考虑非期望产出的中国海水养殖业全要素生产率研究——基于Global Malmquist-Luenberger指数

本文运用Global Malmquist-Luenberger指数方法,将海水养殖过程中的非期望产出纳入评价体系,在环境约束下对我国海水养殖业的全要素生产率进行综合评价。选取我国沿海9省份2003-2014年的数据为研究对象进行分析,发现样本期内我国海水养殖业全要素生产率自2008年起稳步提升;环渤海经济圈涨幅最大,南海经济圈的增长则略显微弱;山东省全要素生产率的增速最快,广东省生产率的提升最为缓慢,整体发展不平衡;生产率的提高主要来源于技术的进步,相对技术效率的提升作用未显现。海水养殖业的进一步发展需要在继续提高技术的同时注重效率的改进。

“丝绸之路经济带”绿色全要素能源效率的地区差异及影响因素研究——基于Global Malmquist-Luenberger指数的实证分析

在推进"一带一路"建设背景下,探讨"丝绸之路经济带"沿线国家与地区能源效率的差异,对经济带能源合作和可持续发展具有重要意义。运用方向性距离函数和Global Malmquist-Luenberger指数方法,测算了碳排放约束下"丝绸之路经济带"核心区、重要区及辐射区全要素能源效率的变化,并运用Tobit模型对其影响因素进行实证分析。结果表明:在2000-2014年期间,"丝绸之路经济带"绿色全要素能源效率整体呈现上升趋势,但核心区、重要区及辐射区之间存在显著差异,核心区和重要区能源效率变化特征相似,技术效率和技术进步共同推动效率增长;技术进步是辐射区能源效率增长的主要来源。人均GDP和产业结构对能源效率增长具有正向影响,但能源结构对能源效率增长有显著的负向作用。

环境约束下的中国耕地利用效率及影响因——基于Global Malmquist-Luenberger指数方法

利用GML指数方法和面板数据回归模型,兼顾面源污染和碳排放,测度并分析2009~2015年中国耕地利用效率的时空分异特征及影响因素,明确不同区域的耕地利用效率提升途径。结果表明,在考虑非期望产出情况下,我国耕地利用效率大致呈逐年上升趋势。四大区域耕地利用效率均不同程度增长,其中东北地区耕地利用效率波动幅度较大;从各区域耕地利用效率的动力源看,技术进步是四大区域耕地利用效率增长的主要动力,纯技术效率与规模效率成为制约四大区域耕地利用效率增长的瓶颈;各影响因素对各区域耕地利用效率影响存在差异。耕地资源禀赋对东部、中部、东北地区耕地利用效率影响显著,西部地区则易受自然条件影响。

环境与资源约束下城市全要素生产率的测算与分解——基于方向性距离函数和Global Malmquist-Luenberger指数

为了在资源与环境约束下研究城市全要素生产率的结构与变化规律,对285个中国城市在2003—2014年间的绿色全要素生产率变化程度进行了测算、分解,其结果表明绿色全要素生产率以年均2.12%的速度增长,其中技术进步和技术效率提升的平均速度分别为1.74%与0.37%。绿色全要素生产率在累积增长率上小于传统全要素生产率,表明中国城市发展过程中的环境与资源代价过高;但也有部分城市能够实现经济增长与环境规制之间的有效协调。城市绿色全要素生产率的累积增长率存在中部>东部>西部的区域差异,技术进步在东部地区绿色全要素生产率增长过程中的贡献最高,而中、西部则相对较多地依赖技术效率改善。

How far has the globe gone in achieving One Health?Current evidence and policy implications based on global One Health index

