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Due to the growing awareness of environmental protection and their economic benefits, there has been rapid development in the closed-loop supply chain (CLSC) in recent years, with a general occurrence of CLSCs led by collectors. Even with government support such as subsidies, the operation of CLSC still requires immense investment, such as purchasing recycling equipment. Nevertheless, the unprecedented economic recession during the post-pandemic era has heightened the risk of insufficient funding for CLSC. This highlights the importance of understanding the complexities involved in CLSC financing strategies, as they are crucial for ensuring the sustainability and resilience of CLSC in the face of challenges. To investigate the equilibrium decisions and financing strategy selection of CLSCs, we developed and analyzed a series of three-stage Stackelberg models, considering practical scenarios involving capital constraints, environmentally friendly green activities, government subsidies for End-of-Life (EOL) recycling, as well as introducing common trade credit financing and bank financing for generality. The findings demonstrate: (1) Under trade credit financing, it is always beneficial for the collector granting credit. Interest income can motivate the collector to recover more EOL products. (2) In addition to financing interest rates, government subsidies and remanufacturing cost savings can affect the financing strategy selection of the capital-constrained manufacturer. Our study provides guidance for managers in selecting optimal financing strategies under specific conditions. (3) The total profit of CLSC under trade credit financing is always higher and we propose a revenue-sharing contract to realize the win-win status with the optimal profit of CLSC. (4) Furthermore, our results underscore the importance of government recycling subsidies, remanufacturing cost savings, and the positive impact achieved by reducing recycling difficulties and enhancing customer awareness of green consumption. • The recycling rate increases with an increase in the financing rate. • Trade credit financing (TCF) is always beneficial to the collector. • Specific subsidy ranges make TCF with a higher interest rate the optimal strategy. • Whole CLSC profits more with TCF than bank financing. • Revenue-sharing contract can further improve CLSC performance. [ABSTRACT FROM AUTHOR]

Methamphetamine use disorder (MUD) can cause impulsive behavior, anxiety, and depression. Stimulation of the left dorsolateral prefrontal cortex in MUD patients by intermittent theta burst repetitive transcranial magnetic stimulation (iTBS-rTMS) is effective in reducing cravings, impulsive behavior, anxiety, and depression. The purpose of this study was to explore whether these psychological factors helped to predict MUD patients' responses to iTBS-rTMS treatment. Fifty MUD patients and sixty healthy subjects matched for general conditions were used as study subjects. The study randomly divided MUD patients into iTBS-rTMS and sham stimulation groups and received 20 sessions of real or sham iTBS-rTMS treatment, and the study collected cue-related evoked craving data before and after treatment. All subjects completed the Barratt Impulsiveness Scale (BIS-11), Self-rating Anxiety Scale (SAS), and Self-rating Depression Scale (SDS). The MUD patients showed significantly higher levels of impulsivity, anxiety, and depression than the healthy subjects. The MUD patients who received the real treatment had significantly lower impulsivity, anxiety, and depression scores, and better treatment effects on cravings than the sham stimulation group. The Spearman rank correlation and stepwise multiple regression analyses showed that the baseline BIS-11 and the reduction rate (RR) of BIS-11 and RR of SDS were positively correlated with the decrease in cravings in the iTBS-rTMS group. ROC curve analysis showed that RR of SDS (AUC = 91.6 %; 95 % CI = 0.804–1.000) had predictive power to iTBS- rTMS therapeutic efficacy, the cutoff value is 15.102 %. iTBS-rTMS had a good therapeutic effect in MUD patients and the baseline impulsivity, the improved depression and impulsivity were associated with therapeutic effect of iTBS-rTMS. The improved depression had the potential to predict the efficacy of the iTBS-rTMS modality for MUD treatment. • iTBS-rTMS can reduce craving, impulsivity, depression, and anxiety in methamphetamine use disorder (MUD) patients. • Impulsivity and depression might be good indicators for predicting the efficacy of iTBS. • The efficacy of ITBS-rTMS in MUD patients is not only related to neurophysiologic changes but also to psychological factors. [ABSTRACT FROM AUTHOR]

