Sequence Distribution Research Articles

Protein sequence design on given backbones with deep learning.

Deep learning methods for protein sequence design focus on modeling and sampling the many- dimensional distribution of amino acid sequences conditioned on the backbone structure. To produce physically foldable sequences, inter-residue couplings need to be considered properly. These couplings are treated explicitly in iterative methods or autoregressive methods. Non-autoregressive models treating these couplings implicitly are computationally more efficient, but still await tests by wet experiment. Currently, sequence design methods are evaluated mainly using native sequence recovery rate and native sequence perplexity. These metrics can be complemented by sequence-structure compatibility metrics obtained from energy calculation or structure prediction. However, existing computational metrics have important limitations that may render the generalization of computational test results to performance in real applications unwarranted. Validation of design methods by wet experiments should be encouraged.

Fine-Tuning Gradient Copolymers with Diverse and Controlled Microstructure and Mechanical Properties via Monomer Sequence Distribution: An In Silico Study

Fine-Tuning Gradient Copolymers with Diverse and Controlled Microstructure and Mechanical Properties via Monomer Sequence Distribution: An In Silico Study

Some Properties of Deferred Nörlund I-Statistical Convergence in Probability, Mean, and Distribution for Sequences of Random Variables

This paper investigates the concept of deferred Nörlund I -statistical convergence in probability, mean of order r, distribution, and explores the relationships among these notions. We present a novel approach to deferred Nörlund I-statistical convergence, which allows for a deeper understanding of the convergence behavior in various contexts. We examine the convergence properties in terms of probability, mean of order r, and distribution, providing a comprehensive analysis of their interdependencies. Our findings contribute to the field of statistical convergence theory, shedding light on the deferred Nörlund I-statistical convergence and its connections with probability, mean of order r, and distribution.

Synthesis, kinetic study and characterization of C5‐dienes/styrene copolymers via living anionic polymerization in cyclopentyl methyl ether solvent

Abstract1,3‐Dienes/styrene sequence‐controlled copolymers are widely used as thermoplastic elastomers, transparent impact resin and synthetic rubber and other materials. In this work, the binary anionic copolymerization of styrene (S) and C5‐dienes including 1,3‐pentadiene (P, E/Z = 65/35) and isoprene (I) were studied in cyclopentyl methyl ether (CPME) ‘green’ solvent using n‐BuLi as initiator, and the effects of copolymerization monomer ratio and polar additive (PA) on the copolymerization kinetics and monomer sequence distributions were investigated. The kinetic analysis results showed that all copolymerization systems were the first‐order reaction and the C5‐dienes/S could be quantitatively consumed. The addition of S or I was conducive to the efficient conversion of P. Although the addition of PAs had little effect on the polymerization rate, it had a great influence on the microstructure and sequence distribution of the copolymer. 1H NMR tracking analysis showed that, for S/P copolymerization with different feeding ratios 1/3 < fP < 2/3, the instant composition FP in the copolymer remained relatively constant at 15% < FP < 35% when the monomer conversion rate was below 60%, and thus the inevitable formation of P microblocks in subsequent polymerization sequences was observed. Additionally, similar sequence distributions were obtained in the case of I/P copolymerization systems. By contrast, S/I copolymerization conformed to the typical random copolymerization pattern, and the copolymerization activity of S was slightly higher than that of the I in CPME. The use of strong PAs such as 2,2‐di(2‐tetrahydrofuran)propane directly resulted in a change of monomer sequence from a random pattern to a gradual block pattern. Moreover, the 3,4‐isoprene branch units were much more sensitive to solvent and PA than 1,2‐pentadiene units for C5‐dienes; also Fourier transform infrared and DSC analysis verified the microstructure and sequence analysis results mentioned above. In addition, the results of gel permeation chromatography showed that the copolymerization process in CPME had excellent controllable characteristics. © 2023 Society of Industrial Chemistry.

