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Abstract This article introduces a novel integrated nearest level controller (NLC) combined with selective harmonic mitigation (SHM) control approach aimed at efficiently suppressing lower‐order harmonics has been introduced. The proposed methodology is implemented on the PUC‐7 inverter topology, leveraging the combined benefits offered by both NLC and SHM controllers through a hybrid model. The proposed method demonstrates the capability to reduce lower‐order harmonics up to the 49th harmonic from the load voltage. The particle swarm optimization algorithm is employed to determine optimal switching angles and their corresponding nearest levels, thereby reducing implementation time, computational complexity, and overall system intricacy. The performance analysis of the proposed control strategy across various scenarios, including fluctuations in modulation index and monitoring diverse parameters such as load dynamics has been performed. This approach yields a significant reduction in total harmonic distortion in both load voltage and current. A comparative analysis between NLC, selective harmonic mitigation (SHM), and the integrated NLC‐SHM approach is carried out on the PUC‐7 inverter. The integrated SHM‐NLC control is implemented and validated using the MATLAB Simulink environment, complemented by hardware‐based experimentation, to ascertain its effectiveness.

Abstract As major terrestrial carbon sinks, forests play an important role in mitigating climate change. The relationship between the seasonal uptake of carbon and its allocation to woody biomass remains poorly understood, leaving a significant gap in our capacity to predict carbon sequestration by forests. Here, we compare the intra-annual dynamics of carbon fluxes and wood formation across the Northern hemisphere, from carbon assimilation and the formation of non-structural carbon compounds to their incorporation in woody tissues. We show temporally coupled seasonal peaks of carbon assimilation (GPP) and wood cell differentiation, while the two processes are substantially decoupled during off-peak periods. Peaks of cambial activity occur substantially earlier compared to GPP, suggesting the buffer role of non-structural carbohydrates between the processes of carbon assimilation and allocation to wood. Our findings suggest that high-resolution seasonal data of ecosystem carbon fluxes, wood formation and the associated physiological processes may reduce uncertainties in carbon source-sink relationships at different spatial scales, from stand to ecosystem levels.

As soil microbial respiration is the major component of land CO2 emissions, differences in the functional dependence of respiration on soil moisture among Earth system models (ESMs) contributes significantly to the uncertainties in their projections. Using soil organic C (SOC) stocks and CO2 data from a boreal forest–mire ecotone in Finland and Bayesian data assimilation, we revised the original precipitation-based monotonic saturation dependency of the Yasso07 soil carbon model using the non-monotonic Ricker function based on soil volumetric water content. We fit the revised functional dependency of moisture to the observed microbial respiration and SOC stocks and compared its performance against the original Yasso07 model and the version used in the JSBACH land surface model with a reduction constant for decomposition rates in wetlands. The Yasso07 soil C model coupled with the calibrated unimodal Ricker moisture function with an optimum in well-drained soils accurately reconstructed observed SOC stocks and soil CO2 emissions and clearly outperformed previous model versions on paludified organo-mineral soils in forested peatlands and water-saturated organic soils in mires. The best estimate of the posterior moisture response of decomposition used both measurements of SOC stocks and CO2 data from the full range of moisture conditions (from dry and xeric to wet and water-saturated soils). We observed unbiased residuals of SOC and CO2 data modelled with the moisture optimum in well-drained soils, suggesting that this modified function accounts more precisely for the long-term SOC change dependency according to ecosystem properties as well as the contribution of short-term CO2 responses including extreme events. The optimum moisture for decomposition in boreal forests was found in well-drained soils instead of the mid-range between dry and water-saturated conditions as is commonly assumed among soil C and ESMs. Although the unimodal moisture modifier with an optimum in well-drained soils implicitly incorporates robust biogeochemical mechanisms of SOC accumulation and CO2 emissions, it needs further evaluation with large-scale data to determine if its use in land surface models will decrease the uncertainty in projections.

We developed tree level biomass (dry weight) models for Norway spruce (Picea abies [L.] H. Karst.), silver birch (Betula pendula Roth), rowan (Sorbus aucuparia L.) and aspen (Populus tremula L.) growing in young spruce dominated seedling stands with high mixture of broadleaves. The study material was collected from three planted Norway spruce seedling stands located on mineral soil in southern Finland. Biomass models were estimated by individual tree component (stem, living branches, foliage, stump, and roots with diameter of 2 mm) by using a multi-response approach (seemingly unrelated regression), which estimated the parameters of the sub-models (tree component) simultaneously. Even though the application and generalization of the developed models can be restricted by the limited material, they provide new information of seedling biomass allocation and more reliable biomass predictions for spruce and birch growing in young seedling stand compared with those of the commonly applied biomass models (Repola 2008, 2009) in Finland. Repola’s models (2008, 2009) tended to produce biased predictions for crown and below-ground biomasses of seedlings by allocating too much biomass to roots and too little to needle and branches. In addition, this study provides biomass models for aspen and rowan, which were not previously available.

