Deep learning of Parkinson's movement from video, without human-defined measures.

BACKGROUND: The core clinical sign of Parkinson's disease (PD) is bradykinesia, for which a standard test is finger tapping: the clinician observes a person repetitively tap finger and thumb together. That requires an expert eye, a scarce resource, and even experts show variability and inaccuracy. Existing applications of technology to finger tapping reduce the tapping signal to one-dimensional measures, with researcher-defined features derived from those measures. OBJECTIVES: (1) To apply a deep learning neural network directly to video of finger tapping, without human-defined measures/features, and determine classification accuracy for idiopathic PD versus controls. (2) To visualise the features learned by the model. METHODS: 152 smartphone videos of 10s finger tapping were collected from 40 people with PD and 37 controls. We down-sampled pixel dimensions and videos were split into 1 s clips. A 3D convolutional neural network was trained on these clips. RESULTS: For discriminating PD from controls, our model showed training accuracy 0.91, and test accuracy 0.69, with test precision 0.73, test recall 0.76 and test AUROC 0.76. We also report class activation maps for the five most predictive features. These show the spatial and temporal sections of video upon which the network focuses attention to make a prediction, including an apparent dropping thumb movement distinct for the PD group. CONCLUSIONS: A deep learning neural network can be applied directly to standard video of finger tapping, to distinguish PD from controls, without a requirement to extract a one-dimensional signal from the video, or pre-define tapping features.

The association of cognitive function and its changes with all-cause mortality among community-dwelling older adults.

Background: The association of cognitive function, its changes, and all-cause mortality has not reached a consensus, and the independence of the association between changes in cognitive function and mortality remains unclear. The purpose of this study was to evaluate the longitudinal association between baseline cognitive function and cognitive changes over 1 year with subsequent all-cause mortality among the older adults aged 60 and above. Methods: A prospective cohort study utilizing the Community Older Adults Health Survey data. Initiated in 2018, the study annually assessed all individuals aged 60+ in Dalang Town, Dongguan City. Cognitive function was assessed using the Chinese version of the Mini-Mental State Examination (MMSE). A total of 6,042 older adults individuals were included, and multivariate Cox proportional hazard models were used to examine cognitive function's impact on mortality. Results: Participants' median age was 70 years, with 39% men. Over a median 3.08-year follow-up, 525 died. Mortality risk increased by 6% per MMSE score decrease (adjusted HR = 1.06, 95%CI: 1.05-1.08). Compared to those with normal cognitive function at baseline, participants with mild cognitive impairment and moderate to severe cognitive impairment had significantly higher mortality risks (adjusted HR = 1.40, 95%CI: 1.07-1.82; HR = 2.49, 95%CI: 1.91-3.24, respectively). The risk of death was 5% higher for each one-point per year decrease in cognitive function change rate (HR = 1.05, 95%CI: 1.02-1.08). Compared with participants with stable cognitive function, those with rapid cognitive decline had a 79% increased risk of death (adjusted HR = 1.79, 95% CI: 1.11-2.87), with baseline cognitive function influencing this relationship significantly (P for interaction = 0.002). Conclusion: Baseline cognitive impairment and rapid cognitive decline are associated with higher all-cause mortality risks in Chinese older adults. Baseline function influences the mortality impact of cognitive changes.

Exploring road safety using alignment perspective features in real driving images: A case study on mountain freeways.

INTRODUCTION: While driving, drivers frequently adapt their driving behaviors according to their perception of the road's alignment features. However, traditional two-dimensional alignment methods lack the ability to capture these features from the driver's perspective. METHOD: This study introduces a novel method for road alignment recognition, employing image recognition technology to extract alignment perspective features, namely alignment perspective skewness (APS) and alignment perspective kurtosis (APK), from in-real driving images. Subsequently, the K-means clustering algorithm is utilized for road segment classification based on APS and APK indicators. Various sliding step length for clustering are employed, with step length ranging from 100m to 400m. Furthermore, the accident rates for different segment clusters are analyzed to explore the relationship between alignment perspective features and traffic safety. A 150 km mountain road section of the Erlianhaote-Guangzhou freewway from Huaiji to Sihui is selected as a case study. RESULTS: The results demonstrate that using alignment perspective features as classification criteria produces favorable clustering outcomes, with superior clustering performance achieved using shorter segment lengths and fewer cluster centers. The road segment classification based on alignment perspective features reveals notable differences in accident rates across categories; while traditional two-dimensional parameters-based classification methods fail to capture these differences. The most significant differences in accident rates across categories are observed with segment length of 100m, with the significance gradually diminishing as segment length increases and disappearing entirely when the length exceeds 300m. IMPLICATION: These findings validate the reliability of using alignment perspective features (APS and APK) for road alignment classification and road safety analysis, providing valuable insights for road safety management.

