Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual attention based image zero watermark scheme with ensemble similarity

Most existing digital image watermarking schemes tend to have the inherent conflicts between imperceptibility and robustness because watermarks are embedded by parameter modification. Image watermark techniques resolve this dilemma by extracting invariant features from the image as “embedded” watermark. In this paper we propose an image zero watermark scheme based on visual attention regions of images. In the proposed scheme visual attention model carefully selects top-N salient areas, where a set of selected Scale Invariant Feature transform (SIFT) descriptors are extracted as a watermark. The distance of each pair of SIFT descriptors from the reference and test images are calculated by Kullback-Leibler (KL) divergence after mapping into the high dimensional space respectively. The final distance of two sets of SIFT descriptor are determined by ensemble similarity. The experimental results indicate that the proposed scheme outperforms image zero watermark scheme based on color and edge histograms (CEH) and is robust to attacks of geometric distortion, contrast/luminance distortion and JPEG compression.
Exploiting features from triangle geometry for digit recognition

Triangle is a basic geometry. There are six types of triangle, but scalene triangle was chosen to be used in this research which is based on coordinates of corners generated by our proposed algorithm. In this paper, nine features are proposed. Six of the features were derived from coordinates and sides of triangle whereas three others are angle of corners. After features are identified, the image is zoned into 25 zones. The zoning processes are based on Cartesian plan, Vertical and Horizontal zones. From the zoning process, nine features are expanded to become 225 features. The features proposed are used on HODA, MNIST, IFHCDB and BANGLA datasets. Experiments are conducted using supervised learning which are Support Vector Machine (SVM) and Multi-layer Perceptron (MLP). Results from the experiments are evaluated with different Cost (c) for the SVM and Learning Rate (LR) for the MLP. Then, the result is compared to the state of the art researches in this area.
Cubical Sets and Trace Monoid Actions

This paper is devoted to connections between trace monoids and cubical sets. We prove that the category of trace monoids is isomorphic to the category of generalized tori and it is a reflective subcategory of the category of cubical sets. Adjoint functors between the categories of cubical sets and trace monoid actions are constructed. These functors carry independence preserving morphisms in the independence preserving morphisms. This allows us to build adjoint functors between the category of weak asynchronous systems and the category of higher dimensional automata.
Separation of heart sound signal from lung sound signal by adaptive line enhancement

This paper presents a technique for separation of heart sound signal (HSS) from lung sound signal (LSS) using adaptive line enhancement (ALE). The ALE is used to extract a semi-periodic signal component (HSS) from a synthetic white Gaussian noise (WGN). Application of ALE to separation of HSS from LSS has also been demonstrated. For when synthetic data (WGN) is combined with the HSS, it is found that ALE can separate the HSS at input signal-to-noise ratio (SNRin) of 27dB. The results for when the ALE is applied to the combined HSS-LSS show that ALE can separate HSS even if the SNRin equals ×5dB.
Belief Propagation Stereo Matching Based on Differential Geometry Constraint of Disparity

The particularities of stereo matching for slant planes and curve surfaces are studied and a differential geometric constraint of disparity is put forward based on image segmentation, The energy function is constructed according to the disparity constraint, which can reflect better the depth structure of visual scene, The classic belief propagation optimization algorithm based on front parallel plane assumption is improved using the disparity constraint the disparities of pixels in segmentation area are optimized iteratively until the energy function is minimized. The experiments on Middlebury Test Set show that the proposed method is more fit for vision scenes of slant planes and even curved surfaces.
Acquisition of energy-efficient bipedal walking using CPG-based reinforcement learning

Although there have been much research on robot walking, the energy efficiency of central pattern generator (CPG)-based walking has not received much attention. This study proposes a novel method for acquiring energy-efficient CPG-based bipedal walking for a robot with knees and feet. In this method, we introduce a torque-free period for swing leg control into the swing leg control cycle. During this period, no torque is applied to the hip joint controller, and therefore no energy is consumed. When and for how long the torque-free period is inserted into the swing leg control cycle is adaptively acquired by reinforcement learning. Simulation experiments demonstrate the feasibility of our method. The energy consumed in acquiring walking is reduced by 40% compared with simple CPG-based walking without the torque-free period in the practical learning speed. Walking stability is maintained with respect to external disturbances on a level floor. Although the method is more unstable on slopes with the torque-free period, the torque-free-period can be adaptively eliminated to achieve stable walking on the slopes.
Silibinin strongly synergizes human prostate carcinoma DU145 cells to doxorubicin-induced growth Inhibition, G2-M arrest, and apoptosis.

