Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Cellular Automata and Lattice Boltzmann Methods to Model Cancer Growth: Analysis of Combination Treatment Outcomes

In Canada it is estimated that 76,600 people will die of cancer in 2014. Cancer, a collection of over 200 diseases, has differences existing between globally, between individuals and overtime in one individual. Treatment options are similarly varied. These differences make selecting the best possible treatment for every type of cancer very challenging. In addition, with no single cure for cancer, treatments are often combined in different ways to form the best overall option. In an attempt to synthesize the properties of these diseases into a collection of common cellular changes, Hanahan and Weinberg proposed “the hallmarks of cancer” – 10 differences between healthy cells and cancer cells, present in almost every cancer. There exists the potential for treatments that are broadly applicable if they reverse these general properties. This work seeks to simulate early cancer growth, specifically looking at these hallmarks, and detect the best combinations of hallmarks to remove in order to stop cancer growth. This hybrid simulation combines a discrete model of cancer cells using cellular automata, with a continuous model of blood flow using lattice Boltzmann methods. Hallmarks relevant during the early growth stages of solid tumour development are simulated using rules in the cellular automata. Hallmarks were removed in pairs, triplets and quadruplets in order to model combination therapy, abstracting drugs that target these properties as the removal of the hallmark from the system. Overall growth of the tumours with “treatments” applied were compared to tumours where all hallmarks were present. It was found that many combinations had no effect on tumour growth. In some cases combinations even increased growth, selecting for the most aggressive hallmarks since weaker hallmarks were unavailable. However, in general, as more treatments were applied, cancer growth decreased. This work is the first to simulate removing hallmarks in pairs, triplets and quadruplets from a model with biologically relevant oxygen flow. It provides a proof of concept that not all combinations are equally effective, even if the individual treatments are effective. This work suggests some combinations should be avoided while others could potentially be beneficial in a variety of diseases.
Self-Medication among Pregnant Women Attending Manhyia Government Hospital

Background: A major determinant to achieving the Sustainable Development Goal (3) is by reducing maternal mortality. Self-medication is one of the many health seeking behaviour that endangers the life of the pregnant woman and impedes maternal health. Methods: The study was conducted to determine the knowledge and practices of self –medication among pregnant women attending Manhyia Government Hospital. The study was a descriptive cross -sectional study. A structured questionnaire was used and 70 pregnant women were selected using the convenience sampling technique. Results: The findings revealed that: treating minor illness (25%) lack of time to consult health professional (15%) and emergency use and cultural belief in efficacy of traditional methods (14%) were some of the main factors that influenced respondents to self- medicate. Even though most respondents (59%) were aware of the effects of self-medication, 41% of the respondents indicated that self-medication could not cause any effect to both mother and fetus. Conclusion: The study suggests that the main factors informing the practice of self-medication were to treat minor illness in pregnancy, to avoid long hours spent in the health facility, for emergency use. Drugs mostly used for such purposes included analgesics and herbal drugs. The study recommends nurses and midwives to enforce health education on the effects of self-medication during antenatal.
W-Nb Co-Doped VO2 Films Realizing near Room-Temperature Transition and Satisfactory Thermochromic Performance for Smart Window

The W-Nb co-doped VO2 films are prepared through hydrothermal method. The effects of the Nb and W dopants are investigated respectively on the phase transition temperature (θc) and optical properties of VO2 by keeping the concentration of partner dopant at 1.0 at. %. The Nb doping induces a reduction of θc at a rate of ~ -13.0 °C per at. % Nb as Nb is less than ~1.5 at. %. For more than 1.5 at. % Nb, the θc shows a slight increase from ~23.0 °C. The W doping leads to a linear decrease of θc with a rate of ~ -17.2 °C per at. % W, more effective in reducing θc than the Nb dopant. However, the heavy W doping results in more serious deterioration of the solar energy modulation (ΔTsol) than the Nb doping. Therefore, taking use of the complementary advantages of W and Nb dopants, the 1.0 at. % W + 1.5 at. % Nb co-doped VO2 realizes the room-temperature transition at 23.0 °C with a satisfactory ΔTsol of ~9.6%, much better than the 1.5 at. % W + 1.0 at. % Nb co-doped which has a θc of ~22.1 °C and ΔTsol of ~5.3%. This work demonstrates the W-Nb co-doping is an effective doping formula in improving the performance of VO2 for smart window applications.
A comparative analysis of the volatility nature of cryptocurrency and JSE market

