently, widely used models such as the Physical Habitat Simulation (PHABSIM) system are expensive to apply. There is, thus, a demand for rapid methods for defining habitat-discharge relationships from simple field measurements. This paper reports the analysis of data from 63 sites in the UK where PHABSIM has been applied. The results demonstrate that there are strong relationships between single measurements of channel form and river hydraulics and the habitat available for target species. The results can form the basis of a method to estimate sensitivity of physical habitat to flow change by visiting a site at only one flow. Furthermore, the uncertainty in estimates reduces as more information is collected. This allows the user to select the level of investment in data collection appropriate for the desired confidence in the estimates. The method is demonstrated using habitat indicators for different life stages of Atlantic salmon, brown trout, roach and dace.
Improved YOLO-X Model for Tomato Disease Severity Detection using Field Dataset

—In the past decade, the field of automatic plant disease detection has undergone significant complexity. Advancements in convolutional neural network in deep learning have enabled the rapid and precise detection of ailments, facilitated the development of effective treatments and ultimately led to higher crop yields. One of the most challenging scenarios in plant disease occurs when multiple diseases manifest on a single leaf, exacerbating the difficulty of diagnosis due to overlapping symptoms. This study addresses these challenges by employing an enhanced YOLO-X model for detection tomato leaf diseases. The technique presented here enhances the Spatial Pyramid Pooling layer in order to extract valuable features from training data of various sizes more efficiently. We were able to increase the model's ability to identify a broader spectrum of disease symptoms by concatenating variables from multiple layers and varying sizes. In addition, we incorporate a large number of connections to increase the generalizability of the design. The application of an IoU-based (Intersection over Union) regression loss function increases the convergence of the network and the precision of the detection. For experimentation, we created a customized dataset consisting of 1220 tomato plant leaf images from various farms in Southern part of India, encompassing overlapping diseases and varying degrees of severity. The dataset includes images of healthy leaves as well as different severity levels of tomato leaf curl and tomato leaf mold stress on a single leaf. Our suggested improved SPP-based YOLO-X model beats the original YOLO-X model, according to experimental findings, which show an improvement in test dataset accuracy and a 73.42% mean Average Precision on field-collected dataset.
Effects of wetting-drying and stress ratio on anisotropic stiffness of an unsaturated soil at very small strains

The very small strain shear modulus of soil, G0, is affected by many factors including soil properties, current stress state, stress history, and matric suction. Very little research has been conducted on anisotropic shear moduli of unsaturated soils. In this study, the effects of wetting–drying and stress ratio on anisotropic shear stiffness of an unsaturated completely decomposed tuff (CDT) at very small strains have been investigated using a modified triaxial testing system equipped with three pairs of bender elements. During drying and wetting tests, the measured very small strain shear moduli increased in a nonlinear fashion, but at a reduced rate as the matric suction increased. Similar to the stress-dependent soil-water characteristic curves (SDSWCCs), there was hysteresis between the drying and wetting curves showing the variations in shear moduli with matric suction. Variation in suction on the specimens under isotropic conditions produced changes in stiffness anisotropy (expressed as G0(hh)/G0(h.
Lower Ordovician graptolite biozonation and lithofacies of southern Bolivia: relevance for palaeogeographic interpretations

The interpretation of the lithofacies and basin evolution of the early Ordovician of southern Bolivia is based on a number of sections on an E–W transect. Lithostratigraphic units are extremely diachronous and only the available data on the graptolite biostratigraphy enabled an interpretation of the basin evolution. The newly proposed graptolite biozonation includes the biozones of Rhabdinopora flabelliformis, Adelograptus sp. , Araneograptus murrayi, Hunnegraptus copiosus, Tetragraptus phyllograptoides, Expansograptus protobalticus, Expansograptus holmi, Baltograptus minutus, Azygograptus lapworthi and Isograptus victoriae. Isograptus victoriae is the first isograptid identified from Gondwanan South America. The early Ordovician succession of southern Bolivia is the most complete one documented from South America and can be used as a standard for this continent. The faunas are most easily correlated with the faunal succession of Scandinavia and without doubt belong to the Atlantic graptolite faunal province. They show distinct differences from coeval faunas of the Argentine Precordillera, referable to the Pacific faunal province.
Storm-Track Activity in IPCC AR4/CMIP3 Model Simulations

