Miracle-dz/UniFAR-FTUs huggingface dataset:
The Discipline Gap: What's Trust Got to Do with It?

Background/Context If we are serious about eliminating the racial achievement gap, we need to address the discipline gap as well. The scholarly literature generally paints a positive picture of the potential of trust to transform schools. Research on student trust has shown that students who trust their teachers and schools are suspended and expelled less frequently and have more positive academic outcomes. However, we know little about if or how the impact of trust may vary by race or gender. Research Question Do the benefits of trusting relationships accrue equally to all students? Do trusting student–teacher relationships pay off in less discipline and improved academic outcomes for all students, or do the benefits of trust depend on the race and gender of the student? Research Design Structural equation modeling was used to model the relationships between student trust, behavior, and high school outcomes, controlling for socioeconomic status, school size, and prior achievement. Data, drawn from the Educational Longitudinal Survey of 2002, includes responses from more than 6,000 public high school students (n = 6,352) who identify as African American or White. Comparisons are made between results for White, African American, and African American male students. Findings/Results Student trust is associated with fewer disciplinary incidents and better academic outcomes; however, the benefits of trust do not accrue equally to all students. Black students, particularly males, benefit less from trust. Controlling for trust, behavior, and standardized measures of math and reading ability, Black students are penalized multiple times for a single disciplinary incident: by the suspension (or other consequence), by missed instruction, and by the impact on their grades (and possibly their future course placement and postsecondary plans). In other words, there are unequal consequences of equal discipline. Conclusions/Recommendations This research found that Black and White students with roughly equivalent discipline records, scores on achievement tests, and levels of trust still have substantially different high school outcomes. Although efforts to implement restorative justice or positive behavior support programs are a step in the right direction, results suggest that they will not be enough. Schools must deal with implicit bias and the unequal consequences of equal discipline. To do this, we must scrutinize course placement practices, grading, and the messages that we send to students. Failure to do so will continue to leave us with a vast education debt and will continue to fuel the achievement gap.
Prompting Reflections for Integrating Self-Regulation into Teacher Technology Education

Background Technology represents a major topic in educational research. Nevertheless, a gap in the research remains concerning how teachers can bring technology into the classroom. This study focuses on the technological pedagogical content knowledge (TPCK) framework, which aims to consolidate the multidisciplinary professional knowledge related to technology, pedagogy, and content that teachers need so that they can teach and students can learn effectively using technology tools. Purpose The goal of the present study was to investigate the value of modification reflection prompts (“think ahead”) as a complementary reflective framework during the teacher preparatory program, beyond the more traditional judgment reflection prompts (“think back”). In particular, we examined how preservice science teachers may capitalize on learning from modification prompts versus judgment prompts versus both (“think back” and “think ahead”), compared with learning from generic prompts (“stop and think”) based on the IMPROVE model oriented to TPCK. We examined these four treatments’ effects on preservice teachers’ actual design of science lessons and development of their own self-reflection abilities. Participants Participants were 199 first-year preservice science teachers in their preparatory programs at a university in central Israel. Research Design We created a quasi-experimental opportunity for four groups of preservice science teachers to systematically contemplate ready-made TPCK-oriented lesson designs. Each used one of four different reflective methods (the independent variable): modification, judgment, combined modification+judgment, or generic prompts. Then we examined the differential contribution of these treatment methods to the two dependent variables: (1) preservice teachers’ skills for designing actual science lessons and (2) their judgment-type and modification-type self-reflection ability regarding the planning, monitoring, and evaluation phases of their lesson-design process. Data Collection and Analysis Data were scored by coding schemes and were analyzed by multivariate analysis of variance and follow-up analyses of variance with repeated measures. Findings Results indicated that preservice teachers who contemplated a combination of both judgment and modification reflections in treatment improved more in their lesson-design skills and in their self-reflection ability (of both types at the three phases), compared with preservice teachers who contemplated only a single type of reflective prompt (generic or only judgment or modification). Lasting effects (after a semester without the IMPROVE model, prompts, or TPCK focus) revealed that the combined approach continued to significantly outperform the single approaches. Recommendations The current study reinterprets the instructional-reflective framework of teacher education programs to include modification reflection too as a means of developing preservice teachers’ capacity to integrate technology in their lesson designs.
Frequency Splitting and other Things that Filters and Wireless Power Transfer Systems have in Common

In this paper, the phenomenon of frequency splitting in resonating Wireless Power Transfer Systems is considered. In particular, the property of impedance inverters of converting an impedance into an admittance is here exploited to give a simple and intuitive explanation of that phenomenon. Furthermore, some analogies between WPT systems and filters are here highlighted showing that the frequency splitting phenomenon is also present in Chebyshev filter responses.
The History of Radiation from Leaky-Wave Antennas