Objectives To assess the ability of baseline serum biomarkers to predict disease activity and remission status in juvenile idiopathic arthritis (JIA) at 18-year follow-up (FU) in a population-based setting.Methods Clinical data and serum levels of inflammatory biomarkers were assessed in the longitudinal population-based Nordic JIA cohort study at baseline and at 18-year FU. A panel of 16 inflammatory biomarkers was determined by multiplexed bead array assay. We estimated both univariate and multivariate logistic regression models on binary outcomes of disease activity and remission with baseline variables as explanatory variables.Results Out of 349 patients eligible for the Nordic JIA cohort study, 236 (68%) had available serum samples at baseline. We measured significantly higher serum levels of interleukin 1β (IL-1β), IL-6, IL-12p70, IL-13, MMP-3, S100A9 and S100A12 at baseline in patients with active disease at 18-year FU than in patients with inactive disease. Computing receiver operating characteristics illustrating the area under the curve (AUC), we compared a conventional prediction model (gender, age, joint counts, erythrocyte sedimentation rate, C reactive protein) with an extended model that also incorporated the 16 baseline biomarkers. Biomarker addition significantly improved the ability of the model to predict activity/inactivity at the 18-year FU, as evidenced by an increase in the AUC from 0.59 to 0.80 (p=0.02). Multiple regression analysis revealed that S100A9 was the strongest predictor of inactive disease 18 years after disease onset.Conclusion Biomarkers indicating inflammation at baseline have the potential to improve evaluation of disease activity and prediction of long-term outcomes.

Globally, annual emissions from managed organic soils accounts for up to 5% of all anthropogenic greenhouse gas (GHG) emissions. Climate-wise management and restoration of degraded organic soils could reduce GHG emissions quickly and at relatively low costs. The European Union (EU) Member States that have large areas of organic soils with high GHG emissions are Sweden, Finland, Germany, Ireland, Poland, Netherlands, and the Baltic countries. To meet the climate targets and objectives of the Paris Agreement the land-use sector is indispensable and mitigation policies targeting organic soils will be needed. The international regulatory framework is broad and quite unspecific. In contrast, the European Union has initiated binding regulation for the land-use sector through the EU Climate Law, the EU LULUCF regulation, and the proposed EU Nature Restoration Law. However, even this regulatory approach is not on track to deliver on its binding ambitions, indicating the need for more effective implementation measures also on organic soils in the EU and its member states. Furthermore, we argue that appropriate policy selection should consider current knowledge regarding the climate impacts of management options of organic soils. Lastly, we need more studies on GHG emissions, and standardized methods for GHG inventories, to resolve uncertainties surrounding the impacts of management to GHG emissions. Successful policy implementation requires more efforts but also improved scientific justification through continuous consideration of climate policy integrity and strengthening of the reliability of GHG inventories.

It is increasingly recognized that light-absorbing impurities (LAI) deposited on snow and ice affect their albedo and facilitate melting processes leading to various feedback loops, such as the ice albedo feedback mechanism. Black carbon (BC) is often considered the most important LAI, but some areas can be more impacted by high dust emissions. Iceland is one of the most important high latitude sources for the Arctic due to high emissions and the volcanic nature of the dust. We studied optical properties of volcanic dust from Iceland and Chile to understand how it interacts with the Sun’s radiation and affects areas of deposition as LAI. Optical properties of dust samples were measured at the laboratory of the Finnish Geospatial Research Institute (FGI) using the latest setup of the FGI’s goniospectrometer. We found that, depending on the particle size, the albedo of dry volcanic dust on the visible spectrum is as low as 0.03, similar to that of BC, and the albedo decreases with increasing particle size. Wet dust reduces its albedo by 66% compared to dry sample. This supports the comparability of their albedo reducing effects to BC as LAIs, and highlights their significant role in albedo reduction of snow and ice areas. The potential use of the results from our measurements is diverse, including their use as a ground truth reference for Earth Observation and remote sensing studies, estimating climate change over time, as well as measuring other ecological effects caused by changes in atmospheric composition or land cover.

Abstract Background There is a growing interest concerning the relationship between obesity and several medical conditions and inflammation. Nevertheless, there is a lack of studies regarding body mass index (BMI) among patients with juvenile idiopathic arthritis (JIA). Our aim was to investigate the impact of BMI on health-related quality of life (HRQoL) measured with a 36-Item Short Form Survey (SF-36), disease activity, and disability in young adults with JIA. Methods This study is a part of the population-based Nordic JIA cohort study. All newly diagnosed patients with JIA were recruited consecutively between 1997–2000 in specific regions in the Nordic countries. Patients in this sub-study were enrolled from 434 patients who attended their 18-year follow-up visit. Patients were classified according to the World Health Organization (WHO) into four groups based on their BMI. HRQoL, disease characteristics, disability, fatigue, sleep quality, physical activity, pain, comorbidities, and social status were assessed. Results Three hundred fifty-five patients from the original study cohort were enrolled in this study and 72% of them were female. Mean age was 23.9 (± SD 4.4) years. A significant relationship was found between the JIA categories and BMI groups (p = 0.014). A significant relationship was also found between BMI and disease activity scores (DAS28) (p = 0.028), disability (p

