Miracle-dz/UniFAR-FTUs huggingface dataset:
"All of Me": Mining Users' Attributes from their Public Spotify Playlists

In the age of digital music streaming, playlists on platforms like Spotify have become an integral part of individuals' musical experiences. People create and publicly share their own playlists to express their musical tastes, promote the discovery of their favorite artists, and foster social connections. These publicly accessible playlists transcend the boundaries of mere musical preferences: they serve as sources of rich insights into users' attributes and identities. For example, the musical preferences of elderly individuals may lean more towards Frank Sinatra, while Billie Eilish remains a favored choice among teenagers. These playlists thus become windows into the diverse and evolving facets of one's musical identity. In this work, we investigate the relationship between Spotify users' attributes and their public playlists. In particular, we focus on identifying recurring musical characteristics associated with users' individual attributes, such as demographics, habits, or personality traits. To this end, we conducted an online survey involving 739 Spotify users, yielding a dataset of 10,286 publicly shared playlists encompassing over 200,000 unique songs and 55,000 artists. Through extensive statistical analyses, we first assess a deep connection between a user's Spotify playlists and their real-life attributes. For instance, we found individuals high in openness often create playlists featuring a diverse array of artists, while female users prefer Pop and K-pop music genres. Building upon these observed associations, we create accurate predictive models for users' attributes, presenting a novel DeepSet application that outperforms baselines in most of these users' attributes.
WAL-Net: Weakly supervised auxiliary task learning network for carotid plaques classification

The classification of carotid artery ultrasound images is a crucial means for diagnosing carotid plaques, holding significant clinical relevance for predicting the risk of stroke. Recent research suggests that utilizing plaque segmentation as an auxiliary task for classification can enhance performance by leveraging the correlation between segmentation and classification tasks. However, this approach relies on obtaining a substantial amount of challenging-to-acquire segmentation annotations. This paper proposes a novel weakly supervised auxiliary task learning network model (WAL-Net) to explore the interdependence between carotid plaque classification and segmentation tasks. The plaque classification task is primary task, while the plaque segmentation task serves as an auxiliary task, providing valuable information to enhance the performance of the primary task. Weakly supervised learning is adopted in the auxiliary task to completely break away from the dependence on segmentation annotations. Experiments and evaluations are conducted on a dataset comprising 1270 carotid plaque ultrasound images from Wuhan University Zhongnan Hospital. Results indicate that the proposed method achieved an approximately 1.3% improvement in carotid plaque classification accuracy compared to the baseline network. Specifically, the accuracy of mixed-echoic plaques classification increased by approximately 3.3%, demonstrating the effectiveness of our approach.
Tau-related reduction of glucose metabolism in mild cognitive impairment occurs independently of APOE ε4 genotype and is gradually modulated by β-amyloid

Background PET imaging studies have shown that spatially distributed measurements of β-amyloid are significantly correlated with glucose metabolism in Mild Cognitive Impairment (MCI) independently of the APOE ε4 genotype. In contrast, the relationship between tau and glucose metabolism at different stages of Alzheimer’s Disease (AD) has not been fully understood. Objective We hypothesize that spatially distributed scores of tau PET are associated with an even stronger reduction of glucose metabolism, independent of the APOE ε4 genotype and gradually modulated by β-amyloid. Methods We applied a cross-sectional statistical analysis to concurrent [18F]flortaucipir PET, [18F]florbetapir PET, and 2-[18F]fluoro-2-deoxyglucose (FDG) PET images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. We employed a Singular Value Decomposition (SVD) approach to the cross-correlation matrix between tau and the FDG images, as well as between tau and β-amyloid PET images. The resulting SVD-based tau scores are associated with cortical regions where a reduced glucose metabolism is maximally correlated with distributed patterns of tau, accounting for the effect of spatially distributed β-amyloid. Results From a population of MCI subjects, we found that the SVD-based tau scores had their maximal spatial representation within the entorhinal cortex and the lateral inferior temporal gyrus, and were significantly correlated with glucose metabolism in several cortical regions, independently from the confounding effect of the β-amyloid scores and APOE ε4. Moreover, β-amyloid gradually modulated the association between tau and glucose metabolism. Conclusions Our approach uncovered spatially distributed patterns of the tau-glucose metabolism relationship after accounting for the β-amyloid effects. We showed that the SVD-based tau scores have a strong relationship with decreasing glucose metabolism. By highlighting the more significant role of tau, rather than β-amyloid, on the reduction of glucose metabolism, our results could have important consequences in the therapeutic treatment of AD.
A nascent riboswitch helix orchestrates robust transcriptional regulation through signal integration

