Miracle-dz/UniFAR-FTUs huggingface dataset:
Summaries of the Egalitarian and Complementarian Positions on the Role of Women in the Home and in Christian Ministry

B. Fallen Disorder and Hierarchy Sin introduced into God's created order many manifestations of disorder and corrupted relationships. Among the chief examples of sin's defilement is the introduction of an illegitimate hierarchy in the relationship between woman and man. Gen. 3:16 (the curse on the woman) suggests that, because of sin, the woman would have a disposition of subservience before the man, and the man would have, in contrary measure, a disposition of supremacy over the woman. Thus, the relationship of male/female equality intended by God in creation is now defiled by the presence of a sinful and harmful hierarchical tendency.
A Star-Connected Rectifier Employed by the Three-Phase Interleaved LLC Resonant Converter used by the High-Efficiency Isolated AC – DC Converter

the power conversion efficiency of an isolated ac–converter is a dominant factor in the overall efficiency of dc distribution systems. To improve the power conversion efficiency of the dc distribution system, a threephase interleaved full-bridge LLC resonant converter employing a Y-connected rectifier is proposed as the isolated ac–dc high-frequency-link power-conversion system. The proposed Y-connected rectifier has the capability of boosting the output voltage without increasing the transformer’s turn ratio. Especially, the frequency of the rectifier’s output ripple is six times higher than the switching frequency, thereby reducing the output capacitor and the secondary transformer’s RMS current. However, the tolerance of the converter’s resonant components in each primary stage causes the unbalance problem of output ripple current. It cannot be solved using fuzzy logic control technique. To solve the current unbalance problem, a current balancing with fuzzy logic controller method is proposed for the output rectifying current. The performance of the proposed converter and the current balancing method of a 10 kW (300 V/33.3 A) prototype converter verified using MATLAB/SIMULINK software.
Aalborg Universitet Urban design for mobilities Towards material

The aim of this paper is twofold: firstly, to present a critique of mainstream transport thinking based on the so-called ‘mobilities turn’, and secondly to connect this to a design perspective. The aim is thus to establish this reflection based upon a theoretically informed discussion. In this paper, we shall explore the potential for a better understanding of contemporary urban challenges through the cross-disciplinary approach of ‘mobilities design’. The paper investigates how this notion is based on an understanding of materialities and social action that is framed under the heading of ‘material pragmatism’. The paper critically discusses transport versus mobilities and uses the combination of urban design and mobilities not just to argue for a pragmatic approach to urban transformation, but also to illustrate how such a different frame of understanding is better suitable for the ‘kind of a problem a city is’ to paraphrase the well-known urban scholar Jane Jacobs. submitted: September 2017 reviewed: January 2018 accepted: March 2018 © 2017 Ole B. Jensen. This is an open access article licensed under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/bync-nd/3.0/). #urban design
3D PULMONARY NODULES DETECTION USING FAST MARCHING

Pulmonary nodule detection is an important step in lung cancer detection because nodules are the alert signal of lung cancer. The early detection of them can hence increase the patient’s survival rates. This paper proposes an automated computer aided diagnosis system for detection of pulmonary nodules based on three dimensional (3D) structures. Lung parenchyma segmentation using fast marching method was employed. A simple thresholding technique is used to extract candidate nodules from the segmented lung parenchyma. A 3D image of nodule candidates is reconstructed by mean of stacked 2D images. To find the connected voxels of a blob, a 3D connected component labelling is used. Features extracted from each blob are then fed into the classifier. The random forest algorithm has been invoked for nodule and non-nodule classification. The proposed detection methodology can give the accuracy of 92%.
Modeling and control of piezoelectric microactuators

This project deals with modeling and control of two types of piezoelectric actuators. In particular, two lumped-parameter models were developed for a provided commercially available stack actuator. Great emphasis is given to modeling of hysteresis – a major nonlinear phenomenon present in the stack actuator – by phenomenological models. Quality of the models is validated by comparison of model simulations and real actuator displacement measurements acquired by optical interferometer. Results show that all introduced models describe the behavior of the stack actuator very well. Inverses of the models are subsequently used for design of feedforward hysteresis compensators. Simulations prove that hysteresis can be compensated perfectly by model inverses; measurements show that hysteresis in real stack actuator can be compensated with very good results. The other piezoelectric actuator investigated in this project was commercially available linear plate ultrasonic actuator. Closed-loop operation of the actuator was not possible due to low interferometer real-time sampling rate, hence a few practical experiments with open-loop control were conducted. These indicated that the actuator is difficult to control in open-loop due to the highly nonlinear behavior.
Cerebral aneurysms.

