Binary Formation Research Articles

A Pilot Empirical Study of “Intra-firm Boilerplate” CAM Reporting – DOW 30 Companies

On June 1, 2017, the Public Company Accounting Oversight Board (PCAOB) promulgated the new auditing standard AS 3101: The Auditor's Report on an Audit of Financial Statements When the Auditor Expresses an Unqualified Opinion. This new standard significantly expands the auditor’s report by requiring the inclusion of critical audit matters (CAMs) in an unqualified opinion. The primary objective of this paper is to examine whether the auditors were using an “intra-firm boilerplate” practice in CAM reporting. We analyzed the 10-Ks filed by the DOW 30 companies during the two-year fiscal periods of 2019 and 2020 by comparing the related CAMs. To run the binomial test on SPSS, we coded the relevant qualitative data in our data sheet before operationalizing them into the required binary format. Our empirical data indicate that most of the CAMs reported in fiscal year 2020 were either on new audit topics or with significant modifications in comparison to 2019. However, a substantial number (38%) of the CAMs reported in fiscal year 2020 were virtually the same as in fiscal year 2019. Our empirical results support former SEC chairperson Jay Clayton’s concern on “boilerplate” practice in CAM reporting.

Identification of Duplicates in Mulberry Germplasm Using Morphological Descriptors and SSR Markers

Germplasm collections invariably contain duplicate accessions, both within and between genebanks. These redundancies are a burden for curators because they do not contribute to the diversity in the collection, but do require genebank budget for maintenance. Thus, both from a genetic and economic point of view, identification and elimination of redundancies should be an important genebank objective. In field gene banks, duplicate accessions are widespread and their identification is required to facilitate germplasm administration and lower the maintenance costs. The goal of this study was to identify the duplicates in mulberry germplasm that has been morphologically and agronomically evaluated. Until now the identification of duplicate accessions had to rely on comparison of morphological characters which are subject to environmental variation. However, it is possible to make routine use of molecular markers based on genomic DNA for the identification of duplicate accessions of vegetatively propagated species. In the present study, among the mulberry germplasm 312 accessions were characterized using 17 qualitative morphological descriptors and identifiied 84 suspected duplicates using multivariate cluster analysis. Further, the suspected duplicates were screened using 12 SSR markers and scored the polymorphic alleles using binary format. The data matrix was subjected to multivariate cluster analysis and 14 mulberry accessions were confirmed as true duplicates. The identification of redundant accessions enables curators to concentrate their efforts on the characterization, evaluation, and regeneration of distinct genetic material. The molecular markers aids in giving priorities for the evaluation and regeneration of unique genetic materials in field genebank.

A text-based, generative deep learning model for soil reflectance spectrum simulation in the solar range (400–2499 nm)

Soil spectral reflectance is a necessary input for land surface and radiative transfer models, and can be used to infer soil properties. Numerous soil reflectance inversion models have been developed based on mechanistic approaches, each with their own limitations. Mechanistic models based on radiative transfer theory are usually based on only a few input soil properties, whereas data-driven approaches are limited by high non-uniformity of available published datasets that severely limits the amount of data usable for model calibration. To address these limitations, a fully data-driven soil optics generative model (SOGM) for simulation of soil reflectance spectra from soil property inputs was developed based on the denoising diffusion probabilistic model (DDPM). The model was trained on an extensive dataset comprising nearly 180,000 soil spectra-property set pairs from 17 published datasets. The model generates soil reflectance spectra from text-based inputs describing soil properties and their values rather than only numerical values and labels in binary vector format, which means the model can handle variable formats for property reporting. Because the model is generative, it can simulate reasonable output spectra based on an incomplete set of available input properties, which becomes more reliable as the input property set becomes more complete. Two additional sub-models were also built to complement the SOGM: a spectral padding model that can fill in the gaps for spectra shorter than the target solar range (400 to 2499 nm), and a wet soil spectra model that can estimate the effects of water content on soil reflectance spectra given the dry spectrum predicted by the SOGM. It can also be easily integrated with other soil–plant radiation models used for remote sensing research such as PROSAIL and Helios 3D plant modeling software. The testing results of the SOGM on new datasets not included in model training demonstrated that the model can generate reasonable soil reflectance spectra based on available property inputs. Results also show soil clay/sand/silt fraction, organic carbon content, nitrogen content, and iron content tended to be important properties for spectra simulation. Inclusion of some trace minerals like nickel as model inputs decreased model performance because of their low concentrations and large propensity for ground-truth measurement error.

