Similar Analysis Research Articles

Global Field Time-Frequency Representation-Based Discriminative Similarity Analysis of Passive Auditory ERPs for Diagnosis of Disorders of Consciousness.

Behavioural diagnosis of patients with disorders of consciousness (DOC) is challenging and prone to inaccuracies. Consequently, there have been increased efforts to develop bedside assessment based on EEG and event-related potentials (ERPs) that are more sensitive to the neural factors supporting conscious awareness. However, individual detection of residual consciousness using these techniques is less established. Here, we hypothesize that the cross-state similarity (defined as the similarity between healthy and impaired conscious states) of passive brain responses to auditory stimuli can index the level of awareness in individual DOC patients. To this end, we introduce the global field time-frequency representation-based discriminative similarity analysis (GFTFR-DSA). This method quantifies the average cross-state similarity index between an individual patient and our constructed healthy templates using the GFTFR as an EEG feature. We demonstrate that the proposed GFTFR feature exhibits superior within-group consistency in 34 healthy controls over traditional EEG features such as temporal waveforms. Second, we observed the GFTFR-based similarity index was significantly higher in patients with a minimally conscious state (MCS, 40 patients) than those with unresponsive wakefulness syndrome (UWS, 54 patients), supporting our hypothesis. Finally, applying a linear support vector machine classifier for individual MCS/UWS classification, the model achieved a balanced accuracy and F1 score of 0.77. Overall, our findings indicate that combining discriminative and interpretable markers, along with automatic machine learning algorithms, is effective for the differential diagnosis in patients with DOC. Importantly, this approach can, in principle, be transferred into any ERP of interest to better inform DOC diagnoses.

Structural changes and assembly mechanisms of microbial communities during rapid sedimentation of Yellow River sediments

Microbial communities are essential for the biogeochemical cycles in aquatic ecosystems. The effects of sediment depositional processes on the microbial community characteristics in the Yellow River have not been extensively studied at the in-situ macroscopic scale. Since the Yellow River diversion reservoir has the sedimentation pond, it can be used as a natural experimental area. This study investigated changes in microbial community structures, functions, and assembly mechanisms under sediment deposition by analysing 26 water and sediment samples. The results showed that during rapid sediment deposition, different community structures formed between the water body and the sediment (Analysis of similarities, P<0.01), and the variability between them increased with increasing water depth. Sediments are more closely associated with carbon, nitrogen, and sulfur cycling processes, while water is more closely associated with light reactions. Under changing sediment concentrations, the microbial community diversities, community compositions, and functions changed significantly. Actinobacteria and Cyanobacteria were the species responsible for the significant differences in the microbial communities in the water, with linear discriminant analysis scores of 4.478–4.724 and 4.427–5.007, respectively. Water temperature, NH4+-N, and electrical conductivity were the most critical factors that affected the microbial community structures. During the rapid deposition of sediments, microbial community assembly was dominated by stochastic process. This study may provide a reference for exploring the mechanism of microbial community changes in reservoirs under the dynamic hydrological conditions of the Yellow River.

Allergenicity and Linear Epitope Analysis of Scy p 8, an Allergen from Mud Crab.

Scy p 8 (triosephosphate isomerase) as a crab allergen in inducing distinct T-helper (Th) cell differentiation and a linear epitope associated with allergenicity remain elusive. In this study, mice sensitized with Scy p 8 exhibited significantly upregulated levels of IgE, IgG1, and IL-4 release, inducing a Th2 immune response. Moreover, the release of IFN-γ (Th1) and the levels of Treg cells were downregulated, while IL-17A (Th17) was upregulated, indicating that Scy p 8 disrupted the Th1/Th2 balance and Th17/Treg balance in mice. Furthermore, bioinformatics prediction and serum samples from crab-allergic patients and mice enabled the discovery of 8 linear epitopes of Scy p 8. Meanwhile, the analysis of peptide similarity and tertiary superposition revealed that 8 epitopes of Scy p 8 exhibited conservation across various species, potentially resulting in cross-reactivity. These findings possess the potential to enhance the comprehension of crab allergens, thereby establishing a foundation for investigating cross-reactivity.

