In the present work, methodology of statistical analysis of change evolved by Kundzewicz and Robson (204) is revised to obtain a robust methodology named as “Comprehensive Aproach” which addresses research gaps of earlier method, as also those found by literature review. Main aspects of the revised method are: 1) importance of graphical representations as first step, in which, if line spectrum has constant spectral density function then time series is random and no need of further trend detection, 2) importance of computation of statistical parameters of data for deciding type of step change test to be used and for cross checking results of exploratory data analysis (EDA), 3) application of EDA, statistical parameters and checking assumption(s) about the data by statistical test(s) is suggested and also results of these steps can be used to cross check results of each other, 4) suggested basis for selection of step change test(s) i.e. evaluation of two aspects of step change viz. detection and location of step change, 5) suggested basis for selection of trend detection tests i.e. evaluation of all four aspects of trend viz. magnitude, statistical significance, beginning and end of trend and nature of trend, 6) evaluation of regional significance is suggested as essential wherever applicable. The revised method i.e. “Comprehensive Approach” is applied for the trend detection of rainfall of seven homogenous rainfall regions and al India at annual, monthly and seasonal temporal scales for three time periods 1901-203, 1948-203 and 1970-203. Between 100 N to 300 N, there was marked increase in precipitation from 190 to 1950s, but decrease after about 1970 (Trenberth et al., 207). Thus starting years of three time periods are selected as 1901, 1948 and 1970. To have similarity of end year, in analysis periods given in chapters 1, 2 and chapters 3, 4; their end years are kept close to each other i.e. end year of analysis periods is 203 in chapters 1, 2 and end year of analysis periods is 204 in chapters 3, 4. Thus 203 are considered as common end year of three time periods. Burn and Elnur (202) sugested that least number of years required for ensuring statistical validity of results of trend detection are 25 years. So in the third time period (1970-203), the duration is 34 years which is more than 25 years. Three time periods are having data of 103 years (1901-203), 56 years (1948-203) and 34 years (1970- 203) so effect of different time durations on trend detection analysis results is studied. Also temporal scales used in trend detection analysis are annual, monthly and seasonal (4 seasons) thus presence of trend is assessed in these main temporal scales. Results of the analysis showed that, statistically significant trends are found in: 1) winter rainfall time series of peninsular India (PENIN) region for the time period 1901-203, 2) pre-monsoon rainfall time series of north west India (NWIND) and central north east India (CNEIN) regions for the time period 1948-203, 3) monsoon rainfall time series of west central India (WCIND) region for the time period 1948-203, 4) August month rainfall time series of north east India (NEIND) region for the time period 1901-203, 5) June month rainfall time series of NEIND region for the time period 1948-203, 6) Also regionally significant trends are detected in pre- monsoon rainfall time series of five homogeneous regions for the time period 1948-203. Regionally significant trends are detected in pre-monsoon rainfall time series of five homogeneous regions for the time period 1948-203. But effect of cross correlation between rainfall time series of stations of subdivisions and between the sub-divisions in a region is not accounted in the field/regional significance evaluation and Hegel et al. (207) suggested that reactions to external forcing in trends of regional precipitation trends exhibit weak signal to noise ratios and likely to exhibit strong variations in space because of dependency of precipitation on geographic parameters like pornography and atmospheric circulation. Thus attribution of precipitation is more difficult. Also Saikranthi et al. (2013) suggested that homogeneity of rainfall zones may change in future. So, attribution of trends detected in pre-monsoon rainfall time series of five homogeneous regions was not possible. The results of statistically significant trends are confirmed by smoothing curves, innovative trend analysis plots and Sen.’s slope estimates. Contributions by present trend detection study on rainfall of homogenous regions by using “Comprehensive Approach” method are: 1) modification of guidelines of statistical analysis of change to evolve a robust method termed as “Comprehensive Approach”, 2) systematic trend detection analysis is performed pertaining to the rainfall of core monsoon India (CORIN) region and homogeneous India (HOMIN) region, which was not done earlier, 3) systematic trend detection analysis is performed on the rainfall of al India and seven homogenous regions concurrently for aforesaid temporal scales and time periods (except regional significance evaluation only for five homogeneous