Built-in Components Research Articles

Аналіз технологій реконфігурації систем інтернету речей на рівні програмних модулів та завантажувачів

The subject of study and research in this article are the technology of programming and interaction of nodes, as well as individual small-sized components of embedded Internet of Things (IoT) systems. The goal is to increase the flexibility of IoT system components by simplifying the reconfiguration process of individual nodes and components. The task is: to analyze existing approaches to building configurable systems, analyze and describe existing solutions that implement joint approaches; to analyze the tools for implementing the selected approaches; to describe the method of building a living system based on the analysis approach; and to provide a technical example of the proposed programming method. According to the tasks, the following results were obtained. Possible ways of reconfiguration of IoT components are analyzed. Methods of reconfiguration at the network level and partial node reconfiguration are considered. Methods to ensure the flexibility of IoT components are analyzed and classified. A comparative analysis of the summary parameters of the loaders was carried out. The possibility of using software components as immutable blocks of code to modify the microcontroller program as a method of reconfiguration was analyzed. The idea of using variable software modules to represent the microcontroller program at a higher level of abstraction with a modified bootloader is thus proposed. Elements of a method for reprogramming variable software modules of microcontrollers as middleware are proposed. Conclusions. According to a review of the existing types of systems, they were classified according to the level of organization of their reconfigured parts. According to the obtained preliminary classifications, some architectural solutions were considered from the point of view of improving operational characteristics. The main advantages for each type of organization of the reconfigurable parts of the systems are highlighted. An analysis of practical solutions regarding the modification of the built-in components of microcontrollers for managing and updating their firmware was conducted. The practical significance of this study is the proposal of a method of programming with variable software modules for microcontrollers and the obtained results of a competitive analysis of methods of modifying components and loader characteristics.

Application of Iterative Elastic SH Reverse Time Migration to Synthetic Ultrasonic Echo Data

The ultrasonic echo technique is widely used in non-destructive testing (NDT) of concrete objects for thickness measurements, geometry determinations and localization of built-in components. To improve ultrasonic imaging of complex concrete structures, we transferred a seismic imaging technique, the Reverse Time Migration (RTM), to NDT in civil engineering. RTM, in contrast to the conventionally used synthetic aperture focusing technique (SAFT) algorithms, considers all wavefield types and thus, can handle complex wave propagations in any direction with no limit on velocity variations and reflector dip. In this paper, we focused on the development, application and evaluation of a two-dimensional elastic RTM algorithm considering horizontally polarized shear (SH) waves only. We applied the elastic SH RTM routine to synthetic ultrasonic echo SH-wave data generated with a concrete model incorporating several steps and circular cavities. As these features can often be found in real-world NDT use cases, their imaging is extremely important. By using elastic SH RTM, we were able to clearly reproduce almost all reflectors inside the concrete model including the vertical step edges and the cross sections of the cavities. We were also capable to show that more features could be mapped compared to SAFT, and that imaging of complex reflectors could be sharpened compared to elastic P-SV (compressional-vertically polarized shear) RTM. Our promising results illustrate that elastic SH RTM has the potential to significantly enhance the reconstruction of challenging concrete structures, representing an important step forward for precise, high-quality ultrasonic NDT in civil engineering.

Wet sieving and magnetic separation for the treatment of radioactive secondary waste produced from waterjet abrasive suspension cutting

