ABSTRACT
This research demonstrates that the type of product option framing (additive vs. subtractive) and the temporal distance between an option choice and later buying behavior can influence ...decision difficulty. In two studies, the authors show that consumers who engage in additive option framing experience greater difficulty in making decisions for the near future than for the distant future, whereas consumers who engage in subtractive option framing experience greater difficulty in making decisions for the distant future than for the near future. In addition, by using theories of mental simulation, the authors show that communication strategies that promote process simulations for distant‐future choices in the subtractive option framing condition and those that promote outcome simulations for near‐future choices in the additive option framing condition are most effective in reducing decision difficulty. These effects hold across varying product categories and varying option prices.
Thermochromic smart windows are optical devices that can regulate their optical properties actively in response to external temperature changes. Due to their simple structures and as they do not ...require other additional energy supply devices, they have great potential in building energy-saving. However, conventional thermochromic smart windows generally have problems with high response temperatures and low response rates. Owing to their great effect in photothermal conversion, photothermal materials are often used in smart windows to assist phase transition so that they can quickly achieve the dual regulation of light and heat at room temperature. Based on this, research progress on the phase transition of photothermal material-assisted thermochromic smart windows is summarized. In this paper, the phase transition mechanisms of several thermochromic materials (VO2, liquid crystals, and hydrogels) commonly used in the field of smart windows are introduced. Additionally, the applications of carbon-based nanomaterials, noble metal nanoparticles, and semiconductor (metal oxygen/sulfide) nanomaterials in thermochromic smart windows are summarized. The current challenges and solutions are further indicated and future research directions are also proposed.
Thermochromic smart windows can automatically control solar radiation according to the ambient temperature. Compared with photochromic and electrochromic smart windows, they have a stronger ...applicability and lower energy consumption, and have a wide range of application prospects in the field of building energy efficiency. At present, aiming at the challenge of the high transition temperature of thermochromic smart windows, a large amount of innovative research has been carried out via the principle that thermochromic materials can be driven to change their optical performance by photothermal or electrothermal effects at room temperature. Based on this, the research progress of photo- and electro-driven thermochromic smart windows is summarized from VO
-based composites, hydrogels and liquid crystals, and it is pointed out that there are two main development trends of photo-/electro-driven thermochromic smart windows. One is exploring the diversified combination methods of photothermal materials and thermochromic materials, and the other is developing low-cost large-area heating electrodes.
Molybdenum disulfide (MoS2) is a layered transition metal-sulfur compound semiconductor that shows promising prospects for applications in optoelectronics and integrated circuits because of its low ...preparation cost, good stability and excellent physicochemical, biological and mechanical properties. MoS2 with high quality, large size and outstanding performance can be prepared via chemical vapor deposition (CVD). However, its preparation process is complex, and the area of MoS2 obtained is difficult to control. Machine learning (ML), as a powerful tool, has been widely applied in materials science. Based on this, in this paper, a ML Gaussian regression model was constructed to explore the growth mechanism of MoS2 material prepared with the CVD method. The parameters of the regression model were evaluated by combining the four indicators of goodness of fit (r2), mean squared error (MSE), Pearson correlation coefficient (p) and p-value (p_val) of Pearson’s correlation coefficient. After comprehensive comparison, it was found that the performance of the model was optimal when the number of iterations was 15. Additionally, feature importance analysis was conducted on the growth parameters using the established model. The results showed that the carrier gas flow rate (Fr), molybdenum sulfur ratio (R) and reaction temperature (T) had a crucial impact on the CVD growth of MoS2 materials. The optimal model was used to predict the size of molybdenum disulfide synthesis under 185,900 experimental conditions in the simulation dataset so as to select the optimal range for the synthesis of large-size molybdenum disulfide. Furthermore, the model prediction results were verified through literature and experimental results. It was found that the relative error between the prediction results and the literature and experimental results was small. These findings provide an effective solution to the preparation of MoS2 materials with a reduction in the time and cost of trial and error.
DAB+ is the upgraded version of digital audio broadcasting (DAB). DAB and DAB+ coexist in many countries, so receivers are required to be compatible with both standards. In this paper, a solution ...integrating an MPEG1-LayerII (MP2) decoder and an advanced audio coding (AAC) low-complexity (AAC LC) decoder is proposed to provide basic audio decoding for both DAB and DAB+. It also utilizes simple methods to improve high frequencies and stereo quality instead of complicated spectrum band replication and parametric stereo. A highly integrated low-power audio decoder design compatible with DAB/DAB+ and using a purely ASIC approach is presented. As a result of the system structure optimization and hardware sharing, the audio decoder is fabricated in 1P4M 0.18- μm CMOS technology using only 3.2 mm 2 silicon area (including 147 456 bits RAM and 170 496 bits ROM). The power consumption of the audio decoder is 10.4 mW for DAB audio decoding and 8.5 mW for DAB+ audio decoding. Laboratory and field tests show that the function is correct and the audio quality is good for receiving both DAB and DAB+. The audio decoder is thus proven to be a low-cost low-power solution for the two existing DAB standards.
