El fracaso en los emprendedores colombianos: una aproximación desde la logística

El objetivo de esta investigación se centra en el análisis de los factores que inciden con mayor frecuencia en el fracaso de los emprendimientos en Colombia, y considerar su proximidad con el concepto de logística como actividad elemental para el desarrollo de los emprendimientos en el país. La finalidad de esta investigación es mostrar que los patrones que conducen al fracaso, los cuales están catalogados dentro de las categorías financiera, organizacional, operativa, de entorno, de mercadeo o de recursos humanos, tienen un nivel de incidencia dentro del fracaso, por lo cual, se puede ejecutar un análisis que permita demostrar el orden de las seis categorías mencionadas según su impacto dentro del fracaso y a su vez, brindar estrategias que permitan reducir las posibilidades de fracasar en los emprendimientos.

Memoria de los consumidores expuestos a la publicidad

La psicología y la publicidad son dos disciplinas que se han complementado, la publicidad se ha visto beneficiada con esta alianza, ya que el principal aporte que le hace la psicología a la publicidad es poder determinar aquellos factores o estrategias que generan en el consumidor: atención, asociación entre marca y producto, para luego almacenarse en la memoria y así generar una posible conducta de compra en el individuo. Los medios de comunicación cumplen un papel importante en la transmisión de la información publicitaria, dependiendo del medio utilizado se enfoca la información teniendo en cuenta el campo perceptivo que recibirá la información, para lograr asociación y posterior almacenamiento en la memoria. Para poder medir la jerarquía del recuerdo en la memoria de los individuos ante la mención de una categoría de servicio de un producto, la publicidad y el mercadeo hacen uso de la prueba Top of Mind.

Genesis and classification of soils from subtropical mountain regions of Southern Brazil.

Soils formed in high mountainous regions in southern Brazil are characterized by great accumulation of organic matter (OM) in the surface horizons and variation in the degree of development. We hypothesized that soil properties and genesis are influenced by the interaction of parent materials and climate factors, which differ depending on the location along the altitudinal gradient. The goal of this study was to characterize and classify the soil, evaluate soil distribution, and determine the interactive effects of soil-forming factors in the subtropical mountain regions in Santa Catarina state. Soil samples were collected in areas known for wine production, for a total of 38 modal profiles. Based on morphological, physical, and chemical properties, soils were evaluated for pedogenesis and classified according to the Brazilian System of Soil Classification, with equivalent classes in the World Reference Basis (WRB). The results indicated that pedogenesis was strongly influenced by the parent material, weather, and relief. In the areas where basic effusive rocks (basalt) were observed, there was formation of extensive areas of clayey soils with reddish color and higher iron oxide contents. There was a predominance of Nitossolos Vermelhos and Háplicos (Nitisols), Latossolos Vermelhos (Ferralsols), and Cambissolos Háplicos (Cambisols), highlighting the pedogenetic processes of eluviation, illuviation of clay, and latosolization in conditions of year-long, large-volume, well-distributed rainfall and stability of land forms. In areas with acid effusive rocks (rhyodacites), medial or clayey soils were observed with lower iron oxide content, invariably acidic, and with low base content. For these soils, relief promoted substantial removal of material, resulting in intense rejuvenation, with a predominance of Cambissolos Háplicos (Cambisols) and lesser occurrence of Nitossolos Brunos (Nitisols) and Neossolos Litólicos (Leptosols). Soils formed from sedimentary rocks also tended to be more acidic, but with higher sand content, and the soils identified were Cambissolos Háplicos and Húmicos (Cambisols). Cluster analysis separated the soil profiles into three groups: the first and largest was formed by profiles originating from sedimentary rocks and rhyodacites; the second, smaller group was formed by four profiles in the Água Doce region (acidic rocks); and the third was formed by profiles derived from basalt. Discriminant analysis was effective in grouping soil classes. Thus, the study highlighted the importance of geology in the formation of soils in this landscape associated with climate and relief.

Acoustic identification of 12 species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Examining the Effectiveness of Discriminant Function Analysis and Cluster Analysis in Species Identification of Male Field Crickets Based on Their Calling Songs

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.

