Large Domain Research Articles

When one logic is not enough: Integrating first-order annotations in OWL ontologies

In ontology development, there is a gap between domain ontologies which mostly use the Web Ontology Language, OWL, and foundational ontologies written in first-order logic, FOL. To bridge this gap, we present Gavel, a tool that supports the development of heterogeneous ‘FOWL’ ontologies that extend OWL with FOL annotations, and is able to reason over the combined set of axioms. Since FOL annotations are stored in OWL annotations, FOWL ontologies remain compatible with the existing OWL infrastructure. We show that for the OWL domain ontology OBI, the stronger integration with its FOL top-level ontology BFO via our approach enables us to detect several inconsistencies. Furthermore, existing OWL ontologies can benefit from FOL annotations. We illustrate this with FOWL ontologies containing mereotopological axioms that enable additional, useful inferences. Finally, we show that even for large domain ontologies such as ChEBI, automatic reasoning with FOL annotations can be used to detect previously unnoticed errors in the classification.

Novel role of thermomechanical grain boundary engineering in the microstructure evolution of austenitic stainless steel

The effect of special grain boundary development via the grain boundary engineering process (GBE) was explored in a bimodal microstructured 316L austenitic stainless steel with an average grain size of 1.92 μm. The GBE process was carried out by the rolling-annealing method via two routes of low and medium applied strain, followed by a short annealing period in a single-step and iterative manner. The grain boundary character distribution was obtained by Electron Backscatter Diffraction (EBSD) analysis, and the intergranular corrosion resistance and the tensile behavior of the samples were examined. Microstructural characterization showed that applying low strain repetitively increased the coincidence site lattice (CSL) and Σ3 boundaries percentage and created large twin-related domains (TRD). The reduced sensitization was attributed to a high proportion of CSLs and large-sized TRDs by applying a low-strain route. In the early stages of the low-strain route, the grain boundary character distribution showed a high number of primary twin nuclei in coarse grains and a continuous network of single twin nuclei in smaller grains, creating a high percentage of Σ3-grain boundaries. The low applied strain and the absence of the necessary driving force for the recrystallization and GBs migration led to the formation of twin nuclei, which would assist with the reduction of microstructure energy. A high percentage of Σ3 boundaries and an increase in the percentage of triple points consisting of low energy boundaries were found to be influential factors in increasing elongation.

Raster approach to modelling the failure of arbitrarily inclined interfaces with structured meshes

This paper presents an approach to evaluate the failure of arbitrarily inclined interfaces using FE models with structured spatial discretization, providing accurate prediction of crack propagation along paths known a priori that are not constrained to the element boundaries. The combination of algorithms for the generation of structured discretization of representative polycrystalline microstructures with novel cohesive element formulations allow modelling the failure of complex topologies along rasterised boundaries, with noticeably higher computational efficiency and comparable accuracy. Two formulations of raster cohesive elements are presented, adopting either elastic-brittle or Tvergaard–Hutchinson traction separation laws. The formulations proposed are first validated comparing the failure of the interface within bi-crystal structures discretised using hexahedral elements either within a structured mesh (i.e. with rasterised boundaries) or an unstructured mesh (i.e. with planar boundary). Subsequently, the effectiveness of the formulations is demonstrated comparing the inter-granular crack propagation within complex polycrystalline microstructures. The behaviour of the novel cohesive element formulation in structured meshes consisting of regular hexahedral elements is in excellent agreement with the deformation and failure of classic cohesive element formulations placed along the planar boundaries of unstructured meshes consisting of tetrahedral elements. The higher computational cost of the raster cohesive elements is more than compensated by the increase in computational efficiency of structured meshes when compared to unstructured meshes, leading to a reduction of the simulation time of up to over 200 times for the simulations presented in the paper, thus allowing the simulation of large domains.

A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms.

Traditional gene set enrichment analysis falters when applied to large genomic domains, where neighboring genes often share functions. This spatial dependency creates misleading enrichments, mistaking mere physical proximity for genuine biological connections. Here we present Spatial Adjusted Gene Ontology (SAGO), a novel cyclic permutation-based approach, to tackle this challenge. SAGO separates enrichments due to spatial proximity from genuine biological links by incorporating the genes' spatial arrangement into the analysis. We applied SAGO to various datasets in which the identified genomic intervals are large, including replication timing domains, large H3K9me3 and H3K27me3 domains, HiC compartments and lamina-associated domains (LADs). Intriguingly, applying SAGO to prostate cancer samples with large copy number alteration (CNA) domains eliminated most of the enriched GO terms, thus helping to accurately identify biologically relevant gene sets linked to oncogenic processes, free from spatial bias.

