julilili42/papers huggingface dataset:
Impact of various aeration strategies on the removal of micropollutants and biological effects in aerated horizontal flow treatment wetlands
2022-03-08

Two aerated horizontal subsurface flow treatment wetlands were studied over two years for the removal efficacy with respect of conventional wastewater parameters, micropollutants and effect-based methods. One wetland served as control and was aerated 24 h d<sup>-1</sup> across 100% of the fractional length of the system. The second aerated horizontal flow treatment wetland was investigated under several aeration modes: first year with a zone of 85% aeration, followed by five months with a zone of 50% aeration and six months with a zone of 35% aeration. With 85% aeration, no significant difference in the removal efficacy as compared to the fully aerated control could be observed, except for E. coli, which were removed four times better in the control. No significant difference in removal efficacy for Total Organic Carbon, 5-day Carbonaceous Biochemical Oxygen Demand, caffeine, and naproxen were observed. A 50% non-aerated zone reduced the overall removal efficacy of biological effects. The highest removal efficacy for the moderately biodegradable micropollutants benzotriazole and diclofenac was observed in the system with 50% aeration. This could be due to the sharp increase of dissolved oxygen (DO) and oxidation reduction potential at the passage from the non-aerated to the aerated zone (at 75% of the fractional length). The internal concentration profiles of caffeine, ibuprofen and naproxen varied from 12.5%, 25%, 50% to 75% fractional length due to redox shift, DO variations and other conditions. A reduction of the aerated zone to 35% of the fractional length results in reduced treatment efficacy for benzotriazole, diclofenac, acesulfame and biological effects but 50% aeration yielded as much degradation as the fully aerated control. These results indicate that less aeration could provide similar effluent water quality, depending on the pollutants of interest. E. coli and biological effects were removed best in the fully aerated system.
Acquisition of false certainty: Learners increase their confidence in the correctness of incorrect answers after online information search
2022-03-08

Abstract Background Explorative online information search activities are self‐regulated learning processes that require monitoring in the form of accurate metacognitive judgments about one's own knowledge. People have to judge what they know, but also understand what they do not know. Previous research has explored those two aspects in relation to each other mostly by employing measures of metacognitive calibration and points toward a potential detrimental effect of using the internet to answer knowledge test items. Objectives This research aimed to disentangle those two aspects of knowledge and to describe a false certainty effect (FaCE), indicating an increase in confidence in the correctness of incorrect responses in a knowledge test after online information search. We also aimed to further explore the conditions under which this effect occurs. Methods In two studies participants’ knowledge and on‐item confidence ratings were measured before and after a short online information search activity. In Study 1, we analyzed data of two samples with and without knowledge gain. In Study 2, we manipulated the familiarity of knowledge test items and whether there was an information search activity. Results Study 1 showed that false certainty occurred even when a search activity did not lead to any learning success. This FaCE, however, was stronger when there was actual knowledge gain. In Study 2, we found that the effect was caused by the information search activity itself and not by the pre‐post methodology of identical knowledge‐test items. Implications Our results demonstrate the emergence of increased confidence in the correctness of incorrect responses in knowledge tests after online information search activities. Educators and researchers should be aware of this undesired false certainty effect of computer‐assisted learning on individuals’ knowledge monitoring.
Optimal surgical workup to ensure safe recovery of the donor after living liver donation – A systematic review of the literature and expert panel recommendations
2022-03-08