A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids

Brain organoids represent a useful tool for modeling of neurodevelopmental disorders and can recapitulate brain volume alterations such as microcephaly. To monitor organoid growth, brightfield microscopy images are frequently used and evaluated manually which is time-consuming and prone to observer-bias. Recent software applications for organoid evaluation address this issue using classical or AI-based methods. These pipelines have distinct strengths and weaknesses that are not evident to external observers. We provide a dataset of more than 1,400 images of 64 trackable brain organoids from four clones differentiated from healthy and diseased patients. This dataset is especially powerful to test and compare organoid analysis pipelines because of (1) trackable organoids (2) frequent imaging during development (3) clone diversity (4) distinct clone development (5) cross sample imaging by two different labs (6) common imaging distractors, and (6) pixel-level ground truth organoid annotations. Therefore, this dataset allows to perform differentiated analyses to delineate strengths, weaknesses, and generalizability of automated organoid analysis pipelines as well as analysis of clone diversity and similarity.

Quantitative Analysis of Comprehensive Similarity in Restoration of Ancient Building Walls Using Hue–Saturation–Value Color Space and Circular Local Binary Pattern

Evaluating the effects of wall restoration on ancient buildings has been a difficult task, and it is important that the overall appearance of the restored walls of ancient buildings is similar, harmonious, and uniform. This paper used a hue–saturation–value (HSV) color space and Circular Local Binary Pattern (CLBP) to analyze the comprehensive similarity between a restored wall and the original walls in Qi Li Ancient Town. The results show that the values of the comprehensive similarity calculation of ancient buildings based on the color and texture were consistent with the actual situation. The method is suitable for evaluating the degree of matching between wall repair materials and the appearance of the original wall materials of ancient buildings, and it can also be used to assess the comprehensive similarity between the repair materials and the original building walls before carrying out the wall repair in order to select more suitable materials for wall repair and achieve the best repair effect. And it is flexible and objective compared to human judgement. Through the accurate restoration of ancient buildings, not only can we protect cultural heritage and continue the historical lineage, we can also enhance the aesthetic value of buildings and meet people’s needs for historical and cultural tracing.

Analysis of similarities and differences between transient symptomatic zinc deficiency and acrodermatitis enteropathica in children: a case report of a Chinese Yi-ethnic infant

BackgroundTransient symptomatic zinc deficiency (TSZD), an acquired type of zinc deficiency, is a rare, but probably underrecognized disease, extremely in breastfed premature with low birthweight infants. Its clinical manefestations are similar to Acrodermatitis enteropathica (AE), which is a genetic zinc absorption disorder caused by SLC39A4 gene mutations. This gene encodes a member of the zinc/iron-regulated transporter-like protein (ZIP) family. The encoded protein localizes to cell membranes and is required for zinc uptake in the intestine. TSZD is often misdiagnosed as AE because of their extremely similar manefestations, characterized by a typical rash. Therefore, the differention between them is still a clinical challenging.Case presentationHere, we present a case of TSZD in a 4 month and 23 days female Chinese Yi-ethnic premature with AE-like skin lesions, mainly presenting periorificial, perianal and perineal crusted, eroded, erythemato-squamous eruption. Laboratory examination showed the patient’s blood zinc level was significantly decreased. Further sequencing of the SLC39A4 gene showed no mutation in the infant and her parents. Skin lesions significantly improved after 6 days of initial zinc supplementation (3 mg/kg/d), and maintenance treatment with 1 mg/kg/day of zinc was discontinued after 8 months without recurrence.ConclusionsThe clinical manifestations of TSZD and AE are extremely similar, leading to a high rate of clinical misdiagnosis. While genetic analysis of the SLC39A4 gene is a reliable method for differentiating TSZD from AE. It is recommended that SLC39A4 gene test should be performed as far as possible in children with AE-like rash.

