Miracle-dz/UniFAR-FTUs huggingface dataset:
Variability of soil moisture proxies and hot days across the climate regimes of Australia

The frequency of extreme events such as heat waves are expected to increase due to the effect of climate change, particularly in semiarid regions of Australia. Recent studies have indicated a link between soil moisture deficits and heat extremes, focusing on the coupling between the two. This study investigates the relationship between the number of hot days (Tx90) and four soil moisture proxies (Standardized Precipitation Index, Antecedent Precipitation Index, Mount's Soil Dryness Index, and Keetch‐Byram Drought Index), and how the strength of this relationship changes across various climate regimes within Australia. A strong anticorrelation between Tx90 and each moisture index is found, particularly for tropical savannas and temperate regions. However, the magnitude of the increase in Tx90 with decreasing moisture is strongest in semiarid and arid regions. It is also shown that the Tx90‐soil moisture relationship strengthens during the El Niño phases of El Niño–Southern Oscillation in regions which are more sensitive to changes in soil moisture.
Research on Risk Contagion in ESG Industries: An Information Entropy-Based Network Approach

Sustainable development is a practical path to optimize industrial structures and enhance investment efficiency. Investigating risk contagion within ESG industries is a crucial step towards reducing systemic risks and fostering the green evolution of the economy. This research constructs ESG industry indices, taking into account the possibility of extreme tail risks, and employs VaR and CoVaR as measures of tail risk. The TENET network approach is integrated to to capture the structural evolution and direction of information flow among ESG industries, employing information entropy to quantify the topological characteristics of the network model, exploring the risk transmission paths and evolution patterns of ESG industries in an extreme tail risk event. Finally, Mantel tests are conducted to examine the existence of significant risk spillover effects between ESG and traditional industries. The research finds strong correlations among ESG industry indices during stock market crash, Sino–US trade frictions, and the COVID-19 pandemic, with industries such as the COAL, CMP, COM, RT, and RE playing key roles in risk transmission within the network, transmitting risks to other industries. Affected by systemic risk, the information entropy of the TENET network significantly decreases, reducing market information uncertainty and leading market participants to adopt more uniform investment strategies, thus diminishing the diversity of market behaviors. ESG industries show resilience in the face of extreme risks, demonstrating a lack of significant risk contagion with traditional industries.
Satellite estimation of photosynthetically active radiation in Southeast Asia: Impacts of smoke and cloud cover

[1] Since large-scale variations in photosynthetically active radiation (PAR) influence the terrestrial carbon sources and sinks through the plant photosynthesis variations, large-scale evaluation of PAR is required. In the present study a simple PAR estimation model was developed for Southeast Asia, where large-scale forest fires occurred during El Nino years. The model considered the smoke aerosol released by forest fires using satellite-based smoke detection methods. A comparison study with ground-based solar radiation data for Malaysia and Thailand indicated that the current model could estimate monthly PAR with 10% (root-mean-square) accuracy and would successfully trace the seasonal and year-to-year variations in PAR, including the forest fire periods. During the peak-smoke month in Indonesia, September 1997, the reduction of PAR by smoke reached 63–75% in the center of the Kalimantan and Sumatra Islands. From the analyses of the smoke and cloud cover impacts on PAR in 1997–1999, annual PAR variations were found to be mostly regulated by smoke variations on the Malay Peninsula, Sumatra, and Kalimantan Islands and cloud cover variations on the Indo-China Peninsula. Thus annual variations in PAR changed with location. These variations did not simply correlate with year-to-year variations in cloud cover associated with the El Nino and La Nina cycle, but exhibited more complicated spatial variations due to the existence of smoke in Southeast Asia.
Exploiting the Features of Clinical Judgment to Improve Assessment of Disease Severity in the Emergency Department: An Acutelines Study

