Miracle-dz/UniFAR-FTUs huggingface dataset:
Topology preserving surface extraction using adaptive subdivision

We address the problem of computing a topology preserving isosurface from a volumetric grid using Marching Cubes for geometry processing applications. We present a novel topology preserving subdivision algorithm to generate an adaptive volumetric grid. Our algorithm ensures that every grid cell satisfies two local geometric criteria: a complex cell criterion and a star-shaped criterion. We show that these two criteria are sufficient to ensure that the surface extracted from the grid using Marching Cubes has the same genus and connectedness as that of the exact isosurface. We use our subdivision algorithm for accurate boundary evaluation of CSG combinations of polyhedra and low degree algebraic primitives, translational motion planning, model simplification and remeshing. The running time of our algorithm varies between a few seconds for simple models composed of a few thousand triangles to tens of seconds for complex polyhedral models represented using hundreds of thousands of triangles.
An Algorithm for Automatic Road Asphalt Edge Delineation from Mobile Laser Scanner Data Using the Line Clouds Concept

Accurate road asphalt extent delineation is needed for road and street planning, road maintenance, and road safety assessment. In this article, a new approach for automatic roadside delineation is developed based on the line clouds concept. The method relies on line cloud grouping from point cloud laser data. Using geometric criteria, the initial 3D LiDAR point data is structured in lines covering the road surface. These lines are then grouped according to a set of quasi-planar restriction rules. Road asphalt edge limits are extracted from the end points of lines belonging to these groups. Finally a two-stage smoothing procedure is applied to correct for edge occlusions and other anomalies. The method was tested on a 2.1 km stretch of road, and the results were checked using a RTK-GNSS measured dataset as ground truth. Correctness and completeness were 99% and 97%, respectively.
The impact of a sports vision training program in youth field hockey players.

The aim of this study was to investigate whether a sports vision training program improves the visual performance of youth male field hockey players, ages 12 to 16 years, after an intervention of six weeks compared to a control group with no specific sports vision training. The choice reaction time task at the D2 board (Learning Task I), the functional field of view task (Learning Task II) and the multiple object tracking (MOT) task (Transfer Task) were assessed before and after the intervention and again six weeks after the second test. Analyzes showed significant differences between the two groups for the choice reaction time task at the D2 board and the functional field of view task, with significant improvements for the intervention group and none for the control group. For the transfer task, we could not find statistically significant improvements for either group. The results of this study are discussed in terms of theoretical and practical implications. Key pointsPerceptual training with youth field hockey playersCan a sports vision training program improve the visual performance of youth male field hockey players, ages 12 to 16 years, after an intervention of six weeks compared to a control group with no specific sports vision training? The intervention was performed in the "VisuLab" as DynamicEye(®) SportsVision Training at the German Sport University Cologne.We ran a series of 3 two-factor univariate analysis of variance (ANOVA) with repeated measures on both within subject independent variables (group; measuring point) to examine the effects on central perception, peripheral perception and choice reaction time.The present study shows an improvement of certain visual abilities with the help of the sports vision training program.
Lid opening and conformational stability of T1 Lipase is mediated by increasing chain length polar solvents

