Miracle-dz/UniFAR-FTUs huggingface dataset:
Stereo Matching by Filtering-Based Disparity Propagation

Stereo matching is essential and fundamental in computer vision tasks. In this paper, a novel stereo matching algorithm based on disparity propagation using edge-aware filtering is proposed. By extracting disparity subsets for reliable points and customizing the cost volume, the initial disparity map is refined through filtering-based disparity propagation. Then, an edge-aware filter with low computational complexity is adopted to formulate the cost column, which makes the proposed method independent on the local window size. Experimental results demonstrate the effectiveness of the proposed scheme. Bad pixels in our output disparity map are considerably decreased. The proposed method greatly outperforms the adaptive support-weight approach and other conditional window-based local stereo matching algorithms.
Dynamic visualization of large numbers of off-screen objects on mobile devices: an experimental comparison of wedge and overview+detail

Overview+Detail [25] and Wedge [16] have been proposed in the literature as effective approaches to resolve the off-screen objects problem on mobile devices. However, they have been studied with a small number of off-screen objects and (in most studies) with static scenarios, in which users did not have to perform any navigation activity. In this paper, we propose improvements to Wedge and Overview+Detail which are specifically aimed at simplifying their use in dynamic scenarios that involve large numbers of off-screen objects. We compare the effectiveness of the two approaches in the considered scenario with a user study, whose results show that Overview+Detail allows users to be faster in searching for off-screen objects and more accurate in estimating their location.
Relationship between polymorphism of cystathionine beta synthase gene and congenital heart disease in Chinese nuclear families.

OBJECTIVE To study the relationship between polymorphism of cystathionine beta synthase (CBS) gene and development of congenital heart disease (CHD). METHODS One hundred and twenty-seven CHD case-parent triads were recruited from Liaoning Province as patient group, and 129 healthy subjects without family history of birth defect were simultaneously recruited as control group together with their biological parents. For all subjects the polymorphism of CBS gene G919A locus was examined by PCR-ARMS method. RESULTS The frequencies of three genotypes (w/w, w/m, and m/m) in control group were 27.2%, 58.4%, and 14.4%, respectively, with no significant difference in gender. A significant difference in the allele frequency was found between CHD patients and controls, the wild allele frequency was 67.9% in patients and 55.7% in controls. CHD parents' genotype distribution was significantly different from that in controls. Further comparison of each type of CHD showed that genotype frequencies in several CHD subtypes were significantly different from those in their corresponding controls. The results of TDT analysis showed that no allele transmission disequilibrium existed in CHD nuclear families. CONCLUSIONS CBS gene G919A mutation is associated with the development of CHD, and the mutated allele may decrease the risk of CHD.
A 2D Finite Element Thermal Model of a Three-Phase-Inverter Heat Sink

This paper presents the analysis and simulation of a three-phase voltage-source inverter. The inverter is driven using space vector modulation and it has a dead time of 2 ? s. During this simulation, power losses on the power electronic switches are calculated and used on a thermal model. The thermal conduction equation was solved to predict the temperature distribution. The finite element numerical method was used to solve the thermal conduction equation. A C code finite element thermal model was programmed.
Pitavastatin increases HDL particles functionally preserved with cholesterol efflux capacity and antioxidative actions in dyslipidemic patients.

