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Tracheostomy in Children: Experience from a Tertiary Care Center in South India
Bayesian inference of a spatially dependent semi-Markovian model with application to Madagascar Covid’19 data
This article presents an approach to stochastic analysis of disease dynamics. We develop an explicit semi-Markovian model that accounts for spatial dependence, operating in discrete time over a finite state space. The model allowed us to have a propagation model conditioned by neighboring states and quantifies two key characteristics : spatial propagation timescales and propagation law in a region dependent on neighboring states. The model is inferred from data collected on the spread of Covid’19 in Madagascar’s 22 regions, using the Bayesian approach to get a better idea of model parameter values. The result has demonstrated the effect of neighborhoods on the propagation dynamics of diseases. We conclude with a discussion of potential future theoretical developments.
Infectious Disease Emergencies in Older Adults in India: A Prospective Observational Study Comparing Youngest Old, Middle Old, and Oldest Old Patients
Characterizing limit order books in call auctions of a stock market
Statistical and dynamical characteristics of stock markets have been extensively studied, providing a solid basis for econophysics and its application as “stylized facts”. However, most of those studies are for markets under the continuous auction, i.e., trades are executed sequentially. There has been less research on another major type of auction, call auctions, where orders are accumulated and those are executed at once in the final moment. This study focuses on the structure of the limit order books of stocks under call auctions. Using the data of all stocks listed in the Tokyo Stock Exchange, we find that the shapes of the limit order books in call auctions are well fitted by a simple functional form of a hyperbolic tangent. From the fitting, we define the “median spread” and the “width” of limit orders. The ratios of the “width” to the “median spread” of most stocks are found to be similar, indicating that the execution ratios (the trading volume relative to the total number of orders) are nearly equal among them. Furthermore, the deviation in this ratio from the majority is found to be a good indicator to find the stocks of the companies making outstanding profit. Our results demonstrate that those parameters of the structure of the limit order book well characterize the states of the market under call auctions.
Plasmapheresis for Hypertriglyceridemia-induced Acute Pancreatitis: A Systematic Review and Meta-summary of Case Reports
Research on asphalt pavement structure with cement treated large size macadam (CTB–50) base course
Cement-treated large-size macadam base (CTB–50) has a high modulus, high strength, and good durability, which can increase the paving and rolling thickness, reduce the base layers, and enhance the overall structure of the pavement structure. However, there are no studies conducted on the mechanical response of asphalt pavement with a CTB–50 base course such that it can be promoted and applied in pavement engineering using CTB–50. This study analyzed the mechanical response and fatigue life of asphalt pavement structures with different base courses. Subsequently, the typical pavement structure form of asphalt pavement with a CTB–50 base course was recommended, and its effectiveness was verified through two highway engineering projects. The results showed that the base structure reduced from a three-layer CTB–30 base course structure to a two-layer CTB–50 base course structure, and the base layer bottom tensile stress of the asphalt pavement with CTB–50 base course is reduced by 5% compared to that of the asphalt pavement with CTB–30 base course. Based on the principle of equivalent fatigue life, the CTB–50 base layer thickness of the asphalt pavement can be reduced by approximately 6 cm compared to that of the CTB–30 base layer. The recommended pavement structure can reduce one layer in the construction of the base layer and improve the integrity of the asphalt pavement structure. The experimental road paved with the recommended CTB–50 base course pavement structure showed no evident pavement disease, whereas the road section with the CTB–30 base course showed early crack diseases in the asphalt pavement.
