No description available.

No description available.

No description available.

No description available.

Many attempts have been made to explain the nature of auditory verbal hallucinations (AVH) or the phenomenon of “hearing voices”. In the contemporary discussion of auditory verbal hallucinations, the raw material of the voices of AVH is seen as either inner speech, a spontaneously activated auditory experience, or imagined speech. Some contemporary theories of AVH are self-proclaimed self-monitoring theories which claim that AVH are the result of a failure of self-monitoring of some raw material, while other theories claim that AVH are produced without a self-monitoring failure. In this paper, I argue that even the theories that claim to not rely on self-monitoring, are in fact selfmonitoring theories. I argue that any viable theory of AVH will need to be a self-monitoring theory. Further, I argue that Daniel Gregory’s imagined speech self-monitoring theory is the most parsimonious and complete of the explanatory theories of AVH since it is able to explain characteristics that other theories cannot, including AVH that take place in what seem to be the voices of others, perceived spatial location, intensity of sound, multiple voices, and the intermittent nature of AVH. Further, I show that the imagined speech theory can be well integrated into a general understanding of schizophrenia, while still retaining its explanatory power for all populations that experience AVH, not just schizophrenics, and that for these reasons, it is the strongest contemporary explanatory theory of auditory verbal hallucinations. / Många försök har gjorts för att förklara naturen av auditiva verbala hallucinationer (AVH) eller fenomenet att "höra röster". I den samtida diskussionen om auditiva verbala hallucinationer ses råmaterialet till rösterna i AVH som antingen inre tal, en spontant aktiverad auditiv upplevelse, eller inbillat tal. Vissa samtida teorier om AVH är självutnämnda teorier om självövervakning som hävdar att AVH är resultatet av ett misslyckande i självövervakningen av något råmaterial, medan andra teorier hävdar att AVH produceras utan ett misslyckande i självövervakning. I den här uppsatsen hävdar jag att även de teorier som påstår att de inte är beroende av självövervakning i själva verket är det. Jag hävdar att varje användbar teori om AVH måste vara en teori om självövervakning. Vidare argumenterar jag att Daniel Gregorys Imagined Speech Theory är den mest sparsamma och fullständiga av de förklarande teorierna om AVH eftersom den kan förklara egenskaper som andra teorier inte kan förklara, inklusive AVH som äger rum i vad som verkar vara andras röster, upplevd rumslig placering, ljudintensitet, flera röster och AVH:s intermittenta karaktär. Vidare visar jag att The Imagined Speech Theory kan integreras väl i en allmän förståelse av schizofreni, samtidigt som den behåller sin förklaringskraft för alla populationer som upplever AVH, inte bara schizofreniker, och att den av dessa skäl är den starkaste samtida förklaringsteorin för auditiva verbala hallucinationer. / De nombreuses tentatives ont été faites pour expliquer la nature des hallucinations auditives verbales (HAV) ou le phénomène des "voix entendues". Dans la discussion contemporaine sur les hallucinations auditives verbales, la matière première des voix des HAV est considérée comme étant soit un discours intérieur, soit une expérience auditive activée spontanément, soit un discours imaginé. Certaines théories contemporaines de l'HVA sont des théories autoproclamées d'autosurveillance qui prétendent que l’HVA est le résultat d'un échec d'autosurveillance d'une certaine matière première, tandis que d'autres théories prétendent que l’HVA est produite sans échec d'autosurveillance. Dans cet essai, je soutiens que même les théories qui prétendent ne pas reposer sur une autosurveillance, sont en fait des théories d'autosurveillance. Je soutiens que toute théorie viable de l’HAV devra être une théorie d'autosurveillance. En outre, je soutiens que la théorie de l'autosurveillance de la parole imaginée (The Imagined Speech Theory) de Daniel Gregory est la plus parcimonieuse et la plus complète des théories explicatives de l’HAV puisqu'elle est capable d'expliquer des caractéristiques que les autres théories ne peuvent pas expliquer, y compris les HAV qui a lieu dans ce qui semble être la voix des autres, la localisation spatiale perçue, l'intensité du son, les voix multiples et la nature intermittente. En outre, je montre que la théorie de la parole imaginée peut être bien intégrée dans une compréhension générale de la schizophrénie, tout en conservant son pouvoir explicatif pour toutes les populations qui font l'expérience des HAV, pas seulement les schizophrènes, et que pour ces raisons, c'est la théorie explicative contemporaine la plus solide des hallucinations auditives verbales.

