論五言詩體的音步組合原理

中國早期詩體的生成與音樂有直接關係，五言詩也不例外。它是由一個對稱音步與一個非對稱音步組成的詩行，且對稱音步在前，非對稱音步在後。這是在四言體和楚辭體之後形成的一種新詩體，也是中國詩體發展形式上的一個飛躍。它興盛於漢代，以漢語詩體對音樂節奏的探索爲内在動力，又有賴於語言的發展。中國古典詩詞脱胎於音樂，因而特别重視詩歌的聲音節奏，對稱具有重要意義。同時，由於漢語是一字一音的語言，理想的詩行需要保證有單音詞的靈活存在和自由組合的音樂條件，五言詩恰恰能够同時滿足這兩條要求。五言詩體的初起階段，詩人所關注的主要是音步的對稱和詩行的對稱，進而關注詞性的對稱和句法的對稱。其所以走向格律化，同樣是音樂節奏在其中起了重要作用

Selection of Schizochytrium limacinum mutants based on butanol tolerance

Background: Mutation breeding is one of the most important routes to achieving high docosahexaenoic acid (DHA) productivity using Schizochytrium. However, few selection strategies have been reported that aim to generate a high DHA content in Schizochytrium lipids. Results: First, culture temperature altered the butanol tolerance of Schizochytrium limacinum B4D1. Second, S. limacinum E8 was obtained by selecting mutants with high butanol tolerance. This mutant exhibited a 17.97% lower proportion of DHA than the parent strain S. limacinum B4D1. Third, a negative selection strategy was designed in which S. limacinum F6, a mutant with poor butanol tolerance, was obtained. The proportion of DHA in S. limacinum F6 was 11.22% higher than that of parent strain S. limacinum B4D1. Finally, the performances of S. limacinum B4D1, E8 and F6 were compared. These three strains had different fatty acid profiles, but there was no statistical difference in their biomasses and lipid yields. Conclusion: It was feasible to identified the relative DHA content of S. limacinum mutants based on their butanol tolerance

Electrochemical synthesis of phosphorus and sulfur co-doped graphene quantum dots as efficient electrochemiluminescent immunomarkers for monitoring okadaic acid

Abstract(#br)In this study, water-dispersed, uniform-sized phosphorus and sulfur co-doped graphene quantum dots (P, S-GQDs) were prepared by the one-step electrolysis of a graphite rod in an alkaline solution containing sodium phytate and sodium sulfide. Compared with GQDs and mono-doped GQDs (P-GQDs and S-GQDs), the P, S-GQDs dramatically improved the electrochemiluminescence (ECL) performance. Therefore, they were used as bright ECL signaling markers through conjugation with a monoclonal antibody against okadaic acid (anti-OA-MAb). Moreover, as an effective matrix for OA immobilization, the carboxylated multiwall carbon nanotubes-poly(diallyldimethylammonium) chloride-Au nanocluster (CMCNT-PDDA-AuNCs) composite promoted electron transfer and enlarged the surface area. Owing to the multiple amplifications, a competitive indirect ECL immunosensor for highly sensitive quantitation of OA has been developed. Under the optimized conditions, the 50% inhibitory concentration (IC 50 ) of the immunosensor was 0.25 ng mL −1 , and its linear range was 0.01–20 ng mL −1 with a low detection limit of 0.005 ng mL −1 . Finally, the proposed ECL sensor was successfully utilized to detect OA contents in mussel samples. Therefore, this study provides new insights into the designation of ECL luminophores and expands application of co-doped GQDs in fabrication of ECL immunosensors for shellfish toxin determination

Design and experiments with a SLAM system for low-density canopy environments in greenhouses based on an improved Cartographer framework

