Multidimensional Complex Research Articles

Optical bottle beam transmit in polycyclic tornado mode

Light-field shaping technology is of significant importance for applications in particle trapping and optical communication. In this paper, we generate a new class of tunable polycyclic tornado Laguerre-Gaussian beams (TPTLGBs) experimentally and numerically by applying an annular spiral-zone phase (ASZP) with the second order chirped factor to Laguerre-Gaussian beams. By the parameters of the ASZP, we can modulate the focusing and diffraction of TPTLGBs along z-axis, controlling the number and quality of optical bottles (OBs) formed. In addition, it is possible to precisely control the direction of rotation of TPTLGBs during propagation. We further explore the specific effects of the ASZP and the central vortex phase on TPTLGBs. Adjusting the parameters of TPTLGBs, we obtain a high intensity focus. The multi-dimensional tunability and complex phase structure of TPTLGBs also provide new possibilities for further development of optical technology.

Inclusive Public Toilets: A Universal Design Enquiry for Indian Context.

Public toilets fulfil an essential need for all human beings. In the context of India, the diversity of population implies a diverse set of complex barriers in the public toilet experience. Inclusion and the contextual translation of universal design becomes crucial, considering the distinct socio-cultural dimensions. This study intends to enquire the above-mentioned perspective and contribute towards an understanding of inclusion and universal design in public toilets. The methodology is a three-part process including literature review, experiential case reflections and ethnographic field perspectives. The gathered data is mapped thematically and assessed qualitatively, based on the existing principles of universal design. The insights from the assessment highlight the need for contextualization of existing universal design principles, bringing out a multi-dimensional complexity of inclusion across human needs, behaviour, physical, planning and service aspects. This study paves a way forward for evolving design directions by raising further questions through fresh perspectives on inclusion & accessibility in public toilets. The raised questions contribute to a dilemma of standardisation versus contextual customisation around the understanding of inclusion and universal design, focusing on the scenario of Indian public toilets.

Comparative Analysis of the Physical, Tactical, Emotional, and Mood Characteristics of Under-13 Soccer Players by Performance Level.

Background and Objectives: Soccer is a sport characterized by various unpredictable situations in which physical abilities are associated with athletic performance. There are several capabilities that young soccer players must develop to adapt to the needs of the competition. This study analyzes the physical characteristics, tactical knowledge, emotional intelligence, and mood states of youth soccer players at different competitive levels. Materials and Methods: The sample consisted of 36 male soccer players with an average age of 12.65 ± 0.48 years, weight of 44.92 ± 7.49 kg, and height of 157.2 ± 0.08 cm. A cross-sectional correlational study design was selected. Inferential analysis was conducted via the RV coefficient to assess relationships between groups. Two-sample tests (Student's t test or the Mann-Whitney U test) were used to assess the distribution of the samples. Standardized mean differences (i.e., Cohen's d) were calculated as effect sizes. Results: For the yo-yo intermittent endurance test level 1, the Premier category showed higher speed (p = 0.01, d = 0.40) and superior estimated VO2max (p = 0.01, d = -0.91). The statistically significant variables included the hamstring strength exercise of the hamstrings for the angle of rupture (p = 0.04, d = -0.04, d = -0.72), the COD-Timer 5-0-5 for contact time-5-0-5 (ms) (p = 0.04, d = 0.69) and 10 m-5-0-5 (s) (p = 0.02, d = 0.79), tactical knowledge of in-game performance (p = 0.01, d = -1.19), support level (p = 0.01, d = -1.27), decision-making ability (p = 0.01, d = 0.59), melancholy (p = 0.01, d = 0.59), confusion (p = 0.01, d = 0.56), and emotional intelligence (p = 0.04, d = 0.77). The Premier category presented slightly higher averages than did category A. In the assessment of running-based anaerobic sprint test power (p < 0.05, d = 0.83) and mood states (p < 0.05, d = 0.59), players in category A presented higher results. Conclusions: The performance capacity of youth soccer players encompasses a multidimensional complexity that includes physical, tactical, emotional, and psychological aspects, which vary among players of the same age.

