Search

Paulownia fortunei, one of the world's fastest growing timber tree species, is universally applied with fertilizer as a management approach to meet the nutrient requirements for efficient cultivation. The substantial effects of fertilizer on soil microorganisms in Paulownia plantations have been empirically tested; however, the successive chronosequence of soil microbial carbon and nitrogen functional genes under different fertilizer application durations remains limited. The objective of this study was to explore the characteristics of soil microorganisms involved in carbon and nitrogen cycling and greenhouse gas (GHG) production under different fertilizer application durations. Different fertilizer treatments, i.e., the short-term group (SG) versus the long-term group (LG), and durations were applied to subtropical plantations in southern China and compared with zonal evergreen broad-leaved forests. Results showed that fertilizer treatment significantly increased the relative abundance of Acidobacteriota and the expression of nirK and nosZ. The functional groups that dominated metabolism in SG and LG treatments belonged to Actinobacteria and Acidobacteriota, respectively, suggesting that the nutrient preference of microorganisms in forest soil may change from copiotrophs to oligotrophs with increasing fertilizer application duration. Correlation network analysis showed that the communities that dominated the carbon and nitrogen cycles belonged to Actinobacteria and Acidobacteriota, respectively, and were closely related to ammonium nitrogen and available iron. Actinobacteria and Acidobacteriota were likely the major taxa that affected soil GHG production under different fertilizer application durations. We concluded that long-term fertilizer use changed the preference of microbial nutrient uptake into recalcitrant nutrients, and the sensitivity of the microbial community to nutrients gradually decreased with increasing fertilizer application time. The dominant Actinobacteria affected soil carbon and nitrogen cycles largely by stimulating denitrification to increase the release of nitrous oxide, which might lead to the loss of nitrogen components and the intensification of the GHG effect with increasing fertilizer application time. [ABSTRACT FROM AUTHOR]

For wire-feed laser additive manufacturing (WLAM), the build geometrical parameters are one of the indicators of build quality; thus, it is crucial to monitor the geometrical parameters in real-time for quality assurance. However, the current research and development for in situ geometry monitoring are in the early phase due to interweaved correlation of the sensing data and their comprehensive effects on the bead geometry, as well as the high characterization cost to model these effects. This paper focuses on using machine learning techniques to enable in-process geometry monitoring by comprehensively modeling the correlation between the real-time molten pool sensing data and bead geometry properties. A deep learning-based multi-modality convolutional neural network (m-CNN) is trained to take the molten pool image and thermal profile as the input to comprehensively estimate the geometric properties of the build bead. The network is configured by the hyperparameter optimization process and experimentally validated by the real-time molten pool sensing data collected on a wire-feed laser additive manufacturing (AM) system. The effect of using the temperature data from the leading, center, and tailing positions of the molten pool on the prediction performance of the CNN model is studied and analyzed. The CNN model's performance is compared with a support vector regression model for comparison. The developed model represents an in-process monitoring framework for real-time estimation of post-processing bead geometric properties and takes a step towards developing in situ quality control strategy for the metal AM system. [ABSTRACT FROM AUTHOR]

Casing deformation occurs frequently in shale gas wells, resulting in the failure of some fracturing stages to complete normal operations, which seriously affects shale gas production. This paper firstly analyzes the casing deformation mechanism of shale gas wells and determines that the casing shear deformation caused by formation slip is the main factor of casing deformation. In order to solve the problem of casing shear deformation, a finite element numerical model including the formation, cement ring, and the casing is established. The casing shear deformation caused by formation slip is simulated, and the deformation results obtained are consistent with those measured in the actual wellbore. Based on the numerical model, a casing deformation governance method is proposed to optimize the wellbore trajectory and adjust the cement ring properties. It is calculated that reducing the dip angle á of the formation and casing vertical direction and reducing the formation slip is beneficial to reducing casing deformation. The use of low elastic modulus cement and uncementing operations can provide a buffer space for formation slip, effectively reduce casing deformation, and provide an effective treatment method for shear deformation of shale gas wells. [ABSTRACT FROM AUTHOR]

