Miracle-dz/UniFAR-FTUs huggingface dataset:
Preference Change : Approaches from Philosophy, Economics and Psychology

PREFACE, LIST OF AUTHORS 1. PREFERENCE CHANGE - AN INTRODUCTION Till Grune-Yanoff and Sven Ove Hansson 2. THREE ANALYSES OF SOUR GRAPES Brian Hill 3. FOR BETTER OR FOR WORSE: DYNAMIC LOGICS OF PREFERENCE Johan van Benthem 4. PREFERENCE, PRIORITIES AND BELIEF Dick de Jongh and Fenrong Liu 5. WHY THE RECEIVED MODELS OF CONSIDERING PREFERENCE CHANGE MUST FAIL Wolfgang Spohn 6. EXPLOITABLE PREFERENCE CHANGES Edward F. McClennen 7. RECURSIVE SELF-PREDICTION IN SELF-CONTROL AND ITS FAILURE George Ainslie 8. FROM BELIEF REVISION TO PREFERENCE CHANGE Till Grune-Yanoff and Sven Ove Hansson 9. PREFERENCE UTILITARIANISM BY WAY OF PREFERENCE CHANGE? Wlodek Rabinowicz 10. THE ETHICS OF NUDGE Luc Bovens 11. PREFERENCE KINEMATICS Richard Bradley 12. POPULATION-DEPENDENT COSTS OF DETECTING TRUSTWORTHINESS - AN INDIRECT EVOLUTIONARY ANALYSIS Werner Guth, Hartmut Kliemt and Stefan Napel
Noise removal at the rod synapse of mammalian retina

Mammalian rods respond to single photons with a hyperpolarization of about 1 mV which is accompanied by continuous noise. Since the mammalian rod bipolar cell collects signals from 20–100 rods, the noise from the converging rods would overwhelm the single-photon signal from one rod at scotopic intensities (starlight) if the bipolar cell summed signals linearly (Baylor et al., 1984). However, it is known that at scotopic intensities the retina preserves single-photon responses (Barlow et al., 1971; Mastronarde, 1983). To explore noise summation in the rod bipolar pathway, we simulated an array of rods synaptically connected to a rod bipolar cell using a compartmental model. The performance of the circuit was evaluated with a discriminator measuring errors in photon detection as false positives and false negatives, which were compared to physiologically and psychophysically measured error rates. When only one rod was connected to the rod bipolar, a Poisson rate of 80 vesicles/s was necessary for reliable transmission of the single-photon signal. When 25 rods converged through a linear synapse the noise caused an unacceptably high false positive rate, even when either dark continuous noise or synaptic noise where completely removed. We propose that a threshold nonlinearity is provided by the mGluR6 receptor in the rod bipolar dendrite (Shiells & Falk, 1994) to yield a synapse with a noise removing mechanism. With the threshold nonlinearity the synapse removed most of the noise. These results suggest that a threshold provided by the mGluR6 receptor in the rod bipolar cell is necessary for proper functioning of the retina at scotopic intensities and that the metabotropic domains in the rod bipolar are distinct. Such a nonlinear threshold could also reduce synaptic noise for cortical circuits in which sparse signals converge.
The Level of Hepatitis B Virus Replication Is Not Affected by Protein ISG15 Modification but Is Reduced by Inhibition of UBP43 (USP18) Expression1

