117,374 research outputs found
John Wesley letter to John Valton, 1782 March 24
No full textTo
Mr [John] Valton
At Birstal[l] near Bradforth [Bradford]
Leeds [in another hand]
Yorkshire
Madely [Madeley]
March 24, 1782
My dear brother
I have no objection to your proposal: let the trustees give such a bond as you mention and see that the scarecrow house be made as handsome and convenient as the house at Leeds is. In particular, I beg all the windows may be sashes opening downward. Do not spoil the house to save a little expense.
I think you have my plan:
Huddersfield, April 23
Halifax, Wed. 24
Kighley [Keighley], Sat. 27
Bingley, Sund. 28
Yeadon, Mond. 29
Otley, Wedn. May 1.
Frid. 3, Bradforth [Bradford]. Sat. 4, Wakefield. Sund. 5, Birstal[l], noon. Evening, Bradforth [Bradford]. Mond., Dawgreen. Tues., Leeds. I am
Your affectionate friend and brother
J WesleyPresented to Page A. Thomas in celebration of 35 years of service to Bridwell Library
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Square Dancing with the Stars to Enhance Dynamic Hirschman Linkages?
No full textIn this Presidential Address, the author takes the reader on a reconnaissance of his life and time as a regional scientist. He points out scenery he found scintillating along the way, hoping that some may pick up the banner and chew on a few of the ideas for a while. He suggests a revisit to Albert O. Hirschman’s notion of key sectors and more empirical analysis related to Marcus Berliant’s and Masahisa Fujita’s notion of knowledge creation and transfer.Presidential Address, San Antonio, Texas, March 29, 2014 (53rd Meetings of the Southern Regional Science Association
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Impaired reinforcement learning and Bayesian inference in psychiatric disorders: from maladaptive decision making to psychosis in schizophrenia
No full textComputational modelling has been gaining an increasing amount of support from the
neuroscience community as a tool to assay cognition and computational processes in
the brain. Lately, scientists have started to apply computational methods from neuroscience
to the study of psychiatry to gain further insight into the mechanisms leading
to mental disorders. In fact, only recently has psychiatry started to move away from
categorising illnesses using behavioural symptoms in an attempt for a more biologically
driven diagnosis. To date, several neurobiological anomalies have been found
in schizophrenia and led to a multitude of conceptual framework attempting to link
the biology to the patients’ symptoms. Computational modelling can be applied to
formalise these conceptual frameworks in an effort to test the validity or likelihood
of each hypothesis. Recently, a novel conceptual model has been proposed to describe
how positive symptoms (delusions, hallucinations and thought disorder) and
cognitive symptoms (poor decision-making, i.e. “executive functioning”) might arise
in schizophrenia. This framework however, has not been tested experimentally or
against computational models. The focus of this thesis was to use a combination of
behavioural experiments and computational models to independently assess the validity
of each component that make up this framework.
The first study of this thesis focused on the computational analysis of a disrupted
prediction-error signalling and its implications for decision-making performances in
complex tasks. Briefly, we used a reinforcement-learning model of a gambling task
in rodents and disrupted the prediction-error signal known to be critical for learning.
We found that this disruption can account for poor performances in decision-making
due to an incorrect acquisition of the model of the world. This study illustrates how
disruptions in prediction-error signalling (known to be present in schizophrenia) can
lead to the acquisition of an incorrect world model which can lead to poor executive
functioning or false beliefs (delusions) as seen in patients.
The second study presented in this thesis addressed spatial working memory performances
in chronic schizophrenia, bipolar disorder, first episode psychosis and family
relatives of DISC1 translocation carriers. We build a probabilistic inference model
to solve the working memory task optimally and then implemented various alterations
of this model to test commonly debated hypotheses of cognitive deficiency
in schizophrenia. Our goal was to find which of these hypotheses accounts best for
the poor performance observed in patients. We found that while the performance at
the task was significantly different for most patients groups in comparison to controls,
this effect disappeared after controlling for IQ in one group. The models were
nonetheless fitted to the experimental data and suggest that working memory maintenance
is most likely to account for the poor performances observed in patients. We
propose that the maintenance of information in working memory might have indirect
implications for measures of general cognitive performance, as these rely on a correct
filtering of information against distractions and cortical noise.
Finally the third study presented in this thesis assessed the performance of medicated
chronic schizophrenia patients in a statistical learning task of visual stimuli
and measured how the acquired statistics influenced their perception. We find that
patient with chronic schizophrenia appear to be unimpaired at statistical learning
of visual stimuli. The acquired statistics however appear to induce less expectation-driven
‘hallucinations’ of the stimuli in the patients group than in controls. We find
that this is in line with previous literature showing that patients are less susceptible
to expectation-driven illusions than controls. This study highlights however the idea
that perceptual processes during sensory integration diverge from this of healthy controls.
