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Cryptanalysts have been looking for differential characteristics in ciphers for decades and it remains unclear how the subkey values and more generally the Markov assumption impacts exactly their probability estimation. There were theoretical efforts considering some simple linear relationships between differential characteristics and subkey values, but the community has not yet explored many possible nonlinear dependencies one can find in differential characteristics. Meanwhile, the overwhelming majority of cryptanalysis works still assume complete independence between the cipher rounds. We give here a practical framework and a corresponding tool to investigate all such linear or nonlinear effects and we show that they can have an important impact on the security analysis of many ciphers. Surprisingly, this invalidates many differential characteristics that appeared in the literature in the past years: we have checked differential characteristics from 8 articles (4 each for both SKINNY and GIFT) and most of these published paths are impossible or working only for a very small proportion of the key space. We applied our method to SKINNY and GIFT, but we expect more impossibilities for other ciphers. To showcase our advances in the dependencies analysis, in the case of SKINNY we are able to obtain a more accurate probability distribution of a differential characteristic with respect to the keys (with practical verification when it is computationally feasible). Our work indicates that newly proposed differential characteristics should now come with an analysis of how the key values and the Markov assumption might or might not affect/invalidate them. In this direction, more constructively, we include a proof of concept of how one can incorporate additional constraints into Constraint Programming so that the search for differential characteristics can avoid (to a large extent) differential characteristics that are actually impossible due to dependency issues our tool detected. Published version

Triplosphaeria guizhouensis L.L. Liu & Z.Y. Liu, sp. nov. Figure 2. Index Fungorum number: IF 900370; Facesoffungi number: FoF 10694 Etymology: In reference to the host location, Guizhou province, where the holotype was collected. Saprobic on decaying submerged wood in freshwater habitats. Asexual morph: Colonies on natural substrate effuse, consisting of individual conidium scattered over the substrate surface, conspicuous, brown to black. Mycelium mostly immersed, consisting of branched, septate, smooth, subhyaline to pale brown hyphae. Conidiophores absent. Conidiogenous cells monoblastic. Conidia solitary, straight or slightly curved, conidia body 18.9–23 × 8–9 μm (x = 21 × 8.5 μm, n = 15), composed of three or four columns of cells, 5–7-septate in each column, guttulate, smooth-walled or sometimes verrucose on the base cell, with 3–4 setose appendages. Appendages (4.7–) 12.6–18.9 (–21.5) long, 1–1.5 μm wide, divergent, pale brown to brown, 2–4-septate, straight or slightly flexuous, smooth-walled. Sexual morph: Undetermined. Cultural characteristics: Conidia germinating on WA and germ tubes produced from appendages within 12 h. Colonies on PDA growing slowly, reaching 20–25 mm DIAM. after one month at 25°C, under dark condition, circular, consisting of a matted felt with velutinous appearance, umbonate, surface of the colony mouse grey, in reverse brown. Material examined: CHINA, Guizhou Province, Chishui City, Chishui river basin, 28°25′N, 106°0′E, at an altitude of 204 m, on submerged decaying wood in a stream, 16 July 2019, L.L. Liu, CS1-18-1 (GZAAS 20–0407, holotype), ex-type living culture GZCC 19–0512. Notes: Triplosphaeria guizhouensis shares similar morphological characteristics with the tetraploa -like anamorph in having cylindrical conidia with columns of cells and apical appendages (Tanaka et al., 2009). Phylogenetic analyses of combined LSU, ITS, SSU, tef1-α, and β-tubulin sequence data indicates that the new strain (GZAAS20-0407) nested within the Tetraplosphaeriaceae, and was resolved as a monophyletic clade with the genus Triplosphaeria (FIGURE 1). Triplosphaeria guizhouensis can be distinguished from other Triplosphaeria species in having conidia with ¾ columns and ¾ setose appendages. Moreover, the conidia of T. guizhouensis on the host plant differs from those of Triplosphaeria produced under culture conditions in having smaller conidia and shorter appendages (TABLE 2). Triplosphaeria sp. formed smaller conidia on the host plant also (TABLE 2) (Tanaka et al., 2009). In phylogenetic analysis, T. guizhouensis is sister to Tetraplosphaeria sp. (HHUF 27481) (Figure 1). Morphologically, T. guizhouensis is well distinguishable from Triplosphaeria sp. by quite smaller conidia (18.9–23 × 8–9 µm vs. (26–) 31.5–46 × 14–23 µm) and shorter appendages ((4.7–) 12.6–18.9 (–21.5) µm vs. 36–90µm). The teleomorph of T. guizhouensis is unknown, however based on anamorph form and molecular data, it clearly belongs to Triplosphaeria., Published as part of Liu, Ling-Ling, Feng, Yao, Wei, Quan-Quan, Zhang, Meng, Gu, Xiao-Feng, Liu, Zuo-Yi & Gou, Jiu-Lan, 2023, Triplosphaeria guizhouensis sp. nov. (Tetraplosphaeriaceae, Pleosporales), a novel taxon from freshwater habitat in Guizhou Province, China, pp. 173-183 in Phytotaxa 603 (2) on pages 177-179, DOI: 10.11646/phytotaxa.603.2.4, http://zenodo.org/record/8157954, {"references":["Tanaka, K., Hirayama, K., Yonezawa, H., Hatakeyama, S., Harada, Y., Sano, T., Shirouzu, T. & Hosoya, T. (2009) Molecular taxonomy of bambusicolous fungi: Tetraplosphaeriaceae, a new pleosporalean family with tetraploa-like anamorphs. Studies in Mycology 64: 175 - 209. https: // doi. org / 10.3114 / sim. 2009.64.10"]}