Challenges in Implementing High Protein Nutrition for ICU Patients
Reciprocal effects of conditioned medium on gene and protein expression of limbal epithelial cells and limbal fibroblasts in congenital aniridia
Congenital aniridia is marked by substantial inflammatory changes to the ocular surface. However the exact mechanisms of epithelial-stromal interaction are not fully understood. The purpose of this study was to investigate inflammatory cytokine expression in limbal epithelial cells and fibroblasts following exposure to each other’s conditioned medium (CM). Healthy primary limbal epithelial cells (pLECs) and healthy (LFC) or aniridia primary limbal fibroblasts (AN-LFC) were isolated. A PAX6-deficient limbal epithelial cell line (mut-LSCs) modeled aniridia. pLECs underwent siRNA-mediated PAX6 knockdown (siPAX6 pLECs) with control cells transfected with non-specific siRNA (siCtrl pLECs). siCtrl and siPAX6 pLECs were treated with LFC-CM and AN-LFC-CM for 24 hours, while LFC and AN-LFC were treated with pLECs-CM and mut-LSCs-CM for 48 hours. Gene and protein expression of IL-1β, IL-6, IL-8, TNF-α and VEGF-A were measured using qPCR and ELISA. Except for an increased IL-8 protein expression in siPAX6 pLECs treated with LFC-CM, gene and protein levels of inflammatory biomarkers remained unchanged in siCtrl and siPAX6 pLECs, regardless of treatment with LFC-CM or AN-LFC-CM. In LFCs, pLECs-CM decreased TNF-α mRNA and IL-8 protein, while increasing IL-1β, IL-6, IL-8 mRNA and IL-6 protein. LFCs treated with mut-LSCs-CM showed decreased TNF-α mRNA and increased IL-6 protein. AN-LFCs treated with pLECs-CM showed increased IL-6, IL-8 and VEGF-A mRNA and IL-6 protein. mut-LSCs-CM did not alter AN-LFC expression. Limbal fibroblasts’ secretome minimally inflames limbal epithelial cells, suggesting a supportive niche role. In contrast, pLECs-CM induces a stronger fibroblast response, indicating abnormal interactions in congenital aniridia.
Author Response: The Sleep Quality of Intensive Care Unit Patients on Noninvasive Ventilation Depends Not Only on Noninvasive Ventilation- and ICU-related Factors but Also on Numerous Other Factors
Factors affecting the maximum outcome payments of social impact bonds
As governments globally seek market-based solutions to address complex social challenges, Social Impact Bonds (SIBs) have gained prominence in public policy reforms for their potential to align fiscal accountability with social innovation. SIBs are innovative financial tools designed to fund social projects through outcome-based payments, lower government financial pressure, and increase the efficiency with which social problems are solved. In a SIB, the maximum outcome payment refers to the highest amount the outcome payer is willing to provide, and is one of the key factors attracting investor participation. It is typically calculated as the sum of service costs and fiscal savings. However, the current approach often prioritizes reducing government expenditure, without sufficiently accounting for the risks and interests of investors. This improper formulation of maximum outcome payments may cause financing bottleneck and hinder the sustainable development of SIBs. To achieve a balance between government cost control and investor returns, this paper systematically examines the key factors influencing maximum outcome payments through multiple regression analysis, with a focus on macroeconomic factors and bond characteristics. The results indicate that maximum outcome payments are correlated with inflation, capital raised, and the size of the target population for the SIB. Therefore, when determining maximum outcome payments, issuers should consider not only fiscal savings but also bond characteristics and macroeconomic factors.
Development and Validation of a Neurological Outcome Prediction Score for Children Requiring Mechanical Ventilation: The NOPS-VC Score
Planning trajectory for UAVs using the self-organizing migrating algorithm
Ensuring efficient and safe trajectory planning for UAVs in complex and dynamic environments is a critical challenge, especially for UAVs that are increasingly deployed in applications like environmental monitoring, disaster management, and surveillance. The primary complications in the safe control of UAVs include real-time obstacle avoidance, adaptation to unpredictable environmental changes, and coordination among multiple UAVs to prevent collisions. This paper addresses these challenges by proposing a novel approach for UAV trajectory planning that integrates obstacle avoidance and target acquisition. We introduce a new cost function designed to minimize the distance to the target while maximizing the distance from obstacles, effectively balancing these competing objectives to ensure safety and efficiency. To optimize this cost function, we employ the self-organizing migrating algorithm, a swarm intelligence algorithm inspired by the cooperative and competitive behaviors observed in natural organisms. Our method enables UAVs to autonomously generate safe and efficient paths in real-time, adapt to dynamic changes, and scale to large swarms without relying on centralized control. Simulation results across three scenarios-including a complex environment with ten UAVs and multiple obstacles-demonstrate the effectiveness of our approach. The UAVs successfully reach their targets while avoiding collisions, confirming the reliability and robustness of the proposed method. This work contributes to advancing autonomous UAV operations by providing a scalable and adaptable solution for trajectory planning in challenging environments.
