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This paper draws from the experience of the 3-year, Horizon 2020 project, AI4PublicPolicy, and examines the essential actions public municipalities should take to adequately prepare for the integration of Artificial Intelligence (AI) into their policy making processes under the scope of the five pilot cities involved in the project. The study explores a range of issues including organisational, technological, and ethical aspects. It also underlines the importance to understand local environments, involve stakeholders, evaluate the relevance and the availability of the data, assess the technological readiness, improve internal capacities and assure legal and ethical compliance. In order to promote transparency and cultivate public trust, the document also emphasizes the significance of elaborating on user-centric, agile and stable AI-based tools and solutions, such as dashboards of Explainable AI (XAI) services. Municipalities may pave their way towards automated, transparent and citizen-centric development of public policies by handling the challenges of AI deployment with the help of the current framework.

Fire is an integral ecosystem process and a major natural source of vegetation disturbance globally. Yet at the same time, humans use and manage fire in diverse ways and for a huge range of purposes. Therefore, it is perhaps unsurprising that a central finding of the first Fire Model Intercomparison Project was simplistic representation of humans is a substantial shortcoming in the fire modules of dynamic global vegetation models (DGVMs). In response to this challenge, we present a novel, global geospatial model that seeks to capture the diversity of human–fire interactions. Empirically grounded with a global database of anthropogenic fire impacts, WHAM! (the Wildfire Human Agency Model) represents the underlying behavioural and land system drivers of human approaches to fire management and their impact on fire regimes. WHAM! is designed to be coupled with DGVMs (JULES-INFERNO in the current instance), such that human and biophysical drivers of fire on Earth, and their interactions, can be captured in process-based models for the first time. Initial outputs from WHAM! presented here are in line with previous evidence suggesting managed anthropogenic fire use is decreasing globally and point to land use intensification as the underlying reason for this phenomenon.

The nonlinear dependence of the mean-squared displacement (MSD) on time is a common characteristic of particle transport in complex environments. Frequently, this anomalous behavior only occurs transiently before the particle reaches a terminal Fickian diffusion. This study shows that a system of hierarchically coupled Ornstein–Uhlenbeck equations is able to describe both transient subdiffusion and transient superdiffusion dynamics, as well as their sequential combinations. To validate the model, five distinct experimental, molecular dynamics simulation, and theoretical studies are successfully described by the model. The comparison includes the transport of particles in random optical fields, supercooled liquids, bedrock, soft colloidal suspensions, and phonons in solids. The model’s broad applicability makes it a convenient tool for interpreting the MSD profiles of particles exhibiting transient anomalous diffusion.

This study aimed to investigate the effects of a polyphenolic phytogenic feed additive (PFA) based on plant extracts, such as Embelia officinalis, Ocimum sanctum and nut fibre, on the redox status, haematological parameters, and piglet mortality in sows. A total of 64 primiparous sows were divided into two groups: T1-control group: regular gestation (GF) and lactation feed (LF), T2 group: regular GF and LF supplemented with a PFA (10 g daily) for 14 days before and 7 days after the farrowing. Blood samples were collected 0–3 h after farrowing. Haematological parameters (Packed Cell Volume/PCV, White Blood Cells/WBC, Platelets/PLTs) were counted in blood smears. Thiobarbituric acid reactive substances (TBARS) and protein carbonyls (CARBS) levels were determined in sow plasma. The performance and reproductive parameters of sows at farrowing and weaning days were recorded. The mean numbers of PCV and PLT counts in the T2 group were higher in comparison to the T1 group (p = 0.041, p = 0.033, respectively). In contrast, the mean numbers of WBC and neutrophils were almost significantly higher in the T2 group (p = 0.051). The mean number of stillborn piglets was significantly higher in the T1 group (2.12) compared to the T2 group (1.03). The mean number of alive piglets 24 h after farrowing and the mean number of the weaned piglets were significantly higher in group T2 (13.9 vs. 15.4 and 12.6 vs. 14.3). Sows in group T2 had significantly more backfat at weaning than the sows in group T1 (13.3 vs. 12.7). The mean levels of CARBS (nmol/mL) and TBARS (μmol/L) in group T1 (24.8 and 18.7) were significantly higher in comparison to group T2 (18.3 and 14.9). In conclusion, the use of a polyphenolic PFA in sows has beneficial effects on their welfare and performance due to its antioxidative effects. Furthermore, PFAs appear to exert antithrombotic, anti-inflammatory, and protective effects on PLTs, WBCs, and RBCs, respectively.