Dynamic impact of delivery modes on gut microbiota in preterm infants hospitalized during the initial 4 weeks of life

Preterm infants face a high risk of various complications, and their gut microbiota plays a pivotal role in health. Delivery modes have been reported to affect the development of gut microbiota in term infants, but its impact on preterm infants remains unclear. Here, we collected fecal samples from 30 preterm infants at five-time points within the first four weeks of life. Employing 16 S rRNA sequencing, principal coordinates analysis, the analysis of similarities, and the Wilcoxon rank-sum test, we examined the top dominant phyla and genera, the temporal changes in specific taxa abundance, and their relationship with delivery modes, such as Escherichia-Shigella and Enterococcus based on vaginal delivery and Pluralibacter related to cesarean section. Moreover, we identified particular bacteria, such as Taonella, Patulibacter, and others, whose proportions fluctuated among preterm infants born via different delivery modes at varying time points, as well as the microbiota types and functions. These results indicated the influence of delivery mode on the composition and function of the preterm infant gut microbiota. Importantly, these effects are time-dependent during the early stages of life. These insights shed light on the pivotal role of delivery mode in shaping the gut microbiota of preterm infants and have significant clinical implications for their care and management.

Abstract PO3-27-05: Racioethnic and Ancestral Differences in Risk of Cardiometabolic Conditions and Cardiovascular Disease in Women Treated for Breast Cancer: the Pathways Heart Study

Abstract Background: Despite the established literature of racioethnic disparities in cardiovascular disease (CVD) in the general population, few studies have examined such differences in women after BC treatment, who are at higher risk due to cardiotoxic cancer treatment. Moreover, few prior studies have considered genetic similarity among the participants in the analyses, which can be objectively inferred to delineate the ancestral background of an individual. Methods: The Pathways Heart Study was established to investigate the incidence of cardiometabolic risk factors and CVD events in women with a history of BC at Kaiser Permanente Northern California (KPNC). The main study endpoints for this analysis were cardiometabolic risk factors (hypertension, diabetes, and dyslipidemia) and CVD events, identified by ICD and CPT codes from EHR. Prevalent conditions were identified within 3 years prior to the date of BC diagnosis, and incident conditions were from the date of BC diagnosis to December 31, 2021. Ethnicity was self-reported and classified as non-Hispanic White (NHW), non-Hispanic Black (NHB), Asian, Hispanic, other, or unknown. Global genetic ancestry was estimated to capture the proportion of continental ancestries genetically similar to the reference populations in Africa, Americas, Asia, and Europe from the 1000 Genome Project and Human Genome Diversity Project (HGDP), which, with the current lack of universally accepted labeling, are herein referred to as African, Native American, Asian, and European ancestry, respectively. Multivariable logistic and Cox proportional hazards regression models with all-cause mortality considered as competing risk were used to analyze the associations of race and ethnicity and genetic similarity with prevalent and incident cardiometabolic risk factors and CVD events. Results: Of the 4,071 women with BC in this analysis, 2,713 (66.6%) self-reported as NHW, 305 (7.5%) as NHB, 512 (12.6) as Asian, 447 (11.0%) as Hispanic, and 94 (2.3%) as other or unknown. NHB, Asian, and Hispanic women were more like to have prevalent diabetes than NHW women, the pattern of which persisted after BC diagnosis. Adjusted OR (95% CI) of risk of incident diabetes was 1.74 (1.21-2.49) for NHB, 3.63 (2.59-5.08) for Asian, and 2.19 (1.58-3.04) for Hispanic women, as compared to NHW. Analysis of genetic similarity revealed results consistent with self-reported race and ethnicity (sHR [95% CI] per 25% increment of African ancestry 1.19 [1.07-1.34], Asian ancestry 1.57 [1.44-1.72], and Native American ancestry 1.60 [1.29-2.00]), in comparison to European ancestry. For CVD risk, NHB women were more like to develop any prevalent and incident CVD than NHW women, particularly for ischemic heart disease (incident risk sHR=1.80 [1.10-2.94]). Genetic similarity analyses also showed higher risk of ischemic heart disease associated with African ancestry (incident risk per 25% increment, sHR=1.23 [1.06-1.43]). In contrast, Hispanic women were at lower risk of any incident CVD, serious CVD, arrhythmia, heart failure or cardiomyopathy, and ischemic heart disease. Similarly, lower risk of these CVD conditions was associated with Native American ancestry. Conclusions: Compared with women who self-reported as NHW, those self-reported as NHB, Asian, and Hispanic were at higher risk of diabetes prior to BC diagnosis and the elevated risk persisted after BC diagnosis. Moreover, Black women had higher risk of prevalent and incident CVD, whereas Hispanic women had lower risk of CVD, the latter of which might be related to the admixture of Native American ancestry. To our knowledge, this is the largest multi-ethnic study of disparities in CVD health in women post BC treatment, demonstrating corroborating findings between self-reported race and ethnicity and genetic similarity. The results highlight disparities in cardiometabolic risk factors and CVD among BC survivors that may warrant more research and clinical attentions. Citation Format: Song Yao, Haiyang Sheng, Peter Fiorica, Richard Cheng, Lucas Mendicino, Angela Omilian, Qianqian Zhu, Janise Roh, Cecile Laurant, Valerie Lee, Isaac Ergas, Carlos Iribarren, Jamal Rana, Mai Nguyen-Huynh, Eileen Rillamas-Sun, Dawn Hershman, Christine Ambrosone, Lawrence Kushi, Heather Greenlee, Marilyn Kwan. Racioethnic and Ancestral Differences in Risk of Cardiometabolic Conditions and Cardiovascular Disease in Women Treated for Breast Cancer: the Pathways Heart Study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-27-05.

