Sensitive Applications Research Articles

Towards understanding Trans-cleavage of natural and synthetic nucleic acids by Cas12a for sensitive CRISPR biosensing

CRISPR/Cas systems have been widely utilized for the development of biosensing platforms for precision molecular diagnostics. Their remarkable biosensing performance critically depends on the efficiency of sequence-independent trans-cleavage in type V and VI Cas effectors. Cas12a, a typical example of type V Cas effector exhibits varying trans-cleavage efficiency on different types of nucleic acids, and also in response to different nucleobase sequences. However, the underlying mechanism of Cas12a’s trans-cleavage characteristic remains unclear. To explore this mechanism, we introduced Xeno nucleic acids (XNA) as potential trans-cleavage substrates of Cas12a. XNAs are chemically modified nucleic acid analogues, which originate from chemical modifications of nucleobases, sugar moieties, and the backbone. We observed a progressive decrease in trans-cleavage rates by Cas12a across different types of XNAs, in the following sequence: nucleobase-modified XNA > sugar moiety-modified XNA > backbone-modified XNA. In addition, more complex chemical modifications on either of the three above locations led to the lowering of the trans-cleavage rate of Cas12a. These findings elucidate the mechanism behind Cas12a’ trans-cleavage characteristic, which is attributed to its higher affinity of Cas12a for substrates with simpler chemical structures, leading to increased trans-cleavage efficiency. Based on these findings, we also developed a colorimetric CRISPR/Cas12a biosensing system utilizing XNA for the detection of circulating tumor DNA (ctDNA), with a limit of detection of 10 pM and a 4 logs detection range from 10 pM to 100 nM. These results indicate that XNA can serve as a novel Cas12a trans-cleavage substrate for sensitive biosensing applications.

Quantum-enhanced algorithms for real-time processing in cryptographic systems: A path towards post-quantum security

New technologies such as quantum computing present a major challenge to the current cryptographic systems; thus, quantum-resistant techniques are required. This work describes a new approach for adapting QE schemes to real-life IT security applications, giving a glimpse of the way to post-quantum security. Hence, the architecture proposed here incorporates classical and quantum methods to present a vast enhancement in speed and the stability of security. The system seeks to solve this problem using a hybrid quantum-classical computing strategy. It achieves a 470 percent performance improvement in latency while withstanding both classical and post-quantum attacks concurrently. Field experiments and numerous tests for the accuracy and practicability of the framework established its elasticity and robustness. This research suggests many directions for further research – improving the efficiency of merging quantum-classical users, studying the adaptive quantum algorithms issue, and employing machine learning technology for the identification of threats. The applicability of quantum-enhanced cryptographic processing in producing practical and commercially viable technology highlights the significant advances that have been made in guaranteeing the security of sensitive applications in the coming years, including commerce and appeals. The findings of this type of work can be helpful to the continuous process of establishing post-quantum cryptographic standards and increasing the use of quantum-safe technologies.

Sulfur dioxide gas sensor based on vanadium oxide doped TiO2 nanopaper

Abstract The gas sensor based on TiO2 nanomaterials is promising for both industry and daily life because of its simple fabrication, low cost, high sensitivity, and easy application to micro-devices. However, its selectivity is relatively low and strongly influenced by the environment, thus limiting its practical application. In this work, we prepared TiO2 nanopaper by methods of hydrothermal synthesis and conventional paper preparation. To improve the selectivity, we added V2O5 by immersing the as-prepared nanopaper in an ammonium metavanadate (NH4VO3) solution evenly dispersed in ethanol. Nanopaper is a random array of long nanowires and nanofibers, which retains its shape and structure at high temperature, unlike pure nanowires, due to its high porosity and mechanical stability. V2O5 leads to a selective sensing performance with high catalytic activity for SO2 gas. The surface structure of the sensing material and its porosity were characterized by SEM, XRD, XPS. The improved sensing material exhibited a high response of about 22.6 for 100 ppm SO2 and a fast response and recovery of 9 s and 14 s, respectively. It also exhibited good reproducibility and selectivity in other interfering gases. Furthermore, the long-term sensing performance in the atmospheric environment was maintained for about 50 days.