Humans and other animals systematically discount the value of future rewards as a function of their delay, and individual differences in the steepness of this ``delay discounting'' are predictive of a range of important real-world outcomes. Episodic future thinking, the mental simulation of episodes in the personal future, is one means by which to curb delay discounting. This thesis seeks to contribute to our understanding of how this effect occurs. The account that predominates in the literature is that episodic future thinking simulates the experience of future rewards, enabling their undiscounted value to be appreciated in the present. This thesis takes this account as a starting point, formalizing it in a mathematical model and carrying out several experimental studies to test its predictions. We find that key predictions are not borne out and develop an alternative account in which simulated experience plays a less central role. / Thesis / Doctor of Philosophy (PhD) / Pursuing our goals for the future usually means sacrificing immediate gratification, yet we often make decisions that are not in our best interest over the long term. This is because we assign lower subjective value to future rewards the further they are from the present. Individuals differ in how much they devalue future rewards, and these differences are related to many real-world outcomes. Our tendency to devalue future rewards is reduced when we vividly imagine the future in a process called ``episodic future thinking,'' and this thesis seeks to understand how this effect occurs. The most obvious explanation would seem to be that episodic future thinking ``simulates'' the experience of future rewards and allows us to recognize their value in the present. However, using results from several experimental studies, I argue that this may not be the best explanation after all, and I develop an alternative.

Remote sensing imagery has proven useful in studying the coastal geomorphology of les Iles de la Madeleine. Standard panchromatic photography provided the basis for mapping of the island and aided in the interpretation of the evolution of this tombolo system. This study presents a systematic evaluation of five types of remotely sensed data: (1) colour infrared photography, (2) conventional colour photography, (3) panchromatic photography (red and green bands), (4) black and white infrared photography and (5) thermal line scan imagery as applied to the southern portion of les Iles de la Madeleine. The results of this study have shown that beach investigations are enhanced through the use of multisensor imagery, and that colour infrared provides the best single source for data aquisition. / Thesis / Bachelor of Arts (BA)

