Sleep Quality and Emotional Adaptation among Freshmen in Elite Chinese Universities during Prolonged COVID-19 Lockdown:The Mediating Role of Anxiety Symptoms

Under the effects of COVID-19 and a number of ongoing lockdown tactics,anxiety symptoms and poor sleep quality have become common mental health issues among college freshmen and are intimately related to their emotional adaptation.To explore this connection,this study gathered data from a sample of 256 freshmen enrolled in an elite university in China in September 2022.The association between sleep quality,anxiety symptoms,and emotional adaptation was clarified using correlation analysis.Additionally,the mediating function of anxiety symptoms between sleep quality and emotional adaptation was investigated using a structural equation model.The results reveal that:(1)Chinese elite university freshmen who were subjected to prolonged lockdown had poor sleep quality and mild anxiety symptoms;(2)a significant positive correlation between poor sleep quality and anxiety symptoms was identified;(3)anxiety symptoms were found to have a significant negative impact on emotional adaptation;(4)poor sleep quality had a negative impact on emotional adaptation through anxiety symptoms.This research makes a valuable contribution by offering insights into the intricate relationship between sleep quality and emotional adaptation among freshmen in elite Chinese universities during prolonged lockdown conditions,and it is beneficial for schools and educators to further improve school schedules and psychological health initiatives.

A Spectral Convolutional Neural Network Model Based on Adaptive Fick’s Law for Hyperspectral Image Classification

Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification.

Effect of bowel rehabilitative therapy on structural adaptation of remnant small intestine: animal experiment

AIM: To investigate the individual and the combined effects of glutamine, dietary fiber, and growth hormone on the structural adaptation of the remnant small bowel. METHODS: Forty-two adult male Sprague-Dawley rats underwent 85% mid-small bowel resection and received total parenteral nutrition (TPN) support during the first three postoperational days.From the 4th postoperational day, animals were randomly assigned to receive 7 different treatments for 8 days: TPNcon group, receiving TPN and enteral 20 g x L(-1) glycine perfusion; TPN+Gln group, receiving TPN and enteral 20 g x L(-1) glutamine perfusion; ENcon group, receiving enteral nutrition (EN) fortified with 20 g x L(-1) glycine; EN+Gln group, enteral nutrition fortified with 20 g x L(-1) glutamine; EN+Fib group, enteral nutrition and 2 g x d(-1) oral soybean fiber; EN+GH group, enteral nutrition and subcutaneous growth hormone (GH) (0.3 IU) injection twice daily; and ENint group, glutamine-enriched EN, oral soybean fiber, and subcutaneous GH injection. RESULTS: Enteral glutamine perfusion during TPN increased the small intestinal villus height (jejunal villus height 250 microm +/- 29 microm in TPNcon vs 330 microm +/- 54 microm in TPN+Gln, ileal villus height 260 microm +/- 28 microm in TPNcon vs 330 microm +/- 22 microm in TPN+Gln, P【0.05) and mucosa thickness (jejunal mucosa thickness 360 microm +/- 32 microm in TPNcon vs 460 microm +/- 65 microm in TPN+Gln, ileal mucosa thickness 400 microm +/- 25 microm in TPNcon vs 490 microm +/- 11 microm in TPN+Gln,P【 0.05) in comparison with the TPNcon group. Either fiber supplementation or GH administration improved body mass gain (end body weight 270 g +/- 3.6g in EN+Fib, 265.7 g +/- 3.3 g in EN+GH, vs 257 g +/- 3.3 g in ENcon, P【 0.05), elevated plasma insulin-like growth factor (IGF-I) level (880 microg x L(-1). 52 microg x L-(-1) in EN+Fib,1200 microg x L(-1). 96 microg x L-(-1) in EN +/- GH, vs 620 microg x L(-1).43 microg x L-(-1) in ENcon, P【 0.05), and increased the villus height (jejunum 560 microm +/- 44 microm in EN +/- Fib, 530 microm +/- 30 microm in EN +/- GH, vs 450 microm +/- 44 microm in ENcon, ileum 400 microm +/- 30 microm in EN+Fib, P【0.05) and the mucosa thickness (jejunum 740 microm +/- 66 microm in EN +/- Fib, 705 microm +/- 27 microm in EN +/- GH, vs 608 microm +/- 58 microm in ENcon, ileum 570 microm +/- 27 microm in EN +/- Fib, 560 microm +/- 56 microm in remnant jejunum and ileum. Glutamine-enriched EN produced little effect in body mass, plasma IGF-I level, and remnant small bowel mucosal structure. The ENint group had greater body mass (280 g +/- 2.2g), plasma IGF-I level (1450 microg x L(-1). 137 microg x L-(-1)), and villus height (jejunum 620 microm +/- 56 microm, ileum 450 microm +/- 31 microm) and mucosal thickness (jejunum 800 microm +/- 52 microm, ileum 633 microm +/- 33 microm) than those in ENcon, EN+Gln (jejunum villus height and mucosa thickness 450 microm +/- 47 microm and 610 +/- 63 microm, ileum villus height and mucosa thickness 330 microm +/- 39 microm and 500 microm +/- 52 microm), EN+GH groups (P【0.05), and than those in EN+Fib group although no statistical significance was attained. CONCLUSION: Both dietary fiber and GH when used separately can enhance the postresectional small bowel structural adaptation. Simultaneous use of these two gut-trophic factors can produce synergistic effects on small bowel structural adaptation. Enteral glutamine perfusion is beneficial in preserving small bowel mucosal structure during TPN, but has little beneficial effect during EN.

