Heuristic Methodology for Forecasting of Production in Waste Management

The forecast of waste production and disposal is an important requirement for a future waste management planning. The problem is very often a short time series of the database. This paper suggests an approach to forecast the production of multiple waste types in micro-regions taking into account this challenge by combining many techniques. The heuristic methodology consisting of few steps is formulated. First, the input data are transformed and the methods from cluster analysis are repetitively applied. The second step is  about a determination of quality for trend functions based on historical data. In the last step is performed the  testing. The di erent type of representatives from cluster analysis is used to calculate indices of determination which are compared. This procedure is repeated until the criteria hit. The proposed approach reduced the  computational time and managed to aggregate micro-regions with a similar trend. The forecast should have contributions in terms of building new facilities or adaptations to the existing ones, where it is necessary to estimate the production of waste for several years in advance. The article includes a case study of production forecast for several waste types in territorial units of the Czech Republic. The forecast is based on data in years 2009{2014 and following year 2015 was used to assess the quality of the nal models. In the future, the database will expand and thus it will be possible to make more precise estimates and to develop statistical methods to measure this prognostic tool

Mass absorption cross-section and absorption enhancement from long term black and elemental carbon measurements: A rural background station in Central Europe

Black carbon (BC) is a dominant aerosol light absorber, and its brown carbon (BrC) coating can enhance absorption and lead to uncertainties concerning the radiative forcing estimation. This study investigates the mass absorption cross-section of equivalent BC (MAC(eBC)) during a long-term field measurement (2013-2017) at a rural Central European site. The MAC enhancement factor (E-abs) and the contribution of BrC coatings to the absorption coefficient (B-abs) were estimated by combining different approaches. The annual mean B-abs and MAC(eBC) values decreased slightly over the measurement period associated with change in the submicron aerosol size distribution. Regardless of the wavelength, B-abs exhibited clear seasonal and diurnal variations, with higher values in winter when a higher absorption Angstromexponent (1.4) was observed due to the local biomass burning (BB). In contrast, MACeBC did not have a distinct temporal trend at 600 nm (7.84 +/- 2.79 m(2) g(-1)), while it showed a seasonal trend at 370 nm with higher values in winter (15.64 +/- 4.77 m(2) g(-1)). During this season, E-abs_(660) was 1.18 +/- 0.27 and did not exhibit any clear wavelength dependence, despite the influence of BB. During the study period, BrC-attributed absorption was observed in 31% of the samples, with a contribution of up to 40% of total Babs. In summer, the E-abs_(660) increased to 1.59 +/- 0.60, when a larger BC coating could be formed by secondary aerosol fractions. During this season, MAC(eBC)_ (660) and E-abs_(660) showed comparable source profiles that were mainly associated with aged air masses over central Europe, thereby supporting the fact that characteristics of coating materials formed during atmospheric aging are a major factor driving the MAC(eBC)_(660) measured at the regional background site. Further field investigations of the composition of BC coatings would help to better understand and estimate uncertainties related to the radiative effect of aerosols

Detection of virgin olive oil adulteration using low field unilateral NMR

The detection of adulteration in edible oils is a concern in the food industry, especially for the higher priced virgin olive oils. This article presents a low field unilateral nuclear magnetic resonance (NMR) method for the detection of the adulteration of virgin olive oil that can be performed through sealed bottles providing a non-destructive screening technique. Adulterations of an extra virgin olive oil with different percentages of sunflower oil and red palm oil were measured with a commercial unilateral instrument, the profile NMR-Mouse. The NMR signal was processed using a 2-dimensional Inverse Laplace transformation to analyze the transverse relaxation and self-diffusion behaviors of different oils. The obtained results demonstrated the feasibility of detecting adulterations of olive oil with percentages of at least 10% of sunflower and red palm oils

Cholesterol modulates presynaptic and postsynaptic properties of excitatory synaptic transmission

Cholesterol is a structural component of cellular membranes particularly enriched in synapses but its role in synaptic transmission remains poorly understood. We used rat hippocampal cultures and their acute cholesterol depletion by methyl-β-cyclodextrin as a tool to describe the physiological role of cholesterol in glutamatergic synaptic transmission. Cholesterol proved to be a key molecule for the function of synapses as its depletion resulted in a significant reduction of both NMDA receptor (NMDAR) and AMPA/kainate receptor-mediated evoked excitatory postsynaptic currents (eEPSCs), by 94% and 72%, respectively. We identified two presynaptic and two postsynaptic steps of synaptic transmission which are modulated by cholesterol and explain together the above-mentioned reduction of eEPSCs. In the postsynapse, we show that physiological levels of cholesterol are important for maintaining the normal probability of opening of NMDARs and for keeping NMDARs localized in synapses. In the presynapse, our results favour the hypothesis of a role of cholesterol in the propagation of axonal action potentials. Finally, cholesterol is a negative modulator of spontaneous presynaptic glutamate release. Our study identifies cholesterol as an important endogenous regulator of synaptic transmission and provides insight into molecular mechanisms underlying the neurological manifestation of diseases associated with impaired cholesterol synthesis or decomposition

