Mathematical Index Research Articles

Cumulative estrogen exposure and prospective memory in older women

This study looked at cumulative lifetime estrogen exposure, as estimated with a mathematical index (Index of Cumulative Estrogen Exposure (ICEE)) that included variables (length of time on estrogen therapy, age at menarche and menopause, postmenopausal body mass index, time since menopause, nulliparity and duration of breastfeeding) known to influence estrogen levels across the life span, and performance on prospective and retrospective memory measures in a group of 50 postmenopausal women (mean age=69.3years) who, if they were current or former users of estrogen therapy, had started therapy within 5years of menopause. The ICEE was found to be a significant predictor of performance on the Prospective Memory task (F(1)=4.21, p=.046, ηp2=.084). No significant relationship was noted between the ICEE and performance on measures of retrospective memory. The results suggest that the level of cumulative lifetime exposure to estrogen a woman has influences her prospective memory performance later in life and that the influence of reproductive and biological markers of endogenous estrogen exposure are relevant factors to consider when studying the effect of estrogen therapy on cognitive functioning in postmenopausal women. In addition, the finding that performance on a measure of prospective memory, but not performance on measures of retrospective memory, was associated with the ICEE adds further support to the theory that the frontal cortex may be especially sensitive to estrogen.

A functional mathematical index for predicting effects of food processing on eight sweet potato (Ipomoea batatas) cultivars

In this paper we apply an improved functional mathematical index (FMI), modified from those presented in previous publications, to define the influence of different cooking processes of eight sweet potato (Ipomoea batatas) cultivars on composition of six bioactive phenolic compounds (flavonoids). The index allows the evaluation of nutritional, safety, and processing aspects of the following six phenolic compounds: neochlorogenic acid (3-CQA), cryptochlorogenic acid (4-CQA), chlorogenic acid (5-CQA), and three isochlorogenic acids, namely isochlorogenic acid A (3,5-diCQA), isochlorogenic acid B (3,4-diCQA), and isochlorogenic acid C (4,5-diCQA). These sweet potato components are considered to be the most representative phenolic compounds in this widely consumed food. The results of the mathematical analysis suggest that the derived total and individual FMI values provide a tool for predicting the relative adverse effects of food-processing effects (boiling, deep frying, microwaving, oven baking, sautéing, and steaming) on the evaluated phenolic compounds of eight sweet potato varieties. The use of the FMI makes it possible to predict the effects of processing conditions on the content of phenolic compounds of new sweet potato varieties, without the need to actually subject the sweet potatoes to the various cooking conditions.

Spatial Distribution Pattern of The Fruit Fly, Bactrocera Dorsalis Complex (Diptera: Tephritidae) in Mango Orchard

The spatial distribution of Bactrocera dorsalis complex in the mango orchard that was analyzed using various mathematical indices dispersion and regression models showed an aggregated distribution. Taylor’s power law and Iwao’s regression model fitted well to all data sets. However, Iwao’s regression model fitted the data better, yielding higher values of R 2 than Taylor’s power law. As the regression of the reciprocal of k of negative binomial (1/ k ) on x [ k = ( x 2 – s 2 /n) / ( s 2 – x )] was not significant, the calculation of a common k was justified to be 1.30. This implies that the grade of aggregation of the fruit flies population was relatively constant throughout the time despite the variation in sample means. Since the clump size (λ) value was more than 2, the aggregated distribution might be due to the behavior and environmental factors working together. Keywords: Bactrocera dorsalis complex, spatial, distribution, trapping, mango

Cut-off points of the visceral adiposity index (VAI) identifying a visceral adipose dysfunction associated with cardiometabolic risk in a Caucasian Sicilian population

BackgroundThe Visceral Adiposity Index (VAI) is a sex-specific mathematical index, based on Waist Circumference (WC), Body Mass Index (BMI), triglycerides (TG) and HDL cholesterol (HDL) levels, indirectly expressing visceral adipose function and insulin sensitivity. Our aim was to find the optimal cut-off points of VAI identifying a visceral adipose dysfunction (VAD) associated with cardiometabolic risk in a Caucasian Sicilian population.MethodsMedical check-up data of 1,764 Primary Care patients (PC patients) were retrospectively and cross-sectionally examined using a receiver-operating characteristic (ROC) curve to determine appropriate stratified-for-age cut-off of VAI, for the identification of PC patients with Metabolic Syndrome (MetS) according to the NCEP-ATP III criteria. The PC patients with higher VAI scores were subdivided into three groups according to VAI tertiles (i.e. PC patients with mild VAD, moderate VAD or severe VAD). Finally, VAD classes were compared to classical cardio- and cerebrovascular risk factors as independent predictors of coronary heart disease and/or myocardial infarction, transient ischemic attack and/or ischemic stroke.ResultsModerate and severe VADs proved to be independently associated with cardiovascular events [(OR: 5.35; 95% CI: 1.92-14.87; p = 0.001) and (OR: 7.46; 95% CI: 2.64-21.05; p < 0.001) respectively]. Mild, moderate and severe VADs were found to be independently associated with cerebrovascular events [(OR: 2.73; 95% CI: 1.12-6.65; p = 0.027), (OR: 4.20; 95% CI: 1.86-9.45; p = 0.001) and (OR: 5.10; 95% CI: 2.14-12.17; p < 0.001) respectively].ConclusionsOur study suggests that among Caucasian Sicilian subjects there are clear cut-off points of VAI able to identify a VAD strongly associated with cardiometabolic risk.