Process-based forest models combine biological, physical, and chemical process understanding to simulate forest dynamics as an emergent property of the system. As such, they are valuable tools to investigate the effects of climate change on forest ecosystems. Specifically, they allow testing of hypotheses regarding long-term ecosystem dynamics and provide means to assess the impacts of climate scenarios on future forest development. As a consequence, numerous local-scale simulation studies have been conducted over the past decades to assess the impacts of climate change on forests. These studies apply the best available models tailored to local conditions, parameterized and evaluated by local experts. However, this treasure trove of knowledge on climate change responses remains underexplored to date, as a consistent and harmonized dataset of local model simulations is missing.Here, our objectives were (i) to compile existing local simulations on forest development under climate change in Europe in a common database, (ii) to harmonize them to a common suite of output variables, and (iii) to provide a standardized vector of auxiliary environmental variables for each simulated location to aid subsequent investigations. Our dataset of European stand- and landscape-level forest simulations contains over 1.1 million simulation runs representing 135 million simulation years for more than 13,000 unique locations spread across Europe. The data were harmonized to consistently describe forest development in terms of stand structure (dominant height), composition (dominant species, admixed species), and functioning (leaf area index). Auxiliary variables provided include consistent daily climate information (temperature, precipitation, radiation, vapor pressure deficit) as well as information on local site conditions (soil depth, soil physical properties, soil water holding capacity, plant-available nitrogen). The present dataset facilitates analyses across models and locations, with the aim to better harness the valuable information contained in local simulations for large-scale policy support, and for fostering a deeper understanding of the effects of climate change on forest ecosystems in Europe.

Background: Low computed tomography (CT)-determined muscle mass, commonly determined with height-adjusted muscle indexes (MIs), predicts worse survival in several cancers and has been suggested as a prognostic assessment tool. Although several MIs measured at the level of the 3rd lumbar vertebra (L3) are commonly used, it remains unestablished how different L3-determined MIs perform in survival prognostication compared to each other. The objective of this study was to investigate the performance of different MIs for survival prognostication in renal cell carcinoma (RCC). Methods: We retrospectively enrolled 214 consecutive patients with RCC. We determined three L3-MIs (psoas muscle index (PMI), psoas muscle index and erector spinae index (PMI+ESI), and whole skeletal muscle index (SMI)) from preoperative CT scans. Categorization of those with low and normal muscle mass was based on the Youden Index sex-specific MI cut-offs. We determined sensitivity, specificity, and accuracy metrics for predicting 1-year, 5-year, and overall survival (OS) using Cox regression models. Results: Low PMI, PMI+ESI, and SMI significantly predicted decreased 1-year, 5-year, and OS in uni- and multivariate models. PMI+ESI and SMI were more accurate than PMI in males, and PMI and PMI+ESI were more accurate than SMI in females in the prediction of 1-year survival. However, there were no differences in accuracies between MIs in 5-year and OS prediction. Interpretation: PMI+ESI performed well overall in short-term prognostication, but there were no differences between the MIs in long-term prognostication. We recommend the use of PMI+ESI for muscle evaluation, particularly when SMI cannot be evaluated.

Abstract Land-based mitigation measures are needed to achieve climate targets. One option is the mitigation of currently high greenhouse gas (GHG) emissions of nutrient-rich drained peatland forest soils. Continuous cover forestry (CCF) has been proposed as a measure to manage this GHG emission source; however, its emission reduction potential and impact on timber production at regional and national scales have not been quantified. To quantify the potential emission reduction, we simulated four management scenarios for Finnish forests: (i) The replacement of clear-cutting by selection harvesting on nutrient-rich drained peatlands (CCF) and (ii) the current forest management regime (BAU), and both at two harvest levels, namely (i) the mean annual harvesting (2016–2018) and (ii) the maximum sustainable yield. The simulations were conducted at the stand scale with a forest simulator (MELA) coupled with a hydrological model (SpaFHy), soil C model (Yasso07) and empirical GHG exchange models. Simulations showed that the management scenario that avoided clear-cutting on nutrient-rich drained peatlands (i.e. CCF) produced approximately 1 Tg CO2 eq. higher carbon sinks annually compared with BAU at equal harvest level for Finland. This emission reduction can be attributed to the maintenance of a higher biomass sink and to the mitigation of soil emissions from nutrient-rich drained peatland sites.

Abstract Background The aim of this long-term follow-up study was to compare the disease characteristics of HLA-B27 positive and negative patients with juvenile idiopathic arthritis (JIA). Methods The study is a cohort study with consecutive cases of newly diagnosed Finnish patients with JIA according to the International League of Associations for Rheumatology (ILAR) criteria [1]. Patients were enrolled between 1997 and 2000 from a defined area of Southern Finland. Clinical data including disease activity and serology were registered during a mean period of 17.5 years. Results 159 patients completed the 18-year follow-up study. HLA-B27 was available for 151 patients, of which 25% were HLA-B27 positive. Chronic uveitis was diagnosed in 30% of HLA-B27 positive and 29% of HLA-B27 negative patients. HLA-B27 positive patients had a lower prevalence of temporomandibular (TMJ) involvement than the antigen negative ones, 19% versus 28%. None of the HLA-B27 positive patients had cervical spine affected compared to 11% of antigen negative patients (p = 0.022). Of the HLA-B27 positive patients, 54% had had biological medication at some point during follow-up versus 25% in the negative group (p = 0.003). At last follow-up, 32% of antigen positive patients were not in remission compared to 18% of the antigen negative (p = 0.017). Conclusions The use of biological medication was more common in HLA-B27 positive patients with JIA. At the 18-year follow-up, more antigen positive patients had active disease compared HLA-B27 negative patients. This real-world follow-up study indicates that the prospects for worse outcome with HLA-B27 positivity in long-term should be taken into consideration.

