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High-efficiency stepdown/step-up converter for series-connected energy storage system
This work introduces a novel stepdown/step-up converter designed to optimize the run time of series-connected Battery, whose voltage drops progressively with increased usage, eventually falling below the necessary operating levels. The proposed converter automatically transitions between stepdown, step-up, and stepdown/step-up modes based on a comparison of input and output voltages, with the stepdown/step-up mode restricted to the narrowest range to minimize its lower efficiency in power conversion. It supports an input voltage range from 2.5 to 8V and incorporates a capacitive coupling level shift circuit to maintain the gate-source voltage of the power transistor under 5V, protecting against gate oxide layer damage. Fabricated with 180nm BCD technology, the converters compact size is 1.44mm by 0.73mm. Testing reveals that this converter achieves up to 93% power conversion efficiency, an 11% improvement over conventional models, and supports an output current up to 500mA, a 67% increase, enhancing the performance and longevity of Battery in compact electronic devices. The Author(s) 2025. -
High-Gain Sequentially Rotated LHCP Metasurface Antenna Array for Uplink Ka-Band CubeSat Applications
This paper presents a compact circularly polarized 2 2 microstrip antenna array with a metasurface superstrate designed for Ka-band uplink CubeSat communication applications. The proposed antenna array operates at 28 GHz and consists of four-square patch elements arranged in a sequential rotation, connected through a sequential-phase feed network to achieve stable circular polarization. To enhance gain and axial ratio performance, a 6 6 rotated plus-shaped metasurface layer composed of periodic unit cells is placed above the antenna array.The antenna structure, with overall dimensions of 22 20 6.04 mm3, is designed and simulated using ANSYS HFSS. Simulation results demonstrate an impedance bandwidth of 8.12% (26.74-29.00 GHz) for |S11| < -10 dB and a 3-dB axial ratio bandwidth of 1.52% (27.42-27.84 GHz). The antenna array achieves broadside LHCP achieves a maximum gain of 14.8 dBi at 27.5 GHz with a half-power beamwidth of 9 along the Phi = 90 plane. The inclusion of the metasurface layer results in a gain improvement of approximately 5.2 dBi and with a peak gain of 15.5 dBi and a total efficiency greater than 95%. 2025 IEEE. -
High-Movement Human Segmentation in Video Using Adaptive N-Frames Ensemble
A wide range of camera apps and online video conferencing services support the feature of changing the background in real-time for aesthetic, privacy, and security reasons. Numerous studies show that the Deep-Learning (DL) is a suitable option for human segmentation, and the ensemble of multiple DL-based segmentation models can improve the segmentation result. However, these approaches are not as effective when directly applied to the image segmentation in a video. This paper proposes an Adaptive N-Frames Ensemble (AFE) approach for high-movement human segmentation in a video using an ensemble of multiple DL models. In contrast to an ensemble, which executes multiple DL models simultaneously for every single video frame, the proposed AFE approach executes only a single DL model upon a current video frame. It combines the segmentation outputs of previous frames for the final segmentation output when the frame difference is less than a particular threshold. Our method employs the idea of the N-Frames Ensemble (NFE) method, which uses the ensemble of the image segmentation of a current video frame and previous video frames. However, NFE is not suitable for the segmentation of fast-moving objects in a video nor a video with low frame rates. The proposed AFE approach addresses the limitations of the NFE method. Our experiment uses three human segmentation models, namely Fully Convolutional Network (FCN), DeepLabv3, and Mediapipe. We evaluated our approach using 1711 videos of the TikTok50f dataset with a single-person view. The TikTok50f dataset is a reconstructed version of the publicly available TikTok dataset by cropping, resizing and dividing it into videos having 50 frames each. This paper compares the proposed AFE with single models and the Two-Models Ensemble, as well as the NFE models. The experiment results show that the proposed AFE is suitable for low-movement as well as high-movement human segmentation in a video. 2022 Tech Science Press. All rights reserved. -
High-Performance ?-cyclodextrin-Ti3C2Tx MXene-Based Electrochemical Sensor for the Detection of Neurological Disorder Biomarker
