Miracle-dz/UniFAR-FTUs huggingface dataset:
Best Practices and Guidelines (2022) for Scale-Up and Tech Transfer in Freeze-Drying Based on Case Studies. Part 1: Challenges during Scale Up and Transfer

The freeze-drying process scale-up and transfer remain a complicated and non-uniform practice. We summarized inefficient and good practices in these papers and provided some practical advice. It was demonstrated that using the same process set points/times in laboratory and commercial scale dryers may lead to loss of product quality (collapse or vial breakage). The emerging modeling approach demonstrated practical advantages. However, the upfront generation of some input parameters (vial heat transfer coefficient, minimum controllable pressure, and maximum sublimation rate) is essential for model utilization. While the primary drying step can be transferred with a high degree of confidence (e.g., using modeling), and secondary drying is usually fairly straightforward, predicting potential changes in product behavior during freezing remains challenging.
An optical spacer is no panacea for light collection in organic solar cells

The role of an optical spacer layer has been examined by optical simulations of organic solar cells with various bandgaps. The simulations have been performed with the transfer matrix method and the finite element method. The results show that no beneficial effect can be expected by adding an optical spacer to a solar cell with an already optimized active layer thickness.
Supercapacitor and Bidirectional DC-DC Converter-based Active Charge Balancing Scheme for Lithium-ion Batteries

The stored charge inside the series-connected lithium-ion battery cells within a battery pack must need to be well equalized for optimum capacity utilization, operational safety, and a longer lifecycle. This paper proposed an innovative supercapacitor and bidirectional DC-DC converter-based cell-to-pack-to-cell (C2P2C) active charge balancing scheme where a supercapacitor is used as a temporary energy tank while shuttling the balancing energy. The bidirectional DC-DC converter works in buck/boost mode to control the charging/discharging of the supercapacitor alongside modulating the balancing parameters to accomplish cell-pack and pack-cell balancing simultaneously during the charging and discharging period respectively. Laboratory test data is used for battery modeling and simulation studies are conducted in MATLAB-Simscape to verify the effectiveness of the proposed scheme. The most innovative and attractive aspects of the proposed scheme are its high balancing speed, reduced component requirement, and robustness compared to similar topologies in its class. A comparative study with state-of-the-art coupled inductor-based topology is also demonstrated to support the claim.
Read the Debug Manual: A Debugging Manual for CS1 Students

Debugging manuals help programmers develop strategies to reduce program issues. These manuals assume the reader has prior programming knowledge to comprehend the presented strategies. While this assumed knowledge is above Introductory Programming (CS1) students’ programming abilities, it does illustrate a variety of strategies they can use during the debugging process to help them realise different approaches that are available to successfully debug a problem. In this research paper, we present a debugging manual, Read the Debugging Manual (RTDM), that is designed for CS1 students. The manual presents a variety of strategies that can be applied across the debugging process without assumed prior programming knowledge. A pilot study was conducted to evaluate the manual, where CS1 students were provided the manual as a debugging intervention for a programming activity. Students were invited to share their experiences and feedback on the manual by participating in a survey. The results show students wanting worked examples in the manual to practice strategies. Providing students with the manual seems to be supporting Self-Regulated Learning (SRL) strategies, helping students recall existing strategies and introducing them to new ones. The paper concludes with future research opportunities to improve the manual.
Improving Visual Inertial Odometry with UWB Positioning for UAV Indoor Navigation

This paper presents a method to improve the localization accuracy for visual inertial odometry (VIO) by combining the ultra-wideband (UWB) positioning technology. The overall architecture is mainly divided into two stages. In the first stage, the constraint on UWB short-term position change is adopted to improve the pose estimation results of the VIO system. It is also used to solve the translation error caused by the lack of visual features and vibration during the flight. In the second stage, a loose coupling method based on nonlinear optimization is utilized to fuse the local pose estimator of the VIO system with the global constraints from the UWB positioning. At the beginning of each optimization, the alignment between the VIO and UWB frames is estimated to avoid the influence of the coordinate transformation caused by the cumulative error of the VIO system. Since there are no public datasets available for comparison, we have established several datasets containing large vibration amplitudes and weak feature points. In the experiment, the performance evaluation of the proposed technique is carried out using the Apriltag approach for verification.
Energetics, structure, and long-range interaction of vacancy-type defects in carbon nanotubes: Atomistic simulations

