Automatic age estimation system for face images

Humans are the most important tracking objects in surveillance systems. However, human tracking is not enough to provide the required information for personalized recognition. In this paper, we present a novel and reliable framework for automatic age estimation based on computer vision. It exploits global face features based on the combination of Gabor wavelets and orthogonal locality preserving projections. In addition, the proposed system can extract face aging features automatically in real-time. This means that the proposed system has more potential in applications compared to other semi-automatic systems. The results obtained from this novel approach could provide clearer insight for operators in the field of age estimation to develop real-world applications. © 2012 Lin et al

World caf\ue9 method to engage smart energy-district project partners in assessing urban co-benefits

Urban energy-district projects introduce outstanding technological innovation in buildings and energy systems increasing sustainability in city neighborhoods. Such projects generate additional co-benefits for the city beyond changes in physical elements and development of social and institutional relationships (e.g. local employment, environmental quality, public health, property values, innovation attitude, etc.). Since exceeding main declared goals or not always clearly foreseen in the early project phase, these co-benefits are often not properly understood and considered. However, only their explicit recognition will make possible their inclusion in the assessment of the whole project\u2019s performance. From these considerations, this study faces the issue of engaging project partners in assessing co-benefits in order to consider a broad spectrum of relevant, positive effects in the evaluation process. Group knowledge and group thinking of this complex topic are investigated through the world caf\ue9 method, providing an atmosphere of trust and open discussions among participants. This empirical work lays the foundations to go beyond the mere economic measure as the sole criterion for assessing project effects, also including changes in end-user behavior and intangible asset

Microalgae biomass from swine wastewater and its conversion to bioenergy

© 2018 Elsevier Ltd Ever-increasing swine wastewater (SW) has become a serious environmental concern. High levels of nutrients and toxic contaminants in SW significantly impact on the ecosystem and public health. On the other hand, swine wastewater is considered as valuable water and nutrient source for microalgae cultivation. The potential for converting the nutrients from SW into valuable biomass and then generating bioenergy from it has drawn increasing attention. For this reason, this review comprehensively discussed the biomass production, SW treatment efficiencies, and bioenergy generation potentials through cultivating microalgae in SW. Microalgae species grow well in SW with large amounts of biomass being produced, despite the impact of various parameters (e.g., nutrients and toxicants levels, cultivation conditions, and bacteria in SW). Pollutants in SW can effectively be removed by harvesting microalgae from SW, and the harvested microalgae biomass elicits high potential for conversion to valuable bioenergy

Soft-Boosted Self-Constructing Neural Fuzzy Inference Network

© 2013 IEEE. This correspondence paper proposes an improved version of the self-constructing neural fuzzy inference network (SONFIN), called soft-boosted SONFIN (SB-SONFIN). The design softly boosts the learning process of the SONFIN in order to decrease the error rate and enhance the learning speed. The SB-SONFIN boosts the learning power of the SONFIN by taking into account the numbers of fuzzy rules and initial weights which are two important parameters of the SONFIN, SB-SONFIN advances the learning process by: 1) initializing the weights with the width of the fuzzy sets rather than just with random values and 2) improving the parameter learning rates with the number of learned fuzzy rules. The effectiveness of the proposed soft boosting scheme is validated on several real world and benchmark datasets. The experimental results show that the SB-SONFIN possesses the capability to outperform other known methods on various datasets

A cross-sectional analysis of traditional medicine use for malaria alongside free antimalarial drugs treatment amongst adults in high-risk malaria endemic provinces of Indonesia

© 2017 Suswardany et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background The level of traditional medicine use, particularly Jamu use, in Indonesia is substantial. Indonesians do not always seek timely treatment for malaria and may seek self-medication via traditional medicine. This paper reports findings from the first focused analyses of traditional medicine use for malaria in Indonesia and the first such analyses worldwide to draw upon a large sample of respondents across high-risk malaria endemic areas. Methods A sub-study of the Indonesia Basic Health Research/Riskesdas Study 2010 focused on 12,226 adults aged 15 years and above residing in high-risk malaria-endemic provinces. Logistic regression was undertaken to determine the significant associations for traditional medicine use for malaria symptoms. Findings Approximately one in five respondents use traditional medicine for malaria symptoms and the vast majority experiencing multiple episodes of malaria use traditional medicine alongside free antimalarial drug treatments. Respondents consuming traditional medicine for general health/common illness purposes every day (odds ratio: 3.75, 95% Confidence Interval: 2.93 4.79), those without a hospital in local vicinity (odds ratio: 1.31, 95% Confidence Interval: 1.10 1.57), and those living in poorer quality housing, were more likely to use traditional medicine for malaria symptoms. Conclusion A substantial percentage of those with malaria symptoms utilize traditional medicine for treating their malaria symptoms. In order to promote safe and effective malaria treatment, all providing malaria care in Indonesia need to enquire with their patients about possible traditional medicine use

