A monthly indicator of Brazilian GDP. The Brazilian business cycle and growth cycle

This paper constructs an indicator of Brazilian GDP at the monthly ftequency. The peculiar instability and abrupt changes of regimes in the dynamic behavior of the Brazilian business cycle were explicitly modeled within nonlinear ftameworks. In particular, a Markov switching dynarnic factor model was used to combine several macroeconomic variables that display simultaneous comovements with aggregate economic activity. The model generates as output a monthly indicator of the Brazilian GDP and real time probabilities of the current phase of the Brazilian business cycle. The monthly indicator shows a remarkable historical conformity with cyclical movements of GDP. In addition, the estimated filtered probabilities predict ali recessions in sample and out-of-sample. The ability of the indicator in linear forecasting growth rates of GDP is also examined. The estimated indicator displays a better in-sample and out-of-sample predictive performance in forecasting growth rates of real GDP, compared to a linear autoregressive model for GDP. These results suggest that the estimated monthly indicator can be used to forecast GDP and to monitor the state of the Brazilian economy in real time.

GSR deposition along the bullet path in contact shots to composite models

In contact shots, all the materials emerging from the muzzle (combustion gases, soot, powder grains, and metals from the primer) will be driven into the depth of the entrance wound and the following sections of the bullet track. The so-called "pocket" ("powder cavity") under the skin containing soot and gunpowder particles is regarded as a significant indicator of a contact entrance wound since one would expect that the quantity of GSR deposited along the bullet's path rapidly declines towards the exit hole. Nevertheless, experience has shown that soot, powder particles, and carboxyhemoglobin may be found not only in the initial part of the wound channel, but also far away from the entrance and even at the exit. In order to investigate the propagation of GSRs under standardized conditions, contact test shots were fired against composite models of pig skin and 25-cm-long gelatin blocks using 9-mm Luger pistol cartridges with two different primers (Sinoxid® and Sintox®). Subsequently, 1-cm-thick layers of the gelatin blocks were examined as to their primer element contents (lead, barium, and antimony as discharge residues of Sinoxid® as well as zinc and titanium from Sintox®) by means of X-ray fluorescence spectroscopy. As expected, the highest element concentrations were found in the initial parts of the bullet tracks, but also the distal sections contained detectable amounts of the respective primer elements. The same was true for amorphous soot and unburned/partly burned powder particles, which could be demonstrated even at the exit site. With the help of a high-speed motion camera it was shown that for a short time the temporary cavitation extends from the entrance to the exit thus facilitating the unlimited spread of discharge residues along the whole bullet path.

Pollen and non-pollen palynomorph records of the Holocene part of the composite sediment core TMD from lake Tso Moriri (NW India) and of modern surface samples from the Tso Moriri region

The high-altitude lake Tso Moriri (32°55'46'' N, 78°19'24'' E; 4522 m a.s.l.) is situated at the margin of the ISM and westerly influences in the Trans-Himalayan region of Ladakh. Human settlements are rare and domestic and wild animals are concentrating at the alpine meadows. A set of modern surface samples and fossil pollen from deep-water TMD core was evaluated with a focus on indicator types revealing human impact, grazing activities and lake system development during the last ca. 12 cal ka BP. Furthermore, the non-pollen palynomorph (NPP) record, comprising remains of limnic algae and invertebrates as well as fungal spores and charred plant tissue fragments, were examined in order to attest palaeolimnic phases and human impact, respectively. Changes in the early and middle Holocene limnic environment are mainly influenced by regional climatic conditions and glacier-fed meltwater flow in the catchment area. The NPP record indicates low lake productivity with high influx of freshwater between ca. 11.5 and 4.5 cal ka BP which is in agreement with the regional monsoon dynamics and published climate reconstructions. Geomorphologic observations suggest that during this period of enhanced precipitation the lake had a regular outflow and contributed large amounts of water to the Sutlej River, the lower reaches of which were integral part of the Indus Civilization area. The inferred minimum fresh water input and maximum lake productivity between ca. 4.5-1.8 cal ka BP coincides with the reconstruction of greatest aridity and glaciation in the Korzong valley resulting in significantly reduced or even ceased outflow. We suggest that lowered lake levels and river discharge on a larger regional scale may have caused irrigation problems and harvest losses in the Indus valley and lowlands occupied by sedentary agricultural communities. This scenario, in turn, supports the theory that, Mature Harappan urbanism (ca. 4.5-3.9 cal ka BP) emerged in order to facilitate storage, protection, administration, and redistribution of crop yields and secondly, the eventual collapse of the Harappan Culture (ca. 3.5-3 cal ka BP) was promoted by prolonged aridity. There is no clear evidence for human impact around Tso Moriri prior to ca. 3.7 cal ka BP, with a more distinct record since ca. 2.7 cal ka BP. This suggests that the sedimentary record from Tso Moriri primarily archives the regional climate history.

Composite materials impact damage detection using neural networks

This thesis considers two basic aspects of impact damage in composite materials, namely damage severity discrimination and impact damage location by using Acoustic Emissions (AE) and Artificial Neural Networks (ANNs). The experimental work embodies a study of such factors as the application of AE as Non-destructive Damage Testing (NDT), and the evaluation of ANNs modelling. ANNs, however, played an important role in modelling implementation. In the first aspect of the study, different impact energies were used to produce different level of damage in two composite materials (T300/914 and T800/5245). The impacts were detected by their acoustic emissions (AE). The AE waveform signals were analysed and modelled using a Back Propagation (BP) neural network model. The Mean Square Error (MSE) from the output was then used as a damage indicator in the damage severity discrimination study. To evaluate the ANN model, a comparison was made of the correlation coefficients of different parameters, such as MSE, AE energy, AE counts, etc. MSE produced an outstanding result based on the best performance of correlation. In the second aspect, a new artificial neural network model was developed to provide impact damage location on a quasi-isotropic composite panel. It was successfully trained to locate impact sites by correlating the relationship between arriving time differences of AE signals at transducers located on the panel and the impact site coordinates. The performance of the ANN model, which was evaluated by calculating the distance deviation between model output and real location coordinates, supports the application of ANN as an impact damage location identifier. In the study, the accuracy of location prediction decreased when approaching the central area of the panel. Further investigation indicated that this is due to the small arrival time differences, which defect the performance of ANN prediction. This research suggested increasing the number of processing neurons in the ANNs as a practical solution.