Miracle-dz/UniFAR-FTUs huggingface dataset:
Complicated rupture process of the Mw 7.0 intraslab strike‐slip earthquake in the Tohoku region on 10 July 2011 revealed by near‐field pressure records

We examined fault models of the Tohoku strike‐slip intraslab earthquake (Mw 7.0) on 10 July 2011 using near‐field tsunami data. After constraining the strike and location of the fault from tsunami source distribution, we investigated fault models assuming simple rupture of one fault, and simultaneous rupture of two conjugate faults. The estimated single fault reached >30 km down into the slab from the plate interface, suggesting bending stress enhancement after the 2011 Tohoku‐Oki earthquake, but the depth extent was inconsistent with the aftershock activity. The model involving conjugate faults extended ~20 km below the slab surface and was more consistent with the aftershocks. We concluded that it is more plausible that this earthquake involved two conjugate strike‐slip faults, and the enhancement of the downdip extensional stress after Tohoku‐Oki earthquake was not large enough to allow rupture to propagate deeply into the slab beneath the landward slope of the Japan Trench.
Statistical low flow estimation using GIS analysis in humid montane regions in Puerto Rico

: Statistical analysis of watershed parameters derived using a Geographical Information system (GIS) was done to develop equations for estimating the 7d–10yr, 30d–10yr, and 7d–2yr low flow for watersheds in humid montane regions of Puerto Rico. Digital elevation models and land use, geology, soils, and stream network coverages were used to evaluate 21 geomorphic, 10 stream channel, 9 relief, 7 geology, 4 climate, and 2 soil parameters for each watershed. To assess which parameters should be used for further investigation, a correlation analysis was used to determine the independence and collinearity among these parameters and their relationship with low flows. Multiple regression analyses using the selected parameters were then performed to develop the statistical models of low flows. The final models were selected in the basis of the Mallow Cp statistic, the adjusted R2, the Press statistic, the degree of collinearity, and an analysis of the residuals. In the final models, drainage density, the ratio of length of tributaries to the length of the main channel, the percent of drainage area with northeast aspect, and the average weighted slope of the drainage were the most significant parameters. The final models had adjusted standard errors of 58.7 percent, 59.2 percent, and 48.6 percent for the 7d–10yr, 30d–10yr, and 7d–2yr low flows respectively. For comparison, the best model based on watershed parameters that can be easily measured without a GIS had an adjusted standard error of 82.8 percent.
Coalescence of fractures under shear stresses in experiments

A series of uniaxial compression tests were performed on gypsum specimens with preexisting fractures to study the failure mechanism of fractures and rock bridges in fractured rock masses. The coalescence mechanism of two parallel and offset fractures was investigated by monitoring the process of fracture initiation and propagation with a video camera. The tests showed that two inclined parallel fractures can coalesce by shear failure and/or tensile failure under a uniaxial load. The coalescence path and mechanism mainly depend on the relative position of the two fractures. For instance, when the two fractures are coplanar or slightly offset, coalescence is generated by shear failure; when they are overlapping in the loading direction, coalescence is generated by mixed shear and tensile failure. Two types of preexisting fractures, one without initial surface contact and hence frictionless and another with surface contact and friction, were used to study the influence of fracture contact conditions on the coalescence path and load. It was found that coalescence of fractures with surface contact and friction requires loads as much as 35% higher than that for coalescence of fractures without contact and friction. A stress analysis was conducted in this study to explain the different coalescence mechanisms. The analytical work indicated that different fracture geometries produce significantly different stress fields in the rock bridge area and hence result in different failure modes.
Adult Age Differences in Attention to Semantic Context

