Miracle-dz/UniFAR-FTUs huggingface dataset:
Strengthening the Impact of Using a Trauma-informed Lens in the Classroom

This paper explores how changing an approach from a traditional behaviour model to that of a trauma-informed lens for children who have experienced adverse childhood experiences from abuse, neglect, violence or witnessing violence in the home, grief and loss (death, divorce, unnatural events) can have an impact on their engagement to learning and emotional challenges. This study comes from a strengths perspective acknowledging students' character strengths that can be built on for overcoming adversity. It aims to put forward a framework from a trauma-informed lens to support teacher capacity to strengthen the use of interventions that contribute to improved student engagement. Research collected through seven teachers’ narratives examines the complex relational, behavioural and cognitive learning needs of these students and their teachers’ needs to feel empowered to teach in an inclusive classroom or innovative learning environment. The study aims to suggest that all children can benefit from trauma-informed principles and pedagogy as protective factors enhancing resiliency. The key findings of the study was that frameworks need to be tailored to the needs of the individuals. The interventions used to meet specific goals need to be explicit, planned and purposeful. A proactive strengths-based approach in an inclusive environment through a trauma-informed lens is required for best outcomes.
System Model Bias Processing Approach for Regional Coordinated States Information Involved Filtering

In the Kalman filtering applications, the conventional dynamic model which connects the states information of two consecutive epochs by state transition matrix is usually predefined and assumed to be invariant. Aiming to improve the adaptability and accuracy of dynamic model, we propose multiple historical states involved filtering algorithm. An autoregressive model is used as the dynamic model which is subsequently combined with observation model for deriving the optimal window-recursive filter formulae in the sense of minimum mean square error principle. The corresponding test statistics characteristics of system residuals are discussed in details. The test statistics of regional predicted residuals are then constructed in a time-window for model bias testing with two hypotheses, that is, the null and alternative hypotheses. Based on the innovations test statistics, we develop a model bias processing procedure including bias detection, location identification, and state correction. Finally, the minimum detectable bias and bias-to-noise ratio are both computed for evaluating the internal and external reliability of overall system, respectively.
Zonal Detached-Eddy Simulation Applied to the Tip-Clearance Flow in an Axial Compressor

This paper presents the study of the tip-clearance flow in an axial compressor using several turbulence-modeling approaches: Reynolds-averaged Navier–Stokes, unsteady Reynolds-averaged Navier–Stokes, and zonal detached-eddy simulation. Rotor simulations are carried out on the same mesh based on the zonal-detached-eddy-simulation requirements, and compared to experimental data. Zonal detached-eddy simulation brings significant improvements over Reynolds-averaged Navier–Stokes and unsteady Reynolds-averaged Navier–Stokes approaches to reach accurate integral values, especially the total-pressure-gradient prediction near the casing, as well as to capture complex flow patterns near the casing. Whereas the unsteady Reynolds-averaged Navier–Stokes method predicts only tip-leakage and induced vortices, the zonal-detached-eddy-simulation approach is able to reveal more complex phenomena as the tip-leakage vortex, the contra-rotative induced vortex, and numerous secondary vortices are captured. Because of their in.
Study on Diesel Engine Anomaly Detection Based on Hyper-sphere Classification with Maximal Distance

Aimed at insufficiency and imbalance data distribution in diesel engine fault detection,an abnormal detection method based on hyper-sphere classification with maximum distance was proposed.Analyzed the poor generalization capability of support vector data description model and the merits of the optimal separation hyper-plane of support vector machine,the ratio of the radius to the separation margin and the abnormal samples information were introduced to balance the description accuracy and generalization ability of the hyper-sphere.Then,an optimal selection method for the model parameters was presented with the valuation index of the number of support vectors and area under curve of receiver operating characteristics.The diesel engine anomaly detection results show that the proposed method is more effective than SVDD.
Existence of solutions for a nonlocal elliptic system with critical and subcritical exponential growth

