Search Results (91)

Extraneous details in visual representations can prompt children to use well-rehearsed, yet inappropriate, strategies that can hinder mathematics learning. Prior domain knowledge can reduce the negative effects of extraneous details in instructional materials. The present study tested whether prior knowledge of fractions and instruction on measurement division (MD) could overcome children’s inappropriate counting strategies when solving fraction division problems with images of LEGO^® bricks. Fourth and fifth graders (N = 39) were randomly assigned to two instructional conditions: one that demonstrated how to solve fraction division problems using LEGO bricks that included explanations on MD concepts, and the other with the same demonstrations but without explanations. All participants then completed a task that measured whether the studs on the bricks prompted inappropriate counting when solving the problems. Almost one-third of the sample counted the studs to some degree. Greater prior knowledge of fractions concepts and knowledge of how to represent fractions with LEGO bricks were related to fewer inappropriate counting strategies, but contrary to expectations, fraction magnitude was not related. The two conditions did not differ on participants’ counting strategies. Extraneous details on LEGO bricks are related to the application of well-practiced counting strategies for children with lower domain knowledge. Full article

Against the backdrop of frequent public health emergencies caused by infectious diseases, it is urgent to evaluate the importance of urban epidemic prevention by integrating population mobility networks. In this study, a comprehensive evaluation index system is constructed based on a population mobility network, and the improved entropy weight method and analytic hierarchy process are used to obtain the comprehensive weights. The weight imbalance problem of traditional methods is solved by introducing community structure weighting and subjective weight. We establish a Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS)-based evaluation model named city importance evaluation based on the division of communities and TOPSIS (CICT) for the importance of urban epidemic prevention and simulate the model using data from 297 cities in China. It can rank indicators that affect the importance of cities in infectious disease prevention and control and identify key cities for infectious disease prevention and control. The influence of various indicators on the evaluation objectives vary during different investigation periods, but the entropy weights of confirmed cases, hospital beds, and practicing (assistant) physicians remain at a high level. Cities with a high number of confirmed cases consistently rank at the top in the comprehensive evaluation, but this model can also identify potential key cities with fewer confirmed cases. These cities require key management during the outbreak of infectious diseases. The evaluation model can scientifically assess the epidemic prevention significance of cities, improve the efficiency of public health emergency management, and provide quantitative support for formulating urban epidemic control strategies, promoting resource optimization allocation, and implementing targeted measures. Full article

The traditional finite element method deals with the temperature field around the cooling tube due to the computational efficiency problems caused by grid division and the uncertainty of the convective heat transfer coefficient, resulting in inaccurate calculation results around the cooling tube. We conducted experiments to study the thermal stress and temperature gradient caused by various factors such as different materials of cooling pipes, pipe diameters, cooling water temperatures, and flow rates. The results showed that aluminum alloy pipes had the highest cooling efficiency but also produced a large temperature gradient. Pipe diameter had the most significant impact on cooling efficiency. Additionally, it is recommended that the cooling water flow velocity is not less than 0.6 m/s to achieve the best efficiency for the cooling pipe of any pipe diameter. The influence range of the cooling pipe on concrete could vary with pipe material, flow rate, and ambient factors. Our experimental results were compared with other heat transfer formulas (the Dittus–Boelter formula and the Yang Joo-Kyoung formula). According to the measured results, the formula is modified). The modified formula can estimate the heat transfer coefficient more accurately according to the flow rate and pipeline characteristics. Finally, the applicability of the formula is further verified by comparing the concrete on the bottom plate of a dam. The proposed heat transfer prediction model can estimate the heat transfer coefficient according to the flow rate and pipeline characteristics, The accuracy of the convection coefficient under different working conditions is improved by 10–25%. It is convenient to predict concrete temperature in practical engineering. Full article

