956 resultados para DM FC
Resumo:
Determinar la validez concurrente del Sistema de Observación de Tiempo de Instrucción de Condición Física (SOFIT) a través de acelerometría, como método para medir los niveles de actividad física (AF) de los escolares de 1º a 9º durante la clase de educación física en tres colegios públicos de Bogotá, Colombia. Estudio transversal entre Octubre de 2014 y Marzo de 2015. La medición se realizó en tres colegios públicos de Bogotá. Participaron 48 estudiantes (25 niñas; 23 niños), entre 5 y 17 años, seleccionados de acuerdo al protocolo de SOFIT. El resultado se categoriza en porcentaje de tiempo en comportamiento sedentario, AF moderada, AF vigorosa, y AF moderada a vigorosa. Se validó utilizando como patrón de oro la acelerometría en las mismas categorías. Se realizó diferencia de medias, regresión lineal y modelo de efectos fijos. La correlación entre SOFIT y acelerometría fue buena para AF moderada (rho=,958; p=0,000), AF vigorosa (rho=,937; p=0,000) y AF de moderada a vigorosa (rho=0,962; p=0,000). Al igual que utilizando un modelo de efectos fijos, AF moderada (β1=0,92; p=0,00), vigorosa (β1=0,94; p=0,00) y AF de moderada a vigorosa (β1=0,95; p=0,00), mostrando ausencia de diferencias significativas entre los dos métodos para la medición de los niveles de AF. El comportamiento sedentario correlacionó positivamente en Spearman (rho=,0965; p=0,000), El sistema SOFIT demostró ser válido para medir niveles de AF en clases de educación física, tras buena correlación y concordancia con acelerometría. SOFIT es un instrumento de fácil acceso y de bajo costo para la medición de la AF durante las clases de educación física en el contexto escolar y se recomienda su uso en futuros estudios.
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Objetivo: determinar los niveles de actividad física (AF) de niños y adolescentes entre 10 y 17 años durante los periodos de recreo escolar en un colegio distrital de Bogotá. Método: estudio de corte transversal en un colegio distrital de la localidad de Puente Aranda en Bogotá. Fueron observados a través del sistema de observación de juego y de actividad en el tiempo libre en jóvenes (SOPLAY) los niveles y tipos de AF de niños y adolescentes en los periodos de recreo durante tres semanas, utilizando una condición de observación diferente para cada semana. Adicionalmente, las condiciones del contexto de las áreas recreo deportivas fueron evaluadas. Resultados: las prevalencias de escolares sedentarios fueron de 52,4 %, 77,3 % y 64,9 % durante la 1ª, 2ª y 3ª semana respectivamente. El sexo femenino fue más sedentario con el masculino (57 %, 82 % y 73 % vs 45 %, 70 % y 54 %) para cada semana observada. Se obtuvieron diferencias significativas (p<0,05) en los niveles de AF de los escolares. Conclusión: niños y adolescentes presentan elevadas prevalencias de sedentarismo siendo las actividades más frecuentes estar sentado, de pie o acostado durante los periodos de recreo. El sexo masculino mostró porcentajes superiores de participación en AF moderadas vigorosas. Las áreas recreo deportivas no contaban con condiciones del contexto relacionadas con disponibilidad de equipamiento para realizar AF ni existencia de actividades organizadas. Son necesarios programas e intervenciones eficaces que promuevan la AF en niños y adolescentes durante el recreo de la jornada escolar.
