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Macau, Macau Business, MAG, MB, MB Featured, Opinion | The late psychologist, business and management consultant Edward de Bono gained a worldwide reputation for ‘lateral thinking’, which included his ‘six thinking hats’ and ‘tools for thinking’. Though his work is arguably only plausible pseudoscience, his ‘tools for thinking’ remain interesting. Consider some of these from his Cognitive Research Trust (CoRT), in approaching planning, e.g.: CAF (Consider All Factors); EBS (Examine Both Sides); and OPV (consider Other People’s Views). Here I apply them to Macau.

The physiological mechanisms underlying variation in aggression in fish remain poorly understood. One possibly confounding variable is the lack of standardization in the type of stimuli used to elicit aggression. The presentation of controlled stimuli in videos, a.k.a. video playback, can provide better control of the fight components. However, this technique has produced conflicting results in animal behaviour studies and needs to be carefully validated. For this, a similar response to the video and an equivalent live stimulus needs to be demonstrated. Further, different physiological responses may be triggered by live and video stimuli and it is important to demonstrate that video images elicit appropriate physiological reactions. Here, the behavioural and endocrine response of male Siamese fighting fish Betta splendens to a matched for size conspecific fighting behind a one-way mirror, presented live or through video playback, was compared. The video playback and live stimulus elicited a strong and similar aggressive response by the focal fish, with a fight structure that started with stereotypical threat displays and progressed to overt attacks. Post-fight plasma levels of the androgen 11-ketotestosterone were elevated as compared to controls, regardless of the type of stimuli. Cortisol also increased in response to the video images, as previously described for live fights in this species. These results show that the interactive component of a fight, and its resolution, are not needed to trigger an endocrine response to aggression in this species. The study also demonstrates for the first time in a fish a robust endocrine response to video stimuli and supports the use of this technique for researching aggressive behaviour in B. splendens.

The key challenge of Unsupervised Domain Adaptation (UDA) for analyzing time series data is to learn domain-invariant representations by capturing complex temporal dependencies. In addition, existing unsupervised domain adaptation methods for time series data are designed to align marginal distribution between source and target domains. However, existing UDA methods (e.g. R-DANN Purushotham et al. (2017), VRADA Purushotham et al. (2017), CoDATS Wilson et al. (2020)) neglect the conditional distribution discrepancy between two domains, leading to misclassification of the target domain. Therefore, to learn domain-invariant representations by capturing the temporal dependencies and to reduce the conditional distribution discrepancy between two domains, a novel Attentive Recurrent Adversarial Domain Adaptation with Top-k time series pseudo-labeling method called ARADA-TK is proposed in this paper. In the experiments, our proposed method was compared with the state-of-the-art UDA methods (R-DANN, VRADA and CoDATS). Experimental results on four benchmark datasets revealed that ARADA-TK achieves superior classification accuracy when it is compared to the competing methods.

It has become increasingly clear that the early use of decomposition for addition is associated with later mathematical achievement. This study examined how younger children execute a base-10 decomposition strategy to solve complex arithmetic (e.g. two-digit addition). 24 addition problems in two modalities (WA: Written Arithmetic; OA: Oral Arithmetic) with sums less than 100 were administered to 22 Japanese and 22 Singaporean 6-year-old kindergarteners. Our findings reveal that they were able to solve complex addition. For instance, Japanese kindergarteners tended to solve complex arithmetic using base-10 decomposition across the modality, whereas Singaporean kindergarteners used standard algorithms and basic counting to solve complex WA and OA problems, respectively. We speculate that Japanese kindergarteners might have a clearer understanding of the base-10 concept and were able to use this knowledge more readily than Singaporean kindergarteners. Mathematical experiences in kindergarten and number-naming systems have been put forward as two of the crucial contributors for such cross-cultural differences. This study also provides new directions for future research on the understanding of the base-10 concept and its application among young children.

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.

Macau, Macau Business, MAG, MB, MB Featured, Opinion | Here we are, at the start of a new academic year in Macau’s higher education (HE). What will students learn? What kind of people are the institutions turning out? For example, look at the thousands of students studying business and technology in Macau, the big recruiters in HE.