Widespread manganese-sensing transcriptional riboswitches effect the dependable gene regulation needed for bacterial manganese homeostasis in changing environments. Riboswitches – like most structured RNAs – are believed to fold co-transcriptionally, subject to both ligand binding and transcription events; yet how these processes are orchestrated for robust regulation is poorly understood. Through a combination of single molecule and bulk approaches, we discovered how a single Mn2+ ion and the transcribing RNA polymerase (RNAP), paused immediately downstream by a DNA template sequence, are coordinated by the bridging switch helix P1.1 in the paradigmatic Lactococcus lactis riboswitch. This coordination achieves a heretofore-overlooked semi-docked global conformation of the nascent RNA, P1.1 base pair stabilization, transcription factor NusA ejection, and RNAP pause extension, thereby enforcing transcription readthrough. Our work demonstrates how a central, adaptable RNA helix functions analogous to a molecular fulcrum of a first-class lever system to integrate disparate signals for finely balanced gene expression control.
Malaria parasite resistance to azithromycin is not readily transmitted by 1 mosquitoes 2

14 Drug resistance in malaria parasites severely erodes our ability to control disease. Combination 15 therapies—where multiple compounds are combined to reduce the probability of resistance 16 emerging to two or more compounds simultaneously—are the favoured solution to stemming 17 antimalarial resistance. Thus, identifying suitable partner compounds for combinations is a 18 priority. We sought potential partner compounds with inherent refractoriness to the spread of 19 resistance that might better protect the primary antimalarial. We focused on azithromycin, a cheap, 20 safe antibacterial that kills malaria parasites by blocking protein synthesis in the apicoplast—a 21 relict plastid in malaria parasites. Selection for azithromycin resistance in rodent ( Plasmodium 22 berghei ) and human ( P. falciparum ) malaria parasites yielded various mutations in the apicoplast-23 encoded gene for the 50S large ribosomal subunit protein L4 (Rpl4). P. berghei Rpl4 mutant 24 parasites developed poorly in mosquitoes, producing aberrant oocysts and low numbers of 25 sporozoites. P. falciparum Rpl4 mutants developed normally in mosquitoes. The azithromycin 26 resistant mutants of both P. berghei and P. falciparum parasites could establish liver stage 27 infections, but both species developed aberrantly
Chronic potentiation of metabotropic glutamate receptor 2 with a nanobody accelerates amyloidogenesis in Alzheimer’s disease

Immunotherapy of Alzheimer’s disease (AD) is a promising approach to reduce the accumulation of amyloid-beta (Aβ), a critical event in the onset of the disease. Targeting the group II metabotropic glutamate receptors, mGlu2 and mGlu3, could be important in controlling Aβ production, although their respective contribution remains unclear due to the lack of selective tools. Here, we show that enhancing mGlu2 receptor activity increases Aβ1-42 peptide production whereas activation of mGlu3 has no effect. We show that such a difference likely results from the direct interaction of APP with mGlu3, but not with mGlu2 receptors, that prevents APP amyloidogenic cleavage and Aβ1-42 peptides production. We then show that chronic treatments of the AD model 5xFAD mice with a brain-penetrating mGlu2-potentiating nanobody accelerated amyloid aggregation and exacerbated memory deficits, but had no effect in control mice. Our results confirm that a selective mGluR2 activation exacerbates AD disease development, suggesting that therapeutic benefices could be obtained with blockers of this receptor. Our study also provides the proof-of-concept that chronic administration of nanobodies targeting neuroreceptors can be envisioned to treat brain diseases.
Finding Important Arguments from a Legal Case

