Catastrophic chaos theory: predicting recovery of health or death

Recently, we revealed a standard pattern of a macroscopic molecular network for controlling morphogenetic processes such as the development of organs, including blast, mesoderm, heart, and hands during about sevenfold cell divisions and a standard bio-chemical clock like the circadian one (Naitoh in Artif Life Robot 13, 2008; Japan J Ind Appl Math 28(1), 2011; J Phys Conf Ser 344, 2012; Artif Life Robot 17, 2012) A network model derived logically based on experimental observations is described by a nonlinear differential equation for predicting time evolutions of six macroscopic molecular groups: three gene groups and three enzyme groups, which include promoting and suppressing factors. Here, the macroscopic model extended for also describing aging processes shows various types of cycles and reveals the physical condition for determining whether or not living beings such as humans can survive after getting ill. It is stressed that, after becoming ill, living systems with overly fast generation of information molecules such as various genes end in death, whereas relatively fast production of enzymes leads to recovery. This may also explain an essential feature underlying carcinogenic processes.     

An architecture framework for an adaptive extensible processor

To improve the performance of embedded processors, an effective technique is collapsing critical computation subgraphs as application-specific instruction set extensions and executing them on custom functional units. The problem with this approach is the immense cost and the long times required to design a new processor for each application. As a solution to this issue, we propose an adaptive extensible processor in which custom instructions (CIs) are generated and added after chip-fabrication. To support this feature, custom functional units are replaced by a reconfigurable matrix of functional units (FUs). A systematic quantitative approach is used for determining the appropriate structure of the reconfigurable functional unit (RFU). We also introduce an integrated framework for generating mappable CIs on the RFU. Using this architecture, performance is improved by up to 1.33, with an average improvement of 1.16, compared to a 4-issue in-order RISC processor. By partitioning the configuration memory, detecting similar/subset CIs and merging small CIs, the size of the configuration memory is reduced by 40%.     

Transflective IPS‐LCD with improved reflective contrast ratio

Abstract— In order to improve the reflective contrast ratio of transflective IPS‐LCDs, a novel pixel design for a normally white reflective IPS has been proposed. In this design, the large‐inter‐electrode‐spacing layout using a novel driving method and a double‐layered electrode have effectively reduced the light leakage. By applying these two technologies, a transflective IPS‐LCD has been successfully demonstrated with a high contrast ratio (15:1) in the reflective mode and a wide‐viewing‐angle characteristic in the transmissive mode.     

A low wall-loading DEMO reactor design with high priority for early and reliable realization of a tokamak fusion reactor over the cost performance

Based on scientific databases adopted for designing ITER plasmas and on the advancement of fusion nuclear technology from the recent R&D program, a low wall-loading DEMO fusion reactor has been designed, where high priority has been given to the early and reliable realization of a tokamak fusion plasma over the cost performance. Since the major radius of this DEMO reactor is chosen to be 10 m, plasma ignition is achievable with a low fusion power of 0.8 GW and an operation period of 4–5 hours is available only with inductive current drive. The low ignition power makes it possible to adopt a first wall with an austenitic stainless steel, for which significant databases and operating experience exists, due to its use in the presence of neutron irradiation in fission reactors. In step with development of advanced materials, a step-wise increase of the fusion power seems to be feasible and realistic, because this DEMO reactor has the potential to produce a fusion power of 5 GW.     

Self-identification algorithm for zeolite-based thermal capacity gas sensor

Microsystem Technologies - We demonstrate a new operation mode of thermal gas sensor based on thermal capacity extraction with identification algorithm. The system is a silicon microstructure...     

Mechanical property enhancement of aligned multi-walled carbon nanotube sheets and composites through press-drawing process

A solid-state drawing and winding process was done to create thin aligned carbon nanotube (CNT) sheets from CNT arrays. However, waviness and poor packing of CNTs in the sheets are two main weaknesses restricting their reinforcing efficiency in composites. This report proposes a simple press-drawing technique to reduce wavy CNTs and to enhance dense packing of CNTs in the sheets. Non-pressed and pressed CNT/epoxy composites were developed using prepreg processing with a vacuum-assisted system. Effects of pressing on the mechanical properties of the aligned CNT sheets and CNT/epoxy composites were examined. Pressing with distributed loads of 147, 221, and 294 N/m showed a substantial increase in the tensile strength and the elastic modulus of the aligned CNT sheets and their composites. The CNT sheets under a press load of 221 N/m exhibited the best mechanical properties found in this study. With a press load of 221 N/m, the pressed CNT sheet and its composite, respectively, enhanced the tensile strength by 139.1 and 141.9%, and the elastic modulus by 489 and 77.6% when compared with non-pressed ones. The pressed CNT/epoxy composites achieved high tensile strength (526.2 MPa) and elastic modulus (100.2 GPa). Results show that press-drawing is an important step to produce superior CNT sheets for development of high-performance CNT composites.     

