Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrical impedance tomography and prior information

In electrical impedance tomography (EIT) images of the object are formed based on passive electrical properties of the interior structures. In EIT an array of electrodes is attached around the object and small alternating currents are injected via these electrodes and the resulting voltages are measured. Using di erent current injections and voltage measurements, an approximation for the spatial distribution of impedance (or resistivity) within the object can be reconstructed. Mathematically the EIT reconstruction problem is a nonlinear ill-posed inverse problem, the solution of which necessitates the use of regularization methods. In this thesis new approaches of EIT image reconstrution are proposed. Three novel methods are developed, all of which exploit available prior information. The rst one, the basis constraint method, is based on a learning process from which a few basis images are obtained and the solution is forced to be a linear combination of these few images. In the learning process the available prior information that is based on the object properties is e ectively utilized. Due to the parameter reduction the reconstruction procedure becomes fast. However, the method still enables the modelling of small changes in the interior structures. It was found that if the actual resistivity distribution is in accordance with the prior this method gives good results, but if it is not, misleading results are obtained. The second proposed method is a modi cation of the rst one and it is based on the Tikhonov regularization technique. In this method the solution is drawn towards the assumed solution, that is, towards the linear combination of the basis images with the aid of properly constructed regularization matrix. This method gives good resistivity estimates when the actual resistivity distribution is in accordance with the prior but even if it is not, the resistivity distribution can be quite well reconstructed. The third method is based on the state space representation of the EIT reconstruction problem. The method is applicable to such cases in which the resistivity distribution can not be assumed to be time-invariant within one measurement cycle. With this method fast resistivity changes can be tracked. National Library of Medicine Classi cation: WN 180, WN 206, QT 36 AMS Subject Classi cation: 65R30, 35R30, 65N30, 92C55, 93E12 INSPEC Thesaurus: electric impedance imaging; inverse problems; nite element analysis; Bayes methods; Kalman lters
Benchmarking analysis of three multimedia models: RESRAD, MMSOILS, and MEPAS

Multimedia modelers from the United States Environmental Protection Agency (EPA) and the United States Department of Energy (DOE) collaborated to conduct a comprehensive and quantitative benchmarking analysis of three multimedia models. The three models-RESRAD (DOE), MMSOILS (EPA), and MEPAS (DOE)-represent analytically based tools that are used by the respective agencies for performing human exposure and health risk assessments. The study is performed by individuals who participate directly in the ongoing design, development, and application of the models. A list of physical/chemical/biological processes related to multimedia-based exposure and risk assessment is first presented as a basis for comparing the overall capabilities of RESRAD, MMSOILS, and MEPAS. Model design, formulation, and function are then examined by applying the models to a series of hypothetical problems. Major components of the models (e.g., atmospheric, surface water, groundwater) are evaluated separately and then studied as part of an integrated system for the assessment of a multimedia release scenario to determine effects due to linking components of the models. Seven modeling scenarios are used in the conduct of this benchmarking study: (1) direct biosphere exposure, (2) direct release to the air, (3) direct release to the vadose zone, (4) direct release to the saturated zone, (5) direct release to surface water, (6) surface water hydrology, and (7) multimedia release. Study results show that the models differ with respect to (1) environmental processes included (i.e., model features) and (2) the mathematical formulation and assumptions related to the implementation of solutions (i.e., parameterization).
THE ANALYSIS AND DESIGN OF SINGLE PLATE FRAMING CONNECTIONS

In this paper, two typical single plate framing connections are discussed and illustrated. In both cases, the connection comprises a single plate, with prepunched bolt holes, that is shop welded to the supporting member. The standard design procedure for the single plate framing connection is too assume each bolt carries an equal portion of the total shear load and, in agreement with the simple support assumption, that relatively free rotation occurs between the end of the beam and the supporting member. In order to evaluate the end moment generated by the single plate framing connection, the beam line method of analysis was used. Included in the discussion is an explanation of moment-rotation curves as well as results and summaries a various full beam tests--three- bolt test, five-bolt test, seven-bolt test and three-bolt test with six-inch bolt pitch. Also, design formulas and recommended design procedures are discussed.
Vehicle-to-Vehicle Communications: Readiness of V2V Technology for Application

The purpose of this research report is to assess the readiness for application of vehicle-to-vehicle (V2V) communications, a system designed to transmit basic safety information between vehicles to facilitate warnings to drivers concerning impending crashes. The United States Department of Transportation and the National Highway Traffic Safety Administration (NHTSA) have been conducting research on this technology for more than a decade. This report explores technical, legal, and policy issues relevant to V2V, analyzing the research conducted thus far, the technological solutions available for addressing the safety problems identified by the agency, the policy implications of those technological solutions, legal authority and legal issues such as liability and privacy. Using this report and other available information, decision-makers will determine how to proceed with additional activities involving vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-pedestrian (V2P) technologies.
Robust control design for vehicle active suspension systems with uncertainty

