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Abstract Artificial intelligence (AI) telephone is reliable for the follow‐up and management of hypertensives. It takes less time and is equivalent to manual follow‐up to a high degree. We conducted a reliability study to evaluate the efficiency of AI telephone follow‐up in the management of hypertension. During May 18 and June 30, 2020, 350 hypertensives managed by the Pengpu Community Health Service Center in Shanghai were recruited for follow‐up, once by AI and once by a human. The second follow‐up was conducted within 3–7 days (mean 5.5 days). The mean length time of two calls were compared by paired t‐test, and Cohen's Kappa coefficient was used to evaluate the reliability of the results between the two follow‐up visits. The mean length time of AI calls was shorter (4.15 min) than that of manual calls (5.24 min, P

Abstract Background The association between remnant cholesterol (RC) and diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) remains unclear. Morphological changes in retinal vessels have been reported to predict vascular complications of diabetes, including DR. Methods This cross-sectional study included 6535 individuals with T2DM. The RC value was calculated using the recognized formula. The retinal vascular parameters were measured using fundus photography. The independent relationship between RC and DR was analyzed using binary logistic regression models. Multiple linear regression and subgroup analyses were employed to investigate the link between RC and vascular parameters, including the retinal arteriolar diameter (CRAE), venular diameter (CRVE), and fractal dimension (Df). Mediation analysis was performed to assess whether the vascular morphology could explain the association between RC and DR. Results RC was independently associated with DR in patients with a longer duration of T2DM (> 7 years). Patients with the highest quartile RC levels had larger CRAE (5.559 [4.093, 7.025] μm), CRVE (7.620 [5.298, 9.941] μm) and Df (0.013 [0.009, 0.017]) compared with patients with the lowest quartile RC levels. Results were robust across different subgroups. The association between RC and DR was mediated by CRVE (0.020 ± 0.005; 95% confidence interval: 0.012–0.032). Conclusions RC may be a risk factor for DR among those who have had T2DM for a longer period of time. Higher RC levels were correlated with wider retinal arterioles and venules as well as higher Df, and it may contribute to DR through the dilation of retinal venules.

Abstract As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.

Abstract Stress tolerance plays a vital role in ensuring the effectiveness of piezoresistive sensing films used in flexible pressure sensors. However, existing methods for enhancing stress tolerance employ dome-shaped, wrinkle-shaped, and pyramidal-shaped microstructures in intricate molding and demolding processes, which introduce significant fabrication challenges and limit the sensing performance. To address these shortcomings, this paper presents periodic microslits in a sensing film made of multiwalled carbon nanotubes and polydimethylsiloxane to realize ultrahigh stress tolerance with a theoretical maximum of 2.477 MPa and a sensitivity of 18.092 kPa−1. The periodic microslits permit extensive deformation under high pressure (e.g., 400 kPa) to widen the detection range. Moreover, the periodic microslits also enhance the sensitivity based on simultaneously exhibiting multiple synapses within the sensing interface and between the periodic sensing cells. The proposed solution is verified by experiments using sensors based on the microslit strategy for wind direction detection, robot movement sensing, and human health monitoring. In these experiments, vehicle load detection is achieved for ultrahigh pressure sensing under an ultrahigh pressure of over 400 kPa and a ratio of the contact area to the total area of 32.74%. The results indicate that the proposed microslit strategy can achieve ultrahigh stress tolerance while simplifying the fabrication complexity of preparing microstructure sensing films.

Poor electron conductivity is the key issue influencing the rate capability of NaTi2(PO4)3 (NTP). Hence, herein, polyacrylonitrile (PAN) was utilized as a NTP modifier by simply mixing NTP in a liquid PAN suspension, followed by sintering at 850 °C for 5 h. The product with a PAN/NTP mass ratio of 0.3 delivered splendid rate capabilities (achieving lithiation capacities of 282.9, 243.0, 207.1, 173.1, 133.5, and 257.5 mAh g−1 at 0.1, 0.2, 0.4, 0.8, 1.6, and 0.1 A−1, respectively) and excellent long cycling life (capacity retention of 165.5 mAh g−1 after 1200 cycles at 0.5 A g−1). Based on detailed structural and compositional characterizations, as well as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), the uniform N-doped carbon coating stemming from PAN carbonization around the NTP particles promoted electron transfer, while the oxygen vacancies induced by N-doping in NTP facilitated Li+ diffusion. The boosted and well matched electronic and ionic conductivities give rise to the optimized electrochemical performance.

In this paper, we present a novel deep-learning framework that incorporates quantified uncertainty for predicting the mechanical properties of nanocomposite materials, specifically taking into account their morphology and composition. Due to the intricate microstructures of nanocomposites and their dynamic changes under diverse conditions, traditional methods, such as molecular dynamics simulations, often impose significant computational burdens. Our machine learning models, trained on comprehensive material datasets, provide a lower computational cost alternative, facilitating rapid exploration of design spaces and more reliable predictions. We employ both convolutional neural networks and feedforward neural networks for our predictions, training separate models for yield strength and ultimate tensile strength. Furthermore, we integrate uncertainty quantification into our models, thereby providing confidence intervals for our predictions and making them more reliable. This study paves the way for advancements in predicting the properties of nanocomposite materials and could potentially be expanded to cover a broad spectrum of materials in the future.

Heavy metal in soil have been shown to be toxic with high concentrations and acts as selective pressure on both bacterial metal and antibiotic resistance determinants, posing a serious risk to public health. In cadmium (Cd) and zinc (Zn) contaminated soil, chitosan (Chi) and Trichoderma harzianum (Tri) were applied alone and in combination to assist phytoremediation by Amaranthus hypochondriacus L. Prevalence of antibiotic and metal resistance genes (ARGs and MRGs) in the soil was also evaluated using metagenomic approach. Results indicated that the phytoremediation of Cd and Zn contaminated soil was promoted by Chi, and Tri further reinforced this effect, along with the increased availability of Cd and Zn in soil. Meanwhile, combination of Chi and Tri enhanced the prevalence of ARGs (e.g., multidrug and β-lactam resistance genes) and maintained a high level of MRGs (e.g., chromium, copper) in soil. Soil available Zn and Cd fractions were the main factors contributing to ARGs profile by co-selection, while boosted bacterial hosts (e.g., Mitsuaria, Solirubrobacter, Ramlibacter) contributed to prevalence of most MRGs (e.g., Cd). These findings indicate the potential risk of ARGs and MRGs propagation in phytoremediation of metal contaminated soils assisted by organic and biological agents.

