Miracle-dz/UniFAR-FTUs huggingface dataset:
Student loan debt and U.S. married households’ stock investment decisions

This study aims to examine the effects of student loan debt on the decisions of U.S. married households to invest in stocks located in non-retirement accounts. Using longitudinal datasets from the 2011 to 2017 U.S. Panel Study of Income Dynamics and a fixed effects logit model, the results show mixed findings. The presence of student debt decreases the probability that married households will own stocks, but the amount of student debt does not show a statistically significant effect. The findings suggest that the incidence of student debt raises the perception of liquidity constraints and debt burden among married households.
Bi-objective finite horizon optimal control problems with Bolza and maximum running cost

In this paper, we investigate optimal control problems with two objective functions of different nature that need to be minimized simultaneously. One objective is in the classical Bolza form and the other one is defined as a maximum running cost. Our approach is based on the Hamilton-Jacobi-Bellman framework. In the problem considered here the existence of Pareto solutions is not guaranteed. So first, we consider the bi-objective problem to be minimized over the convexified dynamical system. We show that if a vector is (weak) Pareto optimal solution for the convexified problem, then there exists an (weak) e-Pareto optimal solution of the original problem that is in the neighborhood of this vector. After we define an auxiliary optimal control problem and show that the weak Pareto front of the convexified problem is a subset of the zero level set of the corresponding value function. Moreover, with a geometrical approach we establish a characterization of the Pareto front. It is also proved that the (weak) e-Pareto front is contained in the negative level set of the auxiliary optimal control problem that is less or equal e. Some numerical examples are considered to show the relevance of our approach.
Anatomy of the Sagittarius A complex. II : λ1300 μm and λ870 μm continuum observations of Sgr A and its subm/IR spectrum

We present a λ870μm map and ON-OFF measurements of Sgr A * and determine its flux density to be S 870μm =4.8±1.2 Jy. We confirm flux densities of S 1300μm =2.6±0.6 Jy and S 350μm =18.5±9 Jy derived earlier (Zylka & Mezger 1988; Mezger et al. 1989). We reanalyse previously published and unpublished high-resolution flux density measurements to determine its spectrum from radio wavelengths to the Near Infrared (NIR)
Copy Number Variation Regions Differing in Segregation Patterns Span Different Sets of Genes

Simple Summary Copy number variations (CNVs) are a substantial fraction of the total genetic variability and have a major effect on phenotypic performance by altering gene expression patterns. However, the identification of CNVs remains challenging. Recent studies suggest that CNVs hardly fit with Mendelian segregation patterns and can be classified as segregating (shared by parents and offspring) and non-segregating. Both CNV classes have been hypothesized to be important in explaining between-populations (segregating CNVs) and between-individuals (non-segregating CNVs) differences in performance. Here, we report that the two CNV classes spanned different sets of genes, thus supporting that theory. Abstract Copy number variations regions (CNVRs) can be classified either as segregating, when found in both parents, and offspring, or non-segregating. A total of 65 segregating and 31 non-segregating CNVRs identified in at least 10 individuals within a dense pedigree of the Gochu Asturcelta pig breed was subjected to enrichment and functional annotation analyses to ascertain their functional independence and importance. Enrichment analyses allowed us to annotate 1018 and 351 candidate genes within the bounds of the segregating and non-segregating CNVRs, respectively. The information retrieved suggested that the candidate genes spanned by segregating and non-segregating CNVRs were functionally independent. Functional annotation analyses allowed us to identify nine different significantly enriched functional annotation clusters (ACs) in segregating CNVR candidate genes mainly involved in immunity and regulation of the cell cycle. Up to five significantly enriched ACs, mainly involved in reproduction and meat quality, were identified in non-segregating CNVRs. The current analysis fits with previous reports suggesting that segregating CNVRs would explain performance at the population level, whereas non-segregating CNVRs could explain between-individuals differences in performance.
Ceramic Porous Preforms Manufactured from Waste Materials

The goal of this study is to develop a method of manufacturing porous ceramic skeletons used as semi-finished products for re-inforcement of composite materials or as filters. For manufacturing skeletons, only waste materials from coal combustion (fly ashes and bottom slags) as well as rubber granules from used tires and car parts were used. These granules were a pore-forming agent that underwent thermal degradation during sintering process. The influence of sintering temperature, portion, and type of rubber granules on the porosity of developed ceramic skeletons was determined. The study of structure of base materials and the developed ceramic skeletons in a scanning electron microscope as well as their X-ray phase analysis were made. results will allow to predict phases that can be formed on the metal-reinforcement interface during pressure infiltration.
Environmental Modeling and Traffic Simulation: A multivariate approach to monitor urban air pollutant agents

