Miracle-dz/UniFAR-FTUs huggingface dataset:
An Interlaboratory Comparison of Thrust Measurements for a 200W Quad Confinement Thruster

We present an inter-laboratory comparison of the performance and plasma plume measurements of the 200W Quad Confinement Thruster (QCT-200) between the Surrey Space Centre (SSC) electric propulsion laboratory and the ESA Propulsion Laboratory (EPL) at ESA-ESTEC. The test campaign involves thrust balance measurements of the QCT-200 device over a range of operating conditions, and plasma plume measurements using Faraday probes. A matching set of test conditions following a common test procedure is conducted in both facilities and the results critically compared.
The Impact of the United State Presidential Election on Jakarta Islamic Index Stocks: Bid-ask Spread Perspective

: The political event which associated with the capital market is one of the interesting phenomena to be investigated. The aim of this study is to explore the impact of the United State Presidential Election against the liquidity of Jakarta Islamic Index. Bid-ask spread with Corwin and Shultz formulation was employed as liquidity proxy. This study conducted an event study and regression methodologies. The results of this study reported that after the event date experienced a higher bid-ask spread on the first and the second day than the previous event date. These findings imply that this event has information content.
Continuous Quality Improvement of Leadership Education Program Through PDCA Cycle

The reinforcement of quality assurance system in university education is in great demand. With the goal of quality assurance of a class curriculum, the plan-do-check-act (PDCA) cycle was applied on leadership education on graduate students of engineering, resulting in seven years of continuously improved quality of the education program in which students achieved their learning goals. At the end of the course, the authors analyzed the gap between the target and the progress made to date and reflected the next course design with the evaluation results for improvement. The traditional leadership education only gave students knowledge regarding leadership in the form of lectures. Therefore, how to apply this knowledge through students’ action has been a big issue for them. The leadership education program was introduced to improve leadership ability of students, which integrates knowledge, simulated experiences, and real actions. This leadership education program was conducted in the masters program at the Shibaura Institute of Technology’s Graduate School of Engineering and Science between 2008 and 2013. The diagnostic, formative, and overall evaluations were made to measure the extent to which students achieved their goals. With evaluation results of clarified learning outcomes, a PDCA cycle was repeated in order to improve quality of the education program in three stages. This research concludes that this cycle led to the achievement to produce effective leadership actions of students.
Longitudinal Analysis of Coronavirus-Neutralizing Activity in COVID-19 Patients

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic has now been continuing for more than two years. The infection causes COVID-19, a disease of the respiratory and cardiovascular system of variable severity. Here, the humoral immune response of 80 COVID-19 patients from the University Hospital Frankfurt/Main, Germany, was characterized longitudinally. The SARS-CoV-2 neutralization activity of serum waned over time. The neutralizing potential of serum directed towards the human alpha-coronavirus NL-63 (NL63) also waned, indicating that no cross-priming against alpha-coronaviruses occurred. A subset of the recovered patients (n = 13) was additionally vaccinated with the mRNA vaccine Comirnaty. Vaccination increased neutralization activity against SARS-CoV-2 wild-type (WT), Delta, and Omicron, although Omicron-specific neutralization was not detectable prior to vaccination. In addition, the vaccination induced neutralizing antibodies against the more distantly related SARS-CoV-1 but not against NL63. The results indicate that although SARS-CoV-2 humoral immune responses induced by infection wane, vaccination induces a broad neutralizing activity against multiple SARS-CoVs, but not to the common cold alpha-coronavirus NL63.
Computing Outside the Box: Average Consensus over Dynamic Networks

Networked systems of autonomous agents, and applications thereof, often rely on the control primitive of average consensus , where the agents are to compute the average of private initial values. To provide reliable services that are easy to deploy, average consensus should continue to operate when the network is subject to frequent and unpredictable change, and should mobilize few computational resources, so that deterministic, low powered, and anonymous agents can partake in the network. In this stringent adversarial context, we investigate the implementation of average consensus by distributed algorithms over networks with bidirectional, but potentially short-lived, communication links. Inspired by convex recurrence rules for multi-agent systems, and the Metropolis average consensus rule in particular, we design a deterministic distributed algorithm that achieves asymptotic average consensus, which we show to operate in polynomial time in a synchronous temporal model. The algorithm is easy to implement, has low space and computational complexity, and is fully distributed, requiring neither symmetry-breaking devices like unique identifiers, nor global control or knowledge of the network. In the fully decentralized model that we adopt, to our knowledge, no other distributed average consensus algorithm has a better temporal complexity. Our approach distinguishes itself from classical convex recurrence rules in that the agent’s values may sometimes leave their previous convex hull. As a consequence, our convergence bound requires a subtle analysis, despite the syntactic simplicity of our algorithm.
A high-performance generalized discontinuous PWM algorithm

