Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-Term Occupancy Grid Prediction Using Recurrent Neural Networks

We tackle the long-term prediction of scene evolution in a complex downtown scenario for automated driving based on Lidar grid fusion and recurrent neural networks (RNNs). A bird’s eye view of the scene, including occupancy and velocity, is fed as a sequence to a RNN which is trained to predict future occupancy. The nature of prediction allows generation of multiple hours of training data without the need of manual labeling. Thus, the training strategy and loss function are designed for long sequences of real-world data (unbalanced, continuously changing situations, false labels, etc.). The deep CNN architecture comprises convolutional long short-term memories (ConvLSTMs) to separate static from dynamic regions and to predict dynamic objects in future frames. Novel recurrent skip connections show the ability to predict small occluded objects, i.e. pedestrians, and occluded static regions. Spatio-temporal correlations between grid cells are exploited to predict multimodal future paths and interactions between objects. Experiments also quantity improvements to our previous network, a Monte Carlo approach, and literature.
ZnO Nanoparticles Catalyst in the Synthesis of Bioactive Fused Pyrimidines as Anti-breast Cancer Agents Targeting VEGFR-2.

BACKGROUND Pyrimidines emerged as a remarkable class of heterocyclic compounds that have reinforced the pharmaceutical chemistry with various bioactive antitumor agents. Moreover, pyrimidine scaffold displayed VEGFR-2 inhibitory activity. Also, nano-sized catalysts are used in organic reactions in order to speed up the catalytic process. OBJECTIVE We were interested herein to synthesize a new series of fused pyrimidines using ZnO(NPs) to investigate their antitumor efficiency against breast MCF7 cancer and their VEGFR- 2 inhibition properties. METHOD A simple and efficient method for the synthesis of fused pyrimidines was developed using zinc oxide nanoparticles ZnO(NPs) in refluxing ethanol. RESULTS The proposed structures of all new fused pyrimidines are in agreement with their spectral data. Antitumor evaluation of newly fused pyrimidine derivatives against breast MCF-7 cancer was performed. It was apparent that the 2-phenylpyrazolo[1,5-a]pyrimidine derivatives 9a (IC50 = 9.12±1.16 µg/ml), 9c (IC50 = 9.10±1.07 µg/ml) and 9d (IC50 = 9.60±1.22 µg/ml) exhibited equipotent antitumor activity as Tamoxifen (IC50 = 9.11±0.90 µg/ml). Also, the inhibitory activity of the novel fused pyrimidine derivatives on VEGFR-2 as well as Tamoxifen was determined using breast cancer cell line MCF-7. The data was obvious that 2-phenylpyrazolo[1,5-a]pyrimidine derivatives 9a, 9c and 9d exhibited noticeable VEGFR-2 inhibitory effect with % inhibition ranging from 80-84 % versus Tamoxifen 93.5%. CONCLUSION We succeeded in this context to synthesize new fused pyrimidines using ZnO(NPs) as anti-breast cancer agents targeting VEGFR-2.
DFF-DEN: Deep Feature Flow with Detail Enhancement Network for Hand Segmentation in Depth Video

Recently, researches are emerging to extend CNN-based segmentation approaches from still image to video. Directly applying per-frame based image segmentation networks on video is not efficient. To address this issue, a promising direction is to explore the video continuity. A state-of-the-art approach called Deep Feature Flow (DFF) runs the segmentation network only on sparse key frames and propagates feature maps to other frames via cross-frame motion. However, such approach does not work well for hand segmentation in a video as it is not robust to hand posture change. In this paper, we propose to incorporate a light-weight detail enhancement network (DEN) into the DFF framework to achieve robustness against cross-frame motion and hand posture change. Experimental results on a public depth video dataset, FingerPaint, demonstrate that our approach achieves higher segmentation accuracy than the DFF-based approach with similar speedups against the per-frame based video hand segmentation approach.
RANIBIZUMAB VERSUS VERTEPORFIN PHOTODYNAMIC THERAPY IN ASIAN PATIENTS WITH MYOPIC CHOROIDAL NEOVASCULARIZATION

