Sensors MDPI

🗺️ Layer-by-Layer Immobilization of DNA Aptamers on Ag-Incorporated Co-Succinate Metal–Organic Framework for Hg(II) Detection 🧑 Shubham S. Patil, Vijaykiran N. Narwade, Kiran S. Sontakke, Tibor Hianik* and Mahendra D. Shirsat* 🏫 Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Faculty of Mathematics, Physics and Informatics, Comenius University 🔎 Layer-by-layer (LbL) immobilization of #DNAaptamers in the realm of #electrochemical detection of #heavymetal ions (HMIs) offers an enhancement in specificity, sensitivity, and low detection limits by leveraging the cross-reactivity obtained from multiple interactions between immobilized aptamers and developed material surfaces. In this research, we present a LbL approach for the immobilization of thiol- and amino-modified DNA aptamers on a Ag-incorporated cobalt-succinate metal–organic framework (MOF) (Ag@Co-Succinate) to achieve a cross-reactive effect on the electrochemical behavior of the sensor. The solvothermal method was utilized to synthesize Ag@Co-Succinate, which was also characterized through various techniques to elucidate its structure, morphology, and presence of functional groups, confirming its suitability as a host matrix for immobilizing both aptamers. The Ag@Co-Succinate aptasensor exhibited extraordinary sensitivity and selectivity towards Hg(II) ions in electrochemical detection, attributed to the unique binding properties of the immobilized aptamers. The exceptional limit of detection of 0.3 nM ensures the sensor’s suitability for trace-level Hg(II) detection in various environmental and analytical applications. Furthermore, the developed sensor demonstrated outstanding repeatability, highlighting its potential for long-term and reliable monitoring of Hg(II). https://lnkd.in/gN6QFcW2

🗺️ Determination of N-Acetyl-L-cysteine Ethyl Ester (NACET) by Sequential Injection Analysis 🧑 Lea Kukoc-Modun*, Tomislav Kraljevic, Dimitrios Tsikas, Tony G. Spassov and Spas D. Kolev* 🏫 University of Split, Sveučilište u Mostaru - University of Mostar, Sofia University, University of Melbourne 🔎 New #sequentialinjectionanalysis (SIA) methods with #optical sensing for the determination of N-acetyl-L-cysteine ethyl ester (NACET) have been developed and optimized. NACET is a potential drug and antioxidant with advantageous pharmacokinetics. The methods involve the reduction of Cu(II) in its complexes with neocuproine (NCN), bicinchoninic acid (BCA), and bathocuproine disulfonic acid (BCS) to the corresponding chromophoric Cu(I) complexes by the analyte. The absorbance of the Cu(I) complexes with NCN, BCA, and BCS was measured at their maximum absorbance wavelengths of 458, 562, and 483 nm, respectively. The sensing manifold parameters and experimental conditions were optimized for each of the Cu(II) complexes used. Under optimal conditions, the corresponding linear calibration ranges, limits of detection, and sampling rates were 8.0 × 10−6–2.0 × 10−4 mol L−1, 5.5 × 10−6 mol L−1, and 60 h−1 for NCN; 6.0 × 10−6–1.0 × 10−4 mol L−1, 5.2 × 10−6 mol L−1, and 60 h−1 for BCA; and 4.0 × 10−6–1.0 × 10−4 mol L−1, 2.6 × 10−6 mol L−1, and 78 h−1 for BCS. The Cu(II)-BCS complex was found to be best performing in terms of sensitivity and sampling rate. Usual excipients in pharmaceutical preparations did not interfere with NACET analysis. https://lnkd.in/gpG9-fYK