Application of discriminant function analysis and change-point problem in dating volcanic ashes

The application of Discriminant function analysis (DFA) is not a new idea in the study of tephrochrology. In this paper, DFA is applied to compositional datasets of two different types of tephras from Mountain Ruapehu in New Zealand and Mountain Rainier in USA. The canonical variables from the analysis are further investigated with a statistical methodology of change-point problems in order to gain a better understanding of the change in compositional pattern over time. Finally, a special case of segmented regression has been proposed to model both the time of change and the change in pattern. This model can be used to estimate the age for the unknown tephras using Bayesian statistical calibration

Factor analysis and discriminant validity:a brief review of some practical issues

Growth in availability and ability of modern statistical software has resulted in greater numbers of research techniques being applied across the marketing discipline. However, with such advances come concerns that techniques may be misinterpreted by researchers. This issue is critical since misinterpretation could cause erroneous findings. This paper investigates some assumptions regarding: 1) the assessment of discriminant validity; and 2) what confirmatory factor analysis accomplishes. Examples that address these points are presented, and some procedural remedies are suggested based upon the literature. This paper is, therefore, primarily concerned with the development of measurement theory and practice. If advances in theory development are not based upon sound methodological practice, we as researchers could be basing our work upon shaky foundations.

University Student Depression Inventory (USDI) : confirmatory factor analysis and review of psychometric properties

Background: The 30-item USDI is a self-report measure that assesses depressive symptoms among university students. It consists of three correlated three factors: Lethargy, Cognitive-Emotional and Academic motivation. The current research used confirmatory factor analysis to asses construct validity and determine whether the original factor structure would be replicated in a different sample. Psychometric properties were also examined. Method: Participants were 1148 students (mean age 22.84 years, SD = 6.85) across all faculties from a large Australian metropolitan university. Students completed a questionnaire comprising of the USDI, the Depression Anxiety Stress Scale (DASS) and Life Satisfaction Scale (LSS). Results: The three correlated factor model was shown to be an acceptable fit to the data, indicating sound construct validity. Internal consistency of the scale was also demonstrated to be sound, with high Cronbach Alpha values. Temporal stability of the scale was also shown to be strong through test-retest analysis. Finally, concurrent and discriminant validity was examined with correlations between the USDI and DASS subscales as well as the LSS, with sound results contributing to further support the construct validity of the scale. Cut-off points were also developed to aid total score interpretation. Limitations: Response rates are unclear. In addition, the representativeness of the sample could be improved potentially through targeted recruitment (i.e. reviewing the online sample statistics during data collection, examining the representativeness trends and addressing particular faculties within the university that were underrepresented). Conclusions: The USDI provides a valid and reliable method of assessing depressive symptoms found among university students.

Morphometric analysis of yellowfin tuna, Thunnus albacares, from the Eastern Pacific Ocean

ENGLISH: Morphometric data from yellowfin tuna, Thunnus albacares, were collected from various locations in the eastern Pacific Ocean during 1974 to 1976, to assess geographic and temporal variation of morphometric characters. The data were statistically adjusted, using allometric formulae to partition size. Discriminant analyses were applied to the adjusted morphometric characters. Yellowfin sampled from north of 15°N-20oN were different from those sampled from south of 15°N-20oN. The absence of any clinal relationships between morphometric characters and latitude or longitude suggests a pattern of somewhat distinct regional groups. These results clearly demonstrate geographic variation in morphometric characters of yellowfin in the eastern Pacific Ocean, which suggests differences between the life histories of the northern and southern groups. SPANISH: Entre 1974 Y1976 se tomaron datos morfométricos de atunes aleta amarilla, Thunmus albacares, de varios lugares en el Océano Pacífico oriental, a fin de evaluar la variación geográfica y temporal de los caracteres morfométricos. Se ajustaron los datos estadísticamente, usando fórmulas alométricas para eliminar los efectos del tamaño. Se aplicaron análisis discriminantes a los caracteres morfométricos ajustados. Aletas amarillas muestreados provenientes del norte de 15°N-20°N eran diferentes a aquellos muestreados del sur de 15°N -20°N. La falta de una relación clinal entre los caracteres morfométricos y latitud o longitud sugiere la existencia de grupos regionales algo distintos. Estos resultados demuestran claramente una variación geográfica en los caracteres morfométricos del aleta amarilla en el Océano Pacífico oriental, la cual sugiere diferencias en los ciclos vitales de los grupos del norte y del sur. (PDF contains 41 pages.)