Factors that promote student well-being in schools: a scoping review of Australian and Aotearoa New Zealand literature

Well-being has been touted for many years as a critical factor in achieving positive outcomes for students in schools across Australia, Aotearoa New Zealand, and globally. Despite extensive reporting of student well-being concerns, further research is needed to fully understand this complex construct. This paper presents a scoping review aimed at developing a comprehensive understanding of student well-being by examining key factors highlighted in the literature. Using the PRISMA-ScR approach, a search was conducted using Google Scholar to identify studies published between 2010 and 2023 that focus on student well-being in Australian and Aotearoa New Zealand school contexts. Additional relevant grey literature, including policy documents, contributed to this review. A total of 46 studies met the eligibility criteria for more detailed analysis. The review identified three primary themes influencing student well-being: the role of student voice, the impact of the physical environment (which we call perivallon), and the nature of student relationships with teachers, peers, and themselves. These factors were found to be interrelated, with relationships serving as both an independent influence and a mediating factor affecting the other dimensions. The literature review leads to a multi-dimensional complexity model of well-being. This model suggests potential mechanisms by which a small change to an external factor can have far reaching, and potentially unexpected, impacts on student well-being. The implications and limitations of such a model are discussed, and avenues for future research are suggested.

Complexity Evaluation for Urban Intersection Scenarios in Autonomous Driving Tests: Method and Validation

As autonomous driving technology scales up, complex urban intersections pose significant safety challenges. Current testing methods struggle to simulate these complex scenarios at a manageable cost, making simulation testing essential. For effective evaluation, establishing comprehensive and objective complexity metrics is crucial. However, existing complexity evaluation methods often depend on the performance of the primary vehicle and are based on local interaction relationships, which lack a global perspective and objectivity and have yet to be validated by autonomous driving systems. To address this issue, this paper proposes a multidimensional complexity assessment framework that introduces system-level indicators such as vehicle count, interaction density, disorder, and risk. This framework quantifies the complex interactions at intersections from a global perspective, independent of primary vehicle performance. Experimental results demonstrate that the complexity evaluation results are highly consistent with the performance of a high-level autonomous driving system (Apollo). The framework has been successfully applied to test scenario generation on the Apollo platform, achieving twice the scenario generation efficiency of traditional methods, thus showcasing substantial engineering value.

Measuring complexity in mega construction projects: fuzzy comprehensive evaluation and grey relational analysis

PurposeMega construction projects (MCPs), characterized by their vast scale, numerous stakeholders and complex management, often face significant uncertainties and challenges. While existing research has explored the complexity of MCPs, it predominantly focuses on qualitative analysis and lacks systematic quantitative measurement methods. Therefore, this study aims to construct a complexity measurement model for MCPs using fuzzy comprehensive evaluation and grey relational analysis.Design/methodology/approachThis study first constructs a complexity measurement framework through a systematic literature review, covering six dimensions of technical complexity, organizational complexity, goal complexity, environmental complexity, cultural complexity and information complexity and comprising 30 influencing factors. Secondly, a fuzzy evaluation matrix for complexity is constructed using a generalized bell-shaped membership function to effectively handle the fuzziness and uncertainty in the assessment. Subsequently, grey relational analysis is used to calculate the relational degree of each complexity factor, identifying their weights in the overall complexity. Finally, the weighted comprehensive evaluation results of project complexity are derived by combining the fuzzy evaluation results with the grey relational degrees.FindingsTo validate the model’s effectiveness, the 2020 Xi’an Silk Road International Conference Center construction project is used as a case study. The results indicate that the overall complexity level of the project is moderate, with goal complexity being the highest, followed by organizational complexity, environmental complexity, technical complexity, cultural complexity and informational complexity. The empirical analysis demonstrates that the model can accurately reflect the variations across different dimensions of MCP complexity and can be effectively applied in real-world projects.Originality/valueThis study systematically integrates research on MCPs complexity, establishing a multidimensional complexity measurement framework that addresses the limitations of previous studies focusing on partial dimensions. Moreover, the proposed quantitative measurement model combines fuzzy comprehensive evaluation and grey relational analysis, enhancing the accuracy and objectivity of complexity measurement while minimizing subjective bias. Lastly, the model has broad applicability and can be used in MCPs across different countries and regions, providing a scientific and effective basis for identifying and managing MCP complexity.

