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In order to efficiently utilize straw biomass resources, the mixed microbes were used to pretreat corn straw and anaerobic fermentation was carried out. The effects of the straw particle size, the solid-liquid ratio, and the initial pH value on both the pretreatment process and the anaerobic digestion were investigated. On the basis of single factor experiments, the pretreatment conditions were optimized using the response surface method. The pretreatment was conducted at a temperature of 30 °C for a duration of 15 days. The results indicated that the optimal parameters in pretreatment process were as follows: a straw particle size of 20 mesh, a solid-liquid ratio of 1:17, and an initial pH value of 6.5. The predicted cumulative methane production under these conditions was 3740 mL, while the experimental result obtained was (3805 ± 67) mL. With a relative deviation of 1.68% between the predicted and experimental values, the model optimized the pretreatment conditions and improved the prediction of cumulative methane production. The methane yield of corn straw achieved 243 mL/(g-VSadded).

Background The choroid plexus (CP) is involved in neurodegenerative diseases. However, the association of CP with cardiovascular risk factors and cerebral small vessel disease in older adults remains unclear. Methods and Results This population‐based study included 1263 participants (60 years and older) from the MIND‐China (Multimodal Interventions to Delay Dementia and Disability in Rural China) substudy (2018–2020), of which 111 individuals completed diffusion tensor imaging examination. CP volume was automatically segmented. White matter hyperintensities (WMHs), enlarged perivascular spaces (EPVS), cerebral microbleeds, and lacunes were assessed following the Standards for Reporting Vascular Changes on Neuroimaging 1. Peak width of skeletonized mean diffusivity and free water were derived from diffusion tensor imaging images. We used linear regression models to evaluate the association between CP volume and cardiovascular risk factors, WMH volumes, and diffusion tensor imaging metrics, and logistic regression models to examine the association between CP volume and EPVS, cerebral microbleeds, and lacunes. The CP volume increased with age (P

Background: Individuals with autism spectrum disorder (ASD) have inhibitory control deficits. The combination of transcranial direct current stimulation (tDCS) and inhibitory control training produces good transfer effects and improves neuroplasticity. However, no studies have explored whether applying tDCS over the dlPFC improves inhibitory control and produces transfer effects in children with ASD. Objective: To explore whether multisession tDCS could enhance inhibitory control training (response inhibition), near-transfer (interference control) and far-transfer effects (sustained attention; stability of attention) in children with ASD and the generalizability of training effects in daily life and the class, as reflected by behavioral performance and neural activity measured by functional near-infrared spectroscopy (fNIRS). Methods: Twenty-eight autistic children were randomly assigned to either the true or sham tDCS group. The experimental group received bifrontal tDCS stimulation at 1.5 mA, administered for 15 min daily across eight consecutive days. tDCS was delivered during a computerized Go/No-go training task. Behavioral performance in terms of inhibitory control (Dog/Monkey and Day/Night Stroop tasks), sustained attention (Continuous Performance and Cancellation tests), prefrontal cortex (PFC) neural activity and inhibitory control and sustained attention in the class and at home were evaluated. Results: Training (response inhibition) and transfer effects (interference control; sustained attention) were significantly greater after receiving tDCS during the Go/No-go training task than after receiving sham tDCS. Changes in oxyhemoglobin (HbO) concentrations in the dlPFC and FPA associated with consistent conditions in the Day/Night Stroop and Continuous Performance test were observed after applying tDCS during the inhibitory control training task. Notably, transfer effects can be generalized to classroom environments. Conclusion: Inhibitory control training combined with tDCS may be a promising, safe, and effective method for improving inhibitory control and sustained attention in children with ASD.

ABSTRACTAccurately mapping large-scale areas of aquaculture ponds along China’s coastal areas is challenging. This study proposes a multi-featured decision tree method that incorporates multi-spectral indices, water inundation frequency (WIF), and object-oriented rules to extract aquaculture ponds in coastal zones using 65332 Sentinel-2 images on the GEE platform. The proposed method was validated, with the average overall accuracy of the extraction results from 2017 to 2021 reaching 90.80%, and an average F1 Score of 0.91. The results of this study indicate that the overall area of aquaculture ponds in China's coast in 2021 was 7633.83 km2, mainly located in coastal bay estuaries in Shandong Province, Jiangsu Province and Guangdong Province. In recent years, the area of coastal ponds for aquaculture in China has shown a decreasing trend, with an average annual decrease of 235.65 km2. The analysis combined with land use data shows that the ponds that have been reduced in the past five years have mainly been converted to abandoned aquaculture ponds, wetlands, and other land use types.

Abstract Introduction We sought to characterize cognitive profiles associated with enlarged perivascular spaces (EPVS) among Chinese older adults. Methods This population‐based study included 1191 dementia‐free participants (age ≥60 years) in the MIND‐China MRI Substudy (2018–2020). We visually evaluated EPVS in basal ganglia (BG) and centrum semiovale (CSO), white matter hyperintensities (WMHs), lacunes, cerebral microbleeds (CMBs), and cortical superficial siderosis. We used a neuropsychological test battery to assess cognitive function. Data were analyzed using general linear models. Results Greater BG‐EPVS load was associated with lower z‐scores in memory, verbal fluency, and global cognition (p 0.05); among apolipoprotein E (APOE) ‐ε4 carriers, greater CSO‐EPVS load was associated with lower verbal fluency z‐score, even when controlling for other CSVD markers (p

ObjectivesCerebral small vessel disease (CSVD) visible on MRI can be asymptomatic. We sought to develop and validate a model for detecting CSVD in rural older adults.MethodsThis study included 1,192 participants in the MRI sub-study within the Multidomain Interventions to Delay Dementia and Disability in Rural China. Total sample was randomly divided into training set and validation set. MRI markers of CSVD were assessed following the international criteria, and total CSVD burden was assessed on a scale from 0 to 4. Logistic regression analyses were used to screen risk factors and develop the diagnostic model. A nomogram was used to visualize the model. Model performance was assessed using the area under the receiver-operating characteristic curve (AUC), calibration plot, and decision curve analysis.ResultsThe model included age, high blood pressure, white blood cell count, neutrophil-to-lymphocyte ratio (NLR), and history of cerebral infarction. The AUC was 0.71 (95% CI, 0.67–0.76) in the training set and 0.69 (95% CI, 0.63–0.76) in the validation set. The model showed high coherence between predicted and observed probabilities in both the training and validation sets. The model had higher net benefits than the strategy assuming all participants either at high risk or low risk of CSVD for probability thresholds ranging 50–90% in the training set, and 65–98% in the validation set.ConclusionA model that integrates routine clinical factors could detect CSVD in older adults, with good discrimination and calibration. The model has implication for clinical decision-making.

