Miracle-dz/UniFAR-FTUs huggingface dataset:
An iterative approach for analysis of harmonic penetration in the power transmission networks

An iterative process of computing harmonic voltage profile on a power system transmission network is presented. A method based upon frequency domain analysis is utilized in conjunction with the fundamental load flow computations. The concepts of conventional reactive power and the distortion power incorporated to determine interaction between the power system and harmonic generating sources. The model of the transmission system considered lends itself to the determination of the standing wave pattern and can be used in identifying the points of maxima and minima on the transmission line as well as the two end points. A phase shifting model of the transformer is presented for the harmonic analysis. Three examples of power transmission systems are taken to illustrate use of the algorithm. >
Robot Kinematics Identification: KUKA LWR4+ Redundant Manipulator Example

This work is aimed at a comprehensive discussion of algorithms for the kinematic parameters identification of robotic manipulators. We deal with an open-loop geometric calibration task, when a full 6D robot's end-effector pose is measured. Effective solutions of such a task is of high interest in many practical applications, because it can dramatically improve key robot characteristics. On the first step, we select optimal calibration configurations. A comparative analysis of three different algorithms and two observability indexes used for numerical optimization is provided. Afterwards, using the acquired and pre-processed experimental data we identify modified Denavit-Hartenberg parameters of the manipulator. Estimates are obtained resolving original nonlinear forward kinematics relations. Finally, we compare nominal and calibrated geometric parameters and show how much deviations in these parameters affect robot positioning accuracy. To the best of our knowledge, such integrated efforts are new for the KUKA LWR4+ robot and Nikon K610 optical coordinate measuring machine (CMM), which were used in the study. Discussion of practical issues on how to organise the experiment is an additional contribution of this work. The proposed procedure is highly automated and can be implemented to improve manipulator's performance on a periodic basis.
Overcoming Barriers as a Nepali Woman through Emotional Intelligence: My Emotional Literacy Journey into my Ph.D. in Educational Leadership

This article explores my process of being emotionally literate, realizing my personal power through this process, and deciding to move ahead with my PhD to explore further my contribution to the flourishing of humanity. In this qualitative reflective self-study, I have used my detailed personal, professional, and academic reflective journal and audio-visual narratives that I kept over seven years as data to explore the process of learning. The article reveals my process of learning from my experiences as a confused Nepali girl to my experience of working as a journalist, to becoming an aspiring educational leader and a researcher. The results are discussed using a microscopic lens into my childhood together with an understanding of how social settings played a major role in my learning and how emotional intelligence played an instrumental role in deconstructing that and helped me understand myself better, urging me to explore further through my PhD research as an educational leader.
High-overtone, bulk acoustic resonator frequency stability improvements

In an effort to counter the effects of both moderate-term and long-term frequency instability associated with the (-30 PPM//spl deg/C) frequency-temperature coefficient in high overtone, bulk acoustic resonators (HBAR), AFC loop stabilization of low-noise, 640 MHz HBAR oscillators has been demonstrated. A thermoelectric (TE) cooler is used as the resonator frequency tuning element. The TE cooler approach provides a means of obtaining near-equal device heating and cooling time-response characteristics, allowing stable loop operation. Using this technique, long-term, fractional frequency stability improvement to five parts in 10/sup 7/ has been demonstrated. Prototype resonators have been fabricated on thicker (700 ns delay) YAG crystals and evaluated in oscillators operating at both 320 MHz and 640 MHz that exhibit flicker-of-frequency noise comparable, on a Sy(f) basis, to that reported for ultra-low noise, multiple crystal oscillators operating in the 80-100 MHz range. <<ETX>>
A Study of Inductance Computations for Transverse Flux Linear Motor Considering Nonlinearity of Magnetic Material

