Miracle-dz/UniFAR-FTUs huggingface dataset:
$\beta$ -Ga2O3 Delta-Doped Field-Effect Transistors With Current Gain Cutoff Frequency of 27 GHz

As an ultra-wide bandgap semiconductor, <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub> has attracted great attention for high-power, high-voltage, and optoelectronic applications. However, until now, high-frequency performance of gallium oxide devices has been limited to relatively low current gain cutoff frequencies below 5 GHz. Here, we show that highly localized delta-doping designs can enable high-sheet-charge density to enable devices with short gate lengths that allow high-frequency operation. Field-effect transistors with a gate length of 120 nm on such delta-doped <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub> are reported here with extrinsic unity current gain frequency of 27 GHz. The device has a peak drain current of 260 mA/mm, transconductance (gm) of 44 mS/mm, and three-terminal off-state breakdown voltage of 150 V. These results demonstrate that the potential of <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub> for future RF and millimeter-wave device applications.
Nowcasting by Bayesian Smoothing: A flexible, generalizable model for real-time epidemic tracking

Delays in case reporting are common to disease surveillance systems, making it difficult to track diseases in real-time. “Nowcast” approaches attempt to estimate the complete case counts for a given reporting date, using a time series of case reports that is known to be incomplete due to reporting delays. Modeling the reporting delay distribution is a common feature of nowcast approaches. However, many nowcast approaches ignore a crucial feature of infectious disease transmission—that future cases are intrinsically linked to past reported cases—and are optimized to a single application, which may limit generalizability. Here, we present a Bayesian approach, NobBS (Nowcasting by Bayesian Smoothing) capable of producing smooth and accurate nowcasts in multiple disease settings. We test NobBS on dengue in Puerto Rico and influenza-like illness (ILI) in the United States to examine performance and robustness across settings exhibiting a range of common reporting delay characteristics (from stable to time-varying), and compare this approach with a published nowcasting package. We show that introducing a temporal relationship between cases considerably improves performance when the reporting delay distribution is time-varying, and we identify trade-offs in the role of moving windows to accurately capture changes in the delay. We present software implementing this new approach (R package “NobBS”) for widespread application. Significance Achieving accurate, real-time estimates of disease activity is challenged by delays in case reporting. However, approaches that seek to estimate cases in spite of reporting delays often do not consider the temporal relationship between cases during an outbreak, nor do they identify characteristics of robust approaches that generalize to a wide range of surveillance contexts with very different reporting delays. Here, we present a smooth Bayesian nowcasting approach that produces accurate estimates that capture the time evolution of the epidemic curve and outperform a previous approach in the literature. We assess the performance for two diseases to identify important features of the reporting delay distribution that contribute to the model’s performance and robustness across surveillance settings.
A K-Band Complex Permittivity Sensor for Biomedical Applications in 130-nm SiGe BiCMOS

In this brief, an integrated K-band complex permittivity sensor for characterization of biomaterials is presented. The circuit enables determining both real and imaginary part of the permittivity of a material under test exposed to the sensor. We propose several enhancements of the classical capacitive sensing concept, which is based on an oscillator with a resonant tank and a capacitor realized as an integrated stub. To resolve the inherent trade-off of this method between sensitivity to variation of <inline-formula> <tex-math notation="LaTeX">${\varepsilon }$ </tex-math></inline-formula>’ and frequency tuning range of the oscillator, we propose using magnetic tuning of the resonant tank inductor. Additionally, the amplitude of oscillation gives an indication about the quality factor of the resonant tank, which can be translated into material losses, quantified by <inline-formula> <tex-math notation="LaTeX">${\varepsilon }$ </tex-math></inline-formula>” or loss tangent. To guarantee the oscillator startup even for high loss materials, we propose using a feedback loop sensing the amplitude of the oscillation and controlling the bias current. Finally, we integrate a digitally tunable reflection type phase shifter to enhance the sensitivity. The chip is fabricated in a 130-nm SiGe BiCMOS technology. It consumes only 24 mA from a single 1.5-V supply and occupies a chip area of 1.8 mm<sup>2</sup>. The sensor has been calibrated using ethanol–water solutions in steps of 5% of concentration change.
Navigating Coexistence: Ecological Drivers and Social Implications of Predator-induced Regime Shifts in the Northeast Pacific

