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Objectives: The authors aimed to investigate the impact of severe bleeding and use of red blood cell (RBC) transfusion on the development of postoperative stroke after surgical (SAVR) and transcatheter aortic valve replacement (TAVR), taken from the FinnValve registry. Design: Nationwide, retrospective observational study. Setting: Five Finnish university hospitals participated in the registry. Participants: A total of 6,463 patients who underwent SAVR (n = 4,333) or TAVR (n = 2,130). Interventions: Patients who underwent TAVR or SAVR with a bioprosthesis with or without coronary revascularization. Measurements and Main Results: The incidence of postoperative stroke after SAVR was 3.8%. In multivariate analysis, the number of transfused RBC units (odds ratio [OR], 1.098; 95% confidence interval [CI], 1.064–1.133) was one of the independent predictors of postoperative stroke. The incidence of stroke increased, along with the severity of perioperative bleeding, according to the European Coronary Artery Bypass Grafting (E-CABG) bleeding grades were as follows: grade 0, 2.2% (reference group); grade 1, 3.4% (adjusted OR, 1.841; 95% CI, 1.105–3.066); grade 2, 5.5% (adjusted OR, 3.282; 95% CI, 1.948–5.529); and grade 3, 14.8% (adjusted OR, 7.103; 95% CI, 3.612–13.966). The incidence of postoperative stroke after TAVR was 2.5%. The number of transfused RBC units was an independent predictor of stroke after TAVR (adjusted OR, 1.155; 95% CI, 1.058–1.261). The incidence of postoperative stroke increased, along with the severity of perioperative bleeding, as stratified by the E-CABG bleeding grades: E-CABG grade 0, 1.7%; grade 1, 5.3% (adjusted OR, 1.270; 95% CI, 0.532–3.035); grade 2, 10.0% (adjusted OR, 2.898; 95% CI, 1.101–7.627); and grade 3, 30.0% (adjusted OR, 10.706; 95% CI, 2.389–47.987). Conclusions: Perioperative bleeding requiring RBC transfusion and/or reoperation for intrathoracic bleeding is associated with an increased risk of postoperative stroke after

The physiological underpinnings of the necessity of sleep remain uncertain. Recent evidence suggests that sleep increases the convection of cerebrospinal fluid (CSF) and promotes the export of interstitial solutes, thus providing a framework to explain why all vertebrate species require sleep. Cardiovascular, respiratory and vasomotor brain pulsations have each been shown to drive CSF flow along perivascular spaces, yet it is unknown how such pulsations may change during sleep in humans. To investigate these pulsation phenomena in relation to sleep, we simultaneously recorded fast fMRI, magnetic resonance encephalography (MREG), and electroencephalography (EEG) signals in a group of healthy volunteers. We quantified sleep-related changes in the signal frequency distributions by spectral entropy analysis and calculated the strength of the physiological (vasomotor, respiratory, and cardiac) brain pulsations by power sum analysis in 15 subjects (age 26.5 ± 4.2 years, 6 females). Finally, we identified spatial similarities between EEG slow oscillation (0.2–2 Hz) power and MREG pulsations. Compared with wakefulness, nonrapid eye movement (NREM) sleep was characterized by reduced spectral entropy and increased brain pulsation intensity. These effects were most pronounced in posterior brain areas for very low-frequency (≤0.1 Hz) vasomotor pulsations but were also evident brain-wide for respiratory pulsations, and to a lesser extent for cardiac brain pulsations. There was increased EEG slow oscillation power in brain regions spatially overlapping with those showing sleep-related MREG pulsation changes. We suggest that reduced spectral entropy and enhanced pulsation intensity are characteristic of NREM sleep. With our findings of increased power of slow oscillation, the present results support the proposition that sleep promotes fluid transport in human brain.

Barkhausen noise (BN) measurements are commonly used for surface characterisation. However, often there is also a need to verify the sub-surface region because detrimental tensile stresses may be present after different manufacturing steps. Especially in a grinding burn, the surface stress may be compressive, but it changes quickly into tensile stress below the surface. The aim of this study was to find out whether regular surface-sensitive BN measurement is also sensitive to the stresses below the surface caused by grinding burns. More specifically, the aim was to study the relationship between BN features and sub-surface stresses and to identify a model that estimates sub-surface stresses. Real samples were collected from an actual process. The samples were cylindrical samples manufactured from commercial alloyed AISI/SAE L6 steel that was through-hardened prior to grinding. Barkhausen noise measurements were carried out for 42 grinding burn locations followed by X-ray diffraction-based residual stress surface measurements and residual stress depth profiles. Depth information was obtained through step-by-step electrolytic removal of thin layers. The stress profiles were pre-processed through interpolation and averaged stress was calculated as a function of depth below the surface. Correlation analysis was carried out to evaluate the relationships between BN features and stress at different depths and among BN features. The main outcome of the analysis was that BN measurement is dominated by the sub-surface tensile stresses rather than the compressive stress at the surface. It was also noticed that BN features form two groups, corresponding to average Barkhausen activity and magnetising field strength leading to maximum Barkhausen activity. Models for stress at different steps were identified systematically. The performance of the models for sub-surface stresses was reasonable with R2 values of around 0.85 and root mean squared error (RMSE) values of aroun

Current strategies to predict psychosis identify only a small proportion of individuals at risk. Additional strategies are needed to increase capacity for pre­diction and prevention of serious mental illness, ideally during childhood and adolescence. One possible approach would be to investigate systems in which psychosis risk factors are concentrated during childhood. One notable such system is represented by Child and Adolescent Mental Health Services (CAMHS). Although psychotic disorders are uncommon in CAMHS, many risk factors for psychosis are highly prevalent in young people who enter this system. We hypothesized, therefore, that youth attending CAMHS would be a high-risk group for psychosis if followed into adulthood and, furthermore, that CAMHS systems would capture a substantial proportion of future psychosis cases. We constructed a total population cohort study of all Finns born in 1987 (N=55,875), linking together extensive register data on health care contacts from birth through age 28 years. We identified all individuals diagnosed with a psychotic or bipolar disorder by age 28 (N=1,785). The risk of psychosis/bipolar disorder by age 28 years was 1.8% for individuals who had not attended CAMHS during childhood or adolescence, whereas it was 12.8% for those with a history of any outpatient CAMHS contact (odds ratio, OR=7.9, 95% CI: 7.2‐8.7). Furthermore, the risk of psychosis/bipolar disorder by age 28 years was 2.3% for individuals without a history of inpatient CAMHS admission, whereas it was 24.0% for those with a history of inpatient CAMHS admission (OR=13.3, 95% CI: 11.9‐14.9), and 36.5% for those with a history of inpatient CAMHS admission in adolescence (age 13‐17 years) (OR=24.2, 95% CI: 21.2‐27.6). Individuals who attended CAMHS but received no mental disorder diagnosis had an equally high risk of subsequently developing a psychosis/bipolar disorder as individuals who did receive a diagnosis (OR=0.9, 99.5% CI: 0.7‐1.1). Compared to other

Cerium (Ce) and europium (Eu)-doped TiO₂ thin films were obtained by sol-gel dip-coating technique. SEM micrographs showed that the surfaces are covered by agglomerated particles due to the repeating coating process. XRD patterns showed the presence of TiO₂ anatase phase. Raman spectra revealed that the peaks recorded at 146 cm⁻¹(Eg) and 397 cm⁻¹(B1g) were related to the anatase phase. EIS measurements proved that Ce-TiO2 (1wt%) and Eu-TiO₂ (0.1wt%) photocatalysts possessed a lower electron transfer resistance than pure TiO₂, which can lead to effective separation of electron/ hole pairs during the photoreactions. The photoactivity of Ce and Eu-doped TiO₂ was investigated by the degradation of amido black10B dye (AB) under UV excitation and varying the initial pH and concentrations. It was found that Eu-TiO₂ (0.1wt%) exhibited higher photocatalytic activity, reaching a first-order reaction rate of kapp(0.036min-1), t1/2 was around 12 min and AB removal was 98.94%, under optimal pH of 3.5 and AB concentration of 10ppm compared to (t1/2 = 45 min, t1/2=30 min), (kapp = 0.022 min-1, kapp = 0.026min-1) and AB removal (94.78%, 96.44%), respectively for pure TiO₂ and Ce-TiO₂ (1wt%). Further increase in Eu/Ce amount up to optimal concentration (1wt% Ce and 0.1wt% Eu) led to a decrease in the AB removal. The mineralization of AB using Eu-TiO₂ photocatalyst was confirmed by HPLC analysis.

