Miracle-dz/UniFAR-FTUs huggingface dataset:
The Reciprocal Effects of Language Proficiency and Depression among Low-Income Latinx Youth

ABSTRACT Extant research associates language with essential social and emotional processes. Although the risk for depression among Latinx youth in the United States is well documented, the link between their language proficiency and depressive symptoms remains poorly understood. Further, research employing standardized language assessments with Latinx early adolescents is scarce and reciprocal associations between language proficiency and depressive symptoms have not been examined. This longitudinal study addressed these gaps by investigating the relation between language proficiency and depression in a sample of 218 dual language Latinx students of predominantly low-income backgrounds (Mage = 12.1, SD = 1.1; 49.1% female) recruited from seven public schools in a large city in the Midwest of the United States. Language proficiency in English and Spanish was assessed using the Woodcock-Muñoz Language Survey-Revised and depressive symptoms were assessed using the Children’s Depression Inventory. Paired samples t-tests showed lower than expected growth in English vocabulary and higher than expected growth in the ability to reason using lexical knowledge in Spanish over a one-year period. Cross-lagged panel analyses (χ 2 (99) = 211.19, p < . 001, CFI = . 93, TLI = . 92, RMSEA = . 07 (90% CI [.06, .09])) indicated that growth in English language proficiency is predictive of decreased depressive symptoms. Likewise, increases in depressive symptoms are predictive of decreased English language proficiency. Results have important implications for the design of appropriate psychological interventions and sensible educational policies for students of linguistic minority backgrounds.
Variational Integrators for Structure-Preserving Filtering

Estimation and filtering are important tasks in most modern control systems. These methods rely on accurate discretetime approximations of the system dynamics. We present filtering algorithms that are based on discrete mechanics techniques (variational integrators), which are known to preserve system structures (momentum, symplecticity, constraints, for instance) and have stable long-term energy behavior. These filtering methods show increased performance in simulations and experiments on a real digital control system. The particle filter as well as the extended Kalman filter benefit from the statistics-preserving properties of a variational integrator discretization, especially in low bandwidth applications. Moreover, it is shown how the optimality of the Kalman filter can be preserved through discretization by means of modified discrete-time Riccati equations for the covariance updates. This leads to further improvement in filter accuracy, even in a simple test example.
Cannabinoid Hyperemesis: An Erratic Syndrome Linked with Cannabis Abuse

Cannabinoid hyperemesis syndrome (CHS) is characterized by chronic cannabis use, recurrent episodes of intractable nausea and vomiting, frequent hot bathing and abdominal pain [1]. The syndrome was first described by Allen et al. [2], and later Sontineni et al. [3] who proposed abridged clinical diagnostic criteria. Simonetto et al. by appraising all PubMed indexed journals with case reports and case series on CHS, reported a case series of 98 patients [4]. This study confirmed the previously stated outcomes. The researchers avowed that CHS should be measured in younger patients with chronic cannabis use and repeated nausea, vomiting, as well as pain in the abdominal. Amid illicit drug, cannabis is the utmost typically used this drug in the world [5].
Cornerstone: Foundational Models and Services for Integrated Battle Planning

Abstract : The Air Force has three mission elements, air, space and cyber that it must command and control as a Joint and Coalition partner. Today's Air Operations Centers (AOCs) want to improve multi-domain collaboration. To address these challenges, Air Force Research Laboratory Information Directorate (AFRL/RI) is sponsoring exploration and development of an Integrated Battle Planning Capability (IBPC) to coordinate and synchronize planning across the three domains. As a first step toward this goal, BAE Systems is developing Cornerstone, a suite of web services for mission request brokering, dynamic model management, plan management, and a Unified Plan Representation (UPR). The UPR is based on already established community standards and a common ontology of shared and domain-specific concepts. This paper describes Cornerstone? s research and development accomplishments to date, including an overview of the ontology, system design, and elaboration of the web services. Results from an initial Limited Technology Experiment (LTE) are reviewed. In the LTE, Cornerstone services correctly used the Jena semantic reasoning engine to broker air, cyber, and space mission option data among simulated and human domain-planners.
Fiscal Divergence and Business Cycle Synchronization: Irresponsibility Is Idiosyncratic [with Comments]

