Image-maps,a hybrid design with satellite images as background and map symbols uploaded,aim to combine the advantages of maps’high interpretation efficiency and satellite images’realism.The usability of image-maps i...Image-maps,a hybrid design with satellite images as background and map symbols uploaded,aim to combine the advantages of maps’high interpretation efficiency and satellite images’realism.The usability of image-maps is influenced by the representations of background images and map symbols.Many researchers explored the optimizations for background images and symbolization techniques for symbols to reduce the complexity of image-maps and improve the usability.However,little literature was found for the optimum amount of symbol loading.This study focuses on the effects of background image complexity and map symbol load on the usability(i.e.,effectiveness and efficiency)of image-maps.Experiments were conducted by user studies via eye-tracking equipment and an online questionnaire survey.Experimental data sets included image-maps with ten levels of map symbol load in ten areas.Forty volunteers took part in the target searching experiments.It has been found that the usability,i.e.,average time viewed(efficiency)and average revisits(effectiveness)of targets recorded,is influenced by the complexity of background images,a peak exists for optimum symbol load for an image-map.The optimum levels for symbol load for different image-maps also have a peak when the complexity of the background image/image map increases.The complexity of background images serves as a guideline for optimum map symbol load in image-map design.This study enhanced user experience by optimizing visual clarity and managing cognitive load.Understanding how these factors interact can help create adaptive maps that maintain clarity and usability,guiding AI algorithms to adjust symbol density based on user context.This research establishes the practices for map design,making cartographic tools more innovative and more user-centric.展开更多
Viral infectious diseases,characterized by their intricate nature and wide-ranging diversity,pose substantial challenges in the domain of data management.The vast volume of data generated by these diseases,spanning fr...Viral infectious diseases,characterized by their intricate nature and wide-ranging diversity,pose substantial challenges in the domain of data management.The vast volume of data generated by these diseases,spanning from the molecular mechanisms within cells to large-scale epidemiological patterns,has surpassed the capabilities of traditional analytical methods.In the era of artificial intelligence(AI)and big data,there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information.Despite the rapid accumulation of data associated with viral infections,the lack of a comprehensive framework for integrating,selecting,and analyzing these datasets has left numerous researchers uncertain about which data to select,how to access it,and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels,from the molecular details of pathogens to broad epidemiological trends.The scope extends from the micro-scale to the macro-scale,encompassing pathogens,hosts,and vectors.In addition to data summarization,this review thoroughly investigates various dataset sources.It also traces the historical evolution of data collection in the field of viral infectious diseases,highlighting the progress achieved over time.Simultaneously,it evaluates the current limitations that impede data utilization.Furthermore,we propose strategies to surmount these challenges,focusing on the development and application of advanced computational techniques,AI-driven models,and enhanced data integration practices.By providing a comprehensive synthesis of existing knowledge,this review is designed to guide future research and contribute to more informed approaches in the surveillance,prevention,and control of viral infectious diseases,particularly within the context of the expanding big-data landscape.展开更多
The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus...The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus(SCN)integrates environmental signals to maintain complex and robust circadian rhythms.Understanding the complexity and synchrony within SCN neurons is essential for effective circadian clock function.Synchrony involves coordinated neuronal firing for robust rhythms,while complexity reflects diverse activity patterns and interactions,indicating adaptability.Interestingly,the SCN retains circadian rhythms in vitro,demonstrating intrinsic rhythmicity.This study introduces the multiscale structural complexity method to analyze changes in SCN neuronal activity and complexity at macro and micro levels,based on Bagrov et al.’s approach.By examining structural complexity and local complexities across scales,we aim to understand how tetrodotoxin,a neurotoxin that inhibits action potentials,affects SCN neurons.Our method captures critical scales in neuronal interactions that traditional methods may overlook.Validation with the Goodwin model confirms the reliability of our observations.By integrating experimental data with theoretical models,this study provides new insights into the effects of tetrodotoxin(TTX)on neuronal complexities,contributing to the understanding of circadian rhythms.展开更多
Soil microbial communities are key factors in maintaining ecosystem multifunctionality(EMF).However,the distribution patterns of bacterial diversity and how the different bacterial taxa and their diversity dimensions ...Soil microbial communities are key factors in maintaining ecosystem multifunctionality(EMF).However,the distribution patterns of bacterial diversity and how the different bacterial taxa and their diversity dimensions affect EMF remain largely unknown.Here,we investigated variation in three measures of diversity(alpha diversity,community composition and network complexity)among rare,intermediate,and abundant taxa across a latitudinal gradient spanning five forest plots in Yunnan Province,China and examined their contributions on EMF.We aimed to characterize the diversity distributions of bacterial groups across latitudes and to assess the differences in the mechanisms underlying their contributions to EMF.We found that multifaceted diversity(i.e.,diversity assessed by the three different metrics)of rare,intermediate,and abundant bacteria generally decreased with increasing latitude.More importantly,we found that rare bacterial taxa tended to be more diverse,but they contributed less to EMF than intermediate or abundant bacteria.Among the three dimensions of diversity we assessed,only community composition significantly affected EMF across all locations,while alpha diversity had a negative effect,and network complexity showed no significant impact.Our study further emphasizes the importance of intermediate and abundant bacterial taxa as well as community composition to EMF and provides a theoretical basis for investigating the mechanisms by which belowground microorganisms drive EMF along a latitudinal gradient.展开更多
The construction projects’ dynamic and interconnected nature requires a comprehensive understanding of complexity during pre-construction. Traditional tools such as Gantt charts, CPM, and PERT often overlook uncertai...The construction projects’ dynamic and interconnected nature requires a comprehensive understanding of complexity during pre-construction. Traditional tools such as Gantt charts, CPM, and PERT often overlook uncertainties. This study identifies 20 complexity factors through expert interviews and literature, categorising them into six groups. The Analytical Hierarchy Process evaluated the significance of different factors, establishing their corresponding weights to enhance adaptive project scheduling. A system dynamics (SD) model is developed and tested to evaluate the dynamic behaviour of identified complexity factors. The model simulates the impact of complexity on total project duration (TPD), revealing significant deviations from initial deterministic estimates. Data collection and analysis for reliability tests, including normality and Cronbach alpha, to validate the model’s components and expert feedback. Sensitivity analysis confirmed a positive relationship between complexity and project duration, with higher complexity levels resulting in increased TPD. This relationship highlights the inadequacy of static planning approaches and underscores the importance of addressing complexity dynamically. The study provides a framework for enhancing planning systems through system dynamics and recommends expanding the model to ensure broader applicability in diverse construction projects.展开更多
