Miracle-dz/UniFAR-FTUs huggingface dataset:
Dense LIDAR point clouds from room-scale scans

LiDARs can capture distances with high accuracy and should be very useful to create point clouds that provide highly detailed representations of an environment. If these reconstructions are meant as baseline or ground truth for other algorithms, they must have a high density and accuracy. Currently available LiDARs do still face some limitations. Either they have a limited range, or they have a rather limited resolution in one or more dimensions. As a consequence, all of them have to undergo motion to capture a larger environment. While some systems follow extremely well-predictable motion paths such as satellite trajectories or robotic arms, others require more spontaneous and flexible motion. These systems use either visual simultaneous localization and mapping (vSLAM), GPS or IMU to achieve this, but they are generally designed in such a way that human intervention is required during the creation of high-quality point clouds. In this paper, we make use of a rotating LiDAR with an attached IMU to create dense point clouds of room-scale environments with the base accuracy of the LiDAR by compensating for the various inaccuracies that are introduced by the LiDAR's motion. The resulting dense scans are suitable as ground truths for other techniques because we retain the error distribution of the LiDAR itself through the densification. In contrast to other works, we do not aim at a visually pleasing or easily meshable result and we can therefore avoid potentially inaccurate assumptions about the flatness of surfaces. We take a two-step approach. First, we densify from a stationary position changing only the LiDAR's pitch. Second, we add free motion to expose obstructed views. We show that motion paths determined by repeated Iterative Closest Point (ICP) as well as image matching on height maps can be used to create feasible priors for densification using ICP.
Case Report: Clinical Treatment of the First Critical Patient With Coronavirus Disease (COVID-19) in Liaocheng, Shandong Province

This paper reports the clinical characteristics, diagnosis, and treatment of the first critical COVID-19 patient in Liaocheng City, who was admitted to the intensive care unit isolation ward of Liaocheng People's Hospital on February 11, 2020. On admission, the patient had difficulty breathing, the oxygenation index was 135 mmHg, and the blood lactate was 5.6 mmol/L. After comprehensive treatment including high-flow nasal cannula oxygen therapy, plasma exchange, antiviral and anti-infection therapies, immune regulation, liquid volume management, glucocorticoid, enteral nutrition support, analgesia and sedation, blood glucose control, anticoagulation and thrombus prevention, and electrolyte balance maintenance, the patient was finally cured, and discharged. The purpose of this case report is to provide a reference for the clinical diagnosis and treatment of critical COVID-19 patients.
Quality estimation models for gaming video streaming services using perceptual video quality dimensions

The gaming industry is one of the largest digital markets for decades and is steady developing as evident by new emerging gaming services such as gaming video streaming, online gaming, and cloud gaming. While the market is rapidly growing, the quality of these services depends strongly on network characteristics as well as resource management. With the advancement of encoding technologies such as hardware accelerated engines, fast encoding is possible for delay sensitive applications such as cloud gaming. Therefore, already existing video quality models do not offer a good performance for cloud gaming applications. Thus, in this paper, we provide a gaming video quality dataset that considers hardware accelerated engines for video compression using the H.264 standard. In addition, we investigate the performance of signal-based and parametric video quality models on the new gaming video dataset. Finally, we build two novel parametric-based models, a planning and a monitoring model, for gaming quality estimation. Both models are based on perceptual video quality dimensions and can be used to optimize the resource allocation of gaming video streaming services.
Computational Modeling of Interstitial Fluid Pressure and Velocity in Non-small Cell Lung Cancer Brain Metastases Treated With Stereotactic Radiosurgery