While changes in the abundance of keystone predators can have cascading effects resulting in regime shifts, the role of mesopredators in these processes remains underexplored. We conducted annual surveys of rocky reef communities that varied in the recovery of a keystone predator (sea otters Enhydra lutris) and the mass mortality of a mesopredator (sunflower sea star Pycnopodia helianthoides) due to an infectious wasting disease. By fitting a population model to empirical data, we show that sea otters had the greatest impact on the mortality of large sea urchins, but that Pycnopodia decline corresponded to a 311% increase in medium urchins and a 30% decline in kelp densities. Our results reveal predator complementarity in size-selective prey consumption strengthens top-down control on urchins, affecting the resilience of alternative reef states by reinforcing the resilience of kelp forests and eroding urchin barrens. We reveal previously underappreciated species interactions within a ‘classic’ trophic cascade and regime shift, highlighting the critical role of middle-level predators in mediating rocky reef state transitions.
Board 48: Analysis of a Trial of Mentoring between Civil Engineering Students and Practicing Engineers

Mark Milke is a Professor in the Department of Civil and Natural Resources Engineering, University of Canterbury, in Christchurch, New Zealand. Since 1991 he has taught and conducted research there on solid waste management, design for civil and natural resources engineers, systems, professional development, and other topics in civil and environmental engineering. He was an Associate Editor for the international research journal Waste Management from 2003-2009, and is currently AE for Civil Engineering and Environmental Systems. He has a BSc from Harvey Mudd College, a MSc from Univ. Wisconsin—Madison, and a PhD from Carnegie Mellon University, and he is a New Zealand Chartered Professional Engineer. From 2009-2017 he has led the curriculum review process in his department, and has been a leader in curriculum innovations by developing new courses in engineering design, communication skills portfolio, and professional engineering development.
Subjective and objective quality reporting and choice of hospital: Evidence from maternal care services in Germany

We study patient choice of healthcare provider based on both objective and subjective quality measures in the context of maternal care hospital services in Germany. Objective measures are obtained from publicly reported clinical indicators, while subjective measures are based on satisfaction scores from a large and nationwide patient survey. We merge both quality metrics to detailed hospital discharge records and quantify the additional distance expectant mothers are willing to travel to give birth in maternity clinics with higher reported quality. Our results reveal that patients are on average willing to travel between 0.7-4.2 additional kilometers for a one standard deviation increase in reported quality. Furthermore, patients respond independently to both objective and subjective quality measures, suggesting that satisfaction scores may constitute important complements to clinical indicators when choosing healthcare provider. JEL Classifications: C25, D82, H51, I11, I18.
Demography, clinical profile, morbidity and mortality pattern of snake bite cases in children: a study at tertiary teaching hospital

Background: Snake bite is one of the important health problems in tropical and sub-tropical countries including India. Most snake bites present without envenomation as most bites are usually due to non-poisonous snakes and even poisonous snakes can control amount of venom injected. Even though mortality is under reported, India accounts for most of deaths due to snake bite.Methods: A hospital based descriptive case study was conducted at Pediatric ward of VIMS Ballari. All children with definite history of snake bite with fang marks or features of local/systemic envenomation were included in study. Demographic parameters, symptomatology and complications were noted down as per pro forma and data was analyzed.Results: Most bites occurred in lower limbs in older children while playing outdoors. Most cases were from rural area. Majority presented with local toxicity followed by hemotoxicity and neuroparalysis. Two children died, one because of respiratory paralysis and other by acute kidney injury.Conclusions: Snake bite is a preventable health problem. By wearing protective shoes and avoiding outdoor sleep many snake bites can be avoided. Early, aggressive but judicious use of antisnake venom is a cornerstone of management.
Supplementary Materials for UnOS: Uniﬁed Unsupervised Optical-ﬂow and Stereo-depth Estimation by Watching Videos

