Miracle-dz/UniFAR-FTUs huggingface dataset:
X-Fields: Implicit Neural View-, Light-and Time-Image Interpolation

, 3D projection, occlusion) in a hard-coded and differentiable form. The NN represents the input to that rendering as an implicit map, that for any view, time, or light coordinate and for any pixel can quantify how it will move if view, time or light coordinates change (Jacobian of pixel position with respect to view, time, illumination, etc.). Our X-Field representation is trained for one scene within minutes, leading to a compact set of trainable parameters and hence real-time navigation in view, time and illumination.
Don’t Read Too Much Into It: Adaptive Computation for Open-Domain Question Answering

Most approaches to Open-Domain Question Answering consist of a light-weight retriever that selects a set of candidate passages, and a computationally expensive reader that examines the passages to identify the correct answer. Previous works have shown that as the number of retrieved passages increases, so does the performance of the reader. However, they assume all retrieved passages are of equal importance and allocate the same amount of computation to them, leading to a substantial increase in computational cost. To reduce this cost, we propose the use of adaptive computation to control the computational budget allocated for the passages to be read. We first introduce a technique operating on individual passages in isolation which relies on anytime prediction and a per-layer estimation of an early exit probability. We then introduce SKYLINEBUILDER, an approach for dynamically deciding on which passage to allocate computation at each step, based on a resource allocation policy trained via reinforcement learning. Our results on SQuAD-Open show that adaptive computation with global prioritisation improves over several strong static and adaptive methods, leading to a 4.3x reduction in computation while retaining 95% performance of the full model.
Separation control and drag reduction for boat-tailed axisymmetric bodies through contoured transverse grooves

We describe the results of a numerical and experimental investigation aimed at assessing the performance of a control method to delay boundary layer separation consisting of the introduction on the surface of contoured transverse grooves, i.e. of small cavities with an appropriate shape orientated transverse to the incoming flow. The shape of the grooves and their depth – which must be significantly smaller than the thickness of the incoming boundary layer – are chosen so that the flow recirculations present within the grooves are steady and stable. This passive control strategy is applied to an axisymmetric bluff body with various rear boat tails, which are characterized by different degrees of flow separation. Variational multiscale large eddy simulations and wind tunnel tests are carried out. The Reynolds number, for both experiments and simulations, is $Re=u_{\infty }D/\unicode[STIX]{x1D708}=9.6\times 10^{4}$ ; due to the different incoming flow turbulence level, the boundary layer conditions before the boat tails are fully developed turbulent in the experiments and transitional in the simulations. In all cases, the introduction of one single axisymmetric groove in the lateral surface of the boat tails produces significant delay of the boundary layer separation, with consequent reduction of the pressure drag. Nonetheless, the wake dynamical structure remains qualitatively similar to the one typical of a blunt-based axisymmetric body, with quantitative variations that are consistent with the reduction in wake width caused by boat tailing and by the grooves. A few supplementary simulations show that the effect of the grooves is also robust to the variation of the geometrical parameters defining their shape. All the obtained data support the interpretation that the relaxation of the no-slip boundary condition for the flow surrounding the recirculation regions, with an appreciable velocity along their borders, is the physical mechanism responsible for the effectiveness of the present separation-control method.
Model-Assisted Survey Regression Estimation with the Lasso

In the U.S. Forest Service’s Forest Inventory and Analysis (FIA) program, as in other natural resource surveys, many auxiliary variables are available for use in model-assisted inference about finite population parameters. Some of this auxiliary information may be extraneous, and therefore model selection is appropriate to improve the efficiency of the survey regression estimators of finite population totals. A model-assisted survey regression estimator using the lasso is presented and extended to the adaptive lasso. For a sequence of finite populations and probability sampling designs, asymptotic properties of the lasso survey regression estimator are derived, including design consistency and central limit theory for the estimator and design consistency of a variance estimator. To estimate multiple finite population quantities with the method, lasso survey regression weights are developed, using both a model calibration approach and a ridge regression approximation. The gains in efficiency of the lasso estimator over the full regression estimator are demonstrated through a simulation study estimating tree canopy cover for a region in Utah.
Data-Driven Learning of Geometric Scattering Networks