Supplemental Digital Content is Available in the Text. Ranibizumab 0.5 mg administered over 12 months was efficacious and well-tolerated in Asian patients with visual impairment due to myopic choroidal neovascularization. Ranibizumab treatment guided by visual acuity stabilization or disease activity criteria resulted in statistically superior efficacy compared with verteporfin photodynamic therapy.
Temporal Motion Smoothness and the Impact of Frame Rate Variation on Video Quality

There has been a strong recent trend to improve the perceptual quality-of-experience of viewers by expanding the spatial resolution, dynamic range, color gamut, and frame rate of videos. Conceptually, increasing video frame rate should create a benefit of smoother perception of motion. However, how to measure motion smoothness is not a well resolved problem. In this study, we measure the smoothness of motion by examining the local phase correlation of complex wavelet coefficients along the temporal direction. Our experiments based on subjective-rated databases show that this novel measure provides a new means to capture the impact of frame rate on video quality, and demonstrates strong promise at improving the performance of objective video quality assessment models.
Anatomy and techniques in posterior urethroplasty

Given its complex anatomy, injury to the posterior urethra may result in a number of reconstructive challenges. With the appropriate operative planning and experience, surgical repair can be very successful. This review discusses the applicable techniques for the perineal approach to posterior urethral stenosis, including bulbomembranous anastomosis for pelvic fracture urethral injury and repair of vesicourethral anastomotic stenosis (VUAS) following prostate surgery. The advanced techniques reviewed include an adaptation allowing a bulbar artery sparing approach to posterior urethroplasty and an intrasphincteric urethroplasty procedure which may allow continence preservation in patients with membranous urethral stenosis.
The Case for a Visual Discovery Assistant: A Holistic Solution for Accelerating Visual Data Exploration

Visualization is one of the most effective and widely-used techniques for understanding data. Yet, the growing use of visualizations for exploratory data analysis poses new demands beyond simply the graphical presentation and visualization authoring capabilities offered in existing tools. In particular, many data analysis tasks involve navigating large collections of visualizations to make sense of trends in data; at present, this navigation is done manually or programmatically. We outline a vision for an intelligent, interactive, understandable, and usable tool that can help automate this largely manual navigation: we call our tool VIDA 1 —short for VIsual Discovery Assistant. We argue that typical navigation tasks can be organized across two dimensions—overall goal and precision of speciﬁcation. We organize prior work—both our own work, as well as other ongoing work in this area—across these two dimensions, and highlight new research challenges. Together, addressing these challenges underlying VIDA can help pave the way for a comprehensive solution for removing the pain points in visual data exploration.
100+ Times Faster Video Completion by Optical-Flow-Guided Variational Refinement

Despite the higher video-completion quality that recently proposed methods have enabled for a wide variety of cases, their computational complexity remains a major concern. These methods typically frame video completion as an optimization problem over the whole spatiotemporal domain-a problem that is expensive to solve both in time and space. In this paper we propose a lighter-weight multipass video-completion pipeline that replaces global spatiotemporal optimization with simpler frame-by-frame motion reconstruction and refinement. We achieve a processing speed of 2.6 seconds per frame on Full HD content while delivering nearly state-of-the-art completion quality for a wide range of dynamic scenes captured using a free-moving camera. To validate the performance of our proposed method, we conducted a subjective comparison of different video-completion results for 26 test sequences from the DAVIS data set.
Smoothness Metrics in Complex Movement Tasks

