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The place of theology is under threat in the modern university. It is denied a place, except insofar as it is useful in the training of religious professionals or as a phenomenon in its own right, on the grounds that relate to an unscientific scientism that both makes metaphysical assumptions it itself does not recognise as scientific or denies its own epistemological commitments. This article argues that the notion of education in ‘liberal knowledge’ or ‘universal knowledge’, the idea at the heart of John Henry Newman’s The Idea of a University provides a sufficiently robust counter to these assaults on the place of theology proper in the modern university and that refusing such a place to it undermines the claim of universities to use the name at all. It is precisely the uselessness of theology that guarantees its place in the university committed to universal knowledge and universal enquiry.

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.

To determine whether living according to specific traditional Chinese cultural values was associated with satisfaction of the five needs in Maslow’s motivational hierarchy and overall life satisfaction, a mixed-method approach was employed, with an empirical questionnaire and supplemental interviews. The questionnaire assessed the hypothesized relationships that traditional Chinese values had with personal life outcomes, including health, employment, satisfaction of the five needs from Maslow’s hierarchy, and life satisfaction. The interviews examined the relationships that several demographic variables had with living by traditional Chinese values. The results of the empirical data revealed that most Chinese people today are still living according to the traditional Chinese cultural values, and that living by those traditional values are strongly associated with satisfaction of all five of the human needs in the Maslow hierarchy, as well as with overall life satisfaction. Additionally, the results of the qualitative interviews readily supported the empirical findings, and also revealed that the time during which inter-generational transmission of the Chinese cultural values occurs is when parents teach those values to their children at a very early age, that is, between 3 and 8 years old, before the children start primary school.

The geochemistry and mineralogy of sediments provide relevant information for the understanding of the origin and metallogenic mechanism of ferromanganese nodules and crusts. At present, there are still few studies on the sediment origin of the Clarion–Clipperton Zone (CCZ) of the east Pacific, particularly on the systematic origin of sediments with a longer history/length. Here, bulk sediment geochemistry and clay mineral compositions were analyzed on a 5.7 m gravity core (GC04) obtained at the CCZ, an area rich in polymetallic nodules. The results indicate that the average total content of rare earth elements (REE), including yttrium (REY), in sediments is 454.7 ppm and the REEs distribution patterns normalized by the North American Shale Composite of samples are highly consistent, with all showing negative Ce anomalies and more obvious enrichment in heavy REE (HREE) than that of light REE (LREE). Montmorillonite/illite ratio, discriminant functions and smear slide identification indicate multiple origins for the material, and are strongly influenced by contributions from marine biomass, while terrestrial materials, seamount basalts and their alteration products and authigenic source also make certain contributions. The REY characteristics of the sediments in the study area are different from those of marginal oceanic and back-arc basins, and more similar to pelagic deep-sea sediments. Based on LREE/HREE-1/δCe and LREE/HREE-Y/Ho diagrams, we conclude that samples from the study area had pelagic sedimentary properties which suffered from a strong “seawater effect”.

The widespread W-(Mo)-Sn-Nb-Ta polymetallic mineralization in Southeast (SE) China is genetically associated with Mesozoic highly fractionated granitic rocks. Such rocks have enigmatic mineralogical and geochemical features, making its petrogenesis an intensely debated topic. To better understand the underlying magma evolution processes, petrography, garnet chemistry and whole-rock major and trace element data are reported for Jurassic highly fractionated granitic rocks and associated microgranite and aplitepegmatite dikes from Macao and compared with coeval similar granitic rocks from nearby areas in SE China. Despite the fact that the most evolved rocks in Macao are garnet-bearing aplite-pegmatite dikes, the existence of coeval two-mica and garnet-bearing biotite and muscovite granites displaying more evolved compositions (e.g, lower Zr/Hf ratios) indicates that the differentiation sequence reached higher degrees of fractionation at a regional scale. Although crystal fractionation played an important role, late-stage fluid/melt interactions, involving F-rich fluids, imparted specific geochemical characteristics to Macao and SE China highly fractionated granitic rocks such as the non-CHARAC (CHArge-and-RAdius-Controlled) behavior of trace elements, leading, for example, to non-chondritic Zr/Hf ratios, Rare Earth Elements (REE) tetrad effects and Nb-Ta enrichment and fractionation. Such process contributed to the late-stage crystallization of accessory phases only found in these highly evolved facies. Among the latter, two populations of garnet were identified in MGI (Macao Group I) highly fractionated granitic rocks: small grossular-poor euhedral grains and large grossular-rich skeletal garnet grains with quartz inclusions. The first group was mainly formed through precipitation from highly evolved Mn-rich slightly peraluminous melts under low-pressure and relatively low temperature (∼700 °C) conditions. Assimilation of upper crust metasedimentary materials may have contributed as a source of Mn and Al to the formation of garnet. The second group has a metasomatic origin related to the interaction of magmatic fluids with previously crystallized mineral phases and, possibly, with assimilated metasedimentary enclaves or surrounding metasedimentary strata. The highly fractionated granitic rocks in Macao represent the first stage in the development of granite-related W-(Mo)-Sn-Nb-Ta mineralization associated with coeval more evolved lithotypes in SE China.

