Miracle-dz/UniFAR-FTUs huggingface dataset:
Uplink Spectral and Energy Efficiency Analysis of Low Resolution Quantized-Massive MIMO Systems

Massive MIMO with hundreds of antennas at base station (BS), is a key technology for wireless communication in 5G standard. Using low-resolution analog to digital converters (ADCs) is an ongoing research in respond to the challenge of high power consumption of such huge number of antennas at the BS. In this paper, we analyze energy efficiency (EE) and spectral efficiency (SE) of uplink massive MIMO employing low resolution quantizers and zero-forcing (ZF) detection at the BS. Considering circuit power consumption, we propose approximate expressions for the uplink sum rate and energy efficiency of a single cell system, in which $K$ single antenna users communicate with a base station having $M$ antennas. These expressions are validated by performing Monte-Carlo simulation. Then, using the proposed expressions, we evaluate the effects of different parameters such as M, K, average transmit power, and number of quantization bits on the SE and EE performance of the system. Indeed, we show that there is a special $M$ in order to maximize energy efficiency with respect to the effective system parameters.
The Relationship Between ADT and MDADT Schemes for Switched Systems*

The relationship between ADT and MDADT schemes for switched systems is investigated. Some apparent flaws and misunderstandings in the existing literatures have been pointed out. The strengths and weaknesses of the stability results under two schemes are discussed for switched systems. The theoretical findings are also applicable to other types of stability problems for the system based on these two schemes. Finally, the effectiveness and validity of the obtained results can be seen from two numerical examples borrowed from the existing results.
A Force Reflection Impedance Control Scheme for Dual User Haptic Training System

In this paper, an impedance control based training scheme for a dual user haptic surgery training system is introduced. The training scheme allows the novice surgeon (trainee) to perform a surgery operation while an expert surgeon (trainer) supervises the procedure. Through the proposed impedance control structure, the trainer receives trainee's position to detect his (her) wrong movements. Besides, a novel force reflection term is proposed in order to efficiently utilize trainer's skill in the training loop. Indeed, the trainer can interfere into the procedure whenever needed either to guide the trainee or suppress his (her) authority due to his (her) supposedly lack of skill to continue the operation. Each haptic device is stabilized and the closed loop stability of the nonlinear system is investigated. Simulation results show the appropriate performance of the proposed control scheme.
Design and Thermal Analysis of a Rotating Transformer

A rotating transformer is a reliable, compact and brush-less method to power the field winding of a wound-rotor synchronous machine. In the interest of efficiency, safety and reliability, wound rotor synchronous machines remain the preferred generator topology for many applications. This is due to the ability to fully control and easily switch-off, the rotor magnetic field. When designing a rotating transformer for this application, the close proximity to the machine means effective cooling is paramount, along with the desire for high power density and efficiency. Accurate thermal and loss modelling is needed to develop an optimal design. However, numerous thermal properties are difficult to accurately model or predict in advance. In addition, multi-stranded litz wire, typically required when operating at high frequencies, is challenging to model. Both in terms of the AC loss and the effectiveness of heat extraction from the winding slot. To combat this, standard manufacturer cores are first used to allow a rapid and cost-effective investigation into the design. A liquid-cooled test facility allows a detailed thermal and loss analysis to be conducted on the candidate transformer prototype. Through these experimental tests and the use of thermal modelling analysis techniques, critical thermal and loss data is obtained and used to improve the performance prediction for a new, more optimised rotating transformer geometry.
A Novel Contactless Rotary-to-Linear Magnetic Actuator

