As artificial intelligence grows, human–robot collaboration becomes more common for efficient task completion. Effective communication between humans and AI-assisted robots is crucial for maximizing collaboration potential. This study explores human–robot interactions, focusing on the differing mental models used by humans and collaborative robots. Humans communicate using knowledge, skills, and emotions, while robotic systems rely on algorithms and technology. This communication disparity can hinder productivity. Integrating emotional intelligence with cognitive intelligence is key for successful collaboration. To address this, a communication model tailored for human–robot teams is proposed, incorporating robots’ observation of human emotions to optimize workload allocation. The model’s efficacy is demonstrated through a case study in an SAP system. By enhancing understanding and proposing practical solutions, this study contributes to optimizing teamwork between humans and AI-assisted robots.

The utilization of creative design methodologies plays a pivotal role in nurturing innovation within the contemporary competitive market landscape. Although Theory of Inventive Problem Solving (TRIZ) has been recognized as a potent methodology for engendering innovative concepts, its intricate nature and time-consuming learning and application processes pose significant challenges. Furthermore, TRIZ has faced criticism for its limitations in processing design problems and facilitating designers in knowledge acquisition. Conversely, Environment-Based Design (EBD), a question-driven design methodology, provides robust methods and approaches for formulating design problems and identifying design conflicts. Large Language Models (LLMs) have also demonstrated the ability to streamline the design process and enhance design productivity. This study aims to propose an iteration of TRIZ integrated by EBD and supported by an LLM. This LLM-based conceptual design model assists designers through the conceptual design process. It begins by using question-asking and answering methods from EBD to gather relevant information. It then follows the EBD methodology to formulate the information into an interaction-dependence network, leading to the identification of functions and conflicts required by TRIZ. Lastly, TRIZ is used to generate inventive solutions. An evaluation is carried out to measure the effectiveness of the integrated approach. The results indicate that this approach successfully generates questions, processes designers’ responses, produces functional analysis elements, and generates ideas to resolve contradictions.

Language control in the bilingual brain has remained in the limelight of research over the past decades. However, the mechanisms underlying bilingual language control may be more intricate than typically assumed due to the hierarchical nature of language. This study aimed to investigate the dynamics of bilingual language control at the phonetic level. Participants, who were speakers of Chinese, English and German, named the letters of the alphabet in English (L2) or German (L3) following an alternating language-switching paradigm. Two sets of letters were selected, differing in the phonological similarity of their pronunciation across the two languages, thereby allowing the exploration of cross-language phonological influences. Each participant completed two sessions of letter-naming tasks. In one session, seven phonologically similar letters were randomly repeated either in single-language blocks or in alternate-language blocks. In the other session, seven phonologically dissimilar letters were similarly manipulated. The results indicated local inhibition, reflected by switch costs and global inhibition, reflected by mixing costs. Reversed language dominance, another indicator of global inhibition, was not observed. However, there was a tendency for larger global inhibition to be applied to the more dominant language. Moreover, there was significantly faster naming for phonologically similar letters compared to dissimilar ones, suggesting a facilitation effect for both English and German, irrespective of whether letter naming occurred in single- or alternate-language blocks. These findings provided evidence for the role of inhibitory and facilitative mechanisms at the phonetic level, suggesting language-specific control in the bilingual brain and underscoring the complexity and dynamics of managing language control across multiple levels of processing.

External seeded free-electron lasers (FELs) have exhibited substantial progress in diverse applications over the last decade. However, the frequency up-conversion efficiency in single-stage seeded FELs, particularly in high-gain harmonic generation (HGHG), remains constrained to a modest level. This limitation restricts its capability to conduct experiments within the ‘water window’. This paper presents a novel method for generating coherent X-ray FEL pulses in the water window region based on the HGHG scheme with multi-stage harmonic cascade. Without any additional modifications to the HGHG configuration, simulation results demonstrate the generation of intense 3 nm coherent FEL radiation using an external ultraviolet seed laser. This indicates an increase of the harmonic conversion number to approximately 90. A preliminary experiment is performed to evaluate the feasibility of this method. The proposed approach could potentially serve as an efficient method to broaden the wavelength coverage accessible to both existing and planned seeded X-ray FEL facilities.

