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Analyzing the formation mechanisms of industrial parks and quantitatively evaluating the related hazard levels are important for understanding the development and planning of industrial parks, but there is currently a lack of relevant research. In this study, Beijing was taken as a case study. The analysis results showed that (1) the overall spatial distribution of industrial parks in Beijing followed a clustering pattern, with nested spatial distribution pattern, where larger structures contributed 53.96% of the variance; (2) for the overall spatial distribution of industrial parks, kernel density of enterprises was the main influencing factor, which there were synergistic enhancement effects with almost all other influencing factors, especially urban construction, the number of financial institutions, the population density, this can share transportation and other resources, achieving coordinated development. According to these main factors, the prediction model of the future spatial distribution pattern of industrial parks in Beijing was established; (3) for site selection of each industrial park, twenty-two industrial parks near industrial enterprises in Beijing were more affected by industrial enterprise clustering, and the remaining 65 industrial parks were strongly affected by terrain, (4) The industrial parks in the central and southern parts of Beijing presented a relatively high hazard level to the surrounding sensitive receptors. These results provide theoretical support for the development and layout of industrial parks. [ABSTRACT FROM AUTHOR]

In order to improve the crashworthiness of the novel circular-vein branched nested tube (CVBNT) proposed in recent research work, the crashworthiness design is optimised in this paper. Based on numerical simulation technology, the finite element model under transverse quasi-static compression of CVBNT is first established and effectively verified. Then, the energy absorption characteristics of CVBNT and different nested tubes were compared and analysed to reveal the excellent energy absorption performance of CVBNT. Finally, the structural design and the cross-sectional thickness optimisation of CVBNT are carried out. The results show that CVBNT has better energy absorption capacity than other nested tubes. The parameters N and γ have an important influence on the crashworthiness of CVBNT, and when N = 6, γ = 0.5 is the best choice in favour of its crashworthiness. At the same time, the optimisation of cross-section thickness effectively improves the crashworthiness of CVBNT. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The performance wagon is the key stage mechanical equipment to realize rich performances and diversified changes on the stage, which can carry actors or scenery. In order to solve the problem of low intelligence and poor flexibility of the traditional performance wagon, which can not walk or rotate arbitrarily according to the designated path in accordance with the program arrangement, a new type of performance omnidirectional vehicle form based on nested structure is proposed. The structure is composed of an inner and outer nested double ring frame, and the relative motion and combined motion of the nested inner and outer double rings are realized by meshing the large gear ring of the outer ring with the tension adjustment of the inner ring and driving the pinion components. The omnidirectional vehicle for the proposed structure is designed. Based on the kinematics principle, the kinematics analysis system is carried out for the omnidirectional vehicle, and the kinematics model is established. On this basis, the track estimation is carried out and the three-dimensional model is established to analyze the dynamics of the omnidirectional vehicle. An omnidirectional vehicle platform based on the nested structure is built for system experiment and tests. The results show that the omnidirectional vehicle based on the nested structure has good mechanical performance, and can realize trajectory motion with good robustness and high precision.

Because of its wide distribution, high yield potential, and short cycle, the potato has become essential for global food security. However, the complexity of tetrasomic inheritance, the high level of heterozygosity of the parents, the low multiplication rate of tubers, and the genotype-by-environment interactions impose severe challenges on tetraploid potato--breeding programs. The initial stages of selection take place in experiments with low selection accuracy for many of the quantitative traits of interest, for example, tuber yield. The goal of this study was to investigate the contribution of incorporating a family effect in the estimation of the total genotypic effect and selection of clones in the initial stage of a potato-breeding program. The evaluation included single trials (STs) and multi-environment trials (METs). A total of 1,280 clones from 67 full-sib families from the potato-breeding program at Universidade Federal de Lavras were evaluated for the traits total tuber yield and specific gravity. These clones were distributed in six evaluated trials that varied according to the heat stress level: without heat stress, moderate heat stress, and high heat stress. To verify the importance of the family effect, models with and without the family effect were compared for the analysis of ST and MET data for both traits. The models that included the family effect were better adjusted in the ST and MET data analyses for both traits, except when the family effect was not significant. Furthermore, the inclusion of the family effect increased the selective efficiency of clones in both ST and MET analyses via an increase in the accuracy of the total genotypic value. These same models also allowed the prediction of clone effects more realistically, as the variance components associated with family and clone effects within a family were not confounded. Thus, clonal selection based on the total genotypic value, combining the effects of family and clones within a family, proved to be a good alternative for potato-breeding programs that can accommodate the logistic and data tracking required in the breeding program. [ABSTRACT FROM AUTHOR]

