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Abstract Employing electrochemistry for the selective functionalization of liquid alkanes allows for sustainable and efficient production of high-value chemicals. However, the large potentials required for C(sp 3)-H bond functionalization and low water solubility of such alkanes make it challenging. Here we discover that a Pt/IrO x electrocatalyst with optimized Cl binding energy enables selective generation of Cl free radicals for C-H chlorination of alkanes. For instance, we achieve monochlorination of cyclohexane with a current up to 5 A, Faradaic efficiency (FE) up to 95% and stable performance over 100 h in aqueous KCl electrolyte. We further demonstrate that our system can directly utilize concentrated seawater derived from a solar evaporation reverse osmosis process, achieving a FE of 93.8% towards chlorocyclohexane at a current of 1 A. By coupling to a photovoltaic module, we showcase solar-driven production of chlorocyclohexane using concentrated seawater in a membrane electrode assembly cell without any external bias. Our findings constitute a sustainable pathway towards renewable energy driven chemicals manufacture using abundant feedstock at industrially relevant rates.

Abstract Novel active DNA transposons, such as Spy transposons from the PHIS superfamily, are identified through bioinformatics in this study. The native transposases cgSpy and cvSpy displayed transposition activities of approximately 85% and 35% compared to the hyperactive piggyBac transposase (hyPB). The cgSpy transposon showed unique characteristics, including a lack of overproduction inhibition and reduced efficiency for insertion sizes between 3.1 to 8.5 kb. Integration preferences of cgSpy are found in genes and regulatory regions, making it suitable for genetic manipulation. Evaluation in T‐cell engineering demonstrated that cgSpy‐mediated chimeric antigen receptor (CAR) modification is comparable to the PB system, indicating its potential utility in cell therapy. This study unveils the promising application of the active native transposase, Spy, from Colletes gigas, as a valuable tool for genetic engineering, particularly in T‐cell manipulation.

Abstract Tuning interfacial electric fields provides a powerful means to control electrocatalyst activity. Importantly, electric fields can modify adsorbate binding energies based on their polarizability and dipole moment, and hence operate independently of scaling relations that fundamentally limit performance. However, implementation of such a strategy remains challenging because typical methods modify the electric field non-uniformly and affects only a minority of active sites. Here we discover that uniformly tunable electric field modulation can be achieved using a model system of single-atom catalysts (SACs). These consist of M-N4 active sites hosted on a series of spherical carbon supports with varying degrees of nanocurvature. Using in-situ Raman spectroscopy with a Stark shift reporter, we demonstrate that a larger nanocurvature induces a stronger electric field. We show that this strategy is effective over a broad range of SAC systems and electrocatalytic reactions. For instance, Ni SACs with optimized nanocurvature achieved a high CO partial current density of ~400 mA cm−2 at >99% Faradaic efficiency for CO2 reduction in acidic media.

Abstract Renewable electricity powered electrochemical CO2 reduction (CO2R) offers a valuable method to close the carbon cycle and reduce our overreliance on fossil fuels. However, high purity CO2 is usually required as feedstock, which potentially decreases the feasibility and economic viability of the process. Direct conversion of flue gas is an attractive option but is challenging due to the low CO2 concentration and the presence of O2 impurities. As a result, up to 99% of the applied current can be lost towards the undesired oxygen reduction reaction (ORR). Here, we show that acidic electrolyte can significantly suppress ORR on Cu, enabling generation of multicarbon products from simulated flue gas. Using a composite Cu and carbon supported single-atom Ni tandem electrocatalyst, we achieved a multicarbon Faradaic efficiency of 46.5% at 200 mA cm-2, which is ~20 times higher than bare Cu under alkaline conditions. We also demonstrate stable performance for 24 h with a multicarbon product full-cell energy efficiency of 14.6%. Strikingly, this result is comparable to previously reported acidic CO2R systems using pure CO2. Our findings demonstrate a potential pathway towards designing efficient electrolyzers for direct conversion of flue gas to value-added chemicals and fuels.