The dynamics and conformational landscape of proteins in organic solvents are events of potential interest in nonaqueous process catalysis. Conformational changes, folding transitions, and stability often correspond to structural rearrangements that alter contacts between solvent molecules and amino acid residues. However, in nonaqueous enzymology, organic solvents limit stability and further application of proteins. In the present study, molecular dynamics (MD) of a thermostable Geobacillus zalihae T1 lipase was performed in different chain length polar organic solvents (methanol, ethanol, propanol, butanol, and pentanol) and water mixture systems to a concentration of 50%. On the basis of the MD results, the structural deviations of the backbone atoms elucidated the dynamic effects of water/organic solvent mixtures on the equilibrium state of the protein simulations in decreasing solvent polarity. The results show that the solvent mixture gives rise to deviations in enzyme structure from the native one simulated in water. The drop in the flexibility in H2O, MtOH, EtOH and PrOH simulation mixtures shows that greater motions of residues were influenced in BtOH and PtOH simulation mixtures. Comparing the root mean square fluctuations value with the accessible solvent area (SASA) for every residue showed an almost correspondingly high SASA value of residues to high flexibility and low SASA value to low flexibility. The study further revealed that the organic solvents influenced the formation of more hydrogen bonds in MtOH, EtOH and PrOH and thus, it is assumed that increased intraprotein hydrogen bonding is ultimately correlated to the stability of the protein. However, the solvent accessibility analysis showed that in all solvent systems, hydrophobic residues were exposed and polar residues tended to be buried away from the solvent. Distance variation of the tetrahedral intermediate packing of the active pocket was not conserved in organic solvent systems, which could lead to weaknesses in the catalytic H-bond network and most likely a drop in catalytic activity. The conformational variation of the lid domain caused by the solvent molecules influenced its gradual opening. Formation of additional hydrogen bonds and hydrophobic interactions indicates that the contribution of the cooperative network of interactions could retain the stability of the protein in some solvent systems. Time-correlated atomic motions were used to characterize the correlations between the motions of the atoms from atomic coordinates. The resulting cross-correlation map revealed that the organic solvent mixtures performed functional, concerted, correlated motions in regions of residues of the lid domain to other residues. These observations suggest that varying lengths of polar organic solvents play a significant role in introducing dynamic conformational diversity in proteins in a decreasing order of polarity.
Rainfall frequency analysis using block maxima and peaks over threshold approaches.

In the present study extreme rainfall frequency analysis was performed using block maxima (BM) and peaks over threshold (POT) approaches based on daily rainfall data gathered from three meteorological stations in Greece (Larisa, Agxialos, Trikala). In the first method, 9 different probability distributions (2 and 3 parameter distributions) were fitted to the samples (that were previously checked for randomness, trends and change points in the mean) in order to estimate rainfall depths for high return periods. According to diagnostic plots and Kolmogorov-Smirnov goodness of fit test, the fitting was acceptable for all the distributions that were considered in the three stations. However, the 3-parameter distributions and more specifically GEV for Larisa and Trikala and 3-parameter Lognormal for Agxialos, had a better fitting in the extreme values and could be considered more suitable for statistical modeling in these three stations. In the POT approach a suitable threshold was selected based on plots and statistical indexes. The excesses were modeled using the Generalized Pareto (GP) and a mixed model of Poisson and GP distributions. The estimated rainfall depths in this approach show similarities between the two models, as well as with those of the 3 parameter distributions used in the BM approach.
Subclinical Coronary and Aortic Atherosclerosis Detected by Magnetic Resonance Imaging in Type 1 Diabetes With and Without Diabetic Nephropathy

Background— Patients with type 1 diabetes and nephropathy maintain an excess cardiovascular mortality compared with diabetic patients with normoalbuminuria. We sought to evaluate coronary and aortic atherosclerosis in a cohort of asymptomatic type 1 diabetic patients with and without diabetic nephropathy using cardiovascular magnetic resonance imaging. Methods and Results— In a cross-sectional study, 136 subjects with long-standing type 1 diabetes without symptoms or history of cardiovascular disease, including 63 patients (46%) with nephropathy and 73 patients with normoalbuminuria, underwent cardiovascular magnetic resonance imaging. All subjects underwent cardiac exercise testing and noninvasive tests for peripheral artery disease and autonomic neuropathy. Coronary artery stenoses were identified in 10% of subjects with nephropathy (versus 0% with normoalbuminuria; P=0.007). Coronary plaque burden, expressed as right coronary artery mean wall thickness (1.7±0.3 versus 1.3±0.2 mm; P<0.001) and maximum right coronary artery wall thickness (2.2±0.5 versus 1.6±0.3 mm; P<0.001), was greater in subjects with nephropathy. The prevalence of thoracic (3% versus 0%; P=0.28) and abdominal aortic plaque (22% versus 16%; P=0.7) was similar in both groups. Subjects with and without abdominal aortic plaques had similar coronary plaque burden. Conclusions— In asymptomatic type 1 diabetes, cardiovascular magnetic resonance imaging reveals greater coronary plaque burden in subjects with nephropathy compared with those with normoalbuminuria.
Effects of reducing the number of candidate tasks in voluntary task switching

