Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Heterogeneity in Growth Mixture Models: A Case Study of Model Selection using Direct Behavior Rating

This study investigates student classroom behavior changes over one year using multilevel growth mixture modeling to demonstrate how modifying assumptions of invariance affects parameter estimates, number of classes, and proportion of students assigned to each class. Current best practices for growth mixture modeling emphasize the importance of the proper specification, but the impact of these assumptions on the parameters and latent class composition has not been thoroughly addressed in applied research in multilevel growth mixture models. Using the Direct Behavior Rating Single Item Scale measures from 1975 students in lower elementary, upper elementary and middle school, a series of models were compared from full invariance to partial noninvariance. This research provides a description of steps, decisions, and results from testing for noninvariance, and how these affect the resulting subgroups and model parameters. Results indicated a dramatic shift in the students from higher classes to lower classes as the model was relaxed to allow for class level difference in variance parameters. The best fitting models for each grade group contained three latent classes characterized by students with consistently good classroom behavior, students with less consistent moderate behavior, and students with highly variable behavior. Criterion measures provided validation of these results. Research on classroom behavior heterogeneity using GM modeling represents an important Janice Kooken – University of Connecticut, 2015 addition to the knowledge base by providing a descriptive typology of student behavior, lending information necessary to fine tune behavior interventions. This research suggests that using variability as a criteria for the typology results is a more sensitive screening instrument identifying more students for follow up. This research also suggests that because student classroom behavior is highly variable for the students most at risk due to behavior problems, variability should be measured and tracked in single case studies to identify interventions to reduce this variability.
LncRNA FTX ameliorates neuropathic pain by targeting miR-320a in a rat model of chronic constriction injury.

INTRODUCTION Long non-coding RNAs (lncRNAs) participate in the process of neuropathic pain (NP). Herein, the goal of this research was to examine the roles of lncRNA five prime to XIST (FTX) in influencing chronic constriction injury (CCI)-induced NP. MATERIAL AND METHODS We have established a rat CCI model to simulate NP in vivo. Reverse transcription-quantitative PCR (RT-qPCR) was used to detect mRNA levels of FTX, microRNA (miR)-320a, and runt-related transcription factor 2 (RUNX2) in the spinal cord. This was followed by subsequent regulation of FTX or miR-320a levels in vivo by intrathecal injection of overexpression FTX or miR-320a mimic lentivirus. The behaviour of rat NP the paw withdrawal threshold (PWT) and paw withdrawal latency (PWL). Enzyme-linked immunosorbent assay (ELISA) was used to assess the secretion of pro-inflammatory and anti-inflammatory factors in the spinal cord tissue. A correlation between FTX and miR-320a, and RUNX2 was validated by luciferase reporter. RESULTS FTX levels were reduced in CCI rats ( p < 0.05), and miR-320a was a direct target of FTX. Overexpression of FTX typically reduced PWL and PWT as well as neuroinflammation thus alleviating NP ( p < 0.05). However, increasing miR-320a reversed the alleviation of FTX on NP, increased PWL and PWT, and promoted neuroinflammation ( p < 0.05). Additionally, RUNX2, which is a miR-320a target gene, was significantly repressed in CCI rats and its expression was increased by FTX, however, this increase was attenuated by elevated miR-320a ( p < 0.05). CONCLUSIONS In the CCI-induced NP rat model, FTX attenuates NP and neuroinflammation by regulating the miR-320a/RUNX2 axis. This provides a new vision for NP treatment.
Application of He's Exp-ftmction Method to the Stochastic mKdV Equation

With the help of Hermit transformation, it is firstly that the exp-fimction method is applied to solve nonlinear stochastic partial differential equations, and some new exact solutions of the stochastic mKdV equation in the white noise environment are obtained. It is shown that the exp-function method provides a straightforward and important mathematical tool for nonlinear stochastic partial differential equations in mathematical physics.
CONVERGENCE OF THE NEWTON-TYPE METHOD FOR GENERALIZED EQUATIONS

