Wireless Integrated Gait Analysis System for Heel-Strike and Toe-Off Measurement

This paper presents the development of a wireless system for gait analysis. Nowadays, gait analysis becoming an important tool to diagnosis or evaluate certain diseases. It has a lot of improvements since the introduction of biomechanics and gait analysis has to be more precise. A lot of studies had been made to determine the measuring of the gait parameters. However, only a few of them specify the measurement of “heelstrike” and “toe-off” timing parameters. Even though there is a research center providing the stated quantitative information, it has been done in a highly accurate computer laboratory. This super computer method is very expensive and not affordable. While in the medical world, the gait parameters analyzed without any guarantee of the results obtained. Therefore, there is a need of the system that is not only low cost but also can produce a real-time feedback. The main objective of this new insole system is to design and implemented a low cost and wearable solution for “heel-strike” and “toe-off” timing parameters using the Force Sensing Resistor (FSR) sensor. The design of this new insole system consisting of six FSR sensors that will deliver a convenient result in the stated gait parameters and offer an additional function which is the gait symmetry observation. The advantage of this project is that it would be a great achievement in the new gait analysis system by introducing the concept of portable wireless and real time feedback device (self–monitor). In conclusion, the design of this new insole system is predicted to help clinician and researchers to develop a new model of gait analysis system

Using Transmissive Photonic Band Edge Shift to Detect Explosives: A Study with 2,4,6-Trinitrotoluene (TNT)

Photonic crystals (PhCs) possess outstanding optical properties that can be exploited for chemical sensing. We utilized a three-dimensional close-packed PhC structure made of functionalized silica nanoparticles. They consist of alternating high and low refractive index regions and have optical properties, such as photonic band structures, that are very sensitive to the change of physical structures. This study used 2,4,6-trinitrotoluene (TNT) to illustrate a detection method based on the transmissive photonic band edge shift (TPBES) due to the binding of TNT with amine anchored on particle surfaces to form Meisenheimer (amine-TNT) complexes. PhCs are exceptionally sensitive to a small change in refractive index caused by surface modification. As a result, they are suitable for sensing specific reactions between an amine and TNT. This method achieved a wide detection range of TNT concentrations from 10$^{-12}$ to 10$^{-4}$ M. 2,4-Dinitrotoluene (DNT) and toluene were used as a control and blank, respectively. Because of gravitational sedimentation, the TNT-functionalized particles were self-assembled in pure ethanol. They were measured by UV–visible transmission spectroscopy. A three-dimensional model to simulate the detection system was built using the particles’ center-to-center distance (a) and effective dielectric constant (ε) as a function of the TNT concentrations. Two sets of simulations were performed: the first set involved a parametric sweep of the center-to-center distance of TNT-functionalized crystals using ε = 2.015. The second set involved a parametric sweep of the dielectric constant with a = 263.1 nm. These perturbations yield a TPBES response that is in agreement with our experimental results

Logic Design for Linear Regression Model Using ASIC in Engine Oil Degradation Monitoring System

A degradation analysis in automotive engine oil is concerned with the unrespectable cost of equipment for data storage. System-on-Chip gives possible cost effective in reducing the bulky equipment and reliance on labor. This article discusses a new technique of degradation monitoring where an engine oil degradation model is used and translated into the logic gate based on the Least Square Method of statistical analysis. The degradation model is based on the optical properties where the percentage transmittance of light is varied due to the increase of contaminates contents in the engine oil at a certain period. A linear regression model is chosen in register-transfer level (RTL) development of the digital circuit design. In the algorithm development, the data set are collected at every one hour up to 300 hours and stored in a temporary register. Linear regression is implemented at every 5 data to obtain the degraded condition based on the variation of the slope

Stormwater characterisation and modelling for Sungai Air Hitam in Selangor, Malaysia using model for urban stormwater improvement conceptualisation (music)

The aim of this study is to evaluate the current water quality status of one of the urban rivers in Malaysia, called Sungai Air Hitam. The river's water supply is not only unsuitable for the inhabitants but also hazardous to the aquatic species that depend on it. In order to simulate the water quality formulation of the river, the Model for Urban Stormwater Improvement Conceptualization (MUSIC) was used. The effects of various best management practices (BMPs) components have been examined to improve the river's water quality. This study also investigated different scenarios of the expected future changes in the land cover and the quality of the river. As the proportion of impervious surfaces increases, the urban hydrology cycle can be significantly altered, resulting in an increase in volumes and peak flows, and a decrease in storage, infiltration, and interception. The MUSIC results have shown significant reductions in biochemical oxygen demand (BOD), total suspended solids (TSS), total phosphorus (TP), and total nitrogen (TN) after introducing BMPs. It was also noticed that the prediction of pollutants falls within the acceptable range set by the Urban Stormwater Management Manual for Malaysia (MSMA) 2nd edition. For the land cover, it was found that the total reduction of BOD, TSS, TP, and TN for existing land use is 92.5 %, 94.5 %, 90.7 % and 91.9 %. Meanwhile, the total reduction in future land use is 81.6 % for BOD, 86.2 % for TSS, 80.9 % for TP and 80.8 % for TN. From the simulation results, it was observed that the application of BMPs has successfully reduced the observed mean BOD concentration from 92.38 mg/L (Class V) to 6.93 mg/L (Class IV) of the national water quality standards, NWQS, water quality index. As a result, the water quality index of the overall catchment has improved from Class IV to Class III (WQ1, WQ3, and WQ4) and from Class V to IV (WQ2) with the application of the BMPs. This assessment aims to raise awareness within the Sungai Air Hitam community regarding the importance of preserving river cleanliness and understanding the long-term environmental impact of water quality. These findings underscore the importance of an integrated system in managing urban water systems, which can offer valuable insight to the decision-makers

