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To investigate the long-term treatment outcomes of early stage bulky cervical cancer treated with definite chemoradiotherapy (CCRT) using intensity-modulated radiotherapy (IMRT) followed by intracavity brachytherapy (ICRT) and the impact of histologic subtype on survival.From 2004 to 2016, 126 patients with FIGO stage IB2-IIB bulky (≥4 cm) cervical cancer treated with CCRT followed by ICRT were retrospectively reviewed. Long-term treatment-related acute/late toxicities and treatment outcomes including overall survival (OS), locoregional recurrence-free survival (LRRFS), and distant metastasis-free survival (DMFS) were reported. Different histologic subtype between squamous cell carcinoma (SCC) and adenocarcinoma/adenosquamous carcinoma (AC/ASC)) of uterine cervix were also compared.Median follow-up time for alive patients was 117 months. The 5-year OS, LRRFS and DMFS were 75.3%, 87.8% and 75.6%, respectively. The most common ≥ grade 3 acute toxicity was hematologic toxicity (41.3%). The rates of ≥ grade 3 late toxicities were 4% of proctitis, 0.8% of urethral stricture and 0.8% of radiation dermatitis (peri-anal skin necrosis and gangrene). The 5-year OS/LRRFS/DMFS for SCC and AC/ASC were 81.7%/93.7%/81.5% and 51.9%/65.8%/53.5%, respectively (all log-rank p 0.05). The AC/ASC histology was an independent prognostic factor for worse OS, LRRFS, and DMFS (All p 0.05).After long-term follow up, definite CCRT using IMRT followed by ICRT is a feasible treatment with favorable acute and late treatment toxicities for patients with early stage bulky cervical cancer. This treatment outcomes were excellent for "bulky" FIGO stage IB2-IIB SCC of the uterine cervix but seemed insufficient for AC/ASC of uterine cervix.

In this paper, we introduce the notion of Lie $ n $-centralizers. We then give a description of Lie $ n $-centralizers on a generalized matrix algebra and present the necessary and sufficient conditions for a Lie $ n $-centralizer to be proper. As applications, we determine generalized Lie $ n $-derivations on a generalized matrix algebra and Lie $ n $-centralizers of some operator algebras.

The improvement of treatment for patients with 'driver-gene-negative' lung adenocarcinoma (LUAD) remains a critical problem to be solved. We aimed to explore the role of methylation of N6 adenosine (m6A)-related long noncoding RNA (lncRNA) in stratifying 'driver-gene-negative' LUAD risk. Patients negative for mutations in EGFR, KRAS, BRAF, HER2, MET, ALK, RET, and ROS1 were identified as 'driver-gene-negative' cases. RNA sequencing was performed in 46 paired tumors and adjacent normal tissues from patients with 'driver-gene-negative' LUAD. Twenty-three m6A regulators and relevant lncRNAs were identified using Pearson's correlation analysis. K-means cluster analysis was used to stratify patients, and a prognostic nomogram was developed. The CIBERSORT and pRRophetic algorithms were employed to quantify the immune microenvironment and chemosensitivity. We identified two clusters highly consistent with the prognosis based on their unique expression profiles for 46 m6AlncRNAs. A risk model constructed from nine m6A lncRNAs could stratify patients into high- and low-risk groups with promising predictive power (C-index = 0.824), and the risk score was an independent prognostic factor. The clusters and risk models were closely related to immune characteristics and chemosensitivity. Additional pan-cancer analysis using the nine m6AlncRNAs showed that the expression of DIO3 opposite strand upstream RNA (DIO3OS) is closely related to the immune/stromal score and tumor stemness in a variety of cancers. Our results show that m6AlncRNAs are a reliable prognostic tool and can aid treatment decision-making in 'driver-gene-negative' LUAD. DIO3OS is associated with the development of various cancers and has potential clinical applications.

Hyacinth, one of the five best-selling bulbous flowers in the world, is a favored flower of garden landscapes in the spring. Hyacinth has a single origin, but there are many horticultural varieties. Physical mapping of ribosomal DNA (rDNA) and telomeric repeat loci by fluorescence in situ hybridization (FISH) is helpful to understand the genetic relationship and chromosome inheritance in hyacinth breeding. In this study, 45S rDNA, 5S rDNA and telomeric repeats were used as probes, the mitotic metaphase chromosomes of 8 diploid hyacinth cultivars were analyzed by FISH location, and their karyotype parameters were analyzed by Q-type cluster analysis. The results showed that two 45S rDNA loci were detected in all eight hyacinth cultivars, four 5S rDNA loci were detected in ‘Gypsy Queen’, and three were detected in other cultivars. In addition to the presence of telomere loci at both ends of chromosomes, seven telomere loci were detected in ‘Gypsy Princess’ and ‘Yellow Stone’, and eight telomere loci were detected in other cultivars. At the same time, when the euclidean distance between groups was 20, the eight hyacinth cultivars were clustered into three groups (‘Yellow Stone’, ‘Red Pearl’ and ‘Pink Pearl’), and ‘Gypsy Prince’ was a single group; the other four cultivars were in one group. The distribution of 45S rDNA loci in diploid hyacinth cultivars was relatively conservative, while the locus number and distribution of 5S rDNA and telomeric repeats were highly polymorphic. The FISH physical mapping in this study provides a basic understanding of the karyotype evolution of hyacinth species, which could increase the understanding of the evolutionary history and phylogenetic relationships of hyacinths.

