The Research of the Ecosystem on Green Construction

Green construction ecosystem was studied. The author analyses the system of construction, and proposed the system of green construction based on ecology theory which was included subsystem of the condition, process and objective on the ecosystem in order to lay the foundation for system evaluation. The text analyses elements of green construction system, which would help to improve the competitiveness of green construction for construction enterprises, and meet the requirements of environmentally friendly, resource-saving society. The competitiveness of green construction was considered with objective which was evaluated to maximize the competitiveness, and it overcomes the current competitiveness evaluation from the owners and the interests of construction enterprises ignoring the ecological environment. It is a new method which could provide a strong support as a business strategy based on ecological environmental protection, development and green construction program formulation. Analyses indicators of competitiveness and the relationship of the construction phase, it could identify the main reason for the green effect, and find the need to improve measures in order to lay the foundation for further enhancing the competitiveness of construction enterprises

Use of low-dose computed tomography to assess pulmonary tuberculosis among healthcare workers in a tuberculosis hospital

BACKGROUND: According to the World Health Organization, China is one of 22 countries with serious tuberculosis (TB) infections and one of the 27 countries with serious multidrug-resistant TB strains. Despite the decline of tuberculosis in the overall population, healthcare workers (HCWs) are still at a high risk of infection. Compared with high-income countries, the TB prevalence among HCWs is higher in low- and middle-income countries. Low-dose computed tomography (LDCT) is becoming more popular due to its superior sensitivity and lower radiation dose. However, there have been no reports about active pulmonary tuberculosis (PTB) among HCWs as assessed with LDCT. The purposes of this study were to examine PTB statuses in HCWs in hospitals specializing in TB treatment and explore the significance of the application of LDCT to these workers. METHODS: This study retrospectively analysed the physical examination data of healthcare workers in the Beijing Chest Hospital from September 2012 to December 2015. Low-dose lung CT examinations were performed in all cases. The comparisons between active and inactive PTB according to the CT findings were made using the Pearson chi-square test or the Fisher’s exact test. Comparisons between the incidences of active PTB in high-risk areas and non-high-risk areas were performed using the Pearson chi-square test. Analyses of active PTB were performed according to different ages, numbers of years on the job, and the risks of the working areas. Active PTB as diagnosed by the LDCT examinations alone was compared with the final comprehensive diagnoses, and the sensitivity and positive predictive value were calculated. RESULTS: A total of 1 012 participants were included in this study. During the 4-year period of medical examinations, active PTB was found in 19 cases, and inactive PTB was found in 109 cases. The prevalence of active PTB in the participants was 1.24%, 0.67%, 0.81%, and 0.53% for years 2012 to 2015. The corresponding incidences of active PTB among the tuberculosis hospital participants were 0.86%, 0.41%, 0.54%, and 0.26%. Most HCWs with active TB (78.9%, 15/19) worked in the high-risk areas of the hospital. There was a significant difference in the incidences of active PTB between the HCWs who worked in the high-risk and non-high-risk areas (odds ratio [OR], 14.415; 95% confidence interval (CI): 4.733 – 43.896). Comparisons of the CT signs between the active and inactive groups via chi-square tests revealed that the tree-in-bud, cavity, fibrous shadow, and calcification signs exhibited significant differences (P = 0.000, 0.021, 0.001, and 0.024, respectively). Tree-in-bud and cavity opacities suggest active pulmonary tuberculosis, whereas fibrous shadow and calcification opacities are the main features of inactive pulmonary tuberculosis. Comparison with the final comprehensive diagnoses revealed that the sensitivity and positive predictive value of the diagnoses of active PTB based on LDCT alone were 100% and 86.4%, respectively. CONCLUSIONS: Healthcare workers in tuberculosis hospitals are a high-risk group for active PTB. Yearly LDCT examinations of such high-risk groups are feasible and necessary. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40249-017-0274-6) contains supplementary material, which is available to authorized users

Fast and accurate trajectory tracking control of an autonomous surface vehicle with unmodeled dynamics and disturbances

