Harnessing the Spatial-Temporal Attention of Diffusion Models for High-Fidelity Text-to-Image Synthesis

Diffusion-based models have achieved state-of-the-art performance on text-to-image synthesis tasks. However, one critical limitation of these models is the low fidelity of generated images with respect to the text description, such as missing objects, mismatched attributes, and mislocated objects. One key reason for such inconsistencies is the inaccurate cross-attention to text in both the spatial dimension, which controls at what pixel region an object should appear, and the temporal dimension, which controls how different levels of details are added through the denoising steps. In this paper, we propose a new text-to-image algorithm that adds explicit control over spatial-temporal cross-attention in diffusion models. We first utilize a layout predictor to predict the pixel regions for objects mentioned in the text. We then impose spatial attention control by combining the attention over the entire text description and that over the local description of the particular object in the corresponding pixel region of that object. The temporal attention control is further added by allowing the combination weights to change at each denoising step, and the combination weights are optimized to ensure high fidelity between the image and the text. Experiments show that our method generates images with higher fidelity compared to diffusion-model-based baselines without fine-tuning the diffusion model. Our code is publicly available at https://github.com/UCSB-NLP-Chang/Diffusion-SpaceTime-Attn.Comment: 20 pages, 16 figure

Fault Diagnosis of Water Quality Monitoring Devices Based on Multiclass Support Vector Machines and Rule-Based Decision Trees

Preventing faults of sensors, wireless transmitters, and gateways are essential for water quality management in intensive aquaculture. It remains a challenging task to achieve high fault diagnostic accuracy of water quality monitoring and controlling devices. This paper proposes a hybrid water quality monitoring device fault diagnosis model based on multiclass support vector machines (MSVM) in combination with rule-based decision trees (RBDT). In the modeling process, an RBDT is used to diagnose the gateway fault and wireless transmitter fault at the same time as a feature selection tool to reduce the number of features. A multiclass support vector machine classifier is employed to diagnose the faults of water quality sensors due to its robustness and generalization. We adopted an RBDT-MSVM algorithm to construct a fault diagnosis model. The diagnostic results indicate that RBDT-MSVM model has great potential for fault diagnosis of online water quality devices. RBDT-MSVM was tested and compared with other algorithms by applying it to diagnose faults of water quality monitoring devices in river crab culture ponds. The diagnostic results indicate that the model has great potential for fault diagnosis of online water quality devices. The experimental results show that the proposed model RBDT-MSVM can achieve classification accuracy as high as 92.86%, which is superior to the other three fault diagnosis methods. The results clearly confirm the superiority of the developed model in terms of classification accuracy, and that it is a suitable and effective method for fault diagnosis of water quality monitoring devices in intensive aquaculture

Fe-doped and sulfur-enriched Ni3S2 nanowires with enhanced reaction kinetics for boosting water oxidation

Exploring cost-effective and highly-active oxygen evolution reaction (OER) electrocatalysts is a pressing task to propel water electrolysis for green hydrogen production. Herein, we constructed a class of Fe-doped and S-enriched Ni3S2 nanowires electrocatalysts for optimizing the target intermediates adsorption to decrease the OER overpotentials at various current densities. The optimal Ni3S2-1.4%Fe electrocatalyst possesses the most active sites and exhibits an ultralow overpotential of 190 mV at 10 mA cm−2 with an excellent stability of > 60 h, exceeding the majority of recently-reported Ni3S2-based electrocatalysts. The trivalence Fe-doping not only reduces the electron density of the Ni center, but also enables the sulfur enrichment on the Ni3S2 surface, which greatly improves the intrinsic activity and the number of target intermediates (∗OOH). A novel methanol-assisted electrochemical evaluation further reveals that the Ni3S2-1.4%Fe electrocatalyst demonstrates a weaker binding ability to ∗OH with the rapid generation of ∗OOH species, and thus gives a lower apparent activation energy compared with the surface sulfur reduced ones. This work provides a new perspective for regulating the adsorption of intermediates through doping strategy

Effects of Chinese Herbs on the Hemagglutination and Adhesion of Escherichia Coli Strain In Vitro

