Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing High-Performance MPI Libraries with On-the-fly Compression for Modern GPU Clusters*

While the memory bandwidth of accelerators such as GPU has significantly improved over the last decade, the commodity networks such as Ethernet and InfiniBand are lagging in terms of raw throughput creating. Although there are significant research efforts on improving the large message data transfers for GPU-resident data, the inter-node communication remains the major performance bottleneck due to the data explosion created by the emerging High-Performance Computing (HPC) applications. On the other hand, the recent developments in GPU-based compression algorithms exemplify the potential of using high-performance message compression techniques to reduce the volume of data transferred thereby reducing the load on an already overloaded inter-node communication fabric. The existing GPU-based compression schemes are not designed for “on-the-fly” execution and lead to severe performance degradation when integrated into the communication libraries. In this paper, we take up this challenge and redesign the MVAPICH2 MPI library to enable high-performance, on-the-fly message compression for modern, dense GPU clusters. We also enhance existing implementations of lossless and lossy compression algorithms, MPC and ZFP, to provide high-performance, on-the-fly message compression and decompression. We demonstrate that our proposed designs can offer significant benefits at the microbenchmark and application-levels. The proposed design is able to provide up to 19% and 37% improvement in the GPU computing flops of AWP-ODC with the enhanced MPCOPT and ZFP-OPT schemes, respectively. Moreover, we gain up to 1.56x improvement in Dask throughput. To the best of our knowledge, this is the first work that leverages the GPU-based compression techniques to significantly improve the GPU communication performance for various MPI primitives, MPI-based data science, and HPC applications.
“Vulnerable Funding in the Global Economy”

We study the international propagation of financial conditions from the United States to global financial markets. The impact is highly heterogeneous alongside the quantiles of the distribution of the two major funding sources, credit and equity. Indeed, it is greater on the lower quantiles, which means that analogous to vulnerable growth episodes, examined by the past literature, there exist as well vulnerable funding periods of a global scale, originated from financial weakness in the US. These episodes are related to downside risk in terms of credit creation and firms’ market value around the world. Our estimates differentiate between first and second moment (i.e. uncertainty) shocks to financial conditions. This distinction proves to be relevant as it uncovers a complex propagation of shocks via different economic channels. On the one hand, credit growth largely responds to first moment shocks of US financial conditions four quarters after their occurrence, which is consistent with a credit view explanation of the transmission. On the other hand, stock markets react more sensitively and rapidly (mainly within a quarter) to second moment shocks, which can be theoretically associated with a portfolio channel underlying the shocks spread. We also document a heterogeneous impact across countries. In the case of credit growth this heterogeneity is better explained by the size or depth of the markets, while in the case of stock markets, the explanation is rooted on the strength of the financial connectedness with the US. JEL classification: E44, F34, F37, F44, G15.
European Roller Coracias garrulus in the Pleistocene and Holocene of Croatia

Fossil remains of the European Roller Coracias garrulus in Croatia are relatively rare. The European Roller has been found at four sites situated along the Adriatic coast: Marlera I and Šandalja II in the northern Adriatic, and Vela Spila and Markova Spilja on the southern part. The oldest find is from Marlera I, which dates back to the Late Pleistocene (Marine Isotope Stage 3 MIS 3) and the youngest are the Holocene (MIS 1) finds at Vela Spila and Markova Spilja. Immature bones were found in Vela Spila deposits, indicating breeding during the Late Pleistocene in the southern Adriatic. So far, the European Roller has not been determined in deposits from continental Croatia.
Your “Flamingo” is My “Bird”: Fine-Grained, or Not

