Miracle-dz/UniFAR-FTUs huggingface dataset:
A genetic programming approach for real-time crash prediction to solve trade-off between interpretability and accuracy

Abstract Real-time crash risk prediction is a hot topic of emerging technology. Due to the lack of basic risk formation theory, previous studies focussed on the application of complex models to improve the accuracy of prediction, ignoring the interpretation of variables, while the traditional statistical analysis method can interpret variables, but the prediction accuracy is poor, which falls into a dilemma of trade-off. In this study, based on the traffic flow information of elevated expressway, an improved genetic programming (GP) approach with elite gene bank is applied to obtain an explicit traffic flow crash risk function to solve the above trade-off problem. Logistic regression and backward-propagation neural network combined with partial dependency plot were used as baseline methods to examine the interpretability and accuracy of GP. It is found that GP prediction model has been proved to be able to select important variables and solve the trade-off dilemma, which has good interpretability and accuracy. The results show that crash risk in the traffic flow mainly comes from the traffic volume, speed of the upstream section, and the speed of the current section. Furthermore, the error of GP comes from the unobserved heterogeneity and crash mechanism theory is proposed.
GIS and Remote Sensing-Based Multi-Criteria Analysis for Delineation of Groundwater Potential Zones: A Case Study for Industrial Zones in Bangladesh

Groundwater is a crucial natural resource that varies in quality and quantity across Bangladesh. Increased population and urbanization place enormous demands on groundwater supplies, reducing both their quality and quantity. This research aimed to delineate the groundwater potential zone in the Gazipur district, Bangladesh, by integrating eleven thematic layers. Data and information were gathered from Landsat 8, the digital elevation model, the google earth engine, and several ancillary sources. A multi-criterion decision-making (MCDM) based analytical hierarchy process (AHP) was used in a GIS platform to estimate the groundwater potential index. The potential index values were finally classified into five sub-groups: very low, low, moderate, high, and very high to generate a groundwater water potential zone (GWPZ) map. The results show that groundwater potential in about 0.002% (0.026 km2) of the area is very low, 3.83% (63.18 km2) of the area is low, 56.2% (927.05 km2) of the area is medium, 39.25% (647.46 km2) of the area is high, and the rest 0.72% (11.82 km2) of the area is very high. The validation of GWPZ maps based on the groundwater level data at 20 observation wells showed an overall accuracy of 80%. In addition, the ROC curve showed 84% accuracy of GWPZ maps when validated with water inventory points across the study region. Overall, this study presents an easy and practical approach for identifying groundwater potential zones, which may help improve planning and sustainable groundwater resource management.
LTCC High K miniature filters in L and S bands

In current communication systems, whether terrestrial or spatial, whether fixed or mobile, there is a real interest in developing high performance miniature RF front-ends. This is applied in particular to filter devices, in which the size and the quality factors are clearly in conflict. For low frequency bands around the GHz, the wavelengths remain significant, making it difficult the miniaturization efforts. On the other hand, we must also ensure that these filters will be easily interconnected with other other system components, including active devices.For all these reasons, the development of multilayer filter structures using high permittivity substrates (Er = 68) in an LTCC approach is consolidated as an interesting alternative. It may lead to a significant footprint reduction without decreasing the electrical performances.As part of this work, two multilayer filter structures have been developed to meet the given specifications in L and S bands, given by a space manufacturer. These filters have as main features a high rejection level and low losses in the passband. To meet the specifications, a vertically stacked SIW filter and a short-circuited stubs filter in a stripline configuration were studied. The SIW filter is characterized by a high quality factor, which results in low insertion loss and good flatness. The stubs filter allows in contrast to reduce the footprint but at the price of impacting the electrical performance. In both cases we take advantage of the flexibility offered by the LTCC technology as it finally provides an additional freedom degree compared to a conventional planar approach. For the SIW filter, the topological architecture was studied and designed in detail, to be able to arrange and synthetize couplings between twelve cavities. In a similar way, for the stub filter a synthesis that takes profit of all the offered freedom degrees was developed.Given the filters complexity, especially due to the high order and the implementation of “electrical walls" based on specific vias patterns, a close attention must be paid during the simulation and optimization phase. In addition, the high permittivity substrate does not allow to conceive 50-Ohms lines. Finally, access transitions constitute a challenging task, especially for the SIW case.This thesis was co-funded by CNES (Centre National d'Etudes Spatiales) and Thales Alenia Space, and was accompanied by an R&T project funded by CNES. The German foundry Via Electronic was responsible for the filters fabrication.
Effect of Mindfulness Intervention on Inattentive Behaviors in Children at Risk for ADHD: A Single-Subject Study

