Further Work and Conclusion Essay Example

Further Work and Conclusion Paper Additional directions for this work include refining and extending our cardiac study with a view to clinical implementation. Furthermore, we suggest that rhythmic signals arising from other biological systems may have application for the techniques described in this paper. An investigation of the optimal windowing parameter set would be instructive since our findings suggest the existence of physiological thresholds in the spectral entropy level and variance that are applicable to a variety of patients. As noted at the end of Section 5.4.3, one challenge would be to investigate and improve the utility of the measure (alone or combining methods) when applied to patients that demonstrate a mix of different pathologies and arrhythmias. Adjusting the spectral entropy window to covary with instantaneous heart rate so that ÃŽ ± always contains ten beats exactly would further reduce issues related to variations in the heart rate. Extending the algorithm to include other dimensions in the disorder map (e.g., heart rate) will likely improve the accuracy of results and may increase the number of arrhythmias the spectral entropy can distinguish between. We will write a custom essay sample on Further Work and Conclusion specifically for you for only $16.38 $13.9/page Order now We will write a custom essay sample on Further Work and Conclusion specifically for you FOR ONLY $16.38 $13.9/page Hire Writer We will write a custom essay sample on Further Work and Conclusion specifically for you FOR ONLY $16.38 $13.9/page Hire Writer An accurate automatic detector of atrial fibrillation would be clinically useful in monitoring for relapse of fibrillation in patients and in assessing the efficacy of antiarrhythmic drugs (Israel 2004). An implementation integrated with an ambulatory ECG or heart rate monitor would be useful in improving the understanding of arrhythmias on time scales longer than that available using conventional ECG analysis techniques alone. Measures of disorder in the frequency domain have practical significance in a range of biological signals. For example, the regularity of the background electroencephalography (EEG is the measurement of electrical activity produced by the brain as recorded from electrodes placed on the scalp) alters with developmental and psychophysiological factors: some mental or motor tasks cause localized desynchronization; in addition, the background becomes more irregular in some neurological and psychiatric disorders (see Inouye et al. 1991; Rosso 2007 and references therein). The spectral entropy method and the concept of the disorder map described in this paper are not cardiac specific: it would be instructive to adapt these ideas to other rhythmic signals where a rapid detection of arrhythmia would be informative. 5.6 Conclusion In this paper we have presented an automatic arrhythmia detection algorithm that is able to rapidly detect the presence of atrial fibrillation using only the time series of patients’ beats. The algorithm employs a general technique for quickly quantifying disorder in high-frequency event series: the spectral entropy is a measure of disorder applied to the power spectrum of periods of time series data. The physiologically motivated use of the spectral entropy is shown to distinguish atrial fibrillation and flutter from other rhythms. For a given set of parameters, we are able to determine from a disorder map two threshold conditions (based on the level and variance of spectral entropy values) that enable the detection of fibrillation in a variety of patients. We apply the algorithm to the MIT-BIH atrial fibrillation database of 25 patients. When the algorithm is set to identify abnormal rhythms within 6 s it agrees with 85.7% of the annotations of professional rhythm assessors; for a response time of 30 s this becomes 89.5%, and with 60 s it is 90.3%. The algorithm provides a rapid way to detect fibrillation, demonstrating usable response times as low as 6 s and may complement other detection techniques. There also exists the potential for our spectral entropy and disorder map implementations to be adapted for the rapid identification of disorder in other rhythmic signals. 5.7 Appendix This appendix contains images of the electrocardiograms referred to in Sections 5.4.1 and 5.4.2. They represent examples where we believe the annotations provided as part of the MIT-BIH atrial fibrillation database to be incorrect, and where rhythms other than atrial fibrillation and atrial flutter are present in patient electrocardiograms. The following figures were obtained using the Chart-O-Matic facility on the physionet website (Goldberger et al. 2000) for patients comprising the MIT-BIH atrial fibrillation database (afdb). We give selected example electrocardiograms (ECGs) to illustrate the point under consideration and stress that there are additional times that could have been used for demonstrative purposes. The rhythm assessments to which we are comparing are provided as annotations included as part of the afdb. For other examples of ECGs corresponding to the rhythms given here, see Bennett 2002. 