BACKGROUND Sigmoid colon cancer faces challenges due to anatomical diversity,including variable inferior mesenteric artery(IMA)branching and tumor localization complexities,which increase intraoperative risks.AIM To c...BACKGROUND Sigmoid colon cancer faces challenges due to anatomical diversity,including variable inferior mesenteric artery(IMA)branching and tumor localization complexities,which increase intraoperative risks.AIM To comprehensively evaluate the impact of three-dimensional(3D)visualization technology on enhancing surgical precision and safety,as well as optimizing perioperative outcomes in laparoscopic sigmoid cancer resection.METHODS A prospective cohort of 106 patients(January 2023 to December 2024)undergoing laparoscopic sigmoid cancer resection was divided into the 3D(n=55)group and the control(n=51)group.The 3D group underwent preoperative enhanced computed tomography reconstruction(3D Slicer 5.2.2&Mimics 19.0).3D reconstruction visualization navigation intraoperatively guided the following key steps:Tumor location,Toldt’s space dissection,IMA ligation level selection,regional lymph node dissection,and marginal artery preservation.Outcomes included operative parameters,lymph node yield,and recovery metrics.RESULTS The 3D group demonstrated a significantly shorter operative time(172.91±20.69 minutes vs 190.29±32.29 minutes;P=0.002),reduced blood loss(31.5±11.8 mL vs 44.1±23.4 mL,P=0.001),earlier postoperative flatus(2.23±0.54 days vs 2.53±0.61 days;P=0.013),shorter hospital length of stay(13.47±1.74 days vs 16.20±7.71 days;P=0.013),shorter postoperative length of stay(8.6±2.6 days vs 10.5±4.9 days;P=0.014),and earlier postoperative exhaust time(2.23±0.54 days vs 2.53±0.61 days;P=0.013).Furthermore,the 3D group exhibited a higher mean number of lymph nodes harvested(16.91±5.74 vs 14.45±5.66;P=0.030).CONCLUSION The 3D visualization technology effectively addresses sigmoid colon anatomical complexity through surgical navigation,improving procedural safety and efficiency.展开更多
The authors regret that an error occurred during the preparation of their article:One of the official databases,which was used for functional trait collections,contained an incorrect term–'chametophytes'–for...The authors regret that an error occurred during the preparation of their article:One of the official databases,which was used for functional trait collections,contained an incorrect term–'chametophytes'–for the life form category'chamaephytes'.Unfortunately,this incorrect term was used throughout the article following the nomenclature of this official database:in one instance in the main text,in Fig.3 and its caption,in Fig.5,and in two instances in the supplementary material.展开更多
This study examined how psychological meaningfulness moderates job complexity and work-family conflict in Nigerian secondary school teachers.This study included 1694 teachers from 17 Nigerian secondary schools(female=6...This study examined how psychological meaningfulness moderates job complexity and work-family conflict in Nigerian secondary school teachers.This study included 1694 teachers from 17 Nigerian secondary schools(female=69.54%,mean age=33.19,SD=6.44 years).The participants completed the Work-family Conflict Scale,Job Complexity Scale,and Psychological Meaningfulness Scale.Study design was cross-sectional.Hayes PROCESS macro analysis results indicate a higher work-family conflict with job complexity among the secondary school teachers.While psychological meaningfulness was not associated with work-family conflict,it moderated the link between job complexity and work-family conflict in secondary school teachers such that a meaningful work endorsement is associated with lower employee’s work-life conflict.Thesefindings point to the importance of job functions to quality of family life.The studyfindings also suggest a need for supporting psychological meaningfulness for healthy work related quality of family life based on balancing work and family role demands.展开更多
Ulva prolifera green tides are becoming aworldwide environmental problem,especially in the Yellow Sea,China.However,the effects of the occurrence of U.prolifera green tides on the community organization and stability ...Ulva prolifera green tides are becoming aworldwide environmental problem,especially in the Yellow Sea,China.However,the effects of the occurrence of U.prolifera green tides on the community organization and stability of surrounding microbiomes have still not been de-termined.Here,the prokaryotic microbial community network stability and assembly char-acteristics were systematically analyzed and compared between the green tide and non-green tide periods.U.prolifera blooms weaken the community complexity and robustness of surrounding microbiomes,increasing fragmentation and decreasing diversity.Bacteria and archaea exhibited distinct community distributions and assembly patterns under the influ-ence of green tides,and bacterial communities were more sensitive to outbreaks of green tides.The bacterial communities exhibited a greater niche breadth and a lower phyloge-netic distance during the occurrence of U.prolifera green tides compared to those during the non-green tide period while archaeal communities remained unchanged,suggesting that the bacterial communities underwent stronger homogeneous selection and more sensitive to green tide blooms than the archaeal communities.Piecewise structural equation model analysis revealed that the different responses of major prokaryotic microbial groups,such as Cyanobacteria,to environmental variables during green tides,were influenced by the variations in pH and nitrate during green tides and correlated with the salinity gradient during the non-green tide period.This study elucidates the response of the adaptability,associations,and stability of surrounding microbiomes to outbreaks of U.prolifera green tides.展开更多
Binary sequences constructed by Legendre symbols are widely used in communication and cryptography since they have many good pseudo-random properties.In this paper,we determine the 2-adic complexity of the sum sequenc...Binary sequences constructed by Legendre symbols are widely used in communication and cryptography since they have many good pseudo-random properties.In this paper,we determine the 2-adic complexity of the sum sequence of any k many Legendre sequences and show that the 2-adic complexity of the sum sequences of any k many Legendre sequences reaches the maximum by proving the case of k=2 and 3,which implies that the sum sequences can resist the attack of rational approximation algorithm.展开更多
Integrated Sensing and Communication(ISAC)is envisioned as a promising technology for Sixth-Generation(6G)wireless communications,which enables simultaneous high-rate communication and high-precision target localizati...Integrated Sensing and Communication(ISAC)is envisioned as a promising technology for Sixth-Generation(6G)wireless communications,which enables simultaneous high-rate communication and high-precision target localization.Compared to independent sensing and communication modules,dual-function ISAC could leverage the strengths of both communication and sensing in order to achieve cooperative gains.When considering the communication core network,ISAC system facilitates multiple communication devices to collaborate for networked sensing.This paper investigates such kind of cooperative ISAC systems with distributed transmitters and receivers to support non-connected and multi-target localization.Specifically,we introduce a Time of Arrival(TOA)based multi-target localization scheme,which leverages the bi-static range measurements between the transmitter,target,and receiver channels in order to achieve elliptical localization.To obtain the low-complexity localization,a two-stage search-refine localization methodology is proposed.In the first stage,we propose a Successive Greedy Grid-Search(SGGS)algorithm and a Successive-Cancellation-List Grid-Search(SCLGS)algorithm to address the Measurement-to-Target Association(MTA)problem with relatively low computational complexity.In the second stage,a linear approximation refinement algorithm is derived to facilitate high-precision localization.Simulation results are presented to validate the effectiveness and superiority of our proposed multi-target localization method.展开更多
