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Abstract Background Understanding factors associated with antiretroviral treatment (ART) adherence is crucial for ART success among people living with HIV (PLHIV) in the “test and treat” era. Multiple psychosocial factors tend to coexist and have a syndemic effect on ART adherence. We aimed to explore factors associated with ART adherence and the syndemic effect of multiple psychosocial factors on ART adherence among PLHIV newly starting ART in Guangdong Province, China. Methods Newly diagnosed PLHIV from six cities in Guangdong Province were recruited between May 2018 and June 2019, and then followed up from May 2019 to August 2020. Baseline and follow-up data were collected from a questionnaire and the national HIV surveillance system, the follow-up data of which were analyzed in this study. A Center for Adherence Support Evaluation (CASE) index > 10 points was defined as optimal ART adherence, which was measured via participants’ self-reported adherence during follow-up survey. Multivariable logistic regression was used to identify factors associated with ART adherence. Exploratory factor analysis (EFA) and multi-order latent variable structural equation modeling (SEM) were performed to explore the syndemic effect of multiple psychosocial factors on ART adherence. Results A total of 734 (68.53%) follow-up participants were finally included in this study among the 1071 baseline participants, of whom 91.28% (670/734) had self-reported optimal ART adherence. Unemployment (aOR = 1.75, 95%CI: 1.01–3.02), no medication reminder (aOR = 2.28, 95%CI: 1.09–4.74), low medication self-efficacy (aOR = 2.28, 95%CI: 1.27–4.10), low social cohesion (aOR = 1.82, 95%CI: 1.03–3.19), no social participation (aOR = 5.65, 95%CI: 1.71–18.63), and ART side effects (aOR = 0.46, 95%CI: 0.26–0.81) were barriers to optimal ART adherence. The EFA and second-order latent variable SEM showed a linear relationship (standardized coefficient = 0.43, P

Introduction Ferroptosis is a new type of cell death characterized by lipid peroxidation and iron dependency, representing an emerging disease regulation mechanism. The limited understanding of ferroptosis in peripheral nerve injury (PNI) complicates the management of such injuries. Mitochondrial dysfunction, which contributes to ferroptosis, further exacerbates the challenges of peripheral nerve repairMethodsIn this study, we established an in vitro model of Schwann cells model treated with TBHP and an in vivo sciatic nerve crush injury model in rats. These models were used to investigate the effects of fibroblast growth factor 21 (FGF21) on PNI, both in vitro and in vivo, and to explore the potential mechanisms linking injury-induced ferroptosis and mitochondrial dysfunction.Results Our findings reveal that PNI triggers abnormal accumulation of lipid reactive oxygen species (ROS) and inactivates mitochondrial respiratory chain complex III, leading to mitochondrial dysfunction. This dysfunction catalyzes the oxidation of excessive polyunsaturated fatty acids, resulting in antioxidant imbalance and loss of ferroptosis suppressor protein 1 (FSP1), which drives lipid peroxidation. Additionally, irregular iron metabolism, defective mitophagy, and other factors contribute to the induction of ferroptosis. Importantly, we found that FGF21 attenuates the abnormal accumulation of lipid ROS, restores mitochondrial function, and suppresses ferroptosis, thus promoting PNI repair. Notably, glutathione peroxidase 4 (GPX4), a downstream target of nuclear factor E2-related factor 2 (Nrf2), and the ERK/Nrf2 pathway are involved in the regulation of ferroptosis by FGF21.ConclusionFGF21 promotes peripheral nerve repair by inhibiting ferroptosis caused by mitochondrial dysfunction. Therefore, targeting mitochondria and ferroptosis represents a promising therapeutic strategy for effective PNI repair.

In order to analyze the motion of the human lower limb, a comprehensive process was created in this paper. Firstly, an exoskeleton robot platform was leveraged and a dynamic model of human-exoskeleton lower limb was created for identifying human parameters. Then the sEMG signal was utilized to extract information about muscle activity through multi-group experiments, and a backpropagation neural network (BPNN) was built to forecast joint torque. An inverse dynamics analysis combining the human motion data with the dynamic model can not only verify the reliability of prediction result by this BPNN but also the correctness of identified results before. Moreover, the mean absolute error (MAE), root mean square error (RMSE), and Pearson correlation coefficient (PCC) were used as evaluation index of both identification and prediction results. The proposed protocol can give accurate identified parameters for subject and estimated joint torque from sEMG during swing motion. We believe it can be extended to various types of human motion movement and potentially applied to complete human motion analysis.

