Miracle-dz/UniFAR-FTUs huggingface dataset:
A Culturally Sensitive and Theory-Based Intervention on Prevention and Management of Diabetes: A Cluster Randomized Control Trial

Type 2 diabetes is an emerging concern in Kenya. This clustered-randomized trial of peri-urban communities included a theory-based and culturally sensitive intervention to improve diabetes knowledge, health beliefs, dietary intake, physical activity, and weight status among Kenyan adults. Those in the intervention group (IG) received a culturally sensitive diabetes education intervention which applied the Health Belief Model in changing knowledge, health beliefs and behavior. Participants attended daily education sessions for 5 days, each lasting 3 h and received mobile phone messages for an additional 4 weeks. The control group (CG) received standard education on COVID-19. Data was collected at baseline, post-intervention (1 week), and follow-up assessment (5 weeks). Linear mixed effect analysis was performed to assess within and across group differences. Compared to the control, IG significantly increased diabetes knowledge (p < 0.001), health beliefs including perceived susceptibility (p = 0.05), perceived benefits (p = 0.04) and self-efficacy (p = 0.02). IG decreased consumption of oils (p = 0.03), refined grains (p = 0.01), and increased intake of fruits (p = 0.01). Perceived barriers, physical activity, and weight status were not significantly different between both groups. The findings demonstrate the potential of diabetes education in improving diabetes knowledge, health beliefs, and in changing dietary intake of among adults in Kenya.
Rotation of principal components

Recent research has pointed to a number of inherent disadvantages of unrotated principal components and empirical orthogonal functions when these techniques are used to depict individual modes of variation of data matrices in exploratory analyses. The various pitfalls are outlined and illustrated with an alternative method introduced to minimize these problems via available linear transformations known as simple structure rotations. The rationale and theory behind simple structure rotation and Procrustes target rotation is examined in the context of meteorological/climatological applications. This includes a discussion of the six unique ways to decompose a rotated data set in order to maximize the physical interpretability of the rotated results. The various analytic simple structure rotations available are compared by a Monte Carlo simulation, which is a modification of a similar technique developed by Tucker (1983), revealing that the DAPPFR and Promax k = 2 rotations are the most accurate in recovering the input structure of the modes of variation over a wide range of conditions. Additionally, these results allow the investigator the opportunity to check the accuracy of the unrotated or rotated solution for specific types of data. This is important because, in the past, the decision of whether or not to apply a specific rotation has been a ‘blind decision’. In response to this, a methodology is presented herein by which the researcher can assess the degree of simple structure embedded within any meteorological data set and then apply known information about the data to the Monte Carlo results to optimize the likelihood of achieving physically meaningful results from a principal component analysis.
Proximal and Remote Sensing Data Integration to Assess Spatial Soil Heterogeneity in Wild Blueberry Fields

Wild blueberries (Vaccinium angustifolium Ait.) are often cultivated uniformly despite significant within-field variations in topography and crop density. This study was conducted to relate apparent soil electrical conductivity (ECa), topographic attributes, and multi-spectral satellite imagery to fruit yield and soil attributes and evaluate the potential of site-specific management (SSM) of nutrients. Elevation and ECa at multiple depths were collected from two experimental fields (referred as FieldUnd, FieldFlat) in Normandin, Quebec, Canada. Soil samples were collected at two depths (0–0.05 m and 0.05–0.15 m) and analyzed for a range of soil properties. Statistical analyses of fruit yield, soil, and sensor data were used to characterize within-field variability. Fruit yield showed large variability in both fields (CVUnd = 54.4%, CVFlat = 56.5%), but no spatial dependence. However, several soil attributes showed considerable variability and moderate to strong spatial dependence. Elevation and the shallowest depths of both the Veris (0.3 m) and DUALEM (0.54 m) ECa sensors showed moderate to strong spatial dependence and correlated significantly to most soil properties in both study sites, indicating the feasibility of SSM. In place of management zone delineation, a quadrant analysis of the shallowest ECa depth vs. elevation provided four sensor combinations (scenarios) for theoretical field conditions. ANOVA and Tukey–Kramer’s post hoc test showed that the greatest differentiation of soil properties in both fields occurred between the combinations of high ECa/low elevation versus low ECa/high elevation. Vegetation indices (VIs) obtained from satellite data showed promise as a biomass indicator, and bare spots classified with satellite imagery in FieldUnd revealed significantly distinct soil properties. Combining proximal and multispectral data predicted within-field variations of yield-determining soil properties and offered three theoretical scenarios (high ECa/low elevation; low ECa/high elevation; bare spots) on which to base SSM. Future studies should investigate crop response to fertilization between the identified scenarios.
On blocking in loss networks

