Miracle-dz/UniFAR-FTUs huggingface dataset:
4 The hepatic uptake of VLDL in lrp - ldlr -/- vldlr -/- mice is regulated by LPL activity and involves proteoglycans and SR-BI

Lipoprotein lipase (LPL) activity plays an important role in preceding the remnant clearance via the three major apoE-recognizing receptors, the LDL receptor (LDLr), LDLr related protein (LRP), and VLDL receptor (VLDLr). We recently showed that lrp - ldlr -/- vldlr -/- mice have elevated fasted plasma total cholesterol (TC) and triglyceride (TG), mainly present as VLDL. However, since VLDL is continuously produced by the liver, their core remnants must thus still be cleared to attain steady state lipid levels in plasma. The aim of this study was to determine whether LPL activity is important for the clearance of VLDL core remnants irrespective of these receptors, and to determine the mechanisms involved in the hepatic uptake of these remnants. Administration of an adenovirus expressing LPL (Ad LPL ) into lrp - ldlr -/- vldlr -/- mice reduced both VLDL-TG and VLDL-TC levels. Conversely, inhibition of LPL by Ad APOC1 increases plasma VLDL-TG and VLDL-TC levels. Metabolic studies with radiolabeled VLDL-like emulsion particles showed that the clearance and hepatic association of their core remnants positively correlated with LPL activity. This hepatic association was independent of the bridging function of LPL and HL, since heparin did not reduce the liver association. In vitro studies demonstrated that VLDL-like emulsion particles avidly bound to the cell surface of primary hepatocytes from lrp - ldlr -/- vldlr -/- mice, followed by slow internalization, and involved heparin-releasable cell surface proteins as well as scavenger receptor BI (SR-BI). Collectively, we conclude that hepatic VLDL remnant uptake in absence of the three classical apoE-recognizing receptors is regulated by LPL activity and involves heparan sulfate proteoglycans and SR-BI. clearance previously catalytically inactive LPL rather than increased the cell association of the particles. These data indicate that the rapid initial hepatic association of the particle core remnants in lrp - ldlr -/- vldlr -/- mice is likely to be independent of the bridging function of LPL and HL. This is corroborated by our observation that Ad APOC1 reduced the hepatic association of the particle core remnants without affecting either post-heparin plasma levels of LPL activity (11.5±7.6 vs 11.4±1.6 µmol FFA/h/mL) LPL protein (295±40 vs 254±53 ng/mL) to Ad LacZ the positive correlation between plasma LPL and hepatic VLDL remnant uptake in lrp - ldlr -/- vldlr -/-mice does seem to
HEAVY METAL CONTENT OF THE VEGETATION ON KARSTIC SOILS

Osszefoglalas - A talaj-novenyzet kapcsolatrendszer fontos szerepet jatszik a karsztokologiai rendszer folyamataiban. A talaj toleralni kepes a kornyezeti behatasokat, amelyek megvaltoztathatjak a karsztrendszert. Bizonyos korlatok kozott a talaj kepes megkotni a nem-karsztos anyagokat, amelyek termeszetes vagy mesterseges folyamatok eredmenyekent jutnak be a talajba. A talajok savanyodasa kovetkezteben a nehezfemek mobilizalodhatnak a talajban, es igy konnyen bejuthatnak a novenyi szervezetekbe es a karsztvizrendszerbe. A tanulmany bemutatja az Aggteleki Karszt teruleten folyo vizsgalati eredmenyek alapjan a teruleten az EDTA oldhato nehezfem tartalom es a novenyzet nehezfem tartalmanak kapcsolatat. Summary - The soil-vegetation system has a great importance to process in the karst-ecologycal system. Soils can buffer environmental impacts and they can change the karst system. Within certain limits, soils can bind the nonkarstic materials (e.g. heavy metals) which enter the soil by deposition or any anthropogenic influent. The result of the soil acidification the heavy metals can get into the vegetation and the karst water system. The present paper describes investigations the heavy metal content of plants in relation to the exchangeable heavy metal content in the Aggtelek region, Hungary.
Biostratigraphical and palaeobiogeographical implications of Lower Silurian Radiolaria from black cherts of the Armorican Massif (France)

