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Increased resting heart rate indicates high-workload hearts with augmented aortic hydraulic power in hypertensive pigs

Clarifying the inceptive pathophysiology of hypertensive heart disease helps to impede the disease progression. Through coarctation of the infrarenal abdominal aorta (AA), we induced hypertension in minipigs and evaluated physiological reactions and morpho-functional changes of the heart. Moderate aortic coarctation was achieved with approximately 30 mmHg systolic pressure gradient in minipigs. Hypertension was assessed by pressure increment of the carotid artery. Perioperative heart rate (HR) was recorded. We measured aortic flow rate and pressure proximal to coarctation to calculate hydraulic power, an indicator for cardiac workload, and resistance. The hearts harvested at sacrifice were examined for myocardial hypertrophy, fibrosis, and dysfunction. The parameters capable of indicating high-workload heart and their prediction effectiveness were determined by cluster and receiver operating characteristic (ROC) analyses. Prolonged AA coarctation for 8–12 weeks induced hypertension in a portion of minipigs. The cluster of minipigs exhibiting increased aortic hydraulic power displayed hypertension and mean HR elevation without changing arterial resistance. Notably, the blood pressure and HR were measured under full anesthesia, equivalent to resting status. Myocardial hypertrophy was not detected at the tissue, cellular or molecular levels. Expression of biomarkers for cellular stress and heart failure didn’t increase except for heat shock protein 40. ROC analysis showed that aortic hydraulic power, resting HR, and mean blood pressure, but not arterial resistance, can serve as the indicators for high-workload hearts. These results suggested that resting HR increase in hypertensive pigs indicates hearts with high workload. Heart failure may develop without appropriate treatment.

Hippocampal subfield volume alterations and associations with severity measures in long COVID and ME/CFS: A 7T MRI study

Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) patients share similar symptoms including post-exertional malaise, neurocognitive impairment, and memory loss. The neurocognitive impairment in both conditions might be linked to alterations in the hippocampal subfields. Therefore, this study compared alterations in hippocampal subfields of 17 long COVID, 29 ME/CFS patients, and 15 healthy controls (HC). Structural MRI data was acquired with sub-millimeter isotropic resolution on a 7 Telsa MRI scanner and hippocampal subfield volumes were then estimated for each participant using FreeSurfer software. Our study found significantly larger volumes in the left hippocampal subfields of both long COVID and ME/CFS patients compared to HC. These included the left subiculum head (long COVID; p = 0.01, ME/CFS; p = 0.002,), presubiculum head (long COVID; p = 0.004, ME/CFS; p = 0.005), molecular layer hippocampus head (long COVID; p = 0.014, ME/CFS; p = 0.011), and whole hippocampal head (long COVID; p = 0.01, ME/CFS; p = 0.01). Notably, hippocampal subfield volumes were similar between long COVID and ME/CFS patients. Additionally, we found significant associations between hippocampal subfield volumes and severity measures of ‘Pain’, ‘Duration of illness’, ‘Severity of fatigue’, ‘Impaired concentration’, ‘Unrefreshing sleep’, and ‘Physical function’ in both conditions. These findings suggest that hippocampal alterations may contribute to the neurocognitive impairment experienced by long COVID and ME/CFS patients. Furthermore, our study highlights similarities between these two conditions.

Development and effectiveness analysis of a safety management model for SMEs integrating lean management innovation with SQCDP framework

This study organically integrates the safety, quality, cost, delivery, and people (SQCDP) management mode and lean management to create the SQCDP + lean safety management (SLSM) mode, which addresses certain problems faced by China’s small- and medium-sized enterprises (SMEs), such as imperfect safety management systems, poor regulatory implementation, challenging problem correction, and perfunctory management. It then explains the benefits proposed mode for SMEs and the establishment of a novel mode that aligns with the current safety production and operation management of SMEs. The application of the SLSM mode to a private machinery manufacturing company in Wenzhou resulted in the effective shouldering of safety responsibilities by the company, a year-on-year decrease in accident rates, and a significant increase in production efficiency, thereby providing corporate managers with guidance and suggestions for making improvements.

