Miracle-dz/UniFAR-FTUs huggingface dataset:
Find your voice : through emotional focused therapy and attachment theory

This final paper is part of the requirements for completion of a Master’s Degree in Social Work. This experiential final paper is based on a clinical field practicum focused upon Emotionally Focused Therapy (EFT) with couples. This document presents the practicum student’s research into EFT and an exploration of the theoretical basis for EFT. Within the context of the requirements for graduate studies, investigation into the theory, ideology and challenges of this clinical approach was carried out in a private practice clinical environment. The primary goals of this field practicum were to gain knowledge of the process of EFT, and to learn the skills and challenges of this therapeutic process under supervision of an EFT clinician. A comprehensive investigation into Attachment Theory and its application to EFT was initiated. The field practicum provided a supervised environment to study Attachment Theory, EFT and its processes within the context of the practicum student’s personal and professional ideology. Clinical challenges; including student-client, student-supervisor and the student’s introspective relationships; are discussed within the framework of EFT. The challenge of Emotionally Focused Therapy for the clinician is the ability to develop a secure therapeutic relationship that provides the appropriate environment for clients to voice their vulnerabilities in order to allow healthy change to occur. The clinician is therefore responsible to insure that any of their own emotional triggers are addressed in order for the therapeutic relationship to be at its optimal functioning. Understanding Attachment Theory and the potential our own history has to influence or impact a therapeutic relationship is paramount in working with EFT.
Turbo-Equalization for Single-Carrier Transmission over MIMO Broadband Wireless Channel: Performance vs. complexity trade-offs

This paper addresses the issue of advanced equalization methods for space-time communications over MIMO broadband wireless channel. Instead of resorting to conventional multiuser detection techniques (based on the straightforward analogy between antennas and users), we adopt a different point of view and separate time equalization from space equalization, thus introducing a higher degree of freedom in the overall spacetime equalizer design. The linear part of the equalizer is derived in both time and frequency domains.
A Multi-Scale Particle Swarm Optimization ( PSO ) Approach to Image Registration

* Author contact information: ychen@hrl.com Abstract – We formulate the image registration problem as a search for optimal registration transformation parameters, and show how to use Particle Swarm Optimization (PSO) to optimize an objective function in a multi-dimensional parameter space efficiently. Compared with traditional image registration approaches, which are “open-loop” algorithms, the proposed approach uses registration quality feedback loop to drive the parameter search while avoiding potential problems common to open-loop algorithms, namely feature detection, matching and transformation parameter estimation. Furthermore, we show that using a coarse-to-fine multi-scale representation for registration with PSO can lead to better convergence and lower computation cost than using only single scale images. Examples demonstrating all aspects of the proposed approaches are given.
Morphine Attenuates Testosterone Response to Central Injection of Kisspeptin in Male Rats

Background Kisspeptin and naloxone stimulate the reproductive axis while morphine inhibits its function. We have investigated the effect of central injection of kisspeptin-10 on mean plasma testosterone concentration in morphine or naloxone pretreated rats. Materials and Methods In this experimental study, 60 male Wistar rats that were divid- ed into 12 groups (n=5 per group) received saline, kisspeptin (1 nmol, ICV), naloxone (2 mg/kg, subcutaneously), morphine (5 or 10 mg/kg, sc) or co-administrations of kisspeptin, morphine and naloxone at 09:00 - 09:30. In the co-administrated groups, kisspeptin was injected 15 minutes following morphine or naloxone injections. Blood samples were collected 60 minutes following injections via the tail vein. Plasma testosterone concentration was measured by a rat testosterone ELISA kit. Results Central injection of kisspeptin or subcutaneous injection of naloxone significantly increased the mean plasma testosterone concentration compared to saline while subcutaneous injections of different doses of morphine (5 or 10 mg/kg) significantly decreased testosterone compared to saline. The results revealed that morphine significantly attenuated the testosterone increase after kisspeptin injection compared to kisspeptin while a stimulatory additive effect was observed in the kisspeptin/naloxone group compared to either naloxone or kisspeptin. Conclusion Morphine and kisspeptin systems may interact with each other to control the hypothalamic-pituitary-gonadal (HPG) axis.
Role of four-week resistance exercise in preserving the heart against ischaemia–reperfusion-induced injury

