Beta Burst Characteristics and Coupling within the Sensorimotor Cortical-Subthalamic Nucleus Circuit Dynamically Relate to Bradykinesia in Parkinson's Disease.

Background: Bursts of exaggerated subthalamic nucleus (STN) beta activity are believed to contribute to clinical impairments in Parkinson's disease (PD). No previous studies have explored burst characteristics and coupling across the sensorimotor cortical-STN circuit and determined their relationship to dynamic measurements of bradykinesia.

Objective: We sought to (1) establish the characteristics of sensorimotor cortical and STN bursts during naturalistic behaviors, (2) determine the predictability of STN bursts from motor cortical recordings, and (3) relate burst features to continuous measurements of bradykinesia using wearable sensors.

Field-free spin hall oscillator based on giant magnetoresistance effect and its potential for electrical synchronization.

Spin Hall nano oscillators (SHNOs) have attracted much attention in recent years due to their great potential for applications in neuromorphic computation. However, the output power of SHNOs is very low and an external magnetic field is required to generate microwave signal continuously, which hinders the further development of SHNOs. In order to solve the two problems, we propose a new-type SHNO based on the giant magnetoresistance (GMR) effect, while retaining the advantage of the simple fabrication process of the conventional oscillator.

Modeling and Analysis of Environmental Electromagnetic Interference in Multiple-Channel Neural Recording Systems for High Common-Mode Interference Rejection Performance.

Environmental electromagnetic interference (EMI) has always been a major interference source for multiple-channel neural recording systems, and little theoretical work has been attempted to address it. In this paper, equivalent circuit models are proposed to model both electromagnetic interference sources and neural signals in such systems, and analysis has been performed to generate the design guidelines for neural probes and the subsequent recording circuit towards higher common-mode interference (CMI) rejection performance while maintaining the recorded neural action potential (AP) signal quality. In vivo animal experiments with a configurable 32-channel neural recording system are carried out to validate the proposed models and design guidelines.

Quantifying local field potential dynamics with amplitude and frequency stability between ON and OFF medication and stimulation in Parkinson's disease.

Neural oscillations are critical to understanding the synchronisation of neural activities and their relevance to neurological disorders. For instance, the amplitude of beta oscillations in the subthalamic nucleus has gained extensive attention, as it has been found to correlate with medication status and the therapeutic effects of continuous deep brain stimulation in people with Parkinson's disease. However, the frequency stability of subthalamic nucleus beta oscillations, which has been suggested to be associated with dopaminergic information in brain states, has not been well explored.

Lithium Niobate Electro-Optic Modulation Device without an Overlay Layer Based on Bound States in the Continuum.

Electro-optic modulation devices are essential components in the field of integrated optical chips. High-speed, low-loss electro-optic modulation devices represent a key focus for future developments in integrated optical chip technology, and they have seen significant advancements in both commercial and laboratory settings in recent years. Current electro-optic modulation devices typically employ architectures based on thin-film lithium niobate (TFLN), traveling-wave electrodes, and impedance-matching layers, which still suffer from transmission losses and overall design limitations.

Effects of Training and Calibration Data on Surface Electromyogram-Based Recognition for Upper Limb Amputees.

Surface electromyogram (sEMG)-based gesture recognition has emerged as a promising avenue for developing intelligent prostheses for upper limb amputees. However, the temporal variations in sEMG have rendered recognition models less efficient than anticipated. By using cross-session calibration and increasing the amount of training data, it is possible to reduce these variations.

Klobuchar, NeQuickG, BDGIM, GLONASS, IRI-2016, IRI-2012, IRI-Plas, NeQuick2, and GEMTEC Ionospheric Models: A Comparison in Total Electron Content and Positioning Domains.

Global navigation satellite systems (GNSS) provide a great data source about the ionosphere state. These data can be used for testing ionosphere models. We studied the performance of nine ionospheric models (Klobuchar, NeQuickG, BDGIM, GLONASS, IRI-2016, IRI-2012, IRI-Plas, NeQuick2, and GEMTEC) both in the total electron content (TEC) domain-i.

Conduction treatment of temporal lobe epilepsy in rats: the dose-effect relationship between current resistance and therapeutic effect.

Objective: To investigate the effect of current resistance on therapeutic outcomes, and the mechanism of current conduction treatment in a rat model of temporal lobe epilepsy (TLE).

Methods: Rats were randomly divided into four groups: normal control, epileptic group, low-resistance conduction (LRC) and high-resistance conduction (HRC) group. The content of glutamate (Glu) and gamma-amino butyric acid (GABA) in the hippocampus was determined using a neurotransmitter analyzer.

Assessment of solar energy potential in China using an ensemble of photovoltaic power models.

Development of solar energy is one of the key solutions towards carbon neutrality in China. The output of solar energy is dependent on weather conditions and shows distinct spatiotemporal characteristics. Previous studies have explored the photovoltaic (PV) power potential in China but with single models and low-resolution radiation data.

Enhanced Terahertz Fingerprint Sensing Mechanism Study of Tiny Molecules Based on Tunable Spoof Surface Plasmon Polaritons on Composite Periodic Groove Structures.