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Objetivo: Establecer la relación entre la exposición ocupacional a altas temperaturas o sobrecarga térmica con el comportamiento fisiológico, metabólico y electrocardiográfico. Métodos: estudio de corte transversal, donde se incluyeron dos grupos (expuesto y no expuesto a altas temperaturas) en una empresa minera, en el departamento de Boyacá, Colombia, en el año 2016. El número de participantes fue de 160 trabajadores del género masculino, grupo expuesto (n=86) y grupo no expuesto (n=74). La exposición ocupacional a sobrecarga térmica se evaluó con el índice de temperatura de globo y bulbo húmedo (TGBH), el comportamiento fisiológico con el índice de costo cardiaco relativo (ICCR) con mediciones de frecuencia cardiaca (FC), el comportamiento metabólico con la determinación del colesterol total (CT), colesterol de alta densidad (C-HDL), colesterol de baja densidad (C-LDL), triglicéridos (TG) y glicemia basal (GL). Las alteraciones electrocardiográficas con la toma de Electrocardiograma de 12 derivaciones. También fueron evaluadas variables antropométricas, tensión arterial, hábitos y antecedentes de enfermedad cardiovascular en ambos grupos. Resultados: incrementos significativos del ICCR (p<0.001) y la carga física (p<0.001) fueron encontrados en los trabajadores expuestos a altas temperaturas. Los índices lipídicos y glicemia, así como los antecedentes personales cardiovasculares, IMC, consumo de cigarrillo y consumo de alcohol, no mostraron significancia. El antecedente familiar de ACV (p=0.043) y el EKG alterado (p=0.011) mostraron una asociación significativa con la exposición a altas temperaturas. El modelo de regresión lineal múltiple explicó la relación entre el incremento del ICCR y la exposición a altas temperaturas (β=4,213, IC 95%: 1.57,6.85) ajustado por variables fisiológicas y electrocardiográficas. Conclusiones: La exposición ocupacional a altas temperaturas, presenta asociación con las alteraciones cardiovasculares a nivel fisiológico y electrocardiográfico, aumentando el ICCR y la carga física de trabajo (GE trabajo).
Resumo:
Antecedentes y objetivos: La hiperhidrosis primaria afecta el 2,8% de la población de Estados Unidos. Condición que impacta el desarrollo social de los individuos afectados, ocasionando fobia social. Existen opciones disponibles para el tratamiento de la hiperhidrosis incluyendo medicamentos tópico, sistémico, inyectable y quirúrgico. El objetivo de ésta revisión sistemática de la literatura es determinar la efectividad y seguridad de los dispositivos de emisión de microondas, radiofrecuencia no ablativa y sistema de ultrasonido microfocalizado para el tratamiento de la hiperhidrosis primaria. Materiales y métodos: Se realizó una revisión sistemática de la literatura de artículos obtenidos de bases de datos: Medline, Cochrane, Embase, Ovid y Scielo. Se incluyeron ensayos clínicos aleatorizados controlados, ensayos cuasiexperimentales desde el 2011; donde evaluaran el uso de estos dispositivos en el manejo de hiperhidrosis primaria. Resultados: Se seleccionaron 21 artículos en total. Se encontró que con los tres dispositivos se logra una reducción significativa a puntajes entre 1 y 2 de la escala de Severidad de la Hiperhidrosis; en 3 estudios se encontró mejoría en la calidad de vida; los eventos adversos fueron transitorios, siendo más frecuentes con el dispositivo de emisión de microondas. Conclusión: Primera revisión sistemática de la literatura sobre el efecto de estos tres dispositivos en el manejo de hiperhidrosis. Se espera aportar a la literatura existente una recomendación acerca de la efectividad y seguridad de estos dispositivos para que sea aplicado en los pacientes con diagnóstico de hiperhidrosis primaria.