Formation of wind-fed black hole high-mass X-ray binaries: The role of Roche-lobe-overflow post black hole formation

The three dynamically confirmed wind-fed black hole high-mass X-ray binaries (BH-HMXBs) are suggested to all contain a highly spinning black hole (BH). However, based on the theories of efficient angular momentum transport inside the stars, we expect that the first-born BHs in binary systems should have low spins, which is consistent with gravitational-wave observations. As a result, the origin of the high BH spins measured in wind-fed BH-HMXBs remains a mystery. In this paper, we conduct a binary population synthesis study on wind-fed BH-HMXBs at solar metallicity with the use of the newly developed code POSYDON odot $ are prevalent, posing a challenge in explaining simultaneously all observed properties of the BH-HMXB in our Galaxy, Cygnus X-1, and potentially hinting that the accretion efficiency onto non-degenerate stars, before the formation of the BH, is also more conservative than assumed in our simulations.

The enigmatic origin of two dormant BH binaries: Gaia BH1 and Gaia BH2

Abstract The two systems, namely, Gaia BH1 and Gaia BH2, that have been confirmed as dormant (i.e., no X-ray emission detected) black hole (BH) - low-mass star binaries in the latest Gaia mission data release (DR3) are intriguing in the context of their formation and evolution. Both systems consist of $\sim 9\, \mathrm{{\rm M}_{\odot }}$ BH and $\sim 1\, \mathrm{{\rm M}_{\odot }}$ star orbiting each other on a wide, eccentric orbit (e ∼ 0.5). We argue that formation of such Gaia BH-like systems through the isolated binary evolution (IBE) channel, under the standard common envelope assumptions, and from dynamical interactions in young massive and open clusters are equally probable, and that the formation rate of such binaries is of the order of $10^{-7}\, \mathrm{{\rm M}_{\odot }}^{-1}$ for both channels. We estimate that, according to our models, there are at most ∼900 detectable Gaia BH-like binaries in the Milky Way thin disc. What plays an important role in formation of Gaia BH-like systems via the IBE channel is the mutual position of the natal kick velocity vector and the binary angular momentum vector. We find that natal kicks with a median magnitude of ∼40 km/s are preferred for the formation of Gaia BH1-like binaries. Approximately 94% of those binaries are formed with the BH spin misaligned to the orbital axis by less than 40○. Gaia BH2-like binaries form if the low velocity natal kick (of median magnitude ∼20 km/s) is directed within 15○ about the orbital plane. In addition to natal kick, we also discuss the influence of tidal interaction and the adopted common envelope λce parameter prescription on the evolution of Gaia BH-like binaries. We follow the subsequent evolution of the binaries, once formed as Gaia BH1 and Gaia BH2 systems, to investigate their connection with the low-mass X-ray binary population.

Correction to: Three-body binary formation in clusters: analytical theory

Correction to: Three-body binary formation in clusters: analytical theory

Are all models wrong? Falsifying binary formation models in gravitational-wave astronomy using exceptional events

Abstract As the catalogue of gravitational-wave transients grows, several entries appear ‘exceptional’ within the population. Tipping the scales with a total mass of ∼150M⊙, GW190521 likely contained black holes in the pair-instability mass gap. The event GW190814, meanwhile, is unusual for its extreme mass ratio and the mass of its secondary component. A growing model-building industry has emerged to provide explanations for such exceptional events, and Bayesian model selection is frequently used to determine the most informative model. However, Bayesian methods can only take us so far. They provide no answer to the question: does our model provide an adequate explanation for exceptional events in the data? If none of the models we are testing provide an adequate explanation, then it is not enough to simply rank our existing models—we need new ones. In this paper, we introduce a method to answer this question with a frequentist p-value. We apply the method to different models that have been suggested to explain the unusually massive event GW190521: hierarchical mergers in active galactic nuclei and globular clusters. We show that some (but not all) of these models provide adequate explanations for exceptionally massive events like GW190521.

