The accurate prediction of carbon prices poses a tremendous challenge to relevant industry practitioners and governments. This paper proposes a novel hybrid model incorporating modified ensemble empirical mode decomposition (MEEMD) and long short-term memory (LSTM) optimized by the improved whale optimization algorithm (IWOA). This model is based on the nonlinear and non-stationary characteristics of carbon price. The original carbon price is first decomposed into nine intrinsic mode functions (IMFs) and a residual using the MEEMD model. Then, the random forest method is applied to determine the input variables of each IMF and the residual, in the LSTM neural network. The carbon price is then predicted by the LSTM model optimized by the IWOA. The proposed hybrid model is applied to predict the carbon prices of Beijing, Fujian, and Shanghai to assess its effectiveness. The results reveal that the model achieved higher prediction performance than 11 other benchmark models. Our observations indicate that decomposition of carbon price can effectively improve the accuracy of prediction. Moreover, the improved LSTM model is more suitable for time series prediction. The proposed model provides a novel and effective carbon price forecasting tool for governments and enterprises. This paper applies the system archetypes to investigate water, energy, food, and land nexus (WEFLN) in the Jatiluhur reservoir, the largest reservoir in Indonesia. The Jatiluhur reservoir has multiple functions such as hydropower supply and water supply for different end users. Multiple functions and multiple users mean there are tradeoffs in fulfilling the needs of different end users. Through feedback loops, the system dynamics tools concern on the interdependencies and the complexities of the nexus elements. It is found that growth engines such as industrial development and residential development support industrial and residential sectors. However, water availability will be a crucial issue as water supply can bound the growth engines. This situation is called the limits to growth archetype. Another system archetype named the success to successful is also identified. The success to successful archetype reminds us to distribute water and energy properly to sustain the growth in all sectors. Finally, outputs of this study can be a basis to develop a computer model and to support sustainable functions of the other reservoirs. In contrast to other Latin American countries, where the presence of arsenic (As) in drinking water sources and related adverse human health impacts are well-known, little is internationally known from Nicaragua. However, the As problem is of high relevance as numerous assessments by national research, governmental and non-governmental institutions have proven. To assess for the first time and globally disseminate this predominantly nationally originated information is the aim of this review. In Nicaragua, >1000 water samples have been analyzed for total As from 1991 to 2017. By today, 144 communities distributed within 12 departments and one autonomous region (RACCS) are impacted with As. At least 55,700 people are exposed to drinking water with As (n = 173; range 10-1320 μg/L, mean 48.30 μg/L; 21.95%). Arsenic in surface water ranged from 0.99 to 2650 μg/L (n = 124, mean 65.62 μg/L, 62.9%  less then  10 μg/L); and in groundwater from 0.10 to 1320 μg/L [n = 624, mean 20.86 μg/L (70.7%  less then  10 μg/L)]. ty scale is needed, calling for the cooperation of national entities with communities in problem detection and solving. Background Vancomycin-resistant Enterococcus (VRE) has become more common in nosocomial infections, especially in urine samples. However, until now, no treatment regimen has been proven to effectively eradicate urine VRE colonization. Therefore, to evaluate the efficacy of doxycycline in eradicating urine VRE and shortening VRE isolation period, we compared VRE colony detection period between doxycycline-treated and untreated patients. Methods A retrospective cohort study of 83 patients with VRE colonization in urine cultures was conducted at a tertiary academic hospital from January 2011 to February 2018. Kaplan-Meier survival analysis was used to evaluate eradication rates in the treatment and non-treatment groups. Factors affecting urine VRE colonization persistence were analyzed by multiple logistic regression analysis. Results The overall rate of VRE eradication during the entire hospital stay was higher in the doxycycline treatment group (90.5%) than in the non-treatment group (58.1%, p=0.014). Survival analysis showed that the 5-, 10-, and 20-day cumulative eradication rates were 78.3%, 100%, and 100% in the doxycycline treatment group, and 18.5%, 45.7%, and 67.8% in the non-treatment group, respectively, thereby indicating that eradication rates were higher in the doxycycline treatment group than in the non-treatment group (p less then 0.001). Only doxycycline treatment was shown to affect urine VRE colonization persistence in multivariate logistic regression analysis. Conclusion Doxycycline treatment enhanced the eradication rate of urine VRE colonization and appeared to be useful in shortening VRE isolation period.Cancer incidence has been increasing steadily and is the leading cause of mortality worldwide. Gastric cancer is still most common malignancy in Korea. Cancer initiation and progression are multistep processes involving various growth factors and their ligands. Among these growth factors, we have studied hepatocyte growth factor (HGF), which is associated with cell proliferation and invasion, leading to cancer and metastasis, especially in gastric cancer. We explored the intercellular communication between HGF and other surface membrane receptors in gastric cancer cell lines. Using complimentary deoxyribonucleic acid microarray technology, we found new genes associated with HGF in the stomach cancer cell lines, NUGC-3 and MKN-28, and identified their function within the HGF pathway.  https://www.selleckchem.com/products/vu661013.html  The HGF/N-methyl-N'-nitroso-guanidine human osteosarcoma transforming gene (c-MET) axis interacts with several molecules including E-cadherin, urokinase plasminogen activator, KiSS-1, Jun B, and lipocalin-2. This pathway may affect cell invasion and metastasis or cell apoptosis and is therefore associated with tumorigenesis and metastasis in gastric cancer.