Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved survival associated with somatic PIK3CA mutations in copy-number low endometrioid endometrial adenocarcinoma

The phosphoinositide-3-kinase (PI3K) signaling pathway has been implicated in the development of endometrioid endometrial adenocarcinoma (EEC). Recently, The Cancer Genome Atlas (TCGA) project stratified EEC into four molecular subgroups, with the majority of tumors falling into the copy-number low-EEC (CNL-EEC) molecular subgroup. The aim of the present study was to investigate whether alterations of the PI3K pathway are associated with specific survival outcomes in patients with EEC. The clinical and genomic data of 307 patients with endometrioid-type tumors were obtained from TCGA project, including 90 patients in the CNL-EEC subgroup. Patients were evaluated in terms of survival and clinicopathological characteristics, as well as mutations in the PI3K catalytic subunit alpha (PIK3CA) gene and their effect on PIK3CA function. In CNL-EEC subgroup patients, somatic PIK3CA mutations (48/90 cases) were associated with significantly improved overall survival compared with that of wild-type PIK3CA (P=0.018). Furthermore, this improved survival was specific to the CNL-EEC subgroup and was not observed in other TCGA molecular subgroups. The majority of CNL-EEC cases were low-stage (stage I) and low-to-intermediate grade (grades 1–2) endometrioid tumors. There were no significant differences in age, stage, histology or International Federation of Gynecology and Obstetrics grade between PIK3CA-mutated and non-mutated patient groups (P>0.05). In addition, the majority of cases contained activating PIK3CA mutations. Overall, in the TCGA cohort, PIK3CA mutations had a favorable effect on the survival of patients with EEC, and this effect was dependent on tumoral molecular sub-stratification. Future studies on larger independent cohorts with long term follow-up are warranted to further analyze this association.
Self- and peer-modeling combined with self-monitoring to increase rates of on-task behavior

This study investigated the effectiveness of using self-as-a-model and peermodeling techniques in a package with self-monitoring to increase on-task behavior during independent seatwork time in math. The intervention package included self and peermodeling videos, a self-monitoring training video, coaching statements for use during each video session, a tactile self-monitoring prompt, and a self-monitoring grid. Three male students and one female student in the second and third grades indentified as displaying high rates of off-task behavior by their classroom teacher were included in the study. Two of the participants received their math instruction in a special education classroom. A multiple-probe, multiple-baseline design was used to evaluate the intervention package over the course of approximately 4 weeks. Dependent variables included rates of on-task behavior, academic productivity, and teacher and participant satisfaction with the intervention. Comparison data from classroom peers for on-task behavior were also
VCP/p97 cooperates with YOD1, UBXD1 and PLAA to drive clearance of ruptured lysosomes by autophagy

Rupture of endosomes and lysosomes is a major cellular stress condition leading to cell death and degeneration. Here, we identified an essential role for the ubiquitin‐directed AAA‐ATPase, p97, in the clearance of damaged lysosomes by autophagy. Upon damage, p97 translocates to lysosomes and there cooperates with a distinct set of cofactors including UBXD1, PLAA, and the deubiquitinating enzyme YOD1, which we term ELDR components for Endo‐Lysosomal Damage Response. Together, they act downstream of K63‐linked ubiquitination and p62 recruitment, and selectively remove K48‐linked ubiquitin conjugates from a subpopulation of damaged lysosomes to promote autophagosome formation. Lysosomal clearance is also compromised in MEFs harboring a p97 mutation that causes inclusion body myopathy and neurodegeneration, and damaged lysosomes accumulate in affected patient tissue carrying the mutation. Moreover, we show that p97 helps clear late endosomes/lysosomes ruptured by endocytosed tau fibrils. Thus, our data reveal an important mechanism of how p97 maintains lysosomal homeostasis, and implicate the pathway as a modulator of degenerative diseases.
Semi-tied covariance matrices for hidden Markov models

There is normally a simple choice made in the form of the covariance matrix to be used with continuous-density HMMs. Either a diagonal covariance matrix is used, with the underlying assumption that elements of the feature vector are independent, or a full or block-diagonal matrix is used, where all or some of the correlations are explicitly modeled. Unfortunately when using full or block-diagonal covariance matrices there tends to be a dramatic increase in the number of parameters per Gaussian component, limiting the number of components which may be robustly estimated. This paper introduces a new form of covariance matrix which allows a few "full" covariance matrices to be shared over many distributions, whilst each distribution maintains its own "diagonal" covariance matrix. In contrast to other schemes which have hypothesized a similar form, this technique fits within the standard maximum-likelihood criterion used for training HMMs. The new form of covariance matrix is evaluated on a large-vocabulary speech-recognition task. In initial experiments the performance of the standard system was achieved using approximately half the number of parameters. Moreover, a 10% reduction in word error rate compared to a standard system can be achieved with less than a 1% increase in the number of parameters and little increase in recognition time.
Making Friends and Making Art: An Intergenerational Learning Experience