Production of IL-6 by T cells from the femoral head of patients with rapidly destructive coxopathy (RDC)

We developed a method to improve the quantitative precision of FDG-PET scans in cancer patients. The total-lesion evaluation method generates a correlation coefficient (r) constrained Patlak parametric image of the lesion together with three calculated glucose metabolic indices: (a) the total-lesion metabolic index ("KT-tle", ml/min/lesion); (b) the total-lesion voxel index ("VT-tle", voxels/lesion); and (c) the global average metabolic index ("KV-tle", ml/min/voxel). METHODS: The glucose metabolic indices obtained from conventional region of interest (ROI) and multiplane evaluation were used as standards to evaluate the accuracy of the total-lesion evaluation method. Computer simulations and four patients with metastatic melanoma before and after chemotherapy were studied. RESULTS: Computer simulations showed that the total-lesion evaluation method has improved precision (% s.d. < 0.6%) and accuracy (approximately 10% error) compared with the conventional ROI method (% s.d. approximately 5%; approximately 25% error). The KT-tle and VT-tle indices from human FDG-PET studies using the total-lesion evaluation method showed excellent correlations with the corresponding values obtained from the conventional ROI methods and multiplane evaluation (r approximately 1.0) and CT lesion volume measurements. CONCLUSION: This method is a simple but reliable way to quantitatively monitor tumor FDG uptake. The method has several advantages over the conventional ROI method: (a) less sensitive to the ROI definition, (b) no need for image registration of serial scan data and (c) includes tumor volume changes in the global tumor metabolism.     

Identification of a golf swing robot using soft computing approach

Golf swing robots have been recently developed in an attempt to simulate the ultra high-speed swing motions of golfers. Accurate identification of a golf swing robot is an important and challenging research topic, which has been regarded as a fundamental basis in the motion analysis and control of the robots. But there have been few studies conducted on the golf swing robot identification, and comparative analyses using different kinds of soft computing methodologies have not been found in the literature. This paper investigates the identification of a golf swing robot based on four kinds of soft computing methods, including feedforward neural networks (FFNN), dynamic recurrent neural networks (DRNN), fuzzy neural networks (FNN) and dynamic recurrent fuzzy neural networks (DRFNN). The performance comparison is evaluated based on three sets of swing trajectory data with different boundary conditions. The sensitivity of the results to the changes in system structure and learning rate is also investigated. The results suggest that both FNN and DRFNN can be used as a soft computing method to identify a golf robot more accurately than FFNN and DRNN, which can be used in the motion control of the robot.     

Brave induction: a logical framework for learning from incomplete information

This paper introduces a novel logical framework for concept-learning called brave induction. Brave induction uses brave inference for induction and is useful for learning from incomplete information. Brave induction is weaker than explanatory induction which is normally used in inductive logic programming, and is stronger than learning from satisfiability, a general setting of concept-learning in clausal logic. We first investigate formal properties of brave induction, then develop an algorithm for computing hypotheses in full clausal theories. Next we extend the framework to induction in nonmonotonic logic programs. We analyze computational complexity of decision problems for induction on propositional theories. Further, we provide examples of problem solving by brave induction in systems biology, requirement engineering, and multiagent negotiation.     

Effect of cold rolling on the superconducting and electronic properties of two amorphous alloys; Nb50Zr35Si15 and Nb70Zr15Si15

The effect of cold rolling on the superconducting properties was examined for amorphous Nb₅₀Zr₃₅Si₁₅ and Nb₇₀Zr₁₅Si₁₅ superconductors. Cold rolling to 10 to 20% reduction in thickness results in a rise of superconducting transition temperature (T _c) and a decrease in transition width (T _c), upper critical field gradient near , critical current density [J _c(H)] and normal electrical resistivity (_n). Changes of about 7% forT _c 33% for T _c, 12% for and 70% forJ _c(H) are found. The rise ofT _c upon cold rolling was considered to originate from the increase in the electron-phonon coupling constant () due to an increase in the electronic density of states at the Fermi level [N(E _f)] and a decrease in the phonon frequency (), while the decreases in T_c,J _c(H) and _n were attributed to the decrease in fluxoid pinning force due to an increase in homogeneity in the amorphous structure. From the results described above, the following two conclusions were derived: (a) cold rolling causes changes in electronic and phonon-states in the quenched amorphous phase, and (b) deformation upon cold rolling occurs not only in the coarse deformation bands observable by optical microscopy, but also on a much finer scale comparable to the coherence length (7.7 nm).