917 resultados para Change processes
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This study focused on obtaining a deeper understanding of the perceived learning of female professionals during workplace transition. The women's lived experiences were explored through a feminist interpretive lens (Bloom, 1998). The study also drew upon concepts from adult learning such as barriers and facilitating factors to learning, resistance, transformative learning, and multiple ways of knowing. Five women participated in a 1 -hour interview and a focus group activity. The findings are presented under the 2 broad themes of perceived learning and factors affecting learning. The most common theme of perceived learning was participants' experience of increased self-knowledge. Additionally, while learning was thought of as a struggle, it provided either an opportunity for a reexamination of goals or a reexamination of self. Reflection by participants seemed to follow two orientations and other types of perceived learning included experiential, formal, and informal learning. In the broad theme of factors affecting learning, contradictions and conflict emerged through the examination of participants' multiple subjectivities, and within their naming of many factors as both facilitating factors and barriers to learning. The factors affecting learning themes included personal relationships, professional communities, selfesteem, attitude and emotion, the gendered experience of transition, time, and finances. The final theme explored participants' view of work and their orientations to the future. A proposed model of learning during workplace transition is presented (Figure 1 ) and the findings discussed within this proposed model's framework. Additional developmental theories of women (Josselson, 1987; Levinson & Levinson, 1996), communities of practice theories (Wenger, 1998), and career resilience theories (Pulley, 1995) are discussed within the context of the proposed model. Implications to practice for career counsellors, people going through workplace transition, human resource managers and career coaches were explored. Additionally implications to theory and future areas of research are also discussed.
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This-~-case study used ethnographic-methodo-logy. --The research project was an introductory study of one adult's present and past experiences with the visual arts, exploring, in particular, the causes and processes that were related to the individual's changes of mind in order to develop an understanding of why that individual had changed her mind about what was significant in the visual arts. The individual who provided the data was a solid supporter of art galleries: female, middle-aged, graduate of university and college, married with two children, and living in an urban community. The data were collected from two informal conversational interviews and from a written description of one change experience selected by the participant. The individual had positive experiences with art during early childhood, in elementary and secondary school, during university, in avocational drawing and painting studio courses, and in aesthetic experiences. All of these experiences have had individual effects and, together, they have had a cumulative effect on the development of the participant's opinions and ideas about the visual arts. The experiences which had the most effect on the development of the individual's perspectives on the visual arts were handson studio, educational, and aesthetic experiences. Further research is suggested to investigate why some adults change their minds about the visual arts.
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Analysis of power in natural resources management is important as multiple stakeholders interact within complex, social-ecological systems. As a sub-set of these interactions, community climate change adaptation is increasingly using participatory processes to address issues of local concern. While some attention has been paid to power relations in this respect, e.g. evaluating international climate regimes or assessing vulnerability as part of integrated impact assessments, little attention has been paid to how a structured assessment of power could facilitate real adaptation and increase the potential for successful participatory processes. This paper surveys how the concept of power is currently being applied in natural resources management and links these ideas to agency and leadership for climate change adaptation. By exploring behavioural research on destructive leadership, a model is developed for informing participatory climate change adaptation. The working paper then concludes with a discussion of developing research questions in two specific areas - examining barriers to adaptation and mapping the evolution of specific participatory processes for climate change adaptation.