• PSTFS optimizes crop type classifications by fully mining crop phenology information. • PSTFS ranks features by importance and then iteratively prunes redundant features. • We used an SVM classifier to produce a high-quality corn map of Heilongjiang, China. • The optimal features identified by PSTFS are key crop phenological characteristics. • PSTFS can be extended to other land cover types and other dense remote sensing data. Accurate information on crop distribution and its changes is important for food security and environmental management. Although time series analysis is a widely-used and useful tool to characterize the seasonal dynamics of crops, the traditional image stacking approach misses important phenological events. This condition makes it difficult to identify the spectral and temporal features that are potentially important for crop identification, and therefore, makes it difficult to determine the optimal feature inputs for classifying crops with both high accuracy and low computation time. To address this gap, we developed a method to automatically select the spectro-temporal features by mining crop phenology information so as to improve the accuracy of crop classifications. This method of Phenology-based Spectral and Temporal Feature Selection (PSTFS) contains two major components: to identify the features with the highest separability between each pair of classes, and to prune redundant features to retain the best for classification. Using this optimal set of features and support vector machines (SVMs), we generated a high-quality corn cultivation map of China's Heilongjiang Province for 2011. The corn map had accuracies greater than 85% and agreed well with the corn census areas. We also demonstrate the goodness of this method for selecting features with high interpretability: it identified two phenological stages (three leaf and milky mature) that could best separate corn from other land use classes in the region. Our approach indicates the great potential for using the PSTFS method in conjunction with SVM classifiers to accurately map crop types based on satellite time series data. [ABSTRACT FROM AUTHOR]

Reclamation of degraded grasslands as managed grasslands has been increasingly accelerated in recent years in China. Land use change affects soil nitrogen (N) dynamics and nitrous oxide (N 2 O) emissions. However, it remains unclear how large-scale grassland reclamation will impact the grassland ecosystem as a whole. Here, we investigated the effects of the conversion from native to managed grasslands on soil N dynamics and N2O emissions by field experiments in Hulunber in northern China. Soil (0–10 cm), nitrate (NO 3 − ), ammonium (NH 4 + ), and microbial N were measured in plots in a temperate steppe ( Leymus chinensis grassland) and two managed grasslands ( Medicago sativa and Bromus inermis grasslands) in 2011 and 2012. The results showed conversion of L. chinensis grassland to M. sativa or B. inermis grasslands decreased concentrations of NO 3 − –N, but did not change NH 4 + –N. Soil microbial N was slightly decreased by the conversion of L. chinensis grassland to M. sativa , but increased by the conversion to B. inermis. The conversion of L. chinensis grassland to M. sativa (i.e., a legume grass) increased N 2 O emissions by 26.2%, while the conversion to the B. inermis (i.e., a non-legume grass) reduced N 2 O emissions by 33.1%. The conversion from native to managed grasslands caused large created variations in soil NO 3 − –N and NH 4 + –N concentrations. Net N mineralization rates did not change significantly in growing season or vegetation type, but to net nitrification rate. These results provide evidence on how reclamation may impact the grassland ecosystem in terms of N dynamics and N 2 O emissions. [ABSTRACT FROM AUTHOR]

• High-frequency rTMS of left dorsolateral prefrontal cortex (DLPFC) could reduce cue-induced craving for methamphetamine. • High-frequency rTMS of left DLPFC could improve decision-making function of methamphetamine use disorders. • The subjects of the study were patients with methamphetamine use disorder, reducing craving and improve decision-making function might be a strategy to help prevent relapse and treat methamphetamine use disorder. Methamphetamine abuse is escalating worldwide. Its strong and irreversible neurotoxicity generally causes structural and functional changes in the brain. Repetitive transcranial magnetic stimulation (rTMS) as a non-invasive tool can be used to modulate neuronal activity, cortical excitability, and dopaminergic neurotransmission. This study aims to explore the efficacy of high-frequency rTMS in reducing drug craving and increasing decision-making ability for methamphetamine use disorder patients. Sixty-four methamphetamine use disorder patients were randomized to sham rTMS group and 10-Hz rTMS group. Visual analog scale (VAS) and Iowa game test (IGT) were used to evaluate drug craving and cognitive decision-making ability before and after treatment. Before the treatment, the two groups had no differences in the scores of VAS and IGT. After the intervention, VAS scores of 10-Hz rTMS group were significantly lower than that of sham rTMS group. In addition, the two groups had significant differences in the net score of IGT on block 4 and block 5, which favoured the 10-Hz rTMS group. Taken together, the present results suggest that High-frequency rTMS can be used to reduce drug craving and improve decision-making function for methamphetamine use disorder. [ABSTRACT FROM AUTHOR]

