Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of Particle Physics Models with Implication to Neutrino Mass and Dark Matter Phenomenology in Light of Recent Data

The presence of a mysterious form of matter constituting 26.8% of the total energy budget of the present universe, is confirmed indirectly by, rotational velocity of spiral galaxies, gravitational lensing and collision of galaxies in bullet cluster. This matter is called as dark matter (DM), because it does not show electromagnetic interaction. The standard model(SM) of particle physics which is a successful theory, explaining many physical phenomena, does not include a particle candidate of DM. It also unable to explain the smallness of neutrino mass as confirmed by neutrino oscillation experiments. In this thesis we explore the viable scenarios of non-zero neutrino mass and DM in beyond the standard model(BSM) frameworks.
Specific Fluorescent Probes for Imaging DNA in Cell-Free Solution and in Mitochondria in Living Cells

New styryl dyes consisting of N-methylpyridine or N-methylquinoline scaffolds were synthesized, and their binding affinities for DNA in cell-free solution were studied. The replacement of heterocyclic residue from the pyridine to quinoline group as well as variation in the phenyl part strongly influenced their binding modes, binding affinities, and spectroscopic responses. Biological experiments showed the low toxicity of the obtained dyes and their applicability as selective dyes for mitochondria in living cells.
Experimental study on shear lag of curved box girder under earthquake excitation

A plexiglass cantilever curved box girder model is built to investigate shear lag effect distribution law in curved box girder. Firstly the finite element model is established based on ANSYS. Secondly the testing is performed on earthquake shaking table test under different earthquake excitations. Finally, the comparative analysis between the theoretical and experimental results is performed. From the above results, it is shown that an evident shear lag effect occur at the junction between web and flange of the cantilever curved box girder model under simulated earthquake excitations, and under the same condition, different kinds of earthquake excitations have limited influence on shear lag effect in curved box girder.
EEG Based Thought-to-Text Translation Via Deep Learning

Major contributors to impairment are neurological conditions such epilepsy, Alzheimer's disease, multiple sclerosis, Parkinson's disease, and others. These neurodegenerative conditions are life-altering, and those afflicted with them must fight a new battle every day. This manuscript presents the implementation of a Thought-to-Text Conversion BCI system. The system employs a joint CNN-LSTM deep neural network to learn high-level features from MI-EEG signals. To eliminate various artifacts from EEG signals, pre-processing is employed, such as utilizing a band-pass filter. Although an Auto-encoder layer is included, it has been found to decrease efficiency. The XGBoost Classifier is utilized to classify EEG signals into five EEG imagery tasks. This Deep Learning model is then pickled using Python and deployed to the server. The server prompts the development of a GUI that maps the input EEG signals to corresponding alphabets. The Neural Network is trained on multiple open-sourced EEG data-sets, utilizing various optimization algorithms to achieve high system accuracy and desirable efficiency for real-time applications. The textual output obtained can be utilized to aid in the rehabilitation of paralysis and stroke patients. The proposed hybrid model achieved an accuracy of 96.89% on testing data.while taking approximately 6 seconds per letter to be typed on the GUI screen.
Acute Toxic Effects of levamisole and Ivermectin in Mice

The study's objectives were to investigate the acute toxicity and related biochemical effects of levamisole and ivermectin in mice. The 24 h oral median lethal dose (LD50) of levamisole was determined by the up-and-down method and was 155.5 mg/ kg of body weight. The treated mice showed signs of acute poisoning represented by excessive grooming, lacrimation, piloerection, straub tail, tachycardia, bulged eyes, tremor, convulsion and finally death within 24 h of treatment. The approximate lethal dose (ALD) of levamisole was 368 mg/kg, and the mice showed signs of poisoning similar to the previous signs of poisoning within 24 h of treatment. The 24 h oral LD50 of ivermectin was 115.2 mg/kg and the mice showed acute signs of poisoning, represented by excessive grooming, lacrimation, closed eyelids, piloerection, tachycardia, rapid respiration, depression, flat body appearance, paralysis and finally death within 24 h of treatment, while the approximate lethal dose of ivermectin was 121 mg/kg and also with the presence of severe poisoning signs as mentioned before. Non-lethal toxic doses of levamisole at 100 and 150 mg/kg and ivermectin at 75 and 100 mg/kg led to significant blood biochemical changes after 24 h of treatment, represented by a significant increase in the activity of the enzymes alkaline phosphatase (ALP), lactate dehydrogenase (LDH), glutamate dehydrogenase (GDH), and a significantly increased total bilirubin concentration in the blood plasma of mice. These results proved the presence of acute toxicity and biochemical effects of both anthelmintics levamisole and ivermectin even though they have wide safety margins.
Laryngocele: Report of two rare cases and review of the literature

