Enhanced SPARQL-based design rationale retrieval

Design rationale (DR) is an important category within design knowledge, and effective reuse of it depends on its successful retrieval. In this paper, an ontology-based DR retrieval approach is presented, which allows users to search by entering normal queries such as questions in natural language. First, an ontology-based semantic model of DR is developed based on the extended issue-based information system-based DR representation in order to effectively utilize the semantics embedded in DR, and a database of ontology-based DR is constructed, which supports SPARQL queries. Second, two SPARQL query generation methods are proposed. The first method generates initial SPARQL queries from natural language queries automatically using template matching, and the other generates initial SPARQL queries automatically from DR record-based queries. In addition, keyword extension and optimization is conducted to enhance the SPARQL-based retrieval. Third, a design rationale retrieval prototype system is implemented. The experimental results show the advantages of the proposed approach

Automatic Article Commenting: the Task and Dataset

Comments of online articles provide extended views and improve user engagement. Automatically making comments thus become a valuable functionality for online forums, intelligent chatbots, etc. This paper proposes the new task of automatic article commenting, and introduces a large-scale Chinese dataset with millions of real comments and a human-annotated subset characterizing the comments' varying quality. Incorporating the human bias of comment quality, we further develop automatic metrics that generalize a broad set of popular reference-based metrics and exhibit greatly improved correlations with human evaluations.Comment: ACL2018; with supplements; Dataset link available in the pape

An approach for design rationale retrieval using ontology-aided indexing

Design rationale (DR) is an important part of design knowledge. Effective reuse of DR depends on its successful retrieval. In this paper, an approach for structured DR retrieval using ontology-aided indexing is presented. Firstly, an ontology-based semantic model of DR is developed based on the extended IBIS-based DR representation in order to effectively utilise the semantics embedded in DR. Then, an ontology-aided indexing method is proposed to build indexes for DR records to index the semantic concepts and relationships in DR. Furthermore, three kinds of query modes are developed to support flexible querying, among which natural language input query and DR record-based query have much more semantics and thus lead to better retrieval results. Finally, a prototype system is implemented. Experimental results show the effectiveness of the proposed approach

SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills

Traditional multitask learning methods basically can only exploit common knowledge in task- or language-wise, which lose either cross-language or cross-task knowledge. This paper proposes a general multilingual multitask model, named SkillNet-X, which enables a single model to tackle many different tasks from different languages. To this end, we define several language-specific skills and task-specific skills, each of which corresponds to a skill module. SkillNet-X sparsely activates parts of the skill modules which are relevant either to the target task or the target language. Acting as knowledge transit hubs, skill modules are capable of absorbing task-related knowledge and language-related knowledge consecutively. Based on Transformer, we modify the multi-head attention layer and the feed forward network layer to accommodate skill modules. We evaluate SkillNet-X on eleven natural language understanding datasets in four languages. Results show that SkillNet-X performs better than task-specific baselines and two multitask learning baselines (i.e., dense joint model and Mixture-of-Experts model). Furthermore, skill pre-training further improves the performance of SkillNet-X on almost all datasets. To investigate the generalization of our model, we conduct experiments on two new tasks and find that SkillNet-X significantly outperforms baselines

Crafting NPB with tetraphenylethene: a win–win strategy to create stable and efficient solid-state emitters with aggregation-induced emission feature, high hole-transporting property and efficient electroluminescence

N,N′-Di-(1-naphthyl)-N,N′-diphenyl-(1,1′-biphenyl)-4,4′-diamine (NPB) possesses high thermal and morphological stability and is one of the well-known hole-transporting materials for the fabrication of organic light-emitting diodes (OLEDs). Modification of NPB by the covalent integration of tetraphenylethene (TPE) into its structure dramatically changes its emission behavior: the resulting adduct (TPE–NPB) is highly emissive in the aggregated state, showing a novel phenomenon of aggregation-induced emission (AIE). The adduct is thermally and morphologically stable. Non-doped multilayer electroluminescence (EL) devices using TPE–NPB as an emitting layer were fabricated, which emitted green light with a maximum luminance and current efficiency of 11[thin space (1/6-em)]981 cd m−2 and 11.9 cd A−1, respectively. Even better device performances are observed in the bilayer device without NPB. Our strategy takes the full advantage of the AIE property in the solid state and retains the inherent properties of conventional luminophores. It opens a new avenue in the development of stable and efficient solid-state fluorescent materials for OLED application

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Regional Ecological Risk Assessment in the Huai River Watershed during 2010–2015