Multiple cropping systems are particularly important in China to feed the 19% of the world’s population with only 8% of the arable land. Rising temperatures can dramatically affect multiple cropping systems and, as a consequence, food security in China. Here, we investigate the impacts of climate change on the northern limits and crop planting areas of multiple cropping systems in China, and estimate the impacts of the change in the crop planting areas of multiple cropping systems on the China’s crop production (maize, wheat, and rice). Based on both historical climate observations from the China Meteorological Administration and future climate A1B emission scenario (IPCC, 2007) data for China, we evaluate the effects of climate change on multiple cropping systems in China. Historical statistical crop yield and simulated crop yield by Agricultural Production Systems Simulator (APSIM model) in 2011–2100 were used to quantify the crop production (maize, wheat, and rice) in China. We found that the northern limits of multiple cropping systems have been shifted northward. The projected area of cultivated land for triple-cropping system may significantly expand during the 21st century. The northern shifts resulted in a 2.2% (∼8,000,000 t) increase in national production of three major crops (maize, wheat, and rice) during the period from 1981 to 2010, positively impacting China’s food security. Therefore, we conclude that the warming due to climate change may cause a positive impact on the crop production in China if concomitant changes adapted in multiple cropping systems take place. [ABSTRACT FROM AUTHOR]

Georeferencing image sequences is critical for mobile mapping systems. Traditional methods such as bundle adjustment need adequate and well-distributed ground control points (GCP) when accurate GPS data are not available in complex urban scenes. For applications of large areas, automatic extraction of GCPs by matching vehicle-born image sequences with geo-referenced ortho-images will be a better choice than intensive GCP collection with field surveying. However, such image matching generated GCP’s are highly noisy, especially in complex urban street environments due to shadows, occlusions and moving objects in the ortho images. This study presents a probabilistic solution that integrates matching and localization under one framework. First, a probabilistic and global localization model is formulated based on the Bayes’ rules and Markov chain. Unlike many conventional methods, our model can accommodate non-Gaussian observation. In the next step, a particle filtering method is applied to determine this model under highly noisy GCP’s. Owing to the multiple hypotheses tracking represented by diverse particles, the method can balance the strength of geometric and radiometric constraints, i.e., drifted motion models and noisy GCP’s, and guarantee an approximately optimal trajectory. Carried out tests are with thousands of mobile panoramic images and aerial ortho-images. Comparing with the conventional extended Kalman filtering and a global registration method, the proposed approach can succeed even under more than 80% gross errors in GCP’s and reach a good accuracy equivalent to the traditional bundle adjustment with dense and precise control. [ABSTRACT FROM AUTHOR]

