Background: Critically ill patients after Intensive Care Unit (ICU) discharge may present disability in their cognitive and physical functions. Objectives: To investigate the quality of life (QoL) of both COVID-19 and non-COVID-19 patients following ICU discharge, lung function, and physical performance of participants. Methods: This study was prospective and conducted between 2020 and 2021 in the “X” hospital. If patients were Mechanically-Ventilated (MV) > 48 h, they were included. Results: Fifty COVID-19 and seventy-two non-COVID-19 participants were included in this study. The mean (SD) of the total SF-36 scores at COVID-19 patients at hospital discharge and 3 and 12 months were 46.5 (14.5), 68.6 (17.8), and 82.3 (8.9) (p < 0.05), while non-COVID-19 participants were 48.5 (12.1), 72.2 (9.9), and 82.7 (5.4) (p < 0.05). The forced expiratory volume in one second (FEV1) and 6-minute walking distance (6MWD) were assessed at 3 and 12 months and significantly improved over 12 months. Conclusion: The QoL of COVID-19 patients improved significantly over time as FEV1 and 6MWD. Full article

Background: Risk factors for severe dengue manifestations have been attributed to various factors, including specific serotypes, sex, and age. Mexico has seen the re-emergence of DENV-3, which has not circulated in a decade. Objective: To describe dengue serotypes by age, sex, and their association with disease severity in dengue-positive serum samples from epidemiological surveillance system units. Materials and Methods: A descriptive analysis was conducted to evaluate the frequency of dengue severity by sex, age, disease quarter, geographical location, and dengue virus serotypes. The study was conducted using laboratory samples from confirmed dengue cases through RT-qPCR from the epidemiological surveillance laboratory network of the Mexican Social Security Institute, Mexico. Simple frequencies and proportions were calculated using the z-test for proportional differences between groups. Bivariate analysis with adjusted Chi2 was performed, and binary logistic regression models were constructed using the forward Wald method considering the model’s predictive capacity. The measure of association was the odds ratio, with 95% confidence intervals. Statistical significance was set to an alpha level of <0.05. Results: In 2023, 10,441 samples were processed for dengue RT-qPCR at the IMSS, with a predominance of serotype DENV-3 (64.4%). The samples were mostly from women (52.0%) and outpatient cases (63.3%). The distribution of dengue severity showed significant variations by age, with a lower proportion of severe cases in young children and a higher proportion in the 5- to 14-year-old group. Hospitalizations increased significantly with severity. Warm regions had more cases overall and severity. Cases were most frequent from July to September. While DENV-2 was associated with severity, DENV-4 was not. Binary regression identified higher risk in women, age extremes, and DENV-2, with an overall predictive model of 58.5%. Conclusions: Women, age groups at the extremes of life, and the DENV-2 serotype presented severe risk of dengue in a population with social security in Mexico during 2023. Full article

Excessive pressure drop within the internal flow channel of the water hydraulic throttle valve will generate severe noise. In order to reduce the noise of the throttle valve, in this paper, the model of the throttle valve was established, and the flow characteristics and acoustic characteristics of the valve were simulated. The simulation results showed that the parameters of the throat structure, such as the half angle, throat inlet angle and throat length, have a significant effect on the noise of the valve. Then, the three main structural parameters were used as optimization variables, and radial basis function (RBF) neural networks and multi-island genetic algorithms (MIGA) were used to reduce the noise of the valve. The approximate model of the relationship between the structural parameters of the valve and noise was established by RBF neural networks, and MIGA was used to optimize the approximate model. Finally, the optimal valve model was established based on the obtained optimal parameters, and its noise was analyzed through simulation and experiment. The research results indicated that the optimization method, which combines RBF Neural Network and MIGA, can effectively reduce the noise of hydraulic throttle valves. Full article

Graphene hybrid-filler polymer composites have emerged as prominent materials that revolutionize heavy industries. This review paper encapsulates an in-depth analysis of different influential factors, such as filler/graphene type, aspect ratios, dispersion methods, filler-matrix compatibility, fiber orientation, synergistic effects, different processing techniques, and post-curing conditions, which affect the processing and properties of graphene hybrid polymer composites, as well as their resultant applications. Additionally, it discusses the substantial role of graphene reinforcement with other fillers, such as carbon nanotubes, silica, nano-clays, and metal oxides, to produce functionalized hybrid polymer composites with synergistically enhanced tailored properties, offering solutions for heavy industries, including aerospace, automotive, electronics, and energy harvesting. This review concludes with some suggestions and an outlook on the future of these composite materials by emphasizing the need for continued research to fully optimize their potential. Full article

