Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing dominance of tennis' big three via multiple-output Bayesian quantile regression models

Tennis has seen a myriad of great male tennis players throughout its history and we are often interested in the discussion of who is/was the greatest player of all time. While we do not try to answer this question here, we delve into comparing some key statistics related to dominance over their opponents for the male players with the most Grand Slam titles, currently: Djokovic, Federer and Nadal, in alphabetical order. Here we consider the minutes played and the relative points in each of their completed matches, as a measure of dominance against other players. We consider important covariates such as surface, win or loss, type of tournament and whether their opponent was a top 20 ranked player in the world or not, to create a more complete comparison of their performance. We consider a Bayesian quantile regression model for multiple-output response variables to take into account the dependence between minutes and relative points won. This approach is compelling since we do not need to choose a probability distribution for the joint probability distribution of our response variable. Our results agree with the common intuition of Nadal’s superiority in clay courts, Federer’s superiority in grass courts and Djokovic’s superiority in hard courts given their success in each of these surfaces; though Nadal’s dominance in clay court games is unique. Federer shows his dominance regarding minutes spent in the court in wins, while Djokovic takes the edge when considering the dimension of relative points won, for most of the comparisons. While minutes can be directly connected to style of play, the relative points dimension could express more directly different levels of advantage over their opponent, in which Djokovic seems to be the overall leader in this analysis. ∗e-mail: b.santos@kent.ac. uk 1 ar X iv :2 11 1. 05 63 1v 1 [ st at . A P] 1 0 N ov 2 02 1
Palette: Image-to-Image Diffusion Models

This paper develops a unified framework for image-to-image translation based on conditional diffusion models and evaluates this framework on four challenging image-to-image translation tasks, namely colorization, inpainting, uncropping, and JPEG restoration. Our simple implementation of image-to-image diffusion models outperforms strong GAN and regression baselines on all tasks, without task-specific hyper-parameter tuning, architecture customization, or any auxiliary loss or sophisticated new techniques needed. We uncover the impact of an L2 vs. L1 loss in the denoising diffusion objective on sample diversity, and demonstrate the importance of self-attention in the neural architecture through empirical studies. Importantly, we advocate a unified evaluation protocol based on ImageNet, with human evaluation and sample quality scores (FID, Inception Score, Classification Accuracy of a pre-trained ResNet-50, and Perceptual Distance against original images). We expect this standardized evaluation protocol to play a role in advancing image-to-image translation research. Finally, we show that a generalist, multi-task diffusion model performs as well or better than task-specific specialist counterparts. Check out https://diffusion-palette.github. io/ for an overview of the results and code.
Application and Assessment of the Divide-and-Conquer method on some Integer Optimization Problems

In this paper the Divide-and-Conquer method is applied and assessed to three integer optimizations problems: Multidimensional Knapsack Problem (d-KP), Bin Packing Problem (BPP) and Travelling Salesman Problem (TSP). For each case, the method is introduced, together with the design of numerical experiments, in order to empirically establish its performance from both points of view: its computational time and its numerical accuracy.
Layer-controlled Ferromagnetism in Atomically Thin CrSiTe$_3$ Flakes

The research on two-dimensional (2D) van der Waals (vdW) ferromagnets has promoted the development of ultrahigh-density and nanoscale data storage. However, intrinsic ferromagnetism in layered magnets is always subject to many factors, such as stacking orders, interlayer couplings, and the number of layers. Here, we report a magnetic transition from soft to hard ferromagnetic behaviors as the thickness of CrSiTe3 flakes decreases down to several nanometers. Phenomenally, in contrast to the negligible hysteresis loop in the bulk counterparts, atomically thin CrSiTe3 shows a rectangular loop with finite magnetization and coercivity as thickness decreases down to ~8 nm, indicative of a single-domain and out-of-plane ferromagnetic order. We find that the stray field is weakened with decreasing thickness, which suppresses the formation of the domain wall. In addition, thickness-dependent ferromagnetic properties also reveal a crossover from 3 dimensional to 2 dimensional Ising ferromagnets at a ~7 nm thickness of CrSiTe3, accompanied by a drop of the Curie temperature from 33 K for bulk to ~17 K for 4 nm sample.
Towards Tractable Mathematical Reasoning: Challenges, Strategies, and Opportunities for Solving Math Word Problems

