Level Of Precision Research Articles

The PAU survey: photometric calibration of narrow band images

ABSTRACT The physics of the accelerating Universe (PAU) camera is an optical narrow band and broad band imaging instrument mounted at the prime focus of the William Herschel Telescope. We describe the image calibration procedure of the PAU survey data. We rely on an external photometric catalogue to calibrate our narrow band data using stars that have been observed by both data sets. We fit stellar templates to the stellar broad-band photometry of the Sloan Digital Sky Survey and synthesize narrow band photometry that we compare to the PAUS narrow band data to determine their calibration. Consequently, the PAUS data are in the AB system as inherited from its reference calibrator. We do several tests to check the performance of the calibration. We find it self-consistent when comparing repeated observations of the same objects, with a good overall accuracy to the AB system which we estimate to be at the 2 per cent precision level and no significant trends as a function of narrow band filter or wavelength. Repeated observations allow us to build a spatial map of the illumination pattern of the system. We also check the wavelength dependence of the calibration comparing to stellar spectra. We find that using only blue stars reduces the effects of variations in the stellar template fitting to broad-band colours, improving the overall precision of the calibration to around 1 per cent and its wavelength uniformity. The photometric redshift performance obtained with the PAUS data attests to the validity of our calibration to reach the PAUS science goals.

Multicriteria decision support under uncertainty: combining outranking methods with Bayesian networks

AbstractAssessing alternative solutions that have uncertain evaluations in conflicting multiple criteria is not straightforward. Probabilistic models such as Bayesian networks (BNs) can effectively model and represent the uncertainty in such problems, but they do not include built-in mechanisms to guide different decision makers (DMs) with varying preferences toward the final decision. We propose a systematic approach to combine outranking methods with BNs to provide decision support for solutions with multiple and conflicting criteria under uncertainty. The proposed approach is based on Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), and it offers different levels of precision and flexibility to the DMs in assessing the solutions. Our approach includes graphical tools and summary metrics to enhance the presentation of its results to the DMs. We test our approach with a case study on supplier selection where the uncertainty in supplier performances is modeled with a BN. We demonstrate that the proposed approach can enable the joint use of multiple criteria techniques with probabilistic modeling techniques like BNs to provide decision support in complex environments including uncertainty.

IOT-BASED SMART FARMING IMPLEMENTATION TO OPTIMIZE WORK EFFICIENCY OF HYDROPONIC FARMERS PAKISAJI MALANG

Background: Farmers can market their crops due to the significant market share for hydroponic agriculture products. However, this presents a dilemma as the market demands a consistent supply of high-quality crops. Precise nutrient levels and controlled chemical-physics parameters are crucial considerations in hydroponic yields. Thus far, these factors have been managed manually, leading to challenges in achieving desired outcomes. Objective: This community service program aimed to address this issue by developing a real-time automated system for monitoring and controlling chemicalphysics parameters and nutrient levels via an Android application. The goal was to enhance the effectiveness and productivity of hydroponic crop harvests. Method: The program commenced with designing the system based on farmer requirements, followed by the installation and testing of equipment at partner locations. Subsequently, technical training on system features and usage was provided. Results: The system was successfully installed at Grahaponik. According to questionnaire responses, 68.4% of farmers expressed satisfaction, and 78.9% of total participants reported that the system was easy to employ. Technology installation, implementation, and dissemination to local hydroponic farmer groups were conducted. Hydroponic farmers acknowledged the user-friendliness of the devices. Conclusion: Partners' acceptance of the instruments was favorable, facilitating their ease of use and thereby enhancing the effectiveness of hydroponic farming.

On current limitations of online eye-tracking to study the visual processing of source code

