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Abstract Genetic parasites, including viruses and transposons, exploit components from the host for their own replication. However, little is known about virus-transposon interactions within host cells. Here, we discover a strategy where human cytomegalovirus (HCMV) hijacks L1 retrotransposon encoded protein during its replication cycle. HCMV infection upregulates L1 expression by enhancing both the expression of L1-activating transcription factors, YY1 and RUNX3, and the chromatin accessibility of L1 promoter regions. Increased L1 expression, in turn, promotes HCMV replicative fitness. Affinity proteomics reveals UL44, HCMV DNA polymerase subunit, as the most abundant viral binding protein of the L1 ribonucleoprotein (RNP) complex. UL44 directly interacts with L1 ORF2p, inducing DNA damage responses in replicating HCMV compartments. While increased L1-induced mutagenesis is not observed in HCMV for genetic adaptation, the interplay between UL44 and ORF2p accelerates viral DNA replication by alleviating replication stress. Our findings shed light on how HCMV exploits host retrotransposons for enhanced viral fitness.

Abstract Lasing threshold in the conventional lasers is the minimum input power required to initiate laser oscillation. It has been widely accepted that the conventional laser threshold occurring around a unity intracavity photon number can be eliminated in the input-output curve by making the so-called β parameter approach unity. The recent experiments, however, have revealed that even in this case the photon statistics still undergo a transition from coherent to thermal statistics when the intracavity mean photon number is decreased below unity. Since the coherent output is only available above the diminished threshold, the long-sought promise of thresholdless lasers to produce always coherent light has become questionable. Here, we present an always-coherent thresholdless laser based on superradiance by two-level atoms in a quantum superposition state with the same phase traversing a high-Q cavity. Superradiant lasing was observed without the conventional lasing threshold around the unity photon number and the photon statistics remained near coherent even below it. The coherence was improved by reducing the coupling constant as well as the excited-state amplitude in the superposition state. Our results pave a way toward always-coherent thresholdless lasers with more practical media such as quantum dots, nitrogen-vacancy centers and doped ions in crystals.

Abstract Background Stroke causes long-term disabilities, highlighting the need for innovative rehabilitation strategies for reducing residual impairments. This study explored the potential of functional near-infrared spectroscopy (fNIRS) for monitoring cortical activation during rehabilitation using digital therapeutics. Methods This cross-sectional study included 18 patients with chronic stroke, of whom 13 were men. The mean age of the patients was 67.0 ± 7.1 years. Motor function was evaluated through various tests, including the Fugl–Meyer assessment for upper extremity (FMA-UE), grip and pinch strength test, and box and block test. All the patients completed the digital rehabilitation program (MotoCog®, Cybermedic Co., Ltd., Republic of Korea) while being monitored using fNIRS (NIRScout®, NIRx Inc., Germany). Statistical parametric mapping (SPM) was employed to analyze the cortical activation patterns from the fNIRS data. Furthermore, the K-nearest neighbor (K-NN) algorithm was used to analyze task performance and fNIRS data to classify the severity of motor impairment. Results The participants showed diverse task performances in the digital rehabilitation program, demonstrating distinct patterns of cortical activation that correlated with different motor function levels. Significant activation was observed in the ipsilesional primary motor area (M1), primary somatosensory area (S1), and contralateral prefrontal cortex. The activation patterns varied according to the FMA-UE scores. Positive correlations were observed between the FMA-UE scores and SPM t-values in the ipsilesional M1, whereas negative correlations were observed in the ipsilesional S1, frontal lobe, and parietal lobe. The incorporation of cortical hemodynamic responses with task scores in a digital rehabilitation program substantially improves the accuracy of the K-NN algorithm in classifying upper limb functional levels in patients with stroke. The accuracy for tasks, such as the gas stove-operation task, increased from 44.4% using only task scores to 83.3% when these scores were combined with oxy-Hb t-values from the ipsilesional M1. Conclusions The results advocated the development of tailored digital rehabilitation strategies by combining the behavioral and cerebral hemodynamic data of patients with stroke. This approach aligns with the evolving paradigm of personalized rehabilitation in stroke recovery, highlighting the need for further extensive research to optimize rehabilitation outcomes.

Abstract Lithium-sulfur batteries (LSBs) have garnered significant attention as a promising next-generation rechargeable battery, offering superior energy density and cost-effectiveness. However, the commercialization of LSBs faces several challenges, including the ionic/electronic insulating nature of the active materials, lithium polysulfide (LiPS) shuttle effect, volume expansion/contraction of the cathode, and issues with Li metal anode. Despite numerous efforts to address these challenges, previous studies have predominantly been conducted under mild conditions such as high electrolyte-to-sulfur (E/S) ratio, low sulfur loading, and excess Li metal, which cover issues related to Li metal anode. However, for realizing high-energy–density LSBs, practical conditions such as low E/S ratio, high sulfur loading, and limited Li metal are essential. Under these conditions, the increased current on Li metal and higher LiPS concentration exacerbate issues with Li metal anode such as dendrite growth, dead Li, high reactivity with electrolyte, and high reactivity with LiPSs. These problems lead to rapid failure of Li metal, significantly impacting the electrochemical performance of LSBs. Consequently, protecting Li metal anode is crucial for the practical LSBs. This paper introduces the challenges associated with Li metal anode in LSBs and reviews research focused on protecting Li metal anode in each battery component: anode, electrolyte, cathode, and separator/interlayer. Finally, we discuss future research directions of each component towards practical LSBs. Graphical Abstract

Abstract We observed the frequency pushing of the cavity resonance as a result of the coupling of the cavity field with the ground state 138Ba in a high-Q cavity. A weak probe laser propagated along the axis of a Fabry–Pérot cavity while ground-state barium atoms traversed the cavity mode perpendicularly. By operating the atom–cavity composite in the vicinity of an exceptional point, we could observe a greatly enhanced frequency shift of the cavity transmission peak, which was pushed away from the atomic resonance, resulting in up to 41 ± 7 kHz frequency shift per atom from the empty cavity resonance. We analyzed our results by using the Maxwell–Schrödinger equation and obtained good agreement with the measurements.