Despite the rapid growth of developing markets, aided by globalization, comparative studies of cryptocurrency and stock market volatility have focused on the developed markets and neglected developing ones. In this regard, this study compares cryptocurrency volatility with that of the Johannesburg Stock Exchange (JSE), a developing market. GARCH-type models are applied to daily log returns of Bitcoin, Ethereum, and the FTSE/JSE 4O in two ways. Firstly, the models are applied directly; secondly, structural breaks are tested and accounted for in the models. The sample period was from September 18, 2017, to May 27, 2021. The results show higher volatility and higher volatility persistence in cryptocurrency than in the JSE market. They also show that persistence is overestimated for cryptocurrencies when structural breaks are not accounted for. The opposite was true for the JSE.Moreover, the two cryptocurrencies were found to have close to identical volatility plots that differ from that of the JSE. High volatility periods of cryptocurrency also did not coincide with that of JSE and those of JSE did not coincide with the cryptocurrency ones. There is also evidence of an inverse leverage effect in cryptocurrency, which opposes the normal leverage effect of the JSE market.
Boundary observability, controllability and stabilization of linear elastodynamic systems

In 1988 Lions obtained observability and exact controllability results for linear homogeneous isotropic elastodynamic systems [ SIAM Rev., 30 (1988), pp. 1--68]. Applying some new identities we extend his theorems to nonisotropic systems. In 1991 Lagnese obtained uniform stabilizability results for two-dimensional linear homogeneous isotropic systems by applying a somewhat artificial feedback [Nonlinear Anal. , 16 (1991), pp. 35--54]. Then he asked whether analogous results hold for a natural and physically implementable boundary feedback. Using some new identities and applying a method introduced in 1987 by Zuazua and the second author [ J. Math. Pures. Appl. , 69 (1990), pp. 33--54], we give an affirmative answer to this question in all dimensions and also for nonisotropic systems. Moreover, we obtain good decay estimates. Finally, applying a recent general method of uniform stabilization, we construct boundary feedbacks leading to arbitrarily large energy decay rates.
STOP-Bang Score and Prediction of Severity of Obstructive Sleep Apnea in a First Nation Community in Saskatchewan, Canada

The STOP-Bang questionnaire is an easy-to-administer scoring model to screen and identify patients at high risk of obstructive sleep apnea (OSA). However, its diagnostic utility has never been tested with First Nation peoples. The objective was to determine the predictive parameters and the utility of the STOP-Bang questionnaire as an OSA screening tool in a First Nation community in Saskatchewan. The baseline survey of the First Nations Sleep Health Project (FNSHP) was completed between 2018 and 2019. Of the available 233 sleep apnea tests, 215 participants completed the STOP-Bang score questionnaire. A proportional odds ordinal logistic regression analysis was conducted using the total score of the STOP-Bang as the independent variable with equal weight given to each response. Predicted probabilities for each score at cut-off points of the Apnea Hypopnea Index (AHI) were calculated and plotted. To assess the performance of the STOP-Bang questionnaire, sensitivity, specificity, positive predictive values (PPVs), negative predictive values (NPVs), and area under the curve (AUC) were calculated. These data suggest that a STOP-Bang score ≥ 5 will allow healthcare professionals to identify individuals with an increased probability of moderate-to-severe OSA, with high specificity (93.7%) and NPV (91.8%). For the STOP-Bang score cut-off ≥ 3, the sensitivity was 53.1% for all OSA and 72.0% for moderate-to-severe OSA. For the STOP-Bang score cut-off ≥ 3, the specificity was 68.4% for all OSA and 62.6% for moderate-to-severe OSA. The STOP-Bang score was modestly superior to the symptom of loud snoring, or loud snoring plus obesity in this population. Analysis by sex suggested that a STOP-Bang score ≥ 5 was able to identify individuals with increased probability of moderate-to-severe OSA, for males with acceptable diagnostic test accuracy for detecting participants with OSA, but there was no diagnostic test accuracy for females.
The Role of Dipolarizing Flux Bundles in Magnetotail Dynamics