In this work, the ?-cyclodextrin-MXene (?-CD-MXene) composite was employed as a modifier for carbon fiber paper (CFP) electrodes and quantification of L-methionine (L-Met). The ?-CD-MXene composite was prepared by hydrothermal synthesis route by adding ?-CD and Ti3C2Tx MXenes obtained via the Minimally intensive layer delamination technique. Cyclic voltammetry (CV) and Differential Pulse Voltammetry (DPV) were conducted to study the influence of scan rate and pH on the electrooxidation of L-Met studies using the ?-CD-MXene/CFP electrode. The layered structure of the exfoliated Ti3C2Tx MXenes with charge transfer efficiency in combination with the host-guest interaction ability of ?-CD enhances the electrooxidation of L-Met. The ?-CD-MXene/CFP electrode showcased high sensitivity, reproducibility, and stability, and the anodic peak currents were in linearity with L-Met concentration within the range of 0.09-540 ?M and LOD of 0.03 ?M under various optimized conditions. In addition, the developed sensor showcases highly selective and non-interfering sensing of L-Met. 2024 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. -
High-Performance 15-Level Multilevel Inverter for Renewable and Smart Grid Applications
Multilevel inverters have emerged as a promising solution for improving power quality, reducing switching stress, and enhancing conversion efficiency in renewable energy and smart grid applications. Conventional two-level topologies struggle with high Total Harmonic Distortion (THD), electromagnetic interference, and bulky filters, limiting their suitability for high-power systems. To address these challenges, advanced multilevel architectures have been designed to deliver multiple voltage steps, thereby approximating a sinusoidal waveform with greater precision. This paper investigates a high-performance multilevel inverter with an optimized 15-level configuration that achieves superior harmonic reduction, enhanced voltage boosting, and reduced switching device count compared to conventional alternatives. A detailed switching sequence and operational modes are provided to demonstrate the generation of fifteen distinct output voltage levels. Simulation and analytical results validate the performance in terms of THD minimization, voltage stress reduction, and waveform quality. The proposed configuration is suitable for integration with photovoltaic systems, wind generation, and smart grid applications where reliability, efficiency, and grid compliance are essential. Furthermore, the design demonstrates modularity, scalability, and compatibility with wide bandgap semiconductors, reinforcing its role as a practical solution for modern energy systems. 2025 IEEE. -
High-performance 2D photonic crystal sensor for simultaneous detection of chemical and biological analytes
This work proposes a two-dimensional (2D) photonic crystal based sensor for multi-analyte detection across biochemical and biological domains. The proposed sensor can detect sulfuric acid, hydrogen peroxide, salt concentrations in seawater, alcohol detection, cancer cell detection, and aberrant bone tissue without any external modification to the sensor configuration. The intriguing aspect of the proposed sensor is that its structural parameters are optimised to detect refractive index values in the range of 12, and the resonant wavelength is therefore shifted to a longer wavelength. Based on the shift, the performance parameters of the analyte are observed. The proposed sensor offers excellent performance metrics, including a high transmission efficiency of 100%, a high-quality factor of 1,600, a sensitivity of 315nm/RIU, and a maximum detection limit of 0.09. The footprint of the proposed design is 16?m. This makes the sensor suitable for photonic integrated circuits and lab-on-chip applications. It offers a promising platform for next-generation optical sensing technologies. The Author(s), under exclusive licence to The Optical Society of India 2025. -
High-Performance Ammonia Sensing with Citrus Hystrix-Mediated ZnO Nanoparticles in TFT-Based Devices
We present a sustainable green synthesis approach for zinc oxide nanoparticles (ZnO NPs) utilizing Citrus hystrix leaf extract and their application as an active medium in a thin film transistor (TFT)-based ammonia gas sensor. For the first time, ZnO NPs derived from Citrus hystrix serve as a receptor layer in a thin film transistor (TFT) device, enabling selective ammonia detection at a significantly reduced initiation temperature. The synthesized ZnO NPs, with a wurtzite structure and an average crystallite size of approximately 14 nm, are deposited onto the TFT sensor without the need for an external conducting layer. The sensor demonstrates excellent sensitivity and selectivity, achieving a maximum response of ~85 % at 20 ppm, with a rapid response time of about 10 seconds at room temperature. Notably, the TFT device exhibits an electron mobility of ~10.2 cm2/V ? s and a high on/off ratio (>10?) at room temperature. The sensing mechanism is attributed to the oxidation-reduction interactions between surface-adsorbed oxygen and NH? molecules on the ZnO NPs, which modulate the device's electrical conductivity. This work underscores the importance of eco-friendly fabrication of high-performance, durable devices, addressing contemporary environmental and economic concerns. 2025 Wiley-VCH GmbH. -
