University of East London

This article explores various analytical issues involved in conceptualizing the interrelationships of gender, class, race and ethnicity and other social divisions. It compares the debate on these issues that took place in Britain in the 1980s and around the 2001 UN World Conference Against Racism. It examines issues such as the relative helpfulness of additive or mutually constitutive models of intersectional social divisions; the different analytical levels at which social divisions need to be studied, their ontological base and their relations to each other. The final section of the article attempts critically to assess a specific intersectional methodological approach for engaging in aid and human rights work in the South.

Machine learning techniques are being widely used to develop an intrusion detection system (IDS) for detecting and classifying cyberattacks at the network-level and the host-level in a timely and automatic manner. However, many challenges arise since malicious attacks are continually changing and are occurring in very large volumes requiring a scalable solution. There are different malware datasets available publicly for further research by cyber security community. However, no existing study has shown the detailed analysis of the performance of various machine learning algorithms on various publicly available datasets. Due to the dynamic nature of malware with continuously changing attacking methods, the malware datasets available publicly are to be updated systematically and benchmarked. In this paper, a deep neural network (DNN), a type of deep learning model, is explored to develop a flexible and effective IDS to detect and classify unforeseen and unpredictable cyberattacks. The continuous change in network behavior and rapid evolution of attacks makes it necessary to evaluate various datasets which are generated over the years through static and dynamic approaches. This type of study facilitates to identify the best algorithm which can effectively work in detecting future cyberattacks. A comprehensive evaluation of experiments of DNNs and other classical machine learning classifiers are shown on various publicly available benchmark malware datasets. The optimal network parameters and network topologies for DNNs are chosen through the following hyperparameter selection methods with KDDCup 99 dataset. All the experiments of DNNs are run till 1,000 epochs with the learning rate varying in the range [0.01-0.5]. The DNN model which performed well on KDDCup 99 is applied on other datasets, such as NSL-KDD, UNSW-NB15, Kyoto, WSN-DS, and CICIDS 2017, to conduct the benchmark. Our DNN model learns the abstract and high-dimensional feature representation of the IDS data by passing them into many hidden layers. Through a rigorous experimental testing, it is confirmed that DNNs perform well in comparison with the classical machine learning classifiers. Finally, we propose a highly scalable and hybrid DNNs framework called scale-hybrid-IDS-AlertNet which can be used in real-time to effectively monitor the network traffic and host-level events to proactively alert possible cyberattacks.

Abstract There are many ecological diversity measures, but their suitability for use with highly diverse bacterial communities is unclear and seldom considered. We assessed a range of species richness and evenness/dominance indices, and the use of species abundance models using samples of bacteria from zinc-contaminated and control soils. Bacteria were assigned to operational taxonomic units (OTUs) using amplified ribosomal DNA restriction analysis of 236 clones from each soil. The reduced diversity apparent in the contaminated soil was reflected by the diversity indices to varying degrees. The number of clones analysed and the weighting given to rare vs. abundant OTUs are the most important considerations when selecting measures. Our preferences, arrived at using theory and practical experience, include: the log series index alpha; the Q statistic (but only if coverage is 50% or more); the Berger-Parker and Simpson's indices, although their ecological relevance may be limited; and, unexpectedly, the Shannon-Wiener and Shannon evenness indices, even though their meanings may not be clear and their values inaccurate when coverage is low. For extrapolation, the equation for the log series distribution seems the best for extrapolating from OTU accumulation curves while non-parametric methods, such as Chao 1, show promise for estimating total OTU richness. Due to a preponderance of single-occurrence OTUs, none of the five species abundance models fit the OTU abundance distribution of the control soil, but both the log and log normal models fit the less diverse contaminated soil. Species abundance models are useful, irrespective of coverage, because they address the whole distribution of a sample, aiding comparison by revealing overall trends as well as specific changes in particular abundance classes.

In this paper we take a fresh look at the empirical evidence on the relationship between financial development and economic growth with a view to identifying outstanding issues and offering some suggestions about how these may be addressed in the future. To illustrate our suggestions we also present some new evidence utilising the proposed approaches. We examine the empirical literature from two angles. The first is the issue of whether, how and to what extent the financial system can contribute to the process of economic growth. Questions about the association amongst financial deepening, investment, and the efficiency of capital fall in this category. The question of causality between finance and growth can also be considered from this perspective. The second angle relates to the question of whether financial liberalisation can stimulate investment and growth. Evidence on this question has been adduced from countries where financial reforms took place. There is,...

