Miracle-dz/UniFAR-FTUs huggingface dataset:
Pilot Effectiveness and Transportability Trial of Multi-Family Psychoeducational Psychotherapy (MF-PEP) for Childhood Mood Disorders in a Community Behavioral Health Setting

ii Acknowledgements . v Vita . vii List of Tables . x Chapter 1: Introduction . 01 Chapter 2: Method . 88 Chapter 3: Results . 110 Chapter 4: Discussion . 137 References . 166 Appendix A: Demographics Form . 190 Appendix B: Parent Group Evaluation Form . 192 Appendix C: Child Group Evaluation Form . 193 Appendix D: MF-PEP Therapist Session Evaluation Survey . 195 Appendix E: MF-PEP Therapist Post-Group Feedback Survey . 196 Appendix F: Individual/Family Therapist Questionnaire about MF-PEP . 200 Appendix G: Parent’s Qualitative Feedback about MF-PEP on the Parent Group Evaluation Survey . 203 Appendix H: Children’s Qualitative Feedback about MF-PEP on the Child Group Evaluation Survey . 205 ix Appendix I: Child Therapists’ Qualitative Feedback about MF-PEP on the MF-PEP Therapist Session Evaluation Survey . 206 Appendix J: Parent Therapists’ Qualitative Feedback about MF-PEP on the MF-PEP Therapist Session Evaluation Survey . 212 Appendix K: MF-PEP Therapists’ Qualitative Feedback about MF-PEP on the MF-PEP Therapist Post-Group Feedback Survey . 217 Appendix L: Community Therapists’ Qualitative Feedback on the Individual/Family Therapist Questionnaire about MF-PEP . 220
Street Medicine: A Program Evaluation

STREET MEDICINE: A PROGRAM EVALUATION By ARIEL L. EDWARDS DECEMBER 8, 2016 INTRODUCTION: Homeless individuals have poorer health outcomes than their housed counterparts, yet there are many barriers to receiving consistent medical and behavioral health care. Street Medicine is a method of health care delivery in which a multidisciplinary group of health care providers bring health care to people living on the streets. Street Medicine could be a promising solution to meeting the unmet health needs of people experiencing homelessness. AIM: The purpose of the evaluation was to examine the effectiveness of Mercy Care’s Street Medicine program at engaging their homeless patients in consistent care and decreasing the number of patients that seek unnecessary hospital services. METHODS: A retroactive medical records review was conducted for 284 patients. Of the 284 patients, 26 patients had to be excluded from data analysis because the patients had not been seen during the Street Medicine rounds and are not considered Street Medicine patients. All of the data that were extracted were collected using a computer-based data collection form. The data was analyzed using frequency tables and t-tests in SAS. RESULTS: Results suggest that 54.26% of the Street Medicine patients are connected to Mercy Care through Street Medicine and/or clinic visits and engaging in consistent primary care and behavioral health care services. The average number of total Street Medicine encounters per patient was lower than the average number of clinic encounters. For both Street Medicine and clinic encounters, the patients accessed more primary care services than behavioral health services and case management services. There was no significant difference in ED visits before or after the initial Mercy Care encounter. The average number of total hospital admission days significantly increased from 0.98 days before the patient’s initial Mercy Care encounter to 1.84 days after the initial Mercy Care encounter. DISCUSSION: The Street Medicine program may be a promising solution for getting and keeping people experiencing homelessness engaged in health care and decreasing the number of patients that turn to the hospital for avoidable and costly health care services. The Street Medicine program eliminates many of the barriers to care that people experiencing homelessness face and could potentially decrease the rates of morbidity and mortality in this vulnerable community.
Running Title : Motivated Learning from Interesting Events Motivated Learning from Interesting Events : Adaptive , Multitask Learning Agents for Complex Environments Corresponding

