Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of dialect variation on speech intelligibility in noise

Recent research has shown that listeners can classify talkers based on their regional dialect of American English (AE). The present experiment explored the effects of regional dialect variation on speech intelligibility. Participants from various AE dialects transcribed meaningful English sentences mixed with noise. The sentences were produced by male and female talkers from four different AE regional dialects. At a favorable signal‐to‐noise ratio (−2 dB), intelligibility of General American and Southern talkers was significantly better than Northern and Mid‐Atlantic talkers, and was significantly better for the Northern than the Mid‐Atlantic talkers. At a more difficult signal‐to‐noise ratio (−6 dB), intelligibility was equally poor for the Southern, Northern, and Mid‐Atlantic talkers, but remained significantly better for the General American talkers. No effects of listener dialect were observed. Thus, speech intelligibility in noise was generally poorer for more phonologically marked dialects (e.g., No.
Low‐Altitude UAV Imaging Accurately Quantifies Eelgrass Wasting Disease From Alaska to California

Declines in eelgrass, an important and widespread coastal habitat, are associated with wasting disease in recent outbreaks on the Pacific coast of North America. This study presents a novel method for mapping and predicting wasting disease using Unoccupied Aerial Vehicle (UAV) with low‐altitude autonomous imaging of visible bands. We conducted UAV mapping and sampling in intertidal eelgrass beds across multiple sites in Alaska, British Columbia, and California. We designed and implemented a UAV low‐altitude mapping protocol to detect disease prevalence and validated against in situ results. Our analysis revealed that green leaf area index derived from UAV imagery was a strong and significant (inverse) predictor of spatial distribution and severity of wasting disease measured on the ground, especially for regions with extensive disease infection. This study highlights a novel, efficient, and portable method to investigate seagrass disease at landscape scales across geographic regions and conditions.
Historical Changes in Wind‐Driven Ocean Circulation Can Accelerate Global Warming

Mitigation and adaptation strategies for climate change depend on accurate climate projections for the coming decades. While changes in radiative heat fluxes are known to contribute to surface warming, changes to ocean circulation can also impact the rate of surface warming. Previous studies suggest that projected changes to ocean circulation reduce the rate of global warming. However, these studies consider large greenhouse gas forcing scenarios, which induce a significant buoyancy‐driven decline of the Atlantic Meridional Overturning Circulation. Here, we use a climate model to quantify the previously unknown impact of changes to wind‐driven ocean circulation on global surface warming. Wind‐driven ocean circulation changes amplify the externally forced warming rate by 17% from 1979 to 2014. Accurately simulating changes to the atmospheric circulation is key to improving near‐term climate projections.
Random‐digit dialling in the UK: viability revisited

A main obstacle to using telephone methods for social surveys in the UK has been the inability to select a representative and unbiased probability sample of the general population. However, recent changes in the UK telephone numbering system and advances in telephony software appear to provide the means for using random‐digit dialling (RDD). This paper presents the results of a study designed to test the feasibility of RDD. The focus is on the sampling method, but we also assess other aspects of the RDD survey method, in the context of a total survey error framework. Although we conclude that RDD is now a viable survey method in the UK, further research and development is advocated to improve the efficiency of fieldwork and response rates.
Solar Control of the Pickup Ion Plume in the Dayside Magnetosheath of Venus

Using the 8.5‐year Venus Express measurements, we demonstrate the asymmetric plasma distributions in the Venusian magnetosheath. An escaping plume is formed by pickup oxygen ions in the hemisphere where the motional electric field points outward from Venus, while the velocity of solar wind protons is faster in the opposite hemisphere. The pickup O+ escape rate is estimated to be (3.6 ± 1.4) × 1024 s−1 at solar maximum, which is comparable to the ion loss rate through the magnetotail, and (1.3 ± 0.4) × 1024 s−1 at solar minimum. The increase of O+ fluxes with extreme ultraviolet (EUV) intensity is significant upstream of the bow shock, partially attributed to the increase of exospheric neutral oxygen density. However, the solar wind velocity just has a slight effect on the pickup O+ escape rate in the magnetosheath, while the effect of solar wind density is not observed. Our results suggest the pickup O+ escape rate is mainly controlled by EUV radiation.
Contrasting Influence of Nitrogen Oxides on the Cloud Condensation Nuclei Activity of Monoterpene‐Derived Secondary Organic Aerosol in Daytime and Nighttime Oxidation