In this paper, fast and accurate trajectory tracking control of an autonomous surface vehicle (ASV) with complex unknowns including unmodeled dynamics, uncertainties and/or unknown disturbances is addressed within a proposed homogeneity-based finite-time control (HFC) framework. Major contributions are as follows: (1) In the absence of external disturbances, a nominal HFC framework is established to achieve exact trajectory tracking control of an ASV, whereby global finitetime stability is ensured by combining homogeneous analysis and Lyapunov approach; (2) Within the HFC scheme, a finite-time disturbance observer (FDO) is further nested to rapidly and accurately reject complex disturbances, and thereby contributing to an FDO-based HFC (FDO-HFC) scheme which can realize exactness of trajectory tracking and disturbance observation; (3) Aiming to exactly deal with complicated unknowns including unmodeled dynamics and/or disturbances, a finite-time unknown observer (FUO) is deployed as a patch for the nominal HFC framework, and eventually results in an FUO-based HFC (FUOHFC) scheme which guarantees that accurate trajectory tracking can be achieved for an ASV under harsh environments. Simulation studies and comprehensive comparisons conducted on a benchmark ship demonstrate the effectiveness and superiority of the proposed HFC schemes

Intuitive Fine-Tuning: Towards Simplifying Alignment into a Single Process

Supervised Fine-Tuning (SFT) and Preference Optimization (PO) are two fundamental processes for enhancing the capabilities of Language Models (LMs) post pre-training, aligning them better with human preferences. Although SFT advances in training efficiency, PO delivers better alignment, thus they are often combined. However, common practices simply apply them sequentially without integrating their optimization objectives, ignoring the opportunities to bridge their paradigm gap and take the strengths from both. To obtain a unified understanding, we interpret SFT and PO with two sub-processes -- Preference Estimation and Transition Optimization -- defined at token level within the Markov Decision Process (MDP) framework. This modeling shows that SFT is only a specialized case of PO with inferior estimation and optimization. PO evaluates the quality of model's entire generated answer, whereas SFT only scores predicted tokens based on preceding tokens from target answers. Therefore, SFT overestimates the ability of model, leading to inferior optimization. Building on this view, we introduce Intuitive Fine-Tuning (IFT) to integrate SFT and Preference Optimization into a single process. IFT captures LMs' intuitive sense of the entire answers through a temporal residual connection, but it solely relies on a single policy and the same volume of non-preference-labeled data as SFT. Our experiments show that IFT performs comparably or even superiorly to sequential recipes of SFT and some typical Preference Optimization methods across several tasks, particularly those requires generation, reasoning, and fact-following abilities. An explainable Frozen Lake game further validates the effectiveness of IFT for getting competitive policy

Antifungal effects of sisal leaf juice on Lasiodiplodia theobromae, the causal agent of mulberry root rot

This study was carried out to evaluate the antifungal activities of leaf juices (fresh juice, fermented juice, boiled juice and sterile juice) of nine sisal varieties on Lasiodiplodia theobromae, the causal agent of mulberry root rot. Results show that all the leaf juices could inhibit the mycelial growth in different degrees (the inhibitory rates ranged from 63.3 to 100%), due to different varieties and treatments. Among the nine varieties, the inhibition effects of hybrid 76416 and Agave americana were the best with absolute inhibition of all the leaf juice treatments against the mycelial growth, followed by Agave Amaniensis, Agave virdis, Agave angustifolia and Hybrid 11648. The inhibitory effect of some fresh juices would be cut down after being fermented, boiled and sterilized. The treated mycelia of L.theobromae were malformed, enlarged, broken and plasma leaked when observed under the microscope. Most of the leaf juices could inhibit the conidial germination absolutely, except A.amaniensis, H.11648 and A. angustifolia. The average germination rate of A. amaniensis, H.11648 and A. angustifolia was 72.4, 16.6 and 13%, respectively. The control efficiency of the fresh juice of H. 11648 against mulberry root rot in the field reached 73.1%.Key words: Sisal, leaf juice, anti-fungi, anti-fungal activities, mulberry root rot, Lasiodiplodia theobromae

Single-cell sequencing and multiple machine learning algorithms to identify key T-cell differentiation gene for progression of NAFLD cirrhosis to hepatocellular carcinoma

Introduction: Hepatocellular carcinoma (HCC), which is closely associated with chronicinflammation, is the most common liver cancer and primarily involves dysregulated immune responses in the precancerous microenvironment. Currently, most studies have been limited to HCC incidence. However, the immunopathogenic mechanisms underlying precancerous lesions remain unknown.Methods: We obtained single-cell sequencing data (GSE136103) from two nonalcoholic fatty liver disease (NAFLD) cirrhosis samples and five healthy samples. Using pseudo-time analysis, we systematically identified five different T-cell differentiation states. Ten machine-learning algorithms were used in 81 combinations to integrate the frameworks and establish the best T-cell differentiation-related prognostic signature in a multi-cohort bulk transcriptome analysis.Results: LDHA was considered a core gene, and the results were validated using multiple external datasets. In addition, we validated LDHA expression using immunohistochemistry and flow cytometry.Conclusion: LDHA is a crucial marker gene in T cells for the progression of NAFLD cirrhosis to HCC