Because of its wide distribution, high yield potential, and short cycle, the potato has become essential for global food security. However, the complexity of tetrasomic inheritance, the high level of heterozygosity of the parents, the low multiplication rate of tubers, and the genotype-by-environment interactions impose severe challenges on tetraploid potato–breeding programs. The initial stages of selection take place in experiments with low selection accuracy for many of the quantitative traits of interest, for example, tuber yield. The goal of this study was to investigate the contribution of incorporating a family effect in the estimation of the total genotypic effect and selection of clones in the initial stage of a potato-breeding program. The evaluation included single trials (STs) and multi-environment trials (METs). A total of 1,280 clones from 67 full-sib families from the potato-breeding program at Universidade Federal de Lavras were evaluated for the traits total tuber yield and specific gravity. These clones were distributed in six evaluated trials that varied according to the heat stress level: without heat stress, moderate heat stress, and high heat stress. To verify the importance of the family effect, models with and without the family effect were compared for the analysis of ST and MET data for both traits. The models that included the family effect were better adjusted in the ST and MET data analyses for both traits, except when the family effect was not significant. Furthermore, the inclusion of the family effect increased the selective efficiency of clones in both ST and MET analyses via an increase in the accuracy of the total genotypic value. These same models also allowed the prediction of clone effects more realistically, as the variance components associated with family and clone effects within a family were not confounded. Thus, clonal selection based on the total genotypic value, combining the effects of family and clones within a family, proved to be a good alternative for potato-breeding programs that can accommodate the logistic and data tracking required in the breeding program.

Abstract Background Over time, demographic and health survey (DHS) data remain valuable to examine variables relating to nationally representative population outcomes for low- and middle-income countries. In Tanzania, there are very limited DHS-based studies on the uptake of Modern Contraceptive Use (MCU). Present studies have focused on measurements at the level of individuals, yet research has shown that MCU variations exists at other levels within populations. In this study, we use a variance component modelling approach to explore variation in MCU at primary sampling unit (PSU) and regional levels while considering survey sample weights. Methods Using DHS data from 2016–2017 in Tanzania, we study different variance structures and the respective variation on MCU in a sample of 5263 Women of Reproductive Age (WRA) defined as between the ages of 15–49 years. First, a single variance component was used, followed by its extension to a random coefficient model and we tracked changes in the models. Results There was an influence of random variations on MCU on the levels of populations much explained by PSU-level clustering than region. On the fixed part, age of a woman, husband education level, desire to have children, and exposure to media and wealth tertiles were important determinants for MCU. Compared to WRA in 15–19 years, the odds of MCU among middle aged women (20–29 and 30–39 years) were 1.94 (95%CI:1.244–3.024) and 2.28 (95%CI:1.372–3.803). Also, increases in media exposure and middle and rich wealth tertiles women led to higher odds for MCU. We also found the presence of random effects influence of wealth tertiles levels on MCU. Conclusion This study highlighted the utility of accounting for variance structures in addressing determinants of MCU while using DHS national level data. Apart from MCU, the DHS data have been widely applied to examine other variables pertaining to public health issues. This approach could be considered a better modelling technique for the DHS studies compared to traditional survey approaches, and to guide hierarchical population-based interventions to increase MCU.

In this article, we explore the extraction of recursive nested structure in the processing of binary sequences. Our aim was to determine whether humans learn the higher‐order regularities of a highly simplified input where only sequential‐order information marks the hierarchical structure. To this end, we implemented a sequence generated by the Fibonacci grammar in a serial reaction time task. This deterministic grammar generates aperiodic but self‐similar sequences. The combination of these two properties allowed us to evaluate hierarchical learning while controlling for the use of low‐level strategies like detecting recurring patterns. The deterministic aspect of the grammar allowed us to predict precisely which points in the sequence should be subject to anticipation. Results showed that participants' pattern of anticipation could not be accounted for by "flat" statistical learning processes and was consistent with them anticipating upcoming points based on hierarchical assumptions. We also found that participants were sensitive to the structure constituency, suggesting that they organized the signal into embedded constituents. We hypothesized that the participants built this structure by merging recursively deterministic transitions. [ABSTRACT FROM AUTHOR]

In this paper, we prove the existence of a spherical t -design formed by adding extra points to an arbitrarily given point set on the sphere and, subsequently, deduce the existence of nested spherical designs. Estimates on the number of required points are also given. For the case that the given point set is a spherical t 1 -design such that t 1 < t and the number of points is of optimal order t 1 d , we show that the upper bound of the total number of extra points and given points for forming nested spherical t -design is of order t 2 d + 1. A brief discussion concerning the optimal order in nested spherical designs is also given. [ABSTRACT FROM AUTHOR]

Optical tilt mirrors (OTM) enable the mirrors to achieve high precision posture adjustment, playing a significant role in various optical system applications in the fields such as active optics, adaptive optics, satellite communications and biomedicines. However, the rapid development of modern technologies has brought new challenges to OTM in terms of their dimension, operating space and dynamic performance. Herein, a novel biaxial optical flexible tilt mirror (OFTM) driven by four simple bonded-type thin sheet piezoelectric actuators was proposed, where the OFTM was designed based on the flexible bending motions of composite piezoelectric beams. Particularly, OFTM is mainly composed of PZT sheet and stainless steel substrate, and shows a dimension of 42 mm × 42 mm × 0.2 mm. A theoretical model of OFTM was established to accurately describe the relationship between input electric field and output pose based on elastic beam theory, where the relationship was verified by both finite element analysis and experimental results. Finally, an OFTM prototype was fabricated and presented good performance on motion behaviors. Compared with traditional fast steering mirror (FSM) and MEMS mirror, the developed OFTM shows low cost, small size and simple manufacturing process, which greatly extends the applications of OFTTM in emerging fields. [Display omitted] • A novel biaxial optical flexible tilt mirror (OFTM) driven by four bonded-type piezoelectric actuators was developed. • A model was established to describe the relationship between static characterictics and structural parameters of OFTM. • Static and dynamic test results demonstrated the feasibility of OFTM in beam steering at closed-loop working conditions. [ABSTRACT FROM AUTHOR]

