Sign language continues to be the preferred method of communication among the deaf and the hearing-impaired. Advances in information technology have prompted the development of systems that can facilitate automatic translation between sign language and spoken language. More recently, systems translating between Arabic sign and spoken language have become popular. This paper reviews systems and methods for the automatic recognition of Arabic sign language. Additionally, this paper highlights the main challenges characterizing Arabic sign language as well as potential future research directions.Index Terms-Arabic sign language recognition (ArSLR), continuous sign recognition, image-based, isolated word recognition, sensor-based.

Background Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic disease with pathophysiological characteristics of transforming growth factor-β (TGF-β), and reactive oxygen species (ROS)-induced excessive fibroblast-to-myofibroblast transition and extracellular matrix deposition. Macrophages are closely involved in the development of fibrosis. Nuclear factor erythroid 2 related factor 2 (Nrf2) is a key molecule regulating ROS and TGF-β expression. Therefore, Nrf2 signaling modulation might be a promising therapy for fibrosis. The inhalation-based drug delivery can reduce systemic side effects and improve therapeutic effects, and is currently receiving increasing attention, but direct inhaled drugs are easily cleared and difficult to exert their efficacy. Therefore, we aimed to design a ROS-responsive liposome for the Nrf2 agonist dimethyl fumarate (DMF) delivery in the fibrotic lung. Moreover, we explored its therapeutic effect on pulmonary fibrosis and macrophage activation. Results We synthesized DMF-loaded ROS-responsive DSPE-TK-PEG@DMF liposomes (DTP@DMF NPs). DTP@DMF NPs had suitable size and negative zeta potential and excellent capability to rapidly release DMF in a high-ROS environment. We found that macrophage accumulation and polarization were closely related to fibrosis development, while DTP@DMF NPs could attenuate macrophage activity and fibrosis in mice. RAW264.7 and NIH-3T3 cells coculture revealed that DTP@DMF NPs could promote Nrf2 and downstream heme oxygenase-1 (HO-1) expression and suppress TGF-β and ROS production in macrophages, thereby reducing fibroblast-to-myofibroblast transition and collagen production by NIH-3T3 cells. In vivo experiments confirmed the above findings. Compared with direct DMF instillation, DTP@DMF NPs treatment presented enhanced antifibrotic effect. DTP@DMF NPs also had a prolonged residence time in the lung as well as excellent biocompatibility. Conclusions DTP@DMF NPs can reduce macrophage-mediated fibroblast-to-myofibroblast transition and extracellular matrix deposition to attenuate lung fibrosis by upregulating Nrf2 signaling. This ROS-responsive liposome is clinically promising as an ideal delivery system for inhaled drug delivery. Graphical Abstract

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We read with great interest on the study by Fernando et al., 1 The authors indicated that frailty was directly associated with mortality in patients with in-hospital cardiac arrest (IHCA). We appreciated the author's efforts, and fully agreed with the author's insight that the presence of pre-admission frailty evaluated by Clinical Frailty Scale (CFS) was associated with increased in-hospital mortality, but there was a limitation that independent risk factors in subgroups with and without frailty were not analyzed separately. Therefore, we supplemented that study with our retrospective cohort to determine whether CFS was an independent risk factor for in-hospital mortality of IHCA in subgroups with and without frailty. We retrospectively collected the data of consecutive patients !18 years of age, admitted to the hospital wards at the Zigong fourth people's hospital, from January 1, 2017 to December 31, 2018, who experienced IHCA. All data were extracted from hospital information system (HIS) and laboratory informationsystem (LIS), which were listed in Table 1. All statistical analyses were performed with R (Version 3.6.2

Multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), principal component analysis (PCA) and factor analysis (FA), were used to evaluate temporal and spatial variations in and to interpret large and complex water quality datasets collected from the Shuangji River Basin. The datasets, which contained 19 parameters, were generated during the 2 year (2018–2020) monitoring programme at 14 different sites (3192 observations) along the river. Hierarchical CA was used to divide the twelve months into three periods and the fourteen sampling sites into three groups. Discriminant analysis identified four parameters (CODMn, Cu, As, Se) loading more than 68% correct assignations in temporal analysis, while seven parameters (COD, TP, CODMn, F, LAS, Cu and Cd) to load 93% correct assignations in spatial analysis. The FA/PCA identified six factors that were responsible for explaining the data structure of 68% of the total variance of the dataset, allowing grouping of selected parameters based on common characteristics and assessing the incidence of overall change in each group. This study proposes the necessity and practicality of multivariate statistical techniques for evaluating and interpreting large and complex data sets, with a view to obtaining better information about water quality and the design of monitoring networks to effectively manage water resources.

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Iron-carbon substrates have attracted extensive attention in water treatment due to their excellent processing ability. The traditional iron-carbon substrate suffers from poor removal effects, separation of the cathode and anode, hardening, secondary pollution, etc. In this study, a new type of iron-carbon-loaded substrate (NICLS) was developed to solve the problems of traditional micro-electrolytic substrates. Through experimental research, a preparation method for the NICLS with Fe and C as the core, zeolite as the skeleton, and water-based polyurethane as the binder was proposed. The performance of the NICLS in phosphorus-containing wastewater was analyzed. The results are as follows: The optimal synthesis conditions of the NICLS are 1 g hydroxycellulose, wood activated carbon as the cathode, an activated carbon particle size of 200-60 mesh, and an Fe/C ratio of 1:1. Acidic conditions can promote the degradation of phosphorus by the NICLS. Through the characterization of the NICLS (scanning electron microscope (SEM), X-ray diffractometer (XRD), and energy-dispersive spectrometer (EDS), etc.), it is concluded that the mechanism of the NICLS phosphorus removal is a chemical reaction produced by micro-electrolysis. Using the NICLS to treat phosphorus-containing wastewater has the advantages of high efficiency and durability. Therefore, it can be considered that the NICLS is a promising material to remove phosphorus.

We assessed the predictive value of serum ammonia level on admission for the 28-day mortality of patients with sepsis. We retrospectively included septic patients admitted to the emergency department of West China Hospital, Sichuan University and The Fourth People's Hospital of Zigong city from June 2017 to May 2018. Patients were divided into 2 groups according to 28-day survival. Comparisons of serum ammonia level and sequential organ failure assessment (SOFA) score were made between 2 groups. Multivariate logistic regression models were employed to determine independent risk factors affecting 28-day mortality rate, and receiver operating characteristic (ROC) curve was also used to evaluate the efficacy of risk factors. Total of 316 patients were included into the study, 221 survived to 28 days and 95 were died before 28 days. The 28-day mortality rate was 30.06%. Multivariate logistic regression analyses revealed that the ammonia level, C reactive protein, SOFA score, and the leukocyte were independent risk factors for the 28-day mortality rate. In predicting the 28-day mortality rate, the SOFA score presented an area under the ROC curve (AUC) of 0.815, and the ammonia levels presented the AUC of 0.813. The ammonia level, C reactive protein, SOFA score, and the leukocyte are independent risk factors for 28-day mortality rate in septic patients. Moreover, the serum ammonia and SOFA score have similar predictive values. The serum ammonia level is also a suitable early indicator for prognostic evaluation of patients with sepsis as well.