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Forestry has traditionally been one of Myanmar's most important economic sectors, generating more in export earnings in the period 2010-2018. It is estimated that the country will have lost 12 million ha of forest between 1990 and 2020 - the third largest absolute forest loss of all countries during that period. The government now aims to restore or reforest about 884,000 ha on reserved forest (RF) and public protected forest (PPF) land under its 2016-28 Myanmar reforestation and rehabilitation program (MRRP). A range of reforms is needed to encourage private sector investment. These include: (i) identification of sufficiently large areas of suitable land close to potential processing sites or transport infrastructure and planning of land-use allocation; (ii) improving the availability of information on identified areas and on the process of acquiring plantation leases; (iii) streamlining leasing procedures and terms and scope of leases, including possible private management of state plantations; (iv) simplifying regulations on harvest and transport of plantation timber; (v) reviewing the suitability of current fiscal incentives, including tax holidays; (vi) improving information on areas and productivity of established plantations; and (vii) identifying priority research and development needs and delivery mechanisms.

The Maltese-English parallel corpus MaCoCu-mt-en 1.0 was built by crawling the ".mt" internet top-level domain in 2021, extending the crawl dynamically to other domains as well. All the crawling process was carried out by the MaCoCu crawler (https://github.com/macocu/MaCoCu-crawler). Websites containing documents in both target languages were identified and processed using the tool Bitextor (https://github.com/bitextor/bitextor). Considerable efforts were devoted into cleaning the extracted text to provide a high-quality parallel corpus. This was achieved by removing boilerplate and near-duplicated paragraphs and documents that are not in one of the targeted languages. Document and segment alignment as implemented in Bitextor were carried out, and BicleanerAI (https://github.com/bitextor/bicleaner-ai) and Bifixer (https://github.com/bitextor/bifixer) were used for fixing, cleaning, and deduplicating the final version of the corpus. While the TXT format consists solely of pairs of source and target segments (one or several sentences), each segment pair in the TMX format is accompanied by the following metadata: - source and target document URL; - quality score as provided by the tool BicleanerAI; - translation direction identification: the source segment in each segment pair was identified by using a probabilistic model; - personal information identification ("biroamer-entities"): segments containing personal information are flagged, so final users of the corpus can decide whether to use these segments; - language variants: the language variant of English (British or American) was identified for every segment pair on document and domain level. Notice and take down: Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please: (1) Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted. (2) Clearly identify the copyrighted work claimed to be infringed. (3) Clearly identify the material that is claimed to be infringing and information reasonably sufficient in order to allow us to locate the material. (4) Please write to the contact person for this resource whose email is available in the full item record. We will comply with legitimate requests by removing the affected sources from the next release of the corpus. This action has received funding from the European Union's Connecting Europe Facility 2014-2020 - CEF Telecom, under Grant Agreement No. INEA/CEF/ICT/A2020/2278341. This communication reflects only the author's view. The Agency is not responsible for any use that may be made of the information it contains.