From the macroscopic to the microscopic world, quantum mechanical effects in acoustics and elastic waves have become increasingly important. Observations on the quantum effects of acoustic and ...elastic waves using experimental methods have been reported in the literature. However, the conventional formulations of acoustic and elastic waves are still mainly governed by classical models. In this study, we investigated the quantization of acoustic and elastic waves using generalized Lorenz gauges. The potential variables of acoustic and elastic waves can be quantized in a manner similar to that of electrodynamics. The results include the Schrödinger equation with minimal coupling between the field and particles. The quantization of field variables is established as a consequence of the gauge symmetry property of the Schrödinger equation. Later, we explored the connections between the parallel formulations of mechanics and waves through an algebraic aspect. This highlights the isomorphism pattern from the theoretical characterization within the parallel formulations. To support the results, the derivations of potential formulations based on Lorenz gauges and functional mapping between field variables are presented.
It has been long appreciated that precipitation falls unevenly in time, but the degree of unevenness and its changes with warming have been seldomly quantified. These quantifications, however, matter ...to various sectors (e.g. crop and livestock yields) for addressing evolutionary hydro-meteorological hazards. Using gauge observations at hourly- and daily-resolution, precipitation unevenness is measured by the number of wettest days/hours for half of seasonal precipitation totals over Eastern China, a major breadbasket vulnerable to precipitation volatility intra-seasonally. Across the region, half of seasonal totals needs only 11 d or even more unexpectedly just 44 h to precipitate. During 1970-2017, though seasonal precipitation amount changed little, the intra-seasonal distribution of precipitation, in both frequency and amount, has been getting significantly more uneven, with more widespread and faster changes manifesting in hourly records. The regional-scale unevenness increase is unlikely modulated by internal variability alone, suggesting detectable contributions from anthropogenic climate change. The increased unevenness has led to significant lengthening of the longest dry spells, exposing the region to a more volatile precipitation mode-burstier-but-wetter storms with prolonged droughts in-between.
Display omitted
•WGSR is an important reaction for H2 production and CO2 capture.•A comprehensive review of the research progress in the WGSR is given.•State-of-the-art thermodynamic and kinetic ...characteristics of the WGSR are underlined.•WGSR behaviors in certain special environments are emphasized.•WGSR in membrane reactors for carbon capture and H2 production is addressed.
The water gas shift reaction is an important and commonly employed reaction in the industry. In the water gas shift reaction, hydrogen is produced from water or steam while carbon monoxide is converted into carbon dioxide. Over the years, on account of the progress in hydrogen energy and carbon capture and storage for developing alternative fuels and mitigating the atmospheric greenhouse effect, the water gas shift reaction has become a crucial route to simultaneously reach the requirements of hydrogen production and carbon dioxide enrichment, thereby enhancing CO2 capture. This article provides a comprehensive review of the research progress in the water gas shift reaction, with particular attention paid to the thermodynamic and kinetic characteristics. The performance of the water gas shift reaction highly depends on the adopted catalysts whose progress in recent years is extensively reviewed. The behaviors of the water gas shift reaction in special environments are also illustrated, several cases have the ability to proceed with water gas shift reaction without any catalyst. The utilization of several separation technologies on the water gas shift reaction such as carbon capture and storage and membrane reactors for purifying hydrogen and enriching carbon dioxide will be addressed as well. Reviewing past studies suggests that separating hydrogen and carbon dioxide in the product gas from the water gas shift reaction can not only increase efficiency but also enhance the usability for further application. The CO conversion is beyond the thermodynamic limitation after applying membrane for the water gas shift reaction.
Research on uncertainty-oriented optimal attitude control of spacecraft with complex space environments and multi-source uncertainties is a research hotspot. Considering that the uncertain parameters ...in the control system are difficult to quantify, this study proposed an interval uncertainty-oriented optimal control method based on the linear quadratic regulator (LQR) for spacecraft attitude control. The interval state-space equation of the spacecraft attitude dynamic with uncertain controlled feedback gain was constituted by expanding the deterministic model into an order-extended interval matrix format. Based on the interval uncertainty propagation method, the interval-based Riccati equation in LQR was proposed using the modified interval estimation method. Therefore, the interval-controlled feedback gain and interval cost function could be obtained, and the overestimation attributed to the interval expansion could be avoided. The interval-based reliability was investigated using the state-threshold interference model, and the interval-based safety index was developed. The interval uncertainty-based multi-objective optimal control model with constraints was proposed to balance both minimizations of the optimal control cost function and state vector fluctuation by considering these two interval indices as the constraints in optimal control. A flowchart and a numerical example of satellite attitude control were applied to reflect the effectiveness.
Chemotherapy has been widely applied in clinics. However, the therapeutic potential of chemotherapy against cancer is seriously dissatisfactory due to the nonspecific drug distribution, multidrug ...resistance (MDR) and the heterogeneity of cancer. Therefore, combinational therapy based on chemotherapy mediated by nanotechnology, has been the trend in clinical research at present, which can result in a remarkably increased therapeutic efficiency with few side effects to normal tissues. Moreover, to achieve the accurate pre-diagnosis and real-time monitoring for tumor, the research of nano-theranostics, which integrates diagnosis with treatment process, is a promising field in cancer treatment. In this review, the recent studies on combinational therapy based on chemotherapy will be systematically discussed. Furthermore, as a current trend in cancer treatment, advance in theranostic nanoparticles based on chemotherapy will be exemplified briefly. Finally, the present challenges and improvement tips will be presented in combination therapy and nano-theranostics.
