Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability and Order of Accuracy Analysis of High-Order Schemes Formulated Using the Flux Reconstruction Approach

A stability analysis is performed on high-order schemes formulated using the Flux Reconstruction (FR) approach. The one-dimensional advection model equation is used for the assessment of the stability region of these schemes when coupled with Runge-Kutta-type time-march procedures. Schemes are created using different numbers of internal points for each cell of the discrete domain, in such a way that a broad spectrum of spatial discretization orders can be analyzed. Multiple correction functions are employed so that well-known schemes, for instance the Discontinuous Galerkin (DG) and the Staggered-Grid schemes, may also be included in the study. The stability analysis is performed by identifying the behavior, in the complex plane, of the eigenvalues associated with each one of the considered cases. It is observed that, as the order of the scheme increases, a significant decrease in its domain of stability occurs, followed by a significant reduction in the amount of artificial dissipation that is introduced to the solution.
Analysis of a High-Dimensional Mathematical Model for Plant Virus Transmission with Continuous and Impulsive Roguing Control

Roguing and replanting are the most common strategies to control plant diseases and pests. How to build the mathematical models of plant virus transmission and consider the impact of roguing and replanting strategies on plant virus eradication is of great practical significance. In the present paper, we propose the mathematical models for plant virus transmission with continuous and impulsive roguing control. For the model with continuous control strategies, the threshold values for the existences and stabilities of multiple equilibria have been given, and the effect of roguing strategies on the threshold values is also addressed. Furthermore, the model with impulsive roguing control tactics is proposed, and the existence and stability of the plant-only and disease-free periodic solutions of the model are investigated by calculating several threshold values. Moreover, when selecting the design control strategy to minimize the threshold, we systematically analyze the existence of the optimal times of roguing infected plants within a replanting cycle, which is of great significance to the design and optimization of the prevention and control strategy of plant virus transmission. Finally, numerical investigations are given to reveal the main conclusions, and the biological implications of the main results are briefly discussed in the last section.
Longitudinal Changes in Temporospatial Gait Characteristics during the First Year Post-Stroke

Given the paucity of longitudinal data in gait recovery after stroke, we compared temporospatial gait characteristics of stroke patients during subacute (<2 months post-onset, T0) and at approximately 6 and 12 months post-onset (T1 and T2, respectively) and explored the relationship between gait characteristics at T0 and the changes in gait speed from T0 to T1. Forty-six participants were assessed at T0 and a subsample of twenty-four participants were assessed at T2. Outcome measures included Fugl-Meyer lower-extremity motor score, 14 temporospatial gait parameters, and symmetry indices of 5 step parameters. Except for step width, all temporospatial parameters improved from T0 to T1 (p ≤ 0.0001). Additionally, significant improvements in symmetry were found for the initial double-support time and single-support time (p ≤ 0.0001). As a group, no significant differences were found between T1 and T2 in any of the temporospatial measures. However, the individual analysis revealed that 42% (10/24) of the subsample showed a significant increase in gait speed (Welch’s t-test, p ≤ 0.002). Yet, only 5/24 (21%) of the participants improved speed from T1 to T2 according to speed-based minimum detectable change criteria. The increase in gait speed from T0 to T1 was negatively correlated with gait speed and stride length and positively correlated with the symmetry indices of stance and single-support times at T0 (p ≤ 0.002). Temporospatial gait parameters and stance time symmetry improved over the first 6 months after stroke with an apparent plateau thereafter. A greater increase in gait speed during the first 6 months post-stroke is associated with initially slower walking, shorter stride length, and more pronounced asymmetry in stance and single-support times. The improvement in lower-extremity motor function and bilateral improvements in step parameters collectively suggest that gait changes over the first 6 months after stroke are likely due to a combination of neurological recovery, compensatory strategies, and physical therapy received during that time.
Development of an integrated total quality management and performance measurement system for self-assessment: A method

