Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive Load Detection For Advanced Driver Assistance Systems

In this thesis, we investigate cognitive load detection and classification based on minimally invasive methods. Cognitive load detection is crucial for many emerging applications such as advanced driver assistance systems (ADAS) and industrial automation. Numerous studies in the past have reported several psychological measures, such as eye-tracking, electrocardiogram (ECG), electroencephalogram (EEG), as indicators of cognitive load. However, existing physiological features are invasive in nature. Consequently, the objective of this study is to determine the feasibility of non-invasive features such as pupil dilation measurements low-cost eye-tracker with minimal constraints on the subject for cognitive load detection. In this study, data from 33 participants were collected while they underwent tasks that are designed to permeate three different cognitive difficulty levels with and without cognitive maskers and the following measurements were recorded: eye-tracking measures (pupil dilation, eye-gaze, and eye-blinks), and the response time from the detection response task (DRT). We also demonstrate the classification of cognitive load experienced by humans under different task conditions with the help of pupil dilation and reaction time. Developing a model that can accurately classify cognitive load can be used in various sectors such as semi-autonomous vehicles and aviation. we have used a data fusion approach by combining pupil dilation and DRT reaction time to determine if the classification accuracy increases. Further, we have compared the classifier with the highest classification accuracy using data fusion against the accuracy of the same classifier with only one feature (pupil dilation; reaction time) at a time.
Packet Scheduling in Multipath TCP: Fundamentals, Lessons, and Opportunities

Multipath transmission control protocol (MPTCP) is a transport protocol that allows the simultaneous use of multiple transmission control protocol subflows across the existing IP addresses between peers. Since each subflow undergoes the bottleneck link condition of its path, selecting the best subflow to schedule an outgoing packet plays a key role in the multipath performance. While good scheduling decisions can significantly improve throughput, wrong decisions prevent users from benefiting the aggregating capacities of available subflows. To deal with this concern, in the last years, several scheduling solutions were proposed to achieve different goals and applications. Different from other surveys and tutorials, in this article, we provide a tutorial of packet scheduling in the MPTCP that brings not only its fundamentals but also a detailed analysis of multipath performance from a consistent experimental methodology. In a multipath network setup, we compare single-criterion and multicriteria schedulers under different bottleneck conditions and multipath congestion controls. From a comprehensive experimental analysis that unveils several performance issues, we discuss the lessons learned and research opportunities regarding the multipath throughput improvement as the central motivation. In this way, this article provides a comprehensive analysis of packet scheduling in the MPTCP, not only in theory but in practice as well.
The efficacy of hypoxic training techniques in Australian footballers

Hypoxic training techniques have been gaining popularity in team sports, with a range of methods employed. However, before this work, there was a paucity of information on the responses of team sport athletes to hypoxic training. This work explores how team sport athletes respond to these interventions, complementing other recent work in this area. The primary focus of this thesis is on two hypoxic training techniques; Live High-Train High (LHTH) and Live Low-Train High (LLTH).
How User’s First Impression Forms on Mobile user Interface?: An ERPs Study

ABSTRACT In an era of mobile Internet, the using of mobile interfaces is ineluctable in our daily life. To some extent, the first impression of the mobile user interfaces determines users’ downloading and using behavior, even affects the overall user experience. In fact, the underlying neural mechanism of users’ first impression formation of mobile user interface is worthy to be investigated. Considering the process of first impression formation is always unconscious and transient, event-related potentials (ERPs), which are used to track users’ cerebral activities could be an appropriate method to explore this process. In the present study, the perceived usability and esthetics are taken as the evaluation dimensions of user’ first impression formation, and ERPs were used to investigate which dimensions were automatically activated when users browsed the mobile user interfaces passively without any explicit guidance. The ERPs results showed that N2 was dominated by perceived usability and esthetics, which reflected in enhanced N2 for high esthetics than for low esthetics, and larger N2 for high-perceived usability/high esthetics compared to low-perceived usability/low esthetics. Moreover, there was a larger late positive potential (LPP) for low esthetics interfaces with respect to high esthetics ones. The findings revealed that users could make an implicit evaluation spontaneously to the mobile user interfaces with different levels of perceived usability and esthetics. Furthermore, users’ first impression is significantly affected by the differences in esthetics but marginally influenced by the difference in perceived usability. The suggestions from this study for mobile application designers might be that the esthetics design of the mobile user interface should be prioritized in the early design stage.
A metal artifact reduction method for small field of view CT imaging