At present，robot joint reducers are all constant transmission ratio，which makes it difficult for the motor to reach peak efficiency. Based on the nested structure，a compact continuously variable transmission （CVT） for robots is proposed，which can effectively increase the power usage of the motor by changing the transmission ratio in real time. Firstly，the mechanism of variable speed transmission is studied to obtain the relationship between transmission ratio and the ratio of planetary gear to sun gear radius，and the nested structure and the axial movement system of planetary gear and sun gear plate are designed. Secondly，the mathematical models of envelope angle on planetary and sun gear，transmission ratio，and radial movement of metal belt are deduced. Based on the multi-rigid-body dynamics simulation software，the output speed of the CVT is verified to show that the forward and reverse deviations of the transmission are 1.89% and 3.87% respectively. Finally，the principle prototype of the CVT is manufactured and the torque experiment platform is built，and the output torque is set to a specific value to test the corresponding input torque. The experiment shows that the test value is basically the same as the theoretical value，and the average transmission efficiency is 72.1%，which indirectly verifies the correctness of the theoretical derivation.

The aim of this paper is to present a novel approach to energy use forecasting. We propose a nested fuzzy cognitive map in which each concept at a higher level can be decomposed into another fuzzy cognitive map, multilayer perceptron artificial neural network or long short-term memory network. Historical data related to energy consumption are used to construct a nested fuzzy cognitive map in order to better understand energy use behavior. Through the experiments, the usefulness of the nested structure in energy demand prediction is demonstrated, by calculating three popular metrics: Mean Square Error, Mean Absolute Error and the correlation coefficient. A comparative analysis is performed, applying classic multilayer perceptron artificial neural networks, long short-term memory networks and fuzzy cognitive maps. The results confirmed that the proposed approach outperforms the classic methods in terms of prediction accuracy. Moreover, the advantage of the proposed approach is the ability to present complex time series in the form of a clear nested structure presenting the main concepts influencing energy consumption on the first level. The second level allows for more detailed problem analysis and lower forecast errors. [ABSTRACT FROM AUTHOR]

Named entity recognition is a basic task in natural language processing, and there is a large number of nested structures in named entities. Nested named entities become the basis for solving many tasks in NLP. A nested named entity recognition model based on dual-flow features complementary is proposed for obtaining efficient feature information after text coding. Firstly, sentences are embedded at both the word level and the character level of the words, then sentence context information is obtained separately via the neural network Bi-LSTM; Afterward, two vectors perform low-level feature complementary to reinforce low-level semantic information; Sentence-local information is captured with the multi-head attention mechanism, then the feature vector is sent to the high-level feature complementary module to obtain deep semantic information; Finally, the entity word recognition module and the fine-grained division module are entered to obtain the internal entity. The experimental results show that the model has a great improvement in feature extraction compared to the classical model. [ABSTRACT FROM AUTHOR]

Analyzing the formation mechanisms of industrial parks and quantitatively evaluating the related hazard levels are important for understanding the development and planning of industrial parks, but there is currently a lack of relevant research. In this study, Beijing was taken as a case study. The analysis results showed that (1) the overall spatial distribution of industrial parks in Beijing followed a clustering pattern, with nested spatial distribution pattern, where larger structures contributed 53.96% of the variance; (2) for the overall spatial distribution of industrial parks, kernel density of enterprises was the main influencing factor, which there were synergistic enhancement effects with almost all other influencing factors, especially urban construction, the number of financial institutions, the population density, this can share transportation and other resources, achieving coordinated development. According to these main factors, the prediction model of the future spatial distribution pattern of industrial parks in Beijing was established; (3) for site selection of each industrial park, twenty-two industrial parks near industrial enterprises in Beijing were more affected by industrial enterprise clustering, and the remaining 65 industrial parks were strongly affected by terrain, (4) The industrial parks in the central and southern parts of Beijing presented a relatively high hazard level to the surrounding sensitive receptors. These results provide theoretical support for the development and layout of industrial parks., Competing Interests: Declarations. Conflict of interest: The authors declare that they have no competing interests. Consent for publication: Not applicable. Consent to participate: Not applicable. Ethics approval: Not applicable., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Background: Over time, demographic and health survey (DHS) data remain valuable to examine variables relating to nationally representative population outcomes for low- and middle-income countries. In Tanzania, there are very limited DHS-based studies on the uptake of Modern Contraceptive Use (MCU). Present studies have focused on measurements at the level of individuals, yet research has shown that MCU variations exists at other levels within populations. In this study, we use a variance component modelling approach to explore variation in MCU at primary sampling unit (PSU) and regional levels while considering survey sample weights. Methods: Using DHS data from 2016–2017 in Tanzania, we study different variance structures and the respective variation on MCU in a sample of 5263 Women of Reproductive Age (WRA) defined as between the ages of 15–49 years. First, a single variance component was used, followed by its extension to a random coefficient model and we tracked changes in the models. Results: There was an influence of random variations on MCU on the levels of populations much explained by PSU-level clustering than region. On the fixed part, age of a woman, husband education level, desire to have children, and exposure to media and wealth tertiles were important determinants for MCU. Compared to WRA in 15–19 years, the odds of MCU among middle aged women (20–29 and 30–39 years) were 1.94 (95%CI:1.244–3.024) and 2.28 (95%CI:1.372–3.803). Also, increases in media exposure and middle and rich wealth tertiles women led to higher odds for MCU. We also found the presence of random effects influence of wealth tertiles levels on MCU. Conclusion: This study highlighted the utility of accounting for variance structures in addressing determinants of MCU while using DHS national level data. Apart from MCU, the DHS data have been widely applied to examine other variables pertaining to public health issues. This approach could be considered a better modelling technique for the DHS studies compared to traditional survey approaches, and to guide hierarchical population-based interventions to increase MCU. [ABSTRACT FROM AUTHOR]