In this article, an after school art program titled, Making Friends and Making Art is described. The art program provided an opportunity for older adults and children to work together. Over a six-week period, community members, age 50 years and older, volunteered to learn along-side local elementary age children to create a collaborative mosaic project. Through the analysis of the data, themes of value-sharing, cooperation and collaboration, motivation, and playful interaction emerged. Also evident was that the artmaking experience provided mutual benefits for both generations. The art-making experiences and discussions about art were useful in generating relationships between older and younger generations. This project may serve as a practical example of intergenerational art education.
Automatically Extracting Typical Syntactic Differences from Corpora

We develop an aggregate measure of syntactic difference for automatically find- ing common syntactic differences between collections of text. With the use of this measure, it is possible to mine for differences between, for example, the English of learners and natives, or between related dialects. If formulated in advance, hypotheses can also be tested for statistical significance. It enables us to find not only absence or presence, but also under- and overuse of specific constructs. We have applied our measure to the English of Finnish immigrants in Australia to look for traces of Finnish grammar in their English. The outcomes of this de- tection process were analysed and found to be insightful. A report is included in this article. Besides explaining our method, we also go into the theory behind it, including permutation statistics, and the custom normalizations required for applying these tests to syntactical data. We also explain how to use the software we developed to apply this method to new corpora, and give some suggestions for further research.
Image quality assessment with mean squared error in a log based perceptual response domain

Up to now, there existing a lot of models that predict subjective quality of the contents of natural images which have undergone some unknown distortion procedures. These models, no matter fall in to the bottom-up mechanism or belong to the top-down functional modelling, fail to provide an easy-applied and reliable solution. The complex computation procedure prevents them from being widely used in related image processing areas such as image enhancement, image reconstruction and video coding. In the present work, we start from a two stage nonlinear perception model, which transforms the input image into a decorrelated one and then further reduces the redundancy between neighboring pixels by another nonlinear normalization procedure which transforms the previous output into a perceptual response domain. The final quality prediction is computed as the Euclid distance of the reference image and the distorted one in this response domain, this will make the new model be readily applied in other areas.
Contributions à la dissémination d'informations haptiques dans un environnement multimodal. (Contributions to haptic information dissemination in a multimodal environment )

La majorite des interfaces reposent essentiellement sur la vision pour transmettre des informations aux utilisateurs. Cependant certaines situations requierent des techniques d'interactions permettant d'afficher des informations de maniere non-visuelle. Nous avons donc etudie des solutions apportees par le sens du toucher. Apres un apercu sur le domaine de la conception d'interfaces, en particulier sur la notion de multimodalite, nous nous sommes interesses a une modalite en particulier : l'haptique, qui utilise le sens du toucher. Notre contribution a ce domaine commence par la conception et l'evaluation d'icones tactiles permettant de coder des informations a l'aide d'une matrice de picots. Elles ont ete utilisees dans un systeme de guidage pour aider des utilisateurs a explorer des formes geometriques grâce au sens du toucher. Nous avons aussi concu et evalue des icones utilisant le retour de force d'un bras articule. Ces deux systemes d'icones ont ete utilises dans une application d'exploration de schemas de circuits electriques. Cette application multimodale permet a plusieurs enfants deficients visuels ou voyants d'explorer des schemas de circuits electriques en collaboration. Ils disposent d'informations visuelles et haptiques pour comprendre la forme du circuits, ainsi que les composants presents. Cette application utilise une architecture logicielle multimodale, que nous avons concue et detaillee. L'architecture en question propose des briques de base permettant de faciliter la conception et le developpement d'application multimodales, et en particulier celles utilisant le retour haptique.
Sugeno-Type Fuzzy Inference Model for Stock Price Prediction

operations of the prediction of stock price are complex and risky due to fluctuation in the stock market because of the vagueness, incompleteness, and uncertainty of the information used. However, it is therefore as a matter of necessity to seek to foresee stock prices because traders need to know when to invest in order to get the maximum return of the investment. This paper proposes a Sugeno-type fuzzy inference system for stock price prediction using technical indicators as its input values. Knowledge Base, Fuzzification, Inference Engine and Defuzzification are the essential components of our model. We explore Sugeno-type fuzzy inference engine to optimize the estimated result. We evaluate the degree of participation of each input parameter with Trapezoidal membership function. Center of Gravity technique is employed for defuzzification. We employ object oriented design tool to model our database. MATLAB and fuzzy relational database are used in the implementation of our study. The development of this system is based on the selection of stock data history which are studied and used for training the system. This system provides vital support to stock traders, researchers and other financial experts in making decisions as regards stock trading.
Reliable Perfusion Maps in Stroke MRI Using Arterial Input Functions Derived From Distal Middle Cerebral Artery Branches

