Miracle-dz/UniFAR-FTUs huggingface dataset:
Dosage Compensation in Drosophila: Its Canonical and Non-Canonical Mechanisms

Dosage compensation equalizes gene expression in a single male X chromosome with that in the pairs of autosomes and female X chromosomes. In the fruit fly Drosophila, canonical dosage compensation is implemented by the male-specific lethal (MSL) complex functioning in all male somatic cells. This complex contains acetyl transferase males absent on the first (MOF), which performs H4K16 hyperacetylation specifically in the male X chromosome, thus facilitating transcription of the X-linked genes. However, accumulating evidence points to an existence of additional, non-canonical dosage compensation mechanisms operating in somatic and germline cells. In this review, we discuss current advances in the understanding of both canonical and non-canonical mechanisms of dosage compensation in Drosophila.
Orders on free groups induced by oriented words

For every finite rank k, k>1, we explicitly construct (2k)! left orders on the free group F_k of rank k. Each order is induced by a word of length 2k in which each generator of F_k and its inverse appear exactly once. For each of these (2k)! words we define a real valued function on F_k, which is shown to be a quasi-character with small relative defect and which is used as a weight function to define the corresponding order (the elements of F_k which evaluate to positive real numbers are declared positive in the group). Some of the orders we define on F_k are extensions of the usual lexicographic order on the positive monoid and some have word reversible positive cones. We characterize the defining words leading to orders of either of these two types.
Tracking the Subsolar Bow Shock and Magnetopause

Global magnetohydrodynamic models predict that plasma velocities vary almost linearly from 0 km s−1 at the nose of the stationary magnetopause on the stagnation streamline to a limiting value of 0.25 VSW for high solar wind Alfvénic Mach numbers at the nose of the bow shock, where VSW is the solar wind velocity. This paper presents a proof‐of‐concept study showing how two‐point measurements of the plasma velocity in the subsolar magnetosheath can be used to determine gradients in the plasma velocity and consequently the steady‐state or slowly moving locations of both the nose of the magnetopause and the nose of the bow shock. The results may be of use to those binning magnetosheath observations to develop empirical models, those testing models for magnetopause erosion or deposition in response to magnetic reconnection, and those determining the stand‐off distance of the bow shock as a function of solar wind conditions.
Synthesis and Characterization of Reproducible Linseed Oil-Loaded Silica Nanoparticles with Potential Use as Oxygen Scavengers in Active Packaging

Commercially available oxygen scavengers used to prevent lipid autoxidation, microbial growth and enzymatic browning in food products present several issues, which include the usage of metals and their moisture dependence to work properly. We present the synthesis and characterization of a moisture-independent oil-based oxygen scavenging system comprised of linseed oil and silica nanoparticles. The system was synthesized via sol-gel chemistry and was characterized using morphological analysis (SEM, AFM, TEM, and N2 adsorption/desorption), oil-loading analysis (TGA), and surface analysis (ζ-potential and ATR-FTIR). Performance of the system was evaluated through headspace measurements and reproducibility of synthetic procedure was verified using six replicates. Nanoparticles showed the desired spherical shape with a diameter of (122.7 ± 42.7 nm) and mesoporosity (pore diameter = 3.66 ± 0.08 nm), with an encapsulation efficiency of 33.9 ± 1.5% and a highly negative ζ-potential (−56.1 ± 1.2 mV) in basic solution. Performance of the system showed a promising high value for oxygen absorption of 25.8 ± 4.5 mL O2/g of encapsulated oil (8.3 ± 1.5 mL O2/g of nanocapsules) through a moisture independent mechanism, which suggests that the synthesized system can be used as an oxygen scavenger in dry atmosphere conditions.
An Improved Phased Array Ultrasonic Probe Using 0.91Pb(Zn1/3Nb2/3)O3–0.09PbTiO3 Single Crystal

A 96-channel phased array probe for echocardiography using a single-plate, 0.91Pb(Zn1/3Nb2/3)O3–0.09PbTiO3 (PZNT 91/9) single-crystal transducer with dimensions of 14×20 mm has been fabricated to realize greater sensitivity and broader bandwidth properties. The center frequency of the probe, 3.5 MHz, was selected to cover the bandwidths of two conventional lead zirconate titanate (PZT) ceramic probes with center frequencies of 2.5 and 3.75 MHz. A solder paste was used to connect a flexible printed circuit to the PZNT 91/9 transducer. The echo amplitude of the PZNT 91/9 probe is about 6 dB higher than that of the two PZT probes, and the fractional bandwidths are 30 and 25 percentage points wider, respectively. The B-mode image quality of the PZNT 91/9 probe is comparable to that of the two PZT probes, and the Doppler sensitivity of the PZNT 91/9 probe is almost equal to that of the 2.5 MHz PZT probe, which means that the PZNT 91/9 probe matches both the penetration of the 2.5 MHz PZT probe and the resolution of 3.75 MHz PZT probe.
A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education

