Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaborative Ad Transparency: Promises and Limitations

Several targeted advertising platforms offer transparency mechanisms, but researchers and civil societies repeatedly showed that those have major limitations. In this paper, we propose a collaborative ad transparency method to infer, without the cooperation of ad platforms, the targeting parameters used by advertisers to target their ads. Our idea is to ask users to donate data about their attributes and the ads they receive and to use this data to infer the targeting attributes of an ad campaign. We propose a Maximum Likelihood Estimator based on a simplified Bernoulli ad delivery model. We first test our inference method through controlled ad experiments on Facebook. Then, to further investigate the potential and limitations of collaborative ad transparency, we propose a simulation framework that allows varying key parameters. We validate that our framework gives accuracies consistent with real-world observations such that the insights from our simulations are transferable to the real world. We then perform an extensive simulation study for ad campaigns that target a combination of two attributes. Our results show that we can obtain good accuracy whenever at least ten monitored users receive an ad. This usually requires a few thousand monitored users, regardless of population size. Our simulation framework is based on a new method to generate a synthetic population with statistical properties resembling the actual population, which may be of independent interest.
Second‐Order Approach to Local Influence

To examine global and local influence, and their relations for regression models, we study the perturbation-formed surface of a variable, such as the maximum likelihood estimate of a parameter, by evaluating the second derivative or curvature of the surface. (The corresponding slope of this surface is related to the curvature of the likelihood displacement surface of Cook.) Examples show that this approach, with the aid of plots, is helpful not only to discover influential cases including those hidden in an individual global sense but also to understand the nature of influence
New explicit trigonometrically-fitted fourth-order and fifth-order Runge-Kutta-Nyström methods for periodic initial value problems

In this work, we derive two new Runge-Kutta-Nystrom (RKN) methods for solving periodic second order ordinary differential equations. We constructed these methods based on the RKN method of three-stage fourth-order derived by Garcia and RKN method of four-stage fifth-order derived by Hairer. The numerical results show that the efficiency of the new methods is more than the other existing methods.
FDTD Simulation of a Reversed Dipole Using a Combination of Phase Conjugation and Angular Spectrum Domain Method to Achieve Focusing Enhancement in Scattering Media

In recent years, light has been used in medical fields as a diagnostic, characterization, and therapeutic tool. One of the challenges that faces this field is the focusing of light through scattering media. To this purpose, it is important to have a theoretical description of the light propagation through biological tissue. In this work, a reversed dipole is described using the angular spectrum of plane waves method (ASPW) and simulated in the scheme of finite difference time domain method (FDTD) to examine the
Prevalence and risk factors associated with dysglycemia among overweight and obese Palestinian children in the Hebron governorate [version 1; peer review: awaiting peer review]

Background : The prevalence of dysglycemia among adolescents and younger children has been rising, yet health professionals are still unaware of the significance of this problem. According to the Palestinian Ministry of Health (MOH) records, most diabetic children under the age of 20 in Palestine are classified as type I; nonetheless, very limited data are available for policymakers to frame cost-effective screening programs. This study aims to determine the prevalence of dysglycemia in a sample of obese and overweight Palestinian children, identify risk factors associated with dysglycemia, and examine risk factors variance by gender. Methods : A cross-sectional sample of observed obese and overweight children was selected from public schools in the Hebron governorate. Informed consent, physical examination, anthropometric, and laboratory tests (Blood Glucose Level (BGL) and fasting BGL ) were performed on a sample of 511 students (44.6% boys and 55.4% girls) aged 13–18-years (13-15 years =46.2% and 16-18 years =53.8%). Results : The prevalence of confirmed overweight and obese cases was 73.2%, and dysglycemia prevalence among the confirmed cases was 3.7% (
Improving the Scalability and Capabilities of the Nexus Hardware Task Management System

