Miracle-dz/UniFAR-FTUs huggingface dataset:
Salud Mental: The Conceptualization and Experiences of Mental Health among Undocumented Mexican Immigrants

xiv CHAPTER ONE . 2 Undocumented Latinx Immigrants . 2 Statement of the Problem . 5 Theoretical Framework . 6 Purpose of Study . 6 Role of the Researcher . 7 Research Questions . 7 Definitions of Terms . 7 Latinx . 8 Undocumented Latinx Immigrants. 8 Mental Health and Mental Health Services. 8 Mixed-Status Families. 8 Significance of the Study . 9 Methodology . 9
Temperature dependence of the stress response of fibre Bragg gratings

Fibre Bragg gratings, used as stress sensing elements, show a temperature dependence of their stress response, which is mainly characterized by Young's modulus of the fibre material. The temperature dependence of the stress response of a fibre Bragg grating over a range from −38 °C to +110 °C has been measured. The stress sensitivity decreases linearly by 1.22 × 10−4 K−1 over this range which is nearly identical to the increase of Young's modulus of fused silica over this range implying that it is predominantly Young's modulus which defines and characterizes this thermal dependence. Significantly, bare and re-coated fibres show a markedly different behaviour below 0 °C due to the glass transition temperature of the jacket material.
Non-linear dynamics of a system of coupled oscillators with essential sti # ness nonlinearities

We study the resonant dynamics of a two-degree-of-freedom system composed of a linear oscillator weakly coupled to a strongly non-linear one, with an essential (non-linearizable) cubic sti#ness non-linearity. For the undamped system this leads to a series of internal resonances, depending on the level of (conserved) total energy of oscillation. We study in detail the 1:1 internal resonance, and show that the undamped system possesses stable and unstable synchronous periodic motions (non-linear normal modes—NNMs), as well as, asynchronous periodic motions (elliptic orbits—EOs). Furthermore, we show that when damping is introduced certain NNMs produce resonance capture phenomena, where a trajectory of the damped dynamics gets ‘captured’ in the neighborhood of a damped NNM before ‘escaping’ and becoming an oscillation with exponentially decaying amplitude. In turn, these resonance captures may lead to passive non-linear energy pumping phenomena from the linear to the non-linear oscillator. Thus, sustained resonance capture appears to provide a dynamical mechanism for passively transferring energy from one part of the system to another, in a one-way, irreversible fashion. Numerical integrations con<rm the analytical predictions. 2003 Elsevier Ltd. All rights reserved.
Constructing Knowledge for Automated Text-Based Emotion Expressions *

Humans are used to convey their thought through their (conscious or unconscious) choice of words. Some words possess emotive meaning together with their descriptive meaning. We develop a prototype of a synthetic 3D face that shows emotion associated to text-based speech in an automated way. As a first step, we studied how humans express emotions in face to face communication. Based on this study, we develop a 2D affective lexicon database and a set of rules that describes dependencies between linguistic contents and emotions. The result described in this paper proposes an initial step for developing knowledge for an affective-based multimodal fission.
Conceptualizing Principal–Student Racial Congruence

Principal–student racial congruence exists in a school when the race of the principal matches that of the largest race group among the student population. We argue that principal–student racial congruence is a topic that has received little attention in the literature. Using Texas data, we investigate the presence of principal–student racial congruence in public schools and the varying ways it manifests across differing school contexts. We found a slim majority of public schools to be racially congruent. Although we are aware of no research basis for considering racial congruence in administrator placement practices, our analysis suggests that Texas school districts do exactly that. Further, we found the likelihood of a White principal–student match to be much higher than that of any other congruency. The implications of our findings, as well as their contribution to a larger discussion of race and school leadership, are offered in the concluding sections of the article.
Bionic vision inspired on-road obstacle detection and tracking using radar and visual information