This work presents an interdisciplinary assessment examining air quality tracking in urban environments. This application is well suited to be approached with wireless sensor networks' paradigm in their overall variations. The proposed modeling application takes advantage of Vehicle Sensor Networks (VSN) by embedding sensor nodes in public transportation, addressing this study case with bus lines so that the mobiles spread the sampling activity through many different places visited during the route. Simultaneously, it alleviates power management restrictions, packaging dimensions (size and weight), and general maintenance issues. We perform environmental modeling based on real data considering temporal and spatial multivariate behavior on observed phenomena. We consider the city of São Paulo in our case study and parse the asserted data to create a multivariate map of samples, showing the behavior of five different air pollutants from fossil-fueled vehicles (CO, O3, PM10, NO2 and SO2) simultaneously while it also varies in time. Furthermore, the experiment considers a detailed description of roads, bus lines, vehicle itineraries, and general traffic information. The input data that has unformatted or missing information due to being sourced from real sensors is handled to create the map mentioned above. Our methodology addresses the following: 1) the mentioned environmental simulation, 2) the deployment of mobile sensor nodes and performing sensing process, 3) the implementation of network activity and delivery of collected data, 4) visualization of monitored environment based on gathered data using Voronoi Diagrams to fill blank data at non-reached areas. Finally, our VSN-based approach improved 126 times lower error and 11 times higher coverage compared to conventional monitoring with air quality stations.
Estimation and prediction of time-varying GARCH models through a state-space representation: a computational approach

ABSTRACT We propose a state-space approach for GARCH models with time-varying parameters able to deal with non-stationarity that is usually observed in a wide variety of time series. The parameters of the non-stationary model are allowed to vary smoothly over time through non-negative deterministic functions. We implement the estimation of the time-varying parameters in the time domain through Kalman filter recursive equations, finding a state-space representation of a class of time-varying GARCH models. We provide prediction intervals for time-varying GARCH models and, additionally, we propose a simple methodology for handling missing values. Finally, the proposed methodology is applied to the Chilean Stock Market (IPSA) and to the American Standard&Poor's 500 index (S&P500).
Psychiatric Treatment in Pregnancy: A Narrative Review

Pregnancy, childbirth and the puerperium are a series of transformations and huge changes in a woman’s life, which may also be accompanied by various mental problems. Very often, women experiencing mental disorders during this period and their doctors face a decision on safety of treatment. The purpose of the following review was to assess the safety of treatment during pregnancy. Internet scientific database PubMed was searched. There are groups of psychiatric medications contraindicated during pregnancy such as valproates as well as relatively safe ones such as selective serotonin reuptake inhibitors (SSRIs) or antipsychotics. However, in every clinical situation, a decision should be made with caution, based on individual characteristics of patient, severity of disorder and clinical picture.
Upper bound for effective differential elimination

We present an upper bound for the number of differentiations in differential elimination for systems of polynomial ODEs, the first such bound as far as we are aware. Elimination of unknowns from systems of equations, starting with Gaussian elimination, is a problem of general interest. In this paper, we study elimination of unknowns from systems of polynomial ODEs, that is, how to derive consequences of a system that do not depend on a selected set of unknowns. This is called differential elimination. One way to do this is to find a uniform (independent of the coefficients of the system) upper bound $N$ so that, after differentiating the system $N$ times, the remaining computation becomes polynomial elimination.
Modeling association between multivariate correlated outcomes and high-dimensional sparse covariates: the adaptive SVS method

ABSTRACT The problem of modeling the relationship between a set of covariates and a multivariate response with correlated components often arises in many areas of research such as genetics, psychometrics, signal processing. In the linear regression framework, such task can be addressed using a number of existing methods. In the high-dimensional sparse setting, most of these methods rely on the idea of penalization in order to efficiently estimate the regression matrix. Examples of such methods include the lasso, the group lasso, the adaptive group lasso or the simultaneous variable selection (SVS) method. Crucially, a suitably chosen penalty also allows for an efficient exploitation of the correlation structure within the multivariate response. In this paper we introduce a novel variant of such method called the adaptive SVS, which is closely linked with the adaptive group lasso. Via a simulation study we investigate its performance in the high-dimensional sparse regression setting. We provide a comparison with a number of other popular methods under different scenarios and show that the adaptive SVS is a powerful tool for efficient recovery of signal in such setting. The methods are applied to genetic data.
Rare Earth Elements Recovery from Primary and Secondary Resources Using Flotation: A Systematic Review