Continuous Infusion of Linezolid: Explaining the Discrepant Survival Outcomes between Two Studies
Relationships between fatigue severity scale (FSS)/ scale for mood assessment (EVEA) and clinical manifestations in spanish long-COVID patients
Aim This study aims to investigate the influence of fatigue and mood disturbances in Spanish long-COVID patients and to establish relationships between these factors and other clinical manifestations. Method A descriptive correlational study was conducted using a self-administered online questionnaire. The sample was obtained through non-random convenience sampling, comprising 374 participants from various regions of Spain. Data collection occurred between July 2, 2022, and November 30, 2022. The questionnaire collected demographic information and inquired about symptomatology as well as self-perception of health status. Validated scales, namely the Fatigue Severity Scale (FSS) and the Scale for Mood Assessment (EVEA), were utilized. Results The non-random sample consisted of 374 participants from diverse regions of Spain, of whom 79.9% were women. Over 70% of participants reported fatigue, while the EVEA revealed high scores in sadness-depression (4.94 ± 2.82) and anxiety (4.57 ± 2.88). Significant relationships were identified between fatigue and mood disturbances and neurological, psychological, locomotive, and pain symptoms. Conclusions Given the impact of the syndrome on psychological, social and economic spheres, regular monitoring of patients with long COVID is crucial. This study corroborates previous research findings and is notable for demonstrating the persistence of symptoms for over a year. Mood disorders, such as anxiety and depression, are closely related to physical symptoms, highlighting the need for holistic healthcare approaches.
Patients with Benzodiazepine Intoxication Require Neurological and Psychiatric Examination in Order to Guide and Monitor Withdrawal
Association between shortened maternal and fetal telomere length and abnormal fetal development
A number of intrinsic, maternal and environmental factors have been linked to the risk of fetal developmental anomalies. In a previous study, we showed that telomere length (TL) was notably reduced in amniotic fluid when the fetus exhibited a developmental anomaly. In this new study, we measured the fetal and maternal TL for 75 evolutive pregnancies with congenital malformation. We also measured the TL of 50 pregnant women without fetal anomalies and 50 non-pregnant control women who had at least one child with normal development. In fetal samples, telomeres were significantly shortened in cases with congenital anomalies compared to controls (n = 93) (P < 0.0001). Interestingly, age-adjusted maternal TL was also significantly reduced in these cases (P < 0.01). Receiver operating characteristic (ROC) analysis showed that maternal TL, at the optimal cut-off value, identified cases of congenital anomalies with 92% specificity and 73% sensitivity. In addition, fetal and maternal TL were correlated, with 15% to 38% of the variance in fetal TL attributable to maternal TL. Telomere shortening can lead to increased sensitivity to various maternal exposure factors and may contribute to compromised organogenesis, possibly due to inadequate cell proliferation or genomic instability. Measuring maternal TL during the periconceptional period could serve as a useful predictive biomarker for assessing the risk of fetal developmental anomalies.
Author Response: Letter on “Impact of Noninvasive Ventilation on Quality of Sleep among Patients Admitted to the Critical Care Unit” — Limitations and Recommendations
Enhanced uncertainty sampling with category information for improved active learning
Traditional uncertainty sampling methods in active learning often neglect category information, leading to imbalanced sample selection in multi-class computer vision tasks. Our approach integrates category information with uncertainty sampling through a novel active learning framework to address this limitation. Our method employs a pre-trained VGG16 architecture and cosine similarity metrics to efficiently extract category features without requiring additional model training. The framework combines these features with traditional uncertainty measures to ensure balanced sampling across classes while maintaining computational efficiency. Extensive experiments across both object detection and image classification tasks validate our method’s effectiveness. For object detection, our approach achieves competitive mAP scores while ensuring balanced category representation. For image classification, our method achieves accuracy comparable to state-of-the-art approaches while reducing computational overhead by up to 80%. The results validate our approach’s ability to balance sampling efficiency with dataset representativeness across different computer vision tasks. This work offers a practical, efficient solution for large-scale data annotation in domains with limited labeled data and diverse class distributions.