Driving Forces in the Formation of Biocondensates of Highly Charged Proteins: A Thermodynamic Analysis of the Binary Complex Formation.

A thermodynamic analysis of the binary complex formation of the highly positively charged linker histone H1 and the highly negatively charged chaperone prothymosin α (ProTα) is detailed. ProTα and H1 have large opposite net charges (-44 and +53, respectively) and form complexes at physiological salt concentrations with high affinities. The data obtained for the binary complex formation are analyzed by a thermodynamic model that is based on counterion condensation modulated by hydration effects. The analysis demonstrates that the release of the counterions mainly bound to ProTα is the main driving force, and effects related to water release play no role within the limits of error. A strongly negative Δcp (=-0.87 kJ/(K mol)) is found, which is due to the loss of conformational degrees of freedom.

Functional modulation of RAGE activation by multimeric S100B using single-domain antibodies.

S100B is a multifunctional protein primarily found in the brain, where it plays crucial roles in cell proliferation, differentiation, and survival. It has intra- and extracellular functions and, depending on S100B levels, can exhibit both neurotrophic and neurotoxic activities, both mediated by the receptor for advanced glycation end products (RAGE). Here, we report the discovery and characterization of nanobodies (Nbs) targeting dimeric and tetrameric S100B, which are the two most abundant oligomeric functional forms of the protein, aiming to modulate S100B-mediated RAGE activation. Two Nbs were selected for detailed structural and functional studies, and found to bind tetrameric S100B with high affinity, as determined by biolayer interferometry analysis and SEC-stable binary complex formation. Structural and docking analyses revealed preferential contact sites of Nbs with S100B regions implicated in interactions with RAGE, namely residues at the interfacial cleft on dimeric S100B and the at hydrophobic cleft formed by the association of two homodimeric units in the tetramer. In accordance, assays in SH-SY5Y cells showed that Nbs modulate the RAGE-mediated neurotrophic activity of S100B by hindering its functional interactions with the receptor. Biolayer interferometry competition assays between tetrameric S100B and the RAGE-VC1 domain, confirmed that Nbs selectively block S100B-mediated RAGE engagement, in agreement with cell activation experiments. These findings highlight Nbs as powerful tools for elucidating molecular and cellular mechanisms through the modulation of S100B and RAGE functions, inspiring potential therapeutic applications.

Dual Active Galactic Nuclei: Precursors of Binary Supermassive Black Hole Formation and Mergers

The presence of dual active galactic nuclei (AGNs) on scales of a few tens of kiloparsecs can be used to study merger-induced accretion on supermassive black holes (SMBHs) and offer insights about SMBH mergers, using dual AGNs as merger precursors. This study uses the Romulus25 cosmological simulation to investigate the properties and evolution of dual AGNs. We first analyze the properties of AGNs (L bol > 1043 erg s−1) and their neighboring SMBHs (any SMBHs closer than 30 pkpc to an AGN) at z ≤ 2. This is our underlying population. We then applied the luminosity threshold of L bol > 1043 erg s−1 to the neighboring SMBHs thereby identifying dual and multiple AGNs. Our findings indicate an increase in the number of both single and dual AGNs from lower to higher redshifts. We also find that the number of dual AGNs with separations of 0.5–4 kpc is twice the number of duals with separations of 4–30 kpc. All dual AGNs in our sample resulted from major mergers. Compared to single AGNs, duals have a lower black hole-to-halo mass ratio. We found that the properties of dual AGN host halos, including halo mass, stellar mass, star formation rate, and gas mass, are generally consistent with those of single AGN halos, albeit tending toward the higher end of their respective property ranges. Our analysis uncovered a diverse array of evolutionary patterns among dual AGNs, including rapidly evolving systems, slower ones, and instances where SMBH mergers are ineffective.

