Miracle-dz/UniFAR-FTUs huggingface dataset:
A null-model analysis of the spatio-temporal distribution of earthworm species assemblages in Colombian grasslands

Abstract: Earthworm assemblages are usually spatio-temporally structured in mosaics of patches with different species composition. We re-analysed results of past research carried out in Eastern Colombia to explore how interspecific competition accounts for this pattern. In three sown pastures and three native savannas, density data matrices were obtained from spatially explicit samplings at several successive dates, and spatio-temporal patterns of species assemblages were described through partial triadic analyses and geostatistics. This first analysis detected assemblage patchiness in the six plots at spatial scales ranging from 6 to 33 m. Species richness ranged from 5 to 6 species per plot. Null models were further used to analyse niche overlap and morphometric distribution patterns at two different scales, i.e. at the ‘plot level’ and the ‘patch level’. Seasonal and vertical niche overlaps were higher than expected by chance at both scales, indicating high environmental constraints on assemblage membership. Within-patch overlaps were lower than plot-scale overlaps. Biometric niche overlap was random at the plot level and was weakly lower than that expected by chance in patches. Body weight was significantly overdispersed and constant whatever the scale, while body length and diameter showed a similar trend within patches. These results suggest that earthworms form distinct assemblages within patches, mainly driven by deterministic responses to competition: ecologically similar species avoid competition through spatial segregation, whereas a minimal level of ecological segregation is required to allow co-existence in a given patch.
Towards a Complexity Theory for the Congested Clique

The congested clique model of distributed computing has been receiving attention as a model for densely connected distributed systems. While there has been significant progress on the side of upper bounds, we have very little in terms of lower bounds for the congested clique; indeed, it is now known that proving explicit congested clique lower bounds is as difficult as proving circuit lower bounds. In this work, we use various more traditional complexity theory tools to build a clearer picture of the complexity landscape of the congested clique: \beginitemize ıtem Nondeterminism and beyond: We introduce the nondeterministic congested clique model (analogous to NP) and show that there is a natural canonical problem family that captures all problems solvable in constant time with nondeterministic algorithms. We further generalise these notions by introducing the constant-round decision hierarchy (analogous to the polynomial hierarchy). ıtem Non-constructive lower bounds: We lift the prior non-uniform counting arguments to a general technique for proving non-constructive uniform lower bounds for the congested clique. In particular, we prove a time hierarchy theorem for the congested clique, showing that there are decision problems of essentially all complexities, both in the deterministic and nondeterministic settings. ıtem Fine-grained complexity: We map out relationships between various natural problems in the congested clique model, arguing that a reduction-based complexity theory currently gives us a fairly good picture of the complexity landscape of the congested clique. \enditemize
Verdict, Sentencing, and Certainty as a Function of Sex of Juror and Amount of Evidence in a Simulated Rape Trial

The purpose was to investigate the relationship between sex of juror and amount of evidence to verdict, sentencing, and certainty in a simulated rape trial. Subjects were 118 female and 109 male college students. Analyses indicate, even under conditions of strong evidence, men are less likely to find the defendant guilty and prescribe shorter sentences than women. Women, under the conditions of moderate evidence, were more likely than men to find the defendant guilty. The results also suggest that certitude and severity of sentence are driven by the verdict reached rather than by gender. The findings are compared with those of other studies and discussed in terms of the ideation of men and women, environment and subjects' characteristics, and mode of presentation in a simulated rape trial.
Getting a handle on how the brain generates complexity

Sensory processing in cortex across modalities appears to rely on a “simple-to-complex” hierarchical computational strategy in which neurons at later levels in the hierarchy combine inputs from earlier levels to create more complex neuronal selectivities. The specifics of this process are still poorly understood, however. In this issue of Network, Plebe shows how computational modeling of experimental data on neuronal tuning in secondary visual cortex can help us understand how the brain increases neuronal tuning complexity across the visual cortical hierarchy.
MAGELLAN: An Integrated Adaptive Architecture for Mobile Robotics

Abstract : In this paper we describe MAGELLAN, an integrated architecture for mobile robotics. The system represents its spatial knowledge in terms of a topological network that connects a set of distinct places, each represented by evidence grids that contain probabilistic descriptions of occupancy. MAGELLAN includes a module for place recognition that determines its initial location and when it has reached a goal, a module for continuous localization that maintains accurate estimates of the robot's position, and a module for navigation that generates path plans and executes them using reactive behaviors. Experiments in two laboratories with different characteristics suggest that the system can operate robustly across a range of environments, including ones that involve dynamic changes.
Expert finding in question-answering websites: a novel hybrid approach

