Complex Sequence Research Articles

Exploring the Possible Role of Hybridization in the Evolution of Photosynthetic Pathways in Flaveria (Asteraceae), the Prime Model of C4 Photosynthesis Evolution

Flaveria (Asteraceae) is the prime model for the study of C4 photosynthesis evolution and seems to support a stepwise acquisition of the pathway through C3-C4 intermediate phenotypes, still existing in Flaveria today. Molecular phylogenies of Flaveria based on concatenated data matrices are currently used to reconstruct the complex sequence of trait shifts during C4 evolution. To assess the possible role of hybridization in C4 evolution in Flaveria, we re-analyzed transcriptome data of 17 Flaveria species to infer the extent of gene tree discordance and possible reticulation events. We found massive gene tree discordance as well as reticulation along the backbone and within clades containing C3-C4 intermediate and C4-like species. An early hybridization event between two C3 species might have triggered C4 evolution in the genus. The clade containing all C4 species plus the C4-like species F. vaginata and F. palmeri is highly supported in our phylogenetic analyses, but it might be of hybrid origin involving F. angustifolia and F. sonorensis (both C3-C4 intermediate) as parental lineages. Hybridization seems to be a driver of C4 evolution in Flaveria and likely promoted the fast acquisition of C4 traits. This new insight can be used in further exploring C4 evolution and can inform C4 bioengineering efforts.

Nonlinear Inflatable Actuators for Distributed Control in Soft Robots.

As soft robotic systems grow in complexity and functionality, the size and stiffness of the needed control hardware severely limits their application potential. Alternatively, functionality can be embodied within actuator characteristics, drastically reducing the amount of peripherals. Functions such as memory, computation, and energy storage then result from the intrinsic mechanical behavior of precisely designed structures. Here, actuators are introduced with tunable characteristics to generate complex actuation sequences from a single input. Intricate sequences are made possible by harnessing hysteron characteristics encoded in the buckling of a cone-shaped shell incorporated in the actuator design. A large variety of such characteristics are generated by varying the actuator geometry. This dependency is mapped and used for creating a tool to determine the actuator geometry that yields a desired characteristic. Using this tool, a system with six actuators is created that plays the final movement of Beethoven's Ninth Symphony with a single pressure supply.

Yukon ice patches: Bryophyte generation from ancient ice-entombed assemblages

ABSTRACT In Southwestern Yukon, ice patches have shown substantial retreat since the Little Ice Age (1600–1900 AD) in response to warming trends. These ice patches support unique alpine wetlands that have formed habitats for diverse flora and fauna over millennia. With ice retreat, pristine bryophyte populations are exposed beneath accumulated ancient dung. Given that bryophytes have been shown to survive extreme conditions including ice entombment and can regenerate from viable cells, emergent ice margin bryophyte and dung samples from the Granger and Gladstone ice patches were assayed for regrowth potential under growth chamber conditions. Diaspore (spore/fragment) generation of species found in the original subfossil material was indicated in 68 percent of assays, emphasizing the cyclical establishment of ancient ice patch vegetation. One of the oldest samples, dating 4036 calibrated years BP from the Gladstone ice patch margin, showed remarkable bryophyte generation from diaspores in dung. These Yukon ice patches form reservoirs of cryopreserved biota and have a critical role in maintaining alpine diversity, which provides summer refuge for caribou and other alpine fauna. Ice margin fluctuations, which bury and release populations through time, are part of a complex revegetation sequence in alpine regions that has followed deglaciation.

RecON: Online learning for sensorless freehand 3D ultrasound reconstruction.

Sensorless freehand 3D ultrasound (US) reconstruction based on deep networks shows promising advantages, such as large field of view, relatively high resolution, low cost, and ease of use. However, existing methods mainly consider vanilla scan strategies with limited inter-frame variations. These methods thus are degraded on complex but routine scan sequences in clinics. In this context, we propose a novel online learning framework for freehand 3D US reconstruction under complex scan strategies with diverse scanning velocities and poses. First, we devise a motion-weighted training loss in training phase to regularize the scan variation frame-by-frame and better mitigate the negative effects of uneven inter-frame velocity. Second, we effectively drive online learning with local-to-global pseudo supervisions. It mines both the frame-level contextual consistency and the path-level similarity constraint to improve the inter-frame transformation estimation. We explore a global adversarial shape before transferring the latent anatomical prior as supervision. Third, we build a feasible differentiable reconstruction approximation to enable the end-to-end optimization of our online learning. Experimental results illustrate that our freehand 3D US reconstruction framework outperformed current methods on two large, simulated datasets and one real dataset. In addition, we applied the proposed framework to clinical scan videos to further validate its effectiveness and generalizability.

