Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Content-Based Sparse Attention with Routing Transformers

Self-attention has recently been adopted for a wide range of sequence modeling problems. Despite its effectiveness, self-attention suffers from quadratic computation and memory requirements with respect to sequence length. Successful approaches to reduce this complexity focused on attending to local sliding windows or a small set of locations independent of content. Our work proposes to learn dynamic sparse attention patterns that avoid allocating computation and memory to attend to content unrelated to the query of interest. This work builds upon two lines of research: It combines the modeling flexibility of prior work on content-based sparse attention with the efficiency gains from approaches based on local, temporal sparse attention. Our model, the Routing Transformer, endows self-attention with a sparse routing module based on online k-means while reducing the overall complexity of attention to O(n1.5d) from O(n2d) for sequence length n and hidden dimension d. We show that our model outperforms comparable sparse attention models on language modeling on Wikitext-103 (15.8 vs 18.3 perplexity), as well as on image generation on ImageNet-64 (3.43 vs 3.44 bits/dim) while using fewer self-attention layers. Additionally, we set a new state-of-the-art on the newly released PG-19 data-set, obtaining a test perplexity of 33.2 with a 22 layer Routing Transformer model trained on sequences of length 8192. We open-source the code for Routing Transformer in Tensorflow.1
Emergent 
QCD3
 quantum phase transitions of fractional Chern insulators

Motivated by the recent work of QED$_3$-Chern-Simons quantum critical points of fractional Chern insulators (Phys. Rev. X \textbf{8}, 031015, (2018)), we study its non-Abelian generalizations, namely QCD$_3$-Chern-Simons quantum phase transitions of fractional Chern insulators. These phase transitions are described by Dirac fermions interacting with non-Abelian Chern-Simons gauge fields ($U(N)$, $SU(N)$, $USp(N)$, etc.). Utilizing the level-rank duality of Chern-Simons gauge theory and non-Abelian parton constructions, we discuss two types of QCD$_3$ quantum phase transitions. The first type happens between two Abelian states in different Jain sequences, as opposed to the QED3 transitions between Abelian states in the same Jain sequence. A good example is the transition between $\sigma^{xy}=1/3$ state and $\sigma^{xy}=-1$ state, which has $N_f=2$ Dirac fermions interacting with a $U(2)$ Chern-Simons gauge field. The second type is naturally involving non-Abelian states. For the sake of experimental feasibility, we focus on transitions of Pfaffian-like states, including the Moore-Read Pfaffian, anti-Pfaffian, particle-hole Pfaffian, etc. These quantum phase transitions could be realized in experimental systems such as fractional Chern insulators in graphene heterostructures.
BIHL: A Fast and High Performance Object Proposals based on Binarized HL Frequency

In recent years, the use of object proposal as a preprocessing step for target detection to improve computational efﬁciency has become an effective method. Good object proposal methods should have high object detection recall rate and low computational cost, as well as good location accuracy and repeatability. However, it is difﬁcult for current advanced algorithms to achieve a good balance in the above performance. Therefore, it is especially important to ensure that the recall rate and location quality are not degraded while accelerating object generation.For this problem, we propose a class-independent object proposal algorithm BIHL. It combines the advantages of window scoring and superpixel merging. First, a binarized horizontal high frequency component feature and a linear classiﬁer are used to learn and generate a set of candidate boxs with a objective score. Then, the candidate boxs are merged based on the principle of location and score proximity. Different from superpixel merging algorithm, our method does not use pixel level operation to avoid a lot of computation without losing performance. Experimental results on the VOC2007 dataset and the VOC2007 synthetic interference dataset containing 297,120 test images show that when including difﬁcult-to-identify objects with an IOU threshold of 0.5 and 10000 budget proposals, our method achieves a 99.3 % detection recall and an mean average best overlap of 81.1 % . The average processing time of our method for all test
Taylor Expansion Policy Optimization