We consider a ‘reduced state space' approach to the analysis of blocking in stochastic loss networks. We show how this approach provides insight into the approximations currently used in large networks and enables improved approximations to be deduced. We further give some ‘heavy traffic' asymptotic results for the limiting scheme of Kelly (1986).
High Pole Number Epoxy-Casted Rotor Reluctance Synchronous Wind Generator

In this paper we consider the design and performance of a reluctance synchronous machine for a 5 MW, medium-speed geared wind generator drive-train. Since achieving an acceptable power factor for high pole number reluctance machines is challenging, a modular epoxy-casted rotor is proposed. The performance of such a reluctance rotor synchronous generator was evaluated by means of finite element modeling and multi-objective design optimization. Through the design optimization method, the torque density versus power factor Pareto front performance of the generator was determined. This provided insightful information on this type of rotor generator. At a reasonably good torque density of 24 kNm/m3 and efficiency of 98.8%, a power factor of 0.72 was obtained for the selected generator design with its 16-pole, epoxy-casted reluctance rotor.
Mechanically driven light-generator with high durability

Mechanically activated luminescence from solids (mechanoluminescence) is a classical optical phenomenon induced in a substance when stressed or cleaved. However, no practical application has been realized due to its low luminescent intensity and lack of reproducibility. We demonstrate highly bright and durable mechanoluminescent flexible composite films with a brightness of ∼120 cd/m2 and durability over ∼100 000 repeated mechanical stresses by using a combination of copper-doped zinc sulfide (ZnS:Cu) particles and polydimethylsiloxane. Furthermore, the possibility of mechanoluminescent color-tuning by changing the repetitive stress rate on the composite films is also suggested. These findings can open a window for developing smart systems and opto-mechanical devices.
Bivariate Conditional Sampling of Moisture Flux over a Tropical Ocean

Abstract New applications of conditional sampling using the bivariate joint frequency distribution (JFD) and conditional mean distribution (CMD) are introduced to analyze time series of water vapor flux obtained from aircraft gust-probe vertical velocity and water vapor data collected during free convective conditions (zi/L≈−46) in the Atlantic trade winds. The JFD can provide estimates of fractional time as well as mean and variance estimates for the four ways vertical velocity/moisture fluctuations can combine (up-moist, up-dry, down-moist, down-dry). These combinations were interpreted using a subcloud layer model consisting of upward and downward moving convective cells and a mixing zone between them. The data suggest detrainment from the up-moving cell becomes the predominant mixing process above 0.08zi. The fractional time and mean values were used to parameterize the moisture flux. Three parameterization methods are introduced; two estimated the moisture flux to within 10% while a third, simpler ve.
A two‐grid method for expanded mixed finite‐element solution of semilinear reaction–diffusion equations

We present a scheme for solving two‐dimensional semilinear reaction–diffusion equations using an expanded mixed finite element method. To linearize the mixed‐method equations, we use a two‐grid algorithm based on the Newton iteration method. The solution of a non‐linear system on the fine space is reduced to the solution of two small (one linear and one non‐linear) systems on the coarse space and a linear system on the fine space. It is shown that the coarse grid can be much coarser than the fine grid and achieve asymptotically optimal approximation as long as the mesh sizes satisfy H=O(h1/3). As a result, solving such a large class of non‐linear equation will not be much more difficult than solving one single linearized equation. Copyright © 2003 John Wiley & Sons, Ltd.
LiNbO3 Film Bulk Acoustic Resonator for n79 band

