Miracle-dz/UniFAR-FTUs huggingface dataset:
Test-Retest Reliability of Resting Brain Small-World Network Properties across Different Data Processing and Modeling Strategies

Resting-state functional magnetic resonance imaging (fMRI) with graph theoretical modeling has been increasingly applied for assessing whole brain network topological organization, yet its reproducibility remains controversial. In this study, we acquired three repeated resting-state fMRI scans from 16 healthy controls during a strictly controlled in-laboratory study and examined the test-retest reliability of seven global and three nodal brain network metrics using different data processing and modeling strategies. Among the global network metrics, the characteristic path length exhibited the highest reliability, whereas the network small-worldness performed the poorest. Nodal efficiency was the most reliable nodal metric, whereas betweenness centrality showed the lowest reliability. Weighted global network metrics provided better reliability than binary metrics, and reliability from the AAL90 atlas outweighed those from the Power264 parcellation. Although global signal regression had no consistent effects on the reliability of global network metrics, it slightly impaired the reliability of nodal metrics. These findings provide important implications for the future utility of graph theoretical modeling in brain network analyses.
Self-Assessment of INTERHEART Risk Stratification among the Middle-Aged Community in Malaysia

Research background and Objectives: Age is an independent risk factor for cardiovascular disease (CVD), but CVD risk factors are preventable, and lack of awareness of its risk factors is a contributing factor to CVDs. Middle-aged people may be more likely to engage in unhealthy lifestyle behaviours which can increase the risk of CVD. Health self-assessment is crucial for early detection and management of health issues and early lifestyle intervention for better personalised health management. This study aims to determine the self-assessment of INTERHEART risk classification among the middle-aged community in Malaysia. Method: Local community members aged 40–60 years and who are currently residing in Malaysia were recruited via non-randomised sampling. Sociodemographic characteristics and dietary pattern related to salt, fibre, fat (deep fried/snacks), poultry/meat intakes, and other cardiovascular risk factors (waist-hip ratio, medical history related to diabetes/hypertension, history/exposure of tobacco use, psychosocial status, and level of physical activity) were assessed; INTERHEART risk scores were then computed and stratified into low, medium and high risks. Results: Approximately 45% (n = 273/602) of middle-aged respondents in Malaysia are at moderate-to-high risk of cardiovascular events, with men being more likely to develop CVD compared to women. The results of the survey indicated that poultry/meat intake (61%), physical inactivity (59%), and second-hand smoke (SHS) exposure (54%) are the most prevalent risk factors among the respondents. One-third of the respondents consumed excessive salty food and deep fried foods/snacks/fast food, and only one-third of them consumed vegetables/fruits at a recommended level. It is worrying that about a quarter of the respondents felt several periodical/permanent stresses and even felt sad/blue/depressed for two weeks or more in a row. Males, labour workers, and those with lower educational levels are more likely to develop CVD events. Conclusions: This study found that 45% of the middle-aged respondents were having moderate-to-high risk for cardiovascular events with multiple risk factors related to unhealthy lifestyle habits and environmental factors. In addition to non-modifiable factors such as gender and age, sociodemographic factors, i.e., educational level and occupation, are equally important factors to determine CVD risk. Overall, the findings of this study emphasize the clinical relevance of assessing multiple factors in the determination of CVD risks for early prevention and management of cardiovascular diseases.
Impacts of Community Energy Trading on Low Voltage Distribution Networks

The wide spread of distributed energy resources (DERs) enabled the transformation of the passive consumer to an active prosumer. One of the promising approaches for optimal management of DERs and maximizing benefits for the community and prosumers is community energy trading (CET). CET gives the prosumers the flexibility and freedom to trade electricity within the neighborhood and maximize their economic benefits besides maximizing local consumption of renewable energy sources generation. Despite the economic benefits of CET for individuals and the whole community, it could cause impacts on the low voltage distribution network (LVDN). Therefore, there is a need for a comprehensive evaluation of the potential impacts of CET on LVDN. This study compared CET with the home energy management system (HEMS) regarding community operation costs and interaction with the retailer. Furthermore, this paper focused on assessing the impacts of CET between prosumers on the phase unbalance of LVDN. Moreover, the impacts on transformer loading, lines loading, and voltage deviations are assessed. Compared to the corresponding HEMS scenarios, the results demonstrate that CET reduces the community electricity cost by up to 31%. CET resulted in better self-consumption by reducing the exports to the retailer by 93% and better self-sufficiency by covering up to 54% of energy demand by community DERs. However, CET resulted in increasing the community peak demand, accordingly, higher impacts on the LVDN. The transformer is lightly loaded in all scenarios. CET resulted in limit violations in some lines, whereas most are lightly loaded. The voltage magnitude and voltage unbalance exceeded the acceptable limits at some nodes of the LVDN.
Degrees of computability and randomness

