Mixed-method approach incorporating Geographic information system (GIS) tools for optimizing collection costs and convenience of the biowaste separate collection.

Nowadays, dealing with organic waste (or biowaste) remains a global phenomenon. Especially developing countries worldwide generate more than 50 percent organicwaste. In the European Union (EU) with a share of 34%, biowaste is a dominantfraction of the municipal waste (EEA, 2020). Therefore, separate collection at source and environmentally sound treatment of biowaste are of key importance. An intensive optimisation of biowaste separate collection is needed to balance demands of municipal representatives and households' needs. Based on the mixed-method approach we developed a MCDA model complemented by expert-based weighting assessment and combined with the GIS localisation tools aimed at the optimisation of biowaste container locations that reflects various spatial conditions, preconditions for the localisation of containers and its cost intensity. We concluded that changing the density of containers, distance between the address point and container, and selecting container locations that respect the habits of households and demands of the collection technology significantly affect the total and collection costs. We confirmed that the decreases in the total costs were not significant for maximum walking distances of over 95 m, and would approach zero for distances of over 230 m. When the maximum walking distance exceeds 268 m, 40% of all inhabitants would not participate in the system as it would be inconvenient for them. A recycling campaign is needed to increase their willingness to participate in the system. We provided arguments for decision-makers how to balance convenience of the biowaste separation system and collection costs by proper localisation of biowaste containers.

Predictive modelling as a tool for effective municipal waste management policy at different territorial levels.

Nowadays, the European municipal waste management policy based on the circular economy paradigm demands the closing of material and financial loops at all territorial levels of public administration. The effective planning of treatment capacities (especially sorting plants, recycling, and energy recovery facilities) and municipal waste management policy requires an accurate prognosis of municipal waste generation, and therefore, the knowledge of behavioral, socio-economic, and demographic factors influencing the waste management (and recycling) behavior of households, and other municipal waste producers. To enable public bodies at different territorial levels to undertake an effective action resulting in circular economy we evaluated various factors influencing the generation of municipal waste fractions at regional, micro-regional and municipal level in the Czech Republic. Principal components were used as input for traditional models (multivariable linear regression, generalized linear model) as well as tree-based machine learning models (regression trees, random forest, gradient boosted regression trees). Study results suggest that the linear regression model usually offers a good trade-off between model accuracy and interpretability. When the most important goal of the prediction is supposed to be accuracy, the random forest is generally the best choice. The quality of developed models depends mostly on the chosen territorial level and municipal waste fraction. The performance of these models deteriorates significantly for lower territorial levels because of worse data quality and bigger variability. Only the age structure seems to be important across territorial levels and municipal waste fractions. Nevertheless, also other factors are of high significance in explaining the generation of municipal waste fractions at different territorial levels (e.g. number of economic subjects, expenditures, population density and the level of education). Therefore, there is not one single effective public policy dealing with circular economy strategy that fits all territorial levels. Public representatives should focus on policies effective at specific territorial level. However, performance of the models is poor for lower territorial levels (municipality and micro-regions). Thus, results for municipalities and micro-regions are weak and should be treated as such.

Possible consequences of Covid-19 on the nervous system.

OBJECTIVES: The aim of the survey was to find out what the possible consequences are of the COVID-19 disease on the nervous system and to propose a method of using artificial intelligence. MATERIAL AND METHODS: Recent research has shown that the risks to patients due to severe acute coronavirus 2 respiratory syndrome (SARS-COV-2) differ most significantly depending on age and the presence of underlying comorbidities such as: cardiovascular disease, hypertension, diabetes and others. The consequences of COVID-19 on the nervous system are especially important. We performed a detailed selection of articles describing the effects of COVID-19 on the nervous system. RESULTS: We made a clear summary of the main consequences of COVID-19 on the nervous system and suggested a way to use artificial intelligence. CONCLUSION: We confirmed research that artificial intelligence methods have the potential to accelerate prediction, especially for the possible consequences of COVID-19 on the nervous system.

Multi-Electrode Array with a Planar Surface for Cell Patterning by Microprinting.

