Miracle-dz/UniFAR-FTUs huggingface dataset:
INFERENCE ON TWO-COMPONENT MIXTURES UNDER TAIL RESTRICTIONS

Many econometric models can be analyzed as finite mixtures. We focus on two-component mixtures, and we show that they are nonparametrically point identified by a combination of an exclusion restriction and tail restrictions. Our identification analysis suggests simple closed-form estimators of the component distributions and mixing proportions, as well as a specification test. We derive their asymptotic properties using results on tail empirical processes and we present a simulation study that documents their finite-sample performance.
Low incidence of cannibalism among brood parasitic cuckoo catfish embryos

Abstract Brood parasites have demanding needs of host resources. Brood parasitic offspring are highly competitive and frequently cause the failure of host broods and the survival of a single parasitic offspring. Accordingly, virulent brood parasites lay a single egg in the same host nest to avoid sibling competition. In the cuckoo catfish (Synodontis multipunctatus), which parasitize mouthbrooding cichlid fishes in Lake Tanganyika, the modes of host and parasite oviposition lead to frequent cases of multiple parasitism. We experimentally tested the prediction that multiple parasitism leads to frequent cannibalism among offspring. Cuckoo catfish embryos prey upon host offspring to obtain nourishment during their 3-week development in the host buccal cavity and may also consume conspecific embryos. The potential benefits of cannibalism in the system are, therefore, twofold; to decrease competition for limited resources (i.e., host brood with rich yolk sacs) and to directly obtain nourishment by consuming rivals. We found that cannibalism indeed provided measurable benefits in terms of increased growth of the cannibals, but cannibalism was rare and typically occurred once all host offspring had been consumed. This implies that cannibalism among cuckoo catfish embryos emerges to mitigate starvation rather than eliminate competition.
The Influence of Selected Factors on the Detection of Giardia intestinalis by Microscopic and Immunoenzymatic Methods

Background: Giardia intestinalis is one of the most common parasites in humans. Contaminated food and water can be a source of infection. Substances added to food are intended to increase its safety. We aimed to determination of the influence of various microorganisms and compounds that stimulate digestive functions, as well as preservatives and antioxidants on the detection of G. intestinalis by microscopic and immunoenzymatic methods. Methods: Twenty stool samples, archived in 1998–2018 in the Provincial Sanitary and Epidemiological Station in Bydgoszcz (Poland), collected both from patients referred for parasitic examinations by a doctor of a medical facility and from private individuals, were used to assess the impact of selected factors (such as bacterial strains, viruses and substances added to food) on the detection of G. intestinalis by microscopic and immunoenzymatic methods. Results: G. intestinalis was detected by both microscopic and immunoenzymatic methods with the same sensitivity (100%). The result of the G. intestinalis determination was positive in 90% of the samples after the addition of potassium sorbate, and in 25% of the samples after the addition of citric acid. Conclusion: The presence of other microorganism such as bacteria and viruses does not influence on the detection of G. intestinalis by microscopic and immunoenzymatic methods in stool samples. Citric acid as an antioxidant added to foods affects the detection of G. intestinalis. Due to the small number of samples used, it is necessary to continue research on the impact of various factors on the detection of protozoa.
DeepMorpher: deep learning-based design space dimensionality reduction for shape optimisation

ABSTRACT In engineering design optimisations, the dimensionality of the design space plays a critical role in determining the number of computationally expensive evaluations required to explore the design space and reach convergence. Dimensionality reduction allows engineers to represent high-dimensional design spaces in a more compact form to reduce the computational cost while retaining design flexibility. In order to reduce the dimensions of design space for shape optimisation problems, we propose a deep learning-based architecture named DeepMorpher. Our proposed architecture is a PointNet-based encoder-decoder network, which can directly be trained on 3D point-cloud geometries, and generate simulation-ready high-quality geometries without any pre-processing or post-processing steps. Our proposed DeepMorpher can work with multiple baseline templates and allows explainability and disentanglement of learned low-dimensional latent space through sampling, interpolation and feature space visualisation. To evaluate our approach, we created an engineering dataset consisting of 3D ship hull designs. The quantitative and qualitative experimentation results of the present study demonstrate that DeepMorpher can outperform previous state-of-the-art autoencoder-based shape-generative models by several orders of magnitudes. To demonstrate the high representation capacity and compactness of learned low-dimensional latent space, we employed DeepMorpher within a simulation-based design optimisation framework to perform a real-world constrained multi-objective optimisation to find optimal ship hull designs. Highlights A deep learning-based autoencoder network for reducing the dimensionality of design space in shape optimisation is proposed. The proposed network learns an explainable and disentangled low-dimensional latent space where each dimension captures different attributes of high-dimensional input shape. The proposed network incorporates free-form deformation within the architecture to generate simulation-ready geometries with high visual quality. The efficacy of the proposed network was demonstrated inside a simulation-based design optimisation framework to perform multi-objective Bayesian optimisation using multiple baseline templates to find optimal designs.
Measurement of t-channel single top quark production in pp collisions

