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With the fifth generation (5G) communication technology, the mobile multiuser networks have developed rapidly. In this paper, the performance analysis of mobile multiuser networks which utilize decode-and-forward (DF) relaying is considered. We derive novel outage probability (OP) expressions. To improve the OP performance, we study the power allocation optimization problem. To solve the optimization problem, we propose an intelligent power allocation optimization algorithm based on grey wolf optimization (GWO). We compare the proposed GWO approach with three existing algorithms. The experimental results reveal that the proposed GWO algorithm can achieve a smaller OP, thus improving system efficiency. Also, compared with other channel models, the OP values of the 2-Rayleigh model are increased by 81.2% and 66.6%, respectively.

Classification of electroencephalogram (EEG) is a key approach to measure the rhythmic oscillations of neural activity, which is one of the core technologies of brain-computer interface systems (BCIs). However, extraction of the features from non-linear and non-stationary EEG signals is still a challenging task in current algorithms. With the development of artificial intelligence, various advanced algorithms have been proposed for signal classification in recent years. Among them, deep neural networks (DNNs) have become the most attractive type of method due to their end-to-end structure and powerful ability of automatic feature extraction. However, it is difficult to collect large-scale datasets in practical applications of BCIs, which may lead to overfitting or weak generalizability of the classifier. To address these issues, a promising technique has been proposed to improve the performance of the decoding model based on data augmentation (DA). In this article, we investigate recent studies and development of various DA strategies for EEG classification based on DNNs. The review consists of three parts: what kind of paradigms of EEG-based on BCIs are used, what types of DA methods are adopted to improve the DNN models, and what kind of accuracy can be obtained. Our survey summarizes the current practices and performance outcomes that aim to promote or guide the deployment of DA to EEG classification in future research and development.

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.

As safety is one of the most important properties of drugs, chemical toxicology prediction has received increasing attentions in the drug discovery research. Traditionally, researchers rely on in vitro and in vivo experiments to test the toxicity of chemical compounds. However, not only are these experiments time consuming and costly, but experiments that involve animal testing are increasingly subject to ethical concerns. While traditional machine learning (ML) methods have been used in the field with some success, the limited availability of annotated toxicity data is the major hurdle for further improving model performance. Inspired by the success of semi-supervised learning (SSL) algorithms, we propose a Graph Convolution Neural Network (GCN) to predict chemical toxicity and trained the network by the Mean Teacher (MT) SSL algorithm. Using the Tox21 data, our optimal SSL-GCN models for predicting the twelve toxicological endpoints achieve an average ROC-AUC score of 0.757 in the test set, which is a 6% improvement over GCN models trained by supervised learning and conventional ML methods. Our SSL-GCN models also exhibit superior performance when compared to models constructed using the built-in DeepChem ML methods. This study demonstrates that SSL can increase the prediction power of models by learning from unannotated data. The optimal unannotated to annotated data ratio ranges between 1:1 and 4:1. This study demonstrates the success of SSL in chemical toxicity prediction; the same technique is expected to be beneficial to other chemical property prediction tasks by utilizing existing large chemical databases. Our optimal model SSL-GCN is hosted on an online server accessible through: https://app.cbbio.online/ssl-gcn/home.