Background: Clinical judgment, also known as gestalt or gut feeling, can predict deterioration and can be easily and rapidly obtained. To date, it is unknown what clinical judgement precisely entails. The aim of this study was to elucidate which features define the clinical impression of health care professionals in the ED. Method: A nominal group technique (NGT) was used to develop a consensus-based instrument to measure the clinical impression score (CIS, scale 1–10) and to identify features associated with either a more severe or less severe estimated disease severity. This single-center observational cohort study included 517 medical patients visiting the ED. The instrument was prospectively validated. The predictive value of each feature for the clinical impression was assessed using multivariate linear regression analyses to adjust for potential confounders and validated in the infection group. Results: The CIS at the ED was associated with ICU admission (OR 1.67 [1.37–2.03], p < 0.001), in-hospital mortality (OR 2.25 [1.33–3.81], p < 0.001), and 28-day mortality (OR 1.33 [1.07–1.65], <0.001). Dry mucous membranes, eye glance, red flags during physical examination, results of arterial blood gas analysis, heart and respiratory rate, oxygen modality, triage urgency, and increased age were associated with a higher estimated disease severity (CIS). On the other hand, behavior of family, self-estimation of the patient, systolic blood pressure, and Glascow Coma Scale were associated with a lower estimated disease severity (CIS). Conclusion: We identified several features that were associated with the clinical impression of health care professionals in the ED. Translating the subjective features and objective measurements into quantifiable parameters may aid the development of a novel triage tool to identify patients at risk of deterioration in the ED.
QUANTITES DE MATIERES ORGANIQUES ASSOCIEES AUX SOLS DU DOMAINE FERRALLITIQUE AU CAMEROUN

La densité apparente et la teneur en carbone ayant été mesurées dans une quarantaine de projïls du domaine ferrallitique au Cameroun, les quantités globales de matière organique présentes par unité de surface dans diflérents sols ont pu être calculées. Les sols des savanes du centre et les sols des forêts denses du sud sont plus spécialement comparés : les quantités globales de matière organique, plus régulières que les teneurs de l’horizon Ai, sont à peu près équivalentes dans ces deux milieux de pédoclimats si différents. Par contre, la répartition verticale de la matière organique, et sa proportion relativement au plasma argileux, ne sont pas les mêmes. Ces quantités globales sont nettement plus importantes dans les sols d’altitude (montagnes de l’ouest) où le climat est assez uniformément humide. Elles sont au contraire plus faibles dans la partie nord du plateau de I’Adamaoua, où le contraste saisonnier est particulièrement accusé. Les différences de pédoclimat n’interviendraient donc sur ce stock global qu’a partir de certains seuils. Les poids de matière organique sont confrontés ensuite aux poids de d@érentes parties de la matière végétale associée à ces sols, parties aériennes, litière, système racinaire. Mais ces données, tirées surtout de la littérature, sont incomplètes et comme notre approche est uniquement quantitative, on s’est limité à Jixer quelques ordres de grandeur, et à établir des relations, sans préjuger des mécanismes.
Residence time distributions in surface transient storage zones in streams: Estimation via signal deconvolution

Little is known about the impact of surface transient storage (STS) zones on reach‐scale transport and the fate of dissolved nutrients in streams. Exchange with these locations may influence the rates of nutrient cycling often observed in whole‐stream tracer experiments, particularly because they are sites of organic matter collection and lower flow velocities than those observed in the thalweg. We performed a conservative stream tracer experiment (slug of dissolved NaCl) in the Ipswich River in northeastern Massachusetts and collected solute tracer data both in the thalweg and adjacent STS zones at three locations in a fifth‐order reach. Tracer time series observed in STS zones are an aggregate of residence time distributions (RTDs) of the upstream transport to that point (RTDTHAL) and that of the temporary storage within these zones (RTDSTS). Here we demonstrate the separation of these two RTDs to determine the RTDSTS specifically. Total residence times for these individual STS zones range from 4.5 to 7.5 h, suggesting that these zones have the potential to host important biogeochemical transformations in stream systems. All of the RTDSTS show substantial deviations from the ideal prescribed by the two‐state (mobile/immobile) mass transfer equations. The deviations indicate a model mismatch and that parameter estimation based on the mass transfer equations will yield misleading values.
Comparative Analysis of Psychophysiological Responses in Fibromyalgia Patients: Evaluating Neuromodulation Alone, Neuromodulation Combined with Virtual Reality, and Exercise Interventions

