The effects of lead (Pb) and pest damage on soil enzyme activities, pakchoi and Spodoptera litura performance.

Plant-soil interactions have bottom-up and top-down effects within a plant community. Heavy metal pollution can change plant-soil interactions, directly influence bottom-up effects and indirectly affect herbivores within the community. In turn, herbivores can affect plant-soil interactions through top-down effects. However, the combined effects of heavy metals and herbivores on soil enzymes, plants and herbivores have rarely been reported. Therefore, the effects of lead (Pb), Spodoptera litura and their combined effects on soil enzyme activities, pakchoi nutrition, defence compounds and S. litura fitness were examined here. Results showed that Pb, S. litura and their combined effects significantly affected soil enzymes, pakchoi and S. litura. Specifically, exposure to double stress (Pb and S. litura) decreased soil urease, phosphatase and sucrase activities compared with controls. Furthermore, the soluble protein and sugar contents of pakchoi decreased, and the trypsin inhibitor content and antioxidant enzyme activity increased. Finally, the S. litura development period was extended, and survival, emergence rates and body weight decreased after exposure to double stress. The combined stress of Pb and S. litura significantly decreased soil enzyme activities. Heavy metal accumulation in plants may create a superposition or synergistic effect with heavy metal-mediated plant chemical defence, further suppressing herbivore development. Pb, S. litura and their combined effects inhibited soil enzyme activities, improved pakchoi resistance and reduced S. litura development. The results reveal details of soil-plant-herbivore interactions and provide a reference for crop pest control management in the presence of heavy metal pollution.

On explosive boiling of a multicomponent Leidenfrost drop.

The gasification of multicomponent fuel drops is relevant in various energy-related technologies. An interesting phenomenon associated with this process is the self-induced explosion of the drop, producing a multitude of smaller secondary droplets, which promotes overall fuel atomization and, consequently, improves the combustion efficiency and reduces emissions of liquid-fueled engines. Here, we study a unique explosive gasification process of a tricomponent droplet consisting of water, ethanol, and oil ("ouzo"), by high-speed monitoring of the entire gasification event taking place in the well-controlled, levitated Leidenfrost state over a superheated plate. It is observed that the preferential evaporation of the most volatile component, ethanol, triggers nucleation of the oil microdroplets/nanodroplets in the remaining drop, which, consequently, becomes an opaque oil-in-water microemulsion. The tiny oil droplets subsequently coalesce into a large one, which, in turn, wraps around the remnant water. Because of the encapsulating oil layer, the droplet can no longer produce enough vapor for its levitation, and, thus, falls and contacts the superheated surface. The direct thermal contact leads to vapor bubble formation inside the drop and consequently drop explosion in the final stage.

Coreference Resolution Based on High-Dimensional Multi-Scale Information.

Coreference resolution is a key task in Natural Language Processing. It is difficult to evaluate the similarity of long-span texts, which makes text-level encoding somewhat challenging. This paper first compares the impact of commonly used methods to improve the global information collection ability of the model on the BERT encoding performance. Based on this, a multi-scale context information module is designed to improve the applicability of the BERT encoding model under different text spans. In addition, improving linear separability through dimension expansion. Finally, cross-entropy loss is used as the loss function. After adding BERT and span BERT to the module designed in this article, F1 increased by 0.5% and 0.2%, respectively.

Pose ResNet: 3D Human Pose Estimation Based on Self-Supervision.

The accurate estimation of a 3D human pose is of great importance in many fields, such as human-computer interaction, motion recognition and automatic driving. In view of the difficulty of obtaining 3D ground truth labels for a dataset of 3D pose estimation techniques, we take 2D images as the research object in this paper, and propose a self-supervised 3D pose estimation model called Pose ResNet. ResNet50 is used as the basic network for extract features. First, a convolutional block attention module (CBAM) was introduced to refine selection of significant pixels. Then, a waterfall atrous spatial pooling (WASP) module is used to capture multi-scale contextual information from the extracted features to increase the receptive field. Finally, the features are input into a deconvolution network to acquire the volume heat map, which is later processed by a soft argmax function to obtain the coordinates of the joints. In addition to the two learning strategies of transfer learning and synthetic occlusion, a self-supervised training method is also used in this model, in which the 3D labels are constructed by the epipolar geometry transformation to supervise the training of the network. Without the need for 3D ground truths for the dataset, accurate estimation of the 3D human pose can be realized from a single 2D image. The results show that the mean per joint position error (MPJPE) is 74.6 mm without the need for 3D ground truth labels. Compared with other approaches, the proposed method achieves better results.