Abstract The extent of human‐induced change and damage to Earth's ecosystems renders ecosystem repair an essential part of our future survival strategy, and this demands that restoration ecology provide effective conceptual and practical tools for this task. We argue that restoration ecology has to be an integral component of land management in today's world, and to be broadly applicable, has to have a clearly articulated conceptual basis. This needs to recognize that most ecosystems are dynamic and hence restoration goals cannot be based on static attributes. Setting clear and achievable goals is essential, and these should focus on the desired characteristics for the system in the future, rather than in relation to what these were in the past. Goal setting requires that there is a clear understanding of the restoration options available (and the relative costs of different options). The concept of restoration thresholds suggests that options are determined by the current state of the system in relation to biotic and abiotic thresholds. A further important task is the development of effective and easily measured success criteria. Many parameters could be considered for inclusion in restoration success criteria, but these are often ambiguous or hard to measure. Success criteria need to relate clearly back to specific restoration goals. If restoration ecology is to be successfully practiced as part of humanity's response to continued ecosystem change and degradation, restoration ecologists need to rise to the challenges of meshing science, practice and policy. Restoration ecology is likely to be one of the most important fields of the coming century.

"This book is a critical and ethnographic study of camgirls: women who broadcast themselves over the web for the general public while trying to cultivate a measure of celebrity in the process. The narrative follows that of the camgirl phenomenon, beginning with the earliest experiments in personal homecamming and ending with the newest forms of identity and community being articulated through social networking sites like Live Journal, YouTube, MySpace, and Facebook. It is grounded in interviews, performance analysis of events transpiring between camgirls and their viewers, and the author's own experiences as an ersatz camgirl while conducting the research."--BOOK JACKET.

Finding robust brain substrates of mood disorders is an important target for research. The degree to which major depression (MDD) and bipolar disorder (BD) are associated with common and/or distinct patterns of volumetric changes is nevertheless unclear. Furthermore, the extant literature is heterogeneous with respect to the nature of these changes. We report a meta-analysis of voxel-based morphometry (VBM) studies in MDD and BD. We identified studies published up to January 2015 that compared grey matter in MDD (50 data sets including 4101 individuals) and BD (36 data sets including 2407 individuals) using whole-brain VBM. We used statistical maps from the studies included where available and reported peak coordinates otherwise. Group comparisons and conjunction analyses identified regions in which the disorders showed common and distinct patterns of volumetric alteration. Both disorders were associated with lower grey-matter volume relative to healthy individuals in a number of areas. Conjunction analysis showed smaller volumes in both disorders in clusters in the dorsomedial and ventromedial prefrontal cortex, including the anterior cingulate cortex and bilateral insula. Group comparisons indicated that findings of smaller grey-matter volumes relative to controls in the right dorsolateral prefrontal cortex and left hippocampus, along with cerebellar, temporal and parietal regions were more substantial in major depression. These results suggest that MDD and BD are characterised by both common and distinct patterns of grey-matter volume changes. This combination of differences and similarities has the potential to inform the development of diagnostic biomarkers for these conditions.

Journal Article Nitroimidazole drugs-action and resistance mechanisms I. Mechanism of action Get access David I. Edwards David I. Edwards Chemotherapy Research Unit, University of East LondonRomford Road, London E15 4LZ, UK Search for other works by this author on: Oxford Academic PubMed Google Scholar Journal of Antimicrobial Chemotherapy, Volume 31, Issue 1, January 1993, Pages 9–20, https://doi.org/10.1093/jac/31.1.9 Published: 01 January 1993 Article history Received: 06 March 1992 Accepted: 11 May 1992 Published: 01 January 1993

