Climate change is expected to alter the factors that drive changes in adaptive variation. This is especially true for species with long life spans and limited dispersal capabilities. Rapid climate ...changes may disrupt the migration of beneficial genetic variations, making it challenging for them to keep up with changing environments. Understanding adaptive genetic variations in tree species is crucial for conservation and effective forest management. Our study used landscape genomic analyses and phenotypic traits from a thorough sampling across the entire range of Quercus longinux, an oak species native to Taiwan, to investigate the signals of adaptation within this species.
Using ecological data, phenotypic traits, and 1,933 single-nucleotide polymorphisms (SNPs) from 205 individuals, we classified three genetic groups, which were also phenotypically and ecologically divergent. Thirty-five genes related to drought and freeze resistance displayed signatures of natural selection. The adaptive variation was driven by diverse environmental pressures such as low spring precipitation, low annual temperature, and soil grid sizes. Using linear-regression-based methods, we identified isolation by environment (IBE) as the optimal model for adaptive SNPs. Redundancy analysis (RDA) further revealed a substantial joint influence of demography, geology, and environments, suggesting a covariation between environmental gradients and colonization history. Lastly, we utilized adaptive signals to estimate the genetic offset for each individual under diverse climate change scenarios. The required genetic changes and migration distance are larger in severe climates. Our prediction also reveals potential threats to edge populations in northern and southeastern Taiwan due to escalating temperatures and precipitation reallocation.
We demonstrate the intricate influence of ecological heterogeneity on genetic and phenotypic adaptation of an oak species. The adaptation is also driven by some rarely studied environmental factors, including wind speed and soil features. Furthermore, the genetic offset analysis predicted that the edge populations of Q. longinux in lower elevations might face higher risks of local extinctions under climate change.
Purpose
– The purpose of this paper is to identify the factors that influence people to play socially interactive games on mobile devices. Based on network externalities and theory of uses and ...gratifications (U&G), it seeks to provide direction for further academic research on this timely topic.
Design/methodology/approach
– Based on 237 valid responses collected from online questionnaires, structural equation modeling technology was employed to examine the research model.
Findings
– The results reveal that both network externalities and individual gratifications significantly influence the intention to play social games on mobile devices. Time flexibility, however, which is one of the mobile device features, appears to contribute relatively little to the intention to play mobile social games.
Originality/value
– This research successfully applies a combination of network externalities theory and U&G theory to investigate the antecedents of players’ intentions to play mobile social games. This study is able to provide a better understanding of how two dimensions – perceived number of users/peers and individual gratification – influence mobile game playing, an insight that has not been examined previously in the mobile apps literature.
A three-dimensional model was developed to simulate the radiation heat transfer in the AlSi10Mg packed bed. The volume of fluid method (VOF) was used to capture the free surface during selective ...laser melting (SLM). A randomly packed powder bed was obtained using discrete element method (DEM) in Particle Flow Code (PFC). The proposed model has demonstrated a high potential to simulate the selective laser melting process (SLM) with high accuracy. In this paper, the effect of the laser scanning speed and laser power on the thermodynamic behavior of the molten pool was investigated numerically. The results show that the temperature gradient and the resultant surface tension gradient between the center and the edge of the molten pool increase with decreasing the scanning speed or increasing the laser power, thereby intensifying the Marangoni flow and attendant turbulence within the molten pool. However, at a relatively high scanning speed, a significant instability may be generated in the molten pool. The perturbation and instability in the molten pool during SLM may result in an irregular shaped track.
•Maximizing network lifetime will be cope with by resolving energy hole problem and preserving energy.•The energy hole problem is relieved by gradient deployment algorithm.•Based on the Choquet ...integral and Entropy, entropy-driven abnormal event monitoring algorithm is proposed.•Entropy-driven aggregation tree-based routing algorithm is designed for energy consumption.