Abstract Structural and mechanistic studies on human odorant receptors (ORs), key in olfactory signaling, are challenging because of their low surface expression in heterologous cells. The recent structure of OR51E2 bound to propionate provided molecular insight into odorant recognition, but the lack of an inactive OR structure limited understanding of the activation mechanism of ORs upon odorant binding. Here, we determined the cryo-electron microscopy structures of consensus OR52 (OR52cs), a representative of the OR52 family, in the ligand-free (apo) and octanoate-bound states. The apo structure of OR52cs reveals a large opening between transmembrane helices (TMs) 5 and 6. A comparison between the apo and active structures of OR52cs demonstrates the inward and outward movements of the extracellular and intracellular segments of TM6, respectively. These results, combined with molecular dynamics simulations and signaling assays, shed light on the molecular mechanisms of odorant binding and activation of the OR52 family.

Abstract Owing to the emergenceof energy storage and electric vehicles, the desire for safe high‐energy‐density energy storage devices has increased research interest in anode‐free lithium metal batteries (AFLMBs). Unlike general lithium metal batteries (LMBs), in which excess Li exists to compensate for the irreversible loss of Li, only the current collector is employed as an anode and paired with a lithiated cathode in the fabrication of AFLMBs. Owing to their unique cell configuration, AFLMBs have attractive characteristics, including the highest energy density, safety, and cost‐effectiveness. However, developing AFLMBs with extended cyclability remains an issue for practical applications because the high reactivity of Li with limited inventory causes severely low Coulombic efficiency (CE), poor cyclability, and dendrite growth. To address these issues, tremendous effort has been devoted to stabilizing Li metal anodes for AFLMBs. In this review, the importance and challenges of AFLMBs are highlighted. Then, diverse strategies, such as current collectors modification, advanced electrolytes, cathode engineering, and operation protocols are thoroughly reviewed. Finally, a future perspective on the strategy is provided for insight into the basis of future research. It is hoped that this review provides a comprehensive understanding by reviewing previous research and arousing more interest in this field.

In this study, we applied machine learning to estimate soil moisture levels in South Korea by harnessing data from the Sentinel-1 C-band synthetic aperture radar (SAR). Our approach incorporated not only the relationship between backscattering coefficients and soil moisture but also diverse physical characteristics. This encompassed topographic information, soil physics data, and antecedent precipitation which is a hydrological factor influencing the initial condition of soil moisture. We applied a variety of machine-learning techniques and conducted a comprehensive analysis to compare the performance of each model.

Chromophoric dissolved organic matter (CDOM) is a mixture of various types of organic matter and a useful parameter for monitoring complex inland surface waters. Remote sensing has been widely utilized to detect CDOM in various studies; however, in many cases, the dataset is relatively imbalanced in a single region. To address these concerns, data were acquired from hyperspectral images, field reflection spectra, and field monitoring data, and the imbalance problem was solved using a synthetic minority oversampling technique (SMOTE). Using the on-site reflectance ratio of the hyperspectral images, the input variables Rrs (452/497), Rrs (497/580), Rrs (497/618), and Rrs (684/618), which had the highest correlation with the CDOM absorption coefficient aCDOM (355), were extracted. Random forest and light gradient boosting machine algorithms were applied to create a CDOM prediction algorithm via machine learning, and to apply SMOTE, low-concentration and high-concentration datasets of CDOM were distinguished by 5 m−1. The training and testing datasets were distinguished at a 75%:25% ratio at low and high concentrations, and SMOTE was applied to generate synthetic data based on the training dataset, which is a sub-dataset of the original dataset. Datasets using SMOTE resulted in an overall improvement in the algorithmic accuracy of the training and test step. The random forest model was selected as the optimal model for CDOM prediction. In the best-case scenario of the random forest model, the SMOTE algorithm showed superior performance, with testing R2, absolute error (MAE), and root mean square error (RMSE) values of 0.838, 0.566, and 0.777 m−1, respectively, compared to the original algorithm’s test values of 0.722, 0.493, and 0.802 m−1. This study is anticipated to resolve imbalance problems using SMOTE when predicting remote sensing-based CDOM. It is expected to produce and implement a machine learning model with improved reliable performance.

The objective and scope of this Limited Output Transcranial Electrical Stimulation 2023 (LOTES-2023) guidance is to update the previous LOTES-2017 guidance. These documents should therefore be considered together. The LOTES provides a clearly articulated and transparent framework for the design of devices providing limited output (specified low-intensity range) transcranial electrical stimulation for a variety of intended uses. These guidelines can inform trial design and regulatory decisions, but most directly inform manufacturer activities - and hence were presented in LOTES-2017 as “Voluntary industry standard for compliance controlled limited output tES devices”. In LOTES-2023 we emphasize that these standards are largely aligned across international standards and national regulations (including those in USA, EU, and South Korea), and so might be better understood as “Industry standards for compliance controlled limited output tES devices”. LOTES-2023 is therefore updated to reflect a consensus among emerging international standards, as well as best available scientific evidence. “Warnings” and “Precautions” are updated to align with current biomedical evidence and applications. LOTES standards applied to a constrained device dose range, but within this dose range and for different use-cases, manufacturers are responsible to conduct device-specific risk management.