Flue-cured tobacco (Nicotiana tabacum L.) is a high value-per-acre crop that is intensively managed to optimize the yield of high quality cured leaf. Aerial remote sensing, specifically unmanned aerial vehicles (UAVs), present flue-cured tobacco producers and researchers with a potential tool for scouting and crop management. A two-year study, conducted in Southside Virginia at the Southern Piedmont Agricultural Research and Extension Center and on commercial farms, assessed the potential of aerial remote sensing in flue-cured tobacco. The effort encompassed two key objectives. First, examine the use of the enhanced normalized difference vegetation index (ENDVI) for separating flue-cured tobacco varieties and nitrogen rates. Secondly, develop hyperspectral indices and/or machine learning classification models capable of detecting Phytophthora nicotianae (black shank) incidence in flue-cured tobacco. In 2017, UAV-acquired ENDVI surveys demonstrated the ability to consistently separate between flue-cured tobacco varieties and nitrogen rates from topping to harvest. In 2018, ENDVI revealed significant differences among N-rates as early as 34 days after transplanting. Two hyperspectral indices were developed to detect black shank incidence based on differences in the spectral profiles of asymptomatic flue-cured tobacco plants compared to those with black shank symptoms. Testing of the indices showed significant differences between the index values of healthy and symptomatic plants (alpha = 0.05). In addition, the indices were able to detect black shank symptoms pre-symptomatically (alpha = 0.09). Subspace linear discriminant analysis, a machine learning classification, was also used for prediction of black shank incidence with up to 85.7% classification accuracy. / Master of Science / Unmanned Aerial Vehicle’s (UAVs) or drones, as they are commonly referred to, may have potential as a tool in flue-cured tobacco research and production. UAVs combined with sensors and cameras provide the opportunity to gather a large amount of data on a particular crop, which may be useful in crop management. Given the intensive management of flue-cured tobacco, producers may benefit from extra insight on how to better assess threats to yield such as under-fertilization and disease pressure. A two-year study was conducted in Southside Virginia at the Southern Piedmont Agricultural Research and Extension Center and on commercial farms. There were two objectives to this effort. First, assess the ability of UAV-acquired multispectral near-infrared imagery to separate flue-cured tobacco varieties and nitrogen rates. Secondly, develop hyperspectral indices and machine learning models that can accurately predict the incidence of black shank in flue-cured tobacco. Flue-cured tobacco nitrogen rates were significantly different in 2017 from 59 days after transplanting to harvest using UAV-acquired near-infrared imagery. In 2018, heavy rainfall may have led to nitrogen leaching from the soil resulting in nitrogen rates being significantly different as early as 34 days after transplanting. The imagery also showed a significant relationship with variety maturation type in the late stages of crop development during ripening. Two hyperspectral indices were developed and one machine learning model was trained. Each had the ability to detect black shank incidence in fluecured tobacco pre-symptomatically, as well as separated black shank infested plants from healthy plants.

NeuroGaze is a novel Virtual Reality (VR) interface that integrates electroencephalogram (EEG) and eye tracking technologies to enhance user interaction within virtual environments (VEs). Diverging from traditional VR input devices, NeuroGaze allows users to select objects in a VE through gaze direction and cognitive intent captured via EEG signals. The research assesses the performance of the NeuroGaze system against conventional input devices such as VR controllers and eye gaze combined with hand gestures. The experiment, conducted with 20 participants, evaluates task completion time, accuracy, cognitive load through the NASA-TLX surveys, and user preference through a post-evaluation survey. Results indicate that while NeuroGaze presents a learning curve, evidenced by longer average task durations, it potentially offers a more accurate selection method with lower cognitive load, as suggested by its lower error rate and significant differences in the physical demand and temporal NASA-TLX subscale scores. This study highlights the viability of incorporating biometric inputs for more accessible and less demanding VR interactions. Future work aims to explore a multimodal EEG-Functional near-infrared spectroscopy (fNIRS) input device, further develop machine learning models for EEG signal classification, and extend system capabilities to dynamic object selection, highlighting the progressive direction for the use of Brain-Computer Interfaces (BCI) in virtual environments.

A large literature has not reached consensus on foreign aid’s economic effects. Using geolocated aid data and daytime satellite images over nearly 10,000 African neighborhoods, I examine the economic growth impact of World Bank and Chinese aid to 36 Africa countries from 2002-2013, covering 88% of the continent’s population, by sector (e.g. Health, Education, Water Supply and Sanitation, etc.).  I estimate each funder and aid sector’s average treatment effect with an inverse probability weighting approach and adjust for two types of confounders: those I provide in a tabular format and proxies based on satellite images of each neighborhood. The use of image-based confounders may reduce bias due to omitted variables and measurement errors when unobserved or mis-measured variables are visible remotely.  To measure economic outcomes, I use a new wealth index generated by a machine learning algorithm trained to associate USAID-funded DHS survey wealth measures with daytime and nighttime satellite imagery from the same years and locations. The availability of the wealth estimate for 3-year periods over thirty years enabled the analysis to use panel data and fixed effects at the second administrative division (e.g. county, district, city) level. The results are heterogenous across sectors but generally show small positive effects of World Bank aid and larger positive effects of Chinese aid.  Substantive results are generally robust to the choice of computer vision image model, except for three funder-sectors where wide confidence intervals make one model but not the other statistically insignificant.