Petroleum asphaltene-derived highly porous carbon for the efficient removal of pharmaceutical compounds in water

Journal of Porous Materials - Highly porous carbons (PCs) were successfully developed through KOH chemical activation process from petroleum asphaltene for the efficient removal of pharmaceutical...     

Explainable probabilistic deep learning framework for seismic assessment of structures using distribution-free prediction intervals

A new probabilistic framework is proposed for providing a distribution-free prediction interval (PI) of seismic responses required for various earthquake engineering applications. The framework overcomes the limitation of point prediction models and avoids the complexity of traditional probabilistic methods. The framework utilizes a few assumptions of probability distributions and requires no prior assumed statistical distribution for the PI. Ensemble probabilistic deep learning models (DLMs) are used to provide quality-driven PIs of seismic responses for low- to mid-rise buildings with limited irregularity. Considering these systems and ground motions with the aid of Monte Carlo simulation and nonlinear time-history analysis (NLTHA), huge datasets are generated for training. To have an insight into the probabilistic DLM, explainable artificial intelligence techniques are used. The superiority of the proposed framework in quantifying uncertainties is validated by comparison with the conventional Bayesian method. In addition, its applicability is investigated by providing bounds of seismic fragility curves, life cycle cost, and resilience index obtained by NLTHA for a benchmark case study model. The results showed that the proposed framework is robust and outperforms the conventional Bayesian method in uncertainty quantification for the considered dataset.     

Developing centrifugal spun thermally cross-linked gelatin based fibrous biomats for antibacterial wound dressing applications

Fibrous materials obtained from natural polymers, such as gelatin, have been used in medical applications due to their biocompatibility and biodegradability. Herein, free-standing durable fibrous gelatin biomats with antibacterial activity were developed via a simple, low cost and fast production route, centrifugal spinning, and subsequent thermal crosslinking. After a series of preliminary experiments, droplet−/bead-free porous biomats with fine fibers, 3.41 ± 1.8 μm in diameter, were fabricated. Subsequently, antimicrobial biomats were produced by adding AgNO₃ into the production solution. X-ray diffractometer and energy dispersive X-ray results showed Ag NPs existing as AgCl in the biomats, which could be attributed to chemical reaction between the Ag NPs and residual Cl in the impure gelatin. Later, both the neat-gelatin and Ag-gelatin biomats were thermally crosslinked at 170°C to gain stability against water. Although the Ag addition reduced ultimate tensile strength by half, from 881 to 495 kPa, the crosslinked biomats were robust enough to be used for wound dressing applications. They were also found to be highly breathable, with the air permeability of 256 and 81.2 mm/s, respectively. The biomats showed antibacterial activity against Escherichia coli and Staphylococcus aureus bacteria. The results show that the free-standing fibrous-gelatin-based biomats produced is applicable for wound dressing applications.     

The effect of carbon dioxide during the desulfurization of flue gas with Mardin–Mazıdagı phosphate rock

The effects of temperature, CO₂ concentration and particle size on simultaneous calcination/sulfation of Mardin–Maz?dag? phosphate rock in fluidized-bed reactor were investigated. For this, a raw sample was exposed to calcination and sulfation processes in a fluidized-bed reactor to determine the effects of parameters by using a model gas mixture similar to the flue gas composition. The calcination ratio increased with increasing temperature and decreasing particle size, but decreased with increasing CO₂ concentration. In sulfation process, however, sulphate conversion ratio increased with increasing CO₂ ratio and decreased with decreasing particle size. The sulfation reaction is well represented by the shrinking core model and can be divided into two regions with different rate controlling step. For low conversions, the controlling step was found to be chemical reaction at the interface, but the diffusion through the product layer for high conversion. The activation energies for the chemical reaction at the interface and diffusion through the product layer cases were calculated as 100 and 296 kJ mol^?1, respectively.     

Reinforced thin-film composite nanofiltration membranes: Fabrication,characterization, and performance testing

Hollow-fiber (HF) membranes have the advantage of a higher packing density compared to flat-sheet and spiral-wound configurations. However, the low pressure tolerance of HF membranes limits their applications in nanofiltration (NF). In this study, reinforced thin-film composite (r-TFC) HF NF membranes were fabricated and evaluated in tests with water containing different salts and organic matter. Reinforced polysulfone ultrafiltration membranes were used as a support for a polyamide layer prepared from piperazine and trimesoyl chloride monomers. The interfacial polymerization conditions were optimized via selection of the trimesoyl chloride reaction time that gave the highest membrane performance. A specific permeate flux of 5.1 L m^–2 h^–1 bar^–1, an MgSO₄ rejection of 69%, and an NaCl rejection of 26% at a transmembrane pressure of 6 bars were obtained with the optimized r-TFC membranes. Performance studies with water characterized by synthetic solution demonstrated removals of the total organic carbon, ultraviolet absorbance at 254 nm, and turbidity in excess of 65, 80, and 90%, respectively. The results of this study illustrate the feasibility of manufacturing r-TFC HFs and using them in water-treatment applications. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48001.     

