A Study on the Origin of Peroxisomes: Possibility of Actinobacteria Symbiosis

The origin of peroxisomes as having developed from the endoplasmic reticulum (ER) was proposed on the basis of the similarity between some peroxisomal proteins and ER proteins, and the localization of some peroxisomal proteins on the ER. To study the evolutionary distance between peroxisomes and ER and Prokaryotes, we carried out a phylogenetic analysis of CDC48 (cell division control 48) and its homologs, including ER-localized CDC48, CDC48 homologs in Prokaryotes and peroxisome-localized PEX1 and PEX6. A similarity search analysis of peroxisomal protein sequences to prokaryotic protein sequences using BLAST at several thresholds (E-values) was also done. We propose Actinobacteria symbiosis for the origin of peroxisomes based on the following evidence: (1) PEX1 and PEX6 are close in distance to CDC48 homologs in Actinobacteria, and these distances are closer than to ER-localized CDC48. (2) Actinobacteria proteins show the highest degree of similarity to peroxisomal proteins compared with other prokaryotes

Space-Time and Matter in IIB Matrix Model - gauge symmetry and diffeomorphism -

We pursue the study of the type IIB matrix model as a constructive definition of superstring. In this paper, we justify the interpretation of space-time as distribution of eigenvalues of the matrices by showing that some low energy excitations indeed propagate in it. In particular, we show that if the distribution consists of small clusters of size $n$, low energy theory acquires local SU(n) gauge symmetry and a plaquette action for the associated gauge boson is induced, in addition to a gauge invariant kinetic term for a massless fermion in the adjoint representation of the SU(n). We finally argue a possible identification of the diffeomorphism symmetry with permutation group acting on the set of eigenvalues, and show that the general covariance is realized in the low energy effective theory even though we do not have a manifest general covariance in the IIB matrix model action.Comment: 25 page

Self-limiting processes in thermal atomic layer etching of nickel by hexafluoroacetylacetone

Abdulrahman H. Basher, Ikutaro Hamada, and Satoshi Hamaguchi. Jpn. J. Appl. Phys. 59 090905

The Effect of Planar Sinks on the Interstitial Loop Growth under High Temperature Neutron Irradiation

The role of planar sinks such as surfaces and grain boundaries for the defect structure developments was studied in fission neutron irradiated Ni and Ni alloys of 2 at% Si, Cu, Ge and Sn to the dose of 4x10^n/m^2 (>1MeV) at 573 K by comparison between thin foil irradiation and bulk irradiation. The number density of interstitial loops increases and then decreases with the increase of distance from planar sinks. Observed defect structure developments were interpreted in terms of the variation of point defect concentration with the change of sink efficiency. The necessity of the introduction of cascade localization induced bias effect is emphasized

The Clinical Significance of CT in the Preoperative Diagnosis of Colon and Rectal Cancer

The clinical significance of CT in the preoperative diagnosis of colon and rectal cancer was studied. Thirty four patients were investigated in this series. The diagnostic criteria of the CT examination were previously established in a study of wall invasion (S factor), lymph node metastasis (N factor), liver metastasis (H factor) and peritoneal dissemination (P factor). The CT diagnosis was done prospectively according to these criteria, and the CT diagnosis was compared with the macroscopic and histological diagnosis. The accuracy of the prospective diagnosis as to H, S, N and P factors was 79.4%, 55.9%, 41.2% and 20.6%, respectively. The diagnostic value of CT seemed to be acceptable as to the H factor, but limited to some extent to the S and N factors

Consistent map building in petrochemical complexes for firefighter robots using SLAM based on GPS and LIDAR

The objective of this study was to achieve simultaneous localization and mapping (SLAM) of firefighter robots for petrochemical complexes. Consistency of the SLAM map is important because human operators compare the map with aerial images and identify target positions on the map. The global positioning system (GPS) enables increased consistency. Therefore, this paper describes two Rao-Blackwellized particle filters (RBPFs) based on GPS and light detection and ranging (LIDAR) as SLAM solutions. Fast-SLAM 1.0 and Fast-SLAM 2.0 were used in grid maps for RBPFs in this study. We herein propose the use of Fast-SLAM to combine GPS and LIDAR. The difference between the original Fast-SLAM and the proposed method is the use of the log-likelihood function of GPS; the proposed combination method is implemented using a probabilistic mathematics formulation. The proposed methods were evaluated using sensor data measured in a real petrochemical complex in Japan ranging in size from 550–380 m. RTK-GPS data was used for the GPS measurement and had an availability of 56%. Our results showed that Fast-SLAM 2.0 based on GPS and LIDAR in a dense grid map produced the best results. There was significant improvement in alignment to aerial data, and the mean square root error was 0.65 m. To evaluate the mapping consistency, accurate 3D point cloud data measured by Faro Focus 3D (± 3 mm) was used as the ground truth. Building sizes were compared; the minimum mean errors were 0.17 and 0.08 m for the oil refinery and management building area and the area of a sparse building layout with large oil tanks, respectively. Consequently, a consistent map, which was also consistent with an aerial map (from Google Maps), was built by Fast-SLAM 1.0 and 2.0 based on GPS and LIDAR. Our method reproduced map consistency results for ten runs with a variance of ± 0.3 m. Our method reproduced map consistency results with a global accuracy of 0.52 m in a low RTK-Fix-GPS environment, which was a factory with a building layout similar to petrochemical complexes with 20.9% of RTK-Fix-GPS data availability

Evaluation of respiratory rate monitoring performance using a home oxygen monitoring device among patients with interstitial lung disease and chronic obstructive pulmonary disease

Background: Home monitoring devices have been developed to measure adherence to home oxygen therapy. In this study, we evaluated the performance of TeleOx®, a commercially available remote monitoring device, in comparison with polysomnography (PSG) in patients with interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD) and the factors that affected TeleOx® correct use. Methods: TeleOx® was connected on the patient or concentrator side. The oxygen flow rates were set at 1, 3, and 5 L/min. Intraclass correlation coefficient (ICC) (2, 1) was used to determine the agreement between respiratory rate measured using TeleOx® and that measured using PSG, and the minimum acceptable level of reliability was >0.7. Results: In total, 22 patients (16 with ILD and 6 with COPD) were assessed. In patients with ILD, the detection rate of patients’ respiration assessed using TeleOx® did not change according to the device’s position. It increased from 53.5% to 79.0% by changing the position from the concentrator to the patient side in patients with COPD. The ICC (2, 1) value indicated that TeleOx® had acceptable reliability at oxygen flow rates of 1 and 3 L/min regardless of the device’s position in patients with ILD (the concentrator side: 0.9 and 0.82, respectively; the patient side: 0.95 and 0.82, respectively), whereas that did only at the oxygen flow rate of 1 L/min and in connecting TeleOx® on the patient side in patients with COPD (0.73). Conclusion: The monitoring performance of TeleOx® differed according to its position, oxygen flow rates, and patients’ diseases

Radar-Based Automatic Detection of Sleep Apnea Using Support Vector Machine

2020 International Symposium on Antennas and Propagation (ISAP), 25-28 Jan. 2021, Osaka, JapanEarly diagnosis of sleep-apnea-related breathing problems helps to avoid the increased risk they can cause. In this study, we performed simultaneous radar measurements and polysomnography on patients with sleep apnea. A support vector machine algorithm was applied to the radar data to automatically detect sleep apnea events. Support vector machine parameters were optimized using the relationship between the radar and polysomnography data. The support vector machine was found to be effective in noncontact detection of central/mixed sleep apnea events using radar data. The proposed approach achieved an accuracy of 79.5%, a recall of 71.2%, and a precision of 71.2%