World conferences on higher education have reported the effect of social changes on university systems. Particularly, changes that induce a transformation in the academic profession. Here, we study the paradigm shift of the profession in its dimensions, trends, and future scenarios. We conduct this study in two phases: first, we applied an inventory on the perception of university teaching to a sample of 2312 professors in the region; after that, we conducted a focus group for each of the ten dimensions in which we noticed indicators of change. With the quantitative data, we performed an ANOVA to identify three clusters of professionalization with dimensions open to change and related to each other: (1) Planning, Teaching Development, and Communicative Capacity; (2) Communication, Evaluation, and Self-evaluation; (3) Professional Self-evaluation, Teaching Innovation and Improvement and Individual Learning Support. With the focus groups we have identified the need to incorporate pedagogical models of inclusive education and teaching based on technological advances as the main drivers of change. We concluded with the proposal of four possible scenarios of future professionalism: (1) entrenched professionalism; (2) semi-professionalism; (3) fragmented professionalism; or (4) balanced professionalism. Full article

Efficiently predicting and understanding refuelling patterns in the context of HFVs is paramount for optimising fuelling processes, infrastructure planning, and facilitating vehicle operation. This study evaluates several supervised machine learning methodologies for predicting the refuelling behaviour of HFVs. The LightGBM model emerged as the most effective predictive model due to its ability to handle time series and seasonal data. The selected model integrates various input variables, encompassing refuelling metrics, day of the week, and weather conditions (e.g., temperature, precipitation), to capture intricate patterns and relationships within the data set. Empirical testing and validation against real-world refuelling data underscore the efficacy of the LightGBM model, demonstrating a minimal deviation from actual data given limited data and thereby showcasing its potential to offer valuable insights to fuelling station operators, vehicle manufacturers, and policymakers. Overall, this study highlights the potential of sustainable predictive modelling for optimising fuelling processes, infrastructure planning, and facilitating vehicle operation in the context of HFVs. Full article

This article reported on the effect of Cu-content and sintering temperature on the magnetic permeability and power losses of monolithic iron-deficient NiCuZn-ferrite components with low Cu-contents aimed to be used for power applications at frequencies up to 1 MHz. In particular $\left[{\left({\mathrm{N}\mathrm{i}}_{\mathsf{\alpha }}{\mathrm{Z}\mathrm{n}}_{\mathrm{b}}\right)}_{1-\mathrm{x}}{\mathrm{C}\mathrm{u}}_{\mathrm{x}}\right]{\mathrm{F}\mathrm{e}}_{1.9}{\mathrm{O}}_4$ ferrite compositions are investigated with a constant Ni/Zn atomic ratio a/b = 0.9 and 0 < x < 0.017. As found, the addition of Cu enables the achievement of good magnetic performance at lower sintering temperatures and, therefore, lower production cost. At all Cu-contents, the initial permeability as a function of the sintering temperature passes through a maximum above which structural deterioration due to asymmetric grain growth occurs. The temperature at which this maximum permeability occurs depends on the Cu content and coincides with the achievement of the maximum density of 5.1–5.2 g cm⁻³ (relative density ~97%). At Cu-contents x = 0.006–0.012 and sintering temperatures 1200–1100 °C power losses (tan(δ)/μ at 1 MHz, 25 °C) οf 50 × 10⁻⁶ could be achieved and initial permeabilities (10 kHz, 0.1 mT, 25 °C) of around 400 with very good frequency and temperature stability. At CuO content higher than 4 wt.% (i.e., x > 0.012) and sintering temperatures higher than 1150 °C, pronounced microstructural disturbances due to asymmetric grain growth result in low permeabilities and high losses. It is suggested that at low CuO contents and low sintering temperatures, the densification enhancement may not proceed through Cu-rich phase segregation but through the creation of oxygen vacancies. Full article

