1,145 research outputs found
A SMARC Effect for Loudness
Various reports suggest that the pitch height of musical tones may be represented along a mental space, with lower pitch heights represented on the left or lower sectors and higher pitch heights represented on the right or upper sectors of the mental space. Given that in Western languages the loudness of tones is often addressed spatially, with loud sounds referred to as \u201chigh\u201d and quiet sounds referred to as \u201clow,\u201d here we investigated whether loudness might also have a spatial representation. Participants judged whether a tone was louder or quieter than a reference tone, by pressing two keys: one at the top and the other at the bottom of a response box. Participants were faster in a situation where they pressed the key at the top to report louder sounds, and the key at the bottom to report quieter sounds, than vice versa. This result supports the view that loudness, like other types of magnitudes, might be represented spatially
Musicians have better memory than nonmusicians: A meta-analysis
Background
Several studies have found that musicians perform better than nonmusicians in memory tasks, but this is not always the case, and the strength of this apparent advantage is unknown. Here, we conducted a meta-analysis with the aim of clarifying whether musicians perform better than nonmusicians in memory tasks.
Methods
Education Source; PEP (WEB)\u2014Psychoanalytic Electronic Publishing; Psychology and Behavioral Science (EBSCO); PsycINFO (Ovid); PubMed; ScienceDirect\u2014AllBooks Content (Elsevier API); SCOPUS (Elsevier API); SocINDEX with Full Text (EBSCO) and Google Scholar were searched for eligible studies. The selected studies involved two groups of participants: young adult musicians and nonmusicians. All the studies included memory tasks (loading long-term, short-term or working memory) that contained tonal, verbal or visuospatial stimuli. Three meta-analyses were run separately for long-term memory, short-term memory and working memory.
Results
We collected 29 studies, including 53 memory tasks. The results showed that musicians performed better than nonmusicians in terms of long-term memory, g = .29, 95% CI (.08\u2013.51), short-term memory, g = .57, 95% CI (.41\u2013.73), and working memory, g = .56, 95% CI (.33\u2013.80). To further explore the data, we included a moderator (the type of stimulus presented, i.e., tonal, verbal or visuospatial), which was found to influence the effect size for short-term and working memory, but not for long-term memory. In terms of short-term and working memory, the musicians\u2019 advantage was large with tonal stimuli, moderate with verbal stimuli, and small or null with visuospatial stimuli.
Conclusions
The three meta-analyses revealed a small effect size for long-term memory, and a medium effect size for short-term and working memory, suggesting that musicians perform better than nonmusicians in memory tasks. Moreover, the effect of the moderator suggested that, the type of stimuli influences this advantage
Nabonidus, King of Babylon
It may seem anomalous to devote this column, which should contain the portrait of someone who contributed to the issue's main topic, to the last Neo-Babylonian king, having at disposal a considerable number of renowned scholars, explorers, philologists, and archaeologists who could well have deserved this attention: Pietro Della Valle, Carsten Niebuhr, Georg Friedrich Grotefend, Paul-Émile Botta, Austen Henry Layard, Robert Koldewey, and Ernest Renan are just some of the many possible illustrious candidates.There is basically one reason for the choice of Nabonidus: he is one of the very few characters involved with cultural heritage as both agent and object. As agent, he has been considered the first archaeologist ever, and—even if his description as "archaeologist" may be extreme—his use of the past for ideological purposes is undeniable; as object, he—or rather his acts, attitudes, and dispositions—were reinterpreted and transmitted to modern times through different literary testimonies
Preliminary study of food residues and cooking practices in the Medieval Hospital of Santa Maria della Scala in Siena (Central Italy)
El artĂculo trata sobre el estudio del uso de algunas cerámicas medievales y de los alimentos preparados y consumidos en el Hospital medieval del Santa Maria della Scala en Siena (Italia Central). Esta investigaciĂłn muestra la integraciĂłn entre los datos obtenidos con el análisis arqueolĂłgico y arqueomĂ©trico (utilizando el análisis de residuos orgánicos) de las cerámicas y la investigaciĂłn sobre los documentos histĂłricos encontrados en el mismo contexto, el hospital medieval del Santa Maria della Scala en Siena. DespuĂ©s del estudio arqueolĂłgico-formal, algunas cerámicas han sido seleccionadas para el análisis con cromatografĂa de gases acoplada a espectrometrĂa de masas con el fin de identificar los residuos orgánicos preservados y conocer su contenido original. Los datos obtenidos han sido integrados con la informaciĂłn proporcionada por los documentos escritos encontrados durante el estudio del Hospital acerca de las compras y de la vida cotidiana en su interior
Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course. A proof-of-principle study
Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options. Approaches to improve clinical decisions, such as collective intelligence of human groups and machine learning algorithms are widely investigated. Methods: Medical students and a machine learning algorithm predicted the course of disease on the basis of randomly chosen clinical records of patients that attended at the Multiple Sclerosis service of Sant'Andrea hospital in Rome. Results: A significant improvement of predictive ability was obtained when predictions were combined with a weight that depends on the consistence of human (or algorithm) forecasts on a given clinical record. Conclusions: In this work we present proof-of-principle that human-machine hybrid predictions yield better prognoses than machine learning algorithms or groups of humans alone. To strengthen this preliminary result, we propose a crowdsourcing initiative to collect prognoses by physicians on an expanded set of patients
Contribution of anthropogenic consolidation processes to subsidence phenomena from multi-temporal DInSAR: a GIS-based approach
The paper introduces an approach based on the combination of multi-temporal Differential Interferometric Synthetic Aperture Radar and geographical information systems analysis to investigate and separate several contributions to subsidence phenomena over the municipality of Ravenna (Emilia Romagna, Italy). In particular, the relationship between displacements detected over built environment and consolidation processes after construction was assessed and filtered out from the subsidence map to quantify the local overestimation of subsidence phenomena due to the mentioned processes. It requires descriptive attributes related to the age of construction and intended uses. The outcomes of the present study highlight ground consolidation processes that seem to be active over areas settled in the last 30 years with a component contributing to vertical rates up to 3 mm/yr. Such contribution represents the 20% of the cumulative displacements reported for coastal villages where different sources of subsidence increase the vulnerability to coastal erosion. We discuss the contribution of consolidation processes over a couple of recently settled areas to separate among contributions and avoid the misinterpretation of effects due to other anthropogenic sources of subsidence
Noise in multiple sclerosis: unwanted and necessary
As our knowledge about the etiology of multiple sclerosis (MS) increases, deterministic paradigms appear insufficient to describe the pathogenesis of the disease, and the impression is that stochastic phenomena (i.e. random events not necessarily resulting in disease in all individuals) may contribute to the development of MS. However, sources and mechanisms of stochastic behavior have not been investigated and there is no proposed framework to incorporate nondeterministic processes into disease biology. In this report, we will first describe analogies between physics of nonlinear systems and cell biology, showing how small-scale random perturbations can impact on large-scale phenomena, including cell function. We will then review growing and solid evidence showing that stochastic gene expression (or gene expression “noise”) can be a driver of phenotypic variation. Moreover, we will describe new methods that open unprecedented opportunities for the study of such phenomena in patients and the impact of this information on our understanding of MS course and therapy
About a new method to measure fractional Ca2+ currents through ligand-gated ion channels
[No abstract available
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