Measurements of t-channel single top quark production in proton-proton collisions at the LHC at center-of-mass energies of 7 and 8 TeV, using data collected with the CMS experiment during the years 2011 and 2012, are presented. The analyses consider final states where the W boson from the top quark decays into electron-neutrino or muon-neutrino, and makes use of kinematic characteristics of electroweak single top production for the separation of signal from backgrounds using multivariate methods. The results are compared with the most precise Standard Model theory predictions. Measurements of top/anti-top cross section ratio and of various differential single top quark production cross sections are also presented. Presented at EPS-HEP 2015 European Physical Society Conference on High Energy Physics 2015 Measurement of t-channel single top quark production in pp collisions Francesco Fabozzi∗ (on behalf of the CMS collaboration) INFN-Napoli & Universita della Basilicata E-mail: Francesco.Fabozzi@cern.ch Measurements of t-channel single top quark production in proton-proton collisions at the LHC at center-of-mass energies of 7 and 8 TeV, using data collected with the CMS experiment during the years 2011 and 2012, are presented. The analyses consider final states where the W boson from the top quark decays into electron-neutrino or muon-neutrino, and makes use of kinematic characteristics of electroweak single top production for the separation of signal from backgrounds using multivariate methods. The results are compared with the most precise Standard Model theory predictions. Measurements of top/anti-top cross section ratio and of various differential single top quark production cross sections are also presented. The European Physical Society Conference on High Energy Physics 22–29 July 2015 Vienna, Austria
The Influence of Media Information Sources on Preventive Behaviors in China: After the Outbreak of COVID-19 Pandemic

Background As announced by the World Health Organization (WHO), since March 2020, the COVID-19 pandemic has become a global pandemic. In order to prevent the spread of COVID-19, Chinese government carried out very strict prevention and control policy. Objective The study aimed to explore the effect of news reports on COVID-19 vaccine from traditional media and social media on COVID-19 preventive behaviors. Methods Adults aged between 18 and 58 years old completed an online survey reporting how they gathered media information sources regarding the COVID-19 vaccine, as well as any details relating to risk perception, vaccine efficacy, and preventive behaviors in COVID-19 pandemic. Results Our results showed that traditional and social media information sources both significantly and positively influenced people's COVID-19 preventive behaviors, with the former showing a stronger effect. COVID-19 contact risk perception and vaccine efficacy awareness of media audiences partly mediate this relationship. Audiences who reported more exposing news reports on COVID-19 vaccine from the media show stronger risk perception and vaccine efficacy awareness. This increases their COVID-19 preventive behaviors. Conclusions This study found that media information sources have an important impact on people's COVID-19 preventive behaviors. People believe more in the news information of the mainstream media about the COVID-19 pandemic. Moreover, much of the news information of social media is also from the important mainstream media. Media organizations should shoulder greater social responsibility, embed the health-related benefits of COVID-19 vaccination into the values and cultural order of the whole society, find and shape a common space of meaning, and produce forms of internal coupling and value identification.
Reconstruction of magnetic clouds from in-situ spacecraft measurements and intercomparison with their solar sources

Abstract Coronal Mass Ejections (CMEs) are eruptive events that originate, propagate away from the Sun, and carry along solar material with embedded solar magnetic field. Some are accompanied by prominence eruptions. A subset of the interplanetary counterparts of CMEs (ICMEs), so-called Magnetic Clouds (MCs) can be characterized by magnetic flux-rope structures. We apply the Grad-Shafranov (GS) reconstruction technique to examine the configuration of MCs and to derive relevant physical quantities, such as magnetic flux content, relative magnetic helicity, and the field-line twist, etc. Both observational analyses of solar source region characteristics including flaring and associated magnetic reconnection process, and the corresponding MC structures were carried out. We summarize the main properties of selected events with and without associated prominence eruptions. In particular, we show the field-line twist distribution and the intercomparison of magnetic flux for these flux-rope structures.
Confidence Intervals for Forecast Verification