Objectives To identify long-term disease activity trajectories from childhood to adulthood by using the clinical Juvenile Arthritis Disease Activity Score (cJADAS10) in juvenile idiopathic arthritis (JIA). Second, to evaluate the contribution of the cJADAS10 components and explore characteristics associated with active disease at the 18-year follow-up.Methods Patients with onset of JIA in 1997–2000 were followed for 18 years in the population-based Nordic JIA cohort. We used a discrete mixture model for longitudinal clustering of the cJADAS10 and its components. We assessed factors potentially associated with higher scores on the patient’s global assessment of well-being (PaGA) by hierarchical clustering and correlation analysis.Results Four disease activity trajectories were identified based on the cJADAS10 components among 427 patients. In trajectory-group 2, the PaGA and the physician’s global assessment of disease activity (PhGA) increased significantly during the course, but not the active joint count. The increase in the PaGA was significantly higher than the increases in the PhGA and the active joint count (p

Abstract Ovarian cysts contribute to reduced reproductive performance in pigs. Unfortunately, the mechanism of lutein cysts formation remains unknown. Here, we compared the endocrine and molecular milieus of intact, healthy preovulatory follicles (PF), gonadotropin (eCG/hCG)-induced healthy and atretic-like PF, as well as gonadotropin-provoked and spontaneous ovarian cysts in gilts. Several endocrine and molecular indicators and microRNA were compared in walls of PF and cysts. Intact and healthy PF, showed high estradiol/androstendione and low progesterone levels associated with CYP17A1, HSD17B1, and CYP19A1 elevation and reduced StAR/HSD3B1 protein expression. In contrast, low estradiol/androstendione and high progesterone concentrations, accompanied by decreased CYP17A1, HSD17B1, CYP19A1 and increased HSD3B1 protein abundance, appeared in atretic-like PF, gonadotropin-induced and spontaneous cysts. High progesterone receptor (PGR) protein abundance was maintained in intact and healthy PF, while it dropped in atretic-like PF, gonadotropins-induced and spontaneous cysts. The atretic PF showed high level of TNFα compared to healthy PF. In conclusion, follicular lutein cysts could be recruited from atretic-like PF with lost estrogenic milieu and inability to ovulate. Ovulatory cascade was presumably disrupted by a low PGR and high TNFα levels associated with earlier luteinization of follicular walls. These results suggest a novel mechanism of lutein ovarian cysts development in pigs and, perhaps, other species.

Abstract Dietary fiber (DF) supplementation is one of the strategies to prevent on-farm infections; it has the capability to improve gut health and piglet performance. Among the beneficial DFs, micro-fibrillated cellulose (MFC) is a new-generation plant-derived innovative feed ingredient; MFC, originating from sugar-beet pulp, has a hyper-branched structure with the ability to form shear-thinning hydrogel and has a high water-binding capacity. We aimed to determine the effects of MFC supplementation on piglets' performance before and after weaning. We included 45 sows and their piglets in this trial and monitored the results until the piglets were 7 weeks old. Piglets supplemented with MFC had higher body weight and average daily growth (ADG) than did control piglets, both pre- and post-weaning. In addition, MFC supplementation in post-weaning piglets improved butyrate content, and reduced diarrhea incidence. These phenomena, perhaps due to the MFC supplementation at different stages until age 7 weeks. In addition, after weaning, MFC supplementation stimulated the growth of butyrate-producing bacteria such as Ruminococcus.2, Ruminococcaceae.UCG.014, Intestinibacter, Roseburia, and Oribacterium genera, as well as reduced the pathogenic bacteria, such as Campylobacter, and Escherichia. Evidently, supplementation of MFC in feed to young piglets can improve growth performance and butyric acid content and reduce post-weaning diarrhea.

Language aware schools need to be supported by language aware teacher education. In this study we analysed teacher socialisation among class teachers in Swedish immersion in Finland by qualitative content analysis of immersion teacher group discussions. We found that immersion teacher socialisation occurred mainly after entering the profession, as the participants had not participated in immersion themselves and had not attended a teacher education programme specifically designed for immersion. Based on the findings related to immersion socialisation we argue how the teacher education needs to be developed in order to better support teacher socialisation for language aware schools.

The notions of change, such as birth, death, growth, evolution and longevity, extend across reality, including biological, cultural and societal phenomena. Patterns of change describe how success and composition of every entity, from species to societies, vary across time. Languages develop into new languages, music and fashion continuously evolve, economies rise and decline, ecological and societal crises come and go. A common way to perceive and analyse change processes is through patterns of rise and decline, the ubiquitous, often distinctively unimodal trajectories describing life histories of various entities. These patterns come in different shapes and are measured according to varying definitions. Depending on how they are measured, patterns of rise and decline can reveal, emphasize, mask or obscure important dynamics in natural and cultural phenomena. Importantly, the variations of how dynamics are measured can be vast, making it impossible to directly compare patterns of rise and decline across fields of science. Standardized analysis of these patterns has the potential to uncover important but overlooked commonalities across natural phenomena and potentially help us catch the onset of dramatic shifts in entities' state, from catastrophic crashes in success to gradual emergence of new entities. We provide a framework for standardized recognizing, characterizing and comparing patterns of change by combining understanding of dynamics across fields of science. Our toolkit aims at enhancing understanding of the most general tendencies of change, through two complementary perspectives: dynamics of emergence and dynamics of success. We gather comparable cases and data from different research fields and summarize open research questions that can help us understand the universal principles, perception-biases and field-specific tendencies in patterns of rise and decline of entities in nature.