PURPOSE We recently demonstrated the strong anticancer efficacy of silibinin,an active constituent of a widely consumed dietary supplement milk thistle extract, against human prostate cancer cells in culture and nude mice xenografts. We also observed that pharmacologically achievable concentrations of silibinin in animal studies were in the range of 25-100 microM, depending on the dose regimen, which did not show any apparent toxicity to the animals. In this study, we assessed whether silibinin synergizes the therapeutic potential of the chemotherapeutic drug doxorubicin against prostate cancer, the effectiveness of which is limited because of high systemic toxicity. EXPERIMENTAL DESIGN Prostate cancer cells were treated with silibinin and doxorubicin, either alone or in combination, and cell growth was determined by manual cell counting. Cell cycle progression was assessed by saponin/propidium iodide staining and fluorescence-activated cell sorter analysis. Protein levels of cell cycle regulators were determined by Western blotting, and cdc2/p34 kinase activity was analyzed by in-beads kinase assay. Apoptosis was quantified by annexin V/propidium iodide staining and fluorescence-activated cell sorter analysis. RESULTS Silibinin strongly synergized the growth-inhibitory effect of doxorubicin in prostate carcinoma DU145 cells (combination index, 0.235-0.587), which was associated with a strong G(2)-M arrest in cell cycle progression, showing 88% cells in G2-M phase by this combination compared with 19 and 41% of cells in silibinin and doxorubicin treatment alone, respectively. The underlying mechanism of G2-M arrest showed a strong inhibitory effect of combination on cdc25C, cdc2/p34, and cyclin B1 protein expression and cdc2/p34 kinase activity. More importantly, this combination caused 41% apoptotic cell death compared with 15% by either agent alone. Silibinin and doxorubicin alone as well as in combination were also effective in inhibiting the growth of androgen-dependent prostate carcinoma LNCaP cells. CONCLUSION These findings suggest a need for in vivo studies with this combination in preclinical prostate cancer models. Positive outcomes might be relevant for a clinical application in prostate cancer patients.
Design of CASIA-ARM: A novel rehabilitation robot for upper limbs

The population of disabled stroke survivors is increasing sharply over the world, and robot-assisted training has been proved to be effective to help motor relearning and alleviate the shortage of physical therapists. This paper presents the design details of a novel upper limb rehabilitation robot named CASIA-ARM, which can assist poststroke patients to perform shoulder and elbow rehabilitation training in the horizontal plane, and provide both force and visual feedback to the patient: 1) A five-bar closed-chain structure is designed to realize a stiff and low-inertial mechanism. Workspace and singularity analysis is given, which guarantees that the workspace is large enough for upper limb moving and no singularity in the workspace. 2) Cable transmission, motor current controller and impedance control method guarantee the transparent and compliant interaction between the human and the robot. 3) Implementation examples of passive training based on position control and active training based on impedance control are presented in detail. 4) In order to evaluate the robot's applicability and performance, examples of trajectory tracking and active reaching tasks are used in this study, and the preliminary test results are also given (tracking error: 0.86±0:42 mm, force control error: 1.41±0.79 N in the X direction, and 1.22±0.91 N in the Y direction).
Quasi-Poisson Manifolds

Abstract A quasi-Poisson manifold is a $G$ -manifold equipped with an invariant bivector field whose Schouten bracket is the trivector field generated by the invariant element in ${{\Lambda }^{3}}\mathfrak{g}$ associated to an invariant inner product. We introduce the concept of the fusion of such manifolds, and we relate the quasi-Poisson manifolds to the previously introduced quasi-Hamiltonian manifolds with group-valued moment maps.
Who is talking about what: social map-based recommendation for content-centric social websites

Content-centric social websites, such as discussion forums and blog sites, have flourished during the past several years. These sites often contain overwhelming amounts of information that are also being updated rapidly. To help users locate their interests at such sites (e.g., interesting blogs to read or discussion forums to join), researchers have developed a number of recommendation technologies. However, it is difficult to make effective recommendations for new users (a.k.a. the cold start problem) due to a lack of user information (e.g., preferences and interests). Furthermore, the complexity of recommendation algorithms often prevents users from comprehending let alone trusting the recommended results. To tackle the above two challenges, we are building a social map-based recommender system called Pharos. A social map summarizes users' content-related social behavior over time (e.g., reading, writing, and commenting behavior during the past week) as a set of latent communities. Each community is characterized by the theme of the content being discussed and the key people involved. By discovering, ranking, and displaying the most "popular" latent communities, Pharos creates a visual social map of a website. This enables new users to obtain a quick overview of the site, alleviating the cold start problem. Furthermore, we use the social map as a context to help explain Pharos-recommended content and people. Users can also interactively explore the social map to locate their interested content or people that are not being explicitly recommended, compensating for the imperfection in the recommendation algorithms. We have deployed Pharos within our company and our preliminary evaluation shows the usefulness of Pharos.
The Impact of perception on Work behavior