The Technical Notes series provides an outlet for a variety of NCAR Manuscripts that contribute in specialized ways to the body of scientific knowledge but that are not suitable for journal, monograph, or book publication. Reports in this series are issued by the NCAR scientific divisions. Designation symbols for the series include: under the sponsorship of the National Science Foundation. Any opinions , findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Flexibility of bacterial type IV pili determined using atomic force microscopy

FLEXIBILITY OF BACTERIAL TYPE IV PILI DETERMINED USING ATOMIC FORCE MICROSCOPY Joshua Mogyoros Advisor: University of Guelph, 2016 Dr. John R. Dutcher Type IV pili (T4P) are very thin protein filaments extended and retracted from the surface of certain Gram-negative bacteria. T4P play a major role in processes such as adhesion, twitching motility and biofilm formation. We improve on previous atomic force microscopy (AFM) measurements of the mechanical properties of T4P of Pseudomonas aeruginosa. A protocol was adapted and developed to perform single cell force spectroscopy (SCFS) by adhering a single bacterium to the end of a colloidal cantilever which is brought into contact with a substrate, allowing the pili to adhere. Force-distance curves are then collected by retracting the cantilever, corresponding to the stretching of the T4P. The persistence length, a parameter that characterizes the flexibility of a polymer, can be determined from the worm-like chain (WLC) model. The value of the persistence length measured by total internal reflection fluorescence (TIRF) microscopy is a factor of 1000 times greater than that measured in AFM experiments. We show that the SCFS protocol is unlikely to be successful without rolling the bacteria beneath the cantilever, which could result in the T4P contacting the adhesive that coats the cantilever. We suggest that the persistence length discrepancy in the literature is due to a force-induced conformational change that occurs when pulling the T4P in the AFM experiments.
Systematic comparison of initial velocities for neutron stars in different models

I have studied the initial velocity (Maxwellian and exponential distributions) and the scale height of isolated old (aged ≥ 109 yr) neutron stars (NSs) at different Galactocentric distances R in three population models. The smooth time-independent 3-D axisymmetric gravitational potentials (Miyamoto-Nagai and Paczyński models) were also used. The correlation between these quantities significantly affects the shapes of the profiles and distributions of the simulated sample, because the differences in the initial kick can arise from differences in the formation and evolution of NSs with other physical parameters. The scale height of the density distribution increases systematically with R. I have also shown that the distribution of old NSs in these population models agrees with the observed structure of the Galaxy in terms of initial velocities (1-D and 3-D), as well as the scale height distributions. These distributions tend to have an asymptotic behavior at the point R = 2.75 kpc. This means that the quality of the models can be described in terms of a mean of the fitted Gaussian, and this could also give an overall perspective of the phase space properties of nearby old NSs on a given gravitational potential.
Portfolio Selection using Cointegration and Modern Portfolio Theory: An Application to the Colombo Stock Exchange

Profitable stock market investments have never been easy due to the lack of predictability and higher risk of stock returns. Hence the necessity of portfolio selection has arisen in order to find the ideal portfolio which best suits the stock market behavior. This study aims at devising the ideal sector portfolio and identifying a better strategy for developing the ideal sector portfolio in the Colombo Stock Exchange (CSE). It covers a period when CSE was one of the best performing stock exchanges in the world; the post civil war period in Sri Lanka. In this study better portfolios were derived from two strategies: (1) Cointegration approach; and (2) Modern Portfolio Theory (including Capital Market Theory) where both are widely used to derive portfolios related to stock market trading. Then the performances of the better portfolios derived were compared by means of the Sharpe Ratio, Information Ratio, Return and Risk in order to determine the ideal portfolio as well as the better strategy. Final conclusion of the study states that “Market portfolio” obtained from the Modern Portfolio Theory performs better than “Best Cointegrated portfolio” obtained from the Cointegration approach in the considered period of time by dominating most of the comparison measures. Also the ideal portfolio consisted of eight sectors out of twenty sectors in CSE with varying weight percentages. Further the best portfolio selection method between the two strategies could have been obtained regardless the period if the methodology is implemented for several Stock Exchanges. However, limitations in accessing necessary data prevented this implementation in the study. Keywords: Sharpe Ratio; Information Ratio; Cointegration; Modern Portfolio Theory; Capital Market Theory; Colombo Stock Exchange. 2010 Mathematics Subject Classification: 62P20
Research on Low Illumination Image Enhancement Algorithm and Its Application in Driver Monitoring System