In this paper, the problem of source localization using only frequency difference of arrival (FDOA) measurements is considered. A new FDOA-only localization technique is developed to determine the position of a narrow-band source. In this scenario, time difference of arrival (TDOA) measurements are not normally useful because they may have large errors due to the received signal having a small bandwidth. Conventional localization algorithms such as the two-stage weighted least squares (TSWLS) method, which jointly exploits TDOA and FDOA measurements for positioning, are thus no longer applicable since they will suffer from the thresholding effect and yield meaningless localization results. FDOA-only localization is non-trivial, mainly due to the high nonlinearity inherent in FDOA equations. Even with two FDOA measurements being available, FDOA-only localization still requires finding the roots of a high-order polynomial. For practical scenarios with more sensors, a divide-and-conquer (DAC) approach may be applied, but the positioning solution is suboptimal due to ignoring the correlation between FDOA measurements. To address these challenges, in this work, we propose a Bayesian approach for FDOA-only source positioning. The developed method, referred to as the Gaussian division method (GDM), first converts one FDOA measurement into a Gaussian mixture model (GMM) that specifies the prior distribution of the source position. Next, the GDM assumes uncorrelated FDOA measurements and fuses the remaining FDOAs sequentially by invoking nonlinear filtering techniques to obtain an initial positioning result. The GDM refines the solution by taking into account and compensating for the information loss caused by ignoring that the FDOAs are in fact correlated. Extensive simulations demonstrate that the proposed algorithm provides improved performance over existing methods and that it can attain the Cramér–Rao lower bound (CRLB) accuracy under moderate noise levels. Full article

Objectives: Cleft lip and palate is a multifactorial disease that causes various problems, such as maxillary and facial morphological abnormalities, oral dysfunction, and postoperative scarring due to lip and palate formation after birth. This condition can easily cause obstruction and may require surgical orthodontic treatment in the future. Methods: In this study, we performed multi-segment Le Fort type 1 osteotomy on a patient with a cleft lip and palate who presented with a crossbite, horizontal inclination of the occlusal plane due to dental arch stenosis on the left side of the maxilla, and deviation of the mandible. Results: In this case, close occlusion was achieved by improving the patient’s facial appearance and occlusal relationship by combining sagittal division of the mandibular ramus, and the stability of the occlusion was measured without relapse 1 year after the surgery. Conclusions: This case is considered of great medical significance, as there have been few reports of cases showing a stable course. Full article

Research background: Modern enterprises operate in conditions of very dynamic changes, where the increasing complexity of the environment affects their ability to achieve their assumed organizational goals. These goals are extremely important in the context of the current functioning of the enterprise, as well as in moving towards sustainable economic development. Functioning in this era of unpredictability and turbulence is a significant challenge not only in the context of the current activities of business entities, but especially for their development. An important element in the aspect of development is the ability to recognize and identify development factors that may directly and/or indirectly affect the results of the activities or projects that are undertaken. In this context, undertaking research on development factors during the COVID-19 pandemic (referred to in the literature as a time of crisis in global economies) seems to be fully justified, and the adoption of comparative periods, i.e., before and during the pandemic, has cognitive value. This value also refers to the possibility of recognizing the conditions needed for the strategic management of the enterprise in the context of a transformation towards sustainable development goals. The authors of the study point to the research gap related to the lack of in-depth and multifaceted research on the factors in the development of family businesses in the SME sector. Purpose of the article: The purpose of the paper is to analyze and assess the development factors of family businesses in the SME sector in Poland during two periods, namely 2018–2019 (two years before the COVID-19 pandemic) and 2020–2021 (two years in the COVID-19 pandemic period). Methods: To achieve this aim, a comparative analysis of the performance of family businesses in the SME sector was carried out based on the author’s own data. These data were obtained through surveys (CAPI method) carried out among micro-, small-, and medium-sized family enterprises in the Masovian Voivodeship in Poland, taking into account the two research periods indicated above. Statistical methods were also used in the data analysis. The average values of the assessments of the importance of groups of development factors for the development of the enterprise were analyzed using an analysis of variance with repeated measures in a mixed model, because the average assessments were determined on an interval scale. Tests of between-subject effects made it possible to compare enterprises of different sizes, and tests of within-subject effects and tests of interactive effects made it possible to compare two time perspectives. Findings and value added: The findings of this study contribute to the literature on family businesses in the SME sector and the factors in their development. The implementation of this publication contributed to filling the revealed research gap, as well as solving the formulated research problem, along with verifying the research hypotheses formulated in the work. Based on the research conducted, the main determinants of development in family enterprises in the SME sector were identified, taking into account both individual factors and groups of factors. The conducted research allowed us to show the similarities and differences both between the individual size classes of these enterprises and between the research periods. The added value of the empirical research conducted refers to the identification of factors for the development of family enterprises in the SME sector, their comparison in terms of the size classes of these entities, and the comparison of their importance in economically and socially diverse research periods, i.e., before and during the COVID-19 pandemic. It should be emphasized that while the literature on the subject presents research in this area in relation to family enterprises in general, research on these family units belonging to the SME sector, along with their division into size classes, is much less common. The implementation of the research is, therefore, an important contribution to the development of the broadly understood science of the development of family enterprises, showing the importance of groups of factors in their development in light of the changing conditions of the modern economy in the individual size classes of these entities. Full article