Metrical dental analysis on golden monkey (Rhinopithecus roxellana)

Dental variation in the Chinese golden monkey (Rhinopithecus roxellana) is here evaluated by univariate, bivariate, and multivariate analyses. Allometric analyses indicate that canines and P3s are positively, but other dimensions negatively scaled to mandible and maxilla, and to body size. With the exception of the mesiodistal dimensions of I-1 and M-3, and the buccolingual dimension of Pq, mandibular dental variables show similar scaling relative to body size. Analysis of residuals shows that males have significantly larger canine, P-3 and buccolingual dimensions of the postcanine teeth (M-2 and M-3) than females. A significant difference in shape between the sexes is found in the buccolingual dimension of the upper teeth, but not in the mandible. Unlike the situation in some other species, Female golden monkeys do nor exhibit relatively larger postcanine teeth than males, in fact, the reverse is true, especially for M(2)s and M(3)s. The fact that most of the dental variables show low negative allometry to body size might be related a cold environment that has led to the development of larger body size with I-educed energy loss. When the raw data are examined by Discriminant Function Analysis the sexes are clearly distinguishable.

Fingerprint Volatile Organic Compounds (VOC) analysis in Goat’s Milk and Halloumi Cheese as Marker for Authentication of Region of Origin

Goats’ milk is responsible for unique traditional products such as Halloumi cheese. The characteristics of Halloumi depend on the original features of the milk and on the conditions under which the milk has been produced such as feeding regime of the animals or region of production. Using a range of milk (33) and Halloumi (33) samples collected over a year from three different locations in Cyprus (A, Anogyra; K, Kofinou; P, Paphos), the potential for fingerprint VOC analysis as marker to authenticate Halloumi was investigated. This unique set up consists of an in-injector thermo desorption (VOCtrap needle) and a chromatofocusing system based on mass spectrometry (VOCscanner). The mass spectra of all the analyzed samples are treated by multivariate analysis (Principle component analysis and Discriminant functions analysis). Results showed that the highland area of product (P) is clearly identified in milks produced (discriminant score 67%). It is interesting to note that the higher similitude found on milks from regions “A” and “K” (with P being distractive; discriminant score 80%) are not ‘carried over’ on the cheeses (higher similitude between regions “A” and “P”, with “K” distinctive). Data have been broken down into three seasons. Similarly, the seasonality differences observed in different milks are not necessarily reported on the produced cheeses. This is expected due to the different VOC signatures developed in cheeses as part of the numerous biochemical changes during its elaboration compared to milk. VOC however it is an additional analytical tool that can aid in the identification of region origin in dairy products.

Video-based analysis of Gait pathologies

L’analyse de la marche a émergé comme l’un des domaines médicaux le plus im- portants récemment. Les systèmes à base de marqueurs sont les méthodes les plus fa- vorisées par l’évaluation du mouvement humain et l’analyse de la marche, cependant, ces systèmes nécessitent des équipements et de l’expertise spécifiques et sont lourds, coûteux et difficiles à utiliser. De nombreuses approches récentes basées sur la vision par ordinateur ont été développées pour réduire le coût des systèmes de capture de mou- vement tout en assurant un résultat de haute précision. Dans cette thèse, nous présentons notre nouveau système d’analyse de la démarche à faible coût, qui est composé de deux caméras vidéo monoculaire placées sur le côté gauche et droit d’un tapis roulant. Chaque modèle 2D de la moitié du squelette humain est reconstruit à partir de chaque vue sur la base de la segmentation dynamique de la couleur, l’analyse de la marche est alors effectuée sur ces deux modèles. La validation avec l’état de l’art basée sur la vision du système de capture de mouvement (en utilisant le Microsoft Kinect) et la réalité du ter- rain (avec des marqueurs) a été faite pour démontrer la robustesse et l’efficacité de notre système. L’erreur moyenne de l’estimation du modèle de squelette humain par rapport à la réalité du terrain entre notre méthode vs Kinect est très prometteur: les joints des angles de cuisses (6,29◦ contre 9,68◦), jambes (7,68◦ contre 11,47◦), pieds (6,14◦ contre 13,63◦), la longueur de la foulée (6.14cm rapport de 13.63cm) sont meilleurs et plus stables que ceux de la Kinect, alors que le système peut maintenir une précision assez proche de la Kinect pour les bras (7,29◦ contre 6,12◦), les bras inférieurs (8,33◦ contre 8,04◦), et le torse (8,69◦contre 6,47◦). Basé sur le modèle de squelette obtenu par chaque méthode, nous avons réalisé une étude de symétrie sur différentes articulations (coude, genou et cheville) en utilisant chaque méthode sur trois sujets différents pour voir quelle méthode permet de distinguer plus efficacement la caractéristique symétrie / asymétrie de la marche. Dans notre test, notre système a un angle de genou au maximum de 8,97◦ et 13,86◦ pour des promenades normale et asymétrique respectivement, tandis que la Kinect a donné 10,58◦et 11,94◦. Par rapport à la réalité de terrain, 7,64◦et 14,34◦, notre système a montré une plus grande précision et pouvoir discriminant entre les deux cas.

