Biochar is increasingly used in crop production as a fertilizer; however, its effects on nutrient cycling and stoichiometry in rice paddy soil–plant systems are unclear. We tested for effects of contrasting rates of biochar on soil and rice plant organ carbon (C), nitrogen (N), and phosphorus (P) concentrations and stoichiometry and soil physicochemical properties in early and late paddies. Overall, biochar reduced soil bulk density by an average of 7.4%, while application at 10, 20, and 40 t ha−1 increased soil C and N concentrations in early paddies by 31.6, 41.3, and 104.2%, respectively, and by 8.0, 5.0, and 21.8%, respectively; in late paddies, there were increases of 23.0, 94.1, and 117.0%, respectively, and 6.7, 15.4, and 18.0%, respectively (P < 0.05). Following biochar application at 10, 20, and 40 t ha−1, soil concentration of P decreased in early paddies by 10.9, 19.0, and 13.9%, respectively, and increased in late paddies by 4.3, 16.4, and 20.1%, respectively. Biochar increased ratios of soil C:N and C:P in early and late paddies (P < 0.05), and there was no effect on concentration and stoichiometry of soil available nutrients. Biochar reduced rice plant organ concentration of N and P in early rice and increased leaf N:P ratios. Despite the biochar application improved nutrient status in plant–soil system, we did not observe a significant increase in yield (P > 0.05). According to the N:P value of leaves between treatments, it was found that biochar alleviated the current situation of N limitation in paddy fields during the mature period and transformed the N limitation of early rice into a joint limitation of N and P. These results show that the addition of biochar to subtropical paddy soils leads to a short-term reduction in soil bulk density and increases in soil C and N concentrations and soil fertility. Thus, biochar applied at optimal rates is likely to improve the sustainability of subtropical paddy rice production.

Weeds contribute to biodiversity and a wide range of ecosystem functions. It is crucial to map different weed species and analyze their physiological activities. Remote sensing techniques for plant identification, especially hyperspectral imaging, are being developed using spectral response patterns to vegetation for detection and species identification. A library of hyperspectral images of 40 urban weed species in northeast China was established in this study. A terrestrial hyperspectral camera was used to acquire 435 hyperspectral images. The hyperspectral information for each weed species was extracted and analyzed. The spectral characteristics and vegetation indices of different weeds revealed the differences between weed species in the cities of northeast China and indirectly characterized the growth and physiological activity levels of different species, but could not effectively distinguish different species. Five methods—first derivative spectrum (FDS), second derivative spectrum (SDS), standard normal variate (SNV), moving averages (MA), and Savitzky-Golay (SG) smoothing—were used to pretreat the spectral curves to maximize the retention of spectral characteristics while removing the influence of noise. We investigated the application of a convolutional neural network (CNN) with terrestrial hyperspectral remote sensing to identify urban weeds in northeast China. A CNN classification model was established to distinguish weeds from the hyperspectral images and demonstrated a test accuracy of 95.32% to 98.15%. The accuracy of the original spectrum was 97.45%; SNV had the best accuracy (98.15%) and SG was the least accurate (95.32%). This provides a baseline for understanding the hyperspectral characteristics of urban weed species and monitoring their growth. It also contributes to the development of a hyperspectral imaging database with global applicability.

Routine blood examination is an easy way to examine infectious diseases. This study is aimed to develop a model to diagnose serious bacterial infections (SBI) in ICU neonates based on routine blood parameters. This was a cross-sectional study, and data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III). SBI was defined as suffering from one of the following: pyelonephritis, bacteraemia, bacterial meningitis, sepsis, pneumonia, cellulitis, and osteomyelitis. Variables with statistical significance in the univariate logistic regression analysis and log systemic immune–inflammatory index (SII) were used to develop the model. The area under the curve (AUC) was calculated to assess the performance of the model. A total of 1,880 participants were finally included for analysis. Weight, haemoglobin, mean corpuscular volume, white blood cell, monocyte, premature delivery, and log SII were selected to develop the model. The developed model showed a good performance to diagnose SBI for ICU neonates, with an AUC of 0.812 (95% confidence interval (CI): 0.737–0.888). A nomogram was developed to make this model visualise. In conclusion, our model based on routine blood parameters performed well in the diagnosis of neonatal SBI, which may be helpful for clinicians to improve treatment recommendations.

