Optimal Detection Research Articles

Performance analysis of mean level CFAR detectors in homogeneous gamma-distributed radar clutter

ABSTRACT In this paper, a novel and exact mathematical formulation of three mean level constant false alarm rate (CFAR) detectors has been developed considering a homogeneous gamma-distributed (GM) clutter. These detectors include the cell averaging (CA), the greatest-of (GO), and the smallest-of (SO)-CFAR detection schemes. To do so, we derived closed-form expressions for the probability density function (pdf), and the cumulative distribution function (cdf) of the sum of an exponential fluctuating target submerged in gamma-distributed sea clutter. Then, we developed exact and explicit expressions for the probability of false alarm (P fa ) and probability of detection (P d ) of the optimal fixed threshold detector and the three considered CFAR detectors. The correctness of our expressions is then examined and validated via numerical simulations. Assuming a homogeneous GM background, the detection performance of these three detectors is carried out, discussed, and compared with that of the optimal detector. Experimental results with Sentinel-1 synthetic aperture radar (SAR) data demonstrate the effectiveness of the proposed closed-form expressions and show that the considered CFAR schemes are efficient for ship detection in sea clutter backgrounds.

Thermodynamics and Kinetics-Directed Regulation of Nucleic Acid-Based Molecular Recognition.

Nucleic acid-based molecular recognition plays crucial roles in various fields like biosensing and disease diagnostics. To achieve optimal detection and analysis, it is essential to regulate the response performance of nucleic acid probes or switches to match specific application requirements by regulating thermodynamics and kinetics properties. However, the impacts of thermodynamics and kinetics theories on recognition performance are sometimes obscure and the relative conclusions are not intuitive. To promote the thorough understanding and rational utilization of thermodynamics and kinetics theories, this review focuses on the landmarks and recent advances of nucleic acid thermodynamics and kinetics and summarizes the nucleic acid thermodynamics and kinetics-based strategies for regulation of nucleic acid-based molecular recognition. This work hopes such a review can provide reference and guidance for the development and optimization of nucleic acid probes and switches in the future, as well as for advancements in other nucleic acid-related fields.

Error performance of DF cooperative SMTs with I/Q imbalance over Beckmann fading channels

The direct down-conversion principle, which has generally been used in the design of multiple-input multiple-output (MIMO) schemes, including space modulation techniques (SMTs), is attractive to researchers because of its low cost, low power consumption with fewer components, flexible and simple structure. However, hardware imperfections such as in-phase (I) and quadrature-phase (Q) imbalance (IQI) negatively affect the performance of the systems with direct down-conversion in practice. On the other hand, cooperative communication is a promising technology that can be utilized in the design of future wireless networks due to its significant advantages such as increasing system reliability, extending network coverage, reducing channel degradation, and providing high quality of service. In this study, SMT-based methods are integrated into cooperative systems, and a flexible and comprehensive model is presented that is applicable to many channel structures. Specifically, the error performance analysis of space shift keying (SSK), spatial modulation (SM), and quadrature SM (QSM) systems in the presence of IQI in decode-and-forward (DF) cooperative communication is carried out by analytical derivations and computer simulations over generalized Beckmann fading channels. The obtained results show that the performance of SMT-based DF cooperative systems is superior to the conventional schemes, and the effects of receiver IQI can be eliminated by optimal detector designs.

The development of Liver Research Cymru, a new partnership to increase hepatology research activity in Wales

