Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal Variability of Precipitation and Biomass of Alpine Grasslands on the Northern Tibetan Plateau

The timing regimes of precipitation can exert profound impacts on grassland ecosystems. However, it is still unclear how the peak aboveground biomass (AGBpeak) of alpine grasslands responds to the temporal variability of growing season precipitation (GSP) on the northern Tibetan Plateau. Here, the temporal variability of precipitation was defined as the number and intensity of precipitation events as well as the time interval between consecutive precipitation events. We conducted annual field measurements of AGBpeak between 2009 and 2016 at four sites that were representative of alpine meadow, meadow-steppe, alpine steppe, and desert-steppe. Thus, an empirical model was established with the time series of the field-measured AGBpeak and the corresponding enhanced vegetation index (EVI) (R2 = 0.78), which was used to estimate grassland AGBpeak at the regional scale. The relative importance of the three indices of the temporal variability of precipitation, events, intensity, and time interval on grassland AGBpeak was quantified by principal component regression and shown in a red–green–blue (RGB) composition map. The standardized importance values were used to calculate the vegetation sensitivity index to the temporal variability of precipitation (VSIP). Our results showed that the standardized VSIP was larger than 60 for only 15% of alpine grassland pixels and that AGBpeak did not change significantly for more than 60% of alpine grassland pixels over the past decades, which was likely due to the nonsignificant changes in the temporal variability of precipitation in most pixels. However, a U-shaped relationship was found between VSIP and GSP across the four representative grassland types, indicating that the sensitivity of grassland AGBpeak to precipitation was dependent on the types of grassland communities. Moreover, we found that the temporal variability of precipitation explained more of the field-measured AGBpeak variance than did the total amount of precipitation alone at the site scale, which implies that the mechanisms underlying how the temporal variability of precipitation controls the AGBpeak of alpine grasslands should be better understood at the local scale. We hypothesize that alpine grassland plants promptly respond to the temporal variability of precipitation to keep community biomass production more stable over time, but this conclusion should be further tested. Finally, we call for a long-term experimental study that includes multiple natural and anthropogenic factors together, such as warming, nitrogen deposition, and grazing and fencing, to better understand the mechanisms of alpine grassland stability on the Tibetan Plateau.
The role of resilience in student‐athletes' sport and school burnout and dropout: A longitudinal person‐oriented study

Although it has been shown that student‐athletes who pursue upper secondary school alongside with an athletic career may be prone to sport and school burnout, the concrete life changes resulting from burning out, such as dropping out of sport or school, have not been investigated. Moreover, it is unknown why some student‐athletes do not burnout. The purpose of the present study was to examine whether there are different kinds of profiles—based on the level and development of sport and school burnout symptoms across upper secondary school—that can be identified among student‐athletes and how resilience and the likelihood of dropping out from sport or school differ between the profiles. The sample consisted of 491 (49% females) Finnish student‐athletes who filled in questionnaires four times during the three years of upper secondary school. The data were analyzed by using growth mixture modeling. Three burnout profiles were identified: (a) Average profile, (b) Increased burnout profile, and (c) Non‐risk profile. The profiles differed significantly in terms of student‐athletes’ resilience and the likelihood of dropping out, as those in the Increased burnout group symptoms were less resilient and more likely to dropout from sport than those in the other two groups. Furthermore, those in the Non‐risk profile were more resilient than athletes in the other two groups. The results can be used in teaching student‐athletes resilience‐related skills which can prevent them from burning out and dropping out from sport and school.
Investigation on core-fucosylated prostate-specific antigen as a refined biomarker for differentiation of benign prostate hyperplasia and prostate cancer of different aggressiveness

Prostate cancer represents a major cause of cancer death in men worldwide. Novel non-invasive methods are still required for differentiation of non-aggressive from aggressive tumors. Recently, changes in prostate-specific antigen glycosylation pattern, such as core-fucosylation, have been described in prostate cancer. The objective of this study was to evaluate whether the core-fucosylation determinant of serum prostate-specific antigen may serve as refined marker for differentiation between benign prostate hyperplasia and prostate cancer or identification of aggressive prostate cancer. A previously developed liquid chromatography–mass spectrometry/mass spectrometry–based strategy was used for multiplex analysis of core-fucosylated prostate-specific antigen (fuc-PSA) and total prostate-specific antigen levels in sera from 50 benign prostate hyperplasia and 100 prostate cancer patients of different aggressiveness (Gleason scores, 5–10) covering the critical gray area (2–10 ng/mL). For identification of aggressive prostate cancer, the ratio of fuc-PSA to total prostate-specific antigen (%-fuc-PSA) yielded a 5%–8% increase in the area under the curve (0.60) compared to the currently used total prostate-specific antigen (area under the curve = 0.52) and %-free prostate-specific antigen (area under the curve = 0.55) tests. However, our data showed that aggressive prostate cancer (Gleason score > 6) and non-aggressive prostate cancer (Gleason score ≤ 6) could not significantly (p-value = 0.08) be differentiated by usage of %-fuc-PSA. In addition, both non-standardized fuc-PSA and standardized %-fuc-PSA had no diagnostic value for differentiation of benign prostate hyperplasia from prostate cancer. The %-fuc-PSA serum levels could not improve the differentiation of non-aggressive and aggressive prostate cancer compared to conventional diagnostic prostate cancer markers. Still, it is unclear whether these limitations come from the biomarker, the used patient cohort, or the imprecision of the applied method itself. Therefore, %-fuc-PSA should be further investigated, especially by more precise methods whether it could be clinically used in prostate cancer diagnosis.
Making cold malignant pleural effusions hot: driving novel immunotherapies

