Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Suitable Control Methods for Full Vehicle with Four MR Dampers Part II Controller Synthesis and Road Test Validation

The significant non-linearity and uncertainty in the behavior of magnetorheological (MR) suspension systems has been one of the main challenges in the application of this technology in the development of appropriate control algorithms. Here, four model-free control algorithms studied theoretically in prior work are applied to a full vehicle featuring four MR dampers and evaluated through road test to identify the most suitable control algorithm. The four model-free control algorithms include the well-known skyhook control, the hybrid control, the fuzzy logic control, and a newly proposed intelligent control algorithm, the human simulated intelligent control (HSIC). As the first step, four MR dampers (two for the front parts and two for the rear parts) are designed and manufactured based on the damping-force levels and mechanical dimensions of stock dampers of the test vehicle. After experimentally measuring the magnetic-field-dependent force property and controllability, a precise inverse model of MR damp.
Single-stage three-phase buck-boost type AC-DC converter with high power factor

A new control process for single-stage three-phase buck-boost type AC-DC power converters with high power factor, sinusoidal input currents and adjustable output voltage is proposed. This converter allows variable power factor operation, but this work focus on achieving unity power factor. The proposed control method includes a fast and robust input current controller based on a vectorial sliding mode approach. The active nonlinear control strategy applied to this power converter, allows high quality input currents. Given the comparatively slow dynamics of the DC output voltage, a proportional integral (PI) controller is adopted to regulate the converter output voltage. The voltage controller modulates the amplitudes of the current references, which are sinusoidal and synchronous with the input source voltages. Experimental results from a laboratory prototype show the high power factor and the low harmonic distortion characteristics of the circuit.
Providing diabetes education to patients with chronic kidney disease: A survey of diabetes educators in Ontario, Canada

Background Patients with diabetes and chronic kidney disease (CKD) have complex diabetes care needs. Diabetes educators can play an important role in their clinical care. Aim To understand diabetes educators’ experience providing diabetes support to patients with CKD and elicit their view on the additional care needs of this population. Methods We conducted a quantitative online survey of diabetes educators between May 2019 and May 2020. We surveyed English-speaking educators actively practicing in Ontario, Canada for at least 1 year. We recruited them through provincial Diabetes Education Programs and Diabetes Education Section Chairs of Diabetes Canada. Results We made email contact with 219/233 (94%) Diabetes Education Programs and 11/12 (92%) provincial Diabetes Canada Section Chairs. 122 unique diabetes educators submitted complete surveys (survey participation rate ∼79%). Most worked in community education programs (91%). Almost half were registered nurses (48%), and 39% had practiced for more than 15 years. Respondents noted difficulty helping patients balance complex medical conditions (19%), faced socioeconomic barriers (17%), and struggled to provide dietary advice (16%). One-third were uncertain of how to support those receiving dialysis. Eighty-five percent felt they needed more training and education to care for this high-risk group. When asked about the care needs of patients with CKD, almost all (90%) felt that patients needed more diabetes support in general. Improvement in care coordination was most commonly suggested (38%). Conclusions In this study of the diabetes educators’ experience treating patients with diabetes and CKD, respondents noted numerous challenges. There may be opportunities to better support both diabetes care professionals, and patients who live with multiple medical comorbidities.
Towards a Resilience to Stress Index Based on Physiological Response: A Machine Learning Approach

This study proposes a new index to measure the resilience of an individual to stress, based on the changes of specific physiological variables. These variables include electromyography, which is the muscle response, blood volume pulse, breathing rate, peripheral temperature, and skin conductance. We measured the data with a biofeedback device from 71 individuals subjected to a 10-min psychophysiological stress test. The data exploration revealed that features’ variability among test phases could be observed in a two-dimensional space with Principal Components Analysis (PCA). In this work, we demonstrate that the values of each feature within a phase are well organized in clusters. The new index we propose, Resilience to Stress Index (RSI), is based on this observation. To compute the index, we used non-supervised machine learning methods to calculate the inter-cluster distances, specifically using the following four methods: Euclidean Distance of PCA, Mahalanobis Distance, Cluster Validity Index Distance, and Euclidean Distance of Kernel PCA. While there was no statistically significant difference (p>0.01) among the methods, we recommend using Mahalanobis, since this method provides higher monotonic association with the Resilience in Mexicans (RESI-M) scale. Results are encouraging since we demonstrated that the computation of a reliable RSI is possible. To validate the new index, we undertook two tasks: a comparison of the RSI against the RESI-M, and a Spearman correlation between phases one and five to determine if the behavior is resilient or not. The computation of the RSI of an individual has a broader scope in mind, and it is to understand and to support mental health. The benefits of having a metric that measures resilience to stress are multiple; for instance, to the extent that individuals can track their resilience to stress, they can improve their everyday life.
Genetic Programming Approach for Prediction of Local Scour Downstream of Hydraulic Structures