Whether what you see in Figure 1 is a "flamingo" or a "bird", is the question we ask in this paper. While fine-grained visual classification (FGVC) strives to arrive at the former, for the majority of us non-experts just "bird" would probably suffice. The real question is therefore – how can we tailor for different fine-grained definitions under divergent levels of expertise. For that, we re-envisage the traditional setting of FGVC, from single-label classification, to that of top-down traversal of a pre-defined coarse-to-fine label hierarchy – so that our answer becomes "bird" ⇒ "Phoenicopteriformes" ⇒ "Phoenicopteridae" ⇒ "flamingo". To approach this new problem, we first conduct a comprehensive human study where we confirm that most participants prefer multi-granularity labels, regardless whether they consider themselves experts. We then discover the key intuition that: coarse-level label prediction exacerbates fine-grained feature learning, yet fine-level feature betters the learning of coarse-level classifier. This discovery enables us to design a very simple albeit surprisingly effective solution to our new problem, where we (i) leverage level-specific classification heads to disentangle coarse-level features with fine-grained ones, and (ii) allow finer-grained features to participate in coarser-grained label predictions, which in turn helps with better disentanglement. Experiments show that our method achieves superior performance in the new FGVC setting, and performs better than state-of-the-art on the traditional single-label FGVC problem as well. Thanks to its simplicity, our method can be easily implemented on top of any existing FGVC frameworks and is parameter-free.
Running head: A COMPARATIVE ANALYSIS OF PATIENTS WITH CHEST PAIN 1 A Comparative Analysis of Patients with Chest Pain On and Off a Clinical Decision Unit

3 Background and Significance.4 Problem Statement.5 Needs Assessment.6 Objectives and Aims.7 Review of Literature.8 Theoretical Model.13 Methodology.14 Evaluation Plan.18 Findings.19 Recommendation and Discussion.31 References.35 Appendices.40 Evidence Table.44 A COMPARATIVE ANALYSIS OF PATIENTS WITH CHEST PAIN 3 Abstract Purpose: The purpose of this study was to compare the outcomes, specifically length of stay (LOS) for patients with chest pain referred to an outpatient observation clinical decision unit (CDU) co-managed with Nurse Practitioners with an open admission model of care, compared to patients with chest pain referred to outpatient observation services outside of the CDU. Observation medicine is a continuously evolving practice utilized to improve efficiency whilePurpose: The purpose of this study was to compare the outcomes, specifically length of stay (LOS) for patients with chest pain referred to an outpatient observation clinical decision unit (CDU) co-managed with Nurse Practitioners with an open admission model of care, compared to patients with chest pain referred to outpatient observation services outside of the CDU. Observation medicine is a continuously evolving practice utilized to improve efficiency while decreasing cost. A discharged inpatient that equates to an observation stay yet reimbursed at a higher inpatient rate creates opportunities for recoupment of payments and possible insurance claim denials. Patients with chest pain are a large portion of emergency department visits annually and frequently referred to outpatient observation units. Low-risk chest pain protocols were utilized to provide streamlined expedited care. Nurse Practitioners have an opportunity to decrease the length of stay and improve efficiency. Method: A randomized retrospective chart review was conducted of medical records of patients with chest pain referred to outpatient observation. A descriptive analysis compared patients with chest pain in an observation unit with nurse practitioners to patients with chest pain managed outside of the observation unit. The period was 1 September 2016 and end on 31 August 2017. A total of 128 patients discharged from observation care with a discharge diagnosis of chest pain were analyzed. Conclusions: Mean Length of Stay (LOS) was lower and statistically significant (P-value <0.05) for Clinical Decision Unit (CDU) which utilizes Nurse Practitioner services for managing patients with Chest pain compared to any outside unit. This lower LOS can significantly lower our Health care expenses.
The nanoscale topography of GluN2-NMDA receptor subtypes tunes plasticity at glutamatergic synapses

Univ. de Bordeaux, Interdisciplinary Institute for Neuroscience, UMR 5297, F-33000 Bordeaux, France CNRS, IINS UMR 5297, Bordeaux, France CNC Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504 Coimbra, Portugal Univ. de Bordeaux, Bordeaux Imaging Center, F-33000 Bordeaux, France CNRS, Bordeaux Imaging Center UMS 3420, F-33000 Bordeaux, France INSERM, Bordeaux Imaging Center US 04, F-33000 Bordeaux, France Institut d’Optique & CNRS, LP2N UMR 5298, F-33400 Talence, France Univ. Bordeaux, Laboratoire Photonique Numérique et Nanosciences (LP2N), UMR 5298, F-33400 Talence, France. UCL Institute of Neurology, University College London, London, UK Department of Life Sciences, Faculty of Sciences and Technology, University of Coimbra, 3004-517 Coimbra, Portugal
Lesion-Aware Transformers for Diabetic Retinopathy Grading