Abstract Visible light‐based human–machine interactive media is capable of transmitting electrical readouts to machines and providing intuitive feedback to users simultaneously. Currently, many inorganic mechanoluminescent (ML) materials‐based interactive media, typically ZnS‐loaded phosphors (ZLPs), have been successfully demonstrated. However, organic ML materials‐based solutions were rarely exploited despite their huge merits of strong structural modification, abundant luminescence property, low cost, easy preparation, and so on. Here, we propose a novel interactive tactile display (ITD) based on organic ML materials (Cz‐A6‐dye) and triboelectric nanogenerator, with ultra‐brightness (130% enhancement) and ultra‐low threshold pressure (57% reduction) as compared to ZLPs. The proposed ITD achieves the conversion of weak mechanical stimuli into visible light and electrical signals simultaneously, without extra power supplies. Furthermore, the relationship between the luminous performance of organic ML materials and mechanical force is quantified, benefiting from the uniform ML layer prepared. Enabled by convolutional neural networks, the high‐accuracy recognition (97.1%) for handwriting and identity of users is realized at the same time. Thus, the ITD has great potential for intelligent wearable electronics and classified military applications.

Recent advancements in the field of endothelial markers of lymphatic vessels and lymphangiogenic factors have shed light on the association between several ocular diseases and ocular nascent lymphatic vessels. The immune privilege of corneal tissue typically limits the formation of lymphatic vessels in a healthy eye. However, vessels in the eyes can potentially undergo lymphangiogenesis and be conditionally activated. It is evident that nascent lymphatic vessels in the eyes contribute to various ocular pathologies. Conversely, lymphatic vessels are present in the corneal limbus, ciliary body, lacrimal glands, optic nerve sheaths, and extraocular muscles, while a lymphatic vasculature-like system exists in the choroid, that can potentially cause several ocular pathologies. Moreover, numerous studies indicate that many ocular diseases can influence or activate nascent lymphatic vessels, ultimately affecting patient prognosis. By understanding the mechanisms underlying the onset, development, and regression of ocular nascent lymphatic vessels, as well as exploring related research on ocular diseases, this article aims to offer novel perspectives for the treatment of such conditions.

To explore the synergisic effect of DH (Dendrobium huoshanense) and KBT (Keemun black tea) on preventing immunity reduction. The solid-liquid ratio, extraction time and extraction times of DH and KBT were studied by single factor test and orthogonal test with the extraction rate of Dendrobium polysaccharide and black tea polyphenols as indexes, the extraction techniques of DH and Keemun black tea were optimized respectively. The optimal ratio of KBT and DH was determined by toxicity test and phagocytosis test on RAW264.7 cells. The results showed that the optimum extraction conditions of DH polysaccharide were as follows: The ratio of material to liquid was 1:80 (g/mL), the extraction time was 80 min, and the extraction times were 4 times. The optimum extraction conditions of KBT polyphenols were as follows: The ratio of material to liquid was 1:80 (g/mL), the extraction time was 25 min, and the extraction times were 5 times. The ratio of KBT to DH was determined by observing the effect of different proportions of the mixture on macrophages. The results of the in vitro experiment showed that the extract mixture of 75% KBT and 25% DH had the best immune-enhancing effect. The results of the in vivo test showed that the high-dose group of KTDH could significantly reduce the changes of levels of cytokines IL-2 and IL-6 due to immunosuppression in mice (P

With the popularization of electric vehicles (EVs), the charging behavior of users will inevitably affect the power grid in the process of vehicle-to-grid (V2G). It is particularly important to consider the behavior characteristics and charging habits of EV users to guide their charging behavior. This paper presents a hybrid demand response (HDR) strategy based on price-sensitive demand response (PSDR), as well as incentive-based demand response (IBDR) strategy. PSDR strategy based on time-of-use (TOU) price is to guide EV users charging behavior by implementing dynamic TOU price. IBDR strategy is to put forward a charging point accumulation mechanism based on incentive subsidies and set charging reward and punishment points for different types of users according to the type of users. Then converting the TOU price into the form of points and setting a limited value for incentive points in combination with peak and valley periods to obtain the HDR strategy. Considering the uncertainty of users’ response, the model of users’ participation response is established. The multi-objective optimization model of reward and punishment coefficient and unit integral value is established by comprehensively considering various benefits. Finally, simulation results show that this strategy can effectively improve the adhesion of EV users and reduce the impact of their charging on the power grid.

With the breakthrough of key technologies of renewable energy, microgrid is gradually developing towards 100% renewable energy. However, aiming at the characteristics of renewable energy power such as randomness and intermittency, the microgrid needs to cope with the “double” fluctuations from the power source side and the load side, which will pay more costs for absorbing renewable energy. To implement “source-grid-load-storage” integration, this research establishes a hierarchical scheduling model for microgrid, which considers the demand response (DR) characteristics of electric vehicle (EV) users and is 100% powered by renewable energy. The model includes two layers, EV layer and renewable energy microgrid (REMG) layer. The first layer is EV layer. This layer formulates an appropriate charging price according to the user’s price response characteristics, and initially regulates the fluctuation of the original load while taking into account the customer satisfaction. The second layer is REMG layer. Based on the preliminarily optimized load, this layer adjusts the renewable energy rejection, the interactive power of main grid, and the output of pumped storage and battery storage under grid connection mode and island mode. The REMG layer can reduce system operating costs, while suppressing interactive power fluctuations and increasing the utilization rate of renewable energy. Simulation shows that the proposed optimal scheduling model can achieve win-win between EV and users.