5.7.1 Disagreements with annotations Rhythm assessments have been questioned before (Tateno Glass 2000, 2001); here we give explicit examples from the afdb where we believe the ECG suggests a rhythm different from that given by the annotation. The figures and ideas in this section pertain to Section 5.4.1 of the main text. Instances where atrial fibrillation has been missed in annotations We observe in Patients 08219 (Figure 5.4) and 08434 (Figure 5.5) periods of atrial fibrillation that we believe to have been missed in the annotations but are correctly identified by our detection algorithm. Cases such as these serve to negatively impact the results of the algorithm unfairly; however, we note that such instances comprise a small proportion of the afdb. Instances where atrial flutter has been missed in annotations Atrial flutter may have been misannotated in Patients 04936 (Figure 5.6) and 08219 (Figure 5.7). This unreliability of rhythm assessment, compounded with the limited number of periods of atrial flutter in the database, prevents us from drawing meaningful quantitative conclusions regarding the success of the detection algorithm in identifying flutter. Despite this, we believe that the spectral entropy is in principle still capable of identifying flutter. 5.7.2 Other rhythms The unreliability of parts of the annotations still does not account for all false predictions produced by the detection algorithm. We suggest the presence of other rhythms within the afdb to be an additional factor that needs to be considered. The figures and ideas in this section pertain to Section 5.4.2 of the main text. Instances of fib-flutter Fib-flutter denotes periods where the rhythm transitions in quick succession between atrial fibrillation and flutter (Horvath et al. 2000). Such behavior naturally causes the variance to increase (thereby exceeding the standard deviation threshold in the algorithm for classification as atrial fibrillation) and one might question whether it is still appropriate to classify those periods as standard atrial fibrillation. We identify in the ECG of Patient 04936 periods of fib-flutter which likely accounts for the high proportion of false negative results (Figures 5.8 and 5.9). Instances of sinus arrest Sinus arrest occurs when the sinoatrial node fails to fire, resulting in increased irregularity of the heart rhythm, whilst still retaining QRS complexes indicative of normal sinus rhythm; this condition (along with sinus arrhythmia) is likely responsible for the high proportion of false positives seen in Patient 05091 (Figure 5.10). Conclusion The natural world makes no distinction between scientific disciplines. Increasingly, answers to scientific questions lie at the intersection of traditional disciplines. This thesis has applied techniques developed in physics and mathematics to problems in ecology and medicine. I have shown how simple methods of time series analysis can enable rapid detection of cardiac arrhythmia; how ecosystems may respond and adapt to the loss of species; how species can modify their feeding interactions in manmodified environments; and how spatial landscape can affect the spread of fluctuations of venture capital firm populations. Moving forward, my current research is motivated by one fundamental question: What does a food web represent? Practically, we must ask: (i) What ecological mechanisms underlie foodweb structure? and (ii) How does food-web structure change through time? What ecological mechanisms underlie food-web structure? How does individual-level species behaviour lead to observed food-web structure (Stouffer 2010)? How does behaviour underlie differences (or similarities) among distinct food-web types (Th ´ebault Fontaine 2010)? Can we combine these distinct food-web types to understand complete patterns of interactions within ecological communities (Lafferty et al. 2008)? How do environmental factors affect species interactions (Lalibert ´e Tylianakis 2010)? Exciting work has begun to address these questions. Answers to these questions will lead to new questions. Progress relies on the exchange of ideas, many of which will originate in fields other than ecology. How does food-web structure change through time? What assembly mechanisms lead to observed food-web structure (Piechnik et al. 2008)? Are current, static, models consistent with empirical data on food-web assembly (Albrecht et al. 2010)? What role do invasive species play in food-web dynamics (Lopezaraiza-Mikel et al. 2007)? Experiment and theory are advancing. Ecological data are improving and more sophisticated methods of analysis are developing. We are increasingly achieving that fundamental goal of ecology—a central tenet shared by the physical sciences—prediction. Previous Page   Algorithm and Discussion

