Exploration Of Dynamics Research Articles

Spintronic terahertz metasurface emission characterized by scanning near-field nanoscopy

Abstract Understanding the ultrafast excitation, detection, transportation, and manipulation of nanoscale spin dynamics in the terahertz (THz) frequency range is critical to developing spintronic THz optoelectronic nanodevices. However, the diffraction limitation of the sub-millimeter waves – THz wavelengths – has impaired experimental investigation of spintronic THz nano-emission. Here, we present an approach to studying laser THz emission nanoscopy from W|CoFeB|Pt metasurfaces with ∼60-nm lateral spatial resolution. When comparing with statistic near-field THz time-domain spectroscopy with and without the heterostructures on fused silica substrates, we find that polarization- and phase-sensitive THz emission nanoscopy is more sensitive than the statistic THz scattering intensity nanoscopy. Our approach opens explorations of nanoscale ultrafast THz spintronic dynamics in optically excited metasurfaces.

Study on the urban digital transformation gyroscope model

Purpose Urban digital transformation has become a key strategy in global countries. This study aims to provide a comprehensive and dynamic exploration of the intrinsic traits associated with urban digital transformation, in order to yield detailed insights that can contribute to the formulation of well-informed decisions and strategies in the field of urban development initiatives. Design/methodology/approach Through analysis of parallels between urban digital transformation and gyroscope motion in physics, the study developed the urban digital transformation gyroscope model (UDTGM), which comprises of seven core elements. With the balanced panel dataset from 268 cities at and above the prefecture level in China, we validate the dynamic mechanism of this model. Findings The findings of this study underscore that the collaboration among infrastructure development, knowledge-driven forces and economic operations markedly bolsters the urban digital transformation gyroscope’s efficacy. Practical implications This research introduces a groundbreaking framework for comprehending urban digital transformation, potentially facilitating its balanced and systemic practical implementation. Originality/value This study pioneers the UDTGM theoretically and verifies the dynamic mechanism of this model with real data.

An integrated approach for understanding global earthquake patterns and enhancing seismic risk assessment

Earthquakes, as intricate natural phenomena, profoundly impact lives, infrastructure, and the environment. While previous research has explored earthquake patterns through data analysis methods, there has been a gap in examining the time intervals between consecutive earthquakes across various magnitude categories. Given the complexity and vastness of seismic data, this study aims to provide comprehensive insights into global seismic activity by employing sophisticated data analysis methodologies on a century-long dataset of seismic events. The four-phase methodology encompasses exploratory data analysis (EDA), temporal dynamics exploration, spatial pattern analysis, and cluster analysis. The EDA serves as the foundational step, providing fundamental insights into the dataset's attributes and laying the groundwork for subsequent analyses. Temporal dynamics exploration focuses on discerning variations in earthquake occurrences over time. Spatial analysis identifies geographic regions with heightened earthquake activity and uncovers patterns of seismic clustering. K-means clustering is employed to delineate distinct earthquake occurrence clusters or hotspots based on geographical coordinates. The study's findings reveal a notable increase in recorded earthquakes since the 1960s, peaking in 2018. Distinct patterns in seismic activity are linked to factors such as time, human activities, and plate boundaries. The integrated approach enriches understanding of global earthquake trends and patterns, contributing to improved seismic hazard assessments, early warning systems, and risk mitigation efforts.

Unlocking the Thermal Efficiency of Irregular Open-Cell Metal Foams: A Computational Exploration of Flow Dynamics and Heat Transfer Phenomena

