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YOLO has become a central real-time object detection system for robotics, driverless cars, and video monitoring applications. We present a comprehensive analysis of YOLO’s evolution, examining the innovations and contributions in each iteration from the original YOLO up to YOLOv8, YOLO-NAS, and YOLO with transformers. We start by describing the standard metrics and postprocessing; then, we discuss the major changes in network architecture and training tricks for each model. Finally, we summarize the essential lessons from YOLO’s development and provide a perspective on its future, highlighting potential research directions to enhance real-time object detection systems.

•Impaired working memory is observed in patients with fibromyalgia.•Cognitive dysfunction and anatomical changes in fibromyalgia are not directly associated.•Depression moderates the association between grey matter volume and cognition in fibromyalgia. Patients with fibromyalgia are characterised by having, along with persistent chronic pain, cognitive impairments, mainly in working memory capacity. It has been suggested that abnormalities in fronto-parietal neural circuits might account for this dysfunction. However, limited body of neuroimaging research and mixed or inconsistent results have led to inconclusive evidence. Our investigation aimed to explore the neural links between working memory dysfunction and brain grey matter volume in fibromyalgia using voxel-based morphometry (VBM), considering the influence of pain and affective symptoms. Thirty female patients with fibromyalgia and twenty-seven healthy female individuals participated in the present investigation. Working memory functioning was assessed using the Wechsler Adult Intelligence Scale III (WAIS-III) and the Wechsler Memory Scale III (WMS-III). VBM data (global and regional grey matter volume) were also analysed. As expected, fibromyalgia patients scored lower on Arithmetic, Letter-Number Sequencing and Working Memory Index than healthy individuals. Nonetheless, we found no differences in grey matter volume between groups. Moderation analyses highlighted the importance of considering affective symptoms of fibromyalgia, such as depression, to characterize associations between local grey matter volumes in the insula and prefrontal cortices (orbitofrontal and ventrolateral prefrontal cortex) with working memory functioning. These results suggest that moderate to severe symptoms of depression appear to be critical for understanding the emergence of associations between grey matter volume and working memory, offering valuable new insights into this complex relationship. Further research based on multimodal imaging approaches is needed to refine current findings and explore neural circuits underlying cognitive impairment in fibromyalgia.

The spring viraemia of carp virus (SVCV) poses a significant threat to global aquaculture, yet effective antiviral drugs and vaccines remain unavailable. Understanding the interplay between host-pathogen interactions and SVCV replication is crucial for devising preventive strategies. ZF4 cells were exposed to UV-inactivated SVCV or live SVCV at different multiplicities of infection, and the modulation of the unfolded protein response (UPR) was assayed by qPCR at different times. Moreover, ZF4 cells were treated with several UPR modulators to investigate their effect on viral replication. The UPR was also modulated in zebrafish larvae, and its impact on the survival against SVCV infection was evaluated. This study reveals how SVCV exploits the host's UPR to facilitate its replication. SVCV targets the immunoglobulin heavy chain-binding protein (BiP) and the activating transcription factor 4 (ATF4) during early infection to enhance viral RNA synthesis and translation. At later stages, activation of the BiP, the PKR-like ER kinase (PERK), and the inositol-requiring enzyme 1 alpha (IRE1α) pathways supports the release of viral progeny and induces cellular processes, including immune responses and apoptotic cell death. Furthermore, the data demonstrate that modulating UPR pathways, particularly ATF6 and PERK, significantly affect viral replication, providing a novel avenue for antiviral drug development. Preliminary studies suggest the feasibility of chemically modulating the UPR to combat SVCV, though optimizing administration conditions to maximize efficacy while minimizing side effects warrants further investigation. These findings offer critical insights into the molecular mechanisms underlying SVCV pathogenesis and highlight promising targets for therapeutic intervention.

This paper addresses the problem of achieving lifelong open-ended learning autonomy in robotics, and how different cognitive architectures provide functionalities that support it. To this end, we analyze a set of well-known cognitive architectures in the literature considering the different components they address and how they implement them. Among the main functionalities that are taken as relevant for lifelong open-ended learning autonomy are the fact that architectures must contemplate learning, and the availability of contextual memory systems, motivations or attention. Additionally, we try to establish which of them were actually applied to real robot scenarios. It transpires that in their current form, none of them are completely ready to address this challenge, but some of them do provide some indications on the paths to follow in some of the aspects they contemplate. It can be gleaned that for lifelong open-ended learning autonomy, motivational systems that allow finding domain-dependent goals from general internal drives, contextual long-term memory systems that all allow for associative learning and retrieval of knowledge, and robust learning systems would be the main components required. Nevertheless, other components, such as attention mechanisms or representation management systems, would greatly facilitate operation in complex domains.

[This corrects the article DOI: 10.1371/journal.pone.0230010.].