A moderately well-preserved radiolarian assemblage was recovered from organic-rich black chert in a Llandovery (Lower Silurian) sequence that crops out in southern Brittany (Chalonnes-sur-Loire section, Armorican Massif, France). The assemblage is composed of two families (Rotasphaeridae and Haplotaeniatidae), four genera (? Diparvapila, Secuicollacta, Orbiculopylorum, Haplotaeniatum) and 13 species. Some were identified from whole specimens preserved in silica and extracted following dilute hydrofluoric acid processing, while others were recognized in thin-section preparations, as they are beautifully preserved as ‘carbonized’ microfossils. The age range suggested by conodonts and chitinozoans yielded after HF processing from one of the 27 studied samples is in good agreement with the previously published age based on graptolites. The recovered radiolarians are discussed, documented and compared with known Rhuddanian, Aeronian and lower Telychian assemblages in the literature. The stratigraphic ranges are extended for the species Secuicollacta bipola, S. hexactinia, S. parvitesta, Orbiculopylorum granti and O. splendens based on our new data. A significant number of radiolarians found in our samples occur in Llandovery sections from Alaska, Nevada, Arctic Canada and Sweden. These similarities are used to discuss the palaeodistribution of Lower Silurian Radiolaria and our observations support the hypothesis of a wide geographical distribution for these Palaeozoic species.
Application of machine learning approaches to administrative claims data to predict clinical outcomes in medical and surgical patient populations

Objective This study aimed to develop and validate a claims-based, machine learning algorithm to predict clinical outcomes across both medical and surgical patient populations. Methods This retrospective, observational cohort study, used a random 5% sample of 770,777 fee-for-service Medicare beneficiaries with an inpatient hospitalization between 2009–2011. The machine learning algorithms tested included: support vector machine, random forest, multilayer perceptron, extreme gradient boosted tree, and logistic regression. The extreme gradient boosted tree algorithm outperformed the alternatives and was the machine learning method used for the final risk model. Primary outcome was 30-day mortality. Secondary outcomes were: rehospitalization, and any of 23 adverse clinical events occurring within 30 days of the index admission date. Results The machine learning algorithm performance was evaluated by both the area under the receiver operating curve (AUROC) and Brier Score. The risk model demonstrated high performance for prediction of: 30-day mortality (AUROC = 0.88; Brier Score = 0.06), and 17 of the 23 adverse events (AUROC range: 0.80–0.86; Brier Score range: 0.01–0.05). The risk model demonstrated moderate performance for prediction of: rehospitalization within 30 days (AUROC = 0.73; Brier Score: = 0.07) and six of the 23 adverse events (AUROC range: 0.74–0.79; Brier Score range: 0.01–0.02). The machine learning risk model performed comparably on a second, independent validation dataset, confirming that the risk model was not overfit. Conclusions and relevance We have developed and validated a robust, claims-based, machine learning risk model that is applicable to both medical and surgical patient populations and demonstrates comparable predictive accuracy to existing risk models.
An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or direct commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works, requires prior specific permission and/or a fee. Permissions may be requested from Publications Consider a set S of n data points in real d-dimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q ∈ R d , the closest point of S to q can be reported quickly. Given any positive real , a data point p is a (1 +)-approximate nearest neighbor of q if its distance from q is within a factor of (1 +) of the distance to the true nearest neighbor. We show that it is possible to preprocess a set of n points in R d in O(dn log n) time and O(dn) space, so that given a query point q ∈ R d , and > 0, a (1 +)-approximate nearest neighbor of q can be computed in O(c d,, log n) time, where c d,, ≤ d 1 + 6d// d is a factor depending only on dimension and. In general, we show that given an integer k ≥ 1, (1 +)-approximations to the k nearest neighbors of q can be computed in additional O(kd log n) time.
Public Health Goal for Endrin In Drinking Water