AbstractThe climatological storm-track activity simulated by 17 Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4)/phase 3 of the Coupled Model Intercomparison Project (CMIP3) models is compared to that in the interim ECMWF Re-Analysis (ERA-Interim). Nearly half of the models show significant biases in storm-track amplitude: four models simulate storm tracks that are either significantly (>20%) too strong or too weak in both hemispheres, while four other models have interhemispheric storm-track ratios that are biased by over 10%. Consistent with previous studies, storm-track amplitude is found to be negatively correlated with grid spacing. The interhemispheric ratio of storm-track activity is highly correlated with the interhemispheric ratio of mean available potential energy, and this ratio is biased in some model simulations due to biases in the midlatitude temperature gradients. In terms of geographical pattern, the storm tracks in most CMIP3 models exhibit an equatorward bia.
O3 and NO2 ground‐based measurements by visible spectrometry during Arctic winter and spring 1988

Ozone and nitrogen dioxide have been monitored by ground-based visible spectrometry from ESRANGE base at Kiruna in Sweden (68N, 22E) from mid January until early April 1988. Stratospheric winter was exceptionally long and cold this year and spring final warming developed only in March. Ozone column was found to increase slowly during this period from 400 DU to 450 DU in the average. After February 15, several rapid decreases by 30% lasting a few days have been observed in correlation with advection from the North West. They are indicative of the presence of an ozone minimum above polar regions during the period. The diurnal variation amplitude is in agreement with the current NOX photochemistry assuming the NO2 layer centered around 30 km. As already observed in the Southern polar regions, the day to day and seasonal NO2 variations are closely associated with stratospheric temperature. Calculations and comparison with other experimental data show that this behaviour cannot de interpreted with the current photochemistry.
Experimental study of the system phlogopite-diopside from 3.5 to 17 GPa

Abstract On the basis of both natural samples and experimental studies, clinopyroxene is a potential reservoir for potassium in the Earth’s mantle. The amount of K partitioning into clinopyroxene depends on the phase assemblage present, the bulk composition, pressure, and temperature. To investigate some of these dependencies, subsolidus and melting phase relations in the system phlogopite-diopside have been studied to 17 GPa. In this system, phlogopite becomes unstable with increasing pressure, breaking down to potassium richterite, which in turn breaks down to another K-bearing hydrous phase (phase X), such that a K-rich phase coexists with clinopyroxene to 17 GPa. Clinopyroxenes contain ≤ 1.3 wt% K2O in assemblages of phlogopite + clinopyroxene ± olivine ± liquid at 3-5 GPa, phlogopite + clinopyroxene + garnet ± olivine ± liquid at 7-9 GPa, clinopyroxene + garnet + olivine ± potassium richterite ± liquid at 11 GPa, and clinopyroxene + olivine + garnet + phase X at 14 and 17 GPa. In these assemblages, K is partitioned into hydrous phases or liquid, rather than into the clinopyroxene. By inference, phlogopite (or its higher-pressure breakdown products) is the primary host for K in the mantle (if H2O is present), and any coexisting clinopyroxene has very low concentrations of K. Conversely, the natural occurrence of clinopyroxene with >> 1 wt% K2O requires that phlogopite, potassium richterite, or phase X is not stable in the local source environment of such samples.
Low‐frequency variability in coastal sea level from tide gauges and altimetry

[1] Long sea level observations are fundamental for studies of the low-frequency changes in ocean circulation and climate. Tide gauges provide records several decades long, but their locations are geographically sparse and confined to the coastline. To assess the extent to which tide gauge point measurements represent broader-scale conditions in the adjacent ocean, we compare tide gauge records to altimeter data in their vicinity for the period 1993–2008. The analysis is based on detrended annual mean series and focuses on interannual variability. The best agreement between tide gauge and altimeter series is found for mid-ocean islands in the tropical Pacific and Indian oceans and along the coast of western Australia. Elsewhere, along most continental coasts, root-mean-square differences between the two sea level estimates can be substantial when compared to the observed variability or the expected measurement noise, with the worst correspondence found in western South America, Japan, and eastern Australia. Differences in magnitude as well as poor correlations between the tide gauge and altimeter estimates are involved. Although land motions and measurement errors can be a factor, results point to the presence of considerable short spatial structure in coastal sea level at interannual time scales, which can be related to the low-frequency dynamics of coastally trapped circulations, western boundary currents and associated eddy regimes, or response to river runoff. Knowing whether coastal sea level variability becomes more spatially homogeneous at longer time scales must await longer sea level records.
A Novel Class-Imbalanced Ship Motion Data-Based Cross-Scale Model for Sea State Estimation