Multi-relation spatiotemporal graph residual network model with multi-level feature attention: A novel approach for landslide displacement prediction

Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters. While most existing prediction methods focus on time-series forecasting for individual monitoring points, there is limited research on the spatiotemporal characteristics of landslide deformation. This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention (MFA-MRSTGRN) that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion. This model integrates internal seepage factors as data feature enhancements with external triggering factors, allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset. The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules: multi-level feature attention, temporal-residual decomposition, spatial multi-relational graph convolution, and spatiotemporal fusion prediction. This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets, facilitating adaptive exploration of the evolving multi-relational, multi-dimensional spatiotemporal complexities in landslides. When applying this model to predict the displacement of the Liangshuijing landslide, we demonstrate that the MFA-MRSTGRN model surpasses traditional models, such as random forest (RF), long short-term memory (LSTM), and spatial temporal graph convolutional networks (ST-GCN) models in terms of various evaluation metrics including mean absolute error (MAE = 1.27 mm), root mean square error (RMSE = 1.49 mm), mean absolute percentage error (MAPE = 0.026), and R-squared (R2 = 0.88). Furthermore, feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models. This research provides an advanced and reliable method for landslide displacement prediction.

Intelligent Diagnosis of Bearing Failures Based on Recurrence Quantification and Energy Difference

Bearing health is key for maintaining good performance and safety in rotating machinery. As the diagnosis of mechanical faults develops toward intelligence and automation, accurate and systematic fault diagnosis algorithms are imperative. Focusing on the diagnosis of rolling bearing failures, this study utilizes a sliding time window to extract essential data segments. A series of signal processing techniques, including filtering, amplitude–frequency analysis, Hilbert envelope analysis, and energy analysis, is applied to establish a comprehensive dataset. For extraction of the hidden properties of the data, the recurrence quantity spectrum is defined for the input of the neural network. The goal is to obtain a cleaner dataset with enhanced features. A convolution neural network is constructed. Different activation functions in the activation layer are compared for better fault diagnosis algorithms. The established feature matrices are specifically defined to accurately identify the subtlest defects of bearings, thereby facilitating early detection. The proposed procedure distinguishes various fault modes. As for the multidimensional complexities of fault signals, this study carries out a comprehensive comparison of energies, recurrence quantification, and amplitude–frequency characteristics of bearing fault detection to assess the accuracy, computational efficiency, and robustness of bearing fault diagnosis. The proposed method and bearing fault detection procedures have potential in practical applications.

Multidimensional multiscale complexity analysis of sediment dynamics in the Yanhe Watershed of the loess Plateau, China

The Yanhe Watershed, emblematic of the loess hilly-gully landscape and ecological fragility in China's Loess Plateau, has experienced significant soil erosion and extensive soil-water conservation measures. To elucidate sediment dynamics and identify influencing factors in this region from 1960 to 2020, a novel multidimensional multiscale complexity analysis (MMCA) method was developed, based on entropy and complexity perspectives. This method integrated the refined composite multiscale fuzzy entropy (RCMFE) with multidimensional complexity analysis, offering a nuanced evaluation of sediment complexity and its implications for water resource management and ecological restoration. The findings revealed two distinct stages of sediment complexity variations: 1971–1988 and 2000–present. During the first period, the operation of the Wangyao Reservoir predominantly influenced sediment dynamics, initially reducing sediment complexity through sediment interception but later increasing it during discharge phases, particularly at larger scales. After 2002, extensive vegetation restoration efforts significantly reduced sediment complexity but raised concerns about long-term ecosystem resilience. Over the past decade, urbanization and climate change have exacerbated sediment instability, especially over semi-annual scales. This study advocates for management strategies that prioritize ecosystem sustainability and address the challenges posed by climate change and urbanization, facilitating improved soil and water conservation efforts in the Yanhe Watershed and similar regions in the Loess Plateau.

Canonical Transient Receptor Potential (TRPC) Channels in Cardiovascular Pathology and their Modulators.

