-
Optics Express Apr 2024In order to improve the safety of spacecraft, the research on artificial neural network and digital twin technology based on, to our best knowledge, a novel fiber Bragg...
In order to improve the safety of spacecraft, the research on artificial neural network and digital twin technology based on, to our best knowledge, a novel fiber Bragg grating (FBG) sensor array is proposed for intelligent sensing monitoring of spacecraft on-orbit collisions. Femtosecond FBG arrays were fabricated on the novel oxide-doped fiber by point-by-point writing technique. The femtosecond FBG is analyzed using the time-dependent perturbation theory of quantum mechanics. The FBG array can achieve high-temperature measurement of 1100 °C and large strain measurement of 15000 µε. The sensing arrays were deployed on the surface of the spacecraft. Constructed the multi-layer perceptron neural network structure and convolutional neural network structure. 1200 samples were trained. Conducted model accuracy testing. The accuracy rate is above 98%, and accuracy verification has been implemented. The digital twin model was designed based on various data such as strain and temperature of the spacecraft structure under impact monitored by FBG sensors. A precise mapping has been formed between the physical entities of spacecraft and digital twins. Empower spacecraft with functions such as self-monitoring, judgment, and response. To ensure the stable and safe operation of spacecraft.
PubMed: 38859286
DOI: 10.1364/OE.515568 -
Optics Express May 2024Conventional radar jamming and deception systems typically necessitate the custom design of complex circuits and algorithms to transmit an additional radio signal toward...
Conventional radar jamming and deception systems typically necessitate the custom design of complex circuits and algorithms to transmit an additional radio signal toward a detector. Consequently, they are often cumbersome, energy-intensive, and difficult to operate in broadband electromagnetic environment. With the ongoing trend of miniaturization of various devices and the improvement of radar system performance, traditional techniques no longer meet the requirements for broadband, seamless integration, and energy efficiency. Time-varying metasurfaces, capable of manipulating electromagnetic parameters in both temporal and spatial domains, have thus inspired many contemporary research studies to revisit established fields. In this paper, we introduce a time-varying metasurface driven radar jamming and deception system (TVM-RJD), which can perfectly overcome the aforementioned intrinsic challenges. Leveraging a programmable bias voltage, the TVM-RJD can alter the spectrum distribution of incident waves, thereby deceiving radar into making erroneous judgments about the target's location. Experimental outcomes affirm that the accuracy deviation of the TVM-RJD system is less than 0.368 meters, while achieving a remarkable frequency conversion efficiency of up to 96.67%. The TVM-RJD heralds the expansion into a wider application of electromagnetic spatiotemporal manipulation, paving the way for advancements in electromagnetic illusion, radar invisibility, etc.
PubMed: 38858959
DOI: 10.1364/OE.521602 -
Proceedings of the National Academy of... Jun 2024The perception of sensory attributes is often quantified through measurements of sensitivity (the ability to detect small stimulus changes), as well as through direct...
The perception of sensory attributes is often quantified through measurements of sensitivity (the ability to detect small stimulus changes), as well as through direct judgments of appearance or intensity. Despite their ubiquity, the relationship between these two measurements remains controversial and unresolved. Here, we propose a framework in which they arise from different aspects of a common representation. Specifically, we assume that judgments of stimulus intensity (e.g., as measured through rating scales) reflect the mean value of an internal representation, and sensitivity reflects a combination of mean value and noise properties, as quantified by the statistical measure of Fisher information. Unique identification of these internal representation properties can be achieved by combining measurements of sensitivity and judgments of intensity. As a central example, we show that Weber's law of perceptual sensitivity can coexist with Stevens' power-law scaling of intensity ratings (for all exponents), when the noise amplitude increases in proportion to the representational mean. We then extend this result beyond the Weber's law range by incorporating a more general and physiology-inspired form of noise and show that the combination of noise properties and sensitivity measurements accurately predicts intensity ratings across a variety of sensory modalities and attributes. Our framework unifies two primary perceptual measurements-thresholds for sensitivity and rating scales for intensity-and provides a neural interpretation for the underlying representation.
Topics: Humans; Perception; Sensory Thresholds; Sensation; Judgment
PubMed: 38857385
DOI: 10.1073/pnas.2312293121 -
PloS One 2024This body image study tests the viability of transferring a complex psychophysical paradigm from a controlled in-person laboratory task to an online environment. 172...
