Contraction of Heat Shock Protein 70 Genes Uncovers Heat Adaptability of Ostrea denselamellosa

The milin oyster Ostrea denselamellosa is a live-bearing species with a sharp decline in the natural population.Unlike other oysters,O.denselamellosa lives in the subtidal zone and its adaptability to heat,salinity,etc.is different from most other oys-ters.Heat shock proteins 70(HSP70)are a family of conserved ubiquitously expressed heat shock proteins which are produced in re-sponse to stressful conditions,especially heat.In this study,we identified Hsp70 genes through bioinformatic analysis in five species of oyster.Among them,O.denselamellosa holds the fewest number of Hsp70 genes,which may be one of the reasons why O.den-selamellosa cannot tolerate high temperatures.The conserved motifs and gene structures of Hsp70B2 sub-family and other types of Hsp70 in O.denselamellosa were different from that of Hspa12 sub-family,which may be due to performing necessary multiple phy-siological functions.Transcription profile analysis for Hsp70 genes of O.denselamellosa indicated that gills play an important role in responding to multiple external challenges.In addition,synteny analysis of Hsp70 genes among O.denselamellosa,O.edulis and Cras-sostrea ariakensis showed that Hsp70 genes in genus of Ostrea genome might have evolved from a common ancestor with genus of Crassostrea.In short,our results lay the foundation for further investigation of the evolution of O.denselamellosa Hsp70 genes and heat adaptability.

Relationship between family cohesion/adaptability and postpartum depressive symptoms:A single-center retrospective study

BACKGROUND Depression is the most common mental illness in postpartum mothers,and the etiology of postpartum depression remains poorly understood.Over the past several decades,studies have reported that postpartum depression is caused by multiple factors,such as genetic,psychological,pregnancy,and environmental factors,with the family environment being an important environmental factor.The theory of family cohesion and adaptability put forward by Olson is a classic model that describes the level of family function.However,to date,this model has not been examined regarding its applicability to patients with postpartum depression.AIM To investigate the relationship between family cohesion and adaptability and the risk of postpartum depressive symptoms.METHODS We retrospectively analyzed 1446 patients admitted to the postpartum healthcare clinic of the Affiliated Foshan Maternity and Child Healthcare Hospital from April 2021 to December 2021.Patients were grouped according to whether postpartum depression symptoms were reported(symptoms,n=454;no symptoms,n=992).All patients completed the Edinburgh Postpartum Depression Scale and the Chinese version of the Family Cohesion and Adaptability Assessment Scale II.Baseline and clinical data were compared between groups.Univariate regression analysis was used to investigate the association between different types of family cohesion and postpartum depressive symptoms and the association between different family adaptability types and postpartum depressive symptoms.RESULTS After adjusting for age,education,occupation,gravidity,parity,and mode of delivery,disengaged[adjusted odds ratio(AOR)=3.36,95%CI:1.91-5.91],and separated(AOR=1.97,95%CI:1.34-2.90)family cohesion types showed a higher risk of postpartum depression than the connection type,whereas the enmeshed type(AOR=0.38,95%CI:0.28-0.51)protected against postpartum depressive symptoms.Rigid(AOR=4.41,95%CI:3.02-6.43)and structured families(AOR=1.88,95%CI:1.34-2.63)had a higher risk of postpartum depressive symptoms than flexible families,whereas chaotic families(AOR=0.35,95%CI:0.24-0.51)protected against postpartum depressive symptoms.CONCLUSION Family cohesion and adaptability are influencing factors for postpartum depressive symptoms,with higher family cohesion and adaptability being associated with a lower risk of postpartum depressive symptoms.