Abstract Background The essential premise of living donor liver transplantation is the assurance that the donors will have a complication‐free perioperative course and a prompt recovery. Selection of appropriate donors is the first step to support this premise and is based on tests that constitute the donor workup. The exclusion of liver pathologies and assessment of liver anatomy and volume in the donor candidate are the most important elements in the selection of the appropriate candidate. Objective To determine whether there is evidence to define an optimal donor surgical workup that would improve short‐term outcomes of the donor after living liver donation. Data sources Ovid Medline, Embase, Scopus, Google Scholar, and Cochrane Central. Methods Systematic review following PRISMA guidelines and recommendations using the GRADE approach derived from an international expert panel. Results Although a liver biopsy remains the only method to exactly determine the percentage and type of steatosis and to detect other liver pathologies, its routine use is not supported. Both magnetic resonance imaging (MRI) and computed tomography (CT) appear to be adequate for quantifying liver volume; the preference for one or the other is often based on center expertise. MRI is clearly a better technique to assess biliary anatomy, although aberrant biliary anatomy may not be clearly detected. MRI is also more accurate than CT in determining low grades of steatosis. CT angiography is the imaging test of choice to assess the vascular anatomy. There is no evidence of the need for catheter angiography in the modern evaluation of a living liver donor. Conclusions A donor liver biopsy is indicated if abnormalities are present in serological or imaging tests. Both MRI and CT imaging appear to be adequate methodologies. The routine use of catheter angiography is not supported in view of the adequacy of CT angiography in delineating liver vascular anatomy. No imaging modality available to quantify liver volume is superior to another. Biliary anatomy is better defined with MRI, although poor definition can be expected, particularly for abnormal ducts.
Fetal Tissue-Derived Mast Cells (MC) as Experimental Surrogate for In Vivo Connective Tissue MC
2022-03-08

Bone-marrow-derived mast cells are matured from bone marrow cells in medium containing 20% fetal calf serum (FCS), interleukin (IL)-3 and stem-cell factor (SCF) and are used as in vitro models to study mast cells (MC) and their role in health and disease. In vivo, however, BM-derived hematopoietic stem cells account for only a fraction of MC; the majority of MC in vivo are and remain tissue resident. In this study we established a side-by-side culture with BMMC, fetal skin MC (FSMC) or fetal liver MC (FLMC) for comparative studies to identify the best surrogates for mature connective tissue MC (CTMC). All three MC types showed comparable morphology by histology and MC phenotype by flow cytometry. Heterogeneity was detected in the transcriptome with the most differentially expressed genes in FSMC compared to BMMC being Hdc and Tpsb2. Expression of ST2 was highly expressed in BMMC and FSMC and reduced in FLMC, diminishing their secretion of type 2 cytokines. Higher granule content, stronger response to FcεRI activation and significantly higher release of histamine from FSMC compared to FLMC and BMMC indicated differences in MC development in vitro dependent on the tissue of origin. Thus, tissues of origin imprint MC precursor cells to acquire distinct phenotypes and signatures despite identical culture conditions. Fetal-derived MC resemble mature CTMC, with FSMC being the most developed.
A Bounded $p$-norm Approximation of Max-Convolution for Sub-Quadratic Bayesian Inference on Additive Factors
2022-03-08

Max-convolution is an important problem closely resembling standard convolution; as such, max-convolution occurs frequently across many fields. Here we extend the method with fastest known worst-case runtime, which can be applied to nonnegative vectors by numerically approximating the Chebyshev norm , and use this approach to derive two numerically stable methods based on the idea of computing -norms via fast convolution: The first method proposed, with runtime in (which is less than for any vectors that can be practically realized), uses the -norm as a direct approximation of the Chebyshev norm. The second approach proposed, with runtime in (although in practice both perform similarly), uses a novel null space projection method, which extracts information from a sequence of -norms to estimate the maximum value in the vector (this is equivalent to querying a small number of moments from a distribution of bounded support in order to estimate the maximum). The -norm approaches are compared to one another and are shown to compute an approximation of the Viterbi path in a hidden Markov model where the transition matrix is a Toeplitz matrix; the runtime of approximating the Viterbi path is thus reduced from steps to k \\log(k))$ steps in practice, and is demonstrated by inferring the U.S. unemployment rate from the S&amp;P 500 stock index.
Do people know when they are good at spotting liars? – Metacognitive efficiency in Lie Detection
2022-03-08