Microbial and hydrothermal venting activities on the seafloor are important for the formation of sediment-hosted stratiform sulfide (SHSS) deposits. Fe isotopic compositions are sensitive to both microbial and hydrothermal activities and may be used to investigate the formation of these deposits. However, to the best of our knowledge, no Fe isotopic studies have been conducted on SHSS deposits. In the Devonian Dajiangping SHSS-type pyrite deposit (389 Ma), South China, laminated pyrite ores were precipitated from exhalative hydrothermal fluids, whereas black shales were deposited during intervals with no exhalation. Pyrite grains from black shales mostly display positive δ56Fe-py (0.01–0.73‰), higher than marine sediments (ca. 0‰), due to pyrite deriving Fe from basinal shuttled Fe(III) (hydr-)oxides and slowly crystallizing in pores of sediments with equilibrium fractionation, except for negative δ56Fe-py (−0.17‰ to −0.24‰) of two samples caused by mixing of Fe from underlain laminated ores. The positive δ34S-py (3.50–24.5‰) of black shales reflect that sulfur of pyrite originated from quantitative reduction of sulfate in closed pores of sediments. In contrast, pyrite grains of laminated ores have negative δ56Fe-py (−0.60‰ to −0.21‰), which were not only inherited from the negative δ56Fe of hydrothermal fluids but also caused by kinetic fractionation during rapid precipitation of a pyrite precursor (FeS) in hydrothermal plumes. These ores have negative δ34S-py (−28.7‰ to −1.82‰), because H2S for pyrite mineralization was produced by bacterial sulfate reduction (BSR) in a sulfate-rich seawater column or shallow sediments. The δ56Fe-py values of laminated ores co-vary positively with δ34S-py and δ13C-carbonate along the ore stratigraphy, with δ13C-carbonate values ranging from −12.0‰ to −2.50‰. However, they correlate negatively with aluminum-normalized total organic carbon (TOC/Al2O3). Organic carbon is thus considered to enhance the production of H2S by BSR activities, increase pyrite precipitation rates and promote the expression of kinetic fractionation of Fe isotopes. Intriguingly, in the ore units with vigorous hydrothermal venting activities, δ56Fe-py, δ34S-py and δ13C-carbonate values display a consistently increasing trend. Such results suggest that venting hydrothermal fluids significantly inhibited the H2S production of BSR, which then reduced the pyrite crystallization rate and decreased the kinetic fractionation of Fe isotopes. Our study reveals that the formation of SHSS deposits relies on H2S from microbial activities and metals from hydrothermal exhalation on the seafloor, but that vigorous exhalation can inhibit microbial activities and thus sulfide precipitation rates. The integrated use of Fe, S, and C isotopes can effectively elucidate these dynamic interactions between hydrothermal venting and microbial activities during the formation of SHSS deposits.

Monitoring signals such as fetal heart rate (FHR) are important indicators of fetal well-being. Computer-assisted analysis of FHR patterns has been successfully used as a decision support tool. However, the absence of a gold standard for the building blocks decision-making in the systems design process impairs the development of new solutions. Here we propose a prognostic model based on advanced signal processing techniques and machine learning algorithms for the fetal state assessment within a comprehensive evaluation process. Feature-engineering-based and time-series-based machine learning classifiers were modeled into three data segmentation schemas for CTU-UHB, HUFA, and DB-TRIUM datasets and the generalization performance was assessed by a two-way cross-dataset evaluation. It has been shown that the feature-based algorithms outperformed the time-series ones on data-limited scenarios. The Support Vector Machines (SVM) obtained the best results on the datasets individually: specificity (85.6% ) and sensitivity (67.5%). On the other hand, the most effective generalization results were achieved by the Multi-layer perceptron (MLP) with a specificity of 71.6% and sensitivity of 61.7%. The overall process provided a combination of techniques and methods that increased the final prognostic model performance, achieving relevant results and requiring a smaller amount of data when compared to the state-of-the-art fetal status assessment solutions.

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.

This essay presents a mapping of the historical concepts that contributed to the emergence of post-digital aesthetics and their connections to the concept of post-media in historical terms. It also analyzes the transition from techno-positivism to discourse of resistance against the effects of the capital technological industrial complex and how these advances in technology influence artistic discourses, practices and are the leverage of art and technology which is nothing more than a representation of the aesthetics of capital. Following art and capitalism as an ideology of innovation. Is proposed an unstinting theory about technology, geology, and the importance of these conditions to the post-digital aesthetics in terms of material disponible and conceptual articulation. Producing a reconfiguration of the post-digital conceptual approach as I propose beyond the dysfunctional aesthetics and connected with the concept of radical ecology centered in the usability of electronic garbage and technical obsolescent technologies in the arts.

The occurrence of endocrine disrupting chemicals (EDCs) is a major issue for marine and coastal environments in the proximity of urban areas. The occurrence of EDCs in the Pearl River Delta region is well documented but specific data related to Macao is unavailable. The levels of bisphenol-A (BPA), estrone (E1), 17α-estradiol (αE2), 17β-estradiol (E2), estriol (E3), and 17α-ethynylestradiol (EE2) were measured in sediment samples collected along the coastline of Macao. BPA was found in all 45 collected samples with lower BPA concentrations associated to the presence of mangrove trees. Biodegradation assays were performed to evaluate the capacity of the microbial communities of the surveyed ecosystems to degrade BPA and its analogue BPS. Using sediments collected at a WWTP discharge point as inoculum, at a concentration of 2 mg l−1 complete removal of BPA was observed within 6 days, whereas for the same concentration BPS removal was of 95% after 10 days, which is particularly interesting since this compound is considered recalcitrant to biodegradation and likely to accumulate in the environment. Supplementation with BPA improved the degradation of bisphenol-S (BPS). Aiming at the isolation of EDCs-degrading bacteria, enrichments were established with sediments supplied with BPA, BPS, E2 and EE2, which led to the isolation of a bacterial strain, identified as Rhodoccoccus sp. ED55, able to degrade the four compounds at different extents. The isolated strain represents a valuable candidate for bioremediation of contaminated soils and waters.