Parkinson's disease (PD) is a chronic neurodegenerative disease mainly characterized by movement disorders and other non-motor symptoms, including the loss of dopaminergic neurons in the substantia nigra parts. Abnormal α-synuclein aggregation in the brain is closely associated with the loss of dopaminergic neurons. α-synuclein can propagate in the central nervous system (CNS) and periphery under pathological conditions. Many researches have focused on its aggregation and distribution in the CNS and explored its relationship with PD. But in recent years, the distribution of α-synuclein in peripheral tissues have been paid much attention. This review summarized the distribution of α-synuclein in the choroid plexus, blood, saliva, gastrointestine and other tissues, and discussed the potential mechanism of α-synuclein aggregation, providing a basis for the early diagnosis and intervention of PD.

Examining the role of immune-related genes (IRGs) in "driver gene negative" lung adenocarcinoma (LUAD) may provide new ideas for the treatment and study for this LUAD subgroup. We aimed to find the hub immune-related gene pairs can stratify the risk of "driver-gene-negative" LUAD.IRGs were identified according to ImmPort database based on RNA sequencing results of tumors and normal tissues from 46 patients with "driver gene negative" LUAD at The First Affiliated Hospital of Sun Yat-sen University and cyclically singly paired as immune-related gene pairs (IRGPs). Multivariate Cox analysis was used to construct an immune risk model and a prognostic nomogram combining was also been developed. Immune microenvironment landscape described by CIBERSORT and drug sensitivity calculated by pRRophetic algorithm were used to explore possible treatment improvements.A novel immune risk model with 5-IRGPs (CD1A|CXCL135, CD1A|S100A7L2, IFNA7|CMTM2, IFNA7|CSF3, CAMP|TFR2) can accurately distinguish patients in the high- and low-risk groups. Risk score act as an independent prognostic factor and is related to clinical stage. There are significant differences in tumor immune microenvironment and PD-1/PD-L1/CTLA-4 expression between groups. The low-risk patient may benefit more from the commonly used chemotherapy regimens such as gemcitabine and paclitaxel.This study constructed 5-IRGPs as a reliable prognostic tool and may represent genes pairs that are potential rationale for choice of treatment for "driver gene negative" LUAD.

Neuroinflammation is closely related to the pathogenesis of neurodegenerative diseases. Activation of microglia, the resident immune cells in CNS, induces inflammatory responses, resulting in the release of neurotoxic molecules, which favors neuronal death and neurodegeneration. Nuclear receptor-related 1 (Nurr1) protein, one of the orphan nuclear receptor superfamilies, is an emerging target for neuroprotective therapy. In addition, the anti-inflammatory function of cannabinoid (CB) receptors has attracted increasing interest. As both CB receptors (especially CB2 receptor) and Nurr1 exist in microglia, and regulate a number of same molecular points such as NF-κB, we herein explored the interplay between the CB2 receptor and Nurr1 as well as the regulatory mechanisms in microglial cells. We showed that the application of CB2 receptor agonists JWH015 (1, 10 μM) significantly increased the nuclear Nurr1 protein in BV-2 cells and primary midbrain microglia. Overexpression of Nurr1 or application of Nurr1 agonist C-DIM12 (10 μM) significantly increased the mRNA level of CB2 receptor in BV-2 cells, suggesting that positive expression feedback existing between the CB2 receptor and Nurr1. After 2-AG and JWH015 activated the CB2 receptors, the levels of p-ERK, p-AKT, p-GSK-3β in BV-2 cells were significantly increased. Using ERK1/2 inhibitor U0126 and PI3K/AKT inhibitor LY294002, we revealed that the amount of Nurr1 in the nucleus was upregulated through β-arrestin2/ERK1/2 and PI3K/AKT/GSK-3β signaling pathways. With these inhibitors, we found a cross-talk interaction between the two pathways, and the ERK1/2 signaling pathway played a more dominant regulatory role. Furthermore, we demonstrated that when the CB2 receptor was activated, the phagocytic function of BV-2 cells was significantly weakened; the activation of Nurr1 also inhibited the phagocytic function of BV-2 cells. Pretreatment with the signaling pathway inhibitors, especially U0126, reversed the inhibitory effect of 2-AG on phagocytosis, suggesting that CB2 receptor may regulate the phagocytic function of microglia by activating Nurr1. In conclusion, CB2 receptor or/and Nurr1-mediated signal pathways play instrumental roles in the progress of phagocytosis, which are expected to open up new treatment strategies for neurodegenerative diseases.

