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For the Environment: An Assessment of Recent Military Intervention in Informal Gold Mining Communities in Ghana
Full text linkThis article reflects critically on the impacts of the recent ban on artisanal and small-scale mining (ASM) – low-tech, labour-intensive mineral extraction and processing – in Ghana. Government officials claimed that a ban was necessary because the country’s ASM activities, most of which are found in the informal economy, pose a serious threat to local waterbodies and that security forces were needed for its enforcement. It is argued here, however, that projecting the ban and associated military intervention as actions taken specifically to protect the environment has helped the government escape scrutiny over its choice of strategy to combat illegal mining. Perhaps more importantly, it has masked what may be the real reasons behind these moves: 1) to help the government regain control of the purchasing side of an ASM sector that is now heavily populated and influenced by foreigners; and 2) to put it in an improved position to demarcate parcels of land to the multinational mineral exploration and mining companies that supply it with significant quantities of revenue in the form of taxes, royalties and permit fees
Voting, contagion and the trade-off between public health and political rights: Quasi-experimental evidence from the Italian 2020 polls
No full textFISH FEEDING INTENSITY ASSESSMENT IN AQUACULTURE: A NEW AUDIO DATASET AFFIA3K AND A DEEP LEARNING ALGORITHM
Full text linkAssessment of suspended growth biological process for treatment and reuse of mixed wastewater for irrigation of edible crops under hydroponic conditions
Full text linkDue to the increasing freshwater deterioration and demand for irrigation, there is pressing need to reclaim and reuse wastewater for agricultural operations. While this practice is gaining significant traction in developed world, it is quite rare in most developing countries with inadequate or no functional sewerage facilities and treatment systems at both municipal and industrial levels occasioned by high investment and operational costs. Consequently, wastewaters generated are in complex heterogenous mix of industrial, domestic, municipal and agricultural runoff wastewater. Biological technologies which utilize the expertise of microorganisms are considered robust, efficient and economically attractive for treatment of wide range of wastewaters and they have high suitability in developing countries. This work therefore assessed the potential of suspended growth biological process (SGBP) for reclamation and reuse of mixed wastewater composed a mixture of domestic effluent, pharmaceutical, textile, petroleum discharges and agricultural runoff for irrigation of edible crops (lettuce and beets) with plants phenological parameters as measuring indicators. The germination and phenological characteristics of crops were studied in a hydroponic unit under four irrigation regimes: tap water as control, mixed wastewater, SGBP treated wastewater, and tap water mixed with nutrient solution as upper control, for a duration of 45-d. The results proved that the SGBP treated wastewater had no negative impact on germination responses of the seed crops. However, residual recalcitrant compounds caused early stunted growth in plant root systems with resultant limited access to nutrients. Consequently, plant vegetative growth and phenological development as well as chlorophyll production were reduced. In comparison to nutrients supplemented solution, nutrients deficiency and imbalance in treated wastewater contributed to the poor development in irrigated plants. The outcomes of seed germination and plant growth experiments show a positive indication for reuse of mixed wastewater in agriculture. However, there is need for further research to explore the long-term benefits and limitations of reusing such treated wastewater
Ensemble-based method for the Inverse Frobenius-Perron Operator Problem: Data Driven Global Analysis from Spatiotemporal "Movie" data
Full text linkGiven a sequence of empirical distribution data (e.g. a movie of a spatiotemporal process such as a fluid flow), this work develops an ensemble data assimilation method to estimate the transition probability that represents a finite approximation of the Frobenius-Perron operator. This allows a dynamical systems knowledge to be incorporated into a prior ensemble, which provides sensible estimates in instances of limited observation. We demonstrate improved estimates over a constrained optimization approach (based on a quadratic programming problem) which does not impose a prior on the solution except for Markov properties. The estimated transition probability then enables several probabilistic analysis of dynamical systems. We focus only on the identification of coherent patterns from the estimated Markov transition to demonstrate its application as a proof-of-concept. To the best of our knowledge, there have not been many works on data-driven methods to identify coherent patterns from this type of data. While here the results are presented only in the context of dynamical systems applications, this work we present here has the potential to make a contribution in wider application areas that require the estimation of transition probabilities from a time-ordered spatio-temporal distribution data
SP-GAN: Self-growing and Pruning Generative Adversarial Networks
Full text linkThis paper presents a new Self-growing and Pruning Generative Adversarial Network (SP-GAN) for realistic image generation. In contrast to traditional GAN models, our SPGAN is able to dynamically adjust the size and architecture of a network in the training stage, by using the proposed selfgrowing and pruning mechanisms. To be more specific, we first train two seed networks as the generator and discriminator, each only contains a small number of convolution kernels. Such small-scale networks are much easier and faster to train than large-capacity networks. Second, in the self-growing step,we replicate the convolution kernels of each seed network to augment the scale of the network, followed by fine-tuning the augmented/expanded network. More importantly, to prevent the excessive growth of each seed network in the self-growing stage, we propose a pruning strategy that reduces the redundancy of an augmented network, yielding the optimal scale of the network. Last, we design a new adaptive loss function that is treated as a variable loss computational process for the training of the proposed SP-GAN model. By design, the hyperparameters of the loss function can dynamically adapt to different training stages. Experimental results obtained on a set of datasets demonstrate the merits of the proposed method, especially in terms of the stability and efficiency of network training. The source code of the proposed SP-GAN method is publicly available at https://github.com/Lambert-chen/SPGAN.git