This paper presents a model of motivation in learning agents to achieve adaptive, multi-task learning in complex, dynamic environments. Previously, computational models of motivation have been considered as speed-up or attention focus mechanisms for planning and reinforcement learning systems, however these different models do not provide a unified approach to the development or evaluation of computational models of motivation in different learning settings. This paper models motivation for machine learning as a process that reasons about the states and changes encountered by an agent to produce a learning stimulus that focuses learning and action. Context free grammars and events are introduced as adaptable representations of states and learning tasks. This extends existing learning algorithms to complex, dynamic environments in which tasks cannot be completely predicted prior to learning. Two agent models are presented for motivated reinforcement learning and motivated supervised learning, which incorporate this model of motivation. The formalisms used to define motivated reinforcement learning agents and motivated supervised learning agents further allow the definition of consistent techniques for evaluating motivated learning agent models. Three new metrics are introduced for evaluating learning efficiency, characterizing computational models of motivation and visualizing the emergent behavior of motivated learning agents. The paper concludes with a demonstration of the motivated reinforcement learning agent model that uses novelty and interest as the motivation function. The model is evaluated using the new metrics, showing that motivated reinforcement learning agents using general, task-independent concepts such as novelty and interest can learn multiple task-oriented behaviors.
Estimation of light transport parameters in tissues using coherent backscattering : A revaluation of the method

The suitability of using the angular peak shape of the coherent backscat-tered light for estimating the light transport parameters of tissues has been investigated. Milk and methylene blue doped milk were used as tissue phantoms for the measurements carried out with a He-Ne laser (632.8nm). Results indicate that while the technique accurately estimates the transport length, it can determine the absorption coefficient only when the absorption is moderate (α > 1cm −1) for the long transport lengths typical of tissues. Further, the possibility of determining the anisotropy factor by estimating the single scattering contribution to the diffuse background is examined. It is shown that the anisotropy factor can be estimated reasonably well, provided it is lesser than a limit set by the accuracy of the intensity measurement (g < 0.6 for our setup). The anisotropy factor is accurately estimated by corroborating the coherent backscattering measurements with transmission measurements and independently by angle-resolved scattering measurements.
An experimental study of network performance impact of increased latency in software defined radios

Software Defined Radios are becoming more and more prevalent. Especially in the radio amateur community, Software Defined Radios are a big success. The wireless industry also has considerable interest in the dynamic reconfigurability and other advantages of Software Defined Radios. Our research focuses on the latency of Software Defined Radios and its impact on throughput in modern wireless protocols. Software Defined Radio systems often employ a bus system to transfer the samples from a radio frontend to the processor which introduces a non-negligible latency. Additionally, the signal processing calculations on general-purpose processors introduce additional latencies that are not found on conventional radios. This work concentrates on one particular Software Defined Radio system called GNU Radio, an open source Software Defined Radio application, and one of its hardware components, the Universal Software Radio Peripheral (USRP), and analyzes its receive and transmit latencies. We will use these measurements to characterize the performance impact on IEEE 802.15. 4 implementation in GNU Radio. Additionally, we present two Software Defined Radio implementations of short-range radio standards, a FSK scheme used in the Chipcon CC1000 radio, and the physical layer of IEEE 802.15. 4. We use these implementations for round trip time measurements and introduce two sample applications, a physical layer bridge between the FSK scheme and IEEE 802.15. 4, and a dual channel receiver that receives two radio channels concurrently.
Alternating-time temporal belief and knowledge logic in multi-agent systems

Multi-agent cooperation logics, which provide powerful tool for modeling knowledge-based systems and cooperative problem solving process, gained great research interest in multi-agent systems community in the last five years. ATEL (alternating-time temporal epistemic logic) which is an important kind of multi-agent cooperation logics only takes knowledge into account, but does not deal with belief of agents. To solve this problem, firstly, general concurrent game structures are developed by extending concurrent game structures. Secondly, by introducing three kinds of belief operators into ATEL, a new multi-agent cooperation logic named ATBKL (alternating-time temporal belief and knowledge logic) is developed. Thirdly, a model checking algorithm is presented, and it is proved that the model checking complexity of ATBKL is PTIME-complete. Lastly, several desired properties of ATBKL are gained and proved. As a result, an expressive and powerful tool is developed for knowledge-based systems modeling. Further research is undertaken to model cooperative problem solving process based on this new logic.
Automatic visual recognition for metro surveillance

