A recurrent neural network using historical data to predict time series indoor PM2.5 concentrations for residential buildings

Due to the severe outdoor PM2.5 pollution in China, many people have installed air-cleaning systems in homes. To make the systems run automatically and intelligently, we developed a recurrent neural network (RNN) that uses historical data to predict the future indoor PM2.5 concentration. The RNN architecture includes an autoencoder and a recurrent part. We used data measured in an apartment over the course of an entire year to train and test the RNN. The data include indoor/outdoor PM2.5 concentration, environmental parameters and time of day. By comparing three different input strategies, we found that a strategy employing historical PM2.5 and time of day as inputs performed best. With this strategy, the model can be applied to predict the relatively stable trend of indoor PM2.5 concentration in advance. When the input length is 2 h and the prediction horizon is 30 min, the median prediction error is 8.3 µg/m³ for the whole test set. For times with indoor PM2.5 concentrations between (20,50] µg/m³ and (50,100] µg/m³, the median prediction error is 8.3 and 9.2 µg/m³, respectively. The low prediction error between the ground-truth and predicted values shows that the RNN can predict indoor PM2.5 concentrations with satisfactory performance.     

基于熵权物元模型的长三角幸福河层次评价

将幸福河概念与长江三角洲区域一体化发展战略相结合，基于自然、人类社会、人水关系3个系统构建了包含24个指标的长三角幸福河层次评价指标体系；引入需求层次理论，以基础Ⅰ层次、基础Ⅱ层次、提升Ⅰ层次、提升Ⅱ层次、幸福层次5个层次作为幸福河的层次评价等级，运用熵权物元模型，建立了长三角幸福河层次评价模型，并对2018年长三角三省一市幸福河层次等级进行了评价。结果表明，三省一市均处于转化中的中间状态，其中江苏省向提升Ⅰ层次转化，浙江省、安徽省向提升Ⅱ层次转化，上海市向幸福层次转化，说明区域整体幸福河层次处于较高水平，但稳定性较差。     

Teff (Eragrostis tef) processing,utilization and future opportunities: a review

The demand for food production has been constantly increasing due to rising population. In developed countries, for example, the emergence of regional production of old grains that are rarely utilized, along with the production of commonly consumed grains, has gained importance in recent years. These grains, known collectively as ancient or heirloom grains, have offered both farmers and consumers novel ways of cultivation and products with interesting taste, characteristics and nutritional value. Among the 30 000 plant species known, only five cereals currently provide more than 50% of the world's energy intake – bread wheat (Triticum aestivum), rice (Oryza sativa), sorghum (Sorghum bicolor), millets (Panicum sp.) and maize (Zea mays). The excessive utilization of these selected species has a great potential to cause genetic losses and difficulty in bridging future agricultural demands. Teff (Eragrostis tef), an ancient grain extensively cultivated in countries like Eritrea and Ethiopia, provides promising alternatives for new food uses since its nutritional value is significantly higher than most others cereal grains. The absence of gluten allows flexibility in food utilization since it can be directly substituted to gluten-containing products. The grain also offers an excellent balance of essential amino acids and minerals, which can fulfil the recommended daily intake and eliminates the need for fortification and enrichment. This review provides a general overview of the physical properties and nutritional composition of teff grains related to processing and applications in the food and feed industries. The current status of teff utilization, as well as the challenges in production and commercialization, and future opportunities is presented and discussed.     

Dual pH‐ and thermal‐responsive nanocomposite hydrogels for controllable delivery of hydrophobic drug baicalein

