Actual Patterns Research Articles

Decoding the spread of non-indigenous fishes in the Mediterranean Sea

The ocean is dynamically changing due to the influence of climate processes and human activities. The construction of the Suez Canal in the late nineteenth century opened the Pandora’s box by facilitating the dispersal of Red Sea species in the Mediterranean Sea. In this study, we developed an open-source spatio-temporal numerical analysis framework to decodify the complex spread of Mediterranean non-indigenous fish species (NIS) that entered through the Suez Canal. We utilized 772 historical detection records of 130 NIS to disentangle their dynamic spread through space and time. The results indicated that species follow a north-westward trajectory with an average expansion time step of 2.5 years. Additionally, we estimated the overall time for a NIS to reach the Central Mediterranean Sea from the Suez Canal at approximately 22 years. Based on the analysis, more than half of the introduced fishes have been established in less than 10 years. Finally, we proceeded in the cross-validation of our results using actual spread patterns of invasive fishes of the Mediterranean Sea, resulting up to 90% of temporal and spatial agreement. The methodology and the findings presented herein may contribute to management initiatives in highly invaded regions around the globe.

Bio-inspired “Self-denoising” capability of 2D materials incorporated optoelectronic synaptic array

In in-sensor image preprocessing, the sensed image undergoes low level processing like denoising at the sensor end, similar to the retina of human eye. Optoelectronic synapse devices are potential contenders for this purpose, and subsequent applications in artificial neural networks (ANNs). The optoelectronic synapses can offer image pre-processing functionalities at the pixel itself—termed as in-pixel computing. Denoising is an important problem in image preprocessing and several approaches have been used to denoise the input images. While most of those approaches require external circuitry, others are efficient only when the noisy pixels have significantly lower intensity compared to the actual pattern pixels. In this work, we present the innate ability of an optoelectronic synapse array to perform denoising at the pixel itself once it is trained to memorize an image. The synapses consist of phototransistors with bilayer MoS2 channel and p-Si/PtTe2 buried gate electrode. Our 7 × 7 array shows excellent robustness to noise due to the interplay between long-term potentiation and short-term potentiation. This bio-inspired strategy enables denoising of noise with higher intensity than the memorized pattern, without the use of any external circuitry. Specifically, due to the ability of these synapses to respond distinctively to wavelengths from 300 nm in ultraviolet to 2 µm in infrared, the pixel array also denoises mixed-color interferences. The “self-denoising” capability of such an artificial visual array has the capacity to eliminate the need for raw data transmission and thus, reduce subsequent image processing steps for supervised learning.

Load Forecasting and Operation Optimization of Ice-Storage Air Conditioners Based on Improved Deep-Belief Network

The prediction of cold load in ice-storage air conditioning systems plays a pivotal role in optimizing air conditioning operations, significantly contributing to the equilibrium of regional electricity supply and demand, mitigating power grid stress, and curtailing energy consumption in power grids. Addressing the issues of minimal correlation between input and output data and the suboptimal prediction accuracy inherent in traditional deep-belief neural-network models, this study introduces an enhanced deep-belief neural-network combination prediction model. This model is refined through an advanced genetic algorithm in conjunction with the “Statistical Products and Services Solution” version 25.0 software, aiming to augment the precision of ice-storage air conditioning load predictions. Initially, the input data undergo processing via the “Statistical Products and Services Solution” software, which facilitates the exclusion of samples exhibiting low coupling. Subsequently, the improved genetic algorithm implements adaptive adjustments to surmount the challenge of random weight parameter initialization prevalent in traditional deep-belief networks. Consequently, an optimized deep-belief neural-network load prediction model, predicated on the enhanced genetic algorithm, is established and subjected to training. Ultimately, the model undergoes simulation validation across three critical dimensions: operational performance, prediction evaluation indices, and operating costs of ice-storage air conditioners. The results indicate that, compared to existing methods for predicting the cooling load of ice-storage air conditioning, the proposed model achieves a prediction accuracy of 96.52%. It also shows an average improvement of 14.12% in computational performance and a 14.32% reduction in model energy consumption. The prediction outcomes align with the actual cooling-load variation patterns. Furthermore, the daily operational cost of ice-storage air conditioning, derived from the predicted cooling-load data, has an error margin of only 2.36%. This contributes to the optimization of ice-storage air conditioning operations.