High-performance reconfigurable FET for a simple variable gain buffer amplifier design
Design and simulation of variable gain analog buffer amplifier using single gate reconfigurable field-effect transistor (SG-RFET) with strained silicon channel are proposed. The design simplicity makes SG-RFET device a potential candidate compared to the multi-gate RFET devices. The gain of the proposed configuration is varied by tuning the feedback voltage. The voltage gain of the proposed configuration can be tuned from 0.97V/V to 5V/V with an output load of 1 k?. The operational transconductance amplifier (OTA) using the SG-RFET device is used in the proposed buffer amplifier design. 2021 Informa UK Limited, trading as Taylor & Francis Group. -
High-performance Zn(ii)-based coordination polymer as an electrode material for pseudocapacitive energy storage and hydrogen evolution
Recently, multifunctional materials for energy storage and production have been investigated to address diverse energy challenges. However, innovative methodologies focusing on the design and synthesis of novel materials remain essential to effectively tackle persistent challenges such as material degradation, high overpotentials, low conductivity, inferior cycling performance, elevated resistance, and high production costs. Working along these lines, we report a simplistic gram-scale synthesis, characterization, and excellent electrochemical behavior of a Zn(ii)-based coordination polymer (COP) abbreviated as Zn(DAB). It has been obtained in quantitative yields through a facile one-pot reaction between N4-ligand, 3,3?-diaminobenzidine (DAB), and Zn(ii) ions, derived from Zn(OAc)22H2O, at room temperature. The proposed structure of the COP was established through a series of standard spectroscopic and electron microscopic analyses. These methods unveiled the self-assembly of indefinitely long coordination strands, resulting in a two-dimensional (2D) layered structure. Zn(DAB), when probed for its electrochemical characteristics, reveals exemplary results. The material showed a high specific capacitance of 2091.4 F g?1, calculated at 1 A g?1 with 92% retention over 5000 charge-discharge cycles. Additionally, the COP also exhibited a subservient overpotential of 263 mV at a current density of 10 mA cm?2 for the hydrogen evolution reaction. These results highlight the promising potential of Zn(DAB) as a multifunctional electrode material for sustainable energy applications. 2025 The Royal Society of Chemistry. -
High-precision lung disease detection and classification from chest radiographs using deep and ensemble neural networks
Chest X-rays are a quick and effective way to diagnose lung diseases. This research developed deep learning models to automatically detect chest X-rays of COVID-19, normal, and viral pneumonia patients. The goal was to evaluate deep learning for automated detection of lung diseases from chest X-rays. The research implemented transfer learning with ResNet101 and EfficientNetB0 architectures using a public chest x-ray database with over 21,000 images across COVID-19, normal, and other pneumonia infection classes. Pretrained ImageNet weights were used to initialize the models before fine-tuning them to classify features in chest X-rays. Data augmentation techniques like rotation, shifting, and flipping were applied to expand the number and diversity of training images. The models achieved exceptional performance with accuracy scores of 93.7% for ResNet101 and 95.3% for EfficientNetB0 on test data. Additionally, an Ensemble model, the combination of the two models, was implemented, achieving an accuracy of 96.4%. The findings demonstrate the capability of Ensemble deep convolutional neural networks for accurate automated classification of chest X-rays for Lung disease. Through data augmentation and transfer learning, high-precision models were developed without needing exceedingly sizeable medical image datasets. These deep learning classifiers could serve as rapid diagnostic decision support systems to identify potential lung disease patients using readily available chest X-rays. Such tools could assist healthcare providers, especially when access to expensive diagnostic tests is limited. 2026 Author(s). -
High-resolution spectral analysis of three high-latitude carbon stars