Epigenetic modifications are essential for plant development. EFD encodes a SAM-dependent methyltransferase essential for the pollen wall pattern formation and male fertility in Arabidopsis. Here, we found that the expression of DRM2, a de novo DNA methyltransferase in plants, can complement the defects of efd, suggesting its de novo DNA methyltransferase ability. Genetic analysis reveals that EFD plays roles through HB21 as its knockout fully restored the efd fertility. The methylation and H3K27me3 analysis indicates that EFD represses the transcription expression of HB21 through epigenetic modifications. Besides, both EMSA and tobacco transient expression assays showed that HB21 repressed the expression of the genes including CalS5, RPG1/SWEET8, CYP703A2 and NST2 which are essential for pollen formation and anther dehiscence. Altogether, our study reveals a double negative regulatory cascade mediated by epigenetic modifications to coordinate anther development, which provides new insights into epigenetic regulation and anther development.

As a novel VTOL unmanned aerial vehicle, lifting-wing multicopter with simple structure, good stability and longer flight range has been unveiled to be in service. But how to make range as long as possible to realize its potential advantages is one of the key issues in the practical application of lifting-wing multicopter. Thus, this study aims to propose a range and transition time performance evaluation to realize a sizing optimization design method for the lifting-wing multicopter. First, the dynamic model and the propulsion system model are established. Based on these models, evaluation methods for range and transition time performance are obtained with the consideration of mounting angle. Second, the influences of the main parameters on range performance are studied to offer references for design. Then, an explicit design process is proposed. Finally, a prototype is implemented, and flight experiments are performed to verify the evaluation and design method. The results indicate that the performance evaluation method has enough accuracy and suggest that it is possible to design a lifting-wing multicopter using the presented design method.

Chemical bonds, including covalent and ionic bonds, endow semiconductors with stable electronic configurations but also impose constraints on their synthesis and lattice-mismatched heteroepitaxy. Here, the unique multi-scale van der Waals (vdWs) interactions are explored in one-dimensional tellurium (Te) systems to overcome these restrictions, enabled by the vdWs bonds between Te atomic chains and the spontaneous misfit relaxation at quasi-vdWs interfaces. Wafer-scale Te vdWs nanomeshes composed of self-welding Te nanowires are laterally vapor grown on arbitrary surfaces at a low temperature of 100 °C, bringing greater integration freedoms for enhanced device functionality and broad applicability. The prepared Te vdWs nanomeshes can be patterned at the microscale and exhibit high field-effect hole mobility of 145 cm2/Vs, ultrafast photoresponse below 3 μs in paper-based infrared photodetectors, as well as controllable electronic structure in mixed-dimensional heterojunctions. All these device metrics of Te vdWs nanomesh electronics are promising to meet emerging technological demands.

