Triplet Energy Gap-Regulated Room Temperature Phosphorescence in Host-guest Doped Systems.

The organic room temperature phosphorescence (RTP) materials via host-guest doped method receive considerable attention in the fields of optoelectronics, bioimaging, and information encryption. Despite many host-guest doped materials with excellent RTP properties have been developed, their luminous mechanism is still limited. Here, a series of host-guest doped materials, using Benzophenone as the host and quinone compounds as the guests, were constructed to investigate the effect of the triplet energy gap (ΔET) between the host and guest on triplet states population. The guest's triplet state is proposed to be a "triplet energy reservoir", gathering the triplet excitons to emit RTP when ΔET is large and returning triplet excitons to the host when ΔET is small. By combining the results of steady-state and delayed emission spectra, time-resolved transient absorption, and theoretical calculations, A bidirectional energy transfer process is proved, which are triplet-triplet energy transfer and reverse triplet-triplet energy transfer processes. The thermal equilibrium of these two energy transfer processes can be regulated by the ΔET and temperature. The potential applications of these RTP properties are also realized in data encryption and anti-counterfeiting. This work provides valuable insight into the design of host-guest doped materials based on energy transfer mechanisms.

Multiple Resonance Quasi-fluorescence from BN-Doped Aromatic Compounds Modified with "Naphthalene" Units Approaches the BT.2020 Green Light Standard.

Creating fluorophores that meet the Broadcast Service Television 2020 (BT.2020) standard is a significant achievement. In this paper, we present an innovative strategy that could revolutionize the development of high-performance narrowband fluorophores for ultra-high-definition displays. Our approach combines classic multi-resonance BN-doped fragments with naphthalene, creating two novel narrowband bright green quasi-fluorescent emitters, NT-2B and NT-3B. When tested in dilute toluene, these molecules exhibit emission peaks at 510 and 511 nm with extremely narrow FWHM values of 15 and 14 nm, respectively. Both molecules also demonstrate conventional fluorescence properties with high photoluminescence quantum yields (PLQYs) of up to 85%. Notably, OLEDs containing NT-2B achieve a peak EQE of approximately 30% and at a doping concentration of 5 wt.%, OLEDs based on NT-2B achieve a CIEy value of roughly 0.75, closely matching the BT.2020 standard.

Occupational Exposure to Silica Dust and Silicosis Risk in Chinese Noncoal Mines: Qualitative and Quantitative Risk Assessment.

BACKGROUND: Despite increasing awareness, silica dust-induced silicosis still contributes to the huge disease burden in China. Worryingly, recent silica dust exposure levels and silicosis risk in Chinese noncoal mines remain unclear. OBJECTIVE: We aimed to determine recent silica dust exposure levels and assess the risk of silicosis in Chinese noncoal mines. METHODS: Between May and December 2020, we conducted a retrospective cohort study on 3 noncoal mines and 1 public hospital to establish, using multivariable Cox regression analyses, prediction formulas of the silicosis cumulative hazard ratio (H) and incidence (I) and a cross-sectional study on 155 noncoal mines in 10 Chinese provinces to determine the prevalence of silica dust exposure (PDE), free silica content, and total dust and respirable dust concentrations. The qualitative risk of silicosis was assessed using the International Mining and Metals Commission's risk-rating table and the occupational hazard risk index; the quantitative risk was assessed using prediction formulas. RESULTS: Kaplan-Meier survival analysis revealed significant differences in the silicosis probability between silica dust-exposed male and female miners (log-rank test χ21=7.52, P=.01). A total of 126 noncoal mines, with 29,835 miners and 4623 dust samples, were included; 13,037 (43.7%) miners were exposed to silica dust, of which 12,952 (99.3%) were male. The median PDE, free silica content, total dust concentration, and respirable dust concentration were 61.6%, 27.6%, 1.30 mg/m3, and 0.58 mg/m3, respectively, indicating that miners in nonmetal, nonferrous metal, small, and open-pit mines suffer high-level exposure to silica dust. Comprehensive qualitative risk assessment showed noncoal miners had a medium risk of silicosis, and the risks caused by total silica dust and respirable silica dust exposure were high and medium, respectively. When predicting H and I over the next 10, 20, and 30 years, we assumed that the miner gender was male. Under exposure to current total silica dust concentrations, median I10, I20, and I30 would be 6.8%, 25.1%, and 49.9%, respectively. Under exposure to current respirable silica dust concentrations, median I10, I20, and I30 would be 6.8%, 27.7%, and 57.4%, respectively. These findings showed that miners in nonmetal, nonferrous metal, small, and open-pit mines have a higher I and higher qualitative silicosis risk. CONCLUSIONS: Chinese noncoal miners, especially those in nonmetal, nonferrous metal, small, and open-pit mines, still suffer high-level exposure to silica dust and a medium-level risk of silicosis. Data of both total silica dust and respirable silica dust are vital for occupational health risk assessment in order to devise effective control measures to reduce noncoal mine silica dust levels, improve miners' working environment, and reduce the risk of silicosis.