• Combining origami theory and nesting system to propose a new lightweight and thin-walled structure design scheme. • The failure mechanisms of NOB and OCB were analyzed by quasi-static compression tests combined with the FEM. • NOB significantly improves the SEA compared to OCB, and PCF value remains unchanged. • Multi-objective optimization of NOB using RS model combined with NSGA-II. In recent years, the study of the crashworthiness of lightweight and efficient thin-walled energy-absorbing structures has received increasing attention. In this work, 3D printing technology was adopted to create a nested origami crash box with stiffness variation, which was made of short carbon fiber reinforced nylon material. The structure effectively inhibits the development of failure behavior of short carbon fiber-reinforced nylon origami crash box due to material brittleness. The quasi-static compression experiment results indicate that compared to origami crash box, nested origami crash box improves by 40% in specific energy absorption and 50% in crash force efficiency, while the initial peak crushing force remains unchanged. The effects of three key geometrical parameters, namely dihedral angle, distance between tubes, and height difference on the damage mechanism of the nested origami crash box are discussed in detail using the finite element method, and the response surface model combined with the non-dominated sorting genetic algorithm II is used for multi-objective optimization. In this work, the concepts of origami theory and nested systems are integrated for the first time, aiming to achieve a stable and efficient energy-absorbing deformation mode by precisely modulating the stress transfer path of the structure and its stiffness. This work provides new ideas for the design and fabrication of novel lightweight energy-absorption boxes. [ABSTRACT FROM AUTHOR]

The energy absorption behavior of nested tubes under lateral loading conditions was investigated in this study. Nested tubes are considered as an alternative to energy absorption structures used in many industries including automotive, military, and aerospace. Steel tubes with the same wall thickness and different diameters were used in the experiments. First, experiments of single tubes were carried out, and the deformation behavior of tubes under lateral load was examined in detail. Afterward, experiments were carried out on nested tube samples in which a minimum of 2 and a maximum of 6 tubes were used together in different numbers and sequences. It was seen from the experiments that the best-nested tube configuration in terms of energy absorption capacity was the sample that contains 6 tubes with 1767 J. While this sample absorbed 5% higher energy than the sample with 5 tubes, the specific energy absorption value was calculated to be 10% lower. Additionally, the sample with 6 tubes has a value of 43% in terms of energy efficiency which is 7% lower compared to that of the sample with 5 tubes. It was determined that the sample with 5 tubes yielded the most efficient design when specific energy absorption capability, work effectiveness, and energy efficiency parameters were considered.

Merging different flood characteristics in a distribution function is provided by copula structures. In this study, the nested copula structure was used to construct a trivariate distribution of flood duration (D), peak (P), and volume (V). The required data were obtained by screening the flood events recorded at Armand Gauging Station, Iran. The characteristics of selected 63 flood events (1993–2018) were extracted and the best marginal distribution function of each was determined by Kolmogorov–Smirnov test. Then the fitness of six different copula functions (Frank, Clayton, Joe, Gumbel–Hougaard, Gaussian and Student's t were examined for creating the joint distribution function. The best fitted marginal distribution is Johnson SB, for flood duration, and Lognormal (3p), for flood peak and flood volume. The best-fitted function for creating bivariate and trivariate distributions of flood characteristics in Armand Basin is Frank copula. In the next phase, the bivariate and trivariate joint return periods (at two states of AND, OR), Kendall return period and conditional return periods were calculated. The results revealed that the conditional return period of one flood variable given two other flood variables is greater than the corresponding values for the conditional return period of two flood variables given the third flood variable. [ABSTRACT FROM AUTHOR]

