Complexity Considerations in the Heisenberg Uncertainty Principle

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.

Scale, Complexity, and Cybersecurity Risk Management

Elementary information theory is used to model cybersecurity complexity, where the model assumes that security risk management is a binomial stochastic process. Complexity is shown to increase exponentially with the number of vulnerabilities in combination with security risk management entropy. However, vulnerabilities can be either local or non-local, where the former is confined to networked elements and the latter results from interactions between elements. Furthermore, interactions involve multiple methods of communication, where each method can contain vulnerabilities specific to that method. Importantly, the number of possible interactions scales quadratically with the number of elements in standard network topologies. Minimizing these interactions can significantly reduce the number of vulnerabilities and the accompanying complexity. Two network configurations that yield sub-quadratic and linear scaling relations are presented.

Applying the Shearlet-Based Complexity Measure for Analyzing Mass Transfer in Continuous-Flow Microchannels

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.

The Impact of Storyline Complexity on L2 Learners’Written Performance

Task-based Language Teaching(TBLT)research has provided ample evidence that cognitive complexity is an important aspect of task design that influences learner’s performance in terms of fluency,accuracy,and syntactic complexity.Despite the substantial number of empirical investigations into task complexity in journal articles,storyline complexity,one of the features of it,is scarcely investigated.Previous research mainly focused on the impact of storyline complexity on learners’oral performance,but the impact on learners’written performance is less investigated.Thus,this study aims at investigating the effects of narrative complexity of storyline on senior high school students’written performance,as displayed by its complexity,fluency,and accuracy.The present study has important pedagogical implications.That is,task design and assessment should make a distinction between different types of narrative tasks.For example,the task with single or dual storyline.Results on task complexity may contribute to informing the pedagogical choices made by teachers when prioritizing work with a specific linguistic dimension.

Exploring Biocomplexity in Cancer: A Comprehensive Review

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.

Data complexity-based batch sanitization method against poison in distributed learning

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.

A Comparative Analysis of Syntactic Complexity in Applied Linguistics Abstracts Written by Chinese Novice Writers and Native English Advanced Writers

The rhetorical structure of abstracts has been a widely discussed topic, as it can greatly enhance the abstract writing skills of second-language writers. This study aims to provide guidance on the syntactic features that L2 learners can employ, as well as suggest which features they should focus on in English academic writing. To achieve this, all samples were analyzed for rhetorical moves using Hyland’s five-rhetorical move model. Additionally, all sentences were evaluated for syntactic complexity, considering measures such as global, clausal and phrasal complexity. The findings reveal that expert writers exhibit a more balanced use of syntactic complexity across moves, effectively fulfilling the rhetorical objectives of abstracts. On the other hand, MA students tend to rely excessively on embedded structures and dependent clauses in an attempt to increase complexity. The implications of these findings for academic writing research, pedagogy, and assessment are thoroughly discussed.

Analysis of the Role of Syntactic Complexity in Students’ Reading Comprehension: A Teacher’s Perspective

This study examines the role of the syntactic complexity of the text in the reading comprehension skills of students.Utilizing the qualitative method of research,this paper used structured interview questions as the main data-gathering instruments.English language teachers from Coral na Munti National High School were selected as the respondents of the study.Finding of the study suggests that the syntactic complexity of the text affects the reading comprehension of the students.Students found it challenging to understand the message that the author conveyed if he or she used a large number of phrases and clauses in one sentence.Furthermore,the complex sentence syntactic structure was deemed the most challenging for students to understand.To overcome said challenges in comprehending text,various reading intervention programs were utilized by teachers.These interventions include focused or targeted instruction and the implementation of the Project Dear,suggested by the Department of Education.These programs were proven to help students improve their comprehension as well as their knowledge in syntactical structure of sentences.This study underscores the importance of selecting appropriate reading materials and implementing suitable reading intervention programs to enhance students’comprehension skills.