We investigated whether the confidence in lie detection judgments is a signal for the accuracy of judgments. We argue that previous methods in tackling this question are inadequate as the assessment of judgment accuracy and confidence is confounded with response bias and lie detection performance. We addressed this confidence-accuracy puzzle by applying a hierarchical Bayesian approach based on Signal-Detection Theory to estimate metacognitive efficiency.Metacognitive efficiency describes individuals' insight into the accuracy of their judgments about truth and deception, but unlike previous measures, it is free of bias and independent of lie detection performance. In re-analyses of 12 studies (N=2817 participants in total), metacognitive efficiency was on average only about 23% of what would have been expected given participants’ discrimination performance. Hence, individuals largely lack metacognitive insight into the quality of their judgments, which is particularly problematic because they cannot reliably discriminate between lies and truths.
Parsimonious Mixed Models
2022-03-08

The analysis of experimental data with mixed-effects models requires decisions about the specification of the appropriate random-effects structure. Recently, Barr, Levy, Scheepers, and Tily, 2013 recommended fitting `maximal' models with all possible random effect components included. Estimation of maximal models, however, may not converge. We show that failure to converge typically is not due to a suboptimal estimation algorithm, but is a consequence of attempting to fit a model that is too complex to be properly supported by the data, irrespective of whether estimation is based on maximum likelihood or on Bayesian hierarchical modeling with uninformative or weakly informative priors. Importantly, even under convergence, overparameterization may lead to uninterpretable models. We provide diagnostic tools for detecting overparameterization and guiding model simplification.
Texture Synthesis Using Convolutional Neural Networks
2022-03-08

Here we introduce a new model of natural textures based on the feature spaces of convolutional neural networks optimised for object recognition. Samples from the model are of high perceptual quality demonstrating the generative power of neural networks trained in a purely discriminative fashion. Within the model, textures are represented by the correlations between feature maps in several layers of the network. We show that across layers the texture representations increasingly capture the statistical properties of natural images while making object information more and more explicit. The model provides a new tool to generate stimuli for neuroscience and might offer insights into the deep representations learned by convolutional neural networks.
The RHIC SPIN Program: Achievements and Future Opportunities
2022-03-08

Time and again, spin has been a key element in the exploration of fundamental physics. Spin-dependent observables have often revealed deficits in the assumed theoretical framework and have led to novel developments and concepts. Spin is exploited in many parity-violating experiments searching for physics beyond the Standard Model or studying the nature of nucleon-nucleon forces. The RHIC spin program plays a special role in this grand scheme: it uses spin to study how a complex many-body system such as the proton arises from the dynamics of QCD. Many exciting results from RHIC spin have emerged to date, most of them from RHIC running after the 2007 Long Range Plan. In this document we present highlights from the RHIC program to date and lay out the roadmap for the significant advances that are possible with future RHIC running.
The LOFT perspective on neutron star thermonuclear bursts
2022-03-08

This is a White Paper in support of the mission concept of the Large Observatory for X-ray Timing (LOFT), proposed as a medium-sized ESA mission. We discuss the potential of LOFT for the study of thermonuclear X-ray bursts on accreting neutron stars. For a summary, we refer to the paper.
Supervised learning sets benchmark for robust spike detection from calcium imaging signals
2022-03-08

A fundamental challenge in calcium imaging has been to infer the timing of action potentials from the measured noisy calcium fluorescence traces. We systematically evaluate a range of spike inference algorithms on a large benchmark dataset recorded from varying neural tissue (V1 and retina) using different calcium indicators (OGB-1 and GCamp6). We show that a new algorithm based on supervised learning in flexible probabilistic models outperforms all previously published techniques, setting a new standard for spike inference from calcium signals. Importantly, it performs better than other algorithms even on datasets not seen during training. Future data acquired in new experimental conditions can easily be used to further improve its spike prediction accuracy and generalization performance. Finally, we show that comparing algorithms on artificial data is not informative about performance on real population imaging data, suggesting that a benchmark dataset may greatly facilitate future algorithmic developments.
Branching Ratios for the Decay of $d^*(2380)$
2022-03-08

