Analysis of the V.A.R. as a tool to investigate the impact of higher education on economic growth in Macau in the period 2000–2019

This article employs the panel data model to investigate the influence of both higher education scale and quality on economic growth in Macau from 2000–2019 and constructs a V.A.R. model to examine the impact of the higher education scale on economic growth. The model is constructed based on the Cobb–Douglas production function with an alteration derived from existing relevant studies to include enrolled university students as one of the variables. It is found that all-time series are stationary; through the pairwise Granger Causality test, it is observed that the number of students enrolled in the Granger cause of G.D.P. Study results show a high level of a statistically significant relationship in the positive direction between higher education and economic growth, while a 1% increase in enrolled students will lead to a 0.5547% increase in G.D.P. Moreover, in general, higher education exerts a significant positive effect on economic growth in Macau, while the effect of fixed capital formation appears insignificant. In addition, the labour force plays a remarkably positive role in the economic growth of Macau

Geoscience-aware deep learning:A new paradigm for remote sensing

Information extraction is a key activity for remote sensing images. A common distinction exists between knowledge-driven and data-driven methods. Knowledge-driven methods have advanced reasoning ability and interpretability, but have difficulty in handling complicated tasks since prior knowledge is usually limited when facing the highly complex spatial patterns and geoscience phenomena found in reality. Data-driven models, especially those emerging in machine learning (ML) and deep learning (DL), have achieved substantial progress in geoscience and remote sensing applications. Although DL models have powerful feature learning and representation capabilities, traditional DL has inherent problems including working as a black box and generally requiring a large number of labeled training data. The focus of this paper is on methods that integrate domain knowledge, such as geoscience knowledge and geoscience features (GK/GFs), into the design of DL models. The paper introduces the new paradigm of geoscience-aware deep learning (GADL), in which GK/GFs and DL models are combined deeply to extract information from remote sensing data. It first provides a comprehensive summary of GK/GFs used in GADL, which forms the basis for subsequent integration of GK/GFs with DL models. This is followed by a taxonomy of approaches for integrating GK/GFs with DL models. Several approaches are detailed using illustrative examples. Challenges and research prospects in GADL are then discussed. Developing more novel and advanced methods in GADL is expected to become the prevailing trend in advancing remotely sensed information extraction in the future.</p

A case study on the impacts of future climate change on soybean yield and countermeasures in Fujin city of Heilongjiang province, China

Global climate change poses a great impact on crop growth, development and yield. Soybean production in Northeast China, which is one of the traditional dominant soybean production areas in China, is of great significance for developing the domestic soybean industry and reducing dependence on imported soybeans. Therefore, it is crucial to evaluate the impacts of future climate change on soybean yield in Northeast China, and to propose reasonable adaptation measures. In this study, we took Fujin city of Heilongjiang province in Northeast China as an example, and used the CROPGRO-soybean model in DSSAT (Decision Support System for Agrotechnology Transfer) to simulate the impacts of future climate change on soybean yield in the four periods of the 2020s (2021-2030), 2030s (2031-2040), 2040s (2041-2050) and 2050s (2051-2060) under two representative concentration pathway (RCP) scenarios (RCP4.5 and RCP8.5), and further determine the best agronomic management practices. The results showed that the calibrated and validated model is suitable for simulating soybean in the study area. By analyzing the meteorological data under future climate scenarios RCP4.5 and RCP8.5 from the PRECIS regional climate model, we found that the average temperature, cumulative precipitation and cumulative solar radiation would mostly increase during the growing season in Fujin city of Heilongjiang province. Combined with the model simulation results, it is shown that under the effect of CO2 fertilization, future climate change will have a positive impact on soybean yield. Compared to the baseline (1986-2005), the soybean yield would increase by 0.6% (7.4%), 3.3% (5.1%), 6.0% (16.8%) and 12.3% (20.6%) in the 2020s, 2030s, 2040s and 2050s under RCP4.5 (RCP8.5).Moreover, the optimal sowing dates and the optimal supplemental irrigation amount under RCP4.5 (RCP8.5) are May 10 (May 5) and 50 mm (40mm), respectively. Under future climate conditions, the agronomic management practices, such as advancing the sowing date and supplementary irrigation in the key stage of soybean growth would increase soybean yield and make soybean growth more adaptable to future climate change

Left versus right approach for middle and lower esophageal squamous cell carcinoma: A propensity score-matched study

BackgroundDespite superior short-term outcomes, there is considerable debate about the oncological efficacy of the left approach esophagectomy for middle and lower squamous esophageal carcinoma (ESCC). A propensity score-matched retrospective study was conducted to evaluate the left approach’s short- and long-term effects.MethodsWe recorded data from patients with ESCC who underwent curative resection via the left or right approach between January 2010 and December 2015. Propensity score matching (PSM) was performed, and maximally selected rank statistics (MSRS) were utilized to determine the appropriate number of lymph nodes to resect during esophagectomy.ResultsOne hundred and forty-eight ESCC patients underwent esophagectomy via the right approach, and 108 underwent the left approach esophagectomy. After PSM, the left approach esophagectomy showed statistically significant superiority in operative time and time to oral intake, and there was a trend toward a shorter length of hospital stay. Fewer cervical, upper thoracic, and recurrent laryngeal nerve lymph nodes were harvested via the left approach than the right approach; the total number of lymph nodes harvested via the left and right approaches was similar. Similar long-term survival outcomes were achieved. MSRS suggested that at least 25 lymph nodes are needed to be resected during esophagectomy to improve survival in N0 patients.ConclusionsThe left approach esophagectomy might facilitate postoperative recovery in patients with middle and lower ESCC. With adequate lymphadenectomy, the left approach esophagectomy might achieve similar long-term outcomes for middle and lower ESCC patients