Similarity Threshold Research Articles

Camouflage Target Recognition Based on Dimension Reduction Analysis of Hyperspectral Image Regions

Hyperspectral reconnaissance technology can realize three-dimensional reconnaissance by using target space and spectral information, which effectively improves the efficiency of battlefield reconnaissance. However, in order to obscure what is true and what is false to confuse the enemy, camouflage technology is also developing. Hiding the target in the background environment and setting false targets have become common camouflage procedures on the battlefield. The camouflaged target has very similar spatial and spectral characteristics to the real target, so the method of identifying the camouflaged target according to the similarity threshold of the original spectral data is no longer reliable. In order to solve the problem of high spectral similarity and low discrimination between a camouflaged target and a real target in a hyperspectral image, a joint processing method of spatial spectrum information is adopted in this paper. Firstly, the hyperspectral image is preprocessed, and then the target area to be measured is determined. Finally, the dimensions of the determined sensitive small area are reduced. Experiments show that this processing method can effectively reduce the spectral similarity of true and false targets, increase the spectral difference of true and false targets and improve the ability to identify true and false targets based on hyperspectral images.

Real-Ear-to-Coupler Difference: Physical and Perceptual Differences.

The real-ear-to-coupler difference (RECD) is a recommended measure for accurate hearing aid fittings, especially for pediatric populations. However, for adults, many clinicians question whether it is necessary. Hearing aids were fit on two groups of 85 older adults seen at a Veterans Administration audiology clinic. One group was fit using RECD measurements, whereas the second group was fit with population-based average RECD values. The two groups had similar pure-tone hearing thresholds. Like previous studies, there was little difference between the measured RECD for the right and left ears among the participants. Although the majority of the measured RECDs were within 1 SD of the mean, approximately 20% of those measured were outside of the normal range. It also was found that all participants produced lower (improved) Hearing Handicap Inventory for Elderly-Screening (HHIE-S) scores from pre- to postfitting, thus suggesting a reduction in self-perceived hearing handicap. Despite having similar prefitting HHIE-S scores, those participants who had their hearing aids fit using measured RECD values had lower postfitting scores than the group that was fit with average RECD values. Furthermore, there was a significant difference between the groups on several questions of the International Outcome Inventory-Hearing Aids, suggesting that there was higher satisfaction with the fittings based on the custom RECD rather than the fittings based on the average RECD. This study demonstrated that, in addition to performing verification using real-ear measurements, accurate conversion of dB HL to dB SPL using personalized RECD likely improved hearing aid satisfaction.

Different item characteristics of a mild cognitive impairment screening tool in the community-based Yilan Study: application of the item response theory.

This study aimed to use item response theory (IRT) to explore the item-by-item characteristics of a mild cognitive impairment (MCI) screening tool using community-based data. The Yilan Study is a community-based study that has been conducted since 2012. Until March 2020, 2230 older adults were interviewed according to the household registration data. IRT was applied to determine the item-by-item distinctive characteristics of the Eight-item Interview to Differentiate Aging and Dementia (AD8). The MCI characteristics in the AD8 items have varying degrees of item response threshold. In all circumstances, item AD8-8, which is related to self-rated memory ability, had a low item response threshold. AD8-5 and AD8-7, which are related to the comparisons of time-oriented functional status, had slightly lower thresholds, especially for those aged 65-79 years or without activity limitations. Conversely, AD8-1, AD8-2, AD8-3, AD8-4, and AD8-6 had similar item response thresholds and discriminative power; these items have more detailed functional descriptions or examples for illustration. Concise and understandable elements are often expected in community-based screening tools. For community-based health screening and population empowerment in the early detection of MCI, assessment tool items with detailed functional descriptions and examples for illustration have similar validities in most of the population. Items related to self-rated memory ability might be less valid. More examples may be needed for items constructed for comparing time-oriented functional status, especially in extremely old adults and individuals with activity limitations.

