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An object-based visual attention model for robotic applications.

By extending integrated competition hypothesis, this paper presents an object-based visual attention model, which selects one object of interest using low-dimensional features, resulting that visual perception starts from a fast attentional selection procedure. The proposed attention model involves seven modules: learning of object representations stored in a long-term memory (LTM), preattentive processing, top-down biasing, bottom-up competition, mediation between top-down and bottom-up ways, generation of saliency maps, and perceptual completion processing. It works in two phases: learning p

A game theoretical approach to optimal control of dual drug delivery for HIV infection treatment.

For human immunodeficiency virus (HIV) infection treatment, the host immune system and antiviral drugs form a coalition to fight against HIV. Evidence suggests that drug therapy with Highly Active Antiretroviral Therapy can effectively prolong the life of the patient because it can reduce the replication of HIV while, at the same time, protecting the CD4+ T cells. The dosages of different drugs, however, are important in determining the success of the treatment. In addition, drug therapy for HIV is complicated by the fact that viruses can mutate, thereby effectively escaping from the attack of

Segmentation of psoriasis vulgaris images using multiresolution-based orthogonal subspace techniques.

In this paper, a method is proposed for the segmentation of color images using a multiresolution-based signature subspace classifier (MSSC) with application to psoriasis images. The essential techniques consist of feature extraction and image segmentation (classification) methods. In this approach, the fuzzy texture spectrum and the two-dimensional fuzzy color histogram in the hue-saturation space are first adopted as the feature vector to locate homogeneous regions in the image. Then these regions are used to compute the signature matrices for the orthogonal subspace classifier to obtain a mo

On the role of anxiety in decisions under possiblistic uncertainty.

We focus on situations in which we must decide on what time to take an action. The action is not in question it is the time of action. We call these "time for action decisions," a prototypical example being deciding when to leave on a journey. We point out that during this type of decision process, the decision-maker recognizes two groups of forces acting on him: one that pushes him to act now and other that pushes him act later. We note that the strength of these forces depends on the information available about various uncertainties associated with the situation. It also strongly depends upo

Optimal generation scheduling based on AHP/ANP.

This paper proposes an application of the analytic hierarchy process (AHP) and analytic network process (ANP) for enhancing the selection of generating power units for appropriate price allocation in a competitive power environment. The scheme addresses adequate ranking, prioritizing, and scheduling of units before optimizing the pricing of generation units to meet a given demand. In the deregulated environment, the classical optimization techniques will be insufficient for the above-mentioned purpose. Hence, by incorporating the interaction of factors such as load demand, generating cost curv

Learning automata-based bus arbitration for shared-medium ATM switches.

Although new high-bandwidth network technologies are being introduced and widely deployed, asynchronous transfer mode (ATM) is still considered one of the most important network technologies currently in use. A number of ATM switch architectures have been proposed in the literature. However, industry has shown that is better to use the well-known shared-medium technique in the design of these ATM switches. In this paper, four variations of a new distributed scheme are proposed for the arbitration of a shared bus of an ATM switch. These schemes are based on learning automata. By taking advantag

Identification of general fuzzy measures by genetic algorithms based on partial information.

This study develops an identification procedure for general fuzzy measures using genetic algorithms. In view of the difficulty in data collection in practice, the amount of input data is simplified through a sampling procedure concerning attribute subsets, and the corresponding detail design is adapted to the partial information acquired by the procedure. A specially designed genetic algorithm is proposed for better identification, including the development of the initialization procedure, fitness function, and three genetic operations. To show the applicability of the proposed method, this st

Fast image classification using a sequence of visual fixations.

Based on human retinal sampling distributions and eye movements, a sequential resolution image preprocessor is developed. Combined with a nearest neighbor classifier, this preprocessor provides an efficient image classification method, the sequential resolution nearest neighbor (SRNN) classifier. The human eye has a typical fixation sequence that exploits the nonuniform sampling distribution of its retina. If the retinal resolution is not sufficient to identify an object, the eye moves in such a way that the projection of the object falls onto a retinal region with a higher sampling density. S

An instrumented glove for grasp specification in virtual-reality-based point-and-direct telerobotics.

