Psychologist Bias in Implicit Responding to Religiously Divergent Nonpatient
Targets and Explicit Responding to Religiously Divergent Patients  Jennifer Ruff

Abstract
This study examines how psychologists responded to a mainstream group believed to
be most religiously diverse from them, Evangelical Christians (ECs). Clinicians were
presented with two vignettes which described patients with comparable symptoms of
generalized anxiety disorder, who differed on either religiosity or career and volunteer
activity conditions. They rated each on measures of empathy and prognosis. Clinicians
completed a scale that measures attitudes about Christian beliefs that range from
orthodox to liberal positions. Clinicians’ automatic responding to EC targets was also
compared to automatic responding to Secular or No Religion targets on a timed implicit
measure, which reduces the opportunity to censor bias. Liberality of religious attitudes in
relation to Christian beliefs was associated with less cognitive and affective empathy and
a poorer prognosis for the EC patient. On the implicit measure, religiously liberal
clinicians’ attitudes toward Christian beliefs was associated with negative responding to
EC targets compared to Secular or No Religion targets. Last, given the opportunity to do
so, clinicians’ motivation to control prejudice reactions did not moderate the effects of
automatic negative responding to EC’s on self-reported expressions of empathy or
prognosis in relation to the EC vignette patient.  Full Dissertation



Acceleration of Finite Field Arithmetic with an Application to Reverse Engineering Genetic Networks  Edgar Ferrer

Abstract
This research is originally motivated by an application of computational biology where genetic networks are modeled by means of finite fields. We present a set of efficient algorithms for finite field arithmetic over GF(2m), which are implemented on a High Performance Reconfigurable Computing platform. In this way, we deliver new and efficient designs on Field Programmable Gate Arrays (FPGA) for accelerating finite-field arithmetic. We have designed a fast and space-saving multiplier, which has been used for creating other efficient architectures for inversion and exponentiation which have in turn been used for developing a new and efficient architecture for finite-field interpolation. Full Dissertation