Reproductive and developmental toxicity of perfluorooctane sulfonate (PFOS) in the white-footed mouse (Peromyscus leucopus)

Concerns about per- and polyfluoroalkyl substances (PFAS) stem from their ubiquitous presence in the environment, bioaccumulation, resistance to degradation, and toxicity. Previously, toxicity data relevant to ecological risk assessment has largely been aquatic, terrestrial invertebrates, or avian in origin. In this study, repeated oral exposures of perfluorooctane sulfonate (PFOS) were administered to white-footed mice (Peromyscus leucopus) to evaluate effects on reproduction and development. Prenatal exposure to high doses of PFOS caused neonatal mortality, though growth and development were unaffected by low doses. Additionally, parental (P) generation animals exhibited increased liver:body weight, increased hepatocyte cytoplasmic vacuolization, and decreased serum thyroxine (T4) levels. Total litter loss was selected as the protective critical effect in this study resulting in a benchmark dose low (BMDL) of 0.12 mg/kg-d PFOS. Importantly, PFOS exposure has been linked to reduced adult recruitment in myriad species and at similar thresholds to this study. Similarities in critical/toxicologic effects across taxa may add confidence in risk assessments at sites with multiple taxa or environments.

Reliability-based multi-attribute large group decision making under probabilistic linguistic environment

This study proposes a more rational and effective multi-attribute large group decision making (MALGDM) method with probabilistic linguistic term set (PLTS) from reliability perspective. A reliability measure method is first proposed to compute the reliability degree of the PLTS, and then a normalization method is presented to normalize the ignorant PLTSs with respect to maximizing their reliability degrees. An efficient clustering method combining the opinion similarity of experts and the reliability degrees of the clusters formed is introduced. Moreover, an objective method of determining the similarity and reliability thresholds is presented. After classifying the large-scale experts, the consensus levels of clusters and the global consensus level are measured and the cluster that need to adjust information is identified based on its consensus level and reliability degree. Then, an optimization model to maximize the global consensus level and the global reliability degree is then built to obtain the evaluation values for improving the consensus levels and reliability degrees. The deviation between the expectation values of the evaluation values before and after adjustment is constrained by the parameter provided by the experts within the cluster that need adjustment. Finally, an application example of the selection of the hotel for isolating the entry personnel during the Covid-19 pandemic and some comparative analyses are provided to validate the proposed method.

Clustered federated learning with weighted model aggregation for imbalanced data

As a promising edge learning framework in future 6G networks, federated learning (FL) faces a number of technical challenges due to the heterogeneous network environment and diversified user behaviors. Data imbalance is one of these challenges that can significantly degrade the learning efficiency. To deal with data imbalance issue, this work proposes a new learning framework, called clustered federated learning with weighted model aggregation (weighted CFL). Compared with traditional FL, our weighted CFL adaptively clusters the participating edge devices based on the cosine similarity of their local gradients at each training iteration, and then performs weighted per-cluster model aggregation. Therein, the similarity threshold for clustering is adaptive over iterations in response to the time-varying divergence of local gradients. Moreover, the weights for per-cluster model aggregation are adjusted according to the data balance feature so as to speed up the convergence rate. Experimental results show that the proposed weighted CFL achieves a faster model convergence rate and greater learning accuracy than benchmark methods under the imbalanced data scenario.

Ownership structure of oil revenues: Political institutions and financial markets in oil-producing countries

This study examines the impact of the ownership structure of oil revenues on financial markets and institutions, and the intermediating role of political institutions. Using the fixed-effects model and GMM for robustness, we analyse data from 82 oil-producing countries. We find several key results. Firstly, government ownership of oil revenues undermines the efficiency of financial institutions when the quality of political institutions is weak, but enhances their efficiency when political institutions are strong. Secondly, the impact of private ownership of oil revenues is negative on the depth of and access to financial institutions when the quality of political institutions is weak, but positive when political institutions are strong. We observe similar threshold effects for the depth of and access to financial markets in the subsample of developing countries. We conclude that oil-producing countries need solid political institutions to benefit from oil wealth and to boost financial development.