Emotional intelligence is the automatic detection of human emotions using various intelligent methods. Several studies have been conducted on emotional intelligence, and only a few have been adopted in education. Detecting student emotions can significantly increase productivity and improve the education process. This paper proposes a new deep learning method to detect student emotions. The main aim of this paper is to map the relationship between teaching practices and student learning based on emotional impact. Facial recognition algorithms extract helpful information from online platforms as image classification techniques are applied to detect the emotions of student and/or teacher faces. As part of this work, two deep learning models are compared according to their performance. Promising results are achieved using both techniques, as presented in the Experimental Results Section. For validation of the proposed system, an online course with students is used; the findings suggest that this technique operates well. Based on emotional analysis, several deep learning techniques are applied to train and test the emotion classification process. Transfer learning for a pre-trained deep neural network is used as well to increase the accuracy of the emotion classification stage. The obtained results show that the performance of the proposed method is promising using both techniques, as presented in the Experimental Results Section.
Modeling Transition Probabilities for Loan States Using a Bayesian Hierarchical Model

MODELING TRANSITION PROBABILITIES FOR LOAN STATES USING A BAYESIAN HIERARCHICAL MODEL Rebecca M. Richardson Department of Statistics Master of Science A Markov Chain model can be used to model loan defaults because loans move through delinquency states as the borrower fails to make monthly payments. The transition matrix contains in each location a probability that a borrower in a given state one month moves to the possible delinquency states the next month. In order to use this model, it is necessary to know the transition probabilities, which are unknown quantities. A Bayesian hierarchical model is postulated because there may not be sufficient data for some rare transition probabilities. Using a hierarchical model, similarities between types or families of loans can be taken advantage of to improve estimation, especially for those probabilities with little associated data. The transition probabilities are estimated using MCMC and the Metropolis-Hastings algorithm. ACKNOWLEDGEMENTS Thanks to my parents, who encouraged me every step of the way, and my husband who pushed me when I needed it. CONTENTS CHAPTER
Cytoskeletal Mechanics: Models and Measurements in Cell Mechanics

1. Introduction and the biological basis for cell mechanics Mohammad R. K. Mofrad and Roger Kamm 2. Experimental measurements of intracellular mechanics Paul Janmey and Christoph Schmidt 3. The cytoskeleton as a soft glassy material Jeffrey Fredberg and Ben Fabry 4. Continuum elastic or viscoelastic models for the cell Mohammad R. K. Mofrad, Helene Karcher and Roger Kamm 5. Multiphasic models of cell mechanics Farshid Guuilak, Mansoor A. Haider, Lori A. Setton, Tod A. Laursen and Frank P. T. Baaijens 6. Models of cytoskeletal mechanics based on tensegrity Dimitrije Stamenovic 7. Cells, gels and mechanics Gerald H. Pollack 8. Polymer-based models of cytoskeletal networks F. C. MacKintosh 9. Cell dynamics and the actin cytoskeleton James L. McGrath and C. Forbes Dewey, Jr 10. Active cellular motion: continuum theories and models Marc Herant and Micah Dembo 11. Summary Mohammad R. K. Mofrad and Roger Kamm.
Electromagnetic Waves Fluctuations in Random Fractal Media

Scaling in the fluctuations structure of electromagnetic radiation propagating through the turbulent media was investigated. It is found out that the radiation in this case obtains stable fractal properties. Numerical simulation shows that fractal dimension of the diffracted radiation intensity and phase coincides with that of the screen. In experiments electromagnetic waves intensity fluctuations demonstrate fractal properties. Laser beams propagating through the random media manifest fractal properties stably in random displacements of beam "center of gravity". In this case fractality is more distinctly observed when characteristic sizes of turbulent inhomogeneities exceed laser beam diameter. It is shown that the Hurst parameter and scaling is connected with the meteorological conditions of the path. (5 pages)
Red-diode-clad-pumped Er3+/Dy3+ codoped ZrF4 fiber: A promising mid-infrared laser platform.

