Severe Bottleneck Research Articles

Efficient structural node similarity computation on billion-scale graphs

Structural node similarity is widely used in analyzing complex networks. As one of the structural node similarity metrics, role similarity has the good merit of indicating automorphism (isomorphism). Existing algorithms to compute role similarity (e.g., Role Sim and NED) suffer from severe performance bottlenecks and thus cannot handle large real-world graphs. In this paper, we propose a new framework, namely Struct Sim, to compute nodes’ role similarity. Under this framework, we first prove that Struct Sim is an admissible role similarity metric based on the maximum matching. While the maximum matching is still too costly to scale, we then devise the Bin Count matching that not only is efficient to compute but also guarantees the admissibility of Struct Sim. Bin Count-based Struct Sim admits a precomputed index to query a single pair of node in $$O(k\log D)$$ time, where k is a small user-defined parameter and D is the maximum node degree. To build the index, we further devise an FM-sketch-based technique that can handle graphs with billions of edges. Extensive empirical studies show that Struct Sim performs much better than the existing works regarding both effectiveness and efficiency when applied to compute structural node similarities on the real-world graphs.

Predicting ultrafast nonlinear dynamics in fibre optics with a recurrent neural network

The propagation of ultrashort pulses in optical fibre plays a central role in the development of light sources and photonic technologies, with applications from fundamental studies of light–matter interactions to high-resolution imaging and remote sensing. However, short pulse dynamics are highly nonlinear, and optimizing pulse propagation for application purposes requires extensive and computationally demanding numerical simulations. This creates a severe bottleneck in designing and optimizing experiments in real time. Here, we present a solution to this problem using a recurrent neural network to model and predict complex nonlinear propagation in optical fibre, solely from the input pulse intensity profile. We highlight particular examples in pulse compression and ultra-broadband supercontinuum generation, and compare neural network predictions with experimental data. We also show how the approach can be generalized to model other propagation scenarios for a wider range of input conditions and fibre systems, including multimode propagation. These results open up novel perspectives in the modelling of nonlinear systems, for the development of future photonic technologies and more generally in physics for studies in Bose–Einstein condensates, plasma physics and hydrodynamics.

A Reference Genome Assembly of American Bison, Bison bison bison.

Bison are an icon of the American West and an ecologically, commercially, and culturally important species. Despite numbering in the hundreds of thousands today, conservation concerns remain for the species, including the impact on genetic diversity of a severe bottleneck around the turn of the 20th century and genetic introgression from domestic cattle. Genetic diversity and admixture are best evaluated at genome-wide scale, for which a high-quality reference is necessary. Here, we use trio binning of long reads from a bison–Simmental cattle (Bos taurus taurus) male F1 hybrid to sequence and assemble the genome of the American plains bison (Bison bison bison). The male haplotype genome is chromosome-scale, with a total length of 2.65 Gb across 775 scaffolds (839 contigs) and a scaffold N50 of 87.8 Mb. Our bison genome is ~13× more contiguous overall and ~3400× more contiguous at the contig level than the current bison reference genome. The bison genome sequence presented here (ARS-UCSC_bison1.0) will enable new research into the evolutionary history of this iconic megafauna species and provide a new tool for the management of bison populations in federal and commercial herds.

A Confidence-Aware Machine Learning Framework for Dynamic Security Assessment

Dynamic Security Assessment (DSA) for the future power system is expected to be increasingly complicated with the higher level penetration of renewable energy sources (RES) and the widespread deployment of power electronic devices, which drive new dynamic phenomena. As a result, the increasing complexity and the severe computational bottleneck in real-time operation encourage researchers to exploit machine learning to extract offline security rules for the online assessment. However, traditional machine learning methods lack in providing information on the confidence of their corresponding predictions. A better understanding of confidence of the prediction is of key importance for Transmission System Operators (TSOs) to use and rely on these machine learning methods. Specifically, from the perspective of topological changes, it is often unclear whether the machine learning model can still be used. Hence, being aware of the confidence of the prediction supports the transition to using machine learning in real-time operation. In this paper, we propose a novel Conditional Bayesian Deep Auto-Encoder (CBDAC) based security assessment framework to compute a confidence metric of the prediction. This informs not only the operator to judge whether the prediction can be trusted, but it also allows for judging whether the model needs updating. A case study based on IEEE 68-bus system demonstrates that CBDAC outperforms the state-of-the-art machine learning-based DSA methods and the models that need updating under different topologies can be effectively identified. Furthermore, the case study verifies that effective updating of the models is possible even with very limited data.