Laryngocele is a rare clinical condition characterized by an abnormal dilation of the laryngeal saccule. The present study focused on two separate cases of diagnosed patients. The first patient suffered from internal laryngocele and complained of hoarseness for almost 1 year. Plasma was used to treat the internal laryngocele and the outcomes were satisfying. The patient did not undergo any tracheostomy due to previous endoscopic surgery. The second patient included in the present study was diagnosed with mixed laryngocele and complained of swelling on the left side of the upper aspect of the neck with considerable pain for >1 month. The patient was prepped for excision by an external transcervical technique under general anesthesia. None of the two patients had any recurrence or other changes during follow-up. The purpose of reporting these two cases of laryngocele was to increase awareness of this condition. Surgery is still the first-line treatment for diagnosed cases, but with the advent of new microscopic techniques, the use of plasma in an inter-pharynx setting has become more common. The results observed after using plasma to treat one internal laryngocele may be relevant to better understanding the application of this method and confirm that it may be a new suitable approach to treat this condition.
Broadened waveguide laser structures at 780 nm

Two AlGaAs/GaAs broadened waveguide laser structures, one asymmetric, one nearly symmetric, were designed for high power at about 780 nm. The design concept is based on low losses and higher gain for the fundamental mode with higher losses and lower gain for higher-order modes. To achieve these results, the positions of the quantum wells, thicknesses of the cladding layers, doping profiles, and the compositions of all the layers are carefully chosen. The structures are designed to have a loss of about 0.5/cm for the TE0 mode and more than 5 /cm for higher order modes for both structures. The asymmetric structure has a lower threshold current density (~750 A/cm2) and a higher slope (about 0.9 W/A) of the light-current curve compared to the symmetric structure. Increased L-I slope for the asymmetric structure results mainly from increased hole injection efficiency because the quantum wells are close to the p-side. Ridge-guide lasers fabricated with the asymmetric structure produced greater than 350 mW at 25°C. The beam divergence of the asymmetric structure was 6° × 14°.
Effect of Pre and Postoperative Nursing Intervention on Pain and Postoperative Complications among Patients undergoing Hip Replacement

: Hip replacement is a common surgical treatment in orthopedics. The successful recovery post hip replacement surgery requires not only proper surgical technique but also effective pre and postoperative nursing care which may be of great value in increasing level of post-operative comfort and reducing or preventing the occurrence of postoperative complications. Purpose: To determine the effect of pre and postoperative nursing intervention on pain and postoperative complications among patients undergoing hip replacement. Setting: The study was conducted at orthopedic departments at Menoufia University and Shebin El-Kom teaching hospitals. Sampling: A consecutive sample of 80 adult patients who were planned for hip replacement surgery was assigned randomly and alternatively into two equal groups, 40 patients for each group. Instruments: Three instruments were used for data collection: Structured interview questionnaire, visual analogue pain scale and observational checklist for performance and complications. Results: The majority of the study and control group (92.5%, 90% respectively) had worst pain level at pre intervention, while 65% of study group compared to 20% of control group had no pain at follow up period. There was statistically significant reductions of postoperative complications occurrence among study group compared to control group at postoperative period. Conclusion: pre and post postoperative nursing care had a positive impact on reducing patient’s pain intensity and complications after hip replacement among study group than control group. Recommendation: Supervised health teaching regarding pre and postoperative care should be given among hip replacement patients to reduce pain and postoperative complications.
The Mediation Role of Peer Effects, Test Anxiety and Academic Motivation in Relationship Between Intelligence and Self Efficacy Among University Students

