Search Results (17)

Low-temperature atmospheric-pressure plasma jets are generally considered a safe medical technology with no significant long-term side effects in clinical studies reported to date. However, there are studies emerging that show plasma jets can cause significant side effects in the form of skin burns under certain conditions. Therefore, with a view of developing safer plasma treatment approaches, in this study we have set out to provide new insights into the cause of these skin burns and how to tailor plasma treatments to mitigate these effects. We discovered that joule heating by the plasma bullet currents is responsible for creating skin burns during helium plasma jet treatment of live mice. These burns can be mitigated by treating the mice at a further distance so that the visible plasma plume does not contact the skin. Under these treatment conditions we also show that the plasma jet treatment still retains its medically beneficial property of producing reactive oxygen species in vivo. Therefore, treatment distance is an important parameter for consideration when assessing the safety of medical plasma treatments. Full article

Given the cost-effective nature of promoting desirable behaviors among individuals and societies, national and local governments have widely applied the nudge concept in various public policy fields. This viewpoint briefly explains the concept of nudge and presents the trend of nudge application in public health policy with illustrative examples. While most academic evidence on its effectiveness has been derived from Western countries, there is a significant accumulation of cases of nudge practices in non-Western countries, including the Western Pacific nations. This viewpoint also provides tips for designing nudge interventions. We introduce a simple, three-step procedure for this purpose: (1) identify target behavior, (2) determine friction and fuel of the behavior, and (3) design and implement a nudge—as well as the behavioral process map and the EAST framework. Full article

Membrane proteins play important roles in biological functions, with accompanying allosteric structure changes. Understanding intramolecular dynamics helps elucidate catalytic mechanisms and develop new drugs. In contrast to the various technologies for structural analysis, methods for analyzing intramolecular dynamics are limited. Single-molecule measurements using optical microscopy have been widely used for kinetic analysis. Recently, improvements in detectors and image analysis technology have made it possible to use single-molecule determination methods using X-rays and electron beams, such as diffracted X-ray tracking (DXT), X-ray free electron laser (XFEL) imaging, and cryo-electron microscopy (cryo-EM). High-speed atomic force microscopy (HS-AFM) is a scanning probe microscope that can capture the structural dynamics of biomolecules in real time at the single-molecule level. Time-resolved techniques also facilitate an understanding of real-time intramolecular processes during chemical reactions. In this review, recent advances in membrane protein dynamics visualization techniques were presented. Full article

In this study, we report atmospheric electric field (AEF) anomalies observed around the time of earthquakes (EQs) in Japan. Using a newly developed AEF observation network with three spatially separated stations in Japan (Chofu, Kakioka, and Iwaki), we conducted a study for two EQs that occurred within a few 100 km from the EQ epicenter under relatively good local weather conditions as shown by a local all-sky camera and weather information. Time series and wavelet analyses of the AEF indicate that fluctuation anomalies in the AEF with periods of 10–60 min and larger than 70 min were observed from a few hours before up to a few hours after the occurrence of the EQs. The lag in the onset time increased with increasing distance from the EQ epicenter to the field site. The above-mentioned characteristics of these AEF fluctuation anomalies were similar among the three stations, and therefore the observed AEF anomalies were considered to be an imminent precursor of EQs. The observed AEF anomalies were likely to be caused by internal gravity waves (IGWs) generated around the EQ epicenter a few hours before the EQ, passing over the field site while changing the AEF by changing the space charge density in the surface layer of the atmosphere. Full article

Current methods used to treat non-muscle invasive bladder cancer are inadequate due to a high recurrence rate after surgery and the occurrence of adverse events such as interstitial pneumonia following intravesical instillation therapy. Low-temperature plasma is a new form of physical therapy that provides a rich source of reactive oxygen species (ROS). Oxidative solutions, created by pre-treatment of aqueous media with plasma before application to target cells, lead to the destruction of cancer cells through oxidative stress pathways. This study focuses on the effects of plasma-activated media (PAM) in bladder cancer cells. PAM treatment increases oxidative stress that leads to cell cycle arrest and concomitantly depolarises the mitochondrial membrane leading to increased mitochondrial ROS production. Cell cycle arrest and increased mitochondrial ROS production led to an increase in caspase 3/cytochrome c activity, which might explain the induction of apoptosis in bladder cancer cells in vitro and in a bladder cancer tumour in vivo. These observations highlight the potential of plasma activated solutions as a new adjuvant therapy in the clinical treatment of bladder cancer. Full article