An inexact PAM method for computing Wasserstein barycenter with unknown supports

Wasserstein barycenter is the centroid of a collection of discrete probability distributions which minimizes the average of the $$\ell _2$$ -Wasserstein distance. This paper focuses on the computation of Wasserstein barycenters under the case where the support points are free, which is known to be a severe bottleneck in the D2-clustering due to the large scale and nonconvexity. We develop an inexact proximal alternating minimization (iPAM) method for computing an approximate Wasserstein barycenter, and provide its global convergence analysis. This method can achieve a good accuracy with a reduced computational cost when the unknown support points of the barycenter have low cardinality. Numerical comparisons with the 3-block B-ADMM in Ye et al. (IEEE Trans Signal Process 65:2317–2332, 2017) and an alternating minimization method involving the LP subproblems on synthetic and real data show that the proposed iPAM can yield comparable even a little better objective values in less CPU time, and hence, the computed barycenter will render a better role in the D2-clustering.

No severe genetic bottleneck in a rapidly range-expanding bumblebee pollinator.

Genetic bottlenecks can limit the success of populations colonizing new ranges. However, successful colonizations can occur despite bottlenecks, a phenomenon known as the genetic paradox of invasion. Eusocial Hymenoptera such as bumblebees (Bombus spp.) should be particularly vulnerable to genetic bottlenecks, since homozygosity at the sex-determining locus leads to costly diploid male production (DMP). The Tree Bumblebee (Bombus hypnorum) has rapidly colonized the UK since 2001 and has been highlighted as exemplifying the genetic paradox of invasion. Using microsatellite genotyping, combined with the first genetic estimates of DMP in UK B. hypnorum, we tested two alternative genetic hypotheses (‘bottleneck’ and ‘gene flow’ hypotheses) for B. hypnorum's colonization of the UK. We found that the UK population has not undergone a recent severe genetic bottleneck and exhibits levels of genetic diversity falling between those of widespread and range-restricted Bombus species. Diploid males occurred in 15.4% of reared colonies, leading to an estimate of 21.5 alleles at the sex-determining locus. Overall, the findings show that this population is not bottlenecked, instead suggesting that it is experiencing continued gene flow from the continental European source population with only moderate loss of genetic diversity, and does not exemplify the genetic paradox of invasion.

Mating system evolution and genetic structure of diploid sexual populations of Cyrtomium falcatum in Japan

Evolution of mating systems has become one of the most important research areas in evolutionary biology. Cyrtomium falcatum is a homosporous fern species native to eastern Asia. Two subspecies belonging to a sexual diploid race of C. falcatum are recognized: subsp. littorale and subsp. australe. Subspecies littorale shows intermediate selfing rates, while subsp. australe is an obligate outcrosser. We aimed to evaluate the process of mating system evolution and divergence for the two subspecies using restriction site associated DNA sequencing (RAD-seq). The results showed that subsp. littorale had lower genetic diversity and stronger genetic drift than subsp. australe. Fluctuations in the effective population size over time were evaluated by extended Bayesian skyline plot and Stairway plot analyses, both of which revealed a severe population bottleneck about 20,000 years ago in subsp. littorale. This bottleneck and the subsequent range expansion after the LGM appear to have played an important role in the divergence of the two subspecies and the evolution of selfing in subsp. littorale. These results shed new light on the relationship between mating system evolution and past demographic change in fern species.

Phenological tracking of a seasonal climate window in a recovering tropical island bird species

Constraints on evolutionary adaptation and range shifts mean that phenotypic plasticity, which includes physiological, developmental or behavioural responses to environmental conditions, could be an important mode of adaptation to a changing climate for many species with small insular populations. While there is evidence to suggest adaptive plasticity to climate in some island populations, little is known about this capacity in species that have experienced a severe population bottleneck. In a changing climate, plasticity in the timing of life-history events, such as in breeding phenology, is adaptive if timing is optimised in seasonal environments, although these processes are poorly understood for tropical species. Here, we quantify the effects of climate on the breeding phenology and success of the Mauritius kestrel (Falco punctatus), a tropical raptor whose extinction has been averted by conservation management. We show that the timing of egg-laying is advancing in response to warming, at rates similar to temperate bird populations. Individual females show plasticity to temperature, although there is limited variation among individual responses. We show that advances in breeding phenology are likely to be adaptive, as they track changes in a seasonal climate window of favourable conditions, defined by late winter-early spring temperatures and the onset of the summer rainy season. Our results provide a rare example of a small and bottlenecked insular population that has adjusted to recent climate change through phenotypic plasticity. Furthermore, seasonal climate windows and their dynamics may be widespread mechanisms through which tropical species are impacted by and respond to climate change.