Non‐covalent Intramolecular Interactions Induced High‐Performance Terpolymer Donors

AbstractTernary polymerization are demonstrated as a feasible and successful method of optimizing absorption, energy level, and crystallinity by maintaining the excellent properties of a polymer matrix. However, the third unit inevitably interrupts the periodic sequence distribution of the ordering packing of conjugated backbones, and thus balancing the trade‐off between the advantages of the third component and the disruption caused by the nonperiodic sequence distribution remains a great challenge. Herein, two terpolymer donors L1 and L2 are developed by introducing diethyl‐5,5′“‐dibromo‐4,4′”‐bis(2‐ethylhexyl)‐[2,2′:5′,2′'‐terthiophene]‐3′,4′‐dicarboxylate (DDT) unit as the third component. Owing to the electron‐deficient ability and S···O non‐covalent intramolecular interactions of DDT, terpolymers L1 and L2 displays deeper energy levels, enhanced molecular rigidity, and planarity than PM6. After blending with L8‐BO, the L1‐based polymer solar cells exhibit well miscibility with L8‐BO, leading to a more well‐defined nanofibrous morphology, face‐on orientation, and a slight energy loss in the blend films. As a result, the optimized L1:L8‐BO‐based device achieves a record power conversion efficiency (PCE) as high as 18.75%. This work provides a feasible strategy to develop high‐performance polymer donors via utilizing S···O non‐covalent intramolecular interactions to improve the planarity of polymer donors.

Synthesis of bio-based polyesters from carvone-derived epoxides

Degradable polymers synthesized from biomasses have become increasingly appealing for their environmentally friendly and sustainable features. In this study, (R)-(−)-carvone, a natural monoterpene, and its hydrogenated derivative, (+)-dihydrocarvone, are oxidized to afford two epoxy compounds, termed as EK and MOO, respectively. The epoxides are subject to ring-opening copolymerization with cyclic anhydrides, including phthalic anhydride and cis-5-norbornene-exo-2,3-dicarboxylic anhydride, organocatalyzed by a phosphazene base. High or complete anhydride conversion can be reached at 100 °C when the epoxides are used in slight excesses. The resulting polyesters exhibit fully alternating sequence distribution, high glass transition temperature (108–142 °C), and two-step thermal degradation (above 200 °C) which is distinct from the polyesters derived from common epoxides. Compared with EK, MOO allows better controlled and distinctly higher molar mass (>10 kg mol−1), indicating much less profound (intramolecular) transesterification occurring on the polyester backbone. Most interestingly, the lactone moiety of MOO, generated together with the epoxide moiety by oxidation and previously shown polymerizable, stays intact during the copolymerization, which may constitute a simple strategy for utilizing bio-sourced bifunctional compounds chemoselectively and/or orthogonally.

Geographic and Ecological Diversity of Green Sulfur Bacteria in Hot Spring Mat Communities.

Three strains of thermophilic green sulfur bacteria (GSB) are known; all are from microbial mats in hot springs in Rotorua, New Zealand (NZ) and belong to the species Chlorobaculum tepidum. Here, we describe diverse populations of GSB inhabiting Travel Lodge Spring (TLS) (NZ) and hot springs ranging from 36.1 °C to 51.1 °C in the Republic of the Philippines (PHL) and Yellowstone National Park (YNP), Wyoming, USA. Using targeted amplification and restriction fragment length polymorphism analysis, GSB 16S rRNA sequences were detected in mats in TLS, one PHL site, and three regions of YNP. GSB enrichments from YNP and PHL mats contained small, green, nonmotile rods possessing chlorosomes, chlorobactene, and bacteriochlorophyll c. Partial 16S rRNA gene sequences from YNP, NZ, and PHL mats and enrichments from YNP and PHL samples formed distinct phylogenetic clades, suggesting geographic isolation, and were associated with samples differing in temperature and pH, suggesting adaptations to these parameters. Sequences from enrichments and corresponding mats formed clades that were sometimes distinct, increasing the diversity detected. Sequence differences, monophyly, distribution patterns, and evolutionary simulation modeling support our discovery of at least four new putative moderately thermophilic Chlorobaculum species that grew rapidly at 40 °C to 44 °C.