Evolutionary multiobjective overlapping community detection based on similarity matrix and node correction

The method of overlapping community detection based on fuzzy clustering is sensitive to the initialization of community centers, which easily traps in local optima and leads to node misclassification. This paper proposes an evolutionary multiobjective algorithm based on similarity matrix and node correction to detect overlapping communities to solve the above problems. Firstly, the algorithm determines a similarity community for each node by setting the similarity threshold. Then, the central nodes are found more accurately through the similarity distribution of the similarity communities. Secondly, under the framework of the evolutionary multiobjective algorithm, the similarity communities of the central nodes are used as the initial communities to obtain the nonoverlapping communities. In addition, the algorithm proposes a correction strategy for the noncentral nodes based on the similarity communities. The correction strategy obtains the adjacent nodes of each node’s similarity community. It then uses each adjacent node’s community to correct the nonoverlapping community. Finally, the algorithm adjusts the noncentral nodes’ correction strategy. This correction strategy corrects the overlapping nodes according to the number of each overlapping node’s labels. It takes the separation operation to further correct overlapping nodes to obtain the corrected overlapping communities. This paper uses seventeen real networks and a variety of synthetic networks with different parameters to verify the proposed algorithm’s effectiveness. And the proposed algorithm achieves higher accuracy of community detection in most networks than four state-of-the-art overlapping community detection algorithms.

Orsum: a Python package for filtering and comparing enrichment analyses using a simple principle

BackgroundEnrichment analyses are widely applied to investigate lists of genes of interest. However, such analyses often result in long lists of annotation terms with high redundancy, making the interpretation and reporting difficult. Long annotation lists and redundancy also complicate the comparison of results obtained from different enrichment analyses. An approach to overcome these issues is using down-sized annotation collections composed of non-redundant terms. However, down-sized collections are generic and the level of detail may not fit the user’s study. Other available approaches include clustering and filtering tools, which are based on similarity measures and thresholds that can be complicated to comprehend and set.ResultWe propose orsum, a Python package to filter enrichment results. orsum can filter multiple enrichment results collectively and highlight common and specific annotation terms. Filtering in orsum is based on a simple principle: a term is discarded if there is a more significant term that annotates at least the same genes; the remaining more significant term becomes the representative term for the discarded term. This principle ensures that the main biological information is preserved in the filtered results while reducing redundancy. In addition, as the representative terms are selected from the original enrichment results, orsum outputs filtered terms tailored to the study. As a use case, we applied orsum to the enrichment analyses of four lists of genes, each associated with a neurodegenerative disease.Conclusionorsum provides a comprehensible and effective way of filtering and comparing enrichment results. It is available at https://anaconda.org/bioconda/orsum.

High-efficient hierarchical federated learning on non-IID data with progressive collaboration

Hierarchical federated learning (HFL) allows multiple edge aggregations at edge devices before one global aggregation to address both issues of non-independent and identically distributed (non-IID) data and communication bottleneck in federated learning (FL). To solve the non-IID issue, most HFL algorithms assume that clients can be assigned to any edge device. In practice, however, these assumptions are always unrealistic. In this paper, we propose a high-efficient HFL algorithm, named FedPEC, which introduces progressive edge collaboration rather than unrealistic client allocation. FedPEC estimates the initial number of collaborators based on our proved convergence upper bound, and then constantly adjusts the estimated number of collaborators according to the characteristics of each stage in the following rounds. Guided by the estimated number of collaborators, each edge device can be assigned an appropriate collaborator set based on an adaptive similarity threshold. Extensive experiments are conducted to investigate FedPEC in terms of accuracy, loss, and convergence speed with various data sets. Our experimental results demonstrate that FedPEC can significantly outperform state-of-the-art FL algorithms.

Perception and Propagation Characteristics of Bone-Conducted Stimuli Presented to the Human Facial Cranium.