ABSTRACT In three experiments age differences in attention to semantic context were examined. The performance of younger adults (ages 18–29 years) and older adults (ages 60–79 years) on a semantic priming task indicated that both age groups could use information regarding the probability that a prime and target would be related to flexibly anticipate the target category given the prime word (Experiment 1). The timing by which target expectancies were reflected in reaction time performance was delayed for older adults as compared to younger adults, but only when the target was expected to be semantically unrelated to the prime word (Experiment 2). When the target and prime were expected to be semantically related, the time course of priming effects was similar for younger and older adults (Experiment 3). Together the findings indicate that older adults are able to use semantic context and the probability of stimulus relatedness to anticipate target information. Although aging may be associated with a delay in the timing by which controlled expectancies are expressed, these findings argue against an age-related decline in the ability to represent contextual information.
Hydrogen sulfide oxidation in novel Horizontal-Flow Biofilm Reactors dominated by an Acidithiobacillus and a Thiobacillus species

ABSTRACT Hydrogen Sulfide (H2S) is an odourous, highly toxic gas commonly encountered in various commercial and municipal sectors. Three novel, laboratory-scale, Horizontal-Flow Biofilm Reactors (HFBRs) were tested for the removal of H2S gas from air streams over a 178-day trial at 10°C. Removal rates of up to 15.1 g [H2S] m−3 h−1 were achieved, demonstrating the HFBRs as a feasible technology for the treatment of H2S-contaminated airstreams at low temperatures. Bio-oxidation of H2S in the reactors led to the production of H+ and sulfate (SO2−4) ions, resulting in the acidification of the liquid phase. Reduced removal efficiency was observed at loading rates of 15.1 g [H2S] m−3 h−1. NaHCO3 addition to the liquid nutrient feed (synthetic wastewater (SWW)) resulted in improved H2S removal. Bacterial diversity, which was investigated by sequencing and fingerprinting 16S rRNA genes, was low, likely due to the harsh conditions prevailing in the systems. The HFBRs were dominated by two species from the genus Acidithiobacillus and Thiobacillus. Nonetheless, there were significant differences in microbial community structure between distinct HFBR zones due to the influence of alkalinity, pH and SO4 concentrations. Despite the low temperature, this study indicates HFBRs have an excellent potential to biologically treat H2S-contaminated airstreams.
NAO influence on sub‐decadal moisture variability over central North America

A strong statistically significant spectral peak with a frequency of 7–8 years is computed for tree‐ring reconstructed summer PDSI averaged at continental and regional scales over North America for the period 1645–1990. A similar, though non‐significant spectral peak is computed for instrumental summer PDSI averaged over North America for the shorter period from 1900–1990. The winter NAO index (1781–2002) has a very strong spectral signature at this same 7–8 year sub‐decadal frequency and is coherent with summer PDSI across a broad sector of the central U.S. Composite analyses confirm a PDSI response to extremes of the NAO over the central U.S., with drought prevalent during negative extremes, and wetness during positive extremes. The winter NAO index leads summer PDSI and a contingency table analysis indicates that extrema in the winter NAO index may have modest forecast value for the following spring‐summer moisture regimes over the central U.S.
Laboratory abrasion tests on beach flint shingle

Abstract Laboratory tumbling experiments demonstrate that rounded flint beach shingle is less durable than commonly supposed. The mean rate of abrasion for dark grey Sussex flints (Senonian) in the first few hours of tumbling increases with weight whereas that of white Normandy flints (Turonian and Coniacian) does not. Depending on pebble weight, the Sussex flints abrade at up to six times the rate of the Normandy flints. Abrasion rates also vary according to tumbler load, the water:shingle ratio, and tumbling period. The abrasion rate of Sussex flints decreases with time at a much greater rate than could be expected from the reduction in size. The abrasion debris is mostly silt sized, but small quantities of sand are produced from samples containing larger pebbles. In situ abrasion of flint shingle is estimated to be significant, reducing the protection shingle beaches afford to cliffs thus exacerbating Chalk cliff instability.
Small Worlds: The Dynamics of Networks between Order and Randomness