Author(s): Liu, Jiang | Advisor(s): Angelopoulos, Vassilis | Abstract: Transient (~40s time scale) flux tubes carrying strong northward magnetic field and earthward flow are frequently observed in the magnetotail. Here I use the term "dipolarizing flux bundles" (DFBs) to describe these flux tubes. Thought to be generated by tail reconnection at XGSM=~-20 RE, DFBs travel earthward towards the inner edge of the plasma sheet, bringing significant changes to the near-earth magnetotail. After twenty years of extensive study on DFBs, numerous questions regarding their role in magnetotail dynamics remain. The THEMIS mission, which enables multi-point observations at different tail locations, provides the opportunity to answer many of these questions. With a statistical study based on THEMIS data, I explore the dipolarizing flux bundle's role in several aspects of magnetotail dynamics---its importance in magnetotail flux transport, the mechanisms controlling its motion, the modifications its motion makes to the ambient plasma, its current system, and the modifications it makes to the global magnetotail current system. First, I establish that DFBs are the major, high-efficiency magnetic flux carriers in near-earth magnetotail convection. Therefore, the DFB flux transport properties I found (e.g., DFBs transport more magnetic flux during substorm time) may shape all near-earth magnetotail convection. Then I investigate how a DFB's earthward motion modifies the plasma inside it as well as the ambient plasma. Dipolarizing flux bundle motion results in a total pressure buildup inside the ~1000km-thin DF layer; the buildup exerts a tailward force from there to retard DFB motion. This motion also builds up thermal pressure, the distribution of which requires the existence of field-aligned currents (FACs) near the DFB. To confirm the existence of these FACs, I infer the DFB-associated current system from magnetic field variations. The magnetic field variations are consistent with region-2-sense (towards/away from earth to the DFB's dusk/dawn side) FACs immediately earthward of the DFB and region-1-sense (opposite to region-2-sense) FACs inside the DF layer. Such a FAC configuration is similar to that of a substorm current wedge (SCW). In addition, the amount of current carried by several DFBs is sufficient to form a typical ~1 MA SCW. Therefore, I suggest that dipolarizing flux bundles are "wedgelets"---building blocks of a substorm current wedge.
Precision measurements of the $^{60}$Co $\beta$-asymmetry parameter in search for tensor currents in weak interactions

The {beta}-asymmetry parameter A-tilde for the Gamow-Teller decay of {sup 60}Co was measured by polarizing the radioactive nuclei with the brute-force low-temperature nuclear-orientation method. The {sup 60}Co activity was cooled down to milliKelvin temperatures in a {sup 3}He-{sup 4}He dilution refrigerator in an external 13-T magnetic field. The {beta} particles were observed by a 500-{mu}m-thick Si PIN diode operating at a temperature of about 10 K in a magnetic field of 0.6 T. Extensive geant4 Monte Carlo simulations were performed to gain control over the systematic effects. Our result, A-tilde=-1.014(12){sub stat}(16){sub syst}, is in agreement with the standard-model value of -0.987(9), which includes recoil-order corrections that were addressed for the first time for this isotope. Further, it enables limits to be placed on possible tensor-type charged weak currents, as well as other physics beyond the standard model.
Role of thermal conduction in an advective accretion with bipolar outflows