Smoothness is a main characteristic of goal-directed human movements. The suitability of approaches quantifying movement smoothness is dependent on the analyzed signal's structure. Recently, activities of daily living (ADL) received strong interest in research on aging and neurorehabilitation. Such tasks have complex signal structures and kinematic parameters need to be adapted. In the present study we examined four different approaches to quantify movement smoothness in ADL. We tested the appropriateness of these approaches, namely the number of velocity peaks per meter (NoP), the spectral arc length (SAL), the speed metric (SM) and the log dimensionless jerk (LDJ), by comparing movement signals from eight healthy elderly (67.1a ± 7.1a) with eight healthy young (26.9a ± 2.1a) participants performing an activity of daily living (making a cup of tea). All approaches were able to identify group differences in smoothness (Cohen's d NoP = 2.53, SAL = 1.95, SM = 1.69, LDJ = 4.19), three revealed high to very high sensitivity (z-scores: NoP = 1.96 ± 0.55, SAL = 1.60 ± 0.64, SM = 3.41 ± 3.03, LDJ = 5.28 ± 1.52), three showed low within-group variance (NoP = 0.72, SAL = 0.60, SM = 0.11, LDJ = 0.71), two showed strong correlations between the first and the second half of the task execution (intra-trial R2s: NoP = 0.22 n.s., SAL = 0.33, SM = 0.36, LDJ = 0.91), and one was independent of other kinematic parameters (SM), while three showed strong models of multiple linear regression (R2s: NoP = 0.61, SAL = 0.48, LDJ = 0.70). Based on our results we make suggestion toward use examined smoothness measures. In total the log dimensionless jerk proved to be the most appropriate in ADL, as long as trial durations are controlled.
Informal caregiving patterns and trajectories of psychological distress in the UK Household Longitudinal Study

Abstract Background Approximately seven million people in the UK are engaged in informal caregiving. Informal caregivers are at risk of poorer mental and physical health. However, less is known about how the relationship between the informal caregiving and psychological distress changes over time. The aim of this study was to investigate longitudinal associations between the informal caregiving and psychological distress amongst UK men and women aged 16+. Methods Data were analysed from the UK Household Longitudinal Study (UKHLS, n = 9368), a nationally representative study of UK households. Longitudinal linear mixed modelling was used to estimate associations between the longitudinal patterns of informal caregiving (non-caregiver/one episode of 1–2 years/intermittent caregiving/3+ years caregiving) and trajectories of psychological distress across seven waves of UKHLS data. Results Informal caregiving was not associated with psychological distress for men. Women engaged in long-term (⩾3 years) or intermittent caregiving had higher levels of psychological distress at the point of initiation, compared with women who were not caregivers throughout the study period (3+ years caregiver: regression coefficient 0.48, 95% confidence interval (CI) 0.07–0.89; intermittent caregiver: regression coefficient 0.47, 95% CI 0.02–0.92). Trajectories of psychological distress changed little over time, suggesting a plateau effect for these caregiving women. Conclusions Women engaged in long-term or repeated shorter episodes of informal caregiving reported more symptoms of psychological distress than non-caregiving women. Given the increased risk of reporting psychological distress and the increasing importance of the informal care sector, the risk of poorer mental health of informal caregivers should be a priority for public health.
The Reproducibility and External Validity of a Modified Rugby League Movement-Simulation Protocol for Interchange Players.

PURPOSE To assess the reliability and external validity of a rugby league movement-simulation protocol for interchange players (RLMSP-i) that was adapted to include physical contact between participants. METHODS A total of 18 rugby players performed 2 trials of a modified RLMSP-i, 7 d apart. The simulation was conducted outdoors on artificial turf with movement speeds controlled using an audio signal. Microtechnology was used to measure locomotive and accelerometer (ie, PlayerLoad™) metrics for both bouts (∼23 min each) alongside heart rate (HR) and rating of perceived exertion (RPE). RESULTS Reported for each bout, total distance (102 [3] m·min-1 and 101 [3] m·min-1), low-speed distance (77 [3] m·min-1 and 79 [4] m·min-1), high-speed distance (25 [3] m·min-1 and 22 [4] m·min-1), PlayerLoad (10 [1] AU·min-1 and 10 [1] AU·min-1), PlayerLoad slow (3.2 [0.6] AU·min-1 and 3.2 [0.6] AU·min-1), 2-dimensional PlayerLoad (6.0 [0.9] AU·min-1 and 5.7 [0.8] AU·min-1), and HR (86 [5]%HRmax and 84 [6]%HRmax) were similar to match play. The coefficient of variation (CV%) for locomotive metrics ranged from 1.3% to 14.4%, accelerometer CV% 4.4% to 10.0%, and internal load 4.8% to 13.7%. All variables presented a CV% less than the calculated moderate change during 1 or both bouts of the simulation except high-speed distance, percentage of the participant's peak HR, and RPE. CONCLUSION The modified RLMSP-i offers a reliable simulation to investigate influences of training and nutrition interventions on the movement and collision activities of rugby league interchange players.
Evidence of Cerebellar Involvement in the Onset of a Manic State

