Miracle-dz/UniFAR-FTUs huggingface dataset:
Fire-Maintained Pine Savannas and Woodlands of the Southeastern United States Coastal Plain

Descriptions by early naturalists provide glimpses of presettlement southeastern coastal plain landscapes. Means (1996) quoted Bartram (1791): “This plain is mostly … the great long-leaved pine (P. palustris Linn.), the earth covered with grass, interspersed with an infinite variety of herbaceous plants, and embellished with extensive savannas, always green, sparkling with ponds of water…. We left the magnificent savanna …, passing through a level, open, airy pine forest, the stately trees scatteringly planted by nature, arising straight and erect from the green carpet, embellished with various grasses and flowering plants, and gradually ascending the sand hills … ”
Effects of Acute Tryptophan Depletion on Brain Serotonin Function and Concentrations of Dopamine and Norepinephrine in C57BL/6J and BALB/cJ Mice

Background Acute tryptophan depletion (ATD) is a method of lowering brain serotonin (5-HT) synthesis. Administration of large neutral amino acids (LNAA) limits the transport of endogenous tryptophan (TRP) across the blood–brain barrier by competition with other LNAAs and subsequently decreases serotonergic neurotransmission. A recent discussion on the specificity and efficacy of the ATD paradigm for inhibition of central nervous 5-HT has arisen. ATD Moja-De is a revised mixture of AAs which is less nauseating than conventional protocols, possibly because of an administration in accordance with the body weight of the subjects. It has been used in the preliminary clinical studies, but its effects on central 5-HT mechanisms and other neurotransmitter systems have not been validated in an animal model. Design We tested ATD Moja-De (TRP-) in two strains of mice, C57BL/6 and BALB/cJ, which are reported to have impaired 5-HT synthesis relative to other strains of mice. Results ATD Moja-De lowered brain TRP, significantly decreased central nervous 5-HT synthesis as indexed by 5-HTP levels after decarboxlyase inhibition, and lowered 5-HT and 5 HIAA in both strains of mice, however, more so in C57 BL/6 than in BALB/cJ. Dopamine and its metabolites as well as norepinephrine were not affected. A tryptophan-balanced control mixture did not increase 5-HT or 5-HIAA. Conclusion The present findings suggest that ATD Moja-De effectively suppresses central serotonergic function, and that the effects of ATD Moja-De are specific to serotonin function.
Numerical Modelling of a Slowly Creeping Landslide In Crystalline Rock - a Case Study

Glacial erosion brings many alpine valleys to limit equilibrium because of the steepened valley flanks. Instable slopes hold potential dangers, even though slowly creeping landslides as treated below can be observed and do seldom show surprising behavior as long as they do not accelerate. Nevertheless a sudden loss of stability can lead to uncontrollable movements with much higher velocities. Aim of the project presented here is to gain a better understanding of mass movements and the influences of different boundary conditions on slope displacement. A well monitored example for a slowly creeping landslide is the mass movement Hochmais Atemkopf, situated in the Kaunertal, Tyrol, Austria. Based on a geological model a calculation model including four sliding masses has been developed. In addition, external effects were also taken into account to get an idea of their possible influences on stability and deformation. This paper presents a limit equilibrium analysis and the preliminary results of a numerical finite element study.
Australian Information Security Management Conference Conferences , Symposia and Campus Events 2008 Trust me . I am a Doctor . Your records are safe

Primary care medical practices in Australia have been identified as a profession in need of assistance with information security practices. Whilst guidelines exist, there is little assistance in an accessible and easily implemented form for medical practices. This research presents the preliminary findings of a study which advocates that information security practices can be improved using a capability operational framework which is contextualised to its target environment.
International Journal of Advanced Research in Computer Science and Software Engineering

— To evaluate the interconnection topology, data loss is the measure performance parameter. This paper analyze the packet loss during the fault in mesh interconnection network topology with source routing using network simulator NS2. The designed framework considers two parameters packet size and packet generation interval to evaluate the performance of mesh interconnection topology. The mesh simulation network uses both with and without acknowledgement transmissions. The results describe the network performance of mesh in the end.
Analysing graph transformation systems through constraint handling rules