Background The incidence and severity of liver disease in the United Kingdom have increased over the last 20 years. Many patients present with advanced disease with limited treatment options and subsequently high morbidity and mortality. There was also a significant correlation with deprivation. Strategies that support the earlier detection of liver disease are paramount to reverse this trend. Despite significant progress in terms of novel pathways, the optimal strategy for early detection of liver disease remains unknown. Novel ways to tackle the deprivation gradient and reduce health inequalities are urgently required. Methods Clinical research has an enormous role to play both in terms of identifying the true scale of this challenge, where current gaps exist, and to identify the optimal early detection strategies and their implementation. WE therefore established Liver Rsearch Cymru (LRC) a multi-disciplinary collaboration that seeks to maximise the benefits from our existing data sources and clinical networks and increase the output of hepatology research in Wales. Results LRC has developed the first Wales wide research collaborative. We have successfully collaborated with the Secure Anonymised Information Linkage (SAIL) data resource to develop a greater understanding of liver disease burdens through comprehensive analysis of primary and secondary care data. We are now using this information to evaluate the effectiveness of local early detection pathways and to identify the scale of delays in diagnosis with a view to addressing this important care gap. Conclusion LRC has successfully brought together patients. Hepatologists and population/primary care academics to better understand current discrepancies in the early diagnosis of liver disease in Wales. In addition, it has laid a foundation for future research work based both on our preliminary findings and allowed us to collaborate with other more established liver disease research groups.

Understanding Treatment Decisions and Management for Patients with Advanced Renal Cell Carcinoma Using Hypothetical Case Studies: A Vodcast.

In recent years, the armamentarium of therapies for the management of advanced renal cell carcinoma (aRCC) has grown. Combination therapies, including immuno-oncology (IO) agents and tyrosine kinase inhibitors [TKIs (IO-TKI)], and IO-IO combinations, are now approved for first-line treatment of aRCC. Decisions regarding the use of these combinations, IO-IO versus IO-TKI, can be challenging, as they have not been compared in a randomized trial; each of these combinations have been compared with sunitinib alone. In addition, patient-, disease-, and treatment-based factors must be evaluated in the decision-making process. More important is the consideration of patient management during treatment and optimal detection and management of toxicities to ensure continued benefit. In this vodcast, two experts in the field of kidney cancer will present case studies that represent typical patients seen in practice. The faculty will discuss treatment approaches, adverse event management, and which factors to consider during the treatment decision-making process. Viewers of the vodcast will get a better understanding of clinical trial outcomes related to an IO-TKI combination, such as axitinib plus pembrolizumab, that they can apply to their practice immediately. In addition, they will gain real-world insight into how experts approach the treatment of patients with aRCC and, more importantly, therapy management.

Optimal multi-spectrum polarization detection with full-Stokes in a single channel by using standard retarders

Polarization detection with full-Stokes is one of the important way to obtain spatial distribution and physical information on targets. However, the most full-Stokes multi-spectrum polarization detection system is relatively complex, as the traditional method is generally designed for multi-channel to adapt the different wavelength. In this paper, we propose an optimal polarization detection method to obtain the full-Stokes vector of the incident light in one channel for different wavelengths. This method utilizes two standard retarders for multi-spectrum full polarization modulation, which can obtain accurately the desired retardance to achieve optimal system performance at multi-wavelengths. The numeric analysis validates the feasibility of the dual-retarders detection system based on tunable polarization retardance method. Furthermore, in experiments, just two much more readily available quarter-wave plate (QWP) retarders are utilized, the various special retardance within 0.2° errors and high polarization measurement accuracy below 10-2 level at multi-wavelengths are achieved. This method, with a simple structure, has excellent application prospects in high-precision polarization detection, such as solar magnetic field detection.

Spatiotemporal evolution and influencing factors of flood resilience in Beibu Gulf Urban Agglomeration