Abstract Background Condom use at last intercourse is an effective indicator for human immunodeficiency virus (HIV) prevention. To identify at-risk individuals and improve prevention strategies, this study explored factors associated with condomless sex at last intercourse in the last year and developed a risk estimation model to calculate the individual possibility of condomless sex among college students in Zhuhai, China. Methods A cross-sectional study was conducted among 1430 college students who had sex in the last year from six universities in Zhuhai. The least absolute shrinkage and selection operator (LASSO) and logistic regression were performed to explore the predictors of condomless sex. The nomogram was constructed to calculate the individual possibility of condomless sex. Discrimination and calibration of the nomogram were evaluated using the area under the receiver-operator characteristic curve (AUROC) and the calibration curve. Results The proportion of students who had condomless sex at last intercourse was 18.2% (260/1430). Students who had experienced more types of intimate partner violence (aOR, 1.58; 95% CI, 1.31 ~ 1.92) and had anal sex (aOR, 1.75; 95% CI, 1.06 ~ 2.84) were more likely to have condomless sex. Students who had heterosexual intercourse (aOR, 0.37; 95% CI, 0.21 ~ 0.70), used condoms at first sex (aOR, 0.20; 95% CI, 0.14 ~ 0.27), had high attitudes towards condom use (aOR, 0.87; 95% CI, 0.80 ~ 0.95) and self-efficacy for condom use (aOR, 0.84; 95% CI, 0.78 ~ 0.90) were less likely to have condomless sex. The nomogram had high accuracy with an AUROC of 0.83 and good discrimination. Conclusions Intimate partner violence, anal sex, condom use at first sex, attitude towards condom use, and self-efficacy for condom use were associated with condomless sex among college students. The nomogram was an effective and convenient tool for calculating the individualized possibility of condomless sex among college students. It could help to identify individuals at risk and help universities and colleges to formulate appropriate individualized interventions and sexual health education programs.

With the deepening application of artificial intelligence in the field of education, teaching quality evaluation has become the key to improving educational effectiveness. In order to quantify the effectiveness of knowledge transmission and mastery in digital media teaching, this paper proposes an improved Bayesian knowledge tracking model (BF-BKT), which has been specifically optimized for teaching quality evaluation. The motivation stems from the shortcomings of existing technology in evaluating teaching quality, especially the lack of effective integration of student learning behavior and forgetting patterns. This article describes the development process of the BF-BKT model, which innovatively combines learning behavior data and forgetting patterns by introducing behavioral forgetting features to more accurately predict students’ learning status and teaching effectiveness. The BF-BKT model not only considers whether students have mastered a certain knowledge point, but also further analyzes their forgetting situation at different time points, providing a more comprehensive perspective for evaluating teaching quality. To validate the performance of the BF-BKT model, we compared it with the traditional BKT model and two diverse BKT variants. We conducted systematic experiments and analysis by selecting public datasets as simulation scenarios. The experimental results show that the BF-BKT model performs well in predicting students’ knowledge mastery and evaluating teaching quality, and its performance is superior to other comparative methods, proving the effectiveness and superiority of the model.

Abstract Background Mechanical power (MP) is the total energy released into the entire respiratory system per minute which mainly comprises three components: elastic static power, Elastic dynamic power and resistive power. However, the energy to overcome resistance to the gas flow is not the key factor in causing lung injury, but the elastic power (EP) which generates the baseline stretch of the lung fibers and overcomes respiratory system elastance may be closely related to the ARDS severity. Thus, this study aimed to investigate whether EP is superior to other ventilator variables for predicting the severity of lung injury in ARDS patients. Methods We retrieved patient data from the Medical Information Mart for Intensive Care III (MIMIC-III) database. The retrieved data involved adults (≥ 18 years) diagnosed with ARDS and subjected to invasive mechanical ventilation for ≥ 48 h. We employed univariate and multivariate logistic regression analyses to investigate the correlation between EP and development of moderate-severe ARDS. Furthermore, we utilized restricted cubic spline models to assess whether there is a linear association between EP and incidence of moderate-severe ARDS. In addition, we employed a stratified linear regression model and likelihood ratio test in subgroups to identify potential modifications and interactions. Results Moderate-severe ARDS occurred in 73.4% (296/403) of the patients analyzed. EP and MP were significantly associated with moderate-severe ARDS (odds ratio [OR] 1.21, 95% confidence interval [CI] 1.15–1.28, p

