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While the accumulation and increased circulation of genomic data have captured much attention over the past decade, privacy risks raised by the diversification and integration of omics have been largely overlooked. In this paper, we propose the outline of a framework for assessing privacy risks in multi-omic research and databases. Following a comparison of privacy risks associated with genomic and epigenomic data, we dissect ten privacy risk-impacting omic data properties that affect either the risk of re-identification of research participants, or the sensitivity of the information potentially conveyed by biological data. We then propose a three-step approach for the assessment of privacy risks in the multi-omic era. Thus, we lay grounds for a data property-based, ‘pan-omic’ approach that moves away from genetic exceptionalim. We conclude by inviting our peers to refine these theoretical foundations, put them to the test in their respective fields, and translate our approach into practical guidance.

Introduction: Patients with brief arrhythmias are a challenging group to treat effectively with catheter ablation. Current standard approaches for the localization and treatment of brief arrhythmias suffer from several limitations, including the lack of spatiotemporal stability and adequate resolution. Recently, novel methods became available that open new perspectives and can be implemented both on the atrial and ventricular level to approach the diagnosis and treatment of these arrhythmias. Areas covered: In this paper, we demonstrate in each section a novel mapping modality that has a potential to approach arrhythmias considered unmappable in the past. After describing the method, we focused on the most important features of each system that makes mapping of short arrhythmias feasible. At the end of each section, we gave a short overview about necessary developments to improve the utility of these systems in the near future. Expert opinion: Treating brief episodes of tachycardias remains a challenge and can cause significant frustration for electrophysiologists. Although the broadening of the indication is clearly visible, currently available sequential mapping techniques often fail to map short-lived arrhythmias. New beneficial technological features permit the mapping of these previously considered unmappable arrhythmias, and offer a new perspective in their management.

This review aimed, as part of a larger FIFA project aiming to steer women's football research, to scope literature on any level of competitive football for women, to understand the current quantity of research on women's football injuries. The study reviewed all injury-related papers scoped by a recent scoping review mapping all published women's football research with an updated search performed on 23 February 2021. Eligibility criteria assessment followed the recent scoping review with injury-specific research focus. A total of 497 studies were scoped. Most studies contained an epidemiological (N = 226; 45%) or risk factors assessment (N = 105; 21%). Less assessed areas included financial burden (N = 1

This work is motivated by recent researches in particles and their bienergy in different types of geometric structures and applied physical spacetime phases. In this paper, we define a new approach of bienergy and biangle with Sasaki metric in Minkowski spacetime. Moreover, we use the ED-frame method for bienergy and biangle of first and second kind fields. We study the bienergy and biangle for the extended Darboux frame (ED-frame) fields of first and second kind on some hypersurfaces in Minkowski spacetime. Also, we obtain main results as a new relationship for biangle and bienergy of the particle on the hypersurface in Minkowski spacetime. We get new geometric properties of some graphics with the bienergy and biangle. Finally, we determine a new relationship for biangle and bienergy of the particle on the hypersurface in Minkowski spacetime.

The phenomenon of contemporary tourism, overtourism, known mainly from destinations such as Barcelona, Venice, Amsterdam or Prague, does not avoid even small destinations with a rather regional character. Karstejn (Czech Republic), known for its iconic Gothic castle, is visited by up to 250,000 visitors every year. The township Karlstejn is thus daily exposed to the streams of tourists who influence the local environment, inhabitants and the quality of their lives. While the negative influences and impacts of overtourism on the locals in the destination are already well mapped, despite the importance of the influence and the vital role that visitors play in a destination, little academic attention has been directed toward understanding their point of view (Moyle et s., 2013). Therefore, this paper aims to fill this research gap and to examine the visitors’ perception of overtourism impacts in the peak season in the destination Karlstejn. 174 questionnaires were obtained during August 2019 and evaluated using statistical methods of principal component analysis (PCA), linear regression and non-parametric analysis of variance (ANOVA). The results show contradiction to a general definition of overtourism (UNWTO, 2018; Responsible Tourism Partnership, 2019) that implies a deterioration in the quality of life of both local and negative impact on the visitors' experience.

Geohazard risk is high in Arab countries due to ineffective disaster preparedness measures, mismanagement, lack of public awareness, inadequate funding and lack of stakeholder support. One such country is Egypt, which is hit by floods every year that cost lives and bring the economy to a standstill. Moreover, not much has been done to map flood-prone areas. In this paper, flood susceptibility modelling was evaluated in the Ras Gharib region of Egypt using two effective techniques machine learning technique-MLT (Support Vector Machine (SVM)) and deep learning method-DL (Convolutional Neural Networks (CNN)). Thirteen flood related factors and flood inventory layer were prepared to construct these models. Validation was performed with 30% of the flood locations where receiver operating characteristic (ROC) curves showed that the deep learning technique (CNN) gave a prediction accuracy of 86.5% (high performance), while the MLTs (SVM) gave 71.6% (medium performance). The results show that CNN provides 17% better than SVM which indicates a powerful and accurate model in flood susceptibility mapping. Results were confirmed using the Astro Digital images shortly after the 2016 flood, in which the CNN model provides a good agreement.