A vehicle active suspension system, in comparison with its counterparts, plays a crucial role in adequately guarantee the stability of the vehicle and improve the suspension performances. With a full understanding of the state of the art in vehicle control systems, this thesis identifies key issues in robust control design for active suspension systems with uncertainty, contributes to enhance the suspension performances via handling tradeoffs between ride comfort, road holding and suspension deflection. Priority of this thesis is to emphasize the contributions in handing actuator-related challenges and suspension model parameter uncertainty. The challenges in suspension actuators are identified as time-varying actuator delay and actuator faults. Time-varying delay and its effects in suspension actuators are targeted and analyzed. By removing the assumptions from the state of the art methods, state-feedback and output-feedback controller design methods are proposed to design less conservative state-feedback and output-feedback controller existence conditions. It overcomes the challenges brought by generalized timevarying actuator delay. On the other hand, a novel fault-tolerant controller design algorithm is developed for active suspension systems with uncertainty of actuator faults. A continuous-time homogeneous Markov process is presented for modeling the actuator failure process. The fault-tolerant H∞ controller is designed to guarantee asymptotic the stability, H∞ performance, and the constrained performance with existing possible actuator failures. It is evident that vehicle model parameter uncertainty is a vital factor affecting the performances of suspension control system. Consequently, this thesis presents two robust control solutions to overcome suspension control challenges with nonlinear constraints. A novel fuzzy control design algorithm is presented for active suspension systems with uncertainty. By using the sector nonlinearity method, Takagi-Sugeno (T-S) fuzzy systems are used to model the system. Based on Lyapunov stability theory, a new reliable fuzzy controller is designed to improve suspension performances. A novel adaptive sliding mode controller design approach is also developed for nonlinear uncertain vehicle active suspension systems. An adaptive sliding mode controller is designed to guarantee the stability and improve the suspension performances. In conclusion, novel control design algorithms are proposed for active suspension systems with uncertainty in order to guarantee and improve the suspension performance. Simulation results and comparison with the state of the art methods are provided to evaluate the effectiveness of the research contributions. The thesis shows insights into practical solutions to vehicle active suspension systems, it is expected that these algorithms will have significant potential in industrial applications and electric vehicles industry.
The Acceptability and Impact of the Xploro Digital Therapeutic Platform to Inform and Prepare Children for Planned Procedures in a Hospital: Before and After Evaluation Study (Preprint)

BACKGROUND There is increasing interest in finding novel approaches to improve the preparation of children for hospital procedures such as surgery, x-rays, and blood tests. Well-prepared and informed children have better outcomes (less procedural anxiety and higher satisfaction). A digital therapeutic (DTx) platform (Xploro) was developed with children to provide health information through gamification, serious games, a chatbot, and an augmented reality avatar. OBJECTIVE This before and after evaluation study aims to assess the acceptability of the Xploro DTx and examine its impact on children and their parent’s procedural knowledge, procedural anxiety, and reported experiences when attending a hospital for a planned procedure. METHODS We used a mixed methods design with quantitative measures and qualitative data collected sequentially from a group of children who received standard hospital information (before group) and a group of children who received the DTx intervention (after group). Participants were children aged between 8 and 14 years and their parents who attended a hospital for a planned clinical procedure at a children’s hospital in North West England. Children and their parents completed self-report measures (perceived knowledge, procedural anxiety, procedural satisfaction, and procedural involvement) at baseline, preprocedure, and postprocedure. RESULTS A total of 80 children (n=40 standard care group and n=40 intervention group) and their parents participated in the study; the children were aged between 8 and 14 years (average 10.4, SD 2.27 years) and were attending a hospital for a range of procedures. The children in the intervention group reported significantly lower levels of procedural anxiety before the procedure than those in the standard group (two-tailed t63.64=2.740; P=.008). The children in the intervention group also felt more involved in their procedure than those in the standard group (t75=−2.238; P=.03). The children in the intervention group also reported significantly higher levels of perceived procedural knowledge preprocedure (t59.98=−4.892; P=.001) than those in the standard group. As for parents, those with access to the Xploro intervention reported significantly lower levels of procedural anxiety preprocedure than those who did not (t68.51=1.985; P=.05). During the semistructured write and tell interviews, children stated that they enjoyed using the intervention, it was fun and easy to use, and they felt that it had positively influenced their experiences of coming to the hospital for a procedure. CONCLUSIONS This study has shown that the DTx platform, Xploro, has a positive impact on children attending a hospital for a procedure by reducing levels of procedural anxiety. The children and parents in the intervention group described Xploro as improving their experiences and being easy and fun to use.
HPV Prevalence and Genotype Distribution Among Women From Hengyang District of Hunan Province, China