Reliable crop type maps are vital for agricultural monitoring, ensuring food security, and environmental sustainability assessments. Coarse-resolution imagery such as MODIS are widely used for crop type mapping due to their short revisit cycles, which is advantageous for detecting the seasonal dynamics of different crop types. However, the inherently low spatial resolution may restrict their utility for mapping crop types in regions with heterogeneous agricultural landscapes. Agricultural statistics, which provide crop acreage information at different spatial and temporal scales, have the potential to improve crop type mapping from remote sensing. Yet, previous studies have often used agricultural statistics as reference data to evaluate the accuracy of satellite-derived crop type maps but have rarely utilized them to improve crop type distribution mapping. The utility of integrating agricultural statistics with satellite images to produce high-accuracy crop type maps is rarely explored. This study presents a methodology for mapping sub-pixel crop type distributions via the integration of MODIS time series and agricultural statistics. We tested our approach in Heilongjiang Province, which has the highest agricultural production in China. First, we used an optimized random forest regression (RF-r) model with training samples derived from high spatial resolution images (i.e. SPOT and Landsat) to predict the sub-pixel crop type distributions from MODIS time series. To optimize the RF-r model, an 8-day MODIS time series of five vegetation indices in 2011 were used as the candidate independent variables, and a backward feature elimination strategy was implemented to select the best variables for model prediction. Second, we developed an Iterative Area Gap Spatial Allocation (IAGSA) method to spatially reconcile the discrepancies between the crop acreage estimated from MODIS-based maps and the agricultural statistics. We found that the MODIS-derived crop fractions agreed with those derived from the high-resolution images, with R2 > 0.75 for all crop types, yet there was a clear discrepancy between the crop acreage estimated from MODIS and agricultural statistics. The sub-pixel crop type maps adjusted by IAGSA were not only consistent with the agricultural statistics for crop acreage, but also retained the spatial distribution patterns of the original MODIS-derived crop fraction. Our results suggest the advantages of integrating coarse-resolution images and agricultural statistics to map sub-pixel crop type distributions, and to provide consistent estimation of crop acreage. The presented methodology has the potential to map large-scale crop type extent across regions in a cost-effective way. • Integrating MODIS images and agricultural statistics for crop type mapping. • Combing random forest with backward elimination strategy to select optimal features. • IAGSA reconciles the discrepancy between MODIS-based crop area and statistical data. • It is tested in Heilongjiang Province and generated high-quality crop fraction maps. • This method can be extended to other crop types and other coarse resolution images. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a critical component of smart cities and a key contributor to the achievement of the United Nations Sustainable Development Goal (UNSDG) 11: Sustainable Cities and Communities. The IoT is an infrastructure that enables devices to communicate with each other over the Internet, providing critical components for smart cities, such as data collection, generation, processing, analysis, and application handling. IoT-based applications can promote sustainable urban development. Many studies demonstrate how the IoT can improve smart cities' sustainable development. This systematic literature review provides valuable insights into the utilization of the IoT in the context of smart cities, with a particular focus on its implications for sustainable urban development. Based on an analysis of 73 publications, we discuss the role of IoT in the sustainable development of smart cities, focusing on smart communities, smart transportation, disaster management, privacy and security, and emerging applications. In each domain, we have detailed the attributes of IoT sensors. In addition, we have examined various communication technologies and protocols suitable for transmitting sensor-generated data. We have also presented the methods for analyzing and integrating these data within the IoT application layer. Finally, we identify research gaps in the literature, highlighting areas that require further investigation.

Objective: In this study, we established a Sprague-Dawley rat model of vulvar squamous intraepithelial lesions and investigated the impact of focused ultrasound on the expression of hypoxia-inducible factor-1α (HIF-1α), vascular endothelial growth factor (VEGF) and mutant type p53 (mtp53) in the vulvar skin of rats with low-grade squamous intraepithelial lesions (LSIL)., Materials and Methods: The vulvar skin of 60 rats was treated with dimethylbenzanthracene (DMBA) and mechanical irritation three times a week for 14 weeks. Rats with LSIL were randomly allocated into the experimental group or the control group. The experimental group was treated with focused ultrasound, while the control group received sham treatment., Results: After 14 weeks treatment of DMBA combined with mechanical irritation, LSIL were observed in 44 (73.33%) rats, and high-grade squamous intraepithelial lesions (HSIL) were observed in 14 (23.33%) rats. 90.91% (20/22) of rats showed normal pathology and 9.09% (2/22) of rats exhibited LSIL in the experimental group at four weeks after focused ultrasound treatment. 22.73% (5/22) of rats exhibited LSIL, 77.27% (17/22) of rats progressed to HSIL in the control group. Compared with the control-group rats, the levels of HIF-1α, VEGF and mtp53 were significantly decreased in experimental-group rats ( p  < 0.05)., Conclusions: These results indicate that DMBA combined with mechanical irritation can induce vulvar squamous intraepithelial lesion in SD rats. Focused ultrasound can treat LSIL safely and effectively, prevent the progression of vulvar lesions, and improve the microenvironment of vulvar tissues by decreasing the localized expression of HIF-1α, VEGF, and mtp53 in rats.

