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The Editorial Board of the INSAM Journal of Contemporary Music, Art and Technology decided that both issues of 2022 will be dedicated to one main theme, namely, “Fighting for the attention: Music and art on social media”. We can say that this call for papers went very successfully, as we are now presenting to you INSAM Journal No. 9. In a year which has seen many grave turbulences on socio-economic and political levels on a global scale, we have once again confirmed the importance of social media for communication and the spreading of news, and we have also seen the limitations of these tools. Turning to music and art on social media, our Main Theme section consists of five intriguing papers, Beyond the Main Theme section has two articles, (Inter)Views bring three exciting pieces, and the Reviews one festival report.

This article examines the conditions under which a system of extended collective licensing (ECL) for the use of works contained in the collections of cultural heritage institutions (CHIs) participating in Europeana could function within a cross-border basis. ECL is understood as a form of collective rights management whereby the application of freely negotiated copyright licensing agreements between a user and a collective management organisation (“CMO”), is extended by law to non-members of the organisation. ECL regimes have already been put in place in a few Member States and so far, all have the ability to apply only on a national basis. This article proposes a mechanism that would allow works licensed under an ECL system in one territory of the European Union to be made available in all the territories of the Union. The proposal rests on the statutory recognition of the “country of origin” principle, as necessary and sufficient territory for the negotiation and application of an ECL solution for the rights clearance of works contained in the collection of a cultural heritage institution, including orphan works.

This report reviews the tools and mechanisms which could contribute to offsetting the negative effects of the current crisis on primary school outcomes in Madagascar. In a context of rapid deterioration of key education indicators, including enrollment and survival, key education stakeholders are faced with the challenging task of identifying tools and mechanisms that may contribute to rapidly restoring access to education. While a variety of programs have been implemented in the past, limited evidence exists on their potential impact on key factors influencing school outcomes. In addition, given the limited domestic and international resources at the disposal of policy-makers, priorities need to be established that will focus on the most urgent and important aspects of the current situation. This report aims at providing key stakeholders in the sector with information on existing tools and mechanisms that could potentially be used to put a halt to the rapid decline of the sectors. The analysis also identifies interventions with a strong potential to offset the effects of the crisis over the short and medium term.

This paper explores the link between archaeology and the digital humanities, especially the adoption of 3D modeling technology, which is becoming an integral part of archaeological practice. Here we present a case study, a sample of 3D models from a large collection of well-preserved medieval ceramics from the excavations of the Sanctuary of Zeus at Nemea, Greece. This growing digital collection can illustrate the advantages, potential, and challenges presented by the incorporation of 3D technology into archaeological practice. 3D modeling technology can facilitate documentation, interpretation, and publication of archaeological datasets. However, the longevity of these datasets remains uncertain and require extensive dialogue and collaboration, as storage space requirements, support of current digital infrastructure, and long-term data accessibility and preservation are matters that do not have standardized solutions. More effort needs to be invested in preserving these large datasets before 3D modeling can become fully incorporated into archaeological practice.

This study begins with a discussion regarding the military crises of third and early fourth century Roman Empire and how they appear to have missed Sicily entirely, resulting in the island entering a period of prosperity, especially in the rural regions. The direct link between the establishment of Constantinople as capital of the Empire and Sicily’s subsequent economic boom is also examined. Within this historical context, the relationship between the mosaics of North Africa and those of Sicily begins with a survey of the richly-decorated Villa Romana del Casale near modern-day Piazza Armerina. The extensive collections of mosaics adorning this villa are examined in depth and grouped thematically. Finally, comparisons of the motifs, and the methodologies used for creating these mosaics are made with similar, and in some cases even identical works found in North Africa, especially around Carthage. From this, it can be determined that not only were the mosaics of Piazza Armerina influenced by North African design, but they may have even been made by North African mosaicists themselves.

Il flyer presenta le attività dell'Historic Urban Landscape Workshop svoltosi i a Salerno il 26-27 novembre 2018. Il prodotto, sviluppato includendo gli elementi fondamentali della Visual Identity del progetto e nel rispetto degli obblighi di dissemination e communication previsti dall'Annotated Model Grant Agreement, dettaglia le presentazioni di best practices di riuso adattivo del patrimonio culturale italiano presso la Fondazione EBRIS di Salerno.

Data tables containing macroscopic facies description of subsurface data acquisition campaigns carried out in the Ria Formosa: 1) 41 manual holes with an Eijkelkamp Auger (code RFM); 2) 5 mechanical bores per roto-percussion with a 6t mobile drilling rig (code RF). The manual boreholes were photographed and described in situ, registering stratigraphy, colour, textural class, sedimentary structures, visible organic matter, and presence of bioclasts. The drilling depth oscillated between 1.55m and 8.6m. Mechanical boreholes were recovered and analysed in laboratory, described as the manual boreholes. Drilling depth oscillated between and between 11m and 26.5m. The boreholes were sampled, on average, every 0.6m (mechanical, in the laboratory) and 0.8m (manual, in the field). Selected samples were used for carbon-14 dating, and for textural and micropalaeontological analysis. Table is an export output of subsurface dataset created with Rockworks15. Borehole location is in decimal Lat. Long. WGS84 Datum. Data is published as part of the SIHER research project (PTDC/CTE-GIX112236/2009).