The paper is devoted to the integral functionals $\int_0^\infty f(X_t)\,{\mathrm{d}t}$ of Markov processes in $\X$ in the case $d\ge 3$. It is established that such functionals can be presented as the integrals $\int_{\X} f(y) \G(x, \mathrm{d}y, \omega)$ with vector valued random measure $\G(x, \mathrm{d}y, \omega)$. Some examples such as compound Poisson processes, Brownian motion and diffusions are considered., Comment: 12 pages. arXiv admin note: text overlap with arXiv:2006.07514

We consider the problem of deriving from experimental data an approximation of an unknown function, whose derivatives also approximate the unknown function derivatives. Solving this problem is useful, for instance, in the context of nonlinear system identification for obtaining models that are more accurate and reliable than the traditional ones, based on plain function approximation. Indeed, models identified by accounting for the derivatives can provide a better performance in several tasks, such as multi-step prediction, simulation, Nonlinear Model Predictive Control, and control design in general. In this paper, we propose a novel approach based on convex optimization, allowing us to solve the aforementioned identification problem. We develop an optimality analysis, showing that models derived using this approach enjoy suitable optimality properties in Sobolev spaces. The optimality analysis also leads to the derivation of tight uncertainty bounds on the unknown function and its derivatives. We demonstrate the effectiveness of the approach with two numerical examples. The first one is concerned with approximation of an univariate function, the second one with multi-step prediction of the Chua chaotic circuit.

Complex product and production systems often result in high variability in the production flow, prohibiting the sustainable implementation of lean practices. In this paper the authors introduce a PDCA cycle to analyse and reduce variability in value streams. The value stream is divided into zones, which are then qualified as stable or unstable. Lean practices can be applied in stable zones, unstable zones remain expert-driven. Measures are introduced to reduce variability in unstable zones with the ultimate target, to turn them into stable zones, extending sustainable lean activities in the value stream, step by step. An IT system is developed to acquire, process and visualise the vast amount of data to provide structured information for experts and management for the reduction of variability in production.

The characterization of firearm discharge residue (FDR) as a piece of evidence plays an essential role in interpreting the forensic cases involving the use of firearms, such as robberies, murders, suicides, and serious attacks. In the last decade, modern or non-toxic primers have emerged due to environmental issues. Forensic examination of gunshot residue (GSR) has become challenging as primer compositions now vary greatly. The goal of this paper is to provide the elemental profiling of both toxic and lead-free cartridge primers available in the Turkish ammunition market. Inductively coupled plasma-mass spectrometry (ICP-MS), scanning electron microscopy coupled with energy-dispersive X-ray analysis (SEM-EDS), and X-ray photoelectron spectroscopy (XPS) were used in this investigation. Multivariate statistical methodologies such as principal component analysis (PCA) and Pearson's correlation coefficient (PCC) analysis were used to interpret the elemental profile data determined in the residue generated after ignition of the cartridge primers. Three components were observed: Ba-Sb-Pb-Cu-Gd, Ti-Sr-Zn, and Al-Ca-Ga, which is also consistent with the PCC analysis. SEM-EDS was employed to confirm the existence of GSR particles. The binding energies, determined using XPS, indicated the chemical state assignments in samples such as Pb(NO3)(2), Sb2S3, Ba(NO3)(2), CuO, ZnO and MoS2. This research will improve the robustness of the interpretation of GSR-related evidence., Giresun University Scientific Research Unit [FEN-BAP-A-270220-40], This study was financially supported by Giresun University Scientific Research Unit [Fund Number: FEN-BAP-A-270220-40].

Assessing the extent and level of building damages is crucial to support post-earthquake rescue and relief activities. There is a large body of literature proposing novel frameworks for automating earthquake-induced building damage mapping using high-resolution remote sensing images. Yet, its deployment in real-world scenarios is largely limited to the manual interpretation of images. Although manual interpretation is costly and labor-intensive, it is preferred over automatic and semi-automatic building damage mapping frameworks such as machine learning and deep learning because of its reliability. Therefore, this review paper explores various automatic and semi-automatic building damage mapping techniques with a quest to understand the pros and cons of different methodologies to narrow the gap between research and practice. Further, the research gaps and opportunities are identified for the future development of real-world scenarios earthquake-induced building damage mapping. This review can serve as a guideline for researchers, decision-makers, and practitioners in the emergency management service domain.

In this paper we provide two significant extensions to the recently developed parameter estimation-based observer design technique for state-affine systems. First, we consider the case when the full state of the system is reconstructed in spite of the presence of unknown, time-varying parameters entering into the system dynamics. Second, we address the problem of reduced order observers with finite convergence time. For the first problem, we propose a simple gradient-based adaptive observer that converges asymptotically under the assumption of generalised persistent excitation. For the reduced order observer we invoke the advanced dynamic regressor extension and mixing parameter estimator technique to show that we can achieve finite convergence time under the weak interval excitation assumption. Simulation results that illustrate the performance of the proposed adaptive observers are given. This include, an unobservable system, an example reported in the literature and the widely popular, and difficult to control, single-ended primary inductor converter.

This paper presents the results of field and laboratory studies of slurry tracks along the South Coast rail line in NSW, Australia. Site investigations on fouled tracks were followed by a series of laboratory tests to determine the properties of mud fines, and how they can reduce track performance. This study reveals two distinctly different ways of forming slurry tracks, i.e., non-subgrade and subgrade mud pumping, resulting in different characteristics of degraded tracks. More cohesive the fouling materials are, the greater the reduction in hydraulic conductivity (kb) and shear strength (Sb) of the contaminated ballast. When the fouling index FI > 30%, kb drops severely, causing insufficient drainage capacity of the track while the loss of Sb can exceed 22%. Different types of fouling index are also discussed with reference to the field and laboratory data, followed by proposed empirical equations to estimate the values of kb and Sb.

The mounting evidence of unintended harmful social consequences of automated algorithmic decision-making (AADM), powered by AI and big data, in transformative services (e.g., welfare services), is startling. The algorithmic harm experienced by individuals, communities and society-at-large involves new injustice claims and disputes that go beyond issues of social justice. Drawing from the theory of “abnormal justice” in this paper we articulate a new theory of algorithmic justice that addresses the questions: WHAT is the matter of algorithmic justice? WHO counts as a subject of algorithmic justice? HOW are algorithmic justices performed? and How to address and resolve disputes about the WHAT, WHO and HOW of algorithmic justice? We illustrate the theory of algorithmic justice by drawing from a case of AADM in social welfare services, widely adopted by governments around the world. Our research points to datafication, technological inscribing and the systemic nature of injustices as important IS-specific aspects of algorithmic justice. Our main practical contribution comes from the articulation of algorithmic justice as a framework that (1) makes visible the injustices related to the “what”, “who”, and “how” of AADM in transformative services, and (2) provides further insights into how we might address and resolve these algorithmic injustices.