Amphoteric Chelating Ultrasmall Colloids for FAPbI3 Nanodomains Enable Efficient Near-Infrared Light-Emitting Diodes.

Perovskite light-emitting diodes (PeLEDs) are the next promising display technologies because of their high color purity and wide color gamut, while two classical emitter forms, i.e., polycrystalline domains and quantum dots, are encountering bottlenecks. Weak carrier confinement of large polycrystalline domains leads to inadequate radiative recombination, and surface ligands on quantum dots are the main annihilation sites for injected carriers. Here, pinpointing these issues, we screened out an amphoteric agent, namely, 2-(2-aminobenzoyl)benzoic acid (2-BA), to precisely control the in situ growth of FAPbI3 (FA: formamidine) nanodomains with enhanced space confinement, preferred crystal orientation, and passivated trap states on the transport-layer substrate. The amphoteric 2-BA performs bidentate chelating functions on the formation of ultrasmall perovskite colloids (<1 nm) in the precursor, resulting in a smoother FAPbI3 emitting layer. Based on monodispersed and homogeneous nanodomain films, a near-infrared PeLED device with a champion efficiency of >22% plus enhanced T80 operational stability was achieved. The proposed perovskite nanodomain film tends to be a mainstream emitter toward the performance breakthrough of PeLED devices covering visible wavelengths beyond infrared.

Machine learning framework for predicting cytotoxicity and identifying toxicity drivers of disinfection byproducts

Drinking water disinfection can result in the formation disinfection byproducts (DBPs, > 700 have been identified to date), many of them are reportedly cytotoxic, genotoxic, or developmentally toxic. Analyzing the toxicity levels of these contaminants experimentally is challenging, however, a predictive model could rapidly and effectively assess their toxicity. In this study, machine learning models were developed to predict DBP cytotoxicity based on their chemical information and exposure experiments. The Random Forest model achieved the best performance (coefficient of determination of 0.62 and root mean square error of 0.63) among all the algorithms screened. Also, the results of a probabilistic model demonstrated reliable model predictions. According to the model interpretation, halogen atoms are the most prominent features for DBP cytotoxicity compared to other chemical substructures. The presence of iodine and bromine is associated with increased cytotoxicity levels, while the presence of chlorine is linked to a reduction in cytotoxicity levels. Other factors including chemical substructures (CC, N, CN, and 6-member ring), cell line, and exposure duration can significantly affect the cytotoxicity of DBPs. The similarity calculation indicated that the model has a large applicability domain and can provide reliable predictions for DBPs with unknown cytotoxicity. Finally, this study showed the effectiveness of data augmentation in the scenario of data scarcity.

Towards limited-domain full waveform ambient noise inversion

SUMMARY Ambient noise tomography is a well-established tomographic imaging technique but the effect that spatially variable noise sources have on the measurements remains challenging to account for. Full waveform ambient noise inversion has emerged recently as a promising solution but is computationally challenging since even distant noise sources can have an influence on the interstation correlation functions and therefore requires a prohibitively large numerical domain, beyond that of the tomographic region of interest. We investigate a new strategy that allows us to reduce the simulation domain while still being able to account for distant contributions. To allow nearby numerical sources to account for distant true sources, we introduce correlated sources and generate a time-dependent effective source distribution at the boundary of a small region of interest that excites the correlation wavefield of a larger domain. In a series of 2-D numerical simulations, we demonstrate that the proposed methodology with correlated sources is able to successfully represent a far-field source that is simultaneously present with nearby sources and the methodology also successfully results in a robustly estimated noise source distribution. Furthermore, we show how beamforming results can be used as prior information regarding the azimuthal variation of the ambient noise sources in helping determine the far-field noise distribution. These experiments provide insight into how to reduce the computational cost needed to perform full waveform ambient noise inversion, which is key to turning it into a viable tomographic technique. In addition, the presented experiments may help reduce source-induced bias in time-dependent monitoring applications.