Abstract Background Evidence has linked self-reported sedentary behavior (SB) and physical activity (PA) with cognitive impairment; however, the underlying mechanisms are poorly understood. We examined the associations of the accelerometer-measured movement behaviors with plasma neurofilament light chain (NfL) among older adults and the role of systemic low-grade inflammation in the associations. Results This population-based study included 1,029 dementia-free older adults (age ≥ 60 years, range 60–88 years; 59.48% women) who undertook the ActiGraph substudy (March 2018-December 2020) in MIND-China. There were nonlinear relationships of daily SB and PA time with plasma NfL concentration, such that more daily SB time or less time spent in daily light-intensity physical activity (LPA) and moderate-to-vigorous-intensity physical activity (MVPA) was significantly associated with increased plasma NfL only when SB time ≥ 8.00 h/day or LPA time

Abstract To investigate the ability of the ratio of blood urea nitrogen (BUN) to serum albumin ratio (BAR) in patients with sepsis in intensive care units (ICUs) to predict the prognosis of short-and long-term death. Data are from the Marketplace for Intensive Care Medical Information IV (MIMIC-IV v2.0) database for patients with sepsis as defined by SEPSIS-3. The primary outcome was 30-day mortality and the secondary outcome was 360-day mortality. Kaplan–Meier (KM) survival curves were plotted to describe differences in BAR mortality in different subgroups and area under the curve (AUC) analysis was performed to compare the predictive value of sequential organ failure assessment (SOFA), BAR, blood urea nitrogen (BUN) and albumin. Multivariate Cox regression models and subgroup analysis were used to determine the correlation between BAR and 30-day mortality and 360-day mortality. A total of 7656 eligible patients were enrolled in the study with a median BAR of 8.0 mg/g, including 3837 in the ≤ 8.0 group and 3819 in the BAR > 8.0 group, with 30-day mortality rates of 19.1% and 38.2% (P

Background: The structural brain alterations for subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are poorly defined. We sought to characterize grey matter volume (GMV) and cortical thickness associated with SCD and MCI among rural-dwelling older adults in China. Methods: This population-based cross-sectional study included 1072 dementia-free participants from the brain MRI sub-study of MIND-China (2018–2020). We defined MCI following the Petersen’s criteria, and SCD as the self-rated Ascertain Dementia 8-item Questionnaire score ≥ 2. Data were analyzed using voxel-based morphometry (VBM), surface-based morphometry analysis (SBM), and logistic regression models. Results: SCD was defined in 243 persons and MCI in 246 individuals. The VBM analysis showed that MCI (vs. normal cognition) was significantly associated with reduced GMV in brain regions such as the bilateral parahippocampus, bilateral hippocampus, and bilateral fusiform (P 0.05). The ROI-wise SBM analysis revealed that SCD was significantly associated with cortical thinning in the right paracentral sulcus, left caudal middle frontal gyrus, and left entorhinal cortex (P

Ibuprofen, commonly used for pain relief, inflammation, and to reduce high fever, etc., is a widely available over-the-counter drug. In recent years, due to the excessive use of ibuprofen, its presence in the aquatic environments has shown a significant increasing trend, raising concerns about potential risks to environmental safety, which attracted people’s close attention. Notably, biochar, known as an environmentally friendly functional material, had been widely studied and applied for the removal of ibuprofen in water environments. According to current reports, the adsorption capacity value of biochar for IBP is between 9.69–309 mg/g, and the adsorption mechanism mainly includes π-π stacking, hydrogen bonding, pore filling, etc. In response to this research hotspot, this study reviewed the most recent research progress on the adsorption of ibuprofen using biochar-based materials, including the modified preparation process of biochar and the adsorption mechanism of IBP on various modified biochar surfaces. Additionally, potential challenges and future development directions for the practical applications of biochar were discussed and proposed.

Abstract Surveillance is an intricate challenge worldwide especially in those complicated environments such as nuclear plants, banks, crowded areas, barns, etc. Deploying self‐powered wireless sensor nodes can increase the system's event detection capabilities by collecting environmental changes, while the incompatibility among components (energy harvesters, sensors, and wireless modules) limits their application. Here, a broadly compatible self‐powered visualized platform (SPVP) is reported to construct a passive internet of events (IoE) network for surveillance systems. By encoding electric signals into reference and working LEDs, SPVP can visualize resistance change generated by commercial resistive sensors with a broad working range (

There are two kinds of chlorites occurred in Anshan area, among which the hydrothermal Fe-chlorite with longer Fe-OH wavelength is spatially related to the high-grade magnetite ore, meaning that wavelength mapping of chlorites can be used to target the BIF-hosted high grade iron ore. In this article, quadratic polynomial, cubic spline, and quartic polynomial method were used to interpolate the absorption wavelength near 2250 nm of China ZY1-02D satellite hyperspectral image. The result of quadratic polynomial is continuous without data overlapping or intervals, thus most suitable for discrimination of the chlorites. The field truth shows that the spatial distribution of Fe-chlorite, validated by XRD analysis, is not only in accordance with that of high grade magnetite ore bodies, but also consistent with the recently discovered concealed iron bonanza. The study shows that hyperspectral remote sensing techniques can play significant role in the exploration of magnetite iron ore in east Liaoning Province.

Biological pretreatment can promote the degradation of biomass and enhance methane production via the subsequent anaerobic digestion. In addition, a large amount of bio-heat can be generated during the pretreatment process to provide heat for the anaerobic digestion process. In this study, composite microorganisms were employed for pretreating corn straw. The impact of different pretreatment times and the heat generated by the pretreatment process on subsequent anaerobic digestion were studied. The results show that the maximum temperature of the pretreatment process was 56.2 °C, obtained on day 6. After 14 days of pretreatment, the degradation rate of the pretreatment group increased by 41% compared with the control group. As a consequence, straws with different pretreatment times were used for anaerobic digestion. The group that underwent 6 days of pretreatment and utilized bio-heat generated from pretreatment achieved the highest cumulative methane production of 401.58 mL/g VS, which was 60.13% higher than in the control group without pretreatment. After 6 days of composite microorganism pretreatment, the group that utilized bio-heat achieved a 29.08% increase in cumulative methane production compared to the group that did not utilize bio-heat. In conclusion, this study highlights the potential of biological pretreatment with composite microorganisms followed by anaerobic digestion using bio-heat as an effective method for treating corn straw.

To enhance the market participation initiatives from the power source and load sides, we propose a novel power system optimal scheduling and cost compensation mechanism for China’s peak regulation ancillary service market. Owing to China’s energy structure, thermal power accounts for nearly half of the country’s installed power generation capacity. Although the willingness of thermal power units to participate in peak regulation auxiliary services is low, we propose a peak regulation cost compensation and capacity-proportional allocation mechanism. This mechanism comprehensively considers the source-load initiative. From the source side, it encourages entities to participate in peak regulation, and the restriction of the peak regulation initiative is set to ensure that each entity benefits from the peak regulation transaction. From the load side, it takes the shiftable and sheddable load as the hybrid demand response and uses the price information to influence the power consumption behavior of the user side. Subsequently, a peak regulation scheduling model was constructed with the multi-objective minimum thermal power output fluctuation of the lowest system operating cost and minimum renewable energy abandonment. This was solved using a mixed-integer linear programming model and CPLEX. Finally, a power system consisting of wind-solar-hydro-thermal-storage and hybrid demand response with a modified IEEE 30-bus system was tested to verify the effectiveness. It was proven that the proposed method improves the utilization rate of renewable energy and optimizes the scheduling of the economic benefit system of each power generation entity.