Sentiment recognition analysis is an important method for studying social textual information. It has an important position in social text analysis and research. However, at present, the efficiency of official document text sentiment recognition is low, and manual judgment methods are often used, so the subjective consciousness is strong. This article aims to study the sentiment official document text recognition and analysis method based on the neural network BERT model. It extracts the sentiment information contained in the internet text information through the BERT–SVM model algorithm under deep learning and then mines the user's sentiment. Sentiment analysis is carried out on the sentences in the article, considering the influencing factors of individuals, society, and even the country, putting the method in the position of analyzing the different sentiments represented by a sentence or each word. This article first describes the related technologies of text sentiment recognition, such as feedforward neural networks, convolutional neural networks, and recurrent neural networks. By sentiment training using LSTM-RNN and LSTM-RNN-word2vec models, experiments show that the average accuracy of sentiment classification is 95.12%, the K nearest neighbors result is 90.87% and the Bayesian classifier is 86.84%. By comparison, the BERT–SVM model improves the accuracy of text sentiment classification. [ABSTRACT FROM AUTHOR]

A Schiff base compound 6-amino-5-(((2-hydroxynaphthalen-1-yl)methylene)amino)-2-mercaptopyrimidin-4-ol (AHM) in acetonitrile solvent is found to show "OFF–ON type" mode upon addition of Al3+ ion and successfully applied for selective recognition of Al3+ ion. In this work, the reconsideration of excited state intramolecular proton transfer (ESIPT) and twisted intramolecular charge transfer (TICT) has been explored in detail based on density functional theory (DFT) and time-dependent density functional theory (TD-DFT) methods. In the absence of Al3+, the lone pair electrons are transferred from –C = N to –OH forming a hydrogen-bonding configuration, and AHM shows weak fluorescence. When AHM is coordinated with metal ion, the TICT state is eliminated, and emission is significantly enhanced. Thus, in this paper, the origination of the non-emissive behavior of AHM has been explained in detail. The frontier molecular orbitals (MOs) and hole-electrons are used to analyze the charge distribution, providing strong evidence for the possibility of ESIPT and TICT processes occurring. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) paradigm, by transforming physical devices into innovative items, affects every aspect of our daily lives. It has brought a slew of evolutionary and revolutionary services that were almost impossible to imagine until recently. The numerous services and applications offered by IoT cover numerous fields, such as personal healthcare, urban life, energy management, and manufacturing. A tremendous amount of data is produced to reach valuable information and meet users' needs. In addition, since the number of services and applications is increasing rapidly, an efficient method to fulfill the growing demands in different application domains becomes challenging. To handle the mentioned problems, task scheduling mechanisms have a significant influence. Despite the importance of these methods in the IoT, an in-depth and systematic review of the current works in this area is clearly lacking. Therefore, we aim to overcome this gap by adopting an organized manner. In fact, this paper aims to specify the challenging problems in IoT task scheduling, highlight the effective works, and outline some hints for upcoming studies. [ABSTRACT FROM AUTHOR]