Equalization of basic public services enabled by digitization: A study of mechanism and heterogeneity

Digitalization has penetrated into every aspect of life. However, research on the mechanisms through which digitalization affects the equalization of basic public services, as well as the heterogeneity of its impact on different fields of these services, is still insufficient. Based on the panel data of 30 provincial-level administrative regions in China from 2013 to 2023, this paper studies the mechanism and heterogeneity of the impact of digital development on the equalization of basic public services. The research finds that the improvement of the digital development level can significantly promote the equalization process of basic public services, and this finding remains robust after a series of endogeneity and robustness tests. The discussions on regional heterogeneity and spatial complexity show that digitalization makes a greater contribution to the equalization of basic public services in the central and western regions and the northeast than in the east. However, achieving equalization of basic public services across regions through digitalization is challenging. The development of digitalization and the equalization of basic public services are limited by territorial cohesion in geographical space. Underdeveloped regions have poor access to digitalization for achieving equalization of basic public services. This leads to a ‘digital divide’ between developed and underdeveloped regions. It also results in a ‘low-lying area’ phenomenon in basic public services. Additionally, the promoting effect of digitalization on the equalization of different areas of basic public services varies significantly. The effect is strongest for basic living services. It is moderate for environmental protection services and education services. The effect on medical services is not significant.

Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement

Soil spectroscopy is a widely used method for estimating soil properties that are important to environmental and agricultural monitoring. However, a bottleneck to its more widespread adoption is the need for establishing large reference datasets for training machine learning (ML) models, which are called soil spectral libraries (SSLs). Similarly, the prediction capacity of new samples is also subject to the number and diversity of soil types and conditions represented in the SSLs. To help bridge this gap and enable hundreds of stakeholders to collect more affordable soil data by leveraging a centralized open resource, the Soil Spectroscopy for Global Good initiative has created the Open Soil Spectral Library (OSSL). In this paper, we describe the procedures for collecting and harmonizing several SSLs that are incorporated into the OSSL, followed by exploratory analysis and predictive modeling. The results of 10-fold cross-validation with refitting show that, in general, mid-infrared (MIR)-based models are significantly more accurate than visible and near-infrared (VisNIR) or near-infrared (NIR) models. From independent model evaluation, we found that Cubist comes out as the best-performing ML algorithm for the calibration and delivery of reliable outputs (prediction uncertainty and representation flag). Although many soil properties are well predicted, total sulfur, extractable sodium, and electrical conductivity performed poorly in all spectral regions, with some other extractable nutrients and physical soil properties also performing poorly in one or two spectral regions (VisNIR or NIR). Hence, the use of predictive models based solely on spectral variations has limitations. This study also presents and discusses several other open resources that were developed from the OSSL, aspects of opening data, current limitations, and future development. With this genuinely open science project, we hope that OSSL becomes a driver of the soil spectroscopy community to accelerate the pace of scientific discovery and innovation.

Estimating whole-body centre of mass sway during quiet standing with inertial measurement units

Our ability to balance upright provides a stable platform to perform daily activities. Balance deficits associated with various clinical conditions may affect activities of daily living, highlighting the importance of quantifying standing balance in ecological environments. Although typically performed in laboratory settings, the growing availability of low-cost inertial measurement units (IMUs) allows the assessment of balance in the real world. However, it is unclear how many IMUs are required to adequately estimate linear displacements of the centre of mass (CoM) at stance widths associated with daily activities. While wearing IMUs on their head, sternum, back, right thigh, right shank, and left shank, 16 participants stood quietly on a force platform in narrow, hip-width, and shoulder-width stances, each for three two-minute trials. Using a multi-segment biomechanical model, we estimated CoM displacements from all possible combinations of the IMUs. We then calculated the correlation between the IMU- and force platform- CoM estimates to determine the minimal number of IMUs needed to estimate CoM sway. Four IMUs were necessary to accurately estimate anteroposterior (AP) and mediolateral (ML) CoM displacements across stance widths. Using IMUs on the back, right thigh, and both shanks, we found strong correlations between the IMU CoM estimation and the force platform CoM estimation in narrow stance (AP: r = 0.92±0.04, RMSE = 2.39±2.08 mm; ML: r = 0.97±0.02, RMSE = 1.16±0.77 mm), hip-width stance (AP: r = 0.93±0.04, RMSE = 2.00±1.18 mm; ML: r = 0.92±0.06, RMSE = 0.92±0.70 mm), and shoulder-width stance (AP: r = 0.93±0.03, RMSE = 1.95±1.66 mm; ML: r = 0.86±0.13, RMSE = 1.39±1.46 mm). These results indicate that IMUs can be used to estimate CoM displacements during quiet standing and that four IMUs are necessary to do so. Using an algorithm based on a simple biomechanical model, researchers and clinicians can estimate whole-body CoM displacements accurately during unperturbed quiet standing. This approach can improve the ecological validity of standing balance research and opens the possibility for assessing/monitoring patients with standing balance deficits.

