Study on synthesis and application of collagen‐modified polylactic acid

To modify the degradability and improve the hydrophilicity of polylactic acid (PLA), collagen‐modified polylactide (CPLA) was synthesized by means of grafting modification method including chloridization and aminolysis, and its structure was characterized by FTIR, ¹H NMR, and fluorescein isothiocyanate‐labeled fluorescence spectra. Subsequently, the hydrophilicity and degradation behavior of CPLA were characterized. Finally, CPLA was used as a carrier for the preparation of the trypsin sustained release microspheres via the emulsion‐solvent evaporation technique, followed with its characterization. Results showed that the collagen had been grafted into PLA and the graft ratio of collagen measured about 6.7%. Water absorption behavior test indicated that the hydrophilicity of CPLA was significantly higher than PLA. Furthermore, degradability test revealed that the degradation behavior of PLA was obviously modified and there was no obvious acid‐catalyzed self‐accelerating degradation behavior in the degradation process of CPLA. It was also indicated that the encapsulation efficiency and drug content in trypsin‐loaded CPLA microspheres were all clearly higher than trypsin‐loaded PLA microspheres. The results suggested that CPLA showed a great potential as matrix for drug delivery. POLYM. COMPOS., 36:88–93, 2015. © 2014 Society of Plastics Engineers     

Phosphorus Removal from Si-Fe Alloy Using SiO2-Al2O3-CaO Slag

Metallurgical and Materials Transactions B - Phosphorus removal from silicon using a combination of solvent and slag refining, with lower carbon footprint and lower energy requirement than the...     

Nanosilica Supported Dual Acidic Ionic Liquid as a Recyclable Catalyst for the Rapid and Green Synthesis of Polycyclic Phenolic Compounds

Generally ionic liquids have gained increasing attention in organic synthesis as catalyst and solvent. However, there are some drawbacks, including the difficulties in the product purification, ionic liquid recycling, and use of excess amounts of the expensive ionic liquid when the ionic liquid is used in the organic reactions. In addition, the high viscosity of ionic liquids can lead to mass transfer limitations in fast chemical reactions. These problems can be overcome by the use of supported ionic liquid phases. In this article, a simple, efficient and green method has been developed for the synthesis of bisphenolic antioxidants by the reaction of 2-tert-butyl-4-methylphenol and aldehydes in the presence of nanosilica supported dual acidic ionic liquid (NSSDAIL) as robust and reusable catalyst under solvent-free conditions. Three different NSSDAILs were synthesized and characterized using SEM, BET, IR, and XRD techniques. High yields of the products, short reaction times, use of a non corrosive, non toxic and reusable catalyst, and use of solvent-free condition are the worthwhile advantages of the current method.     

民俗文化在城市村落中的延续——浅析新安县民俗文化村规划设计

河南省洛阳市新安县民俗文化村规划设计,在"有机更新"理论的指导下,尊重民俗文化,提出"整体性""自发性""延续性""阶段性""经济性""综合效益"等原则,以实现其可持续发展,并力图使民俗文化村成为真正的"工作居住平衡体".     

Integration of time series forecasting in a dynamic decision support system for multiple reservoir management to conserve water sources