Background: Early imaging-based treatment response assessment of brain metastases following stereotactic radiosurgery (SRS) remains challenging. The aim of this study is to determine whether early (within 12 weeks) intratumoral changes in interstitial fluid pressure (IFP) and velocity (IFV) estimated from computational fluid modeling (CFM) using dynamic contrast-enhanced (DCE) MRI can predict long-term outcomes of lung cancer brain metastases (LCBMs) treated with SRS. Methods: Pre- and post-treatment T1-weighted DCE-MRI data were obtained in 41 patients treated with SRS for intact LCBMs. The imaging response was assessed using RANO-BM criteria. For each lesion, extravasation of contrast agent measured from Extended Tofts pharmacokinetic Model (volume transfer constant, Ktrans) was incorporated into a computational fluid model to estimate tumor IFP and IFV. Estimates of mean IFP and IFV and heterogeneity (skewness and kurtosis) were calculated for each lesion from pre- and post-SRS imaging. The Wilcoxon rank-sum test was utilized to assess for significant differences in IFP, IFV, and IFP/IFV change (Δ) between response groups. Results: Fifty-three lesions from 41 patients were included. Median follow-up time after SRS was 11 months. The objective response (OR) rate (partial or complete response) was 79%, with 21% demonstrating stable disease (SD) or progressive disease (PD). There were significant response group differences for multiple posttreatment and Δ CFM parameters: post-SRS IFP skewness (mean −0.405 vs. −0.691, p = 0.022), IFP kurtosis (mean 2.88 vs. 3.51, p = 0.024), and IFV mean (5.75e-09 vs. 4.19e-09 m/s, p = 0.027); and Δ IFP kurtosis (mean −2.26 vs. −0.0156, p = 0.017) and IFV mean (1.91e-09 vs. 2.38e-10 m/s, p = 0.013). Posttreatment and Δ thresholds predicted non-OR with high sensitivity (sens): post-SRS IFP skewness (−0.432, sens 84%), kurtosis (2.89, sens 84%), and IFV mean (4.93e-09 m/s, sens 79%); and Δ IFP kurtosis (−0.469, sens 74%) and IFV mean (9.90e-10 m/s, sens 74%). Conclusions: Objective response was associated with lower post-treatment tumor heterogeneity, as represented by reductions in IFP skewness and kurtosis. These results suggest that early post-treatment assessment of IFP and IFV can be used to predict long-term response of lung cancer brain metastases to SRS, allowing a timelier treatment modification.
Machine-Learning Classifiers in Discrimination of Lesions Located in the Anterior Skull Base

Purpose: The aim of this study was to investigate the diagnostic value of machine-learning models with radiomic features and clinical features in preoperative differentiation of common lesions located in the anterior skull base. Methods: A total of 235 patients diagnosed with pituitary adenoma, meningioma, craniopharyngioma, or Rathke cleft cyst were enrolled in the current study. The discrimination was divided into three groups: pituitary adenoma vs. craniopharyngioma, meningioma vs. craniopharyngioma, and pituitary adenoma vs. Rathke cleft cyst. In each group, five selection methods were adopted to select suitable features for the classifier, and nine machine-learning classifiers were employed to build discriminative models. The diagnostic performance of each combination was evaluated with area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity calculated for both the training group and the testing group. Results: In each group, several classifiers combined with suitable selection methods represented feasible diagnostic performance with AUC of more than 0.80. Moreover, the combination of least absolute shrinkage and selection operator as the feature-selection method and linear discriminant analysis as the classification algorithm represented the best comprehensive discriminative ability. Conclusion: Radiomics-based machine learning could potentially serve as a novel method to assist in discriminating common lesions in the anterior skull base prior to operation.
VVC bitstream extraction and merging operations for multi-stream media applications

