Showing papers by "Manchester Metropolitan University published in 2019"
TL;DR: A review of the current field and knowledge in regards to MFCs and the known mechanisms underpinning MFC technology, which allows bacteria to facilitate in electron transfer processes is given in this article.
Abstract: Research into alternative renewable energy generation is a priority, due to the ever-increasing concern of climate change. Microbial fuel cells (MFCs) are one potential avenue to be explored, as a partial solution towards combating the over-reliance on fossil fuel based electricity. Limitations have slowed the advancement of MFC development, including low power generation, expensive electrode materials and the inability to scale up MFCs to industrially relevant capacities. However, utilisation of new advanced electrode-materials (i.e. 2D nanomaterials), has promise to advance the field of electromicrobiology. New electrode materials coupled with a more thorough understanding of the mechanisms in which electrogenic bacteria partake in electron transfer could dramatically increase power outputs, potentially reaching the upper extremities of theoretical limits. Continued research into both the electrochemistry and microbiology is of paramount importance in order to achieve industrial-scale development of MFCs. This review gives an overview of the current field and knowledge in regards to MFCs and discusses the known mechanisms underpinning MFC technology, which allows bacteria to facilitate in electron transfer processes. This review focusses specifically on enhancing the performance of MFCs, with the key intrinsic factor currently limiting power output from MFCs being the rate of electron transfer to/from the anode; the use of advanced carbon-based materials as electrode surfaces is discussed.
434 citations
Hamburg University of Applied Sciences1, Manchester Metropolitan University2, Bournemouth University3, University of Beira Interior4, University of Malta5, Universidade Federal de Santa Maria6, Universidade de Passo Fundo7, Nottingham Trent University8, University of Aveiro9, Universidade Nova de Lisboa10
TL;DR: In this article, the authors explore the advantages of the introduction of the SDGs into teaching and suggest that it can catalyse the engagement of students in Higher Education Institutions (HEI) with the concepts of sustainability.
276 citations
TL;DR: In this paper, the authors identify the main sustainable development goals approached by experts from different geographic regions, according to their experience and research area, and discuss the relation between these goals and the main local issues and challenges of each region.
265 citations
TL;DR: In this paper, the role of the Extended Producer Responsibility (EPR) principle and its application may assist in fostering the collection and recycling of waste streams that contain plastic, and some recommendations that may be useful in enhancing extended producer responsibility.
208 citations
TL;DR: The results indicate that operating an IoT device in a temperature of −20 °C can shorten its life by about half, and with a 10% improvement in receiver sensitivity, NB-IoT 882 MHz and LoRaWAN can increase coverage by up to 398% and 142%, respectively, without adverse effects on the energy requirements.
Abstract: The rapid growth of Internet-of-Things (IoT) in the current decade has led to the development of a multitude of new access technologies targeted at low-power, wide area networks (LP-WANs). However, this has also created another challenge pertaining to technology selection. This paper reviews the performance of LP-WAN technologies for IoT, including design choices and their implications. We consider Sigfox, LoRaWAN, WavIoT, random phase multiple access (RPMA), narrowband IoT (NB-IoT), as well as LTE-M and assess their performance in terms of signal propagation, coverage and energy conservation. The comparative analyses presented in this paper are based on available data sheets and simulation results. A sensitivity analysis is also conducted to evaluate network performance in response to variations in system design parameters. Results show that each of RPMA, NB-IoT, and LTE-M incurs at least 9 dB additional path loss relative to Sigfox and LoRaWAN. This paper further reveals that with a 10% improvement in receiver sensitivity, NB-IoT 882 MHz and LoRaWAN can increase coverage by up to 398% and 142%, respectively, without adverse effects on the energy requirements. Finally, extreme weather conditions can significantly reduce the active network life of LP-WANs. In particular, the results indicate that operating an IoT device in a temperature of −20 °C can shorten its life by about half; 53% (WavIoT, LoRaWAN, Sigfox, NB-IoT, and RPMA) and 48% in LTE-M compared with environmental temperature of 40 °C.
204 citations
TL;DR: This work formalizes the task of securing big data and its scope, provides a taxonomy to categories threats to fog-based IoT systems, presents a comprehensive comparison of state-of-the-art contributions in the field according to their security service and recommends promising research directions for future investigations.