Mathematical reasoning would be one of the next frontiers for artificial intelligence to make significant progress. The ongoing surge to solve math word problems (MWPs) and hence achieve better mathematical reasoning ability would continue to be a key line of research in the coming time. We inspect non-neural and neural methods to solve math word problems narrated in a natural language. We also highlight the ability of these methods to be generalizable, mathematically reasonable, interpretable, and explainable. Neural approaches dominate the current state of the art, and we survey them highlighting three strategies to MWP solving: (1) direct answer generation, (2) expression tree generation for inferring answers, and (3) template retrieval for answer computation. Moreover, we discuss technological approaches, review the evolution of intuitive design choices to solve MWPs, and examine them for mathematical reasoning ability. We finally identify several gaps that warrant the need for external knowledge and knowledge-infused learning, among several other opportunities in solving MWPs.
Multimodal Approach for Metadata Extraction from German Scientific Publications

Nowadays, metadata information is often given by the authors themselves upon submission. However, a significant part of already existing research papers have missing or incomplete metadata information. German scientific papers come in a large variety of layouts which makes the extraction of metadata a non-trivial task that requires a precise way to classify the metadata extracted from the documents. In this paper, we propose a multimodal deep learning approach for metadata extraction from scientific papers in the German language. We consider multiple types of input data by combining natural language processing and image vision processing. This model aims to increase the overall accuracy of metadata extraction compared to other state-of-the-art approaches. It enables the utilization of both spatial and contextual features in order to achieve a more reliable extraction. Our model for this approach was trained on a dataset consisting of around 8800 documents and is able to obtain an overall F1-score of 0.923.
Very weak solution for the exterior stationary Stokes equations with Navier slip boundary condition

In some problems of fluid mechanics, it is possible to be confronted with data that are not regular, that is why we are interested here in the search for the so-called very weak solutions for the stationary Stokes problem with Navier-type boundary conditions in a three-dimensional exterior domain. The problem describes the flow of a viscous and incompressible fluid past an obstacle where we assume that the fluid may slip on the boundary of the obstacle. Because the flow domain is unbounded, we set the problem in weighted Sobolev spaces in order to control the behavior at infinity of the solutions. Our purpose is to prove the existence and the uniqueness of a very weak solution in a Hilbertian framework.
MAJORCA: Multi-Architecture JOP and ROP Chain Assembler

Nowadays, exploits often rely on a code-reuse approach. Short pieces of code called gadgets are chained together to execute some payload. Code-reuse attacks can exploit vul-nerabilities in the presence of operating system protection that prohibits data memory execution. The ROP chain construction task is the code generation for the virtual machine defined by an exploited executable. It is crucial to understand how powerful ROP attacks can be. Such knowledge can be used to improve software security. We implement MAJORCA that generates ROP and JOP payloads in an architecture agnostic manner and thoroughly consider restricted symbols such as null bytes that terminate data copying via strcpy. The paper covers the whole code-reuse payloads construction pipeline: cataloging gadgets, chaining them in DAG, scheduling, linearizing to the ready-to-run payload. MAJORCA automatically generates both ROP and JOP payloads for x86 and MIPS. MAJORCA constructs payloads respecting restricted symbols both in gadget addresses and data. We evaluate MAJORCA performance and accuracy with rop-benchmark and compare it with open-source compilers. We show that MAJORCA outperforms open-source tools. We propose a ROP chaining metric and use it to estimate the probabilities of successful ROP chaining for different operating systems with MAJORCA as well as other ROP compilers to show that ROP chaining is still feasible. This metric can estimate the efficiency of OS defences.
Time-frequency channel estimation for digital amplitude modulation broadcasting systems based on OFDM

Digital AM broadcasting (DAMB) channels are investigated in detail. First, the normalised ICI power of time-variant DAMB channels is calculated to determine the range of total subcarriers of an OFDM-based DAMB system. The number of subcarriers provides a base for the subsequent channel estimation. Then, two time-frequency channel estimators with real coefficients are constructed and analysed for a DAMB system based on OFDM. Finally, their BER performance is simulated in DAMB channels. In conclusion, the 1-D estimator provides a better trade-off between BER performance and computational complexity than a 2-D estimator. The low complexity of a 1-D estimator makes it suitable for use in wireless communication systems such as WLAN, DVB and so on.
Development and testing of a clinical outcome measurement tool to assess wheeled mobility and seating interventions