FATOR DE CONDIÇÃO: BASES CONCEITUAIS, APLICAÇÕES E PERSPECTIVAS DE USO EM PESQUISAS ECOLÓGICAS COM PEIXES

Normal 0 21 false false false PT-BR X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabela normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-fareast-language:EN-US;} CONDITION FACTOR: CONCEPTUAL FOUNDATIONS, APPLICATIONS AND PROSPECTS FOR USE IN ECOLOGICAL RESEARCH WITH FISHES. This review aimed to detect trends in the use of condition factor from studies with different aquatic and semiaquatic organisms and present the main indexes and their uses for fish, assessing its potential application to questions involving the effect of environmental change on populations. We conducted a literature review involving the scientific articles published between 1950 and 2009, which used the condition factor. The data were evaluated in two steps. At first, more general, there was a significant increase in the number of publications, with the occurrence of 2,666 articles in 567 journals. Most studies involved the fish group, followed by molluscs, crustaceans, birds, mammals, amphibians, and reptiles. This was an expected trend, since the tool was developed initially for the first group. In the second step, restricted to 54 articles in 20 journals related to fish, it was found that the condition factor of Fulton was the most common, followed by the allometric condition factor, and the relative factor. In general, the reviewed articles met the limitations intrinsic to each type of content regarding the applicability in populations of species with different intensities of allometry between the sexes and ranges of length classes. The importance of using these indices as tools and practices available in the evaluation of population issues in different ecological scales is reflected in the wide variety of themes and approaches of the articles. These factors justify the need of improving mathematical indices, as well as standardization of the types of condition factor used in studies dealing with the same species, making easier comparisons and, consequently, their management and conservation actions. Keywords: Fitness; energy investment; weight-length relationship; structural component; allometry.

Application of a Functional Mathematical Index for Antibacterial and Anticarcinogenic Effects of Tea Catechins

Tea leaves produce secondary metabolites that are involved in the defense of the plants against invading pathogens. In the case of green teas, these metabolites are polyphenolic compounds called catechins. Previous studies developed a mathematical formula called functional mathematical index (FMI) that was used to describe the quality of different olive oils and potatoes in terms of compositional parameters and antioxidative properties of individual components. This study extends the development of the FMI concept to define an "optimum tea" based on reported relationships between the content of structurally different catechins of a large number of teas and their dual beneficial effects: antimicrobial activities against a foodborne pathogen and inhibition of human cancer cell lines. The described mathematical approach may be useful for predicting relative beneficial effects of new teas based on their catechin content.

APPLICATION OF A FUNCTIONAL MATHEMATICAL QUALITY INDEX TO ASPARAGINE, FREE SUGAR AND PHENOLIC ACID CONTENT OF 20 COMMERCIAL POTATO VARIETIES

ABSTRACTIn this article, we apply a functional mathematical index (FMI), introduced in a previous publication, to 20 commercial potato varieties. The index allows evaluation of nutritional, safety and processing “quality parameters” of different potato cultivars. The main goal of the index is to link the quality of the chemical composition with factors that may affect the growth, production, distribution and processing of potatoes and potato products for commercial use. The index has been used to assess FMI values of 20 commercial potato cultivars in terms of their content of asparagine and reducing sugars, which form heat‐induced potentially toxic acrylamide and of antioxidative phenolic compounds, which participate in nonenzymatic browning reactions and may exert beneficial effects after consumption.PRACTICAL APPLICATIONSThe index could be useful to a wide set of users, including consumers of potatoes as well as to potato producers and breeders, because it makes it possible to relate the index to the potato price and operate a more accurate choice for selection of so‐called “optimal potatoes.” Potato producers may find the index useful because it can help them detect the critical points throughout the whole food production chain in order to facilitate selection of high‐quality potatoes for sale to consumers. Potato breeders could apply the index to the development and selection of improved cultivars for commercial use.