Abstract: The proliferation of inter-connected devices in critical industries, such as healthcare and power grid, is changing the perception of what constitutes critical infrastructure. The rising interconnectedness of new critical industries is driven by the growing demand for seamless access to information as the world becomes more mobile and connected and as the Internet of Things (IoT) grows. Critical industries are essential to the foundation of today’s society, and interruption of service in any of these sectors can reverberate through other sectors and even around the globe. In today’s hyper-connected world, the critical infrastructure is more vulnerable than ever to cyber threats, whether state sponsored, criminal groups or individuals. As the number of interconnected devices increases, the number of potential access points for hackers to disrupt critical infrastructure grows. This new attack surface emerges from fundamental changes in the critical infrastructure of organizations technology systems. This paper aims to improve understanding the challenges to secure future digital infrastructure while it is still evolving. After introducing the infrastructure generating big data, the functionality-based fog architecture is defined. In addition, a comprehensive review of security requirements in fog-enabled IoT systems is presented. Then, an in-depth analysis of the fog computing security challenges and big data privacy and trust concerns in relation to fog-enabled IoT are given. We also discuss blockchain as a key enabler to address many security related issues in IoT and consider closely the complementary interrelationships between blockchain and fog computing. In this context, this work formalizes the task of securing big data and its scope, provides a taxonomy to categories threats to fog-based IoT systems, presents a comprehensive comparison of state-of-the-art contributions in the field according to their security service and recommends promising research directions for future investigations.
169 citations
TL;DR: In this paper, current trends on textile recycling, the barriers impeding greater recycling, and outlines the socioeconomic advantages of moving towards a circular economy are discussed, together with some of the measures that may be used to further reduce the current waste deriving from the apparel sector.
166 citations
TL;DR: The authors posits a number of provocations for scholars and researchers engaged with Critical Disability Studies. And summarises some of the analytical twists and turns occurring over the last few years, concluding that "criticism of disability studies has been a hot topic in recent years".
Abstract: This article posits a number of provocations for scholars and researchers engaged with Critical Disability Studies. We summarise some of the analytical twists and turns occurring over the last few ...
155 citations
TL;DR: There is a substantial difference within studies that estimated the prevalence and incidence of LBP, which could inform healthcare policy makers to critically examine the data sources of prevalence and frequency studies; this in return might help for resource allocation to manage the condition.
Abstract: Low back pain (LBP) is a common health problem among adults of working age population, and its prevalence or incidence increases with increasing in age. The purpose of this review was to examine the real-world prevalence or incidence of LBP. A systematic review of the literature was conducted in accordance to the PRISMA guideline. Allied and Complementary Medicine Database, Cumulative Index of Nursing and Allied Health Literature, MEDLINE, SportDiscuss and Scopus electronic databases were searched using specifically developed search strategies to identify studies using patients’ electronic medical records published in English up to February 2019. The quality of the included studies was assessed using a tool that consists of ten items addressing a risk of bias. The search yielded 756 published studies, of which 13 were deemed relevant and were included in this review. The included studies reported incidence or prevalence data from Canada, United States of America (USA), Sweden, Belgium, Finland, Israel, and Netherlands. All the included studies were assessed to be methodologically sound (low risk of bias). The prevalence and incidence of LBP ranged from 1.4 to 20.0% and 0.024–7.0%, respectively. Three studies reported that the Odds of LBP in male patient was higher than their female counterparts (odds ratio > 1; range 1.11–17.29). Nine studies identified the risk factors of LBP to be age, sex, and race. The remaining four studies also listed high intensity of physical activity, high spinal load, lifting, bending, and twisting as the risk factors for LBP. The results of this study highlighted there is a substantial difference within studies that estimated the prevalence and incidence of LBP. This finding could inform healthcare policy makers to critically examine the data sources of prevalence and incidence studies; this in return might help for resource allocation to manage the condition. PROSPERO registration number: CRD42017078598, https://www.crd.york.ac.uk/prospero/
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147 citations
TL;DR: Advances from 2012 in the use of eMIPs in sensing platforms for the detection of biologically relevant materials are focused on, including the development of increased polymer layer dimensions for whole bacteria detection and theUse of mixed monomer compositions to increase selectivity toward analytes.
