Adaptation Path Research Articles

A Study on Factors Influencing Digital Reading Behavior of Junior High School Students

Abstract The present study aimed to explore the impact pathway of digital reading willingness and behavior among junior high school students in Guangxi’s developed urban areas, so as to improve the digital reading quality of teenagers. This study took students from key junior high schools in Nanning, Guilin, and Liuzhou as the research subjects. The UTAUT model retained three factors, performance expectation, effort expectation, and social impact, while introducing two variables, perceived risk and immersive experience, to jointly develop a factor model for the digital reading behavior of junior high school students in Guangxi. After conducting a questionnaire survey using an “online + offline” method, 497 valid questionnaires were obtained. SPSS 23 was used to perform reliability and validity analysis and descriptive statistical analysis, while AMOS 26.0 was used to conduct discriminant validity analysis, model adaptation analysis, hypothesis testing, and path analysis. The research conclusion was that performance expectations, effort expectations, social impact, and immersive experience all had a positive and significant impact on the digital reading willingness of junior high school students; performance expectations, effort expectations, social impact, and immersive experience positively influenced their digital reading behavior through their digital reading willingness, while perceived risk was found to have no significant impact on digital reading willingness and corresponding behavior. This article used a composite research method to study a sample of student groups in specific regions. It was an early introduction of immersive experience and perceived risk indicators in the study of digital reading behavior, specifically exploring the digital reading patterns of junior high school students who had received less attention in previous studies but were in a critical period of growth.

Mechanism of strategic remoulding of high-dimensional industrial eco-economy and the reconstruction of carbon neutral industrial chain

Considerable changes in the international society, fierce international competition and unpredictable economic changes are currently observed. Since then, the epidemic has had a far-reaching impact, and many industrial and supply chains have suffered from ‘broken chains’, ‘blocked chains’ and ‘poor chains’. The European Union (EU) has also sounded the alarm on China’s ‘card neck’ restrictions and ‘entity list’. Therefore, pursuing the integration of dual carbon landscape planning and industrial chain and addressing the key high-dimensional ecological economy ‘neck-choking’ problem path have become important tasks. National ministries and commissions have issued a number of documents to promote the integration and innovation of the industrial chain, high-, medium- and low-dimensional enterprises, and guide such industries to take the road of ‘high dimensional’ development. This paper takes eco-economic strategy as the starting point to reshape the systematic theoretical analysis framework of economic strategy mechanism. In response to the high-dimensional industrial transformation adaptation path and carbon neutral industry chain development model of the academic inquiry, the ‘profit model’ is set as the core and configuration complementary, alternative management thinking analysis path and model. Simultaneously, the high-dimensional industrial eco-economic industrial chain adaptation path is identified. The effects of high-dimensional industry ‘five forces’, ‘colouring map’ and ‘new tools’ are explored and then integrated and refined to improve the implementation efficiency of the carbon neutral industrial chain. Finally, focusing on the high-dimensional ecological economic strategy reshaping mechanism, the formation of sustainable development of the ‘carbon neutral’ industrial chain, unified standards and the realisation of the chain length system is investigated.

The adaptation path of environmental governance in the Yellow River Basin for regional ecological improvement

The adaptation path of environmental governance in the Yellow River Basin for regional ecological improvement

Prototypical Bidirectional Adaptation and Learning for Cross-Domain Semantic Segmentation

Cross-domain semantic segmentation, which aims to address the distribution shift while adapting from a labeled source domain to an unlabeled target domain, has achieved great progress in recent years. However, most existing work adopts a source-to-target adaptation path, which often suffers from clear class mismatching or class imbalance issues. We design PBAL, a prototypical bidirectional adaptation and learning technique that introduces bidirectional prototype learning and prototypical self-training for optimal inter-domain alignment and adaptation. We perform bidirectional alignments in a complementary and cooperative manner which balances both dominant and tail categories as well as easy and hard samples effectively. In addition, We derive prototypes efficiently from a source-trained classifier, which enables class-aware adaptation as well as synchronous prototype updating and network optimization. Further, we re-examine self-training and introduce prototypical contrast above it which greatly improves inter-domain alignment by promoting better intra-class compactness and inter-class separability in the feature space. Extensive experiments over two widely studied benchmarks show that the proposed PBAL achieves superior domain adaptation performance as compared with the state-of-the-art.