In this paper, a novel integrated SHE-NLC control is proposed for the mitigation of unwanted lower-order harmonics in the cascaded H-bridge multilevel inverter. The proposed algorithm has been developed by hybridizing the NLC and SHE methods, in an attempt to keep the merits of both the individual control. The switching angles and nearest levels are calculated by applying the Genetic Algorithm (GA). The proposed technique reduces the calculation time and implementation complexity, thus can be a viable alternative to the real time implementation for SHE. Integrated NLC-SHE control is tested by varying the modulation index and load dynamics. This technique resulted in the reduction in Total Harmonic Distortion (THDs) in load voltage and current. Comparative analysis of NLC, SHE and Integrated NLC-SHE technique is also performed on the CHB nine-level inverter. There is significant reduction in voltage and current THD values and power losses. Efficiency of the inverter is increased. The efficacy of the proposed control CHB nine-level is tested on MATLAB Simulink environment and further validated by experimental results.

Abstract Background Litter size is going up in modern pig production. Due to large litter size and increased farrowing duration, newborn piglets, during parturition, can suffer from asphyxiation. This alters their blood energy parameters and can contribute to their reduced vitality at birth, which is detrimental to their growth performance and survival. We aimed to evaluate the effects of vitality score, piglets’ umbilical cord blood lactate, glucose, and butyrate, and birth order on growth performance and the preweaning mortality of piglets. Results The more vital (vitality score 2, VS2) piglets had higher umbilical cord blood glucose and butyrate, lower blood lactate, and higher colostrum intake (CI) at birth, and showed higher body weight at birth and at weaning than did less vital piglets (vitality score 1, VS1). Umbilical cord lactate negatively correlated with vitality, colostrum intake, and growth before weaning. Among the four birth-order groups (BOGs), piglets born earlier during parturition had a higher mean vitality score than those born later. BOG1 and BOG2 had significantly higher CI (p

Vegetation phenology, which refers to the seasonal changes in plant physiology, biomass and plant cover, is affected by many abiotic factors, such as precipitation, temperature and water availability. Phenology is also associated with the carbon dioxide (CO2) exchange between ecosystems and the atmosphere. We employed digital cameras to monitor the vegetation phenology of three northern boreal peatlands during five growing seasons. We derived a greenness index (green chromatic coordinate, GCC) from the images and combined the results with measurements of CO2 flux, air temperature and high-resolution satellite data (Sentinel-2). From the digital camera images it was possible to extract greenness dynamics on the vegetation community and even species level. The highest GCC and daily maximum gross photosynthetic production (GPPmax) were observed at the site with the highest nutrient availability and richest vegetation. The short-term temperature response of GCC depended on temperature and varied among the sites and months. Although the seasonal development and year-to-year variation in GCC and GPPmax showed consistent patterns, the short-term variation in GPPmax was explained by GCC only during limited periods. GCC clearly indicated the main phases of the growing season, and peatland vegetation showed capability to fully compensate for the impaired growth resulting from a late growing season start. The GCC data derived from Sentinel-2 and digital cameras showed similar seasonal courses, but a reliable timing of different phenological phases depended upon the temporal coverage of satellite data.

Abstract Background With juvenile idiopathic arthritis (JIA), there are several protocols and practices used worldwide for the transition from paediatric to adult care. In this study, we examined the transferral rates and disease activity after transition, as well as the disease- and health-related outcomes. We also introduce the transition practices employed in the Nordic countries. Methods The study population comprised 408 participants with a disease onset from 1997 to 2000 who attended an 18-year follow-up visit in this population-based Nordic JIA cohort study. The patients were retrospectively divided into three subgroups: Patients transferred directly from paediatric care to adult rheumatology care, patients referred there later, and patients never transferred during the 18-year follow-up period. Results One hundred and sixty-three (40%) JIA patients had been directly transferred to an adult clinic. The cumulative transition rate was 52%, but there were significant differences between the participating centres. Fifty patients had later been referred to an adult clinic. Among the 195 patients who had never been transferred, 39% were found to have disease activity at the study visit. Conclusion This study highlights the need to reconsider transition practices to avoid our undesirable finding of patients with disease activity in JIA, but no appropriate health care follow-up.