Since bone conduction (BC) has the advantage that it does not cover the ear canal and can be easily heard even when earplugs are worn, it has been applied to various communication devices. Conventional BC is mainly applied to the mastoid process of the temporal bone (the osseous bulge behind the ear), however, some of recent BC devices, such as smart glasses, present stimuli to faces. The face has very complex structures in the human body; therefore, it is highly likely that the hearing and propagation characteristics of sound will change depending on the part to which sound is presented. However, the characteristics of BC presented to the face has not yet been studied in detail. In this study, we measured hearing threshold and ear canal sound pressure (ECSP) when BC stimuli were presented to various parts of the facial cranium (nasal, infraorbital region, zygomatic, jaw angle, and chin), and compared them with conventional placements of BC stimulus (the mastoid process, condyle process, and forehead). The facial parts such as the infraorbital region, zygomatic, and jaw angle had similar hearing thresholds and ECSPs to those of the mastoid process. The results suggested that these facial parts can be used as stimulus placements of BC devices.

Quantification of right atrial fibrosis by cardiac magnetic resonance: verification of the method to standardize thresholds

Introduction and objectivesLate gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) allows noninvasive detection of left atrial fibrosis in patients with atrial fibrillation (AF). However, whether the same methodology can be used in the right atrium (RA) remains unknown. Our aim was to define a standardized threshold to characterize RA fibrosis in LGE-CMR. MethodsA 3 Tesla LGE-CMR was performed in 53 individuals; the RA was segmented, and the image intensity ratio (IIR) calculated for the RA wall using 1 557 767 IIR pixels (40 994±10 693 per patient). The upper limit of normality of the IIR (mean IIR+2 standard deviations) was estimated in healthy volunteers (n=9), and patients who had undergone previous typical atrial flutter ablation (n=9) were used to establish the dense scar threshold. Paroxysmal and persistent AF patients (n=10 each) were used for validation. IIR values were correlated with a high-density bipolar voltage map in 15 patients undergoing AF ablation. ResultsThe upper normality limit (total fibrosis threshold) in healthy volunteers was set at an IIR = 1.21. In the postablation group, 60% of the maximum IIR pixel (dense fibrosis threshold) was calculated as IIR = 1.29. Endocardial bipolar voltage showed a weak but significant correlation with IIR. The overall accuracy between the electroanatomical map and LGE-CMR to characterize fibrosis was 56%. ConclusionsAn IIR > 1.21 was determined to be the threshold for the detection of right atrial fibrosis, while an IIR > 1.29 differentiates interstitial fibrosis from dense scar. Despite differences between the left and right atria, fibrosis could be assessed with LGE-CMR using similar thresholds in both chambers.

Somatosensory Profiles Differentiate Pain and Psychophysiological Symptoms Among Young Adults With Irritable Bowel Syndrome: A Cluster Analysis.

The aim of this study was to investigate if somatosensory profiles can differentiate pain and psychophysiological symptoms among young adults with irritable bowel syndrome (IBS). We performed a cluster analysis of data collected from a randomized clinical trial of 80 IBS patients and 21 age-matched healthy controls (HCs) to stratify pain and symptoms among young adults with IBS by their peripheral sensory profiles. Data of quantitative sensory testing and IBS-related pain and symptoms were collected at baseline and 6-week and 12-week follow-ups. Using the K-means method, IBS patients were classified into 2 clusters, the "IBS normal threshold" (IBS-NT) and the "IBS increased threshold" (IBS-IT). The IBS-NT cluster had a similar pain threshold as the HCs, and the IBS-IT cluster had an increased threshold of somatic pain perception (lower cold pain threshold, higher heat pain threshold, and higher pressure pain threshold, all P<0.001) than HCs. Compared with the IBS-NT cluster, the IBS-IT cluster reported higher levels of IBS-related pain intensity, anxiety, fatigue, and sleep disturbance over the 3 visits (all P<0.05). Young adults with IBS fell into 2 clusters, one with a similar sensory threshold as the HCs and another with an increased pain threshold, who reported higher pain intensity and more severe symptoms. Somatic sensory profiles should be integrated into further personalized self-management intervention among patients with IBS.