The adoption of IoT for smart health applications is a relevant tool for distributed and intelligent automatic diagnostic systems. This work proposes the development of an integrated solution to monitor maternal and fetal signals for high-risk pregnancies based on IoT sensors, feature extraction based on data analytics, and an intelligent diagnostic aid system based on a 1-D convolutional neural network (CNN) classifier. The fetal heart rate and a group of maternal clinical indicators, such as the uterine tonus activity, blood pressure, heart rate, temperature, and oxygen saturation are monitored. Multiple data sources generate a significant amount of data in different formats and rates. An emergency diagnostic subsystem is proposed based on a fog computing layer and the best accuracy was 92.59% for both maternal and fetal emergency. A smart health analytics system is proposed for multiple feature extraction and the calculation of linear and nonlinear measures. Finally, a classification technique is proposed as a prediction system for maternal, fetal, and simultaneous health status classification, considering six possible outputs. Different classifiers are evaluated and a proposed CNN presented the best results, with the F1-score ranging from 0.74 to 0.91. The results are validated based on the diagnosis provided by two specialists. The results show that the proposed system is a viable solution for maternal and fetal ambulatory monitoring based on IoT.

Stock movement prediction is one of the most challenging problems in time series analysis due to the stochastic nature of financial markets. In recent years, a plethora of statistical methods and machine learning algorithms were proposed for stock movement prediction. Specifically, deep learning models are increasingly applied for the prediction of stock movement. The success of deep learning models relies on the assumption that massive training data are available. However, this assumption is impractical for stock movement prediction. In stock markets, a large number of stocks do not have enough historical data, especially for the companies which underwent initial public offering in recent years. In these situations, the accuracy of deep learning models to predict the stock movement could be affected. To address this problem, in this paper, we propose novel instance-based deep transfer learning models with attention mechanism. In the experiments, we compare our proposed methods with state-of-the-art prediction models. Experimental results on three public datasets reveal that our proposed methods significantly improve the performance of deep learning models when limited training data are available.

Macao inhabit a population of 683,100. The birth rate has been dropping while the death rate has risen compared to two years ago. Cemeteries are becoming crowded, and burial spots are demanding. In this case, video calls and social media can be the solution. How about our beloved ancestors? Can we video call them on their memorial days? This paper presents a VR experience of immersing oneself in the 3D VR of the Chapel of St. Michael of Macao to create a peaceful atmosphere for grave mourning. The chapel is also a personal space where we can be truly isolated in serenity. It is a retreat to pray, disconnect, and reconnect to the beloved deaths that may not be buried in an easily accessible location. The authors propose a possible future of mourning our loved ones through virtual reality and telepresence: an immersive experience connected with Macao's extraordinary and cultural unicity.

Noise pollution is increasingly present in aquatic ecosystems, causing detrimental effects on growth, physiology and behaviour of organisms. However, limited information exists on how this stressor affects animals in early ontogeny, a critical period for development and establishment of phenotypic traits. We tested the effects of chronic noise exposure to increasing levels (130 and 150 dB re 1 μPa, continuous white noise) and different temporal regimes on larval zebrafish (Danio rerio), an important vertebrate model in ecotoxicology. The acoustic treatments did not affect general development or hatching but higher noise levels led to increased mortality. The cardiac rate, yolk sac consumption and cortisol levels increased significantly with increasing noise level at both 3 and 5 dpf (days post fertilization). Variation in noise temporal patterns (different random noise periods to simulate shipping activity) suggested that the time regime is more important than the total duration of noise exposure to down-regulate physiological stress. Moreover, 5 dpf larvae exposed to 150 dB continuous noise displayed increased dark avoidance in anxiety-related dark/light preference test and impaired spontaneous alternation behaviour. We provide first evidence of noise-induced physiological stress and behavioural disturbance in larval zebrafish, showing that both noise amplitude and timing negatively impact key developmental endpoints in early ontogeny.