Background: Magnetic resonance fingerprinting (MRF) is a method to speed up acquisition of quantitative MRI data. However, MRF does not usually produce contrast-weighted images that are required by radiologists, limiting reachable total scan time improvement. Contrast synthesis from MRF could significantly decrease the imaging time. Purpose: To improve clinical utility of MRF by synthesizing contrast-weighted MR images from the quantitative data provided by MRF, using U-nets that were trained for the synthesis task utilizing L1- and perceptual loss functions, and their combinations. Study type: Retrospective. Population: Knee joint MRI data from 184 subjects from Northern Finland 1986 Birth Cohort (ages 33–35, gender distribution not available). Field strength and sequence: A 3 T, multislice-MRF, proton density (PD)-weighted 3D-SPACE (sampling perfection with application optimized contrasts using different flip angle evolution), fat-saturated T2-weighted 3D-space, water-excited double echo steady state (DESS). Assessment: Data were divided into training, validation, test, and radiologist’s assessment sets in the following way: 136 subjects to training, 3 for validation, 3 for testing, and 42 for radiologist’s assessment. The synthetic and target images were evaluated using 5-point Likert scale by two musculoskeletal radiologists blinded and with quantitative error metrics. Statistical tests: Friedman’s test accompanied with post hoc Wilcoxon signed-rank test and intraclass correlation coefficient. The statistical cutoff P <0.05 adjusted by Bonferroni correction as necessary was utilized. Results: The networks trained in the study could synthesize conventional images with high image quality (Likert scores 3–4 on a 5-point scale). Qualitatively, the best synthetic images were produced with combination of L1- and perceptual loss functions and perceptual loss alone, while L1-loss alone led to significantly poorer image quality (Likert scores below 3). The in

Synopsis In this study, deep convolutional neural networks (DCNN) are used to synthesize contrast-weighted magnetic resonance (MR) images from quantitative parameter maps of the knee joint obtained with magnetic resonance fingerprinting (MRF). Training of the neural networks was performed using data from 142 patients, for which both standard MR images and quantitative MRF maps of the knee were available. The study demonstrates that synthesizing contrast-weighted images from MRF-parameter maps is possible utilizing DCNNs. Furthermore, the study indicates a need to tune up the dictionary used in MRF so that the parameters expected from the target anatomy are well-covered.

Background: Exergames can provide encouraging exercise options. Currently, there is limited evidence regarding home-based exergaming in the postoperative phase of total knee replacement (TKR). Objective: This study aimed to investigate the effects of a 4-month postoperative home-based exergame intervention with an 8-month follow-up on physical function and symptoms among older persons undergoing TKR compared with home exercise using a standard protocol. In addition, a concurrent embedded design of a mixed methods study was used by including a qualitative component within a quantitative study of exergame effects. Methods: This was a dual-center, nonblinded, two-arm, parallel group randomized controlled trial with an embedded qualitative approach. This study aimed to recruit 100 patients who underwent their first unilateral TKR (aged 60–75 years). Participants were randomized to the exergame or standard home exercise arms. Participants followed a custom-made exergame program independently at their homes daily for 4 months. The primary outcomes at 4 months were function and pain related to the knee using the Oxford Knee Score questionnaire and mobility using the Timed Up and Go test. Other outcomes, in addition to physical function, symptoms, and disability, were game user experience, exercise adherence, physical activity, and satisfaction with the operated knee. Assessments were performed at the preoperative baseline and at 2, 4, and 12 months postoperatively. Exergame adherence was followed from game computers and using a structured diary. Self-reported standard exercise was followed for 4 months of intervention and physical activity was followed for 12 months using a structured diary. Qualitative data on patients’ perspectives on rehabilitation and exergames were collected through laddering interviews at 4 and 12 months. Results: This study was funded in 2018. Data collection began in 2019 and was completed in January 2022. The COVID-19 pandemic caused an u

Wastewater flowrate exhibits valuable information on the conditions in a sewer line. However, existing hardware flowrate sensors are rather expensive, vulnerable to fouling and breakages, and require frequent and laborious maintenance. Therefore, they are typically only mounted in a few key locations of a sewer system, leading to a lack of important information in a major part of the network. Utilizing more cost-effective sensors and a soft sensor approach is advisable for estimating the flowrate at locations where hardware sensors are lacking. Here, the development and testing of a data-driven soft sensor for estimating the wastewater flowrate based on the water level information obtained from a low-cost ultrasonic distance sensor are presented. The research included a long-term functionality testing period of the sensor in a cold region. The soft sensor-based flowrate was applied to estimate inflow and infiltration, indicating the conditions of the sewer line. The harsh conditions inside the sewer manhole caused challenges for the reliability of the distance measurement based on an ultrasonic principle. With the developed model-based soft sensor, it seems possible to accurately estimate the wastewater flowrate. Together with additional information, it might also enable accurate monitoring of inflows and infiltrations.

Background: The prognostic value of preoperative hemoglobin in patients undergoing esophagectomy is unknown. The aim of this study was to examine whether preoperative hemoglobin is associated with prognosis in patients undergoing esophagectomy for cancer. Materials and methods: This was a population-based nationwide retrospective cohort study in Finland, using Finnish National Esophago-Gastric Cancer Cohort (FINEGO). Esophagectomy patients with available preoperative hemoglobin measurement were included. Multivariable cox regression provided hazard ratios (HR) with 95% confidence intervals (CI), adjusted for calendar period of surgery, age at surgery, sex, comorbidity (Charlson Comorbidity Index), tumor histology, tumor stage, neoadjuvant therapy, type of surgery (minimally invasive or open) and annual hospital volume. Results: Of the 1313 patients, 932 (71.0%) were men and 799 (60.9%) had esophageal adenocarcinoma. Overall all-cause mortality was significantly higher in the lowest hemoglobin count tertile (HR 1.26 (1.07–1.47)) compared to the highest tertile, but this association was attenuated after adjustment for confounding. No differences were found between the preoperative hemoglobin groups in the adjusted analyses of 90-day all-cause, 5-year all-cause, and 5-year cancer-specific mortality. Conclusions: In this population-based nationwide study, preoperative hemoglobin count had no independent prognostic significance in esophageal cancer.

Background: People with severe mental illness (SMI) have an elevated risk of obesity but the causes and mechanisms are unclear. We explored the familial association between parental SMI and body mass index (BMI) in middle-aged offspring. Our objective was to determine if the offspring of either parent with SMI have an increased risk for obesity. Methods: The Northern Finland Birth Cohort 1966 is a cohort study of offspring with expected date of birth in 1966. The data include originally 12 068 mothers and 12 231 children from the provinces of Lapland and Oulu in Finland. The final study sample included 5050 middle-aged offspring. Parental SMI was used as exposure in the study. BMI measured at the age of 46 years was used as a primary outcome. Results: Risk for obesity was elevated in the offspring of mothers with SMI [overweight: adjusted odds ratio (OR) 1.93 (1.29–2.90), obese class I: 1.97 (1.20–3.25), obese classes II–III: 2.98 (1.67–5.33)]. For the offspring of either parent with SMI, statistically significant results were found in obese class I and obese classes II–III [overweight: adjusted OR 1.21 (0.94–1.54), obese class I: 1.52 (1.03–1.08), obese classes II–III: 1.53 (1.01–2.32)]. Conclusions: We found an elevated risk of obesity in the middle-aged offspring of either parent with SMI, especially in the offspring of mothers with SMI. Thus, there might be a common familial pathway leading to the co-occurrence of obesity and SMI.

Only 3–5% of heavy alcohol users develop acute alcohol pancreatitis (AAP). This suggests that additional triggers are required to initiate the inflammatory process. Genetic susceptibility contributes to the development of AAP, and SPINK1 mutation is a documented risk factor. We investigated the prevalence of the SPINK1(N34S) mutation in patients with AAP compared to heavy alcohol users who had never suffered an episode of pancreatitis. Blood samples for the mutational analysis from patients with first episode (n = 60) and recurrent AAP (n = 43) and from heavy alcohol users without a history of AAP (n = 98) as well as from a control population (n = 1914) were obtained. SPINK1 mutation was found in 8.7% of the patients with AAP. The prevalence was significantly lower in healthy controls (3.4%, OR 2.72; 1.32–5.64) and very low in alcoholics without pancreatitis (1.0%, OR 9.29; 1.15–74.74). In a comparison adjusted for potential cofounders between AAP patients and alcoholics, SPINK1 was found to be an independent marker for AAP. The prevalence of the SPINK1 mutation is overrepresented in AAP patients and very low in alcoholics without pancreatitis. This finding may play a role in understanding the variable susceptibility to AAP found in heavy alcohol users.

