Flight Data Monitoring (FDM) programmes have become a key part of every major airline’s safety management system. They are primarily based on learning from unwanted deviations in flight parameters encountered during normal flight operations. Owing to its unique nature, anomaly detection of FDM presents distinct problem complexities from the majority of analytical and learning tasks. This methodology, while useful, concentrates only on a small part of the operation, leaving most of the data unprocessed, and does not allow for analysing events that had the potential to go wrong but were recovered in time by the crews. This research focused on analysing an FDM dataset of 1332 approaches between January 2018 and July 2022 at Tenerife South Airport (Spain), where there is a known phenomenon of increasing headwinds during the final approach. The flights were clustered using self-organising maps (SOM) by patterns of increasing headwinds, and the clusters were assessed in terms of clustering performance. The clusters were well differentiated. A further comparison between the results from the airline showed that 88 flights were affected by wind shifts, while 27 flights were picked up by the airline. The results demonstrate that SOMs are a meaningful tool for clustering flight data and can complement the current FDM analysis methodology. Combining both methodologies could shift FDM data analysis to look beyond exceedances into what went well, thus shifting the FDM paradigm towards a more safety-II-based method.

Cognates are studied in many psychological studies of bilingual language processing. Despite their frequent use, there is no clear operationalized definition of what constitutes a cognate. We conducted a literature search in three major journals to better understand how cognate status is typically defined and operationalized. In these journals, we analyzed similarity of cognate and non-cognate stimuli. We found that approximately 60% of the reviewed studies operationalized cognate status empirically. Stimulus analyses revealed a similarity continuum between cognates and non-cognates without a consistent cut-off. Based on these results, we make recommendations for future research.

This paper explores the role that sensitively portrayed literary representations of hallucinations and dissociation may have in counteracting stigma associated with these experiences. In it, we focus on narratives of young people experiencing hallucinatory and dissociative phenomena in two award-winning, young adult novels: How It Feels to Float by Helena Fox and A Monster Calls by Patrick Ness. We identify and discuss three literary devices in these two novels that promote empathy for the characters and their experiences. The narrative accounts in both novels challenge conceptions of hallucinations and dissociation as unknowable and unrelatable experiences with their empathic portrayals of relatable characters that create comprehensible accounts of adolescents grappling with their sense of reality. Importantly, they highlight the potential role that literature can play in stigma reduction by positively shaping young peoples’ understandings of unfamiliar mental health experiences.

Effect chain modeling approaches are applied to model cause-effect relations and analyze affected elements and dependencies. In this paper a systematic literature research is conducted to derive main characteristics and limitations of existing approaches. Then, the Model-based Effect Chain Analysis (MECA) method is introduced. Evaluation proves applicability of the method by means of a case example. This is done in the context of a project with a German automotive company. In the project 66 workshops were conducted to model certification-compliant effect chains in accordance to the UN ECE 156.

Climate warming is occurring most rapidly in the Arctic, which is both a sentinel and a driver of further global change. Ecosystems and human societies are already affected by warming. Permafrost thaws and species are on the move, bringing pathogens and vectors to virgin areas. During a five-year project, the CLINF – a Nordic Center of Excellence, funded by the Nordic Council of Ministers, has worked with the One Health concept, integrating environmental data with human and animal disease data in predictive models and creating maps of dynamic processes affecting the spread of infectious diseases. It is shown that tularemia outbreaks can be predicted even at a regional level with a manageable level of uncertainty. To decrease uncertainty, rapid development of new and harmonised technologies and databases is needed from currently highly heterogeneous data sources. A major source of uncertainty for the future of contaminants and infectious diseases in the Arctic, however, is associated with which paths the majority of the globe chooses to follow in the future. Diplomacy is one of the most powerful tools Arctic nations have to influence these choices of other nations, supported by Arctic science and One Health approaches that recognise the interconnection between people, animals, plants and their shared environment at the local, regional, national and global levels as essential for achieving a sustainable development for both the Arctic and the globe.