Steady-state advective accretion flows in the presence of thermal conduction are studied. All three components of velocity in a spherical coordinates are considered and the flow displays both inflowing and outflowing regions according to our similarity solutions. Thermal conductivity provides latitudinal energy transport and so, the flow rotates more slowly and becomes hotter with increasing thermal conductivity coefficient. We also show that opening angle of the outflow region decreases as thermal conduction becomes stronger.
Almost identical imitations of (3,1)-dimensional manifold pairs and the manifold mutation

Abstract In this paper, we construct from any given good (3,1)-dimensional manifold pair finitely many almost identical imitations of it whose exteriors are mutative hyperbolic 3-manifolds. The equivariant versions with the mutative reduction property on the isometry group are also established. As a corollary, we have finitely many hyperbolic 3-manifolds with the same volume and the same isometry group.
ON THE GRAVITATIONAL STABILITY OF GRAVITO-TURBULENT ACCRETION DISKS

Low mass, self-gravitating accretion disks admit quasi-steady, “gravito-turbulent” states in which cooling balances turbulent viscous heating. However, numerical simulations show that gravito-turbulence cannot be sustained beyond dynamical timescales when the cooling rate or corresponding turbulent viscosity is too large. The result is disk fragmentation. We motivate and quantify an interpretation of disk fragmentation as the inability to maintain gravito-turbulence due to formal secondary instabilities driven by: (1) cooling, which reduces pressure support; and/or (2) viscosity, which reduces rotational support. We analyze the axisymmetric gravitational stability of viscous, non-adiabatic accretion disks with internal heating, external irradiation, and cooling in the shearing box approximation. We consider parameterized cooling functions in 2D and 3D disks, as well as radiative diffusion in 3D. We show that generally there is no critical cooling rate/viscosity below which the disk is formally stable, although interesting limits appear for unstable modes with lengthscales on the order of the disk thickness. We apply this new linear theory to protoplanetary disks subject to gravito-turbulence modeled as an effective viscosity, and cooling regulated by dust opacity. We find that viscosity renders the disk beyond ∼60 au dynamically unstable on radial lengthscales a few times the local disk thickness. This is coincident with the empirical condition for disk fragmentation based on a maximum sustainable stress. We suggest turbulent stresses can play an active role in realistic disk fragmentation by removing rotational stabilization against self-gravity, and that the observed transition in behavior from gravito-turbulent to fragmenting may reflect instability of the gravito-turbulent state itself.
Mixed order transition and condensation in an exactly soluble one dimensional spin model

Mixed order phase transitions (MOT), which display discontinuous order parameter and diverging correlation length, appear in several seemingly unrelated settings ranging from equilibrium models with long-range interactions to models far from thermal equilibrium. In a recent paper [], an exactly soluble spin model with long-range interactions that exhibits MOT was introduced and analyzed both by a grand canonical calculation and a renormalization group analysis. The model was shown to form a bridge between two classes of 1D models exhibiting MOT, namely between spin models with inverse distance square interactions and surface depinning models. In this paper, we elaborate on the calculations performed in []. We also analyze the model in the canonical ensemble, which yields a better insight into the mechanism of MOT. In addition, we generalize the model to include Potts and general Ising spins and also consider a broader class of interactions that decay with distance using a power law different from 2.
Decent Work and Turnover Intentions Among Chinese Millennials: A Longitudinal Study

Turnover among millennial employees is frequent and is more common when work is not considered decent. Nevertheless, the potential reasons for why decent work attainment links with millennials’ turnover intentions deserves further exploration. Grounded in the psychology of working theory and social exchange theory, the current research explored the roles of overall well-being and perceived career opportunity in the relation between decent work and turnover intentions. Through an analysis of three-wave data obtained from 327 millennials in China, we found that decent work was indirectly related to turnover intentions via overall well-being, and that perceived career opportunity served as an important moderator in this relation. The results suggest that millennials who perceive their work as indecent may have greater turnover intentions in part because they are less satisfied with their lives. This relation is even stronger when they perceive few career opportunities in their current job.
PROSPECTS FOR DETECTING ASTEROSEISMIC BINARIES IN KEPLER DATA