Hepatitis B virus (HBV) causes both acute and chronic infection of the human liver and is associated with the development of liver cirrhosis and hepatocellular carcinoma. UBP43 (USP18) is known as an ISG15-deconjugating enzyme and an inhibitor of type I IFN signaling independent of its enzyme activity. In this study, we examined the role of these two previously identified functions of UBP43 in the innate immune response to HBV viral infection. As an in vivo HBV replication model system, a replication-competent DNA construct was injected hydrodynamically into the tail veins of mice. Although the lack of ISG15 conjugation in the absence of ISG15-activating enzyme UBE1L (UBA7) did not affect the level of HBV replication, the steady-state level of HBV DNA was substantially reduced in the UBP43-deficient mice in comparison to the wild-type controls. In addition, introduction of short hairpin RNA against UBP43 resulted in substantially lower levels of HBV DNA at day 4 postinjection and higher levels of ISG mRNAs. These results suggest that HBV infection is more rapidly cleared if UBP43 expression is reduced. Furthermore, these results illustrate the therapeutic potential of modulating UBP43 levels in treating viral infection, especially for viruses sensitive to IFN signaling.
A Moment-based 3D Object Tracking Algorithm for High-speed Vision

In this paper we propose a method of realizing continuous tracking of a three-dimensional object by calculating moments of a translating and rotating object whose shape is known, either analytically or by using a table, and matching them with those of the input image. In simulation, the position and orientation is accurately recognized. Using a noise model and particle filter, we show that the position and orientation can be recognized even with noisy images.
E‐business and organisational change: Reconciling traditional values with business transformation

While much attention has recently been focused on the problems facing Internet start‐ups, the challenge of e‐business affects a much broader constituency of organisations. For established companies, the key challenge is one of change. Such companies must rethink fundamental aspects of company strategy, which may lead to a radical overhaul of existing ways of doing business, with company structure and culture becoming much more customer‐focused. Resistance at all company levels may need to be overcome, with a need to build commitment and consensus around e‐business strategies. However, companies must also deal with a paradox in e‐business change. As the “dot.com” crash showed, there are many strengths in “bricks and mortar” companies. Evolving a new business model based around “e‐enablement” must therefore avoid the “baby and bathwater syndrome”. Only by recognising and rising to these challenges and dilemmas, and devoting sufficient time, resources and expertise to them, will companies make a success of their e‐business ventures.
Three-Source Extractors for Polylogarithmic Min-Entropy

We continue the study of constructing explicit extractors for independent general weak random sources. The ultimate goal is to give a construction that matches what is given by the probabilistic method - an extractor for two independent n-bit weak random sources with min-entropy as small as log n + O(1). Previously, the best known result in the two-source case is an extractor by Bourgain [1], which works for min-entropy 0.49n; and the best known result in the general case is an earlier work of the author [2], which gives an extractor for a constant number of independent sources with min-entropy polylog(n). However, the constant in the construction of [2] depends on the hidden constant in the best known seeded extractor, and can be large; moreover the error in that construction is only 1/poly(n). In this paper, we make two important improvements over the result in [2]. First, we construct an explicit extractor for three independent sources on n bits with min-entropy k ≥ polylog(n). In fact, our extractor works for one source with poly-logarithmic min-entropy and another independent block source with two blocks each having poly-logarithmic min-entropy. This significantly improves previous constructions, and the next step would be to break the 0.49n barrier in two-source extractors. Second, we improve the error of the extractor from 1/poly(n) to 2-kΩ(1), which is almost optimal and crucial for cryptographic applications. Some of our techniques may be of independent interests.
Design of Modified Shannon Based Full Adder Cell Using PTL Logic for Low Power Applications

The proposed full adder cell for low power applications has been implemented using Shannon decomposition based technique for sum and carry operation. By using the Shannon’s theorem the transistor count has decreased thereby the total chip area gets minimized; hence the power also gets reduced to a considerable amount. The designs are simulated using SPICE tool which results in 25.6% improvement in power dissipation and 20% improvement in transistor count for the Modified Shannon based full adder cell when compared with MCIT based full adder cell. Keywords— Shannon’s technique, power, transistor count, area, propagation delay, PTL.
A Specification and Verification Method on Component Composition of Real-Time Reactive Systems