In this paper, a generalized discontinuous pulsewidth modulation (GDPWM) method with superior high modulation operating range performance characteristics is developed. An algorithm which employs the conventional space-vector PWM method in the low modulation range, and the GDPWM method in the high modulation range, is established. As a result, the current waveform quality, switching losses, voltage linearity range, and the overmodulation region performance of a PWM voltage-source inverter (PWM-VSI) drive are optimized online, as opposed to conventional modulators with fixed characteristics. Due to its compactness, simplicity and superior performance, the algorithm is suitable for most high-performance PWM-VSI drive applications. This paper provides detailed performance analysis of the method and compares it to the other methods. The experimental results verify the superiority of this algorithm to the conventional PWM methods.
Intelligent Diagnosis Model of Traction Seat of Urban Rail Vehicle Based on Harris Hawks Optimization

Traction seat is an important connecting part of urban rail vehicle, which plays an important role in maintaining smooth running and power transmission of the vehicle body. Timely diagnosis of early failure of traction seat is the key to ensure the safe operation of urban rail vehicles. In order to realize the intelligent diagnosis of traction seat, a multialgorithm fusion scheme based on the Harris Hawk algorithm (HHO) is proposed to realize the fault diagnosis of traction seat. Firstly, the early mechanism of traction seat was studied, and the simulation experiment platform of urban rail vehicle traction seat was built to obtain the vibration data of the early crack traction seat model, so as to facilitate the simulation experiment research. Then, the vibration data of the traction seat were processed by HHO optimized variational mode decomposition (HVMD) to obtain several intrinsic mode functions (IMFs). Secondly, the multiscale permutation entropy (MPE) of each IMF is quantified and its average value is used to construct the energy characteristic vector. Finally, feature vectors are input into the HHO optimized support vector machine (HSVM) model to train a pattern recognizer. Through Python simulation verification, the results show that the model can accurately extract the characteristic information of traction seat and accurately identify the fault type, and the recognition rate reaches 100%.
Analysis of International Competitiveness of China’s Mobile Phone Industry Based on Data Mining Algorithm

In order to analyze the international competitiveness of China-made mobile phones, this paper combines data mining algorithms to analyze the international competitiveness of China’s mobile phone industry, improve the international market share of China-made mobile phones, and study the concept of multiattribute problems and related research methods. Moreover, the paper carries out the model description of the selected research methods combining principal component analysis, data envelopment analysis, and sorting method approaching the ideal solution. In addition, this paper expounds on the principles and models of PCA, DEA, and TOPSIS and selects an intelligent algorithm suitable for this model. Finally, this paper verifies the validity of the model proposed in this paper, conducts statistical analysis through the data mining model, evaluates the data mining effect through multiple simulation exercises, and verifies the validity of the system model.
THE EFFECT OF SPRAYING MAULI BANANA (Musa acuminata) STEM EXTRACT 25% CONCENTRATION ON THE DIMENSIONAL STABILITY OF ALGINATE IMPRESSION

Background: Alginate is an ingredient derived from brown seaweed extract which is anhydro-P-d-mannuronic acid. Alginate is often used as an impression material. A factor that must be considered when using impression materials is to prevent the infection. Prevention of infection transmission is done by administering disinfectants by spraying. However, this material has imbibition properties and expansion can occur in the model. 25% Mauli banana extract solution can be used as a disinfectant in alginate impressions and does not affect the dimensional stability of the alginate impressions. Objective: To analyze the effect of spraying mauli banana (Musa acuminata) stem extract 25% concentration on the dimensional stability of alginat impression. Methods: This research was pure experimental research using pretest-posttest and control group design. The research sample consisted of 15 samples that divided into 3 groups; aquades, 1% sodium hypochlorite, and 25% Mauli banana stem extract. The research data were analyzed using One Way Anova. Results: The average value calculation of the difference before and after spraying the aquades was 0.504 mm, the 1% sodium hypochlorite group was 0.502 mm and the 25% Mauli banana stem extract was 0.328 mm. Statistical tests showed no significant differences among all treatment groups on alginate dimensional stability or there was no effect on spraying 25% Mauli banana stem extract in the dimensional stability of alginate impression with sig. 0,401 (p > 0.05). Conclusion: There was no significant effect on spraying Mauli banana (Musa acuminata) stem extract 25% on the dimensional stability of the alginate impression.
The Impacts of Housing Characteristics and Built-Environment Features on Mental Health

