Layer-by-layer self-assembly of multifunctional enzymatic UF membranes

In order to eliminate membrane fouling and to ensure enzymatic hydrolysis of urea, multifunctional biocatalytic membranes were prepared by using urease (URE) and trypsin (TRY) enzymes on the sulfonated polysulfone (SPSf) ultrafiltration membrane via layer-by-layer (LbL) self-assembly method. The membrane architecture consisted of multilayer assembly with TRY and URE enzymes as the outer layer and inner sandwiched layer, respectively. Polyethyleneimine (PEI) and alginate (ALG) were used as cationic and anionic polyelectrolytes. Sulfonation and PEI deposition were successfully accomplished as confirmed by attenuated total reflectance Fourier transform infrared spectroscopy, differential scanning calorimetry (DSC) and scanning electron microscopy analysis, contact angle measurements, staining with toluidine blue and Congo red dyes and dead-end filtration experiments. A characteristic value of SPSf membrane with a high water permeability (1000 L/m².h.bar) and 95% bovine serum albumin (BSA) rejection was observed. In static conditions, URE activities of SPSf2-PEI-URE membrane were not affected by BSA fouling, while TRY immobilizations with increased concentrations (SPSf2-PEI-URE-PEI-ALG-TRY) significantly lowered the activity of URE. In dynamic conditions, each deposited layer exhibited individual resistance to flow that can be considered as irreversible fouling and caused 90% of flux decline for the SPSf2-PEI-URE-PEI-ALG-TRY membrane assembly. The recovery of the initial flux for the multilayered membrane at the end of six fouling and washing cycles was observed 85%. Moreover, at the end of 5 cycles, 78% of the URE initial activity of the multilayered membrane was preserved. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48750.     

Estimating crown diameters in urban forests with Unmanned Aerial System-based photogrammetric point clouds

Field measurements are the main source of information when determining stand parameters, which are essential to produce an effective forest management plan. However, conducting terrestrial measurements is neither time- nor cost-efficient in most cases. In recent years, the advent of sophisticated remote sensing technologies has enabled the extraction of accurate and robust information about the physical characteristics of trees. Crown diameter is one of the most important stand parameters that should be measured or estimated. This study proposes a Polynomial Fitting Based (PFB) methodology to estimate crown diameters of urban trees with Unmanned Aerial System (UAS)-based data. Crown diameters estimated with the PFB methodology were compared not only to a reference data but also to those estimated based on five widely used image segmentation algorithms, which were the Mean Shift Segmentation (MSS), Morphological Profiles Based Segmentation (MPBS), Multiresolution Segmentation (MRS), Seeded Region Growing Segmentation (SRGS) and Watershed Segmentation (WS). Quantitative investigations revealed that the PFB approach outperformed the other segmentation-based approaches. The PFB approach estimated the crown diameters with root-mean-square errors (RMSE) ranging from 0.69 m to 0.92 m. The PFB methodology was found to be a practical and robust approach for the estimation of crown diameters, which plays a very significant role in effective forest management.     

Towards more active and stable PdAgCr electrocatalysts for formic acid electrooxidation: The role of optimization via response surface methodology

In this study, multiwall carbon nanotube (MCNT)‐supported Pd (Pd/MWCNT) catalysts are prepared by using NaBH₄ reduction method. In order to maximize the oxidation and reduction of H₂SO₄, synthesis conditions (Pd ratio, molar ratio of NaBH₄/K₂PdCl₄, volume of deionized water, and duration of agitation) are optimized by using response surface methodology (RSM). The optimum synthesis conditions are determined as 58.2% of Pd by weight, 154.6 molar ratio of NaBH₄ to K₂PdCl₄, 19.48 mL of deionized water, and 186.16 min of agitation duration. The effect of electrochemical measurement conditions on the oxidation kinetics of Pd/MWCNT is also investigated by RSM. The optimum electrochemical measurement conditions are found as 10 μL of catalyst mixture, 90°C of H₂SO₄ solution, and 5.5 M H₂SO₄. The Pd/MWCNT, Pd₅₀Ag₅₀/MWCNT, and Pd_65.6Ag_33.6Cr_0.80/MWCNT catalysts prepared under optimized conditions are characterized by using X‐ray diffraction, transmission electron microscopy, N₂ adsorption‐desorption, and inductively coupled plasma mass spectrometry. The crystallite sizes of these catalysts are found as 4.85, 5.66, and 5.26 nm for Pd/MWCNT, Pd₅₀Ag₅₀/MWCNT, and Pd_65.6Ag_33.6Cr_0.80/MWCNT catalysts, respectively. Isotherms of all these catalysts are found to be similar to Type V isotherms with H3 hysteresis loop. The average particle size of Pd₅₀Ag₅₀/MWCNT and Pd_65.6Ag_33.6Cr_0.80/MWCNT catalysts are determined as 5.2 and 9.2 nm, respectively. Electrochemical performance of as‐prepared catalysts is evaluated by using cyclic voltammetry and chronoamperometry. The formic acid electrooxidation (FAEO) activities are found as 18.9, 27.8, and 51.6 mA/cm² for Pd/MWCNT, Pd₅₀Ag₅₀/MWCNT, and Pd_65.6Ag_33.6Cr_0.80/MWCNT, respectively. Pd_65.6Ag_33.6Cr_0.80/MWCNT shows the highest activity and stability. Optimization of synthesis conditions and electrochemical measurement parameters allow us to obtain very good electrochemical activity and stability for FAEO reaction compared with anode catalysts in the literature.     