Everyone knows the small-world phenomenon: soon after meeting a stranger, we are surprised to discover that we have a mutual friend, or we are connected through a short chain of acquaintances. In his book, Duncan Watts uses this intriguing phenomenon--colloquially called "six degrees of separation"--as a prelude to a more general exploration: under what conditions can a small world arise in any kind of network? The networks of this story are everywhere: the brain is a network of neurons; organisations are people networks; the global economy is a network of national economies, which are networks of markets, which are in turn networks of interacting producers and consumers. Food webs, ecosystems, and the Internet can all be represented as networks, as can strategies for solving a problem, topics in a conversation, and even words in a language. Many of these networks, the author claims, will turn out to be small worlds.How do such networks matter? Simply put, local actions can have global consequences, and the relationship between local and global dynamics depends critically on the network's structure. Watts illustrates the subtleties of this relationship using a variety of simple models---the spread of infectious disease through a structured population; the evolution of cooperation in game theory; the computational capacity of cellular automata; and the sychronisation of coupled phase-oscillators.Watts's novel approach is relevant to many problems that deal with network connectivity and complex systems' behaviour in general: How do diseases (or rumours) spread through social networks? How does cooperation evolve in large groups? How do cascading failures propagate through large power grids, or financial systems? What is the most efficient architecture for an organisation, or for a communications network? This fascinating exploration will be fruitful in a remarkable variety of fields, including physics and mathematics, as well as sociology, economics, and biology.
Blebs Promote Cell Survival by Assembling Oncogenic Signaling Hubs

Most human cells require anchorage for survival. Cell-substrate adhesion activates diverse signaling pathways, without which cells undergo anoikis – a form of programmed cell death1. Acquisition of anoikis resistance is a pivotal step in cancer disease progression, as metastasizing cancer cells often lose firm attachment to surrounding tissue2–5. In these poorly attached states, cells adopt rounded morphologies and form small hemispherical plasma membrane protrusions called blebs6–13. Bleb function has been thoroughly investigated in the context of amoeboid migration but is far less examined in other scenarios14–19. Here we show by quantitative subcellular 3D imaging and manipulation of cell morphological states that blebbing triggers the formation of plasma membrane-proximal signaling hubs that confer anoikis resistance. Specifically, we discovered in melanoma cells that blebbing generates plasma membrane contours, which recruit curvature-sensing septin proteins as scaffolds for constitutively active mutant NRAS and effectors. These signaling hubs activate ERK and PI3K – canonical promoters of pro-survival pathways. Inhibition of blebs or septins has little effect on the survival of well-adhered cells, but in detached cells causes NRAS mislocalization, reduced MAPK and PI3K activity, and ultimately, death. This unveils an unanticipated morphological requirement for mutant NRAS to operate as an effective oncoprotein. Moreover, we find that though some BRAF mutant melanoma do not rely on this survival pathway in a basal state, BRAF/MEK inhibition strongly sensitizes them to both bleb and septin inhibition. Importantly, we demonstrate that fibroblasts engineered to sustain blebbing acquire the same anoikis resistance as cancer cells even without harboring oncogenic mutations. These data define a role for blebs as potent signaling organelles capable of integrating myriad cellular information flows into concerted cellular responses, in this case granting robust anoikis resistance.
Predicting the COVID-19 patients’ status using chest CT scan �ndings: A risk assessment model based on Decision tree

Background: The role of chest computed tomographic (CT) to diagnosis coronavirus disease-2019 (COVID-19) is still an open �eld to be explored. The aim of this study was to apply the decision tree (DT) model to predict critical or non-critical status of patients infected with COVID-19 based on available information on non-contrast CT scan. Method: This study was performed onpatients with COVID-19 who underwent chest CTscan atBaqiyatallahHospital, Tehran, Iran. In this retrospectivestudy, the medical records of 1078 patients with COVID-19 were evaluated. The classi�cation and regression tree (CART) of decision treemodeland k-fold cross validation were used to predict the status of patients and to measure their sensitivity, speci�city and area under curve (AUC). Results: Data included 169 critical cases and 909 non-critical cases. The bilateral distribution and multifocal lung involvement were165 (97.6%) and 766 (84.3%) in critical patients, respectively.According to DT model, total opacity score, age, lesion types and gender were statistically signi�cant predictors incritical patients.Moreover, the results showed that the accuracy, sensitivity and speci�city of the DT model were 93.3%, 72.8% and 97.1%, respectively. Conclusions: The presented algorithm demonstrates the factors affecting the patient's condition. In addition, this model has the potential characteristics for clinical applicationsand canalso identify high-risk subpopulations that need speci�c prevention.
Additional fossil records of Succinea (Austrosuccinea/archeyi) (Powell) (Mollusca : Succineidae) in New Zealand

