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Understanding the regime shifts of Social–Ecological Systems (SES) and their local effects and driving factors over a long period of time is significant for future sustainability. We provide a perspective on the processes unfolding over time in order to identify the regime shifts of an SES based on changes in the relationships between the SES components. In addition, we investigate their driving factors and local effects. The applicability of this approach is demonstrated by analyzing the evolution of the SES in Guizhou Province, China, over the past 600 years. Six evolutionary phases are identified: the slow expansion of cultivation, the rapid expansion of cultivation, the continuous expansion of cultivation, the slower expansion of cultivation, the transformation of ecological protection driven by returning farmland to forest, and green development driven by urbanization. Our study establishes the empirical relationship between the state (phase) of the SES and its driving factors and effects. This study on the evolution, driving factors, and effects of the SES in Guizhou Province, China, provides an important reference for long-term regional planning and policy making.

Recurrent urinary tract infection (RUTI) can damage renal function and has impact on healthcare costs and patients’ quality of life. There were 2 stages for development of prediction models for RUTI. The first stage was a scenario in the clinical visit. The second stage was a scenario after hospitalization for urinary tract infection caused by Escherichia coli. Three machine learning models, logistic regression (LR), decision tree (DT), and random forest (RF) were built for the RUTI prediction. The RF model had higher prediction accuracy than LR and DT (0.700, 0.604, and 0.654 in stage 1, respectively; 0.709, 0.604, and 0.635 in stage 2, respectively). The decision rules constructed by the DT model could provide high classification accuracy (up to 0.92 in stage 1 and 0.94 in stage 2) in certain subgroup patients in different scenarios. In conclusion, this study provided validated machine learning models and RF could provide a better accuracy in predicting the development of single uropathogen (E. coli) RUTI. Both host and bacterial characteristics made important contribution to the development of RUTI in the prediction models in the 2 clinical scenarios, respectively. Based on the results, physicians could take action to prevent the development of RUTI.

Autophagy, a widespread degradation system in eukaryotes, plays an important role in maintaining the homeostasis of the cellular environment and the recycling of substances. Optical probes for the tracking of autophagy can be used as an effective tool not only to visualize the autophagy process but also to study autophagy-targeted drugs. Various molecule probes for autophagy of cancer cells emerge but are very limited for that of fungal cells, resulting in the lack of research on antifungal drugs targeting autophagy. To address this issue, we report an azole NIR fluorescence-based theranostic probe

Rationale and ObjectiveGut microbiota have been targeted by alternative therapies for non-communicable diseases. We examined the gut microbiota of a healthy Taiwanese population, identified various bacterial drivers in different demographics, and compared them with dialysis patients to associate kidney disease progression with changes in gut microbiota.Study DesignThis was a cross-sectional cohort study.Settings and ParticipantsFecal samples were obtained from 119 healthy Taiwanese volunteers, and 16S rRNA sequencing was done on the V3-V4 regions to identify the bacterial enterotypes. Twenty-six samples from the above cohort were compared with fecal samples from 22 peritoneal dialysis and 16 hemodialysis patients to identify species-level bacterial biomarkers in the dysbiotic gut of chronic kidney disease (CKD) patients.ResultsSpecific bacterial species were identified pertaining to different demographics such as gender, age, BMI, physical activity, and sleeping habits. Dialysis patients had a significant difference in gut microbiome composition compared to healthy controls. The most abundant genus identified in CKD patients was Bacteroides, and at the species level hemodialysis patients showed significant abundance in B. ovatus, B. caccae, B. uniformis, and peritoneal dialysis patients showed higher abundance in Blautia producta (p ≤ 0.05) than the control group. Pathways pertaining to the production of uremic toxins were enriched in CKD patients. The abundance of the bacterial species depended on the type of dialysis treatment.ConclusionThis study characterizes the healthy gut microbiome of a Taiwanese population in terms of various demographics. In a case-control examination, the results showed the alteration in gut microbiota in CKD patients corresponding to different dialysis treatments. Also, this study identified the bacterial species abundant in CKD patients and their possible role in complicating the patients’ condition.

Sorafenib is the first approved systemic targeting agent for advanced HCC; however, when used alone, drug resistance can result in considerably reduced efficacy. Here, we demonstrate that niclosamide, an antihelminthic agent approved by the US Food and Drug Administration, can be repurposed to increase sorafenib sensitivity in sorafenib-resistant HCC cells. We generated sorafenib-resistant HCC cell lines (HepG2215_R and Hep3B_R) with elevated IGF-1R levels and strong properties in terms of stemness and epithelial–mesenchymal transition. Niclosamide was found to increase sorafenib sensitivity effectively in both cell lines and their organoids. The underlying mechanism involves the modulation of cancer stemness, IGF-1R/p-IGF1R/OCT4, and metabolic changes. The combination of sorafenib and niclosamide, but not linsitinib, effectively suppressed the IGF-1R/OCT4 expressions, yielded a synergistic combination index (CI), and attenuated stemness-related properties such as secondary tumor sphere formation and cell migration in sorafenib-resistant HCC cells. Notably, niclosamide significantly suppressed the sorafenib-induced IGF-1R phosphorylation prompted by IGF-1 treatment. Niclosamide effectively downregulated the sorafenib-induced gene expression associated with glycolysis (GLUT1, HK2, LDHA, and PEPCK), stemness (OCT4), and drug resistance (ABCG2) and enhanced the ability of sorafenib to reduce the mitochondrial membrane potential in vitro. The synergistic effect of a combination of niclosamide and sorafenib in vivo was further demonstrated by the decreased tumor size and tumor volume resulting from apoptosis regulation. Our results suggest that niclosamide can enhance sorafenib sensitivity in sorafenib-resistant HCC cells through IGF-1R/stemness regulation and metabolic changes. Our findings highlight a practical clinical strategy for enhancing sorafenib sensitivity in HCC.