The widespread emergence of antimicrobial resistance (AMR) is a serious threat to global public health and among Gram-positive cocci, Streptococcus pneumoniae constitutes a priority in the list of AMR-threatening pathogens. To counteract this fundamental problem, the bacterial cell division cycle and the crucial proteins involved in this process emerged as novel attractive targets. FtsZ is an essential cell division protein, and FtsZ inhibitors, especially the benzamide derivatives, have been exploited in the last decade. In this work, we identified, for the first time, some benzodioxane–benzamide inhibitors capable of targeting FtsZ in Streptococcus pneumoniae, in addition to their previously demonstrated activity against other bacteria. These promising benzamides, with minimal inhibitory concentrations (MICs) ranging from 25 to 80 µg/mL, demonstrated bactericidal activity against S. pneumoniae. This was evidenced by their ability to dramatically affect growth and viability, further supported by the morphological changes observed through microscopy. Moreover, the compounds were characterized in vitro, combining turbidity measurements and confocal imaging, and significant alteration of a GTP-induced FtsZ assembly was found, in line with our previous data from other microorganisms. Full article

This paper investigates the effect of nonlinear changes in insulation resistance on the accuracy of a 2 × 550 kV DC voltage scaling standard device. As the voltage and electric field strength increase, the insulating material exhibits nonlinear conductivity characteristics, leading to a decrease in the insulation resistance value, which in turn affects the potential distribution and the partial voltage ratio and thus reduces the measurement accuracy of the standard device. In order to study this problem in depth, this paper builds a nonlinear resistance measurement platform for insulating materials, and it fits and analyzes the experimental data using an NCIR neural network (Neural Network for Nonlinear Characteristics of Insulation Resistance). In addition, in this paper, the finite element model of the standard device was established by ANSYS simulation, and the equivalent resistance network model was established by applying MATLAB in order to calculate the variation in the voltage dividing ratio under different voltages. The results of the study showed that the nonlinear variation in insulation resistance significantly affects the voltage division ratio of the standard device, especially at high voltage conditions. Addressing the issue, this paper proposes to optimize the electric field distribution by optimizing the structure of the grading ring and adding a shielding resistor layer to reduce the influence of nonlinear effects. Simulation results show that the addition of a second layer to the shielding resistor can effectively improve the measurement accuracy of the device, and the reduction in voltage division ratio error is significant. Compared with the case of a shielding resistor with only one layer, the voltage divider ratio was reduced from 109,998.203 to 109,998.994, and the relative error was reduced 44%, changing from 1.634 × 10⁻⁵ to 9.15 × 10⁻⁶. The above study provides an optimized solution for achieving high-precision DC voltage measurement. Full article