The purpose of this study was to develop the Functioning Everyday with a Wheelchair - Capacity (FEW-C), a valid and reliable performance-based observation tool to measure the effects of wheeled mobility and seating interventions on functional capabilities specific to consumers needs. The tool was modeled after the Functioning Everyday with a Wheelchair (FEW), a companion self-report measure and characteristics of the capacity qualifier of the World Health Organization International Classification of Functioning, Disability, and Health. Prior to the development of the tool a systematic review of the scientific literature revealed limited availability of performance based measures of functional outcome that could be applied across the spectrum of wheeled mobility and seating devices or types of impairments. Excellent interrater reliability coefficients (ICC 2,k = 0.98) were established with 13 wheeled mobility and seating device users and 8 trained raters. Internal consistency of the FEW-C, based on a sample of 25 wheeled mobility and seating device users, yielded Cronbach's alphas ranging from 0.74 to 0.89 indicating good internal consistency without redundancy. Multitrait-multimethod matrix analyses, yielded fair to good convergent and discriminant validity when compared with other tools that were measuring similar traits by different methods. A non-randomized clinical trial was implemented to test the ability of the performance-based FEW-C to detect statistical and practical change over time, and to ascertain if the FEW-C results differed from the companion self-report tools. Findings indicated that the FEW-C and other self-report tools were able to measure practical changes in function over time with very large Cohen's d effect sizes ( 2.28 - 3.18) following the provision of a new wheeled mobility and seating device, however, each of the tools behaved differently. These findings further confirmed the effectiveness of the wheeled mobility and seating interventions provided by the clinicians. Our findings also indicated that the operationalization of the items of the reliable and valid FEW self-report tool into a performance-based observational tool yielded another reliable and valid tool for gathering data about functioning with a wheeled mobility and seating device, and that each tool contributed unique information to wheeled mobility and seating assessments.
The Effects of Airfoil Camber on Flutter Suppression Regarding Timoshenko Beam Theory

The application of Timoshenko beam theory is presented, thereby the effects of airfoil camber can be investigated analytically and numerically by considering rotary inertia and shear deformation in addition to moment of inertia, aerodynamic loading and bending/torsion coupling. Regarding a tuned blisk, the analysis is simplified to a single blade with plunge and pitch DOF. Pressure distribution of the airfoil surfaces and the resulting aerodynamic forces are calculated with ‘ANSYS/FLOTRAN’ during one-cycle time marching at several reduced frequencies. A parametric relation is then achieved by Roger’s approximation including quasi-inertia, quasi-damping, quasi-elastic and lag terms. The final aeroelastic equations are established by bending-torsion and aerodynamics-structure coupling which is solved by state space approach. This procedure is repeated at several free stream velocities until the real component of an eigenvalue equals zero. The latest velocity is the flutter speed. Following this procedure, flutter characteristics of two similar aeroleastic cases are determined considering only one difference in blade configuration; one with cambered and the other with uncambered airfoil. Comparison of these two cases shows the considerable suppression effect of airfoil camber on flutter.
Robust stable control of haptic devices based on transparency maximization

The performance of haptic devices is evaluated based on the concept of transparency, while their stability has prevalently been evaluated based on the passivity criterion. Due to the conservativeness of passivity, it appears as an obstacle to improving transparency. In the present paper, passivity is suggested to be replaced by the complementary stability criterion which accounts for the robust stability of the interaction in the presence of uncertain user hand dynamics. In this respect, an algorithm is proposed which guarantees transparency of the haptic device in a stable manner. Assuming that the dynamics of the device is known, a certain compensatory structure is assigned. This special structure guarantees transparency of the device by compensating for the dynamics of the device and its control loop. The design objective is to obtain a stabilizing controller which achieves robust interaction stability in the presence of parametric uncertainties of user hand dynamics and other sources of uncertainties. An iterative method is implemented, in conjunction with the D-K iteration algorithm, to derive controller dynamics. The algorithm is applied to a series elastic actuator-based haptic device. This results in a widened frequency range of transparent impedance emulation. Simulation results confirm enhanced transparency and robust stability.
Dynamic variability in SHP-1 abundance determines natural killer cell responsiveness

