Bubble dynamics is important in flow boiling of minichannel, and ultrasonic field effects bubble behaviors. However, flow boiling bubble movements in minichannels under ultrasonic field have received ...little research attention and are still poorly understood. In this paper, the effects of ultrasonic field on bubble dynamics are experimentally studied by capturing the bubble motion behaviors of the flow boiling bubbles. The ultrasonic frequencies are set to 23, 28, 32, and 40 kHz. Bubble tracking algorithm, which studies the growth, trajectories, velocities, and traveled distances for bubbles, is created to qualitatively describe bubble motion behavior of flow boiling in minichannel. It is found that after the application of ultrasound, the detachment frequency, velocity, and travel distance of the bubbles significantly increases, and the growth behavior and trajectory are extremely complex, the two-phase gas-liquid flow is extremely unstable. The bubbles gain kinetic energy as the ultrasound frequency increases. Finally, numerical simulations are used to quantitatively investigate the mechanism of bubble motion in microchannels under ultrasonic fields.
The key system serves as a vital foundation for ensuring the security of information systems. In the presence of a large scale of heterogeneous sensors, the use of low-quality keys directly impacts ...the security of data and user privacy within the sensor network. Therefore, the demand for high-quality keys cannot be underestimated. Random numbers play a fundamental role in the key system, guaranteeing that generated keys possess randomness and unpredictability. To address the issue of random number requirements in multi-sensor network security, this paper introduces a new design approach based on the fusion of chaotic circuits and environmental awareness for the entropy pool. By analyzing potential random source events in the sensor network, a high-quality entropy pool construction is devised. This construction utilizes chaotic circuits and sensor device awareness technology to extract genuinely random events from nature, forming a heterogeneous fusion of a high-quality entropy pool scheme. Comparatively, this proposed scheme outperforms traditional random entropy pool design methods, as it can meet the quantity demands of random entropy sources and significantly enhance the quality of entropy sources, ensuring a robust security foundation for multi-sensor networks.
The silent information regulator sirtuin 1 (SIRT1) protein, a highly conserved NAD
-dependent deacetylase belonging to the sirtuin family, is a post-translational regulator that plays a role in ...modulating inflammation. SIRT1 affects multiple biological processes by deacetylating a variety of proteins including histones and non-histone proteins. Recent studies have revealed intimate links between SIRT1 and inflammation, while alterations to SIRT1 expression and activity have been linked to inflammatory diseases. In this review, we summarize the mechanisms that regulate SIRT1 expression, including upstream activators and suppressors that operate on the transcriptional and post-transcriptional levels. We also summarize factors that influence SIRT1 activity including the NAD
/NADH ratio, SIRT1 binding partners, and post-translational modifications. Furthermore, we underscore the role of SIRT1 in the development of inflammation by commenting on the proteins that are targeted for deacetylation by SIRT1. Finally, we highlight the potential for SIRT1-based therapeutics for inflammatory diseases.
•Effects of triangular prisms on local and average thermal hydraulic characteristics are studied.•Effects of triangular prism orientation, height and offset value on performances are ...analyzed.•Minichannel with backward triangular prisms shows best comprehensive performance.•Best comprehensive performance is obtained when prism height is about half of minichannel height.•Comprehensive performance decreases with the increase in offset value.
Micro/mini-channel heat sinks (MCHSs) are currently projected as an advance cooling solution for heat dissipation in the high heat flux devices. Triangular prism (TP) has a special effect on forced-convection heat transfer due to the specificity of its flow separation. To further improve the thermal performance in MCHS, this study explores the effects of regular TPs on thermal and hydraulic characteristics in a minichannel heat sink under inlet Reynolds number (Re) of 221–884 using numerical simulation. The orientation arrangement and height (Hp = 0.5–2 mm) of TP, as well as the offset value (S = 0–1.2 mm) between two adjacent TPs in the width direction of the minichannel are selected as studied parameters. The results show that the minichannel with backward triangular prism (MC-BTP, apex of TP points to outlet) performs the best heating wall temperature uniformity, highest Nusselt number (Nu) and largest friction coefficient (f). The MC-BTP also presents the greatest comprehensive performance evaluation criterion (PEC) at most of operation condition, especially at high Re. For MC-BTP, with the increase in Hp, the f increases, but the Nu and PEC increase at first and then decrease; moreover, increasing S results in the f, Nu and PEC declining. Overall, the MC-BTP with Hp = 1 mm and S = 0 yields highest PEC at most of operation condition. The friction coefficient ratio, heat transfer enhancement factor and PEC in this minichannel are in ranges of 1.45–2.22, 1.39–2.33 and 1.23–1.79, respectively. Also the maximum PEC value (1.79) is obtained at Re = 884.
