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Precipitation holds significant importance as a climate parameter in various applications, including studies on the impacts of climate change. However, its simulation or projection accuracy is low, primarily due to its high stochasticity. Specifically, climate models often overestimate the frequency of light rainy days while simultaneously underestimating the total amounts of extreme observed precipitation. This phenomenon, known as "drizzle bias", specifically refers to the model's tendency to overestimate the occurrence of light precipitation events. Consequently, even though the overall precipitation totals are generally well represented, there is often a significant bias in the number of rainy days. The present study aims to minimize the drizzle bias in model output by developing and applying two statistical approaches. In the first approach, the number of rainy days is adjusted based on the assumption that the relationship between observed and simulated rainy days remains the same in time (thresholding). In the second, a machine learning method (random forest or RF) is used for the development of a statistical model that describes the relationship between several climate (modelled) variables and the observed number of wet days. The results demonstrate that employing a multivariate approach yields results that are comparable to the conventional thresholding approach when correcting sub-periods with similar climate characteristics. However, the importance of utilizing RF becomes evident when addressing periods exhibiting extreme events, marked by a significantly distinct frequency of rainy days. These disparities are particularly pronounced when considering higher temporal resolutions. Both methods are illustrated on data from three EURO-CORDEX climate models. The two approaches are trained during a calibration period, and they are applied for the selected evaluation period. [ABSTRACT FROM AUTHOR]

The increasing trend of the intensity and frequency of temperature and precipitation extremes during the past decades has substantial environmental and socioeconomic impacts. Thus, the objective of the present study is the comparison of several statistical methods of the extreme value theory (EVT) in order to identify which is the most appropriate to analyze the behavior of the extreme precipitation, and high and low temperature events, in the Mediterranean region. The extremes choice was made using both the block maxima and the peaks over threshold (POT) technique and as a consequence both the generalized extreme value (GEV) and generalized Pareto distributions (GPDs) were used to fit them. The results were compared, in order to select the most appropriate distribution for extremes characterization. Moreover, this study evaluates the maximum likelihood estimation, the L-moments and the Bayesian method, based on both graphical and statistical goodness-of-fit tests. It was revealed that the GPD can characterize accurately both precipitation and temperature extreme events. Additionally, GEV distribution with the Bayesian method is proven to be appropriate especially for the greatest values of extremes. Another important objective of this investigation was the estimation of the precipitation and temperature return levels for three return periods (50, 100, and 150 years) classifying the data into groups with similar characteristics. Finally, the return level values were estimated with both GEV and GPD and with the three different estimation methods, revealing that the selected method can affect the return level values for both the parameter of precipitation and temperature. [ABSTRACT FROM AUTHOR]

This study analyses the temperature and precipitation dependence among stations in the Mediterranean. The first station group is located in the eastern Mediterranean (EM) and includes two stations, Athens and Thessaloniki, while the western (WM) one includes Malaga and Barcelona. The data was organized in two time periods, the hot-dry period and the cold-wet one, composed of 5 months, respectively. The analysis is based on a new statistical technique in climatology: the Copula method. Firstly, the calculation of the Kendall tau correlation index showed that temperatures among stations are dependant during both time periods whereas precipitation presents dependency only between the stations located in EM or WM and only during the cold-wet period. Accordingly, the marginal distributions were calculated for each studied station, as they are further used by the copula method. Finally, several copula families, both Archimedean and Elliptical, were tested in order to choose the most appropriate one to model the relation of the studied data sets. Consequently, this study achieves to model the dependence of the main climate parameters (temperature and precipitation) with the Copula method. The Frank copula was identified as the best family to describe the joint distribution of temperature, for the majority of station groups. For precipitation, the best copula families are BB1 and Survival Gumbel. Using the probability distribution diagrams, the probability of a combination of temperature and precipitation values between stations is estimated. [ABSTRACT FROM AUTHOR]