California with whom OEHHA contracted through the UC Office of the President for their peer reviews of the PHG documents, and gratefully acknowledge the comments received from all interested parties. This Public Health Goal (PHG) technical support document provides information on health effects from contaminants in drinking water. PHGs are developed for chemical contaminants based on the best available toxicological data in the scientific literature. These documents and the analyses contained in them provide estimates of the levels of contaminants in drinking water that would pose no significant health risk to individuals consuming the water on a daily basis over a lifetime. risk assessments and adopt PHGs for contaminants in drinking water based exclusively on public health considerations. The Act requires that PHGs be set in accordance with the following criteria: 1. PHGs for acutely toxic substances shall be set at levels at which no known or anticipated adverse effects on health will occur, with an adequate margin of safety. 2. PHGs for carcinogens or other substances which can cause chronic disease shall be based solely on health effects without regard to cost impacts and shall be set at levels which OEHHA has determined do not pose any significant risk to health. 3. To the extent the information is available, OEHHA shall consider possible synergistic effects resulting from exposure to two or more contaminants. 4. OEHHA shall consider the existence of groups in the population that are more susceptible to adverse effects of the contaminants than a normal healthy adult. 5. OEHHA shall consider the contaminant exposure and body burden levels that alter physiological function or structure in a manner that may significantly increase the risk of illness. 6. In cases of insufficient data to determine a level of no anticipated risk, OEHHA shall set the PHG at a level that is protective of public health with an adequate margin of safety. 7. In cases where scientific evidence demonstrates that a safe dose-response threshold for a contaminant exists, then the PHG should be set at that threshold. 8. The PHG may be set at zero if necessary to satisfy the requirements listed above. 9. OEHHA shall consider exposure to contaminants in media other than drinking water, including food and air and the resulting body burden. 10. PHGs adopted by OEHHA shall be reviewed every five years and revised as necessary based on the availability of new scientific data. PHGs adopted …
photoreceptor cell line as a cell model for studying retinal ciliopathies. Frontiers in Genetics

The retina contains several ciliated cell types, including the retinal pigment epithelium (RPE) and photoreceptor cells. The photoreceptor cilium is one of the most highly modiﬁed sensory cilia in the human body. The outer segment of the photoreceptor is a highly elaborate primary cilium, containing stacks or folds of membrane where the photopigment molecules are located. Perhaps unsurprisingly, defects in cilia often lead to retinal phenotypes, either as part of syndromic conditions involving other organs, or in isolation in the so-called retinal ciliopathies. The study of retinal ciliopathies has been limited by a lack of retinal cell lines. RPE1 retinal pigment epithelial cell line is commonly used in such studies, but the existence of a photoreceptor cell line has largely been neglected in the retinal ciliopathy ﬁeld. 661W cone photoreceptor cells, derived from mouse, have been widely used as a model for studying macular degeneration, but not described as a model for studying retinal ciliopathies such as retinitis pigmentosa. Here, we characterize the 661W cell line as a model for studying retinal ciliopathies. We fully characterize the expression proﬁle of these cells, using whole transcriptome RNA sequencing, and provide this data on Gene Expression Omnibus for the advantage of the scientiﬁc community. We show that these cells express the majority of markers of cone cell origin. Using immunostaining and confocal microscopy, alongside scanning electron microscopy, we show that these cells grow long primary cilia, reminiscent of photoreceptor outer segments, and localize many cilium proteins to the axoneme, membrane and transition zone. We show that siRNA knockdown of cilia genes Ift88 results in loss of cilia, and that this can be assayed by high-throughput screening. We present evidence that the 661W cell line is a useful cell model for studying retinal ciliopathies.
Combining Crowdsourcing and Learning to Improve Engagement and Performance