From the Department of Cerebrovascular and Endovascular Neurosurgery, New Jersey Neuroscience Institute, JFK Medical Center, Edison, N.J. ( J.L.B.); the Department of Endovascular Surgery, Institute for Neurology and Neurosurgery, Roosevelt Medical Center, New York ( J.K.S.); and the Department of Neurosurgery, Seattle Neuroscience Institute, Swedish Medical Center, Seattle (D.W.N.). Address reprint requests to Dr. Brisman at the Department of Cerebrovascular and Endovascular Neurosurgery, New Jersey Neuroscience Institute at JFK Medical Center, Edison, NJ 08818, or at jbrisman@solarishs.org.
DEVELOPMENT OF SRF SPOKE CAVITIES FOR LOW AND INTERMEDIATE ENERGY ION LINACS

The fabrication of the first European spoke cavity prototype has been achieved in July 2002. A series of mechanical and RF tests at warm and cold temperature was performed this year. These tests have demonstrated, on the one hand, the good feasibility, stiffness and tunability of the spoke cavity and, on the other hand, its excellent RF performances with a maximum accelerating field of 12.5 MV/m reached at 4.2K. INTRODUCTION Spoke cavities have been studied for 3 years at IPN Orsay. Beam dynamics studies [1] dedicated to the EURISOL [2] and XADS [3] European projects have pointed out that this kind of cavity is particularly suited to be used from typically 20 MeV up to 100 or 150 MeV (for proton linacs). In this framework, IPN has studied a 2-gap, beta 0.35, 352 MHz spoke cavity. The optimization of the RF parameters (done with MAFIA [4]) and the structural analysis (done with ACORD-CP [5]) are presented in [6-8]. The prototype has been fabricated, from February to July 2002, by the French company Cerca [9] and a series of tests started since the delivery date. First of all, we will describe the measurements performed at room temperature to know in particular the mechanical properties of the cavity like its sensitivity versus displacement and load, its mechanical stiffness, the frequency shift due to fabrication and vacuum load, the accelerating field profile. Then, we will show the results obtained during the three tests, in January, March and July 2003, performed at 4.2K into our new vertical cryostat. Finally, the recent developments made on the new beta=0.15 spoke cavity will be presented. TESTS AT ROOM TEMPERATURE Dimensional Controls Before the tests, we studied the frequency variation (i.e. ∆f~+300 kHz) observed between the “theoretical” value calculated with MAFIA (fcalculated=358.55 MHz) and the frequency measured at the delivery (fmeasured=358.85 MHz). Note: calculations and measurements have been done for the cavity at atmospheric pressure. Thanks to the dimensional measurements of the main cavity pieces (e.g. the spoke bar, the cavity length.) done by Cerca during the fabrication process and the respective sensitivities calculated with MAFIA, we had estimated the frequency variation due to fabrication errors. As we can see in Table 1, the estimation (i.e. +455 kHz) is in good agreement with the measurement. On one hand, the little difference between the “theoretical” frequency and the “real” one and on the other hand, the very good accelerating field flatness due to strong magnetic coupling between both cells (see section above) means that spoke cavity doesn’t need to be tuned at room temperature. It’s a strong advantage as compared to elliptical cavities for instance. Table 1: Estimation of the frequency variation due to fabrication errors. Areas Sensitivity with MAFIA (kHz/mm) Errors (mm) Frequency variation (kHz) Cavity diameter 950 -0.1 +95 Spoke base diameter 650 -0.2 -130 Racetrack width 800 -0.2 +160 Racetrack thickness 600 +0.2 -120 Wall-to-wall cavity length 450 +1.0 +450 Total variation +455
kNN Research based on Multi-Source Query Points on Road Networks