Dengue Fever (DF) is a common vector-borne disease with catastrophic health implications. DF prediction modelling is a challenging task, although technologies such as Geographical Information Systems (GIS) and spatial statistics have improved our understanding of dengue dynamics. In this paper, we create a robust data analysis model to (i) provide a better understanding of confirmed dengue fever cases despite missing data, (ii) obtain better insights into risk factors associated with confirmed cases, and (iii) by means of machine learning, create clusters of patients with comparable characteristics. The last was accomplished with a self-organizing feature map (SOFM) and the density-based spatial clustering of applications with noise (DBSCAN). The approaches used to classify confirmed cases were: Decision Tree, k-nearest neighbours, Random Forest, AdaBoost, Support Vector Classification (SVC), CatBoost, and Naive Bayes. The CatBoost classifier achieved the best accuracy for the analysis of confirmed cases. Spatial analysis was conducted using the ordinary least square (OLS) and geographically weighted regression (GWR) models to identify high-risk areas. SOM can group patients with similar features into clusters, then DBSCAN detects and retrieves six clusters from this data. The clustering of confirmed cases increases CatBoost’s modelling prediction accuracy and reveals complex factors that influence prediction accuracy. Because confirmed cases in each cluster have different features, CatBoost is applied to each cluster individually to improve the prediction accuracy. Variable values in each cluster are analysed to clarify the confirmed cases of a specific subset of DF incidents. Overall, OLS outperforms GWR when identifying hotspot areas. The proposed novel, data-driven and machine-learning-based strategy facilitates the understanding and identification of patterns associated with confirmed DF cases. The study's findings can be utilized to cluster historical patient data into groups or subgroups sharing similar variables. Using identifiable patient clusters rather than raw history data improves the model accuracy provided by CatBoost.

The paper focuses on the robustness of rankings of academic journal quality and research impact in general, and in Economics, in particular, based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). The paper analyses 299 leading international journals in Economics using quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in various RAMs, which are based on alternative transformations of citations and influence. All existing RAMs to date have been static, so two new dynamic RAMs are developed to capture changes in impact factor over time and escalating journal self citations. Alternative RAMs may be calculated annually or updated daily to determine When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs are grouped in four distinct classes that include impact factor, mean citations and non-citations, journal policy, number of high quality papers, and journal influence and article influence. These classes include the most widely used RAMs, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Eigenfactor (or Journal Influence), Article Influence, h-index, and PI-BETA (Papers Ignored - By Even The Authors). As all existing RAMs to date have been static, two new dynamic RAMs are developed to capture changes in impact factor over time (5YD2 = 5YIF/2YIF) and Escalating Self Citations. We highlight robust rankings based on the harmonic mean of the ranks of RAMs across the 4 classes. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal quality, impact and influence relative to the harmonic mean of the ranks.

In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimers disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.

KUCUKTOPCU, ERDEM/0000-0002-8708-2306 WOS: 000431521400003 In this paper, the daily reference evapotranspiration (ET0) for Bulawayo Goetz was estimated from climatic data using neuro computing techniques. The region lacks reliable weather data and experiences inconsistencies in the measuring process due to inadequate and obsolete measuring equipment. This paper aims to propose neuro computing techniques as an alternative methodology to estimating evapotranspiration. Firstly, ET0 was calculated using FAO-56 Penman-Monteith (PM) equation from available climatic data. Data was divided into training, testing and validation for neuro computing purposes. The study also investigated the effect of different normalisation techniques on neuro computing ET0 estimation accuracy. In another application, neuro-computing ET0 estimates were compared against those obtained using empirical methods and their calibrated versions. The Z-score normalisation technique for all data sets gave best results with a Multi-layer perceptron (5-5-1) model having RMSE, MAE and R-2 values in the range 0.12-0.25mm day(-1), 0.08-0.15mm day(-1) and 0.94-0.99 respectively. There were no significant differences in ET0 estimation accuracy by neuro computing techniques due to normalisation technique. The Neuro computing techniques were superior to empirical methods in ET0 estimation for Bulawayo Goetz. The Neuro computing techniques are recommended for use in cases of limited climatic data at Bulawayo Goetz.

The link between theory, practice and research in Initial Teacher Education (ITE) has been widely discussed in international literature. However, more needs to be done in regard to the examination of concrete examples to foster research and teaching practice in existing teacher education programmes. This paper focuses on a practicum model in ITE which aims at linking teaching and research, theory and practice. The reflective component of the model is oriented towards student teacher professional development under a democratic view of education. Integrating teaching and research and promoting teaching practice as a space of transformation rather than a process of adaptation or of application of theory may well represent a move towards knowledge mobilisation and research-informed practice. The paper concludes with some lessons learned and possible directions in order to overcome the shortcomings of the model and to enhance its positive and innovative features., Financial Support by CIEC (Research Centre on Child Studies, IE, UMinho; FCT R&D unit 317, Portugal) by the Strategic Project UID/CED/00317/2013, with financial support of National Funds through the FCT (Foundation for Science and Technology) and co-financed by European Regional Development Funds (FEDER) through the COMPETE 2020 - Competitiveness and Internationalization Operational Program (POCI) with the reference POCI-01-0145-FEDER-007562

