A fuzzy adaptive extended Kalman filter exploiting the Student's t distribution for mobile robot tracking

To solve the problem of non-Gaussian distribution of measurement noise during the actual process of trajectory tracking when the mobile robot is performing tasks, a novel fuzzy adaptive extended Kalman filter exploiting the Student's t distribution for a robot path tracking is proposed. The distributions of process and measurement noise are modeled using the Student's t distribution. With the adaptive fuzzy controller, the adaptive factors are designed to adjust the covariance matrices of the process and measurement noises simultaneously, which optimize the posterior state and tracking accuracy. The simulation results show that the proposed algorithm has better accuracy and is more robust than existing state-of-the-art algorithms

A fuzzy adaptive extended Kalman filter exploiting the Student's t distribution for mobile robot tracking

To solve the problem of non-Gaussian distribution of measurement noise during the actual process of trajectory tracking when the mobile robot is performing tasks, a novel fuzzy adaptive extended Kalman filter exploiting the Student's t distribution for a robot path tracking is proposed. The distributions of process and measurement noise are modeled using the Student's t distribution. With the adaptive fuzzy controller, the adaptive factors are designed to adjust the covariance matrices of the process and measurement noises simultaneously, which optimize the posterior state and tracking accuracy. The simulation results show that the proposed algorithm has better accuracy and is more robust than existing state-of-the-art algorithms

Data_Sheet_1_Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling.ZIP

<p>Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By “multi-level” we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization.</p

Data_Sheet_2_Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling.docx

<p>Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By “multi-level” we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization.</p

Room-Temperature CuI-Catalyzed <i>N</i>‑Arylation of Cyclopropylamine

A general and efficient CuI/N-carbazolyl-1H-pyrrole-2-carbohydrazide catalyst system was developed for the N-arylation of cyclopropylamine using aryl bromides at room temperature. Herein, 5 mol % CuI and 5 mol % of the ligand were used to synthesize N-aryl cyclopropylamines in moderate to excellent yields. This protocol was scaled up to produce the desired product at gram levels and has been generalized for C–N coupling between aryl bromides and amines at room temperature

DataSheet1_Multi-Level Computational Modeling of Anti-Cancer Dendritic Cell Vaccination Utilized to Select Molecular Targets for Therapy Optimization.pdf

Dendritic cells (DCs) can be used for therapeutic vaccination against cancer. The success of this therapy depends on efficient tumor-antigen presentation to cytotoxic T lymphocytes (CTLs) and the induction of durable CTL responses by the DCs. Therefore, simulation of such a biological system by computational modeling is appealing because it can improve our understanding of the molecular mechanisms underlying CTL induction by DCs and help identify new strategies to improve therapeutic DC vaccination for cancer. Here, we developed a multi-level model accounting for the life cycle of DCs during anti-cancer immunotherapy. Specifically, the model is composed of three parts representing different stages of DC immunotherapy – the spreading and bio-distribution of intravenously injected DCs in human organs, the biochemical reactions regulating the DCs’ maturation and activation, and DC-mediated activation of CTLs. We calibrated the model using quantitative experimental data that account for the activation of key molecular circuits within DCs, the bio-distribution of DCs in the body, and the interaction between DCs and T cells. We showed how such a data-driven model can be exploited in combination with sensitivity analysis and model simulations to identify targets for enhancing anti-cancer DC vaccination. Since other previous works show how modeling improves therapy schedules and DC dosage, we here focused on the molecular optimization of the therapy. In line with this, we simulated the effect in DC vaccination of the concerted modulation of combined intracellular regulatory processes and proposed several possibilities that can enhance DC-mediated immunogenicity. Taken together, we present a comprehensive time-resolved multi-level model for studying DC vaccination in melanoma. Although the model is not intended for personalized patient therapy, it could be used as a tool for identifying molecular targets for optimizing DC-based therapy for cancer, which ultimately should be tested in in vitro and in vivo experiments.</p

DataSheet1_Data mining and safety analysis of BTK inhibitors: A pharmacovigilance investigation based on the FAERS database.ZIP

