Search Results (66,572)

Background: Men’s Olympic boxing follows a regulatory temporal structure, but previous studies have shown that this structure varies during competitions. However, these investigations have not thoroughly analyzed the differences in bout development according to weight category. Additionally, most studies have focused on a limited number of categories, leaving gaps in the temporal analysis of various categories. Aim: To determine the temporal structure in the featherweight, lightweight, welterweight, light heavyweight, and heavyweight categories of men’s Olympic boxing, in order to establish models that can help adjust training to meet competitive demands. Methods: An observational approach was used, analyzing 73 bouts involving 80 boxers who competed in the 2020 Tokyo Olympic Games. Results: Most bouts ended after the completion of the full regulation time across all categories. The most common actions were short punching sequences (two to five punches), occurring mainly in the center of the ring. Differences between weight categories were minimal, with the welterweight category showing the most variability. Conclusion: This study presents temporal models that will help coaches and boxers adjust their training with greater precision, improving the efficiency of training sessions according to competitive objectives. Full article

In order to improve the accuracy and efficiency of flow pattern recognition and to solve the problem of the real-time monitoring of flow patterns, which is difficult to achieve with traditional visual recognition methods, this study introduced a flow pattern recognition method based on a convolutional neural network (CNN), which can recognize the flow pattern under different pressure and flow conditions. Firstly, the complex gas–liquid distribution and its velocity field in the annulus were investigated using a computational fluid dynamics (CFDs) simulation, and the gas–liquid distribution and velocity vectors in the annulus were obtained to clarify the complexity of the flow patterns in the annulus. Subsequently, a sequence model containing three convolutional layers and two fully connected layers was developed, which employed a CNN architecture, and the model was compiled using the Adam optimizer and the sparse classification cross entropy as a loss function. A total of 450 images of different flow patterns were utilized for training, and the trained model recognized slug and annular flows with probabilities of 0.93 and 0.99, respectively, confirming the high accuracy of the model in recognizing annulus flow patterns, and providing an effective method for flow pattern recognition. Full article

The makapuno coconut endosperm is distinguished by its soft and irregular texture, in contrast to the solid endosperm of regular coconuts. To establish a scientific foundation for studying makapuno coconuts, callus was induced from makapuno endosperm using a combination of plant growth regulators. The induction was successful, and the resulting callus was subsequently subcultured for further study. Transcriptome sequencing of the makapuno callus identified 429 differentially expressed genes (DEGs), with 273 upregulated and 156 downregulated, compared to callus derived from regular coconut endosperm. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that these DEGs were involved in key metabolic pathways, including fructose and mannose metabolism, carbon fixation in photosynthetic organisms, galactose metabolism, and amino sugar and nucleotide sugar metabolism. Furthermore, lipid content analysis of the makapuno callus revealed a significantly higher total lipid level compared to regular callus, with notable differences in the levels of specific fatty acids, such as myristic acid, palmitic acid, and linoleic acid. This study establishes a novel platform for molecular biological research on makapuno coconuts and provides valuable insights into the molecular mechanisms underlying the formation of makapuno callus tissue. The findings also lay the groundwork for future research aimed at elucidating the unique properties of makapuno endosperm and exploring its potential applications. Full article