The orbital angular momentum (OAM) holography has been developed and experimentally demonstrated the capability of holographic multiplexation and high-security encryption. However, the helical phase of an OAM mode can only be encoded into one hologram associated with a target image, and this severely limits the information capacity in practical applications. The modulated orbital angular momentum (MOAM) holography is proposed by imposing multiple modulation phase modes onto one OAM mode. Three essential properties, including the MOAM-preservation, MOAM-selectivity and MOAM-multiplexation are investigated. This method can significantly enhance the holographic information capacity and it has broad prospects for optical encryption and beam manipulations.

In this study, we examined online conversations on Twitter about the Russia-Ukraine War and investigated differences between bots and non-bots accounts. Using ‘Russia’ and ‘Ukraine’ as keywords, we employed a Twitter API to collect data from 17 February to 18 March on Twitter. We obtained a large dataset of over 3.7 million tweets generated by about one million distinct accounts. We then analyzed one percent of the data using interval sampling for bot detection and found that about 13.4 percent of the accounts were social media bots, responsible for about 16.7 percent of the tweets. We examined the difference between bots and non-bots regarding online conversations on the Russia-Ukraine War through account analysis, textual analysis, and interaction analysis. The results show that bots exist on both sides, bots from the Ukrainian side contributed a louder voice while bots on the Russian side demonstrated more effective communication. In addition, there were differences and similarities between bots and non-bots in the behavior of online conversations, but the difference seemed to be relatively weaker than those found in previous studies.

The treatment of infected bone defects in complex oral and maxillofacial structures remains a challenge. An injectable gellan gum (GG)-based hydrogel loaded with nanohydroxyapatite particles and chlorhexidine (nHA/CHX) can accelerate the repair of infected bone defects.

In the process of drilling, the drilling fluid will invade into the bedding plane of shale under the action of pressure difference that will cause hydration collapse and wellbore instability. In order to ensure the wellbore stability during shale oil and gas drilling, it is necessary to clarify the invasion law of drilling fluid along bedding fractures during the drilling process. The immersion experiment method is often used to study the invasion law of drilling fluid, which is quite different from the actual invasion process of drilling fluid underground. In this paper, the depth of drilling fluid invasion into shale under different confining pressures and displacement times is intuitively and accurately determined by the displacement experiment and NMR scanning first. Also, then the mathematical relationships between drilling fluid invasion depth and invasion time, invasion pressure difference, confining pressure, bedding angle, and drilling fluid viscosity were established. The errors between the calculated values of the drilling fluid invasion depth and the experimental values were less than 15%, and the calculation accuracy was high. In addition to the influence of invasion time, formation pressure difference and confining pressure on invasion depth were researched through the method of numerical simulation. The results showed that the liquid invasion depth increased logarithmically with the increase of invasion time and formation pressure difference, but it grew slowly in the later period and tended to be stable; the invasion depth decreased exponentially with the increase of confining pressure, bedding plane angle, and drilling fluid viscosity. The results in the paper provide a basis for the subsequent determination of the collapse pressure and collapse period of bedding shale.

Deep neural networks (DNNs) may suffer from significantly degenerated performance when the training and test data are of different underlying distributions. Despite the importance of model generalization to out-of-distribution (OOD) data, the accuracy of state-of-the-art (SOTA) models on OOD data can plummet. Recent work has demonstrated that regular or off-manifold adversarial examples, as a special case of data augmentation, can be used to improve OOD generalization. Inspired by this, we theoretically prove that on-manifold adversarial examples can better benefit OOD generalization. Nevertheless, it is nontrivial to generate on-manifold adversarial examples because the real manifold is generally complex. To address this issue, we proposed a novel method of Augmenting data with Adversarial examples via a Wavelet module (AdvWavAug), an on-manifold adversarial data augmentation technique that is simple to implement. In particular, we project a benign image into a wavelet domain. With the assistance of the sparsity characteristic of wavelet transformation, we can modify an image on the estimated data manifold. We conduct adversarial augmentation based on AdvProp training framework. Extensive experiments on different models and different datasets, including ImageNet and its distorted versions, demonstrate that our method can improve model generalization, especially on OOD data. By integrating AdvWavAug into the training process, we have achieved SOTA results on some recent transformer-based models., Comment: Computer Vision and Image Understanding (CVIU) [under review]