Abstract Triboelectric nanogenerators (TENGs) represent a promising next‐generation renewable energy technology. TENGs have become increasingly popular for harvesting vibration energy in the environment due to their advantages of lightweight, broad range of material choices, low cost, and no pollution. However, issues such as input force irregularity, working bandwidth, efficiency calculation, and dynamic modeling hinder the use of TENGs in industrial or practical applications. In this paper, the modeling process of the dynamical system of a TENG is reviewed from the perspective of energy flow. In addition, this paper reviews the main contributions made in recent years to achieve optimized output based on springs, magnetic forces, and pendulums, and introduces different ways to increase the bandwidth of TENGs. Finally, the main problems of TENGs in the process of harvesting vibration energy are discussed. This review may serve as a practical reference for methods to convert irregular mechanical input sources into optimized output performance toward the commercialization of TENGs.

As the charcoal processing product of Scutellariae Radix (SR), SR Carbonisata (SRC) has been clinically used as a cooling blood and hemostatic agent for thousands of years. However, the underlying active ingredients and mechanism of SRC still remained unspecified. In this study, SRC derived carbon dots (SRC-CDs) were extracted and purified from the aqueous solution of SRC, followed by physicochemical property assessment by series of technologies. The cooling blood and hemostatic effects of SRC-CDs were further evaluated via a blood-heat and hemorrhage (BHH) rat model. Results showed that the diameters of obtained fluorescent SRC-CDs ranged from 5.0 nm to 10.0 nm and possessed functional group-rich surfaces. Additionally, the as-prepared SRC-CDs showed remarkable cooling blood and hemostasis effects in BHH model, mainly manifested by significant improvement of elevated rectal temperature, inflammatory cytokines (TNF-α, IL-6, and IL-1β) levels, as well as protein expressions of myD88 and NF-κB p65, abnormal coagulation parameters (elevated APTT and FIB), hemogram parameters (RBC, HGB, and HCT), and histopathological changes in lung and gastric tissues. This study, for the first time, demonstrated that SRC-CDs were the cooling blood and hemostatic active components of SRC, which could inhibit the release of inflammatory cytokines by regulating myD88/NF-κB signaling pathway, and activating the fibrin system and endogenous coagulation pathway. These results not only provide a new perspective for the study of active ingredients of carbonized herbs represented by SRC, but also lay an experimental foundation for the development of next-generation nanomedicines.

Background Rehabilitation is crucial to recovering patients’ dysfunction, improving their life quality, and promoting an early return to their family and society. In China, most patients in rehabilitation units are patients transferred from neurology, neurosurgery, and orthopedics, and most of these patients face problems such as continuously bedridden or varying degrees of limb dysfunction, all of which are risk factors for deep venous thrombosis. The formation of deep venous thrombosis can delay the recovery process and result in significant morbidity, mortality, and higher healthcare costs, so early detection and individualized treatment are needed. Machine learning algorithms can help develop more precise prognostic models, which can be of great significance in the development of rehabilitation training programs. In this study, we aimed to develop a model of deep venous thrombosis for inpatients in the Department of Rehabilitation Medicine at the Affiliated Hospital of Nantong University using machine learning methods. Methods We analyzed and compared 801 patients in the Department of Rehabilitation Medicine using machine learning. Support vector machine, logistic regression, decision tree, random forest classifier, and artificial neural network were used to build models. Results Artificial neural network was the better predictor than other traditional machine learnings. D-dimer levels, bedridden time, Barthel Index, and fibrinogen degradation products were common predictors of adverse outcomes in these models. Conclusions Risk stratification can help healthcare practitioners to achieve improvements in clinical efficiency and specify appropriate rehabilitation training programs.

Abstract Background Osteoarthritis, a common degenerative disease of articular cartilage, is characterized by degeneration of articular cartilage, changes in subchondral bone structure, and formation of osteophytes, with main clinical manifestations including increasingly serious swelling, pain, stiffness, deformity, and mobility deficits of the knee joints. With the advent of the big data era, the processing of mass data has evolved into a hot topic and gained a solid foundation from the steadily developed and improved machine learning algorithms. Aiming to provide a reference for the diagnosis and treatment of osteoarthritis, this paper using machine learning identifies the key feature genes of osteoarthritis and explores its relationship with immune infiltration, thereby revealing its pathogenesis at the molecular level. Methods From the GEO database, GSE55235 and GSE55457 data were derived as training sets and GSE98918 data as a validation set. Differential gene expressions of the training sets were analyzed, and the LASSO regression model and support vector machine model were established by applying machine learning algorithms. Moreover, their intersection genes were regarded as feature genes, the receiver operator characteristic (ROC) curve was drawn, and the results were verified using the validation set. In addition, the expression spectrum of osteoarthritis was analyzed by immunocyte infiltration and the co-expression correlation between feature genes and immunocytes was construed. Conclusion EPYC and KLF9 can be viewed as feature genes for osteoarthritis. The silencing of EPYC and the overexpression of KLF9 are associated with the occurrence of osteoarthritis and immunocyte infiltration.

Objective: The study aimed to compare the variance of constituents of volatile oil in the stems, leaves and flowers of Vitex negundo var. heterophylla (VNH). Methods: The volatile oil in the stems, leaves and flowers of VNH were extracted by hydrodistillation, respectively, and their constituents were analyzed and identified by GC-MS, and the differences in their chemical compositions were analyzed by principal component analysis (PCA) and cluster analysis. Results: Total of 83 volatile components were identified from different parts of the VNH, including olefins, alcohols, ketones, esters, etc. 14, 58 and 55 volatile components were detected from the stems, leaves, and flowers, accounting for 59.91%, 98.32% and 95.83% of the total volatile oils in each part, respectively. Only 8 volatile components were shared by three parts, whereas 4, 22 and 21 volatile components were unique to the stems, leaves and flowers, respectively. The differential components of the volatile oils from different parts of VNH were obtained by PCA, in which the signature volatile components in the stem were 2,4-bis (1,1-dimethylethyl)-phenol, 14-methyl-pentadecanoic acid, methyl ester, heneicosane, etc, and the trademark volatile components in the leaves were β-terpinene, elemol, caryophyllene oxide, etc, whereas the hallmark volatile components in the flowers were formed by sabenene, 2,3-dihydro-3-[2-aminoethyl]-5-methoxy-1,3- dimethyl-indole-2-one, citenamide, etc. As revealed by the results of the cluster analysis, the stems of VNH were clustered with the flowers and then with the leaves. Conclusion: The composition of the volatile oil in the stems, leaves and flowers of of VNH had certain variability, which would provide a scientific basis for the further medicinal or industrial exploitation of different parts of VNH.