Abstract. Dismantling of reactor pressure vessels and their built-in components is an enormous challenge in the deconstruction of a nuclear power plant. Due to the years of exposure to neutron radiation, the activated components can only be dismantled and packaged remotely. For reasons of radiation protection, preference is given to techniques that can be used underwater due to the shielding effect. A cutting method that meets these requirements is the waterjet abrasive suspension cutting technique (WAS). The cutting tool is capable of slicing metallic internals and other materials using a pure jet of water mixed with an abrasive substance at high velocity and pressure. The process offers numerous technical advantages, but it has a major disadvantage in producing secondary waste. Due to the addition of the abrasive substance, the WAS process produces a waste mixture of inactive abrasive particles and radioactive steel particles (activated by neutron radiation) during the dismantling of steel components in nuclear facilities. Since the steel particles are radioactive when the reactor pressure vessel (RPV) and its internals are dismantled, this particle mixture currently has to be disposed of as radioactive waste. This leads to a doubling of the radioactive waste. Despite the technical advantages, the WAS process used for cutting purposes is a severely disadvantage from an economic point of view, considering the significant disposal costs of the radioactive waste. The research project NaMaSK (wet sieving and magnetic separation of grain mixtures to minimise secondary waste in the dismantling of nuclear facilities), funded by the German Federal Ministry of Education and Research (BMBF), aims to separate the two fractions (abrasive and steel particles) with the help of magnetic separation and wet sieving. For this purpose, a prototype separation system MaSK (magnetic separation of grain mixtures to minimise secondary waste in the dismantling of nuclear facilities) with a magnetic filter and sieve has already been built and tested, and it can separate up to 98 % of the steel particles from the mixture. The separation process aimed to reduce the total amount of secondary waste by reusing abrasive particles for further WAS cutting. In the new test plant NaMaSK, the mode of operation will be converted from a batch process to continuous operation to highlight the economic aspect of the separation process. In this regard, an efficient design of the sieve structure and magnetic filter, followed by process optimisation, will be implemented. These new developments and the first results will be presented at the conference.

SmartOCT: smartphone-integrated optical coherence tomography.

Smartphone devices have seen unprecedented technical innovation in computational power and optical imaging capabilities, making them potentially invaluable tools in scientific imaging applications. The smartphone's compact form-factor and broad accessibility has motivated researchers to develop smartphone-integrated imaging systems for a wide array of applications. Optical coherence tomography (OCT) is one such technique that could benefit from smartphone-integration. Here, we demonstrate smartOCT, a smartphone-integrated OCT system that leverages built-in components of a smartphone for detection, processing and display of OCT data. SmartOCT uses a broadband visible-light source and line-field OCT design that enables snapshot 2D cross-sectional imaging. Furthermore, we describe methods for processing smartphone data acquired in a RAW data format for scientific applications that improves the quality of OCT images. The results presented here demonstrate the potential of smartphone-integrated OCT systems for low-resource environments.

Towards Differential Static Magnetic Localization of Commercial Capsule Endoscopes: An Evaluation Using Different Ring and Cylindrical Magnets

Abstract. Capsule endoscopy is a promising diagnostic tool for the entire gastrointestinal tract. Since a patient swallows the capsules, their size must be sufficiently small. The principal built-in components are cameras, silver-oxide batteries, light emitting diodes, and an antenna for transmitting the video. For diagnosis and treatment, the precise localization of the capsules for specific video frames is required. Recently, static magnetic localization of these capsules with an integrated permanent magnet showed promising results. However, in the state-of-the-art, relatively large magnets compared to the small capsules were used. Therefore, in this extended paper, the localization performance of a recently proposed optimized differential static magnetic localization method for different sized disc and ring magnets was evaluated. The ring magnets were designed for integration with the two batteries of commercial capsules. The magnets were evaluated in static and dynamic scenarios to evaluate the performance of the method in a patient's daily life. It was revealed that the mean position and orientation errors did not exceed 5 mm and 4∘, respectively, for all applied magnets except for the 1.5 and 3 mm long disc magnets. Moreover, the results indicated that the ferromagnetic batteries of capsule endoscopes increase the localization performance when they are centered within a diametrical ring magnet. Overall, it was revealed that the localization performance of the optimized differential method is significantly better than the state-of-the-art even when the magnet volume is significantly reduced compared to previous work. Therefore, it was concluded that 5 mm long disc magnet or a ring magnet are excellent candidates for integration into a commercial capsule for magnetic localization and yield the advantage of being passive magnetic sources.

