Terahertz-Pulse Radiation Properties of Oxygen-Deficient YBa2Cu3O7−δ Thin Films

By measuring the detailed characteristics of terahertz-pulse (THz-pulse) radiation and applying THz time-domain spectroscopy, we investigate the generation mechanism of THz-pulse radiation from biased YBa₂Cu₃O_7?δ (YBCO) thin films with various carrier concentrations. To vary the carrier concentration, the oxygen deficiency of the YBCO samples was systematically varied. With decreasing carrier concentration, the THz-pulse width increases and the response speed of supercarriers to illumination by femtosecond optical pulses tends to decrease. By examining the radiated waveforms, we clarify the influence of carrier doping not only on the relaxation process of quasiparticles but also on the excitation process. A suitably underdoped YBCO film results in maximum efficiency for generating THz radiation. This tendency is difficult to explain if we only consider the variation in transmittance, which has been the approach till now. Instead, we suggest that a variation in quasiparticle excitation efficiency due to carrier doping should also be considered.     

Repeated comprehensibility maximization in competitive learning

In this study, we propose a new type of information-theoretic method in which the comprehensibility of networks is progressively improved upon within a course of learning. The comprehensibility of networks is defined by using mutual information between competitive units and input patterns. When comprehensibility is maximized, the most simplified network configurations are expected to emerge. Comprehensibility is defined for competitive units, and the comprehensibility of the input units is measured by examining the comprehensibility of competitive units, with special attention being paid to the input units. The parameters to control the values of comprehensibility are then explicitly determined so as to maximize the comprehensibility of both the competitive units and the input units. For the sake of easy reproducibility, we applied the method to two problems from the well-known machine learning database, namely, the Senate problem and the cancer problem. In both experiments, any type of comprehensibility can be improved upon, and we observed that fidelity measures such as quantization errors could also be improved.     

Oxygen reduction at negatively charged iron porphyrins heat-treated and bridged by alkaline-earth metal ions

An ordered network of tetrasodium tetra(4-sulphonatophenyl)porphyrin iron(III) chloride (FeTPPS₄Na₄), which exhibited a higher catalytic activity for oxygen reduction than Co and Ir(CO)TPPS₄Na₄, was fabricated by complexation with alkaline-earth metal ions. Heat treatment of these complexes enhanced their catalytic activity with the highest performance observed with Ba²⁺-FeTPPS₄. The onset potential for oxygen reduction (E_onset) was 720 mV vs. Ag|AgCl, which is almost the same as that for Pt-impregnated carbon black. The number of electrons, n, transferred during oxygen reduction at a Ba²⁺-FeTPPS₄-coated electrode, as determined by rotating ring-disc experiments, was 3.9 and suggests that oxygen was reduced to water. A neutral solution of FeTPPS₄Na₄ was acidified by the addition of barium ion, and the elemental ratio Fe:S:Ba in the resulting Ba²⁺-FeTPPS₄ complex was approximately 1:4:2.5. This suggests the formation of a highly ordered network with Fe sites bridged with barium ions in addition to the normal salt bridges between sulphonates. Catalytic oxidation reactions with nitric oxide and nitrite ion as the intermediate at the heat-treated Ba²⁺-FeTPPS₄ indicate the formation of Fe(IV) and Fe(IV) π-cation radicals or Fe(V). The agreement between the potential of Fe(IV) π-cation radical formation and E_onset suggests that the redox cycle of the Fe(III)/Fe(IV) π-cation radical provides a sufficient driving force for the observed 4-electron reduction of oxygen at the heat-treated Ba²⁺-FeTPPS₄ electrode.     

Production of aminoacyl prolines using the adenylation domain of nonribosomal peptide synthetase with class III polyphosphate kinase 2-mediated ATP regeneration

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IoT-oriented high-efficient anti-malware hardware focusing on time series metadata extractable from inside a processor core

We aim to improve the efficiency of our previously proposed anti-malware hardware; it is a hardware-implemented malware detection mechanism that uses information inside the processor. We previously evaluated a prototype, but, due to its prototypical nature, there remain limitations, such as only detecting certain behaviors, high power consumption, and a tendency to bloat the training model. In this paper, we propose a circuit and a learning method to achieve high efficiency, low power consumption, and light weight for the model. In considering these three issues, we focus on time-series metadata obtained by transforming the processor information. To improve efficiency, we implement predictive detection to predict the behavior of metadata in the malware detection component. This lets the model detect malware within less than 19% of the number of execution cycles of the conventional method. To reduce power consumption, we implement a sampling circuit that interrupts the input to the detection circuit at regular intervals, reducing the system’s uptime by 99% while maintaining judgment accuracy. Finally, for a light weight, we focus on the training process of the metadata generator based on a machine-learning model. By applying sampling learning and feature dimensionality reduction in the training process, a metadata generator approximately 16% smaller than the previous version is created.