—Recently, several programming models have been proposed that try to relieve parallel programming. One of these programming models is StarSs. In StarSs, the programmer has to identify pieces of code that can be executed as tasks, as well as their inputs and outputs. Thereafter, the runtime system (RTS) determines the dependencies between tasks and schedules ready tasks onto worker cores. Previous work has shown that the StarSs RTS may constitute a bottleneck that limits the scalability of the system and proposed a hardware task management system called Nexus to eliminate this bottleneck. Nexus has several limitations, however. For example, the number of inputs and outputs of each task is limited to a ﬁxed constant and Nexus does not support double buffering. In this paper we present Nexus++ that addresses these as well as other limitations. Experimental results show that double buffering increases the utilization from about 60% to almost 100% and that Nexus++ signiﬁcantly enhances the scalability of applications parallelized using StarSs.
Gendered Patterns in Popular ASMR Roleplay Gendered Patterns in Popular ASMR Roleplay

Autonomous Sensory Meridian Response (ASMR), as a physiological phenomenon and emerging art form has been more and more studied, with some research relating to gender expression and sexuality. There remains a gap for how ASMR is contextualized in its most popular and revealing settings. I conducted an ethnographic content analysis of twenty of the most viewed ASMR roleplay videos on YouTube over the past year. In not limiting my analysis to women’s participation in ASMR and focusing on those videos most popular, I found that while women creators replicated feminine scripts of care catering to an audience made up mostly of straight women, men utilized heterosexual signaling to the same audience.
Energy-Efficient Adaptive 3D Sensing: Supplementary Technical Report

where ke is a method-independent constant. According to ANSI Z136, this analytic expression for MPE we use holds for a wide range of wavelengths from visible light to NIR light (including commonly used 630nm, 800nm, 938nm, and 1064nm), as long as the temporal duration is longer than 18μs. When SWIR laser such as 1550nm is used, eye-safety is not a concern, and our system’s SNR gain still holds. When the temporal duration is shorter than 18μs, which could happen for point scanning (e.g., 10μs for each point for a 10fps 10k-point system), we still use this expansion as an approximation for ease of derivation; it is easy to verify that the conclusion still holds with the exact formula. Rearranging Eq. 1,
Zmienność stochastyczna w wybranych modelach rynków finansowych

Głównym obiektem badań niniejszej pracy doktorskiej są modele rynków nansowych ze zmiennością stochastyczną, czyli modele, w których zmienność ceny akcji jest opisywana pewnym procesem stochastycznym. Modele te są rozwinięciem klasycznego modelu Blacka-Scholesa, w którym przyjmuje się, że zmienność ceny jest stała. Założenie to prowadzi jednak do pewnych sprzeczności z obserwacjami na rynku (na przykład do tak zwanego uśmiechu zmienności). Zmienność stochastyczna jest jednym ze sposobów na pokonanie tej trudności.
Cross-validated mixed-datatype bandwidth selection for nonparametric cumulative distribution/survivor functions

ABSTRACT We propose a computationally efficient data-driven least square cross-validation method to optimally select smoothing parameters for the nonparametric estimation of cumulative distribution/survivor functions. We allow for general multivariate covariates that can be continuous, discrete/ordered categorical or a mix of either. We provide asymptotic analysis, examine finite-sample properties through Monte Carlo simulation, and consider an illustration involving nonparametric copula modeling. We also demonstrate how the approach can also be used to construct a smooth Kolmogorov–Smirnov test that has a slightly better power profile than its nonsmooth counterpart.
ESG-Based Market Risk Prediction and Management Using Machine Learning and Natural Language Processing

The future of finance goes hand in hand with social responsibility, environmental stewardship, and corporate ethics. In order to stay competitive, companies are increasingly disclosing more information about their environmental, social, and governance (ESG) performance. Higher ESG ratings are generally positively correlated with valuation and profitability while negatively correlated with volatility (Campagna et al., 2020). Chasing ESG has led to an increase in ESG data and rating providers, but investors are frustrated by the lack of standardized ESG data. On one hand, ESG rating providers give different metrics and parameters so that issuers are bombarded with “ESG reporting fatigue”. On the other hand, the complexity of multidimensional ESG metrics leads to difficulties in direct comparison between different companies, especially those in different industries. But thankfully, emerging capabilities in Artificial Intelligence and Natural Language Processing (NLP) technology have the potential to provide new perspectives to existing data to help bridge the ESG disclosure gap. In this project, we aim to use NLP techniques to automatically extract and analyze companies’ ESG initiatives and keywords directly from ESG reports as well as third-party news and articles, and to create an internal ESG score that is more accurate, comprehensive, and intuitive. Based on the internal ESG score, we studied the relationship between ESG initiatives and companies’ market risk. The result shows that a better internal ESG internal score is positively correlated with a lower Value at Risk (VaR).
ENTERING EUROPEAN COUNTRIES: ADVANTAGES AND DIFFICULTIES FOR CHINESE ELECTRIC VEHICLE FIRMS