Introduction: Chronic hepatitis B virus (HBV) infection is associated with significant global morbidity and mortality. Low treatment rates are observed in patients living with HBV; the reasons for this are unclear. This study sought to describe patients' demographic, clinical and biochemical characteristics across three continents and their associated treatment need. Methods: This retrospective cross-sectional post hoc analysis of real-world data used four large electronic databases from the United States, United Kingdom and China (specifically Hong Kong and Fuzhou). Patients were identified by first evidence of chronic HBV infection in a given year (their index date) and characterized. An algorithm was designed and applied, wherein patients were categorized as treated, untreated but indicated for treatment and untreated and not indicated for treatment based on treatment status and demographic, clinical, biochemical and virological characteristics (age; evidence of fibrosis/cirrhosis; alanine aminotransferase [ALT] levels, HCV/HIV coinfection and HBV virology markers). Results: In total, 12,614 US patients, 503 UK patients, 34,135 patients from Hong Kong and 21,614 from Fuzhou were included. Adults (99.4%) and males (59.0%) predominated. Overall, 34.5% of patients were treated at index (range 15.9–49.6%), with nucleos(t)ide analogue monotherapy most commonly prescribed. The proportion of untreated-but-indicated patients ranged from 12.9% in Hong Kong to 18.2% in the UK; almost two-thirds of these patients (range 61.3–66.7%) had evidence of fibrosis/cirrhosis. A quarter (25.3%) of untreated-but-indicated patients were aged ≥ 65 years. Conclusion: This large real-world dataset demonstrates that chronic hepatitis B infection remains a global health concern; despite the availability of effective suppressive therapy, a considerable proportion of predominantly adult patients apparently indicated for treatment are currently untreated, including many patients with fibrosis/cirrhosis. Causes of disparity in treatment status warrant further investigation. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to construct a clinically practical model to precisely predict lymph node (LN) metastasis in bladder cancer patients. Methods: Four independent cohorts were included. The least absolute shrinkage and selection operator regression with multivariate logistic regression were applied. The diagnostic efficacy of LN score and CT/MRI was compared by accuracy, sensitivity, specificity, and area under curve (AUC). Results: A total of 606 patients were included to develop a basic prediction model. After multistep gene selection, the LN metastasis prediction model was constructed with 5 genes. The model can accurately predict LN metastasis with an AUC of 0.781. For clinically practical use, we transformed the model into a Fast LN Scoring System using the SYSMH cohort (n = 105). High LN score patients exhibited a 72.2% LN metastasis rate, while low LN score patients showed a 3.4% LN metastasis rate. The LN score achieved a superior accuracy than CT/MRI (0.882 vs. 0.727). Application of LN score can correct the diagnosis of 88% (22/25) patients who were misdiagnosed by CT/MRI. Discussion: The clinically practical LN score can precisely, rapidly, and conveniently predict LN status, which will assist preoperative diagnosis for LN metastasis and guide precise therapy. [ABSTRACT FROM AUTHOR]

HTO has proven to be a cost-effective surgical procedure in the treatment of KOA, but few investigations have studied radiological changes and clinical effectiveness of OWHTO in geriatric patients. 76 patients were recruited in this retrospective study. According to the age, patients were divided into two groups (≤ 60, Group "Young"; > 60, Group "Geriatric"). Demographic data, radiological imaging and postoperative complications were analyzed. Kellgren–Lawrence grade (K–L), weight-bearing line ratio (WBLR); posterior tibial slope angle (PTS); American knee score (AKS); Western Ontario and McMaster Universities Arthritis Index (WOMAC) and visual analog scale (VAS) were introduced to estimate the clinical outcome of OWHTO. There were 18 male and 58 female patients in the present study with a mean age of 58.5 ± 9.2 years (ranges from 40 to 82 years); the average age was 51.4 ± 4.1 years and 67.3 ± 4.9 years for group Y and G respectively, 44.7% and 31.5% patients were older than 60 and 65 years. BMI for the 76 patients was 26.6 ± 3.2 kg/m2, and geriatric patients were more likely accompanied by one or more comorbidities (70.6 vs. 45.2%). There were 34 and 42 patients in group Geriatric and group Young respectively, and no significant difference of MPTA, WBLR, PTS and WOMAC, VAS, AKS and ROM between the two group (P > 0.05) were found. After more than a two-year follow-up period, postoperative WBLR, AKS, WOMAC and VAS were much more desired than preoperative, and no significant difference of these variables between the young and geriatric group (P > 0.05), however, elderly patients were more likely to suffer from a longer bone union time. OWHTO can avoid geriatric patients from undergoing secondary knee surgery in the short term, however the survival rate of OWHTO in geriatric patients should be ultimately clarified by different studies. [ABSTRACT FROM AUTHOR]