The driver monitoring system (DMS) plays an essential role in reducing traffic accidents caused by human errors due to driver distraction and fatigue. The vision-based DMS has been the most widely used because of its advantages of non-contact and high recognition accuracy. However, the traditional RGB camera-based DMS has poor recognition accuracy under complex lighting conditions, while the IR-based DMS has a high cost. In order to improve the recognition accuracy of conventional RGB camera-based DMS under complicated illumination conditions, this paper proposes a lightweight low-illumination image enhancement network inspired by the Retinex theory. The lightweight aspect of the network structure is realized by introducing a pixel-wise adjustment function. In addition, the optimization bottleneck problem is solved by introducing the shortcut mechanism. Model performance comparison test results demonstrate that the Structure Similarity Index Measure index of the proposed model is 7.04% and 31.03% higher than that of Multi-Scale Retinex with Color Restoration and Contrast Limiting Adaptive Histogram Equalization, respectively. In the use case, the proposed model is capable to process videos with a resolution of 400×600 at a speed of 20fps on average, which meets the requirements of DMS video stream processing speed. Furthermore, a MobileNet based distraction state recognition network pre-trained on the SFD3 dataset is adopted as the back-end to verify its application in the DMS system. The results show that the accuracy in the driver's distracted behavior recognition with a low-light environment is improved by 75.39% compared to before use.
Mixture of Normalizing Flows for European Option Pricing

We present a mixture of normalizing ﬂows (MoNF) approach to European option pricing with guarantees that its estimations are free from static arbit-rage. In contrast to many existing methods that meet economic rationality constraints (e.g., non-arbitrage) by introducing auxiliary losses, our solu-tion meets those constraints exactly by design. To achieve this, we propose to build a model for risk neutral density using normalizing ﬂows, which results in a pricing model, instead of modelling the option pricing function directly. First, we convert the constraints for direct pricing models to the constraints for models backed by risk neutral density estimation, then we design a speciﬁc NF architecture that meets these constraints. Furthermore, we ﬁnd that employing a mixture of such normalizing ﬂows improves the performance signiﬁcantly, compared to using a deeper single NF. Finally, we present a mechanism to regular-ise the proposed model, and this regularisation can serve as a bridge between our method and any sample-based mathematical ﬁnance method. The evaluations on ﬁve option datasets show superiority of our method compared to mathematical ﬁnance solutions and some other neural networks based methods. The code is available at https://github.com/qmfin/MoNF .
Single sand-dust image restoration using information loss constraint

Abstract Outdoor images captured during sand–dust weather condition typically yield poor contrast and colour shift. A novel method for single sand–dust images restoration is introduced in this paper, which relies on the atmospheric scattering model and information loss constraint. To compensate the colour shift and achieve proper luminance, the proposed atmospheric light is changing with the content of the local scenes, which is initially estimated on the basis of the general scattering model and the grey-world assumption. Then, the initial atmospheric light is updated and the coarse transmission is estimated under the information loss constraint. Next, the fast guide filter is exploited in the post-refinement process to inhibit the halo artefacts. Comparison experiments demonstrate that the proposed algorithm is straightforward and efficient, the contrast and colour shift of different kinds of sand-dust images can be well compensated, especially, nice colour fidelity and proper luminance can be maintained.
Global Riverine Export of Dissolved Lignin Constrained by Hydrology, Geomorphology, and Land‐Cover

The land‐to‐ocean export of terrestrial dissolved organic matter (tDOM) links the two largest organic carbon (OC) pools on Earth and is changing due to anthropogenic activity and climate change. Lignin phenols are often utilized as diagnostic markers for tDOM in aquatic systems, but information on the global dissolved lignin flux is still uncertain as linkages between future changes in export and global changes are poorly constrained. Thirty‐two new measurements from 15 Chinese rivers and 548 measurements collected from 97 global rivers were combined to analyze its distributions, fluxes, and potential controls. Dissolved lignin concentrations (in μg L−1) varied by more than two orders of magnitude (0.7–138 μg L−1) and were positively correlated with dissolved OC (DOC) concentrations globally, suggesting coupled export of dissolved lignin and DOC. The carbon‐normalized lignin yields (in mg g OC−1) varied by an order of magnitude (<1–30 mg (g OC)−1) and was significantly lower in the Arctic than in temperate and tropical rivers. Correlation analyses indicated that the dissolved lignin flux (FLignin) was mainly affected by water discharge and mean basin slope, while the area‐normalized yield of dissolved lignin as well as discharge‐weighted lignin concentration strongly and positively correlated with forest coverage. We, for the first time, estimated global FLignin ranges from 0.58 to 1.2 Tg yr−1 by using different approaches. Our synthesis reveals that future changes in land‐cover that is driven by climate change as well as other human activities would impose a significant influence on the land‐to‐ocean export of tDOM.