Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of Environmental, Biotic and Spatial Factors on Diatom Metacommunity Structure in Swedish Headwater Streams

Stream assemblages are structured by a combination of local (environmental filtering and biotic interactions) and regional factors (e.g., dispersal related processes). The relative importance of environmental and spatial (i.e., regional) factors structuring stream assemblages has been frequently assessed in previous large-scale studies, but biotic predictors (potentially reflecting local biotic interactions) have rarely been included. Diatoms may be useful for studying the effect of trophic interactions on community structure since: (1) a majority of experimental studies shows significant grazing effects on diatom species composition, and (2) assemblages can be divided into guilds that have different susceptibility to grazing. We used a dataset from boreal headwater streams in south-central Sweden (covering a spatial extent of ∼14000 km2), which included information about diatom taxonomic composition, abundance of invertebrate grazers (biotic factor), environmental (physicochemical) and spatial factors (obtained through spatial eigenfunction analyses). We assessed the relative importance of environmental, biotic, and spatial factors structuring diatom assemblages, and performed separate analyses on different diatom guilds. Our results showed that the diatom assemblages were mainly structured by environmental factors. However, unique spatial and biological gradients, specific to different guilds and unrelated to each other, were also evident. We conclude that biological predictors, in combination with environmental and spatial variables, can reveal a more complete picture of the local vs. regional control of species assemblages in lotic environments. Biotic factors should therefore not be overlooked in applied research since they can capture additional local control and therefore increase accuracy and performance of predictive models. The inclusion of biotic predictors did, however, not significantly influence the unique fraction explained by spatial factors, which suggests low bias in previous assessments of unique regional control of stream assemblages.
End of the Century pCO2 Levels Do Not Impact Calcification in Mediterranean Cold-Water Corals

Ocean acidification caused by anthropogenic uptake of CO2 is perceived to be a major threat to calcifying organisms. Cold-water corals were thought to be strongly affected by a decrease in ocean pH due to their abundance in deep and cold waters which, in contrast to tropical coral reef waters, will soon become corrosive to calcium carbonate. Calcification rates of two Mediterranean cold-water coral species, Lophelia pertusa and Madrepora oculata, were measured under variable partial pressure of CO2 (pCO2) that ranged between 380 µatm for present-day conditions and 930 µatm for the end of the century. The present study addressed both short- and long-term responses by repeatedly determining calcification rates on the same specimens over a period of 9 months. Besides studying the direct, short-term response to elevated pCO2 levels, the study aimed to elucidate the potential for acclimation of calcification of cold-water corals to ocean acidification. Net calcification of both species was unaffected by the levels of pCO2 investigated and revealed no short-term shock and, therefore, no long-term acclimation in calcification to changes in the carbonate chemistry. There was an effect of time during repeated experiments with increasing net calcification rates for both species, however, as this pattern was found in all treatments, there is no indication that acclimation of calcification to ocean acidification occurred. The use of controls (initial and ambient net calcification rates) indicated that this increase was not caused by acclimation in calcification response to higher pCO2. An extrapolation of these data suggests that calcification of these two cold-water corals will not be affected by the pCO2 level projected at the end of the century.
Regional Homogeneity of Intrinsic Brain Activity in Happy and Unhappy Individuals

Background Why are some people happier than others? This question has intrigued many researchers. However, limited work has addressed this question within a neuroscientific framework. Methods The present study investigated the neural correlates of trait happiness using the resting-state functional magnetic resonance imaging (rs-fMRI) approach. Specifically, regional homogeneity (ReHo) was examined on two groups of young adults: happy and unhappy individuals (N = 25 per group). Results Decreased ReHo in unhappy relative to happy individuals was observed within prefrontal cortex, medial temporal lobe, superior temporal lobe, and retrosplenial cortex. In contrast, increased ReHo in unhappy relative to happy individuals was observed within the dorsolateral prefrontal cortex, middle cingulate gyrus, putamen, and thalamus. In addition, the ReHo within the left thalamus was negatively correlated with Chinese Happiness Inventory (CHI) score within the happy group. Limitations As an exploratory study, we examined how general trait happiness is reflected in the regional homogeneity of intrinsic brain activity in a relatively small sample. Examining other types of happiness in a larger sample using a multitude of intrinsic brain activity indices are warranted for future work. Conclusions The local synchronization of BOLD signal is altered in unhappy individuals. The regions implicated in this alteration partly overlapped with previously identified default mode network, emotional circuitry, and rewarding system, suggesting that these systems may be involved in happiness.
MIAEC: Missing Data Imputation Based on the Evidence Chain