Purpose: Compared with people without diabetes, people with type 2 diabetes (T2D) are at higher risk of both subnormal vitamin C status and increased oxidative stress. We aimed to investigate the associations of serum vitamin C concentrations with all-cause and cause-specific mortality among adults with and without T2D. Methods: The current analysis included 20,045 adults (2691 people with T2D and 17,354 without T2D) from the Third National Health and Nutrition Examination Survey (NHANES III) and NHANES 2003–2006. Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Restricted cubic spline analyses were used to examine the dose–response relationship. Results: After a median follow-up of 17.3 years, 5211 deaths were documented. Individuals with T2D had a lower level of serum vitamin C concentrations compared with those without T2D (the median value: 40.1 vs. 44.9 μmol/L). Furthermore, the dose–response relationship between serum vitamin C and mortality showed different patterns between participants with and without T2D. In individuals without T2D, there was a nonlinear association of serum vitamin C concentrations with all-cause, cancer, and CVD mortality, with the lowest risk around a serum vitamin C concentration of 48.0 μmol/L (all Poverall < 0.05, Pnonlinearity < 0.05). In contrast, among those with T2D in the similar concentration range, higher serum vitamin C levels (ranged from 0.46 to 116.26 μmol/L) were linearly associated with lower all-cause and cancer mortality (both Poverall < 0.05, Pnonlinearity > 0.05). Significant additive interaction was observed between diabetes status and serum vitamin C levels with regard to all-cause and cancer mortality (P < 0.001). In addition, C-reactive protein, gamma-glutamyl transpeptidase, and HbA1c explained 14.08, 8.96, and 5.60% of the association between serum vitamin C and all-cause mortality among individuals with T2D, respectively. Conclusions: Higher serum vitamin C concentrations were significantly associated with lower risk of mortality in participants with T2D in a linear dose–response manner, while a nonlinear association was observed in participants without T2D, with an apparent threshold around 48.0 μmol/L. These findings suggest that the optimal vitamin C requirement may differ in individuals with and without T2D. [ABSTRACT FROM AUTHOR]

Falls are a serious public health problem in the aging population because of the associated clinical and socioeconomic impact. Although previous studies have investigated fall-risk-increasing drugs (FRIDs), few studies have focused on dosage among adult inpatients. This study aimed to evaluate associations between fall risk and dosage of different FRIDs classes in hospital inpatients. Inpatients who experienced falls at medical or surgical wards of Changhua Christian Hospital from January 2017 to December 2021 were identified and matched by age, sex, and hospital ward to randomly selected controls (four per case). Anonymous patient data were extracted from the hospital medical data repository, including demographic characteristics, comorbidities, fall-risk scores, and drug prescriptions. Medication dosages were computed using the anatomical therapeutic chemical classification and the defined daily dose system of the World Health Organization. A total of 852 cases and 3408 controls were identified as eligible. Reducing the use of CNS-active medications, administering lower doses of sedative-hypnotics, prescribing sufficient dopaminergic anti-Parkinson agents, and using NSAIDs instead of opioids are imperative in preventing falls among hospitalized patients according to the findings in the study. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Patient Biochemistry and Treatment Need in Chronic Hepatitis B Virus Infection Across Three Continents: Retrospective Cross-Sectional Cohort Studies." The original article was published without open access, but the error has been resolved and the article is now available under a Creative Commons Attribution 4.0 International License. The correction also includes the removal of a duplicate reference and the addition of an affiliation for one of the authors. The publisher, Springer Nature, remains neutral in terms of jurisdictional claims and institutional affiliations. [Extracted from the article]

Understanding the internal mechanism of CO2 adsorption and separation of COF adsorbent materials is of great significance for high-efficiency carbon capture and storage (CCS). Herein, polyarylether-based covalent organic frameworks (PAE-COFs) structures with functionalized –CN, –COOH, and –C(NH2)NOH groups were evaluated for CO2 adsorption and separation over N2 by using grand canonical Monte Carlo (GCMC) simulation and density functional theory (DFT). Our calculation results showed that the adsorption and separation performance of CO2 in COF frameworks was related to the physical characteristics of pores, the types of gas molecules, and the interaction between COFs and gas molecules. JUC-505 modified by –CN functional group provided a feasible microporous environment with moderate specific surface area and porosity, presenting a high CO2 adsorption capacity of 5.14 mmol/g at 273 K and 1 bar. The PAE-COFs structures had good CO2/N2 separation performance, in which the CO2/N2 selectivity of JUC-505-COOH reached up to 90 at 273 K and 1 bar. Interactions analysis showed that the van der Waals and Coulomb interactions between CO2 and the framework were significantly stronger than those between N2 and the framework. Therefore, CO2 had a higher adsorption heat, which led to the larger adsorption capacity and the high selectivity of CO2 over N2. The gas radial distribution functions and 2D density distribution displayed that the CO2 adsorption corresponded to a multi-layer adsorption in frameworks, leading to the high performances of PAE-COFs for CO2 capture and separation. [ABSTRACT FROM AUTHOR]