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Sustainability of change for improvement initiatives has been widely reported as a global challenge both within and outside health care settings. The purpose of this study was to examine the extent to which factors related to staff training and involvement, staff behaviour, and clinical leaders’ and senior leaders’ engagement and support impact the long term sustainability of practice changes for BPSO health care organizations who have implemented Registered Nursing Association of Ontario’s (RNAO) Best Practice Guidelines. Semi structured interviews with eleven organizational leaders’ from ten health care organizations were conducted to explore the unique experiences, views and perspectives on factors related to staff, clinical leaders and senior leaders and their involvement and impact on the long term sustainability of clinical practice changes within organizations who had implemented Registered Nursing Association of Ontario’s (RNAO) Best Practice Guidelines (BPGs). The interviews were coded and analyzed using thematic content analysis. Further analysis identified patterns and themes in relation to: 1. The National Health Service (NHS) Sustainability Model which was used as the theoretical framework for this research; and 2. Organizations found to have sustained practice changes longer term verses organizations that did not. Six organizations were found to have sustained practice changes while the remaining four were found to have been unsuccessful in their efforts to sustain the changes. Five major findings in relation to sustainability emerged from this study. First is the importance of early and sustained engagement and frontline staff, managers, and clinical leaders in planning, implementation and ongoing development of BPGs through use of working groups and champions models. Second is the importance of ongoing provision of formal training, tools and resources to all key stakeholders during and after the implementation phase and efforts made to embed changes in current processes whenever possible to ensure sustainability. Third is to ensure staff and management are receptive to the proposed change(s) and/or have been given the necessary background information and rationale so they understand and can support the need for the change. Fourth is the need for early and sustained fiscal and human resources dedicated to supporting BPG implementation and the ongoing use of the BPGs already in place. Fifth is ensuring clinical leaders are trusted, influential, respected and seen as clinical resources by frontline staff. The significance of this study lies in a greater understanding of the influence and impact of factors related to staff on the long term sustainability of implemented practice changes within health care organizations. This study has implications for clinical practice, policy, education and research in relation to sustainability in health care.
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Avec les avancements de la technologie de l'information, les données temporelles économiques et financières sont de plus en plus disponibles. Par contre, si les techniques standard de l'analyse des séries temporelles sont utilisées, une grande quantité d'information est accompagnée du problème de dimensionnalité. Puisque la majorité des séries d'intérêt sont hautement corrélées, leur dimension peut être réduite en utilisant l'analyse factorielle. Cette technique est de plus en plus populaire en sciences économiques depuis les années 90. Étant donnée la disponibilité des données et des avancements computationnels, plusieurs nouvelles questions se posent. Quels sont les effets et la transmission des chocs structurels dans un environnement riche en données? Est-ce que l'information contenue dans un grand ensemble d'indicateurs économiques peut aider à mieux identifier les chocs de politique monétaire, à l'égard des problèmes rencontrés dans les applications utilisant des modèles standards? Peut-on identifier les chocs financiers et mesurer leurs effets sur l'économie réelle? Peut-on améliorer la méthode factorielle existante et y incorporer une autre technique de réduction de dimension comme l'analyse VARMA? Est-ce que cela produit de meilleures prévisions des grands agrégats macroéconomiques et aide au niveau de l'analyse par fonctions de réponse impulsionnelles? Finalement, est-ce qu'on peut appliquer l'analyse factorielle au niveau des paramètres aléatoires? Par exemple, est-ce qu'il existe seulement un petit nombre de sources de l'instabilité temporelle des coefficients dans les modèles macroéconomiques empiriques? Ma thèse, en utilisant l'analyse factorielle structurelle et la modélisation VARMA, répond à ces questions à travers cinq articles. Les deux premiers chapitres étudient les effets des chocs monétaire et financier dans un environnement riche en données. Le troisième article propose une nouvelle méthode en combinant les modèles à facteurs et VARMA. Cette approche est appliquée dans le quatrième article pour mesurer les effets des chocs de crédit au Canada. La contribution du dernier chapitre est d'imposer la structure à facteurs