Search

Membranes are a key component of proton exchange membrane water electrolysis (PEMWE) cells and are exposed to various stressors during operation, which can significantly reduce cell lifetime. PEMWE membranes incorporating woven web layers within the membrane structure for mechanical reinforcement are a promising, commonly used industrial strategy to mitigate the formation of membrane defects. Within this study the structural mechanics of a PEMWE cell is investigated, specifically the woven web reinforced membrane. Experimental tensile tests are conducted on the membrane to obtain stress-strain data. These measurements were utilized to parameterize a geometrically simplified model of the woven web reinforced membrane through a tensile test simulation. The validated model is applied in a 2D-cell simulation to identify resulting stresses and strains in the membrane during various electrolysis operation modes. The results herein allow the used PEMWE cell geometry to be systematically evaluated and optimized with respect to mechanical membrane stability. For the applied PEMWE cell setup, no failure is to expect during normal operation, including varied temperatures and differential pressure. Increasing the gap size at the edge of the electrochemically active cell area, however, leads to large deformations when the gap becomes larger than 0.2 mm.

Membranes are a key component of proton exchange membrane water electrolysis (PEMWE) cells and are exposed to various stressors during operation, which can significantly reduce cell lifetime. PEMWE membranes incorporating woven web layers within the membrane structure for mechanical reinforcement are a promising, commonly used industrial strategy to mitigate the formation of membrane defects. Within this study the structural mechanics of a PEMWE cell is investigated, specifically the woven web reinforced membrane. Experimental tensile tests are conducted on the membrane to obtain stress-strain data. These measurements were utilized to parameterize a geometrically simplified model of the woven web reinforced membrane through a tensile test simulation. The validated model is applied in a 2D-cell simulation to identify resulting stresses and strains in the membrane during various electrolysis operation modes. The results herein allow the used PEMWE cell geometry to be systematically evaluated and optimized with respect to mechanical membrane stability. For the applied PEMWE cell setup, no failure is to expect during normal operation, including varied temperatures and differential pressure. Increasing the gap size at the edge of the electrochemically active cell area, however, leads to large deformations when the gap becomes larger than 0.2 mm.

Humans are ubiquitously exposed to endocrine disrupting chemicals (EDCs), substances that interfere with endogenous hormonal signaling. Exposure during early development is of particular concern due to the programming role of hormones during this period. A previous epidemiological study has shown association between prenatal co-exposure to 8 EDCs (Mixture N1) and language delay in children, suggesting an effect of this mixture on neurodevelopment. Furthermore, in utero exposure to Mixture N1 altered gene expression and behavior in adult mice. In this study, we investigated whether epigenetic mechanisms could underlie the long term effects of Mixture N1 on gene expression and behavior. To this end, we analyzed DNA methylation at regulatory regions of genes whose expression was affected by Mixture N1 in the hippocampus of in utero exposed mice using bisulfite-pyrosequencing. We show that Mixture N1 decreases DNA methylation in males at three genes that are part of the hypothalamus-pituitary-adrenal (HPA) axis: Nr3c1, Nr3c2, and Crhr1, coding for the glucocorticoid receptor, the mineralocorticoid receptor, and the corticotropin releasing hormone receptor 1, respectively. Furthermore, we show that the decrease in Nr3c1 methylation correlates with increased gene expression, and that Nr3c1, Nr3c2, and Crhr1 methylation correlates with hyperactivity and reduction in social behavior. These findings indicate that an EDC mixture corresponding to a human exposure scenario induces epigenetic changes, and thus programming effects, on the HPA axis that are reflected in the behavioral phenotypes of the adult male offspring.