Within the legal field, the strength of an argument can be the deciding factor in the outcome of a case. Lawyers find themselves spending hours going over and analysing legal precedents and relevant statutes to build a compelling argument, and with the exponential growth in case data availability it can be useful for a lawyer if an artificial intelligence tool can automatically show important arguments present in a similar case from the past. In this work we propose an approach to estimate the importance of arguments using Natural Language Processing techniques. As a first step arguments are extracted from a legal case, and then the importance of each argument is estimated in an automated way. We explored both supervised and unsupervised approach to estimate the importance of arguments in a legal case.
A holistic system for fostering active aging: the D3A project

Recent research highlights the significance of active aging, emphasizing its role in enhancing the well-being of the elderly population. To effectively promote active aging and address the evolving needs of our growing global aging demographic, a fusion of technological innovation and progressive policy strategies is imperative. In response to this challenge, we introduce the D3A (Digital Assistant for Active Aging) system – a pioneering platform aimed at elevating the quality of life for the elderly. D3A focuses on optimizing interconnected facets of physical and cognitive performance. Within this framework, healthcare professionals can tailor individualized training regimens encompassing both physical and cognitive exercises, which can be experienced in both traditional and virtual reality settings. D3A leverages artificial intelligence algorithms to assess the efficacy of these exercises, providing valuable support to healthcare providers. Moreover, the platform incorporates wearable devices to monitor users’ physiological parameters, serving as crucial indicators of their overall health. Also, D3A employs blockchain technology to ensure robust security and data immutability for access control, activity logs, and health records within the application. This holistic approach to active aging promises a brighter future for our aging population, driven by innovation and evidence-based care.
Does A Longer Commuting Time Increases The Probability Of Being Victim Of Urban Violence? The Evidence From Brazilian Metropolitan Regions

Empirical evidence about the influence of exposure to public spaces on victimization strongly support the routine activities theory but, maybe reflecting the difficult of available data, specific evidence about the influence of the commuting on probability of victimization is not abundant. In this paper, we analyze this relationship using a large nationally representative cross-section sample of Brazilian individuals for 2009, using propensity score matching techniques to create counterfactuals and performing robustness checks and implementing a simulation-based sensitivity analysis that support a causal interpretation of the results. We find that individuals with more than one hour of commuting have an overall 2.1% increase in the probability of being victim of robbery, with no robust impact on theft. Also, following the exposure literature we find larger effect on the probability of robbery victimization on women when compared with men, 2.5% and 2.2% respectively.
Offset-dependence of production-related 4D time shifts: Real data examples and modeling

We present examples of 4D time-shifts obtained with offset and angle sub-stacks of seismic data acquired in deep (Gulf of Mexico) and shallow water (North Sea) marine environments. We compare the observations with two proposed rock-physics models using different linear relationships between the velocity change and the strain field induced by reservoir compaction. The model involving only vertical strain component predicts a similar time-shift with offset behavior as that observed from the data. We do not observe a strong decrease of time-shifts with offset as reported in previous publications.
Differential responses of production and respiration to temperature and moisture drive the carbon balance across a climatic gradient in New Mexico