In this paper, the existence of nontrivial solutions to the following nonlocal elliptic system: −Δu=1|x|μ∗G(v)g(v),v>0inΩ,−Δv=1|x|μ∗F(u)f(u),u>0inΩ,u=0,v=0on∂Ω$$ \left\{\begin{array}{l}-\Delta u=\left[\frac{1}{{\left|x\right|}^{\mu }}\ast G(v)\right]g(v),v>0\kern0.5em \mathrm{in}\kern0.5em \Omega, \\ {}-\Delta v=\left[\frac{1}{{\left|x\right|}^{\mu }}\ast F(u)\right]f(u),u>0\kern0.5em \mathrm{in}\kern0.5em \Omega, \\ {}u=0,v=0\kern0.5em \mathrm{on}\kern0.5em \mathrm{\partial \Omega}\end{array}\right. $$ is studied by variational method, where Ω$$ \Omega $$ is a bounded open subset of ℝ2$$ {\mathrm{\mathbb{R}}}^2 $$ with smooth boundary ∂Ω,0
Assessment of Water Parameters of Upper Kodera Dam in Mount Abu after Rainfall

The current research aims to investigate the effects of physicochemical factors on water quality, particularly during the summer at Upper Kodera Dam in Mount Abu (Raj), India. For the investigation of physicochemical factors such such as water and air temperature, pH, transparency, total hardness, dissolved oxygen, total alkalinity, and chemical oxygen demand, water samples from the dam were taken. The acquired findings were compared to WHOBIS (World Health Organization and Bureau of Indian Standard) values permitted limits for drinking water. A few parameters at various stations were found to be close to the allowable limits. With reference to the analysed criteria, the current study identified how rainfall affects the water quality of Upper Kodera Dam water. Samples of 10 water were taken from Upper Kodra Dam between May 2021 and November 2022. Total hardness, Alkalinity, chloride, pH, total dissolved solids, iron, dissolved oxygen, fluoride, nitrate, sulphate, chromium, iron, chromium, and MPN of coliforms are among the biological and physicochemical parameters that were examined. According to the report, the current water supply needs urgent remediation since the water quality is subpar.
The Aim of Medicine. Sanocentricity and the Autonomy Thesis

: Recent criticisms of medicine converge on fundamental questions about the aim of medicine. The main task of this paper is to propose an account of the aim of medicine. Discussing and rejecting the initially plausible proposal according to which medicine is pathocentric, the paper presents and defends the Autonomy Thesis, which holds that medicine is not pathocentric, but sanocentric, aiming to promote health with the final aim to enhance autonomy. The papercloses byconsideringthe objection that the Autonomy Thesis is overly permissive and allows many highly controversial procedures as legitimate parts of medicine.
ON NON-ISOTROPIC JACOBI PSEUDOSPECTRAL METHOD

在这篇论文，非各向同性的 Jacobi 假光谱方法被建议，它的应用斧子考虑了。 一些结果在上；多维的 Jacobi 高斯类型插值和相关 Bernstein 杰克森类型不平等斧子建立了，它起一个重要作用在假光谱方法。 假光谱方法被用于一二 -- 维的单个问题中间 axisymmetric 上的一个问题领域。 建议计划的集中被建立。 数字结果表明建议方法的效率。
Word-final strength and weakness

Word-final syllables are known to show phonological strength, presumably due to final lengthening (Steriade 1994; Barnes 2002), but also phonological weakness. We propose that final weakening effects are also due to final lengthening under the assumption that duration due a phonetic source (i.e. final lengthening) is not on linguistic par with duration from a phonological source. We show further support for our proposal through the results of perception studies with adults that show less sensitivity to word-final duration differences. We note that child language phonology often shows unexpected final syllable strength and include two such diary studies with English-learning children. We propose that this difference between child and adult phonology is due to children not yet having learned to differentiate the import of duration based on its source.
Spatial and temporal interactions in distributed inhibition-stabilized networks