Placental trophoblastic cells play important roles in placental development and fetal health. However, the mechanism of trophoblastic cell fusion is still not entirely clear. The level of Tspan5 in the embryo culture medium was detected using enzyme-linked immunosorbent assay (ELISA). Fusion of BeWo cells was observed by immunofluorescence. Cell fusion-related factors and EMT-related factors were identified by qRT-PCR and western blotting. Notch protein repressor DAPT was used to verify the role of Tspan5 in BeWo cells. The expression of Tspan5 was significantly increased in embryo culture medium. The fusion of BeWo cells was observed after treatment with forskolin (FSK). Cell fusion-related factors (i.e. β-hCG and syncytin 1/2) and Tspan5 were significantly increased after FSK treatment. In addition, FSK treatment promoted EMT-related protein expression in BeWo cells. Knockdown of Tspan5 inhibited cell fusion and EMT-related protein levels. Notch-1 and Jagged-1 protein levels were significantly upregulated, and the EMT process was activated by overexpression of Tspan5 in FSK-treated BeWo cells. Interestingly, blocking the Notch pathway by the repressor DAPT had the opposite results. These results indicated that Tspan5 could promote the EMT process by activating the Notch pathway, thereby causing cell fusion. These findings contribute to a better understanding of trophoblast cell syncytialization and embryonic development. Tspan5 may be used as a therapeutic target for normal placental development.

This paper focuses on the design, analysis, and multi-objective optimization of a novel 5-degrees of freedom (DOF) double-driven parallel mechanism. A novel 5-DOF parallel mechanism with two double-driven branch chains is proposed, which can serve as a machine tool. By installing two actuators on one branch chain, the proposed parallel mechanism can achieve 5-DOF of the moving platform with only three branch chains. Afterwards, analytical solution for inverse kinematics is derived. The 5$\times$5 homogeneous Jacobian matrix is obtained by transforming actuator velocities into linear velocities at three points on the moving platform. Meanwhile, the workspace, dexterity, and volume are analyzed based on the kinematic model. Ultimately, a stage-by-stage Pareto optimization method is proposed to solve the multi-objective optimization problem of this parallel mechanism. The optimization results show that the workspace, compactness, and dexterity of this mechanism can be improved efficiently.

In this work, we present a high-power, high-repetition-rate, all-fiber femtosecond laser system operating at 1.5 $\unicode{x3bc}$m. This all-fiber laser system can deliver femtosecond pulses at a fundamental repetition rate of 10.6 GHz with an average output power of 106.4 W – the highest average power reported so far from an all-fiber femtosecond laser at 1.5 $\unicode{x3bc}$m, to the best of our knowledge. By utilizing the soliton-effect-based pulse compression effect with optimized pre-chirping dispersion, the amplified pulses are compressed to 239 fs in an all-fiber configuration. Empowered by such a high-power ultrafast fiber laser system, we further explore the nonlinear interaction among transverse modes LP01, LP11 and LP21 that are expected to potentially exist in fiber laser systems using large-mode-area fibers. The intermodal modulational instability is theoretically investigated and subsequently identified in our experiments. Such a high-power all-fiber ultrafast laser without bulky free-space optics is anticipated to be a promising laser source for applications that specifically require compact and robust operation.