In this work, we investigate the application of Taylor expansions in reinforcement learning. In particular, we propose Taylor expansion policy optimization, a policy optimization formalism that generalizes prior work (e.g., TRPO) as a first-order special case. We also show that Taylor expansions intimately relate to off-policy evaluation. Finally, we show that this new formulation entails modifications which improve the performance of several state-of-the-art distributed algorithms.
A Power-Efficient Binary-Weight Spiking Neural Network Architecture for Real-Time Object Classification

Neural network hardware is considered an essential part of future edge devices. In this paper, we propose a binary-weight spiking neural network (BW-SNN) hardware architecture for low-power real-time object classification on edge platforms. This design stores a full neural network on-chip, and hence requires no off-chip bandwidth. The proposed systolic array maximizes data reuse for a typical convolutional layer. A 5-layer convolutional BW-SNN hardware is implemented in 90nm CMOS. Compared with state-of-the-art designs, the area cost and energy per classification are reduced by 7$\times$ and 23$\times$, respectively, while also achieving a higher accuracy on the MNIST benchmark. This is also a pioneering SNN hardware architecture that supports advanced CNN architectures.
Going beyond the one-off: How can STEM engagement programmes with young people have real lasting impact?

<p>A major focus in the STEM public engagement sector concerns engaging with young people, typically through schools. The aims of these interventions are often to positively affect students&#8217; aspirations towards continuing STEM education and ultimately into STEM-related careers. Most schools engagement activities take the form of short one-off interventions that, while able to achieve positive outcomes, are limited in the extent to which they can have lasting impacts on aspirations. We review various different emerging programmes of repeated interventions with young people, assessing what impacts can realistically be expected. Short series of interventions appear also to suffer some limitations in the types of impacts achievable. However, deeper programmes that interact with both young people and those that influence them over significant periods of time (months to years) seem to be more effective in influencing aspirations. We discuss how developing a Theory of Change and considering young people&#8217;s wider learning ecologies are required in enabling lasting impacts in a range of areas. </p>
Kinetics of random sequential adsorption of two-dimensional shapes on a one-dimensional line.

Saturated random sequential adsorption packings built of two-dimensional ellipses, spherocylinders, rectangles, and dimers placed on a one-dimensional line are studied to check analytical prediction concerning packing growth kinetics [A. Baule, Phys. Rev. Lett. 119, 028003 (2017)PRLTAO0031-900710.1103/PhysRevLett.119. 028003]. The results show that the kinetics is governed by the power law with the exponent d=1.5 and 2.0 for packings built of ellipses and rectangles, respectively, which is consistent with analytical predictions. However, for spherocylinders and dimers of moderate width-to-height ratio, a transition between these two values is observed. We argue that this transition is a finite-size effect that arises for spherocylinders due to the properties of the contact function. In general, it appears that the kinetics of packing growth can depend on packing size even for very large packings.
W2S: A Joint Denoising and Super-Resolution Dataset

Denoising and super-resolution (SR) are fundamental tasks in imaging. These two restoration tasks are well covered in the literature, however, only separately. Given a noisy low-resolution (LR) input image, it is yet unclear what the best approach would be in order to obtain a noise-free high-resolution (HR) image. In order to study joint denoising and super-resolution (JDSR), a dataset containing pairs of noisy LR images and the corresponding HR images is fundamental. We propose such a novel JDSR dataset, Wieldfield2SIM (W2S), acquired using microscopy equipment and techniques. W2S is comprised of 144,000 real fluorescence microscopy images, used to form a total of 360 sets of images. A set is comprised of noisy LR images with different noise levels, a noise-free LR image, and a corresponding high-quality HR image. W2S allows us to benchmark the combinations of 6 denoising methods and 6 SR methods. We show that state-of-the-art SR networks perform very poorly on noisy inputs, with a loss reaching 14dB relative to noise-free inputs. Our evaluation also shows that applying the best denoiser in terms of reconstruction error followed by the best SR method does not yield the best result. The best denoising PSNR can, for instance, come at the expense of a loss in high frequencies, which is detrimental for SR methods. We lastly demonstrate that a light-weight SR network with a novel texture loss, trained specifically for JDSR, outperforms any combination of state-of-the-art deep denoising and SR networks.
Submetrizability of strongly topological gyrogroups