Mechanical linear actuators are employed extensively in various industrial applications where a linear motion is required. Typical linear mechanical actuators such as ball screws, chain drives, scotch yokes and rack-and-pinion systems convert a rotary motion into a linear motion using different mechanisms. In this paper, a novel magnetic rotary-to-linear actuator is introduced. The proposed actuator utilizes permanent magnets to transmit mechanical power from a rotary part (the rotor) to a linear part (the slider) or vice versa. There is no mechanical contact between the rotor and the slider which results in higher reliability, less maintenance requirements and longer lifetime. Although, this rotary-to-linear system is intended to replace mechanical linear actuators, it could also be used in linear-to-rotary systems such as in wave energy converters. The system was analyzed and simulated using 3-D Finite Element Analysis (FEA). Moreover, a prototype was built, and the concept of operation was experimentally verified.
Effects of Manufacturing Imperfections and Design Parameters on Radial Magnetic Forces in the BLDC Claw-Pole Motor

The demand for overall noise level reduction in cars has increased as of late; meanwhile, the number of auxiliary drives in cars has also increased significantly. Especially in electric vehicles, the application of conventional auxiliary drives, the noise of which is then masked by that of the combustion engine or other dominant noise sources, may not be possible. To address these circumstances, this paper studies the formation of radial magnetic forces in the low-cost sub-fractional hp single-phase outer-rotor BLDC claw-pole motor caused by manufacturing imperfections. Those explored herein include eccentricity, stator part misalignment, and non-uniform magnetization, as well as design parameter variations like air-gap asymmetry and type of magnetization pattern. The findings show that eccentricity and non-uniform magnetization cause unbalanced radial magnetic forces of pulsating character which may trigger system resonances at four times the rotational frequency.
Pump-Back Validation of a Medium Voltage High-Frequency “SiC+Si” Hybrid Three-Level ANPC Inverter for Hybrid-Electric Propulsion Application

High power density medium voltage high speed electric motors for aircraft hybrid electric propulsion applications often require high output fundamental frequency from the power inverter. Conventional Si-based medium voltage drive has a switching frequency that is not sufficient to meet the dynamic and harmonic requirements for such application. A “SiC+Si” hybrid three-level active neutral point clamped (ANPC) inverter has been developed as high-speed motor drive for hybrid electric propulsion. Single-phase and three-phase pump-back tests are performed to validate the power capability and basic control functions. The implementation and test results will be reported in this paper.
Wie übersetzt NMT Eigennamen und Zahlen?

Abstract Since September 2016, when Google implemented the neural machine translation (NMT) technique in Google Translate (GNMT), the overall quality of machine translation (MT) has improved significantly, narrowing the gap between MT and human translation (HT). One detail aspect of MT quality is how the system can cope with the translation of proper names and numbers, so-called Named Entities (NEs). This paper outlines the principles underlying the GNMT translation of NEs and analyzes form changes including errors that are encountered during NMT-based translation and the causes of those form changes. First, on the basis of Wu et al. (2016), a simple model for GNMT-based NE translation is created, and within this model NE translations in 60 target texts are analyzed and compared to those of a professional translator. According to this model, GNMT-derived NE-form changes can roughly be attributed to four causes: segmentation, memory, features of training corpora, and functionality in the attention system.
M2M Communications as a Promising Technique to Support Green Powered Base Stations

One of the crucial challenges in Internet of Things (IoT) is to maximize the use of renewable power sources (RPSs) like solar energy. In our presented model, Base Stations (BSs) are powered via a combination of a renewable power source and the conventional electric grid (EG). However, optimal utilization of renewable energies for BSs is also significantly important due to inaccessibility of solar energy during the night, so that BSs attempt to reduce EG-based power consumptions, remarkably. Moreover, the total power-consumption in BSs depends on the data traffic demand from sensors per cell. Machine-to-Machine (M2M) communication is a new technology, which is expected to reduce random connection demands from the sensors deployed over a wireless sensor network (WSN). Indeed, this paper presents an optimal strategy for green power management according to M2M impressive capabilities in sharing data among adjacent sensors and therefore offloading a portion of the data traffic from BSs. In this method, sensors instead of sending their connection requests to BSs, search their required files via M2M connections based on certain security rules, at first. This process finally results in green powered BSs with minimum referring to the EG, as it is confirmed through simulations.
Personal Cloud Storage Services Evaluation Model Based on User Experience

