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Tunable oxygen vacancy diffusion and electronic conduction through strain engineering in PZT films

Effect of individualized PEEP on lung ultrasound score and optic nerve sheath diameter in elderly patients undergoing laparoscopic rectal cancer surgery: A randomized controlled trial

Objective Positive end-expiratory pressure (PEEP) is widely used during surgery, but its effects on lung and brain protection remain debated. This study aimed to evaluate the impact of individualized PEEP on lung ultrasound score (LUS) and optic nerve sheath diameter (ONSD) in elderly patients undergoing laparoscopic rectal cancer surgery. Methods Forty-six patients aged 60–79 years undergoing laparoscopic rectal tumour resection between June 2022 and December 2022 were randomized into two groups: Group E (individualized PEEP guided by driving pressure) and Group C (control group, PEEP = 5 cm H2O). LUS was assessed 30 minutes postoperatively. ONSD was measured at 5 minutes before anesthesia induction (T0), 5 minutes after tracheal tube insertion (T1), 5 and 60 minutes after Trendelenburg positioning (T2, T3), and 30 minutes postoperatively (T4). Arterial oxygen index (OI) and arterial partial pressure of carbon dioxide (PaCO2) were recorded post-intubation and pre-extubation. Postoperative pulmonary and neurological complications were followed up. Results Postoperative LUS was significantly lower in Group E than in Group C (P < 0.05). OI was significantly higher in Group E before extubation (P < 0.05). There were no significant differences in ONSD between groups. Within each group, ONSD values at T2 and T3 were significantly higher than those at T0 (P < 0.01). No significant differences were observed in the incidence of postoperative complications between the two groups. Conclusions During laparoscopic radical resection for rectal cancer, individualized PEEP reduces LUS scores, improves oxygenation, and does not increase ONSD values compared to fixed PEEP. Trial registration Chinese Clinical Trial Registry: ChiCTR2200060434.

Pupil size modulation drives retinal activity in mice and shapes human perception

Abstract Retinal adaptation is assisted by the pupil, with pupil contraction and dilation thought to prevent global light changes from triggering neuronal activity in the retina. However, we find that pupillary constriction from increased light, the pupillary light reflex (PLR), can drive strong responses in retinal ganglion cells (RGCs) in vivo in mice. The PLR drives neural activity in all RGC types, and pupil-driven activity is relayed to the visual cortex. Furthermore, the consensual PLR allows one eye to respond to luminance changes presented to the other eye, leading to a binocular response and modulation during low-amplitude luminance changes. To test if pupil-induced activity is consciously perceived, we performed psychophysics on human volunteers, finding a perceptual dimming consistent with PLR-induced responses in mice. Our findings thus uncover that pupillary dynamics can directly induce visual activity that is consciously detectable, suggesting an active role for the pupil in encoding perceived ambient luminance.

Sensitivity analysis of digital twin model for energy community PV system

Augmented secretary bird optimization algorithm for wireless sensor network deployment and engineering problem

This study develops an enhanced Secretary Bird Optimization Algorithm (ASBOA) based on the original Secretary Bird Optimization Algorithm (SBOA), aiming to further improve the solution accuracy and convergence speed for wireless sensor network (WSN) deployment and engineering optimization problems. Firstly, a differential collaborative search mechanism is introduced in the exploration phase to reduce the risk of the algorithm falling into local optima. Additionally, an optimal boundary control mechanism is employed to prevent ineffective exploration and enhance convergence speed. Simultaneously, an information retention control mechanism is utilized to update the population. This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). The results show that in the CEC2017 30-dimensional case, ASBOA performed best on 23 out of 30 functions; in the CEC2017 100-dimensional case, ASBOA performed best on 26 out of 30 functions; and in the CEC2022 20-dimensional case, it performed best on 9 out of 12 functions. Furthermore, the convergence curves and boxplot results indicate that ASBOA has faster convergence speed and robustness. Finally, ASBOA was applied to WSN problems and three engineering design problems (three-bar truss, tension/compression spring, and cantilever beam design). In the engineering problems, ASBOA consistently outperformed competing methods, while in the WSN deployment scenario, it achieved a coverage rate of 88.32%, an improvement of 1.12% over the standard SBOA. These results demonstrate that the proposed ASBOA has strong overall performance and significant potential in solving complex optimization problems. Although ASBOA performs well in these problems, its performance in high-dimensional multimodal problems and complex constrained optimization is unstable, and the introduced strategies add some complexity. Additionally, different parameter settings may lead to varying results, and the sensitivity of different problems to these parameters can also differ. It is necessary to adjust the settings according to the specific problem at hand in order to further refine and achieve a more stable version.

