Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing Alternative Monetization Strategies on YouTube

One of the key emerging roles of the YouTube platform is providing creators the ability to generate revenue from their content and interactions. Alongside tools provided directly by the platform, such as revenue-sharing from advertising, creators co-opt the platform to use a variety of off-platform monetization opportunities. In this work, we focus on studying and characterizing these alternative monetization strategies. Leveraging a large longitudinal YouTube dataset of popular creators, we develop a taxonomy of alternative monetization strategies and a simple methodology to detect their usage automatically. We then proceed to characterize the adoption of these strategies. First, we find that the use of external monetization is expansive and increasingly prevalent, used in 18% of all videos, with 61% of channels using one such strategy at least once. Second, we show that the adoption of these strategies varies substantially among channels of different kinds and popularity, and that channels that establish these alternative revenue streams often become more productive on the platform. Lastly, we investigate how potentially problematic channels -- those that produce Alt-lite, Alt-right, and Manosphere content -- leverage alternative monetization strategies, finding that they employ a more diverse set of such strategies significantly more often than a carefully chosen comparison set of channels. This finding complicates YouTube's role as a gatekeeper, since the practice of excluding policy-violating content from its native on-platform monetization may not be effective. Overall, this work provides an important step toward broadening the understanding of the monetary incentives behind content creation on YouTube.
Location-Free Camouflage Generation Network

Camouflage is a common visual phenomenon, which refers to hiding the foreground objects into the background images, making them briefly invisible to the human eye. Previous work has typically been implemented by an iterative optimization process. However, these methods struggle in 1) efficiently generating camouflage images using foreground and background with flexible structure; 2) camouflaging foreground objects to regions with multiple appearances (e.g. the junction of the vegetation and the mountains), which limit their practical application. To address these problems, this paper proposes a novel Location-free Camouflage Generation Network (LCG-Net) that fuse high-level features of foreground and background image, and generate result by one inference. Specifically, a Position-aligned Structure Fusion (PSF) module is devised to guide structure feature fusion based on the point-to-point structure similarity of foreground and background, and introduce local appearance features point-by-point. To retain the necessary identifiable features, a new immerse loss is adopted under our pipeline, while a background patch appearance loss is utilized to ensure that the hidden objects look continuous and natural at regions with multiple appearances. Experiments show that our method has results as satisfactory as state-of-the-art in the single-appearance regions and are less likely to be completely invisible, but far exceed the quality of the state-of-the-art in the multi-appearance regions. Moreover, our method is hundreds of times faster than previous methods. Benefitting from the unique advantages of our method, we provide some downstream applications for camouflage generation, which show its potential. The related code and dataset will be released at https://github.com/Tale17/LCG-Net.
Probing the parameters of the intergalactic medium using quasars

We continue our series of papers on intergalactic medium (IGM) tracers using quasi-stellar objects (QSOs), having examined gamma-ray bursts (GRBs) and blazars in earlier studies. We have estimated the IGM properties of hydrogen column density (Nhxigm), temperature and metallicity using XMM-Newton QSO spectra over a large redshift range, with a collisional ionisation equilibrium (CIE) model for the ionised plasma. The Nhxigm parameter results were robust with respect to intrinsic power laws, spectral counts, reflection hump and soft excess features. There is scope for a luminosity bias given both luminosity and Nhxigm scale with redshift, but we find this unlikely given the consistent IGM parameter results across the other tracer types reviewed. The impact of intervening high column density absorbers was found to be minimal. The Nhxigm from the QSO sample scales as (1 + z)1.5±0.2. The mean hydrogen density at z = 0 is n0 = (2.8 ± 0.3) × 10−7 cm−3, the mean IGM temperature over the full redshift range is log(T/K) = 6.5±0.1, and the mean metallicity is [X/H] = −1.3±0.1(Z ∼ 0.05). Aggregating with our previous GRB and blazar tracers, we conclude that we have provided evidence of the IGM contributing substantially and consistently to the total X-ray absorption seen in the spectra. These results are based on the necessarily simplistic slab model used for the IGM, due to the inability of current X-ray data to constrain the IGM redshift distribution.
A Model and Survey of Distributed Data-Intensive Systems