Enhancing the Segmentation Accuracy of the Otsu Method for Calculating Blood Vessel Rupture Volumes in CT-Scan Images

The precise quantification of cerebral hemorrhage volume assumes paramount significance, given its consequential impact on subsequent medical interventions. While antecedent scholarly endeavors have undertaken cerebral hemorrhage volume computations, the attendant accuracy remains amenable to refinement. The main contribution to this research is the development of a rectangle algorithm using the Otsu method, which can be used to calculate the total volume of brain hemorrhage in CT-Scan images of the human brain. The present investigation seeks to augment the segmentation paradigm inherent to the Otsu method, thereby advancing the precision of cerebral hemorrhage volume assessments. The Otsu method is conceived with the purpose of automating the segmentation of the hemorrhagic domain through the determination of threshold values. The refinement of the Otsu method’s accuracy is effectuated by the formulation of an algorithm aimed at maximizing the mean discrepancy between object and background intensities within the object image, predicated upon the ascertained threshold values. These determined thresholds subsequently govern the transformation of grayscale images into binary format, achieved through the quotient of the threshold value and the mean variance, thereby amplifying segmentation precision. The incorporation of variance and mean values in the binarization of grayscale images affords adaptability in threshold modulation commensurate with the intensity spectrum of the image. The research corpus leverages CT-Scan images sourced from RSUP M. Djamil Padang, West Sumatra, encompassing a compendium of 100 image slices culled from a quintet of patients. Empirical findings attest to the fortification of the Otsu method in the segmentation milieu, substantiating the augmentation of threshold value accuracy. This enhancement is conspicuously manifest in the outcomes of segmentation tests, underscoring the superior efficacy of the Otsu method in discerning between objects and backgrounds. The corollary effect is a discernibly more accurate computation of volumes employing the Otsu-T methodology. The import of this research rests in its successful establishment of automated threshold values and the concomitant elevation of segmentation precision.

Temporal and geogrpahic trends in female representation within European cardiovascular imaging among 13,436 individuals associated with EACVI

Abstract Introduction Women are under-represented in cardiology trial enrolment, specialty training, faculty, scientific authorship and board membership in cardiology journals and societies. An EACVI Task Force on Women in Cardiovascular Imaging aims to promote women’s representation and leadership, but data is lacking in this area. Purpose To characterise the representation of women in cardiovascular imaging within Europe and examine temporal and geographic trends. Methods We scraped publicly available name data from over 100 online sources including EACVI taskforces, committees, research project members, consensus and position paper authors, board membership and past presidents alongside members of affiliated cardiovascular imaging national societies and working groups. We also included names from EACVI or national accreditation records for cardiac imaging. We recorded data on country location and year of affiliation. We defined gender in a binary manner as either male or female. The previously validated artificial intelligence (AI) system Namsor assigned gender based on name morphology and geolocation data. We pre-set a confidence of gender-name matching of 95%. Results The AI was able to assign gender at 95% confidence to 12,643/13,436 (94.1%) names. The overall number of names assigned female gender was 5903/12643 (46.7%), rejecting the null hypothesis that gender was equally distributed (i.e. 50% female) [p<0.0001]. Among the 9712 individuals with year of affiliation we observed female representation to increase over time: 1989-2000 4/18 (22.2%), 2001-2004 107/287 (37.8%) 2005-2009 77/170 (45.3%), 2010-2014 109/203 (53.7%), 2015-2019 1063/2022 (51.3%) and 2020-2024 3352/3064 (52.2%) (Cochran-Armitage trend test 24.196 [p<0.0001]) (Figure 1). Female representation was lower in countries outside of Europe, compared to within Europe; 740/2654 (27.9%) vs. 5163/9989 (51.7%) [p<0.0001]. The lowest rate of female representation was in Saudia Arabia (15.1%), the highest in Lithuania (83.3%). Figure 2 displays a choropleth of gender representation (%) between European countries with n>20. Conclusion(s) There are significant limitations in this form of analysis, including that we have arbritarily defined gender in a binary format, thereby excluding individuals who do not identify with such a social construct. It is also likely that the excluded names based on the 95% confidence of the AI software disproportionately represents individuals from ethnic minorities. However, our data provides a basic understanding of the representation of women in European cardiovascular imaging over time and between countries. We observed a trend of increasing female participation but with substantial variation between countries both inside and outside of Europe. This data may be useful to refine and direct efforts to improve female representation in areas in which it is needed most.

