NARROW BAND PEROVSKITE SINGLE CRYSTAL PHOTODETECTORS WITH TUNABLE SPECTRAL RESPONSE

Photoelectronic devices using perovskite single-crystal materials having a narrow spectral response, e.g., with a full-width-at-half-maximum response of less than about 20 nm, are provided. The response spectra are continuously (in frequency band) settable or tunable, e.g., from blue to red, by changing the halide composition and thus the band gap of the single crystals. The narrow-band response can be explained by the strong surface charge recombination of the excess carriers lose to the crystal surfaces generated by short wavelength light. The excess carriers generated by below-band gap excitation locate away from the surfaces and can be much more efficiently collect by the electrodes to produce a photocurrent

Anti-Idling Systems for Service Vehicles with A/C-R Units: Modeling, Holistic Control, and Experiments

As people have begun to pay more attention to energy conservation and emission reduction in recent years, anti-idling has become a growing concern for automobile engineers due to the low efficiency and high emissions caused by engine idling, i.e., the engine is running when the vehicle is not moving. Currently, different technologies and products have emerged in an effort to minimize engine idling. By studying and comparing most of these methods, the conclusion can be drawn that there is still much room to improve existing anti-idling technologies and products. As a result, the optimized Regenerative Auxiliary Power System (RAPS) is proposed. Service vehicles usually refer to a class of vehicles that are used for special purposes, such as public buses, delivery trucks, and long-haul trucks. Among them, there are vehicles with auxiliary devices such as air conditioning or refrigeration (A/C-R) systems that are essential to be kept running regardless of the vehicle motion. In addition, such auxiliary systems usually account for a large portion of fuel from the tank. Food delivery trucks, tourist buses, and cement trucks are examples of such service vehicles. As a leading contributor to greenhouse gas emissions, these vehicles sometimes have to frequently idle to for example keep people comfortable, and keep food fresh on loading and unloading stops. This research is intended to develop and implement a novel RAPS for such service vehicles with the A/C-R system as the main auxiliary device. The proposed RAPS can not only electrify the auxiliary systems to achieve anti-idling but also use regenerative braking energy to power them. As the main power consuming device, the A/C-R system should be treated carefully in terms of its efficiency and performance. Thus, the developments of an advanced controller for A/C-R system to minimize energy consumption and an optimum power management system to maximize the overall efficiency of the RAPS are the primary objectives of this thesis. In this thesis, a model predictive controller (MPC) is designed based on a new A/C-R simplified model to minimize the power consumption while meeting the temperature requirements. The controller is extensively validated under both common and frosting conditions. Meanwhile, after integrating the RAPS into a service vehicle, its powertrain turns into a parallel hybrid system due to the addition of an energy storage system (ESS). For the sake of maximizing the overall efficiency, RAPS requires a power management controller to determine the power flow between different energy sources. As a result, a predictive power management controller is developed to achieve this objective, where a regenerative iv braking control strategy is developed to meet the driver’s braking demand while recovering the maximum braking energy when vehicles brake. For the implementation of the above controllers, a holistic controller of the RAPS is designed to deal with the auxiliary power minimization and power management simultaneously so as to maximize the overall energy efficiency and meet the high nonlinearities and wide operating conditions

Turmeric and black pepper spices decrease lipid peroxidation in meat patties during cooking.

Spices are rich in natural antioxidants and have been shown to be potent inhibitors of lipid peroxidation during cooking of meat. Turmeric contains unique conjugated curcuminoids with strong antioxidant activity. Piperine, one of the main constituents of black pepper, is known to increase the bioavailability of curcuminoids in mouse and human studies when consumed with turmeric. We investigated whether adding black pepper to turmeric powder may further inhibit lipid peroxidation when added to meat patties prior to cooking. The addition of black pepper to turmeric significantly decreased the lipid peroxidation in hamburger meat. When investigating the antioxidant activity of the main chemical markers, we determined that piperine did not exhibit any antioxidant activity. Therefore, we conclude that other black pepper ingredients are responsible for the increased antioxidant activity of combining black pepper with turmeric powder

Testing the Behavioral Life-Cycle Model fore Saving and Consumption.