Ion channels play a crucial role in various aspects of cardiac function, such as regulating rhythm and contractility. As a result, they serve as key targets for therapeutic interventions in cardiovascular diseases. Cell function is substantially influenced by the concentration of free cytosolic calcium (Ca2+) and the voltage across the plasma membrane. These characteristics are known to be regulated by Ca2+-permeable non-selective cationic channels, although our knowledge of these channels is still inadequate. The transient receptor potential (TRP) superfamily comprises of many non-selective cation channels with diverse Ca2+ permeability. Canonical or classical TRP (TRPC) channels are a subgroup of the TRP superfamily that are expressed ubiquitously in mammalian cells. TRPC channels are multidimensional signalling protein complexes that play essential roles in a variety of physiological and pathological processes in humans, including cancer, neurological disorders, cardiovascular diseases, and others. The objective of this article is to focus on the role that TRPC channels play in the cardiovascular system. The role of TRPC channels will be deeply discussed in cardiovascular pathology. Together, a critical element in developing novel treatments that target TRPC channels is comprehending the molecular mechanisms and regulatory pathways of TRPC channels in related cardiovascular diseases and conditions.

Oblique collision of low-frequency dust-acoustic solitons and rogue waves in a multi-dimensional anisotropic self-gravitating electron-depleted complex plasmas

Oblique collision of low-frequency dust-acoustic solitons and rogue waves in a multi-dimensional anisotropic self-gravitating electron-depleted complex plasmas

Der Standort Österreich aus Sicht der ökonomischen Komplexität

Abstract Economic complexity indicators attempt to map latent factors for long-term growth. In this analysis, we shed light on Austria as a business location using multidimensional complexity indicators that allow statements to be made about regional specialization, key technologies for the green transition and individual sectors such as the semiconductor industry. Austria usually occupies top international positions or is at least among the leaders, and this has remained stable over the last 20 years. This implies extensive opportunities for diversification into promising technologies. For individual brown industries, however, there is a risk of getting locked into products whose demand will decline in the course of the green transition.

Multidimensional complex signal processing and feature extraction for fatigue testing data

AbstractThis study focuses on implementing a multiaxial racetrack amplitude filter designed for processing fatigue testing data. The filter utilizes the concept of a multiaxial racetrack to map a multidimensional signal into a multidimensional space and employs amplitude filtering to eliminate noise while preserving structural outliers and sequential characteristics inherent in the signal. This research evaluates the effectiveness of this method in processing multidimensional data and compares it to conventional data preprocessing methods in the context of fatigue test data. Furthermore, the effectiveness of two optimization strategies proposed to address the limitations related to the filter's “filtering radius” and “filtering direction” has been validated. The findings reveal that the proposed filter is a versatile multidimensional signal processing technique suitable for diverse domains requiring signal order and shape preservation, particularly in fatigue analysis.

Transformable 3D curved high-density liquid metal coils – an integrated unit for general soft actuation, sensing and communication

Rigid solenoid coils have long been indispensable in modern intelligent devices. However, their sparse structure and challenging preparation of flexible coils for soft robots impose limitations. Here, a transformable 3D curved high-density liquid metal coil (HD-LMC) is introduced that surpasses the structural density level of enameled wire. The fabrication technique employed for high-density channels in elastomers is universally applicable. Such HD-LMCs demonstrated excellent performance in pressure, temperature, non-contact distance sensors, and near-field communication. Soft electromagnetic actuators thus achieved significantly improved the electromagnetic force and power density. Moreover, precise control of swinging tail motion enables a bionic pufferfish to swim. Finally, HD-LMC is further utilized to successfully implement a soft rotary robot with integrated sensing and actuation capabilities. This groundbreaking research provides a theoretical and experimental basis for expanding the applications of liquid metal-based multi-dimensional complex flexible electronics and is expected to be widely used in liquid metal-integrated robotic systems.