The whole system was implemented using Tensorflow [1]. When minimizing Eq. 5 in the RDVO module, we used the 3D representation described as in the last line of Eq. 6. When calculating the rigid-aware flow consistency loss term in Eq. 9, the 2D representation in the first line of Eq. 6 was adopted. In the first stage of training, the smoothness loss of optical flow was applied across the entire image, i.e. Lfs = Ls(Ft→s, 1, 2). In the third stage of training, the smoothness loss of optical flow was only applied on the moving region, i.e. Lfs = Ls(Ft→s, 1−Mt, 2)
Estimating the biomass of Carex cinerascens (Cyperaceae) in floodplain wetlands in Poyang Lake, China

Abstract The estimation of wetland plant biomass is key to understanding the dynamic changes of the structure and functions of wetland ecosystems. Relatively few studies on the spatiotemporal dynamics of wetland plant biomass have been conducted because of the difficulties in obtaining detailed and accurate data. Carex cinerascens meadows are important patches in Poyang Lake in eastern China and provide significant food resources and habitats for wintering waterbirds, particularly geese. We proposed a method to estimate the biomass of C. cinerascens in a subsection of Poyang Lake, i.e. Baisha Lake, employing the digital elevation model and water level gradient of the lake combined with the logistic regression model based on data from field measurements in different elevations. We obtained four C. cinerascens biomass estimation models based on four elevations divided. The maximum biomass decreased with decreasing elevation. Meanwhile, the maximum growth rate initially increased and subsequently decreased. The biomass of C. cinerascens per unit area ranged from 0.10 to 0.58 kg/m2 in the autumn and winter. Significant differences in the growth process of C. cinerascens were observed in different water level gradients. The total biomass of C. cinerascens in Baisha Lake changed following an S-shaped curve and reached 221, 503, and 615 t in the middle of October, November, and December, respectively. The research results can be used to forecast the biomass of C. cinerascens under different hydrological conditions in Poyang Lake, and to provide wetland plant biomass estimation methods for other similar regions.
An investigation into stratosphere-troposphere exchange using air-particle trajectories

Tropical stratosphere-troposphere exchange is examined by the use of water vapour data and trajectory calculations. Water vapour data from the Microwave Limb Sounder (MLS) instrument and two-dimensional trajectories calculated from the assimilated data of the United Kingdom Meteorological Office (UKMO) are used to examine the evolution of water vapour upon iseiltropes near the 68 hPa surface. Three-dimensional trajectories calculated from the assimilated data of the European Centre for Medium-Range Forecasts (ECMWF) are used to examine the flow of air across the tropopause. Combination of the MLS and UKIVIO data allows the construction of purelyisentropic evolutions of water vapour. On tirnescales less than those characteristic of diffusion and of methane oxidation, comparisons of these evolutions to the observed cases can be used to show where vertical motions must cross isentropic surfaces. As such, a comparison of monthly-averaged, water-vapour maps on isentropic surfaces near 68 hPa to monthly-averaged maps of the same data after ten-day iserltrol)icadvections is presented for most of the operation time of the 183 GHz antenna of the MLS instrument November 1992 to March 1993. The comparison shows that the two evolutions rarely match each other and thins that vertical airflows must be present over most of the tropical region, throughout the year, near 68 hPa. The use of three-dimensional trajectories allows for a more-direct and more-detailed analysis of tropical, cross-tropopause motion. Though the lesser reliability of vertical wind-data does mean that only those three-dimensional-trajectory results that were in basic agreement with the results of the two-dimensional case described above could be considered useful, such an agreement was generally found during this study. Three-dimensional trajectories are presented to show that though crosstrop opause motion does occur throughout the tropical region a persistent longitudinal-preference in the motion existed for all times investigated the winters of 1980, 1981 and 1993 and all seasons of 1992. Crossing frequencies are shown to be much higher over the mid-Pacific throughout the year and much lower over the Indonesian and Asian monsoons, both extrema being visible at the ECMWF model-levels at 110 and 90 hiPa. The peak crossing was stronger during the 1993 winter than in any other winter and stronger in autumn than in any other season of 1992. Furthermore, whenever the peak crossing showed an increase in magnitude it was accompanied by an increase in the concentration of particle crossings into the mid-Pacific. Taken together, the results of the twoand threedimensional experiments also suggest that longitudinal variations in the 68 hPa, MLS water-vapour-concentrations occur not through differential uplift but by variations in the height of the tropopa.use.
LVIS: A Dataset for Large Vocabulary Instance Segmentation

