Miracle-dz/UniFAR-FTUs huggingface dataset:
Parental involvement in organized after-school activities and adolescent motivational beliefs

Abstract This study examined the associations between parental involvement in adolescents’ organized after-school activities and adolescents’ motivational beliefs. Data were reported by 231 Mexican-origin and European American adolescents who participated in an organized after-school activity (57% female, M age = 12.37, SD = .54) and their parents. Overall parental involvement positively predicted adolescents’ motivational beliefs (i.e., ability self-concepts and values). Latent profile analyses revealed unique patterns across the three types of parental involvement (i.e., instrumental support, verbal encouragement, and activity connections) that differentially predicted adolescents’ motivational beliefs. This approach highlighted the importance of parent-activity connections. Adolescents of parents who reported average instrumental support and verbal encouragement, but low activity connections had lower motivational beliefs compared to adolescents whose parents had average involvement across all dimensions. There were no differences by adolescent ethnicity. The current findings underscore the importance of parental involvement in promoting positive youth development.
Improvement of moving object detection accuracy on aerial imagery using sensor geometry

In this paper, we propose an efficient approach to improve moving object detection accuracy which is adaptive to changes in object size according to the altitude of the aircraft. The proposed algorithm can effectively detect moving objects with various pixel-scale from 8x8 to 100x100 in full-HD motion imagery. It consists of two stages which are detection and fusion. At the first stage, two algorithms are performed simultaneously: One is one-stage object detection network for detecting large objects, and the other is optical flow method for detecting small moving objects. In the second stage, results from the first stage are fused with a Ground Sample Distance (GSD) of imagery. We have conducted experiments using aerial imagery taken at a height between 130 meters and 400 meters. We evaluated the detection performance of our method in terms of precision, recall and normalized multiple object detection accuracy (N-MODA). Through experiments, we proved that the superiority of the proposed method.
Mitosis, cytokinesis and multinuclearity in a Xanthonema (Xanthophyta) isolated from Antarctica

The ultrastructure of a Xanthonema strain featuring multinucleate cells was investigated by transmission electron microscopy. An important specific feature of the organisation of the photosynthetic apparatus in this strain is its association with mitochondrial profiles. The chloroplast girdle is composed of two different U-shaped lamellae, one peripheral and one subcentral. Multinuclearity is observed as often as the uninucleate state. The transition from the uninucleate to the multinucleate stage is connected to disturbances in the normal division pattern of the parietal chloroplast-mitochondria complex during interphase. As a result mitosis is not coordinated with cytokinesis. The return to the uninucleate stage occurs as a result of asynchronous cytokinesis or by aplanospore formation. Mitosis is of the semi-closed type, as in Tribonema. Centrioles replicate in early interphase, after the end of karyokinesis and progeny nuclei separate with the aid of CER invagination. Filament fragmentation takes place between neighbouring cells where two U-shaped segments adjoin, resulting in fragment ends being rounded rather than ‘zweispitzig’. The taxonomic significance of various ultrastructural features for the classification of filamentous Xanthophyta is discussed.
Time-Lapse Seismic and Electrical Monitoring of the Vadose Zone during a Controlled Infiltration Experiment at the Ploemeur Hydrological Observatory, France

The vadose zone is the main host of surface and subsurface water exchange and has important implications for ecosystems functioning, climate sciences, geotechnical engineering, and water availability issues. Geophysics provides a means for investigating the subsurface in a non-invasive way and at larger spatial scales than conventional hydrological sensors. Time-lapse hydrogeophysical applications are especially useful for monitoring flow and water content dynamics. Largely dominated by electrical and electromagnetic methods, such applications increasingly rely on seismic methods as a complementary approach to describe the structure and behavior of the vadose zone. To further explore the applicability of active seismics to retrieve quantitative information about dynamic processes in near-surface time-lapse settings, we designed a controlled water infiltration experiment at the Ploemeur Hydrological Observatory (France) during which successive periods of infiltration were followed by surface-based seismic and electrical resistivity acquisitions. Water content was monitored throughout the experiment by means of sensors at different depths to relate the derived seismic and electrical properties to water saturation changes. We observe comparable trends in the electrical and seismic responses during the experiment, highlighting the utility of the seismic method to monitor hydrological processes and unsaturated flow. Moreover, petrophysical relationships seem promising in providing quantitative results.
Bottomland hardwood forest growth and stress response to hydroclimatic variation: evidence from dendrochronology and tree ring Δ13C values