Viticulture represents an important economic activity for Greek agriculture. Winegrapes are cultivated in many areas covering the whole Greek territory, due to the favorable soil and climatic conditions. Given the dependence of viticulture on climate, the vitivinicultural sector is expected to be affected by possible climatic changes. The present study is set out to investigate the impacts of climatic change in Greek viticulture, using nine bioclimatic indices for the period 1981-2100. For this purpose, reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the regional climatic model Regional Climate Model Version 3 (RegCM3) are used. It was found that the examined regional climate model estimates satisfactorily these bioclimatic indices. The results of the study show that the increasing trend of temperature and drought will affect all wine-producing regions in Greece. In vineyards in mountainous regions, the impact is positive, while in islands and coastal regions, it is negative. Overall, it should be highlighted that for the first time that Greece is classified into common climatic characteristic categories, according to the international Geoviticulture Multicriteria Climatic Classification System (MCC system). According to the proposed classification, Greek viticulture regions are estimated to have similar climatic characteristics with the warmer wine-producing regions of the world up to the end of twenty-first century. Wine growers and winemakers should take the findings of the study under consideration in order to take measures for Greek wine sector adaptation and the continuation of high-quality wine production. [ABSTRACT FROM AUTHOR]

An exceptionally cold episode occurred in January 2017 over the Balkan Peninsula. Analysis of historical records showed that it was one of the coldest extreme episodes. Even though the low temperatures of January 2017 did not break previous low records for all stations, the long duration was quite extreme, resulting in strong socioeconomic impacts in the region of interest. The 10-year to 100-year return values of minimum temperatures were calculated based on block maxima method and the maximum likelihood estimates. The estimated return periods of the absolute minimum temperature are approximately 15 or 20 years for almost all stations. For only one station, the absolute minimum temperature of January 2017 might happen once in every 300 years according to the return level results. Moreover, the extreme cold episode over the Balkans during the period of 5 January 2017 to 12 January 2017 was associated with a significant outbreak of arctic air masses into eastern-central Europe and the Balkans and a cutoff low at the level of 500 hPa over the region. [ABSTRACT FROM AUTHOR]

The main goal of the present study is to identify the prevailing atmospheric circulation patterns (circulation types) that are associated with the occurrence of precipitation (both mean and extreme) over southern Romania. A daily circulation type calendar derived from an automatic and objective classification scheme is used in synergy with the daily precipitation time series from five weather stations in the study area for a sixty-year period (1961–2020). Both mean and extreme precipitation do not show statistically significant trends, except for the annual precipitation at Constanța, for the value with daily precipitation totals greater than the 95th percentile at Craiova and the number of days exceeding the 99th percentile at Buzău and Râmnicu -Vâlcea, where significant negative trends were noticed. Moreover, the precipitation trends were analyzed in relation to the atmospheric circulation types. Non-significant positive trends were observed for the precipitation amounts (annually, winter, spring, and autumn) corresponding to very rainy circulation types (C, Cwsw), while for summer, the equivalent trends were negative. Moreover, it became evident that during extreme precipitation events, the predominant circulation types (C, Cwsw) are associated with western or almost western atmospheric circulation and Mediterranean- or Atlantic-originated depressions. [ABSTRACT FROM AUTHOR]

Drought over the Greek region is characterized by a strong seasonal cycle and large spatial variability. Dry spells longer than 10 consecutive days mainly characterize the duration and the intensity of Greek drought. Moreover, an increasing trend of the frequency of drought episodes has been observed, especially during the last 20 years of the 20th century. Moreover, the most recent regional circulation models (RCMs) present discrepancies compared to observed precipitation, while they are able to reproduce the main patterns of atmospheric circulation. In this study, both a statistical and a dynamical downscaling approach are used to quantify drought episodes over Greece by simulating the Standardized Precipitation Index (SPI) for different time steps (3, 6, and 12 months). A statistical downscaling technique based on artificial neural network is employed for the estimation of SPI over Greece, while this drought index is also estimated using the RCM precipitation for the time period of 1961-1990. Overall, it was found that the drought characteristics (intensity, duration, and spatial extent) were well reproduced by the regional climate models for long term drought indices (SPI12) while ANN simulations are better for the short-term drought indices (SPI3). [ABSTRACT FROM AUTHOR]

The ability of a fine resolution regional climate model (10 × 10 km) in simulating efficiently the climate characteristics (temperature, precipitation, and wind) over Greece, in comparison to the previous version of the model with a 25 × 25 km resolution, is examined and analyzed in the present study. Overall, the results showed that the finer resolution model presented a better skill in generating low winter temperatures at high altitudinal areas, the temperature difference between the islands and the surrounding sea, high rainfall totals over the mountainous areas, the thermal storms during summer, and the wind maxima over the Aegean Sea. Regarding the future projections, even though the two models agree on the climatic signal, differences are found mainly to the magnitude of change of the selected parameters. Finally, it was found that at higher pressure levels, the present day projections of the two models do not show significant differences since the topography and terrain does not play such an important role as the general atmospheric circulation. [ABSTRACT FROM AUTHOR]