Context:Eye-tracking is an increasingly popular instrument to study how programmers process and comprehend source code. While most studies are conducted in controlled environments with lab-grade hardware, it would be desirable to simplify and scale participation in experiments for users sitting remotely, leveraging home equipment. Objective:This study investigates the possibility of performing eye-tracking studies remotely using open-source algorithms and consumer-grade webcams. It establishes the technology’s current limitations and evaluates the quality of the data collected by it. We conclude by recommending ways forward to address the shortcomings and make remote code-reading studies in support of eye-tracking feasible in the future. Method:We gathered eye-gaze data remotely from 40 participants performing a code reading experiment on a purpose-built web application. The utilized eye-tracker worked client-side and used ridge regression to generate x- and y-coordinates in real-time predicting the participants’ on-screen gaze points without the need to collect and save video footage. We processed and analysed the collected data according to common practices for isolating eye-movement events and deriving metrics used in software engineering eye-tracking studies. In response to the lack of an algorithm explicitly developed for detecting oculomotor fixation events in low-frequency webcam data, we also introduced a dispersion threshold algorithm for that purpose. The quality of the collected data was subsequently assessed to determine the adequacy and validity of the methodology for eye-tracking. Results:The collected data was found to be of varying quality despite extensive calibration and graphical user guidance. We present our results highlighting both the negative and positive observations from which the community hopefully can learn. Both accuracy and precision were low and ultimately deemed insufficient for drawing valid conclusions in a high-precision empirical study. We nonetheless contribute to identifying critical limitations to be addressed in future research. Apart from the overall challenge of vastly diverse equipment, setup, and configuration, we found two main problems with the current webcam eye-tracking technology. The first was the absence of a validated algorithm to isolate fixations in low-frequency data, compromising the assurance of the accuracy of the data derived from it. The second problem was the lack of algorithmic support for head movements when predicting gaze location. Unsupervised participants do not always keep their heads still, even if instructed to do so. Consequently, we frequently observed spatial shifts that corrupted many collected datasets. Three encouraging observations resulted from the study. Even when shifted, gaze points were consistently dispersed in patterns resembling both the shape and size of the stimuli without extreme deviations. We could also distinguish recognizable reading patterns. Linearity was significantly different when participants were reading source code compared to natural text, and we could detect the expected left-to-right and top-to-bottom reading directions for participants reading natural text snippets. Conclusion:The accuracy and precision levels were not sufficient for a word-by-word analysis of code reading but could be adequate for a broader, coarse-grained precision study. Additionally we identified two main issues compromising the collected data validity and contributed a fixation detection algorithm to approach one of these issues. With suitable solutions to the identified issues, remote eye-tracking studies with webcams on code reading could eventually be feasible.

Analisis Financial Distress dengan Menggunakan Metode Altman Z-Score pada PT. Cahaya Bintang Medan Tbk

This research aims to determine and analiyze the Altman Z-Score mothod in assessing the level of bankruptcy PT. Cahaya Medan Tbk for The 2018- 2021 period and to provide evidence that the altman Z-score method is effectively used in assessing the level of company bankruptcy with a relatively reliable level of precision and accuracy at PT.Cahaya Bintang Medan Tbk for the 2018-2021 period. The type of research used is quantitative descriptive analysis, namely by collecting, clarifying, analyzing and interpreting data obtained from the company so that it can provide a picture of the actual situatuin the calculation technique used in this reseatch is the Altman Z-Score model formula. Based on the results of calculations using the modified Altman Z-Score method from the 2018-2021 period, it shows that PT. Cahaya Bintang Medan Tbk is in the safe zone or safe because the average Z-Score value is above 2,60 or Z2,60

Versatile hybrid transparent triboelectric nanogenerator-solar cell device enables efficient energy harvesting and personal handwriting recognition

The continuous energy supply for wearable electronic devices, including health monitoring sensors and human-machine interface devices, poses a significant challenge to their development. Renewable energy sources, such as nanogenerators and solar cells, offer promising solutions to this challenge. In this study, we explore the potential of a versatile device based on a smart hybrid triboelectric nanogenerator (SH TENG) and photovoltaic (PV) cell for efficient energy harvesting and personal handwriting recognition. A transparent, self-cleaning, UV-protective, bidirectional, non-rigid, lightweight, ultra-durable, eco-friendly, and uniform composite of epoxy resin/ZnO/Ag nanowires-based sandwich-like TENG can produce a power density of 2.3 W m−2. Integrating SH TENG with PV led to improved energy harvesting and increased the charging voltage of the capacitor by up to 5 times. Moreover, this material is a multifunctional sensor capable of detecting temperature, humidity, pressure, handwriting content, and the writer. These features make it an intriguing candidate for e-skin applications. By employing a generalized deep neural network (DNN) model, our device can accurately recognize handwritten letters, numbers, and personal identification with a high level of precision, achieving an accuracy of 97 %. This device can function as an intelligent touch screen with dual-purpose energy production and detection, paving the way for developing highly efficient and sustainable wearable electronic devices.