Background:In the 21st century,as globalization accelerates and global public health crises occur,the One Health approach,guided by the holistic thinking of human-animal-environment and emphasizing interdisciplinary collaboration to address global health issues,has been strongly advocated by the international community.An immediate requirement exists for the creation of an assessment tool to foster One Health initiatives on both global and national scales.Methods:Built upon extensive expert consultations and dialogues,this follow-up study enhances the 2022 global One Health index(GOHI)indicator system.The GOHI framework is enriched by covering three indices,e.g.external drivers index(EDI),intrinsic drivers index(IDI),and core drivers index(CDI).The comprehensive indicator system incorporates 13 key indicators,50 indicators,and 170 sub I-indicators,utilizing a fuzzy analytic hierarchy process to ascertain the weight for each indicator.Weighted and summed,the EDI,IDI,and CDI scores contribute to the computation of the overall GOHI 2022 score.By comparing the ranking and the overall scores among the seven regions and across 160 countries/territories,we have not only derived an overall profile of the GOHI 2022 scores,but also assessed the GOHI framework.We also compared rankings of indicators and sub Iindicators to provide greater clarity on the strengths and weaknesses of each region within the One Health domains.Results:The GOHI 2022 performance reveals significant disparities between countries/territories ranged from 39.03 to 70.61.The global average score of the GOHI 2022 is 54.82.The average score for EDI,IDI,and CDI are 46.57,58.01,and 57.25,respectively.In terms of global rankings,countries from North America,Europe and Central Asia,East Asia and Pacific present higher scores.In terms of One Health domains of CDI,the lowest scores are observed in antimicrobial resistance(median:43.09),followed by food security(median:53.78),governance(median:54.77),climate change(median:64.12)and zoonotic diseases(median:69.23).Globally,the scores of GOHI vary spatially,with the highest score in North America while lowest in sub-Saharan Africa.In addition,evidence shows associations between the socio-demographic profile of countries/territories and their GOHI performance in certain One Health scenarios.Conclusion:The objective of GOHI is to guide impactful strategies for enhancing capacity building in One Health.With advanced technology and an annually updated database,intensifying efforts to refine GOHI's data-mining methodologies become imperative.The goal is to offer profound insights into disparities and progressions in practical One Health implementation,particularly in anticipation of future pandemics.

广东省绿色发展绩效的动态变化与空间分异研究——基于碳排放视角下的Global Malmquist-Luenberger指数测算

为评价广东省绿色发展绩效、掌握其变化规律与空间分异特征,本文以包含碳排放等负面产出的范围方向性距离函数(RDM)、Global Malmquist-Luenberger指数为基础,动态测算了广东省21个城市的绿色发展绩效。测算结果表明,广东省绿色发展绩效在2003—2017年间实现了比率约74.0%的总体增长;2012年后绩效进步速度明显加快,并且进步动力更多来自技术进步。珠三角地区城市绿色发展绩效进步幅度远远领先于省内其他地区,粤东地区城市绿色发展绩效则出现了显著的退步,使广东省绿色发展呈现出明显的"核心-边缘"格局。此外,碳排放在绿色发展中扮演着重要角色,忽视碳排放因素会导致广东省绿色发展绩效被显著低估。

中国废弃资源综合利用业全要素生产率分析——基于Global Malmquist-Luenberger指数的应用

文章利用全要素生产率增长分析中国废弃资源综合利用业的发展质量,具体选用Global Malmquist-Luenberger指数,考虑了该产业也产出“三废”的现实情况,将其作为非期望产出纳入废弃资源综合利用业的投入产出指标中进行综合评价。选取了我国19个省份的规模以上相关企业的投入产出指标数据进行了分析,结果表明:以2015年为分界线,废弃资源综合利用业全要素生产率累积增长以趋缓的表现下降到2015的第一个低谷之后回升,在2018年进入第二个谷底,后期快速拉升;在区域分析中,区域指标作用差异性明显,东北地区、黄河中游地区表现突出,作为循环经济发展应有内容,废弃资源综合利用业全要素率增长,单一改进力量的强势不利于统筹绿色发展,因协调技术进步、技术效率、规模报酬因子之间的关系,发挥地区间的有机互补作用,协同发展。

A New Monsoon Index and the Geographical Distribution of the Global Monsoons

A new monsoon index, the dynamical normalized seasonality (DNS), is introduced to study the issue of monsoons. This DNS index can describe both seasonal variation and interannual variability of different monsoon regions. It can also be used to delimit the geographical distribution of the global monsoon systems. Furthermore, it is pointed out that the index is very useful for understanding deeply the monsoons to study the difference, relationship, and interactions among the classical monsoon, ordinary monsoon and monsoon-like system.