sur les paramètres variant dans le temps et de montrer qu'il existe un petit nombre de sources de cette instabilité. Le premier article analyse la transmission de la politique monétaire au Canada en utilisant le modèle vectoriel autorégressif augmenté par facteurs (FAVAR). Les études antérieures basées sur les modèles VAR ont trouvé plusieurs anomalies empiriques suite à un choc de la politique monétaire. Nous estimons le modèle FAVAR en utilisant un grand nombre de séries macroéconomiques mensuelles et trimestrielles. Nous trouvons que l'information contenue dans les facteurs est importante pour bien identifier la transmission de la politique monétaire et elle aide à corriger les anomalies empiriques standards. Finalement, le cadre d'analyse FAVAR permet d'obtenir les fonctions de réponse impulsionnelles pour tous les indicateurs dans l'ensemble de données, produisant ainsi l'analyse la plus complète à ce jour des effets de la politique monétaire au Canada. Motivée par la dernière crise économique, la recherche sur le rôle du secteur financier a repris de l'importance. Dans le deuxième article nous examinons les effets et la propagation des chocs de crédit sur l'économie réelle en utilisant un grand ensemble d'indicateurs économiques et financiers dans le cadre d'un modèle à facteurs structurel. Nous trouvons qu'un choc de crédit augmente immédiatement les diffusions de crédit (credit spreads), diminue la valeur des bons de Trésor et cause une récession. Ces chocs ont un effet important sur des mesures d'activité réelle, indices de prix, indicateurs avancés et financiers. Contrairement aux autres études, notre procédure d'identification du choc structurel ne requiert pas de restrictions temporelles entre facteurs financiers et macroéconomiques. De plus, elle donne une interprétation des facteurs sans restreindre l'estimation de ceux-ci. Dans le troisième article nous étudions la relation entre les représentations VARMA et factorielle des processus vectoriels stochastiques, et proposons une nouvelle classe de modèles VARMA augmentés par facteurs (FAVARMA). Notre point de départ est de constater qu'en général les séries multivariées et facteurs associés ne peuvent simultanément suivre un processus VAR d'ordre fini. Nous montrons que le processus dynamique des facteurs, extraits comme combinaison linéaire des variables observées, est en général un VARMA et non pas un VAR comme c'est supposé ailleurs dans la littérature. Deuxièmement, nous montrons que même si les facteurs suivent un VAR d'ordre fini, cela implique une représentation VARMA pour les séries observées. Alors, nous proposons le cadre d'analyse FAVARMA combinant ces deux méthodes de réduction du nombre de paramètres. Le modèle est appliqué dans deux exercices de prévision en utilisant des données américaines et canadiennes de Boivin, Giannoni et Stevanovic (2010, 2009) respectivement. Les résultats montrent que la partie VARMA aide à mieux prévoir les importants agrégats macroéconomiques relativement aux modèles standards. Finalement, nous estimons les effets de choc monétaire en utilisant les données et le schéma d'identification de Bernanke, Boivin et Eliasz (2005). Notre modèle FAVARMA(2,1) avec six facteurs donne les résultats cohérents et précis des effets et de la transmission monétaire aux États-Unis. Contrairement au modèle FAVAR employé dans l'étude ultérieure où 510 coefficients VAR devaient être estimés, nous produisons les résultats semblables avec seulement 84 paramètres du processus dynamique des facteurs. L'objectif du quatrième article est d'identifier et mesurer les effets des chocs de crédit au Canada dans un environnement riche en données et en utilisant le modèle FAVARMA structurel. Dans le cadre théorique de l'accélérateur financier développé par Bernanke, Gertler et Gilchrist (1999), nous approximons la prime de financement extérieur par les credit spreads. D'un côté, nous trouvons qu'une augmentation non-anticipée de la prime de financement extérieur aux États-Unis génère une récession significative et persistante au Canada, accompagnée d'une hausse immédiate des credit spreads et taux d'intérêt canadiens. La composante commune semble capturer les dimensions importantes des fluctuations cycliques de l'économie canadienne. L'analyse par décomposition de la variance révèle que ce choc de crédit a un effet important sur différents secteurs d'activité réelle, indices de prix, indicateurs avancés et credit spreads. De l'autre côté, une hausse inattendue de la prime canadienne de financement extérieur ne cause pas d'effet significatif au Canada. Nous montrons que les effets des chocs de crédit au Canada sont essentiellement causés par les conditions globales, approximées ici par le marché américain. Finalement, étant donnée la procédure d'identification des chocs structurels, nous trouvons des facteurs interprétables économiquement. Le comportement des agents et de l'environnement économiques peut varier à travers le temps (ex. changements de stratégies de la politique monétaire, volatilité de chocs) induisant de l'instabilité des paramètres dans les modèles en forme réduite. Les modèles à paramètres variant dans