Miracle-dz/UniFAR-FTUs huggingface dataset:
Wide-field Multi-object Spectroscopy to Enhance Dark Energy Science from LSST Thematic

LSST will open new vistas for cosmology in the next decade, but it cannot reach its full potential without data from other telescopes. Cosmological constraints can be greatly enhanced using wide-field (> 20 deg total survey area), highly-multiplexed optical and near-infrared multi-object spectroscopy (MOS) on 4–15m telescopes. This could come in the form of suitably-designed large surveys and/or community access to add new targets to existing projects. First, photometric redshifts can be calibrated with high precision using cross-correlations of photometric samples against spectroscopic samples at 0 < z < 3 that span thousands of sq. deg. Cross-correlations of faint LSST objects and lensing maps with these spectroscopic samples can also improve weak lensing cosmology by constraining intrinsic alignment systematics, and will also provide new tests of modified gravity theories. Large samples of LSST strong lens systems and supernovae can be studied most efficiently by piggybacking on spectroscopic surveys covering as much of the LSST extragalactic footprint as possible (up to ∼ 20, 000 square degrees). Finally, redshifts can be measured efficiently for a high fraction of the supernovae in the LSST Deep Drilling Fields (DDFs) by targeting their hosts with wide-field spectrographs. Targeting distant galaxies, supernovae, and strong lens systems over wide areas in extended surveys with (e.g.) DESI or MSE in the northern portion of the LSST footprint or 4MOST in the south could realize many of these gains; DESI, 4MOST, Subaru/PFS, or MSE would all be well-suited for DDF surveys. The most efficient solution would be a new wide-field, highly-multiplexed spectroscopic instrument in the southern hemisphere with > 6m aperture. In two companion white papers we present gains from deep, small-area MOS and from single-target imaging and spectroscopy. ar X iv :1 90 3. 09 32 3v 1 [ as tr oph . C O ] 2 2 M ar 2 01 9
Self-organised criticality in random graph processes

In the first half of this thesis, we study the random forest obtained by conditioning the Erdős--Renyi random graph G(N,p) to include no cycles. We focus on the critical window, in which, as studied by Aldous for G(N,p): p(N) = 1+λN-1/3 N We describe a scaling limit for the sizes of the largest trees in this critical random forest, in terms of the excursions above zero of a particular reflected diffusion. We proceed by showing convergence of the reflected exploration process associated to the critical random forests, using careful enumeration of classes of forests, and the asymptotic properties of uniform trees. In the second half of this thesis, we study a random graph process where vertices have one of k types. An inhomogeneous random graph represents the initial connections between vertices, and over time new edges are added homogeneously, as in the classical random graph process. Each vertex is frozen at some rate, resulting in the removal of its entire component. This is a version of the frozen percolation model introduced by R\'ath, which (under mild conditions) exhibits self-organised criticality: the dynamics first drive the system to a critical state, and from then on maintain it in criticality. We prove a convergence result for the proportion of vertices of each type which survive until time t, and describe the local limit in terms of a multitype branching process whose parameters are critical and given by the solution to an unusual differential equation driven by Perron--Frobenius eigenvectors. The argument relies on a novel multitype exploration process, leading to a concentration result for the proportion of types in all large components of a near-critical inhomogeneous random graph; and on a stronger convergence result for mean-field frozen percolation, when the initial graphs may be random.
Signal separation in convolutive mixtures : contributions to blind separation of sparse sources and adaptive subtraction of seismic multiples

The recovery of correlated signals from their linear combinations is a challenging task and has many applications in signal processing. We focus on two problems that are the blind separation of sparse sources and the adaptive subtraction of multiple events in seismic processing. A special focus is put on convolutive mixtures: for both problems, finite impulse response filters can indeed be estimated for the recovery of the desired signals.For instantaneous and convolutive mixing models, we address the necessary and sufficient conditions for the exact extraction and separation of sparse sources by using the L0 pseudo-norm as a contrast function. Equivalences between sparse component analysis and disjoint component analysis are investigated.For adaptive multiple subtraction, we discuss the limits of methods based on independent component analysis and we highlight equivalence with Lp-norm-based methods. We investigate how other regularization parameters may have more influence on the estimation of the desired primaries. Finally, we propose to improve the robustness of adaptive subtraction by estimating the extracting convolutive filters directly in the curvelet domain. Computation and memory costs are limited by using the uniform discrete curvelet transform.
Age-related learning difficulty through trial-and-error method associated with decreased default mode network integration in healthy middle-aged adults