Adenoid Cystic Carcinoma (ACC) has been considered as a "quiet" tumor. It is typically malignancy arising from exocrine glands with poor long-term prognosis due to high rate of recurrence and distant metastasis. It is characterized by perineural infiltration, distant metastasis, and positive incision edge. Surgery is the first line treatment for ACC, followed by cytotoxic chemotherapy and/or radiotherapy as adjuvant treatments to avoid recurrence. But recurrence or metastasis still occurs in more than 50% ACC. Recurrent and/or metastasis (R/M) ACC is usually incurable, and no systemic agent has been found effective. With the widespread use of whole exome sequencing (WES) and whole genome sequencing (WGS), its internal oncogenic mechanism is gradually revealed, which involving molecular mutations such as the MYB family gene translocation, Notch signal pathway, DNA damage repair (DDR) pathway and epigenetic molecular mutations. The review helps us to understand the linkage among the pathways and targeted genes in diagnosis and related treatment of ACC till now.

As global warming continues, extreme precipitation events occur frequently in inland areas, seriously affecting human security and the ecological environment. Spatiotemporal evolution of extreme precipitation as well as response of extreme precipitation to climatic warming and its mechanism were investigated by considering the Weihe river basin in a monsoon transition zone of China as a research object. The results indicate that while the annual average temperature of the Weihe river basin increased with fluctuations from 1966 to 2017, except for the consecutive dry days (CDD) and simple daily intensity index that increased slightly, the other extreme precipitation indices (consecutive wet days, R25, and Rx5day) tended to decrease. Moreover, except for the CDD, the other four indices gradually increased from the northwest to the southeast, showing a similar trend to the temperature. The relationship between the 95th percentile threshold and temperature (hereinafter referred to as the P 95d–T relationship) in the Weihe river basin demonstrates the hook structure and its strength in terms of response is mainly dominated by the super-Clausius–Clapeyron (C–C) and C–C scaling. Furthermore, the peak temperature rises gradually from the northwest to the southeast. The results can provide important reference for the prediction of climate change and future studies of disaster risk in the Weihe river basin.

A hierarchical Co@NCNT/CoMoOx precatalyst is designed, and then a surface self-reconstruction process is deliberately induced, resulting in a superior alkaline HER performance with 600 h stability even in alkaline natural seawater.

Atomically two-dimensional (2D) layered ferroelectric semiconductors, in which the polarization switching process occurs within the channel material itself, offer a new material platform that could drive electronic components towards structural simplification and high-density integration. Here, a room-temperature 2D layered ferroelectric semiconductor, bismuth oxychalcogenides (Bi

The augmentation parameters matter to few-shot semantic segmentation since they directly affect the training outcome by feeding the networks with varying perturbated samples. However, searching optimal augmentation parameters for few-shot segmentation models without annotations is a challenge that current methods fail to address. In this paper, we first propose a framework to determine the ``optimal'' parameters without human annotations by solving a distribution-matching problem between the intra-instance and intra-class similarity distribution, with the intra-instance similarity describing the similarity between the original sample of a particular anatomy and its augmented ones and the intra-class similarity representing the similarity between the selected sample and the others in the same class. Extensive experiments demonstrate the superiority of our optimized augmentation in boosting few-shot segmentation models. We greatly improve the top competing method by 1.27\% and 1.11\% on Abd-MRI and Abd-CT datasets, respectively, and even achieve a significant improvement for SSL-ALP on the left kidney by 3.39\% on the Abd-CT dataset.

One-shot medical landmark detection gains much attention and achieves great success for its label-efficient training process. However, existing one-shot learning methods are highly specialized in a single domain and suffer domain preference heavily in the situation of multi-domain unlabeled data. Moreover, one-shot learning is not robust that it faces performance drop when annotating a sub-optimal image. To tackle these issues, we resort to developing a domain-adaptive one-shot landmark detection framework for handling multi-domain medical images, named Universal One-shot Detection (UOD). UOD consists of two stages and two corresponding universal models which are designed as combinations of domain-specific modules and domain-shared modules. In the first stage, a domain-adaptive convolution model is self-supervised learned to generate pseudo landmark labels. In the second stage, we design a domain-adaptive transformer to eliminate domain preference and build the global context for multi-domain data. Even though only one annotated sample from each domain is available for training, the domain-shared modules help UOD aggregate all one-shot samples to detect more robust and accurate landmarks. We investigated both qualitatively and quantitatively the proposed UOD on three widely-used public X-ray datasets in different anatomical domains (i.e., head, hand, chest) and obtained state-of-the-art performances in each domain. The code is available at https://github.com/heqin-zhu/UOD_universal_oneshot_detection., Comment: Eealy accepted by MICCAI 2023. 11pages, 4 figures, 2 tables. arXiv admin note: text overlap with arXiv:2203.06433