Data is a precious resource in today’s society, and it is generated at an unprecedented and constantly growing pace. The need to store, analyze, and make data promptly available to a multitude of users introduces formidable challenges in modern software platforms. These challenges radically impacted the research fields that gravitate around data management and processing, with the introduction of distributed data-intensive systems that offer innovative programming models and implementation strategies to handle data characteristics such as its volume, the rate at which it is produced, its heterogeneity, and its distribution. Each data-intensive system brings its specific choices in terms of data model, usage assumptions, synchronization, processing strategy, deployment, guarantees in terms of consistency, fault tolerance, and ordering. Yet, the problems data-intensive systems face and the solutions they propose are frequently overlapping. This article proposes a unifying model that dissects the core functionalities of data-intensive systems, and discusses alternative design and implementation strategies, pointing out their assumptions and implications. The model offers a common ground to understand and compare highly heterogeneous solutions, with the potential of fostering cross-fertilization across research communities. We apply our model by classifying tens of systems: an exercise that brings to interesting observations on the current trends in the domain of data-intensive systems and suggests open research directions.
A Standardized Pipeline for Colon Nuclei Identification and Counting Challenge

Nuclear segmentation and classification is an essential step for computational pathology. TIA lab from Warwick University organized a nuclear segmentation and classification challenge (CoNIC) for H&E stained histopathology images in colorectal cancer with two highly correlated tasks, nuclei segmentation and classification task and cellular composition task. There are a few obstacles we have to address in this challenge, 1) limited training samples, 2) color variation, 3) imbalanced annotations, 4) similar morphological appearance among classes. To deal with these challenges, we proposed a standardized pipeline for nuclear segmentation and classification by integrating several pluggable components. First, we built a GAN-based model to automatically generate pseudo images for data augmentation. Then we trained a self-supervised stain normalization model to solve the color variation problem. Next we constructed a baseline model HoVer-Net with cost-sensitive loss to encourage the model pay more attention on the minority classes. According to the results of the leaderboard, our proposed pipeline achieves 0.40665 mPQ+ (Rank 49th) and 0.62199 r2 (Rank 10th) in the preliminary test phase.
Benchmarking Emergency Department Triage Prediction Models with Machine Learning and Large Public Electronic Health Records

The demand for emergency department (ED) services is increasing across the globe, particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have become increasingly challenging due to the shortage of medical resources and the strain on hospital infrastructure caused by the pandemic. As a result of the widespread use of electronic health records (EHRs), we now have access to a vast amount of clinical data, which allows us to develop predictive models and decision support systems to address these challenges. To date, however, there are no widely accepted benchmark ED triage prediction models based on large-scale public EHR data. An open-source benchmarking platform would streamline research workflows by eliminating cumbersome data preprocessing, and facilitate comparisons among different studies and methodologies. In this paper, based on the Medical Information Mart for Intensive Care IV Emergency Department (MIMIC-IV-ED) database, we developed a publicly available benchmark suite for ED triage predictive models and created a benchmark dataset that contains over 400,000 ED visits from 2011 to 2019. We introduced three ED-based outcomes (hospitalization, critical outcomes, and 72-hour ED reattendance) and implemented a variety of popular methodologies, ranging from machine learning methods to clinical scoring systems. We evaluated and compared the performance of these methods against benchmark tasks. Our codes are open-source, allowing anyone with MIMIC-IV-ED data access to perform the same steps in data processing, benchmark model building, and experiments. This study provides future researchers with insights, suggestions, and protocols for managing raw data and developing risk triaging tools for emergency care.
IJSRD-International Journal for Scientific Research & Development| Vol. 6, Issue 05, 2018 | ISSN (online): 2321-0613

