Miracle-dz/UniFAR-FTUs huggingface dataset:
Ground truth free retinal vessel segmentation by learning from simple pixels

Retinal vessel segmentation is fundamental for the automatic retinal image analysis and ocular disease screening. This paper aims to learn a ground truth free feature aggregation strategy for the vessel segmentation. Five vesselness maps modelling the vessels’proﬁle, appearance, and shape are ﬁrst generated. Together, the histogram of the local binary pattern and the green colour are extracted. In each vesselness map, the pixels with large vesselness values are regarded as simple positive samples. The pixels with small vesselness values are regarded as simple negative samples, and the pixels with mediocre values are treated as difﬁcult pixels. The simple positive samples and simple negative samples near the difﬁcult pixels consist of the training dataset while the rest vesselness maps together with the local binary pattern histogram, and green colour channel are used as the features to learn a strong classiﬁer. Then, without leveraging any ground truth, multiple kernel boosting is used to combine four support vector machine kernels to learn a strong vessel model for each image. Applying this learnt model to the pixels with mediocre values in the single vesselness map, their label will be determined. Totally, ﬁve strong vessel models are learnt. Finally, pixels with the majority supports from the strong vessel models are labelled as vessel pixels. The proposed method achieves accuracy of 94.83%, sensitivity of 72.59%, and speciﬁcity of 98.11% on DRIVE dataset, and accuracy of 95.51%, sensitivity of 78.09%, and speciﬁcity of 97.56% on STARE. It outperforms the state-of-the-art unsupervised methods and achieves comparable performances to the supervised methods.
Experimental constraints on nonskeletal CaCO3 precipitation from Proterozoic seawater

Precambrian carbonates record secular variations in the style of CaCO3 nucleation and growth, yet the geochemical conditions recorded by some enigmatic textures remain poorly quantified. Here, we performed CaCO3 nucleation experiments in synthetic seawater in order to constrain the mineralization pathways of synsedimentary calcite microspar cement, a prolific component of Proterozoic carbonates. We found that dissolved PO4 above ∼12 μmol/L (µM) inhibits the nucleation of aragonite and calcite and permits the formation of an amorphous Ca-Mg carbonate (ACMC) precursor once CaCO3 supersaturation (Ωcal) is ≥ 45. Depending on seawater Mg/Ca, ACMC then rapidly recrystallizes to monohydrocalcite and/or calcite. This precipitation mechanism is consistent with sedimentological, petrographic, and geochemical characteristics of Proterozoic synsedimentary calcite microspar cement, and it suggests that kinetic interactions among common seawater ions may open nontraditional CaCO3 mineralization pathways and sustain high CaCO3 supersaturation.
Cerebrovascular Response to an Acute Bout of Short Interval High Intensity Interval Exercise and Recovery in Healthy Adults

Introduction: High intensity interval exercise (HIIE) is performed widely. However, the field possesses limited knowledge regarding the acute HIIE cerebrovascular response. Our objective was to characterize the middle cerebral artery blood velocity (MCAv) response during an acute bout of short interval HIIE in healthy adults. We hypothesized MCAv would decrease below BL 1) during HIIE, 2) following HIIE, 3) and 30-minutes after HIIE. As a secondary objective, we investigated sex differences in the MCAv response during HIIE. Methods: Fourteen healthy adults (7 male) completed the HIIE session. The 10-minute HIIE session included alternating 1-minute bouts of high-intensity and low-intensity intervals. MCAv, mean arterial pressure (MAP), heart rate (HR), and expired end tidal carbon dioxide (PETCO2), were recorded at BL, during HIIE, following HIIE, and 30-minutes after HIIE. Results: Contrary to our hypothesis, MCAv remained above BL for the HIIE duration. MCAv peaked at the third minute then decreased concomitantly with PETCO2. MCAv was lower than BL after HIIE (p=0.03). Thirty minutes after HIIE, MCAv returned to near BL values (p = 0.47). Women showed higher BL MCAv (x = 70.9 {+/-} 8.1 cm/s) compared to men (x = 59.3 {+/-} 5.8 cm/s, p = 0.01). A greater magnitude of MCAv response was observed in men resulting in non-significant differences during HIIE secondary to higher workload (p = 0.03). Conclusions: Collectively, these findings show that in healthy adults, MCAv remained above BL during a 10-minute short-interval HIIE and returned to resting values 30 minutes after exercise.
Making Cross-Domain Recommendations by Associating Disjoint Users and Items Through the Affective Aware Pseudo Association Method