Background: Patients with severe aortic stenosis and left ventricular systolic dysfunction have a poor prognosis, and this may result in inferior survival also after aortic valve replacement. The outcomes of transcatheter and surgical aortic valve replacement were investigated in this comparative analysis. Methods: The retrospective nationwide FinnValve registry included data on patients who underwent transcatheter or surgical aortic valve replacement with a bioprosthesis for severe aortic stenosis. Propensity score matching was performed to adjust the outcomes for baseline covariates of patients with reduced (≤ 50%) left ventricular ejection fraction. Results: Within the unselected, consecutive 6463 patients included in the registry, the prevalence of reduced ejection fraction was 20.8% (876 patients) in the surgical cohort and 27.7% (452 patients) in the transcatheter cohort. Reduced left ventricular ejection fraction was associated with decreased survival (adjusted hazards ratio 1.215, 95%CI 1.067–1.385) after a mean follow-up of 3.6 years. Among 255 propensity score matched pairs, 30-day mortality was 3.1% after transcatheter and 7.8% after surgical intervention (p = 0.038). One-year and 4-year survival were 87.5% and 65.9% after transcatheter intervention and 83.9% and 69.6% after surgical intervention (restricted mean survival time ratio, 1.002, 95%CI 0.929–1.080, p = 0.964), respectively. Conclusions: Reduced left ventricular ejection fraction was associated with increased morbidity and mortality after surgical and transcatheter aortic valve replacement. Thirty-day mortality was higher after surgery, but intermediate-term survival was comparable to transcatheter intervention. Trial registration: The FinnValve registry ClinicalTrials.gov Identifier: NCT03385915.

The sustainable and safe use of rotating machines can be enhanced by condition monitoring. Acceleration signals are commonly used for the indirect measurement of condition, but their analysis can be complicated in industrial applications. When the number of monitored targets is large, efficiently conducted data analysis is essential. The aim of this research was to develop automated, data-driven methods for the analysis of acceleration signals and related data acquired from rotating machines especially in real measurement environments. Methods that simplify system identification would ease the implementation of algorithms, while online monitoring benefits from methods that detect anomalies automatically. The proposed methods for system identification help to automate the selection of training samples, signal features and signal processing settings by optimizing computational criteria through data exploration. Two of the methods proposed for anomaly detection monitor the residuals of regression models and one applies an adaptive approach based on an autocorrelation-based criterion. Methods that need training data from a target in undamaged condition were studied by using real measurement data from azimuth thrusters and a roller leveler. The autocorrelation-based criterion developed for detecting local faults in slowly rotating rolling element bearings was studied with laboratory and simulation data. The results indicated that automated selection of training samples systematized the identification of anomaly detection models and their operating areas in the case of azimuth thrusters. Automated feature selection revealed previously unknown dependencies between acceleration signals and parameters, such as steel strip properties in roller leveling. In addition, certain patterns of local faults in slowly rotating rolling element bearings could be detected automatically from short time series that contained only a few fault impulses. The findings of this work can, Tiivistelmä Pyörivien koneiden kunnonvalvonta voi parantaa niiden kestävää ja turvallista käyttöä. Kiihtyvyyssignaaleja käytetään tavallisesti kunnon epäsuorassa mittauksessa, mutta niiden analysointi voi olla monimutkaista teollisissa sovelluksissa. Kun valvottavia kohteita on useita, on olennaista suorittaa data-analyysi tehokkaasti. Tämän tutkimuksen tarkoituksena oli kehittää automaattisia dataan perustuvia menetelmiä pyörivistä koneista mitattujen kiihtyvyyssignaalien ja niihin liittyvän datan analysointiin erityisesti todellisissa mittausympäristöissä. Järjestelmän identifiointia yksinkertaistavat menetelmät voivat helpottaa algoritmien käyttöönottoa, kun taas jatkuvassa valvonnassa on hyötyä menetelmistä, jotka havaitsevat poikkeavuuksia automaattisesti. Järjestelmän identifiointiin ehdotetut menetelmät auttavat automatisoimaan opetusnäytteiden, signaalin piirteiden ja signaalin prosessointiasetusten valintaa optimoiden laskennallisia kriteerejä datan perusteella. Kaksi esiteltyä menetelmää poikkeavuuksien havaitsemiseen seuraa regressiomallien jäännösvirhettä ja yksi soveltaa mukautuvaa menetelmää, joka perustuu autokorrelaatiosta laskettuun kriteeriin. Menetelmiä, jotka tarvitsevat opetusdataa vauriottomasta kohteesta, tutkittiin todellisella mittausdatalla ruoripotkureista sekä rullaoikaisukoneesta. Hitaasti pyörivien vierintälaakerien paikallisten vikojen havaitsemiseen kehitettyä autokorrelaatioon perustuvaa kriteeriä tutkittiin laboratorio- ja simulointidatalla. Tulokset osoittivat, että opetusdatan automaattinen valinta systematisoi poikkeavuuksien havaitsemiseen kehitettyjen mallien ja niiden toiminta-alueiden identifiointia ruoripotkurien tapauksessa. Automatisoitu piirteiden valinta paljasti ennalta tuntemattomia riippuvuuksia kiihtyvyyssignaaleista ja parametreista, kuten rullaoikaistavan teräsnauhan ominaisuuksista. Lisäksi tietyt vierintälaakereiden paikallisten vikojen piirteet voitiin havaita automaattisesti lyhyistä aikasarjoista, jotka kattoi

Background: The prevalence of atrial fibrillation (AF) is increasing with an aging worldwide population, yet a comprehensive understanding of its causes and consequences remains limited. We aim to assess the causes and consequences of AF via a bidirectional Mendelian randomization (MR) analysis. Methods: We used publicly available genome-wide association study (GWAS) summary data, centralized and harmonized by an open GWAS database. We assessed the genetically predicted effects of 5048 exposures on risk of AF, and the genetically predicted effects of genetic liability to AF, on 10 308 outcomes via two-sample MR analysis. Multivariable MR analysis was further conducted to explore the comparative roles of identified risk factors. Results: MR analysis suggested that 55 out of 5048 exposure traits, including four proteins, play a causal role in AF (P <1e-5 allowing for multiple comparisons). Multivariable analysis suggested that higher body mass index, height and systolic blood pressure as well as genetic liability to coronary artery diseases independently cause AF. Three out of the four proteins (DUSP13, TNFSF12 and IL6R) had a drug prioritizing score for atrial fibrillation of 0.26, 0.38 and 0.88, respectively (values closer to 1 indicating stronger evidence of the protein as a potential drug target). Genetic liability to AF was linked to a higher risk of cardio-embolic ischaemic stroke. Conclusions: Our results suggest body mass index, height, systolic blood pressure and genetic liability to coronary artery disease are independent causal risk factors for AF. Several proteins, including DUSP13, IL-6R and TNFSF12, may have therapeutic potential for AF.

Genetic and early environmental differences including early health habits associate with future health. To provide insight on the causal nature of these associations, monozygotic (MZ) twin pairs discordant for health habits provide an interesting natural experiment. Twin pairs discordant for leisure-time physical activity (LTPA) in early adult life is thus a powerful study design to investigate the associations between long-term LTPA and indicators of health and wellbeing. We have identified 17 LTPA discordant twin pairs from two Finnish twin cohorts and summarize key findings of these studies in this paper. The carefully characterized rare long-term LTPA discordant MZ twin pairs have participated in multi-dimensional clinical examinations. Key findings highlight that compared with less active twins in such MZ twin pairs, the twins with higher long-term LTPA have higher physical fitness, reduced body fat, reduced visceral fat, reduced liver fat, increased lumen diameters of conduit arteries to the lower limbs, increased bone mineral density in loaded bone areas, and an increased number of large high-density lipoprotein particles. The findings increase our understanding on the possible site-specific and system-level effects of long-term LTPA.