BACKGROUND: Inequalities in health are acknowledged in many developed countries, whereby disadvantaged groups systematically suffer from worse health outcomes such as lower life expectancy than non-disadvantaged groups. Engaging members of disadvantaged communities in public health initiatives has been suggested as a way to reduce health inequities. This systematic review was conducted to evaluate the effectiveness of public health interventions that engage the community on a range of health outcomes across diverse health issues. METHODS: We searched the following sources for systematic reviews of public health interventions: Cochrane CDSR and CENTRAL, Campbell Library, DARE, NIHR HTA programme website, HTA database, and DoPHER. Through the identified reviews, we collated a database of primary studies that appeared to be relevant, and screened the full-text documents of those primary studies against our inclusion criteria. In parallel, we searched the NHS EED and TRoPHI databases for additional primary studies. For the purposes of these analyses, study design was limited to randomised and non-randomised controlled trials. Only interventions conducted in OECD countries and published since 1990 were included. We conducted a random effects meta-analysis of health behaviour, health consequences, self-efficacy, and social support outcomes, and a narrative summary of community outcomes. We tested a range of moderator variables, with a particular emphasis on the model of community engagement used as a potential moderator of intervention effectiveness. RESULTS: Of the 9,467 primary studies scanned, we identified 131 for inclusion in the meta-analysis. The overall effect size for health behaviour outcomes is d = .33 (95% CI .26, .40). The interventions were also effective in increasing health consequences (d = .16, 95% CI .06, .27); health behaviour self-efficacy (d = .41, 95% CI .16, .65) and perceived social support (d = .41, 95% CI .23, .65). Although the type of community engagement was not a significant moderator of effect, we identified some trends across studies. CONCLUSIONS: There is solid evidence that community engagement interventions have a positive impact on a range of health outcomes across various conditions. There is insufficient evidence to determine whether one particular model of community engagement is more effective than any other.

We describe a quantitative evaluation of the performance of different classifiers in the task of automatic age estimation. In this context, we generate a statistical model of facial appearance, which is subsequently used as the basis for obtaining a compact parametric description of face images. The aim of our work is to design classifiers that accept the model-based representation of unseen images and produce an estimate of the age of the person in the corresponding face image. For this application, we have tested different classifiers: a classifier based on the use of quadratic functions for modeling the relationship between face model parameters and age, a shortest distance classifier, and artificial neural network based classifiers. We also describe variations to the basic method where we use age-specific and/or appearance specific age estimation methods. In this context, we use age estimation classifiers for each age group and/or classifiers for different clusters of subjects within our training set. In those cases, part of the classification procedure is devoted to choosing the most appropriate classifier for the subject/age range in question, so that more accurate age estimates can be obtained. We also present comparative results concerning the performance of humans and computers in the task of age estimation. Our results indicate that machines can estimate the age of a person almost as reliably as humans.

In this article, we assess the structural equivalence of the Zimbardo Time Perspective Inventory (ZTPI) across 26 samples from 24 countries ( N = 12,200). The ZTPI is proven to be a valid and reliable index of individual differences in time perspective across five temporal categories: Past Negative, Past Positive, Present Fatalistic, Present Hedonistic, and Future. We obtained evidence for invariance of 36 items (out of 56) and also the five-factor structure of ZTPI across 23 countries. The short ZTPI scales are reliable for country-level analysis, whereas we recommend the use of the full scales for individual-level analysis. The short version of ZTPI will further promote integration of research in the time perspective domain in relation to many different psycho-social processes.

Background Preterm birth may leave the brain vulnerable to dysfunction. Knowledge of future neurodevelopmental delay in children born with various degrees of prematurity is needed to inform practice and policy. Objective To quantify the long‐term cognitive, motor, behavioural and academic performance of children born with different degrees of prematurity compared with term‐born children. Search strategy PubMed and Embase were searched from January 1980 to December 2016 without language restrictions. Selection criteria Observational studies that reported neurodevelopmental outcomes from 2 years of age in children born preterm compared with a term‐born cohort. Data collection and analysis We pooled individual estimates of standardised mean differences ( SMD ) and odds ratios ( OR ) with 95% confidence intervals using a random effects model. Main results We included 74 studies (64 061 children). Preterm children had lower cognitive scores for FSIQ ( SMD : −0.70; 95% CI : −0.73 to −0.66), PIQ ( SMD : −0.67; 95% CI : −0.73 to −0.60) and VIQ ( SMD : −0.53; 95% CI : −0.60 to −0.47). Lower scores for preterm children in motor skills, behaviour, reading, mathematics and spelling were observed at primary school age, and this persisted to secondary school age, except for mathematics. Gestational age at birth accounted for 38–48% of the observed IQ variance. ADHD was diagnosed twice as often in preterm children ( OR : 1.6; 95% CI : 1.3–1.8), with a differential effect observed according to the severity of prematurity ( I 2 = 49.4%, P = 0.03). Conclusions Prematurity of any degree affects the cognitive performance of children born preterm. The poor neurodevelopment persists at various ages of follow up. Parents, educators, healthcare professionals and policy makers need to take into account the additional academic, emotional and behavioural needs of these children. Tweetable abstract Adverse effect of preterm birth on a child's neurodevelopment persists up to adulthood.