In 1998, European countries qualified for entry into European Monetary Union (EMU) on the basis of five "convergence criteria. " The criteria were enshrined in the 1992 Maastricht Treaty and quantify targets concerning inflation, long-term bond yields, exchange rates, government debt, and the government budget. The Maastricht convergence criteria are of more than historical relevance, since they will also be applied to future EMU entrants. Further, the 1997 "Stability and Growth Pact" implies that the fiscal criteria are still, in principle, binding.1 Most economists particularly non-Europeans view the Maastricht convergence criteria with skepticism. The reason is simple: they have little to do with standard economic arguments concerning "optimal currency areas," monetary unions that are desirable and sustainable. The consensus in economics is that from a theoretical viewpoint, monetary unions make sense for countries with synchronized business cycles, integrated markets, flexibility, and mechanisms to share risk. The overlap between the Maastricht convergence criteria and the optimum currency area criteria is small.2 Clearly the direct correspondence between the (Maastricht) criteria actually applied for EMU entry and the appropriate (optimum currency area) criteria is poor. In this paper we ask if there is an indirect connection. We focus on the most controversial Maastricht criteria the total
Distribution dynamics of complex systems

A complex system is defined as a system with many interdependent parts having emergent self-organization; analyzing and designing such complex systems is a new challenge. A common observable structure of many complex systems is the network, which is connections among nodes, and thus inherently difficult to describe. The goal of this research is to introduce an effective methodology to describe complex systems, and thus we will construct a population balance (distribution kinetics) model based on the association-dissociation process to describe the evolution of complex systems. Networks are commonly observed structures in complex systems with interdependent parts that self-organize. How networks come into existence and how they change with time are fundamental issues in numerous networked systems. Based on the nodal-linkage distribution, we propose a unified population dynamics approach for the network evolution. Size-independent rate coefficients yield an exponential network without preferential attachment, and size-dependent rate coefficients produce a power law network with preferential attachment. For nonlinearly growing networks, when the total number of connections increases faster than the total number of nodes, the network is said to accelerate. We propose a systematic model, a population dynamics model, for the dynamics of growing networks represented by distribution kinetics equations, and perform the moment calculations to describe the dynamics of such networks. Power law distributions have been observed in numerous physical and social systems; for example, the size distributions of particles and cities are often power laws. Each system is an ensemble of clusters, comprising units that combine with or dissociate from the cluster. To describe the growth of clusters, we hypothesize that a distribution
Nutritional and Functional Properties of Four Traditional Mucilaginous Vegetables used by Rural Populations in Benin Republic

Child malnutrition is one of the public health problems. Unfortunately, some of our vegetables such as Adansonia digitata, Bombax brevicuspe, Ceiba pentandra and Grewia venusta, with important nutritional value, are neglected. To assess the nutritional value of these vegetables, their protein, lipid, fibre and mineral content as well as polyphenols have been determined using reference methods as per AOAC (Association of Official Analytical Chemists). The results showed that the leaves of A. digitata, B. brevicuspe, C. pentandra and the flower buds of G. venusta have a protein content from 17.19 g/100g; 19.84 g/100g; 9.26 g/100g; 13.01 g/100g respectively. Their lipid content is respectively 1.03 g/100g; 1.71 g/100g; 2.75 g/100g; 0.12 g/100g and their fibre content varies from 9.42 to 24.95 g/100g. These plants are also rich in iron, calcium, magnesium and vitamin C. In addition, the polyphenol content of these plants shows that they are important in the prevention of certain diseases. Given the different nutritional potential of each of these plants, it would be useful to popularize them in order to contribute to improving the quality of the food consumed by the population.
UvA-DARE (Digital Simple-current algebra constructions of 2+1-dimensional topological orders