This is a pioneer study that presents genetic programming (GP) as a new tool for prediction of local scour downstream of grade-control structures. The objective of this study is to provide an alternative formulation to conventional regression based equations and verify the superiority of GP over regression analysis. The training and testing patterns of the proposed GP formulation are based on well established and widely dispersed experimental results from the literature. Linear and nonlinear regression-based equations were derived throughout regression analysis on dimensionless parameters obtained from dimensional analysis. The GP-based formulation results are compared with experimental results and other equations and found to be more accurate.
Antibody-Dependent Enhancement of SARS-CoV-2 Infection of Human Immune Cells: In Vitro Assessment Provides Insight in COVID-19 Pathogenesis

Patients with COVID-19 generally raise antibodies against SARS-CoV-2 following infection, and the antibody level is positively correlated to the severity of disease. Whether the viral antibodies exacerbate COVID-19 through antibody-dependent enhancement (ADE) is still not fully understood. Here, we conducted in vitro assessment of whether convalescent serum enhanced SARS-CoV-2 infection or induced excessive immune responses in immune cells. Our data revealed that SARS-CoV-2 infection of primary B cells, macrophages and monocytes, which express variable levels of FcγR, could be enhanced by convalescent serum from COVID-19 patients. We also determined the factors associated with ADE, and found which showed a time-dependent but not viral-dose dependent manner. Furthermore, the ADE effect is not associated with the neutralizing titer or RBD antibody level when testing serum samples collected from different patients. However, it is higher in a medium level than low or high dilutions in a given sample that showed ADE effect, which is similar to dengue. Finally, we demonstrated more viral genes or dysregulated host immune gene expression under ADE conditions compared to the no-serum infection group. Collectively, our study provides insight into the understanding of an association of high viral antibody titer and severe lung pathology in severe patients with COVID-19.
Implementation Exchange: The Implementation Profile

It all started ten years ago. First, there was a perceived need. MS/OR researchers had discovered by the early 70's that, in spite of the technical sophistication and instrinsic beauty of many of their models, a relatively small percentage were being used by practicing managers. Better understanding of the implementation process was needed. We became interested in the problem as an aspect of behavioral science. And finally, a research site emerged. A major US corporation was implementing a computerized sales forecasting model.Great care was taken to make sure that the research was rigorous and “correctly done. ” The research questions were straightforward: 1. What basic attitudes affect implementation success? 2. How can these attitudes be measured? 3. How do these attitudes affect implementation success?
System Maturity Indices for Decision Support in the Defense Acquisition Process

Abstract : The Technology Readiness Level (TRL) scale is a measure of maturity of an individual technology, with a view towards operational use in a system context. A comprehensive set of concerns becomes relevant when this metric is abstracted from an individual technology to a system context, which may involve interplay among multiple technologies that are integrated through the defense acquisition process. This paper proposes the development of a system focused approach for managing system development and making effective and efficient decisions during the defense acquisition process. For this to be accomplished, a new System Readiness Level (SRL) index will incorporate both the current TRL scale and the concept of an integration readiness level (IRL). This paper describes the foundations for the SRL and provides techniques for determining current and future readiness of a system to determine its position in the defense acquisition process. In addition, it proposes optimization models than can provide management with an optimal development plan that can meet the objectives of the development team, based on constrained resources. These, in turn, can become the foundation for the development of a monitoring and evaluation tool that will be analogous to Earned Value Management used in project management.
The impact of Insurance for Economic Growth: the Evidence from new EU member States

The aim of this paper is to examine relationship between insurance sector development and economic in 11 new EU member states from Central and Eastern Europe, using annual data for the period 1999-2018. We apply dynamic and fully modified ordinary least squares to estimate the relationship between the variables. The results of our study indicate there are a positive and a significant relationship between insurance, measured through penetration, and economic growth These results could be useful for regional governments that seek to improve economic growth as they suggest the need for implementation of stimulative policies for the development of insurance industry
Towards a nondestructive procedure for characterization of molding compounds