Progress on object detection is enabled by datasets that focus the research community’s attention on open challenges. This process led us from simple images to complex scenes and from bounding boxes to segmentation masks. In this work, we introduce LVIS (pronounced ‘el-vis’): a new dataset for Large Vocabulary Instance Segmentation. We plan to collect 2.2 million high-quality instance segmentation masks for over 1000 entry-level object categories in 164k images. Due to the Zipfian distribution of categories in natural images, LVIS naturally has a long tail of categories with few training samples. Given that state-of-the-art deep learning methods for object detection perform poorly in the low-sample regime, we believe that our dataset poses an important and exciting new scientific challenge. LVIS is available at http://www.lvisdataset. org.
Dynamic Sampling Versions of Popular SPC Charts for Big Data Analysis

The statistical process control (SPC) chart is an effective tool for the analysis, interpretation, and visualization of data from sequential processes. Commonly used SPC charts such as the Shewhart, CUSUM and EWMA charts are widely implemented in detecting distributional shifts in various processes. With recent scientific and technological advancements, massive amounts of data continue to be generated by production, medical, agricultural and many other industrial processes. Conventional SPC charts have significant drawbacks in monitoring such processes, specifically when the velocity of the data flow is greater than the run time of the monitoring procedure. In the literature, dynamic sampling control charts [15] are becoming popular due to their ability to adaptively control the next sampling time of the monitoring process. In this thesis, we incorporate similar ideas to conventional SPC charts for the real-time monitoring of big data processes. Traditional SPC charts are designed to give a warning signal at a particular time point if a process reading plots beyond its control limit(s). This approach does not provide ample information of the likelihood of a potential shift in the process. We implement existing methods of designing control charts with p-values, which gives information about the performance of the current observations and potentially, of observations in near future. The control chart gives a signal for a mean shift if the p-value is less than some pre-specified significance level. We utilize the computed p-values of the charting statistic in designing variable sampling schemes, specifically the dynamic sampling schemes which are an increasing function of the p-value. The vi resulting control charts have variable sampling intervals, and hence skips several observations. Thus, their computing times are much faster than traditional charts. This thesis provides guidance on how to incorporate dynamic sampling schemes for monitoring big data streams in other types of SPC charts. We perform extensive simulation studies to compare the performance of the dynamic sampling control charts with conventional control charts. Our results show that the dynamic sampling versions of three commonly used SPC charts can monitor big data streams efficiently.
Developing parallel real-coded genetic algorithms for decision-making systems of socio-ecological and economic planning

This article presents a new approach to designing decision-making systems for socio-economic and ecological planning using parallel real-coded genetic algorithms (RCGAs), aggregated with simulation models by objective functions. A feature of this approach is the use of special agent-processes, which are autonomous genetic algorithms (GAs) acting synchronously in parallel streams and exchanging periodically by the best potential decisions. This allows us to overcome the premature convergence problem in local extremums. In addition, it was shown that the combined use of diﬀ erent crossover and mutation operators signiﬁ cantly improves the time eﬃ ciency of RCGAs, as well as the quality of the decisions obtained (proximity to optimum), providing a more diverse population of potential decisions (individuals). In this paper, several suggested crossover and mutation
Can Computer-Based Testing Achieve Quality and Efficiency in Assessment?