Highlights: A printable multifunctional electronic skin (e-skin) with an excellent self-healing ability was developed via a simple, clean and universally applicable method. Water served as both the only solvent throughout the fabrication process and the trigger of the self-healing process. Each e-skin component was biocompatible. Combined with conventional electronics, signals collected by the e-skin could be transmitted to smartphones via Bluetooth for post-processing.Electronic skins (e-skins) with an excellent sensing performance have been widely developed over the last few decades. However, wearability, biocompatibility, environmental friendliness and scalability have become new limitations. Self-healing ability can improve the long-term robustness and reliability of e-skins. However, self-healing ability and integration are hardly balanced in classical structures of self-healable devices. Here, cellulose nanofiber/poly(vinyl alcohol) (CNF/PVA), a biocompatible moisture-inspired self-healable composite, was applied both as the binder in functional layers and the substrate. Various functional layers comprising particular carbon materials and CNF/PVA were patterned on the substrate. A planar structure was beneficial for integration, and the active self-healing ability of the functional layers endowed self-healed e-skins with a higher toughness. Water served as both the only solvent throughout the fabrication process and the trigger of the self-healing process, which avoids the pollution and bioincompatibility caused by the application of noxious additives. Our e-skins could achieve real-time monitoring of whole-body physiological signals and environmental temperature and humidity. Cross-interference between different external stimuli was suppressed through reasonable material selection and structural design. Combined with conventional electronics, data could be transmitted to a nearby smartphone for post-processing. This work provides a previously unexplored strategy for multifunctional e-skins with an excellent practicality. [ABSTRACT FROM AUTHOR]

Resveratrol (RES) is a polyphenol with diverse beneficial biological and pharmacological activities, and our previous results have demonstrated its neuroprotective effects in several metabolic diseases, including non-alcoholic fatty liver disease. The aim of the present study is to investigate the potential effect of RES against oleic acid (OA)-induced cell injuries in SH-SY5Y cells and explore the possible mechanism. Based on the dose- and time-dependent effects of OA on cell proliferation and LDH release, SH-SY5Y cells were challenged with OA and incubated with or without RES (10–5–10–9 mM) or sitagliptin (STG, 10–7 mM). Lipid accumulation, SREBP1 and PPARα protein expression, glucose consumption and IRS1, AKT, ERK phosphorylation under insulin stimulation, and ROS production were detected. The protein expression of brain-derived neurotrophic factor (BDNF), Copine 6, and key molecules in the Wnt/β-catenin signalling pathway were measured via western blot. The expression of Wnt 1 was also measured via immunofluorescence staining. The results showed that RES treatment could alleviate the neurotoxicity induced by OA, as indicated by the increased cell proliferation and the decreased concentration of LDH in the supernatant. The increased lipid deposition and protein expression of SREBP1 and PPARα induced by OA was also reversed by treatment with RES. Moreover, RES could upregulate glucose consumption and the protein expression of phosphorylated IRS1, AKT, ERK and reduced ROS production in OA-induced SH-SY5Y cells. Furthermore, RES treatment reversed the imbalanced protein expression of BDNF, Copine 6, p-β-catenin, and Wnt 1 in SH-SY5Y cells induced by OA and decreased the hyperexpression of p-GSK3β. However, these effects were suppressed by DKK1, which is a specific antagonist of the Wnt signalling pathway. These results suggested that RES has a neuroprotective effect against OA-induced cell injury and dysfunctional glucolipid metabolism, and the mechanism might involve its ability to regulate oxidative stress and insulin resistance via the Wnt/β-catenin signalling pathway. [ABSTRACT FROM AUTHOR]