Numerical simulation of downhole temperature distribution in producing oil wells

An improved numerical simulation method is presented to calculate the downhole temperature distribution for multiple pay zones in producing oil wells. Based on hydrodynamics and heat transfer theory, a 2-D temperature field model in cylindrical coordinates is developed. In the model, we considered general heat conduction as well as the heat convection due to fluid flow from porous formation to the borehole. We also take into account the fluid velocity variation in the wellbore due to multiple pay zones. We present coupled boundary conditions at the interfaces between the wellbore and adjacent formation, the wellbore and pay zone, and the pay zone and adjacent formation. Finally, an alternating direction implicit difference method （ADI） is used to solve the temperature model for the downhole temperature distribution. The comparison of modeled temperature curve with actual temperature log indicates that simulation result is in general quite similar to the actual temperature log. We found that the total production rate, production time, porosity, thickness of pay zones, and geothermal gradient, all have effects on the downhole temperature distribution.

基于Downhole工艺的海底静力触探及其设备研制

论述基于Downhole CPT的海底静力触探工艺和实施方案,并在此基础上研制了适用于水深10～100 m,触探最大深度120 m的海底静力触探设备。对设备中的管内锥探总成、海底机座以及推进速度控制策略等核心问题进行了探讨。码头与海底试验中,触探数据结果与钻探取样基本符合,验证了工艺方案与触探设备达到了预期的工艺要求。

Complexity and applicability analysis among OVM, GFM and FVDM models

The complexity and applicability of three relative car-following models are investigated and they are the optimal velocity model （OVM）,the generalized force model （GFM） and the full velocity difference model （FVDM）.The vehicle trajectory data used is collected from the digital pictures obtained at a 30-storey building near Ⅰ-80 freeway.Three different calibrating methods are used to estimate the model parameters and to study the relationships between model complexity and applicability from overall,inter-driver and intra-driver analysis.Results of the three methods of the OVM,GFM and FVDM show that the complexity and applicability are not consistent and the complicated models are not always superior to the simple ones in modeling car-following.The findings of this study can provide useful information for car-following behavior modeling.

Study on complexity of plant communities at different altitudes on the Northern Slope of Changbai Mountain

By the method of gradient pattern analysis, twenty plots were set at altitudes of 700-2600 m with an interval of 100 m on the northern slope of the Changbai Mountain. The dissimilarity of respective sub-plots in the same community was measured and the complexity of plant communities at different altitudes was analyzed. The result from binary data of tree species in canopy tree indicated that the sub-plots in the communities, except subalpine Betula ermanii forest, showed comparatively high dissimilarity in species composition. Especially, the dissimilarity index (0.7) of broadleaved/Korean pine forest at low altitudes was obviously higher than other communities. The differences are not obvious between communities referring to dark coniferous forest. Comparatively, the dissimilarity in sub-plots of the communities at altitude of 1400 m was slightly higher than that of other communities, which reflected the complexity of tree species compositions of transitory-type communities. For subalpine Betula ermanii forest, tree species composition was simple and showed a high similarity between sub-plots. The results derived from binary data of shrub showed that the dissimilarity index of shrub species in broadleaved/Korean pine forest at low altitudes was higher than that in other communities, but the divergence tendency wasn抰 so obvious as that of arbor species. The dissimilarity derived from binary data of herb and all plant species at different altitudes showed greatly close tendency, and the differences in herb and all plant species between sub-plots were the greatest for the communities of broad-leaved-Korean pine forest and alpine tundra zone..

Structural Complexity Analysis of Information Systems Based on Petri Nets

Aim To present a quantitative method for structural complexity analysis and evaluation of information systems. Methods Based on Petri net modeling and analysis techniques and with the aid of mathematical tools in general net theory(GNT), a quantitative method for structure description and analysis of information systems was introduced. Results The structural complexity index and two related factors, i.e. element complexity factor and connection complexity factor were defined, and the relations between them and the parameters of the Petri net based model of the system were derived. Application example was presented. Conclusion The proposed method provides a theoretical basis for quantitative analysis and evaluation of the structural complexity and can be applied in the general planning and design processes of the information systems.