Competitive environments and priorities change over time, effective enterprise management always depends on the effective measurement of performance and results. The first condition to establish and implement, and ultimately to achieve excellence, is a sound system for performance measurement (PM). Many organizations also adopt the total quality management (TQM) philosophies and continuous improvements in the pursuit of excellence. There is a need to foster TQM/PM integration with feasible means of self-assessment. This paper presents the key findings from an empirical study of TQM/PM integration (TPI) in Hong Kong. It discusses the essential ingredients and self-assessment criteria for building a TPI model. A results-oriented scoring method to facilitate TPI in public sector and government organizations is also described.
Identification of Metabolism-Related Genes Influencing Prognosis of Multiple Myeloma Patients

Multiple myeloma (MM) is the second most commonly diagnosed hematological malignancy. Understanding the basic mechanisms of the metabolism in MM may lead to new therapies that benefit patients. We collected the gene expression profile data of GSE39754 and performed differential analysis. Furthermore, identify the candidate genes that affect the prognosis of the differentially expressed genes (DEGs) related to the metabolism. Enrichment analysis is used to identify the biological effects of candidate genes. Perform coexpression analysis on the verified DEGs. In addition, the candidate genes are used to cluster MM into different subtypes through consistent clustering. Use LASSO regression analysis to identify key genes, and use Cox regression analysis to evaluate the prognostic effects of key genes. Evaluation of immune cell infiltration in MM is by CIBERSORT. We identified 2821 DEGs, of which 348 genes were metabolic-related prognostic genes and were considered candidate genes. Enrichment analysis revealed that the candidate genes are mainly related to the proteasome, purine metabolism, and cysteine and methionine metabolism signaling pathways. According to the consensus clustering method, we identified the two subtypes of group 1 and group 2 that affect the prognosis of MM patients. Using the LASSO model, we have identified 10 key genes. The prognosis of the high-risk group identified by Cox regression analysis is worse than that of the low-risk group. Among them, PKLR has a greater impact on the prognosis of MM, and the prognosis of MM patients is poor when the expression is high. In addition, the level of immune cell infiltration in the high-risk group is higher than that in the low-risk group. In the summary, metabolism-related genes significantly affect the prognosis of MM patients through the metabolic process of MM patients. PKLR may be a prognostic risk factor for MM patients.
Laplace transform of waveforms with hysteretic distortion

A brief account of the exponential model introduces the reader to one of the mathematical descriptions of the double non‐linearity of the hysteretic phenomena. The model described here satisfies the requirement for calculating the Laplace transforms in closed form for excitation waveforms constructed of straight lines. The method is demonstrated by applying it to a triangular excitation in the hysteretic process. It is shown that the Laplace transform of the induction waveform can also be calculated when the same excitation waveform is being applied in an anhysteretic process. It is also shown that when the excitation is small and falls within the limits of the Rayleigh region the calculation becomes simpler. This is demonstrated by formulating the Laplace transform of the induction waveform that resulted from triangular excitation in the Rayleigh region for both the hysteretic and anhysteretic cases.
STIFFENED, COUPLED SHEAR WALLS

The paper presents a general continuum analysis of a pair of laterally loaded, coupled shear walls, supported either on rigid or elastic foundations, with either one or two stiffening beams at arbitrary positions on the height. Numerical studies are used to investigate the influence of the rigidities and locations of the stiffening beams on the lateral deflections and internal forces in the structure. Numerical examples on representative structures show that, if the coupling beams are relatively flexible, the structural performance can be greatly improved by the addition of two stiffening beams, and the lateral deflections and lintel beam shears and moments can be significantly reduced. These and other study findings are discussed.
A compact Wilkinson power divider with curved PBG cells