Abstract An important challenge in genetics, evolution and biotechnology is to understand and predict how mutations combine to alter phenotypes, including molecular activities, fitness and disease. In diploids, mutations in a gene can combine on the same chromosome or on different chromosomes as a “heteroallelic combination”. However, a direct comparison of the extent, sign, and stability of the genetic interactions between variants within and between alleles is lacking. Here we use thermodynamic models of protein folding and ligand-binding to show that interactions between mutations within and between alleles are expected in even very simple biophysical systems. Protein folding alone generates within-allele interactions and a single molecular interaction is sufficient to cause between-allele interactions and dominance. These interactions change differently, quantitatively and qualitatively as a system becomes more complex. Altering the concentration of a ligand can, for example, switch alleles from dominant to recessive. Our results show that intra-molecular epistasis and dominance should be widely expected in even the simplest biological systems but also reinforce the view that they are plastic system properties and so a formidable challenge to predict. Accurate prediction of both intra-molecular epistasis and dominance will require either detailed mechanistic understanding and experimental parameterization or brute-force measurement and learning.

In order to evaluate the risk level of the urban gas pipeline system, and provide the reference for follow-up prevention efforts, a quantitative analysis method of gas pipeline accident risk was proposed based on polymorphic fuzzy Bayesian network. Firstly, risk factors were sorted out from 86 accident investigation reports, so that the city gas pipeline risk element system was established. Subsequently, the fault tree model was built to seek the match between risk hazards and accidents, which can convert into the Bayesian network structure. After that, fuzzy set theory and probability distribution method were introduced to calculate the prior probability of the root node and the conditional probability of the intermediate nodes, evidence-based inference of Bayesian network was used to predict the probability of accidents, analyze the importance of risk elements, and reverse diagnose key causal factors. Finally, this method was applied to the risk analysis of the “10·21” large pipeline gas leakage accident in Shenyang. The results of the case validation show the a priori probability of the accident is 688%, which verifies the effectiveness of the risk system. Besides, important risk elements derived from prediction and backward diagnosis are consistent with the direct causes analyzed in the accident investigation report. The polymorphic fuzzy Bayesian network approach for gas pipeline system risk can evaluate gas pipeline accident risk accurately and identify key risk-causing factors, which provides some reference for decision making in the safety management of city gas pipelines.

Hydrogels are soft–wet materials with a hydrophilic three-dimensional network structure offering controllable stretchability, conductivity, and biocompatibility. However, traditional conductive hydrogels only operate in mild environments and exhibit poor environmental tolerance due to their high water content and hydrophilic network, which result in undesirable swelling, susceptibility to freezing at sub-zero temperatures, and structural dehydration through evaporation. The application range of conductive hydrogels is significantly restricted by these limitations. Therefore, developing environmentally tolerant conductive hydrogels (ETCHs) is crucial to increasing the application scope of these materials. In this review, we summarize recent strategies for designing multifunctional conductive hydrogels that possess anti-freezing, anti-drying, and anti-swelling properties. Furthermore, we briefly introduce some of the applications of ETCHs, including wearable sensors, bioelectrodes, soft robots, and wound dressings. The current development status of different types of ETCHs and their limitations are analyzed to further discuss future research directions and development prospects.

Abstract We conducted a matched retrospective cohort study of two cohorts to estimate inactivated vaccine effectiveness (VE) and its comparative effectiveness of booster dose among older people in Shanghai. Cohort 1 consisted of a vaccinated group (≥1 dose) and an unvaccinated group (3,317,475 pairs), and cohort 2 consisted of a booster vaccinated group and a fully vaccinated group (2,084,721 pairs). The Kaplan–Meier method and Cox regression models were used to estimate risk and hazard ratios (HRs) study outcomes. For cohort 1, the overall estimated VEs of ≥1 dose of inactivated vaccine against SARS-CoV-2 infection, severe/critical Covid-19, and Covid-19 related death were 24.7% (95%CI 23.7%−25.7%), 86.6% (83.1%−89.4%), and 93.2% (88.0%−96.1%), respectively. Subset analysis showed that the booster vaccination provided greatest protection. For cohort 2, compared with full vaccination, relative VEs of booster dose against corresponding outcome were 16.3% (14.4%−17.9%), 60.5% (37.8%−74.9%), and 81.7% (17.5%−95.9%). Here we show, although under the scenario of persistent dynamic zero-Covid policy and non-pharmaceutical interventions, promoting high uptake of the full vaccination series and booster dose among older adults is critically important. Timely vaccination with the booster dose provided effective protection against Covid-19 outcomes.

Citrus is the largest fruit crop around the world, while high nitrogen (N) application in citrus orchards is widespread in many countries, which results not only in yield, quality and environmental issues but also slows down the establishment of citrus canopies in newly cultivated orchards. Thus, the objective of this study was to investigate the physiological inhibitory mechanism of excessive N application on the growth of citrus seedlings. A pot experiment with the citrus variety Orah (Orah/Citrus junos) at four N fertilization rates (0, 50, 100, and 400 mg N/kg dry soil, denoted as N0, N50, N100, and N400, respectively) was performed to evaluate the changes of root morphology, biomass, N accumulation, enzyme activities, and so on. The results showed that the N400 application significantly reduced the total biomass (from 14.24 to 6.95 g/Plant), N accumulation (from 0.65 to 0.33 g/Plant) and N use efficiency (92.69%) in citrus seedlings when compared to the N100 treatment. The partial least squares pathway model further showed that the decline of biomass and N accumulation by high N application were largely attributed to the reduction of root growth through direct and indirect effects (the goodness of fit under the model was 0.733.) rather than just soil N transformation and activity of root N uptake. These results are useful to optimize N management through a synergistic N absorption and utilization by citrus seedlings.

ObjectiveTo determine if there are sex differences in myelin in Parkinson’s disease, and whether these explain some of the previously-described sex differences in clinical presentation.MethodsThirty-three subjects (23 males, 10 females) with Parkinson’s disease underwent myelin water fraction (MWF) imaging, an MRI scanning technique of in vivo myelin content. MWF of 20 white matter regions of interest (ROIs) were assessed. Motor symptoms were assessed using the Unified Parkinson’s Disease Rating Scale (UPDRS). Principal component analysis, logistic and multiple linear regressions, and t-tests were used to determine which white matter ROIs differed between sexes, the clinical features associated with these myelin changes, and if overall MWF and MWF laterality differed between males and females.ResultsConsistent with prior reports, tremor and bradykinesia were more likely seen in females, whereas rigidity and axial symptoms were more likely seen in males in our cohort. MWF of the thalamic radiation, cingulum, cingulum hippocampus, inferior fronto-occipital fasciculi, inferior longitudinal fasciculi, and uncinate were significant in predicting sex. Overall MWF and asymmetry of MWF was greater in males. MWF differences between sexes were associated with tremor symptomatology and asymmetry of motor performance.ConclusionSex differences in myelin are associated with tremor and asymmetry of motor presentation. While preliminary, our results suggest that further investigation of the role of biological sex in myelin pathology and clinical presentation in Parkinson’s disease is warranted.