Background and Objectives: Fibromyalgia, a chronic condition, manifests as widespread musculoskeletal pain, fatigue, sleep disturbances, autonomic and cognitive dysfunction, hypersensitivity to stimuli, and various somatic and psychiatric symptoms. This study, a controlled and randomized experiment, aimed to evaluate and compare the immediate effects of different treatments on fibromyalgia patients. Materials and Methods: The treatments included the EXOPULSE Mollii suit, a combination of the EXOPULSE Mollii suit with a virtual reality (VR) protocol, and a physical exercise regimen. A cohort of 89 female fibromyalgia patients was randomly assigned to one of four groups: Control (n = 20), Suit only (n = 22), Suit combined with VR (n = 21), and Exercise (n = 26). Results: This study found notable differences across the groups in several key parameters. In the Control group, significant changes were observed in Forced Expiratory Volume (FEV 1/FEV 6), the Numeric Rating Scale (NRS) for pain, Pressure Pain Threshold (PPT) at the epicondyle, cortical arousal levels, the 10 m up-and-go test, and in all measured variables related to temperature and muscle oxygenation. For the group using the suit alone, there were significant differences noted in the NRS, the chair stand test, palm temperature, and all muscle oxygenation parameters. The Suit + VR group showed significant changes in the NRS, PPT at the knee, handgrip strength test, the 10 m up-and-go test, one-leg balance test with the right leg, muscle oxygen saturation (SmO2), deoxygenated hemoglobin (HHb), and oxygenated hemoglobin (O2Hb). Finally, the Exercise group exhibited significant differences in FEV 1/FEV 6, chest perimeter difference, NRS, PPT at both the epicondyle and knee, cortical arousal, the chair stand test, the 10-m up-and-go test, and in SmO2, HHb, and O2Hb levels. Conclusions: combining neuromodulation with VR and targeted exercise regimens can effectively alleviate fibromyalgia symptoms, offering promising avenues for non-pharmacological management.
Biological and physical quality of a mined soil under revegetation with perennial grasses

The objective of this work was to evaluate a population of mites and springtails and a physical condition of a mined soil revegeted with different species of perennial grasses. The treatments evaluated were: Urochloa brizantha, Hemarthria altissima, Paspalum notatum, Cynodon dactylon and Spontaneous vegetation. For comparative effects a natural soil were used as reference. In 2014, 56 soil samples were collected in the 0.00-0.10 m layer for the determination of the population of mites and springtails, the physical attributes and the organic carbon content. The Hemarthria altissima was the most prominent plant species among perennial grasses, to date, providing an average density of mites and springtails very close to the natural soil. Among the physical attributes, bulk density showed the most sensitive variable the changes promoted by plant species, after 11 years of revegetation.
Patrón de distribución espacial de las especies arbóreas de la región de El Salto, Durango

The purpose of this study was to determine the pattern of spatial distribution of trees present in the region of El Salto, Pueblo Nuevo, Durango. For this purpose, 12 communities that are representative of the conditions of the forests of the region were selected, where 269 round sites of 0.1 ha were randomly distributed at an altitude range of 1 500 to 3 000 m. The pattern of distribution of the trees by altitude level was determined by applying Cox’s and Morisita’s indices, and the pattern corresponding to each species was tested with the Poisson and negative binomial distribution adjustment tests. The level of aggregation was evaluated through the clustering parameter K, the ratio of the average density per taxon in relation to the mean 1/K, and the average number per individual per species in relation to the individuals present in the sampling unit m*. Cox’s and Morisita’s indices ranged from 12.05 to 17.39 and from 1.18 to 1.28, respectively, indicating that at each level of altitude individuals are distributed on an aggregate basis. At the same time, Cox’s index and the negative binomial distribution adjustment (P>0.05) pointed out that the individuals per species are distributed in clusters. The values of the parameter K, 1/K and m*, which ranged from 0.002 to 0.454, from 2 to 500 and from 9 to 69, respectively, exhibit a high degree of aggregation between individuals.
Gene Signature of Regulatory T Cells Isolated from Children with Selective IgA Deficiency and Common Variable Immunodeficiency

