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Constructing a low-carbon agriculture (LCA) park is considered an effective means to reduce greenhouse gas (GHG) emissions in developing countries. This study aims to explore the effectiveness of integrated low-carbon agricultural technologies based on evidence from a pilot LCA experiment in Shanghai, China, from 2008 to 2011.

Integrated low-carbon technologies in an agricultural park were adopted to reduce GHG emissions. Reduced emissions and net economic benefits were calculated by comparing emissions before and after the implementation of the experiment.

Results show that the low-carbon agricultural park experiment markedly reduced GHG emissions. This outcome can be attributed to the integrated technologies adopted in the experiment, including the reuse and recycle of resources, control of environmental pollution and GHG emissions and improvement of economic efficiency and social benefit. All the technologies adopted are already available and mature, thus indicating the great potential of LCA to reduce GHG emissions despite the lack of advanced technologies. However, supporting policies may be necessary to motivate private interests in LCA because of the considerable starting investments.

Previous macro-level and policy studies on LCA are based on knowledge from experimental studies, which typically specify environmental conditions to explore solely the effects of one low-carbon technology. Practically, integrating several low-carbon technologies in one experiment may be more effective, particularly for extensive agriculture, in developing countries. The effectiveness of integrated technologies is insufficiently discussed in the literature. Therefore, this study explores how effective integrated feasible LCA technologies can be in terms of both emission reduction and economic benefits based on the data obtained from an experiment in Shanghai, China.

This study aims to identify the current state of the art and the gaps in the application of computable general equilibrium (CGE) models on studying climate change adaptation.

A systematic review is conducted to select, classify and analyze relevant studies from two databases of Web of Science and Scopus.

Totally, 170 articles based on selected keywords were found from both databases, where 56 articles were duplicates. The authors further excluded 17 articles owing to preliminary exclusion criteria. Hence, 97 papers were selected for full-text review and more detailed assessment. Only a few of the studies explicitly have addressed the role of autonomous adaptation embodied in the CGE models. Over one-third of the studies have focused on planned adaptation without explicitly mentioning autonomous adaptation. Agriculture was the most addressed sector, and country-level models are the most adopted. Only one article has focused on South America.

The review suggests that autonomous adaptation embodied in CGE models was not well addressed in the literature. As the limited studies have shown that autonomous adaptation can dramatically mitigate direct climate change impacts, further studies are needed to examine the importance of the autonomous adaptation for better understanding of climate change impacts. Furthermore, CGE models can provide a joint assessment considering both mitigation and adaptation strategies and management measures as such models have also been widely used to address effects of mitigation measures in the literature.

The studies on climate change adaptation based on CGE models have been systematically reviewed, and state-of-the-art knowledge and research gaps have been identified.

The purpose of this paper is to design and implement new tracking and summarization algorithms for Chinese news content. Based on the proposed methods and algorithms, the authors extract the important sentences that are contained in topic stories and list those sentences according to timestamp order to ensure ease of understanding and to visualize multiple news stories on a single screen.

This paper encompasses an investigational approach that implements a new Dynamic Centroid Summarization algorithm in addition to a Term Frequency (TF)-Density algorithm to empirically compute three target parameters, i.e., recall, precision, and F-measure.

The proposed TF-Density algorithm is implemented and compared with the well-known algorithms Term Frequency-Inverse Word Frequency (TF-IWF) and Term Frequency-Inverse Document Frequency (TF-IDF). Three test data sets are configured from Chinese news web sites for use during the investigation, and two important findings are obtained that help the authors provide more precision and efficiency when recognizing the important words in the text. First, the authors evaluate three topic tracking algorithms, i.e., TF-Density, TF-IDF, and TF-IWF, with the said target parameters and find that the recall, precision, and F-measure of the proposed TF-Density algorithm is better than those of the TF-IWF and TF-IDF algorithms. In the context of the second finding, the authors implement a blind test approach to obtain the results of topic summarizations and find that the proposed Dynamic Centroid Summarization process can more accurately select topic sentences than the LexRank process.

The results show that the tracking and summarization algorithms for news topics can provide more precise and convenient results for users tracking the news. The analysis and implications are limited to Chinese news content from Chinese news web sites such as Apple Library, UDN, and well-known portals like Yahoo and Google.

The research provides an empirical analysis of Chinese news content through the proposed TF-Density and Dynamic Centroid Summarization algorithms. It focusses on improving the means of summarizing a set of news stories to appear for browsing on a single screen and carries implications for innovative word measurements in practice.