Research on the effects of family care degree on stigma and psychosocial adaptation among the patients with Parkinson’s disease

Objective:This study aimed to investigate the status quo of family care degree,stigma and psychosocial adaptation of the patients with Parkinson’s disease(PD),and discuss the effects of family care degree on stigma and psychosocial adaptation among the patients with PD.Methods:This study was conducted between September 2018 and April 2019 on patients with PD who were admitted to a Ter tiary Grade A hospital in Dalian city.A total of 246 PD patients were investigated by convenience sampling method using self-designed general information questionnaire,along with family care index(APGAR),24-item Stigma Scale for Chronic Illness(SSCI),and Psychosocial Adjustment Scale(PAS)for PD.And patients were divided into two groups according to the level of family care degree and compared with stigma and psychosocial adaptation.Results:The total score of family care for patients with PD was 6.97±2.46,family function was good in 132 cases(53.7%),moderate barrier in 92 cases(37.4%),and severe barrier in 22 cases(8.9%).The scores of stigma and psychosocial adaptability and their dimensions in the group with high degree family care were higher than the low degree group.Conclusions:The overall level of family care for PD patients was poor.Improving family care degree can help patients with PD to reduce stigma and improve psychosocial adaptation.

HAL1 mediate salt adaptation in Arabidopsis thaliana

The yeast HAL1 gene was introduced into Arabidopsis thaliana by Agrobacterium tumefaciens-mediated transformation with vacuum infiltration under the control of CaMV 35S promoter. Thirty-three individual kanamycin resistant plants were obtained from 75,000 seeds. Southern blotting analysis indicated that HAL1 gene had been integrated into all of the transgenic plants’ genomes. The copy number of HAL1 gene in transgenic plants was mostly 1 to 3 by Southern analysis. Phenotypes of transgenic plants have no differences with wild type plants. several samples of transformants were self-pollinated, and progenies from transformed and non-transformed plants (controls) were evaluated for salt tolerance and gene expression. Measurement of concentrations of intracellular K+ and Na+ showed that transgenic lines were able to retain less Na+ than that of the control under salt stress. Results from different tests indicated the expression of HAL1 gene promotes a higher level of salt tolerance in vivo in the transgenic Arabidopsis plants.

The Impact of Climate Change on Rainfall Patterns in Ghana:A Zoning Adaptation Strategy through Developing Agroforestry

As a developing country in Africa,the effect of climate change is one of the sufferings of Ghana.The effect is much felt in rainfall variability because of the country over reliance on rainfall for agriculture.While various researches have studied the impact of climate change in Ghana,few among them have extended to its impact on rainfall pattern across all the ecological zones in the country.The trends in the rainfall from seven selected meteorological stations across all the ecological zones were analyzed using data from the NASA satellite.The Mann-Kendall and Sen’s Slope Test were used for the analysis.The study found decreasing trend in most of the monthly and yearly rainfall pattern across the ecological zones,and suggested cashew agroforestry as a zoning adaptation strategy.

Akreos Adapt折叠式人工晶体植入的初步临床观察

目的观察Akreos Adapt人工晶体使用的临床效果,评价其安全性和有效性。方法回顾分析我院植入Akreos Adapt人工晶体患者52例(52眼),随访观察视力、手术并发症及晶体居中性。结果裸眼视力≥0.7者48例,占93.3%,无严重手术并发症发生,晶体具有良好的居中性。结论Akreos Adapt人工晶体植入简单、安全、有效,具有良好的视觉质量。