Educational Mobile Apps Enhancing Communication Skills in Children With Autism in Arab Countries

This exploratory literature review investigates the landscape of educational mobile applications designed for children with autism spectrum disorder (ASD) in Arab countries, with a specific focus on their efficacy in improving communication skills. After a comprehensive search of academic databases and digital libraries, nine studies were reviewed. These studies discussed seven Arabic-language applications designed for ASD children. Consistent with previous research findings, these applications were found to be effective in enhancing communication skills among ASD individuals. By shedding light on the few existing Arabic-language educational mobile applications for ASD children in Arab countries, this comprehensive review contributes significantly to the discourse surrounding ASD interventions. Additionally, it highlights the immediate need for linguistically and culturally sensitive educational applications, designed for a specific population of Arab children with ASD.

MKIDGen3: Energy-resolving, single-photon-counting microwave kinetic inductance detector readout on a radio frequency system-on-chip.

Microwave Kinetic Inductance Detectors (MKIDs) are superconducting detectors capable of single-photon counting with energy resolution across the ultraviolet, optical, and infrared (UVOIR) spectrum with microsecond timing precision. MKIDs are also multiplexable, providing a feasible way to create large-format, cryogenic arrays for sensitive imaging applications in biology, astronomy, and quantum information. Building large, cryogenic MKID arrays requires processing highly multiplexed, wideband readout signals in real time; this task has previously required large, heavy, and power-intensive custom electronics. In this work, we present the third-generation UVOIR MKID readout system (Gen3), which is capable of reading out twice as many detectors with an order of magnitude lower power, weight, volume, and cost-per-pixel as compared to the previous system. Gen3 leverages the Xilinx RFSoC4x2 platform to read out 2048, 1MHz MKID channels per board. The system takes a modern approach to FPGA design using Vitis High-Level Synthesis to specify signal processing blocks in C/C++, Vivado ML intelligent design runs to inform implementation strategy and close timing, and Python productivity for Zynq to simplify interacting with and programming the FPGA using Python. This design suite and tool flow allows general users to contribute to and maintain the design and positions Gen3 to rapidly migrate to future platforms as they become available. In this work, we describe the system requirements, design, and implementation. We also provide performance characterization details and show that the system achieves detector-limited resolving power in the case of few readout tones and minimal degradation with all 2048 tones. Planned upgrades and future work are also discussed. The Gen3 MKID readout system is fully open-source and is expected to facilitate future array scaling to megapixel-sized formats and increase the feasibility of deploying UVOIR MKIDs in space.

High sensitivity and high figure of merit graphene mid-infrared multi-band tunable metamaterial perfect absorber

In the research of this paper, we have devised a mid-infrared band metamaterial perfect absorber made of graphene material. The absorber is composed of a traditional three-layer structure of MPA. The top layer is a graphene layer with a specific structure, with SiO2 as the dielectric layer and the gold film as the substrate. In the wavelength range of 5500 – 13000 nm, the graphene layer generates seven absorption peaks and shows ultra-high absorption efficiency. The respective absorption rates are 91.17%, 99.41%, 99.01%, 95.69%, 94.16%, 96.89%, and 95.01%. By verifying the absorption spectra and the principle of effective impedance matching, analyze the electric field distribution image of the xoy plane based on the principle of surface plasmon resonance, we have proved that it conforms to the classical physical theory and expounded the reason why the absorption peaks were formed. The comparison of different graphene patterns has confirmed the superiority of this structure. By changing the relaxation time and Fermi level of graphene, the tunability of the absorber structure has been verified. Changing the incident angle has proved its insensitivity to the polarization angle (0° - 50°). Finally, by calculating and comparing the figure of merit (FOM) and the sensitivity (S), it is shown that this structure has significant sensitivity and excellent application ability and value. We firmly believe that our absorber can be well applied in high-sensitivity sensors, filters and detectors, and can contribute to fields such as photoelectric detection, optical communication and photoelectric sensing.

