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"fi": "Tutkimuksessa haastateltiin 35 korkeasti koulutettua ihmistä heidän urahistorioistaan ja työllisyydestään, keskittyen pätkätyöläisyyteen ja määräaikaisiin työsuhteisiin ja siihen, miten pätkätyöläiset hahmottavat työnsä ja sen merkitykset. Haastateltavista 26 oli naisia, 9 miehiä. Ammattiryhmittäin jaoteltuna aineisto koostuu 13 tutkijan, 4 kätilön, 4 toimittajan, 4 sairaanhoitajan ja 10 projektiammattilaisen haastattelusta. Haastatteluaineistoa on yhteensä 506 sivua. Haastatteluissa kysyttiin vastaajilta heidän pätkätyöläisyyden kokemuksistaan. Haastattelut olivat kerronnallisia. Ainoa varsinainen haastattelukysymys oli \"Sinulla on kokemusta pätkätyöstä, kerrotko siitä?\", jonka jälkeen haastattelu muovautui haastattelijan ja haastateltavan yhteispelinä vapaamuotoisesti. Seuraavia seikkoja tuli esille useimmissa haastatteluissa: vastaajan koulutushistoria, työhistoria tai elämänkulku, pätkätöiden tavoitteet, vastaajan ammatti-identiteetti ja ammattiliittojäsenyys. Haastateltavat kertoivat myös pätkätyöläisyyden parhaista ja pahimmista puolista, pätkätyöläisen pärjäämisestä, taloudellisen epävarmuuden tunteesta, jaksamisesta, työyhteisön suhtautumisesta pätkätyöläisiin ja siitä, mitä yhteiskunnan tulisi tehdä pätkätyöläisyyden suhteen. Aineistosta on tehty html-versio, jonka hakemiston avulla haastatteluja/kirjoituksia/tms. on helppo selata."
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],
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"en": "A common finding in studies investigating support for reading problems is large inter-individual variation in responsiveness. This study examined factors associated with response to standardized educational support in children with reading difficulties. \r\n\r\nThe study sample consists of 357 Finnish children in Grades 3 and 4, as well as their SEN teachers and guardians. The children identified after teacher evaluation and individual assessment as having reading fluency difficulties were asked to participate in the study. The 13-week support period consisted of 1) weekly, manualized peer-group practice sessions instructed by SEN teachers at school, 2) independent practice at school with a digital reading game, and 3) home practice. \r\n\r\nThe study design consisted of four points of measurement: screening, pre, post, and follow-up. The data was collected in two consecutive cohorts in school years 2023-2024 and 2024-2025, the follow-up measures being carried out at the beginning of the following school year. \r\n\r\n1) The student data includes cognitive and academic skills assessments, as well as self-reports/questionnaires on learning-related emotions and academic self-beliefs, motivation, psychological well-being, experiences related to their social and learning environment, and reading habits. In addition, data was collected also of their involvement and activities with regard to all three elements of the support program. \r\n\r\n2) The guardian data includes questionnaire data of demographic information, family history of learning difficulties, parenting (e.g. parental self-efficacy, homework support) as well as parental reports