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As an emergent tourism sector, driving tourism connects car use and touristic activities intimately. Following the notion of the ‘inhabited car’, this article explores how and why Chinese tourists inhabit a travelling car for drivers/passengers in the leisure automobility and driving tourism context. Through three different road trips and ‘mobile methods’, it was found that Chinese tourists inhabit the car in four ways: driving, gazing, listening, and communicating. Through this embodied habitation, the car is turned into a ‘touristic inhabitation’ space for protecting the tourists generating touristic emotions、social interactions, and tourism meanings. The study contributes to automobility and tourism literature and provides implications for driving tourism development in China.

Nowadays, the increasing number of medical diagnostic data and clinical data provide more complementary references for doctors to make diagnosis to patients. For example, with medical data, such as electrocardiography (ECG), machine learning algorithms can be used to identify and diagnose heart disease to reduce the workload of doctors. However, ECG data is always exposed to various kinds of noise and interference in reality, and medical diagnostics only based on one-dimensional ECG data is not trustable enough. By extracting new features from other types of medical data, we can implement enhanced recognition methods, called multimodal learning. Multimodal learning helps models to process data from a range of different sources, eliminate the requirement for training each single learning modality, and improve the robustness of models with the diversity of data. Growing number of articles in recent years have been devoted to investigating how to extract data from different sources and build accurate multimodal machine learning models, or deep learning models for medical diagnostics. This paper reviews and summarizes several recent papers that dealing with multimodal machine learning in disease detection, and identify topics for future research.

<jats:p>Causal machine learning is an approach that combines causal inference and machine learning to understand and utilize causal relationships in data. In current research and applications, traditional machine learning and deep learning models always focus on prediction and pattern recognition. In contrast, causal machine learning goes a step further by revealing causal relationships between different variables. We explore a novel concept called Double Machine Learning that embraces causal machine learning in this research. The core goal is to select independent variables from a gesture identification problem that are causally related to final gesture results. This selection allows us to classify and analyze gestures more efficiently, thereby improving models’ performance and interpretability. Compared to commonly used feature selection methods such as Variance Threshold, Select From Model, Principal Component Analysis, Least Absolute Shrinkage and Selection Operator, Artificial Neural Network, and TabNet, Double Machine Learning methods focus more on causal relationships between variables rather than correlations. Our research shows that variables selected using the Double Machine Learning method perform well under different classification models, with final results significantly better than those of traditional methods. This novel Double Machine Learning-based approach offers researchers a valuable perspective for feature selection and model construction. It enhances the model’s ability to uncover causal relationships within complex data. Variables with causal significance can be more informative than those with only correlative significance, thus improving overall prediction performance and reliability.</jats:p>

Ligand peptides that have high affinity for ion channels are critical for regulating ion flux across the plasma membrane. These peptides are now being considered as potential drug candidates for many diseases, such as cardiovascular disease and cancers. In this work, we developed Multi-Branch-CNN, a CNN method with multiple input branches for identifying three types of ion channel peptide binders (sodium, potassium, and calcium) from intra- and inter-feature types. As for its real-world applications, prediction models that are able to recognize novel sequences having high or low similarities to training sequences are required. To this end, we tested our models on two test sets: a general test set including sequences spanning different similarity levels to those of the training set, and a novel-test set consisting of only sequences that bear little resemblance to sequences from the training set. Our experiments showed that the Multi-Branch-CNN method performs better than thirteen traditional ML algorithms (TML13), yielding an improvement in accuracy of 3.2%, 1.2%, and 2.3% on the test sets as well as 8.8%, 14.3%, and 14.6% on the novel-test sets for sodium, potassium, and calcium ion channels, respectively. We confirmed the effectiveness of Multi-Branch-CNN by comparing it to the standard CNN method with one input branch (Single-Branch-CNN) and an ensemble method (TML13-Stack). The data sets, script files to reproduce the experiments, and the final predictive models are freely available at https://github.com/jieluyan/Multi-Branch-CNN.

