Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of Dopant Activation in Silicon Employing Differential Hall Effect Metrology (DHEM)

Differential Hall Effect Metrology (DHEM) technique was used to characterize highly n-type doped Si epi layers deposited on p-type Si wafers. Total dopant concentration, doping depth profile and post deposition annealing condition were changed for various sample sets and influence of such changes on the resistivity, mobility and carrier concentration depth profiles were studied. It was determined that samples annealed at 900 °C had higher activation compared to those annealed at 700 °C. Gradation in doping depth profiles did not result in similar gradation in resistivity values. Carrier concentration at the near-surface region was found to be lower in all samples. It is shown that electrical properties of films forming ultra-shallow junctions can be studied in detail and correlated with process parameters using DHEM data obtained at sub-nm depth resolution.
Two‐dimensional projection uniformity for space‐filling designs

We investigate a space‐filling criterion based on L2 ‐type discrepancies, namely the uniform projection criterion, aiming at improving designs' two‐dimensional projection uniformity. Under a general reproducing kernel, we establish a formula for the uniform projection criterion function, which builds a connection between rows and columns of the design. For the commonly used discrepancies, we further use this formula to represent the two‐dimensional projection uniformity in terms of the Lp ‐distances of U‐type designs. These results generalize existing works and reveal new links between the two seemingly unrelated criteria of projection uniformity and the maximin Lp ‐distance for U‐type designs. We also apply the obtained results to study several families of space‐filling designs with appealing projection uniformity. Because of good projected space‐filling properties, these designs are well adapted for computer experiments, especially for the case where not all the input factors are active.
Corporate Derivatives and Risk Management: A Moderated Mediation Test

The present study contributes to existing literature by empirically testing the moderated mediating role of firm’s risk on the relationship between derivative usage and firm value by gathering sample data of Pakistani and Malaysian non-financial firms. By using Bootstrap technique of Hayes (2015), study finds that the use of derivative has both direct and indirect effect on firm value in Pakistan, contrary to Malaysia, as derivative usage significantly enhances firm value by reducing firm’s risk. Findings remain same for both foreign currency and interest rate derivative usage that firm’s risk significantly mediates the relationship between derivative usage and firm value in Pakistani non-financial corporations. Keywords: Derivative Usage, Firm Value, Firm's Risk, Moderated Mediation, Pakistan, Malaysia
Insertion Mutation of MSMEG_0392 Play an Important Role in Resistance of M. smegmatis to Mycobacteriophage SWU1

Purpose Phage is a new choice for the treatment of multi-drug-resistant bacteria, and phage resistance is also an issue of concern. SWU1 is a mycobacteriophage, and the mechanism of its resistance remain poorly understood. Methods The mutant strains which were stably resistant to SWU1 were screened by transposon mutation library. The stage of phage resistance was observed by transmission electron microscope (TEM). The insertion site of transposon was identified by thermal asymmetric interlaced PCR (TAIL-PCR). The possible relationship between insertion site and phage resistance was verified by gene knockout technique. The fatty acid composition of bacterial cell wall was analyzed by Gas Chromatography-Mass Spectrometer (GC-MS). Through the amplification and sequencing of target genes and gene complement techniques to find the mechanism of SWU1 resistance. Results The transposon mutant M12 which was stably resistant to mycobacteriophage SWU1 was successfully screened. It was confirmed that resistance occurred in the adsorption stage of bacteriophage. It was verified that the insertion site of the transposon was located in the MSMEG_3705 gene, but after knocking out the gene in the wild type M. smegmatis mc2 155, the resistance of the knockout strain to SWU1 was not observed. Through the amplification and sequencing of the target gene MSMEG_0392, it was found that there was an adenine insertion mutation at position 817. After complementing MSMEG_0392 in M12, it was found that M12 returned to sensitivity to SWU1. Conclusion We confirmed that the resistance of M12 to SWU1 was related to the functional inactivation of MSMEG_0392 and this phenomenon may be caused by the change of cell wall of M. smegmatis.
Vibration characteristics analysis of stiffened cylindri cal shell

Based upon a type of semi-analytical method, the linear equation sets of shell and stiffeners are established separately. The compatibility of displa c ements and stresses on the interface between the shell and the stiffeners is emp loyed to derive the equation of the integralted structure, and then the characte ris tic equation on natural frequencies and mode shapes. The main advant ages are the transverse shear deformation and rotary inertia are considered natu rally, further more, without any limit to the thickness of shell and the height of stiffener. The convergence studies of several numerical examples and results show that present method is reliable. The method in this paper can be easily dev eloped to solve the corresponding problems of stiffened composite laminated shel ls, stiffened piezolaminated shell.
Mini implants versus conventional diameter implants for 4-implant-supported mandibular overdentures. One year randomized prospective clinical and radiographical study