The primary aim of this paper is to analyze the mediation role of peer effects, test anxiety, and academic motivation in the relationship between intelligence and selfefficacy among UTAS university students in Oman. A sample size (N = 477) of university students used as the study participants. Moreover, there were 150 males (31.4%) and 327 females (68.6%) in the participant ratios. This research used a deductive research approach to test the 4 study hypotheses. Self-efficacy was accessed using the General Self-Efficacy scale (GSES) tool. GSES measures selfefficacy’s self-perception to self-report questionnaires that respond to the hypothesis that analyzes the coping abilities of various research participants. The data was analyzed using SPSS and AMOS software to provide the output for the hypothesis testing. The four hypotheses were then analyzed using the SPSS AMOS software, the mediation phase of structuring equations. The interactions are as follows: academic motivation and intelligence (estimate = 0.182, S.E = 0.052, P-value = 0.00<0.05) and peer effects and test anxiety (estimate = 0.055, S.E = 0.023, P-value = 0.016>0.05). Thus, mediation has an objective role on peer effects, test anxiety and academic motivation in the connection between self-efficacy and intelligence among university students.
Axial Plane Nanoscale Measurements of Cardiomyocytes Based on Microspheres

After eons of evolution, biological systems have developed excellent actuating methodology in micro-nano scale, which inspired the design and development of advanced microrobots. Cardiomyocytes have received extensive attention following the development of bio-syncretic robots in terms of its spontaneous contraction and high energy efficiency. However, the multipoint, high-precision synchronized, and comprehensive acquisition of the axial motion parameters of cardiomyocytes still constitutes the major factor hindering the development of quantitative control methods for bio-syncretic robots. Herein, off-focus imaging method was proposed to quantify the axial beating of cardiomyocyte. The spontaneously beating of cardiomyocytes were quantitative analyzed based on the combination of cross-correlation and off-focusing imaging. We also validated the use of the proposed SiO2 microspheres in cardiotoxicity test. Following the administration of isoproterenol, cardiomyocytes exhibited positive inotropic and chronotropic effects. Finally, we analyzed the beating responses of individual cardiomyocytes at different locations, and we validated the feasibility of multipoint, synchronized measurements. In the future, this study can also be extended to the analysis of the motion coupling relationship between individual cardiomyocytes and cardiomyocyte clusters, thus providing a data acquisition platform for the dynamic analysis and modeling of bio-syncretic robot actuators.
Effect of Temporal Acquisition Parameters on the Image Quality of Ultrasound Axial Strain Time-constant Elastograms

Effect of Temporal Acquisition Parameters on the Image Quality of Ultrasound Axial Strain Time-constant Elastograms. (August 2011) Joshua Kavunkal Varghese, B.S., Texas A&M University Chair of Advisory Committee: Dr. Raffaella Righetti Recent developments in ultrasound elastography have suggested the possibility of using elastographic methods to estimate the temporal mechanical properties of complex tissues. In this context, elastographic methods to image the axial strain time constant (TC) have been developed. The axial strain TC is a parameter that is related to the viscoelastic and poroelastic behavior of tissues. Estimation of this parameter can be done using curve fitting methods. However, the effect of temporal ultrasonic acquisition parameters, such as window of observation, acquisition rate, and input noise, on the image quality of the resultant TC elastograms has not been investigated yet. Elucidating such effects could be useful for diagnostic applications. This work explores the effects of varying windows of observation, acquisition rate, and input noise on the image quality (accuracy and signal-to-noise ratio (SNR)) of axial strain TC estimates and elastograms using a previously developed simulation model. By varying the amount of data collected as a percentage of the expected TC, the algorithms were able to compute a minimum threshold collection time for an accurate TC estimation as a percentage of the expected TC. The effect of acquisition parameters
Stress mindset, coping strategies, and well-being of secondary students in Singapore during the COVID-19 pandemic

