This paper presents the design and analysis of a novel passive Ultra High Frequency (UHF) radio frequency identification (RFID) based sensor for crack detection in coal mining conveyor belts. The ...proposed sensor is built on an interdigital capacitor (IDC) based resonator integrated with a commercial UHF RFID chip. The paper illustrates the theoretical sensing principles of the sensor along with its design requirements. To enable the operation of the conveyor belt sample in the UHF band, a dielectric characterization of the belt is performed. This characterization helps obtain the material parameters of the belt, such as the dielectric constant and loss tangent. A thorough analysis of the proposed sensor in terms of simulation and experiment is also exemplified in this paper. Both simulated and experimental studies cater to a robust sensor performance for detecting cracks in the conveyor belt environment. The simulated analysis illustrates the variation of different sensing parameters, including impedance, gain, and backscattered power, with respect to different crack widths, orientations, and locations. The experimental results of fabricated sensor prototypes eventually manifest the backscattered power variation of the sensor into the change of received signal strength indicator (RSSI). An extensive analysis of the experimentally obtained results demonstrates that the proposed sensor can reliably and efficiently detect the presence and growth of cracks along with their variation in widths and orientations. The validation of simulated results through experiments essentially lays the basis for adopting machine learning based crack characterization in the future.
Accurate and early detection of biomarkers provides the molecular evidence for disease management, allowing prompt actions and timely treatments to save lives. Multivalent biomolecular interactions ...between the probe and biomarker as well as controlled probe orientation on material surfaces are keys for highly sensitive detection. Here we report the bioengineering of programmable and multifunctional nanoprobes, which can provide rapid, specific and highly sensitive detection of emerging diseases in a range of widely used diagnostic systems. These nanoprobes composed of nanosized cell wall fragments, termed as synthetic bionanofragments (SynBioNFs), are generated by the fragmentation of genetically programmed yeast cells. SynBioNFs display multiple copies of biomolecules for high-affinity target binding and molecular handles for the precisely orientated attachment on surfaces used in diagnostic platforms. SynBioNFs are demonstrated for the capture and detection of SARS-CoV-2 virions using multiple diagnostic platforms, including surface-enhanced Raman scattering, fluorescence, electrochemical and colorimetric-based lateral flow systems with sensitivity comparable with the gold-standard reverse-transcription quantitative polymerase chain reaction.
In article number 1704025, Matt Trau and co‐workers report the use of alternating current electrohydrodynamic (ac‐EHD) fluidic manipulation to create an adjustable nanoscaled mixing effect to ...optimally enhance traditionally‐slow probe‐RNA target hybridization. This is a novel approach for amplification‐free multi‐RNA type profiling, with high detection sensitivity and reliability for use in cancer liquid biopsies.
Smart farming has the potential to overcome the challenge of 2050 to feed 10 billion people. Both artificial intelligence (AI) and the internet of things (IoT) have become critical prerequisites to ...smart farming due to their high interoperability, sensors, and cutting-edge technologies. Extending the role of responsible leadership, this paper proposes an AI and IoT based smart farming system in Bangladesh. With a comprehensive literature review, this paper counsels the need to go beyond the simple application of traditional farming and irrigation practices and recommends implementing smart farming enabling responsible leadership to uphold sustainable agriculture. It contributes to the current literature of smart farming in several ways. First, this paper helps to understand the prospect and challenges of both AI and IoT and the requirement of smart farming in a nonwestern context. Second, it clarifies the interventions of responsible leadership into Bangladesh’s agriculture sector and justifies the demand for sustainable smart farming. Third, this paper is a step forward to explore future empirical studies for the effective and efficient use of AI and IoT to adopt smart farming. Finally, this paper will help policymakers to take responsible initiatives to plan and apply smart farming in a developing economy like Bangladesh.
