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Background The long-term outcomes of COVID-19 hospitalisation in individuals with pre-existing airway diseases are unknown. Methods Adult participants hospitalised for confirmed or clinically suspected COVID-19 and discharged between 5 March 2020 and 31 March 2021 were recruited to the Post-hospitalisation COVID-19 (PHOSP-COVID) study. Participants attended research visits at 5 months and 1 year post discharge. Clinical characteristics, perceived recovery, burden of symptoms and health-related quality of life (HRQoL) of individuals with pre-existing airway disease (i.e., asthma, COPD or bronchiectasis) were compared to the non-airways group. Results A total of 615 out of 2697 (22.8%) participants had a history of pre-existing airway diseases (72.0% diagnosed with asthma, 22.9% COPD and 5.1% bronchiectasis). At 1 year, the airways group participants were less likely to feel fully recovered (20.4% versus 33.2%, p

Abstract The global marine aquarium trade has created new local markets across the planet, including in Indonesia, now the second-largest exporting country of marine aquarium fish in the world. Participating in the global aquarium trade has been touted as a potentially sustainable addition to fisher livelihoods, but scant data exist showing the numbers of fish coming off the reef and how those fish contribute to income. To determine how participants in the trade incorporate aquarium species in their livelihoods, we examine source-level aquarium fish collecting and trading data in the Banggai Archipelago, a region in Central Sulawesi that has become a significant source for popular aquarium, also known as ornamental, fish species. Using a sustainable livelihoods lens, we examine this data to understand how participants in the aquarium trade both contribute to as well as benefit from the trade and consider how their participation relates to emerging Blue Justice principles. From one year of buying and selling data at the fisher, intermediary buyer, and regional trader levels, we show that catching and selling fish for the aquarium trade represents an average of nearly 20% of their gross annual income and provides added diversity and flexibility to fisher and trader livelihoods in the region, especially during seasons of rough weather. We suggest that managers of an impending marine protected area in the region would do well to consider how to sustain these livelihood benefits.

High-resolution (< 1 km) atmospheric modeling is increasingly used to study precipitation distributions in complex terrain and cryosphere–atmospheric processes. While this approach has yielded insightful results, studies over annual timescales or at the spatial extents of watersheds remain unrealistic due to the computational costs of running most atmospheric models. In this paper we introduce a high-resolution variant of the Intermediate Complexity Atmospheric Research (ICAR) model, HICAR. We detail the model development that enabled HICAR simulations at the hectometer scale, including changes to the advection scheme and the wind solver. The latter uses near-surface terrain parameters which allow HICAR to simulate complex topographic flow features. These model improvements clearly influence precipitation distributions at the ridge scale (50 m), suggesting that HICAR can approximate processes dependent on particle–flow interactions such as preferential deposition. A 250 m HICAR simulation over most of the Swiss Alps also shows monthly precipitation patterns similar to two different gridded precipitation products which assimilate available observations. Benchmarking runs show that HICAR uses 594 times fewer computational resources than the Weather Research and Forecasting (WRF) atmospheric model. This gain in efficiency makes dynamic downscaling accessible to ecohydrological research, where downscaled data are often required at hectometer resolution for whole basins at seasonal timescales. These results motivate further development of HICAR, including refinement of parameterizations used in the wind solver and coupling of the model with an intermediate-complexity snow model.

Numerical models of ocean biogeochemistry are becoming the major tools used to detect and predict the impact of climate change on marine resources and to monitor ocean health. However, with the continuous improvement of model structure and spatial resolution, incorporation of these additional degrees of freedom into fidelity assessment has become increasingly challenging. Here, we propose a new method to provide information on the model predictive skill in a concise way. The method is based on the conjoint use of a k-means clustering technique, assessment metrics, and Biogeochemical-Argo (BGC-Argo) observations. The k-means algorithm and the assessment metrics reduce the number of model data points to be evaluated. The metrics evaluate either the model state accuracy or the skill of the model with respect to capturing emergent properties, such as the deep chlorophyll maximums and oxygen minimum zones. The use of BGC-Argo observations as the sole evaluation data set ensures the accuracy of the data, as it is a homogenous data set with strict sampling methodologies and data quality control procedures. The method is applied to the Global Ocean Biogeochemistry Analysis and Forecast system of the Copernicus Marine Service. The model performance is evaluated using the model efficiency statistical score, which compares the model–observation misfit with the variability in the observations and, thus, objectively quantifies whether the model outperforms the BGC-Argo climatology. We show that, overall, the model surpasses the BGC-Argo climatology in predicting pH, dissolved inorganic carbon, alkalinity, oxygen, nitrate, and phosphate in the mesopelagic and the mixed layers as well as silicate in the mesopelagic layer. However, there are still areas for improvement with respect to reducing the model–data misfit for certain variables such as silicate, pH, and the partial pressure of CO2 in the mixed layer as well as chlorophyll-a-related, oxygen-minimum-zone-related, and particulate-organic-carbon-related metrics. The method proposed here can also aid in refining the design of the BGC-Argo network, in particular regarding the regions in which BGC-Argo observations should be enhanced to improve the model accuracy via the assimilation of BGC-Argo data or process-oriented assessment studies. We strongly recommend increasing the number of observations in the Arctic region while maintaining the existing high-density of observations in the Southern Oceans. The model error in these regions is only slightly less than the variability observed in BGC-Argo measurements. Our study illustrates how the synergic use of modeling and BGC-Argo data can both provide information about the performance of models and improve the design of observing systems.