Food insecurity and early childhood development among children 24–59 months in Nigeria: A multilevel mixed effects modelling of the social determinants of health inequities

Food insecurity (FI) has been identified as a determinant of child development, yet evidence quantifying this association using the newly developed Early Childhood Development Index 2030 (ECDI2030) remains limited. Herein, we provide national estimates of early childhood development (ECD) risks using the ECDI2030 and examined to what extent FI was associated with ECD among children aged 24–59 months in Nigeria. This population based cross-sectional analyses used data from the UNICEF-supported 2021 Multiple Indicator Cluster Survey in Nigeria. The analytic sample comprised children aged 24–59 months (weighted N = 12,112). We measured early childhood development for each child using the ECDI2030, measured across three domains: learning, psychosocial well-being and health. Food insecurity was assessed using the Food Insecurity Experience Scale (FIES), categorized as none/mild, moderate and severe. We fitted mixed-effects multilevel logistic regression models, with random intercepts, to estimate the odds of association between FI status and ECD. A total of 11,494 children aged 24–59 months (mean ± SD age, 43.4 ± 9.9 months), including 5,797 boys (50.2%) and 5,697 girls (49.8%), were included in the study. Approximately 46.4% of children were developmentally off track and about 76% of children lived in food-insecure households. The intercept-only model indicated significant variation in ECD prevalence across communities (τ00 = 0.94, intraclass correlation = 0.22, p < 0.0001), suggesting nonignorable variability in ECD across communities. Adjusting for confounders, we observed no significant association between FI and ECD. However, increasing child’s age and disability status appeared as significant risk factors for higher odds of children being developmentally off track. These findings highlight that while FI alone may not explain ECD, a combination of individual and contextual factors plays a crucial role. Future interventions addressing ECD in Nigeria should consider these multidimensional influences to promote optimal child development.

3D printing of different fibres towards HA/PCL scaffolding induces macrophage polarization and promotes osteogenic differentiation of BMSCs

With the rise of bone tissue engineering (BET), 3D-printed HA/PCL scaffolds for bone defect repair have been extensively studied. However, little research has been conducted on the differences in osteogenic induction and regulation of macrophage (MPs) polarisation properties of HA/PCL scaffolds with different fibre orientations. Here, we applied 3D printing technology to prepare three sets of HA/PCL scaffolds with different fibre orientations (0–90, 0-90-135, and 0-90-45) to study the differences in physicochemical properties and to investigate the response effects of MPs and bone marrow mesenchymal stem cells (BMSCs) on scaffolds with different fibre orientations. The results showed that multi-angle staggered fibres affected the overall porosity and compressive strength of the scaffolds. Compared with the other two groups, the 0-90-45 scaffold induced osteogenic differentiation of BMSCs more significantly, while promoting the polarisation of MPs towards the M2 phenotype to form an osteogenic-friendly immune microenvironment. Unexpectedly, the 0-90-45 scaffold significantly upregulated the expression of angiogenic genes (PDGF, VEGF). Therefore, we conclude that the multi-angle interlaced fibres better mimic the physiological structure of cancellous bone, and that the excellent biomimetic properties reflect the best in vitro osteogenic, immunomodulatory and angiogenic effects. In conclusion, this study is a step forward in the exploration of BET scaffolds and provides a very promising bone filling material.

