Interactions between nation branding and corporate branding

The aim of this article is studying interactions between nation branding and corporate branding through reviewing the literature. Results show that both branding of a country and its corporates have influence to each other, either positive or negative effect that is called virtuous cycle or a vicious cycle. In fact, these two types of branding, act as a synergistic reinforcement tool to protect, improve or enhance the other one and therefore should be observed and maintained simustainasly.Keywords: National Reputation, CorporateBranding, Brand Positive Cycle, National Identit

From imaging to simulation: a framework applied to simulate the blood flow in the carotids

In this work we present a methodology to extract information from medical imaging and use it for hemodynamical simulation in arteries. Based on in-vivo magnetic resonance images (MRI), the velocity of the blood flow has been measured at different positions and times. Also, the anatomy of the vessel has been converted into a volume mesh suitable for numerical modeling. This data has been used to solve computationally the dynamics of the fluid inside the artery in healthy and pathologic cases. As an application, we have developed a computational model within the carotids. The next step in the pipeline will be to extend the simulation to fluidstructure interaction (FSI) to find the parameters in an atherosclerotic plaque that could lead to rupture.Peer Reviewe

From imaging to simulation: a framework applied to simulate the blood flow in the carotids

In this work we present a methodology to extract information from medical imaging and use it for hemodynamical simulation in arteries. Based on in-vivo magnetic resonance images (MRI), the velocity of the blood flow has been measured at different positions and times. Also, the anatomy of the vessel has been converted into a volume mesh suitable for numerical modeling. This data has been used to solve computationally the dynamics of the fluid inside the artery in healthy and pathologic cases. As an application, we have developed a computational model within the carotids. The next step in the pipeline will be to extend the simulation to fluidstructure interaction (FSI) to find the parameters in an atherosclerotic plaque that could lead to rupture.Peer Reviewe

An observational prospective study of topical acidified nitrite for killing methicillin-resistant Staphylococcus aureus (MRSA) in contaminated wounds

Background Endogenous nitric oxide (NO) kills bacteria and other organisms as part of the innate immune response. When nitrite is exposed to low pH, NO is generated and has been used as an NO delivery system to treat skin infections. We demonstrated eradication of MRSA carriage from wounds using a topical formulation of citric acid (4.5%) and sodium nitrite (3%) creams co-applied for 5 days to 15 wounds in an observational prospective pilot study of 8 patients. Findings Following treatment with topical citric acid and sodium nitrite, 9 of 15 wounds (60%) and 3 of 8 patients (37%) were cleared of infection. MRSA isolates from these patients were all sensitive to acidified nitrite in vitro compared to methicillin-sensitive S. aureus and a reference strain of MRSA. Conclusions Nitric oxide and acidified nitrite offer a novel therapy for control of MRSA in wounds. Wounds that were not cleared of infection may have been re-contaminated or the bioavailability of acidified nitrite impaired by local factors in the tissue

Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound

Lung ultrasound (LUS) is an important imaging modality used by emergency physicians to assess pulmonary congestion at the patient bedside. B-line artifacts in LUS videos are key findings associated with pulmonary congestion. Not only can the interpretation of LUS be challenging for novice operators, but visual quantification of B-lines remains subject to observer variability. In this work, we investigate the strengths and weaknesses of multiple deep learning approaches for automated B-line detection and localization in LUS videos. We curate and publish, BEDLUS, a new ultrasound dataset comprising 1,419 videos from 113 patients with a total of 15,755 expert-annotated B-lines. Based on this dataset, we present a benchmark of established deep learning methods applied to the task of B-line detection. To pave the way for interpretable quantification of B-lines, we propose a novel "single-point" approach to B-line localization using only the point of origin. Our results show that (a) the area under the receiver operating characteristic curve ranges from 0.864 to 0.955 for the benchmarked detection methods, (b) within this range, the best performance is achieved by models that leverage multiple successive frames as input, and (c) the proposed single-point approach for B-line localization reaches an F1-score of 0.65, performing on par with the inter-observer agreement. The dataset and developed methods can facilitate further biomedical research on automated interpretation of lung ultrasound with the potential to expand the clinical utility.Comment: 10 pages, 4 figure

Evaluating assumptions of scales for subjective assessment of thermal environments – Do laypersons perceive them the way, we researchers believe?

International audienc

Evaluating assumptions of scales for subjective assessment of thermal environments – Do laypersons perceive them the way, we researchers believe?

People's subjective response to any thermal environment is commonly investigated by using rating scales describing the degree of thermal sensation, comfort, and acceptability. Subsequent analyses of results collected in this way rely on the assumption that specific distances between verbal anchors placed on the scale exist and that relationships between verbal anchors from different dimensions that are assessed (e.g. thermal sensation and comfort) do not change. Another inherent assumption is that such scales are independent of the context in which they are used (climate zone, season, etc.). Despite their use worldwide, there is indication that contextual differences influence the way the scales are perceived and therefore question the reliability of the scales’ interpretation. To address this issue, a large international collaborative questionnaire study was conducted in 26 countries, using 21 different languages, which led to a dataset of 8225 questionnaires. Results, analysed by means of robust statistical techniques, revealed that only a subset of the responses are in accordance with the mentioned assumptions. Significant differences appeared between groups of participants in their perception of the scales, both in relation to distances of the anchors and relationships between scales. It was also found that respondents’ interpretations of scales changed with contextual factors, such as climate, season, and language. These findings highlight the need to carefully consider context-dependent factors in interpreting and reporting results from thermal comfort studies or post-occupancy evaluations, as well as to revisit the use of rating scales and the analysis methods used in thermal comfort studies to improve their reliability

The Scales Project, a cross-national dataset on the interpretation of thermal perception scales

Thermal discomfort is one of the main triggers for occupants’ interactions with components of the built environment such as adjustments of thermostats and/or opening windows and strongly related to the energy use in buildings. Understanding causes for thermal (dis-)comfort is crucial for design and operation of any type of building. The assessment of human thermal perception through rating scales, for example in post-occupancy studies, has been applied for several decades; however, long-existing assumptions related to these rating scales had been questioned by several researchers. The aim of this study was to gain deeper knowledge on contextual influences on the interpretation of thermal perception scales and their verbal anchors by survey participants. A questionnaire was designed and consequently applied in 21 language versions. These surveys were conducted in 57 cities in 30 countries resulting in a dataset containing responses from 8225 participants. The database offers potential for further analysis in the areas of building design and operation, psycho-physical relationships between human perception and the built environment, and linguistic analyses

The Scales Project, a cross-national dataset on the interpretation of thermal perception scales

Thermal discomfort is one of the main triggers for occupants' interactions with components of the built environment such as adjustments of thermostats and/or opening windows and strongly related to the energy use in buildings. Understanding causes for thermal (dis-)comfort is crucial for design and operation of any type of building. The assessment of human thermal perception through rating scales, for example in post-occupancy studies, has been applied for several decades; however, long-existing assumptions related to these rating scales had been questioned by several researchers. The aim of this study was to gain deeper knowledge on contextual influences on the interpretation of thermal perception scales and their verbal anchors by survey participants. A questionnaire was designed and consequently applied in 21 language versions. These surveys were conducted in 57 cities in 30 countries resulting in a dataset containing responses from 8225 participants. The database offers potential for further analysis in the areas of building design and operation, psycho-physical relationships between human perception and the built environment, and linguistic analyses