Where's Waldo?® How perceptual, cognitive, and emotional brain processes cooperate during learning to categorize and find desired objects in a cluttered scene

The Where's Waldo problem concerns how individuals can rapidly scan a scene to detect a target object in it. This dissertation develops the ARTSCAN Search neural model to clarify how brain mechanisms that govern spatial and object attention, spatially-invariant object learning and recognition, reinforcement learning, and eye movement search are coordinated to enable learning and directed search for desired objects at specific locations in a cluttered scene. In the model, interactions from the Where cortical processing stream to the What cortical processing stream modulate invariant category learning of a desired object, whereas interactions from the What cortical processing stream to the Where cortical processing stream support search for the object. In particular, when an invariant object category representation is activated top-down by a cognitive plan or by an active motivational source in the model's What stream, it can shift spatial attention in the Where stream and thereby selectively activate the locations of sought-after object exemplars. These combined What-to-Where and Where-to-What interactions clarify how the brain's solution of the Where's Waldo problem overcomes the complementary deficiencies of What and Where stream processes taken individually by using inter-stream interactions that allow both invariant object recognition and spatially selective attention and action to occur

Frequently Hypercyclic and Chaotic Behavior of Some First-Order Partial Differential Equation

We study a particular first-order partial differential equation which arisen from a biologic model. We found that the solution semigroup of this partial differential equation is a frequently hypercyclic semigroup. Furthermore, we show that it satisfies the frequently hypercyclic criterion, and hence the solution semigroup is also a chaotic semigroup

Non-Adiabatic Effects on Electron Beam Quality for Frequency-Tunable Gyrotrons

We propose an unconventional electron gun structure in which the emitter is located on a concave cathode surface with a non-uniform electric field. Such a design violates the intuition that an emitter should place close to a uniform electric field to reduce the velocity spread. The commonly employed design guide based on the adiabatic condition predicts a huge velocity spread of 24%, but the simulation using EGUN code and verified with CST particle studio shows a very low spread of 2.8%. Examining the magnetic moment and the kinetic energy of the beam reveals that the electrons experience a relatively long acceleration process due to the much weak electric field. That's why the non-adiabatic effect matters. In addition to the cyclotron compression and the E$\times$B drift, the "resonant" polarization drift plays a crucial role in reducing the overall velocity spread.Simulations show a decent beam quality with the pitch factor of 1.5 and the transverse velocity spread of 2.8% over a wide range of the magnetic field (7.4-8.0 T) and the beam voltage (12-22 kV) with a high structural tolerance. The promising results with the wide working range enable the development of continuous frequency-tunable gyrotrons.Comment: 5 pages, 5 figures, and 2 table

Out-Of-Band Management on UEFI System Firmware

The modern Redfish is a specification that utilize RESTful interface semantics to access data defined in model format to perform out-of-band (OOB) management through specific OOB software or hardware (such as Baseboard Management Controller, BMC). The OOB management allow users to configure system remotely when the system is in either power-off or power-on state. Industry can expect there are more and more pre-boot firmware drivers (like UEFI drivers) and system peripherals (such as PCI devices, PCI add-on-card and so on) support Redfish Schema/Configuration data model in the near future. This article describes the method to abstract the data communication/synchronization between UEFI drivers and OOB management on UEFI firmware environment. Furthermore, this article is not only restricted to single OOB management on system, the abstracts method described in this article is flexible and extensible to support multiple OOB management instances on one system simultaneously. Not only Redfish OOB management data model is supported, this article fulfills the requirements of any other data model of OOB managements such as OData XML/JSON data model, CIM-XML data model, 3rd party data model and etc

Traditional Chinese Medicine Diagnosis “ Yang-Xu Zheng

Pathogenesis of sepsis includes complex interaction between pathogen activities and host response, manifesting highly variable signs and symptoms, possibly delaying diagnosis and timely life-saving interventions. This study applies traditional Chinese medicine (TCM) Zheng diagnosis in patients with severe sepsis and septic shock to evaluate its adaptability and use as an early predictor of sepsis mortality. Three-year prospective observational study enrolled 126 septic patients. TCM Zheng diagnosis, Acute Physiology and Chronic Health Evaluation (APACHE) II score, and blood samples for host response cytokines measurement (tumor necrosis factor-α, Interleukin-6, Interleukin-8, Interleukin-10, Interleukin-18) were collected within 24 hours after admission to Intensive Care Unit. Main outcome was 28-day mortality; multivariate logistic regression analysis served to determine predictive variables of the sepsis mortality. APACHE II score, frequency of Nutrient-phase heat, and Qi-Xu and Yang-Xu Zhengs were significantly higher in nonsurvivors. The multivariate logistic regression analysis identified Yang-Xu Zheng as the outcome predictor. APACHE II score and levels of five host response cytokines between patients with and without Yang-Xu Zheng revealed significant differences. Furthermore, cool extremities and weak pulse, both diagnostic signs of Yang-Xu Zheng, were also proven independent predictors of sepsis mortality. TCM diagnosis “Yang-Xu Zheng” may provide a new mortality predictor for septic patients