Detector Output Research Articles

Efficiency of sub-THz – DC energy conversion of a silicon detector

The efficiency of sub-THz to DC energy conversion of a silicon-based plasmonic detector was studied. The dependence of the signal at the detector output on the incident radiation power was measured. In the power linear region, the coefficient η was shown to grow with increasing power and to saturate in the sub-linear regime. The maximum achieved values of η were 0.4% for the radiation frequency of 97 GHz. The measurements were carried out both at room temperature and when the detector was cooled to liquid nitrogen temperature.

A progressive phase multiple-injection locking technique for jitter suppression in voltage-controlled ring oscillator

ABSTRACT This paper presents a jitter reduction technique for a voltage-controlled ring oscillator (VCRO). This technique is useful in employing VCRO-based circuits like Analog to Digital Converter (ADC), Phase Locked Loop (PLL), and various time-based circuits whose performance is severely degraded by jitter accumulation, an inherent property of VCRO. In the proposed technique, a 1-bit time-to-digital converter (TDC) is used to extract information about jitter with a sensitivity of 4ps/bit. The rise in phase detector output bit leads VCRO to work in Progressive Phase Multi-Injection Locking (PPM-IL) mode until VCRO gets jitter-free. The proposed work is designed in SCL 180 nm CMOS technology at 1.8 V supply. After enabling the proposed technique, the RMS jitter reduces from 7.436 ps to 1.198ps for VCRO running at 63 MHz and consumes a total power of 1.112 mW.

Laser-fibre interface for single-particle detector amplification and transportation

Abstract Single quantum particle detectors (e.g. photo-multiplier tubes and electron multipliers) produce ns-output pulses that time-correlate to particles that enter them. The detector output pulses usually require amplification at source, before being sent to counting electronics for analysis. A laser-based transport system is detailed here that converts the detector output into light pulses that are injected into single mode fibre. Pulse delivery is then by fibre, so that electrical interference from the laboratory environment and earth grounding loops are eliminated. A fast photodiode and differential amplifier converts the signal exiting the fibre into a voltage pulse for subsequent timing experiments.

Advanced Beam Estimation for Antennas Via Patterned Coupling-Line Detection Board in Ka-Band

In this research, we present an innovative method for estimating the beams of array antennas. Traditional beam analysis methods rely on placing receiving antennas in the far-field region, which requires moving or rotating the Tx or Rx, and using radiation pattern measurements. However, such methods often demand vast spatial requirements and the use of high-cost network analyzers. In contrast, the technique proposed in this study utilizes a board patterned with coupling lines strategically placed in the antenna's near-field zone. Signals intercepted by these coupling lines undergo conversion into DC voltage via a power detector situated at the line terminus. Interestingly, this method enables beam estimation solely based on the DC voltage level output of the power detector, thus offering a cost-effective and space-efficient solution that represents a significant advancement from traditional beam estimation methods.

A 0.01–50 GHz power detector with temperature compensation and wideband DC‐blocking capacitor

AbstractThis letter presents a 0.01–50‐GHz resistive matching power detector implemented in a commercial 0.15‐ GaAs pseudomorphic high electron mobility transistor technology. An analytical expression is derived for the voltage responsivity of the detector as a function of temperature. To compensate for the temperature dependence of the detector, bias diode topology and mesa resistor load are employed. For an input power of −20 dBm at 1 GHz, the maximum variation of the detector output voltage is less than 0.5 dB over the temperature from C to C. The detector's S11 is less than −8 dB, the dynamic range (DR) is 55 dB, and the maximum voltage responsivity is 700 V/W. An on‐chip wideband capacitor with a bent‐strip shape is designed for direct current blocking. The detector can be used for wideband power monitoring and power amplifier control loop for its high DR and temperature stability.