A novel liposomal drug delivery system for PMMA bone cements

The population in developed countries is ageing and the number of people experiencing joint-related conditions, such as osteoarthritis, is expected to increase. Joint replacements are currently the most effective treatment for severe joint conditions and although many of these procedures are successful, infection developing after the procedure is still an issue, requiring complex and expensive revisions. Whilst incorporating a powdered antibiotic within the bone cement can reduce infection rates, the powder frequently agglomerates, resulting in poor antibiotic release characteristics and compromised mechanical performance of the cement. To overcome these issues, a novel delivery system consisting of antibiotic-loaded nano-sized liposomes was developed for inclusion into polymethyl methacrylate (PMMA) bone cement. This system was tested in a commercial cement (Palacos R) and consistently delivered a higher percentage (22%) of the incorporated antibiotic when compared to the powdered antibiotic cement (9%), meaning less antibiotic needs to be incorporated than with conventional cement. The novel system resulted in a controlled and gradual release of antibiotic over a longer, 30-day period and enhanced the toughness, bending strength and Vickers hardness of the cement, without altering its polymerization or molecular structure. This new material has the potential to significantly reduce infections in cemented joint replacements leading to enhanced patient quality of life and reduced healthcare costs

Cross-cultural validation of the Cardiac Depression Scale in Iran

Background. The Cardiac Depression Scale (CDS) is a disease-specific instrument for measuring depression in cardiac patients. This study was designed to validate the CDS in an Iranian population. Methods. Translation and back-translation of the 26-item CDS scale was performed using recommended procedures. The Iranian translation of the CDS (I-CDS) was administered to 261 individuals in Iran, concurrently with the Beck Depression Inventory. The factor structure of the I-CDS was examined using exploratory factor analysis procedures to enable comparison with previous psychometric evaluation ofthe CDS. Receiver operating characteristic curves were used to examine the ability of the I-CDS to discriminate between categories of depression. Results. First-order exploratory factor analysis uncovered two robust factors, consistent with the second-order dimensions originally reported by the developers of this instrument. Cronbach's alpha was .88 for the total 26-item I-CDS, indicating satisfactory internal consistency of the I-CDS. Intercorrelation between the total scores for the I-CDS and BDI was .62 (p < .001). For the I-CDS cut-off of 90, the sensitivity was 85%, and specificity was 61% with a computed area under the curve (AUC) of 0.81 (95% CI, 0.76-0.87). For the I-CDS cut-off of 100, the sensitivity was 81%, and specificity was 63% with a computed AUC of 0.81 (95% CI, 0.76-0.87). Conclusion. This validation study of the Iranian version of theCDSdemonstrated that it is an acceptable, reliable, and valid measure of depression in people with heart disease.Copyright © The British Psychological Society

Bioprocessing for elimination antibiotics and hormones from swine wastewater

© 2017 Elsevier B.V. Antibiotics and hormones in swine wastewater have become a critical concern worldwide due to the severe threats to human health and the eco-environment. Removal of most detectable antibiotics and hormones, such as sulfonamides (SAs), SMs, tetracyclines (TCs), macrolides, and estrogenic hormones from swine wastewater utilizing various biological processes were summarized and compared. In biological processes, biosorption and biodegradation are the two major removal mechanisms for antibiotics and hormones. The residuals in treated effluents and sludge of conventional activated sludge and anaerobic digestion processes can still pose risks to the surrounding environment, and the anaerobic processes’ removal efficiencies were inferior to those of aerobic processes. In contrast, membrane bioreactors (MBRs), constructed wetlands (CWs) and modified processes performed better because of their higher biodegradation of toxicants. Process modification on activated sludge, anaerobic digestion and conventional MBRs could also enhance the performance (e.g. removing up to 98% SMs, 88.9% TCs, and 99.6% hormones from wastewater). The hybrid process combining MBRs with biological or physical technology also led to better removal efficiency. As such, modified conventional biological processes, advanced biological technologies and MBR hybrid systems are considered as a promising technology for removing toxicants from swine wastewater

Problematic effects of antibiotics on anaerobic treatment of swine wastewater

© 2018 Elsevier Ltd Swine wastewaters with high levels of organic pollutants and antibiotics have become serious environmental concerns. Anaerobic technology is a feasible option for swine wastewater treatment due to its advantage in low costs and bioenergy production. However, antibiotics in swine wastewater have problematic effects on micro-organisms, and the stability and performance of anaerobic processes. Thus, this paper critically reviews impacts of antibiotics on pH, COD removal efficiencies, biogas and methane productions as well as the accumulation of volatile fatty acids (VFAs) in the anaerobic processes. Meanwhile, impacts on the structure of bacteria and methanogens in anaerobic processes are also discussed comprehensively. Furthermore, to better understand the effect of antibiotics on anaerobic processes, detailed information about antimicrobial mechanisms of antibiotics and microbial functions in anaerobic processes is also summarized. Future research on deeper knowledge of the effect of antibiotics on anaerobic processes are suggested to reduce their adverse environmental impacts

Evolution of Landau Levels into Edge States at an Atomically Sharp Edge in Graphene

The quantum-Hall-effect (QHE) occurs in topologically-ordered states of two-dimensional (2d) electron-systems in which an insulating bulk-state coexists with protected 1d conducting edge-states. Owing to a unique topologically imposed edge-bulk correspondence these edge-states are endowed with universal properties such as fractionally-charged quasiparticles and interference-patterns, which make them indispensable components for QH-based quantum-computation and other applications. The precise edge-bulk correspondence, conjectured theoretically in the limit of sharp edges, is difficult to realize in conventional semiconductor-based electron systems where soft boundaries lead to edge-state reconstruction. Using scanning-tunneling microscopy and spectroscopy to follow the spatial evolution of bulk Landau-levels towards a zigzag edge of graphene supported above a graphite substrate we demonstrate that in this system it is possible to realize atomically sharp edges with no edge-state reconstruction. Our results single out graphene as a system where the edge-state structure can be controlled and the universal properties directly probed.Comment: 16 pages, 4 figure