This study examines the impact of perception on work behavior. Individual differences are important in studying organizational behavior and management for a very important reason. Individual differences have a direct effect on behavior, every person is unique because of his perception, people with different perceptions have different characteristics, needs, how they perceive the world and other individuals and interact differently with bosses, co-workers, subordinates and customers. Individual perceptions shape organizational behavior and consequently individual and organizational success For example, individual differences help examine why some people embrace change and others are fearful of it. Or why some employees will be productive only if they are closely supervised, while others will be productive only if they are not . Or why some workers learn new tasks more effectively than others A helpful way to think about the importance of individual differences in influencing work behavior is through the use of the Attraction- Selection- Attrition (ASA) framework. Different people are attracted to different careers and organizations as a function of their own abilities, interests and personalities. Similarly organization select employees on the basis of the needs the organization has . Needs refers to not only to skills and abilities, but also to individual attributes such as values, and personality. Not all attraction decisions and selection decisions work out, however, Attrition occurs when individuals discover they do not like being part of the organizations and selects to resign or when the organization determines an individual isn’t successding and select to terminate .
An evaluation of a programme of problem-based learning within a clinical psychology doctorate

Problem-Based learning (PBL) is a widely used teaching method in UK Clinical Psychology training. This study considers the experience of using PBL as part of the University of Bath’s Doctorate in Clinical Psychology. Questionnaire and focus group analyses suggest PBL was predominantly experienced as useful by trainees when completed during the first year of clinical training, especially in terms of skill development around leadership and team working; which was maintained at two-year follow-up when the same cohort of trainees completed an adapted version of the questionnaire during their third year of training. Trainees suggested some difficulties with PBL (e.g. anxieties concerning the lack of a teacher) and suggested improvements (e.g. to timetabling and the case vignette), which have helped sculpt new PBL teaching for subsequent trainees. This study has its limitations, and future research is recommended to further evaluate the use of PBL within clinical psychology training courses nationally.
A 77GHz 4-channel automotive radar transceiver in SiGe

A fully integrated 4-channel automotive radar transceiver chip, integrated in a 200-GHz SiGe:C production technology, is presented. With a typical transmit power of 2 x +7 dBm at the antenna ports and all functions active, the chip draws a current of about 600 mA from a single 5.5 V supply. The design permits FMCW operation in the 76 to 77 GHz band at chip-backside temperatures from -40degC to +125degC.
Extracts of Immature Orange (Aurantii fructus immaturus) and Citrus Unshiu Peel (Citri unshiu pericarpium) Induce P-Glycoprotein and Cytochrome P450 3A4 Expression via Upregulation of Pregnane X Receptor

P-glycoprotein (P-gp) and cytochrome P450 3A4 (CYP3A4) are expressed in the intestine and are associated with drug absorption and metabolism. Pregnane X receptor (PXR) is the key molecule that regulates the expression of P-gp and CYP3A4. Given that PXR activity is regulated by a variety of compounds, it is possible that unknown PXR activators exist among known medicines. Kampo is a Japanese traditional medicine composed of various natural compounds. In particular, immature orange [Aurantii fructus immaturus (IO)] and citrus unshiu peel [Citri unshiu pericarpium (CP)] are common ingredients of kampo. A previous study reported that kampo containing IO or CP decreased the blood concentration of concomitant drugs via upregulation of CYP3A4 although the mechanism was unclear. Some flavonoids are indicated to alter P-gp and CYP3A4 activity via changes in PXR activity. Because IO and CP include various flavonoids, we speculated that the activity of P-gp and CYP3A4 in the intestine may be altered via changes in PXR activity when IO or CP is administered. We tested this hypothesis by using LS180 intestinal epithelial cells. The ethanol extract of IO contained narirutin and naringin, and that of CP contained narirutin and hesperidin. Ethanol extracts of IO and CP induced P-gp, CYP3A4, and PXR expression. The increase of P-gp and CYP3A4 expression by the IO and CP ethanol extracts was inhibited by ketoconazole, an inhibitor of PXR activation. The ethanol extract of IO and CP decreased the intracellular concentration of digoxin, a P-gp substrate, and this decrease was inhibited by cyclosporine A, a P-gp inhibitor. In contrast, CP, but not IO, stimulated the metabolism of testosterone, a CYP3A4 substrate, and this was inhibited by a CYP3A4 inhibitor. These findings indicate that the ethanol extract of IO and CP increased P-gp and CYP3A4 expression via induction of PXR protein. Moreover, this induction decreased the intracellular substrate concentration.
An evaluation of image registration methods for chest radiographs