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Introducción: El monitoreo hemodinámico es una herramienta para diagnosticar el choque cardiogénico y monitorear la respuesta al tratamiento; puede ser invasivo, mínimamente invasivo o no invasivo. Se realiza rutinariamente con catéter de arteria pulmonar (CAP) o catéter de Swan Ganz; nuevas técnicas de monitoreo hemodinámico mínimamente invasivo tienen menor tasa de complicaciones. Actualmente se desconoce cuál técnica de monitoreo cuenta con mayor seguridad en el paciente con choque cardiogénico. Objetivo: Evaluar la seguridad del monitoreo hemodinámico invasivo comparado con el mínimamente invasivo en pacientes con choque cardiogénico en cuidado intensivo adultos. Diseño: Revisión sistemática de la literatura. Búsqueda en Pubmed, EMBASE, OVID - Cochrane Library, Lilacs, Scielo, registros de ensayos clínicos, actas de conferencias, repositorios, búsqueda de literatura gris en Google Scholar, Teseo y Open Grey hasta agosto de 2016, publicados en inglés y español. Resultados: Se identificó un único estudio con 331 pacientes críticamente enfermos que comparó el monitoreo hemodinámico con CAP versus PiCCO que concluyó que después de la corrección de los factores de confusión, la elección del tipo de monitoreo no influyó en los resultados clínicos más importantes en términos de complicaciones y mortalidad. Dado que se incluyeron otros diagnósticos, no es posible extrapolar los resultados sólo a choque cardiogénico. Conclusión: En la literatura disponible no hay evidencia de que el monitoreo hemodinámico invasivo comparado con el mínimamente invasivo, en pacientes adultos críticamente enfermos con choque cardiogénico, tenga diferencias en cuanto a complicaciones y mortalidad.
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We propose a new password-based 3-party protocol with a formal security proof in the standard model. Under reasonable assumptions we show that our new protocol is more efficient than the recent protocol of Abdalla and Pointcheval (FC 2005), proven in the random oracle model. We also observe some limitations in the model due to Abdalla, Fouque and Pointcheval (PKC 2005) for proving security of such protocols.
Resumo:
Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
Resumo:
Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
Resumo:
The value of soil evidence in the forensic discipline is well known. However, it would be advantageous if an in-situ method was available that could record responses from tyre or shoe impressions in ground soil at the crime scene. The development of optical fibres and emerging portable NIR instruments has unveiled a potential methodology which could permit such a proposal. The NIR spectral region contains rich chemical information in the form of overtone and combination bands of the fundamental infrared absorptions and low-energy electronic transitions. This region has in the past, been perceived as being too complex for interpretation and consequently was scarcely utilized. The application of NIR in the forensic discipline is virtually non-existent creating a vacancy for research in this area. NIR spectroscopy has great potential in the forensic discipline as it is simple, nondestructive and capable of rapidly providing information relating to chemical composition. The objective of this study is to investigate the ability of NIR spectroscopy combined with Chemometrics to discriminate between individual soils. A further objective is to apply the NIR process to a simulated forensic scenario where soil transfer occurs. NIR spectra were recorded from twenty-seven soils sampled from the Logan region in South-East Queensland, Australia. A series of three high quartz soils were mixed with three different kaolinites in varying ratios and NIR spectra collected. Spectra were also collected from six soils as the temperature of the soils was ramped from room temperature up to 6000C. Finally, a forensic scenario was simulated where the transferral of ground soil to shoe soles was investigated. Chemometrics methods such as the commonly known Principal Component Analysis (PCA), the less well known fuzzy clustering (FC) and ranking by means of multicriteria decision making (MCDM) methodology were employed to interpret the spectral results. All soils were characterised using Inductively Coupled Plasma Optical Emission Spectroscopy and X-Ray Diffractometry. Results were promising revealing NIR combined with Chemometrics is capable of discriminating between the various soils. Peak assignments were established by comparing the spectra of known minerals with the spectra collected from the soil samples. The temperature dependent NIR analysis confirmed the assignments of the absorptions due to adsorbed and molecular bound water. The relative intensities of the identified NIR absorptions reflected the quantitative XRD and ICP characterisation results. PCA and FC analysis of the raw soils in the initial NIR investigation revealed that the soils were primarily distinguished on the basis of their relative quartz and kaolinte contents, and to a lesser extent on the horizon from which they originated. Furthermore, PCA could distinguish between the three kaolinites used in the study, suggesting that the NIR spectral region was sensitive enough to contain information describing variation within kaolinite itself. The forensic scenario simulation PCA successfully discriminated between the ‘Backyard Soil’ and ‘Melcann® Sand’, as well as the two sampling methods employed. Further PCA exploration revealed that it was possible to distinguish between the various shoes used in the simulation. In addition, it was possible to establish association between specific sampling sites on the shoe with the corresponding site remaining in the impression. The forensic application revealed some limitations of the process relating to moisture content and homogeneity of the soil. These limitations can both be overcome by simple sampling practices and maintaining the original integrity of the soil. The results from the forensic scenario simulation proved that the concept shows great promise in the forensic discipline.