Most cervical cancers were closely associated with human papillomavirus (HPV) infections. Therefore, understanding the ecological diversity of HPV prevalence and genotype distribution among various populations in different geographical regions was essential for optimizing HPV vaccination and maximizing the vaccination effects. A total of 12,053 patient data from the three-level hospitals in Hengyang city were retrospectively analyzed. In this study, the HPV prevalence was 10.16% overall, and the multiple-type infection rate was 1.83%. The HR-HPV infection rate was 8.52%. The top six HPV genotypes were as follows in descending order: HPV16, HPV58, HPV52, HPV39, HPV51, and HPV53. The HPV prevalence in the group above 60 years old was the most, and their HR-HPV infection rate corresponded to the most too. The infection rates of HPV and HR-HPV among outpatients were both lower than those among the hospitalized-patients, respectively. Among the hospitalized-patients, the infection rates of HPV and HR-HPV among the 50–60 years group were the most in both. The HR-HPV ratio-in-positive among HPV-positive patients with the histopathologic examination was higher than that among those patients without. Among 52 HPV-positive patients with cervical squamous carcinoma, the ratio-in-positive of HPV16 was 61.54%. This study demonstrated that the HPV prevalence varied with age among women from Hengyang district of Hunan province in China and showed that HPV16, HPV58, HPV52, HPV39, HPV51, and HPV53 genotypes were more popularly distributed in this region, which could provide the experimental basis for Chinese public health measures on cervical cancer prevention.
AXIAL PERFORMANCE OF CONTINUOUS-FLIGHT-AUGER PILES FOR BEARING

Technology for the construction of continuous-flight-auger (CFA) piles has advanced to the point where these types of piles potentially can be considered as reliable as other types of piling (driven piles, drilled shafts) for supporting bearing loads produced by highway structures. To provide a basis for the axial design and construction of CFA piles in the coastal soils of the Houston District of the Texas Department of Transportation (TxDOT), a thorough comparison was made of several axial capacity prediction methods and capacities of CFA piles measured in numerous load tests performed for the private sector. The current TxDOT design method for drilled shafts was found to provide the most accurate prediction of pile capacity in predominantly clay soil profiles, while the Federal Highway Administration design method for drilled shafts was the most accurate in predominantly sand and mixed sand-clay profiles. Data on grout pressures, grout volumes, grout mix designs and grout placement procedures were also collected from experts and assembled into a preliminary construction specification. A special effort was made to construct (and carefully monitor the construction of) three instrumented test piles at three geologically diverse sites in the Houston District: (1) a stiff clay site, (2) a site with a profile consisting of stiff clay and loose, waterbearing sand, and (3) a site consisting of dry, medium dense sand. Analysis of the axial load test results confirmed the preliminary findings given above and also confirmed that with appropriate construction controls CFA piles can be installed with high axial capacity and a high degree of structural integrity.
The value of atherogenic index of plasma in non-obese patients with non-alcoholic fatty liver disease: a secondary analysis based on a cross-sectional study.

Background Atherogenic index of plasma (AIP) is elevated in fatty liver, but its value in non-obese patients with non-alcoholic fatty liver disease (NAFLD) is unclear. Methods The present study involved non-obese Chinese and Japanese participants. We used univariate and multivariate logistic regression model to determine risk factors. The performances of risk factors were compared by calculation of the area under the receiver operating characteristic curve. Results In the unadjusted model, we observed that odds ratio (OR) for every one standard deviation (SD) increase in AIP was 52.30. In the adjusted model I and model II, the OR for every one SD increase in AIP was 36.57 and 50.84, respectively. The area under the receiver operating characteristic curve for AIP was 0.803 and 0.802 in the development group and in the validation group, respectively. The best cut-off value of AIP in the discrimination between NAFLD and non-NAFLD was 0.005 in the Chinese group and was − 0.220 in the Japanese group, respectively. Conclusions Our results indicate that AIP and NAFLD have a positive correlation in Chinese and Japanese populations. AIP is an independent correlative factor of non-obese patients with NAFLD, which can be used as a new indicator of health examination.
Ringhals Diagnostics and Monitoring, Final Research Report 2012-2014