Inductance is an important parameter to assess electric motor characteristics. In this paper, the methods of apparent and incremental inductance calculations are introduced for a transverse flux linear motor (TFLM), which has a peculiar coil shape. To consider the nonlinearity of magnetic material, nonlinear analysis is performed by 3-dimensional equivalent magnetic circuit network (3D EMCN). The calculation method is verified by test results.
Comparison of Conventional Control and Robust Control on Double-Pipe Heat Exchanger

Abstract—Heat exchanger is a device used to mix liquids having different temperatures. In this case, the temperature control becomes a critical objective. This research work presents the temperature control of the double-pipe heat exchanger (multi-input multi-output (MIMO) system), which is modeled as first-order coupled hyperbolic partial differential equations (PDEs), using conventional and advanced control techniques, and develops appropriate robust control strategy to meet stability requirements and performance objectives. We designed the proportional–integral–derivative (PID) controller and H-infinity controller for a heat exchanger (HE) system. Frequency characteristics of sensitivity functions and open-loop and closed-loop time responses are simulated using MATLAB software and the stability of the system is analyzed using Kalman's test. The simulation results have demonstrated that the H-infinity controller is more efficient than PID in terms of robustness and performance.
Deep Learning for 3D Human Digitisation

In this Dissertation, the process of 3D Human Digitisation from single photographs using Deep Learning techniques is studied. A review of the related work in this ﬁeld is performed and an approach that improves the state of the art techniques is presented, obtaining a working pipeline that yields 3D models that can be directly animated and imported into video games, animations and other content creation projects.
The Effect of Twitter User’s Commenting Behavior on the Propagation of COVID-19 Misinformation

A BSTRACT We investigate how including comments when sharing (accountable or false) news on social media would affect its propagation on social media. When sharing external news, users may directly share without comment, copy-paste contents from the news, or posting their own opinions. We hypothesize posting comments would boost the chance of the post to propagate on social media. With a dataset of 170K COVID-19 news-sharing Tweets, we use regression models to test our hypothesis on sharing of news of different qualities. Our results show that the users’ commenting behavior when sharing external news on social media signiﬁcantly boost its propagation across both trustworthy and false news. The effect of such commenting behavior is much larger than any content factors such as emotions in the comments themselves. This ﬁnding calls for awareness on this factor before study the effect of contents in future studies on the propagation of misinformation.
Research on Nonlinear Identification Model of Wavelet Neural Network Trained by Artificial Fish Swarm Algorithm

To describe the complex nonlinear characteristics of a system accurately, a Wavelet Neural Network (WNN) identification model based on Artificial Fish Swarm (AFS) algorithm is proposed. In the identification model, AFS algorithm is introduced to optimize the parameters combination of the network for the satisfactory WNN model. The simulation shows that, the proposed method is a good nonlinear identification capability, and is feasible to identify the nonlinear system.
Impact of Physical Activity-Based Interventions on Children and Adolescents’ Physical Self-Concept: A Meta-Analysis

ABSTRACT Background: Observational studies associate physical activity (PA) with improved perceptions of children and adolescents’ physical self-concept (PSC) and global self-concept (GSC). However, only a few PA-based interventions exist for improving PSC and their results have been inconclusive. Objective: To determine the effect of specific PA-based programmes on the PSC (including its sub-dimensions) and GSC of children and adolescents, and to assess possible moderators. Methods: The databases Web of Science, Scopus, SportDiscus, PubMed, CINAHL, and Cochrane Library were reviewed in February 2020. Only studies with pre-post measurements and control groups were included. The impact of PA-based interventions was explored through different meta-analyses and moderator analyses. Results: Altogether, 20 studies were included in the meta-analysis. Positive and significant effects of PA were determined on self-perceived physical appearance (g = 0.13; 95% CI = 0.03, 0.23), self-perceived sport competence (g = 0.30; 95% CI = 0.09, 0.51), self-perceived physical fitness (g = 0.19; 95% CI = 0.05, 0.32), PSC (g = 0.31; 95% CI = 0.10, 0.52), and GSC (g = 0.17; 95% CI = 0.01, 0.33). The existence of additional interventions in PA-based programmes (e.g., interventions focused on psychological factors or healthy habits) moderated the influence of PA on self-perceived sport competence and physical fitness. Moreover, environment and time were distinguished as moderators for self-perceived physical appearance and sport competence. Further, intervention type, gender, and frequency of intervention moderated the effects of PA on PSC. Conclusions: PA-based interventions, especially in school, seem to be beneficial for the development of positive physical self-perceptions.
CLFormer: A Lightweight Transformer Based on Convolutional Embedding and Linear Self-Attention With Strong Robustness for Bearing Fault Diagnosis Under Limited Sample Conditions