A multicenter retrospective study of antidepressant use in outpatient clinics in China pre- and post-COVID.

BACKGROUND: Analyzing antidepressant prescribing in real-world settings can provide clinicians and health policymakers valuable information. AIM: This epidemiological study examined the status and trends in antidepressant prescribing among the Chinese population from July 1, 2017, to June 30, 2022. METHOD: A retrospective study was conducted in three hospitals. Data were collected 2.5 years before and 2.5 years after the onset of the COVID-19 pandemic. We analyzed the number of patients diagnosed with depression and their corresponding antidepressant prescriptions. Using the chi-square test, stratified analyses were performed to explore the characteristics of these prescriptions in different ages and sexes. RESULTS: The study included 124,355 patients and 400,840 antidepressant prescriptions. We observed fluctuating upward trends in the number of patients and antidepressant prescriptions. Post-COVID-19, the number of patients increased by 37.1% compared to the pre-pandemic period, and the number of antidepressant prescriptions rose by 88.3%. The three most frequently prescribed antidepressants for adolescents were sertraline, citalopram, and escitalopram. Among adults, citalopram, escitalopram, and sertraline were most common, while in older adults, citalopram, escitalopram, and mirtazapine were predominant. Male patients used mirtazapine, venlafaxine, paroxetine, bupropion, fluvoxamine, vortioxetine, and clomipramine more frequently compared to female patients, who were more likely to be prescribed citalopram, flupentixol/melitracen, agomelatine, and fluoxetine. Antidepressant monotherapy represented 76.6% of prescriptions, with the most common combination being antidepressants and anxiolytics. CONCLUSION: Over the past 5 years, both the number of patients and antidepressant prescriptions have shown upward trends, and the COVID-19 pandemic has impacted prescribing. Understanding the changes in antidepressant prescriptions can identify adherence to national guidelines.

Multiple Enol-Keto Isomerization and Excited-State Unidirectional Intramolecular Proton Transfer Generate Intense, Narrowband Red OLEDs.

A novel series of excited-state intramolecular proton transfer (ESIPT) emitters, namely, DPNA, DPNA-F, and DPNA-tBu, endowed with dual intramolecular hydrogen bonds, were designed and synthesized. In the condensed phase, DPNAs exhibit unmatched absorption and emission spectral features, where the minor 0-0 absorption peak becomes a major one in the emission. Detailed spectroscopic and dynamic approaches conclude fast ground-state equilibrium among enol-enol (EE), enol-keto (EK), and keto-keto (KK) isomers. The equilibrium ratio can be fine-tuned by varying the substitutions in DPNAs. Independent of isomers and excitation wavelength, ultrafast ESIPT takes place for all DPNAs, giving solely KK tautomer emission maximized at >650 nm. The spectral temporal evolution of ESIPT was resolved by a state-of-the-art technique, namely, the transient grating photoluminescence (TGPL), where the rate of EK* → KK* is measured to be (157 fs)-1 for DPNA-tBu, while a stepwise process is resolved for EE* → EK* → KK*, with a rate of EE* → EK* of (72 fs)-1. For all DPNAs, the KK tautomer emission shows a narrowband emission with high photoluminescence quantum yields (PLQY, ∼62% for DPNA in toluene) in the red, offering advantages to fabricate deep-red organic light-emitting diodes (OLED). The resulting OLEDs give high external quantum efficiency with a spectral full width at half-maximum (FWHM) as narrow as ∼40 nm centered at 666-670 nm for DPNAs, fully satisfying the BT. 2020 standard. The unique ESIPT properties and highly intense tautomer emission with a small fwhm thus establish a benchmark for reaching red narrowband organic electroluminescence.