This report gives an account of the work performed by the Department of Nuclear Engineering, Chalmers, in the frame of research collaboration with Ringhals, Vattenfall AB, contract No. 630217-031. The contract constitutes a 3-year co-operative research work concerning diagnostics and monitoring of the BWR and PWR units. The work in the contract has been performed between January 1st 2012, and December 31st, 2014. During this period, we have worked with four main items as follows: 1. Development and application of the analysis method of core barrel vibrations, developed in the previous Stages, to three ex-core measurements performed during several cycles in R2, R3 and R4. What regards R2, this was the first attempt to analyze ex-core measurements taken at BOC, MOC and EOC, with the new curve-fitting procedure; 2. Investigation of the ultra-low frequency oscillations in reactor power in R4; 3. Development of the theory and simulations in order to determine the void content in R1 from the analysis of in-core measurements; 4. Evaluation of the measurements made in R1 with the use of 4 LPRMs and one TIP detector, for testing the velocity and void fraction profile reconstruction methods. This work was performed at the Department of Nuclear Engineering, Chalmers University of Technology by Victor Dykin, Cristina Montalvo (visitor from the Technical University of Madrid), Imre Pazsit (project co-ordinator) and Henrik Nylen, who was also the contact person at Ringhals.
Analytical techniques for the improvement of mass spectrometry protein profiling

Bioinformatics is rapidly advancing through the ”post-genomic” era following the sequencing of the human genome. In preparation for studying the inner workings behind genes, proteins and even smaller biological elements, several subdivisions of bioinformatics have developed. The subdivision of proteomics, concerning the structure and function of proteins, has been aided by the mass spectrometry data source. Biofluid or tissue samples are rapidly assayed for their protein composition. The resulting mass spectra are analyzed using machine learning techniques to discover reliable patterns which discriminate samples from two populations, for example, healthy or diseased, or treatment responders versus non-responders. However, this data source is imperfect and faces several challenges: unwanted variability arising from the data collection process, obtaining a robust discriminative model that generalizes well to future data, and validating a predictive pattern statistically and biologically. This thesis presents several techniques which attempt to intelligently deal with the problems facing each stage of the analytical process. First, an automatic preprocessing method selection system is demonstrated. This system learns from data and selects a combination of preprocessing methods which is most appropriate for the task at hand. This reduces the noise affecting potential predictive patterns. Our results suggest that this method can help adapt to data from different technologies, improving downstream predictive performance. Next, the issues of feature selection and predictive modeling are revisited with respect to the unique challenges posed by proteomic profile data. Approaches to model selection through kernel learning are also investigated. Key insights are obtained for designing the feature selection and predictive modeling portion of the analytical framework. Finally, methods for interpreting the results of predictive modeling are demonstrated. These methods are used to assure the user of various desirable properties: validation of the strength of a predictive model, validation of reproducible signal across multiple data generation sessions and generalizability of predictive models to future data. A method for labeling profile features with biological identities is also presented, which aids in the interpretation of the data. Overall, these novel techniques give the protein profiling community additional support and leverage to aid the predictive capability of the technology.
Symptoms are the Most Effective Child SCAT5 Component for Recognizing Concussion on the Day of Injury

Background: The Child Sport Concussion Assessment Tool 5th Edition (Child SCAT5) was developed to evaluate children between 5-12 years of age for a suspected concussion. However, limited empirical evidence exists demonstrating the value of the Child SCAT5 for acute concussion assessment. Therefore, the purpose of our study was to examine differences and assess the diagnostic properties of Child SCAT5 scores among concussed and non-concussed middle school children on the same day as a suspected concussion.Methods: Our participants included 34 concussed (21 boys, 13 girls; age=12.8±0.86 years) and 44 non-concussed (31 boys, 13 girls; age=12.4±0.76 years) middle school children who were administered the Child SCAT5 upon suspicion of a concussion. Child SCAT5 scores were calculated from the symptom evaluation (total symptoms, total severity), child version of the Standardized Assessment of Concussion (SAC-C), and modified Balance Error Scoring System (mBESS). The Child SCAT5 scores were compared between the concussed and non-concussed groups. Non-parametric effect sizes (r=z/√n) were calculated to assess the magnitude of difference for each comparison. The diagnostic properties (sensitivity, specificity, diagnostic accuracy, predictive values, likelihood ratios, and diagnostic odds ratio) of each Child SCAT5 score were also calculated.Results: Concussed children endorsed more symptoms (p<0.001, r=0.45), higher symptom severity (p<0.001, r=0.44), and had higher double leg (p=0.046, r=0.23), single leg (p=0.035, r=0.24), and total scores (p=0.022, r=0.26) for the mBESS than non-concussed children. No significant differences were observed for the SAC-C scores (p’s≥0.542). The quantity and severity of endorsed symptoms had the best diagnostic accuracy (AUC=0.76–0.77), negative predictive values (NPV=0.84–0.88), and negative likelihood ratios (-LR=0.22–0.31) of the Child SCAT5 scores.Conclusions: The symptom evaluation was the most effective component of the Child SCAT5 for differentiating between concussed and non-concussed middle school children on the same day as a suspected concussion.