Timed component interface control flow automata (TCICFA) is presented to specify and verify composite real-time components' invocation behavior and timing constraint information. By analyzing TCICFAs, a component reachability graph (CRG) can be constructed based on the constructing algorithm we presented. Each node in CRG is equipped with a state formula which has been computed with the construction of the CRG, and assertions can be made at each node to express safety, real-time liveness and other trustworthiness properties. Then all kinds of nonfunctional trustworthiness properties of composite components in real-time reactive systems (RTRS) can be verified based on the CRG using a SAT solver.
Introduction of Insect Antifreeze Protein Genes into the Model Plant Arabidopsis thaliana

Injury inflicted by frost and freezing is found in all plants exposed to such damaging temperatures. Antifreeze proteins protect against these injurious temperatures by providing freeze resistance to organisms in which they occur. The expression of antifreeze proteins in a plant is a possible means of increasing the frost resistance and freeze tolerance of plants. Freeze tolerance curves of non-cold acclimated and cold acclimated A. thaliana were generated in untransformed A. thaliana. Research was conducted to obtain organisms with highly efficient antifreeze proteins. The Tenebrio molitor and Choristoneura fumiferana cDNA clones were acquired from A/F Proteins Inc. through a material transfer agreement. The antifreeze proteinencoding cDNA fragments will be cloned into an expression vector and transformed into Arabidopsis thaliana to determine if expression of antifreeze proteins will increase the freeze tolerance of A. thaliana.
Approximations to magic: finding unusual medical time series

In this work we introduce the new problem of finding time series discords. Time series discords are subsequences of longer time series that are maximally different to all the rest of the time series subsequences. They thus capture the sense of the most unusual subsequence within a time series. While the brute force algorithm to discover time series discords is quadratic in the length of the time series, we show a simple algorithm that is 3 to 4 orders of magnitude faster than brute force, while guaranteed to produce identical results.
Investigating shared aetiology between type 2 diabetes and major depressive disorder in a population based cohort

Type II diabetes (T2D) and major depressive disorder (MDD) are often co‐morbid. The reasons for this co‐morbidity are unclear. Some studies have highlighted the importance of environmental factors and a causal relationship between T2D and MDD has also been postulated. In the present study we set out to investigate the shared aetiology between T2D and MDD using Mendelian randomization in a population based sample, Generation Scotland: the Scottish Family Health Study (N = 21,516). Eleven SNPs found to be associated with T2D were tested for association with MDD and psychological distress (General Health Questionnaire scores). We also assessed causality and genetic overlap between T2D and MDD using polygenic risk scores (PRS) assembled from the largest available GWAS summary statistics to date. No single T2D risk SNP was associated with MDD in the MR analyses and we did not find consistent evidence of genetic overlap between MDD and T2D in the PRS analyses. Linkage disequilibrium score regression analyses supported these findings as no genetic correlation was observed between T2D and MDD (rG = 0.0278 (S.E. 0.11), P‐value = 0.79). As suggested by previous studies, T2D and MDD covariance may be better explained by environmental factors. Future studies would benefit from analyses in larger cohorts where stratifying by sex and looking more closely at MDD cases demonstrating metabolic dysregulation is possible. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.
Efficient Processing of Updates for Moving Objects with Varying Speed and Direction

Spatio-temporal databases aim at appropriately managing moving objects so as to support various types of queries. While much research has been conducted on developing query processing techniques, less effort has been made to address the issue of when and how to update location information of moving objects. Previous work shifts the workload of processing updates to each object which usually has limited CPU and battery capacities. This results in a tremendous processing overhead for each moving object. In this paper, we develop a novel update strategy, namely the possible region update strategy (PRUS), to explicitly indicate a time point at which object needs to update location information. As each object knows in advance when to update (meaning that it does not have to continuously check), the processing overhead can be greatly reduced. In addition, a possible region update procedure (PRUP) is designed to efficiently process the updates issued from moving objects. Extensive experiments are conducted to demonstrate the effectiveness and the efficiency of the proposed PRUS and PRUP.
Solving for Optimal Simple Rules in Rational-Expectations Models