Administrative legal principles of human rights-based approach by the police

One of the priority tasks of reforming law enforcement agencies is to build a preventive mechanism based on the observance of human and civil rights and freedoms, protection of society from violence and discrimination, and creation of barrier-free space for people with limited mobility. The multidimensional nature and complexity of the issues requiring statutory regulation in these areas determine the relevance of the subject under study. The purpose of this study was to model the administrative legal mechanism of police activity in which human rights would be optimally and effectively implemented. To fulfil this purpose, the methodology used included a combination of comparative rule-making, system analysis, internal and external induction, constructive cognition and content analysis. It was found that the observance of human rights in police activities is inextricably linked to the implementation of the rule of law and the provision of protective police services. Numerous cases of violations revealed during journalistic investigations and widely discussed by the public have become one of the reasons for the rapid decline in public trust in state law enforcement institutions, and as a result, a substantial obstacle to Ukraine’s integration into the European space. The study analysed the key reasons affecting the effectiveness of administrative legal strategies for ensuring a human rights-based approach in the practical activities of the National Police bodies (units). Specifically, these include transition processes related to the harmonisation of national legislation with international and European standards, low level of material and social security of police officers, insufficient level of professionalism, influence of negative environment, narrow understanding of administrative legal activities in the field of human rights related to the prevention of administrative and criminal offences. The study concluded that the principles of the rule of law, respect for human rights and freedoms and partnership-based interaction with the public are crucial and interrelated in the preventive activities of police. The study outlined the key areas of improvement of national legislation in the field of development and/or optimisation of administrative legal systems for ensuring the functioning of organisational, technical, information, and economic resources as guarantees of the implementation of the declared constitutional rights and freedoms. The results of this study can be used to formulate and improve the norms of national legislation that regulate the activities of law enforcement agencies and determine the content of its guidelines

Computational Simulation of Monopile Scour under Tidal Flow Considering Suspended Energy Dissipation

Local scour around bridge foundations significantly impacts the stability and safety of marine structures. The development of scour holes adjacent to the pile foundations of sea-crossing bridges, influenced by tidal currents, involves multidimensional physical fields, multiscale coupling, and complex variations in marine loads. However, experimental models alone are inadequate for investigating the underlying mechanisms. Numerical simulation, a critical tool for studying local scour processes, faces the challenge of accurately modeling sediment transport, particularly under tidal flow conditions near pile foundations. To solve this challenge, this research considers the effect of reciprocating flow on sediment shear as well as its characteristic dissipation based on the immersed boundary method, introduces a reciprocating flow dissipation mechanism, and adds a momentum exchange term between the fluid and the sediment to derive a new controlling equation; a new tidal flow localized scour solver is ultimately constructed, termed TidalflowFOAM. The solver effectively simulates complex flow conditions under tidal currents, extending the modeling capabilities to more realistic three-dimensional bridge scour scenarios under combined wave and current conditions. Validation through cases reported in the literature and a series of controlled experiments, encompassing varying depths, flow velocities, and pile diameters, demonstrates the solver’s proficiency in capturing post-vortex data and accurately reflecting the influence of key factors on scour depth. However, the fidelity of the simulated scour hole morphology under tidal flow conditions behind the piles requires enhancement. The proposed numerical model for tidal flow conditions has high solution accuracy and can guide practical engineering applications.

Multidimensional Encryption by Chip-Integrated Metasurfaces.

Facing the challenge of information security in the current era of information technology, optical encryption based on metasurfaces presents a promising solution to this issue. However, most metasurface-based encryption techniques rely on limited decoding keys and struggle to achieve multidimensional complex encryption. It hinders the progress of optical storage capacity and puts encryption security at a disclosing risk. Here, we propose and experimentally demonstrate a multidimensional encryption system based on chip-integrated metasurfaces that successfully incorporates the simultaneous manipulation of three-dimensional optical parameters, including wavelength, direction, and polarization. Hence, up to eight-channel augmented reality (AR) holograms are concealed by near- and far-field fused encryption, which can only be extracted by correctly providing the three-dimensional decoding keys and then vividly exhibit to the authorizer with low crosstalk, high definition, and no zero-order speckle noise. We envision that the miniature chip-integrated metasurface strategy for multidimensional encryption functionalities promises a feasible route toward the encryption capacity and information security enhancement of the anticounterfeiting performance and optically cryptographic storage.