Abstract. Wetland forests around the world have been reduced to a small proportion of their original expanse due to changing climatic conditions and intensification of human land use activities. As a case in point, the Columbia bottomland hardwood forests along the Brazos–Colorado coastal basin on the Gulf coast of Texas are currently threatened by an increasingly erratic hydroclimate in the form of both extreme floods and droughts and by urban expansion. In this study, we use dendrochronology and tree ring carbon isotopes to understand the effect of changing hydroclimatic conditions on the functional attributes of these forests. We examined the tree rings of Quercus nigra at four sites within the Columbia bottomlands, of which one site experiences frequent and prolonged flooding, while the other three are less flood prone. The objectives of this study were to (i) understand the impact of hydroclimatic variation on radial growth, using tree ring width analysis, (ii) assess the magnitude of physiological stress inflicted by extreme hydroclimatic conditions, using tree ring Δ13C measurements as a proxy, and (iii) evaluate the relationship between tree ring width and Δ13C values. Radial growth across the landscape was influenced most strongly by the midgrowing season climate, while the early growing season climate had the strongest effect on Δ13C. Growth inhibition was minimal, and tree ring Δ13C values were not affected in trees at the wetter site under extreme hydrological conditions such as droughts or floods. In addition, trees at the wet site were less sensitive to precipitation and showed no response to higher temperatures. In contrast, trees at the three drier sites experienced growth inhibition and had lower tree ring Δ13C values during dry periods. Our results indicate more favorable growing conditions and lower stress in trees growing under wetter hydrological conditions. Management and conservation strategies dependent on site-specific conditions are critical for the health of these wetland forests under a rapidly changing hydroclimate. This study provides the first dendrochronological baseline for this region and a better understanding of favorable conditions for the growth and health of these forests, which can assist in management decisions such as streamflow regulation and conservation plans.
Improving Kernel-Driven BRDF Model for Capturing Vegetation Canopy Reflectance With Large Leaf Inclinations

Semiempirical, kernel-driven linear bidirectional reflectance distribution function (BRDF) models are widely used to characterize vegetation reflectance anisotropy and provide land surface bidirectional reflectance factor (BRF) products at the regional and global scales. However, these models usually imply an assumption of spherical leaf inclination. The effects of such an ideal assumption on simulating surface BRF remain inadequately quantified. In this article, we first evaluated the effects of leaf inclination on the most commonly used kernel-driven RossThick-LiSparse-Reciprocal (RTLSR) model by using the reflectance benchmark simulated by the mature PROSAIL (PROSAIL+SAIL) radiative transfer model. Subsequently, we improved the RTLSR model into a four-parameter version (RTLSRV4p) with a new volumetric scattering kernel derived from the assumption of vertical leaf inclination. Finally, the proposed RTLSRV4p model was validated by PROSAIL canopy BRF simulations, in situ canopy BRF measurements, and wide-angle infrared dual-mode line/area Aarray scanner (WIDAS) airborne observations. Validation results demonstrate that RTLSRV4p improves vegetation reflectance characterization for large leaf inclinations compared to the original RTLSR model, especially for the near-infrared (NIR) spectral domain. When validated against the simulated canopy BRFs, the mean root-mean-square error (RMSE), mean absolute percentage error (MAPE), bias, and coefficient of determination (R2) were improved from 0.0810, 31.63%, 0.0651, 0.6578 to 0.0453, 13.38%, 0.0326, 0.8734. Using the in situ BRF measurement, the fitted RMSE, MAPE, bias, and R2 were improved from 0.0917, 14.31%, 0.0728, and 0.5776 to 0.0226, 3.35%, 0.0166, and 0.9744. These validation metrics were improved from 0.0423, 10.85%, 0.0347, and 0.6598 to 0.0258, 5.85%, 0.0181, and 0.8732 when compared against the WIDAS observations. The RTLSRV4p model also shows good performance in calculating the reflectance of vegetation. These extensive validations suggest that RTLSRV4p is promising for capturing vegetation reflectance under large leaf inclinations.
The Teaching of Evolution--We Need To Do Better.

volutionary processes provide such a strong scientific and philosophical framework for the study of life that Dobzhansky (1973) was led to state forcefully that, ". nothing in biology makes sense except in the light of evolution. " For this enlightened perspective to be transmitted clearly to students of biology, the teaching of evolution must begin with an accurate definition and description of the major features of evolutionary processes and the possible outcomes of such processes. However, a perusal of some of the books most com-
C-H activation: a Critical Evaluation of a Published Method and its Application Towards Inherently Chiral Calix[4]arenes

C–H activation offers an intriguing access into inherently chiral calix[4]arenes, but has been little explored in the literature. In this article, we report our investigation into a published C–H activation method that uses carbamates to direct a palladium catalyzed C–H activation and subsequent reaction with N-bromosuccinimide. However, we show that this report is unfortunately flawed on a number of points. An earlier reported study revealed the more likely SEAr mechanism of the bromination reaction, which did not involve palladium catalysis. We nevertheless employed the SEAr bromination in an attempt to form inherently chiral calix[4]arenes, using a chiral (+)-menthyl carbamate as a directing group. Unfortunately, although the reaction was high yielding, the diastereomers formed were inseparable and we were unable to quantify their ratio. Subsequent removal of the chiral (+)-menthyl carbamate, returned a small positive optical rotation, suggesting that at least a level of asymmetric induction was achieved in the bromination to afford a non-racemic product.
Kernel Density Estimation of White Noise for Non-diversifiable Risk in Decision Making