Let X and Y be real or complex Banach spaces. Suppose that f: X->Y is a Frechet differentiable function and F: X => 2 Y is a set-valued mapping with closed graph. In the present paper, we study the Newton-type method for solving generalized equation 0 Ɛ f(x) + F(x). We prove the existence of the sequence generated by the Newton-type method and establish local convergence of the sequence generated by this method for generalized equation. GANIT J. Bangladesh Math. Soc. Vol. 35 (2015) 27-40
A multiphase model for compressible flows with interfaces, shocks, detonation waves and cavitation

A compressible multiphase unconditionally hyperbolic model is proposed. It is able to deal with a wide range of applications: interfaces between compressible materials, shock waves in condensed multiphase mixtures, homogeneous two-phase flows (bubbly and droplet flows) and cavitation in liquids. Here we focus on the generalization of the formulation to an arbitrary number of fluids, and to mass and energy transfers, and extend the associated Godunov method. We first detail the specific problems involved in the computation of thermodynamic interface variables when dealing with compressible materials separated by well-defined interfaces. We then address one of the major problems in the modelling of detonation waves in condensed energetic materials and propose a way to suppress the mixture equation of state. We then consider another problem of practical importance related to high-pressure liquid injection and associated cavitating flow. This problem involves the dynamic creation of interfaces. We show that the multiphase model is able to solve these very different problems using a unique formulation. We then develop the Godunov method for this model. We show how the non-conservative terms must be discretized in order to fulfil the interface conditions. Numerical resolution of interface conditions and partial equilibrium multiphase mixtures also requires the introduction of infinite relaxation terms. We propose a way to solve them in the context of an arbitrary number of fluids. This is of particular importance for the development of multimaterial reactive hydrocodes. We finally extend the discretization method in the multidimensional case, and show some results and validations of the model and method.
Coherence of Warm-Season Continental Rainfall in Numerical Weather Prediction Models

Abstract A recent study by Carbone et al. revealed “episodes” of warm-season rainfall over North America characterized as coherently propagating signals often linking multiple mesoscale convective systems over spatial scales of 1000–3000 km and timescales of 1–3 days. The present study examines whether these propagating signals are found in two numerical weather prediction (NWP) models commonly used today, namely, the Eta Model from the National Centers for Environmental Prediction and the newly developed Weather Research and Forecast (WRF) model. The authors find that the diurnal cycle of rainfall over much of the United States east of the Rockies is poorly represented, particularly over the central United States, where a nocturnal rainfall maximum is observed. Associated with this nocturnal maximum is an axis of propagating rainfall emanating from the western High Plains in the late afternoon, extending across the Midwest overnight, and occasionally continuing to the Appalachians on the second day. This.
Numerical Prediction of Dynamics of Interaction of Laser Discharge Plasma with a Hemisphere-Cylinder in a Supersonic Flow

The effect of a laser discharge onto supersonic flow past a hemisphere-cylinder at Mach 3.45 is considered. Flow details accompanying supersonic streamlining for three values of energy of a laser impulse 13 mJ, 127 mJ and 258 mJ are simulated numerically on the basis of the Euler equations. The energy deposition is modeled via the combining heated rarefied channels. Complex unsteady vortex contact structures caused by the Richtmyer-Meshkov instability together with a rarefaction wave reflection are shown to be the reason for the reduction of the stagnation pressure. Optimization of the characteristics of the energy sources has been realized taking into account the flow analysis and the comparison of the computational and experimental data. Energy estimations are provided for the three considered parameters of the laser impulse.
Artificial accelerograms composition based on the CEEMD

In this work, a new methodology for generating spectrum-compatible accelerograms is presented. The proposed methodology considers the non-stationary and non-linear characteristics of seismic signals and utilizes the Hilbert–Huang transform (HHT) to analyse them. The two reported drawbacks of HHT, i.e. the mode mixing phenomenon and the end effects issue, are resolved through the proposed methodology. More specifically, the advantages of the recently introduced complementary ensemble empirical mode decomposition (CEEMD) are exploited in order to eliminate the mode mixing phenomenon. Moreover, the application of the proposed method only to the strong motion duration of the seismic signal assists to overcome the end effects issue. Thirty natural seismic records of different characteristics, such as frequency content, amplitude and duration, are employed as initial seed signals to demonstrate the proposed method. To illustrate the effectiveness of the proposed technique, comparisons with three established methods for generating spectrum-compatible seismic accelerograms are also provided.
What's the Bound on the Average Number of Normals?