With the wake of the growing demand for network storage of users, a large number of personal cloud storage service platforms have emerged. Only by optimizing the user experience to maintain user stickiness and attract potential users can PCSSs providers take advantage of market opportunities and gain a strong competitive edge. Focusing on a total of 16 hierarchical dimensions of user experience of personal cloud storage services including overall experience, its elements and sub-elements, this paper combines user experience quantification model and cloud storage service evaluation to construct four quantitative models, including compensatory models (simple linear model and prospect theory value model) and non- compensatory models (conjunctive models and dis junctive models). Baidu, one of the mainstream cloud storage service providers in China, was selected as a case study to verify each model. Results show that the prospect theory value model has a relatively higher performance in regard to fit of goodness. The results of the study are expected to provide a reference for service design, helping service providers to understand users more intuitively and to allocate resources scientifically and efficiently.
Auto-reclosing Protection Scheme for Multi-Terminal Mixed Lines Using Synchrophasor Measurements

The paper proposes a selective auto-reclosing scheme for multi-terminal mixed lines using synchrophasor measurements. Selective auto-reclosing for multi-terminal mixed lines can be performed using information regarding the faulted section. The faulted section can be identified based on a comparison of the calculated and measured positive sequence voltage quantities at all terminals. The positive sequence voltage at each terminal can be calculated in terms of the positive sequence voltage, current measured at both the remote terminals and positive sequence current measured at the local terminal. The method is tested using EMTDC/PSCAD simulations. The simulation studies show that the proposed method identified the correct faulted section and the scheme is robust to variations in fault resistance, the angle of fault inception, the position of the fault on the line and type of fault.
Crowd Behavior Simulation based on Psychological emotion, sociological role and personality

In order to realize the real navigation behavior of virtual human, a new method is proposed to integrate the psychological emotion, sociological role and personality characteristics of virtual human into the collision avoidance behavior, so as to generate diversified collision avoidance behavior according to different internal attributes of virtual human. Based on the principle of minimum cost, the influences of psychological emotion, sociological role and personality parameters on the parameters of predictive collision avoidance behavior are studied. Finally, the relationship between the fuzzy reasoning method and the predictive collision avoidance behavior parameters is established. The simulation results show that our approach is effective and feasible. Eventually realistic crowd phenomena are created in the scenarios in city environment.
Topological Graphic Passwords Made By Series Sun-graphs On Odd-graceful Property

In this paper, two kinds of sun-graph models in ring network are given odd-graceful labellings, So they have the topological graphic passwords (Topsnut-gpws). Furthermore, they can be encrypted by corresponding Topsnut-matrix and Text-based passwords, which make information transmission more secure and reliable.
Online Characterization of a Synchronous Generator Using an Unscented Kalman Filter

This paper presents techniques to characterize a salient pole synchronous generator while it is online. Due to the need for an accurate model of the power system, the WECC and NERC introduced a policies which states that utilities need to maintain up-to-date parameters for their system for generating units above 20MW. Consequently, the common practice is to follow the IEEE 115 standard which requires the generator to be taken offline. Taking a generator offline creates a significant cost for the generation facility due to the time required to parameterize the machines. The Unscented Kalman Filter is chosen to capture the states and estimate the parameters of a salient pole synchronous machine while it is online. The chosen algorithm is tested, tuned, and verified against a simulated generator in MATLAB in both steady state and transient conditions in a two-step process. Online steady state parameter tests were also conducted on a 20hp generator and compared to the results of IEEE 15 tests conducted on the machine.
High-Speed Obstacle Avoidance at the Dynamic Limits for Autonomous Ground Vehicles