An open-cell metal foam has excellent characteristics such as low density, high porosity, high specific surface area, high thermal conductivity, and low mass due to its unique internal three-dimensional network structure. It has gradually become a new material for enhanced heat transfer in industrial equipment, new compact heat exchangers, microelectronic device cooling, etc. This research established a comprehensive three-dimensional structural model of open-cell metal foams utilizing Laguerre–Voronoi tessellations and employed computational fluid dynamics to investigate its flow dynamics and coupled heat transfer performance. By exploring the impact of foam microstructure on flow resistance and heat transfer characteristics, the study provided insights into the overall convective heat transfer performance across a range of foam configurations with varying pore densities and porosities. The findings revealed a direct correlation between convective heat transfer coefficient (h) and pressure drop (ΔP) with increasing Reynolds number (Re), accompanied by notable changes in fluid turbulence kinetic energy (e) and temperature (T), ultimately influencing heat transfer efficiency. Furthermore, the analysis demonstrated that alterations in porosity (ε) and pore density significantly affected unit pressure drop (ΔP/L) and convective heat transfer coefficient (h). This study identified an optimal configuration, highlighting a metal foam with a pore density of 20 PPI and a porosity of 95% as exhibiting superior overall convective heat transfer performance.

Oxidative Stress-Mediated Repression of Virulence Gene Transcription and Biofilm Formation as Antibacterial Action of Cinnamomum burmannii Essential Oil on Staphylococcus aureus.

This work aimed to identify the chemical compounds of Cinnamomum burmannii leaf essential oil (CBLEO) and to unravel the antibacterial mechanism of CBLEO at the molecular level for developing antimicrobials. CBLEO had 37 volatile compounds with abundant borneol (28.40%) and showed good potential to control foodborne pathogens, of which Staphylococcus aureus had the greatest inhibition zone diameter (28.72 mm) with the lowest values of minimum inhibitory concentration (1.0 μg/mL) and bactericidal concentration (2.0 μg/mL). To unravel the antibacterial action of CBLEO on S. aureus, a dynamic exploration of antibacterial growth, material leakage, ROS formation, protein oxidation, cell morphology, and interaction with genome DNA was conducted on S. aureus exposed to CBLEO at different doses (1/2-2×MIC) and times (0-24 h), indicating that CBLEO acts as an inducer for ROS production and the oxidative stress of S. aureus. To highlight the antibacterial action of CBLEO on S. aureus at the molecular level, we performed a comparative association of ROS accumulation with some key virulence-related gene (sigB/agrA/sarA/icaA/cidA/rsbU) transcription, protease production, and biofilm formation in S. aureus subjected to CBLEO at different levels and times, revealing that CBLEO-induced oxidative stress caused transcript suppression of virulence regulators (RsbU and SigB) and its targeted genes, causing a protease level increase destined for the biofilm formation and growth inhibition of S. aureus, which may be a key bactericidal action. Our findings provide valuable information for studying the antibacterial mechanism of essential oil against pathogens.

Study on the Relationship Between Actor-Network and Sustainable Manufacturing: The Case of IKEA

This thesis explores the application of Actor-Network Theory (ANT) in the realm of sustainable manufacturing, employing IKEA as a case study. The study systematically investigates the multifaceted interactions among diverse actors within the sustainable manufacturing network. The research is structured around key themes such as government bodies, suppliers, consumers, and technology providers, offering a detailed analysis of stakeholder interests, needs, and the alignment thereof. Problematization within the study involves a deep exploration of the intricate dynamics arising at the intersection of ANT and Sustainable Manufacturing. The analysis unveils the central role of stakeholder alignment in shaping the sustainable manufacturing landscape. The thesis reveals that when stakeholder interests converge, translation processes facilitate collaboration, enabling the network to harness collective agency in advancing sustainability goals. However, it also recognizes the complexities arising from misaligned interests and power dynamics, acknowledging conflicts inherent in sustainable manufacturing networks. The Mobilization and Activation phase delves into the strategies employed to summon various actors, including IKEA, government bodies, suppliers, consumers, and technology providers, into action. This multifaceted endeavor highlights the importance of understanding the mechanisms that harness the potential of each actor within the network. The study emphasizes the pivotal roles of government policies, industrial practices, societal influences, and smart technologies in the success of sustainable manufacturing at IKEA. The stakeholder analysis uncovers the complex web of rights, demands, and challenges faced by each group, ranging from IKEA's balancing act between economic sustainability and ethical production.

