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Abstract: The concept of muscle quality encompasses both microand macroscopic aspects of muscle architecture and composition and has gained increasing attention with inclusion in the definition of sarcopenia, indicating the significance of muscle quality in evaluating muscle function and strength among older individuals. Muscle quality consists of two main components: neuromuscular and morphological and is often defined as the ratio between the two. The aim of this review is to present currently used methods for assessment of muscle quality with an emphasis on neuromuscular component in older adults. The most used methods for assessing morphological component are imaging techniques, such as magnetic resonance imaging, computed tomography, dualenergy X-ray absorptiometry and non-imaging bioimpedance analysis. In the neuromuscular component upper and lower body strength are assessed with different methods such as hand grip strength, isokinetic lower limb strength and isometric lower limb strength. Currently, there are three proposed muscle quality assessment methods for field or population studies: muscle quality index, ultrasound sarcopenia index and bioimpedancederived phase angle. Despite the exploration of muscle quality through various assessment methods, a consensus on the most appropriate and universally applicable approach has yet to be established.
Keywords: ageing, skeletal muscle, ultrasound sarcopenia index, muscle quality index, phase angle
Published in DiRROS: 13.05.2024; Views: 129; Downloads: 110
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Abstract: Dream research is entering a new era of accelerating insights and discoveries, thanks to the rise of powerful digital analysis tools that are enabling important advances in the empirical study of dreams. This paper illustrates the use of these tools, drawing on the resources of the Sleep and Dream Database, a free online archive of information about sleep and dreaming. These tools include statistical analyses of survey responses, systematic word searches of large collections of dream reports, and a well-grounded set of baseline frequencies to help with comparative measurement. The goal of this paper is to provide readers with an initial orienta-tion to the new world of dream discovery that has opened up because of tools like these. Several basic empirical findings are presented regarding clearly observable patterns of perception, emotion, and social interaction in dreaming. The paper will close with reflections on the emerging interplay of dreaming and technology.
Keywords: dreams, word searching, content analysis, continuity hypothesis
Published in DiRROS: 13.05.2024; Views: 142; Downloads: 76
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Abstract: The aim of the current study was to explore the impact of the CoVID-19 out-break on the dreams of a group of Italian participants. a total of 403 individuals were recruited online through a cross-sectional survey on Moodle. The qualitati-ve content of their dreams was analysed using the Dream Interview (TKYDQ), a tool created by Bulkeley. In addition, the Pittsburgh Sleep Quality Index (PSQI) was used to assess the quantitative aspects of dreams. from the results of our stu-dy, three macro-categories of content in the participants' dreams were identified: 1) dreams with phobic content; 2) dreams with a persecutory theme and 3) “old normal” dreams. Moreover, some sleep-related difficulties such as problems falling asleep and mild clinical sleep disorders were identified in the sample. The pro-longed quarantine and the lifestyle adopted during the pandemic have intensely influenced our dream activities, and it seems that CoVID-19 has already entered our collective unconscious in a symbolic way and through the processing of images and scenes related to the epidemic. The study, therefore, aims to explore how cata-strophic events affect mental health, specifically sleep quality and dream content.
Keywords: dreams, sleep, collective trauma, COVID-19, pandemic
Published in DiRROS: 13.05.2024; Views: 116; Downloads: 94
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Abstract: The historiography of dreams has yet to emerge as a distinct field, and key changes in dream research are worthy of consideration to reflect on tacit knowled-ge in academia. Gesturing toward such a historiography, the historical construc-tion of the “dream” is examined from a discursive perspective via localization in the internal/external and subjective/objective, communicative and social imagined spaces of dreams, as well as the theoretical paradigms of essentialism and contextu-alism. Premodern to post-postmodern epistemes are considered as shaping forces in these discourses, involving power and authority in determining what counts as legitimate or significant knowledge. The discussion concludes with reflections on the current state of dream research from a post-postmodern perspective, suggesting the ontological multiplicity of the “dream.”
Keywords: historiography of dreams, history of dreams, discourse, epistemes, intellectual history, post-postmodernism
Published in DiRROS: 13.05.2024; Views: 141; Downloads: 232
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Abstract: For a set ${\mathcal Q}$ of points in the plane and a real number $\delta \ge 0$, let $\mathbb{G}_\delta({\mathcal Q})$ be the graph defined on ${\mathcal Q}$ by connecting each pair of points at distance at most $\delta$. We consider the connectivity of $\mathbb{G}_\delta({\mathcal Q})$ in the best scenario when the location of a few of the points is uncertain, but we know for each uncertain point a line segment that contains it. More precisely, we consider the following optimization problem: given a set ${\mathcal P}$ of $n-k$ points in the plane and a set ${\mathcal S}$ of $k$ line segments in the plane, find the minimum $\delta \ge 0$ with the property that we can select one point $p_s\in s$ for each segment $s\in {\mathcal S}$ and the corresponding graph $\mathbb{G}_\delta( {\mathcal P}\cup \{ p_s\mid s\in {\mathcal S}\})$ is connected. It is known that the problem is NP-hard. We provide an algorithm to exactly compute an optimal solution in ${\mathcal O}(f(k) n \log n)$ time, for a computable function $f(\cdot)$. This implies that the problem is FPT when parameterized by $k$. The best previous algorithm uses ${\mathcal O}((k!)^k k^{k+1}\cdot n^{2k})$ time and computes the solution up to fixed precision.
Keywords: computational geometry, uncertainty, geometric optimization, fixed parameter tractability, parametric search
Published in DiRROS: 13.05.2024; Views: 134; Downloads: 147
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