Augmented and Virtual Reality Based Segmentation Algorithm for Human Pose Detection in Wearable Cameras

Pose graph optimisation is a crucial method that helps reduce cumulative errors while estimating visual trajectories for wearable cameras. However, when the posture graph's size increases with each additional camera movement, the optimization's efficiency diminishes. In terms of ongoing sensitive applications, such as extended reality and computer-generated reality, direction assessment is a major test. This research proposes an incremental pose graph segmentation technique that accounts for camera orientation variations as a solution to this challenge. The computation only improves the cameras that have seen large direction changes by breaking the posture chart during these instances. As a result, pose graph optimisation is essentially slowed down and optimised more quickly. For every camera that hasn't been optimised using a pose graph, the algorithm employs the wearable cameras at the start and end of each camera's trajectory segment. The final camera in attendance is then determined by weighted average the various postures evaluated with these wearable cameras; this eliminates the need for lengthy nonlinear enhancement computations, reduces disturbance, and achieves excellent accuracy. Experiments on the EuRoC, TUM, and KITTI datasets demonstrate that pose graph optimisation scope is reduced while maintaining camera trajectories accuracy.

Integrated membranes system for water application in microbiology/molecular biology

An integrated membrane filtration system was developed to make water purity suitable for microbiology/molecular biology research. Water samples were collected from outlets in different buildings of the National Research Center and analyzed for their composition before filtration. An integrated membrane system was developed based on mathematical modeling. Flat sheet membranes were produced, including microfiltration, ultrafiltration, and nanofiltration membranes. The flat sheet membranes were converted to a spiral wound module filter to simulate the local market filters and applied in the integrated membrane system that was designed and installed. The produced water was analyzed and compared to molecular-grade water used in different molecular biology/microbiology applications. Both PCR, agarose gel electrophoresis, bacterial liquid cultures, and viral propagation indicated that treated water using the herein-developed system exhibited comparable performance to the molecular grade water provided with imported reagent kits. So, this research can offer a promising solution for producing high-quality water suitable for sensitive laboratory applications.

3D Printed Metallic Pillar Nanomechanical Resonators Decorated with TiO2 Nanotubes for Highly Sensitive Environmental Applications

AbstractMicro and nanomechanical devices offer enhanced sensing capabilities for detecting biological and chemical small molecules. However, miniaturization necessitates advanced fabrication processes and complex measurement systems, hindering routine sensor analysis. While alternative methods like 3D printing show promise, challenges such as low device resolution persist due to intrinsic damping of polymer inks. In this study, an array of micrometric pillar resonators is fabricated in Ti6Al4 V alloy using additive manufacturing based on laser powder bed fusion technology. These metallic nanomechanical resonators exhibit a very high quality factor with minimal difference between air and vacuum measurements due to low intrinsic damping. Furthermore, titania nanotubes grown on the pillars via anodic oxidation heighten sensitivity for molecular dye degradation evaluation. Leveraging the weak coupling phenomenon among the pillars in the array, these devices facilitate large‐scale parallelized measurements, here demonstrated with real‐time analysis of dye degradation process. This approach to creating mass sensing devices via metallic additive manufacturing can usher in a new generation of highly performing resonating sensor arrays, offering a cost‐effective and efficient alternative to traditional silicon microfabrication methods.

Enhancing Reliability in Multilevel Inverter: A Fault‐Tolerant Approach With Reduced Switch Count

ABSTRACTReliability is a major concern in multilevel inverters (MLI) due to the increased number of power switches and diodes, which increases the chance of switch failures and complicates the inverter design. The primary challenges faced by the current MLI design include higher control complexity, increased parasitic elements, more extensive protection, and lack of multiple fault tolerance. Therefore, developing reduced switch MLI with fault‐tolerant ability is crucial to ensure system availability and prevent adverse outcomes. To address these challenges, this article introduces a highly resilient fault‐tolerant reduced switch count (FTRSC) MLI topology offering fault tolerance with minimal switch count. The proposed topology provides fault tolerance in case of single‐ and multiple‐switch open‐circuit (OC) failures. The inherent fault‐tolerant operation is analyzed for the proposed topology's symmetric and asymmetric configurations. The simulation and experimental results validate the effectiveness of the proposed topology considering normal, faulty, and postfault conditions. Furthermore, the reliability evaluation of the proposed work is carried out using the Markov chain model, resulting in a high total mean time to failure of approximately 117,550 h/failures, along with an efficiency of 96.3%. These findings demonstrate that the proposed circuit has enhanced reliability and extended mean time to failure, affirming its suitability for sensitive industrial applications. Finally, a thorough comparison with recent studies highlights the superiority of the proposed system.

