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Clinical experience plays a vital role in the development of the professional identity (PI) of nursing students. China has applied a strict zero- COVID health policy in combating the COVID-19 pandemic since December 2019 and studies have been conducted in different places of China to explore PI development of nursing students during the pandemic time among the intern nursing students who are on clinical practices. This review study aims to synthesize the previous studies and provide a comprehensive picture of the impacts of the pandemic on the PI development of intern nursing students. Arksey and O'Malley's five-stage scoping review framework was used. Combinations of keywords were used to search relevant articles in both Chinese and English databases published from inception of the articles until the final search date (10 March 2022). The initially included articles were also appraised for their quality, and those that passed the appraisal were left for data analysis. The analytic results were cross-checked among the reviewers. Three themes emerged from the included studies: 1) the PI levels, 2) the impacts of personal and social factors of PL, and 3) the specific impact of the COVID-19 pandemic. The levels of students' PI ranged from 66%-80% of the total scores in PI instruments, almost the same levels as in pre-pandemic time, despite the elevated social image of nurses after the COVID-19 pandemic. There is no consensus about the impacts of most personal and social factors on students' PI across the studies. The impacts of COVID-19 on PI were both positive and negative. COVID-19 epidemic exerted complicated impacts on the PI of intern nursing students. While it is necessary to address the fear of the COVID-19 pandemic among intern nursing students, the pandemic may not be an opportunistic time to enhance the students' PI.

To evaluate the safety of each anti-TNF therapy for patients with rheumatoid arthritis (RA) and then make the best choice in clinical practice. We searched PUBMED, EMBASE, and the Cochrane Library. The deadline for retrieval is August 2021. The ORs, Confidence Intervals (CIs), and p values were calculated by STATA.16.0 software for assessment. 72 RCTs involving 28332 subjects were included. AEs were more common with adalimumab combined disease-modifying anti-rheumatic drugs (DMARDs) compared with placebo (OR = 1.60, 95% CI: 1.06, 2.42), DMARDs (1.28, 95% CI: 1.08, 1.52), etanercept combined DMARDs (1.32, 95% CI: 1.03, 1.67); certolizumab combined DMARDs compared with placebo (1.63, 95% CI: 1.07, 2.46), DMARDs (1.30, 95% CI: 1.10, 1.54), etanercept combined DMARDs (1.34, 95% CI: 1.05, 1.70). In SAEs, comparisons between treatments showed adalimumab (0.20, 95% CI: 0.07, 0.59), etanercept combined DMARDs (0.39, 95% CI: 0.15, 0.96), golimumab (0.19, 95% CI: 0.05, 0.77), infliximab (0.15, 95% CI: 0.03,0.71) decreased the risk of SAEs compared with golimumab combined DMARDs. In infections, comparisons between treatments showed adalimumab combined DMARDs (0.59, 95% CI: 0.37, 0.95), etanercept (0.49, 95% CI: 0.28, 0.88), etanercept combined DMARDs (0.56, 95% CI: 0.35, 0.91), golimumab combined DMARDs (0.51, 95% CI: 0.31, 0.83) decreased the risk of infections compared with infliximab combined DMARDs. No evidence indicated that the use of TNF-α inhibitors influenced the risk of serious infections, malignant tumors. In conclusion, we regard etanercept monotherapy as the optimal choice for RA patients in clinical practice when the efficacy is similar. Conversely, certolizumab + DMARDs therapy is not recommended. identifier PROSPERO CRD42021276176.

Background A cluster of pneumonia cases were reported by Wuhan Municipal Health Commission, China in December 2019. A novel coronavirus was eventually identified, and became the COVID-19 epidemic that affected public health and life. We investigated the psychological status and behavior changes of the general public in China from January 30 to February 3, 2020. Methods Respondents were recruited via social media (WeChat) and completed an online questionnaire. We used the State-Trait Anxiety Inventory, Self-rating Depression Scale, and Symptom Checklist-90 to evaluate psychological status. We also investigated respondents’ behavior changes. Quantitative data were analyzed by t -tests or analysis of variance, and classified data were analyzed with chi-square tests. Results In total, 608 valid questionnaires were obtained. More respondents had state anxiety than trait anxiety (15.8% vs 4.0%). Depression was found among 27.1% of respondents and 7.7% had psychological abnormalities. About 10.1% of respondents suffered from phobia. Our analysis of the relationship between subgroup characteristics and psychological status showed that age, gender, knowledge about COVID-19, degree of worry about epidemiological infection, and confidence about overcoming the outbreak significantly influenced psychological status. Around 93.3% of respondents avoided going to public places and almost all respondents reduced Spring Festival-related activities. At least 70.9% of respondents chose to take three or more preventive measures to avoid infection. The three most commonly used prevention measures were making fewer trips outside and avoiding contact (98.0%), wearing a mask (83.7%), and hand hygiene (82.4%). Conclusions We need to pay more attention to public psychological stress, especially among young people, as they are likely to experience anxiety, depression, and psychological abnormalities. Different psychological interventions could be formulated according to the psychological characteristics of different gender and age groups. The majority of respondents followed specific behaviors required by the authorities, but it will take time to observe the effects of these behaviors on the epidemic.