Southwestern North America faces an imminent transition to a warmer, more arid climate, and it is critical to understand how these changes will affect the carbon balance of southwest ecosystems. In order to test our hypothesis that differential responses of production and respiration to temperature and moisture shape the carbon balance across a range of spatio-temporal scales, we quantified net ecosystem exchange (NEE) of CO2 and carbon storage across the New Mexico Elevational Gradient, which consists of six eddy-covariance sites representing biomes ranging from desert to subalpine conifer forest. Within sites, hotter and drier conditions were associated with an increasing advantage of respiration relative to production such that daily carbon uptake peaked at intermediate temperatures ‐ with carbon release often occurring on the hottest days ‐ and increased with soil moisture. Across sites, biotic adaptations modified but did not override the dominant effects of climate. Carbon uptake increased with decreasing temperature and increasing precipitation across the elevational gradient; NEE ranged from a source of � 30gCm � 2 yr � 1 in the desert grassland to a sink of � 350gCm � 2 yr � 1 in the subalpine conifer forest. Total aboveground carbon storage increased dramatically with elevation, ranging from 186gCm � 2 in the desert grassland to 26600gCm � 2 in the subalpine conifer forest. These results make sense in the context of global patterns in NEE and biomass storage, and support that increasing temperature and decreasing moisture shift the carbon balance of ecosystems in favor of respiration, such that the potential for ecosystems to sequester and store carbon is reduced under hot and/or dry conditions. This implies that projected climate change will trigger a substantial net release of carbon in these New Mexico ecosystems (� 3Gt CO2 statewide by the end of the century), thereby acting as a positive feedback to climate change.
TOWARDS AUTOMATING THE ASSESSMENT OF TEACHERS’ TEACHING EMOTIONS IN PRESCHOOL CLASSROOMS

In-person assessment of teaching emotion as part of a teacher’s working performance evaluation is onerous, and can be intrusive to some teachers in teaching. This study shows preliminary attempts at solving this issue using a machine learning approach with bi-modal artificial neural networks, which made predictions by combining acoustic and textual features extracted from preschool teachers’ spontaneous speech captured in real teaching scenarios. In a binary classification task identifying the emotions as “positive” and “negative”, the prediction achieved an accuracy of 79.0%, an F1-score of 83.1% in cross-validation, and an accuracy of 68.4%, an F1-score of 67.2% in leave-one-subject-out validation. When further adding speech samples identified as “neutral” to the task, a decreased accuracy of 52.4% and F1-score of 53.6% were received in cross-validation, confirming the difficulties in labelling this type of naturalistic speech data even for human raters.
SPEECH RATE EFFECTS IN FRENCH STOP VOICING PRODUCTION AND PERCEPTION

Studies on speech rate variation have reported shortening of prevoicing and aspiration of stops in fast speech. Perception studies have also found that the boundary between short and long-lag VOT stops shifts to shorter VOTs when the speech rate increases in the carrier phrase. However, no previous study has explored how speech rate variation affects the perception of prevoiced stops. Our study aims to fill this gap by investigating the effects of speech rate variation on French stops, which contrast prevoiced and short-lag stops. We collected production and perception data from the same participants using the same speech materials. Thirty-one self-identified native speakers of French participated in an online experiment. The production results confirmed previous observations of shortening of prevoicing and aspiration in fast speech. The perception results showed an expected shift in perception for positive VOTs based on speech rate but not for negative VOTs.
USING MAHALANOBIS DISTANCE TO FILTER ERRONEOUS VOWEL FEATURES IN LESS-RESOURCED LANGUAGES : APPLICATION TO QUEBEC FRENCH

A major challenge in building shareable datasets for phonetic studies consists of maximising data collections while minimising the errors involved, in particular when automatic processes come into play (e.g. labeling, formant detection.). Automatically extracting formants from large amounts of speech frequently produces artifacts, due to formant jumps, alignment problems, or noise. One solution is to use formant range filters. However this requires prior knowledge about the vowels, such as formant range information. Here we propose to use the Mahalanobis distance to remove erroneous values relying only on the labeled speech data. Our study is conducted on a Quebec French corpus including more than 170 k tokens of 16 vowel types. Results show that the proposed method can complement the threshold-based filter approach. Furthermore, it can be used autonomously for undocumented languages to eliminate erroneous values. The approach also makes it easy to adjust the degree of filtering.
The natural cardioprotective particle HDL modulates connexin43 gap junction channels

High-density lipoprotein (HDL) is known for its cardioprotective properties independent from its cholesterol transport activity. These properties are mediated by activation of kinases such as protein kinase C (PKC). Connexin43 (Cx43) is a gap junction protein present in ventricular cardiomyocytes. PKC-dependent phosphorylation modiﬁes Cx43 gap junction channel properties and is involved in cardioprotection. We hypothesized that cardioprotective properties of HDL may be mediated in part by affecting Cx43 gap junction channels.
KOREAN LISTENERS’ WEIGHTING AND INTEGRATION OF CUES TO THE THREE-WAY KOREAN STOP CONTRAST