We report, for the first time, to the best of our knowledge, mid-infrared (mid-IR) laser generation, from a red-diode-clad-pumped Er3+/Dy3+ codoped ZrF4 fiber laser. A free-running laser at ∼3.4 µm, mainly from the 4F9/2→4I9/2 transition of Er3+, directly excited by a 659-nm laser diodehas been achieved at room temperature with a maximum power of 0.8 W and 8.8% slope efficiency. In this system, the long-lived 4I11/2 and 4I13/2 states are rapidly depopulated by energy transfer to the codoped Dy3+ ions and energy transfer upconversion between the Er3+ ions, resulting in the accelerated recycling of ions. Additionally, the free-running dual-wavelength operation state at ∼3.3 and ∼3.5 µm is also observed, producing a total maximum power of 0.95 W with 10.7% slope efficiency, representing the first watt-class output from a diode-pumped rare-earth-doped fiber laser far beyond 3 µm. By employing a diffraction grating, continuous spectral tuning across the 642-nm range from 3053.9 to 3695.9 nm has been demonstrated. The proposed scheme provides, to the best of our knowledge, a promising new platform for laser generation in the mid-IR region of 3-4 µm.
SCAFG: Classifying Single Cell Types Based on an Adaptive Threshold Fusion Graph Convolution Network

Single-cell RNA sequencing (scRNA-seq) technology has been a significant direction for single-cell research due to its high accuracy and specificity, as it enables unbiased high-throughput studies with minimal sample sizes. The continuous improvement of scRNA-seq technology has promoted parallel research on single-cell multi-omics. Instead of sequencing bulk cells, analyzing single cells inspires greater discovery power for detecting novel genes without prior knowledge of sequence information and with greater sensitivity when quantifying rare variants and transcripts. However, current analyses of scRNA-seq data are usually carried out with unsupervised methods, which cannot take advantage of the prior distribution and structural features of the data. To solve this problem, we propose the SCAFG (Classifying Single Cell Types Based on an Adaptive Threshold Fusion Graph Convolution Network), a semi-supervised single-cell classification model that adaptively fuses cell-to-cell correlation matrices under various thresholds according to the distribution of cells. We tested the performance of the SCAFG in identifying cell types on diverse real scRNA-seq data; then, we compared the SCAFG with other commonly used semi-supervised algorithms, and it was shown that the SCAFG can classify single-cell data with a higher accuracy.
Fast and robust solution methods for the water quality equations

This thesis discusses the use of fast and robust solution methods for advection-dominated advection-diffusion-reaction equations coming from water quality problems. Therefore we look at fluxlimiters by the FCT method in combination with the local-theta approach to increase both the accuracy and the efficiency. The discretized equations (by the FVM method) are solved by means of iterative methods.
Mycotoxins Contamination in Rice: Analytical Methods, Occurrence and Detoxification Strategies

The prevalence of mycotoxins in the environment is associated with potential crop contamination, which results in an unavoidable increase in human exposure. Rice, being the second most consumed cereal worldwide, constitutes an important source of potential contamination by mycotoxins. Due to the increasing number of notifications reported, and the occurrence of mycotoxins at levels above the legislated limits, this work intends to compile the most relevant studies and review the main methods used in the detection and quantification of these compounds in rice. The aflatoxins and ochratoxin A are the predominant mycotoxins detected in rice grain and these data reveal the importance of adopting safety storage practices that prevent the growth of producing fungi from the Aspergillus genus along all the rice chain. Immunoaffinity columns (IAC) and QuECHERS are the preferred methods for extraction and purification and HPLC-MS/MS is preferred for quantification purposes. Further investigation is still required to establish the real exposition of these contaminants, as well as the consequences and possible synergistic effects due to the co-occurrence of mycotoxins and also for emergent and masked mycotoxins.
On the Design of Backscatter Communications With Retransmissions

To support massive connections of Internet of Things (IoT) devices, backscatter communication has been proposed as a promising technique. However, its transmission reliability cannot be guaranteed due to the lack of error protection. To solve this problem, the optimization design of backscatter communications with retransmissions is studied in this letter. First, its analytical error performance is derived based on finite blocklength data rate theory. Second, the resource allocation and the retransmission strategy are jointly optimized to improve transmission reliability with low costs. Finally, the simulation results are provided to verify the performance gains of our proposed scheme.
A Data-Reconstructed Fractional Volatility Model

Based on criteria of mathematical simplicity and consistency with empirical market data, a stochastic volatility model is constructed, the volatility process being driven by fractional noise. Price return statistics and asymptotic behavior are derived from the model and compared with data. Deviations from Black-Scholes and a new option pricing formula are also obtained.
Testing of high speed ground reaction force treadmill for kinetic analysis for running in static and dynamic loading conditions

