Dominant Model-Parameter Determination for the Analysis of Current Imbalance Across Paralleled Power Transistors

In this article, we propose a new sensitivity-based analytical equation, the nn -devices forward propagation of variance (NFPV). Using the proposed NFPV equation, the dominant device model parameters— essential for accurate analysis of energy-loss variation due to the current imbalance across paralleled power transistors from statistical parameter variations—are efficiently determined. The proposed method with the NFPV equation is faster than conventional methods that use Monte Carlo simulation. We conducted experimental validation using the measured current–voltage characteristics of commercially available 100 silicon mosfet s and 300 silicon carbide mosfet s. The results show that the proposed NFPV-based method efficiently finds the dominant device model parameters, which are sufficient and necessary to reproduce the energy-loss variation, regardless of the number of parallel transistors. The results also show that the determined dominant device model parameters are valid under practical situations, such as uneven parasitic inductances and device temperature imbalance among paralleled transistors. The proposed method determines the dominant device model parameters 9.33× faster than the conventional method while maintaining the same accuracy. Additionally, we demonstrate that, compared with the conventional method, an increase in the number of candidate statistical model parameters increases the efficiency of the proposed method

Numerical method for evaluating the lateral resistance of sleepers in ballasted tracks

AbstractBallasted track sleepers have the important function of providing sufficient lateral resistance to prevent the lateral movement of rails. If the lateral force induced by the thermal expansion of steel rails overcomes the lateral resistance of sleepers, rail buckling may occur. More attention has been paid to this problem of lateral stability since the introduction of continuous welded rails. However, there is a high degree of uncertainty in the prediction of the lateral resistance of sleepers. In view of the foregoing, a series of laboratory tests was conducted on 1/5-scale models to evaluate the lateral resistance of sleepers. Single-sleeper pullout tests and track panel pullout tests were conducted on different types of concrete sleepers. The results of the pullout tests revealed the effects of the sleeper shape, the sleeper spacing, and the number of sleepers on the lateral resistance. Based on the model test results, a new numerical method for evaluating the lateral resistance of sleepers is proposed

Correlations of perioperative coagulopathy, fluid infusion and blood transfusions with survival prognosis in endovascular aortic repair for ruptured abdominal aortic aneurysm

Background: Factors associated with survival prognosis among patients who undergo endovascular aortic repair (EVAR) for ruptured abdominal aortic aneurysms (rAAA) have not been sufficiently investigated. In the present study, we examined correlations between perioperative coagulopathy and 24-h and 30-day postoperative survival. Relationships between coagulopathy and the content of blood transfusions, volumes of crystalloid infusion and survival. Methods: This was a retrospective study of the medical records of all patients who underwent EVAR for rAAA at Chiba-Nishi General Hospital during the period from October 2013 to December 2015. Major coagulopathy was defined using the international normalized ratio or activated partial thromboplastin time (APTT) ratio of at least 1.5, or platelet count less than 50 × 10/l. We quantified the amounts of blood transfusions and crystalloid infusions administered from arrival to the hospital to admission to ICU following operations. Results: Coagulopathy among patients with rAAA was found to progress even after they had presented at the hospital. No statistically significant correlation between preoperative coagulopathy and mortality was found, although a significantly greater degree of postoperative coagulopathy was seen among patients who died both within 24-h and 30 days postoperatively. Among patients with postoperative coagulopathy, lesser quantities of fresh frozen plasma (FFP) compared with red cell concentrate (RCC) were used during the period from hospital arrival to postoperative ICU entry. In both groups of patients who did not survive after 24-h and 30 days, FFP was used less than RCC. Large transfusions of crystalloids administered during the periods from hospital arrival to surgery and from hospital arrival to the end of surgery were associated with postoperative incidence of major coagulopathy, death within 24-h, and death within 30 days. Conclusion: Coagulopathy progressed during care in the emergency outpatient clinic and operations. Postoperative coagulopathy was associated with poorer outcomes. Smaller FFP/RCC ratios and larger volumes of crystalloid infusion were associated with development of coagulopathy and poorer prognosis of survival

Additional kernel observer: privilege escalation attack prevention mechanism focusing on system call privilege changes

Cyberattacks, especially attacks that exploit operating system vulnerabilities, have been increasing in recent years. In particular, if administrator privileges are acquired by an attacker through a privilege escalation attack, the attacker can operate the entire system and cause serious damage. In this paper, we propose an additional kernel observer (AKO) that prevents privilege escalation attacks that exploit operating system vulnerabilities. We focus on the fact that a process privilege can be changed only by specific system calls. AKO monitors privilege information changes during system call processing. If AKO detects a privilege change after system call processing, whereby the invoked system call does not originally change the process privilege, AKO regards the change as a privilege escalation attack and applies countermeasures against it. AKO can therefore prevent privilege escalation attacks. Introducing the proposed method in advance can prevent this type of attack by changing any process privilege that was not originally changed in a system call, regardless of the vulnerability type. In this paper, we describe the design and implementation of AKO for Linux x86 64-bit. Moreover, we show that AKO can be expanded to prevent the falsification of various data in the kernel space. Then, we present an expansion example that prevents the invalidation of Security-Enhanced Linux. Finally, our evaluation results show that AKO is effective against privilege escalation attacks, while maintaining low overhead

