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Although effective in reducing virus transmission, face masks might compromise face recognition and trait judgments. With this study, we aimed to observe the influence of masks on face recognition and trait judgments—more specifically, in trustworthiness, dominance, and distinctiveness judgments. Also, we wanted to observe the possible influence of trait judgments on facial recognition for masked and unmasked faces, which has never been done before. For that, we conducted an online study where 140 participants observed and made trait judgments of masked and unmasked faces in a within-subjects design. After a distractive task, participants performed a recognition memory test. As expected, we observed a better recognition of faces shown without a mask during the study phase, which allowed the holistic processing of the faces. The worst performance was found for faces encoded with a mask but tested without it, occurring simultaneity disruption in holistic face processing and the violation of the encoding specificity principle. Regarding the trait judgments, unmasked faces were considered more distinctive, and masked faces were considered more trustworthy. More interestingly, we can conclude that facial distinctiveness predicts face recognition, regardless of mask use. In contrast, dominance judgments only predicted face recognition when faces were presented without a mask. When faces were exposed with masks, trustworthiness overrides dominance, becoming more critical to recognizing faces. We can interpret these results from an evolutionary perspective. [ABSTRACT FROM AUTHOR]

Considering the global pandemic we currently experience, face masks have become standard in our daily routine. Even though surgical masks are established as a safety measure against the dissemination of COVID-19, previous research showed that their wearing compromises face recognition. Consequently, the capacity to remember to whom we transmit information—destination memory—could also be compromised. In our study, through a between-participants design (experiment 1) and a within-participants design (experiment 2), undergraduate students have to transmit Portuguese proverbs to masked and unmasked celebrity faces. Following our hypothesis, participants who shared information with masked faces had worse destination memory performance than those who shared information with unmasked faces. Also, we observed lower recognition for masked faces compared to unmasked faces. These results were expected since using a surgical mask affects facial recognition, thus making it harder to recognize a person to whom information was previously transmitted. More importantly, these results also support the idea that variables associated with the recipient's face are important for destination memory performance. [ABSTRACT FROM AUTHOR]

Characterization of brain infarct lesions in rodent models of stroke is crucial to assess stroke pathophysiology and therapy outcome. Until recently, the analysis of brain lesions was performed using two techniques: (1) histological methods, such as TTC (Triphenyltetrazolium chloride), a time-consuming and inaccurate process; or (2) MRI imaging, a faster, 3D imaging method, that comes at a high cost. In the last decade, high-resolution micro-CT for 3D sample analysis turned into a simple, fast, and cheaper solution. Here, we successfully describe the application of brain contrasting agents (Osmium tetroxide and inorganic iodine) for high-resolution micro-CT imaging for fine location and quantification of ischemic lesion and edema in mouse preclinical stroke models. We used the intraluminal transient MCAO (Middle Cerebral Artery Occlusion) mouse stroke model to identify and quantify ischemic lesion and edema, and segment core and penumbra regions at different time points after ischemia, by manual and automatic methods. In the transient-ischemic-attack (TIA) mouse model, we can quantify striatal myelinated fibers degeneration. Of note, whole brain 3D reconstructions allow brain atlas co-registration, to identify the affected brain areas, and correlate them with functional impairment. This methodology proves to be a breakthrough in the field, by providing a precise and detailed assessment of stroke outcomes in preclinical animal studies. [ABSTRACT FROM AUTHOR]

Research on familiar faces has been conducted in different countries and resort to celebrities faces, stimuli that are highly constrained by geographic context and cultural peculiarities, since many celebrities are only famous in particular countries. Despite their relevance to psychological research, there are no normative studies of celebrities' facial recognition in Portugal. We developed a database with 160 black and white pictures of famous persons' faces in this work. The data collection took place in two different studies. In study 1, participants were asked to recognize and name celebrity faces; while in study 2, celebrity names were rated for AoA, familiarity, and distinctiveness. Data were gathered from two different samples of Portuguese young adults aged between 18 and 25 years old, and both procedures were performed online through a questionnaire created in Qualtrics software. This database provides ratings of AoA, familiarity, facial distinctiveness, recognition rate, and naming rate for each celebrity, which will allow further selection of celebrities, based on these five attributes, for studies using Portuguese samples. Also, possible relationships between these five variables were analyzed and presented, highlighting facial distinctiveness as a predictor for both naming and recognition rate of celebrity faces. [ABSTRACT FROM AUTHOR]

In this paper we study the representation of periodically time-varying convolutional codes by means of periodic input-state-output models. In particular, we focus on period two and investigate under which conditions a given two-periodic convolutional code (obtained by alternating two time-invariant encoders) can be represented by a periodic input-state-output system. We first show that one cannot expect, in general, to obtain a periodic input-state-output representation of a periodic convolutional code by means of the individual realizations of each of the associated time-invariant codes. We, however, provide sufficient conditions for this to hold in terms of the column degrees of the associated column reduced generator matrices. Moreover, we derive a sufficient condition to obtain a periodic state-space realization that is minimal. Finally, examples to illustrate the results are presented. [ABSTRACT FROM AUTHOR]

Two dimensional (2D) convolutional codes is a class of codes that generalizes standard one-dimensional (1D) convolutional codes in order to treat two dimensional data. In this paper we present a novel and concrete construction of 2D convolutional codes with the particular property that their projection onto the horizontal lines yield optimal [in the sense of Almeida et al. (Linear Algebra Appl 499:1–25, 2016)] 1D convolutional codes with a certain rate and certain Forney indices. Moreover, using this property we show that the proposed constructions are indeed maximum distance separable, i.e., are 2D convolutional codes having the maximum possible distance among all 2D convolutional codes with the same parameters. The key idea is to use a particular type of superregular matrices to build the generator matrix. [ABSTRACT FROM AUTHOR]

Maximum distance separable (MDS) convolutional codes are characterized through the property that the free distance meets the generalized Singleton bound. The existence of free MDS convolutional codes over $${\mathbb {Z}}_{p^{r}}$$ was recently discovered in Oued and Sole (IEEE Trans Inf Theory 59(11):7305-7313, 2013) via the Hensel lift of a cyclic code. In this paper we further investigate this important class of convolutional codes over $${\mathbb {Z}}_{p^{r}}$$ from a new perspective. We introduce the notions of p-standard form and r-optimal parameters to derive a novel upper bound of Singleton type on the free distance. Moreover, we present a constructive method for building general (non necessarily free) MDS convolutional codes over $${\mathbb {Z}}_{p^{r}}$$ for any given set of parameters. [ABSTRACT FROM AUTHOR]