Background: Covid-19 pandemic has boosted digitalization in healthcare, as mobility restrictions and social distancing rules have made healthcare providers to adopt digital tools to replace or complement face-to-face interactions. Purpose: We discuss the effects of Covid-19 pandemic on physicians’ use of digital media. We examine whether Covid-19 conditions have changed how physicians use internet resources for information search, how they engage in social media, and their attitude towards online events. Basic procedures: The study was done as a longitudinal panel survey in four waves. The sample was a panel including active physicians in Finland. The panel was updated annually. Identical surveys were administered in 2018, 2019, 2020 and 2021. Spring 2020 was the time when Finland executed mobility restrictions and re-organization of healthcare because of pandemic. Comparing results of the survey before and after Covid-19 restrictions gives us a unique opportunity to do comparative analysis of Covid-19 effects. Main findings: Our results show that the use of digital media for information search stayed relatively stable without statistically significant change during the four-year period covered in the study. The use of social media rose steadily from 2018 to 2021 with no significant difference in the trend. However, there was a significant change in the attitude of Finnish physicians on online events. Year 2021, the attitude remained in this more positive level. Principal conclusions: As use of digital media including social media was already high prior Covid-19 in Finland, our results do not show significant change because of special circumstances introduced in 2020. However, our results show that the attitudes towards online events turned more positive during Covid-19 related restrictions. This could indicate that Covid-19 era has triggered a change that might continue also when pandemic related restrictions will be removed.

We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD.

Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.

Application of membrane technologies in biorefinery processes has been studied for some time. The heterogenous nature of biorefinery steams, however, results in unideal performance of membrane systems and considerable fouling of membranes, which is decreasing the efficiency of separation. As a part of BioSPRINT project, this study focuses on application of separating monomeric sugars from the hemicelluloses fraction of lignocellulosic biomass, where pressure-driven nanofiltration with several diafiltration stages has been proposed for the separation task. Diafiltration is required to overcome the decreased separation efficiency when the retentate concentrations and viscosity increases. A lumped parameter dynamical model of the diafiltration plant is applied. The key model parameters are identified from experimental data from a laboratory membrane unit to reflect the considered biorefinery process. The model is then simulated to study the sensitivity of the uncertain model parameters (related to membrane fouling, solute concentrations, viscosity, and mass transfer coefficients) to the diafiltration plant performance (product purity, operation time). The model is implemented in the MATLAB®/Simulink environment. The simulation results are expected to identify potential sources of scale-up challenges in biorefinery-related membrane applications. The developed dynamic model also allows to investigate different operational strategies of diafiltration plants in the future.

Spontaneous preterm birth (SPTB) is the leading cause of neonatal death and morbidity worldwide. Certain risk factors predispose infants to SPTB, but over half of SPTBs occur in pregnancies where there is no identifiable risk factor. Previous studies have suggested that SPTB has a genetic background and that both maternal and fetal genomes contribute to its likelihood. Other biological factors are also associated with SPTB, but knowledge about these factors is limited. One of the key tissues involved in parturition is the placenta. The aim of this study was to determine the biological factors behind predisposition to SPTB using hypothesis-free methods. A genome-wide association study (GWAS) was used to investigate fetal genetic variants that predispose infants to SPTB. The results suggest that a variant of slit guidance ligand 2 (SLIT2) is associated with SPTB. Additionally, the study showed that SLIT2 and its receptor roundabout guidance receptor 1 (ROBO1) are expressed in placenta, and their mRNA levels are higher in SPTB placentas compared to term controls. A knockdown experiment showed that Slit–Robo signaling affects genes involved in inflammation in placental cells. In a comparative proteomics screen of SPTB, spontaneous term, and elective preterm placentas, proteins for which particular levels are associated with SPTB were identified. Rare and potentially damaging variants of the genes coding for the identified proteins were sought from whole exome sequencing (WES) data. This yielded a candidate, alpha-1 antitrypsin (AAT), which is encoded by SERPINA1. Experiments revealed that SERPINA1 affects actin cytoskeleton, Slit–Robo signaling, and extracellular matrix organization in the placenta. Some heat shock proteins (HSPs) are associated with pregnancy complications. Thus, genetic and genomic datasets were used to identify SPTB-predisposing HSPs from the mother, infant, and placenta. In addition, the association of nuclear hormone receptors (NRs) with S, Tiivistelmä Spontaani ennenaikainen synnytys on vastasyntyneiden yleisin kuolinsyy ja sairauksille altistava tekijä. Ennenaikaisuudelle altistavia tekijöitä tunnetaan, mutta silti yli puolet tapauksista ovat sellaisia, joiden syy jää tunnistamatta. Sekä äidin että lapsen perintötekijät vaikuttavat ennenaikaisen syntymän riskiin. Ennenaikaisuuteen on liitetty myös muita biologisia tekijöitä, mutta tietoa ei ole riittävästi. Yksi synnytyksen käynnistymiseen vaikuttavista kudoksista on istukka. Tavoitteenamme oli löytää hypoteesivapaita menetelmiä käyttämällä biologisia tekijöitä, jotka liittyvät ennenaikaiseen synnytykseen. Genominlaajuisen assosiaatiokartoituksen avulla tarkastelimme lapsen perimän geenivariantteja, jotka altistavat ennenaikaisuudelle. Osoitimme, että SLIT2-geenin variantti voi altistaa ennenaikaisuudelle ja että SLIT2-proteiini ja sen reseptori ROBO1 tuottuvat istukassa. Molempien mRNA-tasot olivat koholla ennenaikaisesti syntyneiden istukoissa verrattuna täysiaikaisiin. Näiden geenien hiljentäminen vaikutti pääasiassa tulehdukseen liittyviin geeneihin. Kun vertasimme spontaanien ennenaikaisesti syntyneiden istukoissa olevia proteiineja täysaikaisesti ja keisarinleikkauksella syntyneiden istukoissa oleviin proteiineihin, havaitsimme, että proteiinien määrät poikkesivat toisistaan. Etsimme harvinaisia ja mahdollisesti vahingollisia variantteja sellaisista geeneistä, jotka koodaavat löytämiämme proteiineja. Havaitsimme, että alpha-1 antitrypsiini (AAT) -proteiini ja sitä koodaava SERPINA1-geeni voivat liittyä ennenaikaisuuteen. Osoitimme, että AAT säätelee solujen ulkopuolisia rakenteita istukassa. Lämpösokkiproteiinien uskotaan liittyvän raskauskomplikaatioihin, ja siksi tarkastelimme useita aineistoja tunnistaaksemme ennenaikaisuuteen liittyviä lämpösokkiproteiineja. Tarkastelimme myös hormonireseptoreja, joiden aktiivisuutta lämpösokkiproteiinit säätelevät. Löysimme useita lämpösokkiproteiineja ja hormonireseptoreja, jotka voivat liittyä ennenaikai

Scandium is currently classified as a critical raw material for the European Union, and several research projects focus on the search for new sources to supply to its expected increasing demand. The Kiviniemi mafic intrusion in Finland is a potential primary source for Sc; at Kiviniemi, Sc occurs mainly within the lattices of ferrous silicates, clinopyroxene and amphibole. Some of the main challenges in leaching of Kiviniemi-type feed material are related to either the complexity of Fe and Ti separation from Sc-containing solutions or a possible gelation problem when leaching a material with a high SiO₂ content. According to preliminary beneficiation tests, direct acid leaching of the Kiviniemi feed material was not successful mainly due to extensive leaching of Fe from the ferrous concentrate. Therefore, a processing scenario with conventional magnetic separation followed by pyrometallurgical reduction of the FeO component to tackle the Fe issue prior hydrometallurgical stage was studied in the previous parts of our project. Leaching experiments in this study focus on the possibilities to extract Sc from low-FeO, Sc₂O₃-enriched amorphous slag. Both a synthetic slag and slags produced from Kiviniemi concentrates were submitted to H₂SO₄-based leaching experiments applying dry digestion, H₂O₂-assisted leaching, and high-pressure acid leaching (HPAL). The formation of silicic acid (gelation) under acidic conditions was avoided with all these methods. With H₂O₂-assisted leaching, efficiencies reached 40–50%, whereas leaching with dry digestion was very limited. With HPAL, the leaching efficiency remained at 30–45% under experimental conditions of 2.5 M H₂SO₄, 60 bar, and 150 °C. These levels of leaching efficiencies are due to an amorphous structure and high SiO₂ content of the slag. Future options for hydrometallurgical processing of Kiviniemi-type slags could include controlled cooling of the slag to produce crystalline structures, combined potentially with f

We investigated whether temperament modifies an association between polygenic intelligence potential and cognitive test performance in midlife. The participants (n = 1647, born between 1962 and 1977) were derived from the Young Finns Study. Temperament was assessed with Temperament and Character Inventory over a 15-year follow-up (1997, 2001, 2007, 2012). Polygenic intelligence potential was assessed with a polygenic score for intelligence. Cognitive performance (visual memory, reaction time, sustained attention, spatial working memory) was assessed with CANTAB in midlife. The PGSI was significantly associated with the overall cognitive performance and performance in visual memory, sustained attention and working memory tests but not reaction time test. Temperament did not correlate with polygenic score for intelligence and did not modify an association between the polygenic score and cognitive performance, either. High persistence was associated with higher visual memory (B = 0.092; FDR-adj. p = 0.007) and low harm avoidance with higher overall cognitive performance, specifically better reaction time (B = −0.102; FDR-adj; p = 0.007). The subscales of harm avoidance had different associations with cognitive performance: higher “anticipatory worry,” higher “fatigability,” and lower “shyness with strangers” were associated with lower cognitive performance, while the role of “fear of uncertainty” was subtest-related. In conclusion, temperament does not help or hinder one from realizing their genetic potential for intelligence. The overall modest relationships between temperament and cognitive performance advise caution if utilizing temperament-related information e.g. in working-life recruitments. Cognitive abilities may be influenced by temperament variables, such as the drive for achievement and anxiety about test performance, but they involve distinct systems of learning and memory.

