Vertically stacked transition metal dichalcogenide-graphene heterostructures provide a platform for novel optoelectronic applications with high photoresponse speeds. Photoinduced nonequilibrium carrier and lattice dynamics in such heterostructures underlie these applications but have not been understood. In particular, the dependence of these photoresponses on the twist angle, a key tuning parameter, remains elusive. Here, using ultrafast electron diffraction, we report the simultaneous visualization of charge transfer and electron−phonon coupling in MoS 2 -graphene heterostructures with different stacking configurations. We find that the charge transfer timescale from MoS 2 to graphene varies strongly with twist angle, becoming faster for smaller twist angles, and show that the relaxation timescale is significantly shorter in a heterostructure as compared to a monolayer. These findings illustrate that twist angle constitutes an additional tuning knob for interlayer charge transfer in heterobilayers and deepen our understanding of fundamental photophysical processes in heterostructures, of importance for future applications in optoelectronics and light harvesting.

I n response to highly unpredictable sudden-onset natural disasters, efficient and effective management of disaster relief inventory (DRI) is essential. This study proposes a simple framework based on three fundamental DRI-related decision themes, which are (1) who respond to DRI calling, (2) where to locate DRI, and (3) how to control DRI, aiming at identifying the research gaps between the realities' calling and the literature's consideration with a focus on DRI management. We review relevant literature for each decision theme, summarize the insights provided by the literature, assess the practical needs and procedures and present our detailed perspectives on the research gaps in practice. The chief implication from our observations and arguments is that scaling up a DRI response for catastrophic disasters and events which prepares the whole community for worst-case scenarios has been highlighted in academics and practice but lack operational research in the area of relevant decision-making tactics. Existing research concerning the DRI management issues of various coordination forms of disaster responders, the location-allocation decision-making determinants with DRI prepositioning and the DRI control policy in the face of various disaster uncertainties is still far from being fully understood, appropriately characterized and profoundly discussed. We recommend the potential future research areas with the implications of this review in the last conclusion section, wishing to provide researchers a better understanding of the needs in the real-world.

Excitons are elementary optical excitation in semiconductors. The ability to manipulate and transport these quasiparticles would enable excitonic circuits and devices for quantum photonic technologies. Recently, interlayer excitons in 2D semiconductors have emerged as a promising candidate for engineering excitonic devices due to their long lifetime, large exciton binding energy, and gate tunability. However, the charge-neutral nature of the excitons leads to weak response to the in-plane electric field and thus inhibits transport beyond the diffusion length. Here, we demonstrate the directional transport of interlayer excitons in bilayer WSe2 driven by the propagating potential traps induced by surface acoustic waves (SAW). We show that at 100 K, the SAW-driven excitonic transport is activated above a threshold acoustic power and reaches 20 μm, a distance at least ten times longer than the diffusion length and only limited by the device size. Temperature-dependent measurement reveals the transition from the diffusion-limited regime at low temperature to the acoustic field-driven regime at elevated temperature. Our work shows that acoustic waves are an effective, contact-free means to control exciton dynamics and transport, promising for realizing 2D materials-based excitonic devices such as exciton transistors, switches, and transducers up to room temperature.

Single‐cell Hi‐C technology is emerging and will provide unprecedented opportunities to elucidate chromosomal dynamics with high resolution. How to characterize pseudo time‐series of single cells using single‐cell Hi‐C maps is an essential and challenging topic. To this end, a powerful circular trajectory reconstruction tool CIRCLET is developed to resolve cell cycle phases of single cells by considering multiscale features of chromosomal architectures without specifying a starting cell. CIRCLET reveals its best superiority based on the combination of one feature set about global information and another two feature sets about local interactional information in terms of designed evaluation indexes and verification strategies from a collection of cell‐cycle Hi‐C maps of 1171 single cells. Further division of the reconstructed trajectory into 12 stages helps to accurately characterize the dynamics of chromosomal structures and explain the special regulatory events along cell‐cycle progression. Last but not the least, the reconstructed trajectory helps to uncover important regulatory genes related with dynamic substructures, providing a novel framework for discovering regulatory regions even cancer markers at single‐cell resolution.