Overcoming the Limitations of Learning-Based VQA for Counting Questions with Zero-Shot Learning

Visual question answering (VQA) research has garnered increasing attention in recent years. It is considered a visual Turing test because it requires a computer to respond to textual questions based on an image. Expertise in computer vision, natural language processing, knowledge understanding, and reasoning is required to solve the problem of VQA. Most techniques employed for VQA consist of models that are developed to learn the combination of image and question features along with the expected answer. The techniques chosen for image and question feature extraction and combining the features change with each model. This method of teaching a model of the question–answer pattern is ineffective for queries that involve counting and reasoning. This approach also requires considerable resources and large datasets for the training. The general VQA datasets feature a restricted number of items as responses to counting questions ([Formula: see text]), and the distribution of the answers is not uniform. To investigate these issues in VQA, we created synthetic datasets that could be modified to adjust the number of objects in the image and the amount of occlusion. Specifically, a zero-shot learning VQA system was devised for counting-related questions that provide answers by analyzing the output of an object detector and the query keywords. Using synthetic datasets, our model generated 100% correct results. Testing on the benchmark datasets task directed image understanding challenge (TDIUC) and TallyQA-simple indicated that the proposed model matched the performance of the learning-based baseline models. This methodology can be used efficiently for counting VQA questions confined to certain domains when the number of items to be counted is significant.

Neutron spectroscopy of plutonium using a handheld detection system

The ability to distinguish multiple forms of plutonium from one another, such as oxide and metal, is paramount in areas of nuclear nonproliferation and international safeguards. In its metal form, plutonium can be readily used in a nuclear weapon, while oxide forms are associated with nuclear reactor fuel. Oxide-based plutonium forms emit neutrons with an energy spectrum that is significantly different from the fission neutrons that are emitted from plutonium metal. Organic scintillation detectors output pulses that are proportional to the neutron energy deposited, and therefore present a means of distinguishing these plutonium forms based on their energy spectra. In this work, metal and oxide forms of plutonium were measured using a handheld detection system based on an organic glass scintillator. Monte Carlo modeling of these experiments was performed to provide insight into the origin of the features in the observed light output spectra. Through analysis of multiple regions of these spectra, in a matter of minutes we were able to unambiguously discriminate oxide and metal plutonium forms from one another and from a plutonium-beryllium neutron source, which was considered for comparison because these sources are commonly used in industrial applications. The ability to discriminate weapons-usable material from nuclear reactor fuel has applications in nuclear treaty verification and safeguards.

Calibrating the global network of gravitational wave observatories via laser power calibration at NIST and PTB

Current gravitational wave (GW) observatories rely on photon calibrators that use laser radiation pressure to generate displacement fiducials used to calibrate detector output signals. Reducing calibration uncertainty enables optimal extraction of astrophysical information such as source distance and sky position from detected signals. For the ongoing O4 observing run that started on 24 May 2023, the global GW detector network is employing a new calibration scheme with transfer standards calibrated at both the National Institute of Standards and Technology (NIST) and the Physikalisch-Technische Bundesanstalt (PTB). These transfer standards will circulate between the observatories and the metrology institutes to provide laser power calibration traceable to the International System of Units (SI) and enable assessment and reduction of relative calibration errors for the observatory network. The Laser Interferometer Gravitational-Wave Observatory (LIGO) project and the Virgo project are currently participating in the new calibration scheme. The Large-scale Cryogenic Gravitational-wave Telescope project (KAGRA) is expected to join in 2024, with the LIGO Aundha Observatory in India joining later. Before implementing this new scheme, a NIST-PTB bilateral comparison was conducted. It validated the scale representation by both laboratories, with a degree of equivalence of −0.2% and an associated expanded uncertainty of 0.32% (k = 2) which is significantly lower than previous studies. We describe the transfer of power sensor calibration, including detailed uncertainty estimates, from the transfer standards calibrated by NIST and PTB to the sensors operating continuously at the interferometer end stations. Finally, we discuss the ongoing calibration of Pcal-induced displacement fiducials for the O4 observing run. Achieved combined standard uncertainty levels as low as 0.3% facilitate calibrating the interferometer output signals with sub-percent accuracy.