BackgroundChronic disease management (CDM) falls under production relations, and digital technology belongs to the realm of productivity. Production relations must adapt to the development of productivity. Simultaneously, the prevalence and burden of chronic diseases are becoming increasingly severe, leveraging digital technology to innovate chronic disease management model is essential.MethodsThe model was built to cover experts in a number of fields, including administrative officials, public health experts, information technology staff, clinical experts, general practitioners, nurses, metrologists. Integration of multiple big data platforms such as General Practitioner Contract Platform, Integrated Community Multimorbidity Management System and Municipal and District-Level Health Information Comprehensive Platform. This study fully analyzes the organizational structure, participants, service objects, facilities and equipment, digital technology, operation process, etc., required for new model in the era of big data.ResultsBased on information technology, we build Integrated Community Multimorbidity Care Model (ICMCM). This model is based on big data, is driven by “technology + mechanism,” and uses digital technology as a tool to achieve the integration of services, technology integration, and data integration, thereby providing patients with comprehensive people-centered services. In order to promote the implementation of the ICMCM, Shanghai has established an integrated chronic disease management information system, clarified the role of each module and institution, and achieved horizontal and vertical integration of data and services. Moreover, we adopt standardized service processes and accurate blood pressure and blood glucose measurement equipment to provide services for patients and upload data in real time. On the basis of Integrated Community Multimorbidity Care Model, a platform and index system have been established, and the platform's multidimensional cross-evaluation and indicators are used for management and visual display.ConclusionsThe Integrated Community Multimorbidity Care Model guides chronic disease management in other countries and regions. We have utilized models to achieve a combination of services and management that provide a grip on chronic disease management.

Nanoplastics (NPs), regarded as the emerging contaminants, can enter and be mostly accumulated in the digest tract, which pose the potential threat to intestinal health. In this study, mice were orally exposed to polystyrene (PS), PS-COOH and PS-NH2 NPs with the size of ∼100 nm at a human equivalent dose for 28 consecutive days. All three kinds of PS-NPs triggered Crohn’s ileitis-like features, such as ileum structure impairment, increased proinflammatory cytokines and intestinal epithelial cell (IEC) necroptosis, and PS-COOH/PS-NH2 NPs exhibited higher adverse effects on ileum tissues. Furthermore, we found PS-NPs induced necroptosis rather than apoptosis via activating RIPK3/MLKL pathway in IECs. Mechanistically, we found that PS-NPs accumulated in the mitochondria and subsequently caused mitochondrial stress, which initiated PINK1/Parkin-mediated mitophagy. However, mitophagic flux was blocked due to lysosomal deacidification caused by PS-NPs, and thus led to IEC necroptosis. We further found that mitophagic flux recovery by rapamycin can alleviate NP-induced IEC necroptosis. Our findings revealed the underlying mechanisms concerning NP-triggered Crohn’s ileitis-like features and might provide new insights for the further safety assessment of NPs.

A capacitance-to-voltage converter (CVC) is proposed in this paper and applied to a readout circuit for a micro-electro-mechanical system (MEMS) accelerometer to improve the power efficiency. In a traditional readout circuit, the front-end CVC has to operate at a high sampling frequency to resist thermal noise deterioration due to the large parasitic capacitance introduced by the mechanical sensing element. Thus, the back-end analog-to-digital converter (ADC) also has to operate at a high sampling frequency to avoid noise aliasing when sampling the output signal of the CVC, which leads to high power consumption. The average CVC technique is proposed in this paper to reduce the sampling frequency requirement of the back-end ADC and thus reduce the power consumption. Both the traditional readout circuit and the proposed readout circuit are simulated with a commercial 0.18 μm BCD process. The simulation results show that noise aliasing occurs, and the noise power spectral density (PSD) of the traditional readout circuit increases by 12 dB when the sampling frequency of back-end ADC is reduced by 24 dB. However, in the proposed readout circuit, a noise aliasing effect does not occur. Moreover, the proposed readout circuit reduces the power consumption by 53% without thermal noise deterioration. In addition, the proposed CVC circuits are fabricated in an 0.18 μm BCD process, and the test results show that the presented readout circuit based on the average CVC technique can obtain better performance than the traditional CVC-based readout circuit.

The vehicle routing problem (VRP) problem is a classic NP-hard problem. Usually, the traditional optimization method cannot effectively solve the VRP problem. Metaheuristic optimization algorithms have been successfully applied to solve many complex engineering optimization problems. This paper proposes a discrete Harris Hawks optimization (DHHO) algorithm to solve the shared electric vehicle scheduling (SEVS) problem considering the charging schedule. The SEVS model is a variant of the VPR problem, and the influence of the transfer function on the model is analyzed. The experimental test data are based on three randomly generated examples of different scales. The experimental results verify the effectiveness of the proposed DHHO algorithm. Furthermore, the statistical analysis results show that other transfer functions have apparent differences in the robustness and solution accuracy of the algorithm.

Electrical stimulation is widely used in nerve regulation and treatment. The detection of the distribution of stimulation current in tissues is of great significance to improve the accuracy of electrical stimulation, but the current technical means are still difficult to achieve the non-invasive detection of stimulation current. This study proposes a non-invasive detection method of electrical stimulation current based on the magneto-acoustic (MA) effect, which has the advantages of high spatial resolution and high spatial contrast. In this study, continuous sine waves with the frequency of 20kHz are used to stimulate samples. The MA signal generated by the stimulation current in the samples in a stable magnetic field is detected by lock-in amplifier, and the two-dimensional distribution of sound source is extracted. The current density distribution of samples is simulated by the method of finite element analysis, and the simulation results are verified by experiments. The results show that under the electrical stimulation of the order of 0.01A, the location measurement of two-dimensional surface sound source with millimeter accuracy can be achieved non-invasively in isolated pork and pig brain, and the measurement accuracy of weak MA signal can reach 10−7Pa. In short, the stimulation current detection method based on MA effect can achieve the non-invasive and high-precision detection of electrical stimulation current distribution, which is of great significance to improve the stimulation accuracy and study the neural regulation mechanism of electrical stimulation.

Hydrogels are considered an ideal platform for personalized healthcare due to their unique characteristics, such as their outstanding softness, appealing biocompatibility, excellent mechanical properties, etc. Owing to the high similarity between hydrogels and biological tissues, hydrogels have emerged as a promising material candidate for next generation bioelectronic interfaces. In this review, we discuss (i) the introduction of hydrogel and its traditional applications, (ii) the work principles of hydrogel in bioelectronics, (iii) the recent advances in hydrogel bioelectronics for health monitoring, and (iv) the outlook for future hydrogel bioelectronics’ development.