We explored the therapeutic effects of low-intensity pulsed ultrasound (LIPUS) on a rat model of ovarian damage induced by cyclophosphamide. A total of 44 female rats with premature ovarian insufficiency induced by cyclophosphamide were randomly divided into two groups (an ultrasound group and a control group); 22 normal rats without premature ovarian insufficiency were also included as a third group. The ultrasound group was treated with LIPUS, while the other two groups received the same treatment but without any power output. We monitored the estrous cycles of all rats. Seven days after treatment, 21 rats were selected to mate with male rats. We then recorded the pregnancy rate along with the number and weight of newborn rats per nest. We collected samples of blood, uterus and ovaries from the remaining 45 rats before they were sacrificed. Compared with the normal group, the control group exhibited disordered estrous cycles, more atretic follicles (p < 0.01), higher levels of serum follicle-stimulating hormone (p < 0.01), fewer other follicles (p < 0.01) and lower serum levels of E 2 and anti-Müllerian hormone (p < 0.01). Compared with the control group, the ultrasound group had normal estrous cycles with fewer atretic follicles (p < 0.01), lower levels of serum follicle-stimulating hormone (p < 0.01), more other follicles (p < 0.01) and higher levels of serum E 2 (p < 0.01). No significant difference in the levels of serum anti-Müllerian hormone was noted between the control group and the ultrasound group. No significant differences were observed between the three groups with respect to pregnancy rate or the number and weight of newborns per nest (p > 0.05). In conclusion, our data indicate that LIPUS could improve some ovarian functions of rats with premature ovarian insufficiency., Competing Interests: Conflict of interest disclosure None of the authors has any conflict of interest to declare., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Tubulointerstitial fibrosis (TIF) is one of the main pathological features of various progressive renal damages and chronic kidney diseases. Mesenchymal stromal cells (MSCs) have been verified with significant improvement in the therapy of fibrosis diseases, but the mechanism is still unclear. We attempted to explore the new mechanism and therapeutic target of MSCs against renal fibrosis based on renal proteomics., Methods: TIF model was induced by adenine gavage. Bone marrow-derived MSCs was injected by tail vein after modeling. Renal function and fibrosis related parameters were assessed by Masson, Sirius red, immunohistochemistry, and western blot. Renal proteomics was analyzed using iTRAQ-based mass spectrometry. Further possible mechanism was explored by transfected galectin-3 gene for knockdown (Gal-3 KD) and overexpression (Gal-3 OE) in HK-2 cells with lentiviral vector., Results: MSCs treatment clearly decreased the expression of α-SMA, collagen type I, II, III, TGF-β1, Kim-1, p-Smad2/3, IL-6, IL-1β, and TNFα compared with model rats, while p38 MAPK increased. Proteomics showed that only 40 proteins exhibited significant differences (30 upregulated, 10 downregulated) compared MSCs group with the model group. Galectin-3 was downregulated significantly in renal tissues and TGF-β1-induced rat tubular epithelial cells and interstitial fibroblasts, consistent with the iTRAQ results. Gal-3 KD notably inhibited the expression of p-Akt, p-GSK3β and snail in TGF-β1-induced HK-2 cells fibrosis. On the contrary, Gal-3 OE obviously increased the expression of p-Akt, p-GSK3β and snail., Conclusion: The mechanism of MSCs anti-renal fibrosis was probably mediated by galectin-3/Akt/GSK3β/Snail signaling pathway. Galectin-3 may be a valuable target for treating renal fibrosis., (© 2021. The Author(s).)

Live-cell Raman imaging based on bioorthogonal Raman probes with distinct signals in the cellular Raman-silent region (1800-2800 cm -1 ) has attracted great interest in recent years. We report here a class of water-soluble and biocompatible polydiacetylenes with intrinsic ultrastrong alkyne Raman signals that locate in this region for organelle-targeting live-cell Raman imaging. Using a host-guest topochemical polymerization strategy, we have synthesized a water-soluble and functionalizable master polydiacetylene, namely poly(deca-4,6-diynedioic acid) (PDDA), which possesses significantly enhanced (up to ~10 4 fold) alkyne vibration compared to conventional alkyne Raman probes. In addition, PDDA can be used as a general platform for multi-functional ultrastrong Raman probes. We achieve high quality live-cell stimulated Raman scattering imaging on the basis of modified PDDA. The polydiacetylene-based Raman probes represent ultrastrong intrinsic Raman imaging agents in the Raman-silent region (without any Raman enhancer), and the flexible functionalization of this material holds great promise for its potential diverse applications.