Validation of nutritional risk index method against patientgenerated subjective global assessment in screening malnutrition in colorectal cancer patients

Objective：To validate malnutrition screening tool of nutrition risk index （NRI） against patent-generated subjective global assessment （PG-SGA） as a gold standard tool in colorectal cancer patients before radiotherapy.Methods：Nutritional status of 52 volunteer colorectal cancer patients with a mean age of 54.1±16.8 years who referred to radiotherapy center were assessed by PG-SGA （gold standard method） and NRI.Serum albumin levels of patients were determined by colorimetric method.A contingency table was used to determine the sensitivity,specificity,and predictive value of the NRI in screening patients at risk of malnutrition,in comparison with the PG-SGA in patients before radiotherapy.Results：The findings of PG-SGA and NRI showed that 52％ and 45％ of patients in our study were moderately or severely malnourished respectively.The NRI had a sensitivity of 66％ and a specificity of 60％ against PG-SGA.The positive predictive value was 64％ and the negative predicative value was 62％.The agreement between NRI and PG-SGA was statistically insignificant （kappa =0.267; P＞0.05）.Conclusions：The findings of present study showed that the prevalence of malnutrition was high in patients with colorectal cancer.Moreover,NRI method had low sensitivity and specificity in assessing nutritional status of patients with cancer.It seems that the combination of anthropometric,laboratory parameters and a subjective scoring system may be helpful tools in screening of malnutrition in cancer patients.

基于Global Stability Index(GSI)理论的水煮笋软罐头货架期预测

应用食品货架期预测新方法—Global Stability Index(GSI)进行水煮笋软罐头基于综合品质指标的保质期预测。基于恒温加速实验测定分析产品于23、33、43℃储藏温度下的品质变化规律,以色泽、可溶性蛋白质和维生素C作为水煮笋的关键质量指标,应用GSI理论描述产品基于多指标的综合劣变过程,获得不同温度下GSI值的变化趋势。结果表明,水煮笋软罐头GSI值的下降符合零级反应动力学。使用阿伦尼乌斯方程建立GSI货架期预测模型,并表征模型参数,计算出20℃下产品的保质期约为186d。经过理论预测与实验对比,得到的GSI值相对误差在22%以下,证明了该货架期预测方法的可靠性。

Estimation of Global Solar Radiation Using Clearness Index and Cloud Transmittance Factor at Trans-Himalayan Region in Nepal

This paper presents the global solar radiation (GSR) and cloud transmittance factor (cf) measured at the horizontal surface over a period of one year from 2009 to 2010 using CMP6 Pyranometer and NILUUV Irradiance Meter at Lukla (Latitude 26.69oN,Longitude 86.73?E and Altitude 2850 m) in the foothills of the Mt Everest (8850 m high). Monthly and seasonal variations of global solar radiation as well as correlation between clearness index and cloud transmittance factor at Lukla are presented. The annual average daily global solar radiation is about 3.83 kWh/sq·m/day which is sufficient to promote solar active and passive energy technology at high mountain terrain where there is no other viable alternative sources of energy. The maximum and minimum global solar radiation of 5.33 and 2.08 kWh/sq·m/day is recorded in April and September 2010 respectively. The seasonal variation of solar energy is about 2.87 kWh/sq·m/day and 4.83 kWh/sq·m/day in summer and spring respectively which is not in line with the general trend. The coefficient of determination (R2) between cloud transmittance factor (cf) and clearness factor (K) is found to be 0.97. This novel result can be utilized to estimate the global solar radiation at the horizontal surface where K and cf are available.

Global instability index as a crystallographic stability descriptor of halide and chalcogenide perovskites

Crystallographic stability is an important factor that affects the stability of perovskites.The stability dictates the commercial applications of lead-based organometal halide perovskites.The tolerance factor(t)and octahedral factor(μ)form the state-of-the-art criteria used to evaluate the perovskite crystallographic stability.We studied the crystallographic stabilities of halide and chalcogenide perovskites by exploring an effective alternative descriptor,the global instability index(GII)that was used as an indicator of the stability of perovskite oxides.We particularly focused on determining crystallographic reliability by calculating GII.We analyzed the bond valence models of the 243 halide and chalcogenide perovskites that occupied the lowest-energy cubic-phase structures determined by conducting the first-principles-based total energy minimization calculations.The decomposition energy(ΔHD)reflects the thermodynamic stability of the system and is considered as the benchmark that helps assess the effectiveness of GII in evaluating the crystallographic stability of the systems under study.The results indicated that the accuracy of predicting thermodynamic stability was significantly higher when GII(73.6%)was analyzed compared to the cases when t(55%)andμ(39.1%)were analyzed to determine the stability.The results obtained from the machine learning-based data mining method further indicate that GII is an important descriptor of the stability of the perovskite family.