This body image study tests the viability of transferring a complex psychophysical paradigm from a controlled in-person laboratory task to an online environment. 172 female participants made online judgements about their own body size when viewing images of computer-generated female bodies presented in either in front-view or at 45-degrees in a method of adjustment (MOA) paradigm. The results of these judgements were then compared to the results of two laboratory-based studies (with 96 and 40 female participants respectively) to establish three key findings. Firstly, the results show that the accuracy of online and in-lab estimates of body size are comparable, secondly that the same patterns of visual biases in judgements are shown both in-lab and online, and thirdly online data shows the same view-orientation advantage in accuracy in body size judgements as the laboratory studies. Thus, this study suggests that that online sampling potentially represents a rapid and accurate way of collecting reliable complex behavioural and perceptual data from a more diverse range of participants than is normally sampled in laboratory-based studies. It also offers the potential for designing stratified sampling strategies to construct a truly representative sample of a target population.
Topics: Humans; Female; Body Image; Adult; Psychophysics; Young Adult; Adolescent; Body Size; Visual Perception; Judgment; Internet
PubMed: 38857270
DOI: 10.1371/journal.pone.0302747 -
Cancer Management and Research 2024In situations where pathological acquisition is difficult, there is a lack of consensus on distinguishing between adenocarcinoma and squamous cell carcinoma from imaging...
PURPOSE
In situations where pathological acquisition is difficult, there is a lack of consensus on distinguishing between adenocarcinoma and squamous cell carcinoma from imaging images, and each doctor can only make judgments based on their own experience. This study aims to extract imaging features of chest CT, extract sensitive factors through logistic univariate and multivariate analysis, and model to distinguish between lung squamous cell carcinoma and lung adenocarcinoma.
METHODS
We downloaded chest CT scans with clear diagnosis of adenocarcinoma and squamous cell carcinoma from The Cancer Imaging Archive (TCIA), extracted 19 imaging features by a radiologist and a thoracic surgeon, including location, spicule, lobulation, cavity, vacuolar sign, necrosis, pleural traction sign, vascular bundle sign, air bronchogram sign, calcification, enhancement degree, distance from pulmonary hilum, atelectasis, pulmonary hilum and bronchial lymph nodes, mediastinal lymph nodes, interlobular septal thickening, pulmonary metastasis, adjacent structures invasion, pleural effusion. Firstly, we apply the glm function of R language to perform logistic univariate analysis on all variables to select variables with P < 0.1. Then, perform logistic multivariate analysis on the selected variables to obtain a predictive model. Next, use the roc function in R language to calculate the AUC value and draw the ROC curve, use the val.prob function in R language to draw the Calibrat curve, and use the rmda package in R language to draw the DCA curve and clinical impact curve. At the same time, 45 patients diagnosed with lung squamous cell carcinoma and lung adenocarcinoma through surgery or biopsy in the Radiotherapy Department and Thoracic Surgery Department of our hospital from 2023 to 2024 were included in the validation group. The chest CT features were jointly determined and recorded by the two doctors mentioned above and included in the validation group. The included image feature data are complete and does not require preprocessing, so directly entering statistical calculations. Perform ROC curves, calibration curves, DCA, and clinical impact curves in the validation group to further validate the predictive model. If the predictive model performs well in the validation group, further draw a nomogram to demonstrate.
RESULTS
This study extracted 19 imaging features from the chest CT scans of 75 patients downloaded from TCIA and finally selected 18 complete data for analysis. First, univariate analysis and multivariate analysis were performed, and a total of 5 variables were obtained: spicule, necrosis, air bronchogram Sign, atelectasis, pulmonary hilum and bronchial lymph nodes. After conducting modeling analysis with AUC = 0.887, a validation group was established using clinical cases from our hospital, Draw ROC curve with AUC = 0.865 in the validation group, evaluate the accuracy of the model through Calibrate calibration curve, evaluate the reliability of the model in clinical practice through DCA curve, and further evaluate the practicality of the model in clinical practice through clinical impact curve.
CONCLUSION
It is possible to extract influential features from ordinary chest CT scans to determine lung adenocarcinoma and squamous cell carcinoma. The model we have set up performs well in terms of discrimination, accuracy, reliability, and practicality.