Background: Although metastatic hormone-sensitive prostate cancer (mHSPC) treatments have evolved, androgen deprivation therapy (ADT) remains a widely used regimen. Therefore, this study sought patients who did not progress to castration-resistant prostate cancer (CRPC) but received ADT monotherapy and factors affecting overall survival (OS) in de novo mHSPC. Methods: De novo mHSPC patients who received ADT treatment were included. ADT included luteinizing hormone-releasing hormone agonists with or without anti-androgen. The total cohort was divided into two groups relative to CRPC progression within two years. Logistic analysis was used to identify factors that did not progress CRPC within two years. Cox regression was used to assess the independent predictors for OS. Results: The total cohort was divided into the no-CRPC within two years group (n = 135) and the CRPC within two years group (n = 126). Through multivariate logistic analysis, the life expectancy (odds ratio [OR] 0.95, 95% CI 0.91–0.99, p = 0.014) and Gleason scores (≥9 vs. ≤8; OR 0.43, 95% CI 0.24–0.75, p = 0.003) were associated with the group without castration-resistant prostate cancer progression within two years. The multivariate Cox model revealed that life expectancy (hazard ratio [HR] 0.951, 95% CI 0.904–0.999, p = 0.0491), BMI (HR 0.870, 95% CI 0.783–0.967, p = 0.0101), and CCI (≥2 vs. <2; HR 2.018, 95% CI 1.103–3.693, p = 0.0227) were significant predictive factors for OS. Conclusions: Patients with long life expectancy and a Gleason score of 9 or more were more likely to develop mCRPC while alive. Patients with short life expectancy, low BMI, and worsening comorbidity were more likely to die before progressing to CRPC. Although intensified treatment is essential for oncologic outcomes in mHSPC, shared decision making is integral for patients who may not benefit from this treatment. Full article

This work introduces a generalized version of the pulse width modulation (PWM) switch model applied in the small-signal modeling of converters based on the multistate switching cell (MSSC) operating in discontinuous conduction mode (DCM). It consists of extending the concept formerly introduced by Vorperian for the representation of multiphase converters in DCM, yielding a circuit-based approach that does not rely on matrix manipulations unlike state-space averaging (SSA). The derived dc and ac models are valid for any number of switching states and any operating region defined in terms of the duty cycle, thus allowing for determining the voltage gain and distinct transfer functions. A thorough discussion of results is presented to demonstrate the applicability of the derived models to represent distinct configurations of the MSSC. Full article

Addressing the current issue of limited control methods for badminton serving devices, this paper proposes a vision-based multimodal control system and method for badminton serving. The system integrates computer vision recognition technology with traditional control methods for badminton serving devices. By installing vision capture devices on the serving device, the system identifies various human body postures. Based on the content of posture information, corresponding control signals are sent to adjust parameters such as launch angle and speed, enabling multiple modes of serving. Firstly, the hardware design for the badminton serving device is presented, including the design of the actuator module through 3D modeling. Simultaneously, an embedded development board circuit is designed to meet the requirements of multimodal control. Secondly, in the aspect of visual perception for human body recognition, an improved BlazePose candidate region posture recognition algorithm is proposed based on existing posture recognition algorithms. Furthermore, mappings between posture information and hand information are established to facilitate parameter conversion for the serving device under different postures. Finally, extensive experiments validate the feasibility and stability of the developed system and method. Full article

Hitherto, over 50% of countries with marine waters have established MSPs or launched related legal actions. However, there are still conceptual and practical challenges to be overcome in the development of MSP. In this study, we investigate two main approaches in MSP (hard vs. soft sustainability) through reports, published manuscripts and meeting proceedings in seven pioneering countries (Belgium, Netherlands, Norway, Germany, United Kingdom, Australia, and Canada). We highlight the gaps, challenges, and solutions in each of these approaches. From our findings, there are four common challenges in both soft and hard sustainability approaches as follows: (i) the political framework and inconsistent support of MSP efforts, (ii) insufficient knowledge on social dimensions, (iii) insufficient stakeholder engagement in the diversity of stakeholder’s groups or in their contribution to the planning process from the initial steps, and (iv) finding a balance between environmental conservation and economic growth. We recommend that future studies should investigate how MSP can become more adaptive to long-term environmental and economic targets, how effective involving socioeconomic strata is in MSP, and how decision-making tools could help to cover the gaps in MSP. Furthermore, public forums are suggested to be developed to facilitate the systematic sharing of MSP experiences worldwide. Full article