Inpatient service utilization amongst infants diagnosed with Respiratory Syncytial Virus infection (RSV) in the United States

Introduction Respiratory syncytial virus (RSV) is the leading cause of hospitalization among US infants. Characterizing service utilization during infant RSV hospitalizations may provide important information for prioritizing resources and interventions. Objective The objective of this study was to describe the procedures and services received by infants hospitalized during their first RSV episode in their first RSV season, in addition to what proportion of infants died during this hospitalization. Methods In this retrospective observational study, we analyzed three different administrative claims datasets to examine healthcare service utilization during RSV hospitalizations among infants. The study population included infants born between July 2016 and February 2020 who experienced an RSV episode during their first RSV season and had an associated inpatient hospitalization. We stratified infants into three comorbidity groups: healthy term, palivizumab-eligible, and other comorbidities. Outcomes included extracorporeal membrane oxygenation, supplemental oxygen use (in-hospital and post-discharge), mechanical ventilation (invasive and non-invasive), chest imaging, infant mortality, length of inpatient stay, intensive care unit (ICU) admission, and number of days in the ICU. Results Chest imaging was the most frequently administered procedure during RSV-associated hospitalizations, with approximately 34–38% of infants receiving it. Around one-quarter of infants were admitted to the ICU during their first RSV hospitalization. Median lengths of stay in the hospital were 3–4 days, extending to 4–6 days in the presence of ICU admission. Palivizumab-eligible infants had higher utilization of healthcare services and spent more time in the hospital or ICU compared to healthy infants or those with other comorbidities. Conclusions This study provides insights into the utilization of healthcare services during RSV hospitalizations among infants. Understanding service utilization patterns can aid in improved management and resource allocation for infants in the United States, ultimately contributing to better outcomes and reduced healthcare costs overall. However, likely under-ascertainment of ventilation and oxygen-related services in insurance claims remains an impediment to studying these outcomes.

Spectral study of COVID-19 pandemic in Japan: The dependence of spectral gradient on the population size of the community

We have carried out spectral analysis of coronavirus disease 2019 (COVID-19) notifications in all 47 prefectures in Japan. The results confirm that the power spectral densities (PSDs) of the data from each prefecture show exponential characteristics, which are universally observed in the PSDs of time series generated by nonlinear dynamical systems, such as the susceptible/exposed/infectious/recovered (SEIR) epidemic model. The exponential gradient increases with the population size. For all prefectures, many spectral lines observed in each PSD can be fully assigned to a fundamental mode and its harmonics and subharmonics, or linear combinations of a few fundamental periods, suggesting that the COVID-19 data are substantially noise-free. For prefectures with large population sizes, PSD patterns obtained from segment time series behave in response to the introduction of public and workplace vaccination programs as predicted by theoretical studies based on the SEIR model. The meaning of the relationship between the exponential gradient and the population size is discussed.

Communication needs regarding heart failure trajectory and palliative care between patients and healthcare providers: A cross-sectional study

Introduction Heart failure (HF) is a chronic condition with an unpredictable trajectory, making effective communication between patients and healthcare providers crucial for optimizing outcomes. This study aims to investigate and compare the communication needs regarding HF trajectory and palliative care between patients and healthcare providers and to identify factors associated with the communication needs of patients with HF. Methods A cross-sectional study design was employed, involving 100 patients with HF and 35 healthcare providers. Data were collected using structured questionnaires assessing communication needs, health literacy, self-care behavior, and social support. Statistical analyses were performed, including Spearman’s rank correlation, Pearson’s correlation, and multiple regression analyses. Results Patients prioritized communication related to device-related questions, whereas healthcare providers focused more on aspects of HF in daily life. Both groups ranked end-of-life communication as the lowest priority. The communication needs of patients were positively correlated with health literacy (r = 0.27, p = .007), self-care behavior (r = 0.32, p = .001), and social support (r = 0.24, p = .016). Multiple regression analyses indicated that self-care behavior was a significant factor influencing the communication needs of patients (β = 0.27, p = .011). Conclusions Enhanced patient-centered communication strategies are required to address the communication priority gaps between patients and healthcare providers. Improving health literacy, supporting self-care behaviors, and leveraging social support are critical in meeting patients’ communication needs. Tailored communication training for healthcare providers can bridge this gap and improve overall HF management.