regions), which was not done earlier, 4) Man Kendal test with block bootstrapping approach (MKBBS) test (not effected by serial correlation) is used for trend detection of serially correlated data and Man Kendal (MK) test is used for trend detection of serially uncorrelated data. Sen.’s slope is used for evaluation of trend magnitude, 5) evaluation of field/regional significance of trends in rainfall over five homogenous regions is performed, which was not done earlier, 6) Location of beginning, end and progress of trend in rainfall of all India and seven homogenous regions concurrently is performed, which was not done earlier. As mentioned aforesaid, attribution of regionally significant trends detected in pre-monsoon rainfall time series of five homogeneous regions for the time period 1948-203 was not possible because of non-accounting of effects of cross correlation, attribution of rainfall is difficult and homogeneity of rainfall zones may change in future as discussed above in detail. So a thorough investigation about trends in rainfall, three temperatures (minimum, mean and maximum) and stream flow at regional (basin) scale was proposed to be ascertained. As Tapi basin is exposed to occurrence of heavy floods (Joshi and Shah, 2014) and it is climatically sensitive (Bhamare and Agone, 201; Gosain et al. 206; Deshpande et al., 2016), it is considered as study area. The trend detection analysis of gridded data (chapter 4) and regional time series (chapter 3) of rainfall and three temperatures data (1971-204) along with that for station data of stream flow (1979-204) of five gauging stations (chapter 4) is carried out using “Comprehensive Approach” for all temporal scales. Common available end year of data of rainfall, temperature and stream flow was 204 as data after 204 was not available for stream flow for all five gauging stations. Also data of rainfall (0.50 x 0.50) was available from year 1971, which was common starting year among data of rainfall and three temperatures. Also common starting year of stream flow data was 1979. Because of unavailability of rainfall data (0.50 x 0.50) before 1971, the three time periods used in chapters 1 and 2 are not used in chapters 3 and 4, thus only one time period is used for rainfall and three temperatures (1971-204) and stream flow (1979-204). The analysis has shown the presence of regionally significant rends in the gridded data of annual mean temperature (Tmean) and winter Tmean over Tapi basin apart from significant trends found in regional time series of annual Tmean and winter Tmean of Tapi basin. Monthly, winter and pre- monsoon stream flow volume time series have also shown regionally significant trends over five gauging stations of Tapi basin. Main contributions of the trend detection analysis of hydro- climatic variables of Tapi basin are: 1) grid wise, regional scale and station wise trend detection of three temperatures, rainfall and stream flow respectively is performed, which was not done earlier, 2) regional significance evaluation of gridded data (rainfall and three temperatures) and station data of stream flow (five stream flow gauging stations) is performed, which was not done earlier, 3) all four aspects of trend of hydro-climatic variables are evaluated, which was not done earlier, 4) systematic trend detection study of gridded, regional and station data of hydro-climatic variables is performed in present study which was not done earlier. After detection of regionally significant trends, next step is finding the causal factors through attribution study. Once causal factors of climate change observed in given variable are found, then remedial measures can be carried out for minimizing the effect of these factors on climate change observed in given variable. There are three main methods of attribution found in literature viz. finger printing, optimal finger printing and artificial neural network (ANN) model. In finger printing method only the leading empirical orthogonal function (EOF) is used, so this method is conservative. In optimal finger printing, multivariate regression is used, which has certain assumptions which are difficult to be fulfilled in the case of climate studies as climate is essentially a non-linear dynamic system. ANN being non-linear in nature provides the required solution for the attribution problem related to climate. Attribution of regionally significant trends detected in monthly, winter and pre-monsoon stream flow volume time series of five gauging stations of Tape basin is not performed because five gauging stations were not representative of entire Tapi basin and two out of the five gauging stations have missing data greater than 15%. Number of significant monotonically increasing trends are more in winter gridded Tmean data as compared to annual gridded Tmean data. Thus attribution analysis of winter gridded Tmean data has given first priority followed by attribution of annual gridded Tmean data. ANN model is developed for the attribution of climate change observed in gridded data of winter Tmean and annual Tmean in three steps: 1) input variable selection (IVS) based on