Abstract Background One noteworthy concern within the realm of education is the level of engagement demonstrated by students. Among the factor that can have a crucial role in this domain is teacher support, especially emotional support which has an impact on several aspects of learners’ education. Furthermore, various studies have investigated the relationship between Emotional Intelligence (EI) and learners’ engagement. Methods Accordingly, this study investigated the possible role of trait EI and the emotional support of teachers and how these constructs may work to associate learners’ engagement. For this objective, a total of 309 Chinese students across different colleges and universities in 5 provinces of Beijing, Shanghai, Jiangsu, Hubei, and Shaanxi were enrolled. They were 126 females and 183 males, with ages ranging from 18 to 30 years old (Mean = 24.6). Results The results of this research through running Structural Equation Modeling (SEM) demonstrated that teachers’ emotional support and trait EI both can associate students’ learning engagement. The final measurement model shows that about 73% of changes in learners’ engagement can be associated by their trait EI and teachers’ emotional support. Conclusions This study underscores the importance of emotional support from teachers and the trait of EI in relation to students’ engagement in learning. Both factors were shown to play a significant role in associating student engagement. Moreover, this study could potentially have wider impacts on members of academic teams.

This paper uses explanatory variables to carry out the degree of executive unfairness on the stability of the team, using the number of members serving in the sample period to measure the stability of the executive team, the introduction of risk-taking, inefficient investment mediating variables on the role of corporate merger and acquisition behavior impact path. By calculating the causal relationship between executive team stability and corporate technological innovation performance, it is concluded that the degree of external positive inequity in compensation impacts corporate stability. It is found that the mean value of executive compensation in the agriculture and forestry industry is 0.287, the median is 0.193, and the average annual growth rate of average executive compensation is 24.2%, which can provide practical suggestions for corporate managers and decision-makers about compensation setting and team building.

Given the traditional single-value assessment index for the energy storage system， a multi-dimensional value assessment method for the energy storage system of distribution networks is proposed. With different applications and composite values of the energy storage system taken into account， the multi-dimensional indexes are pre-selected and calculated in terms of economy， reliability， and environmental protection. Given the indexes' variability characteristics and synergistic coupling degree， the pre-selected indexes are redundantly screened， and the index system is streamlined. The variable weight hierarchical analysis method based on intuitionistic fuzzy theory is used to determine the comprehensive weight coefficients and define the total assessed value of the energy storage system. The Garver 6-node test system is taken as an example： the proposed assessment method is used to sequence the different scheme groups and select the optimal configuration scheme. The results verify the rationality and effectiveness of the method.

Synthetic health data have the potential to mitigate privacy concerns when sharing data to support biomedical research and the development of innovative healthcare applications. In this work, the authors introduce a use case oriented benchmarking framework to evaluate data synthesis models through a set of utility and privacy metrics.

Abstract Several single-center studies have evaluated the predictive performance of mechanical power (MP) on weaning outcomes in prolonged invasive mechanical ventilation (IMV) patients. The relationship between MP and weaning outcomes in all IMV patients has rarely been studied. A retrospective study was conducted on MIMIC-IV patients with IMV for more than 24 h to investigate the correlation between MP and weaning outcome using logistic regression model and subgroup analysis. The discriminative ability of MP, MP normalized to dynamic lung compliance (Cdyn-MP) and MP normalized to predicted body weight (PBW-MP) on weaning outcome were evaluated by analyzing the area under the receiver-operating characteristic (AUROC). Following adjustment for confounding factors, compared with the reference group, the Odds Ratio of weaning failure in the maximum MP, Cdyn-MP, and PBW-MP groups increased to 3.33 [95%CI (2.04–4.53), P

Given the high carbon emission level of the industrial park integrated energy system， a low-carbon economic dispatch model of the integrated energy system considering the time-varying carbon emission factor is proposed. Firstly， to improve the carbon emission model of the whole process of electric energy production， the carbon emission characteristics of tie-line and energy storage charging and discharging are studied. Secondly， the low-carbon potential of load-side dispatchable resources is explored， and a dispatch model of load-side dispatchable resources under the incentive of price signals and time-varying carbon emission factor curve is constructed； a low-carbon economic dispatch model of the industrial park integrated energy system considering the time-varying carbon emission factor curve is constructed to optimize the system operation with the objective of minimum operation cost and carbon emission. The simulation results show that the low-carbon economic dispatch model can effectively reduce the carbon emission level of the system and reduce the total operation cost of industrial park.