This study systematically explored the characteristics of explosion and pressure fluctuations of ethyl acetate (EA)/hydrogen (H2)/air mixtures under different initial pressures (1–3 bar), H2 fractions (4%, 8%, 12%), and equivalence ratios of EA (0.5–1.4). The flame images indicated that a higher pressure, a higher H2 fraction, and a higher equivalence ratio could cause flame instability. An analysis of the dimensionless growth rate indicated that the flame instability was impacted by both thermal diffusion and hydrodynamic effects. The results also indicated that a higher initial pressure or H2 fraction could accelerate the combustion reaction and increase the explosion pressure and deflagration index. The maximum values were observed at 21.841 bar and 184.153 bar·m/s. However, their effects on explosion duration and heat release characteristics differed between lean and rich mixtures. Additionally, this study examined pressure fluctuations in both the time and frequency domains. The findings indicated a strong correlation between pressure fluctuation and flame instability. Modifying the H2 fraction and equivalence ratio to enhance flame stability proved effective in reducing pressure fluctuation amplitude. This study offers guidance for evaluating explosion risks associated with EA/H2/air mixtures and for designing related combustion devices.

With the support of big data mining techniques, utilizing social media data containing location information and rich semantic text information can construct large-scale daily activity OD flows for urban populations, providing new data resources and research perspectives for studying urban spatiotemporal structures. This paper employs the ST-DBSCAN algorithm to identify the residential locations of Weibo users in four communities and then uses the BERT model for activity-type classification of Weibo texts. Combined with the TF-IDF method, the results are analyzed from three aspects: temporal features, spatial features, and semantic features. The research findings indicate: ① Spatially, residents’ daily activities are mainly centered around their residential locations, but there are significant differences in the radius and direction of activity among residents of different communities; ② In the temporal dimension, the activity intensities of residents from different communities exhibit uniformity during different time periods on weekdays and weekends; ③ Based on semantic analysis, the differences in activities and venue choices among residents of different communities are deeply influenced by the comprehensive characteristics of the communities. This study explores methods for OD information mining based on social media data, which is of great significance for expanding the mining methods of residents’ spatiotemporal behavior characteristics and enriching research on the configuration of public service facilities based on community residents’ activity spaces and facility demands.

In this article, the SIR model is used to fit the spread of influenza A in Ningbo, ranging from January 1, 2023 to June 30, 2023. The data that can be collected is the daily newly confirmed cases, but the daily number of infected individuals and recovered individuals is unknown. The initial number of susceptible individuals with exposure risk is also unknown. Based on the incompleteness of the data, the parameter estimation problem of the SIR model is transformed into an optimization problem. The Particle Swarm Optimization algorithm is used to solve the optimization problem. The goodness of fit (R2) of the daily cumulative number of confirmed cases is 0.998. The model can reflect the cycle, peak, and trend of the entire spread of influenza A and is consistent with reality during the post-COVID-19 period.

Abstract Craniofacial microsomia (CFM; also known as Goldenhar syndrome), is a craniofacial developmental disorder of variable expressivity and severity with a recognizable set of abnormalities. These birth defects are associated with structures derived from the first and second pharyngeal arches, can occur unilaterally and include ear dysplasia, microtia, preauricular tags and pits, facial asymmetry and other malformations. The inheritance pattern is controversial, and the molecular etiology of this syndrome is largely unknown. A total of 670 patients belonging to unrelated pedigrees with European and Chinese ancestry with CFM, are investigated. We identify 18 likely pathogenic variants in 21 probands (3.1%) in FOXI3. Biochemical experiments on transcriptional activity and subcellular localization of the likely pathogenic FOXI3 variants, and knock-in mouse studies strongly support the involvement of FOXI3 in CFM. Our findings indicate autosomal dominant inheritance with reduced penetrance, and/or autosomal recessive inheritance. The phenotypic expression of the FOXI3 variants is variable. The penetrance of the likely pathogenic variants in the seemingly dominant form is reduced, since a considerable number of such variants in affected individuals were inherited from non-affected parents. Here we provide suggestive evidence that common variation in the FOXI3 allele in trans with the pathogenic variant could modify the phenotypic severity and accounts for the incomplete penetrance.