Mentions of new concepts appear regularly in texts and require automated approaches to harvest and place them into Knowledge Bases (KB), e.g., ontologies and taxonomies. Existing datasets suffer from three issues, (i) mostly assuming that a new concept is pre-discovered and cannot support out-of-KB mention discovery; (ii) only using the concept label as the input along with the KB and thus lacking the contexts of a concept label; and (iii) mostly focusing on concept placement w.r.t a taxonomy of atomic concepts, instead of complex concepts, i.e., with logical operators. To address these issues, we propose a new benchmark, adapting MedMentions dataset (PubMed abstracts) with SNOMED CT versions in 2014 and 2017 under the Diseases sub-category and the broader categories of Clinical finding, Procedure, and Pharmaceutical / biologic product. We provide usage on the evaluation with the dataset for out-of-KB mention discovery and concept placement, adapting recent Large Language Model based methods., Comment: The dataset, data construction scripts, and baseline implementation are available at https://zenodo.org/record/8043690 (Zenodo) and https://github.com/KRR-Oxford/OET (GitHub)

DNNs are one of the most widely used Deep Learning models. The matrix multiplication operations for DNNs incur significant computational costs and are bottlenecked by data movement between the memory and the processing elements. Many specialized accelerators have been proposed to optimize matrix multiplication operations. One popular idea is to use Processing-in-Memory where computations are performed by the memory storage element, thereby reducing the overhead of data movement between processor and memory. However, most PIM solutions rely either on novel memory technologies that have yet to mature or bit-serial computations which have significant performance overhead and scalability issues. In this work, an in-SRAM digital multiplier is proposed to take the best of both worlds, i.e. performing GEMM in memory but using only conventional SRAMs without the drawbacks of bit-serial computations. This allows the user to design systems with significant performance gains using existing technologies with little to no modifications. We first design a novel approximate bit-parallel multiplier that approximates multiplications with bitwise OR operations by leveraging multiple wordlines activation in the SRAM. We then propose DAISM - Digital Approximate In-SRAM Multiplier architecture, an accelerator for convolutional neural networks, based on our novel multiplier. This is followed by a comprehensive analysis of trade-offs in area, accuracy, and performance. We show that under similar design constraints, DAISM reduces energy consumption by 25\% and the number of cycles by 43\% compared to state-of-the-art baselines., Comment: 12 pages, 9 figures

Additional file 1: Table S1. Comparisons of our genomic assembly with previous published genomic assembly of Agrostis ipsilon. Table S2. Circadian clock components in genome of Agrosis ipsilon. Table S3. Juvenile hormone regulatory pathway in genome of Agrosis ipsilon. Table S4. Top 10 GSEA enriched pathways after different durations of tethered-flight moths of Agrostis ipsilon. Table S5. Primers used in this study.

Discovering entity mentions that are out of a Knowledge Base (KB) from texts plays a critical role in KB maintenance, but has not yet been fully explored. The current methods are mostly limited to the simple threshold-based approach and feature-based classification, and the datasets for evaluation are relatively rare. We propose BLINKout, a new BERT-based Entity Linking (EL) method which can identify mentions that do not have corresponding KB entities by matching them to a special NIL entity. To better utilize BERT, we propose new techniques including NIL entity representation and classification, with synonym enhancement. We also propose KB Pruning and Versioning strategies to automatically construct out-of-KB datasets from common in-KB EL datasets. Results on five datasets of clinical notes, biomedical publications, and Wikipedia articles in various domains show the advantages of BLINKout over existing methods to identify out-of-KB mentions for the medical ontologies, UMLS, SNOMED CT, and the general KB, WikiData.

Applying deep learning techniques, particularly language models (LMs), in ontology engineering has raised widespread attention. However, deep learning frameworks like PyTorch and Tensorflow are predominantly developed for Python programming, while widely-used ontology APIs, such as the OWL API and Jena, are primarily Java-based. To facilitate seamless integration of these frameworks and APIs, we present Deeponto, a Python package designed for ontology engineering. The package encompasses a core ontology processing module founded on the widely-recognised and reliable OWL API, encapsulating its fundamental features in a more "Pythonic" manner and extending its capabilities to include other essential components including reasoning, verbalisation, normalisation, projection, and more. Building on this module, Deeponto offers a suite of tools, resources, and algorithms that support various ontology engineering tasks, such as ontology alignment and completion, by harnessing deep learning methodologies, primarily pre-trained LMs. In this paper, we also demonstrate the practical utility of Deeponto through two use-cases: the Digital Health Coaching in Samsung Research UK and the Bio-ML track of the Ontology Alignment Evaluation Initiative (OAEI)., Comment: under review at Semantic Web Journal