Diagnostics using a physics-based engine model in aero gas turbine engine verification tests

In the present study, the application of a diagnostic method using a physics-based model is proposed during engine verification testing. A physics-based engine model is constructed, based on a 0-dimensional system analysis method, and then revised through performance adaptation with a basic engine model. Adaptation factors are used for the compressor, secondary air system, nozzle, exhaust gas temperature, and engine thrust. Gas path analysis is conducted using the physics-based engine model and the performance test data in real time. A health parameter that can quantitatively evaluate the performance difference of components was defined. Health parameters for the compressor capacity and efficiency, secondary air system, and nozzle are calculated from the gas path analysis. The multi-variable Newton–Raphson method is employed for the performance adaptation and gas path analysis in real time. A single-shaft gas turbine engine, which is constructed based on the core part of a turbofan engine currently under development, is utilized to test and evaluate the effectiveness of the proposed method. Three tests are performed for engine verification. The proposed diagnostic method is applied to the aero gas turbine engine verification test. In 33 test cases, the fault detection rates for the compressor's variable guide vane, secondary air system, and variable area nozzle are 100%, 91%, and 79%, respectively. As a result, it is confirmed that the proposed method can simultaneously detect abnormalities in the compressor's variable guide vane, secondary air system, and variable area nozzle. In addition, this study indicates that applying the physics-based engine model to the diagnostics logic can effectively detect failures with a small amount of data.

Conflict and Adaptation Path between the Certainty Requirements of Appraisal Opinions and Practices

Conflict and Adaptation Path between the Certainty Requirements of Appraisal Opinions and Practices

Adapting critical infrastructure to climate change: A scoping review

Critical infrastructure is a foundational component of a functional society and is under threat from the impacts of climate change. To ensure communities are not left without fundamental supplies and services, the adaptation of critical infrastructure to climate change needs to be understood holistically. This paper uses a scoping literature review to investigate the relationship between critical infrastructure and climate change. In the absence of a common definition for adaptive critical infrastructure, an outcomes-based definition is proposed that captures the four types of critical infrastructure: physical, ecological, institutional and cultural. A typology was developed to critically interrogate the focus of adaptive critical infrastructure. It shows that the focus across elements such as conceptualisation and management ranges from tangible to intangible infrastructure, and from positivist to interpretivist in approach. The literature review identified relationship-building as a key management objective across the spectrums. The typology contributes knowledge on how the choice of infrastructure focus and adaptation methods influences adaptation outcomes and path dependencies.

Chemical reactor with integrated heat exchanger, heater, and high conductance catalyst holder

With the growing development in the Internet of Things and smart devices, researchers attach great importance to wearable sensor to monitor biological and environmental parameters. These handy tools offer several opportunities to users, such as healthier lifestyles and a sense of safety. As the wearable sensing industry is advancing, the demand for more accurate and reliable sensing approaches has become necessary. Because of high conductivity, large surface area, biocompatibility, and excellent physical and chemical properties, carbon nanomaterials have considerable potential in wearable sensing technology. This chapter presents an overview of recent progress in carbon structures and, following that, an in-depth review of the recent progress in wearable sensors in clinical and industry. Finally, the current status of commercial sensing devices, possible limitations, and difficulties in the adaptation path of this technology in the industry are discussed.

U-ASD Net: Supervised Crowd Counting Based on Semantic Segmentation and Adaptive Scenario Discovery