on students’ difficulties, and their use of freetime. \r\n\r\n3) The teacher data consists of questionnaires data (self-reports) of professional experience, self-efficacy in teaching, stress and work engagement, and experiences of professional support. Teachers also provided data on participating students with respect to learning support provided at school, collaboration with parents, and their experiences of interaction with the students. During the study the teachers also kept diary of the implementation of support program. \r\n\r\nStudy was a part of the The Centre of Excellence in Learning Dynamics and Intervention Research (CoE InterLearn), funded by the Research Council of Finland for years 2022-2029.",
"fi": "Yleinen havainto lukemisvaikeuksissa tukemista koskevassa tutkimuskirjallisuudessa on suuri yksilöllinen vaihtelu tuesta hyötymisessä. Tässä tutkimuksessa tarkasteltiin tekijöitä, jotka ovat yhteydessä yksilöllisiin eroihin lukemissujuvuuteen kohdentuvasta standardoidusta tuesta hyötymisessä. \r\n\r\nTutkimusaineisto koostui 357 lapsesta koululuokilla 3 ja 4, sekä heidän erityisopettajistaan ja huoltajistaan. Osallistujiksi kutsuttiin lapsia, joilla oli sekä opettajan arvion että yksilöllisen lukutaidon arvioinnin perusteella tunnistettu lukutaidon sujuvuuden kehityksen ongelma. Tukijakso kesti 13 viikkoa, ja se koostui 1) erityisopettajan toteuttamista viikoittaisista, manualisoituun harjoitusohjelmaan perustuvista pienryhmätapaamisista, 2) lukutaidon itsenäisestä harjoittelusta lukutaidon tukemiseen kehitetyllä oppimispelillä, ja 3) kotiharjoittelusta. \r\n\r\nTutkimusasetelmassa oli neljä mittausajankohtaa: tutkittavien seulonta, alkumittaus, loppumittaus ja viivästetty mittaus. Aineisto kerättiin kahdesta kohortista peräkkäisinä kouluvuosina 2023-2024 ja 2024-2025. Viivästetty mittaus toteutettiin seuraavan kouluvuoden alussa. \r\n\r\n1) Oppilasta koskevat tiedot sisältävät kognitiivisten ja akateemisten taitojen testituloksia, sekä itsearviointeja/kyselylomakevastauksia oppimiseen liittyvistä tunteista, minäuskomuksista, motivaatiosta, psyykkisestä hyvinvoinnista, kokemuksista sosiaalisesta ja oppimisympäristöstä, sekä lukemistottumuksista. Lisäksi tutkimuksessa kerättiin tietoa heidän osallistumisestaan ja aktiivisuudestaan koskien tukiohjelman kolmea osa-aluetta. \r\n\r\n2) Huoltajalta kerätyt tiedot koskevat perheen demografisia taustatietoja, oppimisvaikeuksien perhetaustaa, näkemyksiä vanhemmuudesta (minäpystyvyys, koulutyön tukeminen) sekä huoltajien näkemyksiä lapsen oppimisen ongelmista sekä vapaa-ajan käytöstä. \r\n\r\n3) Opettajalta kerätyt tiedot koostuvat kyselylomakevastauksista koskien ammatillista kokemusta, minäpystyvyyttä, kuormittuneisuutta ja työn imua sekä kokemuksia ammatillisesta tuesta. Opettajilta kerättiin myös oppilaskohtaista tietoa koulussa tarjotusta oppimisen tuesta, yhteistyöstä vanhempien kanssa sekä kokemuksia oppilasvuorovaikutuksesta. Tutkimusaineistoon kuuluu myös opettajien tutkimuksen aikana pitämä päiväkirja tukiohjelman toteutumisesta. \r\n\r\nTutkimus oli osa Suomen Akatemian vuosille 2022-2029 rahoittaman Oppimisen ja interventiotutkimuksen huippuyksikön (CoE InterLearn) toimintaa."