The general position problem is to find the cardinality of the largest vertex subset SS such that no triple of vertices of SS lies on a common geodesic. For a connected graph GG, the cardinality of SS is denoted by gp(G){\rm{gp}}\left(G) and called the gp{\rm{gp}}-number (or general position number) of GG. In the paper, we obtain an upper bound and a lower bound regarding the gp{\rm{gp}}-number in all cacti with kk cycles and tt pendant edges. Furthermore, the exact value of the gp{\rm{gp}}-number on wheel graphs is determined.

As a physical carrier of energy Internet， integrated energy system can improve energy utilization efficiency. Therefore， its optimal dispatching has attracted extensive attention of scholars all over the world. Firstly， the comprehensive demand response and the operation model of multi-energy storage device are modeled； Then， the minimum total operation cost of the integrated energy system is taken as the objective function to construct the optimal dispatching model of the integrated energy system considering the comprehensive demand response and multi-energy storage devices； Then， the CVaR （conditional value at risk） is used to deal with the output uncertainty of renewable energy； Finally， an example of an electric-heat-cold integrated energy system is analyzed. The results show that the model proposed in this paper can reduce the operation cost of the integrated energy system and measure the operational risk caused by output uncertainty of renewable energy.

Background: Alveolar epithelial cell injury is a key factor in the occurrence and development of pulmonary acute respiratory distress syndrome (ARDSp). Yet the gene expression profile of alveolar epithelial cells of patients with ARDSp remains unclear. Methods: We analyzed single nuclear RNA sequencing (snRNA-Seq) data from autopsy lung tissues of both ARDSp patients and healthy donors. Sequence data for type 2 alveolar epithelizal cells (AT2) were extracted by the Seurat package. Differentially expressed genes (DEGs) in AT2 were identified by the criteria |log2FC| ≥ 0.25 and P

With the increase in the elderly population in China and the growing number of individuals who are unable to walk normally, research on lower limb exoskeletons is becoming increasingly important. This study proposes a complete dynamic model parameter identification scheme for the human–machine coupling model of lower limb exoskeletons. Firstly, based on the coupling model, the excitation trajectory is optimized, data collection experiments are conducted, and the dynamic parameter vector of the system is identified using the least squares method. Secondly, this lays the foundation for designing adaptive control based on RBF neural network approximation. Thirdly, the Lyapunov function is used to prove that the RBF neural network adaptive controller can achieve stable tracking of the lower limb exoskeleton. Finally, simulation analysis reveals that increasing the gains of the RBF controllers effectively reduces tracking errors. Furthermore, the tracking errors and control torques show that adaptive control based on the RBF neural network approximation works well.

Exoskeleton robots are functioning in contexts with more complicated motion control needs as a result of the technology and applications for these robots rapidly developing. This calls for novel control techniques to accommodate their employment in a range of real-world settings. This paper proposes a bionic control method for a human–exoskeleton coupling dynamic model based on the CPG model, utilizing a model on the dynamics of the human–exoskeleton interaction. The CPG network is established as an oscillator by two neurons inhibiting one another, which approximates the torques simulated in the inverse dynamic analysis as the input to the exoskeleton robot. The findings of the simulation assessment suggest that the bionic control strategy may improve the robot’s ability to move quickly and steadily, as well as better adapt to challenging environments.

The increasing number of Artificial Intelligence of Things (AIoT) devices at the edge layer brings serious challenges to the traditional access network architecture, which results in a decrease in data transmission due to different QoS requirements. To improve the QoS of the URLLC service and mMTC service in the AIoT, a Hybrid Services Collaborative Resource Scheduling Strategy (HSCRS) is proposed. First, a multi-layer collaborative resource scheduling framework for the AIoT hybrid services is designed based on the F-RAN. Then, a throughput weighting model for hybrid services is constructed to analyze the throughput characteristics of mMTC service and URLLC service. Furthermore, a sub-channel allocation and power control method is designed to solve the resource scheduling strategy of hybrid services. Experimental results show that the proposed method can largely improve the network throughput performance.