A methodology to identify identical single-board computers based on hardware behavior fingerprinting

The connectivity and resource-constrained nature of single-board devices open the door to cybersecurity concerns affecting Internet of Things (IoT) scenarios. One of the most important issues is the presence of unauthorized IoT devices that want to impersonate legitimate ones by using identical hardware and software specifications. This situation can provoke sensitive information leakages, data poisoning, or privilege escalation in IoT scenarios. Combining behavioral fingerprinting and Machine/Deep Learning (ML/DL) techniques is a promising approach to identify these malicious spoofing devices by detecting minor performance differences generated by imperfections in manufacturing. However, existing solutions are not suitable for single-board devices since they do not consider their hardware and software limitations, underestimate critical aspects such as fingerprint stability or context changes, and do not explore the potential of ML/DL techniques. To improve it, this work first identifies the essential properties for single-board device identification: uniqueness, stability, diversity, scalability, efficiency, robustness, and security. Then, a novel methodology relies on behavioral fingerprinting to identify identical single-board devices and meet the previous properties. The methodology leverages the different built-in components of the system and ML/DL techniques, comparing the device internal behavior with each other to detect variations that occurred in manufacturing processes. The methodology validation has been performed in a real environment composed of 15 identical Raspberry Pi 4 Model B and 10 Raspberry Pi 3 Model B＋ devices, obtaining a 91.9% average TPR with an XGBoost model and achieving the identification for all devices by setting a 50% threshold in the evaluation process. Finally, a discussion compares the proposed solution with related work, highlighting the fingerprint properties not met, and provides important lessons learned and limitations.

Validation of Novel Ultrasonic Phased Array Borehole Probe by Using Simulation and Measurement

Low-frequency ultrasonic testing is a well-established non-destructive testing (NDT) method in civil engineering for material characterization and the localization of cracks, reinforcing bars and delamination. A novel ultrasonic borehole probe is developed for in situ quality assurance of sealing structures in radioactive waste repositories using existing research boreholes. The aim is to examine the sealing structures made of salt concrete for any possible cracks and delamination and to localize built-in components. A prototype has been developed using 12 individual horizontal dry point contact (DPC) shear wave transducers separated by equidistant transmitter/receiver arrays. The probe is equipped with a commercially available portable ultrasonic flaw detector used in the NDT civil engineering industry. To increase the sound pressure generated, the number of transducers in the novel probe is increased to 32 transducers. In addition, the timed excitation of each transducer directs a focused beam of sound to a specific angle and distance based on the previously calculated delay time. This narrows the sensitivity of test volume and improves the signal-to-noise ratio of the received signals. In this paper, the newly designed phased array borehole probe is validated by beam computation in the CIVA software and experimental investigations on a half-cylindrical test specimen to investigate the directional characteristics. In combination with geophysical reconstruction methods, it is expected that an optimised radiation pattern of the probe will improve the signal quality and thus increase the reliability of the imaging results. This is an important consideration for the construction of safe sealing structures for the safe disposal of radioactive or toxic waste.

A Comparative Study of TVOC and HCHO Emissions From Various Multilayer Built-in Furniture Components Based on ISO 16000-9:2006 Emission Test Chamber Methods

Multilayer materials of built-in furniture components emit volatile organic compounds (VOCs) into the indoor environment. Although many green building rating systems have set criteria for indoor environments, typical buildings in Thailand have not implemented these requirements, especially for local furniture. This study aimed to identify the magnitude of VOC emissions and the relationships between these VOC emissions and inner structures, finishing techniques used for built-in components, and the cost of interior built-in furniture built by local contractors. A total of 33 specimens of built-in components normally found in Thailand were prepared and wrapped in plastic before being transported to the test facility. The total volatile organic compound (TVOC) and formaldehyde (HCHO) emission rates were measured using emission test chambers, as per the ISO 16000-9 standard, with a size of 0.21 m³, at a temperature of 23 °C, a relative humidity of 45%, an air exchange rate of 0.5 ACH, and a loading factor of 0.42 m²m-³. The measurements were conducted 3 days and 28 days after the specimens were unwrapped. It was found that specimens finished with coating techniques had the highest TVOC and HCHO emission rates, while those with single-layer materials that used covering techniques had the lowest TVOC and HCHO emission rates. The covering techniques were found to be cheaper but less durable than coating techniques. All specimens exhibited high emission concentrations in the chambers (i.e., more than the standard limit) even after 28 days. This should help raise awareness of the importance of selecting built-in furniture based on finishing techniques that make use of low-VOC materials, which are available on the market and provide better indoor air quality.

