bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantitative evaluation of electrical conductivity inside stress corrosion crack with electromagnetic NDE methods
Authors: Cai Wenlu , Jomdecha Cherdpong , Zhao Yingsong , Wang Li , Xie Shejuan , Chen Zhenmao 
Published: September 2020

This paper presents a comparison of studies on the local distributed electrical conductivity in stress corrosion crack (SCC) from signals of eddy current testing (ECT) and direct current potential drop (DCPD) aiming to improve SCC sizing accuracy when using electromagnetic non-destructive testing (NDT) methods. Experimental setups of ECT and DCPD were established, respectively, to collect measurement signals due to artificial SCCs in a plate of austenitic stainless steel. The local conductivity in the SCC region was reconstructed from the feature parameters extracted from the measured ECT and DCPD signals through inverse analyses. The inversion strategies for ECT and DCPD, each including an efficient forward simulation and an optimization scheme, were introduced from the viewpoint of conductivity reconstruction. Inversion results obtained from the measured ECT and DCPD signals showed the consistent trend which proved the validity of the predicted electrical conductivity indirectly. It is clarified that the electrical conductivity in a SCC is relatively high at the crack tip area and may become as high as 17% of that of the base material. These results provide a good reference to enhance the sizing accuracy of SCC with an electromagnetic NDT method such as ECT by updating the conductive crack model based on the results of this work.
This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
Physic perspective fusion of electromagnetic acoustic transducer and pulsed eddy current testing in non-destructive testing system
Authors: Guo Wei , Gao Bin , Yun Tian Gui , Si Dan 
Published: September 2020

Comprehensive non-destructive testing (NDT) for pipelines is a critical and challenging task. This paper proposes a novel physic perspective fusion NDT method of electromagnetic acoustic transducer (EMAT) and pulsed Eddy current testing (PECT) for detecting hybrid defects. This transceiver-integrated fusion sensor structure can simultaneously excite ultrasound and pulsed eddy current. Therefore, the generated ultrasound is applied to detect deep defects, while the eddy current detects surface defects. The theoretical derivation of EMAT and PECT fusion mechanism has been developed for analysis and interpretation of the results. In addition, numerical simulation on the detection of hybrid defects including surface defects with different width, depth and multiple bottom-thinning defects has been conducted. Experiments on both ferromagnetic and non-ferromagnetic material verify the feasibility of composite detection. Finally, tests have been validated on pipeline with weld defects, and the results show that the composite inspection method is capable of monitoring thickness variations and inspecting surface defects.
This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
Health-related effects of education level: a Mendelian randomization study
Authors: Yuan Shuai , Xiong Ying , Michaëlsson Madeleine , Michaëlsson Karl , Larsson Susanna C. 
Published: September 2020

AbstractBackgroundA deeper understanding of the causal links from education level to health outcomes may shed a light for disease prevention at a novel and efficient perspective.MethodsWe conducted a wide-angled Mendelian randomization to disentangle the causal role of education level from intelligence for 31 health outcomes and explore to what extent body mass index and smoking mediate the associations. Univariable and multivariable Mendelian randomization analyses were performed.ResultsGenetically higher education level was associated with lower risk of major mental disorders and most somatic diseases independent of intelligence. The intelligence-adjusted odds ratios for each additional standard deviation of education (4.2 years) were 0.48 (0.37, 0.62) for suicide attempts, 0.50 (0.36, 0.68) for large artery stroke, 0.51 (0.42, 0.63) for heart failure, 0.52 (0.42, 0.65) for lung cancer, 0.45 (0.33,0.61) for rheumatoid arthritis, and 0.48 (0.43, 0.55) for type 2 diabetes. Higher education level adjusted for intelligence was additionally associated with lower risk of insomnia, major depressive disorder, stroke, coronary artery disease, breast cancer, ovarian cancer and gout but with higher risk of obsessive-compulsive disorder, anorexia nervosa, bipolar disorder and prostate cancer. Moreover, higher education level was associated with modifiable health-related risk factors in a favorable manner. Adjustment for body mass index and smoking attenuated the associations between education level and several outcomes, especially for type 2 diabetes and heart failure. High education level exerts causal protective effects on major somatic diseases.ConclusionsThese findings emphasize the importance of education to reduce the burden of common diseases.
Does pericentral mu-rhythm “power” corticomotor excitability? – a matter of EEG perspective
Authors: Karabanov Anke Ninija , Madsen Kristoffer Hougaard , Krohne Lærke Gebser , Siebner Hartwig Roman 
Published: September 2020