Вербальные фатические паттерны в русско-, немецко- и англоязычном экзаменационном дискурсе

The central task of the presented research is to describe the consideration of actual patterns as culturally fixed communicative formulas implemented by senders in order to establish, maintain or interrupt/terminate a communicative contact and achieve the initial communicative intention. From the standpoint of the integrative-comparative approach being developed, combining the achievements of various scientific fields, an attempt is made to fill in some theoretical and methodological gaps in this subject area, including the definition of the phatic function of communication is clarified and a step is taken to develop a systematic representation of contact patterns as means of its verbal expression. The object of the study is the phatic function of communication, the subject is contact patterns. As the research material, the fragments of texts of the Russian-, German- and English-language examination discourse as a multidimensional broad-context education, the core of which is the communicative situation "exam", represented by a variable set of relevant event moments, are analyzed. Each of the highlighted event moments of this situation (greeting, introduction, ticket offer /selection, preparation of the answer, response, additional questions, evaluation of the answer, gratitude, farewell) is correlated with a conventional set of phatic patterns in Russian, German and English. The nomenclature of national factual patterns is illustrated by concrete examples from the corresponding national corpora. The actual patterns are classified taking into account the contextual environment, the initial communicative intention, convolution/unfoldment, the presence or absence of emotional and axiological coloring. There are actual patterns that are actualized mainly by the examiner or examinee, and patterns that can be implemented by all participants in this communicative situation. Prospects for further research are outlined, first of all, the hierarchical ordering of contact patterns and the accentuation of their performativity.

Predicting parameters of airway dynamics generated from inspiratory and expiratory plethysmographic airway loops, differentiating subtypes of chronic obstructive diseases

BackgroundThe plethysmographic shift volume–flow loop (sRaw-loop) measured during tidal breathing allows the determination of several lung function parameters such as the effective specific airway resistance (sReff), calculated from the ratio...

Monitoring of Ventilation, Portable Air Cleaner Operation, and Particulate Matter in California Classrooms: A Pilot Study

Interest in improving ventilation and indoor air quality (IAQ) in California schools has grown since the COVID-19 pandemic. This paper presents a field protocol for simultaneous monitoring of usage patterns of in-room portable air cleaners (PACs), indoor and outdoor concentrations and composition of particulate matter (PM), and CO2 as an indicator of outdoor air ventilation rates (VRs). This protocol was implemented for a 7-week pilot study in four occupied California classrooms in 2022. Monitoring results showed that VRs and indoor PM were generally well maintained in the classrooms studied. One classroom had much higher overall VRs, as well as higher average indoor PM2.5 concentrations compared to similar classrooms, suggesting a possible strong impact of window/door opening behavior on both VRs and indoor PM. The actual use patterns of PACs in these classrooms varied significantly. No clear correlations were observed between PAC use patterns and indoor PM2.5 concentrations in this pilot study, possibly due to low outdoor PM2.5 concentrations and already efficient central filtration (i.e., MERV 13 filters in central ventilation systems). Information gathered through such field monitoring can help schools to understand the actual classroom ventilation and IAQ conditions and best allocate resources to classrooms that need further IAQ improvements.

Prior-Guided gated convolutional networks for rainstorm forecasting

Accurate rainstorm forecasting is crucial for the sustainable development of human society. Recently, machine learning-based rainstorm prediction methods have shown promising results. However, these methods often fail to adequately consider the prior knowledge of rainstorms and do not explicitly account for the dynamic spatio-temporal patterns of rainstorm events. This study introduces a novel end-to-end prior-informed rainstorm forecasting model that incorporates both fundamental physical priors and the spatio-temporal development patterns of rainstorms. The model utilizes a gated convolutional encoder-decoder network to effectively represent the spatio-temporal patterns of rainstorm events. A key component of the representation network is the Substantial Derivative-GuIded gated convolutional Unit (SDGiU), which updates latent states under the constraints of physical priors. Additionally, an integrated loss function is designed to minimize reconstruction errors on multiple scales and facilitate the generation of forecasts that reproduce the actual spatio-temporal patterns of rainstorm formation, development and dissipation. Experimental results on two reanalysis datasets show that the proposed forecasting model outperforms competing state-of-the-art baselines by at least 19.7% (15.0%) in overall Critical Success Index (Heidke Skill Score). Qualitative analysis indicates that the proposed model can generate predictions that are both physically consistent and spatially-temporally coherent.

