Miracle-dz/UniFAR-FTUs huggingface dataset:
Lucid dream induction by visual and tactile stimulation: An exploratory sleep laboratory study

In a lucid dream the dreamer is aware of the dream state. Previous research has shown that external stimuli (e.g. flashing lights) presented to a person during REM sleep can trigger lucidity. To further examine the possibility of lucid dream induction by external stimulation, visual and tactile stimuli were investigated in an exploratory sleep laboratory study. In the first experiment 10 participants spent two none-consecutive nights in a sleep laboratory. In the first night a visual stimulus (flashing lights) was presented during REM sleep and in the second night tactile stimulation (vibration) at the index finger was utilized, again in REM sleep. In the second experiment 14 participants spent a single night in the sleep laboratory and tactile stimulation (vibration) either at the wrist or at the ankle was applied during REM sleep. The participants were instructed to perform two consecutive left-to-right eye movements to indicate lucidity in the dream. Light stimulation yielded one signal-verified lucid dream out of 18 application trials (5.6 %) whereas tactile stimulation at the index finger did not provoke any lucid dream at all (21 applications). Tactile stimulation at the wrist or ankle resulted in two signal-verified lucid dreams out of 27 trials (7.4 %). Stimuli were incorporated in 38.9 %, 42.9 %, and 55.6 % of stimulations, respectively. The results suggest that lucid dreams might be triggered by visual or tactile stimulation. However, the frequencies of the induced lucid dreams are – in comparison to earlier studies – quite low. Furthermore, for tactile stimulation it seems important at which part of the body the stimulation is applied. In general, the intensity of stimulation needs to be adjusted because stimulation often led to an awakening of participants. Thus it seems important for future studies to focus on factors like waking thresholds and preparation of participants in order to minimize awakenings and to maximize lucid dream induction.
A new name, and notes on extra-floral nectaries, in Lagunaria (Malvaceae, Malvoideae)

The Australian taxon Lagunaria patersonius subsp. bracteata is raised to specific rank as L. queenslandica, based upon morphological and ecological dissimilarities between it and the autonymic taxon, L. patersonius subsp. patersonius. The latter taxon occurs on the southwest Pacific Ocean islands, Lord Howe and Norfolk Islands. Extra-floral nectaries are reported in Lagunaria, apparently for the first time, and contrasted with those occurring in species of Hibiscus sections Bombicella and Furcaria.
Bacterial shifts associated with coral-macroalgal competition in the Caribbean Sea

Present-day coral reefs are impacted by frequent disturbance and increasing global stressors, which provide an environment that supports the growth of alternative dominants, such as macroalgae, sponges, and tunicates, rather than stony corals. Competitively damaging inter - actions arise between macroalgae and reef-building corals that can involve chemical, physical, and microbial mechanisms. Using 16S rRNA denaturing gradient gel electrophoresis (DGGE), amplicon sequencing, and multivariate analyses, we examined coral- and algae-associated bac - terial assemblages along interaction gradients between the common Caribbean stony corals Montastraea faveolata and Porites astreoides and the benthic macroalgae Halimeda opuntia and Dictyota menstrualis. Benthic surveys were conducted in 3 Caribbean locations, and interactions were sampled for bacterial analyses. Both macroalgae were capable of inducing shifts in coral- associated bacteria to an assemblage that more closely resembled macroalgal-associated bacteria. Overall, M. faveolata-associated bacteria were more significantly affected by macroalgal competi- tors than were P. astreoides-associated bacteria at all sites. Bacteria associated with M. faveolata corals changed during > 83% of interactions, even when samples were taken 5 cm away from competing macroalgae. Detectable shifts in coral-associated bacteria at all sampling sites suggest that macroalgae play a large role in coral holobiont health. The degree to which coral species maintain stable microbial assemblages in the face of environmental fluctuations and competitive stress may indicate specific species and coral reefs that have the capacity to resist perturbations and those that may need additional protection in the future.
‘You Can’t Win’: The Non-Profit Double-Bind and Experiences of Organisational Contradictions in the Non-Profit and Voluntary Sector