AP-1 and SP1 trans-activate the expression of hepatic CYP1A1 and CYP2A6 in the bioactivation of AFB1 in chicken.

Dietary exposure to aflatoxin B1 (AFB1) is harmful to the health and performance of domestic animals. The hepatic cytochrome P450s (CYPs), CYP1A1 and CYP2A6, are the primary enzymes responsible for the bioactivation of AFB1 to the highly toxic exo-AFB1-8,9-epoxide (AFBO) in chicks. However, the transcriptional regulation mechanism of these CYP genes in the liver of chicks in AFB1 metabolism remains unknown. Dual-luciferase reporter assay, bioinformatics and site-directed mutation results indicated that specificity protein 1 (SP1) and activator protein-1 (AP-1) motifs were located in the core region -1,063/-948, -606/-541 of the CYP1A1 promoter as well as -636/-595, -503/-462, -147/-1 of the CYP2A6 promoter. Furthermore, overexpression and decoy oligodeoxynucleotide technologies demonstrated that SP1 and AP-1 were pivotal transcriptional activators regulating the promoter activity of CYP1A1 and CYP2A6. Moreover, bioactivation of AFB1 to AFBO could be increased by upregulation of CYP1A1 and CYP2A6 expression, which was trans-activated owing to the upregulalion of AP-1, rather than SP1, stimulated by AFB1-induced reactive oxygen species. Additionally, nano-selenium could reduce ROS, downregulate AP-1 expression and then decrease the expression of CYP1A1 and CYP2A6, thus alleviating the toxicity of AFB1. In conclusion, AP-1 and SP1 played important roles in the transactivation of CYP1A1 and CYP2A6 expression and further bioactivated AFB1 to AFBO in chicken liver, which could provide novel targets for the remediation of aflatoxicosis in chicks.

Copper-Catalyzed [4+1+1] Annulation of Ammonium Salts and Anthranils: Synthesis of 2,3-Diaroylquinolines.

A copper(I)-catalyzed protocol is developed for the synthesis of various 2,3-diaroylquinolines starting from achiral ammonium salts and anthranils through [4+1+1] annulation. Using copper(I) chloride as the sole catalyst, this reaction is featured with easily available starting materials, broad substrate scope, good yields and simple reaction conditions.

Causal relationship between circulating insulin-like growth factor-1 and Parkinson's disease: a two-sample Mendelian randomization study.

Background: Linear associations between circulating insulin-like growth factor-1 (IGF-1) levels and Parkinson's disease (PD) have been evidenced in observational studies. Yet, the causal relationship between IGF-1 levels and PD remains obscure. We conducted Mendelian randomization to examine the correlation between genetically predicted IGF-1 levels and PD. Methods: By reviewing genome-wide association studies (GWAS) that are publicly accessible, we uncovered SNPs linked to both serum concentrations of IGF-1 and PD. A two-sample Mendelian randomization (MR) analysis was carried out to evaluate the individual effect of IGF-1 on PD. Results: In a primary causal effects model in MR analysis, employing the inverse-variance weighted (IVW) method, IGF-1 levels exhibited a notable association with the risk of PD (OR, 1.020, 95% CI, 1.003-1.038, p = 0.0215). Multiple evaluations revealed that horizontal pleiotropy was improbable to distort the main results (MR-Egger: P PD intercept =0.719), and no bias was detected by leave-one-out analysis. Conclusion: This study unearthed evidence indicating that heightened IGF-1 levels might be causally correlated with an increased risk of PD.

