Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection

Camouflaged objects that blend into natural scenes pose significant challenges for deep-learning models to detect and synthesize. While camouflaged object detection is a crucial task in computer vision with diverse real-world applications, this research topic has been constrained by limited data availability. We propose a framework for synthesizing camouflage data to enhance the detection of camouflaged objects in natural scenes. Our approach employs a generative model to produce realistic camouflage images, which can be used to train existing object detection models. Specifically, we use a camouflage environment generator supervised by a camouflage distribution classifier to synthesize the camouflage images, which are then fed into our generator to expand the dataset. Our framework outperforms the current state-of-the-art method on three datasets (COD10k, CAMO, and CHAMELEON), demonstrating its effectiveness in improving camouflaged object detection. This approach can serve as a plug-and-play data generation and augmentation module for existing camouflaged object detection tasks and provides a novel way to introduce more diversity and distributions into current camouflage datasets

Transforming Wikipedia into Augmented Data for Query-Focused Summarization

The manual construction of a query-focused summarization corpus is costly and timeconsuming. The limited size of existing datasets renders training data-driven summarization models challenging. In this paper, we use Wikipedia to automatically collect a large query-focused summarization dataset (named as WIKIREF) of more than 280,000 examples, which can serve as a means of data augmentation. Moreover, we develop a query-focused summarization model based on BERT to extract summaries from the documents. Experimental results on three DUC benchmarks show that the model pre-trained on WIKIREF has already achieved reasonable performance. After fine-tuning on the specific datasets, the model with data augmentation outperforms the state of the art on the benchmarks

RIS-based IMT-2030 Testbed for MmWave Multi-stream Ultra-massive MIMO Communications

As one enabling technique of the future sixth generation (6G) network, ultra-massive multiple-input-multiple-output (MIMO) can support high-speed data transmissions and cell coverage extension. However, it is hard to realize the ultra-massive MIMO via traditional phased arrays due to unacceptable power consumption. To address this issue, reconfigurable intelligent surface-based (RIS-based) antennas are an energy-efficient enabler of the ultra-massive MIMO, since they are free of energy-hungry phase shifters. In this article, we report the performances of the RIS-enabled ultra-massive MIMO via a project called Verification of MmWave Multi-stream Transmissions Enabled by RIS-based Ultra-massive MIMO for 6G (V4M), which was proposed to promote the evolution towards IMT-2030. In the V4M project, we manufacture RIS-based antennas with 1024 one-bit elements working at 26 GHz, based on which an mmWave dual-stream ultra-massive MIMO prototype is implemented for the first time. To approach practical settings, the Tx and Rx of the prototype are implemented by one commercial new radio base station and one off-the-shelf user equipment, respectively. The measured data rate of the dual-stream prototype approaches the theoretical peak rate. Our contributions to the V4M project are also discussed by presenting technological challenges and corresponding solutions.Comment: 8 pages, 5 figures, to be published in IEEE Wireless Communication

Role of HMGB1 in apoptosis-mediated sepsis lethality

Severe sepsis, a lethal syndrome after infection or injury, is the third leading cause of mortality in the United States. The pathogenesis of severe sepsis is characterized by organ damage and accumulation of apoptotic lymphocytes in the spleen, thymus, and other organs. To examine the potential causal relationships of apoptosis to organ damage, we administered Z-VAD-FMK, a broad-spectrum caspase inhibitor, to mice with sepsis. We found that Z-VAD-FMK–treated septic mice had decreased levels of high mobility group box 1 (HMGB1), a critical cytokine mediator of organ damage in severe sepsis, and suppressed apoptosis in the spleen and thymus. In vitro, apoptotic cells activate macrophages to release HMGB1. Monoclonal antibodies against HMGB1 conferred protection against organ damage but did not prevent the accumulation of apoptotic cells in the spleen. Thus, our data indicate that HMGB1 production is downstream of apoptosis on the final common pathway to organ damage in severe sepsis

MD-2 is required for disulfide HMGB1-dependent TLR4 signaling

Innate immune receptors for pathogen- and damage-associated molecular patterns (PAMPs and DAMPs) orchestrate inflammatory responses to infection and injury. Secreted by activated immune cells or passively released by damaged cells, HMGB1 is subjected to redox modification that distinctly influences its extracellular functions. Previously, it was unknown how the TLR4 signalosome distinguished between HMGB1 isoforms. Here we demonstrate that the extracellular TLR4 adaptor, myeloid differentiation factor 2 (MD-2), binds specifically to the cytokine-inducing disulfide isoform of HMGB1, to the exclusion of other isoforms. Using MD-2–deficient mice, as well as MD-2 silencing in macrophages, we show a requirement for HMGB1-dependent TLR4 signaling. By screening HMGB1 peptide libraries, we identified a tetramer (FSSE, designated P5779) as a specific MD-2 antagonist preventing MD-2–HMGB1 interaction and TLR4 signaling. P5779 does not interfere with lipopolysaccharide-induced cytokine/chemokine production, thus preserving PAMP-mediated TLR4–MD-2 responses. Furthermore, P5779 can protect mice against hepatic ischemia/reperfusion injury, chemical toxicity, and sepsis. These findings reveal a novel mechanism by which innate systems selectively recognize specific HMGB1 isoforms. The results may direct toward strategies aimed at attenuating DAMP-mediated inflammation while preserving antimicrobial immune responsiveness