Prebiotic supplements and high-protein (HP) diets reduce body weight and modulate intestinal microbiota. Our aim was to elucidate the combined effect of an inulin/oligofructose (FOS) and HP diet on body weight gain, energy metabolism and faecal microbiota. Forty male C57BL/6NCrl mice were fed a control (C) diet for 2 weeks and allocated to a C or HP (40 % protein) diet including no or 10 % inulin/FOS (C + I and HP + I) for 4 weeks. Inulin/FOS was added in place of starch and cellulose. Body weight, food intake, faecal energy and nitrogen were determined. Indirect calorimetry and faecal microbiota analysis were performed after 3 weeks on diets. Body weight gain of HP-fed mice was 36 % lower than HP + I- and C-fed mice (P < 0⋅05). Diet digestibility and food conversion efficiency were higher in HP + I- than HP-fed mice (P < 0⋅01), while food intake was comparable between groups. Total energy expenditure (heat production) was 25 % lower in HP + I- than in C-, HP- and C + I-fed mice (P < 0⋅001). Carbohydrate oxidation tended to be 24 % higher in HP- than in HP + I-fed mice (P < 0⋅05). Faecal nitrogen excretion was 31–45 % lower in C-, C + I- and HP + I- than in HP-fed mice (P < 0⋅05). Faecal Bacteroides–Prevotella DNA was 2⋅3-fold higher in C + I- and HP + I- relative to C-fed mice (P < 0⋅05), but Clostridium leptum DNA abundances was 79 % lower in HP + I- than in HP-fed mice (P < 0⋅05). We suggest that the higher conversion efficiency of dietary energy of HP + I but not C + I-fed mice is caused by higher digestibility and lower heat production, resulting in increased body mass.

Neonatal sepsis is a major cause of death and disability in newborns. Commonly used biomarkers for diagnosis and evaluation of treatment response lack sufficient sensitivity or specificity. Additionally, new targets to treat the dysregulated immune response are needed, as are methods to effectively screen drugs for these targets. Available research methods have hitherto not yielded the breakthroughs required to significantly improve disease outcomes, we therefore describe the potential of zebrafish (Danio rerio) larvae as preclinical model for neonatal sepsis. In biomedical research, zebrafish larvae combine the complexity of a whole organism with the convenience and high-throughput potential of in vitro methods. This paper illustrates that zebrafish exhibit an immune system that is remarkably similar to humans, both in terms of types of immune cells and signaling pathways. Moreover, the developmental state of the larval immune system is highly similar to human neonates. We provide examples of zebrafish larvae being used to study infections with pathogens commonly causing neonatal sepsis and discuss known limitations. We believe this species could expedite research into immune regulation during neonatal sepsis and may hold keys for the discovery of new biomarkers and novel treatment targets as well as for screening of targeted drug therapies.

Feeding management of the postnatal and preweaning calf has an important impact on calf growth and development during this critical period and affects the health and well-being of the calves. After birth, an immediate and sufficient colostrum supply is a prerequisite for successful calf rearing. Colostrum provides high amounts of nutrient as well as non-nutrient factors that promote the immune system and intestinal maturation of the calf. The maturation and function of the neonatal intestine enable the calf to digest and absorb the nutrients provided by colostrum and milk. Therefore, colostrum intake supports the start of anabolic processes in several tissues, stimulating postnatal body growth and organ development. After the colostrum feeding period, an intensive milk feeding protocol, that is, at least 20% of BW milk intake/day, is required to realise the calf potential for growth and organ development during the preweaning period. Insufficient milk intake delays postnatal growth and may have detrimental effects on organ development, for example, the intestine and the mammary gland. The somatotropic axis as the main postnatal endocrine regulatory system for body growth is stimulated by the intake of high amounts of colostrum and milk and indicates the promotion of anabolic metabolism in calves. The development of the forestomach is an important issue during the preweaning period in calves, and forestomach maturation is best achieved by solid feed intake. Unfortunately, intensive milk-feeding programmes compromise solid feed intake during the first weeks of life. In the more natural situation for beef calves, when milk and solid feed intake occurs at the same time, calves benefit from the high milk intake as evidenced by enhanced body growth and organ maturation without impaired forestomach development during weaning. To realise an intensive milk-feeding programme, it is recommended that the weaning process should not start too early and that solid feed intake should be at a high extent despite intensive milk feeding. A feeding concept based on intensive milk feeding prevents hunger and abnormal behaviour of the calves and fits the principles of animal welfare during preweaning calf rearing. Studies on milk performance in dairy cows indicate that feeding management during early calf rearing influences lifetime performance. Therefore, an intensive milk-feeding programme affects immediate as well as long-term performance, probably by programming metabolic pathways during the preweaning period.