The focus of this article is the self-organization of neural systems under constraints. In 2016, we proposed a theory for self-organization with constraints to clarify the neural mechanism of functional differentiation. As a typical application of the theory, we developed evolutionary reservoir computers that exhibit functional differentiation of neurons. Regarding the self-organized structure of neural systems, Warren McCulloch described the neural networks of the brain as being “heterarchical”, rather than hierarchical, in structure. Unlike the fixed boundary conditions in conventional self-organization theory, where stationary phenomena are the target for study, the neural networks of the brain change their functional structure via synaptic learning and neural differentiation to exhibit specific functions, thereby adapting to nonstationary environmental changes. Thus, the neural network structure is altered dynamically among possible network structures. We refer to such changes as a dynamic heterarchy. Through the dynamic changes of the network structure under constraints, such as physical, chemical, and informational factors, which act on the whole system, neural systems realize functional differentiation or functional parcellation. Based on the computation results of our model for functional differentiation, we propose hypotheses on the neuronal mechanism of functional differentiation. Finally, using the Kolmogorov–Arnold–Sprecher superposition theorem, which can be realized by a layered deep neural network, we propose a possible scenario of functional (including cell) differentiation. Full article

The cerebellum, a brain region with a high degree of plasticity, is pivotal in motor control, learning, and cognition. The cerebellar reserve is the capacity of the cerebellum to respond and adapt to various disorders via resilience and reversibility. Although structural and functional recovery has been reported in mammals and has attracted attention regarding treatments for cerebellar dysfunction, such as spinocerebellar degeneration, the regulatory mechanisms of the cerebellar reserve are largely unidentified, particularly at the circuit level. Herein, we established an optical approach using zebrafish, an ideal vertebrate model in optical techniques, neuroscience, and developmental biology. By combining two-photon laser ablation of the inferior olive (IO) and long-term non-invasive imaging of “the whole brain” at a single-cell resolution, we succeeded in visualization of the morphological changes occurring in the IO neuron population and showed at a single-cell level that structural remodeling of the olivocerebellar circuit occurred in a relatively short period. This system, in combination with various functional analyses, represents a novel and powerful approach for uncovering the mechanisms of the cerebellar reserve, and highlights the potential of the zebrafish model to elucidate the organizing principles of neuronal circuits and their homeostasis in health and disease. Full article

Nivolumab (NIVO) plus low-dose ipilimumab (IPI) has shown a promising survival benefit in first-line treatment of microsatellite instability-high (MSI-H) colorectal cancer. We hypothesized that this regimen might also be beneficial for MSI-H gastric cancer (GC), which accounts for ~5% of all GC cases. NO LIMIT (WJOG13320G/CA209-7W7) is an investigator-initiated, single-arm, open-label, 14-center phase 2 trial of NIVO plus low-dose IPI for MSI-H GC in the first-line setting. Eligibility criteria include unresectable advanced, recurrent, or metastatic gastric or esophagogastric junction cancer with a histologically confirmed diagnosis of adenocarcinoma; confirmed MSI-H status with the MSI-IVD Kit (FALCO); no prior systemic anticancer therapy; an Eastern Cooperative Oncology Group performance status of 0 or 1; and a measurable lesion per RECIST 1.1. The primary objective of the study is to determine the overall response rate (ORR) for the NIVO+IPI regimen as assessed by blinded independent central review. Secondary end points include progression-free survival, overall survival, duration of response, safety, tolerability, and biomarkers. The number of patients was set at 28 on the basis of the threshold and expected ORR values of 35 and 65%, respectively, with a one-sided alpha error of 0.025 and power of 0.80. Subjects will receive treatment with nivolumab (240 mg) biweekly in combination with ipilimumab (1 mg/kg) every 6 weeks. The results of this study should clarify the therapeutic potential of NIVO+IPI for MSI-H GC in the first-line setting. Trial registration: JapicCTI-205400. Full article

Debris flow disasters pose a serious threat to public safety in many areas all over the world, and it may cause severe consequences, including losses, injuries, and fatalities. With the emergence of deep learning and increased computation powers, nowadays, machine learning methods are being broadly acknowledged as a feasible solution to tackle the massive data generated from geo-informatics and sensing platforms to distill adequate information in the context of disaster monitoring. Aiming at detection of debris flow occurrences in a mountainous area of Sakurajima, Japan, this study demonstrates an efficient in-situ monitoring system which employs state-of-the-art machine learning techniques to exploit continuous monitoring data collected by a wireless accelerometer sensor network. Concretely, a two-stage data analysis process had been adopted, which consists of anomaly detection and debris flow event identification. The system had been validated with real data and generated favorable detection precision. Compared to other debris flow monitoring system, the proposed solution renders a batch of substantive merits, such as low-cost, high accuracy, and fewer maintenance efforts. Moreover, the presented data investigation scheme can be readily extended to deal with multi-modal data for more accurate debris monitoring, and we expect to expend addition sensory measurements shortly. Full article