The great support from Chinese governments to upgrade the automotive industry has propelled Chinese automotive firms into developing and producing electric vehicles in recent years. However, despite their emergence in foreign markets, the internationalisation of Chinese EV firms still needs to be studied more. This paper investigates the advantages and disadvantages of Chinese EV firms when they expand into European markets. Our study finally provides solutions to mitigate the disadvantages to develop their businesses in Europe better.
The Accuracy Evaluation Shared Task as a Retrospective Reproduction Study

We investigate the data collected for the Accuracy Evaluation Shared Task as a retrospective reproduction study. The shared task was based upon errors found by human annotation of computer generated summaries of basketball games. Annotation was performed in three separate stages, with texts taken from the same three systems and checked for errors by the same three annotators. We show that the mean count of errors was consistent at the highest level for each experiment, with increased variance when looking at per-system and/or per-error-type breakdowns.
HTTP Video Streaming: the quality - reliability - latency triangle

—Nowadays, IP video trafﬁc is responsible for a vast amount of the global IP trafﬁc over Internet, an increasing trend fueled not only by the usage of personal computers, but also by the rising in prominence of mobile devices and smart-tvs as primary entertainment consumption devices among users. As of 2018, the leading paradigm of delivery is HTTP-based adaptive streaming , a technique which carries pre-encoded video segments over HTTP/TCP packets. While many efforts have been spent towards reaching a satisfying visual experience, one critical point remains mostly untackled by all the prominent HAS protocols: the latency of delivery . With the term latency we indicate the time passed from the instant a video is captured to the moment it gets displayed on the user’s device, a key aspect in the viewing of live events such as sports or happenings. In this white-paper we will evaluate some innovative ap- proaches and technological advancements which can re-balance the triangle between visual quality , network reliability and oc- cupation and delivery latency , by ﬁrst examining the reasons which lead to an increase in latency for HAS protocols, and then investigating some of the most promising proposals in the ﬁeld.
P RONUNCIATION M ODELING FOR C HILDREN ’ S S PEECH

: The accuracy of automatic speech processing systems for children’s speech lags heavily behind the accuracy of systems for adult speech. One of the reasons is a high pronunciation variability in children’s speech. Modeling this variability can be effective to increase performance. We investigate whether MAUS, a system developed for phonemic segmentation and trained on adult speech, which explicitly models deviations from canonical pronunciations, can be applied to children’s speech. We compare it to a recently presented system trained on children’s speech. We evaluate whether the systems can capture pronunciation variability as well as the performance on phonemic segmentation.
Do you trust this speaker? The impact of prompting on middle-school students’ consideration of source when watching con icting videos

Colin Lescarret (  lescarret.colin@gmail.com ) CLLE: Cognition Langues Langages Ergonomie https://orcid.org/0000-0002-9227-8127 Julien Magnier CLLE: Cognition Langues Langages Ergonomie Valérie Le Floch CLLE: Cognition Langues Langages Ergonomie Jean-Christophe Sakdavong CLLE: Cognition Langues Langages Ergonomie Jean-Michel Boucheix University of Burgundy: Universite de Bourgogne Franck Amadieu CLLE: Cognition Langues Langages Ergonomie
Testing the Inhibition of Uropathogenic Escherichia coli by Urinary Lactobacilli