YouTube has become increasingly popular for marketing purposes. As corporate and user-generated content is widely available on this platform, beauty-related professionals need to understand how to create videos that make their products more appealing and stand out from the clutter. In this study, we examine four factors (i.e., perceived usefulness of the information, perceived credibility of the information, attitude toward the purchase, and perceived video characteristics) that affect the purchase intentions of female consumers. After viewing beauty-related videos, a sample of 204 female consumers was analyzed by structural equation modeling. The findings showed that videos with more views, likes, and comments tend to have a greater effect on the respondents' intentions to purchase. Also, the factors of perceived usefulness of the information, perceived credibility of the information, and attitude toward the purchase exhibited a significant effect on the intention to buy beauty-related products. The result showed that perceived video characteristics (such as quality and visuals) did not significantly influence the purchase intention, however, there is evidence that this factor should not be ignored by content creators. Finally, our research provides insights, strategies, and future directions for industry practitioners and marketers.

Dennis Zuev* The Belt and Road Initiative (BRI) has become the largest infrastructure program in history, and has become a symbol of growing significance of China and its power.

This study, focusing on the China's Yao minority community, investigates the feasibility to create a generative computational method to replicate the diversity of the existing Yao traditional wood buildings, addressing the critical issues currently facing computational design methods, in the attempt to adapt genetic-generative algorithms to the study of local ancient architecture. The project develops a computational tool to generate a network of three-dimensional prototypes, or building structures, derived from traditional wood frame village houses. It studies possible housing structures that illustrate some of the key working methods available in digital systems such as ‘generating' and ‘compositing' taking as a starting point computational strategies oriented towards geometry and where a set of local variables play a decisive role: available local technologies, use of raw materials, and the dimensioning of timber components based on data collected from Yao architecture.

Artists are increasingly using blockchain as a tool for trading digital artwork as non-fungible tokens (NFTs); however, some are also beginning to experiment with the blockchain as a medium for generative art, using it as a seed for a generative process or to continuously modify an evolving piece. This paper surveys, reviews, and classifies the state-of-the-art in blockchain-interactive NFTs and presents a liberal-arts critique of the opportunities and threats posed by this technology, whilst addressing existing criticism on the broader topic of art-related NFTs. The paper examines some of the most experimental pieces minted on the Hic et Nunc (HEN) and Teia NFT marketplaces, for which a purpose-built research tool was developed. The survey reveals some reliance on centralised infrastructure, namely blockchain indexers, placing undesired trust on third parties which undermines the potential longevity of the artwork. The paper concludes with recommendations for artists and NFT platform designers for developing more resilient and economically sustainable architectures.

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.

Approximately 50 million people are suffering from epilepsy worldwide. Corals have been used for treating epilepsy in traditional Chinese medicine, but the mechanism of this treatment is unknown. In this study, we analyzed the transcriptome of the branching coral Acropora digitifera and obtained its Kyoto Encyclopedia of Genes and Genomes (KEGG), EuKaryotic Orthologous Groups (KOG) and Gene Ontology (GO) annotation. Combined with multiple sequence alignment and phylogenetic analysis, we discovered three polypeptides, we named them AdKuz1, AdKuz2 and AdKuz3, from A. digitifera that showed a close relationship to Kunitz-type peptides. Molecular docking and molecular dynamics simulation indicated that AdKuz1 to 3 could interact with GABAA receptor but AdKuz2–GABAA remained more stable than others. The biological experiments showed that AdKuz1 and AdKuz2 exhibited an anti-inflammatory effect by decreasing the aberrant level of nitric oxide (NO), IL-6, TNF-α and IL-1β induced by LPS in BV-2 cells. In addition, the pentylenetetrazol (PTZ)-induced epileptic effect on zebrafish was remarkably suppressed by AdKuz1 and AdKuz2. AdKuz2 particularly showed superior anti-epileptic effects compared to the other two peptides. Furthermore, AdKuz2 significantly decreased the expression of c-fos and npas4a, which were up-regulated by PTZ treatment. In addition, AdKuz2 reduced the synthesis of glutamate and enhanced the biosynthesis of gamma-aminobutyric acid (GABA). In conclusion, the results indicated that AdKuz2 may affect the synthesis of glutamate and GABA and enhance the activity of the GABAA receptor to inhibit the symptoms of epilepsy. We believe, AdKuz2 could be a promising anti-epileptic agent and its mechanism of action should be further investigated.