partial mutual information (PMI), 2) data splitting using k-means clustering method and Neyman allocation, 3) ANN model formulation by using best training algorithm among Levenberg-Marquardt (LM) algorithm, scaled conjugate gradient (SCG) algorithm and Broyden, Fletcher, Goldfarb, and Shano (BFGS) algorithm and optimum number of hidden neurons (varying from 1 to 3) corresponding to performance in terms of mean squared error (MSE) and to use these in final ANN model formulation with computation of performance evaluation measures (PEMs). Aforesaid third step is repeated for 50 iterations for each input forcing and given target output to minimize any random variation due to reinitialization of training algorithms. Also random variations due to initialization of ANN model are minimized by keeping initial weights and biases equal to zero. Final PEMs evaluated were the averages of 50 iterations as mentioned aforesaid. Target outputs used in two ANN attribution models are time series of regional winter Tmean and regional annual Tmean. Also in some cases of ANN model formulations, network parameters are kept less than number of data points in the training set for minimizing overriding. Inputs for ANN model were circulation indices and regional, global and national scale input variables. The inputs selected by PMI based input selection (PMIS) algorithm in the step of IVS of both ANN attribution models are seen to be subjected to natural and anthropogenic forcing, which undisputedly shows significant role of anthropogenic activities in observed climate change in aforesaid two gridded temperature variables. Also ranking of input forcing is performed in both the ANN attribution models according to their final PEM values. In the case of ANN attribution model for regional winter Tmean time series, dominant role of natural (‘nat’) input forcing is found behind the given climate change as compared to anthropogenic (‘anth’) input forcing. Among ‘anth’ inputs, effect of land cover (‘Landcover’) input forcing is found to be dominant as compared to green house gases (‘GHgases’) input forcing. Among ‘Landcover’ inputs, urban landcover input was found to be one of the important inputs. In the case of ANN attribution model for regional annual Tmean time series, dominant role of ‘anth’ input forcing is found behind the given climate change as compared to ‘nat’ input forcing. Among ‘anth’ inputs, there is dominant role of ‘Landcover’ input forcing as compared to ‘GHgases’ input forcing. Among ‘Landcover’ inputs, urban landcover input was found to be one of the important inputs. Contributions of attribution study are: 1) checking of input independence and significance by using PMI IVS method, which was not performed earlier, 2) division of data in such a way that al patterns of whole data are present in training, testing and validation subsets and the statistical properties of these subsets are similar to each other and to whole data, which was not performed earlier, 3) using LM, SCG and BFGS algorithms which are converging fatly as compared to Windrow-Hof algorithm and gradient descent algorithm. Also these three algorithms are les liable to be get stuck in local minima, 4) using land cover data as input forcing to ANN model used for attribution of climate change, which was not done earlier.

Im Rahmen der szintigraphischen Untersuchung der Halswirbelsäule gibt es unterschiedliche Aussagen zum physiologischen Speicherungsverhalten, insbesondere der kaudalen Facettengelenke. Eine Objektivierung der Szintigramme und Ermittlung von Normalbereichen der entsprechenden Speicherquotienten ist daher wichtig und stellt das Ziel dieser Arbeit dar. Zur Untersuchung kamen dafür 31 Pferde, bei denen es sich um Patienten der Chirurgischen Tierklinik in Leipzig aus dem Jahr 2008 handelte. Falls bei einem Pferd eine Lahmheit der Vordergliedmaße vorhanden war, wurde mit Hilfe der klinischen und szintigraphischen Untersuchung, sowie mittels diagnostischer Anästhesien als deren Ursache die Halswirbelsäule ausgeschlossen. Alle Pferde wiesen eine freie Beweglichkeit des Halses in alle Richtungen auf. Zur Bildung von Speicherquotienten wurden die als Interessenareale dienenden Facettengelenke C3/C4 bis C7/Th1, sowie der Wirbelkörper des sechsten Halswirbels zu verschiedenen Referenzarealen ins Verhältnis gesetzt. Als Referenzareale wurden dabei der Wirbelkörper des dritten und des vierten Halswirbels, sowie das auch als Interessenareal dienende Facettengelenk C3/C4 getestet. Anschließend wurden Normalbereiche für die Speicherquotienten ermittelt. Nach sonographischer Muskeldickenmessung über den Facettengelenken wurden deren Speicherquotienten mit Hilfe einer Formel auf einen Nullwert korrigiert, und für diese korrigierten Werte wurden ebenfalls Normalbereiche ermittelt. Es zeigte sich, dass die Speicherquotienten nach der Muskeldickenkorrektur gegenüber den nativen Speicherquotienten eine größere Streuung aufwiesen und somit größere und ungenauere Normalbereiche hervorbrachten. Dementsprechend sollten die nativen Speicherquotienten bevorzugt werden. Als das am besten geeignete Referenzareal für die Interessenareale