Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparative Evaluation of Leading Dense Stereo Vision Algorithms using OpenCV

Stereo vision is an active research area of machine vision aiming to develop human like vision abilities in robots and other machines. During the last decade several stereo vision algorithms for computing dense disparity map have been developed aiming at improving the accuracy and computation speed of the algorithms. Currently, Graph Cut, Semi Global Block Matching and Block Matching are the most researched algorithms. This paper presents a comparative evaluation of these algorithms for their accuracy and speed on standard test bed images and images captured by a prototype stereo vision setup developed by the first author. KeywordsMachine Vision, Stereo Vision, Disparity map, OpenCV
Phlegmasia cerulea dolens in the Emergency Department: A case report

Background: Phlegmasia cerulea dolens is a rare form of deep venous thrombosis (DVT) characterized by massive thrombosis of the veins in a lower extremity. Presumptive diagnosis is made on clinical grounds and confirmed with a point-of-care ultrasound (POCUS). Diagnostic failure can lead to limb loss and even death. Case: We describe a case of a 38 year-old male who presented to the emergency department (ED) with painful cyanotic swelling of his right lower extremity. Clinical exam and POCUS confirmed the diagnosis of phlegmasia cerulea dolens. This patient was successfully treated with anticoagulation and endovascular thrombolytic therapy. Conclusion: This report emphasizes the importance of early diagnosis of the disease with POCUS, which can confirm the diagnosis of phlegmasia within minutes of clinical suspicion. Additionally, it describes the successful therapy with anticoagulation and endovascular thrombolysis.
Computational reinforcement learning using rewards from human feedback

A promising method of learning from human feedback is reward shaping, where a robot is trained via human-delivered instantaneous rewards. The existing approach, which requires numerous reward signals about the quality of agent’s actions from the human trainer, is based on a number of assumptions about human capabilities. For example, it assumes that humans can provide a precisely correct feedback to an agent’s action, or that they would always prefer to train an agent by means of reward signals, or that they can assess an agent’s actions for any length of training. In this thesis, we have relaxed these assumptions and have addressed two important issues which are not handled by the existing approach. First, how to compute a potential function using human feedback which can indicate the correctness of an action in terms of increasing or decreasing potential. Second, how to design training methods which cater to human preferences. Furthermore, we have identified that there are two important preferences of a human trainer in the application of reward shaping: (a) a preference to transfer knowledge by providing demonstrations and (b) a preference for short training durations. To address these issues, we have introduced three new methods of computing rewards from human-feedback. The first method, named rewards from state preference, takes human feedback as preferences of states in terms of distance to the goal state. It removes the assumption of highly accurate evaluative feedback from the user. It computes a high-quality potential function for potential-based reward shaping from only a few human feedbacks. Using feedbacks as state preferences, a ranking model is learned which computes a complete ranking of states. These state rankings define a potential function for
Rendering Procedural Textures for Visualization of Thematic Data in 3D Geovirtual Environments

3D geovirtual environments, such as virtual 3D city and landscape models, can be used as scenery for visualizing thematic data. which can be communicated using suitable color mappings or hatch patterns. For rendering purposes, these hatches patterns can be represented as image-based or procedural textures. The resulting quality of image-based textures, and thus the effective communication of the respective thematic data, is subject to resolution and filtering artifacts. In contrast to thereto, procedural textures are not limited with respect to resolution and can be filtered adaptively to achieve high visual quality. However, challenges in parametrization and design often hinders their application. To counterbalance these drawbacks, this paper presents an interactive rendering technique that facilitates the application and design of procedural hatch patterns for the mapping of thematic data to 3D geovirtual environments.
Level Set Segmentation of Retinal OCT Images

Optical coherence tomography (OCT) yields high-resolution images of the retina. Reliable identification of the retinal layers is necessary for the extraction of clinically useful information used for tracking the progress of medication and diagnosis of various ocular diseases. Many automatic methods have been proposed to aid with the analysis of retinal layers, mainly, due to the complexity of retinal structures, the cumbersomeness of manual segmentation and variation from one specialist to the other. However, a common drawback suffered by existing methods is the challenge of dealing with image artefacts and inhomogeneity in pathological structures. In this paper, we embed prior knowledge of the retinal architecture derived from the gradient information, into the level set method to segment seven (7) layers of the retina. Mainly, we start by establishing the region of interest (ROI). The gradient edges obtained from the ROI are used to initialise curves for the layers, and the layer topology is used in constraining the evolution process towards the actual layer boundaries based on image forces. Experimental results show our method obtains curves that are close to the manual layers labelled by experts.
Dynamical Analysis of Pace and Trot Gait Using a 3D Quadrupedal Model