Topological gyrogroups, with a weaker algebraic structure without associative law, have been investigated recently. We prove that each $T_{0}$-strongly topological gyrogroup is completely regular. We also prove that every $T_{0}$-strongly topological gyrogroup with a countable pseudocharacter is submetrizable. Finally, we prove that the left coset space $G/H$ is submetrizable if $H$ is an admissible $L$-subgyrogroup of a $T_{0}$-strongly topological gyrogroup $G$.
Core-corona effect in hadron collisions and muon production in air showers

It is very well known that the fraction of energy in a hadron collision going into electromagnetic particles (electrons and photons, including those from decays) has a large impact on the number of muons produced in air shower cascades. Recent measurements at the LHC confirm features that can be linked to a mixture of different underlying particle production mechanisms such as a collective statistical hadronization (core) in addition to the expected string fragmentation (corona). Since the two mechanisms have a different electromagnetic energy fraction, we present a possible connection between statistical hadronization in hadron collisions and muon production in air showers. Using a novel approach, we demonstrate that the core-corona effect as observed at the LHC could be part of the solution for the lack of muon production in simulations of high energy cosmic rays. To probe this hypothesis, we study hadronization in high energy hadron collisions using calorimetric information over a large range of pseudorapidity in combination with the multiplicity of central tracks. As an experimental observable, we propose the production of energy in electromagnetic particles versus hadrons, as a function of pseudorapidity and central charged particle multiplicity.
Infants Born to Mothers With a New Coronavirus (COVID-19)

A novel viral respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is responsible for an epidemic of the coronavirus disease 2019 (COVID-19) in cases in China and worldwide. Four full-term, singleton infants were born to pregnant women who tested positive for COVID-19 in the city of Wuhan, the capital of Hubei province, China, where the disease was first identified. Of the three infants, for who consent to be diagnostically tested was provided, none tested positive for the virus. None of the infants developed serious clinical symptoms such as fever, cough, diarrhea, or abnormal radiologic or hematologic evidence, and all four infants were alive at the time of hospital discharge. Two infants had rashes of unknown etiology at birth, and one had facial ulcerations. One infant had tachypnea and was supported by non-invasive mechanical ventilation for 3 days. One had rashes at birth but was discharged without parental consent for a diagnostic test. This case report describes the clinical course of four live born infants, born to pregnant women with the COVID-19 infection.
The effects of exergames on anxiety levels: A systematic review and meta‐analysis

There are currently many different approaches to performing exergames and there is still no consensus as to whether exergames are able to reduce anxiety levels, as well as whether exergames provide greater reductions on anxiety levels when added to traditional forms of clinical interventions. Therefore, the aim of the present systematic review and meta‐analysis was to access data from studies that evaluated the effects of exergames on anxiety levels in humans. PubMed, Scopus and Cochrane databases were searched up to 22 February 2019. Inclusion criteria were acute and chronic (short‐term and long‐term interventions) studies which evaluated the effects of exergames in anxiety levels as primary or secondary aim. Of the 1342 studies found, 17 and 10 were included in qualitative analyses and meta‐analyses, respectively. The within‐group analysis found that exergames (standardized mean difference [SMD]: −0.57 [95% Confidence interval (CI): −0.86 to −0.28], P < . 001) and usual care (SMD: −0.21 [95% CI: −0.34 to −0.08], P = .002) resulted in significant improvements on anxiety levels. However, the between‐group meta‐analysis on the effects of control interventions vs exergames (SMD: 0.02 [95% CI: −0.55 to 0.60], P = .939) found no significant difference between groups in anxiety levels reductions. There was also no significant difference (SMD: −0.04 [95% CI: −0.32 to 0.25], P = .805) between usual care vs exergames plus usual care interventions in anxiety levels reductions. Although exergames demonstrated within‐group improvements in anxiety levels across different clinical populations, it was not greater than the effects from non‐exercise interventions. Also, given the paucity of studies, small sample sizes, different research designs, and different population investigated, the existing evidence is insufficient to support the advantages of usual care supplemented by exergame intervention over usual care standalone in anxiety levels reduction.
Sex steroid hormones differentially regulate CYP2D in female wild-type and CYP2D6-humanized mice.