Inspired by the cooperation between the cone cell and the rod cell in human vision system, this paper presents a novel method for fusing millimeter wave (MMW) radar and monocular vision sensor information for on-road obstacle detection. The MMW radar performs similarly as the cone cell to indicate potential target region in the view, while the camera plays the same role as that of the rod cell to obtain precise target contour and to allow tracking over frames. Using real-world data collected from on-road vehicles, experimental evaluations have shown that, our proposed system could detect on-road obstacles with high detection rate and low false-alarm rate, yet the overall image processing time is significantly reduced compared to conventional approaches. In addition, the system has been applied on our unmanned vehicle for the past two years' “Future Challenge” autonomous vehicles competition.
Dealing with the complexity of state space exploration algorithms for SDL systems

The treatment of complexity is one of the main problems in the area of validation and ver cation of formally speci ed protocols. The problem can be tackled by using heuristics, partial order simulation methods, and optimization strategies. We present these mechanisms and describe the way they work. Their usefulness will be discussed by presenting the results of some experiments.
Novel HIV-1 Knockdown Targets Identified by an Enriched Kinases/Phosphatases shRNA Library Using a Long-Term Iterative Screen in Jurkat T-Cells

HIV-1 is a complex retrovirus that uses host machinery to promote its replication. Understanding cellular proteins involved in the multistep process of HIV-1 infection may result in the discovery of more adapted and effective therapeutic targets. Kinases and phosphatases are a druggable class of proteins critically involved in regulation of signal pathways of eukaryotic cells. Here, we focused on the discovery of kinases and phosphatases that are essential for HIV-1 replication but dispensable for cell viability. We performed an iterative screen in Jurkat T-cells with a short-hairpin-RNA (shRNA) library highly enriched for human kinases and phosphatases. We identified 14 new proteins essential for HIV-1 replication that do not affect cell viability. These proteins are described to be involved in MAPK, JNK and ERK pathways, vesicular traffic and DNA repair. Moreover, we show that the proteins under study are important in an early step of HIV-1 infection before viral integration, whereas some of them affect viral transcription/translation. This study brings new insights for the complex interplay of HIV-1/host cell and opens new possibilities for antiviral strategies.
Printer Identification Using Supervised Learning for Document Forgery Detection

Identifying the source printer of a document is important in forgery detection. The larger the number of documents to be investigated for forgery, the less time-efficient manual examination becomes. Assuming the document in question was scanned, the accuracy of automatic forgery detection depends on the scanning resolution. Low (100-200 dpi) and common (300-400 dpi) resolution scans have less distinctive features than high-end scanner resolution, whereas the former is more widespread in offices. In this paper, we propose a method to automatically identify source printers using common-resolution scans (400 dpi). Our method depends on distinctive noise produced by printers. Independent of the document content or size, each printer produces noise depending on its printing technique, brand and slight differences due to manufacturing imperfections. Experiments were carried out on a set of 400 documents of similar structure printed using 20 different printers. The documents were scanned at 400 dpi using the same scanner. Assuming constant settings of the printer, the overall accuracy of the classification was 76.75%.
Investigating the effects of co-witness influence on blame attribution