Data aggregation is one of the essential and fundamental processes in Wireless Sensor Networks (WSNs). When and how to gather data from the sensors to the sink has a direct impact on the lifetime of the WSNs because the energy consumption is proportion to the frequency of data transmission. In general, sensors in a WSN are randomly distributed for creating a massive coverage WSN environment within a short period. Because the sensors nearby the sink are responsible for more data forwarding tasks, they normally have much shorter lifetime than those located away from the sink. Once all sensors nearby the sink run out of energy, the data collected from the terminal sensors can not reach the sink because all established connections to the sink are broken, which is called the termination of a WSN lifetime. This paper proposes a strategy with multiple algorithms for deploying sensors aiming at maximizing a WSN lifetime. The proposed Entropy-driven Data Aggregation with Gradient Distribution (EDAGD) deployment strategy contains three algorithms: (1) multihop tree-based data aggregation, (2) entropy-driven aggregation tree-based routing algorithm and (3) gradient deployment algorithm. The numerical and experimental results indicating that the proposed EDAGD method outperforms the conventional algorithm with the random deployment strategy.
Data heterogeneity is the obstacle for the resource sharing on Semantic Web (SW), and ontology is regarded as a solution to this problem. However, since different ontologies are constructed and ...maintained independently, there also exists the heterogeneity problem between ontologies. Ontology matching is able to identify the semantic correspondences of entities in different ontologies, which is an effective method to address the ontology heterogeneity problem. Due to huge memory consumption and long runtime, the performance of the existing ontology matching techniques requires further improvement. In this work, an extended compact genetic algorithm-based ontology entity matching technique (ECGA-OEM) is proposed, which uses both the compact encoding mechanism and linkage learning approach to match the ontologies efficiently. Compact encoding mechanism does not need to store and maintain the whole population in the memory during the evolving process, and the utilization of linkage learning protects the chromosome’s building blocks, which is able to reduce the algorithm’s running time and ensure the alignment’s quality. In the experiment, ECGA-OEM is compared with the participants of ontology alignment evaluation initiative (OAEI) and the state-of-the-art ontology matching techniques, and the experimental results show that ECGA-OEM is both effective and efficient.
Cone-beam computed tomography (CBCT) integrated with a linear accelerator is widely used to increase the accuracy of radiotherapy and plays an important role in image-guided radiotherapy (IGRT). For ...comparison with fan-beam computed tomography (FBCT), the image quality of CBCT is indistinct due to X-ray scattering, noise, and artefacts. We proposed a deep learning model, "Cycle-Deblur GAN", combined with CycleGAN and Deblur-GAN models to improve the image quality of chest CBCT images. The 8706 CBCT and FBCT image pairs were used for training, and 1150 image pairs were used for testing in deep learning. The generated CBCT images from the Cycle-Deblur GAN model demonstrated closer CT values to FBCT in the lung, breast, mediastinum, and sternum compared to the CycleGAN and RED-CNN models. The quantitative evaluations of MAE, PSNR, and SSIM for CBCT generated from the Cycle-Deblur GAN model demonstrated better results than the CycleGAN and RED-CNN models. The Cycle-Deblur GAN model improved image quality and CT-value accuracy and preserved structural details for chest CBCT images.
Research on the relationship between obesity and rotator cuff tears (RCTs) has been limited to the impact of obesity on the results of arthroscopic repair of RCTs; thus, a need for rigorous research ...controlling for other factors affecting RCTs is warranted, especially to better understand the impact of body mass index (BMI) on RCT severity.
A retrospective study of admission records contained in electronic medical records pertaining to patients who were admitted for RCT repair on 1 shoulder between January 2018 and July 2022 was conducted. In total, 386 patients were included. In accordance with guidance regarding obesity from Taiwan's Ministry of Health and Welfare, patients were divided into three groups: underweight or normal weight (BMI <24.0 kg/m2), overweight (BMI 24.0-26.9 kg/m2), or obese (BMI ≥27.0 kg/m2). Magnetic resonance imaging was used to assess RCT severity in terms of four parameters: Patte stage (PS), fatty infiltration (FI), anteroposterior tear size (AP), and retraction size. Multinomial logistic regression analysis was performed on PS and FI grade data, and multiple linear regression analysis was performed on AP tear size and retraction size in order to analyze impact.
