Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Predictions Based on Accelerated Degradation Data and Spatial Count Data

This dissertation aims to develop methods for statistical predictions based on various types of data from different areas. We focus on applications from reliability and spatial epidemiology. Chapter 1 gives a general introduction of statistical predictions. Chapters 2 and 3 investigate the photodegradation of an organic coating, which is mainly caused by ultraviolet (UV) radiation but also affected by environmental factors, including temperature and humidity. In Chapter 2, we identify a physically motivated nonlinear mixed-effects model, including the effects of environmental variables, to describe the degradation path. Unit-to-unit variabilities are modeled as random effects. The maximum likelihood approach is used to estimate parameters based on the accelerated test data from laboratory. The developed model is then extended to allow for time-varying covariates and is used to predict outdoor degradation where the explanatory variables are time-varying. Chapter 3 introduces a class of models for analyzing degradation data with dynamic covariate information. We use a general path model with random effects to describe the degradation paths and a vector time series model to describe the covariate process. Shape restricted splines are used to estimate the effects of dynamic covariates on the degradation process. The unknown parameters of these models are estimated by using the maximum likelihood method. Algorithms for computing the estimated lifetime distribution are also described. The proposed methods are applied to predict the photodegradation path of an organic coating in a complicated dynamic environment. Chapter 4 investigates the Lyme disease emergency in Virginia at census tract level. Based on areal (census tract level) count data of Lyme disease cases in Virginia from 1998 to 2011, we analyze the spatial patterns of the disease using statistical smoothing techniques. We also use the space and space-time scan statistics to reveal the presence of clusters in the spatial and spatial/temporal distribution of Lyme disease. Chapter 5 builds a predictive model for Lyme disease based on historical data and environmental/demographical information of each census tract. We propose a Divide-Recombine method to take advantage of parallel computing. We compare prediction results through simulation studies, which show our method can provide comparable fitting and predicting accuracy but can achieve much more computational efficiency. We also apply the proposed method to analyze Virginia Lyme disease spatio-temporal data. Our method makes large-scale spatio-temporal predictions possible. Chapter 6 gives a general review on the contributions of this dissertation, and discusses directions for future research.
A GAMIFICATION APPROACH FOR THE IMPROVEMENT OF PAID CROWD-BASED LABELLING OF GEOSPATIAL DATA

Abstract. Non-commercial, unpaid crowdsourcing is the basis of many non-profit projects on the Internet such as Wikipedia or OpenStreetMap. A prerequisite for such projects to be successful is to find a sufficient number of volunteer crowdworkers who are intrinsically motivated to participate. In the field of geodata collection, many tasks exist that in principle could be solved with crowdsourcing; however, finding a large number of volunteers is problematic. There is also paid crowdsourcing in addition to crowdsourcing based on voluntary collaboration. The main incentive for participating in paid crowdsourcing projects is primarily payment for the work. Thus, intrinsic motivation is replaced by extrinsic motivation. However, intrinsic motivation simply replaced by extrinsic motivation can lead to a reduction in performance. If there are no additional intrinsic incentives in addition to monetary payment, it can happen that crowdworkers only perform exactly as much work as is necessary to satisfy the employers. Gamification may positively influence the motivation of paid crowdworkers. The goal of this paper is to investigate whether it is possible to increase the performance of paid crowdworkers with gamification. To this end, we have developed a web-based tool for the labelling of 3D triangle meshes. We presented this tool with and without game elements to paid crowdworkers and investigated to what extent gamification influenced the quality and quantity of the collected data.
Numerical simulation study on erosion mechanism of pre-mixed abrasive water jet