Objective We studied the cardioprotective effect of resistance training against ischaemia–reperfusion-induced injury. Methods Forty male rats were divided into trained and sedentary groups (n = 20 for each). The trained rats were exercised at 12 repetitions/set, four sets/day and five days/week for four weeks. Transient regional ischaemia of the left anterior descending coronary artery (40 min) was followed by 80 min of reperfusion. Results Baseline developed and diastolic pressures and coronary flow were similar in the two groups. While diastolic pressure increased and developed pressure and coronary flow decreased in both the ischaemic and perfusion periods (as indices of cardiac damage), there were no statistically significant differences between the trained and sedentary groups in these parameters. Resistance training did not significantly change the infarct size and apoptosis rate. Conclusion We did not see a cardioprotective effect of resistance exercise against ischaemia–reperfusion-induced injury in this study. A precise conclusion about this issue needs more investigations.
EVOLUTION AND MUTATION RATES OF SEQUENTIAL DYNAMICAL SYSTEMS

In this paper we study the evolution of sequential dynamical systems (SDS) as a result of the erroneous replication of the SDS words. An SDS consists of (a) a finite, labeled graph Y in which each vertex has a state, (b) a vertex labeled sequence of functions (Fvi,Y ), and (c) a word w, i.e. a sequence (w1, . . . , wk), where each wi is a Y -vertex. The function Fwi,Y updates the state of vertex wi as a function of the states of wi and its Y -neighbors and leaves the states of all other vertices fixed. The SDS over the word w and Y is the composed map: [FY , w] = Qk i=1 Fwi . The word w represents the genotype of the SDS in a natural way. We will randomly flip consecutive letters of w with independent probability q and study the resulting evolution of the SDS. We introduce combinatorial properties of SDS which allow us to construct a new distance measure D for words. We show that D captures the similarity of corresponding SDS. We will use the distance measure D to study neutrality and mutation rates in the evolution of words. We analyze the structure of neutral networks of words and the transition of word populations between them. Furthermore, we prove the existence of a critical mutation rate beyond which a population of words becomes essentially randomly distributed, and the existence of an optimal mutation rate at which a population maximizes its mutant offspring.
Hippocampal sharp wave bursts coincide with neocortical "up-state" transitions.

The sleeping neocortex shows nested oscillatory activity in different frequency ranges, characterized by fluctuations between "up-states" and "down-states. " High-density neuronal ensemble recordings in rats now reveal the interaction between synchronized activity in the hippocampus and neocortex: Electroencephalographic sharp waves in the hippocampus were more probable during down-states than during up-states, and tended to coincide with transitions from down-states to up-states. The form of cortical activity fluctuations and their interactions with sharp waves depend on sleep depth: In deeper sleep stages, characterized by strong neocortical oscillation in the delta range or slower (approximately 0.8-4 Hz), sharp-wave-triggered peri-event time histograms (PETH) are consistent with a longer duration for down-states than for up-states. In lighter sleep, the sharp-wave-triggered PETH suggested longer up-states than down-states. These results highlight the interplay in the hippocampal/neocortical loop: Decreased neocortical input during down-states may be a factor in generation of sharp waves. In turn, sharp waves may facilitate down-to-up transitions. This interplay may reflect joint memory trace reactivation in the hippocampus and in the neocortex, possibly contributing to consolidation of long-term memory: Off-line reactivation of recent neural activity patterns in the hippocampus occurs during 50-100-msec electroencephalographic sharp waves, corresponding to pyramidal-cell population bursts. The neocortical up-states starting in correspondence with sharp waves may be influenced by the reactivated information carried by the hippocampal sharp wave.
Saddle-node bifurcations in the spectrum of HOCl