Ultra-low-field magnetization transfer imaging at 0.055T with low specific absorption rate.

PURPOSE: To demonstrate magnetization transfer (MT) effects with low specific absorption rate (SAR) on ultra-low-field (ULF) MRI. METHODS: MT imaging was implemented by using sinc-modulated RF pulse train (SPT) modules to provide bilateral off-resonance irradiation. They were incorporated into 3D gradient echo (GRE) and fast spin echo (FSE) protocols on a shielding-free 0.055T head scanner. MT effects were first verified using phantoms. Brain MT imaging was conducted in both healthy subjects and patients. RESULTS: MT effects were clearly observed in phantoms using six SPT modules with total flip angle 3600° at central primary saturation bands of approximate offset ±786 Hz, even in the presence of large relative B0 inhomogeneity. For brain, strong MT effects were observed in gray matter, white matter, and muscle in 3D GRE and FSE imaging using six and sixteen SPT modules with total flip angle 3600° and 9600°, respectively. Fat, cerebrospinal fluid, and blood exhibited relatively weak MT effects. MT preparation enhanced tissue contrasts in T2-weighted and FLAIR-like images, and improved brain lesion delineation. The estimated MT SAR was 0.0024 and 0.0008 W/kg for two protocols, respectively, which is far below the US Food and Drug Administration (FDA) limit of 3.0 W/kg. CONCLUSION: Robust MT effects can be readily obtained at ULF with extremely low SAR, despite poor relative B0 homogeneity in ppm. This unique advantage enables flexible MT pulse design and implementation on low-cost ULF MRI platforms to achieve strong MT effects in brain and beyond, potentially augmenting their clinical utility in the future.

Regional Functionalization Molecular Design Strategy: A Key to Enhancing the Efficiency of Multi-Resonance OLEDs.

Herein, we propose a regional functionalization molecular design strategy that enables independent control of distinct pivotal parameters through different molecule segments. Three novel multiple resonances thermally activated delayed fluorescence (MR-TADF) emitters A-BN, DA-BN, and A-DBN, have been successfully synthesized by integrating highly rigid and three-dimensional adamantane-containing spirofluorene units into the MR framework. These molecules form two distinctive functional parts: part 1 comprises a boron-nitrogen (BN)-MR framework with adjacent benzene and fluorene units forming a central luminescent core characterized by an exceptionally rigid planar geometry, allowing for narrow FWHM values; part 2 includes peripheral mesitylene, benzene, and adamantyl groups, creating a unique three-dimensional "umbrella-like" conformation to mitigate intermolecular interactions and suppress exciton annihilation. The resulting A-BN, DA-BN, and A-DBN exhibit remarkably narrow FWHM values ranging from 18 to 14 nm and near-unity photoluminescence quantum yields. Particularly, OLEDs based on DA-BN and A-DBN demonstrate outstanding efficiencies of 35.0 % and 34.3 %, with FWHM values as low as 22 nm and 25 nm, respectively, effectively accomplishing the integration of high color purity and high device performance.

Ultra-low-field magnetic resonance angiography at 0.05 T: A preliminary study.

