Exploring Effective Priors and Efficient Models for Weakly-Supervised Change Detection

Weakly-supervised change detection (WSCD) aims to detect pixel-level changes with only image-level annotations. Owing to its label efficiency, WSCD is drawing increasing attention recently. However, current WSCD methods often encounter the challenge of change missing and fabricating, i.e., the inconsistency between image-level annotations and pixel-level predictions. Specifically, change missing refer to the situation that the WSCD model fails to predict any changed pixels, even though the image-level label indicates changed, and vice versa for change fabricating. To address this challenge, in this work, we leverage global-scale and local-scale priors in WSCD and propose two components: a Dilated Prior (DP) decoder and a Label Gated (LG) constraint. The DP decoder decodes samples with the changed image-level label, skips samples with the unchanged label, and replaces them with an all-unchanged pixel-level label. The LG constraint is derived from the correspondence between changed representations and image-level labels, penalizing the model when it mispredicts the change status. Additionally, we develop TransWCD, a simple yet powerful transformer-based model, showcasing the potential of weakly-supervised learning in change detection. By integrating the DP decoder and LG constraint into TransWCD, we form TransWCD-DL. Our proposed TransWCD and TransWCD-DL achieve significant +6.33% and +9.55% F1 score improvements over the state-of-the-art methods on the WHU-CD dataset, respectively. Some performance metrics even exceed several fully-supervised change detection (FSCD) competitors. Code will be available at https://github.com/zhenghuizhao/TransWCD

Evaluation of the Ecological Quality of the Taishan Region Based on Landsat Series of Satellite Images

The deterioration of ecological environment has seriously restricted regional sustainable development. Taishan region is one of the ecological protection and restoration of life community of mountains-rivers-forests-farmlands-lakes-grasslands in China. Its ecological quality changes are directly related to the overall layout of ecological restoration and protection projects. In this study, the Taishan region of China was taken as study area, and the grade change, spatial distribution, and spatial temporal fluctuation of the ecological environment quality were quantified. Based on the ENVI platform, the Landsat series of three images of the Taishan region in 2005, 2013, and 2017 serve as the data source, and the remote sensing ecological index model (RSEI) was used. According to the change characteristics of land use types, the driving factors of ecological environmental quality change were analyzed. The results showed that: (1) The area ratio of the ecological environment quality above the middle level was in order from large to small: 2005 (97.37%) > 2017 (91.46%) > 2013 (84.64%). (2) The overall quality of the ecological environment declined during the period of 2005-2013. (3) The overall change ranges from 2013 to 2017 are smaller than those from 2005 to 2013. The area of the deteriorating area decreased by 44.90%, and the area of the constant area and the area of the area that improved increased by 16.17% and 28.72%, respectively. During 2013-2017, the general trend is getting better and better. The improved areas were mainly concentrated in the main urban areas (Taishan District, Daiyue District), eastern Ningyang County, and western Xintai City. The research results can provide a scientific basis for the scientific evaluation of the ecological environment quality during the development and construction of the region, and have important value in the design and application of the ecological environment quality optimization path

Optimal Routing and Charging of Electric Logistics VehiclesBased on Long-Distance Transportation and Dynamic Transportation System

The application of electric vehicles (EVs) in the logistics industry has become more extensive. However, the mileage limitation of electric logistics vehicles (ELVs) and the long-distance distribution of ELVs have become urgent problems. Therefore, this paper proposes a long-distance distribution model for ELVs based on dynamic traffic information considering fleet mileage, distribution time and total distribution cost as the optimisation objectives, thus reasonably planning road selection and charging, and alleviating “mileage anxiety” in the long-distance distribution of ELVs. The model proposed in this paper comprehensively considers the characteristics of the high-speed and low-speed roads, the changes in road traffic flow on weekdays and non-weekdays, the time-of-use electricity price of electric vehicle charging stations (EVCSs) and uses the M/M/s queuing theory model to determine the charging waiting time. Finally, a real traffic network is taken as an example to verify the practicability and effectiveness of this model

Impact of glucocorticoids and rapamycin on autophagy in Candida glabrata-infected macrophages from BALB/c mice

ObjectiveIn the defense against microorganisms like Candida albicans, macrophages recruit LC3(Microtubule-associated protein 1A/1B-light chain 3) to the periplasm, engaging in the elimination process through the formation of a single-membrane phagosome known as LC3-associated phagocytosis (LAP). Building on this, we propose the hypothesis that glucocorticoids may hinder macrophage phagocytosis of Candida glabrata by suppressing LAP, and rapamycin could potentially reverse this inhibitory effect.MethodsRAW264.7 cells were employed for investigating the immune response to Candida glabrata infection. Various reagents, including dexamethasone, rapamycin, and specific antibodies, were utilized in experimental setups. Assays, such as fluorescence microscopy, flow cytometry, ELISA (Enzyme-Linked Immunosorbent Assay), Western blot, and confocal microscopy, were conducted to assess phagocytosis, cytokine levels, protein expression, viability, and autophagy dynamics.ResultsGlucocorticoids significantly inhibited macrophage autophagy, impairing the cells’ ability to combat Candida glabrata. Conversely, rapamycin exhibited a dual role, initially inhibiting and subsequently promoting phagocytosis of Candida glabrata by macrophages. Glucocorticoids hinder macrophage autophagy in Candida glabrata infection by suppressing the MTOR pathway(mammalian target of rapamycin pathway), while the activation of MTOR pathway by Candida glabrata diminishes over time.ConclusionOur study elucidates the intricate interplay between glucocorticoids, rapamycin, and macrophage autophagy during Candida glabrata infection. Understanding the implications of these interactions not only sheds light on the host immune response dynamics but also unveils potential therapeutic avenues for managing fungal infections