Description The responsiveness of mouse and human natural killer cells is inversely correlated with the abundance of the phosphatase SHP-1. Tuning NK cell responses Natural killer (NK) cells are innate immune cells that detect and kill virally infected cells and transformed cells. NK cells become activated when they receive signals through stimulatory receptors in the absence of balancing signals through inhibitory receptors. The effectiveness of NK cells as a cancer immunotherapy depends on a better understanding of how their cell-killing capability is developed and maintained. Wu et al. found that the responsiveness of mouse and human NK cell subsets was inversely correlated with the abundance of the tyrosine phosphatase SHP-1, which mediates inhibitory receptor signaling. Acute reductions in SHP-1 abundance or activity enhanced the ability of NK cells to kill cells, suggesting that targeting SHP-1 in NK cells ex vivo may enhance their therapeutic potential. Interactions between human leukocyte antigen (HLA) molecules on target cells and the inhibitory killer cell immunoglobulin-like receptors (KIRs) and heterodimeric inhibitory receptor CD94-NKG2A on human natural killer (NK) cells shape and program various response capacities. A functionally orthologous system exists in mice, consisting of major histocompatibility complex (MHC) molecules on target cells and the inhibitory Ly49 and CD94-NKG2A receptors on NK cells. Here, we found that the abundance of Src homology 2 domain–containing phosphatase-1 (SHP-1) in NK cells was established by interactions between MHCs and NK cell inhibitory receptors, although phenotypically identical NK cell populations still showed substantial variability in endogenous SHP-1 abundance and NK cell response potential. Human and mouse NK cell populations with high responsiveness had low SHP-1 abundance, and a reduction in SHP-1 abundance in NK cells enhanced their responsiveness. Computational modeling of NK cell activation by membrane-proximal signaling events identified SHP-1 as a negative amplitude regulator, which was validated by single-cell analysis of human NK cell responsiveness. The amount of mRNA and protein varied among responsive NK cells despite their similar chromatin accessibility to that of unresponsive cells, suggesting dynamic regulation of SHP-1 abundance. Low intracellular SHP-1 abundance was a biomarker of responsive NK cells. Together, these data suggest that enhancing NK cell function through the acute loss of SHP-1 abundance or activity may enhance the tumoricidal capacity of NK cells.
单纯输注抗BCMA与抗BCMA输注联合抗CD19嵌合抗原受体T细胞治疗复发/难治性多发性骨髓瘤免疫重建的对比

目的 观察比较单纯输注抗B细胞成熟抗原（BCMA）嵌合抗原受体T细胞（CAR-T细胞）与输注抗BCMA联合抗CD19 CAR-T细胞治疗复发/难治性多发性骨髓瘤（RRMM）患者免疫重建的差异。 方法 以2017年6月至2020年12月在我院行CAR-T细胞治疗的61例RRMM患者为研究对象，其中单纯接受抗BCMA靶点者26例，接受抗BCMA联合抗CD19靶点者35例。 流式细胞术分别测定CAR-T治疗前后不同时间点的T细胞亚群（CD3+、CD4+、CD8+、CD4+/CD8+）、B细胞（CD19+）及NK细胞（CD16+CD56+），免疫比浊法检测免疫球蛋白IgG、IgA及IgM水平。 对比两组淋巴细胞亚群及免疫球蛋白的重建规律。 结果 CAR-T细胞输注后，CD8+T淋巴细胞恢复最快，BCMA组与BCMA+CD19组分别在输注后3个月和输注后1个月时恢复至输注前水平［BCMA：695（357, 1264）个/µl对424（280, 646）个/µl；BCMA+CD19：546（279, 1672）个/µl对314（214, 466）个/µl］。 两组NK细胞均在输注后3个月时恢复至正常水平［分别为171（120, 244）个/µl、153（101, 218）个/µl（正常参考范围150～1100个/µl）］，但BCMA组不能维持在稳定水平。 两组CD4+ T淋巴细胞恢复缓慢，输注后12个月内仍处于持续低水平，多数患者未观察到恢复。 CD4+/CD8+比值倒置持续1年以上。 两组CD19+B细胞均在输注后3个月恢复至输注前水平［BCMA：62（10, 72）个/µl对57（24, 78）个/µl；BCMA+CD19：40（4, 94）个/µl对29（14, 46）个/µl］。 BCMA组IgG在输注后12个月恢复至输注前水平［7.82（6.03, 9.64）g/L对6. 92（4.62, 12.76）g/L］，BCMA+CD19组未恢复。 IgA先后在输注后9个月和12个月恢复至输注前水平［BCMA：0.46（0.07, 0.51）g/L对0.22（0.12, 4.01）g/L；BCMA+CD19：0.46（0.22, 0.98）g/L对0. 27（0.10, 0.53）g/L］。 两组IgM在输注后6个月恢复至输注前水平［BCMA：0.43（0.06, 0.60）g/L对0. 20（0.13, 0.37）g/L；BCMA+CD19：0.53（0.10, 0.80）g/L对0. 16（0.11, 0.28）g/L］。 两组患者淋巴细胞亚群重建及免疫球蛋白恢复在各时间点的差异均无统计学意义。 结论 在接受CAR-T细胞治疗的RRMM患者中，可基本不考虑单纯抗BCMA CAR-T与抗BCMA联合抗CD19 CAR-T治疗之间免疫重建的差异而选择合适的靶抗原。 中国临床试验注册中心：ChiCTR-OIC-17011271、ChiCTR-OIC-17011272
Evaluating the Impact of Meningococcal Vaccines With Synthetic Controls