Multizone representation of time-varying airflows in naturally ventilated dwellings: Occupant-generated CO2 approach

Accurate measurement of air exchange-rates (AERs) is crucial in naturally ventilated dwellings. AER calculations must take into account the multizone and time-varying aspects to avoid significant deviations from reality. To address the issues of invasiveness, high cost, and inability to track real-time changes in airflow and to represent real airflow patterns associated with the multiple tracer gas methods, this study proposes a practical and feasible approach, belonging to the occupant-generated CO2 methods, for the multizone representation of time-varying airflow in naturally ventilated dwellings. In this approach, the idea of state traversal is introduced to account for all possible airflow patterns. For each airflow pattern, the transient indoor CO2 mass balance equation associated with Kalman filter, and the dynamic simulation of indoor temperature are applied to successively determine the airflow pattern that is closest to the actual pattern. The approach's reliability for multizone representation of airflow is validated in controlled multizone environments, and its applicability to natural ventilation of real residential situations is also evaluated. This study further examines the zoning criterion and the approach's correction capability, while also providing a detailed analysis of its strengths and weaknesses.

Visualizing road connectivity under traffic influence: a CiteSpace-based method

ABSTRACT The connectivity of roads under the influence of traffic is determined by the topological connections established by the road network and the transport connections formed by moving vehicles between two roads simultaneously. A thorough examination of this connectivity is crucial for comprehending traffic patterns and providing guidance to address transportation issues such as traffic congestion. However, existing methods ignore the intuitive representation and explanation of this connectivity, limiting the understanding of actual traffic patterns. This study aimed to intuitively visualize the connectivity of roads under the influence of traffic using CiteSpace, a bibliometric tool for analyzing the relationship between literature keywords. Here, the literature was replaced by trajectory, and keywords were replaced by roads. We then presented the connectivity of roads under the influence of traffic in a network, where nodes represented roads and edges represented the topological and transport connections between roads. A case study was conducted in Beijing, demonstrating the dynamic connectivity of roads under the influence of traffic in the visualized network. By comparing the visualized network with the topological road network, we identified three types of road connectivity under the influence of traffic: roads with topological connections but lacking transport connections, roads with transport connections but lacking topological connections, and roads with both topological and transport connections. This finding further revealed the traffic relationship between roads. Additionally, we simultaneously presented the multidimensional traffic characteristics in the visualized network, aiding in predicting traffic states.

Dimensions of Text Complexity in the Spoken and Written Modes: A Comparison of Theory-Based Models

In many studies, grammatical complexity has been treated as a single unified construct. However, other research contradicts that view, suggesting instead that the different structural types and syntactic functions of complexity features are distributed in texts in fundamentally different ways. These patterns have been documented in general corpora that include a wide range of spoken and written registers. One question that has not been fully addressed is whether grammatical complexity features are organized in the same ways in the spoken versus written modes. The present study tests the empirical adequacy of four competing models based on different theoretical conceptualizations of text complexity, comparing their goodness-of-fit in spoken versus written modes. The results show that text complexity must be treated as a multi-dimensional construct; dimensions that combine structural type and syntactic function provide the best account of the actual patterns of linguistic co-occurrence. To a large extent, the same complexity dimensions operate in both the spoken and written modes. Two of these dimensions—dependent phrases functioning as noun modifiers and finite dependent clauses functioning as clause-level constituents—represent the strongest co-occurrence patterns. In addition, these two dimensions operate in complementary distribution, in both the spoken and written modes. Overall, though, these two dimensions are shown to represent stronger co-occurrence patterns in the written mode than in the spoken mode.