Reinforcement Learning-Based Method to Exploit Vulnerabilities of False Data Injection Attack Detectors in Modular Multilevel Converters

Implementing control schemes for modular multilevel converters (M2Cs) involves both a cyber and a physical level, leading to a cyber-physical system (CPS). At the cyber level, a communication network enables the data exchange between sensors, control platforms, and monitoring systems. Meanwhile, at the physical level, the semiconductor devices that comprise the M2C are switched ON/OFF by the control system. In this context, almost all published works in this research area assume that the CPS always reports correct information. However, this may not be the case when the M2C is affected by cyber-attacks, such as the one named false data injection attack (FDIA), where the data seen by the control system is corrupted through illegitimate data intrusion into the CPS. To deal with this situation, FDIA detectors for the M2C are recently starting to be studied, where the goal is to detect and mitigate the attacks and the attacked sub-modules. This paper proposes a reinforcement learning (RL)-based method to uncover the deficiencies of existing FDIAs detectors used for M2C applications. The proposed method auto-generates complex attack sequences able to bypass FDIA detectors. Therefore, it points out the weaknesses of current detectors: This valuable information can be used later to improve the performance of the detectors, establishing more reliable cybersecurity solutions for M2Cs. The RL environment is developed in Matlab/Simulink augmented by PLECS/blockset, and it is made available to researchers on a website to motivate future research efforts in this area. Hardware-in-the-loop (HIL) studies verify the proposal's effectiveness.

Offline Learning in Children: The Effect of Night Sleep and Wakefulness on Memory Consolidation of a Complex Motor Task

Background and Aims Sleep after a new sequence memory training can enhance the explicit memory in children. However, children’s sleep-dependent motor memory consolidation particularly in implicit complex sequence tasks is unclear. Therefore, this study aims to investigate the role of night-time sleep and wakefulness on children’s motor memory consolidation following an implicit complex task. Methods In the current study, 26 boys aged 9-12 years were randomly assigned in two groups of sleep and awake. Acquisition phase included 10 blocks of 96 trials. The sleep group performed initial training at 8 (±1) PM while the awake group performed it at 8 (±1) AM by using the dynamic arm movement task. The participants were not aware of the sequence order. After training, the children’s performance was tested after 12 hours. Results The results of 2×2 Mixed ANOVA in the consolidation phase showed the significant main effect of block on response time (P=0.000) and prediction error (P=0.023). However, the interaction effect of block and group were not significant on response time (P=0.566) and prediction error (P=0.887). Conclusion The sequence memory consolidation in children under an implicit complex task can be improved offline regardless of having sleep between training and test sessions. Hence, sleep is not necessary for offline enhancement of motor sequence skills. Passage of time is effective for improvement in dynamic arm movement task. Therefore, the role of sleep in offline learning of motor skills depends on the nature of the task used in training.

Exceptional sets

In this paper, we study sequences of complex numbers of the first order. Multiple terms are allowed for such sequences. We also consider complex sequences with a finite maximum density. We construct special coverings of multiple sets {λk,nk} consisting of circles centered at points λk of special radii. In particular, we construct coverings are with connected components of a relatively small diameter, as well as coverings that are C0-sets. These coverings act as exceptional sets for entire functions of exponential type. Outside these sets, we obtain a representation of the logarithm of the modulus of an entire function. Previously, a similar representation was obtained by B. Ya. Levin outside the exceptional set, with respect to which only its existence is asserted. In contrast to this, in this paper we present a simple effective construction of an exceptional set. We construct bases of the invariant subspace of analytic functions in a convex domain. They consist of linear combinations of eigenfunctions and associated functions (exponential monomials) of the differentiation operator divided into relatively small groups.

