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In the brain imaging based on electrical impedance tomography, it is sometimes not able to attach 16 electrodes due to space restriction caused by craniotomy. As a result of this, the number of boundary measurements decreases, and spatial resolution of reconstructed conductivity distribution is reduced. The purpose of this study is to enhance reconstruction quality in cases of limited measurement.

A new data expansion method based on the shallow convolutional neural network is proposed. An eight-electrode model is built from which fewer boundary measurements can be obtained. To improve the imaging quality, shallow convolutional neural network is constructed which maps limited voltage data of the 8-electrode model to expanded voltage data of a quasi-16-electrode model. The predicted data is compared with the quasi-16-electrode data. Besides, image reconstruction based on L1 regularization method is conducted.

The results show that the predicted data generally coincides with the quasi-16-electrode data. It is found that images reconstructed with the data of eight-electrode model are the poorest. Nevertheless, imaging results when the limited data is expanded by the proposed method show large improvement, and there is a minor difference with the images recovered with the quasi-16-electrode data. Also, the impact of noise is studied, which shows that the proposed method is robust to noise.

To enhance reconstruction quality in the case of limited measurement, a new data expansion method based on the shallow convolutional neural network is proposed. Both simulation work and phantom experiments have demonstrated that high-quality images of cerebral hemorrhage and cerebral ischemia can be obtained when the limited measurement is expanded by the proposed method.

Financial communication refers to the strategies and practices employed by companies to share financial information and engage with investors, stakeholders and the broader financial community. At its core lies investor relations management (IRM), focused on achieving effective two-way communication between the company and these groups for fair valuation of securities. Key financial communication activities include investor meetings, earnings calls, roadshows, annual reports, market analysis and crisis communication. Moreover. stakeholder theory emphasizes identifying and managing relationships with all individuals and entities that can affect or be affected by the company's operations. Stakeholders include shareholders, employees, creditors, suppliers, communities, regulators etc., classified as primary (essential) or secondary (indirectly involved). Proactive stakeholder engagement is crucial for achieving corporate objectives. Additionally, investor relations (IR) specifically deal with managing interactions with shareholders, creditors and potential investors through information dissemination, utilizing finance, marketing and communication techniques. Implementation channels include regulated disclosures, shareholder meetings, media engagement and forums. Other covered aspects include crisis communication strategies, corporate reputation management, internal communication practices, transparency and disclosure guidelines and legal/ethical considerations surrounding corporate communication. Overall, robust financial communication capabilities are vital for corporate success, reputation building and sustainable growth in today's competitive landscape.

To ensure the reliable and safe operation of elevated-temperature pipes and equipment in the long term, it is essential to thoroughly assess the creep rupture life. Nevertheless, there is currently no design code that specifies a creep rupture life evaluation method for non-nuclear elevated-temperature equipment. The paper aims to discuss this issue.

An analysis was conducted to compare the differences and conservativeness in calculating creep strain using three major codes (ASME-CC-2843, API-579 and BS-7910) based on the results of the 316H creep constitutive model and creep strain prediction. In addition, the creep resistances of 316H, 304H and 347H were compared. Subsequently, the ANSYS Usercreep subroutine was developed to compare the discrepancies between different codes under multiaxial stress conditions using numerical simulations.

BS-7910 employs the Norton creep model with calculation parameters for the average creep strain rate, which is not applicable for the engineering design stage. ASME-CC2843 code primarily focuses on the primary and secondary creep stages, making it more suitable for non-nuclear pipeline and equipment design. For 316H, the creep strain curves predicted by ASME-CC2843 and API-579 typically intersect at a specific point. By combining the creep strain predicted by ASME-CC2843 and API-579, 347H exhibits superior predicted creep resistance compared to 316H, whereas 316H exhibited better predicted creep resistance than 304H.

This study provides a guide for future evaluation methods and material choices for non-nuclear equipment and pipelines operating at elevated temperatures.

The construction industry has been investigating “where Henry Ford is in the industry system.” Given that listed construction enterprises are the backbone of the promotion of the high-quality development of the industry, their research and innovation are of considerable importance. This study aims to comprehensively assess the research and development (R&D) status quo and trends within various types of construction enterprises in order to identify effective strategies to enhance R&D efficiency in the construction industry.