Abstract The present study explored the association between stress mindset and well-being of students during the Coronavirus Disease 2019 pandemic. The study also sought to examine how the relationship between students’ stress-mindset and well-being can be mediated by students’ coping strategies. The study applied a cross-sectional survey design, with secondary students (N = 617) from Singapore as participants. The results of parallel mediation analyses suggest that students who endorse a stress-is-enhancing mindset also tend to apply engagement coping strategies and that the use of such coping strategies serve as a potential mediator of the relationship between the students’ stress-is-enhancing mindset and well-being. The stress-is-debilitating mindset was found to have a positive relationship with depressive symptoms; this relationship was not significantly mediated by coping. The findings suggest that endorsing a stress-is-enhancing mindset, along with the use of engagement coping, may serve as a protective factor to promote adolescents’ well-being when experiencing high stress.
A coupled adjoint method for optimal design in fluid-structure interaction problems with large displacements

Computational Fluid-Structure Interaction (FSI) methods have reached a significant level of maturity which has led to their incorporation into the analysis stage of industrial applications. However, optimising the structural and/or the aerodynamic performance in highly non-linear coupled FSI problems remains a challenging task, due to the high computational cost of evaluating the functions in this problem and their gradients. Adjoint methods have shown to be an efficient methodology for this latter task, as they can compute sensitivities with a computational cost independent of the number of design variables. On the other hand, their implementation is complex, particularly when the linearisation of the system equations is convoluted. In this thesis, we develop a novel technique for the evaluation of the coupled adjoint problem. It is based on the consistent application of Algorithmic Differentiation to the fixed-point iterators of the subproblems. This approach makes the computation of the adjoint independent from the solution methods employed for the primal problem, and overcomes the usual limitation for most realistic applications, which is the need for an explicit construction of the analytic Jacobian of the coupled problem. The method poses no restrictions to the non-linearity of the physics in either the fluid or structural field, and it is amenable to partitioned solution methods for the adjoint equations. We have implemented this method in the open-source SU2 suite, by incorporating structural analysis and FSI capabilities and combining them with the available AD tool for the solution of the coupled adjoint. Finally, the validity of the implementations is assessed through a number of studies. We test the structural and FSI solvers using commercial codes and benchmark cases. Then, we demonstrate the accuracy of the sensitivities obtained using the proposed method. The advantages of our adjoint method for gradient-based optimisation are finally shown for a range of cases, from structural-only to fully coupled optimal design problems.
AI-based SoS performance classification for resilience reaction

This works provides a comprehensive performance evaluation approach for system-of-systems (SoS). Various attributes are extracted from different level and various aspects, such as graph-based communication quality, dynamic response of physical component systems (PCSs) and mission-oriented features of management component systems (MCSs). AI-based classifier is employed thereafter based on the performance feature construction, to classify SoS performance into 5 status, Normal, Robust, Fault-tolerance, Resilience and Breakdown, which shows the necessity of a resilience SoS reaction. The effectiveness of the performance feature construction is verified by the high accuracy of training set in the simulation.
Host Range and Loop-Mediated Isothermal Amplification Detection of Globisporangium sylvaticum from Guizhou, China

Globisporangium, especially G. sylvaticum, causes devastating root rot, blight, and other diseases in various species of cash crops. To investigate the distribution and host range of G. sylvaticum in Guizhou, a suitable habitat for this pathogen, we collected 156 root-diseased samples, isolated the pathogens, and found that G. sylvaticum is widespread and has eleven host plants, including four novel hosts. Furthermore, to effectively identify G. sylvaticum, we developed a simple and dependable method based on loop-mediated isothermal amplification (LAMP), which used a primer set designed from the internal transcribed spacer sequences with high specificity and sensitivity of 1 pg/μL. Additionally, to perform field identification, we used the “Plant-LAMP” method with crude DNA extraction to detect the pathogen in 45 root samples from nine species of plants. Our results showed that this method could effectively detect G. sylvaticum in diseased roots. Therefore, our findings not only enrich existing research on the diversity of pathogenic Globisporangium in Guizhou but also present an efficient LAMP field detection method that could significantly contribute to plant disease management and prevention.
Loss of ANCO1 Expression Regulates Chromatin Accessibility and Drives Progression of Early-Stage Triple-Negative Breast Cancer