Comparing the multivariate relationships of conceptual adversity models and structural brain development in adolescent girls: A registered report.

Adverse experiences throughout development confer risk for a multitude of negative long-term outcomes, but the processes via which these experiences are neurobiologically embedded are still unclear. Adolescence provides an opportunity to understand how these experiences impact the brain's rapidly changing structure. Two models are central to current adversity conceptualizations: a cumulative risk model, where all types of experiences are combined to represent accumulating stress, and a dimensional model, where certain features of experience (e.g., threat or deprivation) exert unique neurophysiological influence. In this registered report, we extended upon previous research by using a form of representational similarity analysis to examine whether the dimensional and cumulative risk models of adversity predict cortical thinning in frontoparietal and frontotemporal networks and volumetric changes in subcortical regions throughout adolescence. Drawing from a longitudinal sample of 179 adolescent girls (ages 10-13 years at the first wave) from Lane County, Oregon, United States, and up to four waves of follow-up data, we found that operationalizing adversity by similarity in threat and deprivation provided better prediction of brain development than similarity in overall adversity. However, these dimensions do not exhibit unique associations with developmental changes in the hypothesized brain changes. These results underscore the significance of carefully defining adversity and considering its impact on the entire brain. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Measuring teacher-student relationships among children with emotional and behavioral problems

A rapidly growing body of research indicates that the quality of children's relationships with teachers can affect students’ emotional, behavioral, and school related adjustment. The vast majority of this research has relied on measures that assess teacher—rather than student—perceptions of these relationships. In this study, we administered a student self-report measure of teacher-student relationships (TSR) to 185 children, all of whom had emotional and behavioral problems. Children's special education teachers (N = 76) also completed a validated measure of TSR. Results of a confirmatory factor analysis of child ratings confirmed a model that included three TSR factors: Communication, Trust, and Alienation. Analyses of similarities between student and teacher views of their relationship with one another suggested limited concordance, however, student perceptions of TSR were robust predictors of their emotional, behavioral, and school adjustment even after controlling for teacher perceptions of TSR. These findings provide preliminary support for the importance assessing student perceptions of TSR and initial evidence for the construct validity, reliability and criterion-related validity of a child report measure of teacher-student relationships among students with emotional and behavioral problems.

