Sound symbolic associations in Spanish emotional words: affective dimensions and discrete emotions.

Sound symbolism refers to non-arbitrary associations between word forms and meaning, such as those observed for some properties of sounds and size or shape. Recent evidence suggests that these connections extend to emotional concepts. Here we investigated two types of non-arbitrary relationships. Study 1 examined whether iconicity scores (i.e. resemblance-based mapping between aspects of a word's form and its meaning) for words can be predicted from ratings in the affective dimensions of valence and arousal and/or the discrete emotions of happiness, anger, fear, disgust and sadness. Words denoting negative concepts were more likely to have more iconic word forms. Study 2 explored whether statistical regularities in single phonemes (i.e. systematicity) predicted ratings in affective dimensions and/or discrete emotions. Voiceless (/p/, /t/) and voiced plosives (/b/, /d/, /g/) were related to high arousing words, whereas high arousing negative words tended to include fricatives (/s/, /z/). Hissing consonants were also more likely to occur in words denoting all negative discrete emotions. Additionally, words conveying certain discrete emotions included specific phonemes. Overall, our data suggest that emotional features might explain variations in iconicity and provide new insight about phonemic patterns showing sound symbolic associations with the affective properties of words.

Cellular Exchange Imaging (CEXI): Evaluation of a diffusion model including water exchange in cells using numerical phantoms of permeable spheres.

PURPOSE: Biophysical models of diffusion MRI have been developed to characterize microstructure in various tissues, but existing models are not suitable for tissue composed of permeable spherical cells. In this study we introduce Cellular Exchange Imaging (CEXI), a model tailored for permeable spherical cells, and compares its performance to a related Ball & Sphere (BS) model that neglects permeability. METHODS: We generated DW-MRI signals using Monte-Carlo simulations with a PGSE sequence in numerical substrates made of spherical cells and their extracellular space for a range of membrane permeability. From these signals, the properties of the substrates were inferred using both BS and CEXI models. RESULTS: CEXI outperformed the impermeable model by providing more stable estimates cell size and intracellular volume fraction that were diffusion time-independent. Notably, CEXI accurately estimated the exchange time for low to moderate permeability levels previously reported in other studies ( κ < 25 µ m / s $$ \kappa <25\kern0.3em \mu \mathrm{m}/\mathrm{s} $$ ). However, in highly permeable substrates ( κ = 50 µ m / s $$ \kappa =50\kern0.3em \mu \mathrm{m}/\mathrm{s} $$ ), the estimated parameters were less stable, particularly the diffusion coefficients. CONCLUSION: This study highlights the importance of modeling the exchange time to accurately quantify microstructure properties in permeable cellular substrates. Future studies should evaluate CEXI in clinical applications such as lymph nodes, investigate exchange time as a potential biomarker of tumor severity, and develop more appropriate tissue models that account for anisotropic diffusion and highly permeable membranes.

Your words went straight to my heart: the role of emotional prototypicality in the recognition of emotion-label words.

Emotional words differ in how they acquire their emotional charge. There is a relevant distinction between emotion-label words (those that directly name an emotion, e.g., "joy" or "sadness") and emotion-laden words (those that do not name an emotion, but can provoke it, e.g., "party" or "death"). In this work, we focused on emotion-label words. These words vary in their emotional prototypicality, which indicates the extent to which the word refers to an emotion. We conducted two lexical decision experiments to examine the role played by emotional prototypicality in the recognition of emotion-label words. The results showed that emotional prototypicality has a facilitative effect in word recognition. Emotional prototypicality would ease conceptual access, thus facilitating the retrieval of emotional content during word recognition. In addition to the theoretical implications, the evidence gathered in this study also highlights the need to consider emotional prototypicality in the selection of emotion-label words in future studies.

Emoji-SP, the Spanish emoji database: Visual complexity, familiarity, frequency of use, clarity, and emotional valence and arousal norms for 1031 emojis.