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Sustainability, as a trend of social development and the embodiment of corporate social responsibility, has begun to receive more attention. To achieve this goal, sustainable supplier selection (SSS) ...and order allocation (OA) are seen as the crucial activities in corporate management. In the process of SSS, the psychological behavior of decision-makers (DMs) could play a critical role in the evaluation results. Therefore, introducing it into the decision-making process may lead to decision in line with the actual situation. In the uncertain multi-criteria group decision-making (MCGDM) problem described by probability linguistic term sets (PLTS), the DMs can evaluate the criteria of each supplier based on his own preference and hesitation, which is useful to avoid the loss of information. For this reason, this study develops a novel multi-criteria group decision-making combined with fuzzy multi-objective optimization (MCGDM-FMOO) model for SSS/OA problems by considering the triple bottom line (TBL) in which includes economic, environmental and social factors. The proposed method includes four stages. (1) the best-worst method (BWM) and entropy weight method are utilized to assign the weights of criteria to obtain the comprehensive weight. According to the output weights, the an acronym for interactive and multi-criteria decision-making in Portugese (TODIM) approach is applied to rank the suppliers under PLTS environment; (2) a FMOO model that can effectively deal with uncertainties and dynamic nature of parameter is formulated for allocating optimal order quantities; (3) two novel approaches are utilized to solve the FMOO model in order to obtain the richer Pareto frontier; and (4) the final OA solution is achieved by technique for order preference by similarity to ideal solution (TOPSIS) method. Finally, the validity and practicability of proposed MCGDM-FMOO model are verified by an example and comparative analysis with other classical MCGDM methods.
•The rainwater transformation ratio (RTR) on soil-mantled karst hillslope was tested.•Bedrock fissures were a key factor affecting RTR at the surface and below ground.•Soil loss on slopes with ...bedrock fissures was lower than on those without fissures.•On soil-mantled hillslopes, 60% of rainwater was transformed into drainage runoff.•Slope gradients showed a significant effect on RTR during rainfall events.
Karst slopes have thin soil layers covering bedrock and feature multiple near-surface soil-rock interfaces (SRIs), which can produce hydrological processes that differ from those of nonkarst slopes. This study investigated the differences in the proportions of rainwater transformed into surface and belowground runoff and measured soil loss on soil-mantled karst slopes with different hydrological situations: bedrock with fissures (HS-1) and without fissures (HS-2). The rainfall intensity was 50 mm/h. Three slope gradients (5°, 15° and 25°) were applied, and surface runoff (SR), subsurface flow (SF), underground fissure flow (UFF) and soil-rock interface flow (SRIF) were collected during rainfall. No SR was produced on 5° slopes in either treatment. The proportion of rainwater absorbed by soil (RH) was approximately 34%-46% of the rainwater, with no significant differences (p > 0.05) between HS-1 and HS-2. On the 5° and 15° slopes, 28%-61% of the rainwater was transformed into UFF under HS-1, and 29%-50% of the rainwater was transformed into SRIF under HS-2. On the 25° slope, the SRIF and UFF proportions were<18%. Bedrock fissures greatly affected the type of runoff but had little effect on the near-surface soil water. The SR and SF amounts were 29%-67% and 3%-38% higher in HS-2 than in HS-1, respectively. Due to bedrock fissures, on average, 6% of rainwater was lost as underground flow during rainfall, and the extra rainwater, 30% on average, flowed along the SRI underground, potentially forming UFF. This difference occurs because the infiltrating rainwater that reaches the SRI can freely drain through bedrock fissures in HS-1 but not in HS-2. The soil loss via SF, SRIF and UFF was very low (<0.05 g/L). Therefore, slope gradients and bedrock fissures both have major effects on rainwater transformation, and soil loss via rainfall impact is very slow on soil-mantled karst slopes.
The problem of missing data, particularly for dichotomous variables, is a common issue in medical research. However, few studies have focused on the imputation methods of dichotomous data and their ...performance, as well as the applicability of these imputation methods and the factors that may affect their performance. In the arrangement of application scenarios, different missing mechanisms, sample sizes, missing rates, the correlation between variables, value distributions, and the number of missing variables were considered. We used data simulation techniques to establish a variety of different compound scenarios for missing dichotomous variables and conducted real-data validation on two real-world medical datasets. We comprehensively compared the performance of eight imputation methods (mode, logistic regression (LogReg), multiple imputation (MI), decision tree (DT), random forest (RF), k-nearest neighbor (KNN), support vector machine (SVM), and artificial neural network (ANN)) in each scenario. Accuracy and mean absolute error (MAE) were applied to evaluating their performance. The results showed that missing mechanisms, value distributions and the correlation between variables were the main factors affecting the performance of imputation methods. Machine learning-based methods, especially SVM, ANN, and DT, achieved relatively high accuracy with stable performance and were of potential applicability. Researchers should explore the correlation between variables and their distribution pattern in advance and prioritize machine learning-based methods for practical applications when encountering dichotomous missing data.