In the context of global climate change and rapid urbanization, enhancing flood resilience is essential for mitigating urban flood risk. However, few studies have conducted long-term, cross-scale dynamic evaluations of flood resilience and analyzed its influencing factors and mechanisms. Taking the Beibu Gulf urban agglomeration as the study area, a long-term, cross-scale dynamic evaluation index system based on the “Robustness-Resistance-Recovery” (3Rs) framework were adopted to assess the spatiotemporal evolution of flood resilience from 2000 to 2020. Furthermore, the optimal parameters-based geographical detector model is employed to identify the key influencing factors and mechanisms. The results reveal that pre-flood robustness is lower in coastal areas and higher in inland regions. In the during-flood stage, cities with greater comprehensive power exhibit stronger resistance. Post-flood recovery is higher in city centers and marginal mountainous areas, while coastal and inland low-lying regions show lower recovery. The flood resilience of urban agglomerations has improved in recent years, largely due to the enhancement of urban flood control infrastructure and healthcare capacity. However, disparities between cities persist. From 2000 to 2020, economic factors have been the primary drivers of improved flood resilience, while ecological factors have gained increasing importance over the past decade. These findings provide valuable insights for flood prevention, mitigation, and resilience management in urban agglomerations. The proposed dynamic evaluation index system offers a reference framework for evaluating flood resilience in other regions.

Optical signal characteristics analysis of atmospheric disturbance density fields generated by high-speed aircraft

Aircraft disturbs the adjacent atmospheric environment in flight, forming spatial distribution features of atmospheric density that differ from the natural background, which may potentially be utilized as tracer characteristics to introduce new technologies for indirectly sensing the presence of aircraft. In this paper, the concept of a long-range aircraft detection based on the atmospheric disturbance density field is proposed, and the detection mode of tomographic imaging of the scattering light of an atmospheric disturbance flow field is designed. By modeling the spatial distribution of the disturbance density field, the scattered echo signal images of active light towards the disturbance field at long distance are simulated. On this basis, the characteristics of the disturbance optical signal at the optimal detection resolution are analyzed. The results show that the atmospheric disturbance flow field of the supersonic aircraft presents circular in the light-scattering echo images. The disturbance signal can be further highlighted by differential processing of the adjacent scattering images. As the distance behind the aircraft increases, the diffusion range of the disturbance signal increases, and the signal intensity and contrast with the background decrease. Under the ground-based observation conditions of the aircraft at a height of 10000 m, a Mach number of 1.6, and a detection distance of 100 km, the contrast between the disturbance signal and the background was 30 dB at a distance of one time from the rear of the fuselage, and the diffusion diameter of the disturbance signal was 50 m. At a distance eight times the length of the aircraft, the contrast decreased to 10 dB, and the diameter increased to 290 m. The contrast was reduced to 3 dB at a distance nine times the length of the aircraft, and the diameter was diffused to 310 m. These results indicate the possibility of long-range aircraft detection based on the characteristics of the atmospheric density field.

Rapid detection of chlorpyrifos in miscellaneous beans based on nitrogen and phosphorus doped carbon quantum dots fluorescence probe

A fluorescent probe based on N, P-doped carbon quantum dots was established to detect chlorpyrifos. N, P-doped carbon quantum dots were prepared by one-step hydrothermal method with trisodium citrate, dipotassium hydrogen phosphate and urea. The sensing mechanism was based on the fluorescence quenching of N, P-doped carbon quantum dots by chlorpyrifos through internal filtering effect. The results indicated that the linear range was 0.025 ~ 25µg/mL with the detection limit of 0.0008µg/g under the optimal detection conditions. The method was applied to different miscellaneous beans with the recoveries of 90.2% ~ 105.7% and the relative standard deviations were less than 4.8%. The fluorescent probe has the advantages of economy, high efficiency, easy preparation and specificity.

Exploring the tree algorithms to generate the optimal detection system of students' stress levels

Exploring the tree algorithms to generate the optimal detection system of students' stress levels

Advanced design of target-driven self-powered sensor assisted by cascade catalytic strategy