Given a query point set and an object point set, a multi-source query of k nearest neighbors (MQ-kNN) returns the query set for its k closest objects. However, most existing nearest neighbor query algorithms are based on a single-source query point (SQ-kNN), and the query point is often the user's location. However, in some cases, a query can be a point set. For example, a user wants to choose a house from the existing idle houses (query points) and hopes that its surrounding facilities (object points) are best. For this kind of application, we study the problem of MQ-kNN on road networks and try to solve MQ-kNN query problems. A basic algorithm based on Dijkstra algorithm is proposed as an original algorithm by calculating SQ-kNN repeatedly. Then, two improved algorithms are proposed by taking all query points as a whole and adopting the effective pruning strategy. Comprehensive experiments on five road network datasets clearly demonstrate the efficiency of this method.
1 Stochastic Volatility Models : Considerations for the Lay Actuary

Stochastic models for asset prices processes are now familiar to actuaries. Many of the models used in life office and pension fund valuation and asset-liability modelling studies assume deterministic volatility parameters. Empirical evidence however, suggests that volatility in asset prices varies with time. Further, volatilities implied by traded option prices show a term structure for implied volatility, as well as an apparent dependence on the "moneyness" of the option. These observations seem to be at odds with a constant volatility assumption. In this paper we present some empirical observations concerning volatility, and consider the impact of volatility on actuarial work. We then review some of the common models which incorporate stochastic volatility and consider issues related to parameterising such models. 1 We are indebted to Stuart Jones for his patience and for providing invaluable technical assistance. We would also like to thank Dylan Brooks and Carmela Calvosa for providing data and fruitful discussions.
Making Large UPS Systems More Efficient Revision

As energy resources become more scarce and more expensive, electrical efficiency is becoming a more important performance factor in the specification and selection of large UPS systems. There are three subtle but significant factors that can materially affect a company’s cost of operating a UPS system and particularly the electrical bill. Unfortunately, the people who specify systems often fail to recognize these factors, which leads to increased costs to the owner because operational efficiencies are not correctly considered. This paper discusses the common errors and misunderstandings in evaluating UPS efficiency. UPS efficiency curves are explained, compared, and their cost implications quantified. Executive summary >
A Novel Wideband Phase Shifter Using T-and Pi-Networks

In this paper, a wideband differential phase shifter based on modified Tand Pi-networks is proposed. Invoking the even-odd mode analysis in this symmetric phase shifter, closed-form equations of its S-parameters are derived. The derived equations enable a generic design scheme of the phase shifter, that is, ideally the phase shifter can be designed for any differential phase requirements. To illustrate the proposed idea, design parameters for differential phases of 45◦, 60◦, 75◦, 90◦, 105◦ and 120◦ are evaluated and tabulated considering a center frequency of 3GHz. Simulation of these examples using the Keysight ADS exhibits the intended performance. For validation, a 90◦ phase shifter has been fabricated and tested. The measurement results show a return loss better that 10 dB, an insertion loss of less than 1 dB, and a ±7◦ of phase deviation from 1.18 GHz to 5.44 GHz, which is equivalent to a fractional bandwidth of 142%.
A Crowdsourcing Approach to Chinese Vocabulary Learning

The fast development of new technology, particularly web-based andmobile technology, has been transforming ways how languages aretaught and learned. The current study examines the use of Memrise, acrowdsourcing spaced repetition program, by college students ofChinese, and its effects on Chinese character learning. The findings ofthe study demonstrate the effectiveness of the program. The study hasalso identified important factors and conditions that should exist inorder for the use of the program to be successful. Based on the findingsof the study, suggestions are made for language teachers in regards tousing Memrise or similar programs in vocabulary teaching. Eventhough the current study focuses on Chinese character learning, thefindings of the study can be applied to any other languages.
Real-Time Local Event Detection in GeoTagged Tweet Streams