Purpose: This study aimed to evaluate clinical and radiographic outcomes of mini-implants versus conventional diameter implants for 4-implant-supported mandibular overdentures after one year. Materials and methods: 12 edentulous patients with insufficient retention of their conventional mandibular dentures and reduced mandibular ridge width were assigned into 2 groups; group 1 (conventional implants group, control); received four conventional diameter implants using flap surgical approach, group 2 (mini-implant group): received four mini-implants in the interforaminal area of the mandible using flapless surgical approach. For both groups, implants were loaded immediately with mandibular overdentures via O-ring attachments. Plaque index, Gingival Index, probing depth, implant stability and marginal bone loss was assessed at baseline, 6 months and 12 months after overdenture insertion. Results: The survival rates were 95.9% and 91.7% for conventional implant and min-implants groups without difference between groups. For both groups, Plaque index, gingival index and implant stability did not differ significantly between observation times. Probing depth and marginal bone loss significantly increased with passage of time. Conventional diameter group showed significantly higher plaque, gingival indices, probing depth, implant stability and marginal bone loss than mini-implant group after six and 12 months. Conclusion: Within the limitation of this randomized trial, mini-implants may be a suitable alternative to conventional diameter implant in patients with reduced buccolingual bone thickness as it was associated with reduced Plaque index, Gingival Index, probing depth and marginal bone loss after one year. However, conventional diameter implants provided more implant stability than mini-implants.
Comparing Resource Adequacy Metrics: Preprint

As the penetration of variable generation (wind and solar) increases around the world, there is an accompanying growing interest and importance in accurately assessing the contribution that these resources can make toward planning reserve. This contribution, also known as the capacity credit or capacity value of the resource, is best quantified by using a probabilistic measure of overall resource adequacy. In recognizing the variable nature of these renewable resources, there has been interest in exploring the use of reliability metrics other than loss of load expectation. In this paper, we undertake some comparisons using data from the Western Electricity Coordinating Council in the western United States.
Analysis of voltage-source-inverter-driven brushless dc motors with unbalanced Hall sensors

Brushless dc motors with Ha l l sensors are widely used in various industrial and electromechanical applications. These machines have often been considered in the literature, under one common assumption ideal placement of the sensors, which is often not the case, especially for low-precision motors. This thesis is composed o f three manuscripts which investigate the unbalance o f Ha l l sensors and propose methods to eliminate its adverse effects. The studies presented here show that misalignment of H a l l sensors leads to unbalanced operation of the inverter and motor phases, which in turn results in increased low-frequency harmonics in torque ripple, possible acoustic noise, and degradation of the overall drive performance. Thus, the first manuscript introduces the problem of the misaligned Ha l l sensors by using a detailed model o f a sample brushless dc motor and proposes a simple yet practical averaging technique to significantly decrease the effects of the misplaced sensors in steady state. The second manuscript extends the discussion to the dynamic performance of a low-precision brushless dc motor by introducing extrapolating filters which specifically target the transient operation. The third manuscript generalizes the concepts presented in the first two papers by taking into account both steady-state and transient performances and provides extensive hardware studies. The presented research considers a typical industrial brushless dc motor and includes measurements, detailed models and hardware experiments to validate the analysis. The proposed averaging approach is shown to achieve performance characteristics very close to those of a motor with perfectly balanced Ha l l sensors.
Personalized Driver Braking Behavior Modelling in the Car-following Scenario: An Importance Weight-based Transfer Learning Approach

Accurately recognizing braking intensity levels (BIL) of drivers is important for guaranteeing the safety and avoiding traffic accidents in intelligent transportation systems. In this paper, an instance-level transfer learning (TL) framework is proposed to recognize BIL for a new driver with insufficient driving data by combining Gaussian Mixture Model (GMM) and importance weighted least squares probabilistic classifier (IWLSPC). By considering the statistic distribution, GMM is applied to cluster the data of braking behaviors into three levels with different intensities. With the density ratio calculated by unconstrained least-square importance fitting (ULSIF), LSPC is modified as IWLSPC to transfer the knowledge from one driver to another and recognize BIL for a new driver with insufficient driving data. Comparative experiments with non-transfer methods indicate that the proposed framework obtains a higher accuracy in recognizing BIL in the car following scenario, especially when sufficient data are not available.
How to Get the Most Out of U-Net for Glacier Calving Front Segmentation