The Relationship between Commercial, Technological, Research (Multidimensional) Complexity Indices and Financial Development

The source of economic growth is the supply-demand balance. Demand refers to consumption and supply refers to production. Producing quality products plays an important role on the production side of this balance. The country, which has a wide range of qualified products called sophisticated products, continues to grow with financial development. The concept of economic complexity refers to product diversity. This concept has taken its place in the literature by being expanded into commercial, technological, and research complexity indices as the content of the multidimensional complexity index. In this study, the relationship between multidimensional complexity indices and financial development indicators of E7 (Emerging) countries (Brazil, China, India, Indonesia, Mexico, Russia, Turkey) is analyzed with Gengenbach, Urbain, and Westerlund Cointegration Test and Mean Group Estimator applied in case of cointegration. It has been determined that these variables are cointegrated, and this relationship between the commercial and technological complexity index and financial development is significant. As a result of the analysis with the mean group estimator, it was concluded that the technological complexity index has a greater impact on financial development than the commercial and research complexity indices.

Dynamic Cleavage-Remodeling of Covalent Organic Networks into Multidimensional Superstructures.

Superstructures with complex hierarchical spatial configurations exhibit broader structural depth than single hierarchical structures and the associated broader application prospects. However, current preparation methods are greatly constrained by cumbersome steps and harsh conditions. Here, for the first time, a concise and efficient thermally responsive dynamic synthesis strategy for the preparation of multidimensional complex superstructures within soluble covalent organic networks (SCONs) with tunable morphology from 0D hollow supraparticles to 2D films is presented. Mechanism study reveals the thermally responsive dynamic "cleavage-remodeling" characteristics of SCONs, synthesized based on the unique bilayer structure of (2.2)paracyclophane, and the temperature control facilitates the process from reversible solubility to reorganization and construction of superstructures. Specifically, during the process, the oil-water-emulsion two-phase interface can be generated through droplet jetting, leading to the preparation of 0D hollow supraparticles and other bowl-like complex superstructures with high yield. Additionally, by modulating the volatility and solubility of exogenous solvents, defect-free 2D films are prepared relying on an air-liquid interface. Expanded experiments further confirm the generalizability and scalability of the proposed dynamic "cleavage-remodeling" strategy. Research on the enrichment mechanism of guest iodine highlights the superior kinetic mass transfer performance of superstructural products compared to single-hierarchical materials.

First Evidence on the Validity of the Complexity Index Derived from the Resident Assessment Instrument for Home Care in Home Care Patients

ObjectivesRecently, a Complexity Index (CI), based on the multidimensional complexity model and derived from the Resident Assessment Instrument for Home Care (interRAI HC) was proposed as a decision-support tool to help frontline health care professionals in their clinical evaluation to identify and analyze complex situations. This study aims to test the CI: (1) concurrent validity with another measure of complexity (ie, the COMID), (2) convergent validity with related constructs assessed by interRAI HC scales (eg, depression), (3) divergent validity (comparison between CI-COMID and scales-COMID correlations), and (4) predictive validity on coordination meetings. DesignA cross-sectional observational design was used for a secondary analysis of interRAI HC and COMID data collected in routine home care nursing practice (July-December 2021). Setting and ParticipantsParticipants were community-dwelling adults receiving home care, with full interRAI HC and COMID assessments (N = 3533). MethodsCorrelational analyses were conducted to test the concurrent validity of the CI (with the COMID) and the convergent and divergent validity of the CI (with interRAI HCSwitzerland scales, eg, Depression Rating Scale, Method for Assigning Priority Levels, and a Frailty Index). A receiver operating characteristic (ROC) analysis was conducted to test the discriminative ability of CI on specific professional team coordination meetings. ResultsResults showed that the CI correlated positively and strongly with the COMID (ρ = 0.691, P < .001, concurrent validity), positively with all the tested scales (P < .001, convergent validity), whereas the CI-COMID correlation was higher than the interRAI HC scales–COMID correlations (divergent validity). The ROC analysis showed the CI had a high area under the curve (AUC = 0.719, predictive validity). Conclusions and ImplicationsThe CI demonstrates good validity properties with a strong correlation with the COMID and a high predictive value for coordination meeting. It is distinct from the other interRAI HC scales and has its place among them to support the clinical analysis of complex situations.