Bandwidth Improvement of MMIC Single-Pole-Double-Throw Passive HEMT Switches with Radial Stubs in Impedance-Transformation Networks

In this paper, we propose a new configuration for improving the isolation bandwidth of MMIC single-pole-double-throw (SPDT) passive high-electron-mobility transistor (HEMT) switches operating at millimeter frequency range. While the conventional configuration adopted open-stub loading for compensation of the off-state capacitance, radial stubs were introduced in our approach to improve the operational bandwidth of the SPDT switch. Implemented in 0.15 m GaAs pHEMT technology, the proposed configuration exhibited a measured insertion loss of less than 2.5 dB with better than 30 dB isolation level over the frequency range from 33 GHz to 44 GHz. In terms of the bandwidth of operation, the proposed configuration achieved a fractional bandwidth of 28.5% compared to that of 12.3% for the conventional approach. Such superior bandwidth performance is mainly attributed to the less frequency dependent nature of the radial stubs

Computational Framework for Optimal Carbon Taxes Based on Electric Supply Chain Considering Transmission Constraints and Losses

A modeling and computational framework is presented for the determination of optimal carbon taxes that apply to electric power plants in the context of electric power supply chain with consideration of transmission constraints and losses. In order to achieve this goal, a generalized electric power supply chain network equilibrium model is used. Under deregulation, there are several players in electrical market: generation companies, power suppliers, transmission service providers, and consumers. Each player in this model tries to maximize its own profit and competes with others in a noncooperative manner. The Nash equilibrium conditions of these players in this model form a finite-dimensional variational inequality problem (VIP). By solving this VIP via an extragradient method based on an interior point algorithm, the optimal carbon taxes of power plants can be determined. Numerical examples are provided to analyze the results of the presented modeling

Complement activation mediates cetuximab inhibition of non-small cell lung cancer tumor growth in vivo

<p>Abstract</p> <p>Background</p> <p>Cetuximab, an antibody targeting the epidermal growth factor receptor (EGFR), increases survival in patients with advanced EGFR-positive non-small cell lung cancer when administrated in combination with chemotherapy. In this study, we investigated the role of complement activation in the antitumor mechanism of this therapeutic drug.</p> <p>Results</p> <p>EGFR-expressing lung cancer cell lines were able to bind cetuximab and initiate complement activation by the classical pathway, irrespective of the mutational status of EGFR. This activation led to deposition of complement components and increase in complement-mediated cell death. The influence of complement activation on the activity of cetuximab <it>in vivo </it>was evaluated in xenografts of A549 lung cancer cells on nude mice. A549 cells express wild-type EGFR and have a KRAS mutation. Cetuximab activity against A549 xenografts was highly dependent on complement activation, since complement depletion completely abrogated the antitumor efficacy of cetuximab. Moreover, cetuximab activity was significantly higher on A549 cells in which a complement inhibitor, factor H, was genetically downregulated.</p> <p>Conclusions</p> <p>We demonstrate for the first time that the <it>in vivo </it>antitumor activity of cetuximab can be associated with a complement-mediated immune response. These results may have important implications for the development of new cetuximab-based therapeutic strategies and for the identification of markers that predict clinical response.</p

Analysis of Personal Life Patterns Using Accelerometer-Based Wearable Devices

Many commercially available wearable devices are equipped with sensors to measure motion and physiological signals from the wearer. G-sensors are commonly used in such wearable devices for counting steps, estimating energy expenditure and detecting sleep duration. In this study, two features derived from G-sensor motion signals, average cadence (step count divided by time) and ratio of high G value (outside the range of 0.5g~1.5g), were used to classify physical activities into four intensity levels (sedentary, light, moderate, hard). Eighty physical activity samples were collected and trained by the Weka machine learning software to form a classification model. G-sensor motion signals from four participants were collected over two weeks and classified into four activity intensity levels using the model. Physical activity levels (PAL) and personal life patterns of the participants were then derived. This data can then be used to tailor additional services for individual users of wearable devices. A BLE (Bluetooth Low Energy) based system for older adults with dementia, combining personal life pattern analysis with localization function, is also proposed as an example application.</p

Atomistic Control in Molecular Beam Epitaxy Growth of Intrinsic Magnetic Topological Insulator MnBi2Te4