In traditional video decoding applications, the number of elementary streams that a hardware decoding platform of an end device can decode is determined at runtime by the. Upon request by the application, the decoding platform verifies whether a new decoding instance with an associated requirement in terms of data rate can fit under the current workload. Conversely, if a device can decode one 4K elementary stream in hardware, it may not be able to simultaneously decode four HD elementary streams that would each correspond to requirements in terms of data rate of 1/4 of the 4K elementary stream. Current video decoding platforms are thus designed with the assumption that each elementary stream requires the instantiation of a dedicated video decoder instance. At the same time, it has been increasingly common in new media applications such as immersive media applications to simultaneously consume several elementary streams in a synchronised fashion. The demo presents a new paradigm for media applications for which elementary streams may be consumed in such synchronised manner where the same decoder instance can be used. The demonstrator leverages on new features of the Versatile Video Coding (VVC) standard and interfaces being defined in the ongoing standardisation of MPEG-I part 13: Video Decoding Interface for Immersive Media. Stitching and cropping videos in the compressed domain can be achieved by an application via such defined interfaces. Without those interfaces, the same tasks are possible with the High Efficiency Video Coding (HEVC) standard to some extent but are tedious. In this demonstrator, we thus show how the new VVC codec can enable the decoupling of the number of elementary streams consumed by the application and the number of running video decoder instances. In addition, memory usage and CPU performance are also collected and compared with a tradition multiple decoding instance approach.
WERFE: A Gene Selection Algorithm Based on Recursive Feature Elimination and Ensemble Strategy

Gene selection algorithm in micro-array data classification problem finds a small set of genes which are most informative and distinctive. A well-performed gene selection algorithm should pick a set of genes that achieve high performance and the size of this gene set should be as small as possible. Many of the existing gene selection algorithms suffer from either low performance or large size. In this study, we propose a wrapper gene selection approach, named WERFE, within a recursive feature elimination (RFE) framework to make the classification more efficient. This WERFE employs an ensemble strategy, takes advantages of a variety of gene selection methods and assembles the top selected genes in each approach as the final gene subset. By integrating multiple gene selection algorithms, the optimal gene subset is determined through prioritizing the more important genes selected by each gene selection method and a more discriminative and compact gene subset can be selected. Experimental results show that the proposed method can achieve state-of-the-art performance.
Tree damage and microclimate of forest canopies along a hurricane-impact gradient in Cusuco National Park, Honduras

Abstract: Past studies of large, infrequent wind disturbances have shown that topographical, biological and meteorological factors interact to create complex damage patterns to forest ecosystems. However, the extent to which some of these factors change the forest microclimate along a vertical forest profile is poorly known. In a previous study, we correlated tree damage with a hurricane model that estimated past hurricane impacts within Cusuco National Park, Honduras over a 15-y period. Here we use the model to compare physical tree damage among different species in ten 150 ×150-m plots and to correlate modelled exposure of hurricanes to microclimate measurements along the vertical canopy over a 12-mo period. It was found that past hurricane impacts could still be detected long after the events. Different tree species showed different levels of wind damage. Most branch damage was observed on conifers (Pinus spp.), followed by angiosperm species. Vapour pressure deficit increased with height in the canopy and with increased disturbance level. A linear model explained 83% of the total variance in vapour pressure deficit, with 67% attributed to monthly fluctuation, 15% to altitude, 12% to historical hurricane damage and 6% to height in the canopy.
Distinct Insular Functional Connectivity Changes Related to Mood and Fatigue Improvements in Major Depressive Disorder Following Tai Chi Training: A Pilot Study

Objective: Tai chi (TC), a contemplative practice combining slow movements and deep breathing, has been shown to be clinically effective in alleviating depressive symptoms. Feelings of fatigue or low vitality often accompany major depressive disorder (MDD) though they are commonly overlooked and not well understood neurologically. By using resting state functional connectivity (rs-FC) using the insula as the seed, this study examines the relationship between mood and vitality symptoms in MDD and how they are impacted by TC training. Methods: Patients (N = 16) with MDD participated in a 10-week TC intervention. Self-report scores of vitality (using the SF-36 scale) and depressed mood (using the Beck Depression Inventory) as well as rs-fMRI were collected pre- and post-intervention. A seed-to-voxel approach was used to test whether changes in insular rs-FC were related to therapeutic improvement in MDD-related symptoms resulting from TC practice. Results: We found decreased self-reported depressed mood and increased vitality following the TC intervention. Furthermore, decreases in depressed mood were associated with increased rs-FC between the right anterior insula (AIC) and superior temporal gyrus and caudate (cluster-corrected p < 0.05). Increased vitality was associated with increased rs-FC between the right posterior insula (PIC) and regions associated with sensorimotor processes (cluster-corrected p < 0.05). Conclusion: These results provide support for differential changes in insula connectivity as neural correlates of symptom improvement in MDD.
Adolescents’ Emotion Regulation Strategies Questionnaire: Initial Validation and Prospective Associations With Nonsuicidal Self-Injury and Other Mental Health Problems in Adolescence and Young Adulthood in a Swedish Youth Cohort