Late testing and antiretroviral therapy (ART) prevailed among people living with HIV (PLHIV) and impacted the benefit of immediate ART. This study aimed to identify the benefit of the test-and-immediate-treat policy in China, the effect of immediate ART, and the influence of late testing and ART on the whole PLHIV in Guangdong Province, China. We designed two tendency analyses in aggregative form and two cohorts (surveillance and ART cohort) in individuals' perspectives based on the HIV/AIDS Comprehensive Response Information Management System. Two interrupted time series models were conducted for tendency analysis from 2009 to 2018 to explore the all-cause and short-term mortality decrease after the test-and-immediate-treat policy. A time-dependent Cox model was performed for the surveillance cohort from 1992 to 2018 and a joint model was utilized for the ART cohort to identify the effect of immediate ART and the influence of late testing and ART on death. The tendency analysis included 324,914 and 68,679 person-year for all-cause/short-term mortality. A total of 49,289 and 26,287 PLHIV were recruited in the surveillance and ART cohort with 5,557 and 459 deaths, respectively. The short-term mortality dropped from 4.69 cases/100 person-year in January 2009 to 0.35 cases/100 person-year in December 2018 (standardized rate). The all-cause mortality saw a decreasing trend from 1.46 cases/100 person-year in January 2009 to 0.14 cases/100 person-year in December 2018 (standardized rate). The tendency analysis showed a significant short-term mortality slope decrease after the test-and-immediate-treat policy (P = 0.024). From the surveillance cohort, late testing, in general, was a risk factor for all-cause mortality [hazard ratio (HR) = 1.330, 95% CI, 1.250, 1.416]. ART cohort showed higher hazards of all-cause mortality among PLHIV with no late testing, but late ART (HR = 1.690, 95% CI, 1.166, 2.451) and both the late testing and late ART (HR = 1.335, 95% CI, 1.042, 1.710). Immediate ART might decrease the hazard of all-cause death though it is insignificant (HR = 0.923, 95% CI: 0.755, 1.129) in the ART cohort. The test-and-immediate-test policy brought benefit to PLHIV. We should enlarge HIV testing using comprehensive approaches to decrease late testing and ART and increase the benefit of immediate ART.

There are multiple types of services in the Internet of Things, and existing access control methods do not consider situations wherein the same types of services have multiple access options. In order to ensure the QoS quality of user access and realize the reasonable utilization of Internet of Things network resources, it is necessary to consider the characteristics of different services to design applicable access control strategies. In this paper, a preference-aware user access control strategy in slices is proposed, which can increase the number of users in the system while balancing slice resource utilization. First, we establish the user QoS model and slice QoS index range according to the delay, rate and reliability requirements, and we select users with multiple access options. Secondly, a user preference matrix is established according to the user QoS requirements and the slice QoS index range. Finally, a preference matrix of the slice is built according to the optimization objective, and access control decisions are made for users through the resource utilization state of the slice and the preference matrix. The verification results show that the proposed strategy not only balances slice resource utilization but also increases the number of users who can access the system.

As one of the most important components of urban space, an outdated inventory of road-side trees may misguide managers in the assessment and upgrade of urban environments, potentially affecting urban road quality. Therefore, automatic and accurate instance segmentation of road-side trees from urban point clouds is an important task in urban ecology research. However, previous works show under- or over-segmentation effects for road-side trees due to overlapping, irregular shapes and incompleteness. In this paper, a deep learning framework that combines semantic and instance segmentation is proposed to extract single road-side trees from vehicle-mounted mobile laser scanning (MLS) point clouds. In the semantic segmentation stage, the ground points are filtered to reduce the processing time. Subsequently, a graph-based semantic segmentation network is developed to segment road-side tree points from the raw MLS point clouds. For the individual tree segmentation stage, a novel joint instance and semantic segmentation network is adopted to detect instance-level roadside trees. Two complex Chinese urban point cloud scenes are used to evaluate the individual urban tree segmentation performance of the proposed method. The proposed method accurately extract approximately 90% of the road-side trees and achieve better segmentation results than existing published methods in both two urban MLS point clouds. Living Vegetation Volume (LVV) calculation can benefit from individual tree segmentation. The proposed method provides a promising solution for ecological construction based on the LVV calculation of urban roads.

