Miracle-dz/UniFAR-FTUs huggingface dataset:
Intention to Use Eight Antenatal Care Model and Associated Factors Among Pregnant Women Who Come for Antenatal Care in Northwest of Amhara Region Referral Hospitals, Ethiopia, 2021

Background:Maternal and perinatal mortality is highly associated with four or fewer antenatal care (ANC) visit. Due to this, WHO develop a new model called minimum of eight antenatal care (ANC8+) contact. This model is used to re-think and re-design the service through context speci�c expectations. Besides, the model is beyond survival, aim to maximize health and wellbeing of women even at post pregnancy motherhood, and social health of the family and community at large. Since shortage of related studies in Ethiopia so far, this study aim to address those gaps. Objective:To assess intention to use ANC8+ model and associated factors among pregnant women who come for antenatal care contact in Northwest of Amhara region referral hospitals, Ethiopia, 2021. Method:An institution-based cross-sectional study was conducted from September 1st to October 30th, 2021 in Northwest of Amhara regional state referral hospitals. A multistage sampling technique was used to select 847 eligible women. A structured, pretested, and interviewer-administered questionnaire was employed. EPI data version 4.6 and SPSS version 23 were used for data entry and analysis, respectively. Binary logistic regression model was �tted to identify factors associated with pregnant women intention to use ANC8+ model. A p-value of ≤ 0.05 was used to declare statistical association in the last model. Result:Overall, 739 (88.8%, 95% CI: 86.68, 90.97) women had the intention to use ANC8+. Pregnant women in the age group between 20 to 30 years (AOR = 19.84, 95% CI: 3.01, 130.64), and ≥ 31 years (AOR = 3.92, 95% CI: 1.79, 8.58), being farmer in occupation (AOR = 0.13, 95% CI: 0.04, 0.43), government employee (AOR = 5.58, 95% CI: 1.64, 18.97), good attitude (AOR = 38.76, CI 5.99, 250.73), positive subjective norm (AOR = 10.83, 95% CI: 4.36, 26.92) and perceived behavioral control (AOR = 8.98, 95% CI: 3.26, 24.71) were factors associated with women’s intention to use ANC8+. Conclusion:More than four-fths of the pregnant women had intention to use ANC8+. Increase in age, being the government employee , having good attitude, positive subjective norm and perceived behavioral control were positively, while being a farmer negatively associated to intention to use ANC8+ contact. Therefore, empowering women, developing socio cultural integrity with the health system through health education and trainings to local health cadres and community leaders would possibly increase the intention of using ANC8+.
Spectral Masked Autoencoder for Few-Shot Hyperspectral Image Classification

Though deep learning methods have achieved the state-of-the-art performance for hyperspectral image (HSI) classification, they often highly rely on large amount of samples for training, and introduce few-shot challenge due to the lack of labeled samples. In this paper, a self-supervised method is presented for HSI classification in the few-shot scenario, where masked autoencoder is employed to reconstruct the masked bands in spectral domain for model pretraining with limited labeled sample, namely Spectral-MAE. The proposed method not only avoids the overfitting via the pretraining, but also provides the model’s ability for effective feature extraction while avoiding the high spatial redundancy. Experiments conducted verify the effectiveness of the proposed method for HSI classification in few-shot situation as compared with other methods.
Using Squeeze-and-Excitation Vision Transformer with Local Feature Fusion for Ship Classification in SAR Images

The categorization of synthetic aperture radar (SAR) ships primarily focuses on large ships with distinct features, but accurately identifying SAR ships remains challenging due to limited samples in certain ship categories. In this study, we propose a compressed and excited Vision Transformer model based on local feature fusion. This model leverages local feature fusion and channel modeling through the squeezing-and-excitation (SE) mechanism to effectively balance the contributions of each feature. By incorporating better local information, we are able to extract deeper features even from small datasets. To evaluate the efficacy of our model, we trained it on the three-category OpenSARShip 2.0 dataset and conducted experiments. The results demonstrate that our proposed model achieves superior classification accuracy compared to existing methods.
3D Reconstruction of Pancake Sea Ice Using Lidar and Cameras