The aim of this study is to evaluate Chinese herbs' efficacy on adhesive properties of Escherichia coli (E. coli). The effects of Chinese herbal solution on the hemagglutination and adhesion by E. coli strain were studied. E. coli C16 was isolated from a patient with urinary tract infection. The MIC value of herbal solution for the E. coli C16 was 0.1g/ml. The MBC value was 0.2g/ml. The effects of herbal solution on the hemagglutination abilities of E. coli C16 were dependent on the herbal solution used. The strain C16 lost half of its hemagglutination abilities when the herbal solution concentration was at MIC (0.05g/ml). Herbal solution decreased the adherence of strain C16 in a dose-dependent way. The numbers of adherent bacteria were reduced to 45% of the control values after growth with herbal solution at MIC. The results show that anti-adhesion is one mode of action for Chinese herbs used against pathogens

The Rapid Emergence of Tigecycline Resistance in blaKPC–2 Harboring Klebsiella pneumoniae, as Mediated in Vivo by Mutation in tetA During Tigecycline Treatment

Tigecycline is one of the last resort treatments for carbapenem-resistant Klebsiella pneumoniae (CRKP) infections. Tigecycline resistance often occurs during the clinical treatment of CRKP, yet its mechanism has still not been clearly elucidated. This study presents an analysis of a tigecycline resistance mechanism that developed in clinical isolates from a 56-year-old female patient infected with CRKP during tigecycline treatment. Consecutive clonal consistent K. pneumoniae isolates were obtained during tigecycline treatment. Whole genome sequencing of the isolates was performed, and putative single nucleotide polymorphisms and insertion and deletion mutations were analyzed in susceptible and resistant isolates. The identified gene of interest was examined through experiments involving transformations and conjugations. Four isolates, two of which were susceptible and two resistant, were collected from the patient. All of the isolates belonged to Sequence Type 11 (ST11) and were classified as extensively drug resistant (XDR). One amino acid substitution S251A in TetA was identified in the tigecycline-resistant isolates. Subsequent transformation experiments confirmed the contribution of the TetA variant (S251A) to tigecycline resistance. The transfer capacity of tigecycline resistance via this mutation was confirmed by conjugation experiments. Using southern blot hybridization and PCR assays, we further proved that the tetA gene was located on a transferable plasmid of ca. 65 kb in an Escherichia coli EC600 transconjugant. Our results provide direct in vivo evidence that evolution in the tetA gene can lead to tigecycline treatment failure in CRKP clinical strains that carry tetA. Moreover, the transfer capacity of tigecycline resistance mediated by mutated tetA is a threat

In Situ Assembly of 2D Conductive Vanadium Disulfide with Graphene as a High-Sulfur-Loading Host for Lithium-Sulfur Batteries

Lithium-sulfur (Li-S) batteries are deemed to be one of the most promising energy storage technologies because of their high energy density, low cost, and environmental benignancy. However, existing drawbacks including the shuttling of intermediate polysulfides, the insulating nature of sulfur, and the considerable volume change of sulfur cathode would otherwise result in the capacity fading and unstable cycling. To overcome these challenges, herein an in situ assembly route is presented to fabricate VS2/reduced graphene oxide nanosheets (G-VS2) as a sulfur host. Benefiting from the 2D conductive and polar VS2 interlayered within a graphene framework, the obtained G-VS2 hybrids can effectively suppress the polysulfide shuttling, facilitate the charge transport, and cushion the volume expansion throughout the synergistic effect of structural confinement and chemical anchoring. With these advantageous features, the obtained sulfur cathode (G-VS2/S) can deliver an outstanding rate capability (approximate to 950 and 800mAh g(-1) at 1 and 2C, respectively) and an impressive cycling stability at high rates (retaining approximate to 532mAh g(-1) after 300 cycles at 5C). More significantly, it enables superior cycling performance of high-sulfur-loading cathodes (achieving an areal capacity of 5.1mAh cm(-2) at 0.2C with a sulfur loading of 5mg cm(-2)) even at high current densities