Abstract This article deals with the robust planar rigid formation control problem of three second‐order coleaders with unknown flowfields acting on the velocity and acceleration respectively. To ...yield the uniform boundedness property of the resulting system, an adaptive projection is introduced to design the novel adaptive neural control law. To avoid the derivatives of Gaussian functions of neural networks, dynamic surface is used. Simulation results are provided to illustrate the effectiveness of the proposed control law.
Hybrid flow shop scheduling problems are encountered in many real-world manufacturing operations such as computer assembly, TFT-LCD module assembly, and solar cell manufacturing. Most research ...considers the scheduling problem in regard to time requirements and the steps needed to improve production efficiency. However, the increasing amount of carbon emissions worldwide is contributing to the worsening global warming problem. Many countries and international organizations have started to pay attention to this problem, even creating mechanisms to reduce carbon emissions. Furthermore, manufacturing enterprises are showing growing interest in realizing energy savings. Thus, the present research study focuses on reducing energy costs and completion time at the manufacturing-system level. This paper proposed a multi-objective mixed-integer programming for energy-efficient hybrid flow shop scheduling with lot streaming in order to minimize both the production makespan and electric power consumption. Due to a trade-off between these objectives and the computational complexity of the proposed multi-objective mixed-integer program, this study adopts the genetic algorithm (GA) to obtain approximate Pareto solutions more efficiently. In addition, a multi-objective energy efficiency scheduling algorithm is also developed to calculate the fitness values of each chromosome in GA.
A novel non-probabilistic sensor placement method for structural health monitoring is proposed with interval numbers based on the relationship of interval for sensor number (RISEN) index, and an ...iterative multiobjective optimization algorithm is constituted to optimize sensor placement. To avoid the limitation of scarce statistical information, the interval objectives of effective independence and eigenvalue vector product methods are derived. To overcome the inaccuracy of sensor number decisions using the determinate methods in uncertain cases, the novel RISEN index is defined to ascertain the best sensor number. Considering the number and locations of sensors as two types of design variables, two methods are regarded as optimization objectives, which are composed of the multiobjective optimal sensor placement methods. Based on the modified hypervolume evaluation index, an iterative multiobjective optimization algorithm is investigated using the updating process to improve the efficiency of the sensor placement. The validity of the method is proven using four examples.
This paper proposes a framework to perform the sensor classification by using multivariate time series sensors data as inputs. The framework encodes multivariate time series data into two-dimensional ...colored images, and concatenate the images into one bigger image for classification through a Convolutional Neural Network (ConvNet). This study applied three transformation methods to encode time series into images: Gramian Angular Summation Field (GASF), Gramian Angular Difference Field (GADF), and Markov Transition Field (MTF). Two open multivariate datasets were used to evaluate the impact of using different transformation methods, the sequences of concatenating images, and the complexity of ConvNet architectures on classification accuracy. The results show that the selection of transformation methods and the sequence of concatenation do not affect the prediction outcome significantly. Surprisingly, the simple structure of ConvNet is sufficient enough for classification as it performed equally well with the complex structure of VGGNet. The results were also compared with other classification methods and found that the proposed framework outperformed other methods in terms of classification accuracy.
Background
Women and their health care providers need a reliable answer to this important question: If a woman chooses to participate in regular mammography screening, then how much will this choice ...improve her chances of avoiding a death from breast cancer compared with women who choose not to participate?
Methods
To answer this question, we used comprehensive registries for population, screening history, breast cancer incidence, and disease‐specific death data in a defined population in Dalarna County, Sweden. The annual incidence of breast cancer was calculated along with the annual incidence of breast cancers that were fatal within 10 and within 11 to 20 years of diagnosis among women aged 40 to 69 years who either did or did not participate in mammography screening during a 39‐year period (1977‐2015). For an additional comparison, corresponding data are presented from 19 years of the prescreening period (1958‐1976). All patients received stage‐specific therapy according to the latest national guidelines, irrespective of the mode of detection.
Results
The benefit for women who chose to participate in an organized breast cancer screening program was a 60% lower risk of dying from breast cancer within 10 years after diagnosis (relative risk, 0.40; 95% confidence interval, 0.34‐0.48) and a 47% lower risk of dying from breast cancer within 20 years after diagnosis (relative risk, 0.53; 95% confidence interval, 0.44‐0.63) compared with the corresponding risks for nonparticipants.
Conclusions
Although all patients with breast cancer stand to benefit from advances in breast cancer therapy, the current results demonstrate that women who have participated in mammography screening obtain a significantly greater benefit from the therapy available at the time of diagnosis than do those who have not participated.
After 20 years of follow‐up, women who participate in mammography screening have a 47% lower risk of dying from breast cancer. Although all patients with breast cancer potentially can benefit from advances in breast cancer therapy, women who participate in mammography screening obtain a significantly greater benefit from the therapy available at the time of diagnosis than those who do not participate.
PDF
