Group Decision Algorithm for Aged Healthcare Product Purchase Under q-Rung Picture Normal Fuzzy Environment Using Heronian Mean Operator

With the intensification of the aging, the health issue of the elderly is arousing public concern increasingly. Various healthcare products for the elderly are emerging from the market, thus how to select suitable aged healthcare product is critical to the well-being of the elderly. In the literature, nonetheless, a comprehensive and standardized evaluation framework to support healthcare product purchase decision for the aged is currently lacking. This paper proposes a novel group decision-making method to aid the decision-making of aged healthcare product purchase based on q-rung picture normal fuzzy Heronian mean (q-RPtNoFHM) operators. In it, firstly, a new fuzzy variable called the q-rung picture normal fuzzy set (q-RPtNoFS) is defined to reasonably describe different responses to healthcare product evaluation, for which, some definitions including operational laws, a score function, and an accuracy function of q-RPtNoFSs are introduced. Then, two q-RPtNoFHM operators are presented to aggregate group decision information. In addition, some properties of q-RPtNoFHM operators, such as monotonicity, commutativity, and idempotency, are discussed. Finally, an example on antihypertensive drugs purchase is gave to illustrate the practicality of the proposed method, and conduct sensitivity analysis to analyze the effectiveness and flexibility of proposed methods

Water-Borne Perovskite Quantum Dot-Loaded, Polystyrene Latex Ink

Highly lipophilic nanocrystals (NCs) of cesium lead halides were successfully embedded in polystyrene (PS) particles by deliberately controlling the swelling of the PS particles in the mixtures of good and bad organic solvents. The resulting composite particles were readily transferred into water via simple stepwise solvent exchange, which yielded water-borne perovskite NC-based inks with outstanding structural and chemical stability in aqueous media. Minimal change in the photoluminescence (PL) of the NCs loaded in the PS particles was visible after 1 month of incubation of the composite particles in water in a broad pH range from 1 to 14, which could otherwise be hardly realized. Loading into the PS particles also made the NCs highly stable against polar organic solvents, such as ethanol, intense light irradiation, and heat. The NC PL intensity slightly changed after the composite particles were heated at 75°C and under irradiation of strong blue light (@365 nm) for 1 h. Furthermore, the PS matrices could effectively inhibit the exchange of halide anions between two differently sized perovskite NCs loaded therein, thereby offering a considerable technical advantage in the application of multiple perovskite NCs for multicolor display in the future

Forecasting Technology Trends Using Text Mining of the Gaps Between Science and Technology: The Case of Perovskite Solar Cell Technology

How to detect and identify the future trends of emerging technologies as early as possible is crucial for government R&D strategic planning and enterprises\u27 practices. To avoid the weakness of using only scientific papers or patents to study the development trends of emerging technologies, this paper proposes a framework that uses scientific papers and patents as data resources and integrates the text mining and expert judgment approaches to identify technology evolution paths and forecast technology development trends within the short term. The perovskite solar cell technology is selected as a case study. In this case, the text mining and expert judgment methods are applied to analyze the technology evolution path, and gaps analysis between science and technology is used to forecast the technology development trend. This paper will contribute to the technology forecasting and foresight methodology, and will be of interest to solar photovoltaic technology R&D experts

Evaporation from Sand and Loess Soils: An Experimental Approach

In arid and semiarid areas, low rainfall and high evaporation make groundwater the main source of soil water in the vadose zone. In order to understand the upward migration rate of soil water and the mechanisms of moisture migration in the vadose zone, evaporation experiments in sand and loess soils were conducted. The evaporation and imbibition of the soil columns were measured in order to analyze the upward migration rate of soil water. Hydrochemical and isotopic methods were applied to investigate the microscopic mechanisms of water movement in the vadose zone. The results show that soil columns with higher loess contents have higher imbibition and evaporation rates. Obvious evaporation occurs only after soil water has reached the surface layer of the soil column, and the evaporation rate is related to soil composition. Salt migrates in the same direction as that of water movement and accumulates after the evaporation of water. The greater the evaporation, the greater the salt accumulation. Only strong hydraulic connections between soil water support the diffusion of salt from areas of higher concentration to those of lower concentration. Before liquid water reaches the surface layer, there are two regions of unsaturated soil. In the lower column, soil water moves in the form of liquid water and hydraulic connections are strong. In the upper column, water vapor from the lower column diffuse in soil pore spaces, and some are absorbed or condensed in the soil

Isotopes and hydrochemistry of Daihai Lake recharging sources, Northern China

Daihai Lake has faced severe shrinkage in recent years due to over-exploitation. Stable isotopes (D and O-18) and hydrochemistry are employed to investigate the source of lake water to better understand its recharge dynamics. Results show that, in additional to local rainfall, groundwater is also an important water supply to the lake and accounts for a greater proportion. The groundwater is not recharged by local rainfall, but originates from other sources with significantly depleted isotope values. Combined with springs and artesian wells in the basin, it is consistent with the recent discover of external groundwater recharging in Northern China

Identifying Potential Breakthrough Research: A Machine Learning Method Using Scientific Papers and Twitter Data

Breakthrough research may signal shifts in science, technology, and innovation systems. Early identification of breakthrough research is important not only for scientists, but also for policy makers and R&D experts in developing R&D strategies and allocating R&D resources. Researchers mostly use scientific papers data to identify potential breakthrough research, but they rarely make use of Twitter data related to scientific research and machine learning methods. Analysis of Twitter data is of great significance for us to understand the public\u27s perception of potential breakthrough research and to identify potential breakthrough research. Machine learning methods can assist us in predicting the trend of events by utilizing prior knowledge and experience. Therefore, this paper proposes a framework for identifying potential breakthrough research using machine learning methods with scientific papers and Twitter data. We select solar cells as a case study to verify the valid and flexible of this framework. In this case, we use machine learning method to discover potential breakthrough research from scientific papers, and we use Twitter data mining to analyze Twitter users\u27 sense of and response to the discovered potential breakthrough research, which aims to achieve a more extensive and diverse assessment of the discovered potential breakthrough research. This paper contributes to identifying potential breakthrough research, as well as understanding the emergence and development of breakthrough research. It will be of interest to R&D experts in the field of solar cell technology

Evaluation of China\u27s New Energy Vehicle Policy Texts with Quantitative and Qualitative Analysis

As one of the strategic emerging industries, the new energy vehicle (NEV) industry receives strong support from the Chinese government. The Chinese government has formulated a large number of policies to promote the development of NEV industry. Evaluating and analyzing the NEV policies are of great significance for improving policy formulation. In this study, we comprehensively analyze 253 NEV policy texts by employing quantitative and qualitative methods. We present the policy instrument types and semantic structure characteristics of policy texts based on the content analysis. The advantages and disadvantages of policy texts are identified by using a quantitative evaluation model. Our results show that the most frequently used policy instrument is regulatory, and the main policy objective is the demand-pull. The policies with higher scores are more comprehensive. Three suggestions are put forward to improve NEV policies