This article presents subjective norms for 1031 emojis in six dimensions: visual complexity, familiarity, frequency of use, clarity, emotional valence, and emotional arousal. This is the largest normative study conducted so far that relies on subjective ratings. Unlike the few existing normative studies, which mainly comprise face emojis, here we present a wide range of emoji categories. We also examine the correlations between the dimensions assessed. Our results show that, in terms of their affective properties, emojis are analogous to other stimuli, such as words, showing the expected U-shaped relationship between valence and arousal. The relationship between affective properties and other dimensions (e.g., between valence and familiarity) is also similar to the relationship observed in words, in the sense that positively valenced emojis are more familiar than negative ones. These findings suggest that emojis are suitable stimuli for studying affective processing. Emoji-SP will be highly valuable for researchers of various fields interested in emojis, including computer science, communication, linguistics, and psychology. The full set of norms is available at: https://osf.io/dtfjv/ .

I want it small or, rather, give me a bunch: the role of evaluative morphology on the assessment of the emotional properties of words.

ABSTRACTEvaluative markers of diminution and augmentation typically express quantity or intensity. Prior evidence suggests that they also convey emotions, although it remains unexplored as to whether this function is mediated by their role in expressing quantification/intensification. Here we investigated the effects of evaluative suffixes on the assessment of word affective properties by asking participants (N = 300) to score valence and arousal features for augmentatives, diminutives and base words with negative, positive or neutral valence. Diminutives and, to a lesser extent, augmentatives were assessed more positively than base forms in negative words and more negatively than bases in positive words. The capacity of diminution to express attenuated emotions is in line with its function in conveying quantity. By contrast, valence effects for augmentatives suggests a role in expressing pejoration and amelioration that is not mediated by quantification. With regard to arousal, negative, neutral and positive augmentatives showed higher scores than base words, which, in addition, were also rated higher than diminutives. These incremental effects suggest that suffixes which convey larger quantity are also associated with increased arousal. Thus, with the exception of valence effects in augmentatives, it seems that evaluative suffixes encode both valence and arousal through quantification.

High Performance Computing PP-Distance Algorithms to Generate X-ray Spectra from 3D Models.

X-ray crystallography is a powerful method that has significantly contributed to our understanding of the biological function of proteins and other molecules. This method relies on the production of crystals that, however, are usually a bottleneck in the process. For some molecules, no crystallization has been achieved or insufficient crystals were obtained. Some other systems do not crystallize at all, such as nanoparticles which, because of their dimensions, cannot be treated by the usual crystallographic methods. To solve this, whole pair distribution function has been proposed to bridge the gap between Bragg and Debye scattering theories. To execute a fitting, the spectra of several different constructs, composed of millions of particles each, should be computed using a particle-pair or particle-particle (pp) distance algorithm. Using this computation as a test bench for current field-programmable gate array (FPGA) technology, we evaluate how the parallel computation capability of FPGAs can be exploited to reduce the computation time. We present two different solutions to the problem using two state-of-the-art FPGA technologies. In the first one, the main C program uses OmpSs (a high-level programming model developed at the Barcelona Supercomputing Center, that enables task offload to different high-performance computing devices) for task invocation, and kernels are built with OpenCL using reduced data sizes to save transmission time. The second approach uses task and data parallelism to operate on data locally and update data globally in a decoupled task. Benchmarks have been evaluated over an Intel D5005 Programmable Acceleration Card, computing a model of 2 million particles in 81.57 s - 24.5 billion atom pairs per second (bapps)- and over a ZU102 in 115.31 s. In our last test, over an up-to-date Alveo U200 board, the computation lasted for 34.68 s (57.67 bapps). In this study, we analyze the results in relation to the classic terms of speed-up and efficiency and give hints for future improvements focused on reducing the global job time.

SUBTLEX-CAT: Subtitle word frequencies and contextual diversity for Catalan.