Diabetic retinopathy (DR) is the leading cause of permanent blindness in the working-age population. And automatic DR diagnosis can assist ophthalmologists to design tailored treatments for patients, including DR grading and lesion discovery. However, most of existing methods treat DR grading and lesion discovery as two independent tasks, which require lesion annotations as a learning guidance and limits the actual deployment. To alleviate this problem, we propose a novel lesion-aware transformer (LAT) for DR grading and lesion discovery jointly in a unified deep model via an encoder-decoder structure including a pixel relation based encoder and a lesion filter based decoder. The proposed LAT enjoys several merits. First, to the best of our knowledge, this is the first work to formulate lesion discovery as a weakly supervised lesion localization problem via a transformer decoder. Second, to learn lesion filters well with only image-level labels, we design two effective mechanisms including lesion region importance and lesion region diversity for identifying diverse lesion regions. Extensive experimental results on three challenging benchmarks including Messidor-1, Messidor-2 and EyePACS demonstrate that the proposed LAT performs favorably against state-of-the-art DR grading and lesion discovery methods.
UWS Academic Portal Effects of covid-19 lockdown on physical activity, sedentary behavior, and satisfaction with life in Qatar Hermassi,

This study examined the effects of home confinement on physical activity (PA) and life satisfaction during the COVID-19 outbreak in Qatar. A total of 1144 subjects participated (male: n = 588; female: n = 556; age: 33.1 ± 11.1 years; mass: 76.1 ± 16.4 kg; height: 1.70 ± 0.11 m; body mass index (BMI): 26.1 ± 4.44 kg/m2). Online survey questions considered “before” and “during” confinement. Confinement reduced all PA intensities (ηp = 0.27–0.67, p < 0.001) and increased daily sitting time from 3.57 ± 1.47 to 6.32 ± 1.33 h per weekday (ηp = 0.67, p < 0.001). The largest reduction was detected for the sum parameter all physical activity (minutes per week, ηp = 0.67, p < 0.001; MET (metabolic equivalent of task)-minutes/week, ηp = 0.69, p < 0.001). Life satisfaction decreased, with the score for “I am satisfied with my life” (ηp = 0.76, p < 0.001) decreasing from 28.1 ± 4.81 to 14.2 ± 6.41 arbitrary units (AU). Concerning life satisfaction, the largest change was detected for the statement “the conditions of my life are excellent” (dmale = 7.93). For all parameters, time effects were indicative of large negative effects in both genders. In terms of magnitude, the difference between gender was greatest for the parameter “the conditions of my life are excellent” (difference between groups, d = 4.84). In conclusion, COVID-19 confinement decreased PA, increased sitting time, and decreased life satisfaction in Qatar. These precautionary findings explicate the risk of psychosocial impairment and the potential physical harm of reducing physical activity during early COVID-19 confinement in 2020.
UWS Academic Portal Electromyographic assessment of the lower leg muscles during concentric and eccentric phases of standing heel raise Ugbolue, Ukadike

Only a small number of muscle activation patterns from lower limbs have been reported and simultaneous muscle activation from several lower limb muscles have not yet been investigated. The purpose of this study was to examine any gender differences in surface electromyography (EMG) activity from six recorded lower limb muscles of the dominant limb at baseline (i.e., with the foot placed flat on the floor and in the neutral position), and during concentric and eccentric phases when performing a heel raise task. In total, 10 females and 10 males performed a standing heel raise task comprising of three continuous phases: baseline, unloading (concentric muscle action), and loading (eccentric muscle action) phases. Muscle activation from six muscles (gastrocnemius medialis, gastrocnemius lateralis, soleus, tibialis anterior, peroneus longus, and peroneus brevis) were measured using the Myon 320 EMG System. Root mean squared values of each muscle were calculated for each phase. Descriptive and inferential statistics were incorporated into the study. Statistically significant p values were set at 0.05. The results showed no significant differences between baseline, concentric, and eccentric phases with respect to each of the muscles investigated. Except for the gastrocnemius medialis at baseline and concentric phases, no significant differences were observed between genders or contractions. The data suggests that gender does not significantly influence the eccentric phase during the standing heel raise task.
Effect of crude propolis on the performance and feed digestibility of new zealand white rabbits