AbstractBackgroundElectroencephalography (EEG) and single-pulse transcranial magnetic stimulation (spTMS) of the primary motor hand area (M1-HAND) have been combined to explore whether the instantaneous expression of pericentral mu-rhythm drives fluctuations in corticomotor excitability, but this line of research has yielded diverging results.ObjectivesTo re-assess the relationship between the mu-rhythm power expressed in left pericentral cortex and the amplitude of motor potentials (MEP) evoked with spTMS in left M1-HAND.Methods15 non-preselected healthy young participants received spTMS to the motor hot spot of left M1-HAND. Regional expression of mu-rhythm was estimated online based on a radial source at motor hotspot and informed the timing of spTMS which was applied either during epochs belonging to the highest or lowest quartile of regionally expressed mu-power. Using MEP amplitude as dependent variable, we computed a linear mixed-effects model, which included mu-power and mu-phase at the time of stimulation and the inter-stimulus interval (ISI) as fixed effects and subject as a random effect. Mu-phase was estimated by post-hoc sorting of trials into four discrete phase bins. We performed a follow-up analysis on the same EEG-triggered MEP data set in which we isolated mu-power at the sensor level using a Laplacian montage centered on the electrode above the M1-HAND.ResultsPericentral mu-power traced as radial source at motor hot spot did not significantly modulate the MEP, but mu-power determined by the surface Laplacian did, showing a positive relation between mu-power and MEP amplitude. In neither case, there was an effect of mu-phase on MEP amplitude.ConclusionThe relationship between cortical oscillatory activity and cortical excitability is complex and minor differences in the methodological choices may critically affect sensitivity.
Chronic Exposure to Glucocorticoids Induces Suboptimal Decision-Making in Mice
Authors: Cabeza Lidia , Ramadan Bahrie , Giustiniani Julie , Houdayer Christophe , Pellequer Yann , Gabriel Damien , Fauconnet Sylvie , Haffen Emmanuel , Risold Pierre-Yves , Fellmann Dominique , Belin David , Peterschmitt Yvan 
Published: September 2020

AbstractAnxio-depressive symptoms as well as severe cognitive dysfunction including aberrant decision-making (DM) are documented in neuropsychiatric patients with hypercortisolaemia. Yet, the influence of the hypothalamo-pituitary-adrenal (HPA) axis on DM processes remains poorly understood. As a tractable mean to approach this human condition, adult male C57BL/6JRj mice were chronically treated with corticosterone (CORT) prior to behavioural, physiological and neurobiological evaluation. The behavioural data indicate that chronic CORT delays the acquisition of contingencies required to orient responding towards optimal DM performance in a mouse Gambling Task (mGT). Specifically, CORT-treated animals show a longer exploration and a delayed onset of the optimal DM performance. Remarkably, the proportion of individuals performing suboptimally in the mGT is increased in the CORT condition. This variability seems to be better accounted for by variations in sensitivity to negative rather than to positive outcome. Besides, CORT-treated animals perform worse than control animals in a spatial working memory (WM) paradigm and in a motor learning task. Finally, Western blotting neurobiological analyses show that chronic CORT downregulates glucocorticoid receptor expression in the medial Prefrontal Cortex (mPFC). Besides, corticotropin-releasing factor signalling in the mPFC of CORT individuals negatively correlates with their DM performance. Collectively, this study describes how chronic exposure to glucocorticoids induces suboptimal DM under uncertainty in a mGT, hampers WM and motor learning processes, thus affecting specific emotional, motor, cognitive and neurobiological endophenotypic dimensions relevant for precision medicine in biological psychiatry.
PSA-targeted Alpha-, Beta- and Positron Emitting Immuno-Theranostics in Murine Prostate Cancer Models and Non-Human Primates
Authors: Veach Darren R. , Storey Claire M. , Lückerath Katharina , Braun Katharina , von Bodman Christian , Lamminmäki Urpo , Kalidindi Teja , Strand Sven-Erik , Strand Joanna , Altai Mohamed , Damoiseaux Robert , Zanzonico Pat , Benabdallah Nadia , Pankov Dmitry , Scher Howard I. , Scardino Peter , Larson Steven M. , Lilja Hans , McDevitt Michael R. , Thorek Daniel L. J. , Ulmert David 
Published: September 2020