The robustness of deep neural networks is usually lacking under adversarial examples, common corruptions, and distribution shifts, which becomes an important research problem in the development of deep learning. Although new deep learning methods and robustness improvement techniques have been constantly proposed, the robustness evaluations of existing methods are often inadequate due to their rapid development, diverse noise patterns, and simple evaluation metrics. Without thorough robustness evaluations, it is hard to understand the advances in the field and identify the effective methods. In this paper, we establish a comprehensive robustness benchmark called \textbf{ARES-Bench} on the image classification task. In our benchmark, we evaluate the robustness of 55 typical deep learning models on ImageNet with diverse architectures (e.g., CNNs, Transformers) and learning algorithms (e.g., normal supervised training, pre-training, adversarial training) under numerous adversarial attacks and out-of-distribution (OOD) datasets. Using robustness curves as the major evaluation criteria, we conduct large-scale experiments and draw several important findings, including: 1) there is an inherent trade-off between adversarial and natural robustness for the same model architecture; 2) adversarial training effectively improves adversarial robustness, especially when performed on Transformer architectures; 3) pre-training significantly improves natural robustness based on more training data or self-supervised learning. Based on ARES-Bench, we further analyze the training tricks in large-scale adversarial training on ImageNet. By designing the training settings accordingly, we achieve the new state-of-the-art adversarial robustness. We have made the benchmarking results and code platform publicly available., Comment: International Journal of Computer Vision (IJCV) [under review]

Additional file 2: Fig. S1. Life cycle of Agrotis ipsilon and crop damage. Fig. S2. Distribution of 17-mer frequency in Agrotis ipsilon. Fig. S3. Chromosomes of Agrotis ipsilon in cell of testis from fifth instar larvae. Thirty-one pairs (2n = 62) were present at diakinesis during meiosis. Fig. S4. Venn plot of gene function in five databases in Agrotis ipsilon. Fig. S5. Dot plots of syntenic orthologous between A. ipsilon and S. litura. Fig. S6. KEGG analysis of rapidly expanded gene families in Agrostis ipsilon. Fig. S7. Expression profiles of P450 genes in different tissues and developmental stages of Agrostis ipsilon. Fig. S8. Distribution of P450 genes on the chromosomes of A. ipsilon. Fig. S9. Expression profiles of GST genes in different tissues and developmental stages of Agrostis ipsilon. Fig. S10. Distribution of GST genes on the chromosomes of Agrostis ipsilon. Fig. S11. The expression level of pigment-dispersing factor (PDF) in heads of migrating moths and tethered-flight moths. Fig. S12. The expression level of JH signaling pathway genes, Broad and Kr-h1, in different tissues of migrating moths and tethered-flight moths (*p < 0.05, **p < 0.01). Fig. S13. RNA-seq of tethered-flight. Fig. S14. GSEA after different durations of tethered-flight moths of Agrostis ipsilon. Fig. S15. Trend analysis of DEGs after different durations of tethered flight. Fig. S16. GSEA analysis of southward and northward migrating moths.

Chimera states are firstly discovered in nonlocally coupled oscillator systems. Such a nonlocal coupling arises typically as oscillators are coupled via an external environment whose characteristic time scale $\tau$ is so small (i.e., $\tau \rightarrow 0$) that it could be eliminated adiabatically. Nevertheless, whether the chimera states still exist in the opposite situation (i.e., $\tau \gg 1$) is unknown. Here, by coupling large populations of Stuart-Landau oscillators to a diffusive environment, we demonstrate that spiral wave chimeras do exist in this oscillator-environment coupling system even when $\tau$ is very large. Various transitions such as from spiral wave chimeras to spiral waves or unstable spiral wave chimeras as functions of the system parameters are explored. A physical picture for explaining the formation of spiral wave chimeras is also provided. The existence of spiral wave chimeras is further confirmed in ensembles of FitzHugh-Nagumo oscillators with the similar oscillator-environment coupling mechanism. Our results provide an affirmative answer to the observation of spiral wave chimeras in populations of oscillators mediated via a slowly changing environment and give important hints to generate chimera patterns in both laboratory and realistic chemical or biological systems., Comment: 28 pages, 8 figures

This documentary opens the gate to a courtyard and the lives of the Yang family as they look into the past and towards the future for guidance on how to secure a home in post-reform China. Yang used to live with his two uncles in his ancestral courtyard home until the Land Reform swept the country in the 1950's. As a result of the collectivization that ensued, his uncles were assigned `landlord´ class status, stripped of their property rights and evicted. Because he enjoyed `middle peasant´ status, Yang was allowed to stay. However, he was force to share the Yang clan courtyard with three poor peasant families, and has been living with them ever since. Today in post-Reform China's market economy, property rights have been restored and many Chinese are seeking to better their living conditions. The aging Yang now has the opportunity to buy back a portion of his family courtyard. At the same time, Yang's son dreams of building a courtyard home by the lake. This documentary opens the gate to the Yang ancestral courtyard and sheds light on the lives and emotions of the family as they look into the past and towards the future for guidance on how to secure a home in which they and the future generations of Yangs can continue to prosper.