Numerous studies have examined the impact ofwater quality degradation on bacterial community structure,yet insights into its effects on the bacterial ecological networks remain scarce.In this study,we investigated the...Numerous studies have examined the impact ofwater quality degradation on bacterial community structure,yet insights into its effects on the bacterial ecological networks remain scarce.In this study,we investigated the diversity,composition,assembly patterns,ecological networks,and environmental determinants of bacterial communities across 20 ponds to understand the impact of water quality degradation.Our findings revealed that water quality degradation significantly reduces the α-diversity of bacterial communities in water samples,while sediment samples remain unaffected.Additionally,water quality deterioration increases the complexity of bacterial networks in water samples but reduces it in sediment samples.These shifts in bacterial communities were primarily governed by deterministic processes,with heterogeneous selection being particularly influential.Through redundancy analysis(RDA),multiple regression on matrices(MRM),and Mantel tests,we identified dissolved oxygen(DO),ammonium nitrogen(NH_(4)^(+)-N),and C/N ratio as key factors affecting the composition and network complexity of bacterial communities in both water and sediment.Overall,this study contributes a novel perspective on the effect ofwater quality deterioration on microbial ecosystems and provides valuable insights for improving ecological evaluations and biomonitoring practices related to water quality management.展开更多
Coastal wetlands store large amounts of soil organic carbon(SOC),and have assumed key roles in mitigating increasing CO_(2)in the atmosphere.The ongoing debate about SOC stabilization mechanisms stems partly from our ...Coastal wetlands store large amounts of soil organic carbon(SOC),and have assumed key roles in mitigating increasing CO_(2)in the atmosphere.The ongoing debate about SOC stabilization mechanisms stems partly from our incomplete understanding of its complex chemical architecture at the molecular scale.Deciphering the molecular composition of soil organic matter is crucial for revealing mechanisms that govern SOC persistence.This study utilized the field sampling data from 2016 and aimed to characterize molecular composition of SOC in typical salt marsh(SM)and freshwater marsh(FM)in Louisiana coastal regions,USA by extending the application of graph networks with pyrolysis-gas chromatography-mass spectrometry,and then to quantify potential links between SOC persistence and molecular diversity and network complexity.The results revealed that SOC predominantly consisted of alkyl compounds(Alkyl),phenol(Ph),lignin(Lg),and aliphatic compounds,constituting 23.21%and 27.85%,17.84%and 21.55%,16.94%and 15.49%,17.20%and 15.93%of total ion chromatogram(TIC)in SM and FM wetlands,respectively.Molecular diversity in SM was higher than that in FM,while the network graph exhibited greater complexity in FM,featuring 167 and 123 nodes,and 1935 and 1982 edges in the network graphs of SOC from SM and FM,respectively.Correlation analysis confirmed positive relations between molecular diversity indices,network complexity,and abundance of stable carbon isotopes(δ^(13)C).The variance partitioning analysis(VPA)supplied that soil nutrients exerted the most significant control on SOC persistence.Molecular diversity and network complexity,when combined with soil nutrients,could explain 34%of the variances in SOC persistence.展开更多
Visual question answering(VQA)is a multimodal task,involving a deep understanding of the image scene and the question’s meaning and capturing the relevant correlations between both modalities to infer the appropriate...Visual question answering(VQA)is a multimodal task,involving a deep understanding of the image scene and the question’s meaning and capturing the relevant correlations between both modalities to infer the appropriate answer.In this paper,we propose a VQA system intended to answer yes/no questions about real-world images,in Arabic.To support a robust VQA system,we work in two directions:(1)Using deep neural networks to semantically represent the given image and question in a fine-grainedmanner,namely ResNet-152 and Gated Recurrent Units(GRU).(2)Studying the role of the utilizedmultimodal bilinear pooling fusion technique in the trade-o.between the model complexity and the overall model performance.Some fusion techniques could significantly increase the model complexity,which seriously limits their applicability for VQA models.So far,there is no evidence of how efficient these multimodal bilinear pooling fusion techniques are for VQA systems dedicated to yes/no questions.Hence,a comparative analysis is conducted between eight bilinear pooling fusion techniques,in terms of their ability to reduce themodel complexity and improve themodel performance in this case of VQA systems.Experiments indicate that these multimodal bilinear pooling fusion techniques have improved the VQA model’s performance,until reaching the best performance of 89.25%.Further,experiments have proven that the number of answers in the developed VQA system is a critical factor that a.ects the effectiveness of these multimodal bilinear pooling techniques in achieving their main objective of reducing the model complexity.The Multimodal Local Perception Bilinear Pooling(MLPB)technique has shown the best balance between the model complexity and its performance,for VQA systems designed to answer yes/no questions.展开更多
In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovative...In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovatively addresses the joint estimation of the Direction of Departure(DOD), Direction of Arrival(DOA), and Doppler frequency for incoherent targets. We propose a novel approach that significantly reduces computational complexity by utilizing the TemporalSpatial Nested Sampling Model(TSNSM). Our methodology begins with a multi-linear mapping mechanism to efficiently eliminate unnecessary virtual Degrees of Freedom(DOFs) and reorganize the remaining ones. We then employ the Toeplitz matrix triple iteration reconstruction method, surpassing the traditional Temporal-Spatial Smoothing Window(TSSW) approach, to mitigate the single snapshot effect and reduce computational demands. We further refine the highdimensional ESPRIT algorithm for joint estimation of DOD, DOA, and Doppler frequency, eliminating the need for additional parameter pairing. Moreover, we meticulously derive the Cramér-Rao Bound(CRB) for the TSNSM. This signal model allows for a second expansion of DOFs in time and space domains, achieving high precision in target angle and Doppler frequency estimation with low computational complexity. Our adaptable algorithm is validated through simulations and is suitable for sparse array MIMO radars with various structures, ensuring higher precision in parameter estimation with less complexity burden.展开更多
The security of Federated Learning(FL)/Distributed Machine Learning(DML)is gravely threatened by data poisoning attacks,which destroy the usability of the model by contaminating training samples,so such attacks are ca...The security of Federated Learning(FL)/Distributed Machine Learning(DML)is gravely threatened by data poisoning attacks,which destroy the usability of the model by contaminating training samples,so such attacks are called causative availability indiscriminate attacks.Facing the problem that existing data sanitization methods are hard to apply to real-time applications due to their tedious process and heavy computations,we propose a new supervised batch detection method for poison,which can fleetly sanitize the training dataset before the local model training.We design a training dataset generation method that helps to enhance accuracy and uses data complexity features to train a detection model,which will be used in an efficient batch hierarchical detection process.Our model stockpiles knowledge about poison,which can be expanded by retraining to adapt to new attacks.Being neither attack-specific nor scenario-specific,our method is applicable to FL/DML or other online or offline scenarios.展开更多