The applicability of using ultrasonics for characterizing and fingerprinting molding compounds is investigated in this study. The goal is to compile a database of ultrasonic parameters for several commercial molding compound and investigate if different molding compounds have distinct "signatures". The suitability of using ultrasonic parameters to estimate the void fraction is also investigated using calibration specimens with varying amounts of voids (simulated with 100 /spl mu/m glass spheres). Results presented demonstrate that different classes of molding compounds can be distinguished from each other from their frequency dependent attenuation curves and acoustic impedance. In general, the biphenyl resins exhibit a lower attenuation, higher velocity and higher impedance than the creosol-novolac resin. Post-mold cure (PMC) does not change the attenuation curves significantly, and the molding compounds retain distinctly different behaviors. The attenuation measured for even the least attenuative molding compound (MP7320) at 30 MHz is significantly higher (/spl sim/10 dB) than that at 10 MHz. The slope of the frequency dependent scattering loss correlated well with the volume fraction of the simulated voids. Thus, ultrasonics is demonstrated to be an attractive technique to monitor the material parameters of molding compounds nondestructively and over a small area.
Estimation of Warehouse Throughput in Freight Transport Demand Model for the Netherlands

This paper presents an extension of the classical four-step freight modeling framework with a logistics chain model. Modeling logistics at the regional level establishes a link between trade flow and transport flow, allows the warehouse and distribution center locations and throughput volumes to be determined, and permits more detailed and accurate policy decision support systems. This paper describes a two-stage logistics model that estimates the volume of regional warehouse throughput. The first stage estimates interregional trade flows by means of a gravity model application and starts from regional production and consumption volumes. The second stage, the logistics chain model, splits the production–consumption flow between direct shipments and shipments that go through warehouse facilities. An aggregate multinomial logit discrete choice model is used to determine the flow volumes for each of the possible logistics chains. Consistency is achieved between the gravity and logistics chain models by a joint estimation of unknown parameters. A new data set from a transport flow survey produced by Statistics Netherlands is used; the data set includes information on the types of loading and unloading location. This data set enables model calibration with respect to regional warehouse throughput. The proposed logistics chain model produces accurate estimates of regional warehouse throughput and plausible parameter values. The paper presents the specification of the new model, the data set used, and the results of the estimation.
Efficiency of modulated and dose rate altered flattening filter free beams in high dose per fraction radiotherapy applications on the survival of prostate cancer cell lines

Background: The radiobiological effect of high dose rate FFF beams on the DU-145 cells was investigated with SBRT plans which have >10 Gy. Methods and Materials: To compare the radiobiological effect on DU-145 cell line four experiments designed: (1) the constant dose rate of 6 MV and 6 MV FFF with increased dose per pulse (2) the effect of dose per pulse while increasing instantaneous dose rate for 6 MV and 6 MV FFF, (3) the effect of increased average dose rate for 6 MV FFF and (4) the effect of protracted treatment time and modulation of 6 MV FFF beams. The survival fraction was counted with WST. Results: FF and FFF for 6 MV with same dose rate and treatment time has no effect on cell survival. Significant differences was observed on survival which were irradiated with 6 MV 600 MU/min and 6 MV FFF 1400 MU/min (p=0.024). There was no difference between 6 MV FFF 600 MU/min and 6 MV FFF 1400 MU/min for 10 Gy. The significant survival difference obtained for 20 Gy. The survival percentages for both 10 Gy and 20 Gy with Cyberknife were obtained higher than FFF. Conclusion: Our in-vitro study presented here show that higher dose rate and reduced treatment time might become a crucial factor for SBRT especially which has >10 Gy fraction
Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies

Identifying the epitope of an antibody is a key step in understanding its function and its potential as a therapeutic. Sequence-based clonal clustering can identify antibodies with similar epitope complementarity, however, antibodies from markedly different lineages but with similar structures can engage the same epitope. We describe a novel computational method for epitope profiling based on structural modelling and clustering. Using the method, we demonstrate that sequence dissimilar but functionally similar antibodies can be found across the Coronavirus Antibody Database, with high accuracy (92% of antibodies in multiple-occupancy structural clusters bind to consistent domains). Our approach functionally links antibodies with distinct genetic lineages, species origins, and coronavirus specificities. This indicates greater convergence exists in the immune responses to coronaviruses than is suggested by sequence-based approaches. Our results show that applying structural analytics to large class-specific antibody databases will enable high confidence structure-function relationships to be drawn, yielding new opportunities to identify functional convergence hitherto missed by sequence-only analysis.
Inside California's Prisons and Beyond: A Snapshot of In-Prison and Re-entry Programs

CEBC Working Papers are designed to share Center findings and to solicit informal peer review but have not been formally peer reviewed. Unless otherwise indicated, Working Papers can be quoted and cited without permission of the author, provided the source is clearly referred to as a working paper. WORKING PAPER The authors would like to thank the program staff for answering questions and providing information about their programs. We would also like to thank Susan Turner, Joan Petersilia, Jesse Jannetta, Kristy Matsuda, Elizabeth Bernstein, Jean Merrell, and Valerie Jenness for their support and input on this report. Inside California’s Prisons and Beyond: A Snapshot of In-Prison and Re-entry Programs
Management Forecasting Ability and Predictive Ability of Dividend Changes for Future Earnings

