Preliminary design and multi-objective optimization of electro-hydrostatic actuator

Electro-hydrostatic actuator is generally regarded as the preferred solution for more electrical aircraft actuation systems. It is of importance to optimize the weight, efficiency and other key design parameters, during the preliminary design phase. This paper describes a multi-objective optimization preliminary design method of the electro-hydrostatic actuator with the objectives of optimizing the weight and efficiency. Models are developed to predict the weight and efficiency of the electro-hydrostatic actuator from the requirements of the control surface. The models of weight prediction are achieved by using scaling laws with collected data, and the efficiency is calculated by the static energy loss model. The multi-objective optimization approach is used to find the Pareto-front of objectives and relevant design parameters. The proposed approach is able to explore the influence of the level length of linkage, displacement of pump and torque constant of motor on the weight and efficiency of the electro-hydrostatic actuator, find the Pareto-front designs in the defined parameter space and satisfy all relevant constraints. Using an electro-hydrostatic actuator for control surface as a test case, the proposed methodology is demonstrated by comparing three different conditions. It is also envisaged that the proposed prediction models and multi-objective optimization preliminary design method can be applied to other components and systems

Artificial intelligence-driven microbiome data analysis for estimation of postmortem interval and crime location

Microbial communities, demonstrating dynamic changes in cadavers and the surroundings, provide invaluable insights for forensic investigations. Conventional methodologies for microbiome sequencing data analysis face obstacles due to subjectivity and inefficiency. Artificial Intelligence (AI) presents an efficient and accurate tool, with the ability to autonomously process and analyze high-throughput data, and assimilate multi-omics data, encompassing metagenomics, transcriptomics, and proteomics. This facilitates accurate and efficient estimation of the postmortem interval (PMI), detection of crime location, and elucidation of microbial functionalities. This review presents an overview of microorganisms from cadavers and crime scenes, emphasizes the importance of microbiome, and summarizes the application of AI in high-throughput microbiome data processing in forensic microbiology

An electromagnetic wearable 3-DoF resonance human body motion energy harvester using ferrofluid as a lubricant

Wearable energy harvester offers clean and continuous power for wearable sensors or devices, and plays an important role in a wide range of applications such as the health monitoring and motion track. In this study, we investigate a small electromagnetic resonance wearable kinetic energy harvester. It consists of a permanent magnet (PM) supported by two elastic strings within a rectangular box form a 3-degree-of-freedom (3-DoF) vibrator. Copper windings are attached to the outer surface of the box to generate electrical energy when the PM is forced to vibrate. To minimize any frictional losses, ferrofluid is used such that the poles of PM are cushioned by the ferrofluid, to the effect that the PM will not touch the inner of the box. Simulation results show that the ferrofluid can keep the PM ‘contactless’ from the box even subject to 10 times gravity acceleration. A prototype is built and tested under different loading conditions. Resistance load experimental results indicate the proposed harvester can generate 1.11.1 mW in walking condition and 2.282.28 mW in running condition. An energy storage circuit is employed and the energy storage experimental results show that the average storage power during walking and running conditions are 0.0140.014 mW and 0.1490.149 mW respectively. It is shown that the developed harvester can be readily attached on a shoe to offer continuous power supply for wearable sensors and devices

Single-pixel imaging based on deep learning

Single-pixel imaging can collect images at the wavelengths outside the reach of conventional focal plane array detectors. However, the limited image quality and lengthy computational times for iterative reconstruction still impede the practical application of single-pixel imaging. Recently, deep learning has been introduced into single-pixel imaging, which has attracted a lot of attention due to its exceptional reconstruction quality, fast reconstruction speed, and the potential to complete advanced sensing tasks without reconstructing images. Here, this advance is discussed and some opinions are offered. Firstly, based on the fundamental principles of single-pixel imaging and deep learning, the principles and algorithms of single-pixel imaging based on deep learning are described and analyzed. Subsequently, the implementation technologies of single-pixel imaging based on deep learning are reviewed. They are divided into super-resolution single-pixel imaging, single-pixel imaging through scattering media, photon-level single-pixel imaging, optical encryption based on single-pixel imaging, color single-pixel imaging, and image-free sensing according to diverse application fields. Finally, major challenges and corresponding feasible approaches are discussed, as well as more possible applications in the future

