Language variation in teacher speech in a dual immersion preschool

This study investigates the language input provided for English-Mandarin emergent bilingual children in a California English-Mandarin dual immersion preschool. As illustrated in previous studies, teacher speech in foreign language classrooms often serves as the native standard of the target language, thus necessarily limiting students’ exposure to stylistic variation. The current research focused on the language input for emergent bilingual preschoolers who were Chinese heritage language learners and the use of sociolinguistic variables, including Mandarin lexical tones and word-initial sibilants, by their teachers. Results show that although the teachers perceived their classroom roles differently, they tried to provide clear and rich Mandarin input with tonal and sibilant variables that were used in consistent patterns. Except for the constraints of the linguistic environment, standard variables were preferred in classroom discourse. This implies that the particular needs of the English-dominant children to acquire Mandarin have been acknowledged and addressed by teachers. This type of modification in language input may affect children’s development of phonetic categories and their sociolinguistic competence

Decomposition-Based-Sorting and Angle-Based-Selection for Evolutionary Multiobjective and Many-Objective Optimization

Multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem (MOP) into a number of scalar optimization subproblems and then solves them in parallel. In many MOEA/D variants, each subproblem is associated with one and only one solution. An underlying assumption is that each subproblem has a different Pareto-optimal solution, which may not be held, for irregular Pareto fronts (PFs), e.g., disconnected and degenerate ones. In this paper, we propose a new variant of MOEA/D with sorting-and-selection (MOEA/D-SAS). Different from other selection schemes, the balance between convergence and diversity is achieved by two distinctive components, decomposition-based-sorting (DBS) and angle-based-selection (ABS). DBS only sorts ${L}$ closest solutions to each subproblem to control the convergence and reduce the computational cost. The parameter ${L}$ has been made adaptive based on the evolutionary process. ABS takes use of angle information between solutions in the objective space to maintain a more fine-grained diversity. In MOEA/D-SAS, different solutions can be associated with the same subproblems; and some subproblems are allowed to have no associated solution, more flexible to MOPs or many-objective optimization problems (MaOPs) with different shapes of PFs. Comprehensive experimental studies have shown that MOEA/D-SAS outperforms other approaches; and is especially effective on MOPs or MaOPs with irregular PFs. Moreover, the computational efficiency of DBS and the effects of ABS in MOEA/D-SAS are also investigated and discussed in detail

Characterization and Performance Testing of Two-Stage Reciprocating Compressors using a Hot-Gas Load Stand with Carbon Dioxide

This paper presents the performance measurements of carbon dioxide two-stage reciprocating compressors using a hot-gas load stand. The data is used to characterize the compressors’ performances and evaluate the oil management between the two compressors. A compressor load stand has been redesigned to conduct the compressor performance tests. Two hermetic reciprocating compressors, including two oil separators, two intercooling fans and safety control valves, are connected to the load stand. A membrane tank filled with the working fluid is connected to the load stand, using an appropriate back pressure on the membrane to ensure a fixed intermediate pressure as the anchor point of the hot gas cycle. The first series of compressor tests was conducted for varying suction pressures and varying discharge pressures with different pressure ratios. In a second series, the running time was varied and the suction pressure was kept constant. Based on these measurements, the compressor performance indices, such as the volumetric and overall isentropic efficiencies, have been determined. Furthermore, compressor initial clearance factor can be calculated, based on available compressor maps, which is useful tool for future carbon dioxide system modeling. Also, a simulation model to predict the compressor performance has been developed. The entire process can be simulated to provide the compressor performance data for different working conditions. Finally, the compressor performance measurements are used to validate the model predictions

Characterization and Performance Testing of Two-Stage Reciprocating Compressors during the Dynamic Charging of a Tank with Air

Relative little information is available in the literature with respect to compressor performances during dynamic charging processes. Therefore, the work presented in this paper focuses on the experimental performance testing of two-stage reciprocating compressors using air as the working fluid during the dynamic charging of a tank. A new test stand has been designed and built to conduct the dynamic compressor performance tests. Performance tests have been conducted from an initial pressure of 101.3 kPa to a final tank pressure of 3600 kPa. To achieve the final pressure of 3600 kPa, two hermetic reciprocating compressors are used in series. Due to the nature of the charging process, initially only the first stage compressor is activated until the tank pressure reaches a level that requires activation of the second stage compressor. Â Along with the experimental effort, a simulation model to predict the compressor dynamic performance has been developed. In this model, the initial clearance factors of the two compressors can be calculated based on available compressor maps. These clearance factors are then used as inputs to the dynamic model. The entire charging process can be simulated to provide the compressor performance data as the function of time. Finally, the predicted performance is validated using the test data and presented in this paper

Dynamic experimental investigation on the volatilization behavior of lead and cadmium in the simulated Municipal Solid Waste (MSW) influenced by sulfur compounds during incineration