Cement-based concrete is a widely used material for a great variety of constructions. Although, cement has great properties and high performance, its intrinsic brittleness is a weakness that requires further investigation for improvement. Graphene demonstrates a number of excellent properties, such as high flexibility, 1TPaYoung’sModulus, 130 GPa tensile strength, high electrical and thermal conductivity. This study investigated the feasibility of implementing graphene into the concrete matrix for improving its compressive and tensile or flexural strength. The aim of this research is to study the performance of Graphene cement concrete, and also to compare the compressive and split tensile of M25 concrete by replacing cement with 1% and 2% and 3% graphene oxide. To study compressive strength, cubes of 150mm x 150mm x 150mm size and for split tensile strength cylinders of 150mm diameter x 300mm length were casted. These specimens were tested at 28days, 56days and 90days of curing. The specimen were tested for its compressive and split tensile strength and found that the use graphene in concrete is a good advantage than Normal Concrete.
Wilbur R. Knorr on Thābit ibn Qurra: A Case-Study in the Historiography of Premodern Science

There was a widespread belief among historians of science of my generation that high competence with regard to content and languages alone can guarantee better, more reliable results than can good philology combined with high competence in history or the other human sciences. In my casestudy of Wilbur R.Knorr’s analysis of several medieval Arabic and Latin texts on the balance, or steelyard, I highlight a variety of factors that compromised time and again his understanding and interpretation of his chosen texts. I conclude that a greater openness to more complex historiographical assumptions and more sophisticated methodological approaches as well as a greater willingness to contextualize documents in numerous dimensions before coming to conclusions about their specific meaning is crucial if we are to correct and improve upon work such as Knorr’s analysis of the Kitab al-qarastun, ascribed to Thābit ibn Qurra, and the Liber de canonio. The way forward is to enhance and temper philological analysis with solid analysis of scientific content within its relevant contexts.
Health behaviours prior to pregnancy and fertility outcomes: Triangulation of evidence in the Norwegian Mother, Father and Child Cohort Study (MoBa)

Introduction: Current advice to improve fertility includes reducing alcohol and caffeine consumption, achieving healthy weight-range, and stopping smoking. Advice is informed by observational evidence, which is often biased by confounding. Methods: This study uses data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Medical Birth Registry of Norway. First, we analysed associations between health behaviours prior to pregnancy (alcohol and caffeine consumption, body-mass index (BMI) and smoking) and multiple indicators of fertility (including number of children, time to conception, and miscarriage) (n=83,128 women, 67,555 men), adjusting for birthyear, education and attention deficit and hyperactive-impulsive (ADHD) traits. Second, we used individual-level Mendelian randomisation (MR) to explore possible causal effects of health behaviours on fertility outcomes (n=27,216 women, 26,131 men). Finally, we performed summary-level MR for available outcomes (n=91,462-1,232,091) and conducted multi-variable MR to control for education and ADHD liability. Results: In observational analysis, higher BMI and smoking (and to a lesser extent caffeine) were predominantly associated with reduced fertility outcomes. Unexpectedly, higher alcohol consumption was associated with predominantly improved fertility outcomes. There was little evidence from individual-level MR analyses, except smoking and higher BMI were associated with younger age at first birth in women (mean difference in years, per SD increase in genetic score; smoking: -2.65 (95%CI: -3.57, -1.73); BMI: -0.11 (95%CI: -0.16, -0.08)) and men (smoking: -2.82 (95%CI: -4.07, -1.58); BMI: -0.17 (95%CI: -0.23, -0.11)). These results were replicated in the summary-level MR analysis, however effects attenuated after adjusting for education and ADHD liability. Conclusions: Most observational evidence for associations between health behaviours and fertility was not supported by MR analyses, suggesting possible residual confounding. Evidence from MR analyses supported an effect of smoking and higher BMI on younger age of first birth, but multivariable MR suggested this might be explained by underlying liability to ADHD and low educational attainment.
Long-term symptoms after SARS-CoV-2 infection in a cohort of hospital employees: duration and predictive factors