Study on Adaptability of Introduced Pear Varieties

[Objectives]To study the adaptability of introduced pear.[Methods]Five pear varieties,"Aidang"pear,"Taiwan Zaomi"pear,"Cuiguan"pear,"Tianjin Yali"pear and"Zaosheng Xinshui"pear,were introduced.Then,using these five varieties,the phenology of pear trees,various characters of fruit,stress resistance(heat tolerance and cold tolerance)of varieties were studied.[Results]The plants of 5 varieties of pear trees grew fast and were robust;in late March,it went into the flowering period;"Aidang"pear fruit had a certain number of stone cells;"Taiwan Zaomi"pear had the highest sweetness;"Cuiguan"pear had the largest fruit;these five varieties of pear trees had good water resistance,heat resistance and cold resistance.[Conclusions]This study can provide a reference for the introduction of pear trees,and can also provide a practical basis for the large-scale planting of pear trees.

Effects of sports on school adaptability, resilience and cell phone addiction tendency of high school students

BACKGROUND Sport help promote healthy physical and mental development of high school students.To date,there have been few studies on the effect of sport on school adaptability,resilience and cell phone addiction tendency of high school students.AIM To explore the effects of sports on school adaptability,resilience and cell phone addiction of high school students.METHODS A stratified random sampling method was used to select 600 students from two high schools in Lhasa,and Physical Activity Rating Scale,School Adjustment Scale for High School Students,Chinese Adolescents Resilience Scale,and Mobile Phone Addiction Index were used for field questionnaire survey.RESULTS Sport was positively correlated with school adaptability and resilience(P<0.01),school adaptability was positively correlated with resilience(P<0.01)and cell phone addiction was negatively correlated with sports,school adaptability and resilience(P<0.01).The direct effect of sport on cell phone addiction was significant(P<0.001),accounting for 20.51%of the total effect.The mediating effect of school adaptability on sport and cell phone addiction was significant(P<0.001),accounting for 17.38%and 35.36%of the total effect value,respectively.School adjustment and resilience had a significant chain-mediated effect on sport and cell phone addiction(P<0.001),accounting for 26.75%of the total effect.CONCLUSION Sport affected the cell phone addiction tendency of senior high school students through the mediating effect of school adaptability and resilience,and through the chain mediation effect of both.

Optimization Strategy for Passive Form Design of Architectural Grey Space under the Background of Climate Adaptability

Taking the bottom grey space with great influence on outdoor thermal comfort as the research object,this paper summarizes the morphological characteristics and climate response methods of two types of bottom grey space:overhead grey space and canopy grey space.The spatial form indexes that greatly affect the ecological performance of architectural grey space such as ventilation,shading,etc.are discussed,and two passive spatial form indexes of spatial scale and location orientation are studied.According to the research of related scholars and literature summary,the optimization strategies for passive form design of architectural grey space based on climate adaptability are put forward,which will provide a reference for the climate adaptive design of architectural grey space,and helps to improve the outdoor thermal environment from the micro scale and create a better living environment.

Adaptability analysis and optimization of log suite for uncased wellbores of shale gas reservoirs:A case study of Sichuan Basin,China

Significant progress has been made in the exploration and development of unconventional gas resources in China since the beginning of the 21st century.With a rapid increase in yield,the exploration and development of shale gas have been upgraded to a level of national strategy.Logging is one of the core technologies in gas exploration and development.However,logging technologies face the challenges of complex geological conditions and well casing environment,high temperature,high pressure,and strong heterogeneity.Despite the rich experience accumulated,unified understanding and implementation specifications are yet to be established for shale gas well logging.Given the analysis and comparison of the effectiveness and adaptability of logging technologies at different stages of shale gas exploration and development for the Sichuan Basin,this study optimizes the log suite to meet the demand for highefficiency exploration and development of shale gas.According to the adaptability analysis of shale gas log suite,the mandatory logging items of exploratory wells should include caliper log(CAL),natural gamma ray spectrometry(NGS)log,spontaneous potential(SP)log,directional survey,borehole compensated sonic log,litho-density log(LDL),compensated neutron log(CNL),dual laterologmicrospherically focused log/dual induction-laterolog log/array induction log,temperature log,elemental capture spectroscopy(ECS)log,formation microimager(FMI)log,and array sonic log.The log suite of appraisal wells is almost the same as that for exploratory wells,excluding the ECS log and microresistivity scanning imaging.Meanwhile,for the logging of horizontal/highly-deviated holes,the log suite of vertical wells should be referred to according to specific well conditions.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Operations Improvement Function and Organisational Adaptability of Petroleum Tank Farms in South-South, Nigeria