In Situ Crystal Growth and Fusing-Confined Engineering of Quasi-Monocrystalline Perovskite Thick Junctions for X-ray Detection and Imaging.

Metal halide perovskites exhibit great promise for utilization in X-ray detection owing to their excellent optoelectronic properties and high X-ray attenuation capabilities. However, fabricating large-area thick films for high-performance perovskite X-ray detection remains challenging. This study develops an in situ crystal growth and fusing-confined approach to prepare high-quality, large-scale perovskite quasi-monocrystalline thick junctions. The perovskite crystals are grown in situ using a highly concentrated perovskite colloidal solution in 2-methoxyethanol. Introducing methylammonium chloride enhances grain reorganization during in situ growth and fusing-confined processes, effectively reducing grain boundaries and surface defects. This allows for the preparation of quasi-monocrystalline thick junctions of large grains (>100 μm) with high crystallinity, uniform orientation, and vertical penetration across the film thickness. Additionally, the carrier mobility and lifetime of the thick junctions are significantly enhanced. The optimized MAPbI3 detectors demonstrate an X-ray sensitivity of 2.6 × 104 μC Gyair-1 cm-2 and an exceptionally low detection limit of 1 nGyair s-1. Furthermore, inspired by a honeycomb structure, these detectors realize X-ray imaging in 64 × 64 pixels through a pixelated separation design, effectively reducing the charge-sharing effect. This study offers valuable insights into the preparation of large-scale perovskite quasi-monocrystalline thick junctions for highly sensitive X-ray detection and imaging applications.

Synthesis, characterization, and application of novel fluorescent sporopollenin for effective detection of mercury (II) ions from aqueous media

In this investigation, a novel environmentally friendly functionalized fluorescent Sp-TAB hybrid material was advanced for the sensitive detection of environmentally polluting Hg(II). The characterization of the synthesized fluorescent Sp-TAB hybrid material using SEM and EDX provided insights into morphological and structural changes in the material's pore structure, while XRD and FT-IR analyses revealed the impact of the prepared material at each stage. Optimal parameters such as temperature, contact time, and pH influencing Hg(II) ion detection were determined. Application of the fluorescent Sp-TAB hybrid material was determined a detection limit (LOD) of 4.87 μM for Hg(II) ions. This study shows the potential of the immobilization-enhanced fluorescent Sp-TAB hybrid material for sensitive Hg(II) ion detection in tap water. Additionally, this study is believed to serve as a model for sensitive and practical detection applications of heavy metals in the future.

GC/MS Screening of Substances Released from Post-Consumer Recycled HDPE Pellets into 95% Ethanol: Reproducibility and Variation between Production Batches

The use of post-consumer recycled (PCR) plastic materials in sensitive packaging applications, such as for cosmetic products and detergents, requires a clear understanding of the identities and quantities of chemical substances, which they may release into packed products. With many potential sources of and thus different types of potentially releasable substances, a reliable non-targeted screening method is required to assess these materials. Such a method should be readily applicable in industrial practice and provide a realistic estimation of substance release. This investigation focused on the use of gas chromatography/coupled mass spectrometry (GC/MS) to analyze substances, which recycled HDPE (rHDPE) plastic pellets release into 95% ethanol under accelerated testing conditions. The results of the repeated testing of reference samples clearly demonstrated the good reproducibility of the described methodology, with standard deviations of repeated determinations of the total released substance amounts of 6.8–8.1%. The application to several production batches of three commercial rHDPE grades additionally demonstrated that the batch-to-batch variation of substances which rHDPE materials release can be confined to less than 10% of variation of the total detectable substance amount. The described methodology is therefore seen as a pragmatic, repeatable assessment of recycled HDPE plastic batches with a view to substance release.