IntroductionAlzheimer’s disease (AD), the most common form of dementia, is characterized by progressive cognitive decline. To address this, we conducted a randomized, double-blinded, sham-controlled study to investigate the therapeutic potential of transcranial direct current stimulation (tDCS) on patients with amyloid positron emission tomography (PET)- positive AD.MethodsParticipants already undergoing pharmacological treatment and testing positive for amyloid PET were divided into Active-tDCS (n = 8) and Sham-tDCS (n = 8) groups. For 12 weeks, participants or their caregivers administered daily bi-frontal tDCS (YMS-201B+, Ybrain Inc., Seongnam, Korea) at home (2 mA, 30 min). Pre- and post-intervention assessments included neuropsychological tests and blood sample measurements for oligomerized beta-amyloid.ResultsThe Active-tDCS group demonstrated significant improvements in cognitive domains such as language abilities, verbal memory, and attention span and in frontal lobe functions compared to the Sham-tDCS group. Furthermore, the Active-tDCS group showed a marked reduction in post-intervention plasma Aβ oligomerization tendency level, suggesting changes in pivotal AD-associated biomarkers.DiscussionOur results emphasize the potential therapeutic benefits of tDCS for mild AD patients with amyloid PET positivity and stress the urgency for broader research, considering the global challenges of dementia and the need to pursue innovative therapeutic strategies.

Small-scale reservoirs located in river estuaries are a significant water resource supporting agricultural and industrial activities; however, they face annual challenges of eutrophication and algal bloom occurrences due to excessive nutrient accumulation and watershed characteristics. Efficient management of algal blooms necessitates a comprehensive analysis of their spatiotemporal distribution characteristics. Therefore, this study aims to develop a chlorophyll-a (Chl-a) estimation model based on high-resolution satellite remote sensing data from Sentinel-2 multispectral sensors and multiple linear regression. The multiple linear regression (MLR) models were constructed using multiple reflectance-based variables that were collected over 2 years (2021–2022) in an estuarine reservoir. A total of 21 significant input variables were selected by backward elimination from the 2–4 band algorithms as employed in previous Chl-a estimation studies, along with the Sentinel-2 B1-B8A wavelength ratio. The developed algorithm exhibited a coefficient of determination of 0.65. Spatiotemporal variations in Chl-a concentration generated by the algorithm reflected the movement of high Chl-a concentration zones within the body of water. Through this analysis, it turned out that Sentinel-2-based spectral images were applicable to a small-scale reservoir which is relatively long and narrow, and the algorithm estimated changes in concentration levels over the seasons, revealing the dynamic nature of Chl-a distributions. The model developed in this study is expected to support effective algal bloom management and water quality improvement in a small-scale reservoir or similar complex water quality water bodies.

Abstract The illumination problem in mathematics questions the existence of a bounded region in which light rays from a point light source do not illuminate the whole region. Since Penrose disproved the illumination problem with elliptical reflective boundaries, the interest has mostly remained in ray optics mainly because there can be no completely dark region for light waves due to diffraction. Here, in a two-dimensional Penrose cavity with elliptical boundaries, we report experimental observation of a symmetry-broken mode in the long-wavelength regime with the half of the cavity region with reflection symmetry almost unilluminated in the steady state. The half-illuminated mode (HIM) was observed in an acoustic cavity by using the schlieren method. The HIM originated from the coherent superposition of near-degenerate modes, among which two scarred modes with opposite parities played a major role. The illuminated part of the HIM could be even flipped by choosing different coefficients in the coherent superposition of the participating modes. The HIM of the Penrose cavity provides new perspective to the illumination problem in an open system.

The human neuropeptide Y (NPY) acts through G-protein coupled receptors and is involved in food intake, stress response, anxiety, and memory retention. Here, the authors show that, unlike in other neuropeptides, both the N-terminal and the C-terminal regions of NPY interact with the NPY receptor 1.

ObjectiveGait is a complex behavior that involves not only the musculoskeletal system, but also higher-order brain functions, including cognition. This study was performed to investigate the correlation between lower limb muscle activity and cortical activation during treadmill walking in two groups of elderly people: the young-old (aged 65–74 years) and the old-old (aged 75–84 years).MethodsThirty-one young-old and 31 old-old people participated in this study. All participants were sequentially subjected to three gait conditions on a treadmill: (1) comfortable walking, (2) fast walking, and (3) cognitive dual-task walking. During treadmill walking, the activity of the lower limb muscles was measured using a surface electromyography system, and cortical activation was measured using a functional near-infrared spectroscopy system. The correlation between muscle activity and cortical activation during treadmill walking was analyzed and compared between the two groups.ResultsDuring comfortable walking, lower extremity muscle activity had a strong correlation with cortical activation, especially in the swing phase; this was significantly stronger in the young-old than the old-old. During fast walking, the correlations between lower limb muscle activity and cortical activation were stronger than those during comfortable walking in both groups. In cognitive dual-task walking, cortical activation in the frontal region and motor area was increased, although the correlation between muscle activity and cortical activation was weaker than that during comfortable walking in both groups.ConclusionThe corticomotor correlation differed significantly between the old-old and the young-old. These results suggest that gait function is compensated by regulating corticomotor correlation as well as brain activity during walking in the elderly. These results could serve as a basis for developing gait training and fall prevention programs for the elderly.

