ISSN / EISSN : 1932-6203 / 1932-6203
Published by: Public Library of Science (PLoS) (10.1371)
Total articles ≅ 261,056
Latest articles in this journal
PLOS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0262763
The mouse has dichromatic color vision based on two different types of opsins: short (S)- and middle (M)-wavelength-sensitive opsins with peak sensitivity to ultraviolet (UV; 360 nm) and green light (508 nm), respectively. In the mouse retina, cone photoreceptors that predominantly express the S-opsin are more sensitive to contrasts and denser towards the ventral retina, preferentially sampling the upper part of the visual field. In contrast, the expression of the M-opsin gradually increases towards the dorsal retina that encodes the lower visual field. Such a distinctive retinal organization is assumed to arise from a selective pressure in evolution to efficiently encode the natural scenes. However, natural image statistics of UV light remain largely unexplored. Here we developed a multi-spectral camera to acquire high-quality UV and green images of the same natural scenes, and examined the optimality of the mouse retina to the image statistics. We found that the local contrast and the spatial correlation were both higher in UV than in green for images above the horizon, but lower in UV than in green for those below the horizon. This suggests that the dorsoventral functional division of the mouse retina is not optimal for maximizing the bandwidth of information transmission. Factors besides the coding efficiency, such as visual behavioral requirements, will thus need to be considered to fully explain the characteristic organization of the mouse retina.
PLOS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0262173
The Modern Western Diet has been associated with the rise in metabolic and inflammatory diseases, including obesity, diabetes, and cardiovascular disease. This has been attributed, in part, to the increase in dietary omega-6 polyunsaturated fatty acid (PUFA) consumption, specifically linoleic acid (LA), arachidonic acid (ARA), and their subsequent metabolism to pro-inflammatory metabolites which may be driving human disease. Conversion of dietary LA to ARA is regulated by genetic variants near and within the fatty acid desaturase (FADS) haplotype block, most notably single nucleotide polymorphism rs174537 is strongly associated with FADS1 activity and expression. This variant and others within high linkage disequilibrium may potentially explain the diversity in both diet and inflammatory mediators that drive chronic inflammatory disease in human populations. Mechanistic exploration into this phenomenon using human hepatocytes is limited by current two-dimensional culture models that poorly replicate in vivo functionality. Therefore, we aimed to develop and characterize a three-dimensional hepatic construct for the study of human PUFA metabolism. Primary human hepatocytes cultured in 3D hydrogels were characterized for their capacity to represent basic lipid processing functions, including lipid esterification, de novo lipogenesis, and cholesterol efflux. They were then exposed to control and LA-enriched media and reproducibly displayed allele-specific metabolic activity of FADS1, based on genotype at rs174537. Hepatocytes derived from individuals homozygous with the minor allele at rs174537 (i.e., TT) displayed the slowest metabolic conversion of LA to ARA and significantly reduced FADS1 and FADS2 expression. These results support the feasibility of using 3D human hepatic cultures for the study of human PUFA and lipid metabolism and relevant gene-diet interactions, thereby enabling future nutrition targets in humans.
PLOS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0260480
The increasing energy demand and the target to reduce environmental pollution make it essential to use efficient and environment-friendly renewable energy systems. One of these systems is the Photovoltaic (PV) system which generates energy subject to variation in environmental conditions such as temperature and solar radiations. In the presence of these variations, it is necessary to extract the maximum power via the maximum power point tracking (MPPT) controller. This paper presents a nonlinear generalized global sliding mode controller (GGSMC) to harvest maximum power from a PV array using a DC-DC buck-boost converter. A feed-forward neural network (FFNN) is used to provide a reference voltage. A GGSMC is designed to track the FFNN generated reference subject to varying temperature and sunlight. The proposed control strategy, along with a modified sliding mode control, eliminates the reaching phase so that the sliding mode exists throughout the time. The system response observes no chattering and harmonic distortions. Finally, the simulation results using MATLAB/Simulink environment demonstrate the effectiveness, accuracy, and rapid tracking of the proposed control strategy. The results are compared with standard results of the nonlinear backstepping controller under abrupt changes in environmental conditions for further validation.
PLoS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0260455
Intelligent and safe overtaking maneuvering is always a challenging task for autonomous vehicles. This paper proposes and experimentally implements a novel approach of overtaking maneuvering using modified form of Rendezvous Guidance (RG) algorithm for trajectory planning and obstacle avoidance, considering driver safety and comfort during autonomous overtaking. The simulations for all possible scenarios are conducted to ensure the effectiveness of proposed modified RG algorithm. These scenarios involved presence and absence of obstacle vehicle in overtaking lane alongside leading vehicle in driving lane. In addition, the enhanced performance of modified RG algorithm is established over conventional RG algorithm by comparative analysis. The results indicate that overtaking maneuvering period could be decreased by 10% using a modified RG algorithm and vehicle will cover less distance to complete overtaking. The efficacy of proposed method is justified by performing experiments using mobile robots. The experimental results and simulation results of modified RG algorithm are compared, and their plots are almost identical.
