Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement Development and Validation for Construct Validity of the Treatment: The Grief Recovery Method® Instrument (GRM-I)

ABSTRACT Background: Death education is focused on the lifestyle behavioral and emotional aspects of grief. Although several interventions exist that aim to influence grief, many have not been theoretically examined and have lacked valid and reliable instrumentation. Purpose: This study described a construct validity approach used to develop and validate the Grief Recovery Method® Instrument (GRM-I), a measure used to assess implicit theoretical variables of an intervention intended to influence grief and promote grief recovery. Methods: Content analysis of the program handbook, expert panel, and peer review were used to develop items. A pilot study and field and validity tests were used for validation purposes. Internal consistency was assessed using Cronbach’s alpha. Results: Confirmatory analysis (n = 279) showed an overall adequate fit of the data to the hypothesized factorial structure (normed fit index = 0.97; relative fit index = 0.83; incremental fit index = 0.97; Tucker-Lewis index = 0.87; comparative fit index = 0.98; parsimony normed fit index = 0.19; parimony comparative fit index = 0.20; and root mean square error of approximation = 0.09). Cronbach’s alpha for the full measure was 0.87. Discussion: This study established the GRM-I as a content valid and reliable measure. Translation to Health Education Practice: With future evaluative use of the GRM-I to test the implicit theoretical structure of the death education intervention, research will be able to show how and to what extent intervention components influenced variables of grief and grief recovery.
Particle Filter-Weight Estimation and Dual Particle Filter

When the clean state is not available, a dual estimation approach is required. A dual algorithm, dual particle filter, for nonlinear state and parameters estimation is presented. Dual filter is combined with particle filter for nonlinear situation. Two separate particle filters run con-currently: one for signal estimation which is called particle state filter, and another for model estimation which is called particle weight filter. The signal filter uses the current estimate of the system parameters for signal particle filtering, and the new estimate of signal with observations are used for parameters estimation. Sequential approaches instead of iterative approaches are chosen with respecting on line processing. And particle filter is more appropriate for rough nonlinear problems compared with extended Kalman filter. Methods are compared on several simulations of nonlinear noisy time series.
Analysis of Financial Stability

On the macro-economic policy side of Central Banking a remarkable consensus has been emerging over the last two decades. This covers both the applicable theoretical framework for analysing the transmission mechanism of monetary policy and also the appropriate institutional structure for the Central Bank to deploy its macro-economic policies. There is no such consensus on the appropriate theoretical framework for the analysis of financial stability. Indeed some would claim that there is no proper theoretical framework for this function in being at all. However, we propose one such framework based on the work of Goodhart, Sunirand and Tsomocos (2004, 2005, 2006a and b).
A Directivity-Enhanced Directional Coupler Using Epsilon Negative Transmission Line

In this paper, a high directivity parallel coupled line coupler using the ε negative (ENG) transmission line is proposed. With the aid of even- and odd-mode analysis, it is shown that by using ENG transmission lines in a parallel coupled line coupler, the even- and odd-mode phase velocities can become equal at a desired frequency. Hence, the directivity of a coupler can be infinite theoretically. The coupler circuit model and closed-form relations for lumped elements of this model are presented. In addition, a design procedure for microstrip implementation of this coupler is proposed. Based on the proposed procedure, a 10-dB ENG directional coupler is designed at 2 GHz and validated by full-wave simulations. This coupler is fabricated and measurement results are presented. Experimental results show maximum directivity of nearly 40 dB at 1.95 GHz.
Event-related potential measures of emotion regulation in early childhood

Emotion regulation in adults may be mediated by frontal cortical activities that adjust attention in response to challenging emotions. We examined event-related potentials across emotional conditions to assess normative patterns and individual differences in cortical mechanisms of emotion regulation in 4–6-year-olds. The children viewed pictures of angry, neutral, and happy faces during a Go/No-go task. Angry faces generated the greatest (frontocentral) N2 amplitudes and fastest N2 latencies, and happy faces produced the smallest amplitudes and slowest latencies. Frontal electrodes showed larger N2s to angry faces in the Go condition. The P3b was also largest for angry faces. More fearful children showed faster latency N2s to angry faces. These results are interpreted in terms of early-developing mechanisms for regulating anxiety and processing emotional information.
Taut Immersions into Complete Riemannian Manifolds

The main purpose of this paper is to propose a natural generalization of the notion of a taut immersion into a complete Riemannian manifold. We explain the motivation behind our definition, give many examples, note some interesting topological and geometric properties of such immersions, and remark on many intriguing relations to other well-known topics in geometry such as transformation groups, Morse theory, Blaschke manifolds and tori without conjugate points.
Analysis of Persistent RFI Signals Captured Using the CISR Coherent Sampling Mode