This paper describes the history and development of tafsir in Southeast Asia, namely Indonesia, Malaysia, Brunei Darusalam, Singapore and Thailand, aimed at providing a new discourse to the academic world, that Islam has another treasure in Far Asia, which is known as a pluralistic country because Islam entered in those countries without any wars. And to provide information related the books, author influence, and method of their tafsir in general.

The exam from HIST295 (History) in December 2013

Abstract copyright UK Data Service and data collection copyright owner.BackgroundThe Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.Household datasetsUp to 2015, the LFS household datasets were produced twice a year (April-June and October-December) from the corresponding quarter's individual-level data. From January 2015 onwards, they are now produced each quarter alongside the main QLFS. The household datasets include all the usual variables found in the individual-level datasets, with the exception of those relating to income, and are intended to facilitate the analysis of the economic activity patterns of whole households. It is recommended that the existing individual-level LFS datasets continue to be used for any analysis at individual level, and that the LFS household datasets be used for analysis involving household or family-level data. From January 2011, a pseudonymised household identifier variable (HSERIALP) is also included in the main quarterly LFS dataset instead.Change to coding of missing values for household seriesFrom 1996-2013, all missing values in the household datasets were set to one '-10' category instead of the separate '-8' and '-9' categories. For that period, the ONS introduced a new imputation process for the LFS household datasets and it was necessary to code the missing values into one new combined category ('-10'), to avoid over-complication. This was also in line with the Annual Population Survey household series of the time. The change was applied to the back series during 2010 to ensure continuity for analytical purposes. From 2013 onwards, the -8 and -9 categories have been reinstated.LFS DocumentationThe documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each volume alongside the appropriate questionnaire for the year concerned. However, LFS volumes are updated periodically by ONS, so users are advised to check the ONS LFS User Guidance page before commencing analysis.Additional data derived from the QLFSThe Archive also holds further QLFS series: End User Licence (EUL) quarterly datasets; Secure Access datasets (see below); two-quarter and five-quarter longitudinal datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.End User Licence and Secure Access QLFS Household datasetsUsers should note that there are two discrete versions of the QLFS household datasets. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. Secure Access household datasets for the QLFS are available from 2009 onwards, and include additional, detailed variables not included in the standard EUL versions. Extra variables that typically can be found in the Secure Access versions but not in the EUL versions relate to: geography; date of birth, including day; education and training; household and family characteristics; employment; unemployment and job hunting; accidents at work and work-related health problems; nationality, national identity and country of birth; occurrence of learning difficulty or disability; and benefits. For full details of variables included, see data dictionary documentation. The Secure Access version (see SN 7674) has more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.Changes to variables in QLFS Household EUL datasetsIn order to further protect respondent confidentiality, ONS have made some changes to variables available in the EUL datasets. From July-September 2015 onwards, 4-digit industry class is available for main job only, meaning that 3-digit industry group is the most detailed level available for second and last job.Review of imputation methods for LFS Household data - changes to missing valuesA review of the imputation methods used in LFS Household and Family analysis resulted in a change from the January-March 2015 quarter onwards. It was no longer considered appropriate to impute any personal characteristic variables (e.g. religion, ethnicity, country of birth, nationality, national identity, etc.) using the LFS donor imputation method. This method is primarily focused to ensure the 'economic status' of all individuals within a household is known, allowing analysis of the combined economic status of households. This means that from 2015 larger amounts of missing values ('-8'/-9') will be present in the data for these personal characteristic variables than before. Therefore if users need to carry out any time series analysis of households/families which also includes personal characteristic variables covering this time period, then it is advised to filter off 'ioutcome=3' cases from all periods to remove this inconsistent treatment of non-responders. Occupation data for 2021 and 2022 data filesThe ONS have identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. For further information on this issue, please see: https://www.ons.gov.uk/news/statementsandletters/occupationaldatainonssurveys. Main Topics:The LFS household datasets cover:characteristics of the household: number of people of working age; number of people over working age; number of children aged 0 to 4; number of children aged 5 to 15; number of dependent children (i.e. those in full-time education) aged 16 to 18economic activity in the household: number of people in employment; number of people in full-time employment; number of people in part-time employment; unemployed; economically inactive; students; sick or disabled; economically inactive but would like to work and are not seeking work because they do not believe there is work available ('discouraged workers'); care of dependants Compilation/Synthesis