An experimental investigation of a novel compact Wilkinson power divider incorporating a 1‐D PBG slow‐wave structure, in the form of perforation on the curved microstrip line itself, is presented. The size of the power divider is reduced by 22% due to the slow‐wave effect. The inclusion of the PBG cells does not generate additional insertion loss when compared to the conventional design. © 2001 John Wiley & Sons, Inc. Microwave Opt Technol Lett 31: 81–83, 2001.
Tracing the component unreliability contributions and recognizing the weak parts of a bulk power system

Individual components of a complex bulk power system (BPS) have different impacts on the overall system unreliability. It would be very useful to determine the contribution of each system component to the system unreliability, and recognize the weak parts (WP) within the system. This would provide a useful tool to direct remedial measures for improving the system reliability in BPS operation and planning processes. This paper presents an unreliability tracing (UT) technique for a BPS based on two UT principles, i.e., the failure component sharing principle (FCSP) and the proportional sharing principle (PSP). The technique is illustrated by application to the RBTS and the IEEE-RTS. The case studies indicate that the developed technique can distribute the system unreliability indices to components impartially and reasonably, and can therefore be used to recognize the WP of a BPS. Copyright © 2010 John Wiley & Sons, Ltd.
PROPOSAL OF USING A TIME CONSTANT FOR SPECIFYING ATRIUM SMOKE FILLING IN FIRE CODES

A time constant including building geometry and design fire characteristics was suggested for specifying smoke filling in atria. From the survey results on 138 local atria, time constants of 73 atria were calculated. The smoke filling times required to fill 80 % of the space volume were evaluated from the NFPA smoke filling equation with a slow t 2 -fire. The time for the smoke front to reach the ceiling was taken into account. It is further confirmed that time constant is a better parameter than the space volume used in the current fire codes, and is thus recommended to the Authority.
Examination of the Benefits of Enhancing Chip Seal Surface Treatments with Paving Fabric Interlayers

Paving fabric interlayers have been used in the United States (U.S.) to mitigate reflective cracking in hot mix asphalt (HMA) overlays for decades. Chip seal surface treatments (or simply chip seals) have been used to seal roads for over a century. Combining paving fabric interlayers with chip seals is a hybrid system that has been successfully used in the U.S. and elsewhere abroad for reflective cracking control and extending pavement’s service life for more than 25 years. Besides this application field, it has also been widely used in several other countries for reducing subgrade moisture content and stabilizing roadways built on expansive clay sub-grades. This paper will examine the exploding use of paving fabrics under chip seal systems in the U.S. through literature review, it will update the reader on the systems’ current use and it will pay some emphasis on using the system to stabilize roadways over expansive clay subgrades.
Beiwe: A data collection platform for high-throughput digital phenotyping

Beiwe is a high-throughput data collection platform for smartphone-based digital phenotyping. It has been in development and use since 2013. Beiwe consists of two native front-end applications: one for Android (written in Java and Kotlin) and one for iOS (written in Swift and Objective-C). The Beiwe back-end, which is based on Amazon Web Services (AWS), has been implemented primarily in Python 3.6, but it also makes use of Django for ORM and Flask for API and web servers. It uses several AWS services, such as S3 for flat file storage, EC2 virtual servers for data processing, Elastic Beanstalk for orchestration, and RDS for PostgreSQL database engine. Most smartphone applications use software development kits (SDKs) that generate unvalidated behavioral summary measures using closed proprietary algorithms. These applications do not meet the high standards of reproducible science, and often require researchers to modify their scientific questions based on what data happens to be available. In contrast, Beiwe collects raw sensor and phone use data, and its data collection parameters can be customized to address specific scientific questions of interest. Collection of raw data also improves reproducibility of studies and enables re-analyses of data and pooling of data across studies. Every aspect of Beiwe data collection is fully customizable, including which sensors to sample, how frequently to sample them, whether to add Gaussian noise to GPS location, whether to use Wi-Fi or cellular data for uploads, how frequently to upload data, specification of surveys and their response options, and skip logic. All study settings are captured in a JSON-formatted configuration file, which can be exported from and imported to Beiwe to enhance transparency and reproducibility of studies.
User Experience Evaluation in BCI: Filling the Gap