PLoS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0262752
Objectives: Motivators and barriers are pivotal factors in the adoption of health behaviors. This study aims to identify patterns of the motivators and barriers influencing heart health behaviors among multi-ethnic Asian adults with behavior-modifiable risk factors for heart disease, namely obesity, physical inactivity and smoking. Methods: A population-based survey of 1,000 participants was conducted in Singapore. Participants were assessed for behavior-modifiable risk factors and asked about motivators and barriers to heart health behaviors. Exploratory and confirmatory factor analyses were conducted to identify factors underlying motivator and barrier question items. Logistic regression was conducted to examine the associations of motivator and barrier factors with sociodemographic characteristics. Results: The twenty-five motivator and barrier items were classified into three (outcome expectations, external cues and significant others including family and friends) and four (external circumstances, limited self-efficacy and competence, lack of perceived susceptibility, benefits and intentions and perceived lack of physical capability) factors respectively. Among participants with behavior-modifiable risk factors, those with lower education were more likely to be low in motivation factor of “outcome expectations” and “external cues”. The well-educated were more likely to be high in the barrier factor of “lack of perceived susceptibility, benefits and intention” and were less likely to have the motivation factor of “significant others (family or friends)”. Those aged 60–75 years had low motivations and high barriers compared to their younger counterparts. Older age was more likely to be low in motivation factor of “outcome expectations” and “external cues” and high in barrier factor of “limited self-efficacy and competence” and “perceived lack of physical capability”. Conclusions: Findings underscore the importance of a targeted intervention and communication strategy addressing specific motivation and barrier factors in different population segments with modifiable risk factors.
PLOS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0262483
Background: The Rowland Universal Dementia Assessment Scale (RUDAS) is currently widely used for research and clinical purposes in many countries. However, its applicability and validity have not been evaluated in the Ethiopian context so far. Therefore, we designed this study to assess the reliability and validity of Rowland Universal Dementia Assessment Scale to detect major neurocognitive disorder among older people in Ethiopia. Methods: An institution-based cross-sectional study was conducted among selected older people residing in Macedonia institutional care center, Addis Ababa, Ethiopia. The gold standard diagnosis was determined using the Diagnostic and Statistical Manual of Mental Disorders criteria for major neurocognitive disorders. Stata v16 statistical software was used for data analysis. Receivers operating curve analysis, correlations, linear regression, and independent t-test were performed with statistically significant associations declared at a p-value of <0.05. Inter-rater, internal consistency reliabilities, content, criterion and construct validities were also determined. Results: A total of 116 individuals participated in the study with a 100% response rate. Most (52.7%) of the participants were male and the mean age in years was 69.9± 8. The Cronbach’s alpha for RUDAS was 0.7 with an intra-class correlation coefficient value of 0.9. RUDAS has an area under the receivers operating curve of 0.87 with an optimal cutoff value of ≤ 22. At this cutoff point, RUDAS has sensitivity and specificity of 92.3 and 75.3 with positive and negative likelihood ratios as well as positive and negative predictive values of 3.7, 0.1, 65.5%, and 91.5%, respectively. There has also been a significant difference in the mean scores of RUDAS among the two diagnostic groups showing good construct validity. Conclusion: The Rowland Universal Dementia Assessment Scale has been demonstrated to be a valid and reliable tool to detect major neurocognitive disorder. Policy makers and professionals can incorporate the tool in clinical and research practices in developing countries.
PLOS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0262026
Recent research suggests that country-years where presidents won their previous election with an absolute majority are more likely to be associated with high government respect for human rights, in comparison to country-years where presidents won their previous election by a mere plurality. With this follow-up article, I replicate these findings with a greatly expanded dataset, and I explore whether country-years where presidents have been elected using a majoritarian system are more likely to be associated with high government respect for human rights, in comparison to country-years where presidents have been elected using a non-majoritarian system. Ultimately, I find that not only are presidents elected with a plurality associated with comparatively lower levels of human rights respect, but so are presidents elected via a non-majoritarian system. These findings suggest that policymakers seeking to improve human rights practices may want to consider directing their efforts towards promoting electoral reform with an emphasis on mandating a minimum of a majority in order to win an election.