3 Results 12 3.1 File 290, Block 8 . 12 3.2 File 290, Block 11 . 12 3.3 File 27, Block 7 . 12 3.4 File 218, Block 10 . 14 3.5 File 218, Block 12 . 16
InSight: a systematic approach to create dynamic human-controller-interactions

We present InSight, an intuitive technique to control smart objects with existing input devices in the environment, while simply looking at them. By leveraging the user's line of sight as a heuristic of gaze and attention, the InSight system directs input focus from input devices to the device that the user is looking at, thus creating an intuitive metaphor: you control the object you are looking at. In this paper, we contribute with technical details of the hardware and software implementation, and a discussion of single user and multi-user interaction possibilities.
Demand induction with a discrete distribution of patients

We test the "induced demand" model on cesarean section, relying on a natural experiment of proportional fee reduction of all delivery procedures. This fee change does not imply any substitution effect and allows a proper measure of the income effect. We extend the demand induction model and derive its testable implications by introducing a discrete class of patients towards which physicians can discriminate their inducement behaviour. The empirical test is performed estimating a simultaneous binary probit model in which the probability of c-section delivery depends on the type of hospital chosen and the latter is allowed to be endogenously determined.
Comparative studies of constraint satisfaction and Davis-Putnam algorithms for maximum satisfiability problems

Maximum satissability (MAX-SAT) is an extension of satissability (SAT), in which a partial solution is sought that satisses the maximum number of clauses in a logical formula. Enumerative methods giving guaranteed optimal solutions can be derived from traditional search algorithms used to solve SAT problems, in particular the Davis-Putnam procedure. Algorithms have also been developed for the maximal constraint satisfaction problem (MAX-CSP), a generalization of MAX-SAT, that are extensions of search algorithms used to solve constraint satisfaction problems. In the present work, these algorithms were compared over the same sets of problems, using comparable implementations. In addition, variants of each algorithm were tested to determine the contribution of component strategies that often make up a working algorithm. The componential analysis was done using traditional multi-factor experimental designs in which the eeect of diierent strategies could be studied at the same time that problem parameters were varied. Most of this work was done with MAX-2SAT problems, although Davis-Putnam variants were also tested with MAX-3SAT. The performance of Davis-Putnam on MAX-SAT problems depended heavily on the combination of strategies used, and the superiority of a particular combination also depended on problem characteristics. In particular , the clause:variable ratio was shown to be an important determinant of relative performance. The best MAX-CSP algorithms were competitive with Davis-Putnam in this domain, but relative performance depended, again, on problem parameters.
The Role of Self-Efficacy and Cognitive Behaviour Therapy in Forming Prosocial Behaviour

Prosocial value can be associated with the positive behaviours that are commonly practised in the socio-surrounding of a civilised community, for example, the action of helping, loving and developing empathy with each other. The formation of the prosocial behaviour also has a connection with one’s self-efficacy. The individual’s mastery of his or her self-efficacy can contribute to the differences in how he or she is behaving. All of the ethical values in every religion explain life as revolving around helping one another and living peacefully in society. The effort of helping based on the concerns towards other people could be the motivational factors that are closely related to the prosocial behaviour. Having positive personality traits and then backed with a sound religious belief ingrain the necessary moral compass that guides a person into behaving in ways that are considered society-friendly. Meanwhile, media roles depending on the content are capable of propagating decent values among the larger mass. Generally speaking, these factors are sufficient in educating and nurturing normal individuals to attain better self-efficacy. However, on an earnest ground considering individuals who suffer from a low level of self-efficacy, which resulted in antisocial behaviour, a more structured and empirical psychological intervention needs to be administered.
Focal axonal swellings and associated ultrastructural changes attenuate conduction velocity in central nervous system axons: a computer modeling study

The constancy of action potential conduction in the central nervous system (CNS) relies on uniform axon diameter coupled with fidelity of the overlying myelin providing high‐resistance, low capacitance insulation. Whereas the effects of demyelination on conduction have been extensively studied/modeled, equivalent studies on the repercussions for conduction of axon swelling, a common early pathological feature of (potentially reversible) axonal injury, are lacking. The recent description of experimentally acquired morphological and electrical properties of small CNS axons and oligodendrocytes prompted us to incorporate these data into a computer model, with the aim of simulating the effects of focal axon swelling on action potential conduction. A single swelling on an otherwise intact axon, as occurs in optic nerve axons of Cnp1 null mice caused a small decrease in conduction velocity. The presence of single swellings on multiple contiguous internodal regions (INR), as likely occurs in advanced disease, caused qualitatively similar results, except the dimensions of the swellings required to produce equivalent attenuation of conduction were significantly decreased. Our simulations of the consequences of metabolic insult to axons, namely, the appearance of multiple swollen regions, accompanied by perturbation of overlying myelin and increased axolemmal permeability, contained within a single INR, revealed that conduction block occurred when the dimensions of the simulated swellings were within the limits of those measured experimentally, suggesting that multiple swellings on a single axon could contribute to axonal dysfunction, and that increased axolemmal permeability is the decisive factor that promotes conduction block.
The Archive for the Psychology of Religion