The aim of this work is to investigate the recent past and future patterns of the Etesian winds, one of the most persistent localized wind systems in the world, which dominates the wind regime during warm period over the Aegean Sea and eastern Mediterranean. An objective classification method, the Two Step Cluster Analysis (TSCA), is applied on daily data from regional climate model simulations carried out with RegCM3 for the recent past (1961-1990) and future periods (2021-2050 and 2071-2100) constrained at lateral boundaries either by ERA-40 reanalysis fields or the global circulation model (GCM) ECHAM5. Three distinct Etesian patterns are identified by TSCA with the location and strength of the anticyclonic action center dominating the differences among the patterns. In case of the first Etesian pattern there is a ridge located over western and central Europe while for the other two Etesian patterns the location of the ridge moves eastward indicating a strong anticyclonic center over the Balkans. The horizontal and vertical spatial structure of geopotential height and the vertical velocity indicates that in all three Etesian patterns the anticyclonic action center over central Europe or Balkan Peninsula cannot be considered as an extension of the Azores high. The future projections for the late 21st century under SRES A1B scenario indicate a strengthening of the Etesian winds associated with the strengthening of the anticyclonic action center, and the deepening of Asian thermal Low over eastern Mediterranean. Furthermore the future projections indicate a weakening of the subsidence over eastern Mediterranean which is rather controlled by the deepening of the south Asian thermal Low in line with the projected in future weakening of South Asian monsoon and Hadley cell circulations. [ABSTRACT FROM AUTHOR]

This paper revisits a mathematical model of motivic analysis, together with its computational realization, from an interdisciplinary perspective, relating it to concepts and methods in the field of computational music analysis. Issues such as segmentation, motivic formation, knowledge representation, similarity and categorization, and interpretation of results are discussed. A further introspection on the approach, in the context of mathematics, computation, and music analysis as a large interdisciplinary field, reveals relations between the three: the mathematical model (motivic topologies), its computational counterpart (OM-Melos), and music analysis (Réti's and Nattiez’ methods). In doing so, we stress the importance of neutrality, objectivity, and scientific rigour in the modelling part while at the same time preserving the freedom of the music analyst in order to create musically interesting results. [ABSTRACT FROM PUBLISHER]

In the present study, both parametric (peak over threshold: mean residual life, dispersion index, threshold choice) and non-parametric (percentiles indices 95% and 99%) statistical techniques are employed, aiming at the identification of rainfall thresholds above which a precipitation event can be characterized as extreme. The analysis is based on 45 years (1960-2004) rain gauge daily records from 65 meteorological stations over the European region. According to two climatologically based criteria that were introduced in the study, it was found that a combined peak over threshold methodology has been shown to yield higher threshold values above which extreme precipitation events occur, in comparison to the 95th percentile indices. Overall, concerning northern Europe, it was found that in the majority of the stations, the threshold values vary from 20 to 30 mm, while the results concerning the Mediterranean region are less coherent and the selection of extreme precipitation thresholds differs from region to region. Stations over eastern Mediterranean appear to have thresholds higher than 30 mm, while stations located over the main cyclone trajectories and the cyclogenesis zone of Mediterranean are those with the higher extreme precipitation thresholds (higher than 45 mm). [ABSTRACT FROM AUTHOR]

This paper reports on data mining of Cretan folk songs for distinctive patterns. A pattern is distinctive if it occurs with higher probability in a corpus as compared to an anticorpus. A small set of transcribed Cretan folk songs was encoded, organized using a knowledge base of classes, and mined using distinctive pattern discovery methods. In this exploratory study several highly distinctive melodic patterns emerge, indicating the ability of distinctive patterns to describe subgroups of folk songs. [ABSTRACT FROM AUTHOR]

