Miracle-dz/UniFAR-FTUs huggingface dataset:
Auditory-Tactile Music Perception

The coupled perception of sound and vibration is a known phenomenon during live pop or organ concerts. However, even during a symphonic concert in a classical hall, sound can excite perceivable vibrations at the body surface. The concert visitor might not be aware of those vibrations, because the tactile percept is integrated with the other senses into one multi-modal percept. This article discusses the influence of whole-body vibrations on the listener experience during the reproduction of concerts recordings. Four sequences were selected from classical and modern music, which include low frequency content (e.g., organ, kettledrum, contrabass). A stimulus length of 1.5 minutes was chosen in order to provide enough time for habituation. The audio signal was reproduced using a surround setup. Additional seat vibrations have been generated from the audio signal. Test participants were asked to rate the overall quality of the concert experience. The results show that vibrations have a significant influence o.
Using SPOT-VGT NDVI as a successive ecological indicator for understanding the environmental implications in the Tarim River Basin, China

The resilience and vulnerability of terrestrial ecosystem in the Tarim River Basin, Xinjiang is critical in sustainable development of the northwest region in China. To learn more about causes of the ecosystem evolution in this wide region, vegetation dynamics can be a surrogate indicator of environmental responses and human perturbations. This paper aims to use the inter-annual and intra-annual coefficient of variation (CoV) derived by the SPOT-VGT Normalized Difference Vegetation Index (NDVI) as an integrated measure of vegetation dynamics to address the environmental implications in response to climate change. To finally pin down the vegetation dynamics, the intra-annual CoV based on monthly NDVI values and the inter-annual CoV based on seasonally accumulated NDVI values were respectively calculated. Such vegetation dynamics can then be associated with precipitation patterns extracted from the Tropical Rainfall Measuring Mission (TRMM) data and irrigation efforts reflecting the cross-linkages between human society and natural systems. Such a remote sensing analysis enables us to explore the complex vegetation dynamics in terms of distribution and evolution of the collective features of heterogeneity over local soil characteristics, climate change impacts, and anthropogenic activities at differing space and time scales. Findings clearly indicate that the vegetation changes had an obvious trend in some high mountainous areas as a result of climate change whereas the vegetation changes in fluvial plains reflected the increasing evidence of human perturbations due to anthropogenic activities. Some possible environmental implications were finally elaborated from those cross-linkages between economic development and resources depletion in the context of sustainable development.
Enabling Early Health Care Intervention by Detecting Depression in Users of Web-Based Forums using Language Models: Longitudinal Analysis and Evaluation

Background Major depressive disorder is a common mental disorder affecting 5% of adults worldwide. Early contact with health care services is critical for achieving accurate diagnosis and improving patient outcomes. Key symptoms of major depressive disorder (depression hereafter) such as cognitive distortions are observed in verbal communication, which can also manifest in the structure of written language. Thus, the automatic analysis of text outputs may provide opportunities for early intervention in settings where written communication is rich and regular, such as social media and web-based forums. Objective The objective of this study was 2-fold. We sought to gauge the effectiveness of different machine learning approaches to identify users of the mass web-based forum Reddit, who eventually disclose a diagnosis of depression. We then aimed to determine whether the time between a forum post and a depression diagnosis date was a relevant factor in performing this detection. Methods A total of 2 Reddit data sets containing posts belonging to users with and without a history of depression diagnosis were obtained. The intersection of these data sets provided users with an estimated date of depression diagnosis. This derived data set was used as an input for several machine learning classifiers, including transformer-based language models (LMs). Results Bidirectional Encoder Representations from Transformers (BERT) and MentalBERT transformer-based LMs proved the most effective in distinguishing forum users with a known depression diagnosis from those without. They each obtained a mean F1-score of 0.64 across the experimental setups used for binary classification. The results also suggested that the final 12 to 16 weeks (about 3-4 months) of posts before a depressed user’s estimated diagnosis date are the most indicative of their illness, with data before that period not helping the models detect more accurately. Furthermore, in the 4- to 8-week period before the user’s estimated diagnosis date, their posts exhibited more negative sentiment than any other 4-week period in their post history. Conclusions Transformer-based LMs may be used on data from web-based social media forums to identify users at risk for psychiatric conditions such as depression. Language features picked up by these classifiers might predate depression onset by weeks to months, enabling proactive mental health care interventions to support those at risk for this condition.
New technology based on clamping for high gradient radio frequency photogun