In situ study of oxidation states of platinum nanoparticles on a polymer electrolyte fuel cell electrode by near ambient pressure hard X-ray photoelectron spectroscopy

We performed in situ hard X-ray photoelectron spectroscopy (HAXPES) measurements of the electronic states of platinum nanoparticles on the cathode electrocatalyst of a polymer electrolyte fuel cell (PEFC) using a near ambient pressure (NAP) HAXPES instrument having an 8 keV excitation source. We successfully observed in situ NAP-HAXPES spectra of the Pt/C cathode catalysts of PEFCs under working conditions involving water, not only for the Pt 3d states with large photoionization cross-sections in the hard X-ray regime but also for the Pt 4f states and the valence band with small photoionization cross-sections. Thus, this setup allowed in situ observation of a variety of hard PEFC systems under operating conditions. The Pt 4f spectra of the Pt/C electrocatalysts in PEFCs clearly showed peaks originating from oxidized Pt(II) at 1.4 V, which unambiguously shows that Pt(IV) species do not exist on the Pt nanoparticles even at such large positive voltages. The water oxidation reaction might take place at that potential (the standard potential of 1.23 V versus a standard hydrogen electrode) but such a reaction should not lead to a buildup of detectable Pt(IV) species. The voltage-dependent NAP-HAXPES Pt 3d spectra revealed different behaviors with increasing voltage (0.6 → 1.0 V) compared with decreasing voltage (1.0 → 0.6 V), showing a clear hysteresis. Moreover, quantitative peak-fitting analysis showed that the fraction of non-metallic Pt species matched the ratio of the surface to total Pt atoms in the nanoparticles, which suggests that Pt oxidation only takes place at the surface of the Pt nanoparticles on the PEFC cathode, and the inner Pt atoms do not participate in the reaction. In the valence band spectra, the density of electronic states near the Fermi edge reduces with decreasing particle size, indicating an increase in the electrocatalytic activity. Additionally, a change in the valence band structure due to the oxidation of platinum atoms was also observed at large positive voltages. The developed apparatus is a valuable in situ tool for the investigation of the electronic states of PEFC electrocatalysts under working conditions

Temporal switching and cell-to-cell variability in Ca2+ release activity in mammalian cells

Genetically identical cells in a uniform external environment can exhibit different phenotypes, which are often masked by conventional measurements that average over cell populations. Although most studies on this topic have used microorganisms, differentiated mammalian cells have rarely been explored. Here, we report that only approximately 40% of clonal human embryonic kidney 293 cells respond with an intracellular Ca2+ increase when ryanodine receptor Ca2+ release channels in the endoplasmic reticulum are maximally activated by caffeine. On the other hand, the expression levels of ryanodine receptor showed a unimodal distribution. We showed that the difference in the caffeine sensitivity depends on a critical balance between Ca2+ release and Ca2+ uptake activities, which is amplified by the regenerative nature of the Ca2+ release mechanism. Furthermore, individual cells switched between the caffeine-sensitive and caffeine-insensitive states with an average transition time of approximately 65 h, suggestive of temporal fluctuation in endogenous protein expression levels associated with caffeine response. These results suggest the significance of regenerative mechanisms that amplify protein expression noise and induce cell-to-cell phenotypic variation in mammalian cells

A New Deep State-Space Analysis Framework for Patient Latent State Estimation and Classification from EHR Time Series Data

Many diseases, including cancer and chronic conditions, require extended treatment periods and long-term strategies. Machine learning and AI research focusing on electronic health records (EHRs) have emerged to address this need. Effective treatment strategies involve more than capturing sequential changes in patient test values. It requires an explainable and clinically interpretable model by capturing the patient's internal state over time. In this study, we propose the "deep state-space analysis framework," using time-series unsupervised learning of EHRs with a deep state-space model. This framework enables learning, visualizing, and clustering of temporal changes in patient latent states related to disease progression. We evaluated our framework using time-series laboratory data from 12,695 cancer patients. By estimating latent states, we successfully discover latent states related to prognosis. By visualization and cluster analysis, the temporal transition of patient status and test items during state transitions characteristic of each anticancer drug were identified. Our framework surpasses existing methods in capturing interpretable latent space. It can be expected to enhance our comprehension of disease progression from EHRs, aiding treatment adjustments and prognostic determinations.Comment: 21 pages, 6 figure