Peat fires in the northern high latitudes have the potential to burn vast amounts of carbon-rich organic soil, releasing large quantities of long-term stored carbon to the atmosphere. Due to anthropogenic activities and climate change, peat fires are increasing in frequency and intensity across the high latitudes. However, at present they are not explicitly included in most fire models. Here we detail the development of INFERNO-peat, the first parameterization of peat fires in the JULES-INFERNO (Joint UK Land Environment Simulator INteractive Fire and Emission algoRithm for Natural envirOnments) fire model. INFERNO-peat utilizes knowledge from lab and field-based studies on peat fire ignition and spread to be able to model peat burnt area, burn depth, and carbon emissions, based on data of the moisture content, inorganic content, bulk density, soil temperature, and water table depth of peat. INFERNO-peat improves the representation of burnt area in the high latitudes, with peat fires simulating on average an additional 0.305×106 km2 of burn area each year, emitting 224.10 Tg of carbon. Compared to Global Fire Emissions Database version 5 (GFED5), INFERNO-peat captures ∼ 20 % more burnt area, whereas INFERNO underestimated burning by 50 %. Additionally, INFERNO-peat substantially improves the representation of interannual variability in burnt area and subsequent carbon emissions across the high latitudes. The coefficient of variation in carbon emissions is increased from 0.071 in INFERNO to 0.127 in INFERNO-peat, an almost 80 % increase. Therefore, explicitly modelling peat fires shows a substantial improvement in the fire modelling capabilities of JULES-INFERNO, highlighting the importance of representing peatland systems in fire models.

The aim of this research was to investigate the influence of a foliar fertilization program, consisted of the BUD 14 nitrogen-calcium commercial formulation (N: 14% w/w, CaO: 5.5% w/w) as a biostimulant, on bud development percentage, flowering rate, classification of flowers into open, closed and triple, flower and pollen quality traits, fruit quality attributes, and leaf nutritional status of the ‘Hayward’ kiwifruit cultivar. The study was realized during a two-year experimental period in Naoussa, Central Macedonia, Greece. The results showed that BUD 14 induced synchronization in bud development relative to different vegetative stages including initiation of bud expansion, appearance of leaf apices covered by hair and deployment of 2-8 leaves and increased the flowering rate of open flowers. Pedicel length, ovary fresh weight, and dry weight, dry matter and length in female flowers as well as maximum pollen grain diameter and area in polar view in male flowers were significantly enhanced in the BUD 14 treatment. Fruit quality characteristics like average weight and dry mass were significantly augmented, and a 1.5-fold and 2-fold increase was recorded in canes length and number of kiwifruits per cane. In addition, leaf nutrient Ca and Mg concentrations were significantly enhanced, compared to the control. The efficacy of BUD 14 as a more target-oriented and environmentally friendly alternative method of supplying plants with smaller and controlled amounts of nutrients for breaking bud dormancy and improving their development was demonstrated, enhancing flower and fruit quality, leaf nutrition, kiwifruit developmental characteristics, and finally the total production per fruit per tree.

The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.

Future African aerosol emissions, and therefore air pollution levels and health outcomes, are uncertain and understudied. Understanding the future health impacts of pollutant emissions from this region is crucial. Here, this research gap is addressed by studying the range in the future health impacts of aerosol emissions from Africa in the Shared Socioeconomic Pathway (SSP) scenarios, using the UK Earth System Model version 1 (UKESM1), along with human health concentration–response functions. The effects of Africa following a high-pollution aerosol pathway are studied relative to a low-pollution control, with experiments varying aerosol emissions from industry and biomass burning. Using present-day demographics, annual deaths within Africa attributable to ambient particulate matter are estimated to be lower by 150 000 (5th–95th confidence interval of 67 000–234 000) under stronger African aerosol mitigation by 2090, while those attributable to O3 are lower by 15 000 (5th–95th confidence interval of 9000–21 000). The particulate matter health benefits are realised predominantly within Africa, with the O3-driven benefits being more widespread – though still concentrated in Africa – due to the longer atmospheric lifetime of O3. These results demonstrate the important health co-benefits from future emission mitigation in Africa.

Objective: The aim of this study was to explore the range of experiences encountered by parents and caretakers of children with autism spectrum disorder. Materials and methods: An inductive conventional content analysis approach was utilized for this study. Twenty-four (N = 24) parent responses to open-ended questions about their experience parenting a child with autism spectrum disorder were analyzed. Results: Based on content analysis of responses, five main categories emerged: emotional distress, growth and role change, perspective change, support or the need for support, and family strain. Within the main categories, 20 subcategories were identified. Conclusion: Findings from this study show that families and caretakers of children with autism spectrum disorder endorse many emotions and complex experiences, both positive and negative. The implications from these data are great and include the need for support and resources for families impacted by autism spectrum disorder.