The Goddess Demeter †Greek History Essay

The Goddess Demeter – Greek History Essay Free Online Research Papers The Goddess Demeter Greek History Essay Have you ever thought about how it would be if we lived in a world where there was a god for everything? Very long ago, Greeks strongly believed in different kind of gods and goddesses. One of these goddesses was Demeter who provided fertility. â€Å"Demeter provides all nutrition on the earth, allowing her to be considered a vital source of survival† (A.L. Davidson, The Greek Goddess Demeter). Some of her main symbols include poppy seeds, and corn, which of course have to do with agriculture; and some colors, which represent her, are pink, brown, green, and yellow. She also taught mankind the art of sowing and sloughing. â€Å"She can also cross dimensional barriers between worlds and alter her form to appear as an elderly woman† (marvunapp.com/Appendix/demeterc.htm). She did not have many enemies, but only disliked the ones who did not help her when she was in search of her daughter Persephone, and also those who ate sacred plants. Demeter was an influential goddess with many characteristics, and a unique history. Demeter had many personality traits and only few flaws. She was the most generous of all goddesses and was very understanding and respectful. That is why she gained the sympathy and favor of the other Olympian gods. Not only she had the their sympathy but beyond that she also had the ability to truly sympathize with humans. In addition Demeter was very modest and shy. One of her flaws is her ability to invoke curses. For instance, â€Å"she cursed King Erysichton with insatiable hunger and endow mystical ability in sorcerers and mystics that know how to call upon her such as Clea† (marvunapp.com/Appendix/demeterc.htm). Although Demeter is a goddess, she has a family background. Demeter is the daughter of Cronus and Rhea; also sister of Zeus, Poseidon, Pluto, Hera and Hestia. â€Å"She never married† (theoi.com/Summary/Demeter.html), but was lovers with her brother Zeus. She had many children but her daughter Persephone was the most known one because of the famous myth. Haides fell in love with Persephone and Zeus helped him to kidnap her from her mother and take her to the Underworld. When Demeter found out that Haides had kidnapped her beloved daughter she became very angry. She searched everywhere for her and even brought â€Å"deadly starvation down upon mankind until Zeus agreed to let her return† (theoi.com/Summary/Demeter.html). Unfortunately when Hermes was sent to the Underworld in search of Persephone, he gave her a pomegranate and Persephone ate it. As a consequence of this, Persephone was forced to stay with Hades for a third of the year. â€Å"Only when Persephone is with her, Demeter lets things grow† (Micha F. Lindemans, Demeter.) Since agriculture played an important role in Greek history, Demeter was worshipped in many different ways. Particularly, she was worshipped in agricultural societies. Furthermore, the first loaf of bread from the harvest was sacrificed in her honor. Also, Demeter was often portrayed as a solemn woman, often wearing a wreath of braided ears of corn. Some regions were she was worshipped at were Attika, Messenia, and Ena. Demeter’s primary festival was the Athenian Thesmophoria. It celebrates the half of the year when Demeter didnt work as the goddess of the harvest; she spent this half of the year with her daughter. If we had lived in the ancient Greek times, then Demeter would have been very significant in our lives. Demeter taught humans how to grow, preserve, and prepare grain. Again, earth could not produce without her allowing it. The Greeks experienced that themselves when Persephone was taken away from her mother. Her history is very unique, not only her search for Persephone and the consequences that followed, but also many other myths.Above that. she is the mother of earth itself and is â€Å"invoked as the bringer of the seasons† (Micha F. Lindemans, Demeter.) Research Papers on The Goddess Demeter - Greek History EssayCanaanite Influence on the Early Israelite ReligionMind TravelBook Review on The Autobiography of Malcolm XHarry Potter and the Deathly Hallows EssayComparison: Letter from Birmingham and CritoHonest Iagos Truth through DeceptionWhere Wild and West MeetThe Masque of the Red Death Room meaningsGenetic EngineeringInfluences of Socio-Economic Status of Married Males

The Fifth Replies of Descartes Essay Example | Topics and Well Written Essays - 1000 words

The Fifth Replies of Descartes - Essay Example The Fifth Replies of Descartes The argument in question is the argument of Discourse. The problem with this counter argument is the inherent bias. There is a premise and theres a conclusion if one accepts the premise the conclusion must be accepted. Renà ©e Descartes says that he knows he exists it is inherent that he knows what he is and what his nature is, it is the very definition of establishing his existence. This knowledge (of existing) cannot be separated from the knowledge of what that existence is about. This point can be elaborated through an example for instance one sees a bottle of water. His eyes tell him that it is there. Since this person has the premise that what his eyes see is in fact real (or existing) it means that he knows that the bottle exists. When he say that it exists it means it has certain properties that indicate that it exists. No one can say that something exists without acknowledging the properties. Existence without the knowledge of its properties is even more illogical than deriving a conclusion that existence of self also encompasses the nature of self. When Renà © Descartes say that he thinks therefore he exists, it means that he is aware of what he is and what his nature is. Otherwise there is no existence. Every existence has its properties; be it divine authority like God or as trivial as a plastic water bottle. The objection of Descartes’s claim rests with the understanding of premise. If the critics accept the premise when Renà ©e says that something exists, he also bases this by understanding some properties.