Abstract: The accurate detection of biological materials has remained at the forefront of scientific research for decades. This includes the detection of molecules, proteins, and bacteria. Biomimetic sensors look to replicate the sensitive and selective mechanisms that are found in biological systems and incorporate these properties into functional sensing platforms. Molecularly imprinted polymers (MIPs) are synthetic receptors that can form high affinity binding sites complementary to the specific analyte of interest. They utilise the shape, size, and functionality to produce sensitive and selective recognition of target analytes. One route of synthesizing MIPs is through electropolymerization, utilising predominantly constant potential methods or cyclic voltammetry. This methodology allows for the formation of a polymer directly onto the surface of a transducer. The thickness, morphology, and topography of the films can be manipulated specifically for each template. Recently, numerous reviews have been published in the production and sensing applications of MIPs; however, there are few reports on the use of electrosynthesized MIPs (eMIPs). The number of publications and citations utilising eMIPs is increasing each year, with a review produced on the topic in 2012. This review will primarily focus on advancements from 2012 in the use of eMIPs in sensing platforms for the detection of biologically relevant materials, including the development of increased polymer layer dimensions for whole bacteria detection and the use of mixed monomer compositions to increase selectivity toward analytes.
144 citations
TL;DR: The electrochemical performance of the developed system was similar or better than those obtained using commercial glassy carbon and screen-printed carbon electrodes and represents a significant advance in AM (3D-printing) technology for analytical chemistry.
Abstract: Herein, we report a complete additively manufactured (AM) electrochemical sensing platform. In this approach, a fully AM/3D-printed electrochemical system, using a conventional low-cost 3D printer (fused deposition modeling) fabricating both the conductive electrodes and the nonconductive/chemically inert electrochemical cell is reported. The electrodes (working, counter, and pseudo-reference) are AM using a conductive fused-filament comprised of a mixture of carbon black nanoparticles and polylactic acid (CB/PLA). AM components partially coated with silver ink presented a similar behavior to a conventional Ag/AgCl reference electrode. The performance of the AM working electrode was evaluated after a simple and fast polishing procedure on sandpaper and electrochemical activation in a NaOH solution (0.5 mol L-1). Following the electrochemical activation step, a considerable improvement in the electrochemical behavior (current intensity and voltammetric profile) was obtained for model analytes, such as dopamine, hexaammineruthenium(III) chloride, ferricyanide/ferrocyanide, uric acid, and ascorbic acid. Excellent repeatability (RSD = 0.4%, N = 10) and limit of detection (0.1 μmol L-1) were obtained with the all complete AM electrochemical system for dopamine analysis. The electrochemical performance of the developed system (after simple electrochemical activation of the working electrode) was similar or better than those obtained using commercial glassy carbon and screen-printed carbon electrodes. The results shown here represents a significant advance in AM (3D printing) technology for analytical chemistry.
Mayo Clinic1, Sandia National Laboratories2, University of New Mexico3, Manchester Metropolitan University4, Swansea University5, University of Strathclyde6, University of Liverpool7, Queen's University Belfast8, Leidos9, Trinity College, Dublin10, SINTEF11, Swiss Federal Laboratories for Materials Science and Technology12, University of Grenoble13, Karolinska Institutet14, Technical University of Denmark15, Stockholm University16, University of California, Los Angeles17, Keele University18, University of North Carolina at Chapel Hill19, Chinese Academy of Sciences20, University of Jena21, University of Texas Southwestern Medical Center22, University of Texas at Austin23, Santa Clara University24, University of Birmingham25, Newcastle University26, University of Porto27, University of Helsinki28, MedImmune29, Harvard University30, University of Pittsburgh31, Tel Aviv University32, Northeastern University33, University of Santiago de Compostela34, University of Fribourg35, University of Oklahoma36, Zhejiang University37, Wake Forest University38, University of Brescia39, Houston Methodist Hospital40, Cornell University41, University of California, San Diego42, University of Texas at Dallas43, Princess Margaret Cancer Centre44
TL;DR: Following the authors' call to join in the discussion over the suitability of implementing a reporting checklist for bio–nano papers, the community responds.
Abstract: Following our call to join in the discussion over the suitability of implementing a reporting checklist for bio–nano papers, the community responds.
TL;DR: The association of increased neuroinflammation during the progression of MCI and AD, relative to HCs, is supported, and an inverse association between TSPO levels in the parietal region and Mini-Mental State Examination scores in AD subjects is identified.
TL;DR: A patch-based CNN method for automated mass detection in full-field digital mammograms (FFDM) and the proposed framework improves upon mass detection results described in the literature on the INbreast database, in terms of both TPR and FPI.