SUBTLEX-CAT is a word frequency and contextual diversity database for Catalan, obtained from a 278-million-word corpus based on subtitles supplied from broadcast Catalan television. Like all previous SUBTLEX corpora, it comprises subtitles from films and TV series. In addition, it includes a wider range of TV shows (e.g., news, documentaries, debates, and talk shows) than has been included in most previous databases. Frequency metrics were obtained for the whole corpus, on the one hand, and only for films and fiction TV series, on the other. Two lexical decision experiments revealed that the subtitle-based metrics outperformed the previously available frequency estimates, computed from either written texts or texts from the Internet. Furthermore, the metrics obtained from the whole corpus were better predictors than the ones obtained from films and fiction TV series alone. In both experiments, the best predictor of response times and accuracy was contextual diversity.

Is There an Orthographic Boost for Ambiguous Words During Their Processing?

The present study explores the issue of why ambiguous words are recognized faster than unambiguous ones during word recognition. To this end we contrasted two different hypotheses: the semantic feedback hypothesis (Hino and Lupker in J Exp Psychol Hum Percept Perform 22:1331-1356, 1996. https://doi.org/10.1037/0096-1523.22.6.1331 ), and the hypothesis proposed by Borowsky and Masson (J Exp Psychol Learn Mem Cognit 22:63-85, 1996. https://doi.org/10.1037/0278-7393.22.1.63 ). Although both hypotheses agree that ambiguous words benefit during recognition in that they engage more semantic activation, they disagree as to whether or not this greater semantic activation feeds back to the orthographic level, hence speeding up the orthographic coding of ambiguous words. Participants were presented with ambiguous and unambiguous words in two tasks, a lexical decision task (LDT) and a two-alternative forced-choice task (2AFC). We found differences between ambiguous and unambiguous words in both the LDT and the 2AFC tasks. These results suggest that the orthographic coding of ambiguous words is boosted during word processing. This finding lends support to the semantic feedback hypothesis.

Be aware of the rifle but do not forget the stench: differential effects of fear and disgust on lexical processing and memory.

The aim of this study was to investigate the role of discrete emotions in lexical processing and memory, focusing on disgust and fear. We compared neutral words to disgust-related words and fear-related words in three experiments. In Experiments 1 and 2, participants performed a lexical decision task (LDT), and in Experiment 3 an affective categorisation task. These tasks were followed by an unexpected memory task. The results of the LDT experiments showed slower reaction times for both types of negative words with respect to neutral words, plus a higher percentage of errors, this being more consistent for fear-related words (Experiments 1 and 2) than for disgust-related words (Experiment 2). Furthermore, only disgusting words exhibited a higher recall accuracy than neutral words in the memory task. Moreover, the advantage in memory for disgusting words disappeared when participants carried out an affective categorisation task during encoding (Experiment 3), suggesting that the superiority in memory for disgusting words observed in Experiments 1 and 2 could be due to greater elaborative processing. Taken together, these findings point to the relevance of discrete emotions in explaining the effects of the emotional content on lexical processing and memory.

Correction of Visual Perception Based on Neuro-Fuzzy Learning for the Humanoid Robot TEO.

New applications related to robotic manipulation or transportation tasks, with or without physical grasping, are continuously being developed. To perform these activities, the robot takes advantage of different kinds of perceptions. One of the key perceptions in robotics is vision. However, some problems related to image processing makes the application of visual information within robot control algorithms difficult. Camera-based systems have inherent errors that affect the quality and reliability of the information obtained. The need of correcting image distortion slows down image parameter computing, which decreases performance of control algorithms. In this paper, a new approach to correcting several sources of visual distortions on images in only one computing step is proposed. The goal of this system/algorithm is the computation of the tilt angle of an object transported by a robot, minimizing image inherent errors and increasing computing speed. After capturing the image, the computer system extracts the angle using a Fuzzy filter that corrects at the same time all possible distortions, obtaining the real angle in only one processing step. This filter has been developed by the means of Neuro-Fuzzy learning techniques, using datasets with information obtained from real experiments. In this way, the computing time has been decreased and the performance of the application has been improved. The resulting algorithm has been tried out experimentally in robot transportation tasks in the humanoid robot TEO (Task Environment Operator) from the University Carlos III of Madrid.