The article argues that everyday bordering has become a major technology of control of both social diversity and discourses on diversity, in a way that threatens the convivial co-existence of pluralist societies, especially in metropolitan cities, as well as reconstructs everyday citizenship. The article begins with an outline of a theoretical and methodological framework, which explores bordering, the politics of belonging and a situated intersectional perspective for the study of the everyday. It then analyses the shift in focus of recent UK immigration legislation from the external, territorial border to the internal border, incorporating technologies of everyday bordering in which ordinary citizens are demanded to become either border-guards and/or suspected illegitimate border crossers. We illustrate our argument in the area of employment examining the impact of the requirements of the immigration legislation from the situated gazes of professional border officers, employers and employees in their bordering encounters.

A sample of 257 young people aged between eight and 18 who had undertaken individual instrumental tuition were interviewed in depth about their performing history from the start of playing. A subset of 94 of these individuals also kept a practice diary for a 42‐week period. The data collected allowed estimates to be calculated of the amount of time devoted to various types of practice and other activities. The sample was selected in order to encompass a wide range of levels of musical achievement, from pupils at a highly selective specialist music school through to individuals who had abandoned instrumental study after less than a year of formal instruction. Data about formal examination successes confirmed the very wide range of achievement in the sample. It was discovered that there was a strong relationship between musical achievement and the amount of formal practice undertaken. Weaker relationships were discovered between achievement and amount of informal playing. There was no evidence that high achievers were able to gain a given level of examination success on less practice than low achievers. High achievers tended to be more consistent in their pattern of practice from week to week, and tended to concentrate technical practice in the mornings. These data lend strong support to the theory that formal effortful practice is a principal determinant of musical achievement.

The current prominence and future promises of the Internet of Things (IoT), Internet of Everything (IoE) and Internet of Nano Things (IoNT) are extensively reviewed and a summary survey report is presented. The analysis clearly distinguishes between IoT and IoE which are wrongly considered to be the same by many people. Upon examining the current advancement in the fields of IoT, IoE and IoNT, the paper presents scenarios for the possible future expansion of their applications.

BACKGROUND: Transthyretin amyloidosis cardiomyopathy (ATTR-CM) is an increasingly recognized cause of heart failure in older individuals. We sought to characterize the natural history of ATTR-CM and compare outcomes and quality of life among patients with acquired and hereditary forms of the disease. METHODS: We studied 711 patients with wild-type ATTR-CM, 205 with hereditary ATTR-CM associated with the V1221 variant (V122I-hATTR-CM), and 118 with non-V122I-hATTR-CM at the UK National Amyloidosis Center between 2000 and 2017. Patients underwent prospective protocolized evaluations comprising assessment of cardiac parameters, functional status by 6-minute walk test, quality of life according to the Kansas City Cardiomyopathy Questionnaire, and survival. Hospital service usage pre- and postdiagnosis was established using English central health records in a subset of patients. RESULTS: There was substantial diagnostic delay, with patients using hospital services a median (interquartile range) of 17 (9-27) times during the 3 years before diagnosis, by which time quality of life was poor; diagnosis of wild-type ATTR-CM was delayed >4 years after presentation with cardiac symptoms in 42% of cases. Patients with V122I-hATTR-CM were more impaired functionally ( P<0.001) and had worse measures of cardiac disease ( P<0.001) at the time of diagnosis, a greater decline in quality of life, and poorer survival ( P<0.001) in comparison with the other subgroups. CONCLUSIONS: ATTR-CM is an inexorably progressive and eventually fatal cardiomyopathy associated with poor quality of life. Diagnosis is often delayed for many years after symptoms develop. Improved awareness and wider use of recently validated diagnostic imaging methods are urgently required for patients to benefit from recent therapeutic developments.

In this paper, we develop and test a model of diversification mode choice (how firms decide between acquisitions and greenfield start-up ventures) which includes institutional, cultural, and transaction cost variables. Using a sample of Japanese firms entering western Europe, our results show the model correctly predicts over eighty-seven percent of the mode choices. Thus, we provide strong initial evidence to support using institutional, cultural and transaction cost variables to predict firms’ choices between acquisitions and greenfield start-ups in international expansion. Our findings also suggest that organizations which have developed strong intangible capabilities may be able to more readily leverage these capabilities through greenfield start-ups. Copyright © 2000 John Wiley & Sons, Ltd.