Continuous-flow microchannels are widely employed for synthesizing various materials,including nanoparticles,polymers,and metal-organic frameworks(MOFs),to name a few.Microsystem technology allows precise control over...Continuous-flow microchannels are widely employed for synthesizing various materials,including nanoparticles,polymers,and metal-organic frameworks(MOFs),to name a few.Microsystem technology allows precise control over reaction parameters,resulting in purer,more uniform,and structurally stable products due to more effective mass transfer manipulation.However,continuous-flow synthesis processes may be accompanied by the emergence of spatial convective structures initiating convective flows.On the one hand,convection can accelerate reactions by intensifying mass transfer.On the other hand,it may lead to non-uniformity in the final product or defects,especially in MOF microcrystal synthesis.The ability to distinguish regions of convective and diffusive mass transfer may be the key to performing higher-quality reactions and obtaining purer products.In this study,we investigate,for the first time,the possibility of using the information complexity measure as a criterion for assessing the intensity of mass transfer in microchannels,considering both spatial and temporal non-uniformities of liquid’s distributions resulting from convection formation.We calculate the complexity using shearlet transform based on a local approach.In contrast to existing methods for calculating complexity,the shearlet transform based approach provides a more detailed representation of local heterogeneities.Our analysis involves experimental images illustrating the mixing process of two non-reactive liquids in a Y-type continuous-flow microchannel under conditions of double-diffusive convection formation.The obtained complexity fields characterize the mixing process and structure formation,revealing variations in mass transfer intensity along the microchannel.We compare the results with cases of liquid mixing via a pure diffusive mechanism.Upon analysis,it was revealed that the complexity measure exhibits sensitivity to variations in the type of mass transfer,establishing its feasibility as an indirect criterion for assessing mass transfer intensity.The method presented can extend beyond flow analysis,finding application in the controlling of microstructures of various materials(porosity,for instance)or surface defects in metals,optical systems and other materials that hold significant relevance in materials science and engineering.展开更多
This work introduces a modification to the Heisenberg Uncertainty Principle (HUP) by incorporating quantum complexity, including potential nonlinear effects. Our theoretical framework extends the traditional HUP to co...This work introduces a modification to the Heisenberg Uncertainty Principle (HUP) by incorporating quantum complexity, including potential nonlinear effects. Our theoretical framework extends the traditional HUP to consider the complexity of quantum states, offering a more nuanced understanding of measurement precision. By adding a complexity term to the uncertainty relation, we explore nonlinear modifications such as polynomial, exponential, and logarithmic functions. Rigorous mathematical derivations demonstrate the consistency of the modified principle with classical quantum mechanics and quantum information theory. We investigate the implications of this modified HUP for various aspects of quantum mechanics, including quantum metrology, quantum algorithms, quantum error correction, and quantum chaos. Additionally, we propose experimental protocols to test the validity of the modified HUP, evaluating their feasibility with current and near-term quantum technologies. This work highlights the importance of quantum complexity in quantum mechanics and provides a refined perspective on the interplay between complexity, entanglement, and uncertainty in quantum systems. The modified HUP has the potential to stimulate interdisciplinary research at the intersection of quantum physics, information theory, and complexity theory, with significant implications for the development of quantum technologies and the understanding of the quantum-to-classical transition.展开更多
Nowadays,collaborative writing has gained much attention of many scholars.And task complexity is a crucial factor that influences second language(L2)writing.However,little research has explored how task complexity aff...Nowadays,collaborative writing has gained much attention of many scholars.And task complexity is a crucial factor that influences second language(L2)writing.However,little research has explored how task complexity affects the quality of L2 collaborative writing.This study investigates the impact of task complexity on syntactic complexity,lexical complexity,and accuracy of the second language collaborative writing.English learners(N=50)in a Chinese university were required to complete two writing tasks collaboratively:a simple task and a complex task.Through analyzing their compositions,we found that task complexity has a significant impact on syntactic complexity and high complexity writing tasks help increase the syntactic complexity of second language collaborative writing.However,task complexity has little impact on lexical complexity and accuracy.The accuracy of writing tasks is largely influenced by the task requirements.The research results may enhance the understanding of collaborative writing and task complexity and provide valuable guidance for the second language teaching.展开更多
Living objects have complex internal and external interactions. The complexity is regulated and controlled by homeostasis, which is the balance of multiple opposing influences. The environmental effects finally guide ...Living objects have complex internal and external interactions. The complexity is regulated and controlled by homeostasis, which is the balance of multiple opposing influences. The environmental effects finally guide the self-organized structure. The living systems are open, dynamic structures performing random, stationary, stochastic, self-organizing processes. The self-organizing procedure is defined by the spatial-temporal fractal structure, which is self-similar both in space and time. The system’s complexity appears in its energetics, which tries the most efficient use of the available energies;for that, it organizes various well-connected networks. The controller of environmental relations is the Darwinian selection on a long-time scale. The energetics optimize the healthy processes tuned to the highest efficacy and minimal loss (minimalization of the entropy production). The organism is built up by morphogenetic rules and develops various networks from the genetic level to the organism. The networks have intensive crosstalk and form a balance in the Nash equilibrium, which is the homeostatic state in healthy conditions. Homeostasis may be described as a Nash equilibrium, which ensures energy distribution in a “democratic” way regarding the functions of the parts in the complete system. Cancer radically changes the network system in the organism. Cancer is a network disease. Deviation from healthy networking appears at every level, from genetic (molecular) to cells, tissues, organs, and organisms. The strong proliferation of malignant tissue is the origin of most of the life-threatening processes. The weak side of cancer development is the change of complex information networking in the system, being vulnerable to immune attacks. Cancer cells are masters of adaptation and evade immune surveillance. This hiding process can be broken by electromagnetic nonionizing radiation, for which the malignant structure has no adaptation strategy. Our objective is to review the different sides of living complexity and use the knowledge to fight against cancer.展开更多
基金National Natural Science Foundation of China(No.42301518)Hubei Key Laboratory of Regional Development and Environmental Response(No.2023(A)002)Key Laboratory of the Evaluation and Monitoring of Southwest Land Resources(Ministry of Education)(No.TDSYS202304).
