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Säännöllinen merilinjaliikenne on tärkeä osa intermodaalikuljetusta Euroopassa. Suomen maantieteellisen sijainnin vuoksi suurin osa maan tuonnista ja viennistä kulkee meritse. Hangon satama on Suomen eteläisin satama. Kun 1.1.2015 Rikkidirektiivi tuli voimaan, Hangon satama sai hyviä kustannus- ja ympäristöhyötyjä lyhyimmän merimatkan vuoksi verrattuna muihin Euroopan satamiin. Tässä opinnäytetyössä tutkitaan Suomen Hangon Länsisataman ja Viron Paldiskin Pohjoissataman välillä olevaa säännöllistä merilinjaliikenteen kehitysmahdollisuutta. Tutkimuksessa keskitytään kuorma-autoihin ja puoliperävaunuihin, joita kuljetetaan ropax aluksella Sailor. Tutkimuksen tavoitteena on selvittää kuinka tyytyväisiä kuljettajat ovat HankoPaldiski reittiin ja löytää kehitysmahdollisuuksia. Opinnäytetyön toimeksiantajat ovat logistiikkayritys ja satama-agentti Oy Victor Ek Ab ja HankoPaldiski reittin operaattori DFDS. Opinnäytetyössä käytetään kvalitatiivista ja kvantitatiivista menetelmää, eli käsitellään tilastotietoja sekundaarilähteistä ja kuljettajien haastatteluista. Teoreettinen osa tutkimuksesta koostuu Suomen meriliikenteen tilastojen analyysistä. Tutkimusta toteutettiin suorittamalla asiakastyytyväisyyskysely ja käsittelemällä sen tuloksia. Kysely tehtiin haastattelun muodossa. Kyselyn tulokset ovat nyt tiedossa DFDS operatiiviselle päällikölle. Reitin ongelmat rekkakuljettajien näkökulmasta ovat mielenkiintoisia ja olleet tuntemattomia varustamolle.
We employ a single-charge counting technique to measure the full counting statistics of Andreev events in which Cooper pairs are either produced from electrons that are reflected as holes at a superconductor–normal-metal interface or annihilated in the reverse process. The full counting statistics consists of quiet periods with no Andreev processes, interrupted by the tunneling of a single electron that triggers an avalanche of Andreev events giving rise to strongly super-Poissonian distributions.
Objective: To illustrate the views of chief physicians in Finnish primary healthcare health centres (HCs) on the existing research capacity of their centres, their attitudes to practice-based research network activity, and research topics of interest to them. Design: A cross-sectional survey study. Setting: Finnish HCs. Subjects: Chief physicians in Finnish HCs. Main outcome measures: We used a questionnaire that included five-point Likert scales and multiple choice and open-ended questions to identify the chief physician’s profile, the HC content, the attitudes of chief physicians towards engagement in research, research topics of interest to them, and factors that may influence their motivation. Descriptive methods were used for the analysis of the quantitative data, while the qualitative data were processed using inductive thematic analysis. Results: There was a relatively good representation of all hospital districts. One-third of HCs had at least one person doing research, and 61% of chief physicians would support research in their setting. Their stimulus for research was primarily testing new therapies, protocols, and care processes, as well as effectiveness and healthcare improvement. The expected benefits that motivate engagement in Practice-based research networks (PBRNs) are evidence-based practice and raised professional capacity and profile of the HC. Conclusions: Chief physicians regard research as an elementary part of the development of primary care practices and health policy. Their motivation to engage in PBRN activity is determined by the relevance of the research to their interests and the management of competing priorities and resource limitations.
We employ a single-charge counting technique to measure the full counting statistics of Andreev events in which Cooper pairs are either produced from electrons that are reflected as holes at a superconductor–normal-metal interface or annihilated in the reverse process. The full counting statistics consists of quiet periods with no Andreev processes, interrupted by the tunneling of a single electron that triggers an avalanche of Andreev events giving rise to strongly super-Poissonian distributions.
Abstract Clinical placements are an important part of nursing education to developing nursing students’ competencies. In enhancing clinical learning, to focus on mentors’ competences is pivotal as they are the main role models and experts in guiding. This study is validated the Italian version of the Mentors’ Competence Instrument. A sampling frame of 648 mentors was involved. The final sample included 291 mentors (response rate 45%). Confirmatory Factor Analysis was performed. Fit indices were also calculated to evaluate validity. The scale demonstrated optimal fit indexes and its validity was confirmed by psychometrical testing. In detail, Root Mean Square Error of Approximation is 0.058, Standardized Root Mean Residual is 0.046, Comparative Fit Index is 0.893 and Tucker-Lewis Index 0.886. Cronbach’s alpha ranges from 0.77 to 0.95 among factors. This is the first validation of the scale performed in a different country from the original study. The performed psychometric testing showed that the scale is valid and reliable, as well as consistent with the theoretical structure reported for a different national context. This scale can be beneficial for comparing mentors’ competencies across different clinical learning environments and could be used to build a broader model of mentors’ competencies.