BACKGROUND: Loss of arm function is a common problem after stroke. Robot-assisted training might improve arm function and activities of daily living. We compared the clinical effectiveness of robot-assisted training using the MIT-Manus robotic gym with an enhanced upper limb therapy (EULT) programme based on repetitive functional task practice and with usual care. METHODS: RATULS was a pragmatic, multicentre, randomised controlled trial done at four UK centres. Stroke patients aged at least 18 years with moderate or severe upper limb functional limitation, between 1 week and 5 years after their first stroke, were randomly assigned (1:1:1) to receive robot-assisted training, EULT, or usual care. Robot-assisted training and EULT were provided for 45 min, three times per week for 12 weeks. Randomisation was internet-based using permuted block sequences. Treatment allocation was masked from outcome assessors but not from participants or therapists. The primary outcome was upper limb function success (defined using the Action Research Arm Test [ARAT]) at 3 months. Analyses were done on an intention-to-treat basis. This study is registered with the ISRCTN registry, number ISRCTN69371850. FINDINGS: Between April 14, 2014, and April 30, 2018, 770 participants were enrolled and randomly assigned to either robot-assisted training (n=257), EULT (n=259), or usual care (n=254). The primary outcome of ARAT success was achieved by 103 (44%) of 232 patients in the robot-assisted training group, 118 (50%) of 234 in the EULT group, and 85 (42%) of 203 in the usual care group. Compared with usual care, robot-assisted training (adjusted odds ratio [aOR] 1·17 [98·3% CI 0·70-1·96]) and EULT (aOR 1·51 [0·90-2·51]) did not improve upper limb function; the effects of robot-assisted training did not differ from EULT (aOR 0·78 [0·48-1·27]). More participants in the robot-assisted training group (39 [15%] of 257) and EULT group (33 [13%] of 259) had serious adverse events than in the usual care group (20 [8%] of 254), but none were attributable to the intervention. INTERPRETATION: Robot-assisted training and EULT did not improve upper limb function after stroke compared with usual care for patients with moderate or severe upper limb functional limitation. These results do not support the use of robot-assisted training as provided in this trial in routine clinical practice. FUNDING: National Institute for Health Research Health Technology Assessment Programme.

Within the UK, the "Long Term Athlete Development" (LTAD) model has been proposed by a variety of national governing bodies to offer a first step to considering the approach to talent development. The model, which is primarily a physiological perspective, presents an advancement of understanding of developing athletic potential alongside biological growth. It focuses on training to optimize performance longitudinally, and considers sensitive developmental periods known as "windows of opportunity". However, it appears that there are a number of problems with this theoretical model that are not necessarily transparent to coaches. Principally, the model is only one-dimensional, there is a lack of empirical evidence upon which the model is based, and interpretations of the model are restricted because the data on which it is based rely on questionable assumptions and erroneous methodologies. Fundamentally, this is a generic model rather than an individualized plan for athletes. It is crucial that the LTAD model is seen as a "work in progress" and the challenge, particularly for paediatric exercise scientists, is to question, test, and revise the model. It is unlikely that this can be accomplished using classical experimental research methodology but this should not deter practitioners from acquiring valid and reliable evidence.

AIMS: To characterize e-cigarette use, users and effects in a sample of Electronic Cigarette Company (TECC) and Totally Wicked E-Liquid (TWEL) users. DESIGN AND SETTING: Online survey hosted at the University of East London with links from TECC/TWEL websites from September 2011 to May 2012. MEASUREMENTS: Online questionnaire. PARTICIPANTS: One thousand three hundred and forty-seven respondents from 33 countries (72% European), mean age 43 years, 70% male, 96% Causasian, 44% educated to degree level or above. FINDINGS: Seventy-four percent of participants reported not smoking for at least a few weeks since using the e-cigarette and 70% reported reduced urge to smoke. Seventy-two percent of participants used a 'tank' system, most commonly, the eGo-C (23%). Mean duration of use was 10 months. Only 1% reported exclusive use of non-nicotine (0 mg) containing liquid. E-cigarettes were generally considered to be satisfying to use; elicit few side effects; be healthier than smoking; improve cough/breathing; and be associated with low levels of craving. Among ex-smokers, 'time to first vape' was significantly longer than 'time to first cigarette' (t1104 = 11.16, P < 0.001) suggesting a lower level of dependence to e-cigarettes. Ex-smokers reported significantly greater reduction in craving than current smokers (χ(2) 1 = 133.66, P < 0.0007) although few other differences emerged between these groups. Compared with males, females opted more for chocolate/sweet flavours (χ(2) 1 = 16.16, P < 0.001) and liked the e-cigarette because it resembles a cigarette (χ(2) 3 = 42.65, P < 0.001). CONCLUSIONS: E-cigarettes are used primarily for smoking cessation, but for a longer duration than nicotine replacement therapy, and users believe them to be safer than smoking.