Our results revealed that the average age of the 386 patients was 63.41 years (SD = 9.29) and the mean BMI was 25.88 (SD = 3.72) kg/m2. We found significant differences in PS (P = .003), FI (P < .001), retraction size (P = .001), and AP tear size (P = .001) among patients who were underweight or normal weight, overweight, and obese. After controlling for other risk factors, including age, gender, RCT-prone occupation, duration of shoulder pain prior to surgery, history of shoulder injury, and tobacco use, we found that obese patients had higher severity levels in PS (B = 1.21, OR = 3.36, P = .029), FI (B = 1.38, OR = 3.96, P < .001), retraction size (β = 0.18, P = .001), and AP tear size (β = 0.18, P = .001) compared to underweight or normal weight patients.
Our study demonstrates that a correlation exists between BMI-measured obesity and RCT severity. We therefore suggest that adults control their weight given that maintaining a healthy weight is highly associated with better shoulder health.
Objective
To assess pelvic floor muscle (PFM) strength and influencing factors among healthy women at different life stages.
Design
Multicentre cross‐sectional study.
Setting
Fourteen hospitals in ...China.
Population
A total of 5040 healthy women allocated to the following groups (with 1680 women per group): premenopausal nulliparous, premenopausal parous and postmenopausal.
Methods
The PFM strength was evaluated by vaginal manometry. Multivariate logistic regression was used to determine the influencing factors for low PFM strength.
Main Outcome Measures
Maximum voluntary contraction pressure (MVCP).
Results
The median MVCP values were 36, 35 and 35 cmH2O in premenopausal nulliparous (aged 19–51 years), premenopausal parous (aged 22–61 years), and postmenopausal (aged 40–86 years) women, respectively. In the premenopausal nulliparous group, physical work (odds ratio, OR 2.05) was the risk factor for low PFM strength, which may be related to the chronic increased abdominal pressure caused by physical work. In the premenopausal parous group, the number of vaginal deliveries (OR 1.28) and diabetes (OR 2.70) were risk factors for low PFM strength, whereas sexual intercourse (<2 times per week vs. none, OR 0.55; ≥2 times per week vs. none, OR 0.56) and PFM exercise (OR 0.50) may have protective effects. In the postmenopausal group, the number of vaginal deliveries (OR 1.32) and family history of pelvic organ prolapse (POP) (OR 1.83) were risk factors for low PFM strength.
Conclusions
Physical work, vaginal delivery, diabetes and a family history of POP are all risk factors for low PFM strength, whereas PFM exercises and sexual life can have a protective effect. The importance of these factors varies at different stages of a woman's life.
Myocyte enhancer factor 2A (MEF2A) is widely distributed in various tissues or organs and plays crucial roles in multiple biological processes. To examine the potential effects of MEF2A on skeletal ...muscle myoblast, the functional role of MFE2A in myoblast proliferation and differentiation was investigated. In this study, we found that the mRNA expression level of Mef2a was dramatically increased during the myogenesis of bovine skeletal muscle primary myoblast. Overexpression of MEF2A significantly promoted myoblast proliferation, while knockdown of MEF2A inhibited the proliferation and differentiation of myoblast. RT-PCR and western blot analysis revealed that this positive effect of MEF2A on the proliferation of myoblast was carried out by triggering cell cycle progression by activating CDK2 protein expression. Besides, MEF2A was found to be an important transcription factor that bound to the myozenin 2 (MyoZ2) proximal promoter and performed upstream of MyoZ2 during myoblast differentiation. This study provides the first experimental evidence that MEF2A is a positive regulator in skeletal muscle myoblast proliferation and suggests that MEF2A regulates myoblast differentiation via regulating MyoZ2.
► We compare celebrity endorsements to online customer reviews on shopping behavior. ► An experiment investigated consumer responses to search and experience good. ► Search good endorsed by a ...celebrity evoked more attention, desire, and action. ► Experience good endorsed by an online customer evoked more memory, search and share.
The goal of this study is to compare the influence of celebrity endorsements to online customer reviews on female shopping behavior. Based on AIDMA and AISAS models, we design an experiment to investigate consumer responses to search good and experience good respectively. The results revealed that search good (shoes) endorsed by a celebrity in an advertisement evoked significantly more attention, desire, and action from the consumer than did an online customer review. We also found that online customer reviews emerged higher than the celebrity endorsement on the scale of participants’ memory, search and share attitudes toward the experience good (toner). Implications for marketers as well as suggestions for future research are discussed.
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