The objective of this study was to evaluate the performance and digestibility of diets containing different levels of crude propolis for growing rabbits. Forty-eight New Zealand White rabbits, 43 days old, of both genders, were used, distributed in a completely randomized design. There were four diets with different inclusion levels of crude propolis (0.0; 0.5; 1.0 and 1.5%). There was no statistical difference for performance regarding the inclusion levels of crude propolis (p = 0.85), as well as for the variables dry matter consumption, neutral detergent fiber and acid detergent fiber (p ≥ 0.07). Crude protein consumption showed a statistical difference in relation to gender (p = 0.04): males showed higher consumption. However, final weight, total weight gain, daily weight gain and feed efficiency were not influenced by the addition of crude propolis (p ≥ 0.37). Dry matter digestibility, crude protein, neutral detergent fiber and acid detergent fiber were not influenced by the inclusion levels of crude propolis in the diets (p ≥ 0.12). This study indicates that the inclusion of raw propolis up to 1.5% in the diets does not affect the performance parameters of rabbits.
Low muscle strength, high body mass index, and low bone mineral density among adult Special Olympics athletes in the United States in 2018-2019

Adults with intellectual disabilities (ID) have increasing life expectancy, but a large-scale analysis of the presence of aging-related conditions in adults with ID is absent in the literature. The purpose of this study was to examine the associations between the presence of low muscle strength, high body mass index (BMI), and low bone mineral density (BMD) with age and sex in adult Special Olympics (SO) athletes from the United States (U.S.). Data were collected during 2018-2019 from U.S. male and female SO athletes, ≥20 years old, with diagnosed ID (N = 14,137; 42.4% female). Grip strength (n = 6,477; 40.9% female), chair stand time (n = 6,444; 40.5% female), BMI (n = 7,824; 43.7% female), and BMD (n = 3,091; 43.2% female) measurements were provided from the Special Olympics International Healthy Athletes System. Binary logistic regression analyses were performed to examine associations between age (banded by decades) and sex (male and female) with low grip strength, high chair stand time, high BMI, or low BMD based on established cut-points for sarcopenia, obesity, and osteopenia. Low grip strength, high chair stand time, high BMI, and low BMD were identified in 43.8%, 46.2%, 50.3%, and 28.7% of each sample, respectively. The coexistence of all four conditions was observed in 3.5% (n = 737) of athletes. Males were significantly more likely than females to exhibit low grip strength (OR = 1.88, 95% CI = 1.70 – 2.08; p < .001) and low BMD (OR = 1.27, 95% CI = 1.08 – 1.49; p = .004) and significantly less likely to have high chair stand time (OR = 0.88, 95% CI = 0.80 – 0.97; p = .013) and high BMI (OR = 0.56, 95% CI = 0.51 – 0.61; p < .001). Athletes who reported participation in ≥150 minutes of physical activity per week were less likely to have high BMI (OR = 0.78, 95% CI = 0.70 – 0.87; p < .001), while athletes who acquired 5-6 (OR = 1.49, 95% CI = 1.15 – 1.93; p = .013) or ≥6 hours (OR = 1.66, 95% CI = 1.25 – 2.21; p < .001) of screen time per day were at higher risk for high BMI. Odds ratios for all
Self-Supervised Learning on 3D Point Clouds by Learning Discrete Generative Models

While recent pre-training tasks on 2D images have proven very successful for transfer learning, pre-training for 3D data remains challenging. In this work, we introduce a general method for 3D self-supervised representation learning that 1) remains agnostic to the underlying neural network architecture, and 2) specifically leverages the geometric nature of 3D point cloud data. The proposed task softly segments 3D points into a discrete number of geometric partitions. A self-supervised loss is formed under the interpretation that these soft partitions implicitly parameterize a latent Gaussian Mixture Model (GMM), and that this generative model establishes a data likelihood function. Our pretext task can therefore be viewed in terms of an encoder-decoder paradigm that squeezes learned representations through an implicitly defined parametric discrete generative model bottleneck. We show that any existing neural network architecture designed for supervised point cloud segmentation can be repurposed for the proposed unsupervised pretext task. By maximizing data likelihood with respect to the soft partitions formed by the unsupervised point-wise segmentation network, learned representations are encouraged to contain compositionally rich geometric information. In tests, we show that our method naturally induces semantic separation in feature space, resulting in state-of-the-art performance on downstream applications like model classification and semantic segmentation.
Response of the International Energy Agency (IEA) Wind 15 MW WindCrete and Activefloat floating wind turbines to wind and second-order waves