ABSTRACT Introduction Efficient learning is critical to adapting to different environments. There are well-known learning principles in cognitive rehabilitation, including errorless (EL) and trial-and-error (T&E) learning; however, little is known about their underlying neural mechanisms. In the current study, to understand the age-related changes in learning benefits and neural mechanisms applying EL and T&E learning methods in healthy middle-aged adults, we conducted a graph theoretical analysis using functional magnetic resonance imaging data and analyzed the relationship between learning benefits and age, as well as functional network connectivity and age, with both learning principles. Method A total of 43 participants performed a color-name association task through EL and T&E learning methods. We focused on the functional connectivity patterns of the default mode network (DMN) since previous studies demonstrated this network to be more distinctive and important for the T&E learning method than EL. Within-network functional connectivity was used as the graph metric. Results Age showed significant moderate negative correlations with T&E scores and within-DMN functional connectivity in the test state following T&E learning. Conversely, age was not significantly correlated with EL scores or within-DMN functional connectivity in either the EL learning or test states. Conclusions Our findings demonstrate the age-related learning decline associated with decreased DMN integration with aging, when applying the T&E method but not the EL method, even in healthy middle-aged adults. Relationships between the underlying neural network and age are different depending on the learning method. This suggests the need to take into consideration the remaining learning ability through the T&E learning method compared to normal aging and to utilize residual DMN functioning, in addition to the comparison between score differences between EL and T&E methods, when tailoring an individual learning approach.
on CMS information server CMS NOTE 1997 / 015 CMS Note The Compact Muon Solenoid Experiment

We investigate the possibility to search for squarks and gluinos in t he 4l + Emiss T + jets final state.within the mSUGRA framework. With the chosen set of model paramet ers: A0 = 0, tan = 2 and with both negative and positive, for an integrated luminosity of 10 fb 1 the CMS detector would probe squarks and gluino mass range up to 1 TeV. The reach is higher by 100 GeV in the > 0 case when compared to the < 0 case.
Extragalactic optical and near-infrared foregrounds to 21-cm epoch of reionisation experiments

Abstract Foreground contamination is one of the most important limiting factors in detecting the neutral hydrogen in the epoch of reionisation. These foregrounds can be roughly split into galactic and extragalactic foregrounds. In these proceedings we highlight information that can be gleaned from multi-wavelength extragalactic surveys in order to overcome this issue. We discuss how clustering information from the lower-redshift, foreground galaxies, can be used as additional information in accounting for the noise associated with the foregrounds. We then go on to highlight the expected contribution of future optical and near-infrared surveys for detecting the galaxies responsible for ionising the Universe. We suggest that these galaxies can also be used to reduce the systematics in the 21-cm epoch of reionisation signal through cross-correlations if enough common area is surveyed.
Effect of dose and trap type on captures of striped and spotted cucumber beetles using synthetic vittatalactone

Striped cucumber beetle, Acalymma vittatum (F.) and spotted cucumber beetle (Diabrotica undecimpunctata howardi Barber) are key pests of cucurbits. Pesticide applications directed against cucumber beetles can jeopardize bee pollination which is essential to crop yield. Alternative selective tactics, including behavioral control for managing cucumber beetles, are needed in order to improve pest management. The striped cucumber beetle pheromone vittatalactone is attractive to both male and female adults, and also to spotted cucumber beetles. We tested the response of both species to different doses of synthetic vittatalactone, and to different trap types, in field trapping experiments in Maryland. Both species showed strong dose–response in May–June and October 2020. Among 12 trap types tested during a 2-wk experiment in June, using 1 mg mixed vittatalactone, sticky panel traps caught the most of each species, with vittatalactone-baited traps exceeding unbaited traps by >8 fold for striped and >2 fold for spotted, and with significant response to yellow versus clear color absent in striped, but strong in spotted. Among nonsticky traps, those with yellow or yellow-green exceeded those without these colors for both beetle species, and a ground-placed boll weevil trap captured the most striped cucumber beetles. Bucket-style traps caught excessive nontarget bumblebees (Bombus spp.) if yellow, and a few beetles, if all green. Results allow field monitoring with a choice of sticky or nonsticky traps and suggested lure loading of 1 mg mixed vittatalactone, containing ∼90 µg active isomer. These findings contribute to the development of multispecies behavioral monitoring and control as a component of cucurbit IPM.
A review of Handbook of Ion Channels, by Jie Zheng and Matthew C. Trudeau