Mindfulness is the increased awareness that arises when we pay attention on purpose to the present non-judgmentally. To investigate the influence of mindfulness on inattentive behaviors in children at risk for attention deficit hyperactivity disorder (ADHD), a single-subject A-B-A reversal experimental design was adopted in which two children at risk for ADHD received 6-week mindfulness training, with 20-30 minutes per session and 3-4 times per week. The results based on visual analysis, C-statistics, and social validity analysis showed that mindfulness training was effective in reducing the duration of inattentive behaviors in children at risk for ADHD, and that the training could improve the function of the attention network in these children, which could be reflected in the increased efficiency in the vigilance network and the executive function network.
Utility of Non-High-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratio in Evaluating Incident Diabetes Risk

Purpose Diabetes is one of the most prevalent chronic diseases in the world, and its prevalence is expected to rise further. To help understand the utility of the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) in diabetes prevention, this large-scale longitudinal cohort study aims to explore the association of NHHR with diabetes risk and compare it as a risk predictor with conventional lipid parameters. Patients and Methods This observational study extracted data from the NAGALA longitudinal cohort study conducted in Japan between 2004 and 2015. Multivariate Cox regression analysis was used to evaluate the association between NHHR and the risk of diabetes. The dose–response relationship was analyzed by restricted cubic spline (RCS) regression and the potential risk threshold was estimated. The receiver operator characteristic curve (ROC) was used to analyze and calculate the predictive value and optimal threshold of NHHR and other conventional lipids for new-onset diabetes. Results Of the 15,464 people aged 18–79, 373 (2.41%) were diagnosed with new-onset diabetes during the study period, with a median age of 46 years. The sensitivity analysis based on multivariate adjustment showed that the independent positive correlation between diabetes and NHHR was stable in different populations. RCS and ROC analysis indicated that the association between NHHR and diabetes was non-linear, and the NHHR was a better marker for predicting diabetes risk than other conventional lipid parameters; Additionally, it is worth noting that an NHHR of approximately 2.74 may be the optimal threshold for intervention in diabetes risk. Conclusion In the general population, NHHR is a better marker for predicting diabetes risk than conventional lipid parameters, and an NHHR of about 2.74 may be the optimal threshold for assessing diabetes risk.
A microfluidic chaotic mixer platform for cancer stem cell immunocapture and release

OF THE THESIS A Microfluidic Chaotic Mixer for Cancer Stem Cell Immunocapture and Release by Sebastian Wesley Shaner Master of Science in Bioengineering San Diego State University, 2016 Isolation of exceedingly rare and ambiguous cells, like cancer stem cells (CSCs), from a pool of other abundant cells is a daunting task primarily due to the inadequately defined properties of such cells. With phenotypes of different CSCs fairly well-defined, immunocapturing of CSCs is a desirable cell-specific capture technique. A microfluidic device is a proven candidate that offers the platform for user-constrained microenvironments that can be optimized for small-scale volumetric flow experimentation. In this study, we show how a well-known passive micromixer design (staggered herringbone mixer – SHM) can be optimized to induce maximum chaotic mixing within antibody-laced microchannels and, ultimately, promote CSC capture. The device’s (Cancer Stem Cell Capture Chip CSC 3 TM) principle design configuration is called: Single-Walled Staggered Herringbone (SWaSH). The CSC 3 TM was constructed of a polydimethylsiloxane (PDMS) foundation and thinly coated with an alginate hydrogel derivatized with streptavidin. The results of our work showed that the non-stickiness of alginate and antigen-specific antibodies allowed for superb target-specific cell isolation and negligible non-specific cell binding. Future engineering design directions include developing new configurations (e.g. Staggered High-Low Herringbone (SHiLoH) and offset SHiLoH) to optimize microvortex generation within the microchannels. This study’s qualitative and quantitative results can help stimulate progress into refinements in device design and prospective advancements in cancer stem cell isolation and more comprehensive single-cell and cluster analysis.
TOWARD A LOW-COST, MULTISPECTRAL, HIGH ACCURACY MAPPING SYSTEM FOR VINEYARD INSPECTION