We derive the surface and basal radar reflectance and backscatter coefficients of the southern McMurdo Ice Shelf (SMIS) and part of the nearby Ross Ice Shelf (RIS), Antarctica, from radar statistical reconnaissance using a 60-MHZ airborne survey. The surface coefficients are further inverted in terms of snow density and roughness, providing a spatial distribution of the processes contributing to the surface boundary conditions. We disentangle the basal coefficients from surface transmission losses, and we provide the basal coherent content, an indicator of the boundary geometric disorder that is also self-corrected from englacial attenuation. The basal radar properties exhibit sharp gradients along specific iso-depths, suggesting an abrupt modification of the ice composition and geometric structure. We interpret this behavior as locations where the pressure-melting point is reached, outlining fields of freezing and melting ice. Basal steps are observed at both SMIS and RIS, suggesting a common geometric expression of widespread basal processes. This technique offers a simultaneous view of both the surface and basal boundary conditions to help investigate the ice-shelf stability, while its application to airborne data significantly improves coverage of the difficult-to-observe ice–ocean boundary. It also provides constraints on thermohaline circulation in ice shelves cavities, which are analogs for ice-covered ocean worlds.

Identifying options for the sustainable intensification of cropping systems in southern Africa under prevailing high climate risk is needed. With this in mind, we tested an intercropping system that combined the staple crop maize with lablab, a local but underutilised legume. Grain and biomass productivity was determined for four variants (i) sole maize (sole-maize), (ii) sole lablab (sole-lablab), (iii) maize/lablab with both crops sown simultaneously (intercropped-SP) and (iv) maize/lablab with lablab sown 28 days after the maize crop (intercropped-DP). Soil water and weather data were monitored and evaluated. The trial was conducted for two seasons (2015/2016 and 2016/2017) at two sites in the Limpopo Province, South Africa: Univen (847 mm rainfall, 29.2 °C maximum and 18.9 °C minimum temperature average for the cropping season over the years 2008–2017) and Syferkuil (491 mm rainfall, with 27.0 °C maximum and 14.8 °C minimum temperature). Analysis revealed three key results: The treatment with intercropped-SP had significantly lower maize yields (2320 kg ha−1) compared with maize in intercropped-DP (2865 kg ha−1) or sole-maize (2623 kg ha−1). As expected, maize yields in the El Niño affected in season 2015/2016 were on average 1688 kg ha−1 lower than in 2016/2017. Maize yields were significantly lower (957 kg ha−1) at Univen, the warmer site with higher rainfall, than at Syferkuil. In 2015/2016, maximum temperature at Univen exceeded 40 °C around anthesis. Furthermore, soil water was close to the estimated permanent wilting point (PWP) for most of the cropping season, which indicates possible water limitations. In Syferkuil, the soil water was maintained well above PWP. Lablab yields were low, around 500 ha−1, but stable as they were not affected by treatment across season and site. Overall, the study demonstrated that intercropped-DP appears to use available soil water more efficiently than sole maize. Intercropped-DP could therefore be considered as an option for sustainable intensification under high climate risk and resource-limited conditions for smallholders in southern Africa.

We compare refined data sets for Atlantic benthic foraminiferal oxygen isotope ratios and for North American mammalian diversity, faunal turnover, and body mass distributions. Each data set spans the late Paleocene through Pleistocene and has temporal resolution of 1.0 m.y.; the mammal data are restricted to western North America. We use the isotope data to compute five separate time series: oxygen isotope ratios at the midpoint of each 1.0-m.y. bin; changes in these ratios across bins; absolute values of these changes (= isotopic volatility); standard deviations of multiple isotope measurements within each bin; and standard deviations that have been detrended and corrected for serial correlation. For the mammals, we compute 12 different variables: standing diversity at the start of each bin; per-lineage origination and extinction rates; total turnover; net diversification; the absolute value of net diversification (= diversification volatility); change in proportional representation of major orders, as measured by a simple index and by a G-statistic; and the mean, standard deviation, skewness, and kurtosis of body mass. Simple and liberal statistical analyses fail to show any consistent relationship between any two isotope and mammalian time series, other than some unavoidable correlations between a few untransformed, highly autocorrelated time series like the raw isotope and mean body mass curves. Standard methods of detrending and differencing remove these correlations. Some of the major climate shifts indicated by oxygen isotope records do correspond to major ecological and evolutionary transitions in the mammalian biota, but the nature of these correspondences is unpredictable, and several other such transitions occur at times of relatively little global climate change. We conclude that given currently available climate records, we cannot show that the impact of climate change on the broad patterns of mammalian evolution involves linear forcings; instead, we see only the relatively unpredictable effects of a few major events. Over the scale of the whole Cenozoic, intrinsic, biotic factors like logistic diversity dynamics and within-lineage evolutionary trends seem to be far more important.