Resumo:
This overview focuses on the application of chemometrics techniques for the investigation of soils contaminated by polycyclic aromatic hydrocarbons (PAHs) and metals because these two important and very diverse groups of pollutants are ubiquitous in soils. The salient features of various studies carried out in the micro- and recreational environments of humans, are highlighted in the context of the various multivariate statistical techniques available across discipline boundaries that have been effectively used in soil studies. Particular attention is paid to techniques employed in the geosciences that may be effectively utilized for environmental soil studies; classical multivariate approaches that may be used in isolation or as complementary methods to these are also discussed. Chemometrics techniques widely applied in atmospheric studies for identifying sources of pollutants or for determining the importance of contaminant source contributions to a particular site, have seen little use in soil studies, but may be effectively employed in such investigations. Suitable programs are also available for suggesting mitigating measures in cases of soil contamination, and these are also considered. Specific techniques reviewed include pattern recognition techniques such as Principal Components Analysis (PCA), Fuzzy Clustering (FC) and Cluster Analysis (CA); geostatistical tools include variograms, Geographical Information Systems (GIS), contour mapping and kriging; source identification and contribution estimation methods reviewed include Positive Matrix Factorisation (PMF), and Principal Component Analysis on Absolute Principal Component Scores (PCA/APCS). Mitigating measures to limit or eliminate pollutant sources may be suggested through the use of ranking analysis and multi criteria decision making methods (MCDM). These methods are mainly represented in this review by studies employing the Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and its associated graphic output, Geometrical Analysis for Interactive Aid (GAIA).
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An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE and GAIA. Initial analyses established high, low and moderate traffic scenarios as well as low, low to moderate, moderate, high and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75µm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 - >300 µm, whereas metal concentrations in finer size range of <1-75 µm were not affected. As practical implications, solids <1 µm and organic matter from 1 - >300 µm can be targeted for removal of Ni, Cu, Pb, Cd, Cr and Zn from build-up whilst organic matter from <1 - >300 µm can be targeted for removal of Cd, Cr, Pb and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.
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Heart failure is a complex disorder, characterized by activation of the sympathetic nervous system, leading to dysregulated Ca2+ homeostasis in cardiac myocytes and tissue remodeling. In a variety of diseases, cardiac malfunction is associated with aberrant fluxes of Ca2+ across both the surface membrane and the internal Ca2+ store, the sarcoplasmic reticulum (SR). One prominent hypothesis residues is that in heart failure, the activity of the ryanodine receptor (RyR2) Ca2+ release channel in the SR is increased due to excess phosphorylation and that this contributes to excess SR Ca2+ leak in diastole, reduced SR Ca2+ load and decreased contractility (Huke & Bers, 2008). There is controversy over which serine residues in RyR2 are hyperphosphorylated in animal models of heart failure and whether this is via the CaMKII or the PKA-linked signaling pathway. S2808, S2814 and S2030 in RyR2 have been variously claimed to be hyperphosphorylated. Our aim was to examine the degree of phosphorylation of these residues in RyR2 from failing human hearts. The use of human tissue was approved by the Human Research Ethics Committee, The Prince Charles Hospital, EC28114. Left ventricular tissue samples were obtained from an explanted heart of a patient with endstage heart failure (Emery Dreifuss Muscular Dystrophy with cardiomyopathy) and non-failing tissue was from a patient with cystic fibrosis undergoing heart-lung transplantation with no history of heart disease. SR vesicles were prepared as described by Laver et al. (1995) and examined with SDS-Page and Western Blot. Transferred proteins were probed with antibodies to detect total protein phosphorylation, phosphorylation of RyR2 serine residues S2808, S2814, S2030 and for the key proteins calsequestrin, triadin, junctin and FKBP12.6. To avoid membrane stripping artifact, each membrane was exposed to one phosphorylation-specific antibody and signal densities