Rare earth minerals (REMs) contain rare earth elements (REEs) that are important in modern technologies due to their unique magnetic, phosphorescent, and catalytic properties. However, REMs are not only non-renewable resources but also non-uniformly distributed on the Earth’s crust, so the processing of REE-bearing secondary resources via recycling is one potential route to ensure the long-term sustainability of REE supply. Flotation—a method that separates materials based on differences in their surface wettability—is a process applied for both mineral processing and recycling of REEs, especially when the particles are fine and/or a high-purity product is required. In this review, studies about rare earth flotation from 2012 to 2021 were systematically reviewed using the PRISMA guideline. It was found that most REM flotation research works focused on finding better collectors and depressants while, for recycling, studies on advanced flotation techniques like froth flotation, ion flotation, solvent sublation, electroflotation, and adsorbing colloid flotation with an emphasis on the recovery of dissolved REEs from aqueous solutions dominated.
VALUATION OF VULNERABLE OPTIONS UNDER THE DOUBLE EXPONENTIAL JUMP MODEL WITH STOCHASTIC VOLATILITY

In this paper, we extend the framework of Klein [15] [Journal of Banking & Finance 20: 1211–1229] to a general model under the double exponential jump model with stochastic volatility on the underlying asset and the assets of the counterparty. Firstly, we derive the closed-form characteristic functions for this dynamic. Using the Fourier-cosine expansion technique, we get numerical solutions for vulnerable European put options based on the characteristic functions. The inverse fast Fourier transform method provides a fast numerical algorithm for the twice-exercisable vulnerable Bermuda put options. By virtue of the modified Geske and Johnson method, we obtain an approximate pricing formula of vulnerable American put options. Numerical simulations are made for investigating the impact of stochastic volatility on vulnerable options.
A Cross Check on the Existence of Leptonphilic Dark Matter Particles

Many cosmic ray (CR) experiments have confirmed the lepton excess in CR lepton spectra at $\gtrsim 30 \mathrm{GeV}$, which can be explained both by astrophysical sources and dark matter (DM) annihilation or decay. A cross check is needed. However, the current direct detection cannot probe the leptonphilic DM particles with mass in the range $100 \mathrm{GeV} - 10 \mathrm{TeV}$ which derived from indirect detection. In this letter, we propose an scenario to provide a cross check on the existence of such DM particles, via hydrogen-atmosphere pulsating white dwarfs (DAVs) in DM-dense environments. An important observable has been proposed and corresponding estimations have been made. The estimation show that the potential sensitivity on the $m_{\chi} - \sigma_{\chi,e}$ plane could be extended to a region with $5 \mathrm{GeV} \lesssim m_{\chi} \lesssim 10^{4} \mathrm{GeV}$ and $\sigma_{\chi,e} \gtrsim 10^{-40} \mathrm{cm}^{2}$, which could give us a cross check on the existence of the leptonphilic DM particles with indirect DM detection in near future.
Service Provisioning in Edge-Cloud Continuum: Emerging Applications for Mobile Devices

Disruptive applications for mobile devices can be enhanced by edge computing facilities. In this context, Edge Computing (EC) is a proposed architecture to meet the mobility requirements imposed by these applications in a wide range of domains, such as the Internet of Things, Immersive Media, and Connected and Autonomous Vehicles. EC architecture aims to introduce computing capabilities in the path between the user and the Cloud to execute tasks closer to where they are consumed, thus mitigating issues related to latency, context awareness, and mobility support. In this survey, we describe which are the leading technologies to support the deployment of EC infrastructure. Thereafter, we discuss the applications that can take advantage of EC and how they were proposed in the literature. Finally, after examining enabling technologies and related applications, we identify some open challenges to fully achieve the potential of EC, and also research opportunities on upcoming paradigms for service provisioning. This survey is a guide to comprehend the recent advances on the provisioning of mobile applications, as well as foresee the expected next stages of evolution for these applications.
Productive agglomerations in Paraná and their determinants

This paper aims to analyze the determinants of productive agglomerates in the State of Paraná, southern Brazil, mainly focusing on the effects of economies of specialization and diversification. To achieve its aim, ten industrial sectors (the most representative in terms of job offer) were selected and through panel data (using spatial panel), regressions were estimated, one for each industry, considering the 399 towns and the period between 2000 and 2015. The results from all sectors showed statistically significant externalities originated in the productive specialization, affecting positively the dynamics of industrial growth in the Paraná towns. Moreover, in many sectors, a spatial effect was observed, with spillover of the industrialization dynamics to neighboring towns.
Synergistic Activity of Remdesivir–Nirmatrelvir Combination on a SARS-CoV-2 In Vitro Model and a Case Report