The current study investigates whether listeners’ cue weighting predicts their cue integration as the speech signal unfolds over time. It does so by testing the time course of acoustic cue integration in the processing of Korean stop contrasts by native Korean listeners. Listeners’ weighting of voice onset time (VOT) and fundamental frequency (F0) to perceive Korean stop contrasts was measured with a cue-weighting speech perception task, and the time course of VOT and F0 integration was examined with a visual-world eye-tracking task. The results revealed that the timing of VOT integration is predicted by listeners’ reliance on F0, with delayed integration of VOT in target-competitor pairs where F0 is a primary cue to process the stop contrast. These results suggest that listeners adapt their integration of acoustic cues in spoken word recognition based on the importance they assign to individual cues.
DISCERNING DIMENSIONS OF QUALITY FOR STATE OF THE ART SYNTHETIC SPEECH

This paper describes an approach for determining the dimensions of quality for state-of-the-art synthetic speech. We propose that current evaluation metrics do not fully capture the meaningful dimensions of text-to-speech (TTS) and voice conversion (VC) systems. In order to develop a revised paradigm for meaningful evaluation, we conducted two experiments. First, we determined descriptive terms by querying naïve listeners on their impressions of modern TTS and VC systems. In a second experiment, we refined these terms into dimensions of quality and similarity by showcasing a consolidation procedure of manual clusterings. The resulting dimensions contain the standard evaluation categories of “intelligibility” and “naturalness” for both conditions. We could additionally discern dimensions of “tempo” and “demographics” in both domains. The final two dimensions as well as the relationships between categories proved to be different between TTS and VC, suggesting the need for modified evaluation scales based on the target construct.
Aqueous history of Mars as inferred from landed mission measurements of rocks, soils, and water ice

The missions that have operated on the surface of Mars acquired data that complement observations acquired from orbit and provide information that would not have been acquired without surface measurements. Data from the Viking Landers demonstrated that soils have basaltic compositions, containing minor amounts of salts and one or more strong oxidants. Pathfinder with its rover confirmed that the distal portion of Ares Vallis is the site of flood‐deposited boulders. Spirit found evidence for hydrothermal deposits surrounding the Home Plate volcanoclastic feature. Opportunity discovered that the hematite signature on Meridiani Planum as seen from orbit is due to hematitic concretions concentrated on the surface as winds eroded sulfate‐rich sandstones that dominate the Burns formation. The sandstones originated as playa muds that were subsequently reworked by wind and rising groundwater. Opportunity also found evidence on the rim of the Noachian Endurance Crater for smectites, with extensive leaching along fractures. Curiosity acquired data at the base of Mount Sharp in Gale Crater that allows reconstruction of a sustained fluvial‐deltaic‐lacustrine system prograding into the crater. Smectites and low concentrations of chlorinated hydrocarbons have been identified in the lacustrine deposits. Phoenix, landing above the Arctic Circle, found icy soils, along with low concentrations of perchlorate salt. Perchlorate is considered to be a strong candidate for the oxidant found by the Viking Landers. It is also a freezing point depressant and may play a role in allowing brines to exist at and beneath the surface in more modern periods of time on Mars.
Livestock fodder development as an essential component of catchment management: case study in Mai Zeg-Zeg

1 Arid Land Research Center, Tottori University, 1390 Hamasaka, Tottori 680-0001, Japan 2 Department of Land Resources Management and Environmental Protection, Mekelle University, P.O. Box 231, Ethiopia 3 ADCS Mekelle May Zeg-zeg project, Mekelle, Ethiopia 4 Geography Department, Gent University, Krijgslaan 281 (S8), B 9000, Gent, Belgium 5 Department of Earth and Environmental Sciences, Divison of Geography, K.U. Leuven, Celestijnenlaan 200 E, B3001 Heverlee, Belgium * Corresponding author: nigussie_haregeweyn@yahoo.com