Surface hardness determination of laser cladding using laser-induced breakdown spectroscopy and machine learning (PLSR, CNN, ResNet, and DRSN).

In this study, we employed laser-induced breakdown spectroscopy (LIBS) along with machine learning algorithms, which encompass partial least squares regression (PLSR), the deep convolutional neural network (CNN), the deep residual neural network (ResNet), and the deep residual shrinkage neural network (DRSN), to estimate the surface hardness of laser cladding layers. (The layers were produced using Fe316L, FeCrNiCu, Ni25, FeCrNiB, and Fe313 powders, with 45 steel and Q235 serving as substrates.) The research findings indicate that both linear and nonlinear models can effectively fit the relationship between LIBS spectra and surface hardness. Particularly, the model derived from the ResNet exhibits superior performance with an R 2 value as high as 0.9967. We hypothesize that the inclusion of numerous noises in the LIBS spectra contributes to the enhanced predictive capability for surface hardness, thereby leading to the superior performance of the ResNet compared to the DRSN.

Protein Corona-Mediated Inhibition of Nanozyme Activity: Impact of Protein Shape.

During biomedical applications, nanozymes, exhibiting enzyme-like characteristics, inevitably come into contact with biological fluids in living systems, leading to the formation of a protein corona on their surface. Although it is acknowledged that molecular adsorption can influence the catalytic activity of nanozymes, there is a dearth of understanding regarding the impact of the protein corona on nanozyme activity and its determinant factors. In order to address this gap, we employed the AuNR@Pt@PDDAC [PDDAC, poly(diallyldimethylammonium chloride)] nanorod (NR) as a model nanozyme with multiple activities, including peroxidase, oxidase, and catalase-mimetic activities, to investigate the inhibitory effects of the protein corona on the catalytic activity. After the identification of major components in the plasma protein corona on the NR, we observed that spherical proteins and fibrous proteins induced distinct inhibitory effects on the catalytic activity of nanozymes. To elucidate the underlying mechanism, we uncovered that the adsorbed proteins assembled on the surface of the nanozymes, forming protein networks (PNs). Notably, the PNs derived from fibrous proteins exhibited a screen mesh-like structure with smaller pore sizes compared to those formed by spherical proteins. This structural disparity resulted in a reduced efficiency for the permeation of substrate molecules, leading to a more robust inhibition in activity. These findings underscore the significance of the protein shape as a crucial factor influencing nanozyme activity. This revelation provides valuable insights for the rational design and application of nanozymes in the biomedical fields.

A novel spatiotemporal graph convolutional network framework for functional connectivity biomarkers identification of Alzheimer's disease.

BACKGROUND: Functional connectivity (FC) biomarkers play a crucial role in the early diagnosis and mechanistic study of Alzheimer's disease (AD). However, the identification of effective FC biomarkers remains challenging. In this study, we introduce a novel approach, the spatiotemporal graph convolutional network (ST-GCN) combined with the gradient-based class activation mapping (Grad-CAM) model (STGC-GCAM), to effectively identify FC biomarkers for AD. METHODS: This multi-center cross-racial retrospective study involved 2,272 participants, including 1,105 cognitively normal (CN) subjects, 790 mild cognitive impairment (MCI) individuals, and 377 AD patients. All participants underwent functional magnetic resonance imaging (fMRI) and T1-weighted MRI scans. In this study, firstly, we optimized the STGC-GCAM model to enhance classification accuracy. Secondly, we identified novel AD-associated biomarkers using the optimized model. Thirdly, we validated the imaging biomarkers using Kaplan-Meier analysis. Lastly, we performed correlation analysis and causal mediation analysis to confirm the physiological significance of the identified biomarkers. RESULTS: The STGC-GCAM model demonstrated great classification performance (The average area under the curve (AUC) values for different categories were: CN vs MCI = 0.98, CN vs AD = 0.95, MCI vs AD = 0.96, stable MCI vs progressive MCI = 0.79). Notably, the model identified specific brain regions, including the sensorimotor network (SMN), visual network (VN), and default mode network (DMN), as key differentiators between patients and CN individuals. These brain regions exhibited significant associations with the severity of cognitive impairment (p < 0.05). Moreover, the topological features of important brain regions demonstrated excellent predictive capability for the conversion from MCI to AD (Hazard ratio = 3.885, p < 0.001). Additionally, our findings revealed that the topological features of these brain regions mediated the impact of amyloid beta (Aß) deposition (bootstrapped average causal mediation effect: ß = -0.01 [-0.025, 0.00], p < 0.001) and brain glucose metabolism (bootstrapped average causal mediation effect: ß = -0.02 [-0.04, -0.001], p < 0.001) on cognitive status. CONCLUSIONS: This study presents the STGC-GCAM framework, which identifies FC biomarkers using a large multi-site fMRI dataset.

