Ultra-Broad Emission Copper Halide Scintillator-Based X-Ray Imager.

Lead-free metal-halide scintillators are gaining considerable attention as more eco-friendly and superior alternatives to their lead-based counterparts. However, novel broad-emission band scintillators like the state-of-the-art CsI: Tl scintillator, which can generate high signals due to its strong compatibility with the spectral responsivity of regular photodiode arrays, are still less investigated. Herein, a TPACuI (TPACI) copper halide scintillator with a unique ultra-broad emission (FWHM > 240 nm) is developed, which shows universal compatibility with the peak response range of commercial photodetector.

Multi-Time-Scale Optimal Scheduling Strategy for Marine Renewable Energy Based on Deep Reinforcement Learning Algorithm.

Surrounded by the Shandong Peninsula, the Bohai Sea and Yellow Sea possess vast marine energy resources. An analysis of actual meteorological data from these regions indicates significant seasonality and intra-day uncertainty in wind and photovoltaic power generation. The challenge of scheduling to leverage the complementary characteristics of various renewable energy sources for maintaining grid stability is substantial.

Capillary Manganese Halide Needle-Like Array Scintillator with Isolated Light Crosstalk for Micro-X-Ray Imaging.

The exacerbation of inherent light scattering with increasing scintillator thickness poses a major challenge for balancing the thickness-dependent spatial resolution and scintillation brightness in X-ray imaging scintillators. Herein, a thick pixelated needle-like array scintillator capable of micrometer resolution is fabricated via waveguide structure engineering. Specifically, this involves integrating a straightforward low-temperature melting process of manganese halide with an aluminum-clad capillary template.

Predictive role of impulsivity, anxiety, and depression in the efficacy of intermittent theta burst transcranial magnetic stimulation modalities for treating methamphetamine use disorder: A randomized clinical trial.

Introduction: Methamphetamine use disorder (MUD) can cause impulsive behavior, anxiety, and depression. Stimulation of the left dorsolateral prefrontal cortex in MUD patients by intermittent theta burst repetitive transcranial magnetic stimulation (iTBS-rTMS) is effective in reducing cravings, impulsive behavior, anxiety, and depression. The purpose of this study was to explore whether these psychological factors helped to predict MUD patients' responses to iTBS-rTMS treatment.

Near-Field Microwave Scattering Formulation by A Deep Learning Method.

A deep learning method is applied to modelling electromagnetic (EM) scattering for microwave breast imaging (MBI). The neural network (NN) accepts 2D dielectric breast maps at 3 GHz and produces scattered-field data on an antenna array composed of 24 transmitters and 24 receivers. The NN was trained by 18,000 synthetic digital breast phantoms generated by generative adversarial network (GAN), and the scattered-field data pre-calculated by method of moments (MOM).

p-Nrf2/HO-1 Pathway Involved in Methamphetamine-induced Executive Dysfunction through Endoplasmic Reticulum Stress and Apoptosis in the Dorsal Striatum.

Methamphetamine (METH) abuse is known to cause executive dysfunction. However, the molecular mechanism underlying METH induced executive dysfunction remains unclear. Go/NoGo experiment was performed in mice to evaluate METH-induced executive dysfunction.

Singlet Fission-Based High-Resolution X-Ray Imaging Scintillation Screens.

X-ray imaging technology is critical to numerous different walks of daily life, ranging from medical radiography and security screening all the way to high-energy physics. Although several organic chromophores are fabricated and tested as X-ray imaging scintillators, they generally show poor scintillation performance due to their weak X-ray absorption cross-section and inefficient exciton utilization efficiency. Here, a singlet fission-based high-performance organic X-ray imaging scintillator with near unity exciton utilization efficiency is presented.

Dielectric Breast Phantoms by Generative Adversarial Network.

In order to conduct the research of machine-learning (ML) based microwave breast imaging (MBI), a large number of digital dielectric breast phantoms that can be used as training data (ground truth) are required but are difficult to be achieved from practice. Although a few dielectric breast phantoms have been developed for research purpose, the number and the diversity are limited and is far inadequate to develop a robust ML algorithm for MBI. This paper presents a neural network method to generate 2D virtual breast phantoms that are similar to the real ones, which can be used to develop ML-based MBI in the future.

Heterojunctions on TaO@MWCNT for Ultrasensitive Ethanol Sensing at Room Temperature.