Sea state estimation (SSE) is significant to the development of autonomous ships, which can enhance the sustainable development of maritime transportation. Traditional model-based methods are limited by their drawbacks, such as high costs and inaccurate estimations. The deep learning model shows superior performance, but it requires that the sample quantity for each sea state should be almost the same. Since the occurrence probability of each state is different, the ships mainly work in low sea states, and the collected ship motion data for different sea states are highly imbalanced. This work proposes a novel class-imbalanced ship motion data-based cross-scale model for SSE. The model consists of three major components: a multi-scale feature learning module, a cross-scale feature learning module, and a prototype classifier module. The multi-scale and cross-scale feature learning modules are designed to learn abundant coarse and fine-level features from the ship motion data. The prototype classifier is utilized to overcome the limitation of the conventional softmax classifier to produce better estimates. Our research highlights our model’s remarkable scalability and versatility with 30 publicly available datasets in time series classification, demonstrating superior performance over baseline methods in 21 cases. Notably, it outperformed ShapeNet by 5.72% and EDI by 26.3%. We further validated our model’s proficiency using ship motion datasets, consistently surpassing eight state-of-the-art baselines and five class-imbalanced learning methods. Ablation and sensitivity studies, emphasize the critical role of each model component. Our findings underscore the model’s robustness and its potential to advance time series classification in diverse domains.
Grain Size of Quartz as an Indicator of Winter Monsoon Strength on the Loess Plateau of Central China during the Last 130,000 Yr

Abstract The Chinese loess-paleosol sequence constitutes an important record of variations in Asian monsoon climate over the past 2.4 myr. Magnetic susceptibility of loess and paleosols has been used as a proxy for summer monsoon intensity, while median grain size has been regarded as a measure of the strength of winter monsoon winds that were responsible for most of the dust transport. However, median grain size is only an approximate index of winter monsoon strength because both paleosols and loess have been modified, to various degrees, by weathering processes that have produced pedogenic clay. The quartz component of loess and paleosols is largely unaffected by weathering processes and therefore constitutes a more reliable proxy index of monsoon wind strength. Median grain size (Qmd) and maximum grain size (Qmax) values of monomineralic quartz isolated from the loess-paleosol section at Luochuan in the central Loess Plateau are characterized by two main intervals during the last ca. 130,000 yr when these parameters were significantly greater than 9 and 85 μm, respectively, and three main intervals when they were lower. The data imply that the winter monsoon weakened during the intervals with low Qmd and Qmax values, which coincide with marine oxygen isotope stages 5, 3, and 1, and was strongest ca. 67,000 and 20,000 yr ago during isotope stages 4 and 2. However, both quartz grainsize records display second-order high-frequency, high-amplitude variations, which are lacking in the magnetic susceptibility record, that imply rapid and significant changes in atmospheric conditions that affect dust transport and deposition.
Tetragonal structure of CaSiO3 perovskite above 20 GPa

High‐resolution synchrotron X‐ray diffraction measurements were performed at 20–46 GPa on CaSiO3 perovskite (Ca‐pv) synthesized in a laser heated diamond cell. After heating, we observed peak splittings for the cubic 200 and 211 diffraction lines, attributable to a tetragonal distortion of Ca‐pv. The bulk modulus of the tetragonal phase is 255 ± 5 GPa for K0T′ = 4. The observed intensities and d‐spacings of the split lines indicate that the c‐axis is shorter than the a‐axes (c/a = 0.993 − 0.996). This is compatible with either SiO6 octahedron rotation around the a‐axes or SiO6 octahedron distortion (shorter Si‐O bonds along the c‐axis than the a‐axes), provided that the observed phase has a tetragonal unit cell. These structural distortions in Ca‐pv can affect its physical properties and capacity for large cations.
Path-Coefficient study in Maize Grain Yield with Yield Attributes

Bio-metric observations recorded in the field trial conducted at the Agricultural College and Research Institute. Madurai to study the effect of plant density and mode of nitrogen application on Deccan hybrid maize were subjected to a path coefficient analysis to study the cause and effect of the yield attributes on the grain yield. The three yield attributes viz. grain number per cob. length of cob and 1000 grain weight exhibited posi tive and highly significant correlation with grain yield. Of these 1000 grain weight had the maximum direct effect while the length of cob. the grain number per cob had their influence on the yield through 1000 grain weight.
Modelling Holocene tides on the NW European continental shelf

A numerical model of the M2 tide on the NW European continental shelf has been used to estimate the effect of uniform depth changes, of the order of the Holocene eustatic variation, on tidal elevation amplitudes, sand transport paths, and the position of tide-generated fronts. Minor changes are indicated around the outer shelf, but the Southern Bight of the North Sea is seen to develop from a quiet, shallow sea of low tidal amplitude (< 5m) to its present state of vigorous tidal action with mean coastal amplitudes around 2m. Shifts in the position and strength of amphidromes are shown to cause strong spatial gradients in the rate of change of tidal amplitudes in the Irish Sea and English Channel, but the tidal contribution to absolute changes in mean high water levels is found to be everywhere less than 5% of the eustatic contribution. Development of this modelling approach requires more realistic description of bathymetric variation and an estimate of ocean tidal changes.
Structural elements of the southern Tethyan Himalaya crust from wide‐angle seismic data