We aim to explore the feasibility of head and neck time-of-flight (TOF) magnetic resonance angiography (MRA) at ultra-low-field (ULF). TOF MRA was conducted on a highly simplified 0.05 T MRI scanner with no radiofrequency (RF) and magnetic shielding. A flow-compensated three-dimensional (3D) gradient echo (GRE) sequence with a tilt-optimized nonsaturated excitation RF pulse, and a flow-compensated multislice two-dimensional (2D) GRE sequence, were implemented for cerebral artery and vein imaging, respectively. For carotid artery and jugular vein imaging, flow-compensated 2D GRE sequences were utilized with venous and arterial blood presaturation, respectively. MRA was performed on young healthy subjects. Vessel-to-background contrast was experimentally observed with strong blood inflow effect and background tissue suppression. The large primary cerebral arteries and veins, carotid arteries, jugular veins, and artery bifurcations could be identified in both raw GRE images and maximum intensity projections. The primary brain and neck arteries were found to be reproducible among multiple examination sessions. These preliminary experimental results demonstrated the possibility of artery TOF MRA on low-cost 0.05 T scanners for the first time, despite the extremely low MR signal. We expect to improve the quality of ULF TOF MRA in the near future through sequence development and optimization, ongoing advances in ULF hardware and image formation, and the use of vascular T1 contrast agents.

Highly Horizontal Oriented Tricomponent Exciplex Host with Multiple Reverse Intersystem Crossing Channels for High-Performance Narrowband Electroluminescence and Eye-Protection White Organic Light-Emitting Diodes.

Despite multiple-resonance thermally activated delayed fluorescence (MR-TADF) emitters with small full-width at half maximum are attractive for wide color-gamut display and eye-protection lighting applications, their inefficient reverse intersystem crossing (RISC) process and long exciton lifetime induce serious efficiency roll-off, which significantly limits their development. Herein, a novel device concept of building highly efficient tricomponent exciplex with multiple RISC channels is proposed to realize reduced exciton quenching and enhanced upconversion of nonradiative triplet excitons, and subsequently used as a host for high-performance MR-TADF organic light-emitting diodes (OLEDs). Compared with traditional binary exciplex, the tricomponent exciplex exhibits obviously improved photoluminescence quantum yield, emitting dipole orientation and RISC rate constant, and a record-breaking external quantum efficiency (EQE) of 30.4% is achieved for tricomponent exciplex p-PhBCzPh: PO-T2T: DspiroAc-TRZ (50: 20: 30) based OLED. Remarkably, maximum EQEs of 36.2% and 40.3% and ultralow efficiency roll-off with EQEs of 26.1% and 30.0% at 1000 cd m-2 are respectively achieved for its sky-blue and pure-green MR-TADF doped OLEDs. Additionally, the blue emission unit hosted by tricomponent exciplex is combined with an orange-red TADF emission unit to achieve a double-emission-layer blue-hazard-free warm white OLED with an EQEmax of 30.3% and stable electroluminescence spectra over a wide brightness range.

Operational Deflection Shape Measurements on Bladed Disks with Continuous Scanning Laser Doppler Vibrometry.

The continuous scanning laser Doppler vibrometry (CSLDV) technique is usually used to evaluate the vibration operational deflection shapes (ODSs) of structures with continuous surfaces. In this paper, an extended CSLDV is demonstrated to measure the non-continuous surface of the bladed disk and to obtain the ODS efficiently. For a bladed disk, the blades are uniformly distributed on a given disk. Although the ODS of each blade can be derived from its response data along the scanning path with CSLDV, the relative vibration direction between different blades cannot be determined from those data. Therefore, it is difficult to reconstruct the complete vibration mode of the whole blade disk. In order to measure the complete ODS of the bladed disk, a method based on ODS frequency response functions (ODS FRFs) has been proposed. While the ODS of each blade is measured by designing the suitable scanning paths in CSLDV, an additional response signal is obtained at a fixed point as the reference signal to identify the relative vibration phase between the blade and the blade of the bladed disk. Finally, a measurement is performed with a simple bladed disk and the results demonstrate the feasibility and effectiveness of the proposed extended CSLDV method.