The Radiation Therapy Oncology Group (RTOG) 9310 protocol clinical trial established high-dose methotrexate (HDMTX) as the standard for primary central nervous system lymphoma (PCNSL). We aimed to investigate the RTOG 9310 protocol’s PCNSL outcomes by examining progression-free survival (PFS) and overall survival (OS) rates and determining the influential factors. Between 2007 and 2020, 87 patients were histopathologically diagnosed with PCNSL and treated with the RTOG 9310 protocol. All received HDMTX 2.5 g/m2 and vincristine 1.4 mg/m2/day for 1 day during weeks 1, 3, 5, 7, and 9, and procarbazine 100 mg/m2/day for 1 day during weeks 1, 5, and 9. Dexamethasone was administered on a standard tapering schedule from the first week to the sixth week. Whole brain radiotherapy (WBRT), consisting of 45 Gy for patients with less than a complete response to the chemotherapy or 36 Gy for complete responders, was started 1 week after the last dose of chemotherapy was administered. Within three weeks of the completion of WBRT, patients received two courses of cytarabine, which were separated by 3–4 weeks. Clinical, radiological, and histopathological characteristics were retrospectively reviewed. All patients completed five HDMTX cycles and a mean follow-up of 60.2 (range, 6–150) months. Twenty-eight (32.2%) patients experienced recurrence during follow-up. The mean time to recurrence was 21.8 months, while the mean PFS was 104.3 (95% confidence interval (CI), 90.6–118.0) months. Eleven (12.6%) patients died; the mean OS was 132.1 (95% CI, 122.2–141.9) months. The 3- and 5-year survival rates were 92.0% and 87.4%, respectively. One patient experienced acute renal failure, while the remainder tolerated any cytotoxic side effects. On multivariate analysis, the Eastern Cooperative Oncology Group performance score ≤ 2; the International Extranodal Lymphoma Study Group low-risk status; XBP-1, p53, and c-Myc negativity; homogenous enhancement; gross total resection, independently correlated with long PFS and OS. The RTOG 9310 protocol is effective for PCNSL and features good outcomes.

Colored dissolved organic matter (CDOM) in inland waters is used as a proxy to estimate dissolved organic carbon (DOC) and may be a key indicator of water quality and nutrient enrichment. CDOM is optically active fraction of DOC so that remote sensing techniques can remotely monitor CDOM with wide spatial coverage. However, to effectively retrieve CDOM using optical algorithms, it may be critical to select the absorption coefficient at an appropriate wavelength as an output variable and to optimize input reflectance wavelengths. In this study, we constructed a CDOM retrieval model using airborne hyperspectral reflectance data and a machine learning model such as random forest. We evaluated the best combination of input wavelength bands and the CDOM absorption coefficient at various wavelengths. Seven sampling events for airborne hyperspectral imagery and CDOM absorption coefficient data from 350 nm to 440 nm over two years (2016–2017) were used, and the collected data helped train and validate the random forest model in a freshwater reservoir. An absorption coefficient of 355 nm was selected to best represent the CDOM concentration. The random forest exhibited the best performance for CDOM estimation with an R2 of 0.85, Nash-Sutcliffe efficiency of 0.77, and percent bias of 3.88, by using a combination of three reflectance bands: 475, 497, and 660 nm. The results show that our model can be utilized to construct a CDOM retrieving algorithm and evaluate its spatiotemporal variation across a reservoir.

Abstract Hyperradiance in which radiation rate exceeds that of superradiance has been theoretically investigated in various coherently-coupled emitter-field systems. In most cases, either proposed setups were experimentally challenging or the mean photon number in a cavity was limited. In this paper, with numerical simulations and analytic calculations, we demonstrate that significant hyperradiance with a large mean photon number can occur in a microlaser system, where pairs of two-level atoms prepared in quantum superposition states traverse a high-Q cavity in the presence of a pump field intersecting the cavity mode. Hyperradiance is induced when the intracavity-pump Rabi frequency is out of phase with respect to the atom-cavity coupling so that the reduction of atomic polarization by the atom-cavity coupling is compensated by the pump Rabi frequency in the steady state to maximize atomic photoemission.

Abstract We present a practical laser linewidth broadening phenomenon in the viewpoint of high sensitivity of an exceptional point (EP). A stochastic simulation model is implemented to describe the fluctuations in the cavity resonance frequencies. The linewidth originated from external noises are maximized at the EP. The linewidth enhancement factor behaves similarly to the Petermann factor although the Petermann effect is not considered. In the long coherence time limit, the power spectral density of the laser exhibits a splitting in the vicinity of the EP although the cavity eigenfrequencies coalesce at the EP.

Cortical connectivity analysis is a widely used method for understanding the causes of neurological disorders and related brain mechanisms. Although there exist numerous activity analysis toolboxes for functional near-infrared spectroscopy (fNIRS), there are only a few cortical connectivity analysis toolboxes. In 2019, we released a MATALB toolbox named OptoNet, which has helped researchers to analyze brain networks using fNIRS. In this study, we developed an advanced MATLAB toolbox, named OptoNet II, to add new features that overcome the shortcomings of OptoNet. With these new features, OptoNet II can efficiently analyze cortical connectivity according to brain region using any fNIRS channel sets and can present the results of two connectivity analyses with auto-thresholding based on surrogate tests. To evaluate the efficacy of the new functions, the finger-tapping task experiment was carried out before and after transcranial direct current stimulation (tDCS) in the primary motor area. OptoNet II can efficiently show the effects of tDCS on functional brain region connectivity, which has been difficult to confirm by conventional methods. In this article, we propose the OptoNet II as a useful and efficient toolbox for researchers who want to perform cortical connectivity analysis using fNIRS.