文摘Image-maps,a hybrid design with satellite images as background and map symbols uploaded,aim to combine the advantages of maps’high interpretation efficiency and satellite images’realism.The usability of image-maps is influenced by the representations of background images and map symbols.Many researchers explored the optimizations for background images and symbolization techniques for symbols to reduce the complexity of image-maps and improve the usability.However,little literature was found for the optimum amount of symbol loading.This study focuses on the effects of background image complexity and map symbol load on the usability(i.e.,effectiveness and efficiency)of image-maps.Experiments were conducted by user studies via eye-tracking equipment and an online questionnaire survey.Experimental data sets included image-maps with ten levels of map symbol load in ten areas.Forty volunteers took part in the target searching experiments.It has been found that the usability,i.e.,average time viewed(efficiency)and average revisits(effectiveness)of targets recorded,is influenced by the complexity of background images,a peak exists for optimum symbol load for an image-map.The optimum levels for symbol load for different image-maps also have a peak when the complexity of the background image/image map increases.The complexity of background images serves as a guideline for optimum map symbol load in image-map design.This study enhanced user experience by optimizing visual clarity and managing cognitive load.Understanding how these factors interact can help create adaptive maps that maintain clarity and usability,guiding AI algorithms to adjust symbol density based on user context.This research establishes the practices for map design,making cartographic tools more innovative and more user-centric.
基金supported by the National Natural Science Foundation of China(32370703)the CAMS Innovation Fund for Medical Sciences(CIFMS)(2022-I2M-1-021,2021-I2M-1-061)the Major Project of Guangzhou National Labora-tory(GZNL2024A01015).
文摘Viral infectious diseases,characterized by their intricate nature and wide-ranging diversity,pose substantial challenges in the domain of data management.The vast volume of data generated by these diseases,spanning from the molecular mechanisms within cells to large-scale epidemiological patterns,has surpassed the capabilities of traditional analytical methods.In the era of artificial intelligence(AI)and big data,there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information.Despite the rapid accumulation of data associated with viral infections,the lack of a comprehensive framework for integrating,selecting,and analyzing these datasets has left numerous researchers uncertain about which data to select,how to access it,and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels,from the molecular details of pathogens to broad epidemiological trends.The scope extends from the micro-scale to the macro-scale,encompassing pathogens,hosts,and vectors.In addition to data summarization,this review thoroughly investigates various dataset sources.It also traces the historical evolution of data collection in the field of viral infectious diseases,highlighting the progress achieved over time.Simultaneously,it evaluates the current limitations that impede data utilization.Furthermore,we propose strategies to surmount these challenges,focusing on the development and application of advanced computational techniques,AI-driven models,and enhanced data integration practices.By providing a comprehensive synthesis of existing knowledge,this review is designed to guide future research and contribute to more informed approaches in the surveillance,prevention,and control of viral infectious diseases,particularly within the context of the expanding big-data landscape.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12275179,11875042,and 12150410309)the Natural Science Foundation of Shanghai(Grant No.21ZR1443900).
文摘The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus(SCN)integrates environmental signals to maintain complex and robust circadian rhythms.Understanding the complexity and synchrony within SCN neurons is essential for effective circadian clock function.Synchrony involves coordinated neuronal firing for robust rhythms,while complexity reflects diverse activity patterns and interactions,indicating adaptability.Interestingly,the SCN retains circadian rhythms in vitro,demonstrating intrinsic rhythmicity.This study introduces the multiscale structural complexity method to analyze changes in SCN neuronal activity and complexity at macro and micro levels,based on Bagrov et al.’s approach.By examining structural complexity and local complexities across scales,we aim to understand how tetrodotoxin,a neurotoxin that inhibits action potentials,affects SCN neurons.Our method captures critical scales in neuronal interactions that traditional methods may overlook.Validation with the Goodwin model confirms the reliability of our observations.By integrating experimental data with theoretical models,this study provides new insights into the effects of tetrodotoxin(TTX)on neuronal complexities,contributing to the understanding of circadian rhythms.
基金supported by the Fundamental Research Funds of Chinese Academy of Forestry(Nos.CAFYBB2022SY037,CAFYBB2021ZA002 and CAFYBB2022QC002)the Basic Research Foundation of Yunnan Province(Grant No.202201AT070264).
文摘Soil microbial communities are key factors in maintaining ecosystem multifunctionality(EMF).However,the distribution patterns of bacterial diversity and how the different bacterial taxa and their diversity dimensions affect EMF remain largely unknown.Here,we investigated variation in three measures of diversity(alpha diversity,community composition and network complexity)among rare,intermediate,and abundant taxa across a latitudinal gradient spanning five forest plots in Yunnan Province,China and examined their contributions on EMF.We aimed to characterize the diversity distributions of bacterial groups across latitudes and to assess the differences in the mechanisms underlying their contributions to EMF.We found that multifaceted diversity(i.e.,diversity assessed by the three different metrics)of rare,intermediate,and abundant bacteria generally decreased with increasing latitude.More importantly,we found that rare bacterial taxa tended to be more diverse,but they contributed less to EMF than intermediate or abundant bacteria.Among the three dimensions of diversity we assessed,only community composition significantly affected EMF across all locations,while alpha diversity had a negative effect,and network complexity showed no significant impact.Our study further emphasizes the importance of intermediate and abundant bacterial taxa as well as community composition to EMF and provides a theoretical basis for investigating the mechanisms by which belowground microorganisms drive EMF along a latitudinal gradient.
文摘The construction projects’ dynamic and interconnected nature requires a comprehensive understanding of complexity during pre-construction. Traditional tools such as Gantt charts, CPM, and PERT often overlook uncertainties. This study identifies 20 complexity factors through expert interviews and literature, categorising them into six groups. The Analytical Hierarchy Process evaluated the significance of different factors, establishing their corresponding weights to enhance adaptive project scheduling. A system dynamics (SD) model is developed and tested to evaluate the dynamic behaviour of identified complexity factors. The model simulates the impact of complexity on total project duration (TPD), revealing significant deviations from initial deterministic estimates. Data collection and analysis for reliability tests, including normality and Cronbach alpha, to validate the model’s components and expert feedback. Sensitivity analysis confirmed a positive relationship between complexity and project duration, with higher complexity levels resulting in increased TPD. This relationship highlights the inadequacy of static planning approaches and underscores the importance of addressing complexity dynamically. The study provides a framework for enhancing planning systems through system dynamics and recommends expanding the model to ensure broader applicability in diverse construction projects.