Recently, Demanet and Liefooghe (2014; Experiment 3) reported an experiment on voluntary task switching (VTS) in which the number of candidate tasks to choose from was reduced from 4 to 2 before participants indicated their task choice. This procedure was intended to prevent participants from choosing a task in advance of the presentation of a prompt to do so. This procedure is highly similar to a procedure recently employed by Kleinsorge and Scheil (2013) in a study of cued task switching which yielded evidence for a selective facilitation of task switches by a reduction of the number of tasks to two. In order to examine whether a similar effect would also be observed with VTS, we conceptually replicated the experiment of Demanet and Liefooghe (2014) with an additional control condition in which the number of tasks was not reduced. In this experiment, no evidence for a facilitation of task switching could be observed, pointing to a functional divergence between explicit task cues and the internally generated cues involved in VTS. In addition, we observed evidence for a selective advantage of forced switch trials over repetition-possible trials that was largely independent of the duration of the preparation interval. This effect was accompanied by a massive increase of task indication times in conditions with a reduced number of tasks, suggesting that this manipulation resulted in a pronounced change in the way participants performed voluntary task switches.
MedleyDB: A Multitrack Dataset for Annotation-Intensive MIR Research

We introduceMedleyDB: a dataset of annotated, royaltyfree multitrack recordings. The dataset was primarily developed to support research on melody extraction, addressing important shortcomings of existing collections. For each song we provide melody f0 annotations as well as instrument activations for evaluating automatic instrument recognition. The dataset is also useful for research on tasks that require access to the individual tracks of a song such as source separation and automatic mixing. In this paper we provide a detailed description of MedleyDB, including curation, annotation, and musical content. To gain insight into the new challenges presented by the dataset, we run a set of experiments using a state-of-the-art melody extraction algorithm and discuss the results. The dataset is shown to be considerably more challenging than the current test sets used in the MIREX evaluation campaign, thus opening new research avenues in melody extraction research.
Usefulness of Magnetic Resonance-Derived Quantitative Measurements of Cerebral Blood Flow and Volume in Prediction of Infarct Growth in Hyperacute Stroke

Background and Purpose The identification of the tissue at risk for infarction remains challenging in stroke patients. In this study, we evaluated the value of quantitative cerebral blood flow (CBF) and cerebral blood volume (CBV) measurements in the prediction of infarct growth in hyperacute stroke. Methods Fluid-attenuated inversion recovery (FLAIR), diffusion-weighted (DW), and gradient-echo echo-planar perfusion-weighted (PW) sequences were obtained in 66 patients within 6 hours of stroke onset; ischemia was confirmed on follow-up FLAIR images. We delineated the following: (1) the initial infarct on DW images, (2) the area of hemodynamic disturbance on mean transit time (MTT) maps, and (3) the final infarct on follow-up FLAIR images. MTT, CBF, and CBV were calculated in the following areas: area of initial infarct (INF), area of infarct growth (IGR, final minus initial infarct), the hemodynamically disturbed area that remained viable (OLI, hemodynamic disturbance minus final infarct), and all contralateral mirror regions. Results Compared with mirror regions, the MTT in abnormal areas was always prolonged. The respective mean±SD CBF and CBV values were as follows: for INF, 28±16 mL/min per 100 g and 6.9±2.7%; for IGR, 36±20 mL/min per 100 g and 8.9±3.1%; for OLI, 50±17 mL/min per 100 g and 11.2±3%; and for mirror regions, 64±23 mL/min per 100 g and 8.7±2.5%. The CBV and CBF values were significantly different between all abnormal areas (except for the CBF between INF and IGR). In the area of DW/PW mismatch, a combined CBF or CBV threshold of 35 or 8.2, respectively, predicted evolution to infarction with a sensitivity of 81% and a specificity of 76%. Conclusions Quantitative measurements of CBF and CBV in hyperacute stroke may help to predict infarct growth and to select the subjects who will benefit from thrombolysis.
Using a classifier to track the edge of a conveyor belt