The study examined the nexus between operations improvement function (dimensioned by contingency planning, benchmarking and continuous improvement processes) and organisational adaptability of Petroleum tank farms in South-South, Nigeria. The contingency theory and the theory of routine dynamics underpinned the study, and positivism was the underlying philosophy. The study adopted the cross-sectional survey through the use of questionnaire. 820 middle and top-level managers constituted the elements of the population, and the Krejcie & Morgan’s formula was used to determine the sample size of 262 respondents. Structural Equation Modeling was deployed to test the hypotheses at a 0.05 significance level. The results showed that contingency planning;benchmarking and continuous improvement processes all have a significant positive relationship with organisational adaptability of Petroleum tank farms in South-South, Nigeria. The study concludes that Petroleum tank farms’ operations should focus on the adoption of contingency planning, benchmarking and continuous improvement processes to enhance organisational adaptability. Therefore, it is recommended that the management of Petroleum tank farms should put in place mechanisms to advance continuous improvement processes by allocating the necessary amount of resources, such as energy, time and money, in order to promote the continuous development of the continuous improvement systems. Furthermore, managers of Petroleum tank farms should make better the adoption of contingency planning, ensuring that there is as much necessary training and information for employees on how to act during a crises situation, in order to evaluate safety and prepare in advance for recovery from disasters.

Quaternion-Based Adaptive Trajectory Tracking Control of a Rotor-Missile with Unknown Parameters Identification

This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncertainty of structural and aerodynamic parameters,the six-degree-of-freedom(6Do F) nonlinear equations describing the position and attitude dynamics of the rotor-missile are established,respectively,in the inertial and body-fixed reference frames.Next,a hierarchical adaptive trajectory tracking controller that can guarantee closed-loop stability is proposed according to the cascade characteristics of the 6Do F dynamics.Then,a memory-augmented update rule of unknown parameters is proposed by integrating all historical data of the regression matrix.As long as the finitely excited condition is satisfied,the precise identification of unknown parameters can be achieved.Finally,the validity of the proposed trajectory tracking controller and the parameter identification method is proved through Lyapunov stability theory and numerical simulations.

Population genomic data reveal low genetic diversity,divergence and local adaptation among threatened Reeves's Pheasant(Syrmaticus reevesii)

Population genomic data could provide valuable information for conservation efforts;however,limited studies have been conducted to investigate the genetic status of threatened pheasants.Reeves’s Pheasant(Syrmaticus reevesii)is facing population decline,attributed to increases in habitat loss.There is a knowledge gap in understanding the genomic status and genetic basis underlying the local adaptation of this threatened bird.Here,we used population genomic data to assess population structure,genetic diversity,inbreeding patterns,and genetic divergence.Furthermore,we identified candidate genes linked with adaptation across the current distribution of Reeves’s Pheasant.The present study assembled the first de novo genome sequence of Reeves’s Pheasant and annotated 19,458 genes.We also sequenced 30 individuals from three populations(Dabie Mountain,Shennongjia,Qinling Mountain)and found that there was clear population structure among those populations.By comparing with other threatened species,we found that Reeves’s Pheasants have low genetic diversity.Runs of homozygosity suggest that the Shennongjia population has experienced serious inbreeding.The demographic history results indicated that three populations experienced several declines during the glacial period.Local adaptative analysis among the populations identified 241 candidate genes under directional selection.They are involved in a large variety of processes,including the immune response and pigmentation.Our results suggest that the three populations should be considered as three different conservation units.The current study provides genetic evidence for conserving the threatened Reeves’s Pheasant and provides genomic resources for global biodiversity management.