Self-consistent (non-)Abelian statistics in 2 + 1 dimensions (2 + 1D) are classiﬁed by modular tensor categories (MTCs). In recent works, a simpliﬁed axiomatic approach to MTCs, based on fusion coefﬁcients N ijk and spins s i , was proposed. A numerical search based on these axioms led to a list of possible (non-)Abelian statistics, with rank up to N = 7. However, there is no guarantee that all solutions to the simpliﬁed axioms are consistent and can be realized by bosonic physical systems. In this paper, we use simple-current algebra to address this issue. We explicitly construct many-body wave functions, aiming to realize the entries in the list (i.e., realize their fusion coefﬁcients N ijk and spins s i ). We ﬁnd that all entries can be constructed by simple-current algebra plus conjugation under time-reversal symmetry. This supports the conjecture that simple-current algebra is a general approach that allows us to construct all (non-)Abelian statistics in 2 + 1D. It also suggests that the simpliﬁed theory based on ( N ijk ,s i ) is a classifying theory at least for simple bosonic 2 + 1D topological orders (up to invertible topological orders).
Second Moment Analysis of the Nonlinear Eddy Current Model with Material Uncertainties

In this paper we study the eddy current problem with uncertainties in the nonlinear material characteristic originating, e.g., from measurements. In the case of small input uncertainties adjoint techniques can be used to efficiently approximate the solutions statistics (first order second moment method) at very low computational cost. We will carry out the corresponding sensitivity analysis and investigate the methods approximation properties. The main contribution of the present work is the extension to nonlinear problems. Numerical results for an electrical transformer and a comparison with the standard Monte Carlo method are given.
Regularity of Lipschitz minima

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About Production-Transport Problem Reduction To The Two-Level Problem Of Discrete Optimization And Its Application

In this study, the application of the production and transport task is considered to solve the problem of the distribution of the limited capacities of data transmission channels between different nodes of the computer network. A scheme is proposed for reducing the problem to a two-level continuous-discrete optimization problem. The model is formulated and numerical results are obtained to solve the problem of power distribution in the network of the information and computing center.
Eigenvalue assignment in state feedback control for uncertain systems

This paper presents a method for assignment the eigenvalues by state feedback for uncertain linear systems. This eigenvalue assignment is based on Karbassi-Bell method. The main advantage of this method is that we can parameterizations of the state feedback control for linear multivariable systems and we can use of this form to find optimal solution. For optimization of this problem we propose a genetic algorithm.
The effect of adding dried waste produced from red grape juice processing ( Vitis vinifera L. var. Siahe sardasht) on physico-chemical parameters and functional properties of beef sausage

The aim of this study was to determine the effect of different levels (0, 1& 2%)of dried waste of the red grape juice’s processing as a functional ingredient on the physicochemical parameters and functional properties of beef sausage. For this purpose, physic-chemical analysis including measurement of moisture, protein, fat, carbohydrate, pH and calorie content were carried out. Then, samples from the point of functional properties including Water Holding Capacity (WHC), Expressible Moisture Content (EMC) and cooking loss were evaluated. The results showed that the addition of dried waste from the processing of red grape has no significant effect on physic-chemical properties of samples except for ash and pH (p> 0.05) and improved the functional properties through a significant increase in WHC, the reducing EMC and cooking loss in sample. Pearson correlation coefficients indicate a direct relationship between cooking loss and EMC and a reverse relationship between these two factors with WHC. Therefore, the use of the red grape dried waste as a rich source of fiber may improve the properties of technology, functional andnutritionalvalue ofthesausage.
Docosahexaenoic acid supplementation decreases liver fat content in children with non-alcoholic fatty liver disease: double-blind randomised controlled clinical trial