Solar Jet Hunter: a citizen science initiative to identify and characterize coronal jets at 304 AA

Solar coronal jets seen in extreme ultraviolet (EUV) are ubiquitous on the Sun, and they have been found in and at the edges of active regions, at the boundaries of coronal holes, and in the quiet Sun. Jets have various shapes, sizes, brightness, velocities, and durations in time, which complicates their detection by automated algorithms. So far, solar jets reported in the Heliophysics Event Knowledgebase (HEK) have been mostly reported by humans looking for them in the data, with different levels of precision regarding their timing and positions. We created a catalog of solar jets observed in EUV at 304 \ containing precise and consistent information on the jet timing, position, and extent. We designed a citizen science project, Solar Jet Hunter, on the Zooniverse platform, to analyze EUV observations at 304 \ from the Solar Dynamic Observatory/Atmospheric Imaging Assembly (SDO/AIA). We created movie strips for regions of the Sun in which jets have been reported in HEK and ask the volunteers to 1) confirm the presence of at least one jet in the data and 2) report the timing, position, and extent of the jet. We report here the design of the project and the results obtained after the analysis of data from 2011 to 2016. We note that 365 "coronal jet" events from HEK served as input for the citizen science project, equivalent to more than 120,000 images distributed into 9,689 "movie strips." Classification by the citizen scientists resulted in 883 individual jets being identified. We demonstrate how citizen science can enhance the analysis of solar data with the example of Solar Jet Hunter. The catalog of jets thusly created is publicly available and will enable statistical studies of jets and related phenomena. This catalog will also be used as a training set for machines to learn to recognize jets in further datasets.

Longitudinal soluble marker profiles reveal strong association between cytokine storms resulting from macrophage activation and disease severity in COVID-19 disease

SARS-CoV2 infection results in a range of disease severities, but the underlying differential pathogenesis is still not completely understood. At presentation it remains difficult to estimate and predict severity, in particular, identify individuals at greatest risk of progression towards the most severe disease-states. Here we used advanced models with circulating serum analytes as variables in combination with daily assessment of disease severity using the SCODA-score, not only at single time points but also during the course of disease, to correlate analyte levels and disease severity. We identified a remarkably strong pro-inflammatory cytokine/chemokine profile with high levels for sCD163, CCL20, HGF, CHintinase3like1 and Pentraxin3 in serum which correlated with COVID-19 disease severity and overall outcome. Although precise analyte levels differed, resulting biomarker profiles were highly similar at early and late disease stages, and even during convalescence similar biomarkers were elevated and further included CXCL3, CXCL6 and Osteopontin. Taken together, strong pro-inflammatory marker profiles were identified in patients with COVID-19 disease which correlated with overall outcome and disease severity.

High-Precision and Real-Time Measurement of Water Isotope Ratios Based on a Mid-Infrared Optical Sensor.

A compact spectrometer based on a mid-infrared optical sensor has been developed for high-precision and real-time measurement of water isotope ratios. The instrument uses laser absorption spectroscopy and applies the weighted Kalman filtering method to determine water isotope ratios with high precision and fast time response. The precision of the measurements is 0.41‰ for δ18O and 0.29‰ for δ17O with a 1 s time. This is much faster than the standard running average technique, which takes over 90 s to achieve the same level of precision. The successful development of this compact mid-infrared optical sensor opens up new possibilities for its future applications in atmospheric and breath gas research.

Structural Evolution of the Pharmaceutical Peptide Octreotide upon Controlled Relative Humidity and Temperature Variation