Rural Roads to cognitive Resilience (RRR): A prospective cohort study protocol

Background Ambient air pollution, detrimental built and social environments, social isolation (SI), low socioeconomic status (SES), and rural (versus urban) residence have been associated with cognitive decline and risk of Alzheimer’s disease and related dementias (ADRD). Research is needed to investigate the influence of ambient air pollution and built and social environments on SI and cognitive decline among rural, disadvantaged, ethnic minority communities. To address this gap, this cohort study will recruit an ethnoracially diverse, rural Florida sample in geographic proximity to seasonal agricultural burning. We will (1) examine contributions of smoke-related fine particulate matter (PM 2.5 ) exposures to SI and cognitive function; (2) determine effects of built and social environments on SI and cognitive function; and (3) contextualize SI and cognitive function among residents from different ethnoracial groups during burn and non-burn seasons. Methods We will recruit 1,087 community-dwelling, dementia-free, ≥45-year-olds from five communities in Florida’s Lake Okeechobee region. Over 36 months, participants will complete baseline visits to collect demographics, health history, and health measurements (e.g., blood pressure, body mass index) and 6-month follow-ups assessing cognitive function and social isolation at each visit. A subsample of 120 participants representative of each community will wear smartwatches to collect sensor data (e.g., heart rate) and daily routine and predefined activities (e.g., GPS-captured travel, frequent destinations) over two months. Ecological momentary assessments (EMA) (e.g., whether smoke has bothered participant in last 30 minutes) will occur over two months during agricultural burning and non-burning months. PurpleAir monitors (36 total) will be installed in each community to continuously monitor outdoor PM 2.5 levels. Discussion We expect to identify individual- and community-level factors that increase the risk for SI and cognitive decline in a vulnerable rural population.

Molecular epidemiology and phylogenetic insights of lumpy skin disease in cattle from diverse agro-ecological regions of Punjab, Pakistan

Lumpy skin disease (LSD) is an emerging, highly contagious transboundary disease of bovines caused by the Lumpy skin disease virus (LSDV), responsible for substantial economic losses to the dairy, meat, and leather industries in Pakistan as well as various countries around the world. Epidemiological information on LSD is scarce in Punjab, Pakistan. Therefore, a molecular epidemiological study was conducted in two agro-ecologically diverse districts (Bhakkar and Jhang) of Punjab, Pakistan. A total of 800 blood samples were randomly collected from the jugular vein of clinically suspected cattle with nodular lesions using a multistage cluster sampling technique. The sampling unit was indigenous, crossbred, and exotic breeds of cattle. Four hundred samples were collected from each district. Ten union councils (UC) were selected from each district, and two villages were selected from each union council. From each village, twenty cattle were selected for sample collection. The PCR-based overall prevalence of LSDV in clinically suspected cattle using the P32 gene was 36.25% (36.25%; 290/800). The multivariable logistic regression analysis indicated that animals who were not treated with acaricide (P = 0.014; OR = 1.459; C.I = 1.079–1.972), body condition score (emaciated animals; P = 0.019; OR = 1.573; CI = 1.076–2.301), and gender (female; (P = 0.016; OR = 1.435; CI = 1.072–1.969) were significantly at higher risk for LSDV infection in cattle. The phylogenetic insights revealed that our isolates were linked to Kenya, China, Russia, Egypt, India, Zimbabwe, Iraq, and Iran. It can be concluded that LSD is widely distributed in the study area, with evidence of genetic diversity. Further studies are required on genetic composition using variable genetic markers for effective control and eradication of LSDV in Pakistan.