Knowledge graphs (KGs) structure knowledge to develop intelligent systems in several application domains. Industrial maintenance support requires knowledge and expertise on a variety of aspects of the factory, machinery, and components. However, the actual creation and maintenance process of KGs has remained unelaborated. We review the KG literature to integrate previous models into one process model also incorporating knowledge engineering principles within. The literature review and a subsequent case study together represent the problem and objectives definition phases of a design science project. The contributions include the integrated process model for KG creation and maintenance and the initially observed design challenges in the KG process operationalisation in a context of supporting industrial maintenance.

Power-to-X (P2X) pathways represent alternative storage technologies for utilization of surplus electricity from renewable energy sources (RES) and for greenhouse gas (GHG) emission reduction. These P2X pathways can be used to convert renewable surplus electricity and carbon dioxide from various sources into valuable products such as synthetic fuels and chemicals. Significant progress has been made in these processes towards replacement of conventional fossil fuel-based technologies in the recent years. In this paper the development of these novel technologies is reviewed, having a focus especially on the techno-economic analysis. Key performance indicators such as plant efficiency and production cost are discussed. Finally, knowledge gaps and future research outlook of P2X are highlighted.

Recent evolution of the industrial Internet of Things empowers the classical manufacturing model with cloud computing integration for Industry 4.0. Cloud integration advances the capabilities of manufacturing systems with cloud-based controlling and real-time process monitoring, which is renowned as cloud manufacturing (CM). However, cloud integration exposes the entire manufacturing ecosystem to a new set of security risks and increments in end-to-end latency. Moving security services toward the edge eradicates message routing latency toward the cloud and eliminates the central point of failure while leveraging the entire system’s performance. We propose a blockchain and fog-computing-enabled security service architecture that operates on fog nodes at the edge of manufacturing equipment clusters. The proposed service facilitates CM equipment authentication and equipment-cloud channel privacy protection while preserving anonymity and unlinkability over the blockchain. We implemented the proposed architecture with hyperledger fabric and compared the performance advantage over the state-of-the-art solutions.

A sorption-enhanced process for hydrogenation of CO₂ to methanol was designed and investigated by mathematical modelling and techno-economic analysis. The modelling methodology combined dynamic modelling of the cyclic reactor operation with pseudo-steady state modelling of the overall process. With continuous adsorption of water in the sorption-enhanced process, highly pure methanol (>99%) was produced without downstream distillation. The dynamic reactor cycle was designed and optimized to maximize the methanol production rate. The cycle and the process were modelled in two reactor configurations: adiabatic and isothermal. Under the default cost assumptions for the raw materials (CO₂ 50 €/t, hydrogen 3000 €/t) the adiabatic configuration was found more competitive in terms of the overall methanol production cost, at 1085 €/t compared to 1255 €/t for the isothermal case. The cost estimate for the adiabatic case was found comparable to a reference process representing conventional CO₂ hydrogenation to methanol (1089 €/t). In addition to the methanol process, the developed modeling method has potential in the design of other sorption-enhanced processes.

Background: Preterm birth is defined as live birth before 37 completed weeks of pregnancy, and it is a major problem worldwide. The molecular mechanisms that lead to onset of spontaneous preterm birth are incompletely understood. Prediction and evaluation of the risk of preterm birth is challenging as there is a lack of accurate biomarkers. In this study, our aim was to identify placental proteins that associate with spontaneous preterm birth. Methods: We analyzed the proteomes from placentas to identify proteins that associate with both gestational age and spontaneous labor. Next, rare and potentially damaging gene variants of the identified protein candidates were sought for from our whole exome sequencing data. Further experiments we performed on placental samples and placenta-associated cells to explore the location and function of the spontaneous preterm labor-associated proteins in placentas. Results: Exome sequencing data revealed rare damaging variants in SERPINA1 in families with recurrent spontaneous preterm deliveries. Protein and mRNA levels of alpha-1 antitrypsin/SERPINA1 from the maternal side of the placenta were downregulated in spontaneous preterm births. Alpha-1 antitrypsin was expressed by villous trophoblasts in the placenta, and immunoelectron microscopy showed localization in decidual fibrinoid deposits in association with specific extracellular proteins. siRNA knockdown in trophoblast-derived HTR8/SVneo cells revealed that SERPINA1 had a marked effect on regulation of the actin cytoskeleton pathway, Slit–Robo signaling, and extracellular matrix organization. Conclusions: Alpha-1 antitrypsin is a protease inhibitor. We propose that loss of the protease inhibition effects of alpha-1 antitrypsin renders structures critical to maintaining pregnancy susceptible to proteases and inflammatory activation. This may lead to spontaneous premature birth.

Background: The psychosocial wellbeing of children and adolescents is an ongoing global concern. Despite positive outcomes of child- and family-focused programs, the fragmentation of services presents challenges. To enhance harmonization and diminish fragmentation of service policies, we implement a preventive collaborative service model for children and families. The rationale for our study is based on analyses of national and local data before implementing the service model in the pilot area. Methods: The need for a preventive service model for children and families was demonstrated using national and local data sources. First, a national school health survey was utilized to screen adolescents’ perceptions of their depressive symptoms and support. Second, time trends in child and adolescent psychiatric and child protection service use were investigated. For these aims, epidemiological data of the study area (city of Oulu) were compared with data from the whole country (Finland). Third, local usage data of the preventive stand-alone Let’s Talk About Children (LT) intervention before the service model implementation were evaluated. After these analyses, Let’s Talk About Children Service Model (LT-SM) implementation in the pilot area is described in detail. Results: The background data showed that 17% of the adolescents in the study area had reported depressive symptoms, and almost half of them had not received professional help. Child and adolescent psychiatric outpatient visits had increased during the last decade, but the number of visits remains lower in the study area compared with the country as a whole. The number of adolescent psychiatric inpatient days had increased contrary to a decreasing national trend. The number of urgent child welfare placements was also higher compared with the whole country. The local LT intervention data revealed very low utilization rates. These results indicated a necessity to enhance preventive and collaborative support

The aim of this study was to assess the biofilm formation of Streptococcus mutans, Staphylococcus aureus, Enterococcus faecalis, and Escherichia coli on titanium implants with CAD-CAM tooling techniques. Twenty specimens of titanium were studied: Titanium grade 2 tooled with a Planmeca CAD-CAM milling device (TiGrade 2), Ti₆Al₄V grade 5 as it comes from CAD-DMLS device (computer aided design-direct metal laser sintering device) (TiGrade 5), Ti₆Al₄V grade 23 as it comes from a CAD-CAM milling device (TiGrade 23), and CAD-DMLS TiGrade 5 polished with an abrasive disc (TiGrade 5 polished). Bacterial adhesion on the implants was completed with and without saliva treatment to mimic both extraoral and intraoral surgical methods of implant placement. Five specimens/implant types were used in the bacterial adhesion experiments. Autoclaved implant specimens were placed in petri plates and immersed in saliva solution for 30 min at room temperature and then washed 3× with 1× PBS. Bacterial suspensions of each strain were made and added to the specimens after saliva treatment. Biofilm was allowed to form for 24 h at 37 °C and the adhered bacteria was calculated. Tooling techniques had an insignificant effect on the bacterial adhesion by all the bacterial strains studied. However, there was a significant difference in biofilm formation between the saliva-treated and non-saliva-treated implants. Saliva contamination enhanced S. mutans, S. aureus, and E. faecalis adhesion in all material types studied. S. aureus was found to be the most adherent strain in the saliva-treated group, whereas E. coli was the most adherent strain in the non-saliva-treated group. In conclusion, CAD-CAM tooling techniques have little effect on bacterial adhesion. Saliva coating enhances the biofilm formation; therefore, saliva contamination of the implant must be minimized during implant placement. Further extensive studies are needed to evaluate the effects of surface treatments of the titanium

Supercritical carbon dioxide extraction has been established as a promising and clean technology alternative to conventional separation techniques. Despite a high energy demand of extraction processes, their energy analysis has been scarcely considered. In this study, a supercritical carbon dioxide batch extraction process was modelled through system identification, forming a full simulator of its control loops affecting the energy consumption. The modelling was based on data acquired through systematic approach including experimental design and identification of dynamic process responses and energy consumption. Regression analysis and 12 identified models for subprocesses showed feasible performance during simulations with experimental data. The best local model for a subprocesses exhibited a Mean Absolute Percentage Error of 3% with independent test data. Regression model for steady-state electricity consumption showed a Mean Absolute Percentage Error of 7.6%, also suggesting the existence of nonlinearities between the response and other process variables. The identification approach reveals new information on energy consumption and dynamics of energy consumption of supercritical extraction in transient operating conditions. The models can be applied for further developments in real-time energy monitoring and optimization of supercritical extraction processes.