In this work, a self-powered microsensor platform based on enzyme biofuel cells (EBFCs) was developed for intelligent monitoring of disease markers miRNA-451. The cascade catalysis system constructed by using the strategy of enzyme-like ZIF-8 nanocapsule incorporation with biological enzymes, which could simultaneously take into account the specificity of biological enzymes and the high activity of nano-enzymes, significantly promoted the electron transfer between glucose and the bio-anode surface, and improved the sensitivity and stability of the sensing system. Meanwhile, the target-triggered hybridisation chain reaction (HCR) amplification strategy to achieve exponential signal amplification based on accurate recognition, and jointly improve the detection sensitivity. As expected, the micro-sensor platform has a wide linear range of 0.5-1.0 fmol/L with a low limit of detection (LOD) of 0.13 fmol/L (S/N=3) and exhibits excellent selectivity, reproducibility and stability in interference assays under optimal detection conditions. The designed self-powered system is simple to construct, easy to transport and the data transmission mode is intelligent and controllable, which is expected to be used in basic biochemical research, clinical diagnosis and environmental monitoring.

Leveraging AI for real time crime prediction, disaster response optimization and threat detection to improve public safety and emergency management in the US

Leveraging AI for real time crime prediction, disaster response optimization and threat detection to improve public safety and emergency management in the US

Determination of Polyphenols in Cigar Tobacco by HPLC

A high performance liquid chromatography (HPLC) method was developed for the determination of neochlorogenic acid, cryptochlorogenic acid and caffeic acid in cigar tobacco. Firstly, the extraction method, extraction liquid concentration and dosage, column temperature and mobile phase flow rate of polyphenols in cigar tobacco were discussed. Then the detection limit, recovery rate, precision and standard curve of three polyphenols were tested. Finally, tobacco samples were tested. The results showed that the optimal extraction conditions were: ultrasonic extraction, extraction time was 30 min, methanol volume concentration was 50%, dosage was 20 mL, the optimal detection conditions were: column temperature was 30 ℃, flow rate was 1.0 mL/min, detection wavelength was 340 nm. The contents of neochlorogenic acid, cryptochlorogenic acid and caffeic acid were in the range of 0~0.202 mg/g, 0~0.331 mg/g and 0.050~0.073 mg/g, respectively, and the linear correlation coefficients of the three polyphenols were ≥0.9991, indicating that the linear correlation of the method was good, and the detection limit was ≤0.066 mg/L. The precision was ≤0.427%, and the recovery was 95.13~96.39%. The results showed that the method had good precision, high accuracy, short analysis time and high detection efficiency, and could be used as an effective method for the detection of polyphenols in cigar tobacco leaves.

Retraction Note: Application of light sensors based on reinforcement learning in martial arts action optimization and image defect detection

Retraction Note: Application of light sensors based on reinforcement learning in martial arts action optimization and image defect detection

Early detection for carbohydrate antigen-19-9 based on surface enhanced Raman spectroscopy aptamer sensor

BackgroundIncipient screening for cervical cancer is crucial for treatment and improving prognosis. In this work, SERS based aptamer sensor (aptasensor) has been developed and applied to high-sensitivity detection of cervical cancer tumor marker (Carbohydrate antigen19-9 (CA19-9)) with a microporous chip, which was used as surface enhanced Raman scattering (SERS) analysis platform. MethodsThe aptamer of CA19-9 was immobilized on the gold nanodumbbell as a capture probe and the gold nanobipyramid containing complementary aptamer chains of the signal molecule Cy5 was modified as a signal probe. SERS aptasensor was constructed by combining signal probes and capture probes. It caused signal molecule Cy5 were sandwiched between the signal probes and capture probes; the constructed SERS aptasensor generated a strong SERS signal of Cy5. Based on the strong specificity of the aptamer, the CA19-9 aptamer binds specifically to CA19-9 when CA19-9 exist in the detection environment. The signal probe was released, resulting in a decrease in the SERS signal of the detection environment. ResultsUnder the optimal detection conditions, the detection limit of the aptasensor was calculated to be 1.16 × 10−3 U/mL and limit of quantification is equal to 3.87 × 10−3 U/mL. In addition, a standard cervical cancer bearing mouse model was constructed and the SERS spectra of the serum of mice at different stages were measured. The CA19-9 content in the serum of mice at different stages was calculated. Compared with the results of enzyme-linked immunosorbent assay (ELISA), relative error (RE) values (2.54 %, −6.093 %, −4.922 %, and 3.04 %) of the CA19-9 concentrations detected by the two methods on the day of 0, 7, 14 and 28. ConclusionThe proposed SERS aptasensor provides a new and reliable platform for early cervical cancer screening, and its low RE value proves that it will be a promising CA19-9 detection method.