Digital Audio Broadcasting (DAB) receiver requires fast Automatic Gain Control (AGC) to compensate the strength loss due to the multipath propagation in mobile receiving condition. But fast AGC could ...also incorrectly amplify DAB's null symbol and the following phase reference symbol to cause the synchronization problem. In this paper, we mathematically analyze the AGC circuit under a Rayleigh fading channel and give the basic rule to generate the AGC feedback voltage. Then a fast and high accuracy AGC algorithm with least affection on the DAB null symbol is proposed. The algorithm is simplified to have only add, shift and compare operations, making it easy for hardware and software implementation. Finally the algorithm is simulated and verified on Field Program Gate Array (FPGA) device. The test results show that the proposed AGC algorithm can be settled within 0.5 ms, and keep the received signal stable at a moving speed from stationary to over 120 km/h, both in city and suburban area. The algorithm and the analysis method can also be used for AGC design in other wireless systems.
Perceptual Noise Substitution (PNS) is an important tool used in the Advanced Audio Coding (AAC) standard. The common PNS decoders use the Newton-Raphson method, which applies iterations to calculate ...the adjustment coefficient of the noise. This method is suitable for software AAC decoders, whereas for many portable consumer devices, hardware AAC decoders are preferred to reduce the power consumption. This paper proposes a low complexity PNS decoding algorithm based on partition and linear interpolation method. The proposed algorithm is optimized for hardware implementation, and consumes only 24-31% computations of the Newton-Raphson method, thus reduces the max clock frequency of the decoder and its power consumption. Also the proposed algorithm has nearly the same subjective perception with the Newton-Raphson method.
Digital broadcast has been proved to be the most efficient way to provide messages after heavy disasters where all the communication networks may be damaged. This paper reports several new techniques ...for Digital Audio Broadcast (DAB) to enhance its ability in emergency warning. A novel bidirectional multimedia communication method between two DAB transmitters is also reported. Government in disaster area can use the local DAB transmitter to communicate in multimedia with the outside. These techniques may find a new application area for the DAB system.
Vanadium dioxide (VO2) is a key material for thermochromic smart windows that can respond to environmental temperature to regulate near-infrared transmittance automatically. To date, VO2-based smart ...windows have made great progress, but practical applications still remain restricted by two tough challenges, i.e., low solar regulation ability and unpopular color. In view of the above two challenges, in this paper, novel warm/cool-tone switchable VO2-based composite films were designed and prepared. The novel composite films demonstrate outstanding optical properties: ΔTsol = 18.92% and Tlum,l = 48.70%. The high solar modulation efficiency is attributed to the modulation of the thermochromic microcapsules in visible light waveband and VO2 in near-infrared region. Meanwhile changes in color of the composite films at different temperatures were also studied in order to develop high-performance warm/cool-tone switchable thermochromic smart windows. These promising results will benefit to promote the popularization and application of smart windows.
Two-dimensional (2D) materials have intriguing physical and chemical properties, which exhibit promising applications in the fields of electronics, optoelectronics, as well as energy storage. ...However, the controllable synthesis of 2D materials is highly desirable but remains challenging. Machine learning (ML) facilitates the development of insights and discoveries from a large amount of data in a short time for the materials synthesis, which can significantly reduce the computational costs and shorten the development cycles. Based on this, taking the 2D material MoS2 as an example, the parameters of successfully synthesized materials by chemical vapor deposition (CVD) were explored through four ML algorithms: XGBoost, Support Vector Machine (SVM), Naïve Bayes (NB), and Multilayer Perceptron (MLP). Recall, specificity, accuracy, and other metrics were used to assess the performance of these four models. By comparison, XGBoost was the best performing model among all the models, with an average prediction accuracy of over 88% and a high area under the receiver operating characteristic (AUROC) reaching 0.91. And these findings showed that the reaction temperature (T) had a crucial influence on the growth of MoS2. Furthermore, the importance of the features in the growth mechanism of MoS2 was optimized, such as the reaction temperature (T), Ar gas flow rate (R f), reaction time (t), and so on. The results demonstrated that ML assisted materials preparation can significantly minimize the time spent on exploration and trial-and-error, which provided perspectives in the preparation of 2D materials.
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