Quadrupeds selectively use pace gait or trot gait in the middle of their locomotion speed range. However, it remains unclear why they select pace or trot gait depending on their species or conditions. In this paper, we use a simple 3D quadrupedal model to find periodic solutions corresponding to the motions of pace and trot gait. Using physical parameters of dogs, we compared obtained solutions of pace and trot using obtained touchdown angles of legs and three criteria: stability, energy efficiency, and maximum ground reaction force(GRF). From the results, we found that solutions of pace and trot had different touchdown angles of legs. In addition, we also found that regardless of locomotion speed, the solutions of pace were more stable and had smaller GRF than those of trot. On the other hand, the solutions of trot were more efficient motions than those of pace. These results can partially explain the reasons of selecting pace and trot gait by animals.
Top-k Dominating Queries on Skyline Groups

The top-<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="zhu-ieq1-2904065.gif"/></alternatives></inline-formula> dominating (TKD) query on skyline groups returns <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="zhu-ieq2-2904065.gif"/></alternatives></inline-formula> skyline groups that dominate the maximum number of points in a given data set. The TKD query combines the advantages of skyline groups and top-<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="zhu-ieq3-2904065.gif"/></alternatives></inline-formula> dominating queries, thus has been frequently used in decision making, recommendation systems, and quantitative economics. Traditional skylines are inadequate to answer queries from both <italic>individual</italic> and <italic>groups</italic> of points. The group size could be too large to be processed in a reasonable time as a single operator (i.e., the skyline group operator). In this paper, we address the performance problem of grouping for TKD queries in skyline database. We formulate the problem of grouping, define the group operator in skyline, and propose several efficient algorithms to find top-<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="zhu-ieq4-2904065.gif"/></alternatives></inline-formula> skyline groups. Thus, we provide a systematic study of TKD queries on skyline groups and validate our algorithms with extensive empirical results on synthetic and realworld data.
Different Security Issues of Internet of Things (IoT)

—In our daily life Internet of Things(IoT) are present everywhere. Internet of Things is the set of all physical objects that are attached to internet. IoT has various applications in hospitals,our homes, prevent fires and many more effective functions. But this applications can come under huge risks of security issues and privacy loss. To make this IoT device more secure, lot of research work has been carried out to counterpart those problems and find for better way to reduce those risks . In this paper we examine in detail about different security challenges,requirements in Internet of Things and research challenges.
Ant Lion optimizer for state based object oriented testing

Abstract Object-oriented paradigm is the most widely exploited design paradigm in the IT industry. The great functionalities of object-orientation not only improve the developed software but also introduce a wide variety of problems in testing. For instance, not only the object but also the state of object impacts testing. Various other serious issues of testing come along with object orientation. Thus, this has always been a major concern of software testers. Hence, it is very important to optimize this whole process of object-oriented software testing. Numerous meta-heuristic algorithms have been exploited in the past to accomplish this goal. In this paper, we are presenting a novel nature-inspired algorithm, AntLion Optimization (ALO) to generate optimal test paths for object-oriented software. Here, we are accompanying model based testing instead of code based testing as, this helps in reducing the testing effort and cost by identifying the error and bugs in the design phase itself. The main goal of model based software testing is to cover all the transitions present in the system i.e. full path coverage must be there. ALO is a novel meta-heuristic algorithm based on the random movement of ants in search of food, constructing traps by antlions, tricking the ants in trap, catching preys and reconstruction of traps. We introduces a random factor in the fitness function to capture the random motion of ants in the search space in search of food. This algorithm has been applied on three object-oriented software applications and the result guarantees complete path coverage which is a primary goal of software testing.
Dipotassium Glycyrrhizinate Against MDV on CEFs by Promoting MDV-Infected Cells Apoptosis in vitro

【Objective】The aim of the study is to test the antiviral activity and mechanism of dipotassium glycyrrhizinate(DG)against Marek's disease virus(MDV) in vitro. 【Method】 Using MTT test and standard plaque reduction assay on chick embryo fibroblast cells(CEFs), the antiviral effect of DG against MDV was observed by antiviral assay, time-of-addition assay and virucidal assay, and the antiviral mechanism was tested by cell apoptosis assay. 【Result】Antiviral assay showed that DG could reduce the damage of MDV to CEFs, EC50was(893.5±36.99) μg·mL-1,SI3.36 and the inhibition ratio was 94.4%, at the maximum with no-cytotoxic concentration. Time-of-addition assay and virucidal assay demonstrated that DG could inhibit the viral replication in the full replication cycle and inactivated MDV particles in non time-dependent manner. Moreover, DG could promote MDV-infected cells apoptosis in vitro. 【Conclusion】DG could inhibit MDV on CEFs by promoting MDV-infected cells apoptosis in vitro.
An integrated cyber-physical system for automatic identification of massive discs