Abstract In this study, a humanoid prototype of 2-DOF (degrees of freedom) lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton. To improve the detection accuracy of the human-robot interaction torque, a BPNN (backpropagation neural networks) is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque sensor. Meanwhile, the backstepping controller is designed to realize the exoskeleton's passive position control, which means that the person passively adapts to the exoskeleton. On the other hand, a variable admittance controller is used to implement the exoskeleton's active follow-up control, which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable performance. To improve the wearable comfortable effect, serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control parameters. Finally, the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.

In this study, the potato whole flour was added to wheat flour with wheat gluten was auxiliary added to make potato noodle. Three groups of the potato powder noodles with different total flour content were studied from three levels: texture characteristics, microstructure and physicochemical properties of noodles. It was found that the potato powder had a certain effect on the mechanical properties of dough, the formation and structure of gluten network, and the cooking parameters and appearance of noodles. The results showed that the overall index was the best when the total amount of the potato powder was 20% (g/g)and the amount of gluten was 0.03% (g/g). It was also found that the effect of the potato powder on dough was bidirectional. The effect of the potato starch on the dough was negative, but the polysaccharides and protein in the potato powder may have a positive effect on the dough and gluten network. At the same time,the addition of wheat gluten can improve the stability of dough and the quality of noodles.

Digital twin technology can support teachers in this major to complete monitoring related topics and application research and serve teaching and scientific research through the establishment of automatic monitoring teaching model laboratory and in-depth combination with the current students’ skill training needs in this major. This exploration aims to make the visual sensor industry have a steady stream of talents. Promoting the development of visual sensor technology is to promote the development of science and technology. Based on the teaching research of visual sensing design using digital technology, a set of teaching systems of visual sensing design is designed by using the methods of literature research and investigation and analysis. Special topics are set up from the aspects of professional subjects; regarding course content, various sensor principle research courses, visual sensor design courses, experimental courses, and example courses are set up; teaching methods are divided into online and offline synchronous classes; the evaluation method should focus on the distribution, examples, and practice. The results show that traditional classroom teaching is seriously separated from extracurricular learning. Most students are in a state of passive acceptance of knowledge and have few thinking activities. The established teaching system integrates brain and cognition, photoelectric foundation, sensory imaging, visual sensing imaging, visual sensing technology courses, computer technology, virtual experiment courses, and physical experiment courses. It can carry out more than 30 experiments of optical microscopic imaging and X-ray imaging based on the principle of visual sensing. Therefore, the teaching effect and teaching mode of the proposed digital visual sensing teaching system have been greatly improved.

Abstract Background The bacterial CRISPR/Cas genome editing system has provided a major breakthrough in molecular biology. One use of this technology is within a nuclease-based gene drive. This type of system can install a genetic element within a population at unnatural rates. Combatting of vector-borne diseases carried by metazoans could benefit from a delivery system that bypasses traditional Mendelian laws of segregation. Recently, laboratory studies in fungi, insects, and even mice, have demonstrated successful propagation of CRISPR gene drives and the potential utility of this type of mechanism. However, current gene drives still face challenges including evolved resistance, containment, and the consequences of application in wild populations. Additional research into molecular mechanisms that would allow for control, titration, and inhibition of drive systems is needed. Results In this study, we use artificial gene drives in budding yeast to explore mechanisms to modulate nuclease activity of Cas9 through its nucleocytoplasmic localization. We examine non-native nuclear localization sequences (both NLS and NES) on Cas9 fusion proteins in vivo through fluorescence microscopy and genomic editing. Our results demonstrate that mutational substitutions to nuclear signals and combinatorial fusions can both modulate the level of gene drive activity within a population of cells. Conclusions These findings have implications for control of traditional nuclease-dependent editing and use of gene drive systems within other organisms. For instance, initiation of a nuclear export mechanism to Cas9 could serve as a molecular safeguard within an active gene drive to reduce or eliminate editing.

We extend the array theory to design 2D curved coding metasurfaces in order to achieve arbitrary wavefront control. The extended array theory establishes the relationship between wavefront and curved-surface, which provides a simple and effective method to obtain the layout of desired metasurfaces. According the theory, we present 2D curved metasurfaces with 3-bit coding elements. Both simulations and measurements demonstrate that the proposed designs can manipulate wavefront effectively. For normal incidence, the aperture efficiency of normal reflection is more than 90%. For general oblique incidence, the proposed designs almost meet the expectances, but the aperture efficiency decreases with the increase of desired scattering elevation angle. The curved coding metasurfaces are expected to be applied to many devices such as conformal antenna array.