Abstract Mesenchymal stromal cells (MSC) have shown potential efficacy in both animal and human trials of acute respiratory distress syndrome (ARDS). Especially during the COVID-19 pandemic, MSC was intensely studied for treating COVID-19-induced ARDS. The purpose of this study is to evaluate the safety and efficacy of MSC in ARDS via a meta-analysis of randomized controlled trials (RCTs). Therefore, a meta-analysis of RCTs of MSC as a therapy for ARDS was conducted. The protocol of this review was registered on Open Science Framework. With no language restriction and according to the “PICOs” principle, searches were conducted on Pubmed and Embase to retrieve any clinical literature on MSC for ARDS. Any RCT, which compared MSC to controls for ARDS, where MSC and controls were intravenously infused, of any dosage, was eligible for inclusion. A total of 13 RCTs, which evaluated MSC versus control for treating ARDS, enrolling a total of 655 cases, met the inclusion criteria and appeared in this meta-analysis. A heterogeneity assessment was carried out using the χ 2 test, where a P value less than 0.05 was considered significant. The choice of a fixed-effect or a random-effect model was decided by the I 2 value in each of the analyses. This meta-analysis indicated that there was no significant difference in terms of adverse events between MSC and control for ARDS (OR = 0.64, 95% CI [0.34, 1.20], P = 0.17, and I 2 = 0%). In comparison with control, MSC could reduce the mortality of ARDS (OR = 0.66, 95% CI [0.46, 0.96], P = 0.03, and I 2 = 10%). Based on the results of our meta-analysis, the safety of MSC was demonstrated to be non-inferior to that of standard treatment, and MSC may reduce the mortality rate of ARDS. Though the heterogeneity in the main results was low (I 2

This study aimed to investigate the evolutionary profile (including diversity, activity, and abundance) of retrotransposons (RTNs) with long terminal repeats (LTRs) in ten species of Tetraodontiformes. These species, Arothron firmamentum, Lagocephalus sceleratus, Pao palembangensis, Takifugu bimaculatus, Takifugu flavidus, Takifugu ocellatus, Takifugu rubripes, Tetraodon nigroviridis, Mola mola, and Thamnaconus septentrionalis, are known for having the smallest genomes among vertebrates. Data mining revealed a high diversity and wide distribution of LTR retrotransposons (LTR-RTNs) in these compact vertebrate genomes, with varying abundances among species. A total of 819 full-length LTR-RTN sequences were identified across these genomes, categorized into nine families belonging to four different superfamilies: ERV (Orthoretrovirinae and Epsilon retrovirus), Copia, BEL-PAO, and Gypsy (Gmr, Mag, V-clade, CsRN1, and Barthez). The Gypsy superfamily exhibited the highest diversity. LTR family distribution varied among species, with Takifugu bimaculatus, Takifugu flavidus, Takifugu ocellatus, and Takifugu rubripes having the highest richness of LTR families and sequences. Additionally, evidence of recent invasions was observed in specific tetraodontiform genomes, suggesting potential transposition activity. This study provides insights into the evolution of LTR retrotransposons in Tetraodontiformes, enhancing our understanding of their impact on the structure and evolution of host genomes.

Nutritional supplements have been extensively used as health interventions for the elderly. However, with the spread of COVID-19, no consensus exists on whether nutritional interventions could improve muscle mass and physical activity in community-dwelling older adults. To conduct a systematic review and meta-analysis to explore the effects of different nutritional interventions on muscle mass and physical performance in the elderly, we searched PubMed, Web of Science, Elsevier, and Cochrane databases from their founding dates to December 2023. The meta-analysis was performed using RevMan5.3 software. Only randomized controlled trials (RCTs) were considered, and the overall mean difference (MD) or standardized mean difference (SMD) with 95% confidence interval (CI) was calculated. There were 33 studies comprising 3579 elderly persons meeting the inclusion criteria. Comprehensive analysis suggested that the intervention effect of fat-free mass (FFM), appendix skeletal muscle mass (ASMM), handgrip strength (HGS), gait speed, and short physical performance battery (SPPB) score was higher in the nutritional supplement group than in the control group. The results of subgroup analysis demonstrated that protein supplementation (SMD = 0.82, p < 0.0001) had an optimal effect on ASMM (SMD = 0.89, p < 0.0001) and FFM (MD = 2.09, p < 0.0001) in the elderly. Vitamin D supplementation (SMD = 0.52, p < 0.0001) had a marginal effect on ASMM, and energy supplementation (SMD = 0.39, p = 0.0005) had the lowest effect. Moreover, nutritional interventions had the most significant impact on HGS (MD = 1.06, p < 0.0001) and TUG (MD = 0.14, p < 0.0001) in individuals aged 65–75 years old, with positive effects on FFM (MD = 1.62, p < 0.0001) and HGS (MD = 0.82, p < 0.0001) when compared to healthy elderly individuals, and had greater effect on ASMM (SMD = 0.69, p < 0.0001) than on the elderly with sarcopenia. Nutritional supplements can enhance muscle mass and physical performance in the elderly, while protein is recommended for muscle function. The golden period for implementing nutritional interventions to improve muscle function is before the age of 75 years. However, the impact of nutritional interventions varies with age and population. Given the limited evidence on nutritional interventions, more detailed and high-quality studies are highly warranted in the future.