Heterojunctions of TaO and multiwalled carbon nanotubes (MWCNTs) have been successfully synthesized by a facile and cost-effective hydrothermal method, with a super thin and uniform TaO shell wrapped around the MWCNT. The combination of TaO and MWCNTs at the interface not only modifies the morphology but also forms the p-n heterojunction, which contributes to the reconstruction of band structure, as well as the low resistance of matrix and highly chemisorbed oxygen content. The TaO@MWCNT p-n heterojunction exhibits ultrasensitive performance to ethanol at room temperature, with a response of 3.

Highly Efficient, Flexible, and Eco-Friendly Manganese(II) Halide Nanocrystal Membrane with Low Light Scattering for High-Resolution X-ray Imaging.

Scintillators enable invisible X-ray to be converted into ultraviolet (UV)/visible light that can be collected using a sensor array and is the core component of the X-ray imaging system. However, combining the excellent properties of high light output, high spatial resolution, flexibility, non-toxicity, and cost effectiveness into a single X-ray scintillator remains a great challenge. Herein, a novel scintillator based on benzyltriphenylphosphonium manganese(II) bromide (BTPMnBr) nanocrystal (NC) membranes was developed by the in situ fabrication strategy.

The chain-mediation pathway of gender regarding academic delay of gratification in college students is regulated by anxiety/depressive mood and prospective memory.

Objective: This study investigated the relationship between gender and academic delay of gratification (ADOG) in college students and explored the mediating roles of anxiety/depressive mood and prospective memory to provide a theoretical intervention approach based on internal mechanisms.

Methods: Random cluster sampling was conducted on 609 students from three universities situated in the Province of Anhui, China with the use of data from several questionnaires: the general information questionnaire, Generalized Anxiety Disorder Scale, Patient Health Questionnaire, Prospective and Retrospective Memory (PRM) Questionnaire, and ADOG Scale.

Results: The females' anxiety and depression levels were lower than that of the males, while the female PRM and ADOG performance improved when compared to that of the males.

Effect of Coupling Medium on Penetration Depth in Microwave Medical Imaging.

In microwave medical imaging, the human skin reflects most of microwave energy due to the impedance mismatch between the air and the body. As a result, only a small portion of the microwave energy can enter the body and work for medical purpose. One solution to tackle this issue is to use a coupling (or matching) medium, which can reduce unwanted reflections on the skin and meanwhile improve spatial imaging resolution.

Associations of executive function and age of first use of methamphetamine with methamphetamine relapse.

Background And Aims: Methamphetamine (MA) is a psychostimulant associated with a high relapse rate among patients with MA use disorder (MUD). Long-term use of MA is associated with mental disorders, executive dysfunction, aggressive behaviors, and impulsivity among patients with MUD. However, identifying which factors may be more closely associated with relapse has not been investigated.

Optoelectronic Artificial Synaptic Device Based on Amorphous InAlZnO Films for Learning Simulations.

Neuromorphic computing, which mimics brain function, can address the shortcomings of the "von Neumann" system and is one of the critical components of next-generation computing. The use of light to stimulate artificial synapses has the advantages of low power consumption, low latency, and high stability. We demonstrate amorphous InAlZnO-based light-stimulated artificial synaptic devices with a thin-film transistor structure.

Generation of Digital Brain Phantom for Machine Learning Application of Dopamine Transporter Radionuclide Imaging.

While machine learning (ML) methods may significantly improve image quality for SPECT imaging for the diagnosis and monitoring of Parkinson's disease (PD), they require a large amount of data for training. It is often difficult to collect a large population of patient data to support the ML research, and the ground truth of lesion is also unknown. This paper leverages a generative adversarial network (GAN) to generate digital brain phantoms for training ML-based PD SPECT algorithms.

The Influence of Online Game Behaviors on the Emotional State and Executive Function of College Students in China.

Since the classification of gaming disorder (GD) by the World Health Organization (WHO) as "mental disorder caused by addictive behaviors," there has been controversy regarding whether online game behaviors can lead to mental disorder. This study aims to clarify the correlation between the online game behaviors of college students and anxiety, depression, and executive function of college students in China, from a questionnaire-based investigation. Based on the whole class random sampling method, a questionnaire survey was conducted among college students in Northern Anhui, China from March 7 to March 27, 2020.

Performance analysis of an all-dielectric planar Mikaelian lens antenna for 1-D beam-steering application.