Abstract Background Little is known about how the obesogenic environment influences emotional states associated with glial responses and neuronal function. Here, we investigated glial reactivation and neuronal electrophysiological properties in emotion-related brain regions of high-fat diet (HFD) and ob/ob mice under chronic stress. Methods The glial reactivation and neuronal activities in emotion-related brain regions were analyzed among normal diet mice (ND), HFD mice, wild-type mice, and ob/ob mice. To further activate or inhibit astrocytes in medial prefrontal cortex (mPFC), we injected astrocytes specific Gq-AAV or Gi-AAV into mPFC and ongoing treated mice with CNO. Results The results showed that obesogenic factors per se had no significant effect on neuronal activities in emotion-related brain regions, or on behavioral performance. However, exposure to a chronic stressor profoundly reduced the frequency of spontaneous inhibitory postsynaptic currents (sIPSCs) and spontaneous excitatory postsynaptic currents (sEPSCs) in the mPFC; depressive-like behaviors were seen, accompanied by significant upregulation of astrocyte reactivation. We identified resilient and susceptible mice among chronic social defeat stress-exposed HFD mice. As expected, astrocyte reactivity was upregulated, while neuronal activity was depressed, in the mPFC of susceptible compared to resilient mice. Furthermore, activating astrocytes resulted in similar levels of neuronal activity and depressive-like behaviors between resilient and susceptible mice. Additionally, inhibiting astrocyte reactivation in the mPFC of HFD mice upregulated neuronal activities and inhibited depressive-like behaviors. Conclusions These observations indicate that obesogenic factors increase the risk of depression, and improve our understanding of the pathological relationship between obesity and depression. Graphical Abstract

Abstract Introduction Population‐based studies have rarely explored the associations of the triglyceride–glucose (TyG) index, a surrogate marker of insulin resistance, with dementia and plasma biomarkers for amyloid beta (Aβ) and neurodegeneration. Methods This population‐based study included 5199 participants (age ≥ 65 years); of these, plasma Aβ, total tau, and neurofilament light chain (NfL) were measured in 1287 persons. Dementia and subtypes were diagnosed following the international criteria. TyG index was calculated as ln(fasting triglyceride(mg/dL) × fasting glucose[mg/dL]/2). Data were analyzed using logistic and general linear regression models. Results Dementia, Alzheimer's disease (AD), and vascular dementia (VaD) were diagnosed in 301, 195, and 95 individuals, respectively. A high TyG index was significantly associated with increased likelihoods of dementia and AD; the significant association with dementia remained among participants without cardiovascular disease or diabetes. In the biomarker subsample, a high TyG index was correlated with elevated plasma Aβ, but not with total tau or NfL. Discussion High TyG index is associated with dementia, possibly via Aβ pathology.

Oral environment deterioration results from a lack of self-cleaning ability in patients with cognitive dysfunction but is also a risk factor for cognitive dysfunction. Adverse oral conditions can be alleviated and improved through a self-management and medical examination. In this review, the epidemiological evidence of previous studies is integrated to highlight the relationship between periodontitis, tooth loss, oral flora, oral dysfunction and cognitive dysfunction, emphasizing the importance of oral health for cognition. The results show that poor oral condition is associated with cognitive impairment. Although many previous studies have been conducted, there is a lack of higher-level research evidence, different judgment criteria, and conflicting research results. There is a bidirectional relationship between oral health and cognitive dysfunction. A comprehensive analysis of the relationship between oral health and cognitive dysfunction that explores the relationship and takes measures to prevent cognitive dysfunction and control the progression of such diseases is warranted in the future.

BackgroundEpithelioid hemangioendothelioma (EHE) is an extremely uncommon malignant neoplasm that originates from vascular endothelial or pre-endothelial cells. In this report, we present the case of patient who was diagnosed with a primary giant EHE of the spine and underwent treatment with total en-bloc spondylectomy (TES).Case presentationA 43-year-old male patient with a history of he presented to our hospital with chronic and progressive back pain. Physical examination revealed weakened sensation of acupuncture and touch on the left costal arch, while relatively normal neurological functions were preserved. Radiological examinations identified a giant destructive soft tissue lesion occupying the T8 vertebral region, with moderate destruction of the pedicle and lamina, as well as the 7th left rib. A preoperative biopsy of the 8th vertebra resulted in a diagnosis of epithelioid hemangioendothelioma(EHE). Postoperative immunohistochemical and pathological reports confirmed the presence of EHE in the left ribs and T8 ribs. The patient underwent resection of the 7th left rib and posterior pedicle screw fixation with 8 pairs of screws and a titanium mesh cage. Subsequently, thoracic en bloc spondylectomy was performed on the T8 vertebra. The patient did not receive radiation or chemotherapy following surgery. Over a period of 3 years, the patient remained free of disease and relapse.ConclusionThe use of transarterial embolization with spherical embolic agents (TES) has been demonstrated to be a safe, effective, and reliable treatment option for hepatic epithelioid hemangioendothelioma (EHE). Nevertheless, it is crucial to conduct long-term follow-up of this patient in order to assess their clinical outcome.

ObjectiveTo explore the associations of macular microvascular parameters with cerebral small vessel disease (CSVD) in rural-dwelling older adults in China.MethodsThis population-based cross-sectional study included 195 participants (age ≥ 60 years; 57.4% women) in the optical coherence tomographic angiography (OCTA) sub-study within the Multimodal Interventions to delay Dementia and disability in rural China (MIND-China). Macular microvascular parameters were measured using the OCTA. We automatically estimated volumes of gray matter, white matter, and white matter hyperintensity (WMH), and manually assessed numbers of enlarged perivascular spaces (EPVS) and lacunes on brain magnetic resonance imaging. Data were analyzed with the general linear models.ResultsAdjusting for multiple confounders, lower vessel skeleton density (VSD) and higher vessel diameter index (VDI) were significantly associated with larger WMH volume (P < 0.05). Lower VSD and foveal density-300 (FD-300) of left eye were significantly associated with lower brain parenchymal volume (P < 0.05). In addition, lower areas of foveal avascular zone (FAZ) and FD-300 of left eye were significantly associated with more EPVS (P < 0.05). The associations of abnormal macular microvascular parameters with WMH volume were evident mainly among females. Macular microvascular parameters were not associated with lacunes.ConclusionMacular microvascular signs are associated with WMH, brain parenchymal volume, and EPVS in older adults. The OCTA-assessed macular microvascular parameters can be valuable markers for microvascular lesions in the brain.