In-Depth Characterization of bZIP Genes in the Context of Endoplasmic Reticulum (ER) Stress in Brassica campestris ssp. chinensis.

Numerous studies have been conducted to investigate the genomic characterization of bZIP genes and their involvement in the cellular response to endoplasmic reticulum (ER) stress. These studies have provided valuable insights into the coordinated cellular response to ER stress, which is mediated by bZIP transcription factors (TFs). However, a comprehensive and systematic investigations regarding the role of bZIP genes and their involvement in ER stress response in pak choi is currently lacking in the existing literature. To address this knowledge gap, the current study was initiated to elucidate the genomic characteristics of bZIP genes, gain insight into their expression patterns during ER stress in pak choi, and investigate the protein-to-protein interaction of bZIP genes with the ER chaperone BiP. In total, 112 members of the BcbZIP genes were identified through a comprehensive genome-wide analysis. Based on an analysis of sequence similarity, gene structure, conserved domains, and responsive motifs, the identified BcbZIP genes were categorized into 10 distinct subfamilies through phylogenetic analysis. Chromosomal location and duplication events provided insight into their genomic context and evolutionary history. Divergence analysis estimated their evolutionary history with a predicted divergence time ranging from 0.73 to 80.71 million years ago (MYA). Promoter regions of the BcbZIP genes were discovered to exhibit a wide variety of cis-elements, including light, hormone, and stress-responsive elements. GO enrichment analysis further confirmed their roles in the ER unfolded protein response (UPR), while co-expression network analysis showed a strong relationship of BcbZIP genes with ER-stress-responsive genes. Moreover, gene expression profiles and protein-protein interaction with ER chaperone BiP further confirmed their roles and capacity to respond to ER stress in pak choi.

Environmental factors and particle size shape the community structure of airborne total and pathogenic bacteria in a university campus.

Given the dense population on university campuses, indoor and outdoor airborne bacterial contamination may lead to the rapid spread of diseases in a university environment. However, there are few studies of the characteristics of airborne and pathogenic bacterial communities in different sites on a university campus. In this study, we collected particulate matter samples from indoor and outdoor locations at a university in Bengbu City, Anhui Province, China, and analyzed the community characteristics of airborne and pathogenic bacteria using a high-throughput sequencing technique. The results showed that the composition of the dominant airborne and pathogenic bacterial communities was consistent among sites at the phylum and genus levels, with differences in their relative abundance. There were significant differences in the structure of the airborne and pathogenic bacterial communities between indoor and outdoor sites (p < 0.05). An analysis of similarities (ANOSIM) indicated that the structure of airborne bacterial communities in indoor sites was influenced by the room occupancy rate, ventilation conditions, and the extent of indoor furnishing (p < 0.05), while the structure of pathogenic bacterial communities was influenced by the number of individuals and spatial dimensions (p < 0.05). The impact of particle size on the structure of airborne and pathogenic bacterial communities was relatively minor. A total of 194 suspected pathogenic bacterial species were identified, accounting for 0.0001-1.3923% of the total airborne bacteria, all of which were conditional pathogens. Among them, Saccharopolyspora rectivirgula, Acinetobacter johnsonii, and Moraxella osloensis exhibited relatively high relative abundance, accounting for 24.40, 16.22, and 8.66% of the total pathogenic bacteria, respectively. Moreover, 18 emerging or re-emerging pathogenic bacterial species with significant implications for human health were identified, although their relative abundance was relatively low (0.5098%). The relative abundance of pathogenic bacteria in indoor environments was significantly higher than outdoors, with the laboratory and dormitory having the highest levels. The findings of this study provide valuable guidance for the prevention and control of airborne bacterial contamination and the associated health risks in both a campus environment and other public spaces with high occupancy rates.