Through the use of misinformation paradigms, research has demonstrated that eyewitnesses can be influenced by their co-witnesses when attempting to attribute blame to the correct person in incidents where there are multiple potential suspects at blame (such as a fight or car accident). The act of blame conformity could directly contribute to the false conviction of innocent bystanders and should therefore be a central focus for research. Yet very little research has attempted to investigate the moderating factors associated with blame conformity. The present thesis investigated the effects of co-witness influence on eyewitness blame attribution. More specifically, the thesis sought to identify the external and internal predictors of blame conformity. A similar experimental paradigm to Thorley (2015) was created to observe blame conformity. In the present studies, confederates were used to expose participants to misleading post-event information about the witnessed crime footage (suggesting that the wrong person had initiated the assault). Participants were then interviewed and asked if they could determine which person from the incident was to blame for initiating the assault. A series of internal and external variables were measured and manipulated to identify the most accurate predictors of blame conformity. In total, four studies were carried out: The studies investigated the effects of age and gender (study 1a); unanimity and group size of misinformation (study 1b; using same data as 1a); personality characteristics (FIRO-B assessment)(study 2); co-witness familiarity (study 3); and the perceived intelligence and authority of the misinformation source (study 4), on co-witness influence. The results found no significant age or gender-related differences in blame conformity. In relation to personality; the results suggested eyewitnesses who scored highly on the wanted control dimension were more likely to accept misinformation from cowitnesses, and were more likely to lose confidence in their own judgements after a group discussion. Results also indicated that participants were more vulnerable to co-witness influence when exposed to misinformation from a majority of co witnesses. Misinformation presented by an individual confederate did not have a significant influence on participants’ responses. It was found that the level of statement similarity with regard to blame attribution was higher when the co-witnesses had a pre-existing relationship. Results indicated that participants were also more likely to conform to the confederate if she was presented as having high intelligence, in comparison to a confederate whose personal characteristics were undisclosed. After controlling for perceived intelligence, the perceived authority of the confederate did not have a significant effect on their influence over the participants. The implications and practical applications of the findings — as well as directions for future research— are discussed within the thesis.
The effect of Efficiency, Service Quality, Aesthetics, and Play against the Perceived Value, Satisfaction, and Loyalty at Ibis Hotels Indonesia

This study aims to determine the effect of efficiency, service quality, play, and aesthetics on perceived value, satisfaction, and loyalty at Ibis Hotels in Indonesia. The data used in this study are primary data, ie data obtained from questionnaires. Target population used in this study is customers who stayed at Ibis Hotels in Indonesia. Characteristics of the population used in this study is male or female, at least minimum education is high school, a minimum age of 18 years, domiciled in Indonesia, stayed at Ibis Hotels in Indonesia at least 2 days 1 night, the last time to stay at Ibis Hotels in Indonesia maximal 1 last year. This study uses cedar measurement interval, ie nominal and ordinal scale of measurement which also presents information about the differences quantity concept of observation to another observation. Type of measurement scale used is a numerical scale that uses five levels of response options that are already available in every statement contained in the questionnaire. The number of respondents used in this study was 285 respondents. This study using Structural Equation Model (SEM) with AMOS 22.0 software for windows. The results of the research results that efficiency, aesthetics direct and positive effect on perceived value; service quality has no effect on perceived value, the play is not a positive effect on perceived value; perceived value direct and positive impact on satisfaction; satisfaction and positive direct effect on loyalty; service quality is not a positive effect on loyalty; play a direct and positive effect on loyalty; Aesthetics has no effect on loyalty.
A multi-stage approach for efficiently learning humanoid robot stand-up behavior

Stand-up motion is among the most essential behaviors for humanoid robots. For achieving stable stand-up behavior, the traditional key-frame based motion planning methods are time-exhausted and expert knowledge dependent. On the other hand, classic trial-and-error based learning methods are inefficient due to the high degrees of freedom (DOFs) for humanoid robots and the difficulty in fixing appropriate reward functions. In this paper, a multi-stage learning approach is proposed to address the above issues. At the first stage, under a trajectory based motion control model, key motion frames sampled from human motion capture data (HMCD) are used for model initialization, through which the solution space could be pruned. At the second stage, the design of experiments (DOE) technique is introduced for fast and active searching in the pruned solution space. At the last stage, a refining process that adopts a stochastic gradient learning strategy is performed to achieve the final behavior. Under this three-stage learning framework, along with a simple heuristic reward function, the learning of the stand-up behavior for a kid-size humanoid robot is fulfilled successfully and efficiently.
A Comparison between Count and Neural Network Models Based on Joint Translation and Reordering Sequences