Abstract Background Sleep characteristics associated with dementia are poorly defined and whether their associations vary by demographics and APOE genotype among older adults are unclear. Methods This population-based cross-sectional study included 4742 participants (age ≥ 65 years, 57.1% women) living in rural China. Sleep parameters were measured using the self-rated questionnaires of the Pittsburgh Sleep Quality Index and Epworth Sleepiness Scale. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE). Dementia was diagnosed following the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria, and the National Institute on Aging-Alzheimer’s Association criteria for Alzheimer’s disease (AD). Data were analysed using multiple logistic and general linear regression models. Results Dementia was diagnosed in 173 participants (115 with AD). Multivariable-adjusted odds ratio (OR) of dementia was 1.71 (95%CI, 1.07-2.72) for sleep duration ≤4 h/night (vs. > 6-8 h/night), 0.76 (0.49-1.18) for > 4-6 h/night, 1.63 (1.05-2.55) for > 8 h/night, 1.11 (1.03-1.20) for lower sleep efficiency (per 10% decrease), and 1.85 (1.19-2.89) for excessive daytime sleepiness. Very short sleep duration (≤4 h/night), lower sleep efficiency, and excessive daytime sleepiness were significantly associated with being diagnosed with AD (multivariable-adjusted OR range = 1.12-2.07; p

The confusing use of Polygonati Rhizoma (PR) and Polygonati Odorati Rhizoma (POR) poses an unpredictable threat to the health of consumers. Sensitive, nondestructive, rapid, and multicomponent techniques for their detection are sought after. In this study, a low-cost, short-wavelength (898–1668 nm), and handheld near-infrared (NIR) spectrometer combined with multivariate spectral evaluation methods was used to establish calibration models for identifying PR and POR. NIR spectra were treated with a standard normal variate (SNV) before performing chemometric approaches. Then principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were tested for calibration model development. The PCA results showed that spectral differences existed between the two herbs. However, the evaluation techniques could not separate them with the required accuracy. The PLS-DA calibration model, on the other hand, could separate the two herbs according to their spectral information with the prediction accuracy of >98.3%. Thus, it has been proven that a rapid, green, and low-cost method to support on-site and practical inspection through a handheld NIR instrument has been established to identify PR and POR and ensure the safety of the clinical medication.

Artificial intelligence gives pregnant women another avenue for receiving healthcare information. With the advancement of information and communication technology, searching online for pregnancy information has become commonplace during COVID-19. This study aimed to explore pregnant women’s information-seeking behavior based on data mining and text analysis in China. Posts on maternal and infant-related websites were collected during 1 June 2020, and 31 January 2021. A total of 5,53,117 valid posts were obtained. Based on the data, we performed correlation analysis, topic analysis, and sentiment analysis. The correlation analysis showed the positive effects of population, population with a college education or above, and GDP on post counts. The topic analysis extracted six, nineteen, eighteen, thirteen, eleven, sixteen, thirteen, sixteen, nineteen, and fourteen topics in different months of pregnancy, reflecting different information needs in various pregnancy periods. The results of sentiment analysis show that a peak of the posts emerged in the second month of pregnancy and the proportion of emotionally positive posts reached its peak in the sixth month of pregnancy. The study provides important insights for understanding pregnant women’s information-seeking behavior.

Dendrobium huoshanense, a traditional medicinal and food homologous plant, belongs to the family Orchidaceae and has a long history of medicinal use. It is reported that the stem of D. huoshanense has a variety of bioactive ingredients such as polysaccharides, flavonoids, sesquiterpenes, phenols, etc. These bioactive ingredients make D. huoshanense remarkable for its pharmacological effects on anti-tumor, immunomodulation, hepatoprotective, antioxidant, and anticataract activities. In recent years, its rich pharmacological activities have attracted extensive attention. However, there is no systematic review focusing on the chemical compositions and pharmacological effects of D. huoshanense. Therefore, the present review aims to summarize current research on the chemical compositions and pharmacological activities of D. huoshanense. This study provides valuable references and promising ideas for further investigations of D. huoshanense.

Abstract Background We investigated the health status of some workers exposed to occupational noise in Xinjiang, and explored the influencing factors of their health level. We aimed to determine the key protection groups of occupational noise hazards, which might provide the basis for the development of targeted noise prevention measures. Methods We used descriptive analysis to investigate a total of 11,800 participants who underwent occupational health examination in Xinjiang Occupational Disease Prevention Hospital. Results The hearing abnormality rate of noise exposure participants was 8.03%, which was higher in males than females (χ2 = 54.507, p

Human–AI collaboration has attracted interest from both scholars and practitioners. However, the relationships in human–AI teamwork have not been fully investigated. This study aims to research the influencing factors of trust in AI teammates and the intention to cooperate with AI teammates. We conducted an empirical study by developing a research model of human–AI collaboration. The model presents the influencing mechanisms of interactive characteristics (i.e., perceived anthropomorphism, perceived rapport, and perceived enjoyment), environmental characteristics (i.e., peer influence and facilitating conditions), and personal characteristics (i.e., self-efficacy) on trust in teammates and cooperative intention. A total of 423 valid surveys were collected to test the research model and hypothesized relationships. The results show that perceived rapport, perceived enjoyment, peer influence, facilitating conditions, and self-efficacy positively affect trust in AI teammates. Moreover, self-efficacy and trust positively relate to the intention to cooperate with AI teammates. This study contributes to the teamwork and human–AI collaboration literature by investigating different antecedents of the trust relationship and cooperative intention.

Summary: Background: Previous research has revealed that KIBRA controls secretion of extracellular vesicles (EVs) by inhibiting the proteasomal degradation of Rab27a and EVs play an important role in amyloid β (Aβ) metabolism and transmission during Alzheimer's disease (AD) pathogenesis. Here, we further test the hypothesis that KIBRA regulates Aβ metabolism via the endosomal-lysosomal system. Methods: We generated KIBRA knockout mice on a 5XFAD background and KIBRA knockdown cells in murine HT22 cells with stably overexpressing APP. Various forms of Aβ and quantification of EVs were analyzed by biochemical methods and nanoparticle tracking analysis, respectively. Multivesicular bodies (MVBs) were visualized by electron microscopy and confocal fluorescent microscopy. In a population-based cohort (n = 1419), KIBRA genotypes and plasma Aβ levels were analyzed using multiple-PCR amplification and Simoa, respectively. Findings: Multiple forms of Aβ were dramatically attenuated in KIBRA knockout mouse brain, including monomers, oligomers, and extracellular deposition, but KIBRA knockout had no effect on intraneuronal APP C-terminal fragment β (APP-CTFβ)/Aβ levels. KIBRA depletion also decreased APP-CTFβ/Aβ-associated EVs secretion and subsequently enhanced MVBs number. Furthermore, we found that excessive accumulation of MVBs harboring APP-CTFβ/Aβ promoted the MVBs-lysosome fusion for degradation and inhibition of lysosomal function rescued secretion of APP-CTFβ/Aβ-associated EVs. More importantly, whole exon sequencing of KIBRA in a large population-based cohort identified the association of KIBRA rs28421695 polymorphism with plasma Aβ levels. Interpretation: These results demonstrate that KIBRA regulates Aβ metabolism via controlling the secretion of APP-CTFβ/Aβ-associated EVs. Funding: National Key R&D Program of China, and National Natural Science Foundation of China.