We present the results of a detailed high-resolution spectroscopic analysis (SUBARU/HDS spectra, R 50 000) of three faint high-latitude carbon stars HE 1104 0957, HE 1205 0521, and HE 1244 3036. Our estimated metallicity for these objects is 2.96, 2.63, and 2.49, respectively. The surface chemical compositions of the objects are found to be characterised by enhanced carbon and heavy elements, such as Y, Ba, La, and Ce. Using the classification criteria for carbon-enhanced metal-poor (CEMP) stars the objects HE 1104 0957 and HE 1205 0521 could not be classified into any known CEMP sub-classes, whereas the object HE 1244 3036 is found to be likely a CEMP-s star. The observed abundance patterns in HE 1244 3036 are also found to match well with the yields of a 2 M AGB star with [Fe/H] = 2.50. Although our kinematic analysis indicates that the objects belong to the halo population, the elemental abundance ratios of HE 1104 0957 and HE 1205 0521 do not match well with those of typical halo objects. Estimated elemental abundances are presented, and kinematic properties of the stars are discussed. The Author(s), 2025. -
High-resolution spectroscopy of HE 0225?0546 and HE 1153?0518: probing the progenitors through abundance patterns and kinematics
We present the results of a high-resolution (SUBARU/HDS, R ? 50 000) spectroscopic study of two metal-poor stars, HE 0225 ?0546 and HE 1153 ?0518. This marks the first such detailed analysis for both objects. Our findings reveal that HE 0225 ?0546 is extremely metal-poor with [Fe/H] ??3.03, while HE 1153 ?0518 is very metal-poor with [Fe/H] ??2.80. Both stars exhibit enhancements in carbon and neutron-capture elements and formally satisfy the criteria for carbon-enhanced metal- poor (CEMP) classification. Although their [Ba/Eu] and [La/Eu] ratios do not allow a secure assignment to any specific CEMP sub-class, the estimated [Ba/Eu] and [Eu/Fe] ratios indicate that both stars fall into the r-II star category. Distinct abundance patterns between the two stars suggest different nucleosynthetic histories. HE 0225 ?0546 shows strong enhancement in Fe-peak elements, while HE 1153 ?0518 is mildly deficient in the same. Both stars are ?-enhanced, though the level of enhancement varies. These results indicate pollution by multiple progenitor channels. Abundance ratios imply that HE 0225 ?0546 is likely enriched by fast-rotating massive stars (FRMS), whereas HE 1153 ?0518 shows signatures consistent with asymptotic giant branch (AGB) star enrichment. Kinematic analyses place both stars in the high-energy, prograde component of the Galactic halo. HE 0225 ?0546 has an apogalactic distance (rapo ) of ?31.8 kpc, placing it in the outer halo, while HE 1153 ?0518 lies closer to the boundary of the inner and outer halo with rapo ?13.8 kpc. Both stars show kinematic coherence with the Sagittarius substructure, suggesting a possible extragalactic origin. The Author(s) 2025. Published by Oxford University Press on behalf of Royal Astronomical Society. -
High-Speed Parity Number Detection Algorithm inRNS Based onAkushsky Core Function
The Residue Number System is widely used in cryptography, digital signal processing, image processing systems and other areas where high-performance computation is required. One of the computationally expensive operations in the Residue Number System is the parity detection of a number. This paper presents a high-speed algorithm for parity detection of numbers in Residue Number System based on Akushsky core function. The proposed approach for parity detection reduces the average time by 20.39% compared to the algorithm based on the Chinese Remainder Theorem. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
High-speed portrait video segmentation using the hybrid combination of deep-learning models and boundary movement adjustment
As global warming intensifies, the development of energy-efficient Artificial Intelligence (AI) technologies has become crucial. Additionally, the growing demand for on-device AI in smartphones, extended reality devices, and autonomous vehicles necessitates AI systems that can function effectively on low-performance hardware. To address these needs, this study proposes hybrid methods in the field of Portrait Video Segmentation (PVS). Our proposed hybrid models leverage Deep-learning based Segmentation Models (DSMs) and a novel Boundary Movement Adjustment (BMA) process to achieve speed and accuracy balance. The Hybrid Serial Model (HSM) not only accelerates PVS but also improves energy efficiency while maintaining a similar level of accuracy. On the other hand, the Hybrid Parallel Model (HPM) enables high-performance PVS even on low-performance devices, ensuring no video frames are lost during high-speed segmentation processing. Tests conducted on Jetson Nano, Raspberry Pi, and a desktop PC demonstrate the effectiveness of these models, showing improvements in PVS speed while maintaining accuracy close to that of traditional DSMs. HSM increased PVS speed from 15.2 Frames Per Second (FPS) to 25.1 FPS on a desktop PC with a 0.5 % accuracy loss, and from 6.3 FPS to 16.5 FPS on a Jetson Nano with a 1 % loss. HPM reached 30 FPS on a desktop PC with a 0.05 % loss, and 29.7 FPS on a Jetson Nano with a 1 % loss. On the Raspberry Pi, the HPM method improved speed from 2.9 FPS to 29.8 FPS, demonstrating its adaptability for low-performance devices. 2025 Elsevier Ltd -
