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Viimeksi tallennetut

  • How consumers perceive the use of bioprocessing and non-thermal technologies to develop minimally processed plant-based foods: Insights from a qualitative study
    Franco Lucas, Bárbara; Arvola, Anne-Kristiina; Sousa, Sofia A.; Ribeiro, José Carlos; Criveanu-Stamatie, Gabriela Daniela; Duta, Denisa Eglantina; Cunha, Luís Miguel; Pennanen, Kyösti; Brunner, Thomas A. (Elsevier, 2026)
    Artikkeli
    Consumers' negative image of currently available plant-based foods (PBFs) as ultra-processed and unhealthy is hampering the transition towards more plant-based diets. A qualitative approach was applied across four European countries – Switzerland, Finland, Portugal and Romania – to explore consumers' views on minimal processing methods and PBFs produced using these methods. Semi-structured in-person interviews were conducted with meat eaters (omnivores and flexitarians). The aim was to reveal and understand their attitudes, perceptions and expectations regarding minimal processing technologies (fermentation, germination, high-pressure processing, pulsed electric field and ultrasound) to produce PBFs. For many interviewees, the perceived level of processing was an important consideration in food choice. Four main themes relevant for the acceptance of minimal processing technologies were identified: i) familiarity and knowledge; ii) benefits perception; iii) perceived risks, concerns and doubts about food safety, resource efficiency and performance; and iv) interest and general attitude. Most interviewees appeared open to using the addressed technologies to produce minimally processed plant-based options. Meat and dairy alternatives and snacks are examples of minimally processed foods that they would be willing to consume. The study provides in-depth insights into the psychological, social and environmental factors that contribute to the acceptance of minimal processing technologies and PBFs. The results can support researchers and the food industry in designing suitable minimally processed PBFs that align with consumers’ expectations.
  • Why generative AI adoption stalls across public service domains: an AMO comparison of Finnish wellbeing and municipal technical services
    Pulkkinen, Jarmo; Rantamäki, Aino; Laukka, Elina (Emerald, 2026)
    Artikkeli
    Purpose This paper aims to examine how Finnish public employees’ perceived barriers to generative AI adoption differ between regional wellbeing services and municipal technical services and identify which ability-motivation-opportunity (AMO) theory dimensions and items pose the greatest constraints. Design/methodology/approach Two web-based surveys were conducted in September 2025. The wellbeing services survey targeted a single regional organization (n = 437); the technical services survey covered land-use planning and construction supervision across 104 municipalities (n = 218). Respondents reporting no prior AI use (n = 321) rated 19 barrier items on a 0–3 scale. Findings Opportunity barriers were the highest-rated AMO dimension in the wellbeing services sample and were significantly more intense there than in the technical services sample; the absence of organizational guidelines, weak peer support, and limited encouragement from colleagues or supervisors accounted for the largest sectoral differences. The technical services barrier profile was more evenly distributed across AMO dimensions. Comparable motivation composites masked an item-level reversal: doubts about generative AI accuracy and reliability were significantly stronger in technical services, where they ranked as the highest-rated barrier. Originality/value The paper offers comparative, employee-level evidence on perceived barriers to generative AI adoption among public-sector non-users. The findings suggest a contextual reading of AMO in which the weight of each dimension may depend on the configuration of public service production. Item-level disaggregation adds a second layer to this reading, since composite comparisons concealed the reliability reversal observed in technical services. Public organizations may benefit from diagnosing employee-level barrier profiles before designing generative AI implementation strategies.
  • Älysopimusten sopimusoikeudellinen arviointi
    Muranen, Eero (2026-09-02)
    Kandidaatintutkielma
    Sopimukset ovat merkittävä osa sekä liiketoimintaa, että koko yhteiskuntaa. Ne ovat jo pitkään luoneet pohjaa koko taloudelliselle toiminnalle. Sopimusvapaus ja sopimussitovuus toimivat sopimusoikeuden perustana, sekä samalla myös sopimustulkinnan lähtökohtana. Teknologisen kehityksen myötä saatavilla on yhä enemmän teknologiaa, joka on muovannut nykypäivän liiketoimintaa ja vaihdantaa. Yksi näistä teknologisista innovaatioista on lohkoketju. Tämän teknologian mukana on noussut uudelleen esiin älysopimuksen käsite, jolla viitataan tässä yhteydessä lohkoketjuteknologiaan perustuvaan ohjelmaan, joka mahdollistaa arvoa sisältävien kohteiden automaattisen vaihdannan ennalta määritettyjen ehtojen avulla. Älysopimusten erityispiirteenä on niiden automaattinen täytäntöönpano ja suojaus väärinkäytöksiltä, sen ehdot kirjoitetaan koodiksi lohkoketjuun, ja määriteltyjen ehtojen täytyttyä ja varmistuttua, tietokone suorittaa sopimustoiminnon. Vielä varsin tuoreena ilmiönä älysopimukset eivät kuitenkaan ole vakituinen osa sopimusoikeutta, eikä niiden oikeudellisesta asemasta ole muodostunut yhtenäistä käsitystä. Tutkielmassa perehdyn älysopimuksen ja lohkoketjun toimintalogiikkaan ja pintapuolisesti myös teknisiin käsitteisiin, sekä sopimusoikeuden perusperiaatteisiin, jotta saamme raamit älysopimuksen sitovuuden arvioinnille. Tarkastelun näkökulma tulee olemaan oikeustieteellinen ja liiketaloudellinen. Tässä kandidaatintutkielmassa varsinaisena tutkimusongelmana selvitän älysopimusten asemaa sitovana sopimuksena sopimusoikeuden ja sen periaatteiden, lähdekirjallisuuden, sekä EU:n datasäädöksen perusteella. Tarkastelen älysopimusten haasteita, ja pohdin niiden luomia sopimusoikeudellisia kysymyksiä.