Bayesian optimization of HDPE copolymerization process based on polymer product-process integration

A framework for finding an optimal operating point of HDPE with the target properties is proposed. A bimodal high-density polyethylene (HDPE) copolymerization process is established to calculate molecular weights, dispersity, and predict properties. The process incorporates a probability-based description method with reactivity ratio to describe the content of monomer A/B and sequence distribution. A properties prediction model is established to predict glass transition temperature, melt temperature, melt index, and density. Bayesian optimization algorithm is utilized to optimize the process. This algorithm combines Gaussian process regression and an expectation improvement model to determine the optimal mass flow of feed and temperature of reactors. The objective function is modified using a penalty function to incorporate property constraints. The optimization goal is to maximize profits by identifying the optimal composition of feed and reactor temperature. Optimized bimodal HDPE copolymerization process leads to a significant increase in profit, with a 21.8 % improvement compared to the original process. The effect of melt index, is considered in determining the optimal operation range and maximizing profit. This provides valuable guidance for producing new grades of HDPE.

New Insights into Phylogenetic Relationship of Hydrocotyle (Araliaceae) Based on Plastid Genomes

Hydrocotyle, belonging to the Hydrocotyloideae of Araliaceae, consists of 95 perennial and 35 annual species. Due to the lack of stable diagnostic morphological characteristics and high-resolution molecular markers, the phylogenetic relationships of Hydrocotyle need to be further investigated. In this study, we newly sequenced and assembled 13 whole plastid genomes of Hydrocotyle and performed comparative plastid genomic analyses with four previously published Hydrocotyle plastomes and phylogenomic analyses within Araliaceae. The plastid genomes of Hydrocotyle exhibited typical quadripartite structures with lengths from 152,659 bp to 153,669 bp, comprising a large single-copy (LSC) region (83,958–84,792 bp), a small single-copy (SSC) region (18,585–18,768 bp), and a pair of inverted repeats (IRs) (25,058–25,145 bp). Each plastome encoded 113 unique genes, containing 79 protein-coding genes, 30 tRNA genes, and four rRNA genes. Comparative analyses showed that the IR boundaries of Hydrocotyle plastomes were highly similar, and the coding and IR regions exhibited more conserved than non-coding and single-copy (SC) regions. A total of 2932 simple sequence repeats and 520 long sequence repeats were identified, with specificity in the number and distribution of repeat sequences. Six hypervariable regions were screened from the SC region, including four intergenic spacers (IGS) (ycf3-trnS, trnS-rps4, petA-psbJ, and ndhF-rpl32) and two coding genes (rpl16 and ycf1). Three protein-coding genes (atpE, rpl16, and ycf2) were subjected to positive selection only in a few species, implying that most protein-coding genes were relatively conserved during the plastid evolutionary process. Plastid phylogenomic analyses supported the treatment of Hydrocotyle from Apiaceae to Araliaceae, and topologies with a high resolution indicated that plastome data can be further used in the comprehensive phylogenetic research of Hydrocotyle. The diagnostic characteristics currently used in Hydrocotyle may not accurately reflect the phylogenetic relationships of this genus, and new taxonomic characteristics may need to be evaluated and selected in combination with more comprehensive molecular phylogenetic results.

SOC estimation for lithium-ion battery based on AGA-optimized AUKF

The window size for covariance matching (CM) of the adaptive unscented Kalman filter (AUKF) affects the state of charge (SOC) estimation performance due to changes with time in the distribution of error innovation sequence (EIS). A new adaptive genetic algorithm (AGA) to address this problem is proposed in this paper. The proposed AUKF (AGA-AUKF1) obtains its best window size determined by the AGA. A novel AUKF (AGA-AUKF2) is proposed to prevent the uncertainty caused by time-varying EIS with the combination of AGA and CM methods. Firstly, the influence of different temperatures on the prediction performance of the algorithm is investigated by FUDS data. The influence of various parameters on the algorithm is further analyzed by FUDS. For different temperatures, initial SOC values, and initial measurement noise covariance, the SOC estimation results show that the accuracy of AGA-AUKFs is better than AUKF. The population size and termination algebra simulation results indicate that the proposed AGA performs well in parameter optimization. Subsequently, the SOC estimation capability of two proposed methods in different working conditions is analyzed by BJDST and US06. The results show that AGA-AUKF2 has better accuracy and robustness than AGA-AUKF1.

