Effect of Cathodal Transcranial Direct Current Stimulation on a Child with Involuntary Movement after Hypoxic Encephalopathy

The aim of the study was to investigate the effect of cathodal transcranial direct current stimulation to the supplementary motor area to inhibit involuntary movements of a child. An 8-year-old boy who developed hypoxic encephalopathy after asphyxia at the age of 2 had difficulty in remaining standing without support because of involuntary movements. He was instructed to remain standing with his plastic ankle-foot orthosis for 10 s at three time points by leaning forward with his forearms on a desk. He received cathodal or sham transcranial direct current stimulation to the supplementary motor area at 1 mA for 10 min. Involuntary movements during standing were measured using an accelerometer attached to his forehead. The low-frequency power of involuntary movements during cathodal transcranial direct current stimulation significantly decreased compared with that during sham stimulation. No adverse effects were observed. Involuntary movement reduction by cathodal stimulation to supplementary motor areas suggests that stimulations modulated the corticobasal ganglia motor circuit. Cathodal stimulation to supplementary motor areas may be effective for reducing involuntary movements and may be safely applied to children with movement disorders

Formal Analysis of Non-profiled Deep-learning Based Side-channel Attacks

This paper formally analyzes two major non-profiled deep-learning-based side-channel attacks (DL-SCAs): differential deep-learning analysis (DDLA) by Timon and collision DL-SCA by Staib and Moradi. These DL-SCAs leverage supervised learning in non-profiled scenarios. Although some intuitive descriptions of these DL-SCAs exist, their formal analyses have been rarely conducted yet, which makes it unclear why and when the attacks succeed and how the attack can be improved. In this paper, we provide the first information-theoretical analysis of DDLA. We reveal its relevance to the mutual information analysis (MIA), and then present three theorems stating some limitations and impossibility results of DDLA. Subsequently, we provide the first probability-theoretical analysis on collision DL-SCA. After presenting its formalization with a proposal of our distinguisher for collision DL-SCA, we prove its optimality. Namely, we prove that the collision DL-SCA using our distinguisher theoretically maximizes the success rate if the neural network (NN) training is completely successful (namely, the NN completely imitates the true conditional probability distribution). Accordingly, we propose an improvement of the collision DL-SCA based on a dedicated NN architecture and a full-key recovery methodology using multiple neural distinguishers. Finally, we experimentally evaluate non-profiled (DL-)SCAs using a newly created dataset using publicly available first-order masked AES implementation. The existing public dataset of side-channel traces is insufficient to evaluate collision DL-SCAs due to a lack of substantive side-channel traces for different key values. Our dataset enables a comprehensive evaluation of collision (DL-)SCAs, which clarifies the current situation of non-profiled (DL-)SCAs

Determination of tritium activity and chemical forms in the exhaust gas from a large fusion test device

A water bubbler system that can distinguish chemical forms of tritium was proposed for long-term tritium monitoring of the exhaust gas of a large fusion test device. The characteristics and performance of the water bubbler system were evaluated under operational conditions and confirmed to be suitable for tritium monitoring. For the tritium measurements, the water bubbler system determined the tritium activity and distinguished the chemical forms of tritium. The tritium activity and chemical forms in the exhaust gas provided helpful information to understand the tritium behavior in the large fusion test device

Effects of Rotation on Standing Accretion Shock Instability in Nonlinear Phase for Core-Collapse Supernovae

We studied the effects of rotation on standing accretion shock instability (SASI) by performing three-dimensional hydrodynamics simulations. Taking into account a realistic equation of state and neutrino heating/cooling, we prepared a spherically symmmetric and steady accretion flow through a standing shock wave onto a proto-neutron star (PNS). When the SASI entered the nonlinear phase, we imposed uniform rotation on the flow advecting from the outer boundary of the iron core, whose specific angular momentum was assumed to agree with recent stellar evolution models. Using spherical harmonics in space and Fourier decompositions in time, we performed mode analysis of the nonspherical deformed shock wave to observe rotational effects on the SASI in the nonlinear phase. We found that rotation imposed on the axisymmetric SASI did not make any spiral modes and hardly affected sloshing modes, except for steady l=2, m=0 modes. In contrast, rotation imposed on the non-axisymmetric flow increased the amplitude of spiral modes so that some spiral flows accreting on the PNS were more clearly formed inside the shock wave than without rotation. The amplitudes of spiral modes increased significantly with rotation in the progressive direction.Comment: 27 pages, 11 figures, Submitted to Ap

Explosive nucleosynthesis in the neutrino-driven aspherical supernova explosion of a non-rotating 15M⊙M_{\odot} star with solar metallicity