     

Nrf2 Activation Sensitizes K-Ras Mutant Pancreatic Cancer Cells to Glutaminase Inhibition

Pancreatic cancer remains intractable owing to the lack of effective therapy for unresectable cases. Activating mutations of K-ras are frequently found in pancreatic cancers, but these have not yet been targeted by cancer therapies. The Keap1-Nrf2 system plays a crucial role in mediating the oxidative stress response, which also contributes to cancer progression. Nrf2 activation reprograms the metabolic profile to promote the proliferation of cancer cells. A recent report suggested that K-ras- and Nrf2-active lung cancer cells are sensitive to glutamine depletion. This finding led to the recognition of glutaminase inhibitors as novel anticancer agents. In the current study, we used murine pancreatic cancer tissues driven by mutant K-ras and p53 to establish cell lines expressing constitutively activated Nrf2. Genetic or pharmacological Nrf2 activation in cells via Keap1 deletion or Nrf2 activation sensitized cells to glutaminase inhibition. This phenomenon was confirmed to be dependent on K-ras activation in human pancreatic cancer cell lines harboring mutant K-ras, i.e., Panc-1 and MiaPaCa-2 in response to DEM pretreatment. This phenomenon was not observed in BxPC3 cells harboring wildtype K-ras. These results indicate the possibility of employing Nrf2 activation and glutaminase inhibition as novel therapeutic interventions for K-ras mutant pancreatic cancers.     

Thickness‐Dependent Structure–Property Relationships in Strained (110) SrRuO3 Thin Films

Thickness‐dependent structure–property relationships in strained SrRuO₃ thin films on GdScO₃ (GSO) substrates are reported. The film is found to have epitaxially stabilized crystal structures that vary with the film thickness. Below 16 nm, the √2a_pc × √2a_pc × 2a_pc monoclinic structure is stabilized while above 16 nm the film has the a_pc × 2a_pc × a_pc tetragonal structure. The thickness‐dependent structural changes are ascribed to the substrate‐induced modification in the RuO₆ octahedral rotation pattern, which highlights the significance of the octahedral rotations for the epitaxial strain accommodation in the coherently‐grown films. Close relationships between the structural and physical properties of the films are also found. The monoclinic film has the uniaxial magnetic easy axis 45° away from the [110]_GSO direction while the tetragonal film has the one that lies along the in‐plane [1–10]_GSO direction. The results demonstrate that the octahedral rotations in the strained perovskite oxide thin films are a key factor for determining their structure phases and physical properties.     

Structural enhanced information and its application to improved visualization of self-organizing maps

In this paper, we propose structural enhanced information for detecting and visualizing main features in input patterns. We have so far proposed information enhancement for feature detection, where, if we want to focus upon components such as units and connection weights and interpret the functions of the components, we have only to enhance competitive units with the components. Though this information enhancement has given favorable results in feature detection, we further refine the information enhancement and propose structural enhanced information. In structural enhanced information, three types of enhanced information can be differentiated, that is, first-, second- and third-order enhanced information. The first-order information is related to the enhancement of competitive units themselves in a competitive network, and the second-order information is dependent upon the enhancement of competitive units with input patterns. Then, the third-order information is obtained by subtracting the effect of the first-order information from the second-order information. Thus, the third-order information more explicitly represents information on input patterns. With this structural enhanced information, we can estimate more detailed features in input patterns. For demonstrating explicitly and intuitively the improved performance of our method, the conventional SOM was used, and we transformed competitive unit outputs so as to improve visualization. The method was applied to the well-known Iris problem, an OECD countries classification problem and the Johns Hopkins University Ionosphere database. In all these problems, we succeeded in visualizing the detailed and important features of input patterns by using the third-order information.