Abstract Graph transformation systems (GTS) and constraint handling rules (CHR) are non-deterministic rule-based state transition systems. CHR is well known for its powerful confluence and program equivalence analyses, for which we provide the basis in this work to apply them to GTS. We give a sound and complete embedding of GTS in CHR, investigate confluence of an embedded GTS and provide a program equivalence analysis for GTS via the embedding. The results confirm the suitability of CHR-based program analyses for other formalisms embedded in CHR.
Feedback Linearization Robot Control based on Gaussian Process Inverse Dynamics Model

In this paper, we analyze the implementation of feedback linearization control scheme based on full data-driven inverse dynamics models. We made no use of physical models in the deﬁnition of the inverse dynamics, that was learned entirely from previously recorded data via Gaussian Process Regression (GPR). The resulting controller was tested on a simulated manipulator with 7 degrees of freedom (dof), to solve a trajectory tracking problem. Different kernel functions were tested, in particular, we analyzed the performance obtained by Squared Exponential (SE) kernel and the recently introduced Geometrically Inspired Polynomial (GIP) kernel. Results show that GIP obtains better tracking precision and is more robust w.r
Does Broadband Matter for Rural Entrepreneurs or ‘Creative Class’ Employees?

Broadband, or high-speed Internet access, has changed the way our society operates; yet there are still parts of rural American where the connection is lagging behind. Closing the ‘digital divide’ is a priority on rural America’s agenda, with government programs focusing on providing broadband infrastructure to unserved (or underserved) areas. An unanswered question, however, is whether a relationship exists between broadband availability and the existence of entrepreneurs or ‘creative class’ workers in rural communities. These types of workers have been shown to be particularly important for economic growth in rural areas. One relevant hypothesis is that some threshold related to broadband exists (a specific download speed, or number of providers) that is positively related to the existence of rural entrepreneurs; such a finding would have meaningful implications for future U.S. broadband policy. This research explores this relationship using county-level data from the 2012 National Broadband Map and measures of entrepreneurship and creative class employees from the Census and ERS. Spatial econometric tools are used to assess the cross-section relationship as of 2012. First-differenced regressions are also used to determine whether increasing levels of broadband have influenced changes in entrepreneurship or creative class employees in rural areas over time.
Sufficient dimension reduction via distance covariance for functional and longitudinal data

We propose a method of sufficient dimension reduction for functional data using distance covariance. We consider the case where the response variable is a scalar but the predictor is a random function. Our method has several advantages. It requires very mild conditions on the predictor, unlike the existing methods require the restrictive linear conditional mean assumption and constant covariance assumption. It also does not involve the inverse of the covariance operator which is not bounded. The link function between the response and the predictor can be arbitrary and our method maintains the model free advantage without estimating the link function. Moreover, our method is naturally applicable to sparse longitudinal data. We use functional principal component analysis with truncation as the regularization mechanism in the development. The justification for validity of the proposed method is provided and under some regularization conditions, statistical consistency of our estimator is established. Simulation studies and real data analysis are also provided to demonstrate the performance of our method.
Issues in Information Systems

This study attempted to investigate what factors significantly affect trust in social commerce. The authors proposed five factors including social influences, customer attitudes/biases/past experiences, reputation of business, reputation of peers, and transactional security. The authors employed three models including multiple regression model, logistic regression model and structural equation model. Sample data was collected from a survey questionnaire. The study found that peer reputation and transaction security significantly affected consumer trust when using social commerce to purchase goods online. Social influence, customer attitude, and business reputation had mixed results. When segmenting by gender, the trust of women was found to be significantly impacted by social influence, customer attitude, and peer reputation, while peer reputation and transaction security significantly impacted men’s trust.
Dissociable roles of neural pattern reactivation and transformation during recognition of words read aloud and silently: An MVPA study of the production effect

Recent work surrounding the neural correlates of episodic memory retrieval has focussed on the decodability of neural activation patterns elicited by unique stimuli. Research in this area has revealed two distinct phenomena: (i) neural pattern reactivation, which describes the fidelity of activation patterns between encoding and retrieval; (ii) neural pattern transformation, which describes systematic changes to these patterns. This study used fMRI to investigate the roles of these two processes in the context of the production effect, which is a robust episodic memory advantage for words read aloud compared to words read silently. Twenty-five participants read words either aloud or silently, and later performed old-new recognition judgements on all previously seen words. We applied multivariate analysis to compare measures of reactivation and transformation between the two conditions. We found that, compared with silent words, successful recognition of aloud words was associated with reactivation in the left insula and transformation in the left precuneus. By contrast, recognising silent words (compared to aloud) was associated with relatively more extensive reactivation, predominantly in left ventral temporal and prefrontal areas. We suggest that recognition of aloud words might depend on retrieval and metacognitive evaluation of speech-related information that was elicited during the initial encoding experience, while recognition of silent words is more dependent on reinstatement of visual-orthographic information. Overall, our results demonstrate that different encoding conditions may give rise to dissociable neural mechanisms supporting single word recognition.
Haplotype-resolved genome and population genomics of the threatened garden dormouse in Europe