The light pollution of the night sky is already a widespread phenomenon, the spatial extent and magnitude of which are increasingly represented in the form of thematic maps and cartographic visualization. Its leading cause needs to be correctly designed or adequately installed outdoor lighting. The problem of excessive artificial light emission at night, together with its adverse effects, has already reached such a level that it has become necessary to develop usable and comprehensible methods for the cartographic representation of the distribution of the phenomenon. In practice, there are several ways to measure the intensity of this pollution. However, there are no uniform legal standards for the use of outdoor lighting and no guidance and guidelines for the visualization of measurement data. Such visualization should provide a consistent, reliable, and, above all, readable picture of the phenomenon adapted to the needs of different audiences. Examples of the representation of the results of measurements of light pollution of the night sky can be found in the literature or a few atlases. Still, they often differ in color scales, value divisions, and measurement units used. This paper reviews the scales and units available in the literature to describe this phenomenon. The differences between the approaches of specialists from different branches and their influence on the final interpretation of the data are also presented. In addition, an authorial solution is proposed to standardize methods of cartographic visualization of the spatial distribution of light smog measurement results. The article attempts to draw attention to the importance of the graphical description of light smog, which will shortly be the subject of increasing research and work on the unification of cartographic communication. Full article

Administrative geography is concerned with the hierarchy of areas related to national and local government in a country. They form an important dataset in the country’s open data provision and act as the geo-referencing backdrop for many types of geospatial data. Proprietary ontologies are built to model and represent these data with little focus on spatial semantics. Studying the quality of these ontologies and developing methods for their evaluation are needed. This paper addresses these problems by studying the spatial semantics of administrative geography data and proposes a uniform set of qualitative semantics that encapsulates the inherent spatial structure of the administrative divisions and allows for the application of spatial reasoning. Topological and proximity semantics are defined and combined into a single measure of spatial completeness and used for defining a set of competency questions to be used in the evaluation process. The significance of the novel measure of completeness and competency questions is demonstrated on four prominent real world administrative geography ontologies. It is shown how these can provide an objective measure of quality of the geospatial ontologies and gaps in their definition. The proposed approach to defining spatial completeness complements the established methods in the literature, that primarily focus on the syntactical and structural dimensions of the ontologies, and offers a novel approach to ontology evaluation in the geospatial domain. Full article

(1) Background: In the context of the Sustainable Development Goals (SDGs) and based on the historical evolution of cultivated land protection policy, we used the Smith model to address the problem of policy implementation bias and provide recommendations on how to ensure that cultivated land protection policy does not deviate in the implementation process. (2) Methods: The historical evolution process of China’s cultivated land protection policy was elucidated using literature analysis and the inductive deduction method; moreover, the issues regarding local evolution were investigated. In addition, utilizing the Smith model, which has an important role in policy implementation, the restoration direction of cultivated land protection in China was summarized. (3) Project: China’s cultivated land protection policy has demonstrated success in two stages of its historical development—from the basic stage of pursuing equal quantity and quality to the new stage of the trinity of “quantity–quality–ecology” of cultivated land. However, the trend of cultivated land protection policy development based on the regional division of labor in China still has some problems, i.e., the total quantity of cultivated land is insufficient, the quality is low, and the implementation of the trinity is unclear. These regional divisions depend on solving the balance of China’s grain security, and using the Smith model to solve the problem of policy implementation has become an important measure to resolve the issue of grain security and achieve the goal of cultivated land protection. (4) Conclusions: The Smith model is suitable for the implementation of China’s cultivated land protection policy. By utilizing the Smith model, the policy target group was found to be conducive to contributing to the maturity of and improvement in China’s cultivated land protection policy. Full article

Under the goal of global poverty eradication, it has become a forward-looking research aim to establish relative poverty criteria and identify people experiencing relative poverty in countries with different demographic characteristics. This paper introduces a new method to measure the relative poverty standard, which is to use the fuzzy decision tree algorithm to objectively estimate the relative poverty standard. The advantage of this algorithm lies in (1) it not only maintaining the regression idea of measuring absolute poverty, but also emphasizing the nonlinearity when the demand is increasing, which can reflect the change in human needs. (2) It overcomes the division of the traditional method which clearly distinguishes between those experiencing poverty and those who are not by means of a subjective threshold, and it also avoids the subjectivity of the selection of multidimensional indicators. (3) It overcomes the problems of data skewness and extreme value issues that traditional methods have, and can exhibit multi-dimensional characteristics. (4) Most importantly, this method can overcome the gap problem caused by the complex population structure in developing countries with huge populations, and is more adaptable under big data conditions than traditional methods. Taking China as an example, using data from the China Household Finance Survey for validation, the validation results show that the relative poverty standard in China in 2019 can be approximately delineated as 5288.5 RMB; this result is higher than the absolute poverty standard line delineated in China in that year, lower than the relative poverty standard line measured using the proportion method, and it can satisfy the average per capita food, tobacco, and alcohol consumption expenditure of Chinese residents in that year. Thus, compared with other methods, the fuzzy decision tree algorithm can better match the identification of relative poverty in developing countries with large populations. Full article