Climatic Refugia and Geographical Isolation Contribute to the Speciation and Genetic Divergence in Himalayan-Hengduan Tree Peonies (Paeonia delavayi and Paeonia ludlowii).

Himalaya and Hengduan Mountains (HHM) is a biodiversity hotspot, and very rich in endemic species. Previous phylogeographical studies proposed different hypotheses (vicariance and climate-driven speciation) in explaining diversification and the observed pattern of extant biodiversity, but it is likely that taxa are forming in this area in species-specific ways. Here, we reexplored the phylogenetic relationship and tested the corresponding hypotheses within Paeonia subsect. Delavayanae composed of one widespread species (Paeonia delavayi) and the other geographically confined species (Paeonia ludlowii). We gathered genetic variation data at three chloroplast DNA fragments and one nuclear gene from 335 individuals of 34 populations sampled from HHM. We performed a combination of population genetic summary statistics, isolation-with-migration divergence models, isolation by environment, and demographic history analyses. We found evidence for the current taxonomic treatment that P. ludlowii and P. delavayi are two different species with significant genetic differentiation. The significant isolation by environment was revealed within all sampled populations but genetic distances only explained by geographical distances within P. delavayi populations. The results of population divergence models and demographic history analyses indicated a progenitor–derivative relationship and the Late Quaternary divergence without gene flow between them. The coalescence of all sampled cpDNA haplotypes could date to the Late Miocene, and P. delavayi populations probably underwent a severe bottleneck in population size during the last glacial period. Genetic variation in Paeonia subsect. Delavayanae is associated with geographical and environmental distances. These findings point to the importance of geological and climatic changes as causes of the speciation event and lineage diversification within Paeonia subsect. Delavayanae.

Population genomics reveal rapid genetic differentiation in a recently invasive population of Rattus norvegicus

BackgroundInvasive species bring a serious effect on local biodiversity, ecosystems, and even human health and safety. Although the genetic signatures of historical range expansions have been explored in an array of species, the genetic consequences of contemporary range expansions have received little attention, especially in mammal species. In this study, we used whole-genome sequencing to explore the rapid genetic change and introduction history of a newly invasive brown rat (Rattus norvegicus) population which invaded Xinjiang Province, China in the late 1970s.ResultsBayesian clustering analysis, principal components analysis, and phylogenetic analysis all showed clear genetic differentiation between newly introduced and native rat populations. Reduced genetic diversity and high linkage disequilibrium suggested a severe population bottleneck in this colonization event. Results of TreeMix analyses revealed that the introduced rats were derived from an adjacent population in geographic region (Northwest China). Demographic analysis indicated that a severe bottleneck occurred in XJ population after the split off from the source population, and the divergence of XJ population might have started before the invasion of XJ. Moreover, we detected 42 protein-coding genes with allele frequency shifts throughout the genome for XJ rats and they were mainly associated with lipid metabolism and immunity, which could be seen as a prelude to future selection analyses in the novel environment of XJ.ConclusionsThis study presents the first genomic evidence on genetic differentiation which developed rapidly, and deepens the understanding of invasion history and evolutionary processes of this newly introduced rat population. This would add to our understanding of how invasive species become established and aid strategies aimed at the management of this notorious pest that have spread around the world with humans.

Genome and population evolution and environmental adaptation of Glyptosternon maculatum on the Qinghai-Tibet Plateau.