C4/C5 bis C7/Th1 erweist sich hierbei die Isokontur-ROI auf dem Facettengelenk C3/C4. Für das Interessenareal C3/C4 eignet sich sowohl der Vergleich mit dem Referenzareal C3, als auch der mit dem Referenzareal C4. Das Interessenareal auf dem Wirbelkörper C6 wird am besten zum Referenzareal C4 ins Verhältnis gesetzt. Hervorzuheben sind die nativen Werte der Normalbereiche für die Gelenke C5/C6 und C6/C7, da hier am häufigsten röntgenologische Veränderungen zu finden sind. Sie betragen für das Gelenk C5/C6 auf der linken Halsseite 0,82-1,10 und auf der rechten Halsseite 0,86-1,10. Für das Gelenk C6/C7 beträgt der Normalbereich für die linke Halsseite 0,75-1,23 und für die rechte Halsseite 0,81-1,17. Zusammenfassend ist zu sagen, dass die quantitative Auswertung mittels der „Regions of Interest“-Technik an der Halswirbelsäule durchaus möglich ist und mit dieser Arbeit akzeptable Normalbereiche für die Facettengelenke C3/C4 bis C7/Th1 und für den Wirbelkörper C6 ermittelt werden konnten. Es fehlen nun noch Werte von Pferden mit einer klinischen Halswirbelsäulenproblematik, um die Aussagekraft der hier ermittelten Normalbereiche zu überprüfen.

Background: Consecutive adult neurogenesis is a well-known phenomenon in the ventricular–subventricular zone of the lateral wall of the lateral ventricles (V–SVZ) and has been controversially discussed in so-called “non-neurogenic” brain areas such as the periventricular regions (PVRs) of the aqueduct and the fourth ventricle. Dopamine is a known modulator of adult neural stem cell (aNSC) proliferation and dopaminergic neurogenesis in the olfactory bulb, though a possible interplay between local dopaminergic neurodegeneration and induction of aNSC proliferation in mid/hindbrain PVRs is currently enigmatic. Objective/Hypothesis: To analyze the influence of chronic–progressive dopaminergic neurodegeneration on both consecutive adult neurogenesis in the PVRs of the V–SVZ and mid/hindbrain aNSCs in two mechanistically different transgenic animal models of Parkinson´s disease (PD). Methods: We used Thy1-m[A30P]h α synuclein mice and Leu9′Ser hypersensitive α4* nAChR mice to assess the influence of midbrain dopaminergic neuronal loss on neurogenic activity in the PVRs of the V–SVZ, the aqueduct and the fourth ventricle. Results: In both animal models, overall proliferative activity in the V–SVZ was not altered, though the proportion of B2/activated B1 cells on all proliferating cells was reduced in the V–SVZ in Leu9′Ser hypersensitive α4* nAChR mice. Putative aNSCs in the mid/hindbrain PVRs are known to be quiescent in vivo in healthy controls, and dopaminergic deficiency did not induce proliferative activity in these regions in both disease models. Conclusions: Our data do not support an activation of endogenous aNSCs in mid/hindbrain PVRs after local dopaminergic neurodegeneration. Spontaneous endogenous regeneration of dopaminergic cell loss through resident aNSCs is therefore unlikely.

The purpose of this study was to identify whether there are differences between regions in Sweden regarding the relationship between lethal violence and mental illness and for the connection when other factors are included in the explanatory model in the form of forensic psychiatric care and financial situation. In order to investigate the purpose and the formulated research questions public data and two different analysis methods, descriptive analysis and regression analysis were used. Using these analysis methods, two different types of differences between regions were identified. At first, two regions were found to have a significant effect in the relationship between lethal violence and mental illness, which changed to none of the regions when forensic psychiatric care and financial aid were taken into account. The second type of regional differences were identified by the fact that some of the regions included significant factors, and some did not. With this result it was concluded that there are differences between regions and these differences change in more complex explanatory models of lethal violence. / Syftet med denna undersökning var att identifiera om det finns skillnader mellan Sveriges regioner när det gäller sambandet mellan dödligt våld och psykisk ohälsa, samt för sambandet då andra påverkande faktorer inkluderas i form av rättspsykiatrisk vård och ekonomisk situation. För att kunna undersöka syftet och de tillhörande frågeställningarna användes offentliga data och två olika analysmetoder, deskriptiv analys och regressionsanalys. Med hjälp av dessa analysmetoder identifierades två olika typer av skillnader mellan regioner. Först visade det sig att två regioner har en signifikant skillnad på sambandet mellan dödligt våld och psykisk ohälsa men som förändrades till inga regioner när man tog hänsyn till rättspsykiatrisk vård och ekonomisk situation. Andra typen av skillnader mellan regionerna identifierades genom att en del av regionerna innehöll signifikanta skillnader och vissa inte. Med detta resultat drogs slutsatserna att det finns skillnader mellan regioner som blir påverkade i mer komplexa förklaringsmodeller av dödligt våld.