Ensuring that a conveyor belt runs true on an X-ray transmission (XRT) particle sorting system is important for a number of reasons. It limits the damage to the edge of the belt, reduces wear to the conveyor and minimises material spillage. Knowing where the belt is also defines the region of interest (ROI) for the applied algorithm, thus reducing false positives outside the ROI. In addition, correct belt tracking ensures that particles are all contained within the detectable area, avoiding the loss of material. Therefore, ensuring correct conveyor belt tracking can greatly impact the cost and efficiency of the sorting system. This paper presents a novel method for tracking the edge of a conveyor belt in a dual energy X-ray transmission (DE-XRT) sorting system. Using a classifier to determine where the belt edge is, the position of the belt is estimated with a pixel error of less than 15 pixels across all test images. An error of this order is expected as the belt edge is 18 pixels wide in the image. The current method, which is not affected by particles lying against the belt, is shown to be better that the previous approach using morphology, which exhibited poorer tracking accuracy when particles touch the belt. In addition, no additional sensors need to be installed and the belt does not need to be specially manufactured, reducing the cost of the conveyor system.
miR-K12-7-5p Encoded by Kaposi's Sarcoma-Associated Herpesvirus Stabilizes the Latent State by Targeting Viral ORF50/RTA

Seventeen miRNAs encoded by Kaposi's sarcoma-associated herpesvirus (KSHV) have been identified and their functions have begun to be characterized. Among these miRNAs, we report here that miR-K12-7 directly targets the replication and transcription activator (RTA) encoded by open reading frame 50. We found that miR-K12-7 targeted the RTA 3′ untranslated region (RTA3′UTR) in a seed sequence-dependent manner. miR-K12-7-5p derived from miR-K12-7 mediates the inhibition of RTA expression, and the mutation of the seed match site totally abrogated the inhibitory effect of miR-K12-7 on RTA3′UTR. The inhibition of RTA expression by miR-K12-7 was further confirmed in the latently KSHV-infected 293/Bac36 cell line through transient transfection of miR-K12-7 expression plasmid or specific inhibitor of miR-K12-7-5p, respectively. The transient transfection of miR-K12-7 into 293/Bac36 cells reduced RTA expression and the expression of the downstream early genes regulated by RTA, and also the production of progeny virus was significantly reduced after treatment with chemical inducers. Our study revealed that another miRNA, miR-K12-7-5p, targets the viral immediate early gene RTA and that this miRNA contributes to the maintenance of viral latency.
Robot Motion Planning Integrating Planning Strategies and Learning Methods

Robot motion planning in a dynamic cluttered workspace requires the capability of dealing with obstacles and deadlock situations. The paper analyzes situations where the robot is considered with its shape and size and it can only perceive the space through its local sensors. The robot explores the space using a planner based on an artificial potential field and incrementally learns a fast way to escape or prevent deadlock situations using a combination of sensor perceptions, field information and planner experience. The knowledge acquired is a high-level network useful for avoiding deadlock areas consisting of local minimum nodes, backtracking nodes and subgoal nodes.
ANN Based on IncCond Algorithm for MPP Tracker

In photovoltaic (PV) generation systems, to get the maximum of the solar output power is the essential part to raise the efficiency of the whole system. A new Artificial Neural Network (ANN) based algorithm for Maximum Power Point Tracking (MPPT) has been proposed in this work. By using the duty ratio data generated from the finest results of the traditional Incremental Conductance (IncCond) method as the neural network training data, and building the DC-DC boost tracker to test it in Saber simulation software, the simulation results are shown to clarity the effectiveness of the proposed method.
Distributed collaborative filtering with domain specialization