Deep learning models can enhance the detection efficiency and accuracy of rapid on-site screening for imported grains at customs, satisfying the need for high-throughput, efficient, and intelligent operations. However, the construction of datasets, which is crucial for deep learning models, often involves significant labor and time costs. Addressing the challenges associated with establishing high-resolution instance segmentation datasets for small objects, we integrate two zero-shot models, Grounding DINO and Segment Anything model, into a dataset annotation pipeline. Furthermore, we encapsulate this pipeline into a software tool for manual calibration of mislabeled, missing, and duplicated annotations made by the models. Additionally, we propose preprocessing and postprocessing methods to improve the detection accuracy of the model and reduce the cost of subsequent manual correction. This solution is not only applicable to rapid screening for quarantine weeds, seeds, and insects at customs but can also be extended to other fields where instance segmentation is required. Full article

Electrolytic plasma polishing (EPPo) is an advanced metal surface finishing technology with high quality and environmental protection that has broad application prospects in the biomedical field. However, the effect of EPPo on surface properties such as corrosion resistance and the wettability of biomedical titanium alloys remains to be investigated. This paper investigated the changes in surface roughness, surface morphology, microstructure, and chemical composition of Ti6Al4V alloy by EPPo and their effects on surface corrosion resistance, wettability, and residual stress. The results showed that Ra decreased from 0.3899 to 0.0577 μm after EPPo. The surface crystallinity was improved, and the average grain size increased from 251 nm to more than 800 nm. The oxidation behavior of EPPo leads to an increase in surface oxygen content and the formation of TiO₂ and Al₂O₃ oxide layers. EPPo can significantly improve the corrosion resistance and wettability of titanium alloy in simulated body fluid and eliminate the residual stress on the sample surface. The surface properties are enhanced not only by the reduction in surface roughness but also by the formation of a denser oxide film on the surface, changes in the microstructure, an increase in surface free energy, and the annealing effect developed during EPPo. This study can provide guidance and references for applying EPPo to biomedical titanium alloy parts. Full article

With the development of large-scale sky surveys, an increasing number of stellar photometric images have been obtained. However, most stars lack spectroscopic data, which hinders stellar classification. Vision Transformer (ViT) has shown superior performance in image classification tasks compared to most convolutional neural networks (CNNs). In this study, we propose an stellar classification network based on the Transformer architecture, named stellar-ViT, aiming to efficiently and accurately classify the spectral class for stars when provided with photometric images. By utilizing RGB images synthesized from photometric data provided by the Sloan Digital Sky Survey (SDSS), our model can distinguish the seven main stellar categories: O, B, A, F, G, K, and M. Particularly, our stellar-ViT-gri model, which reaches an accuracy of 0.839, outperforms traditional CNNs and the current state-of-the-art stellar classification network SCNet when processing RGB images synthesized from the gri bands. Furthermore, with the introduction of urz band data, the overall accuracy of the stellar-ViT model reaches 0.863, further demonstrating the importance of additional band information in improving classification performance. Our approach showcases the effectiveness and feasibility of using photometric images and Transformers for stellar classification through simple data augmentation strategies and robustness analysis of training dataset sizes. The stellar-ViT model maintains good performance even in small sample scenarios, and the inclusion of urz band data reduces the likelihood of misclassifying samples as lower-temperature subtypes. Full article