In this article, the interlaminar shear behavior of a [±45°]_4s laminated carbon fiber reinforced plastic (CFRP) specimen is investigated, by utilizing microscale strain mapping in a wide field of view. A three-point bending device is developed under a laser scanning microscope, and the full-field strain distributions, including normal, shear and principal strains on the cross section of CFRP, in a three-point bending test, are measured using a developed sampling Moiré technique. The microscale shear strain concentrations at interfaces between each two adjacent layers were successfully detected and found to be positive-negative alternately distributed before damage occurrence. The 45° layers slipped to the right relative to the −45° layers, visualized from the revised Moiré phases, and shear strain distributions of the angle-ply CFRP under different loads. The absolute values of the shear strain at interfaces gradually rose with the increase of the bending load, and the sudden decrease of the shear strain peak value implied the occurrence of interlaminar damage. The evolution of the shear strain concentrations is useful in the quantitative evaluation of the potential interlaminar shear failure. Full article

This paper presents a novel approach for acoustic scene classification based on efficient acoustic feature extraction using spectro-temporal descriptors fusion. Grounded on the finding in neuroscience—“auditory system summarizes the temporal details of sounds using time-averaged statistics to understand acoustic scenes”, we devise an efficient computational framework for sound scene classification by using multipe time-frequency descriptors fusion with discriminant information enhancement. To characterize rich information of sound, i.e., local structures on the time-frequency plane, we adopt 2-dimensional local descriptors. A more critical issue raised in how to logically ‘summarize’ those local details into a compact feature vector for scene classification. Although ‘time-averaged statistics’ is suggested by the psychological investigation, directly computing time average of local acoustic features is not a logical way, since arithmetic mean is vulnerable to extreme values which are anticipated to be generated by interference sounds which are irrelevant to the scene category. To tackle this problem, we develop time-frame weighting approach to enhance sound textures as well as to suppress scene-irrelevant events. Subsequently, robust acoustic feature for scene classification can be efficiently characterized. The proposed method had been validated by using Rouen dataset which consists of 19 acoustic scene categories with 3029 real samples. Extensive results demonstrated the effectiveness of the proposed scheme. Full article

A calibrated phase-shifting digital holographic microscope system capable of improving the quality of reconstructed images is proposed. Phase-shifting errors are introduced in phase-shifted holograms for numerous reasons, such as the non-linearity of piezoelectric transducers (PZTs), wavelength fluctuations in lasers, and environmental disturbances, leading to poor-quality reconstructions. In our system, in addition to the camera used to record object information, an extra camera is used to record interferograms, which are used to analyze phase-shifting errors using a sampling Moiré technique. The quality of the reconstructed object images can be improved by the phase-shifting error compensation algorithm. Both the numerical simulation and experiment demonstrate the effectiveness of the proposed system. Full article

Developing efficient Artificial Intelligence (AI)-enabled systems to substitute the human role in non-destructive testing is an emerging topic of considerable interest. In this study, we propose a novel hammering response analysis system using online machine learning, which aims at achieving near-human performance in assessment of concrete structures. Current computerized hammer sounding systems commonly employ lab-scale data to validate the models. In practice, however, the response signal patterns can be far more complicated due to varying geometric shapes and materials of structures. To deal with a large variety of unseen data, we propose a sequential treatment for response characterization. More specifically, the proposed system can adaptively update itself to approach human performance in hammering sounding data interpretation. To this end, a two-stage framework has been introduced, including feature extraction and the model updating scheme. Various state-of-the-art online learning algorithms have been reviewed and evaluated for the task. To conduct experimental validation, we collected 10,940 response instances from multiple inspection sites; each sample was annotated by human experts with healthy/defective condition labels. The results demonstrated that the proposed scheme achieved favorable assessment accuracy with high efficiency and low computation load. Full article

This study proposes mathematical models for functional differentiations that are viewed as self-organization with external constraints. From the viewpoint of system development, the present study investigates how system components emerge under the presence of constraints that act on a whole system. Cell differentiation in embryos and functional differentiation in cortical modules are typical examples of this phenomenon. In this paper, as case studies, we deal with three mathematical models that yielded components via such global constraints: the genesis of neuronal elements, the genesis of functional modules, and the genesis of neuronal interactions. The overall development of a system may follow a certain variational principle. Full article

An optical filter is incorporated in a conventional ultrasound detection system that uses a fiber Bragg grating (FBG) and broadband light source, to demodulate the FBG sensor signal. A novel ultrasound sensing system that does not require an optical filter is presented herein. Ultrasound could be detected via the application of signal processing techniques, such as signal averaging and frequency filters, to the photodetector output that corresponds to the intensity of the reflected light from a broadband light-illuminated FBG. Ultrasonic sensitivity was observed to be enhanced when an FBG was installed as a resonant sensor. This FBG ultrasound detection system is small and cheap to fabricate because it does not use a demodulating optical filter. The experimental results demonstrate that this system could be applied to ultrasonic damage inspection and acoustic emission measurements. Furthermore, this system was able to detect ultrasound despite the amount of strain or temperature that was applied to the FBG sensor because the ultrasound detection was not sensitive to the Bragg wavelength of the FBG sensor. Full article