Question answering websites are becoming an ever more popular knowledge sharing platform. On such websites, people may ask any type of question and then wait for someone else to answer the question. However, in this manner, askers may not obtain correct answers from appropriate experts, and knowledge sharing through question answering websites is interfered. Recently, various approaches have been proposed to automatically find experts in Question answering websites. In this paper, we propose a novel hybrid approach to effectively find experts for the category of the target question in question answering websites. Our approach considers user subject relevance, user reputation and authority of a category in finding experts. The experiment results show that our proposed methods outperform other conventional methods.
New method for the simultaneous detection of metabolites and water in localized in vivo 1H nuclear magnetic resonance spectroscopy

A new two‐scan method for localized 1H in vivo NMR spectroscopy (MRS) without water suppression (WS) is described. In one of the scans, two chemical shift selective 180° pulses are applied prior to a standard localization sequence to invert all metabolite signals upfield and downfield from water, which remains unaffected. The difference spectrum records the metabolites whereas water and accompanying gradient induced artifacts are widely suppressed. The method was implemented on a 4.7‐T system using point resolved spectroscopy with a short echo time of 18 ms. Phantom measurements proved the feasibility of absolute quantification using water as an internal reference. Measurements on healthy rat brain yielded comparable spectrum quality as measurements with water presaturation. The method does not require additional adjustments or sophisticated data postprocessing and scales favorably with increasing B0 field. Therefore, the method should be useful for 1H MRS without WS. Although the two‐step method doubles the minimum total measurement time, it may also be of interest for spectroscopic imaging (SI) without WS, in particular if fast SI techniques are applied. Magn Reson Med 54:190–195, 2005. © 2005 Wiley‐Liss, Inc.
Externalizing in preschoolers and early adolescents : a cross-study replication of a family model

With families of 3'/2-year-olds, the direct and indirect links among parents' depression, marital quality, parenting style, and their children's externalizing behavior were examined using partial least squares analysis. No direct paths were found between parents' depression and their child's behavior. Instead, parents' depression was mediated by the quality of their relationship as a couple or by their parenting style, or by both. A replication with families of 9- to 13-year-olds supported these findings in the form of the interconnections among family variables and children's outcomes, although the magnitude of the family-child linkage was much lower than it was in the younger sample. Children's cognitive and social competence has been found to correlate with their parents' psychological adjustment, parenting style, and, more recently, the quality of their marriage (C. P. Cowan, Cowan, Heming, & Miller, 1991; Hetherington & Clingempeel, 1992). Although the direction of influence, from child to parent or parent to child, has not been clearly established, findings have been consistent in relating children's adaptive or maladaptive behavior to parent functioning in intrapersonal , parent-child, and marital domains. The task of describing pathways from adult functioning to children's adaptation raises both conceptual and statistical issues. Conceptually, the fact that there is a correlation between, for example, mothers' depression and children's aggression, does not tell us whether there is a direct link between maternal and child behavior or an indirect link resulting from the influence of mothers' depression on the quality of their relationships with their children. Statistically, the problem is how to analyze direct and indirect effects in nonexperiment al, observationbased family studies. The question of whether family models of children's development have the same form when children are at different developmental levels has not been given the attention it deserves. Part
Dysproteinemia and the Kidney

Dysproteinemia is a clinical state characterized by abnormal, often excessive, synthesis of immunoglobulin (Ig) molecules or subunits. Dysproteinemia results from clonal proliferation of plasma cells or B lymphocytes. The abnormal circulating Ig molecules or subunits (most commonly free light chains) reach the glomerulus via the systemic circulation and are associated with the development of a variety of pathologic lesions within the kidney. Free light chain molecules may pass through the glomerular basement membrane and form casts within distal tubular lumina (myeloma cast nephropathy) or form crystals within the cytoplasm of proximal tubules (light chain Fanconi syndrome). Alternatively, Ig molecules or subunits may form paraprotein tissue deposits and produce an array of pathologic lesions, most commonly amyloidosis and monoclonal Ig deposition disease. The pattern of renal parenchymal disease is determined by the unique properties of the Ig molecule or subunit. Each of the patterns of renal disease is in turn associated with unique, but frequently overlapping, clinical features and outcomes. This review emphasizes the pathologic, clinical, and prognostic differences among the patterns of renal parenchymal disease related to dysproteinemia.
Estimating rates of rare events at multiple resolutions