Chairperson: Matthew Bundle This thesis proposal describes the design, fabrication, and testing of a high-speed force treadmill capable of measuring the vertical and horizontal ground reaction forces imparted to the bed during the stance phase of human running. Natural frequency, crosstalk, linearity, use of aluminum line shaft with flexible couplings, center of pressures, and comparison to over-ground running were investigated. The natural frequency of the treadmill bed was 113 Hz achieved in part through the use of the line shaft to remove the mass of the motor (36.8 kg) with negligible dissipation of imparted force to the treadmill. The linearity test results showed a high linearity of the force treadmill up to expected forces of human sprinting as well as minimal crosstalk. The center of pressure accuracy was extremely high using measured vertical forces to determine the point of force application. Ground reaction force waveforms in both the horizontal and vertical directions for speeds up to 8.1 ms on the high speed force treadmill were nearly identical to the established methods of in ground force plates in both magnitude of force and duration of contact for same speeds by same subject. The high speed force treadmill demonstrated acceptable accuracy for ground reaction forces such that it can be used for a variety of research gait analysis applications up to the limits of human running speed.
A modified case-control approach to identifying relationships between diseases

In addition, in order to establish causation in observational studies, the time sequence of two events must be known with some certainty. This requirement, although logical, is not easily fulfilled, particularly in a study involving many diseases. In the past, studies have either identified associations between diseases without regard to the time order of those diseases or have evaluated relationships based on several possible time orderings without attempting to identify one order as correct. Relationships between two diseases can be of the form:
An Improved Sea Spray-Induced Heat Flux Algorithm and Its Application in the Case Study of Typhoon Mangkhut (2018)

The prediction of tropical cyclone (TC) intensity has been a lasting challenge. Numerical models often underestimate the intensity of strong TCs. Accurately describing the air–sea heat flux is essential for improving the simulation of TCs. It is widely accepted that sea spray has a nonnegligible effect on the heat transfer between the atmosphere and the ocean. However, the commonly used sea spray-induced heat flux algorithms have poor applicability under high wind speeds, and it is difficult to apply these algorithms to models to forecast TCs. In this study, we proposed an improved sea spray-induced heat flux algorithm based on the FASTEX dataset. This improved algorithm performs much better under high wind speed conditions than the commonly used algorithms and can be used in a coupled numerical model. The addition of sea spray-induced heat fluxes noticeably enhances the total air–sea heat fluxes and allows more energy to be transferred from the ocean to the lower atmosphere. In the simulation of TCs, the addition of sea spray-induced heat fluxes significantly improves the simulation of TC intensity and makes the low-pressure structure and wind field structure more fully developed in the horizontal direction.
Fabrication of Concave Microwells and Their Applications in Micro-Tissue Engineering: A Review

At present, there is an increasing need to mimic the in vivo micro-environment in the culture of cells and tissues in micro-tissue engineering. Concave microwells are becoming increasingly popular since they can provide a micro-environment that is closer to the in vivo environment compared to traditional microwells, which can facilitate the culture of cells and tissues. Here, we will summarize the fabrication methods of concave microwells, as well as their applications in micro-tissue engineering. The fabrication methods of concave microwells include traditional methods, such as lithography and etching, thermal reflow of photoresist, laser ablation, precision-computerized numerical control (CNC) milling, and emerging technologies, such as surface tension methods, the deformation of soft membranes, 3D printing, the molding of microbeads, air bubbles, and frozen droplets. The fabrication of concave microwells is transferring from professional microfabrication labs to common biochemical labs to facilitate their applications and provide convenience for users. Concave microwells have mostly been used in organ-on-a-chip models, including the formation and culture of 3D cell aggregates (spheroids, organoids, and embryoids). Researchers have also used microwells to study the influence of substrate topology on cellular behaviors. We will briefly review their applications in different aspects of micro-tissue engineering and discuss the further applications of concave microwells. We believe that building multiorgan-on-a-chip by 3D cell aggregates of different cell lines will be a popular application of concave microwells, while integrating physiologically relevant molecular analyses with the 3D culture platform will be another popular application in the near future. Furthermore, 3D cell aggregates from these biosystems will find more applications in drug screening and xenogeneic implantation.
Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain

Smartphone-based ecological momentary assessment (EMA) methods are widely used for data collection and monitoring in healthcare but their uptake clinically has been limited. Low back pain, a condition with limited effective treatments, has the potential to benefit from EMA. This study aimed to (i) determine the feasibility of collecting pain and function data using smartphone-based EMA, (ii) examine pain data collected using EMA compared to traditional methods, (iii) characterize individuals’ progress in relation to pain and function, and (iv) investigate the appropriation of the method. Our results showed that an individual’s ‘pain intensity index’ provided a measure of the burden of their low back pain, which differed from but complemented traditional ‘change in pain intensity’ measures. We found significant variations in the pain and function over the course of an individual’s back pain that was not captured by the cohort’s mean scores, the approach currently used as the gold standard in clinical trials. The EMA method was highly acceptable to the participants, and the Model of Technology Appropriation provided information on technology adoption. This study highlights the potential of the smartphone-based EMA method for enhancing the collection of outcome data and providing a personalized approach to the management of low back pain.