Update of the Chronology of Natural Signals in the Near-Surface Mean Global Temperature Record and the Southern Oscillation Index

Time series for the Southern Oscillation Index and mean global near surface temperature anomalies are compared for the 1950 to 2012 period using recently released HadCRU4 data. The method avoids a focused statistical analysis of the data, in part because the study deals with smoothed data, which means there is the danger of spurious correlations, and in part because the El Ni?o Southern Oscillation is a cyclical phenomenon of irregular period. In these situations the results of regression analysis or similar statistical evaluation can be misleading. With the potential controversy arising over a particular statistical analysis removed, the findings indicate that El Nino-Southern Oscillation exercises a major influence on mean global temperature. The results show the potential of natural forcing mechanisms to account for mean global temperature variation, although the extent of the influence is difficult to quantify from among the variability of short-term influences.

The Values of the Prognostic Nutrition Index and the Patient Generated-Subjective Global Assessment during the Nutritional Assessment of Patients with Gastrointestinal Tumors

Objective To compare the value and consistency among the Patient Generated-Subjective Global Assessment(PG-SGA)and the Prognostic Nutrition Index(PNI)for assessing nutritional status in gastrointestinal tumor patients.Methods 251 patients from gastric cancer surgical ward from January 2019 to January 2020 were recruited through convenience sampling in this respective study.Nutritional screening and assessment were conducted for 251 gastrointestinal tumor patients using the nutritional risk screening 2002(NRS 2002)PG-SGA,and the PNI.PNI was calculated using the serum albumin level and the total lymphocyte count obtained from the patients’routine laboratory examination when they were admitted to the hospital.The receiver operating characteristic(ROC)of the PG SGA and the PNI were plotted with the NRS 2002 used as the gold standard,and the diagnostic value of the PG-SGA and PNI was reflected by the area under the curve(AUC),sensitivity,specificity and Youden index.We then determined the optimal cut-off for the PNI and tested the consistency of the PG-SGA and PNI.Results The optimal cut-off point for the PNI was calculated to be 50.78.The AUC of the PG-SGA was 0.908(95%CI 0.871-0.944).The sensitivity was 89.9%,specificity was 76.2%and the Youden index was 0.661.The AUC of the PNI was 0.594(95%CI 0.516-0.572).The sensitivity was 73.8%,specificity was 44.3%and the Youden index was 0.181.In the consistency test,the kappa value was 0.838(P<0.001).Conclusion The PNI is of limited value for assessing malnutrition,although it did have good consistency with the PG-SGA.The combination of the PNI and PG-SGA can be used for diagnosing assessing malnutrition in clinical practice.

Global Stability Index方法在大骨鸡保质期预测中的应用

目的:建立了基于全面稳定性指数(global stability index,GSI)理论预测庄河大骨鸡保质期的新方法。方法:基于恒温加速实验,测定大骨鸡于4、10、20、30℃储藏温度下的感官、汁液流失率、菌落总数和挥发性盐基氮变化规律,建立大骨鸡GSI保质期预测模型。结果:计算得到的GSI值满足零级动力学模型。活化能和指前因子分别为25.52 kJ/mol和11027。GSI实验值和预测值相对误差绝对值在10%范围内。通过GSI模型预测,获得大骨鸡在4、10、20、30℃下的保质期分别为5.9、4.7、3.2、2.3 d。结论:建立的GSI预测模型在4~30℃储藏温度范围内能够有效预测大骨鸡的新鲜度。

Production Chain Length and PPI-CPI Divergence:Analysis Based on the Global Input-output Price Model

Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.