BackgroundGait disturbances are critical motor symptoms in Parkinson’s disease (PD). The mechanisms of gait impairment in PD are not entirely understood but likely involve changes in the Pedunculopontine Nucleus (PPN), a critical locomotion center, and its associated connections. Exercise is universally accepted as helpful in PD, but the extent and intensity of exercise required for plastic changes are unclear.MethodsTwenty-seven PD subjects participated in a 3-month gait training intervention. Clinical assessments and resting-state functional magnetic resonance imaging were performed at baseline and 3 months after exercise. Functional connectivity of PPN was assessed by combining the methods of partial least squares, conditional dependence and partial correlation. In addition, paired t-tests were used to examine the effect of exercise on PPN functional connectivity and clinical measures, and Pearson’s correlation was used to assess the association between altered PPN functional connectivity and clinical measures.ResultsExercise significantly improved Unified Parkinson’s Disease Rating Scale-III (UPDRS-III). A significant increase in right PPN functional connectivity was observed after exercise, which did not correlate with motor improvement. However, the decrease in left PPN functional connectivity significantly correlated with the improvement in UPDRS-III and was linearly related to both number of walks and the duration of walks. In addition, exercise induced a significant increase in the laterality of PPN connectivity strength, which correlated with motor improvement.ConclusionPPN functional connectivity is modifiable by walking exercise in both a dose-independent (right PPN and laterality of PPN connectivity strength) and dose-dependent (left PPN) manner. The PPN may contribute to pathological and compensatory processes in PD gait control. The observed gait improvement by walking exercise is most likely due to the reversal of the maladaptive compensatory mechanism. Altered PPN functional connectivity can be a marker for exercise-induced motor improvement in PD.

The hybridization of PSO for the Optimal Coordination of Directional Overcurrent Protection Relays (DOPR) of the IEEE bus system proposes a new method for coordinating directional overcurrent protection relays in power systems. The method combines the hybrid particle swarm optimization (HPSO) algorithm and a heuristic PSO algorithm to find the minimum total operating time of the directional overcurrent protection relays with speed and accuracy. The proposed method is tested on the IEEE 4-bus, 6-bus, and 8-bus systems, and the results are compared with those obtained using traditional coordination methods. The collected findings suggest that the proposed method may produce better coordination and faster operation of DOPRs than the previous methods, with an increase of up to 74.9% above the traditional technique. The hybridization of the PSO algorithm and heuristic PSO algorithm offers a promising approach to optimize power system protection.

Abstract Systolic blood pressure (SBP) and resting pulse rate (RPR) have been linked to mortality and cardiovascular events in younger population. Till now, no studies simultaneously investigate the non‐linear association of SBP and RPR with all‐cause and cardiovascular mortality among population aged 80 and older. Data of 2828 eligible participants were selected from electronic health records linked attended automated office blood pressure measurement system. The dose‐response relationship between the SBP, RPR, and the risk of all‐cause and cardiovascular mortality was analyzed by Cox model with restricted cubic splines. During the 3.6‐year follow‐up, 442 deaths occurred. Comparing with the optimal SBP (117‐145 mmHg), the lower (HR: 1.39, 95% CI: 1.07‐1.81) and higher SBP (HR: 1.34, 95% CI: 1.08‐1.65) were significantly associated with an increasing risk of all‐cause mortality. The higher SBP (>144 mmHg) was associated with cardiovascular mortality, with the HR (95% CI) as 1.51 (1.07‐2.12). The faster RPR showed the higher risk of all‐cause (HR: 1.36, 95% CI: 1.05‐1.76) and cardiovascular (HR: 1.51, 95% CI: 1.07‐2.13) mortality. We found both higher SBP and faster RPR were independently associated with all‐cause and cardiovascular mortality, and lower SBP was only associated with the increased risk of all‐cause mortality in oldest old community‐dwelling Chinese population. Our results demonstrate the prognostic importance of both SBP and RPR in the elderly.

Abstract Background The gender pay gap in the United States (US) has narrowed over the last several decades, with the female/male earnings ratio in the US increased from about 60% before the 1980s to about 79% by 2014. However, the gender pay gap among the healthcare workforce persists. The objective of this study is to estimate the gender pay gap in the US federal governmental public health workforce during 2010–2018. Methods We used an administrative dataset including annual pay rates and job characteristics of employees of the US Department of Health and Human Services. Employees’ gender was classified based on first names. Regression analyses were used to estimate the gender pay gap using the predicted gender. Results Female employees of the DHHS earned about 13% less than men in 2010, and 9.2% less in 2018. Occupation, pay plan, and location explained more than half of the gender pay gap. Controlling for job grade further reduces the gap. The unexplained portion of the gender pay gap in 2018 was between 1.0 and 3.5%. Female employees had a slight advantage in terms of pay increase over the study period. Conclusions While the gender pay gap has narrowed within the last two decades, the pay gap between female and male employees in the federal governmental public health workforce persists and warrants continuing attention and research. Continued efforts should be implemented to reduce the gender pay gap among the health workforce.

Jellyfish blooms have become a marine environmental issue with detrimental effects on marine ecosystems around the world. The jellyfish Aurelia aurita is one of dominant species of blooms worldwide and also in the Bohai and Yellow Seas (BYSs) of China. To investigate population dynamics and controlling factors on population biomass, a complex population-dynamic model is developed for jellyfish of A. aurita in the BYSs that includes three components, namely, a three-dimensional coupled physical–biogeochemical model, a Lagrangian particle-tracking model, and an energy balance model for the jellyfish life cycle. By comparison, the model well reproduces the individual growth and seasonal evolution of A. aurita population. During individual growth period, the temperature is a key factor controlling growth and dry weight, characterized by a nearly linear growth rate. Longer period tends to favor larger medusa size and further to promote the biomass. The yearly peak biomass shows interannual variations that are controlled by the jellyfish magnitude, food concentration, and effective accumulative temperature of growth, with their contributions quantified through statistical analyses. Only considering the effect of temperature, the yearly peak biomass can be obtained through the durations of suitable temperature ranges for strobilization and individual growth that determines the magnitude and the averaged individual weight, respectively, with longer strobilation duration leading to higher magnitude. The simplified statistical relationships would favor to understand the temperature control on population dynamics of A. aurita.

Amorphous alloys (AAs) have the advantage of low core loss. Thus, they can be used in high-speed motor applications. However, compared with the nominal performances, the performance of the wire-cut electric discharge machine (W-EDM)-processed AA iron core changes significantly, which limits its popularization. This paper focuses on the performance degradation mechanism of the AA ribbon caused by W-EDM and establishes a modified core loss model after machining. First, a 308 × 15 mm ribbon-shaped AA sample machined by W-EDM was prepared. The characterization and analysis of the magnetic properties, phase, magnetic domain, nano-indentation, micro-morphology, and composition were carried out. In this paper, by analysing the variation in the magnetic domain distribution based on domain width and nano-mechanical properties, it is proposed that the performance degradation range of AA ribbons processed by W-EDM is within 1 mm from the edge. By comparing the microscopic morphology and chemical composition changes in the affected and the unaffected area, this paper presents a mechanism for the property deterioration of W-EDM-processed AA ribbons based on electrochemical corrosion. Finally, a modified loss model for W-EDM-processed AAs is established based on the division of the affected area. This model can significantly improve the accuracy of core loss estimation in the medium- and high-frequency bands commonly used in high-speed motors.