We propose in this paper an approach for recognizing either isolated individual, group of people or crowd behaviors in the context of visual surveillance of metro scenes using multiple cameras. In this context, a behavior recognition module relies on a vision module composed of three tasks: (a) motion detection and frame to frame tracking, (b) multiple cameras combination and (c) long term tracking of individuals, groups of people and crowd evolving in the scene. For each tracked actor, the behavior recognition module performs three levels of reasoning: states, events and scenarios. We have also defined a general framework to easily combine and tune various recognition methods (e.g. automaton, Bayesian network or AND/OR tree) dedicated to the analysis of specific situations (e.g. mono/multi actors activities, numerical/symbolic actions or temporal scenarios). Validation results on different methods used to recognize specific behaviors are described.
Structure financière et performance des entreprises dans un contexte sans marché financier : le cas du Cameroun*

Cette etude a pour objectif d’apprecier le caractere discriminant du marche financier dans le comportement des organisations en matiere de choix de financement. Les modeles theoriques (le modele ModiglianiMiller, le TradeOff et le PeckingOrder) et les travaux empiriques sur la structure de propriete ( notamment les tenants de la these de la non neutralite ) reconnaissent que les indicateurs boursiers de la performance (Q de Tobin, le ratio de Marris, la mesure de Sharpe .) sont les seuls sensibles aux structures financiere et de propriete. En outre, la dette discipline les dirigeants par le marche financier et devient ainsi une variable d’action indirecte utilisee par les actionnaires pour s’approprier la valeur. Dans un contexte sans marche financier comme le Cameroun, il s’est avere que la performance, qu’elle soit globale ou focalisee sur la richesse des actionnaires, est independante de la structure financiere; la forte concentration du capital ayant un effet positif marginal sur la valeur globale de l’entreprise. Ce resultat confirme l’hypothese de la neutralite des indicateurs comptables de performance et conforte le caractere discriminant du marche financier dans le comportement des entreprises en matiere de choix de financement; l’absence de ce marche impliquant moins de dettes, plus de concentration du capital pour un controle en interne, conformement aux previsions des theories de l’agence, des droits de propriete et des signaux.
IRAF in the Nineties

The Interactive Data Reduction and Analysis Facility (IRAF) data reduction and analysis system has been around since 1981. Today it is a mature system with hundreds of applications, and is supported on all the major platforms. Many institutions, projects, and individuals around the US and around the world have developed software for IRAF. Some of these packages are comparable in size to the IRAF core system itself. IRAF is both a data analysis system, and a programming environment. As a data analysis system it can be easily installed by a user at a remote site and immediately used to view and process data. As a programming environment IRAF contains a wealth of high and low level facilities for developing new applications for interactive and automated processing of astronomical or other data. As important as the applications programs and user interfaces are to the scientist using IRAF, the heart of the IRAF system is the programming environment. The programming environment determines to a large extent the types of applications which can be built within IRAF, what they will look like, and how they will interact with one another and with the user. While applications can be easily added to or removed from a software system, the programming environment must remain fairly stable, with carefully planned evolution and growth, over the lifetime of a system. The IRAF programming environment is the framework on which the rest of the IRAF system is built. The IRAF programming environment as it exists in 1992, and the work currently underway to enhance the environment are discussed. The structure of the programming environment as a class hierarchy is discussed, with emphasis on the work being done on the image data structures, graphics and image display interfaces, and user interfaces. The new technologies which we feel IRAF must deal with successfully over the coming years are discussed. Finally, a preview of what IRAF might look like to the user by the end of the decade is presented.
Tumour necrosis factor alpha increases melphalan concentration in tumour tissue after isolated limb perfusion