In this study, we examined the relationships between housing characteristics, neighborhood built-environment features, and people’s mental health in Hong Kong, an Asian city well known for its high-density and high-rise housing. The potential mediating effects of people’s perceived living environment were also considered in the analysis. We collected data from 221 participants from two communities in Hong Kong, i.e., Sham Shui Po (SSP) and Tin Shui Wai (TSW), using a stratified random sampling approach. Big datasets were also used to derive relevant built-environment features at the street block level. We used structural equation modeling to explore the complex relationships among housing characteristics, built-environment features, and mental health. The results indicate that the associations between built-environment quality and people’s mental health are weak. For communities with relatively poor housing conditions (i.e., SSP in this study), the impact of housing characteristics on mental health may be more direct; for communities with relatively good housing conditions (i.e., TSW in this study), the effect of housing characteristics on mental health may be indirect. Our findings shed light on the importance of considering different contexts in developing policies related to housing and built environment and mental health.
Structural and Pharmacological Network Analysis of miRNAs Involved in Acute Ischemic Stroke: A Systematic Review

Acute ischemic stroke (AIS) is among the main causes of mortality worldwide. A rapid and opportune diagnosis is crucial to improve a patient’s outcomes; despite the current advanced image technologies for diagnosis, their implementation is challenging. MicroRNAs have been recognized as useful as biomarkers since they are specific and stable for characterization of AIS. However, there is still a lack of consensus over the primary miRNAs implicated in AIS. Here, we performed a systematic review of the literature covering from 2015–2021 regarding miRNAs expression during AIS and built structural networks to analyze and identify the most common miRNAs expressed during AIS and shared pathways, genes, and compounds that seem to influence their expression. We identified two sets of miRNAs: on one side, a set that was independent of geographical location and tissue (miR-124, miR-107, miR-221, miR-223, miR-140, miR-151a, miR-181a, miR-320b, and miR-484); and on the other side, a set that was connected (hubs) in biological networks (miR-27b-3p, miR-26b-5p, miR-124-3p, miR-570-3p, miR-19a-3p, miR-101-3p and miR-25-3p), which altered FOXO3, FOXO4, and EP300 genes. Interestingly, such genes are involved in cell death, FOXO-mediated transcription, and brain-derived neurotrophic factor signaling pathways. Finally, our pharmacological network analysis depicted a set of toxicants and drugs related to AIS for the first time.
Rank-order statistics for validating discriminative power of credit risk models

This paper provides practical insights into common statistical measures used to validate a model’s discriminatory power for the probability of default (PD), loss liven default (LGD) and exposure at default (EAD). The review of available rank-order statistics is not based on analysing empirical data. Thus, the study has more of an informative value without delivering empirical evidence. When there is an alternative model available for comparison, this paper proposes to use the cumulative accuracy curve and the accuracy ratio to assess the rank-order ability for PD models given their popularity in practice. When there is no model available for comparison, due to the limited techniques in this area, this paper proposes to compare the confidence intervals in order to prove that a rating system has any discriminative power. For the LGD/EAD/slotting models, this paper recommends using a graph to check the rank-order ability. No statistical test is recommended. Focusing on enhancing practical implications for the financial industry, this paper advises banks on the existing CRR self-attestation requirements.
Effects of Changes in Osmolarity on the Biological Activity of Human Normal Nucleus Pulposus Mesenchymal Stem Cells

The expansion and maintenance of the NPMSC (nucleus pulposus mesenchymal stem cell) phenotype are considered as potential therapeutic tools for clinical applications in intervertebral disc tissue engineering and regenerative medicine. However, the harsh microenvironment within the intervertebral disc is the main limitation of its regeneration. The osmolarity of the intervertebral disc is higher than that of other tissues, which has an important influence on the biological characteristics of NPMSCs. In this study, we observed the effect of different osmolarities on the biological characteristics of human normal NPMSCs cultured in vitro and explored the role of osmolarity in intervertebral disc degeneration. Our data demonstrated that the change in osmotic pressure has an important effect on the biological activity of NPMSCs, and this effect may occur through the P16INK4A/Rb pathway. This study provides a theoretical basis for the future treatment of intervertebral disc degeneration.
Plasmonic Azobenzene Chemoreporter for Surface-Enhanced Raman Scattering Detection of Biothiols