Missing or incorrect data caused by improper operations can seriously compromise security investigation. Missing data can not only damage the integrity of the information but also lead to the deviation of the data mining and analysis. Therefore, it is necessary to implement the imputation of missing value in the phase of data preprocessing to reduce the possibility of data missing as a result of human error and operations. The performances of existing imputation approaches of missing value cannot satisfy the analysis requirements due to its low accuracy and poor stability, especially the rapid decreasing imputation accuracy with the increasing rate of missing data. In this paper, we propose a novel missing value imputation algorithm based on the evidence chain (MIAEC), which first mines all relevant evidence of missing values in each data tuple and then combines this relevant evidence to build the evidence chain for further estimation of missing values. To extend MIAEC for large-scale data processing, we apply the map-reduce programming model to realize the distribution and parallelization of MIAEC. Experimental results show that the proposed approach can provide higher imputation accuracy compared with the missing data imputation algorithm based on naive Bayes, the mode imputation algorithm, and the proposed missing data imputation algorithm based on K-nearest neighbor. MIAEC has higher imputation accuracy and its imputation accuracy is also assured with the increasing rate of missing value or the position change of missing value. MIAEC is also proved to be suitable for the distributed computing platform and can achieve an ideal speedup ratio.
Effect of hydrogen adsorption on the magnetic properties of a surface nanocluster of iron

The effect of hydrogen adsorption on the magnetic properties of an Fe$_3$ cluster immersed in a Cu(111) surface has been calculated using densifty functional theory and the results used to parametrize an Alexander-Anderson model which takes into account the interaction of d-electrons with itinerant electrons. A number of adatom configurations containing one to seven H-atoms were analyzed. The sequential addition of hydrogen atoms is found to monotonically reduce the total magnetic moment of the cluster with the effect being strongest when the H-atoms sit at low coordinated sites. Decomposition of the charge density indicates a transfer of 0.4 electrons to each of the H-atoms from both the Fe-atoms and from the copper substrate, irrespective of adsorption site and coverage. The magnetic moment of only the nearest neighbor Fe-atoms is reduced and mainly due to increased population of minority spin d-states. This can be modeled by increased indirect coupling of d-states via the conduction s-band in the Alexander-Anderson model.
Semantic Size of Abstract Concepts: It Gets Emotional When You Can’t See It

Size is an important visuo-spatial characteristic of the physical world. In language processing, previous research has demonstrated a processing advantage for words denoting semantically “big” (e.g., jungle) versus “small” (e.g., needle) concrete objects. We investigated whether semantic size plays a role in the recognition of words expressing abstract concepts (e.g., truth). Semantically “big” and “small” concrete and abstract words were presented in a lexical decision task. Responses to “big” words, regardless of their concreteness, were faster than those to “small” words. Critically, we explored the relationship between semantic size and affective characteristics of words as well as their influence on lexical access. Although a word’s semantic size was correlated with its emotional arousal, the temporal locus of arousal effects may depend on the level of concreteness. That is, arousal seemed to have an earlier (lexical) effect on abstract words, but a later (post-lexical) effect on concrete words. Our findings provide novel insights into the semantic representations of size in abstract concepts and highlight that affective attributes of words may not always index lexical access.
Primary care experiences of women with a history of childhood trauma and chronic disease: Trauma-informed care approach.

OBJECTIVE To understand the primary care experiences of women who have a history of childhood trauma and chronic disease. DESIGN Qualitative study using in-depth interviews with directed content analysis. SETTING Family health team in Kingston, Ont. PARTICIPANTS Twenty-six women. METHODS Letters of invitation were sent to eligible participants followed by a telephone survey. Women with an adverse childhood experience (ACE) score of 4 or higher and with 2 or more chronic conditions were invited to participate in a one-on-one interview. MAIN FINDINGS Participants were frequent users of health care services. Most had not been asked about ACEs by their family physicians. Most participants believed that their history of ACEs was important to their health and that providers should ask about childhood experiences. When participants discussed their primary care experiences, the following 6 common themes evolved: the importance of continuity of care; challenges with family medicine residents; provider awareness of abuse history; distress due to triggering events; characteristics of clinic staff and space; and engagement in care plans and choice. These discussions revealed that participants' primary care experiences were not always informed by the principles of trauma-informed care. CONCLUSION Understanding the effect of ACEs on women's health is important. Incorporating a trauma-informed approach can be beneficial and enhance the experience of patients. Physicians should learn to ask patients about their childhood experiences, as it is important to their health care.
Investigation on material removal rate, surface and subsurface characteristics in wire electro discharge machining of Ti50Ni50-xCux shape memory alloy