Persistent uplift means the Qinghai-Tibet Plateau (QTP) is an ideal natural laboratory to investigate genome evolution and adaptation within highland environments. However, how paleogeographic and paleoclimatic events influence the genome and population of endemic fish species remains unclear. Glyptosternon maculatum is an ancient endemic fish found on the QTP and the only critically endangered species in the Sisoridae family. Here, we found that major transposons in the G. maculatum genome showed episodic bursts, consistent with contemporaneous geological and climatic events during the QTP formation. Notably, histone genes showed significant expansion in the G. maculatum genome, which may be mediated by long interspersed nuclear elements (LINE) repetitive element duplications. Population analysis showed that ancestral G. maculatum populations experienced two significant depressions 2.6 million years ago (Mya) and 10 000 years ago, exhibiting excellent synchronization with Quaternary glaciation and the Younger Dryas, respectively. Thus, we propose that paleogeography and paleoclimate were dominating driving forces for population dynamics in endemic fish on the QTP. Tectonic movements and temperature fluctuation likely destroyed the habitat and disrupted the drainage connectivity among populations. These factors may have caused severe bottlenecks and limited migration among ancestral G. maculatum populations, resulting in the low genetic diversity and endangered status of the species today.

Bandwidth limits of luminescent solar concentrators as detectors in free-space optical communication systems

Luminescent solar concentrators (LSCs) have recently emerged as a promising receiver technology in free-space optical communications due to their inherent ability to collect light from a wide field-of-view and concentrate it into small areas, thus leading to high optical gains. Several high-speed communication systems integrating LSCs in their detector blocks have already been demonstrated, with the majority of efforts so far being devoted to maximising the received optical power and the system’s field-of-view. However, LSCs may pose a severe bottleneck on the bandwidth of such communication channels due to the comparably slow timescale of the fluorescence events involved, a situation further aggravated by the inherent reabsorption in these systems, and yet, an in-depth study into such dynamic effects remains absent in the field. To fill this gap, we have developed a comprehensive analytical solution that delineates the fundamental bandwidth limits of LSCs as optical detectors in arbitrary free-space optical links, and establishes their equivalence with simple RC low-pass electrical circuits. Furthermore, we demonstrate a time-domain Monte Carlo simulation platform, an indispensable tool in the multiparameter optimisation of LSC-based receiver systems. Our work offers vital insight into LSC system dynamic behaviour and paves the way to evaluate the technology for a wide range of applications, including visible light communications, high-speed video recording, and real-time biological imaging, to name a few.

All-optical computing based on convolutional neural networks

The rapid development of information technology has fueled an ever-increasing demand for ultrafast and ultralow-energy-consumption computing. Existing computing instruments are pre-dominantly electronic processors, which use electrons as information carriers and possess von Neumann architecture featured by physical separation of storage and processing. The scaling of computing speed is limited not only by data transfer between memory and processing units, but also by RC delay associated with integrated circuits. Moreover, excessive heating due to Ohmic losses is becoming a severe bottleneck for both speed and power consumption scaling. Using photons as information carriers is a promising alternative. Owing to the weak third-order optical nonlinearity of conventional materials, building integrated photonic computing chips under traditional von Neumann architecture has been a challenge. Here, we report a new all-optical computing framework to realize ultrafast and ultralow-energy-consumption all-optical computing based on convolutional neural networks. The device is constructed from cascaded silicon Y-shaped waveguides with side-coupled silicon waveguide segments which we termed “weight modulators” to enable complete phase and amplitude control in each waveguide branch. The generic device concept can be used for equation solving, multifunctional logic operations as well as many other mathematical operations. Multiple computing functions including transcendental equation solvers, multifarious logic gate operators, and half-adders were experimentally demonstrated to validate the all-optical computing performances. The time-of-flight of light through the network structure corresponds to an ultrafast computing time of the order of several picoseconds with an ultralow energy consumption of dozens of femtojoules per bit. Our approach can be further expanded to fulfill other complex computing tasks based on non-von Neumann architectures and thus paves a new way for on-chip all-optical computing.