High-performance oxygen terminated synthetic single crystal diamond detector for high gamma dose rate measurement

A high-performance oxygen terminated synthetic single crystal diamond (SCD) detector (4.5 × 4.5 × 0.5 mm3) is presented. The SCD detector exhibits an extremely low leakage current value of 0.29 pA/mm2 with an electric field of 0.3 V/μm. The charge collection spectrum measured with a238Pu source (5.48 MeV α-particles) irradiation shows that the electron and hole charge collection efficiency (CCE) reach as high as 99.1% and 98.9%, with an energy resolution as low as 2.87% and 2.53%, respectively, compared to Si detector. The SCD detector shows excellent radiation hardness and stability under 60Co γ-ray irradiation with a dose rate of 12.737 kGy/h at 150 V bias and is able to withstand a cumulative dose of up to at least 9.3 kGy. The detector output in current mode is linearly related to the dynamic dose rate (0.409 Gy/h-12.737 kGy/h). Similarly, the counting rate of the detector in counting mode exhibits a strong linear variation within the range of 2.6 mGy/h-1269.36 Gy/h. Our results fully indicate that our fabricated SCD detector can be potentially applied to harsh γ irradiation scenarios, which is of guiding significance on real-time dose monitoring.

Identification of ChatGPT-Generated Abstracts Within Shoulder and Elbow Surgery Poses a Challenge for Reviewers

PurposeTo evaluate the extent to which experienced reviewers can accurately discern between AI-generated and original research abstracts published in the field of shoulder and elbow surgery and compare this to the performance of an AI-detection tool. MethodsTwenty-five shoulder and elbow-related articles published in high-impact journals in 2023 were randomly selected. ChatGPT was prompted with only the abstract title to create an AI-generated version of each abstract. The resulting 50 abstracts were randomly distributed to and evaluated by 8 blinded peer reviewers with at least 5 years of experience. Reviewers were tasked with distinguishing between original and AI-generated text. A Likert scale assessed reviewer confidence for each interpretation and the primary reason guiding assessment of generated text was collected. AI output detector (0-100%) and plagiarism (0-100%) scores were evaluated using GPTZero. ResultsReviewers correctly identified 62% of AI-generated abstracts and misclassified 38% of original abstracts as being AI-generated. GPTZero reported a significantly higher probability of AI output among generated abstracts (median 56%, IQR 51-77%) compared to original abstracts (median 10%, IQR 4-37%; p < 0.01). Generated abstracts scored significantly lower on the plagiarism detector (median 7%, IQR 5-14%) relative to original abstracts (median 82%, IQR 72-92%; p < 0.01). Correct identification of AI-generated abstracts was predominately attributed to the presence of unrealistic data/values. The primary reason for misidentifying original abstracts as AI was attributed to writing style. ConclusionsExperienced reviewers faced difficulties in distinguishing between human and AI-generated research content within shoulder and elbow surgery. The presence of unrealistic data facilitated correct identification of AI abstracts, whereas misidentification of original abstracts was often ascribed to writing style.

Effect of Ca co-doping on gamma-stimulated luminescence of Lu2SiO5:Ce

In order to estimate the stability of the light output of the scintillation detector, the Lu2SiO5:Ce scintillation crystals, additionally doped with Ca2+ ions at concentrations of 0 ÷ 0.4 at%, were studied. The spectra of optical absorption, gamma-luminescence, thermal luminescence, dose and temperature dependences of luminescence were measured. Gamma-luminescence in the dose range 10 - 5·107 Gy was recorded using 60Co gamma-source at the temperature range of 310–460 K. In contrast to the initial sample (non-doped with Ca), in the sample doped with 0.1 at% of Ca, an increase in the luminescence intensity was observed in the range of 390–425 nm, but further with an increase in the concentration of Ca (0.3–0.4 at%), the intensity of this band decreased to the initial level (undoped). At Ca concentrations of 0.3 and 0.4 at%, the intensity of the Ce1 center band remains practically unchanged up to a dose of 5·107 Gy. LSO crystals doped with Ce 0.1 at% and co-doped with Ca 0.1 at% can be recommended as a scintillation detector up to a gamma-dose of 105 Gy at room temperature.

