72 research outputs found
Fabrication and evolution of multilayer silver nanofilms for surface-enhanced Raman scattering sensing of arsenate
Surface-enhanced Raman scattering (SERS) has recently been investigated extensively for chemical and biomolecular sensing. Multilayer silver (Ag) nanofilms deposited on glass slides by a simple electroless deposition process have been fabricated as active substrates (Ag/GL substrates) for arsenate SERS sensing. The nanostructures and layer characteristics of the multilayer Ag films could be tuned by varying the concentrations of reactants (AgNO3/BuNH2) and reaction time. A Ag nanoparticles (AgNPs) double-layer was formed by directly reducing Ag+ ions on the glass surfaces, while a top layer (3rd-layer) of Ag dendrites was deposited on the double-layer by self-assembling AgNPs or AgNPs aggregates which had already formed in the suspension. The SERS spectra of arsenate showed that characteristic SERS bands of arsenate appear at approximately 780 and 420 cm-1, and the former possesses higher SERS intensity. By comparing the peak heights of the approximately 780 cm-1 band of the SERS spectra, the optimal Ag/GL substrate has been obtained for the most sensitive SERS sensing of arsenate. Using this optimal substrate, the limit of detection (LOD) of arsenate was determined to be approximately 5 Ī¼gĀ·l-1
Generalization and Hallucination of Large Vision-Language Models through a Camouflaged Lens
Large Vision-Language Model (LVLM) has seen burgeoning development and
increasing attention recently. In this paper, we propose a novel framework,
camo-perceptive vision-language framework (CPVLF), to explore whether LVLM can
generalize to the challenging camouflaged object detection (COD) scenario in a
training-free manner. During the process of generalization, we find that due to
hallucination issues within LVLM, it can erroneously perceive objects in
camouflaged scenes, producing counterfactual concepts. Moreover, as LVLM is not
specifically trained for the precise localization of camouflaged objects, it
exhibits a degree of uncertainty in accurately pinpointing these objects.
Therefore, we propose chain of visual perception, which enhances LVLM's
perception of camouflaged scenes from both linguistic and visual perspectives,
reducing the hallucination issue and improving its capability in accurately
locating camouflaged objects. We validate the effectiveness of CPVLF on three
widely used COD datasets, and the experiments show the potential of LVLM in the
COD task
Color image steganalysis based on quaternion discrete cosine transform
With the rapid development and application of Internet technology in recent years, the issue of information security has received more and more attention. Digital steganography is used as a means of secure communication to hide information by modifying the carrier. However, steganography can also be used for illegal acts, so it is of great significance to study steganalysis techniques. The steganalysis technology can be used to solve the illegal steganography problem of computer vision and engineering applications technology. Most of the images in the Internet are color images, and steganalysis for color images is a very critical problem in the field of steganalysis at this stage. Currently proposed algorithms for steganalysis of color images mainly rely on the manual design of steganographic features, and the steganographic features do not fully consider the internal connection between the three channels of color images. In recent years, advanced steganography techniques for color images have been proposed, which brings more serious challenges to color image steganalysis. Quaternions are a good tool to represent color images, and the transformation of quaternions can fully exploit the correlation among color image channels. In this paper, we propose a color image steganalysis algorithm based on quaternion discrete cosine transform, firstly, the image is represented by quaternion, then the quaternion discrete cosine transform is applied to it, and the coefficients obtained from the transformation are extracted to design features of the coeval matrix. The experimental results show that the proposed algorithm works better than the typical color image steganalysis algorithm
Revisiting Single Image Reflection Removal In the Wild
This research focuses on the issue of single-image reflection removal (SIRR)
in real-world conditions, examining it from two angles: the collection pipeline
of real reflection pairs and the perception of real reflection locations. We
devise an advanced reflection collection pipeline that is highly adaptable to a
wide range of real-world reflection scenarios and incurs reduced costs in
collecting large-scale aligned reflection pairs. In the process, we develop a
large-scale, high-quality reflection dataset named Reflection Removal in the
Wild (RRW). RRW contains over 14,950 high-resolution real-world reflection
pairs, a dataset forty-five times larger than its predecessors. Regarding
perception of reflection locations, we identify that numerous virtual
reflection objects visible in reflection images are not present in the
corresponding ground-truth images. This observation, drawn from the aligned
pairs, leads us to conceive the Maximum Reflection Filter (MaxRF). The MaxRF
could accurately and explicitly characterize reflection locations from pairs of
