Detected Research Articles

Highly Sensitive Optical Fiber Humidity Sensor Employing SiO2 Coated ZnO Nanoparticle Doped PVA

Highly Sensitive Optical Fiber Humidity Sensor Employing SiO₂ Coated ZnO Nanoparticle Doped PVA

Deep learning and time series signal processing for bending detection in mining environment using optical fiber sensor

Optical fiber sensors are widely used to monitor environmental disturbances that may trigger or affect mining landslides, a complex phenomenon that involves various factors and can cause severe damage. In this study, we propose a method to detect the curvature of a bent optical fiber, which affects the optical signals traveling through it, using deep learning and time series signal processing. We use a Mach-Zehnder interferometer (MZI) sensor and a single-mode fiber (SMF) cable to capture the interference signal caused by different bending angles. We apply a transformation random convolutional kernel (TRANCE) to reduce the signal and extract its mean and standard deviation as features. We train a dense neural network (DNN) with three hidden layers to classify the bending events into four categories: low, medium, high, and extreme. We evaluate our method on a dataset of 400 samples and achieve an average accuracy of 99% in the confusion matrix and the fifty times tenfold validation experiments. Our method outperforms other methods that use multimode fiber (MMF), speckle images, and convolutional neural networks (CNNs) in terms of accuracy, speed, and generalization. Our method also has the advantages of using SMF, which enables integrated sensing and communication, and using 1D signals, which are easier to process than 2D images. Our method is suitable for high-speed signals containing information in dangerous environments.

MicroRNA biosensors for detection of chronic kidney disease.

Chronic kidney disease (CKD) is a prevalent health condition characterized by gradual kidney function loss. Early detection is crucial for the effective management and treatment of CKD. A promising biomarker for various diseases, including chronic kidney disease, is microRNAs (miRNAs), which are becoming increasingly important due to their stability and differential expression in various disease-related states, including CKD. Recent developments in microRNA biosensors have made it possible to detect miRNAs associated with CKD in a sensitive and specific manner. This review article discusses the current state of microRNA biosensors for detecting CKD and highlights their potential applications in clinical settings. Various microRNA biosensors, including electrochemical, optical, and nanomaterial-based sensors, are explored for their ability to detect specific miRNAs linked to CKD progression. The advantages and limitations of these biosensors are evaluated, focusing on factors such as sensitivity, specificity, and ease of use. Overall, microRNA biosensors are promising diagnostic tools for early detection of CKD. However, challenges such as standardizing protocols, validating in large cohorts, and translating to clinical practice remain to be addressed. Future research efforts should aim to overcome these limitations to fully realize the potential of microRNA biosensors in improving the diagnosis and management of CKD.

Strong multi-mode upconversion luminescence of YbVO4: Er3+ phosphors for multimode optical thermometry

This study explored the multi-mode upconversion luminescence in YbVO4: Er3+ under a 980nm laser. The optimal doping concentration of Er3+ ions in YbVO4: Er3+ is 0.02. The phosphor exhibits green (527nm, 2H11/2→4I15/2 and 553nm, 4S3/2→4I15/2), red (654nm, 4F9/2→4I15/2) and near-infrared emissions (803nm, 4I9/2→4I15/2). A multi-mode temperature sensor of YbVO4: Er3+ was developed, featuring three temperature sensing modes based on the luminescent intensity ratio (LIR) of 2H11/2/4S3/2 thermally coupled level, as well as the LIR of 2H11/2/4F9/2 and 4S3/2/4I9/2 non-thermally coupled levels. Corresponding maximum relative sensitivities were determined to be 1.21% K−1 at 298K, 0.93% K−1 at 298K, and 0.33% K−1 at 473K, respectively. The phosphor demonstrates notable temperature sensitivity, highlighting its potential in optical temperature sensing. This study introduces an innovative platform for crafting multi-mode self-reference optical temperature sensors, presenting substantial advancements in the field.

Condensation heat transfer and applicability assessment of a printed circuit heat exchanger as a condenser in a cryogenic CO2 capture and storage system

Global warming is accelerating due to the rapid increase in CO2 emissions and cold energy. CO2 capture and storage systems (CCSSs) using discarded cold energy have been suggested to prevent this problem. To utilize cold energy, a printed circuit heat exchanger (PCHE) with high structural integrity was applied as a condenser in the CCSS. However, studies on condensation heat transfer in PCHE are still lacking, and conventional condensation heat transfer correlations developed in circular-channels do not sufficiently predict heat transfer performance in PCHE. Additionally, evaluating the local heat transfer performance is difficult because PCHE is an all-in-one type heat exchanger. Therefore, in this study, a CO2 condensation experiment in PCHE was conducted using an optical fiber sensor as a measurement, which can evaluate the local heat transfer performance, and a new condensation heat transfer correlation for CO2 in PCHE was developed. The correlation was approximately 20 % smaller than the conventional correlations developed in circular-channels, indicating that CO2 would not be fully condensed if the condenser was designed by conventional correlations. Based on the developed correlation, in-house code was developed and the CCSS using cold energy was compared with the conventional CCSS, which condenses CO2 after pressurizing it to a high pressure. As a result, cold energy based CCSS could replace the conventional CCSS because the CCSS using cold energy was approximately 5.7 million-USD per year more economical than the conventional CCSS when condensing CO2 at 200 tons/h. These results contribute to the design of PCHE-type condensers used in the CCSS.