Anthropogenic nitrogen oxides may influence the cloud condensation nuclei (CCN) activity of biogenic secondary organic aerosols (SOA) in both daytime photooxidation and nighttime NO3 oxidation, which has significant implications for the climatic impact of SOA. We investigated the influence of NOx on the CCN activity of monoterpene‐derived SOA in OH oxidation and in NO3 oxidation. In OH oxidation, NOx had little influence on the hygroscopic parameter κ of organic aerosol (κOrg), which was attributed to the minor fraction of organic nitrates (ON) in SOA (<24%), resulted from the low branching ratio of RO2 + NO to form ON. In contrast, in NO3 oxidation κOrg was much reduced compared to OH/O3 oxidation due to a dominant fraction of ON. We report κ of MT‐derived ON formed in photo‐oxidation and NO3 oxidation (0.029–0.052) for the first time to our knowledge, which may be used to improve model simulations of CCN concentrations.
Syringin exerts anti‐inflammatory and antioxidant effects by regulating SIRT1 signaling in rat and cell models of acute myocardial infarction

This study aimed to investigate the role of syringin in improving heart function during myocardial ischemia/reperfusion (I/R) and to determine whether the sirtuin 1/peroxisome proliferator‐activated receptor gamma coactivator 1 alpha (SIRT1/PGC‐1α) pathway contributes to this cardioprotective effect in vivo and in vitro.
Bayesian inference of toothed whale lifespans

Accurate measures of lifespan and age-specific mortality are important both for understanding life-history evolution and informing conservation and population management strategies. The most accurate data to estimate lifespan are from longitudinal studies, but for many species – especially those such as toothed whales that are wide-ranging and live in difficult-to-access environments - these longitudinal data are not available. However, other forms of age-structured data – such as from mass-strandings - are available for many toothed species, and using these data to infer patterns of age-specific mortality and lifespan remains an important outstanding challenge. Here we develop and test a Bayesian mortality model to derive parameters of a mortality function from age-structured data while accounting for potential error introduced to these data by mistakes in age estimation, sampling biases and population growth. We then searched the literature to assemble a database of 269 published age-structured toothed whale datasets. We applied our mortality model to derive lifespan estimates for 32 species of female and 33 species of male toothed whale. We also use our model to characterise sex differences in lifespan in toothed whales. Our mortality model allows us to curate the most complete and accurate collection of toothed whale lifespans to date.
OSBP-mediated PI(4)P-cholesterol exchange at endoplasmic reticulum-secretory granule contact sites controls insulin secretion

Insulin secretion is the process whereby insulin-containing granules fuse with the plasma membrane of pancreatic β-cells. Exocytosis is preceded by cargo loading and granule biogenesis at the Golgi, followed by maturation and transport of the secretory granules; processes that require modification of both the protein and lipid composition of the granules. Here, we show that insulin-containing secretory granules form physical contacts with the endoplasmic reticulum. The lipid exchange protein OSBP dynamically redistributes to ER-SG contacts in a process regulated by Ca2+ and cytosolic pH, and contributes to cholesterol loading of the granules. This process depends on granular PI(4)P and ER-localized VAPs, and is positively regulated by granular PI4-kinases and negatively regulated by granule-localized Sac2. Loss of Sac2 results in excess accumulation of cholesterol on insulin granules that is normalized when OSBP expression is reduced, and both acute inhibition and siRNA-mediated knockdown of OSBP suppresses glucose-stimulated insulin secretion without affecting insulin production or intracellular Ca2+ signaling. In conclusion, we show that lipid exchange at ER-granule contact sites is involved in the exocytic process, and propose that these contacts act as reaction centers with multimodal functions during insulin granule maturation.
Emergence of universal computations through neural manifold dynamics