3 Introduction . 4 Materials and Methods . 8 MRS Broth and Plate Preparation . 8 Strains Used and Experimental Groups . 9 Bacterial Isolation and Liquid Culture Preparation . 10 Lactobacilli Spent Media Preparation . 11 Buffer Preparation . 12 Well-Diffusion Inhibition Assay . 12 Plate Imaging and Zone Quantification . 13 Results . 15 Inhibition of Background, CFT073, and SVS144 Strains by Lactobacillus Cultures . 15 Inhibition of Background, CFT073, and SVS144 Strains by Lactobacillus Filtrates . 16 Inhibition of UTI89 Strains by L. gasseri Culture and Filtrate . 17 Inhibition of UTI89 Strains by Citrate Buffer . 20 Discussion . 21 Reference List . 23
Can Upregulation of CXCR3 By Phototherapy Improve Vitiligo? It’s Role in Chronicity

Background: Vitiligo is melanocyte death that is affected by oxidative stress which elevated levels of reactive oxygen species can elicit an immune response, and ultimately cause melanocytic death. Objective: The current study aimed to investigate the impact of Narrowband Ultraviolet B (NBUVB) and excimer laser phototherapy on C-X-C motif chemokine receptor 3B expression in vitiligo patients and its impact on vitiligo improvement. Patients and methods: CXCR3B mRNA expression was measured in skin of 25 patients suffering from non-segmental vitiligo before and after generalized ‘NBUVB’ and targeted phototherapy ‘Excimer laser’. All biopsies were kept in - 80C till RNA extraction that was performed utilizing QIAGEN RNeasy Little Pack, QuantiTect Switch Record Unit and QuantiNova SYBR Green PCR Unit. Results: After phototherapy patients with vitiligo had higher CXCR3B mRNA levels, in addition, this was higher in excimer bunch treatment than NBUVB. Conclusion: Such findings draw attention to CXCR3B as an inherited abnormality in vitiligo patients' skin and raise concerns about its potential contributions in maintaining vitiligo or triggering relapses & chronicity.
The study on increasing the equivalent SNR in the certain DOI by adjusting the SD separation in near-infrared brain imaging application

Near-infrared (NIR) brain imaging is one of the most promising techniques for brain research in recent years. As a significant supplement to the clinical imaging technique, such as CT and MRI, the NIR technique can achieve a fast, non-invasive, and low cost imaging of the brain, which is widely used for the brain functional imaging and hematoma detection. NIR imaging can achieve an imaging depth up to only several centimeters due to the reduced optical attenuation. The structure of the human brain is so particularly complex, from the perspective of optical detection, the measurement light needs go through the skin, skull, cerebrospinal fluid (CSF), grey matter, and white matter, and then reverses the order reflected by the detector. The more photons from the Depth of Interest (DOI) in brain the detector capture, the better detection accuracy and stability can be obtained. In this study, the Equivalent Signal to Noise Ratio (ESNR) was defined as the proportion of the photons from the DOI to the total photons the detector evaluated the best Source and Detector (SD) separation. The Monte-Carlo (MC) simulation was used to establish a multi brain layer model to analyze the distribution of the ESNR along the radial direction for different DOIs and several basic brain optical and structure parameters. A map between the best detection SD separation, in which distance the ESNR was the highest, and the brain parameters was established for choosing the best detection point in the NIR brain imaging application. The results showed that the ESNR was very sensitivity to the SD separation. So choosing the best SD separation based on the ESNR is very significant for NIR brain imaging application. It provides an important reference and new thinking for the brain imaging in the near infrared.
The Slow Reveal: Understanding Shareholder Meetings through Options∗

This paper uses options to examine the importance of shareholder meetings and the timing of information released during the meeting cycle. Our findings imply that market participants continuously learn information about meeting agendas and voting outcomes throughout the meeting cycle. Specifically, option implied volatility peaks around the record date and gradually declines leading up to the meeting date. This decline is significant at 0.9%, varies by proposal topic and contentiousness level, and persists after controlling for voting premiums and borrowing fees. These findings suggest that previous studies may have underestimated the importance of shareholder meetings by only considering event returns. JEL classification: G14, G30, G34
Deep learning for 3D+t datasets in material science: Application to the analysis and quantification of the evolution of the 3D morphology of Li-ion batteries

