Miracle-dz/UniFAR-FTUs huggingface dataset:
Comment on “Climate forcing by the volcanic eruption of Mount Pinatubo” by David H. Douglass and Robert S. Knox

[1] Douglass and Knox [2005, hereinafter referred to as DK] present a confusing and erroneous description of climate feedbacks and the climate response to the 1991 Mt. Pinatubo eruption. Their conclusions of a negative climate feedback and small climate sensitivity to volcanic forcing are not supported by their arguments or the observational evidence. As pointed out by Wigley et al. [2005a], this is the consequence of assuming a one-box representation for the climate system, and ignoring energy exchange with the deep ocean. [2] In the description of their analysis, DK make a fundamental mistake in describing the problem. They claim to use ‘‘standard linear response theory,’’ but they confuse the response with the forcing. They say, ‘‘The LW [longwave] effect is by definition the forcing function DF for the climate, represented by the measured surface temperature anomaly DT. ’’ LW radiation changes, however, are produced by both the presence of a forcing agent, in this case stratospheric aerosols, and the response of the climate system. It is the instantaneous net radiation change with no response that is the forcing. The temperature anomaly is the response to forcing, and not the forcing itself, and the LW changes reflect both the true forcing and the effects of the temperature response. [3] In spite of their statement to the contrary, DK apparently do use the correct forcing, as characterized by their equation (5) and illustrated in their Figure 2. Confusion arises because the forcing they use is a scaled version of the estimated aerosol optical depth changes, which represents the true forcing, yet they continually refer to the scaled optical depth as the LW changes. That the two items are different is clear from DK’s Figure 1. [4] The forcing of climate change can be defined as the change in the net radiation at the top of the atmosphere, the tropopause, or the surface, without any response of the climate system, or allowing for the stratosphere to equilibrate. Stenchikov and Robock [1995], Houghton et al. [1996], and Hansen et al. [2005] discuss the standard definitions of radiative forcing and considerations for forcing from aerosols, which are not uniformly mixed in the atmosphere. For our purposes, it is sufficient to consider the forcing at the top of the atmosphere, allowing for no equilibration [Stenchikov and Robock, 1995; Stenchikov et al., 1998]. This forcing can be defined as:
Global geodetic signatures of the Antarctic Ice Sheet

Four scenarios of present day Antarctic ice sheet mass change are developed from comprehensive reviews of the available glaciological and oceanographic evidence. The gridded scenarios predict widely varying contributions to secular sea level change ranging from −1.1 to 0.45 mm/yr, and predict polar motion and time-varying low-degree gravitational coefficients that differ significantly from earlier estimates. A reasonably linear relationship between the rate of sea level change from Antarctica A and the predicted Antarctic is found for the four scenarios. This linearity permits a series of forward models to be constructed that incorporate the effects of ice mass changes in Antarctica, Greenland, and distributed smaller glaciers, as well as postglacial rebound (assuming the ICE-3G deglaciation history), with the goal of obtaining optimum reconciliation between observed constraints on and sea level rise . Numerous viable combinations of lower mantle viscosity and hydrologie sources are found that satisfy “observed” in the range of 1 to 2–2.5 mm/yr and observed for degrees 2, 3, and 4. In contrast, rates of global sea level rise above 2.5 mm/yr are inconsistent with available observations. The successful composite models feature a pair of lower mantle viscosity solutions arising from the sensitivity of to glacial rebound. The paired values are well separated at mm/yr, but move closer together as is. increased, and, in fact, merge around =2-2.5 mm/yr, revealing an intimate relation between and preferred lower mantle viscosity. This general pattern is quite robust and persists for different solutions, for variations in source assumptions, and for different styles of lower mantle viscosity stratification. Tighter constraints for l > 2 may allow some viscosity stratification schemes and source assumptions to be excluded in the future. For a given total observed , the sea level rise from Antarctica A is tightly constrained and ranges from 0 to + 1 mm/yr (corresponding to an ablating ice sheet) as estimates of are raised from 1 to 2.5 mm/yr. However, when the degree 3 zonal harmonic constraint is removed, the solutions show little sensitivity to Antarctic mass balance, emphasizing the need for a well determined odd-degree secular zonal harmonic for determining polar ice mass balance.
Corticosteroid in anti-inammatory treatment of pediatric acute myocarditis: a systematic review and meta-analysis