Background: Pulverized coal detection is an indispensable detection measure in the coal industry. The current detection devices can be divided into two types: invasive and non-invasive. The coal dust detection methods and devices based on acoustics, optics, and electricity have been extensively studied. In order to achieve a high-efficiency online detection scheme, improving the accuracy and stability of the detection means is the primary goal of the research. Objective: The general problems and characteristics of coal dust detection device design are summarized, as well as recent technological developments and the need for online testing to predict future research trends. Methods: The current typical detection devices are classified according to the detection principle and whether they invade the target, analyzing its advantages and disadvantages according to the device performance and application scenarios. Results: It has a beneficial effect on the design of the pulverized coal concentration detection device. Conclusion: The paper summarizes and analyzes several representative coal concentration detection device patents in recent years. Then it points out advantages and main problems. On this basis, the main development direction of the coal dust concentration detection device in the future is discussed.

We report the efficient syntheses of chiral tetrahydroindole pyrazolinones by the asymmetric [3 + 2] cascade cyclizations (indolizations) of simple aniline derivatives with pyrazolinone ketimines as 2C synthons. The chiral phosphoric-acid-catalyzed system uses a concerted π-π interaction/dual H-bond control strategy to catalytically direct the asymmetric aniline, which undergoes a highly chemo-, regio-, and enantioselective [3 + 2] cascade annulation, furnishing a series of optically active tetra-hydroindole pyrazolinones with two contiguous chiral aza-quaternary carbon centers in excellent yields with excellent enantioselectivities. This method features a relatively broad substrate scope for amines and 2-naphthylamines and highlights the emerging value of direct chiral indolizations from simple amine sources in organic synthesis.

MXenes, a new family of two-dimensional (2D) materials, have received extensive interest due to their fascinating physicochemical properties, such as outstanding light-to-heat conversion efficiency. However, the photothermal conversion mechanism of MXenes is still poorly understood. Here, by using femtosecond visible and mid-infrared transient absorption spectroscopy, the electronic energy dissipation dynamics of MXene (Ti3C2Tx) nanosheets dispersed in various solvents are carefully studied. Our results indicate that the lifetime of photoexcited MXene is strongly dependent on the surrounding environment. Especially, the interfacial electron-vibration coupling between the MXene nanosheets and the adjacent solvent molecules is directly observed following the ultrafast photoexcitation of MXene. It suggests that the interfacial interactions at the MXene-solvent interface play a critical role in the ultrafast energy transport dynamics of MXene, which offers a potentially feasible route for tailoring the light conversion properties of 2D systems.

The generation method of three-dimensional fractal discrete fracture network (FDFN) based on multiplicative cascade process was developed. The complex multi-scale fracture system in shale after fracturing was characterized by coupling the artificial fracture model and the natural fracture model. Based on an assisted history matching (AHM) using multiple-proxy-based Markov chain Monte Carlo algorithm (MCMC), an embedded discrete fracture modeling (EDFM) incorporated with reservoir simulator was used to predict productivity of shale gas well. When using the natural fracture generation method, the distribution of natural fracture network can be controlled by fractal parameters, and the natural fracture network generated coupling with artificial fractures can characterize the complex system of different- scale fractures in shale after fracturing. The EDFM, with fewer grids and less computation time consumption, can characterize the attributes of natural fractures and artificial fractures flexibly, and simulate the details of mass transfer between matrix cells and fractures while reducing computation significantly. The combination of AMH and EDFM can lower the uncertainty of reservoir and fracture parameters, and realize effective inversion of key reservoir and fracture parameters and the productivity forecast of shale gas wells. Application demonstrates the results from the proposed productivity prediction model integrating FDFN, EDFM and AHM have high credibility.

This paper presents RF-Transformer, a unified backscatter radio hardware abstraction that allows a low-power IoT device to directly communicate with heterogeneous wireless receivers at the minimum power consumption. Unlike existing backscatter systems that are tailored to a specific wireless communication protocol, RF-Transformer provides a programmable interface to the micro-controller, allowing IoT devices to synthesize different types of protocol-compliant backscatter signals sharing radically different PHY-layer designs. To show the efficacy of our design, we implement a PCB prototype of RF-Transformer on 2.4 GHz ISM band and showcase its capability on generating standard ZigBee, Bluetooth, LoRa, and Wi-Fi 802.11b/g/n/ac packets. Our extensive field studies show that RF-Transformer achieves 23.8 Mbps, 247.1 Kbps, 986.5 Kbps, and 27.3 Kbps throughput when generating standard Wi-Fi, ZigBee, Bluetooth, and LoRa signals while consuming 7.6-74.2 less power than their active counterparts. Our ASIC simulation based on the 65-nm CMOS process shows that the power gain of RF-Transformer can further grow to 92-678. We further integrate RF-Transformer with pressure sensors and present a case study on detecting foot traffic density in hallways. Our 7-day case studies demonstrate RFTransformer can reliably transmit sensor data to a commodity gateway by synthesizing LoRa packets on top of Wi-Fi signals. Our experimental results also verify the compatibility of RF-Transformer with commodity receivers. Code and hardware schematics can be found at: https://github.com/LeFsCC/RF-Transformer.