The purpose of this paper is to investigate the relationship among intellectual capital (IC), financial capital (FC), firm value (V), and value creation (VC) in different business cycles (BC) for the conduct of strategic management that will maintain stable values and further increase V.

This research cites ICs as “other information” to combine ICs and the Ohlson model. Information provided by various capitals is validated by multiple regression analysis. Multi-group analysis is performed to test whether the coefficient is moderated by BC.

Results indicate the significant information of ICs and FC, and the contingency perspective of BC. The value relevance of ICs is moderated by BC. Prosperity has more explanatory capacities, and recession ICs yield more incremental information.

VC is influenced by both ICs and FC. Besides, the macroeconomic situation should also be considered in strategic management and VC management.

In addition to ICs and FC, the macroeconomic situation must be taken into account when conducting strategic management, valuation management, investment decision, or industrial policy.

Results indicate a contingency of BC, which can be a reference for enterprises to create higher V, for investors to make appropriate investment, as well as for governments to formulate sound industrial policies.

This paper applies BC to explore the value relevance of ICs and FC, leverages two models to represent V and VC, and cites complete four aspects of IC as “other information” to combine ICs and Ohlson model.

The purpose of this paper is to compare the performance of commonly used value at risk (VaR) estimation methods for equity indices from both developed countries and emerging markets.

In addition to traditional time‐series models, this paper examines the recently developed nonparametric kernel estimator (KE) approach to predicting VaR. KE methods model tail behaviors directly and independently of the overall return distribution, so are better able to take into account recent extreme shocks.

The paper compares the performance and reliability of five major VaR methodologies, using more than 26 years of return data on 37 equity indices. Through back‐testing of the resulting models on a moving window and likelihood ratio tests, it shows that KE models produce remarkably good VaR estimates and outperform the other common methods.

Financial assets are known to have irregular return patterns; not only the volatility but also the distributions themselves vary over time. This analysis demonstrates that a nonparametric approach (the KE method) can generate reliable VaR estimates and accurately capture the downside risk.

The paper evaluates the performance of several common VaR estimation approaches using a comprehensive sample of empirical data. The paper also reveals that kernel estimation methods can achieve remarkably reliable VaR forecasts. A detailed and complete investigation of nonparametric estimation methods will therefore significantly contribute to the understanding of the VaR estimation processes.

In the present paper, the authors aim to analyze the non‐Newtonian effects of Rabinowitsch fluids on the squeeze film performances between wide parallel rectangular plates.

Based on the cubic‐stress equation model, a nonlinear squeeze‐film Reynolds‐type equation has been derived. By using a small perturbation method, a closed‐form solution of the squeeze film characteristics is derived for the parallel plates considering the non‐Newtonian effects of cubic stresses.

Comparing with the Newtonian‐lubricant parallel plates, the effects of non‐Newtonian cubic‐stress flow rheology provide significant influences upon the squeeze film characteristics.

It is shown that the non‐Newtonian pseudoplastic behavior reduces the load capacity and the response time; however, the effects of non‐Newtonian dilatant lubricant provide an increase in the load‐carrying capacity and therefore lengthen the response time of parallel squeeze‐film plates.

This study aims to investigate the relationship between structural damage and sensitivity indices using the Hilbert‐Huang transform (HHT) method.

The relationship between structural damage and the sensitivity indices is obtained by using the HHT method. Three sensitivity indices are proposed: the ratio of rotation (RR), the ratio of shifting value (SV) and the ratio of bandwidth (RB). The nonlinear single degree of freedom and multiple degree of freedom models with various predominant frequencies are constructed using the SAP2000 program. Adjusted PGA El Centro and Chi‐Chi (TCU068) earthquake data are used as the excitations. Next, the sensitivity indices obtained using the HHT and the fast Fourier transform (FFT) methods are evaluated separately based on the acceleration responses of the roof structures to earthquakes.

Simulation results indicate that, when RR < 1, the structural response is in the elastic region, and neither the RB nor SV in the HHT and FFT spectra change. When the structural response is nonlinear, i.e. RR1, a positive trend of change occurs in RB and RR, while in the HHT spectra, SV increases with an increasing RR. Moreover, the FFT spectra reveal that SV changes only when the RR is sufficiently large. No steady relationship between the RB and the RR can be found.

The paper demonstrates the effectiveness of the HHT method.

The purpose of this paper is to propose a new framework and improve a bi-directional people counting technique using an RGB-D camera to obtain accurate results with fast computation time. Therefore, it can be used in real-time applications.

