Miracle-dz/UniFAR-FTUs huggingface dataset:
An 1800 V triple implanted vertical 6H-SiC MOSFET

6H silicon carbide vertical power MOSFETs with a blocking voltage of 1800 V have been fabricated. Applying a novel processing scheme, n/sup +/ source regions, p-base regions and p-wells have been fabricated by three different ion implantation steps. Our SiC triple ion implanted MOSFETs have a lateral channel and a planar polysilicon gate electrode. The 1800 V blocking voltage of the devices is due to the avalanche breakdown of the reverse diode. The reverse current density is well below 200 /spl mu/A/cm/sup 2/ for drain source voltages up to 90% of the breakdown voltage. The MOSFETs are normally off showing a threshold voltage of 2.7 V. The active area of 0.48 mm/sup 2/ delivers a forward drain current of 0.3 A at Y/sub GS/=10 V and V/sub DS/=8 V. The specific on resistance was determined to 82 m/spl Omega/dcm/sup 2/ at 50 mV drain source voltage and at V/sub GS/=10 V which corresponds to an uppermost acceptable oxide field strength of about 2.7 MV/cm. This specific on resistance is an order of magnitude lower than silicon DMOSFET's of the same blocking capability could offer.
Women vs Men: Who performs better on Energy Literacy?

Energy literacy is seen as one of the most powerful tools, available to ordinary people, to contribute to a more sustainable world. Since women tend to be considered the main caregivers, due to their maternal instinct, being generally more attentive, more altruistic, and more concerned with the future of their children, are women more involved in the transition to a more sustainable future? To answer this question, we seek to assess the literacy levels of Portuguese university members and explore the differences between men and women. Using the Heteroskedastic Ordered Probit, we found that women tend to have lower levels of knowledge about energy, but a more positive and sustainable attitude and behavior.
MAGNET (RE)TRAINING

In 2008, the LHC magnets circuits have been commissioned. In some cases, the magnets experienced quenches, showing some detraining with respect to the previous performance level reached during individual test. In this paper we summarize the training quenches that took place during hardware commissioning for all LHC superconducting magnets. This allows giving estimates for the next hardware commissioning campaign, and for the needed training to reach a given energy. Data show that 6.5 TeV is within reach with a limited amount of training, whereas today it is difficult to estimate the training needed to reach 7 TeV. The case of the dipoles, which dominate by far the training time due to their number and to the longer recovery time, is analysed using a MonteCarlo method that relies on the test data. The retraining shown by the Firm3 dipoles is partially explained by this method.
Design of Intergreen Times Based on Safety Reliability

This study proposes a stochastic approach for the design of intergreen times, that is, signal change and clearance intervals, at signalized intersections based on safety reliability. Unlike the conventional deterministic methods, the proposed method accounts for the uncertainty of input variables deriving intergreen times as well as driver decision randomness at the onset of yellow. The probability of risky behavior, including abrupt stop and red light running, was selected as the safety reliability measure for determining yellow time, and the probability of the occurrence of clearance failure was used as the measure for determining all-red time. A theoretical model of estimating safety reliability and deriving intergreen times was developed and was validated by the use of the Monte Carlo simulation technique. Comparisons with the current methods used in Japan, the United States, and Germany indicated that the proposed method captured the probabilistic nature of traffic and driving decision and thus provided a more rational design of intergreen times.
Fan Fault Diagnosis Based on Lightweight Multiscale Multiattention Feature Fusion Network

Although the deep learning diagnosis model has been widely used in the fault diagnosis of rotating machinery. However, these methods lack the interpretability of the diagnostic process. In other words, it is still a difficult problem to understand that the structural function and the diagnosis process in the model correspond to each other. Therefore, this article discusses how to add multiscale and multiattention mechanism to lightweight network. From different scales, different dimensions, combined with the fault signal characteristics of centrifugal fan, the attention structure of cross layer fusion is designed. How to integrate different functions continuously and effectively to achieve better diagnostic performance is answered. The proposed lightweight multiscale multiattention feature fusion network adaptively recalibrates feature weights, which effectively enhances the fault feature learning ability and antinoise ability. Experimental results show that this network is stronger than other advanced diagnostic models.
Use of Reverse Electrodialysis to Harvest Salinity Gradient Energy from Oilfield Produced Water

