Miracle-dz/UniFAR-FTUs huggingface dataset:
Guide: Helping Underrepresented Students Succeed In Engineering

The Graduate, Undergraduate Initiative for Development and Enhancement (GUIDE) program creates a supportive environment for first year engineering students from underrepresented groups. GUIDE provides first year students with undergraduate and graduate student mentors, financial assistance and faculty advisors to assist them with the transition to university life. In addition, GUIDE scholars attend engineering seminars and career workshops. The engineering seminar series introduces the undergraduate students to different facets of engineering through interactions with engineering faculty and professionals. The career development workshops focus on activities students need to complete to obtain co-ops or internships after they complete the GUIDE program. As part of the program, students meet with the program advisors to discuss their perception of the program and to make suggestions to improve the program. This year’s improvements included changes to the structure of the engineering seminars and improvements to program cohesiveness. Historically, the engineering seminars have consisted of an engineering professional speaking to students about an aspect of engineering. Although the seminars are open-ended and invite student discussion, student participation has been lacking. This year, the students were given several questions or an article relating to the seminar to discuss within their team prior to the seminar. During the first half of the seminar, the GUIDE students discussed the questions and/or the articles with the entire group. During the second half of the seminar, the speaker discussed the topic and, revisited the questions. This structure greatly increased student participation. The GUIDE students commented that they had trouble meeting regularly with their teams and they did not get to know the other GUIDE teams. This year, the students met twice a week as a team. They met once to discuss how school and coursework was going and a second time to do something social. Additionally, each team was responsible for organizing a GUIDE activity during the school year. These activities ranged from hockey games to sledding and skiing. The P ge 10678.1 Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright © 2005, American Society for Engineering Education combination of more frequent team meetings and social GUIDE events greatly improved the cohesiveness of the group. This paper describes changes and improvements in the GUIDE program that have been implemented in the last academic year.
Conceptual Costume Design: Utilizing Recyclable Materials to Help Sustain the Environment

Dress reflects people’s perceptions, yet it is sometimes vague and uncertain. What will be added or subtracted from dress will help to extend our future. Materials produced or removed from clothing will help to sustain our environment. Materials unsuitable with the environment constitute the bulk of the objects we re-use. This study integrates costume design and materials incompatible with the environment in creative ways. Art, with its various and special characteristics, can create conceptual clothing as a new form of art. This project conveys conceptual costume design using materials incompatible with the environment in order to send an environmentally sustainable message. Hopefully, with public- awareness, the recycling of incompatible materials can be used in many ways such as ‘costume design’. The main focus and goal of this study is to address this issue.
Downlink Cellular Interference Alignment

Cellular networks have been notoriously interference-limited systems in dense urban areas, where base stations are deployed in close proximity to one-another. Recently, a signal processing method called Interference Alignment has emerged, making use of the increasing signal dimensions available in the system through multiple-input multiple output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) technologies. In this report, we review the state of the art of interference alignment since its foundation, and we detail algorithms and baseline comparisons to make when applying interference alignment schemes to downlink cellular networks. We also propose a number of research directions of interest which are not yet answered in the current literature.
Adaptive sensing in uncertain environments: Maximum likelihood, sensor networks, and reinforcement learning

The advent of distributed and agile sensing systems that collect data in multiple locations and through a variety of sensing modalities has brought about new and exciting challenges to the field of signal processing. Motivated by problems that arise in the development of these systems, the thesis makes contributions in three domains: (1) distributed optimization for inference in sensor networks, (2) statistical tests for optimality that mitigate the problem of sensitivity to local maxima, and (3) development and analysis of reinforcement learning solutions to stochastic decision problems for resource allocation in agile sensing. A novel incremental gradient method, called incremental aggregated gradient (IAG), that can be used by wireless sensor networks to perform inference in a distributed manner, is proposed and analyzed. A gradient aggregation concept relaxes the common requirement of incremental methods for a diminishing step size for convergence, and a fast convergence rate is established. The convergence of IAG is established under a certain unimodality assumption. For non-convex problems however, for example when IAG is applied to find the maximum likelihood estimator, the method might stagnate at a local maximum. To mitigate this weakness, the following question is addressed: Given the location of a relative maximum of the log-likelihood function, how to assess whether it is the global maximum? We analyze and improve an existing statistical tool, called A Test for Global Maximum, that answers this question by posing it as a hypothesis
End-to-End Learning for Autonomous Driving