le temps (TVP) standards supposent traditionnellement les processus stochastiques indépendants pour tous les TVPs. Dans cet article nous montrons que le nombre de sources de variabilité temporelle des coefficients est probablement très petit, et nous produisons la première évidence empirique connue dans les modèles macroéconomiques empiriques. L'approche Factor-TVP, proposée dans Stevanovic (2010), est appliquée dans le cadre d'un modèle VAR standard avec coefficients aléatoires (TVP-VAR). Nous trouvons qu'un seul facteur explique la majorité de la variabilité des coefficients VAR, tandis que les paramètres de la volatilité des chocs varient d'une façon indépendante. Le facteur commun est positivement corrélé avec le taux de chômage. La même analyse est faite avec les données incluant la récente crise financière. La procédure suggère maintenant deux facteurs et le comportement des coefficients présente un changement important depuis 2007. Finalement, la méthode est appliquée à un modèle TVP-FAVAR. Nous trouvons que seulement 5 facteurs dynamiques gouvernent l'instabilité temporelle dans presque 700 coefficients.
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En concevant que toute société a deux clivages dominants, l’un social et l’autre partisan, cette thèse développe une théorie sur le changement institutionnel. L’hypothèse initiale, selon laquelle les groupes sociaux créés par le premier clivage agiront pour restreindre le changement institutionnel et que le changement aura lieu lors de l’émergence d’un groupe partisan capable de croiser le clivage social, fut testée par les processus traçant les changements qui furent proposés et qui ont eu lieu au sein des conseils nominés en Amérique du Nord britannique. Ces conseils furent modifiés un bon nombre de fois, devenant les chambres secondaires de législatures provinciales avant d’être éventuellement abolies. La preuve supporte l’hypothèse, bien qu’il ne soit pas suffisant d’avoir un groupe partisan qui puisse croiser le clivage qui mène le changement : un débat partisan sur le changement est nécessaire. Ceci remet aussi en cause la théorie prédominante selon laquelle les clivages sociaux mènent à la formation de partis politiques, suggérant qu’il est plus bénéfique d’utiliser ces deux clivages pour l’étude des institutions.
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Les facteurs climatiques ainsi bien que les facteurs non-climatiques doivent être pris en considération dans le processus d'adaptation de l'agriculture aux changements et à la variabilité climatiques (CVC). Ce changement de paradigme met l'agent humain au centre du processus d'adaptation, ce qui peut conduire à une maladaptation. Suite aux débats sur les changements climatiques qui ont attiré l'attention scientifique et publique dans les années 1980 et 1990, l'agriculture canadienne est devenue un des points focaux de plusieurs études pionnières sur les CVC, un phénomène principalement dû à l’effet anthropique. Pour faire face aux CVC, ce n’est pas seulement la mitigation qui est importante mais aussi l’adaptation. Quand il s'agit de l'adaptation, c'est plutôt la variabilité climatique qui nous intéresse que simplement les augmentations moyennes des températures. L'objectif général de ce mémoire de maîtrise est d'améliorer la compréhension des processus d'adaptation et de construction de la capacité d'adaptation ai niveau de la ferme et de la communauté agricole à travers un processus ascendant, c’est-à-dire en utilisant l'approche de co-construction (qui peut également être considéré comme une stratégie d'adaptation en soi), pour développer une gestion et des outils de planification appropriés aux parties prenantes pour accroître ainsi la capacité d'adaptation de la communauté agricole. Pour y arriver, l'approche grounded theory est utilisée. Les résultats consistent de cinq catégories interdépendantes de codes élargis, conceptuellement distinctes et avec un plus grand niveau d'abstraction. La MRC du Haut-Richelieu a été choisie comme étude de cas en raison de plusieurs de ses dimensions agricoles, à part de ses conditions biophysiques favorables. 15 entrevues ont été menées avec les agriculteurs. Les résultats montrent que si certains agriculteurs ont reconnu les côtés positifs et négatifs des CVC, d’autres sont très optimistes à ce sujet comme se ils ne voient que le côté positif; d'où la nécessité de voir les deux côtés des CVC. Aussi, il y a encore une certaine incertitude liée aux CVC, qui vient de la désinformation et la désensibilisation des agriculteurs principalement en ce qui concerne les causes des CVC ainsi que la nature des événements climatiques. En outre, et compte tenu du fait que l'adaptation a plusieurs caractéristiques et types, il existe de nombreux types d'adaptation qui impliquent à la fois l'acteur privé et le gouvernement. De plus, les stratégies d'adaptation doivent être élaborées conjointement par les agriculteurs en concert avec d'autres acteurs, à commencer par les agronomes, car ils servent en tant que relais important entre les agriculteurs et d'autres parties prenantes telles que les institutions publiques et les entreprises privées.