Modulation pattern recognition method of wireless communication automatic system based on IABLN algorithm in intelligent system

The aim of this study is to address the limitations of convolutional networks in recognizing modulation patterns. These networks are unable to utilize temporal information effectively for feature extraction and modulation pattern recognition, resulting in inefficient modulation pattern recognition. To address this issue, a signal modulation recognition method based on a two-way interactive temporal attention network algorithm has been developed. A two-way interactive temporal network is designed on the basis of the long and short-term memory network with the objective of enhancing the contextual connection of the temporal network. The output of the temporal network is attentively weighted using the soft attention mechanism. The proposed algorithm exhibited enhanced overall, average, and maximum recognition rates at varying signal-to-noise ratios, with an increase of 10.34%, 8.33%, and 3.33%, respectively, in comparison to other algorithms within the Radio Machine Learning (RML) 2016.10b dataset. Furthermore, the modulated signal recognition accuracy was as high as 92.84%, with an average increase in the Kappa coefficient of 12.28%. The Kappa coefficient in the Communication Signal Processing Benchmark for Machine Learning (CSPB.ML2018) 2018 dataset was 0.62, representing an average increase of 10.32% over other algorithms. The results demonstrate that the proposed recognition method can enhance the network’s accuracy in recognizing modulated signals. Moreover, it has potential applications in modulation pattern recognition in automatic systems for wireless communications.

Critical behavioral traits foster peer engagement in Online Mental Health Communities

Online Mental Health Communities (OMHCs), such as Reddit, have witnessed a surge in popularity as go-to platforms for seeking information and support in managing mental health needs. Platforms like Reddit offer immediate interactions with peers, granting users a vital space for seeking mental health assistance. However, the largely unregulated nature of these platforms introduces intricate challenges for both users and society at large. This study explores the factors that drive peer engagement within counseling threads, aiming to enhance our understanding of this critical phenomenon. We introduce BeCOPE, a novel behavior encoded Peer counseling dataset comprising over 10, 118 posts and 58, 279 comments sourced from 21 mental health-specific subreddits. The dataset is annotated using three major fine-grained behavior labels: (a) intent, (b) criticism, and (c) readability, along with the emotion labels. Our analysis indicates the prominence of “self-criticism” as the most prevalent form of criticism expressed by help-seekers, accounting for a significant 43% of interactions. Intriguingly, we observe that individuals who explicitly express their need for help are 18.01% more likely to receive assistance compared to those who present “surveys” or engage in “rants.” Furthermore, we highlight the pivotal role of well-articulated problem descriptions, showing that superior readability effectively doubles the likelihood of receiving the sought-after support. Our study emphasizes the essential role of OMHCs in offering personalized guidance and unveils behavior-driven engagement patterns.

Daily briefing: The science behind the deadly Los Angeles firestorm

A discrete choice experiment with health professions trainees to improve the urban-rural health care access disparity in Appalachia: Study protocol

Globally, those who live in rural areas experience significant barriers to accessing health care due to a maldistribution of health care providers. Those who live in rural areas in the Appalachian region of the United States face one of the worst shortages of health care providers despite experiencing more complex health needs compared to Americans in more affluent, urban areas. Prior research has failed to identify effective solutions to narrow the provider maldistribution, despite it being a policy focus for decades. More work is needed to better understand the complex, multidimensional process in which health care providers select jobs and how job, community, and providers’ intrapersonal characteristics influence job selection. This paper is a protocol for a study aimed at identifying effective policies and incentives to improve recruitment of healthcare providers for their first job in rural Appalachia. We will use rigorous, theoretically grounded discrete choice experiment methodology (DCE) to accomplish the study’s objective. The main outcome will be the relative importance of alternative community and job characteristics for trainees’ choices of jobs in rural Appalachia. secondary outcomes of interest will be trade-offs that these trainees make when selecting a job, described in the form of marginal rates of substitution (mRS). Participants include medical residents and fellows, PA students and NP students in their final year of training. The choice context will be the recruitment of these trainees for their first job. Data will be analyzed using mixed logit analysis. Results from this DCE will improve our understanding of the job selection process for health care providers. The identification and prioritization of predictors of trainees’ rural job choices will allow for the development of policies and incentives that will enable policymakers and health care systems to recruit more providers to rural and underserved areas.