Flue Gas Composition and Treatment Potential of a Waste Incineration Plant

Waste-to-energy (WtE) incineration is an important technique in waste management systems and waste hierarchy. It is used to treat approximately 63% of the waste in European countries. The flue gas volumetric rate and its composition are essential to determine and monitor the emissions from waste incineration plants. This paper presents two methodologies used to evaluate the emissions from incinerators during the design phase. The first consists of a set of equations applicable in Excel (calculation model), while the second is the built-in components in Ebsilon 13.2 software which simulates the emissions from a furnace. This paper also proposes a comprehensive flue gas cleaning system for a simulated waste incineration plant in Jordan. According to Ebsilon, the results showed that for a 25 kg/s loading rate, there was 258,514 mg/Nm3, 749.90 mg/Nm3, 890.20 mg/Nm3, and 717 mg/Nm3 of CO2, NO2, SO2, and HCL, respectively. It was noted that these values relate to 1.5 of excess air ratio, where the effect of excess air ratio as the main driver for any combustion process was examined. The calculation method (set of equations) evaluated the flue gas volumetric rate, the CO2 emissions, and N2O and SO2 levels. Ebsilon allows for simulation of the treatment stages and calculates the amount of materials required. Selective non-catalytic reduction (SNCR) (a built-in component in the Ebsilon library) was used to treat the NO2 emissions. For 1.5 of excess air ratio, those emissions were reduced from 749 mg/Nm3 to 180 mg/Nm3, while the Ca(OH)2 injector used to treat the SO2 and HCL emissions reduced emissions from 890.20 mg/Nm3 and 717 mg/Nm3 to 44 mg/Nm3 and 7.16 mg/Nm3, respectively. Regarding the reduction in CO2, the spherical carbon absorption concept was simulated using 9.4 kg/s of carbon which was adequate to verify a 91% reduction rate of CO2. Furthermore, the calculation model was validated and approved as a valuable model to predict the flue gas volume, the oxygen required, and flue gas emissions at the design stage.

Wearable multifunctional soft sensor and contactless 3D scanner using supersonically sprayed silver nanowires, carbon nanotubes, zinc oxide, and PEDOT:PSS

The multifunctional soft sensor developed here is capable of simultaneously sensing six stimuli, including pressure, bending strain, temperature, proximity, UV light, and humidity, with high accuracy and without interference among the respective built-in components. The sensor is fabricated via a facile, scalable, and cost-effective supersonic cold-spraying method using silver nanowires (AgNWs), carbon nanotubes (CNTs), zinc oxide (ZnO), and conducting polymer poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). A mask and laser cutter are used in conjunction with the supersonic cold-spraying method to produce miniaturized multifunctional sensors that can be readily installed on various substrates; for example, the production of gloves capable of multifunctional sensing. In particular, the proximity sensor of the multifunctional glove sensor can produce a three-dimensional (3D) image of a scanned object, showing high potential for use in military, medical, and industrial applications.

5G-Compatible IF-Over-Fiber Transmission Using a Low-Cost SFP-Class Transceiver

With the rise of 5G and beyond, the ever-increasing data-rates demanded by mobile access are severely challenging the capacity of optical fronthaul networks. Despite its high reliability and ease of deployment, legacy digital radio-over-fiber (RoF) technologies face an upcoming bandwidth bottleneck in the short term. This has motivated a renewed interest in the development of analog RoF alternatives, owing to their high spectral efficiency. However, unlike its digital counterpart, analog RoF transmission requires a highly linear transceiver to guarantee signal fidelity. Typical solutions exploited in recent research works tend to adopt the use of bulky benchtop components, such as directly modulated lasers (DML) and photodiodes. Although this provides a convenient and quick path for proof-of-concept demonstrations, there is still a considerable gap between lab developments and commercial deployment. Most importantly, a key question arises: can analog-RoF transceivers meet the 5G requirements while being competitive in terms of cost and footprint? Following this challenge, in this work we exploit the use of a low-cost commercial off-the-shelf (COTS) small form-factor pluggable (SFP) transceiver, originally designed for digital transmission at 1 Gbps, which is properly adapted towards analog RoF transmission. Bypassing the digital electronics circuitry of the SFP, while keeping the original transmitter optical sub-assembly (TOSA) and receiver optical sub-assembly (ROSA), we demonstrate that high-performance 5G-compatible transmission can be performed by reusing the key built-in components of current low-cost SFP-class transceivers. Particularly, we demonstrate error vector magnitude (EVM) performances compatible with 5G 64QAM transmission both at 100MHz and 400MHz. Furthermore, employing a memory polynomial model for digital pre-distortion of the transmitted signal, we achieve 256QAM-compatible performance at 100MHz bandwidth, after 20 km fronthaul transmission.