Correct classification of fractures according to their patterns is critical for developing a treatment plan in orthopaedic surgery. Unfortunately, for proximal humeral fractures (PHF), methods for proper classification have remained a jigsaw puzzle that has not yet been fully solved despite numerous proposed classifications and diagnostic methods. Recently, many studies have suggested that three-dimensional printed models (3DPM) can improve the interobserver agreement on PHF classifications. Moreover, Virtual Reality (VR) has not been properly studied for classification of shoulder injuries. The current study investigates the PHF classification accuracy relative to an expert committee when using either 3DPM or equivalent models displayed in VR among 36 orthopaedic surgery residents from different hospitals. We designed a multicentric randomised controlled trial in which we created two groups: a group exposed to a total of 34 3DPM and another exposed to VR equivalents. Association between classification accuracy and group assignment (VR/3DPM) was assessed using mixed effects logistic regression models. The results showed VR can be considered a non-inferior technology for classifying PHF when compared to 3DPM. Moreover, VR may be preferable when considering possible time and resource savings along with potential uses of VR for presurgical planning in orthopaedics., CC BY 4.0© 2023, The Author(s)Published: 04 February 2023Funding for open access publishing: Universidad Málaga/CBUA.

Humans are ubiquitously exposed to endocrine disrupting chemicals (EDCs), substances that interfere with endogenous hormonal signaling. Exposure during early development is of particular concern due to the programming role of hormones during this period. A previous epidemiological study has shown association between prenatal co-exposure to 8 EDCs (Mixture N1) and language delay in children, suggesting an effect of this mixture on neurodevelopment. Furthermore, in utero exposure to Mixture N1 altered gene expression and behavior in adult mice. In this study, we investigated whether epigenetic mechanisms could underlie the long term effects of Mixture N1 on gene expression and behavior. To this end, we analyzed DNA methylation at regulatory regions of genes whose expression was affected by Mixture N1 in the hippocampus of in utero exposed mice using bisulfite-pyrosequencing. We show that Mixture N1 decreases DNA methylation in males at three genes that are part of the hypothalamus-pituitary-adrenal (HPA) axis: Nr3c1, Nr3c2, and Crhr1, coding for the glucocorticoid receptor, the mineralocorticoid receptor, and the corticotropin releasing hormone receptor 1, respectively. Furthermore, we show that the decrease in Nr3c1 methylation correlates with increased gene expression, and that Nr3c1, Nr3c2, and Crhr1 methylation correlates with hyperactivity and reduction in social behavior. These findings indicate that an EDC mixture corresponding to a human exposure scenario induces epigenetic changes, and thus programming effects, on the HPA axis that are reflected in the behavioral phenotypes of the adult male offspring.

Correct classification of fractures according to their patterns is critical for developing a treatment plan in orthopaedic surgery. Unfortunately, for proximal humeral fractures (PHF), methods for proper classification have remained a jigsaw puzzle that has not yet been fully solved despite numerous proposed classifications and diagnostic methods. Recently, many studies have suggested that three-dimensional printed models (3DPM) can improve the interobserver agreement on PHF classifications. Moreover, Virtual Reality (VR) has not been properly studied for classification of shoulder injuries. The current study investigates the PHF classification accuracy relative to an expert committee when using either 3DPM or equivalent models displayed in VR among 36 orthopaedic surgery residents from different hospitals. We designed a multicentric randomised controlled trial in which we created two groups: a group exposed to a total of 34 3DPM and another exposed to VR equivalents. Association between classification accuracy and group assignment (VR/3DPM) was assessed using mixed effects logistic regression models. The results showed VR can be considered a non-inferior technology for classifying PHF when compared to 3DPM. Moreover, VR may be preferable when considering possible time and resource savings along with potential uses of VR for presurgical planning in orthopaedics., CC BY 4.0© 2023, The Author(s)Published: 04 February 2023Funding for open access publishing: Universidad Málaga/CBUA.