The article deals with the spatial pattern of the supply network of the automotive industry according to the time-accessibility to four car assembly plants in Slovakia. Empirical results are anchored in the spatial concept of integrated periphery and theoretical framework of the nested structure. We obtained the data after a personal meeting with the General Secretary of the Association of the Automotive Industry in Slovakia. The database contains a list of 313 suppliers of different levels. We assume that with increasing distance from automobile assembly plants and decreasing level of the supply network, the geographical concentration of the supply network will become lower. Our results confirm the assumption that tier-1 suppliers are located closer to assembly plants with higher geographical concentration compared to bottom suppliers' levels. On the other hand, these spatial patterns change when we consider a regional production system of the automotive industry that reaches beyond the national territory scale (e.g., KIA) or a launch of a new car assembly plant (JLR) arriving into a developed environment with an existing network of suppliers. [ABSTRACT FROM AUTHOR]

Rational utilization of grassland is crucial to regional sustainable development, in which the classification of grassland utilization is the foundation. Traditional classification mainly focuses on a single attribute of grassland, and it is necessary to develop a new index to comprehensively classify grassland. Based on ecological site (ES) and state-and-transition model (STM) theory, 164 sample points of Inner Mongolia grassland were divided into four ecological sites and eight grassland utilization units by cluster analysis. We found that (1) the classification of grassland utilization based on ES and STM has a strict nested hierarchical structure; (2) soil texture is the main driving factor of grassland utilization units; and (3) the new grassland utilization unit integrates ecological and economic attributes, which is more suitable for grassland management. This new method, combined with remote sensing technology, will show great potential in regional grassland management.

With the popularity of image sensors in various mobile devices, image blurring caused by hand shaking or out of focus becomes ubiquitous, which deteriorates image quality and poses challenges for vision tasks, including object detection, image classification and image segmentation. Designing an efficient blur detection algorithm which can automatically detect and locate blurred regions becomes necessary. In this letter, we design an end-to-end convolution neural network called heterogeneous attention nested U-shaped network (HANUN) for blur detection. We introduce pyramid pooling into encoders to enhance the feature extraction at different scales and reduce the gradual information loss. Inspired by the nested network design, small U-shaped networks are embedded into our decoders to increase the network depth and promote feature fusion with different receptive field scales. In addition, we incorporate a channel attention mechanism in the proposed network to highlight the informative features for detecting the blurry regions. Experimental results show that HANUN outperforms other state-of-the-art algorithms for blur detection tasks on public datasets and real-world images. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a novel approach to energy use forecasting. We propose a nested fuzzy cognitive map in which each concept at a higher level can be decomposed into another fuzzy cognitive map, multilayer perceptron artificial neural network or long short-term memory network. Historical data related to energy consumption are used to construct a nested fuzzy cognitive map in order to better understand energy use behavior. Through the experiments, the usefulness of the nested structure in energy demand prediction is demonstrated, by calculating three popular metrics: Mean Square Error, Mean Absolute Error and the correlation coefficient. A comparative analysis is performed, applying classic multilayer perceptron artificial neural networks, long short-term memory networks and fuzzy cognitive maps. The results confirmed that the proposed approach outperforms the classic methods in terms of prediction accuracy. Moreover, the advantage of the proposed approach is the ability to present complex time series in the form of a clear nested structure presenting the main concepts influencing energy consumption on the first level. The second level allows for more detailed problem analysis and lower forecast errors.

Named entity recognition is a basic task in natural language processing, and there is a large number of nested structures in named entities. Nested named entities become the basis for solving many tasks in NLP. A nested named entity recognition model based on dual-flow features complementary is proposed for obtaining efficient feature information after text coding. Firstly, sentences are embedded at both the word level and the character level of the words, then sentence context information is obtained separately via the neural network Bi-LSTM; Afterward, two vectors perform low-level feature complementary to reinforce low-level semantic information; Sentence-local information is captured with the multi-head attention mechanism, then the feature vector is sent to the high-level feature complementary module to obtain deep semantic information; Finally, the entity word recognition module and the fine-grained division module are entered to obtain the internal entity. The experimental results show that the model has a great improvement in feature extraction compared to the classical model.

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The long-term operation of power equipment and power electronics can cause local overheating and discharges in the insulation material, resulting in irreversible insulation damage. Further development of such damage can eventually lead to equipment failure, but this problem is very difficult to solve. In this paper, inspired by how the petals of morning glory change color with the environment due to the presence of pigmented globules, a dual-function heat alert in the form of a self-healing (HASH) microcapsule with a nested structure is prepared by using microfluidic technology. By combination of the microcapsule with the insulation material, the local overheating in equipment can be detected promptly under live operating conditions without manual external intervention, and the defects that occur can be repaired autonomously. These HASH microcapsules can be pre-embedded in places at which the material is prone to overheating using artificial magnetic targeting. The doping of the matrix material with microcapsules does not cause any deterioration in its electrical or mechanical properties. This technology is expected to be applied to electrical equipment and electronic devices to allow for the early detection of local overheating and the autonomous repair of defects, thereby ensuring the safety of the equipment and improving its service life.