High Speed Obstacle Avoidance at the Dynamic Limits for Autonomous Ground Vehicles by Jiechao Liu Chair: Jeffrey L. Stein and Tulga Ersal Enabling autonomy of passenger-size and larger vehicles is becoming increasingly important in both military and commercial applications. For large autonomous ground vehicles (AGVs), the vehicle dynamics are critical to consider to ensure vehicle safety during obstacle avoidance maneuvers especially at high speeds. This research is concerned with large-size high-speed AGVs with high center of gravity (CoG) that operate in unstructured environments. The term ‘unstructured’ in this context denotes that there are no lanes or traffic rules to follow. No map of the environment is available a priori. The environment is perceived through a planar light detection and ranging sensor. The mission of the AGV is to move from its initial position to a given target position safely and as fast as possible. In this dissertation, a model predictive control (MPC)-based obstacle avoidance algorithm is developed to achieve the objectives through an iterative simultaneous optimization of the path and the corresponding control commands. MPC is chosen because it offers a rigorous and systematic approach for taking vehicle dynamics and safety constraints into account.
Macrophage Death as a Pharmacological Target in Atherosclerosis

Atherosclerosis is a chronic inflammatory disorder characterized by the gradual build-up of plaques within the vessel wall of middle-sized and large arteries. Over the past decades, treatment of atherosclerosis mainly focused on lowering lipid levels, which can be accomplished by the use of statins. However, some patients do not respond sufficiently to statin therapy and therefore still have a residual cardiovascular risk. This issue highlights the need for novel therapeutic strategies. As macrophages are implicated in all stages of atherosclerotic lesion development, they represent an important alternative drug target. A variety of anti-inflammatory strategies have recently emerged to treat or prevent atherosclerosis. Here, we review the canonical mechanisms of macrophage death and their impact on atherogenesis and plaque stability. Macrophage death is a prominent feature of advanced plaques and is a major contributor to necrotic core formation and plaque destabilization. Mechanisms of macrophage death in atherosclerosis include apoptosis, passive or accidental necrosis as well as secondary necrosis, a type of death that typically occurs when apoptotic cells are insufficiently cleared by neighboring cells via a phagocytic process termed efferocytosis. In addition, less-well characterized types of regulated necrosis in macrophages such as necroptosis, pyroptosis, ferroptosis, and parthanatos may occur in advanced plaques and are also discussed. Autophagy in plaque macrophages is an important survival pathway that protects against cell death, yet massive stimulation of autophagy promotes another type of death, usually referred to as autosis. Multiple lines of evidence indicate that a better insight into the different mechanisms of macrophage death, and how they mutually interact, will provide novel pharmacological strategies to resolve atherosclerosis and stabilize vulnerable, rupture-prone plaques.
A Framework for Evaluating Recommender Systems

A Framework for Evaluating Recommender Systems Michael Gabriel Bean Department of Linguistics & English Language, BYU Master of Arts Prior research on text collections of religious documents has demonstrated that viable recommender systems in the area are lacking, if not non-existent, for some datasets. For example, both www.LDS. org and scriptures.byu. edu are websites designed for religious use. Although they provide users with the ability to search for documents based on keywords, they do not provide the ability to discover documents based on similarity. Consequently, these systems would greatly benefit from a recommender system. This work provides a framework for evaluating recommender systems and is flexible enough for use with either website. Such a framework would identify the best recommender system that provides users another way to explore and discover documents related to their current interests, given a starting document. The framework created for this thesis, RelRec, is attractive because it compares two different recommender systems. Documents are considered relevant if they are among the nearest neighbors, where “nearest” is defined by a particular system’s similarity formula. We use RelRec to compare output of two particular recommender systems on our selected data collection. RelRec shows that LDA recommeder outperforms the TF-IDF recommender in terms of coverage, making it preferable for LDS-based document collections.
Classification of Clinical Isolates of Klebsiella pneumoniae Based on Their in vitro Biofilm Forming Capabilities and Elucidation of the Biofilm Matrix Chemistry With Special Reference to the Protein Content