The ABA synthesis enzyme allele OsNCED2^(T)promotes dryland adaptation in upland rice

Upland rice shows dryland adaptation in the form of a deeper and denser root system and greater drought resistance than its counterpart,irrigated rice.Our previous study revealed a difference in the frequency of the OsNCED2 gene between upland and irrigated populations.A nonsynonymous mutation(C to T,from irrigated to upland rice)may have led to functional variation fixed by artificial selection,but the exact biological function in dryland adaptation is unclear.In this study,transgenic and association analysis indicated that the domesticated fixed mutation caused functional variation in OsNCED2,increasing ABA levels,root development,and drought tolerance in upland rice under dryland conditions.OsNCED2-overexpressing rice showed increased reactive oxygen species-scavenging abilities and transcription levels of many genes functioning in stress response and development that may regulate root development and drought tolerance.OsNCED2^(T)-NILs showed a denser root system and drought resistance,promoting the yield of rice under dryland conditions.OsNCED2^(T)may confer dryland adaptation in upland rice and may find use in breeding dryland-adapted,water-saving rice.

Ground-layer Adaptive Optics for the 2.5 m Wide-field and High-resolution Solar Telescope

The 2.5 m wide-field and high-resolution solar telescope(WeHoST)is currently under developing for solar observations.WeHoST aims to achieve high-resolution observations over a super-wide field of view(FOV)of5′×5′,and a desired resolution of 0.3″.To meet the scientific requirements of WeHoST,the ground-layer adaptive optics(GLAO)with a specially designed wave front sensing system is as the primary consideration.We introduce the GLAO configuration,particularly the wave front sensing scheme.Utilizing analytic method,we simulate the performance of both classical AO and GLAO systems,optimize the wave front sensing system,and evaluate GLAO performance in terms of PSF uniformity and correction improvement across whole FOV.The results indicate that,the classical AO will achieve diffraction-limited resolution;the suggested GLAO configuration will uniformly improve the seeing across the full 5′×5′FOV,reducing the FWHM across the axis FOV to less than0.3″(λ≥705 nm,r0≥11 cm),which is more than two times improvement.The specially designed wave front sensor schedule offers new potential for WeHoST’s GLAO,particularly the multi-FOV GLAO and the flexibility to select the detected area.These capabilities will significantly enhance the scientific output of the telescope.

Exercise-induced adaptation of neurons in the vertebrate locomotor system

Vertebrate neurons are highly dynamic cells that undergo several alterations in their functioning and physiologies in adaptation to various external stimuli.In particular,how these neurons respond to physical exercise has long been an area of active research.Studies of the vertebrate locomotor system’s adaptability suggest multiple mechanisms are involved in the regulation of neuronal activity and properties during exercise.In this brief review,we highlight recent results and insights from the field with a focus on the following mechanisms:(a)alterations in neuronal excitability during acute exercise;(b)alterations in neuronal excitability after chronic exercise;(c)exercise-induced changes in neuronal membrane properties via modulation of ion channel activity;(d)exercise-enhanced dendritic plasticity;and(e)exercise-induced alterations in neuronal gene expression and protein synthesis.Our hope is to update the community with a cellular and molecular understanding of the recent mechanisms underlying the adaptability of the vertebrate locomotor system in response to both acute and chronic physical exercise.

Adaptive admittance tracking control for interactive robot with prescribed performance

An adaptive control approach is presented in this paper for tracking desired trajectories in interactive manipulators. The controller design incorporates prescribed performance functions (PPFs) to improve dynamic performance. Notably, the performance of the output error is confined in an envelope characterized by exponential convergence, leading to convergence to zero. This feature ensures a prompt response from admittance control and establishes a reliable safety framework for interactions. Simulation results provide practical insights,demonstrating the viability of the control scheme proposed in this paper.