Crowd counting considers one of the most significant and challenging issues in computer vision and deep learning communities, whose applications are being utilized for various tasks. While this issue is well studied, it remains an open challenge to manage perspective distortions and scale variations. How well these problems are resolved has a huge impact on predicting a high-quality crowd density map. In this study, a hybrid and modified deep neural network (U-ASD Net), based on U-Net and adaptive scenario discovery (ASD), is proposed to get precise and effective crowd counting. The U part is produced by replacing the nearest upsampling in the encoder of U-Net with max-unpooling. This modification provides a better crowd counting performance by capturing more spatial information. The max-unpooling layers upsample the feature maps based on the max locations held from the downsampling process. The ASD part is constructed with three light pathways, two of which have been learned to reflect various densities of the crowd and define the appropriate geometric configuration employing various sizes of the receptive field. The third pathway is an adaptation path, which implicitly discovers and models complex scenarios to recalibrate pathway-wise responses adaptively. ASD has no additional branches to avoid increasing the complexity. The designed model is end-to-end trainable. This integration provides an effective model to count crowds in both dense and sparse datasets. It also predicts an elevated quality density map with a high structural similarity index and a high peak signal-to-noise ratio. Several comprehensive experiments on four popular datasets for crowd counting have been carried out to demonstrate the proposed method’s promising performance compared to other state-of-the-art approaches. The proposed model achieves the lowest count error in terms of the MAE in ShanghaiTech Part A, Part B, and Mall datasets with 64.6, 7.5, and 1.8, respectively. Moreover, it achieves the lowest count error in terms of the MSE in ShanghaiTech Part B, UCF CC 50, UCSD, and Mall datasets with 12.4, 217.8, 2.1, 2.2, respectively. In addition, the proposed model accomplishes the best quality density maps on all the utilized datasets. Furthermore, a new dataset with its manual annotations, called Haramain with three different scenes and different densities, is introduced and used for evaluating the U-ASD Net.

Advancing disaster policies by integrating dynamic adaptive behaviour in risk assessments using an agent-based modelling approach

Recent floods in the United States and Asia again highlighted their devastating effects, and without investments in adaptation, the future impact of floods will continue to increase. Key to making accurate flood-risk projections are assessments of how disaster-risk reduction (DRR) measures reduce risk and how much risk remains after adaptation. Current flood-risk-assessment models are ill-equipped to address this, as they assume a static adaptation path, implying that vulnerability will remain constant. We present a multi-disciplinary approach that integrates different types of adaptive behaviour of governments (proactive and reactive) and households (rational and boundedly rational) in a continental-scale risk-assessment framework for river flooding in the European Union. Our methodology demonstrates how flood risk and adaptation might develop, indicates how DRR policies can steer decisions towards optimal behaviour, and indicates how much residual risk remains that has to be covered by risk-transfer mechanisms. We find that the increase in flood risk due to climate change may be largely offset by adaptation decisions. Moreover, we illustrate that adaptation by households may be more influential for risk reduction than government protection in the short term. The results highlight the importance of integrating behavioural methods from social sciences with quantitative models from the natural sciences, as advocated by both fields.

Spatial Noise-Field Control With Online Secondary Path Modeling: A Wave-Domain Approach

Due to strong interchannel interference in multichannel active noise control (ANC), there are fundamental problems associated with the filter adaptation and online secondary path modeling remains a major challenge. This paper proposes a wave-domain adaptation algorithm for multichannel ANC with online secondary path modelling to cancel tonal noise over an extended region of two-dimensional plane in a reverberant room. The design is based on exploiting the diagonal-dominance property of the secondary path in the wave domain. The proposed wave-domain secondary path model is applicable to both concentric and nonconcentric circular loudspeakers and microphone array placement, and is also robust against array positioning errors. Normalized least mean squares-type algorithms are adopted for adaptive feedback control. Computational complexity is analyzed and compared with the conventional time-domain and frequency-domain multichannel ANCs. Through simulation-based verification in comparison with existing methods, the proposed algorithm demonstrates more efficient adaptation with low-level auxiliary noise.