Several possible mechanisms for the synergistic anti-tumour effects between tumour necrosis factor alpha (TNF-α) and melphalan after isolated limb perfusion (ILP) have been presented. We found a significant sixfold increase in melphalan tumour tissue concentration after ILP when TNF-α was added to the perfusate, which provides a straightforward explanation for the observed synergism between melphalan and TNF-α in ILP. © 2000 Cancer Research Campaign
Productivity Premia for German Manufacturing Firms Exporting to the Euro‐Area and Beyond: First Evidence from Robust Fixed Effects Estimations

This paper makes three contributions. (1) It summarizes in tabular form a recent literature made of 36 micro-econometric studies for 16 different countries on the relationship between export destination and firm performance. (2) It reports estimates of the productivity premium of German firms exporting to the Euro-zone and beyond, controlling for unobserved time invariant firm specific effects, and tests for self-selection of more productive firms into exporting beyond the Euro-zone. (3) It corrects a serious flaw in hitherto published studies that ignore the potentially disastrous consequences of extreme observations, or outliers. The paper shows that estimates of the exporter productivity premium by destination are driven by a small share of outliers. Using a "clean" sample without outliers the estimated productivity premium of firms that export to the Euro-zone only is no longer much smaller that the premium of firms that export beyond the Euro-zone, too, and the premium itself over firms that serve the German market only is tiny. Furthermore, an ex-ante differential that is statistically significant and large only shows up for enterprises that exported to the Euro-zone already and start to export to countries outside the Euro-zone. These conclusions differ considerably from those based on non-robust standard regression analyses.
mTOR signaling and its roles in normal and abnormal brain development

Target of rapamycin (TOR) was first identified in yeast as a target molecule of rapamycin, an anti-fugal and immunosuppressant macrolide compound. In mammals, its orthologue is called mammalian TOR (mTOR). mTOR is a serine/threonine kinase that converges different extracellular stimuli, such as nutrients and growth factors, and diverges into several biochemical reactions, including translation, autophagy, transcription, and lipid synthesis among others. These biochemical reactions govern cell growth and cause cells to attain an anabolic state. Thus, the disruption of mTOR signaling is implicated in a wide array of diseases such as cancer, diabetes, and obesity. In the central nervous system, the mTOR signaling cascade is activated by nutrients, neurotrophic factors, and neurotransmitters that enhances protein (and possibly lipid) synthesis and suppresses autophagy. These processes contribute to normal neuronal growth by promoting their differentiation, neurite elongation and branching, and synaptic formation during development. Therefore, disruption of mTOR signaling may cause neuronal degeneration and abnormal neural development. While reduced mTOR signaling is associated with neurodegeneration, excess activation of mTOR signaling causes abnormal development of neurons and glia, leading to brain malformation. In this review, we first introduce the current state of molecular knowledge of mTOR complexes and signaling in general. We then describe mTOR activation in neurons, which leads to translational enhancement, and finally discuss the link between mTOR and normal/abnormal neuronal growth during development.
Structure of a Heterotetrameric Geranyl Pyrophosphate Synthase from Mint (Mentha piperita) Reveals Intersubunit Regulation[W][OA]