There is growing evidence that many forms of neural computation may be implemented by low-dimensional dynamics unfolding at the population scale. However, neither the connectivity structure nor the general capabilities of these embedded dynamical processes are currently understood. In this work, the two most common formalisms of firing-rate models are evaluated using tools from analysis, topology and nonlinear dynamics in order to provide plausible explanations for these problems. It is shown that low-rank structured connectivity predicts the formation of invariant and globally attracting manifolds in both formalisms, which generalizes existing theories to different neural models. Regarding the dynamics arising in these manifolds, it is proved they are topologically equivalent across the considered formalisms. It is also stated that under the low-rank hypothesis, dynamics emerging in neural models are universal. These include input-driven systems, which broadens previous findings. It is then explored how low-dimensional orbits can bear the production of continuous sets of muscular trajectories, the implementation of central pattern generators and the storage of memory states. It is also proved these dynamics can robustly simulate any Turing machine over arbitrary bounded memory strings, virtually endowing rate models with the power of universal computation. In addition, it is shown how the low-rank hypothesis predicts the parsimonious correlation structure observed in cortical activity. Finally, it is discussed how this theory could provide a useful tool from which to study neuropsychological phenomena using mathematical methods.
Machine-learning and mechanistic modeling of primary and metastatic breast cancer growth after neoadjuvant targeted therapy

Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors prior to surgery while simultaneously allowing for controlled evaluation of biomarkers, toxicity, and suppression of distant (occult) metastatic disease. Yet such trials are rarely preceded by preclinical testing involving surgery. Here we used a mouse model of spontaneous metastasis after surgical removal to develop a predictive mathematical model of neoadjuvant treatment response to sunitinib, a receptor tyrosine kinase inhibitor (RTKI). Longitudinal data consisted of measurements of presurgical primary tumor size and postsurgical metastatic burden in 128 mice (104 for model training, 24 for validation), following variable neoadjuvant treatment schedules over a 14-day period. A nonlinear mixed-effects modeling approach was used to quantify inter-animal variability. Machine learning algorithms were applied to investigate the significance of several biomarkers at resection as predictors of individual kinetics. Biomarkers included circulating tumor- and immune-based cells (circulating tumor cells and myeloid-derived suppressor cells) as well as immunohistochemical tumor proteins (CD31 and Ki67). Our simulations showed that neoadjuvant RTKI treatment inhibits primary tumor growth but has little efficacy in preventing (micro)-metastatic disease progression after surgery. Surprisingly, machine-learning algorithms demonstrated only limited predictive power of tested biomarkers on the mathematical parameters. These results suggest that presurgical modeling might be an effective tool to screen biomarkers prior to clinical trial testing. Mathematical modeling combined with artificial intelligence techniques represent a novel platform for integrating preclinical surgical metastasis models in outcome prediction of neoadjuvant treatment. Major findings Using simulations from a mechanistic mathematical model compared with preclinical data from surgical metastasis models, we found anti-tumor effects of neoadjuvant RTKI treatment can differ between the primary tumor and metastases in the perioperative setting. Model simulations with variable drug doses and scheduling of neoadjuvant treatment revealed a contrasting impact on initial primary tumor debulking and metastatic outcomes long after treatment has stopped and tumor surgically removed. Using machine-learning algorithms, we identified the limited power of several circulating cellular and molecular biomarkers in predicting metastatic outcome, uncovering a potential fast-track strategy for assessing future clinical biomarkers by paring patient studies with identical studies in mice.
INFLATION OF A DIPOLE FIELD IN LABORATORY EXPERIMENTS: TOWARD AN UNDERSTANDING OF MAGNETODISK FORMATION IN THE MAGNETOSPHERE OF A HOT JUPITER

Giant exoplanets at close orbits, or so-called hot Jupiters, are supposed to have an intensive escape of upper atmospheric material heated and ionized by the radiation of a host star. An interaction between outflowing atmospheric plasma and the intrinsic planetary magnetic dipole field leads to the formation of a crucial feature of a hot Jupiter's magnetosphere—an equatorial current-carrying magnetodisk. The presence of a magnetodisk has been shown to influence the topology of a hot Jupiter's magnetosphere and to change a standoff distance of the magnetopause. In this paper, the basic features of the formation of a hot Jupiter's magnetodisk are studied by means of a laboratory experiment. A localized central source produces plasma that expands outward from the surface of the dipole and inflates the magnetic field. The observed structure of magnetic fields, electric currents, and plasma density indicates the formation of a relatively thin current disk extending beyond the Alfvénic point. At the edge of the current disk, an induced magnetic field was found to be several times larger than the field of the initial dipole.
Hydraulic adjustments of Scots pine colonizing a harsh environment on volcano slopes