This special issue of the Journal of Mathematics and Music addresses the topic of computational music analysis. It arose from a series of two international workshops on the topic, one in Berlin and one in Paris, both of which created interesting discussions and debates. In the call for papers, this special issue welcomed previously unpublished contributions that presented computational approaches of any type of music analysis. As a special focus, all papers were asked to analyse the same piece: the first movement of Brahms' String Quartet No. 1. The aim was to bring together diverse computational analytical approaches and methodologies, such as structural, motivic, semiotic, comparative, reductional, harmonic, transformational, and others, using a variety of computational implementation techniques. By focusing on to the same piece, similarities, differences, and complementarities among the approaches on both the methodological and the analytical results levels could be more easily observed. Authors were particularly encouraged to consider Forte's [1] and Huron's [2] analyses of the string quartet, and relate them to their own work if possible. Three papers were chosen for publication, which reflect the various aspects and levels of computation involved. [ABSTRACT FROM AUTHOR]

This study is motivated by an interest in obtaining a new automated classification scheme of daily circulation types suitable for use throughout Europe. The classification scheme is performed on 500 hPa geopotential height anomalies (NCEP Reanalysis data, 2.5°×2.5°). Nine grid points represent the study area. Five anticyclonic types (Anw, Ane, A, Asw and Ase) and seven cyclonic types (C, Cnnw, Cwnw, Cwsw, Cssw, Cse, Cne) are defined. Each of the circulation types has a distinct underlying synoptic pattern that produces the expected type and direction of flow over the study area. The classification scheme is applied to three different case studies in the Mediterranean Basin: Greece, Cyprus and central Italy. The precipitation percentage of the cyclonic type and the mean seasonal correlation coefficients for all circulation types are the two criteria used to evaluate the performance of the classification scheme. The ability of the HadAM3P general circulation model to reproduce the mean pattern and frequency of circulation types at the 500 hPa level in comparison to the NCEP dataset for the period 1960–1990 is also evaluated. The percentage of rainfall that corresponds to the cyclonic circulation types is greater than 85% for the three study regions. Furthermore, the correlation coefficients for the three classifications are very encouraging, for nearly all days of the study period. Compared to observations, the GCM is able to capture the mean patterns but not able to replicate exactly the observed variability of the circulation types over the three study regions. [ABSTRACT FROM AUTHOR]

Abstract: An estimation of the future changes in the extreme conditions over the Greek area has been attempted, by applying the output data from a GCM to two different statistical downscaling models. The first was a multiple linear regression model based on a circulation type approach (MLRct) and the second one used artificial neural networks (ANNs). Two extreme temperature indices (txq90, tnq10) and two extreme precipitation indices (pq90, pxcdd) were selected for the study and simulated by the statistical models. From the comparison of the models during a validation period, it was found that the MLRct was relatively more efficient and the circulation types were proven to be a more reliable predictor. However, both the models underestimated the natural variability of the observed time-series. Generally, the extreme temperature indices were simulated better than the precipitation ones and winter was the season that showed the highest downscaling skill. Subsequently, the present day and future extreme temperature and rainfall conditions were examined using four ensemble members (control runs) and five scenarios driven by the A2 and B2 emission SRES scenarios, from the atmospheric general circulation model HadAM3P. Concerning extreme temperatures, an increase of their values is expected during the future period 2070–2100, according to the MLRct model. The climate change signal of the ANNs model was not so strong and in some cases it was of opposite direction. The results for the extreme precipitation indices showed a spatial incoherence and more complex structure of change. [Copyright &y& Elsevier]

In this paper we describe a new method for discovering recurrent patterns in a corpus of segmented melodies. Elements of patterns in this scheme do not represent individual notes but rather represent melodic segments that are sequences of notes. A new knowledge representation for segmental patterns is designed, and a pattern discovery algorithm based on suffix trees is used to discover segmental patterns in large corpora. The method is applied to a large collection of melodies, including Nova Scotia folk songs, Bach chorale melodies, and sections from the Essen folk song database. Patterns are ranked using a statistical significance method that integrates pattern self-overlap, length, and frequency in a corpus into a single measure. A musical interpretation of some of the statistically significant discovered patterns is presented. [ABSTRACT FROM AUTHOR]