Key messages 1. Development a prognostic index of poor renal evolution in patients with LN. 2. We use clinical, histological and laboratory factors 6 months after diagnosis and treatment 3. Effective tool in the early detection and management, easy to use in clinical practice

Ozone depletion events (ODEs) are a common occurrence in the boundary layer during Arctic spring. Ozone is depleted by bromine species, which are most likely emitted from snow, sea ice, or aerosols in an autocatalytic reaction cycle. Previous three-dimensional modeling studies of ODEs assumed an infinite bromine source at the ground. In the present study, an alternative emission scheme is presented in which a finite amount of bromide in the snow is tracked over time. For this purpose, a modified version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is used to study ODEs in the Arctic from February to May 2019. The model data are compared to in situ measurements, ozone sonde flights, and satellite data. A simulation of the ODEs in the Arctic spring of 2009 using the infinite-bromide assumption on first-year (FY) ice is transferred to the spring of 2019, which achieves good agreement with the observations; however, there is some disagreement in April 2009 and 2019 with respect to an overestimation concerning both the magnitude and the number of ODEs. New simulations using the finite-bromide assumption greatly improve agreement with in situ observations at Utqiaġvik, Alaska, Zeppelin Mountain, Svalbard, and Pallas, Finland, in April 2019, suggesting that bromide on the sea ice is depleted to an extent that reduces the bromine release. The new simulations also slightly improve the agreement with observations at these sites in February and March. A comparison to measurements near Eureka, Canada, and Station Nord, Greenland, shows that multi-year ice and possibly snow-covered land may be significant bromine sources. However, assuming higher releasable bromide near Eureka does not remove all disagreement with the observations. The numerical results are also compared to tropospheric-BrO vertical column densities generated with a new retrieval method from TROPOspheric Monitoring Instrument (TROPOMI) observations. BrO vertical column densities (VCDs) above 5×1013 molec. cm−2 observed by the satellite agree well with the model results. However, the model also predicts BrO VCDs of around 3×1013 molec. cm−2 throughout the Arctic and patches of BrO VCDs of around 1014 molec. cm−2 not observed by the satellite, especially near Hudson Bay. This suggests that snow at Hudson Bay may be a weaker bromine source in late spring compared to snow in the north.

Summary: Background: The scale of COVID-19 and its well documented long-term sequelae support a need to understand long-term outcomes including frailty. Methods: This prospective cohort study recruited adults who had survived hospitalisation with clinically diagnosed COVID-19 across 35 sites in the UK (PHOSP-COVID). The burden of frailty was objectively measured using Fried's Frailty Phenotype (FFP). The primary outcome was the prevalence of each FFP group—robust (no FFP criteria), pre-frail (one or two FFP criteria) and frail (three or more FFP criteria)—at 5 months and 1 year after discharge from hospital. For inclusion in the primary analysis, participants required complete outcome data for three of the five FFP criteria. Longitudinal changes across frailty domains are reported at 5 months and 1 year post-hospitalisation, along with risk factors for frailty status. Patient-perceived recovery and health-related quality of life (HRQoL) were retrospectively rated for pre-COVID-19 and prospectively rated at the 5 month and 1 year visits. This study is registered with ISRCTN, number ISRCTN10980107. Findings: Between March 5, 2020, and March 31, 2021, 2419 participants were enrolled with FFP data. Mean age was 57.9 (SD 12.6) years, 933 (38.6%) were female, and 429 (17.7%) had received invasive mechanical ventilation. 1785 had measures at both timepoints, of which 240 (13.4%), 1138 (63.8%) and 407 (22.8%) were frail, pre-frail and robust, respectively, at 5 months compared with 123 (6.9%), 1046 (58.6%) and 616 (34.5%) at 1 year. Factors associated with pre-frailty or frailty were invasive mechanical ventilation, older age, female sex, and greater social deprivation. Frail participants had a larger reduction in HRQoL compared with before their COVID-19 illness and were less likely to describe themselves as recovered. Interpretation: Physical frailty and pre-frailty are common following hospitalisation with COVID-19. Improvement in frailty was seen between 5 and 12 months although two-thirds of the population remained pre-frail or frail. This suggests comprehensive assessment and interventions targeting pre-frailty and frailty beyond the initial illness are required. Funding: UK Research and Innovation and National Institute for Health Research.

Background & aims: Despite effective direct-acting antivirals (DAAs), hepatitis C virus (HCV) prevalence is high among people who inject drugs (PWIDs) and non-adherence to therapy remains a major obstacle towards HCV elimination in this subpopulation. To overcome this issue, we have combined ongoing opioid agonist therapy (OAT) with DAAs in a directly-observed therapy (DOT) setting. Method: From September 2014 until January 2021 PWIDs at high risk of non-adherence to DAA therapy, who were also on OAT, were included into this microelimination project. Individuals received their OAT and DAAs under supervision of healthcare workers as DOT in a pharmacy or low-threshold facility. Results: In total, 504 HCV RNA-positive PWIDs on OAT (387 men, 76.8%; median age: 38 years [IQR 33–45], HIV: 4.6%; hepatitis B: 1.4%) were included into this study. Two thirds reported ongoing intravenous drug use (IDU) and half of them had no permanent housing. Only 41 (8.1%) were lost to follow-up and two (0.4%) died of reasons unrelated to DAA toxicity. Overall, 90.7% of PWIDs achieved sustained virological response 12 weeks after treatment (SVR12) (95% CI: 88.1–93.2%). By excluding those lost to follow-up and hose who had died of causes unrelated to DAAs, the SVR12 rate was 99.1% (95% CI: 98.3–100.0%; modified intention-to-treat analysis). Four PWIDs (0.9%) experienced treatment failure. Over a median follow-up of 24 weeks (IQR 12–39), 27 reinfections (5.9%) were observed in individuals with the highest IDU rates (81.2%). Importantly, even though some were lost to follow-up, all completed their DAA treatment. By using DOT, adherence to DAAs was excellent with only a total of 86 missed doses (0.3% of 25,224 doses). Conclusions: In this difficult-to-treat population of PWIDs with high rates of IDU , coupling DAA treatment to OAT in a DOT setting resulted in high SVR12 rates equivalent to conventional treatment settings in non-PWID populations.