AIM Although statins increase the plasma concentration of high-density lipoprotein cholesterol (HDL-C), it has not been elucidated whether the increased HDL particles possess normal antiatherosclerotic properties. Pitavastatin functions to increase the plasma HDL-C level and decrease the lowdensity lipoprotein cholesterol (LDL-C) level. In the present study, we sought to examine the qualitative changes in HDL during pitavastatin treatment. METHODS A total of 30 patients with dyslipidemia were treated with 2 mg of pitavastatin for four weeks. The cholesterol efflux capacity and activities of the antioxidative enzymes paraoxonase-1 (PON-1) and platelet-activating factor acetylhydrolase (PAF-AH) were evaluated using polyethethylene glycol-treated HDL fractions before and after pitavastatin treatment. RESULTS Pitavastatin treatment decreased the serum LDL-C level by 39% and increased the serum HDL-C level by 9% (p＜0.05). In addition, pitavastatin increased the phospholipid content of HDL by 7.8% (p＜0.05). The pitavastatin-induced increase in the HDL-C level coincided with an increase in the cholesterol efflux capacity of the isolated HDL fraction of 8.6% (p＜0.05). The post-pitavastatin treatment activity of HDL-associated PON-1 (paraoxonase and arylesterase) was increased by 9% (p＜0.05) and 11% (p＜0.05), respectively, while the HDL-associated PAF-AH activity was not affected by pitavastatin. CONCLUSIONS In addition to its LDL-C-lowering effects, pitavastatin elevates the HDL-C level and enhances the cholesterol efflux capacity and antioxidative properties of HDL. Pitavastatin therefore increases the amount of functional HDL without attenuating HDL quality.
Consistent Adjacency-Spectral Partitioning for the Stochastic Block Model When the Model Parameters Are Unknown

For random graphs distributed according to a stochastic block model, we consider the inferential task of partioning vertices into blocks using spectral techniques. Spectral partioning using the normalized Laplacian and the adjacency matrix have both been shown to be consistent as the number of vertices tend to infinity. Importantly, both procedures require that the number of blocks and the rank of the communication probability matrix are known, even as the rest of the parameters may be unknown. In this article, we prove that the (suitably modified) adjacency-spectral partitioning procedure, requiring only an upper bound on the rank of the communication probability matrix, is consistent. Indeed, this result demonstrates a robustness to model mis-specification; an overestimate of the rank may impose a moderate performance penalty, but the procedure is still consistent. Furthermore, we extend this procedure to the setting where adjacencies may have multiple modalities and we allow for either directed or undirected graphs.
Study of ship speed regimes in the Arctic sea ice conditions

An increase of commercial navigation in the Arctic along the Northern Sea routes will involve the use of large-capacity vessels of high ice-class during the non-escorted transit. To ensure the safety of Arctic navigation, it is necessary to have unbiased data on the influence of ice thickness on vessels’ speed and maneuverability. The paper suggests using a geoinformation system which includes data on speed and routes of the vessels of various capacities, as well as data of remote sensing of the earth about ice conditions. Two parts of traditional routes in the western part of the Russian Arctic were considered: the sea crossing from the Barents Sea to the Kara Sea through the Kara Strait and the transition from the Barents Sea to the Kara Sea through the Cape of Desire. A joint study of this data (layers) on the example of winter navigation of 2018 provides detailed information on the trends of speed reduction of ships under the conditions of fully consolidated ice. Based on the results of the study, the results are presented for four groups of vessels with different gross tonnage, capacity, ice pass and draft. To compare the results, the measured velocities were normalized to relative ones, which made it possible to identify common dependencies and trends. The availability of archival data on measurements of ice thickness in the geographic area under study and the predictive models for increasing ice thickness during the winter time mad it possible to develop adequate methods aimed at estimating the change in the properties of ice by varying the speed of vessels of various classes on the routes in the water area of the Northern Sea Route. Statistical processing of vessel speed in the ice fields made it possible to identify the sameness of the speed-reduction trends for the main groups of vessels and the distinctive features associated with the vessel’s power and the use of icebreaker support.
Leases: an efficient fault-tolerant mechanism for distributed file cache consistency

Caching introduces the overhead and complexity of ensuring consistency, reducing some of its performance benefits. In a distributed system, caching must deal with the additional complications of communication and host failures. Leases are proposed as a time-based mechanism that provides efficient consistent access to cached data in distributed systems. Non-Byzantine failures affect performance, not correctness, with their effect minimized by short leases. An analytic model and an evaluation for file access in the V system show that leases of short duration provide good performance. The impact of leases on performance grows more significant in systems of larger scale and higher processor performance.
Pre and Post Mount Merapi Eruption of Free Air Anomaly in 2010