🗺️ Enhancing Water Safety: Exploring Recent Technological Approaches for Drowning Detection 🧑 Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah and Mohsen Asadnia* 🏫 Macquarie University, UNSW, Edith Cowan University 🔎 Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in #drowningdetection, with a specific focus on #imageprocessing and #sensor-based methods. Furthermore, the potential of #artificialintelligence (AI), #machinelearning algorithms (MLAs), and #robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection systems. However, the image-processing approach requires substantial resources and sophisticated MLAs, making it costly and complex to implement. Conversely, sensor-based approaches offer practical, cost-effective, and widely applicable solutions for drowning detection. These approaches involve data transmission from the swimmer’s condition to the processing unit through sensing technology, utilising both wired and wireless communication channels. This paper explores the recent developments in drowning detection systems while considering costs, complexity, and practicality in selecting and implementing such systems. The assessment of various technological approaches contributes to ongoing efforts aimed at improving water safety and reducing the risks associated with drowning incidents. https://lnkd.in/gFsytUsW

🗺️ Novel Framework for Quality Control in Vibration Monitoring of CNC Machining 🧑 Georgia Apostolou*, Myrsini Ntemi, Spyridon Paraschos, Ilias Gialampoukidis, Angelo Rizzi, Stefanos Vrochidis and Ioannis Kompatsiaris 🏫 Centre for Research and Technology Hellas (CERTH) 🔎 #Vibrations are a common issue in the machining and metal-cutting sector, in which the spindle vibration is primarily responsible for the poor surface quality of workpieces. The consequences range from the need to manually finish the metal surfaces, resulting in time-consuming and costly operations, to high scrap rates, with the corresponding waste of time and resources. The main problem of conventional solutions is that they address the suppression of machine vibrations separately from the quality control process. In this novel proposed framework, we combine advanced vibration-monitoring methods with the AI-driven prediction of the quality indicators to address this problem, increasing the quality, productivity, and efficiency of the process. The evaluation shows that the number of rejected parts, time devoted to reworking and manual finishing, and costs are reduced considerably. The framework adopts a generalized methodology to tackle the #conditionmonitoring and #qualitycontrol processes. This allows for a broader adaptation of the solutions in different CNC machines with unique setups and configurations, a challenge that other data-driven approaches in the literature have found difficult to overcome. https://lnkd.in/gYBQWf6E

🗺️ Detecting Respiratory Viruses Using a Portable NIR Spectrometer—A Preliminary Exploration with a Data Driven Approach 🧑 Jian-Dong Huang*, Hui Wang*, Ultan Power, James A. McLaughlin, Chris Nugent, Enayetur Rahman, Judit Barabas and Paul Maguire 🏫 Ulster University, Queen's University Belfast 🔎 #Respiratory viruses’ detection is vitally important in coping with pandemics such as COVID-19. Conventional methods typically require laboratory-based, high-cost equipment. An emerging alternative method is Near-Infrared (NIR) #spectroscopy, especially a portable one of the type that has the benefits of low cost, portability, rapidity, ease of use, and mass deployability in both clinical and field settings. One obstacle to its effective application lies in its common limitations, which include relatively low specificity and general quality. Characteristically, the spectra curves show an interweaving feature for the virus-present and virus-absent samples. This then provokes the idea of using machine learning methods to overcome the difficulty. While a subsequent obstacle coincides with the fact that a direct deployment of the #machinelearning approaches leads to inadequate accuracy of the modelling results. This paper presents a data-driven study on the detection of two common respiratory viruses, the respiratory syncytial virus (RSV) and the Sendai virus (SEV), using a portable NIR spectrometer supported by a machine learning solution enhanced by an algorithm of variable selection via the Variable Importance in Projection (VIP) scores and its Quantile value, along with variable truncation processing, to overcome the obstacles to a certain extent. We conducted extensive experiments with the aid of the specifically developed algorithm of variable selection, using a total of four datasets, achieving classification accuracy of: (1) 0.88, 0.94, and 0.93 for RSV, SEV, and RSV + SEV, respectively, averaged over multiple runs, for the neural network modelling of taking in turn 3 sessions of data for training and the remaining one session of an ‘unknown’ dataset for testing. (2) the average accuracy of 0.94 (RSV), 0.97 (SEV), and 0.97 (RSV + SEV) for model validation and 0.90 (RSV), 0.93 (SEV), and 0.91 (RSV + SEV) for model testing, using two of the datasets for model training, one for model validation and the other for model testing. These results demonstrate the feasibility of using portable NIR spectroscopy coupled with machine learning to detect respiratory viruses with good accuracy, and the approach could be a viable solution for population screening. https://lnkd.in/g8qdCzDf