Graph neural networks (GNNs) in general, and graph convolutional networks (GCN) in particular, often rely on low-pass graph filters to incorporate geometric information in the form of local smoothness over neighboring nodes. While this approach performs well on a surprising number of standard benchmarks, the efficacy of such models does not translate consistently to more complex domains, such as graph data in the biochemistry domain. We argue that these more complex domains require priors that encourage learning of band-pass and high-pass features rather than oversmoothed signals of standard GCN architectures. Here, we propose an alternative GNN architecture, based on a relaxation of recently proposed geometric scattering transforms, which consists of a cascade of graph wavelet filters. Our learned geometric scattering (LEGS) architecture adaptively tunes these wavelets and their scales to encourage band-pass features to emerge in learned representations. This results in a simplified GNN with significantly fewer learned parameters compared to competing methods. We demonstrate the predictive performance of our method on several biochemistry graph classification benchmarks, as well as the descriptive quality of its learned features in biochemical graph data exploration tasks. Our results show that the proposed LEGS network matches or outperforms popular GNNs, as well as the original geometric scattering construction, while also retaining certain mathematical properties of its handcrafted (nonlearned) design.
Under review as a conference paper at ICLR 2020 completely free-form sampling in image space : Spatial Transformers

Convolutional networks are not aware of an object’s geometric variations, which leads to inefficient utilization of model and data capacity. To overcome this issue, recent works on deformation modeling seek to spatially reconfigure the data towards a common arrangement such that semantic recognition suffers less from deformation. This is typically done by augmenting static operators with learned free-form sampling grids in the image space, dynamically tuned to the data and task for adapting the receptive field. Yet adapting the receptive field does not quite reach the actual goal – what really matters to the network is the effective receptive field (ERF), which reflects how much each pixel contributes. It is thus natural to design other approaches to adapt the ERF directly during runtime. In this work, we instantiate one possible solution as Deformable Kernels (DKs), a family of novel and generic convolutional operators for handling object deformations by directly adapting the ERF while leaving the receptive field untouched. At the heart of our method is the ability to resample the original kernel space towards recovering the deformation of objects. This approach is justified with theoretical insights that the ERF is strictly determined by data sampling locations and kernel values. We implement DKs as generic drop-in replacements of rigid kernels and conduct a series of empirical studies whose results conform with our theories. Over several tasks and standard base models, our approach compares favorably against prior works that adapt during runtime. In addition, further experiments suggest a working mechanism orthogonal and complementary to previous works.
Vocalizations of North American river otters (Lontra canadensis) in two human care populations

There is a dearth of information regarding the vocal repertoire of North American river otters (Lontra canadensis). This indicator species is cosmopolitan yet elusive, making recordings methodologically difficult in the wild. Therefore, this exploratory study uses video and audio recordings of two populations of North American river otters in human care to broaden the known vocal repertoire of river otters in various social contexts. The populations consist of a male-female and a male-male pair. This study is the first to examine the vocalizations produced in a male-male pair of river otters. Call types were acoustically distinguished based on their appearance on a spectrogram. Parameters including average duration, frequency (high, low, max, 1st quarter, center, and 3rd quarter), and power (max and average) were measured for each call. Because vocalizations are the focal point of this study, only behaviors co-occurring with vocalizations were included in the chi square analysis that showed a significant relationship between call type and behavior. Squeaks and whines were present during agonistic behaviors while chirps were produced during non-agonistic behaviors including investigating, stationary, and grooming. Results support that behavior likely plays a role in the type of calls produced by river otters in human care.There is a dearth of information regarding the vocal repertoire of North American river otters (Lontra canadensis). This indicator species is cosmopolitan yet elusive, making recordings methodologically difficult in the wild. Therefore, this exploratory study uses video and audio recordings of two populations of North American river otters in human care to broaden the known vocal repertoire of river otters in various social contexts. The populations consist of a male-female and a male-male pair. This study is the first to examine the vocalizations produced in a male-male pair of river otters. Call types were acoustically distinguished based on their appearance on a spectrogram. Parameters including average duration, frequency (high, low, max, 1st quarter, center, and 3rd quarter), and power (max and average) were measured for each call. Because vocalizations are the focal point of this study, only behaviors co-occurring with vocalizations were included in the chi square analysis that showed a significant .
Design of microwave broadband absorbers using a self‐adaptive differential evolution algorithm

Microwave broadband absorber design for a desired frequency and angle range is presented. The design technique is based on a self‐adaptive Differential Evolution (DE) algorithm. Numerical examples are compared with the existing in the literature and with those found by the other evolutionary algorithms. The results show that the new DE algorithm version outerperforms other global optimizers like Particle swarm optimization (PSO) variants and the classical DE algorithm. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.
Ultrasound imaging: intraexaminer and interexaminer reliability for multifidus muscle thickness assessment in adults aged 60 to 85 years versus younger adults.