This paper presents a preliminary investigation into the 3D reconstruction of pancake sea ice using a multi-sensor approach with LiDAR (Livox Avia) and depth cameras (Intel Realsense D455). Pancake sea ice is a type of ice formed in the dynamic region of the Antarctic Marginal Ice Zone (MIZ). Current models simplify the pancake floe geometry, neglecting the effects ice floe geometry has on the mobility of the sea ice. A series of scans were taken on the SCALE Winter 2022 expedition where a static approach was explored using the customised multi-sensor imaging rig. A pipeline for processing the data using the advantages of a multi-sensor system was explored. Statistical data using established methods in literature resulted in centimetre level roughness measurements. A discussion of the validation and limitations of the sensors is presented.
Exchange equilibria of potassium in some red, black and alluvial soils of India. I, Effect of displacing cations

Exchange equilibria of K+ versus Ca2+, NH4+ and Na+ were studied in seven benchmark soils representing red, black and alluvial soil groups of India. At low K saturation, illitic (alluvial) soils showed higher K selectivity than smectitic (black) and kaolinitic (red) soils. Fine textured smectitic soils maintained high K selectivity even at high K saturation. Potassium was usually preferred to Ca2+ throughout the range of K saturation encountered, except in one kaolinitic and one illitic soil, where cation preference was reversed at higher K saturation. In the K+-NH4+ exchange system, all the soils in general preferred NH4+ to K+. Smectitic soils preferred K+ to Na+, whereas kaolinitic and illitic soils preferred Na+ to K+. With an increase in K saturation, the activity coefficients of adsorbed Ca2+, NH4+ and Na+ always decreased, but that of K+ initially increased and then decreased to unity. The relative escaping tendency of K from the adsorbed to the solution phase was greater in the K+-Ca2+ system followed by the K+-NH4+ and K+-Na+ systems.
Using First Name Information to Improve Race and Ethnicity Classification

ABSTRACT This article uses a recent first name list to develop an improvement to an existing Bayesian classifier, namely the Bayesian Improved Surname Geocoding (BISG) method, which combines surname and geography information to impute missing race/ethnicity. The new Bayesian Improved First Name Surname Geocoding (BIFSG) method is validated using a large sample of mortgage applicants who self-report their race/ethnicity. BIFSG outperforms BISG, in terms of accuracy and coverage, for all major racial/ethnic categories. Although the overall magnitude of improvement is somewhat small, the largest improvements occur for non-Hispanic Blacks, a group for which the BISG performance is weakest. When estimating the race/ethnicity effects on mortgage pricing and underwriting decisions with regression models, estimation biases from both BIFSG and BISG are very small, with BIFSG generally having smaller biases, and the maximum a posteriori classifier resulting in smaller biases than through use of estimated probabilities. Robustness checks using voter registration data confirm BIFSG's improved performance vis-a-vis BISG and illustrate BIFSG's applicability to areas other than mortgage lending. Finally, I demonstrate an application of the BIFSG to the imputation of missing race/ethnicity in the Home Mortgage Disclosure Act data, and in the process, offer novel evidence that the incidence of missing race/ethnicity information is correlated with race/ethnicity.
Express saccades and visual attention

Abstract One of the most intriguing and controversial observations in oculomotor research in recent years is the phenomenon of express saccades in monkeys and man. These are saccades with such short reaction times (100 msec in man, 70 msec in monkeys) that some experts on eye movements still regard them as artifacts or as anticipatory reactions that do not need any further explanation. On the other hand, some research groups consider them not only authentic but also a valuable means of investigating the mechanisms of saccade generation, the coordination of vision and eye movements, and the mechanisms of visual attention. This target article puts together pieces of experimental evidence in oculomotor and related research – with special emphasis on the express saccade – to enhance our present understanding of the coordination of vision, visual attention, and the eye movements subserving visual perception and cognition. We hypothesize that an optomotor reflex is responsible for the occurrence of express saccades, one that is controlled by higher brain functions involved in disengaged visual attention and decision making. We propose a neural network as the basis for more elaborate mathematical models or computer simulations of the optomotor system in primates.
Can One Gauge the Shape of a Basin