Brain-computer interface (BCI) systems can improve the user experience (UX) when used in entertainment technologies. Improved UX can enhance user acceptance, improve quality of life and also increase the system performance of a BCI system. Therefore, the evaluation of UX is essential in BCI research. However, BCI systems are generally evaluated according to the system aspect only so there is no methodology to evaluate UX in BCI systems. This paper gives an overview of such methods from the human-computer interaction field and discusses their possible uses in BCI research.
Wideband rhombic dielectric resonator antenna with CPW slot excitation for IEEE 802.11a/HiperLAN application

A wideband dielectric resonator antenna (DRA) using a CPW-fed inductive slot is proposed in this article. The DRA provides a simple design that exhibits a wide impedance bandwidth of about 26.8% (5.18–6.68 GHz). This is achieved by gradually rotating a square DRA by 45° to generate a rhombic DRA of dimensions 25 × 25 × 5 mm3. DRA structures with different rotation angles have also been studied to provide a comparative study into which orientation offers the best bandwidth. This structure results in the splitting up of the mode, and with suitable selection of the resonator dimensions, these modes can be brought close enough to yield wideband resonance characteristic. The proposed antenna has a realised gain of about 5.5 dBi over the entire band. The antenna covers the IEEE 802.11a, HiperLAN and UNII bands.
DARCLOS: a cloud shadow detection algorithm for TROPOMI

Abstract. Cloud shadows are observed by the TROPOMI satellite instrument as a result of its high spatial resolution as compared to its predecessor instruments. These shadows contaminate TROPOMI's air quality measurements, because shadows are generally not taken into account in the models that are used for aerosol and trace gas retrievals. If the shadows are to be removed from the data, or if shadows are to be studied, an automatic detection of the shadow pixels is needed. We present the Detection AlgoRithm for CLOud Shadows (DARCLOS) for TROPOMI, which is the first cloud shadow detection algorithm for a spaceborne spectrometer. DARCLOS raises potential cloud shadow flags (PCSFs), and actual cloud shadow flags (ACSFs). The PCSFs indicate the TROPOMI ground pixels that are potentially affected by cloud shadows based on a geometric consideration with safety margins. The ACSFs are a refinement of the PCSFs using spectral reflectance information of the PCSF pixels, and identify the TROPOMI ground pixels that are confidently affected by cloud shadows. We validate DARCLOS with true color images made by the VIIRS instrument on board of Suomi NPP orbiting in close constellation with TROPOMI on board of Sentinel 5-P. We conclude that the PCSF can be used to exclude cloud shadow contamination from TROPOMI data, while the ACSF can be used to select pixels for the scientific analysis of cloud shadow effects.
Smart Cluster Housing Monitoring with ESP32, ESP-Mesh and Django

The purpose of this study is to create a monitoring system for cluster housing. The method used in this research was experimental. Monitoring carried out in this system was installed and tested on ten houses. This system used an ESP-MESH for communication between ESP32 boards in residential areas. The process of sending data to the online server used two ESP32 boards that function as a mesh server and a gateway for data transmission. The data sent is in the form of data from ultrasonic sensors, PIR1 and PIR2 sensors, Flame sensors, Gas sensors, and Photos. The photo result was taking by ESP32CAM when the system detects an intruder. When something bad happens, such as fire detection, intruders, and gas leaks, residents will receive text and image notifications through the LINE application. The head of security will also get notifications via the web application. The web application is built using the Django framework. The results of this study are a monitoring system for cluster housing using ESP32, ESP-MESH, and Django. Based on the test results, this system has been running well by the initial objectives.
Collective Reactions to Epidemic Threat: Attachment and Cultural Orientations Predict Early COVID-19 Infection and Mortality Rates and Trajectories