To gain insight into neural events responsible for visual perception of spatial and temporal optical patterns, we study how neural activation propagates in chains of inhibition-stabilized neural networks with nearest-neighbor coupling. The activation generated by local stimuli in such networks propagates between locations, forming spatiotemporal waves that affect the dynamics of activation generated by stimuli separated spatially and temporally. These interactions form characteristic interference patterns, manifested as intrinsic preferences of the network for spatiotemporal frequencies of stimulus intensity, for stimulus velocities, and as contextual ("lateral") interactions between stimuli. Such preferences have been previously attributed to distinct specialized mechanisms.
Quality of Life Impacts Following Surgery for Advanced Head and Neck Cancer

Background Understanding the impact of surgery on patients will enable clinicians to provide evidence-based perioperative management. This study aimed to investigate the quality of life (QoL) impacts following head and neck surgery for advanced stage head and neck cancer. Methods Head and neck cancer survivors were invited to complete five validated questionnaires to investigate QoL. Associations between QoL and patient variables were analyzed. Variables included age, time since operation, length of surgery, length of stay, Comorbidity Index, estimated 10-year survival, sex, flap type, treatment and cancer type. Outcome measures were also compared to normative outcomes. Results The majority of participants (N = 27; 55% male; mean (standard deviation) age: 62.6 (13.8) years; mean time since operation: 801 days) had a squamous cell carcinoma (88.9%) and free flap repair (100%). Time since operation was significantly (P < 0.05) associated with higher rates of depression (r = -0.533), psychological needs (r = -0.0415) and physical/daily living needs (r = -0.527). Length of surgery and length of stay were significantly associated with depression (r = 0.442; r = 0.435) and length of stay was significantly associated with speaking difficulties (r = -0.456). There was a significant association between work and education scores with age (r = 0.471), length of surgery (r = 0.424), Comorbidity Index (r = 0.456) and estimated 10-year survival (r = -0.523). Conclusions Age, time since operation, length of surgery, length of stay, Comorbidity Index and estimated 10-year survival were the outcomes associated with QoL. Patient-reported outcome measures and psychological support could be included in the standard care pathway for head and neck cancer patients to ensure holistic management of their condition.
Bias Introduced by Rounding in Multiple Imputation for Ordered Categorical Variables

ABSTRACT Multivariate normality is frequently assumed when multiple imputation is applied for missing data. When data are ordered categorical, imputing missing data using the fully normal imputation results in implausible values falling outside of the categorical values. Naïve rounding has been suggested to round the imputed values to their categorical neighbors for further analysis. Previous studies showed that, for binary data, the rounded values can result in biased mean estimation when the population distribution is asymmetric. However, it has been conjectured that as the number of categories increases, the bias will decrease. To investigate this conjecture, the present study derives the formulas for the biases of the mean and standard deviation for ordered categorical variables with naïve rounding. Results show that both the biases of the mean and standard deviation decrease as the number of categories increases from 3 to 9. This study also finds that although symmetric population distributions lead to unbiased means of the rounded values, the standard deviations may still be largely biased. A simulation study further shows that the biases due to naïve rounding can result in substantially low coverage rates for the population mean parameter.
Essays on Stochastic Games and on Strategic Equivalence between Normal Form Games

This thesis is a collection of essays on stochastic games with incomplete information and one essay on strategic equivalence between normal form games. In Chapter 1, we propose a new class of stochastic games suitable to the study of situations where there is incomplete information about the payoff relevant state of the world. We show the existence of equilibrium in pure Markov strategies by applying a few restrictions on the framework. We also investigate when the Markov assumption on strategies is reasonable. We show that if the Markov law of motion on the state of the world has full support, players’ beliefs also have full support, players do not learn, and the Markov assumption is reasonable. Another type of situation in which we can guarantee that the Markov assumption is reasonable, is when the game becomes large, if players are interconnected and the dynamics on the state space implied by the Markov law of motion are rich. As an application, we study a dynamic arms race model under incomplete information, an imperfect market competition model where the privately observed variable may be serially correlated over time, and a dynamic search model with hidden search productivity. In Chapter 2, we provide an application of the framework developed in Chapter 1 to multistage R&D races. The framework developed in Chapter 1 is suitable to this type of problem, because R&D races typically involve the development of several intermediate steps and in some industries information about the competitor’s development stage is strategic. In our R&D model, firms need to complete a finite number of intermediate steps before the product or project is finished. In our model, there is incomplete information because firms may not know the competitor’s development stage during the race. By using numerical methods, we study the
Statistical Modeling to Inform Optimal Game Strategy: Markov Plays H-O-R-S-E