ABSTRACTPurposeMost prostate cancer (PCa) patients treated with androgen receptor (AR)-signaling inhibitors develop therapeutic resistance due to restoration of AR-functionality. Thus, there is a critical need for novel treatment approaches. Here we investigate the theranostic potential of hu5A10, a humanized monoclonal antibody specifically targeting free prostate-specific antigen (KLK3).Experimental DesignLNCaP-AR xenografts (NSG mice) andKLK3_Hi-Myctransgenic mice were imaged with89Zr- or treated with90Y- or225Ac-labeled hu5A10; biodistribution and subcellular localization were analyzed by gamma-counting, positron emission tomography (PET), autoradiography and microscopy. Therapeutic efficacy of [225Ac]hu5A10 and [90Y]hu5A10 in LNCaP-AR tumors was assessed by tumor volume measurements, time to nadir (TTN), time to progression (TTP), and survival. Pharmacokinetics of [89Zr]hu5A10 in non-human primates (NHP) were determined using PET.ResultsBiodistribution of radiolabeled hu5A10-constructs was comparable in different mouse models. Specific tumor uptake increased over time and correlated with PSA expression. Treatment with [90Y]/[225Ac]hu5A10 effectively reduced tumor burden and prolonged survival (p≤0.0054). Effects of [90Y]hu5A10 were more immediate than [225Ac]hu5A10 (TTN, p<0.0001) but less sustained (TTP, p<0.0001). Complete responses were observed in 7/18 [225Ac]hu5A10 and 1/9 mice [90Y]hu5A10. Pharmacokinetics of [89Zr]hu5A10 were consistent between NHPs and comparable to those in mice. [89Zr]hu5A10-PET visualized the NHP-prostate over the 2-week observation period.ConclusionsWe present a complete preclinical evaluation of radiolabeled hu5A10 in mouse PCa models and NHPs, and establish hu5A10 as a new theranostic agent that allows highly specific and effective downstream targeting of AR in PSA-expressing tissue. Our data support the clinical translation of radiolabeled hu5A10 for treating PCa.
Inequality in access to health and care services during lockdown – Findings from the COVID-19 survey in five UK national longitudinal studies
Authors: Topriceanu Constantin-Cristian , Wong Andrew , Moon James C , Hughes Alun D , Bann David , Chaturvedi Nish , Patalay Praveetha , Conti Gabriella , Captur Gabriella 
Published: September 2020