Application of high-throughput drug sensitivity testing in children with relapsed and refractory acute leukemia

To explore the current application of high-throughput drug sensitivity (HDS) testing in children with relapsed and refractory acute leukemia (RR-AL) and analyze the feasibility of salvage treatment plans. A retrospective collection of clinical data from children with RR-AL who underwent HDS testing at the Department of Children's Hematology and Oncology of the First Affiliated Hospital of Zhengzhou University from November 2021 to October 2023 was conducted, followed by an analysis of drug sensitivity results and treatment outcomes. A total of 17 children with RR-AL underwent HDS testing, including 7 cases of relapsed refractory acute myeloid leukemia and 10 cases of relapsed refractory acute lymphoblastic leukemia. The detection rate of highly sensitive chemotherapy drugs/regimens was 53% (9/17), while the detection rate of moderately sensitive chemotherapy drugs/regimens was 100% (17/17). Among the 17 RR-AL patients with highly and moderately sensitive chemotherapy drugs and regimens, the MOACD regimen (mitoxantrone + vincristine + cytarabine + cyclophosphamide + dexamethasone) accounted for 100%, with the highest inhibition rate for single-agent mitoxantrone (94%, 16/17), and the highest inhibition rate for targeted therapy being bortezomib (94%, 16/17). Nine patients adjusted their chemotherapy based on HDS testing results, with 4 undergoing hematopoietic stem cell transplantation. Four patients achieved disease-free survival, while 5 died. Eight patients received empirical chemotherapy, with 2 undergoing hematopoietic stem cell transplantation; 4 achieved disease-free survival, while 4 died. HDS testing can identify highly sensitive drugs/regimens for children with RR-AL, improving the rate of re-remission and creating conditions for subsequent hematopoietic stem cell transplantation.

PPDNN-CRP: privacy-preserving deep neural network processing for credit risk prediction in cloud: a homomorphic encryption-based approach

This study proposes a Privacy-Preserving Deep Neural Network for Credit Risk Prediction (PPDNN-CRP) framework that leverages homomorphic encryption (HE) to ensure data privacy throughout the credit risk prediction process. The PPDNN-CRP framework employs the Paillier homomorphic encryption scheme to secure sensitive loan application data during both the training and inference phases. Implemented using TensorFlow for deep neural network operations and TenSEAL for HE, the framework uses the Kaggle loan dataset to evaluate its performance. The results show that PPDNN-CRP achieved an accuracy of 80.48%, demonstrating competitive performance compared to Privacy-Preserving Logistic Regression (PPLR) at 77.23% and a slight decrease from the non-private DNN-CRP model at 86.18%. The model exhibited strong metrics with a precision of 0.84, recall of 0.91, F1-score of 0.87, and an AUC of 0.74. Security analysis confirms that PPDNN-CRP effectively defends against various privacy attacks, including poisoning, evasion, membership inference, model inversion, and model extraction, through robust encryption techniques and privacy measures. This framework offers a promising approach for achieving high-quality credit risk prediction while maintaining data privacy and complying with legal and ethical standards.

Surface Defects‐Induced Photoactivation of Carbon Dots‐NiFe2O4 Nanocomposite: Synthesis, Mechanism and Applications

AbstractThe optical properties of quantum dots are significantly influenced by photoactivation. However, the progress in the development of photoactivation carbon dot (CDs) is still stagnant. Herein, a method for preparing photoactivated CDs/NiFe2O4 by introducing affluent defects onto the surface of CDs through modification with NiFe2O4, extremely filling the gap of photoactivated CDs is proposed. Interestingly, a fantastic fluorescence detection strategy in a unique “OFF‐ON‐OFF” mode, combined with Ag+‐assisted fluorescence enhancement, to establish a dual‐channel regulation mechanism for ultra‐sensitive detection of Hg2+ is first proposed. By increasing surface traps and non‐radiative recombination, defect‐induced manipulation on the surface of CDs creates favorable conditions for enhancing photoactivation capacity. Unexpectedly, the CDs/NiFe2O4 shows a 25‐fold enhancement in fluorescence intensity after exposure to UV‐lamp. Compared to CDs/NiFe2O4, Ag+‐assisted photoactivation CDs/NiFe2O4 exhibits superior selectivity and sensitivity for Hg2+ detection, with low detection limits of 0.7 nM. Moreover, TiO2@CDs/NiFe2O4 catalyst is successfully prepared by anchoring CDs/NiFe2O4 onto the surface of TiO2, which demonstrates efficient degradation of tetracycline within 90 min under visible light irradiation, with a degradation rate of 98.3%. This work first provides a novel defects modification strategy for developing highly active photoactivated CDs technology that is significant for future environmentally sensitive applications.

Freestanding Germanium Photonic Crystal Waveguide for a Highly Sensitive and Compact Mid-Infrared On-Chip Gas Sensor.