Selective IgA deficiency (SIgAD) is the most common form and common variable immunodeficiency (CVID) is the most symptomatic form of predominant antibody deficiency. Despite differences in the clinical picture, a similar genetic background is suggested. A common feature of both disorders is the occurrence of autoimmune conditions. Regulatory T cells (Tregs) are the major immune cell type that maintains autoimmune tolerance. As the different types of abnormalities of Treg cells have been associated with autoimmune disorders in primary immunodeficiency (PID) patients, in our study we aimed to analyze the gene expression profiles of Treg cells in CVID and SIgAD patients compared to age-matched healthy controls. The transcriptome-wide gene profiling was performed by microarray technology. As a result, we analyzed and visualized gene expression patterns of isolated population of Treg cells. We showed the differences at the gene level between patients with and without autoimmunizations. Our findings suggest that the gene signatures of Treg cells isolated from SIgAD and CVID patients differ from age-matched healthy controls and from each other, presenting transcriptional profiles enriched in innate immune or Th response, respectively. The occurrence of autoimmunity in both types of PID is associated with down-regulation of class I IFNs signaling pathways. In summary, our findings improve our understanding of Treg dysfunctions in patients with common PIDs and associated autoimmunity.
Evaluating the effectiveness of induced seismicity mitigation: Numerical modeling of wastewater injection near Greeley, Colorado

Mitigation of injection‐induced seismicity in Greeley, Colorado, is based largely on proximity of wastewater disposal wells to seismicity and consists of cementation of the bottom of wells to eliminate connection between the disposal interval and crystalline basement. Brief injection rate reductions followed felt events, but injection rates returned to high levels, >250,000 barrels/month, within 6 months. While brief rate reduction reduces seismicity in the short term, overall seismicity is not reduced. We examine contributions to pore pressure change by injection from 22 wells within 30 km of the center of seismicity. The combined injection rate of seven disposal wells within 15 km of the seismicity (Greeley Wells) is correlated with the seismicity rate. We find that injection from NGL‐C4A, the well previously suspected as the likely cause of the induced seismicity, is responsible for ~28% of pore pressure increase. The other six Greeley Wells contribute ~28% of pore pressure increase, and the 15 Far‐field Wells between 15 and 30 km from the seismicity contribute ~44% of pore pressure increase. Modeling results show that NGL‐C4A plays the largest role in increased pore pressure but shows that the six other Greeley Wells have approximately the same influence as NGL‐C4A. Furthermore, the 15 Far‐field Wells have significant influence on pore pressure near the seismicity. Since the main mitigation action of cementing the bottom of wells has not decreased seismicity, mitigation based on reduced injection rates and spacing wells farther apart would likely have a higher potential for success.
Design and Implementation of an Efficient System to improve Bag of Features Technique using Spatial Feature Reduction

Image segmentation is a very emerging and important area due to a large number of real life applications. Bag-of-features (BoFs) model is the one of the most successful algorithm used for the image classification. BoF methods are based on order-less collections of quantized local image descriptors; they discard spatial information and are therefore conceptually and computationally simpler than many alternative methods. Bag-of-features algorithm is used for the feature extraction from the image. BoFs model has several advantages like, scalability, simplicity, and generality. But BoFs have some disadvantages to and some of them are Time and Accuracy of the image classification process. In this paper Bag-of-features model is extend by using spatial pooling to improve the time and accuracy of the image classification model. In proposed method first the system is train by creating the database of the image feature for the evaluation process and then the evolution of the features is done for the input image by using clustering algorithm. In the proposed method KKN algorithm is used to find out the similar features from the database. Spatial pooling is then used to improve the performance of the existing system.
Cross-Resolution Perceptual Knowledge Propagation for Low-Resolution Aerial Photograph Categorization