Optical discs can reliably preserve massive data for long-term in low-cost. When querying these accumulative data, it is necessary to quickly obtain the query results, and to seek the physical location of the corresponding optical disc. To this end, it demands each disc have a unique identifier in both the cyber and physical worlds, make massive data be managed effectively, conveniently, and credibly. This paper designs a batch-disc automatic identification system, which integrates common optical disc recorders, printers, and cameras, automatically to print physical label and to burn logical identification on each disc. Consider that each commodity component has its own internal independent timing control and a specific external interface. This study designed and developed a customized mechanical structure, as well as a global software scheduling mechanism to coordinate physical behavior and logical control. The experimental results show that the system can continuously identify 200 discs at once, averaging 2 minutes per disc.
A Virtual Character Posing System based on Reconfigurable Tangible User Interfaces and Immersive Virtual Reality

Computer animation and, particularly, virtual character animation, are very time consuming and skill-intensive tasks, which require animators to work with sophisticated user interfaces. Tangible user interfaces (TUIs) already proved to be capable of making character animation more intuitive, and possibly more efﬁcient, by leveraging the affordances provided by physical props that mimic the structure of virtual counterparts. The main downside of existing TUI-based animation solutions is the reduced accuracy, which is due partly to the use of mechanical parts, partly to the fact that, despite the adoption of a 3D input, users still have to work with a 2D output (usually represented by one or more views displayed on a screen). However, output methods that are natively 3D, e.g., based on virtual reality (VR), have been already exploited in different ways within computer animation scenarios. By moving from the above considerations and by building upon an existing work, this paper proposes a VR-based character animation system that combines the advantages of TUIs with the improved spatial awareness, enhanced visualization and better control on the observation point in the virtual space ensured by immersive VR. Results of a user study with both skilled and unskilled users showed a marked preference for the devised system, which was judged as more intuitive than that in the reference work, and allowed users to pose a virtual character in a lower time and with a higher accuracy.
DENSITY IN ARTEMISIA ORDOSICA SUCCESSIONAL COMMUNITY IN RESPONSE TO SPATIAL HETEROGENEITY OF SOIL MOISTURE AND ORGANIC MATTER

Aims Using environmental spatial heterogeneity to explain the heterogeneity of vegetation is an important issue in ecology.We approached relationships between the spatial heterogeneity of soil moisture,organic matter and densities of Artemisia ordosica and A.frigida in a successional community of A.ordosica. Our objective was to discuss stability mechanisms of the plant community based on changes in spatial heterogeneity.Methods The study area is located at Tengri Desert(arid zone),which belongs to Alashan League of Inner Mongolia.Our sample plot was 80 m× 80 m,which contained 400 quadrats(4 m×4 m). In every quadrat,we determined soil moisture at 40 cm depth(oven-drying method)and soil organic matter at 0-5 cm top soil(potassium dichromate volumetric method),and recorded density of A.ordosica and A.frigida. We analyzed densities in response to the spatial heterogeneity of soil moisture and organic matter using statistics and geostatistics.Important findings The spatial heterogeneities of densities of A.ordosica and A.frigida were related to soil moisture and organic matter at the plot-scale(80 m×80 m). There were a significant positive linear correlation between the heterogeneities of the density of A.frigida and moisture and a significant positive power cortelation between heterogeneties of the density of A.ordosica and soil organic matter.We suggest that A.ordosica enriched the content of organic matter,thus promoting establishment of A.frigida. Both A.frigida and A.ordosica had clumped distributions,which enhanced soil spatial heterogeneity.Findings indicate a competitive displacement relationship between the two species.Thus,changes of soil spatial heterogeneity are factors in A.ordosica community succession in semi-desert zone.
Front-line thrombectomy for acute large-vessel occlusion with underlying severe intracranial stenosis: stent retriever versus contact aspiration.