Abstract The conflict between behavioral finance and standard finance came to the attention of economists since they recognized the importance of psychology in finance. This paper focuses on the empirical study of the behavioral life-cycle model that is a derivative model based on three concepts of behavioral finance, including self-control, mental accounting, and frame dependence. Through testing the differential marginal propensity to consume (MPC) hypothesis and the magnitude of the offset between pension saving and discretionary saving, the results show that the empirical evidence is more consistent with behavioral life-cycle theory

Testing the Behavioral Life-Cycle Model for Saving and Consumption

Abstract The conflict between behavioral finance and standard finance came to the attention of economists since they recognized the importance of psychology in finance. This paper focuses on the empirical study of the behavioral life-cycle model that is a derivative model based on three concepts of behavioral finance, including self-control, mental accounting, and frame dependence. Through testing the differential marginal propensity to consume (MPC) hypothesis and the magnitude of the offset between pension saving and discretionary saving, the results show that the empirical evidence is more consistent with behavioral life-cycle theory

Artificial intelligence-aided rapid and accurate identification of clinical fungal infections by single-cell Raman spectroscopy

Integrating artificial intelligence and new diagnostic platforms into routine clinical microbiology laboratory procedures has grown increasingly intriguing, holding promises of reducing turnaround time and cost and maximizing efficiency. At least one billion people are suffering from fungal infections, leading to over 1.6 million mortality every year. Despite the increasing demand for fungal diagnosis, current approaches suffer from manual bias, long cultivation time (from days to months), and low sensitivity (only 50% produce positive fungal cultures). Delayed and inaccurate treatments consequently lead to higher hospital costs, mobility and mortality rates. Here, we developed single-cell Raman spectroscopy and artificial intelligence to achieve rapid identification of infectious fungi. The classification between fungi and bacteria infections was initially achieved with 100% sensitivity and specificity using single-cell Raman spectra (SCRS). Then, we constructed a Raman dataset from clinical fungal isolates obtained from 94 patients, consisting of 115,129 SCRS. By training a classification model with an optimized clinical feedback loop, just 5 cells per patient (acquisition time 2 s per cell) made the most accurate classification. This protocol has achieved 100% accuracies for fungal identification at the species level. This protocol was transformed to assessing clinical samples of urinary tract infection, obtaining the correct diagnosis from raw sample-to-result within 1 h

An Empirical Study on the Determinants of Labor Entering Monopoly Industry in China’s Urban Labor Market

Industrial segmentation of the labor market is an important factor which causes the wage inequality in China’s urban labor market. This paper aims to investigate the determinants which help people entering monopoly industry by building a logistic model using CHIP data. The results show that the workers’ education, work experience and age are more helpful for labor entering monopoly industry in China’s urban labor market. Compared with the local residents with the same human capital, the probability of the floating population entering the monopoly industry is much smaller.Key words: Industrial segmentation; Urban labor market; Logistic mode

Improving the sensitivity of a near-infrared nanocomposite photodetector by enhancing trap induced hole injection

We report the enhancement of the photoconductive gain of nanocomposite near-infrared photodetectors by a zinc oxide nanoparticles (ZnO NPs) rich surface at the nanocomposite/cathode interface. An argon plasma etching process was used to remove polymer at the surface of nanocomposite films, which resulted in a ZnO NPs rich surface. The other way is to spin-coat a thin layer of ZnO NPs onto the nanocomposite layer. The ZnO NPs rich surface, which acts as electron traps to induce secondary hole injection under reverse bias, increased hole injection, and thus the external quantum efficiency by 2–3 times. The darkcurrent declined one order of magnitude simultaneously as a result of etching the top nanocomposite layer. The specific detectivity at 800 nm was increased by 7.4 times to 1.11x1010 Jones due to the simultaneously suppressed noise and enhanced gain