To reduce metal artifacts, several sinogram inpainting-based metal artifact reduction (MAR) methods have been proposed where projection data within the metal trace region of the sinogram are treated as missing and subsequently estimated. However, these methods generally assume data truncation does not occur and all metal objects reside inside the field-of-view (FOV). For small FOV imaging, these assumptions are violated, and thus existing inpainting-based MAR methods would not be effective. In this paper, we propose a new MAR method to reduce metal artifacts effectively in the presence of data truncation. The main idea behind the proposed method is the synthesis of a sinogram, which is treated as the originally measured sinogram. First, an initial reconstruction step is performed to remove truncation artifacts. The next step consists of a forward projection of the small FOV image, replacing the original sinogram with the synthesized sinogram. The final step is the application of sinogram inpainting based MAR methods using the synthesized sinogram. Verification of the proposed method was performed for three situations: extended cardiac-torso (XCAT) simulation, clinical data, and experimental data. The proposed method was applied with linear MAR (LMAR) and normalized MAR (NMAR), and the performance of the proposed method was compared with that of the previous method. For quantitative evaluation, normalized mean squared error (NMSE) and structure similarity (SSIM) were used. The results show the effectiveness of the proposed method to reduce residual metal artifacts, which are present in the results obtained with the previous method. The evaluation results using NMSE and SSIM also indicate that the proposed method is more effective than the previous method.
ACCELEROMETER-BASED PATTERNS OF PHYSICAL ACTIVITY BY WEIGHT STATUS AND GENDER AMONG US ADULTS: NATIONAL HEALTH AND NUTRITION EXAMINATION SURVEY 2003-2006

Purpose: To examine the patterns of physical activity across days of the week and times of day by gender and weight status among US adults. Methods: Physical velocity data were collected from adults aged 19 years and older from the NHANES 2003-2004 and 2005-2006 (n=8,481) using the Actigraph accelerometer. Velocity of physical activity was assessed during six 4-hour daily time periods for oneweek period to determine the average velocity of activity performed and the percent of daily activity performed during each time period. Results: Normal weight subjects had significantly greater amounts of activity during the 6am-10pm compared to overweight and obese subjects (P<.01) and significantly greater activity during the 10pm-2am and 2am-6am when compared with obese subjects (P<0.1). The Obese group was the only group to exceed 45% of their daily activity during the 10am-2pm and the 2pm-6pm time periods. Conclusion: Regardless of the gender and weight status the greatest mean counts and percent of activity were performed between 10am and 6pm and the amount of mean counts of activity decreased as the weight status increased to the next BMI category.
The role of nitrates in skeletal muscle metabolism during contraction

Inorganic nitrate (NO3-) is a chemical compound found naturally in some foods, mainly green leafy vegetables. Traditionally this anion was considered inert in the human body, but recently the consumption of dietary NO3- has been shown to result in a number of positive physiological effects. These effects include protection against ischaemic reperfusion injury and improvements in glucose regulation in diabetic animal models. Some studies have also shown a reduction in blood pressure and a decrease in oxygen consumption (VO2) for a given sub-maximal exercise workload, i.e. an increase in exercise efficiency after both acute, and chronic NO3- ingestion.
Using a phone-based learning tool as an instructional resource for initial literacy learning in rural African families

Background: Despite increased enrolments at primary schools in Zambia, more than half of the children in Grades 1–4 are unable to meet the required minimum standards for literacy. Aim: The study set out to examine the effects of using a phone-based mobile literacy game (Graphogame) to improve literacy skills in children and adults in rural family settings. Setting: The study was conducted in the Katete District, a rural town in the eastern province of Zambia. Methods: Participants were 73 Grade 2 learners (52% boys, mean age 9 years and 48% girls, mean age 10 years) and 37 parents (mean age 36 years). Three literacy tests, measuring letter-sound identification, phonological awareness, spelling competence and word recognition, were administered to both the children and parents. Parents also reported on their level of education, familiarity with smart phone use, availability of home reading materials and home literacy activities. Results: The findings showed that children who were exposed to the Graphogame performed better than the control group on all literacy measures. Furthermore, parent’s performance on the tests improved after the intervention. Conclusion: The findings suggest that technology can improve literacy skills in both children and adults in rural areas of Zambia.
Self Blood Glucose Measuring in the Non-insulin-requiring Diabetic Patient— To Test or Not to Test