Removal of ring artifacts in CT imaging through detection and correction of stripes in the sinogram

Due to malfunctioning and mis-calibration of cells in digital x-ray detectors as well as impurities on the scintillator screens, stripe artifacts arise in the sinogram which in turn generate ring artifacts in the reconstructed x-ray computed tomography images. In this paper, a novel technique is proposed for the detection and removal of stripe artifacts in a sinogram with a view to suppress the ring artifacts from the tomographic images. To accurately detect the stripe creating pixels using a derivative-based algorithm, at first the sinogram is windowed to create a sub-sinogram by keeping the pixel of examination at the center position in the sub-sinogram. The other pixels in the sub-sinogram are selected from a polyphase component of the sinogram. A new mathematical index is proposed here to isolate the strong and weak ring-generating stripes from the good ones. For the correction of strong ring artifacts resulting from the defective detector elements and dusty scintillator crystals, 2D variable window moving average and weighted moving average filters are proposed in this work. On the other hand, a conventionally trusted constant bias correction scheme is adopted to correct the responses of the mis-calibrated detector elements. To evaluate and compare the performance of the proposed algorithm, real micro-CT images acquired from two flat panel detectors under different operating conditions are used. Experimental results show that the proposed method can remove ring artifacts more effectively without imparting noticeable distortion in the image as compared to a recently reported technique in the literature.

Parsimonious classification of binary lacunarity data computed from food surface images using kernel principal component analysis and artificial neural networks

Lacunarity is about quantifying the degree of spatial heterogeneity in the visual texture of imagery through the identification of the relationships between patterns and their spatial configurations in a two-dimensional setting. The computed lacunarity data can designate a mathematical index of spatial heterogeneity, therefore the corresponding feature vectors should possess the necessary inter-class statistical properties that would enable them to be used for pattern recognition purposes. The objectives of this study is to construct a supervised parsimonious classification model of binary lacunarity data–computed by Valous et al. (2009)–from pork ham slice surface images, with the aid of kernel principal component analysis (KPCA) and artificial neural networks (ANNs), using a portion of informative salient features. At first, the dimension of the initial space (510 features) was reduced by 90% in order to avoid any noise effects in the subsequent classification. Then, using KPCA, the first nineteen kernel principal components (99.04% of total variance) were extracted from the reduced feature space, and were used as input in the ANN. An adaptive feedforward multilayer perceptron (MLP) classifier was employed to obtain a suitable mapping from the input dataset. The correct classification percentages for the training, test and validation sets were 86.7%, 86.7%, and 85.0%, respectively. The results confirm that the classification performance was satisfactory. The binary lacunarity spatial metric captured relevant information that provided a good level of differentiation among pork ham slice images.

Investigation into the compatibility and effectiveness of a new mathematical online voltage sag index

A new mathematical index is investigated in this paper which improves the power quality of a system through providing a tool for online voltage sag mitigation. The index is developed mathematically and applied on transmission and distribution networks. Furthermore, it is verified for its compatibility through the use of a tap changing transformer scheme. Two loading variation scenarios, consisting of induction motors are investigated for each type of network, in order to establish the effectiveness and accuracy of the index.

The Graph Theoretical Approach in Brain Functional Networks: Theory and Applications

The present book illustrates the theoretical aspects of several methodologies related to the possibility of i) enhancing the poor spatial information of the electroencephalographic (EEG) activity on the scalp and giving a measure of the electrical activity on the cortical surface. ii) estimating the directional influences between any given pair of channels in a multivariate dataset. iii) modeling the brain networks as graphs. The possible applications are discussed in three different experimental designs regarding i) the study of pathological conditions during a motor task, ii) the study of memory processes during a cognitive task iii) the study of the instantaneous dynamics throughout the evolution of a motor task in physiological conditions. The main outcome from all those studies indicates clearly that the performance of cognitive and motor tasks as well as the presence of neural diseases can affect the brain network topology. This evidence gives the power of reflecting cerebral states or traits to the mathematical indexes derived from the graph theory. In particular, the observed structural changes could critically depend on patterns of synchronization and desynchronization - i.e. the dynamic binding of neural assemblies - as also suggested by a wide range of previous electrophysiological studies. Moreover, the fact that these patterns occur at multiple frequencies support the evidence that brain functional networks contain multiple frequency channels along which information is transmitted. The graph theoretical approach represents an effective means to evaluate the functional connectivity patterns obtained from scalp EEG signals. The possibility to describe the complex brain networks sub-serving different functions in humans by means of numbers is a promising tool toward the generation of a better understanding of the brain functions.