Dual Sensor Impulse Noise Cancellation for Downstream DSL Systems

Impulse noise presents a severe performance bottleneck in multicarrier systems. For digital subscriber lines (DSL), the use of a common-mode (CM) sensor is a viable technique to mitigate the impulse noise that couples into the useful differential-mode (DM) signal. In this paper, we use time and frequency domain approaches to develop algorithms using the joint processing of CM and DM signals and analyze the performance of dual-sensor based interference cancellation schemes for downstream DSL systems. First, we consider the frequency domain approach and analyze the performance of a per-tone impulse noise canceler without requiring an impulse detector. We derive closed-form expressions on the performance of canceler in various interference scenarios in terms of system parameters. Next, we develop a novel per-symbol time-domain impulse noise canceler by simultaneous estimation of the CM2DM transfer function and the CM impulse noise using a limited number of null carriers. The proposed algorithm eliminates the issues of convergence of the per-tone canceler and stationarity of the impulse noise over multiple symbols. Using derived analytical expressions, we show that the proposed canceler effectively mitigates the impulse noise on a per-symbol basis. We also demonstrate the performance of the considered canceler schemes using measurement and simulation results.

Fine-scale genetic structure of the overwintering Chilo suppressalis in the typical bivoltine areas of northern China.

The rice stem borer (RSB), Chilo suppressalis (Lepidoptera: Pyralidae), is an important agricultural pest that has caused serious economic losses in the major rice-producing areas of China. To effectively control this pest, we investigated the genetic diversity, genetic differentiation and genetic structure of 16 overwintering populations in the typical bivoltine areas of northern China based on 12 nuclear microsatellite loci. Moderate levels of genetic diversity and genetic differentiation among the studied populations were detected. Neighbour-joining dendrograms, Bayesian clustering and principal coordinate analysis (PCoA) consistently divided these populations into three genetic clades: western, eastern and northern/central. Isolation by distance (IBD) and spatial autocorrelation analyses demonstrated no correlation between genetic distance and geographic distance. Bottleneck analysis illustrated that RSB populations had not undergone severe bottleneck effects in these regions. Accordingly, our results provide new insights into the genetic relationships of overwintering RSB populations and thus contribute to developing effective management strategies for this pest.

Population genomics of Plasmodium vivax in Panama to assess the risk of case importation on malaria elimination.

Malaria incidence in Panama has plateaued in recent years in spite of elimination efforts, with almost all cases caused by Plasmodium vivax. Notwithstanding, overall malaria prevalence remains low (fewer than 1 case per 1000 persons). We used selective whole genome amplification to sequence 59 P. vivax samples from Panama. The P. vivax samples were collected from two periods (2007-2009 and 2017-2019) to study the population structure and transmission dynamics of the parasite. Imported cases resulting from increased levels of human migration could threaten malaria elimination prospects, and four of the samples evaluated came from individuals with travel history. We explored patterns of recent common ancestry among the samples and observed that a highly genetically related lineage (termed CL1) was dominant among the samples (47 out of 59 samples with good sequencing coverage), spanning the entire period of the collection (2007-2019) and all regions of the country. We also found a second, smaller clonal lineage (termed CL2) of four parasites collected between 2017 and 2019. To explore the regional context of Panamanian P. vivax we conducted principal components analysis and constructed a neighbor-joining tree using these samples and samples collected worldwide from a previous study. Three of the four samples with travel history clustered with samples collected from their suspected country of origin (consistent with importation), while one appears to have been a result of local transmission. The small number of Panamanian P. vivax samples not belonging to either CL1 or CL2 clustered with samples collected from Colombia, suggesting they represent the genetically similar ancestral P. vivax population in Panama or were recently imported from Colombia. The low diversity we observe in Panama indicates that this parasite population has been previously subject to a severe bottleneck and may be eligible for elimination. Additionally, while we confirmed that P. vivax is imported to Panama from diverse geographic locations, the lack of impact from imported cases on the overall parasite population genomic profile suggests that onward transmission from such cases is limited and that imported cases may not presently pose a major barrier to elimination.

A clue to invasion success: genetic diversity quickly rebounds after introduction bottlenecks

One of the fundamental questions in invasion biology is to understand the genetic mechanisms behind success or failure during the establishment of a species. However, major limitations to understanding are usually a lack of spatiotemporal population data and information on the populations’ colonisation history. In a large-scale, detailed study on the bush-cricket Metrioptera roeselii 70 groups of founders were introduced in areas outside the species’ distribution range. We examined how (1) the number of founders (2–32 individuals), (2) the time since establishment (7 or 15 years after introduction) and (3) possible gene flow affected establishment success and temporal genetic changes of the introduced populations. We found higher establishment success in introductions with larger propagule sizes but genetic diversity indices were only partly correlated to propagule size. As expected, introduced populations were more similar to their founder population the larger the propagule size was. However, even if apparent at first, most of the differentiation in the small propagule introductions disappeared over time. Surprisingly, genetic variability was regained to a level comparable to the large and outbreeding founder population only 15 generations after severe demographic bottlenecks. We suggest that the establishment of these populations could be a result of several mechanisms acting in synergy. Here, rapid increase in genetic diversity of few introductions could potentially be attributed to limited gene flow from adjacent populations, behavioural adaptations and/or even increased mutation rate. We present unique insights into genetic processes that point towards traits that are important for understanding species’ invasiveness.