The presence of vacancy clusters in carbon nanotubes has been assumed to explain the formation of carbon peapods and the difference between the experimentally measured and theoretical fracture strength of nanotubes. We use atomistic simulations at various levels of theory to study the characteristics of large vacancies formed by up to six missing atoms. We show that the formation of big ``holes'' on nanotube walls is energetically unfavorable as the vacancies tend to split into smaller defects due to the reconstruction of the nanotube atomic network. We also demonstrate that there is a weak but long-ranged interaction between the vacancies not only through strain fields but, surprisingly, also due to electronic effects, similar to those of adatoms on metal surfaces.
Design an Assessment for an Introductory Computer Science Course: A Systematic Literature Review

This Research Full Paper presents a literature review on introductory CS assessments. As Computer Science (CS) becomes increasingly popular in the world of big data, more college students are taking introductory CS courses to follow the trend. However, students have different levels of exposure to CS when they start CS in college, varying from no experience to years of coding experience. This disparity in the amount of exposure can pose many problems. In the same intro-level class, some students may think they do not learn anything new, while others believe the professor goes through concepts so fast that they cannot follow the pace. CS professors may also feel confused about how to control the pace and content of introductory courses. Therefore, CS departments need an assessment to measure students’ CS knowledge and then assign them to the appropriate CS introductory courses. Though a vast number of research papers discuss CS introductory courses, few of them focus on developing and validating assessments that evaluate students’ background knowledge (i.e., concept inventory). This paper aims to conduct a systematic literature review to gain an overview of the most important introductory CS contents that need to be assessed, the methods to evaluate students’ understanding of introductory CS concepts, and some existing assessments/concept inventories. By reviewing relevant papers over the last 15 years, we selected 48 papers that are related to assessments and corresponding introductory courses. We collected assessment information and made tables of contents, question types, programming languages, and origins to analyze data. We found that iterations, conditionals, and variables are the most popular assessment contents. Multiple-Choice and Code Writing questions, which are more popular than Code Explaining questions, are the preferred ways of assessing students’ knowledge. Scratch is commonly used as a CS0 assessment language, while Python, Java, C, and Pseudo-codes are employed in CS1 assessments. FCS1, SCS1, and BDSI are existing assessments/concept inventories for CS1 or CS2, but there is not yet a validated assessment or concept inventory that encompasses introductory concepts of CS0 (computational thinking), CS1 (fundamentals), and CS2 (data structure). Designing a comprehensive CS0/CS1/CS2 assessment by using the information collected from our systematic literature review would help students choose the right course and benefit educators and researchers for general use.
Unipolar and Bipolar Pulsed Gate Stresses and Threshold Voltage Shifts in GaN e-HEMTs

In GaN e-HEMTs, Threshold Voltage <tex>$(\boldsymbol{V}_{TH})$</tex> shift from gate voltage <tex>$(\boldsymbol{V}_{GS})$</tex> stress depends on the <tex>$\boldsymbol{V}_{Gs}$</tex> magnitude, stress time, recovery time (time between stress removal and <tex>$\boldsymbol{V}_{TH}$</tex> measurement), temperature and pulse polarity (0 to <tex>$+\boldsymbol{V}_{GS}$</tex> or <tex>$-\boldsymbol{V}_{GS}$</tex> to <tex>$+\boldsymbol{V}_{GS}$</tex>). In this paper, unipolar (0 to <tex>$\boldsymbol{V}_{GS})$</tex> and bipolar <tex>$(-\boldsymbol{V}_{GS}$</tex> to <tex>$+\boldsymbol{V}_{GS})$</tex> pulsed gate stresses have been performed on GaN e-HEMTs with different <tex>$\boldsymbol{V}_{GS}$</tex> magnitudes. The pulse frequency ranges from 25 Hz to 200 kHz. The results show negative <tex>$\boldsymbol{V}_{TH}$</tex> shifts for unipolar <tex>$\boldsymbol{V}_{GS}$</tex> pulses (between 5V and 8V) at long recovery times (above 500 seconds). The <tex>$\boldsymbol{V}_{TH}$</tex> shift is proportional to the <tex>$\boldsymbol{V}_{GS}$</tex> pulse magnitude. When the recovery time is increased from 50 milliseconds to 500 seconds, the measured <tex>$\boldsymbol{V}_{TH}$</tex> shift becomes more negative, indicating a faster release of trapped electrons than holes. In bipolar stresses, results show both positive and negative <tex>$\boldsymbol{V}_{TH}$</tex> shifts with no clear magnitude or frequency dependencies.
Comparison of Parameter Optimizers on COVID-19 Detection From A New Lung CT Scan Dataset