Octreotide is the first synthetic peptide hormone, consisting of eight amino acids, that mimics the activity of somatostatin, a natural hormone in the body. During the past decades, advanced instrumentation and crystallographic software have established X-Ray Powder Diffraction (XRPD) as a valuable tool for extracting structural information from biological macromolecules. The latter was demonstrated by the successful structural determination of octreotide at a remarkably high d-spacing resolution (1.87 Å) (PDB code: 6vc1). This study focuses on the response of octreotide to different humidity levels and temperatures, with a particular focus on the stability of the polycrystalline sample. XRPD measurements were accomplished employing an Anton Paar MHC-trans humidity-temperature chamber installed within a laboratory X’Pert Pro diffractometer (Malvern Panalytical). The chamber is employed to control and maintain precise humidity and temperature levels of samples during XRPD data collection. Pawley analysis of the collected data sets revealed that the octreotide polycrystalline sample is remarkably stable, and no structural transitions were observed. The compound retains its orthorhombic symmetry (space group: P212121, a = 18.57744(4) Å, b = 30.17338(6) Å, c = 39.70590(9) Å, d ~ 2.35 Å). However, a characteristic structural evolution in terms of lattice parameters and volume of the unit cell is reported mainly upon controlled relative humidity variation. In addition, an improvement in the signal-to-noise ratio in the XRPD data under a cycle of dehydration/rehydration is reported. These results underline the importance of considering the impact of environmental factors, such as humidity and temperature, in the context of structure-based drug design, thereby contributing to the development of more effective and stable pharmaceutical products.

Association of Dietary Retinol Intake and Serum Neurofilament Light Chain Levels: Results from NHANES 2013-2014.

There is increasing evidence suggesting that serum neurofilament light chain (sNfL) levels can be used as biomarkers for axonal injury. Retinol is recognized for its significant involvement in nervous system function, but the precise connection between dietary retinol and sNfL levels remains uncertain. Our objective was to investigate the relationship between dietary retinol intake and sNfL, and to find an optimal retinol intake level for neurological health. In the National Health and Nutrition Examination Survey (NHANES), conducted from 2013 to 2014, a cohort of 1684 participants who met the criteria were selected for the study. sNfL levels were measured from stored serum samples using a novel high-throughput immunoassay platform from Siemens Healthineers. Assessment of dietary retinol intake was performed by a uniformly trained interviewer through a 24 h dietary recall method. A generalized linear model was evaluated to assess the correlation between dietary retinol intake and sNfL concentrations. Furthermore, the nonlinear association between the two is further explored using restricted cubic spline (RCS) analysis. Upon adjusting for potential confounders, a 10% increase in dietary retinol intake was associated with a 3.47% increase in sNfL levels (95% CI: 0.54%, 6.49%) across all participants. This relationship was more pronounced in specific subgroups, including those under 60 years of age, non-obese, impaired estimated glomerular filtration rate (eGFR), and non-diabetic. In subgroup analysis, among those younger than 60 years of age (percent change: 3.80%; 95% CI: 0.43%, 7.28%), changes were found in non-obese participants (percent change: 6.28%; 95% CI: 2.66%, 10.02%), those with impaired eGFR (percent change: 6.90%; 95% CI: 1.44%, 12.65%), and non-diabetic patients (percentage change: 4.17%; 95% CI: 1.08%, 7.36%). RCS analysis showed a linear relationship between dietary retinol intake and sNfL levels. Furthermore, the positive correlation between the two was more significant after the inflection point, according to piecewise linear analysis. This current investigation uncovered a J-shaped relationship between dietary retinol and sNfL levels, suggesting that axonal damage can occur when dietary retinol intake increases more than a specific threshold. These findings need to be further confirmed in future prospective studies to determine the precise intake level that may trigger axonal injury.

Evaluating Radiation Exposure to Oral Tissues in C-Arm Fluoroscopy A Dose Analysis

This study investigates the radiation dose to oral mucosal tissues during C-arm fluoroscopy imaging using an Alderson Rando phantom and thermoluminescent dosimeters (TLD-100) for precise measurements. The aim is to assess the potential risks for patients and healthcare personnel exposed to ionising radiation during these procedures. The Alderson Rando phantom, a human-equivalent model, was utilized to simulate radiation exposure in a controlled environment. TLD-100 dosimeters were strategically positioned in the 6th section of the phantom and exposed to radiation at intervals of 0.5, 1, 2, 4, and 8 minutes. The experiments were carried out at Hisar Hospital Intercontinental and the dosimeter readings were then evaluated at Çekmece Nuclear Research Centre. The study demonstrated that the mean radiation doses affecting the internal tissue of the oral mucosa were 0.912 mSv (0.5 minutes), 1.604 mSv (1 minute), 2.719 mSv (2 minutes), 6.763 mSv (4 minutes), and 13.811 mSv (8 minutes). The mean radiation doses affecting the lip skin tissue were 1.423 mSv (0.5 minutes), 2.435 mSv (1 minute), 5.2 mSv (2 minutes), 10.195 mSv (4 minutes), and 17.404 mSv (8 minutes). Results indicate a direct relationship between radiation dose and exposure time, with increasing doses observed at longer exposure times. This research aims to improve patient safety during C-arm scope imaging procedures by determining precise radiation dosage levels for oral mucosal tissues and addressing the lack of published reference values in the literature.

