Miracle-dz/UniFAR-FTUs huggingface dataset:
Religion and the Secular: Historical and Colonial Formations

Introduction Timothy Fitzgerald 1. Dialectics of Conversion: Las Casas and Maya Colonial and Post-colonial Congregacion Anna Blume, (SUNY College of Visual Arts) 2. The Higher Ground: The Secular Knowledge of Objects of Religious Devotion Trevor Stack (University of Aberdeen) 3. The Alaskan Native Claims Settlement Act in the Context of the Colonisation of the Indigenous People of Alaska James Cox, (University of Edinburgh) 4. State Shinto, Westernisation, and the Concept of Religion in Japan Jun'ichi Isomae, (Japan Women's College) 5. Religious and Secular in the Vietnam War and the Emergence of Highland Ethno-nationalism Tom Pearson, (Wabash Center for Learning) 6. Colonialism all the way down? Religion and the secular in early modern writing on south India Will Sweetman, (University of Otaga) 7. Politics as Performance in Colonial and Postcolonial India John Zavos, (University of Manchester) 8. Imperial Inventions of Religion in Colonial Southern Africa David Chidester, (University of Cape Town) 9. Religion in Islamic Thought and Practice Abdulkader Ismail Tayob (University of Cape Town) 10. Rudolf Otto, German Cultural Colonialism, and the 'Discovery' of the Holy Gregory Alles, (McDaniel College) 11. Encompassing Religion and privatised religions and the invention of modern politics Timothy Fitzgerald 12. Colonialism and the Myth of Religious Violence William T. Cavanaugh, (University of St. Thomas, St. Paul, MN.)
Hierarchical Fuzzy Trust Management for Customer-to-Customer in Peer-to-Peer eCommerce

Peer-to-peer (P2P) eCommerce are commonly perceived as an environment offering both opportunities and threats. For peers to be effective they need some mechanism for managing this risk of failure. One way to minimize threats in such an open environment is to exploit reputation to help evaluate the trustworthiness of what and predict the future behaviors of peers. In this study, a set of parameters were identified for describing the trust of a peer and proposes a framework based on a series of underpinning relationships among these factors. In simulation, this trust model has been shown to improve the efficiency of P2P eCommerce system by significantly decreasing the amount of malicious behavior on the network.
Using Schedulability Analysis Techniques to Derive the Average-Case Behavior with a Monte-Carlo Simulation

Evaluating the time-behavior of distributed embedded real-time systems can be performed in many ways. Mainly three different approaches can be used as shown in figure 1. The first one is to test the implemented system, the second one is to perform a simulation and the third one is to conduct a real-time analysis. Each of them has its advantages and disadvantages. Testing the implemented system is certainly the most realistic approach concerning the results, because the final system is used. But correcting any failures discovered at this late design stage can lead to enormous costs. To prevent this situation other approaches have to be used that are suitable for early design stages where mistakes are less expensive to fix. Such methods are the simulation or the analysis of a system. These can also be used in late design phases. For example a tool like chronSIM [1], which allows simulating a system, can provide information on what a system is actually doing especially in the average case. With a simulation however the border cases like the best-case and worst-case time behavior cannot be determined. Due to the coverage problem that simulations have, it is unknown whether such a border case has been simulated or not. Analytical approaches like those based on Tindell and Clark [2] construct the border cases and calculate guaranteed bounds for the time behavior. In [3] an automotive case study was conducted where both approaches simulation and analysis are compared. The conclusion of the paper is that both approaches are needed for the design process
Unleashing the Power of Mobile Cloud Computing using ThinkAir