Tension experience is the basis for music emotion. In music, discrete elements are always organized into complex nested structures to convey emotion. However, the processing of music tension in the nested structure remains unknown. The present study investigated the tension experience induced by the nested structure and the underlying neural mechanisms, using a continuous tension rating task and electroencephalography (EEG) at the same time. Thirty musicians listened to music chorale sequences with non-nested, singly nested and doubly nested structures and were required to rate their real-time tension experience. Behavioral data indicated that the tension experience induced by the nested structure had more fluctuations than the non-nested structure, and the difference was mainly exhibited in the process of tension induction rather than tension resolution. However, the EEG data showed that larger late positive components (LPCs) were elicited by the ending chords in the nested structure compared with the non-nested structure, reflecting the difference in cognitive integration for long-distance structural dependence. The discrepancy between resolution experience and neural responses revealed the non-parallel relations between emotion and cognition. Furthermore, the LPC elicited by the doubly nested structure showed a smaller scalp distribution than the singly nested structure, indicating the more difficult processing of the doubly nested structure. These findings revealed the dynamic tension experience induced by the nested structure and the influence of nested type, shedding new light on the relationship between structure and tension in music.

Brown leaf spot (BLS), Bipolaris oryzae is one of the emerging threats to the rice crop. Its infection caused deficiency of minerals contents in rice crop. Therefore, current study was designed to determine the variations of ionic contents in rice crop after the attack of BLS disease. The leaf samples of resistant rice varieties (Kissan Basmati, Chenab Basmati, IRRI-6) and susceptible varieties (Basmati-2000, Basmati-515, KSK-133) were analyzed, and the significant alterations (p ≤ 0.05) in the ionic contents were noted across treatments, types (un-inoculated and inoculated), groups (susceptible and resistant) and varieties of rice due to the infection of the pathogen. Nested structure analysis of variance revealed a significant difference in ionic status (N, P, K, Na, Ca, Cu, Fe, and Zn) of rice leaves. Resistant type of plants expressed 1.28% and 0.54% while susceptible type showed 1.22% and 0.43% difference in concentrations of N and K respectively. Moreover, resistant type expressed 7379.23, 2229.47, 5.02, 222.68, 28.94 and 662.29 ppm; while, susceptible type showed 7025.38, 1895.02, 4.15, 177.95, 22.17 and 520.71 ppm difference in concentrations of P, Na, Cu, Fe, Zn and Ca, respectively. It was accomplished that resistant variety stored ionic contents at higher concentrations than susceptible. The higher ionic contents concentration in resistant rice plants build up the physiological and biochemical processes of the rice plant, which help to avoid the spread of the pathogen. [ABSTRACT FROM AUTHOR]

Tension experience is the basis for music emotion. In music, discrete elements are always organized into complex nested structures to convey emotion. However, the processing of music tension in the nested structure remains unknown. The present study investigated the tension experience induced by the nested structure and the underlying neural mechanisms, using a continuous tension rating task and electroencephalography (EEG) at the same time. Thirty musicians listened to music chorale sequences with non-nested, singly nested and doubly nested structures and were required to rate their real-time tension experience. Behavioral data indicated that the tension experience induced by the nested structure had more fluctuations than the non-nested structure, and the difference was mainly exhibited in the process of tension induction rather than tension resolution. However, the EEG data showed that larger late positive components (LPCs) were elicited by the ending chords in the nested structure compared with the non-nested structure, reflecting the difference in cognitive integration for long-distance structural dependence. The discrepancy between resolution experience and neural responses revealed the non-parallel relations between emotion and cognition. Furthermore, the LPC elicited by the doubly nested structure showed a smaller scalp distribution than the singly nested structure, indicating the more difficult processing of the doubly nested structure. These findings revealed the dynamic tension experience induced by the nested structure and the influence of nested type, shedding new light on the relationship between structure and tension in music. [ABSTRACT FROM AUTHOR]

Assessing the factors associated with nestedness patterns is a crucial aspect in studies of community structure. Bird assemblages in the Jardines de la Reina archipelago have a stable nested structure but the underlying influences have not been evaluated. We constructed a presence–absence data matrix based on a bird inventory obtained from 43 cays of this archipelago. We calculated nestedness using the NODF metric based on the overlap and decreasing fill and evaluated its significance by running 1,000 iterations of four null models. The matrix columns were rearranged to evaluate seven factors possibly related to the nestedness of bird communities. Bird assemblages exhibited a significant nested pattern (67.93) and all factors contributed (p < 0.01) to the nestedness patterns of bird communities. Habitat diversity and cay area and perimeter were the factors that contributed most to the nested structure. The nestedness pattern in the bird assemblages of the Jardines de la Reina archipelago was potentially caused by the interaction of selective extinction and differential colonization of species, with the former having a more remarkable effect.