We revisit the predictive ability of dividend changes for firms’ future earnings and extend the literature by examining the effect of management forecasting ability. Although prior studies have examined the relationship between dividend changes and future earnings, the empirical evidence is mixed. The belief that dividend changes have implications for future earnings depends on the assumption that managers can accurately assess future earnings prospects. In this regard, we posit that the predictive ability of dividends can vary with managers’ forecasting ability. Analyzing a large sample of Japanese dividend-paying firms, we find that dividend changes, particularly dividend increases, are positively associated with increases in future earnings. Consistent with our hypothesis, this positive association is more pronounced for firms with high-forecasting ability managers. Our findings support the signaling theory of dividend changes and indicate that management forecasting ability has a moderating effect on the linkage between firms’ dividend changes and future earnings.
Analysis of Nursing Effect of Children with Henoch-Schonlein Purpura Based on the PDCA Nursing Model

By applying the PDCA model to the care of children with Henoch-Schonlein purpura, the nursing process can be divided into four stages: planning, execution, inspection, and treatment. According to the age characteristics and disease progression of pediatric patients, a complete nursing plan is formulated to efficiently implement the nursing content and improve the nursing effect. This paper studies the application of the PDCA nursing model in the nursing of children with Henoch-Schonlein purpura and statistically analyzes the disappearance of skin rash, joint pain relief, disappearance of urine protein, disappearance of gastrointestinal symptoms, etc. Finally, this paper combines the experiment to evaluate the intervention effect of this nursing model and provides reference for the follow-up care of children with Henoch-Schonlein purpura. From the results of experimental research, it can be known that PDCA nursing can improve the comfort of children with Henoch-Schonlein purpura, shorten the time for symptom disappearance, and speed up the recovery process.
Insurance Payment Predicting Financial Risk Management Satisfaction of Malaysian Public Sector Employees

Risks are faced daily leading to unexpected bad events and incurring high costs. Notwithstanding, the differences in the ability to handle the situation may depend on their risk protection and financial preparedness. Thus, this study focused on the effect of insurance payment and financial preparedness among others, on the individuals’ financial risk management satisfaction. A multistage random sampling resulted in 500 respondents selected among public sector employees. Logistic regression for 472 data from self-administered questionnaires identified financial preparedness for old age, self-worth, financial risk knowledge, net-worth and insurance payment as influential predictors predicting the likelihood of the financial risk management satisfaction. Higher self-worth and financial risk knowledge, positive net-worth and higher insurance premium payment to cover risks faced would more likely predict individuals to be more satisfied with their financial risk management. Insurance payment was found to be the most influential predictor. Despite public workers having a low probability of the risk of losing jobs, nevertheless there is a need to have insurance protection for other financial risks. Hence, by purchasing insurance for various purposes, they would most probably be having a peace of mind in view of their risks.
Induction of Sunflower Plants Resistance to Meloidogyne incognita Infection by Seed Priming Technique

A greenhouse experiment was conducted during the summer seasons 2019 and 2020 to evaluate the effect of sunflower grains priming in different concentrations of salicylic, ascorbic acids, hydrogen peroxide, thiamine, nitric oxide and Oxamyl growth parameters of sunflower plants under the stress of nematode infection. The best effect was reach by the seed soaking of Nitric oxide at 100 ppm(stem height 66.4 cm; root length 81.96 cm;shoot fresh weight 414.2 g;root fresh weight 201.86 g; shoot dry weight 65.76 g). Meanwhile,the less efficiency was reach with the seed soaking of hydrogen peroxide at 50 ppm (stem height 47.66 cm; root length 53.36 cm; shoot fresh weight 263.6 g; root fresh weight 126.28 g; shoot dry weight 49.52 g). Nematicide Oxamyl (stem height 34.3 cm; root length 32.94 cm;shoot fresh weight 156.0 g; root fresh weight 72.3 g; shoot dry weight 37.94 g) followed by control non soaked the best effect was reached over both season by the seed soaking of hydrogen peroxide at 100 ppm (N: 7.32%; P: 0.78%; K: 6.5%; phenol: 117.1; POX: 1.4; Chlorophyll a: 1.1; Chlorophyll b: 0.7; Total Chlorophyll: 1.74; and Carotene: 1.28). Seed priming in nitric oxide (100 ppm), chitosan(50 ppm)and chitosan(100 ppm), consequently produced the highest averages of seedling growth parameters as compared with the other treatments over both seasons. On the other hand, seed priming in H2O2 at 100 ppm, thiamine at 50 ppm, thiamine at 100 ppm and nitric oxide at 50 ppm resulted the highest values of chemical parameters over both seasons.