In order to optimize the parameters of the pre-mixed abrasive water jet cutting technology and make it more efficient in the coal mine gas environment, finite element analysis software LS-DYNA is used to simulate single abrasive particle of rock erosion rule and analyze the influence of different particle size, different grinding particle impact velocity, different abrasive particle shape on rock erosion effect. The results show that under the same conditions, the greater the impact velocity, the better the erosion effect, and the erosion rate of abrasive particles is almost linear with the erosion rate of rock. With an increase in velocity of abrasive particles, the erosion rate of cube shape of abrasive particles is gradually higher than that of spherical particles of abrasive. The larger the particle size of abrasive particles, the bigger the kinetic energy of them and also the erosion depth and erosion volume on the rock and steel. But when the particle size increases, the erosion rate of abrasive particles on the rock will decrease gradually. The research results provide theoretical basis for optimizing the parameters of pre-mixed abrasive water jet cutting.
Actuation of ionic polymer-metal composites with alkali metal counterions—a molecular dynamics study

Ionic polymer-metal composites (IPMCs) are soft, electroactive materials with unique actuation properties that have attracted the interest of physicists, chemists, and engineers for over two decades. Despite significant progress in our understanding of the phenomenology of their actuation, we are yet to fully elucidate the physics at the nanoscale that underlies their macroscopic actuation. Previous experiments have shown that IPMC actuation depends on the type of counterions that is used to neutralize the acidic polymeric backbone. Some continuum theories have attempted to explain such a modulatory effect, but a complete understanding of the physics at the nanoscale level is lacking. Here, we employ classical molecular dynamics to fill this gap in knowledge. Building upon recent developments in the field, we investigate the response of three IPMC membranes with different metallic counterions that have been considered in earlier experimental research. While we do not detect variations in the axial stress, the examination of the spatial distribution of the through-the-thickness stress components in the three membranes reveals important differences. We show that these differences are well explained in terms of variations in water content as it relates to the type of counterions, challenging existing continuum models of IPMCs that mostly overlooked these factors. Overall, our work brings to light new physics within active materials, inspiring new efforts in material design and engineering, as well as multiscale modeling of soft matter.
Upconverter and downconverter luminescent materials : progress and strategies towards highly efficient photovoltaic solar cells

In this thesis, the downconversion (DC) and upconversion (UC) luminescence properties of rare earth doped materials were investigated for the spectral conversion of part of the solar spectrum, in order to enhance the performances of silicon photovoltaic devices. Significant progress were achieved regarding the understanding of loss mechanisms which limit the photoluminescence quantum yield (PLQY) of those materials. Achieving high PLQY values is of key importance for the successful realisation of DCor UC-enhanced photovoltaic devices. It was found that, in high absorbing materials, the PLQY can be reduced drastically by the self-absorption effect. The constraints imparted by this loss mechanism on the optical performances of the luminescent materials were determined using a one dimensional optical model developed by the author. The model was also experimentally validated via spectroscopic characterisation of a downconverting co-doped Ce/Yb borate glass. The role of self-absorption within an hypothetical DC-enhanced photovoltaic (DC-PV) device was investigated to find out the physical performance limitations of the device. Moreover, an UC material consisting of Er-doped hexagonal sodium yttrium fluoride (β-NaYF4) was theoretically investigated to look at the implications of self-absorption on two experimental situations: the case of a PLQY measurement, and on the effective performance in a UC-enhanced photovoltaic (UC-PV) device. The study demonstrates that an optimization of the thickness is essential in order to reduce the effect of self-absorption and maximize the possible additional photocurrent that could be harvested, and that the optimal thickness takes different values depending on the case considered. As a major progress, an UC material consisting in barium yttrium fluoride (BaY2F8) single crystal doped with Er 3+ was optically characterised resulting in a measured external photoluminescence quantum yield (ePLQY) of 12.1±1.2 % for a BaY2F8:30at%Er 3+ sample of thickness 1.75±0.01 mm, and a measured internal photoluminescence quantum yield (iPLQY) of 14.6±1.5 % in a BaY2F8:20at%Er sample with a thickness of 0.49±0.01 mm. Both values were obtained under excitation at 1493 nm and an irradiance of 7.0±0.7 Wcm−2. The reported iPLQY and ePLQY values are among the highest achieved for monochromatic excitation in this research field. Finally, the losses due to self-absorption were estimated in order to evaluate the maximum iPLQY achievable by this promising UC material. The estimated iPLQY limit values were ∼19%, ∼25% and ∼30%, for 10%, 20% and 30% Er doping level, respectively. The self-absorption model clarifies the origin of the disparity between the theoretical and the experimental PLQY reported for some materials. The results from this work assist with the design and implementation of DC and UC layers for photovoltaic devices, as well as providing a framework for optimization of luminescent materials to other fields of optics and photonics.
A Scoping Review of Interventions for Family Bereavement Care during the COVID-19 Pandemic