3D printed solder masks for printed circuit boards

The use of additive technologies in the creation of soldering masks opens up new opportunities in the production of printed circuit boards, in particular, the use of soldering masks for boards with integrated components. The paper considers the results of experimental data on the adhesion of 3D soldering masks (that is, masks created on a 3D printer) obtained during the study of the introduction of 3D printing into electronic manufacturing processes. For the analysis of adhesion, it is possible to use such methods as breaking load, cross-cut test, and the sticky tape method. A number of experiments were conducted to study the adhesion by testing the breaking load. The samples were formed with different ratios of prepreg/solder mask, then the force at which the fracture occurred was measured. The essence of the cross-cut test is to apply at least three parallel cuts and perpendicular to them also at least three parallel cuts with the tip of the cutter. After the scratching, there must be no flaking of the coating between the lines and in the grid of squares, then the results are assessed. Sticky tape tests are performed by applying the tape with the adhesive side to the test sample with a cured coating applied. The results are assessed by visual inspection using an optical device that provides 3x magnification. The results of the breaking load experiments indicate that 3D masks show comparable separation forces with a prepreg. At the same time, the force is stable for all types of surfaces and practically does not depend on the thickness and configuration of the 3D mask. Experiments with applying cross-cuts show consistently good results with a homogeneous base material – there are no coating detachments. The paper concludes that the use of 3D soldering masks on the inner layers of multilayer printed circuit boards with built-in components is possible, but a number of issues must be solved for this, including those related to the software for forming 3D structures of masks.

Sefaira Simulation in Residential Houses to Determine the Energy Use of Wall Materials

Wall material popularly used in Indonesia is a masonry wall, where the process takes longer than prefabrication wall materials or houses built-in components such as panels or modules. In this study, four types of prefabrication wall materials will be analyzed based on the annual energy use of each material. The wall materials chosen are Hebel, Alderon, Glassfibre Reinforced Cement Board (GRC), and metal deck. The calculation of energy consumption uses a simulation of a 27 m2 one-floor residential building located in Bandung City, West Java, Indonesia. Furthermore, the simulation is analyzed with Sefaira software based on ASHRAE 90.1 - 2013. From the results of this Sefaira analysis, it is obtained that the Energy Use Intensity (EUI) value for Hebel wall material is 58 kWh/m2/yr, Alderon wall 90 kWh/m2/yr, Glassfiber Reinforced Cement Board (GRC) 83 kWh/m2/yr, and metal deck 89 kWh/m2/yr. Among the four recommended prefabricated wall materials, Hebel materials are considered to have the least energy use. Meanwhile, the EUI target of the 2030 Challenge for residential houses is 38 kWh/m2/yr, so it must reduce as much as 45 kWh/m2/yr for Hebel material.

Mesa Python platform for agent-based modelling

Mesa is a licensed by Apache development environment for agent-based models (or ABM) in Python. It allows users to create agent-based models using built-in basic components (such as spatial and agent schedulers) or custom implementations; visualize them using the interface in a web browser; and analyze their results using Python data analysis tools. The purpose of the development of the environment was the desire of the authors to create an alternative for NetLogo, Repast or MASON based on the Python language.