Greece and the surrounding areas experienced an early warm spell with characteristics of a typical summer Mediterranean heatwave in mid-May 2020. The maximum 2 m temperature at Kalamata (southern Greece) reached 40 °C on 16 May and at Aydin (Turkey), it was 42.6 °C on 17 May. There was a 10-standard deviation positive temperature anomaly (relative to the 1975–2005 climatology) at 850 hPa, with a southwesterly flow and warm advection over Greece and western Turkey from 11 to 20 May. At 500 hPa, a ridge was located over the Eastern Mediterranean, resulting in subsidence. The aims of this study were (a) to investigate the prevailing synoptic conditions during this event in order to document its occurrence and (b) to assess whether this out-of-season heatwave was predictable on subseasonal timescales. The subseasonal predictability is not a well-researched scientific topic in the Eastern Mediterranean Sea. The ensemble global forecasts from six international meteorological centres (European Centre for Medium-Range Weather Forecasts—ECMWF, United Kingdom Met Office—UKMO, China Meteorological Administration—CMA, Korea Meteorological Administration—KMA, National Centers for Environmental Prediction—NCEP and Hydrometeorological Centre of Russia—HMCR) and limited area forecasts using the Weather Research and Forecasting model with the Advanced Research dynamic solver (WRF) forced by Climate Forecast System version 2 (CFSv.2; NCEP) forecasts were evaluated for lead times ranging from two to six weeks using statistical scores. WRF was integrated using two telescoping nests covering Europe, the Mediterranean basin and large part of the Atlantic Ocean, with a grid spacing of 25 km, and Greece–western Turkey at 5 km. The results showed that there were some accurate forecasts initiated two weeks before the event's onset. There was no systematic benefit from the increase of the WRF model's resolution from 25 km to 5 km for forecasting the 850 hPa temperature, but regarding the prediction of maximum air temperature near the surface, the high resolution (5 km) nest of WRF produced a marginally better performance than the coarser resolution domain (25 km). [ABSTRACT FROM AUTHOR]

In climatology, there is a clear need for more reliable data, especially in regions where no meteorological stations exist. Different statistical methods as well as regional climate models are usually used for covering areas with limited data. However, important biases between real and simulated climate parameters are observed, especially with respect to extremes. The present study introduces a new statistical method that combines triangular irregular networks and copulas for the simulation of extreme maximum and minimum temperatures. According to the new method, a studied region can be divided into triangles, and a data series can be simulated for every unknown x‐point in each triangle. The simulation of new data series is based on both the distances between the unknown point and the triangle vertices and the observational data available at each vertex. The statistical evaluation of this new method was successful and further demonstrated that the size of the triangle as well as the climatic characteristics of the stations at the triangle vertices can significantly affect the final results. The present investigation proposes the triangular irregular network‐copula method for the simulation of extreme temperatures, as the projections provided by this method are shown to approach the observed extremes values for individual meteorological stations. [ABSTRACT FROM AUTHOR]

The sensitivity of RegCM4 to different physics parameterizations is being investigated in this study. It is the first part of an attempt to find the most optimal combination of configurations to "run" RegCM4 for the area of study. The spatial resolution of the model is 25 × 25 km. The performed simulations include changes in the model's convection, atmospheric boundary layer, and ocean flux schemes for the period 1981–1990 in the Mediterranean region. The simulations were forced by ERA-Interim data for the initial and boundary conditions (ICBC) and sea surface temperature (SST). The processing of the different simulated data was performed on a seasonal basis. For a detailed evaluation of the changes, the domain of study was divided in five smaller areas derived from the EURO-CORDEX analysis domain. E-OBS data were used to validate RegCM4. It has been found that UW-PBL scheme presents a negative bias regarding atmospheric boundary layer thickness and temperature, and it reduces the wet/dry biases of Holtslag PBL scheme. Additionally, BATS1e Monin-Obukhov scheme increases both precipitation and temperature. Regarding cumulus convection schemes, Grell scheme is characterized by a reduction of convective precipitation, while total precipitation increases mainly in the windward side of mountainous ranges. This scheme also presents a cold bias. Wind speed, in the case of Grell and UW-PBL schemes, presents a reduction in continental areas, while a reinforcement of the Etesian winds is evident in Aegean Sea. [ABSTRACT FROM AUTHOR]