Impact of third-order dispersion on the dynamics of dissipative solitons in an ultrafast fiber laser.

Dissipative solitons (DSs), due to the complex interplay among dispersion, nonlinear, gain and loss, illustrate abundant nonlinear dynamics behaviors. Especially, dispersion plays an important role in the research of DS dynamics in ultrafast fiber lasers. Previous studies have mainly focused on the effect of even-order dispersion, i.e., group velocity dispersion (GVD) and fourth-order dispersion. In fact, odd-order dispersions, such as third-order dispersion (TOD), also significantly influences the dynamics of DSs. However, due to the lack of dispersion engineering tools, few experimental researches in this domain have been reported. In this work, by employing a pulse shaper in ultrafast fiber laser, an in-depth exploration of the DS dynamics influenced by TOD was conducted. With the increase of TOD value, the stable single DS undergoes a splitting into two solitons and then enters explosion state, and ultimately evolves into a chaotic state. The laser operation state is correlated to dispersion profile, which could be controlled by TOD. Here, the positive dispersion at long-wavelength side will be gradually shifted to negative dispersion by increasing the TOD, where soliton effect will drive the transitions. These findings offer valuable insights into the nonlinear dynamics of ultrafast lasers and may also foster applications involving higher-order dispersion.

An evolutive model of a boundedly rational consumer with changing preferences and reference group consumption

In this paper, two dynamic models, recently proposed to describe the adaptive repeated choices of a boundedly rational consumer, are joined together. One considers a consumer adjusting the consumption level of a given good over time according to the observed discrepancy between expected and realized utility gain and modifies the utility function according to past consumption experience, also including saturation effects when past consumption is excessive. The other one considers the same adjustment mechanism with constant preferences but with a behavioral effect that introduces a tendency (or bias) to imitate a reference group of consumers. Merging these two models, a two-dimensional nonlinear dynamical system is obtained which describes consumers that decide their next period consumption of a given good by following two different (sometimes contrasting) criteria: their own utility maximization on the one side and imitation of a reference group of consumers on the other side. This leads to a greater uncertainty with respect to the model without the behavioral bias. Such uncertainty is studied through a numerical exploration of the long-run dynamics, guided by some global dynamical features of the nonlinear model, such as the folding action of the critical curves that characterize the behavior of the iterated noninvertible map and the singularities related to the presence of a vanishing denominator, namely focal points and prefocal curves. So, the aim of the paper is twofold: on the one side, it tries to contribute to the literature on the economic theory of boundedly rational consumers represented by evolutionary and behavioral approaches; On the other side, it tries to contribute to the recent literature about the global analysis of discrete dynamical systems characterized by contact bifurcations leading to the creation of complex topological structures of the attractors and their basins of attraction.

Digital writing with AI platforms: the role of fun with/in generative AI

PurposeWith the rapid advancement of generative artificial intelligence (AI), it is important to consider how young people are making sense of these tools in their everyday lives. Drawing on critical postdigital approaches to learning and literacy, this study aims to center the experiences and perspectives of young people who encounter and experiment with generative AI in their daily writing practices.Design/methodology/approachThis critical case study of one digital platform – Character.ai – brings together an adolescent and adult authorship team to inquire about the intertwining of young people’s playful and critical perspectives when writing on/with digital platforms. Drawing on critical walkthrough methodology (Light et al., 2018), the authors engage digital methods to study how the creative and “fun” uses of AI in youths’ writing lives are situated in broader platform ecologies.FindingsThe findings suggest experimentation and pleasure are key aspects of young people’s engagement with generative AI. The authors demonstrate how one platform works to capitalize on these dimensions, even as youth users engage critically and artfully with the platform and develop their digital writing practices.Practical implicationsThis study highlights how playful experimentation with generative AI can engage young people both in pleasurable digital writing and in exploration and contemplation of platforms dynamics and structures that shape their and others’ literate activities. Educators can consider young people’s creative uses of these evolving technologies as potential opportunities to develop a critical awareness of how commercial platforms seek to benefit from their users.Originality/valueThis study contributes to the development of a critical and humanist research agenda around generative AI by centering the experiences, perspectives and practices of young people who are underrepresented in the burgeoning research devoted to AI and literacies.