Modulation of Intermolecular Interactions in Organic Emitters for Highly Efficient Organic Light-Emitting Diodes.

The adverse aggregated-caused quenching (ACQ) problem of most electroluminescent materials existing in highly doped thin films is one of the key factors impeding the commercialization of high-efficiency organic light-emitting diodes (OLEDs) panel. Whereas, by delicately constructing and modulating moderate intermolecular interactions, some aggregates have been demonstrated to present distinct luminescent properties such as tunable emission spectra, improved photoluminescence quantum yields, different emission mechanism and enhanced horizontal transition dipole ratio (Θ) of emitting layer, providing feasible solution for ACQ problem. The luminescence from newly generated emissive state in aggregates is different from the traditional "isolated" molecules in organic electronics and will possess novel properties and applications. Herein, we summarize the different types of intermolecular interactions within emitter aggregates exhibiting distinct luminescent mechanisms, as well as their effects on photoluminescent and electroluminescent properties, offering reliable reference for the advancement of highly efficient OLEDs utilizing aggregated emitters.

Whole-body magnetic resonance imaging at 0.05 Tesla.

Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using a permanent 0.05 Tesla magnet and deep learning for electromagnetic interference elimination, we developed a whole-body scanner that operates using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging various anatomical structures. Furthermore, we developed three-dimensional deep learning reconstruction to boost image quality by harnessing extensive high-field MRI data. These advances pave the way for affordable deep learning-powered ultra-low-field MRI scanners, addressing unmet clinical needs in diverse health care settings worldwide.

Machine Learning Reveals Serum Glycopatterns as Potential Biomarkers for the Diagnosis of Nonalcoholic Fatty Liver Disease (NAFLD).

Nonalcoholic fatty liver disease (NAFLD) has emerged as the predominant chronic liver condition globally, and underdiagnosis is common, particularly in mild cases, attributed to the asymptomatic nature and traditional ultrasonography's limited sensitivity to detect early-stage steatosis. Consequently, patients may experience progressive liver pathology. The objective of this research is to ascertain the efficacy of serum glycan glycopatterns as a potential diagnostic biomarker, with a particular focus on the disease's early stages. We collected a total of 170 serum samples from volunteers with mild-NAFLD (Mild), severe-NAFLD (Severe), and non-NAFLD (None). Examination via lectin microarrays has uncovered pronounced disparities in serum glycopatterns identified by 19 distinct lectins. Following this, we employed four distinct machine learning algorithms to categorize the None, Mild, and Severe groups, drawing on the alterations observed in serum glycopatterns. The gradient boosting decision tree (GBDT) algorithm outperformed other models in diagnostic accuracy within the validation set, achieving an accuracy rate of 95% in differentiating the None group from the Mild group. Our research indicates that employing lectin microarrays to identify alterations in serum glycopatterns, when integrated with advanced machine learning algorithms, could constitute a promising approach for the diagnosis of NAFLD, with a special emphasis on its early detection.

Nitrogen-mediated volatilisation of defensive metabolites in tomato confers resistance to herbivores.

Plants synthesise a vast array of volatile organic compounds (VOCs), which serve as chemical defence and communication agents in their interactions with insect herbivores. Although nitrogen (N) is a critical resource in the production of plant metabolites, its regulatory effects on defensive VOCs remain largely unknown. Here, we investigated the effect of N content in tomato (Solanum lycopersicum) on the tobacco cutworm (Spodoptera litura), a notorious agricultural pest, using biochemical and molecular experiments in combination with insect behavioural and performance analyses. We observed that on tomato leaves with different N contents, S. litura showed distinct feeding preference and growth and developmental performance. Particularly, metabolomics profiling revealed that limited N availability conferred resistance upon tomato plants to S. litura is likely associated with the biosynthesis and emission of the volatile metabolite α-humulene as a repellent. Moreover, exogenous application of α-humulene on tomato leaves elicited a significant repellent response against herbivores. Thus, our findings unravel the key factors involved in N-mediated plant defence against insect herbivores and pave the way for innovation of N management to improve the plant defence responses to facilitate pest control strategies within agroecosystems.