Higher Education in Maldives amidst the Pandemic: An Intersectional Approach to Digital Education
The Covid-19 outbreak upended the core foundations of societies across the globe, leading to dramatic shifts in knowledge, attitudes, and values. The education sector, known for its traditional classroom model, had to adapt quickly. However, the pandemic's impact varied widely due to social, cultural, economic, geographic, and gender factors. Amid such inequal pandemic disruptions, Maldives presents a unique case as an upper-middle-income economy with diverse higher education (HE) opportunities. The pandemic pushed Maldives towards digital education, capitalizing on pre-existing capabilities. The study employs an intersectional feminist approach to the gender digital divide, seeking to understand how the rapid adoption of digital education in Maldives' higher education institutions (HEIs) has unfolded during the pandemic. The analysis reveals deeply entrenched gender norms that have had a disproportionate impact on women students and lecturers in HEIs. Factors like unpaid domestic labour and care work, lack of suitable home space, absence of psychological support, and reinforcement of gender roles have primarily widened the gender digital divide in digital education during the pandemic. Moreover, local, social, and cultural attitudes further exacerbate this divide signifying a pressing need to re-evaluate women's roles in HEIs in the post-pandemic world. 2025 selection and editorial matter, Padma Rani, Bhanu Bhakta. -
Higher Education in Maldives amidst the Pandemic: An Intersectional Approach to Digital Education
The Covid-19 outbreak upended the core foundations of societies across the globe, leading to dramatic shifts in knowledge, attitudes, and values. The education sector, known for its traditional classroom model, had to adapt quickly. However, the pandemic's impact varied widely due to social, cultural, economic, geographic, and gender factors. Amid such inequal pandemic disruptions, Maldives presents a unique case as an upper-middle-income economy with diverse higher education (HE) opportunities. The pandemic pushed Maldives towards digital education, capitalizing on pre-existing capabilities. The study employs an intersectional feminist approach to the gender digital divide, seeking to understand how the rapid adoption of digital education in Maldives' higher education institutions (HEIs) has unfolded during the pandemic. The analysis reveals deeply entrenched gender norms that have had a disproportionate impact on women students and lecturers in HEIs. Factors like unpaid domestic labour and care work, lack of suitable home space, absence of psychological support, and reinforcement of gender roles have primarily widened the gender digital divide in digital education during the pandemic. Moreover, local, social, and cultural attitudes further exacerbate this divide signifying a pressing need to re-evaluate women's roles in HEIs in the post-pandemic world. 2025 selection and editorial matter, Padma Rani, Bhanu Bhakta. -
Higher education institutions as a catalyst for sustainability development
Growing concerns about the planet and society have led to the evolution of the concept of sustainable development. This concept gained popularity when the World Commission on Environment and Development released its report Our Common Future in 1987. In 1975, United Nations Educational, Scientific and Cultural Organization (UNESCO) brought sustainability as the International Environmental Education Program focusing on environmental education. This gave birth to the idea that Higher Educational Institutions (HEIs) can play a significant role in promoting the sustainability agenda. Over the years, this was done by implementing sustainability initiatives on the campus. These initiatives mostly focused on the environment and ignored the social and economic dimensions of sustainability. Given the paucity of adequate knowledge in this field, the chapter aims to explore the challenges in implementing sustainable initiatives and suggest a framework that will guide HEIs to act as a catalyst for sustainability development. 2024, IGI Global. All rights reserved. -
Highly Efficient Photocatalytic Conversion of Amine to Amide and Degradation of Methylene Blue Using BiOClTiO2 Nano Heterostructures