Iceberg-like pyramids in industrially textured silicon enabled 33% efficient perovskite-silicon tandem solar cells

Impedance shaping based stabilization control method for DC Micro-grid Feed-forward compensation

Abstract The ports of the bi-directional converter exhibit negative impedance characteristics when the energy storage unit of a DC microgrid is operating in charging mode. This can decrease the system’s stability margin, potentially leading to oscillation instability. To address this issue, we propose a feed-forward compensation control method based on impedance shaping. This involves designing a transfer function within the current feed-forward loop of the energy storage converter to ensure that the current reference value follows changes in the bus voltage. Selecting an appropriate time constant ensures that the port impedance of the energy storage unit exhibits a positive resistive characteristic close to the oscillation frequency while retaining a negative impedance characteristic in the low-frequency range. This ensures the stability of system operation. MATLAB/Simulink simulations and RT-LAB semi-physical platform testing have verified that the proposed control method effectively enhances the system’s stability margin, ensuring stable operation and minimal steady-state voltage deviation.

RETRACTED: LGD_Net: Capsule network with extreme learning machine for classification of lung diseases using CT scans

Lung diseases (LGDs) are related to an extensive range of lung disorders, including pneumonia (PNEUM), lung cancer (LC), tuberculosis (TB), and COVID-19 etc. The diagnosis of LGDs is performed by using different medical imaging such as X-rays, CT scans, and MRI. However, LGDs contain similar symptoms such as fever, cough, and sore throat, making it challenging for radiologists to classify these LGDs. If LGDs are not diagnosed at their initial phase, they may produce severe complications or even death. An automated classifier is required for the classification of LGDs. Thus, this study aims to propose a novel model named lung diseases classification network (LGD_Net) based on the combination of a capsule network (CapsNet) with the extreme learning machine (ELM) for the classification of five different LGDs such as PNEUM, LC, TB, COVID-19 omicron (COO), and normal (NOR) using CT scans. The LGD_Net model is trained and tested on the five publicly available benchmark datasets. The datasets contain an imbalanced distribution of images; therefore, a borderline SMOTE (BL_SMT) approach is applied to handle this problem. Additionally, the affine transformation methods are used to enhance LGD datasets. The performance of the LGD_Net is compared with four CNN-based baseline models such as Vgg-19 (D 1 ), ResNet-101 (D 2 ), Inception-v3 (D 3 ), and DenseNet-169 (D 4 ). The LGD_Net model achieves an accuracy of 99.71% in classifying LGDs using CT scans. While the other models such as D 1 , D 2 , D 3 , and D 4 attains an accuracy of 91.21%, 94.39%, 93.96%, and 93.82%, respectively. The findings demonstrate that the LGD_Net model works significantly as compared to D 1 , D 2 , D 3 , and D 4 as well as state-of-the-art (SOTA). Thus, this study concludes that the LGD_Net model provides significant assistance to radiologists in classifying several LGDs.

