The value-add of tailored seasonal forecast information for industry decision-making

There is a growing need for more systematic, robust and comprehensive in-formation on the value-add of climate services from both the demand and supply sides. There is a shortage of published value-add assessments which focus on the decision-making context, involve participatory or co-evaluation approaches, avoid over-simplification and address both the quantitative (e.g. economic) and qualitative (e.g. social) value of climate services. The twelve case studies which formed the basis of the European Union-funded SECLI-FIRM project were co-designed by industrial and research partners in order to address these gaps, focusing on the use of tailored sub-seasonal and seasonal forecasts in the energy and water industries. For eight of these case studies it was pos-sible to apply quantitative economic valuation methods: econometric modelling was used for five case studies while three case studies used both cost-loss (relative economic value) analysis and avoided costs. The case studies illustrate the challenges in attempting to produce quantitative estimates of the economic value add of these forecasts. At the same time, many of them highlight how practical value for users – transcending the actual economic value – can be enhanced, for example, through the provision of climate services as an exten-sion to their current use of weather forecasts and with the visualisation tailored towards the user

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Waste processing: New near infrared technologies for material identification and selection

The awareness of environmental issues on a global scale increases the opportunities for waste handling companies. Recovery is set to become all the more important in areas such as waste selection, minerals processing, electronic scrap, metal and plastic recycling, refuse and the food industry. Effective recycling relies on effective sorting. Sorting is a fundamental step of the waste disposal/recovery process. The big players in the sorting market are pushing for the development of new technologies to cope with literally any type of waste. The purpose of this tutorial is to gain an understanding of waste management, frameworks, strategies, and components that are current and emerging in the field. A particular focus is given to spectroscopic techniques that pertains the material selection process with a greater emphasis placed on the NIR technology for material identification. Three different studies that make use of NIR technology are shown, they are an example of some of the possible applications and the excellent results that can be achieved with this technique

WASTE IDENTIFICATION AND SELECTION BY MEANS OF HIPERSPECTRAL NIR TECHNOLOGY

Recovered wood becomes more and more important for the production of wood-base panels. The increasing demand resulted in the need to improve the cleaning process of post-consumer material, eliminating in a more effective and efficient way plastic impurities. We have developed a new method that takes advantages of the NIR spectral images to identify different classes of materials present in wood waste. We have investigated the spectrum of a wide sample of materials as plastics, ceramics, tiles, woods, laminates in the range 1100 - 2500 nm. We found those features that characterized the different classes of materials and searched for those spectral regions able to distinguish them. We have studied the correlation among the various features that characterize the classes and the spectral bands potentially most effective in the discrimination process have been identified. We defined different indices able to distinguish among different materials. The developed classification method shows that the near infrared spectral analysis can be used as an efficient technique to identify different objects facilitating rapid and accurate separation process

Near infrared technology for material identification and selection

The increasing demand for recycled wood to produce particleboard and MDF panels has resulted in the need to improve the cleaning process of post-consumer material, eliminating in a more effective and efficient way plastic impurities. We have developed a new method based on the NIR diffuse reflectance spectral analysis for the identification of different classes of materials that can be used in the selection process. We have investigated the diffuse reflected light in the range 1100 - 2500 nm of a wide sample of materials including plastics, ceramics, tiles, woods and laminates as representative of garbage dump materials. We have considered the typical features of the different classes of materials and looked for those spectral regions that present some difference among the classes. We have studied the correlation among the various features characterizing the spectra of each class and identifying the spectral bands potentially most effective in the discrimination process. Accordingly, six indices able to distinguish different materials have been defined. The results show that the near infrared spectral analysis can be used as an efficient analytical technique to identify different objects facilitating rapid separation process