Background and objective Intrauterine Growth Restriction (IUGR) is a condition in which a fetus does not grow to the expected weight during pregnancy. There are several well documented causes in the literature for this issue, such as maternal disorder, and genetic influences. Nevertheless, besides the risk during pregnancy and labour periods, in a long term perspective, the impact of IUGR condition during the child development is an area of research itself. The main objective of this work is to propose a machine learning solution to identify the most significant features of importance based on physiological, clinical or socioeconomic factors correlated with previous IUGR condition after 10 years of birth. Methods In this work, 41 IUGR (18 male) and 34 Non-IUGR (22 male) children were followed up 9 years after the birth, in average (9.1786 ± 0.6784 years old). A group of machine learning algorithms is proposed to classify children previously identified as born under IUGR condition based on 24-hours monitoring of ECG (Holter) and blood pressure (ABPM), and other clinical and socioeconomic attributes. In additional, an algorithm of relevance determination based on the classifier is also proposed, to determine the level of importance of the considered features. Results The proposed classification solution achieved accuracy up to 94.73%, and better performance than seven state-of-the-art machine learning algorithms. Also, relevant latent factors related to HRV and BP monitoring are proposed, such as: day-time heart rate (day-time HR), day-night systolic blood pressure (day-night SBP), 24-hour standard deviation (SD) of SBP, dropped, morning cortisol creatinine, 24-hour mean of SDs of all NN intervals for each 5 minutes segment (24-hour SDNNi), among others. Conclusion With outstanding accuracy of our proposed solutions, the classification system and the indication of relevant attributes may support medical teams on the clinical monitoring of IUGR children during their childhood development.

Hydrothermal activity on mid-ocean ridges is an important mechanism for the delivery of Zn from the mantle to the surface environment. Zinc isotopic fractionation during hydrothermal activity is mainly controlled by the precipitation of Zn-bearing sulfide minerals, in which isotopically light Zn is preferentially retained in solid phases rather than in solution during mineral precipitation. Thus, seafloor hydrothermal activity is expected to supply isotopically heavy Zn to the ocean. Here, we studied sulfide-rich samples from the Duanqiao-1 hydrothermal field, located on the Southwest Indian Ridge. We report that, at the hand-specimen scale, late-stage conduit sulfide material has lower δ66Zn values (−0.05 ± 0.15 ‰; n = 19) than early-stage material (+0.13 ± 0.15 ‰; n = 10). These lower values correlate with enrichments in Pb, As, Cd, and Ag, and elevated δ34S values. We attribute the low δ66Zn values to the remobilization of earlier sub-seafloor Zn-rich mineralization. Based on endmember mass balance calculations, and an assumption of a fractionation factor (αZnS-Sol.) of about 0.9997 between sphalerite and its parent solution, the remobilized Zn was found consist of about 1/3 to 2/3 of the total Zn in the fluid that formed the conduit samples. Our study suggests that late-stage subsurface hydrothermal remobilization may release isotopically-light Zn to the ocean, and that this process may be common along mid-ocean ridges, thus increasing the size of the previously identified isotopically light Zn sink in the ocean.

The aim of this study was to explore home–school collaboration in the areas of assessment, placement, and Individual Education Plan (IEP) development for children identified with disabilities or special educational needs (SEN) in Macao. Despite the noted benefits of parent–school partnerships from prior research, minimal research has been conducted from the perspective of parents of children with SEN to examine whether these partnerships materialize in the context of Macao. Participants included 115 parents of school-aged children diagnosed with SEN. They provided demographic information and completed a 36-item questionnaire derived from two validated instruments. The research identified a range of factors which hinder parental involvement in decision-making and in the inclusion of children with SEN in optimal ways in Macao schools. Parents indicated they were not receiving relevant information and assessment feedback from the teachers; they were minimally involved in the IEP process, and their children were not receiving one-to-one support, regardless of the type of placement. Parents also underlined issues related to the timing of assessment procedures. Parents of children attending special classes in regular schools voiced more satisfaction with support provision than parents of children following the full inclusion model. Recommendations about how services could be improved for greater parental involvement are discussed. Key Words: parental involvement, school–family collaboration, inclusion, special educational needs, Macao, Individual Education Plans, IEP

The use of learning analytics (LA) in real-world educational applications is growing very fast as academic institutions realize the positive potential that is possible if LA is integrated in decision making. Education in schools on public health need to evolve in response to the new knowledge and th...