The death of a loved one is a major stressor, and bereaved people are at a higher risk of negative health effects. This risk is higher during the COVID-19 pandemic, which raises the need for understanding existing bereavement support interventions. This scoping review aimed to map and summarize findings from the existing literature regarding bereavement support interventions (i.e., psychosocial and psychotherapeutic interventions) for family carers of people who died of COVID-19. The Arksey and O’Malley methodological framework was used. Five databases—Medline, PubMed, CINAHL, Scopus, and Web of Science—were searched for articles available from the inception of COVID-19 pandemic (March 2020) to January 2022, following the PRISMA guidelines. Among the 990 studies identified, only seven met this study’s inclusion criteria. The analysis comprised three key topics: types of support programmes and bereavement interventions; tools used to measure the outcomes; and evidence of the impacts of the interventions. All studies analysed included interdisciplinary interventions, commonly developed in clinical settings. Support for recently bereaved individuals can entail cognitive behavioural therapy strategies and other tools to educate, guide, support, and promote healthy integration of loss. To mitigate the effects of non-normative family bereavement, we recommend a systematic approach and coordination between organizational settings, including access to informal and professional support, in order to find hope while navigating the aftermath of COVID-19.
Strain‐based joint damage estimation approach robust to unknown non‐stationary input force

To avert catastrophic failure in the structures, joints are typically designed to yield, but not fail, so that energy accumulated under cyclic loading is dissipated. Eventually, this renders the structural joints to be characteristically weaker and more vulnerable than the members. Yet, damage detection research mostly assumes damage in the members only. This article proposes a model‐based predictor–corrector algorithm that uses an interacting filtering approach to efficiently estimate joint damage in the presence of input and measurement uncertainties. For the predictor model, a novel strain‐displacement relationship specific to semi‐rigid frames is developed to map nodal displacements to corresponding strain measurements. The proposed estimation method embeds robustness against non‐stationary input (e.g., seismic excitation) in the state filter, itself. For this, an output injection technique is integrated within the state filter. The modified state filter (robust Kalman filter) runs within an enveloping parameter filter (particle filter) to simultaneously estimate the system states and joint damage parameters, respectively, using the response signal. Strain has been adopted as measurement since it is frame independent (beneficial for seismic activity) and also comparatively cheaper to use. Numerical studies are performed on a two‐dimensional (2‐D) three‐story three‐bay shear frame for different joint damage locations and severities. The sensitivity and the stability of the proposed approach are further investigated. Experimental validation of the proposed algorithm is carried out on a 2‐D steel frame.
Whole-Exome Sequencing Reveals Clinical Potential of Circulating Tumor DNA from Peritoneal Fluid and Plasma in Endometrial Cancer

