Miracle-dz/UniFAR-FTUs huggingface dataset:
UvA-DARE Measurement of the inclusive isolated prompt photon cross section in pp collisions at √s = 7 TeV with the ATLAS detector

A measurement of the cross section for the inclusive production of isolated prompt photons in pp collisions at a center-of-mass energy ﬃﬃﬃ s p ¼ 7 TeV is presented. The measurement covers the pseudorapidity ranges j (cid:1) (cid:2) j < 1 : 37 and 1 : 52 (cid:1) j (cid:1) (cid:2) j < 1 : 81 in the transverse energy range 15 (cid:1) E (cid:2) T < 100 GeV . The results are based on an integrated luminosity of 880 nb (cid:2) 1 , collected with the ATLAS detector at the Large Hadron Collider. Photon candidates are identiﬁed by combining information from the calorimeters and from the inner tracker. Residual background in the selected sample is estimated from data based on the observed distribution of the transverse isolation energy in a narrow cone around the photon candidate. The results are compared to predictions from next-to-leading-order perturbative QCD calculations.
Inversion of transferaccommodation zones in salt-bearing extensional systems: insights from analogue modeling

This work uses sandbox analogue models to analyze the formation and subsequent inversion of a decoupled extensional system comprised of two segmented half-grabens with thick early syn-rift salt. The segmented half grabens strike perpendicular to the direction of extension and subsequent shortening. Rifting created first a basement topography that was infilled by model salt, followed by a second phase of extension and sedimentation, followed afterwards by inversion. During 10 the second phase of extension, syn-rift syncline minibasins developed above the basement extensional system and extended beyond the confines of the fault blocks. Sedimentary downbuilding and extension initiated the migration of model salt to the basement highs, forming salt anticlines, reactive diapirs, and salt walls perpendicular to the direction of extension, except for along the transferaccommodation zone where a slightly oblique salt anticline developed. Inversion resulted in decoupled cover and basement thrust systems. Thrusts in the cover system nucleated along squeezed salt structures and along primary welds. 15 New primary welds developed where the cover sequence touched down on basement thrust tips due to uplift, salt extrusion, and syn-contractional downbuilding caused by loading of syn-contractional sedimentation. Model geometries reveal the control imposed by the basement configuration and distribution of salt in the development of a thrust front from the inversion of a salt-bearing extensional system. In 3D, the interaction of salt migrating from adjacent syn-rift basins can modify the expected salt structure geometry, which may in turn influence the location and style of thrust in the cover sequence upon 20 inversion. Results are compared to the northern Lusitanian Basin, offshore Portugal and the Isàbena area of the South-Central Pyrenees, Spain.
and evaluation

In the main suit and ancillary suit, what is most noticeable is the confrontation of one or more plaintiffs against one or more defendants, or the entry and attraction of a person or third parties to the main litigation. The question is, according to the rules governing litigation, can a large number of persons be used as a party to the litigation (plaintiffs or defendants), without all of them participating directly in the proceedings? Article 74 of the Code of Civil Procedure has implicitly identified a form of civil litigation. This type of claims applies to certain non-enclosed people from a village or part of the city, but plaintiff only one or a few of them will be listed in his petition as a defendant. This claim is generally considered to be plaintiff and their teammate, and in particular, such as claims related to consumer rights (According to Article 48 of the e-commerce law, approved by the Islamic Consultative Assembly of Iran on February 17, 2002), are focused on claimants. It should be noted that, this type of lawsuit has the official name in foreign law, especially American law, as a class action. This article proves the necessity of such a lawsuit by focusing on the readers and their teammate.
A global daily gap-filled chlorophyll-a dataset in open oceans during 2001–2021 from multisource information using convolutional neural networks