Recurrent neural networks (RNNs) have produced significant results in many fields, such as natural language processing and speech recognition. Owing to their computational complexity and sequence dependencies, RNNs need to be deployed on customized hardware accelerators to satisfy performance and energy-efficiency constraints. However, designing hardware accelerators for RNNs is challenged by the vast design space and the reliance on ineffective optimization. An efficient automated design space exploration (DSE) strategy that can balance conflicting objectives is wanted. To address the low efficiency and insufficient universality of the resource allocation process employed for hardware accelerators, we propose an automated two-stage design space exploration (DSE) strategy for customized RNN accelerators. The strategy combines a genetic algorithm (GA) and a reinforcement learning (RL) algorithm, and it utilizes symmetrical exploration and exploitation to find the optimal solutions. In the first stage, the area of the hardware accelerator is taken as the optimization objective, and the GA is used for partial exploration purposes to narrow the design space while maintaining diversity. Then, the latency and power of the hardware accelerator are taken as the optimization objectives, and the RL algorithm is used in the second stage to find the corresponding Pareto solutions. To verify the effectiveness of the developed strategy, it is compared with other algorithms. We use three different network models as benchmarks: a vanilla RNN, LSTM, and a GRU. The results demonstrate that the strategy proposed in this paper can provide better solutions and can achieve latency, power, and area reductions of 9.35%, 5.34%, and 11.95%, respectively. The HV of GRMD is reduced by averages of 6.33%, 6.32%, and 0.67%, and the runtime is reduced by averages of 18.11%, 14.94%, and 10.28%, respectively. Additionally, given different weights, it can make reasonable trade-offs between multiple objectives. Full article

Background/Objectives: The Xizang sheep is a unique breed of sheep in the highland regions of China that has gradually developed physiological characteristics adapted to the plate environment through long-term natural selection and artificial breeding. However, little is known about the molecular basis of metabolic adaptation to seasons in Xizang sheep. Methods: In this study, liver tissues from Xizang sheep in summer (SL) and autumn (AL) were selected for transcriptome sequencing to explore the metabolic adaptability of Xizang sheep to seasons. Results: The results showed that a total of 12,046 differentially expressed genes (DEGs) were identified, with 1123 genes significantly upregulated and 951 genes significantly downregulated in autumn. The top five pathways enriched for DEGs were Metabolic pathways, Phagosome, Valine, leucine and isoleucine degradation, Propanoate metabolism, and Fatty acid metabolism, which are involved in immune regulation, fat oxidation, and synthesis. The reduction in lipid synthesis, fatty acid oxidation, and fat breakdown metabolism promotes gluconeogenesis by inhibiting the Peroxisome proliferator-activated receptors (PPAR) and Phosphoinositide 3-kinase- Protein kinase B (PI3K-Akt) signaling pathways. Conclusions: This process helps to maintain the whole-body energy homeostasis of Xizang sheep, facilitating their adaptation to the seasonal changes in the extreme high-altitude environment. These findings provide foundational data for studying the molecular mechanisms of metabolic adaptation to seasons in ruminants. Full article

Vessel traffic flow forecasting in port waterways is critical to improving safety and efficiency of port navigation. Aiming at the stage characteristics of vessel traffic in port waterways in time sequence, which leads to complexity of data in the prediction process and difficulty in adjusting the model parameters, a convolutional neural network (CNN) based on the optimization of the pelican algorithm (POA) and the combination of bi-directional gated recurrent units (BiGRUs) is proposed as a prediction model, and the POA algorithm is used to search for optimized hyper-parameters, and then the iterative optimization of the optimal parameter combinations is input into the best combination of iteratively found parameters, which is input into the CNN-BiGRU model structure for training and prediction. The results indicate that the POA algorithm has better global search capability and faster convergence than other optimization algorithms in the experiment. Meanwhile, the BiGRU model is introduced and compared with the CNN-BiGRU model prediction; the POA-CNN-BiGRU combined model has higher prediction accuracy and stability; the prediction effect is significantly improved; and it can provide more accurate prediction information and cycle characteristics, which can serve as a reference for the planning of ships’ routes in and out of ports and optimizing the management of ships’ organizations. Full article