The ability of trees to survive and naturally regenerate in increasing drought conditions will depend on their capacity to vary key hydraulic and morphological traits that increase drought tolerance. Despite many studies investigating variability in these drought-tolerant traits, there has been limited investigation into this variability under recurrent severe drought conditions since the establishment phase. We investigated the long-term hydraulic and leaf trait adjustments of Scots pine trees settled in an abandoned slag quarry by comparing them across three different topographic positions inducing contrasted effects on growth and development. We measured xylem and foliar traits to compare the water status of trees according to tree location and to evaluate the respective risk for xylem hydraulic failure using the soil-plant hydraulic model SurEau. Compared to upslope and downslope trees, slope trees exhibited lower growth, vulnerability to embolism, specific hydraulic conductivity and photosynthetic pigment contents, as well as higher water potential at turgor loss point and midday water potentials. The hydraulic adjustments of trees settled on slag slopes reduced the risk for hydraulic failure and thus prevented an increase in embolism compared to downslope and upslope trees. These results suggest a prioritization of hydraulic safety over growth in Scots pine developed in a harsh environment, resulting in a dwarf phenotype.
Effect of plasma N2 and thermal NH3 nitridation in HfO2 for ultrathin equivalent oxide thickness

Two methods of HfO2 nitridation including plasma N2 nitridation and thermal NH3 anneal were studied for ultrathin HfO2 gate dielectrics with <1 nm equivalent oxide thickness (EOT). The detailed nitridation mechanism, nitrogen depth profile, and nitrogen behavior during the anneal process were thoroughly investigated by XPS and SIMS analysis for the two types of nitridation processes at different process conditions. Intermediate metastable nitrogen was observed and found to be important during the plasma nitridation process. For thermal NH3 nitridation, pressure was found to be most critical to control the nitrogen profile while process time and temperature produced second order effects. The physical analyses on the impacts of various process conditions are well correlated to the electrical properties of the films, such as leakage current, EOT, mobility, and transistor bias temperature instability.
Auditory confounds can drive online effects of transcranial ultrasonic stimulation in humans

Transcranial ultrasonic stimulation (TUS) is rapidly emerging as a promising non-invasive neuromodulation technique. TUS is already well-established in animal models, providing foundations to now optimize neuromodulatory efficacy for human applications. Across multiple studies, one promising protocol, pulsed at 1000 Hz, has consistently resulted in motor cortical inhibition in humans (Fomenko et al., 2020). At the same time, a parallel research line has highlighted the potentially confounding influence of peripheral auditory stimulation arising from TUS pulsing at audible frequencies. In this study, we disentangle direct neuromodulatory and indirect auditory contributions to motor inhibitory effects of TUS. To this end, we include tightly matched control conditions across four experiments, one preregistered, conducted independently at three institutions. We employed a combined transcranial ultrasonic and magnetic stimulation paradigm, where TMS-elicited motor-evoked potentials (MEPs) served as an index of corticospinal excitability. First, we replicated motor inhibitory effects of TUS but showed through both tight controls and manipulation of stimulation intensity, duration, and auditory masking conditions that this inhibition was driven by peripheral auditory stimulation, not direct neuromodulation. Further, we consider neuromodulation beyond driving overall excitation/inhibition and show preliminary evidence of how TUS might interact with ongoing neural dynamics instead. Primarily, this study highlights the substantial shortcomings in accounting for the auditory confound in prior TUS-TMS work where only a flip-over sham and no active control was used. The field must critically reevaluate previous findings given the demonstrated impact of peripheral confounds. Further, rigorous experimental design via (in)active control conditions is required to make substantiated claims in future TUS studies. Only when direct effects are disentangled from those driven by peripheral confounds can TUS fully realize its potential for research and clinical applications.
Estimation in Multiple Correlation/Prediction