We described the cerebello-cerebral functional connectivity in a subject who developed a manic state after a cerebellar lesion. Whole brain investigation, performed by means of an advanced MRI examination, evidenced an isolated lesion involving the left lobules VI, VIIa (crus I), and IX and the posterior area of the vermis. The cerebello-cerebral functional connectivity analysis detected a pattern of altered connectivity in specific areas of the prefrontal-striatal-thalamic circuits that are typically altered in bipolar subjects during the manic state. Specifically, a pattern of hypo-connectivity was found between the cerebellum and cerebral regions known to be implicated in emotion modulation and social interaction. Conversely, a pattern of hyper-connectivity was found between the cerebellum and posterior cerebral cortical regions that are involved in sensorimotor functions. The present study represents the first evidence that dysregulation of cerebral networks consequent to a cerebellar lesion is at the root of bipolar disorder, at least the manic state, and provides a new framework for interpreting cerebellar modulation in the regulation of mood in specific psychiatric conditions.
LSTM Multiple Object Tracker Combining Multiple Cues

Traditional methods for multiple object tracking usually consider features at image level and reason about simple space and time constraints. However, in this paper we propose a multiple object tracker based on LSTM network to learn temporally correlated features. Our tracker learns features on velocity, position and appearance aspects of the objects to improve tracking accuracy. In order to deal with occlusion problems, velocity model is also used to predict the lost detections for the occluded identities. Besides, pre-association is performed before appearance model to improve the efficiency of calculation. Final association problem is solved by taking the best match. Experiments in MOT17 dataset show that our tracker achieves leading performance compared to other state-of-the-art algorithms.
Possible Mechanisms of Green Tea and Its Constituents against Cancer

A number of epidemiological, clinical, and experimental researches have indicated that administration of green tea appears to have anti-cancer activity. According to findings of laboratory cell culture studies, a diverse mechanism has been observed underlying the effects of green tea catechins against cancer. These mechanisms include anti-oxidant activity, cell cycle regulation, receptor tyrosine kinase pathway inhibition, immune system modulation, and epigenetic modification control. This review discusses the results of these studies to provide more insight into the effects of green tea administration on cancers observed to date in this research field.
Analysis of Sequence Polymorphism of LINEs and SINEs in Entamoeba histolytica

The goal of this dissertation is to study the sequence polymorphism in retrotransposable elements of Entamoeba histolytica. The Quasispecies theory, a concept of equilibrium (stationary), has been used to understand the behaviour of these elements. Two datasets of retrotransposons of Entamoeba histolytica have been used. We present results from both datasets of retrotransposons (SINE1s) of E. histolytica. We have calculated the mutation rate of EhSINE1s for both datasets and drawn a phylogenetic tree for newly determined EhSINE1s (dataset II). We have also discussed the variation in lengths of EhSINE1s for both datasets. Using the quasispecies model, we have shown how sequences of SINE1s vary within the population. The outputs of the quasispecies model are discussed in the presence and the absence of back mutation by taking different values of fitness. From our study of Non-long terminal repeat retrotransposons (LINEs and their non-autonomous partner's SINEs) of Entamoeba histolytica, we can conclude that an active EhSINE can generate very similar copies of itself by retrotransposition. Due to this reason, it increases mutations which give the result of sequence polymorphism. We have concluded that the mutation rate of SINE is very high. This high mutation rate provides an idea for the existence of SINEs, which may affect the genetic analysis of EhSINE1 ancestries, and calculation of phylogenetic distances.
Non-blind Image Restoration Based on Convolutional Neural Network

Blind image restoration processors based on convolutional neural network (CNN) are intensively researched because of their high performance. However, they are too sensitive to the perturbation of the degradation model. They easily fail to restore the image whose degradation model is slightly different from the trained degradation model. In this paper, we propose a non-blind CNN-based image restoration processor, aiming to be robust against a perturbation of the degradation model compared to the blind restoration processor. Experimental comparisons demonstrate that the proposed non-blind CNN-based image restoration processor can robustly restore images compared to existing blind CNN-based image restoration processors.
An End-to-End Text-Independent Speaker Identification System on Short Utterances