Hand posture and force, which define aspects of the way an object is grasped, are features of robotic manipulation. A means for specifying these grasping "flavors" has been developed that uses an instrumented glove equipped with joint and force sensors. The new grasp specification system will be used at the Pennsylvania State University (Penn State) in a Virtual Reality based Point-and-Direct (VR-PAD) robotics implementation. Here, an operator gives directives to a robot in the same natural way that human may direct another. Phrases such as "put that there" cause the robot to define a grasping

Soft object deformation monitoring and learning for model-based robotic hand manipulation.

This paper discusses the design and implementation of a framework that automatically extracts and monitors the shape deformations of soft objects from a video sequence and maps them with force measurements with the goal of providing the necessary information to the controller of a robotic hand to ensure safe model-based deformable object manipulation. Measurements corresponding to the interaction force at the level of the fingertips and to the position of the fingertips of a three-finger robotic hand are associated with the contours of a deformed object tracked in a series of images using neur

Head yaw estimation from asymmetry of facial appearance.

This paper proposes a novel method to estimate the head yaw rotations based on the asymmetry of 2-D facial appearance. In traditional appearance-based pose estimation methods, features are typically extracted holistically by subspace analysis such as principal component analysis, linear discriminant analysis (LDA), etc., which are not designed to directly model the pose variations. In this paper, we argue and reveal that the asymmetry in the intensities of each row of the face image is closely relevant to the yaw rotation of the head and, at the same time, evidently insensitive to the identity

An iterative solution to dynamic output stabilization and comments on "dynamic output feedback controller design for fuzzy systems".

In this note, we will show that the output feedback controller gains K in the paper is only an approximated solution K* = QP(-1)C0(dagger), with the dagger denoting Moore-Penrose inverse of the matrix C0. Consequently K is not equal to K* and therefore it may not satisfy the linear matrix inequality (LMI) constraints in the aforementioned paper. Instead, an iterative LMI approach is suggested to solve the dynamic output stabilization problem for the fuzzy systems.

Fuzzy control stabilization with applications to motorcycle control.

This study develops fuzzy control that is designed with sliding modes to achieve stability of the fuzzy controller. Fuzzy control is formulated in the form of variable structure system (VSS) control. In contrast to previous works in which Lyapunov functions are used to examine the stability, the current study investigates the stability of fuzzy control from the viewpoints of differential geometric methods and the sliding mode theory. Best values for parameters in fuzzy control rules are determined with the aid of sliding modes. In order to improve control performance, a tuning algorithm is exe

In Vitro Investigation of the Cytotoxic Activity of Emodin 35 Derivative on Multiple Myeloma Cell Lines.

BackgroundBortezomib is used for treating multiple myeloma (MM); however, it has considerable adverse effects. Emodin has been reported to exhibit inhibitory effects on MM cell lines. We investigated the efficacy of emodin 35 (E35), an emodin derivative, using U266 and MM1s cell lines in treating MM and the efficacy of combining bortezomib and E35.MethodsMTT assays were used to observe the effects of E35 on MM cell growth. The effects on cellular apoptosis were then observed using Annexin V/propidium iodide (PI) staining assay. The expression of apoptosis-related genes, including the caspase f

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… The quantitative analyses of protein expression were performed using an Image-Pro Plus system (Media Cybernetics, USA). 2.7. Statistical Analysis Data were expressed as mean ± standard deviation (SD) calculated by the data from at least three independent experiments. …

TrkB promotes laryngeal cancer metastasis via activation PI3K/AKT pathway.

ObjectivesThe aim of our study was to investigate the role of TrkB pathway in tumor occurrence and development for in order to provide theoretical basis to laryngeal cancer therapy.Materials and methodsBiological characteristics of the cells were studied by migration tests and colony forming assay. Gene and protein expression analysis was performed by RT-PCR or western blot. in vivo experiments were conducted in syngeneic BALB/c mice.ResultsSignificant changes in protein and gene expression, including higher expression level of TrkB, were found in cells and laryngeal cancer specimens. we demon

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… Images were analyzed with ImagePro (Media Cybernetics, Bethesda, MD, USA) and densitometry data were analyzed by using either conventional Student’s t-test. Results are reported as mean ± SD. A P-value <0.05 was considered significant and all were two-tailed. …

LncRNA OIP5‑AS1 aggravates house dust mite‑induced inflammatory responses in human bronchial epithelial cells via the miR‑143‑3p/HMGB1 axis.