MF59 and AS03 are squalene emulsion-based vaccine adjuvants with similar compositions and droplet sizes. Despite their broad use in licensed influenza vaccines, few studies compared their adjuvant effects and action mechanisms side by side. Considering the majority of adjuvants act on dendritic cells (DCs) to achieve their adjuvant effects, this study compared MF59 and AS03-like adjuvants (AddaVax and AddaS03, respectively) to enhance antigen uptake, DC maturation, ovalbumin (OVA) and seasonal influenza vaccine-induced immune responses. Considering MF59 was reported to activate MyD88 to mediate its adjuvant effects, this study also investigated whether the above-explored adjuvant effects of AddaVax and AddaS03 depended on MyD88. We found AddaVax more potently enhanced antigen uptake at the local injection site, while AddaS03 more potently enhanced antigen uptake in the draining lymph nodes. AddaS03 but not AddaVax stimulated DC maturation. Adjuvant-enhanced antigen uptake was MyD88 independent, while AddaS03-induced DC maturation was MyD88 dependent. AddaVax and AddaS03 similarly enhanced OVA-induced IgG and subtype IgG1 antibody responses as well as influenza vaccine-induced hemagglutination inhibition antibody titers, whileAddaS03 more potently enhanced OVA-specific IgG2c antibody responses. Both adjuvants depended on MyD88 to enhance vaccine-induced antibody responses, while AddaVax depended more on MyD88 to achieve its adjuvant effects. Our study reveals similarities and differences of the two squalene emulsion-based vaccine adjuvants, contributing to our improved understanding of their action mechanisms. Full article

We aim to explore the prerequisites for corporate sustainability from the perspective of non-formal institutions such as culture. Specifically, we seek to investigate whether and how Chinese tea culture influences corporate social responsibility (CSR). We have developed an OLS regression model to examine the relationship between tea culture and CSR, and our findings indicate that local tea culture yields positive effects. To address endogeneity concerns related to this correlation, we employed the local geographic slope as an instrumental variable for tea culture. Subsequent research highlights that the female executive, serving as a mediator variable, represents the primary mechanism influenced by tea culture. Furthermore, our study demonstrates that tea culture exerts a more significant impact on small and medium-sized enterprises as well as state-owned enterprises. Overall, this research contributes to the literature on the determinants of CSR from the vantage point of informal institutions, offering a fresh perspective for exploring the economic ramifications of tea culture for both academia and practitioners. Moreover, it furnishes valuable insights for advancing the sustainable development of enterprises. Full article

Based on the assumption that the process of understanding is partly narrative, this study explores the potential benefits and limitations of using narrative writing in biology education. We investigate what contribution a student-centered narrative intervention can make to the conceptual understanding of protein biosynthesis in the context of viral infections and virus replication. After a teaching sequence on this topic, 68 secondary school students (M = 15.7 years, SD = 0.57 years) explained virus replication in a written text. One subsample (n = 46) was instructed to write a narrative text, while the other one (n = 22) was asked to write an expository (non-fictional) text. Our data analysis encompassed an analysis of the structural narrativity in the student texts, as well as a concept-related rating of the level of scientific correctness in three categories. A post-test questionnaire (35 items) was used to depict the learners’ viewpoints on their respective text production and the learning process that they experienced. Our findings indicate that most learners actually produced the text type they were supposed to, with exceptions in both sub-samples. As to the level of concept-related scientific correctness, we found no major differences between the two interventions. However, for two concepts, compartmentalization and levels of organization, the data indicate the significant advantage of the narrative intervention. We conclude from our results that to some extent, the effective learning properties of narrative texts, derived from the theoretical foundations, could indeed successfully be demonstrated in the field of virus replication. However, narrative text production is not equally beneficial for all aspects of the biological topic, and it also poses specific problems for some learners. Full article

Purpose: Given the emergence of PSMA-targeted diagnostic agents and therapeutics, we sought to investigate patterns of FOLH1 expression in RCC and their impacts on RCC outcomes. Methods: We conducted a pooled multi-institutional analysis of patients with RCC having undergone DNA and RNA next-generation sequencing. FOLH1-high/low expression was defined as the ≥75th/<25th percentile of RNA transcripts per million (TPM). Angiogenic, T-effector, and myeloid expression signatures were calculated using previously defined gene sets. Kaplan–Meier estimates were calculated from the time of tissue collection or therapy start. Results: We included 1,724 patients in the analysis. FOLH1 expression was significantly higher in clear cell (71%) compared to non-clear cell RCC tumors (19.0 versus 3.3 TPM, p < 0.001) and varied by specimen site (45% primary kidney/55% metastasis, 13.6 versus 9.9 TPM, p < 0.001). FOLH1 expression was correlated with angiogenic gene expression (Spearman = 0.76, p < 0.001) and endothelial cell abundance (Spearman = 0.76, p < 0.001). While OS was similar in patients with FOLH1-high versus -low ccRCC, patients with FOLH1-high clear cell tumors experienced a longer time on cabozantinib treatment (9.7 versus 4.6 months, respectively, HR 0.57, 95% CI 0.35–0.93, p < 0.05). Conclusions: We observed differential patterns of FOLH1 expression based on histology and tumor site in RCC. FOLH1 was correlated with angiogenic gene expression, increased OS, and a longer duration of cabozantinib treatment. Full article