Simple Summary Studies on biomarkers for endometrial cancer using circulating tumor DNA (ctDNA) from liquid biopsy samples are lacking. The aim of this study was to analyze gDNA from tumor tissues and ctDNA derived from peritoneal fluid and plasma samples and determine their mutational concordance via microsatellite instability, copy number alteration, and mutational signature analyses using whole-exome sequencing and P53 immunohistochemistry. ctDNA of two patients with negative cytology presented TP53 mutations concordant with those in the tissue, and the ctDNA of a patient with positive cytology harbored both TP53 and POLE mutations, although none were detected in the tissue. This study is the first to demonstrate comprehensive genomic concordance between ctDNA from the peritoneal fluid and tumor gDNA in endometrial cancer at the whole-exome level. Abstract Endometrial cancer (EC) is the most common type of gynecological cancer. Studies comparing tumor gDNA and ctDNA isolated from the plasma and peritoneal fluid of EC patients are limited. Whole-exome sequencing and P53 immunohistochemistry of 24 paired tissue, plasma, and peritoneal fluid samples from 10 EC patients were performed to analyze somatic mutations, copy number alterations, microsatellite instability, and mutational signatures. Mutations in cancer-related genes (KMT2C, NOTCH2, PRKAR1A, SDHA, and USP6) and genes related to EC (ARID1A, CTNNB1, PIK3CA, and PTEN) were identified with high frequencies among the three samples. TP53 and POLE mutations, which are highly related to the molecular classification of EC, were identified based on several key observations. The ctDNA of two patients with negative peritoneal fluid presented TP53 mutations concordant with those in tissues. ctDNA from the plasma and peritoneal fluid of a patient with positive cytology harbored both TP53 and POLE mutations, although none were detected in tissues. Additionally, the patient presented with wild type P53 immunohistochemistry, with a focal “high” expression in a “low” wild type background. The tissues and peritoneal fluid of 75% EC patients showed concordant microsatellite instability. Furthermore, we observed strong mutational concordance between the peritoneal fluid and tumors. Our data suggest that the ctDNA from peritoneal fluid might be a suitable biomarker for identifying the mutational landscape of EC and could complement tumor heterogeneity.
An ultrawideband miniaturized MIMO antenna with split ring Yagi like structures for S and X frequency multiband applications

A miniaturized three split ring-like Multiple-Input Multiple-Output (MIMO) antenna is presented for the S and X frequency band applications. The proposed antenna has been numerically investigated at operating frequency 1-15 gigahertz (GHz). The MIMO antenna is analyzed, and its prototype is measured in five types of structure to identify the effect of the split ring and other physical conditions. This antenna is fabricated on the FR- 4 substrates with a dimension of 25 mm × 40 mm which will provide the miniaturization factor of λ/2. The high gain of 6.61 dBi and an ultrawideband of 3.25 GHz is achieved by using split-ring resonators (SRRs) in the proposed miniaturized MIMO antenna structure. We have also analyzed the effect of the split rings on the overall radiation band and return loss on the S and X frequency band. Furthermore, the prototype measurement confirms the suggested antenna radiation characteristics.
Integrated Multimodal Transportation Model for a Switchgrass-Based Bioethanol Supply Chain: Case Study in North Dakota

In this study, a mixed integer linear programming model that integrates multimodal transport—truck and rail—into the switchgrass-based bioethanol supply chain was formulated. The objective of this study was to minimize the total cost for cultivation and harvesting, infrastructure, the storage process, bioethanol production, and transportation. Strategic decisions, including the number and location of intermodal facilities and biorefineries, and tactical decisions, such as the amount of biomass shipped, processed, and converted into bioethanol, were validated by using North Dakota as a case study. It was found that the multimodal transport scenario was more cost effective than a single mode of transport (truck) and resulted in a lower cost for bioethanol. A sensitivity analysis was conducted to demonstrate the impact of key factors in the decision to use multimodal transport in a switchgrass-based bioethanol supply chain and on the cost of bioethanol.
The Applications of Artificial Intelligence in Cardiovascular Magnetic Resonance—A Comprehensive Review

Cardiovascular disease remains an integral field on which new research in both the biomedical and technological fields is based, as it remains the leading cause of mortality and morbidity worldwide. However, despite the progress of cardiac imaging techniques, the heart remains a challenging organ to study. Artificial intelligence (AI) has emerged as one of the major innovations in the field of diagnostic imaging, with a dramatic impact on cardiovascular magnetic resonance imaging (CMR). AI will be increasingly present in the medical world, with strong potential for greater diagnostic efficiency and accuracy. Regarding the use of AI in image acquisition and reconstruction, the main role was to reduce the time of image acquisition and analysis, one of the biggest challenges concerning magnetic resonance; moreover, it has been seen to play a role in the automatic correction of artifacts. The use of these techniques in image segmentation has allowed automatic and accurate quantification of the volumes and masses of the left and right ventricles, with occasional need for manual correction. Furthermore, AI can be a useful tool to directly help the clinician in the diagnosis and derivation of prognostic information of cardiovascular diseases. This review addresses the applications and future prospects of AI in CMR imaging, from image acquisition and reconstruction to image segmentation, tissue characterization, diagnostic evaluation, and prognostication.
Cytokinin Production by Azospirillum brasilense Contributes to Increase in Growth, Yield, Antioxidant, and Physiological Systems of Wheat (Triticum aestivum L.)