Purpose To evaluate the frequency, duration and patterns of long-term coronavirus disease 2019 (COVID-19) symptoms and to analyse risk factors for long-lasting COVID-19 sequelae among a cohort of hospital employees (HEs). Methods We conducted a survey regarding persistent COVID-19 related symptoms with all HEs from three medical centres in Cologne, Germany, who were tested SARS-CoV-2 PCR positive from March 2020 until May 2021. Duration of symptoms and possible risk factors for protracted COVID-19 course were analysed. Results Of 221 included HEs, a number of 104 HEs (47.1%) reported at least one persisting symptom for more than 90 days after initial SARS-CoV-2 detection. Each one cycle higher initial Ct value significantly increased the chances of overcoming symptoms (odds ratio [OR] 1.05; 95% confidence interval (95%CI) 1.01–1.09; p = 0.019). The occurrence of breathlessness within the first ten days (OR 7.89; 95%CI 1.87–41.43; p = 0.008), an initial Ct value under 30 (OR 3.36; 95%CI 1.22–9.94; p = 0.022) as well as the occurrence of anosmia or ageusia within the first ten days (OR 3.01; 95%CI 1.10–8.84; p = 0.037) showed a statistically significant association with increased odds of illness duration over 90 days. Conclusion About half of the HEs suffered from long lasting symptoms over 90 days after almost entirely mild acute COVID-19. Predictive factors could possibly be used for early treatment to prevent development of long-term symptoms after COVID-19 in future.
Altered brain responses to noxious dentoalveolar stimuli in high-impact temporomandibular disorder pain patients

High-impact temporomandibular disorder (TMD) pain may involve brain mechanisms related to central sensitization. We investigated brain responses to stimulation of trigeminal sites not typically associated with TMD pain by applying noxious dentoalveolar pressure to high- and low-impact TMD pain cases and pain-free controls during functional magnetic resonance imaging (fMRI). Fifty female participants were recruited and assigned to one of three groups based on the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) and Graded Chronic Pain Scale: controls (n=17), low-impact (n=17) and high-impact TMD (n=16). Multimodal whole-brain MRI was acquired following the Human Connectome Project protocol, including stimulus-evoked fMRI scans during which painful dentoalveolar pressure was applied to the buccal gingiva of participants. Group analyses were performed using non-parametric permutation tests for parcellated cortical and subcortical neuroimaging data. There were no significant between-group differences for brain activations/deactivations evoked by the noxious dentoalveolar pressure. For individual group mean activations/deactivations, a gradient in the number of parcels surviving thresholding was found according to the TMD pain grade, with the highest number seen in the high-impact group. Among the brain regions activated in chronic TMD pain groups were those previously implicated in sensory-discriminative and motivational-affective pain processing. These results suggest that dentoalveolar pressure pain evokes abnormal brain responses to sensory processing of noxious stimuli in high-impact TMD pain participants, which supports the presence of maladaptive brain plasticity in chronic TMD pain.
Exploring patient experiences and concerns in the online Cochlear Implant community: a natural language processing approach