SARS-CoV-2 infection causes dopaminergic neuron senescence

COVID-19 patients commonly present with signs of central nervous system and/or peripheral nervous system dysfunction. Here, we show that midbrain dopamine (DA) neurons derived from human pluripotent stem cells (hPSCs) are selectively susceptible and permissive to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. SARS-CoV-2 infection of DA neurons triggers an inflammatory and cellular senescence response. High-throughput screening in hPSC-derived DA neurons identified several FDA-approved drugs that can rescue the cellular senescence phenotype by preventing SARS-CoV-2 infection. We also identified the inflammatory and cellular senescence signature and low levels of SARS-CoV-2 transcripts in human substantia nigra tissue of COVID-19 patients. Furthermore, we observed reduced numbers of neuromelanin+ and tyrosine-hydroxylase (TH)+ DA neurons and fibers in a cohort of severe COVID-19 patients. Our findings demonstrate that hPSC-derived DA neurons are susceptible to SARS-CoV-2, identify candidate neuroprotective drugs for COVID-19 patients, and suggest the need for careful, long-term monitoring of neurological problems in COVID-19 patients.</p

SARS-CoV-2 infection causes dopaminergic neuron senescence

COVID-19 patients commonly present with signs of central nervous system and/or peripheral nervous system dysfunction. Here, we show that midbrain dopamine (DA) neurons derived from human pluripotent stem cells (hPSCs) are selectively susceptible and permissive to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. SARS-CoV-2 infection of DA neurons triggers an inflammatory and cellular senescence response. High-throughput screening in hPSC-derived DA neurons identified several FDA-approved drugs that can rescue the cellular senescence phenotype by preventing SARS-CoV-2 infection. We also identified the inflammatory and cellular senescence signature and low levels of SARS-CoV-2 transcripts in human substantia nigra tissue of COVID-19 patients. Furthermore, we observed reduced numbers of neuromelanin+ and tyrosine-hydroxylase (TH)+ DA neurons and fibers in a cohort of severe COVID-19 patients. Our findings demonstrate that hPSC-derived DA neurons are susceptible to SARS-CoV-2, identify candidate neuroprotective drugs for COVID-19 patients, and suggest the need for careful, long-term monitoring of neurological problems in COVID-19 patients.</p

Partitioning behavior and occurrence of airborne polyfluorinated alkyl substances in Singapore

Polyfluorinated alkyl substances (PFASs) are a large group of organic chemicals, many of which are persistent in the environment, bioaccumulative and pose potential adverse effects to human health. The presence of neutral, volatile PFASs in air are of particular concern, as air quality is an important determinant in terms of public health. However, little experimental information is available on the physicochemical properties of volatile PFASs. The short-term concentration variations of airborne PFASs also remain unknown due to the lack of a highly sensitive analytical method which can also achieve satisfying temporal resolution. Therefore, the aim of current work is to improve our understanding of the partitioning behavior, occurrence and source strength of neutral, volatile PFASs in Singapore. Firstly, air–water partition coefficient (KH) of 4 fluorotelomer alcohols (FTOHs), a subgroup of volatile PFASs, was measured using inert gas-stripping method (IGS). KH values of FTOHs showed strong propensity to partition into air. However, the expected linear dependence of KH on molecular weight was not observed. The unique molecular geometry of FTOHs, with hydrogen bonding and molecular contortion, was probably responsible for the unusual phenomenon. The results were compared to predictions made by SPARC and EPI suite. The erroneous predications given by modeling software packages appeared to confirm the unusual behavior of the compounds.Secondly, the study attempted to develop a novel method based upon thermal desorption and GC–MS for determination of indoor airborne volatile PFASs, including four FTOHs, two fluorooctane sulfonamides (FOSAs), and two fluorooctane sulfonamidoethanols (FOSEs) through low-volume active air sampling. The optimization of sorbent combination was also conducted. The method recovery exhibited significant improvement compared with other existing methods such as passive air sampling method. The approach also achieved relatively high temporal resolution and low noise level. It has been successfullyapplied to routine quantitation of targeted PFASs in indoor office environment of Singapore, which provided further insights toward the indoor source strength of PFASs and performance of building air handlings. Thirdly, the developed thermal desorption method was further applied for determination of target PFASs in urban atmosphere through low-volume active air sampling (0.108 m3). It displayed greatly improved method recovery but higher detection limits in comparison with the conventional protocol, which employs highvolume sample collection (450 m3) and solvent-based sample extraction. Comparison of their performances in the real samples of urban atmosphere showed a higher portability and temporal resolution of thermal desorption method, which would be very useful in source apportionment analysis and assessment of concentration variations in highly-urbanized regions. In addition, the concentration levels of PFASs detected in the ambient air of Singapore were more in line with the European pattern and might indicate an increasing tendency toward using FTOHs in these regions.Doctor of Philosophy (CEE