A survey on packet size optimization for terrestrial,underwater, underground,and body area sensor networks

Packet size optimization is a critical issue in wireless sensor networks (WSNs) for improving many performance metrics (eg, network lifetime, delay, throughput, and reliability). In WSNs, longer packets may experience higher loss rates due to harsh channel conditions. On the other hand, shorter packets may suffer from greater overhead. Hence, the optimal packet size must be chosen to enhance various performance metrics of WSNs. To this end, many approaches have been proposed to determine the optimum packet size in WSNs. In the literature, packet size optimization studies focus on a specific application or deployment environment. However, there is no comprehensive and recent survey paper that categorizes these different approaches. To address this need, in this paper, recent studies and techniques on data packet size optimization for terrestrial WSNs, underwater WSNs, wireless underground sensor networks, and body area sensor networks are reviewed to motivate the research community to further investigate this promising research area. The main objective of this paper is to provide a better understanding of different packet size optimization approaches used in different types of sensor networks and applications as well as introduce open research issues and challenges in this area.     

Comparative characterization of monophenolase and diphenolase activities from a wild edible mushroom (Macrolepiota mastoidea)

In this study, Macrolepiota mastoidea, a wild edible mushroom, was evaluated for its polyphenol oxidase potential. Native electrophoresis, stained by l-dihydroxyphenylalanine, of the crude extracts from this species showed two bands having R_f values of 0.38 (minor) and 0.50 (major), supporting a polyphenol oxidase potential. The crude extracts showed monophenolase activity against 3-(4-hydroxyphenyl)-propionic acid and diphenolase activity against 4-methylcatechol as substrates. Monophenolase and diphenolase activities of enzyme extract prepared from M. mastoidea showed pH optimum values at pH 6.0 and pH 4.0, respectively. The extracts retained about 100% and 60% of their original monophenolase and diphenolase activities at their optimum pH values, respectively. It was estimated from thermodynamic data that M. mastoidea had a thermostable monophenolase activity. Thiourea and ascorbic acid were highly potential inhibitors for monophenolase, and ascorbic acid and sodium metabisulphite for diphenolase activity. It is clear from the present results that the enzyme extracts prepared from M. mastoidea possess polyphenol oxidase activities with interesting properties.     

新疆柯尔克孜族传统发酵饮料博扎中微生物群落结构的PCR-DGGE分析

采用PCR-DGGE 技术分析新疆柯尔克孜民族古老传统发酵饮料--博扎(Bozaa)中微生物种群结构,对博扎细菌和酵母菌DGGE 图谱上主要条带的DNA 进行测序和序列分析。结果表明,博扎中细菌组成包括植物乳杆菌(Lactobacterium plantarum)、短乳杆菌(Lactobacillus brevis)、蜡状芽孢杆菌(Bacillus cereus)、巴氏醋酸杆菌(Acetobacerpasteurianus)、啤酒酵母(Saccharomyces cerevisiae),初步成功解析评估了博扎中微生物的多样性。     

Estimation of monthly diffuse nutrient loads for a watershed in Turkey

Diffuse pollution has a complex nature depending on various land‐use activities like agriculture, livestock breeding and forestry. In this study, an alternative methodology is applied for decreasing the spatial uncertainty of diffuse nutrient load estimations. It is applied in the Melen Watershed, Turkey, which is an important watershed from where additional water will be supplied for the megacity Istanbul via interbasin water transfer. Monthly diffuse nutrient loads were estimated for each subwatershed by utilizing remote sensing (RS) and geographical information systems (GIS). Estimated nutrient loads were considerably different in various months due to the temporally irregular fertilizer application and meteorological conditions. Temporal differences were also predicted in the spatial distribution of the nutrient loads. The methodology is applicable in watershed protection studies, especially where necessary etudes should be conducted in the short term and with limited data. Such efforts in identifying and determining the diffuse loads are important for sustainable management of the watershed.