Low-Temperature and Fast-Charge Sodium Metal Batteries.

Low-temperature operation of sodium metal batteries (SMBs) at the high rate faces challenges of unstable solid electrolyte interphase (SEI), Na dendrite growth, and sluggish Na+ transfer kinetics, causing a largely capacity curtailment. Herein, low-temperature and fast-charge SMBs are successfully constructed by synergetic design of the electrolyte and electrode. The optimized weak-solvation dual-salt electrolyte enables high Na plating/stripping reversibility and the formation of NaF-rich SEI layer to stabilize sodium metal. Moreover, an integrated copper sulfide electrode is in situ fabricated by directly chemical sulfuration of copper current collector with micro-sized sulfur particles, which significantly improves the electronic conductivity and Na+ diffusion, knocking down the kinetic barriers. Consequently, this SMB achieves the reversible capacity of 202.8 mAh g-1 at -20 °C and 1 C (1 C = 558 mA g-1 ). Even at -40 °C, a high capacity of 230.0 mAh g-1 can still be delivered at 0.2 C. This study is encouraging for further exploration of cryogenic alkali metal batteries, and enriches the electrode material for low-temperature energy storage.

Evaluation and Application of Frailty Index in Colorectal Cancer: A Comprehensive Review.

Colorectal cancer (CRC) is a common malignant tumor that primarily affects the elderly population. Surgery is one of the main treatment modalities for CRC. Frailty is a prevalent characteristic among the elderly and a leading cause of mortality. The frailty index (FI) is a comprehensive tool for assessing patients' frailty status, quantifying indicators such as weight loss, fatigue, and nutritional status, to reflect the degree of frailty. In recent years, the FI has undergone modifications to more accurately evaluate the risk of surgical complications and prognosis in CRC patients. This review summarizes the methods for frailty assessment, the development and modifications of the FI, and compiles the research findings and applications of the FI in predicting surgical complications, postoperative recovery, and survival rates in CRC patients. Furthermore, limitations in the current modified frailty index (mFI) and future research directions are discussed. This review provides essential references for further understanding the role of frailty in CRC patients and the clinical application of the mFI.

Optimum Doses and Forms of Selenium Maintaining Reproductive Health via Regulating Homeostasis of Gut Microbiota and Testicular Redox, Inflammation, Cell Proliferation, and Apoptosis in Roosters.

