PLoS ONE最新文献

The present study investigates the feasibility of inducing visual perceptual learning on a peripheral, global direction discrimination and integration task in virtual reality, and tests whether audio-visual multisensory training induces faster or greater visual learning than unisensory visual training. Seventeen participants completed a 10-day training experiment wherein they repeatedly performed a 4-alternative, combined visual global-motion and direction discrimination task at 10° azimuth/elevation in a virtual environment. A visual-only group of 8 participants was trained using a unimodal visual stimulus. An audio-visual group of 9 participants underwent training whereby the visual stimulus was always paired with a pulsed, white-noise auditory cue that simulated auditory motion in a direction consistent with the horizontal component of the visual motion stimulus. Our results reveal that, for both groups, learning occurred and transferred to untrained locations. For the AV group, there was an additional performance benefit to training from the AV cue to horizontal motion. This benefit extended into the unisensory post-test, where the auditory cue was removed. However, this benefit did not generalize spatially to previously untrained areas. This spatial specificity suggests that AV learning may have occurred at a lower level in the visual pathways, compared to visual-only learning.

The multi-objective supply chain needs a full look at enterprise costs, coordinated delivery of different products, and more fluidity and efficiency within the network of the supply chain. However, existing methodologies rarely delve into the intricacies of the industrial supply chain. Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. Additionally, the crossover and mutation operations were enhanced, with determining their respective probabilities determined through a fusion of the elite selection approach and the roulette method. The simulation results indicate that the improved genetic algorithm reduced the supply load from 0.678 to 0.535, labor costs from 1832 yuan to 1790 yuan, and operational time by approximately 39.5%, from 48 seconds to 29.5 seconds. Additionally, the variation in node utilization rates significantly decreased from 30.1% to 12.25%, markedly enhancing resource scheduling efficiency and overall balance within the supply chain.

The spatial arrangement of tourism cities and the strategic placement of tourism and leisure facilities are pivotal to the development of smart tourism cities. The integration of Point of Interest (POI) data, enriched with location-specific insights, holds significant potential for urban planning and the optimization of spatial layouts. This study employs machine learning methodologies to evaluate the suitability of Beijing's main urban area for the introduction of new tourism and leisure facilities. Drawing on POI and demographic data, and considering the distribution patterns of existing tourism and leisure facilities, this research applies machine learning to quantitatively simulate the optimal siting of such amenities. Key findings include: Firstly, compared with the existing tourism and leisure facilities, the fitting degree tested by the machine learning algorithm is 83.5%, suggests that the proposed method is highly feasible. Secondly, the decision-making model, trained with the CART algorithm, reveals that accommodation availability, shopping choices, and transportation infrastructure significantly influence the siting of tourism and leisure facilities in Beijing's urban core. Thirdly, the model training indicates that facilities at various levels in Beijing exhibit a centralized layout, aligned with the city's central axis, with a higher concentration in the urban center than in peripheral regions. The predictive analysis suggests that new tourism and leisure facilities are likely to be concentrated in densely populated areas. Lastly, some areas currently devoid of tourism and leisure facilities are identified as prospective sites for development. It is recommended that these areas be prioritized for the strategic placement. By leveraging machine learning algorithms for facility siting, this study aims to enhance the overall urban layout while mitigating the inherent subjectivity in planning and location decisions, offering valuable insights for the site selection of diverse facilities.

Too low a concentration of dissolved oxygen (DO) in a river can disrupt the ecological balance, while too high a concentration may lead to eutrophication of the water body and threaten the health of the aquatic environment. Therefore, accurate prediction of DO concentration is crucial for water resource protection. In this study, a hybrid machine learning model for river DO prediction, called DWT-KPCA-GWO-XGBoost, is proposed, which combines the discrete wavelet transform (DWT), kernel principal component analysis (KPCA), gray wolf optimization algorithm (GWO), and extreme gradient boosting (XGBoost). Firstly, DWT-db4 was used to denoise the noisy water quality feature data; secondly, the meteorological data were simplified into four principal components by KPCA; finally, the water quality features and meteorological principal components were inputted into the GWO-optimized XGBoost model as features for training and prediction. The prediction performance of the model was comprehensively assessed by comparison with other machine learning models using MAE, MSE, MAPE, NSE, KGE and WI evaluation metrics. The model was tested at three different locations and the results showed that the model outperformed the other models, performing as follows: 0.5925, 0.6482, 6.3322, 0.8523, 0.8902, 0.9403; 0.4933, 0.4325, 6.2351, 0.8952, 0.7928, 0.8632; 0.2912, 0.2001, 4.0523, 0.7823, 0.8425, 0.8463 and the PICP values exceed 95%. The hybrid model demonstrated significant results in predicting dissolved oxygen concentrations for the next 15 days. Compared with other studies, we innovatively improved the prediction accuracy of the model significantly through noise removal and the introduction of multi-source features.

