Quantification of radial arterial pulse characteristics change during exercise and recovery

It is physiologically important to understand the arterial pulse waveform characteristics change during exercise and recovery. However, there is a lack of a comprehensive investigation. This study aimed to provide scientific evidence on the arterial pulse characteristics change during exercise and recovery. Sixty-five healthy subjects were studied. The exercise loads were gradually increased from 0 to 125 W for female subjects and to 150 W for male subjects. Radial pulses were digitally recorded during exercise and 4-min recovery. Four parameters were extracted from the raw arterial pulse waveform, including the pulse amplitude, width, pulse peak and dicrotic notch time. Five parameters were extracted from the normalized radial pulse waveform, including the pulse peak and dicrotic notch position, pulse Area, Area1 and Area2 separated by notch point. With increasing loads during exercise, the raw pulse amplitude increased significantly with decreased pulse period, reduced peak and notch time. From the normalized pulses, the pulse Area, pulse Area1 and Area2 decreased, respectively, from 38 ± 4, 61 ± 5 and 23 ± 5 at rest to 34 ± 4, 52 ± 6 and 13 ± 5 at 150-W exercise load. During recovery, an opposite trend was observed. This study quantitatively demonstrated significant changes of radial pulse characteristics during different exercise loads and recovery phases

What Is ‘Value’ and How Can We Capture It from the Product Value Chain?

The mobile phone industry is based upon the rapid development of handsets and the high turnover of devices in order to drive sales. Phones are often used for shorter periods of time than their designed life, and when discarded it is often through channels that result in lost resource. This unsustainable business model places strain on resources and creates adverse environmental and social impacts. Through interrogation of a stock and flow model, a product-service system (PSS) for a small consumer electronic device, a mobile telephone, is proposed. The points at which value may be extracted from the PSS are identified. A quantitative measure of value is proposed in order to allow the evaluation of the most appropriate time to extract it. This value is not solely monetary, but is derived from the combination of indicators which encompass environmental, economic, and technological factors. A worked example is presented, in which it is found that the precious metals within the phone are the main determinants for value extraction. These metals are found in the printed circuit board, leading to a requirement to design phones for ease of extraction of these components in order to access the value within

A Semi-Analytical Model for Crack Kinking out of The Interface of Bimaterial Anisotropic Layers

Bimaterial interface cracks in composite materials can either continue propagating along the interface or deviate their path, an event known as crack kinking, which can heavily impact structural integrity. To understand the crack kinking phenomenon, in literature is proposed a linear mathematical model based on six coefficients, which depend only on the kink angle and material properties. While earlier studies offer limited data on these coefficients for specific bimaterials, our work presents a verified semi-analytical approach that served as the foundation for the newly developed Matlab app introduced to compute coefficients for a wider range of bimaterial combinations

Five-year risk of HIV diagnosis subsequent to 147 hospital-based indicator diseases: a Danish nationwide population-based cohort study

Lars Haukali Omland,1 Rebecca Legarth,1 Magnus Glindvad Ahlström,1 Henrik Toft Sørensen,2 Niels Obel1 1Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Copenhagen, 2Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark Background: It has been suggested that targeted human immunodeficiency virus (HIV) testing programs are cost-effective in populations with an HIV prevalence >0.1%. Several indicator diseases are known to be associated with increased risk of HIV infection, but estimates of HIV frequency in persons with relevant indicator diseases are nonexistent. Methods: In a nationwide population-based cohort study encompassing all Danish residents aged 20–60 years during 1994–2013, we estimated the 5-year risk of an HIV diagnosis (FYRHD) after a first-time diagnosis of 147 prespecified potential indicator diseases. To estimate the risk of HIV diagnosis in the general population without any indicator diseases, we calculated the FYRHD starting at age 25, 35, 45, and 55 years. Results: The risk in the male general population was substantially higher than the female general population, and the risk was lower in the older age categories. Individuals of African origin had a higher FYRHD than individuals of Danish origin. A number of diseases were identified with a FYRHD >0.1%, with infectious diseases, such as syphilis, hepatitis, and endocarditis, associated with a particularly high FYRHD. Other potential indicator diseases, such as most urologic, nephrologic, rheumatologic, and endocrine disorders were generally associated with a low FYRHD. Conclusion: Our study identified a large number of indicator diseases associated with a FYRHD >0.1%. These data can be used as a tool for planning targeted HIV screening programs. Keywords: HIV, indicator diseases, HIV screening, public healt

Five-year risk of HIV diagnosis subsequent to 147 hospital-based indicator diseases: a Danish nationwide population-based cohort study [Erratum]

Omland LH, Legarth R, Ahlström MG, et al. Clin Epidemiol. 2016;8:333–340.  On page 338, Table 1 was referenced in error under the heading “Patient categories with a particularly high FYRHD”. The incorrect sentence read as “The ten combinations of indicator diseases, age, and sex with the highest FYRDH among individuals of Danish origin, as well as the ten indicator diseases with the highest FYRHD among individuals of African origin, are shown in Table 1.” The correct sentence should read “The ten combinations of indicator diseases, age, and sex with the highest FYRHD among individuals of Danish origin, as well as the ten indicator diseases with the highest FYRHD among individuals of African origin, are shown in Table 2.” Table 2 was missed from being included in the paper.Read the original article&nbsp