Crowdsourcing complex creative tasks remains difﬁcult, in part because these tasks require skilled workers. Most crowd-sourcing platforms do not help workers acquire the skills nec­ essary to accomplish complex creative tasks. In this paper, we describe a platform that combines learning and crowdsourc­ ing to beneﬁt both the workers and the requesters. Workers gain new skills through interactive step-by-step tutorials and test their knowledge by improving real-world images submit­ ted by requesters. In a series of three deployments spanning two years, we varied the design of our platform to enhance the learning experience and improve the quality of the crowd work. We tested our approach in the context of LevelUp for Photoshop , which teaches people how to do basic photograph improvement tasks using Adobe Photoshop. We found that by using our system workers gained new skills and produced high-quality edits for requested images, even if they had little prior experience editing images.
Simulated Distribution of Active Layer Depths in the Frozen Ground Regions of Tibetan Plateau

Active layer is the near-surface layer of frozen soil,which thaws in summer while freezes in winter.In seasonally frozen ground regions as well as permafrost regions,active layer is the most active terrane in terms of thermodynamics.Active layer plays an important role,because almost all ecological,hydrological,pedological and biological activities take place within it.Ground surface freezing index and thawing index are simulated based on the ground surface temperature in the 1990s acquired from 80 meteorological stations on the Tibetan Plateau and nearby regions,together with digital elevation model.Taking the mean annual ground surface temperature isotherm of 0.8 ℃ as the boundary of permafrost and seasonally frozen ground,in consideration of thermal offset,the thawed depth in the permafrost areas and frozen depth in the seasonally frozen ground regions are worked out respectively through Stephen Formula.
Sequential extraction of Zn in deposol.

The aim of the study is prediction of environmental risk of heavy metal by using sequenstial extraction. The soil samples were collected at two different locations, two coal mining areas in Serbia which are potential contaminant spots. Tessier's sheme was applayed for soil fractionation. Fractions were rearranged into five fractions defined as two acid soluble, reducible, oxidisable and residual. Highest concentration of Zn was found in fifth fraction (residual fraction) at both locations, but samples from Kolubara had higher concentration. Lowest concentration of Zn was found in water-soluble and exchangeable adsorbed fraction which is environmentaly dangerous.
UAV Immersive Video Streaming: A Comprehensive Survey, Benchmarking, and Open Challenges

Over the past decade, the utilization of UAVs has witnessed significant growth, owing to their agility, rapid deployment, and maneuverability. In particular, the use of UAV-mounted 360-degree cameras to capture omnidirectional videos has enabled truly immersive viewing experiences with up to 6DoF. However, achieving this immersive experience necessitates encoding omnidirectional videos in high resolution, leading to increased bitrates. Consequently, new challenges arise in terms of latency, throughput, perceived quality, and energy consumption for real-time streaming of such content. This paper presents a comprehensive survey of research efforts in UAV-based immersive video streaming, benchmarks popular video encoding schemes, and identifies open research challenges. Initially, we review the literature on 360-degree video coding, packaging, and streaming, with a particular focus on standardization efforts to ensure interoperability of immersive video streaming devices and services. Subsequently, we provide a comprehensive review of research efforts focused on optimizing video streaming for timevarying UAV wireless channels. Additionally, we introduce a high resolution 360-degree video dataset captured from UAVs under different flying conditions. This dataset facilitates the evaluation of complexity and coding efficiency of software and hardware video encoders based on popular video coding standards and formats, including AVC/H.264, HEVC/H.265, VVC/H.266, VP9, and AV1. Our results demonstrate that HEVC achieves the best trade-off between coding efficiency and complexity through its hardware implementation, while AV1 format excels in coding efficiency through its software implementation, specifically using the libsvt-av1 encoder. Furthermore, we present a real testbed showcasing 360-degree video streaming over a UAV, enabling remote control of the drone via a 5G cellular network.
Finite-temperature structure of the MAPbI3 perovskite: Comparing density functional approximations and force fields to experiment Lahnsteiner,