Hirschsprung disease is a life-long condition that can have a significant impact on both children and their families. This article explores the role of the clinical nurse specialist and the support they can provide from initial diagnosis through the patient’s surgical journey and right through to transition into adult services. Through the provision of education, training, signposting of social and psychological support, and linking in with community-based services, the clinical nurse specialist can help the child and family to limit that impact of the disease. Full article

The development of sustainable biofuels can help to reduce the reliance on fossil fuels and mitigate the impact of climate change. This study analyzes bioethanol production from agro-forestry residual biomass, namely eucalyptus residues and corn stover. The study includes process simulation using Aspen Plus software, followed by economic analysis and life cycle assessment (LCA) with the help of SimaPro software and by applying the environmental footprint (EF) 3.0 method. The economic analysis on the biorefinery’s economic viability, equipment, and production costs reveals a positive decision for bioethanol production from eucalyptus residues due to logistical and transportation costs. The minimum ethanol selling price (MESP) obtained was 2.19 €/L and 2.45 €/L for eucalyptus residues and corn stover, respectively. From the LCA with a functional unit of 1 MJ of ethanol, bioethanol production from eucalyptus residues results in a single score impact of 37.86 µPt, whereas for corn stover, it is 33.47 µPt. In the climate change impact category, the eucalyptus residues scenario has an impact of 0.264 kg CO₂ eq/MJ ethanol while corn stover leads to 0.254 kg CO₂ eq/MJ ethanol. In-situ enzyme production, heat integration, and the use of renewable energy sources were also analyzed. Combining in situ enzyme production with renewable energy sources lowers CO₂ equivalent emissions by 89% for both feedstocks, in comparison to the base-case scenario. Full article

This paper presents a summary of and introduction to research on high-altitude and subatmospheric combustion concerning turbine and scramjet engines. The investigation includes theoretical analysis, experimental studies, and numerical simulations. The analysis encompasses the flow field structure, fuel atomization, and combustion performance. Subsequently, recent research on the combustion performance of liquid fuels, solid fuels, and gaseous fuels under high-altitude and low-pressure plateau environments is reviewed. This includes an evaluation of flame height, flame temperature, combustion rate, fire spread rate, and heat radiation flux. Additionally, combustion performance prediction models for high-altitude environments based on experimental and theoretical analysis have been introduced. Lastly, issues in subatmospheric combustion in the aerospace and plateau fire fields are presented based on the current research. Full article

Daratumumab is being increasingly integrated into first-line multiple myeloma (MM) induction regimens, leading to improved response depth and longer progression-free survival. Autologous stem cell transplantation (ASCT) is commonly performed as a consolidation strategy following first-line induction in fit MM patients. We investigated a cohort of 155 MM patients who received ASCT after first-line induction with or without daratumumab (RVd, n = 110; D-RVd, n = 45), analyzing differences in stem cell mobilization, apheresis, and engraftment. In the D-RVd group, fewer patients successfully completed mobilization at the planned apheresis date (44% vs. 71%, p = 0.0029), and more patients required the use of rescue plerixafor (38% vs. 28%, p = 0.3052). The median count of peripheral CD34+ cells at apheresis was lower (41.37 vs. 52.19 × 10⁶/L, p = 0.0233), and the total number of collected CD34+ cells was inferior (8.27 vs. 10.22 × 10⁶/kg BW, p = 0.0139). The time to recovery of neutrophils and platelets was prolonged (12 vs. 11 days, p = 0.0164; and 16 vs. 14 days, p = 0.0002, respectively), and a higher frequency of erythrocyte transfusions (74% vs. 51%, p = 0.0103) and a higher number of platelet concentrates/patients were required (4 vs. 2; p = 0.001). The use of daratumumab during MM induction might negatively impact stem cell mobilization and engraftment in the context of ASCT. Full article