ADASYN与类别逆比例加权法在阿尔茨海默病不平衡数据中的应用

目的利用自适应合成抽样(adaptive synthetic sampling,ADASYN)与类别逆比例加权法处理类别不平衡数据,结合分类器构建模型对阿尔茨海默病(alzheimer′s disease,AD)患者疾病进程进行分类预测。方法数据源自阿尔茨海默病神经影像学计划(Alzheimer′s disease neuroimaging initiative,ADNI),经随机森林填补缺失值,弹性网络筛选特征子集后,利用ADASYN与类别逆比例加权法处理类别不平衡数据。分别结合随机森林(random forest,RF)、支持向量机(support vector machine,SVM)构建四种模型:ADASYN-RF、ADASYN-SVM、加权随机森林(weighted random forest,WRF)、加权支持向量机(weighted support vector machine,WSVM),与RF、SVM比较分类性能。模型评价指标为宏观平均精确率(macro-average of precision,macro-P)、宏观平均召回率(macro-average of recall,macro-R)、宏观平均F1值(macro-average of F1-score,macro-F1)、准确率(accuracy,ACC)、Kappa值和AUC(area under the ROC curve)。结果ADASYN-RF的分类性能最优(Kappa值为0.938,AUC为0.980),ADASYN-SVM次之。利用ADASYN-RF预测得到的重要分类特征分别为CDRSB、LDELTOTAL、MMSE,在临床上均可得到证实。结论ADASYN与类别逆比例加权法都能辅助提升分类器性能,但ADASYN算法更优。

Dynamics and adaptive control of a dual-arm space robot with closed-loop constraints and uncertain inertial parameters

A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.

Adaptive Proportional-Derivative Sliding Mode Control Law With Improved Transient Performance for Underactuated Overhead Crane Systems

In this paper, an adaptive proportional-derivative sliding mode control(APD-SMC) law, is proposed for 2D underactuated overhead crane systems. The proposed controller has the advantages of simple structure, easy to implement of PD control, strong robustness of SMC with respect to external disturbances and uncertain system parameters, and adaptation for unknown system dynamics associated with the feedforward parts. In the proposed APD-SMC law, the PD control part is used to stabilize the controlled system, the SMC part is used to compensate the external disturbances and system uncertainties,and the adaptive control part is utilized to estimate the unknown system parameters. The coupling behavior between the trolley movement and the payload swing is enhanced and, therefore, the transient performance of the proposed controller is improved.The Lyapunov techniques and the La Salle's invariance theorem are employed in to support the theoretical derivations. Experimental results are provided to validate the superior performance of the proposed control law.

Adaptive synchronization of a critical chaotic system

This paper further investigates the synchronization problem of a new chaotic system with known or unknown system parameters. Based on the Lyapunov stability theory,a novel adaptive control law is derived for the synchronization of a new chaotic system with known or unknown system parameters.Theoretical analysis and numerical simulations showthe effectiveness and feasibility of the proposed schemes.

High-frequency compensation for seismic data based on adaptive generalized S transform

The low-pass fi ltering eff ect of the Earth results in the absorption and attenuation of the high-frequency components of seismic signals by the stratum during propagation.Hence,seismic data have low resolution.Considering the limitations of traditional high-frequency compensation methods,this paper presents a new method based on adaptive generalized S transform.This method is based on the study of frequency spectrum attenuation law of seismic signals,and the Gauss window function of adaptive generalized S transform is used to fi t the attenuation trend of seismic signals to seek the optimal Gauss window function.The amplitude spectrum compensation function constructed using the optimal Gauss window function is used to modify the time-frequency spectrum of the adaptive generalized S transform of seismic signals and reconstruct seismic signals to compensate for high-frequency attenuation.Practical data processing results show that the method can compensate for the high-frequency components that are absorbed and attenuated by the stratum,thereby eff ectively improving the resolution and quality of seismic data.

Climate change impact in the Western Himalaya:people's perception and adaptive strategies

The Himalaya represents a vast mountain system and globally valued for its significant role in regulation of global as well as regional climate that has direct impact on biodiversity and ecosystem services crucial for sustenance of millions of people in Himalaya and adjoining areas. However, mountain regions worldwide are impacted by climate change and at the same time represent distinctive area for the assessment of climate related impacts. Climate change impacts in Himalayan region have its implications on food production, natural ecosystems,retreat of glacier, water supply, human and animal health and overall human well being. The livelihood and food security of the people inhabited in region largely depend on climate sensitive sectors i.e.agriculture, livestock, forestry and their interlinkages with each other, and has the potential to break down food and nutritional security as well as livelihood support systems. People's perception and understanding of climate can be an important asset when it comes to adaptation to climate change impact;however it is not taken into consideration for the development of policy design and implementation of modern mitigation and adaptation strategies by governments and other civil society organizations.The knowledge of local people and farming communities for rural landscape management and sustainable use of bioresources is gaining credence as a key strategy to cope up with the climate change.Therefore, the present study analyzes the indigenous knowledge of local people and their perceptions on climate change, and also documented adaptation approaches at local level in mountain ecosystem of western Himalaya. The study could be useful to policy makers to design appropriate adaptation strategies to cope up with the impacts of climate change.