Based on the data won from annual reports and the CSMAR database for the period 2016–2020, this study examines 104 listed construction enterprises in China. By applying both the data envelopment analysis (DEA) method and the Malmquist productivity index, this research compares and analyzes the static and dynamic differences in R&D efficiency across different types of construction enterprises.

Results suggest that the magnitude of change in the Malmquist decomposition index of 104 listed construction enterprises gradually narrowed, but the comprehensive technological level remained relatively low. Although state-owned enterprises had an advantage in scale efficiency, meaning they could maximize output with given inputs, their technological progress efficiency, also known as the degree of technological innovation, was significantly lower than that of private enterprises. As one finding, state-owned enterprises in comparison with private enterprises experience significant R&D inefficiency. It represents the main cause of their low degree of technological innovation and efficiency.

This study assesses the R&D efficiency of listed construction enterprises in China from the perspective of different market segments, state-owned and private enterprises and suggests approaches to improve strategies for various corporate types. Thus, the study’s new findings contribute to addressing the challenge of low R&D levels in the construction industry in the fields of engineering, construction and architectural management.

To ensure the stable operation of ironmaking process and the quality and output of sinter, the multi-objective optimization of sintering machine batching process was carried out.

The purpose of this study is to establish a multi-objective optimization model with iron taste content and batch cost as targets, constrained by field process requirements and sinter quality standards, and to propose an improved balance optimizer algorithm (LILCEO) based on a lens imaging anti-learning mechanism and a population redundancy error correction mechanism. In this method, the lens imaging inverse learning strategy is introduced to initialize the population, improve the population diversity in the early iteration period, avoid falling into local optimal in the late iteration period and improve the population redundancy error correction mechanism to accelerate the convergence rate in the early iteration period.

By selecting nine standard test functions of BT series for simulation experiments, and comparing with NSGA-?, MOEAD, EO, LMOCSO, NMPSO and other mainstream optimization algorithms, the experimental results verify the superior performance of the improved algorithm. The results show that the algorithm can effectively reduce the cost of sintering ingredients while ensuring the iron taste of sinter, which is of great significance for the comprehensive utilization and quality assurance of sinter iron ore resources.

An optimization model with dual objectives of TFe content and raw material cost was developed taking into account the chemical composition and quality indicators required by the blast furnace as well as factors such as raw material inventory and cost constraints. This model was used to adjust and optimize the sintering raw material ratio. Addressing the limitations of existing optimization algorithms for sintering raw materials including low convergence accuracy slow speed limited initial solution production and difficulty in practical application we proposed the LILCEO algorithm. Comparative tests with NSGA-III MOEAD EO LMOCSO and NMPSO algorithms demonstrated the superiority of the proposed algorithm. Practical applications showed that the proposed method effectively overcomes many limitations of the current manual raw material ratio model providing scientific and stable decision-making guidance for sintering production operations.

This paper explores the association between directors’ and officers’ liability insurance (D&O insurance) and management tone manipulation.

This study uses data from A-share listed non-financial companies from 2009 to 2021 as its sample for empirical tests. In addition, the study relies on text analysis and the construction of models to investigate the relationship between D&O insurance and management tone manipulation.

The authors find that the purchase of D&O insurance will lead to management tone manipulation in the “management discussion and analysis” part of companies’ annual reports, and operating risk and agent cost are the two paths for the effect. Further analysis shows that having a male CEO and employing high-quality auditors can weaken the positive impact of D&O insurance on tone manipulation.

This paper provides a new approach for studying the literature related to D&O insurance and management behavior, and the findings enrich our understanding of the influencing factors and the mechanism of management tone manipulation, thus revealing policy implications for further standardization of the terms and system of D&O insurance in China.

The phenomenon of friction and wear in parallel groove clamps under wind vibration in 10 kV distribution networks represents a significant challenge that can lead to their failure. This study aims to elucidate the wear mechanism of parallel groove clamps under wind-induced vibration through simulation and experimentation.

FLUENT software was used to simulate the flow around the conductor and the parallel groove fixture, and the Karman vortex street phenomenon was discussed. The stress fluctuations of each component under breeze vibration conditions were investigated using ANSYS, and fretting experimentations were conducted at varying amplitudes.