Can artificially induced habitat complexity alter macroinvertebrates diversity? A case study from a freshwater wetland ecosystem

Habitat complexity can enhance the resilience of wetlands against environmental stressors such as extreme weather events, pollution, and habitat loss. The introduction of artificial induced complexity (AIC) can play a significant role in reshaping the macroinvertebrate communities within wetland ecosystems by enhancing habitat quality in protected areas. Therefore, this study was designed to examine the variation of macroinvertebrates community structure in artificially induced complex sanctuary site (SS), partially protected (PP) and open sites (OS) from July 2019-April 2020. AIC in the sanctuary sites was established through the installation of cemented hexapods and ring pipes. Over the study period, a total of 665 macroinvertebrates were gathered, with 55.55% originating from SS, 31.14% from PP, and 18.21% from OS sites. The community consists mainly of Lymnaea acuminatatea and Tubifex tubifex, with the most abundant species being Limnodrillus hoffmeisteri and Branchiura sowerbyi. A notable positive impact of AIC was evident in the increased total abundance and diversity indices of macroinvertebrate communities. The Analysis of Similarity (ANOSIM) revealed significant distinctions in community structures among various intervention types, which was further corroborated by a non-metric multidimensional scaling (nMDS) plot. Similarity of Percentage Analysis (SIMPER) highlighted that Limnodrillus hoffmeisteri made the most significant contribution to the dissimilarity observed among the different intervention types. Canonical Correspondence Analysis (CCA) revealed a close association between the structure of the macroinvertebrate community and three key ecological factors: periphyton biomass, macrophyte cover, and sediment properties. These findings could offer a more effective approach for managers and policymakers engaged in the conservation of macroinvertebrates and the sustainable management of fisheries resources within wetland ecosystems.

On Representation Knowledge Distillation for Graph Neural Networks.

Knowledge distillation (KD) is a learning paradigm for boosting resource-efficient graph neural networks (GNNs) using more expressive yet cumbersome teacher models. Past work on distillation for GNNs proposed the local structure preserving (LSP) loss, which matches local structural relationships defined over edges across the student and teacher's node embeddings. This article studies whether preserving the global topology of how the teacher embeds graph data can be a more effective distillation objective for GNNs, as real-world graphs often contain latent interactions and noisy edges. We propose graph contrastive representation distillation (G-CRD), which uses contrastive learning to implicitly preserve global topology by aligning the student node embeddings to those of the teacher in a shared representation space. Additionally, we introduce an expanded set of benchmarks on large-scale real-world datasets where the performance gap between teacher and student GNNs is non-negligible. Experiments across four datasets and 14 heterogeneous GNN architectures show that G-CRD consistently boosts the performance and robustness of lightweight GNNs, outperforming LSP (and a global structure preserving (GSP) variant of LSP) as well as baselines from 2-D computer vision. An analysis of the representational similarity among teacher and student embedding spaces reveals that G-CRD balances preserving local and global relationships, while structure preserving approaches are best at preserving one or the other.

The red color in Russian, French and Chinese linguistic cultures on the example of phraseology and proverbs