Microphone Identification Using Convolutional Neural Networks

The ability to identify mobile phones through their built-in components has been demonstrated in the literature for various types of sensors including charge coupled devices (CCD)/complementary metal–oxide semiconductors (CMOS), accelerometers, magnetometers, and microphones. The identification is performed by exploiting small but significant differences in the electronic circuits generated during the manufacturing process. Thus, these distinctive traces become an intrinsic property of the electronic components, which can be detected and exploited as a unique fingerprints associated with the mobile phone. Such fingerprints can be used in various scenarios, especially in security and forensics related applications. In this article, the identification of mobile phones through their built-in microphone by means of convolutional neural networks (CNNs) is investigated. In this specific context, CNNs have received very limited attention by the research community so far. An experimental dataset is created by collecting microphone responses from 34 different mobile phones. These responses are then used to perform classification through CNNs. On different experiments, the proposed CNN is able to provide encouraging results; in particular, the achieved identification accuracy of CNNs is superior to the one obtained with more conventional machine learning algorithms like the K -nearest neighbor and support vector machine, also in the presence of additive white Gaussian noise.

Analysis of Operational Events Caused by Faults of NPP Digital Instrumentation and Control Systems

The paper presents the analysis of operational events at nuclear power plants (NPPs) of Ukraine caused by failures and defects of the instrumentation and control systems (I&C systems). The effort contains statistical information about the number and the share of operational events at Ukrainian NPPs due to incorrect performance of analog and digital I&C systems in the general amount of events. The categories of these events according to the international and national classifications have been considered. The paper provides for the brief overview of the recently published EC Joint Research Center Technical Report on digital I&C systems at NPPs of foreign countries based on the information from IAEA and U.S. NRC databases. There are causes of operational events due to defects of the specified systems and main recommendations on their prevention. Using the approach similar to the one in the Technical Report, the paper presents the detailed analysis of direct and root causes, as well as correction measures for the operational events at Ukrainian NPPs from 2013 to 2018 caused by digital I&C systems. The experts considered separately four groups of events due to defects of components in the peripheral part of the digital I&C systems (sensors, actuators), central part of digital I&C systems (software and hardware), cable lines and electronic components of analog I&C systems (built-in components). There is an additional analysis of root causes of events related to digital I&C systems by the types of systems and lifecycle stages (design, mounting, operation) and main sources of occurrences within the systems (software, hardware, cables, etc.).

Shape stability of chosen thin wood based panels after heating

Shape stability of chosen thin wood based panels after heating. Lignocellulose board materials are commonly used for furniture construction. Typically, these are particle boards, fibreboard or plywood with thicknesses from 10 to 20 mm, however, some furniture elements are made of thin boards with a thickness of 3-4 mm (back walls, bottoms of drawers and others). Modern furniture uses built-in components that are a source of heat, such as lamps, power supplies, ovens. Local high temperature may negatively affect the shape stability of thin lignocellulose plates. The aim of the research described in this article was to determine the impact of shortterm exposure to high temperature on the dimensional stability of selected thin plate furniture materials. Four different HDF boards with nominal thicknesses of 3 mm and four different plywood boards with nominal thicknesses of 2 to 4 mm were tested. The test samples were subjected to a short-term exposure to temperatures of up to 250°C. As a result of the tests, it was found that HDF boards are characterized by a much higher shape stability at elevated temperature than boards made of plywood.

Reconstruction of edges in digital building models

Traditionally, the geometry of building components or rooms is either described by their boundary or it is defined by constructive solid models. Modeling tools are available which are based on the principle of constructing building components and of composing a building by adding building components step by step. However, topological relations are relevant besides the shape of components and rooms. These topological relationships are not necessarily explicit information in boundary representation or constructive solid models. As a consequence, they must be computed. At present time, there exists to the best knowledge of the author only a single approach in this subject area that is able to reconstruct topological relations including their geometry. The objects which need to be considered are building components, built-in components and rooms. The challenge is to calculate the three relevant aspects of geometry in digital building models completely and in an efficient way. These three relevant aspects are clashes, voids and contact faces. The existing approach to calculate these aspects is based on space partitioning concepts. Space partitioning concepts store neighboring relations explicitly. The approach presented in this paper is also based on space partitioning. One basic and novel consideration of the approach presented in this paper is to execute the reconstruction procedure in a mesh. The mesh itself is not refined anymore at a certain point during the calculations to avoid uncontrollable refinements. The second basic and novel consideration is the way of avoiding topological inconsistencies. Integer values are chosen for coordinates, and a specific algorithm is presented that guarantees that topological inconsistencies cannot occur. The research presented in this paper addresses the first step on the way to compute clashes, voids and contact faces. This is the reconstruction of edges. This paper presents the theory and a pilot implementation for the reconstruction of straight edges. Examples show the benefits of the approach presented. Open questions are discussed.