This paper utilizes an ingenious text-based affective aware pseudo association method (AAPAM) to link disjoint pseudo users and items across different information domains and leverage them to make cross-domain content-based and collaborative filtering recommendations. This paper demonstrates that the AAPAM method could seamlessly join different information domain datasets to act as one without any additional cross-domain information retrieval protocols. Besides making cross-domain recommendations, the benefit of joining datasets from different information domains through AAPAM is that it eradicates cold start issues while making serendipitous recommendations.
Turbulent kinetic energy in 2D isothermal interchange-dominated scrape-off layer E × B drift turbulence: Governing equation and relation to particle transport

This paper studies the turbulent kinetic energy ( k ⊥) in 2D isothermal electrostatic interchange-dominated E × B drift turbulence in the scrape-off layer and its relation to particle transport. An evolution equation for the former is analytically derived from the underlying turbulence equations. Evaluating this equation shows that the dominant source for the turbulent kinetic energy is due to interchange drive, while the parallel current loss to the sheath constitutes the main sink. Perpendicular transport of the turbulent kinetic energy seems to play a minor role in the balance equation. Reynolds stress energy transfer also seems to be negligible, presumably because no significant shear flow develops under the given assumptions of isothermal sheath-limited conditions in the open field line region. The interchange source of the turbulence is analytically related to the average turbulent E × B energy flux, while a regression analysis of TOKAM2D data suggests a model that is linear in the turbulent kinetic energy for the sheath loss. A similar regression analysis yields a diffusive model for the average radial particle flux, in which the anomalous diffusion coefficient scales with the square root of the turbulent kinetic energy. Combining these three components, a closed set of equations for the mean-field particle transport is obtained, in which the source of the turbulence depends on mean flow gradients and k ⊥ through the particle flux, while the turbulence is saturated by parallel losses to the sheath. Implementation of this new model in a 1D mean-field code shows good agreement with the original TOKAM2D data over a range of model parameters.
Wireless Power Transfer via Topological Modes in Dimer Chains

Topological characteristics, including invariant topological orders, band inversion, and the topological edge mode (TEM) in photonic insulators, have been widely studied. Whether intriguing topological modes can be taken advantage of in simple one-dimensional systems to implement some practical applications is an issue, which is of increasing concern. In this work, based on a photonic dimer chain composed of ultrasubwavelength resonators, we verify experimentally that the TEM in the effective second-order parity-time (PT) system is immune to the inner disorder perturbation, and can be used to realize the long-range wireless power transfer (WPT) with high transmission efficiency. To intuitively show the TEM can be used for WPT, a power signal source is used to excite the TEM. It can be clearly seen that two light-emitting diode (LED) lamps with 0.5 W at both ends of the structure are lit up with the aid of TEMs. In addition, in order to solve the special technical problems of standby power loss and frequency tracking, we further propose that a WPT system with effective third-order PT symmetry can be constructed by using one topological interface mode and two TEMs. Inspired by the long-range WPT with TEMs in this work, the use of more complex topological structures is expected to achieve energy transmission with more functions, such as the WPT devices whose direction can be selected flexibly in the quasiperiodic or trimer topological chains.
On Distributed Nonconvex Optimization: Projected Subgradient Method for Weakly Convex Problems in Networks

The stochastic subgradient method is a widely used algorithm for solving large-scale optimization problems arising in machine learning. Often, these problems are neither smooth nor convex. Recently, Davis et al., 2018 characterized the convergence of the stochastic subgradient method for the weakly convex case, which encompasses many important applications (e.g., robust phase retrieval, blind deconvolution, biconvex compressive sensing, and dictionary learning). In practice, distributed implementations of the projected stochastic subgradient method (stoDPSM) are used to speed up risk minimization. In this article, we propose a distributed implementation of the stochastic subgradient method with a theoretical guarantee. Specifically, we show the global convergence of stoDPSM using the Moreau envelope stationarity measure. Furthermore, under a so-called sharpness condition, we show that deterministic DPSM (with a proper initialization) converges linearly to the sharp minima, using geometrically diminishing step size. We provide numerical experiments to support our theoretical analysis.
Density function analysis for a stochastic SEIS epidemic model with non-degenerate diffusion

In this paper, we construct a stochastic SEIS epidemic model that incorporates constant recruitment, non-degenerate diffusion and infectious force in the latent period and infected period. By solving the corresponding Fokker-Planck equation, we obtain the exact expression of the density function around the endemic equilibrium of the deterministic system provided that the basic reproduction number is greater than one. Our work greatly improves the result of Chen [A new idea on density function and covariance matrix analysis of a stochastic SEIS epidemic model with degenerate diffusion, Appl. Math. Lett. , 2020, 106200].
Bursts before Burst: A Comparative Study on FRB 200428-associated and FRB-absent X-Ray Bursts from SGR J1935+2154