The formation of ice particles in Earth's atmosphere strongly influences the dynamics and optical properties of clouds and their impacts on the climate system. Ice formation in clouds is often triggered heterogeneously by ice-nucleating particles (INPs) that represent a very low number of particles in the atmosphere. To date, many sources of INPs, such as mineral and soil dust, have been investigated and identified in the low and mid latitudes. Although less is known about the sources of ice nucleation at high latitudes, efforts have been made to identify the sources of INPs in the Arctic and boreal environments. In this study, we investigate the INP emission potential from high-latitude boreal forests in the mixed-phase cloud regime. We introduce the HyICE-2018 measurement campaign conducted in the boreal forest of Hyytiälä, Finland, between February and June 2018. The campaign utilized the infrastructure of the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, with additional INP instruments, including the Portable Ice Nucleation Chamber I and II (PINC and PINCii), the SPectrometer for Ice Nuclei (SPIN), the Portable Ice Nucleation Experiment (PINE), the Ice Nucleation SpEctrometer of the Karlsruhe Institute of Technology (INSEKT) and the Microlitre Nucleation by Immersed Particle Instrument (µL-NIPI), used to quantify the INP concentrations and sources in the boreal environment. In this contribution, we describe the measurement infrastructure and operating procedures during HyICE-2018, and we report results from specific time periods where INP instruments were run in parallel for inter-comparison purposes. Our results show that the suite of instruments deployed during HyICE-2018 reports consistent results and therefore lays the foundation for forthcoming results to be considered holistically. In addition, we compare measured INP concentrations to INP parameterizations, and we observe good agreement with the Tobo et al. (2013) parameterization developed from measurements conducted in a ponderosa pine forest ecosystem in Colorado, USA.

The objective of this study was to determine the effects of some environmental and breed group factors on lifetime and per year productivity of sows. A retrospective study was carried out from 1998 to 2007 using information of a production system with 2,400 sows, in La Piedad, Michoacan, Mexico. Data from 6,063 sows belonging to the breed groups PIC Camborough 22, Yorkshire (Y), F1 Landrace (L) x Y (F1 LY) and 3/4Y1/4Lwere used. The response variables were the number of pigs born alive per sow per year (PBY) or per productive lifetime (PBL), number of pigs weaned per year (PWY) or per productive lifetime (PWL), kg of pigs weaned per sow per year (KWY), kg of pigs weaned per sow per lifetime (KWL) and productive lifetime (PLT) of sows. The statistical model included the fixed effect of year of first farrowing (1998-2007), season of first farrowing (spring, summer, fall, winter), breed group of the sow, number of pigs born alive at first farrowing (10 pigs) and year by season interaction. Means and standard deviations estimated for PBY, PWY, KPY, PBL, PWL, KWL and PLT were 21.4±3.71 pigs, 18.2±4.04 pigs, 107.5+25.8 kg, 48.3±22.7 pigs, 41.4±3.71 kg, 243.7±122.9 kg and 805.6±338.8 days, respectively. All factors studied had effect on all traits (P < 0.05), except, breed group on PBY, and season on PWY and KWL. The interaction of year by season was not significant only for PBY. Sows farrowing from 2005 to 2007 and in the fall season had the poorest performance. The best performance per year or productive lifetime corresponded to the 1/4L3/4Y breed group, except for PBY where no differences were found. Also, the 1/4L3/4Y sows stayed longer in the herd. The sows with the smallest litter size at first parity (≤ 6 piglets) had the worst performance.

Abstract Background Obesity is caused by the enlargement of the white adipose tissue (WAT) depots, characterized by the hypertrophic enlargement of malfunctioning adipocytes within WAT which increases the storage of triglycerides (TG) in the lipid droplets (LD). Adipogenesis pathways as well as the expression and activity of some extracellular matrix receptors integrins are upregulated. Integrinβ1 (INTB1) is the main isoform involved in WAT remodeling during obesity and insulin resistance-related diseases. We recently described Integrin Linked Kinase (ILK), a scaffold protein recruited by INTB1, as an important mediator of WAT remodeling and insulin resistance. As the few approved drugs to fight obesity have brought long-term cardiovascular side effects and given that the consideration of INTB1 and/or ILK modulation as anti-obesogenic strategies remains unexplored, we aimed to evaluate the anti-obesogenic capacity of the clinically approved anticoagulant Tirofiban (TF), stated in preclinical studies as a cardiovascular protector. Methods Fully differentiated adipocytes originating from C3H10T1/2 were exposed to TF and were co-treated with specific INTB1 blockers or with siRNA-based knockdown ILK expression. Lipid-specific dyes were used to determine the TG content in LD. The genetic expression pattern of ILK, pro-inflammatory cytokines (MCP1, IL6), adipogenesis (PPARγ, Leptin), thermogenesis (UCP1), proliferation (PCNA), lipid metabolism (FASN, HSL, ATGL), and metabolite transporters (FABP4, FAT, AQP7) were detected using quantitative PCR. Cytoskeletal actin polymerization was detected by confocal microscopy. Immunoblotting was performed to detect INTB1 phosphorylation at Thr788/9 and ILK activity as phosphorylation levels of protein kinase B (AKT) in Ser473 and glycogen synthase kinase 3β (GSK3β) at Ser9. TF was intraperitoneally administered once per day to wildtype and ILK knockdown mice (cKDILK) challenged with a high-fat diet (HFD) or control diet (STD) for 2 weeks. Body and WAT weight gains were compared. The expression of ILK and other markers was determined in the visceral epididymal (epi) and inguinal subcutaneous (sc) WAT. Results TF reduced TG content and the expression of adipogenesis markers and transporters in adipocytes, while UCP-1 expression was increased and the expression of lipases, cytokines or PCNA was not affected. Mechanistically, TF rapidly increased and faded the intracellular phosphorylation of INTB1 but not AKT or GSK3β. F-actin levels were rapidly decreased, and INTB1 blockade avoided the TF effect. After 24 h, ILK expression and phosphorylation rates of AKT and GSK3β were upregulated, while ILK silencing increased TG content. INTB1 blockade and ILK silencing avoided TF effects on the TG content and the transcriptional expression of PPARγ and UCP1. In HFD-challenged mice, the systemic administration of TF for several days reduced the weight gain on WAT depots. TF reduced adipogenesis and pro-inflammatory biomarkers and increased lipolysis markers HSL and FAT in epiWAT from HFD, while increased UCP1 in scWAT. In both WATs, TF upregulated ILK expression and activity, while no changes were observed in other tissues. In HFD-fed cKDILK, the blunted ILK in epiWAT worsened weight gain and avoided the anti-obesogenic effect of in vivo TF administration. Conclusions ILK downregulation in WAT can be considered a biomarker of obesity establishment. Via an INTB1-ILK axis, TF restores malfunctioning hypertrophied WAT by changing the expression of adipocyte-related genes, increasing ILK expression and activity, and reducing TG storage. TF prevents obesity, a property to be added to its anticoagulant and cardiovascular protective advantages.