The Effect of Cognitive Task Complexity on Healthy Gait in the Walking Corsi Test.

Dual-task activities are essential within everyday life, requiring visual-spatial memory (VSM) and mobility skills. Navigational memory is an important component of VSM needed to carry out everyday activities, but this is often not included in traditional tests such as the Corsi block tapping test (CBT). The Walking Corsi Test (WalCT) allows both VSM and navigational memory to be tested together, as well as allowing measures of gait to be collected, thus providing a more complete understanding of dual-task function. The aim of this study was to investigate the effect of an increasingly complex cognitive task on gait in a healthy adult population, using the WalCT and body-worn inertial measurement unit (IMU) sensors. Participants completed both the CBT and WalCT, where they were asked to replicate increasingly complex sequences until they were no longer able to carry this out correctly. IMU sensors were worn on the shins throughout the WalCT to assess changes in gait as task complexity increased. Results showed that there were significant differences in several gait parameters between completing a relatively simple cognitive task and completing a complex task. The type of memory used also appeared to have an impact on some gait variables. This indicates that even within a healthy population, gait is affected by cognitive task complexity, which may limit function in everyday dual-task activities.

Mammalian milk glycomes: Connecting the dots between evolutionary conservation and biosynthetic pathways

Milk oligosaccharides (MOs) are among the most abundant constituents of breast milk and are essential for health and development. Biosynthesized from monosaccharides into complex sequences, MOs differ considerably between taxonomic groups. Even human MO biosynthesis is insufficiently understood, hampering evolutionary and functional analyses. Using a comprehensive resource of all published MOs from >100 mammals, we develop a pipeline for generating and analyzing MO biosynthetic networks. We then use evolutionary relationships and inferred intermediates of these networks to discover (1) systematic glycome biases, (2) biosynthetic restrictions, such as reaction path preference, and (3) conserved biosynthetic modules. This allows us to prune and pinpoint biosynthetic pathways despite missing information. Machine learning and network analysis cluster species by their milk glycome, identifying characteristic sequence relationships and evolutionary gains/losses of motifs, MOs, and biosynthetic modules. These resources and analyses will advance our understanding of glycan biosynthesis and the evolution of breast milk.

The dynamics behind diversity in suboscine songs.

Vocal behavior plays a crucial evolutionary role. In the case of birds, song is critically important in courtship, male-male competition and other key behaviors linked to reproduction. However, under natural conditions, a variety of avian species live in close proximity and share an 'acoustic landscape'. Therefore, they need to be able to differentiate their calls or songs from those of other species and also from those of other individuals of the same species. To do this efficiently, birds display a remarkable diversity of sounds. For example, in the case of vocal learners, such as oscine passerines (i.e. songbirds), complex sequences and subtle acoustic effects are produced through the generation of complex neuromuscular instructions driving the vocal organ, which is remarkably conserved across approximately 4000 oscine species. By contrast, the majority of the sister clade of oscines, the suboscine passerines, are thought not to be vocal learners. Despite this, different suboscine species can generate a rich variety of songs and quite subtle acoustic effects. In the last few years, different suboscine species have been shown to possess morphological adaptations that allow them to produce a diversity of acoustic characteristics. Here, we briefly review the mechanisms of sound production in birds, before considering three suboscine species in more detail. The examples discussed in this Review, integrating biological experiments and biomechanical modeling using non-linear dynamical systems, illustrate how a morphological adaptation can produce complex acoustic properties without the need for complex neuromuscular control.

Prediction of Daily Temperature Based on the Robust Machine Learning Algorithms

Temperature climate is an essential component of weather forecasting and is vital in predicting future weather patterns. Accurate temperature predictions can assist individuals and organizations in preparing for potential weather-related events such as heat waves or cold snaps. However, achieving precise temperature predictions necessitates thoroughly comprehending the underlying factors influencing climate patterns. The study utilized two models, LSTM and DLSTM, to forecast daily air temperature using 1097 data points gathered from central and southern regions of Tabriz city of Iran in Asia from 2017 to 2019. The results indicated that the proposed model had a high accuracy rate for predicting daily air temperature for test data, with RMSEDLSTM = 0.08 °C and R-SquareDLSTM = 0.99. The DLSTM algorithm is known for its high speed, accuracy, time series prediction, noise reduction capabilities for data, the large volume of data processing, and improved performance of predicted data. In summary, while both LSTM and DLSTM are used for predicting data points, DLSTM is a more advanced version that includes multiple layers of memory cells and is better suited for handling complex sequences of events.