Abstract: With recent advances in the field of deep learning, the use of convolutional neural networks (CNNs) in medical imaging has become very encouraging. The aim of our paper is to propose a patch-based CNN method for automated mass detection in full-field digital mammograms (FFDM). In addition to evaluating CNNs pretrained with the ImageNet dataset, we investigate the use of transfer learning for a particular domain adaptation. First, the CNN is trained using a large public database of digitized mammograms (CBIS-DDSM dataset), and then the model is transferred and tested onto the smaller database of digital mammograms (INbreast dataset). We evaluate three widely used CNNs (VGG16, ResNet50, InceptionV3) and show that the InceptionV3 obtains the best performance for classifying the mass and nonmass breast region for CBIS-DDSM. We further show the benefit of domain adaptation between the CBIS-DDSM (digitized) and INbreast (digital) datasets using the InceptionV3 CNN. Mass detection evaluation follows a fivefold cross-validation strategy using free-response operating characteristic curves. Results show that the transfer learning from CBIS-DDSM obtains a substantially higher performance with the best true positive rate (TPR) of 0.98 ± 0.02 at 1.67 false positives per image (FPI), compared with transfer learning from ImageNet with TPR of 0.91 ± 0.07 at 2.1 FPI. In addition, the proposed framework improves upon mass detection results described in the literature on the INbreast database, in terms of both TPR and FPI.
TL;DR: This work designs deep learning methods for real-time DFU localization using an extensive database of 1775 images of DFU to produce a robust deep learning model that can be further improved with a more extensive data set.
Abstract: Current practice for diabetic foot ulcers (DFU) screening involves detection and localization by podiatrists. Existing automated solutions either focus on segmentation or classification. In this work, we design deep learning methods for real-time DFU localization. To produce a robust deep learning model, we collected an extensive database of 1775 images of DFU. Two medical experts produced the ground truths of this data set by outlining the region of interest of DFU with an annotator software. Using five-fold cross-validation, overall, faster R-CNN with InceptionV2 model using two-tier transfer learning achieved a mean average precision of 91.8%, the speed of 48 ms for inferencing a single image and with a model size of 57.2 MB. To demonstrate the robustness and practicality of our solution to real-time prediction, we evaluated the performance of the models on a NVIDIA Jetson TX2 and a smartphone app. This work demonstrates the capability of deep learning in real-time localization of DFU, which can be further improved with a more extensive data set.
TL;DR: A full duplex non-orthogonal multiple access (FD-NOMA)-based decentralized V2X system model is introduced and the approximate closed-form expressions with arbitrary small errors are given to solve the computation complicated problems of the involved exponential integral functions.
Abstract: In order to meet the requirements of massively connected devices, different quality of services (QoS), various transmit rates, and ultra-reliable and low latency communications (URLLC) in vehicle-to-everything (V2X) communications, we introduce a full duplex non-orthogonal multiple access (FD-NOMA)-based decentralized V2X system model. We, then, classify the V2X communications into two scenarios and give their exact capacity expressions. To solve the computation complicated problems of the involved exponential integral functions, we give the approximate closed-form expressions with arbitrary small errors. Numerical results indicate the validness of our derivations. Our analysis has that the accuracy of our approximate expressions is controlled by the division of $\frac {\pi }{2}$ in the urban and crowded scenarios, and the truncation point ${T}$ in the suburban and remote scenarios. Numerical results manifest that: 1) increasing the number of V2X device, NOMA power, and Rician factor value yields a better capacity performance; 2) effect of FD-NOMA is determined by the FD self-interference and the channel noise; and 3) FD-NOMA has a better latency performance compared with other schemes.
TL;DR: The first approved treatment is an intracerebroventricularly administered enzyme for neuronal ceroid lipofuscinosis type 2 disease that delays symptom progression and efforts are underway to make similar progress for other forms of the disorder.
Abstract: Treatment of the neuronal ceroid lipofuscinoses, also known as Batten disease, is at the start of a new era because of diagnostic and therapeutic advances relevant to this group of inherited neurodegenerative and life-limiting disorders that affect children. Diagnosis has improved with the use of comprehensive DNA-based tests that simultaneously screen for many genes. The identification of disease-causing mutations in 13 genes provides a basis for understanding the molecular mechanisms underlying neuronal ceroid lipofuscinoses, and for the development of targeted therapies. These targeted therapies include enzyme replacement therapies, gene therapies targeting the brain and the eye, cell therapies, and pharmacological drugs that could modulate defective molecular pathways. Such therapeutic developments have the potential to enable earlier diagnosis and better targeted therapeutic management. The first approved treatment is an intracerebroventricularly administered enzyme for neuronal ceroid lipofuscinosis type 2 disease that delays symptom progression. Efforts are underway to make similar progress for other forms of the disorder.