The snowpack over the Mediterranean mountains constitutes a key water resource for the downstream populations. However, its dynamics have not been studied in detail yet in many areas, mostly because of the scarcity of snowpack observations. In this work, we present a characterization of the snowpack over the two mountain ranges of Lebanon. To obtain the necessary snowpack information, we have developed a 1 km regional-scale snow reanalysis (ICAR_assim) covering the period 2010–2017. ICAR_assim was developed by means of an ensemble-based data assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) fractional snow-covered area (fSCA) through an energy and mass snow balance model, the Flexible Snow Model (FSM2), using the particle batch smoother (PBS). The meteorological forcing data were obtained by a regional atmospheric simulation from the Intermediate Complexity Atmospheric Research model (ICAR) nested inside a coarser regional simulation from the Weather Research and Forecasting model (WRF). The boundary and initial conditions of WRF were provided by the ERA5 atmospheric reanalysis. ICAR_assim showed very good agreement with MODIS gap-filled snow products, with a spatial correlation of R=0.98 in the snow probability (P(snow)) and a temporal correlation of R=0.88 on the day of peak snow water equivalent (SWE). Similarly, ICAR_assim has shown a correlation with the seasonal mean SWE of R=0.75 compared with in situ observations from automatic weather stations (AWSs). The results highlight the high temporal variability in the snowpack in the Lebanese mountain ranges, with the differences between Mount Lebanon and the Anti-Lebanon Mountains that cannot only be explained by hypsography as the Anti-Lebanon Mountains are in the rain shadow of Mount Lebanon. The maximum fresh water stored in the snowpack is in the middle elevations, approximately between 2200 and 2500 m a.s.l. (above sea level). Thus, the resilience to further warming is low for the snow water resources of Lebanon due to the proximity of the snowpack to the zero isotherm.

Introduction Today, a number of researchers consider the problem of addictive behavior as one of the most global problems for Kazakhstan and Russia. Some scientists consider CBT to be the most effective way to work with addictions. In our country there are no scientific works devoted to the study of addictive beliefs, so we decided to conduct such a study Objectives The Objective of the study was to identify the characteristic addictive beliefs of drug addicts with different type of addiction: opioids and synthetic cathinones (designer drugs called “salts”, “bath salts”) Methods Questionnaire of addictive beliefs by A, Beck, questionnaire of beliefs about cravings by A. Beck and F. Wright, clinical interview. Descriptive statistics and chi-square test were used for data processing Results People with opioid addiction are more likely to believe that their lives will become more depressive if they stop using drugs (p= 0.0347); that drug use is the only way to cope with pain in their life (p= 0.0347) and that they cannot cope with anxiety without drugs (p=0.009). Respondents who use synthetic psychostimulants endorse to believe that addiction is not a problrm for them (p= 0.0358). Conclusions Having categorized these beliefs in accordance with A. Beck’s classification, we came to the conclusion that “relief-oriented beliefs” are more typical for people who use opiates. The motive for use is often the desire to alleviate a negative emotional or physical state. For people using psychostimulants “salt”, “anticipatory beliefs” are more characteristic - the desire to experience euphoria and pleasant experiences Disclosure No significant relationships.

Introduction The anticonvulsant m-Cl-BHM is promising for the pathogenetically directed thrapy does not cause negative effects. Objectives Investigation of the effect of m-Сl-BHM on “immunochemical homeostasis” in rats with experimental alcoholism. Methods m-Cl-BHM was injected at a dose of 100 mg/kg (1/20 LD50) for 5 and 30 days into the stomach of male Wistar rats who preferred alcohol according to the screening conditions and kept for 10 months. in free access to a 15% ethanol solution, which made up the group of “heavy drinkers” (HD). Phenobarbital was administered at a dose of 25 mg/kg (1/20 LD50). Results The features of the monooxygenase system of cytochrome P450 of the liver and ECT in the lymphoid organs of rats were studied at different periods of administration of m-CL-BHM -5 and 30 days. to HD rats. m-CL-BHM has an inducing effect on the monooxygenase system of the liver, causes phase changes in the lymphoid organs and ECT. Long-term administration of m-CL-BHM caused a depletion of the cellular composition of lymphoid organs, a decrease in ECT of spleen cells and peritoneal exudate, these changes were less pronounced compared with phenobarbital. The activation of the immune system inversely regulates the production of enzymes of the cytochrome system, since the concentration of low molecular weight targets is sharply reduced with the help of antibodies. m-Cl-BHM metabolites conjugated to endogenous macromolecules form a full-fledged stimulus for the immune system. Conclusions Neuroimmune response to the introduction of m-CL-BHM is significant in behavioral disorders associated with alcoholism and the correction of this condition. Disclosure No significant relationships.

Introduction Today, a number of researchers consider the problem of addictive behavior as one of the most global problems for Kazakhstan and Russia. Some scientists consider CBT to be the most effective way to work with addictions. In our country there are no scientific works devoted to the study of addictive beliefs, so we decided to conduct such a study. Objectives The Objective of the study was to identify the characteristic addictive beliefs of drug addicts with different type of addiction: opioids and synthetic cathinones (designer drugs called “salts”, “bath salts”). Methods Questionnaire of addictive beliefs by A, Beck, questionnaire of beliefs about cravings by A. Beck and F. Wright, clinical interview. Descriptive statistics and chi-square test were used for data processing. Results People with opioid addiction are more likely to believe that their lives will become more depressive if they stop using drugs (p= 0.0347); that drug use is the only way to cope with pain in their life (p= 0.0347) and that they cannot cope with anxiety without drugs (p=0.009). Respondents who use synthetic psychostimulants endorse to believe that addiction is not a problrm for them (p= 0.0358). Conclusions Having categorized these beliefs in accordance with A. Beck’s classification, we came to the conclusion that “relief-oriented beliefs” are more typical for people who use opiates. The motive for use is often the desire to alleviate a negative emotional or physical state. For people using psychostimulants “salt”, “anticipatory beliefs” are more characteristic - the desire to experience euphoria and pleasant experiences. Disclosure No significant relationships.