We propose a conversion of bilingual sentence pairs and the corresponding word alignments into novel linear sequences. These are joint translation and reordering (JTR) uniquely defined sequences, combining interdepending lexical and alignment dependencies on the word level into a single framework. They are constructed in a simple manner while capturing multiple alignments and empty words. JTR sequences can be used to train a variety of models. We investigate the performances of ngram models with modified Kneser-Ney smoothing, feed-forward and recurrent neural network architectures when estimated on JTR sequences, and compare them to the operation sequence model (Durrani et al., 2013b). Evaluations on the IWSLT German! English, WMT German! English and BOLT Chinese! English tasks show that JTR models improve state-of-the-art phrasebased systems by up to 2.2 BLEU.
Reconstruction of successful software evolution using clone detection

In modern software engineering, researchers regard a software system as an organic life form that must continue to evolve to remain successful. Unfortunately, little is known about how successful software systems have evolved, and consequently little has been learned from previous experience. We demonstrate a heuristic to reconstruct evolution processes of existing software systems by exploiting techniques to detect duplication in large amounts of data. A case study, evaluating various versions of Tomcat using this heuristic, revealed that the removal of duplicated code is a much smaller concern than grouping functionality in classes with one clear responsibility.
Un-Supervised, Semi-Supervised and Supervised Image Retrieval Based on Conceptual Features

To effectively and efficiently retrieve desired images from a large image database, an intuitional and common type of approaches is text-based image retrieval which accesses the images by comparing conceptual terms of a query and image data. Unfortunately, this type of image retrieval is not easy to earn users' satisfactions due to the problem of the image database maintenance. Another useful type is content-based image retrieval which determines the most relevant images according to the content comparisons between a query image and searched images. Although the content-based image retrieval can avoid the problems of text-based image retrieval, it cannot certainly generate good results because of the semantic gap between low-level visual features and high-level concepts. Therefore, in this paper, we propose three types of content-based image retrieval and a conceptual feature to improve the quality of content-based image retrieval. The experimental results show that, the supervised image retrieval using the proposed conceptual features can bring out better retrieval results than the traditional image retrieval using low-level visual features.
RNA-binding protein RBM24 is required for sarcomere assembly and heart contractility.

AIMS The factors responsible for cardiomyopathy are not fully understood. Our studies of the transcriptome of human embryonic stem cell-derived cardiomyocytes identified novel genes up-regulated during cardiac differentiation, including RBM24. We therefore studied how its deficiency affected heart development. METHODS AND RESULTS The expression of Rbm24 was detected in mouse cardiomyocytes and embryonic myocardium of zebrafish at the RNA and protein level. The Rbm24 loss-of-function showed that Rbm24 deficiency resulted in a reduction in sarcomeric proteins, Z-disc abnormality, and diminished heart contractility, resulting in the absence of circulation in zebrafish embryos. Gene expression profiling revealed down-regulation of multiple pathways associated with sarcomere assembly and vasculature development in Rbm24 deficiency. CONCLUSION We identified a novel role of the tissue-specific RNA-binding protein (RBP) Rbm24 involving in the regulation of cardiac gene expression, sarcomeric assembly, and cardiac contractility. This study uncovers a potential novel pathway to cardiomyopathy through down-regulation of the RBP Rbm24.
Probabilistic and Graphical Model based Genetic Algorithm Driven Clustering with Instance-level Constraints

Clustering is traditionally viewed as an unsupervised method for data analysis. However, several recent studies have shown that some limited prior instance-level knowledge can significantly improve the performance of clustering algorithm. This paper proposes a semi-supervised clustering algorithm termed as the probabilistic and graphical model based genetic algorithm driven clustering with instance-level constraints (Cop-CGA). In Cop-CGA, all prior knowledge about pairs of instances that should or should not be classified into the same groups is denoted as a graph and all candidate clustering solutions are sampled from this graph with different orders to assign instances into a certain number of groups. We illustrate how to design the Cop-CGA to guarantee that all candidate solutions satisfy the given constraints and demonstrate the usefulness of background knowledge for genetic algorithm driven clustering algorithm through experiments on several real data sets with artificial hard constraints. One advantage of Cop-CGA is both positive and negative instance-level constraints can be easily incorporated. Moreover, the performance of Cop-CGA is not sensitive to the order of assignment of instances to groups.
Both Minimum MSE and Maximum SNR Channel Training Designs for MIMO AF Multi-Relay Networks with Spatially Correlated Fading