BACKGROUND: Infants born preterm compared with infants born at term are at an increased risk of dying and of serious morbidities in early life, and those who survive have higher rates of neurological impairments. It remains unclear whether exposure to repeat courses of prenatal corticosteroids can reduce these risks. This individual participant data (IPD) meta-analysis (MA) assessed whether repeat prenatal corticosteroid treatment given to women at ongoing risk of preterm birth in order to benefit their infants is modified by participant or treatment factors. METHODS AND FINDINGS: Trials were eligible for inclusion if they randomised women considered at risk of preterm birth who had already received an initial, single course of prenatal corticosteroid seven or more days previously and in which corticosteroids were compared with either placebo or no placebo. The primary outcomes for the infants were serious outcome, use of respiratory support, and birth weight z-scores; for the children, they were death or any neurosensory disability; and for the women, maternal sepsis. Studies were identified using the Cochrane Pregnancy and Childbirth search strategy. Date of last search was 20 January 2015. IPD were sought from investigators with eligible trials. Risk of bias was assessed using criteria from the Cochrane Collaboration. IPD were analysed using a one-stage approach. Eleven trials, conducted between 2002 and 2010, were identified as eligible, with five trials being from the United States, two from Canada, and one each from Australia and New Zealand, Finland, India, and the United Kingdom. All 11 trials were included, with 4,857 women and 5,915 infants contributing data. The mean gestational age at trial entry for the trials was between 27.4 weeks and 30.2 weeks. There was no significant difference in the proportion of infants with a serious outcome (relative risk [RR] 0.92, 95% confidence interval [CI] 0.82 to 1.04, 5,893 infants, 11 trials, p = 0.33 for heterogeneity). There was a reduction in the use of respiratory support in infants exposed to repeat prenatal corticosteroids compared with infants not exposed (RR 0.91, 95% CI 0.85 to 0.97, 5,791 infants, 10 trials, p = 0.64 for heterogeneity). The number needed to treat (NNT) to benefit was 21 (95% CI 14 to 41) women/fetus to prevent one infant from needing respiratory support. Birth weight z-scores were lower in the repeat corticosteroid group (mean difference -0.12, 95%CI -0.18 to -0.06, 5,902 infants, 11 trials, p = 0.80 for heterogeneity). No statistically significant differences were seen for any of the primary outcomes for the child (death or any neurosensory disability) or for the woman (maternal sepsis). The treatment effect varied little by reason the woman was considered to be at risk of preterm birth, the number of fetuses in utero, the gestational age when first trial treatment course was given, or the time prior to birth that the last dose was given. Infants exposed to between 2-5 courses of repeat corticosteroids showed a reduction in both serious outcome and the use of respiratory support compared with infants exposed to only a single repeat course. However, increasing numbers of repeat courses of corticosteroids were associated with larger reductions in birth z-scores for weight, length, and head circumference. Not all trials could provide data for all of the prespecified subgroups, so this limited the power to detect differences because event rates are low for some important maternal, infant, and childhood outcomes. CONCLUSIONS: In this study, we found that repeat prenatal corticosteroids given to women at ongoing risk of preterm birth after an initial course reduced the likelihood of their infant needing respiratory support after birth and led to neonatal benefits. Body size measures at birth were lower in infants exposed to repeat prenatal corticosteroids. Our findings suggest that to provide clinical benefit with the least effect on growth, the number of repeat treatment courses should be limited to a maximum of three and the total dose to between 24 mg and 48 mg.

BackgroundInfants born preterm compared with infants born at term are at an increased risk of dying and of serious morbidities in early life, and those who survive have higher rates of neurological impairments. It remains unclear whether exposure to repeat courses of prenatal corticosteroids can reduce these risks. This individual participant data (IPD) meta-analysis (MA) assessed whether repeat prenatal corticosteroid treatment given to women at ongoing risk of preterm birth in order to benefit their infants is modified by participant or treatment factors.Methods and findingsTrials were eligible for inclusion if they randomised women considered at risk of preterm birth who had already received an initial, single course of prenatal corticosteroid seven or more days previously and in which corticosteroids were compared with either placebo or no placebo. The primary outcomes for the infants were serious outcome, use of respiratory support, and birth weight z-scores; for the children, they were death or any neurosensory disability; and for the women, maternal sepsis. Studies were identified using the Cochrane Pregnancy and Childbirth search strategy. Date of last search was 20 January 2015. IPD were sought from investigators with eligible trials. Risk of bias was assessed using criteria from the Cochrane Collaboration. IPD were analysed using a one-stage approach. Eleven trials, conducted between 2002 and 2010, were identified as eligible, with five trials being from the United States, two from Canada, and one each from Australia and New Zealand, Finland, India, and the United Kingdom. All 11 trials were included, with 4,857 women and 5,915 infants contributing data. The mean gestational age at trial entry for the trials was between 27.4 weeks and 30.2 weeks. There was no significant difference in the proportion of infants with a serious outcome (relative risk [RR] 0.92, 95% confidence interval [CI] 0.82 to 1.04, 5,893 infants, 11 trials, p = 0.33 for heterogeneity). There was a reduction in the use of respiratory support in infants exposed to repeat prenatal corticosteroids compared with infants not exposed (RR 0.91, 95% CI 0.85 to 0.97, 5,791 infants, 10 trials, p = 0.64 for heterogeneity). The number needed to treat (NNT) to benefit was 21 (95% CI 14 to 41) women/fetus to prevent one infant from needing respiratory support. Birth weight z-scores were lower in the repeat corticosteroid group (mean difference -0.12, 95%CI -0.18 to -0.06, 5,902 infants, 11 trials, p = 0.80 for heterogeneity). No statistically significant differences were seen for any of the primary outcomes for the child (death or any neurosensory disability) or for the woman (maternal sepsis). The treatment effect varied little by reason the woman was considered to be at risk of preterm birth, the number of fetuses in utero, the gestational age when first trial treatment course was given, or the time prior to birth that the last dose was given. Infants exposed to between 2-5 courses of repeat corticosteroids showed a reduction in both serious outcome and the use of respiratory support compared with infants exposed to only a single repeat course. However, increasing numbers of repeat courses of corticosteroids were associated with larger reductions in birth z-scores for weight, length, and head circumference. Not all trials could provide data for all of the prespecified subgroups, so this limited the power to detect differences because event rates are low for some important maternal, infant, and childhood outcomes.ConclusionsIn this study, we found that repeat prenatal corticosteroids given to women at ongoing risk of preterm birth after an initial course reduced the likelihood of their infant needing respiratory support after birth and led to neonatal benefits. Body size measures at birth were lower in infants exposed to repeat prenatal corticosteroids. Our findings suggest that to provide clinical benefit with the least effect on growth, the number of repeat treatment courses should be limited to a maximum of three and the total dose to between 24 mg and 48 mg.