Abstract. Confronted with the climate change challenge and the territorial constraints, agriculture has to modernize itself. The use of georeferenced data and remote-sensing imagery is a major step in this direction. This precision mapping of crops requires powerful and accurate acquisition systems, while remaining financially attractive. The development of multispectral sensors and low-cost GNSS makes it possible to consider systems that will be able to map at the plant scale. However, these positioning systems do not yet guarantee a precise overlap of data acquired at different times. Thus, we propose in this paper a method to register terrestrial image data, acquired on vineyard plots. Our method seeks to avoid image registration problems, such as illumination changes, by detecting the vine stocks, reconstructing them in 3D, and registering them individually. The 3D detection method is based on an image-based object detection method (Faster R-CNN) and a structure-from-motion reconstruction of object-masked images. The results that we obtained on a vineyard plot, allowed us to validate the method, with a precision of less than 10 cm, making it possible to map the vine by stock.
OptCom - a 100 Gbit/s transciever demonstrator project

This presentation is about a 100 Gbit/s demonstrator project in its early stage. Our focus is to present our project activities, and – at the oral presentation – highlight with a few examples from different subprojects. The project consists of activities in the following areas: high-speed electronics, assembly technology, optical components, and fibre-optical transmission. The project is a joint project with industry, where Optillion is the industrialand Chalmers is the academic partner. A corresponding project exists also at KTH, which focus on optical modulators.
Generalidades de robots paralelos

Los robots paralelos son utilizados en diversas areas como la simulacion de movimiento, la medicina y la manufactura, entre otras. Se han disenado y construido numerosos de ellos teniendo en cuenta aspectos como grados de libertad, modelos matematicos que aproximan la dinamica real del sistema donde actuan, y las estrategias de control para que respondan adecuadamente ante perturbaciones. El presente articulo describe las generalidades de robots paralelos con el fin de dar a conocer sus aplicaciones industriales, arquitecturas y notacion, metodos y representaciones matematicas necesarias para el analisis de su movilidad, el calculo de la cinematica y la dinamica presentes, el estudio del espacio de trabajo, asi como las estrategias de control implementadas. Se describen las investigaciones y desarrollos futuros que pueden realizarse en esta area de la robotica, asi como una amplia revision bibliografica que permite al lector incursionar profundamente en cualquier aspecto que le sea de interes.
Multi-Objective Bayesian Optimization of Lithium-Ion Battery Cells

The development of lithium-ion batteries (LIBs) based on current practice allows an energy density increase estimated at 10% per year. However, the required power for portable electronic devices is predicted to increase at a much faster rate, namely 20% per year. Similarly, the global electric vehicle battery capacity is expected to increase from around 170 GWh per year today to 1.5 TWh per year in 2030—this is an increase of 125% per year. Without a breakthrough in battery design technology, it will be difficult to keep up with their increasing energy demand. The objective of this investigation is to develop a design methodology to accelerate the LIB development through the integration of electro-chemical numerical simulations and machine learning algorithms. In this work, the Gaussian process (GP) regression model is used as a fast approximation of numerical simulation (conducted using Simcenter Battery Design Studio®). The GP regression models are systematically updated through a multi-objective Bayesian optimization algorithm, which enables the exploration of innovative designs as well as the determination of optimal configurations. The results reported in this work include optimal thickness and porosities of LIB electrodes for several practical charge–discharge scenarios which maximize energy density and minimize capacity fade.
Molecular detection of Giardia intestinalis in fresh vegetables and watercourses of Giza, Egypt