Background. To evaluate the e�cacy of corticosteroids in anti-inammatory treatment of pediatric acute myocarditis. Methods. We searched PubMed, Embase and Cochrane library and included studies before October 2022 for clinical trials, observational studies and retrospective studies which reported on children with acute myocarditis treated with corticosteroid anti-inammatory therapy. The quality of the clinical trials was assessed by Jadad score as an exclusion criterion. Results. This systematic review included 6 studies involving 604 pediatric patients with acute myocarditis. Corticosteroid therapy was not associated with reduced risk of mortality due to acute myocarditis (P = 0.53; RR = 0.87; 95% CI = 0.58 to 1.33) compared to anti-failure treatment. There was a signi�cant improvement in pediatric patients’ left ventricular function measured by left ventricular ejection fraction in the group on corticosteroid anti-inammatory treatment (P = 0.0009; MD = 11.93%; 95% CI = 4.87% to 18.99%). No conclusion can be drawn due to the high heterogeneity in meta-analyses of risk of getting to a clinical endpoint (death or heart transplantation) and changes in left ventricular end-diastolic diameter (LVEDD). Conclusions. Corticosteroid anti-inammatory
Effect of crop residue incorporation on soil organic carbon and greenhouse gas emissions in European agricultural soils

Soil organic matter (SOM) improves soil physicochemical and biological properties, and the sequestration of carbon in SOM may mitigate climate change. Soil organic carbon (SOC) often decreases in intensive cropping systems. Incorporation of crop residues (CR) may be a sustainable management practice to maintain the SOC levels and to increase soil fertility. This study quantifies the effects of CR incorporation on SOC and greenhouse gas (GHG) emissions (CO2 and N2O) in Europe using data from long‐term experiments. Response ratios (RRs) for SOC and GHG emissions were calculated between CR incorporation and removal. The influence of environmental zones (ENZs), clay content and experiment duration on the RRs was investigated. We also studied how RRs of SOC and crop yields were correlated. A total of 475 RRs were derived from 39 publications. The SOC increased by 7% following CR incorporation. In contrast, in a subsample of cases, CO2 emissions were six times and N2O emissions 12 times higher following CR incorporation. The ENZ had no significant influence on RRs. For SOC concentration, soils with a clay content >35% showed 8% higher RRs compared with soils with clay contents between 18 and 35%. As the experiment progressed, RR for SOC concentration increased. For N2O emissions, RR was significantly greater in experiments with a duration <5 yr compared with 11–20 yr. No significant correlations were found between RR for SOC concentration and yields, but differences between sites and study durations were detected. We suggest that a long duration of crop residue incorporation is a win‐win scenario under a continental climate. We conclude that CR incorporation is important for maintaining SOC, but its influence on GHG emissions should be taken into account as well.
The potential of extracellular vesicle lipid proﬁling in Alzheimer’s disease.

Over the past two decades, there has been increasing research into the molecular composition and function of small extracellular vesicles in the central nervous system. This is due in part to the recognition that small extracellular vesicles likely contribute to the pathogenesis of neurological diseases such as Alzheimer’s disease, but also an understanding that small extracellular vesicles are a source of potential biomarkers. Small extracellular vesicles carry speciﬁc cargo that reﬂects their biogenesis and cellular origins, including protein, RNA and lipid. While the protein and RNA content of small extracellular vesicles in the central nervous system diseases and have been studied extensively, our understanding of the lipidome of small extracellular vesicles in the central nervous system is still in its infancy. Lipids play a signiﬁcant role in maintaining central nervous system structure and function, and the dysregulation of lipid metabolism is known to occur in many neurological disorders, including Alzheimer’s disease. Here we review what is currently known about lipid dyshomeostasis in Alzheimer’s disease. We propose that small extracellular vesicle lipids may provide insight into the pathophysiology and progression of Alzheimer’s disease and other neurological disorders, and, in the future perhaps, aid in disease monitoring and detection.
Detecting post-fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field-collected composite burn index data in a ponderosa pine forest

It is challenging to detect burn severity and vegetation recovery because of the relatively long time period required to capture the ecosystem characteristics. Multitemporal remote sensing data can provide multitemporal observations before, during and after a wildfire, and can improve the change detection accuracy. The goal of this study is to examine the correlations between multitemporal spectral indices and field-observed burn severity, and to provide a practical method to estimate burn severity and vegetation recovery. The study site is the Jasper Fire area in the Black Hills National Forest, South Dakota, that burned during August and September 2000. Six multitemporal Landsat images acquired from 2000 (pre-fire), 2001 (post-fire), 2002, 2003, 2005 and 2007 were used to assess burn severity. The normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized burn ratio (NBR), integrated forest index (IFI) and the differences of these indices between the pre-fire and post-fire years were computed and analysed with 66 field-based composite burn index (CBI) plots collected in 2002. Results showed that differences of NDVI and differences of EVI between the pre-fire year and the first two years post-fire were highly correlated with the CBI scores. The correlations were low beyond the second year post-fire. Differences of NBR had good correlation with CBI scores in all study years. Differences of IFI had low correlation with CBI in the first year post-fire and had good correlation in later years. A CBI map of the burnt area was produced using regression tree models and the multitemporal images. The dynamics of four spectral indices from 2000 to 2007 indicated that both NBR and IFI are valuable for monitoring long-term vegetation recovery. The high burn severity areas had a much slower recovery than the moderate and low burn areas.
Simulated soil water storage effects on streamflow generation in a mountainous snowmelt environment, Idaho, USA