Experimental Robot Model Adjustments Based on Force-Torque Sensor Information.

The computational complexity of humanoid robot balance control is reduced through the application of simplified kinematics and dynamics models. However, these simplifications lead to the introduction of errors that add to other inherent electro-mechanic inaccuracies and affect the robotic system. Linear control systems deal with these inaccuracies if they operate around a specific working point but are less precise if they do not. This work presents a model improvement based on the Linear Inverted Pendulum Model (LIPM) to be applied in a non-linear control system. The aim is to minimize the control error and reduce robot oscillations for multiple working points. The new model, named the Dynamic LIPM (DLIPM), is used to plan the robot behavior with respect to changes in the balance status denoted by the zero moment point (ZMP). Thanks to the use of information from force-torque sensors, an experimental procedure has been applied to characterize the inaccuracies and introduce them into the new model. The experiments consist of balance perturbations similar to those of push-recovery trials, in which step-shaped ZMP variations are produced. The results show that the responses of the robot with respect to balance perturbations are more precise and the mechanical oscillations are reduced without comprising robot dynamics.

EmoFinder: The meeting point for Spanish emotional words.

We present here emoFinder ( http://usc.es/pcc/emofinder ), a Web-based search engine for Spanish word properties taken from different normative databases. The tool incorporates several subjective word properties for 16,375 distinct words. Although it focuses particularly on normative ratings for emotional dimensions (e.g., valence and arousal) and discrete emotional categories (fear, disgust, anger, happiness, and sadness), it also makes available ratings for other word properties that are known to affect word processing (e.g., concreteness, familiarity, contextual availability, and age of acquisition). The tool provides two main functionalities: Users can search for words matched on specific criteria with regard to the selected properties, or users can obtain the properties for a set of words. The output from emoFinder is highly customizable and can be accessed online or exported to a computer. The tool architecture is easily scalable, so that it can be updated to include word properties from new Spanish normative databases as they become available.

Semantic Ambiguity: Do Multiple Meanings Inhibit or Facilitate Word Recognition?

It is not clear whether multiple unrelated meanings inhibit or facilitate word recognition. Some studies have found a disadvantage for words having multiple meanings with respect to unambiguous words in lexical decision tasks (LDT), whereas several others have shown a facilitation for such words. In the present study, we argue that these inconsistent findings may be due to the approach employed to select ambiguous words across studies. To address this issue, we conducted three LDT experiments in which we varied the measure used to classify ambiguous and unambiguous words. The results suggest that multiple unrelated meanings facilitate word recognition. In addition, we observed that the approach employed to select ambiguous words may affect the pattern of experimental results. This evidence has relevant implications for theoretical accounts of ambiguous words processing and representation.

Is pupillary response a reliable index of word recognition? Evidence from a delayed lexical decision task.

Previous word recognition studies have shown that the pupillary response is sensitive to a word's frequency. However, such a pupillary effect may be due to the process of executing a response, instead of being an index of word processing. With the aim of exploring this possibility, we recorded the pupillary responses in two experiments involving a lexical decision task (LDT). In the first experiment, participants completed a standard LDT, whereas in the second they performed a delayed LDT. The delay in the response allowed us to compare pupil dilations with and without the response execution component. The results showed that pupillary response was modulated by word frequency in both the standard and the delayed LDT. This finding supports the reliability of using pupillometry for word recognition research. Importantly, our results also suggest that tasks that do not require a response during pupil recording lead to clearer and stronger effects.

Chemical constituents of Helichrysum italicum (Roth) G. Don essential oil and their antimicrobial activity against Gram-positive and Gram-negative bacteria, filamentous fungi and Candida albicans.

