Miracle-dz/UniFAR-FTUs huggingface dataset:
Mental Health Literacy and Its Relation to Sexual and Gender Minority Identity in a Diverse Sample of Undergraduate College Students

Research indicates that mental health literacy (MHL) can promote adaptive health behaviors and reduce stigma toward mental health problems. However, few studies have examined MHL among sexual and gender minority (SGM) individuals, a population that is disproportionately affected by negative mental health outcomes due to experiences with minority stress. This study aimed to fill this gap in the literature by investigating the association between MHL and SGM identity in a sample of demographically diverse college students in New York City. In addition to using a comprehensive measure of MHL, we recorded participants’ self-reported history of a psychological disorder. Results indicated that SGM identity was associated with higher MHL than non-SGM identity over and above other sociodemographic characteristics. This association was fully driven by participants’ self-reported history of a psychological disorder, which was more frequently reported by SGM participants as compared to non-SGM participants. These findings suggest that SGM college students may have higher MHL than non-SGM college students due to their relatively greater likelihood of having personally experienced a psychological disorder. Early MHL intervention with SGM individuals may be warranted to increase MHL prior to a potential onset of psychopathology, with the larger goal of facilitating more positive mental health outcomes. Implications for interventions in school-based settings and future research initiatives are also discussed.
Unfolding executive coaches' identity work through the social constructivist lens: Coach–coachee–organisation

This study responds to a recent call on coaches' professional identity work through a socially con-textualised lens. Coaches, as the freelancer, encounter complex working relationships with clients due to multiple contracting entities; yet coaches' identity work has been neglected in the extant training and development courses. A total of 36 semi ‐ structured interviews with coaches and relational others (e.g., coachees and organisational stakeholders) were conducted to understand how coaches develop professional identity as part of their career development in responding to interactions with relational others. The research findings identify that learning facilitator is the core identity of coaches regardless of varied stages of the coaching process. Three layers of sub ‐ identity are distinguished for them to handle a multi ‐ level working relationship with clients. Coaches often ‘ travel ’ in ‐ and ‐ out between layers of these sub ‐ identities to incorporate micro ‐ personal career interests, meso coaching dyadic working relationships and the macro ‐ level organisational scope into their identity development and negotiation. Accordingly,
Low-temperature phase of BaTiO3: Piezoelectric, dielectric, elastic, and photoelastic properties from ab initio simulations

A complete theoretical characterization of dielectric, elastic, photoelastic, and piezoelectric tensors of the low-temperature rhombohedral phase of BaTiO3 was performed by accurate ab initio simulations within periodic boundary conditions, using one-electron Hamiltonians and atom-centered Gaussian-type-function basis sets as in the crystal program. Because this phase is stable only at very low temperature, experimental characterization is difficult, and none of such tensorial properties have been measured. For this reason, we validated our method by comparing structural, electronic, and vibrational properties of the other three phases of BaTiO3 (cubic, tetragonal, and orthorhombic) with available experimental data. The effect of the adopted one-electron Hamiltonian on the considered tensorial properties, beyond the simple local density approximation and the dependence on the electric field frequency of dielectric and photoelastic constants, is explicitly investigated. © 2014 American Physical Society.
Displacing the other to unite the nation: The parallel society legislation in Denmark

In 2018, the then right-wing government in Denmark led by Lars Løkke Rasmussen and supported by the extreme right-wing party Danish People’s Party presented new legislation to end ‘parallel societies’ in Denmark by toughening the criminal law, enforcing Danish knowledge and nursery school assistance to toddlers, and, more importantly for this article, a series of urban interventions in ‘ghetto areas’ considered as such mainly when the proportion of immigrants and descendants from non-Western countries exceeded 50 per cent. Until recently research has focused on either the discursive elements of the ‘ghetto politics’ in Denmark or the urban interventions from an architectural or urban planning point of view. However, newfangled research deal with the entwined economic elements. In this article, I compare the different developmental plans proposed in the affected areas because of the legislation, with an aim to reach further and point at the inherent elements of urban b/ordering, that is, measures taken to attain social order and gain legitimacy by demarcating categories of people to incorporate some and exclude others through urban space. Indeed, through this comparison, I conclude that the ghetto legislation is a compelling example of the urban b/ordering inherent to the politics and dynamics of current liberal capitalist social democracies. It is a social experiment that remodels the geography of Denmark in terms that recall the eugenic and hygienic social and urban policies of the 19th century and form part of a worrying pattern that may have consequences that go beyond the stated ones.
Application of Johnson Criteria in Evaluating Field Detection and Recognition Probability of IR System