Effective SQL Injection Detection: A Fusion of Binary Olympiad Optimizer and Classification Algorithm

Since SQL injection allows attackers to interact with the database of applications, it is regarded as a significant security problem. By applying machine learning algorithms, SQL injection attacks can be identified. Problem: In the training stage of machine learning methods, effective features are used to develop an optimal classifier that is highly accurate. The specification of the features with the highest efficacy is considered to be an NP-complete combinatorial optimization challenge. Selecting the most effective features refers to the procedure of identifying the smallest and most effective features in the dataset. The rationale behind this paper is to optimize the accuracy, precision, and sensitivity parameters of the SQL injection attack detection method. Method: In this paper, a method for identifying SQL injection attacks was suggested. In the first step, a particular training dataset that included 13 features was developed. In the second step, to specify the best features of the dataset, a specific binary variety of the Olympiad optimization algorithm was developed. Various machine learning algorithms were used to create the optimal attack detector. Results: Based on the experiments carried out, the suggested SQL injection detector using an artificial neural network and the feature selector can achieve 99.35% accuracy, 100% precision, and 100% sensitivity. Owing to selecting about 30% of the effective features, the proposed method enhanced the efficacy of SQL injection detectors.

Preoperative [18F]fluoro-PEG-folate PET/CT in advanced stage epithelial ovarian cancer: A safety and feasibility study

PurposeThe selection for either primary or interval cytoreductive surgery (CRS) in patients with epithelial ovarian cancer (EOC) is currently based on imaging techniques like computed tomography (CT), [18F]fluorodeoxyglucose-positron emission tomography ([18F]FDG-PET), diffusion-weighted magnetic resonance imaging (DW-MRI) and/or diagnostic laparoscopy, but these have limitations. Folate receptor (FR)-targeted PET/CT imaging, using [18F]fluoro-PEG-folate, could improve preoperative assessment, potentially reducing unnecessary laparotomies. This paper presents the first experience with [18F]fluoro-PEG-folate PET/CT imaging in advanced stage EOC, focusing on safety, tolerability, and feasibility for reflecting the extent of disease. MethodsTolerability and safety were monitored after administration of the [18F]fluoro-PEG-folate tracer by measurements of vital function parameters (blood pressure, heart rate, peripheral oxygen saturation, respiratory rate, and temperature). In addition, (serious) adverse events were recorded. Disease burden was quantified using the Peritoneal Cancer Index (PCI) score on preoperative [18F]fluoro-PEG-folate PET/CT and during surgery. PCI scores were compared with intraoperative findings, considering histopathologic results as the gold standard. Tissue specimens were stained for FRα and FRβ. Relative uptake of the radiotracer by EOC lesions and other tissues was quantified using body weighted standardized uptake values (SUV). ResultsThe study was terminated prematurely during the interim analysis after inclusion of eight patients of whom five had completed the study protocol. Although [18F]fluoro-PEG-folate demonstrated safety, efficacy for tumor-specific imaging was limited. Despite clear FRα overexpression, low tracer uptake was observed in EOC lesions, contrasting with high uptake in healthy tissues, posing challenges in specificity and accurately assessing tumor burden. ConclusionsOverall, while [18F]fluoro-PEG-folate was well-tolerated, its clinical utility in the preoperative assessment of the extent of disease in EOC was limited. This highlights the need for further research in developing targeted imaging agents for optimal detection of EOC metastases.Trial registration: Clinicaltrials.gov, NCT05215496. Registered 31 January 2022.