Chemicals underlying the floral aroma of dry teas needs multi-dimensional investigations. Green, black, and freeze-dried tea samples were produced from five tea cultivars, and only ‘Chunyu2’ and ‘Jinguanyin’ dry teas had floral scents. ‘Chunyu2’ green tea contained the highest content of total volatiles (134.75 μg/g) among green tea samples, while ‘Jinguanyin’ black tea contained the highest content of total volatiles (1908.05 μg/g) among black tea samples. The principal component analysis study showed that ‘Chunyu2’ and ‘Jinguanyin’ green teas and ‘Chunyu2’ black tea were characterized by the abundant presence of certain alcohols with floral aroma, while ‘Jinguanyin’ black tea was discriminated due to the high levels of certain alcohols, esters, and aldehydes. A total of 27 shared volatiles were present in different tea samples, and the contents of 7 floral odorants in dry teas had correlations with those in fresh tea leaves (p < 0.05). Thus, the tea cultivar is crucial to the floral scent of dry tea, and these seven volatiles could be promising breeding indices.

Ammonia, a vital component in the synthesis of fertilizers, plastics, and explosives, is traditionally produced via the energy‐intensive and environmentally detrimental Haber–Bosch process. Given its considerable energy consumption and significant greenhouse gas emissions, there is a growing shift toward electrocatalytic ammonia synthesis as an eco‐friendly alternative. However, developing efficient electrocatalysts capable of achieving high selectivity, Faraday efficiency, and yield under ambient conditions remains a significant challenge. This review delves into the decades‐long research into electrocatalytic ammonia synthesis, highlighting the evolution of fundamental principles, theoretical descriptors, and reaction mechanisms. An in‐depth analysis of the nitrogen reduction reaction (NRR) and nitrate reduction reaction (NitRR) is provided, with a focus on their electrocatalysts. Additionally, the theories behind electrocatalyst design for ammonia synthesis are examined, including the Gibbs free energy approach, Sabatier principle, d‐band center theory, and orbital spin states. The review culminates in a comprehensive overview of the current challenges and prospective future directions in electrocatalyst development for NRR and NitRR, paving the way for more sustainable methods of ammonia production. This review delves into the decades‐long research into electrocatalytic ammonia synthesis, highlighting the evolution of fundamental principles, theoretical descriptors, and reaction mechanisms and paving the way for more sustainable methods of ammonia production.

Sjögren's syndrome is an autoimmune disease characterised by dry eyes and mouth, systemic features, and reduced quality of life. There are no disease-modifying treatments. A new biologic, ianalumab (VAY736), with two modes of suppressing B cells, has previously shown preliminary efficacy. This dose-finding trial aimed to assess the safety and efficacy of different subcutaneous doses of ianalumab in patients with moderate to severe primary Sjögren's syndrome. VAY736A2201 was a randomised, parallel, double-blind, placebo-controlled, phase 2b dose-finding study done in 56 centres in 19 countries. Patients aged 18–75 years with primary Sjögren's syndrome with moderate to severe disease activity (European Alliance of Associations for Rheumatology [EULAR] Sjögren's Syndrome Disease Activity Index [ESSDAI] score ≥6) and symptom severity (EULAR Sjögren's Syndrome Patient Reported Index score ≥5) were eligible. Participants were randomly assigned (1:1:1:1) to receive subcutaneous placebo or ianalumab (5 mg, 50 mg, or 300 mg) every 4 weeks for 24 weeks using a secure, online randomisation system. Randomisation was stratified by the ESSDAI score at baseline (≥10 or <10). Study personnel and patients were masked to treatment assignment. The primary outcome was the change in ESSDAI score from baseline to 24 weeks in all randomly assigned patients. Dose-related change in disease activity (ESSDAI) from baseline at week 24 was assessed by multiple comparison procedure with modelling analysis. Safety was measured in all patients who received at least one dose of study drug. This trial is registered with ClinicalTrials.gov, NCT02962895. Between June 27, 2017, and Dec 06, 2018, 293 patients were screened, 190 of whom were randomly assigned (placebo n=49, ianalumab 5 mg n=47, ianalumab 50 mg n=47, ianalumab 300 mg n=47). Statistically significant dose-responses were seen for overall disease activity (ESSDAI score) in four of the five dose-response models tested (p<0·025 in four models, p=0·060 in one model). The ESSDAI score decreased from baseline in all ianalumab groups, with the maximal ESSDAI score change from baseline observed in the ianalumab 300 mg group: placebo-adjusted least-squares mean change from baseline −1·92 points (95% CI −4·15 to 0·32; p=0·092). There were four serious adverse events in three patients considered treatment-related (pneumonia [n=1] and gastroenteritis [n=1] in the placebo group; appendicitis plus tubo-ovarian abscess in the same patient in the ianalumab 50 mg group). The study met its primary objective, showing a dose-related decrease in disease activity as measured by ESSDAI at week 24. Overall, ianalumab was well tolerated and safe, with no increase in infections. To our knowledge, this is the first large, randomised, controlled trial in primary Sjögren's syndrome that met its primary endpoint, and its results mean there is potential for more studies of this mechanism in the future. Novartis.