The distinction between the square of a population correlation coefficient (ρ2) and of the true validity of a sample prediction equation (ρ v 2) as the parameters of interest in multiple correlation and in multiple prediction studies, respectively, is discussed. Real data are used to illustrate the comparison of two estimators for ρ2, RR 2 (Ezekiel) and ROP 2 (Olkin and Pratt), and of three estimators for ρv 2 , RNL 2 (Nicholson, Lord), RSD 2 (Stein, Darlington) and RLO 2 (a jack-knife-like estimator). Interpretive approaches to, and problems in, multiple correlation/prediction estimation are discussed.
On the R ‐boundedness of solution operator families of the generalized Stokes resolvent problem in an infinite layer

In this paper, we prove the R ‐boundedness of solution operator families of the generalized Stokes resolvent problem in an infinite layer with resolvent parameter λ∈Σϵ,γ0 , where Σϵ,γ0={λ∈C||argλ|≤π−ϵ,|λ|≥γ0}(00) , and our boundary conditions are nonhomogeneous Neumann on upper boundary and Dirichlet on lower boundary. We want to emphasize that we can choose 0 < ϵ < π ∕ 2 and γ0 > 0 arbitrarily, although usual parabolic theorem tells us that we must choose a large γ0 > 0 for given 0 < ϵ < π ∕ 2. We also prove the maximal Lp − Lq regularity theorem of the nonstationary Stokes problem as an application of the R ‐boundedness. The key of our approach is to apply several technical lemmas to the exact solution formulas of a resolvent problem. The formulas are obtained through the solutions of the ODEs, in the Fourier space, driven by the partial Fourier transform with respect to tangential space variable x′=(x1,…,xN−1) . Copyright © 2014 John Wiley & Sons, Ltd.
Slot region electron loss timescales due to plasmaspheric hiss and lightning‐generated whistlers

[1] Energetic electrons (E > 100 keV) in the Earth's radiation belts undergo Doppler-shifted cyclotron resonant interactions with a variety of whistler mode waves leading to pitch angle scattering and subsequent loss to the atmosphere. In this study we assess the relative importance of plasmaspheric hiss and lightning-generated whistlers in the slot region and beyond. Electron loss timescales are determined using the Pitch Angle and energy Diffusion of Ions and Electrons (PADIE) code with global models of the spectral distributions of the wave power based on CRRES observations. Our results show that plasmaspheric hiss propagating at small and intermediate wave normal angles is a significant scattering agent in the slot region and beyond. In contrast, plasmaspheric hiss propagating at large wave normal angles and lightning-generated whistlers do not contribute significantly to radiation belt loss. The loss timescale of 2 MeV electrons due to plasmaspheric hiss propagating at small and intermediate wave normal angles in the center of the slot region (L = 2.5) lies in the range 1–10 days, consistent with recent Solar Anomalous and Magnetospheric Particle Explorer (SAMPEX) observations. Wave turbulence in space, which is responsible for the generation plasmaspheric hiss, thus leads to the formation of the slot region. During active periods, losses due to plasmaspheric hiss may occur on a timescale of 1 day or less for a wide range of energies, 200 keV < E < 1 MeV, in the region 3.5 < L < 4.0. Plasmaspheric hiss may thus also be a significant loss process in the inner region of the outer radiation belt during magnetically disturbed periods.
Simultaneous Measurements of Ion Temperature by Segmented Tunnel and Katsumata Probe

Simultaneous measurements of the ion temperature by the segmented tunnel and Katsumata probe in the CASTOR tokamak are reported. The segmented tunnel probe measures two ion saturation currents Iseg 1, Iseg 2 towards two segments of the tunnel. The axis of the tunnel is aligned with the total magnetic field. The value of the ratio of these two currents combined with the results of the PIC modeling provides the ion temperature. Design and experimental arrangement of the Katsumata probe enable us to measure the pure ion current by sweeping the applied voltage. The ion temperature is then estimated from the exponential part of the measured I – V characteristic. Simultaneous measurements of the ion temperature by the segmented tunnel and Katsumata probe agree within a few eV. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)