Background: This study aims to investigate the activity of the remdesivir–nirmatrelvir combination against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) and to report a case of Coronavirus Disease 2019 (COVID-19) cured with this combination. Methods: A Vero E6 cell-based infection assay was used to investigate the in vitro activity of the remdesivir–nirmatrelvir combination. The SARS-CoV-2 strains tested were 20A.EU1, BA.1 and BA.5. After incubation, a viability assay was performed. The supernatants were collected and used for viral titration. The Highest Single Agent (HSA) reference model was calculated. An HSA score >10 is considered synergic. Results: Remdesivir and nirmatrelvir showed synergistic activity at 48 and 72 h, with an HSA score of 52.8 and 28.6, respectively (p < 0.0001). These data were confirmed by performing supernatant titration and against the omicron variants: the combination reduced the viral titer better than the more active compound alone. An immunocompromised patient with prolonged and critical COVID-19 was successfully treated with remdesivir, nirmatrelvir/ritonavir, tixagevimab/cilgavimab and dexamethasone, with an excellent clinical–radiological response. However, she required further off-label prolonged therapy with nirmatrelvir/ritonavir until she tested negative. Conclusions: Remdesivir–nirmatrelvir combination has synergic activity in vitro. This combination may have a role in immunosuppressed patients with severe COVID-19 and prolonged viral shedding.
Hadley Circulation Strength Change in Response to Global Warming: Statistics of Good Models

In this study, we examine future changes in the Hadley cell (HC) strength using CMIP5 climate change simulations. The current study is an extension of a previous study by Seo et al. that used all 30 available models. Here, we select 18-23 well-performing models based on their significant internal sensitivity of the interannual HC strength variation to the latitudinal temperature gradient variation. The model projections along with simple scaling analysis show that the inter-model variability in the HC strength change is a result of the inter-model spread in the meridional temperature gradient across the subtropics for both DJF and JJA, not by the tropopause height or gross static stability change. The HC strength is expected to weaken significantly during DJF, while little change is expected in the JJA HC strength. Compared to the calculations with all model members, selected model statistics increase the linear correlation between the changes in HC strength and meridional temperature gradient by 13~23%, confirming the robust sensitivity of the HC strength to the meridional temperature gradient. Two scaling equations for the selected models predict changes in HC strength better than all-member predictions. In particular, the prediction improvement in DJF is as high as 30%. The simple scaling relations successfully predict both the ensemble-mean changes and model-to-model variations in the HC strength for both seasons.
Blanking period antiarrhythmic drugs after catheter ablation for atrial fibrillation: a meta-analysis of randomized controlled trials

Background Antiarrhythmic drugs (AADs) are frequently prescribed following catheter ablation (CA) for atrial fibrillation (AF). However, to date, there is a lack of large-scale, multicenter controlled studies that have confirmed the efficacy of AADs in reducing the incidence of late recurrence of AF after CA. Furthermore, the optimal duration of short-term use of AADs after CA remains a controversial topic. Methods PubMed, Embase, Cochrane Library, CNKI, and ClinicalTrials.gov were searched until April 25, 2022. We conducted a meta-analysis of randomized controlled trials (RCTs) to assess the efficacy of blanking period AADs in predicting both early and late recurrence of AF. In addition, Grading of Recommendations Assessment, Development and Evaluation (GRADE) was used to assess the quality of evidence in this meta-analysis. Results 12 RCTs with 3,625 patients were included in this meta-analysis. Short-term use of AADs after AF ablation reduced the risk of early recurrence of AF compared with the no-AADs group. In the subgroup analysis of AADs use time, it was found that only using AADs for more than 2 months can reduce the early recurrence of AF after CA. However, when compared with the no-AADs group, short-term use of AADs after CA did not reduce the incidence of late recurrence of AF. Conclusions Short-term use of AADs (more than 2 months) can reduce the early recurrence but not the late recurrence of AF after CA.
Exploring Bracing Adherence in Ponseti Treatment of Clubfoot: A Comparative Study of Factors and Outcomes in Uganda

The Ponseti method of clubfoot treatment involves two phases: initial correction, usually including tenotomy; and bracing, to maintain correction and prevent relapse. Bracing should last up to four years, but in Uganda, approximately 21% of patients drop from clinical oversight within the first two years of using the brace. Our study compared 97 adherent and 66 non-adherent cases to assess the influential factors and effects on functional outcomes. We analyzed qualitative and quantitative data from clinical records, in-person caregiver interviews, and assessments of foot correction and functionality. Children who underwent tenotomy had 74% higher odds of adherence to bracing compared to those who did not undergo tenotomy. Conversely, children from rural households whose caregivers reported longer travel times to the clinic were more likely to be non-adherent to bracing (AOR 1.60 (95% CI: 1.11–2.30)) compared to those without these factors. Adhering to bracing for a minimum of two years was associated with improved outcomes, as non-adherent patients experienced 2.6 times the odds of deformity recurrence compared to adherent patients. Respondents reported transportation/cost issues, family disruptions, and lack of understanding about the treatment method or importance of bracing. These findings highlight the need to address barriers to adherence, including reducing travel/waiting time, providing ongoing education for caregivers on bracing protocol, and additional support targeting transportation barriers and household complexities.