Single atom catalysts (SACs) suffer from the diffusion issues during catalytic process involving large molecules. Here the authors develop a topo-conversion strategy to prepare hollow mesoporous metal-nitrogen-carbon SACs which alleviates the choke point of poor mass transport of SACs.

Developing an environmental-friendly and highly active catalyst in transesterification for biodiesel production is of great importance for a more economic biodisel process. Herein, we reported that waste eggshells were used to adsorb Au(III) in water and convert the Au(III)-polluted eggshells into the functional nanocatalyst-CaO/Au for the transesterification reaction between soybean oil and methanol to the preparation of biodiesel. By coupling of CaO and Au nanoparticles, CaO/Au nanoparticles showed superior catalytic activity for the transesterification reaction between soybean oil and methanol. An optimum performance was observed over CaO/Au nanocomposites in a methanol-oil molar ratio at 12 : 1 with catalyst content of 1.0 wt% at 70 °C for 3 h. Besides, the catalytic activity of CaO/Au nanocatalyst was almost unchanged after recycling for 5 times and the yield of biodiesel still kept at 88.9%. The proof-of concept study provided us a sustainable method for utilization of waste eggshells to remedy the metal ions-polluted wastewater and the synthesis of functional nanocomposite for biodiesel production, show great potential application of waste eggshell in adsorption and catalytic reactions.

Abstract Converting CO2 emissions to valuable carbonaceous chemicals/fuels under mild conditions provides a sustainable way to maintain carbon balance and alleviate the energy shortage. Low‐dimensional material (LDM) supported single‐atom catalysts (SACs) have been attracted significant attention for electrochemical CO2 reduction reaction (ECR) in recent years. This is mainly because integrating the single‐atoms and LDMs can inherit the advantages of themselves and the synergy effects between them are potential to enhance the ECR performance. In this review, we summarized the strategies for synthesizing LDM supported SACs for ECR, and different LDM supported SACs for ECR have been briefly introduced. Moreover, some optimization strategies for LDM supported SACs towards CO2 electroreduction are highlighted. At the end of this review, the perspectives and challenges of LDM supported SACs for ECR are provided.

IntroductionFruit detection is one of the key functions of an automatic picking robot, but fruit detection accuracy is seriously decreased when fruits are against a disordered background and in the shade of other objects, as is commmon in a complex orchard environment.MethodsHere, an effective mode based on YOLOv5, namely YOLO-P, was proposed to detect pears quickly and accurately. Shuffle block was used to replace the Conv, Batch Norm, SiLU (CBS) structure of the second and third stages in the YOLOv5 backbone, while the inverted shuffle block was designed to replace the fourth stage’s CBS structure. The new backbone could extract features of pears from a long distance more efficiently. A convolutional block attention module (CBAM) was inserted into the reconstructed backbone to improve the robot’s ability to capture pears’ key features. Hard-Swish was used to replace the activation functions in other CBS structures in the whole YOLOv5 network. A weighted confidence loss function was designed to enhance the detection effect of small targets.ResultAt last, model comparison experiments, ablation experiments, and daytime and nighttime pear detection experiments were carried out. In the model comparison experiments, the detection effect of YOLO-P was better than other lightweight networks. The results showed that the module’s average precision (AP) was 97.6%, which was 1.8% higher than the precision of the original YOLOv5s. The model volume had been compressed by 39.4%, from 13.7MB to only 8.3MB. Ablation experiments verified the effectiveness of the proposed method. In the daytime and nighttime pear detection experiments, an embedded industrial computer was used to test the performance of YOLO-P against backgrounds of different complexities and when fruits are in different degrees of shade.DiscussionThe results showed that YOLO-P achieved the highest F1 score (96.1%) and frames per second (FPS) (32 FPS). It was sufficient for the picking robot to quickly and accurately detect pears in orchards. The proposed method can quickly and accurately detect pears in unstructured environments. YOLO-P provides support for automated pear picking and can be a reference for other types of fruit detection in similar environments.