The Ediacaran–Cambrian period witnessed episodic extinctions, oxygenation of seawaters, Cambrian explosions, and tectonic events. However, compared with the various high-resolution geochemical records of the early–middle Ediacaran and Cambrian, the available geochemical record of the latest Ediacaran (551–542 Ma) is scarce (especially the strontium isotope and elements), which leads to the ambiguous interpretation of the paleoenvironment of the latest Ediacaran. Therefore, we conducted measurements of strontium isotopes and elemental content of a continuous series of carbonate samples from the Dengying Formation of Well PT1, located in the Sichuan Basin, southeastern Tibetan Plateau, in order to constrain the paleoenvironment of the latest Ediacaran. Strict sample screening was used to ensure that the isotopes and elements were not affected by diagenesis. Our analyses show that the environment and geochemical records of the seawater were controlled by tectonic activities, especially the Gondwana assembly. The global strontium isotope correlation indicates that the Sichuan Basin was a restricted basin (high 87Sr/86Sr values, ∼0.7090), which can be attributed to the existence of a submarine high. Under the background of oxic environment, there were two episodes of anoxic expansion. During the initial stage, the stable terrigenous detrital input and oxic environment provided the prerequisite for the emergence of aerobic organisms in the restricted platform. Then, the decreasing sea level and intense tectonic activities improved the terrigenous detrital input with higher 87Sr/86Sr values (∼0.7095), which stimulated the emergence of aerobic organisms, further resulting in the first episode of anoxic environment. Lastly, a global transgressive resulted in a high sea level, and thus, the Sichuan Basin changed to an open platform. The exchange with extensive oceans led to the increased paleoproductivity, which consumed oxygen and nutrients, further resulting in the second episode of anoxic environment. Thus, the restriction degree, eustatic variations, and the terrigenous detrital input affected the biological evolution and redox conditions.

In this study, we determine the generalization performance of the long and short questionnaire version (i.e. cross validation: fit model on data set from a new set of ASAs). It involves crowd workers on an online platform. They will be asked to use the questionnaire instrument to rate an interaction between an agent and a human user, which is displayed in a 30 second video clip.

This research is the second study into the validation of the questionnaire instrument for evaluating human interaction with an artificial social agent. It involves crowd workers on an online crowdsourcing platform. They will be asked to use the questionnaire instrument to rate an interaction between an agent and a human user, which is displayed in a 30 second video clip. The result of this study will be analysed and used to examine the associations of questionnaire items with the latent constructs, i.e. construct validity.

A novel Gram-stain-negative, aerobic, rod-shaped, non-flagellated, and gliding bacterial strain, designated DF109T, was isolated from the coastal sediment of Jingzi Wharf, Weihai, China. The optimal growth occurs at 28°C, pH 7.0–7.5, and 1.0% (w/v) NaCl environment. The colony was yellow-colored, convex, non-transparent, and circular on 2216E Agar. Phylogenetic analyses of the 16S rRNA gene and genome sequence of this newly isolated strain revealed that it is a member of the genus Gelidibacter within the family Flavobacteriaceae. The phylogenetic analysis based on 16S rRNA gene sequences indicated that strain DF109T has the highest sequence similarity to Gelidibacter japonicus JCM 31967T (98.0%). The average nucleotide identity (ANI) values between genomes of DF109T and G. japonicus JCM 31967T and G. algens DSM 12408T were 86.3% and 78.7% and the digital DNA–DNA hybridization (dDDH) values were 31.4% and 22.4%, respectively. The sole isoprenoid quinone was MK-6 and the major cellular fatty acids were iso-C15:1G, iso-C17:0 3-OH, anteiso-C15:0, and iso-C16:0 3-OH. The major polar lipids of strain DF109T were an aminolipid, a phosphatidylethanolamine, and four unidentified lipids. The genomic DNA G+C content was 37.5 mol%. Strain DF109T is suggested to represent a novel species in the genus Gelidibacter, for which the name Gelidibacter pelagius sp. nov. is proposed. The type strain is DF109T (=MCCC 1H00454T=KCTC 82420T).

