9 research outputs found

    A hybrid supervised ANN for classification and data visualization

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    Supervised ANNs such as Learning Vector Quantization (LVQs) and Multi-Layer Perceptrons (MLPs) usually do not support data visualization beside classification. Unsupervised visualization focused ANNs such as Self-organizing Maps (SOM) and its variants such as Visualization induced SOM (ViSOM) on the other hand, usually do not optimize data classification as compared with supervised ANNs such as LVQ. Thus to provide supervised classification and data visualization simultaneously, this work is motivated to propose a novel hybrid supervised ANN of LVQwithAC by hybridizing LVQ and modified Adaptive Coordinate (AC) approach. Empirical studies on benchmark data sets proven that, LVQwithAC was able to provide superior classification accuracy than SOM and ViSOM. Beside LVQwithAC was able to provide data topology, data structure, and inter-neuron distance preserve visualization. LVQwithAC was also proven able to perform promising classification among other supervised classifiers besides its additional data visualization ability over them. Thus, for applications requiring data visualization and classification LVQwithAC demonstrated its potential if supervised learning is all possible

    AC-ViSOM: Hybridising the Modified Adaptive Coordinate (AC) and ViSOM for Data Visualization

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    ViSOM’s (Visualization induced SOM) final map can be seen as a smooth net embedded in the input space, where the distances among neurons are controlled by a regularization control parameter which is usually heuristically chosen on a trial and error basis. Empirical studies shown that ViSOM suffers from dead neuron problem, since a big number of neurons fall outside of the data region due to the regularization effect, even though the regularization control parameter is properly chosen. In this paper, a modified Adaptive Coordinate (AC) approach that is able to preserve data structure is hybridised with ViSOM is proposed. Experimental studies on benchmark datasets shown that the proposed method was able to eliminate the selection of regularization control parameter and minimizing the dead neuron for better data representation

    Hybridization of Learning Vector Quantization (LVQ) and Adaptive Coordinates (AC) for data classification and visualization

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    Most of the artificial neural network (ANN) methods do not support data classification and visualization simultaneously. Some ANN methods such as learning vector quantization (LVQ), multi-layer perceptrons (MLP) and radial basis function (RBF) perform classification without any visualization. Excellent data visualization on the other hand has been prominently supported by various unsupervised methods such as self-organizing maps (SOM) and its recent variants of visualization induced SOM (ViSOM) and probabilistic regularized SOM (PRSOM). However, being unsupervised these methods do not optimize classification accuracy compared with the supervised classification methods such as LVQ. Thus, the scope of a novel supervised method is felt necessary to facilitate applications requiring good data visualization and intensive classification. LVQ demonstrates classification performance at least as high as other supervised ANN classifiers. Adaptive coordinate (AC) on the other hand, has demonstrated the ability of mirroring weight vectorspsila movements in N-dimensional input space to low dimensional output space to reveal the clustering tendency of data learned by SOM. This mirroring concept motivates this work to hybridize a modified AC with LVQ (LVQwihAC) to support data visualization and classification simultaneously. Empirical studies on benchmark data sets demonstrated that, the LVQwihAC method provides better classification accuracy than the unsupervised methods of SOM, ViSOM and PRSOM besides its promising data visualization with higher computational efficiency. The classification performance is also found at least as good as other supervised classifiers with additional data visualization abilities over them

    A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis

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    The objective of this research was set to propose a supervised ANN method able to perform data classification and data structure, inter-neuron distances and data topology preserved visualization simultaneously. A real world application of mental disorder diagnosis in counseling domain was then investigated and LVQ with AC was employed to facilitate classification and visualization in designing and development of an intelligent decision support system to assist counselors in diagnosis of mental disorders

    Noninstitutional births and newborn care practices among adolescent mothers in Bangladesh

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    This article was published in the International Journal of Educational Development [© 2011 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses] and the definite version is available at : http://doi.org/10.1111/j.1552-6909.2011.01240.x. The Journal's website is at: http://www.jognn.org/article/S0884-2175(15)30542-6/abstractObjective: To describe home-based newborn care practices among adolescent mothers in Bangladesh and to identify sociodemographic, antenatal care (ANC), and delivery care factors associated with these practices. Design: The 2007 Bangladesh Demographic Health Survey, conducted from March 24 to August 11, 2007. Setting: Selected urban and rural areas of Bangladesh. Participants: A total of 580 adolescent women (aged 15-19 years) who had ever been married with noninstitutional births and having at least one child younger than 3 years of age. Methods: Outcomes included complete cord care, complete thermal protection, initiation of early breastfeeding, and postnatal care within 24 hours of birth. Descriptive statistics and multivariate logistic regression methods were employed in analyzing the data. Results: Only 42.8% and 5.1% newborns received complete cord care and complete thermal protection. Only 44.6% of newborns were breastfed within 1 hour of birth. The proportion of the newborns that received postnatal care within 24 hours of birth was 9%, and of them 11% received care from medically trained providers (MTP). Higher level of maternal education and richest bands of wealth were associated with complete thermal care and postnatal care within 24 hours of birth but not with complete cord care and early breastfeeding. Use of sufficient ANC and assisted births by MTP were significantly associated with several of the newborn care practices. Conclusions: The association between newborn care practices of the adolescent mothers and sufficient ANC and skilled birth attendance suggest that expanding skilled birth attendance and providing ANC may be an effective strategy to promote essential and preventive newborn care.Publishe

    Protective Effects of Black Cumin (Nigella sativa) and Its Bioactive Constituent, Thymoquinone against Kidney Injury: An Aspect on Pharmacological Insights

