Täpläpöllö - Amerikan liito-orava

Kirjallisuusarvostelu

Persistent organic pollutants in sediments and fish from Lake Victoria, Uganda

This thesis describes the occurrence and sources of selected persistent organic pollutants (POPs) such as polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and hexachlorocyclohexanes (HCHs) in the northern watershed of Lake Victoria. Sediments and fish were collected from three highly polluted embayments (i.e. Murchison Bay, Napoleon Gulf and Thurston Bay) of the lake. The analysis for PCDD/Fs, PCBs and PBDEs was done using a high resolution mass spectrometer coupled to a gas chromatograph (GC), and a GC equipped with an electron capture detector was used for HCHs. Total (Σ) PCDD/Fs, PCBs and PBDEs in sediments ranged from 3.19 to 478, 313 to 4325 and 60.8 to 179 pg g-1 dry weight (dw), respectively. The highest concentrations of pollutants were found at sites close to industrial areas and wastewater discharge points. The maximum concentrations of PCDD/Fs, PCBs, PBDEs and HCHs in fish muscle homogenates were 49, 779, 495 and 45,900 pg g-1 wet weight (ww), respectively. The concentrations of the pollutants in Nile perch (Lates niloticus) were significantly greater than those in Nile tilapia (Oreochromis niloticus), possibly due to differences in trophic level and dietary feeding habits among fish species. World Health Organization-toxic equivalency quotient (WHO2005-TEQ) values in the sediments were up to 4.24 pg g-1 dw for PCDD/Fs and 0.55 pg TEQ g-1 dw for the 12 dioxin-like PCBs (dl-PCBs). 23.1% of the samples from the Napoleon Gulf were above the interim sediment quality guideline value of 0.85 pg WHO-TEQ g-1 dw set by the Canadian Council for Ministers of the Environment. The WHO2005-TEQs in fish were 0.001-0.16 pg g-1 for PCDD/Fs and 0.001-0.31 pg g-1 ww for dl- PCBs. The TEQ values were within a permissible level of 3.5 pg g−1 ww recommended by the European Commission. Based on the Commission set TEQs and minimum risk level criteria formulated by the Agency for Toxic Substances and Disease Registry, the consumption of fish from Lake Victoria gives no indication of health risks associated to PCDD/Fs and PCBs. Principal component analysis (PCA) indicated that anthropogenic activities such as agricultural straw open burning, medical waste incinerators and municipal solid waste combustors were the major sources of PCDD/Fs in the watershed of Lake Victoria. The ratios of α-/γ-HCH varied from 0.89 to 1.68 suggesting that the highest HCH residues mainly came from earlier usage and fresh γ-HCH (lindane). In the present study, the concentration of POPs in fish were not significantly related to those in sediments, and the biota sediment accumulation factor (BSAF) concept was found to be a poor predictor of the bioavailability and bioaccumulation of environmental pollutants.

Toward a Reliable Classifier For Arrhythmia Diagnosis

Illnesses related to the heart are one of the major reasons for death all over the world causing many people to lose their lives in last decades. The good news is that many of those sicknesses are preventable if they are spotted in early stages. On the other hand, the number of the doctors are much lower than the number of patients. This will makes the auto diagnosing of diseases even more and more essential for humans today. Furthermore, when it comes to the diagnosing methods and algorithms, the current state of the art is lacking a comprehensive study on the comparison between different diagnosis solutions. Not having a single valid diagnosing solution has increased the confusion among scholars and made it harder for them to take further steps. This master thesis will address the issue of reliable diagnosing algorithm. We investigate ECG signals and the relation between different diseases and the heart’s electrical activity. Also, we will discuss the necessary steps needed for auto diagnosing the heart diseases including the literatures discussing the topic. The main goal of this master thesis is to find a single reliable diagnosing algorithm and quest for the best classifier to date for heart related sicknesses. Five most suited and most well-known classifiers, such as KNN, CART, MLP, Adaboost and SVM, have been investigated. To have a fair comparison, the ex-periment condition is kept the same for all classification methods. The UCI repository arrhythmia dataset will be used and the data will not be preprocessed. The experiment results indicates that AdaBoost noticeably classifies different diseases with a considera-bly better accuracy.