Abstract Healthcare workers (HCWs) and healthcare students are at increased risk of becoming infected with and being a vector of transmission of COVID-19. Vaccination efforts amongst this group of persons have been hampered in some countries by hesitancy to uptake the COVID-19 vaccine. The factors related to vaccine hesitancy have been reported in several systematic reviews. However, a comprehensive overview of barriers and facilitators of COVID-19 vaccine hesitancy is greatly needed to address effective interventions in this population. Understanding and designing effective strategies to promote vaccination among HCWs is pivotal to secure an appropriate and safe healthcare provision. The current protocol describes the methodology for an Umbrella Review that explores the barriers and facilitators of COVID-19 vaccine hesitancy for HCWs and healthcare students. The databases that will be searched are CINAHL, MedLine, Cochrane Library, PubMed, ProQuest, Web of Science, Science Direct, IBSS, Google Scholar, and Epistemonikos. Studies will be eligible for inclusion if they: (i) conducted a systematic review (with or without meta-analysis); (ii) included primary sources utilizing a quantitative methodology; (iii) investigated factors related to COVID-19 vaccine hesitancy; (iv) and included a sub/population of HCWs or healthcare students aged 18–65. The screening processes and data extraction will be conducted independently by two reviewers. The Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Systematic Reviews and Research Syntheses will be used to assess the methodological quality of the included reviews. The degree to which the included reviews contain the same primary studies will also be assessed and reported. The outcomes of this review will have wide-reaching implications for the research area, healthcare systems and institutions, and governments worldwide.
Abstract Background: Healthcare workers (HCWs) and healthcare students display high levels of vaccine hesitancy with impact on healthcare provision, patient safety, and health promotion. The factors related to vaccine hesitancy have been reported in several systematic reviews. However, this evidence needs to be synthesised, as interventions to reduce vaccination hesitancy in this population are needed. Methods: This Umbrella Review aimed to explore the barriers and facilitators of vaccine hesitancy toward the COVID-19 vaccine for HCWs and healthcare students. The review was performed and reported in accordance with Joanna Briggs Institutes guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. A protocol was preregistered on PROSPERO (CRD42022327354). Eight databases were searched from November 2019 to 23rd May 2022 to identify any systematic reviews that explored factors associated with hesitancy towards the COVID-19 vaccine for HCWs or healthcare students. Results: A total of 31 studies were included in the review. The majority of studies (71%) were appraised as strong or moderate quality and there was a slight degree of overlap (<5%) of primary studies between the reviews. Vaccine hesitancy was more common among HCWs and healthcare students in specific occupational roles (e.g. nurses) than others (e.g. physicians). Frequent reasons for hesitancy were related to sociodemographic factors (gender, age, ethnicity), occupational factors (COVID-19 exposure, perceived risk, mandatory vaccination), health factors (vaccination history), vaccine-related factors (concerns about safety, efficacy, side-effects, rapid development, testing, approval and distribution of the vaccine), social factors (social pressure, altruism and collective responsibility), distrust factors (key social actors, pandemic management), information factors (inadequate information and sources, exposure to misinformation). Conclusion: The results from this Umbrella Review have wide-reaching implications for the research area, healthcare systems and institutions and governments worldwide. Designing tailored strategies for specific occupational groups is pivotal to increasing vaccine uptake and securing a safe healthcare provision worldwide.
Abstract In this paper, we propose an unobtrusive method and architecture for monitoring a person’s presence and collecting his/her health-related parameters simultaneously in a home environment. The system is based on using a single ultra-wideband (UWB) impulse-radar as a sensing device. Using UWB radars, we aim to recognize a person and some preselected movements without camera-type monitoring. Via the experimental work, we have also demonstrated that, by using a UWB signal, it is possible to detect small chest movements remotely to recognize coughing, for example. In addition, based on statistical data analysis, a person’s posture in a room can be recognized in a steady situation. In addition, we implemented a machine learning technique (k-nearest neighbour) to automatically classify a static posture using UWB radar data. Skewness, kurtosis and received power are used in posture classification during the postprocessing. The classification accuracy achieved is more than 99%. In this paper, we also present reliability and fault tolerance analyses for three kinds of UWB radar network architectures to point out the weakest item in the installation. This information is highly important in the system’s implementation.