基金Supported by the Health Commission of Fuyang City,Anhui,China,No.FY2023-45Fuyang Municipal Science and Technology Bureau,Anhui,China,No.FK20245505+1 种基金Anhui Provincial Health Commission,No.AHWJ2023Baa20164Bengbu Medical University,No.2023byzd215.
文摘BACKGROUND Sigmoid colon cancer faces challenges due to anatomical diversity,including variable inferior mesenteric artery(IMA)branching and tumor localization complexities,which increase intraoperative risks.AIM To comprehensively evaluate the impact of three-dimensional(3D)visualization technology on enhancing surgical precision and safety,as well as optimizing perioperative outcomes in laparoscopic sigmoid cancer resection.METHODS A prospective cohort of 106 patients(January 2023 to December 2024)undergoing laparoscopic sigmoid cancer resection was divided into the 3D(n=55)group and the control(n=51)group.The 3D group underwent preoperative enhanced computed tomography reconstruction(3D Slicer 5.2.2&Mimics 19.0).3D reconstruction visualization navigation intraoperatively guided the following key steps:Tumor location,Toldt’s space dissection,IMA ligation level selection,regional lymph node dissection,and marginal artery preservation.Outcomes included operative parameters,lymph node yield,and recovery metrics.RESULTS The 3D group demonstrated a significantly shorter operative time(172.91±20.69 minutes vs 190.29±32.29 minutes;P=0.002),reduced blood loss(31.5±11.8 mL vs 44.1±23.4 mL,P=0.001),earlier postoperative flatus(2.23±0.54 days vs 2.53±0.61 days;P=0.013),shorter hospital length of stay(13.47±1.74 days vs 16.20±7.71 days;P=0.013),shorter postoperative length of stay(8.6±2.6 days vs 10.5±4.9 days;P=0.014),and earlier postoperative exhaust time(2.23±0.54 days vs 2.53±0.61 days;P=0.013).Furthermore,the 3D group exhibited a higher mean number of lymph nodes harvested(16.91±5.74 vs 14.45±5.66;P=0.030).CONCLUSION The 3D visualization technology effectively addresses sigmoid colon anatomical complexity through surgical navigation,improving procedural safety and efficiency.
文摘The authors regret that an error occurred during the preparation of their article:One of the official databases,which was used for functional trait collections,contained an incorrect term–'chametophytes'–for the life form category'chamaephytes'.Unfortunately,this incorrect term was used throughout the article following the nomenclature of this official database:in one instance in the main text,in Fig.3 and its caption,in Fig.5,and in two instances in the supplementary material.
文摘This study examined how psychological meaningfulness moderates job complexity and work-family conflict in Nigerian secondary school teachers.This study included 1694 teachers from 17 Nigerian secondary schools(female=69.54%,mean age=33.19,SD=6.44 years).The participants completed the Work-family Conflict Scale,Job Complexity Scale,and Psychological Meaningfulness Scale.Study design was cross-sectional.Hayes PROCESS macro analysis results indicate a higher work-family conflict with job complexity among the secondary school teachers.While psychological meaningfulness was not associated with work-family conflict,it moderated the link between job complexity and work-family conflict in secondary school teachers such that a meaningful work endorsement is associated with lower employee’s work-life conflict.Thesefindings point to the importance of job functions to quality of family life.The studyfindings also suggest a need for supporting psychological meaningfulness for healthy work related quality of family life based on balancing work and family role demands.
基金supported by the National Key Research and Development Program of China(No.2022YFC2807500)Laoshan Laboratory(No.LSKJ202203201)+1 种基金the National Natural Science Foundation of China(Nos.42206147,42120104006 and 42176111)the Natural Science Foundation of Shandong Province(Nos.ZR2022QD046,ZR2021QD051).
文摘Ulva prolifera green tides are becoming aworldwide environmental problem,especially in the Yellow Sea,China.However,the effects of the occurrence of U.prolifera green tides on the community organization and stability of surrounding microbiomes have still not been de-termined.Here,the prokaryotic microbial community network stability and assembly char-acteristics were systematically analyzed and compared between the green tide and non-green tide periods.U.prolifera blooms weaken the community complexity and robustness of surrounding microbiomes,increasing fragmentation and decreasing diversity.Bacteria and archaea exhibited distinct community distributions and assembly patterns under the influ-ence of green tides,and bacterial communities were more sensitive to outbreaks of green tides.The bacterial communities exhibited a greater niche breadth and a lower phyloge-netic distance during the occurrence of U.prolifera green tides compared to those during the non-green tide period while archaeal communities remained unchanged,suggesting that the bacterial communities underwent stronger homogeneous selection and more sensitive to green tide blooms than the archaeal communities.Piecewise structural equation model analysis revealed that the different responses of major prokaryotic microbial groups,such as Cyanobacteria,to environmental variables during green tides,were influenced by the variations in pH and nitrate during green tides and correlated with the salinity gradient during the non-green tide period.This study elucidates the response of the adaptability,associations,and stability of surrounding microbiomes to outbreaks of U.prolifera green tides.
文摘Binary sequences constructed by Legendre symbols are widely used in communication and cryptography since they have many good pseudo-random properties.In this paper,we determine the 2-adic complexity of the sum sequence of any k many Legendre sequences and show that the 2-adic complexity of the sum sequences of any k many Legendre sequences reaches the maximum by proving the case of k=2 and 3,which implies that the sum sequences can resist the attack of rational approximation algorithm.
文摘Integrated Sensing and Communication(ISAC)is envisioned as a promising technology for Sixth-Generation(6G)wireless communications,which enables simultaneous high-rate communication and high-precision target localization.Compared to independent sensing and communication modules,dual-function ISAC could leverage the strengths of both communication and sensing in order to achieve cooperative gains.When considering the communication core network,ISAC system facilitates multiple communication devices to collaborate for networked sensing.This paper investigates such kind of cooperative ISAC systems with distributed transmitters and receivers to support non-connected and multi-target localization.Specifically,we introduce a Time of Arrival(TOA)based multi-target localization scheme,which leverages the bi-static range measurements between the transmitter,target,and receiver channels in order to achieve elliptical localization.To obtain the low-complexity localization,a two-stage search-refine localization methodology is proposed.In the first stage,we propose a Successive Greedy Grid-Search(SGGS)algorithm and a Successive-Cancellation-List Grid-Search(SCLGS)algorithm to address the Measurement-to-Target Association(MTA)problem with relatively low computational complexity.In the second stage,a linear approximation refinement algorithm is derived to facilitate high-precision localization.Simulation results are presented to validate the effectiveness and superiority of our proposed multi-target localization method.