We have designed and fabricated Y+36°-cut LiNbO3 Film Bulk Acoustic Resonators (FBAR) compatible with the n79 band. Leveraging longitudinal waves and an energy trapping condition, a single-mode resonance is obtained at 4.7 GHz, with an effective electromechanical coupling coefficient (kt2) of 25 % and quality factor at antiresonance (Qa) of 574. This leads to Qxf and Q× kt2 products of 2.7×1012 Hz and 139, respectively. A Temperature Coefficient of Frequency (TCF) of −75 and −70 ppm/°C respectively at resonance and antiresonance are obtained. These figure-of-merits are the highest reported up to date for LiNbO3 FBARs, highlighting the potentialities of LiNbO3 single crystal film as an alternative to AIN-based BAW devices for next generation of RF filters. To demonstrate this, a tentative filter design based on the measured resonator characteristics is proposed.
Three-dimensional vascular reconstruction and Doppler flow measurement using PMUTs

Piezoelectric Micromachined Ultrasonic Transducer (PMUT) has been studied a lot in the past decades since the merit of easily integrating with IC to develop 2-D array for 3-D imaging applications. However, there are tremendous work and high costs in both time and investment to establish the final goal. In this paper, we propose a low cost approach to achieve 3-D imaging using two 1-D arrays by introducing binocular stereo vision method. The imaging system with two PMUTs is designed to conduct 3-D reconstruction of the vessel in vitro, and the flow velocity can be measured much more accurately comparing to traditional 2-D method. To decrease the requirement of imaging system, especially the number of independence T/R channels, B-mode imaging of the vessel is performed by analogy with Synthetic Aperture Focusing Technique (SAFT) technique. Two images in different directions are collected individually, and then combined and compensated into 3-D imaging. After that, the blood flow velocity is measured using pulsed Doppler. With the combination of 3-D imaging of the vessel and Doppler measurement, the position and morphology of vessel could be obtained, and then the flow velocity can be calculated accurately.
Investigations on Transient and Steady-State Performance of a Micro Heat Pipe

A numerical study is presented of the vapor and liquid e ow in a micro heat pipe with triangular channels, utilizing water as the working medium. The governing equations are derived taking into account the variation in the e ow cross-sectional areas of the vapor and liquid phases and incorporating the phase change during the process. The velocity, pressure, and temperature distributions in the vapor and liquid, in the transient and steady states, are obtained from the analysis. The effective thermal conductivity of the micro heat pipe is calculated, and its dependence on the heat input and the heat transfer coefe cient at the condenser section is investigated. The results of the analysis are compared with those available in literature and discussed in the light of the assumptions made and the extensions incorporated in the present model. Nomenclature Ac = area of cross section of the heat-pipe channel, m 2 Cl = specie c heat of the liquid, J/kg K Cv = specie c heat at constant volume of the vapor, J/kg K DH = hydraulic mean diameter of the channel, m d = one side of the triangular channel, m El = total energy of the liquid per unit volume, q l(ClT + 1 u 2 ), J/m 3 Ev = total energy of the vapor per unit volume, q v(CvT + 1 u 2), J/m 3 f = friction coefe cient h fg = latent heat of vaporization, J/kg h0 = heat transfer coefe cient at the condenser, W/m 2 K k
Magnetoelectric Nanoparticles: Evaluating Stimulation Feasibility of the Possible Next Generation Approach for Deep Brain Stimulation