The apparent average temperature difference and critical dimension of actual target and background were acquired through retrieving infrared target image.The retrieved apparent temperature difference and the measured MRTD curve were combined to determine the corresponding spacial frequency.And,a quantitative relationship between the target infrared image and the probability of detection and recognition was established with Johnson criteria and target transfer probability function(TTPF). The method avoids operater′s subjective judging,so the result is more impersonal.This method was experimentally validated in evaluating the detection and recognition probability of IR system.
Smoothing-parameter tuning for regularized PET image reconstruction using deep learning

In regularized PET image reconstruction, the performance of a reconstruction algorithm depends crucially on the smoothing parameter that controls the balance between the likelihood term and the regularization term. In this work, we propose a new method of tuning the smoothing parameter using deep learning. Unlike the traditional estimation-theoretic approach where the smoothing parameter is estimated directly from the observed noisy data, the deep learning-based method requires large amounts of prior training pairs, which are usually unavailable in routine clinical practice. To overcome this problem, we extend our previous work on the training-set approach which provides a mathematical formula to calculate the smoothing parameter for the simple quadratic spline regularizer. We note that this training-set approach is effective only when the noiseless representative exemplars are available. For deep learning, however, collecting large amounts of such noiseless exemplars for a training dataset is unrealizable. Therefore, instead of collecting them, we generate diverse images similar to the exemplars of the ground truth radiotracer distribution using Gibbs sampling followed by post-processing and calculate the smoothing parameter value for each image. For our deep learning model, we use the residual network architecture that allows deeper layers with higher efficiency than the typical convolutional neural network. The experimental results show that our deep learning method provides optimal values of the smoothing parameter, which are comparable to the accurate values calculated from noiseless exemplars, for a wide range of underlying images.
Kelayakan Finansial Pendirian Bisnis Sosis Sapi PT XYZ di Kota Bogor, Jawa Barat, Indonesia

Sausage products are one of the most popular animal-based foods that considerably contribute to daily human protein needs. As a positive response, PT XYZ, one of the meat processors in Bogor City, plans to establish a beef sausage business. The purpose of the study was to determine the financial feasibility of the proposed business by PT XYZ. Financial feasibility was based on cash flow analysis, profit and loss analysis, and business feasibility analysis. The latter was evaluated based on Net Present Value (NPV), Gross B/C, Net B/C, Internal rate of return (IRR), and payback period indicators. The proposed business showed NPV IDR 67,019,684.22, Gross B/C, of 1.03, a Net B/C of 3.14, an IRR of 66%, and a payback period of 2 Years. The beef sausage business proposed by PT XYZ was financially feasible in regard to those parameters.
Application of fluorescent dyes for some problems of bioelectromagnetics

Fluorescent organic dyes solutions are used for non-contact measurement of the millimeter wave absorption in liquids simulating biological tissue. There is still not any certain idea of the physical mechanism describing this process despite the widespread technology of microwave radiation in the food industry, biotechnology and medicine. For creating adequate physical model one requires an accurate command of knowledge concerning to the relation between millimeter waves and irradiated object. There were three H-bonded liquids selected as the samples with different coefficients of absorption in the millimeter range like water (strong absorption), glycerol (medium absorption) and ethylene glycol (light absorption). The measurements showed that the greatest response to the action of microwaves occurs for glycerol solutions: R6G (building-up luminescence) and RC (fading luminescence). For aqueous solutions the signal is lower due to lower quantum efficiency of luminescence, and for ethylene glycol — due to the low absorption of microwaves. In the area of exposure a local increase of temperature was estimated. For aqueous solutions of both dyes the maximum temperature increase is about 7° C caused with millimeter waves absorption, which coincides with the direct radio physical measurements and confirmed by theoretical calculations. However, for glycerol solution R6G temperature equivalent for building-up luminescence is around 9° C, and for the solution of ethylene glycol it’s about 15°. It is assumed the possibility of non-thermal effect of microwaves on the different processes and substances. The application of this non-contact temperature sensing is a simple and novel method to detect temperature change in small biological objects.
The Effect of Marketing Communications on Consumer Decisions in Using The XL Cellular Card In Banda Aceh: Consumer Motivation a Mediation Variable

Modern marketing is not only oriented by developing good products, interesting rate members, and making them affordable for consumers, but the company has to build communication with the potential consumers in order to receive their aspirations and wills intended to fulfill and satisfy the consumers' need. This research is focused on the impact of marketing communication on the consumers' decision in using cellular card XL, through consumers' motivation. The goal of this study is to determine whether there is an indirect effect of marketing communication for consumer decisions through consumer motivation. The object of this study is the user's XL in Banda Aceh. The sampling method used in this study is the purposive sampling method, the method of sampling based on certain criteria. The analysis technique used is path analysis. The result of this study indicates that marketing communication directly has positive and significant effects on consumers' motivation, consumers' motivation has positive and significant effects on consumers' decisions, and marketing communication has positive and significant effects on consumers' decisions. Meanwhile, marketing communication indirectly has positive effects on consumers' decisions through consumers' motivation.
Brain glucose metabolism and dopamine transporter changes in rats with morphine‐induced conditioned place preference