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],
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"data_catalog": "urn:nbn:fi:att:data-catalog-harvest-kielipankki",
"description": {
"en": "This resource will be available via Korp in Kielipankki – the Language Bank of Finland\n\nThese parallel corpora consist of Biblical verses (historical and contemporary, 1821–2023) from Erzya (myv), Moksha (mdf); Olonets-Karelian (Livvi) (olo), Dvina-Karelian (North Karelian Proper) (krl), Livonian (liv), Veps (vep); Khanty (kca), Mansi (mns); Komi-Permyak (koi), Komi-Zyrian (kpv), Udmurt (udm); Meadow & Eastern Mari (mhr) and Hill Mari (mrj). The majority of the texts, in reference to newer translations, come from the Institute for Bible Translation in Helsinki, Finland as originally organized for the University of Helsinki Language Corpus Server (UHLCS). \nFinnish, Estonian, Hungarian as well as Russian and Ukrainian translations are also included. \nThe purpose of these parallel corpora is to further the studies of translation in Uralic minority languages. Simultaneously, it \nprovides an opportunity to follow changes in lexical and syntactic strategies used in different versions of Biblical verses in one language or compare lexicon and structure between languages. Lemmatization and morphological analyses are provided for all but Khanty, Estonian, Hungarian, Russian and Ukrainian, and the accuracy in the remaining languages should be developed as disambiguation resources. The minority languages have been lemmatized and annotated for both morphological features and syntactic dependencies with the use of open hfst-analysers developed in the GiellaLT (Clarino) infrastructure. \nThe Finnish texts have been analyzed with TNPP (Turku Neural Parser Pipeline), which includes lemmatization, morphological analysis as well as syntactic annotation.\nThe choice of including two closely related Slavic languages is founded on the idea that historically Slavic contact has been representative of Kiev, Novgorod, St Petersburg and Moscovian idioms spoken colloquially.\n \n \n\nThe 27 books of the New Testament are included for the following 15 languages: \nest (2022), \nfin (1932–1938), \nhun (2021), \nkoi (2019), \nkpv (2008), \nkrl (2011), \nmdf (2016), \nmhr (2007), \nmrj (2014), \nmyv (1821–1827, 2006), \nolo (2003), \nrus (1876), \nudm (1997, 2013), \nukr (2022), \nvep (2006).\n\n\nThe 39 books of the Old Testament are included for two languages:\nfin (1932–1938) and udm (2013).\n\n\nAdditionally, the following books are included: \nkca (2013–2018): MRK, GEN, JON; \nkoi (1996): MRK; \nkpv (1995–1997): MRK, JHN; \nkrl (2020–2023): JON;\nliv (1942): MAT; \nmdf (1901): JHN; \nmdf (1995): MRK;\nmdf (2020–2022): GEN, EXO;\nmhr (1994–1995): MRK, LUK, JHN;\nmns (2000–2016): MAT, MRK, LUK, JHN, JON; \nmyv (1910): MAT, MRK, LUK, JHN; \nmyv (1995–1998): MAT, MRK, LUK, ACT; \nmyv (2011–2020): RUT, PSA, ECC, SNG, JON; \nolo (1993–1997): MAT, MRK, LUK, JHN; \nolo (2006–2020): GEN, RUT, PSA, PRO, ISA, JON; \nudm (2016): TOB, JDT, WIS, SIR, BAR, LJE, 1MA, 2MA, 3MA, 1ES, 2ES; \nvep (1992–1998): MAT, MRK, JHN; \nvep (2012–2023): RUT, PSA, PRO, JON."
},
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{
"id": "62b43705-b725-40cd-aa4f-f5b1465678e1",
"url": "http://www.yso.fi/onto/okm-tieteenala/ta6121",
"in_scheme": "http://www.yso.fi/onto/okm-tieteenala/conceptscheme",
"pref_label": {