It is often necessary for drones to complete delivery, photography, and rescue in the shortest time to increase efficiency. Many autonomous drone races provide platforms to pursue algorithms to finish races as quickly as possible for the above purpose. Unfortunately, existing methods often fail to keep training and racing time short in drone racing competitions. This motivates us to develop a high-efficient learning method by imitating the training experience of top racing drivers. Unlike traditional iterative learning control methods for accurate tracking, the proposed approach iteratively learns a trajectory online to finish the race as quickly as possible. Simulations and experiments using different models show that the proposed approach is model-free and is able to achieve the optimal result with low computation requirements. Furthermore, this approach surpasses some state-of-the-art methods in racing time on a benchmark drone racing platform. An experiment on a real quadcopter is also performed to demonstrate its effectiveness.

Hybrid unmanned aerial vehicles (UAVs) integrate the efficient forward flight of fixed-wing and vertical takeoff and landing (VTOL) capabilities of multicopter UAVs. This paper presents the modeling, control and simulation of a new type of hybrid micro-small UAVs, coined as lifting-wing quadcopters. The airframe orientation of the lifting wing needs to tilt a specific angle often within $ 45$ degrees, neither nearly $ 90$ nor approximately $ 0$ degrees. Compared with some convertiplane and tail-sitter UAVs, the lifting-wing quadcopter has a highly reliable structure, robust wind resistance, low cruise speed and reliable transition flight, making it potential to work fully-autonomous outdoor or some confined airspace indoor. In the modeling part, forces and moments generated by both lifting wing and rotors are considered. Based on the established model, a unified controller for the full flight phase is designed. The controller has the capability of uniformly treating the hovering and forward flight, and enables a continuous transition between two modes, depending on the velocity command. What is more, by taking rotor thrust and aerodynamic force under consideration simultaneously, a control allocation based on optimization is utilized to realize cooperative control for energy saving. Finally, comprehensive Hardware-In-the-Loop (HIL) simulations are performed to verify the advantages of the designed aircraft and the proposed controller.

Herein, we report a novel one-pot method for synthesizing polysubstituted pyrrole derivatives via three-component reactions of alkenyl bromides, amines, and isocyanides. The conversion process is catalyzed by a Pd catalyst...

Deep learning is becoming increasingly ubiquitous in medical research and applications while involving sensitive information and even critical diagnosis decisions. Researchers observe a significant performance disparity among subgroups with different demographic attributes, which is called model unfairness, and put lots of effort into carefully designing elegant architectures to address unfairness, which poses heavy training burden, brings poor generalization, and reveals the trade-off between model performance and fairness. To tackle these issues, we propose FairAdaBN by making batch normalization adaptive to sensitive attribute. This simple but effective design can be adopted to several classification backbones that are originally unaware of fairness. Additionally, we derive a novel loss function that restrains statistical parity between subgroups on mini-batches, encouraging the model to converge with considerable fairness. In order to evaluate the trade-off between model performance and fairness, we propose a new metric, named Fairness-Accuracy Trade-off Efficiency (FATE), to compute normalized fairness improvement over accuracy drop. Experiments on two dermatological datasets show that our proposed method outperforms other methods on fairness criteria and FATE., Comment: Accepted by MICCAI 2023

Background: The combination of inhibitory and facilitatory repetitive transcranial magnetic stimulation (rTMS) can improve motor function of stroke patients with undefined mechanism. It has been demonstrated that rTMS exhibits a neuro-modulatory effect by regulating the major inhibitory neurotransmitter γ-aminobutyric acid (GABA) in other diseases. Objectives: To evaluate the effect of combined inhibitory and facilitatory rTMS on GABA in the primary motor cortex (M1) for treating motor dysfunction after acute ischemic stroke. Methods: 44 ischemic stroke patients with motor dysfunction were randomly divided into two groups. The treatment group was stimulated with 10 Hz rTMS at the ipsilesional M1 and 1 Hz rTMS at the contralesional M1. The sham group received bilateral sham stimulation at the motor cortices. The GABA level in the bilateral M1 was measured by proton magnetic resonance spectroscopy (1H-MRS) at 24 hours before and after rTMS stimulation. Motor function was measured using the Fugl-Meyer Assessment (FMA). The clinical assessments were performed before and after rTMS and after 3 months. Results: The treatment group exhibited a greater improvement in motor function 24 hours after rTMS compared to the sham group. The increased improvement in motor function lasted for at least 3 months after treatment. Following 4 weeks of rTMS, the GABA level in the ipsilesional M1 of the treatment group was significantly decreased compared to the sham group. Furthermore, the change of FMA score for motor function was negatively correlated to the change of the GABA:Cr ratio. Finally, the effect of rTMS on motor function outcome was partially mediated by GABA level change in response to the treatment (27.7%). Conclusions: Combining inhibitory and facilitatory rTMS can decrease the GABA level in M1, which is correlated to the improvement of motor function. Thus, the GABA level in M1 may be a potential biomarker for treatment strategy decisions regarding rTMS neuromodulatory interventions.