The Role of Fairness for Accepting Stricter Carbon Taxes in Sweden

Carbon taxes are considered to be an efficient method to reduce greenhouse gas emissions; however, such taxes are generally unpopular, partly because they are seen as unfair. To explore if public acceptance of a stricter carbon tax in Sweden can be enhanced, this study investigates the effectiveness of three different policy designs, addressing collective and personal distributional consequences and promoting procedural aspects (democratic influence). A large-scale (n = 5200) survey is applied, combining a traditional multi-category answer format with a binary choice format. The results show that support for higher carbon taxation can be enhanced if tax revenues are redistributed to affected groups. Policies with collective justice framings can change the attitudes of individuals who express antagonistic attitudes to increased carbon taxation and influence groups comparably more affected by carbon taxes, such as rural residents, low-income groups, and people who are driving long distances. Policy designs addressing collective distributional consequences are, however, less effective on individuals expressing right-leaning ideological views and low environmental concern. Policies addressing personal distributional outcomes, or perceptions of procedural injustice, had no significant effect on policy acceptance.

The Heavier the Faster: A Subpopulation of Heavy, Rapidly Spinning and Quickly Evolving Binary Black Holes

Abstract The spins of binary black holes (BBHs) measured from gravitational waves contain valuable information about their formation pathways. In this study, we propose a new quantity, the “dimensionless net spin” (χ N), which relates to the sum of the angular momenta of the component black holes (BHs) in the system, offering a novel perspective for exploring the origins of BBHs. Through hierarchical Bayesian inference on χ N, we find strong evidence that its distribution is better described by two Gaussian components rather than one, and their branching ratios vary with total mass and redshift: there is a narrow peak at χ N ∼ 0.15 and an extended peak at χ N ∼ 0.3–0.6. The rapidly spinning systems likely dominate the high-mass end of the population and evolve with redshift more quickly. These findings present new challenges to the field binary formation scenario and suggest that dynamical processes may play a key role in the formation of high total mass BBHs.

Efficient Storage and Analysis of Genomic Data: A k-mer Frequency Mapping and Image Representation Method.

k-mer frequencies are crucial for understanding DNA sequence patterns and structure, with applications in motif discovery, genome classification, and short read assembly. However, the exponential increase in the dimension of frequency tables with increasing k-mer length poses storage challenges. In this study, we present a novel method for compressing k-mer data without information loss, aiming to optimize storage and analysis processes. We employed Chaos Game Representation (CGR) to map k-mers to coordinates and used these components to generate raster images of k-mers. The CGR maps were partitioned and labeled based on substrings, with each substring mapped to a subframe, creating a fractal-like structure. The entire k-mer frequency set of each genomic sequence was represented as a single image, with each pixel corresponding to a specific k-mer and its occurrence. This approach reduced file size by up to 16-fold compared to plain text and 3-fold compared to binary format. Furthermore, we demonstrated the feasibility of performing alignment-free similarity analyses on images derived from k-mer frequencies of whole genome sequences from 14 plant species. Our results highlight the potential of this method as a fast and efficient tool for accessing, processing, and analyzing large biological sequence datasets, enabling the retrieval of k-mer frequencies and image reconstruction.