Based on measurements the branching ratios for the decay of the recently discovered dibaryon resonance into two-pion production channels and into the channel are evaluated. Possibilities for a decay into the isoscalar single-pion channel are discussed. Finally also the electromagnetic decay of is considered.
A zero-one law for recurrence and transience of frog processes
2022-03-08

We provide sufficient conditions for the validity of a dichotomy, i.e. zero-one law, between recurrence and transience of general frog models. In particular, the results cover frog models with i.i.d. numbers of frogs per site where the frog dynamics are given by quasi-transitive Markov chains or by random walks in a common random environment including super-critical percolation clusters on . We also give a sufficient and almost sharp condition for recurrence of uniformly elliptic frog processes on . Its proof uses the general zero-one law.
Search with UVES and XSHOOTER for signatures of the low-mass secondary in the post common-envelope binary AA Dor
2022-03-08

AA Dor is a close, totally eclipsing, post common-envelope binary with an sdOB-type primary and an extremely low-mass secondary, located close to the mass limit of stable central hydrogen burning. Within error limits, it may either be a brown dwarf or a late M-type dwarf. We aim to extract the secondary's contribution to the phase-dependent composite spectra. The spectrum and identified lines of the secondary decide on its nature. In January 2014, we measured the phase-dependent spectrum of AA Dor with XSHOOTER over one complete orbital period. Since the secondary's rotation is presumable synchronized with the orbital period, its surface strictly divides into a day and night side. Therefore, we may obtain the spectrum of its cool side during its transit and of its hot, irradiated side close to its occultation. We developed the Virtual Observatory (VO) tool TLISA to search for weak lines of a faint companion in a binary system. We identified 53 spectral lines of the secondary in the ultraviolet-blue, visual, and near-infrared XSHOOTER spectra that are strongest close to its occultation. We identified 57 (20 additional) lines in available UVES (Ultraviolet and Visual Echelle Spectrograph) spectra from 2001. The lines are mostly from C II-III and O II, typical for a low-mass star that is irradiated and heated by the primary. We verified the orbital period of P = 22597.033201 +/- 0.00007 s and determined the orbital velocity Ksec = 232.9 (+16.6 / -6.5) km/s of the secondary. The mass of the secondary is Msec = 0.081 (+0.018 / -0.010) Msun and, hence, it is not possible to reliably determine a brown dwarf or an M-type dwarf nature. Although we identified many emission lines of the secondary's irradiated surface, the resolution and signal-to-noise ratio of our UVES and XSHOOTER spectra are not good enough to extract a good spectrum of the secondary's nonirradiated hemisphere.
A Spectral decomposition for the Bolthausen-Sznitman coalescent and the Kingman coalescent
2022-03-08

We consider both the Bolthausen-Sznitman and the Kingman coalescent restricted to the partitions of Spectral decompositions of the corresponding generators are derived. As an application we obtain a formula for the Green's functions and a short derivation of the well-known formula for the transition probabilities of the Bolthausen-Sznitman coalescent.
The model checking fingerprints of CTL operators
2022-03-08

The aim of this study is to understand the inherent expressive power of CTL operators. We investigate the complexity of model checking for all CTL fragments with one CTL operator and arbitrary Boolean operators. This gives us a fingerprint of each CTL operator. The comparison between the fingerprints yields a hierarchy of the operators that mirrors their strength with respect to model checking.
Precision predictions for scalar leptoquark pair production at the LHC
2022-03-08