Ecosystem deterioration has been and is still a serious threat to human survival and regional economic development. Theoretical and methodological challenges exist in assessing ecological risk of watershed ecosystem that is imposed by natural changes or human activities. To fill this research gap, this research proposes an interdisciplinary and quantitative methodology based on some techniques such as the Procedure for Ecological Tiered Assessment of Risk (PETAR), the Entropy, and the Celluar Automata Markov (CA-Markov). We focused on six vulnerable environmental variables, namely land-use change, water quantity, water quality, gross domestic product (GDP), environmental pollutants, and soil erosion in the Huai River watershed in the Henan Province in order to build multi-dimensional quantitative method. Further, the Coupling Coordination Degree Model is constructed, and the “threshold index” is also addressed to reflect the limitation of ecological risk. Our results show that the spatio-temperal distribution of the eco-environmental quality has greatly varied across this study area during different time spans. Natural eco-environmental quality has moderately degraded in 70% of this study area (mainly agricultural region), at a prefectural level from 2000 to 2010, and has slightly improved over the agricultural region (&lt;170 m above sea level) during 2010–2015. However, when considering negative stressors from human social system on the natural ecosystem, the extent and distribution of the ecological risk varied across the whole area during 2000–2015. The results show that there was almost 90.40% of this region under the ecological risk, with varying extents over the study time, e.g., Kaifeng, Shangqiu, Xuchang, and Xinyang, with a moderate deterioration in the eco-environmental quality, and Zhengzhou with a slight deterioration in the eco-environmental quality. This paper provides a valuable perspective for governments at all levels to manage watershed environment resources

Optimization of the Electrochemical Treatment of 4-chlorophenol Wastewater Using Response Surface Method

Chlorophenols (CPs) are a kind of important organic chemical intermediates, which are produced in various industrial processes. Currently, electrochemical method is the most effective treatment for the degradation of chlorophenols (CPs) in wastewater. In this study, a three-dimensional electrode electrochemical reactor, constructed using the Sn/Sb-Mn-GAC (granular activated carbon) particle electrodes, was used to treat the wastewater containing 4-chlorophenol. On the basis of single factor experiments, the process conditions of the designed three-dimensional electrochemical reactor were optimized using the response surface methodology. The experimental results showed that the three-dimensional electrochemical reactor could effectively reduce 4-chlorophenol by 96.13% at the optimum Na2SO4 concentration of 2 g·L−1, electrode plate distance of 2 cm, current intensity of 2 A, and particle electrode dosage of 14 g. The experimental observations were in reasonable agreement with the modeled values, thus verifying the design of the proposed reactor

Pathogen distribution in pulmonary infection in chinese patients with lung cancer: a systematic review and meta-analysis

Abstract Background The immunity of patients with lung cancer decreases after treatment; thus, they are easily infected with pathogenic bacteria that causes pulmonary infections. Understanding the distribution characteristics of pathogenic bacteria in pulmonary infection in patients with lung cancer after treatment can provide a basis to effectively prevent infection and rationally use antibacterial drugs. However, no meta-analyses have assessed the distribution characteristics of pathogenic bacteria in mainland China. Therefore, our meta-analysis aimed to investigate the pathogen distribution in pulmonary infection in Chinese patients with lung cancer. Methods A literature search was conducted to study the pathogen distribution in pulmonary infection in Chinese patients with lung cancer between January 1, 2020 and December 31, 2022, using English and Chinese databases. The relevant data were extracted. The meta-analysis was performed using a random-effects model ( I2 > 50%) with 95% confidence intervals for forest plots. Data were processed using RevMan 5.3. Results Fifteen studies (2,683 strains in 2,129 patients with pulmonary infection were cultured) met the evaluation criteria. The results showed that Gram-negative bacteria had the highest detection rate (63%), followed by Gram-positive bacteria (23%), and fungi (12%). Among the Gram-negative bacteria detected, the distribution of the main pathogenic bacteria was Klebsiella pneumonia (17%), Pseudomonas aeruginosa (14%), Escherichia coli (13%), Acinetobacter baumannii (7%), Enterobacter cloacae (4%), and Hemophilus influenza (4%). Moreover, the prevalence of pulmonary infections after chemotherapy (53%) was significantly higher than that after surgery (10%), P < 0.05. Conclusions The prevalence of pulmonary infections after treatment, especially after chemotherapy, is high in Chinese patients with lung cancer, and Gram-negative bacteria are the predominant pathogens. Further studies are needed to monitor the prevalence of pulmonary infections and pathogen distribution in lung cancer patients in mainland China