Structures of a DNA Polymerase Caught while Incorporating Responsive Dual-Functional Nucleotide Probes.

Functionalizing nucleic acids using DNA polymerases is essential in biophysical and biotechnology applications. This study focuses on understanding how DNA polymerases recognize and incorporate nucleotides with diverse chemical modifications, aiming to develop advanced nucleotide probes. We present the crystal structures of ternary complexes of Thermus aquaticus DNA polymerase (KlenTaq) with C5-heterocycle-modified environment-sensitive 2'-deoxyuridine-5'-triphosphate (dUTP) probes. These nucleotides include SedUTP, BFdUTP and FBFdUTP, which bear selenophene, benzofuran and fluorobenzofuran, respectively, at the C5 position of uracil, and exhibit high conformational sensitivity. SedUTP and FBFdUTP serve as dual-app probes, combining a fluorophore with X-ray anomalous scattering Se or 19F NMR labels. Our study reveals that the size of the heterocycle influences how DNA polymerase families A and B incorporate these modified nucleotides during single nucleotide incorporation and primer extension reactions. Remarkably, FBFdUTP's responsiveness enabled real-time monitoring of the binary complex formation and polymerase activity through fluorescence and 19F NMR. Comparative analysis of incorporation profiles, fluorescence, 19F NMR data, and crystal structures of ternary complexes highlights the enzyme's plasticity. Key insights are provided into the role of gatekeeper amino acids (Arg660 and Arg587) in accommodating and processing these modified substrates, offering a structural basis for next-generation nucleotide probe development.

Structures of a DNA Polymerase Caught while Incorporating Responsive Dual‐Functional Nucleotide Probes

Functionalizing nucleic acids using DNA polymerases is essential in biophysical and biotechnology applications. This study focuses on understanding how DNA polymerases recognize and incorporate nucleotides with diverse chemical modifications, aiming to develop advanced nucleotide probes. We present the crystal structures of ternary complexes of Thermus aquaticus DNA polymerase (KlenTaq) with C5‐heterocycle‐modified environment‐sensitive 2′‐deoxyuridine‐5′‐triphosphate (dUTP) probes. These nucleotides include SedUTP, BFdUTP and FBFdUTP, which bear selenophene, benzofuran and fluorobenzofuran, respectively, at the C5 position of uracil, and exhibit high conformational sensitivity. SedUTP and FBFdUTP serve as dual‐app probes, combining a fluorophore with X‐ray anomalous scattering Se or 19F NMR labels. Our study reveals that the size of the heterocycle influences how DNA polymerase families A and B incorporate these modified nucleotides during single nucleotide incorporation and primer extension reactions. Remarkably, FBFdUTP's responsiveness enabled real‐time monitoring of the binary complex formation and polymerase activity through fluorescence and 19F NMR. Comparative analysis of incorporation profiles, fluorescence, 19F NMR data, and crystal structures of ternary complexes highlights the enzyme's plasticity. Key insights are provided into the role of gatekeeper amino acids (Arg660 and Arg587) in accommodating and processing these modified substrates, offering a structural basis for next‐generation nucleotide probe development.

EEG-based optimization of eye state classification using modified-BER metaheuristic algorithm