This paper investigates the effects of geometrical factors characterizing the shape of a river basin on the features of its hydrologic response. In particular, we wonder if by measuring the hydrologic response (i.e., gauging) the salient geomorphic features of the basin can be recovered. We argue that the basic structure of the channel network tends, in ideal conditions, to yield some universal characters of the width function W(x) defining the relative proportion of a contributing area at a distance x from the outlet. W(x) exhibits low-frequency features, which are geometry-dominated, and high-frequency features determined by recurrent aggregation patterns. It is suggested that given the shape of the basin one can indeed forecast in a rational manner the main characters of the hydrologic response which are imprinted in reproducible width functions. However, the inverse problem (i.e., the determination of the shape from the measure of the hydrologic response) is less solidly defined because of the possible loss of irretrievable information induced by the dynamics of runoff processes. Therefore the question posed in the title cannot be solved in general, although many elements for a general theory are seemingly established.
Smartflow: Enabling Scalable Spatiotemporal Geospatial Research

BlackSky introduces Smartflow, a cloud-based framework enabling scalable spatiotemporal geospatial research built on open-source tools and technologies. Using STAC-compliant catalogs as a common input, heterogeneous geospatial data can be processed into standardized datacubes for analysis and model training. Model experimentation is managed using a combination of tools, including ClearML, Tensorboard, and Apache Superset. Underpinning Smartflow is Kubernetes, which orchestrates the provisioning and execution of workflows to support both horizontal and vertical scalability. This combination of features makes Smartflow well-suited for geospatial model development and analysis over large geographic areas, time scales, and expansive image archives.We also present a novel neural architecture, built using Smartflow, to monitor large geographic areas for heavy construction. Qualitative results based on data from the IARPA Space-based Machine Automated Recognition Technique (SMART) program1 are presented that show the model is capable of detecting heavy construction throughout all major phases of development.
Delamination in collisional orogens: Thermomechanical modeling

[1] Modes of mantle delamination in collision zones are discussed in the light of 2D numerical modeling. Freely evolving thermomechanical models take into account phase changes in the mantle and melting in the crust. Distinct modes are identified, in which orogens undergo mantle delamination concurrently or after collision. Delamination propagates along the Moho of the subducted plate together with the retreating trench, provided that slab pull is sufficient and that the meta-stability of the crust-lithospheric mantle interface is overcome. Topography is an instantaneous response to delamination and migrates with the focused and localized separation between crust and lithospheric mantle (delamination front). Early exhumation of high-pressure rocks is followed by exhumation of high-temperature, partially molten rocks. Convective stabilization of delamination outlasts slab break-offs and impedes renewed build-up of mechanically strong lithospheric mantle by static cooling. Parameter studies investigate the sensitivity of delamination to the age of the subducted oceanic plate, the collision rate, the mantle rheology, and explore the effects of melting and sedimentation. Mantle flow patterns that form around delamination and subduction are sensitive to and often limited by the semi-permeable 670 km spinel-perovskite transition, demonstrating that phase-changes are essential factors. Delamination may account for the formation of complex boundary zones between continents, such as between Africa and Europe in the Mediterranean, where transient compression and extension, the lack of mantle lithosphere, and the exhumation of high-grade metamorphic core complexes are features also obtained in our modeling results.
InSAR-Based Atmospheric Products for Assimilation in NWP: Perspectives and Challenges