The great detectives: humans versus AI detectors in catching large language model-generated medical writing

BackgroundThe application of artificial intelligence (AI) in academic writing has raised concerns regarding accuracy, ethics, and scientific rigour. Some AI content detectors may not accurately identify AI-generated texts, especially those that have undergone paraphrasing. Therefore, there is a pressing need for efficacious approaches or guidelines to govern AI usage in specific disciplines.ObjectiveOur study aims to compare the accuracy of mainstream AI content detectors and human reviewers in detecting AI-generated rehabilitation-related articles with or without paraphrasing.Study designThis cross-sectional study purposively chose 50 rehabilitation-related articles from four peer-reviewed journals, and then fabricated another 50 articles using ChatGPT. Specifically, ChatGPT was used to generate the introduction, discussion, and conclusion sections based on the original titles, methods, and results. Wordtune was then used to rephrase the ChatGPT-generated articles. Six common AI content detectors (Originality.ai, Turnitin, ZeroGPT, GPTZero, Content at Scale, and GPT-2 Output Detector) were employed to identify AI content for the original, ChatGPT-generated and AI-rephrased articles. Four human reviewers (two student reviewers and two professorial reviewers) were recruited to differentiate between the original articles and AI-rephrased articles, which were expected to be more difficult to detect. They were instructed to give reasons for their judgements.ResultsOriginality.ai correctly detected 100% of ChatGPT-generated and AI-rephrased texts. ZeroGPT accurately detected 96% of ChatGPT-generated and 88% of AI-rephrased articles. The areas under the receiver operating characteristic curve (AUROC) of ZeroGPT were 0.98 for identifying human-written and AI articles. Turnitin showed a 0% misclassification rate for human-written articles, although it only identified 30% of AI-rephrased articles. Professorial reviewers accurately discriminated at least 96% of AI-rephrased articles, but they misclassified 12% of human-written articles as AI-generated. On average, students only identified 76% of AI-rephrased articles. Reviewers identified AI-rephrased articles based on ‘incoherent content’ (34.36%), followed by ‘grammatical errors’ (20.26%), and ‘insufficient evidence’ (16.15%).Conclusions and relevanceThis study directly compared the accuracy of advanced AI detectors and human reviewers in detecting AI-generated medical writing after paraphrasing. Our findings demonstrate that specific detectors and experienced reviewers can accurately identify articles generated by Large Language Models, even after paraphrasing. The rationale employed by our reviewers in their assessments can inform future evaluation strategies for monitoring AI usage in medical education or publications. AI content detectors may be incorporated as an additional screening tool in the peer-review process of academic journals.

Solar-blind ultraviolet emission-detection monolithic integration of AlGaN multiple-quantum-well diodes via concentric ring-circle configuration

AlGaN multiple-quantum-well diode-based solar-blind ultraviolet emission-detection monolithic integration system shows great application value due to its advantages of multifunctionality, secure communication, and anti-interference ability. To reduce the lateral optical propagation loss and improve the emitting light detection efficiency, we have proposed a concentric ring-circle configuration for the system, where the out-ring light-emitting diode is the emitter at 253 and 267 nm, and the inner-circle detector is the receiver. The out-ring light-emitting diode exhibits about twice the injection current at the same bias and slightly higher light output power at the same current due to better current spreading and sidewall light extraction compared to the conventional square–square configuration. Simultaneously, the concentric inner-circle detector maximizes the collection of the emitted light flux. Under the emission-detection mode for the monolithic integration system, compared to the conventional square–square configuration, the concentric ring-circle design presents an improvement in the ratio of emitter injection current to detector output photocurrent and higher output signal amplitude under the same transmission work mode, demonstrating the improved system energy and coupling efficiency. This design provides a potential approach to achieve low power consumption and high bandwidth in the monolithic integrated optoelectronic chips.