[Simulation Study on the Influence of Sampling Delay on the Accuracy of Energy Metabolism Measurement].

Indirect energy metabolism measurement is the gold standard for providing nutritional support for critical illness. The accuracy of the measurement data directly affects the outcome of the disease. In order to study the influence of sampling delay on the accuracy of energy metabolism measurement under mechanical ventilation, the Matlab/Simulink platform and respiratory electrical model were used for simulation and quantitative analysis. The results show that the error of indirect energy metabolism measurement increases with the increase of sampling delay, the error of sampling delay in mechanical ventilation mode is larger than that of spontaneous breathing, and the error of sampling delay in PCV mode of mechanical ventilation is larger than that in VCV mode. Therefore, there should be different sampling delay compensation strategies under severe mechanical ventilation and its different control modes.

[Design and Verification of Lung Diffusion Function Detection System].

A lung diffusion function detection system is designed. Firstly, the controllable collection of air, test gas source and calibration gas source was based on single-breath method measurement principle. Secondly, pulmonary diffusing capacity for carbon monoxide (DlCO) was calculated by gas concentration measured by the non-dispersive infrared sensor to measure, the gas flow measured by the differential pressure sensor, and the temperature, humidity and atmospheric pressure sensors to test and evaluate the quantitative detection and evaluation of lung diffusion function. Moreover, a preliminary verification of the lung diffusion function detection system was implemented, and the results showed that the error of the lung carbon monoxide diffusion and the alveolar volume did not exceed 5%. Therefore, the system has high accuracy and is of great value for early screening and accurate assessment of COPD.

Influence of wild, local and cultivated tobacco varieties on the oviposition preference and offspring performance of Spodoptera litura.

The influences of different plants on herbivores have recently attracted research interest; however, little is known regarding the effects of wild, local and cultivated varieties of the same plant from the same origin on herbivores. This study aimed to examine the effects of different tobacco varieties from the same origin on the oviposition preference and offspring performance of Spodoptera litura. We selected two wild ('Bishan wild tobacco' and 'Badan wild tobacco'), two local ('Liangqiao sun-cured tobacco' and 'Shuangguan sun-cured tobacco') and two cultivated ('Xiangyan No. 5' and 'Cunsanpi') tobacco varieties from Hunan Province, China. We found that female S. litura varied in oviposition preferences across the tobacco varieties. They preferred to lay eggs on the cultivated varieties, followed by the local varieties, with the wild varieties being the least preferred. Furthermore, different tobacco varieties significantly influenced the life history parameters of S. litura. Survival rate, pupal weight, emergence rate and adult dry weight decreased in the following order: cultivated varieties > local varieties > wild varieties. Conversely, the pupal stage and development period decreased in the following order: wild varieties > local varieties > cultivated varieties. Therefore, we conclude that wild tobacco varieties have higher resistance to S. litura than cultivated and local varieties, reflecting the evolutionary advantages of wild tobacco varieties.

Caregivers' feeding behaviour, children's eating behaviour and weight status among children of preschool age in China.

BACKGROUND: Childhood overweight and obesity have become significant public health challenges worldwide. The present study aimed to investigate whether caregivers' feeding behaviour and children's eating behaviour were associated with the weight status of preschool children in China. METHODS: A cross-sectional questionnaire was administered to 912 caregivers of preschool children from April to July 2016. Caregivers' feeding behaviours were assessed by the Chinese Preschooler's Caregiver Feeding Behaviour Scale. Children's eating behaviours were evaluated using the Chinese Preschooler's Eating Behaviour Questionnaire. After controlling for demographic characteristics, multiple linear regression and logistic regression analyses were performed to evaluate the relationship between caregivers' feeding behaviour, children's eating behaviour and children's body mass index (BMI). RESULTS: The results showed that weight concerns on the part of caregivers (ß = 0.53) and food responsiveness on the part of children (ß = 0.93) were positively correlated with children's BMI, whereas caregivers' responsibility for feeding (ß = -0.68) and children's external eating (ß = -0.53) were negatively correlated with BMI. Among caregiver feeding behaviours, weight concerns [odds ratio (OR) =4.54, p < 0.001] and behaviour-restricted feeding (OR =0.29, p < 0.001) were positively correlated with children's BMI. A child's food responsiveness (OR =4.04, p < 0.001) was also positively correlated with his/her BMI, whereas the child's satiety responsiveness (OR =0.42, p < 0.001) and emotional eating habits (OR =0.56, p < 0.001) were negatively correlated with overweight/obesity status. CONCLUSIONS: Our study demonstrated that children's eating behaviour and caregivers' feeding behaviour were associated with weight status among preschool children in China. Behaviour interventions on caregivers and their children may prevent or reduce weight problems in preschool children.