Leaky-wave antennas (LWAs) are now widespread and designed over a wide frequency range, from microwaves up to optics. One of the attractive features of LWAs is their simple design process as a consequence of the accurate analytical description of their radiating features. In this work, we review from a historical perspective the milestones that characterized the mathematical description of radiation from LWAs, starting from the pioneering contributions of N. Marcuvitz and A. A. Oliner, until the more recent developments.
Bin-packing Based Online Dynamic Bandwidth and Wavelength Allocation Algorithm in Super-PON

Super passive optical network (Super-PON) is a next-generation Ethernet PON (NG-EPON) candidate that is envisaged to provide high data rate and low latency. For NG-EPON, there are two types of algorithms that manages bandwidth and wavelength scheduling, namely offline and online. The latter method is more scalable and efficient than the former method. Several online algorithms exist that propose schemes to manage wavelength and bandwidth scheduling. However, these algorithms lack in efficient wavelength utilization and switching. In this work, we propose a novel online bin-packing based dynamic bandwidth and wavelength allocation (DBWA) algorithm for Super-PON, namely updated best fit bin-packing (UBF-BP). This algorithm limits the wavelength switching per cycle, and uses the modified version of best fit bin-packing (BF-BP) technique for optimal wavelength allocation. Simulation results show that the proposed DBWA algorithm has a low complexity and overcomes the inefficiencies of wavelength utilization and switching. This results in lower network delay and higher channel utilization than the state-of-the-art DBWA. Furthermore, to verify the correctness of the proposed algorithm, we propose an analytical model and validate these simulation results with the analytical results.
Efficient computation method for the electromagnetic scattering of complex targets

In this article, we present a fast and accurate numerical method for the computation of scattered electromagnetic field from targets of different sizes and complex shapes. The approach is based on the sampling representation of the complex reflection coefficient of the target where both amplitude and phase information are considered, rather than the usual radar cross section (RCS) where the phase information is missed. The scattering features of the target are organized in a 5-D complex matrix H calculated numerically. The electromagnetic tool (CST) computes this H matrix evaluating the scattered field in a finite number of selected directions. This number is chosen in order to obtain a good reconstruction of overall scattering feature. As assumed for the scattered field, matrix H is also calculated for the same discrete set of directions of the incident wave. Two numerical examples are provided to demonstrate the correctness and the efficiency of the proposed method.
Scattering by Dielectric or Conducting Cylinders above a Lossy Medium and Relevant Focusing Effects

In this paper, we present an analytical solution based on the Cylindrical Wave Approach to study the interaction of a plane-wave with cylindrical objects, either dielectric or conducting, placed above a semi-infinite lossy medium. The effects of focusing of the electromagnetic field by the array of scatterers is investigated. The analytical approach is validated by a comparison with a commercial software. Some numerical examples are presented, considering both TM and TE polarization of the incident wave in the millimeter frequency range at 24 GHz. Interesting applications are in the modelling of the scattered field by objects above a biological tissues, in the presence of wereable or implantable antennas sources.
Compressive Imaging and Direction of Arrival Estimation using Reconfigurable Metasurface Apertures

This paper presents the concept of reconfigurable metasurface apertures as an enabling technology to facilitate physical layer compression for imaging and direction of arrival (DoA) estimation at microwave frequencies. Two different techniques are presented to spatially control the radiated field patterns and generate spatio-temporally incoherent measurement bases to replace the conventional array based raster scanning techniques. Leveraging the physical layer compression, high quality radar imaging and DoA estimation have been achieved, using only two channels for imaging and a single channel for DoA estimation.
FullSight: a Deep Learning based Collaborated Failure Detection Framework of Service Function Chain

Network Function Virtualization (NFV) is one of the most promising technologies which decouples Network Functions (NFs) from hardware resources to support more flexible network services and network resource allocation. However, these benefits increase the possibility of Service Function Chain (SFC) failures due to hardware failures, software defects and burst traffic, resulting in serious consequences. Unfortunately, existing failure detection methods have several issues, such as simplification of detection functionality, heavy overhead, and low accuracy. This paper introduces a framework FullSight, in which control plane and the programmable data plane can collaboratively detect failure and Deep Learning (DL) based algorithms are adopted for failure detection. FullSight can achieve an all-round perception of the state of the SFC, in which network information is acquired through the data plane, SFC components' message is obtained through the control plane. In addition, a failure detection model based on DL is established. Compared with the state-of-the-art methods, FullSight can support 8 kinds of the fine-grained failure detection. Our comprehensive evaluation of prototypes and simulations shows that FullSight can realize rapid and accurate detection and classification of diversified failures in SFCs. The bandwidth overhead reduces by 57% compared with the existing methods. Additionally, FullSight has a detection accuracy up to 93.5%.
A 19-GHz 5-Bit Switch-Type Phase Shifter Design Using Phase Compensation Techniques