Hydrogels have been widely used as mild biomaterials due to their bio‐affinity, high drug loading capability and controllable release profiles. However, hydrogel‐based carriers are greatly limited for the delivery of hydrophobic payloads due to the lack of hydrophobic binding sites. Herein, nano‐liposome micelles were embedded in semi‐interpenetrating poly[(N‐isopropylacrylamide)‐co‐chitosan] (PNIPAAm‐co‐CS) and poly[(N‐isopropylacrylamide)‐co‐(sodium alginate)] (PNIPAAm‐co‐SA) hydrogels which were responsive to both temperature and pH, thereby establishing tunable nanocomposite hydrogel delivery systems. Nano‐micelles formed via the self‐assembly of phospholipid could serve as the link between hydrophobic drug and hydrophilic hydrogel due to their special amphiphilic structure. The results of transmission and scanning electron microscopies and infrared spectroscopy showed that the porous hydrogels were successfully fabricated and the liposomes encapsulated with baicalein could be well contained in the network. In addition, the experimental results of response release in vitro revealed that the smart hydrogels showed different degree of sensitiveness under different pH and temperature stimuli. The results of the study demonstrate that combining PNIPAAm‐co‐SA and PNIPAAm‐co‐CS hydrogels with liposomes encapsulated with hydrophobic drugs is a feasible method for hydrophobic drug delivery and have potential application prospects in the medical field. © 2018 Society of Chemical Industry     

Reduced‐order method for mathematical modeling of multiphase dc‐dc converter

A multiphase dc‐dc converter is effective for miniaturization and achieving high‐power density in a switching power supply. However, its mathematical modeling becomes complex as the phase number of the circuit increases. This study proposes a new modeling method to derive a reduced‐order method in a simple manner. The frequency characteristics of the reduced‐order model are fit to those of the original mathematical model of the multiphase dc‐dc converter. Therefore, the efficacy of the proposed method is validated.     

Advances in statistical mechanics of rock masses and its engineering applications

To efficiently link the continuum mechanics for rocks with the structural statistics of rock masses,a theoretical and methodological system called the statistical mechanics of rock masses(SMRM)was developed in the past three decades.In SMRM,equivalent continuum models of stressestrain relationship,strength and failure probability for jointed rock masses were established,which were based on the geometric probability models characterising the rock mass structure.This follows the statistical physics,the continuum mechanics,the fracture mechanics and the weakest link hypothesis.A general constitutive model and complete stressestrain models under compressive and shear conditions were also developed as the derivatives of the SMRM theory.An SMRM calculation system was then developed to provide fast and precise solutions for parameter estimations of rock masses,such as full-direction rock quality designation(RQD),elastic modulus,Coulomb compressive strength,rock mass quality rating,and Poisson’s ratio and shear strength.The constitutive equations involved in SMRM were integrated into a FLAC3D based numerical module to apply for engineering rock masses.It is also capable of analysing the complete deformation of rock masses and active reinforcement of engineering rock masses.Examples of engineering applications of SMRM were presented,including a rock mass at QBT hydropower station in northwestern China,a dam slope of Zongo II hydropower station in D.R.Congo,an open-pit mine in Dexing,China,an underground powerhouse of Jinping I hydropower station in southwestern China,and a typical circular tunnel in Lanzhou-Chongqing railway,China.These applications verified the reliability of the SMRM and demonstrated its applicability to broad engineering issues associated with jointed rock masses.     

Structural breakdown of starch-based foods during gastric digestion and its link to glycemic response: In vivo and in vitro considerations

The digestion of starch-based foods in the small intestine as well as factors affecting their digestibility have been previously investigated and reviewed in detail. Starch digestibility has been studied both in vivo and in vitro, with increasing interest in the use of in vitro models. Although previous in vivo studies have indicated the effect of mastication and gastric digestion on the digestibility of solid starch-based foods, the physical breakdown of starch-based foods prior to small intestinal digestion is often less considered. Moreover, gastric digestion has received little attention in the attempt to understand the digestion of solid starch-based foods in the digestive tract. In this review, the physical breakdown of starch-based foods in the mouth and stomach, the quantification of these breakdown processes, and their links to physiological outcomes, such as gastric emptying and glycemic response, are discussed. In addition, the physical breakdown aspects related to gastric digestion that need to be considered when developing in vitro–in vivo correlation in starch digestion studies are discussed. The discussion demonstrates that physical breakdown prior to small intestinal digestion, especially during gastric digestion, should not be neglected in understanding the digestion of solid starch-based foods.     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.