Preliminary evaluation of the Chinese version of the Baby Eating Behaviour Questionnaire.

BACKGROUND: This study was conducted to develop a Chinese version of the Baby Eating Behaviour Questionnaire (BEBQ) and to evaluate its reliability and validity. METHODS: The Chinese version of the BEBQ was developed by translation and back-translation of the original BEBQ, followed by revision according to experts on the most appropriate item content. Mothers of 300 infants aged <12 months were recruited for survey participation from the paediatric outpatient departments of two large general hospitals in Xi'an, China. Fifty of the mothers were selected randomly for retesting after 2 weeks. Face-to-face surveys included explanation of the process, administration of the Chinese version of the BEBQ with regard to the exclusive breast-feeding period, and demographic data collection. The reliability, validity and discrimination of the questionnaire were evaluated through correlation coefficient calculation, factor analysis, parallel analysis and other methods. RESULTS: The Chinese version of the BEBQ consists of 15 items in four dimensions (food responsiveness, enjoyment of food, slowness in eating and satiety responsiveness). The cumulative variance contribution rate was 58.4%, the Cronbach's α coefficient was 0.93, the Guttman split-half reliability coefficient was 0.87 and the test-retest reliability coefficient was 0.75. The satiety responsiveness and food responsiveness scores differed significantly according to gestational age at birth, infant sex and average monthly weight gain (all P < 0.05). The enjoyment of food score differed significantly according to average monthly weight gain (P < 0.05). CONCLUSIONS: The Chinese version of the BEBQ showed good reliability and validity and can be used to evaluate infants' appetite through the assessment of eating behaviour.

[Research Progress on Evaluation Method of Parkinson's Disease Bradykinesia Detection Based on Wearable Device].

Parkinson's Disease (PD) is a neurodegenerative disease that occurs in the middle-aged and elderly population and has dyskinesia as the main clinical symptom. Bradykinesia is a typical dyskinesia symptom of Parkinson's disease. The evaluation of bradykinesia based on wearable devices is an important support for individualized diagnosis and telemedicine. This paper focuses on the bradykinesia, expound the existing detection and evaluation techniques for wearable devices and data analysis methods. This paper also analyzes and discusses some current problems in the field and future research directions.

[Freezing of Gait Detection System for Parkinson's Patients Based on Inertial Measurement Unit].

In order to detect freezing of gait of Parkinson's patients automatically, a system based on inertial measurement unit to detect freezing of gait for Parkinson's patients is established. The two inertial measurement units are respectively fixed on the left and right ankles of the patient to be measured, the freezing index is calculated by windowed Fourier transform, the freezing threshold is calculated based on the freezing index during normal walking, and the freezing index and the freezing threshold are compared to complete the detection of freezing of gait. The experimental results show that the number of freezing of gait occurrences in Parkinson's patients is accurately detected, and it has high sensitivity and specificity, which can assist doctors to objectively assess the patient's condition.

A new and important relationship between miRNA-147a and PDPK1 in radiotherapy.

It was found that the expression level of miR-147a was significantly increased and the pathway of PI3K/AKT was dramatically inhibited after radiation. In view of the relationship between miRNA and target genes, we put forward the question, what is the relationship between PI3K/AKT and miR-147a? In order to find the answer to the question, we used bioinformatics techniques to analyze the relationship between miR-147 (a or b) and PI3K/AKT signaling pathway. miR-147a overexpression plasmid and PDPK1 3'UTR luciferase reporter gene plasmid were constructed. Dual luciferase reporter gene system validation experiments were carried out on miR-147a and PDPK1 relationship. The verification experiments were also carried out. Bioinformatics analysis showed that there is a miR-147a binding site in the non-coding region (3'UTR) of PDPK1. In the experimental groups transfected with wild type PDPK1 gene of 3'UTR plasmid, the luciferase activity decreased (or increased) significantly in miR-147a (or inhibitor) group compared with miR-NC (or anti-miR-NC); There was no significant difference between the miR-147a group (or inhibitor) and the miR-NC group (or anti-miR-NC) in the transfection of PDPK1-3'UTR-Mut gene vector. PDPK1 was a target gene for direct regulation of miR-147a downstream. Verifying test results showed that the expression of PDPK1 mRNA and protein was reduced after overexpression of miR-147a, which was up-regulated after silencing miR-147a in TC, and V79 cells. These results suggest that miR-147a could be involved in the regulation of PDPK1 transcription by binding to the target site in PDPK1 mRNA 3'UTR, and then regulated AKT.