Correct classification of fractures according to their patterns is critical for developing a treatment plan in orthopaedic surgery. Unfortunately, for proximal humeral fractures (PHF), methods for proper classification have remained a jigsaw puzzle that has not yet been fully solved despite numerous proposed classifications and diagnostic methods. Recently, many studies have suggested that three-dimensional printed models (3DPM) can improve the interobserver agreement on PHF classifications. Moreover, Virtual Reality (VR) has not been properly studied for classification of shoulder injuries. The current study investigates the PHF classification accuracy relative to an expert committee when using either 3DPM or equivalent models displayed in VR among 36 orthopaedic surgery residents from different hospitals. We designed a multicentric randomised controlled trial in which we created two groups: a group exposed to a total of 34 3DPM and another exposed to VR equivalents. Association between classification accuracy and group assignment (VR/3DPM) was assessed using mixed effects logistic regression models. The results showed VR can be considered a non-inferior technology for classifying PHF when compared to 3DPM. Moreover, VR may be preferable when considering possible time and resource savings along with potential uses of VR for presurgical planning in orthopaedics., CC BY 4.0© 2023, The Author(s)Published: 04 February 2023Funding for open access publishing: Universidad Málaga/CBUA.

Correct classification of fractures according to their patterns is critical for developing a treatment plan in orthopaedic surgery. Unfortunately, for proximal humeral fractures (PHF), methods for proper classification have remained a jigsaw puzzle that has not yet been fully solved despite numerous proposed classifications and diagnostic methods. Recently, many studies have suggested that three-dimensional printed models (3DPM) can improve the interobserver agreement on PHF classifications. Moreover, Virtual Reality (VR) has not been properly studied for classification of shoulder injuries. The current study investigates the PHF classification accuracy relative to an expert committee when using either 3DPM or equivalent models displayed in VR among 36 orthopaedic surgery residents from different hospitals. We designed a multicentric randomised controlled trial in which we created two groups: a group exposed to a total of 34 3DPM and another exposed to VR equivalents. Association between classification accuracy and group assignment (VR/3DPM) was assessed using mixed effects logistic regression models. The results showed VR can be considered a non-inferior technology for classifying PHF when compared to 3DPM. Moreover, VR may be preferable when considering possible time and resource savings along with potential uses of VR for presurgical planning in orthopaedics., CC BY 4.0© 2023, The Author(s)Published: 04 February 2023Funding for open access publishing: Universidad Málaga/CBUA.

Humans are ubiquitously exposed to endocrine disrupting chemicals (EDCs), substances that interfere with endogenous hormonal signaling. Exposure during early development is of particular concern due to the programming role of hormones during this period. A previous epidemiological study has shown association between prenatal co-exposure to 8 EDCs (Mixture N1) and language delay in children, suggesting an effect of this mixture on neurodevelopment. Furthermore, in utero exposure to Mixture N1 altered gene expression and behavior in adult mice. In this study, we investigated whether epigenetic mechanisms could underlie the long term effects of Mixture N1 on gene expression and behavior. To this end, we analyzed DNA methylation at regulatory regions of genes whose expression was affected by Mixture N1 in the hippocampus of in utero exposed mice using bisulfite-pyrosequencing. We show that Mixture N1 decreases DNA methylation in males at three genes that are part of the hypothalamus-pituitary-adrenal (HPA) axis: Nr3c1, Nr3c2, and Crhr1, coding for the glucocorticoid receptor, the mineralocorticoid receptor, and the corticotropin releasing hormone receptor 1, respectively. Furthermore, we show that the decrease in Nr3c1 methylation correlates with increased gene expression, and that Nr3c1, Nr3c2, and Crhr1 methylation correlates with hyperactivity and reduction in social behavior. These findings indicate that an EDC mixture corresponding to a human exposure scenario induces epigenetic changes, and thus programming effects, on the HPA axis that are reflected in the behavioral phenotypes of the adult male offspring.