A forced Boussinesq model with a sponge layer

A well-known reduced model employed to study the wave dynamics is the Boussinesq model. Despite being extensively studied, to our knowledge, there is no research available on a Boussinesq model featuring a sponge layer. Therefore, in this work, we present a Boussinesq model with a sponge layer. Furthermore, we carry out a numerical investigation to explore the advantages and limitations of the proposed model. For this purpose, we compare the numerical solutions of the model with and without the sponge in certain scenarios. The numerical solutions are computed by a pseudospectral method. Our results show that the Boussinesq model with a sponge layer is numerically stable and advantageous because it is able to absorb low-amplitude waves, allowing it to run the numerical simulations for long periods of time without requiring a large spatial domain, but it is not able to absorb high-amplitude waves.

Fabrication uncertainty guided design optimization of a photonic crystal cavity by using Gaussian processes

We present a fabrication uncertainty aware and robust design optimization approach that can be used to obtain robust design estimates for nonlinear, nonconvex, and expensive model functions. It is founded on Gaussian processes and a Monte Carlo sampling procedure, and assumes knowledge about the uncertainties associated with a manufacturing process. The approach itself is iterative. First, a large parameter domain is sampled in a coarse fashion. This coarse sampling is used primarily to determine smaller candidate regions to investigate in a second, more refined sampling pass. This finer step is used to obtain an estimate of the expected performance of the found design parameter under the assumed manufacturing uncertainties. We apply the presented approach to the robust optimization of the Purcell enhancement of a photonic crystal nanobeam cavity. We obtain a predicted robust Purcell enhancement of F¯P≈3.6. For comparison we also perform an optimization without robustness. We find that an unrobust optimum of FP≈256.5 dwindles to only F¯P≈0.7 when fabrication uncertainties are taken into account. We thus demonstrate that the presented approach is able to find designs of significantly higher performance than those obtained with conventional optimization.

Nearshore tsunami amplitudes across the Maldives archipelago due to worst-case seismic scenarios in the Indian Ocean

Abstract. The Maldives face the threat of tsunamis from a multitude of sources. However, the limited availability of critical data, such as bathymetry (a recurrent problem for many island nations), has meant that the impact of these threats has not been studied at an island scale. Conducting studies of tsunami propagation at the island scale but across multiple atolls is also a challenging task due to the large domain and high resolution required for modelling. Here we use a high-resolution bathymetry dataset of the Maldives archipelago, as well as corresponding high numerical model resolution, to carry out a scenario-based tsunami hazard assessment for the entire Maldives archipelago to investigate the potential impact of plausible far-field tsunamis across the Indian Ocean at the nearshore island scales across the atolls. The results indicate that the bathymetry of the atolls, which are characterized by very steep boundaries offshore, is extremely efficient in absorbing and redirecting incoming tsunami waves. Results also highlight the importance that local effects have in modulating tsunami amplitude nearshore, including the location of the atoll in question, the location of a given island within the atoll, and the distance of that island to the reef, as well as a variety of other factors. We also find that the refraction and diffraction of tsunami waves within individual atolls contribute to the maximum tsunami amplitude patterns observed across the islands in the atolls. The findings from this study contribute to a better understanding of tsunamis across complex atoll systems and will help decision and policy makers in the Maldives assess the potential impact of tsunamis across individual islands. An online tool is provided which presents users with a simple interface, allowing the wider community to browse the simulation results presented here and assess the potential impact of tsunamis at the local scale.

Planar wall plumes bounded by vertical and inclined surfaces

Planar wall plumes are gravity-driven flows where a fluid of lower (or higher) density than the ambient rises (or lowers) along a vertical or inclined wall. This study investigates planar wall plumes at five different wall slopes, ranging from a vertical wall (θ=90°) to a shallow inclination of θ=3°, using highly resolved direct numerical simulations. The three-dimensional turbulent structure of these supercritical flows is investigated in detail along with the streamwise evolution of the depth-averaged quantities. Simulations were performed in very large domains in order to focus attention on the behavior of the plumes in the near self-similar state, far downstream of the inlet. In the self-similar state, key quantities such as the entrainment rate, the basal drag coefficient, the Richardson number (or equivalently the Froude number), and the shape factors reach constant values, which dependent only on the slope. The present simulations, along with earlier results for subcritical currents at shallower slopes, provide a complete description of this dependency.