Subacute rumen acidosis (SARA) is a current issue in intensive livestock farming, and it is particularly associated with feeding high-concentrate diets. This study investigated the prevalence and impact of SARA in forty-two Greek dairy sheep flocks by recording rumen pH, milk composition, and milk yield over a period of nine months. Moreover, it explored the use of computerized rumen colorimetry as a management and diagnostic tool for SARA in dairy sheep. In culled ewes, computerized rumen mucosal colorimetry was applied, and rumen wall samples taken for histological examination. SARA cases were identified in 19 farms (45%, n = 42). Farms with SARA cases had lower milk fat levels, while milk yield and milk protein levels did not differ based on the SARA status of the farms. In culled ewes, rumen color was significantly associated with the flock’s SARA status, and affected ewes showed increased thickness in non-keratinized and total epithelial layers. It was concluded that computerized rumen mucosal colorimetry in aged, culled ewes shows promise as an indicator, post mortem, of SARA present in dairy sheep flocks whose impact can be minimized by making significant changes in dietary management.

An outbreak of acute mastitis was investigated in a dairy sheep farm in Central Greece with a prevalence of 8.2%. Two animals were examined with symptoms of hyperacute inflammation in one of the two mammary glands. Affected glands presented swollen to grossly enlarged, warm and painful. In both animals, haematological examination revealed mild anaemia, increased leucocyte counts with mature neutropaenia and left shift, and marked thrombocytosis. Bacteriological examinations of mammary gland secretion yielded heavy growth of Streptococcus dysgalactiae and Escherichia coli from each of the two animals, respectively. Serological examination revealed a high percentage of positive samples for small ruminant lentivirus infection in both animals. The somatic cell count in the bulk-tank milk was 0.65 × 106 cells/mL. The housing conditions were inadequate with high levels of ammonia, intense stocking and muddy bedding. This pathological condition in nulliparous ewes was attributed to the extensive oedema of mammary gland and teat, the relaxation of immunity during the peri-parturient period and the heavily contaminated environment. These findings are in general agreement with corresponding incidents in heifers. Following our instructions for improving housing conditions, no other similar incidents were recorded.

Waddington envisioned stem cell differentiation as a marble rolling down a hill, passing through hierarchically branched valleys representing the cell’s temporal state. The terminal valleys at the bottom of the hill indicate the possible committed cells of the multicellular organism. Although originally proposed as a metaphor, Waddington’s hypothesis establishes the fundamental principles for characterizing the differentiation process as a dynamic system: the generated equilibrium points must exhibit hierarchical branching, robustness to perturbations (homeorhesis), and produce the appropriate number of cells for each cell type. This article aims to capture these characteristics using a mathematical model based on two fundamental hypotheses. First, it is assumed that the gene regulatory network consists of hierarchically coupled subnetworks of genes (modules), each modeled as a dynamical system exhibiting supercritical pitchfork or cusp bifurcation. Second, the gene modules are spatiotemporally regulated by feedback mechanisms originating from epigenetic factors. Analytical and numerical results show that the proposed model exhibits self-organized multistability with hierarchical branching. Moreover, these branches of equilibrium points are robust to perturbations, and the number of different cells produced can be determined by the system parameters.

This study aimed to review recent developments in the agri-food industry, focusing on the integration of innovative digital systems into the livestock industry. Over the last 50 years, the production of animal-based foods has increased significantly due to the rising demand for meat. As a result, farms have increased their livestock numbers to meet consumer demand, which has exacerbated challenges related to environmental sustainability, human health, and animal welfare. In response to these challenges, precision livestock farming (PLF) technologies have emerged as a promising solution for sustainable livestock production. PLF technologies offer farmers the opportunity to increase efficiency while mitigating environmental impact, securing livelihoods, and promoting animal health and welfare. However, the adoption of PLF technologies poses several challenges for farmers and raises animal welfare concerns. Additionally, the existing legal framework for the use of PLF technologies is discussed. In summary, further research is needed to advance the scientific understanding of PLF technologies, and stakeholders, including researchers, policymakers, and funders, need to prioritize ethical considerations related to their implementation.