Coherent manipulation of nitrogen-vacancy centers in diamond via frequency multiplication

Nitrogen-vacancy (NV) centers in diamond as ideally individual spin quantum systems can be coherently manipulated by microwave fields. Compared to the traditional method using the IQ (In-phase/Quadrature) mixer with a local oscillator and intermediate-frequency (IF) signals, we report an effective and technically simple method to generate the required microwave field by frequency multiplication and realize coherent manipulation of the NV center’s electron spin. After frequency multiplication, the IF signal can be directly converted to the high-frequency microwave field with adjustable pulse width, frequency, phase, and amplitude. A series of spin dynamics applications such as Rabi oscillation, free induction decay, and spin-locking are executed, which verified its performance and feasibility. Frequency multiplication can overcome the problem of clock synchronization between the local oscillator and IF signal and greatly reduce the complexity of the experimental system. The method can be easily used to realize a more complex quantum control sequence such as dynamic decoupling and extended to a wide range of spin-based quantum information applications in the future.

14‐4: Efficient Multi‐stage Bayesian Optimization for Optimal Display Circuit Input Signal Design

To correct for threshold variations in the driving transistor, pixel circuits rely on a complex sequence of inputs that drive the circuit through programming and emission phase. In this work we propose a multi‐stage optimization strategy to automate the design of input signals for arbitrary pixel circuits. By solving for the operation phases of pixel circuits separately and in reverse order our algorithm efficiently finds the narrow region of input signal designs that achieve the desired functionality in the large search space. We demonstrate the generality of our algorithm on two common pixel circuits, i.e., 3T1C and 7T1C.

Swarms and mainshock–aftershocks sequences are both triggered by fluids in the Ubaye Region (Western Alps)

SUMMARYThe Ubaye Region (French Western Alps) is one of the most seismically active regions in France. It is regularly struck by mainshock–aftershocks sequences like in 1959 (ML 5.3), seismic swarms (2003–2004), and complex sequences (2012–2015) characterized by successive mainshocks clustered in time and space. This diversity of seismic behaviour highlights the complex processes at play in this area. To improve our understanding of these processes, in this study, we compile a regional catalogue of existing focal mechanisms, completed by 100 new calculated focal mechanisms of aftershocks following the 07/04/2014 mainshock (ML 5.1). The oriented stress-state we reconstruct for different periods and subareas are similar to each other and to previous published values focusing on swarm periods. We then calculate fluid pressure required to trigger the earthquakes. Most of the events (65 per cent) need fluid overpressure between 15 and 40 MPa (17 to 40 per cent of the hydrostatic pressure) with a median value of 24 per cent. Moreover, even the largest events, like the mainshocks in the 2012–2015 sequence, appear to be triggered by fluid pressure, similarly as events within swarm sequences. However, while fluid overpressure decreases with time in an aftershock sequence, it varies randomly at high levels during a swarm sequence. Therefore, based on a fault-valve model, we propose that: (1) the fluids trapped in the fault plane tend toward lithostatic pressure and trigger the mainshock rupture and (2) part of the aftershocks are induced by the diffusing fluid pressure. On the contrary, swarms need external, likely deep, fluid pressure feedings. Fluid pressure is likely to be a common triggering mechanism of the seismicity in the Ubaye Region, even if the involved processes should differ to explain the different types of seismic sequences.