A detailed analysis of the bound-state spectrum of HOCl (hypoclorous acid) in the ground electronic state is presented. Exact quantum mechanical calculations (filter diagonalization) are performed employing an ab initio potential energy surface, which has been constructed using the multireference configuration-interaction method and a quintuple-zeta one-particle basis set. The wave functions of all bound states up to the HO+Cl dissociation threshold are visually inspected in order to assign the spectrum in a rigorous way and to elucidate how the spectrum develops with energy. The dominant features are (1) a 2:1 anharmonic resonance between the bending mode and the OCl stretching mode, which is gradually tuned in as the energy increases, and (2) a saddle-node bifurcation, i.e., the sudden birth of a new family of states. The bifurcation is further investigated in terms of the structure of the classical phase space (periodic orbits, continuation/bifurcation diagram). It is also discussed how the spectrum of.
Estimating of Bellman function via suboptimal strategies

The paper concerns approximate dynamic decision making. It deals with solving Bellman equation to obtain the Bellman function via so-called suboptimal strategies. The sub-optimal strategies are strategies reflecting the revision of the realized past decisions. The revision is conditioned on availability of future knowledge. Suboptimal strategies help to transform the estimation of Bellman function to solving system of algebraic equations, when parametrized form of Bellman function is used. The presented approach is applied to futures trading task.
Textual Entailment Search Task: An Initial Approach Based on Coreference Resolution

In this work we present our initial approach to the Recognizing Textual Entailment Search Pilot Task proposed by NIST. We proposed a new algorithm to address Text Entailment task to a document level making use of coreference resolution and then reducing this problem to a traditional main task problem. We also applied machine learning algorithms and a combination of datasets for the textual entailment task. The features chosen quantity lexical, syntactic and semantic level matching between text and hypothesis sentences. Despite our system being very preliminary, it is placed third among other existing systems.
Targeted Inactivation of GPR26 Leads to Hyperphagia and Adiposity by Activating AMPK in the Hypothalamus

G-protein coupled receptor 26 (GPR26) is a brain-specific orphan GPCR with high expression in the brain region that controls satiety. Depletion of GPR26 has been shown to increase fat storage in C. elegans, whereas GPR26 deficiency in the hypothalamus is associated with high genetic susceptibility to the onset of obesity in mice. However, the metabolic function of GPR26 in mammals remains elusive. Herein, we investigated a role of GPR26 in regulating energy homeostasis by generating mice with targeted deletion of the GPR26 gene. We show that GPR26 deficiency causes hyperphagia and hypometabolism, leading to early onset of diet-induced obesity. Accordingly, GPR26 deficiency also caused metabolic complications commonly associated with obesity, including glucose intolerance, hyperinsulinemia, and dyslipidemia. Moreover, consistent with hyperphagia in GPR26 null mice, GPR26 deficiency significantly increased hypothalamic activity of AMPK, a key signaling event that stimulates appetite. In further support of a regulatory role of GPR26 in satiety, GPR26 knockout mice also demonstrate hypersensitivity to treatment of rimonabant, an endocannabinoid receptor-1 antagonist commonly used to treat obesity by suppressing appetite in humans. Together, these findings identified a key role of GPR26 as a central regulator of energy homeostasis though modulation of hypothalamic AMPK activation.
Nilotinib hampers the proliferation and function of CD8+ T lymphocytes through inhibition of T cell receptor signalling