This paper provides an overview of research on veteran teachers and teacher identity. It analyses issues at the personal, situated and professional levels that have been shown to impact on veteran teachers' identities. The search included empirical studies published in peer-reviewed journals between 2005 and 2016. In total, 19 papers were analysed. Findings revealed that many studies focused on veteran teachers' resilience. Issues concerning veteran teachers' identities are key to understanding why they remain in the profession and are able to sustain their motivation and commitment over time. Many veteran teachers portrayed in the literature built on their confidence regarding their professional competence and relied on internal and external issues to maintain their motivation and commitment to teaching. The role of emotions in the transformation of veteran teachers' identities and the permeable boundaries of the personal, situated and professional scenarios influencing veteran teachers' identities are highlighted in the paper., Financial Support by CIEC (Research Centre on Child Studies, IE, UMinho; FCT R&D unit 317, Portugal) by the Strategic Project UID/CED/00317/2013, with financial support of National Funds through the FCT (Foundation for Science and Technology) and co-financed by European Regional Development Funds (FEDER) through the COMPETE 2020 - Competitiveness and Internationalization Operational Program (POCI) with the reference POCI-01-0145-FEDER-007562

Objectives: The current paper addresses the evidence for circadian clock characteristics associated with attention-deficit hyperactivity disorder (ADHD), and possible therapeutic approaches based on chronomodulation through bright light (BL) therapy. Methods: We review the data reported in ADHD on genetic risk factors for phase-delayed circadian rhythms and on the role of photic input in circadian re-alignment. Results: Single nucleotide polymorphisms in circadian genes were recently associated with core ADHD symptoms, increased evening-orientation and frequent sleep problems. Additionally, alterations in exposure and response to photic input may underlie circadian problems in ADHD. BL therapy was shown to be effective for re-alignment of circadian physiology toward morningness, reducing sleep disturbances and bringing overall improvement in ADHD symptoms. The susceptibility of the circadian system to phase shift by timed BL exposure may have broad cost-effective potential implications for the treatment of ADHD. Conclusions: We conclude that further research of circadian function in ADHD should focus on detection of genetic markers (e.g., using human skin fibroblasts) and development of BL-based therapeutic interventions.

Introduction: The amount of mandatory data that needs to be analyzed as part of a medical device postmarket surveillance (PMS) system has grown exponentially in recent times. This is a consequence of increasingly demanding and complex regulatory requirements from Health Authorities, aimed at a better understanding of the medical device safety evaluation. Proactive approaches to PMS processes are becoming more necessary as regulators increase the scrutiny of device safety. New technologies have been explored to address some of the challenges associated with this changing regulatory environment. Areas covered: This paper focuses on the different technical aspects of blockchain and how this new technology has the potential to support the ongoing efforts to improve the PMS system for medical devices. Expert opinion: To address these challenges, we suggest to generate a private PMS data permissioned blockchain with a proof-of-authority consensus mechanism, to which only a restricted number of designated and audited participants have authorization to validate transactions and add them to the PMS data blockchain ledger. Blockchain has the potential to support a more efficient approach, which could offer many advantages to the different stakeholders involved in the PMS process, such as supporting with new regulatory initiatives.

Introduction: The global burden of cirrhosis is rising, and clinicians increasingly face the challenge of safely prescribing medicines for complications of hepatic disease and comorbidities. Prescribing in patients with cirrhosis is complicated by alterations that can occur in the pharmacology of medicines.Areas covered: This paper provides an overview of current knowledge on the pharmacokinetics and pharmacodynamics of medicines in patients with cirrhosis. We describe the pathophysiological changes that occur and their consequences on pharmacokinetic parameters. We explain that the influence of cirrhosis on the pharmacokinetics depends on several drug and patient characteristics. Patients with cirrhosis also have an increased susceptibility to some toxicological effects of medicines, such as renal impairment and hematological toxicity, which we describe in detail. In addition, we discuss approaches to apply this knowledge in practice and improve safe medication use in patients with cirrhosis.Expert opinion: Tailored pharmacotherapy is needed to ensure safe and appropriate use of medicines in patients with cirrhosis. Clinicians are supported by freely available recommendations on safe drug use in cirrhosis published on a website. In addition, a regular evaluation of medication use in patients with cirrhosis could resolve and prevent medication-related problems.

This paper examines economic growth in 52 African countries for 1961–2016 and seeks to find if there is common growth. As all African countries have their particular features, concerning climate, h...

This paper researches the quality of democratic control of the public police in a democratic society. Governance structures tend to be complex, reflecting that in democratic societies the police pe...

Companies need to rethink the way they create value and grow their business to thrive in tomorrow’s volatile and uncertain business environment. Companies in virtually every industry are being impacted by new disruptive and complex societal trends, such as climate change, energy transition and social inequality. At the same time, companies are increasingly evaluated on their non-financial performance and they ever more compete on speed and sustainability. Still, only a few companies have begun to invent new strategic directions, pioneering strategies focused on creating long-term value, not just for shareholders but for all stakeholders. A playbook on how to create long-term value is currently lacking, making it difficult for companies to capture the opportunities and mitigate the risks created by these societal trends. This paper develops a model of long-term value creation that supports companies in creating long-term value and setting their strategies accordingly. Financial institutions can draw on the model to assess how future proof their investment and/or lending portfolios are.