Exploring and comparing pedagogical beliefs of university instructors in relation to their behavioural patterns regarding learning management system use

ABSTRACT Understanding the relationship between instructors’ pedagogical beliefs and their usage of learning management systems (LMSs) is crucial in higher education. This study addresses this research gap by studying how 64 active university teachers’ pedagogical beliefs match their LMS usage behaviours. Based on 1374 LMS courses, this study intended to illuminate the complex relationship between teachers’ traditional, constructivist, ICT-based beliefs and operational behaviours while using an LMS for technology-enhanced instruction. Four patters were found: low-use (67.2%), administration-oriented (20.3%), communication-oriented (9.4%), and assessment-oriented (3.1%), which provide insights into how university instructors engage with LMS tools, highlighting the different LMS tool-adoption strategies used in higher education. Intriguing links were found between actual usage patterns and pedagogical beliefs, indicating that administration-oriented and low-usage patterns were related with weaker beliefs in ICT use, with the former having the highest constructivist belief scores and the latter recording the lowest. Instructors with communication use patterns had the lowest traditionalist beliefs, while those focusing on assessment had the highest. This research underscores the significance of aligning pedagogical approaches with technology integration within the context of higher education instruction, offering vital insights for universities committed to ongoing improvement in teaching practices and the effective utilisation of LMS technologies.

Study on the co-phasing simulation and experimental of segmented mirror based on broadband light

At present, the co-phasing detection algorithms for segmented mirrors struggle to balance the measurement range and accuracy. This paper proposes a coarse co-phasing measurement method using the incoherent properties of a broadband (400–800 nm) light source combined with the incoherence of two semicircular diffraction patterns of visible light as a template to detect the piston error, and a narrowband algorithm for fine co-phasing measurement. The diversity factors between template patterns and actual diffraction patterns can be calculated by the cross-correlation algorithm. This proposed method addresses long measurement time caused by low target flow rate and is characterized by wide measurement range, high precision and high energy utilization. The method is theoretically researched and simulated and an experimental system which was constructed to verify the effectiveness of this method achieves 15 nm detection accuracy, and the measurement range using the proposed method can match the measurement range of the actuator.

Examining the interfacial behavior of non-Newtonian gas-liquid two-phase flow in horizontal square microchannels

This study investigates the flow dynamics of a non-Newtonian two-phase flow within a horizontal square microchannel. The experimental apparatus employed an acrylic channel with a side length of 8 × 10−4 m. Nitrogen served as the test gas, and the test liquids consisted of water and CMC (Carboxymethylcellulose) aqueous solutions at concentrations of 0.2 and 0.4 %wt. The superficial velocity of working gas and liquids spanned ranges of 0.26–20 m/s and 0.05–1.0 m/s, respectively. A differential pressure transducer was used to measure pressure gradients, while a high-speed video camera captured the flow behavior for analysis with a custom image processing technique. Nonlinear regression statistical analysis was applied to establish the criteria for flow pattern transition. Furthermore, signal processing techniques such as PSD (Power Spectral Density), DWT (Discrete Wavelet Transform), ANN (Artificial Neural Network), and Kolmogorov entropy were employed to analyze the flow behavior based on the pressure gradient signals from the differential pressure transducers. Our findings reveal the occurrence of bubbly, slug, slug-annular, and churn flow patterns. The nonlinear regression statistical analysis offered ambiguous results for determining flow pattern transitions. However, an empirical coefficient was obtained for the nondimensional liquid height. Moreover, the empirical nondimensional liquid height aligned well with the experimental values. The PSD and DWT analysis corroborated each other in clearly characterizing the flow pattern based on pressure gradient fluctuation and wavelet energy. The Kolmogorov entropy effectively captured the chaotic flow pattern. Furthermore, the ANN analysis demonstrated a solid agreement between the predicted and actual flow patterns.

Current status of treatment and disease burden of a cohort of hemophilia B in China.

Hemophilia B is a rare X-chromosome linked hereditary bleeding disorder. Patients require lifelong treatment and it is costly, but there is a lack of research in China on the treatment and burden for this group. Our aim was to review the actual treatment pattern of hemophilia B patients in China, and describe the financial burden and other disease burden from the patient's perspective. Using data collected by the Beijing Hemophilia Home Care Center, descriptive statistics were made on the sociodemographic characteristics and treatment of patients. The annual drug costs were calculated according to the actual factor dosage and price. During the study period, 29.9% of the patients only received on-demand treatment, while the rest of the patients received varying numbers of prophylaxis treatment. The total cost of clotting factors for 341 patients in one year was 16.0 million CNY ($2.5 million), with 46990.8 CNY ($7283.7) per patient. The drug cost of prophylaxis was significantly higher than that of on-demand treatment. The amount of prothrombin complex concentrates used by patients was the largest, more than 5 times of recombinant coagulation factor IX. Based on the average annual wage and average working time of Chinese employees in 2021, the average annual wage loss of HB patients reached 31544.2 CNY ($4889.4). The results of the questionnaire showed that 77.1% and 65.3% of patients had chronic pain and acute pain of different frequencies. The level of prophylaxis for Chinese patients is low; safer and more effective recombinant drugs are not widely available. Patients also face a high burden of drug costs, as well as indirect costs that cannot be underestimated. Therefore, continued efforts are needed to improve the quality of life of patients by reducing their financial burden and promote standardized treatment.