The real-time discovery of local events (e.g., protests, disasters) has been widely recognized as a fundamental socioeconomic task. Recent studies have demonstrated that the geo-tagged tweet stream serves as an unprecedentedly valuable source for local event detection. Nevertheless, how to e ectively extract local events from massive geo-tagged tweet streams in real time remains challenging. To bridge the gap, we propose a method for e ective and real-time local event detection from geo-tagged tweet streams. Our method, named GeoBurst+, rst leverages a novel cross-modal authority measure to identify several pivots in the query window. Such pivots reveal di erent geo-topical activities and naturally attract similar tweets to form candidate events. GeoBurst+ further summarizes the continuous stream and compares the candidates against the historical summaries to pinpoint truly interesting local events. Better still, as the query window shifts, GeoBurst+ is capable of updating the event list with little time cost, thus achieving continuous monitoring of the stream. We used crowdsourcing to evaluate GeoBurst+ on two million-scale data sets, and found it signi cantly more e ective than existing methods while being orders of magnitude faster.
The Phenomenology of Videogames

Jesper Juul has convincingly argued that the conflict over the proper object of study has shifted from “rules or story” to “player or game. ” But a key component of digital games is still missing from either of these oppositions: that of the computer itself. This paper offers a way of thinking about the phenomenology of the videogame from the perspective of the computer rather than the game or the player.
LQR , Inverse Reinforcement Learning , Learning from Expert Demonstrations

This set of notes aims to provide a road map to understand the theory behind the helicopter control application [1]. Typically a reinforcement learning problem can be described by a Markov Decision Process (MDP) consisting of a sextuple (S,A, T , H, I,R) where S is the set of states, A is the set of actions, T is the dynamics model, H is the time horizon, I ⊂ S is the set of initial states; R : S × A → R is the reward (cost) function. As we deal with continuous state and action spaces, the focus is on (discretetime) dynamical systems where the transition dynamics can be described by a (non-linear) function f : xt+1 = f(xt, ut) for some action ut ∈ A. A policy π is a mapping from states x ∈ S to actions u ∈ A. Acting according to policy π yields expected sum of rewards V (π) = E [∑H t=0R(xt, ut|π) ] (also called value function). The goal is to find an optimal policy π∗ that maximizes the expected sum of rewards: π∗ = arg maxπ [∑H t=0R(xt, ut|π) ] .
Modeling Dynamic Behavior of Striatal Medium Spiny Neurons with Point Neuron Models

The aim of this work is to investigate the role of network organization and the neuron model type on the collective dynamic behavior of striatal population. For that purpose, two different scale neuron models which are phenomenological Izhikevich and conductance-based Hodgkin-Huxley (HH) type are used to investigate the dynamic behavior of MS neurons. Two network architectures are proposed with inhibitory and excitatory synaptic currents. In these networks, while all MS neurons affect each other with inhibitory synaptic currents, an excitatory current is applied to all MS neurons in the first layer, to represent the cortical inputs. A mathematical model of a medium spiny neuron of striatum based on HH type neuron model is proposed using different calcium channels and its dynamical behavior is investigated. It is observed that when the original HH model is used, regular spiking type behavior is observed. Including the high threshold calcium current, after hyperpolarization calcium current and voltage gated potasium current into the model improves the modeling capabilities. With extended ion channels, in addition to regular spiking behavior, bursting with resting stage are obtained. Then, Izhikevich neuron model is used in the network structures to compare the dynamic behaviors and computational time.
Probabilistic Model-Based Reinforcement Learning Using The Differentiable Neural Computer

This thesis investigates the use of the Differentiable Neural Computer (DNC) in modelbased Reinforcement Learning (RL). The approach involves learning a predictive, probabilistic model in a Mixture Density Network (MDN) using a Recurrent Neural Network (RNN) – MDN-RNN – which is then used to train a controller to perform optimal actions to receive maximum rewards in an environment. The MDN-RNN is trained to map a state st and action at at timestep t, to the parameters of a Gaussian Mixture Model which are used to sample the predicted next state st+1 at timestep t +1. Recent research has used Long Short Term Memory (LSTM) as the RNN layer for the MDN – MDN-LSTM – and achieved promising results on RL tasks. This research introduces a new MDN architecture that uses a DNC as the RNN layer, the MDN-DNC. The experiments conducted for this work find that the MDN-DNC, trained for fewer epochs, outperforms its LSTM counterpart in the ViZDoom: Take Cover environment in the mean cumulative rewards received with a controller trained using simulations of the model generated through the MDN. The MDN-DNC is observed to learn a more robust model of the environment that is less prone to defects that hinder training of the controller. The MDN-DNC also outperforms when learning the Pommerman Team Competition environment, where quantitative tests are made to compare the states it predicts against the true states received from the environment.
Microfinance for Startups : Experimental Evidence from Pakistan *