Adaptive Maxwell’s Equations Derived Optimization and Its Application in Antenna Array Synthesis

In this paper,a self-adaptive method for the Maxwell’s Equations Derived Optimization(MEDO)is proposed.It is implemented by applying the Sequential Model-Based Optimization(SMBO)algorithm to the iterations of the MEDO,and achieves the automatic adjustment of the parameters.The proposed method is named as adaptive Maxwell’s equations derived optimization(AMEDO).In order to evaluate the performance of AMEDO,eight benchmarks are used and the results are compared with the original MEDO method.The results show that AMEDO can greatly reduce the workload of manual adjustment of parameters,and at the same time can keep the accuracy and stability.Moreover,the convergence of the optimization can be accelerated due to the dynamical adjustment of the parameters.In the end,the proposed AMEDO is applied to the side lobe level suppression and array failure correction of a linear antenna array,and shows great potential in antenna array synthesis.

Research of robust adaptive trajectory linearization control based on T-S fuzzy system

A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.

Adaptive Phase Matching in Grover’s Algorithm

When the Grover’s algorithm is applied to search an unordered database, the successful probability usually decreases with the increase of marked items. In order to solve this problem, an adaptive phase matching is proposed. With application of the new phase matching, when the fraction of marked items is greater , the successful probability is equal to 1 with at most two Grover iterations. The validity of the new phase matching is verified by a search example.

Stealth Adapted Viruses: A Bridge between Molecular Virology and Clinical Psychiatry

Cytopathic “stealth-adapted” viruses bypass the cellular immune defense mechanisms because of molecular deletion or mutation of critical antigen coding genes. They, therefore, do not provoke the inflammatory reaction typical of infections with the conventional viruses from which stealth adapted viruses are derived. Stealth adapted viruses establish persistent, systemic virus infections, which commonly involve the brain. The brain damage can cause major mood and cognitive disorders, fatigue, seizures and various manifestations of an impaired autonomic nervous system. Symptoms can also result from: 1) induced autoimmunity, 2) antibody formation against virus antigens, 3) virus-induced cellular damage to non-brain tissues and 4) induced heightened overall immune reactivity, such that normally unrecognized components of the virus begin to become targeted by the cellular immune system. This last mechanism is relevant to the reported neurological and psychiatric adverse effects of vaccination in certain individuals. It is also appropriate to consider the infectious component of stealth adapted virus infections since family members and others may be at risk for becoming infected.

Assimilating temperature and salinity profiles using Ensemble Kalman Filter with an adaptive observation error and T-S constraint

Temperature （T） and salinity （S） profiles from conductivity-temperature-depth data collected during the Northern South China Sea Open Cruise from August 16 to September 13, 2008 are assimilated using Ensemble Kalman Filter （EnKF）. An adaptive observational error strategy is used to prevent filter from diverging. In the meantime, aiming at the limited improvement in some sites caused by the T and S biases in the model, a T-S constraint scheme is adopted to improve the assimilation performance, where T and S are separately updated at these locations. Validation is performed by comparing assimilated outputs with independent in situ data （satellite remote sensing sea level anomaly （SLA）, the OSCAR velocity product and shipboard ADCP）. The results show that the new EnKF assimilation scheme can significantly reduce the root mean square error （RMSE） of oceanic T and S compared with the control run and traditional EnKF. The system can also improve the simulation of circulations and SLA.

An h-adaptive Discontinuous Galerkin Method for Laminar Compressible Navier-Stokes Equations on Curved Mesh

An h-adaptive method is developed for high-order discontinuous Galerkin methods(DGM)to solve the laminar compressible Navier-Stokes(N-S)equations on unstructured mesh.The vorticity is regarded as the indicator of adaptivity.The elements where the vorticity is larger than a pre-defined upper limit are refined,and those where the vorticity is smaller than a pre-defined lower limit are coarsened if they have been refined.A high-order geometric approximation of curved boundaries is adopted to ensure the accuracy.Numerical results indicate that highly accurate numerical results can be obtained with the adaptive method at relatively low expense.

A Comment on Language Is a Complex Adaptive System: Position Paper

Language not only functions as a communication tool,it has fundamental functions.People’s social interaction and their past experience can affect people’s choice of language,as language is a complex,adaptive system.The paper tries to comment on"A comment on Language Is a Complex Adaptive System:Position Paper"from several aspects to conclude that Language Is a Complex Adaptive System:Position Paper is a comprehensive,creative and influential academic paper which is characteristic of high originality,well-compact organization,detailed literature review.