Crude oil and agricultural futures: An analysis of correlation dynamics

Correlations between oil and agricultural commodities have varied over previous decades, impacted by renewable fuels policy and turbulent economic conditions. We estimate smooth transition conditional correlation models for 12 agricultural commodities and WTI crude oil. While a structural change in correlations occurred concurrently with the introduction of biofuel policy, oil and food price levels are also key influences. High correlation between biofuel feedstocks and oil is more likely to occur when food and oil price levels are high. Correlation with oil returns is strong for biofuel feedstocks, unlike with other agricultural futures, suggesting limited contagion from energy to food markets.

Concise review: Humanized models of tumor immunology in the 21st century: Convergence of cancer research and tissue engineering

Despite positive testing in animal studies, more than 80% of novel drug candidates fail to proof their efficacy when tested in humans. This is primarily due to the use of preclinical models that are not able to recapitulate the physiological or pathological processes in humans. Hence, one of the key challenges in the field of translational medicine is to “make the model organism mouse more human.” To get answers to questions that would be prognostic of outcomes in human medicine, the mouse's genome can be altered in order to create a more permissive host that allows the engraftment of human cell systems. It has been shown in the past that these strategies can improve our understanding of tumor immunology. However, the translational benefits of these platforms have still to be proven. In the 21st century, several research groups and consortia around the world take up the challenge to improve our understanding of how to humanize the animal's genetic code, its cells and, based on tissue engineering principles, its extracellular microenvironment, its tissues, or entire organs with the ultimate goal to foster the translation of new therapeutic strategies from bench to bedside. This article provides an overview of the state of the art of humanized models of tumor immunology and highlights future developments in the field such as the application of tissue engineering and regenerative medicine strategies to further enhance humanized murine model systems.

Microfinance, Efficiency and Agricultural Production in Bangladesh

The objectives of this study were to make a detailed and systematic empirical analysis of microfinance borrowers and non-borrowers in Bangladesh and also examine how efficiency measures are influenced by the access to agricultural microfinance. In the empirical analysis, this study used both parametric and non-parametric frontier approaches to investigate differences in efficiency estimates between microfinance borrowers and non-borrowers. This thesis, based on five articles, applied data obtained from a survey of 360 farm households from north-central and north-western regions in Bangladesh. The methods used in this investigation involve stochastic frontier (SFA) and data envelopment analysis (DEA) in addition to sample selectivity and limited dependent variable models. In article I, technical efficiency (TE) estimation and identification of its determinants were performed by applying an extended Cobb-Douglas stochastic frontier production function. The results show that farm households had a mean TE of 83% with lower TE scores for the non-borrowers of agricultural microfinance. Addressing institutional policies regarding the consolidation of individual plots into farm units, ensuring access to microfinance, extension education for the farmers with longer farming experience are suggested to improve the TE of the farmers. In article II, the objective was to assess the effects of access to microfinance on household production and cost efficiency (CE) and to determine the efficiency differences between the microfinance participating and non-participating farms. In addition, a non-discretionary DEA model was applied to capture directly the influence of microfinance on farm households production and CE. The results suggested that under both pooled DEA models and non-discretionary DEA models, farmers with access to microfinance were significantly more efficient than their non-borrowing counterparts. Results also revealed that land fragmentation, family size, household wealth, on farm-training and off farm income share are the main determinants of inefficiency after effectively correcting for sample selection bias. In article III, the TE of traditional variety (TV) and high-yielding-variety (HYV) rice producers were estimated in addition to investigating the determinants of adoption rate of HYV rice. Furthermore, the role of TE as a potential determinant to explain the differences of adoption rate of HYV rice among the farmers was assessed. The results indicated that in spite of its much higher yield potential, HYV rice production was associated with lower TE and had a greater variability in yield. It was also found that TE had a significant positive influence on the adoption rates of HYV rice. In article IV, we estimated profit efficiency (PE) and profit-loss between microfinance borrowers and non-borrowers by a sample selection framework, which provided a general framework for testing and taking into account the sample selection in the stochastic (profit) frontier function analysis. After effectively correcting for selectivity bias, the mean PE of the microfinance borrowers and non-borrowers were estimated at 68% and 52% respectively. This suggested that a considerable share of profits were lost due to profit inefficiencies in rice production. The results also demonstrated that access to microfinance contributes significantly to increasing PE and reducing profit-loss per hectare land. In article V, the effects of credit constraints on TE, allocative efficiency (AE) and CE were assessed while adequately controlling for sample selection bias. The confidence intervals were determined by the bootstrap method for both samples. The results indicated that differences in average efficiency scores of credit constrained and unconstrained farms were not statistically significant although the average efficiencies tended to be higher in the group of unconstrained farms. After effectively correcting for selectivity bias, household experience, number of dependents, off-farm income, farm size, access to on farm training and yearly savings were found to be the main determinants of inefficiencies. In general, the results of the study revealed the existence substantial technical, allocative, economic inefficiencies and also considerable profit inefficiencies. The results of the study suggested the need to streamline agricultural microfinance by the microfinance institutions (MFIs), donor agencies and government at all tiers. Moreover, formulating policies that ensure greater access to agricultural microfinance to the smallholder farmers on a sustainable basis in the study areas to enhance productivity and efficiency has been recommended. Key Words: Technical, allocative, economic efficiency, DEA, Non-discretionary DEA, selection bias, bootstrapping, microfinance, Bangladesh.