The end-to-end learning approach for autonomous driving has sparked great interest in both academic and industry in recent years. The approach can be defined as learning a model that maps om sensory input, such as image ames om a camera, to driving actions for controlling the autonomous vehicle such as steering. Compared to the traditional autonomous driving system, which o en includes perception, localization, mapping, and path planning, the end-to-end learning approach offers a more efficient method of utilizing large amounts of expert driver demonstrations to achieve fully autonomous driving without acquiring expensive labeling such as bounding box for objects. The end-to-end learning for autonomous driving can be done by supervised learning, where a model is tuned to minimize the differences between predicted actions and ground-truth actions. The training data is usually obtained om expert demonstrations. A model trained in this way, however, suffers om bad performance due to the mismatch between the samples visited by a learned model and those collected by an expert driver. In the first part of the thesis, we introduce the end-to-end approaches via both supervised learning and imitation learning with different data
Seismic Behavior of Asphaltic Concrete Core Dams

In current years the use of asphaltic concrete core dams are increased especially in some areas with shortage of clayey materials. These dams also have less earth work in comparison with clay core dams. Despite of many advantages of this kind of dam in compression of other types, the behavior of these dams against earthquakes and seismic condition isn't clearly specified. In this research using CA2 program (Finite difference Code) Some numerical studies about the behavior of asphaltic concrete core dams with various height and slopes to understand the influence of dam geometry on behavior of these dams under earthquake condition were done. Application of dams with asphalt concrete core is a relatively novel method especially in Iran. Iran is among regions with high seismicity risk. Therefore, investigation and studying the behavior of such types of dams in earthquake conditions is of more importance considering the novelty of implementing asphaltic core dams. In this research, behavior of asphaltic core dams have been studied under earthquake loading using nonlinear dynamic analysis method and a method is presented for assessment of seismic stability of these types of dams in earthquake conditions based on nonlinear dynamic analysis. Results of the proposed method in this research beside other existing methods can assist designers of asphaltic core dams in judgment about dam stability during earthquake occurrence.
A Model-Driven Approach for Evaluating Traceability Information

—A traceability information model (TIM), in terms of requirement traceability, describes the relation of all artifacts that specify, implement, test, or document a software system. Creating and maintaining these models takes a lot of effort, but the inherent information on project progress and quality is seldom utilized. This paper introduces a domain-speciﬁc language (DSL) based approach to leverage this information by specifying and evaluating company-or project-speciﬁc analyses. The capabilities of the Traceability Analysis Language (TAL) are shown by deﬁning coverage, impact and consistency analysis for a model according to the Automotive Software Process Improvement and Capability Determination (A-SPICE) standard. Every analysis is deﬁned as a rule expression that compares a customizable metric’s value (aggregated from the TIM) against an individual threshold. The focus of the Traceability Analysis Language is to make the deﬁnition and execution of information aggregation and evaluation from a TIM conﬁgurable and thereby allow users to deﬁne their own analyses based on their regulatory, project-speciﬁc, or individual needs. The paper elaborates analysis use cases within the automotive industry and reports on ﬁrst experiences from using it.
SMASH ΔΣ modulator with adderless feed-forward loop filter

A novel cascade ΔΣ modulator, which combines the benefits of sturdy MASH (SMASH) topology and feed-forward loop filter, is presented. The proposed ΔΣ architecture is based on moving the power-hungry adder block from the quantiser input to the first integrator output. The proposed architecture shows a better operational transconductance amplifier (OTA) linearity and relaxed OTA DC-gain compared with conventional MASH and SMASH topologies. This feature makes the modulator topology more suitable than conventional MASH and SMASH topologies for low-voltage applications.
A method to evaluate process performance by integrating time and resources

The purpose of process mining is to improve the existing process of the enterprise, so how to measure the performance of the process is particularly important. However, the current research on the performance evaluation method is still insufficient. The main methods of evaluation are mainly using time or resource. These basic statistics cannot evaluate process performance very well. In this paper, a method of evaluating the performance of the process based on time dimension and resource dimension is proposed. This method can be used to measure the utilization and redundancy of resources in the process. This paper will introduce the design principle and formula of the evaluation algorithm. Then, the design and the implementation of the evaluation method will be introduced. Finally, we will use the evaluating method to analyse the event log from a telephone maintenance process and propose an optimization plan.
Development of single channeled serial-connected piezoelectric sensor array and damage visualization based on multi-source wave propagation imaging