Previous studies have found that media coverage of a firm's corporate social irresponsibility (CSiR) often delays or blocks the completion of a cross-border acquisition when the acquiror is a multinational enterprise (MNE) from an emerging market. Drawing from the attention-based view, we argue that the effects of Chinese MNEs’ CSiR on deal completion vary depending on several contextual factors, as these factors garner more attention by making the deals more salient to stakeholders. Using a sample of cross-border acquisitions by Chinese MNEs from 2013 to 2020, we find that CSiR media coverage per se does not decrease the likelihood of a deal's completion. However, consistent with attention-based arguments, we find that CSiR media coverage negatively affects the deal's completion when the acquirors are state-owned enterprises and when the target country has high institutional quality. Our findings enhance our understanding of the effects of CSiR on cross-border acquisitions by highlighting the moderating roles of contextual factors related to stakeholder attention. Thus, it is important for MNEs to recognize the boundary conditions that may influence the potential sanctions from local stakeholders. Based on these findings, this study contributes to the literature on CSiR, cross-border acquisitions, and stakeholder attention.

Design is a highly nonlinear chaotic dynamic process with many possible solutions, which requires enormous knowledge for designers. This paper investigates how environment-based design (EBD) methodology can help designers use only necessary knowledge for their creativity based on three methods: information search, knowledge acquisition and knowledge application. The methods are applied in an aircraft pylon design, which is evaluated by two aerospace design specialists. The paper discussed the different roles of EBD for novice and expert designers in regard to overcoming emotion and knowledge barriers to achieving designer creativity.

The association between time-restricted eating (TRE) and the risk of non-alcoholic fatty liver disease (NAFLD) is less studied. Moreover, whether the association is independent of physical exercise or diet quality or quantity is uncertain. In this nationwide cross-sectional study of 3813 participants, the timing of food intakes was recorded by 24-h recalls; NAFLD was defined through vibration-controlled transient elastography in the absence of other causes of chronic liver disease. OR and 95 % CI were estimated using logistic regression. Participants with daily eating window of ≤ 8 h had lower odds of NAFLD (OR = 0·70, 95 % CI: 0·52, 0·93), compared with those with ≥ 10 h window. Early (05.00–15.00) and late TRE (11.00–21.00) showed inverse associations with NAFLD prevalence without statistical heterogeneity (Pheterogeneity = 0·649) with OR of 0·73 (95 % CI: 0·36, 1·47) and 0·61 (95 % CI: 0·44, 0·84), respectively. Such inverse association seemed stronger in participants with lower energy intake (OR = 0·58, 95 % CI: 0·38, 0·89, Pinteraction = 0·020). There are no statistical differences in the TRE-NAFLD associations according to physical activity (Pinteraction = 0·390) or diet quality (Pinteraction = 0·110). TRE might be associated with lower likelihood of NAFLD. Such inverse association is independent of physical activity and diet quality and appears stronger in individuals consuming lower energy. Given the potential misclassification of TRE based on one- or two-day recall in the analysis, epidemiological studies with validated methods for measuring the habitual timing of dietary intake are warranted.

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords derived from these research questions led to 975 records initially retrieved from 7 scientific search engines. Finally, 86 articles were selected for inclusion in the review. As the primary research finding, we identified 15 ML-based requirement elicitation tasks and classified them into four categories. Twelve different data sources for building a data-driven model are identified and classified in this literature review. In addition, we categorized the techniques for constructing ML-based requirement elicitation methods into five parts, which are Data Cleansing and Preprocessing, Textual Feature Extraction, Learning, Evaluation, and Tools. More specifically, 3 categories of preprocessing methods, 3 different feature extraction strategies, 12 different families of learning methods, 2 different evaluation strategies, and various off-the-shelf publicly available tools were identified. Furthermore, we discussed the limitations of the current studies and proposed eight potential directions for future research.

Previous studies have reported inconsistent associations between low-carbohydrate diets (LCD) and plasma lipid profile. Also, there is little evidence on the role of the quality and food sources of macronutrients in LCD in cardiometabolic health. We investigated the cross-sectional associations between LCD and plasma cardiometabolic risk markers in a nationwide representative sample of the US population. Diet was measured through two 24-h recalls. Overall, healthy (emphasising unsaturated fat, plant protein and less low-quality carbohydrates) and unhealthy (emphasising saturated fat, animal protein and less high-quality carbohydrate) LCD scores were developed according to the percentage of energy as total and subtypes of carbohydrate, protein and fat. Linear regression was used to estimate the percentage difference of plasma marker concentrations by LCD scores. A total of 34 785 participants aged 18–85 years were included. After adjusting for covariates including BMI, healthy LCD was associated with lower levels of insulin, homoeostatic model assessment for insulin resistance (HOMA-IR), C-reactive protein (CRP) and TAG, and higher levels of HDL-cholesterol, with the percentage differences (comparing extreme quartile of LCD score) of −5·91, −6·16, −9·13, −9·71 and 7·60 (all Ptrend < 0·001), respectively. Conversely, unhealthy LCD was associated with higher levels of insulin, HOMA-IR, CRP and LDL-cholesterol (all Ptrend < 0·001). Our results suggest that healthy LCD may have positive, whereas unhealthy LCD may have negative impacts on CRP and metabolic and lipid profiles. These findings underscore the need to carefully consider the quality and subtypes of macronutrients in future LCD studies.