Two lab-scale electrodialysis (RED) stacks with different intermembrane spacing were used in this study. Each stack consists of two membrane pairs. Thick intermembrane spacing stack was made of four identical plexiglass sections, with outer dimensions 5 cm * 5 cm * 1.5 cm and an inner cross-section of 3 cm diameter each to construct two diluted solution compartments and two concentrated solution compartments. For the thin intermembrane spacing configuration, four rubber spacers with a thickness of 1 mm and an inner opening of 3 cm each were used instead of these sections. Two copper sheets were used as anode and cathode electrodes. Different solutions with NaCl concentrations of 15,000, 30,000 and 200,000 mg/l were used as a concentrated solution and different solutions with relatively low NaCl concentrations of 25, 1000 and 3600 mg/l were used as a diluted solution. A 30,000 mg/l NaCl solution was used as a diluted solution when the concentrated stream was with NaCl concentration of 200,000 mg/l. The electrode solution was of 15,000 mg/l (~0.25 M) NaCl and 8,000 mg/l (~0.05 M) CuSO4.5H2O. The results of this study confirmed the validity of using RED technology to harvest energy from salinity gradient using saline and freshwater available abundantly particularly in Iraq. An experiment on a synthetic hypersaline oil field co-produced water as a concentrated stream and seawater as a diluted stream showed that the system performance is reproducible and stable. A maximum power density of 0.029 W/m2 could be harvested.
Flow of Sub-Cooled Cryogens through a Joule-Thomson Device: Investigation of Metastability Conditions

Cryogenic fluid systems are fundamental to space flight architecture. Due to the unique properties of cryogenic fluids and the environments in which they operate for space flight, cryogenic fluid management systems must be developed to maintain these fluids at conditions in which they can be utilized. Liquid oxygen boils at 90 K, and liquid hydrogen boils at 20 K. Significant care must be taken to provide a thermal management system that prevents heat entering these fluids with consequential adverse effects on the performance of the cryogenic fluid systems. One critical component of a cryogenic thermal management system is a Joule-Thomson device. This one small component provides the driving force not only for the production of cryogenic fluids, but for the effective management of thermal loads in many cryogenic fluid systems including those used in space flight architectures.
Simulation of the surface crack detection using inductive heated thermography

During thermo-inductive inspection, an eddy current of high intensity is induced into the inspected material and the thermal response is detected using an infrared camera. Anomalies in the surface temperature during and after inductive heating correspond to inhomogeneities in the material. A finite element simulation of the surface crack detection process using active thermography with inductive heating has been developed. The simulation tool was tested and used for investigations on austenitic steel components with different longitudinal orientated cracks. The shape of the crack varies in the crack opening and the depth. The simulation model was based on the finite element programming software ANSYS. The suitability of the developed simulation of the inductive excited thermography for crack detection will be demonstrated by calculations and experiments. This paper focuses on longitudinal orientated cracks in austenitic steel, which are opened to the surface. The results show that depending on the shape of the crack the temperature distribution of the material under test made of austenitic steel is different. It will be shown how the crack size affects the temperature difference between the crack and the surrounding surface.
CAR-FOLLOWING UNDER NON-CONGESTED AND CONGESTED CONDITIONS

In traffic flow analysis several regimes are distinguished, such as congested and non-congested flow conditions. Indications exist that driving behavior differs by regime, and that it may change discontinuously between regimes. In contrast, most traffic flow models used today basically assume the same car-following behavior irrespective of the traffic flow regime. It is hypothesized that because of this deficiency, these models do not always perform satisfactorily. To clarify this issue, differences in car-following between congested and non-congested flow are analyzed with data from two sites on Dutch freeways. It is shown that, at the same speeds, passenger car drivers follow with smaller headways in non-congested flow than in congested flow. Car-following of truck drivers does not show differences between regimes. Microscopic distance gap - speed models are established for several road user classes, valid for each of the two flow regimes. To show the improvements resulting from these new microscopic relationships, the latter are implemented in a micro simulation model (FOSIM) with which macroscopic patterns in traffic flow are modeled. The macroscopic findings produced with the regime specific car-following rules show a considerable improvement in modeling performance.
Horizontally-split-drain MAGFET ñ a highly sensitive magnetic field sensor

We propose a novel magnetic field sensitive semiconductor device, viz., Horizontally-Split-Drain Magnetic-Field Sensitive Field-Effect Transistor (HSDMAGFET) which can be used to measure or detect steady or variable magnetic fields. Operating principle of the transistor is based on one of the galvanomagnetic phenomena and a Gradual Channel Detachment Effect (GCDE) and is very similar to that of Popovic and Baltesis SDMAGFET. The predicted absolute sensitivity of the new sensor can reach as high value as 1000 V/T. Furthermore, due to its original structure, the spatial resolution of the new MAGFET is very high which makes this device especially useful in reading magnetically encoded data or magnetic pattern recognition.
A long-term prediction of domestic water demand using preprocessing in artificial neural network

