In addition, the respective life cycle inventories (LCIs) are provided, enabling the identification of resource hot spots and quantifying the environmental benefits of end-of-life options.Heightened levels of carbon dioxide (CO2) and other greenhouse gases (GHGs) have prompted research into techniques for their capture and separation, including membrane separation, chemical looping, and cryogenic distillation. Ionic liquids, due to their negligible vapour pressure, thermal stability, and broad electrochemical stability have expanded their application in gas separations. This work provides an overview of the recent developments and applications of ionic liquid membranes (ILMs) for gas separation by focusing on the separation of carbon dioxide (CO2), methane (CH4), nitrogen (N2), hydrogen (H2), or mixtures of these gases from various gas streams. The three general types of ILMs, such as supported ionic liquid membranes (SILMs), ionic liquid polymeric membranes (ILPMs), and ionic liquid mixed-matrix membranes (ILMMMs) for the separation of various mixed gas systems, are discussed in detail. Furthermore, issues, challenges, computational studies and future perspectives for ILMs are also considered. The results of the analysis show that SILMs, ILPMs, and the ILMMs are very promising membranes that have great potential in gas separation processes. They offer a wide range of permeabilities and selectivities for CO2, CH4, N2, H2 or mixtures of these gases. In addition, a comparison was made based on the selectivity and permeability of SILMs, ILPMs, and ILMMMs for CO2/CH4 separation based on a Robeson’s upper bound curves.Apoptosis, a form of programmed cell death, is a highly regulated process critical for tissue development, homeostasis, and pathogenesis of various diseases […].Frailty, one of the major public health problems in the elderly, can result from multiple etiologic factors including biological and physical changes in the body which contribute to the reduction in the function of multiple bodily systems. A diagnosis of frailty can be reached using a variety of frailty assessment tools. In this study, general characteristics and health data were assessed using modified versions of Fried’s Frailty Phenotype (mFFP) and the Frail Non-Disabled (FiND) questionnaire (mFiND) to construct a Self-Organizing Map (SOM). Trained data, composed of the component planes of each variable, were visualized using 2-dimentional hexagonal grid maps. The relationship between the variables and the final SOM was then investigated. The SOM model using the modified FiND questionnaire showed a correct classification rate (%CC) of about 66% rather than the model responded to mFFP models. The SOM Discrimination Index (SOMDI) identified cataracts/glaucoma, age, sex, stroke, polypharmacy, gout, and sufficiency of income, in that order, as the top frailty-associated factors. The SOM model, based on the mFiND questionnaire frailty assessment, is an appropriate tool for assessment of frailty in the Thai elderly. Cataracts/glaucoma, stroke, polypharmacy, and gout are all modifiable early prediction factors of frailty in the Thai elderly.Today, enhancement in sensing technology enables the use of multiple sensors to track human motion/activity precisely. Tracking human motion has various applications, such as fitness training, healthcare, rehabilitation, human-computer interaction, virtual reality, and activity recognition. Therefore, the fusion of multiple sensors creates new opportunities to develop and improve an existing system. This paper proposes a pose-tracking system by fusing multiple three-dimensional (3D) light detection and ranging (lidar) and inertial measurement unit (IMU) sensors. The initial step estimates the human skeletal parameters proportional to the target user’s height by extracting the point cloud from lidars. Next, IMUs are used to capture the orientation of each skeleton segment and estimate the respective joint positions. In the final stage, the displacement drift in the position is corrected by fusing the data from both sensors in real time. The installation setup is relatively effortless, flexible for sensor locations, and delivers results comparable to the state-of-the-art pose-tracking system. We evaluated the proposed system regarding its accuracy in the user’s height estimation, full-body joint position estimation, and reconstruction of the 3D avatar. We used a publicly available dataset for the experimental evaluation wherever possible. The results reveal that the accuracy of height and the position estimation is well within an acceptable range of ±3-5 cm. The reconstruction of the motion based on the publicly available dataset and our data is precise and realistic.Malnutrition is common in older adults and is associated with functional impairment, reduced quality of life, and increased morbidity and mortality. The aim of this study was to explore the association between health (including depression), physical functioning, disability and cognitive decline, and risk of malnutrition. Participants were recruited from nursing homes in Italy and completed a detailed multidimensional geriatric evaluation. All the data analyses were completed using Stata Version 15.1. selleck The study included 246 participants with an age range of 50 to 102 (80.4 ± 10.5). The sample was characterised by a high degree of cognitive and functional impairment, disability, and poor health and nutritional status (according to Mini Nutritional Assessment (MNA), 38.2% were at risk for malnutrition and 19.5% were malnourished). Using a stepwise linear regression model, age (B = -0.043, SE = 0.016, p = 0.010), depression (B = -0.133, SE = 0.052, p = 0.011), disability (B = 0.517, SE = 0.068, p less then 0.001), and physical performance (B = -0.191, SE = 0.095, p = 0.045) remained significantly associated with the malnutrition risk in the final model (adjusted R-squared = 0.298). The logistic regression model incorporating age, depression, disability, and physical performance was found to have high discriminative accuracy (AUC = 0.747; 95%CI 0.686 to 0.808) for predicting the risk of malnutrition. The results of the study confirm the need to assess nutritional status and to investigate the presence of risk factors associated with malnutrition in order to achieve effective prevention and plan a better intervention strategy.