Background: Mental health is a public health issue for European young people, with great heterogeneity in resource allocation. Representative population-based studies are needed. The Global Burden of Disease (GBD) Study 2019 provides internationally comparable information on trends in the health status of populations and changes in the leading causes of disease burden over time. Methods: Prevalence, incidence, Years Lived with Disability (YLDs) and Years of Life Lost (YLLs) from mental disorders (MDs), substance use disorders (SUDs) and self-harm were estimated for young people aged 10–24 years in 31 European countries. Rates per 100,000 population, percentage changes in 1990–2019, 95% Uncertainty Intervals (UIs), and correlations with Sociodemographic Index (SDI), were estimated. Findings: In 2019, rates per 100,000 population were 16,983 (95% UI 12,823–21,630) for MDs, 3,891 (3,020–4,905) for SUDs, and 89·1 (63·8–123·1) for self-harm. In terms of disability, anxiety contributed to 647·3 (432–912·3) YLDs, while in terms of premature death, self-harm contributed to 319·6 (248·9–412·8) YLLs, per 100,000 population. Over the 30 years studied, YLDs increased in eating disorders (14·9%;9·4–20·1) and drug use disorders (16·9%;8·9–26·3), and decreased in idiopathic developmental intellectual disability (–29·1%;23·8-38·5). YLLs decreased in self-harm (–27·9%;38·3–18·7). Variations were found by sex, age-group and country. The burden of SUDs and self-harm was higher in countries with lower SDI, MDs were associated with SUDs. Interpretation: Mental health conditions represent an important burden among young people living in Europe. National policies should strengthen mental health, with a specific focus on young people.

Machine learning techniques are commonly used in the vibration-based condition monitoring of rotating machines. However, few research studies have focused on model training from a practical viewpoint, namely, how to select representative training samples and operating areas for monitoring applications. We focus on these aspects by studying training sets with varying sizes and distributions, including their effects on the models to be identified. The analysis is based on acceleration and shaft speed data available from an azimuth thruster of a catamaran crane vessel. The considered machine learning algorithm was previously introduced in another study suggesting it could detect defects on the thruster driveline components. In this work, practical guidance is provided to facilitate its implementation, and furthermore, an adaptive method for training subset selection is proposed. Results show that the proposed method enabled the identification of usable training subsets in general, while the success of the previous approach was case-dependent. In addition, the use of Kolmogorov–Smirnov or Anderson–Darling tests for normal distribution, as a part of the method, enabled selections that covered the operating area broadly, while other tests were unfavorable in this regard. Overall, the study demonstrates that reconfigurable and automated model implementations could be achievable with minor effort.

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO₂) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO₂ fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO₂ exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO₂ fluxes and to better es

Mature test automation is key for achieving high product quality at speed. However, many organizations still have immature test automation practices that impede them to reap expected benefits. Not all attempts to improve test automation practices are successful, usually caused by ineffective assessment and improvement. This dissertation aims to develop the guidelines for test automation maturity assessment and improvement by synthesizing existing guidelines from various sources, demonstrating the adoption of developed guidelines, and evaluating the effectiveness of the developed guidelines with practitioners. In this dissertation, we synthesized a taxonomy of test automation best practices from 18 test maturity models. We also reviewed 26 academic literature and 55 grey literature sources on the same topic, and found that the current literature includes the guidelines that are not covered in test maturity models, like new technical best practices and advice (e.g., improvement approaches, technical techniques, and experience-based heuristics) on conducting certain best practices. Using synthesized test automation best practices from test maturity models as the base, we developed a test automation maturity survey and distributed it in the current industry to explore the state of practice of test automation maturity. Based on 151 survey responses coming from above 100 organizations in 25 countries, several observations were made to demonstrate the adoption of test automation best practices proposed by existing test maturity models, e.g., there is a lack of guidelines on designing and executing automated tests and the right metrics to measure test automation performance in general. We observed that high levels of test automation maturity (assessed by test automation best practices from test maturity models) can lead to high product quality at speed in modern software developments, using empirical evidence from an experience study (that examined the experience o, Tiivistelmä Kypsä testiautomaatio on avainasemassa korkean tuotelaadun saavuttamisessa ilman että tarvitsee tinkiä tuotekehityksen nopeudesta. Usein organisaatioiden vielä kehittymättömät testiautomaatiokäytännöt estävät niitä saamasta automaatiolta odotettuja hyötyjä. Yritykset parantaa testiautomaatiokäytäntöjä eivät aina onnistu, mikä johtuu yleensä puutteellisesta testiautomaation kypsyydenarvioinnista ja -parantamisesta. Tämän väitöskirjan tavoitteena on kehittää ohjeistusta testiautomaation kypsyyden arviointiin ja parantamiseen syntetisoimalla olemassa olevia ohjeita eri lähteistä, tutkimalla kehitettyjen ohjeiden omaksumista ja arvioimalla kehitettyjen ohjeiden tehokkuutta yhdessä ohjelmistoteollisuuden toimijoiden kanssa. Väitöskirjassa syntetisoitiin testiautomaation hyvien käytäntöjen taksonomia 18 testikypsyysmallista. Kirjallisuuskatsauksessa tutkittiin 26 akateemista ja 55 harmaankirjallisuuden lähdettä. Havaittiin, että nykyinen kirjallisuus sisältää ohjeita, joita ei ole testikypsyysmalleissa, kuten uusia teknisiä hyviä käytäntöjä ja neuvoja (esim. teknisiä menetelmiä ja kokemuspohjaista heuristiikkaa) tiettyjen hyvien käytäntöjen toteuttamiseksi. Kirjallisuudesta syntetisoitujen, kypsyysmalleihin pohjautuvien hyvien käytäntöjen avulla kehitettiin kyselylomake ohjelmistoteollisuuden testiautomaation kypsyyden tilan mittaamiseen. Yli 100 organisaatiosta ja 25 maasta saadun 151 kyselyvastauksen perusteella tehtiin havaintoja testiautomaation hyvien käytäntöjen omaksumisesta. Puutteita havaittiin testiautomaation suunnittelun ja käytön ohjeistuksessa sekä hyötyjen mittaamisen käytänteissä. Tulokset osoittavat, että testiautomaation korkea kypsyysaste voi johtaa tuotteiden korkeaan laatuun hidastamatta tuotekehityksen nopeutta nykyaikaisessa ohjelmistokehityksessä. Havainnot perustuvat sekä empiiriseen kokemustutkimukseen, jossa tutkittiin testiautomaation kypsyyden parantamisessa onnistuneen DevOps-tiimin kokemuksia että kvantitatiiviseen tutkimukseen

The Autism Spectrum Disorders in the European Union (ASDEU) survey investigated local services’ use experiences of autistic adults, carers and professionals with interventions for autistic adults. The majority of the 697 participants experienced recommended considerations prior to deciding on intervention and during the intervention plan and implementation. Psychosocial interventions were the most commonly experienced interventions, while pharmacological interventions NOT recommended for core autistic symptoms were reported by fairly large proportions of participants. Family interventions were experienced slightly more commonly by carers than adults or professionals. Less than the 26% of autistic adult responders who had experienced challenging behaviors reported receiving an intervention to change them. These results provide insights for improving gaps in service provision of interventions among autistic adults.