Many businesses make profit yearly and tend to invest some of the profit so that they can cushion their organizations against any future unknown events that can affect their current profit making. Since future happenings in businesses cannot be predicted accurately, estimates are made using experience or past data which are not exact. The probability element (which is normally determined by experience or past data) is important in investment decision making process since it helps address the problem of uncertainty. Many of the investment decision making methods have incorporated the expectation and risk of an event in making investment decisions. Most of those that use risk account for diversifiable risk (non-systematic risk) only thus limiting the predictability element of these investment methods since total risk are not properly accounted for. A few of these methods include the certainty (probability) element. These include value at risk method which uses covariance matrices as total risk and the binning system which always assumes normal distribution and thus does not take care of discrete cases. Moreover comparison among various entities lacks since the probabilities derived are for individual entities and are just quantile values. Finite investment decision making using real market risk (non-diversifiable risk) was undertaken in this study. Non-diversifiable risk (systematic risk) estimates of a portfolio of stocks determined by a real risk weighted pricing model are used as initial data. The variance of non-diversifiable risk is estimated as a random variable referred to as random error (white noise). The estimator is used to calculate estimates of white noise (wn). A curve estimation of the wn is made using Kernel Density Estimation (KDE). KDE is a non-parametric way to estimate the probability density function of a random variable. KDE is a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample. This is used to derive probability estimates of the non-diversifiable risks of the various stocks. This enables determination of total risk with given probabilities of its occurrence thus facilitating decision making under risky and uncertain situations as well as accentuating comparison among the portfolio of stocks.
Survival and recovery of Mallards and Gadwalls banded in eastern Washington, 1981–1998

Abstract Current estimates of annual survival, an important process affecting population dynamics, are lacking for breeding-waterfowl populations in Washington. I used hunting-season recoveries in conjunction with band-recovery models (program MARK) to estimate survival and recovery probabilities of Mallards (Anas platyrhynchos) and Gadwalls (A. strepera) banded in eastern Washington during 1981–1998. I also evaluated hypotheses about sources of variation in these rates and described the geographical and temporal distribution of band recoveries. Mallard survival and recovery probabilities were sex and age-specific, and recovery rates were year-specific but not strongly correlated with harvest regulations. Survival probability of Mallards was 0.661 for adult males, 0.660 for immature females, 0.606 for adult females, and 0.560 for immature males. Average recovery rates were generally highest for immature males (0.083) followed by adult males (0.050), immature females (0.050), and adult females (0.029). Survival and recovery rates of Gadwalls were 0.576 and 0.054, respectively, but sample size was small (52 recoveries from 436 banded birds) and sex-age classes were pooled prior to analysis. Seventy-two percent of Mallards banded in eastern Washington were recovered in the Columbia Basin of central Washington. The proportion of adult-male recoveries decreased in the Columbia Basin (from 75% in 1981–84 to 54% in 1995–98) and increased in California (from 4% to 22%). The distribution of direct recoveries of Gadwalls was similar to Mallards. My data suggest that annual survival of Mallards and Gadwalls banded in eastern Washington was similar to or slightly higher than survival probabilities in other North America populations.
Influence of grazing and soil conditions on secondary savanna vegetation in India

Abstract. Savanna vegetation and pertinent soil features were studied on 43 sites in a dry tropical forest region of India. Grazing intensity ranged from 0.68 to 0.98. Soil moisture was positively related to the proportion of fine soil particles (< 0.1 mm), and the latter decreased while the proportion of coarse particles (2.0-0.5 mm) increased with increasing grazing intensity. Canopy biomass ranged from 28 to 104 g/m2 in grazed communities and from 230 to 337 g /m2 in ungrazed communities and was positively related to vegetation cover which ranged between 30–72 % in grazed and 68 - 91 % in ungrazed communities. Vegetation cover was negatively related to grazing intensity. Species richness and diversity were highest at low grazing intensity. Using community coefficients and Detrended Correspondence Analysis, the grazed stands were clustered into six and the ungrazed ones into three communities. The grazed communities were recognised as degradation stages and the ungrazed ones as recovery stages. Only five grass species, in various combinations were able to dominate in one of the different stages. Evidently the harsh climatic conditions (high temperatures, high variability in rainfall and a long dry period) in the region permit only a few species already adapted to these conditions to participate in the succession.
Modeling the bias of digital data: an approach to combining digital and survey data to estimate and predict migration trends