Plant growth-promoting rhizobacteria are known to associate with several cereal crops. The rhizobacterium exerts its function by synthesizing diverse arrays of phytohormones, such as cytokinin (Ck). However, it is difficult to determine the plant growth promotion when a bacterium produces many different kinds of phytohormones. Therefore, to assess the involvement of Ck in growth promotion and activation of antioxidant and physiological systems, we set up this experiment. Wheat seeds (Triticum aestivum L.) were inoculated with Azospirillum brasilense RA−17 (which produces zeatin type Ck) and RA−18 (which failed to produce Ck). Results showed that seed inoculation with RA−17 significantly improved growth and yield-related parameters compared with RA−18. The activity of enzymes, proline contents, and endogenous hormonal levels in wheat kernels were improved considerably with RA−17 than with RA−18. Strain RA−17 enhanced grain assimilation more than strain RA−18 resulting in a higher crop yield. These results suggest that microbial Ck production may be necessary for stimulating plant growth promotion and activating antioxidant and physiological systems in wheat.
Green Synthesis of Fluorescent Carbon Dots through Solvothermal Treatment of Buchnania lanzan Leaf Extract

: In the present work we have synthesized fluorescent carbon dots (CDs) through solvothermal treatment of Buchnania lanzan leaves extract at 160 °C for 4 h in oven. Here, Buchnania lanzan leaves serve as a renewable source of carbon. The obtained blackish brown CDs solution was centrifuged and the supernatant was filtered through syringe filter (0.22 µm). Further, the CDs solution was dried in vacuum oven to obtain powder. The synthesized CDs were characterized by different techniques including UV-Visible spectroscopy, fluorescence spectroscopy, fourier trans-form infrared (FTIR), zeta potential, x-ray diffraction (XRD). The as prepared CDs solution was found brownish colored in day light while exhibited green fluorescence under UV light. UV-Visible absorption spectrum displayed characteristic shoulder peaks of CDs at 257 nm and at 356 nm. In the fluorescence spectra, excitation dependent emission behaviour of CDs was seen, which is one of the distinct characteristics of CDs. The negative zeta potential and characteristic peaksin FTIR, suggested presence of carbonyl, amine and hydroxyl functional groups on the CDs surface. XRD spectrum exhibited broad peak at 2θ=19°, suggesting amorphous nature of CDs similar as reported in earlier works. As we have synthesized surface functionalized fluorescent carbon dots from a renewable and abundant precursor, this method can be highly useful in large scale synthesis of carbon dots with reduced costs and will find potential applications in the field of drug delivery,
Research on Chinese live broadcast marketing and sustainable consumption intention under the internet environment

Compared with the traditional marketing model, the live broadcast marketing model increases the role of the anchor, making it a research hotspot. Based on different types of products and different anchor modes, the impact on consumers’ psychology and behavior is the focus of this paper. Through two standard experiments, spss22 0 statistical analysis found that: (1) for functional products, entertainment anchor mode significantly improves consumers’ emotional identity; at the same time, it significantly reduces consumers’ authority identity and knowledge identity; (2) for functional products, knowledge-based anchor mode significantly enhances consumers’ authority identity and knowledge identity, and significantly reduces consumers’ emotional identity; (3) In the functional product scenario, knowledge identity, authority identity and emotional identity all have a positive impact on consumers’ continuous purchase intention.