This paper presents techniques to solve for optimal simple monetary policy rules in rational expectations models, assuming discretion. The techniques described are notable for the flexibility they provide over the structure of the policy rule being solved for. Specifically, not all state variables need enter the policy rule allowing rules optimal conditional on a given information set to be easily constructed. The algorithms described are compared to related solution methods, and applied to the model in Clarida, Gali, and Gertler (1999).
Different Approaches – Common Implications : Brain-Based And Constructivist Learning From A Paradigms And Integral Model Perspective

SYNOPSIS INTRODUCTION Brain-based learning, a recent approach in the educational literature, is related with the structure and the relation of the functioning of the brain with learning. The pioneers of this approach (Caine & Caine, 1994) have come up with principles about brain and learning. Another recent approach, constructivism, is also concerned with teaching and learning and has brought innovative perspectives to the field of education. Although these brain-based and constructivist learning approaches appear as separate domains in the educational literature, when examined closely, it emerges that they have similar fundamental principles. In a limited number of studies related with these two approaches, there is only a cursory mention of their similarities stating that constructivist learning models are brain-compatible (Gülpınar, 2005). The purpose of this study is to closely analyze brain-based and constructivist learning approaches, to reveal their relationship, and in light of paradigms and the integral model, to elaborate on the meaning and importance of this relationship for the field of education and educational research.
Feedforward Control Using Sampled-Data Polynomial for Track Seeking in Hard Disk Drives

To decrease the seek time of hard disk drives, a feedforward control method was developed by using a sampled-data polynomial. The sampled-data polynomial satisfies the boundary conditions that include the characteristics of the zero-order hold, and compensates for the discretization error caused by the zero-order hold without the need for complicated calculations. Therefore, the feedforward control using the sampled-data polynomial enables real-time calculation and does not require lookup tables which need a large amount of memory. The parameters of the sampled-data polynomial are designed by using shock-response-spectrum analysis to minimize the settling vibrations caused by the feedforward control inputs. When the proposed method was applied on a hard disk drive, it significantly reduced the amount of tracking error in the seek control and also reduced the seek time.
Videoendoscopic evaluation of the mare's uterus: III. Findings in the pregnant mare.

During a 5-year period 65 Pony and 20 Thoroughbred pregnant mares were subjected to videoendoscopic hysteroscopy from 10 to 266 days of gestation. The aims of these examinations were to 1) observe foetal and placental development in vivo (60 Pony and 10 Thoroughbred mares); 2) eliminate one of unicornuate twin conceptuses (9 Thoroughbred mares); 3) recover embryonic foetal and placental tissues non-surgically for experimental purposes (47 Pony mares); 4) induce focal separation of the placenta in late gestation as an experimental model of placentitis (5 pony mares and 1 Thoroughbred mare). It was possible to view the embryo and all constituent extra-embryonic membranes of the conceptus between Days 10 and 87 of gestation without having to perforate the allantochorion. This allowed study of physiological processes such as the coordinated uterine contractions responsible for conceptus motility between Days 7 and 17, active foetal movements, which began as early as Day 34, and invasion of chorionic girdle cells into the endometrium, which occurred between Days 34 and 38. From Day 90, vision of the foetus was reduced or prevented by the increased thickness of the allantochorion. Transendoscopic recovery of the conceptus was successful in all of 10 mares under 30 days of gestation, whereas only 10 of 18 attempts between Days 30 and 45 produced the conceptus without resorting to uterine lavage after initial rupture of the allantochorion. All 9 attempts to eliminate one of unilateral twin conceptuses were unsuccessful and the technique was abandoned as clinically unsuitable. Nevertheless, 9 of 22 (41%) single conceptuses remained viable after one or more hysteroscopic examinations. (ABSTRACT TRUNCATED AT 250 WORDS)
Figuring Time by Space: Representing sensory motion in cortical maps