House Prices as a Result of Trading Activities: A Patient Trader Model

Computational Economics - We present a new modeling approach for house price movements as a consequence of the trading behavior of market agents. In our modeling approach, all agents are assumed to...     

A simulation as a service cloud middleware

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.     

Convergence of rule-of-thumb sizing and allocating rules of distributed generation in meshed power networks

This paper presents different approaches to find out and address some rules for distributed generation (DG) integrated mesh type networks, which can be used in the management of future power systems. There are so many influencing factors of efficiency in the integration of DG that we need to analyze these influencing factors obviously. Hence, carefully planning plays a key role in tackling these challenges in the future power systems. In contrast to the majority of existing observations, we focus on the case where the underlying states are multiple and single DG allocations with changing conditions. In several previous studies, the best single bus has been investigated under the specified conditions. However, it follows from the results of this study that all issues concerning DG strongly depend on power network structure and DG locations, and it is worth to note that the best location changes with penetration levels. Also, it is observed that the all buses show different characteristics in terms of DG integrations under the different cases, moreover their optimum size and power factor are different. It means that optimum bus in a network changes with the conditions. On the other hand, the problematic buses can be occurred in voltage profile after the DG integration. As a result, an investigation of rule of thumb approach is performed for evaluation of performance enhancement of DG integrated meshed networks. The results are also used to discuss the integration of DG management strategies under various operating conditions.     

Evaluation of greenhouse residues gasification performance in hydrogen production

In this study, a modeling study was carried out to investigate the potential of hydrogen production from greenhouse tomato and pepper residues blending in different rates (0%, 25%, 50%, 75% and 100%) by air-steam gasification. The numerical model developed for the gasification system assumes that all carbon in the mixture is gasified. Air to fuel rate and steam to fuel rates are 0.05 due to high content of O₂ in biomass residues. The gasifier temperature is 877 °C (1150 K) for developed model. According to the result of this study, increasing tomato residues blending rate increases hydrogen content of syngas. It is mainly caused by the content of O₂ in tomato residues being higher than content of O₂ in pepper residues. This study shows that the O₂ content of greenhouse residues is an important factor in syngas production, especially in H₂ production.     

Implementation of Hydraulic Modelling for Water-Loss Reduction Through Pressure Management

This study was conducted in the Konyaalti Water Distribution Network in Antalya, Turkey. The study area was divided into 18 district metered areas (DMAs) for better management of water losses. Water levels in reservoirs, flow rates, and water pressures were monitored on-line by the SCADA data system. A hydraulic model was calibrated and verified for each DMA using data provided by SCADA. The model results revealed that a number of DMAs exhibited high pressures, greater than 3.5 bars, and high minimum night flow (MNF) throughout the year. Also, the Infrastructure Leakage Index (ILI) for the study area was greater than 20, indicating high water losses. As a result of these findings, a pressure reducing valve (PRV) was installed at DMA No. 2 as an example and set at 3.0 bars resulting in considerable reduction in water losses. The optimum pressure level for setting the PRV was chosen using the hydraulic model. The same model was used to predict water savings due to pressure reduction. The predicted water savings were verified using long periods of flow rates and water pressure profiles. The predicted and measured water savings showed good agreement. The study concluded that hydraulic modelling is essential for applying appropriate pressure management strategies.