The research conducted in this article is aimed at analyzing color symbols in Russian, French and Chinese linguistic cultures using the analysis of phraseology and proverbs. The research methodology is based on a comparative analysis of phraseological units and proverbs containing color components in these languages. In the course of the study, both common and unique features in the color symbolism of each of the linguistic cultures under consideration were identified. Through a comparative analysis of phraseology and proverbs in different languages, it was possible to better understand how color embodies cultural norms, worldview and historical contexts in each nation. This allowed us to see which aspects of color are particularly significant for each culture and what associations and symbolic meanings are associated with them. Special attention is paid to the analysis of differences and similarities in the interpretation of color in the idiomatic expressions of each language. This allows us to understand which cultural and historical factors form unique views and ideas about color in each of the linguistic cultures under consideration. The study also highlights that the interpretation of color symbols in idiomatic expressions depends on the cultural and historical contexts of each language. Idioms are a reflection of the collective consciousness and worldview of the people, and the study of color phenomena in idioms helps to better understand national identity and linguistic evolution. In addition, the study found that the red color can acquire different meanings and connotations in different languages, despite common dictionary definitions. This indicates that the use and attitude towards the color red depends on the cultural and historical characteristics of each language group. The scientific novelty of the work lies in the fact that it combines linguistic analysis with the analysis of cultural characteristics and uses the methodology of synergetic symbolism. This approach allows us to understand how the interaction of different colors creates new symbolic meanings and associations specific to each culture.

Generation of synthetic PET/MR fusion images from MR images using a combination of generative adversarial networks and conditional denoising diffusion probabilistic models based on simultaneous 18F-FDG PET/MR image data of pyogenic spondylodiscitis

BACKGROUND CONTEXTCross-modality image generation from magnetic resonance (MR) to positron emission tomography (PET) using the generative model can be expected to have complementary effects by addressing the limitations and maximizing the advantages inherent in each modality. PURPOSEThis study aims to generate synthetic PET/MR fusion images from MR images using a combination of generative adversarial networks (GANs) and conditional denoising diffusion probabilistic models (cDDPMs) based on simultaneous 18F-fluorodeoxyglucose (18F-FDG) PET/MR image data. STUDY DESIGNRetrospective study with prospectively collected clinical and radiological data. PATIENT SAMPLEThis study included 94 patients (60 men and 34 women) with thoraco-lumbar pyogenic spondylodiscitis (PSD) from February 2017 to January 2020 in a single tertiary institution. OUTCOME MEASURESQuantitative and qualitative image similarity were analyzed between the real and synthetic PET/ T2-weighted fat saturation MR (T2FS) fusion images on the test data set. METHODSWe used paired spinal sagittal T2FS and PET/T2FS fusion images of simultaneous 18F-FDG PET/MR imaging examination in patients with PSD, which were employed to generate synthetic PET/T2FS fusion images from T2FS images using a combination of Pix2Pix (U-Net generator + Least Squares GANs discriminator) and cDDPMs algorithms. In the analyses of image similarity between the real and synthetic PET/T2FS fusion images, we adopted the values of mean peak signal to noise ratio (PSNR), mean structural similarity measurement (SSIM), mean absolute error (MAE), and mean squared error (MSE) for quantitative analysis, while the discrimination accuracy by three spine surgeons was applied for qualitative analysis. RESULTSTotal of 2,082 pairs of T2FS and PET/T2FS fusion images were obtained from 172 examinations on 94 patients, which were randomly assigned to training, validation, and test data sets in 8:1:1 ratio (1664, 209, and 209 pairs). The quantitative analysis revealed PSNR of 30.634 ± 3.437, SSIM of 0.910 ± 0.067, MAE of 0.017 ± 0.008, and MSE of 0.001 ± 0.001, respectively. The values of PSNR, MAE, and MSE significantly decreased as FDG uptake increased in real PET/T2FS fusion image, with no significant correlation on SSIM. In the qualitative analysis, the overall discrimination accuracy between real and synthetic PET/T2FS fusion images was 47.4%. CONCLUSIONSThe combination of Pix2Pix and cDDPMs demonstrated the potential for cross-modal image generation from MR to PET images, with reliable quantitative and qualitative image similarities.