InSAR maps of water vapor can improve the accuracy of Numerical Weather Prediction (NWP) models, especially under extreme precipitation events. However, integrating InSAR data into NWP models is challenging due to the differential nature and absolute phase ambiguity introduced by the unwrapping algorithm. To address this, we propose a new approach that uses ERA5 reanalysis data produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) to estimate the absolute epoch from InSAR data. The proposed method is based on constrained least-squares estimation, and ERA5 data are used as a first guess to untangle distinct atmospheric components without applying additional assumptions or external measurements. This approach will allow us to obtain absolute maps over regions without external in situ measurements (e.g., GNSS or radiosondes). The results are validated using a large GNSS dataset, improving about 29% over the field of the original ERA5.
China's environment in the 1980s: some critical changes

No large, poor and populous country has experienced such a rapid socioeconomic transformation as China during the reforms of the 1980s. At the end of the 1970s, as the country started to shed the legacy of Maoism, its population of 975 million generated GNP of 400 billion renminbi (Rmb), or 410 Rmb per capita; a decade later 1.1 12 billion Chinese produced GNPof 1.568 trillion RMb (1410 Rmb per capita), nearly a fourfold rise in absolute and more than threefold rise in relative terms (1). Even when adjusted for inflation these multiples remain impressive: roughly two and 1.75. Malnutrition still affects nearly a tenth of China's population, including one-fifth of its children (2), but the country's average per capita food availability is now only 7% behind the Japanese mean (3). Life expectancy at birth is now almost 70 years, an unparalleled record among poor populous nations (4). But these economic successes and notable advances in the quality of life have been bought at the cost of very heavy environmental degradation as they accelerated already worrisome trends of the previous generation (5).
Evaluating Data Augmentation for Grapevine Varieties Identification

The grapevine variety identification is important in the wine’s production chain since it is related to its quality, authenticity and singularity. In this study, we addressed the data augmentation approach to identify grape varieties with images acquired in-field. We tested the static transformations, RandAugment, and Cutmix methods. Our results showed that the best result was achieved by the Static method generating 5 images per sample (F1 = 0.89), however without a significative difference if compared with RandAugment generating 2 images. The worst performance was achieved by CutMix (F1 = 0.86).
The theropod that wasn't: an ornithopod tracksite from the Helvetiafjellet Formation (Lower Cretaceous) of Boltodden, Svalbard

Abstract We re-examine a Lower Cretaceous dinosaur tracksite at Boltodden in the Kvalvågen area, on the east coast of Spitsbergen, Svalbard. The tracks are preserved in the Helvetiafjellet Formation (Barremian). A sedimentological characterization of the site indicates that the tracks formed on a beach/margin of a lake or interdistributary bay, and were preserved by flooding. In addition to the two imprints already known from the site, we describe at least 34 additional, previously unrecognized pes and manus prints, including one trackway. Two pes morphotypes and one manus morphotype are recognized. Given the range of morphological variation and the presence of manus tracks, we reinterpret all the prints as being from an ornithopod rather than a theropod, as previously described. We assign the smaller (morphotype A, pes; morphotype B, manus) to Caririchnium billsarjeanti. The larger (morphotype C, pes) track is assigned to Caririchnium sp. , differing in size and interdigital angle from the two described ichnospecies C. burreyi and C. billsarjeanti. The occurrence of a quadrupedal, small to medium-sized ornithopod in Svalbard is puzzling, considering the current palaeogeographical reconstructions and that such dinosaur tracks have mainly been described from Europe but not North America.
Temporal Variation of Threshold Segmentation-Based Mangrove Mapping Indices in Karimunjawa-Kemujan Islands with Sentinel Images

Mangroves are essential vegetation that makes coastal communities resilient to water-related disasters while also helping in climate change mitigation as effective carbon sinks. However, they are subject to numerous stressors and threats. This study analyzed and compared the temporal variation of threshold segmentation-based mangrove mapping indices on quarterly-composited Sentinel imagery of Karimunjawa-Kemujan Islands as an alternative to using machine learning classification algorithms. Results show that Mangrove Vegetation Index (MVI), Automatic Mangrove Map and Index (AMMI), and SWIR Bands (SWIRB) had good separability potential and accuracies exceeded 80% in all quarters. However, SWIRB yielded the best results in simplicity, accuracy, minimal variation, and agreement with the proponent’s set threshold.
Intracranial Stenoses Transcranial Color-Coded Sonography of Contrast-Enhanced Three-Dimensional