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Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.
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There are a large number of agronomic-ecological interactions that occur in a world with increasing levels of CO2, higher temperatures and a more variable climate. Climate change and the associated severe problems will alter soil microbial populations and diversity. Soils supply many atmospheric green house gases by performing as sources or sinks. The most important of these gases include CH4, CO2 and N2O. Most of the green house gases production and consumption processes in soil are probably due to microorganisms. There is strong inquisitiveness to store carbon (C) in soils to balance global climate change. Microorganisms are vital to C sequestration by mediating putrefaction and controlling the paneling of plant residue-C between CO2 respiration losses or storage in semi-permanent soil-C pools. Microbial population groups and utility can be manipulated or distorted in the course of disturbance and C inputs to either support or edge the retention of C. Fungi play a significant role in decomposition and appear to produce organic matter that is more recalcitrant and favor long-term C storage and thus are key functional group to focus on in developing C sequestration systems. Plant residue chemistry can influence microbial communities and C loss or flow into soil C pools. Therefore, as research takings to maximize C sequestration for agricultural and forest ecosystems - moreover plant biomass production, similar studies should be conducted on microbial communities that considers the environmental situations
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The cumulative effects of global change, including climate change, increased population density and domestic waste disposal, effluent discharges from industrial processes, agriculture and aquaculture will likely continue and increases the process of eutrophication in estuarine environments. Eutrophication is one of the leading causes of degraded water quality, water column hypoxia/anoxia, harmful algal bloom (HAB) and loss of habitat and species diversity in the estuarine environment. The present study attempts to characterize the trophic condition of coastal estuary using a simple tool; trophic index (TRIX) based on a linear combination of the log of four state variables with supplementary index Efficiency Coefficient (Eff. Coeff.) as a discriminating tool. Numerically, the index TRIX is scaled from 0 to10, covering a wide range of trophic conditions from oligotrophic to eutrophic. Study area Kodungallur-Azhikode Estuary (KAE) was comparatively shallow in nature with average depth of 3.6±0.2 m. Dissolve oxygen regime in the water column was ranged from 4.7±1.3 mgL−1 in Station I to 5.9±1.4 mgL−1 in Station IV. The average nitrate-nitrogen (NO3-N) of KAE water was 470 mg m−3; values ranged from Av. 364.4 mg m−3 at Station II to Av. 626.6 mg m−3at Station VII. The mean ammonium-nitrogen (NH4 +-N) varied from 54.1 mg m−3 at Station VII to 101 mg m−3 at Station III. The average Chl-a for the seven stations of KAE was 6.42±3.91 mg m−3. Comparisons over different spatial and temporal scales in the KAE and study observed that, estuary experiencing high productivity by the influence of high degree of eutrophication; an annual average of 6.91 TRIX was noticed in the KAE and seasonal highest was observed during pre monsoon period (7.15) and lowest during post monsoon period (6.51). In the spatial scale station V showed high value 7.37 and comparatively low values in the station VI (6.93) and station VII (6.96) and which indicates eutrophication was predominant in land cover area with comparatively high water residence time. Eff. Coeff. values in the KAE ranges from −2.74 during monsoon period to the lowest of −1.98 in pre monsoon period. Present study revealed that trophic state of the estuary under severe stress and the restriction of autochthonous and allochthonous nutrient loading should be keystone in mitigate from eutrophication process