The influence of NBR Shore hardness and PTFE elastic modulus on the sealing characteristics of step rod seals is analyzed in this paper based on the developed mixed elastohydrodynamic lubrication (EHL) model. The optimized selection studies of NBR Shore hardness and PTFE elastic modulus under different operating conditions are carried out based on the principle of minimizing net leakage and friction power loss. Results show that the Shore hardness of the NBR O-ring and, in particular, the elastic modulus of the PTFE ring has a significant effect on the sealing characteristics. Although the high values of these parameters result in high friction forces, they are beneficial for leakage control. To achieve both low leakage and low friction, it is recommended that high hardness and low modulus are selected for moderate-low pressure or high speed conditions, but low hardness and high modulus are selected for high pressure or low speed conditions.

Based on the theory of gas lubrication and elastic mechanics, a theoretical model of gas-elastic coupling lubrication of compliant foil face gas seal (CFFGS) is presented. The correlation between the film pressure and thickness of CFFGS and its effect on the flow field are investigated, and the differential effect of pressure conditions on the flow field and sealing performance is analyzed. Also explored the influence law of operating and structural parameters on sealing performance. Results show that CFFGS have stable and excellent leakage control performance, and the pressure forms has a differential effect on the coordination mechanism of film pressure-deformation-film thickness and the sealing performance. Moreover, compliant foil structure has a positive impact on the end-face adaptive capability and leakage control performance of the seal.

Glutinous rice has very low amylose content and is a good material for determining the structure and physicochemical properties of amylopectin. We selected 29 glutinous rice varieties and determined the amylopectin structure by high-performance anion exchange chromatography with the pulsed amperometric detection method. We also determined the correlation between amylopectin structure and the physicochemical properties of starch extracted from these varieties. The results showed that the amylopectin chain ratio Σdegree of polymerization (DP) ≤ 11/ΣDP ≤ 24 of 29 glutinous rice varieties was greater than 0.26, signifying that these varieties contained type II amylopectin. The results of the correlation analysis with gelatinization temperature showed that ΣDP 6–11 was significantly negatively correlated with the onset gelatinization temperature (GT) (TO), peak GT (TP), and conclusion GT (TC). Among the thermodynamic properties, ΣDP 12–24 was significantly positively correlated with To, Tp, and Tc, ΣDP 25–36 was significantly negatively correlated with To, Tp, and Tc, and ΣDP ≥ 37 had no correlation with the thermodynamic properties. The results of correlation analysis with RVA spectrum characteristic values showed that ΣDP 6–11 was significantly negatively correlated with hot paste viscosity (HPV), cool paste viscosity (CPV), consistency viscosity (CSV), peak time (PeT), and pasting temperature (PaT) among the Rapid Visco Analyzer (RVA) profile characteristics, ΣDP 12–24 was significantly positively correlated with HPV, CPV, CSV, PeT, and PaT, and ΣDP ≥ 25 had no correlation with the viscosity characteristics. Therefore, we concluded that the amylopectin structure had a greater effect on the TO, TP, TC, ΔH and peak viscosity, HPV, CPV, CSV, PeT, and PaT. The glutinous rice varieties with a higher distribution of short chains and a lower distribution of medium and long chains in the amylopectin structure resulted in lower GT and RVA spectrum characteristic values.