As a rising star in the field of deep learning, the Transformers have achieved remarkable achievements in numerous tasks. Nonetheless, due to the safety considerations, complex environment, and limitation of deployment cost in actual industrial production, the algorithms used for fault diagnosis often face the three challenges of limited samples, noise interference, and lightweight, which is an impediment in the fault diagnosis practice of transformer with high requirements for number of samples and parameters. For this reason, this article proposes a lightweight transformer based on convolutional embedding and linear self-attention (LSA), called CLFormer. By modifying the embedding module and the form of self-attention, the aim of lightweight is realized (MFLOPs: 0.12; Params: 4.88 K) under the condition of boosting high-accuracy of transformer. The effectiveness was demonstrated on Self-Made dataset with four comparative models, especially when each type of training sample is $6\times 4$ , the CLFormer achieves the highest average accuracy of 83.58% when the signal-to-noise ratio (SNR) is from −8 to 8 dB for three types of noise. As the first attempt to use transformer for fault diagnosis of rotating machinery, this work provides a feasible strategy for the research topic of fault diagnosis with the goal of practical deployment.
Effects of a Shielding Skirt for Prevention of Sea Lice on the Flow Past Stocked Salmon Fish Cages

The effect of a shielding skirt, a tarpaulin mounted from the surface down to 5 meter depth around a net cage, on the flow pattern at a commercially stocked salmon cage was investigated. Dye was used as a tracer for water movement and the dye spreading was monitored using aerial images. Current meters were employed to investigate the flow close to the net inside and outside the cage. Tests were conducted with and without the shielding skirt. The focus was on the effectiveness of the shielding skirt to deflect water around the cage. This study shows that a shielding skirt can reduce horizontal flow components significantly inside a cage, which is related to a reduction of water exchange. The flow towards a cage is divided by a shielding skirt, i.e. some of the water is transported around the cage, while some is passing underneath the shielding skirt. Some water entering the fish cage from underneath the tarpaulin is transported towards the surface inside the cage. The use of a shielding skirt might not prevent interaction of the upper water layers inside and outside of a fish cage completely, but it has the potential to reduce the inflow of surface water into the cage, if deployed properly.Copyright © 2013 by ASME
Wireless Human Detection with Latitude and Longitude Values by RF Control Robot

In this paper we report on the outcomes of a research and demonstration project on human intrusion detection in a large secure space using a wireless sensor network. This project has been. (with expertise in areas such as sensors, circuits, computer systems, communication and networking, signal processing and security) to execute a large funded project that spanned three to four years. In this paper we report on the specific engineering solution that was developed: the various architectural choices and the associated specific designs. In addition to developing a demonstrable system, the various problems that arose have given rise to a large amount of basic research in areas such as geographical packet routing, distributed statistical detection, sensors and associated circuits, a low power adaptive micro-radio, and power optimizing embedded systems software. We provide an overview of the research results obtained.
yHydra: Deep Learning enables an Ultra Fast Open Search by Jointly Embedding MS/MS Spectra and Peptides of Mass Spectrometry-based Proteomics