The results demonstrate that the impact of breeze vibration on the internal stress of the parallel groove clamps is considerable. The maximum stress observed on the lower clamping block was found to be up to 300 MPa. As wind speed increased, the maximum vibration frequency was observed to reach 72.6 Hz. Concurrently, as the vibration amplitude increased, the damage in the contact zone of the lower clamping block also increased, with the maximum contact resistance reaching 78.0 µO at a vibration amplitude of 1.2 mm. This was accompanied by a shift in the wear mechanism from adhesive wear to oxidative wear and fatigue wear.

This study presents a comprehensive analysis of the fretting wear phenomenon associated with parallel groove clamps under wind vibration. The findings provide a reference basis for the design and protection of parallel groove clamps.

This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.

Few studies only focus on halal cosmetics, although several previous studies have examined halal food and beverages. This study aims to explore the relationship between knowledge, emotional attachment and religiosity on purchase intention, mediated by satisfaction and brand trust. This study stems from the theory of reasoned action (TRA), which merges the knowledge, emotional attachment, religiosity and purchase intention of halal cosmetics.

The researchers distributed online questionnaires to respondents via Google Form using social media (Instagram)/messaging application (WhatsApp). The respondents were Indonesian and Malaysian millennial Muslims. The sampling technique used was purposive sampling. A total of 528 respondents were involved, consisting of 335 Indonesians and 193 Malaysians. However, data for 381 respondents were successfully screened for normality, outliers and multicollinearity. Furthermore, the data was used for examining the hypotheses proposed.

The results for Indonesian and Malaysian samples showed that there is a significant positive effect of knowledge, emotional attachments and religiosity on satisfaction and brand trust. But the Indonesia sample showed that there is no significant effect of religiosity on satisfaction. For Indonesia, there is a positive significant mediating role of satisfaction on purchasing intention. For Malaysia, there is no significant mediating role of satisfaction on purchasing intention. For Indonesia and Malaysia, there are positive significant mediating role of brand trust on purchasing intention.

The study compared consumers of the millennial generation in Indonesia and Malaysia with limited samples. For future research, it is suggested to exploring and combining non-Muslims and Muslims in the millennial generation and testing it in more than two countries.

The study provides an accurate understanding of the relationships proposed, such as knowledge, emotional attachment and religiosity, on satisfaction, brand trust and purchasing intention of millennial Muslim woman consumers in Indonesia and Malaysia, because the millennial Muslim woman consumers in Indonesia and Malaysia had the same behavioral characteristics: Muslim consumers and product characteristics.

The study of halal cosmetics can provide a spiritual commitment for Muslims, who consciously prefer socio-religious values in choosing cosmetic products. Therefore, the halal label of the product is also a reason for social and religious values to increase the social awareness of the Muslim millennial generation in Malaysia and Indonesia.

This research discusses the antecedents and consequences of satisfaction and brand trust on the purchasing intention of halal cosmetics. The response of Muslim consumers to halal cosmetics has not been widely studied in Indonesia and Malaysia. Meanwhile, in Indonesia, the halal label on all products has recently been made mandatory by the Indonesian Ulema Council. Therefore, this research offers insights into the attitudes of Muslim consumers towards halal cosmetics products.

The purpose of this research is to enhance the Laser Powder Bed Fusion (LPBF) additive manufacturing technique by addressing its susceptibility to defects, specifically lack of fusion. The primary goal is to optimize the LPBF process using a digital twin (DT) approach, integrating physics-based modeling and machine learning to predict the lack of fusion.

This research uses finite element modeling to simulate the physics of LPBF for an AISI 316L stainless steel alloy. Various process parameters are systematically varied to generate a comprehensive data set that captures the relationship between factors such as power and scan speed and the quality of fusion. A novel DT architecture is proposed, combining a classification model (recurrent neural network) with reinforcement learning. This DT model leverages real-time sensor data to predict the lack of fusion and adjusts process parameters through the reinforcement learning system, ensuring the system remains within a controllable zone.

This study's findings reveal that the proposed DT approach successfully predicts and mitigates the lack of fusion in the LPBF process. By using a combination of physics-based modeling and machine learning, the research establishes an efficient framework for optimizing fusion in metal LPBF processes. The DT's ability to adapt and control parameters in real time, guided by machine learning predictions, provides a promising solution to the challenges associated with lack of fusion, potentially overcoming the traditional and costly trial-and-error experimental approach.

Originality lies in the development of a novel DT architecture that integrates physics-based modeling with machine learning techniques, specifically a recurrent neural network and reinforcement learning.