Smartphones have exploded in popularity in recent years, becoming ever more sophisticated and capable. As a result, developers worldwide are building increasingly complex applications that require ever increasing amounts of computational power and energy. In this paper we propose ThinkAir, a framework that makes it simple for developers to migrate their smartphone applications to the cloud. ThinkAir exploits the concept of smartphone virtualization in the cloud and provides method level computation offloading. Advancing on previous works, it focuses on the elasticity and scalability of the server side and enhances the power of mobile cloud computing by parallelizing method execution using multiple Virtual Machine (VM) images. We evaluate the system using a range of benchmarks starting from simple micro-benchmarks to more complex applications. First, we show that the execution time and energy consumption decrease two orders of magnitude for the N-queens puzzle and one order of magnitude for a face detection and a virus scan application, using cloud offloading. We then show that if a task is parallelizable, the user can request more than one VM to execute it, and these VMs will be provided dynamically. In fact, by exploiting parallelization, we achieve a greater reduction on the execution time and energy consumption for the previous applications. Finally, we use a memory-hungry image combiner tool to demonstrate that applications can dynamically request VMs with more computational power in order to meet their computational requirements.
An efficient simulation method for multi-polymer systems

We present a new Monte Carlo scheme for the efficient simulation of multi-polymer systems. The method permits chains to be inserted into the system using a biased growth technique. The growth proceeds via the use of a retractable feeler, which probes possible pathways ahead of the growing chain. By recoiling from traps and excessively dense regions, the growth process yields high success rates for both chain construction and acceptance. Extensive tests of the method using self-avoiding walks on a cubic lattice show that for long chains and at high densities it is considerably more efficient than configurational bias Monte Carlo, of which it may be considered a generalization.
Monoamine oxidase type B inhibitors in early Parkinson's disease: meta-analysis of 17 randomised trials involving 3525 patients

Abstract Objective To quantify more reliably the benefits and risks of monoamine oxidase type B inhibitors (MAOBIs) in early Parkinson's disease. Data sources Searches of the Cochrane Library, Medline, Embase, PubMed, and Web of Science for years 1966-2003, plus major journals in the field, abstract books, and proceedings of meetings, for randomised trials comparing MAOBIs with placebo or levodopa. Data extraction Available data on mortality, motor complications, side effects, treatment compliance, and clinician rated disability (for example, unified Parkinson's disease rating scale) were extracted from 17 trials and combined using standard meta-analytic methods. Results No significant difference in mortality existed between patients on MAOBIs and control patients (odds ratio 1.13, 95% confidence interval 0.94 to 1.34; P = 0.2). Patients randomised to MAOBIs had significantly better total scores, motor scores, and activities of daily living scores on the unified Parkinson's disease rating scale at three months compared with patients taking placebo; they were also less likely to need additional levodopa (0.57, 0.48 to 0.67; P < 0.00001) or to develop motor fluctuations (0.75, 0.59 to 0.95; P = 0.02). No difference existed between the two groups in the incidence of side effects or withdrawal of patients. Conclusions MAOBIs reduce disability, the need for levodopa, and the incidence of motor fluctuations, without substantial side effects or increased mortality. However, because few trials have compared MAOBIs with other antiparkinsonian drugs, uncertainty remains about the relative benefits and risks of MAOBIs. Further large, long term comparative trials that include patient rated quality of life measures are needed.
RBPF-SLAM based on probabilistic geometric planar constraints

Recent advances in visual SLAM have focused on improving estimation of sparse 3D points or patches that represent parts of surroundings. In order to establish an adequate scene understanding, inference of spatial relations among landmarks must be part of the SLAM processing. A novel Rao-Blackwilized PF-SLAM algorithm is proposed to utilize geometric relations of landmarks with respect to high level features, such as planes, for improving estimation. These geometric relations are defined as a set of geometric constraint hypotheses inferred during the mapping task. In each prediction-update cycle of estimation, probabilistic constraints are created and applied to update landmarks based on a hierarchical inference process. Based on experiments, improvement over estimation and completeness of the scene description is achieved using the proposal of this paper.
Will the real relationship between facial expression and affective experience please stand up: The case of exhilaration