Humans are ubiquitously exposed to endocrine disrupting chemicals (EDCs), substances that interfere with endogenous hormonal signaling. Exposure during early development is of particular concern due to the programming role of hormones during this period. A previous epidemiological study has shown association between prenatal co-exposure to 8 EDCs (Mixture N1) and language delay in children, suggesting an effect of this mixture on neurodevelopment. Furthermore, in utero exposure to Mixture N1 altered gene expression and behavior in adult mice. In this study, we investigated whether epigenetic mechanisms could underlie the long term effects of Mixture N1 on gene expression and behavior. To this end, we analyzed DNA methylation at regulatory regions of genes whose expression was affected by Mixture N1 in the hippocampus of in utero exposed mice using bisulfite-pyrosequencing. We show that Mixture N1 decreases DNA methylation in males at three genes that are part of the hypothalamus-pituitary-adrenal (HPA) axis: Nr3c1, Nr3c2, and Crhr1, coding for the glucocorticoid receptor, the mineralocorticoid receptor, and the corticotropin releasing hormone receptor 1, respectively. Furthermore, we show that the decrease in Nr3c1 methylation correlates with increased gene expression, and that Nr3c1, Nr3c2, and Crhr1 methylation correlates with hyperactivity and reduction in social behavior. These findings indicate that an EDC mixture corresponding to a human exposure scenario induces epigenetic changes, and thus programming effects, on the HPA axis that are reflected in the behavioral phenotypes of the adult male offspring.

Correct classification of fractures according to their patterns is critical for developing a treatment plan in orthopaedic surgery. Unfortunately, for proximal humeral fractures (PHF), methods for proper classification have remained a jigsaw puzzle that has not yet been fully solved despite numerous proposed classifications and diagnostic methods. Recently, many studies have suggested that three-dimensional printed models (3DPM) can improve the interobserver agreement on PHF classifications. Moreover, Virtual Reality (VR) has not been properly studied for classification of shoulder injuries. The current study investigates the PHF classification accuracy relative to an expert committee when using either 3DPM or equivalent models displayed in VR among 36 orthopaedic surgery residents from different hospitals. We designed a multicentric randomised controlled trial in which we created two groups: a group exposed to a total of 34 3DPM and another exposed to VR equivalents. Association between classification accuracy and group assignment (VR/3DPM) was assessed using mixed effects logistic regression models. The results showed VR can be considered a non-inferior technology for classifying PHF when compared to 3DPM. Moreover, VR may be preferable when considering possible time and resource savings along with potential uses of VR for presurgical planning in orthopaedics., CC BY 4.0© 2023, The Author(s)Published: 04 February 2023Funding for open access publishing: Universidad Málaga/CBUA.

Humans are ubiquitously exposed to endocrine disrupting chemicals (EDCs), substances that interfere with endogenous hormonal signaling. Exposure during early development is of particular concern due to the programming role of hormones during this period. A previous epidemiological study has shown association between prenatal co-exposure to 8 EDCs (Mixture N1) and language delay in children, suggesting an effect of this mixture on neurodevelopment. Furthermore, in utero exposure to Mixture N1 altered gene expression and behavior in adult mice. In this study, we investigated whether epigenetic mechanisms could underlie the long term effects of Mixture N1 on gene expression and behavior. To this end, we analyzed DNA methylation at regulatory regions of genes whose expression was affected by Mixture N1 in the hippocampus of in utero exposed mice using bisulfite-pyrosequencing. We show that Mixture N1 decreases DNA methylation in males at three genes that are part of the hypothalamus-pituitary-adrenal (HPA) axis: Nr3c1, Nr3c2, and Crhr1, coding for the glucocorticoid receptor, the mineralocorticoid receptor, and the corticotropin releasing hormone receptor 1, respectively. Furthermore, we show that the decrease in Nr3c1 methylation correlates with increased gene expression, and that Nr3c1, Nr3c2, and Crhr1 methylation correlates with hyperactivity and reduction in social behavior. These findings indicate that an EDC mixture corresponding to a human exposure scenario induces epigenetic changes, and thus programming effects, on the HPA axis that are reflected in the behavioral phenotypes of the adult male offspring.