BACKGROUND: There is a U-shaped relationship between dietary selenium (Se) ingestion and optimal sperm quality. OBJECTIVES: This study aimed to investigate the optimal dietary dose and forms of Se for sperm quality of breeder roosters and the relevant mechanisms. METHODS: In experiment 1, 18-wk-old Jingbai laying breeder roosters were fed a Se-deficient base diet (BD, 0.06 mg Se/kg), or the BD + 0.1, 0.2, 0.3, 0.4, 0.5, or 1.0 mg Se/kg for 9 wk. In experiment 2, the roosters were fed the BD or the BD + sodium selenite (SeNa), seleno-yeast (SeY), or Se-nanoparticles (SeNPs) at 0.2 mg Se/kg for 9 wk. RESULTS: In experiment 1, added dietary 0.2 and 0.3 mg Se/kg led to higher sperm motility and lower sperm mortality than the other groups at weeks 5, 7, and/or 9. Furthermore, added dietary 0.2-0.4 mg Se/kg produced better testicular histology and/or lower testicular 8-hydroxy-deoxyguanosine than the other groups. Moreover, integrated testicular transcriptomic and cecal microbiomic analysis revealed that inflammation, cell proliferation, and apoptosis-related genes and bacteria were dysregulated by Se deficiency or excess. In experiment 2, compared with SeNa, SeNPs slightly increased sperm motility throughout the experiment, whereas SeNPs slightly reduced sperm mortality compared with SeY at week 9. Both SeY and SeNPs decreased malondialdehyde in the serum than those of SeNa, and SeNPs led to higher glutathione peroxidase (GPX) and thioredoxin reductase activities and GPX1 and B-cell lymphoma 2 protein concentrations in the testis compared with SeY and SeNa. CONCLUSIONS: The optimal dietary Se dose for reproductive health of breeder roosters is 0.25-0.35 mg Se/kg, and SeNPs displayed better effects on reproductive health than SeNa and SeY in laying breeder roosters. The optimal doses and forms of Se maintain reproductive health of roosters associated with regulation intestinal microbiota homeostasis and/or testicular redox balance, inflammation, cell proliferation, and apoptosis.

Isolation of a novel multiple-heavy metal resistant Lampropedia aestuarii GYF-1 and investigation of its bioremediation potential.

BACKGROUND: Heavy metal contamination has been a severe worldwide environmental issue. For industrial pollutions, heavy metals rarely exist as singular entities. Hence, researches have increasingly focused on the detrimental effect of mixed heavy metal pollution. Genome analysis of Lampropedia strains predicted a repertoire of heavy metal resistance genes. However, we are still lack of experimental evidence regarding to heavy metal resistance of Lampropedia, and their potential in mixed heavy metal removal remain elusive. RESULTS: In this study, a Lampropedia aestuarii strain GYF-1 was isolated from soil samples near steel factory. Heavy metal tolerance assay indicated L. aestuarii GYF-1 possessed minimal inhibition values of 2 mM, 10 mM, 6 mM, 4 mM, 6 mM, 0.8 mM, and 4 mM for CdCl2, K2CrO4, CuCl2, NiCl2, Pb(CH3COO)2, ZnSO4, and FeCl2, respectively. The biosorption assay demonstrated its potential in soil remediation from mixed heavy metal pollution. Next the draft genome of L. aestuarii GYF-1 was obtained and annotated, which revealed strain GYF-1 are abundant in heavy metal resistance genes. Further evaluations on differential gene expressions suggested adaptive mechanisms including increased lipopolysaccharides level and enhanced biofilm formation. CONCLUSION: In this study, we demonstrated a newly isolated L. aestuarii GYF-1 exhibited mixed heavy metal resistance, which proven its capability of being a potential candidate strain for industrial biosorption application. Further genome analysis and differential gene expression assay suggest enhanced LPS and biofilm formation contributed to the adaptation of mixed heavy metals.

Heat Stress Impairs Male Reproductive System with Potential Disruption of Retinol Metabolism and Microbial Balance in the Testis of Mice.

BACKGROUND: Heat stress (HS) has a harmful impact on the male reproductive system, primarily by reducing the sperm quality. The testicular microenvironment plays an important role in sperm quality. OBJECTIVES: This study aimed to explore the underlying mechanism by which HS impairs the male reproductive system through the testicular microenvironment. METHODS: Ten-week-old male mice (n = 8 mice/group) were maintained at a normal temperature (25°C, control) or subjected to HS (38°C for 2 h each day, HS) for 2 wk. The epididymides and testes were collected at week 2 to determine sperm quality, histopathology, retinol concentration, the expression of retinol metabolism-related genes, and the testicular microbiome. The testicular microbiome profiles were analyzed using biostatistics and bioinformatics; other data were analyzed using a 2-sided Student's t test. RESULTS: Compared with the control, HS reduced (P < 0.05) sperm count (42.4%) and motility (97.7%) and disrupted the integrity of the blood-testis barrier. Testicular microbial profiling analysis revealed that HS increased the abundance of the genera Asticcacaulis, Enhydrobacter, and Stenotrophomonas (P < 0.05) and decreased the abundance of the genera Enterococcus and Pleomorphomonas (P < 0.05). Notably, the abundance of Asticcacaulis spp. showed a significant negative correlation with sperm count (P < 0.001) and sperm motility (P < 0.001). Moreover, Asticcacaulis spp. correlated significantly with most blood differential metabolites, particularly retinol (P < 0.05). Compared with the control, HS increased serum retinol concentrations (25.3%) but decreased the testis retinol concentration by 23.7%. Meanwhile, HS downregulated (P < 0.05) the expression of 2 genes (STRA6 and RDH10) and a protein (RDH10) involved in retinol metabolism by 27.3%-36.6% in the testis compared with the control. CONCLUSIONS: HS reduced sperm quality, mainly because of an imbalance in the testicular microenvironment potentially caused by an increase in Asticcacaulis spp. and disturbed retinol metabolism. These findings may offer new strategies for improving male reproductive capacity under HS.