The performance of mid-infrared (MIR) on-chip gas sensors, operating via laser absorption spectroscopy, hinges critically on light-matter interaction dynamics, significantly influenced by external confinement and the effective light path length. Conventional on-chip sensors, however, face challenges in achieving the required limit of detection for highly sensitive applications, primarily due to their intrinsically short effective light path. Furthermore, these sensors are limited in their spectral range coverage within the MIR spectrum by the constraints of standard silicon-based platforms. To overcome these limitations, our research presents a novel approach to fabricate a freestanding germanium (Ge) photonic crystal waveguide (PCW) on a germanium-on-insulator (Ge-OI) platform, utilizing yttrium oxide (Y2O3) as the buried oxide layer. This device leverages the broad transparent windows of Ge and Y2O3, broadening the spectral coverage across the MIR range. The introduction of the PCW and its slow light effect significantly elevate external confinement and light-matter interactions, enabling a notable reduction in waveguide length, which traditionally limits on-chip configurations. The freestanding structure not only expands the sensing region and enhances external confinement but also prevents the emergence of leaky modes within the PCW. As a result, our compact sensor achieves an exceptionally low LoD of 7.56 ppm for carbon dioxide (CO2) sensing at the operational wavelength of 4.23 μm, with a compact waveguide length of only 800 μm.

Application and Challenge of Metalloporphyrin Sensitizers in Noninvasive Dynamic Tumor Therapy

Dynamic tumor therapies (mainly including photodynamic therapy (PDT) and sonodynamic therapy (SDT)) offer new approaches to cancer treatment. They are often characterized by their noninvasive nature, high selectivity, and low toxicity. Sensitizers are crucial for dynamic therapy. Developing efficient sensitizers with good biocompatibility and controllability is an important aim in dynamic therapy. Porphyrins and metalloporphyrins attract great attention due to their excellent photophysical properties and low cytotoxicity under non-light. Compared to porphyrins, metalloporphyrins show greater potential for dynamic therapy due to their enhanced photochemical and photophysical properties after metal ions coordinate with porphyrin rings. This paper reviews some metalloporphyrin-based sensitizers used in photo/sonodynamic therapy and combined therapy. In addition, the probable challenges and bottlenecks in clinical translation are also discussed.

A Photovoltaic Self-Powered Volatile Organic Compounds Sensor Based on Asymmetric Geometry 2D MoS2 Diodes

Transition metal dichalcogenides have gained considerable interest for vapour sensing applications due to their large surface-to-volume ratio and high sensitivity. Herein, we demonstrate a new self-powered volatile organic compounds (VOC) sensor based on asymmetric geometry multi-layer molybdenum disulfide (MoS2) diode. The asymmetric contact geometry of the MoS2 diode induces an internal built-in electric field resulting in self-powering via a photovoltaic response. While illuminated by UV-light, the sensor exhibited a high responsivity of ∼60% with a relatively fast response time of ∼10 sec to 200 ppm of acetone, without an external bias voltage. The MoS2 VOC diode sensor is a promising candidate for self-powered, fast, portable, and highly sensitive VOC sensor applications.

Post-Anesthesia Recovery: A Comprehensive Review of Sampe, Modified Aldrete, and White Scoring Systems.

Post-anesthesia recovery is a vital phase in the perioperative continuum, where the quality of care and monitoring heavily influence patient outcomes. This comprehensive review examines the Sampe, Modified Aldrete, and White Scoring Systems, pivotal in evaluating patients' readiness for discharge from the Post-Anesthesia Care Unit (PACU). The review delves into the historical evolution of post-anesthesia care, highlighting the transition from minimal post-operative support to the establishment of PACUs and the subsequent development of structured recovery scoring systems. Each scoring system is analyzed in detail, focusing on its components, criteria, scoring methodology, advantages, and limitations. A comparative analysis underscores these systems' similarities and differences, sensitivity, specificity, and practical applications in clinical settings. Additionally, the review discusses the clinical implications of these scoring systems in enhancing patient management, improving safety, and ensuring standardized care. Emerging technologies and future directions in recovery assessment are also explored, providing insights into potential innovations. This review aims to equip healthcare professionals with a deeper understanding of these scoring systems, facilitating informed decisions to optimize post-anesthesia care and patient outcomes.