Accompanied by an X-ray burst, the fast radio burst (FRB) FRB 200428 was recently confirmed as originating from the Galactic magnetar soft gamma repeater (SGR) SGR J1935+2154. Just before and after FRB 200428 was detected, the Five-hundred-meter Aperture Spherical radio Telescope (FAST) had been monitoring SGR J1935+2154 for eight hours. From UTC 2020 April 27 23:55:00 to 2020 April 28 00:50:37, FAST detected no pulsed radio emission from SGR J1935+2154, while Fermi/Gamma-ray Burst Monitor registered 34 bursts in the X/soft γ-ray band, forming a unique sample of X-ray bursts in the absence of FRBs. After a comprehensive analysis on light curves, time-integrated, and time-resolved spectral properties of these FRB-absent X-ray bursts, we compare this sample with the FRB-associated X-ray burst detected by Insight-HXMT, INTEGRAL, and Konus-Wind. The FRB-associated burst distinguishes itself from other X-ray bursts by its nonthermal spectrum and a higher spectral peak energy, but otherwise is not atypical. We also compare the cumulative energy distribution of our X-ray burst sample with that of first repeating FRB source, FRB 121102, with the calibration of FRB 200428-X-ray burst association. We find a similarity between the two, offering indirect support of the magnetar origin of cosmological FRBs. The event rate density of magnetar bursts is about ∼150 times higher than the FRB event rate density at the energy of FRB 200428. This again suggests that, if all FRBs originate from magnetars, only a small fraction of X-ray bursts are associated with FRBs.
Development and Initial Validation of the Duke Misophonia Questionnaire

Misophonia is characterized by decreased tolerance and accompanying defensive motivational system responding to certain aversive sounds and contextual cues associated with such stimuli, typically repetitive oral (e. g., eating sounds) or nasal (e.g., breathing sounds) stimuli. Responses elicit significant psychological distress and impairment in functioning, and include acute increases in (a) negative affect (e.g., anger, anxiety, and disgust), (b) physiological arousal (e.g., sympathetic nervous system activation), and (c) overt behavior (e.g., escape behavior and verbal aggression toward individuals generating triggers). A major barrier to research and treatment of misophonia is the lack of rigorously validated assessment measures. As such, the primary purpose of this study was to develop and psychometrically validate a self-report measure of misophonia, the Duke Misophonia Questionnaire (DMQ). There were two phases of measure development. In Phase 1, items were generated and iteratively refined from a combination of the scientific literature and qualitative feedback from misophonia sufferers, their family members, and professional experts. In Phase 2, a large community sample of adults (n = 424) completed DMQ candidate items and other measures needed for psychometric analyses. A series of iterative analytic procedures (e.g., factor analyses and IRT) were used to derive final DMQ items and scales. The final DMQ has 86 items and includes subscales: (1) Trigger frequency (16 items), (2) Affective Responses (5 items), (3) Physiological Responses (8 items), (4) Cognitive Responses (10 items), (5) Coping Before (6 items), (6) Coping During (10 items), (7) Coping After (5 items), (8) Impairment (12 items), and Beliefs (14 items). Composite scales were derived for overall Symptom Severity (combined Affective, Physiological, and Cognitive subscales) and Coping (combined the three Coping subscales). Depending on the needs of researchers or clinicians, the DMQ may be use in full form, individual subscales, or with the derived composite scales.
Filling in Cosmic Microwave Background map missing regions via Generative Adversarial Networks

In this work, we propose a new method to fill in (or in-paint) the CMB signal in regions masked out following a point source extraction process. We adopt a modified Generative Adversarial Network (GAN) and compare different combinations of internal (hyper-)parameters and training strategies. We study the performance using a suitable 𝒞r variable in order to estimate the performance regarding the CMB power spectrum recovery. We consider a test set where one point source is masked out in each sky patch with a 1.83 × 1.83 squared degree extension, which, in our gridding, corresponds to 64 × 64 pixels. The GAN is optimized for estimating performance on Planck 2018 total intensity simulations. The training makes the GAN effective in reconstructing a masking corresponding to about 1500 pixels with 1% error down to angular scales corresponding to about 5 arcminutes. Finally, we show that GAN is able to mimic PDF and number density of peaks for both Gaussian and non-Gaussian data with less than 0.5% relative error.
ANTARES upper limits on the multi-TeV neutrino emission from the GRBs detected by IACTs