High clonal diversity in erythromycin-resistant Streptococcus pneumoniae invasive isolates in Madrid, Spain (2000-07)

Erythromycin resistance in Streptococcus pneumoniae is still increasing worldwide. All 78 erythromycin-resistant S. pneumoniae isolates collected from blood cultures in our hospital (2000-07) were studied and the population structure was analysed by using different mathematical diversity indexes. Erythromycin resistance determinants were screened by PCR. The population structure, including multilocus sequence typing, was analysed by using quantitative clonal diversity (diversity ratio, Simpson, Selander-Levin and Shannon mathematical indexes). The leading resistance gene was erm(B) (74.3% of the isolates), followed by the erm(B) plus mef(A) combination (17.9%) and mef(A) alone (7.7%). The most frequent serotypes were 14 (18%), 19A (15.4%) and 6B (11.5%). A polyclonal structure was detected in resistant strains, including the Spain(9V)-3, Spain(6B)-2 and Denmark(14)-32 international clones. Both genetic diversity and genetic distribution were high, particularly among clones containing erm(B) and erm(B) plus mef(A) determinants. The resistance determinants erm(B) and the combination of erm(B) plus mef(A) were observed within multiple S. pneumoniae bacteraemic clones. The preservation of a polyclonal structure might provide a suitable background for further evolution of antibiotic resistance.

The International Publication Productivity of Malaysia in Social Sciences: Developing a Scientific Power Index

The purpose of this study is to evaluate publication output and citation impact in the social sciences in Malaysia, based on Social Science Citation Index (SSCI) data, for the period 1999–2008. In addition to the analysis of trends in publication and citation patterns and national publication profiles, an attempt is made to explore the strengths and weakness of different fields, using a new mathematical index, the scientific power index (PI). The findings indicate that publication output in the social sciences has been on the increase since 1999. Mostpapers have been published in median-impact-factor journals (mean impact factor of 2.72 per paper). Internationally co-authored publications represented 77 per cent of all citations. Most of the prolific authors are from the highly productive institutions; however, none of highly cited first authors are from highly productive institutions. Psychology, economics, management, and environmental studies are the dominant fields in Malaysian social sciences.

The International Publication Productivity of Malaysia in Social Sciences

The purpose of this study is to evaluate publication output and citation impact in the social sciences in Malaysia, based on Social Science Citation Index (SSCI) data, for the period 1999–2008. In addition to the analysis of trends in publication and citation patterns and national publication profiles, an attempt is made to explore the strengths and weakness of different fields, using a new mathematical index, the scientific power index (PI). The findings indicate that publication output in the social sciences has been on the increase since 1999. Mostpapers have been published in median-impact-factor journals (mean impact factor of 2.72 per paper). Internationally co-authored publications represented 77 per cent of all citations. Most of the prolific authors are from the highly productive institutions; however, none of highly cited first authors are from highly productive institutions. Psychology, economics, management, and environmental studies are the dominant fields in Malaysian social sciences.

Separating Thalassemia Trait and Iron Deficiency by Simple InspectionThe Author’s ReplyThe Author’s Reply

Recently the Journal has published interesting articles and correspondence on the subject of the separation of thalassemia trait (TT) from iron deficiency anemia (IDA) by the use of RBC indices. Rathod et al1 calculated 6 previously described indexes on 200 patients and correlated the findings with the findings of hemoglobin electrophoresis and iron studies. They favored the Shine and Lal index.2 Harrington et al3 used morphologic findings for the same purpose and, in the process, generated data showing red cell distribution width (RDW) to be a good discriminatory tool. Ntaios and Chatzinikolaou4 criticized the use of RDW as a discriminator, having previously found it of little value. I believe it is usually easiest to separate TT and IDA by simple inspection, rather than using a mathematical index, using the following rules: (1) TT rarely causes anemia of less than 10 g/dL (100 g/L) of hemoglobin. (The hemoglobin value is usually more than 11 g/dL [110 g/L].) (2) The RBC count in TT is more than 5.0 x 106/μL (5.0 x 1012/L) and in IDA is less than 5.0 x 106/μL (5.0 x 1012/L). (3) The RDW in IDA is more than 17% and in TT is less than 17%. Discordances usually indicate a combined anemia. Here are a few illustrative true patient examples. (1) A …