Neuromodulation reduces interindividual variability of neuronal output.

In similar states, neural circuits produce similar outputs across individuals despite substantial interindividual variability in neuronal ionic conductances and synapses. Circuit states are largely shaped by neuromodulators that tune ionic conductances. It is therefore possible that, in addition to producing flexible circuit output, neuromodulators also contribute to output similarity despite varying ion channel expression. We studied whether neuromodulation at saturating concentrations can increase the output similarity of a single identified neuron across individual animals. Using the LP neuron of the crab stomatogastric ganglion (STG), we compared the variability of f-I curves and rebound properties in the presence of neuropeptides. The two neuropeptides we used converge to activate the same target current, which increases neuronal excitability. Output variability was lower in the presence of the neuropeptides, regardless of whether the neuropeptides significantly changed the mean of the corresponding parameter or not. However, the addition of the second neuropeptide did not add further to the reduction of variability. With a family of computational LP-like models, we explored how increased excitability and target variability contribute to output similarity and found two mechanisms: Saturation of the responses and a differential increase in baseline activity. Saturation alone can reduce the interindividual variability only if the population shares a similar ceiling for the responses. In contrast, reduction of variability due to the increase in baseline activity is independent of ceiling effects.Significance StatementThe activity of single neurons and neural circuits can be very similar across individuals even though the ionic currents underlying activity are variable. The mechanisms that compensate for the underlying variability and promote output similarity are poorly understood but may involve neuromodulation. Using an identified neuron, we show that neuropeptide modulation of excitability can reduce interindividual variability of response properties at a single-neuron level in two ways. First, the neuropeptide increases baseline excitability in a differential manner, resulting in similar response thresholds. Second, the neuropeptide increases excitability towards a shared saturation level, promoting similar maximal firing rates across individuals. Such tuning of neuronal excitability could be an important mechanism compensating for interindividual variability of ion channel expression.

Monolithic Integration, Performance, and Comparison of Self-Aligned and Conventional IGZO Thin-Film Transistors on a Flexible Substrate

Flexible electronics, most prominently thin-film transistors (TFTs) on plastic substrates are considered the prime building block for the realization of innovative wearable systems. Two of the currently most successful fabrication processes of transistors on free standing polymer foils are large-area compatible devices structured by conventional UV lithography and high-speed transistors realized by self-alignment. Here, both processes, based on InGaZnO technology, are combined for the first time. This demonstrates their compatibility, but also showcases the differences between the resulting devices. Concerning the geometry, TFTs with the same nominal designed channel length of 1.5 μm, exhibit real channel length of 1.5 μm (self-aligned) and 4.5 μm (conventional). Furthermore, the integrated side by side fabrication enables the electrical comparison of both types of TFTs excluding external factors. While all TFTs exhibit similar threshold voltages around 0 V and excellent on/off ratios of ≈10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10</sup> , conventional TFTs are easier to fabricate, and have comparably higher mobilities up to 16 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> V <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> . At the same time, self-aligned TFTs demonstrate better AC performance, demonstrating a maximum oscillation frequency of 216 MHz. This integration shows new possibilities for the realization of complex systems made from building blocks optimized for reliability and speed.

Experimental evaluation on analgesic activity of Erandamoola (Ricinus communis) collected in three different seasons wsr to Dravya Samgrahana Kaala