In this research, a novel phononic crystal (PC) is investigated theoretically to enhance acoustic pressure confinement. It consists of multiple nested resonators based on a tapered configuration. Nested phononic crystal resonator (NPCR) can enhance the acoustic pressure amplification at resonant cavity to a great degree better than the traditional one with same dimensions. The resonant frequency of NPCR is mainly located within outermost phononic crystal resonator's (PCR) band gap. Meanwhile, it does not move significantly to high frequency with the addition of inner tapered resonators. The enhanced acoustic pressure resonant amplification is attributed to the improvement of the confinement mode owing to the nested structure working as a taper. Then effects of geometrical dimensions of inner PCRs on acoustic confinement are studied. It shows that resonant frequency and resonant acoustic pressure can be affected by the geometric parameters. NPCR has stronger acoustic confinement effects, which are conducive to improve acoustic sensing sensitivity, acoustic signal frequency resolution and acoustic energy harvesting efficiency. [ABSTRACT FROM AUTHOR]

Multilevel models have become popular models for analyzing longitudinal data over past two decades. Longitudinal designs are common specially in medical science, where data is recorded on patients more than two times. As the data is collected on the same patients repeatedly over time, it is more likely that observations are correlated with each other. When the observations are correlated and the data have nested structure, traditional methods give biased estimates of the parameters, as they require the assumption of independence. The present study is concerned with exploring the effect of misspecification of level-I errors covariance structure in multilevel model for longitudinal data. The fixed effects were estimated with little to no bias, and accurate type-I error rates were observed under all the specifications of the covariance structure for the test of fixed effects. Random effects were estimated poorly for most of the conditions. Overestimated variances of the level-II random effects were accompanied by the underestimated level-I variance. The covariance between intercept and slope was underestimated in all conditions. The over specification of the covariance matrix of level-I errors gave better estimates than correct specification, under-specification and general misspecification. [ABSTRACT FROM AUTHOR]

Oscar Wilde's only novel, The Picture of Dorian Gray (1891), one of the flagship novels of Aestheticism, contains an intricate opium narrative that has yet to receive adequate critical attention. The novel consists of two nested units: the House Beautiful that subsumes a Gothic nursery where Dorian's portrait is placed, and London the Metropolis that harbours Blue Gate Fields in the East End. The former might be read as a miniature of the latter. This double mechanism hinges on a Chinese box in which opium is stored. The structure, which evolves from the classic opium narrative established by Thomas De Quincey's Confessions of an English Opium Eater (1821), enables Wilde to stage a critique on the connection between Aestheticism and the imperial trade of opium. Besides, Wilde's aesthete trio in the novel, Lord Henry Wotton, Dorian Gray, and Adrian Singleton, are cast as opium smokers in order to disrupt the imperialist mindset showcased in the cartoons appearing on trade cards and in magazines that satirise Wilde's promotion of Aestheticism. This essay contends that Wilde's opium narrative exposes the hypocrisy of Empire by demonstrating that the coloniser and the colonised are anamorphic reflections of each other. [ABSTRACT FROM AUTHOR]

A terahertz metamaterial absorber (MA) with properties of broadband width, polarization-insensitive, wide angle incidence is presented. Different from the previous methods to broaden the absorption width, this letter proposes a novel combinatorial way which units a nested structure with multiple metal–dielectric layers. We numerically investigate the proposed MA, and the simulation results show that the absorber achieves a broadband absorption over a frequency range of 0.896 THz with the absorptivity greater than 90%. Moreover, the full-width at half maximum of the absorber is up to 1.224 THz which is 61.2% with respect to the central frequency. The mechanism for the broadband absorption originates from the overlapping of longitudinal coupling between layers and coupling of the nested structure. Importantly, the nested structure makes a great contribution to broaden the absorption width. Thus, constructing a nested structure in a multi-layer absorber may be considered as an effective way to design broadband MAs. [ABSTRACT FROM PUBLISHER]

We propose a fully automatic segmentation method called nested graph cut to segment images (2D or 3D) that contain multiple objects with a nested structure. Compared to other graph-cut-based methods developed for multiple regions, our method can work well for nested objects without requiring manual selection of initial seeds, even if different objects have similar intensity distributions and some object boundaries are missing. Promising results were obtained for separating the brain ventricles, the head, and the uterus region in the mouse-embryo head images obtained using high-frequency ultrasound imaging. The proposed method achieved mean Dice similarity coefficients of 0.87 \pm 0.04 and 0.89 \pm 0.06 for segmenting BVs and the head, respectively, compared to manual segmentation results by experts on 40 3D images over five gestation stages. [ABSTRACT FROM PUBLISHER]

We investigated the effect of crop type heterogeneity on carabid beetles in intensively managed agricultural landscapes. We compared different crops and habitat type configurations and compositions. In addition we assessed the effect of artificial fragmentation by paved roads and water channels in an agricultural landscape. Crop type heterogeneity negatively affected carabid assemblages. Spatial dissection by artificial structures had an even more negative effect on carabid diversity. The nested structure of the carabid assemblages among crop types was caused by a negative response to heterogeneity in the agricultural landscape. Even though crop types in an intensive agricultural landscape increased, the landscape may tend to fragment habitat. Although artificially fragmented habitats had more unstable carabid assemblages, heterogeneity from different crop types has also been shown to be a characteristic of fragmented landscapes. To produce a positive relationship between biodiversity and heterogeneity in an agricultural landscape, farming intensity should be reduced to allow for the conversion of highly productive lands into more natural habitats. [ABSTRACT FROM AUTHOR]