Developing non-noble-metal heterogeneous catalysts with high efficiency in HCOOH dehydrogenation is significant for the acquisition of hydrogen, but remains a great challenge. Here, the authors modulate oxygen coverage of Ti3C2Tx MXenes to boost the catalytic activity toward HCOOH dehydrogenation.

Abstract Background Spontaneous functional recovery occurs during the acute phase after stroke onset, but this intrinsic recovery remains limited. Therefore, exploring the mechanism underlying spontaneous recovery and identifying potential strategies to promote functional rehabilitation after stroke are very important. The CD200/CD200R signaling pathway plays an important role in neurological recovery by modulating synaptic plasticity during multiple brain disorders. However, the effect and mechanism of action of the CD200/CD200R pathway in spontaneous functional recovery after stroke are unclear. Methods In this study, we used a transient middle cerebral artery occlusion (MCAO) model in rats to investigate the function of CD200/CD200R signaling in spontaneous functional recovery after stroke. We performed a battery of behavioral tests (Longa test, adhesive removal test, limb-use asymmetry test, and the modified grip-traction test) to evaluate sensorimotor function after intracerebroventricular (i.c.v.) injection with CD200 fusion protein (CD200Fc) or CD200R blocking antibody (CD200R Ab) post-stroke. Density and morphology of dendritic spines were analyzed by Golgi staining. Microglia activation was evaluated by immunofluorescence staining. Western blot was used to detect the levels of protein and the levels of mRNA were measured by qPCR. Results Our study demonstrated that sensorimotor function, synaptic proteins, and structures were gradually recovered and CD200R was transiently upregulated in ipsilateral cortex after stroke. Synapse-related proteins and dendritic spines were preserved, accompanied by sensorimotor functional recovery, after stereotaxic CD200Fc injection post-stroke. In addition, CD200Fc restrained microglia activation and pro-inflammatory factor release (such as Il-1, Tnf-α, and Il-6) after MCAO. On the contrary, CD200R Ab aggravated sensory function recovery in adhesive removal test and further promoted microglia activation and pro-inflammatory factor release (such as Il-1) after MCAO. The immune-modulatory effect of CD200/CD200R signaling might be exerted partly by its inhibition of the MAPK pathway. Conclusions This study provides evidence that the CD200/CD200R signaling pathway contributes to spontaneous functional recovery by enhancing synaptic plasticity via inhibition of microglia activation and inflammatory factor release.

Large amounts of data will be generated due to the rapid development of the Internet of Things (IoT) technologies and 5th generation mobile networks (5G), the processing and analysis requirements of big data will challenge existing networks and processing platforms. As the most promising technology in 5G networks, edge computing will greatly ease the pressure on network and data processing analysis on the edge. In this paper, we considered the coordination between compute and cache resources between multi-level edge computing nodes (ENs), users under this system can offload computing tasks to ENs to improve quality of service (QoS). We aimed to maximize the long-term profit on the edge, while satisfying the low-latency computing of the users, and jointly optimize the edge-side node offloading strategy and resource allocation. However, it is challenging to obtain an optimal strategy in such a dynamic and complex system. To solve the complex resource allocation problem on the edge and make edge have certain adaptation and cooperation, we used double deep Q-learning (DDQN) to make decisions, ability to maximize long-term gains while making quick decisions. The simulation results prove the effectiveness of DDQN in maximizing revenue when allocation resources on the edge.

Photocatalytic conversion of CO2 into HCOOH is a highly anticipated way to address the long-term demand of energy supply. Herein, we report the fabrication of uniform core-shell nanoparticles composed of a Cu core encapsulated by a Cu2O shell by thermal treatment of a Cu-MOF precursor. Impressively, Cu@Cu2O/C-350 exhibited the catalytic activity in CO2 reduction to HCOOH, attaining a HCOOH production rate of 31 μg/h without any additives at room temperature. Further mechanistic studies indicated that surface Cu2O shell was acted as the active sites for the adsorption and activation of CO2.

Abstract Introduction Multidomain intervention approaches have emerged as a potential strategy to reduce dementia risk. We sought to describe the baseline assessment approaches, health conditions, and risk profiles for brain aging of participants in the randomized controlled Multimodal INterventions to delay Dementia and disability in rural China (MIND‐China). Methods MIND‐China engaged residents who were ≥60 years of age and living in rural communities in the western Shandong province. In March to September 2018, all participants underwent the core module assessments via face‐to‐face interviews, clinical examinations, neuropsychological testings, and laboratory tests. Specific modules of examination were performed for sub‐samples, including brain magnetic resonance imaging scans, genetic and blood biochemical markers, actigraphy testing, cardiopulmonary coupling analysis for sleep quality and disturbances, audiometric testing, and optical coherence tomography examination. We performed descriptive analysis. Results In total, 5765 participants (74.9% of all eligible residents) undertook the baseline assessments. The mean age was 70.9 years (standard deviation, 5.9), 57.2% were women, 40.6% were illiterate, and 88.3% were farmers. The overall prevalence of common chronic diseases was 67.2% for hypertension, 23.4% for dyslipidemia, 23.5% for heart disease, 14.4% for diabetes mellitus, and 5.4% for dementia. The prevalence rates of hypertension, diabetes mellitus, dyslipidemia, obesity, heart disease, depressive symptoms, and dementia were higher in women than in men (P

Design concept evaluation is a huge challenge in the R&D stage of new product development. The information in the assessments often depends on the decision-makers' individual preferences. However, sometimes the decision-makers cannot give precise and complete information because it is very difficult for them to be familiar with all the criteria. In this situation, an incomplete information decision-making matrix is established. In this paper, decision-making methods based on incomplete information are compared in the literature review. Incomplete information determination method using trust mechanism is proved as a proper way to solve this problem, and the missing information are computed based on the alternatives However, in design concept evaluation, experts commonly provide their preferences using linguistic words according to the different attributes. Hence, we propose a three-step Multiple Attributes Group Decision-making (MAGDM) method where the missing value are determined by attributes. In step one, a data repairing method is proposed based on trust theory. After that, in step two, a comprehensive weight determination method combining AHP and entropy is proposed to obtain the weight of index attributes. Finally, the Rough-TOPSIS method is applied in the design scheme ranking step. In the case study, the proposed method is implemented in a tourism product design process to show its effectiveness.