OBJECTIVES: An association is found between changes in cytokine levels and antidepressant treatment outcome. Also, a proinflammatory profile is associated with a favourable electroconvulsive therapy (ECT) outcome. This paper investigates the pattern of inflammatory markers during a course of ECT in older depressed patients and whether this pattern is associated with ECT outcome. We hypothesised that ECT has an anti-inflammatory effect. METHODS: The pattern of CRP, IL-6, IL-10, and TNF-α during a course of ECT was examined using longitudinal mixed model analyses. Serum samples were collected in 99 older depressed patients (mean age: 72.8 ± 8.3 years, MADRS score 33.8 ± 9.0). RESULTS: After Bonferroni correction, there were no statistically significant alterations in levels of inflammatory markers during and after ECT. Effect sizes (Cohen's d) were -0.29 for CRP, -0.13 for IL-6, -0.06 for IL-10, and -0.07 for TNF-α. Changes in CRP or cytokine levels did not differ between remitters and non-remitters. Median baseline levels of CRP were significantly higher in remitters. CONCLUSIONS: A small to medium effect size towards decreased CRP and IL-6 levels was observed. An anti-inflammatory effect of ECT could not be confirmed. However, the findings may suggest that patients with an inflammatory profile benefit more from ECT than other patients. Further studies are needed to confirm these findings. ispartof: WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY vol:22 issue:10 pages:770-777 ispartof: location:England status: published

The Italic consonant stem ablative in -ĕ is usually regarded as an anomalous instance of locative contamination in the ablative singular case endings. This interpretation has long been recognized as problematic, given that the Italic ablative is functionally the result of syncretism with the Proto-Indo-European instrumental, rather than the locative. In addition, it is difficult to reconcile the traditional view with the early Latin epigraphic evidence, which suggests that the Latin consonant stem ending, like the ablative singular endings of all other declensions, once had a final dental (-ĕd). This paper reviews the evidence for the origin and reconstruction of the Italic consonant stem ablative within the broader context of the early development of the Italic case system. It provides further arguments against the conventional locative etymology, and concludes that the consonant reflex can plausibly be aligned with the regular reflexes in other declensions if it is instead derived from a zero-grade instrumental ending ispartof: Symbolae Osloenses vol:94 issue:1 pages:1-23 status: Published online

Organo-modified nanoclay has got considerable attention in recent years to improve the performance of asphalt binders. However, various aspects such as rutting performance using Multiple Stress Creep Recovery (MSCR) test, fatigue performance using Linear Amplitude Sweep (LAS) test and ageing resistivity potential using advanced rheological parameter are still unexplored for better rheological characterisation. The present study deals with rutting, ageing resistivity potential and fatigue performance of asphalt binder (AC-10) modified with organo-modified nanoclay (CL-30B). Different percentages (0, 2, 4 and 6% by weight of binder) of CL-30B were mixed with AC-10 using a high-shear mixer. Different rheological studies, such as Brookfield viscosity, Superpave performance grading, time-temperature sweep, MSCR and LAS tests, were conducted on CL-30B-modified asphalt binders. Effects of CL-30B on performance were observed to be predominant in intermediate to high-temperature range as obtained from the master curve. The ageing resistivity of asphalt binder increased with the addition of CL-30B. The Superpave rutting parameter (G*/Sin delta) increased and non-recoverable creep compliance (J(nr)) estimated from MSCR decreased with inclusion of CL-30B, indicating a better rutting performance of asphalt binders. The number of cycles to fatigue estimated from the LAS test showed improvement in fatigue performance of asphalt binder with addition of CL-30B. The high-temperature performance grade of CL-30B-modified binder was found to be higher compared to virgin binder. The relationship between J(nr) and G*/Sin delta, and recovery (R) and storage modulus (G') parameters are presented in this paper. In addition, ranking of asphalt binder based on various parameters (i.e. G*/Sin delta, AI, J(nr), R, N-f) is discussed in this paper.

This paper considers a low-level unit-load warehouse employing single-deep storage lanes and a single-command manual storage and retrieval policy. Analytical travel distance models are developed for class-based and full turnover storage policies under across-aisle, within-aisle and a newly proposed hybrid product placement schemes. Our computational studies show that the analytical models developed in this paper are very accurate as compared to simulation results and a comparative study with a real-world warehouse case. Hybrid storage policies proposed in this paper outperform all other traditional storage policies. The paper also presents insights and simple design rules to warehouse practitioners.

The market share of generic medicines in France is low compared to other European countries. This perspective paper provides an overview of the generic medicines retail market in France and how the current policy environment may affect the long-term sustainability. Looking at the French generic medicines retail market and the surrounding regulatory framework, all conditions seem to be in place to create a healthy generic medicines market: the country has well-respected regulatory authorities, generic medicines enter the market in a timely manner and prices of generic medicines are competitive compared with other European countries. Despite the success of the demand-side policies targeted at pharmacists and patients, those targeted at physicians were less successful due to a lack of enforcement and a lack of trust in generic medicines by French physicians. Recommendations to increase the use of generic medicines in France round off this perspective paper.

A political leader's authenticity has always been a site of struggle: politicians have tried to control their own image, while mass media has promised to reveal the "real" self behind the electoral campaign. In recent years, social media such as Facebook, Twitter or YouTube have gained a positive reputation as electoral tools. This paper seeks to critically engage with this reputation, by focusing on how these services become discursively articulated with the notion of political "authenticity" in the case of the 2010 municipal elections in Calgary, Canada. In these elections, the intense use of social media by the winning candidate has been seen as proof of the democratic power of these communication technologies to bring together politicians and citizens. A qualitative thematic analysis of 86 undergraduate essays reveals how participants collectively talked about political "authenticity." The paper argues that political "authenticity" becomes articulated as a result of the intrinsic features of social media, reinforcing the longstanding technological determinist view of technology as the guarantor of a better citizen/politician relation. The discursive articulation of social media and political "authenticity" portrays politics as a customer relations service, providing little insight into how we are to understand and relate to democratic politics after elections.

