Moir\'e excitons: from programmable quantum emitter arrays to spin-orbit coupled artificial lattices

Highly uniform and ordered nanodot arrays are crucial for high performance quantum optoelectronics including new semiconductor lasers and single photon emitters, and for synthesizing artificial lattices of interacting quasiparticles towards quantum information processing and simulation of many-body physics. Van der Waals heterostructures of 2D semiconductors are naturally endowed with an ordered nanoscale landscape, i.e. the moir\'e pattern that laterally modulates electronic and topographic structures. Here we find these moir\'e effects realize superstructures of nanodot confinements for long-lived interlayer excitons, which can be either electrically or strain tuned from perfect arrays of quantum emitters to excitonic superlattices with giant spin-orbit coupling (SOC). Besides the wide range tuning of emission wavelength, the electric field can also invert the spin optical selection rule of the emitter arrays. This unprecedented control arises from the gauge structure imprinted on exciton wavefunctions by the moir\'e, which underlies the SOC when hopping couples nanodots into superlattices. We show that the moir\'e hosts complex-hopping honeycomb superlattices, where exciton bands feature a Dirac node and two Weyl nodes, connected by spin-momentum locked topological edge modes.Comment: To appear in Science Advance

Heterologous Expression and Enzymatic Properties of Nicotinamide Nucleoside Kinase from Saccharomyces cerevisiae

In this study, the nicotinamide riboside kinase 1 gene (ScNRK1) was cloned from Saccharomyces cerevisiae, and its soluble expression in Escherichia coli was achieved using pET28a plasmid. The enzyme activity in the fermentation broth was 14.75 IU/mL, and the specific activity the purified enzyme was 2 252.59 IU/mg. In addition, the kinetic parameters of ScNRK1 were significantly higher than those of other reported nicotinamide nucleoside kinases, so ScNRK1 could be more advantageous in the enzymatic synthesis of nicotinamide mononucleotide (NMN)

Ancient polymorphisms and divergence hitchhiking contribute to genomic islands of divergence within a poplar species complex

How genome divergence eventually leads to speciation is a topic of prime evolutionary interest. Genomic islands of elevated divergence are frequently reported between diverging lineages, and their size is expected to increase with time and gene flow under the speciation-with-gene-flow model. However, such islands can also result from divergent sorting of ancient polymorphisms, recent ecological selection regardless of gene flow, and/or recurrent background selection and selective sweeps in low-recombination regions. It is challenging to disentangle these nonexclusive alternatives, but here we attempt to do this in an analysis of what drove genomic divergence between four lineages comprising a species complex of desert poplar trees. Within this complex we found that two morphologically delimited species, Populus euphratica and Populus pruinosa, were paraphyletic while the four lineages exhibited contrasting levels of gene flow and divergence times, providing a good system for testing hypotheses on the origin of divergence islands. We show that the size and number of genomic islands that distinguish lineages are not associated with either rate of recent gene flow or time of divergence. Instead, they are most likely derived from divergent sorting of ancient polymorphisms and divergence hitchhiking. We found that highly diverged genes under lineage-specific selection and putatively involved in ecological and morphological divergence occur both within and outside these islands. Our results highlight the need to incorporate demography, absolute divergence measurement, and gene flow rate to explain the formation of genomic islands and to identify potential genomic regions involved in speciation.Publisher PDFPeer reviewe

Language reorganization patterns in global aphasia–evidence from fNIRS

BackgroundExploring the brain reorganization patterns associated with language recovery would promote the treatment of global aphasia. While functional near-infrared spectroscopy (fNIRS) has been widely used in the study of speech and language impairment, its application in the field of global aphasia is still limited.AimsWe aimed to identify cortical activation patterns of patients with global aphasia during naming and repetition tasks.Methods and proceduresWe recruited patients with post-stroke aphasia from the Department of Rehabilitation Medicine at Huashan Hospital. These individuals were diagnosed with global aphasia without cognitive impairments, as assessed by speech-language pathology evaluations. Age- and sex-matched healthy controls were recruited from the greater Shanghai area. During fNIRS measurement, patients and healthy controls completed the picture-naming and phrase repetition task. Cortical activation patterns on each of these language tasks were then compared between groups.Outcomes and resultsA total of nine patients with global aphasia and 14 healthy controls were included in this study. Compared with the healthy subjects, patients with global aphasia showed increased activation in the left Broca's area, middle temporal gyrus (MTG), superior temporal gyrus (STG), and pre-motor and supplementary motor cortex (SMA) (p < 0.05) in the picture-naming task. Furthermore, the latency of the oxyhemoglobin (HbO) concentration in the left supramarginal gyrus (SMG) region had a strong negative correlation with their score of the naming task (p < 0.01). In the phrase repetition task, decreased activation was detected in the left SMA and SMG (p < 0.05) of patients relative to controls.ConclusionThe left SMG plays a critical role in the language function of patients with global aphasia, especially in their abilities to name and repeat. fNIRS is a promising approach to revealing the changes in brain activities in patients with aphasia, and we believe it will contribute to a deeper understanding of the neurological mechanisms and the establishment of a novel treatment approach for global aphasia

