A new lead alloy current-collector manufactured by a powder rolling process and its corrosion behavior under lead-acid battery conditions

A new powder rolling process for manufacturing current-collector sheets for lead-acid batteries has been developed. Gas-atomized lead–tin and lead–tin–calcium alloy powders obtained by a rapid solidification process in air were employed as raw materials for the powder rolling process. The corrosion behavior of powder-rolled lead–tin alloys with various compositions of tin has been investigated. A dipping corrosion test of square plain sheets of the alloys was performed in H₂SO₄ at 75 °C. The test was repeated up to 20 cycles with each cycle consisting of a controlled 10 mA cm⁻² oxidation current for 6 h and a rest under open circuit voltage for 6 h. The extent of corrosion–elongation and the appearance of the corroded surface of the tested specimens were the main observations. The corrosion–elongation of the corroded sheet of a powder-rolled lead alloy containing 1.5 wt% tin with ca. 200 μm initial thickness was less than 5%, whereas that of the corroded sheet of the cast-rolled lead alloy containing 1.5 wt% tin with the same initial thickness was 25–30% under the same corrosion test conditions. The corroded powder-rolled sheet of the 1.5 wt% tin lead alloy has uniform corrosion, but the cast-rolled sheet of lead alloy containing 1.5 wt% tin was much distorted and was perforated by the corrosion. Intergranular corrosion of the powder-rolled lead–tin alloys was much suppressed as compared with that of the cast-rolled lead–tin alloys.     

Robust intelligent PCA‐based face recognition framework using GNP‐fuzzy data mining

Traditional principal component analysis (PCA) based face recognition algorithms have a low recognition accuracy due to the influence of noise and illumination changes. This paper proposes a robust, intelligent PCA‐based face recognition framework in the complicated illumination database when using multiple training images per person (MTIP‐CID). There are mainly two improvements in the proposed method. One is that a face‐recognition‐oriented genetic‐based clustering algorithm is introduced to reduce the influence of a large number of classes on the classification accuracy in the MTIP‐CID. The other is that a classifier based on fuzzy class association rules (FCARs) is applied to mine the inherent relationships between eigenfaces and to improve the robustness of PCA‐based face recognition in noisy environments. Experimental results on the extended Yale‐B database demonstrate that the proposed framework performs better and is more robust against noise compared with other traditional face recognition algorithms, i.e. linear discriminant analysis (LDA) and local binary patterns (LBPs). © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Fast computation of Q‐value‐based dynamic programming on road networks

One of the essential components of vehicle navigation systems is route planning. The single shortest path problem and multiple shortest path problem have been widely studied for route planning. This paper introduces a Q‐value‐based dynamic programming using the division concept for solving both single and multiple shortest path problems on road networks. The proposed algorithm divides the whole network into different divisions, and the updating of Q values in each division is one stage for searching the optimal routes on road networks. The proposed algorithm can greatly save the computational time without any preprocessing on the road networks. The proposed algorithm is also systematically studied in various sizes of road networks. The simulation results show the efficiency and effectiveness of the proposed algorithm on large‐scale road networks. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Dynamic optimal route search algorithm for car navigation systems with preferences by dynamic programming

Optimal route search to the destination is one of the most important functions of car navigation devices. The development of road traffic infrastructure has made it possible to receive real‐time information of the traffic situation. Route search algorithms for car navigation devices make use of this information to avoid the traffic congestions. Such algorithms should find the new optimal route efficiently when the traffic situation changes. Usually, the minimum traveling time or distance is considered to define the optimal route. However, the minimum traveling time or distance is not always what the user is looking for. The user may prefer to travel on a certain route even at the cost of traveling time or distance. Car navigation devices should consider such preferences when finding the optimal route. In this paper, we propose a dynamic programming algorithm to find the optimal route considering that it should deal with the changes of the traffic situation and multiple criteria. The proposed method uses the information from the previous computation to find the new optimal route considering user preferences when the traveling time of the road section changes. The proposed method was applied to a real road network to find the optimal route. Results show that the proposed method can find the user‐preferred optimal route. Simulation results also show better calculation time of the proposed method compared to the Dijkstra algorithm. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Germline Whole-Gene Deletion of FH Diagnosed from Tumor Profiling

Hereditary leiomyomatosis and renal cell carcinoma (HL (RCC)) entails cutaneous and uterine leiomyomatosis with aggressive type 2 papillary RCC-like histology. HLRCC is caused by pathogenic variants in the FH gene, which encodes fumarate hydratase (FH). Here, we describe an episode of young-onset RCC caused by a genomic FH deletion that was diagnosed via clinical sequencing. A 35-year-old woman was diagnosed with RCC and multiple metastases: histopathological analyses supported a diagnosis of FH-deficient RCC. Although the patient had neither skin tumors nor a family history of HLRCC, an aggressive clinical course at her age and pathological diagnosis of FH-deficient RCC suggested a germline FH variant. After counseling, the patient provided written informed consent for germline genetic testing. She was simultaneously subjected to paired tumor profiling tests targeting the exome to identify a therapeutic target. Although conventional germline sequencing did not detect FH variants, exome sequencing revealed a heterozygous germline FH deletion. As such, paired tumor profiling, not conventional sequencing, was required to identify this genetic deletion. RCC caused by a germline FH deletion has hitherto not been described in Japan, and the FH deletion detected in this patient was presumed to be of maternal European origin. Although the genotype-phenotype correlation in HLRCC-related tumors is unclear, the patient’s family was advised to undergo genetic counseling to consider additional RCC screening.     