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    The prevalence of chronic kidney disease (CKD) is increasing worldwide, and a close association between acute kidney injury (AKI) and CKD has recently been identified. Black cumin (Nigella sativa) has been shown to be effective in treating various kidney diseases. Accumulating evidence shows that black cumin and its vital compound, thymoquinone (TQ), can protect against kidney injury caused by various xenobiotics, namely chemotherapeutic agents, heavy metals, pesticides, and other environmental chemicals. Black cumin can also protect the kidneys from ischemic shock. The mechanisms underlying the kidney protective potential of black cumin and TQ include antioxidation, anti-inflammation, anti-apoptosis, and antifibrosis which are manifested in their regulatory role in the antioxidant defense system, NF-κB signaling, caspase pathways, and TGF-β signaling. In clinical trials, black seed oil was shown to normalize blood and urine parameters and improve disease outcomes in advanced CKD patients. While black cumin and its products have shown promising kidney protective effects, information on nanoparticle-guided targeted delivery into kidney is still lacking. Moreover, the clinical evidence on this natural product is not sufficient to recommend it to CKD patients. This review provides insightful information on the pharmacological benefits of black cumin and TQ against kidney damage

    Potentials of curcumin against polycystic ovary syndrome: Pharmacological insights and therapeutic promises

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    Polycystic ovary syndrome (PCOS) is a common hormonal disorder among women (4%–20%) when the ovaries create abnormally high levels of androgens, the male sex hormones that are typically present in women in trace amounts. The primary characteristics of PCOS include oxidative stress, inflammation, hyperglycemia, hyperlipidemia, hyperandrogenism, and insulin resistance. Generally, metformin, spironolactone, eflornithine and oral contraceptives are used to treat PCOS, despite their several side effects. Therefore, finding a potential candidate for treating PCOS is necessary. Curcumin is a major active natural polyphenolic compound derived from turmeric (Curcuma longa). A substantial number of studies have shown that curcumin has anti-inflammatory, anti-oxidative stress, antibacterial, and anti-apoptotic activities. In addition, curcumin reduces hyperglycemia, hyperlipidemia, hyperandrogenism, and insulin resistance in various conditions, including PCOS. The review highlighted the therapeutic aspects of curcumin against the pathophysiology of PCOS. We also offer a hypothesis to improve the development of medicines based on curcumin against PCOS

    A Systematic Review on Marine Algae-Derived Fucoxanthin: An Update of Pharmacological Insights

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    Fucoxanthin, belonging to the xanthophyll class of carotenoids, is a natural antioxidant pigment of marine algae, including brown macroalgae and diatoms. It represents 10% of the total carotenoids in nature. The plethora of scientific evidence supports the potential benefits of nutraceutical and pharmaceutical uses of fucoxanthin for boosting human health and disease management. Due to its unique chemical structure and action as a single compound with multi-targets of health effects, it has attracted mounting attention from the scientific community, resulting in an escalated number of scientific publications from January 2017 to February 2022. Fucoxanthin has remained the most popular option for anti-cancer and anti-tumor activity, followed by protection against inflammatory, oxidative stress-related, nervous system, obesity, hepatic, diabetic, kidney, cardiac, skin, respiratory and microbial diseases, in a variety of model systems. Despite much pharmacological evidence from in vitro and in vivo findings, fucoxanthin in clinical research is still not satisfactory, because only one clinical study on obesity management was reported in the last five years. Additionally, pharmacokinetics, safety, toxicity, functional stability, and clinical perspective of fucoxanthin are substantially addressed. Nevertheless, fucoxanthin and its derivatives are shown to be safe, non-toxic, and readily available upon administration. This review will provide pharmacological insights into fucoxanthin, underlying the diverse molecular mechanisms of health benefits. However, it requires more activity-oriented translational research in humans before it can be used as a multi-target drug

    Secondhand smoking, knowledge/attitudes and socioeconomic status among married Bangladeshi women: a cross-sectional study

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    ABSTRACT BACKGROUND: There is a paucity of research on knowledge/attitudes regarding the dangers of exposure to secondhand smoking (SHS) among women. The relationship between exposure to SHS, socioeconomic status (SES) and knowledge/attitudes regarding the risks of SHS has often been ignored. We therefore aimed to examine (1) whether SES and exposure to SHS were independently associated with knowledge/attitudes regarding the risks of SHS; and (2) whether women with low SES and exposure to SHS were uniquely disadvantaged in terms of deficient knowledge and more dismissive attitudes towards the risks of SHS. DESIGN AND SETTING: Cross-sectional study in the Rajshahi district, Bangladesh. METHODS: A total of 541 women were interviewed. Knowledge of and attitudes towards the risks of SHS were the outcomes of interest. RESULTS: A majority of the respondents were exposed to SHS at home (49.0%). Only 20.1% had higher levels of knowledge, and only 37.3% had non-dismissive attitudes towards the risks of SHS. Participants in the low SES group and those exposed to SHS had lower odds of higher knowledge and their attitudes towards the risks of SHS were more dismissive. Regarding deficient levels of knowledge and scores indicating more dismissive attitudes, women in the low SES group and who were exposed to SHS were not uniquely disadvantaged. CONCLUSIONS: Exposure to SHS and low SES were independently associated with deficient knowledge and scores indicating more dismissive attitudes. Regarding knowledge/attitudes, the negative effect of exposure to SHS extended across all socioeconomic backgrounds and was not limited to women in either the low or the high SES group
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