Both planning and the design of water supply systems require accurate and reliable prediction of water demand. In this study, artificial neural network (ANN) was used to predict the long-term water demand to determine the relationship between dependent and independent parameters. Using the stationary chain to solve the interpolating characteristic of ANNs, the study presents a reliable approach for long-term forecasting of water demand. The purpose of this study is to provide a convenient and reliable method for long-term forecasting of urban water demand while reducing the prediction uncertainty. In order to evaluate the accuracy of the prediction, multilayer perceptron (MLP) outputs were compared with results from the linear regression model. Findings indicate that MLP is an appropriate solution for monthly long-term water demand forecasting. Furthermore, it can reduce uncertainties and significantly increase the accuracy of the long-term forecasting.
The Collective Integration of Technology (CIT) Model: Helping Teachers Incorporate Technology Meaningfully in their Everyday Work

There is no consensus on how educational technology solutions should be integrated in practice. Although several related models exist, none of them covers how education digitalization should be implemented and managed in a collective manner at both organizational (school) and individual (teacher) levels, so that process improvements support teachers' daily work as well as school and education administration. In this study, one researcher organized the training program for 168 Namibian K-12 teachers to apply remote teaching during the COVID-19 pandemic. The researcher also discussed the program with trainers, and based on participatory observations, created the collective integration of technology (CIT) model through grounded theory. A second researcher collected related theories together, such as models for digitalization of processes;individuals', and organizations' IT innovation adaptation;change management, and organizational learning;among others, for literature review and model comparison. Both researchers evaluated the CIT model that was developed and found that it covers rather well several aspects of different existing models and theories, and, as such, can be considered as theoretically validated, although it still needs empirical validation. Based on the findings, improvements are proposed, and a new version is to be tested in practice.
Transient response of some borehole mandrel tools

The response of transient mandrel tools in realistic well‐logging environments is simulated by first solving the problem analytically in the frequency domain using an efficient high‐speed computer model. Gaussian pulses of reasonable bandwidths are assumed. The geometry modeled includes a borehole, invasion layers, and bed boundaries. Both TE and TM type sources are considered. The resulting receiver voltages, displayed in variable‐density log (VDL) format, yield visually interpretable information regarding signal amplitude and attenuation. The speed and generality of the analytical model makes this approach practical for analyzing tool response in a wide variety of logging geometries. Preliminary results generated by this model demonstrate that transient electromagnetic logging tools have the potential to yield useful information for characterizing the conductivity and dielectric constant of beds penetrated by a wellbore. In the future, the model could be helpful in validating signal processing and data .
RBF network feedforward compensation of load disturbance in idle speed control

Automotive engine idle speed control is a disturbance rejection problem. An engine at idle is typically well away from its most favorable region of operation and exhibits significant nonlinearities. Control of such a system is complicated by delays of both physical (time between induction and power strokes) and computational origin. In the model used, there are two control variables, and these differ in both their range of effectiveness and their temporal characteristics: spark advance is fast-acting but limited in its effect, while throttle has a large range but a slower effect which results both from the dynamics of filling the intake manifold and from the induction-power delay. The spark variable also has a maximum effective value, i.e., a value beyond which it has an effect opposite to that expected. This article describes a nonlinear adaptive feedforward controller for compensation of external load disturbances in the idle speed control of an automotive engine. The controller is based on a radial basis function (RBF) network approximation of certain input-output mappings describing the system. An underlying assumption used in the controller design is that the external engine load is known to the controller. In particular, that might be achieved by putting an appropriate torque sensor in the powertrain or using other available information.
Effect of LEED Ratings and Levels on Office Property Assessed and Market Values

This study examines the effect of Leadership in Energy and Environmental Design (LEED) ratings and certification levels on Assessed (AV) and Market Values (MV), while controlling for a property's characteristics and its location. The overall dataset was developed by combining information from CoStar Group, U.S. Green Building Council (USGBC), and local Assessors/Treasurer. The results indicate that ENERGY STAR designation increases AV and MV substantially. The effect of LEED rating/level on both of these values (AV and MV) can be differentiated based on the level of geographic aggregation. LEED-Existing Building (EB) designation at the Gold level has a strong positive effect on AV, while LEED-EB at the Silver level has a similar effect on both AV and MV. This effect is absent among all LEED-EBs, when controlling only for MSAs. LEED-New Construction at the Gold level has a strong positive effect on MV, while LEED-Core & Shell at the Gold and Silver levels almost doubles that effect on AV, when controlling .
Steady-state and transient performance evaluation of a DTC scheme in the low speed range