No description available.

Thesis (MSc)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: The Okiep copper district in the north-western corner of South Africa is a region that has been mined for over 150 years. Most mining operations have ceased, but years of mining has left the area scattered with abandoned mining sites. Acids (as used in ore processing) together with acid mine drainage generated from tailings exposure, collectively referred to as AMD hereafter, are a contamination risk to water resources and the biodiversity of this arid area. This study focused on an abandoned copper processing pond located close to the town of Nababeep. The leaching pond is unlined and has been excavated in the shallow colluvial soils. The natural soils of the area are shallow (60 cm) (WRB – Arenosol; SA – Oakleaf). Formations of corroded granite-gneiss boulders are an indication of the corrosiveness of the AMD collecting in the pond. The AMD was collected from the pond in the dry season at its most concentrated form and the AMD had exceptionally high concentrations of Al (26.9 g/l), Fe (42.9 g/l), Mg (20.5 g/l), Cu (3.8 g/l) and Mn (3.4 g/l). Melanterite (FeSO4·7H2O), a soluble ferrous compound, was found to play an important role in the immediate release of Fe and sulfates. The pristine soils have a sandy texture (2–5.2 %clay). The minerals detected in the clay phase include illite, kaolinite, montmorillonite and quarts. Pristine soils show some degree of contamination with low pH (4.38–4.77) and high Cu and sulfate contents. Soils located in the processing pond, which have been exposed to AMD for an extended period of time, showed poorly crystalline phases to be present (indicated by a broadening of the XRD peaks for clay minerals). Saturation indices (SI) were determined for saturated paste extracts of the pond soils and the obtained SI values support the notion of dissolution of silicate clays, as the obtained SI values ranged between –1.3 and –11.77 for illite and –4.76 to 0.58 for kaolinite. Jarosite, a new phase, formed in the contaminated soil and is a sink for K. Long term weathering experiments of pristine soils exposed to AMD indicated that clay minerals are significantly weathered and altered, which was identified by observing the broadening of the clay XRD peaks. Fourier transform infrared (FTIR) spectra were generated by scanning clay samples of the weathered soil. Amorphous phases were confirmed by structured water bands with wavenumber values of 3700 and 3300 cm−1 for acid treated soil. Micrographs showed a more amorphous and corroded morphology in the acid treated soil. Metal retention experiments were conducted by exposing the pristine soil to AMD repeatedly. Iron was the predominant metal attenuated in the soil. Metals such as Al, Mn, Na, K, Ca and Co were released by the soil into solution. Removal of Si is associated with the dissolution of clay minerals. The pristine soil shows limited capacity to neutralize acidity and low capacity to retain metals when leached with AMD. Metals were predominantly extracted in the water soluble phase of the long term weathering treatments. Aluminium was the most mobile fraction, being extracted predominantly from the water soluble fraction (2035 mg/kg). Exchangeable and acid soluble fractions did not retain significant quantities of metals. In the soil from the processing pond, the reducible fraction had a high concentration of reducible Fe (21175 mg/kg) and Si (3070 mg/kg). The reducible fraction also had the highest concentration of Cr (15.85 mg/kg), Cu (41.53 mg/kg), Pb (8.0 mg/kg) and Zn (10.65 mg/kg) compared to the other fractions of this soil. For the control experiment, the concentration of Cu (77.3 mg/kg), Pb (10.8 mg/kg) and Zn (24.1 mg/kg) were higher than contaminated soil yet lower for Cr (6.05 mg/kg). From these experiments, it can be concluded that the pristine soils studied have a limited ability to retain heavy metals in the non-bioavailable fraction, and, due to the nature of AMD, they are not effective in retaining metals sufficiently. The findings of this study suggest that the capacity of these pristine soils to buffer pH and retain metals is greatly limited. This could be as a result of (1) the low clay content, (2) the low concentration of secondary carbonates and (3) the low pH of the soil. The leaching of AMD from the pond is thus not regulated by the