This paper investigates the performance of an all-dielectric planar Mikaelian lens based on ray transfer matrices and full-wave analysis for 1-D beam-steering application. This new lens concept has its intrinsic flat shape characteristic allowing for a simple low-cost planar feed technology. To verify the design concept, a lens prototype excited by five rectangular microstrip patch antennas with perforated structure (21×24 holes) is fabricated using stereolithography (SLA) 3-D printing.

Artificial intelligence in single photon emission computed tomography (SPECT) imaging: a narrative review.

Artificial intelligence (AI) has been widely applied to medical imaging. The use of AI for emission computed tomography, particularly single-photon emission computed tomography (SPECT) emerged nearly 30 years ago but has been accelerated in recent years due to the development of AI technology. In this review, we will describe and discuss the progress of AI technology in SPECT imaging.

SPECTnet: a deep learning neural network for SPECT image reconstruction.

Background: Single photon emission computed tomography (SPECT) is an important functional tool for clinical diagnosis and scientific research of brain disorders, but suffers from limited spatial resolution and high noise due to hardware design and imaging physics. The present study is to develop a deep learning technique for SPECT image reconstruction that directly converts raw projection data to image with high resolution and low noise, while an efficient training method specifically applicable to medical image reconstruction is presented.

Methods: A custom software was developed to generate 20,000 2-D brain phantoms, of which 16,000 were used to train the neural network, 2,000 for validation, and the final 2,000 for testing.

Advances in Microwave Near-Field Imaging: Prototypes, Systems, and Applications.

Microwave imaging employs detection techniques to evaluate hidden or embedded objects in a structure or media using electro-magnetic (EM) waves in the microwave range, 300 MHz-300 GHz. Microwave imaging is often associated with radar detection such as target location and tracking, weather-pattern recognition, and underground surveillance, which are far-field applications. In recent years, due to microwaves' ability to penetrate optically opaque media, short-range applications, including medical imaging, nondestructive testing (NDT) and quality evaluation, through-the-wall imaging, and security screening, have been developed.

Perforated extensible 3-D hyperbolic secant lens antenna for directive antenna applications using additive manufacturing.

In this paper, a novel three-dimensional (3-D) generalized hyperbolic secant (H-S) lens is first introduced using perforated dielectric material. The attractiveness of this new lens is its unique intrinsic flat shape characteristic and extensibility for different configuration scenarios, which provide a potential alternative design for a planar Luneburg and half Maxwell fish-eye lens based on a complex conformal mapping method. A high gain and wideband printed antipodal fermi antenna as a feeding source is employed in the proposed lens antenna prototype.

Microwave Imaging by Deep Learning Network: Feasibility and Training Method.

Microwave image reconstruction based on a deep-learning method is investigated in this paper. The neural network is capable of converting measured microwave signals acquired from a 24×24 antenna array at 4 GHz into a 128×128 image. To reduce the training difficulty, we first developed an autoencoder by which high-resolution images (128×128) were represented with 256×1 vectors; then we developed the second neural network which aimed to map microwave signals to the compressed features (256×1 vector).

A Learned Reconstruction Network for SPECT Imaging.

A neural network designed specifically for SPECT image reconstruction was developed. The network reconstructed activity images from SPECT projection data directly. Training was performed through a corpus of training data including that derived from digital phantoms generated from custom software and the corresponding projection data obtained from simulation.

A solution-processed zero-dimensional all-inorganic perovskite scintillator for high resolution gamma-ray spectroscopy detection.

Low dimensional scintillators have been successfully and widely applied in the radiation-detection community for home security, scientific research, and imaging. We have grown zero-dimensional CsPbBr materials with CsPbBr nanocrystals embedded by using a solution-growth method at low temperature. We have demonstrated the scintillation properties of these 0D nanoscintillators with high luminescence quantum efficiency for green light.

Gradient heterostructure perovskite single crystals enable the improvement of radiative recombination for scintillator application.

Recently, organic-inorganic hybrid perovskites (OIHPs) are rising as promising candidates for light-emitting applications, due to their superior optical properties. High performance light-emitting applications such as scintillators require minimum non-radiative recombination and high fractions of radiative recombination. Here, we report a simple solution-processing strategy for the synthesis of funnel-type CHNH(MA)PbCl/CHNH(MA)PbBrCl heterostructure perovskite materials that improve the light emission performances.