Addiction to morphine is a chronic brain disease leading to compulsive abuse. Drug addiction animal models with and without conditioned place preference (CPP) training have been used to investigate cue‐elicited drug craving. We used 18F‐fluorodeoxyglucose (18F‐FDG) and 11C‐2‐β‐carbomethoxy‐3‐β‐(4‐fluorophenyl)tropane (11C‐CFT) micro‐PET/CT scans to examine the regional changes in brain glucose metabolism and dopamine transporter (DAT) availability to study their relationship underlying drug memory in morphine‐treated rat models with and without CPP. Standardized uptake value ratio (SUVr) of 18F‐FDG significantly decreased in the medial prefrontal cortex (mPFC) and cingulate with short‐term morphine administration compared with the baseline condition. Voxelwise analysis indicated glucose metabolism alterations in the somatosensory cortex, hippocampus and cingulate in morphine‐treated rats and in the striatum, thalamus, medial prefrontal cortex, primary motor cortex and many regions in the cortex in the CPP group compared with the baseline condition. Alterative glucose metabolism was also observed in the striatum, primary somatosensory cortex and some cortical regions in the CPP group compared with morphine alone group. DAT expression alterations were only observed in the long‐term morphine compared with the short‐term morphine group. This study shows that cerebral glucose metabolism significantly altered during morphine administration and CPP process mainly in the mPFC, striatum and hippocampus, which indicates that the function of these brain regions is involved in cue‐induced craving and memory retrieval.
The Investigation of EM Scattering from the Time-Varying Overturning Wave Crest Model by the IEM

Investigation of the electromagnetic (EM) scattering of time-varying overturning wave crests is a worthwhile endeavor. Overturning wave crest is one of the reasons of sea spike generation, which increases the probability of false radar alarms and reduces the performance of multitarget detection in the environment. A three-dimensional (3D) time-varying overturning wave crest model is presented in this paper; this 3D model is an improvement of the traditional two-dimensional (2D) time-varying overturning wave crest model. The integral equation method (IEM) was employed to investigate backward scattering radar cross sections (RCS) at various incident angles of the 3D overturning wave crest model. The super phenomenon, where the intensity of horizontal polarization scattering is greater than that of vertical polarization scattering, is an important feature of sea spikes. Simulation results demonstrate that super phenomena may occur in some time samples as variations in the overturning wave crest.
A journey through second order BSDEs and other contemporary issues in mathematical finance.

This PhD dissertation presents two independent research topics dealing with contemporary issues in mathematical finance, the second one being divided into into two distinct problems. Throughout the first part of the dissertation, we study the notion of second order backward stochastic differential equations (2BSDE in the following), first introduced by Cheredito, Soner, Touzi and Victoir, then reformulated by Soner, Touzi and Zhang. We start by proving an extension of their existence and uniqueness results to the case of a continuous generator with linear growth. Then, we pursue our study with another extension to the case of a quadratic generator. The theoretical results obtained in that chapter allow us to solve a problem of utility maximization for an investor in an incomplete market, the source of incompleteness being on one hand the restrictions on the class of admissible trading strategies, and on the other hand the fact that the volatility of the market is uncertain. We prove the existence of optimal strategies, we characterize the value function of the problem thanks to a 2BSDE and solve explicetely several examples which give further insight into the main modifications introduced by the uncertain volatility framework. We conclude the first part of the dissertation by introducing the notion of 2BSDEs reflected on an obstacle. We prove existence and uniqueness of the solutions of those equations and propose an application to the pricing problem of American options under volatility uncertainty. The first chapter of the second part of the dissertation deals with a problem of option pricing in an illiquidity model. We provide asymptotic expansions of those prices in the infinite liquidity limit and highlight a transition phase effect depending on the regularity of the payoff considered. We also give numerical results. Finally, the last chapter of this thesis is devoted to a Principal/Agent problem with moral hazard. A bank (the agent) has a certain number of defaultable loans and is ready to exchange their interests with the promess of payments. The bank can influence the default probabilities by choosing whether it monitors the loans or not, this monitoring being costly for the bank. Those choices are only known by the bank itself. Investors (the principal) want to design contracts which maximize their utility while implicitely giving incentives to the bank to monitor all the loans at all times. We solve explicitely this optimal control problem, we describe the associated optimal contract and its economic implications and provide some numerical simulations.
Close-in stellar companions in close binary stars