Background/Objectives: The prevalence of food allergy (FA) in children is increasing. Dysbiosis of the microbiome has been linked to FA but needs to be better understood. We aimed to characterize the gut and skin microbiome of young food-allergic children over time and within different types of immunoglobulin E (IgE)-mediated FA. Methods: We studied 23 patients, as a pilot study of an ongoing prospective multicenter cohort study including children < 2y with newly diagnosed IgE-mediated FA. Samples (feces/skin swabs) were collected at enrollment and at 1-year follow-up and sequenced for the bacterial 16S rRNA gene (hypervariable v1–v2 region). Results: Gut and skin bacterial diversity was significantly higher in patients compared with controls and increased over time (beta test, Shannon diversity, p < 0.01). Within different types of IgE-mediated FA, bacterial diversity was similar. Community composition differed significantly over time and within IgE-mediated FA types (PERMANOVA: p < 0.01). Several significantly different genus abundances were revealed. We observed a positive correlation between high total IgE and a high abundance of the genus Collinsella in patients with a higher number of allergies/sensitizations (≥3), and patients with tree nut and/or peanut allergy. Conclusions: This study revealed an increased bacterial diversity in children with FA compared with non-atopic children. Importantly, the gut and skin microbiome differed in their composition over time and within different types of IgE-mediated FA. These findings contribute to the understanding of microbiome changes in children with FA and indicate the potential of the genus Collinsella as a biomarker for tree nut and/or peanut allergy and possibly for allergy persistence. Full article

A pink-pigmented, ovoid-rod-shaped, Gram-negative bacterial strain ML10^T was previously isolated in a study of a meromictic lake in British Columbia, Canada. It produces bacteriochlorophyll a, which is incorporated into the reaction center and light harvesting I complexes. This alongside no anaerobic or photoautotrophic growth supports the designation of the strain as an aerobic anoxygenic phototroph. The cells produce wavy polar flagellum and accumulate clear, refractive granules, presumed to be polyhydroxyalkanoate. Sequence of the 16S rRNA gene identified close relatedness to Salinarimonas rosea (97.85%), Salinarimonas ramus (97.92%) and Saliniramus fredricksonii (94.61%). The DNA G + C content was 72.06 mol %. Differences in cellular fatty acids and some physiological tests compared to Salinarimonadaceae members, as well as average nucleotide identity and digital DNA-DNA hybridization, define the strain as a new species in Salinarimonas. Therefore, we propose that ML10^T (=NCIMB 15586^T = DSM 118510^T) be classified as the type strain of a new species in the genus with the name Salinarimonas chemoclinalis sp. nov. Full article

Sap flow within a leaf is a critical indicator of plant vitality and health. This paper introduces an easy-to-use, non-invasive and real-time imaging method for sap microcirculation imaging. From the coherent backscattering of light on a leaf, we show that the acquisition frequency of dynamic speckle can be linked to the microcirculation speed inside the leaf. Unlike conventional methods based on speckle contrast, which use integration times long enough to observe temporal decorrelation within a single image, our approach operates in a regime where speckle patterns appear ‘frozen’ in each frame of a given sequence. This ‘frozen’ state implies that any decorrelation of the speckle pattern within a frame is negligible. However, between successive frames, decorrelation becomes substantial, and it is this inter-frame decorrelation that enables the extraction of dynamic information. In this context, the integration time primarily influences the radiometric levels, while the frame acquisition rate emerges as the key parameter for generating activity index maps. Thus, by accessing different ranges of sap flow activity levels by varying the frame acquisition rate, we reveal, in a non-invasive way, the anatomy of the leaf’s circulatory network with unprecedented richness. We experimentally validate the ability of the method to characterize the vitality of a fig leaf in real time by observing the continuous decrease in sap circulation, first in the smaller vessels and then in the larger ones, following the cutting of the leaf over a 48 h period. Full article