There is growing evidence that in the UK demands for non-profit and voluntary sector organisations to comply with funders’ target driven priorities are often in tension with organisations’ social goals. The implications of this for employees are not yet sufficiently understood. The present article builds on Bateson et al.’s theory of double-bind to develop a socially contextualised model to understand employees’ experiences of workplace contradictions in the sector. Drawing from data provided by 49 individuals working in three case study organisations, our conceptualisation of a ‘non-profit double-bind’ provides a new and novel way of understanding how social meta-communicative processes serve to embed or reframe contradictions within intense employment relationships.
Predation has no competition: factors influencing space and resource use by echinoids in deep‐sea coral habitats, as evidenced by continuous video transects

Predation and competition are highly influential factors determining space use in foraging animals, and ultimately contribute to the spatial heterogeneity observed within habitats. Here we investigated the influence of competition and predation on space and resource use via continuous video transect observations – a tool that has not previously been employed for this purpose. This study therefore also evaluates video data as a pragmatic tool to study community interactions in the deep sea. Observations were compiled from 15 video transects spanning five submarine canyons in the Bay of Biscay, France. Substrate choice, positioning on the coral, echinoid aggregate size, and the presence/absence of predators (e.g. fish and decapods) as well as competitors (both inter- and intra-specific) were recorded. Two dominant co-existing echinoid taxa, echinothurids and Cidaris cidaris (3188 total observations), were observed in the study. For the echinothurids, no significant trends were detected in the inter- and intra-specific competition data. For Cidaris cidaris, significant shifts in substrate use were correlated to the presence of inter-specific competitors (echinothurids), whereby an increase in dead coral substrate usage was observed. Highly significant patterns were detected amongst echinoids near fish and decapod predators. A shift to the base of the coral infra-structure was correlated to the presence of fish, and fewer individuals were observed in the open areas of the reef and a greater number were found in the mid and top sections of the coral when in the presence of decapods. Aggregates formed irrespective of the presence of predators. Aggregations are likely to form for feeding and reproduction rather than for defensive purposes; and migration along the coral infra-structure may be a predator-driven behaviour as echinoids seek refuge from predators.
Impact of socioeconomic factors on nutritional diet in Vietnam from 2004 to 2014: new insights using compositional data analysis

This paper contributes to the analysis of the impact of socioeconomic factors, like food expenditure level and urbanization, on diet patterns in Vietnam, from 2004 to 2014. Contrary to the existing literature, we focus on the diet balance in terms of macronutrients consumption (protein, fat and carbohydrate) and we take into account the fact that the volumes of each macronutrient are not independent. In other words, we are interested in the shares of each macronutrient in the total calorie intake. We use the compositional data analysis (CODA) to describe the evolution of diet patterns over time, and to model the impact of household characteristics on the macronutrient shares vector. We compute food expenditure elasticities of macronutrient shares, and we compare them to classical elasticities for macronutrient volumes and total calorie intake. The compositional model highlights the important role of food expenditure, size of the household and dwelling region in the determination of diet choices. Our results are consistent with the rest of the literature, but they have the advantage to highlight the substitution effects between macronutrients in the context of nutrition transition.
Metabolic traits of westslope cutthroat trout, introduced rainbow trout and their hybrids in an ecotonal hybrid zone along an elevation gradient.