We investigate explosive nucleosynthesis in a non-rotating 15$M_\odot$ star with solar metallicity that explodes by a neutrino-heating supernova (SN) mechanism aided by both standing accretion shock instability (SASI) and convection. To trigger explosions in our two-dimensional hydrodynamic simulations, we approximate the neutrino transport with a simple light-bulb scheme and systematically change the neutrino fluxes emitted from the protoneutron star. By a post-processing calculation, we evaluate abundances and masses of the SN ejecta for nuclei with the mass number $\le 70$ employing a large nuclear reaction network. Aspherical abundance distributions, which are observed in nearby core-collapse SN remnants, are obtained for the non-rotating spherically-symmetric progenitor, due to the growth of low-mode SASI. Abundance pattern of the supernova ejecta is similar to that of the solar system for models whose masses ranges (0.4-0.5) \Ms of the ejecta from the inner region (\le 10,000\km) of the precollapse core. For the models, the explosion energies and the \nuc{Ni}{56} masses are $\simeq 10^{51} \rm erg$ and (0.05-0.06) \Ms, respectively; their estimated baryonic masses of the neutron star are comparable to the ones observed in neutron-star binaries. These findings may have little uncertainty because most of the ejecta is composed by matter that is heated via the shock wave and has relatively definite abundances. The abundance ratios for Ne, Mg, Si and Fe observed in Cygnus loop are well reproduced with the SN ejecta from an inner region of the 15\Ms progenitor.Comment: 15 pages, 1 table, 17 figures, accepted for publication in Astrophyscal Journa

Multiple-Valued Plaintext-Checking Side-Channel Attacks on Post-Quantum KEMs

In this paper, we present a side-channel analysis (SCA) on key encapsulation mechanisms (KEMs) based on the Fujisaki–Okamoto (FO) transformation and its variants. Many post-quantum KEMs usually perform re-encryption during key decapsulation to achieve chosen-ciphertext attack (CCA) security. The side-channel leakage of re-encryption can be exploited to mount a key-recovery plaintext-checking attack (KR-PCA), even if the chosen-plaintext attack (CCA) secure decryption constructing the KEM is securely implemented. Herein, we propose an efficient side-channel-assisted KR-PCA on post-quantum KEMs, and achieve a key recovery with significantly fewer attack traces than existing ones in TCHES 2022 and 2023. The basic concept of the proposed attack is to introduce a new KR-PCA based on a multiple-valued (MV-)PC oracle and then implement a dedicated MV-PC oracle based on a multi-classification neural network (NN). The proposed attack is applicable to the NIST PQC selected algorithm Kyber and the similar lattice-based Saber, FrodoKEM and NTRU Prime, as well as SIKE. We also present how to realize a sufficiently reliable MV-PC oracle from NN model outputs that are not 100% accurate, and analyze the tradeoff between the key recovery success rate and the number of attack traces. We assess the feasibility of the proposed attack through attack experiments on three typical symmetric primitives to instantiate a random oracle (SHAKE, SHA3, and AES software). The proposed attack reduces the number of attack traces required for a reliable key recovery by up to 87% compared to the existing attacks against Kyber and other lattice-based KEMs, under the condition of 99.9999% success rate for key recovery. The proposed attack can also reduce the number of attack traces by 85% for SIKE

Isotope Composition and Chemical Species of Monthly Precipitation Collected at the Site of a Fusion Test Facility in Japan

The deuterium plasma experiment was started using the Large Helical Device (LHD) at the National Institute for Fusion Science (NIFS) in March 2017 to investigate high-temperature plasma physics and the hydrogen isotope effects towards the realization of fusion energy. In order to clarify any experimental impacts on precipitation, precipitation has been collected at the NIFS site since November 2013 as a means to assess the relationship between isotope composition and chemical species in precipitation containing tritium. The tritium concentration ranged from 0.10 to 0.61 Bq L−1 and was high in spring and low in summer. The stable isotope composition and the chemical species were unchanged before and after the deuterium plasma experiment. Additionally, the tritium concentration after starting the deuterium plasma experiment was within three sigma of the average tritium concentration before the deuterium plasma experiment. These results suggested that there was no impact by tritium on the environment surrounding the fusion test facility

Preparatory acoustic emission activity of hydraulic fracture in granite with various viscous fluids revealed by deep learning technique

To investigate the influence of fluid viscosity on the fracturing process, we conducted hydraulic fracturing experiments on Kurokami-jima granite specimens with resins of various viscosities. We monitored the acoustic emission (AE) activity during fracturing and estimated the moment tensor (MT) solutions for 54 727 AE events using a deep learning technique. We observed the breakdown at 14–22 MPa of borehole pressure, which was dependent on the viscosity, as well as two preparatory phases accompanying the expansion of AE-active regions. The first expansion phase typically began at 10–30 per cent of the breakdown pressure, where AEs occurred three-dimensionally surrounding the wellbore and their active region expanded with time towards the external boundaries of the specimen. The MT solutions of these AEs corresponded to crack-opening (tensile) events in various orientations. The second expansion phase began at 90–99 per cent of the breakdown pressure. During this phase, a new planar AE distribution emerged from the borehole and expanded along the maximum compression axis, and the focal mechanisms of these AEs corresponded to the tensile events on the AE-delineating plane. We interpreted that the first phase was induced by fluid penetration into pre-existing microcracks, such as grain boundaries, and the second phase corresponded to the main fracture formation. Significant dependences on fluid viscosity were observed in the borehole pressure at the time of main fracture initiation and in the speed of the fracture propagation in the second phase. The AE activity observed in the present study was fairly complex compared to that observed in previous experiments conducted on tight shale samples. This difference indicates the importance of the interaction between the fracturing fluid and pre-existing microcracks in the fracturing process