We report a high-average-power noise-like pulse (NLP) and dissipative soliton (DS) pulse fiber laser. Average power as high as 4.8 W could be obtained at the fundamental mode-locked repetition rate. The NLP can also be transformed into a more powerful DS mode-locking state by optimizing the polarization and losses of intra-cavity pulses in the nonlinear polarization evolution regime. The operation mode between the NLP and DS can be switched, and the laser output performance in both modes has been studied. The main advantage of this work is switchable high-power operation between the NLP and DS. In comparison with conventional single-mode NLP fiber lasers, the multi-function high-power optical source will greatly push its application in supercontinuum generation, coherence tomography, and industrial processing.

Single domain spectral/pseudospectral integration preconditioning matrices have been shown to be effective operators for solving differential equations. In this study we extend the integration precondition methodology to a multidomain computational framework, and construct global inverse matrices for the advection operator discretized by multidomain Gauss-Lobatto-Legendre pseudospectral methods. These inverse operators can be used as solution operators for solving first order boundary value problems even with piecewise continuous variable coefficients. Moreover, they are effective integration preconditioning matrices for the second order diffusion operator, in the sense that a model diffusion problem can be solved by an iterative method with the number of iteration steps being proportional to the number of subdomains but independent of the degree of the solution polynomial. Numerical experiments were conducted and we observed the performance of the inverse operators as expected.

Resilience, which has rapidly become an area of interest in multiple disciplines, is regarded as being key in disaster mitigation and adaptation. The objective-indicator framework is a common way to evaluate resilience, but limited attention has been paid to measuring the risk perceptions and adaptation behaviors of individuals. In addition, due to limitations related to predicting potential earthquake events, past studies have placed more emphasis on predisaster discussions. Fortunately, this paper explores the changes in risk perceptions and adaptation behaviors in different socioeconomic groups through a comparative analysis between pre- and postearthquake disasters and through one-way analysis of variance (ANOVA) with a post hoc test applied to examine the changes in risk perceptions and adaptation behaviors. The results show that people tend to have greater risk perceptions of future earthquakes but are less willing to retrofit their houses after a serious disaster. Females show greater fear and worry accompanied by a higher willingness to retrofit their houses compared to males. In addition, people with a higher education level and a better occupation might be more willing than others to adopt adaptation behaviors. The results can serve as a reference to provide risk communication, risk education, and diverse disaster adaptation options. Although limitations exist, the results of comparative analysis between the predisaster and postdisaster conditions could serve as a reference for adequate strategies and government decisions on the prioritization of risk management policies.

The design of hybrid structure offers an attractive solution to enhance strength and structural stiffness as well as to achieve lightweight effect and cost reduction. The applications of steel–FRP (fiber-reinforced polymer) composites in transportation and civil engineering have been comprehensively reviewed. In order to apply hybrid structures to car body parts such as B-pillar, flexural performance of steel–FRP composites is investigated by means of three-point bending test in this study. An analytical model is deduced to calculate the initial stiffness, the bending load and the energy absorption of steel–FRP composites. Steel–CFRP (carbon fiber-reinforced polymer) and steel–AFRP (aramid fiber-reinforced polymer) composites are experimentally studied and discussed. The results demonstrate that the steel–FRP composites exhibit significantly higher load-carrying capabilities and initial stiffnesses along with larger energy absorptions in the bending process compared to the single steel sheet.