Decomposition and decoupling effect of energy eco-footprint based on global net primary productivity in urban agglomerations

Net primary productivity(NPP)is an important breakthrough point of current research on ecological footprint improvement.The energy eco-footprint(EEF)of the Four-City Area in Central China(FCACC)was measured by constructing an EEF-NPP model.This work has made the following efforts:(1)Gini coefficient was employed to analyze the degree of matching between the EEF and economic growth,population,and energy consumption.(2)LMDI decomposition method was used to explore the impacts of multiple factors on the EEF in the FCACC.(3)Tapio decoupling model was applied to verify the decoupling relationships between the above influencing factors and the EEF.(4)LMDI decomposition formula was embedded into the decoupling model to analyze the impacts of technical and non-technical factors on the decoupling elasticity of the above.The main findings show that from 2010 to 2020:(1)the degree of matching of EEF-GDP,EEF-population,and EEF-energy consumption increased.(2)energy intensity and per capita GDP were the main factors that affected the EEF.(3)the decoupling states between total energy consumption,energy consumption structure,energy intensity,per capita GDP,and population size with the EEF were expansive negative decoupling,expansive negative decoupling,strong negative decoupling,weak decoupling,and expansive negative decoupling,respectively.(4)the impact of non-technical factors was greater than that of technical factors,and their impacts were always in opposite directions.

天山北坡经济带农业生态效率评价及提升路径研究——基于Super–SBM模型和Global–Malmquist指数

生态效率是权衡经济、资源和环境三者关系的科学评判手段,可定量分析研究区域的农业生态发展水平,为区域农业生态化协同发展提供借鉴之处。以天山北坡经济带为研究区域,采用Super–SBM模型和σ指数测度农业生态效率静态水平和区域差异的敛散性,并运用Global–Malmquist指数研究农业生态效率的动态变化,最后依据无效率分解模型厘清效率损失的原因并提出效率改进的路径。研究结果表明:农业生态效率整体水平不高,区域差异特征明显且呈现扩大趋势;指数分析表明,技术进步是最重要的提升动力,纯技术效率和规模效率在一定程度上抑制了农业生态效率的提升;效率损失的原因在于过量的资源要素投入和污染物排放,其中,地膜、水资源和化肥投入要素冗余程度最高。根据研究结果,提出了相应的对策与建议。

中国粮食主产区农业能源效率变动研究——基于超效率EBM和Global-Malmquist指数模型

基于我国粮食主产区历年13个省份农业生产的面板数据,运用含非期望产出的超效率EBM模型和GlobalMalmquist指数模型测算各省份农业全要素能源效率和能源全要素生产率。结果表明:①我国粮食主产区农业能源使用量逐年上升,各省份农业能源效率存在波动,且易受外部环境影响。②农业能源效率提升与能源全要素生产率紧密相关,技术进步和技术效率是影响农业能源全要素生产率的重要因素。基于上述实证结果,粮食主产区的农业能源效率仍存在改善空间,为推进现代农业进一步发展,应合理安排农业生产布局,推广节能技术,并全面激活资本、科技创新等要素。

Variations and trends of the freezing and thaw- ing index along the Qinghai-Xizang Railway for 1966-2004

Annual freezing and thawing index of 7 meteorological stations along the Qing- hai-Xizang Railway were calculated based on daily maximum and minimum temperature records for 1966-2004. Trends of annual freezing and thawing index were analyzed using the Mann-Kendall test and a simple linear regression method. The results show that： 1） The mean annual freezing indices range from 95 to 2300℃·d and the mean annual thawing indices range from 630 to 3250℃·d. The mean annual freezing index of the 7 stations exhibited decreasing trends with decreasing rate of -16.6- -59.1 ℃·d/10a. The mean annual thawing index of these 7 stations showed increasing trends with the related decreasing rate is 19.83-45.6℃·d/10a. 2） The MK trend test indicated the significant decreasing trends （significant at 〈 0.05 significant level） in the annual freezing index for most stations except for Golmud. The significant increasing trends can be observed in the annual thawing index for 4 stations except Golmud and Tuotuohe. Golmud was the only station with no trends in both annual freezing and annual thawing index.