🗺️ Intelligent Millimeter-Wave System for Human Activity Monitoring for Telemedicine 🧑 Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson and Vamsy P. Chodavarapu* 🏫 University of Dayton, Jubail Industrial College, University of Dayton 🔎 Telemedicine has the potential to improve access and delivery of #healthcare to diverse and aging populations. Recent advances in technology allow for #remotemonitoring of #physiological measures such as heart rate, oxygen saturation, blood glucose, and blood pressure. However, the ability to accurately detect falls and monitor #physicalactivity remotely without invading privacy or remembering to wear a costly device remains an ongoing concern. Our proposed system utilizes a #millimeter-wave (mmwave) #radar #sensor (IWR6843ISK-ODS) connected to an NVIDIA Jetson Nano board for continuous monitoring of human activity. We developed a PointNet neural network for real-time human activity monitoring that can provide activity data reports, tracking maps, and fall alerts. Using radar helps to safeguard patients’ privacy by abstaining from recording camera images. We evaluated our system for real-time operation and achieved an inference accuracy of 99.5% when recognizing five types of activities: standing, walking, sitting, lying, and falling. Our system would facilitate the ability to detect falls and monitor physical activity in home and institutional settings to improve telemedicine by providing objective data for more timely and targeted interventions. This work demonstrates the potential of artificial intelligence algorithms and mmwave sensors for HAR. https://lnkd.in/g_cU9Fcc

🗺️ Enhanced Coprime Array Structure and DOA Estimation Algorithm for Coherent Sources 🧑 Xiaolei Han* andXiaofei Zhang 🏫 Shanghai Business School, Nanjing University of Aeronautics and Astronautics 🔎 This paper presents a new enhanced coprime array for direction of arrival (#DOA) estimation. Coprime arrays are capable of estimating the DOA using coprime properties and outperforming uniform linear arrays. However, the associated algorithms are not directly applicable for estimating the DOA of coherent sources. To overcome this limitation, we propose an enhanced coprime array in this paper. By increasing the number of array #sensors in the coprime array, it is feasible to enlarge the aperture of the array and these additional array sensors can be utilized to achieve spatial smoothing, thus enabling estimation of the DOA for coherent sources. Additionally, applying the spatial smoothing technique to the signal subspace, instead of the conventional spatial smoothing method, can further improve the ability to reduce noise interference and enhance the overall estimation result. Finally, DOA estimation is accomplished using the MUSIC algorithm. The simulation results demonstrate improved performance compared to traditional algorithms, confirming its feasibility. https://lnkd.in/gGtK56wj

🗺️ Human-Robot Joint Misalignment, Physical Interaction, and Gait Kinematic Assessment in Ankle-Foot Orthoses 🧑 Ricardo Luís Andrade*, Joana Figueiredo*, Pedro Fonseca, João P. Vilas-Boas, Miguel T. Silva and Cristina P. Santos 🏫 Universidade do Minho, ULisboa 🔎 Lower limb exoskeletons and orthoses have been increasingly used to assist the user during #gaitrehabilitation through torque transmission and motor stability. However, the physical human-robot interface (HRi) has not been properly addressed. Current orthoses lead to spurious forces at the HRi that cause adverse effects and high abandonment rates. This study aims to assess and compare, in a holistic approach, human-robot joint misalignment and gait #kinematics in three fixation designs of ankle-foot orthoses (AFOs). These are AFOs with a frontal shin guard (F-AFO), lateral shin guard (L-AFO), and the ankle modulus of the H2 exoskeleton (H2-AFO). An experimental protocol was implemented to assess misalignment, fixation displacement, pressure interactions, user-perceived comfort, and gait kinematics during walking with the three AFOs. The F-AFO showed reduced vertical misalignment (peak of 1.37 ± 0.90 cm, p-value < 0.05), interactions (median pressures of 0.39–3.12 kPa), and higher user-perceived comfort (p-value < 0.05) when compared to H2-AFO (peak misalignment of 2.95 ± 0.64 and pressures ranging from 3.19 to 19.78 kPa). F-AFO also improves the L-AFO in pressure (median pressures ranging from 8.64 to 10.83 kPa) and comfort (p-value < 0.05). All AFOs significantly modified hip joint angle regarding control gait (p-value < 0.01), while the H2-AFO also affected knee joint angle (p-value < 0.01) and gait spatiotemporal parameters (p-value < 0.05). Overall, findings indicate that an AFO with a frontal shin guard and a sports shoe is effective at reducing misalignment and pressure at the HRI, increasing comfort with slight changes in gait kinematics. https://lnkd.in/g6Bwpeeb

