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The interdisciplinary field of human movement sciences (HMS) has gained massive interest among educational institutions around the world, not only in terms of academic programs but also in research. With this emergence, the researchers aimed to describe the productivity of HMS research in the Philippines. The descriptive bibliometric analysis phase of this paper considered papers published and indexed in Google Scholar from January 2010 to June 2021 and was analyzed after data cleaning and preprocessing. Results revealed that a total of 274 research publications were recorded between the years 2010 and 2021 with an average annual publication rate of 28.6% as far as the dataset was concerned. Also, public higher education institutions (HEIs) emerged to be the most productive generators of research outputs, specifically topped by the University of the Philippines (UP). Moreover, UP-based authors dominated the rankings of the most productive HMS researchers, with "Jeffrey Pagaduan" in the top rank. Results further indicated that 75% of the authors collaborated with fellow researchers within or outside their institution. Meanwhile, the term "physical education" was recorded to be the most frequently appearing word in most of the publications. Through the aid of the data mining approach social network analysis (SNA), five (5) researchers from public HEIs and two from private HEIs were identified to have the largest networks as discussed in the paper. The exploration of research in terms of productivity and the embedded social network of researchers may serve as a springboard in defining the future development of the field in the Philippines.

Demonstratives---simple referential devices like this and that---are linguistic universals, but their meaning varies cross-linguistically. In languages like English and Italian, demonstratives are thought to encode the referent's distance from the producer (e.g., that one means ``the one far away from me"), while in others, like Portuguese and Spanish, they encode relative distance from both producer and receiver (e.g., aquel means ``the one far away from both of us"). Here we propose that demonstratives are also sensitive to the receiver's focus of attention, hence requiring a deeper form of social cognition than previously thought. We provide initial empirical and computational evidence for this idea, suggesting that producers use demonstratives to redirect the receiver's attention towards the intended referent, rather than only to indicate its physical distance.

While most research on scalar implicature has focused on the lexical scale "some" vs "all," here we investigated an understudied scale formed by two syntactic constructions: categorizations (e.g., "Wilma is a nurse") and comparisons ("Wilma is like a nurse"). An experimental study by Rubio-Fernandez et al. (2017) showed high rates of logical responses to superordinate comparisons, even though they are underinformative when interpreted pragmatically (e.g., "A robin is like a bird" implies that a robin is not a bird). Based on recent studies on enrichment priming, we predicted that including "some" and "all" statements (which typically elicit high rates of pragmatic responses) in sentence verification and sentence evaluation tasks would introduce an informativity bias, increasing pragmatic responses to superordinate comparisons. The results of three Web-based experiments supported our predictions, showing that different scalar expressions not only give rise to different rates of scalar implicatures, but can also affect the degree to which an experimental task elicits pragmatic reasoning.

Similes require two different pragmatic skills: appreciating the intended similarity and deriving a scalar implicature (e.g., "Lucy is like a parrot" normally implies that Lucy is not a parrot), but previous studies overlooked this second skill. In Experiment 1, preschoolers (N = 48; ages 3-5) understood "X is like a Y" as an expression of similarity. In Experiment 2 (N = 99; ages 3-6, 13) and Experiment 3 (N = 201; ages 3-5 and adults), participants received metaphors ("Lucy is a parrot") or similes ("Lucy is like a parrot") as clues to select one of three images (a parrot, a girl or a parrot-looking girl). An early developmental trend revealed that 3-year-olds started deriving the implicature "X is not a Y," whereas 5-year-olds performed like adults.