Filter Design for Estimation of Stellar Metallicity: Insights from Experiments with Gaia XP Spectra

We search for an optimal filter design for the estimation of stellar metallicity, based on synthetic photometry from Gaia XP spectra convolved with a series of filter-transmission curves defined by different central wavelengths and bandwidths. Unlike previous designs based solely on maximizing metallicity sensitivity, we find that the optimal solution provides a balance between the sensitivity and uncertainty of the spectra. With this optimal filter design, the best precision of metallicity estimates for relatively bright (G ∼ 11.5) stars is excellent, σ [Fe/H] = 0.034 dex for FGK dwarf stars, superior to that obtained utilizing custom sensitivity-optimized filters (e.g., SkyMapper v). By selecting hundreds of high-probability member stars of the open cluster M67, our analysis reveals that the intrinsic photometric-metallicity scatter of these cluster members is only 0.036 dex, consistent with this level of precision. Our results clearly demonstrate that the internal precision of photometric-metallicity estimates can be extremely high, even providing the opportunity to perform chemical tagging for very large numbers of field stars in the Milky Way. This experiment shows that it is crucial to take into account uncertainty alongside the sensitivity when designing filters for measuring the stellar metallicity and other parameters.

Functional performance of a vibrotactile sensory substitution device in people with profound vision loss.

This study has shown a vibrotactile sensory substitution device (SSD) prototype, VibroSight, has the potential to improve functional outcomes (i.e., obstacle avoidance, face detection) for people with profound vision loss, even with brief familiarization (<20 minutes). Mobility aids such as long canes are still the mainstay of support for most people with vision loss, but they do have limitations. Emerging technologies such as SSDs are gaining widespread interest in the low vision community. The aim of this project was to assess the efficacy of a prototype vibrotactile SSD for people with profound vision loss in the face detection and obstacle avoidance tasks. The VibroSight device was tested in a movement laboratory setting. The first task involved obstacle avoidance, in which participants were asked to walk through an obstacle course. The second was a face detection task, in which participants were asked to step toward the first face they detected. Exit interviews were also conducted to gather user experience data. Both people with low vision (n = 7) and orientation and mobility instructors (n = 4) completed the tasks. In obstacle avoidance task, participants were able to use the device to detect (p<0.001) and avoid (p<0.001) the obstacles within a significantly larger range, but were slower (p<0.001), when compared with without the device. In face detection task, participants demonstrated a great level of accuracy, precision, and sensitivity when using the device. Interviews revealed a positive user experience, although participants identified that they would require a lighter and compact design for real-world use. Overall, the results verified the functionality of vibrotactile SSD prototype. Further research is warranted to evaluate the user performance after an extended training program and to add new features, such as object recognition software algorithms, into the device.

Validation of the method for determining lincomycin levels and calculating lincomycin levels in broiler chicken plasma using high-performance liquid chromatography.

Antibiotic residues that come from food of animal origin, such as broiler chicken, have a variety of consequences on human health and increase the likelihood of antibiotic resistance. Lincomycin residue investigations in broiler chicken especially in plasma broiler chicken should be undertaken utilizing the validation method analysis. The purpose of this study is to determine the high-performance liquid chromatography (HPLC) as a validation method for calculating the residual concentration of lincomycin in broiler chicken blood plasma and compare it with the minimum Inhibitor Concentration (MIC) and Maximum Residue Limits (MRLs) standards for lincomycin. Thirty-five-day-old broiler chickens cobb 700 were weighed and randomly allocated to and separated into control (placebo) and six treatment groups of varying doses and duration. The treatment group's suggested dosage of lincomycin was 50, 100, or 150 mg/kg/day given to 18-day-old chicken, along with drinking water for a week (A group) and 2 weeks (P group). Lincomycin levels in blood plasma were validated using HPLC. The residual lincomycin concentrations 24 hours and 1 week after injection were compared to the lincomycin MIC and the Indonesian National Standard of MRL. The validation of linscomycin reveals a linear value in blood plasma with an R2 of 0.9983. Precision and accuracy levels indicate promising results for detecting lincomycin. The retention duration for 100 µg/ml lincomycin was 10.0-10.5 minutes. Lincomycin had LOD and LOQ values of 13.98 and 4.86 µg/ml, respectively. After 1 week of dosing at 50 and 100 mg/kg dosages, lincomycin residue detection was 0.00, which was below the MRL criterion of <0.1 ppm. The study found that the residual concentration of 150 mg/kg dosages for a week and 100/150 mg/kg doses for 2 weeks above the lincomycin MIC limits against Mycoplasma synoviae, Staphylococcus aureus, and Salmonella enteritidis. Lincomycin detection by HPLC in chicken blood plasma showed promising results in terms of linearity, accuracy, precision, specificity, and sensitivity. Lincomycin administration for 1 week at doses of 50 and 100 mg/kg resulted in the lowest residual concentration below the lincomycin MIC and MRL standards.