The potential future trend in African aerosol emissions is uncertain, with a large range found in future scenarios used to drive climate projections. The future climate impact of these emissions is therefore uncertain. Using the Shared Socioeconomic Pathway (SSP) scenarios, transient future experiments were performed with the UK Earth System Model (UKESM1) to investigate the effect of African emissions following the high emission SSP370 scenario as the rest of the world follows the more sustainable SSP119, relative to a global SSP119 control. This isolates the effect of Africa following a relatively more polluted future emissions pathway. Compared to SSP119, SSP370 projects higher non-biomass-burning (non-BB) aerosol emissions, but lower biomass burning emissions, over Africa. Increased shortwave (SW) absorption by black carbon aerosol leads to a global warming, but the reduction in the local incident surface radiation close to the emissions is larger, causing a local cooling effect. The local cooling persists even when including the higher African CO2 emissions under SSP370 than SSP119. The global warming is significantly higher by 0.07 K when including the non-BB aerosol increases and higher still (0.22 K) when including all aerosols and CO2. Precipitation also exhibits complex changes. Northward shifts in the Inter-tropical Convergence Zone (ITCZ) occur under relatively warm Northern Hemisphere land, and local rainfall is enhanced due to mid-tropospheric instability from black carbon absorption. These results highlight the importance of future African aerosol emissions for regional and global climate and the spatial complexity of this climate influence.

An equatorward shift in the Asian Westerly Jet Stream attributable to high levels of anthropogenic sulfate aerosol in South and East Asia favours the moisture supply from low-latitudes and moisture flux convergence over arid Central Asia, according to multi-model data analysis.

The aim of this in vivo study was to investigate the effects of a novel mycotoxin detoxifier whose formulation includes clay (bentonite and sepiolite), phytogenic feed additives (curcumin and silymarin) and postbiotics (yeast products) on the health, performance and redox status of weaned piglets under the dietary challenge of fumonisins (FUMs). The study was conducted in duplicate in the course of two independent trials on two different farms. One hundred and fifty (150) weaned piglets per trial farm were allocated into two separate groups: (a) T1 (control group): 75 weaned piglets received FUM-contaminated feed and (b) T2 (experimental group): 75 weaned piglets received FUM-contaminated feed with the mycotoxin-detoxifying agent from the day of weaning (28 days) until 70 days of age. Thiobarbituric acid reactive substances (TBARSs), protein carbonyls (CARBs) and the overall antioxidant capacity (TAC) were assessed in plasma as indicators of redox status at 45 and 70 days of age. Furthermore, mortality and performance parameters were recorded at 28, 45 and 70 days of age, while histopathological examination was performed at the end of the trial period (day 70). The results of the present study reveal the beneficial effects of supplementing a novel mycotoxin detoxifier in the diets of weaners, including improved redox status, potential hepatoprotective properties and enhanced growth performance.

Wildfires are significant contributors to atmospheric gases and aerosols, impacting air quality and composition. This pollution from fires also affects radiative forcing, influencing short‐term weather patterns and climate dynamics. Our research employs the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) to investigate the repercussions of wildfires on aerosol abundances and associated immediate weather responses. We examine the summer season of 2021, a period marked by severe wildfire events in the country during a heatwave period. We conducted sensitivity experiments including and excluding wildfire emissions to measure their effects on aerosol optical depth (AOD), radiative forcing, and weather features such as temperature, humidity, clouds, and atmospheric circulation. Our findings demonstrate that the radiative impacts of wildfires negatively influence the local temperature over the fire smoke plume‐affected areas. Conversely, neighbouring areas of continental Greece experience increases in temperature due to remote effects of wildfire emissions, caused by meteorological feedbacks that reduce atmospheric humidity. Crucially, including fire emissions significantly improves the simulated surface temperatures predicted by the model over the Greek domain. Our work demonstrates that wildfire‐generated aerosols can significantly impact weather conditions and highlights the importance of including both local radiative effects and remote feedback for achieving more accurate weather prediction. [ABSTRACT FROM AUTHOR]

Measurement(s) Climate response Technology Type(s) Climate models Sample Characteristic - Environment The climate system

Background : Chronic Neck Pain (CNP) is one of the main contributing factors to disability in people of working age. Objectives: The aim of this randomized clinical trial was to compare the efficacy between acupuncture and joint mobilization on pain and disability in patients with CNP. Methods : The study involved 45 men and women with CNP, divided into three groups of 15 each. The first group followed a manual therapy protocol with joint mobilization for eight weeks three times per week. The second group followed an acupuncture protocol of equal duration and frequency, while the third group did not follow any treatment. Pain with the Visual Analog Scale (VAS) for pain and functional limitations with the Neck Disability Index (NDI) questionnaire were assessed before and after an 8-week intervention. Analysis of variance was applied while post-hoc comparisons were made to determine the differences among the groups at each time of measurement. Results : Both intervention groups showed statistically significant differences compared to the control group after the end of the intervention in both the VAS and the NDI scores (p< .001). Furthermore, the acupuncture group showed a statistically significant improvement compared to the joint mobilization team after the end of the intervention in the VAS score (p< .001) and the NDI score (p< .05). Conclusion : Both joint mobilization and acupuncture appear to be effective interventions in reducing pain and improving functional ability in people with CNP. However, acupuncture appears to have a greater analgesic effect than joint mobilization.