The southeastern Central Asian Orogenic Belt (CAOB) records the assembly process between several micro-continental blocks and the North China Craton (NCC), with the consumption of the Paleo-Asian Ocean (PAO), but whether the S-wards subduction of the PAO beneath the northern NCC was ongoing during Carboniferous–Permian time is still being debated. A key issue to resolve this controversy is whether the Carboniferous magmatism in the northern NCC was continental arc magmatism. The Alxa Block is the western segment of the northern NCC and contiguous to the southeastern CAOB, and their Carboniferous–Permian magmatism could have occurred in similar tectonic settings. In this contribution, new zircon U–Pb ages, elemental geochemistry and Sr–Nd isotopic analyses are presented for three early Carboniferous granitic plutons in the southwestern Alxa Block. Two newly identified aluminous A-type granites, an alkali-feldspar granite (331.6 ± 1.6 Ma) and a monzogranite (331.8 ± 1.7 Ma), exhibit juvenile and radiogenic Sr–Nd isotopic features, respectively. Although a granodiorite (326.2 ± 6.6 Ma) is characterized by high Sr/Y ratios (97.4–139.9), which is generally treated as an adikitic feature, this sample has highly radiogenic Sr–Nd isotopes and displays significantly higher K2O/Na2O ratios than typical adakites. These three granites were probably derived from the partial melting of Precambrian continental crustal sources heated by upwelling asthenosphere in lithospheric extensional setting. Regionally, both the Alxa Block and the southeastern CAOB are characterized by the formation of early Carboniferous extension-related magmatic rocks but lack coeval sedimentary deposits, suggesting a uniform lithospheric extensional setting rather than a simple continental arc.

We investigate various variable martingale Hardy spaces corresponding to variable Lebesgue spaces $\mathcal {L}_{p(\cdot )}$ defined by rearrangement functions. In particular, we show that the dual of martingale variable Hardy space $\mathcal {H}_{p(\cdot )}^{s}$ with $0<p_{-}\leq p_{+}\leq 1$ can be described as a BMO-type space and establish martingale inequalities among these martingale Hardy spaces. Furthermore, we give an application of martingale inequalities in stochastic integral with Brownian motion.

Automatic generation of high-quality meshes is a base of CAD/CAE systems. The element extraction is a major mesh generation method for its capabilities to generate high-quality meshes around the domain boundary and to control local mesh densities. However, its widespread applications have been inhibited by the difficulties in generating satisfactory meshes in the interior of a domain or even in generating a complete mesh. The element extraction method's primary challenge is to define element extraction rules for achieving high-quality meshes in both the boundary and the interior of a geometric domain with complex shapes. This paper presents a self-learning element extraction system, FreeMesh-S, that can automatically acquire robust and high-quality element extraction rules. Two central components enable the FreeMesh-S: (1) three primitive structures of element extraction rules, which are constructed according to boundary patterns of any geometric boundary shapes; (2) a novel self-learning schema, which is used to automatically define and refine the relationships between the parameters included in the element extraction rules, by combining an Advantage Actor-Critic (A2C) reinforcement learning network and a Feedforward Neural Network (FNN). The A2C network learns the mesh generation process through random mesh element extraction actions using element quality as a reward signal and produces high-quality elements over time. The FNN takes the mesh generated from the A2C as samples to train itself for the fast generation of high-quality elements. FreeMesh-S is demonstrated by its application to two-dimensional quad mesh generation. The meshing performance of FreeMesh-S is compared with three existing popular approaches on ten pre-defined domain boundaries. The experimental results show that even with much less domain knowledge required to develop the algorithm, FreeMesh-S outperforms those three approaches in essential indices. FreeMesh-S significantly reduces the time and expertise needed to create high-quality mesh generation algorithms.

Real-time localization is an important mission for self-driving cars and it is difficult to achieve precise pose information in dynamic environments. In this paper, a novel localization method is proposed to estimate the pose of self-driving cars using a 3D-LiDAR sensor. First, the multi-frame curb features and laser intensity features are extracted. Meanwhile, based on the high-precision curb map generated offline, obstacles on road are detected using region segmentation methods and their features are removed. Furthermore, a map-matching method is proposed to match the features to the map, a robust iterative closest point algorithm is utilized to deal with curb features along with a probability search method dealing with intensity features. Finally, two separate Kalman filters are used to fuse the low-cost global positioning systems and map-matching results. Both offline and online experiments are carried out in dynamic environments and the results demonstrate the accuracy and robustness of the proposed method.