Although there is extensive research indicating the vital role of functional emotion regulation (ER) in healthy psychological development, such research has neglected examination of adolescents. One potential reason for this neglect is the lack of valid ER instruments developed specifically for adolescents. Further, the available ER instruments for adolescents usually require elaborate forms of cognitive reasoning about the internal sequences of cognitions and emotions. To address these limitations, we developed the Adolescents’ Emotion Regulation Strategies Questionnaire (AERSQ), a self-report instrument of adolescents’ commonly used ER strategies in daily life and examined its psychometric characteristics in a 10-year, three-wave cohort of Swedish youths (original N = 991, mean age = 13.7, 14.8, and 25.3 at waves 1, 2, and 3, respectively). Exploratory (wave 1 data) and confirmatory (wave 2 data) factor analyses revealed a five-factor structure for the AERSQ: rumination/negative thinking, positive reorientation, communication, distraction, and cultural activities. We observed gender differences for most ER strategies in adolescence. We also evaluated the associations between the AERSQ subscales and mental health (self-harm; psychological difficulties including hyperactivity, conduct problems, emotional problems, and peer problems; prosocial behavior; depression; anxiety; stress; flourishing; and life satisfaction) across the three time points. Rumination/negative thinking had the strongest relationships with these mental health indicators, both cross-sectionally and longitudinally, in both genders. Distraction and cultural activities were less related to mental health, especially prospectively. Although the AERSQ showed good test–retest reliability and predictive validity over a 10-year period, the low internal consistency of two of its subscales (distraction and cultural activities) indicates that it may benefit from further development both in terms of the included items and psychometric testing.
Is Animal-Assisted Therapy for Minimally Conscious State Beneficial? A Case Study

Objective The goal of this single case study was to qualitatively investigate the effects of animal-assisted therapy in a patient in a minimally conscious state. Method We present a 28-year-old female patient in a minimally conscious state following polytrauma after a sports accident leading to cerebral fat embolism causing multiple CNS ischemic lesions. She received eight animal-assisted therapy sessions and eight paralleled control therapy sessions over 4 weeks. We investigated the reactions of the patient during these sessions via qualitative behavior analysis. Results The patient showed a broader variability and higher quality of behavior during animal-assisted therapy compared to control therapy sessions. Conclusion The observed behavioral changes showed higher arousal and increased awareness in the presence of an animal. The presented case supports the assumption that animal-assisted therapy can be a beneficial treatment approach for patients in a minimally conscious state.
Parents’ Beliefs About Play and the Purpose of Preschool Education, Preschoolers’ Home Activity and Executive Functions