Fire constitutes a key process in the Earth system (ES), being driven by climate as well as affecting the climate by changing atmospheric composition and impacting the terrestrial carbon cycle. However, studies on the effects of fires on atmospheric composition, radiative forcing and climate have been limited to date, as the current generation of ES models (ESMs) does not include fully atmosphere–composition–vegetation coupled fires feedbacks. The aim of this work is to develop and evaluate a fully coupled fire–composition–climate ES model. For this, the INteractive Fires and Emissions algoRithm for Natural envirOnments (INFERNO) fire model is coupled to the atmosphere-only configuration of the UK's Earth System Model (UKESM1). This fire–atmosphere interaction through atmospheric chemistry and aerosols allows for fire emissions to influence radiation, clouds and generally weather, which can consequently influence the meteorological drivers of fire. Additionally, INFERNO is updated based on recent developments in the literature to improve the representation of human and/or economic factors in the anthropogenic ignition and suppression of fire. This work presents an assessment of the effects of interactive fire coupling on atmospheric composition and climate compared to the standard UKESM1 configuration that uses prescribed fire emissions. Results show a similar performance when using the fire–atmosphere coupling (the “online” version of the model) when compared to the offline UKESM1 that uses prescribed fire. The model can reproduce observed present-day global fire emissions of carbon monoxide (CO) and aerosols, despite underestimating the global average burnt area. However, at a regional scale, there is an overestimation of fire emissions over Africa due to the misrepresentation of the underlying vegetation types and an underestimation over equatorial Asia due to a lack of representation of peat fires. Despite this, comparing model results with observations of CO column mixing ratio and aerosol optical depth (AOD) show that the fire–atmosphere coupled configuration has a similar performance when compared to UKESM1. In fact, including the interactive biomass burning emissions improves the interannual CO atmospheric column variability and consequently its seasonality over the main biomass burning regions – Africa and South America. Similarly, for aerosols, the AOD results broadly agree with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations.

Wildfires stand as significant contributors to atmospheric aerosols, exerting a substantial influence on air quality and radiative forcing. In our research, we utilized the Weather Research and Forecasting model coupled with chemistry (WRF−Chem) to delve into the repercussions of wildfires on aerosol pollution and meteorological interactions. Our study centered on Greece, serving as a poignant test case. We focus on the summer of 2021, a period marked by intense wildfire occurrences within the nation.

This in vivo study aimed to investigate the effects of a multi-component mycotoxin-detoxifying agent, containing clays (bentonite, sepiolite), phytogenic feed additives (curcumin, silymarin) and postbiotics (yeast cell wall, hydrolyzed yeast) on the antioxidant capacity, health and reproductive performance of pregnant and lactating sows challenged by mycotoxins. Eighty (80) primiparous sows (mean age 366 ± 3 days) per each of the two trial farms were divided into two groups in each farm: a) T1 (control group): 40 sows received the contaminated feed and b) T2 group (experimental group): 40 sows received the contaminated feed plus the mycotoxin-detoxifying agent, one month before farrowing until the end of the lactation period. Thiobarbituric acid reactive substances (TBARS), protein carbonyls (CARBS) and total antioxidant capacity (TAC) were evaluated as biomarkers of oxidative stress. Clinical and reproductive parameters were recorded. Our results indicate that the administration of a multi-component mycotoxin-detoxifying agent’s administration in sow feed has beneficial effects on oxidative stress biomarkers and can improve sows’ health and performance.

Lemon is a prominent citrus fruit that supports regional economies worldwide. Several agronomic and fruit quality attributes are affected by the rootstock selection, thus its selection is essential for a successful grove. This study aims to compare the agronomic and quality attributes of four lemon cultivars (‘Mikrokarpo Messaras’, ‘Nouvel Athos’, ‘Femminello Commune,’ and ‘Zia gara Bianca’) grafted onto three rootstocks (‘Sour Orange’, ‘Yuma Ponderosa lemon’, and ‘Volkameriana’). The yield and rootstock/scion ratio were estimated along with fruit morphological characteristics (size, equatorial, and polar diameter). Internal fruit quality was also estimated (total soluble solids, total acidity, juiciness, ascorbic acid, total phenols, and total antioxidant activity). ‘Volkameriana’ rootstock stood out among the studied rootstocks, as all grafted lemon varieties increased their productivity. Its combination with the Italian cultivar ‘Femminello Commune’ exhibited enhanced tree vigor and tree yield. For all studied cultivars, the use of ‘Volkameriana’ or ‘Yuma Ponderosa lemon’ rootstocks decreased the total soluble content and total acidity, increased the ascorbic acid content, and did not influence the TSS/TA ratio, total phenols or total antioxidant activity. In conclusion, the vigorous ‘Volkameriana’ and ‘Yuma Ponderosa lemon’ rootstocks are a promising replacement for ‘sour orange’. This research provides valuable insights into the potential use of ‘Yuma Ponderosa lemon’ as a rootstock for lemons, as existing literature is rather limited.