Combining path consistency (PC) algorithms with conditional mutual information (CMI) are widely used in reconstruction of gene regulatory networks. CMI has many advantages over Pearson correlation coefficient in measuring non-linear dependence to infer gene regulatory networks. It can also discriminate the direct regulations from indirect ones. However, it is still a challenge to select the conditional genes in an optimal way, which affects the performance and computation complexity of the PC algorithm. In this study, we develop a novel conditional mutual information-based algorithm, namely RPNI (Regulation Pattern based Network Inference), to infer gene regulatory networks. For conditional gene selection, we define the co-regulation pattern, indirect-regulation pattern and mixture-regulation pattern as three candidate patterns to guide the selection of candidate genes. To demonstrate the potential of our algorithm, we apply it to gene expression data from DREAM challenge. Experimental results show that RPNI outperforms existing conditional mutual information-based methods in both accuracy and time complexity for different sizes of gene samples. Furthermore, the robustness of our algorithm is demonstrated by noisy interference analysis using different types of noise.

The chromosome conformation capture (3C) technique and its variants have been employed to reveal the existence of a hierarchy of structures in three-dimensional (3D) chromosomal architecture, including compartments, topologically associating domains (TADs), sub-TADs and chromatin loops. However, existing methods for domain detection were only designed based on symmetric Hi-C maps, ignoring long-range interaction structures between domains. To this end, we proposed a generic and efficient method to identify multi-scale topological domains (MSTD), including cis- and trans- interacting regions, from a variety of 3D genomic datasets. We first applied MSTD to detect promoter-anchored interaction domains (PADs) from promoter capture Hi-C datasets across 17 primary blood cell types. The boundaries of PADs are significantly enriched with one or the combination of multiple epigenetic factors. Moreover, PADs between functionally similar cell types are significantly conserved in terms of domain regions and expression states. Cell type-specific PADs involve in distinct cell type-specific activities and regulatory events by dynamic interactions within them. We also employed MSTD to define multi-scale domains from typical symmetric Hi-C datasets and illustrated its distinct superiority to the-state-of-art methods in terms of accuracy, flexibility and efficiency.

Motivation CTCF-mediated chromatin loops underlie the formation of topological associating domains (TADs) and serve as the structural basis for transcriptional regulation. However, the formation mechanism of these loops remains unclear, and the genome-wide mapping of these loops is costly and difficult. Motivated by the recent studies on the formation mechanism of CTCF-mediated loops, we studied the possibility of making use of transitivity-related information of interacting CTCF anchors to predict CTCF loops computationally. In this context, transitivity arises when two CTCF anchors interact with the same third anchor by the loop extrusion mechanism and bring themselves close to each other spatially to form an indirect loop. Results To determine whether transitivity is informative for predicting CTCF loops and to obtain an accurate and low-cost predicting method, we proposed a two-stage random-forest-based machine learning method, CCIP (CTCF-mediated Chromatin Interaction Prediction), to predict CTCF-mediated chromatin loops. Our two-stage learning approach makes it possible for us to train a prediction model by taking advantage of transitivity-related information as well as functional genome data and genomic data. Experimental studies showed that our method predicts CTCF-mediated loops more accurately than other methods and that transitivity, when used as a properly defined attribute, is informative for predicting CTCF loops. Furthermore, we found that transitivity explains the formation of tandem CTCF loops and facilitates enhancer-promoter interactions. Our work contributes to the understanding of the formation mechanism and function of CTCF-mediated chromatin loops. Availability and implementation The source code of CCIP can be accessed at: https://github.com/GaoLabXDU/CCIP. Supplementary information Supplementary data are available at Bioinformatics online.

Disaster relief supplies (DRS) play a vital role in natural disaster rescue and relief operations. Often DRS management is initiated and supported by the government, yet the related cost issues have not been fully emphasized. In the face of highly uncertain disaster locations and timing, these supplies are usually prepositioned without proper consumption, which causes enormous waste in practice both economically and environmentally. This chapter highlights the potential to bring the reverse logistics strategies in conventional business practice into DRS management. Incorporating the reverse flow of removed relief items with DRS supply chain management not only benefits in cost reduction and environmental protection, but also enhance the daily management and quality control of DRS. Relying on social trust and efficient marketing network provided by government coordination and international cooperation, the stable quality level and relatively integrated inventories of the removed DRS can achieve economies of scale in the reverse supply chain operations. This chapter aims to develop an understanding of DRS reverse logistics, which energizes the responsible management of DRS for economic, social, and environmental sustainability.