To explore the application of chitosan–gentamicin conjugate (CS-GT) in inhibiting Vibrio parahaemolyticus (V. parahaemolyticus), which is an important pathogen in aquatic animals worldwide, the antimicrobial activity of CS-GT and the effects of a CS-GT dose on the intestine histopathology and intestinal flora of V. parahaemolyticus-infected shrimps were explored. The results showed that CS-GT possessed broad-spectrum antibacterial activity, with minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC) and half inhibitory concentration (IC50) of 20.00 ± 0.01, 75.00 ± 0.02 and 18.72 ± 3.17 μg/mL for V. parahaemolyticus, respectively. Further scanning electron microscope and cell membrane damage analyses displayed that the electrostatic interaction of CS-GT with cell membrane strengthened after CS grafted GT, resulting in leakage of nucleic acid and electrolytes of V. parahaemolyticus. On the other hand, histopathology investigation indicated that high (100 mg/kg) and medium (50 mg/kg) doses of CS-GT could alleviate the injury of a shrimp’s intestine caused by V. parahaemolyticus. Further 16S rRNA gene sequencing analysis found high and medium dose of CS-GT could effectively inhabit V. parahaemolyticus invasion and reduce intestinal dysfunction. In conclusion, CS-GT possesses good antibacterial activity and could protect shrimps from pathogenic bacteria infection.

Abstract Constructing nitrogen (N2) adsorption and activation sites on semiconductors is the key to achieving efficient N2 photofixation. Herein, Mn–W dual‐metal sites on WO3 are designed toward efficient N2 photoreduction via controlled Mn doping. Impressively, the optimal 2.3% Mn‐doped WO3 (Mn‐WO3) exhibits a remarkable ammonia (NH3) production rate of 425 µmol gcat.−1 h−1, representing the best catalytic performance among the ever‐reported tungsten oxide‐based photocatalysts for N2 fixation. Quasi in situ synchrotron radiation X‐ray spectroscopy directly identifies that the Mn–W dual‐metal sites can enhance the polarization of the adsorbed N2, which is beneficial to the N2 activation. Further theoretical calculations reveal that the increased polarization is originated from the electron back‐donation into the antibonding orbitals of the adsorbed N2, hence lowering the reaction energy barrier toward the N2 photofixation. The concept of dual sites construction for inert molecule activation offers a powerful platform toward rational design of highly efficient catalysts for nitrogen fixation and beyond.

Recently, smart cities, smart homes, and smart medical systems have challenged the functionality and connectivity of the large-scale Internet of Things (IoT) devices. Thus, with the idea of offloading intensive computing tasks from them to edge nodes (ENs), edge computing emerged to supplement these limited devices. Benefit from this advantage, IoT devices can save more energy and still maintain the quality of the services they should provide. However, computational offload decisions involve federation and complex resource management and should be determined in the real-time face to dynamic workloads and radio environments. Therefore, in this work, we use multiple deep reinforcement learning (DRL) agents deployed on multiple edge nodes to indicate the decisions of the IoT devices. On the other hand, with the aim of making DRL-based decisions feasible and further reducing the transmission costs between the IoT devices and edge nodes, federated learning (FL) is used to train DRL agents in a distributed fashion. The experimental results demonstrate the effectiveness of the decision scheme and federated learning in the dynamic IoT system.

BackgroundCoronavirus disease 2019 (COVID-19) pandemic has become the most severe global health issue. Abnormal liver functions are frequently reported in these patients. However, liver function abnormality was often overlooked during COVID-19 treatment, and data regarding liver functions after cure of COVID-19 is limited. This study aimed to reveal the changes of liver function tests (LFTs) during hospitalization, and its clinical significance in patients with COVID-19.MethodsIn this retrospective, bi-center study, a total of 158 hospitalized patients diagnosed with COVID-19 in China were included from January 22nd, 2020 to February 20th, 2020. Clinical features, laboratory parameters including LFTs, and treatment data were collected and analyzed. LFTs included alanine transaminase, aspartate aminotransferase, alkaline phosphatase, gamma-glutamyl transferase, and total bilirubin. Patients were considered with abnormal LFTs when any value of these tests was higher than upper limit of normal.ResultsOf 158 patients with COVID-19, 67 (42.41%) patients had abnormal LFTs on admission and another 50 (31.65%) patients developed abnormal LFTs during hospitalization. The incidence of LFTs abnormality in severe COVID-19 cases was significantly higher than non-severe cases. All LFTs in COVID-19 patients were correlated with oxygenation index. There was no statistical difference in treatment between the patients with or without liver test abnormalities. By the time of discharge, there were still 64 (40.50%) patients with abnormal LFTs. Logistic regression analysis identified younger age, hypertension and low lymphocyte counts as independent risk factors for persistent abnormal LFTs during hospitalization.ConclusionLiver function tests abnormality was common in COVID-19 patients and was more prevalent in severe cases than in non-severe cases. A substantial percentage of patients still had abnormal LFTs by the time of discharge.

A damage location method for the autocorrelation peak value change rate based on the vibration response of a random vibration structure is established. To calculate the autocorrelation function of the vibration response of each measurement point, we transformed the maximum values into an autocorrelation peak vector. Under a good condition, the autocorrelation peak vector has a fixed shape; hence, it can be used as a basis for structural damage identification. The two adjacent measurement points with the largest change corresponding to the two nodes of the damage unit and the damage location are determined to calculate the change rate of the autocorrelation peak values between damaged and intact structures. When the degree of damage is 5%, the autocorrelation peak value change rate of the acceleration response on the two nodes of the damage unit is significantly greater than that of the other points, which can accurately determine the damage location, indicating that the damage location index constructed has good damage sensitivity. The damage location index can determine a single damage, as well as a double damage. The antinoise capability of the damage location index gradually improves with an increase in the degree of damage. At 45% degree of damage and signal-to-noise ratio (SNR) of 0 dB, the damage location index can still accurately determine the damage location, which has good antinoise interference capability. The Xi’an Bell Tower is used as a case study, and the feasibility of this method is verified, which provides a new method for the study of damage location of ancient timber structures.