The ability to precisely identify the semantic categories of low-resolution (LR) aerial images is a critical skill in the field of remote sensing. However, accurately performing this task is challenging due to several factors: 1) the complexity of incorporating human visual perception into the recognition algorithm; 2) the significant human effort required to annotate a large number of training LR aerial images; and 3) the difficulty in selecting high-quality features for accurate categorization. To address these challenges, we introduce a groundbreaking approach known as cross-resolution perceptual knowledge propagation (CPKP), which aims to utilize the visual perceptual insights gained from high-resolution (HR) aerial images to improve the categorization of LR images. In particular, our approach draws inspiration from the human visual system to create a novel low-rank model. This model is designed to separate each LR aerial image into multiple visually and semantically prominent foreground regions alongside less noticeable background areas. It accomplishes two key objectives: 1) generating a gaze shifting path (GSP) that replicates the sequence of human gaze shifts and 2) computing the deep features for each GSP. Subsequently, we develop a kernel-induced feature selection (FS) algorithm to extract a concise, yet effective set of deep GSP features that can distinguish between LR and HR aerial images. Utilizing the labels from both LR and HR images, we then collaboratively train a linear classifier for the categorization of LR images. Notably, our CPKP framework significantly enhances the efficiency of training the linear classifier, mainly because acquiring labels for HR aerial photographs is typically more feasible than for LR images. The effectiveness of our method is further demonstrated through extensive visual results and a comparative analysis, showcasing its superiority.
Dynamic topography and lithospheric stresses since 400 Ma

We present a global model of dynamic topography and lithospheric stresses for the last 400 Ma. Our starting point is a simple geodynamic model combining both contributions of subducted lithosphere and long‐wavelength upwellings in a reference frame linked to the fixed African plate. A dominant feature of plate tectonics is the quasi permanence of a girdle of subductions around the Pacific Ocean (or its ancestor), which creates large‐wavelength positive topography anomaly within the ring they form. The superimposition of the resultant extension with the one induced by the dome leads to a permanent extensional regime over Africa and the future Indian ocean which creates faults with azimuth directions depending on the direction of the most active part of the ring of subductions. We thus obtain fractures with NW‐SE azimuth during the period 275–165 Ma parallel to the strike of the subduction zone of the West South American active margin, which appears to be very active during this period. Between 155 and 95 Ma, subduction became more active along the Eastern Australian coast involving a change in the direction of the faults toward an E‐W direction, in agreement with the observed fault systems between Africa and India, Antartica and Australia. During the Mesozoic and the Cenozoic, we correlate the permanent extensional regime over Africa and Indian Ocean with the observed rift systems. Finally we emphasize the role of three primary hotspots as local additional contributors to the stress field imposed by our proposed subduction‐doming system, which help in the opening of Indian and South Atlantic Oceans.
Study on the Leaching Status of Magnesium Nutrients in Soil and its Influencing Factors

Mg is one of the essential medium elements for plant growth and an essential mineral nutrient in agricultural production. In this paper, we summarize the past series of plant Mg nutrition studies and Mg leaching tests in field soils to reveal the leaching status of Mg elements in soils today and their influencing factors. According to the test results of 325 609 soils in the 2016 National Soil Testing and Formulation Program, Mg-deficient soils with exchangeable Mg content (Mgex) <50 mg-kg-1 accounted for 43.8% of soils in the country; among them, soils with 25-50 mg-kg-1 accounted for 7.64%, and those with Mgex <25 mg-kg-1 accounted for 36.14%, and soils in China had a more serious deficient The salinization, acid-alkalization, high heavy metal content and intense leaching of the soil were the important influencing factors for its lack of Mg supply. Positive effect factors of soil Mg leaching include soil exchange Mg content, type of fibrous root crop, light-textured soil, desorption of soil Mg, and weathering of parent material; negative effect factors include type of taproot crop, root secretion, biomass fixation, soil pH and organic matter, colloidal adsorption, and precipitation mineralization.