ABSTRACT We illustrate practical uses of logistic regression and Markov chains by applying these concepts to the problem of developing optimal strategy in the popular basketball game of H-O-R-S-E. Based on data collected by the authors, we estimate model parameters for each author, describe strategies of optimizing each author’s probability of winning, and calculate the stationary distribution of a Markov chain that arises from the game.
Recent progress on intensity and chirp compensation of EADFB laser realized by SOA integration

A novel approach is demonstrated for overcoming the trade-off relationship between the power consumption and transmission distance of an electro-absorption modulator integrated with a DFB laser (EADFB laser). We demonstrate that the monolithic integration of a short semiconductor optical amplifier (SOA) with an EADFB laser is effective in overcoming the limitation imposed by the Kramers-Kronig (K-K) relation of the EA modulator, which cannot be overcome with the conventional method of optimizing the MQW structure of the EA modulator. Our approach provides an EADFB laser with two advantages. One is that we can realize a higher optical output power with smaller power consumption than with a conventional EADFB laser by reducing the DFB laser injection current and allocating it to the SOA section. We design the SOA length based on this concept. The other advantage is the chirp compensation of the EA modulator with the SOA. To confirm the validity of this approach, we investigate the SOA length dependence on the basic characteristics. By using an EADFB laser integrated with a 50-μm-long SOA, we achieve a 2 dB increase in the modulated output power compared with a stand-alone EADFB laser with the same power consumption. We realize an extended transmission distance of 5 km at 40 Gbit/s, and a 1.55-μm-wavelength window, which is conventionally achieved for a 2-km SMF transmission with an EADFB laser. These results indicate that this approach is a promising way to realize a high-speed light source with low power consumption for future large capacity optical network systems.
Multi‐parametric analysis of strongly inhomogeneous periodic waveguideswith internal cutoff frequencies

In this paper, we consider periodic waveguides in the shape of a inhomogeneous string or beam partially supported by a uniform elastic Winkler foundation. A multi‐parametric analysis is developed to take into account the presence of internal cutoff frequencies and strong contrast of the problem parameters. This leads to asymptotic conditions supporting non‐typical quasi‐static uniform or, possibly, linear microscale displacement variations over the high‐frequency domain. Macroscale governing equations are derived within the framework of the Floquet–Bloch theory as well as using a high‐frequency‐type homogenization procedure adjusted to a string with variable parameters. It is found that, for the string problem, the associated macroscale equation is the same as that applying to a string resting on a Winkler foundation. Remarkably, for the beam problem, the macroscale behavior is governed by the same equation as for a beam supported by a two‐parameter Pasternak foundation. Copyright © 2016 John Wiley & Sons, Ltd.
Measurement Theory

What is measurement theory? What is measurement? Why should I care about measurement theory? What are permissible transformations? What are levels of measurement? What about binary (0/1) variables? Is measurement level a fixed, immutable property of the data? Isn't an ordinal scale just an interval scale with error? What does measurement level have to do with discrete vs. continuous? Don't the theorems in a statistics textbook prove the validity of statistical methods without reference to measurement theory? Does measurement level detemine what statistics are valid? But measurement level has been shown empirically to be irrelevant to statistical results, hasn't it? What are some more examples of how measurement level relates to statistical methodology? Are there other theories of measurement? What's the bottom line? References
Pre-weighted Matching Pursuit Algorithms for Sparse Recovery ⋆