ABSTRACT Malignant pleural effusions, arising from either primary mesotheliomas or secondary malignancies, heralds advanced disease and poor prognosis. Current treatments, including therapeutic thoracentesis and tube thoracostomy, are largely palliative. The immunosuppressive environment within the pleural cavity includes myeloid derived suppressor cells, T-regulatory cells, and dysfunctional T cells. The advent of effective immunotherapy with checkpoint inhibitors and adoptive cell therapies for lung cancer and other malignancies suggests a renewed examination of local and systemic therapies for this malady. Prior strategies reporting remarkable success, including instillation of the cytokine interleukin-2, perhaps coupled with checkpoint inhibitors, should be further evaluated in the modern era.
Economic cost analysis of door‐to‐door community‐based distribution of HIV self‐test kits in Malawi, Zambia and Zimbabwe

HIV self‐testing (HIVST) is recommended by the World Health Organization in addition to other testing modalities to increase uptake of HIV testing, particularly among harder‐to‐reach populations. This study provides the first empirical evidence of the costs of door‐to‐door community‐based HIVST distribution in Malawi, Zambia and Zimbabwe.
Robust Adversarial Learning via Sparsifying Front Ends.

It is by now well-known that small adversarial perturbations can induce classification errors in deep neural networks. In this paper, we take a bottom-up signal processing perspective to this problem and show that a systematic exploitation of sparsity in natural data is a promising tool for defense. For linear classifiers, we show that a sparsifying front end is provably effective against $\ell_{\infty}$-bounded attacks, reducing output distortion due to the attack by a factor of roughly $K/N$ where $N$ is the data dimension and $K$ is the sparsity level. We then extend this concept to deep networks, showing that a "locally linear" model can be used to develop a theoretical foundation for crafting attacks and defenses. We also devise attacks based on the locally linear model that outperform the well-known FGSM attack. We supplement our theoretical results with experiments on the MNIST handwritten digit database, showing the efficacy of the proposed sparsity-based defense schemes.
The quantum Frobenius for character varieties and multiplicative quiver varieties

We prove that quantized multiplicative quiver varieties and quantum character varieties define sheaves of Azumaya algebras over the corresponding classical moduli spaces, and we prove that the Azumaya locus of the Kauffman bracket skein algebras contains the smooth locus, proving a strong form of the Unicity Conjecture of Bonahon and Wong. The proofs exploit a strong compatibility between quantum Hamiltonian reduction and the quantum Frobenius homomorphism as it arises in each setting. We therefore introduce the concepts of Frobenius quantum moment maps and their Hamiltonian reduction, and of Frobenius Poisson orders. We use these tools to construct canonical central subalgebras of quantum algebras, and explicitly compute the resulting Azumaya loci we encounter, using a natural nondegeneracy assumption.
Temporal Transferability of Pine Forest Attributes Modeling Using Low-Density Airborne Laser Scanning Data

This study assesses model temporal transferability using airborne laser scanning (ALS) data acquired over two different dates. Seven forest attributes (i.e. stand density, basal area, squared mean diameter, dominant diameter, tree dominant height, timber volume, and total tree biomass) were estimated using an area-based approach in Mediterranean Aleppo pine forests. Low-density ALS data were acquired in 2011 and 2016 while 147 forest inventory plots were measured in 2013, 2014, and 2016. Single-tree growth models were used to generate concomitant field data for 2011 and 2016. A comparison of five selection techniques and five regression methods were performed to regress field observations against ALS metrics. The selection of the best regression models fitted for each stand attribute, and separately for both 2011 and 2016, was performed following an indirect approach. Model performance and temporal transferability were analyzed by extrapolating the best fitted models from 2011 to 2016 and inversely from 2016 to 2011 using the direct approach. Non-parametric support vector machine with radial kernel was the best regression method with average relative % root mean square error differences of 2.13% for 2011 models and 1.58% for 2016 ones.
Wav2Pix: Speech-conditioned Face Generation Using Generative Adversarial Networks