Investigation of the influence of model control parameters on fracture characteristics of GPU parallel FDEM

Abstract Surrounding rock mass fracture characteristics play a significant role in the understanding of the CO2 geological storage and utilization (CGSU) engineering practices in abandoned mines. The combined finite discrete element method (FDEM) shows advantages in simulating fracture and fragmentation of rock-like materials, however, many computational parameters and a lack of basis for accurate values affect the simulation results. For systematic explorations of the influence of the effect of model parameters with different time steps, this study conducted different loading rate specimen tests and unloading rate tests both in laboratory-scale tests and field-scale based on the CUDA-based GPU parallel FDEM program. In laboratory-scale uniaxial compressive strength (UCS) tests, a smaller loading rate ensures a quasi-static loading process and should be below 0.1 ms−1 for simulation. Then, continuous optimization and improvement of the GPU parallel FDEM in tunnel excavation were proposed, and the model parameters reflect the continuous improvement of the simulation results. In the process, the tunnel excavation simulation method with the reduction rate of the opening zone’s Young's modulus in the excavation was performed to investigate the unloading mode and rate by continuing to optimize the GPU parallel FDEM program and model parameters. Besides, the main factor in fracture mode and failure mechanism of the surrounding rock mass also was calibrated. The results indicate that the system kinetic energy of the model is maintained at a small level with the reasonable unloading mode and critical threshold set at a small value, the damping parameters, dissipation mechanism, and excavation fractures are clearer and reasonable, and the computational cost is significantly reduced with GPU parallel FDEM

A helitron-induced RabGDIα variant causes quantitative recessive resistance to maize rough dwarf disease

Maize rough dwarf disease (MRDD), caused by various species of the genus Fijivirus, threatens maize production worldwide. We previously identified a quantitative locus qMrdd1 conferring recessive resistance to one causal species, rice black-streaked dwarf virus (RBSDV). Here, we show that Rab GDP dissociation inhibitor alpha (RabGDIα) is the host susceptibility factor for RBSDV. The viral P7-1 protein binds tightly to the exon-10 and C-terminal regions of RabGDIα to recruit it for viral infection. Insertion of a helitron transposon into RabGDIα intron 10 creates alternative splicing to replace the wild-type exon 10 with a helitron-derived exon 10. The resultant splicing variant RabGDIα-hel has difficulty being recruited by P7-1, thus leading to quantitative recessive resistance to MRDD. All naturally occurring resistance alleles may have arisen from a recent single helitron insertion event. These resistance alleles are valuable to improve maize resistance to MRDD and potentially to engineer RBSDV resistance in other crops

CSR in the Czech Republic - Case study ČSOB

This thesis deals with the topic of corporate social responsibility while drawing mainly on the political theories of CSR formation. Its theoretical part discusses CSR concept in general, depicting its contributions as well as its seaminess. Further it focuses on the application of CSR in the European and Czech context. Although a lot of companies within the Czech Republic identify themselves with the idea of CSR, ČSOB bank is one of the first ones that applied CSR strategically and is considered as one of the leaders in the field. Case study in the empirical part of the thesis examines specific comprehension of CSR in ČSOB and asses it. In the very end CSR in ČSOB is being confronted with the context of CSR in Czech bank sector

Additional file 1: Figure S1. of Ploidy effect and genetic architecture exploration of stalk traits using DH and its corresponding haploid populations in maize

Route used to develop DH population and the corresponding haploid populations. Figure S2. Presentation of DH and haploid populations planted in field. Figure S3. Histogram for genotypic percentage in DH population. Figure S4. QTL detected frequency for RPR and IVDMD in DH and haploid populations with five-split cross validation for 1000 times. For RPR, the QTL at bin 2.02 and 5.05 were detected in DH and haploid population with high frequencies in the 1000 cross-validation, respectively. For IVDMD, the QTL at bin 8.04 and 8.05 were detected in DH and haploid population with high frequencies in the 1000 cross-validation, respectively. Table S1. Primer sequences of genes involved in lignin and cellulose synthesis for RT-PCR. Table S2. Summary of SNP characteristics of DH population. Table S3. Summary of the linkage map characteristics DH population. Table S4. QTL detected for other stalk traits in DH and haploid populations. Table S5. Annotation of the 45 predicted genes located within putative RPR QTL interval in DH population. Table S6. Annotation of the 191 predicted genes located within putative RPR QTL interval in haploid population. Table S7. Annotation of the 24 predicted genes located within the putative IVDMD QTL interval in DH population. Table S8. Annotation of the 191 predicted genes located within putative IVDMD QTL interval in haploid population. (DOCX 870 kb