Laser diode pumped solid-state lasers (DPSSLs) have been widely used in many fields, and their thermal effects have attracted more and more attention. The laser diode (LD) side-pumped amplifier, as a key component of DPSSLs, is necessary for effective heat dissipation. In this paper, instead of the common thermal analysis based only on a crystal rod model, a fluid–structure interaction model including a glass tube, cooling channel, coolant and crystal rod is established in numerical simulation using ANSYS FLUENT for the configuration of an LD array side-pumped laser amplifier. The relationships between cooling layer thickness, coolant velocity and maximum temperature, maximum equivalent stress, inlet pressure and the convective heat transfer coefficient are analyzed. The results show that the maximum temperature (or maximum equivalent stress) decreases with the increase in the coolant velocity; at low velocity, a larger cooling layer thickness with more coolant is not conductive enough for improved heat dissipation of the crystal rod; at high velocity, when the cooling layer thickness is above or below 1.5 mm, the influence of the cooling layer thickness on the maximum temperature can be ignored; and the effect of the cooling layer thickness on the maximum equivalent stress at high velocity is not very significant. The comprehensive influence of various factors should be fully considered in the design process, and this study provides an important reference for the design and optimization of a laser amplifier and DPSSL system.

Deep end-to-end learning based stereo matching methods have achieved great success as witnessed by the leaderboards across different benchmarking datasets. Depth information in stereo vision systems are obtained by a dense and accurate disparity map, which is computed by a robust stereo matching algorithm. However, previous works adopt network layer with the same size to train the feature parameters and get an unsatisfactory efficiency, which cannot be satisfied for the real scenarios by existing methods. In this paper, we present an end-to-end stereo matching algorithm based on "downsize" convolutional neural network (CNN) for autonomous driving scenarios. Firstly, the road images are feed into the designed CNN to get the depth information. And then the "downsize" full-connection layer combined with subsequent network optimization is employed to improve the accuracy of the algorithm. Finally, the improved loss function is utilized to approximate the similarity of positive and negative samples in a more relaxed constraint to improve the matching effect of the output. The loss function error of the proposed method for KITTI 2012 and KITTI 2015 datasets are reduced to 2.62 and 3.26% respectively, which also reduces the runtime of the proposed algorithm. Experimental results illustrate that the proposed end-to-end algorithm can obtain a dense disparity map and the corresponding depth information can be used for the binocular vision system in autonomous driving scenarios. In addition, our method also achieves better performance when the size of the network is compressed compared with previous methods.

Foliar zinc (Zn) fertilization is an important approach for overcoming crop Zn deficiency, yet little is known regarding the subsequent translocation of this foliar-applied Zn. Using synchrotron-based X-ray fluorescence microscopy (XFM) and transcriptome analysis, the present study examined the translocation of foliar absorbed Zn in sunflower (Helianthus annuus) leaves. Although bulk analyses showed that there had been minimal translocation of the absorbed Zn out of the leaf within 7 days, in situ analyses showed that the distribution of Zn in the leaf had changed with time. Specifically, when Zn was applied to the leaf for 0.5 h and then removed, Zn primarily accumulated within the upper and lower epidermal layers (when examined after 3 h), but when examined after 24 h, the Zn had moved to the vascular tissues. Transcriptome analyses identified a range of genes involved in stress response, cell wall reinforcement, and binding that were initially upregulated following foliar Zn application, whereas they were downregulated after 24 h. These observations suggest that foliar Zn application caused rapid stress to the leaf, with the initial Zn accumulation in the epidermis as a detoxification strategy, but once this stress decreased, Zn was then moved to the vascular tissues. Overall, this study has shown that despite foliar Zn application causing rapid stress to the leaf and that most of the Zn stayed within the leaf over 7 days, the distribution of Zn in the leaf had changed, with Zn mostly located in the vascular tissues 24 h after the Zn had been applied. Not only do the data presented herein provide new insight for improving the efficiency of foliar Zn fertilizers, but our approach of combining XFM with a transcriptome methodological system provides a novel approach for the study of element translocation in plants.

Abstract Background Adults with chronic conditions such as heart disease, diabetes, or lung disease are more likely to develop complications from a number of vaccine-preventable diseases, including influenza and pneumonia. In this study, we use the data from a chronic disease management information system in Shanghai to estimate vaccination coverage and characterize predictors of seasonal influenza and 23-valent pneumococcal polysaccharide vaccine (PPSV23) vaccination among people with chronic disease in Shanghai. Methods The Shanghai Centers for Disease Control and Prevention have information systems related to chronic disease management, hospital records, and immunizations. Data from individuals with hypertension, diabetes and chronic obstructive pulmonary disease (COPD) were abstracted during July 2017. The main outcome was coverage of pneumococcal and influenza vaccination. Vaccination coverage was calculated across demographic groups. Significance in bivariate associations was assessed through Pearson’s chi-square tests, and in multivariable models through logistic regression models with a forward stepwise method to select variables. Results In the sample of 2,531,227 individuals ≥15 years, 22.8% were vaccinated for pneumonia from January 2013 to July 2017, and the vaccination coverage of influenza in the 2016/17 influenza season was 0.4%. Vaccination coverage was highest in those 70–79 and lowest in those younger than 60. Compared to urban areas, uptake in rural areas was higher for pneumonia vaccination (OR: 2.43, 95% CI: 2.41, 2.45), but lower for influenza vaccination (OR: 0.55, 95% CI: 0.51, 0.59). Having a greater number of chronic diseases was associated with higher likelihood of pneumonia vaccination (3 vs 1: OR: 1.68, 95% CI: 1.64, 1.71), but this relationship was not statistically significant for influenza vaccination. Conclusions We found low levels with of pneumococcal vaccination, and extremely low uptake of influenza vaccination among individuals with high risk conditions in Shanghai who should be priority groups targeted for vaccination. Interventions could be designed to target groups with low uptake – like younger adults, and individuals who have not yet retired.

Summary: Current photocatalytic uranium (U) extraction methods have intrinsic obstacles, such as the recombination of charge carriers, and the deactivation of catalysts by extracted U. Here we show that, by applying a bias potential on the photocatalyst, the photoelectrochemical (PEC) method can address these limitations. We demonstrate that, owing to efficient spatial charge-carriers separation driven by the applied bias, the PEC method enables efficient and durable U extraction. The effects of multiple operation conditions are investigated. The U extraction proceeds via single-step one-electron reduction, resulting in the formation of pentavalent U, which can facilitate future studies on this often-overlooked U species. In real seepage water the PEC method achieves an extraction capacity of 0.67 gU m−3·h−1 without deactivation for 156 h continuous operation, which is 17 times faster than the photocatalytic method. This work provides an alternative tool for U resource recovery and facilitates future studies on U(V) chemistry.

