Techno-Economical Evaluation of Bio-Oil Production via Biomass Fast Pyrolysis Process: A Review

Biomass pyrolysis is one of the beneficial sources of the production of sustainable bio-oil. Currently, marketable bio-oil plants are scarce because of the complex operations and lower profits. Therefore, it is necessary to comprehend the relationship between technological parameters and economic practicality. This review outlines the technical and economical routine to produce bio-oils from various biomass by fast pyrolysis. Explicit pointers were compared, such as production cost, capacity, and biomass type for bio-oil production. The bio-oil production cost is crucial for evaluating the market compatibility with other biofuels available. Different pretreatments, upgrades and recycling processes influenced production costs. Using an energy integration strategy, it is possible to produce bio-oil from biomass pyrolysis. The findings of this study might lead to bio-oil industry-related research aimed at commercializing the product.

ANALYSIS OF BIM AND MCDM INTEGRATION IN DESIGN, MANUFACTURING AND CONSTRUCTION STAGES

The article analyses the possibilities of synergy between MCDM (Multi Criteria Decision Making) methods and BIM (Building Information Modeling) technologies in order to identify a better integration way and propose a strategy for integrating MCDM and BIM. The two ways of integration were identified after performing literature analysis – the linear one and integrated one. The stages of the integration strategy were discussed and a key strategy for improving the synergy between MCDM and BIM was found. The key strategy intended for masonry veneer and masonry structures in design, manufacture and construction stages to make a decision.

GLE-Net: A Global and Local Ensemble Network for Aerial Object Detection

Recent advances in camera-equipped drone applications increased the demand for visual object detection algorithms with deep learning for aerial images. There are several limitations in accuracy for a single deep learning model. Inspired by ensemble learning can significantly improve the generalization ability of the model in the machine learning field, we introduce a novel integration strategy to combine the inference results of two different methods without non-maximum suppression. In this paper, a global and local ensemble network (GLE-Net) was proposed to increase the quality of predictions by considering the global weights for different models and adjusting the local weights for bounding boxes. Specifically, the global module assigns different weights to models. In the local module, we group the bounding boxes that corresponding to the same object as a cluster. Each cluster generates a final predict box and assigns the highest score in the cluster as the score of the final predict box. Experiments on benchmarks VisDrone2019 show promising performance of GLE-Net compared with the baseline network.

Bagging Based Cross-Media Retrieval Algorithm

It is very challenging to propose a strong learning algorithm with high prediction accuracy of cross-media retrieval, while finding a weak learning algorithm which is slightly higher than that of random prediction is very easy. Inspired by this idea, we propose an imaginative Bagging based cross-media retrieval algorithm (called BCMR) in this paper. First, we utilize bootstrap sampling to carry out random sampling of the original training set. The amount of the sample abstracted by bootstrap is set to be same as the original dataset. Second, 50 bootstrap replicates are used for training 50 weak classifiers independently. We take advantage of homogenous individual classifiers and integrate eight different baseline methods in our experiments. Finally, we generate the final strong classifier from the 50 weak classifiers by the integration strategy of sample voting. We use collective wisdom to eliminate bad decisions so that the generalization ability of the integrated model could be greatly enhanced. Extensive experiments performed on three datasets show that BCMR can effectively improve the accuracy of cross-media retrieval.

Vertical Integration Strategy Implementation Through Hybrid Upstream and Downstream Concession Agreements

Upstream developments in prolific oil and gas fields are highly profitable and hence attract various investors/partners, whereas Downstream developments profitability is margin based and challenging under certain situations to receive similar interest for investment in the same location. Vertical Integration Strategy implementation through hybrid upstream and downstream concession agreements can help address this issue. The seventies witnessed major changes in the oil industry's structures and strategies resulting from the nationalization of oil and gas reserves. This ultimately led to a separation between the upstream sector with national oil companies (NOCs) controlling most of the world reserves and crude production, and the downstream sector with the international oil companies (IOCs) controlling the largest share of the refining and marketing aspects in the main consuming countries. In the recent past, NOCs have started forward integration of its upstream sector with downstream sector to take advantage of the synergies and increase profitability. This paper takes the strategy a step more forward by exploring the possibility of developing oil and gas assets through a hybrid upstream/downstream concession agreement that can be awarded by the host government. The model hybrid agreement is built by integrating a typical upstream concession agreement with downstream equity-based joint venture (JV) agreement. It also takes the learnings from Production Development Production Sharing Agreement (DPSA) applied in the development of a Gas-To-Liquids (GTL) asset or Liquefied Natural Gas (LNG) asset which are usually developed as an integrated upstream and downstream business model. It is also feasible to build the hybrid agreement based on upstream Production Sharing Agreement (PSA) instead of a Concession Agreement. The paper will discuss how the hybrid upstream and downstream concession agreement is built and how it will distribute the risk and rewards across the entire value chain for investors, expand the scope of investment and support in the economic development of the host country.

Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods

In conjunction with big data analysis methods, plant omics technologies have provided scientists with cost-effective and promising tools for discovering genetic architectures of complex agronomic traits using large breeding populations. In recent years, there has been significant progress in plant phenomics and genomics approaches for generating reliable large datasets. However, selecting an appropriate data integration and analysis method to improve the efficiency of phenome-phenome and phenome-genome association studies is still a bottleneck. This study proposes a hyperspectral wide association study (HypWAS) approach as a phenome-phenome association analysis through a hierarchical data integration strategy to estimate the prediction power of hyperspectral reflectance bands in predicting soybean seed yield. Using HypWAS, five important hyperspectral reflectance bands in visible, red-edge, and near-infrared regions were identified significantly associated with seed yield. The phenome-genome association analysis of each tested hyperspectral reflectance band was performed using two conventional genome-wide association studies (GWAS) methods and a machine learning mediated GWAS based on the support vector regression (SVR) method. Using SVR-mediated GWAS, more relevant QTL with the physiological background of the tested hyperspectral reflectance bands were detected, supported by the functional annotation of candidate gene analyses. The results of this study have indicated the advantages of using hierarchical data integration strategy and advanced mathematical methods coupled with phenome-phenome and phenome-genome association analyses for a better understanding of the biology and genetic backgrounds of hyperspectral reflectance bands affecting soybean yield formation. The identified yield-related hyperspectral reflectance bands using HypWAS can be used as indirect selection criteria for selecting superior genotypes with improved yield genetic gains in large breeding populations.

Vietnam in international institutions

<p>This thesis investigates how socialization in three selected institutions, namely the Association of Southeast Asian Nations (ASEAN), the ASEAN Regional Forum (ARF) and the UN Security Council (UNSC) has led to pro-norm behaviour on the part of Vietnamese officials. This behavioural change was evidenced by their support for the creation of an ASEAN Human Rights Body, the adoption of Preventive Diplomacy Papers in the ARF and internalization of the Responsibility to Protect as an emerging norm at the Security Council. Empirical findings in the thesis show that socialization occurred across three case-studies, eliciting pro-norm behaviour on the part of state officials, though to varying degrees. These findings confirm the plausibility of socialization as a source of cooperative behaviour among state agents within social environments. In addition, they provide insights into the slow but increasingly active and substantive cooperation in political and security areas where Vietnam has historically been reluctant. The thesis concludes with a suggestion that socialization could be an extremely useful framework for investigating how far Vietnam might go beyond verbal support for new norms, given the country has recently embarked on a new phase of integration. Vietnam now attaches great importance to the implementation of international commitments that it has made, and considers this a guiding principle for the country‘s new integration strategy. Socialization processes could yield insights about the likely extent of norm internalization and compliance in this new period.</p>

Vietnam in international institutions

<p>This thesis investigates how socialization in three selected institutions, namely the Association of Southeast Asian Nations (ASEAN), the ASEAN Regional Forum (ARF) and the UN Security Council (UNSC) has led to pro-norm behaviour on the part of Vietnamese officials. This behavioural change was evidenced by their support for the creation of an ASEAN Human Rights Body, the adoption of Preventive Diplomacy Papers in the ARF and internalization of the Responsibility to Protect as an emerging norm at the Security Council. Empirical findings in the thesis show that socialization occurred across three case-studies, eliciting pro-norm behaviour on the part of state officials, though to varying degrees. These findings confirm the plausibility of socialization as a source of cooperative behaviour among state agents within social environments. In addition, they provide insights into the slow but increasingly active and substantive cooperation in political and security areas where Vietnam has historically been reluctant. The thesis concludes with a suggestion that socialization could be an extremely useful framework for investigating how far Vietnam might go beyond verbal support for new norms, given the country has recently embarked on a new phase of integration. Vietnam now attaches great importance to the implementation of international commitments that it has made, and considers this a guiding principle for the country‘s new integration strategy. Socialization processes could yield insights about the likely extent of norm internalization and compliance in this new period.</p>