The growth of clean energies and technologies requires a sound financial market, while equity and bond markets are exposed to geopolitical risks. We investigate the response of green equity and green bonds to newly develop decomposed measures of geopolitical risks, including geopolitical acts, threats, and narrow and broad measures. To this end, we apply two robust methods; namely, the cross-quantilogram and quantile and quantile (QQ) approaches, to estimate the conditional and unconditional volatility spillovers considering short, medium, and long term. Surprisingly our empirical investigation demonstrates that all measures of geopolitical risk (except geopolitical acts) transmit positive shocks to the green investments (both equity and bonds) from bearish to bullish market states. At the bullish state, green markets respond negatively to the highest quantiles of all measures of geopolitical risks under a long memory. However, the geopolitical acts negatively shock the green bonds and green equity at some extreme quantiles. Our empirical findings are beneficial by transmitting opportunities and preventing risks for investment decision-making in the green markets, considering geopolitical risks. © 2021

It is well established that renewable energy resources for electricity generation are free. In hot areas, solar energy has become one of the major interests of researchers and specialists. This paper aims to experimentally investigate the maximum voltage generation of a thermoelectric generator (TEG) panel. This panel was built from many TEG modules that are connected in series and in parallel. The panel was exposed to high heat due to solar radiation during summer, either directly or through a Fresnel lens. The other side of the TEG panel was cooled using tap water that was passed through aluminum heat exchangers in an active cooling method. It was found that the maximum open-circuit voltage of this TEG panel using a Fresnel lens was 9.35 V. With no lens, it was 11.75 V at 14:00 h local time. The experiments were done during a sunny July period in Iraq. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Online social networks provide a forum where people make new connections, learn more about the world, get exposed to different points of view, and access information that were previously inaccessible. It is natural to assume that content-delivery algorithms in social networks should not only aim to maximize user engagement but also to offer opportunities for increasing connectivity and enabling social networks to achieve their full potential. Our motivation and aim is to develop methods that foster the creation of new connections, and subsequently, improve the flow of information in the network. To achieve our goal, we propose to leverage the strong triadic closure principle, and consider violations to this principle as opportunities for creating more social links. We formalize this idea as an algorithmic problem related to the densest k-subgraph problem. For this new problem, we establish hardness results and propose approximation algorithms. We identify two special cases of the problem that admit a constant-factor approximation. Finally, we experimentally evaluate our proposed algorithm on real-world social networks, and we additionally evaluate some simpler but more scalable algorithms., QC 20220921

Duplex stainless steels are a group of widely used stainless steels, because of their attractive combination of strength and corrosion resistance. However, these steels embrittle because of a phase separation phenomenon in the ferrite phase when exposed to temperatures within the miscibility gap. This manuscript investigates the phase separation in two commercial stainless steels, the duplex stainless steel (DSS) 22Cr-5Ni (2205 or UNS S32205), and the super-duplex stainless steel (SDSS) 25Cr-7Ni (2507 or UNS S32750), and its subsequent effect on mechanical property evolution. Long-term isothermal aging heat treatments were carried out at industrially relevant temperatures between 250 °C and 350 °C for up to 48,000 hours, and quantitative measurements of the amplitude and wavelength of the phase separated nanostructure were obtained using Small-Angle Neutron Scattering (SANS). These quantifications were used as input parameters in hardness models to predict the hardness evolution. It is concluded that the quantitative information from SANS combined with these hardness models enables the prediction of hardness evolution in DSS at low temperatures, which in turn correlates with the embrittlement of the DSS., Correction in: Metallurgical and Materials Transactions A: Physical Metallurgy and Materials ScienceOpen AccessVolume 53, Issue 2, Pages 739. DOI: 10.1007/s11661-021-06571-4, WOS: 000738504300003, Scopus: 2-s2.0-85122249320, QC 20220921

The use of fibre reinforced concrete (FRC) elements without traditional reinforcement is increasing in applications for which the structure is exposed to cyclic loadings, such as pavements, bridge deck overlays and offshore structures. Cyclic loads produce tensile stresses that can lead to crack initiation and propagation, and thus compromising the mechanical performance and durability that may bring about noncompliance with service or limit state requirements. The loss of performance owe to material fatigue-induced strength degradation might be significantly accelerated in cracked cross-sections. This contribution presents the results and outcomes derived from an experimental program on the flexural fatigue behaviour of pre-cracked fibre reinforced concrete carried out on notched 600x150x150 mm beams. The evolution of the crack opening displacement and other design-sensitive parameters were monitored and analysed. The understanding of the damage propagation is the basis for the proposal of a design-oriented constitutive model, which is meant to be used for predicting the fatigue life in cracking-allowed concrete structures designed to be subjected to fatigue-inducing loads. The constitutive model was calibrated for a content (9 kg/m3) of a specific type of macrosynthetic fibre and considering different fatigue load levels., Postprint (author's final draft)