This paper presents a novel pre-weighted method for the matching pursuit algorithms, termed the Preweighted Matching Pursuit (PwMP) algorithm. The weighted measurement vector is obtained through the pre-weighted process to measurement matrix. PwMP recovers the weighted sparse signal by the weighted measurement vector and unweighted sensing matrix. At last, we get the sparse signal via weighted removal. It is empirically demonstrated that the PwMP algorithm outperforms many existing reconstruction algorithms for both zero-one and Gaussian type signals.
Motif-Level Anomaly Detection in Dynamic Graphs

As many real-world networks evolve over time, such as social networks, user-item networks, and IP-IP networks, anomaly detection for dynamic graphs has attracted growing attention. Most existing studies focus on detecting anomalous nodes or edges but fail to detect anomalous motif instances. In this paper, we propose MADG, a general Motif-level Anomaly Detection framework for dynamic Graphs, which can identify the anomaly in different motifs. Motifs are specific subgraph structures that frequently occur in a network and have been widely used in network analysis. In order to learn discriminative motif-level representations and leverage the temporal information from the dynamic graph, we design motif-augmented GCN and temporal self-attention. We first use motif-augmented GCN to model the topological structure among nodes and motif instances to learn their representations at each snapshot. Then, we feed the representations of multiple snapshots into the self-attention layer with relative temporal encoding in order to capture the evolutionary patterns. Extensive experiments on real-world dynamic graph datasets demonstrate the effectiveness of our proposed MADG framework.
A Review of Logistic Regression and its Application

OF THE THESIS A REVIEW OF LOGISTIC REGRESSION AND ITS APPLICATION by Sultana Mubarika Rahman Chowdhury Florida International University, 2021 Miami, Florida Professor Florence George, Co-Major Professor Professor Sneh Gulati, Co-Major Professor The purpose of this thesis is to do an in-depth review of logistic regression and its application. Additionally, comparison of four different methods of coefficient standardization was done using Heart Disease Dataset. These methods were compared based on testing accuracy, training accuracy, area under the curve, sensitivity, and specificity. Furthermore, logistic regression analysis was applied to National Longitudinal Study of Adolescence Health Survey (Add health) dataset to examine the relationship between anxiety or panic disorder and history of childhood maltreatment, medical conditions such as ADHD, PTSD, some socio-economic conditions and addiction. Results indicated; history of abuse has a significant effect on anxiety disorder. The number of abuses experienced also has a significant association with developing anxiety disorder later in life. Women had higher odds of having such a disorder if they faced maltreatment in their childhood. Moreover, having PTSD and Depression also increased the odds of anxiety substantially.
Multimodal medical image registration using geometric flow and Gabor filter

Image registration is an important step in medical image processing. In this paper, a new correlation-based method using the geometric flow and Gabor filter is proposed for multimodal medical image registration. Firstly, the geometric flow is employed to take advantage of the image regularity. Then the Gabor filter is adopted along different directions to yield a family of filtered images. A feature image, i.e. a weighted combination of these filtered images, is calculated according to the geometric flow. After computing the correlation coefficient between the feature images, the optimal transformation will be found using the particle swarm optimization. The scheme is verified on both simulated and real images. The experimental results demonstrate that this method can accurately register the multimodal medical images. Compared with the up-to-date Walsh transform method, this scheme can reduce translation error by 1.58 pixels, and rotation error by 1.36 degrees.
Water stress mitigation in vegetable cowpea through seed hardening and moisture conservation practices

A field experiment was conducted at the College of Horticulture, Vellanikkara during summer season of 2014 (January - March) to study the potential benefits of seed hardening, antitranspirant spray and mulching for mitigating water stress in vegetable cowpea variety Kashi kanchan. Pod yield, stover yield as well as dry matter production were highest in plots irrigated at 2 days interval (farmer’s practice) followed by those irrigated at 5 days interval. Among treatments, plastic mulching recorded the highest pod yield (2.3 Mg ha-1) which was on par with plant residue mulching (2.1 Mg ha-1). Moreover, mulching resulted in an increased yield of 162-182% over control. Among the seed primers, 0.5% NaCl, and among the antitranspirants, lime water spray recorded the highest pod yield of 1.9 Mg ha-1 and 1.5 Mg ha-1respectively.