Robotics are being used in the intervention with children with Autism Spectrum Disorder (ASD) in many places and already for many years. Many robots were developed and different studies are being made in order to evaluate its effectiveness. “Socially Assistive Robotics” is shown to be effective in different areas mainly in social and emotional development. Milo, a robot developed by a team led by Richard Margolin for the Robots4Autism program (RoboKind, 2020), is one of the robots whose use is reported to be successful. In Macao there is no report of studies or experiences on the use of robots in the intervention with children with ASD. In a collaboration between the Macao Science Centre, the Macao Autism Association (MAA) and the University of Saint Joseph, an exploratory study was developed to understand the applicability of Milo to the work with children with ASD in Macao. The study showed that the robot is able to facilitate social and emotional competences of children with ASD. However, several limitations including language, cultural differences, the inexperienced facilitators and the level of sessions are too simple for the participants to be aware of that may affect the effectiveness of the intervention. It is important to show that the adoption of Milo in Macao for intervening children with ASD can be further implemented, with better practical solutions.

To solve the problem of one-sided pursuit of the shortest distance but ignoring the tourist experience in the process of tourism route planning, an improved ant colony optimization algorithm is proposed for tourism route planning. Contextual information of scenic spots significantly effect people’s choice of tourism destination, so the pheromone update strategy is combined with the contextual information such as weather and comfort degree of the scenic spot in the process of searching the global optimal route, so that the pheromone update tends to the path suitable for tourists. At the same time, in order to avoid falling into local optimization, the sub-path support degree is introduced. The experimental results show that the optimized tourism route has greatly improved the tourist experience, the route distance is shortened by 20.5% and the convergence speed is increased by 21.2% compared with the basic algorithm, which proves that the improved algorithm is notably effective.

In this essay, we respond to Dustin Crummett’s argument that one cannot consistently appeal to body count reasoning to justify being a single-issue pro-life voter if one is also committed to the usual response to the embryo rescue case. Specifically, we argue that a modified version of BCR we call BCR* is consistent with the usual response. We then move to address concerns about the relevance of BCR* to Crummett’s original thesis.

China’s return to social work education, after a nearly 35-year absence, opened the door for partnerships like the 2012 China Collaborative partnership between the Council on Social Work Education’s (CSWE) Katherine A. Kendall Institute, the China Association of Social Work Education (CASWE) and the International Association of Schools of Social Work (IASSW). The University of Alabama School of Social Work (UA SSW) was selected to participate in the collaborative and was connected to the Southwest China Region, specifically partnered with Yunnan University. This manuscript will share the strategies used to engage faculty and students from each partnering institution. Data collected by UA SSW over the five-year partnership will be utilised to contribute to the discussion of the extent to which Western knowledge and theory about social work education might usefully be applied to the Chinese context.

The Dayingezhuang gold deposit in the Jiaodong district, eastern margin of the North China Craton is hosted in Mesozoic granitic rocks and consists of quartz-sulfide veins/veinlets and sulfide disseminations in alteration envelopes. Previous studies mainly focused on the geochronology, sources of ore-forming fluids and metals to investigate the ore genesis. However, enrichment mechanism of Au and other associated trace metals remain unclear. In this study, we present detailed textures and in-situ LA-ICP-MS trace-element compositions of different generations of pyrite, as well as EMP analysis of Au-bearing minerals to discuss the occurrence and enrichment mechanism of Au at this deposit. Three generations of pyrite (Py1, Py2 and Py3) formed during three hydrothermal ore stages (I, II, and III) at Dayingezhuang. Py1 occurs as disseminations in sericitic alteration assemblages and is characterized by low Au (mean 0.15 ppm), Ag, As and Te contents. The time-resolved depth-concentration profiles indicate that Au in Py1 mainly occurs as nanoparticles and/or micron-sized inclusions. Py2 can be further divided into the early undeformed Py2a and later Py2b, which is the product of deformed Py2a with different degrees of brittle to plastic deformation and recrystallization. Py2a in pyrite-siderite-quartz veins is relatively enriched in invisible Au (mean 0.41 ppm), Ag, As, and Te compared to Py1, and contains numerous micron-sized Au inclusions. In contrast, Py2b contains lesser invisible Au (0.21 ppm) and host abundant gold minerals along the grain boundaries and microfractures. Py3 in polymetallic sulfide veins has little Au. As a whole, Au in pyrite is positively correlated with Ag and Te, which is consistent with the results of EMP analysis showing the occurrence of Au as electrum, native gold and minor petzite in pyrite. Such evidences show that the deformation and recrystallization of auriferous Py2a potentially caused local remobilization of Au (mainly as micron-sized inclusion Au) via solid-state ductile flow and subsequent reconcentration of Au in microfractures of Py2b. The pyrite deformation and Au remobilization events were suggested to be related to the continuous reactivation of the regional Zhaoping Fault contemporaneous with gold mineralization. Our study highlights the importance of remobilization and reconcentration of Au triggered by syn-ore tectonic activities at Dayingezhuang and possibly other Au deposits in the Jiaodong district.