As the Archive for the Psychology of Religion transitions to the SAGE publishing house, this editorial outlines the current vision and principles guiding the way forward. This includes a strong emphasis on publishing work that demonstrates transparency, precision, breadth, and depth in areas of theory, research, and pedagogy. The primary article types are described and the submission practicalities are addressed.
How the Brain Generates Movement

Abstract In this study, we assume that the brain uses a general-purpose pattern generator to transform static commands into basic movement segments. We hypothesize that this pattern generator includes an oscillator whose complete cycle generates a single movement segment. In order to demonstrate this hypothesis, we construct an oscillator-based model of movement generation. The model includes an oscillator that generates harmonic outputs whose frequency and amplitudes can be modulated by external inputs. The harmonic outputs drive a number of integrators, each activating a single muscle. The model generates muscle activation patterns composed of rectilinear and harmonic terms. We show that rectilinear and fundamental harmonic terms account for known properties of natural movements, such as the invariant bell-shaped hand velocity profile during reaching. We implement these dynamics by a neural network model and characterize the tuning properties of the neural integrator cells, the neural oscillator cells, and the inputs to the system. Finally, we propose a method to test our hypothesis that a neural oscillator is a central component in the generation of voluntary movement.
A Learning Machine: Part I

Machines would be more useful if they could learn to perform tasks for which they were not given precise methods. Difficulties that attend giving a machine this ability are discussed. It is proposed that the program of a stored-program computer be gradually improved by a learning procedure which tries many programs and chooses, from the instructions that may occupy a given location, the one most often associated with a successful result. An experimental test of this principle is described in detail. Preliminary results, which show limited success, are reported and interpreted. Further results and conclusions will appear in the second part of the paper.
Towards Foundational Semantics - Ontological Semantics Revisited

In line with Nirenburg and Raskin’s paradigm of ontological semantics, we adhere to the basic tenet that natural language semantics needs to be captured with respect to an explicitly formalized ontology. Many researchers in computational semantics, however, have neglected the ontological aspects of meaning representation, and even more have neglected aspects of meaning representation related to domain-independent ontologies, i.e. foundational or upper-level ontologies. In this paper we argue for a stronger integration of foundational ontologies in computational semantics. We show that relying on foundational ontologies can, on the one hand, lead to a clean separation between domain-specific and domain-independent components of natural language processing systems. On the other hand, we show how the interplay between foundational, domain ontologies and lexical semantics resources can elegantly account for disambiguation as well as allow to draw nontrivial inferences. Further, a temporal theory compliant with the foundational ontology is absolutely necessary for supporting temporal reasoning in natural language understanding.
Exploiting Hierarchical Discourse Structure for Review Sentiment Analysis

The overall sentiment of a text is critically affected by its discourse structure. For the first time, this paper incorporates hierarchical discourse structure into an unsupervised sentiment analysis framework. Experimental results show that by integrating discourse structure, the performance of sentiment analysis is improved by 1.9% (from 85.1% to 87.0%), demonstrating the effectiveness of exploiting discourse structure for sentiment analysis.
QIC Program and Model Selection in GEE Analyses

The generalized estimating equation (GEE) approach is a widely used statistical method in the analysis of longitudinal data in clinical and epidemiological studies. It is an extension of the generalized linear model (GLM) method to correlated data such that valid standard errors of the parameter estimates can be drawn. Unlike the GLM method, which is based on the maximum likelihood theory for independent observations, the gee method is based on the quasilikelihood theory and no assumption is made about the distribution of response observations. Therefore, Akaike's information criterion, a widely used method for model selection in glm, is not applicable to gee directly. However, Pan (Biometrics 2001; 57: 120–125) proposed a model-selection method for gee and termed it quasilikelihood under the independence model criterion. This criterion can also be used to select the best-working correlation structure. From Pan's methods, I developed a general Stata program, qic, that accommodates all the distribution and link functions and correlation structures available in Stata version 9. In this paper, I introduce this program and demonstrate how to use it to select the best working correlation structure and the best subset of covariates through two examples in longitudinal studies.
Tracking the articulated motion of two strongly interacting hands