Mutations in the gene ankyrin repeat domain containing 11 (ANKRD11/ANCO1) play a role in neurodegenerative disorders, and its loss of heterozygosity and low expression are seen in some cancers. Here, we show that low ANCO1 mRNA and protein expression levels are prognostic markers for poor clinical outcomes in breast cancer and that loss of nuclear ANCO1 protein expression predicts lower overall survival of patients with triple-negative breast cancer (TNBC). Knockdown of ANCO1 in early-stage TNBC cells led to aneuploidy, cellular senescence, and enhanced invasion in a 3D matrix. The presence of a subpopulation of ANCO1-depleted cells enabled invasion of the overall cell population in vitro and they converted more rapidly to invasive lesions in a xenograft mouse model. In ANCO1-depleted cells, ChIP-seq analysis showed a global increase in H3K27Ac signals that were enriched for AP-1, TEAD, STAT3, and NFκB motifs. ANCO1-regulated H3K27Ac peaks had a significantly higher overlap with known breast cancer enhancers compared to ANCO1-independent ones. H3K27Ac engagement was associated with transcriptional activation of genes in the PI3K-AKT, epithelial–mesenchymal transition (EMT), and senescence pathways. In conclusion, ANCO1 has hallmarks of a tumor suppressor whose loss of expression activates breast-cancer-specific enhancers and oncogenic pathways that can accelerate the early-stage progression of breast cancer.
Advances in Theory and Applicability of Stochastic Network Calculus

Stochastic Network Calculus (SNC) emerged from two branches in the late 90s: the theory of effective bandwidths and its predecessor the Deterministic Network Calculus (DNC). As such SNC’s goal is to analyze queueing networks and support their design and control. In contrast to queueing theory, which strives for similar goals, SNC uses in- equalities to circumvent complex situations, such as stochastic dependencies or non-Poisson arrivals. Leaving the objective to compute exact distributions behind, SNC derives stochastic performance bounds. Such a bound would, for example, guarantee a system’s maximal queue length that is violated by a known small prob- ability only. This work includes several contributions towards the theory of SNC. They are sorted into four main contributions: (1) The first chapters give a self-contained introduction to deterministic net- work calculus and its two branches of stochastic extensions. The focus lies on the notion of network operations. They allow to derive the performance bounds and simplifying complex scenarios. (2) The author created the first open-source tool to automate the steps of cal- culating and optimizing MGF-based performance bounds. The tool automatically calculates end-to-end performance bounds, via a symbolic approach. In a second step, this solution is numerically optimized. A modular design allows the user to implement their own functions, like traffic models or analysis methods. (3) The problem of the initial modeling step is addressed with the development of a statistical network calculus. In many applications the properties of included elements are mostly unknown. To that end, assumptions about the underlying processes are made and backed by measurement-based statistical methods. This thesis presents a way to integrate possible modeling errors into the bounds of SNC. As a byproduct a dynamic view on the system is obtained that allows SNC to adapt to non-stationarities. (4) Probabilistic bounds are fundamentally different from deterministic bounds: While deterministic bounds hold for all times of the analyzed system, this is not true for probabilistic bounds. Stochastic bounds, although still valid for every time t, only hold for one time instance at once. Sample path bounds are only achieved by using Boole’s inequality. This thesis presents an alternative method, by adapting the theory of extreme values. (5) A long standing problem of SNC is the construction of stochastic bounds for a window flow controller. The corresponding problem for DNC had been solved over a decade ago, but remained an open problem for SNC. This thesis presents two methods for a successful application of SNC to the window flow controller.