The application diversity and evolution of AI accelerator architectures require innovative DFT solutions to address issues such as test time, test power, performance and area overhead. Full scan DFT, because of its enhanced controllability and observability, is an industrial de facto test strategy. However, it may not yield an optimal test solution with stringent design constraints of edge-based AI accelerators. In this paper, a novel test architecture based on selective-partial scan is proposed for performance, power and area (PPA) overhead constrained edge-based systolic AI accelerator. In this architecture, the structural test patterns are applied partly in functional manner, which reduces the testability problem of an array to that of a single processing element (PE); thus, resulting in reduced test time and test data volume. Moreover, a delay fault testing method based on Launch-on-Capture is presented for the partial scan based proposed architecture. Experimental results show that proposed architecture is efficient in terms of test power and test time when compared to full scan DFT.

This paper proposes a simple $1^{\mathrm {st}}$ -order disturbance observer (DO)-based optimal control (DOBOC) strategy for surface-mounted permanent magnet synchronous motor (SPMSM) drives. A detailed comparative analysis of three reduced-order (i.e., $1^{\mathrm {st}}$ , $2^{\mathrm {nd}}$ , and $3^{\mathrm {rd}}$ ) DOs has been presented in terms of structural complexity along with transient and steady-state performances. A simple $1^{\mathrm {st}}$ -order DOBOC is proposed with a considerably simple and easy gain tuning procedure without any complex equation and time-consuming weighting matrices selection while ensuring a competitive control performance. Also, the stability of three DOBOCs is proven using the Lyapunov function, which has not been carried out in the previous studies. Furthermore, this paper provides a detailed procedure to systematically select the controller and observer gains of three reduced-order (i.e., $1^{\mathrm {st}}$ , $2^{\mathrm {nd}}$ , and $3^{\mathrm {rd}}$ ) DOBOC by experiment. Comparative experiments are performed to confirm the feasibility of the proposed $1^{\mathrm {st}}$ -order DOBOC using a prototype SPMSM test-bed with a TI TMS320F28335 DSP. Finally, verification results and comparative table are presented to compare the speed tracking performance (e.g., transient response, undershoot (US), steady-state error (SSE), and robustness to load torque disturbances) of three reduced-order DOBOC methods under speed and load torque step-changes.

BackgroundGait problems are critical impairments in Parkinson's disease (PD) and are related to increased risk of fall and negatively impact activities of daily life. Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that can modify the cortical excitability of gait-related brain regions. In this study, we investigated whether multichannel tDCS with simultaneous treadmill gait training could improve gait in PD.MethodsTwenty-four patients with PD were assigned randomly to a real or sham tDCS group. Before intervention, one patient of the real tDCS group was dropped out, leaving 23 patients to be analyzed in this study. Each patient underwent 30 min of treadmill gait training for 10 sessions over four consecutive weeks. Multichannel 4x1 tDCS was applied using five 6-cm-diameter round electrodes. One anode was placed on the CZ, and four cathodes were positioned symmetrically over the FZ, C5, C6, and PZ. Anodal tDCS (2mA) and sham tDCS were delivered for 20 min. The secondary outcomes were gait performance, as measured by the timed up and go test (TUG) and freezing of gait questionnaire (FOG-Q), and balance was assessed using the dynamic gait index (DGI), Berg balance scale (BBS), and functional reach test (FRT). Motor and non-motor performance of patients with PD were assessed using the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Participants were assessed before the intervention, immediately after the intervention, and 4 weeks after completion of the intervention.ResultsThe real tDCS group showed a significant improvement in the 10-m walk test, but the sham group did not. Among the secondary outcome measures, MDS-UPDRS part II, TUG, and BBS were improved only in the real tDCS group. Particularly, MDS-UPDRS part II showed a significant group*time interaction effect, indicating that real tDCS demonstrated a better effect on the activities of daily living patients with PD.ConclusionsThe results of this pilot study suggest that multichannel tDCS applied on the leg motor cortex during treadmill gait training is a safe and effective means to improve gait velocity in patients with PD. Additional rigorous, large-sample, multicenter, randomized controlled trials are needed to confirm the effect of tDCS as a therapeutic adjunct for gait rehabilitation of patients with PD.

The low-density lipoprotein receptor-related protein 6 (LRP6) is a co-receptor of the β-catenin-dependent Wnt signaling pathway and interacts with the Wnt inhibitor sclerostin (SOST). Here the authors present the crystal structure of SOST in complex with the LRP6 E1E2 ectodomain construct, which reveals that the SOST C-terminus binds to the LRP6 E2 domain, and further validate this binding site with in vitro and in vivo experiments.

Abstract The Shannon entropy as a measure of information contents is investigated around an exceptional point (EP) in an open elliptical microcavity as a non-Hermitian system. The Shannon entropy is maximized near the EP in the parameter space for two interacting modes, but the exact maximum position is slightly off the EP toward the weak interaction region while the slopes of the Shannon entropies diverge at the EP. The Shannon entropies also show discontinuity across a specific line in the parameter space, directly related to the exchange of the Shannon entropy as well as the mode patterns with that line as a boundary. This feature results in a nontrivial topological structure of the Shannon entropy surfaces.