We consider the problem of estimating occurrence rates of rare eventsfor extremely sparse data, using pre-existing hierarchies to perform inference at multiple resolutions. In particular, we focus on the problem of estimating click rates for (webpage, advertisement) pairs (called impressions) where both the pages and the ads are classified into hierarchies that capture broad contextual information at different levels of granularity. Typically the click rates are low and the coverage of the hierarchies is sparse. To overcome these difficulties we devise a sampling method whereby we analyze aspecially chosen sample of pages in the training set, and then estimate click rates using a two-stage model. The first stage imputes the number of (webpage, ad) pairs at all resolutions of the hierarchy to adjust for the sampling bias. The second stage estimates clickrates at all resolutions after incorporating correlations among sibling nodes through a tree-structured Markov model. Both models are scalable and suited to large scale data mining applications. On a real-world dataset consisting of 1/2 billion impressions, we demonstrate that even with 95% negative (non-clicked) events in the training set, our method can effectively discriminate extremely rare events in terms of their click propensity.
Caffeine Taste Signaling in Drosophila Larvae

The Drosophila larva has a simple peripheral nervous system with a comparably small number of sensory neurons located externally at the head or internally along the pharynx to assess its chemical environment. It is assumed that larval taste coding occurs mainly via external organs (the dorsal, terminal, and ventral organ). However, the contribution of the internal pharyngeal sensory organs has not been explored. Here we find that larvae require a single pharyngeal gustatory receptor neuron pair called D1, which is located in the dorsal pharyngeal sensilla, in order to avoid caffeine and to associate an odor with caffeine punishment. In contrast, caffeine-driven reduction in feeding in non-choice situations does not require D1. Hence, this work provides data on taste coding via different receptor neurons, depending on the behavioral context. Furthermore, we show that the larval pharyngeal system is involved in bitter tasting. Using ectopic expressions, we show that the caffeine receptor in neuron D1 requires the function of at least four receptor genes: the putative co-receptors Gr33a, Gr66a, the putative caffeine-specific receptor Gr93a, and yet unknown additional molecular component(s). This suggests that larval taste perception is more complex than previously assumed already at the sensory level. Taste information from different sensory organs located outside at the head or inside along the pharynx of the larva is assembled to trigger taste guided behaviors.
Z2F: Heterogeneous graph-based Android malware detection

Android malware is becoming more common, and its invasion of smart devices has brought immeasurable losses to people’s lives. Most existing Android malware detection methods extract Android features from the original application files without considering the high-order hidden information behind them, but these hidden information can reflect malicious behaviors. To solve this problem, this paper proposes Z2F, a detection framework based on multidimensional Android feature extraction and graph neural networks for Android applications. Z2F first extracts seven types of Android features from the original Android application and then embeds them into a heterogeneous graph. On this basis, we design 12 kinds of meta-structures to analyze different semantic spaces of heterogeneous graphs, mine high-order hidden semantic information, and adopt a multi-layer graph attention mechanism to iteratively embed and update information. In this paper, a total of 14429 Android applications were detected and 1039726 Android features were extracted, with a detection accuracy of 99.7%.
Research on local sound field intensity control technique in metasurface based on deep neural networks

The use of tunable metasurface technology to realize the underwater tracking function of submarines, which is one of the hotspots and difficulties in submarine design. The structure-to-sound-field metasurface design approach is a highly iterative process based on trial and error. The process is cumbersome and inefficient. Therefore, an inverse design method was proposed based on parallel deep neural networks. The method took the global and local target sound field feature information as input and the metasurface physical structure parameters as output. The deep neural network was trained using a kernel loss function based on a radial basis kernel function, which established an inverse mapping relationship between the desired sound field to the metasurface physical structure parameters. Finally, the sound field intensity modulation at a localized target range was achieved. The results indicated that within the regulated target range, this method achieved an average prediction error of less than 5 dB for 92.9% of the sample data.
Context-Aware Active Task Discovery for Pervasive Computing

Task computing is mainly involved with how to interact with equipment and services for users. In such new mode user can only concern with the task need to be completed, without having to consider how to complete it. In recent years, this new mode has been considered the preferred choice under the environment of pervasive computing. Active task discovery is the key to task computing, which depends on context and automatically relates the corresponding services to complete the given operation. In this paper, based on active task computing model we present a new context-aware active task discovery mode and raise a good algorithm for discovering and executing task.
E Pluribus Unum: Bilingualism and Loss of Language in the Second Generation.