Enhancing covert communication in NOMA systems with joint security and covert design

The explosion of Internet-of-Thing enables several interconnected devices but also gives rise chance for unauthorized parties to compromise sensitive information through wireless communication systems. Covert communication therefore has emerged as a potential candidate for ensuring data privacy in conjunction with physical layer transmission to render two lines of defense. In this paper, we aim to enhance the individual transmission of nearby users in non-orthogonal multiple access (NOMA) systems under scenarios of an eavesdropper who monitors covert transmission before decoding covert information. For this problem, we first provide a comprehensive analysis of the NOMA system in terms of outage probability (OP), secrecy outage probability (SOP), and detection error probability (DEP), where all of them are quantified in exact and asymptotic closed-form expressions. Besides, we have also derived closed-form formulas for users’ covert and public rates. Under the system requirements of the maximal OP and SOP and the minimal DEP, we formulate the optimization of resource power allocation to: 1) minimize the OP of covert communication and 2) maximize the covert rate. Thanks to the developed analytical expressions, we obtain closed-form expressions for the sub-optimal power allocation coefficient for each problem. Simulation results validate the efficacy of the analytical mathematical frameworks and reveal that the proposed approaches of power allocation can provide attractive performance improvement compared to fixed power allocations only.

Shaping sustainable perceptions: The role of metaphors in Olympic news discourse

The dissemination of sustainable development concepts in large international events like the Olympics has garnered great attention. As a major international sports event, the Beijing Winter Olympics served as an important platform for showcasing China’s sustainable development philosophy through its official news coverage. In this context, metaphor, as a powerful cognitive tool, plays a crucial role in shaping public perception and facilitating the dissemination of values by mapping concrete source domains onto abstract target domains. This paper constructs a critical metaphor analysis framework for sustainable development, analyzing the mechanisms by which metaphors map the concepts of social, economic, and ecological sustainability, and their multifaceted roles in conveying policy proposals, ideologies, cultural values, and social group behaviors. The findings indicate that metaphors effectively facilitate public understanding of sustainability by concretizing abstract concepts. In the social dimension, metaphors emphasize fairness, cultural diversity, and social solidarity; in the economic dimension, they highlight resource recycling, technological innovation, and industrial upgrading; while in the ecological dimension, the focus is on environmental protection and the harmonious coexistence of humanity and nature. Metaphors play a crucial role in shaping public perceptions of policy, reflecting specific values and socio-cultural contexts, facilitating cultural communication and understanding, and enhancing public responsibility and participation awareness.

Association between depression and the prevalence and prognosis of prediabetes: Data from National Health and Nutrition Examination Survey (NHANES) 2013–2018

Background Diagnosis and intervention of prediabetes is an emerging approach to preventing the progression and complications of diabetes. Inflammatory factors and dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis have been suggested as potential mechanisms underlying the pathogenesis of both diabetes and depression. However, the relationship between depression levels and the prevalence of prediabetes and its prognosis remains elusive. This study aimed to explore the relationship between depression and the prevalence of prediabetes and to further explore the all-cause mortality of different levels of depression in patients with prediabetes. Methods Our study used a data set from the National Health and Nutrition Examination Survey (NHANES). Participants were initially divided into two groups (depression vs. non-depression) and further stratified by different depression severity levels. We used a weighted multiple logistic regression model to analyze the association between depression and prediabetes prevalence and a Cox regression model to assess all-cause mortality in prediabetic patients. Results A total of 4384 participants were included, divided into depression group (n = 1379) and non-depression group (n = 3005). Results showed that people with depression were at higher risk of developing prediabetes. After adjusting for covariates, moderate to severe depression was positively associated with prediabetes (moderate to severe depression vs no depression: OR = 1.834, 95%CI: 0.713–4.721; severe depression vs no depression: OR = 1.004, 95% CI 0.429–2.351). In addition, we explored the relationship between all-cause mortality and depressive status in patients diagnosed with prediabetes (n = 2240) and found that moderate to severe depression (HR = 2.109, 95%CI 0.952–4.670) was associated with higher mortality in patients with prediabetes. Conclusions Overall, the findings consistently suggest that depression is positively associated with both the prevalence and mortality risk among individuals with prediabetes. This suggests that depression may be a new and valuable indicator of prediabetes risk. Early treatment of depression improves outcomes in prediabetes.