Synergetic Modulation of Steric Hindrance and Excited State for Anti-Quenching and Fast Spin-Flip Multi-Resonance Thermally Activated Delayed Fluorophore.

Multi-resonance thermally activated delayed fluorescence (MR-TADF) materials hold great promise for advanced high-resolution organic light-emitting diode (OLED) displays. However, persistent challenges, such as severe aggregation-caused quenching (ACQ) and slow spin-flip, hinder their optimal performance. We propose a synergetic steric-hindrance and excited-state modulation strategy for MR-TADF emitters, which is demonstrated by two blue MR-TADF emitters, IDAD-BNCz and TIDAD-BNCz, bearing sterically demanding 8,8-diphenyl-8H-indolo[3,2,1-de]acridine (IDAD) and 3,6-di-tert-butyl-8,8-diphenyl-8H-indolo[3,2,1-de]acridine (TIDAD), respectively. These rigid and bulky IDAD/TIDAD moieties, with appropriate electron-donating capabilities, not only effectively mitigate ACQ, ensuring efficient luminescence across a broad range of dopant concentrations, but also induce high-lying charge-transfer excited states that facilitate triplet-to-singlet spin-flip without causing undesired emission redshift or spectral broadening. Consequently, implementation of a high doping level of IDAD-BNCz resulted in highly efficient narrowband electroluminescence, featuring a remarkable full-width at half-maximum of 34 nm and record-setting external quantum efficiencies of 34.3 % and 31.8 % at maximum and 100 cd m-2, respectively. The combined steric and electronic effects arising from the steric-hindered donor introduction offer a compelling molecular design strategy to overcome critical challenges in MR-TADF emitters.

Air-Stable Self-Driven UV Photodetectors on Controllable Lead-Free CsCu2I3 Microwire Arrays.

The rapid evolution of the Internet of Things has engendered increased requirements for low-cost, self-powered UV photodetectors. Herein, high-performance self-driven UV photodetectors are fabricated by designing asymmetric metal-semiconductor-metal structures on the high-quality large-area CsCu2I3 microwire arrays. The asymmetrical depletion region doubles the photocurrent and response speed compared to the symmetric structure device, leading to a high responsivity of 233 mA/W to 355 nm radiation. Notably, at 0 V bias, the asymmetric device produces an open-circuit voltage of 356 mV and drives to a short-circuit current of 372 pA; meanwhile, the switch ratio (Iph/Idark) reaches up to 103, indicating its excellent potential for detecting weak light. Furthermore, the device maintains stable responses throughout 10000 UV-light switch cycles, with negligible degradation even after 90-day storage in air. Our work establishes that CsCu2I3 is a good candidate for self-powered UV detection and thoroughly demonstrates its potential as a passive device.

Sativene Sesquiterpenoids from the Plant Endophytic Fungus Bipolaris victoriae S27 and Their Potential as Plant-Growth Regulators.

Thirteen new sativene sesquiterpenoids (1 and 3-14), one new natural product (2), and 16 known compounds (15-30) were isolated from the endophytic fungus Bipolaris victoriae S27. Their structures were elucidated by extensive spectroscopic analysis, NMR and ECD calculations, and X-ray crystal diffractions. Compound 1 represented the first example of sativene sesquiterpenoids with a 6/5/3/5-caged tetracyclic ring system. All obtained compounds were evaluated for their plant-growth regulatory activity. The results showed that 1, 3, 4, 6, 8, 11, 12, 17, 19, 26, and 27 could suppress the growth of Arabidopsis thaliana, while 2, 5, 13, 15, 18, and 25 showed promoting effects. Among them, compound 3 showed the most potent plant-growth inhibitory activity, which is obviously superior to that of the marked herbicide glyphosate.

Investigation of critical factors influencing the underestimation of hearing loss predicted by the ISO 1999 predicting model.