Piezoelectric sensors have been widely used for structural health monitoring. However, a single piezoelectric sensor has limited coverage, and multi-channel piezoelectric sensors require massive cabling and channeling devices. This article presents a serial-connected piezoelectric sensor array equipped with conductive fabric tape for damage diagnosis on a wide area, structure using an ultrasonic propagation imaging system. The sensor array was developed as a single channel sensing technique with multiple sensors. Using conductive fabric tape for installation provided convenient and compact installation, light weight, and comparatively low attenuation, compared with the lead wire for the easy smartilization of structures. An aluminum plate with various artificial damages was tested with the proposed sensor array combined with the ultrasonic propagation imaging system. The ultrasonic propagation imaging system stimulated the sensitive areas of the serially connected piezoelectrics and generated multi-wave sources covering a wide area. The multi-source wave propagation video visualized the damages in the form of anomalous waves. Consequently, multi-cabling and multi-channeling are not required because multiple piezoelectrics can be deployed by serial connections using conductive fabric tapes because of the multi-source wavefield generating capability of the ultrasonic propagation imaging system. Therefore, light-weight, compact, and easy installation of the sensor network and inspection for full-scale structures become possible.
[Abbreviated Title: Audiovisual perception and the vestibular brain]

165 Introduction: 726 Discussion: 2760 Figures: 6 Pages: 25 Corresponding Authors Dorita Chang [changd<AT>hku.hk] Department of Psychology, The University of Hong Kong, Hong Kong Jonas Vibell [vibell<AT>hawaii.edu] University of Hawai̒ i at Mānoa, Hawaii
Rewarding Morphine-Induced Synaptic Function of Delta-Opioid Receptors on Central Glutamate Synapses

The rewarding effect of opioids, the driving force for compulsive behaviors of opioid abuse and addiction, is primarily mediated by the mu-opioid receptor. However, the role of the delta-opioid receptor (DOR) in opioid reward and addiction is still poorly understood. Recently discovered adaptive DOR property of exocytotic translocation in sensory neurons after chronic opioid exposure provides a new avenue of conceptual thoughts to exploring the DOR function in this psychoneurological disease. In this study, we investigated potential adaptive function of DOR in neurons of the central nucleus of the amygdala (CeA), a forebrain structure increasingly recognized for mediating stimulus-reward learning in drug addiction. Using whole-cell recordings in CeA slices, we found that in rats displaying morphine-induced behavior of conditioned place preference, a behavioral measure of drug reward, the overall synaptic strength of glutamate synapses in CeA neurons was significantly enhanced. The selective DOR agonist [D-Pen 2 ,D-Pen 5 ]-enkephalin, having no apparent effect on glutamatergic excitatory postsynaptic current (EPSC) in neurons from control rats, produced a significant, dose-dependent inhibition of the synaptic current in neurons from those morphine-treated rats. Detailed analyses of EPSC properties revealed that DOR activation inhibited the EPSC by reducing presynaptic release of glutamate, indicating functional DOR emerging on presynaptic glutamate terminals. The morphine treatment also significantly increased DOR proteins in CeA preparations of synaptosomes. These findings provide functional evidence for an adaptive modulation by presynaptic DOR of a key synaptic activity altered by morphine, thus implying likely important involvement of DOR in opioid reward and addiction.
Non-Cellular Layers of the Respiratory Tract: Protection against Pathogens and Target for Drug Delivery

Epithelial barriers separate the human body from the environment to maintain homeostasis. Compared to the skin and gastrointestinal tract, the respiratory barrier is the thinnest and least protective. The properties of the epithelial cells (height, number of layers, intercellular junctions) and non-cellular layers, mucus in the conducting airways and surfactant in the respiratory parts determine the permeability of the barrier. The review focuses on the non-cellular layers and describes the architecture of the mucus and surfactant followed by interaction with gases and pathogens. While the penetration of gases into the respiratory tract is mainly determined by their hydrophobicity, pathogens use different mechanisms to invade the respiratory tract. Often, the combination of mucus adhesion and subsequent permeation of the mucus mesh is used. Similar mechanisms are also employed to improve drug delivery across the respiratory barrier. Depending on the payload and target region, various mucus-targeting delivery systems have been developed. It appears that the mucus-targeting strategy has to be selected according to the planned application.
A Single-Phase Cell-Based Asymmetrical Cascaded Multilevel Inverter

A single-phase asymmetrical cascaded multilevel inverter is introduced with the goal of increasing power quality with the reduction of power in insulated-gate bipolar transistor (IGBT) switches. In the present work, the proposed inverter topology is analyzed and generalized with respect to different proposed algorithms for choosing different voltage source values. To prove the advantages of the proposed inverter, a case study involving a 17-level inverter is conducted. The simulation and experimental results with reduced THD are also presented and compared with the MATLAB/SIMULINK simulation results. Finally, the proposed topology is compared with different multilevel inverter topologies available in the literature in terms of the number of IGBT switches required with respect to the number of levels generated in the output of inverter topologies.
Bile Acids Transporters of Enterohepatic Circulation for Targeted Drug Delivery