University of Leeds1, Queen's University Belfast2, Carleton University3, University of York4, University of Exeter5, University of Helsinki6, Adam Mickiewicz University in Poznań7, Manchester Metropolitan University8, University of Gloucestershire9, Babeș-Bolyai University10, Geological Survey of Canada11, Aarhus University12, University of Łódź13, University of Tartu14, University of Southampton15, University of Aberdeen16, Moscow State University17, Landcare Research18, Russian Academy of Sciences19, Geological Survey of Sweden20, Penza State University21, University of Waterloo22
TL;DR: In this article, the authors analyse testate amoeba-derived hydrological reconstructions from 31 peatlands across Britain, Ireland, Scandinavia and Continental Europe to examine changes in peatland surface wetness during the last 2,000 years.
Abstract: Climate warming and human impacts are thought to be causing peatlands to dry, potentially converting them from sinks to sources of carbon. However, it is unclear whether the hydrological status of peatlands has moved beyond their natural envelope. Here we show that European peatlands have undergone substantial, widespread drying during the last ~300 years. We analyse testate amoeba-derived hydrological reconstructions from 31 peatlands across Britain, Ireland, Scandinavia and Continental Europe to examine changes in peatland surface wetness during the last 2,000 years. We find that 60% of our study sites were drier during the period 1800–2000 CE than they have been for the last 600 years, 40% of sites were drier than they have been for 1,000 years and 24% of sites were drier than they have been for 2,000 years. This marked recent transition in the hydrology of European peatlands is concurrent with compound pressures including climatic drying, warming and direct human impacts on peatlands, although these factors vary among regions and individual sites. Our results suggest that the wetness of many European peatlands may now be moving away from natural baselines. Our findings highlight the need for effective management and restoration of European peatlands.
TL;DR: In this paper, the authors investigated a sample of plastics-converting companies in Emilia Romagna region (Italy), which stand out for radical innovations in business models, with the aim to catalyse changes in current manufacturing practices, and provided empirical support for a positive relationship between business strategies and the use of non-virgin plastic materials.
TL;DR: In this paper, a comprehensive review of the recent progress with cobalt-based electrodes (both as an anode and cathode material) used in SIBs is presented.
TL;DR: Findings show that, under the current setting of an underdeveloped land use planning apparatus, a long-term scenario of high economic growth will increase built-up surfaces in the region by almost 24%, accompanied by a notable decrease in natural areas and cropland.
Hamburg University of Applied Sciences1, Manchester Metropolitan University2, Universiti Teknologi Petronas3, University of Ibadan4, University of Aveiro5, Addis Ababa University6, Pontifical Catholic University of Peru7, University of the Republic8, University of Guyana9, University of Nairobi10, Ardhi University11, Khulna University of Engineering & Technology12
TL;DR: The aim of this paper is to analyse the extent to which cities in a sample of developing countries are attempting to pursue climate change adaptation and the problems which hinder this process, and suggests the use of transformative approaches which may be adopted.
TL;DR: A shift of perspective from ‘theories’ as products to “theorising” as a process can enable empirical researchers to capitalise on the two-way relationships between empirical data and different levels of theory and contribute to the advancement of knowledge.
Abstract: Theories occupy different positions in the scientific circle of enquiry as they vary in scope, abstraction, and complexity. Mid-range theories play a crucial bridging role between raw empirical observations and all-encompassing grand-theoretical schemes. A shift of perspective from ‘theories’ as products to ‘theorising’ as a process can enable empirical researchers to capitalise on the two-way relationships between empirical data and different levels of theory and contribute to the advancement of knowledge. This can be facilitated by embracing theoretically informative (in addition to merely theoretically informed) research, developing mechanism-based explanations, and broadening the repertoire of grand-theoretical orientations.
TL;DR: Variance decomposition results do not rule out these effects of urbanization and globalization on CO2 emissions for South Africa in future, but only long-run significant emissions effect of globalization was noted.
TL;DR: In this article, the authors unpack the experience construct into its core constituent elements, namely, emotions, and propose a framework that unpacks memorable experiences into their constituent element, i.e., emotions.