Although soil processes affect the timing and amount of streamflow generated from snowmelt, they are often overlooked in estimations of snowmelt‐generated streamflow in the western USA. The use of a soil water balance modelling approach to incorporate the effects of soil processes, in particular soil water storage, on the timing and amount of snowmelt generated streamflow, was investigated. The study was conducted in the Reynolds Mountain East (RME) watershed, a 38 ha, snowmelt‐dominated watershed in southwest Idaho. Snowmelt or rainfall inputs to the soil were determined using a well established snow accumulation and melt model (Isnobal). The soil water balance model was first evaluated at a point scale, using periodic soil water content measurements made over two years at 14 sites. In general, the simulated soil water profiles were in agreement with measurements (P < 0·05) as further indicated by high R2 values (mostly > 0·85), y‐intercept values near 0, slopes near 1 and low average differences between measured and modelled values. In addition, observed soil water dynamics were generally consistent with critical model assumptions. Spatially distributed simulations over the watershed for the same two years indicate that streamflow initiation and cessation are closely linked to the overall watershed soil water storage capacity, which acts as a threshold. When soil water storage was below the threshold, streamflow was insensitive to snowmelt inputs, but once the threshold was crossed, the streamflow response was very rapid. At these times there was a relatively high degree of spatial continuity of satiated soils within the watershed. Incorporation of soil water storage effects may improve estimation of the timing and amount of streamflow generated from mountainous watersheds dominated by snowmelt. Copyright © 2008 John Wiley & Sons, Ltd.
Ultrafast mantle impregnation by carbonatite melts

Carbonatitic melts are often invoked as responsible for metasomatism in the mantle because of their unique chemical and physical properties. Here we report on infiltration experiments demonstrating that such melts can percolate very quickly in polycrystalline olivine. Carbonatites can travel over several millimeters in one hour and the infiltration rate is kinetically controlled by cation diffusion in the melt. The observed rates are several orders of magnitude higher than those previously found for basalt infiltration in mantle lithologies. Infiltration proceeds by a dissolution-precipitation mechanism wherein porosity is created in the dunite by dissolution of olivine at grain edges. This reaction is accompanied by forsterite reprecipitation in the carbonatite reservoir. Such a mechanism would likely favor chemical exchange between melt and matrix during percolation. We propose a migration model combining infiltration and compaction by which carbonatite melts can travel upward in the mantle over hundreds to thousands of meters on time scales of 0.1–1 m.y.
Time-Efficient Identification Procedure for Neurological Complications of Rescue Patients in an Emergency Scenario Using Hardware-Accelerated Artificial Intelligence Models

During an emergency rescue operation, rescuers have to deal with many different health complications like cardiovascular, respiratory, neurological, psychiatric, etc. The identification process of the common health complications in rescue events is not very difficult or time-consuming because the health vital symptoms or primary observations are enough to identify, but it is quite difficult with some complications related to neurology e.g., schizophrenia, epilepsy with non-motor seizures, or retrograde amnesia because they cannot be identified with the trend of health vital data. The symptoms have a wide spectrum and are often non-distinguishable from other types of complications. Further, waiting for results from medical tests like MRI and ECG is time-consuming and not suitable for emergency cases where a quick treatment path is an obvious necessity after the diagnosis. In this paper, we present a novel solution for overcoming these challenges by employing artificial intelligence (AI) models in the diagnostic procedure of neurological complications in rescue situations. The novelty lies in the procedure of generating input features from raw rescue data used in AI models, as the data are not like traditional clinical data collected from hospital repositories. Rather, the data were gathered directly from more than 200,000 rescue cases and required natural language processing techniques to extract meaningful information. A step-by-step analysis of developing multiple AI models that can facilitate the fast identification of neurological complications, in general, is presented in this paper. Advanced data analytics are used to analyze the complete record of 273,183 rescue events in a duration of almost 10 years, including rescuers’ analysis of the complications and their diagnostic methods. To develop the detection model, seven different machine learning algorithms-Support Vector Machine (SVM), Random Forest (RF), K-nearest neighbor (KNN), Extreme Gradient Boosting (XGB), Logistic Regression (LR), Naive Bayes (NB) and Artificial Neural Network (ANN) were used. Observing the model’s performance, we conclude that the neural network and extreme gradient boosting show the best performance in terms of selected evaluation criteria. To utilize this result in practical scenarios, the paper also depicts the possibility of embedding such machine learning models in hardware like FPGA. The goal is to achieve fast detection results, which is a primary requirement in any rescue mission. An inference time analysis of the selected ML models and VTA AI accelerator of Apache-TVM machine learning compiler used for the FPGA is also presented in this research.
Understanding the use of spectrum‐based fault localization