Abstract It is hypothesised that the empirical correlation between facial expression and affective experience varies as a function of the correlational design used to compute the coefficients. Predictions about the rank order of five designs were derived based on two assumptions. Female subjects were placed into one of three alcohol conditions (no ethanol, low dose, high dose) and were exposed to 30 slides containing jokes or cartoons. The degree of rated funniness and overt behaviour were intercorrelated using five different designs to analyse the same set of data. The results show that within-subject analyses yielded higher coefficients than between-subjects analyses. Aggregation of data increased the coefficients for within-subject analyses, but not for between-subject analyses. A cheerful mood was associated with hyper-expressiveness, i.e. the occurrence of smiling and laughter at relatively low levels of perceived funniness. It was demonstrated that low correlations between facial expression and affe.
GUIDE, a structured pre-dialysis programme that increases the use of home dialysis

Background Despite the many advantages it offers, the percentage of dialysis patients that receive home dialysis [peritoneal dialysis (PD) or home haemodialysis (HHD)] in the Netherlands has declined over the last decade. Pre-dialysis education could stimulate the use of home dialysis. This article presents the results of the pre-dialysis programme GUIDE, with regard to the following question: Does the implementation of a structured pre-dialysis programme with a home-focused approach increase the number of pre-dialysis patients that choose and receive home dialysis? Methods The GUIDE process starts when a patient has an eGFR of 15 mL/min/1.73 m2. The process begins with a home visit from a case manager and the completion of questionnaires by the patient, the case manager and the nephrologist. A multidisciplinary meeting (MDM) is held to determine a specific patient profile (or treatment recommendation). This is followed by patient education, a second MDM and finally the selection of the treatment by the patient and the nephrologist. This retrospective observational study describes the selection process of all patients that received a treatment recommendation between 12 September 2013 and 18 December 2014 at Meander Medical Centre. Data were collected by file research and analysis of questionnaires. Results One hundred and two patients were included. They started the process at a mean eGFR of 12.3 mL/min/1.73 m2. Home dialysis was recommended for 62.8% of the patients who were advised to have dialysis treatment. Of the patients that opted for dialysis, 34.2% chose PD and 8.2% chose HHD; 22.9% started home dialysis as their first therapy, compared with 17.6% in the months before implementation of GUIDE. Finally, 32.1% of the patients that received dialysis therapy received home dialysis. In the months before GUIDE, an average of just 19.5% of the patients that received dialysis received home dialysis. Conclusions In comparison to historical data, the pre-dialysis programme GUIDE increases the number of patients that choose and receive home dialysis.
Design and Implementation of A Real-Time Face Recognition System for Mobile Robot

—This paper proposes a real-time face recognition system for mobile robot which can recognize the faces of human beings instantly from the images and also identify the users. The proposed system consists of the face detection and the face recognition subsystems. In the face detection subsystem, it uses the facial color filter to partition the possible facial color areas, and then applies the connected component labeling procedures to localize the objective faces initially. After this, an ellipse mask is adopted to verify where the faces are in the image, and then normalize these face blocks for the later faces recognition procedures. In order to recognize the faces, the principal component analysis method aims to determine the eigenvector of each face. After constructing the database of the weight vector for all sample faces, one can use the magnitude of the Euclidean distance between the objective and every sample to determine which face sample is the closest and the resultant one. From experimental results, it is seen that the proposed real-time face recognition system for mobile robots have fast and precise recognition abilities. It also can be applied to access control systems, security systems, the human-machine interaction systems and so on.
Neural Net Models for Open-Domain Discourse Coherence

Discourse coherence is strongly associated with text quality, making it important to natural language generation and understanding. Yet existing models of coherence focus on measuring individual aspects of coherence (lexical overlap, rhetorical structure, entity centering) in narrow domains. In this paper, we describe domain-independent neural models of discourse coherence that are capable of measuring multiple aspects of coherence in existing sentences and can maintain coherence while generating new sentences. We study both discriminative models that learn to distinguish coherent from incoherent discourse, and generative models that produce coherent text, including a novel neural latent-variable Markovian generative model that captures the latent discourse dependencies between sentences in a text. Our work achieves state-of-the-art performance on multiple coherence evaluations, and marks an initial step in generating coherent texts given discourse contexts.
Electrophysiological evidence of serotonergic impairment in long-term MDMA ("ecstasy") users.