Dynamically urethra-adapted and obligations-oriented trilayer hydrogels integrate scarless urethral repair

Forecasting impacts of climate change on barking deer distribution in Pakistan

Correction: Recombinant cyclin B-Cdk1-Suc1 capable of multi-site mitotic phosphorylation in vitro

Healthcare-seeking intentions of middle-aged and elderly individuals with critical diseases: an expanded TPB model in the post-pandemic era

Emergency temporary standards and COVID-19 trends among Oregon farmworkers

Background During the COVID-19 pandemic, migrant and seasonal farmworkers were deemed essential due to their central roles in US agricultural operations. However, employer-provided housing and transportation conditions increased their risks of SARS-CoV-2 exposure, and some states implemented emergency temporary standards (ETSs) at the insistence of farmworker advocates. Despite numerous studies examining the effectiveness of policy interventions (e.g., workplace closures) for mitigating SARS-CoV-2 transmission, limited research has specifically examined the effectiveness of interventions aimed at protecting farmworkers from COVID-19. Methods We used an interrupted time series analysis to estimate how two ETSs and one executive order issued in Oregon impacted COVID-19 trends from March 1, 2020, to February 27, 2021, for the overall population and among agricultural labor groups in Oregon. Results Our models show that the ETS and executive order, which specifically targeted farmworker housing, transportation, and worksites, did not demonstrate any significant effects on the numbers of COVID-19 cases or associated deaths. However, the other ETS, which targeted all workplaces, was associated with statistically significant decreases in COVID-19 cases among the general population (−142.36214, p-value<0.0001), producers (−1.67128, p-value = 0.0009), hired workers (−2.39413, p-value = 0.0014), unpaid workers (−1.01572, p-value = 0.0003), and migrant workers (−0.60017, p-value = 0.0166). None of the three policy changes were found to have any statistically significant impacts on the numbers of COVID-19–associated deaths. Conclusions The ETS targeting all workplaces was more effective for reducing COVID-19 transmission than the ETS or executive order specifically targeting farmworkers, indicating that the design, communication, and implementation of ETSs targeting farmworkers should be re-evaluated.

Comparative analysis of reproductive health knowledge and practices of female college students in Xinjiang medical and non-medical majors in 2023

Mental health concerns and needs of international students in higher education settings: A scoping review protocol

Introduction The transition to higher education is a significant milestone for many individuals; however, it also brings new stressors and challenges, particularly for international students adjusting to life in a foreign country. Despite the increasing diversity of student populations globally, there remains a gap in existing reviews that capture the full scope of international student mental health concerns and needs. Existing reviews on the mental health and psychosocial adjustment of international students often concentrate on acculturation stress, thus overlooking other mental health concerns such as depression and anxiety, as well as positive mental health experiences like increased well-being. Meanwhile, other reviews tend to focus more heavily on specific regions, such as the United States and Australia, or student populations, particularly East-Asian students. While valuable, this focus may limit our understanding of the diverse mental health experiences of international students. Objective The objective of this scoping review is to map and summarize research on international students’ mental health experiences and concerns (e.g., depression) as well as factors influencing their well-being (e.g., social support and institutional resources). Methods A search strategy guided by the Joanna Briggs Institute (JBI) Manual of Evidence Synthesis has been developed according to the Population, Concern, and Context (PCC) framework and will be applied to four electronic databases (i.e., MEDLINE, Embase, PsycInfo, and CINAHL). Two reviewers will pilot the selection strategy on subsets of 10 articles until a 90% agreement rate is achieved. Once this rate is reached, a single reviewer will screen the remaining articles independently. Two reviewers will pilot data extraction on subsets of 10 included studies, after which one reviewer will proceed independently. Main findings will be presented through descriptive statistics, using tables and figures. Expected contributions This scoping review will assess existing literature on the mental health needs and experiences of international students, highlighting overlooked issues, such as challenges beyond acculturation stress and the experiences of underrepresented student populations, including those studying outside of Western countries. Ultimately, the findings may identify areas for further research and inform educational institutions and mental health professionals in developing support resources that can effectively address diverse needs of international students.