Giardia lamblia is a food-borne protozoan parasite, responsible for the considerable outspread of human gastrointestinal infections (Ortega & Adam, 1997). The clinical presentation varies from asymptomatic to severe diarrhea, abdominal pain, nausea, fatigue and vomiting (the most widespread symptoms) (Ortega & Kvac, 2013). Giardia is a highly active flagellated organism with two forms: the trophozoite (9–21μm long and 5–15μm wide) and oval infective thick-walled cyst (7-14μm long) which is excreted in feces of the infected host. Giardia has a relatively simple life cycle, which is completed within a single host (Smith et al., 1993). Giardia cyst is resistant to environmental and water treatment stresses (Grit et al., 2012, Alum et al., 2014). It can ARTICLE INFO ABSTRACT Article History: Received: Jan. 16, 2022 Accepted: April 29, 2022 Online: May 25, 2022 _______________
Older adults’ satisfaction with mHealth UI design-based culture: A case study of Jordan

ABSTRACT The dramatic growth of the older population worldwide has resulted in a renewed need for mobile health applications (mHealth apps). The use of mHealth UI-designed-based culture can be useful in improving the quality of healthcare for elderly users. Therefore, there is a need for a comprehensive examination of the impact of mHealth UI design-based culture on older adult people’s satisfaction. This study was conducted to promote older adults’ satisfaction with mHealth UI design-based culture in a culturally specific context. We examined the influence of learning, screen, application capabilities, and terminology and application information on older adults’ overall satisfaction with mHealth UI. Eighty-five older adults’ users from general population in Jordan participated in this study. The results showed different correlation coefficients between these factors. This study paves the way for future research to consider culture in the design of mHealth UI.
Mechanisms Underlying Directional Motion Processing and Form-Motion Integration Assessed with Visual Perceptual Learning

Dynamic Glass patterns (GPs) are visual stimuli commonly employed to study form–motion interactions. There is brain imaging evidence that non-directional motion induced by dynamic GPs and directional motion induced by random dot kinematograms (RDKs) depend on the activity of the human motion complex (hMT+). However, whether dynamic GPs and RDKs rely on the same processing mechanisms is still up for dispute. The current study uses a visual perceptual learning (VPL) paradigm to try to answer this question. Identical pre- and post-tests were given to two groups of participants, who had to discriminate random/noisy patterns from coherent form (dynamic GPs) and motion (RDKs). Subsequently, one group was trained on dynamic translational GPs, whereas the other group on RDKs. On the one hand, the generalization of learning to the non-trained stimulus would indicate that the same mechanisms are involved in the processing of both dynamic GPs and RDKs. On the other hand, learning specificity would indicate that the two stimuli are likely to be processed by separate mechanisms possibly in the same cortical network. The results showed that VPL is specific to the stimulus trained, suggesting that directional and non-directional motion may depend on different neural mechanisms.
A Novel Method to Inspect 3D Ball Joint Socket Products Using 2D Convolutional Neural Network with Spatial and Channel Attention