STUDY DESIGN Intraexaminer and interexaminer, within- and between-day reliability study. OBJECTIVES To compare the intraexaminer and interexaminer procedural reliability of ultrasound imaging (USI) thickness measurements of the lumbar multifidus muscle at rest and during a contralateral lower-limb lift (CLL) between older (60-85 years of age) and younger (18-40 years of age) adults. BACKGROUND Among younger adults, USI has been shown to be reliable and valid for assessing multifidus thickness. Older adults present with age-related changes that may impact assessment. To our knowledge, no USI studies have focused on establishing reliability for multifidus thickness assessments in older adults. METHODS Two examiners performed assessments of lumbar multifidus thickness at rest and during a CLL in 30 older and 31 younger adults. Intraclass correlation coefficient (ICC) with 95% confidence interval, standard error of measurement, 95% minimal detectable change for resting and during the CLL, and percent thickness change were calculated. RESULTS Within-day interexaminer procedural reliability for multifidus thickness measurements was similar among younger (ICC = 0.90-0.92) and older adults (ICC = 0.86-0.90), as was between-day intraexaminer and interexaminer reliability (younger adults, ICC = 0.84-0.94; older adults, ICC = 0.86-0.93). Throughout, estimates of percent thickness change were inconsistent (ICC = 0.31-0.86), and standard errors of measurement and minimal detectable changes were larger for older adults. CONCLUSION Ultrasound imaging reliability for measurements of multifidus thickness at rest and during a CLL among older adults is consistent with previously published findings for younger adults. Among older adults, it may be preferable to have a single examiner conduct USI assessments.
A Controlled Experiment of Different Code Representations for Learning-Based Bug Repair

Training a deep learning model on source code has gained significant traction recently. Since such models reason about vectors of numbers, source code needs to be converted to a code representation and then will be transformed into vectors. Numerous approaches have been proposed to represent source code, from sequences of tokens to abstract syntax trees. However, there is no systematic study to understand the eﬀect of code representation on learning performance. Through a controlled experiment, we examine the impact of various code representations on model accuracy and usefulness in learning-based program repair. We train 21 diﬀerent models, including 14 diﬀerent homogeneous code representations, four mixed representations for the buggy and ﬁxed code, and three diﬀerent embeddings. We also conduct a user study to qualitatively evaluate the usefulness of inferred ﬁxes in diﬀer-ent code representations. Our results highlight the importance of code representation and its impact on learning and usefulness. Our ﬁndings indicate that (1) while code abstractions help the learning process, they can adversely impact the usefulness of inferred ﬁxes from a developer’s point of view; this emphasizes the need to look at the patches generated from the practitioner’s perspective, which is often neglected in the literature, (2) mixed representations can outperformhomogeneous coderepresentations, (3) bug type can aﬀect the eﬀectiveness of diﬀerent code representations; although current techniques use a single code representation for all bug types, there is no single best code representation applicable to all
Word Order in Övdalian

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Transforming growth factor-beta 1 expression and myofibroblast formation during arterial repair.

Transforming growth factor-beta 1 (TGF-beta 1) plays a central role in tissue repair owing to its modulating effects on cell growth and the synthesis of extracellular matrix. We have previously shown that adventitial fibroblasts differentiate to myofibroblasts after endoluminal injury, thereby contributing to arterial remodeling. Since TGF-beta 1 exerts several biologic actions attributed to myofibroblasts, we examined its role in myofibroblast formation in a porcine model of balloon overstretch coronary artery injury. TGF-beta 1 transcripts were induced in numerous adventitial cells 2 days after injury (47 +/- 10%, P < .001 versus control). These cells displayed no smooth muscle (SM) markers, i.e., alpha-SM actin or desmin, which suggested their fibroblastic origin. This was further corroborated by the rare presence of macrophages in the injured adventitia (3 +/- 1%). At 7 to 8 days, most TGF-beta 1-expressing cells demonstrated alpha-SM actin immunoreactivity. Their myofibroblast phenotype was confirmed by electron microscopy, which revealed microfilaments (stress fibers) and a well-developed rough endoplasmic reticulum. The distribution of TGF-beta 1 transcripts by in situ hybridization was paralleled by the immunolocalization of intracellular and extracellular TGF-beta 1 epitopes. At later times (> 14 days after injury), the decrease in TGF-beta 1 coincided with the disappearance of adventitial myofibroblasts, whereas the neointima exhibited longer TGF-beta 1 expression. In conclusion temporal and spatial relationships between TGF-beta 1 and myofibroblast formation suggest an important role for autocrine TGF-beta 1 in the phenotypic modulation of vascular fibroblasts. Induction of TGF-beta 1 expression may provide a differentiation signal for adventitial fibroblasts to become myofibroblasts, which affect arterial remodeling via their mechanical and synthetic properties.
Flow cytometric characterization of human umbilical cord blood lymphocytes: immunophenotypic features.