The present study aimed to investigate the effects of a commercial phytogenic feed additive (PFA) on the prevention of post-weaning diarrhea and oxidative stress in piglets. The concentrations of thiobarbituric acid reactive substances (TBARS) and protein carbonyls (CARBS) were investigated as biomarkers for oxidative damage, as were the health and performance parameters of weaned piglets. In total, 100 weaned piglets were divided into two groups: a control group (T1), which was fed regular weaning feed; an experimental group (T2), which was fed regular weaning feed supplemented with a phenolic feed additive (PFA) for 3 weeks. The TBARS and CARBS concentrations in plasma samples from 20 piglets per group were measured at 45 and 65 days of age. Fecal samples were collected from 24 weaned piglets per group using FTA ELUTE cards. Diarrhea score, body weight (BW) at weaning, and average daily weight gain (ADWG) were recorded. The TBARS (p < 0.001) and CARBS (p = 0.001) concentrations were significantly higher in the T1 group compared to those in the T2 group. The lowest diarrhea score was noted in the T2 group for the age groups of 45 (p < 0.001) and 65 days (p = 0.008). In conclusion, the use of a phenolic PFA in the current study had beneficial antioxidative and antimicrobial effects on weaned piglets, which improved their health and growth performance.

For the radiative impact of individual climate forcings, most previous studies focused on the global mean values at the top of the atmosphere (TOA), and less attention has been paid to surface processes, especially for black carbon (BC) aerosols. In this study, the surface radiative responses to five different forcing agents were analyzed by using idealized model simulations. Our analyses reveal that for greenhouse gases, solar irradiance, and scattering aerosols, the surface temperature changes are mainly dictated by the changes of surface radiative heating, but for BC, surface energy redistribution between different components plays a more crucial role. Globally, when a unit BC forcing is imposed at TOA, the net shortwave radiation at the surface decreases by -5.87±0.67 W m−2 (W m−2)−1 (averaged over global land without Antarctica), which is partially offset by increased downward longwave radiation (2.32±0.38 W m−2 (W m−2)−1 from the warmer atmosphere, causing a net decrease in the incoming downward surface radiation of -3.56±0.60 W m−2 (W m−2)−1. Despite a reduction in the downward radiation energy, the surface air temperature still increases by 0.25±0.08 K because of less efficient energy dissipation, manifested by reduced surface sensible (-2.88±0.43 W m−2 (W m−2)−1) and latent heat flux (-1.54±0.27 W m−2 (W m−2)−1), as well as a decrease in Bowen ratio (-0.20±0.07 (W m−2)−1). Such reductions of turbulent fluxes can be largely explained by enhanced air stability (0.07±0.02 K (W m−2)−1), measured as the difference of the potential temperature between 925 hPa and surface, and reduced surface wind speed (-0.05±0.01 m s−1 (W m−2)−1). The enhanced stability is due to the faster atmospheric warming relative to the surface, whereas the reduced wind speed can be partially explained by enhanced stability and reduced Equator-to-pole atmospheric temperature gradient. These rapid adjustments under BC forcing occur in the lower atmosphere and propagate downward to influence the surface energy redistribution and thus surface temperature response, which is not observed under greenhouse gases or scattering aerosols. Our study provides new insights into the impact of absorbing aerosols on surface energy balance and surface temperature response.