Purpose For patients with lung malignancies with RET rearrangement, the efficacy of immune checkpoint inhibitors is limited. The characteristics of the tumour immune microenvironment (TIME) and molecular pathological features of these patients have not been well elucidated. Methods The pathology and TIME characteristics of 29 patients with lung malignancies with RET rearrangement were retrospectively analysed, and their relationships with clinical efficacy and prognosis were investigated. Gene detection relied on high-throughput sequencing, and TIME detection was based on multiplex immunohistochemistry technology. Results Of the 29 patients, 86% (25/29) had adenocarcinoma, and the acinar type accounted for the greatest percentage of patients, followed by the solid type, regardless of whether the disease was early or locally advanced and metastatic. In addition, we report a novel KIF5B-RET(k24:R8) rearrangement in pulmonary sarcoma. The density of CD8 + T cells in the tumour stroma in the early-stage patients was significantly higher than that in the locally advanced and metastatic patients (P = 0.014). The proportion of M2 macrophages in the tumour stroma was significantly higher than that in the tumour parenchyma (P = 0.046). Although the difference was not statistically significant (P = 0.098), patients positive for M2 macrophage infiltration into the tumour parenchyma (≥ 5%) may have had a better prognosis. Conclusions A novel KIF5B-RET rearrangement variant in pulmonary sarcoma shows similar TIME characteristics to lung cancer. Among patients with lung malignancies with RET rearrangement, patients with M2 macrophage infiltration into the tumour parenchyma may have a better prognosis, but further studies with larger cohorts are needed.

Brain radiomics can reflect the characteristics of brain pathophysiology. However, the value of T1-weighted images, quantitative susceptibility mapping, and R2* mapping in the diagnosis of Parkinson's disease (PD) was underestimated in previous studies. In this prospective study to establish a model for PD diagnosis based on brain imaging information, we collected high-resolution T1-weighted images, R2* mapping, and quantitative susceptibility imaging data from 171 patients with PD and 179 healthy controls recruited from August 2014 to August 2019. According to the inclusion time, 123 PD patients and 121 healthy controls were assigned to train the diagnostic model, while the remaining 106 subjects were assigned to the external validation dataset. We extracted 1408 radiomics features, and then used data-driven feature selection to identify informative features that were significant for discriminating patients with PD from normal controls on the training dataset. The informative features so identified were then used to construct a diagnostic model for PD. The constructed model contained 36 informative radiomics features, mainly representing abnormal subcortical iron distribution (especially in the substantia nigra), structural disorganization (e.g., in the inferior temporal, paracentral, precuneus, insula, and precentral gyri), and texture misalignment in the subcortical nuclei (e.g., caudate, globus pallidus, and thalamus). The predictive accuracy of the established model was 81.1 ± 8.0% in the training dataset. On the external validation dataset, the established model showed predictive accuracy of 78.5 ± 2.1%. In the tests of identifying early and drug-naïve PD patients from healthy controls, the accuracies of the model constructed on the same 36 informative features were 80.3 ± 7.1% and 79.1 ± 6.5%, respectively, while the accuracies were 80.4 ± 6.3% and 82.9 ± 5.8% for diagnosing middle-to-late PD and those receiving drug management, respectively. The accuracies for predicting tremor-dominant and non-tremor-dominant PD were 79.8 ± 6.9% and 79.1 ± 6.5%, respectively. In conclusion, the multiple-tissue-specific brain radiomics model constructed from magnetic resonance imaging has the ability to discriminate PD and exhibits the advantages for improving PD diagnosis.