The direction of protein evolution is destined by the stability

Protein evolution is potentially governed by protein stability. Here, we investigated the relationship between protein evolution and stability through the random mutational drift of a thermophilic bacterial protein, an esterase of Alicyclobacillus acidocaldarius (Aac-Est), at high and low temperatures. In the first random mutation of Aac-Est, few proteins exhibit increased activity at 65 °C, indicating that the wild-type (WT) Aac-Est is located on the peak of a mountain in a fitness landscape for activity at high temperature. To obtain higher active variants than those of WT, it must go down the mountain once and climb another, higher mountain. In the second and third generations from lower active templates, the evolvability (the proportion of variants with higher activity in all the variants obtained in a given generation than a parent protein) depended on the stability of the template proteins. Compared to WT, the stability-maintaining template could recover the activity more. Thus, a low-activity variant with high stability is able to drift vastly in sequence space and reach the foot of a higher mountain. Meanwhile, random mutations in stability-loss templates produced several variants with higher activity at 40 °C than those produced by WT, via cold adaptation. Our results indicate that maintaining protein stability enables the protein to search sequence space and evolve in the original environment, and proteins with lost stability use a cold adaptation path.

School Adaptation and Career Path

School Adaptation and Career Path

Adaptive Planning for Resilient Coastal Waterfronts

Adaptive Planning for Resilient Coastal Waterfronts

Adaptive Planning for Resilient Coastal Waterfronts

Adaptive Planning for Resilient Coastal Waterfronts

A rapidly converging filtered‐error algorithm for multichannel active noise control

AbstractIn this paper, a multichannel adaptive control algorithm is described which has good convergence properties while having relatively small computational complexity. This complexity is similar to that of the filtered‐error algorithm. In order to obtain these properties, the algorithm is based on a preprocessing step for the actuator signals using a stable and causal inverse of the minimum‐phase part of the transfer path between actuators and error sensors, the secondary path. The latter algorithm is known from the literature as postconditioned filtered‐error algorithm, which improves convergence rate for the case that the minimum‐phase part of the secondary path increases the eigenvalue spread. However, the convergence rate of this algorithm suffers from delays in the adaptation path because adaptation rates have to be reduced for larger delays. The contribution of this paper is to modify the postconditioned filtered‐error scheme in such a way that the adaptation rate can be set to a higher value. Consequently, the scheme also provides good convergence if the system contains significant delays. Furthermore, a regularized extension of the scheme is given which can be used to limit the actuator signals. Copyright © 2006 John Wiley & Sons, Ltd.

The Role of Recreational Sport in the Adaptation of First Generation Immigrants in the United States

The aim of the study was to analyze immigration-related changes in recreational sport participation of Korean and Polish immigrants and to establish the role of recreational sport in their adaptation to the new life in United States. Thirty semi-structured in-depth interviews were conducted with first and one and a half generation immigrants from Korea and Poland residing in metro Chicago and Urbana-Champaign areas. The findings of this study show that the majority of interviewed immigrants experienced low levels of recreational sport participation during the first post-settlement period. The social class and ethnic background of immigrants, however, heavily influenced subsequent changes in their sport participation. The study also determined that the interviewed immigrants followed three distinct paths in the adaptation process. They either (1) acculturated to the culture of the White American mainstream; (2) assimilated to the sub-culture of their own ethnic community; (3) preserved their ethnic values and promoted their ethnic group solidarity. The adaptation path chosen was dependant on immigrants' ethnic group, and their socio-economic status.

Active noise and vibration cancellation system

An active noise and vibration control system (20) for cancellation of noise or vibration. The system (20) provides a system whereby the adaptation path and feedforward path are implemented in separate hardware. As a result, the computational burden on the digital signal processor (DSP) (28) is reduced allowing the DSP (28) to handle multiple inputs (22), error sensors (34), and transducers (32). In one embodiment, the processing of the input signal from sensor (22) takes place in a waveform generator (24) comprising a phase-locked loop, a frequency divider, a shift register, and at least one switched capacitor filter. In another embodiment the input signal processing takes place in separate feedforward circuitry including a field programmable gate array (64).

Adaptation behavior of a feedforward amplifier linearizer

Feedforward linearization has advantages in bandwidth and generality over other linearization methods. However, it is based on the subtraction of nearly equal quantities, so its major parameters must adapt to changes in environmental or operating conditions. This paper is the first published analysis of adaptation behavior in feedforward amplifier linearizers. As such, it presents an analytical framework and several new results, including convergence time and coefficient jitter, a bias effect that leads to extreme accuracy requirements in one coefficient, the effect of delay mismatch, and the mitigating effects of a filter inserted in one adaptation path.