images. Building upon this, we design a reflection location-aware cascaded
framework, specifically tailored for SIRR. Powered by these innovative
techniques, our solution achieves superior performance than current leading
methods across multiple real-world benchmarks. Codes and datasets will be
publicly available
Research on temporalāspatial relationship between ground fracturing wells and underground drilling for substitution drainage of during extraction exhaustion period
In order to make use of the favorable extraction conditions formed by ground fracturing to carry out the underground borehole replacement extraction in the drainage exhaustion period of ground fracturing wells, and form the advanced treatment of ground fracturing wells + underground borehole replacement extraction mode of underground borehole replacement extraction, the temporalļ¼spatial relationship between ground fracturing wells and underground drilling for substitution extraction of during drainage exhaustion period was studied. Through the analysis of the distribution law of fracturing fractures, the investigation of the effect of ground fracturing on enhancing permeability and promoting extraction, and the numerical simulation of the variation law of coal reservoir parameters, the influence and effective range of ground fracturing wells in Lu āan Mining Area are mastered. Numerical simulation method is used to analyze and determine the optimal temporalļ¼spatial relationship between ground fracturing wells and underground drilling for substitution extraction. Based on the drainage curve of surface fractured wells and the demand of drilling in the drainage exhaustion period, the definition and division method of the drainage exhaustion period of surface fractured wells are discussed, and the discriminant indexes and key time nodes of the drainage exhaustion period of surface fractured wells are put forward. The results show : The effective influence range of ground fracturing wells is 80 m. In this area, the reservoir pressure can be decreased by about 50%, the permeability coefficient can be increased by 0.77ā1.40 times, and the average pure volume of single underground drilling for substitution extraction can reach 53.68ā131.67 m3/d, which improves the extraction efficiency of downhole drilling. When the position of ground fracturing wells is fixed along the axis of the underground drilling, the shorter the normal distance between the underground drilling and the ground fracturing wells, the better the extraction effect.When the normal distance between the ground fracturing wells and the underground drilling is constant, the best extraction results are achieved when the ground fracturing wells is located in the middle of the axial direction of the underground drilling.The gas production rate of ground fracturing wells is used as an indicator of drainage exhaustion period.And the critical value of the indicator of drainage exhaustion period of surface fractured wells in the Lu'an mine area is 200 m3/d, and the corresponding failure period time node is 8~10 years
Synaptic Targeting and Function of SAPAPs Mediated by Phosphorylation-Dependent Binding to PSD-95 MAGUKs
The PSD-95/SAPAP/Shank complex functions as the major scaffold in orchestrating the formation and plasticity of the post-synaptic densities (PSDs). We previously demonstrated that the exquisitely specific SAPAP/Shank interaction is critical for Shank synaptic targeting and Shank-mediated synaptogenesis. Here, we show that the PSD-95/SAPAP interaction, SAPAP synaptic targeting, and SAPAP-mediated synaptogenesis require phosphorylation of the N-terminal repeat sequences of SAPAPs. The atomic structure of the PSD-95 guanylate kinase (GK) in complex with a phosphor-SAPAP repeat peptide, together with biochemical studies, reveals the molecular mechanism underlying the phosphorylation-dependent PSD-95/SAPAP interaction, and it also provides an explanation of a PSD-95 mutation found in patients with intellectual disabilities. Guided by the structural data, we developed potent non-phosphorylated GK inhibitory peptides capable of blocking the PSD-95/SAPAP interaction and interfering with PSD-95/SAPAP-mediated synaptic maturation and strength. These peptides are genetically encodable for investigating the functions of the PSD-95/SAPAP interaction in vivo. Using structural biology, cell biology, and electrophysiology approaches, Zhu et al. demonstrate that phosphorylation of the N-terminal repeating sequences of SAPAPs is required for the SAPAP/PSD-95 complex formation and SAPAP's synaptic targeting and maturation functions. They also developed a potent non-phosphorylated PSD-95 GK inhibitory peptide that can effectively disrupt the SAPAP/PSD-95 complex formation and thus inhibit excitatory synaptic activities. Keywords: GK domain; PSD-95; SAPAP; MAGUK; postsynaptic density; synaptic scaffold proteins; synaptogenesis; synaptic plasticit
Understanding, Categorizing and Predicting Semantic Image-Text Relations
Two modalities are often used to convey information in a complementary and
beneficial manner, e.g., in online news, videos, educational resources, or
scientific publications. The automatic understanding of semantic correlations
between text and associated images as well as their interplay has a great
