Miracle-dz/UniFAR-FTUs huggingface dataset:
Her Support, His Support: Money, Masculinity, and Marital Infidelity

Recent years have seen great interest in the relationship between relative earnings and marital outcomes. Using data from the 1997 National Longitudinal Survey of Youth, I examine the effect of relative earnings on infidelity, a marital outcome that has received little attention. Theories of social exchange predict that the greater one’s relative income, the more likely one will be to engage in infidelity. Yet, emerging literature raises questions about the utility of gender-neutral exchange approaches, particularly when men are economically dependent and women are breadwinners. I find that, for men, breadwinning increases infidelity. For women, breadwinning decreases infidelity. I argue that by remaining faithful, breadwinning women neutralize their gender deviance and keep potentially strained relationships intact. I also find that, for both men and women, economic dependency is associated with a higher likelihood of engaging in infidelity; but, the influence of dependency on men’s infidelity is greater than the influence of dependency on women’s infidelity. For economically dependent persons, infidelity may be an attempt to restore relationship equity; however, for men, dependence may be particularly threatening. Infidelity may allow economically dependent men to engage in compensatory behavior while simultaneously distancing themselves from breadwinning spouses.
Interval volume decomposer: a topological approach to volume traversal

The Interval Volume Decomposer (IVD) is an interface for decomposing an entire volume into interval volumes each of which characterizes a distinctive volume feature. The advantage of the IVD is that it allows us to look inside the volume by peeling interval volumes from outside to inside not only interactively but also automatically. This is achieved due to the rigorous analysis of nested structures of the decomposed interval volumes by constructing a level-set graph that delineates isosurface transitions according to the scalar field. A robust algorithm for computing such level-set graphs is introduced in order to extract significant structures in the volume by putting together local interval volumes into a finite number of global groups. Several decomposition examples of medical and simulated datasets are demonstrated so that the present interface effectively traverses the underlying structures of the volume.
Catching up faster by switching sooner: a predictive approach to adaptive estimation with an application to the AIC–BIC dilemma

Summary. Prediction and estimation based on Bayesian model selection and model averaging, and derived methods such as the Bayesian information criterion BIC, do not always converge at the fastest possible rate. We identify the catch‐up phenomenon as a novel explanation for the slow convergence of Bayesian methods, which inspires a modification of the Bayesian predictive distribution, called the switch distribution. When used as an adaptive estimator, the switch distribution does achieve optimal cumulative risk convergence rates in non‐parametric density estimation and Gaussian regression problems. We show that the minimax cumulative risk is obtained under very weak conditions and without knowledge of the underlying degree of smoothness. Unlike other adaptive model selection procedures such as the Akaike information criterion AIC and leave‐one‐out cross‐validation, BIC and Bayes factor model selection are typically statistically consistent. We show that this property is retained by the switch distribution, which thus solves the AIC–BIC dilemma for cumulative risk. The switch distribution has an efficient implementation. We compare its performance with AIC, BIC and Bayesian model selection and averaging on a regression problem with simulated data.
Econometrics of welfare evaluation of price changes: The case of food price increases in M´ exico

Two rounds of food price increases in the past two years have generated a significant amount of economic research reporting the welfare effects of the price increases. Most reported research assumes constant demand or approximates second order substitution effects. Poverty forecasts with these assumptions may overestimate or underestimate the effect of food price increases in a nation where most households consume diverse food baskets. We demonstrate that calculating compensating variation from a theoretically consistent food demand system is required to obtain accurate welfare measurement, including standard errors of estimates. We use Mexican household survey data to estimate a complete household food demand system, with adjustment for household demographics, from cross-sectional data.
Classifying the secondary component of the binary star W Aquilae

AIMS: The object W Aql is an asymptotic giant branch (AGB) star with a faint companion. By determining more carefully the properties of the companion, we hope to better constrain the properties of the AGB star. METHODS: We present new spectral observations of the binary star W Aql at minimum and maximum brightness and new photometric observations of W Aql at minimum brightness. RESULTS: The composite spectrum near minimum light is predominantly from the companion at wavelengths $\lambda$ < 6000 $\AA$. This spectrum can be classified as F8 to G0, and the brightness of the companion is that of a dwarf star. Therefore, it can be concluded that the companion is a main sequence star. From this, we are able to constrain the mass of the AGB component to 1.04 - 3 $M_\odot$ and the mass of the W Aql system to 2.1 - 4.1 $M_\odot$ . Our photometric results are broadly consistent with this classification and suggest that the main sequence component suffers from approximately 2 mag of extinction in the V band primarily due to the dust surrounding the AGB component.
A Study of the Impact of Laboratory Approach on Achievement and Process Skills in Science among Is Standard Students

