Constructing and evaluating core inflation measures from component‐level inflation data

This paper undertakes a comprehensive examination of 10 measures of core inflation and evaluates which measure produces the best forecast of headline inflation out‐of‐sample. We use the Personal Consumption Expenditure Price Index as our measure of inflation. We use two sets of components (17 and 50) of the Personal Consumption Expenditure Price Index to construct these core inflation measures and evaluate these measures at the three time horizons (6, 12 and 24 months) most relevant for monetary policy decisions. The best measure of core inflation for both sets of components and over all time horizons uses weights based on the first principal component of the disaggregated (component‐level) prices. Interestingly, the results vary by the number of components used; when more components are used the weights based on the persistence of each component is statistically equivalent to the weights generated by the first principal component. However, those forecasts using the persistence of 50 components are statistically worse than those generated using the first principal component of 17 components. The statistical superiority of the principal component method is due to the fact that it extracts (in the first principal component) the common source of variation in the component level prices that accurately describes trend inflation over the next 6–24 months.     

General mechanisms of drought response and their application in drought resistance improvement in plants

Plants often encounter unfavorable environmental conditions because of their sessile lifestyle. These adverse factors greatly affect the geographic distribution of plants, as well as their growth and productivity. Drought stress is one of the premier limitations to global agricultural production due to the complexity of the water-limiting environment and changing climate. Plants have evolved a series of mechanisms at the morphological, physiological, biochemical, cellular, and molecular levels to overcome water deficit or drought stress conditions. The drought resistance of plants can be divided into four basic types-drought avoidance, drought tolerance, drought escape, and drought recovery. Various drought-related traits, including root traits, leaf traits, osmotic adjustment capabilities, water potential, ABA content, and stability of the cell membrane, have been used as indicators to evaluate the drought resistance of plants. In the last decade, scientists have investigated the genetic and molecular mechanisms of drought resistance to enhance the drought resistance of various crops, and significant progress has been made with regard to drought avoidance and drought tolerance. With increasing knowledge to comprehensively decipher the complicated mechanisms of drought resistance in model plants, it still remains an enormous challenge to develop water-saving and drought-resistant crops to cope with the water shortage and increasing demand for food production in the future.     

An Economic Model-Based Matching Approach Between Buyers and Sellers Through a Broker in an Open E-Marketplace

A broker in an open e-marketplace enables buyers and sellers to do business with each other. Although a broker plays an important role in e-marketplaces, theory and guidelines for matching between buyers and sellers in multi-attribute exchanges are limited. Therefore, a challenge for a broker’s responsibility is how to maximize a buyer’s total satisfaction degree as its goals under the consideration of trade-off between a buyer’s buying quantity and price paid to a seller, and other attributes. To solve this challenge, this paper proposes an economic model-based matching approach between a buyer’s requirements and a seller’s offers. The major contributions of this paper are that (i) a broker can model a seller’s price policy as per a buyer’s buying quantity through communication between a broker and a seller; (ii) due to each buyer’s different quantity demand, a broker models a buyer’s satisfaction degree as per a buyer’s buying quantity based on communication between a broker and a buyer; and (iii) to carry out a broker’s matching processes, an objective function and a set of constraints are generated to help a broker to maximize a buyer’s total satisfaction degree. Experimental results demonstrate the good performance of the proposed approach.     

Study on the Centralization Strategy of the Blood Allocation Among Different Departments within a Hospital

By far, the researches on how to distribute blood products among different departments in hospital have not been further studied, though the problem of blood shortage and wastage that caused by improper blood allocation is severe, which may endanger patient’s lives and impose considerable costs on hospitals. In order to solve this problem, this paper mainly studies on how to distribute the blood items among different departments within a hospital and investigates the allocation approach with the novel management method by centralizing the inventory of several different departments. By integrating the blood inventory requirements of some departments, the hospital could reduce the rate of blood shortage and wastage effectively, release the pressure of the occupancy of resources and reduce the bullwhip effect of blood products. This paper illustrates the centralization principle in hospital and formulates the mixed integer programming model to work out the optimal allocation network scheme and the optimal inventory setting for every department. And the results of the numerical example demonstrate that this centralization method could considerably reduce blood shortage and wastage in hospital by about 72% and 90% respectively. Furthermore, it could decrease the total cost by about 108,540 RMB a month on blood supply chain management in the hospital and improve the effect of some certain surgeries by transfusing the fresh blood to patients.     

Effects of Strain Rate,Temperature and Grain Size on the Mechanical Properties and Microstructure Evolutions of Polycrystalline Nickel Nanowires: A Molecular Dynamics Simulation

Through molecular dynamics(MD)simulation,the dependencies of temperature,grain size and strain rate on the mechanical properties were studied.The simulation results demonstrated that the strain rate from 0.05 to 2 ns~(–1 )affected the Young’s modulus of nickel nanowires slightly,whereas the yield stress increased.The Young’s modulus decreased approximately linearly;however,the yield stress firstly increased and subsequently dropped as the temperature increased.The Young’s modulus and yield stress increased as the mean grain size increased from 2.66 to6.72 nm.Moreover,certain efforts have been made in the microstructure evolution with mechanical properties association under uniaxial tension.Certain phenomena such as the formation of twin structures,which were found in nanowires with larger grain size at higher strain rate and lower temperature,as well as the movement of grain boundaries and dislocation,were detected and discussed in detail.The results demonstrated that the plastic deformation was mainly accommodated by the motion of grain boundaries for smaller grain size.However,for larger grain size,the formations of stacking faults and twins were the main mechanisms of plastic deformation in the polycrystalline nickel nanowire.     

Fuzzy Views on Black-Litterman Portfolio Selection Model

In this paper, views of investor are described in fuzzy sets, and two fuzzy Black-Litterman models are constructed with fuzzy views and fuzzy random views respectively. In the models, expected returns and uncertainty matrix of views are redefined and the views are formulated by fuzzy approaches suitably. Then the models are tested with data from Chinese financial markets. Empirical results show that the fuzzy random views model performs the best, and both the fuzzy models are better than the traditional ones, demonstrating that the fuzzy approaches can contain more information in the views and measure the uncertainty more correctly.     

Aristotle Said “Happiness is a State of Activity” — Predicting Mood Through Body Sensing with Smartwatches

We measure and predict states of Activation and Happiness using a body sensing application connected to smartwatches. Through the sensors of commercially available smartwatches we collect individual mood states and correlate them with body sensing data such as acceleration, heart rate, light level data, and location, through the GPS sensor built into the smartphone connected to the smartwatch. We polled users on the smartwatch for seven weeks four times per day asking for their mood state. We found that both Happiness and Activation are negatively correlated with heart beats and with the levels of light. People tend to be happier when they are moving more intensely and are feeling less activated during weekends. We also found that people with a lower Conscientiousness and Neuroticism and higher Agreeableness tend to be happy more frequently. In addition, more Activation can be predicted by lower Openness to experience and higher Agreeableness and Conscientiousness. Lastly, we find that tracking people’s geographical coordinates might play an important role in predicting Happiness and Activation. The methodology we propose is a first step towards building an automated mood tracking system, to be used for better teamwork and in combination with social network analysis studies.