In conclusion, this thesis suggests that impairments in reinforcement learning and
Bayesian inference appear to be able to account for the positive and cognitive symptoms
observed in schizophrenia, but that further work is required to merge these
findings. Specifically, while our studies addressed individual components such as
associative learning, working memory, implicit learning & perceptual inference, we
cannot conclude that deficits of reinforcement learning and Bayesian inference can
collectively account for symptoms in schizophrenia. We argue however that the studies
presented in this thesis provided evidence that impairments of reinforcement
learning and Bayesian inference are compatible with the emergence of positive and
cognitive symptoms in schizophrenia
Letter from unknown writer to Jesse L. Boyce
No full textLetter to Jesse L. Boyce from unknown author (possibly Jack) about the investigation into the powder magazine located in the Grand Canyon. Some personal news is included in the letter such as the writer's marriage to the daughter of C.A. Taylor, former Supervisor of Cochise County
Free-radical approaches to new fluorocarbon derivatives
No full textThis thesis is concerned with the free-radical addition of nitrogen, silicon and oxygen containing compounds to fluoroalkenes and the chemistry of some of the adducts produced. Free-radical adducts of many amines cannot be produced directly since nucleophilic attack on the fluoroalkene is often the preferred reaction pathway. An alternative route to primary and secondary mono-amine adducts via N-trimethylsilylamines has been developed. An alternative synthesis of di-amine adducts via amides has met with some success. Free-radical additions of organosilicon compounds to fluoroalkenes have produced a variety of fluorosilicon adducts. The chemistry of some of these adducts has been investigated. Work with mono- and di-oxygen functional compounds has provided information on the scope and limitations of this type of free-radical addition reaction. The dehydrofluorination of ether/hexafluoropropene mono- and di-adducts has been investigated and some novel dienes have been produced. Polymers containing amide or ether groups added to hexafluoropropene under free-radical conditions. The use of a solvent dramatically increased the degree of this incorporation. The electrochemical fluorination of cyclic ether/hexafluoropropene di-adducts has been investigated. Good recoveries of highly fluorinated products were obtained, indicating that these types of adducts are good starting materials for electrochemical fluorination
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Modeling maladaptive decision-making in a rat version of the Iowa Gambling Task
No full textDeficits in decision-making have been repeatedly observed in various psychiatric disorders (i.e. ADHD, Pathological Gambling, Mania, OCD and Substance Abuse) as well as in frontal lobe patients. Such decision-making deficits are often assessed using the Iowa Gambling task (IGT) [1]. The IGT represents a realistic decision-making task where subjects are asked to choose between targets associated with rewards and penalties of varying likelihood and amplitude. Previous studies have shown that when healthy participants take the IGT, around a third of these perform poorly, similar to psychiatric patients [1].Recently, these behavioral findings were successfully translated to animal research in a rodent version of the IGT, the Rat Gambling Task (RGT). In common with human studies, it was found that a third of a healthy population of rats exhibited poor decision-making performances [2]. The rats were tested in other tasks aiming at characterizing behavioral traits such as impulsivity, sensitivity to reward, cognitive inflexibility and risk seeking. Poor decision makers were always characterized by high scores for a combination of these behavioral traits.Here we use a model of learning and decision-making in the RGT to answer the following questions: (1) how do the behavioral traits described above influence learning; (2) how is this manifested in terms of their decision-making performance?In order to model the learning and decision process of the RGT, we used a TD-learning algorithm [3]. The model agent experiences the environment by learning the values of rewards and penalties for each state using trial and error sampling. As the agent gets a more accurate representation of the environment, it takes more appropriate decisions, using a ‘softmax’ action selection process. The RGT is modeled as a Markov decision process and we extended the classical TD-learning algorithm by incorporating risk seeking [4], reward sensitivity and cognitive inflexibility. These behavioral traits were implemented independently and influence either the learning rate or the perception of rewards by the agent. The parameters of the model were extracted for each rat by fitting their performance to the model.We found that the model could account for the performances of good and poor subpopulations of decision makers. Additionally, the parameters defining the behavioral traits extracted from the model correlated significantly with those measured experimentally for the poor and good decision makers’ subgroups. The model was also able to predict the inflexibility of poor decision makers during reversal conditions.Our work supports the hypothesis that it is a combination of high scores for risk seeking, sensitivity to reward and cognitive inflexibility that lead to poor decision-making performances. According to the model, behavioral traits affect the learning process of the subjects by altering the estimated value of the received rewards and reducing their ability to reverse their initial estimations. This results in an incorrect perception of the environment, leading to an optimal decision-making according to their world representation but aberrant according to the real outcome of the task.<br/
Sarah L. Blum Author Visit - Warrior Nurse: PTSD and Healing
No full textHear Sarah L. Blum, author of Women Under Fire: Abuse in the Military, discuss her newest book, Warrior Nurse: PTSD and Healing followed by a Q&A and book signing.
Sarah L. Blum is a decorated Vietnam veteran who served as an operating room nurse during the intense fighting of 1967. In recognition of her service, she was awarded the Army Commendation Medal.
Sponsored by CWU Veterans Center and CWU Libraries.https://digitalcommons.cwu.edu/libraryevents/1252/thumbnail.jp
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