In this paper we analyse the relationship between the mean and extreme precipitation for five stations in Hungary and the circulation types at the 500 hPa level, for a 52‐year period, 1958–2010. We used daily rainfall data for each station and a calendar of the daily circulation types at the 500 hPa geopotential height for Hungary based on an automatic classification scheme. A trend analysis showed that, in general, the mean and extreme precipitation rarely exhibit significant trends, similarly to previous studies. The only exception was found for the number of annual and summer rainy days in Budapest with significant negative trends (p = .05), as well as the number of days with rainfall amounts greater than the 95% probability level for Debrecen with a significant positive trend. It was found that the circulation types that are mainly responsible for the largest precipitation amounts overall show (in some cases significant) negative trends, as well as the precipitation amounts that are associated with them (Cwsw, Cse, Cwnw). In most cases, the circulation types that are prevailing during the extreme precipitation events are associated with western or almost‐western atmospheric circulations (Cwsw, Ase) and Mediterranean‐ or Atlantic‐origin depressions. [ABSTRACT FROM AUTHOR]

The highest rainfall totals (912.2 mm) and the largest number of raindays (133 days), since 1958, were recorded in Thessaloniki during the year of 2014. Extreme precipitation heights were also observed on a seasonal, monthly and daily basis. The examined year presented the highest daily rainfall intensity, the maximum daily precipitation and the largest number of heavy precipitation days (greater than 10 mm), and it also exceeded the previous amounts of precipitation of very wet (95th percentile) and extremely wet (99th percentile) days. According to the automatic circulation type classification scheme that was used, it was found that during this exceptionally wet year, the frequency of occurrence of cyclonic types at the near surface geopotential level increases, while the same types decreased at a higher atmospheric level (500 hPa). The prevailing type was type C which is located at the centre of the study area (Greece), but several other cyclonic types changed during this year not only their frequency but also their percentage of rainfall as well as their daily precipitation intensity. It should be highlighted that these findings differentiated on the seasonal-scale analysis. Moreover, out of the three teleconnection patterns that were examined (Scandinavian Pattern, Eastern Mediterranean Teleconnection Pattern and North Sea-Caspian Pattern), the Scandinavian one (SCAND) was detected during the most of the months of 2014 meaning that it was highly associated with intense precipitation over Greece. [ABSTRACT FROM AUTHOR]

The article discusses various papers published within the issue including one on audio input for the analysis of solo violin performance of Bach partitas, one on the problem of predicting bowing parameters from a score, and another on machine learning and music.

Fabry disease is a rare lysosomal storage disorder caused by mutations in the GLA gene, which, without treatment, can cause significant renal dysfunction. We evaluated the effects of enzyme replacement therapy with agalsidase alfa on renal decline in patients with Fabry disease using data from the Fabry Outcome Survey (FOS) registry. Male patients with Fabry disease aged >16 years at agalsidase alfa start were stratified by low (≤0.5 g/24 h) or high (>0.5 g/24 h) baseline proteinuria and by 'classic' or 'non-classic' phenotype. Overall, 193 male patients with low (n = 135) or high (n = 58) baseline proteinuria were evaluated. Compared with patients with low baseline proteinuria, those with high baseline proteinuria had a lower mean ± standard deviation baseline eGFR (89.1 ± 26.2 vs. 106.6 ± 21.8 mL/min/1.73 m2) and faster mean ± standard error eGFR decline (−3.62 ± 0.42 vs. −1.61 ± 0.28 mL/min/1.73 m2 per year; p < 0.0001). Patients with classic Fabry disease had similar rates of eGFR decline irrespective of baseline proteinuria; only one patient with non-classic Fabry disease had high baseline proteinuria, preventing meaningful comparisons between groups. In this analysis, baseline proteinuria significantly impacted the rate of eGFR decline in the overall population, suggesting that early treatment with good proteinuria control may be associated with renoprotective effects. [ABSTRACT FROM AUTHOR]