Mount Merapi eruption in 2010 was one type of eruption with large scale during the last 100 years. Eruptions that was occurred resulting topographic changes in the peak of Mount Merapi, and the possibility of changing the subsurface structure. The research was part of a large study that has been conducted to assess the subsurface changes of pre-and post-eruption of Mount Merapi in 2010. The study discussed observations of free air anomalies pre and after the 2010 eruption. There were grouped into three periods. Processing of air anomalies was free to use using the 2nd orde calculation method. The results obtained were the changes in the contours of the FAA Mount Merapi in 1988, 1998, and 2011 as a result of topographic changes that occurred in the peak area and the alleged dynamics of the surface. The dynamics at Mount Merapi in the 1988 to 2011 period occurred in the northwest, southeast, east, and northeast of the study area and southeast of the peak of Mount Merapi.
Estimating River Surface Elevation From ArcticDEM

ArcticDEM is a collection of 2‐m resolution, repeat digital surface models created from stereoscopic satellite imagery. To demonstrate the potential of ArcticDEM for measuring river stages and discharges, we estimate river surface heights along a reach of Tanana River near Fairbanks, Alaska, by the precise detection of river shorelines and mapping of shorelines to land surface elevation. The river height profiles over a 15‐km reach agree with in situ measurements to a standard deviation less than 30 cm. The time series of ArcticDEM‐derived river heights agree with the U.S. Geological Survey gage measurements with a standard deviation of 32 cm. Using the rating curve for that gage, we obtain discharges with a validation accuracy (root‐mean‐square error) of 234 m3/s (23% of the mean discharge). Our results demonstrate that ArcticDEM can accurately measure spatial and temporal variations of river surfaces, providing a new and powerful data set for hydrologic analysis.
Status of the Intracellular Gate in the Activated-not-open State of Shaker K+ Channels

Voltage-dependent K+ channels like Shaker use an intracellular gate to control ion flow through the pore. When the membrane voltage becomes more positive, these channels traverse a series of closed conformations before the final opening transition. Does the intracellular gate undergo conformational changes before channel opening? To answer this question we introduced cysteines into the intracellular end of the pore and studied their chemical modification in conditions favoring each of three distinct states, the open state, the resting closed state, and the activated-not-open state (the closed state adjacent to the open state). We used two independent ways to isolate the channels in the activated-not-open state. First, we used mutations in S4 (ILT; Smith-Maxwell, C.J., J.L. Ledwell, and R.W. Aldrich. 1998. J. Gen. Physiol. 111:421–439; Ledwell, J.L., and R.W. Aldrich. 1999. J. Gen. Physiol. 113:389–414) that separate the final opening step from earlier charge-movement steps. Second, we used the open channel blocker 4-aminopyridine (4-AP), which has been proposed to promote closure of the intracellular gate and thus specifically to stabilize the activated-not-open state of the channels. Supporting this proposed mechanism, we found that 4-AP enters channels only after opening, remaining trapped in closed channels, and that in the open state it competes with tetraethylammonium for binding. Using these tools, we found that in the activated-not-open state, a cysteine located at a position considered to form part of the gate (Shaker 478) showed higher reactivity than in either the open or the resting closed states. Additionally, we have found that in this activated state the intracellular gate continued to prevent access to the pore by molecules as small as Cd2+ ions. Our results suggest that the intracellular opening to the pore undergoes some rearrangements in the transition from the resting closed state to the activated-not-open state, but throughout this process the intracellular gate remains an effective barrier to the movement of potassium ions through the pore.
On the Evaluation of Mined Frequent Sequences - An Evidence Theory-based Method