In the Upper Oldman River, Alberta, introduced non-native hatchery rainbow trout (Oncorhynchus mykiss) hybridize with native westslope cutthroat trout (O. clarkii), resulting in a hybrid swarm. Rainbow trout dominate at low elevations ( 1400 m), and hybrids are numerically dominant in the mid-elevation range. We hypothesized that metabolism of rainbow trout would exceed that of cutthroat trout, and that the elevation gradient in genetic makeup would be mirrored by a gradient in metabolic traits, with intermediate traits in the hybrid-dominated ecotone. Metabolic traits were measured and regressed against the genetic makeup of individuals and elevation. Rainbow trout had higher oxygen consumption rates (OCRs), higher white muscle lactate dehydrogenase (LDH), and citrate synthase (CS) activity, and higher plasma acetylcholinesterase (AchE) than cutthroat trout. Hybrids had intermediate OCRs and AchE, but LDH activity as high as rainbow trout. While hybrid zones are usually modelled as a balance between cross species mating and selection against hybrids, ecotonal hybrid zones, where hybrids proliferate in intermediate habitats and have traits that appear well suited to ecotonal conditions, have been proposed for some plants and animals, and may have important implications for resource management and conservation. © 2011 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 105, 56–72.
Comparison of intelligent systems, artificial neural networks and neural fuzzy model for prediction of gas hydrate formation rate

The main objective of this study was to present a novel approach for predication of gas hydrate formation rate based on the Intelligent Systems . Using a data set including about 470 data obtained from flow tests in a mini-loop apparatus, different predictive models were developed. From the results predicted by these models, it can be pointed out that the developed models can be used as powerful tools for prediction of gas hydrate formation rate with total errors of less than 4%.
A Multi-Dimensional Transform for Future Video Coding

In this paper, we propose a Multi-Dimensional Transform(MDT) technique for future video coding. Unlike traditional video codecs, H.264/AVC uses an integer 4×4 block transform. Using small block size coding, H.264/AVC obtains high temporal prediction efficiency, but it has limitation in utilizing spatial redundancy. The proposed MDT is a new method for additionally reducing spatial redundancies of image. Experimental results indicate MDT can provide better RD performance than the conventional H.264/AVC transform.
Food Selection for Diabetic Patients by using Image Classification

The Increase in number of diabetic patients in day to day life due to lack of proper diet tends us to sought out a solution for it. Food Image Classification is a technique where a classifier assigns to the image one class out of a pre-defined set of food classes, a set of characteristics representing the visual content of the image is extracted and quantified. We use Bag-of-Features model for automatic selection of food images, BoF methods are based on the order less collections of quantized local image descriptors, and they discard spatial information and are conceptually and computationally simpler than many alternative methods. Image classification undergoes key point extraction, builds a visual dictionary by using k-means clustering and then finally classifies the food image into various classifiers.
Expression of Human Nerve Growth Factor β and Bacterial Protein Disulfide Isomerase ( DsbA ) as a Fusion Protein ( DsbA : : hNGF ) Significantly Enhances Periplasmic Production of hNGF β in Escherichia coli

Production of human nerve growth factor β, a neurotrophin required for the development and survival of the nerve cells, in Escherichia coli forms insoluble aggregates because it exhibits complex three disulfide bonds in its structure. Also periplasmic expression of it using a usual bacterial signal peptide often has multiple difficulties. In this study a useful method was used to improve periplasmic expression of hNGFβ. To promoting NGF production and translocation through the inner membrane, the pET39b plasmid that permits DsbA expression as a fusion protein with hNGF in comparison to pET22b plasmid with a routine signal peptide (pelB) were used. Studies carried out in the present work indicated high expression and periplasmic translocation of rhNGF when pET39b-DsbA::hNGF plasmid (over expression of DsbA) was used. In contrast, when pelB signal sequence was used for periplasmic expression, no rhNGF production was obtained. These results indicate the efficiency of DsbA over expression to increase the total yield and periplasmic expression of the recombinant proteins with multiple disulfide bonds.
Effect of the Aqueous Extracts of Grewiavenusta Leaves on Poloxamer 407-Induced Hyperlipidemic Rats