Comparative proteomics reveals the response and adaptation mechanisms of white Hypsizygus marmoreus against the biological stress caused by Penicillium

White Hypsizygus marmoreus is a popular edible mushroom.Its mycelium is easy to be contaminated by Penicillium,which leads to a decrease in its quality and yield.Penicillium could compete for limited space and nutrients through rapid growth and produce a variety of harmful gases,such as benzene,aldehydes,phenols,etc.,to inhibit the growth of H.marmoreus mycelium.A series of changes occurred in H.marmoreus proteome after contamination when detected by the label-free tandem mass spectrometry(MS/MS)technique.Some proteins with up-regulated expression worked together to participate in some processes,such as the non-toxic transformation of harmful gases,glutathione metabolism,histone modification,nucleotide excision repair,clearing misfolded proteins,and synthesizing glutamine,which were mainly used in response to biological stress.The proteins with down-regulated expression are mainly related to the processes of ribosome function,protein processing,spliceosome,carbon metabolism,glycolysis,and gluconeogenesis.The reduction in the function of these proteins affected the production of the cell components,which might be an adjustment to adapt to growth retardation.This study further enhanced the understanding of the biological stress response and the growth restriction adaptation mechanisms in edible fungi.It also provided a theoretical basis for protein function exploration and edible mushroom food safety research.

Fast compressed sensing spectral measurement with adaptive gradient multiscale resolution

We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution measurement.Mimicking the characteristics of the human retina system,the resolution distribution follows the principle of gradually decreasing.The system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a user.The system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements.

Noise-tolerate and adaptive coefficient zeroing neural network for solving dynamic matrix square root

The solving of dynamic matrix square root(DMSR)problems is frequently encountered in many scientific and engineering fields.Although the original zeroing neural network is powerful for solving the DMSR,it cannot vanish the influence of the noise perturbations,and its constant-coefficient design scheme cannot accelerate the convergence speed.Therefore,a noise-tolerate and adaptive coefficient zeroing neural network(NTACZNN)is raised to enhance the robust noise immunity performance and accelerate the conver-gence speed simultaneously.Then,the global convergence and robustness of the pro-posed NTACZNN are theoretically analysed under an ideal environment and noise-perturbed circumstances.Furthermore,some illustrative simulation examples are designed and performed in order to substantiate the efficacy and advantage of the NTACZNN for the DMSR problem solution.Compared with some existing ZNNs,the proposed NTACZNN possesses advanced performance in terms of noise tolerance,solution accuracy,and convergence rate.

Complementary-Label Adversarial Domain Adaptation Fault Diagnosis Network under Time-Varying Rotational Speed andWeakly-Supervised Conditions

Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems,such as relatively ideal speed conditions and sample conditions.In engineering practice,the rotational speed of the machine is often transient and time-varying,which makes the sample annotation increasingly expensive.Meanwhile,the number of samples collected from different health states is often unbalanced.To deal with the above challenges,a complementary-label(CL)adversarial domain adaptation fault diagnosis network(CLADAN)is proposed under time-varying rotational speed and weakly-supervised conditions.In the weakly supervised learning condition,machine prior information is used for sample annotation via cost-friendly complementary label learning.A diagnosticmodel learning strategywith discretized category probabilities is designed to avoidmulti-peak distribution of prediction results.In adversarial training process,we developed virtual adversarial regularization(VAR)strategy,which further enhances the robustness of the model by adding adversarial perturbations in the target domain.Comparative experiments on two case studies validated the superior performance of the proposed method.

A Novel Clutter Suppression Algorithm for Low-Slow-Small Targets Detecting Based on Sparse Adaptive Filtering

Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.

Reinforcement learning based adaptive control for uncertain mechanical systems with asymptotic tracking

This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.