Abstract. The EU Horizon 2020 project COREWIND (COst REduction and increase performance of floating WIND technology) has developed two floating platforms for the new International Energy Agency (IEA) Wind 15 MW reference wind turbine. One design – “WindCrete” – is a spar floater, and the other – “Activefloat” – is a semi-submersible floater; both designs are made of concrete. In this work the design of the floaters is introduced with their aero–hydro–servo-elastic numerical models, and the responses of both floaters in both static and dynamic simulations are investigated. The static displacements and natural frequencies are simulated and discussed. Additionally, the effects of the mean wave drift forces and second-order difference-frequency wave forces on the systems' responses are presented. The increase in the turbine's power capacity to 15 MW in IEA Wind model leads to an increase in inertial forces and aerodynamic thrust force when compared to similar floating platforms coupled to the Technical University of Denmark (DTU) 10 MW reference model. The goal of this work is to investigate the floaters' responses for different load cases. The results in this paper suggest that at mild wave loads the motion responses of the 15 MW floating offshore wind turbines (FOWTs) are dominated by low-frequency forces. Therefore, motions are dominated by the wind forces and second-order wave forces rather than the first-order wave forces. After assessing and understanding the models' responses, the two 15 MW FOWT numerical reference models are publicly available to be used in the research and development of floating wind energy.
On the Role of MBS Purchases for the Macroeconomic Effects of QE1∗

This paper studies the quantitative contribution of MBS purchases to the macroeconomic effects of the US Federal Reserve’s first round of quantitative easing, QE1. We develop a macroeconomic model with costly financial intermediation, collateralized lending, and an explicit specification of distinct central bank asset purchase programs. We show that MBS purchases induce a fall in mortgage rates and increases in the price of collateral and in bank lending, which stimulates aggregate demand and real activity. We replicate the time paths of purchased asset and of associated price effects at the onset of the global financial crisis. Our calibrated model predicts that MBS purchases accounted for more than 85% of the (cumulated) output effects of QE1 and that an equally sized intervention with purchases of treasuries only would have led to about 30% smaller output effects. JEL classification: E43, E44, E51, E52
Reducing Domain Gap by Reducing Style Bias

Convolutional Neural Networks (CNNs) often fail to maintain their performance when they confront new test domains, which is known as the problem of domain shift. Recent studies suggest that one of the main causes of this problem is CNNs’ strong inductive bias towards image styles (i.e. textures) which are sensitive to domain changes, rather than contents (i.e. shapes). Inspired by this, we propose to reduce the intrinsic style bias of CNNs to close the gap between domains. Our Style-Agnostic Networks (SagNets) disentangle style encodings from class categories to prevent style biased predictions and focus more on the contents. Extensive experiments show that our method effectively reduces the style bias and makes the model more robust under domain shift. It achieves remarkable performance improvements in a wide range of cross-domain tasks including domain generalization, unsupervised domain adaptation, and semi-supervised domain adaptation on multiple datasets.1
Bag-of-Words Baselines for Semantic Code Search

The task of semantic code search is to retrieve code snippets from a source code corpus based on an information need expressed in natural language. The semantic gap between natural language and programming languages has for long been regarded as one of the most significant obstacles to the effectiveness of keyword-based information retrieval (IR) methods. It is a common assumption that “traditional” bag-of-words IR methods are poorly suited for semantic code search: our work empirically investigates this assumption. Specifically, we examine the effectiveness of two traditional IR methods, namely BM25 and RM3, on the CodeSearchNet Corpus, which consists of natural language queries paired with relevant code snippets. We find that the two keyword-based methods outperform several pre-BERT neural models. We also compare several code-specific data pre-processing strategies and find that specialized tokenization improves effectiveness.