The modern automobile industry is rapidly shifting toward the era of self-driving cars. Due to rapid technological development, many mechanical parts in automobiles have been switched to electronic devices. Therefore, the proportion of electronic devices in modern cars is increasing. Even though many parts have been replaced by electronic devices, vehicles still require the periodic maintenance not only for mechanical parts, but also for automotive electronics. To guarantee the high reliability of automotive Application-Specific Integrated Circuits (ASICs), automotive chips are tested during manufacturing for functional and structural defects. Moreover, automobile chips are also tested using several in-field diagnostic techniques (e.g., online Built-In Self-Test (BIST), Software-Based Self-Test (SBST)) while the chips are operating. By using these in-field diagnostic techniques, functional and structural defects in automotive ASICs, which occur in the early-life cycle and normal operation, can be detected. However, automotive semiconductor devices still require testing for aging-induced defects and soft errors to prevent critical functional failures. Moreover, aging-induced defects are hard to detect with conventional in-field diagnostic techniques which is based on BIST techniques. Thus, this work presents a secure Controller Area Network (CAN) -based Test Access Mechanism (TAM) for aging defect diagnosis with efficient soft-error resilient scan cell design for automotive ASICs. The proposed TAM incurs area overhead of 6% to 9% depending upon the selection of mode identification. Further, the proposed Aging monitoring and Soft Error Resilience Flip Flop (ARFF) incurs 22% less area and power as compared to separate implementation of the Built-In Soft Error Resilience (BISER) and the Early Capture Flip Flop (ECFF).

This paper proposes an improved torque ripple minimization (TRM) method using model-based loss minimization (LM) control to reduce the torque ripples and enhance the efficiency for surface-mounted permanent magnet synchronous motor (SPMSM) drives. The conventional SPMSM drives usually achieve the maximum torque per ampere (MTPA) control by applying the zero d-axis current (ZDC) and ignore an actual core loss resistance in the controller design. Unlike the conventional MTPA method, the proposed TRM selects the appropriate d-axis current value by making the derivative of the electromagnetic torque equal to zero in the SPMSM drives. Consequently, the proposed method can improve the torque ripples and efficiency compared to the conventional MTPA. Using the proportional-integral (PI) controllers, comparative experimental verifications between the proposed model-based TRM, the conventional model-based MTPA, and the conventional model-based LM are performed through a prototype SPMSM drive with a TI TMS320F28335 digital signal processor (DSP).

This paper designs an adaptive sliding mode speed controller (ASMSC) that can compensate for parameter uncertainty of an interior permanent magnet synchronous motor (IPMSM) drive. Unlike the previous control systems, the proposed ASMSC guarantees a precise speed tracking capability in the presence of severe parameter variations without accurate knowledge on the motor parameter values and uncertainty bounds. In particular, the proposed adaptive switching gain tuning (ASGT) term can effectively solve the excessive input energy consumption problem due to an unnecessarily overestimated switching gain. Next, the convergence and stability analysis are proven through a Lyapunov function. The feasibility of the proposed approach is verified via experimental results using a prototype IPMSM test bed with a TI TMS320F28335 digital signal processor. In this paper, the proposed SMSC is investigated with two control terms: without an ASGT term and with an ASGT term. In addition, the conventional proportional-integral speed controller and conventional linear matrix inequalities based sliding mode speed controller are chosen for the performance comparison. Finally, the proposed ASMSC can assure more robust and faster speed performances against the parameter uncertainty under three dynamic load conditions.

This paper proposes an improved model predictive control (MPC) scheme with a robust prediction and stability-constrained finite states for three-phase voltage source inverters (3Φ-VSIs) with an LC filter. In this paper, the stability-constrained finite states are selected via the asymptotic stability conditions as a key factor to reduce the total harmonic distortions (THDs) and steady-state errors. Meanwhile, the Kalman filter-based observers improve the overall robustness against model mismatches and noises via a robust prediction. To select the stabilized finite states, the stability conditions are derived by the equivalent feedback-gains and constrained in the exhausting search of the proposed finite-set (FS) MPC. Unlike conventional FS-MPC methods, three control targets (i.e., robustness, stability, and optimality) are simultaneously achieved as the new contributions to remarkably enhance the voltage control performance of the 3Φ-VSI, which are also the challenge of the conventional control methods. To verify the superiority of the proposed FS-MPC, comparative studies are conducted on a prototype three-wire 3Φ-VSI system with a TI TMS320F28335 DSP under practical conditions (i.e., parameter mismatches, linear/nonlinear-load step-changes). The experimental results confirm that the performance of the proposed FS-MPC has been significantly improved in terms of lower THDs, smaller steady-state errors, faster dynamic response, and more robustness under critical system changes as compared with the conventional FS-MPC.

Understanding the concentration and distribution of cyanobacteria blooms is an important aspect of managing water quality problems and protecting aquatic ecosystems. Airborne hyperspectral imagery (HSI)—which has high temporal, spatial, and spectral resolutions—is widely used to remotely sense cyanobacteria bloom, and it provides the distribution of the bloom over a wide area. In this study, we determined the input spectral bands that were relevant in effectively estimating the main two pigments (PC, Phycocyanin; Chl-a, Chlorophyll-a) of cyanobacteria by applying data-driven algorithms to HSI and then evaluating the change in the spatio-temporal distribution of cyanobacteria. The input variables for the algorithms consisted of reflectance band ratios associated with the optical properties of PC and Chl-a, which were calculated by the selected hyperspectral bands using a feature selection method. The selected input variable was composed of six reflectance bands (465.7–589.6, 603.6–631.8, 641.2–655.35, 664.8–679.0, 698.0–712.3, and 731.4–784.1 nm). The artificial neural network showed the best results for the estimation of the two pigments with average coefficients of determination 0.80 and 0.74. This study proposes relevant input spectral information and an algorithm that can effectively detect the occurrence of cyanobacteria in the weir pool along the Geum river, South Korea. The algorithm is expected to help establish a preemptive response to the formation of cyanobacterial blooms, and to contribute to the preparation of suitable water quality management plans for freshwater environments.