In the ﬁeld of speaker recognition, text-independent speaker i-dentiﬁcation on short utterances is still a challenging task, since it is rather tough to extract a robust and dicriminative speaker feature in short duration condition. This paper explores an end-to-end speaker identiﬁcation system, which maps utterances to a speaker identity subspace where the similarity of speakers can be measured by Euclidean distance. To be speciﬁc, we apply stacked gated recurrent unit (GRU) architectures to extract utterance-level feature. Then it is assumed that one’s various utterances can be viewed as transformations of a single object in an ideal speaker identity subspace. Based on this assumption, the residual convolution neural network (ResCNN) architecture is utilized to model the transformation, and the whole system is jointly optimized by speaker identity subspace loss. Experimental results demonstrate the effectiveness of our proposed system and superiroity over pervious methods. For example, the GRU learned feature reduces the equal error rate by 27.53% relatively and the speaker identity subspace loss further brings 7.22% relative reduction compared to softmax loss.
Patient- and Nutrition-Derived Outcome Risk Assessment Score as a Predictor of Mortality in Critically Ill Surgical Patients: A Retrospective, Single-Center Observational Study.

BACKGROUND The Patient- And Nutrition-Derived Outcome Risk Assessment (PANDORA) was recently validated for predicting mortality in hospitalized patients; however, its utility in the intensive care unit (ICU) remains unknown. METHODS We investigated whether PANDORA is associated with 30, 90, and 180 day mortality in critically ill surgical patients by performing logistic regressions, controlling for age, sex, race, body mass index, macronutrient deficit, and length of stay. The area under the receiver operating characteristic curves (AUC) of PANDORA vs Acute Physiology and Chronic Health Evaluation (APACHE) II scores for mortality at each time point were also compared. RESULTS 312 patients comprised the analytic cohort. PANDORA was associated with mortality at 30 (OR 1.08; 95% CI 1.04-1.13; P < .001), 90 (OR 1.09; 95% CI 1.03-1.12; P < .001), and 180 days (OR 1.10; 95% CI 1.06-1.15; P < .001). PANDORA and APACHE II were comparable for mortality prediction at 30 (AUC: 0.69, 95% CI 0.62-0.76 vs 0.74, 95% CI 0.67-0.81; P = .29), 90 (AUC: 0.71, 95% CI 0.63-0.77 vs 0.74, 95% CI 0.67-0.80; P = .52), and 180 days (AUC: 0.73, 95% CI 0.67-0.79 vs 0.75, 95% CI 0.69-0.81; P = .66). CONCLUSION In surgical ICU patients, PANDORA was associated with mortality and was comparable with APACHE II for mortality prediction at 30, 90, and 180 days after initiation of care. Prospective studies are needed to assess whether nutrition support, stratified by PANDORA scores, can improve outcomes in surgical ICU patients.
Remodeling of lumbar motor circuitry remote to a thoracic spinal cord injury promotes locomotor recovery

Retrogradely-transported neurotrophin signaling plays an important role in regulating neural circuit specificity. Here we investigated whether targeted delivery of neurotrophin-3 (NT-3) to lumbar motoneurons (MNs) caudal to a thoracic (T10) contusive spinal cord injury (SCI) could modulate dendritic patterning and synapse formation of the lumbar MNs. In vitro, Adeno-associated virus serotype two overexpressing NT-3 (AAV-NT-3) induced NT-3 expression and neurite outgrowth in cultured spinal cord neurons. In vivo, targeted delivery of AAV-NT-3 into transiently demyelinated adult mouse sciatic nerves led to the retrograde transportation of NT-3 to the lumbar MNs, significantly attenuating SCI-induced lumbar MN dendritic atrophy. NT-3 enhanced sprouting and synaptic formation of descending serotonergic, dopaminergic, and propriospinal axons on lumbar MNs, parallel to improved behavioral recovery. Thus, retrogradely transported NT-3 stimulated remodeling of lumbar neural circuitry and synaptic connectivity remote to a thoracic SCI, supporting a role for retrograde transport of NT-3 as a potential therapeutic strategy for SCI.