Pavement Maintenance Prioritization Using Analytic Hierarchy Process

The prioritization of maintenance activities is commonly applied in pavement maintenance planning. A widely adopted practice is to express maintenance priority in the form of a priority index, computed by means of an empirical mathematical expression. Though convenient to use, empirical mathematical indices often do not have a clear physical meaning and cannot accurately and effectively convey the priority assessment or intention of highway agencies and engineers. In an attempt to overcome this limitation, this study explores the use of an analytic hierarchy process (AHP) for the prioritization of pavement maintenance activities. The main aim is to identify an approach that can reflect the engineering judgment of highway agencies and engineers more closely. Three forms of AHP are examined, namely, the distributive-mode relative AHP, the ideal-mode relative AHP, and the absolute AHP. The applications of the three methods are illustrated by using an example problem, and the results are compared with the priority assessments obtained by a direct assessment method in which the raters make the evaluation by directly comparing all maintenance activities together. The study concludes that the absolute AHP is suitable for the pavement maintenance prioritization process, on the basis of its ability to provide priority assessments for pavement maintenance activities in good agreement with the priority assessments obtained by the direct assessment method and its operational advantage in evaluating a large number of maintenance activities.

Online fuzzy voltage collapse risk quantification

Many voltage stability indicators have been proposed in the past for the voltage collapse assessment. Almost all of them are determined through quite complex analytical tools; therefore, it is difficult for system operators to give them a physical meaning. In order to perform a simple and reliable evaluation of the security margins, it is necessary to make a synthesis of the information given by the various indices. The present work proposes an Artificial Intelligence-based tool for the evaluation of the voltage security. In particular, a Fuzzy Inference Engine is developed and optimized by two different approaches (Neural Networks and Genetic Algorithms). Starting from the state estimation, a given set of mathematical indices is computed to represent a snapshot of the current electric system operating point. The numerical values are then translated into a set of symbolic and linguistic quantities that are manipulated through a set of logical connectives and Inference Methods provided by the mathematical logic. As a result, the Fuzzy Logic gives a MW measure of the distance from the collapse limit, a metric usually appreciated by system operators. The Fuzzy System has been built and optimized by using, as a test system, a detailed model of the EHV Italian transmission network connected to an equivalent of the UCTE network (about 1700 buses).

Evaluation of mathematical indices based on CBC parameters in discriminating iron status from thalassemia

Evaluation of mathematical indices based on CBC parameters in discriminating iron status from thalassemia

Customer loyalty and employee engagement: an alignment for value

PurposeThe purpose of his paper is to show that the rational and emotional triggers associated with customer loyalty and employee engagement can be measured in a macro manner through mathematical indexing. Myriad factors, among them digitalization and disintermediation, have gradually eroded the power of an elite group of senior managers to control corporate messaging and manage corporate reputation. Other stakeholder groups, particularly employees and customers, have become empowered under these current corporate conditions. For this reason, establishing high levels of customer loyalty and employee engagement are leading determinants of brand performance. These indexes can serve as powerful tools to build integrated messaging.Design/methodology/approachThis article explores the impact of customer loyalty and employee engagement on corporate performance, and identifies how these qualities can be quantifiably measured by sophisticated mathematical indexes. To do this, the authors review the factors that contribute to form corporate reputation, and how this formation process has changed over time. It places special emphasis on how senior corporate leaders have conceded branding power to employee and customer stakeholders.FindingsBy highlighting the promising early successes of companies leading this research, this paper demonstrates the potential advantages effective use of customer loyalty and employee engagement indexes can return. By acknowledging the power of these indexes, companies have the unique capability to build integrated communications solutions that address the expectations of both employees and customers, the two most contributory groups in building brand strength.Originality/valueBy shedding light on changes in the modern marketplace, this article can help shape thinking on effective ways to leverage human capital in order to maintain and grow brand and reputation.

Persistent patterns of interconnection in time-varying cortical networks estimated from high-resolution EEG recordings in humans during a simple motor act

In this work, a novel approach based on the estimate of time-varying graph indices is proposed in order to capture the basic schemes of communication within the functional brain networks during a simple motor act. To achieve this, we used a cascade of computational tools able to estimate first the electrical activity of the cortical surface by using high-resolution EEG techniques. From the cortical signals of different regions of interests we estimated the time-varying functional connectivity patterns by means of the adaptive partial directed coherence. The time-varying connectivity estimation returns a series of networks evolving during the examined task which can be summarized and interpreted with the aid of mathematical indices based on graph theory. The combination of all these methods is demonstrated on a set of high-resolution EEG data recorded from a group of healthy subjects performing a simple foot movement. It can be anticipated that the combination of the time-varying connectivity with the theoretical graph analysis is able to reveal precious information about the interconnections of the cerebral network as the significant persistence of mutual links and three-node motifs.