User data scarcity has always been indicated among the major problems of collaborative filtering recommender systems. That is, if two users do not share sufficiently large set of items for whom their ratings are known, then the user-to-user similarity computation is not reliable and a rating prediction for one user can not be based on the ratings of the other. This paper shows that this problem can be solved, and that the accuracy of collaborative recommendations can be improved by: a) partitioning the collaborative user data into specialized and distributed repositories, and b) aggregating information coming from these repositories. This paper explores a content-dependent partitioning of collaborative movie ratings, where the ratings are partitioned according to the genre of the movie and presents an evaluation of four aggregation approaches. The evaluation demonstrates that the aggregation improves the accuracy of a centralized system containing the same ratings and proves the feasibility and advantages of a distributed collaborative filtering scenario.
Soft landing control strategy for biped robot

The purpose of this paper was to present a soft landing control strategy for a biped robot to avoid and absorb the impulsive reaction forces (which weakens walking stability) caused by the landing impact between the swing foot and the ground. ,First, a suitable trajectory of the swing foot is preplanned to avoid the impulsive reaction forces in the walking direction. Second, the impulsive reaction forces of the landing impact are suppressed by the on-line trajectory modification based on the extended time-domain passivity control with admittance causality that has the reaction forces as inputs and the decomposed swing foot’s positions to trim off the forces as the outputs. ,The experiment data and results are described and analyzed, showing that the proposed soft landing control strategy can suppress the impulsive forces and improve walking stability. ,The main contribution is that a soft landing control strategy for a biped robot was proposed to deal with the impulsive reaction forces generated by the landing impact, which enhances walking stability.
DETECTION OF SIGNALS FROM COSMIC REIONIZATION USING RADIO INTERFEROMETRIC SIGNAL PROCESSING

Observations of the H i 21 cm transition line promises to be an important probe into the cosmic dark ages and epoch of reionization. One of the challenges for the detection of this signal is the accuracy of the foreground source removal. This paper investigates the extragalactic point source contamination and how accurately the bright sources (≳1 Jy) should be removed in order to reach the desired rms noise and be able to detect the 21 cm transition line. Here, we consider position and flux errors in the global sky model for these bright sources as well as the frequency independent residual calibration errors. The synthesized beam is the only frequency dependent term included here. This work determines the level of accuracy for the calibration and source removal schemes and puts forward constraints for the design of the cosmic reionization data reduction scheme for the upcoming low frequency arrays such as, Murchison Widefield Array, Precision Array to Probe Epoch of Reionization, etc. We show that in order to detect the reionization signal the bright sources need to be removed from the data sets with a positional accuracy of ∼0.1 arcsec. Our results also demonstrate that the efficient foreground source removal strategies can only tolerate a frequency independent antenna based mean residual calibration error of ≲0.2% in amplitude or ≲0. °2 in phase, if they are constant over each days of observations (6 hr). In future papers, we will extend this analysis to the power-spectral domain and also include the frequency-dependent calibration errors and direction-dependent errors (ionosphere, primary beam, etc.).
Strategyproof Computing: Systems Infrastructures for Self-Interested Parties

The widespread deployment of high-speed internet access is ushering in a new era of distributed computing, in which parties both contribute to a global pool of shared resources and access the pooled resources to support their own computing needs. We argue that system designers must explicitly address the self-interest of individual parties if these next-generation computing systems are to ﬂourish. We propose strategyproof computing , a vision for an open computing infrastructure in which resource allocation and negotiation schemes are incentive-compatible, and individual parties can treat other resources as their own. In this paper we outline key guiding principles for the vision of strategyproof computing, deﬁne the strategyproof computing paradigm, and lay out a systems-related research agenda.