The time revolution in macromolecular crystallography.

Macromolecular crystallography has historically provided the atomic structures of proteins fundamental to cellular functions. However, the advent of cryo-electron microscopy for structure determination of large and increasingly smaller and flexible proteins signaled a paradigm shift in structural biology. The extensive structural and sequence data from crystallography and advanced sequencing techniques have been pivotal for training computational models for accurate structure prediction, unveiling the general fold of most proteins. Here, we present a perspective on the rise of time-resolved crystallography as the new frontier of macromolecular structure determination. We trace the evolution from the pioneering time-resolved crystallography methods to modern serial crystallography, highlighting the synergy between rapid detection technologies and state-of-the-art x-ray sources. These innovations are redefining our exploration of protein dynamics, with high-resolution crystallography uniquely positioned to elucidate rapid dynamic processes at ambient temperatures, thus deepening our understanding of protein functionality. We propose that the integration of dynamic structural data with machine learning advancements will unlock predictive capabilities for protein kinetics, revolutionizing dynamics like macromolecular crystallography revolutionized structural biology.

Multiplexed near infrared fluorescence lifetime imaging in turbid media.

Fluorescence lifetime imaging (FLI) plays a pivotal role in enhancing our understanding of biological systems, providing a valuable tool for non-invasive exploration of biomolecular and cellular dynamics, both in vitro and in vivo. Its ability to selectively target and multiplex various entities, alongside heightened sensitivity and specificity, offers rapid and cost-effective insights. Our aim is to investigate the multiplexing capabilities of near-infrared (NIR) FLI within a scattering medium that mimics biological tissues. We strive to develop a comprehensive understanding of FLI's potential for multiplexing diverse targets within a complex, tissue-like environment. We introduce an innovative Monte Carlo (MC) simulation approach that accurately describes the scattering behavior of fluorescent photons within turbid media. Applying phasor analyses, we enable the multiplexing of distinct targets within a single FLI image. Leveraging the state-of-the-art single-photon avalanche diode (SPAD) time-gated camera, SPAD512S, we conduct experimental wide-field FLI in the NIR regime. Our study demonstrates the successful multiplexing of dual targets within a single FLI image, reaching a depth of 1cm within tissue-like phantoms. Through our novel MC simulation approach and phasor analyses, we showcase the effectiveness of our methodology in overcoming the challenges posed by scattering media. This research underscores the potential of NIR FLI for multiplexing applications in complex biological environments. By combining advanced simulation techniques with cutting-edge experimental tools, we introduce significant results in the non-invasive exploration of biomolecular dynamics, to advance the field of FLI research.

Relativistic spin-0 Duffin–Kemmer–Petiau equation in Bonnor–Melvin–Lambda solution

In this paper, we conduct a comprehensive exploration of the relativistic quantum dynamics of spin-0 scalar particles, as described by the Duffin–Kemmer–Petiau (DKP) equation, within the framework of a magnetic space-time. Our focus is on the Bonnor–Melvin–Lambda (BML) solution, a four-dimensional magnetic universe characterized by a magnetic field that varies with axial distance. To initiate this investigation, we derive the radial equation using a suitable wave function ansatz and subsequently employ special functions to solve it. Furthermore, we extend our analysis to include Duffin–Kemmer–Petiau oscillator fields within the same BML space-time background. We derive the corresponding radial equation and solve it using special functions. Significantly, our results show that the geometry’s topology and the cosmological constant (both are related to the magnetic field strength) influence the eigenvalue solution of spin-0 DKP fields and DKP-oscillator fields, leading to substantial modifications in the overall outcomes.