Low molecular weight thiols (biothiols) are highly active compounds extensively involved in human physiology. Their abnormal levels have been associated with multiple diseases. In recent years, major efforts have been devoted to developing new nanosensing methods for the low cost and fast quantification of this class of analytes in minimally pre-treated samples. Herein, we present a novel strategy for engineering a highly efficient surface-enhanced Raman scattering (SERS) spectroscopy platform for the dynamic sensing of biothiols. Colloidally stable silver nanoparticles clusters equipped with a specifically designed azobenzene derivative (AzoProbe) were generated as highly SERS active substrates. In the presence of small biothiols (e.g., glutathione, GSH), breakage of the AzoProbe diazo bond causes drastic spectral changes that can be quantitatively correlated with the biothiol content with a limit of detection of ca. 5 nM for GSH. An identical response was observed for other low molecular weight thiols, while larger macromolecules with free thiol groups (e.g., bovine serum albumin) do not produce distinguishable spectral alterations. This indicates the suitability of the SERS sensing platform for the selective quantification of small biothiols.
Comparative Advantage of the United States and South Korean Manmade Textile Industries

This study examined the comparative advantage of manmade textile (MMT) industries in the United States (US) and South Korea (SK). The Revealed Comparative Advantage (RCA) framework was used to assess the MMT industries’ performance in both countries from 2004 to 2013. With the recent ratification of the United States-South Korea Free Trade Agreement (KORUS FTA), it is important to understand the current state of these industries. Using UN Comtrade export data, the RCA index values were calculated and analyzed for 27 MMT commodities, three aggregate groups, and the whole industry. It was found that SK had a consistent comparative advantage for the whole industry. Furthermore, SK had a larger number of products with a comparative advantage. The research findings indicate that the MMT industry in SK is likely to outperform the US following the complete ratification of the KORUS FTA.
Data-driven dynamic robust resource allocation: Application to efficient transportation

 Develop the foundations for the science of cyber-physical systems (CPS) and intelligent autonomous systems in smart cities, to assure safety, efficiency and security for application areas such as transportation, healthcare and network systems.  Relevant fields: control theory, optimization, machine learning, statistics, game theory, and robotics.  Current ongoing research topics: ontology representations for assuring safety of perception, learning and control of connected autonomous vehicles; learning and control based on heterogeneous data in the Internet of Things level; T-SET UTC research on technologies for safe and efficient transportation  Research contributions: data-driven real-time robust resource allocation with application in smart cities, especially in ride-sharing of intelligent transportation systems; secure control and attack detection of CPS for DARPA HACMS project; wireless sensor and control networks.
Intracavity interferometry using synchronously pumped OPO

The concept of system for intracavity interferometry based on the beat note detection in subharmonic synchronously intracavity pumped optical parametrical oscillator (OPO) is presented. The system consisted of SESAM-modelocked, picosecond, diode pumped Nd:YVO4 laser, operating at wavelength 1.06 μm and tunable linear intracavity pumped OPO based on MgO:PPLN crystal, widely tunable in 1.5 μm able to deliver two independent trains of picosecond pulses. The optical length of the OPO cavity was set to be exactly twice the pumping cavity length. In this configuration the OPO produces signal pulses with the same repetition frequency as the pump laser but the signal consists of two completely independent pulse trains. For purpose of pump probe measurements the setup signal with half repetition rate and scalable amplitude was derived from the OPO signal using RF signal divider, electropotical modulator and fiber amplifier. The impact of one pump beam on the sample is detected by one probing OPO train, the other OPO train is used as a reference. The beat note measured using the intracavity interferometer is proportional to phase modulation caused by the pump beam. The bandwidth of observed beat-note was less than 1 Hz (FWHM), it corresponds to a phase shift measurement error of less than 1.5 × 10-7 rad without any active stabilization. Such compact low-cost system could be used for ultra-sensitive phase-difference measurements (e.g. nonlinear refractive index measurement) for wide range of material especially in spectral range important for telecom applications.
Vibration-Based Damage Detection for a Population of Like Structures via a Multiple Model Framework

This study focuses on the problem of vibration-based damage detection for a population of like structures. Although nominally identical, like structures exhibit variability in their characteristics due to variability in the materials and manufacturing. This inevitably leads to variability in the dynamics, which may be so significant as to mask deviations due to damage. Damage detection, conventionally employing a single nominal (baseline) model for the population, thus becomes challenging, with available methods exhibiting inadequate performance. The use of a new, Multiple Model (MM) framework, is presently explored for the potential alleviation of the problem. Within it, four response-only methods are considered and exhaustively tested via a population of laboratory-scale like composite beams and delamination type damage. The results illustrate the improvement in performance attained within the postulated framework, with one parametric method achieving impressive performance characteristics. The general conclusion is that the MM framework offers some new and exciting possibilities for effectively tackling the problem of damage detection for a population of like structures.