With the depletion of shallow metal mineral resources, deep mining has become more common. In the process of deep mining, heat hazards in mines seriously threaten the health of personnel and the safety of mining operations. According to the flow and low-temperature characteristics of abundant water in Maoping Lead Zinc Mine, this paper proposes the direct use of the low-temperature water inflow of the mine as the cold source by which to conduct the heat exchange with a single spiral-tube heat exchanger for mine cooling. An experimental platform was built for the cooling system to allow us to explore the mechanism of the influence of the inlet air volume and air temperature and the inlet water temperature and flow on the cooling effect of the single spiral-tube heat exchanger. It was found that with the increase in the inlet air volume and inlet water temperature, the cooling efficiency of the heat exchanger decreased, while with the increase in the inlet air temperature, the cooling efficiency of the heat exchanger increased. Within the experimental range, 127.2 m3/h was found to be the optimum inlet air volume, and 33.0 °C was the most appropriate inlet air temperature; the water temperature of Maoping Coal Mine is about 20 °C throughout the year, and the industrial test site can reduce the wind temperature of 31.5 °C to 23.9 °C. The inlet water flow is positively related to the cooling effect. With the increase in the water flow, the outlet temperature of the air flow at each working point was continuously reduced, and the cooling effect of the heat exchanger was improved. The moisture content of the inlet air flow can be reduced by increasing the low-temperature inlet water flow. Through experiments, the feasibility of the cooling system that directly uses the mine’s low-temperature water as the cold source was verified. A multiple linear regression analysis equation for the cooling system model is proposed, which provides a reference for formulating effective measures to prevent and control heat hazards in mines.

There are many indices for evaluating the operational performance of parallel robots, but most of them start from kinematics and rarely pay special attention to the force transmission process. After studying the relationship and characteristics of the forward and reverse force transmission of the Stewart parallel manipulator under quasi-static conditions, three new indices are proposed in this paper, which are forward force sensitivity, reverse force sensitivity, and overall force sensitivity. Subsequently, the influences of six parameters on the overall force sensitivity index are analyzed. Furthermore, this paper propose three new structural optimization design schemes based on the three newly proposed indices. Finally, it is verified experimentally that the unit reverse force sensitivity of a single joint is consistent with the theory and the error between the theoretical and experimental values is obtained.

Although nanomedicine has been highly investigated for cancer treatment over the past decades, only a few nanomedicines are currently approved and in the market; making this field poorly represented in clinical applications. Key research gaps that require optimization to successfully translate the use of nanomedicines have been identified, but not addressed; among these, the lack of control of the release pattern of therapeutics is the most important. To solve these issues with currently used nanomedicines (e.g., burst release, systemic release), different strategies for the design and manufacturing of nanomedicines allowing for better control over the therapeutic release, are currently being investigated. The inclusion of stimuli-responsive properties and prolonged drug release have been identified as effective approaches to include in nanomedicine, and are discussed in this paper. Recently, smart sustained release nanoparticles have been successfully designed to safely and efficiently deliver therapeutics with different kinetic profiles, making them promising for many drug delivery applications and in specific for cancer treatment. In this review, the state-of-the-art of smart sustained release nanoparticles is discussed, focusing on the design strategies and performances of polymeric nanotechnologies. A complete list of nanomedicines currently tested in clinical trials and approved nanomedicines for cancer treatment is presented, critically discussing advantages and limitations with respect to the newly developed nanotechnologies and manufacturing methods. By the presented discussion and the highlight of nanomedicine design criteria and current limitations, this review paper could be of high interest to identify key features for the design of release-controlled nanomedicine for cancer treatment.

The existence of antibiotics in the environment can trigger a number of issues by fostering the widespread development of antimicrobial resistance. Currently, the most popular techniques for removing antibiotic pollutants from water include physical adsorption, flocculation, and chemical oxidation, however, these processes usually leave a significant quantity of chemical reagents and polymer electrolytes in the water, which can lead to difficulty post-treating unmanageable deposits. Furthermore, though cost-effectiveness, efficiency, reaction conditions, and nontoxicity during the degradation of antibiotics are hurdles to overcome, a variety of photocatalysts can be used to degrade pollutant residuals, allowing for a number of potential solutions to these issues. Thus, the urgent need for effective and rapid processes for photocatalytic degradation leads to an increased interest in finding more sustainable catalysts for antibiotic degradation. In this review, we provide an overview of the removal of pharmaceutical antibiotics through photocatalysis, and detail recent progress using different nanostructure-based photocatalysts. We also review the possible sources of antibiotic pollutants released through the ecological chain and the consequences and damages caused by antibiotics in wastewater on the environment and human health. The fundamental dynamic processes of nanomaterials and the degradation mechanisms of antibiotics are then discussed, and recent studies regarding different photocatalytic materials for the degradation of some typical and commonly used antibiotics are comprehensively summarized. Finally, major challenges and future opportunities for the photocatalytic degradation of commonly used antibiotics are highlighted.

Introduction: Hemorrhagic shock (HS) is a severe medical emergency. Early diagnosis of HS is important for clinical treatment. In this paper, we report a flexible material-based heart sound monitoring device which can evaluate the degree of HS through a phonocardiogram (PCG) change. Methods: Progressive hemorrhage treatments (H1, H2, and H3 stage) were used in swine to build animal models. The PCG sensor was mounted on the chest of the swine. Routine monitoring was used at the same time. Results: This study showed that arterial blood pressure decreased significantly from the H1 phase, while second heart sound amplitude (S2A) and energy (S2E) decreased significantly from the H2 phase. Both S2A and S2E correlated well with BP (p < 0.001). The heart rate, pulse pressure variation and serum hemoglobin level significantly changed in the H3 stage (p < 0.05). Discussion: The change of second heart sound (S2) was at the H2 stage and was earlier than routine monitoring methods. Therefore, PCG change may be a new indicator for the early detection of HS severity.

In order to gradually reduce automobile exhaust pollution and improve fuel quality, the NOx sensor, which can be monitored in real time in an automobile engine’s electronic control system, has become an indispensable part of the automobile lean burn system. In these types of NOx sensors, Au-doped platinum electrodes have received great attention due to their selectivity towards NO. However, the reaction process of NO gas on the Au-doped platinum electrode in the sensor and the possible regulation mechanism is still unclear. In this paper, the density functional theory (DFT) was used to analyze the effect of Au-doped Pt electrodes on the performance of nitrogen oxide sensors in automobiles. Firstly, the adsorption energies of NO molecules on pure Pt and Au/Pt surfaces were compared. The adsorption and dissociation of NO on Pt substrates doped with Au monomers, dimers, and trimers were investigated. These results showed that Au can effectively weaken the adsorption energy of NO molecules on a Pt surface. It was noted that with the increase in the number of Au atoms on the surface of Pt(111), the adsorption capacity of NO molecules on the alloy surface becomes weaker. When observing the transition state of NO decomposition on three different alloy surfaces, the study showed that the activation energy and reaction heat of NO dissociation increased. It further showed that doping with Au increased the activation energy of NO decomposition, thereby effectively inhibiting the decomposition of NO.