Influence of bronfenbrenner ecological theory on career choices of preservice teachers of students with developmental disabilities

Bioinformatics analysis to explore biomarkers and mechanisms of action associated with endoplasmic reticulum stress and ferroptosis in Parkinson’s disease

Objective It has been demonstrated that Parkinson’s disease (PD) is closely associated with endoplasmic reticulum stress (ERS) and ferroptosis. However, the specific mechanisms underlying these associations remain unclear. Consequently, this study investigated the mechanisms connecting these factors and explored potential biomarkers for PD. Methods Data for PD and ERS, as well as information on ferroptosis, were sourced from public databases and relevant literature. Candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis. Further investigations included functional enrichment analysis, the construction of a protein-protein interaction (PPI) network, and the examination of related genes. Subsequently, biomarkers were validated using the least absolute shrinkage and selection operator regression algorithm. Additionally, correlations among biomarkers, gene set enrichment analysis, chromosomal and subcellular localization, immune cell infiltration, regulatory mechanisms, and drug predictions were conducted. Results Initially, seven candidate genes were identified, predominantly associated with type II diabetes mellitus. Furthermore, five interacting associations within the PPI network and twenty related genes were identified, primarily engaged in the physical interactions pathway. Subsequently, three biomarkers were screened: N-myc downstream-regulated gene 1 (NDRG1), dihydrolipoamide dehydrogenase (DLD), and cold-inducible RNA-binding protein (CIRBP). A detailed analysis revealed a positive correlation between CIRBP and DLD, while NDRG1 exhibited a negative correlation with DLD; all three biomarkers were chiefly enriched in the oxidative phosphorylation pathway and PD. NDRG1 is located on chromosome 8, DLD on chromosome 7, and CIRBP on chromosome 19, with all three primarily localized in the nucleus. A total of 31 differential immune cells were identified between the disease and control groups, with neurons representing the highest proportion and the most significant negative correlation observed between DLD and pro B-cells. The interactions involving NORAD-hsa-miR-1277-5p-DLD, NEAT1-hsa-miR-128-3p-CIRBP, and XIST-hsa-miR-3173-5p-NDRG1 were found to be pivotal. Additionally, these biomarkers were regulated by 15 common transcription factors. Finally, nicotinamide adenine dinucleotide, pyruvic acid, nitric oxide, and phosphates were predicted as potential co-targeted therapeutic agents. Conclusions NDRG1, DLD, and CIRBP were identified as biomarkers for PD, thereby opening new avenues for elucidating disease mechanisms, facilitating early diagnosis, and identifying potential therapeutic targets.

Band gap and dispersion characteristics of phononic crystal microchannels under fluid solid coupling

Predictors of elevated carotid intima-media thickness as a surrogate marker for cardiovascular disease in pediatric chronic kidney disease

Background Chronic kidney disease (CKD), especially in its late stages, carries significant morbidity and mortality, often due to cardiovascular problems. Mortality rates for children with CKD and cardiovascular disorders remain high even in high-income countries. Elevated carotid intima-media thickness (CIMT) is considered a marker for vascular thickness and future cardiovascular events in younger populations. This study aimed to determine predictors of cardiovascular events in pediatric patients with CKD with CIMT as a surrogate marker. Materials and methods A retrospective cohort study was conducted on children aged 2–18 years with CKD at Dr. Sardjito Hospital, Yogyakarta, Indonesia, from September 1st 2022–31st December 2023. We used multivariate logistic regression to identify independent predictors at diagnosis (e.g., age, male sex, obesity, CKD stage, and hypertension) associated with elevated CIMT (outcome), measured at least three months post-diagnosis as a proxy for cardiovascular risk. Results A total of 71 patients were recruited, 35 (49.3%) of whom were male, and the median age (range) was 14.67 years (4.6–18.8). Twenty-four children (33.8%) had increased vascular thickness. In the multivariate analysis, male sex was independently associated with increased vascular thickness with an adjusted odds ratio (95% CI) of 2.911 (1.012–8.371, p = 0.047). Conclusion Approximately one in three children with CKD experienced increased vascular thickness. Male was an independent predictor for increased vascular thickness in children with CKD.

Efficient node deployment for enhancing coverage and connectivity in Wireless Sensor Networks