At present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growth information. The scientific and rational design of agricultural robots plays a huge role in planting and production efficiency, however, the factors affecting their design are complex and ambiguous, so it is necessary to use a rational evaluation system to make a preferential decision among multiple design options. In order to reduce the subjectivity and blindness of program selection in the process of agricultural robot design, make the decision more objective and reasonable, and thus enhance the practicality and scientificity of the program, a new comprehensive evaluation method based on user requirements is proposed. First, after researching and interviewing users and farming operations, obtaining raw information on requirements, using the Kano model to classify the requirements and establishing an evaluation index system. Secondly, the combination of hierarchical analysis(AHP) and entropy weighting method is used to assign weights to the evaluation index system, calculate the weight value and importance ranking of each index, and carry out various program designs based on the ranking. Finally, the VIKOR method was applied to evaluate and rank the design solutions. The new evaluation method can better complete the preferential decision of the agricultural robot design scheme and get a more perfect design scheme, which reduces the influence of human subjective thinking in the decision-making process. The method not only corrects the traditional evaluation method, but also effectively improves the accuracy and comprehensiveness of the design evaluation process. It also provides a reference for designers to preferably select design solutions and promotes the development of small mobile machines in the context of smart agriculture.

To solve the problem that the rotor estimation accuracy is greatly affected by parameter nonlinearity and high frequency oscillation, when the synchronous reluctance motor adopts the sensorless control system.This article proposes a new flux saturation model considering cross saturation effect applied to sensorless control of SynRM. The magnetic flux saturation data obtained by the hysteresis voltage injection method is used to estimate the model parameters, and the motor model under accurate magnetic flux saturation is obtained. The proposed magnetic flux saturation model is applied to the position sensorless control system of the synchronous reluctance motor. The proposed magnetic flux saturation model can effectively represent cross saturation and satisfy the reciprocity condition, and solve the nonlinear relationship between SynRM current and flux linkage. Finally, builting an experimental platform to verify the validity and correctness of the theoretical and experimental analysis.

As the cyclable sodium ions' primary suppliers, O3‐type layer‐structured manganese‐based oxides are recognized as one of the most competitive cathode candidates for sodium‐ion batteries. Suffering from complex structural transformations and transition metal migration during the sodium intercalation/deintercalation process, particularly at high voltage, the energy density and lifespan cannot satisfy the increasing demand. The orbital and electronic structure of the octahedral center metal element plays an important role in maintaining the octahedral structural integrity and improving the Na+ diffusivity by the introduced heterogeneous [Me–O] (Me: transition metals) chemical bonding. Herein, inspired by the 4f and 5d orbital bonding possibility from the abundant configuration of extranuclear electrons and large ion radius, O3‐type Na[La0.01Ni0.3Mn0.54Cu0.1Ti0.05]O2 was synthesized with a nearly single crystal structure. Based on the experimental and computational results, the introduced heterogeneous [La–O] chemical bond with larger bond strength can not only ensure the stability of the lattice oxygen framework and the reversibility of oxygen redox but also optimize the oxygen local electronic structure resulting from La 5d and O 2p orbital mixing due to O 2p → La 5d charge transfer. It delivers an optimal electrochemical performance with a high energy density and cycling lifespan. The large‐sized nearly single‐crystallized particles have a high ion diffusion without hindering by the crystal gap. Meanwhile, the uneven sodium ions' insertion and extraction inside the particles with oxygen release will be alleviated with varying degrees of success. It can efficiently increase the cycling lifespan by alleviating electrolyte side reactions.

Noise and vibration signal classification can be applied to fault diagnosis in mechanical and electronic systems such as electric vehicles. Traditional signal classification technology uses signal time and frequency domain characteristics as the identification basis. This study proposes a technique for visualizing sound signals using the Wigner–Ville distribution (WVD) method to extract vibration signal characteristics and artificial neural networks as the signal classification basis. A brushless motor is used as the machinery power source to verify the feasibility of this method to classify different signal vibration characteristics. In this experimental work, six states in various brushless motor revolutions were deliberately designed for measuring vibration signals. The brushless motor vibration signal is imaged using the WVD analysis method to extract the vibration signal characteristics. Through the WVD method, the brushless motor data is converted, and the YOLO (you only look once) deep coiling machine neural method is used to identify and classify the brushless motor WVD images. The Wagener analysis method parameters and recognition rates are discussed, thereby improving accurate motor fault diagnostic capabilities. This research provides a method for fault diagnosis that can be accurately performed without dismantling the brushless motor. The proposed approach can improve the reliability and stability of brushless motor applications.