Asteroseismology may in principle be used to detect unresolved stellar binary systems comprised of solar-type stars and/or red giants. This novel method relies on the detection of the presence of two solar-like oscillation spectra in the frequency spectrum of a single light curve. Here, we make predictions of the numbers of systems that may be detectable in data already collected by the NASA Kepler Mission. Our predictions, which are based upon TRILEGAL and BiSEPS simulations of the Kepler field of view, indicate that as many as 200 or more “asteroseismic binaries” may be detectable in this manner. Most of these binaries should be comprised of two He-core-burning red giants. Owing largely to the limited numbers of targets with the requisite short-cadence Kepler data, we expect only a small number of detected binaries containing solar-type stars. The predicted yield of detections is sensitive to the assumed initial mass ratio distribution (IMRD) of the binary components and therefore represents a sensitive calibration of the much debated IMRD near mass ratio unity.
CARBON DEFLAGRATION IN TYPE Ia SUPERNOVA. I. CENTRALLY IGNITED MODELS

A leading model for Type Ia supernovae (SNe Ia) begins with a white dwarf near the Chandrasekhar mass that ignites a degenerate thermonuclear runaway close to its center and explodes. In a series of papers, we shall explore the consequences of ignition at several locations within such dwarfs. Here we assume central ignition, which has been explored before, but is worth revisiting, if only to validate those previous studies and to further elucidate the relevant physics for future work. A perturbed sphere of hot iron ash with a radius of ∼100 km is initialized at the middle of the star. The subsequent explosion is followed in several simulations using a thickened flame model in which the flame speed is either fixed—within the range expected from turbulent combustion—or based on the local turbulent intensity. Global results, including the explosion energy and bulk nucleosynthesis (e.g., 56Ni of 0.48–0.56 M☉) turn out to be insensitive to this speed. In all completed runs, the energy released by the nuclear burning is adequate to unbind the star, but not enough to give the energy and brightness of typical SNe Ia. As found previously, the chemical stratification observed in typical events is not reproduced. These models produce a large amount of unburned carbon and oxygen in central low velocity regions, which is inconsistent with spectroscopic observations, and the intermediate mass elements and iron group elements are strongly mixed during the explosion.
Aridity drives the loss of dung beetle taxonomic and functional diversity in three contrasting deserts

Aridity gradients are of great interest for understanding the responses of biodiversity to water availability and water stress. However, little is known about the responses of many animal groups, which are crucial for assessing the effects of climate change. Here, we study the effects of aridity on dung beetle communities, a group with well‐known responses to large‐scale environmental gradients.
Classification of Non-Small Cell Lung Cancer Based on Gene Expression in Cases of Smokers and Non-Smokers using Ensemble Methods with Statistical Based Feature Selection

: Lung cancer is one of the leading causes of death globally. One of the main risk factors for lung cancer is smoking, which causes more than 90% of lung cancer cases. There are two types of lung cancer, i.e., Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC), which the latter is the most common. One method that can be used to detect cancer is the implementation of machine learning on gene expression data. Machine learning is one approach that promises good performance in classifying gene expression data. This study aimed to predict the existence of NSCLC based on gene expression, whether including NSCLC or normal. We used three data sets, i.e., GSE10072, GSE19804, and GSE19188, which relate to the cases of NSCLC in smokers and nonsmokers. The prediction was carried out using six Ensemble Methods, i.e., Random Forest, Adaptive Boosting, Extra Tree, Gradient Boosting, Extreme Gradient Boosting, and Categorical Boosting. Feature selection was carried out by calculating the correlation between feature and target according to statistical parameters, i.e., ANOVA, Mutual Information (MI), and a combination of ANOVA and MI. We obtained the prediction model that outperformed the related studies for two similar data sets with the value of accuracy for the GSE10072, GSE19804, and GSE19188 data sets 100%, 97.22%, and 100%, respectively.