In China, coal, often with a high level of sulfur, is always mixed with municipal solid waste (MSW) in waste incineration plants due to the low heating value and high moisture content of MSW. The influence of sulfur compounds on the volatilization of heavy metals in MSW is of great concern for China’s waste incineration plants. In this study, the continuous dynamic volatilization process of Pb and Cd is investigated by adding different forms of sulfur compounds, elemental sulfur (S), and sodium sulfate (Na2SO4), to the simulated MSW in a laboratory incinerator, at both 1 and 3 wt %, respectively. The experimental results show that the added S begins to affect the volatilization of Pb and Cd at about 700 °C; adding S can lead up to 49.6% reduction in the volatilization of Pb, as the produced sulfur dioxide is promoting the formation of a condensed sulfate phase, and part of Pb is fixed in the form of PbS in the bottom ash. But for Cd, adding S causes up to 15.9% increase in its volatilization as S seizes part of O2 in the air, which is conducive to forming the reducing atmosphere. In the reducing atmosphere, CdO can be easily reduced to Cd, which volatilizes more easily than CdO at high temperatures. In fact, in the reducing atmosphere, the volatilization of Cd far outweighs the volatilization of Pb at 700–800 °C. On the other hand, adding Na2SO4 almost has no influence on the volatilization of lead and cadmium below 900 °C

CuO-In 2

The CuO-In2O3 core-shell nanowire was fabricated by a two-step method. The CuO nanowire core (NWs) was firstly grown by the conventional thermal oxidation of Cu meshes at 500°C for 5 hours. Then, the CuO nanowires were immersed into the suspension of amorphous indium hydroxide deposited from the In(AC)3 solution by ammonia. The CuO nanowires coated with In(OH)3 were subsequently heated at 600°C to form the crystalline CuO-In2O3 core-shell structure, with In2O3 nanocrystals uniformly anchored on the CuO nanowires. The gas sensing properties of the formed CuO-In2O3 core-shell nanowires were investigated by various reducing gases such as hydrogen, carbon monoxide, and propane at elevated temperature. The sensors using the CuO-In2O3 nanowires show improved sensing performance to hydrogen and propane but a suppressed response to carbon monoxide, which could be attributed to the enhanced catalytic properties of CuO with the coated porous In2O3 shell and the p-n junction formed at the core-shell interface

Akuammiline alkaloid derivatives: divergent synthesis and effect on the proliferation of rheumatoid arthritis fibroblast-like synoviocytes

During the past decades, rheumatoid arthritis had become a serious problem, torturing millions of patients because of unclear pathogenesis and no ideal therapies. Natural products remain an important source of medicines to treat various major diseases such as rheumatoid arthritis (RA) given their excellent biocompatibility and structural diversity. Herein, we have developed a versatile synthetic method for constructing various skeletons of akuammiline alkaloid analogs based on our previous research on the total synthesis of the related indole alkaloids. We have also evaluated the effect of these analogs on the proliferation of RA fibroblast-like synoviocytes (FLSs) in vitro and analyzed the corresponding structure-activity relationship (SAR). Among these analogs, compounds 9 and 17c have demonstrated a promising inhibitory effect on the proliferation of RA-FLSs, with IC50 values of 3.22 ± 0.29 μM and 3.21 ± 0.31 μM, respectively. Our findings provide a solid foundation for future pharmacological studies on akuammiline alkaloid derivatives and inspiration for the development of anti-RA small molecule drugs derived from natural products

A novel nomogram for adult primary perihilar cholangiocarcinoma and considerations concerning lymph node dissection

ObjectiveTo construct a reliable nomogram available online to predict the postoperative survival of patients with perihilar cholangiocarcinoma.MethodsData from 1808 patients diagnosed with perihilar cholangiocarcinoma between 2004 and 2015 were extracted from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database. They were randomly divided into training and validation sets. The nomogram was established by machine learning and Cox model. The discriminant ability and prediction accuracy of the nomogram were evaluated by concordance index (C-index), receiver operator characteristic (ROC) curve and calibration curve. Kaplan-Meier curves show the prognostic value of the associated risk factors and classification system.ResultsMachine learning and multivariate Cox risk regression model showed that sex, age, tumor differentiation, primary tumor stage(T), lymph node metastasis(N), TNM stage, surgery, radiation, chemotherapy, lymph node dissection were associated with the prognosis of perihilar cholangiocarcinoma patients relevant factors (P < 0.05). A novel nomogram was established. The calibration plots, C-index and ROC curve for predictions of the 1-, 3-, and 5-year OS were in excellent agreement. In patients with stage T1 and N0 perihilar cholangiocarcinoma, the prognosis of ≥4 lymph nodes dissected was better than that of 1- 3 lymph nodes dissected (P < 0.01).ConclusionThe nomogram prognostic prediction model can provide a reference for evaluating the prognosis and survival rate of patients with perihilar cholangiocarcinoma. Patients with stage T1 and N0 perihilar cholangiocarcinoma have more benefits by increasing the number of lymph node dissection