Bile acids (BAs) are important steroidal molecules with a rapidly growing span of applications across a variety of fields such as supramolecular chemistry, pharmacy, and biomedicine. This work provides a systematic review on their transport processes within the enterohepatic circulation and related processes. The focus is laid on the description of specific or less-specific BA transport proteins and their localization. Initially, the reader is provided with essential information about BAs′ properties, their systemic flow, metabolism, and functions. Later, the transport processes are described in detail and schematically illustrated, moving step by step from the liver via bile ducts to the gallbladder, small intestine, and colon; this description is accompanied by descriptions of major proteins known to be involved in BA transport. Spillage of BAs into systemic circulation and urine excretion are also discussed. Finally, the review also points out some of the less-studied areas of the enterohepatic circulation, which can be crucial for the development of BA-related drugs, prodrugs, and drug carrier systems.
MASTER Real-Time Multi-Message Observations of High Energy Phenomena

This review considers synchronous and follow-up MASTER Global Robotic Net optical observations of high energy astrophysical phenomena such as fast radio bursts (FRB), gamma-ray bursts (including prompt optical emission polarization discovery), gravitational-wave events, detected by LIGO/VIRGO (including GW170817 and independent Kilonova discovery), high energy neutrino sources (including the detection of IC-170922A progenitor) and others. We report on the first large optical monitoring campaign of the closest at that moment radio burster FRB 180916.J0158+65 simultaneously with a radio burst. We obtained synchronous limits on the optical flux of the FRB 180916.J0158+65 and FRB 200428 (soft gamma repeater SGR 1935+2154)(The CHIME/FRB Collaboration, Nature 2020, 587) at 155093 MASTER images with the total exposure time equal to 2,705,058 s, i.e., 31.3 days. It follows from these synchronous limitations that the ratio of the energies released in the optical and radio ranges does not exceed 4 × 105. Our optical monitoring covered a total of 6 weeks. On 28 April 2020, MASTER automatically following up on a Swift alert began to observe the galactic soft gamma repeater SGR 1935+2154 experienced another flare. On the same day, radio telescopes detected a short radio burst FRB 200428 and MASTER-Tavrida telescope determined the best prompt optical limit of FRB/SGR 1935+2154. Our optical limit shows that X-ray and radio emissions are not explained by a single power-law spectrum. In the course of our observations, using special methods, we found a faint extended afterglow in the FRB 180916.J0158+65 direction associated with the extended emission of the host galaxy.
Commande d'une éolienne à base de GADA par modes glissants d'ordre supérieur et observateur grand gain

Le rendement d'une eolienne dependant essentiellement de la puissance du vent, de la courbe de puissance de la turbine et de l'habilite de la generatrice a repondre aux fluctuations du vent, cet article propose alors une strategie de commande de la generatrice asynchrone double alimentation d'une eolienne ; strategie robuste aux incertitudes de modelisation de la generatrice et de l'aerogenerateur, et qui permet d'optimiser la production energetique (rendement). Pour ce faire, il est mit en œuvre un observateur a grand gain pour estimer le couple aerodynamique et des commandes par mode glissant d'ordre superieur. La strategie globale ainsi proposee a ete validee sur une eolienne tripale de 1.5 MW en utilisant le simulateur FAST.
Inside the perpendicular spin-torque memristor

Memristors are non-volatile nano-resistors. Their resistance can be tuned by applied currents or voltages and set to a large number of levels between two limit values. Thanks to these properties, memristors are ideal building blocks for a number of applications such as multilevel non-volatile memories and artificial nano-synapses, which are the focus of this work. A key point towards the development of large scale memristive neuromorphic hardware is to build these neural networks with a memristor technology compatible with the best candidates for the future mainstream non-volatile memories. Here we show the first experimental achievement of a memristor compatible with Spin-Torque Magnetic Random Access Memory. The resistive switching in our spin-torque memristor is linked to the displacement of a magnetic domain wall by spin-torques in a perpendicularly magnetized magnetic tunnel junction. We demonstrate that our magnetic synapse has a large number of intermediate resistance states, sufficient for neural computation. Moreover, we show that engineering the device geometry allows leveraging the most efficient spin torque to displace the magnetic domain wall at low current densities and thus to minimize the energy cost of our memristor. Our results pave the way for spin-torque based analog magnetic neural computation.