Objective: To establish a SD rat model of vulvar squamous intraepithelial lesions., Methods: Seventy female SD rats were randomized into 4 groups, namely the blank control group ( n =10), mechanical irritation group ( n =10), acetone solution group ( n =10), and mechanical irritation with DMBA acetone solution group ( n =40, model group), and the corresponding treatments were administered 3 times a week for 14 weeks. The changes of the vulvar skin of the rats were observed regularly until the 18th week. The expression of mutant p53 (mtp53) and vascular endothelial growth factor (VEGF) proteins were detected using immunohistochemistry and Western blotting, and the expressions of mtp53 and VEGF mRNA were detected with qRT- PCR in the blank control group and model group., Results: No significant differences were found in the morphological or histopathological changes of the skin among the blank control group, mechanical irritation group and acetone solution group. In the model group, low-grade squamous intraepithelial lesions (LSIL) occurred in 28 rats (70%) and high-grade squamous intraepithelial lesions (HSIL) in 11 rats (27.5%) at 14 weeks, with a success rate of 97.5% in inducing vulvar squamous intraepithelial lesions. Compared with the blank control group, the rats in the model group showed significantly increased expressions of mtp53 and VEGF at both the protein level ( P &lt; 0.05) and the mRNA level ( P &lt; 0.05)., Conclusions: DMBA in acetone solution combined with mechanical irritation can induce vulvar squamous intraepithelial lesions in female SD rats.

Protecting the environment and enhancing food security are among the world's Sustainable Development Goals and greatest challenges. International food trade is an important mechanism to enhance food security worldwide. Nonetheless, it is widely concluded that in international food trade importing countries gain environmental benefits, while exporting countries suffer environmental problems by using land and other resources to produce food for exports. Our study shows that international food trade can also lead to environmental pollution in importing countries. At the global level, our metaanalysis indicates that there was increased nitrogen (N) pollution after much farmland for domestically cultivated N-fixing soybeans in importing countries was converted to grow high N-demanding crops (wheat, corn, rice, and vegetables). The findings were further verified by an intensive study at the regional level in China, the largest soybean-importing country, where the conversion of soybean lands to corn fields and rice paddies has also led to N pollution. Our study provides a sharp contrast to the conventional wisdom that only exports contribute substantially to environmental woes. Our results suggest the need to evaluate environmental consequences of international trade of all other major goods and products in all importing countries, which have significant implications for fundamental rethinking in global policy-making and debates on environmental responsibilities among consumers, producers, and traders across the world., Competing Interests: The authors declare no conflict of interest.

Spatially explicit ecosystem services valuation and change is a newly developing area of research in the field of ecology. Using the Beijing region as a study area, the authors have developed a spatially explicit ecosystem services value index and implemented this to quantify and spatially differentiate ecosystem services value at 1-km grid resolution. A gravity model was developed to trace spatial change in the total ecosystem services value of the Beijing study area from a holistic point of view. Study results show that the total value of ecosystem services for the study area decreased by 19.75% during the period 1996-2006 (3,226.2739 US$×10(6) in 1996, 2,589.0321 US$×10(6) in 2006). However, 27.63% of the total area of the Beijing study area increased in ecosystem services value. Spatial differences in ecosystem services values for both 1996 and 2006 are very clear. The center of gravity of total ecosystem services value for the study area moved 32.28 km northwestward over the 10 years due to intensive human intervention taking place in southeast Beijing. The authors suggest that policy-makers should pay greater attention to ecological protection under conditions of rapid socio-economic development and increase the area of green belt in the southeastern part of Beijing.

Taking Jining City of Shandong Province, one of the most important winter wheat production regions in Huanghuaihai Plain as an example, the winter wheat yield was estimated by using the 250 m MODIS-NDVI data smoothed by Savitzky-Golay filter. The NDVI values between 0. 20 and 0. 80 were selected, and the sum of NDVI value for each county was calculated to build its relation with winter wheat yield. By using stepwise regression method, the linear regression model between NDVI and winter wheat yield was established, with the precision validated by the ground survey data. The results showed that the relative error of predicted yield was between -3.6% and 3.9%, suggesting that the method was relatively accurate and feasible.