Image registration is commonly used in medical applications for revealing changes in different series of images. In this study, the performances of different registration scenarios based on different feature extraction and matching methods were assessed in the context of chest radiographic images. For this purpose, combination of three well known key point descriptors (SIFT, SURF and ORB) were used as feature detectors. For feature matching, SIFT and SURF methods were also employed individually. The tests were conducted on chest X-ray images of real patient data taken at different times. The accuracies of the registered images were assessed by two different validation algorithms. The experiments revealed that the highest registration accuracy is achieved when SIFT and SURF descriptors are used together for key point extraction, and SIFT algorithm is used for feature matching.
Rigid and Articulated Point Registration with Expectation Conditional Maximization

This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration. The problem is recast into a missing data framework where unknown correspondences are handled via mixture models. Adopting a maximum likelihood principle, we introduce an innovative EM-like algorithm, namely, the Expectation Conditional Maximization for Point Registration (ECMPR) algorithm. The algorithm allows the use of general covariance matrices for the mixture model components and improves over the isotropic covariance case. We analyze in detail the associated consequences in terms of estimation of the registration parameters, and propose an optimal method for estimating the rotational and translational parameters based on semidefinite positive relaxation. We extend rigid registration to articulated registration. Robustness is ensured by detecting and rejecting outliers through the addition of a uniform component to the Gaussian mixture model at hand. We provide an in-depth analysis of our method and compare it both theoretically and experimentally with other robust methods for point registration.
Ask Me Even More: Dynamic Memory Tensor Networks (Extended Model)

We examine Memory Networks for the task of question answering (QA), under common real world scenario where training examples are scarce and under weakly supervised scenario, that is only extrinsic labels are available for training. We propose extensions for the Dynamic Memory Network (DMN), specifically within the attention mechanism, we call the resulting Neural Architecture as Dynamic Memory Tensor Network (DMTN). Ultimately, we see that our proposed extensions results in over 80% improvement in the number of task passed against the baselined standard DMN and 20% more task passed compared to state-of-the-art End-to-End Memory Network for Facebook's single task weakly trained 1K bAbi dataset.
Shrunken p‐Values for Assessing Differential Expression with Applications to Genomic Data Analysis

Summary In many scientific problems involving high‐throughput technology, inference must be made involving several hundreds or thousands of hypotheses. Recent attention has focused on how to address the multiple testing issue; much focus has been devoted toward the use of the false discovery rate. In this article, we consider an alternative estimation procedure titled shrunken p‐values for assessing differential expression (SPADE). The estimators are motivated by risk considerations from decision theory and lead to a completely new method for adjustment in the multiple testing problem. In addition, the decision‐theoretic framework can be used to derive a decision rule for controlling the number of false positive results. Some theoretical results are outlined. The proposed methodology is illustrated using simulation studies and with application to data from a prostate cancer gene expression profiling study.
Primary thyroid mucosa-associated lymphoid tissue lymphoma; a clinicopathological study of seven cases

Purpose Primary thyroid mucosa-associated lymphoid tissue (MALT) lymphoma is a very rare subgroup of thyroid lymphoma, accounting for about 6 to 28% of all primary thyroid lymphomas. The purpose of this study was to evaluate its clinicopathological features and treatment outcomes. Methods We identified seven patients with thyroid MALT lymphoma who were treated between January 1997 and December 2007, and reviewed their clinicopathological features and follow-up outcomes. Results There were five female and two male patients, and their mean age was 73 years. All patients presented with palpable neck mass. Two patients had hoarseness and dyspnea. All patients had a history of Hashimoto's thyroiditis with a mean of 175 months. Malignant lymphoma was suspected in only three patients using core needle biopsy. Four patients underwent thyroidectomy in the absence of preoperative pathologic confirmation, and histologic diagnosis was obtained after surgery. As initial treatment, complete surgical resection was performed in five patients, radiotherapy in one, and a combination of chemotherapy and radiotherapy in one. Six patients were alive for the mean follow-up period of 66 months and one patient died of unrelated causes. There were neither recurrences nor disease-specific mortalities. Conclusion When primary thyroid MALT lymphoma occurs in the thyroid or is confined to the neck, it responds well to local treatment such as surgical resection and external beam radiation therapy.
Addressing Instance Ambiguity in Web Harvesting

Web Harvesting enables the enrichment of incomplete data sets by retrieving required information from the Web. However, the ambiguity of instances may greatly decrease the quality of the harvested data, given that any instance in the local data set may become ambiguous when attempting to identify it on the Web. Although plenty of disambiguation methods have been proposed to deal with the ambiguity problems in various settings, none of them are able to handle the instance ambiguity problem in Web Harvesting. In this paper, we propose to do instance disambiguation in Web Harvesting with a novel disambiguation method inspired by the idea of collaborative identity recognition. In particular, we expect to find some common properties in forms of latent shared attribute values among instances in the list, such that these shared attribute values can differentiate instances within the list against those ambiguous ones on the Web. Our extensive experimental evaluation illustrates the utility of collaborative disambiguation for a popular Web Harvesting application, and shows that it substantially improves the accuracy of the harvested data.