OBJECTIVE "Ecstasy," or 3,4-methylenedioxymethamphetamine (MDMA), causes long-term impairment to the serotonin (5-HT) system in rats, dogs, and nonhuman primates. 5-HT dysfunction has also been observed in human recreational users of the drug, but whether 5-HT dysfunction in humans is caused by MDMA has not been established, since dysfunction may have preceded MDMA exposure. This ambiguity about causation is particularly important in MDMA research, because 5-HT deficiency is a predictor of risky behavior. METHOD The 5-HT function of 22 long-term MDMA users was compared to that of 20 drug-naive comparison subjects and 19 cannabis users. 5-HT function was assessed with the intensity dependence paradigm, a tool that measures 5-HT-related attenuation of neural response to auditory stimuli (measured with EEG). RESULTS Long-term MDMA users exhibited 5-HT dysfunction, relative to both cannabis users and drug-naive comparison subjects. This dysfunction was related to total MDMA consumption (after removing the effect of frequency of use) but not to frequency of use (after removing the effect of total consumption). CONCLUSIONS These data show that 5-HT dysfunction occurs in MDMA users, is related to users' MDMA consumption, and is independent of cannabis use. The results do not suggest that self-medication explains this relationship, because the deficit was related to total MDMA consumption but not frequency of consumption. The results are thus consistent with the thesis that MDMA consumption causes 5-HT impairment in humans.
Packet travel times in wireless relay chains under spatially and temporally dependent interference

We investigate the statistics of the number of time slots T that it takes a packet to travel through a chain of wireless relays. Derivations are performed assuming an interference model for which interference possesses spatiotemporal dependency properties. When using this model, results are harder to arrive at analytically, but they are more realistic than the ones obtained in many related works that are based on independent interference models. First, we present a method for calculating the distribution of T. As the required computations are extensive, we also obtain simple expressions for the expected value E[T] and variance Var[T]. Finally, we calculate the asymptotic limit of the average speed of the packet. Our numerical results show that spatiotemporal dependence has a significant impact on the statistics of the travel time T. In particular, we show that, with respect to the independent interference case, E[T] and Var[T] increase, whereas the packet speed decreases.
MIMO output feedback adaptive neural network control of an autonomous scale model helicopter mounted in a 2DOF platform

In this paper, we present an application of adaptive feedback output control using radial basis functions as the building block to the adaptive element. The application focuses the tracking stabilization of a scale helicopter restricted to a 2DOF platform. Actuator saturation is handled through the pseudo-control hedging (PCH) method. The plant model representing this restricted situation has 3DOF and the control efficiency can be stated through simulations
Efficient Intercarrier Interference Mitigation for Pilot-Aided Channel Estimation in OFDM Mobile Systems

Motivated by the possibility of decreasing the intersymbol interference (ISI) which is due to large delays of a multipath mobile radio channel, orthogonal frequency division multiplexing (OFDM) became very popular. However, the timevariance of the mobile radio channel induces intercarrier interference (ICI) yielding substantial channel estimation errors and thereby tremendous transmission impairments. Contrary to previous algorithms which resort to a linearization of the time-variant channel, we combat the ICI using eigenspaces of time-domain covariance matrices defined by the autocorrelation function of the Doppler spread. We perform a basis expansion using Slepian sequences and determine the basis coefficients of the time-variant channel by channel estimates from previous OFDM symbols. Once we know these basis coefficients, we obtain the necessary time-variant channel estimation by the Slepian sequences. These time-variant channel estimates allow a symbol detection in frequency domain which eliminates the ICI almost completely. Simulation results investigate both the signal to interference ratio (SIR) and the bit error ratio (BER) of our new ICI mitigation methods and reveal the superiority compared to previous algorithms for ICI reduction.
Risk-averse Newsvendor Networks: Resource Flexibility, Sharing, and Hedging