Dynamical exploration of optical soliton solutions for M-fractional Paraxial wave equation.

This work explores diverse novel soliton solutions due to fractional derivative, dispersive, and nonlinearity effects for the nonlinear time M-fractional paraxial wave equation. The advanced exp [-φ(ξ)] expansion method integrates the nonlinear M-fractional Paraxial wave equation for achieving creative solitonic and traveling wave envelopes to reconnoiter such dynamics. As a result, trigonometric and hyperbolic solutions have been found via the proposed method. Under the conditions of the constraint, fruitful solutions are gained and verified with the use of the symbolic software Maple 18. For any chosen set of the allowed parameters 3D, 2D and density plots illustrate, this inquisition achieved kink shape, the collision of kink type and rogue wave, periodic rogue wave, some distinct singular periodic soliton waves for time M-fractional Paraxial wave equation. As certain nonlinear effects cancel out dispersion effects, optical solitons typically can travel great distances without dissipating. We have constructed reasonable soliton solutions and managed the actual meaning of the acquired solutions of action by characterizing the particular advantages of the summarized parameters by the portrayal of figures and by interpreting the physical occurrences. New precise voyaging wave configurations are obtained using symbolic computation and the previously described methodologies. However, the movement role of the waves is explored, and the modulation instability analysis is used to describe the stability of waves in a dispersive fashion of the obtained solutions, confirming that all created solutions are precise and stable.

Ab initio calculation of nonequilibrium quasiparticle-phonon dynamics in superconductors

Phonon-induced Cooper pair breaking, inciting nonequilibrium quasiparticle (QP) bursts, is known to deteriorate the performance of superconducting devices. However, a detailed understanding of QP-phonon dynamics is lacking due to the absence of a well-established theoretical framework. This paper presents a fully ab initio scheme of calculating nonequilibrium, polarization-dependent QP-phonon dynamics in superconductors. The authors find that with only an 8% deviation from the equilibrium phonon Bose–Einstein distribution, the resulting nonequilibrium QP population is 83 times larger than the equilibrium Fermi–Dirac distribution, and the longitudinal acoustic (LA) phonon polarization is most responsible for QP generation. The authors demonstrated that the qubit transition rate in Josephson junction-based transmon qubits is increased by orders of magnitude when taking these nonequilibrium distributions into account, compared to equilibrium distributions. This framework allows an in-depth exploration of nonequilibrium QP-phonon dynamics in various Josephson-junction-based superconducting devices. It paves the way for formulating advanced phonon shielding strategies to target the LA polarization, potentially leading to enhanced device performance, such as increased coherence time of transmon qubits or reduced thermal noise in cryogenics.

Skin-Inspired Multi-Modal Mechanoreceptors for Dynamic Haptic Exploration.

Active sensing is a fundamental aspect of human and animal interactions with the environment, providing essential information about the hardness, texture, and tackiness of objects. This ability stems from the presence of diverse mechanoreceptors in the skin, capable of detecting a wide range of stimuli and from the sensorimotor control of biological mechanisms. In contrast, existing tactile sensors for robotic applications typically excel in identifying only limited types of information, lacking the versatility of biological mechanoreceptors and the requisite sensing strategies to extract tactile information proactively. Here, inspired by human haptic perception, a skin-inspired artificial 3D mechanoreceptor (SENS) capable of detecting multiple mechanical stimuli is developed to bridge sensing and action in a closed-loop sensorimotor system for dynamic haptic exploration. A tensor-based non-linear theoretical model is established to characterize the 3D deformation (e.g., tensile, compressive, and shear deformation) of SENS, providing guidance for the design and optimization of multimode sensing properties with high fidelity. Based on SENS, a closed-loop robotic system capable of recognizing objects with improved accuracy (≈96%) is further demonstrated. This dynamic haptic exploration approach shows promise for a wide range of applications such as autonomous learning, healthcare, and space and deep-sea exploration.