This study aims to describe the preference for primary healthcare (PHC) and investigate associated factors among homebound residents in both rural and urban areas of China. It provides valuable ...insights to facilitate the rational allocation of healthcare resources and promote the utilization of PHC.
In this nationally representative cross-sectional study, we utilized the most recent data (2020) from the China Family Panel Studies (CFPS). Participants were recruited from 25 provincial-level administrative regions in both rural and urban areas of China. Homebound patients were asked to provide details about their individual characteristics, variables related to family caregiving, and preferences for PHC. Multivariable logistic models were used to analyze potential factors associated with preference for PHC. Estimates of association were reported as odds ratios (OR) and their 95% confidence intervals (CI).
The study found that 58.43% of rural patients reported a preference for PHC, while 42.78% of urban patients favored PHC. Compared to rural participants who did not received inpatient care in the past year, those who received inpatient care in the past year had 67% lower odds of choosing PHC (OR:0.33, 95% CI:0.19-0.59); Compared to rural participants who did not received family caregiving when ill, those who received family caregiving when ill had 59% lower odds of choosing PHC (OR: 0.41, 95% CI:0.21-0.77). Correspondingly, Compared to urban participants who did not received inpatient care in the past year, those who had received inpatient care in the past year had 75% lower odds of choosing PHC (OR: 0.25, 95% CI: 0.10-0.56); Compared to urban participants who did not received family caregiving when ill, those who received family caregiving when ill had 73% lower odds of choosing PHC (OR: 0.27, 95% CI: 0.11-0.63); Compared to urban participants who with agricultural Hukou, those with Non-agricultural Hukou had 61% lower odds of choosing PHC (OR: 0.39, 95% CI:0.18-0.83); Compared to urban participants living in the eastern part of mainland China, those living in the central part of China had 188% higher odds of choosing PHC (OR: 2.88, 95% CI: 1.14-7.29).
Policymakers should focus on tailoring PHC to vulnerable populations and prioritizing family-based public health strategies for enhancing homebound patients' perceptions of PHC. Furthermore, further study is needed on whether the Hukou registration system affects the barriers that homebound patients experience in choosing healthcare providers.
Acoustofluidics, the fusion of acoustics and microfluidic techniques, has recently seen increased research attention across multiple disciplines due in part to its capabilities in contactless, ...biocompatible, and precise manipulation of micro‐/nano‐objects. Herein, a bimodal signal amplification platform which relies on acoustofluidics‐induced enrichment of nanoparticles is introduced. The dual‐function biosensor can perform sensitive immunofluorescent or surface‐enhanced Raman spectroscopy (SERS) detection. The platform functions by using surface acoustic waves to concentrate nanoparticles at either the center or perimeter of a glass capillary; the concentration location is adjusted simply by varying the input frequency. The immunofluorescence assay is achieved by concentrating fluorescent analytes and functionalized nanoparticles at the center of the microchannel, thereby improving the visibility of the fluorescent output. By modifying the inner wall of the glass capillary with plasmonic Ag nanoparticle‐deposited ZnO nanorod arrays and focusing analytes toward the perimeter of the microchannel, SERS sensing using the same device setup is achieved. Nanosized exosomes are used as a proof‐of‐concept to validate the performance of the acoustofluidic bimodal biosensor. With its sample‐enrichment functionality, bimodal sensing, short processing time, and minute sample consumption, the acoustofluidic chip holds great potential for the development of lab‐on‐a‐chip based analysis systems in many real‐world applications.
Acoustofluidics‐assisted signal amplification platform is introduced to develop bimodal immunofluorescent and surface‐enhanced Raman spectroscop biosensors. The platform functions by using surface acoustic waves to concentrate the target of interest at either the center or perimeter of a glass capillary. Nanosized exosomes are used as a proof‐of‐concept to validate the performance of the acoustofluidic bimodal biosensor.
Identifying influential nodes in complex networks has attracted the attention of many researchers in recent years. However, due to the high time complexity, methods based on global attributes have ...become unsuitable for large-scale complex networks. In addition, compared with methods considering only a single attribute, considering multiple attributes can enhance the performance of the method used. Therefore, this paper proposes a new multiple local attributes-weighted centrality (LWC) based on information entropy, combining degree and clustering coefficient; both one-step and two-step neighborhood information are considered for evaluating the influence of nodes and identifying influential nodes in complex networks. Firstly, the influence of a node in a complex network is divided into direct influence and indirect influence. The degree and clustering coefficient are selected as direct influence measures. Secondly, based on the two direct influence measures, we define two indirect influence measures: two-hop degree and two-hop clustering coefficient. Then, the information entropy is used to weight the above four influence measures, and the LWC of each node is obtained by calculating the weighted sum of these measures. Finally, all the nodes are ranked based on the value of the LWC, and the influential nodes can be identified. The proposed LWC method is applied to identify influential nodes in four real-world networks and is compared with five well-known methods. The experimental results demonstrate the good performance of the proposed method on discrimination capability and accuracy.
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