Flavonoids of Rosa roxburghii Tratt offers protection against radiation induced apoptosis and inflammation in mouse thymus.

The present study evaluated the protective effect of the natural compound flavonoids of Rosa roxburghii Tratt (FRT) against γ-radiation-induced apoptosis and inflammation in mouse thymus cells in vivo and in vitro. Thymus cells and mice were exposed to 60Co γ-ray at a dose of 6 Gy. The radiation treatment induced significant cell apoptosis and inflammation. Radiation increased the expressions of cleaved caspase 3/8-10, AIF, and PARP-1, and FRT could mitigate their activation and inhibit subsequent apoptosis in the thymus both in vitro or in vivo. Irradiation increased the mRNA expression of ICAM-1/VCAM-1, IL-1α/IL-6 and TNF-α/NF-κB. Our results also indicated that FRT alleviated gene expression of some inflammatory factors such as ICAM-1/VCAM-1, TNF-α/NF-κB, but not IL-1α/IL-6. Irradiation increased the protein expression levels of ICAM-1/VCAM-1, IL-1α/IL-6 and TNF-α/NF-Κb, and our results also indicated that FRT alleviated protein level expression of certain inflammatory factors such as ICAM-1, IL-1α/IL-6, TNF-α/NF-κB, but not VCAM-1. Our results suggested that FRT enhanced radioprotection at least partially by regulating caspase 3/8-10, AIF, and PARP-1 to reduce apoptosis and by regulating ICAM-1, IL-1α/IL-6, TNF-α/NF-κB to reduce inflammation.

The use of a logistic regression model to develop a risk assessment of intraoperatively acquired pressure ulcer.

AIMS AND OBJECTIVES: To screen the factors of intraoperatively acquired pressure ulcer and establish a new risk assessment model of intraoperatively acquired pressure ulcer. DESIGN: This is a prospective study. METHODS: A total of 1,963 patients who received neurosurgery, orthopaedics, paediatric surgery and cardiac surgery therapy in Sichuan Academy of Medical Science and Provincial People's Hospital in China from October 2015-October 2016 were enrolled in the study, and their clinical parameters were collected. Multivariable logistic regression analysis and decision tree analysis were used to analyse and screen the factors of intraoperatively acquired pressure ulcer and establish the risk assessment model of intraoperatively acquired pressure ulcer. RESULTS: The risk factors for intraoperatively acquired pressure ulcer included the application of external force during operation (ß = 1.10, OR = 3.20), lean body mass (ß = 1.08, OR = 2.95), time of operation ≥6 hr (ß = 2.66, OR = 14.30), prone position operation (ß = 1.13, OR = 3.10), cardiopulmonary bypass during operation (ß = 1.72, OR = 5.59) and intraoperative blood loss (ß = 0.67, OR = 1.95). The new risk assessment model showed that the AUC of ROC curve was 0.897 (p < .001). According to the maximum principle of Youden's index, the sensitivity, specificity and Youden's index J of the model were 0.81, 0.88 and 0.69, respectively, when the cut-off point was set at π = 0.025. CONCLUSIONS: A new and relatively reliable assessment model for intraoperatively acquired pressure ulcer is established. RELEVANCE TO CLINICAL PRACTICE: Pressure ulcers remain a challenge in clinical nursing. A new risk assessment model of pressure ulcers that is applicable to surgical patients is highly recommended.

[Application of Static Characteristics of Plantar Pressure Distribution in the Assessment of Knee Joint Injury].

OBJECTIVE: This paper used plantar pressure analysis equipment to discuss the plantar pressure distribution pattern and balance ability of patients with the knee joint injury under static standing. METHODS: Zebris FDM-S plantar pressure analysis equipment was used to collect plantar pressure data from subjects with the knee joint injury and healthy control subjects. We compared the pressure values in each region of pelma, and then assessing the balance ability of the subjects based on the trajectory of the overall pressure center movement. RESULTS: Compared with the healthy control group, patients with knee joint injury have a significantly lower pressure in the heel areas and a significantly higher pressure in the middle foot area. And the total pressure of the injured limb foot in the patient group is lower than that in the contralateral foot. In addition, there is a significant increase in the parameters of the balance ability index in the patient group. CONCLUSIONS: The plantar pressure distribution pattern of patients with knee joint injury is different from that of normal people in static standing, and the balance ability is poor. Therefore, this method has a positive guiding significance in the evaluation and application of knee joint injury.

[Walking Ability Assessment System for Parkinson's Patients Based on Inertial Sensor].