    Contracts constitute a significant part of both business and society as a whole. They have long formed the foundation for all economic activity. Freedom of contract and the binding nature of contracts serve as the basis of contract law, as well as the starting point for contractual interpretation. Technological development has made increasingly more technology available, technology that has shaped today's business and exchange. One of these technological innovations is blockchain. Alongside this technology, the concept of the smart contract has re-emerged, referring in this context to a program based on blockchain technology that enables the automatic exchange of items containing value through predetermined conditions. A distinctive feature of smart contracts is their automatic enforcement and protection against misuse: their terms are written as code onto the blockchain, and once the specified conditions are met and verified, the computer executes the contractual action. However, as a still fairly recent phenomenon, smart contracts have not become an established part of contract law, and no unified understanding of their legal status has yet formed. In this thesis, I examine the operational logic of smart contracts and blockchain, and superficially also the relevant technical concepts, as well as the fundamental principles of contract law, in order to establish a framework for assessing the binding nature of smart contracts. The perspective of the analysis will be both legal and business economic. The actual research problem addressed in this bachelor's thesis is to determine the status of smart contracts as binding contracts on the basis of contract law and its principles, source literature, and the EU Data Act. I examine the challenges posed by smart contracts and consider the contract law questions they raise.
    Kokoteksti luettavissa vain Tritonian asiakaskoneilla.
  • Can Common Recycling Targets Deliver Convergence? Evidence From EU Municipal Waste Recycling, 2004–2023
    Cong, Lianghan; Liu, Lan; Lu, Shuaiyi; Jiang, Pan; Katsuyuki, Haneda; Lü, Xiaoshu (John Wiley & Sons, 2026)
    Artikkeli
    The EU Waste Framework Directive sets common municipal waste recycling targets for all Member States, yet large cross-country gaps persist. This paper examines whether EU-27 recycling rates converged over 2004–2023, whether convergence stalled after 2018, and which factors shaped catch-up. Using an EU-27 panel, we combine sigma-convergence, beta-convergence, and the Phillips–Sul log-t test. Recycling performance became markedly less dispersed over the full period: the coefficient of variation fell from 0.810 in 2004 to 0.380 in 2023, the absolute beta-convergence coefficient was −0.040 (p < 0.001), and the Phillips–Sul test did not reject full-panel convergence. However, convergence stalled in 2018. A Chow test identifies a structural break, while placebo tests show that the dispersion trend shifted from negative to near zero in that year. Using bilateral UN Comtrade data on pre-ban exports of recovered paper and waste plastics to China, we test whether post-2018 convergence varied with exposure to the Chinese import ban. Conditional beta-convergence estimates show that the WFD compliance gap is strongly associated with catch-up, but the relationship is nonlinear: countries with the largest gaps improve more slowly. This pattern is consistent with structural lock-in. Greater landfill dependence was also associated with lower ESIF absorption rates, indicating co-located structural and institutional barriers. As of 2023, only 6 of 27 Member States had reached the 2025 recycling target of 55%. These findings suggest that common targets support convergence, although the process remains vulnerable to external shocks and structural and institutional constraints.
  • Early and late mortality among patients with T1–T3 head and neck squamous cell carcinoma: a machine learning analysis using a SEER population-based cohort study
    Alabi, Rasheed Omobolaji; Bazina, Mahmoud; Guntinas-Lichius, Orlando; Elmusrati, Mohammed; Almangush, Alhadi; Tiblom Ehrsson, Ylva; Laurell, Göran; Mäkitie, Antti A. (Springer, 2026)
    Artikkeli
    Despite advances in the management of head and neck squamous cell carcinoma (HNSCC), mortality within 6 months of diagnosis remains a substantial clinical challenge. The objectives of this study are: (i) to develop a machine learning (ML) model using data from the Surveillance, Epidemiology, and End Results (SEER) program to assess the influence of patient characteristics, tumor features, and treatment modalities on early mortality in HNSCC; (ii) to explore and compare the prognostic potentials of patient-, tumor, and treatment-related factors across distinct mortality time points—6-month mortality (early mortality), 24-month mortality, and 5-year mortality; and (iii) to externally and independently validate the early mortality model using multicenter data from the Thuringian Cancer Registry (Jena, Germany) and a prospective observational cohort from the Helsinki University Hospital (Helsinki, Finland). We identified 4802 patients with HNSCC from the SEER for model development. Permutation-based feature importance was used to identify risk factors associated with early mortality. External validation was conducted using 1952 cases from the Thuringian Cancer Registry and 58 cases from the Helsinki University Hospital. The ML model achieved a weighted area under curve (AUC) of 0.75 for predicting early mortality in the SEER cohort. External validation yielded weighted AUC values of 0.70 (Germany) and 0.60 (Finland). Aggregate feature importance for early mortality indicated that higher age at diagnosis, presence of earlier primary malignant tumors besides HNSCC, unmarried patients with T1–T3 HNSCC, T3 stage, and having hypopharyngeal or laryngeal cancer, in decreasing order of significance, were important. For 24-month mortality, the associated risk factors in decreasing order of significance were T3 stage, being elderly in terms of age at diagnosis, presence of earlier primary malignant tumors besides HNSCC, having hypopharyngeal or oral cavity cancer, and N3 stage. The associated risk factors for 5-year mortality were found to be the same with those of early mortality with the additional inclusion of T2 stage. Identification of patients at elevated risk of early death supports timely intervention and individualized therapeutic decision-making. The developed ML model identified several risk factors associated with early death and may aid in clinical decision-making with the potential to improve survival outcomes.