quantified using Bio-Rad Quantity One software. We found no distinguishable difference between failing and healthy hearts in the protein expression levels of RyR2, triadin, junctin or calsequestrin. We found an expected upregulation of total RyR2 phosphorylation in the failing heart sample, compared to a matched amount of RyR2 (quantified using densiometry) in healthy heart. Probing with antibodies detecting only the phosphorylated form of the specific RyR2 residues showed that the increase in total RyR2 phosphorylation in the failing heart was due to hyperphosphorylation of S2808 and S2814. We found that S2030 phosphorylation levels were unchanged in human heart failure. Interestingly, we found that S2030 has a basal level of phosphorylation in the healthy human heart, different from the absence of basal phosphorylation recently reported in rodent heart (Huke & Bers, 2008). Finally, preliminary results indicate that less FKBP 12.6 is associated with RyR2 in the failing heart, possibly as a consequence of PKA activation. In conclusion, residues S2808 and S2814 are hyperphosphorylated in human heart failure, presumably due to upregulation of the CaMKII and/or PKA signaling pathway as a result of chronic activation of the sympathetic nervous system. Such changes in RyR2 phosphorylation are believed to contribute to the leaky RyR2 phenotype associated with heart failure, which increases the incidence of arrhythmia and contributes to the severely impaired contractile performance of the failing heart. Huke S & Bers DM. (2008). Ryanodine receptor phosphorylation at serine 2030, 2808 and 2814 in rat cardiomyocytes. Biochemical and Biophysical Research Communications 376, 80-85. Laver DR, Roden LD, Ahern GP, Eager KR, Junankar PR & Dulhunty AF. (1995). Cytoplasmic Ca2+ inhibits the ryanodine receptor from cardiac muscle. Journal of Membrane Biology 147, 7-22. Proceedings
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This paper examines the linkages between diversity management (DM), innovation and high performance in social enterprises. These linkages are explicated beyond traditional framing of DM limited to workforce composition, to include discussions of innovation through networked diversity practices; reconciliation; and funding options. The paper draws upon a UK-based national survey and the case study data. Multiple data collection methods were used, including semi-structured interviews, questionnaires and workshops with participant observation. NVivo and SPSS software packages were utilized in order to analyse the qualitative and quantitative data, respectively. We used thematic coding and cropping techniques in analysing the case studies in the paper. A broad range of conflicting and supporting literature was enfolded into the conversations and discussion. The paper demonstrates that social enterprises exhibit unique characteristics in terms of size and location, as well as their double remit to add value both economically and socially. As a conclusion, we argue for social enterprises to consider options for DM in the interests of maximization of innovation and business performance. We contend that further research is needed to describe how social entrepreneurs draw upon their various ‘diversity resources’ in the process of innovation
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Human hair fibres are ubiquitous in nature and are found frequently at crime scenes often as a result of exchange between the perpetrator, victim and/or the surroundings according to Locard's Principle. Therefore, hair fibre evidence can provide important information for crime investigation. For human hair evidence, the current forensic methods of analysis rely on comparisons of either hair morphology by microscopic examination or nuclear and mitochondrial DNA analyses. Unfortunately in some instances the utilisation of microscopy and DNA analyses are difficult and often not feasible. This dissertation is arguably the first comprehensive investigation aimed to compare, classify and identify the single human scalp hair fibres with the aid of FTIR-ATR spectroscopy in a forensic context. Spectra were collected from the hair of 66 subjects of Asian, Caucasian and African (i.e. African-type). The fibres ranged from untreated to variously mildly and heavily cosmetically treated hairs. The collected spectra reflected the physical and chemical nature of a hair from the near-surface particularly, the cuticle layer. In total, 550 spectra were acquired and processed to construct a relatively large database. To assist with the interpretation of the complex spectra from various types of human hair, Derivative Spectroscopy and Chemometric methods such as Principal Component Analysis (PCA), Fuzzy Clustering (FC) and Multi-Criteria Decision Making (MCDM) program; Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Geometrical Analysis for Interactive Aid (GAIA); were utilised. FTIR-ATR spectroscopy had two important advantages over to previous methods: (i) sample throughput and spectral collection were significantly improved (no physical flattening or microscope manipulations), and (ii) given the recent advances in FTIR-ATR instrument portability, there is real potential to transfer this work.s findings seamlessly to on-field applications. The "raw" spectra, spectral subtractions and second derivative spectra were compared to demonstrate the subtle differences in human hair. SEM images were used as corroborative evidence to demonstrate the surface topography of hair. It indicated that the condition of the cuticle surface could be of three types: untreated, mildly treated and treated hair. Extensive studies of potential spectral band regions responsible for matching and discrimination of various types of hair samples suggested the 1690-1500 cm-1 IR spectral region was to be preferred in comparison with the commonly used 1750-800 cm-1. The principal reason was the presence of the highly variable spectral profiles of cystine oxidation products (1200-1000 cm-1), which contributed significantly to spectral scatter and hence, poor hair sample matching. In the preferred 1690-1500 cm-1 region, conformational changes in the keratin protein attributed to the α-helical to β-sheet transitions in the Amide I and Amide II vibrations and played a significant role in matching and discrimination of the spectra and hence, the hair fibre samples. For gender comparison, the Amide II band is significant for differentiation. The results illustrated that the male hair spectra exhibit a more intense β-sheet vibration in the Amide II band at approximately 1511 cm-1 whilst the female hair spectra displayed more intense α-helical vibration at 1520-1515cm-1. In terms of chemical composition, female hair spectra exhibit greater intensity of the amino acid tryptophan (1554 cm-1), aspartic and glutamic acid (1577 cm-1). It was also observed that for the separation of samples based on racial differences, untreated Caucasian hair was discriminated from Asian hair as a result of having higher levels of the amino acid cystine and cysteic acid. However, when mildly or chemically treated, Asian and Caucasian hair fibres are similar, whereas African-type hair fibres are different. In terms of the investigation's novel contribution to the field of forensic science, it has allowed for the development of a novel, multifaceted, methodical protocol where previously none had existed. The protocol is a systematic method to rapidly investigate unknown or questioned single human hair FTIR-ATR spectra from different genders and racial origin, including fibres of different cosmetic treatments. Unknown or questioned spectra are first separated on the basis of chemical treatment i.e. untreated, mildly treated or chemically treated, genders, and racial origin i.e. Asian, Caucasian and African-type. The methodology has the potential to complement the current forensic analysis methods of fibre evidence (i.e. Microscopy and DNA), providing information on the morphological, genetic and structural levels.
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Many studies carried out in relation to construction procurement methods reveal evidence of a need to change of culture and attitude in the construction industry. This culture change would transition from traditional adversarial relationships to cooperative and collaborative relationships. Relational contracting approaches, such as partnering and relationship management, are business strategies whereby client, commercial participants’ and stakeholders’ objectives are aligned for mutual benefit. The efficacy of relationship management in the client and contractor groups is proven and well documented. However, the industry has a slow implementation of relational contracting down the value chain. This paper reports the findings of an empirical study which examined the practices and prerequisites for relationship management implementation success and for supply chain engagement to develop. Questionnaire survey, interviews and case studies were conducted with Australian contracting organisations in this study. The study reveals that the adaption of relational contracting approach in the supply chain is found to be limited and contractors still prefer to keep suppliers and subcontractors at arm’s length. Findings also show that the degree of match and mismatch between organizational structuring and organizational process is found to have an impact on staff’s commitment level and performance effectiveness.