In this department the MONTHLY presents easE stated 1msolved problems dealing with notions ordinari encountered in undergraduate mathematics. Each problem should be accompanied by relevant references (if any are known to the author) and by a brief description of known partial or related results. Typescripts should be sent to Richard Nowakowski, Department of Mathematics & Statistics & Computing Science, Dalhousie University, Halifax N.S. , Canada B3H 3J5.
On the Derivation Algebras of Lie Algebras

Let L be a Lie algebra over a field of characteristic 0 and let D(L) be the derivation algebra of L, that is, the Lie algebra of all derivations of L. Then it is natural to ask the following questions: What is the structure of D(L)? What are the relations of the structures of D(L) and L? It is the main purpose of this paper to present some results on D(L) as the answers to these questions in simple cases. Concerning the questions above, we give an example showing that there exist non-isomorphic Lie algebras whose derivation algebras are isomorphic (Example 3 in § 5). Therefore the structure of a Lie algebra L is not completely determined by the structure of D(L). However, there is still some intimate connection between the structure of D(L) and that of L.
Money Matters: Broad Divisia Money and the Recovery of Nominal GDP from the COVID-19 Recession

The rise of inflation in 2021 and 2022 surprised many macroeconomists who ignored the earlier surge in money growth because past instability in the demand for simple-sum monetary aggregates had made these aggregates unreliable indicators. We find that the demand for more theoretically-based Divisia aggregates can be modeled and that their growth rates provide useful information for future nominal GDP growth. Unlike M2 and Divisia-M2, whose velocities do not internalize shifts in liabilities across commercial and shadow banks, the velocities of broader Divisia monetary aggregates are more stable and can be reasonably empirically modeled in both the short run and the long run through the COVID-19 pandemic and to date. In the long run, these velocities depend on regulatory changes and mutual fund costs that affect the substitutability of money for other financial assets. In the short run, we control for swings in mortgage activity and use vaccination rates and an index of the stringency of government pandemic restrictions to control for the unusual effects of the pandemic. The velocity of broad Divisia money temporarily declines during crises like the Great and COVID Recessions, but later rebounds. In each recession monetary policy lowered short-term interest rates to zero and engaged in quantitative easing of about $4 trillion. Nevertheless, broad money growth was more robust in the COVID Recession, likely reflecting that the banking system was less impaired and could promote rather than hinder multiple deposit creation. Partly as a result, our framework implies that nominal GDP growth and inflationary pressures rebounded much more quickly from the COVID Recession versus the Great Recession. We consider different scenarios for future Divisia money growth and the unwinding of the pandemic that have different implications for medium-term nominal GDP growth and inflationary pressures as monetary policy tightening seeks to restore low inflation.
Brief Paper On exponential stability of nonlinear time-varying di!erential equations1

Within the Liapunov framework, a su$cient condition for exponential stability of ordinary di! erential equations is proposed. Unlike with classical Liapunov theory, the time derivative of the Liapunov function, taken along solutions of the system, may have positive and negative values. Veri"cation of the conditions of the main theorem may be harder than in the classical case. It is shown that the proposed conditions are useful for the investigation of the exponential stability of fast time-varying systems. This sets the stability study by means of averaging in a Liapunov context. In particular, it is established that exponential stability of the averaged system implies exponential stability of the original fast time-varying system. A comparison of our work with results taken from the literature is included. ( 1999 Elsevier Science Ltd. All rights reserved.
Apoptotic Changes, Oxidative Stress and Immunomodulatory Effects in the Liver of Japanese Seabass (Lateolabrax japonicus) Induced by Ammonia-Nitrogen Stress during Keep-Live Transport