The CYP2D subfamily catalyses the metabolism of about 25% of prescribed drugs, including the majority of antidepressants and antipsychotics. At present, the mechanism of hepatic CYP2D regulation remains largely unknown. This study investigated the role of sex steroid hormones in CYP2D regulation. For this purpose, Cyp2d22 expression was assessed in the distinct phases of the estrous cycle of normocyclic C57BL/6J (WT) female mice. Cyp2d22 was also evaluated in ovariectomised WT and CYP2D6-humanized (hCYP2D6) mice that received hormonal supplementation with either 17β-estradiol (E2) and/or progesterone. Comparisons were also made to male mice. The data revealed that hepatic Cyp2d22 mRNA, protein and activity levels were higher at estrous compared to the other phases of the estrous cycle, and ovariectomy repressed Cyp2d22 expression in WT mice. Tamoxifen, an antiestrogenic compound, also repressed hepatic Cyp2d22 via activation of GH/STAT5b and PI3k/AKT signalling pathways. Both hormones prevented the ovariectomy-mediated Cyp2d22 repression. In case of progesterone, this may be mediated by inhibition of the PI3k/AKT/FOX01 pathway. Notably, Cyp2d22 mRNA levels in WT males were similar to those in ovariectomised mice, and were markedly lower compared to females at estrous, a differentiation potentially regulated by the GH/STAT5b pathway. Sex steroid hormone-related alterations in Cyp2d22 mRNA expression were highly correlated with Hnf1a mRNA. Interestingly, fluctuations in Cyp2d22 in hippocampus and cerebellum followed those in liver. In contrast to WT mice, ovariectomy induced hepatic CYP2D6 expression in hCYP2D6 mice, whereas E2 and/or P prevented this induction. Apparently, sex steroid hormones display a significant gender- and species-specific role in the regulation of CYP2D.
Improved prognostication of glioblastoma beyond molecular subtyping by transcriptional profiling of the tumor microenvironment

Glioblastoma (GBM), the most aggressive form of brain cancer, is characterized by a high level of molecular heterogeneity, and infiltration by various immune and stromal cell populations. Important advances have been made in deciphering the microenvironment of GBMs, but its association with existing molecular subtypes and its potential prognostic role remain elusive. We have investigated the abundance of infiltrating immune and stromal cells in silico, from gene expression profiles. Two cohorts, including in‐house normal brain and glioma samples (n = 70) and a large sample set from TCGA (n = 393), were combined into a single exploratory dataset. A third independent cohort (n = 124) was used for validation. Tumors were clustered based on their microenvironment infiltration profiles, and associations with known GBM molecular subtypes and patient outcome were tested a posteriori in a multivariable setting. We identified a subset of GBM samples with significantly higher abundances of most immune and stromal cell populations. This subset showed increased expression of both immune suppressor and immune effector genes compared to other GBMs and was enriched for the mesenchymal molecular subtype. Survival analyses suggested that tumor microenvironment infiltration pattern was an independent prognostic factor for GBM patients. Among all, patients with the mesenchymal subtype with low immune and stromal infiltration had the poorest survival. By combining molecular subtyping with gene expression measures of tumor infiltration, the present work contributes with improving prognostic models in GBM.
[Epidemiological characteristics of 2019 novel coronavirus family clustering in Zhejiang Province].