Addressing the effect of stacking faults in X-ray diffractograms of graphite through atom-scale simulations

Determining the average contribution and actual distribution of rhombohedral stacking sequences within the average graphitic crystallite remained unsolved. To address this issue, we used a bottom-up approach to simulate X-ray diffractograms of graphite crystallites up to one million atoms in various graphene stacking configurations to find out how to match experimental data. The 100–101 2θ range was highly sensitive to the presence of C layers and can be used to accurately characterize the stacking disorder. On the opposite, the 110–112 2θ range was not sensitive to stacking disorder and thus can be taken as a reference to obtain the average in-plane size La of the crystallites, faulted or not. We used the principle of the L'c parameter, introduced in a former work, which corresponds to the height of the coherent sub-domains within the average crystallite obtainable through the shape of the hkl peaks involving both in-plane and out-of-plane directions. Three types of defects within a Bernal sequence were analyzed, which do not affect the peaks the same way: (i) a substitution of A or B by C, (ii) an insertion of C leading to destructive interferences, and (iii) a so-called "block shifting". It is thus possible to go further in the interpretation of X-Ray diffraction. Finally, we discussed how the overall crystallite size Lc can be obtained from all the 00l peaks.

Charge Distribution Patterns of IA3 Impact Conformational Expansion and Hydration Diffusivity of the Disordered Ensemble.

IA3 is a 68 amino acid natural peptide/protein inhibitor of yeast aspartic proteinase A (YPRA) that is intrinsically disordered in solution with induced N-terminal helicity when in the protein complex with YPRA. Based on the intrinsically disordered protein (IDP) parameters of fractional net charge (FNC), net charge density per residue (NCPR), and charge patterning (κ), the two domains of IA3 are defined to occupy different domains within conformationally based subclasses of IDPs, thus making IA3 a bimodal domain IDP. Site-directed spin labeling (SDSL) electron paramagnetic resonance (EPR) spectroscopy and low-field Overhauser dynamic nuclear polarization (ODNP) spectroscopy results show that these two domains possess different degrees of compaction and hydration diffusivity behavior. This work suggests that SDSL EPR line shapes, analyzed in terms of their local tumbling volume (VL), provide insights into the compaction of the unstructured IDP ensemble in solution and that protein sequence and net charge distribution patterns within a conformational subclass can impact bound water hydration dynamics, thus possibly offering an alternative thermodynamic property that can encode conformational binding and behavior of IDPs and liquid-liquid phase separations.

Integrability of Sequences

Abstract This paper deals with density on the set of natural numbers and its connections to the distribution of sequences. Under the assumption of independence, some formulas are derived.

Circular and L50-like leaderless enterocins share a common ABC-transporter immunity gene

Microbes live within complex communities of interacting populations, either free-living in waters and soils or symbionts of animals and plants. Their interactions include the production of antimicrobial peptides (bacteriocins) to antagonize competitors, and these producers must carry their own immunity gene for self-protection. Whether other coexisting populations are sensitive or resistant to the bacteriocin producer will be key for the population dynamics within the microbial community. The immunity gene frequently consists of an ABC transporter to repel its own bacteriocin but rarely protects against a nonrelated bacteriocin. A case where this cross-resistance occurs mediated by a shared ABC transporter has been shown between enterocins MR10A/B and AS-48. The first is an L50-like leaderless enterocin, while AS-48 is a circular enterocin. In addition, L50-like enterocins such as MR10A/B have been found in E. faecalis and E. faecium, but AS-48 appears only in E. faecalis. Thus, using the ABC transporter of the enterocin MR10A/B gene cluster of Enterococcus faecalis MRR10-3 as a cross-resistance model, we aimed to unravel to what extent a particular ABC transporter can be shared across multiple bacteriocinogenic bacterial populations. To this end, we screened the MR10A/B-ABC transporters in available microbial genomes and analyzed their sequence homologies and distribution. Overall, our main findings are as follows: (i) the MR10A/B-ABC transporter is associated with multiple enterocin gene clusters; (ii) the different enterocins associated with this transporter have a saposin-like fold in common; (iii) the Mr10E component of the transporter is more conserved within its associated enterocin, while the Mr10FGH components are more conserved within the carrying species. This is the least known component of the transporter, but it has shown the greatest specificity to its corresponding enterocin. Bacteriocins are now being investigated as an alternative to antibiotics; hence, the wider or narrower distribution of the particular immunity gene should be taken into account for clinical applications to avoid the selection of resistant strains. Further research will be needed to investigate the mechanistic interactions between the Mr10E transporter component and the bacteriocin as well as the specific ecological and evolutionary mechanisms involved in the spread of the immunity transporter across multiple bacteriocins.