Hyperlipidemia is considered to be one of the greatest risk contributing to the prevalence and severity of cardiovascular diseases. The present study was taken to evaluate the effect of the aqueous leaf extract of Grewiavenusta on poloxamer 407-induced hyperlipidemic rats. The poloxamer 407 (P407) was administered using a single dose of 500mg/kg body weight which induced hyperlipidemia after 24 hours.Oral administration of extract, at dose of 200mg/kg body weight in rats, inhibited serum total cholesterol, triacyglycerides, low density lipoprotein, very low density lipoprotein and increased high density lipoprotein levels as compared to the Group IV treated with the standard drug (atorvastatin). The Results were expressed as mean±SEM by the statistical analysis-SPSS application 20.0 i.e one way ANOVA. The mean±SEM of measured hyperlipidemia induced by poloxamer 407 as 198.0±24.2 mg/dl for TAG, 247.4±30.3 mg/dl for TC. The plant aqueous extract decrease total cholesterol by 44.75% (p<0.05), triacyglyceride by 30.96% (p<0.05), VLDL by 31.06% (p<0.05), LDLc by 50.61% (p<0.05). On the other hand atorvastatin decreased total cholesterol by 33.99% (p<0.05), triacyglyceride by 35.15% (p<0.05), VLDL by 35.10% (p<0.05), LDLc by 37.42% (p<0.05). Both the plant aqueous extract and the standard drug increase the levels of HDLc significantly.
Localisation and policy synthesis for underwater swarming autonomous vehicles with probabilistic guarantees about safe exploration and reachability requirements

This project is concerned with the case of an autonomous underwater vehicle (AUV) submerging in deep ocean to locate and inspect underwater infrastructure, i.e. a pipeline. For this task, proper decision-making and positional accuracy are key, both for getting closer to infrastructure whilst keeping safe and for recording data more accurately. The underwater environment raises significant difficulties to these requirements, due to signal attenuation, multipath fading as well as the presence of extreme and unpredictable currents. To address the aforementioned challenges, we estimate that better localisation can be achieved if the receiver nodes (which in this case are also AUVs floating on the surface) stay in an equilateral triangle formation. On the other hand, to synthesise the appropriate policy that satisfies the requirements for safe exploration and reachability of the pipeline, we employ a reinforcement learning (RL) inspired control policy, that satisfies the required properties, which we express as linear temporal logic (LTL) formulae. The performance of our method is satisfactory and evaluated through several test case scenarios, where different parameters involved are taken into account.
Interpretability of a Service Robot: Enabling User Questions and Checkable Answers

Service robots are becoming more and more capable but at the same time they are opaque to their users. Once a robot starts executing a task it is hard to tell what it is doing or why. To make robots more transparent to their users we propose to expand the capabilities of robots to not only execute tasks but also answer questions about their experience. During execution, our CoBot robots record log files. We propose to use these files as a recording of the robot experience. Log files record the experience of the robot in term of its internals. To process information from the logs we define Log Primitives Operations (LPOs) that the robot can autonomously perform. Each LPO is defined in term of an operation and a set of filters. We frame the problem of understanding questions about robot past experiences, as grounding input sentences to LPOs. To do so, we introduce a probabilistic model to ground sentences to these primitives. We evaluate our approach on a corpus of 133 sentences showing that our method is able to learn the meaning of users’ questions. Finally we introduce the concept of checkable answers to have the robot provide answers that better explain the computation performed to achieve the result reported.
TRAJECTORY PREDICTION UNCERTAINTY MODELING FOR CONTINUOUS DESCENT APPROACHES

One proposed approach to enabling Trajectory Based Operations, and Continuous Descent Approaches in congested airspace, is to use decision support technology with real-time trajectory prediction. A method for defining and quantifying models of real-time uncertainty estimation for use with such technology has been developed previously. A demonstration of this methodology for adding real-time estimation of altitude error to trajectory predictions in the Center/TRACON Automation System is provided. The methodology uses analysis of actual and predicted CDA trajectories obtained from Air Route Traffic Control Center operational data and from CTAS’s trajectory synthesis process, respectively. Altitude error was aggregated over the flight sample through the application of statistical analysis at discrete altitude increments along the predicted descent trajectory. The evolution of altitude error mean and standard deviation was modeled in segments, each represented by an equation that best fit the aggregated data. Three segments describe the evolution of the standard deviation and four the evolution of the mean error. To illustrate the method an initial demonstration was performed with a limited data set. Given a larger set of data the final model could be generally applicable in generating an uncertainty model to support decision support technology in the performance of new arrival procedures such as CDA in congested airspace.
Range imager performance comparison in homodyne and heterodyne operating modes