The Combination of a Graph Neural Network Technique and Brain Imaging to Diagnose Neurological Disorders: A Review and Outlook.

Neurological disorders (NDs), such as Alzheimer's disease, have been a threat to human health all over the world. It is of great importance to diagnose ND through combining artificial intelligence technology and brain imaging. A graph neural network (GNN) can model and analyze the brain, imaging from morphology, anatomical structure, function features, and other aspects, thus becoming one of the best deep learning models in the diagnosis of ND. Some researchers have investigated the application of GNN in the medical field, but the scope is broad, and its application to NDs is less frequent and not detailed enough. This review focuses on the research progress of GNNs in the diagnosis of ND. Firstly, we systematically investigated the GNN framework of ND, including graph construction, graph convolution, graph pooling, and graph prediction. Secondly, we investigated common NDs using the GNN diagnostic model in terms of data modality, number of subjects, and diagnostic accuracy. Thirdly, we discussed some research challenges and future research directions. The results of this review may be a valuable contribution to the ongoing intersection of artificial intelligence technology and brain imaging.

Entropy by Neighbor Distance as a New Measure for Characterizing Spatiotemporal Orders in Microscopic Collective Systems.

Collective systems self-organize to form globally ordered spatiotemporal patterns. Finding appropriate measures to characterize the order in these patterns will contribute to our understanding of the principles of self-organization in all collective systems. Here we examine a new measure based on the entropy of the neighbor distance distributions in the characterization of collective patterns. We study three types of systems: a simulated self-propelled boid system, two active colloidal systems, and one centimeter-scale robotic swarm system. In all these systems, the new measure proves sensitive in revealing active phase transitions and in distinguishing steady states. We envision that the entropy by neighbor distance could be useful for characterizing biological swarms such as bird flocks and for designing robotic swarms.

Translocation of gut microbes to epididymal white adipose tissue drives lipid metabolism disorder under heat stress.

Heat stress induces multi-organ damage and serious physiological dysfunction in mammals, and gut bacteria may translocate to extra-intestinal tissues under heat stress pathology. However, whether gut bacteria translocate to the key metabolic organs and impair function as a result of heat stress remains unknown. Using a heat stress-induced mouse model, heat stress inhibited epididymal white adipose tissue (eWAT) expansion and induced lipid metabolic disorder but did not damage other organs, such as the heart, liver, spleen, or muscle. Microbial profiling analysis revealed that heat stress shifted the bacterial community in the cecum and eWAT but not in the inguinal white adipose tissue, blood, heart, liver, spleen, or muscle. Notably, gut-vascular barrier function was impaired, and the levels of some bacteria, particularly Lactobacillus, were higher in the eWAT, as confirmed by catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) staining when mice were under heat stress. Moreover, integrated multi-omics analysis showed that the eWAT microbiota was associated with host lipid metabolism, and the expression of genes involved in the lipid metabolism in eWAT was upregulated under heat stress. A follow-up microbial supplementation study after introducing Lactobacillus plantarum to heat-stressed mice revealed that the probiotic ameliorated heat stress-induced loss of eWAT and dyslipidemia and reduced gut bacterial translocation to the eWAT by improving gut barrier function. Overall, our findings suggest that gut bacteria, particularly Lactobacillus spp., play a crucial role in heat stress-induced lipid metabolism disorder and that there is therapeutic potential for using probiotics, such as Lactobacillus plantarum.