Abstract Succinea archeyi is recorded from an Upper Pleistocene deposit at Marton (40°05′S; 175°23′E), a Holocene lake deposit at Lake Poukawa, Hawke's Bay (39°47′S; 176°42′E) and from a glacial lake marl in the Cromwell Gorge, Otago (45°05′S; 169°14′E). The significance of the palaeoenvironments at these sites is discussed in relation to what is known of the biology of the living populations.
Blood Brain Barrier KCa3.1 Channels: Evidence for a Role in Brain Na Uptake and Edema in Ischemic Stroke

Background and Purpose : KCa3.1, a calcium-activated potassium channel, regulates ion and fluid secretion in the lung and gastrointestinal tract. It is also expressed on vascular endothelium where it participates in blood pressure regulation. However, the expression and physiological role of KCa3.1 in blood-brain barrier (BBB) endothelium has not been investigated. BBB endothelial cells transport Na + and Cl - from the blood into the brain transcellularly through the cooperation of multiple co-transporters, exchangers, pumps and channels. In the early stages of cerebral ischemia, when the BBB is intact, edema formation occurs by processes involving increased BBB transcellular Na + transport . This study evaluated whether KCa3.1 is expressed on and participates in BBB ion transport. Methods: The expression of KCa3.1 on cultured cerebral microvascular endothelial cells (CMEC), isolated microvessels and brain sections was evaluated by Western blot and immunohistochemistry. Activity of KCa3.1 on CMEC was examined by K + flux assays and patch-clamp. Magnetic resonance spectroscopy and imaging were used to measure brain Na + uptake and edema formation in rats with focal ischemic stroke following TRAM-34 treatment. Results: KCa3.1 current and channel protein were identified on bovine CMEC and freshly isolated rat microvessels. In situ KCa3.1 expression on BBB endothelium was confirmed in rat and human brain sections. TRAM-34 treatment significantly reduced Na + uptake, and cytotoxic edema in the ischemic brain. Conclusions: BBB endothelial cells exhibit KCa3.1 protein and activity and pharmacological blockade of KCa3.1 appears to provide an effective therapeutic approach for reducing cerebral edema formation in the first 3 hours of ischemic stroke. Na + Brighter extravascular Na + content; B) Quantitated extravascular Na + content in the infarct core up to 170 min after induction of MCAO. n = 7 rats; C) Representative T2-weighted images for brain edema evaluation in vehicle- and TRAM-34 treated rats subjected to pMCAO. Brighter intensity indicates more edema; Quantitated Ipsilateral/Contralateral ADC ratios for Vehicle- and TRAM-34 treated rats up to 236 min from onset of MCAO, n=7. Values are mean than
Phylogenetic comparative methods on phylogenetic 3 networks with reticulations 4

— The goal of Phylogenetic Comparative Methods (PCMs) is to study the 15 distribution of quantitative traits among related species. The observed traits are often seen 16 as the result of a Brownian Motion (BM) along the branches of a phylogenetic tree. 17 Reticulation events such as hybridization, gene flow or horizontal gene transfer, can 18 substantially affect a species’ traits, but are not modeled by a tree. Phylogenetic networks 19 have been designed to represent reticulate evolution. As they become available for 20 downstream analyses, new models of trait evolution are needed, applicable to networks. 21 One natural extension of the BM is to use a weighted average model for the trait of a 22 hybrid, at a reticulation point. We develop here an efficient recursive algorithm to compute 23 the phylogenetic variance matrix of a trait on a network, in only one preorder traversal of 24 the network. We then extend the standard PCM tools to this new framework, including 25 phylogenetic regression with covariates (or phylogenetic ANOVA), ancestral trait 26 reconstruction, and Pagel’s λ test of phylogenetic signal. The trait of a hybrid is sometimes 27 outside of the range of its two parents, for instance because of hybrid vigor or hybrid 28 depression. These two phenomena are rather commonly observed in present-day hybrids. 29 Transgressive evolution can be modeled as a shift in the trait value following a reticulation 30 point. We develop a general framework to handle such shifts, and take advantage of the 31 phylogenetic regression view of the problem to design statistical tests for ancestral 32 transgressive evolution in the evolutionary history of a group of species. We study the 33 power of these tests in several scenarios, and show that recent events have indeed the 34 strongest impact on the trait distribution of present-day taxa. We apply those methods to 35 a dataset of Xiphophorus fishes, to confirm and complete previous analysis in this group. 36 All the methods developed here are available in the Julia package PhyloNetworks. 37 (
Sea ice effective microwave emissivities from satellite passive microwave and infrared observations