In order to investigate the influence of typical hypervelocity gas effects on the gas lubrication performance of compliant foil face gas seal (CFFGS) end surfaces, the gas–elastic coupling lubrication theory model of CFFGS is modified by considering the choked flow and inertia effect, and the lubrication performance is solved using the finite difference method. Based on the choking effect, the effect of hypervelocity choked flow on the pressure field and velocity field of the seal is analyzed, and the influence of operating parameters on the choked flow and the mechanism of choked flow on the change in dynamic lubrication and sealing performance are explored. Furthermore, based on the inertia effect, the effect of gas inertia force on the flow field, and the correlation law between the pressure field and velocity field under the influence of operating parameters are studied. Then, the relationship between the inertia effect and sealing performance are analyzed. The results show that choked flow increases sealing outlet pressure significantly, from 0.1 MPa to a maximum of 14.25 MPa, and the sealing outlet flow velocity decreases by up to 50 times. The increase in medium pressure and balance film thickness aggravate the choking effect, resulting in a 20% maximum increase in opening force and a 99.6% maximum decrease in leakage rate. In addition, the inertia effect causes obvious centrifugal movement of the gas flow. As result, the radial flow velocity reduces by up to 50%, and the pressure distribution varies widely. Especially under high rotational speed and high medium pressure, the inertia effect is enhanced to clearly reduce the opening force (max. decrement of 3.5%) and leakage rate (max. decrement of 23%).

In order to remedy the defects of single sensor in robustness, accuracy, and redundancy of target detection, this paper proposed a method for detecting obstacles in farmland based on the information fusion of a millimeter wave (mmWave) radar and a camera. Combining the advantages of the mmWave radar in range and speed measurement and the camera in type identification and lateral localization, a decision-level fusion algorithm was designed for the mmWave radar and camera information, and the global nearest neighbor method was used for data association. Then, the effective target sequences of the mmWave radar and the camera with successful data association were weighted to output, and the output included more accurate target orientation, longitudinal speed, and category. For the unassociated sequences, they were tracked as new targets by using the extended Kalman filter algorithm and were processed and output during the effective life cycle. Lastly, an experimental platform based on a tractor was built to verify the effectiveness of the proposed association detection method. The obstacle detection test was conducted under the ROS environment after solving the external parameters of the mmWave radar and the internal and external parameters of the camera. The test results show that the correct detection rate of obstacles reaches 86.18%, which is higher than that of a single camera with 62.47%. Furthermore, through the contrast experiment of the sensor fusion algorithms, the detection accuracy of the decision level fusion algorithm was 95.19%, which was higher than 4.38% and 6.63% compared with feature level and data level fusion, respectively.

The present study reassessed the effectiveness of the Integrated Model of Advice-giving with participants of varying levels of need for cognition (NFC) and different communication styles (high- and low-context communication styles). Participants (N = 828) were randomly assigned to read one of 33 versions of conversation in which they received advice from a friend. Results showed that NFC moderated the effect of presence of emotional support on recipients’ evaluations of facilitation of coping. Communication styles moderated the effect of presence of emotional support on recipients’ evaluation of facilitation of coping and their intention to implement advice.

Urban heatwaves increase residential health risks. Identifying urban residential sensitivity to heatwave risks is an important prerequisite for mitigating the risks through urban planning practices. This research proposes a new paradigm for urban residential sensitivity to heatwave risks based on social media Big Data, and describes empirical research in five megacities in China, namely, Beijing, Nanjing, Wuhan, Xi’an and Guangzhou, which explores the application of this paradigm to real-world environments. Specifically, a method to identify urban residential sensitive to heatwave risks was developed by using natural language processing (NLP) technology. Then, based on remote sensing images and Weibo data, from the perspective of the relationship between people (group perception) and the ground (meteorological temperature), the relationship between high temperature and crowd sensitivity in geographic space was studied. Spatial patterns of the residential sensitivity to heatwaves over the study area were characterized at fine scales, using the information extracted from remote sensing information, spatial analysis, and time series analysis. The results showed that the observed residential sensitivity to urban heatwave events (HWEs), extracted from Weibo data (Chinese Twitter), best matched the temporal trends of HWEs in geographic space. At the same time, the spatial distribution of observed residential sensitivity to HWEs in the cities had similar characteristics, with low sensitivity in the urban center but higher sensitivity in the countryside. This research illustrates the benefits of applying multi-source Big Data and intelligent analysis technologies to the understand of impacts of heatwave events on residential life, and provide decision-making data for urban planning and management.