Atmospheric blocking events are mid-latitude weather patterns, which obstruct the usual path of the polar jet streams. They are often associated with heat waves in summer and cold snaps in winter. Despite being central features of mid-latitude synoptic-scale weather, there is no well-defined historical dataset of blocking events. Various blocking indices (BIs) have thus been suggested for automatically identifying blocking events in observational and in climate model data. However, BIs show significant regional and seasonal differences so that several indices are typically applied in combination to ensure scientific robustness. Here, we introduce a new BI using self-organizing maps (SOMs), an unsupervised machine learning approach, and compare its detection skill to some of the most widely applied BIs. To enable this intercomparison, we first create a new ground truth time series classification of European blocking based on expert judgement. We then demonstrate that our method (SOM-BI) has several key advantages over previous BIs because it exploits all of the spatial information provided in the input data and reduces the dependence on arbitrary thresholds. Using ERA5 reanalysis data (1979–2019), we find that the SOM-BI identifies blocking events with a higher precision and recall than other BIs. In particular, SOM-BI already performs well using only around 20 years of training data so that observational records are long enough to train our new method. We present case studies of the 2003 and 2019 European heat waves and highlight that well-defined groups of SOM nodes can be an effective tool to diagnose such weather events, although the domain-based approach can still lead to errors in the identification of certain events in a fashion similar to the other BIs. We further test the red blocking detection skill of SOM-BI depending on the meteorological variable used to study blocking, including geopotential height, sea level pressure and four variables related to potential vorticity, and the 500 hPa geopotential height anomaly field provides the best results with our new approach. We also demonstrate how SOM-BI can be used to identify different types of blocking events and their associated trends. Finally, we evaluate the SOM-BI performance on around 100 years of climate model data from a pre-industrial simulation with the new UK Earth System Model (UKESM1-0-LL). For the model data, all blocking detection methods have lower skill than for the ERA5 reanalysis, but SOM-BI performs noticeably better than the conventional indices. Overall, our results demonstrate the significant potential for unsupervised learning to complement the study of blocking events in both reanalysis and climate modelling contexts.

Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000-2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000-2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000-2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008-2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16-32]Tg CH4yr-1 higher methane emissions over the period 2008-2012 compared to 2002-2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002-2006 and 2008-2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

The seasonal and longer-term dynamics of fuel accumulation affect fire seasonality and the occurrence of extreme wildfires. Failure to account for their influence may help to explain why state-of-the-art fire models do not simulate the length and timing of the fire season or interannual variability in burnt area well. We investigated the impact of accounting for different timescales of fuel production and accumulation on burnt area using a suite of random forest regression models that included the immediate impact of climate, vegetation, and human influences in a given month and tested the impact of various combinations of antecedent conditions in four productivity-related vegetation indices and in antecedent moisture conditions. Analyses were conducted for the period from 2010 to 2015 inclusive. Inclusion of antecedent vegetation conditions representing fuel build-up led to an improvement of the global, climatological out-of-sample R2 from 0.579 to 0.701, but the inclusion of antecedent vegetation conditions on timescales ≥ 1 year had no impact on simulated burnt area. Current moisture levels were the dominant influence on fuel drying. Additionally, antecedent moisture levels were important for fuel build-up. The models also enabled the visualisation of interactions between variables, such as the importance of antecedent productivity coupled with instantaneous drying. The length of the period which needs to be considered varies across biomes; fuel-limited regions are sensitive to antecedent conditions that determine fuel build-up over longer time periods (∼ 4 months), while moisture-limited regions are more sensitive to current conditions that regulate fuel drying.

Interactions between aerosols and gases in the atmosphere have been the focus of an increasing number of studies in recent years. Here, we focus on aerosol effects on tropospheric ozone that involve meteorological feedbacks induced by aerosol–radiation interactions. Specifically, we study the effects that involve aerosol influences on the transport of gaseous pollutants and on atmospheric moisture, both of which can impact ozone chemistry. For this purpose, we use the UK Earth System Model (UKESM1), with which we performed sensitivity simulations including and excluding the aerosol direct radiative effect (ADE) on atmospheric chemistry, and focused our analysis on an area with a high aerosol presence, namely China. By comparing the simulations, we found that ADE reduced shortwave radiation by 11 % in China and consequently led to lower turbulent kinetic energy, weaker horizontal winds and a shallower boundary layer (with a maximum of 102.28 m reduction in north China). On the one hand, the suppressed boundary layer limited the export and diffusion of pollutants and increased the concentration of CO, SO2, NO, NO2, PM2.5 and PM10 in the aerosol-rich regions. The NO/NO2 ratio generally increased and led to more ozone depletion. On the other hand, the boundary layer top acted as a barrier that trapped moisture at lower altitudes and reduced the moisture at higher altitudes (the specific humidity was reduced by 1.69 % at 1493 m on average in China). Due to reduced water vapour, fewer clouds were formed and more sunlight reached the surface, so the photolytical production of ozone increased. Under the combined effect of the two meteorology feedback methods, the annual average ozone concentration in China declined by 2.01 ppb (6.2 %), which was found to bring the model into closer agreement with surface ozone measurements from different parts of China.