Speech is a rich biometric signal that contains information about the identity, gender and emotional state of the speaker. In this work, we explore its potential to generate face images of a speaker by conditioning a Generative Adversarial Network (GAN) with raw speech input. We propose a deep neural network that is trained from scratch in an end-to-end fashion, generating a face directly from the raw speech waveform without any additional identity information (e.g reference image or one-hot encoding). Our model is trained in a self-supervised approach by exploiting the audio and visual signals naturally aligned in videos. With the purpose of training from video data, we present a novel dataset collected for this work, with high-quality videos of youtubers with notable expressiveness in both the speech and visual signals.
Learning Pose Estimation for High-Precision Robotic Assembly Using Simulated Depth Images

Most of industrial robotic assembly tasks today require fixed initial conditions for successful assembly. These constraints induce high production costs and low adaptability to new tasks. In this work we aim towards flexible and adaptable robotic assembly by using 3D CAD models for all parts to be assembled. We focus on a generic assembly task - the Siemens Innovation Challenge - in which a robot needs to assemble a gear-like mechanism with high precision into an operating system. To obtain the millimeter-accuracy required for this task and industrial settings alike, we use a depth camera mounted near the robot’s end-effector. We present a high-accuracy two-stage pose estimation procedure based on deep convolutional neural networks, which includes detection, pose estimation, refinement, and handling of near- and full symmetries of parts. The networks are trained on simulated depth images with means to ensure successful transfer to the real robot. We obtain an average pose estimation error of 2.16 millimeters and 0.64 degree leading to 91% success rate for robotic assembly of randomly distributed parts. To the best of our knowledge, this is the first time that the Siemens Innovation Challenge is fully addressed, with all the parts assembled with high success rates.
Topological supercurrents interaction and fluctuations in the multiterminal Josephson effect

We study Josephson effect in the multiterminal junction of topological superconductors. We use symmetry-constrained scattering matrix approach to derive band dispersions of emergent sub-gap Andreev bound states in a multidimensional parameter space of superconducting phase differences. We find distinct topologically protected band crossings that serve as monopoles of finite Berry curvature. Particularly, in a four-terminal junction the admixture of $2\pi$ and $4\pi$ periodic levels leads to an appearance of a finite energy Majorana-Weyl nodes. This topological regime in the junction can be characterized by a quantized nonlocal conductance that measures the Chern number of the corresponding bands. In addition, we calculate current-phase relations, variance, and cross-correlations of topological supercurrents in multiterminal contacts and discuss universality of these transport characteristics. At the technical level these results are obtained by integrating over the group of a circular ensemble that describes the scattering matrix of the junction. We briefly discuss our results in the context of observed fluctuations of the gate dependence of critical current in topological planar Josephson junctions and comment on the possibility of parity measurements from the switching current distributions in multiterminal Majorana junctions.
A Study on the Correlation Between Characteristics of BOD and Corporate Value

This paper takes the listed companies in China as the samples, describes the correlation between the characteristics of BOD (board of directors) companies’ value employing correlation analysis and regression analysis method. Empirical results demonstrates that there is a high negative correlation between board size and company value, and also there is a high negative correlation between board meeting frequency and company performance. Besides, the dual role of board chair and CEO could increase firm performance of target business.
Looking for ancillary signals around GW150914

We replicated the procedure in Liu and Jackson [1], who had found evidence for a low amplitude signal in the vicinity of GW150914. This was based upon the large correlation between the time integral of the Pearson cross-correlation coefficient in the off-source region of GW150914, and the Pearson cross-correlation in a narrow window around GW150914, for the same time lag between the two LIGO detectors as the gravitational wave signal. Our results mostly agree with those in Liu and Jackson [2]. We find the statistical significance of the observed cross-correlation to be about 2.5 σ. We also used the cross-correlation method to search for short duration signals at all other physical values of the time lag, within this 4096 second time interval, but do not find evidence for any statistically significant events in the off-source region.
Mode matching in GANs through latent space learning and inversion

Generative adversarial networks (GANs) have shown remarkable success in generation of unstructured data, such as, natural images. However, discovery and separation of modes in the generated space, essential for several tasks beyond naive data generation, is still a challenge. In this paper, we address the problem of imposing desired modal properties on the generated space using a latent distribution, engineered in accordance with the modal properties of the true data distribution. This is achieved by training a latent space inversion network in tandem with the generative network using a divergence loss. The latent space is made to follow a continuous multimodal distribution generated by reparameterization of a pair of continuous and discrete random variables. In addition, the modal priors of the latent distribution are learned to match with the true data distribution using minimal-supervision with negligible increment in number of learnable parameters. We validate our method on multiple tasks such as mode separation, conditional generation, and attribute discovery on multiple real world image datasets and demonstrate its efficacy over other state-of-the-art methods.
Elevated Muscle Sympathetic Nerve Activity Contributes to Central Artery Stiffness in Young and Middle-Age/Older Adults