Genomic resources are important for evaluating genetic diversity and supporting conservation efforts. The garden dormouse (Eliomys quercinus) is a small rodent that has experienced one of the most severe modern population declines in Europe. We present a high-quality haplotype-resolved reference genome for the garden dormouse, and combine comprehensive short and long-read transcriptomics datasets with homology-based methods to generate a highly complete gene annotation. Demographic history analysis of the genome revealed a sharp population decline since the last interglacial, indicating that colder climates caused severe population declines prior to anthropogenic influence. Using our genome and genetic data from 100 individuals, largely sampled in a citizen-science project across the contemporary range, we conducted the first population genomic analysis for this species to investigate patterns of connectivity between regions and factors explaining population declines. We found clear evidence for population structure across the species’ core Central European range. Notably, our data provide strong evidence that the Alpine population, characterized by strong differentiation likely due to habitat isolation, represents a differentiated evolutionary significant unit (ESU). Our data also show that the predominantly declining Eastern European populations show signs of recent isolation, a pattern consistent with a range expansion from Western to Eastern Europe during the Holocene, leaving relict populations now facing local extinction. Overall, our findings suggest that garden dormouse conservation may be enhanced in Europe through designation of ESUs.
Graspable foods and tools elicit similar responses in visual cortex

Extrastriatal visual cortex is known to exhibit distinct response profiles to complex stimuli of varying ecological importance (e.g., faces, scenes, and tools). The dominant interpretation of these effects is that they reflect activation of distinct “category-selective” brain regions specialized to represent these and other stimulus categories. We sought to explore an alternative perspective: that the response to these stimuli is determined less by whether they form distinct categories, and more by their relevance to different forms of natural behavior. In this regard, food is an interesting test case, since it is primarily distinguished from other objects by its edibility, not its appearance, and there is evidence of food-selectivity in human visual cortex. Food is also associated with a common behavior, eating, and food consumption typically also involves the manipulation of food, often with the hands. In this context, food items share many properties in common with tools: they are graspable objects that we manipulate in self-directed and stereotyped forms of action. Thus, food items may be preferentially represented in extrastriatal visual cortex in part because of these shared affordance properties, rather than because they reflect a wholly distinct kind of category. We conducted fMRI and behavioral experiments to test this hypothesis. We found that behaviorally graspable food items and tools were judged to be similar in their action-related properties, and that the location, magnitude, and patterns of neural responses for images of graspable food items were similar in profile to the responses for tool stimuli. Our findings suggest that food-selectivity may reflect the behavioral affordances of food items rather than a distinct form of category-selectivity.
Protein aggregation is a consequence of the dormancy-inducing membrane toxin TisB in Escherichia coli

Bacterial dormancy is a valuable strategy to survive stressful conditions. Toxins from chromosomal toxin-antitoxin systems have the potential to halt cell growth, induce dormancy and eventually promote a stress-tolerant persister state. Due to their potential toxicity when overexpressed, sophisticated expression systems are needed when studying toxin genes. Here, we present an optimized plasmid expression system for toxin genes based on an artificial 5’ untranslated region. We applied the system to induce expression of the toxin gene tisB from the chromosomal type I toxin- antitoxin system tisB/istR-1 in Escherichia coli. TisB is a small hydrophobic protein that targets the inner membrane, resulting in depolarization and ATP depletion. We analyzed TisB-producing cells by RNA- sequencing and revealed several genes with a role in recovery from TisB-induced dormancy, including the chaperone genes ibpB, spy and cpxP. The importance of chaperone genes suggested that TisB- producing cells are prone to protein aggregation, which was validated by an in vivo fluorescent reporter system. We moved on to show that TisB is an essential factor for protein aggregation upon DNA damage mediated by the fluoroquinolone antibiotic ciprofloxacin in E. coli wild-type cells. The occurrence of protein aggregates correlates with an extended dormancy duration, which underscores their importance for the life cycle of TisB-dependent persister cells. Importance Protein aggregates occur in all living cells due to misfolding of proteins. In bacteria, protein aggregation is associated with cellular inactivity, which is related to dormancy and tolerance to stressful conditions, including the exposure to antibiotics. In Escherichia coli, the membrane toxin TisB is an important factor for dormancy and antibiotic tolerance upon DNA damage mediated by the fluoroquinolone antibiotic ciprofloxacin. Here, we show that TisB provokes protein aggregation, which in turn promotes a deeper state of cellular dormancy. Our study suggests that protein aggregation is a consequence of membrane toxins with the potential to affect the duration of dormancy and the outcome of antibiotic therapy.
A doubly stochastic renewal framework for partitioning spiking variability