PubMed: 38855330
DOI: 10.2147/CMAR.S462951 -
Cureus May 2024This comprehensive literature review explores the transformative impact of artificial intelligence (AI) predictive analytics on healthcare, particularly in improving... (Review)
Review
This comprehensive literature review explores the transformative impact of artificial intelligence (AI) predictive analytics on healthcare, particularly in improving patient outcomes regarding disease progression, treatment response, and recovery rates. AI, encompassing capabilities such as learning, problem-solving, and decision-making, is leveraged to predict disease progression, optimize treatment plans, and enhance recovery rates through the analysis of vast datasets, including electronic health records (EHRs), imaging, and genetic data. The utilization of machine learning (ML) and deep learning (DL) techniques in predictive analytics enables personalized medicine by facilitating the early detection of conditions, precision in drug discovery, and the tailoring of treatment to individual patient profiles. Ethical considerations, including data privacy, bias, and accountability, emerge as vital in the responsible implementation of AI in healthcare. The findings underscore the potential of AI predictive analytics in revolutionizing clinical decision-making and healthcare delivery, emphasizing the necessity of ethical guidelines and continuous model validation to ensure its safe and effective use in augmenting human judgment in medical practice.
PubMed: 38854327
DOI: 10.7759/cureus.59954 -
Cureus May 2024The pharmacovigilance program of India (PvPI), after its inception, has been reliably acquiring force in bringing issues to light among the masses, healthcare... (Review)
Review
The pharmacovigilance program of India (PvPI), after its inception, has been reliably acquiring force in bringing issues to light among the masses, healthcare professionals, the pharma industry, and clinical staff at hospitals. Adverse drug reactions are unintended events that occur after exposure to a drug, biological product, or medical device, and they may result in morbidity and mortality. It is critical to monitor the safety of drugs during the post-marketing phase to find long-term and rare ADRs, as well as ADRs in special populations and patients with co-morbidities that are not usually included during clinical trials. The definitive objective of pharmacovigilance is to collate data and analyze it. Assessing the causality between ADRs and drugs is necessary to decrease the occurrence of ADRs and to reduce the risk of drug-related ADRs. ADRs may lead to increased morbidity, increased hospital stays, and increased cost of treatment, resulting in compromised patient safety. Causality assessment is the evaluation of the likelihood that a particular treatment is the cause of an observed adverse event and establishing a causal association between a drug and a drug reaction is necessary to prevent further recurrences. Numerous methods available for establishing a causal association between the drug and adverse events have been broadly classified into clinical judgment or global introspection, algorithms, and probabilistic methods. These include the Swedish method, World Health Organization-Uppsala Monitoring Centre (WHO-UMC) scale, Naranjo's algorithm, Kramer algorithm, Jones algorithm, Karch algorithm, Bégaud algorithm, Adverse Drug Reactions Advisory Committee guidelines, Bayesian Adverse Reaction Diagnostic Instrument, and so on. Despite various methods available, none of the causality assessment tools have been universally accepted as the gold standard. Naranjo's algorithm and WHO-UMC scales are, however, the most commonly used. Similarly, for preventability and severity assessment of ADRs, the Schumock and Thornton scale and Hartwig and Siegel's scale are most commonly used. Hence, we reviewed different tools and methods available to assess the causality, preventability, and severity of ADRs.
PubMed: 38854273
DOI: 10.7759/cureus.59975 -
Scientific Reports Jun 2024When a single choice impacts on life outcomes, faculties to make ethical judgments come into play. Here we studied decisions in a real-life setting involving...
When a single choice impacts on life outcomes, faculties to make ethical judgments come into play. Here we studied decisions in a real-life setting involving life-and-death outcomes that affect others and the decision-maker as well. We chose a genuine situation where prior training and expertise play a role: firefighting in life-threatening situations. By studying the neural correlates of dilemmas involving life-saving decisions, using realistic firefighting situations, allowed us to go beyond previously used hypothetical dilemmas, while addressing the role of expertise and the use of coping strategies (n = 47). We asked the question whether the neural underpinnings of deontologically based decisions are affected by expertise. These realistic life-saving dilemmas activate the same core reward and affective processing network, in particular the ventromedial prefrontal cortex, nucleus accumbens and amygdala, irrespective of prior expertise, thereby supporting general domain theories of ethical decision-making. We found that brain activity in the hippocampus and insula parametrically increased as the risk increased. Connectivity analysis showed a larger directed influence of the insula on circuits related to action selection in non-experts, which were slower than experts in non rescuing decisions. Relative neural activity related to the decision to rescue or not, in the caudate nucleus, insula and anterior cingulate cortex was negatively associated with coping strategies, in experts (firefighters) suggesting practice-based learning. This shows an association between activity and expert-related usage of coping strategies. Expertise enables salience network activation as a function of behavioural coping dimensions, with a distinct connectivity profile when facing life-rescuing dilemmas.