The purpose of this study is to quantify the distributions of the electric field induced by CoFe2O4 core - BaTiO3 shell magneto-electric nanoparticles (MENPs) when localized in deep brain structures. These fields can be used for deep brain stimulation (DBS), and their effect is compared to the fields induced by conventional DBS electrodes in monopolar and bipolar configuration. A computational approach based on finite element method was applied, along with the use of a highly detailed anatomical model of the brain structures. Different MENPs configurations were investigated and compared to conventional DBS electrode configuration. The activation of nervous fibers was quantified by calculating the Activation Function (AF) defined as the second derivative of the electric potential along the fiber. Electric field amplitudes obtained by MENPs were much lower than the ones obtained by the monopolar and bipolar electrode configurations. The AF values showed that MENPs were able to obtain very localized activation patterns along the fibers. In addition to the minimal invasiveness and proven biocompatibility of the MENPs, the results show that the proposed approach represents an important step towards a selective and minimally invasive strategy for DBS. All these findings are essential in identifying the unique characteristics that MENPs could provide for nervous system stimulation, and how the use of MENPs could improve the development of a new generation of DBS techniques.
On the amplification of small disturbances in a channel flow with a normal magnetic field

Optimal perturbations are investigated in a magnetohydrodynamic flow bounded by perfectly insulating or conducting walls. The parallel channel flow submitted to uniform, normal magnetic field is taken as an example. The stability equations (linearized Navier–Stokes and Maxwell equations) are solved simultaneously, because of the natural existence of a coupling between them. Exponential instability is studied first to set ideas and to fix some reference magnetic Prandtl and magnetic Reynolds numbers. Then, optimal perturbations are searched for by employing the approach first proposed by Butler and Farrell [Phys. Fluids A 4, 1637 (1992)]. The shape of the optimally perturbed velocity is poorly affected by the magnetic field; however, the magnetic field is found to stabilize both exponential instability and algebraically growing perturbations. The critical Reynolds numbers in the presence of magnetic fields can be very large and it is thus possible to find very significant transient growth in subcritical co.
The bell laboratories H I survey

We present a galactic survey which to date consists of 73,000 positions covering −5° < l < 122°, −1° < b < 1° , observed in the J=1 → 0 line of 13CO to an rms noise level of 0.15 K in 0.68 km s−1 channels, using the 7 m antenna at Crawford Hill. It is shown that the internal velocity dispersions of molecular clouds tend to vary inversely with galactocentric radius.
Experimental Study on the Heat Transfer Characteristics of an Evaporating Falling Film on a Horizontal Plain Tube

In this paper, an experimental investigation on the heat transfer of saturated water falling film on a single horizontal plain tube is presented. The water film falling on the outside of the tube has been heated by the condensing steam flowing in the tube, and the heat transfer coefficient between the water film and the steam has been measured. Experiments were performed at saturation temperatures of liquid film and steam as 58°C and 61°C, and 61°C and 65°C, a tube pitch of 57.16 mm, heat fluxes from 10 to 50 kW m-2, and film flow rate per unit of length of the tube up to 0.12 kg m−1 s−1. Brass plain tubes with external diameters of 25.4 mm and lengths of 950 mm were used in the experiments. The experimental results show that the heat transfer coefficient increases with the increasing film flow rate and heat flux, and the quality of vapor has an obvious influence on the heat transfer performance of falling film evaporation. The coupling of condensation and evaporation heat transfer inside and outside the tube is investigated qualitatively in this paper.
Emotion Recognition from EEG Signal Using CA-GCN

Electroencephalography(EEG)-based emotion recognition has become an important task in the field of brain computer interface(BCI). Recently, deep learning methods have achieved excellent results in the field of EEG emotion recognition. However, these methods either ignore the relations between channels or ignore the contributions of different channels, which makes it difficult to improve the recognition performance. In this paper, an end-to-end EEG emotion recognition method that graph convolutional neural network with channel-wise attention(CA-GCN) is proposed. First, we utilize a GCN layer to extract EEG signals spatial information for expressing intrinsic relations between different EEG channels. Furthermore, a channel-wise attention pooling layer in CA-GCN was adopted to extract the contribution of different EEG channels. Sufficient experiments have been carried out on the DEAP database. Experimental results demonstrate that the proposed method outperforms the previous methods, and the recognition accuracy of the proposed method achieve 93.69% and 94.59% in valence and arousal, respectively.
Assessing Rules in Memory Controllers with Hardware Simulator Executing Real Programs