About: Dravya samgrahana kaala is an important scientific documentation mentioned in Ayurveda where there will be change in activity and phytochemical profile of plants in different seasons. Erandamoola (Ricinus communis) is an important medicinal plant where roots are particularly indicated as analgesic. As per Dravya samgrahana vidhi roots are to be collected in Hemanth-Shishira or Greeshma rutu or Pravarat rutu. Hence with this background study has been planned to evaluate analgesic activity of the Erandamoola (Ricinus cumunis) collected in Greeshma (EMG) and Pravrutritu (EMP) and Shishiraritu (EMS) using Eddy’s Hot plate method, in swiss albino mice. Materials and Methods: Roots of matured plant will be collected in three different seasons, shade dried, powdered and used for the study. Swiss Albino mice were randomly grouped into 3 groups of six animals each. Group I served as control, Group II serve as standard with administration of Tramadol whereas Group III (EMG), Group IV (EMP) and Group V (EMS) serve as the test group with administration of 200 mg/kg body weight (Erandmoola collected in Greeshma (EMG), Pravrut ritu (EMP) and Shishira ritu (EMS) respectively. Results: Erandamoola collected in greeshma and pravrut ritus show almost similar pain threshold with a slight increase in values than drug collected in greeshma ritu. Conclusion: Thus Erandamoola (Ricinus communis) can be efficiently used as an analgesic, simulatneously season or Samgrahana kaala is having a definite role on drug activity.

Comparing eDNA metabarcoding primers for assessing fish communities in a biodiverse estuary.

Metabarcoding of environmental DNA is increasingly used for biodiversity assessments in aquatic communities. The efficiency and outcome of these efforts are dependent upon either de novo primer design or selecting an appropriate primer set from the dozens that have already been published. Unfortunately, there is a lack of studies that have directly compared the efficacy of different metabarcoding primers in marine and estuarine systems. Here we evaluate five commonly used primer sets designed to amplify rRNA barcoding genes in fishes and compare their performance using water samples collected from estuarine sites in the highly biodiverse Indian River Lagoon in Florida. Three of the five primer sets amplify a portion of the mitochondrial 12S gene (MiFish_12S, 171bp; Riaz_12S, 106 bp; Valentini_12S, 63 bp), one amplifies 219 bp of the mitochondrial 16S gene (Berry_16S), and the other amplifies 271 bp of the nuclear 18S gene (MacDonald_18S). The vast majority of the metabarcoding reads (> 99%) generated using the 18S primer set assigned to non-target (non-fish) taxa and therefore this primer set was omitted from most analyses. Using a conservative 99% similarity threshold for species level assignments, we detected a comparable number of species (55 and 49, respectively) and similarly high Shannon's diversity values for the Riaz_12S and Berry_16S primer sets. Meanwhile, just 34 and 32 species were detected using the MiFish_12S and Valentini_12S primer sets, respectively. We were able to amplify both bony and cartilaginous fishes using the four primer sets with the vast majority of reads (>99%) assigned to the former. We detected the greatest number of elasmobranchs (six species) with the Riaz_12S primer set suggesting that it may be a suitable candidate set for the detection of sharks and rays. Of the total 76 fish species that were identified across all datasets, the combined three 12S primer sets detected 85.5% (65 species) while the combination of the Riaz_12S and Berry_16S primers detected 93.4% (71 species). These results highlight the importance of employing multiple primer sets as well as using primers that target different genomic regions. Moreover, our results suggest that the widely adopted MiFish_12S primers may not be the best choice, rather we found that the Riaz_12S primer set was the most effective for eDNA-based fish surveys in our system.

Abstract 1515: Shannon entropy of mutational signatures predict sensitivity of signature detection in targeted sequencing