The melting of ice sheets and glaciers is one of the main contributors to global sea-level rise. Hence, continuous monitoring of glacier changes and in particular the mapping of positional changes of their calving front is of significant importance. This delineation process, in general, has been carried out manually, which is time-consuming and not feasible for the abundance of available data within the past decade. Automatic delineation of the glacier fronts in synthetic aperture radar (SAR) images can be performed using deep learning-based U-Net models. This article aims to study and survey the components of a U-Net model and optimize the model to get the most out of U-Net for glacier (calving front) segmentation. We trained the U-Net to segment the SAR images of Sjogren-Inlet and Dinsmoore–Bombardier–Edgworth glacier systems on the Antarctica Peninsula region taken by ERS-1/2, Envisat, RadarSAT-1, ALOS, TerraSAR-X, and TanDEM-X missions. The U-Net model was optimized in six aspects. The first two aspects, namely data preprocessing and data augmentation, enhanced the representation of information in the image. The remaining four aspects optimized the feature extraction of U-Net by finding the best-suited loss function, bottleneck, normalization technique, and dropouts for the glacier segmentation task. The optimized U-Net model achieves a dice coefficient score of 0.9378 with a 20% improvement over the baseline U-Net model, which achieved a score of 0.7377. This segmentation result is further postprocessed to delineate the calving front. The optimized U-Net model shows 23% improvement in the glacier front delineation compared to the baseline model.
Application of Fuzzy-PID compound control on loom electronic let-off and take-up

In order to meet the demands of high speed weaving and diversified varieties of fabric,the let-off motion must be controlled accurately since electronic let-off system of loom has faced some new requirements.The traditional PID controller can not meet the requirements because of its typical complicated,tandem driving,time changing and non-liner winding system.Targeting the shortcomings of the traditional PID controller in loom electronic let-off and take-up motion control,a Fuzzy-PID tension controller is proposed for effective settlement of the problems of dynamic change of the non-liner system.Simulation by Simulink of MatLab is carried out on the basis of SAURER400 loom.The simulation experimental results indicate that the parameters of Fuzzy-PID are better than those of routine PID.This control method has good application potential for electronic let-off system.
Target tracking with infrared imaging and millimetre-wave radar sensor

Two commonly used tracking fusion methods for Kalman filter-based multi-sensor data fusion which are weighed cross-covariance fusion and augmented measurement fusion are analysed in this paper. Based on tracking fusion of infrared sensor and millimetre wave Radar ,the fused states and measurements are compared with individual estimates. Results are presented using Monte Carlo simulation by two given virtual trajectories which show that: (1)the two fusion methods are functionally equivalent if the sensors used for data fusion have identical measurement matrix;(2)the obtained joint state-vector estimate is better than the individual sensor-based estimate. Also presented are the possible reason caused the bias between individual position estimate and true followed by the analysis of the computational advantages of each method. (8 pages)
Seasonal Temperature Extremes in the North Eurasian Regions Depending on ENSO Phase Transitions

Seasonal anomalies of surface air temperature were analyzed for the North Eurasian regions in mid-latitudes using long-term data from the end of the 19th century with an assessment of El Niño Southern Oscillation (ENSO) effects. In particular, temperature anomalies in the spring–summer months for the European (ER) and Asian (AR) Russian regions for different phase transitions of the ENSO phenomena were estimated using the Niño3, Niño3. 4 and Niño4 indices. The largest frequency of the extremely high-temperature and drought conditions in spring–summer months in ER was detected for years starting in the El Niño phase with the transition to the La Niña phase at the end of the year. Such conditions were realized in ER in summer 2010 (“Russian heatwave”). The corresponding largest frequency of high temperature in AR was obtained for conditions with the continuation of the El Niño phase during the whole year. Such conditions in AR were noted, in particular, in the summer of 2015, with an extremely high temperature and extremely low precipitation in the Lake Baikal basin.
Business intelligence for infrastructure and construction industry

In today‘s struggling economy with competition controlling and shrinking the landscape, it is important to make sound business decisions based on complete data. With the proper Business Intelligent implementation, businesses can make decisions and feel comfortable that they are provided with the proper tools and data needed to believe in their decisions. Business Intelligence is the processes, technologies, and tools that help us change data into information, information into knowledge and knowledge into plans that guide organization to succeed, Technologies for gathering, storing, analyzing and providing access to data to help enterprise users to make better business Decisions. The duty of the system is to ensure that correct decision is taken with the available data at the appropriate time according to the environment. The relationship between BI and an organization that uses it is that an organization collectively is a cognitive system: it senses the environment, makes a representation of it, acts on the basis of the representation and learns from the results of its actions, storing its experience as institutional memory. This study explores the opportunities of BI in Infrastructure & surance Industry. If a business competes in the infrastructure or construction industry, one must manage facilities, equipment, resources, large projects with numerous milestones, budgets and finances, schedules and operations. Enterprise is subject to specific service requirements and must comply with strict regulations and reporting requirements and with burdensome bidding processes. Business users are reliant on accurate, timely market research, effective, targeted sales and stakeholder and partner communication, and an efficient set of processes, training techniques and resource planning targets. The enterprise must also manage and understand new growth opportunities and the critical necessity for efficient supply chain and cost optimisation. To compete in this environment, the infrastructure or construction enterprise must establish and leverage a powerful combination of technology, business intelligence and results management and deliver quality and value for every project, every objective and every planning activity.
Suppression of near-surface scattered body to surface waves: Steerable and non-linear filtering approach