Simple Summary Excreta produced by fish during preservation transport can increase ammonia-nitrogen (NH3-N) levels in transport water and reduce survival rates. However, studies on the effects of NH3-N stress on Japanese seabass during transport are limited. The objective of this study was to investigate the effects of NH3-N stress on tissue damage, oxidative stress, apoptosis and immunity in Japanese seabass during transport, and to determine tolerance and response to NH3-N toxicity. The results of this study provide insight into the impact of environmental factors on Japanese seabass during maintenance of live transport, which can be considered during transport in terms of improving the quality of transport water, among other things, to develop optimal procedures for live fish transport and improve survival rates during transport. Abstract This study investigated the effects of NH3-N on antioxidant responses, histoarchitecture, and immunity of Japanese seabass (Lateolabrax japonicus) during keep-live transport. The findings suggest that NH3-N stress transport alters the transcription of P53, Caspase 9, Bcl2, Caspase 3 and Bax genes, demonstrating that NH3-N stress can trigger the apoptotic pathway of P53-Bax-Bcl2 and Caspase and induce apoptosis. NH3-N stress transport also evoked transcriptional upregulation of inflammatory cytokines (tumor necrosis factor α (TNF-α), Toll-like receptor 3 (TLR-3), nuclear factor kappa β (NF-κB), interleukin 6 (IL-6) and interleukin 1β (IL-1β)) and increased complement C3, C4, lysozyme (LZM) and immunoglobulin (IgM) levels, activating the innate immunological system during keep-live transport. In addition, NH3-N stress transport altered changes in the levels of superoxide dismutase (SOD), catalase (CAT), glutathione-related enzymes, and heat shock proteins 70 and 90 in the liver, indicating that the antioxidant system and Hsp protected the cells from NH3-N-induced oxidative stress. When excess ROS were not removed, they caused the body to respond with immunological and inflammatory responses, as well as apoptosis and tissue damage. This helps towards understanding the effect of NH3-N levels on sea bass during keep-live transport.
Colonial system of integration and communication pores in a polymorphic bryozoan Dendrobeania fruticosa (Bryozoa: Cheilostomata)

Bryozoan colonies are composed of zooids, which can differ in structure and function. Autozooids supply heteromorphic zooids with nutrients, which are usually unable to feed. To date, the ultrastructure of the tissues providing nutrient transfer is almost unexplored. Here, we present a detailed description of the colonial system of integration (CSI) and the different types of pore plates in Dendrobeania fruticosa. All cells of the CSI are joined by tight junctions that isolate its lumen. The lumen of the CSI is not a single structure, but a dense network of small interstices filled with a heterogeneous matrix. In autozooids, the CSI is composed of two types of cells: elongated and stellate. Elongated cells form the central part of the CSI, including two main longitudinal cords and several main branches to the gut and pore plates. Stellate cells compose the peripheral part of the CSI, which is a delicate mesh starting from the central part and reaching various structures of autozooids. Autozooids have two tiny muscular funiculi, which start from the caecum apex and run to the basal wall. Each funiculus includes a central cord of extracellular matrix and two longitudinal muscle cells; together they are enveloped with a layer of cells. The rosette complexes of all types of pore plates in D. fruticosa display a similar cellular composition: a cincture cell and a few special cells; limiting cells are absent. Special cells have bidirectional polarity in interautozooidal and avicularian pore plates. This is probably due to the need for bidirectional transport of nutrients during degeneration–regeneration cycles. Cincture cells and epidermal cells of pore plates contain microtubules and inclusions resembling dense‐cored vesicles, which are typical of neurons. Probably, cincture cells are involved in the signal transduction from one zooid to another and can be a part of the colony‐wide nervous system.
The Impact of Polymorphisms in ATP-Binding Cassette Transporter Genes on Anthracycline-Induced Early Cardiotoxicity in Patients with Breast Cancer