The location of commercial spaces in multistory buildings affects their values. We developed a three-level mixed-effects spatial hedonic model in which the nested structure of individual commercial units in multistory buildings is explicitly taken into account in the price determination process. The proposed modeling framework is intuitive and flexible from both substantive and technical perspectives, as evidenced by its diverse extensions to accommodate both the spatial autocorrelation and the complex heteroscedasticity inherent in property values. A unique data set based on the assessed values of commercial properties and officetels, collected by the National Tax Service of Korea in 2012, is merged with structural and location information on buildings for a case study. We found both the floor level and building effects are important factors when valuing commercial units in multistory buildings. We show that model fit is significantly affected if the spatial autocorrelation at the individual level is not included in hedonic price models. [ABSTRACT FROM AUTHOR]

The multidimensional dynamic programming (MDP) algorithm is a traditional method used to solve cascade reservoir operation optimization (CROO) problems, but the high dimensionality called the curse of dimensionalitycannot be ignored. In order to alleviate this problem, this paper proposes a new MDP algorithm named multilayer nested multidimensional dynamic programming (MNDP), which is based on a multilayered, nested structure. MNDP is mainly used to deal with computer memory space and computation complexity problems of MDP in CROO, and its recursive equation of reverse recursion calculation and specific calculation steps are presented in detail. This paper takes the cascade reservoirs of the Li Xianjiang River in China as an example to solve the CROO problem with the proposed MNDP. By comparing with the dynamic programming with successive approximations (DPSA) method, MNDP presents better performance in terms of power generation and the assurance rate in wet, normal, dry, and average years. The global optimality of MNDP is validated by MDP, and the parallel computing results of MNDP are shown in a case study. The MNDP proposed in this paper can reduce not only the programming complexity of MDP, but also the storage of intermediate variables during calculation, thus effectively solving the curse of dimensionality of MDP in CROO and keeping the global convergence feature of MDP. [ABSTRACT FROM AUTHOR]

We propose a method for estimating the parameters of contingency table models, which is motivated by a geometrical idea. Our method--bisector regression for contingency tables (BRCT)--is based on a nested structure of contingency table models. Our method estimates parameters corresponding to the interactions of lower orders after estimating or eliminating those of higher orders. BRCTgenerates a sequence of parameter estimates, each element of which represents a model and a parameter estimate. The length of the sequence is equal to the number of parameters, which is much smaller than the total number of models. We describe the BRCTalgorithm and show an example. We provide explanations for two cases: (a) two factors and (b) K factors. [ABSTRACT FROM AUTHOR]

The processing difficulty of nested grammatical structure has been explained by different psycholinguistic theories. Here I provide corpus and behavioral evidence in favor of usage-based models, focusing on the case of object relative clauses in Spanish as a first language. A corpus analysis of spoken Spanish reveals that, as in English, the overwhelming majority of object relative clauses are pronominal. Spanish allows flexibility of order of surface constituents within the clause. The corpus data revealed significant asymmetries in the frequency of order of surface constituents in pronominal and nonpronominal object relative clauses. Two offline rating tasks and one self-paced reading task were next conducted, showing that complexity judgments and reading processing data mirrored the fine-grained distributional patterns revealed by the corpus analysis. I conclude that frequent object relative clauses may become easier to process as a consequence of use and repetition, and I discuss the implications of these findings for usage-based models of language representation and access. [ABSTRACT FROM AUTHOR]

• The new grassland utilization unit is based on ecological site and STM. • New grassland utilization unit reflects both ecological and economic attributes. • Soil texture is the key factor of the grassland utilization unit. • New grassland utilization unit provides support for management and decision-making. Rational utilization of grassland is crucial to regional sustainable development, in which the classification of grassland utilization is the foundation. Traditional classification mainly focuses on a single attribute of grassland, and it is necessary to develop a new index to comprehensively classify grassland. Based on ecological site (ES) and state-and-transition model (STM) theory, 164 sample points of Inner Mongolia grassland were divided into four ecological sites and eight grassland utilization units by cluster analysis. We found that (1) the classification of grassland utilization based on ES and STM has a strict nested hierarchical structure; (2) soil texture is the main driving factor of grassland utilization units; and (3) the new grassland utilization unit integrates ecological and economic attributes, which is more suitable for grassland management. This new method, combined with remote sensing technology, will show great potential in regional grassland management. [ABSTRACT FROM AUTHOR]

Abstract: A novel scheme for high speed optical differential Manchester code generation is proposed and theoretically demonstrated using the structure of two nested Mach–Zehnder interferometers (MZIs). A 40Gb/s differential Manchester code is generated. The obtained signal quality performances show that, the proposed scheme experiences very low power penalty. [Copyright &y& Elsevier]