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Detecting Visual Cues in the Intensive Care Unit and Association with Patient Clinical Status

Intensive Care Units (ICU) provide close supervision and continuous care to patients with life-threatening conditions. However, continuous patient assessment in the ICU is still limited due to time constraints and the workload on healthcare providers. Existing patient assessments in the ICU such as pain or mobility assessment are mostly sporadic and administered manually, thus introducing the potential for human errors. Developing Artificial intelligence (AI) tools that can augment human assessments in the ICU can be beneficial for providing more objective and granular monitoring capabilities. For example, capturing the variations in a patient's facial cues related to pain or agitation can help in adjusting pain-related medications or detecting agitation-inducing conditions such as delirium. Additionally, subtle changes in visual cues during or prior to adverse clinical events could potentially aid in continuous patient monitoring when combined with high-resolution physiological signals and Electronic Health Record (EHR) data. In this paper, we examined the association between visual cues and patient condition including acuity status, acute brain dysfunction, and pain. We leveraged our AU-ICU dataset with 107,064 frames collected in the ICU annotated with facial action units (AUs) labels by trained annotators. We developed a new"masked loss computation"technique that addresses the data imbalance problem by maximizing data resource utilization. We trained the model using our AU-ICU dataset in conjunction with three external datasets to detect 18 AUs. The SWIN Transformer model achieved 0.57 mean F1-score and 0.89 mean accuracy on the test set. Additionally, we performed AU inference on 634,054 frames to evaluate the association between facial AUs and clinically important patient conditions such as acuity status, acute brain dysfunction, and pain.
Estimating Distances from Parallaxes. VI. A Method for Inferring Distances and Transverse Velocities from Parallaxes and Proper Motions Demonstrated on Gaia Data Release 3

The accuracy of stellar distances inferred purely from parallaxes degrades rapidly with distance. Proper motion measurements, when combined with some idea of typical velocities, provide independent information on stellar distances. Here, I build a direction- and distance-dependent model of the distribution of stellar velocities in the Galaxy, then use this together with parallaxes and proper motions to infer kinegeometric distances and transverse velocities for stars in Gaia DR3. Using noisy simulations, I assess the performance of the method and compare its accuracy to purely parallax-based (geometric) distances. Over the whole Gaia catalog, kinegeometric distances are on average 1.25 times more accurate than geometric ones. This average masks a large variation in the relative performance, however. Kinegeometric distances are considerably better than geometric ones beyond several kpc, for example. On average, kinegeometric distances can be measured to an accuracy of 19% and velocities ( vα*2+vδ2 ) to 16 km s−1 (median absolute deviations). In Gaia DR3, kinegeometric distances are smaller than geometric ones on average for distant stars, but the pattern is more complex in the bulge and disk. With the much more accurate proper motions expected in Gaia DR5, a further improvement in the distance accuracy by a factor of (only) 1.35 on average is predicted (with kinegeometric distances still 1.25 times more accurate than geometric ones). The improvement attained from proper motions is limited by the width of the velocity prior, in a way that the improvement from better parallaxes is not limited by the width of the distance prior.
Robustify and Tighten the Lee Bounds: A Sample Selection Model under Stochastic Monotonicity and Symmetry Assumptions

In the presence of sample selection, Lee's (2009) nonparametric bounds are a popular tool for estimating a treatment effect. However, the Lee bounds rely on the monotonicity assumption, whose empirical validity is sometimes unclear. Furthermore, the bounds are often regarded to be wide and less informative even under monotonicity. To address these issues, this study introduces a stochastic version of the monotonicity assumption alongside a nonparametric distributional shape constraint. The former enhances the robustness of the Lee bounds with respect to monotonicity, while the latter helps tighten these bounds. The obtained bounds do not rely on the exclusion restriction and can be root-$n$ consistently estimable, making them practically viable. The potential usefulness of the proposed methods is illustrated by their application on experimental data from the after-school instruction programme studied by Muralidharan, Singh, and Ganimian (2019).