A fast response time gas ionization chamber detector with a grid structure.

The time response characteristic of the detector is crucial in radiation imaging systems. Unfortunately, existing parallel plate ionization chamber detectors have a slow response time, which leads to blurry radiation images. To enhance imaging quality, the electrode structure of the detector must be modified to reduce the response time. This paper proposes a gas detector with a grid structure that has a fast response time. In this study, the detector electrostatic field was calculated using COMSOL, while Garfield++ was utilized to simulate the detector's output signal. To validate the accuracy of simulation results, the experimental ionization chamber was tested on the experimental platform. The results revealed that the average electric field intensity in the induced region of the grid detector was increased by at least 33%. The detector response time was reduced to 27% -38% of that of the parallel plate detector, while the sensitivity of the detector was only reduced by 10%. Therefore, incorporating a grid structure within the parallel plate detector can significantly improve the time response characteristics of the gas detector, providing an insight for future detector enhancements.

Urine Test Strip Quantitative Assay with a Smartphone Camera.

Urine test strips for urinalysis are a common diagnostic tool with minimal costs and are used in various situations including homecare and hospitalization. The coloration scaled by the naked eye is simple, but it is suitable for semiquantitative analysis only. In this paper, a colorimetric assay is developed based on a smartphone digital camera and urine test strips. Assays of pH, albumin, glucose, and lipase activity were performed as a tool for the diagnosis of aciduria, alkaluria, glycosuria, proteinuria, and leukocyturia. The RGB color channels were analyzed in the colorimetric assay, and the assay exerted good sensitivity, and all the particular diagnoses proved to be reliable. The limits of detection for glucose (0.11 mmol/L), albumin (0.15 g/L), and lipase (2.50 U/μL) were low enough to cover the expected physiological concentration, and the range for pH was also satisfactory. The urine test strips with a camera as an output detector proved applicability to spiked urine samples, and the results were also well in comparison to the standard assays which confirms the practical relevance of the presented findings.

QRS Detector Performance Evaluation Aware of Temporal Accuracy and Presence of Noise.

Algorithms for QRS detection are fundamental in the ECG interpretive processing chain. They must meet several challenges, such as high reliability, high temporal accuracy, high immunity to noise, and low computational complexity. Unfortunately, the accuracy expressed by missed or redundant events statistics is often the only parameter used to evaluate the detector's performance. In this paper, we first notice that statistics of true positive detections rely on researchers' arbitrary selection of time tolerance between QRS detector output and the database reference. Next, we propose a multidimensional algorithm evaluation method and present its use on four example QRS detectors. The dimensions are (a) influence of detection temporal tolerance, tested for values between 8.33 and 164 ms; (b) noise immunity, tested with an ECG signal with an added muscular noise pattern and signal-to-noise ratio to the effect of "no added noise", 15, 7, 3 dB; and (c) influence of QRS morphology, tested on the six most frequently represented morphology types in the MIT-BIH Arrhythmia Database. The multidimensional evaluation, as proposed in this paper, allows an in-depth comparison of QRS detection algorithms removing the limitations of existing one-dimensional methods. The method enables the assessment of the QRS detection algorithms according to the medical device application area and corresponding requirements of temporal accuracy, immunity to noise, and QRS morphology types. The analysis shows also that, for some algorithms, adding muscular noise to the ECG signal improves algorithm accuracy results.

Analog multiplexing of a laser clock and computational photon counting for fast fluorescence lifetime imaging microscopy.