Smart Bricks Curing System using IoT

The existing curing method for bricks lacks in precision and efficiency, resulting in inferior strength and durability in the finished product. Traditional procedures may result in over- or under-curing, causing cracks and decreased structural integrity. Furthermore, manual monitoring and intervention are labor-intensive and prone to human mistake. A smart bricks curing system designed specifically for concrete bricks is critical for obtaining optimal strength and durability. This technology seeks to reduce cracks that threaten the longevity of concrete by maintaining precise moisture levels during the hydration process. The research’s central feature is the implementation of sensors that continuously monitor moisture and temperature levels within the bricks.

OncoGPT: Enhancing oncological decision-making with ASCO guideline–trained AI.

e13607 Background: General-purpose language models like ChatGPT, while proficient in a wide array of topics, often lack the specialized knowledge and precision required for specific fields such as oncology. The American Society of Clinical Oncology (ASCO) guidelines offer a comprehensive resource for oncology professionals, yet sifting through extensive documents for specific information can be daunting. To bridge this gap, we introduce OncoGPT, a specialized GPT model, tailored to provide precise and guideline-adherent oncological advice. Methods: We leveraged GPT-4's advanced language understanding capabilities as the foundation for OncoGPT. This customization involved an extensive training regimen using the complete text of the ASCO clinical guidelines. The training process was meticulously designed to ensure that OncoGPT not only assimilates the detailed information within these guidelines but also understands the context and intricacies of oncological care. Additionally, we created disease-specific versions of OncoGPT, each fine-tuned with guideline subsets pertinent to particular oncological conditions. Further, the training was augmented with specific prompts to foster kind, sincere, and respectful interactions, especially for patient-oriented responses. The model was designed to discern whether the user is a healthcare professional or a patient and adjust the complexity of its responses accordingly. For patients, additional emphasis was placed on delivering information in a kind, responsible, and empathetic manner. Results: OncoGPT's performance was rigorously evaluated for accuracy and reasoning against real-world clinical scenarios. The responses generated by the model were meticulously reviewed by an experienced oncologist to confirm adherence to ASCO guidelines and clinical relevance. This assessment revealed a high level of precision and contextual understanding in OncoGPT's outputs, demonstrating its potential as a valuable tool for oncology practitioners. Importantly, it showed a remarkable ability to tailor its communication style based on the user's background, providing simplified explanations for patients and more detailed responses for professionals. An example of a specific OncoGPT: Breast Cancer OncoGPT: https://chat.openai.com/g/g-VcuECT3jg-oncogpt-breast-cancer Conclusions: OncoGPT represents a significant advancement in the application of AI for medical decision-making. By integrating the depth of ASCO guidelines into a responsive and accurate AI model, OncoGPT offers oncology professionals a powerful tool for accessible, guideline-compliant advice. This development marks a crucial step towards integrating AI more profoundly into specialized medical fields, enhancing both the efficiency and accuracy of clinical decision-making.