Would the existence of extraterrestrial intelligent life (ETI) conflict in any way with Christian belief? We identify six areas of potential conflict. If there be no conflict in any of these areas—and we argue ultimately there is not—we are confident in declaring that there is no conflict, period. This conclusion underwrites the integrity of theological explorations into the existence of ETI, which has become a topic of increasing interest among theologians in recent years.

No existing review has synthesized key questions about acculturation experiences among international migrant workers. This review aimed to explore (1) What are global migrant workers’ experiences with acculturation and acculturative stress? (2) What are acculturative stress coping strategies used by migrant workers? And (3) how effective are these strategies for migrant workers in assisting their acculturation in the host countries? Peer-reviewed and gray literature, without time limitation, were searched in six databases and included if the study: focused on acculturative stress and coping strategies; was conducted with international migrant workers; was published in English; and was empirical. Eleven studies met the inclusion criteria. Three-layered themes of acculturation process and acculturative stress were identified as: individual layer; work-related layer; and social layer. Three key coping strategies were identified: emotion-focused; problem-focused; and appraisal-focused. These coping strategies were used flexibly to increase coping effectiveness and evidence emerged that a particular type of acculturative stress might be solved more effectively by a specific coping strategy. Migrant workers faced numerous challenges in their acculturative process. Understanding this process and their coping strategies could be used in developing research and interventions to improve the well-being of migrant workers.

In the face of the Covid-19 pandemic, the fashion industry was surprised and quickly had to adapt to digital media. However, the relationship between fashion and the multiplicity of screens is not new. Fashion emerged and took its first steps with Cinema, in Modernity. Although there are times when these two systems are further apart from each other, the alliance survived. To analyse contemporaneity, we take as main reference the studies of Gilles Lipovetsky, and his reflections on aesthetic capitalism. The fashion system has many Western fields of life, including art and technology. In this article we discuss how this relationship of fashion adapts and develops with aesthetic capitalism and post-digital art while we analyse representative artefacts from/about fashion. We propose to put the recent digital fashion artefacts in dialogue with post-digital aesthetics theories, discussing the blurred boundaries between the digital and the post-digital, and proposing the instantiation of a post-digital creation cycle applied to fashion artefacts.

Introduction This study aimed to investigate elite athletes’ mental well-being, and to ascertain whether the personal factor resilience and the social factor social support can play a role in promoting mental well-being and life satisfaction. In addition, this is one of the first studies to investigate well-being among elite athletes who are from a region belonging to an unrecognised National Olympic Committee and are not eligible to join the Olympic Games. Material and methods Eighty-four full-time elite athletes (37 males, 47 females) with mean age of 22.36 years old participated in this quantitative research study. Formal letters describing the purpose and organiser of the study were sent to the sport entities in Macao asking their permission for the researchers to contact the elite athletes to participate in this study. After gaining the permission, the elite athletes belonging to these entities were approached individually, to inform them of the purpose of the study and receive their consent. Results Regression revealed that emotional support and adaptability of resilience were strong positive predictors of mental well-being. Additionally, mental well-being was found to be a strong positive predictor of life satisfaction. The results reflected that in elite athletes possessing high adaptability and receiving more emotional support could help to maintain their mental well-being. Conclusions Implications (based on the findings) are discussed in order to provide insights for policy makers or coaches how to promote elite athletes’ mental well-being.