This paper introduces a novel method for collecting and translating texts from the Mixtec to the Spanish language. The method comprises four primary steps. First, we collected a Mixtec–Spanish corpus that includes 4568 sentences from educational and religious domain texts. To enhance the parallel corpus, we generate synthetic data with GPT-3.5. Second, we cleaned the data with a semi-automatic approach followed by preprocessing and tokenization. In preprocessing, we removed stop words, duplicated sentences, special characters, and numbers and converted them to lowercase. Third, we performed semi-automatic alignment to find the correspondence of Mixtec–Spanish sentences to generate sentence-level aligned texts necessary for translation. Finally, we trained automatic translation models based on recurrent neural networks, bidirectional recurrent neural networks, and Transformers. Our system achieved a BLEU score of 95.66 for Mixtec-to-Spanish translation and 99.87 for Spanish-to-Mixtec translation. We also obtained a translation edit rate (TER) of 0.5 for Spanish-to-Mixtec and a TER of 16.5 for Mixtec-to-Spanish. Our research stands out as a pioneering effort in the field of automatic Mixtec-to-Spanish translation in Mexico, filling a gap identified in the current literature.

We describe a computer code that simulates how a satellite observes optical radiation emitted by a lightning flash after it is scattered within an intervening cloud. Our code, CloudScat.jl, is flexible, fully open source and specifically tailored to modern instruments such as the Modular Multispectral Imaging Array (MMIA) component of the Atmosphere–Space Interactions Monitor (ASIM) that operates from the International Space Station. In this article, we describe the algorithms implemented in the code and discuss several applications and examples, with an emphasis on the interpretation of MMIA data.

Background There is a possibility that excess body fat affects bone mass gain and may compromise skeletal health in obese children. The purpose of the study was to identify the relationship between bone mineral density (BMD) and body composition in normal weight, overweight and obese children. Methods This was a cross-sectional study of 6- to 11-year-old children who attended the hospital's outpatient clinic. They were apparently healthy and had no history of prematurity, low birth weight, or chronic diseases. Body mass index (BMI) was used to identify subjects as normal weight, overweight or obese. BMD and body composition were assessed by dual energy X–ray absorptiometry. The BMD values (total and lumbar spine) were compared between normal weight, overweight and obese children. Correlation coefficients were calculated, and multivariate models were performed. Results Forty-nine children were included: 16 with normal weight, 15 that were overweight and 18 with obesity; the mean age was 8.4 ± 1.7 years. All the participants had a normal BMD (> – 2 SD). BMD was higher in obese children and had a positive correlation with total and trunk lean mass in the three study groups ( p  < 0.001). In obese children, an inverse correlation of lumbar spine BMD (Z score) with total and trunk fat mass ( p  < 0.05) was identified. In the multivariate models (with the whole group), the total lean mass was the only significant variable that explained BMD variability. Conclusions BMD in obese children was higher than that in normal weight children, which is explained by their greater lean mass and not by excess body fat. In obese children, a higher fat mass was related to a lower lumbar spine BMD. Lean mass had a direct correlation with BMD in the three study groups and was the most important predictor of BMD, reflecting the importance of strengthening the muscular system through performing physical activity and practicing a healthy lifestyle.

Pygmy hunter-gatherers from Central Africa have shared a network of socioeconomic interactions with non-Pygmy Bantu speakers since agropastoral lifestyle spread across sub-Saharan Africa. Ethnographic studies have reported that their diets differ in consumption of both animal proteins and starch grains. Hunted meat and gathered plant foods, especially underground storage organs (USOs), are dietary staples for pygmies. However, scarce information exists about forager-farmer interaction and the agricultural products used by pygmies. Since the effects of dietary preferences on teeth in modern and past pygmies remain unknown, we explored dietary history through quantitative analysis of buccal microwear on cheek teeth in well-documented Baka pygmies. We then determined if microwear patterns differ among other Pygmy groups (Aka, Mbuti, and Babongo) and between Bantu-speaking farmer and pastoralist populations from past centuries. The buccal dental microwear patterns of Pygmy hunter-gatherers and non-Pygmy Bantu pastoralists show lower scratch densities, indicative of diets more intensively based on nonabrasive foodstuffs, compared with Bantu farmers, who consume larger amounts of grit from stoneground foods. The Baka pygmies showed microwear patterns similar to those of ancient Aka and Mbuti, suggesting that the mechanical properties of their preferred diets have not significantly changed through time. In contrast, Babongo pygmies showed scratch densities and lengths similar to those of the farmers, consistent with sociocultural contacts and genetic factors. Our findings support that buccal microwear patterns predict dietary habits independent of ecological conditions and reflect the abrasive properties of preferred or fallback foods such as USOs, which may have contributed to the dietary specializations of ancient human populations.

Emotional labor, particularly in frontline service roles, has traditionally been examined through the lens of performance strategies, such as surface or deep acting. However, emerging research suggests that employees’ subjective interpretations of emotionally demanding situations—especially attributions of responsibility and perceived fairness—play a critical role in shaping their well-being. This study adopts a qualitative phenomenological approach to explore how frontline employees engage in meaning-making regarding the emotional labor demands during customer interaction. Drawing on six group semi-structured interviews, we conducted a thematic analysis to investigate ho

Journal Article

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