"en": "Languages",
"fi": "Kielitieteet",
"sv": "Språkvetenskaper"
}
}
],
"infrastructure": [],
"keyword": [],
"language": [
{
"id": "1b32ef89-50ea-448b-9267-2fd359950859",
"url": "http://lexvo.org/id/iso639-3/olo",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Livvi",
"fi": "Aunuksenkarjalan kieli"
}
},
{
"id": "cb31f190-f962-47f7-97e2-f1cca09935a6",
"url": "http://lexvo.org/id/iso639-3/liv",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Liv",
"fi": "Liivin kieli",
"sv": "Liviska"
}
},
{
"id": "96e4524b-5d3f-433e-90c2-7f917550a43a",
"url": "http://lexvo.org/id/iso639-3/vep",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Veps",
"fi": "Vepsän kieli",
"sv": "Vepsiska"
}
},
{
"id": "ce9fd8e7-ab07-4764-8da4-bed7e56db401",
"url": "http://lexvo.org/id/iso639-3/kca",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Khanty",
"fi": "Hantin kieli",
"sv": "Chantiska"
}
},
{
"id": "3e97e00f-cabf-4be0-89ff-8d616c71b5f1",
"url": "http://lexvo.org/id/iso639-3/koi",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Komi-Permyak",
"fi": "Komipermjakin kieli"
}
},
{
"id": "6dfb4f24-0795-404c-a14e-3af3c8759ff7",
"url": "http://lexvo.org/id/iso639-3/mhr",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Eastern Mari"
}
},
{
"id": "6f5e7f65-b006-457c-9dc1-d51e3e2723ad",
"url": "http://lexvo.org/id/iso639-3/mns",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Mansi",
"fi": "Mansin kieli",
"sv": "Mansiska"
}
},
{
"id": "8918c29a-2a58-493b-afa9-12cde12b4e4e",
"url": "http://lexvo.org/id/iso639-3/mrj",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Western Mari",
"sv": "Västmariska"
}
},
{
"id": "715d8f7e-7b54-44dd-a737-f075b16b53d1",
"url": "http://lexvo.org/id/iso639-3/kpv",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Komi-Zyrian",
"fi": "Jazvan komi"
}
},
{
"id": "9cdccadf-a0bb-4f3f-ad2c-6608d979bf92",
"url": "http://lexvo.org/id/iso639-3/krl",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Karelian",
"fi": "karjala",
"sv": "karelska"
}
},
{
"id": "33cd261c-a547-4df5-afd0-b84336c718f9",
"url": "http://lexvo.org/id/iso639-3/udm",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Udmurt",
"fi": "udmurtti",
"sv": "udmurtiska"
}
},
{
"id": "b31860e8-38bc-449b-ade7-0b5e0ff96bc9",
"url": "http://lexvo.org/id/iso639-3/mdf",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Moksha",
"fi": "mokša",
"sv": "moksja"
}
},
{
"id": "8d20d1dc-578a-412f-aba6-c625cd94902b",
"url": "http://lexvo.org/id/iso639-3/myv",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Erzya",
"fi": "ersä",
"sv": "erjya"
}
},
{
"id": "3800a029-c3e5-4f6c-8758-d5f2fb028ddb",
"url": "http://lexvo.org/id/iso639-3/est",
"in_scheme": "http://lexvo.org/id/",
"pref_label": {
"en": "Estonian",
"fi": "viro",
"sv": "estniska"
}
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"en": "The study examined the prevalence of inappropriate and violent treatment in Finland's rescue services and emergency medical care, as well as the impacts of these phenomena and potential preventive measures. The survey is part of the Zero Tolerance project (Pelastustoimen nollatoleranssi syrjinnälle ja häirinnälle - faktaa vai fiktiota?), which explores the prevalence, manifestation, measures, and effects of inappropriate and violent treatment experienced in the rescue and emergency medical services sectors. At the beginning of the survey, respondents were asked whether they had