The novel selective BCR‐ABL Breakpoint cluster region – Abelson murine leukemia viral oncogene homolog 1 (BCR‐AML) inhibitor nilotinib (AMN107) is a tyrosine kinase inhibitor that is more potent against leukaemia cells in vitro than imatinib. As nilotinib might be used in the context of allogeneic stem cell transplantation where CD8+ T lymphocytes play a pivotal role in the graft‐versus‐leukaemia (GVL) effect, we investigated effects of nilotinib on this lymphocyte subpopulation. Nilotinib inhibits phytohemagglutinin (PHA)‐induced proliferation of CD8+T lymphocytes in vitro at therapeutically relevant concentrations (0.5–4 μM). The inhibition of CD8+ T lymphocytes specific for leukaemia or viral antigens through nilotinib was associated with a reduced expansion of antigen peptide specific CD8+ T lymphocytes and with a decreased release of interferon—γ and granzyme B by these cells as analysed by flow cytometry and enzyme‐linked immunospot (ELISPOT) assays. The inhibitory effect caused by nilotinib was two times stronger than by imatinib. These effects were mediated through the inhibition of the phosphorylation of ZAP‐70, Lck and ERK 1/2 and the NF‐κβ signalling transduction pathway. Taken together, we observed a strong suppressive impact of nilotinib on the CD8+ T lymphocyte function which should be considered carefully in the framework of allogeneic stem cell transplantation or other T cell based immunotherapies.
Sorting Topic Specific Web Pages Based on Ontology Knowledge

Due to the independence of the domain knowledge, general search engine has "theme drift" problem in the search of domain knowledge. Topic specific search engine offers a faster, and more accurate web resources retrieval service, and a good web page sorting algorithm can improve user experience. In this paper, we proposed a new sorting algorithm for topic specific search engine based on ontology knowledge, by using the hierarchy relationship of ontology knowledge to judge the importance of the words in web pages, and sorted web pages with the obtained cumulated score. To verify the effectiveness of the proposed algorithm, we set up an evaluation system and compared it with traditional sorting algorithm based on TF-IDF. The experimental results show that our algorithm is more accurate and have better user experience.
Performance-Based Service Differentiation in Clouds

Due to fierce competition, cloud providers need to run their data-centers efficiently. One of the issues is to increase data-center utilization while maintaining applications' performance targets. Achieving high data-center utilization while meeting applications' performance is difficult, as data-center overload may lead to poor performance of hosted services. Service differentiation has been proposed to control which services get degraded. However, current approaches are capacity-based, which are oblivious to the observed performance of each service and cannot divide the available capacity among hosted services so as to minimize overall performance degradation. In this paper we propose performance-based service differentiation. In case enough capacity is available, each service is automatically allocated the right amount of capacity that meets its target performance, expressed either as response time or throughput. In case of overload, we propose two service differentiation schemes that dynamically decide which services to degrade and to what extent. We carried out an extensive set of experiments using different services -- interactive as well as non-interactive -- by varying the workload mixes of each service over time. The results demonstrate that our solution precisely provides guaranteed performance or service differentiation depending on available capacity.
Refinement of the Classroom Citizenship Behavior Scale

In its original presentation, scores on two of the three subscales of the Classroom Citizenship Behavior scale were highly reliable. Scores on the subscale measuring the third dimension of classroom citizenship behavior, Courtesy, had poor reliability. We inductively derived additional items for the Courtesy subscale and tested structure and reliability of the revised scale. Exploratory factor analysis indicated that the scale readily divided into three factors of six items each, consistent with the proposed model. Furthermore, the subscale scores associated with these factors demonstrated high reliability. Next, two additional communication classes completed the revised scale and confirmatory factor analyses were run on the new version of the three-factor scale. Fit indices were good. The revised Classroom Citizenship Behaviors scale provides a stronger tool for investigating student behaviors that contribute to the effective functioning of the classroom environment.
Star Formation in the Eagle Nebula

M16 (the Eagle Nebula) is a striking star forming region, with a complex morphology of gas and dust sculpted by the massive stars in NGC 6611. Detailed studies of the famous ``elephant trunks'' dramatically increased our understanding of the massive star feedback into the parent molecular cloud. A rich young stellar population (2 - 3 Myr) has been identified, from massive O-stars down to substellar masses. Deep into the remnant molecular material, embedded protostars, Herbig-Haro objects and maser sources bear evidence of ongoing star formation in the nebula, possibly triggered by the massive cluster members. M 16 is a excellent template for the study of star formation under the hostile environment created by massive O-stars. This review aims at providing an observational overview not only of the young stellar population but also of the gas remnant of the star formation process.
Algebraic shifting and graded Betti numbers