The Evolution of Abnormal Grains during the Heating Stage of a Post-Weld Solution Treatment in a Friction-Stir-Welded 2519 Aluminium Alloy

This work presents an in-depth investigation of the early stages of abnormal grain growth (AGG) in a friction-stir-welded (FSWed) 2519-T820 aluminium alloy. Microstructural evolutions, which occurred during the heating stage of a solution heat treatment (SHT), were studied. It was found that the welded materials underwent a complex sequence of precipitation phenomena, which eventually led to AGG. The evolution of precipitates was found to be heavily dependent on the FSW temperature condition. In a weld produced with a low-heat input, a significant portion of the precipitates were retained in the stir zone after FSW and then underwent coarsening and a subsequent dissolution during the annealing that followed. This led to a reduction in precipitation-pinning forces and thus promoted rapid grain coarsening. In a weld produced with a high-heat input, the initial precipitates were completely dissolved during the FSW, owing to the higher temperature, and then partially re-precipitated during the heating stage of the post-weld heat treatment. Due to the fine-grain structure of the stir zone, re-precipitation typically occurred at grain boundaries, thus promoting significant thermal stability. However, at temperatures approaching the SHT temperature, the new precipitates coarsened and then dissolved, resulting in AGG.

RNA ligase ribozymes with a small catalytic core

Catalytic RNAs, or ribozymes, catalyze diverse chemical reactions that could have sustained primordial life in the hypothetical RNA world. Many natural ribozymes and laboratory evolved ribozymes exhibit efficient catalysis mediated by elaborate catalytic cores within complex tertiary structures. However, such complex RNA structures and sequences are unlikely to have emerged by chance during the earliest phase of chemical evolution. Here, we explored simple and small ribozyme motifs capable of ligating two RNA fragments in a template-directed fashion (ligase ribozymes). One-round selection of small ligase ribozymes followed by deep sequencing revealed a ligase ribozyme motif comprising a three-nucleotide loop opposite to the ligation junction. The observed ligation was magnesium(II) dependent and appears to form a 2′–5′ phosphodiester linkage. The fact that such a small RNA motif can function as a catalyst supports a scenario in which RNA or other primordial nucleic acids played a central role in chemical evolution of life.

PPE Barcoding Identifies Biclonal Mycobacterium ulcerans Buruli Ulcer, Côte d'Ivoire.

Mycobacterium ulcerans, an environmental opportunistic pathogen, causes necrotic cutaneous and subcutaneous lesions, named Buruli ulcers, in tropical countries. PCR-derived tests used to detect M. ulcerans in environmental and clinical samples do not allow one-shot detection, identification, and typing of M. ulcerans among closely related Mycobacterium marinum complex mycobacteria. We established a 385-member M. marinum/M. ulcerans complex whole-genome sequence database by assembling and annotating 341 M. marinum/M. ulcerans complex genomes and added 44 M. marinum/M. ulcerans complex whole-genome sequences already deposited in the NCBI database. Pangenome, core genome, and single-nucleotide polymorphism (SNP) distance-based comparisons sorted the 385 strains into 10 M. ulcerans taxa and 13 M. marinum taxa, correlating with the geographic origin of strains. Aligning conserved genes identified one PPE (proline-proline-glutamate) gene sequence to be species and intraspecies specific, thereby genotyping the 23 M. marinum/M. ulcerans complex taxa. PCR sequencing of the PPE gene correctly genotyped nine M. marinum/M. ulcerans complex isolates among one M. marinum taxon and three M. ulcerans taxa in the African taxon (T2.4). Further, successful PPE gene PCR sequencing in 15/21 (71.4%) swabs collected from suspected Buruli ulcer lesions in Côte d'Ivoire exhibited positive M. ulcerans IS2404 real-time PCR and identified the M. ulcerans T2.4.1 genotype in eight swabs and M. ulcerans T2.4.1/T2.4.2 mixed genotypes in seven swabs. PPE gene sequencing could be used as a proxy for whole-genome sequencing for the one-shot detection, identification, and typing of clinical M. ulcerans strains, offering an unprecedented tool for identifying M. ulcerans mixed infections. IMPORTANCE We describe a new targeted sequencing approach that characterizes the PPE gene to disclose the simultaneous presence of different variants of a single pathogenic microorganism. This approach has direct implications on the understanding of pathogen diversity and natural history and potential therapeutic implications when dealing with obligate and opportunistic pathogens, such as Mycobacterium ulcerans presented here as a prototype.