To address the problem that the low-density canopy of greenhouse crops affects the robustness and accuracy of simultaneous localization and mapping (SLAM) algorithms, a greenhouse map construction method for agricultural robots based on multiline LiDAR was investigated. Based on the Cartographer framework, this paper proposes a map construction and localization method based on spatial downsampling. Taking suspended tomato plants planted in greenhouses as the research object, an adaptive filtering point cloud projection (AF-PCP) SLAM algorithm was designed. Using a wheel odometer, 16-line LiDAR point cloud data based on adaptive vertical projections were linearly interpolated to construct a map and perform high-precision pose estimation in a greenhouse with a low-density canopy environment. Experiments were carried out in canopy environments with leaf area densities (LADs) of 2.945–5.301 m2/m3. The results showed that the AF-PCP SLAM algorithm increased the average mapping area of the crop rows by 155.7% compared with that of the Cartographer algorithm. The mean error and coefficient of variation of the crop row length were 0.019 m and 0.217%, respectively, which were 77.9% and 87.5% lower than those of the Cartographer algorithm. The average maximum void length was 0.124 m, which was 72.8% lower than that of the Cartographer algorithm. The localization experiments were carried out at speeds of 0.2 m/s, 0.4 m/s, and 0.6 m/s. The average relative localization errors at these speeds were respectively 0.026 m, 0.029 m, and 0.046 m, and the standard deviation was less than 0.06 m. Compared with that of the track deduction algorithm, the average localization error was reduced by 79.9% with the proposed algorithm. The results show that our proposed framework can map and localize robots with precision even in low-density canopy environments in greenhouses, demonstrating the satisfactory capability of the proposed approach and highlighting its promising applications in the autonomous navigation of agricultural robots

High preoperative white blood cell count determines poor prognosis and is associated with an immunosuppressive microenvironment in colorectal cancer

BackgroundThe correlation between high white blood cell (WBC) count and poor prognosis has been identified in various types of cancer; however, the clinical significance and immune context of WBC count in colorectal cancer remains unclear.MethodsBetween February 2009 and November 2014, 7,433 patients at the Shanghai Cancer Center who had undergone elective surgery for colorectal cancer were enrolled in this retrospective cohort study. Patients were divided into two groups: low and high preoperative WBC groups. Propensity score matching was used to address the differences in baseline characteristics. The Kaplan–Meier method and Cox regression analysis were used to identify independent prognostic factors in colorectal cancer patients. Tumor-infiltrating immune cells in the high and low preoperative WBC groups were compared using immunohistochemical staining.ResultsOf the 7,433 patients who underwent colorectal cancer surgery and were available for analysis, 5,750 were included in the low preoperative WBC group, and 1,683 were included in the high preoperative WBC group. After propensity score matching, 1,553 patients were included in each group. Kaplan–Meier survival curves showed that a high preoperative WBC count was associated with a decreased overall survival (P = 0.002) and disease-free survival (P = 0.003), and that preoperative WBC count was an independent risk factor for overall survival (hazard ratio, 1.234; 95% confidence interval, 1.068–1.426; P = 0.004) and disease-free survival (hazard ratio, 1.210; 95% confidence interval, 1.047–1.397, P = 0.01). Compared to the low preoperative WBC group, the high preoperative WBC group exhibited higher expression of regulatory T cells (P = 0.0034), CD68+ macrophages (P = 0.0071), and CD66b+ neutrophils (P = 0.0041); increased expression of programmed cell death protein 1 (P = 0.005) and programmed cell death ligand 1 (P = 0.0019); and lower expression of CD8+ T cells (P = 0.0057) in colorectal cancer patients.ConclusionsOur research indicates that a high preoperative WBC count is a prognostic indicator in colorectal cancer patients and is associated with an immunosuppressive tumor microenvironment, which could aid in future risk stratification

Creación y Simulación de Metodologías de Análisis, Clasificación e Integración de Nuevos Requerimientos a Software Propietario

La priorización de nuevos requerimientos a implementar en un software propietario es un punto fundamental para su mantenimiento, la conservación de la calidad, observación de las reglas de negocio y los estándares de la empresa. Aunque existen herramientas de priorización basadas en técnicas probadas y reconocidas, las mismas requieren una calificación previa de cada requerimiento. Si la empresa cuenta con solicitudes provenientes de varios clientes de un mismo producto, aumentan los factores que afectan a la empresa, las herramientas disponibles no contemplan estos aspectos y hacen mucho más compleja la tarea de calificación. Este trabajo de investigación abarca la realización de un relevamiento de los métodos de priorización y selección de nuevos requerimientos utilizados por empresas de la zona de Rosario, y la definición de una metodología para la selección un nuevo requerimiento, que implica el análisis y evaluación de todas las implicaciones sobre el producto de software y la empresa, respetando sus reglas de negocio. La metodología creada conduce a la definición de los procesos para la construcción de una herramienta de calificación y priorización de nuevos requerimientos en software propietario que tiene solicitudes de varios clientes al mismo tiempo, con instrumentos de calificación que consideran todos los aspectos relacionados, proveerá técnicas de priorización actuales y emitirá informes personalizados según diferentes perspectivas de la empresa.Eje: Ingeniería de SoftwareRed de Universidades con Carreras en Informática (RedUNCI