Magnetic nanochain integrated microfluidic biochips

Microfluidic biochips hold great potential for liquid analysis in biomedical research and clinical diagnosis. However, the lack of integrated on-chip liquid mixing, bioseparation and signal transduction presents a major challenge in achieving rapid, ultrasensitive bioanalysis in simple microfluidic configurations. Here we report magnetic nanochain integrated microfluidic chip built upon the synergistic functions of the nanochains as nanoscale stir bars for rapid liquid mixing and as capturing agents for specific bioseparation. The use of magnetic nanochains enables a simple planar design of the microchip consisting of flat channels free of common built-in components, such as liquid mixers and surface-anchored sensing elements. The microfluidic assay, using surface-enhanced Raman scattering nanoprobes for signal transduction, allows for streamlined parallel analysis of multiple specimens with greatly improved assay kinetics and delivers ultrasensitive identification and quantification of a panel of cancer protein biomarkers and bacterial species in 1 μl of body fluids within 8 min.

Abstract P133: Epigenome-Wide Association Study of Moderate-Vigorous Physical Activity in Adult African Americans Identifies Loci Near HCCA2

Regular moderate-vigorous physical activity (MVPA) reduces the risk of cardiovascular and other chronic diseases, among other important benefits at all life stages. It is hypothesized that physical activity may alter disease risk via epigenetic modifications, including potentially long-standing changes in DNA methylation as previous research has shown epigenetic changes following exercise interventions. Most existing reports examine global methylation or study acute exercise effects on DNA methylation. To our knowledge, there are no published epigenome-wide association studies (EWAS) of habitual MVPA. In this analysis, we tested associations between leisure time MVPA and genome-wide variation in CpG methylation, an epigenetic mark, in 2,601 African American participants (1,663 women; mean age 56.6 years) in the Atherosclerosis Risk in Communities (ARIC) study. The Illumina HM450K Bead Chip was used to measure methylation in 471,035 CpG sites in stored frozen leukocyte samples, from visit 2 (1990-1992) or 3 (1993-1995). Linear regression models tested the cross-sectional association of DNA methylation M-value with self-reported leisure time MVPA at the visit of sample collection, modeled as minutes of MVPA per week and by category based on the AHA guidelines for physical activity in adults (none, less than 150, or at least 150 minutes MVPA per week), adjusting for age, sex, body mass index, education, alcohol use in grams per week, smoking status, cancer status, white blood cell count, imputed cell-type proportions using the Houseman method, and batch effects with the top 30 HM450K built-in nonnegative control probe principal components. Three CpGs, cg08269485, cg20272155, and cg08966208, upstream of the cathepsin D encoding gene, CTSD, were observed to be significantly inversely associated (q<0.05, FDR) with MVPA minutes/week. This is a strongly imprinted genomic region (chr11p15.5) and the region has also been reported to include DNA methylation variants that changed in response to an exercise training intervention. Additionally, 163 CpGs that we identified in the literature to be associated with habitual MVPA were also tested using the same models. One CpG, cg07863043, upstream of the adenomatosis polyposis coli gene, APC, in the 5q22.2 genomic region, was observed to be significantly positively associated with achieving at least 150 minutes of MVPA per week compared to none (q=0.0001, FDR). APC encodes a tumor suppressor protein that is an antagonist of the Wnt signaling pathway, and is involved in carcinogenesis and embryonic development. Replication in other populations is ongoing to confirm these findings as well as to identify additional physical activity-related DNA methylation variants.