基金supported by Zhejiang Provincial Natural Science Foundation of China(No.LTGS24D010004)the National Natural Science Foundation of China grant(No.42307064)+2 种基金the National Students’platform for innovation and entrepreneurship training program(No.202410346054)Hangzhou“Young science and technology talent cultivation”project(No.4305F45623004)the Fundamental Research Funds for Climbing Project from Hangzhou Normal University(No.KYQD-2023-217).
文摘Numerous studies have examined the impact ofwater quality degradation on bacterial community structure,yet insights into its effects on the bacterial ecological networks remain scarce.In this study,we investigated the diversity,composition,assembly patterns,ecological networks,and environmental determinants of bacterial communities across 20 ponds to understand the impact of water quality degradation.Our findings revealed that water quality degradation significantly reduces the α-diversity of bacterial communities in water samples,while sediment samples remain unaffected.Additionally,water quality deterioration increases the complexity of bacterial networks in water samples but reduces it in sediment samples.These shifts in bacterial communities were primarily governed by deterministic processes,with heterogeneous selection being particularly influential.Through redundancy analysis(RDA),multiple regression on matrices(MRM),and Mantel tests,we identified dissolved oxygen(DO),ammonium nitrogen(NH_(4)^(+)-N),and C/N ratio as key factors affecting the composition and network complexity of bacterial communities in both water and sediment.Overall,this study contributes a novel perspective on the effect ofwater quality deterioration on microbial ecosystems and provides valuable insights for improving ecological evaluations and biomonitoring practices related to water quality management.
基金Under the auspices of National Natural Science Foundation of China(No.42371061,U20A2083)。
文摘Coastal wetlands store large amounts of soil organic carbon(SOC),and have assumed key roles in mitigating increasing CO_(2)in the atmosphere.The ongoing debate about SOC stabilization mechanisms stems partly from our incomplete understanding of its complex chemical architecture at the molecular scale.Deciphering the molecular composition of soil organic matter is crucial for revealing mechanisms that govern SOC persistence.This study utilized the field sampling data from 2016 and aimed to characterize molecular composition of SOC in typical salt marsh(SM)and freshwater marsh(FM)in Louisiana coastal regions,USA by extending the application of graph networks with pyrolysis-gas chromatography-mass spectrometry,and then to quantify potential links between SOC persistence and molecular diversity and network complexity.The results revealed that SOC predominantly consisted of alkyl compounds(Alkyl),phenol(Ph),lignin(Lg),and aliphatic compounds,constituting 23.21%and 27.85%,17.84%and 21.55%,16.94%and 15.49%,17.20%and 15.93%of total ion chromatogram(TIC)in SM and FM wetlands,respectively.Molecular diversity in SM was higher than that in FM,while the network graph exhibited greater complexity in FM,featuring 167 and 123 nodes,and 1935 and 1982 edges in the network graphs of SOC from SM and FM,respectively.Correlation analysis confirmed positive relations between molecular diversity indices,network complexity,and abundance of stable carbon isotopes(δ^(13)C).The variance partitioning analysis(VPA)supplied that soil nutrients exerted the most significant control on SOC persistence.Molecular diversity and network complexity,when combined with soil nutrients,could explain 34%of the variances in SOC persistence.
文摘Visual question answering(VQA)is a multimodal task,involving a deep understanding of the image scene and the question’s meaning and capturing the relevant correlations between both modalities to infer the appropriate answer.In this paper,we propose a VQA system intended to answer yes/no questions about real-world images,in Arabic.To support a robust VQA system,we work in two directions:(1)Using deep neural networks to semantically represent the given image and question in a fine-grainedmanner,namely ResNet-152 and Gated Recurrent Units(GRU).(2)Studying the role of the utilizedmultimodal bilinear pooling fusion technique in the trade-o.between the model complexity and the overall model performance.Some fusion techniques could significantly increase the model complexity,which seriously limits their applicability for VQA models.So far,there is no evidence of how efficient these multimodal bilinear pooling fusion techniques are for VQA systems dedicated to yes/no questions.Hence,a comparative analysis is conducted between eight bilinear pooling fusion techniques,in terms of their ability to reduce themodel complexity and improve themodel performance in this case of VQA systems.Experiments indicate that these multimodal bilinear pooling fusion techniques have improved the VQA model’s performance,until reaching the best performance of 89.25%.Further,experiments have proven that the number of answers in the developed VQA system is a critical factor that a.ects the effectiveness of these multimodal bilinear pooling techniques in achieving their main objective of reducing the model complexity.The Multimodal Local Perception Bilinear Pooling(MLPB)technique has shown the best balance between the model complexity and its performance,for VQA systems designed to answer yes/no questions.
基金supported in part by the National Natural Science Foundation of China(No.62071476)in part by China Postdoctoral Science Foundation(No.2022M723879)in part by the Science and Technology Innovation Program of Hunan Province,China(No.2021RC3080)。
文摘In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovatively addresses the joint estimation of the Direction of Departure(DOD), Direction of Arrival(DOA), and Doppler frequency for incoherent targets. We propose a novel approach that significantly reduces computational complexity by utilizing the TemporalSpatial Nested Sampling Model(TSNSM). Our methodology begins with a multi-linear mapping mechanism to efficiently eliminate unnecessary virtual Degrees of Freedom(DOFs) and reorganize the remaining ones. We then employ the Toeplitz matrix triple iteration reconstruction method, surpassing the traditional Temporal-Spatial Smoothing Window(TSSW) approach, to mitigate the single snapshot effect and reduce computational demands. We further refine the highdimensional ESPRIT algorithm for joint estimation of DOD, DOA, and Doppler frequency, eliminating the need for additional parameter pairing. Moreover, we meticulously derive the Cramér-Rao Bound(CRB) for the TSNSM. This signal model allows for a second expansion of DOFs in time and space domains, achieving high precision in target angle and Doppler frequency estimation with low computational complexity. Our adaptable algorithm is validated through simulations and is suitable for sparse array MIMO radars with various structures, ensuring higher precision in parameter estimation with less complexity burden.
