Miracle-dz/UniFAR-FTUs huggingface dataset:
Aortic Function’s Adaptation in Response to Exercise-Induced Stress Assessing by 1.5T MRI: A Pilot Study in Healthy Volunteers

Aim Evaluation of the aortic “elastic reserve” might be a relevant marker to assess the risk of aortic event. Our aim was to compare regional aortic elasticity at rest and during supine bicycle exercise at 1.5 T MRI in healthy individuals. Methods Fifteen volunteers (8 men), with a mean age of 29 (23–41) years, completed the entire protocol. Images were acquired immediately following maximal exercise. Retrospective cine sequences were acquired to assess compliance, distensibility, maximum rates of systolic distension and diastolic recoil at four different locations: ascending aorta, proximal descending aorta, distal descending aorta and aorta above the coeliac trunk level. Segmental aortic pulse wave velocity (PWV) was assessed by through plane velocity-encoded MRI. Results Exercise induced a significant decrease of aortic compliance and distensibility, and a significant increase of the absolute values of maximum rates of systolic distension and diastolic recoil at all sites (p<10–3). At rest and during stress, ascending aortic compliance was statistically higher compared to the whole descending aorta (p≤0.0007). We found a strong correlation between the rate pressure product and aortic distensibility at all sites (r = - 0.6 to -0.75 according to the site, p<10–4). PWV measured at the proximal and distal descending aorta increased significantly during stress (p = 0.02 and p = 0.008, respectively). Conclusion Assessment of regional aortic function during exercise is feasible using MRI. During stress, aortic elasticity decreases significantly in correlation with an increase of the PWV. Further studies are required to create thresholds for ascending aorta dysfunction among patients with aneurysms, and to monitor the impact of medication on aortic remodeling.
Psychopathic Traits and Insecure Attachment Patterns in Community-based Subgroups

There is a growing body of research on psychopathic traits in non-clinical populations. This emerging research has documented the prevalence of psychopathic traits in the general population and demonstrated that psychopathy has a similar latent structure as well as similar correlates (e.g., violent behavior, alcohol abuse, and lower intelligence) to forensic/offender samples. Relatedly, there is strong evidence insecure attachment patterns in adulthood are associated with many personality disorders, including psychopathy, but only a few studies have examined the relationship between attachment and psychopathic traits in non-clinical samples (albeit, convenience samples of college students). Thus, two aims of the current study are to: 1) describe and explore the manifestation and expression of psychopathic traits in a large, community-based sample and 2) examine associations between adult attachment disturbances and psychopathic traits in diverse sociodemographic subgroups. Using a cross-sectional design, results showed mean-level psychopathy factor score differences existed only when considering single sociodemographic factors (e.g., age), not an interaction of those factors. Psychopathy factor profiles were also consistent across groups, with higher levels of lifestyle followed by interpersonal, affective, and antisocial traits reported. Regarding the second aim, findings indicated support for the positive association between disturbed attachment patterns in adult relationships and psychopathic traits, although these associations differed in males and females of different age groups. Finally, there was some support for attachment processes acting as a social development pathway toward psychopathy, as insecure attachments in adulthood partially mediated the relationships between age and interpersonal, affective, and lifestyle traits of psychopathy.
MyPosition: sparking civic discourse by a public interactive poll visualization

We present the design and evaluation of MyPosition, a public display in the form of a large projection, featuring an interactive poll visualization. MyPosition aims at facilitating the deliberation and comparison of individual opinions on locally relevant topics in an opportunistic and engaging way. We evaluated MyPosition in an in-the-wild study and demonstrated that the engaging nature of the installation was effective in enticing public discussion. We found that (i) the increased identifiability of users positively impacted the engagement with and the social debate around the installation, however lowered the actual polling rate; (ii) people submitted their personal opinion instead of playing around with the interactive features; and (iii) the display led to considerable discussion as well as nudging among people, in particular in zones beyond the interaction area in front of the screen.
Kinetic Partitioning Modulates Human Telomere DNA G-Quadruplex Structural Polymorphism

Telomeres are specialized chromatin structures found at the end of chromosomes and are crucial to the maintenance of eukaryotic genome stability. Human telomere DNA is comprised of the repeating sequence (T2AG3)n, which is predominantly double-stranded but terminates with a 3’ single-stranded tail. The guanine-rich tail can fold into secondary structures known as a G-quadruplexes (GQs) that may exist as a polymorphic mixture of anti-parallel, parallel, and several hybrid topological isomers. Using single-molecule Förster resonance energy transfer (smFRET), we have reconstructed distributions of telomere DNA GQ conformations generated by an in situ refolding protocol commonly employed in single-molecule studies of GQ structure, or using a slow cooling DNA annealing protocol typically used in the preparation of GQ samples for ensemble biophysical analyses. We find the choice of GQ folding protocol has a marked impact on the observed distributions of DNA conformations under otherwise identical buffer conditions. A detailed analysis of the kinetics of GQ folding over timescales ranging from minutes to hours revealed the distribution of GQ structures generated by in situ refolding gradually equilibrates to resemble the distribution generated by the slow cooling DNA annealing protocol. Interestingly, conditions of low ionic strength, which promote transient GQ unfolding, permit the fraction of folded DNA molecules to partition into a distribution that more closely approximates the thermodynamic folding equilibrium. Our results are consistent with a model in which kinetic partitioning occurs during in situ folding at room temperature in the presence of K+ ions, producing a long-lived non-equilibrium distribution of GQ structures in which the parallel conformation predominates on the timescale of minutes. These results suggest that telomere DNA GQ folding kinetics, and not just thermodynamic stability, likely contributes to the physiological ensemble GQ structures.
Fos‐Like Immunoreactivity Induced by Seizure in Mice Is Specifically Associated With Euchromatin in Neurons