We propose a method that relies on markerless visual observations to track the full articulation of two hands that interact with each-other in a complex, unconstrained manner. We formulate this as an optimization problem whose 54-dimensional parameter space represents all possible configurations of two hands, each represented as a kinematic structure with 26 Degrees of Freedom (DoFs). To solve this problem, we employ Particle Swarm Optimization (PSO), an evolutionary, stochastic optimization method with the objective of finding the two-hands configuration that best explains observations provided by an RGB-D sensor. To the best of our knowledge, the proposed method is the first to attempt and achieve the articulated motion tracking of two strongly interacting hands. Extensive quantitative and qualitative experiments with simulated and real world image sequences demonstrate that an accurate and efficient solution of this problem is indeed feasible.
Integration of RFID and WSN technologies in a Smart Parking System

In this paper, a Smart Parking System (SPS) based on the integration of Ultra-High Frequency (UHF) Radio Frequency Identification (RFID) and IEEE 802.15. 4 Wireless Sensor Network (WSN) technologies is presented. The system is able to collect information about the occupancy state of parking spaces, and to direct drivers to the nearest vacant parking spot by using a customized software application. Such application also leverages an NFC-based e-wallet system to allow users to pay for the parking fee. Furthermore, a software application based on RESTful Java and Google Cloud Messaging (GCM) technologies has been installed on a Central Server in order to manage alert events (e.g. improper use of a reserved space or expiration of the purchased time). In such a case, it promptly informs the traffic cops through an Android mobile app, which has been designed ad hoc for the considered scenario. A proof-of-concept has demonstrated that the proposed solution can meet the real requirements of a SPS.
A new semantic-supported and agent-based decentralized algorithm for resource discovery in economic grid

Grid computing offers geographically dispatched heterogeneous resources in order to perform complex computations. Besides, issues such as sharing, allocation and integration of resources as well as resource discovery are of high importance in grid computing systems. In regards to resource discovery in such systems with such characteristics, various methods have been presented. Among them are methods which use semantic description to display resources. In economic grid computing systems, in order to use shared resources for task implementation, some costs must be paid. In these systems, every user determines a budget and asks for his/her desired task. Aiming at responding to the task, a budgeting algorithm should perform the practice of allocating the grid resources to heterogeneous tasks in a way that the tasks are finalized with the same or less than the pre-determine budget, given their costs and capabilities. This paper proposes a new method for resource discovery based on semantic description in an economic grid.
Surgical Treatment of Inferior Vena Cava Invasion in Patients with Renal Pelvis Transitional Cell Carcinoma by Use of Human Cadaveric Aorta

We herein report a case of radical nephroureterectomy and replacement of the inferior vena cava (IVC) with ahuman cadaveric aortic graft for a patient with renal pelvis transitional cell carcinoma associated with IVC infiltration. In advanced disease, radical surgery is essential to achieve long-term survival. This case entails the use of another treatment option among the numerous options currently available for the management of patients with advanced renal cancer associated with IVC invasion.
Servicenics approach: A social service engineering framework

Servicenics theory [1] is an extension of Gamenics theory for facilitating service engineering. It is an attempt to extend game design to the general principles of service engineering. It is based on the assumption that mobile social game design is based on the generally-applicable design paradigms of service engineering. The author proposes a six-stage view of Servicenics principles that are augmented from the four-stage golden rules of mobile social game design.
Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola

As an emergent infectious disease outbreak unfolds, public health response is reliant on information on key epidemiological quantities, such as transmission potential and serial interval. Increasingly, transmission models fit to incidence data are used to estimate these parameters and guide policy. Some widely used modelling practices lead to potentially large errors in parameter estimates and, consequently, errors in model-based forecasts. Even more worryingly, in such situations, confidence in parameter estimates and forecasts can itself be far overestimated, leading to the potential for large errors that mask their own presence. Fortunately, straightforward and computationally inexpensive alternatives exist that avoid these problems. Here, we first use a simulation study to demonstrate potential pitfalls of the standard practice of fitting deterministic models to cumulative incidence data. Next, we demonstrate an alternative based on stochastic models fit to raw data from an early phase of 2014 West Africa Ebola virus disease outbreak. We show not only that bias is thereby reduced, but that uncertainty in estimates and forecasts is better quantified and that, critically, lack of model fit is more readily diagnosed. We conclude with a short list of principles to guide the modelling response to future infectious disease outbreaks.