potential for enhanced multimodal web search and recommender systems. However,
automatic understanding of multimodal information is still an unsolved research
problem. Recent approaches such as image captioning focus on precisely
describing visual content and translating it to text, but typically address
neither semantic interpretations nor the specific role or purpose of an
image-text constellation. In this paper, we go beyond previous work and
investigate, inspired by research in visual communication, useful semantic
image-text relations for multimodal information retrieval. We derive a
categorization of eight semantic image-text classes (e.g., "illustration" or
"anchorage") and show how they can systematically be characterized by a set of
three metrics: cross-modal mutual information, semantic correlation, and the
status relation of image and text. Furthermore, we present a deep learning
system to predict these classes by utilizing multimodal embeddings. To obtain a
sufficiently large amount of training data, we have automatically collected and
augmented data from a variety of data sets and web resources, which enables
future research on this topic. Experimental results on a demanding test set
demonstrate the feasibility of the approach.Comment: 8 pages, 8 Figures, 5 table
Magnesium isoglycyrrhizinate reduces hepatic lipotoxicity through regulating metabolic abnormalities
The excessive accumulation of lipids in hepatocytes induces a type of cytotoxicity called hepatic lipotoxicity, which is a fundamental contributor to liver metabolic diseases (such as NAFLD). Magnesium isoglycyrrhizinate (MGIG), a magnesium salt of the stereoisomer of natural glycyrrhizic acid, is widely used as a safe and effective liver protectant. However, the mechanism by which MGIG protects against NAFLD remains unknown. Based on the significant correlation between NAFLD and the reprogramming of liver metabolism, we aimed to explore the beneficial effects of MGIG from a metabolic viewpoint in this paper. We treated HepaRG cells with palmitic acid (PA, a saturated fatty acid of C16:0) to induce lipotoxicity and then evaluated the antagonistic effect of MGIG on lipotoxicity by investigating the cell survival rate, DNA proliferation rate, organelle damage, and endoplasmic reticulum stress (ERS). Metabolomics, lipidomics, and isotope tracing were used to investigate changes in the metabolite profile, lipid profile, and lipid flux in HepaRG cells under different intervention conditions. The results showed that MGIG can indeed protect hepatocytes against PA-induced cytotoxicity and ERS. In response to the metabolic abnormality of lipotoxicity, MGIG curtailed the metabolic activation of lipids induced by PA. The content of total lipids and saturated lipids containing C16:0 chains increased significantly after PA stimulation and then decreased significantly or even returned to normal levels after MGIG intervention. Lipidomic data show that glycerides and glycerophospholipids were the two most affected lipids. For excessive lipid accumulation in hepatocytes, MGIG can downregulate the expression of the metabolic enzymes (GPATs and DAGTs) involved in triglyceride biosynthesis. In conclusion, MGIG has a positive regulatory effect on the metabolic disorders that occur in hepatocytes under lipotoxicity, and the main mechanisms of this effect are in lipid metabolism, including reducing the total lipid content, reducing lipid saturation, inhibiting glyceride and glycerophospholipid metabolism, and downregulating the expression of metabolic enzymes in lipid synthesis
Unraveling the microbial puzzle: exploring the intricate role of gut microbiota in endometriosis pathogenesis
Endometriosis (EMs) is a prevalent gynecological disorder characterized by the growth of uterine tissue outside the uterine cavity, causing debilitating symptoms and infertility. Despite its prevalence, the exact mechanisms behind EMs development remain incompletely understood. This article presents a comprehensive overview of the relationship between gut microbiota imbalance and EMs pathogenesis. Recent research indicates that gut microbiota plays a pivotal role in various aspects of EMs, including immune regulation, generation of inflammatory factors, angiopoietin release, hormonal regulation, and endotoxin production. Dysbiosis of gut microbiota can disrupt immune responses, leading to inflammation and impaired immune clearance of endometrial fragments, resulting in the development of endometriotic lesions. The dysregulated microbiota can contribute to the release of lipopolysaccharide (LPS), triggering chronic inflammation and promoting ectopic endometrial adhesion, invasion, and angiogenesis. Furthermore, gut microbiota involvement in estrogen metabolism affects estrogen levels, which are directly related to EMs development. The review also highlights the potential of gut microbiota as a diagnostic tool and therapeutic target for EMs. Interventions such as fecal microbiota transplantation (FMT) and the use of gut microbiota preparations have demonstrated promising effects in reducing EMs symptoms. Despite the progress made, further research is needed to unravel the intricate interactions between gut microbiota and EMs, paving the way for more effective prevention and treatment strategies for this challenging condition
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