The main challenges in smart home systems and cyber-physical systems come from not having enough data and unclear interpretation; thus, there is still a lot to be done in this field. In this work, we propose a practical approach called Discrete Human Activity Recognition (DiscHAR) based on prior research to enhance Human Activity Recognition (HAR). Our goal is to generate diverse data to build better models for activity classification. To tackle overfitting, which often occurs with small datasets, we generate data and convert them into discrete forms, improving classification accuracy. Our methodology includes advanced techniques like the R-Frame method for sampling and the Mixed-up approach for data generation. We apply K-means vector quantization to categorize the data, and through the elbow method, we determine the optimal number of clusters. The discrete sequences are converted into one-hot encoded vectors and fed into a CNN model to ensure precise recognition of human activities. Evaluations on the OPP79, PAMAP2, and WISDM datasets show that our approach outperforms existing models, achieving 89% accuracy for OPP79, 93.24% for PAMAP2, and 100% for WISDM. These results demonstrate the model’s effectiveness in identifying complex activities captured by wearable devices. Our work combines theory and practice to address ongoing challenges in this field, aiming to improve the reliability and performance of activity recognition systems in dynamic environments. Full article

The member of trace-amine associated receptor family, TAAR5 receptor was suggested to recognize tertiary amines, mostly in the olfactory system; however, knocking out the receptor TAAR5 in mice showed an enhancing effect on adult neurogenesis and dopamine neurotransmission in the striatum. To estimate the role of the TAAR5, we performed gene expression profiling of striatal samples from TAAR5 knockout (KO) mice and their wild-type littermates. The higher expression of several genes involved in dopaminergic signaling and the downregulation of genes associated with gliogenesis were revealed in TAAR5-KO mice. Meanwhile, the upregulating effect of TAAR5 knockout on genes was associated with neurogenesis and synaptogenesis. The estimation of cell-type relative abundance through the deconvolution of RNA sequencing data demonstrated that TAAR5-KO striatum samples contain more D2 dopamine receptor-expressing medium spiny neurons but fewer astrocytes than wild-type mice. Our findings indicate that previously identified improvement in cognitive functions and motor coordination in TAAR5-KO mice may activate genes involved in neurogenesis, synaptogenesis, and synapse organization in the striatum. These data suggest that the pharmaceutical targeting of TAAR5 may improve striatum-dependent cognitive or motor functions. At the same time, a more detailed investigation of future TAAR5 antagonists’ effect on glia development is necessary. Full article

Na⁺,K⁺-ATPase is the active ion transport system that maintains the electrochemical gradients for Na⁺ and K⁺ across the plasma membrane of most animal cells. Na⁺,K⁺-ATPase is constituted by the association of two major subunits, a catalytic α and a glycosylated β subunit, both of which exist as different isoforms (in mammals known as α1, α2, α3, α4, β1, β2 and β3). Na⁺,K⁺-ATPase α and β isoforms assemble in different combinations to produce various isozymes with tissue specific expression and distinct biochemical properties. Na⁺,K⁺-ATPase α4β1 is only found in male germ cells of the testis and is mainly expressed in the sperm flagellum, where it plays a critical role in sperm motility and male fertility. Here, we report the molecular structure of Na⁺,K⁺-ATPase α4β1 at 2.37 Å resolution in the ouabain-bound state and in the presence of beryllium fluoride. Overall, Na⁺,K⁺-ATPase α4 structure exhibits the basic major domains of a P-Type ATPase, resembling Na⁺,K⁺-ATPase α1, but has differences specific to its distinct sequence. Dissimilarities include the site where the inhibitor ouabain binds. Molecular simulations indicate that glycosphingolipids can bind to a putative glycosphingolipid binding site, which could potentially modulate Na⁺,K⁺-ATPase α4 activity. This is the first experimental evidence for the structure of Na⁺,K⁺-ATPase α4β1. These data provide a template that will aid in better understanding the function Na⁺,K⁺-ATPase α4β1 and will be important for the design and development of compounds that can modulate Na⁺,K⁺-ATPase α4 activity for the purpose of improving male fertility or to achieve male contraception. Full article