High-definition transcranial direct current stimulation (HD-tDCS) has recently been proposed as a tDCS approach that can be used on a specific cortical region without causing undesirable stimulation effects. In this uncontrolled pilot study, the cortical hemodynamic changes caused by HD-tDCS applied over the ipsilesional motor cortical area were investigated in 26 stroke patients. HD-tDCS using one anodal and four cathodal electrodes at 1 mA was administered for 20 min to C3 or C4 in four daily sessions. Cortical activation was measured as changes in oxyhemoglobin (oxyHb) concentration, as found using a functional near-infrared spectroscopy (fNIRS) system during the finger tapping task (FTT) with the affected hand before and after HD-tDCS. Motor-evoked potential and upper extremity functions were also measured before (T0) and after the intervention (T1). A group statistical parametric mapping analysis showed that the oxyHb concentration increased during the FTT in both the affected and unaffected hemispheres before HD-tDCS. After HD-tDCS, the oxyHb concentration increased only in the affected hemisphere. In a time series analysis, the mean and integral oxyHb concentration during the FTT showed a noticeable decrease in the channel closest to the hand motor hotspot (hMHS) in the affected hemisphere after HD-tDCS compared with before HD-tDCS, in accordance with an improvement in the function of the affected upper extremity. These results suggest that HD-tDCS might be helpful to rebalance interhemispheric cortical activity and to reduce the hemodynamic burden on the affected hemisphere during hand motor tasks. Noticeable changes in the area adjacent to the affected hMHS may imply that personalized HD-tDCS electrode placement is needed to match each patient’s individual hMHS location.

This study estimates soil moisture content (SMC) using Sentinel-1A/B C-band synthetic aperture radar (SAR) images and an artificial neural network (ANN) over a 40 × 50-km2 area located in the Geum River basin in South Korea. The hydrological components characterized by the antecedent precipitation index (API) and dry days were used as input data as well as SAR (cross-polarization (VH) and copolarization (VV) backscattering coefficients and local incidence angle), topographic (elevation and slope), and soil (percentage of clay and sand)-related data in the ANN simulations. A simple logarithmic transformation was useful in establishing the linear relationship between the observed SMC and the API. In the dry period without rainfall, API did not decrease below 0, thus the Dry days were applied to express the decreasing SMC. The optimal ANN architecture was constructed in terms of the number of hidden layers, hidden neurons, and activation function. The comparison of the estimated SMC with the observed SMC showed that the Pearson’s correlation coefficient (R) and the root mean square error (RMSE) were 0.85 and 4.59%, respectively.

Considering the priority of water supply, agricultural water supply capacity downstream of the Yeongsan River Basin was evaluated in this study. The water balance was analyzed using the Please check all author names carefullyMODSIM-decision support system (MODSIM-DSS) to evaluate the agricultural water supply capacity. MODSIM-DSS can also be used to analyze the watershed demand status and agricultural water supply facilities. In this study, the watershed inflow and agricultural reservoir inflow (supply) data for each watershed were obtained using the SWAT outflow data. SWAT was calibrated and validated using 16-years (2005–2020) of daily streamflow data from one water level station and two weirs, by considering water withdrawal and return flows from agricultural, domestic, and industrial water use. The coefficient of determination (R2) was analyzed as 0.50 to 0.80 at three stations. Then, water balance analyses were performed for 41 years (1980–2020) by applying the SWAT outflow results to MODSIM-DSS. The results showed that agricultural water shortages of 517.8 × 106 m3, 520.0 × 106 m3, 579.8 × 106 m3, and 517.5 × 106 m3, occurred in 1992, 1994, 1995, and 2015, respectively. The efficiencies of agricultural water supply for these years were 58.2%, 58.0%, 53.2%, and 58.2%, respectively, which were lower than the 40-year average of 84.5%.

In the elderly, walking while simultaneously engaging in other activities becomes more difficult. This study aimed to examine the changes in cortical activity during walking with aging. We try to reveal the effects of an additional task and increased walking speed on cortical activation in the young-old and the old-old elderly. Twenty-seven young-old (70.2 ± 3.0 years) and 23 old-old (78.0 ± 2.3 years) participated in this study. Each subject completed four walking tasks on the treadmill, a 2 × 2 design; two single-task (ST) walking conditions with self-selected walking speed (SSWS) and fast walking speed (FWS), and two dual-task (DT) walking conditions with SSWS and FWS. Functional near-infrared spectroscopy was applied for measurement of cerebral oxyhemoglobin (oxyHb) concentration during walking. Cortical activities were increased during DT conditions compared with ST conditions but decreased during the FWS compared with the SSWS on the primary leg motor cortex, supplementary motor area, and dorsolateral prefrontal cortex in both the young-old and the old-old. These oxyHb concentration changes were significantly less prominent in the old-old than in the young-old. This study demonstrated that changes in cortical activity during dual-task walking are lower in the old-old than in the young-old, reflecting the reduced adaptive plasticity with severe aging.

This study aims to develop a reservoir operation rule adding downstream environmental flow release (EFR) to the exclusive use of irrigation water supply (IWS) from agricultural reservoirs through canals to rice paddy areas. A reservoir operation option was added in the Soil and Water Assessment Tool (SWAT) to handle both EFR and IWS. For a 366.5 km2 watershed including three agricultural reservoirs and a rice paddy irrigation area of 4744.7 ha, the SWAT was calibrated and validated using 21 years (1998–2018) of daily reservoir water levels and downstream flow data at Gongdo (GD) station. For reservoir water level and streamflow, the average root means square error (RMSE) ranged from 19.70 mm to 19.54 mm, and the coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) had no effect on the improved SWAT. By applying the new reservoir option, the EFR amount for a day was controlled by keeping the reservoir water level up in order to ensure that the IWS was definitely satisfied in any case. The downstream mean wet streamflow (Q95) decreased to 5.70 m3/sec from 5.71 m3/sec and the mean minimum flow (Q355) increased to 1.05 m3/sec from 0.94 m3/sec. Through the development of a SWAT reservoir operation module that satisfies multiple water supply needs such as IWR and EFR, it is possible to manage agricultural water in the irrigation period and control the environmental flow in non-irrigation periods. This study provides useful information to evaluate and understand the future impacts of various changes in climate and environmental flows at other sites.