Synthesis and modification of alternative copolymers for activating membrane enzymes in vitro

Poly(styrene-co-maleic acid) (SMA) is increasingly being used for the solubilization of lipid membranes and membrane proteins is becoming more widespread. To this end, a deeper understanding of the chemical properties of the copolymer and how these translate into membrane solubilization properties and improvement of enzyme activity or stability to better promote the in vitro reaction of membrane enzymes. SMA comes in several different flavors that include the ratio of styrene to maleic acid, the distribution of comonomer sequences, the average chain length, dispersity, and potential chemical modifications. We have introduced a group of SMAs whose composition and length are well defined in a stepwise manner, and obtained the polymer (4-Cl-SMA-QA) for (-)-trans-isopiperitenone dehydrogenase (IPDH) with a single-pass membrane structure domain. The protein extraction efficiency of 4-Cl-SMA-QA is higher than that of the widely used commercial SMA(2/1), up to 82%, the kcat of IPDH embedded in 4-Cl-SMA-QA is increased by a factor of 4, a 30% decrease in Km, and a 5-fold increase in overall catalytic performance. The requirements of SMA lipid particles’ size for single-span and multi-span membrane proteins are analyzed, which is helpful for rapidly selecting suitable scaffold polymers from massive polymer libraries.

Sparse and semi-attention guided faults diagnosis approach for distributed online services

Despite the rapid advance of unsupervised reconstruction models in online service fault diagnosis, existing methods still lead to frequent false positive or false negative alarms. Tracing to the cause, popular reconstruction frameworks may fall into an “identical shortcut”, where both normal and anomalous cases can be well-recovered and hence faults are escaped from monitoring. Moreover, regularly “concept drift” deployed by online services always leads to sequences distribution dramatically change, which is easily wrongly-detected as anomalies. In this work, we present SS-Attention to avoid two contradictory false alarms simultaneously in a unified framework. Specifically, we first revisit the frameworks of MLP, CNN, and transformer, and confirm the important role of self-attention in preventing the model from learning shortcut, which we therefore select as our backbone. Second, we come up with a sparse attention layer to help model capture more long-term dependencies and distinguish local “concept drift” from anomalies. Third, we propose a semi-attention layer that urges model only learn from normal regions and further avoid well-recovering the faults. We evaluate our model on three public online service datasets and surpass the state-of-the-art alternatives by a sufficiently large margin, achieving an average 95.91% F1-Score with an approx. 34.48% economy of training time.

Joint inversion of Rayleigh group and phase velocities for S-wave velocity structure of the 2021 MS6.0 Luxian earthquake source area, China

On September 16, 2021, a MS6.0 earthquake struck Luxian County, one of the shale gas blocks in the Southeastern Sichuan Basin, China. To understand the seismogenic environment and its mechanism, we inverted a fine three-dimensional S-wave velocity model from ambient noise tomography using data from a newly deployed dense seismic array around the epicenter, by extracting and jointly inverting the Rayleigh phase and group velocities in the period of 1.6–7.2 s. The results showed that the velocity model varied significantly beneath different geological units. The Yujiasi syncline is characterized by low velocity at depths of ∼ 3.0–4.0 km, corresponding to the stable sedimentary layer in the Sichuan Basin. The eastern and western branches of the Huayingshan fault belt generally exhibit high velocities in the NE-SW direction, with a few local low-velocity zones. The Luxian MS6.0 earthquake epicenter is located at the boundary between the high- and low-velocity zones, and the earthquake sequences expand eastward from the epicenter at depths of 3.0–5.0 km. Integrated with the velocity variations around the epicenter, distribution of aftershock sequences, and focal mechanism solution, it is speculated that the seismogenic mechanism of the main shock might be interpreted as the reactivation of pre-existing faults by hydraulic fracturing.