Perturbed gut microbiome and fecal and serum metabolomes are associated with chronic kidney disease severity

Abstract Background Chronic kidney disease (CKD) is a severe public health problem associated with a disordered gut microbiome. However, the functional alterations of microbiota and their cross talk with metabolism pathways based on disease severity remain unclear. Results We performed metagenomics and untargeted metabolomics in a cohort of 68 patients with CKD of differing severities and 20 healthy controls to characterize the complex interplay between the gut microbiome and fecal and serum metabolites during CKD progression. We identified 26 microbial species that significantly changed in patients with CKD; 18 species changed as the disease progressed, and eight species changed only in a specific CKD group. These distinct changes in gut microbiota were accompanied by functional alterations in arginine and proline, arachidonic acid, and glutathione metabolism and ubiquinone and other terpenoid-quinone biosynthesis pathways during CKD progression. Further metabolomic analyses revealed that the distributions of toxic and pro-oxidant metabolites from these four essential metabolic pathways varied in the feces and serum as CKD progressed. Furthermore, we observed a complex co-occurrence between CKD severity-related bacteria and the characterized metabolites from the four essential metabolic pathways. Notably, Ruminococcus bromii, fecal hydroquinone, and serum creatinine were identified as the main contributors to the integrated network, indicating their key roles in CKD progression. Moreover, a noninvasive model including R. bromii and fecal hydroquinone, L-cystine, and 12-keto-tetrahydro-LTB4 levels classified the CKD severity (area under the curve [AUC]: > 0.9) and had better performance than the serum creatinine level for mild CKD (AUC: 0.972 vs. 0.896). Conclusions Perturbed CKD severity-related gut microbiota may contribute to unbalanced toxic and pro-oxidant metabolism in the gut and host, accelerating CKD progression, which may be an early diagnostic and therapeutic target for CKD. Video Abstrac

Impact of land use/cover change (LUCC) on sediment connectivity in small watersheds based on a revised index algorithm

Soil erosion is an important cause of global land degradation and other ecological and environmental problems. Revealing the influence mechanism of land use/cover change (LUCC) on sediment yield can provide a scientific basis for efficient comprehensive and decision-making management of watersheds. As an important indicator of sediment yield and transport capacity, sediment connectivity has been widely studied in recent years. However, the existing index of sediment connectivity (IC) ignores the influence of upslope land use/cover on confluence and the corresponding changes in downslope sediment transport. Moreover, a formula describing the upslope and downslope components does not establish an effective correlation with existing soil erosion formulas. Therefore, the index is not closely related to the erosion process and does not reflect the physical process of sediment transport and sediment deposition. In addition, there have been few reports concerning the effect of LUCC on sediment connectivity inside (on-site impact) and outside (off-site impact) the changed patches. Consequently, by based on addition of the revised parameters of the effective confluence area (Ar) and the runoff velocity factor (v) of the sediment delivery distributed (SEDD) model, an improved sediment connectivity index (ICZQ) is proposed. The results indicate that ICZQ has a significant linear relationship with annual runoff depth or sediment yield modulus in small watersheds within 100 km2 in the Loess Plateau, except for feature years containing rainstorm events (daily rainfall exceeding 50 mm). Therefore, the runoff and sediment transport capacity of small watersheds can be characterized by ICZQ under the influence of LUCC and rainfall change. In 1982–2020, driven by LUCC with an enhancement in vegetation (forest and grass), the ICZQ decreased in 90% of the area and decreased by a significant or extremely significant level over 48% of the area. To better understand the effects of LUCC on sediment connectivity, we analyzed on-site and off-site impacts with rainfall remaining unchanged to control the variables. The contribution rates of the on-site and off-site impacts caused by LUCC on sediment connectivity in Lvergou were 61% and 39%, 48% and 52%, respectively, over two typical periods (1985–1990 and 2015–2020). Due to the large proportion that off-site impacts occupied in the sediment connectivity change, the impact of LUCC on sediment connectivity cannot be ignored, especially when the associated scale is relatively small. The present study provides a quantitative method for the optimization of land use/cover patterns, such as vegetation restoration in watersheds along with a reference for further revealing the impact mechanism of erosion and sediment yield in watersheds

Processable poly(2-butylaniline)/hexagonal boron nitride nanohybrids for synergetic anticorrosive reinforcement of epoxy coating

Hexagonal boron nitride (h-BN), a structural analogue of graphene, is a better alternative for anticorrosive coatings because of its electrical insulation properties. In this work, few-layer h-BN nanosheets are obtained by the exfoliation of stacked h-BN powders with poly(2-butyl aniline) (PBA) and incorporated into epoxy coatings for protecting metallic substrate against corrosion. Results show that as prepared composite coatings exhibit high impedance modulus and low water absorption, suggesting their superior performance of corrosion protection owing to the "labyrinth effect" of h-BN and passivation effect of PBA on the metal substrates