Statistical Evaluation of Large-Scale Data Logistics System

Data recording is struggling with the occurrence of errors, which worsen the accuracy of follow-up calculations. Achievement of satisfactory results requires the data processing to eliminate the influence of errors. This paper applies a data reconciliation technique for mining of data from ecording movement vehicles. The database collects information about the start and end point of the route (GPS coordinates) and total duration. The presented methodology smooths available data and allows to obtain an estimation of transportation time through individual parts of the entire recorded route. This process allows obtaining valuable information which can be used for further transportation planning. First, the proposed mathematical model is tested on simplifled example. The real data application requires necessary preprocessing within which anticipated routes are designed. Thus, the database is supplemented with information on the probable speed of the vehicle. The mathematical model is based on weighted least squares data reconciliation which is organized iteratively. Due to the time-consuming calculation, the linearised model is computed to initialize the values for a complex model. The attention is also paid to the weight setting. The weighing system is designed to reflect the quality of specific data and the dependence on the frequency of trafic. In this respect, the model is not strict, which leaves the possibility to adapt to the current data. The case study focuses on the GPS data of shipping vehicles in the particular city in the Czech Republic with several types of roads

Design and Decomposition of Waste Prognostic Model with Hierarchical Structures

The waste management is a dynamically progressive area, with the current trend leading to circular economy scheme. The development in this area requires quality prognosis reflecting the analysed timeframe. The forecast of the waste production and composition of waste is an important aspect with regards to the planning in waste management. However, the regular prognostic methods are not appropriate for these purposes due to short time series of historical data and unavailability of socio-economic data. The paper proposes a general approach via mathematical model for forecasting of future waste-related parameters based on spatially distributed data with hierarchical structure. The approach is based on principles of regression analysis with final balance to ensure the compliance of aggregated data values. The selection of the regression function is a part of mathematical model for high-quality description of data trend. In addition, outlier values are cleared, which occur abundantly in the database. The decomposition of the model into subtasks is performed in order to simpler implementation and reasonable time solvability. The individual algorithm steps are applied to municipal waste production data in the Czech Republic

Strong Inhibitory Effect, Low Cytotoxicity and High Plasma Stability of Steroidal Inhibitors of N-Methyl-D-Aspartate Receptors With C-3 Amide Structural Motif

Herein, we report the synthesis, structure-activity relationship study, and biological evaluation of neurosteroid inhibitors of N-methyl-D-aspartate receptors (NMDARs) receptors that employ an amide structural motif, relative to pregnanolone glutamate (PAG) – a compound with neuroprotective properties. All compounds were found to be more potent NMDAR inhibitors (IC50 values varying from 1.4 to 21.7 μM) than PAG (IC50 = 51.7 μM). Selected compound 6 was evaluated for its NMDAR subtype selectivity and its ability to inhibit AMPAR/GABAR responses. Compound 6 inhibits the NMDARs (8.3 receptors (8.3 ± 2.1 μM) more strongly than it does at the GABAR and AMPARs (17.0 receptors (17.0 ± 0.2 μM and 276.4 ± 178.7 μM, respectively). In addition, compound 6 (10 μM) decreases the frequency of action potentials recorded in cultured hippocampal neurons. Next, compounds 3, 5–7, 9, and 10 were not associated with mitotoxicity, hepatotoxicity nor ROS induction. Lastly, we were able to show that all compounds have improved rat and human plasma stability over PAG

Metal Oxide Sensors for Electronic Noses and Their Application to Food Analysis

Electronic noses (E-noses) use various types of electronic gas sensors that have partial specificity. This review focuses on commercial and experimental E-noses that use metal oxide semi-conductors. The review covers quality control applications to food and beverages, including determination of freshness and identification of contaminants or adulteration. Applications of E-noses to a wide range of foods and beverages are considered, including: meat, fish, grains, alcoholic drinks, non-alcoholic drinks, fruits, milk and dairy products, olive oils, nuts, fresh vegetables and eggs