In this paper, a direct flux and torque control scheme for industrial application is analyzed in order to emphasis the drive performance at standstill and in the low speed range. The control strategy utilizes the torque and rotor flux commands to determine the reference value of the stator flux. In order to improve the low speed performance a closed loop estimator is employed to evaluate the rotor flux. The validity of the control scheme is verified by simulations and experimental tests of an induction motor drive system.
Traction on artificial turf: development of a soccer shoe outsole

Purpose: Official game play on high quality third-generation artificial soccer turf was approved by the FIFA already in 2004. However, it is still unknown how the ‘new’ surface affects traction requirements and thus potentially calls for specific footwear, especially with respect to the shoe outsole. This research project aimed to develop an artificial soccer turf outsole that provides very good traction performance to players. Methods: The whole project consisted of three phases that were carried out over three years: (I) status quo evaluation, (II) modified prototype testing, and (III) market comparison. In each phase an identical, comprehensive testing design, incorporating performance, perception and biomechanical testing procedures, was applied on FIFA 2-star artificial soccer turf. Four different shoe models were comparatively examined in each research phase and respective findings guided the selection of shoes for the following phase. Results: Soccer shoes that were traditionally designed for playing on natural grass were not (soft ground) or only limitedly (firm ground) suited for playing on artificial turf. Better traction performance on artificial soccer turf was achieved by usage of multiple and rather low studs being evenly distributed across the rearfoot and the forefoot areas. The final prototype shoe outperformed three commercially available artificial turf soccer shoes on the market at time of testing. Conclusion: This research provides an improved understanding of the mechanisms of artificial soccer shoe traction. Solid recommendations for the requirements of artificial soccer turf outsoles are stated, which generally confirm players’ intuitive choice of soccer footwear.
A set of stability criteria for delayed cellular neural networks

This work presents a set of criteria on the global asymptotic stability of delayed cellular neural networks (DCNN) by constructing suitable Lyapunov functionals, introducing ingeniously real parameters w/sub i/>0, /spl alpha//sup *//sub ij/, /spl beta//sup *//sub ij/, /spl eta//sup *//sub ij/, /spl zeta//sup *//sub ij/, /spl alpha//sub ij/, /spl beta//sub ij/, /spl eta//sub ij/, /spl zeta//sub ij//spl isin/R with /spl alpha//sup *//sub ij/+/spl beta//sup *//sub ij/=1, /spl alpha//sub ij/+/spl beta//sub ij/=1, /spl eta//sup *//sub ij/+/spl zeta//sup *//sub ij/=1, /spl eta//sub ij/+/spl zeta//sub ij/=1(i, j=1, 2, ., n) and combining with elementary inequality technique 2ab/spl les/a/sup 2/+b/sup 2/. These criteria are of theoretical and applicable important significance in signal processing, especially in speed detection of moving objects, processing of moving images and the design of networks since they possess infinitely adjustable real parameters. This result is also discussed from the point of view of its relationship to earlier results.
Insights into the mechanisms of susceptibility and tolerance against salinity stress in rice plant

ABSTRACT Rice (Oryza sativa L.) is an important food crop that is consumed by more than half of the world's population. Soil salinity is a serious problem that reduces rice yield because it is more sensitive to salt stress than other cereal crops. Salinity affects many aspects of the rice plant phases like it has a damaging effect on rice plant growth e.g. germination inhibition, difficulties in the crop establishment, development of the leaf area, decrease in the production of the dry matter, delay in the seed setting and even leading to the sterility. The susceptibility or resistance to high salinity in rice plants is an organized activity of multiple genes which also interact with other components of the different path­ways of stress signals transduction. The salt tolerance genes can be used to produce salinity tolerant rice varieties by using genetic engineering and marker-assisted selection. In this review, we have discussed the effects of salt stress on different growth stages and yield of the rice plant and updated on different stress-responsive genes and salinity tolerance mechanisms which will be helpful to improve the high-yielding rice varieties against the salinity stress. To develop salt-tolerant and high-yielding rice varieties, we have focused on the need to incorporate genomics, phenotyping, and metabolic profiling into breeding and transgenic approaches.
Finite-Time Supervisory Stabilization for a Class of Nonholonomic Mobile Robots under Input Disturbances

This paper provides a solution for the stabilization of a nonholonomic wheeled mobile robot which is affected by additive input disturbances. The solution is based on the supervisory control framework, finite-time stability and robust multi-output regulation. A supervisor and two controls are designed with the objective to stabilize the first output (in the input-to-output stability sense) while the second output has to be kept under a threshold. The results is then applied to the case of the unicycle mobile robot which has to reach a position (i.e. stabilization) avoiding eventual obstacle during the task (i.e. keeping the second output under a threshold). The effectiveness of the solution is proved mathematically, supported by simulation results and finally tested on a wheeled mobile robot in a real scenario.