Product defect inspections are extremely important for industrial manufacturing processes. It is necessary to develop a special inspection system for each industrial product due to their complexity and diversity. Even though high-precision 3D cameras are usually used to acquire data to inspect 3D objects, it is hard to use them in real-time defect inspection systems due to their high price and long processing time. To address these problems, we propose a product inspection system that uses five 2D cameras to capture all inspection parts of the product and a deep learning-based 2D convolutional neural network (CNN) with spatial and channel attention (SCA) mechanisms to efficiently inspect 3D ball joint socket products. Channel attention (CA) in our model detects the most relevant feature maps while spatial attention (SA) finds the most important regions in the extracted feature map of the target. To build the final SCA feature vector, we concatenated the learned feature vectors of CA and SA because they complement each other. Thus, our proposed CNN with SCA provides high inspection accuracy as well as it having the potential to detect small defects of the product. Our proposed model achieved 98% classification accuracy in the experiments and proved its efficiency on product inspection in real-time.
Cognitive Testing of PAINReportIt-Spanish in Monolingual Hispanic Adults

Background A Spanish language computerized tool would facilitate cancer pain assessment and management for the underserved population of native Spanish speakers who do not speak or lack command of the English language. Objective Our aim was to identify Spanish-speaking adults’ understanding and interpretation of the PAINReportIt-Spanish items and instructions as well as translation and technical issues. Methods In a cross-sectional study, 20 mostly monolingual Spanish-speaking adults engaged in 1.5- to 2-hour, audio-recorded cognitive interviews as they completed the multidimensional PAINReportIt-Spanish. Three bilingual researchers conducted content data analysis. Results Sixteen women and 4 men generally understood the translated text, but some had interpretation issues regarding the 0 to 10 number scale and understanding of the pain quality descriptors. Many participants found the program easy to complete, even when they had problems in some areas. Most participants welcomed the opportunity to report pain in their native language and appreciated research to help Hispanics with the management of their pain. Conclusion PAINReportIt-Spanish is a valid tool to assess pain in a Spanish-speaking population. Improved orientation to the pain reporting tasks and alternate translations for several problematic/confusing Spanish words require additional study, especially among underrepresented black Hispanics and males. Implication for Practice Findings indicate that Spanish-speaking adults (1) easily use a body outline to report their pain location, (2) may use a 0 to 10 scale differently than other individuals, and (3) may have a limited repertoire of pain quality and pattern descriptors.
Changes in Accommodative and Binocular Function following Phakic Intraocular Lens for High and Low-to-Moderate Myopia

The aim was to evaluate accommodative and binocular function of phakic intraocular lens implantable collamer lens (ICL) in high and low-to-moderate myopia. Prospective comparative cohort study with 38 myopic patients who underwent ICL implantation were divided into two groups of 19 patients, each one based on the spherical equivalent (SE): high-power (SE ≤ −6 D) and low-to-moderate (SE > −6 D). The push-up amplitude of accommodation (AA), monocular accommodative facility (MAF), distance and near ocular deviation, near convergence amplitude, near point convergence (NPC), stereopsis, and accommodative convergence/accommodation (AC/A) ratio were assessed before surgery and 1 week and 1 month postoperatively. The mean residual refractive error at 1 month after surgery improved in both groups, 0.18 ± 0.34 D and 0.09 ± 0.26 D, respectively (p < 0.001). There was a significant decrease in AA in both groups between preoperatively and at 1-week (p = 0.001; p = 0.008, respectively) and 1-month follow-up (p = 0.001; p = 0.008). For the rest of the binocular measurements, no statistically significant postoperative changes were found in any group. This finding suggests follow-up studies on amplitude of accommodation in phakic intraocular lens ICL implantation.
RGB-BASED DEEP SURFACE WATER CONTOUR DETECTION

Abstract. The application of remote monitoring of surface water has focused primarily on the detection of water bodies using expensive multi-spectral IR sensors. However, critical information about surface water bodies, particularly the dynamic behavior, is better derived from water contours. We show that water body detection is inadequate in accurately capturing the contours. Furthermore, we argue that RGB-based detection should be sufficient for accurate water detection. We present a new global dataset of remote sensing images obtained from Sentinel-2 and Landsat-8 missions and contour labeled to assist in this effort. We propose a unique UNet-style contour detection system that utilizes multiscale filters to detect contours accurately. Comparisons between our proposed system, existing water detection, and other segmentation and contour detection systems show the system's effectiveness in detecting water.