Multielectrode arrays (MEAs) are devices for non-invasive electrophysiological measurements of cell populations. This paper describes a novel fabrication method of MEAs with a fully planar surface. The surface of the insulation layer and the surface of the electrodes were on one plane; we named this device the planar MEA (pMEA). The main advantage of the pMEA is that it allows uniform contact between the pMEA surface and a substrate for positioning of microfluidic channels or microprinting of a cell adhesive layer. The fabrication of the pMEA is based on a low adhesive Au sacrificial peel-off layer. In divergence from conventional MEAs with recessed electrodes, the electrodes of the pMEA lead across the sloped edge of the insulation layer. To make this, the profile of the edge of the insulation layer was measured and the impedance of the planar electrodes was characterized. The impedance of the pMEA was comparable with the impedance of conventional MEA electrodes. The pMEA was tested for patterning HL-1 cells with a combination of imprinting fibronectin and coating by antifouling poly (l-lysine)-graft-poly(ethylene glycol) (PLL-g-PEG). The HL-1 cells remained patterned even at full confluency and presented spontaneous and synchronous beating activity.

The influence of mode of anaesthesia for caesarean delivery on neonatal Apgar scores in the Czech Republic and Slovakia: secondary analysis of the results of an international survey in 2015.

AIMS: The purpose of this international survey was to describe the impact of current practices and techniques of caesarean section on the neonatal Apgar score in the Czech Republic (CZE) and Slovakia (SVK). METHODS: All Czech and Slovak departments that provide obstetric anaesthesia were invited to participate in a one-month (November 2015) prospective study that monitored in details all peripartum anaesthetic practices, delivered by anaesthesiologists. Participating centers recorded all data on-line in the CLADE-IS database (Masaryk University, CZE). RESULTS AND DISCUSSIONS: We collected data of 10119 women who delivered 10226 newborns. A caesarean section was recorded in 25.1% of deliveries (CZE 23.2%; SVK 30%). General anaesthesia was used for caesarean section in 37.5% of the cases (CZE 40%, SVK 33%). There was no statistically significant difference in the Apgar score lower than 7 in the 1, 5 or 10 min in groups of general and regional anaesthesia for caesarean section, when only elective sections of in-term babies with birth weight over 2500 g were analyzed. We found no statistically significant differences in the Apgar score in newborns of women intubated for caesarean section in rocuronium (n=21; 2.2%) and suxamethonium (n=889; 93%). CONCLUSION: We found no difference in neonatal outcomes in groups of general and regional anaesthesia for caesarean section when only out-of-risk newborns were analyzed. The risk factors were identified as follows: an acute caesarean section, preterm babies, birth weight less than 2 500 g, born in perinatological center and multiple pregnancy - second baby. TRIAL REGISTRATION: ClinicalTrials.gov (ID: NCT02380586) https://clinicaltrials.gov/ct2/show/NCT02380586.

A Miniaturized Colorimeter with a Novel Design and High Precision for Photometric Detection.

Water quality detection plays an increasingly important role in environmental protection. In this work, a novel colorimeter based on the Beer-Lambert law was designed for chemical element detection in water with high precision and miniaturized structure. As an example, the colorimeter can detect phosphorus, which was accomplished in this article to evaluate the performance. Simultaneously, a modified algorithm was applied to extend the linear measurable range. The colorimeter encompassed a near infrared laser source, a microflow cell based on microfluidic technology and a light-sensitive detector, then Micro-Electro-Mechanical System (MEMS) processing technology was used to form a stable integrated structure. Experiments were performed based on the ammonium molybdate spectrophotometric method, including the preparation of phosphorus standard solution, reducing agent, chromogenic agent and color reaction. The device can obtain a wide linear response range (0.05 mg/L up to 7.60 mg/L), a wide reliable measuring range up to 10.16 mg/L after using a novel algorithm, and a low limit of detection (0.02 mg/L). The size of flow cell in this design is 18 mm × 2.0 mm × 800 µm, obtaining a low reagent consumption of 0.004 mg ascorbic acid and 0.011 mg ammonium molybdate per determination. Achieving these advantages of miniaturized volume, high precision and low cost, the design can also be used in automated in situ detection.