PLOS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0262680
Landscape is an ecological category represented by a complex system formed by interactions between society and nature. Spatial patterns of different land uses present in a landscape reveal past and present processes responsible for its dynamics and organisation. Measuring the complexity of these patterns (in the sense of their spatial heterogeneity) allows us to evaluate the integrity and resilience of these complex environmental systems. Here, we show how landscape metrics based on information entropy can be applied to evaluate the complexity (in the sense of spatial heterogeneity) of patches patterns, as well as their transition zones, present in a Cerrado conservation area and its surroundings, located in south-eastern Brazil. The analysis in this study aimed to elucidate how changes in land use and the consequent fragmentation affect the complexity of the landscape. The scripts CompPlex HeROI and CompPlex Janus were created to allow calculation of information entropy (He), variability (He/Hmax), and López-Ruiz, Mancini, and Calbet (LMC) and Shiner, Davison, and Landsberg (SDL) measures. CompPlex HeROI enabled the calculation of these measures for different regions of interest (ROIs) selected in a satellite image of the study area, followed by comparison of the complexity of their patterns, in addition to enabling the generation of complexity signatures for each ROI. CompPlex Janus made it possible to spatialise the results for these four measures in landscape complexity maps. As expected, both for the complexity patterns evaluated by CompPlex HeROI and the complexity maps generated by CompPlex Janus, the areas with vegetation located in a region of intermediate spatial heterogeneity had lower values for the He and He/Hmax measures and higher values for the LMC and SDL measurements. So, these landscape metrics were able to capture the behaviour of the patterns of different types of land use present in the study area, bringing together uses linked to vegetation with increased canopy coverage and differentiating them from urban areas and transition areas that mix different uses. Thus, the algorithms implemented in these scripts were demonstrated to be robust and capable of measuring the variability in information levels from the landscape, not only in terms of spatial datasets but also spectrally. The automation of measurement calculations, owing to informational entropy provided by these scripts, allows a quick assessment of the complexity of patterns present in a landscape, and thus, generates indicators of landscape integrity and resilience.
PLOS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0260964
Objective: To assess the risk of singleton intrauterine fetal death (IUFD) in women by the demographic setting of the online Fetal Medicine Foundation (FMF) Stillbirth Risk Calculator. Methods: Retrospective single-centre case-control study involving 144 women having suffered IUFD and 247 women after delivery of a live-born singleton. Nonparametric receiver operating characteristics (ROC) analyses were performed to predict the prognostic power of the FMF Stillbirth risk score and to generate a cut-off value to discriminate best between the event of IUFD versus live birth. Results: Women in the IUFD cohort born a significantly higher overall risk with a median FMF risk score of 0.45% (IQR 0.23–0.99) compared to controls [0.23% (IQR 0.21–0.29); p<0.001]. Demographic factors contributing to an increased risk of IUFD in our cohort were maternal obesity (p = 0.002), smoking (p<0.001), chronic hypertension (p = 0.015), antiphospholipid syndrome (p = 0.017), type 2 diabetes (p<0.001), and insulin requirement (p<0.001). ROC analyses showed an area under the curve (AUC) of 0.72 (95% CI 0.67–0.78; p<0.001) for predicting overall IUFD and an AUC of 0.72 (95% CI 0.64–0.80; p<0.001), respectively, for predicting IUFD excluding congenital malformations. The FMF risk score at a cut-off of 0.34% (OR 6.22; 95% CI 3.91–9.89; p<0.001) yielded an 82% specificity and 58% sensitivity in predicting IUFD with a positive and negative predictive value of 0.94% and 99.84%, respectively. Conclusion: The FMF Stillbirth Risk Calculator based upon maternal demographic and obstetric characteristics only may help identify women at low risk of antepartum stillbirth.
PLOS ONE, Volume 17; https://doi.org/10.1371/journal.pone.0261856
Containers have emerged as a more portable and efficient solution than virtual machines for cloud infrastructure providing both a flexible way to build and deploy applications. The quality of service, security, performance, energy consumption, among others, are essential aspects of their deployment, management, and orchestration. Inappropriate resource allocation can lead to resource contention, entailing reduced performance, poor energy efficiency, and other potentially damaging effects. In this paper, we present a set of online job allocation strategies to optimize quality of service, energy savings, and completion time, considering contention for shared on-chip resources. We consider the job allocation as the multilevel dynamic bin-packing problem that provides a lightweight runtime solution that minimizes contention and energy consumption while maximizing utilization. The proposed strategies are based on two and three levels of scheduling policies with container selection, capacity distribution, and contention-aware allocation. The energy model considers joint execution of applications of different types on shared resources generalized by the job concentration paradigm. We provide an experimental analysis of eighty-six scheduling heuristics with scientific workloads of memory and CPU-intensive jobs. The proposed techniques outperform classical solutions in terms of quality of service, energy savings, and completion time by 21.73–43.44%, 44.06–92.11%, and 16.38–24.17%, respectively, leading to a cost-efficient resource allocation for cloud infrastructures.