experienced or observed inappropriate or violent treatment, either within their own organization or from external sources. The prevalence of such treatment was assessed by asking how often the respondents or their colleagues had encountered various forms of inappropriate or violent behavior (e.g., threats, sexual harassment, discrimination) during the past 12 months. After this, the respondents were asked to specify their personal experiences and observations related to the different forms of treatment The effects of inappropriate or violent treatment (physical/psychological/professional) were assessed by asking about the type and duration of the impacts. Additionally, the survey explored how the respondents reacted to such situations. Next, the survey asked whether the respondent's organization has a reporting system in place for reporting inappropriate or violent treatment. The respondents were also asked for their views on the functionality and use of these reporting systems, as well as their level of work-related exhaustion. Finally, the survey gathered the respondents' opinions on the measures taken by their organization to prevent inappropriate or violent treatment and the perceived effectiveness of these measures. The background variables in the data include the respondent's occupational group, organizational position, organizational affiliation, gender, work rhythm, length of career, contact method, and language version.",
"fi": "Tutkimuksessa selvitetään epäasiallisen ja väkivaltaisen kohtelun esiintyvyyttä pelastusalalla ja ensihoidossa Suomessa vuonna 2024. Lisäksi tarkastellaan näiden ilmiöiden vaikutuksia sekä keinoja niiden ehkäisemiseksi. Kysely on osa tutkimushanketta Pelastustoimen nollatoleranssi syrjinnälle ja häirinnälle - faktaa vai fiktiota? (Nollatoleranssi-hanke), jossa selvitetään pelastusalan ja ensihoidon kokeman epäasiallisen ja väkivaltaisen kohtelun yleisyyttä, ilmenemismuotoja, toimenpiteitä ja vaikutuksia. Kyselyn alussa kartoitetaan vastaajien kokemuksia tai havaintoja epäasiallisesta tai väkivaltaisesta kohtelusta sekä työskentelyorganisaation sisällä että sen ulkopuolella. Esiintyvyyttä selvitetään muun muassa kysymällä, kuinka usein vastaajat itse tai heidän kollegansa ovat kohdaneet erilaisia epäasiallisen tai väkivaltaisen kohtelun muotoja (esim. uhkailu, seksuaalinen häirintä, syrjintä) viimeisen 12 kuukauden aikana. Tämän jälkeen vastaajia pyydetään tarkentamaan kokemuksiaan ja havaintojaan eri kohtelun muodoista. Epäasiallisen tai väkivaltaisen kohtelun vaikutuksia (fyysiset/psyykkiset/ammatilliset) arvioidaan kysymällä, millaisia ja kuinka pitkäkestoisia vaikutukset ovat olleet. Lisäksi selvitetään, miten vastaajat ovat reagoineet tällaisiin tilanteisiin. Seuraavaksi kyselyssä tiedustellaan, onko vastaajan organisaatiossa käytössä ilmoitusjärjestelmä, jonka kautta voi raportoida epäasiallisesta tai väkivaltaisesta kohtelusta. Vastaajilta kysytään myös heidän näkemyksiään ilmoitusjärjestelmien toimivuudesta ja käytöstä sekä heidän kokemastaan työuupumuksen tasosta. Lopuksi kartoitetaan vastaajien mielipiteitä organisaation toimenpiteistä epäasiallisen tai väkivaltaisen kohtelun ehkäisemiseksi sekä näiden toimenpiteiden vaikuttavuudesta. Taustamuuttujina aineistossa ovat vastaajan ammattiryhmä, organisaatioasema, organisaatiokuuluvuus, sukupuoli, työrytmi, uran pituus, yhteydenottomenetelmä sekä kieliversio."