Intelligent field monitoring system for cruciferous vegetable pests using yellow sticky trap images and an improved Cascade R-CNN

Cruciferous vegetables are important edible vegetable crops. However, they are susceptible to various pests during their growth process, which requires real-time and accurate monitoring of these pests for pest forecasting and scientific control. Hanging yellow sticky boards are a common way to monitor and trap those pests which are attracted to the yellow color. To achieve real-time, low-cost, intelligent monitoring of these vegetable pests on the boards, we established an intelligent monitoring system consisting of a smart camera, a web platform and a pest detection algorithm deployed on a server. After the operator sets the monitoring preset points and shooting time of the camera on the system platform, the camera in the field can automatically collect images of multiple yellow sticky boards at fixed places and times every day. The pests trapped on the yellow sticky boards in vegetable fields, Plutella xylostella, Phyllotreta striolata and flies, are very small and susceptible to deterioration and breakage, which increases the difficulty of model detection. To solve the problem of poor recognition due to the small size and breaking of the pest bodies, we propose an intelligent pest detection algorithm based on an improved Cascade R-CNN model for three important cruciferous crop pests. The algorithm uses an overlapping sliding window method, an improved Res2Net network as the backbone network, and a recursive feature pyramid network as the neck network. The results of field tests show that the algorithm achieves good detection results for the three target pests on the yellow sticky board images, with precision levels of 96.5, 92.2 and 75.0%, and recall levels of 96.6, 93.1 and 74.7%, respectively, and an F1 value of 0.880. Compared with other algorithms, our algorithm has a significant advantage in its ability to detect small target pests. To accurately obtain the data for the newly added pests each day, a two-stage pest matching algorithm was proposed. The algorithm performed well and achieved results that were highly consistent with manual counting, with a mean error of only 2.2%. This intelligent monitoring system realizes precision, good visualization, and intelligent vegetable pest monitoring, which is of great significance as it provides an effective pest prevention and control option for farmers.

Thermoluminescence characterization of flooring tiles from Malaysia for potential use in retrospective dosimetry

In the event of natural disasters or technical malfunctions at nuclear sites, the surrounding media, including individuals, may be subject to unforeseen radiation exposure. Thus, it is not possible to determine the precise level of radiation exposure that each person has received in this scenario. To handle such a problem, the use of retrospective dosimetry can offer an accurate evaluation of the radiation dose acquired as a result of such incidents. This information enables the development of suitable remedial actions. Normally, in the region that has been impacted, several artifacts can serve as natural dosimeters. The study involved the utilization of locally available seven different brands of flooring tiles in Malaysia for the possibility of being used in retrospective dosimetry through exposures to 60Co gamma-rays within a range of 10–200 Gy. To understand the luminescence features of this material, a convenient thermoluminescence (TL) technique has been employed. The dosimetric features of the samples were investigated, including their effective atomic numbers (Zeff), reproducibility, glow curve, dose response, sensitivity, linearity index, energy dependency and fading, which is representative of the usual TL method. Additionally, by analyzing the glow curves of the irradiated samples together with the peak shape method and the initial rise methods, several kinetic parameters, including the kinetic orders (b), activation energy (E) or trap depth, frequency factor (s) or escape probability, and trap lifetime (τ) were calculated. Different kinds of tiles exhibit distinct scenarios in terms of kinetic characteristics. T1 sample exhibits the highest degree of sensitivity and a highly linear dose response among the tile samples that were evaluated. Also, T1, T3, and T5 samples show minimal loss of TL intensity (∼38–39%) one year after irradiation, making them ideal for use as a retrospective dosimeter.

Digital Evaluation of Trueness and Precision of Modern Impression Materials in Implant- Retained Mandibular Overdentures.

The purpose of this in vitro study was to evaluate the dimensional accuracy, trueness, and precision of vinyl siloxane ether (VSXE) and polyvinylsiloxane (PVS) impression materials using different impression techniques. A three-dimensional (3D) printed mandibular model with implants and metal rods served as the reference model. Impressions were taken in custom trays, resulting in four groups: PVS-closed-tray, VSXE-closed-tray, PVS-open-tray, and VSXE-open-tray. The reference model and impressions were scanned and analyzed using 3D analysis software to assess the trueness and precision within each group. There was significant difference in trueness between the groups, with PVS closed tray showing a higher deviation than VSXE-closed-tray and PVS-open-tray. VSXE-open-tray had the lowest deviation, which was statistically significant. In terms of precision, PVS-closed-tray showed the highest deviation, while no significant differences were found among the other groups. VSXE impression material with an open tray technique consistently demonstrated the highest levels of accuracy and precision. Conversely, PVS impression material with a closed tray technique yielded less favorable results. Better understanding of trueness and precision of new impression materials with new impression techniques will increase their clinical effectiveness.