Klebsiella pneumoniae is a human pathogen, capable of forming biofilms on abiotic and biotic surfaces. The limitations of the therapeutic options against Klebsiella pneumoniae is actually due to its innate capabilities to form biofilm and harboring determinants of multidrug resistance. We utilized a newer approach for classification of biofilm producing Klebsiella pneumoniae isolates and subsequently we evaluated the chemistry of its slime, more accurately its biofilm. We extracted and determined the amount of polysaccharides and proteins from representative bacterial biofilms. The spatial distribution of sugars and proteins were then investigated in the biofilm matrix using confocal laser scanning microscopy (CLSM). Thereafter, the extracted matrix components were subjected to sophisticated analysis incorporating Fourier transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, one-dimensional gel-based electrophoresis (SDS-PAGE), high performance liquid chromatography (HPLC), and MALDI MS/MS analysis. Besides, the quantification of its total proteins, total sugars, uronates, total acetyl content was also done. Results suggest sugars are not the only/major constituent of its biofilms. The proteins were harvested and subjected to SDS-PAGE which revealed various common and unique protein bands. The common band was excised and analyzed by HPLC. MALDI MS/MS results of this common protein band indicated the presence of different proteins within the biofilm. The 55 different proteins were identified including both cytosolic and membrane proteins. About 22 proteins were related to protein synthesis and processing while 15 proteins were identified related to virulence. Similarly, proteins related to energy and metabolism were 8 and those related to capsule and cell wall synthesis were 4. These results will improve our understanding of Klebsiella biofilm composition and will further help us design better strategies for controlling its biofilm such as techniques focused on weakening/targeting certain portions of the slime which is the most common building block of the biofilm matrix.
The Role of Pre-existing Cross-Reactive Central Memory CD4 T-Cells in Vaccination With Previously Unseen Influenza Strains

Influenza vaccination is a common approach to prevent seasonal and pandemic influenza. Pre-existing antibodies against close viral strains might impair antibody formation against previously unseen strains–a process called original antigenic sin. The role of this pre-existing cellular immunity in this process is, despite some hints from animal models, not clear. Here, we analyzed cellular and humoral immunity in healthy individuals before and after vaccination with seasonal influenza vaccine. Based on influenza-specific hemagglutination inhibiting (HI) titers, vaccinees were grouped into HI-negative and -positive cohorts followed by in-depth cytometric and TCR repertoire analysis. Both serological groups revealed cross-reactive T-cell memory to the vaccine strains at baseline that gave rise to the majority of vaccine-specific T-cells post vaccination. On the contrary, very limited number of vaccine-specific T-cell clones was recruited from the naive pool. Furthermore, baseline quantity of vaccine-specific central memory helper T-cells and clonotype richness of this population directly correlated with the vaccination efficacy. Our findings suggest that the deliberate recruitment of pre-existing cross-reactive cellular memory might help to improve vaccination outcome.
Advances in deep ultraviolet laser based high-resolution photoemission spectroscopy

We briefly review recent results on photoemission spectroscopy based on the deep and vacuum ultraviolet diode pumped solid-state lasers which we have developed. Cascaded second harmonic generation with the nonlinear crystal KBe2BO3F2 (KBBF) is used to generate deep ultraviolet and vacuum ultraviolet laser radiation, which complements traditional incoherent light sources such as gas discharge lamps and synchrotron radiation, and has greatly improved resolution with respect to energy, momentum, and spin of photoemission spectroscopy. Many new functions have been developed with the advantages of high photon energy, narrow linewidth, high photon flux density, and so on. These have led to the observation of various new phenomena and the amassment of new data in the fields of high temperature superconductivity, topological electronics, Fermi semi-metals, and so forth. These laser systems have revived the field of photoemission spectroscopy and provided a new platform in this frontier research field.