soils and poses a risk for nearby water resources. / AFRIKAANSE OPSOMMING: Die Okiep Koper Distrik, geleë in die noord-westelike hoek van Suid-Afrika, is ‘n streek waar mynbou al vir meer as 150 jaar plaasvind. Die meeste mynbou aktiwiteite is gestaak, maar jare van mynbou het die streek nagelaat met verskeie verlate mynbouterreine. Sure, wat in die prosessering van erts gebruik word, en suurmynwater wat gegenereer word uit die mynuitskot (gesamentlik verwys na as suurmynwater) is ‘n besoedelingsrisiko vir waterbronne en biodiversiteit in hierdie dorre area. Die studie fokus op ‘n verlate koper prosesserings aanleg naby die dorpie Nababeep. Die logingsdam is nie geseël nie en is uitgegrawe in vlak, kolluviale grond. Die natuurlike gronde van hierdie area is vlak (60 cm) (WRB – Arenosol; SA – Oakleaf). Formasies van weggevrete graniet-gneis rotse in die opgaardam is ‘n aanduiding van die bytende potensiaal van hierdie suurmynwater. Suurmynwater was versamel in die dam gedurendie die droë seisoen in die mees gekonsentreerde vorm. Die suurmynwater het besonderse hoë konsentrasies van Al (26.9 g/l), Fe (42.9 g/l), Mg (20.5 g/l), Cu (3.8 g/l) en Mn (3.4 g/l). Melanteriet (FeSO4·7H2O) is ‘n ysterhoudende verbinding en, alhoewel dit oplosbaar is, speel dit ‘n belangrike rol in die onmiddelike vrylating van Fe en sulfate. Die onversteurde grond het ‘n sand tekstuur (2–5.2 % klei). Die minerale wat in die klei fraksie ge-identifiseer is sluit illiet, kaoliniet, montmorilloniet en kwarts in. Die ongerepte gronde dui egter op ‘n mate van besoedeling deurdat dit ‘n lae pH (4.38–4.77) enhoë Cu en sulfaat inhoud het. Die grond wat geleë is naby die prosesseringsaanleg en ook blootgestel is aan suurmynwater vir ‘n verlengde tyd, dui daarop dat swak kristallyne fases teenwoordig is in die grond. Dit word bevestig deur ‘n verbreding van die XRD pieke van kleiminerale. Versadiging indekse (VI), wat bepaal is in versadigde grondekstraksies van die damgrond, ondersteun die oplossing van die silikaatkleie en word gereflekteer deur VI waardes wissel tussen –1.3 en –11.77 vir illiet en –4.76 tot 0.58 vir kaoliniet. Jarosiet is ‘n nuwe fase wat gevorm het in die besoedelde grond en is ‘n sink vir K. Langtermyn verweringseksperimente wat gedoen is deur die onversteurde grond bloot te stel aan suurmynwater wys beduidende verwering en verandering van klei-minerale deur verbreding van die XRD pieke. Fourier transform infrarooi (FTIR) spektra is op kleimonsters van die verweerde grond gegenereer. Amorfe fases is bevestig deur gestruktureerde waterbindings met frekwensies tussen 3700 en 3300 cm−1 vir suurbehandelde grond. Metaal-vasleggings eksperimente is uitgevoer deur herhaaldelik die onversteurde grond aan die suurmynwater bloot te stel. Yster is die metaal wat hoofsaaklik in die grond vasgehou is. Metale soos Al, Mn, Na, K, Ca en Co was vrygestel in oplossing deur die grond. Die vrylating van Si deur die grond word geassosiëer met die oplossing van kleiminerale. Die onversteurde grond toon beperkte vermoë om suur te neutraliseer en metale te bind in die grond wanneer dit met suurmynwater geloog word. Metale was hoofsaaklik ge-ekstraëer in die wateroplosbare fase vir die langtermyn verweringsbehandelings. Aluminium was die mees mobiele fraksie wat ontrek is van die water oplosbare fraksie (2035 mg/kg). Uituilbare en suuroplosbare fraksies het nie ‘n groot hoeveelheid metale vasgehou nie. Gronde wat versamel is naby die prosesseringsdam het die hoë konsentrasies vanFe (21175 mg/kg) en Si (3070 mg/kg) in die gereduseerde fraksie gehad. Die reduserende fraksie het ook die hoogste konsentrasie van Cr (15.85 mg/kg), Cu (41.53 mg/kg), Pb (8.0 mg/kg) en Zn (10.65 mg/kg) gehad in vergelyking met ander fraksies in die grond. Vir die beheer eksperiment was die konsentrasie van Cu (77.3 mg/kg), Pb (10.8 mg/kg) en Zn (24.1 mg/kg) hoër as in die besoedelde grond en laer vir Cr (6.05 mg/kg). Dus kan daar van hierdie eksperimente afgelei word dat die onversteurde grond beperkte kapasiteit het om swaar metale in grond vas te hou in die nie-biobeskikbare fraksie. As gevolg van die aard van die suurmynwater, is die grond nie voldoende om die metale effektief in grond te behou nie. Die bevindinge van hierdie studie dui daarop dat die kapasiteit van die ongerepte grond om pH te buffer en metale in grond te behou baie beperk is. Dit kan toegeskryf word aan die lae kleiinhoud, lae konsentrasie van sekondêre karbonate en die lae pH van die grond. Die loging van suurmynwater van die logingsdam is dus nie gereguleer deur die gronde nie en stel die naasliggende waterbronne in gevaar.