Excessive mobilization of body reserves during the transition from pregnancy to lactation imposes a risk for metabolic diseases on dairy cows. We aimed to establish an experimental model for high v. normal mobilization and herein characterized performance, metabolic and endocrine changes from 7 weeks antepartum (a.p.) to 12 weeks postpartum (p.p.). Fifteen weeks a.p., 38 pregnant multiparous Holstein cows were allocated to two groups that were fed differently to reach either high or normal body condition scores (HBCS: 7.2 NEL MJ/kg dry matter (DM); NBCS: 6.8 NEL MJ/kg DM) at dry-off. Allocation was also based on differences in body condition score (BCS) in the previous and the ongoing lactation that was further promoted by feeding to reach the targeted BCS and back fat thickness (BFT) at dry-off (HBCS: >3.75 and >1.4 cm; NBCS: <3.5 and <1.2 cm). Thereafter, both groups were fed identical diets. Blood samples were drawn weekly from 7 weeks a.p. to 12 weeks p.p. to assess the serum concentrations of metabolites and hormones. The HBCS cows had greater BCS, BFT and BW than the NBCS cows throughout the study and lost more than twice as much BFT during the first 7 weeks p.p. compared with NCBS. Milk yield and composition were not different between groups, except that lactose concentrations were greater in NBSC than in HBCS. Feed intake was also greater in NBCS, and NBCS also reached a positive energy balance earlier than HBCS. The greater reduction in body mass in HBCS was accompanied by greater concentrations of non-esterified fatty acids, and β-hydroxybutyrate in serum after calving than in NBCS, indicating increased lipomobilization and ketogenesis. The mean concentrations of insulin across all time-points were greater in HBCS than in NBCS. In both groups, insulin and IGF-1 concentrations were lower p.p than in a.p. Greater free thyroxine (fT4) concentrations and a lower free 3-3′-5-triiodothyronine (fT3)/fT4 ratio were observed in HBCS than in NBCS a.p., whereas p.p. fT3/fT4 ratio followed a reverse pattern. The variables indicative for oxidative status had characteristic time courses; group differences were limited to greater plasma ferric reducing ability values in NBSC. The results demonstrate that the combination of pre-selection according to BCS and differential feeding before dry-off to promote the difference was successful in obtaining cows that differ in the intensity of mobilizing body reserves. The HBCS cows were metabolically challenged due to intense mobilization of body fat, associated with reduced early lactation dry matter intake and compromised antioxidative capacity.

Tail lesions caused by tail biting are a widespread welfare issue in pig husbandry. Determining their prevalence currently involves labour intensive, subjective scoring methods. Increased societal interest in tail lesions requires fast, reliable and cheap systems for assessing tail status. In the present study, we aimed to test the reliability of neural networks for assessing tail pictures from carcasses against trained human observers. Three trained observers scored tail lesions from automatically recorded pictures of 13 124 pigs. Nearly all pigs had been tail docked. Tail lesions were classified using a 4-point score (0=no lesion, to 3=severe lesion). In addition, total tail loss was recorded. Agreement between observers was tested prior and during the assessment in a total of seven inter-observer tests with 80 pictures each. We calculated agreement between observer pairs as exact agreement (%) and prevalence-adjusted bias-adjusted κ (PABAK; value 1=optimal agreement). Out of the 13 124 scored pictures, we used 80% for training and 20% for validating our neural networks. As the position of the tail in the pictures varied (high, low, left, right), we first trained a part detection network to find the tail in the picture and select a rectangular part of the picture which includes the tail. We then trained a classification network to categorise tail lesion severity using pictures scored by human observers whereby the classification network only analysed the selected picture parts. Median exact agreement between the three observers was 80% for tail lesions and 94% for tail loss. Median PABAK for tail lesions and loss were 0.75 and 0.87, respectively. The agreement between classification by the neural network and human observers was 74% for tail lesions and 95% for tail loss. In other words, the agreement between the networks and human observers were very similar to the agreement between human observers. The main reason for disagreement between observers and thereby higher variation in network training material were picture quality issues. Therefore, we expect even better results for neural network application to tail lesions if training is based on high quality pictures. Very reliable and repeatable tail lesion assessment from pictures would allow automated tail classification of all pigs slaughtered, which is something that some animal welfare labels would like to do.