Replacements of Rare Herbs and Simplifications of Traditional Chinese Medicine Formulae Based on Attribute Similarities and Pathway Enrichment Analysis

A Traditional Chinese Medicine (TCM) formula is a collection of several herbs. TCM formulae have been used to treat various diseases for several thousand years. However, wide usage of TCM formulae has results in rapid decline of some rare herbs. So it is urgent to find common available replacements for those rare herbs with the similar effects. In addition, a formula can be simplified by reducing herbs with unchanged effects. Based on this consideration, we propose a method, called “formula pair,” to replace the rare herbs and simplify TCM formulae. We show its reasonableness from a perspective of pathway enrichment analysis. Both the replacements of rare herbs and simplifications of formulae provide new approaches for a new formula discovery. We demonstrate our approach by replacing a rare herb “Forsythia suspensa” in the formula “the seventh of Sang Ju Yin plus/minus herbs (SSJY)” with a common herb “Thunberg Fritillary Bulb” and simplifying two formulae, “the fifth of Du Huo Ji Sheng Tang plus/minus herbs (FDHJST)” and “Fang Feng Tang” (FFT) to a new formula “Fang Feng Du Huo Tang” (FFDHT)

Performance study on Ca-based sorbents for sequential CO2 and SO2 capture in a bubbling fluidised bed

High temperature CO2 and SO2 sequential capture in a bubbling fluidised bed was investigated using a natural limestone and synthetic composite pellets. Calcination was conducted under oxy-combustion conditions, while carbonation and sulphation occurred in an air-combustion atmosphere. The goal of sequential capture of CO2/SO2 is to desulphurise the flue gas first, followed by cyclic carbonation and calcination. Here, fresh sorbent is first used in the cyclic calcination/carbonation process and then the spent sorbent is sent for sulphation. The pellet carrying capacity is 0.29 g CO2/g sorbents for the first cycle, while that of natural limestone is about 0.45 g CO2/g sorbents. The carrying capacity first fell and then finally plateaued around 0.10 and 0.12 g CO2/g sorbents for limestone and pellets respectively. The SO2 carrying capacity for limestone and pellets after 20 cycles of CO2 capture was 0.17 and 0.22 g SO2/g sorbents respectively. This indicates that the sorbent spent in CO2 capture can be effectively reused for SO2 removal. Abrasion was observed to be the main mode of attrition, but some agglomeration was also found with increasing number of cycles and this may be a concern in the use of Ca-based sorbent for CO2 or SO2 fluidised bed capture

The clinical predictive value of geriatric nutritional risk index in elderly rectal cancer patients received surgical treatment after neoadjuvant therapy

ObjectiveThe assessment of nutritional status has been recognized as crucial in the treatment of geriatric cancer patients. The objective of this study is to determine the clinical predictive value of the geriatric nutritional risk index (GNRI) in predicting the short-term and long-term prognosis of elderly rectal cancer (RC) patients who undergo surgical treatment after neoadjuvant therapy.MethodsBetween January 2014 and December 2020, the clinical materials of 639 RC patients aged ≥70 years who underwent surgical treatment after neoadjuvant therapy were retrospectively analysed. Propensity score matching was performed to adjust for baseline potential confounders. Logistic regression analysis and competing risk analysis were conducted to evaluate the correlation between the GNRI and the risk of postoperative major complications and cumulative incidence of cancer-specific survival (CSS). Nomograms were then constructed for postoperative major complications and CSS. Additionally, 203 elderly RC patients were enrolled between January 2021 and December 2022 as an external validation cohort.ResultsMultivariate logistic regression analysis showed that GNRI [odds ratio = 1.903, 95% confidence intervals (CI): 1.120–3.233, p = 0.017] was an independent risk factor for postoperative major complications. In competing risk analysis, the GNRI was also identified as an independent prognostic factor for CSS (subdistribution hazard ratio = 3.90, 95% CI: 2.46–6.19, p < 0.001). The postoperative major complication nomogram showed excellent performance internally and externally in the area under the receiver operating characteristic curve (AUC), calibration plots and decision curve analysis (DCA). When compared with other models, the competing risk prognosis nomogram incorporating the GNRI achieved the highest outcomes in terms of the C-index, AUC, calibration plots, and DCA.ConclusionThe GNRI is a simple and effective tool for predicting the risk of postoperative major complications and the long-term prognosis of elderly RC patients who undergo surgical treatment after neoadjuvant therapy