A THREE-PHASE INDUCTIVE SENSOR FOR IN VIVO MEASUREMENT OF ELECTRICAL ANISOTROPY OF BIOLOGICAL TISSUES

Biological tissue will have anisotropy in electrical conductivity, due to the orientation of muscular fibers or neural axons as well as the distribution of large size blood vessels. Thus, the in vivo measurement of electrical conductivity anisotropy can be used to detect deep-seated vessels in large organs such as the liver during surgeries. For diagnostic applications, decrease of anisotropy may indicate the existence of cancer in anisotropic tissues such as the white matter of the brain or the mammary gland in the breast.In this paper, we will introduce a new tri-phase induction method to drive rotating high-frequency electrical current in the tissue for the measurement of electrical conductivity anisotropy. In the measurement, three electromagnets are symmetrically placed on the tissue surface and driven by high-frequency alternative currents of  0 kHz, modulated  with 1 kHz 3-phase signals. In the center area of three magnets, magnetic fields are superimposed to produce a rotating induction current. This current produces electrical potentials among circularly arranged electrodes to be used to find the conductivity in each direction determined by the electrode pairs. To find the horizontal and vertical signal components, the measured potentials are amplified by a 2ch lock-in amplifier phase-locked with the 1 kHz reference signal. The superimposed current in the tissue was typically 45 micro Amperes when we applied 150 micro Tesla of magnetic field. We showed the validity of our method by conducting in vitro measurements with respect to artificially formed anisotropic materials and preliminary in vivo measurements on the pig’s liver.Compared to diffusion tensor MRI method, our anisotropy sensor is compact and advantageous for use during surgical operations because our method does not require strong magnetic field that may disturb ongoing surgical operations.Biological tissue will have anisotropy in electrical conductivity, due to the orientation of muscular fibers or neural axons as well as the distribution of large size blood vessels. Thus, the in vivo measurement of electrical conductivity anisotropy can be used to detect deep-seated vessels in large organs such as the liver during surgeries. For diagnostic applications, decrease of anisotropy may indicate the existence of cancer in anisotropic tissues such as the white matter of the brain or the mammary gland in the breast.In this paper, we will introduce a new tri-phase induction method to drive rotating high-frequency electrical current in the tissue for the measurement of electrical conductivity anisotropy. In the measurement, three electromagnets are symmetrically placed on the tissue surface and driven by high-frequency alternative currents of  0 kHz, modulated  with 1 kHz 3-phase signals. In the center area of three magnets, magnetic fields are superimposed to produce a rotating induction current. This current produces electrical potentials among circularly arranged electrodes to be used to find the conductivity in each direction determined by the electrode pairs. To find the horizontal and vertical signal components, the measured potentials are amplified by a 2ch lock-in amplifier phase-locked with the 1 kHz reference signal. The superimposed current in the tissue was typically 45 micro Amperes when we applied 150 micro Tesla of magnetic field. We showed the validity of our method by conducting in vitro measurements with respect to artificially formed anisotropic materials and preliminary in vivo measurements on the pig’s liver.Compared to diffusion tensor MRI method, our anisotropy sensor is compact and advantageous for use during surgical operations because our method does not require strong magnetic field that may disturb ongoing surgical operations

EM Attack Is Non-Invasive? - Design Methodology and Validity Verification of EM Attack Sensor

This paper presents a standard-cell-based semi-automatic design methodology of a new conceptual countermeasure against electromagnetic (EM) analysis and fault-injection attacks. The countermeasure namely EM attack sensor utilizes LC oscillators which detect variations in the EM field around a cryptographic LSI caused by a micro probe brought near the LSI. A dual-coil sensor architecture with an LUT-programming-based digital calibration can prevent a variety of microprobe-based EM attacks that cannot be thwarted by conventional countermeasures. All components of the sensor core are semi-automatically designed by standard EDA tools with a fully-digital standard cell library and hence minimum design cost. This sensor can be therefore scaled together with the cryptographic LSI to be protected. The sensor prototype is designed based on the proposed methodology together with a 128bit-key composite AES processor in 0.18um CMOS with overheads of only 1.9% in area, 7.6% in power, and 0.2% in performance, respectively. The validity against a variety of EM attack scenarios has been verified successfully