BACKGROUND AND OBJECTIVE One of the most important potential advantages in the use of human umbilical cord blood (HUCB) for hematopoietic reconstitution after myeloablative therapy seems to be the lower occurrence of acute graft-versus-host-disease (GvHD) in recipients after allogeneic transplantation. Since mature T cells play an important role in GvHD pathogenesis, we tried to verify whether a different immunophenotypic pattern exists between HUCB and peripheral blood (PB) T cells. DESIGN AND METHODS An immunophenotypic study on 40 HUCB and 40 PB samples from healthy adult volunteers was performed, by means of flow cytometry using a large panel of monoclonal antibodies in double labeling. RESULTS The absolute lymphocyte count was greater in HUCB (5233 +/- 1808 microL) than in adult PB (1941 +/- 378 microL). Significant differences in percentage were found between cord and adult T-cells, respectively (CD3+: 59.9 +/- 12 vs 74.9 +/- 4.6%), CD3- CD16+ and/or CD56+ natural killer (NK) cells (23.8 +/- 10.1 vs 10.8 +/- 5.3%) and CD3+CD16+ and/or CD56+ cytotoxic T lymphocyte subset (0.3 +/- 0.3 vs 10.7 +/- 4.1%). There was no difference in CD4/CD8 ratio (1.7 +/- 0.5 vs 1.6 +/- 0.2%) between the two groups. In absolute terms, HUCB contained an higher number of all lymphocyte subsets, with the exception of CD3+CD16+ and/or CD56+ T lymphocyte subpopulation, CD3+CD25+ and CD3+HLADR+ activated T-cells. CD38, a marker of activation and immaturity, was present on virtually all cord T cells and on approximately half of the adult T cells. The large majority of HUCB T cells co-expressed CD45RA naive antigen (CD4+CD45RA+: 87.6 +/- 5.2%, CD8+ CD45RA+: 93.5 +/- 7.8%; CD4+CD45RO+: 12.3 +/- 5.2%; CD8+CD45RO+: 6.4 +/- 7.8%) whereas in adult PB T cells an higher number of CD45RO+ memory cells was detected (CD4+CD45RA+: 44.8 +/- 9.6%; CD8+CD45RA: 71.5% +/- 8.1%; CD4+CD45RO+: 55.2 +/- 9.6%; CD8+ CD45RO+: 28.5 +/- 8.1%). Finally, less than 14% of lymphocytes were shown to belong to B lineage in both sources, while, in absolute terms, they were more represented in HUCB with respect to adult PB. INTERPRETATION AND CONCLUSIONS In the present study we found significant difference between HUCB and adult PB lymphocytes in their immunophenotypic profile. In particular HUCB showed T lymphocytes that appeared to be phenotypically immature. Indeed, as a likely consequence of poor antigenic experience during pregnancy, the majority of HUCB cells were naive, expressing the RA isoform of the CD45 molecule. These findings could justify the previously reported reduced cord blood lymphocyte alloreactivity when allogeneic transplantation is performed and require further functional studies in order to confirm the impairment of HUCB immune system response to alloantigens.
Loss of Annexin A5 expression attenuates the lipopolysaccharide‐induced inflammatory response of rat alveolar macrophages

Acute lung injury (ALI) is a common respiratory syndrome accompanied with an inflammation response. Annexin A5 (AnxA5) has anti‐thrombotic, anti‐apoptotic, and anti‐inflammatory properties. The current study aims to explore the potential effect of AnxA5 on lipopolysaccharide (LPS)‐induced inflammatory response in alveolar macrophages (AMs). Rat AMs (NR8383) were used in this study, and the cell viabilities at 4, 8, and 16 h after LPS administration with gradient concentrations were determined using cell counting kit‐8 assay. Cell apoptosis and expressions of messenger RNAs (mRNAs) and protein were determined by flow cytometry, quantitative real‐time polymerase chain reaction (qRT‐PCR), and western blot, respectively. We found that LPS suppressed the viability of AMs in a dose‐dependent manner, and it elevated the expression of AnxA5 in AMs. Inhibition of AnxA5 improved the cell viability compared with the LPS group and could reduce the apoptosis rate in comparison with LPS treatment. The knockdown of AnxA5 suppressed the expressions of tumor necrosis factor‐α (TNF‐α), interleukin (IL‐1β), and IL‐6 at both protein and mRNA levels and regulated the expressions of apoptosis‐related molecules (Bax, Bcl‐2, and caspase‐3). Moreover, the knockdown of AnxA5 improved the expression levels of inhibitory κB (IκB) and nuclear factor E2‐related factor 2 (Nrf2) but inhibited the expression of nuclear transcription factor κB (NF‐κB), compared with the LPS group. SN50 and ML385 were used to validate this signaling, and the inhibition of AnxA5 suppressed the LPS‐induced inflammation, indicating that AnxA5 may be a potential anti‐inflammatory target. In addition, NF‐κB/Nrf2 signaling pathway may also be involved in the LPS‐induced inflammatory response of rat alveolar macrophages.