Background and Purpose— Perfusion imaging is widely used in stroke, but there are uncertainties with regard to the choice of arterial input function (AIF). Two important aspects of AIFs are signal-to-noise ratio and bolus-related signal drop, ideally close to 63%. We hypothesized that distal branches of the middle cerebral artery (MCA) provide higher quality of AIF compared with proximal branches. Methods— Over a period of 3 months, consecutive patients with suspected stroke were examined in a 3-T MRI scanner within 24 hours of symptom onset. AIFs were selected manually in M1, M2, and M3 branches of the MCA contralateral to the suspected ischemia. Signal-to-noise ratio and bolus-related signal drop were analyzed. Perfusion maps were created for every patient and mean values at the insular level as well as relative ranges were compared. Results— Mean age of 132 included patients (53 females) was 67.3 years (SD, 14.9) and median National Institutes of Health Stroke Scale was 3 (interquartile range [IQR] 0 to 6). For further analyses, 4 patients were excluded due to discontinuation of scanning or insufficient bolus arrival (signal drop <15%). Median signal-to-noise ratio was highest in M3 branches (36.41; IQR, 29.29 to 43.58). Median signal-to-noise ratio in M2 branches was intermediate (27.54; IQR, 20.78 to 34.00) and median signal-to-noise ratio in M1 was low (12.40; IQR, 9.11 to 17.15). Using AIFs derived from M1 and M2 branches of the MCA median signal drop was 77% (IQR, 72% to 82%) and 78% (IQR, 73% to 83%), respectively. Signal drop was significantly reduced when AIF was selected in M3 branches with a median of 72% (IQR, 63% to 77%; P<0.01). Highest variability of 3456 perfusion maps was found in those derived from M1. Conclusion— The level of AIF selection in the MCA has a major impact on reliability and even quantitative parameters of perfusion maps. For better comparison of perfusion maps, the AIF should be defined by selection of distal branches of the MCA contralateral to the suspected ischemia. In future trials involving perfusion imaging, the MCA segment used for the AIF should be specified.
Effector pathway-dependent relative efficacy at serotonin type 2A and 2C receptors: evidence for agonist-directed trafficking of receptor stimulus.

There are many examples of a single receptor coupling directly to more than one cellular signal transduction pathway. Although traditional receptor theory allows for activation of multiple cellular effectors by agonists, it predicts that the relative degree of activation of each effector pathway by an agonist (relative efficacy) must be the same. In the current experiments, we demonstrate that agonists at the human serotonin2A (5-HT2A) and 5-HT2C receptors activate differentially two signal transduction pathways independently coupled to the receptors [phospholipase C (PLC)-mediated inositol phosphate (IP) accumulation and phospholipase A2 (PLA2)-mediated arachidonic acid (AA) release]. The relative efficacies of agonists differed depending on which signal transduction pathway was measured. Moreover, relative to 5-HT, some 5-HT2C agonists (e.g., 3-trifluoromethylphenyl-piperazine) preferentially activated the PLC-IP pathway, whereas others (e.g., lysergic acid diethylamide) favored the PLA2-AA pathway. In contrast, when two dependent responses were measured (IP accumulation and calcium mobilization), agonist relative efficacies were not different. These data strongly support the hypothesis termed "agonist-directed trafficking of receptor stimulus" recently proposed by Kenakin [Trends Pharmacol Sci 16:232-238 (1995)]. Concentration-response curves to 5-HT2C agonists were fit well by a three-state model of receptor activation, suggesting that two active receptor states may be sufficient to explain pathway-dependent agonist efficacy. Rational drug design that optimizes preferential effector activity within a group of receptor-selective drugs holds the promise of increased selectivity in clinically useful agents.
Facing the Unknown Challenge Structure and Modularity in Morphological Computation

Robotics is coming of age: more and more we are developing robots to function outside the controlled environment of the manufacturing oor and the lab. Robots are routinely used to interact physically with the world in places where humans should not, cannot or do not want to physically act. In handling ever more complex environments, we encounter a new class of robotic missions. These consist of deploying the robot to accomplish a few of a great many possible tasks, without knowing in advance which few tasks will actually be required in this instance of deployment. Even presuming that engineers could easily design a machine to execute each speci c task, both the possibility of deploying so many di erent robots and the possibility designing and deploying one robot complex enough to perform all the tasks are often prohibitively expensive and risky. We refer to a mission where the absence of task de nition is the limiting factor as an Unknown Challenge Mission. In our recent work on the CKBot modular robotic platform we have pioneered new approaches towards building robots quickly as tasks become known by fabricating the passive components of the robot body on the y and connecting them to pre-existing modules. This fabrication can be performed either under remote control with materials such as foam [3] and hot-melt adhesive , or by humans using general-purpose parts as illustrated by the ICRA robotics challenge competition [2] and LocoKit, or by humans using a carefully chosen collection of prefabricated parts as illustrated by our ongoing work on the SEAL pack robots. The ability to embed large parts of the task speci c capabilities in a morphology that is synthesized in situ is best understood in the context of morphological computation, where adaptation of the morphology and ensuing changes in mechanical capabilities and dynamics are seen as an integral part of adapting a robot to its environment.
Bitmap approach to trend clustering for prediction in time series databases