Poly(N-isopropylacrylamide) (PNIPAM) based electrically conductive hydrogels (PNIPAM-ECHs) have been extensively studied in recent decades due to their thermal-responsive (leading to the volume change of hydrogels) and electrically conductive performance. The incorporation of conductive components into the PNIPAM hydrogel network makes it become conductive hydrogel, and as a result, the PNIPAM hydrogel could become sensitive to an electrical signal, greatly expanding its application. In addition, conductive components usually bring new stimuli-responsive properties of PNIPAM-based hydrogels, such as near-infrared light and stress/strain responsive properties. PNIPAM-ECHs display a wide range of applications in human motion detection, actuators, controlled drug release, wound dressings, etc. To summarize recent research advances and achievements related to PNIPAM-ECHs, this manuscript first reviews the design and structure of representative PNIPAM-ECHs according to their conductive components. Then, the applications of PNIPAM-ECHs have been classified and discussed. Finally, the remaining problems related to PNIPAM-ECHs have been summarized and a future research direction is proposed which is to fabricate PNIPAM-ECHs with integrated multifunctionality.

The use of a directional overcurrent protection relay (DOPR) to protect an electrical power system is a crucial instrument for keeping the system dynamic and avoiding undue interruption. The coordination of a DOPR’s primary and backup relays is modelled as a highly constrained optimization problem. The goal is to determine an ideal value that will reduce the overall working time of all primary relays. The coordination is accomplished by the use of particle swarm optimization hybridization (HPSO). Comprehensive simulation experiments are carried out to evaluate the efficacy of the proposed HPSO by employing the time multiplier setting (TMS) and plug setting (PS) as an optimization variable and constant, respectively. The HPSO has been examined satisfactorily utilizing certain IEEE benchmark test systems (9-bus and 14-bus). The outcomes are contrasted with earlier heuristics and evolutionary approaches. Based on the acquired findings, it is clear that the obtained results exceed the other conventional and state of the art procedures in terms of total DOPR operation and the computing time necessary to achieve the global optimal solution.

Owing to the complex and long-term treatment of foot wounds due to diabetes and the limited mobility of patients, advanced clinical surgery often uses wearable flexible devices for auxiliary treatment. Therefore, there is an urgent need for self-powered biomedical devices to reduce the extra weight. We have prepared an electrically stimulated MEMS (Micro Electromechanical System) electrode integrated with wearable OPV (Organic photovoltaic). The wearable OPV is constructed of a bio-affinity PET-ITO substrate and a hundred-nanometer organic layer. Under sunlight and near-infrared light irradiation, a voltage and current are supplied to the MEMS electrode to generate an exogenous lateral electric field directed to the center of the wound. The results of in vitro cell experiments and diabetic skin-relieving biological experiments showed the proliferation of skin fibroblasts and the expression of transforming growth factors increased, and the skin wounds of diabetic mouse healed faster. Our research provides new insights for the clinical treatment of diabetes.

This paper presents an external-cavity dual-wavelength mid-infrared multiple optical parametric oscillator based on a single MgO:APLN crystal, which is pumped by a pulsed 1.064 μm laser. The output power and beam qualities of parametric lasers at different repetition rates and transmittance were studied. When the pump power of the 1.064 μm laser was 34.5 W, the repetition rate was 63 kHz, the maximum output powers of 2.79 W@3.30 μm and 4.92 W@3.84 μm were obtained with the transmittance T = 60%@1.57 μm, corresponding to optical–optical conversion efficiencies of 8.1% and 14.3%, respectively. Meanwhile, the beam qualities of two mid-infrared laser beams were effectively optimized and the pulse widths of 9.72 ns@3.30 μm and 9.67 ns@3.84 μm were obtained synchronously.

Vanadium pentoxide can undergo a reversible phase transition by heating above 260 °C; its non-thermal phase transition, as well as ultrafast dynamical processes, is still not known. Here, femtosecond laser-induced phase transition properties in V2O5 thin films were first explored using femtosecond time-resolved pump–probe spectroscopy. The results show that the phase transient processes occur on a 10−15–10−13 temporal scale. The phase transition and recovery properties are dependent on both the substrates and pump laser energy densities. We propose the oxygen vacancies theory to explain the results, and we provide valuable insights into V2O5 films for potential applications.

Organic donor–acceptor bulk heterojunction are attracting wide interests for solar cell applications due to solution processability, mechanical flexibility, and low cost. The photovoltaic performance of such thin film is strongly dependent on vertical phase separation of each component. Although film-depth-dependent light absorption spectra measured by non-in situ methods have been used to investigate the film-depth profiling of organic semiconducting thin films, the in situ measurement is still not well-resolved. In this work, we propose an in situ measurement method in combination with a self-developed in situ instrument, which integrates a capacitive coupled plasma generator, a light source, and a spectrometer. This in situ method and instrument are easily accessible and easily equipped in laboratories of the organic electronics, which could be used to conveniently investigate the film-depth-dependent optical and electronic properties.

Abstract Background Chinese giant salamander (Andrias davidianus) undergoes a metamorphosis from aquatic larvae to terrestrial adults, with concomitant transfer of respiration from gills to lungs prior to metamorphosis. These two tissues, as well as skin, were sampled to identify the differentially expressed miRNAs. Results High-coverage reference transcriptome was generated from combined gill, lung and skin tissues of metamorphosing juveniles, and lung tissue of adults: 86,282 unigenes with total length of approximately 77,275,634 bp and N50 of 1732 bp were obtained. Among these, 13,246 unigenes were assigned to 288 pathways. To determine the possible involvement of miRNAs in the respiratory transition, small RNA libraries were sequenced; 282 miRNAs were identified, 65 among which were known and 217 novel. Based on the hierarchical clustering analysis, the twelve studied samples were classified into three major clusters using differentially expressed miRNAs. We have validated ten differentially expressed miRNAs and some of their related target genes using qPCR. These results largely corroborated the results of transcriptomic and miRNA analyses. Finally, an miRNA-gene-network was constructed. Among them, two miRNAs with target genes related to oxygen sensing were differentially expressed between gill and lung tissues. Three miRNAs were differentially expressed between the lungs of larvae and lungs of adults. Conclusions This study provides the first large-scale miRNA expression profile overview during the respiration transition from gills to lungs in Chinese giant salamander. Five differentially expressed miRNAs and their target genes were identified among skin, gill and lung tissues. These results suggest that miRNA profiles in respiratory tissues play an important role in the regulation of respiratory transition.