Insights into the Multisymmetric Tailoring of Julichrome Compounds by the Oxygenases JuiN and JuiO: Enzymatic Processing around the Biaryl C–C Axis

Biaryl moieties, especially in the context of natural products (NPs), constitute a privileged scaffold for drug design. However, compound modifications that follow the installation of the defining C–C biaryl axis have not been well documented. Here, we report two iterative monooxygenases, JuiN and JuiO, that catalyze tandem and symmetric hydroxylation and epoxidation chemistries following C–C axis formation en route to the NP julichrome Q6-6. The crystal structure of JuiN-FAD-Q6-6 and mutagenesis experiments revealed the substrate recognition mechanisms driving iterative hydroxylations along the C–C axis. The key to these studies was that the unstable intermediate julichrome Q8-8 was successfully captured using an adsorptive resin in fermentations of a ΔjuiO mutant, thus invoking JuiO in the overall sequence of transformations. A Streptomyces griseorubiginosus-derived enzyme, SgJuiO, was investigated in vitro as a substitute for insoluble JuiO. The biochemical reactions unambiguously demonstrated that SgJuiO iteratively catalyzes the complex sequence of epoxidations on both sides of the C–C biaryl linkage. These findings showcase a tailoring paradigm for biaryl NP biosynthesis and engineering.

River blockage and impulse wave evolution of the Baige landslide in October 2018: Insights from coupled DEM-CFD analyses

On 11 October 2018, the Baige landslide in Southwest China blocked the Jinsha River and induced waves amplifying the landslide-affected area significantly. Devastating flood damage was caused by the consequent dam breach. Such a complex sequence can lead to catastrophic consequences but has rarely been fully reproduced. This paper investigates the landslide-river interaction of the first Baige landslide based on coupled discrete element method (DEM) and computational fluid dynamics (CFD) analyses. To this end, the volume of fluid (VOF) and virtual sphere model are adopted to realise impacted river tracing and accurate terrain modelling. The damming process and impulse wave evolution of the first event are well represented. In addition, the simulated cumulative landslide spreading path, deposit geometry, maximum wave elevation and cumulative wave erosion area satisfactorily match the survey results. Our findings further indicate that the movement path and deposit morphology of the Baige landslide are mainly affected by local terrain, while the propagation of impulse waves is driven by the sliding mass and modulated by the riverbank and hydrodynamic conditions. In particular, we discussed the evolution patterns of impulse waves caused by river damming landslides, encompassing run-up on the opposite bank and quasi-3D propagation along the river direction. This research provides a valuable guide for the practical simulation of river blockage and impulse wave evolution and supports the mitigation of landslide disasters in mountainous areas.

Comprehensive Taxonomical Analysis of Trichophyton Mentagrophytes/Interdigitale Complex of Human and Animal Origin from India

Taxonomic delineation of etiologic agents responsible for recalcitrant dermatophytosis causing an epidemic in India is still debated. The organism responsible for this epidemic is designated as T. indotineae, a clonal offshoot of T. mentagrophytes. To evaluate the real identity of the agent causing this epidemic, we performed a multigene sequence analysis of Trichophyton species isolated from human and animal origin. We included Trichophyton species isolated from 213 human and six animal hosts. Internal transcribed spacer (ITS) (n = 219), translational elongation factors (TEF 1-α) (n = 40), ß-tubulin (BT) (n = 40), large ribosomal subunit (LSU) (n = 34), calmodulin (CAL) (n = 29), high mobility group (HMG) transcription factor gene (n = 17) and α-box gene (n = 17) were sequenced. Our sequences were compared with Trichophyton mentagrophytes species complex sequences in the NCBI database. Except for one isolate (ITS genotype III) from animal origin, all the tested genes grouped our isolates and belonged to the "Indian ITS genotype", currently labeled as T. indotineae. ITS and TEF 1-α were more congruent compared to other genes. In this study, for the first time, we isolated the T mentagrophytes ITS Type VIII from animal origin, suggesting the role of zoonotic transmission in the ongoing epidemic. Isolation of T. mentagrophytes type III only from animal indicates its niche among animals. Outdated/inaccurate naming for these dermatophytes in the public database has created confusion in using appropriate species designation.