Over the past ten years, driven by the need to reduce our dependence on fossil fuels, significant efforts have been made to develop high-performance Li-ion batteries for both electric vehicles and storage of renewable, wind and solar energy. However, the use of liquid electrolytes in conventional Li-ion batteries has many disadvantages such as their limited potential stability window, the dissolution effects of transition metals and their flammable nature which leads to high fire risks. These problems can be overcome by replacing the liquid electrolyte with a solid electrolyte [1].
"Transistor-Like" Spin Nano-Switches: Physics and Applications

Diep, Vinh Quang Ph.D., Purdue University, May 2015. “Transistor-Like” Spin Nano-Switches: Physics and Applications. Major Professor: Professor Supriyo Datta. Progress in the last two decades has effectively integrated spintronics and nanomagnetics into a single field, creating a new class of spin-based devices that are now being widely used in magnetic memory devices. However, it is not clear if these advances could also be used to build logic devices. The objective of this thesis is three-fold: The first is to describe a general paradigm for combining Read and Write units used in memory devices into transistor like nano-switches having input-output isolation and gain. Such switches could be used to build logic circuits without the need of any external circuits or amplification. The second is to describe an experimentally benchmarked simulation model for designing a concrete implementation of a transistor-like switch based on: Giant Spin Hall Effect(Write), Magnetic Tunnel Junction (Read) and magnetic coupling for isolation. It turns out that the model can also be used to analyze/design stray fields in perpendicular magnetic tunnel junction (pMTJ), an important problem in scaled pMTJ devices. The third is to discuss the novel features and possible new class of circuits of spin nano-switches. We will first describe a spin switch nano-oscillator based on the standard principle of incorporating feedback into a device with gain. We then discuss how spin nano-switches can be used to implement different types of neural networks such as second generation, third generation and deep belief neural networks.
The Importance of Prostate-Specific Membrane Antigen Expression in Salivary Gland Tumors

Objective: Prostate-specific membrane antigen (PSMA) is a cell membrane protein expressed by prostate tissues. It is not prostate specific and is also expressed by some non-prostatic solid neoplasms. Our study aimed to investigate the potential role of PSMA in salivary gland tumors. Methods: The present study was designed to retrospectively analyze our cases that presented with salivary gland tumors. The files of 105 patients were reviewed and their paraffin embedded blocks were retrieved from the pathology department. Immunohistochemical examination and staining were done using PSMA antibody. Tumor tissue PSMA immunohistochemical staining was scored semi-quantitatively with the modified quartile approach. Negative staining was scored 0, >0% and ≤25% tissue expression was considered weak (score 1), >25% and ≤50% tissue expression was considered mild (score 2), >50% and ≤75% tissue expression was considered moderate (score 3), and >75% tissue expression was considered strong (score 4). Results: Eighty-eight patients (55 males, 33 females) were included in the study. Forty-eight patients had pleomorphic adenoma (PA), 35 had Warthin’s tumor (WT), two had mucoepidermoid carcinoma, two had adenoid cystic carcinoma, and one had squamous cell carcinoma. There was statistically significant difference in terms of PSMA expression between PA and WT (p=0.003). PSMA expression was high in PA and absent in WT. Conclusion: PSMA is a potential source of inspiration for future studies on the development of novel diagnostic and theranostic investigations of salivary gland tumors. Prospective studies targeting intratumoral PSMA in salivary gland tumors should be planned.
On urban road traffic state evaluation index system and method

Traffic state evaluation is a basic and critical work in the research on road traffic congestion. It can provide basic data support for the improvement measures and information release in traffic management and service. The aim of this research is to obtain a comprehensive value to describe traffic state accurately based on the evaluation index system. In this paper, it is carried out using fuzzy c-means (FCM) algorithm and fuzzy entropy weight method. In the framework, traffic flow was classified into six different states to determine the fuzzy range of indices using the improved FCM clustering analysis. Besides, fuzzy entropy weight method is proposed to compute the evaluation result of traffic state for section, road and road network, respectively. The experiments based on the traffic information in a subset of Beijing’s road network prove that the findings of traffic evaluation are in accordance with the actual situation and people’s sense of traffic state.