Abstract Invasive meningococcal disease (IMD) has a low and unpredictable incidence, presenting challenges for real-world evaluations of meningococcal vaccines. Traditionally, meningococcal vaccine impact is evaluated by predicting counterfactuals from pre-immunization IMD incidences, possibly controlling for IMD in unvaccinated age groups, but the selection of controls can influence results. We retrospectively applied a synthetic control (SC) method, previously used for pneumococcal disease, to data from 2 programs for immunization of infants against serogroups B and C IMD in England and Brazil. Time series of infectious/noninfectious diseases in infants and IMD cases in older unvaccinated age groups were used as candidate controls, automatically combined in a SC through Bayesian variable selection. SC closely predicted IMD in absence of vaccination, adjusting for nontrivial changes in IMD incidence. Vaccine impact estimates were in line with previous assessments. IMD cases in unvaccinated age groups were the most frequent SC-selected controls. Similar results were obtained when excluding IMD from control sets and using other diseases only, particularly respiratory diseases and measles. Using non-IMD controls may be important where there are herd immunity effects. SC is a robust and flexible method that addresses uncertainty introduced when equally plausible controls exhibit different post-immunization behaviors, allowing objective comparisons of IMD programs between countries.
3D-CariGAN: An End-to-End Solution to 3D Caricature Generation from Normal Face Photos

Caricature is a kind of artistic style of human faces that attracts considerable attention in entertainment industry. So far a few 3D caricature generation methods exist and all of them require some caricature information (e.g., a caricature sketch or 2D caricature) as input. This kind of input, however, is difficult to provide by non-professional users. In this paper, we propose an end-to-end deep neural network model that generates high-quality 3D caricature directly from a simple normal face photo. The most challenging issue in our system is that the source domain of face photos (characterized by 2D normal faces) is significantly different from the target domain of 3D caricatures (characterized by 3D exaggerated face shapes and texture). To address this challenge, we (1) build a large dataset of 6,100 3D caricature meshes and use it to establish a PCA model in the 3D caricature shape space, (2) reconstruct a 3D normal full head from the input face photo and use its PCA representation in the 3D caricature shape space to set up correspondence between the input photo and 3D caricature shape, and (3) propose a novel character loss and a novel caricature loss based on previous psychological studies on caricatures. Experiments including a novel two-level user study show that our system can generate high-quality 3D caricatures directly from normal face photos.
Design of Data Transmission Platform Based on LVDS and FPGA Technology

This paper presents a design of data transmission platform based on LVDS and FPGA technology. It is used for data transmission in Audio and Video teaching system, and we provide 64 terminals. The platform mainly contains two parts, multimedia data transmission card and network switch which are connected by LVDS serializer-deserializer. We use FPGA as the core chips to control data transfer.