基金supported in part by the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(Grant No.2022C03174)the National Natural Science Foundation of China(No.92067103)+4 种基金the Key Research and Development Program of Shaanxi,China(No.2021ZDLGY06-02)the Natural Science Foundation of Shaanxi Province(No.2019ZDLGY12-02)the Shaanxi Innovation Team Project(No.2018TD-007)the Xi'an Science and technology Innovation Plan(No.201809168CX9JC10)the Fundamental Research Funds for the Central Universities(No.YJS2212)and National 111 Program of China B16037.
文摘The security of Federated Learning(FL)/Distributed Machine Learning(DML)is gravely threatened by data poisoning attacks,which destroy the usability of the model by contaminating training samples,so such attacks are called causative availability indiscriminate attacks.Facing the problem that existing data sanitization methods are hard to apply to real-time applications due to their tedious process and heavy computations,we propose a new supervised batch detection method for poison,which can fleetly sanitize the training dataset before the local model training.We design a training dataset generation method that helps to enhance accuracy and uses data complexity features to train a detection model,which will be used in an efficient batch hierarchical detection process.Our model stockpiles knowledge about poison,which can be expanded by retraining to adapt to new attacks.Being neither attack-specific nor scenario-specific,our method is applicable to FL/DML or other online or offline scenarios.
基金supported by the Ministry of Science and High Education of Russia(Theme No.368121031700169-1 of ICMM UrB RAS).
文摘Continuous-flow microchannels are widely employed for synthesizing various materials,including nanoparticles,polymers,and metal-organic frameworks(MOFs),to name a few.Microsystem technology allows precise control over reaction parameters,resulting in purer,more uniform,and structurally stable products due to more effective mass transfer manipulation.However,continuous-flow synthesis processes may be accompanied by the emergence of spatial convective structures initiating convective flows.On the one hand,convection can accelerate reactions by intensifying mass transfer.On the other hand,it may lead to non-uniformity in the final product or defects,especially in MOF microcrystal synthesis.The ability to distinguish regions of convective and diffusive mass transfer may be the key to performing higher-quality reactions and obtaining purer products.In this study,we investigate,for the first time,the possibility of using the information complexity measure as a criterion for assessing the intensity of mass transfer in microchannels,considering both spatial and temporal non-uniformities of liquid’s distributions resulting from convection formation.We calculate the complexity using shearlet transform based on a local approach.In contrast to existing methods for calculating complexity,the shearlet transform based approach provides a more detailed representation of local heterogeneities.Our analysis involves experimental images illustrating the mixing process of two non-reactive liquids in a Y-type continuous-flow microchannel under conditions of double-diffusive convection formation.The obtained complexity fields characterize the mixing process and structure formation,revealing variations in mass transfer intensity along the microchannel.We compare the results with cases of liquid mixing via a pure diffusive mechanism.Upon analysis,it was revealed that the complexity measure exhibits sensitivity to variations in the type of mass transfer,establishing its feasibility as an indirect criterion for assessing mass transfer intensity.The method presented can extend beyond flow analysis,finding application in the controlling of microstructures of various materials(porosity,for instance)or surface defects in metals,optical systems and other materials that hold significant relevance in materials science and engineering.
文摘This work introduces a modification to the Heisenberg Uncertainty Principle (HUP) by incorporating quantum complexity, including potential nonlinear effects. Our theoretical framework extends the traditional HUP to consider the complexity of quantum states, offering a more nuanced understanding of measurement precision. By adding a complexity term to the uncertainty relation, we explore nonlinear modifications such as polynomial, exponential, and logarithmic functions. Rigorous mathematical derivations demonstrate the consistency of the modified principle with classical quantum mechanics and quantum information theory. We investigate the implications of this modified HUP for various aspects of quantum mechanics, including quantum metrology, quantum algorithms, quantum error correction, and quantum chaos. Additionally, we propose experimental protocols to test the validity of the modified HUP, evaluating their feasibility with current and near-term quantum technologies. This work highlights the importance of quantum complexity in quantum mechanics and provides a refined perspective on the interplay between complexity, entanglement, and uncertainty in quantum systems. The modified HUP has the potential to stimulate interdisciplinary research at the intersection of quantum physics, information theory, and complexity theory, with significant implications for the development of quantum technologies and the understanding of the quantum-to-classical transition.
文摘Nowadays,collaborative writing has gained much attention of many scholars.And task complexity is a crucial factor that influences second language(L2)writing.However,little research has explored how task complexity affects the quality of L2 collaborative writing.This study investigates the impact of task complexity on syntactic complexity,lexical complexity,and accuracy of the second language collaborative writing.English learners(N=50)in a Chinese university were required to complete two writing tasks collaboratively:a simple task and a complex task.Through analyzing their compositions,we found that task complexity has a significant impact on syntactic complexity and high complexity writing tasks help increase the syntactic complexity of second language collaborative writing.However,task complexity has little impact on lexical complexity and accuracy.The accuracy of writing tasks is largely influenced by the task requirements.The research results may enhance the understanding of collaborative writing and task complexity and provide valuable guidance for the second language teaching.
文摘Living objects have complex internal and external interactions. The complexity is regulated and controlled by homeostasis, which is the balance of multiple opposing influences. The environmental effects finally guide the self-organized structure. The living systems are open, dynamic structures performing random, stationary, stochastic, self-organizing processes. The self-organizing procedure is defined by the spatial-temporal fractal structure, which is self-similar both in space and time. The system’s complexity appears in its energetics, which tries the most efficient use of the available energies;for that, it organizes various well-connected networks. The controller of environmental relations is the Darwinian selection on a long-time scale. The energetics optimize the healthy processes tuned to the highest efficacy and minimal loss (minimalization of the entropy production). The organism is built up by morphogenetic rules and develops various networks from the genetic level to the organism. The networks have intensive crosstalk and form a balance in the Nash equilibrium, which is the homeostatic state in healthy conditions. Homeostasis may be described as a Nash equilibrium, which ensures energy distribution in a “democratic” way regarding the functions of the parts in the complete system. Cancer radically changes the network system in the organism. Cancer is a network disease. Deviation from healthy networking appears at every level, from genetic (molecular) to cells, tissues, organs, and organisms. The strong proliferation of malignant tissue is the origin of most of the life-threatening processes. The weak side of cancer development is the change of complex information networking in the system, being vulnerable to immune attacks. Cancer cells are masters of adaptation and evade immune surveillance. This hiding process can be broken by electromagnetic nonionizing radiation, for which the malignant structure has no adaptation strategy. Our objective is to review the different sides of living complexity and use the knowledge to fight against cancer.