High gradient rf photoguns have been a key development to enable several applications of high quality electron beams. They allow the generation of beams with very high peak current and low transverse emittance, satisfying the tight demands for free-electron lasers, energy recovery linacs, Compton/Thomson sources and high-energy linear colliders. In the present paper we present the design of a new rf photogun recently developed in the framework of the SPARC_LAB photoinjector activities at the laboratories of the National Institute of Nuclear Physics in Frascati (LNF-INFN, Italy). This design implements several new features from the electromagnetic point of view and, more important, a novel technology for its realization that does not involve any brazing process. From the electromagnetic point of view the gun presents high mode separation, low peak surface electric field at the iris and minimized pulsed heating on the coupler. For the realization, we have implemented a novel fabrication design that, avoiding brazing, strongly reduces the cost, the realization time and the risk of failure. Details on the electromagnetic design, low power rf measurements and high power radiofrequency and beam tests performed at the University of California in Los Angeles (UCLA) are discussed in the paper.
New insights into binocular rivalry from the reconstruction of evolving percepts using model network dynamics

When the two eyes are presented with highly distinct stimuli, the resulting visual percept generally switches every few seconds between the two monocular images in an irregular fashion, giving rise to a phenomenon known as binocular rivalry. While a host of theoretical studies have explored potential mechanisms for binocular rivalry in the context of evoked model dynamics in response to simple stimuli, here we investigate binocular rivalry directly through complex stimulus reconstructions based on the activity of a two-layer neuronal network model with competing downstream pools driven by disparate monocular stimuli composed of image pixels. To estimate the dynamic percept, we derive a linear input-output mapping rooted in the non-linear network dynamics and iteratively apply compressive sensing techniques for signal recovery. Utilizing a dominance metric, we are able to identify when percept alternations occur and use data collected during each dominance period to generate a sequence of percept reconstructions. We show that despite the approximate nature of the input-output mapping and the significant reduction in neurons downstream relative to stimulus pixels, the dominant monocular image is well-encoded in the network dynamics and improvements are garnered when realistic spatial receptive field structure is incorporated into the feedforward connectivity. Our model demonstrates gamma-distributed dominance durations and well obeys Levelt's four laws for how dominance durations change with stimulus strength, agreeing with key recurring experimental observations often used to benchmark rivalry models. In light of evidence that individuals with autism exhibit relatively slow percept switching in binocular rivalry, we corroborate the ubiquitous hypothesis that autism manifests from reduced inhibition in the brain by systematically probing our model alternation rate across choices of inhibition strength. We exhibit sufficient conditions for producing binocular rivalry in the context of natural scene stimuli, opening a clearer window into the dynamic brain computations that vary with the generated percept and a potential path toward further understanding neurological disorders.
Information Conveyed by Neuron Populations: Firing Rate, Fluctuation and Synchrony

Recent neuronal experiments have shown that a population of firing neurons may carry not only mean firing rate but also fluctuation and synchrony. In order to theoretically examine this possibility, we have investigated responses of neuronal ensembles to three kinds of inputs: mean-, fluctuation- and synchrony-driven inputs. Equations of motion for mean firing rate, fluctuation and synchrony in neuron ensembles described by the rate-code model, are derived with the use of the augmented moment method which was previously proposed for a study of stochastic ensembles with finite populations. Results calculated by the augmented moment method are in good agreement with those by direct simulations. It has been shown by the independent component analysis of our results that information on mean firing rate, fluctuation and synchrony may be independently conveyed in neuron populations. The calculated input-output relation of mean firing rates is shown to have higher sensitivity for larger multiplicative noise, as recently observed in prefrontal cortex.
Relationship Between Educational Level and Attitudes Towards Alcohol Conversations in Healthcare: A Cross-Sectional Survey Conducted in Four European Countries

Objectives: To examine the association between educational level and attitudes towards alcohol conversations in healthcare using population-based surveys of adults in England, the Netherlands, Norway, and Sweden; and to compare attitudes towards alcohol conversations in healthcare between these four countries. Methods: Cross-sectional surveys were conducted amongst adults in the general population in England (n = 3,499), the Netherlands (n = 2,173), Norway (n = 1,208), and Sweden (n = 3,000). Logistic regression analysis was used to examine associations between attitudes towards alcohol conversations in healthcare and educational level, key demographic variables, alcohol consumption, and country of residence. Results: In all four countries, low educational level (p < 0.001) and male gender (p < 0.001) were associated with holding negative attitudes towards discussing alcohol in healthcare. Risky drinkers had more negative attitudes than low risky drinkers towards discussing alcohol in healthcare (p < 0.001) in all countries except England (p = 0.48), and also reported low levels of perceived honesty and confidence in healthcare (p < 0.001). Conclusion: These findings highlight the importance of considering patients’ socio-economic status when developing and implementing alcohol prevention interventions in healthcare.
Permanence and Global Attractivity of the Discrete Predator-Prey System with Hassell-Varley-Holling III Type Functional Response