Metal-organic frameworks (MOFs) nanosheets have attracted great attention in recent years due to their unprecedented properties. However, the synthesis of MOF nanosheets with controllable thickness still remains a challenge. In this work, a series of MOF nanosheets, such as CuBDC (BDC = 1, 4-benzenedicarboxylate), CoNDC (NDC = naphthalene-2, 6-dicarboxylate), CoBPDC (BPDC = biphenyl-4,4'-dicarboxylate), NiBDC and ZnTCPP (TCPP = tetrakis(4-carboxyphenyl)porphyrin) were successfully synthesized by using a metal hydroxide precursor approach. Importantly, the thicknesses of the obtained MOF nanosheets can be well-regulated by controlling the conversion rate of the metal hydroxides. As a proof-of-concept application, the obtained CuBDC nanosheets were used as the catalyst for olefin epoxidation, which showed much higher catalytic activity compared to the bulk crystals. This work provides an alternative method for the synthesis of various MOF nanosheets, holding great potential for various promising applications.

As the importance of failure is widely recognized, there is increasing research interest in the antecedents of learning from failure. Basing on affective event theory, the current study cast light on individuals’ cognition of error and proposed that employees with higher levels of error learning orientation tend to show more positive grieving after project failure, which in turn increases their learning from failure. Using a sample of 752 employees from 140 project teams, we found empirical evidence to support this theoretical model. Our results indicated that positive grieving mediated the relationship between error learning orientation and learning from failure. Besides, the relationship between error learning orientation and positive grieving is more positive for employees with lower levels of fear of face loss. Our findings help enrich the antecedents of learning from failure by shedding light on how and when error learning orientation matters. Theoretical and practical implications are discussed.

Social media data contains real-time expressed information, including text and geographical location. As a new data source for crowd behavior research in the era of big data, it can reflect some aspects of the behavior of residents. In this study, a text classification model based on the BERT and Transformers framework was constructed, which was used to classify and extract more than 210,000 residents’ festival activities based on the 1.13 million Sina Weibo (Chinese “Twitter”) data collected from Beijing in 2019 data. On this basis, word frequency statistics, part-of-speech analysis, topic model, sentiment analysis and other methods were used to perceive different types of festival activities and quantitatively analyze the spatial differences of different types of festivals. The results show that traditional culture significantly influences residents’ festivals, reflecting residents’ motivation to participate in festivals and how residents participate in festivals and express their emotions. There are apparent spatial differences among residents in participating in festival activities. The main festival activities are distributed in the central area within the Fifth Ring Road in Beijing. In contrast, expressing feelings during the festival is mainly distributed outside the Fifth Ring Road in Beijing. The research integrates natural language processing technology, topic model analysis, spatial statistical analysis, and other technologies. It can also broaden the application field of social media data, especially text data, which provides a new research paradigm for studying residents’ festival activities and adds residents’ perception of the festival. The research results provide a basis for the design and management of the Chinese festival system.

Composites incorporating metallic nanoparticles into metal-organic frameworks are potentially useful but controlling the nanoparticle spatial distribution is challenging. Here, the authors report a strategy that accomplishes this by using a metal oxide as both support and sacrificial template.

In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme.

Development of metal-free nanozymes has raised concern for their extensive applications in photocatalysis and sensing fields. As novel metal-free nanomaterials, covalent organic frameworks (COFs) have engendered intense interest in the construction of nanozymes due to their structural controllability and molecular functionality. The formation of the molecular arrangement by embedding orderly donor-acceptors (D-A) linked in the framework topology to modulate material properties for highly efficient enzyme mimicking activity is of importance but challenging. Here, a strong D-A type of COF was designed and synthesized by integrating electron donor units (pyrene) and electron acceptor units (phenanthroline), named Py-PD COF. Using experiments and theoretical calculations, the introduction of a phenanthroline ring endowed the Py-PD COF with a narrowed band gap, and efficient charge transfer and separation. Further, the Py-PD COF exhibited a superior light-responsive oxidase-mimicking characteristic under visible light irradiation, which could catalyze the oxidation of 3,3",5,5-tetramethylbenzidine (TMB) and give the corresponding evolution of color. The nanoenzymatic activity of the Py-PD COF was light-regulated, which offers a fascinating advantage because of its high efficiency and spatial controllability. Based on previously mentioned characteristics, an "on-off" sensing platform for the colorimetric analysis of isoniazid (INH) could be constructed with a good linear relationship (2-100 μM) and a low limit of detection (1.26 μM). This research shows that not only is Py-PD COF an environmentally friendly compound for the colorimetric detection of INH, but it is also capable of providing the interesting D-A type COF-based material for designing an excellent nanozyme. [ABSTRACT FROM AUTHOR]