The aerial parts of Helichrysum italicum (Roth) G. Don were subjected to hydrodistillation to obtain essential oils which had been analyzed by gas chromatography and gas chromatography coupled with mass spectrometry and tested for antimicrobial activity against 12 bacteria, two yeasts and four fungi by agar diffusion method. The essential oil yielded 0.44% (v/w) and 67 compounds accounting for 99.24% of the oil were identified with a high content of oxygenated sesquiterpenes (61.42%). The most oxygenated sesquiterpene compounds were α-Cedrene (13.61%), α-Curcumene (11.41%), Geranyl acetate (10.05%), Limonene (6.07%), Nerol (5.04%), Neryl acetate (4.91%) and α-Pinene (3.78%). The antimicrobial activity of the essential oil was assayed by using the disk diffusion method on Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 6538, Micrococcus luteus ATCC 4698, Klebsiella pneumonia ATCC 4352, Enterococcus cereus ATCC 2035, Bacillus cereus ATCC 10876, Staphylococcus epidermidis ATCC 12228, Bacillus subtilis ATCC 9372, Pseudomonas aeruginosa ATCC 27853, Enterococcus faecalis ATCC 49452, Proteus mirabilis ATCC 35659, Listeria monocytogenes ATCC 15313 and yeasts Candida albicans ATCC 10231, Saccharomyces cerevisiae ATCC 9763 and fungi, Fusarium solani var. coeruleum, Aspergillus niger, Alternaria alternata, Ascochyta rabiei. H. italicum inhibited the growth of all the tested microorganisms except three bacteria, E. coli ATCC 25922, K. pneumonia ATCC 4352 and L. monocytogenes ATCC 15313. The most sensitive bacterium was E. cereus ATCC 2035 with minimum inhibitory and bactericidal concentrations of 0.79 µg ml-1. A minimum fungistatic and fungicide concentration of 6.325 µg ml-1 and 12.65 µg ml-1 respectively was obtained with C. albicans ATCC 10231 and S. cerevisiae ATCC 9763. However the four fungi were more resistant with fungistatic minimum concentration ranging from 6.325 µg ml-1 to 50.6 µg ml-1 and a fungicide minimum concentration of 50.6 µg ml-1. This antimicrobial activity could be attributed to the essential oil chemical composition. Thus this study represents a first step in the study of the chemical composition of H. italicum (Roth) G. Don collected from north Algeria and its antimicrobial properties.

Terminal carbohydrate composition, IgM level and enzymatic and bacteriostatic activity of European sea bass (Dicentrarchus labrax) skin epidermis extracts.

Although the skin is one of the main defense barriers of fish to date, very little is known about the immune implications and the properties of the numerous substances present in skin cells. In the present study, terminal carbohydrate composition and some components of the skin immunity (total IgM level, and several enzymatic and bacteriostatic activities) present on aqueous and organic epidermal extracts of European sea bass (Dicentrarchus labrax) were determined. Most of the parameters measured followed a protein concentration dose-response. Curiously, both skin extracts have similar levels of total IgM. However, aqueous extracts showed higher presence of some terminal carbohydrates, alkaline phosphatase and esterase activities and lower proteases and ceruloplasmin activities than epidermal organic extracts. Regarding the bacteriostatic activity, the growth of all the bacterial strains tested was reduced when cultivated in presence of organic extracts, being the observed reduction correlated to the protein concentration present in the extract sample. On the contrary, skin aqueous extracts have no significant effect on bacterial growth or even allow bacteria to overgrow, suggesting that the bacteria could use the extracts as a nutrient source. The results are discussed and compared with the same activities studied on fish skin mucus in order to understand their possible implications on mucosal immunity.

Optogenetic Control of Bacterial Cell-Cell Adhesion Dynamics: Unraveling the Influence on Biofilm Architecture and Functionality.