Wearable technologies represent a strong development axis for various medical applications and these devices are increasingly used in daily life as illustrated by smart watches' popularisation. Combined with new data processing methods, it constitutes a promising opportunity for telemonitoring, triage in mass casualty situations, or early diagnosis after a traffic or sport accident. An approach to processing the physiological data is to develop severity scoring systems to quantify the critical level of an individual's health status. However, the existing severity scores require a human evaluation. A first version of a severity scoring system adapted to continuous and real-time wearable monitoring is proposed in this article. The focus is made on three physiological parameters straightforwardly measurable with wrist-wearables: heart rate, respiratory rate, and SpO2, which may be enough to characterise continuously hemodynamic and respiratory status. Intermediate score functions corresponding to each physiological parameter have been established using a sigmoid model. The boundary conditions have been defined based on a survey conducted among 54 health professionals. An adapted function has also been developed to merge the three intermediate scores into a global score. The scores are associated with a triage tricolour code: green for a low-priority casualty, orange for a delayable one, red for an urgent one. Preliminary confrontation of the new severity scoring system with real data has been carried out using a database of 84 subjects admitted to the intensive care unit. Colour classification by the new scoring system was compared with independent physicians' direct evaluation as a reference. The prediction success rate values 74% over the entire database. Two examples of continuous monitoring over time are also given. The new score has turned out to be consistent, and may be easily upgraded with the integration of additional vital signs monitoring or medical information.

This study explored the developmental pathways of all players (n = 313) who represented the Swedish men's senior international team between 2011 and 2023 (n = 118) and/or the U21 international team between 2011-2022. We also examined at which respective level each player's youth club was ranked (i.e., premier, second, or third division club, or international academy) and the age at which they were first present in that club environment. Of the 118 senior international players, 34% were selected at U15-U16, 33% were selected at U17-U18, and 33% were selected at U21 or the senior international level. Later selected (U21 and senior) players had a later senior international debut than early selected (U15-U16) players (-2.5 years, 95% CI [-4.0, -1.0 years]). Later selected players also made their senior club debut later than those selected at the U17-U18 (-1.3 years, 95% CI [-2.0, -0.5 years]) and U15-U16 (-1.9 years, 95% CI [-2.6, -1.1 years]) international level. While the majority (60%) of senior international team players entered a premier division club at some point during their junior years, players from lower clubs were overrepresented among the players who reached the senior international team without previous international team experience and made a later debut in the senior international team. We conclude that senior international players have different career trajectories and that this should be accommodated by providing structures that allow players to progress into, and out of, different development environments that best suit their individual needs as they progress to the senior level.

This paper examines the spatial distribution pattern and influencing factors of Martial Arts Schools (MASs) based on Baidu map data and Geographic Information System (GIS) in China. Using python to obtain the latitude and longitude data of the MASs through Baidu Map API, and with the help of ArcGIS (10.7) to coordinate information presented on the map of China. By harnessing the geographic latitude and longitude data for 492 MASs across 31 Provinces in China mainland as of May 2024, this study employs a suite of analytical tools including nearest neighbor analysis, kernel density estimation, the disequilibrium index, spatial autocorrelation, and geographically weighted regression analysis within the ArcGIS environment, to graphically delineate the spatial distribution nuances of MASs. The investigation draws upon variables such as martial arts boxings, Wushu hometowns, intangible cultural heritage boxings of Wushu, population education level, Per capita disposable income, and population density to elucidate the spatial distribution idiosyncrasies of MASs. (1) The spatial analytical endeavor unveiled a Moran's I value of 0.172, accompanied by a Z-score of 1.75 and a P-value of 0.079, signifying an uneven and clustered distribution pattern predominantly concentrated in provinces such as Shandong, Henan, Hebei, Hunan, and Sichuan. (2) The delineation of MASs exhibited a prominent high-density core centered around Shandong, flanked by secondary high-density clusters with Hunan and Sichuan at their heart. (3) Amongst the array of variables dissected to explain the spatial distribution traits, the explicative potency of 'martial arts boxings', 'Wushu hometowns', 'intangible cultural heritage boxings of Wushu', 'population education level', 'Per capita disposable income', and 'population density' exhibited a descending trajectory, whilst 'educational level of the populace' inversely correlated with the geographical dispersion of MASs. (4) The entrenched regional cultural ethos significantly impacts the spatial layout of martial arts institutions, endowing them with distinct regional characteristics.