This study examined patterns of language adaptation by over 5,000 second-generation students in south Florida and southern California. It found that among most immigrant nationalities, knowledge of and preference for English is nearly universal, that only a minority remain fluent in their parents' languages, and there are wide variations among immigrant groups in the extent of their retention of these languages. The authors used multivariate and multilevel analyses to identify the principal factors accounting for variation in foreign language maintenance and bilingualism. They found that a number of variables emerged as significant predictors, but these variables do not account for differences among immigrant nationalities, such as between children of Asian and Hispanic backgrounds, that become even more sharply delineated. The reasons for this divergence are explored and their policy implications are discussed.
FPGA design and implementation of edge enhancement by using 3×3 mask filter

This paper proposes a method to implement an image filtering module by using 3×3 mask on FPGA. The 3×3 mask filter module has an advantage of minimizing a usage of memory and a propagation delay from input to output. Depending on coefficient value of 3×3 mask filter module, we can acquire several image processing effects such as mean filtering, median filtering, and edge enhancement. When we applied Laplacian filter to enhance sharpness of an image by using the 3×3 mask filter module, not only edges components but also noise components of an image were enhanced by Laplacian filter. So we propose an adaptive edge enhancement by using Laplacian filter that is a method to enhance edge components except noise components of an image by analyzing a variance of pixel data in 3×3 mask. We applied the adaptive edge enhancement by using Laplacian filter to an infrared camera and conducted an experiment about its effect. The experimental result proves that the proposed method is effective to implement the edge enhancement of an image with minimum usage of memory in real time.
Bias in Estimation of Transporter Kinetic Parameters from Overexpression Systems: Interplay of Transporter Expression Level and Substrate Affinity

The objective was to investigate the interplay between transporter expression levels and substrate affinity in controlling the influence of aqueous boundary layer (ABL) resistance on transporter kinetics in an over-expression system. Taurocholate flux was measured across human apical sodium-dependent bile acid transporter (hASBT)-Madin-Darby canine kidney monolayers on different occasions and kinetic parameters estimated with and without considering ABL. In error-free simulation/regression studies, flux values were generated across a range of Jmax, Kt, and substrate concentrations. Similar evaluation was performed for transport inhibition studies. Additionally, simulation/regression studies were performed, incorporating 15% random error to estimate the probability of successfully estimating Kt. Across different occasions, experimental Jmax and Kt estimates for taurocholate were strongly associated (p < 0.001; r2 = 0.82) when ABL was not considered. Simulation/regression results indicate that not considering ABL caused this association, such that Kt estimates were highly positively biased at high hASBT expression. In reanalyzing taurocholate flux data using the ABL-present model, Kt was relatively constant across occasions (∼5 μM) and not associated with Jmax (p = 0.24; r2 = 0.13). Simulations suggest that Jmax and Kt collectively determined ABL influence, which is most prominent under conditions of low monolayer resistance. Additionally, not considering ABL lead to negatively biased Ki estimates, especially at high Jmax. Error-inclusive simulation/regression studies indicated that the probability of successfully estimating Kt depended on the contribution of ABL resistance to flux; when flux became increasingly ABL-limited, probability of success decreased. Results indicate that ABL resistance can bias Kt and Ki estimates from overexpression systems, where the extent of bias is determined by transporter expression level and substrate affinity.
Readability and language complexity in old and new law study guides: A corpus-based account of a stylistic shift

Abstract This article explores linguistic reflexes of a move in South African university distance education towards more learner-orientated study material. In what ways might such material be said to be more accessible? Two aspects of accessibility, namely readability and complexity features, are focused on and these are compared by way of corpus analyses of an earlier, more content-orientated study guide introducing the theory of law and a later, more learner-orientated guide. The findings provide an account of some key linguistic characteristics that appear to underpin the enhanced accessibility of the latter guide.
Toward sustainable health‐care services: principles, challenges, and a process

Sustainable health care combines three key factors: quality patient care, fiscally responsible budgeting and minimizing environmental impact. Although pollution is well understood as a health problem, US health planners have not fully recognized the need to reduce health‐care pollution. Minimizing health‐care pollution, moreover, requires reducing the throughput of energy and materials. Ultimately, sustaining healthy ecosystems requires that health‐care material and energy utilization be limited. However, traditional conceptions of health‐care ethics maintain a philosophy of rescue that makes limiting life‐saving resources, except at a patient’s request, morally worrisome. Moreover, the media image of health care as technologically intensive, together with the common medical view that nature is the enemy, render suspect philosophical perspectives respectful of Earth’s limits. Nevertheless, academic medical centers have advantages as sites for pursuing sustainability: students often uphold environmental ideals, a public health perspective, and an interest in providing services universally; basic biomedical research on campus permits innovative research combining health and environmental considerations; opportunities exist for including environmental concerns in health professional education; some academic medical centers have already stated environmental criteria for purchasing contracts; and health‐care professionals and institutions are increasingly addressing such environmental concerns as mercury use, latex allergies, dioxin pollution, and waste volume. To address these challenges, a visioning process is proposed, designed to formulate a practical plan by means of public, local, and professional participation in the process of articulating creative and morally sound proposals for change.