Abstract. Ocean color data are essential for developing our understanding of biological and ecological phenomena and processes and also of important sources of input for physical and biogeochemical ocean models. Chlorophyll-a (Chl-a) is a critical variable of ocean color in the marine environment. Quantitative retrieval from satellite remote sensing is a main way to obtain large-scale oceanic Chl-a. However, missing data are a major limitation in satellite remote-sensing-based Chl-a products due mostly to the influence of cloud, sun glint contamination, and high satellite viewing angles. The common methods to reconstruct (gap fill) missing data often consider spatiotemporal information of initial images alone, such as Data Interpolating Empirical Orthogonal Functions, optimal interpolation, Kriging interpolation, and the extended Kalman filter. However, these methods do not perform well in the presence of large-scale missing values in the image and overlook the valuable information available from other datasets for data reconstruction. Here, we developed a convolutional neural network (CNN) named Ocean Chlorophyll-a concentration reconstruction by convolutional neural NETwork (OCNET) for Chl-a concentration data reconstruction in open-ocean areas, considering environmental variables that are associated with ocean phytoplankton growth and distribution. Sea surface temperature (SST), salinity (SAL), photosynthetically active radiation (PAR), and sea surface pressure (SSP) from reanalysis data and satellite observations were selected as the input of OCNET to correlate with the environment and phytoplankton biomass. The developed OCNET model achieves good performance in the reconstruction of global open ocean Chl-a concentration data and captures spatiotemporal variations of these features. The reconstructed Chl-a data are available online at https://doi.org/10.5281/zenodo.10011908 (Hong et al., 2023). This study also shows the potential of machine learning in large-scale ocean color data reconstruction and offers the possibility of predicting Chl-a concentration trends in a changing environment.
A Dual Method For Backward Stochastic Differential Equations with Application to Risk Valuation

We propose a numerical recipe for risk evaluation defined by a backward stochastic differential equation. Using dual representation of the risk measure, we convert the risk valuation to a stochastic control problem where the control is a certain Radon-Nikodym derivative process. By exploring the maximum principle, we show that a piecewise-constant dual control provides a good approximation on a short interval. A dynamic programming algorithm extends the approximation to a finite time horizon. Finally, we illustrate the application of the procedure to financial risk management in conjunction with nested simulation and on an multidimensional portfolio valuation problem.
Quantification and modeling of the lumbar erector spinae as a function of sagittal plane torso flexion

Forward bending o f the torso, or torso flexion in the sagittal plane, has previously been associated with reports o f low back disorders in the occupational environment. Sagittal plane torso flexion results in anterior rotation o f the lumbar vertebral bodies, resulting in a flattening o f the lumbar spine. The change in lumbar spine orientation results in lengthening o f the lumbar erector spinae muscles, which alters their force producing capability, and would ultimately alter the loading on the lumbar spine that biomechanical models would predict. Prior studies have also indicated that the sagittal plane moment-arms at several lumbar levels decrease as full torso flexion is reached from neutral. However, the relationship between the erector spinae moment-arm and intermediate torso flexion angles between neutral and near full torso flexion is not known. Thus, this study was undertaken to describe, utilizing magnetic resonance imaging, the lumbar erector spinae musculature with respect to the lumbar spine in the sagittal plane as a function o f quantified torso flexion, and investigate the impact on predicted spinal loading. Magnetic resonance imaging scans from subjects in a lateral recumbent posture for four different torso flexion angles indicated that the moment-arms o f the erector spinae at T^/Li, L4/L5 and L5/S1 decrease as the torso was flexed from neutral to 45 degrees. The decrease in sagittal plane erector spinae moment-arms were able to be predicted from the quantified lumbar spinal curvature, torso flexion angle, and anthropometric measures such as the trunk circumference about the iliac crest and trunk width measures at the iliac crest. Utilizing a three-dimensional dynamic electromyogram-driven biomechanical model o f the torso that predicts spinal loading on the L5/S1 intervertébral disc, the erector spinae vector spinae moment-arm from the L5/S1 intervertébral disc was allowed to vary as a fimction o f measured sagittal plane torso flexion. The decrease in the erector spinae moment-arm as a fimction o f torso flexion resulted in an increase in the predicted spinal loading over what would have been predicted from a biomechanical model that did not allow the erector spinae moment-arm to vary as a fimction o f torso flexion.
Contrasting growth and mortality responses of different species lead to shifts in tropical montane tree community composition in a warmer climate