The first gamma-ray burst detections by Imaging Atmospheric Cherenkov Telescopes have been recently announced: GRB 190114C, detected by MAGIC, GRB 180720B and GRB 190829A, observed by H.E. S.S. A dedicated search for neutrinos in space and time coincidence with the gamma-ray emission observed by IACTs has been performed using ANTARES data. The search covers both the prompt and afterglow phases, yielding no neutrinos in coincidence with the three GRBs studied. Upper limits on the energetics of the neutrino emission are inferred. The resulting upper limits are several orders of magnitude above the observed gamma-ray emission, and they do not allow to constrain the available models.
Training data augmentation for deep learning radio frequency systems

Applications of machine learning are subject to three major components that contribute to the final performance metrics. Within the category of neural networks, and deep learning specifically, the first two are the architecture for the model being trained and the training approach used. This work focuses on the third component, the data used during training. The primary questions that arise are “what is in the data” and “what within the data matters? ” looking into the radio frequency machine learning (RFML) field of automatic modulation classification (AMC) as an example of a tool used for situational awareness, the use of synthetic, captured, and augmented data are examined and compared to provide insights about the quantity and quality of the available data necessary to achieve desired performance levels. Three questions are discussed within this work: (1) how useful a synthetically trained system is expected to be when deployed without considering the environment within the synthesis, (2) how can augmentation be leveraged within the RFML domain, and, lastly, (3) what impact knowledge of degradations to the signal caused by the transmission channel contributes to the performance of a system. In general, the examined data types each make useful contributions to a final application, but captured data germane to the intended use case will always provide more significant information and enable the greatest performance. Despite the benefit of captured data, the difficulties and costs that arise from live collection often make the quantity of data needed to achieve peak performance impractical. This paper helps quantify the balance between real and synthetic data, offering concrete examples where training data is parametrically varied in size and source.
Evaluating Load Balancing Performance in Distributed Storage With Redundancy

To facilitate load balancing, distributed systems store data redundantly. We evaluate the load balancing performance of storage schemes in which each object is stored at <inline-formula> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> different nodes, and each node stores the same number of objects. In our model, the load offered for the objects is sampled uniformly at random from all the load vectors with a fixed cumulative value. We find that the load balance in a system of <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> nodes improves multiplicatively with <inline-formula> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> as long as <inline-formula> <tex-math notation="LaTeX">${d} = {o}\left ({\log ({n})}\right)$ </tex-math></inline-formula>, and improves exponentially once <inline-formula> <tex-math notation="LaTeX">${d} = \Theta \left ({\log ({n})}\right)$ </tex-math></inline-formula>. We show that the load balance improves in the same way with <inline-formula> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> when the service choices are created with XOR’s of <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> objects rather than object replicas. In such redundancy schemes, storage overhead is reduced multiplicatively by <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula>. However, recovery of an object requires downloading content from <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> nodes. At the same time, the load balance increases additively by <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula>. We express the system’s load balance in terms of the maximal spacing or maximum of <inline-formula> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> consecutive spacings between the ordered statistics of uniform random variables. Using this connection and the limit results on the maximal <inline-formula> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula>-spacings, we derive our main results.
Does Personal Liability Deter Individuals from Serving as Independent Directors?

Abstract This study examines whether personal liability for corporate malfeasance deters individuals from serving as independent directors. After the introduction of personal liability in India, we find that individuals are deterred from serving on corporate boards. We find stronger deterrence among firms with greater litigation and regulatory risk, higher monitoring costs, and weak monetary incentives. Expert directors are more likely to exit, resulting in 1.16% lower firm value. We further evaluate whether contemporaneous corporate governance reforms and market developments contribute to this deterrence. Overall, our results suggest that personal liability deters individuals with high reputational costs from serving as independent directors.
Development of arabic sign language dictionary using 3D avatar technologies

The arabic sign language (ArSL) is the natural language of the deaf community in Arabic countries. ArSL suffers from a lack of resources such as unified dictionaries and corpora. In this work, a dictionary of Arabic language to ArSL has been constructed as a part of a translation system. The Arabic words are converted into hamburg notation system (HamNoSys) using eSign editor Software. HamNoSys was used to create manual parameters (handshape, hand orientation, hand location, and hand movement), while non-manual parameters (facial expressions, shoulder raising, mouthing gesture, head tilting, and body movement) added by using (mouth, face, and limbs) in the eSign editor software. The sign then converted to the sign gesture markup language (SiGML) file, and later 3D avatar interprets the SiGML file scripts to the animated sign. The constructed dictionary has three thousand signs; therefore, it can be adopted for the translation system in which written text can be transformed into sign language and can be utilized for the education of deaf people. The dictionary will be available as a free resource for researchers. It is hard and time-consuming work, but it is an essential step in machine translation of whole Arabic text to ArSL with 3D animations.
Sustainable data analysis with Snakemake

Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for a data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results.