Background. Cardiac side effects associated with anthracycline-based treatment may seriously compromise the prognosis of patients with breast cancer (BC). Evidence shows that genes that operate in drug metabolism can influence the risk of anthracycline-induced cardiotoxicity (AIC). ATP-binding cassette (ABC) transporters could serve as one of the potential biomarkers for AIC risk stratification. We aimed to determine the link between single-nucleotide polymorphisms (SNPs) in several ABC genes (ABCB1 rs1045642, ABCC1 rs4148350, ABCC1 rs3743527) and cardiotoxicity. Methods. The study included 71 patients with BC, who were treated with doxorubicin-based chemotherapy. Two-dimensional echocardiography and speckle-tracking echocardiography were performed. AIC was defined as a new decrease of 10 percentage points in the left ventricular ejection fraction (LVEF). SNPs in ABCB1 and ABCC1 genes were evaluated using real-time PCR. Results. After a cumulative dose of 236.70 mg/m2 of doxorubicin, 28.2% patients met the criteria of AIC. Patients who developed AIC had a larger impairment in left ventricular systolic function compared to those who did not develop AIC (LVEF: 50.20 ± 2.38% vs. 55.41 ± 1.13%, p < 0.001; global longitudinal strain: −17.03 ± 0.52% vs. −18.40 ± 0.88%, p < 0.001). The ABCC1 rs4148350 TG genotype was associated with higher rates of cardiotoxicity (TG vs. GG OR = 8.000, 95% CI = 1.405–45.547, p = 0.019). Conclusions. The study showed that ABCC1 rs4148350 is associated with AIC and could be a potential biomarker to assess the risk of treatment side effects in patients with BC.
Constructing formal groups VIII : formal A-modules

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Capacitive Properties of Grain Boundary Josephson Junctions Fabricated on 45 (100) Tilt Asymmetric and 24 (001) Tilt Symmetric Bicrystals

We present a comparative study of the electromag- netic parameters, mainly focused in the analysis of the capacitance (C) associated to the barrier, of (YBCO) grain boundary Josephson junctions (GBJJs) fabricated on 24 (001) symmetric and 45 (100) asymmetric tilt bicrystalline substrates. The Swihart velocity is slightly affected by the nature of the barrier and mainly fixed by the junction width. However, a no- table influence of the barrier structure, so of the geometry of the bicrystal substrate, on the relative dielectric constant to the barrier thickness ratio values, so on C, has been found. We have observed that the capacitance values deduced by means of Fiske steps in YBCO 24 (001) symmetric and 45 (100) asymmetric GBJJs scale with junction resistance in opposite direction. This re- sult could reveal the presence of a tunnel barrier in the YBCO 45 (100) asymmetric GBJJs. On the other hand, different capacitance values have been obtained by means of Fiske steps and hysteresis observed in the current-voltage characteristics in 45 (100) asym- metric GBJJs. An interpretation of this result can be made taking into account the contribution of the depleted YBCO layers close to the crystallographic grain boundary.
Zero is Not Hero Yet: Benchmarking Zero-Shot Performance of LLMs for Financial Tasks

Recently large language models (LLMs) like ChatGPT have shown impressive performance on many natural language processing tasks with zero-shot. In this paper, we investigate the effectiveness of zero-shot LLMs in the financial domain. We compare the performance of ChatGPT along with some open-source generative LLMs in zero-shot mode with RoBERTa fine-tuned on annotated data. We address three inter-related research questions on data annotation, performance gaps, and the feasibility of employing generative models in the finance domain. Our findings demonstrate that ChatGPT performs well even without labeled data but fine-tuned models generally outperform it. Our research also highlights how annotating with generative models can be time-intensive. Our codebase is publicly available on GitHub under CC BY-NC 4.0 license.