ABSTRACT Small-scale studies investigating the relationship between pigs' intestinal microbiota and growth performance have generated inconsistent results. We hypothesized that on farms under favorable environmental conditions (e.g., promoting sow nest-building behavior, high colostrum production, low incidence of diseases and minimal use of antimicrobials), the piglet gut microbiota may develop toward a population that promotes growth and reduces pathogenic bacteria. Using 16S rRNA gene amplicon sequencing, we sampled and profiled the fecal microbiota from 170 individual piglets throughout suckling and postweaning periods (in total 670 samples) to track gut microbiota development and its potential association with growth. During the suckling period, the dominant genera were Lactobacillus and Bacteroides, the latter being gradually replaced by Clostridium sensu scricto 1 as piglets aged. The gut microbiota during the nursery stage, not the suckling period, predicted the average daily growth (ADG) of piglets. The relative abundances of SCFA-producing genera, in particular Faecalibacterium, Megasphaera, Mitsuokella, and Subdoligranulum, significantly correlated with high ADG of weaned piglets. In addition, the succession of the gut microbiota in high-ADG piglets occurred faster and stabilized sooner upon weaning, whereas the gut microbiota of low-ADG piglets continued to mature after weaning. Overall, our findings suggest that weaning is the major driver of gut microbiota variation in piglets with different levels of overall growth performance. This calls for further research to verify if promotion of specific gut microbiota, identified here at weaning transition, is beneficial for piglet growth. IMPORTANCE The relationship between pigs' intestinal microbiota and growth performance is of great importance for improving piglets’ health and reducing antimicrobial use. We found that gut microbiota variation is significantly associated with growth during weaning and the early nursery period. Importantly, transitions toward a mature gut microbiota enriched with fiber-degrading bacteria mostly complete upon weaning in piglets with better growth. Postponing the weaning age may therefore favor the development of fiber degrading gut bacteria, conferring the necessary capacity to digest and harvest solid postweaning feed. The bacterial taxa associated with piglet growth identified herein hold potential to improve piglet growth and health.

Citizen science (CS) is a growing field of participatory science, bringing together the public, researchers, organizations, and communities to participate in various scientific projects that unfold in different sociomaterial settings known as territories. While research on perceived learning in CS has recently grown, the discussion regarding the different learning approaches, territories, and the overall process as well as their associations with learning factors remains meager. In our study, we unpack three types of learning (formal, informal, and nonformal) and their respective territories in CS, and within this context, review a model of learning to synthesize the project-related and individual factors associated with the perceived learning of citizen scientists engaged in CS activities. We conducted an international survey for adults participating in CS, which was then analyzed using exploratory factor analysis (N = 596). We identified the following five factors regarding CS activities and perceived learning: sociomaterial learning, social learning, reflective learning, situational learning, and material learning. We found that perceived learning was lower for citizen scientists who participated in biology CS projects but higher among citizen scientists who participated in the long term and engaged in a variety of CS activities. Our findings highlight that the learning experiences of citizen scientists can be varied within a CS project because of the varied entanglements of project-related and individual factors, which can be better understood through a model of learning. Our findings contribute to developing further the theories and practices related to CS and CS in education.

Forest characteristics vary largely at the regional level and in smaller geographic areas in Finland. The amount of greenhouse gas emissions is related to changes in biomass and the soil type (e.g. upland soils vs. peatlands). In this paper, estimating and explaining spatial patterns of tree biomass change across Finland was the main interest. We analysed biomass changes on different soil and site types between the years 2009 and 2015 using the Finnish multi-source national forest inventory (MS-NFI) raster layers. MS-NFI method is based on combining information from satellite imagery, digital maps and national forest inventory (NFI) field data. Automatic segmentation was used to create silvicultural management and treatment units. An average biomass estimate of the segmented MS-NFI (MS–NFI–seg) map was 73.9 tons ha−1 compared to the national forest inventory estimate of 76.5 tons ha−1 in 2015. Forest soil type had a similar effect on average biomass in MS–NFI–seg and NFI data. Despite good regional and country-level results, segmentation narrowed the biomass distributions. Hence, biomass changes on segments can be considered only approximate values; also, those small differences in average biomass may accumulate when map layers from more than one time point are compared. A kappa of 0.44 was achieved for precision when comparing undisturbed and disturbed forest stands in the segmented Global Forest Change data (GFC-seg) and MS–NFI–seg map. Compared to NFI, 69% and 62% of disturbed areas were detected by GFC-seg and MS–NFI–seg, respectively. Spatially accurate map data of biomass changes on forest land improve the ability to suggest optimal management alternatives for any patch of land, e.g. in terms of climate change mitigation.