First, image calibration is proposed to obtain the ratio and shift values between the depth and the RGB image. In the depth image, a person is detected as foreground by removing the background. Then, the region of interest (ROI) of the detected people is registered based on their location and mapped to an RGB image. Registered people are tracked in RGB images based on the channel and spatial reliability. Finally, people were counted when they crossed the line of interest (LOI) and their displacement distance was more than 2 m.

It was found that the proposed people counting method achieves high accuracy with fast computation time to be used in PCs and embedded systems. The precision rate is 99% with a computation time of 35 frames per second (fps) using a PC and 18 fps using the NVIDIA Jetson TX2.

The precision rate is 99% with a computation time of 35 frames per second (fps) using a PC and 18 fps using the NVIDIA Jetson TX2.

The proposed method can count the number of people entering and exiting a room at the same time. If the previous systems were limited to only one to two people in a frame, this system can count many people in a frame. In addition, this system can handle some problems in people counting, such as people who are blocked by others, people moving in another direction suddenly, and people who are standing still.

This study aims to examine the effects of the proposed mobile Web library application (MWLA) on the search experience and its impact on learners’ engagement, interaction and overall learning outcomes within an institutional repository. Furthermore, the study investigates learners’ acceptance of the MWLA system.

The study suggests implementing an MWLA with Algolia’s search service to improve the institutional repository and enhance learners’ access to reliable information. It involved an experiment with 85 undergraduate students divided into experimental and control groups (CGs), where the experimental group (EG) used MWLA for search tasks, and the CG used the traditional library website. The study evaluated the acceptance and learning behaviours of the EG towards MWLA, considering factors such as usefulness, ease of use, mobility, accessibility, satisfaction and intention to use.

The findings of this study provide empirical evidence that the EG, which used the MWLA, demonstrated superior performance compared to the CG across all institutional repository collections, resulting in improved learning outcomes. Participants were highly satisfied with MWLA and found it user-friendly and beneficial for improving search skills. MWLA’s portability and accessibility motivated active learner engagement.

The powerful search bar of MWLA significantly enhanced learners’ search efficiency, resulting in more effective retrieval of relevant materials. Moreover, learners who actively engaged with previews and full-text content, using appropriate keywords and syntax, achieved higher scores and were more likely to access previews, abstracts and full texts of documents using the sorting-by-year or by-advisor feature.

By inspecting the special connection between negligence and the causes of negligence, this study evaluates the reasonableness of negligence offenses elements from the perspectives of “modes” and “rules.” This study considers that in the core concept of negligent manslaughter in the Criminal Code of Taiwan, “business” comprises an outstretched legal element; thus, “application by analogy” or “customary laws” should be prohibited as a legal basis or when applying the criminal code because those are not allowed under nulla poena sine lege. Nulla poena sine lege must be respected to release construction professionals from material risks in their judicial rights and interests.

This study used data mining analysis with a database of 204 cases where construction professionals were involved in an accusation of gross negligence manslaughter (GNM) (N = 486) between 1995 and 2021 to explore the reasons and distribution of these cases in the construction industry in Taiwan.

The results showed that the main reasons behind lawful GNM accusations against construction professionals are as follows: (1) the violation of employers' duty of care to prevent hazards caused in workplaces where falling and collapsing are concerns during construction, thus resulting in death; (2) gross negligence during design, construction and supervision, causing damages after natural disasters such as earthquakes and typhoons.

This study discusses the whole life circle of construction, starting from planning, design, construction and completion. However, the involvement of other offenses such as providing false statements, forgery, embezzlement, unjust enrichment and fraudulent tax evasion or criminal responsibilities stipulated in the Building Act or administrative punishments are beyond the scope of this study. Future studies will focus on foreign “business GNM” cases from judicial precedents with similar backgrounds to Taiwan in the construction industry to verify whether similar conclusions can be drawn and to examine their differences.

This study applied data mining and data analysis to the data and explored potential causality and patterns of GNM cases in judicial cases. The results of the analyses can be used as evidence for potential causality and thus facilitate construction professionals' self-reflection and contribute to the sustainable development of working environments for construction.

This study agrees with the removal of GNM titled “business” in the Criminal Code of Taiwan to achieve Sustainable Development Goals (SDGs) in the building industry. By doing so, national judicial and management systems will be in line with international standards, ensuring that everyone has equal access to justice.

Goal 16 of the SDGs by the United Nations aims to promote judicial equality, peace, justice and strong institutions. With this basis, this study collected and analyzed data in the field of criminal law and applied the theory of criminal offenses committed by negligence to real construction-related cases. This study especially discusses whether construction professionals were imposed with excessive responsibilities when a court enforced the “duty of care” that asked the professionals to bear the responsibility of results for events that should be and could be foreseen.