Development of Fiber Bragg Grating-Based Temperature Insensitive Novel All Optical Tilt Sensor

Development of Fiber Bragg Grating-Based Temperature Insensitive Novel All Optical Tilt Sensor

Simulation of Optical Tactile Sensors Supporting Slip and Rotation Using Path Tracing and IMPM

Simulation of Optical Tactile Sensors Supporting Slip and Rotation Using Path Tracing and IMPM

Synthesis and application of Schiff base as a dual-mode chemosensor for optical determination of aluminium ion content in water samples

Aluminium is highly abundant in the earth's crust and has played a pivotal role in various industries for centuries. Its versatility and abundance have led to its widespread use in everything from food packaging to construction materials. However, this extensive use has also raised concerns about its potential impact on human health and the environment. This study aimed to synthesize and apply a Schiff base molecule, N-(2-hydroxy-1-naphthylmethylidene)-o-aminoacetophenone (N-HyNA), as an optical sensor for aluminium ion (Al3+) determination. The synthesis of N-HyNA was achieved with a high yield of 85% through the reaction of 2-Hydroxy-1-naphthaldehyde and 2-aminoacetonephenone. N-HyNA showed a maximum absorption wavelength at 465.0 nm, and fluorescence emission at 357.0 nm with the excitation wavelength of 278.0 nm. Both absorption and fluorescence signals of N-HyNA were selectively quenched in the presence of aluminium ion. Under optimal conditions for Al3+ detection, the absorption mode of N-HyNA with DMSO as a solvent had the limit of detection (LOD) of 0.005 ppm and detection range of 0.01 – 2.0 ppm, while the fluorescence mode with EtOH as a solvent had the LOD of 0.013 ppm and detection range of 0.05 – 0.40 ppm. The developed approach demonstrated good agreement in Al3+ determination with the conventional atomic absorption spectroscopic technique when using natural water samples and their standard-spiked samples with recovery ranging from 84.0 – 114.0 %. Additionally, analytical characterization was conducted to investigate the quenching mechanism between Al3+ and N-HyNA, and a computational study was performed to elucidate the binding position of Al3+ in the N-HyNA complex. This developed chemosensor offered a simple and fast, yet accurate and selective detection of Al3+ in water samples.

Hybrid Optical Sensor for Combined Thermal and Dimensional Monitoring in Laser Processing

Hybrid Optical Sensor for Combined Thermal and Dimensional Monitoring in Laser Processing

High-Performance Germanium-Tin Fabry-Perot Microcavity Strip-Loaded Mid-Infrared Waveguide-Based Optical Sensors

High-Performance Germanium-Tin Fabry-Perot Microcavity Strip-Loaded Mid-Infrared Waveguide-Based Optical Sensors

Quasi-Distributed Low-Coherent Optical Sensors for In-Field Monitoring the Harmonic Settlement of Oil Tank

Quasi-Distributed Low-Coherent Optical Sensors for In-Field Monitoring the Harmonic Settlement of Oil Tank

Effect of physiological and environmental factors on mosquito wingbeat frequency.

Wingbeat frequency may serve as a distinctive physical signature for identifying mosquito species. However, variation in wingbeat frequency within species may compromise reliability of wingbeat frequency-based mosquito identification. We examined the impact of mosquito density (number of females), time of day (day or night), gravid status, and age (days post-emergence) on the wingbeat frequency of three important vector mosquito species using infrared optical sensors. Wingbeat frequency of Culex quinquefasciatus was significantly higher (6.2% and 9.5%) for single females compared to groups of five and ten females, respectively, and 9.4% higher during the daytime compared to nighttime. Wingbeat frequency was also significantly higher for gravid Cx. quinquefasciatus (9.4%) and Aedes aegypti (1.4%) than nongravid conspecifics. Within a short age range (five to seven days post-emergence), wingbeat in Cx. quinquefasciatus did not vary significantly. Our results highlight that both extrinsic (density and time of day) and intrinsic (gravid status) factors contribute to wingbeat variation, potentially posing challenges for development of wingbeat profile libraries and the classification of unknown specimens. Traps that aim to use wingbeat frequency and target specific cohorts of the population (i.e., host-seeking or gravid females) will need to account for differences in wingbeat frequency due to multiple factors.