This paper describes a bitmap approach to clustering and prediction of trends in time-series databases. Similar trend patterns, rather than similar data patterns, are extracted from time-series database. We consider four types of matches: (1) Exact match, (2) Similarity match, (3) Exact match by shift, and (4) Similarity match by shift. Each pair of time-series data may be matched in one of these four types if this pair is similar one to another, by similarity (or sim) notion over a threshold. Matched data can be clustered by the same way of matching. To improve performance, we use the notion of center of a cluster. The radius of a cluster is used to determine whether a given time-series data is included in the cluster. We also use a new notion of dissimilarity, called dissim, to make accurate clusters. It is likely that a time-series data is in one cluster rather than in another by using both notions, sim and dissim: a data is similar to one cluster while it is dissimilar to another. For a trend sequence, the cluster that is dissimilar to that sequence is called dissimilar- cluster. The contribution of this paper includes (1) clustering by using not only similarity match but also dissimilarity match. In this way we prevent any positive and negative failures. (2) Prediction by using not only similar trend sequences but also dissimilar trend sequences. (3) A bitmap approach can improve performance of clustering and prediction.
Developing resiliency in children : a school-wide program

This research project addresses the area of Resiliency, specifically, "Why do some children in high risk circumstances develop resilience and bounce back from adversity while others fail to thrive? Further, what could educators and schools as a whole do, if anything, to help those that appear to be having difficulty coping with their life situation? Initially, I had wanted to develop a 'program' to help children develop resiliency traits. However, as I began to study the literature and work on research in this area I discovered that resilience could not be taught through a 'program' but rather it was a 'process' of empowerment for children to learn from. As a school we determined that we had to restructure to assist kids in their personal development. We were quickly becoming understaffed and unable to meet the demands of all students so we tried to develop pro-active programs aimed at helping all kids.This research first addresses resiliency and what it is and then discusses one's school's way to enhance and develop resiliency in students.
Psychiatry: Insights into depression through normative decision-making models

Decision making lies at the very heart of many psychiatric diseases. It is also a central theoretical concern in a wide variety of fields and has undergone detailed, in-depth, analyses. We take as an example Major Depressive Disorder (MDD), applying insights from a Bayesian reinforcement learning framework. We focus on anhedonia and helplessness. Helplessness—a core element in the conceptualizations of MDD that has lead to major advances in its treatment, pharmacological and neurobiological understanding—is formalized as a simple prior over the outcome entropy of actions in uncertain environments. Anhedonia, which is an equally fundamental aspect of the disease, is related to the effective reward size. These formulations allow for the design of specific tasks to measure anhedonia and helplessness behaviorally. We show that these behavioral measures capture explicit, questionnaire-based cognitions. We also provide evidence that these tasks may allow classification of subjects into healthy and MDD groups based purely on a behavioural measure and avoiding any verbal reports.
Spherical Structured Feature Maps for Kernel Approximation

We propose Spherical Structured Feature (SSF) maps to approximate shift and rotation invariant kernels as well as b-order arc-cosine kernels (Cho & Saul, 2009). We construct SSF maps based on the point set on d − 1 dimensional sphere Sd−1. We prove that the inner product of SSF maps are unbiased estimates for above kernels if asymptotically uniformly distributed point set on Sd−1 is given. According to (Brauchart & Grabner, 2015), optimizing the discrete Riesz s-energy can generate asymptotically uniformly distributed point set on Sd−1. Thus, we propose an efficient coordinate decent method to find a local optimum of the discrete Riesz s-energy for SSF maps construction. Theoretically, SSF maps construction achieves linear space complexity and loglinear time complexity. Empirically, SSF maps achieve superior performance compared with other methods.
Revitalizing Political Psychology: The Legacy of Harold D. Lasswell

Introduction. The Displacement Hypothesis. Symbols, Personality, and Appeals: Lasswell's Contribution to the Political Psychology of Propaganda. Democratic Character. Political Psychology and the Risks of Leadership. Political Climate, Mood, and Crisis. Integrating Lasswell's Contributions: Brief Applications. Conclusion: The Role of the Political Psychiatrist.