Muscle sympathetic nerve activity (MSNA) influences the mechanical properties (ie, vascular smooth muscle tone and stiffness) of peripheral arteries, but it remains controversial whether MSNA contributes to stiffness of central arteries, such as the aorta and carotids. We examined whether elevated MSNA (age-related) would be independently associated with greater stiffness of central (carotid-femoral pulse wave velocity [PWV]) and peripheral (carotid-brachial PWV) arteries, in addition to lower carotid compliance coefficient, in healthy men and women (n=88, age: 19–73 years, 52% men). We also examined whether acute elevations in MSNA without increases in mean arterial pressure using graded levels of lower body negative pressure would augment central and peripheral artery stiffness in young (n=15, 60% men) and middle-age/older (MA/O, n=14, 43% men) adults. Resting MSNA burst frequency (bursts·min−1) was significantly correlated with carotid-femoral PWV (R=0.44, P<0.001), carotid-brachial PWV (R=0.32, P=0.004), and carotid compliance coefficient (R=0.28, P=0.01) after controlling for sex, mean arterial pressure, heart rate, and waist-to-hip ratio (central obesity), but these correlations were abolished after further controlling for age (all P>0.05). In young and MA/O adults, MSNA was elevated during lower body negative pressure (P<0.001) and produced significant increases in carotid-femoral PWV (young: &Dgr;+1.3±0.3 versus MA/O: &Dgr;+1.0±0.3 m·s−1, P=0.53) and carotid-brachial PWV (young: &Dgr;+0.7±0.3 versus MA/O: &Dgr;+0.7±0.5 m·s−1, P=0.92), whereas carotid compliance coefficient during lower body negative pressure was significantly reduced in young but not MA/O (young: &Dgr;−0.04±0.01 versus MA/O: &Dgr;0.001±0.008 mm2·mm Hg−1, P<0.01). Collectively, these data demonstrate the influence of MSNA on central artery stiffness and its potential contribution to age-related increases in stiffness of both peripheral and central arteries.
Multi-point correlations for two dimensional coalescing random walks

This paper considers an inﬁnite system of instantaneously coalescing rate one simple random walks on Z 2 , started from the initial condition with all sites in Z 2 occupied. Two-dimensional coalescing random walks are a ‘critical’ model of interacting particle systems: unlike coalescence models in dimensions three or higher, the ﬂuctuation eﬀects are important for the description of large-time statistics in two dimensions, manifesting themselves through the logarithmic corrections to the ‘mean ﬁeld’ answers. Yet the ﬂuctuation eﬀects are not as strong as for the one-dimensional coalescence, in which case the ﬂuctuation eﬀects modify the large time statistics at the leading order . Unfortunately, unlike its one-dimensional counterpart, the two-dimensional model is not exactly solvable, which explains a relative scarcity of rigorous analytic answers for the statistics of ﬂuctuations at large times. This paper’s contribution is to show that the correlation functions of the model decay, for any N ≥ 2, as as t → ∞ . This generalises the results for N = 1 due to Bramson and Griﬀeath and conﬁrms a prediction in the physics literature for N > 1. An analogous statement holds for instantaneously annihilating random walks. The key tools are the known asymptotic ρ 1 ( t ) ∼ log t/πt due to Bramson and Griﬀeath, and the non-collision probability p NC ( t ), that no pair of a ﬁnite collection of N two dimensional simple random walks meets by time t , whose asymptotic p NC ( t ∼ t ) − ( N 2 ) was found by Cox, Merle and Perkins. This paper re-derives the asymptotics both for ρ 1 ( t ) and p NC ( t ) by proving that these quantities satisfy eﬀective rate equations , that is approximate diﬀerential equations at large times. This approach can be regarded as a generalisation of the Smoluchowski theory of renormalised rate equations to multi-point statistics.
Probabilistic sensitivity of Nash equilibria in multi-agent games: a wait-and-judge approach

Motivated by electric vehicle charging control problems, we consider multi-agent noncooperative games where, following a data driven paradigm, unmodelled externalities acting on the players’ objective functions are represented by means of scenarios. Overcoming the nondifferentiability characterizing such a setup, we retrieve a Nash equilibrium in a decentralised manner. Then, building upon recent developments in scenario-based optimization, we accompany the given solution with an a posteriori probabilistic robustness certificate, providing confidence that the computed equilibrium remains unaffected by an "unseen" uncertainty realisation. The latter constitutes, to the best of our knowledge, the first application of the so-called scenario approach to multi-agent Nash equilibrium problems. The efficacy of our approach is demonstrated in simulation for the charging coordination of an electric vehicle fleet.