The effect of the swirl clocking on three-dimensional nozzle guide vane (NGV) is investigated using computational fluid dynamics. The research reports the loss characteristics of leaned and swept NGVs and the influence of swirl clocking. The three-dimensional NGVs are built by stacking the same 2D profile along different linear axes, characterized by different angles with respect to the normal or radial direction: ε = −12° ~ +12° for the leaned and γ = −5° ~ +10° for the swept airfoils. A total of 40 models are analyzed to study the effects of lean and sweep on aerodynamic performance. To investigate the influence of swirl clocking, the analysis cases include the center of the swirl that was positioned at the leading edge as well as the middle of the passage. The prediction results show that the relationship of the changes in mass flow rate and throat area are not monotonic. Further observation confirms the redistribution of loading and flow angle under different lean and sweep angles; thus, three-dimensional design is a key influencing factor on aerodynamic performance. In the presence of swirl clocking, NGV performance is changed significantly and the findings offer new insight and opportunities to improve three-dimensional NGV airfoil design.

Nanostructured materials synthesized by the hydrothermal and thermal reduction process were tested to detect the dimethyl methylphosphonate (DMMP) as a simulant for chemical warfare agents. Manganese oxide nitrogen-doped graphene oxide with polypyrrole (MnO2@NGO/PPy) exhibited the sensitivity of 51 Hz for 25 ppm of DMMP and showed the selectivity of 1.26 Hz/ppm. Nitrogen-doped multi-walled carbon nanotube (N-MWCNT) demonstrated good linearity with a correlation coefficient of 0.997. A comparison between a surface acoustic wave and quartz crystal microbalance sensor exhibited more than 100-times higher sensitivity of SAW sensor than QCM sensor.

G nerve agents are colorless, odorless, and lethal chemical warfare agents (CWAs). The threat of CWAs, which cause critical damage to humans, continues to exist, e.g., in warfare or terrorist attacks. Therefore, it is important to be able to detect these agents rapidly and with a high degree of sensitivity. In this study, a surface acoustic wave (SAW) array device with three SAW sensors coated with different sensing materials and one uncoated sensor was tested to determine the most suitable material for the detection of nerve agents and related simulants. The three materials used were polyhedral oligomeric silsesquioxane (POSS), 1-benzyl-3-phenylthiourea (TU-1), and 1-ethyl-3-(4-fluorobenzyl) thiourea (TU-2). The SAW sensor coated with the POSS-based polymer showed the highest sensitivity and the fastest response time at concentrations below the median lethal concentration (LCt50) for tabun (GA) and sarin (GB). Also, it maintained good performance over the 180 days of exposure tests for dimethyl methylphosphonate (DMMP). A comparison of the sensitivities of analyte vapors also confirmed that the sensitivity for DMMP was similar to that for GB. Considering that DMMP is a simulant which physically and chemically resembles GB, the sensitivity to a real agent of the sensor coated with POSS could be predicted. Therefore, POSS, which has strong hydrogen bond acid properties and which showed similar reaction characteristics between the simulant and the nerve agent, can be considered a suitable material for nerve agent detection.

This paper presents a reconfigurable time-to-digital converter (TDC) used to quantize the phase of the impedance in electrical impedance spectroscopy (EIS). The TDC in the EIS system must handle a wide input-time range for analysis in the low-frequency range and have a high resolution for analysis in the high-frequency range. The proposed TDC adopts a coarse counter to support a wide input-time range and cascaded time interpolators to improve the time resolution in the high-frequency analysis without increasing the counting clock speed. When the same large interpolation factor is adopted, the cascaded time interpolators have shorter measurement time and smaller chip area than a single-stage time interpolator. A reconfigurable time interpolation factor is adopted to maintain the phase resolution with reasonable measurement time. The fabricated TDC has a peak-to-peak phase error of less than 0.72° over the input frequency range from 1 kHz to 512 kHz and the phase error of less than 2.70° when the range is extended to 2.048 MHz, which demonstrates a competitive performance when compared with previously reported designs.

This study assessed the water supply stability for Boryeong multipurpose dam by applying future dry climate change scenarios and Soil and Water Assessment Tool (SWAT). CMCC-CM, INM-CM4, and IPSL-CM5A-MR RCP 4.5 and 8.5 scenarios were selected as the future dry conditions using Runs theory and Standardized Precipitation Index (SPI). For historical (1980−1999), present (2000−2019), and future periods (2030s, 2050s, 2070s, and 2090s) of the 6 scenarios, SWAT model was used to simulate the future dam water supply stability. The stability was evaluated in terms of reliability (RT), resilience (RS), and vulnerability (V) based on the monthly target storage. The results showed that the future RT can be decreased to 0.803 in 2050s IPSL-CM5A-MR RCP 8.5 scenario from present 0.955. The future RS and V showed the minimum value of 0.003 and the biggest value of 3567.6 × 106 m3 in 2070s IPSL-CM5A-MR RCP 4.5 scenario. The future RT, RS, and V showed that the dam has low resilience and is vulnerable to future drought scenarios.