Schiff base synergized with protonation of PEI to achieve smart antibacteria of nanocellulose packaging films.

Microbial growth and reproduction can cause food spoilage. Developing the controlled release packaging films for food is an ideal solution. In this study, polyethyleneimine (PEI) was grafted to cellulose nanofibers (CNF) films by Schiff base, and when the CNF/PEI films were stimulated by pH, PEI released from the CNF/PEI films due to Schiff base hydrolysis, improving the antibacterial efficiency of PEI. Stimulated by acid with pH of 4, the PEI cumulative release rate of the CNF/PEI800 and the CNF/PEI2000 films reached to 92.90 % and 87.28 %, respectively. At the same time, the amino groups of PEI protonated by obtaining H+, the charge density increased, and PEI molecular chains extended, enhancing the antibacterial activity of films. The Zeta potential value on the surface of the CNF/PEI film increased with the decrease of pH value. Schiff base synergized with protonation of PEI to achieve smart antibacteria of CNF packaging films. The antibacterial rates of the film against L. monocytogenes and E. coli were 94.7 % and 90.6 % at pH 4, but 29.5 % and 23.6 % at pH 8, respectively. The developed films also had good barrier properties of oxygen, visible light and mechanical properties, and had an attractive application prospect in food preservation to control release of antibacterial agent.

Mechanical and friction properties of agricultural plastic film during autumn harvest period of cotton in Xinjiang, China.

Agricultural plastic films have caused serious plastic pollution. There are many studies that consider mechanical recycling an appropriate system for the recovery of post-consumption agricultural mulch film. The recovery effect of plastic film depends on the mechanical properties, the level of dirtiness of the post-consumption film, and the recycling process itself. In this study, the mechanical properties of four types of polyethylene plastic films with a thickness of 8, 10, 12, and 10 µm, weather-resistant, commonly used in Xinjiang cotton fields, were tested. As well as the friction coefficient between the film and soil, the cotton stalk, boll shell, and leaf with different moisture contents were measured. Then, the self-propelled straw chopping and residual film recycling combined machine collected the four types of mulch films. The results showed that the longitudinal mechanical properties of the plastic film were greater than the transversal ones, with the exception of the nominal tensile strain at break, and the tensile characteristics of the mulching film covered with soil were greater than those without soil. The dynamic or static friction coefficient between the film and the contact material had a linear relationship with the moisture content of the material. During the recycling operation, the better the mechanical properties of the plastic film, the higher the pick-up rate of the mulch film. The maximum longitudinal tensile force of 12-µm plastic film was 3.42 N, and the nominal tensile strain at break was 303.09%. The pick-up rate reached more than 93% when the 12-µm plastic film was recovered in autumn, which effectively reduced the residue of plastic film coverage in the current year. Moreover, the more soil that was present on the much film, the greater the soil content of the recycled film roll, and the stalk content also increased, but the change was small. The research provides a reference for the mechanical and the friction features of agricultural plastic film in Xinjiang, and provides a theoretical basis for the formulation of standards for film thickness and mechanical properties, as well as the design and optimization of a residual film collecting machine in the cotton field.

Some key issues in building a "source network load storage" complementary energy internet in China.

The key to "dual carbon" lies in low-carbon energy systems. The energy internet can coordinate upstream and downstream "source network load storage" to break energy system barriers and promote carbon reduction in energy production and consumption processes. This article first introduces the basic concepts and key technologies of the energy internet from the current situation of energy supply and demand in China. Second, this paper proposes to create an energy internet with coordinated and complementary "source network load storage" and to construct a new type of power system with six new characteristics in this context. Finally, combined with an example of the energy internet demonstration project, this paper analyses and summarizes the value creation and business type innovation of the energy internet from three aspects: power market mechanisms, comprehensive energy services, and low-carbon energy diversification, and it looks ahead to the future direction of energy internet construction.