Non-reflective hard source method for multiple physically extended sources and scattering bodies

In this paper, we focus on methodologies to inject a noise source in a numerical model of noise propagation in confined domains. This is a problem of primary importance when dealing with propagation of fluid-dynamic induced noise in confined basins, like ships at sea or wind farms. We first assess the performance of the literature hard source (HS) and transparent source methods; successively, we propose a novel method named the non-reflective HS (NRHS) method. It takes advantage of the linearity of the equation governing the propagation of acoustic waves in fluids and is based on the decomposition of the total signal in the sum of direct and reflected signals. It presents the advantages of the hard source method removing the main drawback consisting of the well-known problem of spurious reflections. To check the reliability of the HS vs the NRHS, a non-dimensional parameter (the encumbrance) has been defined, which gives a measure of the extension of the generation domain with respect to the propagation domain in relation to the principal wavelength of the acoustic waves and the presence of reflecting surfaces. The method herein developed gives accurate results in the case of a single-point source, where the literature methods behave well; more importantly, the NRHS method maintains its own accuracy when a noise source needs to be represented by a large number of points in space, situations of very practical importance where the standard methods may exhibit inaccuracy. This is a point of importance since the use of large generation domains is in favor of the accuracy of the source characterization, which can exhibit a complex directivity. The new method has been tested in a number of archetypal situations characterized by the presence of a reflecting plane, a scattering body close to the source location, and two sources placed side by side. In all cases, the method has shown its own superiority with respect to the standard HS method, still preserving the flexibility and simplicity of the latter.

Glycine Receptor β-Targeting Autoantibodies Contribute to the Pathology of Autoimmune Diseases.

Stiff-person syndrome (SPS) and progressive encephalomyelitis with rigidity and myoclonus (PERM) are rare neurologic disorders of the CNS. Until now, exclusive GlyRα subunit-binding autoantibodies with subsequent changes in function and surface numbers were reported. GlyR autoantibodies have also been described in patients with focal epilepsy. Autoimmune reactivity against the GlyRβ subunits has not yet been shown. Autoantibodies against GlyRα1 target the large extracellular N-terminal domain. This domain shares a high degree of sequence homology with GlyRβ making it not unlikely that GlyRβ-specific autoantibody (aAb) exist and contribute to the disease pathology. In this study, we investigated serum samples from 58 patients for aAb specifically detecting GlyRβ. Studies in microarray format, cell-based assays, and primary spinal cord neurons and spinal cord tissue immunohistochemistry were performed to determine specific GlyRβ binding and define aAb binding to distinct protein regions. Preadsorption approaches of aAbs using living cells and the purified extracellular receptor domain were further used. Finally, functional consequences for inhibitory neurotransmission upon GlyRβ aAb binding were resolved by whole-cell patch-clamp recordings. Among 58 samples investigated, cell-based assays, tissue analysis, and preadsorption approaches revealed 2 patients with high specificity for GlyRβ aAb. Quantitative protein cluster analysis demonstrated aAb binding to synaptic GlyRβ colocalized with the scaffold protein gephyrin independent of the presence of GlyRα1. At the functional level, binding of GlyRβ aAb from both patients to its target impair glycine efficacy. Our study establishes GlyRβ as novel target of aAb in patients with SPS/PERM. In contrast to exclusively GlyRα1-positive sera, which alter glycine potency, aAbs against GlyRβ impair receptor efficacy for the neurotransmitter glycine. Imaging and functional analyses showed that GlyRβ aAbs antagonize inhibitory neurotransmission by affecting receptor function rather than localization.

Functional bio-inspired hybrid fliers with separated ring and leading edge vortices.

Recent advances in passive flying systems inspired by wind-dispersed seeds contribute to increasing interest in their use for remote sensing applications across large spatial domains in the Lagrangian frame of reference. These concepts create possibilities for developing and studying structures with performance characteristics and operating mechanisms that lie beyond those found in nature. Here, we demonstrate a hybrid flier system, fabricated through a process of controlled buckling, to yield unusual geometries optimized for flight. Specifically, these constructs simultaneously exploit distinct fluid phenomena, including separated vortex rings from features that resemble those of dandelion seeds and the leading-edge vortices derived from behaviors of maple seeds. Advanced experimental measurements and computational simulations of the aerodynamics and induced flow physics of these hybrid fliers establish a concise, scalable analytical framework for understanding their flight mechanisms. Demonstrations with functional payloads in various forms, including bioresorbable, colorimetric, gas-sensing, and light-emitting platforms, illustrate examples with diverse capabilities in sensing and tracking.