The purpose of the present study was to replicate and extend previous findings that depict a link between preschoolers’ home experience and EFs. It also examined Hungarian parents’ views about the purpose of preschool education and its relationship with their play beliefs. A total of 87 Hungarian preschoolers participated in neuropsychological testing of executive functioning (44 boys, 42 girls, one not reported; mean age = 62.37 months; SD = 8.33 months; age range = 47–80 months) and their parents (8male and 79 females; mean age = 37.73 years; SD = 5.64 years; age range = 22–63 years) filled in questionnaires. The finding from hierarchical regression analyses depicted that the frequency of pretend play the preschoolers engage in and parental play support beliefs were small to medium-sized predictors of children’s inhibitory control, after accounting for age and SES. Children’s frequency of participation in fine motor activities at home was a small but significant predictor of their visual-spatial working memory, after controlling for age and SES. Furthermore, results indicated that parents hold the belief that the development of social-emotional competence and children enjoying themselves instead of academic skills is the primary purpose of preschool education. To sum up, parental play support and preschoolers’ activities at home are important predictors for children’s EF skills.
USE OF SATELLITE WAVE DATA IN THE WORLDWAVES PROJECT

The demand for reliable information on wave conditions, in particular at coastal sites, is increasing. WorldWaves is a newly completed software package, developed by Fugro OCEANOR with funding from industry and within the framework of various European Commission sponsored contracts, notably EnviWave. The system simplifies the modelling of wave conditions in coastal waters, resulting in more timely, lower cost but reliable data. Thus, WorldWaves should be particularly beneficial in developing countries. In WorldWaves, the following are integrated under a single Matlab toolbox: · High quality long-term wave data offshore all global coasts. · Global bathymetric and coastline data. · Two shallow water wave models: SWAN, a third generation wave model and a backward ray-tracing model. · Sophisticated offshore and nearshore wave statistics toolboxes. · A geographic module allowing the user to easily zoom in on geographic maps together with tools to assist the user in setting up the model grid. · A bathymetry editing tool allowing easy editing of the bathymetric data. · A facility allowing users to easily import their own offshore wave data In this paper, we describe the role of satellite wave measurements in enhancing the quality of the final product with examples and applications from South America
Free Space Characteristics of Barley Leaf Slices

Measurements are described of free space content of barley leaf slices. It is shown that the leaf slices contain a Donnan free space of about 3 µ-equiv/g fresh weight of tissue at a concentration of 300 mN, together with a water free space occupying 0.21 ml/g fresh weight. The Donnan free space is shown to be located in cell walls, as in other tissues (beet discs, barley roots) but the water free space is largely due to cut or damaged cells, injected intercellular spaces, and surface films of solution. The results are discussed in relation to free space of intact leaves.
Eyes-free graph legibility: using skin-dragging to provide a tactile graph visualization on the arm

Recent technological advances have enabled novel tactile displays which have mainly focused on providing shorter sensations for notifications and/or simple messages. These have been primarily been used to enhance the user experience. In contrast, conveying information via data charts, such as a line graph, remains largely unexplored. To address this gap, we developed a tactile display prototype. Our prototype uses skin-dragging, a method to produce longer tactile perceptions from dragging a tip on the skin, as the primary means to convey the data. We postulate that if such an approach is successful, it could convey the data in eyes-free scenarios, an element common for on-the-go computing. In an experiment (n=12), we compare the recognition performance of graphs with two different skin-dragging properties, Full-Drag and Dot. The results show that participants performed both techniques equally well, but our Full-Drag technique was greatly preferred. We conclude with design guidelines for tactile displays that focus on graph representations.
A pipeline for multiparty volumetric video conferencing: transmission of point clouds over low latency DASH

The advent of affordable 3D capture and display hardware is making volumetric videoconferencing feasible. This technology increases the immersion of the participants, breaking the flat restriction of 2D screens, by allowing them to collaborate and interact in shared virtual reality spaces. In this paper we introduce the design and development of an architecture intended for volumetric videoconferencing that provides a highly realistic 3D representation of the participants, based on pointclouds. A pointcloud representation is suitable for real-time applications like video conferencing, due to its low-complexity and because it does not need a time consuming reconstruction process. As transport protocol we selected low latency DASH, due to its popularity and client-based adaptation mechanisms for tiling. This paper presents the architectural design, details the implementation, and provides some referential results. The demo will showcase the system in action, enabling volumetric videoconferencing using pointclouds.