Let S = K[x 1 ,. , x n ] denote the polynomial ring in n variables over a field K with each deg x i = 1. Let Δ be a simplicial complex on [n] = {1,. , n} and I Δ C S its Stanley-Reisner ideal. We write Δ e for the exterior algebraic shifted complex of A and Δ c for a combinatorial shifted complex of A. Let β ii+j (I Δ ) = dim K Tor i (K, I Δ ) i+j denote the graded Betti numbers of I Δ . In the present paper it will be proved that (i) β ii+j (I Δ e) < β ii+j (I Δ c) for all i and j, where the base field is infinite, and (ii) β ii+j (I Δ ) ≤ β ii+j (I Δ c) for all i and j, where the base field is arbitrary. Thus in particular one has β ii+j (I Δ ) ≤ β ii+j (I Δlex ) for all i and j, where Δ lex is the unique lexsegment simplicial complex with the same f-vector as A and where the base field is arbitrary.
Distributed Stochastic Variance Reduced Gradient Methods and A Lower Bound for Communication Complexity

We study distributed optimization algorithms for minimizing the average of convex functions. The applications include empirical risk minimization problems in statistical machine learning where the datasets are large and have to be stored on different machines. We design a distributed stochastic variance reduced gradient algorithm that, under certain conditions on the condition number, simultaneously achieves the optimal parallel runtime, amount of communication and rounds of communication among all distributed first-order methods up to constant factors. Our method and its accelerated extension also outperform existing distributed algorithms in terms of the rounds of communication as long as the condition number is not too large compared to the size of data in each machine. We also prove a lower bound for the number of rounds of communication for a broad class of distributed first-order methods including the proposed algorithms in this paper. We show that our accelerated distributed stochastic variance reduced gradient algorithm achieves this lower bound so that it uses the fewest rounds of communication among all distributed first-order algorithms.
Causality is Hard, but No Cause for Concern

During the past 50 years, personality psychology has made considerable progress concerning personality description, and prediction of and by personality. In contrast, explanation of personality development and personality effects has lagged far behind. In the coming decades, much more inspiration and transpiration are needed to change this unsatisfactory situation. (Asendorpf et al., 2016, p. 305)
A Detailed Analysis of Phrase-based and Syntax-based MT: The Search for Systematic Differences

This paper describes a range of automatic and manual comparisons of phrase-based and syntax-based statistical machine translation methods applied to English-German and English-French translation of user-generated content. The syntax-based methods underperform the phrase-based models and the relaxation of syntactic constraints to broaden translation rule coverage means that these models do not necessarily generate output which is more grammatical than the output produced by the phrase-based models. Although the systems generate different output and can potentially be fruitfully combined, the lack of systematic difference between these models makes the combination task more challenging.
Filtered backprojection for thermoacoustic computed tomography in spherical geometry

Thermoacoustic computed tomography (TCT) is a novel imaging technique for non‐destructive evaluation and medical imaging. It uses electromagnetic energy as input and the induced thermoacoustic pressure field as measurement output. The determination of the unknown energy deposition function is based on the integral geometric problem of reconstructing a function from its integrals over certain spheres. We apply the method of approximate inverse to derive filtered backprojection type reconstruction algorithms in spherical scanning geometry. Numerical results are presented and show the validity of the resulting algorithms. Copyright © 2005 John Wiley & Sons, Ltd.
Clustering-Based Collaborative Filtering Approach for Mashups Recommendation over Big Data

Spurred by services computing and Web 2.0, more and more mashups are emerging on the Internet. The overwhelming mashups become too large to be effectively recommended by traditional methods. In view of this challenge, we propose a clustering-based collaborative filtering approach for mashup recommendation over big data. This approach mainly divided into two phases: clustering and collaborative filtering. By using clustering techniques, the data size is reduced so that the computation time of collaborative filtering algorithm is decreased significantly. Several experiments are done to verify the efficient of the proposed approach at the end of this paper.