This work presents the crystal structure of mint heteromeric prenyltransferase, which is responsible for the biosynthesis of geranyl pyrophosphate, a precursor of the monoterpene menthol. By combining biochemical and genetic complementation approaches, the authors show that the molecular mechanism regulating specific product formation is mediated by protein–protein interactions. Terpenes (isoprenoids), derived from isoprenyl pyrophosphates, are versatile natural compounds that act as metabolism mediators, plant volatiles, and ecological communicators. Divergent evolution of homomeric prenyltransferases (PTSs) has allowed PTSs to optimize their active-site pockets to achieve catalytic fidelity and diversity. Little is known about heteromeric PTSs, particularly the mechanisms regulating formation of specific products. Here, we report the crystal structure of the (LSU · SSU)2-type (LSU/SSU = large/small subunit) heterotetrameric geranyl pyrophosphate synthase (GPPS) from mint (Mentha piperita). The LSU and SSU of mint GPPS are responsible for catalysis and regulation, respectively, and this SSU lacks the essential catalytic amino acid residues found in LSU and other PTSs. Whereas no activity was detected for individually expressed LSU or SSU, the intact (LSU · SSU)2 tetramer produced not only C10-GPP at the beginning of the reaction but also C20-GGPP (geranylgeranyl pyrophosphate) at longer reaction times. The activity for synthesizing C10-GPP and C20-GGPP, but not C15-farnesyl pyrophosphate, reflects a conserved active-site structure of the LSU and the closely related mustard (Sinapis alba) homodimeric GGPPS. Furthermore, using a genetic complementation system, we showed that no C20-GGPP is produced by the mint GPPS in vivo. Presumably through protein–protein interactions, the SSU remodels the active-site cavity of LSU for synthesizing C10-GPP, the precursor of volatile C10-monoterpenes.
Outage Scaling Laws and Diversity for Distributed Estimation Over Parallel Fading Channels

We consider scaling laws of the outage for distributed estimation problems over fading channels with respect to the total power and the number of sensors. Using a definition of diversity which involves a fixed number of sensors, we find tight upper and lower bounds on diversity which are shown to depend on the sensing (measurement) signal-to-noise ratios (SNRs) of the sensors. Our results indicate that the diversity order can be smaller than the number of sensors, and adding new sensors might not add to the diversity order depending on the sensing SNR of the added sensor. We treat a large class of envelope distributions for the wireless channel including those appropriate for line of sight scenarios. Finally, we consider fixed power per sensor with an asymptotically large number of sensors and show that the outage decays faster than exponentially in the number of sensors.
Research and Link Simulation of Key Technologies for LTE Downlink

To meet the evolution goals such as high peak rates, larger system capacity. LTE downlink adopts MIMO- OFDM technology. In this paper, we focus on channel estimation, which is one of the core technologies of the LTE downlink. First we establish the system framework . On this basis, we implement the channel estimation with two transmitting antennas and two receiving antennas. LS (Least Square) and LMMSE (Linear Minimum Mean Squared Error) estimation results are compared in the paper. And the results have shown that the algorithms have nice performance without channel coding in the physical downlink. In addition, interpolating methods are shown for the system to get the full-scale channel impulse response.
An approach for source code classification to enhance maintainability

The importance of software development is a design and programming to create a code quality, especially maintainability fatcor. An approach for source code classification to enhance maintainability is a method to clssify and improve code. This approach can increase High cohesion and Low coupling that effect to the internal and the external of software. It can reduce degraded integrity. First of all, we classify source code with software metrics and fuzzy logic and then improve bad smell, ambiguous code with refactoring to be a clean code. The last step, we evaluate the quality of clean code with maintainability measurement.
MiR-375 Promotes Redifferentiation of Adult Human β Cells Expanded In Vitro

In-vitro expansion of β cells from adult human pancreatic islets could provide abundant cells for cell replacement therapy of diabetes. However, proliferation of β-cell-derived (BCD) cells is associated with dedifferentiation. Here we analyzed changes in microRNAs (miRNAs) during BCD cell dedifferentiation and identified miR-375 as one of the miRNAs greatly downregulated. We hypothesized that restoration of miR-375 expression in expanded BCD cells may contribute to their redifferentiation. Our findings demonstrate that overexpression of miR-375 alone leads to activation of β-cell gene expression, reduced cell proliferation, and a switch from N-cadherin to E-cadherin expression, which characterizes mesenchymal-epithelial transition. These effects, which are reproducible in cells derived from multiple human donors, are likely mediated by repression of PDPK1 transcripts and indirect downregulation of GSK3 activity. These findings support an important role of miR-375 in regulation of human β-cell phenotype, and suggest that miR-375 upregulation may facilitate the generation of functional insulin-producing cells following ex-vivo expansion of human islet cells.