Just lifting a finger involves the coordinated opening and closing of billions of ion channels. These natural nanotubes play an essential role in the physiology of all living creatures, from bacteria to humans [1, 2]. By providing for the exchange of ions across cellular membranes, they control a vast range of biological processes, and their dysfunction leads to numerous diseases.
Технологія і безпека продуктів харчування / Technology and safety of food products

The structure of loading different crops onto vessels at the company Ukrelevatorprom’s grain terminal has been considered. The total grain shipped in 2012–2015 was comprised of 33.7–41.5% of maize, 19.7– 32.2% of wheat, 14.4–26.0% of rapeseed, 6.7–14.2% of barley, and 5.4– 11.0% of soya beans. When forming a 35,000-tonne grain shipload, grain lots stored in silos are sometimes of lower quality than contracts require: the protein and gluten contents can be inappropriate, or there can be smut grains or those damaged by sunn pests. The accepted technology of grain shipload formation does not guarantee that the grain quality will be uniform throughout the whole period of loading a vessel, especially in the beginning. In the first 1,000 tonnes of a grain shipload formed, the weight content of wet gluten was found to be 22.6% instead of 23%, the Falling Number was 145–180 s instead of 230s, and the content of smut grains was not the tolerable 5%, but 6.95–7.8%. The subsequent 2,000–3,000 tonnes of wheat, too, had the Falling Number lower than the contract prescribed (142–215 s), and only further on, its value achieved the required range 295–356 s. In the wheat sample formed from 5,000 tonnes, only the test values of the Falling Number (176s) and the content of smut grains (5.1%) were different from what the contract required. The calculated arithmetic means of the quality parameters of the 5,000-tonne wheat samples formed were practically the same as those determined experimentally, except for the values of the Falling Number and the smut grain content. The values of the coefficient of variation obtained showed that the grain lot was of non-uniform quality: it varied in such parameters as the foreign material (20.82–50.93%), sunn pest-damaged grains (7.41–25.76%), Falling Number (8.76–36.36%), and smut grain content (35.88–78.34%). Application of linear programming methods to optimise the shipload composition has allowed all the quality parameters to meet the contract requirements. Loading grain from all silos simultaneously, with the optimum flow ratio, will result in its even distribution in a shipload, and the grain lot will be of higher quality by all the parameters the contract specifies.
Supporting Practice Facilitators in a Learning Health Care System

Author Contributions Michael Parchman, MD, MPH; Brooke Ike, MPH; Katie Osterhage, MMS; and LauraMae Baldwin MD, MPH, contributed to the conception and design of this study. Ashley Johnson, MPH, and Brooke Ike conducted the interviews and developed the initial codebook after reviewing the transcripts and also contributed to the data analysis. All authors contributed to the interpretation of the data and to the writing of the paper. Michael Parchman developed the initial draft of the manuscript, and LauraMae Baldwin, Brooke Ike, Ashley Johnson, and Katie Osterhage provided substantial contributions to the revisions of the manuscript.
Creating Quality: Process Design for Results

This book covers all the basic areas in probability and statistics that are covered in most elementary books on mathematical statistics. It is written so that it can be used at the level in which many courses in a mathematical statistics sequence are taught. If one desires to add an introduction at this level to a more advanced study of probability and statistics, this book will provide the supporting material for such a course.
PRMT5 triggers glucocorticoid-induced cell migration in triple-negative breast cancer