How does the brain represent sensory input? When stimuli move across sensor surfaces, such as a light source moving across the retina, sound moving between the ears, or contact moving over the skin, patterns of activation propagate across sheets of neurons that form the primary sensory cortices. Understanding how the movement of stimuli across the sensor surfaces relates to the activation of the cortical sheet is a fundamental problem in neuroscience. The thesis presents a series of computational neuroscience studies, addressing how sensory stimuli are represented in mammalian primary sensory cortex. Each study constructed a model of how tactile stimuli, experienced by rodents via the array of facial whiskers, are encoded in the barrel cortex area of the primary somatosensory cortex. Each explains how the responses of cortical neurons to sensory stimuli can be predicted from their location in the cortical sheet. In each case, simple organising principles, based on cortical connection geometry and/or local learning rules, could account for how neuronal responses vary according to sensory stimuli. The success of these highly simplified descriptions of cortical circuitry at explaining complex neurophysiological data suggests an important role for sensory experience and neural inter-connection geometry in neural computation. The roles of both have been largely overlooked in recent large-scale efforts to model somatosensory cortical processing, which have focussed instead on cataloguing descriptions of neural tissue in increasing levels of detail. Using a top-down approach to modelling, the thesis generates specific hypotheses about the functional organisation of the sensory cortex, that can be used to guide future experimental work. The contribution of the thesis will therefore have been to lay the foundations of a theoretical framework for studying tactile stimulus processing in the somatosensory cortex, which is emerging as one of the most popular model systems in modern neuroscience.
To Cheat or Not To Cheat: Tryptophan Hydroxylase 2 SNP Variants Contribute to Dishonest Behavior

Although, lying (bear false witness) is explicitly prohibited in the Decalogue and a focus of interest in philosophy and theology, more recently the behavioral and neural mechanisms of deception are gaining increasing attention from diverse fields especially economics, psychology, and neuroscience. Despite the considerable role of heredity in explaining individual differences in deceptive behavior, few studies have investigated which specific genes contribute to the heterogeneity of lying behavior across individuals. Also, little is known concerning which specific neurotransmitter pathways underlie deception. Toward addressing these two key questions, we implemented a neurogenetic strategy and modeled deception by an incentivized die-under-cup task in a laboratory setting. The results of this exploratory study provide provisional evidence that SNP variants across the tryptophan hydroxylase 2 (TPH2) gene, that encodes the rate-limiting enzyme in the biosynthesis of brain serotonin, contribute to individual differences in deceptive behavior.
Scalable Logic Synthesis using a Simple Circuit Structure

This paper proposes an alternate approach to logic synthesis using rewriting and peephole optimization but from a modern perspective. We use a simple logic structure (AIGs) as the basis for all the algorithms, and rely on efficient techniques, such as precomputation, reconvergence analysis, cut enumeration, Boolean matching, exhaustive simulation of small logic cones, and local resource-aware decision procedures based on Boolean satisfiability. The result is a logic synthesis flow that is orders of magnitude faster than traditional ones and more scalable, being applicable to large industrial netlists with millions of gates.
Survival Prediction with Limited Features: a Top Performing Approach from the DREAM ALS Stratification Prize4Life Challenge

Survival prediction with small sets of features is a highly relevant topic for decision-making in clinical practice. I describe a method for predicting survival of amyotrophic lateral sclerosis (ALS) patients that was developed as a submission to the DREAM ALS Stratification Prize4Life Challenge held in summer 2015 to find the most accurate prediction of ALS progression and survival. ALS is a neurodegenerative disease with very heterogeneous survival times. Based on patient data from two national registries, solvers were asked to predict survival for three different time intervals, which was then evaluated on undisclosed information from additional data. I describe methods used to generate new features from existing ones from longitudinal data, selecting the most predictive features, and developing the best survival model. I show that easily obtainable engineered features can significantly improve prediction and could be incorporated into clinical practice. Furthermore, my prediction model confirms previous reports suggesting that past disease progression measured by the ALSFRS (ALS functional rating scale score), time since disease onset, onset site, and age are strong predictors for survival. Regarding prediction accuracy, this approach ranked second.