We present an approach based on local-slope estimation for the separation of scattered surface waves. The near-surface scattered body-to-surface waves, which have comparable amplitudes to reflections, can mask the seismic reflections. These difficulties, added to large amplitude direct and back-scattered surface (Rayleigh) waves, create a major reduction in signalto-noise ratio and degrade the final subsurface image quality. Removal of these waves can be difficult using conventional filtering methods, such as an f − k filter, without distorting the reflected signal. The filtering algorithm we present is based on predicting the spatially varying slope of the noise, using steerable filters, and separating the signal and noise components by applying a directional non-linear filter oriented toward the noise direction. The slope estimation step using steerable filters is very efficient. It requires only a linear combination of a set of basis filters at fixed orientation to synthesize an image filtered at an arbitrary orientation. We apply our filtering approach to simulated seismic data and demonstrate its superiority over conventional f −k techniques in signal preservation and noise suppression.
One Method to Realize Alterable Order Analog Fractance Circuits

The realization of analog circuit of fractance is most important for the fractional calculus application.An approach to design alterable order fractance using Operational Transconductance Amplifiers(OTA) by cascading finite two-port circuit network was presented.The fractance order can be changed by adjusting the controlling current of OTA without changing the circuit structure.The simulations are in agreement with the theoretical values.
Overlapping Risk Exposure , Work Ethic , and Resilience

This article puts forward a new typology of workers, based on an enhanced set of indicators of psychosocial risks and well-being, and examines the character traits associated with each class membership. This article innovates by simultaneously taking into account how hostile behaviours, poor working conditions, and employment precariousness are associated with different subjective measures of well-being. This study uses a person-centered approach by conducting latent class analysis on a representative sample of 5,867 Canadian employees. Six distinct clusters are revealed: “heavily suffering”, “unfulfilled precarious”, “unhealthy stressed”, “untroubled harassed”, “optimistic precarious” and “not exposed”. This article thus shows that it is not harassment or lack of social benefits per se that affect workers’ well-being. It demonstrates that workers’ well-being deteriorates only when hostile behaviours/conflicts and poor working/employment conditions overlap. Binary logistic regression analyses reveal that, controlling for other worker characteristics, this typology of workers is related to work ethic and resilience. The results suggest two key trends: overlapping exposure to precariousness, procedural injustice and poor prospects for career advancement reduces hard work ethic, while overlapping exposure to hostile behaviour/conflicts and competition reduces resilience.
ESTIMATION OF SPATIAL VARIATION OF SOIL PROPERTIES USING EXTENDED KALMAN FILTER ALGORITHM

The finite element method has been a successful analytical tool in solving various geotechnical engineering problems such as prediction of settlements. Accuracy of the finite element analysis depends on that of estimation of soil properties. However, reliable soil properties cannot always be obtained easily. Hence, an extended Kalman filter, numerical technique developed in the field of system identification, is introduced. In the course of this, the finite element technique is employed in estimating spatially variable soil properties using the observed response values. Furthermore a discussion on applicability of this back analysis method is provided.
Energy-Optimal Control for Autonomous Underwater Vehicles Using Economic Model Predictive Control

Improving endurance is important for autonomous underwater vehicles (AUVs) as it affects the operational cost and application range of the vehicle. In this article, we propose an economic model predictive control (EMPC)-based controller to reduce the control energy of AUVs while performing waypoint tracking. The proposed EMPC controller optimizes stage costs capturing the control energy consumed within the prediction horizon and a terminal cost approximating the energy-to-go, the energy required to reach the desired waypoint from the end of the prediction horizon. To approximate the energy-to-go, we partition it into the dynamic and static segments based on the operational characteristics of the optimal vehicle maneuver obtained from off-line trajectory optimization using direct collocation (DC). To account for the disturbances caused by ocean currents, we adopt the energy-to-go to a virtual Earth-fixed frame that transforms the drift in the vehicle location to the drift in the desired waypoint. Theoretical and numerical analyses of the approximated energy-to-go reveal that the proposed controller can balance the tradeoffs among energy components spent for vehicle surge, heave, and yaw controls in consideration of vehicle dynamics. Simulations under different flow conditions are conducted to compare the proposed approach with DC and a line-of-sight (LOS) guidance-based approach that optimizes vehicle surge speed for energy minimization. Through simulations, it is shown that the proposed approach achieves near-optimal performance as DC and outperforms the LOS-based approach.