Platelet Modeling in DHF Patients Using Local Polynomial Semiparametric Regression on Longitudinal Data

Regression analysis is one of the statistical methods used to model the relationship between response variables and predictor variables. Semiparametric regression is a combination of parametric and nonparametric regression. The estimator used in estimating the semiparametric regression model in this research is the Local Polynomial. Longitudinal data can be found in the health sector, including dengue hemorrhagic fever (DHF) data. The laboratory criteria for indication of DHF is thrombocytopenia. This research aims to obtain platelets model for DHF patients that can be used for forecasting so that it is hoped that it can provide information to the medical team in treating DHF patients. The estimated model used is Local Polynomial semiparametric regression on longitudinal data. The response variables in this research were platelets of DHF patients, which were influenced by hemoglobin as parametric predictor variable and examination time while hospitalized as nonparametric predictor variable. In the local polynomial regression model, it is necessary to select the optimal bandwidth and polynomial order method, GCV. The optimum bandwidth selection based on the GCV method obtained is 1.5 and polynomial order of 2, then applied to DHF patient platelet data, producing an estimated local polynomial semiparametric regression model that follows the actual data pattern. Modeling the platelets of DHF patients obtained using a local polynomial estimator resulted in an R2 value of 84.25% and MAPE of 4.5%, indicating highly accurate forecasting, so it can be concluded that the resulting model is better at predicting.

Complex Network-Based Resilience Capability Assessment for a Combat System of Systems

With the increasing complexity and frequency of interactions among a large number of heterogeneous nodes within a combat system of systems (SoS), evaluating the capability of the SoS to withstand external attacks and interferences has become an increasingly challenging and urgent issue. However, the complexity of a combat SoS often brings about difficulties in quantitative analysis. This paper proposes a method to assess the resilience of a combat SoS. Firstly, a network model of a combat SoS is constructed, taking into account multi-functional composite nodes. Secondly, the combat capability model of the combat SoS is built based on the capabilities of the kill chains and kill networks. Lastly, an approach is proposed to calculate the combat capability of the system based on the network’s two-terminal connectivity. Moreover, based on the SoS’s combat capability, the resilience is analyzed from the dimensions of anti-destruction, survival, and recovery. The simulation experiments show that, compared to other methods, the method in this paper for calculating the combat capability of the combat SoS does not depend on the number of kill chains and aligns with the combat processes and actual patterns. Additionally, the resilience measurement method can effectively analyze its capability to cope with external interferences.

Fuzzy membership-function-dependent design of aperiodic sample-data control scheme for nonlinear PMSG-based WECS with quantization measurements via refined looped Lyapunov functional

This manuscript investigates the fuzzy memory sampled-data control (MSDC) scheme for the nonlinear permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS) with quantization measurements. First, due to the complex nonlinearity, a Takagi-Sugeno (T-S) fuzzy modeling approach is successfully applied to the dynamics of nonlinear PMSG-based WECS. Second, by using the information of both quantized aperiodic sampling pattern and signal transmission delay, an H∞-based fuzzy quantized controller is put forward to ensure the stable performance as well as disturbance suppression index of the considered PMSG model by utilizing the refined looped Lyapunov functional (RLLF) approach. This RLLF perfectly utilizes more realistic information about the time derivative of the fuzzy membership function and actual sampling pattern. Then, two new integral inequalities are introduced to approximate the quadratic integral terms arising from the derivative of RLLF. Next, we establish some less conservative stabilization results in terms of linear matrix inequalities (LMIs) using the constructed RLLF, along with the proposed integral inequalities and fuzzy membership function-dependent (MFD) switching ideas. Finally, the simulation studies of PMGS-based WECS are validated numerically, and then a comparative example is provided to emphasize the superiority and relevance of the suggested approach.