Mass spectrometry-based proteomics allows to study all proteins of a sample on a molecular level. The ever increasing complexity and amount of proteomics MS-data requires powerful and yet efficient computational and statistical analysis. In particular, most recent bottom-up MS-based proteomics studies consider either a diverse pool of post-translational modifications, employ large databases – as in metaproteomics or proteogenomics, contain multiple isoforms of proteins, include unspecific cleavage sites or even combinations thereof and thus face a computationally challenging situation regarding protein identification. In order to cope with resulting large search spaces, we present a deep learning approach that jointly embeds MS/MS spectra and peptides into the same vector space such that embeddings can be compared easily and interchangeable by using euclidean distances. In contrast to existing spectrum embedding techniques, ours are learned jointly with their respective peptides and thus remain meaningful. By visualizing the learned manifold of both spectrum and peptide embeddings in correspondence to their physicochemical properties our approach becomes easily interpretable. At the same time, our joint embeddings blur the lines between spectra and protein sequences, providing a powerful framework for peptide identification. In particular, we build an open search, which allows to search multiple ten-thousands of spectra against millions of peptides within seconds. yHydra achieves identification rates that are compatible with MSFragger. Due to the open search, delta masses are assigned to each identification which allows to unrestrictedly characterize post-translational modifications. Meaningful joint embeddings allow for faster open searches and generally make downstream analysis efficient and convenient for example for integration with other omics types. Availability (under MIT license) https://github.com/tzom/yHydra Contact bernhard.renard@hpi.de
Covid Patient Health Monitoring Using IoT During Quarantine

The term “COVID” is breaking the hearts of the entire human community. The Corona virus is more infectious and is exceptionally irresistible, it is vital to isolate the patients and yet the specialists need to screen Corona virus patients as well. With the expanding increase in the number of Corona cases, the doctors find it difficult to keep track on the medical issue of isolated patients. To address this issue, we designed a distant IOT based screen framework, that considers observing of numerous Corona virus patients over the web. The system uses temperature sensor, respiratory sensor and pulse oximeter to measure the health parameters of the patients. If any oddity is detected in patient’s health, the patient presses the emergency help button which we installed in our system. This will alert the doctor and the care taker over IOT remotely. Our system thus provides a safe health monitoring design, in order to prevent the disease spreading through Corona virus and monitoring the individual health of each patient.
Answers and Questions: Forty Years in Bioelectromagnetics

The work began in 1972 when three young assistant professors used a slime mold to see if electromagnetic fields would affect it. The fields did, though the effects were small and hard to tease out of the noise. The cell cycle was lengthened and there were changes in respiration. So, the next question was “how and why? ” Further changes were seen using these and then other bacterial and eukaryotic cells in respiration, in ATP, in the protein replication chain, and so forth. Changes occurred even in cell extracts that lacked an intact plasma membrane. Nerve cells showed changes in leakage of neurotransmitters and in neurite outgrowth from excised ganglia. Based on some experiments with nerve cells, I also did some computer calculations, modeling the internal electric and magnetic fields and current densities in simplified representations of bone fractures and also of spinal cords in vertebrae. More recently, I have collaborated on some theoretical models of what fields might be doing at the cellular and molecular level, particularly with reference to the radical model. With each piece of research, my collaborators and I generally found a small piece of information about fields and biological systems; and each answer raised another set of questions, which is the way of science. Though bioelectromagnetic scientists have learned much and can say much at greater depth about what happens when an organism is exposed to a field, the fundamental question still remains: What exactly is going on here? © 2021 Bioelectromagnetics Society.
The Use of Fluorescent Anti-CEA Antibodies to Label, Resect and Treat Cancers: A Review