Structural crack detection system using internet of things (IoT) for structural health monitoring (SHM): a review

Monitoring the state of civil engineering infrastructure is critical for a country’s economic development since structures with long service life and timely maintenance have lower reconstruction costs. Crack occurrence is the most important element that influences the performance and lifespan of civil infrastructures like bridges and pipelines. As a result, several fracture detection and characterization approaches have been explored and developed in the domains of Structural Health Monitoring (SHM) throughout the last few decades. The major goal of implementing the Internet of Things (IoT) paradigm is to enable the Internet-based connectivity extension of various typical SHM devices. As a result, connected devices can communicate and process data, opening new possibilities in the design of acquisition systems in various disciplines of research and engineering. The researchers have extended the application of the IoT paradigm to the SHM crack detection because of the advances, ensuring that the tests done in this framework can produce good results with promising future improvements. Thus, this paper reviews structural crack detection based IoT for SHM as reported by previous research in the literature. The strengths and limitations of current systems are discussed. This paper is aimed to serve as a reference for crack detection and characterisation researchers as well as others who are interested in SHM in general. In addition, several case studies on real structures, as well as laboratory experiments for monitoring structural crack health of civil engineering structures, are also presented

Landscape-Scale Mining and Water Management in a Hyper-Arid Catchment: The Cuajone Mine, Moquegua, Southern Peru

The expansion of copper mining on the hyper-arid pacific slope of Southern Peru has precipitated growing concern for scarce water resources in the region. Located in the headwaters of the Torata river, in the department of Moquegua, the Cuajone mine, owned by Southern Copper, provides a unique opportunity in a little-studied region to examine the relative impact of the landscape-scale mining on water resources in the region. Principal component and cluster analyses of the water chemistry data from 16 sites, collected over three seasons during 2017 and 2018, show distinct statistical groupings indicating that, above the settlement of Torata, water geochemistry is a function of chemical weathering processes acting upon underlying geological units, and confirming that the Cuajone mine does not significantly affect water quality in the Torata river. Impact mitigation strategies that firstly divert channel flow around the mine and secondly divert mine waste to the Toquepala river and tailings dam at Quebrada Honda remove the direct effects on the water quality in the Torata river for the foreseeable future. In the study area, our results further suggest that water quality has been more significantly impacted by urban effluents and agricultural runoff than the Cuajone mine. The increase in total dissolved solids in the waters of the lower catchment reflects the cumulative addition of dissolved ions through chemical weathering of the underlying geological units, supplemented by rapid recharge of surface waters contaminated by residues associated with agricultural and urban runoff through the porous alluvial aquifer. Concentrations in some of the major ions exceeded internationally recommended maxima for agricultural use, especially in the coastal region. Occasionally, arsenic and manganese contamination also reached unsafe levels for domestic consumption. In the lower catchment, below the Cuajone mine, data and multivariate analyses point to urban effluents and agricultural runoff rather than weathering of exposed rock units, natural or otherwise, as the main cause of contamination

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

Triple-Indicator-Based Multidimensional Colorimetric Sensing Platform for Heavy Metal Ion Detections

Heavy metals are highly toxic at trace levels and their pollution has shown great threat to the environment and public health worldwide where current detection methods require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Herein, we report a low-cost, paper-based microfluidic analytical device (μPAD) for facile, portable, and disposable monitoring of mercury, lead, chromium, nickel, copper, and iron ions. Triple indicators or ligands that contain ions or molecules are preloaded on the μPADs and upon addition of a metal ion, the colorimetric indicators will elicit color changes observed by the naked eyes. The color features were quantitatively analyzed in a three-dimensional space of red, green, and blue or the RGB-space using digital imaging and color calibration techniques. The sensing platform offers higher accuracy for cross references, and is capable of simultaneous detection and discrimination of different metal ions in even real water samples. It demonstrates great potential for semiquantitative and even qualitative analysis with a sensitivity below the safe limit concentrations, and a controlled error range

Colorimetric-based detection of TNT explosives using functionalized silica nanoparticles

This proof-of-concept study proposes a novel sensing mechanism for selective and label-free detection of 2,4,6-trinitrotoluene (TNT). It is realized by surface chemistry functionalization of silica nanoparticles (NPs) with 3-aminopropyl-triethoxysilane (APTES). The primary amine anchored to the surface of the silica nanoparticles (SiO2-NH2) acts as a capturing probe for TNT target binding to form Meisenheimer amine–TNT complexes. A colorimetric change of the self-assembled (SAM) NP samples from the initial green of a SiO2-NH2 nanoparticle film towards red was observed after successful attachment of TNT, which was confirmed as a result of the increased separation between the nanoparticles. The shift in the peak wavelength of the reflected light normal to the film surface (λpeak) and the associated change of the peak width were measured, and a merit function taking into account their combined effect was proposed for the detection of TNT concentrations from 10−12 to 10−4 molar. The selectivity of our sensing approach is confirmed by using TNT-bound nanoparticles incubated in AptamerX, with 2,4-dinitrotoluene (DNT) and toluene used as control and baseline, respectively. Our results show the repeatable systematic color change with the TNT concentration and the possibility to develop a robust, easy-to-use, and low-cost TNT detection method for performing a sensitive, reliable, and semi-quantitative detection in a wide detection range