Dynamic Change Characteristics of Wetlands in Hefei and their Driving Factors Along the Urban–Rural Gradient

Wetlands, as vital components of urban ecological infrastructure, provide essential ecosystem services. However, they face increasing risks of degradation and loss due to their vulnerability, environmental changes, and human activities. Therefore, effective restoration efforts are urgently needed. This study adopts a novel approach by considering the urban–rural gradient and integrates land use data, ecological parameters, and anthropogenic factors in Hefei City. Through morphological spatial pattern analysis, principal component analysis, and affinity propagation, this study identifies and analyzes urban–rural gradients. Using the optimal parameter geographic detector, the drivers of wetland changes from 1990 to 2020 are quantitatively assessed across different urban–rural gradients in Hefei. The findings indicate the following. (1) A persistent reduction in wetland expanse throughout the study duration, diminishing from 1274.56 km2 in 1990 to 1119.37 km2 in 2020, constituting a decrement of 12.17%. (2) Based on geographic detector outcomes, disparate driving forces underpin wetland dynamics across urban–rural gradients, with urban locales predominantly influenced by organic carbon and the proportion of impervious surface factors. Meanwhile, in agricultural and semi-ecological villages, silt is the primary factor, while ecological villages are primarily modulated by both silt and gross domestic product factors. Additionally, synergistic interactions manifest heightened explanatory power. This study elucidates the mechanistic underpinnings of wetland dynamics along urban–rural gradients, providing pivotal insights for developing targeted wetland restoration and conservation policies pertinent to the urban–rural developmental trajectory in Hefei City. Concurrently, it offers relevant recommendations for the multifaceted stewardship and sustainable development of wetlands in Hefei City in the foreseeable future.

Integration of surface swab with optical microscopy for detection and quantification of bacterial cells from stainless-steel surfaces.

Swab sampling is a common method for recovering microbes on various environmental surfaces. Its successful application for a specific target depends on the proper swab method and the following detection assay. Herein, we evaluated critical factors influencing surface swab sampling, aiming to achieve the optimal detection and quantification performance of optical detection for bacterial cells on stainless-steel surfaces. Our results showed the recovery rate of Salmonella enterica (SE1045) cells from the 10×10cm2 stainless-steel surface reached up to 92.71±2.19% when using ammonia bicarbonate-moistened polyurethane foam swabs for gentle collection, followed by ultrasound-assisted release in NH4HCO3 solution. Among the six different foam swabs, the Puritan™ Sterile Large Foam Swab contributed the lowest background noise and highest recovery efficiency when integrated with the optical detection assay. Notably, our method exhibited a strong linear relationship (r2=0.9983) between the detected cell numbers and the theoretical number of SE1045 cells seeded on surfaces in the range of 104-107 Colony Forming Units (CFU), with a limit of detection of 7.2×104 CFU 100cm-2. This integration was completed within 2 h, exhibiting the applicable potential in various settings.

Simultaneous Electrochemical Detection of Catechol and Hydroquinone Based on a Carbon Nanotube Paste Electrode Modified with Electro-Reduced Graphene Oxide.

Effectively detecting catechol (CC) and hydroquinone (HQ) simultaneously is crucial for environmental protection and human health monitoring. In the study presented herein, a novel electrochemical sensor for the sensitive simultaneous detection of CC and HQ was constructed based on an electrochemically reduced graphene oxide (ERGO)-modified multi-walled carbon nanotube paste electrode (MWCNTPE). Scanning electron microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy and electrochemical techniques were utilized to characterize the sensing interface and investigate the sensing mechanism. Under the optimal detection conditions, the oxidation peak currents of CC and HQ show a good linear relationship with their concentrations in the range of 0.4-400 μM with a detection limit of 0.083 μM for CC and 0.028 μM for HQ (S/N = 3). Moreover, the sensor exhibits good performance and can be applied successfully in the simultaneous detection of CC and HQ in tap water samples and urine samples with satisfactory results, indicating its promising application prospects.