AbstractBackgroundAccess to health services and adequate care is influenced by sex, ethnicity, socio-economic position (SEP) and burden of co-morbidities. However, it is unknown whether the COVID-19 pandemic further deepened these already existing health inequalities.MethodsParticipants were from five longitudinal age-homogenous British cohorts (born in 2001, 1990, 1970, 1958 and 1946). A web and telephone-based survey provided data on cancelled surgical or medical appointments, and the number of care hours received during the UK COVID-19 national lockdown. Using binary or ordered logistic regression, we evaluated whether these outcomes differed by sex, ethnicity, SEP and having a chronic illness. Adjustment was made for study-design, non-response weights, psychological distress, presence of children or adolescents in the household, keyworker status, and whether participants had received a shielding letter. Meta-analyses were performed across the cohorts and meta-regression evaluated the effect of age as a moderator.Findings14891 participants were included. Females (OR 1·40, 95% confidence interval [1·27,1·55]) and those with a chronic illness (OR 1·84 [1·65-2·05]) experienced significantly more cancellations during lockdown (all p<0·0001). Ethnic minorities and those with a chronic illness required a higher number of care hours during the lockdown (both OR ≈2·00, all p<0·002). Age was not independently associated with either outcome in meta-regression. SEP was not associated with cancellation or care hours.InterpretationThe UK government’s lockdown approach during the COVID-19 pandemic appears to have deepened existing health inequalities, impacting predominantly females, ethnic-minorities and those with chronic illnesses. Public health authorities need to implement urgent policies to ensure equitable access to health and care for all in preparation for a second wave.
Economic implications of polypharmacy in Nepal: Multicenter community-based study
Authors: Sapkota Binaya , Shakya Suraj , Sah Saroj , Chaudhary Narendra , Tamang Bijendra , Karki Saugat Singh 
Published: September 2020

AbstractObjectiveImproper management of polypharmacy in community and hospital pharmacies may lead to adverse effects and drug interactions in patients of all age groups, especially children and the elderly. This study aimed to determine the scenario of polypharmacy in multiple communities in Nepal and the costs associated with them.DesignCross-sectional studySettingLocal communities of nine districts in NepalParticipantsTotal 400 patients of all age groups, who were consuming medicines and who fulfilled inclusion criteria from May 2017 to August 2018Primary and secondary outcome measuresA semi-structured questionnaire, based on the prescription optimization method, was used for data collection. Multinomial logistic regression was performed to analyze the statistical significance of polypharmacy with the predictor variables (e.g., age, education level, occupation, diagnosis, total cost of medicines). The p-value < 0.05 was considered statistically significant at 95% confidence interval. Polypharmacy cases and their economic implications were reported.ResultsEighty-one patients (20.3%) with an age group of 22-31 years with female patients (219, 54.8%) reported more polypharmacy events. There were 216 patients (54%) with prescriptions of five medicines i.e., moderate polypharmacy. Total number of medicines consumed by all 400 patients was 2269, with a mean±SD 5.67 ±1.08. Total expenditure by all 400 patients was USD 3409.54 during the study period, with a mean±SD8.66±6.04. Both moderate and severe polypharmacy cases were non-significantly related with age, gender and total cost of medications. They had significant relationship in almost all levels of education and occupation and showed mixed type of significance and non-significance with the diagnosis of the respondents.ConclusionPolypharmacy cases can be minimized, considering adverse drug reactions and drug interactions. Further studies are warranted in medication utilization and avoidable polypharmacy along with detailed pharmacoeconomic evaluation.
A new model of decision processing in instrumental learning tasks
Authors: Miletić Steven , Boag Russell J. , Trutti Anne C. , Forstmann Birte U. , Heathcote Andrew 
Published: September 2020

AbstractLearning and decision making are interactive processes, yet cognitive modelling of error-driven learning and decision making have largely evolved separately. Recently, evidence accumulation models (EAMs) of decision making and reinforcement learning (RL) models of error-driven learning have been combined into joint RL-EAMs that can in principle address these interactions. However, we show that the most commonly used combination, based on the diffusion decision model (DDM) for binary choice, consistently fails to capture crucial aspects of response times observed during reinforcement learning. We propose a new RL-EAM based on an advantage racing diffusion (ARD) framework for choices among two or more options that not only addresses this problem but captures stimulus difficulty, speed-accuracy trade-off, and stimulus-response-mapping reversal effects. The RL-ARD avoids fundamental limitations imposed by the DDM on addressing effects of absolute values of choices, as well as extensions beyond binary choice, and provides a computationally tractable basis for wider applications.
Prolonged low-dose dioxin exposure impairs metabolic adaptability to high-fat diet feeding in female but not male mice
Authors: Matteo Geronimo , Hoyeck Myriam P , Blair Hannah L , Zebarth Julia , Rick Kayleigh RC , Williams Andrew , Gagné Rémi , Buick Julie K , Yauk Carole L , Bruin Jennifer E 
Published: September 2020