A novel roof solar chimney with wind-induced channel was designed herein to augment indoor natural ventilation under combined action of wind and solar energy. Compared with the traditional solar chimney, the new rooftop solar chimney improves the air flow due to the wind-induced channel. The effects of channel width ratio, chimney inclination at different outdoor wind speeds on the natural ventilation performance of the roof solar chimney were studied by numerical simulation. Finite-volume method was used for the numerical calculation. It was found that the trends of ventilation rate are different when the channel widths increase. The mass flow rate of the new structure increases with the increase in the inclination angle. When the inclination angles increase from 30° to 90°, the ventilation rate increases by 212% for U = 1.0 m·s−1, 166% for U = 2.0 m·s−1, and 127% for U = 3.0 m·s−1 under the condition of and the solar radiation I = 600 W·m−2.

Although diatom records from lake sediments have been used for quantitative paleoclimatic reconstruction, their validity and sensitivity have rarely been tested rigorously. At Yunlong Lake, an alpine lake in Southwest China, we studied the seasonal succession of diatom assemblages to produce a mean surface water temperature (MSWT) transfer function. In addition, based on the spatial distribution of surface diatom assemblages with water depth, we produced a diatom-water depth (WD) transfer function. Combined with the analysis of diatom assemblages in a sediment core (YL2013-A), changes in surface water temperature and water level over the last ∼100 years were quantitatively reconstructed using the diatom-based transfer functions. Comparison with records of regional meteorology and reservoir water capacity revealed that the diatom-based lake water level reconstruction is a sensitive indicator of short-term fluctuations in precipitation, and it also reflects a long-term stepwise rise in water level caused by the impounding and large-scale extension of the reservoir. In addition, the diatom-inferred MSWT is consistent with the changes in air temperature prior to large-scale human disturbance of the site. However, after the extension of the reservoir, although the regional air temperature continued to increase, the water temperature decreased substantially. This suggests that the large increase in lake water volume in the short term led to a decrease in the average water temperature, which in turn led to the occurrence of a diatom bloom in the cold season. The results demonstrate that diatom transfer functions based on modern observations of the same lake has a high environmental sensitivity and can be used for the quantitative reconstruction of regional climate change. Overall, our findings provide a foundation for the use of lake diatom records for quantitative paleoclimatic reconstruction on various timescales.

AbstractSeptins are GTP-binding proteins conserved across metazoans. They can polymerize into extended filaments and, hence, are considered a component of the cytoskeleton. The number of individual septins varies across the tree of life—yeast (Saccharomyces cerevisiaeCaenorhabditis elegans

In the absence of a proven effective vaccine preventing infection by SARS-CoV-2, or a proven drug to treat COVID-19, the positive results of passive immune therapy using convalescent serum provide a strong lead. We have developed a new class of tetravalent, biparatopic therapy, 89C8-ACE2. It combines the specificity of a monoclonal antibody (89C8) that recognizes the relatively conserved N-terminal domain of the viral Spike (S) glycoprotein, and the ectodomain of ACE2, which binds to the receptor-binding domain of S. This molecule shows exceptional performance in vitro, inhibiting the interaction of recombinant S1 to ACE2 and transduction of ACE2-overexpressing cells by S-pseudotyped lentivirus with IC50s substantially below 100 pM, and with potency approximately 100-fold greater than ACE2-Fc itself. Moreover, 89C8-ACE2 was able to neutralize authentic viral infection in a standard 96-h co-incubation assay at low nanomolar concentrations, making this class of molecule a promising lead for therapeutic applications.

This paper focuses on the position tracking control issue of electrohydraulic systems (EHS). The dynamical model of EHS is introduced in the first place, based on which a type of Variable Structure Disturbance Observer (VSDO) is constructed for EHS to estimate the parametric uncertainty the EHS possesses. Then, a backstepping controller is designed under VSDO to realize the high precision position tracking purpose. To avoid the phenomenon of differential explosion, a dynamic surface control method is adopted in this paper, which improved the position tracking control performance of EHS. The proposed theoretical results are verified by numerical simulation and experiment to illustrate the feasibility.