In most of arid and semi-arid regions, there are limited sources of available fresh water for different domestic and environmental demands. Strategic and parsimonious fresh water-use in water-scarce areas such as Southern New Mexico is crucially important. Elephant Butte and Caballo reservoirs are two integrated reservoirs in this region that provide water supply for many water users in downstream areas. Since Elephant Butte Reservoir is in a semi-arid region, it would be rational to utilize other energy sources such as wind energy to produce electricity and use the water supply to other critical demands in terms of time and availability. This study develops a strategy of optimal management of two integrated reservoirs to quantify the savable volume of water sources through optimal operation management. To optimize operations for the Elephant Butte and Caballo reservoirs as an integrated reservoir operation in New Mexico, the authors in this case study utilized two autoregressive integrated moving average models, one non-seasonal (daily, ARIMA model) and one seasonal (monthly, SARIMA model), to predict daily and monthly inflows to the Elephant Butte Reservoir. The coefficient of determination between predicted and observed daily values and the normalized mean of absolute error (NMAE) were 0.97 and 0.09, respectively, indicating that the daily ARIMA prediction model was significantly reliable and accurate for a univariate based streamflow forecast model. The developed time series prediction models were incorporated in a decision support system, which utilizes the predicted values for a day and a month ahead and leads to save significant amount of water volume by providing the optimal release schedule from Elephant Butte into the Caballo Reservoir. The predicted daily and monthly values from the developed ARIMA prediction models were integrated successfully with the dynamic operation model, which provides the optimal operation plans. The optimal operation plan significantly minimizes the total evaporation loss from both reservoirs by providing the optimal storage levels in both reservoirs. The saved volume of the water would be considered as a significant water supply for environmental conservation actions in downstream of the Caballo Reservoir. Providing an integrated optimal management plan for two reservoirs led to save significant water sources in a region that water shortage has led to significant environmental consequences. Finally, since the models are univariate, they demonstrate an approach for reliable inflow prediction when information is limited to only streamflow values. We find that hydroelectric power generation forces the region to lose significant amount of water to evaporation and therefore hinder the optimal use of freshwater. Based on these findings, we conclude that a water scarce region like Southern New Mexico should gain independence from hydroelectric power and save the freshwater for supporting ecosystem services and environmental purposes.     

Wettability of Al2O3, MgO,and TiB2 Inclusions with Liquid Silicon

Silicon - An experimental study was conducted to characterize the interaction between liquid silicon and refractory inclusions that are often present in silicon as solid inclusions. The...     

A Model to Create Organizational Value with Big Data Analytics

Value creation is a major factor not only in the sustainability of organizations but also in the maximization of profit, customer retention, business goals fulfillment, and revenue. When the value is intended to be created from Big Data scenarios, value creation entails being understood over a broader range of complexity. A question that arises here is how organizations can use this massive quantity of data and create business value? The present study seeks to provide a model for creating organizational value using Big Data Analytics (BDA). To this end, after reviewing the related literature and interviewing experts, the BDA-based organizational value creation model is developed. Accordingly, five hypotheses are formulated, and a questionnaire is prepared. Then, the respective questionnaire is given to the research statistical population (i.e., IT managers and experts, particularly those specializing in data analysis) to test the research hypotheses. In next phase, connections between model variables are scrutinized using the structural equation modeling (measurement and structural models). The results of the study indicate that investigating the infrastructures of the Big Data Analytics, as well as the capabilities of the organization and those of Big Data Analytics is the initial requirement to create organizational value using BDA. Thereby, the Big Data Analytics strategy is formulated, and ultimately, the organizational value is created as well.     

Evaluation of IMERG and MRMS remotely sensed snowfall products

In this study, snow accumulation (SA) estimates of the Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) (IMERG) and Multi-Radar/Multi-Sensor (MRMS) products were evaluated against the SNOwpack TELemetry (SNOTEL) ground observations over a Basin in the western United States from October 2016 to February 2017. IMERG underestimated SA in three snowfall probability thresholds of 45%, 65% and 85%. With increasing the threshold from 45% to 85%, MRMS Bias index showed overestimation compared to that of the IMERG. Overall, MRMS presented more accurate results than the IMERG. In categorical analysis, IMERG had better probability of detection (POD) values than the MRMS although MRMS was generally more accurate than the IMERG in all thresholds. Moreover, with respect to Bias, mean absolute error (MAE) and root mean square error (RMSE) indices in various elevation classes, IMERG was more efficient in lower elevation classes while in categorical analysis, MRMS performed worse than the IMERG based on the POD values. This weakness increased in higher elevation classes. Also, in another comparison in different SA classes, the results showed that IMERG had better performance than the MRMS under moderate snowfall condition. However, MRMS estimates improved in heavy snowfall. In general, it was concluded that the IMERG performed better in snowfall detection than the MRMS; while in contrast, the opposite was true in estimating the SA.