In this thesis we will study LR-reducibility, a weakening of Turing reducibility arising naturally in the context of relative randomness. We will focus particularly on the LRdegrees of c.e. and ∆2 sets. In chapter 2 we present a technique for lower cone avoidance in full approximation constructions, and use it to construct a c.e. LR-degree that is LRincomparable with a given intermediate ∆2 LR-degree. We also give a weak upward density result, showing that every low ∆2 LR-degree is bounded by an incomplete c.e. LR-degree. In chapter 3, we consider splittings of c.e. sets into two c.e. sets of the same LRdegree; an analogue of the notion of mitoticity previously studied in the context of Turing degrees. We show that there are c.e. sets that cannot be split into two c.e. sets of the same LR-degree, and that such sets may be Turing complete or low, and can be made to avoid nontrivial upper cones of c.e. LR-degrees. We also show that this notion differs from Turing nonmitoticity on both the low-for-random and non-low-for-random c.e. sets. Chapter 4 presents a construction of an LR-complete c.e. set that is non-cuppable in the c.e. Turing degrees. This is a strengthening of an earlier result of Barmpalias and Montalbán [7], and can also be seen as a strengthening of a theorem of Harrington (in [53]). In chapter 5 we introduce a new notion of promptness for c.e. sets, prompt nonlow-for-randomness, which can be seen as an LR-analogue of prompt simplicity. We investigate the Turing degrees of promptly non-low-for-random sets, and compare the property of prompt non-low-for-randomness to the traditional property of prompt simplicity.
The association between upward and downward earnings management and equity liquidity: empirical evidence from non-financial firms listed in Vietnam

Abstract The current study aims at examining the impact of earnings management on equity liquidity in the Vietnam stock market when considering the direction of earnings management. We used two proxies of equity liquidity, namely quoted spread and effective spread, and analyzed the data using ordinary least squares (OLS), fixed and random effect models (FEM, REM), and regression with generalized least squares (GLS) to determine the most suitable model. The findings of the study indicate that when downward earnings management increases, the quoted spread also decreases, thus the bid-ask spread is low, meaning that the liquidity is high. This can be explained by the fact that when firms conduct downward earnings management to reduce taxes, investors may expect to buy stocks from these firms at a better price, leading to an increase in trading demand on the market. Whereas upward earnings management has no impact on quoted spread. Our results also showed that there is no evidence to suggest that earnings management has an impact on the effective spread. This means that, in the absence of other factors, an increase in earnings management in either upward or downward directions does not affect the difference between buying and selling prices.
Rôle du facteur de terminaison de la traduction eRF3 (eukaryotic Release Factor 3) dans la stabilité des ARN messagers

La desadenylation des ARNm fait intervenir les complexes de desadenylation PAN2-PAN3 et CCR4-NOT-TOB mais aussi le complexe de terminaison de la traduction eRF1-eRF3. Ces trois complexes ont la capacite d'interagir avec la proteine PABP. Cependant, le role d'eRF3 n'est pas clairement etabli. Il a ete decrit que les facteurs eRF3, PAN3 et TOB sont en competition pour l'interaction avec PABP et qu'il y a un couplage entre la terminaison de la traduction et la desadenylation assure par eRF3. Chez l'homme, le gene eRF3/GSPT1 presente 5 formes alleliques qui different par le nombre de repetitions de codons GGC a l'extremite 5' du cadre de lecture (7, 9, 10, 11 et 12-GGC). Une correlation entre l'allele 12-GGC et le risque de developpement de cancer du sein et de l'estomac a ete mis en evidence. Notre objectif est (i) d'ameliorer notre comprehension du role d'eRF3 dans le processus de couplage traduction-degradation des ARNm, (ii) de comprendre l'effet du polymorphisme de la region N-terminale d'eRF3 sur son interaction avec PABP. A travers la methode de resonnance plasmonique de surface (SPR), nous montrons que l'affinite de la forme allelique 12-GGC est 10 fois plus faible que celle d'eRF3a (10-GGC). Cette difference est essentiellement due a la plus faible association de la forme 12-GGC avec PABP. La plus faible affinite de la forme 12-GGC d'eRF3 entrainerait une deregulation de la desadenylation au moins pour certains ARNm et pourrait ainsi promouvoir la proliferation cellulaire et la carcinogenese. La region N-terminale d'eRF3 contenant la repetition de glycine joue un role crucial dans l'interaction eRF3-PABP, dans la desadenylation et donc dans la stabilite de l'ARNm.
A Random-Walk Approach for Simulating Wastewater Transport and Transformations In the Unsaturated Zone