We present precision predictions for scalar leptoquark pair production at the LHC. Apart from QCD contributions, included are the lepton -channel exchange diagrams relevant in the light of the recent -flavour anomalies. All contributions are evaluated at next-to-leading order in QCD and improved by resummation, in the threshold regime, of the corrections from soft-gluon radiation at the next-to-next-to-leading-logarithmic accuracy. All corrections are found equally relevant. Furthermore, the impact of different sets of parton distribution functions is discussed. These predictions constitute the most precise leptoquark cross section calculations available to date and are necessary for the best exploitation of leptoquark LHC searches.
Differential Impairment Of Cerebrospinal Fluid Synaptic Biomarkers In The Genetic Forms Of Frontotemporal Dementia
2022-03-08

Abstract Background: Approximately a third of frontotemporal dementia (FTD) is genetic with mutations in three genes accounting for most of the inheritance: C9orf72, GRN and MAPT . Impaired synaptic health is a common mechanism in all three genetic variants and so developing fluid biomarkers of this process could be useful as a readout of cellular dysfunction within therapeutic trials. Methods: A total of 193 cerebrospinal fluid (CSF) samples from the GENetic FTD Initiative including 77 presymptomatic (31 C9orf72, 23 GRN, 23 MAPT ) and 55 symptomatic (26 C9orf72 , 17 GRN , 12 MAPT ) mutation carriers as well as 61 mutation-negative controls were measured using a microflow LC PRM-MS set-up targeting 15 synaptic proteins: AP-2 complex subunit beta, complexin-2, beta-synuclein, gamma-synuclein, 14-3-3 proteins (eta, epsilon, zeta/delta), neurogranin, Rab GDP dissociation inhibitor alpha (Rab GDI alpha), syntaxin-1B, syntaxin-7, phosphatidylethanolamine-binding protein 1 (PEBP-1), neuronal pentraxin receptor (NPTXR), neuronal pentraxin 1 (NPTX1), and neuronal pentraxin 2 (NPTX2). Mutation carrier groups were compared to each other and to controls using a bootstrapped linear regression model, adjusting for age and sex. Results: CSF levels of eight proteins were increased only in symptomatic MAPT mutation carriers (compared with controls) and not in symptomatic C9orf72 or GRN mutation carriers: beta-synuclein, gamma-synuclein, 14-3-3-eta, neurogranin, Rab GDI alpha, syntaxin-1B, syntaxin-7, and PEBP-1, with three other proteins increased in MAPT mutation carriers compared with the other genetic groups (AP-2 complex subunit beta, complexin-2, and 14-3-3 proteins zeta/delta). In contrast, CSF NPTX1 and NPTX2 levels were affected in all three genetic groups (decreased compared with controls), with NPTXR concentrations being affected in C9orf72 and GRN mutation carriers only (decreased compared with controls). No changes were seen in the CSF levels of these proteins in presymptomatic mutation carriers. Concentrations of the neuronal pentraxins were correlated with brain volumes in the presymptomatic period for C9orf72 and GRN groups, suggesting that they become abnormal in proximity to symptom onset. Conclusions : Differential synaptic impairment is seen in the genetic forms of FTD, with abnormalities in multiple measures in those with MAPT mutations, but only changes in neuronal pentraxins within the GRN and C9orf72 mutation groups. Such markers may be useful in future trials as measures of synaptic dysfunction, but further work is needed to understand how these markers change throughout the course of the disease.
The influence of learning on robustness of working memory to distractors
2022-03-08

Abstract Inhibition of irrelevant information is a crucial process within the working memory (WM) system. In the present study, we explored how inhibition of distractors is learned within a Sternberg-like WM task and how this learning process affects readout performance. We introduced distractors of varying strength as well as novel stimuli to a classic Sternberg task. Our findings show that the length of the training period affected obstructiveness of distractors as well as differences between WM loads. Significant differences between conditions observed early on in accuracy became void after general ceiling performance was reached. Moreover, accuracy and reaction times, which are commonly used as readouts of WM performance, were affected differently by training. While both improved significantly, only accuracy exhibited differential dependency of experimental conditions on training. It is essential to consider these dynamics when introducing a WM task which requires a long training period.