Objective: The introduction of Bruton’s tyrosine kinase (BTK) inhibitors was a milestone in the treatment of B-cell malignancies in recent years owing to its desired efficacy against chronic lymphocytic leukaemia and small cell lymphocytic lymphoma. However, safety issues have hindered its application in clinical practice. The current study aimed to explore the safety warning signals of BTK inhibitors in a real-world setting using the FDA Adverse Event Reporting System (FAERS) to provide reference for clinical rational drug use.Methods: Owing to the short marketing time of other drugs (zanbrutinib and orelabrutinib), we only analysed ibrutinib and acalabrutinib in this study. All data were obtained from the FAERS database from January 2004 to December 2021. Disproportionality analysis and Bayesian analysis were utilised to detect and assess the adverse event (AE) signals of BTK inhibitors.Results: In total, 43,429 reports of ibrutinib were extracted and 1527 AEs were identified, whereas 1742 reports of acalabrutinib were extracted and 220 AEs were identified by disproportionality analysis and Bayesian analysis. Among reports, males were more prone to develop AEs (58.2% for males vs. 35.6% for females treated with ibrutinib, and 55.9% vs. 31.9%, respectively, for acalabrutinib), and more than 30% of patients that suffered from AEs were over 65 years of age. Subsequently, we investigated the top 20 preferred terms (PTs) associated with the signal strength of ibrutinib and acalabrutinib, and our results identified 25 (13 vs. 12, respectively) novel risk signals. Among the top 20 PTs related to death reports, the terms infectious, pneumonia, pleural effusion, fall, asthenia, diarrhoea, and fatigue were all ranked high for these two BTK inhibitors. Further, cardiac disorders were also an important cause of death with ibrutinib.Conclusion: Patients treated with ibrutinib were more prone to develop AEs than those treated with acalabrutinib. Importantly, infection-related adverse reactions, such as pneumonia and pleural effusion, were the most common risk signals related to high mortality associated with both BTK inhibitors, especially in elderly patients. Moreover, cardiovascular-related adverse reactions, such as atrial fibrillation and cardiac failure, were fatal AEs associated with ibrutinib. Our results provide a rationale for physicians to choose suitable BTK inhibitors for different patients and provide appropriate monitoring to achieve safer therapy and longer survival.</p

Size-Dependent Response of Hydrothermally Grown SnO₂ for a High-Performance NO₂ Sensor and the Impact of Oxygen

A NO2 sensor with a detection limit down to the ppb level based on pristine SnO2 has been developed through a facile poly(acrylic acid)-mediated hydrothermal method. SnO2 particles of solid microsphere, hollow microsphere, and nanosphere morphologies were synthesized, with respective constitutional crystallite of size ∼2 μm in length and 10–20 nm and ∼7 nm in diameter. All sensors show great selectivity to NO2. The hollow microsphere sensor exhibits the best performance, with medium specific surface area (SSA), followed by the nanosphere sensor with the largest SSA. This is attributed to the superposition of two opposite effects on sensor response with increased SSA: more adsorption sites and fewer electrons to be taken out with overly small crystallite that may reach complete depletion. O2 is found to speed up the response and recovery times but reduce the response because O adsorbates facilitate the adsorption/desorption of NO2 thermodynamically, and the two oxidizing gases compete in harvesting electrons from SnO2. The adverse effect of humidity can be minimized by operating the sensor at 110 °C. The response of the hollow microsphere sensor to 50 ppb of NO2 is 8.8 (Rg/Ra) at room temperature, and it increases to 15.1 at 110 °C. These findings are useful for developing other oxidizing gas semiconductor sensors

Additional file 1 of Characteristics and clinical treatment outcomes of chronic hepatitis B children with coexistence of hepatitis B surface antigen (HBsAg) and antibodies to HBsAg

Additional file 1: Table S1. Multivariate analysis of HBsAb-positive status at baseline. Table S2. Crude incidence rate (per 100 PY) of ALT normalization. Figure S1. Kaplan-Meier curves of ALT normalization between HBsAb-positive group and HBsAb-negative group

Physicochemical properties of biochars made from different raw materials.

Physicochemical properties of biochars made from different raw materials.</p