With the rapid development of e-commerce and the change of consumption patterns, more and more consumers are beginning to choose online shopping. Logistics service has become one of the important factors that affects consumer satisfaction of online shopping and restricts the development of e-commerce enterprises. Therefore, it explores the factors influencing the online shopping logistics service and the corresponding relationship between them, and designs corresponding optimization solutions to provide better services to customers, further improve customer satisfaction, establish a good image for the enterprise and improve the efficiency of enterprises. In order to explore the types and the mechanism of consumer online shopping logistics services, from the perspective of online shopping consumers, the evaluation information of online shoppers on the platform is taken as the object of study, using the octopus data collection tool from Tmall to grab a large number of comments, conducting the in-depth analysis and mining using grounded theory research method, and further extracting the main categories and types of logistics service factors through open coding, spindle coding and selective coding. The composition of online shopping logistics service factors is divided into 7 main categories, the main category relationship structure is further mined, and the factors influencing the quality of online shopping logistics service are summarized as four main types of distribution quality, perception experience, after-sales service quality and reliability. Based on the typical relational structure of the main category, the core category of "key influencing factors of online shopping logistics service satisfaction" is finally determined, and the role model of logistics service quality is analyzed. Using the semantic network analysis and theoretical saturation test to verify the types of logistics service quality factors and their mechanism of action, the semantic network analysis using the ROST Content Mining knowledge processing and content mining software to conduct the whole network analysis, and using word frequency analysis and keyword co-occurrence analysis, the results are verified; and the research results are further verified by theoretical saturation test using the original data method and reliability assessment method. The results show that: perceived experience is the direct driving factor of online shopping logistics services, which determines whether the customer conducts online shopping. The quality of after-sales service and reliability indirectly drives consumers' online shopping behavior by influencing perception experience, which is the indirect factor of online shopping logistics service. Delivery quality can not only directly affect the quality of online shopping logistics service but also indirectly affect the online shopping logistics service quality through the perception experience. Obviously, it is necessary to explore the influencing factors of online shopping logistics service. By improving the logistics service in the above aspects, it not only can improve customer satisfaction, acquire and maintain a stable customer base in order to maintain the competitive advantage of enterprises, but also can be used as an important basis for e-commerce enterprise to improve its logistics system, and explore the weak link of the logistics to enable enterprises to get better development. The results of this study are of great significance for B2C e-commerce enterprises to improve the quality of logistics service and improve the competitiveness of enterprises.

Vanadium pentoxide (V2O5) is the most stable phase among many transition metal vanadium oxides, and has already been widely used in many fields. In this study, the morphological, structural, and optical responses of V2O5 film to ultrafast laser irradiation was investigated. The third-order nonlinear optical properties of V2O5 film were measured by common Z-scan technique, and the results showed that V2O5 film has self-defocusing and saturable absorption characteristics. The third-order nonlinear absorption coefficient and nonlinear refractive index were calculated to be −338 cm/GW and −3.62 × 10−12 cm2/W, respectively. The tunable saturated absorption with modulation depth ranging from 13.8% to 29.3% was realized through controlling the thickness of vanadium pentoxide film. V2O5 film was irradiated by ultrafast laser with variable pulse energy, and the morphological and structural responses of the V2O5 to the laser with different energy densities were investigated. The irreversible morphological and structural responses of V2O5 films to ultrafast laser irradiation was analyzed using the phase-contrast microscope and Raman spectrum. The chemical structure change from V2O5 to V6O13 was considered the main reason for refractive index modification.

New shoots (including newly formed leaves and twigs) and fruits of citrus tree are key organs for present yield formation and flower differentiation in the next season, but the relationship between yield fluctuation and accumulations of major nutrients in new shoots and fruits of citrus tree is still unclear. Thus, to quantify the biomass and mineral nutrient accumulation in new shoots and fruits of citrus trees under varied yield levels has essential significance for rational fertilization and pruning management for citrus orchards. The purpose of this study was, therefore, to investigate the accumulation of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg), and the distribution of biomass in new shoots and fruits of citrus trees under low, medium and high-yield levels in each of eight orchards located in Chongqing, China. The results showed that substantial variation of fruit yield was observed in all eight orchards with an average yield of 15.0 (low), 30.9 (medium) and 60.1 (high) kg/plant. The averaged biomass of new shoots ranged from 1.59 to 2.51 kg/plant, which was significantly and positively correlated with fruit yield. Nutrient accumulation in leaves was generally highest among new organs, while more than half of N (52.70–71.4%), P (66.5–80.4%) and K (68.9–85.9%) accumulated in fruit. Fruit yields closely correlated with total amounts of major nutrients in new shoots. Furthermore, the nutrient requirements per unit of newly developed shoots and fruits were gradually decreased with increased yield, but the removed nutrients per ton of fresh fruit were almost stable, indicating that more nutrients were distributed into fruit tissues. Taken together, these findings are valuable for optimizing nutrient and pruning management in citrus orchards in China and other similar countries.

Estimating balanced nutrient requirements for a watermelon plantation is essential to increase its fruit yield and nutrient use efficiency. This is vital for China, which produces 60% of world’s watermelons with excessive fertilizer application. Therefore, datasets between 2000 and 2019 from field experiments in major watermelon producing regions across China were collected to assess relationships between fruit yield and nutrient uptake, and to estimate nitrogen (N), phosphorus (P), and potassium (K) requirements for a target yield using a modified Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model. The results showed that the QUEFTS model predicted a linear increase in fruit yield to 60–70% of the total potential yield when balanced amounts of N, P, and K nutrients were absorbed. To produce 1000 kg of watermelon, 2.11 kg N, 0.27 kg P, and 2.69 kg K were required in shoot, and the corresponding internal efficiencies (IE) were 475, 3682, and 372 kg fruit per kg of N, P, and K, respectively. The modified QUEFTS model also simulated a balanced N, P, and K removal by fruit (accounting for 50.9%, 58.2%, and 66.4% of these nutrient accumulations in shoots, respectively). Field validation experiments further verified that the modified QUEFTS model could be used for estimating balanced nutrient requirements. Results from this study can provide practical guidance on fertilizer recommendations for improving fruit yield while preventing excessive or deficient nutrient supplies in China’s watermelon plantations.

Abstract text summarization aims to offer a highly condensed and valuable information that expresses the main ideas of the text. Most previous researches focus on extractive models. In this work, we put forward a new generative model based on convolutional seq2seq architecture. A hierarchical CNN framework is much more efficient than the conventional RNN seq2seq models. We also equip our model with a copying mechanism to deal with the rare or unseen words. Additionally, we incorporate a hierarchical attention mechanism to model the keywords and key sentences simultaneously. Finally we verify our model on two real-life datasets, GigaWord and DUC corpus. The experiment results verify the effectiveness of our model as it outperforms state-of-the-art alternatives consistently and statistical significantly.