Lin Wang,1,* Jun Xiao,2,* Min-Zhe Li,3 Wen-Hao Teng,2 Jing Jia,1 Lu Lin,1 Sheng Liu,2 Xing-ming Ye,1 Wei-Dong Zang,2 Ying Chen1 1Central Laboratory, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350000, People’s Republic of China; 2Department of Gastrointestinal Surgery, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350000, People’s Republic of China; 3General Surgery Department, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wei-Dong ZangDepartment of Gastrointestinal Surgery, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350000, People’s Republic of ChinaEmail zwddoctor@126.comYing ChenCentral Laboratory, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350000, People’s Republic of ChinaEmail fjbccy@fjmu.edu.cnIntroduction: The aim of the present study was to evaluate a nomogram model for predicting the 5-year overall survival (OS) in lymph node-metastatic colorectal cancer (CRC) patients by combining inflammation markers with some traditional prognostic factors.Methods: A total of 399 patients with stage III (pTXN1-3M0) CRC operated from January 2007 to December 2012 were enrolled in this retrospective study. All patients underwent D2 lymphadenectomy in the hospital. A prognostic nomogram based on the integration of traditional prognostic factors and NLR (neutrophil-to-lymphocyte ratio) and PLR (platelet-to-lymphocyte ratio) was established and compared with the nomogram based on the traditional prognostic factors alone. ROC curves were further applied to verify the predictive accuracy of the established model.Results: Both NLR (P=0.00) and PLR (P=0.01) predicted the 5-year OS. In multivariate analysis, age, T3 category, T4 category, N2 category, N3 category, Pgp (P-glycoprotein), NLR and PLR are proven to be independent (all P≤ 0.05). The established nomogram showed better predictive power than that of traditional profile (c-index: 0.66 versus 0.63) in both training and validation cohorts. External assessment by ROC curve analysis demonstrated that the established model had a good prediction accuracy of 5-year OS in stage III CRC patients, with area under curve values of 0.657 and 0.629 in training and validating sets, respectively.Conclusion: A nomogram based on the integration of traditional prognostic factors and inflammatory markers (NLR and PLR) could provide more precise long-term prognosis information for lymph node-metastatic CRC patients than the model based on traditional profile alone. This model might be useful for clinical application in personalized evaluation.Keywords: nomogram, TNM staging system, lymph node metastasis, colorectal cancer, prognosis

Spectral/pseudospectral integration preconditioning matrices are useful tools for solving differential equations involving pure differential operators d m / d x m . In this study we construct well-conditioned inverse pseudospectral matrices for the basic differential operator and the mixed differential operator d d r a ( r ) d d r on Gauss-Radau-Legendre points based on stepwise integrations and low-rank updates. The inverse matrices can be used either as a solution operator or an effective preconditioner for variable coefficient differential equations of first and second order in polar coordinates. Numerical experiments were conducted and we observed the performance of the inverse operator as expected.

Electric load analysis is an important task in early new stage for design of shipboard power systems (SPSs). The installation generation capacity onboard depends on the accurate result of the analysis, which significantly affects the system economic and secure operations. In the traditional electrical load analysis, the demand factor is often obtained from engineering experiences which may lead to inaccurate analysis results. In order to obtain better results, a methodology for electrical load analysis in SPSs is proposed in this article. The load analysis spreadsheet is adopted to find the power consumption of key electric loads in SPSs. The actual power consumptions of selected loads are collected by intelligent meters. The statistical analysis is then performed to find the critical parameter of each selected load in the load analysis under different operating conditions based on the power measurement of field test and load analysis is performed for estimating system power demand accordingly. The large practical maritime vessel power systems are selected for numerical analysis to ensure the performance of the proposed method. The proposed method has been adopted by local ship builders in Taiwan to better understand the load characteristics in shipboard power systems to support various functions of system planning and operation in a more effective manner.

Mercury (Hg) contamination in remote lakes stems from atmospheric Hg transport to surface waters and subsequent conversion by microbes to neurotoxic methylmercury (MeHg) that biomagnifies in pelagi...

The porous and biomimetic cobalt silicate@diatomite (Co

Load survey has become a routine project for shipbuilding and shipping companies to investigate electrical load characteristics to enhance the power system planning and operation of marine vessels. In this brief perspective, we will outline a few steps to feeder losses analysis based on the result conducted by the load survey. The power flow and feeder loss analysis are extracted and used to determine the critical parameters that can significantly affect the system feeder losses used in the electrical load analysis in new ships. Exploring this new research direction will provide a more thorough understanding of feeder losses in marine vessel power systems. In this paper, a case study of container ship power loss analysis using the Newton–Raphson method is presented. The analysis results can provide shipbuilding corporations and ship owners with useful information for planning, designing, operating, and controlling shipboard power systems. As an energy-saving measure for ship microgrids, the frequency converters are widely used by shipyards for seawater and freshwater cooling systems and heating, ventilation, and air conditioning (HVAC) systems, so that these systems can adjust the speed of the motor according to the actual demand of the load, so as to avoid full-load operation during the motor operation. With the proposed method, other measures, such as battery energy storage systems and energy-saving lighting equipment based on LEDs, are also utilized for shipboard power demand management.

We experimentally demonstrate a 38-fs chirped-pulse amplified (CPA) Ti:sapphire laser system based on the power-scalable thin-disk scheme with an average output power of 1.45 W at a repetition rate of 1 kHz, corresponding to peak power of 38 GW. The beam profile close to the diffraction limit with a measured M2 value of approximately 1.1 is obtained. It demonstrates the potential for an ultra-intense laser with high beam quality compared with the conventional bulk gain amplifier. To the best of our knowledge, this is the first reported Ti:sapphire regenerative amplifier based on the thin-disk approach reaching 1 kHz.