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"en": "Pauna, Kokkonen, Cavaliere, Bayat, Mirowska, Alatarvas, Huttula, Fabritius: Hydrogen Direct Reduced Iron Melting in an Electric Arc Furnace: Benefits of In Situ Monitoring",
"fi": "Pauna, Kokkonen, Cavaliere, Bayat, Mirowska, Alatarvas, Huttula, Fabritius: Hydrogen Direct Reduced Iron Melting in an Electric Arc Furnace: Benefits of In Situ Monitoring"
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"en": "<jats:title>Abstract</jats:title>\n <jats:p>The transition toward environmentally friendly steelmaking using hydrogen direct reduced iron as feed material in electric arc furnaces will eventually require process adjustments due to changes in the pellet properties when compared to, e.g., blast furnace pellets. To this end, the melting of hydrogen direct reduced iron pellets with 68 and 100% reduction degrees and Fe content of 67.24% was investigated in a laboratory-scale electric arc furnace. The presence of iron oxide-rich slag had a significant effect on the arc movement on the melt and an inhibiting effect on iron evaporation. The melting was monitored with video recording and optical emission spectroscopy. The videos were used to monitor the melting behavior, whereas optical emissions revealed iron, gangue elements, and hydrogen from the pellets radiating in the plasma. Furthermore, the flow of the melt is well seen in the videos, as well as the movement of slag droplets on the melt surface. After the experiments, the metal had silica-rich inclusions, whereas slag had mostly penetrated into the crucible. The most notable differences in melting behavior can be attributed to the iron oxide-rich slag, its interaction with the arc and penetration into the crucible, and how it affects the arc movement and heat transfer.</jats:p>\n <jats:p>\n <jats:bold>Graphical Abstract</jats:bold>\n </jats:p>",
"fi": "<jats:title>Abstract</jats:title>\n <jats:p>The transition toward environmentally friendly steelmaking using hydrogen direct reduced iron as feed material in electric arc furnaces will eventually require process adjustments due to changes in the pellet properties when compared to, e.g., blast furnace pellets. To this end, the melting of hydrogen direct reduced iron pellets with 68 and 100% reduction degrees and Fe content of 67.24% was investigated in a laboratory-scale electric arc furnace. The presence of iron oxide-rich slag had a significant effect on the arc movement on the melt and an inhibiting effect on iron evaporation. The melting was monitored with video recording and optical emission spectroscopy. The videos were used to monitor the melting behavior, whereas optical emissions revealed iron, gangue elements, and hydrogen from the pellets radiating in the plasma. Furthermore, the flow of the melt is well seen in the videos, as well as the movement of slag droplets on the melt surface. After the experiments, the metal had silica-rich inclusions, whereas slag had mostly penetrated into the crucible. The most notable differences in melting behavior can be attributed to the iron oxide-rich slag, its interaction with the arc and penetration into the crucible, and how it affects the arc movement and heat transfer.</jats:p>\n <jats:p>\n <jats:bold>Graphical Abstract</jats:bold>\n </jats:p>",
"und": "<jats:title>Abstract</jats:title>\n <jats:p>The transition toward environmentally friendly steelmaking using hydrogen direct reduced iron as feed material in electric arc furnaces will eventually require process adjustments due to changes in the pellet properties when compared to, e.g., blast furnace pellets. To this end, the melting of hydrogen direct reduced iron pellets with 68 and 100% reduction degrees and Fe content of 67.24% was investigated in a laboratory-scale electric arc furnace. The presence of iron oxide-rich slag had a significant effect on the arc movement on the melt and an inhibiting effect on iron evaporation. The melting was monitored with video recording and optical emission spectroscopy. The videos were used to monitor the melting behavior, whereas optical emissions revealed iron, gangue elements, and hydrogen from the pellets radiating in the plasma. Furthermore, the flow of the melt is well seen in the videos, as well as the movement of slag droplets on the melt surface. After the experiments, the metal had silica-rich inclusions, whereas slag had mostly penetrated into the crucible. The most notable differences in melting behavior can be attributed to the iron oxide-rich slag, its interaction with the arc and penetration into the crucible, and how it affects the arc movement and heat transfer.</jats:p>\n <jats:p>\n <jats:bold>Graphical Abstract</jats:bold>\n </jats:p>"
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"en": "Repola, Heikkinen, Lindblad: Pulpwood green density prediction models and sampling-based calibration",
"fi": "Repola, Heikkinen, Lindblad: Pulpwood green density prediction models and sampling-based calibration"