Abstract: Facile green synthesis of BiOClTiO2 was done using combustion technique by Ixora coccinea leaf extract as fuel source. The said material was characterized using XRD, SEM, EDX, HRTEM, SAED, FTIR, and UV-DRS. The particle size was found to be approximately 60nm and a crystallite size of 0.3nm from TEM. The photocatalytic activity of the material was found out using photoluminescence studies, dye degradation and photocatalytic organic conversion. The material showed excellent dye degradation capacity for methylene blue with 80% of the dye degraded under 3hrs. The stabilisation of electronhole pair by the heterostructure gave it the ability to perform easy degradation. The degradation kinetics have also been studied. It also showed an excellent organic conversion property with formylation yield reaching up to 96% and total conversion of the reactant molecule. The material is a potent photocatalyst due to its great efficiency and can have a remarkable role in the synthesis of important organic molecules and detoxification of environment. Graphical Abstract: The heterostructure catalyses the conversion of amine to amides and mineralizes methylene blue under visible light condition. [Figure not available: see fulltext.]. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Highly emissive dibenzofuranfluorophores with aggregation-induced emission for bioimaging in HeLa cell lines
Dibenzo[b,d]furans, structural analogs of furan, represent an emerging class of promising molecules whose solid-state emission properties remain largely unexplored. The aim of the present work is to design and synthesize new dibenzo[b,d]furan-based organic fluorophores for bioimaging applications. The synthesis involved a single-step Schiff base reaction of 4-(dibenzo[b,d]furan-4-yl)aniline with two different ortho-hydroxy aldehydes, furnishing DBF1 and DBF2 in high yields. Both fluorophores DBF1 and DBF2 exhibited high fluorescence in their solid and aggregated states. The photophysical properties in solution, solid, and aggregated states were investigated using absorbance and emission spectroscopy. The aggregation process was confirmed by the particle size analysis using dynamic light scattering (DLS). The cytotoxicity of the molecules was investigated against HeLa cell lines by the standard MTT assay. DBF1 and DBF2 demonstrated exceptional photoluminescence with quantum yields reaching up to 17.89% and 2.26% respectively, highlighting their potential as excellent materials for imaging applications. Both DBF1 and DBF2 exhibited significant toxicity towards HeLa cells with IC50 values of 42.08 ?g ml?1 and 39.74 ?g ml?1, respectively, showcasing notable anti-proliferative activity against HeLa cells. Both fluorophores exhibited excellent emission in HeLa cells with mean relative fluorescence intensities of 1.008 0.77 a.u. and 1.44 0.65 a.u. for DBF1 and DBF2, respectively. Thus, this work presents the lesser explored dibenzo[b,d]furan-based organic fluorophores for bioimaging applications with potential inhibitory activity against HeLa cells. 2025 The Royal Society of Chemistry. -
Highly Luminescent MOF and Its in Situ Fabricated Sustainable Corn Starch Gel Composite as a Fluoro-Switchable Reversible Sensor Triggered by Antibiotics and Oxo-Anions
Frequent use of antibiotics and the growth of industry lead to the pollution of several natural resources which is one of the major consequences for fatality to human health. Exploration of smart sensing materials is highly anticipated for ultrasensitive detection of those hazardous organics. The robust porous hydrogen bonded network encompassing a free-NH2 moiety, Zn(II)-based metal-organic framework (MOF) (1), is used for the selective detection of antibiotics and toxic oxo-anions at the ppb level. The framework is able to detect the electronically dissimilar antibiotic sulfadiazine and nitrofurazone via fluorescence "turn-on"and "turn-off"processes, respectively. The antibiotic-triggered reversible fluoro-switching phenomena (fluorescence "on-off-on") are also observed by using the fluorimetric method. An extensive theoretical investigation was performed to establish the fluoro-switching response of 1, triggered by a class of antibiotics and also the sensing of oxo-anions. This investigation reveals that the interchange of the HOMO-LUMO energy levels of fluorophore and analytes is responsible for such a fluoro-switchable sensing activity. Sensor 1 showed the versatile detection ability which is reflected by the detection of a carcinogenic nitro-group-containing drug "roxarsone". In view of the sustainable environment along with quick-responsive merit of 1, an in situ MOF gel composite (1@CS; CS = corn starch) is prepared using 1 and CS due to its useful potential features such as biocompatibility, toxicologically innocuous, good flexibility, and low commercial price. The MOF composite exhibited visual detection of the above analytes as well as antibiotic-triggered reversible fluoro-switchable colorimetric "on-off-on"response. Therefore, 1@CS represents a promising smart sensing material for monitoring of the antibiotics and oxo-anions, particularly appropriate for the real-field analysis of carcinogenic drug molecule "roxarsone"in food specimens. 2022 American Chemical Society.