Circulating biomarkers have emerged as promising non-invasive, real-time surrogates for cancer diagnosis, prognosis and monitoring of the therapeutic response. Current bio-sensing techniques mostly ...involve detection of either circulating cells or proteins which are inadequate in unfolding complex pathologic transformations. Herein, we report parallel detection of cellular and molecular markers (protein) for cancer using a multiplex platform featuring (i) graphene oxide (GO) functionalization that increases the active surface area and more importantly reduces the functionalization steps for rapid detection, (ii) alternating-current electrohydrodynamic (ac-EHD) fluid flow that provides delicate micro-mixing to enhance target-sensor interactions thereby minimizing non-specific binding and (iii) surface enhanced Raman scattering (SERS) for multiplex detection. We find that our platform possesses high sensitivity for detecting both proteins and cells. More importantly, this platform not only detects the cancer cells but also can simultaneously monitor the heterogeneous expression of cell surface proteins which could be clinically useful to determine effective patient therapy. We demonstrate the specific and sensitive detection of breast cancer cells from a mixture of non-target cells and report the heterogeneous expression of human epidermal growth factor receptor 2 (HER2) proteins on the individual cancer cell surface. Concurrently, we detect as low as 100 fg mL
HER2 and Mucin 16 proteins spiked in blood serum.
Immune checkpoint proteins (ICPs) play a major role in a patient's immune response against cancer. Tumour cells usually express those proteins to communicate with immune cells as a process of ...escaping the anti-cancer immune response. Detecting the major functional immune checkpoint proteins present on cancer cells (such as circulating tumor cells or CTCs) and examining the heterogeneity in their expression at the single-cell level could play a crucial role in both cancer diagnosis and the monitoring of therapy. In this study, we develop a mesoporous gold biosensor to precisely assess ICP heterogeneity in individual cancer cells within a lung cancer model. The platform utilizes a nanostructured mesoporous gold surface to capture CTCs and a Surface Enhanced Raman Scattering (SERS) readout to identify and monitor the expression of key ICP proteins (PD-L1, B7H4, CD276, CD80) in lung cancer cells. The homogeneous and abundant pores in mesoporous 3D gold nanostructures enable increased antibody loading on-chip and an enhanced SERS signal, which are key to our single cell capture, and accurate analysis of ICPs in cancer cells with high sensitivity. Our lung cancer cell line model data showed that our method can detect single cells and analyse the expression of four lung cancer associated ICPs on individual cell surfaces during treatment. To show the potential of our mesoporous gold biosensor in analysing clinical samples, we tested 9 longitudinal Peripheral Blood Mononuclear Cells (PBMC) samples from lung cancer patient before and after therapy. Our mesoporous biosensor successfully captured single CTCs and found that the expression of ICPs in CTCs is highly heterogeneous in both pre-treatment and treated PBMC samples isolated from lung cancer patient blood. We suggest that our findings will help clinicians in selecting the most appropriate therapy for patients.
Monitoring soluble immune checkpoints in circulating fluids has the potential for minimally-invasive diagnostics and personalised therapy in precision medicine. Yet, the sensitive detection of ...multiple immune checkpoints from small volumes of liquid biopsy samples is challenging. In this study, we develop a multiplexed immune checkpoint biosensor (MICB) for parallel detection of soluble immune checkpoints PD-1, PD-L1, and LAG-3. MICB integrates a microfluidic sandwich immunoassay using engineered single chain variable fragments and alternating current electrohydrodynamic in situ nanofluidic mixing for promoting biosensor-target interaction and reducing non-specific non-target binding. MICB provides advantages of simultaneous analysis of up to 28 samples in <2 h, requires as little as a single sample drop (i.e., 20 μL) per target immune checkpoint, and applies high-affinity yeast cell-derived single chain variable fragments as a cost-effective alternative to monoclonal antibodies. We investigate the assay performance of MICB and demonstrate its capability for accurate immune checkpoint detection in simulated patient serum samples at clinically-relevant levels. MICB provides a dynamic range of 5 to 200 pg mL-1 for PD-1 and PD-L1, and 50 to 1000 pg mL-1 for LAG-3 with a coefficient of variation <13.8%. Sensitive immune checkpoint detection was achieved with limits of detection values of 5 pg mL-1 for PD-1, 5 pg mL-1 for PD-L1, and 50 pg mL-1 for LAG-3. The multiplexing capability, sensitivity, and relative assay simplicity of MICB make it capable of serving as a bioanalytical tool for immune checkpoint therapy monitoring.