The dependence of fishbone cycle on energetic particle intensity has been investigated in EAST low-magnetic-shear plasmas. It is observed that the fishbone mode growth rate, saturation amplitude as well as fishbone cycle frequency clearly increase with increasing neutral beam injection (NBI) power. Moreover, enhanced electron density and temperature perturbations as well as energetic particle loss were observed with greater injected NBI power. Simulation results using M3D-K code show that as the NBI power increases, the resonant frequency and the energy of the resonant particles become higher, and the saturation amplitude of the mode also changes, due to the non-perturbative energetic particle contribution. The relationship between the calculated energetic particle pressure ratio and fishbone cycle frequency is obtained as ${f_{\textrm{FC}}} = 2.2{(1000{\beta _{\textrm{ep,calc}}} - 0.1)^{5.9 \pm 0.5}}$. Results consistent with the experimental observations have been achieved based on a predator–prey model.

This paper proposes a task-related electroencephalogram research framework (tEEG framework) to guide scholars’ research on EEG-based cognitive and affective studies in the context of design. The proposed tEEG framework aims to investigate design activities with loosely controlled experiments and decompose a complex design process into multiple primitive cognitive activities, corresponding to which different research hypotheses on basic design activities can be effectively formulated and tested. Thereafter, existing EEG techniques and methods can be applied to analyse EEG signals related to design. Three application examples are presented at the end of this paper to demonstrate how the proposed framework can be applied to analyse design activities. The tEEG framework is presented to guide EEG-based cognitive and affective studies in the context of design. Existing methods and models are summarized, for the effective application of the tEEG framework, from the current literature spread in a wide spectrum of resources and fields.

Primary liver cancer is the third leading cause of cancer-related death worldwide. Most patients are diagnosed at late stages with poor prognosis; thus, identification of modifiable risk factors for primary prevention of liver cancer is urgently needed. The well-established risk factors of liver cancer include chronic infection with hepatitis B virus (HBV) or hepatitis C virus (HCV), heavy alcohol consumption, metabolic diseases such as obesity and diabetes, and aflatoxin exposure. However, a large proportion of cancer cases worldwide cannot be explained by current known risk factors. Dietary factors have been suspected as important, but dietary aetiology of liver cancer remains poorly understood. In this review, we summarised and evaluated the observational studies of diet including single nutrients, food and food groups, as well as dietary patterns with the risk of developing liver cancer. Although there are large knowledge gaps between diet and liver cancer risk, current epidemiological evidence supports an important role of diet in liver cancer development. For example, exposure to aflatoxin, heavy alcohol drinking and possibly dairy product (not including yogurt) intake increase, while intake of coffee, fish and tea, light-to-moderate alcohol drinking and several healthy dietary patterns (e.g. Alternative Healthy Eating Index) may decrease liver cancer risk. Future studies with large sample size and accurate diet measurement are warranted and need to consider issues such as the possible aetiological heterogeneity between liver cancer subtypes, the influence of chronic HBV or HCV infection, the high-risk populations (e.g. cirrhosis) and a potential interplay with host gut microbiota or genetic variations.

During the last glacial termination, a warming trend was generally interrupted by rapid millennium-scale cold reversals, such as the Greenland (Isotope) Stadial 1 (GS-1) and GS-2a events. To understand how glaciers on the Tibetan Plateau (TP) responded to these rapid climate events, this study constrained the timing and extent of three glacial events during the late-glacial period. Specifically, using a cosmogenic 10Be exposure dating method, we dated three prominent glacial moraines (PM1, PM2, PM3) back to 15,850 ± 980, 14,140 ± 880, and 12,430 ± 790 yr in the Pagele valley, southern TP, corresponding to GS-2a, Greenland Interstadial 1 (GI-1), and GS-1, respectively. By simulating glacial extents forced by different climate scenarios, the study constrained the temperature decreases relative to present to be 2.6°C–2.9°C, ~1.6°C, and 1.4°C–1.5°C during the GS-2a, GI-1, and GS-1 periods in the region, with precipitation values of 60%–80%, ~100%, and 80%–90% of present value, respectively. Considering information from oceanic and atmospheric circulation, the study suggested that on the TP, the glacial events during the last glacial termination were well connected with the millennium-scale climate events in the North Atlantic region through the westerlies, while the Indian summer monsoon played a positive role in sustaining the glaciers under the warming climate trend.

Information collection may affect the design quality and designer's performance through changing the structure of information and the way how information is searched and organized. Based on the theoretical analysis conducted by Wang et al., the present work continues to investigate the influence of designer's natural choice of information collection strategy on his/her mental stress both theoretically and empirically. Designers’ stresses are quantified from HRV data and are compared under different information collection strategies.