Reasoning complexity for extended fuzzy description logic with qualifying number restriction

To solve the extended fuzzy description logic with qualifying number restriction （EFALCQ） reasoning problems, EFALCQ is discretely simulated by description logic with qualifying number restriction （ALCQ）, and ALCQ reasoning results are reused to prove the complexity of EFALCQ reasoning problems. The ALCQ simulation method for the consistency of EFALCQ is proposed. This method reduces EFALCQ satisfiability into EFALCQ consistency, and uses EFALCQ satisfiability to discretely simulate EFALCQ satdomain. It is proved that the reasoning complexity for EFALCQ satisfiability, consistency and sat-domain is PSPACE-complete.

Improved reduced-complexity bit and power allocation algorithms for multicarrier systems

Based on the iterative bit-filling procedure, a computationally efficient bit and power allocation algorithm is presented. The algorithm improves the conventional bit-filling algorithms by maintaining only a subset of subcarriers for computation in each iteration, which reduces the complexity without any performance degradation. Moreover, a modified algorithm with even lower complexity is developed, and equal power allocation is introduced as an initial allocation to accelerate its convergence. Simulation results show that the modified algorithm achieves a considerable complexity reduction while causing only a minor drop in performance.

Complexity Behind Simplicity——An analysis of Langston Hughes' Art of Writing in "Early Autumn"

Love is an eternal subject with many references in many novels,but Langston Hughes approaches it in a most simplified manner to portray the complex feeling of the protagonists.He achieves this inward complexity through carefully-treated outward simplicity.The paper discusses this art of writing in Early Autumn from such aspects as the dramatic point of view,well-designed setting,careful presentation and effective rhetorical devices.

The Complexity of Metaphor

Being as one figurative form of language,metaphor plays the most complicated role to make language colorful and vivid.Demonstrating the types and the features of metaphor,this article will focus on the point that metaphor is a complex language phenomenon heavily loaded with the factor of culture.

On Sentence Complexity in THE TIMES: A Comparative Study of SentenceLength and Sentence Complexity in the News Section and the Sports Section

My investigation will serve two purposes. First, I shall investigate the function of the subclauses in the corpus in relation to their complexity, and I shall establish whether there is a correlation between sentence length and sentence complexity.Second, I shall analyse the complexity of the subclauses collected from the two sections and compare the results from these sections, focusing on finite subclauses and non-finite subclauses. I hope to be able to point out some differences in style between the news and sports sections concerning the use of subordinate clauses in various syntactic functions in order to examine how the choice of linguistic structures differs in different sections of The Times.

Numerical simulation of surface and downholedeformation induced by hydraulic fracturing

Tiltmeter mapping technology infers hydraulic fracture geometry by measuringfracture-induced rock deformation, which recorded by highly sensitive tiltmeters placed atthe surface and in nearby observation wells. By referencing Okada＇s linear elastic theory andGreen＇s function method, we simulate and analyze the surface and downhole deformationcaused by hydraulic fracturing using the homogeneous elastic half-space model and layeredelastic model. Simulation results suggest that there is not much difference in the surfacedeformation patterns between the two models, but there is a significant difference in thedownhole deformation patterns when hydraulic fracturing penetrates a stratum. In suchcases, it is not suitable to assume uniform elastic half-space when calculating the downholedeformation. This work may improve the accuracy and reliability of the inversion results oftiltmeter monitoring data.

Using the curve moment and the PSO-SVM method to diagnose downhole conditions of a sucker rod pumping unit

Downhole working conditions of sucker rod pumping wells are automatically identified on a computer from the analysis of dynamometer cards. In this process, extraction of feature parameters and pattern classification are two key steps. The dynamometer card is firstly divided into four parts which include different production information according to the ＂four point method＂ used in actual oilfield production, and then the moment invariants for pattern recognition are extracted. An improved support vector machine （SVM） method is used for pattern classification whose error penalty parameter C and kernel function parameter g are optimally chosen by the particle swarm optimization （PSO） algorithm. The simulation results show the method proposed in this paper has good classification results.