Range imaging cameras measure depth simultaneously for every pixel in a given field of view. In most implementations the basic operating principles are the same. A scene is illuminated with an intensity modulated light source and the reflected signal is sampled using a gain-modulated imager. Previously we presented a unique heterodyne range imaging system that employed a bulky and power hungry image intensifier as the high speed gain-modulation mechanism. In this paper we present a new range imager using an internally modulated image sensor that is designed to operate in heterodyne mode, but can also operate in homodyne mode. We discuss homodyne and heterodyne range imaging, and the merits of the various types of hardware used to implement these systems. Following this we describe in detail the hardware and firmware components of our new ranger. We experimentally compare the two operating modes and demonstrate that heterodyne operation is less sensitive to some of the limitations suffered in homodyne mode, resulting in better linearity and ranging precision characteristics. We conclude by showing various qualitative examples that demonstrate the system's three-dimensional measurement performance.
Apparent digestibility of diets with combinations of soybean hulls and coastcross (Cynodon sp.) hay offered to ram lambs

Soybean hulls (SH) are an alternative fiber source that may be used to maintain neutral detergent fiber (NDF) concentration while increasing the energy concentration of ruminant diets. The objective of this experiment was to determine the effects of replacing coastcross (Cynodon sp.) hay NDF by SH NDF on the apparent digestibility of nutrients and nitrogen balance of Santa Ines ram lambs. Twenty-four animals (42.5 ± 3.6 kg of body weight and six months old) were placed in metabolism crates and assigned in a randomized complete block design defined by body weight (BW). Experimental diets provided a similar concentration of NDF (52%) and crude protein (15%). Hay NDF from a 70% roughage-based diet was replaced with SH NDF by 33%, 67%, and 100%, resulting in 0, 25, 52, and 77% of SH in the dietary dry matter (DM), respectively. There was a linear increase (p 0.05) on water intake when SH replaced hay. The SH can replace forage and may be included up to 77% in the dietary DM of ram lambs with satisfactory values of nutrient digestibilities.
Stochastic Block Partition Graph Challenge-draft -

A challenging and important objective for analyzing real-world graphs is to achieve scalable performance on large graphs. Competitive benchmarks and challenges have proven to be an effective means to advance state-of-the-art performance and foster community collaboration. Past graph challenges such as Graph500 address problems such as search and path-finding with subquadratic complexity. However, some analyses on graphs with real-world applications are NP-hard. Graph partition is a well-known example. Although graph partition, as a combinatorial problem, is NP-hard, existing relaxation methods provide good approximate solutions with subquadratic complexity and hence can scale to large graphs. This paper describes a graph partition challenge with a baseline partition algorithm that has such desired properties. Furthermore, the algorithm employs rigorous Bayesian inferential methods based on a statistical model that captures characteristics of the real-world graphs. This strong foundation enables the algorithm to address limitations of well-known graph partition approaches such as modularity maximization. This paper describes various aspects of the challenge including: (1) the data sets and graph generator, (2) the baseline partition algorithm with pseudocode, (3) an argument for the correctness of parallelizing the Bayesian updates, (4) different parallel computation strategies such as node-based parallelism and matrix-based parallelism, (5) evaluation metrics for both partition correctness and computational requirements, (6) preliminary timing of a Python-based demonstration code and the open source C++ code, and (7) considerations for partitioning the graph in a streaming fashion. Data sets and source code for the algorithm as well as metrics, with detailed documentation are available at GraphChallenge.org.