The transition of bacteria from an individualistic to a biofilm lifestyle profoundly alters their biology. During biofilm development, the bacterial cell-cell adhesions are a major determinant of initial microcolonies, which serve as kernels for the subsequent microscopic and mesoscopic structure of the biofilm, and determine the resulting functionality. In this study, the significance of bacterial cell-cell adhesion dynamics on bacterial aggregation and biofilm maturation is elucidated. Using photoswitchable adhesins between bacteria, modifying the dynamics of bacterial cell-cell adhesions with periodic dark-light cycles is systematic. Dynamic cell-cell adhesions with liquid-like behavior improve bacterial aggregation and produce more compact microcolonies than static adhesions with solid-like behavior in both experiments and individual-based simulations. Consequently, dynamic cell-cell adhesions give rise to earlier quorum sensing activation, better intermixing of different bacterial populations, improved biofilm maturation, changes in the growth of cocultures, and higher yields in fermentation. The here presented approach of tuning bacterial cell-cell adhesion dynamics opens the door for regulating the structure and function of biofilms and cocultures with potential biotechnological applications.

Pupillometric and behavioural evidence shows no differences between polyseme and homonym processing.

Ambiguous words can have related meanings (polysemes, e.g., newspaper) or unrelated meanings (homonyms, e.g., bat). Here we examined the processing of both types of ambiguous words (as well as unambiguous words) in tasks of increasing level of semantic engagement. Four experiments were conducted in which the degree of semantic engagement of the task was manipulated: lexical decision task (Experiments 1 and 2), semantic categorization task (Experiment 3) and number-of-meanings task (Experiment 4). RTs and pupillary response were recorded. To our knowledge, pupillary response had never been used before to study ambiguous words processing in isolation. Results showed faster RTs for ambiguous words with respect to unambiguous words in LDT, and larger pupil dilation was observed for ambiguous words in comparison to unambiguous ones in number-of-meanings task. However, differences between polysemes and homonyms were not observed in any task. These results provide no evidence that polysemes and homonyms are processed differently.

An Adenosylcobalamin Specific Whole-Cell Biosensor.

Vitamin B12 (cobalamin) is essential for human health and its deficiency results in anemia and neurological damage. Vitamin B12 exists in different forms with various bioactivity but most sensors are unable to discriminate between them. Here, a whole-cell agglutination assay that is specific for adenosylcobalamin (AboB12), which is one of two bioactive forms, is reported. This biosensor consists of Escherichia coli that express the AdoB12 specific binding domain of CarH at their surface. In the presence of AdoB12, CarH forms tetramers, which leads to specific bacterial cell-cell adhesions and agglutination. These CarH tetramers disassemble upon green light illumination such that reversion of the bacterial aggregation can serve as internal quality control. The agglutination assay has a detection limit of 500 nм AdoB12, works in protein-poor biofluids such as urine, and has high specificity to AdoB12 over other forms of vitamin B12 as also demonstrated with commercially available supplements. This work is a proof of concept for a cheap and easy-to-readout AdoB12 sensor that can be implemented at the point-of-care to monitor high-dose vitamin B12 supplementation.

CACTUS: a computational framework for generating realistic white matter microstructure substrates.

Monte-Carlo diffusion simulations are a powerful tool for validating tissue microstructure models by generating synthetic diffusion-weighted magnetic resonance images (DW-MRI) in controlled environments. This is fundamental for understanding the link between micrometre-scale tissue properties and DW-MRI signals measured at the millimetre-scale, optimizing acquisition protocols to target microstructure properties of interest, and exploring the robustness and accuracy of estimation methods. However, accurate simulations require substrates that reflect the main microstructural features of the studied tissue. To address this challenge, we introduce a novel computational workflow, CACTUS (Computational Axonal Configurator for Tailored and Ultradense Substrates), for generating synthetic white matter substrates. Our approach allows constructing substrates with higher packing density than existing methods, up to 95% intra-axonal volume fraction, and larger voxel sizes of up to 500µm3 with rich fibre complexity. CACTUS generates bundles with angular dispersion, bundle crossings, and variations along the fibres of their inner and outer radii and g-ratio. We achieve this by introducing a novel global cost function and a fibre radial growth approach that allows substrates to match predefined targeted characteristics and mirror those reported in histological studies. CACTUS improves the development of complex synthetic substrates, paving the way for future applications in microstructure imaging.