Enhancing the generalization ability of neural networks through controlling the hidden layers

In this paper we proposed two new variants of backpropagation algorithm. The common point of these two new algorithms is that the outputs of nodes in the hidden layers are controlled with the aim to solve the moving target problem and the distributed weights problem. One algorithm (AlgoRobust) is not so insensitive to the noises in the data, the second one (AlgoGS) is through using Gauss–Schmidt algorithm to determine in each epoch which weight should be updated, while the other weights are kept unchanged in this epoch. In this way a better generalization can be obtained. Some theoretical explanations are also provided. In addition, simulation comparisons are made between Gaussian regularizer, optimal brain damage (OBD) and the proposed algorithms. Simulation results confirm that the new proposed algorithms perform better than that of Gaussian regularizer, and the first algorithm AlgoRobust performs better than the second algorithm AlgoGS in the noisy data. On the other hand AlgoGS performs better than the AlgoRobust on the data without noise and the final structure obtained by two new algorithms is comparable to that obtained by using OBD.     

Coincidence timing of Schottky CdTe detectors for tomographic imaging

Schottky CdTe detectors are good candidates for large pixel array imagers. For use of such arrays in Positron Emission Tomography (PET) the coincidence timing of the detectors is very important, since it reduces the background from random coincidences. The coincidence timing of a small 2×2×1 mm³ detector has been measured as 11.6 ns, and thus is not much worse than the timing of BGO scintillators, commonly used in PET.     

Universal learning network and its application to robust control

Universal learning networks (ULNs) and robust control system design are discussed, ULNs provide a generalized framework to model and control complex systems. They consist of a number of interconnected nodes where the nodes may have any continuously differentiable nonlinear functions in them and each pair of nodes can be connected by multiple branches with arbitrary time delays. Therefore, physical systems which can be described by differential or difference equations and also their controllers can be modeled in a unified way. So, ULNs constitute a superset of neural networks or fuzzy neural networks. In order to optimize the systems, a generalized learning algorithm is derived for the ULNs, in which both the first order derivatives (gradients) and the higher order derivatives are incorporated. The derivatives are calculated by using forward or backward propagation schemes. These algorithms for calculating the derivatives are extended versions of back propagation through time (BPTT) and real time recurrent learning (RTRL) by Williams in the sense that generalized nonlinear functions and higher order derivatives are dealt with. As an application of ULNs, the higher order derivative, one of the distinguished features of ULNs, is applied to realizing a robust control system in this paper. In addition, it is shown that the higher order derivatives are effective tools to realize sophisticated control of nonlinear systems. Other features of ULNs such as multiple branches with arbitrary time delays and using a priori information will be discussed in other papers.     

In vitro and in vivo antibacterial activities of CS-834, a novel oral carbapenem

CS-834 is a novel oral carbapenem antibiotic. This compound is an ester-type prodrug of the active metabolite R-95867. The antibacterial activity of R-95867 was tested against 1,323 clinical isolates of 35 species and was compared with those of oral cephems, i.e., cefteram, cefpodoxime, cefdinir, and cefditoren, and that of a parenteral carbapenem, imipenem. R-95867 exhibited a broad spectrum of activity covering both gram-positive and -negative aerobes and anaerobes. Its activity was superior to those of the other compounds tested against most of the bacterial species tested. R-95867 showed potent antibacterial activity against clinically significant pathogens: methicillin-susceptible Staphylococcus aureus including ofloxacin-resistant strains, Streptococcus pneumoniae including penicillin-resistant strains, Clostridium perfringens, Neisseria spp., Moraxella catarrhalis, most members of the family Enterobacteriaceae, and Haemophilus influenzae (MIC at which 90% of strains are inhibited, < or =0.006 to 0.78 microg/ml). R-95867 was quite stable to hydrolysis by most of the beta-lactamases tested except the metallo-beta-lactamases from Stenotrophomonas maltophilia and Bacteroides fragilis. R-95867 showed potent bactericidal activity against S. aureus and Escherichia coli. Penicillin-binding proteins 1 and 4 of S. aureus and 1Bs, 2, 3, and 4 of E. coli had high affinities for R-95867. The in vivo efficacy of CS-834 was evaluated in murine systemic infections caused by 16 strains of gram-positive and -negative pathogens. The efficacy of CS-834 was in many cases superior to those of cefteram pivoxil, cefpodoxime proxetil, cefdinir, and cefditoren pivoxil, especially against infections caused by S. aureus, penicillin-resistant S. pneumoniae, E. coli, Citrobacter freundii, and Proteus vulgaris. Among the drugs tested, CS-834 showed the highest efficacy against experimental pneumonia in mice caused by penicillin-resistant S. pneumoniae.     

Cytologic study of ascites and the endometrium in ovarian carcinoma. Clinical significance

OBJECTIVE: To ascertain the usefulness of endometrial cytology with ovarian cancers when examining extension of the disease and to analyze significant factors associated with migration of ovarian cancer cells into the uterine cavity. STUDY DESIGN: Cytologic results on ascites and the endometrium were analyzed in 87 patients with primary ovarian cancer in the absence of metastasis to the endometrium or cervicovagina. RESULTS: Positive results for cytology were found in 62/87 of ascites cases (71.3%) and in 20/87 endometrium cases (23.0%). The 15 cases (15/62 or 24.2%) positive for ascitic and endometrial cytology, divided clinically into stage III (6 cases) and stage IV (9 cases), were classified histologically as serous, 7 cases; mucinous, 2 cases; clear cell, 4 cases; endometrioid, 1 case; and unclassified, 1 case. Half the clear cell carcinomas (4/8 or 50.0%) were positive in the ascites and endometrium. The ascitic volume at surgery exceeded 500 mL in 9/15 cases (60.0%). CONCLUSION: Papillae with basement membrane material in the cores may be structurally associated with migration of ovarian cancer cells into the uterine cavity, especially in clear cell carcinomas. Cytologic positivity of the endometrium and ascites significantly correlated with ascitic volume.