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During recent years, quantum information processing and the study of N−qubit quantum systems have attracted a lot of interest, both in theory and experiment. Apart from the promise of performing efficient quantum information protocols, such as quantum key distribution, teleportation or quantum computation, however, these investigations also revealed a great deal of difficulties which still need to be resolved in practise. Quantum information protocols rely on the application of unitary and non–unitary quantum operations that act on a given set of quantum mechanical two-state systems (qubits) to form (entangled) states, in which the information is encoded. The overall system of qubits is often referred to as a quantum register. Today the entanglement in a quantum register is known as the key resource for many protocols of quantum computation and quantum information theory. However, despite the successful demonstration of several protocols, such as teleportation or quantum key distribution, there are still many open questions of how entanglement affects the efficiency of quantum algorithms or how it can be protected against noisy environments. To facilitate the simulation of such N−qubit quantum systems and the analysis of their entanglement properties, we have developed the Feynman program. The program package provides all necessary tools in order to define and to deal with quantum registers, quantum gates and quantum operations. Using an interactive and easily extendible design within the framework of the computer algebra system Maple, the Feynman program is a powerful toolbox not only for teaching the basic and more advanced concepts of quantum information but also for studying their physical realization in the future. To this end, the Feynman program implements a selection of algebraic separability criteria for bipartite and multipartite mixed states as well as the most frequently used entanglement measures from the literature. Additionally, the program supports the work with quantum operations and their associated (Jamiolkowski) dual states. Based on the implementation of several popular decoherence models, we provide tools especially for the quantitative analysis of quantum operations. As an application of the developed tools we further present two case studies in which the entanglement of two atomic processes is investigated. In particular, we have studied the change of the electron-ion spin entanglement in atomic photoionization and the photon-photon polarization entanglement in the two-photon decay of hydrogen. The results show that both processes are, in principle, suitable for the creation and control of entanglement. Apart from process-specific parameters like initial atom polarization, it is mainly the process geometry which offers a simple and effective instrument to adjust the final state entanglement. Finally, for the case of the two-photon decay of hydrogenlike systems, we study the difference between nonlocal quantum correlations, as given by the violation of the Bell inequality and the concurrence as a true entanglement measure.
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Intensification processes in homegardens of the Nuba Mountains, Sudan, raise concerns about strongly positive carbon (C) and nutrient balances which are expected to lead to substantial element losses from these agroecosystems, in particular via soil gaseous emissions. Therefore, this thesis aimed at the quantification of C, nitrogen (N), phosphorus (P) and potassium (K) input and output fluxes with a special focus on soil gaseous losses, and the calculation of respective element balances. A further focus in this thesis was rainfall, a valuable resource for rain-fed agriculture in the Nuba Mountains. To minimize negative consequences of the high variability of rainfall, risk reducing mechanisms were developed by rain-fed farmers that may lose their efficacy in the course of climate change effects predicted for East Africa. Therefore, the second objective of this study was to examine possible changes in rainfall amounts during the last 60 years and to provide reliable risk and probability statements of rainfall-induced events of agricultural importance to rain-fed farmers in the Nuba Mountains. Soil gaseous emissions of C (in form of CO2) and N (in form of NH3 and N2O) of two traditional and two intensified homegardens were determined with a portable dynamic closed chamber system. For C gaseous emission rates reached their peak at the onset of the rainy season (2,325 g CO2-C ha-1 h-1 in an intensified garden type) and for N during the rainy season (16 g NH3-N ha-1 h-1 and 11.3 g N2O-N ha-1 h-1, in a traditional garden type). Data indicated cumulative annual emissions of 5,893 kg CO2-C ha-1, 37 kg NH3-N ha-1, and 16 kg N2O-N ha-1. For the assessment of the long-term productivity of the two types of homegardens and the identification of pathways of substantial element losses, a C and nutrient budget approach was used. In three traditional and three intensified homegardens observation plots were selected. The following variables were quantified on each plot between June and December in 2010: soil