Background: Patient registries provide long-term, real-world evidence that aids the understanding of the natural history and progression of disease, and the effects of treatment on large patient populations with rare diseases. The year 2021 marks the 20th anniversary of the Fabry Outcome Survey (FOS), an international, multicenter, observational registry (NCT03289065). The primary aims of FOS are to broaden the understanding of Fabry disease (FD), an X-linked lysosomal storage disorder, and to improve the clinical management of affected patients. Here, we review the history of FOS and the analyses and publications disseminated from the registry, and we discuss the contributions FOS studies have made in understanding FD.Results: FOS was initiated in April 2001 and, as of January 2021, 4484 patients with a confirmed diagnosis and patient informed consent have been enrolled from 144 centers across 26 countries. Data from FOS have been published in nearly 60 manuscripts on a wide variety of topics relevant to FD. Analyses of FOS data have investigated the long-term effectiveness and safety of enzyme replacement therapy (ERT) with agalsidase alfa and its effects on morbidity and mortality, as well as the benefits of prompt and early treatment with agalsidase alfa on the progression of cardiomyopathy and the decline in renal function associated with FD. Based on analyses of FOS data, ERT with agalsidase alfa has also been shown to improve additional signs and symptoms of FD experienced by patients. FOS data analyses have provided a better understanding of the natural history of FD and the specific populations of women, children, and the elderly, and have provided practical tools for the study of FD. FOS has also provided methodology and criteria for assessing disease severity which contributed to the continuous development of medical practice in FD and has largely improved our understanding of the challenges and needs of long-term data collection in rare diseases, aiding in future rare disease real-world evidence studies.Conclusion: FOS over the last 20 years has substantially increased the scientific knowledge around improved patient management of FD and continues to expand our understanding of this rare disease. [ABSTRACT FROM AUTHOR]

Classification in music analysis involves the segmentation of a music piece and the categorisation of the segments depending on similarity-based criteria. In this paper we investigate, based on a formal approach, how variations in the representation of the musical segments and in the categorisation algorithm influence the outcome of the classification. More specifically, we vary the choice of features describing each segment, the way these features are represented, and the categorisation algorithm. At the same time, we keep the other parameters, that is the overall model architecture, the music pieces, and the segmentation, fixed. We show that the choice and representation of the features, but not the specific categorisation algorithm, have a strong impact on the obtained analysis. We introduce a distance function to compare the results of algorithmic and human classification, and we show that an appropriate choice of features can yield results that are very similar to a human classification. These results allow an objective evaluation of different approaches to music classification in a uniform setting. [ABSTRACT FROM AUTHOR]

This paper addresses the effects of estimated climate change on the sea-surface dynamics of the Aegean and Ionian Seas (AIS). The main aim is the identification of climate change impacts on the severity and frequency of extreme storm surges and waves in areas of the AIS prone to flooding. An attempt is made to define design levels for future research on coastal protection in Greece. Extreme value analysis is implemented through a nonstationary generalized extreme value distribution function, incorporating time harmonics in its parameters, by means of statistically defined criteria. A 50-year time span analysis is adopted and changes of means and extremes are determined. A Regional Climate Model (RegCM3) is implemented with dynamical downscaling, forced by ECHAM5 fields under 20C3M historical data for the twentieth century and the SRES-A1B scenario for the twenty-first century. Storm surge and wave models (GreCSSM and SWAN, respectively) are used for marine climate simulations. Comparisons of model results with reanalysis and field data of atmospheric and hydrodynamic characteristics, respectively, are in good agreement. Our findings indicate that the dynamically downscaled RegCM3 simulation adequately reproduces the present general circulation patterns over the Mediterranean and Greece. Future changes in sea level pressure and mean wind fields are estimated to be small, yet significant for marine extremes. In general, we estimate a projected intensification of severe wave and storm surge events during the first half of the twenty-first century and a subsequent storminess attenuation leading to the resettlement of milder extreme marine events with increased prediction uncertainty in the second half of the twenty-first century. [ABSTRACT FROM AUTHOR]

In this study an Artificial Neural Network called Self-Organizing Map (SOM) is used in order to classify the synoptic circulation over Europe and especially Eastern Mediterranean. The classification of circulation types is an effective way of summarizing and describing the atmospheric circulation and it is useful in climatology because it provides a better understanding of the climatic variability over an area. Here, the SOM methodology is applied on winter daily geopotential height anomalies of the 500 hPa level, for the period 1971–2000. Twelve unique circulation patterns are identified. Eight of these types are characterized as cyclonic, representing 61% of the total days examined and four types are characterized as anticyclonic, representing 39% of the study period. The results of this classification are comparable to other objective classifications applied on the same study region and present a similar image. Therefore, the SOM methodology is found to be applicable and useful in the classification of circulation types. [ABSTRACT FROM AUTHOR]