Preoperative Alfa-Fetoprotein and Fibrinogen Predict Hepatocellular Carcinoma Recurrence After Liver Transplantation Regardless of the Milan Criteria: Model Development with External Validation

Background/Aims: Patient selection is critically important in improving the outcomes of liver transplantation for hepatocellular carcinoma. The aim of the current study was to identify biochemical measures that could affect patient prognosis after liver transplantation. Methods: A total of 119 patients receiving liver transplantation for hepatocellular carcinoma were used to construct a model for predicting recurrence. The results were validated using an independent sample of 109 patients from independent hospitals. All subjects in both cohorts met the Hangzhou criteria. Results: Analysis of the discovery cohort revealed an association of recurrence with preoperative fibrinogen and AFP levels. A mathematical model was developed for predicting probability of recurrence within 5 years: Y = logit(P) = -4.595 + 0.824 ×fibrinogen concentration (g/L) + 0.641 × AFP score (1 for AFP<=20ng/ml, 2 for 20<AFP<=100ng/ml, 3 for 100<AFP<=200ng/ml, 4 for 200<AFP<=400ng/ml, 5 for AFP> 400ng/ml). At a cutoff score of -0.85, the area under the curve (AUC) was 0.819 in predicting recurrence (vs. 0.655 when using the Milan criteria). In the validation cohort, this model had reasonable performance in predicting 5-year overall survival (68.8% vs. 28.1% in using the -0.85 cutoff, p< 0.001) and disease-free survival (65.7% vs. 25.9%, p< 0.001). The sensitivity and specificity were 77.0% and 62.5%, respectively. The AUC of this newly developed model was similar to that with the Milan criteria (0.698 vs. 0.678). Surprisingly, the DFS in patients with score <= -0.85 under this model but not meeting the Milan criteria was similar to that in patients meeting the Milan criteria (53.8% vs. 60.0%, p=0.380). Conclusions: Preoperative AFP and fibrinogen are useful in predicting recurrence of hepatocellular carcinoma after liver transplantation

The CDEX-1 1 kg Point-Contact Germanium Detector for Low Mass Dark Matter Searches

The CDEX Collaboration has been established for direct detection of light dark matter particles, using ultra-low energy threshold p-type point-contact germanium detectors, in China JinPing underground Laboratory (CJPL). The first 1 kg point-contact germanium detector with a sub-keV energy threshold has been tested in a passive shielding system located in CJPL. The outputs from both the point-contact p+ electrode and the outside n+ electrode make it possible to scan the lower energy range of less than 1 keV and at the same time to detect the higher energy range up to 3 MeV. The outputs from both p+ and n+ electrode may also provide a more powerful method for signal discrimination for dark matter experiment. Some key parameters, including energy resolution, dead time, decay times of internal X-rays, and system stability, have been tested and measured. The results show that the 1 kg point-contact germanium detector, together with its shielding system and electronics, can run smoothly with good performances. This detector system will be deployed for dark matter search experiments.Comment: 6 pages, 8 figure

Adaption of Seasonal H1N1 Influenza Virus in Mice

The experimental infection of a mouse lung with influenza A virus has proven to be an invaluable model for studying the mechanisms of viral adaptation and virulence. The mouse adaption of human influenza A virus can result in mutations in the HA and other proteins, which is associated with increased virulence in mouse lungs. In this study, a mouse-adapted seasonal H1N1 virus was obtained through serial lung-to-lung passages and had significantly increased virulence and pathogenicity in mice. Genetic analysis indicated that the increased virulence of the mouse-adapted virus was attributed to incremental acquisition of three mutations in the HA protein (T89I, N125T, and D221G). However, the mouse adaption of influenza A virus did not change the specificity and affinity of receptor binding and the pH-dependent membrane fusion of HA, as well as the in vitro replication in MDCK cells. Notably, infection with the mouse adapted virus induced severe lymphopenia and modulated cytokine and chemokine responses in mice. Apparently, mouse adaption of human influenza A virus may change the ability to replicate in mouse lungs, which induces strong immune responses and inflammation in mice. Therefore, our findings may provide new insights into understanding the mechanisms underlying the mouse adaption and pathogenicity of highly virulent influenza viruses