This paper reports findings of a two year study concerning the development and implementation of a general-purpose computer-based assessment (CBA) system at a UK University. Data gathering took place over a period of nineteen months, involving a number of formative and summative assessments. Approximately 1,000 students, drawn from undergraduate courses, were involved in the exercise. The techniques used in gathering data included questionnaires, observation, interviews and an analysis of student scores in both conventional examinations and computer-based assessments. Comparisons with conventional assessment methods suggest that the use of CBA techniques may improve the overall performance of students. However it is clear that the technique must not be seen as a "quick fix" for problems such as rising student numbers. If one accepts that current systems test only a relatively narrow range of skills, then the hasty implementation of CBA systems will result in a distorted and inaccurate view of student performance. In turn, this may serve to reduce the overall quality of courses and - ultimately - detract from the student learning experience. On the other hand, if one adopts a considered and methodical approach to computer-based assessment, positive benefits might include increased efficiency and quality, leading to improved student learning.
Passive Microwave Melt Onset Retrieval Based on a Variable Threshold: Assessment in the Canadian Arctic Archipelago

The Canadian Arctic Archipelago (CAA) presents unique challenges to the determination of melt onset (MO) using remote sensing data. High spatial resolution data is required to discern melt onset among the islands and narrow waterways of the region. Current passive microwave retrievals use daily averaged 19 GHz and 37 GHz data from the multi-channel microwave radiometer (SMMR) and/or the special sensor microwave/imager (SSM/I). The development of a new passive microwave melt onset method capable of using higher resolution data is desirable. The new passive microwave melt onset method described here, named the Dynamic Threshold Variability Method (DTVM), uses higher resolution data from the 37 GHz vertically-polarized channel from the advanced microwave scanning radiometers (AMSR-E and AMSR-2). The DTVM MO detection methodology differs from previously presented passive microwave Arctic MO methods in that it does not use a fixed threshold of a brightness temperature parameter. Instead, the DTVM determines MO dates based on the distribution of dates corresponding to the exceedance of a range of brightness temperature variability thresholds. The method also uses swath data instead of daily averaged brightness temperatures, which is found to lead to improved melt detection. Two current passive microwave MO methods are compared and evaluated for applicability in the CAA alongside the DTVM. The DTVM provides MO dates at a higher spatial resolution than earlier methods in addition to higher correlation with MO dates from surface air temperature (SAT) reanalyses. It is found that, for some years, MO dates in the CAA exhibit a latitudinal dependence, while in other years the MO dates in the CAA are relatively uniform across the domain.
FLOATING-POINT-BASED HARDWARE ACCELATOR OF A BEAM PHASE-MAGNITUDE DETECTOR AND FILTER FOR A BEAM PHASE CONTROL SYSTEM IN A HEAVY-ION SYNCHROTRON APPLICATION ∗

A hardware implementation of an adaptive phase and magnitude detector and filter of a beam-phase control system in a heavy ion synchrotron application is presented in this paper. The main components of the hardware are adaptive LMS filters and phase and magnitude detectors. The phase detectors are implemented by using a CORDIC algorithm based on 32-bit binary floating-point arithmetic data formats. The floating-point-based hardware is designed to improve the precision of the past hardware implementation that were based on fixed-point arithmetics. The hardware of the detector and the adaptive LMS filter have been implemented on a programmable logic device (FPGA) for hardware acceleration purpose. The ideal Matlab/Simulink model of the hardware and the VHDL model of the adaptive LMS filter and the phase and magnitude detector are compared. The comparison result shows that the output signal of the floating-point based adaptive FIR filter as well as the phase and magnitude detector agree with the expected output signal of the ideal Matlab/Simulink model.