Automated methods have become crucial components when searching for distinguishers against symmetric-key cryptographic primitives. While MILP and SAT solvers are among the most popular tools to model ciphers and perform cryptanalysis, other methods with different performance profiles are appearing. In this article, we explore the use of Constraint Programming (CP) for differential cryptanalysis on the Ascon authenticated encryption family (first choice of the CAESAR lightweight applications portfolio and current finalist of the NIST LWC competition) and its internal permutation. We first present a search methodology for finding differential characteristics for Ascon with CP, which can easily find the best differential characteristics already reported by the Ascon designers. This shows the capability of CP in generating easily good differential results compared to dedicated search heuristics. Based on our tool, we also parametrize the search strategies in CP to generate other differential characteristics with the goal of forming limited-birthday distinguishers for 4, 5, 6 and 7 rounds and rectangle attacks for 4 and 5 rounds of the Ascon internal permutation. We propose a categorization of the distinguishers into black-box and non-black-box to better differentiate them as they are often useful in different contexts. We also obtained limited-birthday distinguishers which represent currently the best known distinguishers for 4, 5 and 6 rounds under the category of non-black-box distinguishers. Leveraging again our tool, we have generated forgery attacks against both reduced-rounds Ascon-128 and Ascon-128A, improving over the best reported results at the time of writing. Finally, using the best differential characteristic we have found for 2 rounds, we could also improve a recent attack on round-reduced Ascon-HAsh. Agency for Science, Technology and Research (A*STAR) Published version The authors are supported by the Temasek Laboratories.

In practice, the unbalanced mass of the propeller is the leading cause of vibration in a quadcopter. First, a mechanical model of the unbalanced masses is established. Next, consider the vibration reduction problem for quadcopter attitude control. A notch filter is incorporated into to an additive-state-decomposition dynamic inversion controller to obtain a new controller. Stability analysis shows that the proposed control method guarantees that all attitude signals are globally uniformly ultimately bounded. In particular, the notch filter can effectively reduce the vibration having a specific frequency. Finally, the proposed controller is performed on a real quadcopter to verify its vibration reduction performance.

Eutrophication generally promotes but destabilizes grassland productivity. Under eutrophication, plants tend to decrease biomass allocation to roots but increase aboveground allocation and light limitation, likely affecting community stability. However, it remains unclear to understand how shifting plant biomass allocation and light limitation regulate grassland stability in response to eutrophication. Here, using a 5-yr multiple nutrient addition experiment in an alpine meadow, we explored the role of changes in plant biomass allocation and light limitation on its community stability under eutrophication as well as traditionally established mechanisms (i.e., plant Shannon diversity, species asynchrony and grass subcommunity stability). Our results showed that nitrogen (N) addition, rather than phosphorus (P) or potassium (K) addition, significantly reduced the temporal stability of the alpine meadow. In accordance with previous studies, we found that N addition decreased plant Shannon diversity, species asynchrony and grass subcommunity stability, further destabilizing meadow community productivity. In addition, we also found the decrease in biomass allocation to belowground by N addition, further weakening its community stability. Moreover, this shifts in plant biomass allocation from below- to aboveground, intensifying plant light limitation. Further, the light limitation reduced plant species asynchrony, which finally weakened its community stability. Overall, in addition to traditionally established mechanisms, this study highlights the role of plant biomass allocation shifting from belowground to aboveground in determining grassland community stability. These "unseen" mechanisms might improve our understanding of grassland stability in the context of ongoing eutrophication.

The frequency and severity of extreme weather events are increasing and expected to increase more in the future, together with global change. However, how extreme events and global change factors interactively influence community structures and ecosystem processes is largely unknown. Here, we investigated the responses of the temporal stability and resilience of aboveground net primary productivity (ANPP) of an alpine meadow to an extreme flooding event under different treatments of experimental drought and clipping. We found that ecosystems that were exposed to drought treatments for 3 years significantly decreased the temporal stability of community productivity but increased resilience to flooding, whereas their resistance to or recovery from flooding did not change. Neither clipping nor its interaction with drought altered the responses of these community stability metrics to flooding. Drought treatments significantly decreased plant species richness and asynchrony and dominant species stability, leading to a decrease in temporal stability and an increase in resilience in response to the extreme flooding event. The study also revealed that the change in species asynchrony was the dominant impact pathway determining the responses of resilience and temporal stability to flooding. Our results highlight that alpine grassland that experiences a multiyear drought may aggravate the instability of community productivity to extreme climatic events by reducing species asynchrony.

The incapability of modulating the photoresponse of assembled heterostructure devices has remained a challenge for the development of optoelectronics with multifunctionality. Here, a gate-tunable and anti-ambipolar phototransistor is reported based on 1D GaAsSb nanowire/2D MoS