Point sources of wastewater in the subsurface are a potential threat to groundwater quality. Modelling wastewater transport and transformation requires dealing with a complex system of processes and interactions between solutes as well as between the solutes and the solid phase. Therefore the process-based reactive transport model WSTM (Water and Solute Transport Model) was developed, based on the random walk approach and fulfilling the Fokker-Planck equation for the unsaturated water flow. The main focus of this paper is on the mathematical formulation and applications of the model.
Variance Reduction Procedures for Market Risk Estimation

Monte Carlo simulation is one of the commonly used methods for risk estimation on financial markets, especially for option portfolios, where any analytical approximation is usually too inaccurate. However, the usually high computational effort for complex portfolios with a large number of underlying assets motivates the application of variance reduction procedures. Variance reduction for estimating the probability of high portfolio losses has been extensively studied by Glasserman et al. A great variance reduction is achieved by applying an exponential twisting importance sampling algorithm together with stratification. The popular and much faster Delta-Gamma approximation replaces the portfolio loss function in order to guide the choice of the importance sampling density and it plays the role of the stratification variable. The main disadvantage of the proposed algorithm is that it is derived only in the case of Gaussian and some heavy-tailed changes in risk factors. Hence, our main goal is to keep the main advantage of the Monte Carlo simulation, namely its ability to perform a simulation under alternative assumptions on the distribution of the changes in risk factors, also in the variance reduction algorithms. Step by step, we construct new variance reduction techniques for estimating the probability of high portfolio losses. They are based on the idea of the Cross-Entropy importance sampling procedure. More precisely, the importance sampling density is chosen as the closest one to the optimal importance sampling density (zero variance estimator) out of some parametric family of densities with respect to Kullback - Leibler cross-entropy. Our algorithms are based on the special choices of the parametric family and can now use any approximation of the portfolio loss function. A special stratification is developed, so that any approximation of the portfolio loss function under any assumption of the distribution of the risk factors can be used. The constructed algorithms can easily be applied for any distribution of risk factors, no matter if light- or heavy-tailed. The numerical study exhibits a greater variance reduction than of the algorithm from Glasserman et al. The use of a better approximation may improve the performance of our algorithms significantly, as it is shown in the numerical study. The literature on the estimation of the popular market risk measures, namely VaR and CVaR, often refers to the algorithms for estimating the probability of high portfolio losses, describing the corresponding transition process only briefly. Hence, we give a consecutive discussion of this problem. Results necessary to construct confidence intervals for both measures under the mentioned variance reduction procedures are also given.
Nanocomposites Based on Spin-Crossover Nanoparticles and Silica-Coated Gold Nanorods: A Nonlinear Optical Study

A nanocomposite based on silica-coated AuNRs with the aminated silica-covered spin-crossover nanoparticles (SCO NPs) of the 1D iron(II) coordination polymer with the formula [Fe(Htrz)2(trz)](BF4) is presented. For the synthesis of the SCO NPs, the reverse micelle method was used, while the gold nanorods (AuNRs) were prepared with the aspect ratio AR = 6.0 using the seeded-growth method and a binary surfactant mixture composed of cetyltrimethylammonium bromide (CTAB) and sodium oleate (NaOL). The final nanocomposite was prepared using the heteroaggregation method of combining different amounts of SCO NPs with the AuNRs. The nonlinear optical (NLO) properties of the hybrid AuNRs coated with different amounts of SCO NPs were studied in detail by means of the Z-scan technique, revealing that the third-order NLO properties of the AuNRs@SCO are dependent on the amount of SCO NPs grafted onto them. However, due to the resonant nature of the excitation, SCO-induced NLO switching was not observed.
The role of vowel quality in pitch comparison

In normal speech, the fundamental frequency (F0) is higher for close than for open vowels. This phenomenon is called intrinsic F0 (IF0). With constant F0, open vowels sound higher pitched than close ones. Applying Hellstrom’s sensation weighting model for stimulus comparison, IF0 was hypothesized to contribute to this effect by making listeners’ adaptation levels (ALs) for F0 differ between vowels. Two groups of listeners (language students, choir singers) judged, for pairs of successively presented synthetic vowels, which vowel had the higher pitch. The judgments were clearly based on vowel quality; there were also large time‐order effects. The results were well accounted for by the model. It is suggested that the adaptation‐weighting mechanism increases the discriminability of vowels, and also equalizes the average pitch of different vowels in normal speech.
Generalized Nash games with shared constraints: Existence, efficiency, refinement and equilibrium constraints