Electronic memories are subject to failure due to magnetic fields and radiation, causing temporary faults that can be mitigated by error correction codes. Evaluating the efficacy of these mechanisms in hardware can make the design more expensive, take a long prototyping time, and even lose time to market. Hardware simulators or emulators are often generic, requiring specific and specialized development to evaluate memory controllers. This work proposes Absimth to assess the computational system behavior in the presence of memory errors. Absimth is a hardware simulator focusing on memory controller data flow, allowing the creation and configuration of custom modules. The simulator aims to optimize the design of next-generation memory controller architectures, meeting fault tolerance requirements with fast validation before the hardware implementation phases.
Conically scanning lidar error in complex terrain

Conically scanning lidars assume the flow to be homogeneous in order to deduce the horizontal wind speed. However, in mountainous or complex terrain this assumption is not valid implying a risk that the lidar will derive an erroneous wind speed. The magnitude of this error is measured by collocating a meteorological mast and a lidar at two Greek sites, one hilly and one mountainous. The maximum error for the sites investigated is of the order of 10 %. In order to predict the error for various wind directions the flows at both sites are simulated with the linearized flow model, WAsP Engineering 2.0. The measurement data are compared with the model predictions with good results for the hilly site, but with less success at the mountainous site. This is a deficiency of the flow model, but the methods presented in this paper can be used with any flow model.
Analytical Comparison of 3-Level 2-Phase and Double-Step-Down Topologies for Integrated High-Ratio DC-DC Converters in BCD and GaN Process

This paper provides a comprehensive analysis and comparison between 3-level and double-step-down (DSD) integrated power converters, which are two of the most popular topologies for 48V-to-1V point-of-load conversion. Because DSD converters have two inductors, the 3-level topology in this study is also constructed with 2-phase interleaved operation (3L2P) to make the comparison fair. Same chip-area budget, loading conditions and ripples are also ensured, such that comparisons are made under similar bill-of-materials and power density to provide engineers a more practical view of the characteristics of both topologies. Theoretical analysis is provided with similarity in switching behaviors discovered. Transistor-level simulations are conducted in a 180-nm BCD and a commercially available enhancement-mode GaN processes, assuming all power FETs are integrated on-chip. The simulation results agree with our analysis. In conclusion, DSD converters can achieve an overall higher efficiency than 3-level converters at near-same conditions with same or smaller chip-area budget due to the much lower conduction loss. In addition, both topologies, especially the DSD, achieved significantly higher (up to 12%) efficiency in a 200-V GaN process compared to a 55-V BCD process despite being overrated (due to limited available options), because of the much lower switching loss. This makes GaN process worth considering for integrated high-ratio DC-DC converter designs even though the current fabrication cost will be higher.
JSEVAsync: An Asynchronous Event-based Framework to Energy Saving on IoT Devices

Typically the Internet of Things devices are constrained in terms of processing, memory, and energy consumption. Energy consumption is a critical aspect of these devices, being heavily impacted by how programs are developed, and it becomes more evident in interpreted languages that naturally demand more resources. Commonly embedded software development uses Time-triggered (TT) and Event-triggered (ET) architectures to design embedded projects. However, the TT strategy can consume more energy due to the polling method; in contrast, the ET approach can be energy-efficient but cannot deal with multiple events. This paper introduces JSEVAsync, a framework to help developers to design applications using JavaScript language for IoT devices that combine the best parts of TT and ET architectures. This approach uses JavaScript's non-blocking concept as a development interface to structure the algorithms into asynchronous events. To validate it, we compare C- and JavaScript-based applications and analyze the results from the energy consumption perspective. We found that writing code through JSEVAsync can be up to 21% more energy efficient than the traditional method. Moreover, JavaScript can improve design-time aspects such as readability, maintainability, and code reuse.