Lahore in the 21st Century: The functioning and development of a megacity in the global south

In the world of urban studies and history, it is not uncommon for researchers and * writers to draw from established frameworks as points of inquiry. However, in “Lahore in the 21st Century,” Qadeer presents a refreshing departure from this norm. What sets this book apart is its original analytical framework, one specifically tailored to the vibrant city of Lahore. Qadeer’s work is an exploration of the internal dynamics of urban development in Lahore, and it offers readers a unique perspective on how the city functions. At the core of Qadeer’s argument is the notion that Lahore’s social and physical development can be attributed to its internal dynamics. He uses the metaphors of software and hardware to convey this concept. He argues that the indigenous society played a pivotal role in adapting, resisting, and reshaping the initiatives brought by the external forces and dynamics. Qadeer supports his claims with examples of physical and social transformations in Lahore. Qadeer also emphasises the intricate interplay between the city’s internal dynamics and national-scale circumstances. He links Lahore’s evolution to Pakistan’s shifting political landscape and international relations. One of the book’s strengths is the author’s personal connection to the city. As someone who experienced Lahore’s transitions in the aftermath of significant outmigration by Hindu and Sikh communities in 1947, Qadeer combines his lived experiences with scholarly analysis. His memoirs are seamlessly woven into the book and meticulously corroborated with cited works. This blending of personal history and academic endeavor adds depth and authenticity to the narrative. Part of the book also serves as a historical account of Lahore. What distinguishes it from previous works is a fresh perspective on the city’s history, showing how it influences the city’s form and function. A distinctive feature of the book is Qadeer’s limited reliance on other scholars to develop an argument. While this might make it less appealing to those seeking an exhaustive review of literature on Lahore, the author’s diversity of sources is truly impressive. He offers key sources in notes, allowing interested readers to explore them independently. This approach not only keeps the book accessible but also underscores that most of the ideas presented are the author’s own, derived from his thoughtful analysis of the city.

Machine Learning Deciphered Molecular Mechanistics with Accurate Kinetic and Thermodynamic Prediction.

Time-lagged independent component analysis (tICA) and the Markov state model (MSM) have been extensively employed for extracting conformational dynamics and kinetic community networks from unbiased trajectory ensembles. However, these techniques may not be the optimal choice for elucidating transition mechanisms within low-dimensional representations, especially for intricate biosystems. Unraveling the association mechanism in such complex systems always necessitates permutations of several essential independent components or collective variables, a process that is inherently obscure and may require empirical knowledge for selection. To address these challenges, we have implemented an integrated unsupervised dimension reduction model: uniform manifold approximation and projection (UMAP) with hierarchy density-based spatial clustering of applications with noise (HDBSCAN). This approach effectively generates low-dimensional configurational embeddings. The hierarchical application of this architecture, in conjunction with MSM, reveals global kinetic connectivity while identifying local conformational states. Consequently, our methodology establishes a multiscale mechanistic elucidation framework. Leveraging the benefits of the uniform sample distribution and a denoising approach, our model demonstrates robustness in preserving global and local data structures compared to traditional dimension reduction methods in the field of MD analysis area. The interpretability of hyperparameter selection and compatibility with downstream tasks are cross-validated across various simulation data sets, utilizing both computational evaluation metrics and experimental kinetic observables. Furthermore, the predicted Mcl1-BH3 association kinetics (0.76 s-1) is in close agreement with surface plasmon resonance experiments (0.12 s-1), affirming the plausibility of the identified pathway composed of representative conformations. We anticipate that the devised workflow will serve as a foundational framework for studying recognition patterns in complex biological systems. Its contributions extend to the exploration of protein functional dynamics and rational drug design, offering a potent avenue for advancing research in these domains.