Introduction Autism spectrum disorders (ASD) – nosological continuum of genetically and clinically heterogeneous mental disorders united by complex violation of mental development, social interaction and behavior. Objectives Identify the features of brain functioning in children with ASD. Methods Neuropsychological diagnostics (Zh. Glozman), results acoustic brainstem evoked potentials (ABEP), mathematical methods. The study involved 48 children with diagnoses (ICD-10): F84. 0, F84. 1, F84.5, aged 3 to 8 years (average age 4.18 years). Results Neuropsychological examination revealed the main Indices of the functioning of brain blocks: the Index of activation and energy components of activity (I Index), the Index of the right-hemisphere holistic strategy of information processing (Index II-rights), the Index of the left-hemisphere analytical strategy of information processing (Index II-left), the Index of programming, regulation and control of activity (III Index). Then the children were divided into groups (p

Tropospheric bromine release and ozone depletion events (ODEs) as they commonly occur in the Arctic spring are studied using a regional model based on the open-source software package Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). For this purpose, the MOZART (Model for Ozone and Related chemical Tracers)–MOSAIC (Model for Simulating Aerosol Interactions and Chemistry) chemical reaction mechanism is extended by bromine and chlorine reactions as well as an emission mechanism for reactive bromine via heterogeneous reactions on snow surfaces. The simulation domain covers an area of 5040 km×4960 km, centered north of Utqiaġvik (formerly Barrow), Alaska, and the time interval from February through May 2009. Several simulations for different strengths of the bromine emission are conducted and evaluated by comparison with in situ and ozone sonde measurements of ozone mixing ratios as well as by comparison with tropospheric BrO vertical column densities (VCDs) from the Global Ozone Monitoring Experiment-2 (GOME-2) satellite instrument. The base bromine emission scheme includes the direct emission of bromine due to bromide oxidation by ozone. Results of simulations with the base emission rate agree well with the observations; however, a simulation with 50 % faster emissions performs somewhat better. The bromine emission due to bromide oxidation by ozone is found to be important to provide an initial seed for the bromine explosion. Bromine release due to N2O5 was found to be important from February to mid March but irrelevant thereafter. A comparison of modeled BrO with in situ and multi-axis differential optical absorption spectroscopy (MAX-DOAS) data hints at missing bromine release and recycling mechanisms on land or near coasts. A consideration of halogen chemistry substantially improves the prediction of the ozone mixing ratio with respect to the observations. Meteorological nudging is essential for a good prediction of ODEs over the 3-month period.

The San Salvador volcanic complex (El Salvador) and Nejapa-Chiltepe volcanic complex (Nicaragua) have been characterized by a significant variability in eruption style and vent location. Densely inhabited cities are built on them and their surroundings, including the metropolitan areas of San Salvador (∼2.4 million people) and Managua (∼1.4 million people), respectively. In this study we present novel vent opening probability maps for these volcanic complexes, which are based on a multi-model approach that relies on kernel density estimators. In particular, we present thematic vent opening maps, i.e., we consider different hazardous phenomena separately, including lava emission, small-scale pyroclastic density currents, ejection of ballistic projectiles, and low-intensity pyroclastic fallout. Our volcanological dataset includes: (1) the location of past vents, (2) the mapping of the main fault structures, and (3) the eruption styles of past events, obtained from critical analysis of the literature and/or inferred from volcanic deposits and morphological features observed remotely and in the field. To illustrate the effects of considering the expected eruption style in the construction of vent opening maps, we focus on the analysis of small-scale pyroclastic density currents derived from phreatomagmatic activity or from low-intensity magmatic volcanism. For the numerical simulation of these phenomena we adopted the recently developed branching energy cone model by using the program ECMapProb. Our results show that the implementation of thematic vent opening maps can produce significantly different hazard levels from those estimated with traditional, non-thematic maps.

The evaluation of models in general is a nontrivial task and can, due to epistemological and practical reasons, never be considered complete. Due to this incompleteness, a model may yield correct results for the wrong reasons, i.e., via a different chain of processes than found in observations. While guidelines and strategies exist in the atmospheric sciences to maximize the chances that models are correct for the right reasons, these are mostly applicable to full physics models, such as numerical weather prediction models. The Intermediate Complexity Atmospheric Research (ICAR) model is an atmospheric model employing linear mountain wave theory to represent the wind field. In this wind field, atmospheric quantities such as temperature and moisture are advected and a microphysics scheme is applied to represent the formation of clouds and precipitation. This study conducts an in-depth process-based evaluation of ICAR, employing idealized simulations to increase the understanding of the model and develop recommendations to maximize the probability that its results are correct for the right reasons. To contrast the obtained results from the linear-theory-based ICAR model to a full physics model, idealized simulations with the Weather Research and Forecasting (WRF) model are conducted. The impact of the developed recommendations is then demonstrated with a case study for the South Island of New Zealand. The results of this investigation suggest three modifications to improve different aspects of ICAR simulations. The representation of the wind field within the domain improves when the dry and the moist Brunt–Väisälä frequencies are calculated in accordance with linear mountain wave theory from the unperturbed base state rather than from the time-dependent perturbed atmosphere. Imposing boundary conditions at the upper boundary that are different to the standard zero-gradient boundary condition is shown to reduce errors in the potential temperature and water vapor fields. Furthermore, the results show that there is a lowest possible model top elevation that should not be undercut to avoid influences of the model top on cloud and precipitation processes within the domain. The method to determine the lowest model top elevation is applied to both the idealized simulations and the real terrain case study. Notable differences between the ICAR and WRF simulations are observed across all investigated quantities such as the wind field, water vapor and hydrometeor distributions, and the distribution of precipitation. The case study indicates that the precipitation maximum calculated by the ICAR simulation employing the developed recommendations is spatially shifted upwind in comparison to an unmodified version of ICAR. The cause for the shift is found in influences of the model top on cloud formation and precipitation processes in the ICAR simulations. Furthermore, the results show that when model skill is evaluated from statistical metrics based on comparisons to surface observations only, such an analysis may not reflect the skill of the model in capturing atmospheric processes like gravity waves and cloud formation.