By constructing a suitable Lyapunov function and using the comparison theorem of difference equation, sufficient conditions which ensure the permanence and global attractivity of the discrete predator-prey system with Hassell-Varley-Holling III type functional response are obtained. An example together with its numerical simulation shows that the main results are verifiable.
Decay of solutions of a Boussinesq-type system with variable coefficients

We introduce a modified Chebyshev rational approximation applied to a weakly nonlinear, weakly dispersive Boussinesq formulation considered on the whole line, which is a model for waves propagating on the surface of a channel with variable bottom. We also establish rigorous convergence and error estimates in L 2 of the semidiscrete and fully discrete numerical schemes and validate the numerical results using the theory derived in a previous paper on the decay of a linear pulse propagating along the surface of a channel with a random bottom.
Effects of implementation support on children's reading outcomes following an online early reading programme: A cluster-randomised controlled trial

Well-designed computer or app-based instruction has a number of potential benefits (eg increasing accessibility and feasibility of high-quality instruction, reducing time and resources required for training expert delivery, saving instructional time). However, variation in implementation can still affect outcomes when using educational technology. Research generally suggests that without follow-up support after training, implementation of educational interventions is often poor and outcomes reduced. However, the extent to which this is the case when the core element of an intervention is computer or app-delivered is not yet clear. This study investigated the effects of providing ongoing implementation support for Headsprout Early Reading (HER, an early reading programme accessible via a computer or an app), to determine whether such support leads to better outcomes. Twenty-two primary schools (269 learners) participated in a cluster-randomised controlled trial. Eleven schools received initial training followed by ongoing support across the school year, whereas the other 11 schools received initial training and technical support only. Pre- and post-measures of reading skills were conducted using the York Assessment of Reading for
Secrecy Outage Performance Analysis for Uplink CR-NOMA Systems With Hybrid SIC

In the uplink cognitive radio-inspired nonorthogonal multiple access (CR-NOMA) systems, the successive interference cancellation (SIC), and power control (PC) schemes were designed to enhance the outage performance but they lack the capability of protecting signals from being eavesdropped. This work investigates the secrecy performance of uplink CR-NOMA systems with the hybrid SIC and PC (HSIC-PC) scheme in the presence of a passive eavesdropper. Furthermore, through transmitting artificial noise (AN), a new scheme is proposed to improve the security of the cognitive user with HSIC-PC without deteriorating the primary user’s quality of service. Specifically, the primary and secondary users transmit AN cooperatively to enhance the security of the secondary user. The secrecy performance of the proposed scheme is analyzed based on the relationship between the maximum interference power that the primary user can tolerate and the secondary user’s channel gain. The analytical expressions for the secrecy outage probability (SOP) are derived, and the effect of parameters on the SOP is discussed. We also derive the analytical expressions of the asymptotic SOP in the high-power region to obtain further insights. Monte Carlo simulation results are performed to verify the analytical results. The results demonstrate that the proposed scheme performs better than the benchmarks.
Scaling analysis of meteorite shower mass distributions

Meteorite showers are the remains of extraterrestrial objects which are captivated by the gravitational field of the Earth. We have analyzed the mass distribution of fragments from 16 meteorite showers for scaling. The distributions exhibit distinct scaling behavior over several orders of magnitude; the observed scaling exponents vary from shower to shower. Half of the analyzed showers show a single scaling region while the other half show multiple scaling regimes. Such an analysis can provide knowledge about the fragmentation process and about the original meteoroid. We also suggest to compare the observed scaling exponents to exponents observed in laboratory experiments and discuss the possibility that one can derive insight into the original shapes of the meteoroids.
A WENO-Z based Eulerian-Lagrangian code for simulation of shocked flows laden with evaporating droplets.

This paper discusses the progress made towards the development of a high-fidelity computational tool to simulate turbulent flow with shocks and particles or droplets. We have extended our recently developed high-order Eulerian-Lagrangian (EL) method to include the effects of droplet evaporation. The EL method approximates the Euler equations governing the gas dynamics with the improved high order weighted essentially non-oscillatory (WENO-Z) scheme, while individual particles are traced in the Lagrangian frame using high-order time integration schemes. A high-order ENO interpolation determines the carrier phase properties at the particle location. A high-order central weighing deposits the particle influence on the carrier phase. The droplet module is verified against the D 2 -law and for a uniform gas flow interaction with a rectangular cloud of droplets.
Blood Cell Biomarkers of Inflammation and Cytokine Levels as Predictors of Response to Biologics in Patients with Psoriasis