Despite the levels of air pollution in Macao continuing to improve over recent years, there are still days with high-pollution episodes that cause great health concerns to the local community. Therefore, it is very important to accurately forecast air quality in Macao. Machine learning methods such as random forest (RF), gradient boosting (GB), support vector regression (SVR), and multiple linear regression (MLR) were applied to predict the levels of particulate matter (PM10 and PM2.5) concentrations in Macao. The forecast models were built and trained using the meteorological and air quality data from 2013 to 2018, and the air quality data from 2019 to 2021 were used for validation. Our results show that there is no significant difference between the performance of the four methods in predicting the air quality data for 2019 (before the COVID-19 pandemic) and 2021 (the new normal period). However, RF performed significantly better than the other methods for 2020 (amid the pandemic) with a higher coefficient of determination (R2) and lower RMSE, MAE, and BIAS. The reduced performance of the statistical MLR and other ML models was presumably due to the unprecedented low levels of PM10 and PM2.5 concentrations in 2020. Therefore, this study suggests that RF is the most reliable prediction method for pollutant concentrations, especially in the event of drastic air quality changes due to unexpected circumstances, such as a lockdown caused by a widespread infectious disease.

Macau, MNA, Opinion | The Macau government recently approved its first reading of a new bill to attract Macau locals to return to Macau to work. Simultaneously, Macau’s Secretary for Social Affairs and Culture was reported as saying that if Macau could create a better environment and conditions, then ‘local talents who are abroad will surely be interested in returning to Macau’.

Macau, Macau Business, MAG, MB, MB Featured, Opinion | Business 101. When companies plan their business models, typically they must consider, amongst other matters: their products and/or services; demand; market(s) and their environments (economic, political, cultural, social); existing, potential, and likely competition; start-up and ongoing costs and expenses; emergency funding; marketing and promotion; income streams, revenue, and delayed profit; sales; distribution; cash flow; profit margins, gross and net; liabilities; risk analysis, evaluation, and handling; constraints and the ‘what if’ factor; flexibility, adaptability, and adjustment.

Resumo O fascínio do Ocidente pela dicção poética oriental está atestado em várias latitudes e línguas, e resultou numa profícua produção na área da poesia. Sabe-se que a reinvenção da poesia chinesa da autoria de Pound, em grande medida na origem da sua proposta de revolução do idioma poético, nas primeiras décadas do séc. XX, assentou, na verdade, numa falácia; numa concepção errada da natureza da escrita chinesa (e japonesa) como essencialmente pictográfica e ideogramática, na base de propriedades expressivas reconhecidas na poesia que resultariam numa particular eficácia na apreensão e tradução do real. Pessanha enaltece, em termos similares aos da exaltação poundiana, a escrita da poesia chinesa clássica. Interessa-nos rever alguns inventários dos traços da dicção poética chinesa e japonesa que explicam que ela seja tomada como metonímia e metáfora da poesia, ou como meta e utopia da poesia, para perceber o que terá levado autores muito díspares a tentar a mão nos haikus, processo em que sondaremos algumas formulações poéticas em língua portuguesa. Consideramos também que esse fascínio por uma (sonhada) origem da dicção poética, quando cruzada com o habitar (não metafórico, neste caso) do pequenino enclave de Macau, de autores que nele lançaram raízes, resultou em alguns exercícios poéticos particularmente felizes e singulares. Serão trazidos à colação nesta abordagem poemas de Eugénio de Andrade, Sophia de Mello Breyner Andresen, José Tolentino Mendonça, Yao Feng, Fernanda Dias e Fernando Sales Lopes.

Nessa noite decidiram hospedar-se num motel pois queriam acordar às 3.45 para ver o primeiro sol das Américas na Ponta de Seixas, João Pessoa, Paraíba. Subiram à torre do Nazareno às 4.45 e, quando já pensavam que as nuvens não iam deixar assistir ao nascer de mais um dia aprazível, eis que ele, o senhor rei dos dias, surge do mar. Enquanto os olhos brilhavam ao sol, lembrou-se que Chico César era dali perto, do interior da Paraíba, para as bandas de Campina Grande. Recordou que a primeira vez que tentou olhá-lo nos olhos percebeu que ele estava envolvido numa […]

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.