TiNiCu shape memory alloys have superior properties as compared with NITINOL due to their greater ductility, reduced hysteresis temperature range, and quick actuation response. The present article investigates the surface and subsurface modifications occurring due to wire electro discharge machining of Ti50Ni50-xCux shape memory alloy. The machining experiments were performed considering the pulse on time, pulse off time, and servo voltage as the process parameters. The influence of these parameters was studied on the material removal rate, surface roughness, recast layer thickness, microhardness, and phase changes in the machined surface. Longer pulse on time causes greater discharge energy, hence leading to higher material removal rate, surface roughness, and recast layer thickness. The machined surface hardness increased up to 900 Hv, which is about 59% increase with respect to the base material for longer pulse on time due to the recast layer thickness and the formation of oxides. A phase change on the machined surface was observed to cause the shape recoverability of the alloy. The microstructure, composition through EDAX, and the phase changes of the machined surface are also discussed in the article.
Avibactam Restores the Susceptibility of Clinical Isolates of Stenotrophomonas maltophilia to Aztreonam

ABSTRACT Stenotrophomonas maltophilia is an emerging opportunistic pathogen, classified by the World Health Organization as one of the leading multidrug-resistant organisms in hospital settings. The need to discover novel compounds and/or combination therapies for S. maltophilia is urgent. We demonstrate the in vitro efficacy of aztreonam-avibactam (ATM-AVI) against S. maltophilia and kinetically characterize the inhibition of the L2 β-lactamase by avibactam. ATM-AVI overcomes aztreonam resistance in selected clinical strains of S. maltophilia, addressing an unmet medical need.
Type 2 Gaucher disease in an infant despite a normal maternal glucocerebrosidase gene

Gaucher disease (GD) is a recessively inherited autosomal lysosomal storage disease, the most severe of which is type 2, an acute neuronopathic form. We report an affected infant who inherited one mutant allele, Arg257Gln (c.887G>A; p.Arg296Gln) from his father, while the second, Gly202Arg (c.721G>A; p.Gly241Arg) arose by either maternal germline mosaicism or as a de novo mutation. This is the first time mutation Gly202Arg has been reported to be inherited non‐traditionally. This report is part of a growing literature suggesting that GD can be inherited via germline or de novo mutations, and emphasizes that it is critical for clinicians to consider such inheritance when making diagnostic decisions or providing genetic counseling.
Unraveling the Relationships between Ecosystems and Human Wellbeing in Spain

National ecosystem assessments provide evidence on the status and trends of biodiversity, ecosystem conditions, and the delivery of ecosystem services to society. I this study, we analyze the complex relationships established between ecosystems and human systems in Spain through the combination of Driver-Pressure-State-Impact-Response framework and structural equation models. Firstly, to operationalize the framework, we selected 53 national scale indicators that provide accurate, long-term information on each of the components. Secondly, structural equation models were performed to understand the relationships among the components of the framework. Trend indicators have shown an overall progressive biodiversity loss, trade-offs between provisioning and cultural services associated with urban areas vs. regulating and cultural services associated with rural areas, a decoupling effect between material and non-material dimensions of human wellbeing, a rapid growing trend of conservation responses in recent years and a constant growing linear trend of direct or indirect drivers of change. Results also show that all the components analyzed in the model are strongly related. On one hand, the model shows that biodiversity erosion negatively affect the supply of regulating services, while it is positively related with the increase of provisioning service delivery. On the other hand, the most important relationship found in the model is the effect of pressures on biodiversity loss, indicating that response options for conserving nature cannot counteract the effect of the drivers of change. These results suggest that there is an insufficient institutional response to address the underlying causes (indirect drivers of change) of biodiversity loos in Spain. We conclude that more structural changes are required in the Spanish institutional framework to reach 2020 biodiversity conservation international targets.
Technical Note: Responses of Vertical Sections of Wood Samples to Cyclical Relative Humidity Changes

This study investigated moisture responses of the surface, middle, and central portion in the thickness direction of wood samples to cyclic RH changes. Phase lag and amplitude for these sections were determined quantitatively by Fourier analysis. These data were used to suggest a mechanism for the unexpected phenomenon that moisture changes are slower than dimensional changes found in previous work.
A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses

Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of synapses and it is therefore an excellent tool for multi-scale simulations.
Colour stability of thermally modified hardwood.