This study suggests a two-step approach to identifying and interpreting regional convergence clubs in Europe. The first step involves identifying the number and composition of clubs using a space-time panel data model for annual income growth rates in conjunction with Bayesian model comparison methods. A second step uses a Bayesian space-time panel data model to assess how changes in the initial endowments of variables (that explain growth) impact regional income levels over time. These dynamic trajectories of changes in regional income levels over time allow us to draw inferences regarding the timing and magnitude of regional income responses to changes in the initial conditions for the clubs that have been identified in the first step. This is in contrast to conventional practice that involves setting the number of clubs ex ante, selecting the composition of the potential convergence clubs according to some a priori criterion (such as initial per capita income thresholds for example), and using cross-sectional growth regressions for estimation and interpretation purposes. (authors' abstract)

This paper concentrates on the central link between productivity and knowledge capital, and shifts attention from firms and industries to regions. The objective is to measure knowledge elasticity effects within a regional Cobb- Douglas production function framework, with an emphasis on knowledge spillovers. The analysis uses a panel of 203 European regions to estimate the effects over the period 1997-2002. The dependent variable is total factor productivity (TFP). We use a region-level relative TFP index as an approximation to the true TFP measure. This index describes how efficiently each region transforms physical capital and labour into outputs. The explanatory variables are internal and out-of-region stocks of knowledge, the latter capturing the contribution of interregional knowledge spillovers. We use patents to measure knowledge capital. Patent stocks are constructed such that patents applied at the European Patent Office in one year add to the stock in the following and then depreciate throughout the patents effective life according to a rate of knowledge obsolescence. A random effects panel data spatial error model is advocated and implemented for analyzing the productivity effects. The findings provide a fairly remarkable confirmation of the role of knowledge capital contributing to productivity differences among regions, and adding an important dimension to the discussion, showing that knowledge spillover effects increase with geographic proximity. (authors' abstract)

<p>The purpose of this thesis is to disentangle the causes behind differences in regional employment across the 81 Swedish LA regions. Thus, two questions will be answered; which factors causes regional disparity in employment and which where the least and the</p><p>most affected regions during the economic crises of the 1990’s? The answer to these questions are imposed by certain chosen restrictions, where only the situation within two manufacturing industries will be investigated; the car- and machine manufacturing sectors. Previous research claim that there are specific factors that influence and creates regional growth disparity. Among these factors can be found; education, infrastructure, demography, industry diversity and migration. Statistical data then enables a division of the regions on basis of the change in employment level within the manufacturing industries as a share of total employment. It is revealed that the most affected regions during an economic shock are those areas that have the highest employment ratio within these manufacturing sectors. The empirical findings indicates that in the case of Swedish manufacturing industries especially three factors influence the employment level; population, education and migration. Additionally, distance to a larger city is proven to be</p><p>significant during recessions while being insignificant during economic booms. The last factor, diversity, on the other hand indicates that the correlation is the reverse. Hence, diversity has an impact during economic upswings, while this is not the case during downturns. With the development during the 90’s as a reference, the same method is used to locate today’s most vulnerable industrial regions. Statistics show that Ljungby is at the top</p><p>of this list. When studying the strategic development plan for this region it is found that this area follows a policy in line with those variables that this thesis has pin-pointed to be</p><p>beneficial for regional growth. Hence, this region has taken beneficial policy steps in order to decrease the dependency on a vulnerable and market sensitive industrial sector.