The response of tropical trees and tree communities to climate change is crucial for the carbon storage and 20 biodiversity of the terrestrial biosphere. Trees in tropical montane rainforests (TMFs) are considered particularly vulnerable to climate change, but this hypothesis remains poorly evaluated due to data scarcity. To reduce the knowledge gap on the response of TMFs trees to warming, we established a field experiment along a 1300 - 2400 m elevation gradient in Rwanda. Twenty tree species native to montane forests in East and Central Africa were planted in multispecies plots at three sites along the gradient. They have overlapping distributions but primarily occur in either transitional rainforest (1600 - 2000 m a.s.l) or 25 mid elevation TMF (2000 - 3000 m a.s.l.), with both early- (ES) and late-successional (LS) species represented in each elevation origin group. Tree growth (diameter and height) and survival were monitored regularly over two years. We found that ES species, especially from lower elevations, grew faster at warmer sites while several of the LS species, especially from higher elevations, did not respond or grew slower. Moreover, a warmer climate increased tree mortality in LS species, but not much in ES species. ES species with transitional rainforest origin strongly increased in proportion of stand basal area at warmer 30 sites, while TMF species declined, suggesting that lower-elevation ES species will have an advantage over higher-elevation species in a warming climate. The risk of higher-elevation and LS species to become outcompeted by lower-elevation and ES species in a warmer climate has important implications for biodiversity and carbon storage of Afromontane forests.
Peatland-VU-NUCOM (PVN 1.0): Using dynamic PFTs to model peatland vegetation, CH4 and CO2 emissions

Despite covering only 3% of the planet’s land surface, peatlands store 30% of the planet’s terrestrial carbon. The potential to both emit and drawdown CO 2 and CH 4 , means that peatlands have a complex and multifaceted relationship with the global climate system. The net GHG emissions from peatlands depends on many factors but primarily vegetation composition, ground water level and drainage, land management, and soil temperature. Many peatland models use surface water levels to estimate CH 4 exchange, neglecting to consider the efﬁciency of CH 4 transported to the atmosphere by vegetation. 5 To assess the impact of vegetation on the GHG ﬂuxes of peatlands, we have developed a new model, Peatland-VU-NUCOM (PVN). The new PVN model has been built from two parent models, the Peatland-VU and NUCOM-BOG models. To represent dynamic vegetation, we have introduced plant functional types and competition, adapted from the NUCOM-BOG model, into the Peatland-VU model. The PVN model includes plant competition, CH 4 diffusion, ebullition, root, shoot, litter, exudate production, below-ground decomposition, and above-ground moss development, under changing water levels and climatic 10 conditions. PVN is a site-speciﬁc peatland CH 4 and CO 2 emissions model, able to reproduce vegetation dynamics. Here, we present the PVN model structure and explore the model’s sensitivity to environmental input data and the introduction of the new vegetation-competition schemes. We evaluate the model against observed chamber data collected at two peatland sites in the Netherlands to show that the model is able to reproduce realistic plant biomass fractions, and daily CH 4 and CO 2 ﬂuxes. We ﬁnd that this plot-scale model is ﬂexible and robust and suitable to be used to simulate vegetation dynamics 15 and emissions of other peatland sites.
Bootstrap-based, General-purpose Statistical Inference from Diﬀerential Private Releases

Statistical inference with diﬀerential privacy is essential and often depends on bespoke solutions. The combination of sampling and privacy noise for proper inference is not trivial, especially when sampling and privacy noise come from diﬀerent distributions. We propose a general-purpose method combining the bootstrap with diﬀerentially private non-parametric distribution estimation. Our method applies non-private estimators (e.g., MLE for logistic regression) to diﬀerentially private synthetic data or distribution estimates. The advantage of our approach is that the bootstrap is pure post-processing of a diﬀerentially private mechanism—it does not access the sensitive data multiple times and does not increase the privacy budget. The joint sampling and privacy distribution of statistical estimators is approximated through statistical simulation. We present the results of a series of Monte Carlo experiments and show that our method produces valid inferences for a wide range of data sets (univariate data, multivariate data) and statistical problems (i.e., linear and non-linear queries). Furthermore, we show that our method produces valid conﬁdence intervals that are narrower than conﬁdence intervals produced by bespoke methods.
Regional Anesthesia in Upper-Limb Surgery