Noise Suppression Method of Fiber Optic Sensors Driven by Broadband Light Source

Noise Suppression Method of Fiber Optic Sensors Driven by Broadband Light Source

Design and simulation of a highly sensitive photonic crystal fiber sensor for malaria detection

This research focuses on developing an innovative optical sensor utilizing photonic crystal fiber with a unique cladding structure. The photonic crystal fiber’s cladding consists of four layers of circular air holes, with two of them filled with hemoglobin. This arrangement renders the photonic crystal fiber sensitive to changes in hemoglobin concentration, primarily investigating its impact on chromatic dispersion – the wavelength-dependent refractive index variation. The study analyzes two specific wavelengths, 1.2 µm and 1.4 µm, finding high sensitivity at 1.2 µm, calculated to be 0.232 ps/(nm·km)/(g/L). The potential application lies in malaria diagnosis through non-invasive blood sample analysis. We selected the refractive index of an infected red blood cell at the ring stage, setting it at n = 1.395. Our proposed sensor demonstrates outstanding performance in diagnosing malaria at an HGB concentration of 38 g/L at 1.2 µm and at an HGB concentration of 40 g/L at 1.4 µm. By monitoring hemoglobin concentration changes, this photonic crystal fiber-based sensor offers a promising method for early and accurate malaria detection, thus potentially improving global healthcare.

The foundation of excitation-contraction coupling in skeletal muscle: communication between the transverse tubules and sarcoplasmic reticulum.

The expression excitation-contraction (EC) coupling in skeletal muscle was coined in 1952 (Sandow A. Yale J Biol Med 25: 176-201, 1952). The term evolved narrowly to include only the processes at the triad that intervene between depolarization of the transverse tubular (T-tubular) membrane and Ca2+ release from the sarcoplasmic reticulum (SR). From 1970 to 1988, the foundation of EC coupling was elucidated. The channel through which Ca2+ was released during activation was located in the SR by its specific binding to the plant insecticide ryanodine. This channel was called the ryanodine receptor (RyR). The RyR contained four subunits that together constituted the "SR foot" structure that traversed the gap between the SR and the T-tubular membrane. Ca2+ channels, also called dihydropyridine receptors (DHPRs), were located in the T-tubular membrane at the triadic junction and shown to be essential for EC coupling. There was a precise relationship between the two channels. Four DHPRs, organized as tetrads, were superimposed on alternate RyRs. This structure was consistent with the proposal that EC coupling was mediated via a movement of intramembrane charge in the T-tubular system. The speculation was that the DHPR acted as a voltage sensor transferring information to the RyRs of the SR by protein-protein interaction causing the release of Ca2+ from the SR. A great deal of progress was made by 1988 toward understanding EC coupling. However, the ultimate question of how voltage sensing is coupled to the opening of the SR Ca2+ release channel remains unresolved.NEW & NOTEWORTHY The least understood part of the series of events in excitation-contraction coupling in skeletal muscle was how information was transmitted from the transverse tubules to the sarcoplasmic (SR) and how Ca2+ was released from the SR. Through an explosion of technical approaches including physiological, biochemical, structural, pharmacological, and molecular genetics, much was discovered between 1970 and 1988. By the end of 1988, the foundation of EC coupling in skeletal muscle was established.

Facile formation of nanoporous reduced graphene oxide via epoxy-based negative photoresist laser irradiation for highly sensitive and selective gas detection

This study aims to advance gas sensor technology, particularly focusing on chemiresistive gas sensors known for their simplicity and cost-effectiveness. SU-8, an epoxy-based negative photoresist characterized by the presence of eight epoxy groups, is employed as a precursor to laser-induced graphene. Under CO2 laser irradiation, SU-8 rapidly dissociates, forming a porous graphite-like surface and transforming into reduced graphene oxide (rGO). This rGO exhibits exceptional sensitivity, detecting 20 ppb of NO2 at room temperature (25℃), representing a significant achievement for singular materials. Furthermore, the study demonstrates the scalability of rGO not only as a sensing material but also as a framework through a straightforward deposition process. The deposition of SnO2 on rGO shows remarkable selectivity and sensitivity toward NO2 gas, achieving an ultra-low limit of detection of 26.2 ppt. Subsequent Pd deposition enhances the gas sensor's selectivity for hydrogen gas, highlighting its scalability as a framework for diverse gas sensors beyond NO2. In summary, this study showcases the capability of carbonized SU-8 to detect low-concentration NO2 using a singular material. It underscores the material's potential as a versatile framework for gas sensors, demonstrating its adaptability across various gas sensing applications.