Development of analysis of volatile polyfluorinated alkyl substances in indoor air using thermal desorption-gas chromatography–mass spectrometry

The study attempts to utilize thermal desorption (TD) coupled with gas chromatography–mass spectrometry (GC–MS) for determination of indoor airborne volatile polyfluorinated alkyl substances (PFASs), including four fluorinated alcohols (FTOHs), two fluorooctane sulfonamides (FOSAs), and two fluorooctane sulfonamidoethanols (FOSEs). Standard stainless steel tubes of Tenax/Carbograph 1 TD were employed for low-volume sampling and exhibited minimal breakthrough of target analytes in sample collection. The method recoveries were in the range of 88–119% for FTOHs, 86–138% for FOSAs, exhibiting significant improvement compared with other existing air sampling methods. However, the widely reported high method recoveries of FOSEs were also observed (139–210%), which was probably due to the structural differences between FOSEs and internal standards. Method detection limit, repeatability, linearity, and accuracy were reported as well. The approach has been successfully applied to routine quantification of targeted PFASs in indoor environment of Singapore. The significantly shorter sampling time enabled the observation of variations of concentrations of targeted PFASs within different periods of a day, with higher concentration levels at night while ventilation systems were shut off. This indicated the existence of indoor sources and the importance of building ventilation and air conditioning system

High-amylose starch-based gel as green adhesive for plywood:Adhesive property, water-resistance, and flame-retardancy

The escalating demand for environmentally sustainable and cost-effective adhesives in the wood processing and manufacturing sector has prompted exploration into innovative solutions. This study introduces a novel gel adhesive composed of chemically unmodified high-amylose starch (G70, with 68 % amylose content) with a minimal proportion of urea-formaldehyde (UF) (UF/starch = 1:10, w/w). This G70/UF gel demonstrates remarkable adhesive capabilities for wooden boards under both dry conditions (with a shear stress of 4.13 ± 0.12 MPa) and wet conditions (with a shear strength of 0.93 ± 0.07 MPa after 2 h of water soaking). The study unveils that the elevated amylose content in the starch, coupled with a meticulously controlled isothermal process during bonding, is crucial for these enhancements. Specifically, the robust cohesion of amylose chains expedites phase separation between starch and UF, while the isothermal process facilitates the migration and enrichment of UF molecules at the gel-board and gel-air interfaces. Lacking these mechanisms, conventional amylopectin-rich starch/UF gels (27 % amylose content) show minimal improvement. Moreover, the G70/UF gel showcases exceptional fire retardancy. In all, the G70/UF gel presents a promising alternative for plywood production, reducing reliance on unhealthy UF resin while offering satisfactory bonding resistance in diverse conditions and superior flame retardancy.</p