Invited - Metal-oxide thin-film transistor: An enabling technology for smart sensor construction and 3-D monolithic integration

Presently described is a 300 oC TFT technology based on semiconducting MOs. A parallel, double-gate (DG) TFT with its channel sandwiched between two gate electrodes can be readily realized (Fig. 1). The threshold voltage referenced to one electrode of such a TFT can be modulated by the bias applied on the other electrode (Fig. 2). The TFTs could be applied as signal-coupling elements in a tactile sensor array to couple the output of the PVDF sensor to an in-pixel amplifier (inset of Fig. 3). The piezo-cap is elevated above all other features by proper stacking of the component layers, thus facilitating the sampling of a distributed force load applied on the top of the sensor (Fig. 3). Please click Download on the upper right corner to see the full abstract

Stochastic optimization of carbon mitigation path in Shenzhen based on uncertainty of power demand

The core elements of urban carbon emission mitigation optimization path include structural adjustment, low energy supply, technological innovation, and enhanced energy demand management and improvement. How to optimize the combination of these factors to achieve the city’s emission mitigation goals at the lowest cost is very important to study the path of urban low-carbon development. Due to many factors involved, it is difficult to solve this problem by building a mathematical optimization model that includes all the elements. This paper minimizes the total cost of emission mitigations in various departments in Shenzhen, combines the uncertainty of parameters and constraints, and uses mathematically standardized method to establish a stochastic optimization model for urban carbon emissions paths. Considering the uncertainty of energy demand, the optimal promotion rate of technical measures of the city’s various departments in the stochastic optimization model during the planning period can be obtained, and the optimal solution of the city’s low-carbon development optimization path can be formed

Real-Time Adjustment Method for Metro Systems with Train Delays Based on Improved Q-Learning

This paper presents a solution to address the challenges of unexpected events in the operation of metro trains, which can lead to increased delays and safety risks. An improved Q-learning algorithm is proposed to reschedule train timetables via incorporating train detention and different section running times as actions. To enhance computational efficiency and convergence rate, a simulated annealing dynamic factor is introduced to improve action selection strategies. Additionally, importance sampling is employed to evaluate different policies effectively. A case study of Shenzhen Metro is conducted to demonstrate the effectiveness of the proposed method. The results show that the method achieves convergence, fast computation speed, and real-time adjustment capabilities. Compared to traditional methods such as no adjustment, manual adjustment, and FIFO (First-In-First-Out), the proposed method significantly reduces the average total train delay by 54% and leads to more uniform train headways. The proposed method utilizes a limited number of variables for practical state descriptions, making it well suited for real-world applications. It also exhibits good scalability and transferability to other metro systems

Evaluation of the robusticity of mutual fund performance in Ghana using Enhanced Resilient Backpropagation Neural Network (ERBPNN) and Fast Adaptive Neural Network Classifier (FANNC)

Abstract Mutual fund investment continues to play a very important role in the world financial markets especially in developing economies where the capital market is not very matured and tolerant of small scale investors. The total mutual fund asset globally as at the end of 2016 was in excess of $40.4 trillion. Despite its success there are uncertainties as to whether mutual funds in Ghana obtain optimal performance relative to their counterparts in United States, Luxembourg, Ireland, France, Australia, United Kingdom, Japan, China and Brazil. We contribute to the extant literature on mutual fund performance evaluation using a collection of more sophisticated econometric models. We selected six continuous historical years that is 2010–2011, 2012–2013 and 2014–2015 to construct a mutual fund performance evaluation model utilizing the fast adaptive neural network classifier (FANNC), and to compare our results with those from an enhanced resilient back propagation neural networks (ERBPNN) model. Our FANNC model outperformed the existing models in terms of processing time and error rate. This makes it ideal for financial application that involves large volume of data and routine updates