Reliable and timely estimates of migration flows are needed to guide our policy decisions and to improve our understanding of migration processes. However, obtaining timely and fine-grained estimates remains an elusive goal. Digital data provide granular information on time and space based on large sample sizes, but because these samples are often not representative of the general population, the estimates obtained by analyzing these data are biased. We propose a generic method for combining digital and survey data for the purposes of migration estimation by accounting for the bias structure of digital data. Specifically, we show that if the bias has a structure over time and space that can be statistically modeled, we can combine different sources of data for the purposes of prediction. We illustrate our approach by combining geo-located Twitter data for more than two million users (2010-2016) with data from the American Community Survey (ACS) to estimate state-level emigration in the United States. We propose a joint model that draws from both ACS and Twitter data by modeling the spatial and temporal correlation structure of Twitter biases. We show that while Twitter-based estimates are upwardly biased, when these estimates are combined with ACS estimates, the resulting predictions of internal migration flows are more accurate than predictions based on ACS data only. Our method can be used to forecast future migration flows or to fill in missing time periods for which survey estimates are not available. Finally, our model is flexible and can be extended to incorporate multiple sources of data, such as Twitter data, cellphone records, administrative reports, and survey estimates.
Comparative Analysis of Codon Usage and tRNA in Mitochondrial Genomes of Gallus Gallus

Codon usage in mitochondrial genes of 11 Gallus gallus and two Anatidae species was analysed to determine the general patterns in codon choice of Callus gallus species. C3 contents were higher in Gallus gallus than in mammalian mitochondrial genomes that encode protein codon positions. The high C3 contents of Callus gallus might be the result of relatively strong mutational bias that occurred in the lineage of the Callus gallus species. A and C ending codons were detected as the “preferred 77 codons in Callus gallus and Anatidae. The NNR codon families are dominated by the A-ending codons, the NNY codon families are dominated by the C-ending codons and the NNN codon families are dominated by the A-ending or the C-ending codons. A comparison of the relative synonymous codon usage (RSCU) and synonymous codon families (SCF) of tRNA and proteins was made, and two groups can be classified by SCF. The codon usage in Callus gallus species indicates that codons containing A or C at the third position are used preferentially, regardless of whether corresponding tRNAs are encoded in the mtDNA. In both Callus gallus and Anatidae species mtDNA, codon usage biases are highly related to CC-ending binucleotide condons.
Surprisingly small: effects of “generous” social benefits on re-employment of (quasi-) jobless households

Abstract This article analyses whether the extent of public welfare provision influences the speed at which (quasi-)jobless households get (back) into employment. (Quasi-)joblessness is one of the key criteria defining the risk of poverty and social exclusion in the EU. Moreover, the perceived tension between the main functions of social benefits (protecting households from poverty and incentivising job search) is most acute among these households. Based on EU-SILC data, we examine changes of household work intensity during one year after benefit receipt. We observe that “more-generous” social benefits have a slightly negative impact. This can potentially be due to a disincentive effect of social benefits, but it can also mean that the additional financial leeway is used by job seekers to wait for more adequate job offers or engage in further training. Even though statistically significant, the estimated negative effects are very small.
Data linking over RDF knowledge graphs: A survey

Instance matching (IM) is the process of matching instances across Knowledge Bases (KBs) that refer to the same real‐world object (eg, the same person in two different KBs). Several approaches in the literature were developed to perform this process using different algorithmic techniques and search strategies. In this article, we aim to provide the rationale for IM and to survey the existing algorithms for performing this task. We begin by identifying the importance of such a process and define it formally. We also provide a new classification of these approaches depending on the “source of evidence,” which can be considered as the context information integrated explicitly or implicitly in the IM process. We survey and discuss the state‐of‐the‐art IM methods regarding the context information. We, furthermore, describe and compare different state‐of‐the‐art IM approaches in relation to several criteria. Such a comprehensive comparative study constitutes an asset and a guide for future research in IM.
Switching-Like Event-Triggered Control for Networked Control Systems Under Malicious Denial of Service Attacks

This article investigates the switching-like event-triggered control for networked control systems (NCSs) under the malicious denial of service (DoS) attacks. First, by dividing the DoS attacks into S-interval (DoS-free case) and D-interval (DoS case), a switching-like event-triggered communication scheme (SETC) is well designed to deal with intermittent DoS attacks to improve communication efficiency while keeping the desired control performance. Second, by considering the SETC and NCSs into a unified framework, the studied system is transferred into a time-delay system. Then, under the constraint of the number of maximum allowable data dropouts induced by DoS attacks, a stability criterion and a stabilization criterion are derived, which can be used to estimate the event-triggered communication parameters and obtain the security controller gain simultaneously. Moreover, the derived stabilization criterion can also provide a tradeoff to balance communication efficiency and $H_{\infty }$ control performance. At last, a networked invert pendulum on a cart is conducted to show the effectiveness of the proposed method.