Based on drilling data of JT1 and CS1, outcrop profiles and seismic data, the sedimentary pattern, space configuration of source-reservoir-cap combinations and paleouplift evolution characteristics of the Cambrian Lower Canglangpu Member in the central Sichuan paleouplift have been investigated to determine the favorable exploration zones. Controlled by Deyang-Anyue rift, the Lower Canglangpu Member features differential characteristics from east to west in sedimentary framework. In the west side of the Deyang-Anyue rift, this member is composed of clastic sediments, while in the east side of the Deyang-Anyue rift, it is fresh water shelf sediments, with grain beaches occurring along edges of the depressions, shelf and lagoon. Among the beaches, the dolomitic ones are mainly distributed around the depression edge and in the north of the lagoon. The beach sediments could become high quality reservoirs under the effect of karstification. Underlying the Lower Canglangpu Member is the widespread source rock of the Qiongzhusi Formation, so oil and gas generated by the Qiongzhusi Formation source rock can directly charge into the beach reservoirs. The sandy mudstone of the Upper Canglangpu Member can serve as the caprock of the Lower Canglangpu Member reservoir. The dolomitic beaches are located at the higher part of the paleo-uplift during the main accumulation period, with good hydrocarbon accumulation elements. Blocks PT1-CS1, HT1-GT2 and east GT2 are favorable exploration zones.

For a coupled nonlinear Schrodinger system with the negative coherent coupling, which describes two orthogonally polarized pulses in a weakly birefringent fibre, we construct the Darboux dressing t...

Parkinson's disease (PD) is a severe neurodegenerative disorder caused by the progressive loss of dopaminergic neurons in the substantia nigra and affects millions of people. Currently, mitochondrial dysfunction is considered as a central role in the pathogenesis of both sporadic and familial forms of PD. Mitophagy, a process that selectively targets damaged or redundant mitochondria to the lysosome for elimination via the autophagy devices, is crucial in preserving mitochondrial health. So far, aberrant mitophagy has been observed in the postmortem of PD patients and genetic or toxin-induced models of PD. Except for mitochondrial dysfunction, mitophagy is involved in regulating several other PD-related pathological mechanisms as well, e.g., oxidative stress and calcium imbalance. So far, the mitophagy mechanisms induced by PD-related proteins, PINK1 and Parkin, have been studied widely, and several other PD-associated genes, e.g., DJ-1, LRRK2, and alpha-synuclein, have been discovered to participate in the regulation of mitophagy as well, which further strengthens the link between mitophagy and PD. Thus, in this view, we reviewed mitophagy pathways in belief and discussed the interactions between mitophagy and several PD's pathological mechanisms and how PD-related genes modulate the mitophagy process.

Virtual try-on(VTON) aims at fitting target clothes to reference person images, which is widely adopted in e-commerce.Existing VTON approaches can be narrowly categorized into Parser-Based(PB) and Parser-Free(PF) by whether relying on the parser information to mask the persons' clothes and synthesize try-on images. Although abandoning parser information has improved the applicability of PF methods, the ability of detail synthesizing has also been sacrificed. As a result, the distraction from original cloth may persistin synthesized images, especially in complicated postures and high resolution applications. To address the aforementioned issue, we propose a novel PF method named Regional Mask Guided Network(RMGN). More specifically, a regional mask is proposed to explicitly fuse the features of target clothes and reference persons so that the persisted distraction can be eliminated. A posture awareness loss and a multi-level feature extractor are further proposed to handle the complicated postures and synthesize high resolution images. Extensive experiments demonstrate that our proposed RMGN outperforms both state-of-the-art PB and PF methods.Ablation studies further verify the effectiveness ofmodules in RMGN., Accepted by IJCAI2022

In this contribution, we thoroughly investigated the ring-opening alternating copolymerization (ROAC) of cyclic anhydride and epoxide by using commercially available alkali metal carboxylates (AMCs...

In this paper, outcomes of the study on the Backlund transformation, Lax pair, and interactions of nonlinear waves for a generalized (2 + 1)-dimensional nonlinear wave equation in nonlinear optics, fluid mechanics, and plasma physics are presented. Via the Hirota bilinear method, a bilinear Backlund transformation is obtained, based on which a Lax pair is constructed. Via the symbolic computation, mixed rogue–solitary and rogue–periodic wave solutions are derived. Interactions between the rogue waves and solitary waves, and interactions between the rogue waves and periodic waves, are studied. It is found that (1) the one rogue wave appears between the two solitary waves and then merges with the two solitary waves; (2) the interaction between the one rogue wave and one periodic wave is periodic; and (3) the periodic lump waves with the amplitudes invariant are depicted. Furthermore, effects of the noise perturbations on the obtained solutions will be investigated.