This letter proposes channel training designs for two-hop multi-relay networks, where a source, a destination and multiple amplify-and-forward (AF) relays are all equipped with multi-antenna, based on mean square error (MSE) and signal-to-noise ratio (SNR) criteria with taking into account spatial fading correlation between multiple-input multiple-output (MIMO) channel elements. The minimum MSE and maximum SNR channel estimators are initially derived and, then, optimal structures on source training signal and relay matrices are determined. An iterative and a closed-form power allocation solutions are proposed for both channel estimators. Simulation results show that the proposed schemes outperform the conventional schemes.
Contribution of Amphipathicity and Hydrophobicity to the Antimicrobial Activity and Cytotoxicity of β-Hairpin Peptides

Bacteria have acquired extensive resistance mechanisms to protect themselves against antibiotic action. Today the bacterial membrane has become one of the “final frontiers” in the search for new compounds acting on novel targets to address the threat of multi-drug resistant (MDR) and XDR bacterial pathogens. β-Hairpin antimicrobial peptides are amphipathic, membrane-binding antibiotics that exhibit a broad range of activities against Gram-positive, Gram-negative, and fungal pathogens. However, most members of the class also possess adverse cytotoxicity and hemolytic activity that preclude their development as candidate antimicrobials. We examined peptide hydrophobicity, amphipathicity, and structure to better dissect and understand the correlation between antimicrobial activity and toxicity, membrane binding, and membrane permeability. The hydrophobicity, pI, net charge at physiological pH, and amphipathic moment for the β-hairpin antimicrobial peptides tachyplesin-1, polyphemusin-1, protegrin-1, gomesin, arenicin-3, and thanatin were determined and correlated with key antimicrobial activity and toxicity data. These included antimicrobial activity against five key bacterial pathogens and two fungi, cytotoxicity against human cell lines, and hemolytic activity in human erythrocytes. Observed antimicrobial activity trends correlated with compound amphipathicity and, to a lesser extent, with overall hydrophobicity. Antimicrobial activity increased with amphipathicity, but unfortunately so did toxicity. Of note, tachyplesin-1 was found to be 8-fold more amphipathic than gomesin. These analyses identify tachyplesin-1 as a promising scaffold for rational design and synthetic optimization toward an antibiotic candidate.
Fixed-Point Approaches to Computing Bertrand-Nash Equilibrium Prices Under Mixed-Logit Demand

This article presents a detailed technical framework for modeling with Bertrand-Nash equilibrium prices under Mixed Logit demand. Two coercive fixed-point equations provide more stable computational methods than those obtained from the literal first-order conditions. Assumptions to justify derivation and use of these equations are provided. A brief discussion of a GMRES-Newton method with hookstep globalization strategy originally due to Viswanath is also given. This article can be considered a supplement to an article by the authors forthcoming in the journal {\em Operations Research}.
An EAI Integration Framework Based on J 2

J2EE technologies to provide a range of middleware services to simplify a number of complex questions related to enterprise solutions development, deployment and management. J2EE Connector system can reduce the rang of integration and simplify application development, so it gets easier to implement EIS integration by means of tools. Combining The J2EE platform with J2EE Connector architecture, an enterprise integration framework is built in the this paper, which includes client layer ,middle layer and enterprise information system layer . in the framework, business logic is separated from the client side and server side, As a result, the framework can easy meet the increasingly complex and changing requirement of business logic , and this brings the convenience for development , maintenance and use.