INTRODUCTION Physical fatigue can be a common reason for early retirement or sick leave since it appears in the earliest stages of multiple sclerosis (MS). Therefore, a prompt and accurate diagnosis is essential. This systematic review aims to identify and describe the instruments used to assess physical fatigue in MS patients with consideration for the languages used to validate the instruments and their methodological qualities. AREA COVERED This study has been carried out through 'Medline,' 'Scopus,' 'Cinhal,' and 'Web of Science' databases for all the papers published before 24 January 2020. Three independent authors have chosen the eligible studies based upon pre-set criteria of inclusion. Data collection, data items, and assessment of the risk of bias: the data extraction approach was chosen based on the Cochrane Methods. For data collection, the authors followed the recommendations from the COSMIN initiative. Study quality and risk of bias were assessed using the COSMIN Check List. EXPERT OPINION 119 publications have been reviewed. The 45 assessment scales can be divided into specific scales for physical fatigue and specific scales for MS. The most popular tools are the Fatigue Severity Scale and the Modified Fatigue Impact Scale.

The study empirically examines the impact of armed conflict on population growth in Eastern Turkey. The empirical findings confirm the implications of the theoretical model in the body of the paper. The results indicate that PKK recruitment leads to depopulation at the district level while increases rural population growth. Moreover, the results indicate that the number of killed PKK militants in the province to which a district belongs negatively affects population growth at the district level. On the other hand, the results also indicate that number of killed PKK militants does not significantly affect the population growth at the district level while decreases rural population growth. The results show that the percentage of valid votes to registered voters increases the population growth at the district level.

Although possible asymmetries for univariate and multivariate dynamics have been the focus of interest in many areas of economic explorations, it seems that most of the research on military expenditure - economic growth nexus has tended to assume linear relationships. This paper aims to examine possible nonlinearities in military expenditure-economic growth nexus employing data for a sample of 103 countries covering the 1988-2019 period. For this purpose, Panel Smooth Transition Regression, PSTR, models are estimated not only for all countries' sample but also for low income, middle income, and high-income countries' subsamples to reveal possible distinct asymmetric relationships for country groups with different income levels. Empirical results for the whole sample, low income and middle income groups indicate that military expenditure not only governs the regime change, but also low and high levels of military expenditure have distinctive and rising negative effects on economic growth with dissimilar threshold effects. Moreover, empirical findings also indicate that net arms exports govern regime change for high income countries, and as net arms exports rise, the negative impacts of military expenditure on economic growth become deeper.

Purpose: Self-reliance and social participation are strongly promoted by social policy. Both concepts are linked to the concept of vulnerability, for people who do not meet these standards are labelled "vulnerable people". In this paper, the insider's perspective takes central stage by seeking to explore what it means to be labelled a "vulnerable person", and through this to further our insight into the meaning of the concept of vulnerability. Method: Thirty-three in-depth interviews were conducted with 16 allegedly vulnerable people. The data were subjected to thematic content analysis. Results: Our analysis revealed three main dimensions and eight sub-dimensions of perceived vulnerability, outlining an insider's concept of vulnerability. This concept includes manifestations of vulnerability, feelings coexisting with vulnerability, and the image of vulnerable people. Conclusion: The perception of vulnerability changes when interacting with others in society, especially with social policy implementers. In this interaction, the perceived vulnerability increases and becomes societal vulnerability. It concerns a dependency situation in which one's strength and self-determination are not recognized, and the help needed is not provided. By acknowledging the insider's perspective, social policy can fulfil a more empowering role towards "vulnerable people" and contribute to people's well-being. ispartof: INTERNATIONAL JOURNAL OF QUALITATIVE STUDIES ON HEALTH AND WELL-BEING vol:16 issue:1 ispartof: location:United States status: published

Climate change impact search methodologies, for a single hydro-meteorological record, are based mostly on probabilistic, statistical and stochastic processes. The application of these methodologies requires some restrictive assumptions for their validation, which may not be embedded in the structure of the record. Either transformations or approximations are taken into consideration, with idealization and simplification assumptions. In this paper, a series of conceptual trend polygon methodologies are presented without mathematical expression or restrictive assumptions. These are serial, cross- and double polygonal trend methods, in addition to trend star graphs. They help in identifying, interpreting and calculating monthly shifts, producing useful scientific information that cannot be obtained by the classical monotonic trend identification approaches. The methodology is applied to hydro-meteorological series from different regions of the world including precipitation and discharge records.

Predicting the traffic conditions in urban networks is a priority for traffic management centres. This becomes very challenging, especially when the network is affected by traffic incidents that vary in both time and space. Although data-driven modelling can be considered an ideal tool for short-term traffic predictions, its performance is severely degraded if little historical traffic information is available under incident conditions. This paper addresses this challenge by integrating data-driven and traffic simulation modelling approaches. Instead of directly predicting the traffic states using limited historical data, we employ a traffic simulation reinforced by data-driven models. The traffic simulation uses newly reported incident information and the estimated origin-destination (OD) demand flows to capture the complex interaction between drivers and road network, and predicts traffic states under extreme conditions. We showcase the capability of the proposed data-driven enforced traffic simulation platform for incident impact analysis in a real-life sub-network in Sydney, Australia.

Objective: Understanding and managing countertransference (CT) is challenging for therapists and more so for trainees. This study aimed to understand more about trainees’ experiences of CT; and to consider the usefulness for reflective practice of a five component model of CT (origins, triggers, manifestations, effects, and management) and the importance of feedback. Method: Trainee psychologists in Australia and New Zealand took part in a CT training and were invited to take part in the study. Trainees were randomly assigned to 1 of 2 conditions in which they received regular feedback or feedback at the end of the study. Nineteen trainees completed 93 reflective logs. Data from the logs were analysed using thematic analyses. Results: Most trainees perceived their CT originated from formative experiences and personality qualities and were triggered by client concerns and behaviours. They described a wide range of CT manifestations; and perceived the effects of CT as mainly negative. More trainees in the regular feedback condition, compared to post-completion, engaged with the activity. However, there was no difference in themes that emerged in the two groups. Conclusions: The five-component model of CT provides a method for reflecting on CT and could be used to enhance trainees’ reflective practice. Key Points What is already known about this topic: (1)Little is known about trainee psychologists’ experiences of countertransference although there is evidence that trainees experience difficulties understanding and managing their countertransference reactions. (2)Understanding and managing countertransference supports positive therapy outcomes. (3)Hayes’ (1995) model of countertransference proposes five components–origins, triggers, manifestations, effects, and management. What this paper adds: (1)The study provides greater insight into trainees’ views of the five components of countertransference. (2)Hayes’ (1995) model of countertransference appears to provide a useful model of reflective practice that could be used in post-graduate psychology training. (3)This model is also likely to be useful for psychologists and clinical supervisors in their own practices.