Microwave sea ice emissivities are investigated on a global scale by using near-simultaneous images from the temperature-humidity infrared radiometer (THIR) and the dual-polarization scanning multichannel microwave radiometer (SMMR), both onboard the Nimbus 7 satellite. The emissivities in several study areas in the Arctic region are observed to be approximately constant during a 9-month period within the fall, winter, and spring months for both first-year and multiyear ice, with a standard deviation of about 3%. During the onset of summer, when the snow cover starts to melt, emissivity increases of about 30% are observed at 37 GHz for multiyear ice, with the effect decreasing to less than 5% at the 6.6-GHz channels. Multichannel cluster analysis over very large study areas during winter shows considerable variability in emissivities of well-defined clusters of consolidated ice at 37 GHz and about one third as much at 18 GHz. Some nonlinearities in the functional relationship of the emissivities in the consolidated ice regions between first-year and multiyear ice are also evident, especially when data from one frequency is plotted against that of another. However, the cluster analysis technique separates the various emissivity data points into distinct clusters corresponding to radiometrically different ice types. If the variability within each cluster is quantified and taken into account by using multispectral analysis, in addition to improving the capability of classifying ice by age, information about ice thickness and surface characteristics might also be obtainable.
Natural Language Processing for Clinical Laboratory Data Repository Systems: Implementation and Evaluation for Respiratory Viruses

Background: With the growing volume and complexity of laboratory repositories, it has become tedious to parse unstructured data into structured and tabulated formats for secondary uses such as decision support, quality assurance, and outcome analysis. However, advances in Natural Language Processing (NLP) approaches have enabled efficient and automated extraction of clinically meaningful medical concepts from unstructured reports. Objective: In this study, we aimed to determine the feasibility of using the NLP model for information extraction as an alternative approach to a time-consuming and operationally resource-intensive handcrafted rule-based tool. Therefore, we sought to develop and evaluate a deep learning-based NLP model to derive knowledge and extract information from text-based laboratory reports sourced from a provincial laboratory repository system. Methods: The NLP model, a hierarchical multi-label classifier, was trained on a corpus of laboratory reports covering testing for 14 different respiratory viruses and viral subtypes. The corpus included 85k unique laboratory reports annotated by eight Subject Matter Experts (SME). The model's performance stability and variation were analyzed across fine-grained and coarse-grained classes. Moreover, the model's generalizability was also evaluated internally and externally on various test sets. Results: The NLP model was trained several times with random initialization on the development corpus, and the results of the top ten best-performing models are presented in this paper. Overall, the NLP model performed well on internal, out-of-time (pre-COVID-19), and external (different laboratories) test sets with micro-averaged F1 scores >94% across all classes. Higher Precision and Recall scores with less variability were observed for the internal and pre-COVID-19 test sets. As expected, the model's performance varied across categories and virus types due to the imbalanced nature of the corpus and sample sizes per class. There were intrinsically fewer classes of viruses being detected than those tested; therefore, the model's performance (lowest F1-score of 57%) was noticeably lower in the detected cases. Conclusions: We demonstrated that deep learning-based NLP models are promising solutions for information extraction from text-based laboratory reports. These approaches enable scalable, timely, and practical access to high-quality and encoded laboratory data if integrated into laboratory information system repositories.