This study aimed to screen factors related to live birth outcomes of women with first frozen embryo transfer (FET). The enrolled women were divided into training and validation cohorts. The least absolute shrinkage and selection operator (Lasso) regression algorithm of machine learning and the multiple regression model were then used to screen factors relevant to live birth failure (LBF) for the training dataset. A nomogram risk prediction model was established on the basis of the screened factors, and the consistency index (C-index) and calibration curve were derived for evaluating the model. The validation cohort was utilized to validate the nomogram model further. In total, 2083 women who accepted the first FET in our hospital were included and 44 factors were initially screened in this study. On the basis of the training cohort, the screened risk factors via multiple regression analysis with odds ratio (OR) values were female age (OR: 3.092, 95%CI: 1.065–4.852), body mass index (BMI; OR: 1.106, 95%CI: 1.015–1.546), caesarean section (OR: 1.909, 95%CI: 1.318–2.814), number of high-quality embryos (OR: 0.698, 95%CI: 0.599–0.812), and endometrial thickness (OR: 0.957, CI: 0.904–0.980). The nomogram model was generated based on five predictors. Furthermore, favourable results with C-indexes and calibration curves close to ideal curves indicated the accurate predictive ability of the nomogram. Female age, BMI, caesarean section, number of high-quality embryos, and endometrial thickness were independent predictors for LBF. The five factors of the risk assessment model may help to identify LBF with high accuracy in women who accept FET.

Germplasm innovation can provide materials for breeding sugarcane cultivars. Saccharum officinarum is the main source of high-sugar and high-yield genes in sugarcane breeding. ‘Nobilization’ is the theoretical basis for exploiting S. officinarum, and S. officinarum authenticity directly affects sugarcane nobility breeding efficiency. Herein, the authenticity of 22 SLC-series S. officinarum clones imported from Sri Lanka and preserved in the China National Germplasm Repository of Sugarcane (NGRS) was explored by four-primer amplification-arrested mutation PCR (ARMS PCR) and somatic chromosome number counting. The amplified bands from SLC 08 120 and SLC 08 131 were the same with those from S. officinarum clone Badila, i.e. a common band of 428 bp and a S. officinarum-specific band of 278 bp, hence they were tentatively assigned as S. officinarum clones. The other 20 SLC clones had both 278 bp (S. officinarum-specific) and 203 bp (S. spontaneum-specific) bands, which are hybrid characteristics. In addition, the chromosome numbers of SLC 08 120 and SLC 08 131 are both 80, belong to typical S. officinarum. While the chromosome numbers of the other 20 materials are ranging from 101 to 129, consistent with hybrids of S. officinarum and S. spontaneum. This molecular cytological characterization indicates that among the 22 introduced SLC-series clones, only two, SLC 08 120 and SLC 08 131, were S. officinarum. Future agronomic trait and resistance analyses could facilitate their use as crossing parents in sugarcane breeding.

The concentration of suspended particulate organic carbon (POC) and its carbon isotopic composition (δ13CPOC) were analysed in this study with the aim of exploring the sources and factors influencing levels of POC in the surface water around the Antarctic Peninsula. The scanning electron microscopy results suggest that diatom particles formed the main component of suspended particulate matter, indicating that POC was mainly from in situ primary production. The high concentrations of chlorophyll a and POC in sea water mainly occurred in nearshore and sea-ice edge regions, which might be controlled by nutrient and reactive iron inputs stemming from sea-ice melting. The δ13CPOC in the study area is significantly lower than that in low-latitude waters, with a range of -31.8‰ to -22.8‰ (mean -28.9‰), which was controlled by the high CO2 concentration in the Southern Ocean and might be influenced by phytoplankton growth rates and assemblages. This study helps us to understand material cycling in the Antarctic region under the conditions of global climate change.