In triple-negative breast cancer, PRMT5 functions as a master transcriptional coregulator of the glucocorticoid receptor regulating cell migration after dexamethasone treatment. PRMT5 acts in this case as a scaffolding protein independently of its catalytic activity to promote HP1g recruitment. Triple-negative breast cancers (TNBCs) are the most aggressive breast cancers, and therapeutic options mainly rely on chemotherapy and immunotherapy. Although synthetic glucocorticoids (GCs) are given to alleviate the side effects of these treatments, GCs and their receptor, the glucocorticoid receptor (GR), were recently associated with detrimental effects, albeit the mechanisms involved remain elusive. Here, we identified the arginine methyltransferase PRMT5 as a master coregulator of GR, serving as a scaffold protein to recruit phospho-HP1γ and subsequently RNA polymerase II, independently of its methyltransferase activity. Moreover, the GR/PRMT5/HP1γ complex regulated the transcription of GC-target genes involved in cell motility and triggering cell migration of human TNBC cells in vitro and in a zebrafish model. Of note, we observed that GR/PRMT5 interaction was low in primary tumors but significantly increased in residual tumors treated with chemotherapy and GCs in neoadjuvant setting. These data suggest that the routine premedication prescription of GCs for early TNBC patients should be further assessed and that this complex could potentially be modulated to specifically target deleterious GR effects.
GSTT1 as a Predictive Marker and Enhancer for Osteogenic Potential of Human Adipose‐Derived Stromal/Stem Cells

Adipose‐derived stromal/stem cells (ASCs) have been extensively studied as cell sources for regenerative medicine for bone because of their excellent proliferative capacity and the ability to obtain a large number of cells with minimal donor morbidity. On the other hand, the differentiation potential of ASCs is generally lower than that of bone marrow‐derived stromal/stem cells and varies greatly depending on donors. In this study, we mined a marker that can predict the osteogenic potential of ASC clones and also investigated the usefulness of the molecule as the enhancer of osteogenic differentiation of ASCs as well as its mechanism of action. Through RNA‐seq gene analysis, we discovered that GSTT1 (Glutathione S‐transferase theta‐1) was the most distinguished gene marker between highly osteogenic and poorly osteogenic ASC clones. Knockdown of GSTT1 in high osteogenic ASCs by siGSTT1 treatment reduced mineralized matrix formation. On the other hand, GSTT1 overexpression by GSTT1 transfection or GSTT1 recombinant protein treatment enhanced osteogenic differentiation of low osteogenic ASCs. Metabolomic analysis confirmed significant changes of metabolites related to bone differentiation in ASCs transfected with GSTT1. A high total antioxidant capacity, low levels of cellular reactive oxygen species, and increased GSH/GSSG ratios were also detected in GSTT1‐transfected ASCs. When the in vivo effect of GSTT1‐transfected ASCs on bone regeneration was investigated with segmental long‐bone defect model in rats, bone regeneration was significantly better after implantation of GSTT1‐transfected ASCs compared with that of control vector‐transfected ASCs. In conclusion, GSTT1 can be a useful marker to screen the highly osteogenic ASC clones and also a therapeutic factor to enhance the osteogenic differentiation of poorly osteogenic ASC clones. © 2023 American Society for Bone and Mineral Research (ASBMR).
Effectiveness of adding a defibrillator with cardiac resynchronization therapy in heart failure according to the modified Model for End-stage Liver Disease-Albumin score

Abstract Current guidelines lack clear recommendations between the implantation of cardiac resynchronization therapy (CRT) with defibrillator (CRT-D) and CRT with pacemaker (CRT-P). We hypothesized that modified model for end-stage liver disease score including albumin (MELD-Albumin score), could be used to select patients who may not benefit from CRT-D. We consecutively included patients with CRT-P or CRT-D implantation between 2010 and 2022. The primary endpoint was the composite of all-cause mortality or worsening heart failure. We performed multivariable-adjusted Cox proportional hazard regression. We assessed the interaction between the MELD-Albumin score and the effect of adding a defibrillator with CRT.A total of 752 patients were included in this study, with 291 implanted CRT-P. During a median follow-up of 880 days, 205 patients reached the primary endpoint. MELD-Albumin score was significantly associated with the primary endpoint in the CRT-D group [HR 1.16 (1.09–1.24); P < 0.001] but not in the CRT-P group [HR 1.03 (0.95–1.12); P = 0.49]. There was a significant interaction between the MELD-Albumin score and the effect of CRTD (P = 0.013). The optimal cut-off value of the MELD-Albumin score was 12. For patients with MELD-Albumin ≥ 12, CRT-D was associated with a higher occurrence of the primary endpoint [HR 1.99 (1.10–3.58); P = 0.02], whereas not in patients with MELD-Albumin < 12 [HR 1.19 (0.83–1.70); P = 0.35). Our findings suggest that CRT-D is associated with an excess risk of composite clinical endpoints in HF patients with higher MELD-Albumin score.
Benchmarking clinical risk prediction algorithms with ensemble machine learning: An illustration of the superlearner algorithm for the non-invasive diagnosis of liver fibrosis in non-alcoholic fatty liver disease