A major barrier to the diagnosis and effective treatment of solid-tumor cancers is the difficulty in detection and visualization of tumor margins in primary and metastatic disease. The use of fluorescence can augment the surgeon’s ability to detect cancer and aid in its resection. Several cancer types express carcinoembryonic antigen (CEA) including colorectal, pancreatic and gastric cancer. Antibodies to CEA have been developed and tagged with near-infrared fluorescent dyes. This review article surveyed the use of CEA antibodies conjugated to fluorescent probes for in vivo studies since 1990. PubMed and Google Scholar databases were queried, and 900 titles and abstracts were screened. Fifty-nine entries were identified as possibly meeting inclusion/exclusion criteria and were reviewed in full. Forty articles were included in the review and their citations were screened for additional entries. A total of 44 articles were included in the final review. The use of fluorescent anti-CEA antibodies has been shown to improve detection and resection of tumors in both murine models and clinically. The cumulative results indicate that fluorescent-conjugated anti-CEA antibodies have important potential to improve cancer diagnosis and surgery. In an emerging technology, anti-CEA fluorescent antibodies have also been successfully used for photoimmunotherapy treatment for cancer.
The Effect of Confinement Method and Specimen End Condition on Behavior of FRP-Confined Concrete under Concentric Compression

This paper presents an experimental investigation on the influence of confinement method and specimen end condition on axial compressive behavior of fiber reinforced polymer (FRP)-confined concrete. A total of 12 aramid FRP (AFRP)-confined concrete specimens with circular cross-sections were tested. Half of these specimens were manufactured as concrete-filled FRP tubes (CFFTs) and the remaining half were FRP-wrapped concrete cylinders. The effect of specimen end condition was examined on both CFFTs and FRP-wrapped specimens. This parameter was selected to study the influence of loading the FRP jacket on the axial compressive behavior. In this paper the experimentally recorded stress-strain relationships are presented graphically and key experimental outcomes discussed. The results indicate that the performance of FRP-wrapped specimens is similar to that of CFFT specimens and the influence of specimen end condition is negligible.
Addressing methodological issues in a study of impulsivity and vulnerability for transition to alcohol use disorder.

BACKGROUND Heightened behavioural impulsivity has been advocated as pre-existing risk factors for the development of alcohol use disorder (AUD). Nonetheless, studies investigating impulsivity in adolescent/young adult at-risk drinkers - who are at increased risk of developing AUD - report mixed findings. This may be due to methodological limitations related to definitions of at-risk drinking, the retrospective assessment of alcohol intake, and/or the relatively modest sample size of some studies. METHODS Healthy individuals (N = 814, Mag e = 22.50) completed online surveys and a measure of choice impulsivity. Of these, a number also undertook an online measure of response inhibition (n = 627, Mag e = 22.66), and a further subgroup submitted real-time alcohol consumption information for a period of 21 days using an app (n = 543, Mag e = 22.96). Differences in behavioural impulsivity were assessed as a function of various at-risk alcohol intake categories. Hierarchical multiple regression was employed to determine whether impulsivity predicted alcohol use in the form of a continuous index comprising variables related to intake and consequences of use. RESULTS Significantly greater impulsivity was not evident in heavy, standard binge, high binge, harmful, or hazardous alcohol drinkers as compared to controls, regardless of the criteria employed to categorise these at-risk drinkers. Neither choice impulsivity nor reduced response inhibition significantly predicted the alcohol use index. CONCLUSIONS While results could be attributed to the online nature of this research, it is possible more sensitive measures of behavioural impulsivity are required when assessing non-dependent drinkers.
A PERFORMANCEBOUND FOR MIMO-OFDMCHANNELESTIMATION AND PREDICTION

The performance of a mobile MIMO-OFDM system de­ pends on the ability of the system to accurately account for the effects of the frequency-selective time-varying channel at every symbol time and at every frequency subcarrier. In this paper, a vector formulation of the Cramer-Rao bound (CRB) for biased estimators and for functions of parame­ ters is used to find a lower bound on the estimation and prediction error of such a system. Numerical simulations demonstrate the benefits of multiple antennas for channel estimation and prediction and illustrate the impact of cali­ bration errors on estimation performance when using para­ metric channel models.