BACKGROUND AND PURPOSE: Intracranial stenoses are associated with a considerable number of strokes each year. The clinical value of a workstation-based three-dimensional (3D) reconstruction system for transcranial color-coded sonography was evaluated in patients with intracranial stenosis or occlusion. METHODS: Twenty-six patients (13 men, 13 women; mean age, 57 years (cid:1) 12 [SD]) with 36 intracranial stenoses or occlusions, as detected at two-dimensional (2D) color Doppler imaging (CDI) and digital subtraction angiography (DSA), underwent Levovist-enhanced power Doppler imaging (PDI), with subsequent 3D reconstruction. A workstation connected to a magnetic sensor capable of spatial localization of the probe was used to reconstruct 3D images of the circle of Willis from serial PDI images. RESULTS: At DSA, seven (19%) stenoses were estimated to less than 50%, 24 (67%) were 50% or more, and five (14%) were occluded. DSA and 3D-PDI estimates of the degree of stenosis agreed in 33 cases (92%), with a weighted (cid:2) value of 0.86. Disagreement occurred with two subtotal basilar artery stenoses and one subtotal middle cerebral artery stenosis, which were evaluated as being complete occlusions at 3D-PDI. Interobserver agreement between two experienced 3D investigators in estimating the percentage of stenosis was high (correlation coefficient, .98). CONCLUSION: 3D-PDI enables the investigator to reconstruct virtually any arbitrary viewing angle. Compared with conventional CDI, 3D-PDI offers easier spatial assessment of intracranial stenoses, and its findings are sufficiently correlated with angiographic findings. Because different investigators can postprocess the same 3D data, improving reproducibility and reducing investigator dependency in transcranial color-coded sonography may be possible.
The Effects of Gamifying Mathematics Lessons at High School Level

: Gamification encompasses the utilization of "playful" or "game-like" elements within non-gaming contexts. It finds diverse applications, primarily within the realms of education/training and the workplace, with the aim of enhancing teamwork and productivity. Nonetheless, the concept of gamification remains a topic of significant debate. Several authors caution that gamification may undermine intrinsic motivation to learn or perform, particularly among younger audiences. Furthermore, the research community increasingly emphasizes potential negative consequences resulting from specific gamification mechanics, such as competition. In this article, we present an approach to gamification that combines competitive elements, albeit at the level of student groups rather than individuals. The idea is to minimize the exposure of underperforming individuals while capitalizing on collaborative group dynamics, wherein stronger students provide support to weaker ones. We conducted a quasi-experiment, comparing motivation and performance between a gamified classroom scenario and a conventional, non-gamified scenario. The results indicate that the proposed gamification approach boosts motivation and performance in contrast to the non-gamified condition. These findings contribute to a deeper comprehension of the effects of gamification and offer a realistic perspective on its beneficial impacts within educational settings
Deep Learning and Cloudy Optical Time Series: A Case of Study with LSTM to Map LULC in Pantanal

Cloud and cloud shadows are a main source of concern when using dense time series of optical remote sensing images. Machine learning has the potential to effortlessly overcome this barrier using Long Short-Term Memory (LSTM), which is a deep learning algorithm created to analyze time series and has parts dedicated to suppress irrelevant information. In this context, we evaluated the ability of models with LSTM layers to create LULC maps using either cloudy or gap-filled Landsat-8/OLI time series for Pantanal. Five different LSTM models were trained with tenfold cross validation using samples gathered by the authors. Our results indicate that simple models are more accurate with filled time series, but this difference in accuracy was not present in more complex models. We also present a LULC map created for the entire Pantanal.