Objective: Family clusters of Novel coronavirus pneumonia in Zhejiang province were analyzed to provide epidemiological basis for disease control. Methods: The data of family clusters occurred from January 20 to February 10 in Zhejiang Province were collected. Descriptive analysis was used to analyze the clinical symptoms and the serial interval between the subsequent cases and the index cases. Chi-square test was used to analyze the age distribution, gender distribution and the relationship between the subsequent cases and the index cases. Results: 391 cases including 148 family index cases, 189 subsequent cases and 54 asymptomatic infected cases. The clinical symptoms between family index cases and subsequent cases are similar, fever is the most common symptoms in the two groups 114 (77.03%) and 92 (48.68%) respectively, the cases with diarrhea symptoms accounted for the least proportion, which were 7 (4.73%) and 5 (2.65%). The serial interval between the family index cases and the subsequent cases [M (P(25), P(75))] was 3.00 (1.00, 6.00) days. Family secondary attack rate for subsequent cases and asymptomatic infected cases are 31.61% and 43.20% respectively, the family secondary attack rate of the spouses of the family index cases is 63.87%, and are higher than that of their children (30.53%), parents (28.37%) and other family members (20.93%), the difference was statistically significant. Conclusion: 2019 novel coronavirus has shorter serial interval and higher family secondary attack rate, the secondary attack rate of spouses is higher than other family members.
‘Inverse association between the total naevus count and melanoma thickness’

Individuals with a high total naevus count (TNC) are at a higher risk to develop melanoma, and screening efforts have been largely focused on this group. However, some studies suggest that melanomas of patients with many nevi are thinner than those of patients with few nevi. Additionally, nodular melanoma has been associated with individuals with a low naevus count.
[Impact of complicated myocardial injury on the clinical outcome of severe or critically ill COVID-19 patients].

Objective: To analyze the clinical characteristics of the severe or critically ill patients with novel coronavirus pneumonia (COVID-19), and evaluate the impact of complicated myocardial injury on the prognosis of these patients. Methods: A retrospective study was conducted in 54 patients who admitted to Tongji hospital from February 3, 2020 to February 24, 2020 and met the criteria of severe or critical conditions of COVID-19. The clinical characteristics and hospital mortality rate were analyzed and compared between the patients with or without myocardial injury, which was defined with 3 times higher serum cardiac troponin value. Results: The median age of the 54 patients was 68 (59.8, 74.3) years. Among all the patients, 24 (44.4%) patients were complicated with hypertension, 13 (24.1%) with diabetes, 8 (14.8%) with coronary heart disease, and 3 (5.6%) with previous cerebral infarction. During hospitalization, 24 (44.4%) of the patients were complicated with myocardial injury and 26 (48.1%) patients died in hospital. In-hospital mortality was significantly higher in patients with myocardial injury than in patients without myocardial injury (14 (60.9%) vs. 8 (25.8%), P=0.013). Moreover, the levels of C-reactive protein (153.6 (80.3, 240.7) ng/L vs. 49.8 (15.9, 101.9) ng/L) and N-terminal pro-B-type natriuretic peptide (852.0 (400.0, 2 315.3) ng/L vs. 197.0 (115.3, 631.0) ng/L) were significantly higher than patients without myocardial injury (all P<0.01). Conclusions: Prevalence of myocardial injury is high among severe or critically ill COVID-19 patients. Severe or critically ill COVID-19 patients with myocardial injury face a significantly higher risk of in-hospital mortality. The study suggests that it is important to monitor and manage the myocardial injury during hospitalization for severe or critically ill COVID-19 patients.
Germline variation in NFE2L2/CUL3/KEAP1 and risk of head and neck squamous cell carcinoma (HNSCC).

1540 Background: Nuclear factor (erythroid-derived 2)-like 2 (NFE2L2) is a key transcription factor regulating oxidative stress. Activated NFE2L2 translocates to the nucleus and binds anti-oxidant response elements in the promoter regions of cytoprotective genes. It is negatively regulated by its protein complex partners, CUL3 and KEAP1. Recent HNSCC genome profiling studies identified NFE2L2, CUL3 and KEAP1 as recurrent somatically altered genes, suggesting an important role in HNSCC carcinogenesis. We hypothesized that germline variation in NFE2L2, CUL3 and KEAP1affects risk of HNSCC. Methods: The study population consisted of 751 cases (459 oral cavity, 292 oropharynx; 69% smoker) and 862 controls (50% smoker) from the University of Pittsburgh HNSCC case-control study. Subjects were genotyped for 22 single nucleotide polymorphisms (SNPs) located in or near NFE2L2 (10), CUL3 (8) and KEAP1(4) using Sequenom’s iPLEX assay. Odds ratios (OR) for HNSCC risk and corresponding 95% confidence intervals (CI) wer.