OBJECTIVE: To analyze factors influencing the underestimation of noise-induced permanent threshold shift (NIPTS) among manufacturing workers, providing baseline data for revising noise exposure standard. DESIGN: A cross-sectional study was designed with 2702 noise-exposed workers from 35 enterprises from 10 industries. Personal noise exposure level(LAeq,8h) and noise kurtosis level were determined by a noise dosimeter. Questionnaires and hearing loss tests were performed for each subject. The predicted NIPTS was calculated using the ISO 1999:2013 model for each participant, and the actual measured NIPTS was corrected for age and sex. The factors influencing the underestimation of NIPTS were investigated. RESULTS: The predicted NIPTS at each test frequency (0.5, 1, 2, 3, 4, or 6kHz) and mean NIPTS at 2, 3, 4, and 6kHz (NIPTS2346) using the ISO 1999:2013 model were significantly lower than their corresponding measured NIPTS, respectively (P < 0.001). The ISO model significantly underestimated the NIPTS2346 by 12.36 dB HL. The multiple linear regression analysis showed that noise exposure level, exposure duration, age, and kurtosis could affect the degree of underestimation of NIPTS2346. The generalized additive model (GAM) with (penalized) spline components showed nonlinear relationships between critical factors (age, exposure duration, noise level, and kurtosis) and the underestimated NIPTS2346.The underestimated NIPTS2346 decreased with an increase in exposure duration (especially over ten years). There was no apparent trend in the underestimated NIPTS2346 with age. The underestimated NIPTS2346 decreased with the increased noise level [especially > 90 dB(A)]. The underestimated NIPTS2346 increased with an increase in noise kurtosis after adjusting for the noise exposure level and exposure duration and ultimately exhibiting a linear regression relationship. CONCLUSIONS: The ISO 1999 predicting model significantly underestimated the noise-induced hearing loss among manufacturing workers. The degree of underestimation became more significant at the noise exposure condition of fewer than ten years, less than 90 dB(A), and higher kurtosis levels. It is necessary to apply kurtosis to adjust the underestimation of hearing loss and consider the applying condition of noise energy metrics when using the ISO predicting model.

In Situ Transmission Electron Microscopy Investigation on Oriented Attachment of Nanodiamonds.

Oriented attachment (OA) plays an important role in the assembly of nanoparticles and the regulation of their size and morphology, which is expected to be an effective means to modulate the properties of nanodiamonds (NDs). However, there remains a dearth of comprehensive investigation into the OA mechanism of NDs. Using in situ transmission electron microscopy, we conducted atomic-resolution investigation on the OA events of ND pairs under electron beam irradiation. The occurrence of an OA event is contingent upon the alignment between two ND surfaces, and the coalesced particles undergo recrystallization to form spherical shapes. Both experimental observations and molecular dynamics (MD) simulations reveal that ND pairs exhibit a preference for coalescing along the {111} surfaces. Additionally, MD simulations indicate that kinetic factors, such as contact surface area and contact angle, also influence the coalescence process.

An ECG Signal Acquisition and Analysis System Based on Machine Learning with Model Fusion.

Recently, cardiovascular disease has become the leading cause of death worldwide. Abnormal heart rate signals are an important indicator of cardiovascular disease. At present, the ECG signal acquisition instruments on the market are not portable and manual analysis is applied in data processing, which cannot address the above problems. To solve these problems, this study proposes an ECG acquisition and analysis system based on machine learning. The ECG analysis system responsible for ECG signal classification includes two parts: data preprocessing and machine learning models. Multiple types of models were built for overall classification, and model fusion was conducted. Firstly, traditional models such as logistic regression, support vector machines, and XGBoost were employed, along with feature engineering that primarily included morphological features and wavelet coefficient features. Subsequently, deep learning models, including convolutional neural networks and long short-term memory networks, were introduced and utilized for model fusion classification. The system's classification accuracy for ECG signals reached 99.13%. Future work will focus on optimizing the model and developing a more portable instrument that can be utilized in the field.