Abstract: Purpose This paper aims to stimulate the discussion in the fields of hospitality, tourism and leisure on what exactly constitutes “an experience” and how to measure it; the authors unpack the experience construct into its core constituent elements, namely, emotions. Design/methodology/approach The paper reviews insights from psychology and cognitive neuroscience that define experiences as a fine-grained temporal succession of emotions that occur during an experiential episode. Limitations of current methods for measuring experiences are discussed, after which biometric and neuroscientific methods are reviewed that are optimally geared toward measuring emotions, as they occur during an experience with fine temporal detail. Findings An overview is presented of the available studies within the fields of hospitality, tourism and leisure that use these methodologies. These studies show that using these methodologies provides a fruitful methodological approach to measuring experiences in real time. Practical implications Companies are constantly seeking to create memorable experiences for their customers. The proposed research methodologies allow companies to get a more fine-grained image of what impacts customers over the course of their experience and to actively integrate the use of emotions into creating experiences, as emotions are key to making them memorable. Originality/value The paper sketches the contours of a rapidly emerging framework that unpacks memorable experiences into their constituent element – emotions. It is proposed that this will contribute to a deeper understanding of how consumers experience offerings in the hospitality, tourism and leisure industry.
TL;DR: In their recent systematic review of co-production and co-creation in this journal, Voorberg, Bekkers, and Tummers as mentioned in this paper called co-productivity a "magic concept".
Abstract: In their recent systematic review of co-production and co-creation in this journal, Voorberg, Bekkers, and Tummers (2015) called co-creation a ‘magic concept’, to justify both its extraordinarily i...
University of Southern Denmark1, Max Planck Society2, Manchester Metropolitan University3, Radboud University Nijmegen4, Tel Aviv University5, University of Lyon6, University of California, Berkeley7, University of Melbourne8, Spanish National Research Council9, Centre national de la recherche scientifique10, Australian National University11, University of Oxford12, Global Biodiversity Information Facility13, University of Queensland14, Duke University15
TL;DR: The Demographic Species Knowledge Index is developed, which classifies the available information for 32,144 (97%) of extant described mammals, birds, reptiles, and amphibians, and shows that data from zoos and aquariums in the Species360 network can significantly improve knowledge for an almost eightfold gain.
Abstract: Biodiversity loss is a major challenge. Over the past century, the average rate of vertebrate extinction has been about 100-fold higher than the estimated background rate and population declines continue to increase globally. Birth and death rates determine the pace of population increase or decline, thus driving the expansion or extinction of a species. Design of species conservation policies hence depends on demographic data (e.g., for extinction risk assessments or estimation of harvesting quotas). However, an overview of the accessible data, even for better known taxa, is lacking. Here, we present the Demographic Species Knowledge Index, which classifies the available information for 32,144 (97%) of extant described mammals, birds, reptiles, and amphibians. We show that only 1.3% of the tetrapod species have comprehensive information on birth and death rates. We found no demographic measures, not even crude ones such as maximum life span or typical litter/clutch size, for 65% of threatened tetrapods. More field studies are needed; however, some progress can be made by digitalizing existing knowledge, by imputing data from related species with similar life histories, and by using information from captive populations. We show that data from zoos and aquariums in the Species360 network can significantly improve knowledge for an almost eightfold gain. Assessing the landscape of limited demographic knowledge is essential to prioritize ways to fill data gaps. Such information is urgently needed to implement management strategies to conserve at-risk taxa and to discover new unifying concepts and evolutionary relationships across thousands of tetrapod species.
TL;DR: In this paper, a theoretical review examines how democratic education is conceptualized within educational scholarship, focusing on three hundred and seventy-seven articles published in English language peer-reviewed journals.
Abstract: This theoretical review examines how democratic education is conceptualized within educational scholarship. Three hundred and seventy-seven articles published in English language peer-reviewed jour...
TL;DR: Adopting an anti-inflammatory diet may be an effective intervention or preventative means of reducing depression risk and symptoms.
14 May 2019
TL;DR: The evaluation protocols for the two challenge tasks, the datasets involved, and an analysis of the best performing works from the participating teams are outlined, together with a summary of results.
Abstract: Automatic facial micro-expression (ME) analysis is a growing field of research that has gained much attention in the last five years. With many recent works testing on limited data, there is a need to spur better approaches that are both robust and effective. This paper summarises the 2nd Facial Micro-Expression Grand Challenge (MEGC 2019) held in conjunction with the 14th IEEE Conference on Automatic Face and Gesture Recognition (FG) 2019. In this workshop, we proposed challenges for two micro-expression (ME) tasks— spotting and recognition, with the aim of encouraging rigorous evaluation and development of new robust techniques that can accommodate data captured across a variety of settings. In this paper, we outline the evaluation protocols for the two challenge tasks, the datasets involved, and an analysis of the best performing works from the participating teams, together with a summary of results. Finally, we highlight some possible future directions.