The purpose of this study was to compare the effects a laboratory based on the 7E learning cycle model with verification laboratory approach on university students’ development of science process skills and conceptual achievement. In this study the sample consisted of 81 freshman university students who were taking the General Physics Laboratory-Icourse at the university in DAVV Indore. In this study pretestposttest design with control group was used. B.Sc.class students (43) who took lower weighted standard points from university entrance exam (UEE) than BCA class students were selected as experimental group. BCA class students (38) were selected as control group. Thus, this study was quasi-experimental in design. In order to assess hypotheses of study was used “Science Process Skills Test-SPST” and “Force Concept Inventory -FCI” to compare skills and conceptual achievement of control and experimental groups students. Both tools were given to both groups as pretest and posttest.
The Words Children Hear

Young children learn language from the speech they hear. Previous work suggests that greater statistical diversity of words and of linguistic contexts is associated with better language outcomes. One potential source of lexical diversity is the text of picture books that caregivers read aloud to children. Many parents begin reading to their children shortly after birth, so this is potentially an important source of linguistic input for many children. We constructed a corpus of 100 children’s picture books and compared word type and token counts in that sample and a matched sample of child-directed speech. Overall, the picture books contained more unique word types than the child-directed speech. Further, individual picture books generally contained more unique word types than length-matched, child-directed conversations. The text of picture books may be an important source of vocabulary for young children, and these findings suggest a mechanism that underlies the language benefits associated with reading to children.
An Integrated Approach to Maneuver-Based Trajectory Prediction and Criticality Assessment in Arbitrary Road Environments

This paper describes an integrated Bayesian approach to maneuver-based trajectory prediction and criticality assessment that is not limited to specific driving situations. First, a distribution of high-level driving maneuvers is inferred for each vehicle in the traffic scene via Bayesian inference. For this purpose, the domain is modeled in a Bayesian network with both causal and diagnostic evidences and an additional trash maneuver class, which allows the detection of irrational driving behavior and the seamless application from highly structured to nonstructured environments. Subsequently, maneuver-based probabilistic trajectory prediction models are employed to predict each vehicle's configuration forward in time. Random elements in the designed models consider the uncertainty within the future driving maneuver execution of human drivers. Finally, the criticality time metric time-to-critical-collision-probability (TTCCP) is introduced and estimated via Monte Carlo simulations. The TTCCP is a generalization of the time-to-collision (TTC) in arbitrary uncertain multiobject driving environments and valid for longer prediction horizons. All uncertain predictions of all maneuvers of every vehicle are taken into account. Additionally, the criticality assessment considers arbitrarily shaped static environments, and it is shown how parametric free space (PFS) maps can advantageously be utilized for this purpose.
A comparison of the nonlinear frictional characteristics of two‐dimensional and three‐dimensional models of a shallow tidal embayment

The nonlinear frictional behavior of two-dimensional (2-D) and three-dimensional (3-D) models are compared in this study of tides in the Bight of Abaco. The shallow depths and the existence of an extensive set of tidal elevation data (five astronomical and two overtide constituents at 25 stations) from Filloux and Snyder (1979) offer an excellent opportunity to compare the effects of different frictional formulations. In addition, previous modeling efforts in the bight have consistently overpredicted the M6 and generally overdamped the O1, K1, and S2 tides. The results indicate that although the 2-D and 3-D models may be calibrated to produce nearly identical responses for the dominant M2 tide, there are systematic differences in the responses of the primary overrides. These differences are explained using analytical expansions of the friction terms and are shown to be due to differences in the terms that are nonlinear in velocity and in water level. The investigation concludes that the overgeneration of M6 and the overdamping of secondary astronomical tides will occur in 3-D models as well as 2-D models. Although several causes for these problems were considered, improvement in these constituents could be achieved only by modifying the standard quadratic friction or flow-dependent eddy viscosity relations to reduce the nonlinear frictional effect relative to the linear frictional effect. The required modifications suggest the presence of a constant background velocity, residual turbulence field, or possibly the need for a more advanced frictional closure.
Effect and Mechanism of QiShenYiQi Pill on Experimental Autoimmune Myocarditis Rats