Antimicrobial resistance has become a critical global health problem due to the abuse of conventional antibiotics and the rise of multi-drug-resistant microbes. Antimicrobial peptides (AMPs) are a group of natural peptides that show promise as next-generation antibiotics due to their low toxicity to the host, broad spectrum of biological activity, including antibacterial, antifungal, antiviral, and anti-parasitic activities, and great therapeutic potential, such as anticancer, anti-inflammatory, etc. Most importantly, AMPs kill bacteria by damaging cell membranes using multiple mechanisms of action rather than targeting a single molecule or pathway, making it difficult for bacterial drug resistance to develop. However, experimental approaches used to discover and design new AMPs are very expensive and time-consuming. In recent years, there has been considerable interest in using in silico methods, including traditional machine learning (ML) and deep learning (DL) approaches, to drug discovery. While there are a few papers summarizing computational AMP prediction methods, none of them focused on DL methods. In this review, we aim to survey the latest AMP prediction methods achieved by DL approaches. First, the biology background of AMP is introduced, then various feature encoding methods used to represent the features of peptide sequences are presented. We explain the most popular DL techniques and highlight the recent works based on them to classify AMPs and design novel peptide sequences. Finally, we discuss the limitations and challenges of AMP prediction.

The Qiyugou gold deposit, located in the Xiong’ ershan area of the North China Craton, contains abundant bismuth-sulfosalts that are closely associated with gold mineralization. Pyrite is the dominant Au-hosted mineral, and has been formed in three generations (Py1, Py2, and Py3). Py1 grains, generally intergrown with milky quartz, are coarse (>1 mm), euhedral in shape, and Au-depleted in composition. In contrast, subhedral Py2 grains, associated with light gray quartz, are medium to coarse (0.2–3 mm) and are enriched in gold that is both invisible and visible. Py3 grains (0.1–0.5 mm), intergrown with abundant sulfide minerals, are relatively fine and Au-depleted. The time-resolved LA-ICP-MS depth profiles of the Py2 grains indicate that invisible gold occurs as either solid solution or nano-particles of native gold and electrum. Visible gold occurs as small blebs in the Py2 grains where inclusions of native bismuth, galenobismutite, lillianite homologs, tetradymite, and galena are also present. In addition, it is common that electrum in microfracture infillings or along grain boundaries of the Py1 and Py2, are intergrown with bismuthinite derivatives, Bi-Cu sulfosalts, emplectite, tetradymite, chalcopyrite, galena, and Py3. Based on textural relationships and mineral assemblages, calculation of physicochemical conditions show that gold was formed in conditions of fTe2 = ~10−11 and fS2 = ~10−11 to 10−12 for Py2, and fTe2 = ~10−9 to 10-11and fS2 = ~10−10 to 10−11 for Py3. We thus proposed that such physicochemical conditions may have triggered the precipitation of Bi melt, and sulfidation driven by cooling or increase in sulfur content results in the transformation of the Au-Bi liquid into a stable assemblage of native gold and bismuthinite. These bismuth minerals are associated with native gold/Au-bearing minerals, indicating that the Au mineralization of the Qiyugou gold deposit might be genetically associated with Bi melt. The present study highlights the role of Bi as important gold scavengers in arsenic-deficient ore-forming fluid.

Anthropogenic noise of variable temporal patterns is increasing in aquatic environments, causing physiological stress and sensory impairment. However, scarce information exists on exposure effects to continuous versus intermittent disturbances, which is critical for noise sustainable management. We tested the effects of different noise regimes on the auditory system and behaviour in the zebrafish (Danio rerio). Adult zebrafish were exposed for 24 h to either white noise (150 ± 10 dB re 1 μPa) or silent control. Acoustic playbacks varied in temporal patterns—continuous, fast and slow regular intermittent, and irregular intermittent. Auditory sensitivity was assessed with Auditory Evoked Potential recordings, revealing hearing loss and increased response latency in all noise-treated groups. The highest mean threshold shifts (c. 13 dB) were registered in continuous and fast intermittent treatments, and no differences were found between regular and irregular regimes. Inner ear saccule did not reveal significant hair cell loss but showed a decrease in presynaptic Ribeye b protein especially after continuous exposure. Behavioural assessment using the standardized Novel Tank Diving assay showed that all noise-treated fish spent > 98% time in the bottom within the first minute compared to 82% in control, indicating noise-induced anxiety/stress. We provide first data on how different noise time regimes impact a reference fish model, suggesting that overall acoustic energy is more important than regularity when predicting noise effects.