Wound area segmentation really progressed with the emergence of deep learning, due to its robustness in uncontrolled lighting and no need to design hand-crafted features but two limits have still to be overcome: firstly, its performance relies on the size and quality of the training dataset in the medical field, where data annotation is costly and time-consuming; secondly the accuracy of the segmentation depends highly on the camera distance and angle and moreover perspective effects prevent measuring real surfaces in single views. To address concurrently these two issues, we propose to apply multi-view modeling: an image sequence is acquired around the wound site and enables wound 3D reconstruction. Then, a segmentation step is run to extract roughly the wound from the background in each view and to select the best view with an original strategy. This view provides the most accurate segmentation and the real wound bed area even on non planar wounds. Finally, this segmentation is backprojected in each view to generate a complete set of well annotated real images to reinforce the learning step of the neural network. In our experiments, we compare several strategies to select the best view in the image sequence. The proposed method, tested on a dataset of 270 images, outperforms standard deep learning approach based on a single view, as recorded with DICE index and IoU score which rise respectively from 36.53% to 86.3% and 29.48% to 77.09% for the wound class to achieve an overall DICE and IoU score of 93.04% and 86.61% including background class. These results attest to the robustness of our method and its improved accuracy in the wound segmentation task.

Managing environmental risk is essential to ensure organisations minimise their impact on the environment, comply with environmental legislation and maintain their reputation in an increasingly environmentally aware society. Organisations frequently use management systems to plan and execute routine environmental assessments, however environmental impacts may still arise from routine activities or accidents that could be avoided by effective environmental management. Currently there is no method for an organisation to assess the level of awareness their employees have of activities that may lead to an environmental impact, or the level of uptake of environmental management processes. Therefore, the Environmental Management Performance Assessment (EMPA) process was developed to enable organisations to self-assess existing environmental management processes by survey of their employees. The EMPA process was aligned to key phases of the Deming Cycle and involves development and distribution of a survey to organisation employees. The responses are then used to recognise areas for improvement by progression through a bespoke flow chart integrated with the initial survey. This enables demonstration of how particular hazards arise from insufficient awareness at different stages in the Deming Cycle and how these hazards can have wider, reputational, economic, and legislative consequences. The process was trialled by surveying academic researchers on the environmental management processes in their laboratories as a sample set.

Accurate knowledge of snow depth distributions in mountain catchments is critical for applications in hydrology and ecology. Recently, a method was proposed to map snow depth at meter-scale resolution from very-high-resolution stereo satellite imagery (e.g., Pléiades) with an accuracy close to 0.5 m. However, the validation was limited to probe measurements and unmanned aircraft vehicle (UAV) photogrammetry, which sampled a limited fraction of the topographic and snow depth variability. We improve upon this evaluation using accurate maps of the snow depth derived from Airborne Snow Observatory laser-scanning measurements in the Tuolumne river basin, USA. We find a good agreement between both datasets over a snow-covered area of 138 km2 on a 3 m grid, with a positive bias for a Pléiades snow depth of 0.08 m, a root mean square error of 0.80 m and a normalized median absolute deviation (NMAD) of 0.69 m. Satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits at a typical scale of tens of meters. The random error at the pixel level is lower in snow-free areas than in snow-covered areas, but it is reduced by a factor of 2 (NMAD of approximately 0.40 m for snow depth) when averaged to a 36 m grid. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountain catchments.

Ice-nucleating particle (INP) measurements were performed in the boreal environment of southern Finland at the Station for Measuring Ecosystem–Atmosphere Relations (SMEAR II) in the winter–spring of 2018. Measurements with the Portable Ice Nucleation Chamber (PINC) were conducted at 242 K and 105 % relative humidity with respect to water. The median INP number concentration [INP] during a 6-week measurement period was 13 L−1. The [INP] spanned 3 orders of magnitude and showed a general increase from mid-February until early April. No single dominant local or regional sources of INPs in the boreal environment of southern Finland could be identified. Rather, it is hypothesised that the INPs detected at SMEAR II are a result of long-range transport and dilution of INPs sourced far from the measurement site. Despite high variability, the measured [INP] values fall within the range expected for the [INP] measured elsewhere under similar thermodynamic conditions. The [INP] did not correlate with any of the examined parameters during the entire field campaign, indicating that no one single parameter can be used to predict the [INP] at the measurement location during the examined time period. The absence of a correlation across the entire field campaign also suggests that a variety of particles act as INPs at different times, although it was indirectly determined that ambient INPs are most likely within the size range of 0.1–0.5 µm in diameter on average. On shorter timescales, several particle species correlated well with the [INP]. Depending on the meteorological conditions, black carbon (BC), supermicron biological particles and sub-0.1 µm particles, most likely nanoscale biological fragments such as ice-nucleating macromolecules (INMs), correlated with the INP signal. However, an increase in the concentration of any of these particle species may not necessarily lead to the increase in the [INP]; the reasons for this remain unknown. Limitations of the instrumental set-up and the necessity for future field INP studies are addressed.