AbstractObjectiveHuman studies consistently show an association between exposure to persistent organic pollutants, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD, aka “dioxin”), and increased diabetes risk, but rarely consider potential sex differences. We previously showed that a single high-dose TCDD exposure (20 µg/kg) decreased plasma insulin levels in both male and female micein vivo, but effects on glucose homeostasis were sex-dependent. The purpose of the current study was to determine whether prolonged exposure to a physiologically relevant low-dose of TCDD impacts glucose homeostasis and/or the islet phenotype in a sex-dependent manner in either chow-fed or high fat diet (HFD)-fed mice.MethodsMale and female mice were exposed to 20 ng/kg/d TCDD 2x/week for 12 weeks and simultaneously fed standard chow or a 45% HFD. Glucose homeostasis was assessed by glucose and insulin tolerance tests, and glucose-induced plasma insulin levels were measuredin vivo. Histological analysis was performed on pancreas from male and female mice, and islets were isolated from females at 12 weeks for Tempo-Seq® analysis.ResultsLow-dose TCDD exposure did not lead to adverse metabolic consequences in chow-fed male or female mice, or in HFD-fed males. However, TCDD accelerated the onset of HFD-induced hyperglycemia and impaired glucose-induced plasma insulin levels in female mice. TCDD caused a modest increase in islet area in males irrespective of diet, but reduced % beta cell area within islets in females. RNAseq analysis of female islets also revealed abnormal changes to endocrine and metabolic pathways in TCDD-exposed HFD-fed females compared chow-fed females.ConclusionsOur data suggest that prolonged low-dose TCDD exposure has minimal effects on glucose homeostasis and islet morphology in chow-fed male and female mice, but promotes maladaptive metabolic responses in HFD-fed females.
Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit
Authors: Blamey Ben , Toor Salman , Dahlö Martin , Wieslander Håkan , Harrison Philip J , Sintorn Ida-Maria , Sabirsh Alan , Wählby Carolina , Spjuth Ola , Hellander Andreas 
Published: September 2020

AbstractThis paper introduces theHASTE Toolkit, a cloud-native software toolkit capable of partitioning data streams in order to prioritize usage of limited resources. This in turn enables more efficient data-intensive experiments. We propose a model that introduces automated, autonomous decision making in data pipelines, such that a stream of data can be partitioned into a tiered or ordereddata hierarchy. Importantly, the partitioning is online and based on data content rather thana priorimetadata. At the core of the model areinterestingness functionsandpolicies. Interestingness functions assign a quantitative measure of interestingness to a single data object in the stream, an interestingness score. Based on this score, a policy guides decisions on how to prioritize computational resource usage for a given object. The HASTE Toolkit is a collection of tools to adapt data stream processing to this pipeline model. The result is smart data pipelines capable of effective or even optimal use of e.g. storage, compute and network bandwidth, to support experiments involving rapid processing of scientific data characterized by large individual data object sizes. We demonstrate the proposed model and our toolkit through two microscopy imaging case studies, each with their own interestingness functions, policies, and data hierarchies. The first deals with a high content screening experiment, where images are analyzed in an on-premise container cloud with the goal of prioritizing the images for storage and subsequent computation. The second considers edge processing of images for upload into the public cloud for a real-time control loop for a transmission electron microscope.Key PointsWe propose a pipeline model for building intelligent pipelines for streams, accounting for actual information content in data rather thana priorimetadata, and present the HASTE Toolkit, a cloud-native software toolkit for supporting rapid development according to the proposed model.We demonstrate how the HASTE Toolkit enables intelligent resource optimization in two image analysis case studies based on a) high-content imaging and b) transmission electron microscopy.We highlight the challenges of storage, processing and transfer in streamed high volume, high velocity scientific data for both cloud and cloud-edge use cases.