Importance: There is a paucity of research examining patient experiences of cochlear implants, with existing studies limited by small sample sizes and closed question-answer style formats. Objective: To use natural language processing methods to explore patient experiences and concerns in the online cochlear implant (CI) community when in conversation with each other. Design: Cross-sectional study of the online Reddit r/CochlearImplants forum. No date restrictions were imposed; data were retrieved on 11 November 2021 and analysed between November 2021 and March 2022. The following details were extracted for each post: 1) original post content, 2) post comments, and 3) metadata for the original post and user. Setting: Online Reddit forum r/CochlearImplants. Participants: Consecutive sample of all users posting on the r/CochlearImplants forum from 1 March 2015 to 11 November 2021. Main Outcomes and Measures: Natural language processing using the BERTopic automated topic modelling technique was employed to cluster posts into semantically similar topics. Topic categorisation was manually validated by two independent reviewers and Cohen's Kappa calculated to determine inter-rater reliability between machine vs human and human vs human categorisation. Results: We retrieved 987 posts from 588 unique Reddit users on the r/CochlearImplants forum. Posts were initially categorised by BERTopic into 16 different Topics, which were increased to 22 Topics following manual inspection. The most popular topics related to CI connectivity (n = 112),adults considering getting a CI (n=107), surgery-related posts (n = 89) and day-to-day living with a CI (n = 85). Topics with the most comments included Choosing cochlear implant brand (mean = 12.9 comments) and Adults considering getting a CI (mean = 12.2 comments). Cohen's kappa among all posts was 0.62 (machine vs human) and 0.72 (human vs human), and among categorised posts was 0.85 (machine vs human) and 0.84 (human vs human). Conclusions and Relevance: This cross-sectional study of social media discussions amongst the online cochlear implant community identified common attitudes, experiences and concerns of patients living with, or seeking, a cochlear implant. Our validation of natural language processing methods to categorise topics shows that automated analysis of similar Otolaryngology-related content is a viable and accurate alternative to manual qualitative approaches.
Supplemental Information: Spectral Phase Transitions in Optical Parametric Oscillators

Table 1: Parameters for the PPLN waveguide DROPO and pump pulse. Symbol Meaning Value Unit λ Signal Wavelength 1550 nm λ Pump Wavelength 775 nm L Waveguide Length 40 mm α, α Waveguide Loss 0.00691 mm−1 u Walk off/ GVM 0.329 ps/mm Tp Pump Pulse Width 12 ps β (a) 2 Signal GVD 1.12 x 10 −4 ps/mm β (a) 3 Signal TOD 3.09 x 10 −7 ps/mm β (b) 2 Pump GVD 4.06 x 10 −4 ps/mm β (b) 3 Pump TOD 2.51 x 10 −7 psmm 1 Effective nonlinearity 5.16 x 10−5 ps 1 2 /mm G0 2 Power gain at threshold 7.9 b0 3 CW threshold amplitude 5.29 X 10 ps− 1 2
ASSESSMENT OF REDUNDANCY IN THE SEISMIC DESIGN OF MOMENT RESISTING REINFORCED CONCRETE FRAMES

The results of a parametric study devoted to assess the impact of increasing the structural redundancy in ductile reinforced concrete (RC) moment framed buildings are presented. Among the studied variables were the number of stories and the number of bays. Studied models were 4, 8, 12 and 16-story frames with a story height h=3.5 m (11.5 ft). Nonlinear static analyses were used to evaluate numerically redundancy factors. Based on the results of this research and previous studies reported in the literature, it can be concluded that it is justified to account directly structural redundancy in the design by using a redundancy factor, as proposed and done in some international building codes.
An Experimental Study on Hydrodynamic Performance of Flexible Composite Model Propellers

Marine propellers operating in the wake generate the unsteady propeller fluid forces and cause a hull vibration. The deformations of general metal marine propellers are not considered, because they have enough rigidity. However, marine propeller using the composite material called flexible propeller appeared, by controlling the actively blade deformation in response to load changes in one propeller rotation, the possibility of flexible propeller with excellent hydrodynamic performance than enough rigid propeller came into sight. In this study, two kinds of model propellers are used, which are a metal propeller and an elastically deformable propeller that uses a resin with a smaller flexural modulus than metal. Propeller open water tests, fluctuating pressure measurements and blade deformation measurements were conducted in uniform flow and a wake in cavitation tunnel. As a result, it was found that the flexible composite propeller with high skew had a high risk to lower the thrust, torque and efficiency than the metal propeller by the blade tip deformation, but it had a possibility greatly improved cavitation performance. Further, at the time of the propeller reverse it was found that there was a risk of unstable vibration occurs in blade tip part.