A cardinal-based numerical method for fractional optimal control problems with Caputo–Katugampola fractional derivative in a large domain

In this paper, the piecewise Chebyshev cardinal functions (PCCFs) are handled to design a highly accurate direct method to solve a category of fractional optimal control problems (FOCPs) involving the Caputo–Katugampola fractional derivative (as a generalisation of the Caputo derivative) in a large domain. These cardinal functions have many useful features, such as cardinality, exponential accuracy and orthogonality. Notice that the exponential accuracy makes it possible to obtain an approximate solution with very high accuracy for the problem under consideration by applying only a small number of basis functions. In this regard, first, the ordinary and fractional integral matrices of the PCCFs are obtained to construct a direct method using them. Then, the constructed approach turns to solve the FOCP under consideration into deriving the solution of an algebraic system (by the aid of approximating the state and control variables based on the PCCFs). To show the validity of the established technique some illustrative examples are provided.

A Domain Adaptive Semantic Segmentation Method Using Contrastive Learning and Data Augmentation

For semantic segmentation tasks, it is expensive to get pixel-level annotations on real images. Domain adaptation eliminates this process by transferring networks trained on synthetic images to real-world images. As one of the mainstream approaches to domain adaptation, most of the self-training based domain adaptive methods focus on how to select high confidence pseudo-labels, i.e., to obtain domain invariant knowledge indirectly. A more direct means to explicitly align the data of the source and target domains globally and locally is lacking. Meanwhile, the target features obtained by traditional self-training methods are relatively scattered and cannot be aggregated in a relatively compact space. We offer an approach that utilizes data augmentation and contrastive learning in this paper to perform more effective knowledge migration with the basis of self-training. Specifically, the style migration and image mixing modules are first introduced for data augmentation to cope with the problem of large domain gaps in the source and target domains. To assure the aggregation of features from the same class and the discriminability of features from other classes during the training process, we propose a multi-scale pixel-level contrastive learning module. What’s more, a cross-scale contrastive learning module is proposed to help each level of the model gain the capability to obtain more information on the basis of its own original task. Experiments show that our final trained model can effectively classify the images from target domain.

Effect of micronutrients, rhizobium, salicylic acid, and effective microorganisms in plant growth and yield characteristics of green gram [Vigna radiata (L.) Wilczek] in Rupandehi, Nepal

Nepal has a very diverse topography and ecosystem, with mountains in the north and lush plains in the south. Despite the diverse ecology, the production of green gram is still in its minority. This experiment was conducted to assess the effect of micronutrients (Zn, B, Mo, Co, and Mn), rhizobium, effective micro-organisms, and salicylic acid in plant growth, yield, and yield attributes of green gram [Vigna radiata (L.) Wilczek] in Rupandehi district of Nepal in March 2021. Pratikshya variety of green gram was used as a test crop. Different levels of ZnSO4 and Borax, Ammonium Molybdate, Cobalt Nitrate, MnSO4, effective microorganism, Mixture, Salicylic acid, and Rhizobia along with control constituted treatments. Various application methods were used for applying treatments including soil incorporation, seed priming, inoculation, and foliar application. The results revealed that leaf area index, number of branches, number of pods per plant, and yield were significantly different (P < 0.05). Among various treatments, the mixture was found most effective in the case of grain yield (1048.1 kg ha−1), stover yield (2472.7 kg ha−1), biological yield (3520.8 kg ha−1), harvest index (31.2%), and the number of primary branches (4.9). Likewise, the number of secondary branches (6.86) was better with Borax@10 kg ha−1. There was no significant difference in the plant height, number of pods per plant, pod length, pod weight, number of grains per pod, and test weight between different treatments. ZnSO4 @ 25 kg ha−1 was found to have an impact on the number of mature, immature, and total pods per plant. Overall, the study concluded that the mixture of all micronutrients performed better in terms of grain yield while zinc sulphate had great potential for plant growth parameters which could improve the farmers’ livelihood. It is recommended to conduct multi-location trials in a larger domain.