Highly sensitive detection of enhanced terahertz (THz) fingerprint absorption spectrum of trace-amount tiny molecules is essential for biosensing. THz surface plasmon resonance (SPR) sensors based on Otto prism-coupled attenuated total reflection (OPC-ATR) configuration have been recognized as a promising technology in biomedical detection applications. However, THz-SPR sensors based on the traditional OPC-ATR configuration have long been associated with low sensitivity, poor tunability, low refractive index resolution, large sample consumption, and lack of fingerprint analysis.

Multichannel Flexible Pulse Perception Array for Intelligent Disease Diagnosis System.

Pressure sensors with high sensitivity, a wide linear range, and a quick response time are critical for building an intelligent disease diagnosis system that directly detects and recognizes pulse signals for medical and health applications. However, conventional pressure sensors have limited sensitivity and nonideal response ranges. We proposed a multichannel flexible pulse perception array based on polyimide/multiwalled carbon nanotube-polydimethylsiloxane nanocomposite/polyimide (PI/MPN/PI) sandwich-structure pressure sensor that can be applied for remote disease diagnosis.

Wearable and flexible electrochemical sensors for sweat analysis: a review.

Flexible wearable sweat sensors allow continuous, real-time, noninvasive detection of sweat analytes, provide insight into human physiology at the molecular level, and have received significant attention for their promising applications in personalized health monitoring. Electrochemical sensors are the best choice for wearable sweat sensors due to their high performance, low cost, miniaturization, and wide applicability. Recent developments in soft microfluidics, multiplexed biosensing, energy harvesting devices, and materials have advanced the compatibility of wearable electrochemical sweat-sensing platforms.

An iEEG Recording and Adjustable Shunt-Current Conduction Platform for Epilepsy Treatment.

This paper proposes a compact bioelectronics sensing platform, including a multi-channel electrode, intracranial electroencephalogram (iEEG) recorder, adjustable galvanometer, and shunt-current conduction circuit pathway. The developed implantable electrode made of polyurethane-insulated stainless-steel materials is capable of recording iEEG signals and shunt-current conduction. The electrochemical impedance of the conduction, ground/reference, and working electrode were characterized in phosphate buffer saline solution, revealing in vitro results of 517.

Advance of microfluidic constriction channel system of measuring single-cell cortical tension/specific capacitance of membrane and conductivity of cytoplasm.

This paper reported a microfluidic platform which realized the characterization of inherent single-cell biomechanical and bioelectrical parameters simultaneously. Individual cells traveled through a constriction channel with deformation images and impedance variations captured and processed into cortical tension T , specific membrane capacitance C , and cytoplasmic conductivity σ based on an equivalent biophysical model. These properties of thousands of individual cells of K562, Jurkat, HL-60, HL-60 treated with paraformaldehyde (PA)/cytochalasin D (CD)/concanavalin A (ConA), granulocytes of Donor 1, Donor 2, and Donor 3 were quantified for the first time.

Projection of future drought and its impact on simulated crop yield over South Asia using ensemble machine learning approach.

Understanding the development mechanism of drought events, characterization of future drought metrics, and its impact on crop yield is crucial to ensure food security globally, and more importantly, in South Asia. Therefore, the present study assessed the changes in future projected drought metrics and evaluated the future risk of yield reduction under drought intensity. We characterized the magnitude, intensity, and duration of future drought by means of the SPEI drought index using CMIP6 (Coupled Model Inter-comparison Phase-6) climate models.

Refined UNet v3: Efficient end-to-end patch-wise network for cloud and shadow segmentation with multi-channel spectral features.

Semantic segmentation is one of the essential prerequisites for computer vision tasks, but edge-precise segmentation stays challenging due to the potential lack of a proper model indicating the low-level relation between pixels. We have presented Refined UNet v2, a concatenation of a network backbone and a subsequent embedded conditional random field (CRF) layer, which coarsely performs pixel-wise classification and refines edges of segmentation regions in a one-stage way. However, the CRF layer of v2 employs a gray-scale global observation (image) to construct contrast-sensitive bilateral features, which is not able to achieve the desired performance on ambiguous edges.

Sub-Auroral and Mid-Latitude GNSS ROTI Performance during Solar Cycle 24 Geomagnetic Disturbed Periods: Towards Storm's Early Sensing.

Geomagnetic storms-triggered by the interaction between Earth's magnetosphere and interplanetary magnetic field, driven by solar activity-are important for many Earth-bound aspects of life. Serious events may impact the electroenergetic infrastructure, but even weaker storms generate noticeable irregularities in the density of ionospheric plasma. Ionosphere electron density gradients interact with electromagnetic radiation in the radiofrequency domain, affecting sub- and trans-ionospheric transmissions.

Random forest model based fine scale spatiotemporal O trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017.

Ambient ozone (O) concentrations have shown an upward trend in China and its health hazards have also been recognized in recent years. High-resolution exposure data based on statistical models are needed. Our study aimed to build high-performance random forest (RF) models based on training data from 2013 to 2017 in the Beijing-Tianjin-Hebei (BTH) region in China at a 0.

An evaluation of COVID-19 transmission control in Wenzhou using a modified SEIR model.

In December 2019, the first confirmed case of pneumonia caused by a novel coronavirus was reported. Coronavirus disease 2019 (COVID-19) is currently spreading around the world. The relationships among the pandemic and its associated travel restrictions, social distancing measures, contact tracing, mask-wearing habits and medical consultation efficiency have not yet been extensively assessed.

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches.

Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches-Crichton's risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data.