Background Local and regional anesthesia is associated with numerous clinical and institutional advantages relative to general anesthesia. As anesthesiologists and surgeons increasingly integrate local and regional anesthesia into their clinical practice, an understanding of the principles, evolution, and trends underpinning modern anesthetic techniques continues to be relevant. Methods A review of the literature in databases Medline, PubMed, and EMBASE identified recent developments, ongoing trends, and historical milestones in upper-limb regional anesthesia. Results Advances in regional anesthetic techniques in the last century have led to reduced postoperative pain, improved safety, and improved outcomes in upper-limb surgery. The development of ultrasound-guided techniques, as well as pharmacological advances in local anesthetic drugs and adjuncts, has further advanced the role of regional anesthesia. Wide-awake local anesthesia with no tourniquet has allowed certain procedures to be performed on select patients in outpatient and low-resource settings. Conclusions This review provides an overview of local and regional anesthesia in the upper-limb from its historical origins to its contemporary applications in upper-limb surgery, particularly during the COVID-19 pandemic.
How Does Reduction Mammaplasty Surgical Technique Impact Clinical, Aesthetic, and Patient-Reported Outcomes?

Background A comprehensive comparison of surgical, aesthetic, and quality of life outcomes by reduction mammaplasty technique does not exist. We sought to ascertain the effect of technique on clinical, aesthetic, and patient-reported outcomes. Methods Patients with symptomatic macromastia undergoing a superomedial or inferior pedicle reduction mammoplasty by a single surgeon were identified. BREAST-Q surveys were administered. Postoperative breast aesthetics were assessed in 50 matched-patients. Patient characteristics, complications, quality of life, and aesthetic scores were analyzed. Results Overall, 101 patients underwent reductions; 60.3% had a superomedial pedicle. Superomedial pedicle patients were more likely to have grade 3 ptosis (P < 0.01) and had significantly shorter procedure time (P < 0.01). Only the inferior pedicle technique resulted in wound dehiscence (P = 0.03) and reoperations from complications (P < 0.01). Those who underwent an inferior pedicle reduction were 4.3 times more likely to experience a postoperative complication (P = 0.03). No differences in quality of life existed between cohorts (P > 0.05). Superomedial pedicle patients received significantly better scarring scores (P = 0.03). Conclusions The superomedial pedicle reduction mammoplasty technique provides clinical and aesthetic benefits compared with the inferior pedicle technique.
QUALITY OF RANDOMIZED CLINICAL TRIAL REPORTS ON VIRTUAL RE-ALITY DURING PERIPHERAL INTRAVENOUS CATHETERIZATION/VENI-PUNCTURE

Objective : to evaluate the quality of reports of randomized clinical trials on virtual reality during peripheral venous catheterization. Method : an evaluative study, conducted in two stages: scoping review, to identify randomized clinical trials on the subject, published in Cochrane, Cumulative Index to Nursing and Allied Health Literature, Embase, PubMed® and Latin American and Caribbean Health Sciences Literature databases; and quality assessment of the reports of randomized clinical trials, using the Consolidated Standards of Reporting Trials. Data were analyzed using descriptive and inferential statistics, and the Kappa Test was applied. Results : a total of 291 studies were found, eight of which were included. Of these, 75% showed good quality reporting, partially meeting the items previously defined as necessary. Conclusion : the articles presented good quality reports
Modeling and Optimization of Corrosion Penetration Rate in Crude Oil Pipeline using Response Surface Methodology based on Aspen HYSYS Simulation Software

- This study aims to investigate the influence of a number of related parameters namely temperature, pressure, flow rate and pH on the corrosion penetration rate (CPR) of crude oil transportation process by pipelines. It intends the mathematical model of these parameters as independent variables with corrosion penetration rate as a dependent variable. The model was used to establish the best values of these parameters using the response surface methodology. Aspen HYSYS software was utilized to simulate the experiments and to calculate the corrosion penetration rate for each experiment. The experiments designed based on the central composite experimental design (CCD) using Minitab 17 software. The mean absolute percentage error was used to determine the conformance of the developed mathematical model. Its value was 0.02%, this indicates that the developed mathematical model was consistent.
Antiphase dynamics between cold-based glaciers in the Antarctic 1 Dry Valleys region and ice extent in the Ross Sea during MIS 5 2