</p> / <p>Syftet med denna uppsats är att utreda varför anställningsgraden skiljer sig mellan de 81 svenska LA regionerna. De två frågor som skall besvaras är följaktligen; vilka faktorer påverkar skillnader i sysselsättningsgrad samt utpeka vilka regioner var de minst och mest</p><p>drabbade under 1990-talets ekonomiska kris? Dessa frågor har dock begränsats till att undersöka förhållandet inom två tillverkningsindustrier; bil- och maskintillverkning.</p><p>Tidigare forskning hävdar att det finns vissa specifika faktorer som påverkar och skapar regionala skillnader i tillväxt. Bland dessa kan nämnas utbildning, infrastruktur, demografi, diversitet och migration. Den deskriptiva statistiken delar därefter upp Sveriges regioner på basis av förändringen i anställning inom de två valda industrisektorerna som en del av totala sysselsättningen. De hårdast drabbade regionerna under en lågkonjunktur är deregioner som har störst andel av totala arbetskraften inom tillverkningsindustrin. Vidare indikerar de empiriska resultaten att för svensk tillverkningsindustris vidkommande så har främst population, utbildning samt migration ett starkt samband med</p><p>sysselsättningsfrekvensen. Vidare visar det sig att avståndet till en större stad har en inverkan under lågkonjunktur men ej under högkonjunktur. För den sista variabeln, grad av diversitet, visar sig sambandet vara det motsatta; det vill säga ingen påverkan under en konjunkturnedgång, medan en positiv influens under konjunkturuppgång. Med händelseutvecklingen från 90-talet som grund kan samma metod användas för att lokalisera dagens mest sårbara industriregioner. Statistiken visar att Ljungby toppar denna lista. Men då man studerar denna regions framtids- och utvecklingsmål följer dessa just de faktorer som denna uppsats utpekar som viktiga ingredienser för regional tillväxt. Följaktligen har denna region tagit positiva steg i riktning mot att minska sitt beroende av en sårbar och konjunkturkänslig industrisektor.</p>

In November of 1984 and 1985, Euphorbia lathyris was planted into a field naturally infested with Macrophomina phaseolina located at the Campbell Avenue Farm in Tucson, Arizona. Plants without foliar symptoms and rhizosphere soil were sampled regularly from emergence until the following May or June. Soil rhizosphere populations ranged from 0.7-3.0 cfu/g soil in 1985 to 8.0-24.1 cfu/g soil in 1986, and did not change significantly over either growing season (P > 0.05). Both the incidence of disease and the number of infection sites per cm of root increased significantly (P < 0.05) over each growing season and were not related to rhizosphere soil populations of M. phaseolina (P > 0.05). The distribution of infection sites along the tap root over both growing seasons remained the same in that most were located in the top 0-7 cm of tap root. Infected E. lathyris without apparent symptoms were subjected to low-water and high-temperature stress treatments in growth chambers. Root infection was not found to be dependent upon any stress. Lesion development was significantly dependent upon the imposition of any stress treatment, and further root colonization was significantly dependent upon low-water stress (P < 0.05). M. phaseolina was consistently recovered from asymptomatic roots. A consistently lower leaf water potential was measured on infected E. lathyris than from non-infected controls when no stress treatment was applied. Polyclonal antisera made against hyphae and microsclerotia of M. phaseolina was not successful in detecting this pathogen in E. lathyris by I-ELISA. Antisera applied to fresh thin sections of infected plant tissue was effective in staining hyphae of M. phaseolina when used with a second antibody conjugated to fluorescence isothiocyanate or to an enzyme (to which a substrate was added to "stain" hyphae).