Boreal upland forests are generally considered methane (CH4) sinks due to the predominance of CH4 oxidizing bacteria over the methanogenic archaea. However, boreal upland forests can temporarily act as CH4 sources during wet seasons or years. From a landscape perspective and in annual terms, this source can be significant as weather conditions may cause flooding, which can last a considerable proportion of the active season and because often, the forest coverage within a typical boreal catchment is much higher than that of wetlands. Processes and conditions which change mineral soils from acting as a weak sink to a strong source are not well understood. We measured soil CH4 fluxes from 20 different points from regularly irrigated and control plots during two growing seasons. We also estimated potential CH4 production and oxidation rates in different soil layers and performed a laboratory experiment, where soil microcosms were subjected to different moisture levels and glucose addition simulating the fresh labile carbon (C) source from root exudates. The aim was to find the key controlling factors and conditions for boreal upland soil CH4 production. Probably due to long dry periods in both summers, we did not find occasions of CH4 production following the excess irrigation, with one exception in July 2019 with emission of 18 200 µg CH4 m−2 h−1. Otherwise, the soil was always a CH4 sink (median CH4 uptake rate of 260–290 and 150–170 µg CH4 m−2 h−1, in control and irrigated plots, respectively). The median soil CH4 uptake rates at the irrigated plot were 88 % and 50 % lower than at the control plot in 2018 and 2019, respectively. Potential CH4 production rates were highest in the organic layer (0.2–0.6 nmol CH4 g−1 d−1), but some production was also observed in the leaching layer, whereas in other soil layers, the rates were negligible. Potential CH4 oxidation rates varied mainly within 10–40 nmol CH4 g−1 d−1, except in deep soil and the organic layer in 2019, where potential oxidation rates were almost zero. The laboratory experiment revealed that high soil moisture alone does not turn upland forest soil into a CH4 source. However, a simple C source, e.g., substrates coming from root exudates with high moisture, switched the soil into a CH4 source. Our unique study provides new insights into the processes and controlling factors on CH4 production and oxidation, and the resulting net efflux that should be incorporated in process models describing global CH4 cycling.

Driven by environmental and economic aspects, the proliferation of renewable energy sources (RES) has been expanded in power systems worldwide. In this regard, the intermittent generation of such RESs (e.g., photovoltaic and wind farms) can cause several operational and stability problems in such low-inertia power systems. To handle these issues, great interest in the literature has been directed to develop feasible grid-forming voltage source converters (VSC) control schemes that have voltage/frequency regulatory functions. Accordingly, an inclusive review is presented in this paper for these promising grid-forming VSC control schemes which will be the backbone of sustainable converter-dominated power systems. Specifically, control structures, smart grid-support functionalities, stability issues, and fault current mitigations are compared considering the existing grid-forming VSC control schemes. Besides, the applications of grid-forming VSC along with their benefits and drawbacks are investigated for both isolated and bulk power systems. The evaluation aspects are also explored for assessing the performance of the existing VSC control schemes in the grid. Finally, the current challenges that face VSC in forthcoming applications and existing gaps are highlighted while corresponding perspectives for future research studies are defined for stable sustainable low-inertia power systems.

In this paper, different power balance control methods for hybrid marine vessels are analyzed. First, the power grid of a marine vessel is modeled using MATLAB and Simulink. Simulations are then performed using real power plant load data captured from an actual vessel. Isochronous control is used to control the power of the diesel gensets, and different control methods, such as isochronous control and average load power estimation, are used for the battery energy storage system. The system is simulated with different control parameters, and the effects of parameter changes are presented. It is shown that these presented control schemes can be adapted to manage the energy balance in a hybrid vessel, thereby enabling efficient use of the battery energy storage system. A diesel genset and battery energy storage system failure during a dynamic positioning operation is also simulated, and the effect of the failure on the frequency of the power grid of the vessel is presented.

BackgroundIntelligent physical robots based on artificial intelligence have been argued to bring about dramatic changes in health care services. Previous research has examined the use of intelligent physical robots in the health care context from different perspectives; however, an overview of the antecedents and consequences of intelligent physical robot use in health care is lacking in the literature. ObjectiveIn this paper, we aimed to provide an overview of the antecedents and consequences of intelligent physical robot use in health care and to propose potential agendas for future research through a systematic literature review. MethodsWe conducted a systematic literature review on intelligent physical robots in the health care field following the guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Literature searches were conducted in 5 databases (PubMed, Scopus, PsycINFO, Embase, and CINAHL) in May 2021, focusing on studies using intelligent physical robots for health care purposes. Subsequently, the quality of the included studies was assessed using the Mixed Methods Appraisal Tool. We performed an exploratory content analysis and synthesized the findings extracted from the included articles. ResultsA total of 94 research articles were included in the review. Intelligent physical robots, including mechanoid, humanoid, android, and animalistic robots, have been used in hospitals, nursing homes, mental health care centers, laboratories, and patients’ homes by both end customers and health care professionals. The antecedents for intelligent physical robot use are categorized into individual-, organization-, and robot-related factors. Intelligent physical robot use in the health care context leads to both non–health-related consequences (emotional outcomes, attitude and evaluation outcomes, and behavioral outcomes) and consequences for (physical, mental, and social) health promotion for individual users. Accordingly, an integrative framework was proposed to obtain an overview of the antecedents and consequences of intelligent physical robot use in the health care context. ConclusionsThis study contributes to the literature by summarizing current knowledge in the field of intelligent physical robot use in health care, by identifying the antecedents and the consequences of intelligent physical robot use, and by proposing potential future research agendas in the specific area based on the research findings in the literature and the identified knowledge gaps.