In order to evaluate the ability of Parkinson's patients to walk comprehensively, a system based on MEMS to aid clinical quantification of ability in Parkinson's is established. The inertial units are respectively fixed on the back and the waist of subject to be measured. The Kalman fusion algorithm is used to extract the characteristic parameters of accelerometer and gyroscope data. SVM classifier is designed to train and test the classifier by the feature. The results show that the system possesses a high recognition rate for Parkinson's patients and normal subjects and for the classification of the walking ability of patients with Parkinson's disease. So, this system can aid doctors to give more object diagnostic conclusion.

[Digital System for the Geriatric Somatic Function Assessment].

At present, the somatic function assessment of the elderly mostly depends on the doctor's observation and the scale evaluation, and there isn't the objective and quantitative assessment criteria. In this paper, we design and construct a digital system for the geriatric somatic function assessment, which is based on digital ground, inertial unit, mobile terminal and PC terminal. The gait and balance parameters of the elderly were obtained by the Time Up and Go test and five postures test. Based on the linear regression model of gait and balance parameters, the system was used to evaluate the somatic function of the elderly. The experimental results show that the system not only can accurately distinguish elderly between fall and non-fall, but also has a high correlation between the score of the system and the score of clinical geriatric physical function scale.

[Quantitative Evaluation of Regularity of Finger Tapping Movement for Patients with Parkinson's disease].

Finger tapping test is a common testing item for patients with Parkinson's disease(PD)in clinical neurology.It mainly evaluates the fine motor function of patient's hand in three aspects:amplitude,speed and regularity of the movement.This paper focused on the quantitative assessment of regularity of finger tapping movement for PD patients.The movement signals of thumb and index finger were recorded by using inertial sensor unit in the process of tapping test.Two nonlinear dynamic indexes,approximate entropy(ApEn)and sample entropy(SampEn),were calculated,and then the values were statistically analyzed.The experimental results indicated that both indexes had significant differences between patient group and control group.Moreover,the indexes had relatively high correlation with the scores of corresponding unified Parkinson's disease rating scale(UPDRS)item rated by clinical clinician,which illustrated that these two indexes could reflect the injury level of the repetitive finger movement.So,as a reliable method,it can be provided to the clinical evaluation of hand movement function for PD patients.

[Development of Isokinetic Muscle Tone Testing System].

A new type of isokinetic muscle tone testing system was designed for the Parkinson's patients with dysmyotonia. The system consists of a mechanical device, a data acquisition unit, and a data processing and analyzing software. The mechanical device comprises an arm supporting device, a safety limiting device and a height adjusting device. Data acquisition unit, composed of a torque sensor module, a motor control module, a data communication module, and so on, is used to control the arm at constant speed and convert the sensor's analog signal into digital signal, then the signal is transmitted to the computer in real-time by USB interface. The data processing and analyzing software, developed by VC++, has finished the data processing, display, storage, generated the reports, et al. The experimental results show that this system is reliable and safe, not only can evaluate the degree of abnormal muscle tone in Parkinson's patients, but also can be used in the rehabilitation training of patients with dysmyotonia, which has strong expansibility.

A brain structure learning-guided multi-view graph representation learning for brain network analysis.

Background: Resting-state brain networks represent the interconnectivity of different brain regions during rest. Utilizing brain network analysis methods to model these networks can enhance our understanding of how different brain regions collaborate and communicate without explicit external stimuli. However, analyzing resting-state brain networks faces challenges due to high heterogeneity and noise correlation between subjects. This study proposes a brain structure learning-guided multi-view graph representation learning method to address the limitations of current brain network analysis and improve the diagnostic accuracy (ACC) of mental disorders. Methods: We first used multiple thresholds to generate different sparse levels of brain networks. Subsequently, we introduced graph pooling to optimize the brain network representation by reducing noise edges and data inconsistency, thereby providing more reliable input for subsequent graph convolutional networks (GCNs). Following this, we designed a multi-view GCN to comprehensively capture the complexity and variability of brain structure. Finally, we employed an attention-based adaptive module to adjust the contributions of different views, facilitating their fusion. Considering that the Smith atlas offers superior characterization of resting-state brain networks, we utilized the Smith atlas to construct the graph network. Results: Experiments on two mental disorder datasets, the Autism Brain Imaging Data Exchange (ABIDE) dataset and the Mexican Cocaine Use Disorders (SUDMEX CONN) dataset, show that our model outperforms the state-of-the-art methods, achieving nearly 75% ACC and 70% area under the receiver operating characteristic curve (AUC) on both datasets. Conclusions: These findings demonstrate that our method of combining multi-view graph learning and brain structure learning can effectively capture crucial structural information in brain networks while facilitating the acquisition of feature information from diverse perspectives, thereby improving the performance of brain network analysis.