Intrinsic magnetic topological insulators have emerged as a promising platform to study the interplay between topological surface states and ferromagnetism. This unique interplay can give rise to a variety of exotic quantum phenomena, including the quantum anomalous Hall effect and axion insulating states. Here, utilizing molecular beam epitaxy (MBE), we present a comprehensive study of the growth of high-quality MnBi2Te4 thin films on Si (111), epitaxial graphene, and highly ordered pyrolytic graphite substrates. By combining a suite of in-situ characterization techniques, we obtain critical insights into the atomic-level control of MnBi2Te4 epitaxial growth. First, we extract the free energy landscape for the epitaxial relationship as a function of the in-plane angular distribution. Then, by employing an optimized layer-by-layer growth, we determine the chemical potential and Dirac point of the thin film at different thicknesses. Overall, these results establish a foundation for understanding the growth dynamics of MnBi2Te4 and pave the way for the future applications of MBE in emerging topological quantum materials.Comment: 20 pages, 4 figure

Computational Framework for Optimal Carbon Taxes Based on Electric Supply Chain Considering Transmission Constraints and Losses

A modeling and computational framework is presented for the determination of optimal carbon taxes that apply to electric power plants in the context of electric power supply chain with consideration of transmission constraints and losses. In order to achieve this goal, a generalized electric power supply chain network equilibrium model is used. Under deregulation, there are several players in electrical market: generation companies, power suppliers, transmission service providers, and consumers. Each player in this model tries to maximize its own profit and competes with others in a noncooperative manner. The Nash equilibrium conditions of these players in this model form a finite-dimensional variational inequality problem (VIP). By solving this VIP via an extragradient method based on an interior point algorithm, the optimal carbon taxes of power plants can be determined. Numerical examples are provided to analyze the results of the presented modeling

Room-temperature biphoton source with a spectral brightness near the ultimate limit

The biphotons, generated from a hot atomic vapor via the process of spontaneous four-wave mixing (SFWM), have the following merits: stable and tunable frequencies as well as linewidth. Such merits are very useful in the applications of long-distance quantum communication. However, the hot-atom SFWM biphoton sources previously had far lower values of generation rate per linewidth, i.e., spectral brightness, as compared with the sources of biphotons generated by the spontaneous parametric down conversion (SPDC) process. Here, we report a hot-atom SFWM source of biphotons with a linewidth of 960 kHz and a generation rate of 3.7$\times$ $10^5$ pairs/s. The high generation rate, together with the narrow linewidth, results in a spectral brightness of 3.8$\times$ $10^5$ pairs/s/MHz, which is 17 times of the previous best result with atomic vapors and also better than all known results with all kinds of media. The all-copropagating scheme together with a large optical depth (OD) of the atomic vapor is the key improvement, enabling the achieved spectral brightness to be about one quarter of the ultimate limit. Furthermore, this biphoton source had a signal-to-background ratio (SBR) of 2.7, which violated the Cauchy-Schwartz inequality for classical light by about 3.6 folds. Although an increasing spectral brightness usually leads to a decreasing SBR, our systematic study indicates that both of the present spectral brightness and SBR can be enhanced by further increasing the OD. This work demonstrates a significant advancement and provides useful knowledge in the quantum technology using photons

The effect of exercise on the risk of metabolic syndrome associated with sleep insufficiency: a cross-sectional study

IntroductionSleep disturbance and insufficient sleep have been linked to metabolic syndrome, increasing cardiovascular disease and mortality risk. However, few studies investigate the joint effect of sleep and exercise on metabolic syndrome. We hypothesized that regular exercise can mitigate the exacerbation of metabolic syndrome by sleep insufficiency.ObjectiveThe aim of this study was to investigate whether exercise can attenuate or eliminate the relationship between sleep insufficiency and metabolic syndrome.MethodA total of 6,289 adults (mean age = 33.96 years; women: 74.81%) were included in the study, a cross-sectional study conducted based on the results of employee health screening questionnaires and databases from a large healthcare system in central Taiwan. Participants reported sleep insufficiency or not. Self-reported exercise habits were classified into 3 levels: no exercise, exercise &lt;150 min/week, and exercise ≧150 min/week. Multiple logistic regression and sensitivity analyses were conducted to understand the joint associations of sleep patterns and exercise with metabolic syndrome with exposure variables combining sleep duration/disturbances and PA.ResultsCompared with the reference group (sufficient sleep), individuals with sleep insufficiency had a higher risk for metabolic syndrome [adjusted odds ratio (AOR) = 1.40, 95% confidence interval (95% CI): 1.01–1.94, p &lt; 0.05] in females aged 40–64 years, but not in other populations. Sleep insufficiency was not associated with the risk of metabolic syndrome among individuals achieving an exercise level of &lt;150 min/week, and in particular among those achieving ≧150 min/week in all populations in our study.ConclusionSleep insufficiency was related to a higher risk of metabolic syndrome in female healthcare staff aged 40–64 years. Being physically active with exercise habits in these individuals, the risk of metabolic syndrome was no longer significant