amendments, irrigation, biomass removal, symbiotic N2 fixation, C fixation by photosynthesis, atmospheric wet and dry deposition, leaching and soil gaseous emissions. Annual balances for C and nutrients amounted to -21 kg C ha-1, -70 kg N ha-1, 9 kg P ha-1 and -117 kg K ha-1 in intensified homegardens and to -1,722 kg C ha-1, -167 kg N ha-1, -9 kg P ha-1 and -74 kg K ha-1 in traditional homegardens. For the analysis of rainfall data, the INSTAT+ software allowed to aggregate long-term daily rainfall records from the Kadugli and Rashad weather stations into daily, monthly and annual intervals and to calculate rainfall-induced events of agricultural importance. Subsequently, these calculated values and events were checked for possible monotonic trends by Mann-Kendall tests. Over the period from 1970 to 2009, annual rainfall did not change significantly for either station. However, during this period an increase of low rainfall events coinciding with a decline in the number of medium daily rainfall events was observed in Rashad. Furthermore, the availability of daily rainfall data enabled frequency and conditional probability calculations that showed either no statistically significant changes or trends resulting only in minor changes of probabilities.
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This paper considers the problem of language change. Linguists must explain not only how languages are learned but also how and why they have evolved along certain trajectories and not others. While the language learning problem has focused on the behavior of individuals and how they acquire a particular grammar from a class of grammars ${cal G}$, here we consider a population of such learners and investigate the emergent, global population characteristics of linguistic communities over several generations. We argue that language change follows logically from specific assumptions about grammatical theories and learning paradigms. In particular, we are able to transform parameterized theories and memoryless acquisition algorithms into grammatical dynamical systems, whose evolution depicts a population's evolving linguistic composition. We investigate the linguistic and computational consequences of this model, showing that the formalization allows one to ask questions about diachronic that one otherwise could not ask, such as the effect of varying initial conditions on the resulting diachronic trajectories. From a more programmatic perspective, we give an example of how the dynamical system model for language change can serve as a way to distinguish among alternative grammatical theories, introducing a formal diachronic adequacy criterion for linguistic theories.
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Formalizing linguists' intuitions of language change as a dynamical system, we quantify the time course of language change including sudden vs. gradual changes in languages. We apply the computer model to the historical loss of Verb Second from Old French to modern French, showing that otherwise adequate grammatical theories can fail our new evolutionary criterion.
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Developments in the statistical analysis of compositional data over the last two decades have made possible a much deeper exploration of the nature of variability, and the possible processes associated with compositional data sets from many disciplines. In this paper we concentrate on geochemical data sets. First we explain how hypotheses of compositional variability may be formulated within the natural sample space, the unit simplex, including useful hypotheses of subcompositional discrimination and specific perturbational change. Then we develop through standard methodology, such as generalised likelihood ratio tests, statistical tools to allow the systematic investigation of a complete lattice of such hypotheses. Some of these tests are simple adaptations of existing multivariate tests but others require special construction. We comment on the use of graphical methods in compositional data analysis and on the ordination of specimens. The recent development of the concept of compositional processes is then explained together with the necessary tools for a staying- in-the-simplex approach, namely compositional singular value decompositions. All these statistical techniques are illustrated for a substantial compositional data set, consisting of 209 major-oxide and rare-element compositions of metamorphosed limestones from the Northeast and Central Highlands of Scotland. Finally we point out a number of unresolved problems in the statistical analysis of compositional processes