Background To observe the effect of QiShenYiQi pill (QSYQ) on experimental autoimmune myocarditis rats, and to explore its mechanism of action. Material/methods Lewis rats underwent the injection of myocardial myosin mixed with Freund’s complete adjuvant were randomized into 3 groups: model, valsartan, and QSYQ groups. Rats injected with phosphate-buffered saline (PBS) mixed with Freund’s complete adjuvant were used as the control group. Rats were euthanized at 4 and 8 weeks, and we weighed rat body mass, heart mass, and left ventricular mass. Myocardium sections were stained with hematoxylin and eosin (H&E) and Masson trichrome. Myocardial TGF-β1 and CTGF protein expression was detected by immunohistochemistry, and myocardial TGF-β1 and CTGF mRNA expression was detected by real-time qPCR. Results QSYQ reduced HMI and LVMI, as well as the histological score of hearts and CVF, which further decreased over time, and its effect was significantly greater than that of valsartan at 4 and 8 weeks. After 4 weeks, QSYQ inhibited the protein and mRNA expression of TGF-β1 and CTGF, and its effect on lowering CTGF was significantly greater than that of valsartan. In addition, after 8 weeks, QSYQ also inhibited the protein and mRNA expression of CTGF, whereas there was no significant difference in the expression of myocardial TGF-β1. Conclusions This study provides evidence that QSYQ can improve cardiac remodeling of experimental autoimmune myocarditis rats. It also effectively improved the degree of myocardial fibrosis, which is related to the mechanism of regulation of TGF-β1 CTGF.
pBMDS: a behavior-based malware detection system for cellphone devices

Computing environments on cellphones, especially smartphones, are becoming more open and general-purpose, thus they also become attractive targets of malware. Cellphone malware not only causes privacy leakage, extra charges, and depletion of battery power, but also generates malicious traffic and drains down mobile network and service capacity. In this work we devise a novel behavior-based malware detection system named pBMDS, which adopts a probabilistic approach through correlating user inputs with system calls to detect anomalous activities in cellphones. pBMDS observes unique behaviors of the mobile phone applications and the operating users on input and output constrained devices, and leverages a Hidden Markov Model (HMM) to learn application and user behaviors from two major aspects: process state transitions and user operational patterns. Built on these, pBDMS identifies behavioral differences between malware and human users. Through extensive experiments on major smartphone platforms, we show that pBMDS can be easily deployed to existing smartphone hardware and it achieves high detection accuracy and low false positive rates in protecting major applications in smartphones.
Skyline queries in crowd-enabled databases

Skyline queries are a well-established technique for database query personalization and are widely acclaimed for their intuitive query formulation mechanisms. However, when operating on incomplete datasets, skylines queries are severely hampered and often have to resort to highly error-prone heuristics. Unfortunately, incomplete datasets are a frequent phenomenon, especially when datasets are generated automatically using various information extraction or information integration approaches. Here, the recent trend of crowd-enabled databases promises a powerful solution: during query execution, some database operators can be dynamically outsourced to human workers in exchange for monetary compensation, therefore enabling the elicitation of missing values during runtime. Unfortunately, this powerful feature heavily impacts query response times and (monetary) execution costs. In this paper, we present an innovative hybrid approach combining dynamic crowd-sourcing with heuristic techniques in order to overcome current limitations. We will show that by assessing the individual risk a tuple poses with respect to the overall result quality, crowd-sourcing efforts for eliciting missing values can be narrowly focused on only those tuples that may degenerate the expected quality most strongly. This leads to an algorithm for computing skyline sets on incomplete data with maximum result quality, while optimizing crowd-sourcing costs.
An Improved Xen Credit Scheduler for I/O Latency-Sensitive Applications on Multicores

It has long been recognized that the Credit scheduler favors CPU-bound applications while for the latency-sensitive workloads such as those related to stream-based audio/video services, its performance is far from satisfactory. In this paper we present an improved Credit scheduler in Xen to facilitate such tasks on multicore platforms. To this end, we improve the Credit scheduler from three perspectives. First, given the identified Simultaneous Multi-Boost problem, we minimize the system response time by load balancing the virtual CPUs with the BOOST priority between the cores. Second, we address the Premature Preemption problem by monitoring the received network packets in the driver domain and deliberately preventing it from being prematurely preempted during the packet delivery to further reduce and stabilize the I/O latency. Finally, we optimize the frequency of CPU switch by utilizing time-variant slice instead of the existing long time-invariant one to adapt to the dynamic fluctuation of the number of virtual CPUs in the run queue associated with each physical CPU. Our empirical studies show that the proposed improvement can significantly improve the performance of the Credit scheduler for scheduling the I/O latency-sensitive applications.
The Effects of Different Exercise Programmes on Female Body Composition