Intended as an economic and development hub, the Hengqin Cooperation Zone aims to foster collaboration and integration between mainland China, Hong Kong, and Macao, serving as a platform for economic development and innovation among the three regions. The zone's development has increased demand for financial services, often offered through fintech. There is, however, a lack of interoperability between the fintech services currently used in Macao and Hengqin. This may hinder Macao users' adoption of the technology. Thus, our research objective is to identify the factors determining Macao residents' adoption of fintech services in the area and provide insights for service providers, developers, and policymakers. A framework based on the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) was used for this purpose. The responses of 103 Macao residents provided evidence that ease of use significantly and positively impacts the usefulness of the technology. This in turn influences attitudes towards fintech usage. Subjective norms and perceived behavioral control positively impact fintech adoption intentions. The fintech industry and the governments of Macao and Hengqin can work on improving technology's ease of use and usefulness. They can also promote them to Macao users, and provide the resources required for better access to fintech in the zone

The question of how to adequately integrate environment and labor provisions in free trade agreements is still a difficult one for both States and academicians. This article explores China’s approach to environment and labor issues in free trade agreements. For reference and comparison, it relies on the European Union’s and the United States’ approaches in their respective FTAs. The article identifies China’s preference for a case-by-case approach to the inclusion of environmental chapters in its FTAs. Additionally, in most FTAs it avoids to include provisions on labor standards. These two preferences represent major divergences from the European Union’s and the United States’ approaches, characterized by inclusion of chapters on environment and labor in all their modern FTAs. The article also finds that China’s FTAs rely solely on consultations and cooperation for the implementation of environmental and labor provisions, within the framework of Joint Committees and avoid the inclusion of civil society mechanisms. Moreover, resolution of disputes relies exclusively on consultations, in a diverse procedure than the one applicable to trade disputes. Despite alignment with the European Union model, this is another major point of divergence with the United States’ model, which applies the same enforcement mechanism for both environment and labor issues and trade issues and includes the possibility of applying sanctions. Finally, the article concludes that China’s options with regards to the treatment of environment and labor concerns in its free trade agreements aligns with both its domestic governance approach and its approach to international cooperation.

Peer-rewieved journal

Over the past few years, the gaming industry has changed the face of Macao and the lives of its citizens. The liberalisation of casino licensing in 2002 and the implementation of the Chinese government's new visa regulations in 2003, which permitted many mainland Chinese to travel to Hong Kong and Macao on an individual basis, triggered an economic boom. Foreign investment increased dramatically as international companies began to build casinos and hotels. By 2006, gaming revenues had reached a record annual high of US$10.33 billion, far exceeding the US$6.6 billion made on the Las Vegas strip (Gaming Inspection and Coordination Bureau, 2008). Tourist numbers more than doubled from 11 million in 2002 to 21.7 million in 2009 (Statistics and Census Service, 2009a). Rapid economic growth has come at a price, however. There have been many social dislocations and challenges for public policy that can be attributed to the expansion of the gaming industry. A particular issue is land, a fundamental factor of production and an essential component of the gaming industry's success but in short supply in Macao. The tension between casino requirements for land and public needs spills over into debates on matters as diverse as building height restrictions, heritage protection, green space, the opaqueness of government decisions and its lack of consultative mechanisms. © 2011 by The Hong Kong University Press, HKU. All rights reserved.

Vocal differentiation is widely documented in birds and mammals but has been poorly investigated in other vertebrates, including fish, which represent the oldest extant vertebrate group. Neural circuitry controlling vocal behaviour is thought to have evolved from conserved brain areas that originated in fish, making this taxon key to understanding the evolution and development of the vertebrate vocal-auditory systems. This study examines ontogenetic changes in the vocal repertoire and whether vocal differentiation parallels auditory development in the Lusitanian toadfish Halobatrachus didactylus (Batrachoididae). This species exhibits a complex acoustic repertoire and is vocally active during early development. Vocalisations were recorded during social interactions for four size groups (fry: &lt;2 cm; small juveniles: 2–4 cm; large juveniles: 5–7 cm; adults &gt;25 cm, standard length). Auditory sensitivity of juveniles and adults was determined based on evoked potentials recorded from the inner ear saccule in response to pure tones of 75–945 Hz. We show an ontogenetic increment in the vocal repertoire from simple broadband-pulsed ‘grunts’ that later differentiate into four distinct vocalisations, including low-frequency amplitude-modulated ‘boatwhistles’. Whereas fry emitted mostly single grunts, large juveniles exhibited vocalisations similar to the adult vocal repertoire. Saccular sensitivity revealed a three-fold enhancement at most frequencies tested from small to large juveniles; however, large juveniles were similar in sensitivity to adults. We provide the first clear evidence of ontogenetic vocal differentiation in fish, as previously described for higher vertebrates. Our results suggest a parallel development between the vocal motor pathway and the peripheral auditory system for acoustic social communication in fish.

One of the six gaming concession holders in Macao, Macao Entertainment Corp (MEC)1, undertook to centralize three casino/entertainment properties through utilization of a centralized Enterprise Resource Planning (ERP) in April 2010. The Supply Chain (SC) department was the first to apply the ERP in...