For people with psoriasis, biomarkers aiding in the personalization of treatment with biologics are needed. We examined the usefulness of several biomarkers of inflammation in this respect. The neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), and the systemic immune–inflammation index (SII) were measured in patients with psoriasis initiating TNF-α inhibitors (n = 131), IL-17/IL-17R inhibitors (n = 65), or IL-23/IL-12/23 inhibitors (n = 50). The blood levels of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, interferon (IFN)-γ, IL-17A, IL-6, soluble IL-6 receptor (sIL-6R), and soluble IL-6 signal transducer (sIL-6ST) were measured in patients initiating adalimumab (n = 62) or IL-17/IL-17R inhibitors (n = 24). Treatment response was defined by a psoriasis area and severity index (PASI) ≤ 2 three months after treatment initiation. Responders to TNF-α inhibitors had a lower NLR at baseline than non-responders (median and interquartile range (IQR) 2.15 (1.67–2.86) vs. 2.54 (1.88–3.55); p = 0.04). Responders to treatment with adalimumab had lower IL-6 levels at baseline than non-responders (0.99 (0.42–1.4) vs. 1.62 (0.96–2.41) pg/mL; p = 0.02). For the majority of patients, the IL-17A, IL-1β, and IFN-γ levels were below quantification limits. NLR and IL-6 may serve as predictive biomarkers of treatment response to TNF-α inhibitor therapy in patients with psoriasis.
Molecular genetics of early-onset colorectal cancer

Early-onset colorectal cancer (EOCRC) has been rising in global prevalence and incidence over the past several decades. Environmental influences, including generational lifestyle changes and rising obesity, contribute to these increased rates. While the rise in EOCRC is best documented in western countries, it is seen throughout the world, although EOCRC may have distinct genetic mutations in patients of different ethnic backgrounds. Pathological and molecular characterizations show that EOCRC has a distinct presentation compared with later-onset colorectal cancer (LOCRC). Recent studies have identified DNA, RNA, and protein-level alterations unique to EOCRC, revealing much-needed biomarkers and potential novel therapeutic targets. Many molecular EOCRC studies have been performed with Caucasian and Asian EOCRC cohorts, however, studies of other ethnic backgrounds are limited. In addition, certain molecular characterizations that have been conducted for LOCRC have not yet been repeated in EOCRC, including high-throughput analyses of histone modifications, mRNA splicing, and proteomics on large cohorts. We propose that the complex relationship between cancer and aging should be considered when studying the molecular underpinnings of EOCRC. In this review, we summarize current EOCRC literature, focusing on sporadic molecular alterations in tumors, and their clinical implications. We conclude by discussing current challenges and future directions of EOCRC research efforts.
MRK 744 and MRK 1066 : two Seyfert galaxies with strong absorption-line spectra.

Spectrophotometric observations of the nuclei of two Seyfert galaxies, Mrk 744 and Mrk 1066, are reported. Both these objects have strong absorption-hne spectra due to the underlying galaxies. A least squares fitting procedure was used to decompose the spectra into the galaxy contribution, the power-law featureless continuum, and the emission-hne spectrum. Equivalent widths of the G, b, and E2 absorption features were measured and the corresponding values of the fraction of power-law contribution at 4800 Á calculated and compared to the least squares results. The two, fairly independent sets of measurements agree well, indicating a featureless continuum fraction at X4800 A, /, of 0.41+0.08 and a spectral index a = 1.0 ±0.1 for Mrk 744, and / = 0.55 + 0.02, a = 2.4 ±0.2 for Mrk 1066. It is suggested that Seyfert 1.8 galaxies like Mrk 744, and Seyfert 1.9 galaxies as well, may be objects in which the broad-line emitting region is seen nearly edge-on, so that the effects of extinction by dust are unusually large. Subject headings: galaxies: individual — galaxies: nuclei — galaxies: Seyfert
JPEG Artifact Reduction Based on Deformable Offset Gating Network Controlled by a Variational Autoencoder

For the reduction of JPEG compression artifacts, there have been many methods using deep neural networks. Most of them use the JPEG compression quality factor (QF) as prior knowledge in designing and training the networks. However, since the images we get from the Internet are often recompressed, the given QF is not so informative or misleading. Also, early works validated their methods on low QFs less than 50, while recent smartphones use high QFs larger than or equal to 90. In this paper, we propose a new JPEG artifacts reduction network considering the above-stated problems. Specifically, to extract quality information from the input image itself instead of the QF provided in the header of the JPEG file, we use a variational autoencoder (VAE) and regard its latent vector as quality information. In designing the artifact reduction network, we let the network change flexibly according to the input image quality by employing a deformable offset gating (DOG) network. The gating network and VAE are merged as our overall network, dubbed DOG-VAE, where the information from the VAE is used to adjust the DOG network according to the input quality. The DOG-VAE is trained end-to-end with the QFs in the range of [10], [90]. Extensive experiments validate that our method achieves comparable results to the state-of-the-art method for monochrome images and better results for color images. Our codes are available at https://github.com/yunjh410/DOGNet.