Abstract The purpose of this study was to verify the effects of 16 weeks of practicing different exercise programmes on body composition. This is an exploratory and descriptive study of 89 women aged 25 to 55 years (41.42 ± 9.23 years). The subjects were randomly divided into three experimental groups (EG): practitioners of strength training (SG), dance (DG), hydrogymnastics (HG), and a control group (CG) with sedentary women. Measurements of body mass and height, circumferences of the chest, waist, abdomen, hips, thighs, calves, and skinfolds of the triceps, suprailiac and thigh were registered in three different moments: prior to the commencement of the training program, again after 8 weeks of training, and finally after 16 weeks of training. Body density was estimated by using the trifold protocol by Jackson, Pollock and Ward. The ANOVA and deltas of change (Δ%) were used for data analysis. The level of significance was set at p<0.05. The effects of greater statistical significance on body composition related the variables "time", "group" and the interaction between the two (time x group) were observed for the percentage of fat - F% (F (1.79, 152.52) = 24.59, p <0.001, η 2 = 0.22), fat mass - FM (F (1.75, 149.01) = 12.65, p <0.001, η 2 = 0.13) and lean mass - LM (F (1.77, 150.66) = 47.38, p <0.001, η 2 = 0.36). The HG and SG were more beneficial in reducing F%. It was observed that the EG indicated healthier anthropometric aspects compared to the CG, regardless of the type of exercise programmes practiced. The time factor was more representative over the effects of exercise on anthropometric dimensions.
Restricted delegation and revocation in language-based security: (position paper)

In this paper, we introduce a notion of restricted revocable delegation and study its consequences in language-based security. In particular, we add this notion by means of delegate and revoke commands to a simple imperative programming language. We then define an operational semantics for our programming language, in the Natural Semantics style of Gilles Kahn. We briefly discuss our initial ideas about the security properties of the semantics, which are extensions of existing variations of the renowned non-interference property, e.g., in the context of delimited information release.
Full-body exoskeleton robot control for walking assistance by style-phase adaptive pattern generation

We propose an adaptive walking assistance strategy to control an exoskeleton robot. In our proposed framework, we explicitly consider the following: 1) the diversity of user motions (style) and 2) the interactions among a user, a robot, and an environment. To spatially coordinate a wide variety of user motions and robot behaviors, we estimated style parameters from observed user movements. To temporally coordinate the interactions among the user, the robot, and the environment, we synchronized the phases of these three systems with a coupled oscillator model. The estimated style parameters and the phase of the user motion can be used to predict future user movements. We investigated how movement prediction and phase synchronization can be beneficial to control an exoskeleton robot. To evaluate our adaptive walking assistance strategy, we developed simulated user and exoskeleton models. The physical interactions among the user, the exoskeleton, and the ground models are introduced in the simulated system. We show that the necessary torque for the user walking movement was reduced around 40% by using our proposed method to control the exoskeleton model.
Identifying Protein Interaction Abstracts with Contextual Bag of Words

In this paper, we focus on the identification of biomedical abstracts related to protein-protein interactions. We propose a novel feature representation, contextual-bag-of-words, to exploit named entity information. Our method outperforms well-known methods that use named entity information as additional features. Furthermore, we have improved the performance by extracting reliable and informative instances from unlabeled and likely-positive data to provide additional training data.
Solid State Fermentation of Plant Protein Meals Using Lactobacillus acidophilus for Improving Feed Value

Usage of some legumes and oil seed meal as fishmeal substitute is hampered by low protein content and anti nutritional factors (ANF). Inclusion of some exogenous enzyme cocktail like phytase, xylanase can reduce some ANF but is costly. Solid state fermentation of plant proteins is affordable and could be useful in upgrading the protein content, elevating the nutrient and mineral status and eliminating ANF from plant-based feed ingredients. We therefore extracted Lactobacillus acidophilus from intestine of adult African catfish. Extracted L. acidophilus was cultured at 37°C for 48 hrs in Mueller-Hinton Broth. Approximately 10 g of the bacteria broth containing 9.4 log 10 colony forming unit (CFU) per ml was mixed with 200 g meals of bambaranut meal and African yam beans meal placed in a brown bottom flask. The ground meals and bacteria mixtures were fermented for 72 hours. Temperature was maintained at 28.6°C to 34°C. The pH of the mixtures was measured everyday and the fermenting mixture was regularly stirred. Fermentation was stopped after 72 hrs and the meals were subjected to proximate analysis. Protein content of the meals significantly increased (P<0.05) as follows: BNM, 24.82±0.15% to 40.37±0.27% and AYB, 23.65±0.07% to 34.56±1.36%. Lipid content of meals significantly increased (P<0.05) as follows BNM, 7.11±0.01 to 14.29±0.05% and AYB, 2.96±0.45% to 5.76±0.09%. There was general decrease in composition of carbohydrate and ANFs were drastically reduced or completely eliminated from the meals.
Confronting the Equity "Learning Problem" through Practitioner Inquiry

Abstract:This study examined how participation in an inquiry-based workshop on assessing course syllabi for equity-mindedness and cultural inclusivity fostered community college math faculty learning about racial/ethnic equity and equity-mindedness. Findings show that the workshop prompted reflection on what equity means and how participants' teaching practices and classroom environments affect students, especially students of color. For some, reflection was followed by insights about their role as instructors and equity-minded changes in practice; for others, reflection affirmed the value of their existing conceptions and current practice. Despite initial signs of learning, there was little evidence that participants developed lasting equity-mindedness.