Resumen: Antecedentes y objetivos: La enfermedad de Steinert o distrofia miotónica tipo 1 (DM1), (OMIM 160900) es la miopatía más prevalente en el adulto. Es una enfermedad multisistémica con alteración de prácticamente todos los órganos y tejidos y una variabilidad fenotípica muy amplia, lo que implica que deba ser atendida por diferentes especialistas que dominen las alteraciones más importantes. En los últimos años se ha avanzado de manera exponencial en el conocimiento de la enfermedad y en su manejo. El objetivo de la guía es establecer recomendaciones para el diagnóstico, el pronóstico, el seguimiento y el tratamiento de las diferentes alteraciones de la DM1. Material y métodos: Esta guía de consenso se ha realizado de manera multidisciplinar. Se ha contado con neurólogos, neumólogos, cardiólogos, endocrinólogos, neuropediatras y genetistas que han realizado una revisión sistemática de la literatura. Recomendaciones: Se recomienda realizar un diagnóstico genético con cuantificación precisa de tripletes CTG. Los pacientes con DM1 deben seguir control cardiológico y neumológico de por vida. Antes de cualquier cirugía con anestesia general debe realizarse una evaluación respiratoria. Debe monitorizarse la presencia de síntomas de disfagia periódicamente. Debe ofrecerse consejo genético a los pacientes con DM1 y a sus familiares. Conclusión: La DM1 es una enfermedad multisistémica que requiere un seguimiento en unidades especializadas multidisciplinares. Abstract: Background and objectives: Steinert's disease or myotonic dystrophy type 1 (MD1), (OMIM 160900), is the most prevalent myopathy in adults. It is a multisystemic disorder with dysfunction of virtually all organs and tissues and a great phenotypical variability, which implies that it has to be addressed by different specialities with experience in the disease. The knowledge of the disease and its management has changed dramatically in recent years. This guide tries to establish recommendations for the diagnosis, prognosis, follow-up and treatment of the complications of MD1. Material and methods: Consensus guide developed through a multidisciplinary approach with a systematic literature review. Neurologists, pulmonologists, cardiologists, endocrinologists, neuropaediatricians and geneticists have participated in the guide. Recommendations: The genetic diagnosis should quantify the number of CTG repetitions. MD1 patients need cardiac and respiratory lifetime follow-up. Before any surgery under general anaesthesia, a respiratory evaluation must be done. Dysphagia must be screened periodically. Genetic counselling must be offered to patients and relatives. Conclusion: MD1 is a multisystemic disease that requires specialised multidisciplinary follow-up. Palabras clave: Guía clínica, Enfermedad de Steinert, Distrofia miotónica tipo 1, Complicaciones, Recomendaciones, Disfagia, Keywords: Clinical guideline, Steinert's disease, Myotonic dystrophy type 1, Complications, Recommendations, Dysphagia

Background and objectives: Steinert's disease or myotonic dystrophy type 1 (MD1), (OMIM 160900), is the most prevalent myopathy in adults. It is a multisystemic disorder with dysfunction of virtually all organs and tissues and a great phenotypical variability, which implies that it has to be addressed by different specialities with experience in the disease. The knowledge of the disease and its management has changed dramatically in recent years. This guide tries to establish recommendations for the diagnosis, prognosis, follow-up and treatment of the complications of MD1. Material and methods: Consensus guide developed through a multidisciplinary approach with a systematic literature review. Neurologists, pulmonologists, cardiologists, endocrinologists, neuropaediatricians and geneticists have participated in the guide. Recommendations: The genetic diagnosis should quantify the number of CTG repetitions. MD1 patients need cardiac and respiratory lifetime follow-up. Before any surgery under general anaesthesia, a respiratory evaluation must be done. Dysphagia must be screened periodically. Genetic counselling must be offered to patients and relatives. Conclusion: MD1 is a multisystemic disease that requires specialised multidisciplinary follow-up. Resumen: Antecedentes y objetivos: La enfermedad de Steinert o distrofia miotónica tipo 1 (DM1), (OMIM 160900) es la miopatía más prevalente en el adulto. Es una enfermedad multisistémica con alteración de prácticamente todos los órganos y tejidos y una variabilidad fenotípica muy amplia, lo que implica que deba ser atendida por diferentes especialistas que dominen las alteraciones más importantes. En los últimos años se ha avanzado de manera exponencial en el conocimiento de la enfermedad y en su manejo. El objetivo de la guía es establecer recomendaciones para el diagnóstico, el pronóstico, el seguimiento y el tratamiento de las diferentes alteraciones de la DM1. Material y métodos: Esta guía de consenso se ha realizado de manera multidisciplinar. Se ha contado con neurólogos, neumólogos, cardiólogos, endocrinólogos, neuropediatras y genetistas que han realizado una revisión sistemática de la literatura. Recomendaciones: Se recomienda realizar un diagnóstico genético con cuantificación precisa de tripletes CTG. Los pacientes con DM1 deben seguir control cardiológico y neumológico de por vida. Antes de cualquier cirugía con anestesia general debe realizarse una evaluación respiratoria. Debe monitorizarse la presencia de síntomas de disfagia periódicamente. Debe ofrecerse consejo genético a los pacientes con DM1 y a sus familiares. Conclusión: La DM1 es una enfermedad multisistémica que requiere un seguimiento en unidades especializadas multidisciplinares.

La investigación se realizó en la Estación Experimental de Kallutaca, de la Carrera de Ingeniería Agronómica, ubicada en el municipio de Laja, en el departamento de La Paz, en un periodo de 9 semanas. La necesidad de encontrar fuentes alternativas para la producción de cuyes, justifica el uso de aditivos y suplementos para la elaboración de raciones, bajo este efecto surge el principal objetivo de evaluar el comportamiento productivo de la crianza de cuyes (Cavia aparea porcellus), bajo el efecto de tres niveles de cuy-pack en la dieta alimenticia, durante las etapas de crecimiento y engorde. Para el presente estudio se emplearon 64 cuyes, distribuidos en un diseño completo al azar con arreglo factorial. Factor A niveles de cuy-pack y factor B sexo (macho y hembra). Los resultados muestran que el cuy-pack no incide sobre el consumo efectivo de alimento. La mejor conversión alimenticia se registró en el tratamiento T3 con 4.30 g g-1, el factor sexo presenta una mejor asimilación de la ración balanceada en hembras con 5.34 g g-1. La mayor ganancia media diaria registró el tratamiento T3, con una velocidad de crecimiento de 5.86 g día-1. En relación a ganancia de peso acumulado, el tratamiento T3 alcanzó una ganancia de 376.17 g. El mejor rendimiento a la canal muestra del tratamiento T3 con 68.22 %, donde los machos presentan un mayor rendimiento a la canal con 67.21 %. El nivel 0.60 % de cuy-pack es recomendable para la aplicación en la ración alimenticia de cuyes.