Frequent sequences (or temporal associations) mining is a very important topic within the temporal data mining area. Syntactic simplicity, combined with the dual characteristics (descriptive and predictive) of the mined temporal patterns, allow the extraction of useful knowledge from dynamic domains, which are timevarying in nature. Some of the most representative algorithms for mining sequential patterns or frequent associations are Apriori-like algorithms and, therefore, they cannot handle numeric attributes or items. This peculiarity makes it necessary to add a new process in the data preparation step, the discretization process. An important fact is that, depending on the discretization technique used, the number and type of discovered temporal patterns change dramatically. In this paper, we propose a method based on the Shafer’s Theory of Evidencethat uses two information measures proposed by Yagerfor the quality evaluation of the extracted sets of temporal patterns. From a practical point of view, the main goal is to select, for a given dataset, the best discretization technique that leads to the discovery of useful knowledge. Nevertheless the underlying idea is to propose a formal method for assessing the mined patterns, seen as a belief structure, in terms of certainty in the information that represents. In this work, we also present a practical example, describing an application of this proposal in the Intensive Care Burn Unit domain.
Survey of Various Energy Efficient Multicast Routing Protocols for MANET

This paper presents a thorough survey of current work addressing energy efficient multicast routing protocols in Mobile Ad hoc Networks (MANETs). There are so many different issues and solutions which witness the need of energy management in ad hoc wireless networks. The goal of a multicast routing protocol for MANETs is to support the propagation of data from a sender to all the receivers of a multicast group while trying to use the available bandwidth efficiently in the presence of frequent topology changes. Multicasting can improve the efficiency of the wireless link by sending multiple copies of messages by exploiting the inherent broadcast property of wireless transmission. However, offering energy efficient multicast routing is very difficult and challenging task. Now a day, various multicast routing protocols have been proposed for MANETs. All these protocols have distinguishing features and use different mechanisms.
End-to-End DNN Based Speaker Recognition Inspired by I-Vector and PLDA

Recently, several end-to-end speaker verification systems based on deep neural networks (DNNs) have been proposed. These systems have been proven to be competitive for text-dependent tasks as well as for text-independent tasks with short utterances. However, for text-independent tasks with longer utterances, end-to-end systems are still outperformed by standard i-vector + PLDA systems. In this work, we develop an end-to-end speaker verification system that is initialized to mimic an i-vector + PLDA baseline. The system is then further trained in an end-to-end manner but regularized so that it does not deviate too far from the initial system. In this way we mitigate overfitting which normally limits the performance of end-to-end systems. The proposed system outperforms the i-vector + PLDA baseline on both long and short duration utterances.
Speech Enhancement with Wide Residual Networks in Reverberant Environments

This paper proposes a speech enhancement method which exploits the high potential of residual connections in a Wide Residual Network architecture. This is supported on single dimensional convolutions computed alongside the time domain, which is a powerful approach to process contextually correlated representations through the temporal domain, such as speech feature sequences. We find the residual mechanism extremely useful for the enhancement task since the signal always has a linear shortcut and the non-linear path enhances it in several steps by adding or subtracting corrections. The enhancement capability of the proposal is assessed by objective quality metrics evaluated with simulated and real samples of reverberated speech signals. Results show that the proposal outperforms the state-of-the-art method called WPE, which is known to effectively reduce reverberation and greatly enhance the signal. The proposed model, trained with artificial synthesized reverberation data, was able to generalize to real room impulse responses for a variety of conditions (e.g. different room sizes, $RT_{60}$, near & far field). Furthermore, it achieves accuracy for real speech with reverberation from two different datasets.
A Performance Evaluation of OID Mapping Techniques

In this paper, three techniques to implement logical OIDs are thoroughly evaluated: hashing, B-trees and a technique called direct mapping. Among these three techniques, direct mapping is the most robust; it induces at most one page fault to map an OID, and it scales very well to large, rapidly growing databases. Furthermore, the clustering of handles that are used to map logical OIDs is studied. In particular, the performance of B-trees and direct mapping can improve significantly if the handles of objects that are frequently accessed by the same methods are clustered. For direct mapping, two placement policies arc compared: linear and matrix clustering.
Construction and properties of retrovirus packaging cells based on gibbon ape leukemia virus