Modelling population dynamics in ecological systems reveals properties that are difficult to find by empirical means, such as the probability that a population will go extinct when it is exposed to harvesting. To study these properties, we use an aquatic ecological system containing one fish species and an underlying resource as our models. In particular, we study a class of stage-structured population systems with and without starvation. In these models, we study the resilience, the recovery potential, and the probability of extinction and show how these properties are affected by different harvesting rates, both in a deterministic and stochastic setting. In the stochastic setting, we develop methods for deriving estimates of these properties. We estimate the expected outcome of emergent population properties in our models, as well as measures of dispersion. In particular, two different approaches for estimating the probability of extinction are developed. We also construct a method to determine the recovery potential of a species that is introduced in a virgin environment., Export Date: 5 October 2022; Article; Correspondence Address: Aye, T.N.; Division of Applied Mathematics, Box 883, 721 23, Sweden; email: tin.nwe.aye@mdh.se

The widespread interest in learning analytics (LA) is associated with increased availability of and access to student data where students’ actions are monitored, recorded, stored and analyzed. The availability and analysis of such data is argued to be crucial for improved learning and teaching. Yet, these data can be exposed to misuse, for example, to be used for commercial purposes, consequently, resulting in information privacy concerns (IPC) of students who are the key stakeholders and data subjects in the LA context. The main objective of this study is to propose a theoretical model to understand the IPC of students in relation to LA. We explore the concept of IPC as a central construct between its two antecedents: perceived privacy vulnerability and perceived privacy control, and its consequences, trusting beliefs and self-disclosure behavior. Although these relationships have been investigated in other contexts, this study aims to offer mainly theoretical insights on how these relationships may be shaped in the context of LA in higher education. Understanding students’ IPC, the related root causes and consequences in LA is the key step to a more comprehensive understanding of privacy issues and the development of effective privacy practices that would protect students’ privacy in the evolving setting of data-driven higher education., QC 20220524

Universities around the world are teaching PLM following different strategies but most of them limited to design applications. This paper presents a didactic manufacturing plant where design and production are managed in a PLM environment. During the course, students are exposed to the complexity of managing the production of a modular chess set while at the same time they are asked to fulfil design requirements and meet production, quality and cost goals. Course description and achieved results are analyzed thoroughly. Moreover, the efforts to achieve the smart factory are presented.

A high-pressure die-casting process was employed to produce AZ91D components. These cast components were exposed to three different post-treatments: (1) clean blasting, (2) clean blasting and painting, and (3) painting (without clean blasting). The influence of the process parameters first phase injection speed, temperature of fixed half of the die, cooling time, and intensification pressure on distortion and residual stress of the components after each post-treatment were investigated. The results showed that intensification pressure was the most significant factor among the four parameters.

To assess the long-term leaching behaviour of UO2, the main constituent of spent nuclear fuel, the oxidative dissolution of UO2 pellets was studied at high H2O2 exposures ranging from 0.33 mol m(-2) to 1.36 mol m(-2). The experiments were performed in aqueous media containing 10 mM HCO3- where the pellets were exposed to H2O2 three consecutive times. The results indicate that the dissolution yield (amount of dissolved uranium per consumed H2O2) at high H2O2 exposures is significantly lower compared to previous studies of both pellets and powders and decreases for each H2O2 addition for a given pellet. This implies a change in redox reactivity, which is attributed to irreversible alteration of the pellet surface. Surface characterization after the exposure to H2O2, by SEM, XRD and Raman spectroscopy shows, that the surface of all pellets is significantly oxidized., QC 20200624