This article introduces the Modified Al-Biruni Earth Radius (MBER) algorithm, which seeks to improve the precision of categorizing eye states as either open (0) or closed (1). The evaluation of the proposed algorithm was assessed using an available EEG dataset that applied preprocessing techniques, including scaling, normalization, and elimination of null values. The MBER algorithm’s binary format is specifically designed to select features that can significantly enhance the accuracy of classification. The proposed algorithm and competing ones, namely, Al-Biruni Earth Radius (BER), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WAO), Grey Wolf Optimizer (GWO) and Genetic Algorithm (GA) were evaluated using predefined sets of assessment criteria. The statistical analysis employed the ANOVA and Wilcoxon signed-rank tests and assessed the effectiveness and significance of the proposed algorithm compared to the other five algorithms. Furthermore, A series of visual depictions were presented to validate the effectiveness and robustness of the proposed algorithm. Thus, the MBER algorithm outperformed the other optimizers on the majority of the unimodal benchmark functions due to these considerations. Different ML models were used for classification, e.g., DT, RF, KNN, SGD, GNB, SVC, and LR. The KNN model achieved the highest values of Precision (PPV) (0.959425), Negative Predictive Value (NPV) (0.964969), FScore (0.963431), accuracy (0.9612), Sensitivity (0.970578) and Specificity (0.949711). Thus, KNN serves as a fitness function and is optimized by the utilization of Modified Al-Biruni earth radius (MBER). Finally, the accuracy of eye state classification achieved 96.12% using the proposed algorithm.

Efficient indexing and querying of annotations in a pangenome graph.

The current reference genome is the backbone of diverse and rich annotations. Simple text formats, like VCF or BED, have been widely adopted and helped the critical exchange of genomic information. There is a dire need for tools and formats enabling pangenomic annotation to facilitate such enrichment of pangenomic references. The Graph Alignment Format (GAF) is a text format, tab-delimited like BED/VCF files, which was proposed to represent alignments. GAF could also be used to store paths representing annotations in a pangenome graph, but there are no tools to index and query them efficiently. Here, we present extensions to vg and HTSlib that provide efficient sorting, indexing, and querying for GAF files. With this approach, annotations overlapping a subgraph can be extracted quickly. Paths are sorted based on the IDs of traversed nodes, compressed with BGZIP, and indexed with HTSlib/tabix via our extensions for the GAF format. Compared to the binary GAM format, GAF files are easier to edit or inspect because they are plain text, and we show that they are twice as fast to sort and half as large on disk. In addition, we updated vg annotate, which takes BED or GFF3 annotation files relative to linear sequences and projects them into the pangenome. It can now produce GAF files representing these annotations' paths through the pangenome. We showcase these new tools on several applications. We projected annotations for all Human Pangenome Reference Consortium Year 1 haplotypes, including genes, segmental duplications, tandem repeats and repeats annotations, into the Minigraph-Cactus pangenome (GRCh38-based v1.1). We also projected known variants from the GWAS Catalog and expression QTLs from the GTEx project into the pangenome. Finally, we reanalyzed ATAC-seq data from ENCODE to demonstrate what a coverage track could look like in a pangenome graph. These rich annotations can be quickly queried with vg and visualized using existing tools like the Sequence Tube Map or Bandage.

Research on high voltage circuit breaker multi-sensor signal feature selection method based on GA-Kmeans algorithm

Abstract Currently, in the research on fault information of high-voltage circuit breakers (HVCBs) based on multi-sensor data, issues such as shallow feature assessment and unclear feature selection rules exist, leading to a decrease in fault identification accuracy due to redundant characteristics. To address this, this paper proposes a novel feature selection method based on GA-Kmeans. This method encodes the original feature space into binary format and employs the clustering accuracy of the Kmeans model as the fitness function to obtain a high-quality feature subset that maximally represents and distinguishes faults. By combining different feature selection methods with fault diagnosis models, six typical application scenarios are constructed. Results indicate that compared to traditional methods such as Relief-F, KPCA, GA-SVM for feature selection, and SVM for fault diagnosis, the proposed GA-Kmeans method reduces the dimensionality of the original feature space and employs the Kmeans clustering algorithm as the diagnostic model, achieving a final diagnostic accuracy of 95.29%. This method outperforms others, with a 37.24% higher diagnostic accuracy than SVM under the original feature space, and a decrease of 47.90% in standard deviation. This validates the necessity of feature selection and the superiority of the proposed method, providing a reliable and stable diagnostic basis for subsequent mechanical fault diagnosis of HVCBs.