Sleep apnea is one of the most common sleep disorders. The consequences of undiagnosed sleep apnea can be very serious, increasing the risk of high blood pressure, heart disease, stroke, and Alzheimer’s disease over a long period of time. However, many people are often unaware of their condition. The gold standard for diagnosing sleep apnea is nighttime polysomnography monitoring in a specialized sleep laboratory. However, these diagnoses are expensive and the number of beds is limited, and there is insufficient monitoring in terms of time dimension. Existing methods for automated detection use no more than three physiological signals, but all other signals are also associated with the patient’s sleep. In addition, the limited amount of medical real annotation data, especially abnormal samples, lead to weak model generalization capability. The gap between model generalization capability and medical field needs still exists. In this paper, we propose a method for integrating medical interpretation rules into a long short-term memory neural network based on self-attention with multichannel respiratory signals as input. We obtain attention weights through a token-level attention mechanism and then extract key rules of medical interpretation to assist the weights, improving model generalization and reducing the dependence on data volume. Compared with the best prediction performance of existing methods, the average improvements of our method in accuracy, precision, and f1-score are 3.26%, 7.03%, and 1.78%, respectively. The algorithm tested the performance of our model on the Sleep Heart Health Study data set and found that the model outperformed existing methods and could help physicians make decisions in their practices.

The application scopes of two different reductive perturbation methods to derive the Korteweg–de Vries (KdV) equation and coupled KdV (CKdV) equation in two-temperature-ion dusty plasma are given by using the particle-in-cell (PIC) numerical method in the present paper. It suggests that the reductive perturbation method (RPM) is valid if the amplitude of the CKdV solitary wave is small enough. However, for the KdV solitary wave, RPM is valid not only if the amplitude of the KdV solitary wave is small enough, but also if the nonlinear coefficient of the KdV equation is not tending to zero.

Zn is an important trace element involved in various biochemical processes in aquatic species. An 8-week rearing trial was thus conducted to investigate the effects of Zn on juvenile largemouth bass (Micropterus salmoides) by feeding seven diets, respectively, supplemented with no Zn (Con), 60 and 120 mg/kg inorganic Zn (Sul60 and Sul120), and 30, 60, 90 and 120 mg/kg organic Zn (Bio30, Bio60, Bio90 and Bio120). Sul120 and Bio120 groups showed significantly higher weight gain and specific growth rate than Con group, with Bio60 group obtaining the lowest viscerosomatic index and hepatosomatic index. 60 or 90 mg/kg organic Zn significantly facilitated whole body Zn retention. Up-regulation of hepatic superoxide dismutase, glutathione peroxidase and catalase activities and decline of malondialdehyde contents indicated augmented antioxidant capacities by organic Zn. Zn treatment also lowered plasma aminotransferase levels while promoting acid phosphatase activity and hepatic transcription levels of alp1, acp1 and lyz-c than deprivation of Zn. The alterations in whole body and liver crude lipid and plasma TAG contents illustrated the regulatory effect of Zn on lipid metabolism, which could be possibly attributed to the changes in hepatic expressions of acc1, pparγ, atgl and cpt1. These findings demonstrated the capabilities of Zn in potentiating growth and morphological performance, antioxidant capacity, immunity as well as regulating lipid metabolism in M. salmoides. Organic Zn could perform comparable effects at same or lower supplementation levels than inorganic Zn, suggesting its higher efficiency. 60 mg/kg supplementation of organic Zn could effectively cover the requirements of M. salmoides.

According to the public data collected from the Health Commission of Gansu Province, China, regarding the COVID-19 pandemic during the summer epidemic cycle in 2022, the epidemiological analysis showed that the pandemic spread stability and the symptom rate (the number of confirmed cases divided by the sum of the number of asymptomatic cases and the number of confirmed cases) of COVID-19 were different among 3 main epidemic regions, Lanzhou, Linxia, and Gannan; both the symptom rate and the daily instantaneous symptom rate (daily number of confirmed cases divided by the sum of daily number of asymptomatic cases and daily number of confirmed cases) in Lanzhou were substantially higher than those in Linxia and Gannan. The difference in the food sources due to the high difference of the population ethnic composition in the 3 regions was probably the main driver for the difference of the symptom rates among the 3 regions. This work provides potential values for prevention and control of COVID-19 in different regions.