Unlocking stability and efficiency in benzyl isothiocyanate-loaded emulsions: Unveiling synergistic interactions of fish skin gelatin and pectin

In this research endeavor, a novel emulsion delivery system was devised to enhance the retention of the fat-soluble active substance known as benzyl isothiocyanate (BITC). Fish skin gelatin (FSG) and pectin (PEC) were chosen as complex emulsifiers and collectively referred to as FSG-PEC. The interaction between FSG and PEC was examined by turbidity, flourier transform infrared, fluorescence, ultraviolet, methylene blue, and molecular docking. Emulsification activity, emulsification stability, contact angle, appearance structure, average particle size, zeta potential, oil droplet distribution, and retention rate of the encapsulated BITC, were evaluated to determine the optimal concentration ratio of the FSG-PEC complex for effectively safeguarding BITC. The results showed that the turbidity of FSG and PEC was minimal at pH 7, indicating relative stability of the complex. The primary molecular forces between FSG and PEC were electrostatic and hydrogen bond interaction. The interfacial stability, emulsifying activity and stability of FSG-PEC complex at a 2:1 ratio surpassed those of other ratios. Consequently, this optimal ratio was utilized to prepare FSG-PEC emulsion delivery system containing BITC. The resulting emulsion, stored for 14 days at 4 °C, demonstrated compelling attributes with a particle size of 433.33 ± 1.12 nm, a potential of −32.87 ± 0.35 mV, and a BITC retention rate of 59.87 ± 0.65%. The combination of the indicators finally concluded that 2:1 was the optimal ratio to construct the FSG-PEC complex emulsion delivery system. This study constitutes an initial exploration of the interaction dynamics between FSG and PEC, providing a theoretical foundation for subsequent applications.

Complete genome assemblies of several Xylella fastidiosa subspecies multiplex strains reveals high phage content and novel plasmids

The Gram-negative bacterium Xylella fastidiosa (Xf) was originally found in the Americas, but has now been identified in more than 20 countries across America, Asia, and Europe. This plant pathogen is currently listed as a priority pest in Europe due to its socio-economic and ecological impacts. Within the three Xf subspecies fastidiosa, multiplex and pauca, subsp. multiplex displays a notably wider range of host plants than the other two subspecies. Comparative genomics may allow determination of how Xf subsp. multiplex adapts to new and diverse hosts and environments, so it is important that more genomes of this subspecies are defined. Twelve complete closed genomes sequences of Xf subsp. multiplex were obtained using a hybrid assembly approach combining Illumina and Oxford Nanopore technologies. The combined use of Canu and Unicycler assemblers enabled identification and closure of several plasmid sequences with high similarity to other plasmids described in strains of Xf subsp. fastidiosa and subsp. pauca. The analysis also revealed prophage sequences and contigs outside the chromosomes, annotated as phages. These new genomes, in conjunction with those existing in GenBank, will facilitate exploration of the evolutionary dynamics of Xf subsp. multiplex, its host adaptation mechanisms, and the potential emergence of novel strains of this important plant pathogen.

Observation of rapid decay and optical properties of micro-pyramidically grown molybdenum diselenide MoSe2 crystal

In two-dimensional transition metal dichalcogenides (2D-TMDs), the existence of excitons and trions promises their fascinating optical properties for applications in nanophotonic. The more exotic the nanostructure geometry, the less explored its optical responses. The chemical vapor deposition (CVD) technique enables the synthesis of nanostructures with different geometries ranging from monolayers to pyramids driven by a screw-dislocation mechanism. Here we report the CVD synthesis of micro-pyramids with a curious optical response exotic geometry like pyramid. The photoluminescence of as-grown micro-pyramids is significantly diminished compared to their flat-layered structures. In contrast, nanostructured micro-pyramids exhibit a large number of higher-order phononic resonances when excited resonantly by the Raman signal, allowing a more detailed exploration of exciton dynamics. The spectral peak position, intensity, and ratio of the spectral peak reveal local variations in the atomic arrangement of the center and sides of the micro-pyramid. We have investigated the optical response of MoSe2 micro-pyramids and correlated them with their growth-induced nano geometry. In this study, we have taken into account the first step towards producing tunable nanophotonic devices with applications ranging from optoelectronics to nonlinear optics.