Grounded in an ontological, theoretical and methodological position that views children's views and experiences of domestic violence as critical to our understanding of those experiences, this letter to the editor reflects on Kimball's (Journal of Family Violence, 31, 625-637, 2016) review of research since 1999 when Edleson's influential article on children exposed to domestic violence was published (Journal of Interpersonal violence, 14(8), 839-870). Welcoming Kimball's call for research that can capture the full effects of children's exposure', we nonetheless challenge Kimball's criticism of the paucity of research literature directly capturing children's voices. Rather, we argue in this letter that Kimball's (Journal of Family Violence, 31, 625-637, 2016) methodology excluded those published qualitative studies which have engaged directly with children and sought to understand their lived experience of domestic violence. We conclude by highlighting our alignment with Kimball's assertion for the need to capture the voice and experience of children, but argue that this knowledge already exists. We also argue that some questions can only be answered by children and adolescents themselves.

Employees in manufacturing companies are consistently finding themselves exposed to changing job descrip tions and challenges in the era of Industrie 4.0. To ensure the preservation of productivity and competitive advantages, manufacturing companies need to train their employees in interacting with new, emerging technologies. This paper presents possibilities to arrange for the transfer of knowledge in production environments and describes a systematic approach for the conception of hands-on trainings. By means of a systematic guideline, the readers are given the opportunity to design successful hands-on trainings themselves., Export Date: 24 October 2017; Article; CODEN: ZZWFF. QC 20171205

We report for the first time on the ability of Raman microscopy to give information on the structure and composition of Be related samples mimicking plasma facing materials that will be found in ITER. For that purpose, we investigate two types of material. First: Be, W, Be1W9, and Be5W5 deposits containing a few percents of D or N, and second: a Mo mirror exposed to plasma in the main JET chamber (in the framework of the first mirror test in JET with ITER-like wall). We performed atomic quantifications using ion beam analysis for the first samples. We also did atomic force microscopy. We found defect induced Raman bands in Be, Be1W9, and Be5W5 deposits. Molybdenum oxide has been identified showing an enhancement due to a resonance effect in the UV domain., QC 20161024

This paper aim to identify and investigate a group of potential adopters that are compatible with Battery Electric Vehicles (BEV) in terms of range and charging, a group labeled as BEV Compatible (BEV-C). The results reveal that the BEV-C group constitutes 14 % of new vehicle buyers and that their intention to adopt BEVs are stronger compared to the non BEV-C group. The BEV-C group can be characterized as individuals that are less likely to conduct occasional longer drives (over 150 km), perceive BEVs more positively, have higher environmental awareness and have been exposed to more BEV information compared to the non BEV-C group., Conference code: 125226; Export Date: 22 May 2017; Conference Paper. QC 20170531

In this paper the impact of thermal and electrical aging on AC and impulse breakdown strength of oil-impregnated paper was investigated. Sheets of paper were thermally aged at 140 °C for 30 days. A comparison between AC and impulse breakdown strength of unaged paper layers, 10, 20 and 30 days thermally aged paper was performed. In order to investigate the effect of electrical aging, first the paper layers were exposed to partial discharges for 6 hours at accelerated electric stress. The partial discharge was created inside paper samples by introducing a disc shaped cavity on the center of the paper samples. The effect of partial discharges was then investigated on the impulse breakdown strength of oil-impregnated paper. The study shows that thermal aging has very small effect on AC breakdown strength. However, impulse breakdown strength of oil-impregnated paper may reduce up to 40% due to exposure to PD., QC 20160211

Tolah, A., Furnell, S. M., & Papadaki, M. (2019, June). A Comprehensive Framework for Understanding Security Culture in Organizations. In: L. Drevin, & M. Theocharidou (Eds.), Information Security Education. Education in Proactive Information Security: 12th IFIP WG 11.8 World Conference, WISE 12, Lisbon, Portugal, June 25–27, 2019, Proceedings (pp. 143-156). Switzerland, Cham: Springer. Available here