Objective To investigate whether dietary supplementation with docosahexaenoic acid (DHA) decreases liver fat content in children with non-alcoholic fatty liver disease (NAFLD). Design, setting and patients We performed a randomised controlled trial of DHA supplementation (250 and 500 mg/day) versus placebo in 60 children with biopsy-proven NAFLD (20 children per group). Main outcome measures The main outcome was the change in liver fat content as detected by ultrasonography after 6 months of treatment. Secondary outcomes were the changes in insulin sensitivity index, alanine transaminase, triglycerides and body mass index after 6 months of treatment. Results Blood DHA increased in children supplemented with DHA (0.65%, 95% CI 0.30% to 1.10% for the DHA 250 mg group and 1.15%, 0.87% to 1.43% for the DHA 500 mg group). The odds of more severe versus less severe liver steatosis after treatment was lower in children treated with DHA 250 mg/day (OR = 0.01, 0.002 to 0.11, p <0.001) and DHA 500 mg/day (OR = 0.04, 0.002 to 0.46, p = 0.01) as compared to placebo but there was no difference between the DHA groups (p = 0.4). Insulin sensitivity index increased and triglycerides decreased to a similar degree in both DHA groups as compared to placebo but there was no effect on alanine transaminase and body mass index. Conclusion DHA supplementation improves liver steatosis and insulin sensitivity in children with NAFLD.
Internet Mindfulness Meditation Intervention (IMMI) Improves Depression Symptoms in Older Adults

Background: Older adults have fewer physiological reserves and are more likely to be affected by stress. Mindfulness meditation has the potential to be an effective treatment for depression, but little research has been conducted on older adults. The primary objective of this study was to evaluate depression symptom changes in older adults (55–80 years old) taking an Internet Mindfulness Meditation Intervention (IMMI) compared to a waitlist control. The secondary aims were to collect data on pain, perceived stress, resilience, mindfulness, sleep quality, and spirituality. Methods: Fifty older adults were randomized to either the Internet Mindfulness Meditation Intervention, a six-week online intervention with daily home practice, or a waitlist control. Measures were collected at baseline, after the six-week intervention period, and again six weeks later after the waitlist participants completed IMMI. Adherence to home practice was objectively measured with iMINDr. Changes in outcomes for the IMMI and waitlist participants were compared. All participants who completed IMMI were then combined for a within-participant analysis. Results: Adherence to the intervention was low, likely due to a traumatic event in the local area of the participants. Compared to the waitlist participants, those in IMMI had improved depression symptoms (p < 0.00005), perceived stress (p = 0.0007), insomnia symptoms ((p = 0.0009), and pain severity (p = 0.05). In the within-participant analysis of all data before and after IMMI (i.e., those initially randomized to IMMI and waitlist participants who took it), we found improvements in depression symptoms (p = 0.0001), perceived stress (p = 0.0001), insomnia symptoms (p < 0.00005), pain interference (p = 0.003), and spirituality (p = 0.018). A seven-week follow-up after the original six-week IMMI program showed sustained improvements in the IMMI participants. Conclusions: IMMI improved depression and related symptoms compared to controls despite minimal support from study staff. IMMI offers a low-dose, low-cost, easily accessible mindfulness meditation intervention for older adults with depression symptoms.
An Innovative Sentiment Analysis to Measure Herd Behavior

We propose an innovative and forward-looking method to examine investor herd behavior and identify fundamental-driven spurious herding. A sentence-based sentiment analysis approach is conceived to automatically extract attitudes or emotions from textual documents. Then we build a mathematical model to discern herd behavior by exploiting the sentiment indices. Empirical tests in the Chinese stock market indicate that there exists significant true herd behavior among blue-chips. Investors with pessimistic sentiment are more likely to herd than those with optimistic sentiment. Moreover, macroeconomic information tends to play a dominant role in the decision-making processes, and the lack of rapid and efficient firm-specific information enables people to herd around the market consensus.
Diabetes prevention and weight loss with a fully-automated behavioral intervention by email, web and smartphone: A randomized controlled trial among persons with pre-diabetes