Our aim was to compare the inter-rater agreement about transvaginal ultrasonography (TVS) with magnetic resonance imaging (MRI) with regard to diagnosing adenomyosis and for assessing various predefined imaging features of adenomyosis, in the same set of women. The study cohort included 51 women, prospectively, consecutively recruited based on a clinical suspicion of adenomyosis. MRIs and TVS videoclips and 3D volumes were retrospectively assessed by four experienced radiologists and five experienced sonographers, respectively. Each rater subjectively evaluated the presence or absence of adenomyosis, as well as imaging features suggestive of adenomyosis. Fleiss kappa (κ) was used to reflect inter-rater agreement for categorical data, and the intraclass correlation coefficient (ICC) was used to reflect the reliability of quantitative data. Agreement between raters for diagnosing adenomyosis was higher for TVS than for MRI (κ = 0.42 vs. 0.28). MRI had a higher inter-rater agreement in assessing wall asymmetry, irregular junctional zone (JZ), and the presence of myometrial cysts, while TVU had a better agreement for assessing globular shape. MRI showed a moderate to good reliability for measuring the JZ (ICC = 0.57–0.82). For TVS, the JZ was unmeasurable in >50% of cases, and the remaining cases had low reliability (ICC = −0.31–0.08). We found that inter-rater agreement for diagnosing adenomyosis was higher for TVS than for MRI, despite the fact that MRI showed a higher inter-rater agreement in most specific features. Measurements of JZ in the coronal plane with 3D TVS were unreliable and thus unlikely to be useful for diagnosing adenomyosis.

In conventional disorder–order phase transitions, a system shifts from a highly symmetric state, where all states are equally accessible (disorder) to a less symmetric state with a limited number of available states (order). This transition may occur by varying a control parameter that represents the intrinsic noise of the system. It has been suggested that stem cell differentiation can be considered as a sequence of such symmetry-breaking events. Pluripotent stem cells, with their capacity to develop into any specialized cell type, are considered highly symmetric systems. In contrast, differentiated cells have lower symmetry, as they can only carry out a limited number of functions. For this hypothesis to be valid, differentiation should emerge collectively in stem cell populations. Additionally, such populations must have the ability to self-regulate intrinsic noise and navigate through a critical point where spontaneous symmetry breaking (differentiation) occurs. This study presents a mean-field model for stem cell populations that considers the interplay of cell–cell cooperativity, cell-to-cell variability, and finite-size effects. By introducing a feedback mechanism to control intrinsic noise, the model can self-tune through different bifurcation points, facilitating spontaneous symmetry breaking. Standard stability analysis showed that the system can potentially differentiate into several cell types mathematically expressed as stable nodes and limit cycles. The existence of a Hopf bifurcation in our model is discussed in light of stem cell differentiation.

Simple Summary: Subacute rumen acidosis (SARA) is a significant clinical issue in high-yield livestock, including dairy sheep, and it is characterized by rumen pH dropping below 5.8 for at least four hours daily. This condition leads to economic losses due to reduced milk production and lower milk fat content. High-concentrate, low-fiber diets increase the risk of SARA by disrupting rumen fermentation. Diagnosing SARA is challenging, with rumen fluid pH measurement being the gold standard. This study investigated the prevalence of SARA and its impact in forty-two Greek dairy sheep flocks, as well as the potential of computerized rumen colorimetry as a diagnostic tool post mortem. Over nine months, rumen pH and milk composition were monitored, and rumen wall samples were analyzed for color and histological changes. The results showed increased epithelium thickness and discoloration in SARA-affected sheep. This study highlights the prevalence of SARA in the modern intensive dairy sheep industry, underscores the need for balanced feeding strategies, and suggests computerized rumen colorimetry as a promising tool for SARA detection and management in dairy sheep farms. Subacute rumen acidosis (SARA) is a current issue in intensive livestock farming, and it is particularly associated with feeding high-concentrate diets. This study investigated the prevalence and impact of SARA in forty-two Greek dairy sheep flocks by recording rumen pH, milk composition, and milk yield over a period of nine months. Moreover, it explored the use of computerized rumen colorimetry as a management and diagnostic tool for SARA in dairy sheep. In culled ewes, computerized rumen mucosal colorimetry was applied, and rumen wall samples taken for histological examination. SARA cases were identified in 19 farms (45%, n = 42). Farms with SARA cases had lower milk fat levels, while milk yield and milk protein levels did not differ based on the SARA status of the farms. In culled ewes, rumen color was significantly associated with the flock's SARA status, and affected ewes showed increased thickness in non-keratinized and total epithelial layers. It was concluded that computerized rumen mucosal colorimetry in aged, culled ewes shows promise as an indicator, post mortem, of SARA present in dairy sheep flocks whose impact can be minimized by making significant changes in dietary management. [ABSTRACT FROM AUTHOR]