Close binary stars are so close that one component has an effect on the evolution of the other. But how do they form and evolve? This is an unsolved problem. One speculation is that the binary is a part of a hierarchical triple and its orbit shrinks due to interaction with the third component. Therefore, searching for and investigating tertiary components, especially close-in ones, in close binary stars are important for understanding their origin, as well as to test theories of star formation and stellar dynamical interaction.
Reduced basis methods for partial differential equations with stochastic influences

This thesis is concerned with the development of reduced basis methods for parametrized partial differential equations (PPDEs) with stochastic influences. We consider uncertainties in the operator, right-hand side, boundary conditions and in the underlying domain. We are particularly interested in situations where the PPDE has to be evaluated quite often for various instances of the deterministic parameters and the stochastic influences. In the stochastic framework, such a situation occurs, e.g., in Monte Carlo simulations to compute statistical quantities such as mean, variance, or other moments. For the efficient application of the reduced basis method, it is necessary to develop affine decompositions with respect to the stochastic influences. We therefore extend the methodology of the empirical interpolation for the application in the stochastic setting, in particular for noisy input data. Alternatively, we also use a truncated Karhunen–Loève (KL) expansion to resolve and affinely decompose the stochasticity. We derive a-posteriori error bounds for the state variable and output functionals, including also the KL-truncation errors. Non-standard dual problems are introduced for the approximation and analysis of special quadratic outputs which can in particular be applied to efficiently approximate statistical quantities such as mean and moments. We provide new error bounds for such outputs, outperforming standard approximations. To reduce the number of affine terms and hence for the improvement of the efficiency of the reduced simulations, we generalized the partitioning concepts for explicitly given deterministic parameter domains to arbitrary input functions with possibly unknown, high-dimensional, or even without direct parameter dependencies. No a-priori information about the input is necessary. We use all the presented methods for the application to PPDEs with stochastic influences on stochastic and additionally parametrized domains.
Occurrence and potential harms of organochlorine pesticides (OCPs) in environment and their removal by periphyton

Abstract Organochlorine pesticides (OCPs) have been widely used around the world due to their high-efficiency and broad-spectrum insecticidal effects. However, they pose a severe threat to ecosystems and human health due to their easy bioaccumulation and high toxicity. Periphyton is ubiquitous in the submerged substrates surface. It plays a crucial role in carbon, nutrients elements cycling and contaminants transformation in environment. Periphyton can remove OCPs through bioadsorption, bioaccumulation and biodegradation, which alters the fate of OCPs in environment. This review presents a comprehensive summary of OCPs occurrence, global cycle, potential harm in environment, and their removal by periphyton. The OCPs residual have been detected frequently in different environmental medias such as water, soil, atmosphere, sediment, and organisms. Their harm is depending on their physicochemical properties and the exposure route. The main compositions and functions of periphyton have been summarized. Moreover, the artificial cultivation methods of periphyton in laboratory and in-situ field are compared. In addition, the mechanisms of periphyton-mediated OCPs removal and the main factors impacting OCPs removal are also discussed. Periphyton could self-regulate its biological communities to adapt to the OCPs and environment, and then regenerate new species to degrade OCPs. Finally, the prospect of OCPs removal by periphyton and future studies are also proposed. This review provides a systematic introduction on current knowledge of OCPs occurrence, cycle, potential harm in environment, and their removal by periphyton. Graphical Abstract
Assessing informative drop-out in models for repeated binary data

Drop-outs are a common problem in longitudinal studies. In terms of statistical models for the data, there are three types of drop-out mechanisms: drop-out occurring completely at random (CRD), drop-out occurring at random (RD) and informative drop-out (ID). The drop-out mechanism is classified as C R D if the drop-out mechanism is independent of the measurements; as R D if the drop-out mechanism depends only on the observed but not the unobserved measurements, and as ID if the drop-out mechanism depends on both the observed and unobserved measurements. C R D and R D are referred to as ignorable because the drop-out mechanism can be ignored for the purpose of making inferences about the observed measurements, while ID is non-ignorable. Analyses based on an assumption of ignorable drop-out, when in reality the drop-out mechanism is non-ignorable, can lead to misleading or biased results. Likelihood-based models for continuous and categorical longitudinal data subject to non-ignorable drop-out have been developed. In this thesis, we focus on exploring likelihood-based models for binary longitudinal data subject to informative drop-out. The two modelling approaches considered are a selection model proposed by Baker (1995) and a transition model proposed by Liu et al. (1999). We apply these models to a data set from a multiple sclerosis (MS) clinical trial. The aims of the analyses are to investigate whether there is an indication of informative drop-out in this data, and to assess the sentivity of inferences concerning the treatment effects to the underlying drop-out mechanisms. We do not attempt to provide a definitive