Bronchial asthma poses a serious threat to human health. Previous studies have documented the role of long non‑coding RNAs (lncRNAs) in asthma. However, the molecular mechanism underlying bronchial asthma remains unclear. The aim of the present study was to evaluate the role of the lncRNA Opa‑interacting protein 5 antisense RNA1 (OIP5‑AS1) in the house dust mite‑induced inflammatory response in human bronchial epithelial cells. BEAS‑2B cells were treated with Dermatophagoides pteronyssinus peptidase 1 (Der p1) to establish an in vitro model of asthma. OIP5‑AS1 expression levels increased in BE

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… Relative protein expression was quantified using Image-Pro Plus software (version 6.0; Media Cybernetics, Inc.). ELISA ELISA was conducted to determine the levels of the inflammatory factors. …

Nm23-H1 inhibits lung cancer bone-specific metastasis by upregulating miR-660-5p targeted SMARCA5.

BackgroundNm23-H1 gene has been found to be an inhibitor of tumor metastasis in lung cancer. MicroRNAs (miRNAs) play key roles in tumor metastasis through multiple signaling pathways. This study explored whether the nm23-H1 gene could inhibit invasion and metastasis of lung cancer cells by regulating miRNA-660-5p targets.MethodsQuantitative real-time PCR (qRT-PCR) and western blots were used to measure the expression of nm23-H1 and miR-660-5p of various human lung cancer cell lines. Cell counting kit-8 (CCK-8), wound-healing and transwell assay were carried out to assess cell proliferation, mi

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… Image‐Pro software (Media Cybernetics, Bethesda, MD, USA) was used to calculate the fluorescence intensity. Bone metastasis rate was evaluated according to the number of spinal column metastases in each group. …

The PI3K inhibitor buparlisib suppresses osteoclast formation and tumour cell growth in bone metastasis of lung cancer, as evidenced by multimodality molecular imaging.

Non‑small cell lung cancer (NSCLC) metastasis commonly occurs in bone, which often results in pathological fractures. Sustained phosphoinositide‑3‑kinase (PI3K) signalling promotes the growth of PI3K‑dependent NSCLC and elevates osteoclastogenic potential. The present study investigated the effects of a PI3K inhibitor on NSCLC growth in bone and osteoclast formation, and aimed to determine whether it could control symptoms associated with bone metastasis. A bone metastasis xenograft model was established by implanting NCI‑H460‑luc2 lung cancer cells, which contain a phosphatidylinositol‑​4,5‑b

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… Means of the intensity of green fluorescence was calculated using Image-Pro Plus (version 6.0.0.260; Media Cybernetics, Inc., Rockville, MD, USA). The proportion of TUNEL-positive cells compared with the number of total cells was calculated as the percentage of apoptotic cells. …

Technology Integration Methods for Bi-directional Brain-computer Interfaces and XR-based Interventions.

Brain stimulation therapies have been established as effective treatments for Parkinson's disease, essential tremor, and epilepsy, as well as having high diagnostic and therapeutic potential in a wide range of neurological and psychiatric conditions. Novel interventions such as extended reality (XR), video games and exergames that can improve physiological and cognitive functioning are also emerging as targets for therapeutic and rehabilitative treatments. Previous studies have proposed specific applications involving non-invasive brain stimulation (NIBS) and virtual environments, but to date

DyNeuMo Mk-2: An Investigational Circadian-Locked Neuromodulator with Responsive Stimulation for Applied Chronobiology.

Deep brain stimulation (DBS) for Parkinson's disease, essential tremor and epilepsy is an established palliative treatment. DBS uses electrical neuromodulation to suppress symptoms. Most current systems provide a continuous pattern of fixed stimulation, with clinical follow-ups to refine settings constrained to normal office hours. An issue with this management strategy is that the impact of stimulation on circadian, i.e. sleep-wake, rhythms is not fully considered; either in the device design or in the clinical follow-up. Since devices can be implanted in brain targets that couple into the re