Thermal wood modification has been intensively studied in the recent decades because of the possibility to produce wood with improved biodurability and dimensional stability without use of harmful chemicals. Beside altered physical characteristics, wood colour is changed to lighter or darker brown as a result of thermal treatment. Growth of interest in thermal wood treatment has stimulated numerous researches concerned with discoloration of thermally modified wood which is subjected to light exposure. The objective of this study was to evaluate the colour stability of thermally modified hardwood during storage in the dark where wood discolouration is not photoinduced but rather a result of oxidative ageing. Three thermally modified hardwood species – aspen (Populus tremula L.), alder (Alnus incana Moench), birch (Betula pendula Roth.), where investigated. Wood discoloration was monitored by spectrophotometrical measurements of reflectance spectra and chromaticity parameter calculations using CIELAB colour system where L* is the lightness, and a* and b* are the chromatic coordinates. The colour stability of thermally modified wood as well as of untreated wood of the same species was examined by means of assessment of the colour parameter changes (ΔL*, Δa*, Δb*, ΔEab). All wood specimens under study discoloured during the experiment, but the colour change did not exceed two units that is common and accepted for wood products. Untreated and thermally modified wood showed different trends of discoloration during storage in the dark. The final colour changes that were fixed at the end of the experiment were greater for the thermally treated wood.
TRANSPORT IN MICROCHANNELS - A CRITICAL REVIEW

The tremendous enhancement in heat transport obtained by employing microchannels has provided an e ective alternative to conventional methods of heat dissipation, especially in applications related to cooling of microelectronics. A number of theoretical and experimental studies have been reported on the fluid flow and heat transfer mechanisms in mini and microchannels as well as microtubes. Anomalies and deviations from the behavior expected for conventional channels, both in terms of the frictional and heat transfer characteristics have been noticed in microchannels under specific flow conditions and flow regimes. The present work compiles and analyzes the results of the important investigations on fluid flow and heat transfer in microchannels and microtubes.
Early PTSD Symptom Trajectories: Persistence, Recovery, and Response to Treatment: Results from the Jerusalem Trauma Outreach and Prevention Study (J-TOPS)

Context Uncovering heterogeneities in the progression of early PTSD symptoms can improve our understanding of the disorder's pathogenesis and prophylaxis. Objectives To describe discrete symptom trajectories and examine their relevance for preventive interventions. Design Latent Growth Mixture Modeling (LGMM) of data from a randomized controlled study of early treatment. LGMM identifies latent longitudinal trajectories by exploring discrete mixture distributions underlying observable data. Setting Hadassah Hospital unselectively receives trauma survivors from Jerusalem and vicinity. Participants Adult survivors of potentially traumatic events consecutively admitted to the hospital's emergency department (ED) were assessed ten days and one-, five-, nine- and fifteen months after ED admission. Participants with data at ten days and at least two additional assessments (n = 957) were included; 125 received cognitive behavioral therapy (CBT) between one and nine months. Approach We used LGMM to identify latent parameters of symptom progression and tested the effect of CBT on these parameters. CBT consisted of 12 weekly sessions of either cognitive therapy (n = 41) or prolonged exposure (PE, n = 49), starting 29.8±5.7 days after ED admission, or delayed PE (n = 35) starting at 151.8±42.4 days. CBT effectively reduced PTSD symptoms in the entire sample. Main Outcome Measure Latent trajectories of PTSD symptoms; effects of CBT on these trajectories. Results Three trajectories were identified: Rapid Remitting (rapid decrease in symptoms from 1- to 5-months; 56% of the sample), Slow Remitting (progressive decrease in symptoms over 15 months; 27%) and Non-Remitting (persistently elevated symptoms; 17%). CBT accelerated the recovery of the Slow Remitting class but did not affect the other classes. Conclusions The early course of PTSD symptoms is characterized by distinct and diverging response patterns that are centrally relevant to understanding the disorder and preventing its occurrence. Studies of the pathogenesis of PTSD may benefit from using clustered symptom trajectories as their dependent variables.