A 19-GHz 5-bit switch-type phase shifter (STPS) using 180-nm CMOS technology is presented. In this paper, the reverse-direction phase compensation technique is used to make the final results closer to the design goal. The measured insertion loss for all 32 states is 13 ± 1 dB at 19 GHz. The phase shifter achieves a RMS phase error of 3.7° and a RMS amplitude error of 0.5 dB at 19 GHz, which are improved from initial phase error of 8.2° and amplitude error of 0.82 dB, respectively.
Power electronics based on wide-bandgap semiconductors: opportunities and challenges

The expansion of the electric vehicle market is driving the request for efficient and reliable power electronic systems for electric energy conversion and processing. The efficiency, size, and cost of a power system is strongly related to the performance of power semiconductor devices, where massive industrial investments and intense research efforts are being devoted to new wide bandgap (WBG) semiconductors, such as silicon carbide (SiC) and gallium nitride (GaN). The electrical and thermal properties of SiC and GaN enable the fabrication of semiconductor power devices with performance well beyond the limits of silicon. However, a massive migration of the power electronics industry towards WBG materials can be obtained only once the corresponding fabrication technology reaches a sufficient maturity and a competitive cost. In this paper, we present a perspective of power electronics based on WBG semiconductors, from fundamental material characteristics of SiC and GaN to their potential impacts on the power semiconductor device market. Some application cases are also presented, with specific benchmarks against a corresponding implementation realized with silicon devices, focusing on both achievable performance and system cost.
High-Efficiency WPT System for CC/CV Charging Based on Double-Half-Bridge Inverter Topology With Variable Inductors

Efficiency remains a key challenge in wireless charging in academia and industry. In this article, a new wireless power transfer (WPT) system based on a double-half-bridge (DHB) inverter with two variable inductors (VIs) is proposed. Compared with conventional full-bridge (FB) inverters, the DHB inverter can reduce the current through the mosfets under the same output power and thus, reduce the conduction loss. Next, by adjusting the inductances of the VIs instead of using phase shift (PS) method, the output voltage or current can be controlled, while the circulating current can be eliminated and wide-range zero voltage switching operation can be achieved. Consequently, the power loss can be further reduced. Circuit analysis, VI design, as well as hardware implementation, are provided in detail. A laboratory prototype is built to verify the feasibility of the proposed method. Close agreement is obtained between simulation and experimental results. The maximum efficiency can reach 92.4%, which is 3.65% higher than traditional PS control.
Axial Ring Feed Horn with Logarithmic Flare for Offset Gregorian Optics

We present an improved axial ring feed horn using a logarithmic spiral flare opening and tapered groove geometry that is suitable for wide-angle feeding, as required for offset Gregorian telescopes. To enable a design with maximum aperture efficiency, full 2-D field integration was calculated as part of the optimization loop. Since aperture efficiency includes the contributions of cross-polarization, phase, amplitude, and taper, directly optimizing against these terms will result in excellent wideband performance. An example design is shown and optimized for the 30–51 GHz band.
Exploring the potential for top-dressing bread wheat with ammonium chloride to minimize grain yield losses under drought

ABSTRACT The frequency and severity of drought is predicted to rise in many parts of the world. Considering that drought is the main constraint on rain-fed wheat crop production, both agronomic and genetic measures have been taken to minimize yield losses under drought. Beyond its role as a micronutrient, chloride also acts as an osmoticum, implicated in the regulation of stomatal aperture. This study explores the potential for chloride fertilization of Australian bread wheat (Triticum aestivum L.) to minimize grain yield losses caused by drought stress. For this, two drought-tolerant commercial genotypes (Mace and Gladius) and a well-studied drought-tolerant genotype used in wheat breeding (RAC875) were treated with ammonium chloride, potassium chloride, or ammonium bicarbonate, the latter two treatments served as controls for chloride and ammonium, respectively. Plants were grown under either a watered or water-restricted (drought) regime. The genotype RAC875 was found to accumulate leaf chloride at a significantly higher level than the other genotypes under optimal growth conditions. Under drought conditions, top-dressing RAC875 plants with ammonium chloride resulted in up to a 2.5-fold increase in grain number and this effect was not seen when plants were top-dressed with either of the control fertilizers. The ammonium chloride treatment also minimized losses of grain yield in RAC875 plants grown under drought. Treatment effects were accompanied by an increase in stomatal conductance. These results collectively suggest that the compound fertilizer ammonium chloride can improve drought tolerance of wheat.
A Gain Enhanced Metasurface based Monopole Antenna for WLAN Application