The dynamic range and fluctuations of fluorescence intensities and lifetimes in biological samples are large, demanding fast, precise, and versatile techniques. Among the high-speed fluorescence lifetime imaging microscopy (FLIM) techniques, directly sampling the output of analog single-photon detectors at GHz rates combined with computational photon counting can handle a larger range of photon rates. Traditionally, the laser clock is not sampled explicitly in fast FLIM; rather the detection is synchronized to the laser clock so that the excitation pulse train can be inferred from the cumulative photon statistics of several pixels. This has two disadvantages for sparse or weakly fluorescent samples: inconsistencies in inferring the laser clock within a frame and inaccuracies in aligning the decay curves from different frames for averaging. The data throughput is also very inefficient in systems with repetition rates much larger than the fluorescence lifetime due to significant silent regions where no photons are expected. We present a method for registering the photon arrival times to the excitation using time-domain multiplexing for fast FLIM. The laser clock is multiplexed with photocurrents into the silent region. Our technique does not add to the existing data bottleneck, has the sub-nanosecond dead time of computational photon counting based fast FLIM, works with various detectors, lasers, and electronics, and eliminates the errors in lifetime estimation in photon-starved conditions. We demonstrate this concept on two multiphoton setups of different laser repetition rates for single and multichannel FLIM multiplexed into a single digitizer channel for real-time imaging of biological samples.

Guidelines for appropriate use of BirdNET scores and other detector outputs

Guidelines for appropriate use of BirdNET scores and other detector outputs

BPMTrack: Multi-Object Tracking with Detection Box Application Pattern Mining.

The key to multi-object tracking is its stability and the retention of identity information. A common problem with most detection-based approaches is trusting and using all the detector outputs for the association. However, some settings of detectors can affect stable long-range tracking. Based on the principle of reducing the association noise in the detection processing step, we propose a new framework, the Box application Pattern Mining Tracker (BPMTrack), to address this issue. Specifically, we worked on three main aspects: output threshold, association strategy, and motion model. Due to the problem of inconsistency between classification scores and localization accuracy, we propose the Box Quality Estimation Network (BQENet) to predict the localization quality scores of all detections in the current frame, reserving high-quality boxes for the tracker. In addition, based on observations of intensive scenarios, we propose a simple and effective data association method, the Non-Maximum Suppression Integration (NMSI) matching strategy. It recovers the Non-Maximum Suppression (NMS) detection, inputs them into BQENet, and then performs hierarchical matching with reasonable control of box priority to alleviate the problem of absent objects caused by occlusion. Finally, we propose an improved Measurement Correct and Noise Scale (MCNS) Kalman algorithm to improve the prediction accuracy of object positions and, thus, the association quality. We performed an extensive ablation evaluation of the proposed framework to prove its effectiveness. Moreover, the three tracking benchmarks show our method's accuracy and long-distance performance.

Sparsity-guided Discriminative Feature Encoding for Robust Keypoint Detection

Existing handcrafted keypoint detectors typically focus on designing specific local structures manually while ignoring whether they have enough flexibility to explore diverse visual patterns in an image. Despite the advancement of learning-based approaches in the past few years, most of them still rely on the availability of the outputs of handcrafted detectors as a part of training. In fact, such dependence limits their ability to discover various visual information. Recently, semi-handcrafted methods based on sparse coding have emerged as a promising paradigm to alleviate the above issue. However, the visual relationships between feature points have not been considered in the encoding stage, which may weaken the discriminative capability of feature representations for keypoint recognition. To tackle this problem, we propose a novel sparsity-guided discriminative feature representation (SDFR) method that attempts to explore the intrinsic correlations of keypoint candidates, thus ensuring the validity of characterizing distinctive and diverse structural information. Specifically, we first incorporate an affinity constraint into the feature representation objective, which jointly encodes all the patches in an image while highlighting the similarities and differences between them. Meanwhile, a smoother sparsity regularization with the Frobenius norm is leveraged to further preserve the similarity relationships of patch representations. Due to the differentiable property of this sparsity, SDFR is computationally feasible and effective for representing dense patches. Finally, we treat the SDFR model as multiple optimization sub-problems and introduce an iterative solver. During comprehensive evaluations on five challenging benchmarks, the proposed method achieves favorable performances compared with the state of the art in the literature.