This paper advocates for spatial simultaneous functioning (SSF) over time division multiple access (TDMA) in joint communication and sensing (JCAS) scenarios for improved resource utilization and reduced interference. SSF enables the concurrent operation of communication and sensing systems, enhancing flexibility and efficiency, especially in dynamic environments. The study introduces joint design communication and sensing scenarios for single input single output (SISO) and multiple input multiple output (MIMO) JCAS receivers. An MIMO-JCAS base station (BS) is proposed to process downlink communication signals and echo signals from targets simultaneously using interference cancellation techniques. We evaluate the communication performance and sensing estimation across both Rayleigh and measured realistic channels. Additionally, a deep neural network (DNN)-based approach for channel estimation and signal detection in JCAS systems is presented. The DNN outperforms the traditional methods in the bit error rate (BER) versus signal-to-noise ratio (SNR) curves, leveraging its ability to learn complex patterns autonomously. The DNN’s training process fine-tunes the performance based on specific problem characteristics, capturing the nuanced relationships within data and adapting to varying SNR conditions for consistently superior performance compared to the traditional approaches. Full article

In the modern technological era of sophisticated applications and high-quality communications, a platform of clever strategy and quickly updated systems is needed. It should be capable of withstanding the fastest emerging problems like signal attenuation and hostile actions intended to harm the whole network. The main contributions of this work are the production of an OFDM system (with low cost) that can sustain high-speed communications and be easily adjusted with new integrated code while exhibiting the feasibility of implementing a transmitter–receiver system in the same DSP and demonstrating the holistic approach with the qualitative integration of such an architecture in a warfare scenario. Specifically, in this research, the point of view is toward three facts. The first is to show a method of quick self-checking the operational status of a digital signal processor (DSP) platform and then the pedagogical issues of how to fast check and implement an updated code inside DSPs through simple schematics. The second point is to present the prototype system that can easily be programmed using a graphical user interface (GUI) and can change its properties (such as the transmitted modulated sinusoids—orthogonal frequency division multiplexing subcarriers). Alongside the presentation, the measurements are presented and discussed. These were acquired with the use of an oscilloscope and spectrum analyzer. The third point is to qualitatively show the application of such a system inside a modern warfare environment and to recommend various potential system responses according to the development of such a platform of reconfigurable implemented OFDM systems. The implementation was performed for two types of systems: (1) transmitter and (2) transmitter–receiver system. Notably, the system acts quickly with a delay of about 1 msec in the case of transmitting and receiving in the same DSP, suggesting excellent future results under real conditions. Full article

An airborne bistatic radar working in downward-looking mode confronts two major challenges for low-altitude target detection. One is range cell migration (RCM) and Doppler migration (DM) resulting from the relative motion of the radar and target. The other is the non-stationarity characteristic of clutter due to the radar configuration. To solve these problems, this paper proposes a joint implementation method based on sub-aperture processing to achieve clutter suppression and coherent maneuvering target detection. Specifically, clutter Doppler compensation and sliding window processing are carried out to realize sub-aperture space–time processing, removing the clutter non-stationarity resulting from the bistatic geometric configuration. Thus, the output matrix of clutter suppression in the sub-aperture could be obtained. Then, the elements with the same phase of this matrix are superimposed and rearranged to achieve the reconstructed 2-D range-pluse echo matrix. Next, the aperture division with respect to slow time is conducted and the RCM correction based on modified location rotation transform (MLRT) and coherent integration (CI) are realized within each sub-aperture. Finally, the matched filtering process (MFP) is applied to compensate for the RCM/DM among different sub-apertures to coherently integrate the maneuvering target energy of all sub-apertures. The simulation and measured data processing results prove the validity of the proposed method. Full article