📢 📢 📢  A Novel Shunt Zigzag Double-Tap Low-Harmonic Multi-Pulse Rectifier Based on a Three-Stage Power Electronic Phase-Shifting Transformer 🧑🔬:Xiuqing Mu,Xiaoqiang Chen,Qianxiao Liu,Ying Wang,Tun Bai*,Leijiao Ge and Xiping Ma 🏫:兰州交通大学,Tianjin University,State Grid Gansu Electric Power Company Electric Power Science Research Institute 👓:To solve the problem of the large size of traditional industrial frequency phase-shift transformers and the harmonic distortion of multi-pulse wave rectifier systems, this paper proposes a three-stage shunt zigzag power electronic phase-shift transformer based on a double-tap multi-pulse wave rectifier, which combines the power factor correction (PFC) converter with the voltage-type SPWM inverter circuit to form a power electronic converter to realize the frequency boost and power factor correction. Through AC–DC–AC conversion, the frequency of the three-phase AC input voltage is increased, the number of core and coil turns in the transformer is reduced to reduce the size of the phase-shifter transformer, a zigzag structure of the phase-shifter transformer is used to solve the unbalanced distribution of current between the diode bridges, and a passive harmonic suppression method on the DC side is used to generate a loop current by using a group of single-phase rectifier bridges to regulate the input line current of the phase-shifter transformer. The phase-shifted voltage is input into two three-phase diode rectifier bridges to rectify and supply power to the load. Simulation and semi-physical test results show that the proposed method reduces the total harmonic distortion (THD) value of the input current of the phase-shifted transformer to 7.17%, and the THD value of the grid-side input current is further reduced to 2.49%, which meets the harmonic standard and realizes the purpose of power factor correction as well as being more suitable for high-power applications. 👉:https://lnkd.in/gV6JXsZb

📢 📢 📢  An Improved ELOS Guidance Law for Path Following of Underactuated Unmanned Surface Vehicles 🧑🔬: Shipeng Wu,Hui Ye,Wei Liu*,Xiaofei Yang,Ziqing Liu and Hao Zhang 🏫:江苏科技大学 👓:In this paper, targeting the problem that it is difficult to deal with the time-varying sideslip angle of an underactuated unmanned surface vehicle (USV), a line–of–sight (LOS) guidance law based on an improved extended state observer (ESO) is proposed. A reduced-order ESO is introduced into the identification of the sideslip angle caused by the environmental disturbance, which ensures a fast and accurate estimation of the sideslip angle. This enables the USV to follow the reference path with high precision, despite external disturbances from wind, waves, and currents. These unknown disturbances are modeled as drift, which the modified ESO-based LOS guidance law compensates for using the ESO. In the guidance subsystem incorporating the reduced-order state observer, the observer estimation and track errors are proved uniformly ultimately bounded. Simulation and experimental results are presented to validate the effectiveness of the proposed method. The simulation and comparison results demonstrate that the proposed ELOS guidance can help a USV track different types of paths quickly and smoothly. Additionally, the experimental results confirm the feasibility of the method. 👉:https://lnkd.in/gVrCxnA9