Annealing Engineering in the Growth of Perovskite Grains

Perovskite solar cells (PSCs) are a promising and fast-growing type of photovoltaic cell due to their low cost and high conversion efficiency. The high efficiency of PSCs is closely related to the quality of the photosensitive layer, and the high-quality light absorbing layer depends on the growth condition of the crystals. In the formation of high-quality crystals, annealing is an indispensable and crucial part, which serves to evaporate the solvent and drive the crystallization of the film. Various annealing methods have different effects on the promotion of the film growth process owing to the way they work. Here, this review will present a discussion of the growth puzzles and quality of perovskite crystals under different driving forces, and then explain the relationship between the annealing driving force and crystal growth. We divided the main current annealing methods into physical and chemical annealing, which has never been summarized before. The main annealing methods currently reported for crystal growth are summarized to visualize the impact of annealing design strategies on photovoltaic performance, while the growth mechanisms of thin films under multiple annealing methods are also discussed. Finally, we suggest future perspectives and trends in the industrial fabrication of PSCs in the future. The review promises industrial manufacturing of annealed PSCs. The review is expected to facilitate the industrial fabrication of PSCs

MYC-induced reprogramming of glutamine catabolism supports optimal virus replication.

Viruses rewire host cell glucose and glutamine metabolism to meet the bioenergetic and biosynthetic demands of viral propagation. However, the mechanism by which viruses reprogram glutamine metabolism and the metabolic fate of glutamine during adenovirus infection have remained elusive. Here, we show MYC activation is necessary for adenovirus-induced upregulation of host cell glutamine utilization and increased expression of glutamine transporters and glutamine catabolism enzymes. Adenovirus-induced MYC activation promotes increased glutamine uptake, increased use of glutamine in reductive carboxylation and increased use of glutamine in generating hexosamine pathway intermediates and specific amino acids. We identify glutaminase (GLS) as a critical enzyme for optimal adenovirus replication and demonstrate that GLS inhibition decreases replication of adenovirus, herpes simplex virus 1 and influenza A in cultured primary cells. Our findings show that adenovirus-induced reprogramming of glutamine metabolism through MYC activation promotes optimal progeny virion generation, and suggest that GLS inhibitors may be useful therapeutically to reduce replication of diverse viruses

Annealing Engineering in the Growth of Perovskite Grains

Perovskite solar cells (PSCs) are a promising and fast-growing type of photovoltaic cell due to their low cost and high conversion efficiency. The high efficiency of PSCs is closely related to the quality of the photosensitive layer, and the high-quality light absorbing layer depends on the growth condition of the crystals. In the formation of high-quality crystals, annealing is an indispensable and crucial part, which serves to evaporate the solvent and drive the crystallization of the film. Various annealing methods have different effects on the promotion of the film growth process owing to the way they work. Here, this review will present a discussion of the growth puzzles and quality of perovskite crystals under different driving forces, and then explain the relationship between the annealing driving force and crystal growth. We divided the main current annealing methods into physical and chemical annealing, which has never been summarized before. The main annealing methods currently reported for crystal growth are summarized to visualize the impact of annealing design strategies on photovoltaic performance, while the growth mechanisms of thin films under multiple annealing methods are also discussed. Finally, we suggest future perspectives and trends in the industrial fabrication of PSCs in the future. The review promises industrial manufacturing of annealed PSCs. The review is expected to facilitate the industrial fabrication of PSCs

Rapid and sensitive determination of ascorbic acid based on label-free silver triangular nanoplates

In this study, a new method for the detection of ascorbic acid (AA) was proposed. It was based on the protective effect of AA on silver triangular nanoplates (Ag TNPs) against Cl− induced etching reactions. Cl− can attack the corners of Ag TNPs and etch them, causing a morphological shift from triangular nanoplates to nanodiscs. As a result, the solution changes color from blue to yellow. However, in the presence of AA, the corners of Ag TNPs can be protected from Cl− etching, and the blue color of the solution remains unchanged. Using this effect, a selective sensor was designed to detect AA in the range of 0–40.00 μM with a detection limit of 2.17 μM. As the concentration of AA varies in this range, color changes from yellow to blue can be easily observed, so the designed sensor can be used for colorimetric detection. This method can be used to analyze fruit juice samples