Impact of open innovation on industries and firms – A dynamic complex systems view
Full text linkThis paper develops novel behavioural models of open innovation (OI) for competitive markets and uses them to compare the impact of two types of OI frameworks – open source (OS) and patent-licensing (PL). The dynamic consequences of OI, for both OS and PL, are studied using a complex adaptive systems approach. We examine how profits, technology levels, R&D investment, technology adoption and market structure evolve under each and are impacted by underlying market characteristics. While both OS and PL are found to be equivalent in technology outcomes, OS comes with additional advantages to participating firms. Firms in the OS framework earn higher profit and are more efficient with their R&D investments. The industry is less concentrated under OS than under PL, except when market size is very large. In both frameworks, consumer preference for new product adoption has a significant impact. When consumers adopt newly introduced products relatively quickly, market concentration is the higher and overall rate of technological progress slower. These results contribute towards a deeper theoretical understanding of OI, opening new avenues for future research
A Novel Robust Network Data Envelopment Analysis Approach for Performance Assessment of Mutual Funds under Uncertainty
No full textMutual fund (MF) is one of the applicable and popular tools in investment market. The aim of this paper is to propose an approach for performance evaluation of mutual fund by considering internal structure and financial data uncertainty. To reach this goal, the robust network data envelopment analysis (RNDEA) is presented for extended two-stage structure. In the RNDEA method, leader-follower (non-cooperative game) and robust optimization approaches are applied in order to modeling network data envelopment analysis (NDEA) and dealing with uncertainty, respectively. The proposed RNDEA approach is implemented for performance assessment of 15 mutual funds. Illustrative results show that presented method is applicable and effective for performance evaluation and ranking of MFs in the presence of uncertain data. Also, the results reveal that the discriminatory power of robust NDEA approach is more than the discriminatory power of deterministic NDEA models
Lumped kinetic modelling of polyolefin pyrolysis: A non-isothermal method to estimate rate constants
No full textThe measurement of kinetic parameters in the pyrolysis of polyolefins requires the use of a lumped kinetic model for predicting the product distribution of wax, oil and gas yields. A non-isothermal method was established, in which a sample is heated in a tube reactor to a desired temperature at a constant rate of temperature rise. This method avoided the error present in the heating up stage which is inherent in any practical isothermal method in which reaction proceeds to a significant extent before the operating temperatures of polyolefin pyrolysis are reached, which results in challenges when defining the reaction time. The non-isothermal measurements were conducted between 450 and 550°C for polypropylene (PP) and polyethylene (HDPE and LDPE) and the temperature and lump yields are non-linearly regressed to achieve the kinetic parameters. The measured kinetic rate constants have the same trend as those reported in the literature using the isothermal method, but are higher than the values reported above 450°C and similar to the values for lower temperatures of 350°C and 370°C. The kinetic parameters derived are then validated by using isothermal experimental data. The calculated data using the measured kinetic parameters are generally in agreement with the experimental data. The non-isothermal method established in this work proves to be a much faster method for the measurement of intrinsic rate constants at high temperatures
A global perspective of the current state of heavy metals contamination in road dust
Full text link16 Heavy metals are persistent and bio-accumulative, and pose potential risk to human health and 17 ecosystem. We reviewed the current state of heavy metals contamination, the ecotoxicological 18 and human health risk of heavy metals reported in urban road dust from various cities in different 19 continents (Asia, Europe, Africa, America, and Australia). We compared and synthesized the 20 findings on the methods related to sample collection, extraction, analytical tools of heavy metals, 21 their concentrations, level of contamination, ecological risk, non-carcinogenic risk, and 22 carcinogenic risk in road dust. Concentrations of Pb, Zn, Cu, Ni, Cd, Cr, Mn, and Fe were found 23 to be higher than their background values in soil. As expected, the contamination levels of the 24 heavy metals varied extensively among cities, countries, continents, and periods. A high level of 25 contamination is observed for Pb and Cd in road dust due to operating leaded gasoline and the old 26 vehicle population. The highest Zn contamination was observed from road dust in Europe, 27 followed by Asia, Africa, Australia, and America (North America and South America). Cu 28 contamination and the pollution load index (PLI) is found to be the highest in Europe and lowest 29 in Africa, with in-between values of PLI in American and African cities. The potential ecological 30 risk on different continents was observed highest in Asia, followed by Europe, Australia, America, 31 and Africa. A comparative assessment of non-carcinogenic risk for children indicated that 32 Australia is a most susceptible country due to high heavy metals exposure in road dust, followed 33 by Asia. However, there is no susceptible risk in European, African and American cities. We did 34 not observe any potential risk to adults due to non-carcinogenic metals. Carcinogenic risk to all 35 age groups was within the threshold limit range for all the regions worldwide. 3
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