15 During the interglacial and interstadials of Marine Isotope Stage 5 (MIS 5e, 5c, 5a), outlet 16 and alpine glaciers in the Dry Valleys region, Antarctica, appear to have advanced in 17 response to increased precipitation from enhanced open ocean conditions in the Ross Sea. 18 We provide further evidence of this antiphase behaviour through retreat of a peripheral lobe 19 of Taylor Glacier in Pearse Valley, a region that was glaciated during MIS 5. We measured 20 cosmogenic 10 Be and 26 Al in three granite cobbles from thin, patchy drift (Taylor 2 Drift) 21 in Pearse Valley to constrain the timing of retreat of Taylor Glacier. Assuming simple 22 continuous exposure, our minimum, zero erosion, exposure ages suggest Taylor Glacier 23 partially retreated from Pearse Valley no later than 65–74 ka. Timing of retreat after 65 ka 24 and until the Last Glacial Maximum (LGM) when Taylor Glacier was at a minimum position, 25 remains unresolved. The depositional history of permafrost sediments buried below Taylor 2 26 Drift in Pearse Valley was obtained from 10 Be and 26 Al depth profiles to ~3 metres in 27 permafrost in proximity to the cobble sampling sites. Depth profile modelling gives a 28 depositional age for near-surface (<1.65 m) permafrost at Pearse Valley of 180 ka +20 / -40 ka, 29 implying deposition of permafrost sediments predate MIS 5 advances of Taylor Glacier. 30 Depth profile modelling of deeper permafrost sediments (>2.09 m) indicates a depositional 31
Passive microwave remote-sensing-based high-resolution snow depth mapping for Western Himalayan zones using multifactor modeling approach

Abstract. Spatiotemporal snow depth (SD) mapping in the Indian Western Himalayan (WH) region is essential in many applications pertaining to hydrology, natural disaster management, climate, etc. In situ techniques for SD measurement are not sufficient to represent the high spatiotemporal variability in SD in the WH region. Currently, low-frequency passive microwave (PMW) remote-sensing-based algorithms are extensively used to monitor SD at regional and global scales. However, fewer PMW SD estimation studies have been carried out for the WH region to date, which are mainly confined to small subregions of the WH region. In addition, the majority of the available PMW SD models for WH locations are developed using limited data and fewer parameters and therefore cannot be implemented for the entire region. Further, these models have not taken the auxiliary parameters such as location, topography, and snow cover duration (SCD) into consideration and have poor accuracy (particularly in deep snow) and coarse spatial resolution. Considering the high spatiotemporal variability in snow depth characteristics across the WH region, region-wise multifactor models are developed for the first time to estimate SD at a high spatial resolution of 500 m × 500 m for three different WH zones, i.e., Lower Himalayan Zone (LHZ), Middle Himalayan Zone (MHZ), and Upper Himalayan Zone (UHZ). Multifrequency brightness temperature (TB) observations from Advanced Microwave Scanning Radiometer 2 (AMSR2), SCD data, terrain parameters (i.e., elevation, slope, and ruggedness), and geolocation for the winter period (October to March) during 2012–2013 to 2016–2017 are used for developing the SD models for dry snow conditions. Different regression approaches (i.e., linear, logarithmic, reciprocal, and power) are used to develop snow depth models, which are evaluated further to find if any of these models can address the heterogeneous association between SD observations and PMW TB. From the results, it is observed from the analysis that the power regression SD model has improved accuracy in all WH zones with the low root mean square error (RMSE) in the MHZ (i.e., 27.21 cm) compared to the LHZ (32.87 cm) and the UHZ (42.81 cm). The spatial distribution of model-derived SD is highly affected by SCD, terrain parameters, and geolocation parameters and has better SD estimates compared to regional and global products in all zones. Overall results indicate that the proposed multifactor SD models have achieved higher accuracy in deep snowpack (i.e., SD >25 cm) of the WH region compared to previously developed SD models.