Production planning and control in multi-stage assembly systems: an assessment of Kanban, MRP, OPT (DBR) and DDMRP by simulation

Multi-stage assembly systems where the demand for components depends on the market-driven demand for end products, are commonly encountered in practice. Production Planning and Control (PPC) systems for this production context include Kanban, Materials Requirement Planning (MRP), Optimised Production Technology (OPT), and Demand Driven MRP (DDMRP). All four of these PPC systems are widely applied in practice and literature abounds on each of these systems. Yet, studies comparing these systems are scarce and remain largely inconclusive. In response, this study uses simulation to assess the performance of all four PPC systems under different levels of bottleneck severity and due date tightness. Results show that MRP performs the worst, which can be explained by the enforcement of production start dates. Meanwhile, Kanban and DDMRP perform the best if there is no bottleneck. If there is a bottleneck then DDMRP and OPT perform the best, with DDMRP realising lower inventory levels. If there is a severe bottleneck, then the performance results for DDMRP and OPT converge. This identification of contingency factors not only resolves some of the inconsistencies in the literature but also has important implications for the applicability of these four PPC systems in practice.

Genetic variation and phylogeographic structure of Laodelphax striatellus in China based on microsatellite markers

AbstractThe small brown planthopper (SBPH), Laodelphax striatellus (Fallén) (Hemiptera: Delphacidae), is an important agricultural pest that has caused serious economic losses in the major rice‐producing areas of China. To effectively manage this insect pest, we analysed its genetic variation, genetic structure and population demographic history. We used nine nuclear microsatellite loci to investigate the genetic diversity and population genetic structure of SBPH at 43 sampling sites in China. High levels of genetic diversity and genetic differentiation among most populations were detected. Overall, neighbour‐joining dendrograms, STRUCTURE and principal coordinate analysis (PCoA) revealed no genetically distinct groups and exhibited an admixed phylogeographic structure in China. Isolation by distance (IBD) and spatial autocorrelation analyses demonstrated no correlation between genetic distance and geographic distance. On the other hand, bottleneck analysis indicated that SBPH populations had not undergone severe bottleneck effects in these regions. This study provides useful data for resolving the genetic relationships and migration patterns of SBPH and thus contributes to developing effective management strategies for this pest.

Evolutionary rate and genetic load in an emblematic Mediterranean tree following an ancient and prolonged population collapse

Severe bottlenecks significantly diminish the amount of genetic diversity and the speed at which it accumulates (i.e., evolutionary rate). They further compromise the efficiency of natural selection to eliminate deleterious variants, which may reach fixation in the surviving populations. Consequently, expanding and adapting to new environments may pose a significant challenge when strong bottlenecks result in genetic pauperization. Herein, we surveyed the patterns of nucleotide diversity, molecular adaptation and genetic load across 177 gene-loci in a circum-Mediterranean conifer (Pinus pinea L.) that represents one of the most extreme cases of genetic pauperization in widespread outbreeding taxa. We found very little genetic variation in both hypervariable nuclear microsatellites (SSRs) and gene-loci, which translated into genetic diversity estimates one order of magnitude lower than those previously reported for pines. Such values were consistent with a strong population decline that began some ~1Ma. Comparisons with the related and parapatric maritime pine (Pinus pinaster Ait.) revealed reduced rates of adaptive evolution (α and ωa ) and a significant accumulation of genetic load. It is unlikely that these are the result from differences in mutation rate or linkage disequilibrium between the two species; instead they are the presumable outcome of contrasting demographic histories affecting both the speed at which these taxa accumulate genetic diversity, and the global efficacy of selection. Future studies, and programs for conservation and management, should thus start testing for the effects of genetic load on fitness, and integrating such effects into predictive models.