This paper is concerned with an age-structured model in population dynamics. We investigate the uniqueness of solution for this type of nonlinear reaction-diffusion problem when the source term depends on the density, indicating the presence of, for example, mortality and reaction processes. Our result shows that in a spatial environment, if two population densities obey the same evolution equation and possess the same terminal data of time and age, then their distributions must coincide therein. This work is in commemoration of the first death anniversary of V. A. K's father. V. A. K thanks Prof. Nguyen Huy Tuan for introducing him the ultraparabolic problem. The work of V.A.K. was supported by the Research Foundation-Flanders (FWO) under the project 'Approximations for forward and inverse reaction-diffusion problems related to cancer models'. Lesnic, D (reprint author), Univ Leeds, Dept Appl Math, Leeds, W Yorkshire, England. amt5ld@maths.leeds.ac.uk

This study evaluates and compares several machine learning methods on the effects of different parameters in the hydrothermal carbonisation (HTC) process of macroalgae Sargassum horneri. Reaction temperature, residence time, biomass particle size, the amount of catalyst and loaded biomass were considered as inputs and three variables of BET, higher heating value (HHV) and energy recovery were regarded as outputs. For analysing the input parameters, the Taguchi method was used for experimental designs and the obtained results were utilised here as training sets. Various data mining approaches like support vector machine (SVM), group method of data handling, decision tree, random forest, radial basis function, adaptive neuro-fuzzy inference system (ANFIS) and multilayer perceptron (MLP) neural network were implemented to model the problem and two different optimisation techniques named BAT and Grasshopper Optimisation Algorithm (GOA) were employed with MLP and ANFIS model for optimising. By comparing different statistical parameters such as Average Absolute Relative Deviation (AARD), coefficient of determination (R-2), Root Mean Square Error (RMSE) and Standard Deviation (SD), It is found out that SVM method has a considerably better performance relative to other methods for estimating both the BET, HHV and energy recovery parameters. Furthermore, coupling of MLP and ANFIS with GOA increases the accuracy of these models for BET, HHV and energy recovery estimations.

A new bio-economic model for managing population of non-renewable inland fishery resource in uncertain environment is presented. Population dynamics of the resource is described with stochastic differential equations (SDEs) having ambiguous growth and mortality rates. The performance index to be maximized by the manager of the resource while minimized by nature is presented in the context of differential game theory. The dynamic programming principle leads to a Hamilton-Jacobi-Bellman-Isaacs (HJBI) equation that governs the optimal resource management strategy under the ambiguity. The main contribution of this paper is a series of theoretical analysis on the reduced HJBI equation for non-renewable fishery resources in a broad sense, indicating that the ambiguity critically affects the resulting optimal controls. Practical implications of the theoretical analysis results are also presented focusing on artificially hatched Plecoglossus altivelis (Ayu), an important inland fishery resource in Japan.

This paper sets out to deepen our understanding of the relationship between popular music and cultural heritage and to delineate the practices of popular music as cultural heritage. The paper illustrates how the term has been mobilised by a variety of actors, from the public to the private sector, to highlight the value of particular popular music manifestations and justify or encourage their preservation and diffusion for posterity. We focus on Austria, England, France and the Netherlands - countries with diverse popular music histories and with varying national and international reach. Popular music heritage is present in national and local public sector heritage institutions and practices in a number of ways. These range from the preservation and exhibition of the material culture of heritage in museums and archives, to a variety of ‘bottom-up’ initiatives, delineating a rich landscape of emblematic places, valued for their attachment to particular musicians or music scenes. The paper points to an underlying tension between the adoption and replication of conventional heritage practices to the preservation and remembrance of the popular music and its celebration as an expression of the dynamism of contemporary popular culture.

© 2020 The Royal Society of New Zealand. Taxonomic information for New Zealand mosquito species is predominantly morphological with very few molecular data available to date. In this study, the mitochondrial COI gene and nuclear ITS1 were amplified and sequenced from DNA templates representing 17 species; 15 previously known New Zealand species, a newly discovered undescribed Aedes species from the Chatham Islands and a recently eradicated invader, Ae. camptorhynchus. This paper provides DNA barcoding sequences for the entire known New Zealand mosquito fauna, the first for the majority of these species. Phylogenetic analysis of COI and ITS1 indicated that the endemic species are all genetically distinct from the exotic species examined including vector species of pathogens of human diseases. The genus Opifex is distant from the genus Aedes based on analysis of ITS1 sequences, and Ae. chathamicus is more closely related to species within Aedes than to the genus Opifex. Results show Culex asteliae to be a valid species but Cx. rotoruae is not necessarily so. The Aedes species appears to be closely related to Ae. subalbirostris. The introduced Cx. quinquefasciatus was clearly shown to be related to Cx. pipiens; however, the endemic Cx. pervigilans was not. No evidence of population variation based on geographic location was detected.