Objective Methods Results Conclusions The aim of the present study was to identify the risk factors for severe maternal outcomes (SMO) of women with suspected or confirmed infections using the data from the WHO global maternal sepsis study (GLOSS).We conducted a secondary analysis of the GLOSS cohort study, which involved pregnant or recently pregnant women with suspected or confirmed infection around 713 health facilities in 52 low‐ and middle‐income countries, and high‐income countries. A nested case–control study was conducted within the GLOSS cohort. Cases included infection‐related maternal deaths or near misses, while controls represented non‐SMO. Logistic mixed models, adjusting for country variations, were employed. Using univariate analysis, we calculated crude odds ratios (crude OR) and their 95% confidence interval (95% CI). Variables were identified with less than 16% missing data, and P values less than 0.20 were used to perform the multivariate logistic model multilevel.A total of 2558 women were included in the analysis. As for the cases, 134 patients were found in the pregnant in labor or not in labor group and 246 patients in the postpartum or postabortion group. Pregnant women with prior childbirths faced a 64% increased risk of SMO. Ante‐ or intrapartum hemorrhage increased risk by 4.45 times, while trauma during pregnancy increased it by 4.81 times. Pre‐existing medical conditions elevated risk five‐fold, while hospital‐acquired infections increased it by 53%. Secondary infections raised risk six‐fold. Postpartum/postabortion women with prior childbirths had a 45% elevated risk, and pre‐existing medical conditions raised it by 2.84 times. Hospital‐acquired infections increased risk by 93%. Postpartum hemorrhage increased risk approximately five‐fold, while abortion‐related bleeding doubled it. Previous cesarean, abortion, and stillbirth also elevated risk.Key risk factors for SMO include prior childbirths, hemorrhage, trauma, pre‐existing conditions, and hospital‐acquired or secondary infections. Implementing effective alert systems and targeted interventions is essential to mitigate these risks and improve maternal health outcomes, especially in resource‐limited settings. [ABSTRACT FROM AUTHOR]

Linguistic communication is an intrinsically social activity that enables us to share thoughts across minds. Many complex social uses of language can be captured by domain-general representations of other minds (i.e., mentalistic representations) that externally modulate linguistic meaning through Gricean reasoning. However, here we show that representations of others' attention are embedded within language itself. Across ten languages, we show that demonstratives--basic grammatical words (e.g., "this"/"that") which are evolutionarily ancient, learned early in life, and documented in all known languages--are intrinsic attention tools. Beyond their spatial meanings, demonstratives encode both joint attention and the direction in which the listener must turn to establish it. Crucially, the frequency of the spatial and attentional uses of demonstratives varies across languages, suggesting that both spatial and mentalistic representations are part of their conventional meaning. Using computational modeling, we show that mentalistic representations of others' attention are internally encoded in demonstratives, with their effect further boosted by Gricean reasoning. Yet, speakers are largely unaware of this, incorrectly reporting that they primarily capture spatial representations. Our findings show that representations of other people's cognitive states (namely, their attention) are embedded in language and suggest that the most basic building blocks of the linguistic system crucially rely on social cognition. [ABSTRACT FROM AUTHOR]

Leaf senescence is a complex trait which becomes crucial for grain filling because photoassimilates are translocated to the seeds. Therefore, a correct sync between leaf senescence and phenological stages is necessary to obtain increasing yields. In this study, we evaluated the performance of five deep machine-learning methods for the evaluation of the phenological stages of sunflowers using images taken with cell phones in the field. From the analysis, we found that the method based on the pre-trained network resnet50 outperformed the other methods, both in terms of accuracy and velocity. Finally, the model generated, Sunpheno, was used to evaluate the phenological stages of two contrasting lines, B481_6 and R453, during senescence. We observed clear differences in phenological stages, confirming the results obtained in previous studies. A database with 5000 images was generated and was classified by an expert. This is important to end the subjectivity involved in decision making regarding the progression of this trait in the field and could be correlated with performance and senescence parameters that are highly associated with yield increase. [ABSTRACT FROM AUTHOR]

For almost two decades, the poor performance observed withthe so-called Director task has been interpreted as evidence oflimited use of Theory of Mind in communication. Here wepropose a probabilistic model of common ground in referentialcommunication that derives three inferences from an utterance:what the speaker is talking about in a visual context, what sheknows about the context, and what referential expressions sheprefers. We tested our model by comparing its inferences withthose made by human participants and found that it closelymirrors their judgments, whereas an alternative modelcompromising the hearer’s expectations of cooperativenessand efficiency reveals a worse fit to the human data. Ratherthan assuming that common ground is fixed in a givenexchange and may or may not constrain reference resolution,we show how common ground can be inferred as part of theprocess of reference assignment.