OBJECTIVE The optimal front-line thrombectomy choice for primary recanalization of a target artery remains unknown for patients with acute large-vessel occlusion (LVO) and an underlying intracranial atherosclerotic stenosis (ICAS). The authors aimed to compare procedural characteristics and outcomes between patients who received a stent-retriever thrombectomy (SRT) and patients who received a contact aspiration thrombectomy (CAT), as the front-line approach for treating LVO due to severe underlying ICAS. METHODS One hundred thirty patients who presented with acute LVO and underlying severe ICAS at the occlusion site were included. Procedural characteristics and treatment outcomes were compared between patients treated with front-line SRT (n = 70) and those treated with front-line CAT (n = 60). The primary outcomes were the rate of switching to an alternative thrombectomy technique, time from groin puncture to initial reperfusion, and duration of the procedure. Initial reperfusion was defined as revealing the underlying culprit stenosis with an antegrade flow after thrombectomy. RESULTS The rate of switching to an alternative thrombectomy after failure of the front-line technique was significantly higher in the CAT group than in the SRT group (40% vs 4.3%; OR 2.543, 95% CI 1.893–3.417, p < 0.001). The median time from puncture to initial reperfusion (17 vs 31 minutes, p < 0.001) and procedure duration (39 vs 75.5 minutes, p < 0.001) were significantly shorter in the SRT group than in the CAT group. In the binary logistic regression analysis, a longer time from puncture to initial reperfusion was an independent predictor of a 90-day poor (modified Rankin Scale score 3–6) functional outcome (per 1-minute increase; OR 1.029, 95% CI 1.008–1.050, p = 0.006). CONCLUSIONS The authors’ results suggest that SRT may be more effective than CAT for identifying underlying culprit stenosis and therefore considered the optimal front-line thrombectomy technique in acute stroke patients with LVO and severe underlying ICAS.
Learning Determinantal Point Processes by Corrective Negative Sampling

Determinantal Point Processes (DPPs) have attracted significant interest from the machine-learning community due to their ability to elegantly and tractably model the delicate balance between quality and diversity of sets. DPPs are commonly learned from data using maximum likelihood estimation (MLE). While fitting observed sets well, MLE for DPPs may also assign high likelihoods to unobserved sets that are far from the true generative distribution of the data. To address this issue, which reduces the quality of the learned model, we introduce a novel optimization problem, Contrastive Estimation (CE), which encodes information about "negative" samples into the basic learning model. CE is grounded in the successful use of negative information in machine-vision and language modeling. Depending on the chosen negative distribution (which may be static or evolve during optimization), CE assumes two different forms, which we analyze theoretically and experimentally. We evaluate our new model on real-world datasets; on a challenging dataset, CE learning delivers a considerable improvement in predictive performance over a DPP learned without using contrastive information.
Large scale high sensitivity optical diffraction tomography of zebrafish

In this work we demonstrate large scale high sensitivity optical diffraction tomography (ODT) of zebrafish. Compared to previous work the scale and sensitivity are enhanced by the following steps. First, we obtain a large field of view while still maintaining a high image resolution by using a high magnification over numerical aperture ratio ODT set-up. With the inclusion of phase shifting we demonstrate that we operate close to the optimum magnification over numerical aperture ratio. Second, we decrease the noise in the reconstructed images by implementing off-axis sample placement and numerical focus tracking in combination with the acquisition of a large number of projections. Although both techniques lead to an increase in sensitivity independently, we show that combining them is necessary in order to make optimal use of the potential gain offered by each respective method and obtain a refractive index (RI) sensitivity of 8•10-5. In this way, high RI sensitivity can be achieved that is necessary for phase tomography of optically cleared tissue structures, which we can identify for features with RI down to 6•10-4. Third, we optimize the optical clearing procedure to prevent scattering and refraction to deteriorate our large scale images. We demonstrate our technique by imaging a 3 day old zebrafish and an adult cryoinjured zebrafish heart in a large 5.5 x 5.5 x 4.1 mm3 volume with 4 micrometer resolution. Various tissue structures can be clearly identified. The volume of the cryoinjured heart is segmented and quantified based on the refractive index distribution.
Evaluation and Behavior of Spanish Bodybuilders: Doping and Sports Supplements

The use of doping agents has these days become a public health problem, as it also affects young and non-competitive amateurs in different sports. To prepare for competition, bodybuilders perform aggressive dietary protocols, so, bodybuilders frequently consume nutritional supplements (NS) and banned substances in large dosages. Thus, the aim of this study is to analyze the prevalence of banned substances consumption and NS intake in competitive level bodybuilders. A total of 48 bodybuilders (44 males and 4 females) completed a validated online questionnaire on NS consumption. The quantitative data was presented as a mean (M) ± standard deviation (SD), as well as having minimum and maximum values. The categorical variables were expressed using frequencies and percentages. 83.3% of the participants declared that they had consumed or would consume banned substances, the most consumed being anabolic steroids (72.9%). One hundred percent of those sampled use NS. Whey protein (96%), branched-chain amino acids (BCAA) (94%), creatine (85%) and vitamin complexes (83%) were the most consumed, however, there is a low consumption of certain NS which could also increase athletic performance.