Truffles are valuable underground mushrooms with significant economic importance. In recent years, their cultivation has achieved satisfactory results, but not for all species. The harvesting of white truffles (Tuber magnatum Picco) is still dependent on natural production, which is at risk due to various issues, such as improper forest management. A useful practice to protect natural resources is to promote the expansion of productive forests. In this study, we investigate the dynamics of the microbiome in an old and new truffle forest using an amplicon sequencing approach of the fungal ITS region and the prokaryotic 16S rRNA gene. We monitor the soil biological community’s development to compare differences and similarities between the primary productive forest and the expanding area over a two-year sampling period. In particular, we observed the colonization of vacant ecological niches by certain fungi, such as those belonging to the genus Mortierella. Additionally, we examined the competitive interactions between saprotrophs and ectomycorrhizal fungi (ECM). In both study areas, the bacterial community was dominated by Pseudomonadota, Planctomycetota, and Actinomycetota. The behavior of the Tuber genus differed significantly from other ECMs and displayed positive correlations with bacterial taxa such as Ktedonobacter, Zavarzinella, and Sphingomonas. The present work provides an initial overview of expanding white truffle habitats. Further, more specific research is needed to explore potential connections between individual taxa. Full article

In recent years, research has gradually uncovered the mechanisms of animal adaptation to hypoxic conditions in different altitude environments, particularly at the genomic level. However, past genomic studies on high-altitude adaptation have often not delved deeply into the differences between varying altitude levels. This study conducted whole-genome sequencing on 60 Tibetan sheep (Medium Altitude Group (MA): 20 Tao sheep (TS) at 2887 m, High Altitude Group (HA): 20 OuLa sheep (OL) at 3501 m, and Ultra-High Altitude Group (UA): 20 AWang sheep (AW) at 4643 m) from different regions of the Tibetan Plateau in China to assess their responses under varying conditions. Population genetic structure analysis revealed that the three groups are genetically independent, but the TS and OL groups have experienced gene flow with other northern Chinese sheep due to geographical factors. Selection signal analysis identified FGF10, MMP14, SLC25A51, NDUFB8, ALAS1, PRMT1, PRMT5, and HIF1AN as genes associated with ultra-high-altitude hypoxia adaptation, while HMOX2, SEMA4G, SLC16A2, SLC22A17, and BCL2L2 were linked to high-altitude hypoxia adaptation. Functional analysis showed that ultra-high-altitude adaptation genes tend to influence physiological mechanisms directly affecting oxygen uptake, such as lung development, angiogenesis, and red blood cell formation. In contrast, high-altitude adaptation genes are more inclined to regulate mitochondrial DNA replication, iron homeostasis, and calcium signaling pathways to maintain cellular function. Additionally, the functions of shared genes further support the adaptive capacity of Tibetan sheep across a broad geographic range, indicating that these genes offer significant selective advantages in coping with oxygen scarcity. In summary, this study not only reveals the genetic basis of Tibetan sheep adaptation to different altitudinal conditions but also highlights the differences in gene regulation between ultra-high- and high-altitude adaptations. These findings offer new insights into the adaptive evolution of animals in extreme environments and provide a reference for exploring adaptation mechanisms in other species under hypoxic conditions. Full article

Herein, we report the structure-based selection via molecular docking of four N-heterocyclic bis-carbene gold(I) complexes, whose potential as ligands for the hTel23 G-quadruplex structure has been investigated using circular dichroism (CD) spectroscopy, CD melting, and polyacrylamide gel electrophoresis (PAGE). The complex containing a bis(1,2,3,4,6,7,8,9-octahydro-11H-11λ³-pyridazino[1,2-a]indazol-11-yl) scaffold induces a transition from the hybrid (3 + 1) topology to a prevalent parallel G-quadruplex conformation, whereas the complex featuring a bis(2-(2-acetamidoethyl)-3λ³-imidazo[1,5-a]pyridin-3(2H)-yl) moiety disrupted the original G-quadruplex structure. These results deserve particular attention in light of the recent findings on the pathological involvements of G-quadruplexes in neurodegenerative diseases. Full article