Background and Aims. Ensemble machine learning (ML) methods can combine many individual models into a single "super" model using an optimal weighted combination. Here we demonstrate how an underutilized ensemble model, the superlearner, can be used as a benchmark for model performance in clinical risk prediction. We illustrate this by implementing a superlearner to predict liver fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). Methods. We trained a superlearner based on 23 demographic and clinical variables, with the goal of predicting stage 2 or higher liver fibrosis. The superlearner was trained on data from the Non-alcoholic steatohepatitis - clinical research network observational study (NASH-CRN, n=648), and validated using data from participants in a randomized trial for NASH (FLINT trial, n=270) and data from examinees with NAFLD who participated in the National Health and Nutrition Examination Survey (NHANES, n=1244). We compared the performance of the superlearner with existing models, including FIB-4, NFS, Forns, APRI, BARD and SAFE. Results. In the FLINT and NHANES validation sets, the superlearner (derived from 12 base models) discriminates patients with significant fibrosis from those without well, with AUCs of 0.79 (95% CI: 0.73-0.84) and 0.74 (95% CI: 0.68-0.79). Among the existing scores considered, the SAFE score performed similarly to the superlearner, and the superlearner and SAFE scores outperformed FIB-4, APRI, Forns, and BARD scores in the validation datasets. A superlearner model derived from 12 base models performed as well as one derived from 90 base models. Conclusions. The superlearner, thought of as the "best-in-class" ML prediction, performed better than most existing models commonly used in practice in detecting fibrotic NASH. The superlearner can be used to benchmark the performance of conventional clinical risk prediction models.
Sustained delivery of triamcinolone acetonide from a thermosensitive microemulsion gel system for the treatment of sensorineural hearing loss

Abstract Intratympanic administration for the delivery of steroids has been extensively studied but limited because of low permeability of the drug through the row window membrane. Here, to effectively deliver poorly soluble triamcinolone acetonide (TA), microemulsions (ME) were prepared from Capmul MCM (oil), Cremophor RH40 (surfactant), and tetraglycol (cosurfactant) based on solubility studies, emulsifying ability test, and pseudoternary phase diagrams. Microemulsion gel (MEG) was prepared by mixing TA-ME with a poloxamer hydrogel base. The physicochemical properties of ME and MEG formulations were characterized, and the toxicity and oto-protective effectiveness were evaluated in vitro and in vivo. The ME-3 formulation showed a small droplet size (16.5 ± 0.2 nm), narrow PDI (0.067 ± 0.041), and enhanced TA solubility (2619.7 ± 57.6 μg/g). The optimized MEG demonstrated temperature-dependent gelation with a gelation time of 208 ± 10 sec at 37 °C. Slow degradation of the gel matrix sustained release of TA from MEG compared to the ME formulation. Both TA-ME and TA-MEG were found to be nontoxic to NIH3T3 cells at the test concentrations (0 to 5 µg/mL), and biocompatible after intratympanic administration to mice. The incorporation of ME into thermosensitive hydrogels prolonged retention of TA at the site of administration until 6 days. As a consequence, the enhanced drug absorption into the cochlea in TA-MEG group (approximately 2 times higher than other groups) protected hair cells, spiral ganglion neurons, and stria vascular cells from cisplatin-induced damage. Therefore, this injectable TA-loaded MEG is an effective and safe vehicle for the sustained delivery of triamcinolone acetonide into the inner ear. Graphical Abstract