This paper studies how differences in risk exposure and risk attitude affect network configuration. Theory is presented for general utility functions and their mean-variance approximations and illustrated with networks featuring inventory substitution and commonality, or resource sharing and flexibility. When faced with increased risk exposure, risk-neutral newsvendors change resource levels proportionally to standard deviations, but risk-averse agents adjust proportionally to variance. While single-resource risk-averse newsvendors always invest less than risk-neutral newsvendors, they may invest more in networks. Not only may some resource levels increase in risk aversion, even the entire monetary network investment may exceed its risk-neutral counterpart. Two drivers explain this operational hedge, suggesting rules of thumb for strategic placement of safety capacity and inventory in networks. With strongly negative correlations, diversification (risk pooling) suggests to increase inexpensive resources that supply lower profit variance products. This highlights the role of profi to ver demand variance in risk-averse network design. With product profi td ifferences, revenue maximization suggests to increase (decrease) parallel (serial) flexibility. These insights confirm and refine the intuitive notion of safety capacity/inventory and flexibility as an operational hedge to mitigate risk.
Low-Sodium Dietary Approaches to Stop Hypertension Diet Reduces Blood Pressure, Arterial Stiffness, and Oxidative Stress in Hypertensive Heart Failure With Preserved Ejection Fraction

Recent studies suggest that oxidative stress and vascular dysfunction contribute to heart failure with preserved ejection fraction (HFPEF). In salt-sensitive HFPEF animal models, diets low in sodium and high in potassium, calcium, magnesium, and antioxidants attenuate oxidative stress and cardiovascular damage. We hypothesized that the sodium-restricted Dietary Approaches to Stop Hypertension diet (DASH/SRD) would have similar effects in human hypertensive HFPEF. Thirteen patients with treated hypertension and compensated HFPEF consumed the DASH/SRD for 21 days (all food/most beverages provided). The DASH/SRD reduced clinic systolic (155–138 mm Hg; P=0.02) and diastolic blood pressure (79–72 mm Hg; P=0.04), 24-hour ambulatory systolic (130–123 mm Hg; P=0.02) and diastolic blood pressure (67–62 mm Hg; P=0.02), and carotid-femoral pulse wave velocity (12.4–11.0 m/s; P=0.03). Urinary F2-isoprostanes decreased by 31% (209–144 pmol/mmol Cr; P=0.02) despite increased urinary aldosterone excretion. The reduction in urinary F2-isoprostanes closely correlated with the reduction in urinary sodium excretion on the DASH/SRD. In this cohort of HFPEF patients with treated hypertension, the DASH/SRD reduced systemic blood pressure, arterial stiffness, and oxidative stress. These findings are characteristic of salt-sensitive hypertension, a phenotype present in many HFPEF animal models and suggest shared pathophysiological mechanisms linking these 2 conditions. Further dietary modification studies could provide insights into the development and progression of hypertensive HFPEF.
Natural Killer T Cells in Adipose Tissue Are Activated in Lean Mice

Adipose tissues are closely connected with the immune system. It has been suggested that metabolic syndromes such as type 2 diabetes, arteriosclerosis and liver steatosis can be attributed to adipose tissue inflammation characterized by macrophage infiltration. To understand a physiological and pathological role of natural killer T (NKT) cells on inflammation in adipose tissue, we characterized a subset of NKT cells in abdominal and subcutaneous adipose tissues in C57BL/6J mice fed normal or high-fat diets. NKT cells comprised a larger portion of lymphocytes in adipose tissues compared with the spleen and peripheral blood, with epididymal adipose tissue having the highest number of NKT cells. Furthermore, some NKT cells in adipose tissues expressed higher levels of CD69 and intracellular interferon-γ, whereas the Vβ repertoires of NKT cells in adipose tissues were similar to other cells. In obese mice fed a high-fat diet, adipose tissue inflammation had little effect on the Vβ repertoire of NKT cells in epididymal adipose tissues. We speculate that the NKT cells in adipose tissues may form an equivalent subset in other tissues and that these subsets are likely to participate in adipose tissue inflammation. Additionally, the high expression level of CD69 and intracellular IFN-γ raises the possibility that NKT cells in adipose tissue may be stimulated by some physiological mechanism.