We use data over two years from a field experiment with 630 aspiring female entrepreneurs in Punjab, Pakistan to evaluate the impact of a start up loan for enterprises run by women. We find that the treatment increases the likelihood of setting up enterprise by 12% but only in the short run. Treated women whose husband’s have their own business are significantly less likely to set up a business. We find small but significant effects on household assets and measures of financial access but no transformative effects on general household welfare or female agency. We also find weak negative effects on household assets and food consumption for treated households in the left tail of baseline distributions. *This project was funded by the International Growth Centre, Pakistan and received IRB approval from the Lahore School of Economics (RERC-042015-2). The project would not have been possible without the support of Zara Murtaza and Kamran Azim at Kashf Foundation, Pakistan, and Naved Hamid at the Centre for Research in Economics and Business at the Lahore School of Economics. †Lahore School of Economics (farahs@lahoreschool.edu.pk) ‡Centre for the Study of African Economies, Blavatnik School of Government, University of Oxford (mahreen.mahmud@economics.ox.ac.uk) §Lahore School of Economics (azam@lahoreschool.edu.pk)
PRODUCTION OF SUPERIOR F 1 HYBRIDS : GENETIC ANALYSIS FOR ESTIMATING COMBINING ABILITY IN UPLAND COTTON ( GOSSYPIUM HIRSUTUM L . )

A study was conducted in the Department of Plant Breeding and Genetics, Faculty of Crop Production, Sindh Agriculture University, Tandojam, Pakistan during 2007. The objective was to examine the combining ability of eight upland cotton genotypes using F1 hybrid production and also to select desirable progenies from segregating populations. The genotypes comprised four parents as females (BH-160, NB-999, NIBGE-2 and FH-901) and four parents as males (CIM-56, CIM-497, CIM-707 and RH-501). The mean squares due to general combining ability (GCA) and specific combining ability (SCA) were significant for all traits except the GCA of females for number of monopodial branches per plant. The significance of GCA (males and females) and SCA (males x females interaction) variances suggested that both additive and non-additive genes were controlling the characters, yet additive genes were more important because variances due to GCA were, by and large, higher than due to SCA. Among four females, parent NIBGE-2 manifested maximum GCA effects for monopodial branches per plant (0.298), total number of bolls per plant (2.92) and seed cotton yield per plant (10.358), while BH-160 expressed high GCA effects for boll weight (0.12) and NB-999 for sympodial branches per plant (0.80). Among male inbreds, maximum GCA effects for most of the characters were expressed by inbred CIM-506. GCA effects of males and females, therefore, suggested that parents NIBGE-2, NB-999 and CIM-506 may be preferred for hybridization and selection programmes to improve majority of the characters studied. SCA estimates, however, suggested that hybrid FH-901 x CIM-506 expressed maximum effects for boll weight (0.77), NIBGE-2 x CIM497 for bolls per plant (8.58) and seed cotton yield per plant (30.482) and NIBGE-2 x CIM-506 for monopodial branches per plant (2.29). These results indicated that different hybrids may be exploited for hybrid crop development with improved traits.
An Empirical Perspective on Startup Valuations

In this paper, we explore post-money valuations by venture capital stage classiﬁcations. We ﬁnd that valuations can be described as being log-normally distributed, allowing us to think of them in terms of mean, median, and standard deviation, as well as build classical statistical models. We present an OLS log-log regression model as a tool to help practitioners approximate an undisclosed post-money valuation with considerable ease. Our results are statistically signiﬁcant at the p < 0 . 001 level for all terms with an adjusted R 2 of 89 percent. We also describe the results of an equivalent Bayesian model to better understand the uncertainty of our OLS estimates