WOOD RECYCLING BY NIR TECHNOLOGY

The recycling of waste wood has become increasingly important during the last few decades. The use of recovered wood varies among the countries and in Italy, the percentage of recovered wood used for particleboard production, reached the 89%. Anyway, to use recycled wood to produce MDF panels or energy we need to improve the cleaning process of post-consumer material, eliminating in a more effective and efficient way plastic impurities. We first studied in laboratory a wide sample of objects representative of wood garbage dump materials and we developed a new near infrared spectral method for materials identification and selection. We developed a pilot system for the automated online sorting of high volumes of waste wood to which we applied the new method. The material sorter is equipped with a Hyperspectral Imaging Spectroscopy (HIS) system, a conveyor and the processing system we tested. We present the approach and the first results of the identification and selection process

Short-chain fatty acids promote the effect of environmental signals on the gut microbiome and metabolome in mice

Gut microorganisms and the products of their metabolism thoroughly affect host brain development, function and behavior. Since alterations of brain plasticity and cognition have been demonstrated upon motor, sensorial and social enrichment of the housing conditions, we hypothesized that gut microbiota and metabolome could be altered by environmental stimuli, providing part of the missing link among environmental signals and brain effects. In this preliminary study, metagenomic and metabolomic analyses of mice housed in different environmental conditions, standard and enriched, identify environment-specific microbial communities and metabolic profiles. We show that mice housed in an enriched environment have distinctive microbiota composition with a reduction in gut bacterial richness and biodiversity and are characterized by a metabolomic fingerprint with the increase of formate and acetate and the decrease of bile salts. We demonstrate that mice treated with a mixture of formate and acetate recapitulate some of the brain plasticity effects modulated by environmental enrichment, such as hippocampal neurogenesis, neurotrophin production, short-term plasticity and cognitive behaviors, that can be further exploited to decipher the mechanisms involved in experience-dependent brain plasticity

The Relationship between Country of Residence, Gender and the Quality of Life in Australian and Taiwanese Midlife Residents

midlife men and women, multi-cultural quality of life research, probability proportional sampling,

Proposal of MUAC as a fast tool to monitor pregnancy nutritional status: results from a cohort study in Brazil

Objective In Brazil, although the assessment of maternal nutritional status is recommended using body mass index (BMI), this is only possible in settings adequately prepared. Midupper arm circumference (MUAC) is another biological variable identified as a tool for rapid assessment of nutritional status that is correlated with BMI. Therefore, we aim to surrogate BMI by MUAC cut-offs for rapid screening of maternal nutritional status starting at midpregnancy.Design Analysis of the multicentre cohort study entitled ‘Preterm SAMBA’ using an approach of validation of diagnostic test.Setting Outpatient prenatal care clinics from five tertiary maternity hospitals from three different Brazilian regions.Participants 1165 pregnant women attending prenatal care services from 2015 to 2018 and with diverse ethnic characteristics who were enrolled at midpregnancy and followed in three visits at different gestational weeks.Primary and secondary outcome measures Sensitivity, specificity, positive and negative predictive values, likelihood ratio and accuracy of MUAC being used instead of BMI for the assessment of nutritional status of women during pregnancy.Results We found a strong correlation between MUAC and BMI, in the three set points analysed (r=0.872, 0.870 and 0.831, respectively). Based on BMI categories of nutritional status, we estimated the best MUAC cut-off points, finding measures according to each category: underweight <25.75 cm (19–39 weeks); overweight 28.11–30.15 cm (19–21 weeks), 28.71–30.60 cm (27–29 weeks) and 29.46–30.25 cm (37–39 weeks); and obese >30.15 cm (19–21 weeks), >30.60 cm (27–29 weeks) and >30.25 cm (37–39 weeks) per gestational week. Therefore, we defined as adequate between 25.75–28.10 cm (19–21 weeks), 25.75–28.70 cm (27–29 weeks) and 25.75–29.45 cm (37–39 weeks) of MUAC.Conclusion We conclude that MUAC can be useful as a surrogate for BMI as a faster screening of nutritional status in pregnant women