Deterministic ground motion modeling with target earthquakes and site effects in eastern Azerbaijan

In the context of assessing seismic hazard, accurately predicting ground motion stands out as a crucial task. Achieving precision in ground motion modeling proves valuable in revealing the actual pattern, even when faced with insufficient data on soil structure, provided there is precise information about the seismic source. This study introduces a methodology for calculating local- and near-field ground motion, expressed in peak ground acceleration (PGA) and intensity values. The deterministic approach is employed, incorporating source characteristics and one-dimensional (1D) site effects. For the chosen test area, the Ismayilli-Shamakhi region on the southeastern slope of the Greater Caucasus in Azerbaijan, two seismic scenarios are investigated: the 1902 Shamakhi earthquake (magnitude M = 6.8) and the November 25, 2000 Baku-Caspian earthquake (two shocks with moment magnitude Mw = 6.08 and 6.18). Different soil types are considered to validate the proposed methodological procedures. The analysis involves the computation of peak ground acceleration motion for two scenario earthquakes: a local-field event with M = 6.8 and a near-field event with Mw = 6.5, representing the average magnitude of the 2000 Baku-Caspian earthquake. The computed peak ground acceleration values are then used to derive intensities. Notably, the 1902 Shamakhi earthquake and the 2000 Baku-Caspian earthquake exhibit similar trends on surface PGA values. The local-field scenario estimates PGA values ranging from 77 to 328 gal, corresponding to MSK-64 scale intensity levels of VII-IX. The near-field scenario, with PGA values ranging from 28 to 62 gal, aligns with MSK-64 intensity levels of VI–VII. In the final assessment, the amplification factor in the study area varies between 0.55 and 0.83. The seismic hazard level is identified as high in the southern and southeastern regions, particularly in areas with soft shallow and medium-depth soils, indicating a high potential for ground motion amplification.

Design of continuous transition line pattern between layers of composite pressure vessel

To realize efficient and stable continuous transition between different winding process layers of composite pressure vessels. This article uses the non-geodesic winding equation to propose a transition layer design method for composite pressure vessel shells with circular cross-section core molds and ellipsoidal heads. Firstly, the fourth-order Runge–Kutta method is used to solve the non-geodesic stabilized winding pattern and then analyze different regions’ transition ability. Established a calculation model to determine the corresponding transition winding trajectory according to the known core mold shape and fiber position and carried out computer image simulation of different modes of transition layer patterns, and finally carried out experimental verification of 35 MPa composite pressure vessel based on the simulation. The results show that different regions of the core mold have different abilities to change different starting winding angles, and the design of the transition process layer based on this law can save the area needed for transition. This method realizes the smooth transition of different process layers; the fiber of the transition layer does not slip in the actual winding process, and the actual pattern of the winding is consistent with the simulation results, which saves 20.8% of the winding time, and effectively improves the automation of the composite pressure vessel winding process.

Locals’ Claims of Rights and Access to Forest Resources in Three Forest Management Regimes in Gunungkidul Regency, Yogyakarta

One of state forest areas managed by three management regimes is Bunder forest area, Gunungkidul, Yogyakarta. Three management regimes are the production forest of KPH Yogyakarta, the conservation forest of Tahura, and the educational forest of KHDTK Wanagama I. The differences of management regimes are thought to affect the actual interaction pattern of villagers with the forest. This research aims to compare the actual rights and access of villagers to Bunder forest area in three management regimes in the hope of finding more effective forest management patterns. This research used a qualitative approach through the case study method of the interaction villagers of Bunder, Banaran, Ngleri, and Gading villages with the surrounding forests. The results show that forest management regimes affects the way villagers can access the forests. The aggregate value of the actual rights received by the villagers to the production forest of KPH Yogyakarta is higher than the educational forest of KHDTK Wanagama I. The lowest is management regimes in conservation forest of Tahura. Based on the access mechanisms that empower villagers, the educational forest regime of KHDTK Wanagama I is higher than the production forest regime of KPH Yogyakarta and the conservation forest regime of Tahura. This research recommends defining rights and access to increase certainty about the benefits of forest resources.