Civil and Environmental Engineering Challenges for Data Sensing and Analysis

The objective of this study was to identify challenges in civil and environmental engineering that can potentially be solved using data sensing and analysis research. The challenges were recognized through extensive literature review in all disciplines of civil and environmental engineering. The literature review included journal articles, reports, expert interviews, and magazine articles. The challenges were ranked by comparing their impact on cost, time, quality, environment and safety. The result of this literature review includes challenges such as improving construction safety and productivity, improving roof safety, reducing building energy consumption, solving traffic congestion, managing groundwater, mapping and monitoring the underground, estimating sea conditions, and solving soil erosion problems. These challenges suggest areas where researchers can apply data sensing and analysis research.

basic research in computer science and software engineering at sklcs

The State Key Laboratory of Computer Science (SKLCS) is committed to basic research in computer science and software engineering. The research topics of the laboratory include: concurrency theory, theory and algorithms for real-time systems, formal specifications based on context-free grammars, semantics of programming languages, model checking, automated reasoning, logic programming, software testing, software process improvement, middleware technology, parallel algorithms and parallel software, computer graphics and human-computer interaction. This paper describes these topics in some detail and summarizes some results obtained in recent years.

Kinetic study of hydrolysis of xylan and agricultural wastes with hot liquid water

We investigated the kinetics of hot liquid water (HLW) hydrolysis over a 60-min period using a self-designed setup. The reaction was performed within the range 160-220 °C, under reaction conditions of 4.0 MPa, a 1:20 solid:liquid ratio (g/mL), at 500 rpm stirring speed. Xylan was chosen as a model compound for hemicelluloses, and two kinds of agricultural wastes-rice straw and palm shell-were used as typical feedstocks representative of herbaceous and woody biomasses, respectively. The hydrolysis reactions for the three kinds of materials followed a first-order sequential kinetic model, and the hydrolysis activation energies were 65.58 kJ/mol for xylan, 68.76 kJ/mol for rice straw, and 95.19 kJ/mol for palm shell. The activation energies of sugar degradation were 147.21 kJ/mol for xylan, 47.08 kJ/mol for rice straw and 79.74 kJ/mol for palm shell. These differences may be due to differences in the composition and construction of the three kinds of materials. In order to reduce the decomposition of sugars, the hydrolysis time of biomasses such as rice straw and palm shell should be strictly controlled.