The firing rate is a prevalent concept used to describe neural computations, but estimating dynamically changing firing rates from irregular spikes is challenging. An inhomogeneous Poisson process, the standard model for partitioning firing rate and spiking irregularity, cannot account for diverse spike statistics observed across neurons. We introduce a doubly stochastic renewal point process, a flexible mathematical framework for partitioning spiking variability, which captures the broad spectrum of spiking irregularity from periodic to super-Poisson. We validate our partitioning framework using intracellular voltage recordings and develop a method for estimating spiking irregularity from data. We find that the spiking irregularity of cortical neurons decreases from sensory to association areas and is nearly constant for each neuron under many conditions but can also change across task epochs. A spiking network model shows that spiking irregularity depends on connectivity and can change with external input. These results help improve the precision of estimating firing rates on single trials and constrain mechanistic models of neural circuits.
High phenotypic and genotypic plasticity among strains of the mushroom-forming fungus Schizophyllum commune

Schizophyllum commune is a mushroom-forming fungus notable for its distinctive fruiting bodies with split gills. It is used as a model organism to study mushroom development, lignocellulose degradation and mating type loci. It is a hypervariable species with considerable genetic and phenotypic diversity between the strains. In this study, we systematically phenotyped 16 dikaryotic strains for aspects of mushroom development and 18 monokaryotic strains for lignocellulose degradation. There was considerable heterogeneity among the strains regarding these phenotypes. The majority of the strains developed mushrooms with varying morphologies, although some strains only grew vegetatively under the tested conditions. Growth on various carbon sources showed strain-specific profiles. The genomes of seven monokaryotic strains were sequenced and analyzed together with six previously published genome sequences. Moreover, the related species Schizophyllum fasciatum was sequenced. Although there was considerable genetic variation between the genome assemblies, the genes related to mushroom formation and lignocellulose degradation were well conserved. These sequenced genomes will provide a solid basis for functional genomics analyses of the strains of S. commune.
Neural decoding of the speech envelope: Effects of intelligibility and spectral degradation

During continuous speech perception, patterns of endogenous neural activity become time-locked to acoustic stimulus features, such as the speech amplitude envelope. This speech-brain coupling can be decoded using non-invasive brain imaging techniques, including electroencephalography (EEG). Methods like these may provide clinical use as an objective measure of stimulus encoding by the brain, for example, in the case of cochlear implant (CI) listening. Yet, the CI-transmitted speech signal is severely spectrally degraded, rendering its amenability to neural decoding unknown. Furthermore, interplay between acoustic and linguistic factors may lead to top-down modulation of perception, thereby challenging potential audiological applications. We assess neural decoding of the speech envelope under spectral degradation with EEG in acoustically hearing listeners (n = 38; 18-35 years old) using vocoded speech. Additionally, we dissociate sensory from higher-order processing by employing intelligible (English) and non-intelligible (Dutch) stimuli. Subject-specific and group decoders were trained to reconstruct the speech envelope from held-out EEG, with decoder significance determined via random permutation testing. Whereas speech envelope reconstruction did not vary by acoustic clarity, intelligible speech was associated with better decoding accuracy in general. Results were similar across subject-specific and group analyses, with less consistent effects of spectral degradation in group decoding. Permutation tests revealed possible differences in decoder statistical significance by experimental condition. In general, while robust neural decoding was observed at the group level, variability within participants would most likely prevent the clinical use of such a measure to differentiate levels of spectral degradation and intelligibility on an individual basis.