Topics: Humans; Firefighters; Decision Making; Male; Adult; Female; Magnetic Resonance Imaging; Brain; Adaptation, Psychological; Brain Mapping; Prefrontal Cortex
PubMed: 38851794
DOI: 10.1038/s41598-024-63469-y -
Physiology & Behavior Jun 2024Muscle testing is an integral component in assessing musculoskeletal function and tailoring rehabilitation efforts. This study aimed i. to identify an objective... (Review)
Review
Muscle testing is an integral component in assessing musculoskeletal function and tailoring rehabilitation efforts. This study aimed i. to identify an objective evaluation system sensitive to analyze changes in different muscular conditions in different neuromuscular tests across a spectrum of professional experience levels; and ii. to analyze differences in objective parameters and clinical judgment between participants of different levels of expertise in different muscular conditions in different neuromuscular tests. Participants included 60 subjects with Level I to III expertise who performed blinded neuromuscular tests on the middle deltoid and rectus femoris muscles of 40 volunteer subjects. The methodology centered on standardizing test protocols to minimize variability, employing EMG to quantify muscle activity, thermography to capture thermographic muscular response, and digital dynamometry to measure muscular resistance. The findings revealed that while traditional methods like thermography and electromyography provide valuable insights, digital dynamometry stands out for its sensitivity in detecting muscle condition changes in neuromuscular test. Moreover, the data underscored the pivotal role of advanced training and expertise in enhancing the precision and accuracy of neuromuscular diagnostics, since there were significant differences in objective parameters and clinical judgment between participants of different levels of expertise in the different muscular conditions in Middle deltoid and Rectus femoris neuromuscular tests analyzed, presenting higher expertise participant clinical judgment like objective validated instrument.
PubMed: 38851442
DOI: 10.1016/j.physbeh.2024.114602 -
BMC Rheumatology Jun 2024In recent times, there has been acknowledgment of the prevalence of frailty and pre-frailty among individuals with rheumatoid arthritis (RA). Comprehensive Rheumatologic...
BACKGROUND
In recent times, there has been acknowledgment of the prevalence of frailty and pre-frailty among individuals with rheumatoid arthritis (RA). Comprehensive Rheumatologic Assessment of Frailty (CRAF) stands out as a dependable tool grounded in synthesis and clinical judgment. Despite this, a validated Vietnamese rendition of the CRAF is currently unavailable. This study seeks to assess the reliability and validity of the CRAF in a patient with RA in Vietnam.
METHODS
A cross-sectional investigation was carried out with 402 patients diagnosed with rheumatoid arthritis, encompassing both inpatients and outpatients at the Centre for Rheumatology at Bach Mai Hospital in Hanoi, Vietnam. CRAF was employed to gauge the extent of frailty. To establish convergent validity, the scores from the CRAF were correlated with those from the Fried phenotype. Discriminant validity was ascertained through the utilization of receiver operating characteristic (ROC) curve analysis. Additionally, a multivariate logistic regression model was applied to evaluate the individual determinants' relative impact on the CRAF.
RESULTS
In testing for convergent validity, a significant correlation was found between CRAF and Fried phenotype (p < 0.001). The discriminatory power of CRAF was higher than those of the Fried phenotype (difference between areas under the ROC curves = 0.947 (95% CI: 0.927-0.967). Variables associated with frailty at the multivariate analysis were comorbitidy, medication intake, BMI, DAS28-CRP, and age (all at p < 0.01).
CONCLUSION
CRAF exhibited strong validity and accurate discrimination. Incorporating frailty assessment into regular rheumatological practices could signify a significant advancement in the care of rheumatoid arthritis.
PubMed: 38849947
DOI: 10.1186/s41927-024-00394-7