Developers spend significant time locating and fixing bugs, which is often performed manually. Although spectrum‐based fault localization (SFL) techniques aim at helping developers to locate faults, they are not yet used in practice. Recent studies have investigated how developers use SFL, presenting different conclusions about their effectiveness and usefulness. We carried out a user study to further enhance the understanding of SFL. We assessed whether SFL improves the developers' performance and to what extent SFL leads developers to inspect faulty code excerpts. We also investigated the intention of the developers to use SFL and how they interact with SFL. Twenty‐six participants performed debugging tasks using real programs, with and without using the Jaguar SFL tool. Using SFL, more developers located and fixed the bugs. SFL also led more developers to inspect the faulty code and locate the faulty method. However, they did not spend less time locating the faults. SFL was well‐accepted by the participants, who showed intention to use it in their daily activities. Our results indicate that SFL is useful even when the fault is not ranked among the first positions, leading developers to reach faulty code regions and find the bugs.
Diamictic sediments within high Arctic lake sediment cores: evidence for lake ice rafting along the lateral glacial margin

Sediment cores from six small lake basins in the Canadian high Arctic reveal a gravel‐rich (≤30% by weight) to gravel‐poor (≥2%) diamict facies underlying massive, post‐glacial, clayey silt. Ten other lakes contain a second diamict facies within what are interpreted to be glaciolacustrine sedimentary assemblages. The sedimentology, clast fabrics and fossil remains (diatoms, ostracodes and chironomid head capsules) within both diamict facies suggest that these deposits are not tills. Clast fabrics yielded low S1 (0·41–0·57) and high S3 (0·09–0·22) eigenvalues, placing them within the range of ice‐rafted diamictons and glacigenic sediment flows. The high percentage of clast dip angles >45° (15–61%), random clast azimuth and lower diamict contacts conformable to underlying current‐bedded sediment favours an origin as a rain‐out or settling deposit. Samples of the matrix and scrapings of clasts from the diamicts revealed a diatom assemblage dominated by littoral and planktonic forms, such as are found in the littoral regions of the lakes today. This contrasts sharply with the assemblages within the overlying clayey silt, in which benthic forms predominate. Clasts are thus interpreted to have been rafted from the littoral areas of the lake. The process proposed to explain this is rafting by the lake ice cover in a glacial‐marginal environment. Early season meltwater, impounded along the lateral margin of retreating cold‐based glaciers, would buoyantly lift the lake ice cover and any adfrozen lake sediment. Higher lake levels and increased areal extent of seasonal freeze‐on between the lake ice cover and the lake bed would allow the redeposition of littoral sediments to the benthic regions through greater lateral shifting of the ice cover as it broke up. Incision by meltwater streams into the lateral glacial margins would later isolate the lake, allowing seasonal warming of lake water, enough to support the growth and maturation of the ostracode and chironomid species found as fossils within the diamicts.
The hydrologic importance of transpiration control by stomata

Plant canopies are not passive evaporating surfaces. The regulation of water loss from plants is an important function of leaf stomata, and significant stomatal regulation occurs throughout the range of leaf-pore diameters. Leaf pores do not ‘interfere’ with one another to any significant extent in the conductance of water vapor or other gases. The diffusive conductance of small pores is more sensitive to diameter changes at the larger apertures, thus permitting CO2 exchange for photosynthesis without dehydration of the leaf mesophyll. In still air the external resistance over broad leaves limits control by stomata, but light drafts usually minimize this effect in field situations. Characteristic diffusion coefficients for leaf types, based on a careful study of leaf microstructure, physiology, and seasonal variation, are a rational basis for cover-type conversions or biochemical controls to reduce water loss.
My avatar, fashion and me

• Objective Based on the study of Animal Crossing: New Horizons (ACNH), our study aims to understand the relationship between the player, their avatar and fashion. It intends to answer two main questions: What are the specificities of the player’s projection mechanism towards their avatar in this video game? What is the role of fashion in this mechanism?
Adversarial Robustness in Deep Neural Networks based on Variable Attributes Stochastic Ensemble Model

Deep neural networks (DNN) have been shown to suﬀer from critical vulnerabilities under adversarial attacks. This phenomenon stimulated the creation of diﬀerent attack and defense strategies similar to those adopted in cyberspace security. The dependence of such strategies on attack and defense mechanisms makes the associated algorithms on both sides appear as closely reciprocating processes, where the defense method are particularly passive in these processes. Inspired by the dynamic defense approach proposed in cyberspace to solve this end-less arm race, this paper deﬁnes the model order, network structure and smoothing parameters as ensemble variable attributes and proposes a stochastic strategy to builds upon ensemble model through heterogeneous and redundancy models. The proposed method introduces the diversity and randomness characteristic to deep neural network to change