The thesis pertains to some fundamental questions in the theory of games. Our focus is on a class of noncooperative N -player games, called generalized Nash games with shared constraints, or simply, shared-constraint games [Ros65]. In such a game, every strategy-tuple is constrained to lie in a subset C of the product space of strategies. Thus strategies available to a player are only those which when taken jointly with the strategies of all other players, form a tuple that lies in C. The set C is called the shared constraint. Despite their relevance in real-world settings, there are many theoretical properties of these games that are not well understood. What interests us in this thesis is the theoretical character of the equilibria of these games. Shared-constraint games admit two kinds of equilibria: generalized Nash equilibria (GNE) that are ill-posed and often intractable and a smaller subset of them (called variational equilibria or VE) satisfying an exogenous regularity condition that are well-posed and surprisingly tractable. We seek to clarify the nature of these equilibria, study their economic implications and exploit their properties to advance the analytical theory for conventional and somewhat unconventional shared-constraint games. The unconventional shared-constraint games are in fact a class of dynamic games, called multi-leader multi-follower games, which we view through the lens of shared constraints. Four questions are addressed in this thesis with the central theme as shared-constraint games. In the first part of the thesis we present a refinement [MWG95] of the GNE. A refinement of an equilibrium is a subset of the set of equilibria which is nonempty whenever the original set of equilibria is nonempty. Refined equilibria are representative of the set of equilibria and have additional properties that make them more attractive as solution concepts than the original equilibria. The contribution of this work is a theory that gives sufficient conditions for a game to admit the VE as a refinement of the GNE. These conditions are expressed in terms of the Brouwer degree, which is seen to relate the GNE and the VE in a profound manner. Importantly, for certain classes of games, these conditions are also seen to be necessary. The degree theoretic relationship holds in both, primal and primal-dual space. Our work unifies some previously known results and provides mathematical justification for ideas that were known to be intuitive appealing but were hitherto unsubstantiated formally. The second part of this thesis is about multi-leader multi-follower games. These games are
Indoor PDR Trajectory Matching by Gyroscope and Accelerometer Signal Sequence Without Initial Motion State

In recent years, pedestrian dead reckoning (PDR) is considered a popular localization solution for its reliable accuracy. To tackle its intrinsic problem of accumulative errors, various methods are proposed to refine the trajectory by indoor space information to promote localization accuracy. However, these methods usually require the initial motion state, such as starting location and absolute orientation to infer the coordinates. They may be limited because the initial location has to be determined by other highly precise sensors and required people holding the phone ahead in the fixed position to ensure the ${x}$ -axis is consistent with the heading. In this article, we release the constraints by utilizing the gyroscope and accelerometer sensor sequence to estimate the orientation change and trajectory length, which are insensitive to the initial motion state, to build a hidden Markov model (HMM) model to infer the initial motion and refine the trajectory by spatial information. First, the indoor environment is divided into grids to construct a directed map. Then, we use the gyroscope and accelerometer to collect the signal sequence to represent the rotation angle and length information of the trajectory. Finally, the Viterbi algorithm is used for the inference of the whole trajectory including the initial location and orientation. The experiments show that the initial location and absolute orientation can be predicted as the convergence of the matching candidates when the length of the trajectory increases. And the localization error of the proposed method is superior to the compared method with the benefit of rotation angle and trajectory length.
Unemployment insurance design with repeated choices

This article characterizes the relation between the equilibrium unemployment insurance replacement rate and the frequency of its political choice. We first use a tractable analytical model to show how insurance, incentive, and redistribution effects interact at the equilibrium. We then examine a fully repeated choices equilibrium in a quantitative heterogeneous agents model and show that unemployment persistence, whether a policy is announced first or not, and the type of the political process are key determinants of the relation between the equilibrium replacement rate and the frequency of its choice. In a utilitarian welfare context, we find that the equilibrium replacement rate is higher if the policy is chosen more frequently but this relation is reversed in a median voter context.
Air Pollution: A Silent Key Driver of Dementia

In 2017, the Lancet Commission on Dementia Prevention, Intervention, and Care included air pollution in its list of potential risk factors for dementia; in 2018, the Lancet Commission on Pollution concluded that the evidence for a causal relationship between fine particulate matter (PM) and dementia is encouraging. However, few interventions exist to delay or prevent the onset of dementia. Air quality data are becoming increasingly available, and the science underlying the associated health effects is also evolving rapidly. Recent interest in this area has led to the publication of population-based cohort studies, but these studies have used different approaches to identify cases of dementia. The purpose of this article is to review recent evidence describing the association between exposure to air pollution and dementia with special emphasis on fine particulate matter of 2.5 microns or less. We also summarize here the proposed detailed mechanisms by which air pollutants reach the brain and activate the innate immune response. In addition, the article also provides a short overview of existing limitations in the treatment of dementia.