Metabarcoding clarifies the diet of the elusive and vulnerable Australian tjakura (Great Desert Skink, Liopholis kintorei)

IntroductionAccurately quantifying the diet of species has implications for our understanding of their ecology and conservation. Yet, determining the dietary composition of threatened and elusive species in the wild is often difficult.MethodsThis study presents the first dietary assessment of tjakura (Liopholis kintorei) using non-invasive sampling of scats and high-throughput sequencing techniques.ResultsThe tjakura in Uluru consumed 48 invertebrates, 27 plants, and two vertebrate taxa. Fruit flies (Leucophenga spp.), beetles (Harpalus spp. and Omorgus spp.), mosquitos (Culicidae spp.), termites (Termitidae spp.), spiked mallow (Malvastrum americanum), bush tomatoes (Solanum centrale), and wild turnip (Brassica tournefortii) comprised the majority of the diet. Analysis of similarity revealed that food items did not differ significantly between tjakura age groups, seasons, or time since the last fire, however, adults, hot season, and fire scar of 2018 showed a relatively higher prey diversity.DiscussionThese high similarities in diet composition between age classes and fire scars indicate potential intraspecific competition when food resources are scarce. The diet diversity and potential plasticity observed in this study reflect a dietary ecology influenced by food availability rather than preference. Our study demonstrates that scat DNA metabarcoding is an important complementary tool to conventional scat analysis or indigenous knowledge as most food items we identified were previously not recorded through those methods.

Uncovering lobbying strategies in sustainable finance disclosure regulations using machine learning

PurposeWe analyse lobbying behaviour by using Machine Learning approaches. In the context of Sustainable Finance Disclosure Regulation (SFDR), we gain detailed insights, assign these to existing strategies, and measure how strongly which participant influences the regulation. Study design/methodology/approachWe use tri-gram analysis, sentiment analysis, and similarity analysis as methods to obtain insights into the political commentary process of European Supervisory Authorities (ESAs) drafts dealing with SFDR. FindingsOur metadata helps to identify stakeholders and lobbying strategies. We found that the most negative comments came from the regulated, who argued strongly subjectively in a very objective environment of ESG disclosure. We also identified typical lobbying strategies based on arguments, persuasion, and classic cost-benefit considerations. Originality/valueWe generate emotion values and synthesise detailed argument differences and show that modern algorithms can contribute to the identification of interest groups and lobbying strategies. Furthermore, we generate similarity values of arguments that can be taken into account in the analysis of the success of a lobbying strategy.

APIMiner: Identifying Web Application APIs Based on Web Page States Similarity Analysis

Modern web applications offer various APIs for data interaction. However, as the number of these APIs increases, so does the potential for security threats. Essentially, more APIs in an application can lead to more detectable vulnerabilities. Thus, it is crucial to identify APIs as comprehensively as possible in web applications. However, this task faces challenges due to the increasing complexity of web development techniques and the abundance of similar web pages. In this paper, we propose APIMiner, a framework for identifying APIs in web applications by dynamically traversing web pages based on web page state similarity analysis. APIMiner first builds a web page model based on the HTML elements of the current web page. APIMiner then uses this model to represent the state of the page. Then, APIMiner evaluates each element’s similarity in the page model and determines the page state similarity based on these similarity values. From the different states of the page, APIMiner extracts the data interaction APIs on the page. We conduct extensive experiments to evaluate APIMiner’s effectiveness. In the similarity analysis, our method surpasses state-of-the-art methods like NDD and mNDD in accurately distinguishing similar pages. We compare APIMiner with state-of-the-art tools (e.g., Enemy of the State, Crawlergo, and Wapiti3) for API identification. APIMiner excels in the number of identified APIs (average 1136) and code coverage (average 28,470). Relative to these tools, on average, APIMiner identifies 7.96 times more APIs and increases code coverage by 142.72%.

Study of the Genome Diversity of Cornus L. and Mespilus L. Cultivated in the Northern Regions of Azerbaijan

Cranberry and medlar are common in the Guba, Gusar, and Sheki regions of Azerbaijan. A study was conducted to determine the habitats of wild growing forms and biomorphological features. Identification was carried out based on molecular markers. A comparative study of the biomorphological characteristics of genotypes, economic indicators, pomological analysis and assessment of similarity by quantitative indicators was carried out.