Hypotheses on culture-level attachment and individualism/collectivism relationships with COVID-19 infection and death rates during a period at the beginning of the epidemic were tested in data from 53 countries and 50 U.S. states. Results from multilevel growth curve analyses showed group-average anxious attachment predicted a lower initial number of cases and deaths cross-culturally and in the United States, while avoidant attachment predicted a higher initial number of COVID-19 infections in the United States and a higher initial number of deaths in both studies. Yet, during this period, culture-level anxious attachment was associated with a higher growth rate of infections and deaths, while a lower growth rate of infections and deaths was observed in countries and U.S. states with higher individualism and avoidance. The research provides new insights into attachment and culture relationships and points to different mechanisms that may explain initial and growth rate trajectories at the beginning of the epidemic.
Electric vehicle load forecasting using data mining methods

The continuous growth and evolve of vehicle electrification causes the electric power systems to confront new challenges, since the load profile changes, and new parameters are being set. With the number of EVs gradually rising, problems may occur in technical characteristics of the network, like bus voltages and line congestion [1]. Therefore, it is necessary to develop EV management systems so as to prevent such phenomena. The effectiveness of such systems is heavily depended on the early knowledge of future demand. This knowledge can be provided by accurate EV load forecasting techniques. In this paper, the use of various data mining methods is examined and their performance in EV load forecasting is evaluated.
Unsupervised Approach for Autonomous Pavement-Defect Detection and Quantification Using an Inexpensive Depth Sensor

AbstractCurrent pavement condition–assessment procedures are extensively time consuming and laborious; in addition, these approaches pose safety threats to the personnel involved in the process. In this study, a RGB-D sensor is used to detect and quantify defects in pavements. This sensor system consists of a RGB color image, and an infrared projector and a camera that act as a depth sensor. An approach, which does not need any training, is proposed to interpret the data sensed by this inexpensive sensor. This system has the potential to be used for autonomous cost-effective assessment of road-surface conditions. Various road conditions including patching, cracks, and potholes are autonomously detected and, most importantly, quantified, using the proposed approach. Several field experiments have been carried out to evaluate the capabilities, as well as the limitations of the proposed system. The global positioning system information is incorporated with the proposed system to localize the detected defects.
The leading mode and factors for coherent variations among the sub-systems of tropical Asian summer monsoon onset

Previous studies on the Asian summer monsoon (ASM) onset mainly focused on each monsoon sub-system. Mainly based on the monthly mean rainfall and low-level winds in May, this study investigated the dominant onset mode from the perspective of the entire tropical ASM region, which reveals the coherent features among the regional-scale onsets. The results of multivariate empirical orthogonal function (MV-EOF) analysis indicate that the MV-EOF1 presents reduced rainfall and anomalous low-level easterly winds at 850 hPa over the tropical ASM region in May during its positive phase. The corresponding principal component (PC1) is highly correlated with the local monsoon onset dates over Arabian Sea, Bay of Bengal, Indo-China Peninsula, and South China Sea, where the mean monsoon onsets occur in May. The only exception is India subcontinent, where the mean monsoon onsets occur in June. The results indicate that the leading mode captures the synchronized variation of monsoon onset over most of Asian monsoon sub-systems, which exhibits remarkably interannual and interdecadal changes. The factors that modulate the coherent variation of the tropical ASM onset are further examined. The simultaneously delayed ASM onset tends to occur during the easterly phase of the 30- to 80-day oscillation, the decaying phase of El Niño, and the positive phase of Pacific Decadal Oscillation (PDO). The 30- to 80-day oscillation serves as a background condition for the synchronized delayed or advanced ASM onset. El Niño-related sea surface temperature anomalies modulate the tropical ASM onset mode by modulating the tropical Walker Circulation and inducing an atmospheric Rossby wave response. The PDO affects the tropical ASM onset mode mainly via the equatorial Rossby wave response and the extratropical Rossby wave train.