In this paper, laser-induced hyperthermia therapy of cancer is treated as a state estimation problem and solved with a particle filter method, namely the Auxiliary Sampling Importance Resampling algorithm. In state estimation problems, the available measured data are used together with prior knowledge about the physical phenomena, in order to sequentially produce estimates of the desired dynamic variables. Although the hyperthermia treatment of cancer has been addressed in the literature by different computational methods, these usually involved deterministic analyses. On the other hand, state space representation of the problem in a Bayesian framework allows for the analyses of uncertainties present in the mathematical formulation of the problem, as well as in the measured data of observable variables that might be eventually available. Two physical problems are considered in this paper, involving the irradiation with a laser in the near infrared range of a non-homogeneous cylindrical medium representing either a soft-tissue phantom or a skin model, both containing a tumour. The region representing the tumour is assumed to be loaded with nanoparticles in order to enhance the hyperthermia effects and to limit such effects to the tumour. The light propagation problem is coupled with the bioheat transfer equation in the present study. Simulated transient temperature measurements are used in the inverse analysis. Fil: Lamien, Bernard. Universidade Federal do Rio de Janeiro; Brasil Fil: Orlande, Helcio Rangel Barreto. Universidade Federal do Rio de Janeiro; Brasil Fil: Elicabe, Guillermo Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Ciencia y Tecnología de Materiales. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones en Ciencia y Tecnología de Materiales; Argentina

The aim of this work was to evaluate three carbon materials as anodes in microbial fuel cells (MFCs), clarifying their influence on the generation of electricity and on the treatability of winery wastewater, a highly organic-loaded waste. The electrode materials tested were carbon felt, carbon cloth and carbon paper and they were used at the same time as anode and cathode in the tests. The MFC equipped with carbon felt reached the highest voltage and power (72 mV and 420 mW m−2, respectively), while the lowest values were observed when carbon paper was used as electrode (0.2 mV and 8.37·10−6 mW m−2, respectively). Chemical oxygen demand (COD) removal from the wastewater was observed to depend on the electrode material, as well. When carbon felt was used, the MFC showed the highest average organic matter consumption rate (650 mg COD L−1 d−1), whereas by using carbon paper the rate decreased to 270 mg COD L−1 d−1. Therefore, both electricity generation and organic matter removal are strongly related not to the chemical composition of the electrode (which was graphite carbon in the three electrodes), but to its surface features and, consequently, to the amount of biomass adhered to the electrode surface.

The paper deals with the singularly perturbed quasilinear initial value problem exhibiting initial layer. First the nature of solution of differential problem before presenting method for its numerical solution is discussed. The numerical solution of the problem is performed with the use of a finite-fitted difference scheme on an appropriate piecewise uniform mesh (Shishkin-type mesh). An error analysis shows that the method is first-order convergent except for a logarithmic factor, in the discrete maximum norm, independently of the perturbation parameter. Finally, numerical results supporting the theory are presented. The paper deals with the singularly perturbed quasilinear initial value problem exhibiting initial layer. First the nature of solution of differential problem before presenting method for its numerical solution is discussed. The numerical solution of the problem is performed with the use of a finite-fitted difference scheme on an appropriate piecewise uniform mesh (Shishkin-type mesh). An error analysis shows that the method is first-order convergent except for a logarithmic factor, in the discrete maximum norm, independently of the perturbation parameter. Finally, numerical results supporting the theory are presented.

The paper presents in a chronological and systematic way the development of the hybrid method for seismic vulnerability assessment of structures, which combines the use of empirical databases of earthquake damage with the results of nonlinear analysis of representative structural models. The key concepts and milestones in the development of the method are identified, and selected examples of its application are summarised. The first part of the paper focuses on the derivation of hybrid damage probability matrices and the second one with the derivation of fragility curves for reinforced concrete and masonry buildings. Finally, some general conclusions are drawn and directions of future research on the hybrid approach are suggested.

In this paper we consider the location of stops along the edges of an already existing public transportation network. The positive effect of new stops is given by the better access of the passengers to the public transport network, while the passengers’ traveling time increases due to the additional stopping activities of the trains, which is a negative effect for the passengers. The problem has been treated in the literature where the most common model is to cover all demand points with a minimal number of new stops. In this paper, we follow this line and seek for a set of new stops covering all demand points but instead of minimizing the number of new stops we minimize the additional passengers’ traveling time due to the new stops. For computing this additional traveling time we do not only take the stopping times of the vehicles but also acceleration and deceleration of the vehicles into account. We show that the problem is NP-hard, but we are able to derive a finite candidate set and two tractable IP formulations. For linear networks we show that the problem is polynomially solvable. We also discuss the differences to the common models from literature showing that minimizing the number of new stops does not necessarily lead to a solution with minimal additional traveling times for the passengers. We finally provide a case study showing that our new model decreases the traveling times for the passengers while still achieving the minimal number of new stops.

WOS: 000389443300019, PubMed ID: 27291089, Context: Human beings have long utilized plants for medicinal purposes. Investigation of these plants has led to the discovery of several modern drugs. Objective: This paper documents and evaluates traditional knowledge on medicinal plants used by the local people of Mihalgazi district of Eskisehir,Turkey. Materials and methods: Six villages of the study area were visited between February 2014 and April 2015 to collect the data. One hundred and eighty-nine informants were interviewed by the survey method and face to face semi-structured interviews. Taxonomic identification, the most commonly used plant parts, preparation and administration methods were evaluated. Ethnomedicinal data were analyzed quantitatively with relative importance (RI) and the informant consensus factor (FIC). Results: This paper reported a total of 52 medicinal plants (37 wild, 15 cultivated) belonging to 34 families. Some uses of 22 plants were not found in the literature and are reported for the first time in this study. Furthermore, one of the plants, Calamagrostis arundinacea (L.) Roth (Poaceae), was reported for the first time as being used within the scope of traditional therapies. Discussion and conclusion: This study recorded traditional knowledge on medicinal plants used in Mihalgazi, Turkey. This paper provides a basis for further investigations to discover efficient pharmaceuticals., Anadolu University [1402S037], This work was financially supported by Scientific Research Projects Unit of Anadolu University (Project no: 1402S037).