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"en": "<ja:p>Pulpwood arriving at the mills is mainly measured by weighing. In the loading phase of forwarding and trucking, timber is weighed using scales mounted in the grapple loader. The measured weight of timber is converted into volume using a conversion factor defined as green density (kg m). At the mill, the green density factor is determined by sampling measurements, while in connection with weighing with grapple-mounted scales during transportation, fixed green density factors are used. In this study, we developed predictive regression models for the green density of pulpwood. The models were constructed separately by pulpwood assortments: pine (contains mainly L); spruce (mainly (L.) Karst.); decayed spruce; birch (mainly Ehrh. and Roth); and aspen (mainly L.). Study material was composed of the sampling-based measurements at the mills between 2013â2019. The models were specified as linear mixed models with both fixed and random parameters. The fixed effect produced the expected value of green density as a function of delivery week, storage time, and meteorological conditions during storage. The random effects allowed the model calibration by utilizing the previous sampling weight measurements. The model validation showed that the model predictions faithfully reproduced the observed seasonal variation in green density. They were more reliable than those obtained with the current practices. Even the uncalibrated (fixed) predictions had lower relative root mean squared prediction errors than those obtained with the current practices.<ja:sup>â3</ja:sup><ja:italic>Pinus sylvestris</ja:italic><ja:italic>Picea abies</ja:italic><ja:italic>Betula pubescens</ja:italic><ja:italic>Betula pendula</ja:italic><ja:italic>Populus tremula</ja:italic></ja:p>",
"fi": "<ja:p>Pulpwood arriving at the mills is mainly measured by weighing. In the loading phase of forwarding and trucking, timber is weighed using scales mounted in the grapple loader. The measured weight of timber is converted into volume using a conversion factor defined as green density (kg m). At the mill, the green density factor is determined by sampling measurements, while in connection with weighing with grapple-mounted scales during transportation, fixed green density factors are used. In this study, we developed predictive regression models for the green density of pulpwood. The models were constructed separately by pulpwood assortments: pine (contains mainly L); spruce (mainly (L.) Karst.); decayed spruce; birch (mainly Ehrh. and Roth); and aspen (mainly L.). Study material was composed of the sampling-based measurements at the mills between 2013â2019. The models were specified as linear mixed models with both fixed and random parameters. The fixed effect produced the expected value of green density as a function of delivery week, storage time, and meteorological conditions during storage. The random effects allowed the model calibration by utilizing the previous sampling weight measurements. The model validation showed that the model predictions faithfully reproduced the observed seasonal variation in green density. They were more reliable than those obtained with the current practices. Even the uncalibrated (fixed) predictions had lower relative root mean squared prediction errors than those obtained with the current practices.<ja:sup>â3</ja:sup><ja:italic>Pinus sylvestris</ja:italic><ja:italic>Picea abies</ja:italic><ja:italic>Betula pubescens</ja:italic><ja:italic>Betula pendula</ja:italic><ja:italic>Populus tremula</ja:italic></ja:p>",
"und": "<ja:p>Pulpwood arriving at the mills is mainly measured by weighing. In the loading phase of forwarding and trucking, timber is weighed using scales mounted in the grapple loader. The measured weight of timber is converted into volume using a conversion factor defined as green density (kg m). At the mill, the green density factor is determined by sampling measurements, while in connection with weighing with grapple-mounted scales during transportation, fixed green density factors are used. In this study, we developed predictive regression models for the green density of pulpwood. The models were constructed separately by pulpwood assortments: pine (contains mainly L); spruce (mainly (L.) Karst.); decayed spruce; birch (mainly Ehrh. and Roth); and aspen (mainly L.). Study material was composed of the sampling-based measurements at the mills between 2013â2019. The models were specified as linear mixed models with both fixed and random parameters. The fixed effect produced the expected value of green density as a function of delivery week, storage time, and meteorological conditions during storage. The random effects allowed the model calibration by utilizing the previous sampling weight measurements. The model validation showed that the model predictions faithfully reproduced the observed seasonal variation in green density. They were more reliable than those obtained with the current practices. Even the uncalibrated (fixed) predictions had lower relative root mean squared prediction errors than those obtained with the current practices.<ja:sup>â3</ja:sup><ja:italic>Pinus sylvestris</ja:italic><ja:italic>Picea abies</ja:italic><ja:italic>Betula pubescens</ja:italic><ja:italic>Betula pendula</ja:italic><ja:italic>Populus tremula</ja:italic></ja:p>"
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