As part of the Copernicus Marine Environment Monitoring Service (CMEMS), a physical–biogeochemical coupled model system has been developed to monitor and forecast the ocean dynamics and marine ecosystem of the European waters and more specifically on the Iberia–Biscay–Ireland (IBI) area. The CMEMS IBI coupled model covers the north-east Atlantic Ocean from the Canary Islands to Iceland, including the North Sea and the western Mediterranean, with a NEMO-PISCES 1∕36∘ model application. The coupled system has been providing 7 d weekly ocean forecasts for CMEMS since April 2018. Prior to its operational launch, a pre-operational qualification simulation (2010–2016) has allowed assessing the model's capacity to reproduce the main biogeochemical and ecosystem features of the IBI area. The objective of this paper is then to describe the consistency and skill assessment of the PISCES biogeochemical model using this 7-year qualification simulation. The model results are compared with available satellite estimates as well as in situ observations (ICES, EMODnet and BGC-Argo). The simulation successfully reproduces the spatial distribution and seasonal cycles of oxygen, nutrients, chlorophyll a and net primary production, and confirms that PISCES is suitable at such a resolution and can be used for operational analysis and forecast applications. This model system can be a useful tool to better understand the current state and changes in the marine biogeochemistry of European waters and can also provide key variables for developing indicators to monitor the health of marine ecosystems. These indicators may be of interest to scientists, policy makers, environmental agencies and the general public.

This paper presents a numerical study of the oscillations (or recurrences) of tropospheric ozone depletion events (ODEs) using the further-developed one-dimensional KInetic aNALysis of reaction mechanics with Transport (KINAL-T) chemistry transport model. Reactive bromine is the major contributor to the occurrence of ODEs. After the termination of an ODE, the reactive bromine in the air is deposited onto aerosols or on the snow surface, and the ozone may regenerate via NOx-catalyzed photochemistry or by turbulent transport from the free troposphere into the boundary layer. The replenished ozone then is available for the next cycle of autocatalytic bromine release (bromine explosion) leading to another ODE. The oscillation periods are found to be as short as 5 d for the purely chemically NOx-driven oscillation and 30 d for a diffusion-driven oscillation. An important requirement for oscillation of ODEs to occur is found to be a sufficiently strong inversion layer. In a parameter study, the dependence of the oscillation period on the nitrogen oxides' concentration, the inversion layer strength, the ambient temperature, the aerosol density, and the solar radiation is investigated. Parameters controlling the oscillation of ODEs are discussed.

The coarse grid spacing of global circulation models necessitates the application of downscaling techniques to investigate the local impact of a changing global climate. Difficulties arise for data-sparse regions in complex topography, as they are computationally demanding for dynamic downscaling and often not suitable for statistical downscaling due to the lack of high-quality observational data. The Intermediate Complexity Atmospheric Research (ICAR) model is a physics-based model that can be applied without relying on measurements for training and is computationally more efficient than dynamic downscaling models. This study presents the first in-depth evaluation of multiyear precipitation time series generated with ICAR on a 4×4 km2 grid for the South Island of New Zealand for an 11-year period, ranging from 2007 to 2017. It focuses on complex topography and evaluates ICAR at 16 weather stations, 11 of which are situated in the Southern Alps between 700 and 2150mm.s.l (m m.s.l refers to meters above mean sea level). ICAR is assessed with standard skill scores, and the effect of model top elevation, topography, season, atmospheric background state and synoptic weather patterns on these scores are investigated. The results show a strong dependence of ICAR skill on the choice of the model top elevation, with the highest scores obtained for 4 km above topography. Furthermore, ICAR is found to provide added value over its ERA-Interim reanalysis forcing data set for alpine weather stations, improving the median of mean squared errors (MSEs) by 30 % and up to 53 %. It performs similarly during all seasons with a MSE minimum during winter, while flow linearity and atmospheric stability are found to increase skill scores. ICAR scores are highest during weather patterns associated with flow perpendicular to the Southern Alps and lowest for flow parallel to the alpine range. While measured precipitation is underestimated by ICAR, these results show the skill of ICAR in a real-world application, and may be improved upon by further observational calibration or bias correction techniques. Based on these findings ICAR shows the potential to generate downscaled fields for long-term impact studies in data-sparse regions with complex topography.

The rationale for using multi-model ensembles in climate change projections and impacts research is often based on the expectation that different models constitute independent estimates; therefore, a range of models allows a better characterisation of the uncertainties in the representation of the climate system than a single model. However, it is known that research groups share literature, ideas for representations of processes, parameterisations, evaluation data sets and even sections of model code. Thus, nominally different models might have similar biases because of similarities in the way they represent a subset of processes, or even be near-duplicates of others, weakening the assumption that they constitute independent estimates. If there are near-replicates of some models, then treating all models equally is likely to bias the inferences made using these ensembles. The challenge is to establish the degree to which this might be true for any given application. While this issue is recognised by many in the community, quantifying and accounting for model dependence in anything other than an ad-hoc way is challenging. Here we present a synthesis of the range of disparate attempts to define, quantify and address model dependence in multi-model climate ensembles in a common conceptual framework, and provide guidance on how users can test the efficacy of approaches that move beyond the equally weighted ensemble. In the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6), several new models that are closely related to existing models are anticipated, as well as large ensembles from some models. We argue that quantitatively accounting for dependence in addition to model performance, and thoroughly testing the effectiveness of the approach used will be key to a sound interpretation of the CMIP ensembles in future scientific studies.

Introduction The relevance of studying the characteristics of the home environment of a person with mental health problems is determined by the need to identify the resources of the individual and the family to form multilevel adaptive competencies aimed at maintaining mental health. Objectives The present study was conducted to obtain standardized assessments of attitudes towards the home environment, towards the home as a place of functioning of the family with mental patients. Methods The study involved 12 patients aged 21-60 years diagnosed according to ICD-10 F2 with the disease duration of more than 1 year and readmission. Methods used were experimental psychological questionnaire “My home” (Reznichenko, Nartova-Bochaver, Kuznetsova, 2016), mathematical statistics Results The test results showed that the average score for the “strength of significance of the home for its inhabitants” across the data set was 4.14, which differed from the average value of 3.73. Conclusions The psychological foundations of attachment can be associated with a variety of facts, including the frequent absence of patients outside the home environment during readmission periods. The home environment can be a complex of positive feelings and experiences in relation to the home as a personally significant place. The study revealed some of the psychological traits of the subjective attitude to home, which can become indicators of psychological adaptation in persons with mental disorders in the future. Reznichenko S.I., Nartova-Bochaver S.K., Kuznetsova V.B. (2016) Home Attachment Assessment Method. Psychology. Journal of the Higher School of Economics. 13(3): 498-518. Disclosure No significant relationships.