Abstract Mutational processes can cause driver mutations which are a proximal cause of tumorigenesis. COSMIC identifies signatures of biological and environmental events that drive mutational processes and can be identified by examining patterns of somatic mutations. We describe the complexity of the COSMIC mutational signatures and their impact. We introduce Shannon entropy as a metric to measure complexity of trinucleotide distributions, thus capturing a previously ignored dimension of mutational signatures that may predict their identification. Shannon entropy derives from the rich predictive mathematics of information theory. We calculated entropy for all the COSMIC mutation signatures and found that SBS3, homologous recombination repair deficiency (HRD) signature, had highest entropy of 6.326, while SBS2 signature, activation of AID/APOBEC cytidine deaminases, had the lowest entropy of 1.758.We discovered that high entropy signatures (such as HRD SBS3) require more somatic mutations to be reliably detected than do low entropy signatures, important when planning signature detection using targeted panels that have smaller genomic footprint. We demonstrate this correlation with two approaches i) by simulation using MutSigSim, a tool we developed for simulating mutational profiles given the number of mutations, and ii) by using real datasets. Simulation was performed for high, medium, and low entropy signatures. We used cosine similarity of 0.7 as the threshold for detection. For signatures with entropy &amp;lt;2, a signature can be detected 90% of the time with 10 or more mutations. Similarly, signatures with entropies between 2-3, 3-5 and &amp;gt;5 can be detected 90% of the time with 30, 40, and 100 mutations, respectively. Mutation signatures of 1500 samples from a pan solid tumor cohort sequenced with Oncomine Comprehensive Assay Plus or Oncomine TMB were used to confirm these conclusions. We saw that signatures with higher entropy were difficult to detect at cosine similarity threshold of 0.7 in samples with a smaller number of mutations. In a cohort of samples with MSI-high, we detected mismatch repair (MMR) signatures with low to medium entropy with high specificity and good sensitivity. Furthermore, in a cohort of Ovarian cancer samples, it was difficult to detect the high entropy HRD signature at 0.7 threshold when the number of somatic mutations was not high. We show that ability to detect mutation signatures using targeted panels is directly correlated to the complexity of signature and number of mutations. For research use only. Not for use in diagnostic procedures. Citation Format: Ajithavalli Chellappan, Chintan Vora, Jagannath Patro, Shilpa Nair, Rushikesh S. Kanap, Fiona C. Hyland. Shannon entropy of mutational signatures predict sensitivity of signature detection in targeted sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1515.

Similarity of competing risks models with constant intensities in an application to clinical healthcare pathways involving prostate cancer surgery

The recent availability of routine medical data, especially in a university-clinical context, may enable the discovery of typical healthcare pathways, that is, typical temporal sequences of clinical interventions or hospital readmissions. However, such pathways are heterogeneous in a large provider such as a university hospital, and it is important to identify similar care pathways that can still be considered typical pathways. We understand the pathway as a temporal process with possible transitions from a single initial treatment state to hospital readmission of different types, which constitutes a competing risks setting. In this article, we propose a multi-state model-based approach to uncover pathway similarity between two groups of individuals. We describe a new bootstrap procedure for testing the similarity of constant transition intensities from two competing risk models. In a large simulation study, we investigate the performance of our similarity approach with respect to different sample sizes and different similarity thresholds. The studies are motivated by an application from urological clinical routine and we show how the results can be transferred to the application example.

Functional recursion of orientation cues in figure-ground separation

Visual texture is an important cue to figure-ground organization. While processing of texture differences is a prerequisite for the use of this cue to extract figure-ground organization, these stages are distinct processes. One potential indicator of this distinction is the possibility that texture statistics play a different role in the figure vs. in the ground. To determine whether this is the case, we probed figure-ground processing with a family of local image statistics that specified textures that varied in the strength and spatial scale of structure, and the extent to which features are oriented. For image statistics that generated approximately isotropic textures, the threshold for identification of figure-ground structure was determined by the difference in correlation strength in figure vs. ground, independent of whether the correlations were present in figure, ground, or both. However, for image statistics with strong orientation content, thresholds were up to two times higher for correlations in the ground, vs. the figure. This held equally for texture-defined objects with convex or concave boundaries, indicating that these threshold differences are driven by border ownership, not boundary shape. Similar threshold differences were found for presentation times ranging from 125 to 500 ms. These findings identify a qualitative difference in how texture is used for figure-ground analysis, vs. texture discrimination. Additionally, it reveals a functional recursion: texture differences are needed to identify tentative boundaries and consequent scene organization into figure and ground, but then scene organization modifies sensitivity to texture differences according to the figure-ground assignment.