History The initial patent for a practical glucose meter was issued in Elkhart, Indiana, in 1971, and the device has now evolved into a frequently used tool. The utility of finger-stick blood glucose testing using such meters has been solidly demonstrated in patients requiring insulin therapy; however, data are conflicting in non-insulin-requiring type 2 patients. 1 A systematic review of self blood glucose monitoring (SMBG) in type 2 patients not taking insulin concluded: “The overall effect of SMBG was a statistically significant decrease of 0.39% in glycated hemoglobin (HbA1c) compared with the control groups. This is considered clinically relevant. Based on the UK Prospective Diabetes Study, a decrease of 0.39% in HbA1c is expected to reduce risk of microvascular complications by 14%. ” 2 Davidson, on the other hand, in a counterpoint to this study, reviewed several trials and concluded that SMBG fails to reduce HbA1c in type 2 patients not taking insulin and is therefore a waste of money. 3
The Value-Momentum Correlation: An Investment Explanation

This paper shows that both value and momentum premia arise in a q-theoretic framework that considers optimal corporate policies under uncertain financing conditions. Book-to-market and past performance predict future returns because they serve as indicators of firm financing position. The book-to-market ratio increases with financing constraints, with high book-to-market firms investing less and demanding higher risk premia compared to unconstrained, low book-to-market firms. The value premium increases in bad times because value firms become even more constrained, while ample cash reserves allow growth firms to fare much better. Momentum effects appear among the most financially constrained firms. For these firms, financing constraints imply large price swings following cash-flow shocks and valuable equity market timing options imply positive autocorrelation in returns. Absent equity market timing during bad times, momentum disappears. The model is able to explain many empirical features of value and momentum premia, such as: (i) the procyclicality of the momentum premium, (ii) the countercyclicality of the value premium (iii) the negative correlation between the two, and (iv) severe losses to momentums strategies during market rebounds. Several new testable hypotheses arise regarding the fundamentals of value and momentum stocks. The empirical evidence is largely supportive.
Combination of Ensembles of Regularized Regression Models with Resampling-Based Lasso Feature Selection in High Dimensional Data

In high-dimensional data, the performances of various classifiers are largely dependent on the selection of important features. Most of the individual classifiers with the existing feature selection (FS) methods do not perform well for highly correlated data. Obtaining important features using the FS method and selecting the best performing classifier is a challenging task in high throughput data. In this article, we propose a combination of resampling-based least absolute shrinkage and selection operator (LASSO) feature selection (RLFS) and ensembles of regularized regression (ERRM) capable of dealing data with the high correlation structures. The ERRM boosts the prediction accuracy with the top-ranked features obtained from RLFS. The RLFS utilizes the lasso penalty with sure independence screening (SIS) condition to select the top k ranked features. The ERRM includes five individual penalty based classifiers: LASSO, adaptive LASSO (ALASSO), elastic net (ENET), smoothly clipped absolute deviations (SCAD), and minimax concave penalty (MCP). It was built on the idea of bagging and rank aggregation. Upon performing simulation studies and applying to smokers’ cancer gene expression data, we demonstrated that the proposed combination of ERRM with RLFS achieved superior performance of accuracy and geometric mean.
Current Harmonics Suppression Strategy for PMSM With Nonsinusoidal Back-EMF Based on Adaptive Linear Neuron Method

In this article, an adaptive linear neuron based current harmonics suppression method for permanent magnet synchronous motors with nonsinusoidal back electromotive force (EMF) is presented, with due account for dead-time effect. The current harmonics can be well-suppressed by feedforwarding a self-tuning compensation voltage. The proposed method does not rely on the knowledge of back-EMF harmonic components and dead-time effect. Moreover, the proposed method is easy to implement, since it does not need the process to extract the current harmonics. The effectiveness of the proposed method is verified by both simulation and experimental results without requiring additional hardware.
Analysis of lumbar disc degeneration: 82 cases

Aim: The purpose of this study was to investigate if the grade of lumbar disc degeneration. Intervertebral disc degeneration is a common degenerative disease. Material and Methods: A retrospective analysis on 34 males and 48 females with intervertebral discs degeneration and a mean age of 51.5 years. Using MRI, the grade of lumbar intervertebral discs degeneration was assessed according to the Pfirrmann classification. Results: There was a high correlation (R =0.385) and significant association (pearson correlation, p < 0.01) between L3/L4 disc degeneration and the aging. There was also a high correlation (R =0.56) and significant association (pearson correlation, p <0.001) between the L3/L4 disc degeneration and the L4/L5. Conclusion: For many years, excessive or abnormal mechanical load was thought to be the main cause of disk degeneration. Rates of aging and lumbar disc degeneration have gradually increased over the years. It is important to note that there is a significant relationship between aging and L3 / L4 disc degeneration and that L4 / L5 disc degeneration may also be present in patients with L3 / L4 disc degeneration.
How to teach machines to read human rights reports and identify judgments at scale