Morphometric analysis of the venom gland in worker bees of Apis mellifera (Hymenoptera : Apidae) from the pantanal region of Mato Grosso do Sul

In Apis mellifera the acid or venom gland is composed of secretory cells that surround a channel that opens into a reservoir devoid of musculature. This gland can at times present apical branching. In this study we recorded the frequency of branched venom glands in workers of Africanized bees (Apis mellifera Linnaeus) from six localities in the Pantanal region of Mato Grosso do Sul, and analyzed the relation among the length of the main duct, the length of the duct from the reservoir to the beginning of branching, the length of the branched segment (when present) and the total length of the gland. We sought to determine the probable genotypes of the bees from each population by using the model proposed by Alves-Junior. The frequency of branched glands varied from 50% to 83% in the worker bees coming from those places, indicating that this characteristic is primitive in these bees. The results of the Analysis of Discriminant Functions indicated significant differences in the morphometrical segments of the venom gland (Wilk's Lambda = 0.065; F-(27,F-30) = 4.507; P < 0.001), and permitted a differentiation of the populations studied. The genotypes inferred for the bees of each locality agree with the results obtained in the Analysis of Discriminant Functions and form three distinct groups, with some overlapping areas among them. In all of the populations considered the phenotype largevenom gland was predominant. It is inferred that bees with this phenotype (venom gland larger than S. 15 mm) have Gm(1) Gm(1) genotype, being therefore homozygotes for the major alleles and also for the modifier genes that codify this morphological trait. The high frequency of worker bees with large venom gland in all the places considered makes viable the development of a selection program in order to obtain bees with longer venom glands, aimed at the commercial production of venom by the beekeepers of the Pantanal region of Mato Grosso do Sul.

Discrimination of production environments of specialty coffees by means of stable isotopes and discriminant model

The south of Minas Gerais, Brazil stands out among various regions through its capacity for production of specialty coffees. Its potential, manifested through being one of the most award-winning Brazilian regions in recent years, has been recognized by the Cup of Excellence (COE). With the evident relationship between product quality and the environment in mind, the need arises for scientific studies to provide a foundation for discrimination of product origin, creating new methods for combating possible fraud. The aim of this study was to evaluate the use of carbon and nitrogen isotopes in discrimination of production environments of specialty coffees from the Serra da Mantiqueira of Minas Gerais by means of the discriminant model. Coffee samples were composed of ripe yellow and red fruits collected manually at altitudes below 1,000 m, from 1,000 to 1,200 m and above 1,200 m. The yellow and red fruits were subjected to dry processing and wet processing, with five replications. A total of 119 samples were used for discrimination of specialty coffee production environments by means of stable isotopes and statistical modeling. The model generated had an accuracy rate of 89% in discrimination of environments and was composed of the isotope variables of δ15N, δ13C, %C, %N, δD, δ18O (meteoric water) and sensory analysis scores. In addition, for the first time, discrimination of environments on a local geographic scale, within a single municipality, was proposed and successfully concluded. This shows that isotope analysis is an effective method in verifying geographic origin for specialty coffees.