A deep seismic common midpoint (CMP) profile, shot across the southern margin of the Tethyan Himalaya as the first stage of Project International Deep Profiling of Tibet and the Himalaya (Indepth), imaged the top (Main Himalayan Thrust or MHT) and bottom (Moho) of the Indian continental crust underthrusting the Himalaya. We used portable seismographs to record the CMP-profile shots at a wide range of offsets, up to 155 km. Our short-offset data corroborate the CMP-profile data, while our large-offset data are dominated by a band of reflectivity. We interpret the bright onset of this reflective band as the basal detachment of the South Tibetan Detachment system and a phase at the end of the reflective band as the MHT. We used the CMP-profile first-break data to model the uppermost 2 km in detail. The depth of young extensional basins of the Yadong rift system along the CMP profile was constrained to a maximum of 2 km, yielding a throw of 4.6 km across the eastern flank of the rift and a rough estimate of approximately 1.5% east-west extension by normal faulting in the Tethyan Himalaya. The wide-angle data were used to construct a crustal seismic-velocity model down to the MHT. The South Tibetan Detachment System (STDS) basal detachment reflector is observed dipping 12.5°NNE from a depth of about 6 km beneath the surface under the south end of the CMP profile to a depth of 22 km, then flattening to a dip of only 2.5°NNE. Thus our observations suggest that the STDS basal detachment is a deep-rooted basement fault. For the MHT we observe a dip of 7.5°NNE from 20 km depth below sea level at the crest of the High Himalaya crystalline sheet to 36 km below sea level (40 km beneath the surface) at a distance of about 70 km south of the Indus-Yarlung Suture (IYS). From geometrical arguments we suggest that Indian crust underthrusts the surface expression of the IYS within the crust but does not form the lower crust of central and northern Tibet.
West Antarctica: Problem child of Gondwanaland

The evolution of West (Lesser) Antarctica and its relation to East (Greater) Antarctica have major implications for global plate interactions, paleoclimate, and paleobiogeography, as well as Gondwanaland reconstruction. Analyses of marine geophysical data still lead to seemingly unacceptable overlap between the Antarctic Peninsula and the South American continent or else to geologically questionable relationships. A review of the relevant geological and geophysical data indicates that the problem lies in microplate movement and crustal thinning within West Antarctica during Gondwanaland breakup in the late Mesozoic and Cenozoic. The available data allow a range of possible reconstructions with West Antarctica subdivided into several discrete or semidiscrete microplates. Final solution of this problem requires additional geological and, particularly, geophysical data from West Antarctica as a whole, and the Weddell Sea-Ross Sea embayment in particular. Meantime, it seems inadvisable to use the present continental outline of Antarctica on the Pacific side of the Transantarctic Mountains in reconstructing Gondwanaland.
IcoCap: Improving Video Captioning by Compounding Images

Video captioning is a more challenging task compared to image captioning, primarily due to differences in content density. Video data contains redundant visual content, making it difficult for captioners to generalize diverse content and avoid being misled by irrelevant elements. Moreover, redundant content is not well-trimmed to match the corresponding visual semantics in the ground truth, further increasing the difficulty of video captioning. Current research in video captioning predominantly focuses on captioner design, neglecting the impact of content density on captioner performance. Considering the differences between videos and images, there exists an another line to improve video captioning by leveraging concise and easily-learned image samples to further diversify video samples. This modification to content density compels the captioner to learn more effectively against redundancy and ambiguity. In this article, we propose a novel approach called Image-Compounded learning for video Captioners (IcoCap) to facilitate better learning of complex video semantics. IcoCap comprises two components: the Image-Video Compounding Strategy (ICS) and Visual-Semantic Guided Captioning (VGC). ICS compounds easily-learned image semantics into video semantics, further diversifying video content and prompting the network to generalize contents in a more diverse sample. Besides, learning with the sample compounded with image contents, the captioner is compelled to better extract valuable video cues in the presence of straightforward image semantics. This helps the captioner further focus on relevant information while filtering out extraneous content. Then, VGC guides the network in flexibly learning ground truth captions based on the compounded samples, helping to mitigate the mismatch between the ground truth and ambiguous semantics in video samples. Our experimental results demonstrate the effectiveness of IcoCap in improving the learning of video captioners. Applied to the widely-used MSVD, MSR-VTT, and VATEX datasets, our approach achieves competitive or superior results compared to state-of-the-art methods, illustrating its capacity to handle the redundant and ambiguous video data