Forecasting the Progression of Alzheimer's Disease Using Neural Networks and a Novel Pre-Processing Algorithm

Alzheimer's disease (AD) is the most common neurodegenerative disease in older people. Despite considerable efforts to find a cure for AD, there is a 99.6% failure rate of clinical trials for AD drugs, likely because AD patients cannot easily be identified at early stages. This project investigated machine learning approaches to predict the clinical state of patients in future years to benefit AD research. Clinical data from 1737 patients was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and was processed using the "All-Pairs" technique, a novel methodology created for this project involving the comparison of all possible pairs of temporal data points for each patient. This data was then used to train various machine learning models. Models were evaluated using 7-fold cross-validation on the training dataset and confirmed using data from a separate testing dataset (110 patients). A neural network model was effective (mAUC = 0.866) at predicting the progression of AD on a month-by-month basis, both in patients who were initially cognitively normal and in patients suffering from mild cognitive impairment. Such a model could be used to identify patients at early stages of AD and who are therefore good candidates for clinical trials for AD therapeutics.Comment: 10 pages; updated acknowledgement

Human/Farm Animal Relationships

There are various combinations of human beings and farm animals. This paper attempts to evaluate those few studies of humans handling farm animals within a prescribed environment. Personality traits of dairy farmers and livestock people as determined by the Eysenck Personality Inventory (Eysenck 1977) need further study (Seabrook 1974; Arave and Brown 1979). Seabrook\u27s sample size was small (20 herds) and these herds were criticized for having low yields while Arave and Brown\u27s questionnaire did not go far enough

Aspects of the conservation biology of an exploited population of migratory European river lamprey (Lampetra fluviatilis)

Populations of anadromous lampreys across the globe have declined in recent years as a result of anthropogenic impacts. One such species is the European river lamprey, Lampetra fluviatilis, which has declined due to the consequences of factors such as pollution, over-exploitation and anthropogenic barriers. The Humber River Basin contains one of Western Europe’s most important populations of L. fluviatilis but this population may be threatened by the impacts of anthropogenic barriers and commercial exploitation for angling bait. This thesis’s objectives were two-fold. Firstly, to evaluate the efficiency of a semi-formalised nature like bypass specifically designed, but previously untested, to allow upstream passage of migrating river lamprey past a weir at the tidal limit. Secondly, to determine the proportion of UK coarse predator anglers who use lamprey as bait and to gauge their opinions and knowledge regarding the use of lamprey as bait. Passive Integrated Transponder and acoustic telemetry indicated that although attraction efficiency into the bypass was high, up to 70.8 % (calculated as the number of acoustically tagged lamprey that entered the bypass as a percentage of those detected downstream of the weir), the bypass was very inefficient with an estimated passage efficiency of 5.4 % (calculated as the number of PIT tagged lamprey which successfully used the bypass to travel upstream of Naburn weir as a percentage of those that were detected within the bypass during the period of time that the most upstream PIT antennas was operational). Most lamprey that passed the weir directly when the weir was drowned rather than using the bypass. It appears that periods of high river stage increased attraction into the bypass but also created conditions unsuitable for passage through the bypass due to high velocities, especially at an undershot control sluice at the upstream end. Telephone questionnaires of freshwater predator (principally pike, Esox lucius) anglers revealed that 67.8 % of participants used lamprey as bait to some degree and 39.1 % of participants would prefer lamprey to be sourced from the UK. Although participants knew little about the source of their lamprey, they generally agreed that bait companies should source their baits sustainably, that lamprey should be conserved and if lampreys were threatened by exploitation, a ban on their use as angling bait should be implemented. However, the results indicate the existence of a subset of anglers who highly value lamprey as bait and so may oppose conservation efforts or restrictions on use. Overall, this thesis indicates that upstream passage solutions for weaker swimming fish should be focused on removing redundant barriers in waterways rather than creating novel designs for fishways. Additionally, the lack of knowledge surrounding the origin of angling baits combined with the widespread use of threatened species highlights the lack of transparency within the angling bait industry, an issue that deserves further investigation

Milking machines and practices on 60 Illinois dairy farms

Cover title

Anomalous U(1) symmetry and lepton flavor violation

We show that in a large class of models based on anomalous U(1) symmetry which addresses the fermion mass hierarchy problem, leptonic flavor changing processes are induced that are in the experimentally interesting range. The flavor violation occurs through the renormalization group evolution of the soft SUSY breaking parameters between the string scale and the U(1)_A breaking scale. We derive general expressions for the evolution of these parameters in the presence of higher dimensional operators. Several sources for the flavor violation are identified: flavor-dependent contributions to the soft masses from the U(1)_A gaugino, scalar mass corrections proportional to the trace of U(1)_A charge, non-proportional A-terms from vertex corrections, and the U(1)_A D-term. Quantitative estimates for the decays \mu -> e \gamma and \tau -> \mu \gamma are presented in supergravity models which accommodate the relic abundance of neutralino dark matter.Comment: References added, typos corrected, 28 pages LaTeX, includes 14 eps figure

Implications of a Massless Neutralino for Neutrino Physics

We consider the phenomenological implications of a soft SUSY breaking term BN at the TeV scale (here B is the U(1)_Y gaugino and N is the right-handed neutrino field). In models with a massless (or nearly massless) neutralino, such a term will give rise through the see-saw mechanism to new contributions to the mass matrix of the light neutrinos. We treat the massless neutralino as an (almost) sterile neutrino and find that its mass depends on the square of the soft SUSY breaking scale, with interesting consequences for neutrino physics. We also show that, although it requires fine-tuning, a massless neutralino in the MSSM or NMSSM is not experimentally excluded. The implications of this scenario for neutrino physics are discussed.Comment: 14 pages, latex, no figure

EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others' Preference

Humans often attempt to predict what others prefer based on a narrow slice of experience, called thin-slicing. According to the theoretical bases for how humans can predict the preference of others, one tends to estimate the other's preference using a perceived difference between the other and self. Previous neuroimaging studies have revealed that the network of dorsal medial prefrontal cortex (dmPFC) and right temporoparietal junction (rTPJ) is related to the ability of predicting others' preference. However, it still remains unknown about the temporal patterns of neural activities for others' preference prediction through thin-slicing. To investigate such temporal aspects of neural activities, we investigated human electroencephalography (EEG) recorded during the task of predicting the preference of others while only a facial picture of others was provided. Twenty participants (all female, average age: 21.86) participated in the study. In each trial of the task, participants were shown a picture of either a target person or self for 3 s, followed by the presentation of a movie poster over which participants predicted the target person's preference as liking or disliking. The time-frequency EEG analysis was employed to analyze temporal changes in the amplitudes of brain oscillations. Participants could predict others' preference for movies with accuracy of 56.89 ?? 3.16% and 10 out of 20 participants exhibited prediction accuracy higher than a chance level (95% interval). There was a significant difference in the power of the parietal alpha (10~13 Hz) oscillation 0.6~0.8 s after the onset of poster presentation between the cases when participants predicted others' preference and when they reported self-preference (p < 0.05). The power of brain oscillations at any frequency band and time period during the trial did not show a significant correlation with individual prediction accuracy. However, when we measured differences of the power between the trials of predicting other's preference and reporting self-preference, the right temporal beta oscillations 1.6~1.8 s after the onset of facial picture presentation exhibited a significant correlation with individual accuracy. Our results suggest that right temporoparietal beta oscillations may be correlated with one's ability to predict what others prefer with minimal information