Analysis of smart laminated composites integrated with piezoelectric patches using spectral element method and lamination parameters

This paper investigates the effect of stacking sequence on the power output of a smart composite panel integrated with piezoelectric patches, using lamination parameter formulation and spectral element method (SEM). The deformation of the panel is expressed using the first-order shear deformation theory. The strain energy of the host plate is formulated using lamination parameters and the governing equations are derived following Hamilton’s principle. To solve the governing equations accurately and efficiently, a spectral element method is applied where the structure is divided into regions that are continuous in terms of geometry, and element matrices of each region are calculated using the spectral Chebyshev approach. This method benefits both from the (geometry) flexibility of the finite element method and the accuracy of the meshless methods. The developed electromechanical model is used to study the effect of the number of piezo patches and their sizes. To demonstrate the accuracy and performance of the presented SEM, six case studies were investigated by comparing natural frequencies, structural/voltage frequency response functions (FRFs), and computational duration to those obtained from a finite element analysis (FEA). The maximum difference in the predicted natural frequencies between the SEM and FEA results is below 1% and the FRFs obtained using the presented solution technique excellently match the FEA results. Yet, the simulation duration is significantly reduced compared to FEA. To exploit the computational efficiency of the presented analysis approach, optimization case studies were also performed implementing a genetic algorithm to maximize the power output by optimizing the stacking sequence and patch distribution.

Multi-Chromosomal mitochondrial genome of medicinal plant Acorus tatarinowii (Acoraceae): Firstly reported from Acorales Order

Acorus tatarinowii Schott (A. tatarinowii), a well-known traditional Chinese medicinal plant renowned for its high medicinal value, but its mitochondrial genome (mitogenome) is still unexplored. In this study, we meticulously assembled the complete mitochondrial genome of A. tatarinowii using a combination of Illumina short reads and Oxford Nanopore long reads. Our findings revealed that A. tatarinowii possesses a complex chromosomal structural mitogenome, comprising two linear chromosomes and seven circular chromosomes. This mitogenome spans 1.81 Mb in length with a GC content of 38.29 %. Notably, it contained 24 unique mitochondrial core genes, seven unique variable genes, 17 tRNA genes, and three rRNA genes. Analyses of codon usage, most protein-coding genes (PCGs) exhibited a common codon usage preference, with RSCU values greater than 1, and the codon with the highest RSCU value was UAA(End, 1.90). We conducted a thorough analysis of repeat sequences, the distribution of repetitive sequences in nine mitochondrial chromosomes showed distinct patterns. Moreover, we identified 82 and 12 homologous fragments by comparing the sequences of chloroplast and nuclear genomes to the A. tatarinowii mitogenome, respectively. Lastly, We predicted a total of 234 potential RNA editing sites in 28 unique PCGs and discovered that the nad4 gene has been edited the most often, at 26 times. Our results contribute to the enrichment of mitochondrial genome resources for Acoraceae, and the mitogenome also can be used as a reference for other species.

Identifying “sloppy” users in TMS through operation logs

A transportation management system (TMS) is an integral software system for modern logistics and transportation companies. It is crucial to evaluate the quality of a TMS objectively, a task that currently presents significant challenges to both the IT and logistics sectors. One approach to this evaluation is usage analysis. However, usage analysis is complicated by the presence of both diligent users who utilize the system correctly and 'sloppy' users who enter inaccurate data haphazardly. This inaccuracy hampers the success of the information system and obstructs effective decision-making. Thus, identifying and excluding data from such users is essential for an accurate and objective evaluation of a TMS. Yet, the focus has primarily been on identifying outliers, typically for security reasons, while the identification of 'sloppy' users has been overlooked. Against this context we propose a novel method—Log Evaluation through Operation Sequence Distribution (LEOSD). This method distinguishes between abnormal and normal usage of a TMS by analysing system-generated logs. LEOSD is highly efficient and lightweight, minimizing any disruption to ongoing operations. Our experiment, based on real logs gathered from the industry, supports our hypothesis, and shows that LEOSD is effective in identifying 'sloppy' users. The positive results attest to the efficacy and practicality of our proposed method.