Introduction: Thyroid diseases in pregnancy are relatively common and are associated with adverse pregnancy and perinatal outcomes, increasing a neonate’s risk of admission to the neonatal intensive care unit (NICU). The aim of this study was to evaluate the indications for increased risk of NICU admission among the neonates of hypothyroid and hyperthyroid mothers. Material and methods: The study data consisted of all singleton deliveries (n = 734 773) between 2004 and 2016 in Finland collected from the Finnish Medical Birth Register. The odds of NICU admission (with 95% confidence intervals) were compared between the neonates of hypothyroid or hyperthyroid mothers and of mothers without any thyroid diseases by specified neonatal characteristics and morbidities using logistic regression analysis. The studied neonatal characteristics were preterm birth (<37+0 gestational weeks), low birthweight (<2500 g), the rate of small- and large-for-gestational age infants, and eight disease-specific neonatal outcomes: asphyxia, respiratory distress syndrome, meconium aspiration syndrome, pneumothorax, cardiovascular problems, infections, jaundice and hypoglycemia. Results: The most common indications for NICU care were principally the same in the neonates of the mothers with and without thyroid disease: respiratory distress syndrome, infections, preterm birth, low birthweight and neonatal hypoglycemia. The preterm neonates, neonates with low birthweight, and large-for-gestational-age infants had increased odds of NICU admission if their mother had hypothyroidism. Also neonates with cardiovascular problems, jaundice or hypoglycemia associated with maternal diabetes had increased odds of NICU admissions if their mother had hypothyroidism. Further, the preterm neonates, large-for-gestational-age infants, and term infants with jaundice had increased odds of NICU admission if their mother had hyperthyroidism. Conclusions: The most common indications for NICU care were

Objective: The elevated prevalence of cardiometabolic disorders is consistently reported in patients with severe mental illness (SMI). We explored the association between parental SMI and offspring cardiometabolic morbidity. Our hypothesis was that offspring of people with SMI have increased morbidity risk. Method: The Northern Finland Birth Cohort 1966 is a study of offspring whose date of birth was expected in 1966. The follow-up lasted until 2015 (49 years). The final study sample included 11,175 children. We used parental SMI as the exposure in the study. The following cardiometabolic disorders were used as outcome measures: diabetes mellitus, hypertension, hyperlipidemia, coronary artery disease, obesity, and cerebrovascular disorders. Results: There were 139 (14.7%; hazard ratios [HR] = 1.63; 95% confidence interval [CI] = 1.36–1.94) children of parents with SMI who developed cardiometabolic disorder during follow-up and 957 (9.4%) in the comparison cohort. Statistically significant HRs were found in males (HR = 1.95; 95% CI =1.56–2.44), but not in females (HR = 1.29; 95% CI = 0.96–1.73). Conclusions: Having a cardiometabolic disorder was associated with male offspring of parents with SMI. Our findings suggest that there is an elevated risk of coronary artery disease, hyperlipidemia, obesity, and hypertension in the male offspring of parents with SMI. Our results suggest that the somatic health of offspring of parents with SMI should also be considered in addition to their mental health in clinical practice.

Background: The accumulation of disparate diseases in complex multimorbidity makes prevention difficult if each disease is targeted separately. We aimed to examine obesity as a shared risk factor for common diseases, determine associations between obesity-related diseases, and examine the role of obesity in the development of complex multimorbidity (four or more comorbid diseases). Methods: We did an observational study and used pooled prospective data from two Finnish cohort studies (the Health and Social Support Study and the Finnish Public Sector Study) comprising 114 657 adults aged 16–78 years at study entry (1998–2013). A cohort of 499 357 adults (aged 38–73 years at study entry; 2006–10) from the UK Biobank provided replication in an independent population. BMI and clinical characteristics were assessed at baseline. BMIs were categorised as obesity (≥30·0 kg/m²), overweight (25·0–29·9 kg/m²), healthy weight (18·5–24·9 kg/m²), and underweight (<18·5 kg/m²). Via linkage to national health records, participants were followed-up for death and diseases diagnosed according to the International Classification of Diseases 10th Revision (ICD-10). Hazard ratios (HRs) with 95% CIs and population attributable fractions (PAFs) for associations between BMI and multimorbidity were calculated. Findings: Mean follow-up duration was 12·1 years (SD 3·8) in the Finnish cohorts and 11·8 years (1·7) in the UK Biobank cohort. Obesity was associated with 21 non-overlapping cardiometabolic, digestive, respiratory, neurological, musculoskeletal, and infectious diseases after Bonferroni multiple testing adjustment and ignoring HRs of less than 1·50. Compared with healthy weight, the confounder-adjusted HR for obesity was 2·83 (95% CI 2·74–2·93; PAF 19·9% [95% CI 19·3–20·5]) for developing at least one obesity-related disease, 5·17 (4·84–5·53; 34·4% [33·2–35·5]) for two diseases, and 12·39 (9·26–16·58; 55·2% [50·9–57·5]) for complex multimorbidity. The proportion of particip

Estimation of power plant fuel input fractions based on unscented Kalman filtering using a first principles simulation model of the furnace is considered. The approach is described, together with experimental results using data from a full scale circulating fluidized bed power plant. The results encourage the fusion of machine learning and physical models in monitoring of industrial processes.

Objective: Previous studies on the association between metabolic biomarkers and hypertension have been limited by small sample sizes, low number of studied biomarkers, and cross-sectional study design. In the largest study to date, we assess the cross-sectional and longitudinal associations between high-abundance serum biomarkers and blood pressure (BP). Methods: We studied cross-sectional (N = 36 985; age 50.5 ± 14.2; 53.1% women) and longitudinal (N = 4197; age 49.4 ± 11.8, 55.3% women) population samples of Finnish individuals. We included 53 serum biomarkers and other detailed lipoprotein subclass measures in our analyses. We studied the associations between serum biomarkers and BP using both conventional statistical methods and a machine learning algorithm (gradient boosting) while adjusting for clinical risk factors. Results: Fifty-one of 53 serum biomarkers were cross-sectionally related to BP (adjusted P < 0.05 for all). Conventional linear regression modeling demonstrated that LDL cholesterol, remnant cholesterol, apolipoprotein B, and acetate were positively, and HDL particle size was negatively, associated with SBP change over time (adjusted P < 0.05 for all). Adding serum biomarkers (cross-sectional root-mean-square error: 16.27 mmHg; longitudinal: 17.61 mmHg) in the model with clinical measures (cross-sectional: 16.70 mmHg; longitudinal 18.52 mmHg) improved the machine learning model fit. Glucose, albumin, triglycerides in LDL, glycerol, VLDL particle size, and acetoacetate had the highest importance scores in models related to current or future BP. Conclusions: Our results suggest that serum lipids, and particularly LDL-derived and VLDL-derived cholesterol measures, and glucose metabolism abnormalities are associated with hypertension onset. Use of serum metabolite determination could improve identification of individuals at high risk of developing hypertension.

Tiivistelmä. Teollisessa energian- ja lämmöntuotannossa käytetyt biomassapolttoaineet tuottavat palamisprosessin aikana suuria määriä tuhkaa, joka on kemialliselta koostumukseltaan soveltuvaa käytettäväksi erilaisiin kohteisiin. Hyötykäytön mahdollisuuksia on tutkittu Suomessa ja muualla maailmassa jo useiden vuosikymmenten ajan, mutta viimeaikainen biomassapolttoaineiden käytön kasvu on lisännyt mielenkiintoa tutkimukselle. Suomalaisista biomassapolttoainetuhkista suurin osa käytetään metsänlannoitukseen ja maanrakennukseen. Suomessa tuhkien hyötykäytön aste on yli 50 %. Tuhkaa voidaan käyttää joissain kohteissa, kuten metsänlannoituksessa miltei sellaisenaan, kun taas esimerkiksi adsorbenttimateriaalina käytettäessä sitä on esikäsiteltävä laajemmin ennen käyttöä. Tuhkan esikäsittely voi mahdollistaa tuhkille enemmän käyttökohteita. Tuhkien suurimpia käyttökohteita ohjataan Suomessa lainsäädännön avulla. Metsänlannoitukseen käytettävän tuhkan on täytettävä tiettyjä kriteereitä, jotta sitä voidaan käyttää. Tuhkassa ei esimerkiksi saa olla lainsäädännön määräämien rajojen ylittäviä pitoisuuksia raskasmetalleja, sillä näiden on todettu kuormittavan ympäristöä. Vastaavasti maanrakennukseen käytettävälle tuhkalle on määritetty pitoisuusrajoja sekä tiettyjä ominaisuuksia, joita tuhkalla tulee olla. Tällaisia ominaisuuksia voi esimerkiksi olla routimattomuus ja vedenläpäisykyky. Uusiutuvien polttoaineiden käytön lisääntyessä syntyvien tuhkien määrä kasvaa samalla. Tuhkien hävittäminen uudelleenkäyttämisen sijaan on usein taloudellisesti kannattamatonta ja ympäristöä kuormittavampaa, sillä tuhkaa käyttämällä voidaan vähentää työvaiheita esimerkiksi betonintuotannossa. Mikäli tuhkia halutaan hyötykäyttää suurempia määriä, on tuhkille kehitettävä lisää käyttökohteita tai niitä tulisi käyttää laajemmin jo tunnettuihin kohteisiin. Uusista käyttökohteista lupaavimpia on tuhkien käyttö geopolymeerien valmistuksessa. Geopolymeerejä voidaan käyttää laastin sementin ja betonin valm

Energy efficiency is increasingly being considered as a critical measure of process performance due to its importance both in production costs and in environmental footprint. In this work, an indirect energy efficiency estimator was developed for the Tennessee Eastman (TE) benchmark process for the first time. The TE model was first modified to provide the reference values of energy efficiency. A sophisticated model selection scheme was then applied to build the surrogate-model. The results indicate reasonable model performance with mean absolute prediction error around 1.7%. The results also highlight the limitations present in the training set, which are, together with other practical implementation issues, discussed in this work.