Background: One-third of United States adults, 86 million people, have pre-diabetes. Two-thirds of adults are overweight or obese, and thus at risk for diabetes and other cardiometabolic complications. Effective and affordable interventions are needed that can reach these 86 million, and others at high risk, to reduce their progression to diagnosed diabetes. Objectives: To evaluate the effectiveness of a fully-automated algorithm-driven behavioral intervention for diabetes prevention, Alive-PD, delivered via the web, internet, smartphone and automated phone. Methods: Alive-PD provided individually-tailored behavioral support for improvements in physical activity, eating habits, and related factors such as weight loss, stress reduction, and sleep. Weekly emails suggested small-step goals, and linked to an individual web page with progress tracking, tools for overcoming barriers, social support through virtual teams, competition, and health information. A smartphone app and automated phone calls provided further support. The trial randomly assigned 339 persons to the Alive-PD intervention (n=163) or a 6-month wait-list control group (n=176). Participants were eligible if either fasting glucose or hemoglobin A1c (HbA1c) was in the pre-diabetic range. Primary outcome measures were clinic-measured changes in fasting glucose and HbA1c at 6 months. Secondary outcome measures included clinic-measured changes in body weight, body mass index, waist circumference, triglyceride/high-density lipoprotein cholesterol (TG/HDL) ratio, and Framingham 8-year diabetes risk score. Analysis was by intention to treat. Results: Mean age was 55 years, mean BMI was 31.2 kg/m 2 , and 69% were male. Mean fasting glucose was in the pre-diabetic range (mean 109.9 mg/dl), while the mean HbA1c was 5.6%, in the normal range. In intention-to-treat analyses, Alive-PD participants relative to the Control group achieved significantly greater mean (95% CI) reductions in fasting glucose (-7.36 mg/dl [-7.85, -6.87] vs. -2.19 [-2.64, -1.73], P <.0001), HbA1c
Edge‐partitions of planar graphs and their game coloring numbers

Let G be a planar graph and let g(G) and Δ(G) be its girth and maximum degree, respectively. We show that G has an edge‐partition into a forest and a subgraph H so that (i) Δ(H) ≤ 4 if g(G) ≥ 5; (ii) Δ(H) ≤ 2 if g(G) ≥ 7; (iii) Δ(H)≤ 1 if g(G) ≥ 11; (iv) Δ(H) ≤ 7 if G does not contain 4‐cycles (though it may contain 3‐cycles). These results are applied to find the following upper bounds for the game coloring number colg(G) of a planar graph G: (i) colg(G) ≤ 8 if g(G) ≥ 5; (ii) colg(G)≤ 6 if g(G) ≥ 7; (iii) colg(G) ≤ 5 if g(G) ≥ 11; (iv) colg(G) ≤ 11 if G does not contain 4‐cycles (though it may contain 3‐cycles). © 2002 Wiley Periodicals, Inc. J Graph Theory 41: 307–317, 2002
Matching Firms, Managers, and Incentives

We combine unique administrative and survey data to study the match between firms and managers. The data include manager characteristics, firm characteristics, detailed measures of managerial practices, and outcomes for the firm and the manager. A parsimonious model of matching and incentives generates implications that we test with our data. We use the model to illustrate how risk aversion and talent determine how firms select and motivate managers. We show that empirical links between firm governance, incentives, and performance, which have so far been studied in isolation, can instead all be interpreted within our simple unified matching framework.
Geometric Feature Enhancement via Iterative High-Boost Filtering

We propose a new technique for enhancing high frequency geometric features and geometric texture for scatter point clouds. We generalize the classical High-Boost filtering of signal and image processing to the geometric feature manipulation for 3D point clouds. We get a smoothed version of the input point clouds by Adaptive Moving Least Squares (MLS) based point clouds smoothing operator. The distance fields between the point clouds and their corresponding smoothed version are regarded as the high frequency geometric features and geometric textures intuitively. High Boost operations are performed by iteratively updating the position of the input points along the normal direction which is proportion to the distance between the point clouds and their corresponding smoothed versions with given geometric enhancement scale factor. The effectiveness of the proposed method is demonstrated by several examples with both synthetic and real scanned point clouds.