Study design: Network meta-analysis of multiple treatment comparisons of recurrence lumbar disc herniation.

Objective: The purpose of comparing the differences between different surgical approaches for recurrent lumbar disc herniation (LDH).

Methods: The PubMed, Embase, MEDLINE, Cochrane Library, Web of Science, Google Scholar and China National Knowledge Infrastructure databases were searched for articles published before April 10th, 2024. The Markov chain Monte Carlo methods were used to perform a hierarchical Bayesian NMA in R version 4.3.3 using a random effects consistency model. The assessing outcomes were pain intensity, disability, complications and recurrence.

Results: 20 studies including 1556 patients and 7 different approaches (PELD, MED, MIS-TLIF, TLIF, Unilat -TLIF, PLIF and OD) were retrospectively retrieved. the efficacy of each approach was the same in relieving pain, OD was significantly better than PELD and MIS-TLIF in relieving dysfunction (SMD: 1.9[0.21,3.4] and 2.0[0.084,3.8], respectively), In addition, MIS-TLIF was significantly lower than PELD and MED in the complication rate (SMD: 0.37[0.14,0.84] and 0.15[0.034,0.68], respectively), TLIF was significantly Lower than MED in the complication rate (SMD:0.14 [0.027,0.70]), PELD was significantly higher than MIS-TLIF, TLIF and PLIF in the recurrence rate (SMD: 1.3e-17 [2.4e-44,0.00016],1.2e-12[2.1e-36,0.34] and 1.4e-12[6.2e-35,0.013], respectively), MED was significantly higher than MIS-TLIF and PLIF in the recurrence rate (SMD: 2.6e-17[5.6e-44,0.0037] and 3.1e-12[1.6e-34,0.022], respectively), OD was significantly higher than MIS-TLIF, TLIF and PLIF in the recurrence rate (SMD:4.6e+16[2.3e+02,3.0e+43], 4.3e+11[2.4,2.5e+35] and 4.1e+11[35,8.7e+33], respectively).

Conclusions: In the treatment of recurrent lumbar disc herniation, vertebral fusion surgery is superior to repeat discectomy. At the same time, MIS-TLIF may be a preferable surgical procedure in the treatment of recurrent lumbar disc herniation.

Cancer data is widely available in repositories such as the National Cancer Institute (NCI) Genomic Data Commons (GDC). These datasets could serve as controls or comparisons in compendium analyses with user data, avoiding the expense and time of generating additional datasets. However, the user must be able to process their new data in the same manner for these comparisons to be useful. This can be non-trivial. Although the executables themselves are usually available in repositories, the GDC pipelines that describe that entire analysis workflow are currently published as text-based standard operating procedures (SOPs). It is difficult to document a computational workflow to the level of detail and accuracy required to reproduce the results. Discrepancies between versions and exclusions of details accumulate as the documentation inevitably lags behind code revisions. Our goal is to enhance the utility of the GDC by converting the SOPs into an accessible and executable format. Specifically, we converted the GDC DNA sequencing (DNA-Seq) and the GDC mRNA sequencing (mRNA-Seq) SOPs into reproducible, self-installing, containerized, and interactive graphical workflows. These can be applied to reproducibly process user data and to harmonize datasets across repositories. Using our publicly available graphical workflows, we harmonize raw RNA-Seq datasets from the GDC and the Genotype-Tissue Expression (GTEx) project that were originally processed using different methodologies to illustrate the importance of uniform processing of control and treatment data for accurate inference of differentially expressed genes. By disseminating the analytical methodology in a reproducible and executable form, we greatly increase the utility of the GDC by enabling researchers to uniformly process custom data and datasets across multiple repositories to enhance data interpretation. Our approach and open-source executable workflows of making the analytical process as readily available as the data can be applied to other data repositories to increase their impact on scientific research.