Conveyor belts in mining sites are prone to cracks, which leads to dramatic degradation of overall system performance and the breakdown of operation. Crack detection using radio frequency ...identification (RFID) sensing technology is recently proposed to provide robust and low-cost health monitoring systems for conveyor belts. The intelligent machine learning (ML) technique is one of the most promising solutions for crack detection and successful implementation within the IoT paradigm. This paper presents a conveyor belt structural health monitoring (SHM) model using ML and Internet of Things (IoT) connectivity. The model is extensively tested, and the classification is conducted based on simulated data obtained from an Ultra High Frequency (UHF) RFID sensor. Here, the sensor is laid on a belt, and the data are obtained at different crack orientations of vertical, horizontal, and diagonal cracks, for varying crack widths of 0.5 to 5 mm at 10 different locations on the sensor. The ML model is tested with different input features and training algorithms, and their performances are compared and analysed to identify the superior input feature and training algorithm. This method produces high accuracy in determining crack width, orientation, and location. The findings show that the proposed detection system based on ML modelling could detect cracks with 100% accuracy. The proposed system can also distinguish between vertical, horizontal, and diagonal cracks with an accuracy of 83.9%, and has a significant identification rate of 84.4% accuracy for detecting crack-width as narrow as 0.5 mm. Moreover, the model can predict the region of the crack with an accuracy of 95.5%. Overall, the results show that the proposed model is very robust and can perform SHM of conveyor belts with high accuracy for a range of parameters and classification scenarios. The method has huge industrial significance in coal mines.
Assessing T-cell mediated immune status can help to understand the body's response to disease and also provide essential diagnostic information. However, detection and characterization of immune ...response are challenging due to the rarity of signature biomolecules in biological fluid and require highly sensitive and specific assay technique for the analysis. Until now, several techniques spanning from flow cytometry to microsensors have been developed or under investigation for T-cell mediated immune response monitoring. Most of the current assays are designed to estimate average immune responses, i.e., total functional protein analysis and detection of total T-cells irrespective of their antigen specificity. Although potential, immune response analysis without detecting and characterizing the rare subset of T-cell population could lead to over or underestimation of patient's immune status. Addressing this limitation, recently a number of technological advancements in biosensing have been developed for this. The potential of simple and precise micro-technologies including microarray and microfluidic platforms for assessing antigen-specific T-cells will be highlighted in this review, together with a discussion on existing challenges and future aspects of immune-sensor development.
Evolution of mobile broadband is ensured by adopting a unified and more capable radio interface (RI). For ubiquitous connectivity among a wide variety of wireless applications, the RI enables the ...adoption of an adaptive bandwidth with high spectrum flexibility. To this end, the modern-day communication system needs to cater to extremely high bandwidth, starting from below 1 GHz to 100 GHz, based on different deployments. This instigates the creation of a platform called the Internet of Everything (IoE), which is based on the concept of all-round connectivity involving humans to different objects or things via sensors. In simple words, IoE is the intelligent connection of people, processes, data, and things. To enable seamless connectivity, IoE resorts to low-cost, compact, and flexible broadband antennas, RFID-based sensors, wearable electromagnetic (EM) structures, circuits, wireless body area networks (WBAN), and the integration of these complex elements and systems. IoE needs to ensure broader information dissemination via simultaneous transmission of data to multiple users through separate beams and to that end, it takes advantage of metamaterials. The precise geometry and arrangement of metamaterials enable smart properties capable of manipulating EM waves and essentially enable the metamaterial devices to be controlled independently to achieve desirable EM characteristics, such as the direction of propagation and reflection. This review paper presents a comprehensive study on next-generation EM devices and techniques, such as antennas and circuits for wearable and sub 6 GHz 5G applications, WBAN, wireless power transfer (WPT), the direction of arrival (DoA) of propagating waves, RFID based sensors for biomedical and healthcare applications, new techniques of metamaterials as well as transformation optics (TO) and its applications in designing complex media and arbitrary geometry conformal antennas and optical devices that will enable future IoE applications.
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