Abstract The accelerating availability of information from human rights monitors such as Amnesty International, Human Rights Watch, and the US State Department has led to new opportunities to measure repression and human rights protections in higher resolution. However, to date, most approaches that attempt to automatically structure textual reports use simple, lower-dimensional observations such as the counts of words that ignore syntax and word order. While these representations are useful for some applications, they limit the inferences scholars and policy-makers can extract from human rights reports. In this article, we present a new system, PULSAR, that takes syntax and word order into account. This system uniquely allows researchers to extract both the judgements and the aspects/rights being judged from texts at scale. We illustrate that this more detailed information is useful both for improving predictions of physical integrity rights and women's political rights, but also for generating machine learning models that are more interpretable than conventional specifications. This latter benefit holds the promise of coherently connecting qualitative and quantitative analyses of human rights texts.
Molecular mechanisms of oncogenesis & precision medicine approaches for pediatric low-grade gliomas

Pediatric low-grade gliomas (PLGGs) are a heterogeneous group of tumors that collectively represent the most common childhood brain cancer. Despite favorable outcomes with surgical and adjuvant therapies, majority of patients suffer from long-term treatment-related morbidities and recurrent/inoperable disease. This necessitates a deeper understanding of PLGG biology to aid development of molecular diagnostics and low-toxicity targeted therapeutics. Hitherto, PLGGs have been defined by activating mutations that dysregulate the MAPK signaling pathway, leading to clinical testing of RAF/MAPK inhibitors for PLGGs. Interestingly, recent large-scale sequencing efforts discovered novel gene fusions in PLGGs and we identified the unique recurrent association of tumor suppressor Quaking (QKI) with distinct proto-oncogenes, MYB and RAF1, in different PLGG sub-types. We hypothesized that MYB-QKI and QKI-RAF1 function via novel oncogenic mechanisms invoking a two-hit mechanism of gain-of-function in the MYB/RAF1 oncoproteins collaborating with QKI loss of putative tumor suppressor function, describing for the first time a unique gene fusion setting involving both fusion partners with implications for therapeutic targeting. Utilizing heterologous cell model systems and in vivo mouse models, we found MYB-QKI and QKI-RAF1 are capable of driving oncogenesis. Furthermore, MYB-QKI is a specific driver mutation defining angiocentric gliomas and mediates tumorigenesis via a tri-partite mechanism: (1)MYB oncogenic activation via truncation, (2)rearrangement led enhancer translocation that drives MYB-QKI expression and (3)LOH of QKI tumor suppressor. In contrast, QKI-RAF1 drives some pilocytic astrocytomas via aberrant activation of the MAPK pathway in a QKI-dimerization dependent manner. We also found differential response to RAF targeted therapy in QKI-RAF1, compared to BRAF fusions in PLGGs, due to QKI-mediated dimerization. Hence, our study highlights distinct roles for the same gene, QKI in supporting the oncogenic functions of MYB and RAF1 in different PLGG-gene fusions. Overall, our study has uncovered distinct molecular mechanisms associated with different QKI gene fusions in PLGGs. We show that MYB-QKI is specific to angiocentric gliomas and mediates a unique oncogenic program, and with QKI-RAF1 we demonstrate how mutational context guides differential response to targeted therapy. Therefore, our study has important clinical implications on molecular diagnostics and targeted therapy for these rather understudied class of childhood brain tumors. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Cell & Molecular Biology This dissertation is available at ScholarlyCommons: http://repository.upenn. edu/edissertations/1782 First Advisor Adam C. Resnick
Partial characterization of the X chromosome of Diuraphis noxia (Hemiptera: Aphididae)

We present the first sequencing results after separation of the X chromosome of Diuraphis noxia (Kurdjumov) (Hemiptera: Aphididae), the largest known X chromosome described to date, using flow cytometry. The X chromosome of D. noxia is 0.1824 pg (1C) and an estimated 178.4 Mb (1C) in size. Mapping confirmed that the X chromosome contains 13,799 protein coding genes, but with a slight bias towards GC richness when compared to the complete D. noxia genome.
The usage of social media for higher education purposes

of technology and positive the teaching process, use of technology can be by numerous factors, the study is conducted to the current status of teachers' usage of social media in higher education and detection of the usage of social media in higher The questionnaire on the Unified Theory of Acceptance and Use of Technology model as a theoretical framework, on a of the Algebra University College in Applied the research conducted the higher education the of with the media but also with factors that influence the willingness of higher education teachers to use social media for the higher education purposes.