Background: Good social relationships with parents and peers protect children and adolescents from developing mental disorders in adulthood while several negative experiences increase the risk of depression in later life. Methods: We used population-based cohort data from the Northern Finland Birth Cohort (NFBC) 1986. Participants (n = 6147), their teachers and parents reported factors associated with the social environment of children and adolescents. Diagnoses of depression of cohort members were derived from Finnish nationwide registers. We conducted regression analyses to assess which factors of the social environment of childhood and adolescence were associated with depression in young adulthood. Results: Bullying victimization in adolescence was the strongest predictor of depression in young adulthood among girls (OR 2.23: 95% CI 1.47–3.39) and boys (OR 2.44: 95% CI 1.49–4.00). Loneliness and bullying behavior in childhood were associated with depression in boys only. Loneliness in adolescence (OR 1.63: 95% CI 1.30–2.04) was associated with depression among both genders. Spending with the family seemed to protect against the negative impact of bullying and loneliness. Limitations: We used single-item study questions to measure social relationships. These questions do not necessarily describe the phenomena as accurately as the measures validated for them. Conclusions: Problems in social relationships with peers in childhood and adolescence are associated with depression in young adulthood. Time spent with the family is emphasized in situations in which adolescents have problems in peer-relationships.

Objectives: In prospective follow-up studies, participants are normally contacted during the follow-up period. Even though the idea is not to intervene, the studies conducted during follow-up may affect the target population. Our hypotheses were that participation in the prospective Northern Finland Birth Cohort 1986 study (NFBC 1986) increased the use of mental health services and reduced suicidal behaviour due to participation in follow-up studies. Methods: The NFBC 1986 study covered people with an expected date of birth between July 1985 and June 1986 in northern Finland (n=9,396). The participants of the NFBC 1986 were followed since the antenatal period with follow-ups including clinical examinations. The comparison cohort comprised people born in the same area in 1987 (n=8,959), who were not contacted. Registry data on psychiatric treatment, suicide attempts, and suicides were available. Crude risk ratios (RRs) and adjusted (for marital status and education) Mantel-Haenszel RRs were reported. Results: No increase in mental disorders were found in NFBC 1986 compared to comparison cohort. In the crude RR analysis of female participants, a lower risk for suicide attempts was found (RR, 0.67; 95% confidence interval, 0.49 to 0.92; p=0.011). Conclusions: The results did not support our first hypothesis regarding the increased use of mental health services in the NFBC 1986 cohort. However, our second hypothesis gained some support as female participants of the NFBC 1986 had a lower risk of suicide attempts, although it was not due to a higher number of participants receiving psychiatric treatment.

Hypoxia plays an important regulatory role in the vasculature to adjust blood flow to meet metabolic requirements. At the level of gene transcription, the responses are mediated by hypoxia-inducible factor (HIF) the stability of which is controlled by the HIF prolyl 4-hydroxylase-2 (PHD2). In the lungs hypoxia results in vasoconstriction, however, the pathophysiological relevance of PHD2 in the major arterial cell types; endothelial cells (ECs) and arterial smooth muscle cells (aSMCs) in the adult vasculature is incompletely characterized. Here, we investigated PHD2-dependent vascular homeostasis utilizing inducible deletions of PHD2 either in ECs (Phd2∆ECi) or in aSMCs (Phd2∆aSMC). Cardiovascular function and lung pathologies were studied using echocardiography, Doppler ultrasonography, intraventricular pressure measurement, histological, ultrastructural, and transcriptional methods. Cell intrinsic responses were investigated in hypoxia and in conditions mimicking hypertension-induced hemodynamic stress. Phd2∆ECi resulted in progressive pulmonary disease characterized by a thickened respiratory basement membrane (BM), alveolar fibrosis, increased pulmonary artery pressure, and adaptive hypertrophy of the right ventricle (RV). A low oxygen environment resulted in alterations in cultured ECs similar to those in Phd2∆ECi mice, involving BM components and vascular tone regulators favoring the contraction of SMCs. In contrast, Phd2∆aSMC resulted in elevated RV pressure without alterations in vascular tone regulators. Mechanistically, PHD2 inhibition in aSMCs involved actin polymerization -related tension development via activated cofilin. The results also indicated that hemodynamic stress, rather than PHD2-dependent hypoxia response alone, potentiates structural remodeling of the extracellular matrix in the pulmonary microvasculature and respiratory failure.

Catalyst development for biorefining applications involves many challenges. Mathematical modeling can be seen as an essential tool in assisting to explain catalyst performance. This paper presents studies on several machine learning (ML) methods that can model the performance of heterogeneous catalysts with relevant descriptors. A systematic approach for selecting the most appropriate ML method is taken with focus on the variable selection. Regularization algorithms were applied to variable selection. Several different candidate model structures were compared in modeling with interpretation of results. The systematic modeling approach presented aims to highlight the necessary tools and aspects to unexperienced users of ML. Literature datasets for the hydrogenation of 5-ethoxymethylfurfural with simple bimetal catalysts, including main metals and promoters, were studied with the addition of catalyst descriptors found in the literature. Good results were obtained with the best models for estimating conversion, selectivity, and yield with correlations between 0.90 and 0.98. The best identified model structures were support vector regression, Gaussian process regression, and decision tree methods. In general, the use of variable selection procedures was found to improve the performance of models. The modeling methods applied thus seem to exhibit a strong potential in aiding catalyst development based mainly on the information content of descriptor datasets.

Pregnancies conceived through donor oocytes or sperm show increased risk for preeclampsia. We studied this issue in a preeclampsia case-control cohort (n = 2778), and found overrepresentation of donor cell gestations among women with preeclampsia (14/1627, 0.86%; OR 1.81; 95% CI: 1.07–3.08; P = 0.025) compared to the population data. Moreover, we observed excess of male births from donor cell pregnancies (male-to-female ratio 2.5 vs. 0.97; OR 2.57; 95% CI 1.02–6.36; P = 0.043). Maternal age (36.7 vs. 30.2; P < 0.0001) and preterm deliveries (64% vs. 38%; P = 0.046) distinguished donor cell gestations from other pregnancies with preeclampsia. These results support foreign fetal antigens as modulators of preeclampsia.

Continuous and robust measurements are needed for the high end-product quality and efficient and eco-friendly process in paperboard manufacturing. As the online measurements enable the optimization of the manufacturing process making it more cost effective and environmentally friendly, these measurements must be validated carefully and continuously. This paper presents the development of a mass-balance based soft sensor for online estimation of a two-ply paperboard ash content. The developed soft sensor considers the basis weight, moisture and fiber measurements to derive the ash content of the paperboard at the reel. The development of the soft sensor was success (Mean Absolute Percentage Error was 11.80) and during the long-term simulation with measured data, this robust online estimator showed the level and changes in ash content accurately, enabling also the continuous validation of the hardware sensor.

Parental death before adulthood has been shown to increase offspring’s risk of poor health and adverse social consequences. In a sample of 422 subjects with parental death (334 (79.1%) due to natural causes), and 6172 matched controls, those with parental death were given a diagnosis of a psychiatric disorder up to 28 years of age earlier than their controls (10-year survival proportions: 88.6% vs. 93.1%, p = 0.001). Our findings indicate that psychosocial support must be provided as early as when a parent falls ill, especially with those illnesses that are the most common causes of death in the population.