The design and performance of a highly directive gain enhanced metasurface antenna (MSA) has been reported in this paper. The MSA is formed by incorporating the T-shaped patch with $3\times 5$ order metasurface (MS) in which the MS is associated with annular hexagonal shaped patches arranging in periodic manner. This antenna operates at 4.99 GHz and the −10 dB impedance bandwidth has been achieved in the range 4.79 GHz-5.09 GHz. The antenna provides the maximum realized gain of 11.2 dBi at 4.99 GHz. The endfire radiation pattern has been observed along E-plane while nearly omnidirectional pattern has been realized along H-plane. The designed structure can be promoted for WLAN applications.
Evaluation of Instance-Based Learning and Q-Learning Algorithms in Dynamic Environments

Reinforcement learning is an unsupervised learning algorithm, where learning is based upon feedback from the environment. Prior research has proposed cognitive (e.g., Instance-based Learning or IBL) and statistical (Q-learning) reinforcement learning algorithms. However, an evaluation of these algorithms in a single dynamic environment has not been explored. In this paper, a comparison between the statistical Q-learning algorithm and the cognitive IBL algorithm is presented. A well-known environment, “Frozen Lake,” is used to train, generalize, and scale Q-learning and IBL algorithms. For generalizing, the Q-learning and IBL agents were trained on one version of the Frozen Lake and tested on a permuted version of the same environment. For scaling, the two algorithms were tested on a larger version of the Frozen Lake environment. Results revealed that the IBL algorithm used less training time and generalized better to different environment variants. The IBL algorithm was also able to show scalability by retaining its superior performance in the larger environment. These results indicate that the IBL algorithm could be proposed as an alternative to the standard reinforcement learning algorithms based on dynamic programming such as Q-learning. The inclusion of human factors (such as memory) in the IBL algorithm makes it suitable for robust learning in complex and dynamic environments.
Adversarial Networks With Circular Attention Mechanism for Fine-Grained Domain Adaptation

Fine-grained Image Analysis (FGIA) as a branch of the image analysis tasks has received more and more attention in recent years. Compared with ordinary image analysis tasks, FGIA requires more detailed human data annotation, which not only requires the annotator to have professional knowledge, but also requires greater labor costs. An effective solution is to apply the domain adaptation (DA) method to transfer knowledge from existing fine-grained image datasets to massive unlabeled data. This paper presents the circular attention mechanism to cyclically extract deep-level image features to match the label hierarchy from coarse to fine. What is more, the networks effectively improve the distinguishability and transferability of fine-grained features based on the adversarial learning framework. Experimental results show that our proposed method achieves excellent transfer performance on three fine-grained recognition benchmarks.
An Efficient Reference-point Based Surrogate-assisted Multi-objective Differential Evolution for Analog/RF Circuit Synthesis

In this paper, we propose an efficient reference-point based surrogate-assisted multi-objective differential evolution algorithm for analog/RF circuit synthesis, which aims to greatly reduce simulation time while maintaining accuracy. First, offspring are generated by differential evolution operator and polynomial mutation. Then we predict the offspring by Gaussian process. Finally, sort the offspring by modified reference-point based NSGA-III criterion, only the most promising one instead of multiple designs is able to be simulated by the circuit simulator. Experimental results on two real-world circuits show that compared with two state-of-the-art multi-objective evolutionary algorithms, our method can achieve up to 6X simulation time reduction without surrendering any accuracy.
A Wide Tuning Range Phase Locked Loop for 38 GHz Transceiver in 65 nm CMOS

This paper presents a 4.75 GHz integer N phase locked loop used in combination with frequency multipliers to achieve local oscillator signal for an 8K drone camera 38-GHz transceiver. This PLL achieves a phase noise of -100 dBc/Hz and -103 dBc/Hz at 100 kHz and 1 MHz offset, respectively. The PLL fabricated in 65 nm CMOS technology occupies a die area of 0.21 mm2. PLL is made programmable to produce accurate LO generation over process, voltage, and temperature variations.
Human RF-EMF Exposure Assessment for an indoor 5G Access Point with Beamforming Capability using Stochastic Dosimetry

Among the novel technologies that 5th Generation (5G) networks will introduce to fulfill the ambitious goals that promise, there are the antenna arrays with three-dimensional (3D) beamforming capabilities. This technology does the RF-EMF exposure scenario evolve with the particular radiation pattern that the Access Point, in an indoor environment, generates in an adaptive way. The problem of setting up an assessment to evaluate the human exposure levels in such a scenario becomes challenging. In this paper, by the jointly use of deterministic and stochastic methods, it was possible to consider up to 1000 different 3D beamforming patterns of the AP with low computational costs. The work allowed to highlight the conditions of major exposure and to prove the validity of stochastic methods, facing the variability and heterogeneity that will characterized 5G scenarios.