The aim of this study is to determine the success of different parameter optimization methods in a classification done by using a new Convolutional Neural network (CNN) proposed in this study on a new original dataset consisting of lung CT images collected by the researchers from ill/healthy people in order to diagnose COVID-19. To achieve this purpose, the researcher prepared a new data set involving computerized tomography images collected from Erzurum City Hospital Emergency Department for the diagnosis of COVID-19 after the necessary permissions were taken. This new data set consists of 1081 lung CT images, 568 of which belong to 313 people infected with COVID-19. The results obtained for the proposed CNN model through different optimization methods were compared. Precision, recall and f1-score parameters were used while evaluating the results. In our dataset, the highest performance values for the proposed CNN model were achieved by AdaMax optimizer as follows: %89.86 accuracy, %86.51, precision, %95.61 recall and %87.33 f1-score. The classification accuracy values achieved by other optimizers were %89.40 (RMSProp), %87.10 (Adam), %81.11 (SGD).
Unit commitment and hydrothermal generation scheduling by multi‐pass dynamic programming

Abstract This paper applies a very efficient new technique, multi‐pass dynamic programming (MPDP) combined with successive approximations, to solve the weekly thermal unit commitment and hydrothermal generation scheduling problem. Conceptually, dynamic programming is suited for solving this problem, but the long computing time and the large storage memory required become unacceptable for large power systems and long scheduling periods. The MPDP technique can overcome these difficulties. Furthermore, the unit start‐up cost and pumped storage plants are considered in the hydrothermal coordination instead of only the production cost as in the previous application. The algorithm is tested on Taipower system with forty thermal units, seven conventional hydro units and one pumped storage plant. The results show that this method is suitable for practical systems.
STGCN-Based Capacity Estimation of Regional Interruptible Loads with Privacy Preservation

A sound understanding of the regional interruptible loads plays an important role in the demand-side management, which can accelerate the progress of the carbon neutrality. However, the massive work of door-to-door data collecting and the consumers' privacy protection has restricted the application of the interruptible loads. In view of the similar data structure and the superiority of the graph neural network (GCN), this work applies a semi-supervised inductive learning strategy on a spatial-temporal graph neural network (STGCN) to obtain the power consumption regarding interruptible loads of those who does not provide any indoor data from users who are willing to provide all the indoor power consumption data. The nodes connection in the graph is determined by the similarity of the total power usage pattern. Then the total power consumption is fed into STGCN as the input features. After the semi-supervised inductive learning, the model can calculate the interruptible loads power consumption of the desired house. The proposed methodology is validated on the real-world dataset. Different number settings of the labeled and unlabeled nodes are tested to find out the best combination. At last, suggestion is provided for the power utility according to the numerical results of the experiments.
EMG-based Human-in-the-loop Optimization of Ankle Plantar-flexion Assistance with a Soft Exoskeleton

Individualized control strategies were considered as an alternative approach for wearable robotic devices to increase the capability of walking economy. Human-in-the-loop (HIL) optimization can identify appropriate assistive control parameters for specific users based on real-time measurement of human physiological objectives. Recent studies on HIL optimization use metabolic cost as the physiological objective to adjust the control parameters. However, the long measurement times and low signal-to-noise ratio presented significant challenges for the wearable experiments. We presented an EMG-based HIL optimization method with a soft exoskeleton to rapidly and automatically generate customized control parameters for ankle plantar-flexion assistance. Experimental results demonstrated that this method can identify nearly optimal control parameters within a certain parameter space for specific subject in 7.5 minutes. When comparing the assistive condition that exoskeleton provided assistance with optimized control parameters to the assistive conditions that the exoskeleton provided assistance with initial control parameters and the exoskeleton unpowered, the soleus muscle activity was reduced by 11.5% (p < 0.001) and 17.6% (p < 0.001), respectively. Our results demonstrated that the EMG-based HIL optimization can be a promising approach to rapidly improve the assistive performance for exoskeletons.
Extended Kalman Filter Design for State-of-Charge Estimation of a Lithium-Titanate Battery Cell

This paper presents the design of an extended Kalman filter (EKF) as a state-of-charge (SoC) estimator for a lithium–titanate (LTO) battery cell. The design is based on a Thevenin model of the equivalent battery electrical circuit with two parallel resistive-capacitive (RC) elements for the emulation of electrolyte polarization effects. The effectiveness of the proposed SoC estimator is verified through computer simulations on the comprehensive nonlinear battery simulation model featuring battery parameter vs. SoC variations, which is subject to highly dynamic loading regimes.
Grid Synchronization Techniques Analysis of DG Systems Under Grid Fault Conditions