A new and promiscuous α/β hydrolase from Acinetobacter tandoii DSM 14970 T inactivates the mycotoxin ochratoxin A

The presence of ochratoxin A (OTA) in food and feed represents a serious concern since it raises severe health implications. Bacterial strains of the Acinetobacter genus hydrolyse the amide bond of OTA yielding non-toxic OTα and L-β-phenylalanine; in particular, the carboxypeptidase PJ15_1540 from Acinetobacter sp. neg1 has been identified as an OTA-degrading enzyme. Here, we describe the ability to transform OTA of cell-free protein extracts from Acinetobacter tandoii DSM 14970 T, a strain isolated from sludge plants, and also report on the finding of a new and promiscuous α/β hydrolase (ABH), with close homologs highly distributed within the Acinetobacter genus. ABH from A. tandoii (AtABH) exhibited amidase activity against OTA and OTB mycotoxins, as well as against several carboxypeptidase substrates. The predicted structure of AtABH reveals an α/β hydrolase core composed of a parallel, six-stranded β-sheet, with a large cap domain similar to the marine esterase EprEst. Further biochemical analyses of AtABH reveal that it is an efficient esterase with a similar specificity profile as EprEst. Molecular docking studies rendered a consistent OTA-binding mode. We proposed a potential procedure for preparing new OTA-degrading enzymes starting from promiscuous α/β hydrolases based on our results.Key points• AtABH is a promiscuous αβ hydrolase with both esterase and amidohydrolase activities• AtABH hydrolyses the amide bond of ochratoxin A rendering nontoxic OTα• Promiscuous αβ hydrolases are a possible source of new OTA-degrading enzymes

Engineering large nanoporous networks with size and shape selected by appropriate precursors

Large domains of two-dimensional supramolecular porous nanostructures are interesting for various applications from electronics to biology. Here, we investigate the formation of Cu-coordinated networks on Cu(111) using scanning tunneling microscopy and density functional theory (DFT). We consider two molecules with three pyridyl end groups connected to a central benzene ring by either one or two phenyl groups, namely 1,3,5-tris[4-(pyridin)phenyl]benzene (TPyPB) and 1,3,5-tris[4-(pyridin)-[1,1’-biphenyl]benzene (TPyPPB), respectively. Upon deposition of TPyPB at room temperature, a honeycomb nanostructure forms, which is stabilized by Cu adatoms, as previously seen. Upon deposition at 400 K, the growth dynamics change, and molecules become trapped in the hexagonal pores. In contrast, deposition of TPyPPB at room temperature leads to vitreous structures, which rearrange at 400 K forming a low-defect and extended ordered honeycomb phase, which is also stabilized only in the presence of Cu adatoms. The DFT calculations for both honeycomb phases show an impressive agreement with the experimental results, considering the size of such structures. After annealing at 420 K, a complex flower-like structure composed of a mix of two- and three-fold coordinated Cu centers emerges. Further annealing to above 420 K leads to another new phase composed of a high molecular density motif, the so-called diamond phase.

Identification of novel tail-anchored membrane proteins integrated by the bacterial twin-arginine translocase.

The twin-arginine protein transport (Tat) system exports folded proteins across the cytoplasmic membranes of prokaryotes and the energy transducing-membranes of plant thylakoids and mitochondria. Proteins are targeted to the Tat machinery by N-terminal signal peptides with a conserved twin-arginine motif, and some substrates are exported as heterodimers where the signal peptide is present on one of the partner proteins. A subset of Tat substrates is found in the membrane. Tat-dependent membrane proteins usually have large globular domains and a single transmembrane helix present at the N- or C-terminus. Five Tat substrates that have C-terminal transmembrane helices have previously been characterized in the model bacterium Escherichia coli. Each of these is an iron-sulfur cluster-containing protein involved in electron transfer from hydrogen or formate. Here we have undertaken a bioinformatic search to identify further tail-anchored Tat substrates encoded in bacterial genomes. Our analysis has revealed additional tail-anchored iron-sulfur proteins associated in modules with either a b-type cytochrome or a quinol oxidase. We also identified further candidate tail-anchored Tat substrates, particularly among members of the actinobacterial phylum, that are not predicted to contain cofactors. Using reporter assays, we show experimentally that six of these have both N-terminal Tat signal peptides and C-terminal transmembrane helices. The newly identified proteins include a carboxypeptidase and a predicted protease, and four sortase substrates for which membrane integration is a prerequisite for covalent attachment to the cell wall.