We have constructed hybrid retrovirus packaging cell lines that express the gibbon ape leukemia virus env and the Moloney murine leukemia virus gag-pol proteins. These cells were used to produce a retrovirus vector at over 10(6) CFU/ml, with a host range that included rat, hamster, bovine, cat, dog, monkey, and human cells. The gag-pol and env expression plasmids were separately transfected to reduce the potential for helper virus production, which was not observed. The NIH 3T3 mouse cells from which the packaging lines were made are not infectable by gibbon ape leukemia virus; thus, the generation and spread of possible recombinant viruses in the packaging cells is greatly reduced. These simian virus-based packaging cells extend the host range of currently available murine and avian packaging cells and should be useful for efficient gene transfer into higher mammals.
JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation

Objective: The purpose of this paper is to propose a novel algorithm for joint optic disc and cup segmentation, which aids the glaucoma detection. Methods: By assuming the shapes of cup and disc regions to be elliptical, we proposed an end-to-end region-based convolutional neural network for joint optic disc and cup segmentation (referred to as JointRCNN). Atrous convolution is introduced to boost the performance of feature extraction module. In JointRCNN, disc proposal network (DPN) and cup proposal network (CPN) are proposed to generate bounding box proposals for the optic disc and cup, respectively. Given the prior knowledge that the optic cup is located in the optic disc, disc attention module is proposed to connect DPN and CPN, where a suitable bounding box of the optic disc is first selected and then continued to be propagated forward as the basis for optic cup detection in our proposed network. After obtaining the disc and cup regions, which are the inscribed ellipses of the corresponding detected bounding boxes, the vertical cup-to-disc ratio is computed and used as an indicator for glaucoma detection. Results: Comprehensive experiments clearly show that our JointRCNN model outperforms state-of-the-art methods for optic disc and cup segmentation task and glaucoma detection task. Conclusion: Joint optic disc and cup segmentation, which utilizes the connection between optic disc and cup, could improve the performance of optic disc and cup segmentation. Significance: The proposed method improves the accuracy of glaucoma detection. It is promising to be used for glaucoma screening.
Lecture 21: Stochastic Differential Equations

Following is a quote from [3]. Stochastic differential equations provide a link between probability theory and the much older and more developed fields of ordinary and partial differential equations. Wonderful consequences flow in both directions. The stochastic modeler benefits from centuries of development of the physical sciences, and many classic results of mathematical physics (and even pure mathematics) can be given new intuitive interpretations. We first state a result saying that SDEs can be solved.
Molecular Mechanisms Controlling Midline Crossing by Precerebellar Neurons

Precerebellar neurons of the inferior olive (IO) and lateral reticular nucleus (LRN) migrate tangentially from the rhombic lip toward the floor plate following parallel pathways. This process is thought to involve netrin-1 attraction. However, whereas the cell bodies of LRN neurons cross the midline, IO neurons are unable to do so. In many systems and species, axon guidance and cell migration at the midline are controlled by Slits and their receptor Robos. We showed previously that precerebellar axons and neurons do not cross the midline in the absence of the Robo3 receptor. To determine whether this signaling by Slits and the two other Robo receptors, Robo1 and Robo2, also regulates precerebellar neuron behavior at the floor plate, we studied the phenotype of Slit1/2 and Robo1/2/3 compound mutants. Our results showed that many IO neurons can cross the midline in absence of Slit1/2 or Robo1/2, supporting a role for midline repellents in guiding precerebellar neurons. We also show that these molecules control the development of the lamellation of the inferior olivary complex. Last, the analysis of Robo1/2/3 triple mutants suggests that Robo3 inhibits Robo1/2 repulsion in precrossing LRN axons but not in IO axons in which it has a dominant and distinct function.