The integration of renewable energy sources (RES) and their connection to actual transmission power grids around the world at a range of voltage levels has recently gained a significant penetration level. The changes brought by these alternative power sources have an important impact on system performance and efficiency in terms of the quality and the stability of the existing grid, which is not yet dedicated to meet the modern grid code requirements. One of these vital requirements is synchronization with the grid voltage which is achieved by the synchronization unit of the grid side converter (GSC) controller. The synchronization unit usually consists of a phase-locked loop (PLL) algorithm to track the phase angle and amplitude of the grid voltage at the point of common coupling (PCC). This paper analyzes respectively the synchronization capability of four PLL techniques for distributed generation system (DGS) during balanced and unbalanced faults: the synchronous reference frame PLL (SRF-PLL), stationary reference frame PLL (αβ-PLL), decoupled synchronous reference frame PLL (DSRF-PLL), and the recent decoupled stationary reference frame PLL (Dαβ-PLL). The different considered algorithms are presented, analyzed, compared, and their performance is simulated and carried out using MATLAB/SIMULINK.
Increasing workspace and trajectory planning of the parallel robot PAR4

In this paper, increasing workspace and trajectory planning of the parallel robot PAR4 are presented. First, the tracing of workspace is achieved by the inverse kinematic model, then increasing workspace is determined using the method optimization of parameters by the algorithm Simulated Annealing greatly improve the work volume of the parallel robot. Second, the planning trajectory of the robot PAR4 is determined due to the method S-curve and, optimization of the trajectory. Numerical results are presented showing increasing workspace and optimization of the trajectory.
A Framework for teaching programming in High School through Educational Robotics

This Research-to-Practice Full Paper aims to introduce a methodological framework to foster Computational Thinking (CT) skills by teaching programming with Educational Robotics (ER) in High School. Problem-solving is an essential skill for human development, so it is necessary to introduce actions to improve this skill in High School. It is possible to stimulate problem- solving through computer programming teaching with ER. However, as far as we know, there are no methodologies for teaching programming with ER focusing on CT development in High School that went through scientific validation of the proposal. This study is an Educational Design Research that aims to introduce a methodological framework for teaching programming in High School with ER (named CTProgER) and validate two instances of the framework. It was considered consolidated teaching methodologies with ER, combined with the Anthropological Theory of Didactics and evidence from our ER studies. As a result, we present the CTProgER Framework guideline, two instances of the CTProgER Framework, and these instances’ validation through the Delphi method.
Analysis on Voltage to Ground of Submodules for MMC Under NLM and CPS-PWM

Modular multilevel converter (MMC) usually consists of many submodules (SMs). During the commutation transient, the voltage to ground of SM jumps, and high $\mathrm{d}v/\mathrm{d}t$ causes common-mode (CM) current to flow into the ground through parasitic capacitors, resulting in severe conducted EMI. In this paper, the rules of voltage to ground of SMs at different positions are derived under Nearest Level Modulation (NLM) and Carrier Phase-Shift Pulse Width Modulation (CPS-PWM) and further analyze the voltage jump rules. The EMI sources under two different modulation strategies are analyzed by comparing the equivalent number of voltage jump in a fundamental period. Finally, the simulation results illustrate the validity of the analysis.
Novel Passive Electrodynamic Magnetic Bearings

Passive electrodynamic magnetic bearings (EDBs), which are categorized as magnetic bearings, are electromagnetic devices that offer contact and lubrication free bearing operation. Research into magnetic bearings stems from the need for high speed reliable operation. Different types of magnetic bearings such as active magnetic bearings (AMB) and passive magnetic bearings (PMB) have been proposed and investigated, despite the increased cost and complexities, associated with active control of AMBs, they are now employed in industrial applications. However, none electrodynamic PMBs are inherently unstable, and they can only be used in tandem with conventional mechanical bearings. On the other hand, EDBs eliminate the complexities and costs associated with control systems, however, the lack of in-depth understanding of their performance and design procedures, relatively lower stiffness and stability issues at lower speeds, have limited their application potential. In the paper, a novel homopolar EDB topology is proposed, and are analyzed using 3D-FEA. The performance in terms of restoring force, stability and eddy current losses are presented and compared. It is shown that the proposed EDB topology exhibits more than double the restoring force density, of the EDB topologies presented in the literature.
Feature Extraction of Ultrasonic Monitoring during Lithium-ion Battery Cycling

Ultrasonic monitoring is a promising method for state estimation and aging characterization in the battery field. Three feature extraction methods focusing on different ultrasonic wave parts during battery cycling are proposed, and each of which has a strong linear correlation with the state of charge. The Principal Components Analysis, which utilizes the entire ultrasonic wave including oscillatory wave and "first echo", extracts the best performing features, improves the resolution of ultrasonic monitoring in the state of charge estimation, and demonstrates the powerful capabilities of ultrasonic monitoring in battery management applications.