Dragonfly wings-inspired, anti-freezing, ultra-stretchable, and transparent nano-structure sodium alginate-based hydrogel for non-delayed wearable sensing at low-temperatures.

Conductive hydrogels are regarded as an optimal flexible electronic material. Nevertheless, simultaneously achieving excellent mechanical and conductive properties in hydrogels necessitates attention. The high mechanical properties of hydrogels were achieved by employing a strategy that involves constructing a nano-structure network inspired by the highly ordered structure of dragonfly wings. The conductivity and anti-freezing of the hydrogel were enhanced through the construction of a conductive mechanism, achieved by combining ions with nano-particles. The hydrogel exhibits outstanding properties, including anti-freezing, ultra-stretchable (6000%), impressive conductivity (16.2Sm-1), a transparency level of up to 91.2%, and excellent sensitivity in strain sensors. Regulation of the hydrogel matrix's topology and the formation of bionic nano-structures synergistically establish the hydrogel's ultra-stretching and energy dissipation mechanism. The high conductivity of the hydrogel is achieved by constructing a synergistic conduction pathway, which incorporates nano-particles and ions. Under the stretching-induced effect of hydrogel, it facilitates a more efficient path for conduction, thereby enhancing its conductivity and sensing sensitivity under significant strains. Subsequently, this hydrogel was successfully applied to wearable sensor technology, demonstrating surprisingly remarkably prompt non-delayed sensing performance even at low-temperatures. It presents abundant opportunities for expanding the application of hydrogels in flexible electronics.

Evaluation of the Drought Situation Using Remote Sensing Technology, an Applied Study on a Part of North Wasit Governorate in Iraq

Drought presents a substantial threat to both ecological and agricultural systems. Agriculture in Iraq is predicated on precipitation, which is a major contributor to the likelihood of drought resulting from even marginal fluctuations in precipitation. Furthermore, research suggests that Iraq suffers an approximate annual loss of 100,000 acres of arable land due to drought. NDVI and VCI, two significant indices, were utilized in this research to assess and monitor the severity of the drought in the northern region of Wasit province in Iraq. For the period from 1993 to 2023, drought intensity maps were generated utilizing NDVI-based VCI and the Geographic Information System (GIS), an extremely effective spatial data management instrument. NDVI results evidenced that the vegetation cover area was the highest in 1993 and 1998 and declined until it reached the lowest levels in 2023. The vegetation area was concentrated in the southwest parts. In contrast, VCI results demonstrated the extreme drought through the years from 2003 to 2023, which can be attributed to higher temperatures, evaporation, and lower amounts of rainfall. Throughout the thirty-year analysis period, extreme drought conditions were prevalent, especially in the last two decades. Furthermore, this drought should prompt the government to implement preventative measures to avert it. Implementing soil and water conservation measures, such as the establishment of percolation basins, contour bunds, and check dams, can also enhance drought management.

Implementation of Control Valves System on Microturbine Drone’s Rotational Motion

The drone technology has received a wide range of research focusing on improving flight dynamics, battery life, payload capacity and sensor technology. However, for the applications of using drone for high rise buildings are limited by battery life for longer flight with longer duration tasks. This work presents the implementation of a control valve systems for the rotational motion of a microturbine drone. The first objective of this project was to design and develop a control valve system for a microturbine with propeller. The second objective was to measure micro turbine’s performance output which consisted of revolution per minute (rpm) and voltage (V) produced with the control valves system. The final objective was to verify the effectiveness of the control valve system by measuring the differences of the turbine speed of each turbine on the quadcopter to conceptually control the rotational motion of the drones. In conclusion, this work demonstrated the concept of the developed control valve system that can control the rotational motion of the drone.

A Review of CNN-Based Object Recognition and Tracking Systems for Visually Impaired People

Visually impaired persons (VIPs) face significant challenges in navigating their environments, impacting their independence and quality of life. This paper reviews recent advancements in assistive technologies aimed at enhancing mobility and safety for VIPs. It explores various systems, including wearable devices, object detection technologies, and navigation aids, highlighting their functionalities, limitations, and potential future develop- ment. The integration of machine learning and sensor technologies has led to innovative solutions that provide realtime feedback and improved spatial awareness for users. VIPsneed assistance in performing daily tasks such as object detection, obstacle recognition,and navigation, particularly in indoor and outdoor environments. The paper emphasizes the importance of protecting and ensuring the safety of VIPs. Devices typically use sensors like infrared, ultrasonic, and imagery to gather environmental data, which is then processed by machine learning techniques. Users receive feedback via auditory or vibratory means. The paper provides a comprehensive comparative analysis of assistive devices, discussing their key attributes, challenges, and limitations, along with a score-based evaluation to help select appropriate devices for specific needs