Administration of convulsant drugs causes the rapid induction of c‐fos in identified neurons within the mouse central nervous system (Morgan et al., 1987). In particular, Fos‐like immunoreactivity is evident in nuclei of granule cells of the hippocampal dentate gyrus within 30 minutes of the onset of seizure. By immunoelectron microscopy, Fos antibody binding was exclusively localized to dispersed chromatin (euchromatin) of several types of projection neurons and local circuit neurons in various brain regions and especially in the dentate gyrus, 210 minutes after a single injection of Metrazol. Fos‐like immunoreactivity was not detectable in the nucleolus, nor in the characteristic peripheral and nucleolus‐associated heterochromatin of hippocampal granule cells. No immunostaining was observed in nuclei of glial, ependymal or endothelial cells, and no cytoplasmic reactivity was seen in any cell type. These findings support a role for Fos in stimulus‐response coupling at the level of transcriptional regulation in neurons.
A Dataset of Open-Source Android Applications

Android has grown to be the world's most popular mobile platform with apps that are capable of doing everything from checking sports scores to purchasing stocks. In order to assist researchers and developers in better understanding the development process as well as the current state of the apps themselves, we present a large dataset of analyzed open-source Android applications and provide a brief analysis of the data, demonstrating potential usefulness. This dataset contains 1,179 applications, including 4,416 different versions of these apps and 435,680 total commits. Furthermore, for each app we include the analytical results obtained from several static analysis tools including Androguard, Sonar, and Stowaway. In order to better support the community in conducting research on the security characteristics of the apps, our large analytical dataset comes with the detailed information including various versions of AndroidManifest.xml files and synthesized information such as permissions, intents, and minimum SDK. We collected 13,036 commits of the manifest files and recorded over 69,707 total permissions used. The results and a brief set of analytics are presented on our website: http://androsec.rit. edu.
Analysis of Dual-Link Networks for Real-Time Applications

Next-generation networks are expected to support a wide variety of services. Some services such as video, voice, and plant control traffic have explicit timing requirements on a per-message basis rather than on the average. In this paper, we develop a general model of dual-link networks to support real-time communication. We examine the desirable properties of this network and the difficulties in achieving these properties. We then introduce the concept of coherence and develop a theory of coherent dual-link networks. We show that a coherent dual-link network can be analyzed as though it is a centralized system. We then discuss practical considerations in implementing a dual-link network, and implications of this work to address problems observed in the IEEE 802.6 metropolitan area network standard.
Computational Modeling of the Metabolic States Regulated by the Kinase Akt

Signal transduction and gene regulation determine a major reorganization of metabolic activities in order to support cell proliferation. Protein Kinase B (PKB), also known as Akt, participates in the PI3K/Akt/mTOR pathway, a master regulator of aerobic glycolysis and cellular biosynthesis, two activities shown by both normal and cancer proliferating cells. Not surprisingly considering its relevance for cellular metabolism, Akt/PKB is often found hyperactive in cancer cells. In the last decade, many efforts have been made to improve the understanding of the control of glucose metabolism and the identification of a therapeutic window between proliferating cancer cells and proliferating normal cells. In this context, we have modeled the link between the PI3K/Akt/mTOR pathway, glycolysis, lactic acid production, and nucleotide biosynthesis. We used a computational model to compare two metabolic states generated by two different levels of signaling through the PI3K/Akt/mTOR pathway: one of the two states represents the metabolism of a growing cancer cell characterized by aerobic glycolysis and cellular biosynthesis, while the other state represents the same metabolic network with a reduced glycolytic rate and a higher mitochondrial pyruvate metabolism. Biochemical reactions that link glycolysis and pentose phosphate pathway revealed their importance for controlling the dynamics of cancer glucose metabolism.
A Brief survey of Data Mining Techniques Applied to Agricultural Data

As with many other sectors the amount of agriculture data based are increasing on a daily basis. However, the application of data mining methods and techniques to discover new insights or knowledge is a relatively a novel research area. In this paper we provide a brief review of a variety of Data Mining techniques that have been applied to model data from or about the agricultural domain. The Data Mining techniques applied on Agricultural data include k-means, bi clustering, k nearest neighbor, Neural Networks (NN) Support Vector Machine (SVM), Naive Bayes Classifier and Fuzzy cmeans. As can be seen the appropriateness of data mining techniques is to a certain extent determined by the different types of agricultural data or the problems being addressed. This survey summarize the application of data mining techniques and predictive modeling application in the agriculture field.
Investments in Pharmaceuticals Before and After TRIPS

Abstract The TRIPS Agreement, which specifies minimum levels of intellectual property protection for countries in the WTO, has increased levels of patent protection around the world. Using variation across countries in the timing of patent laws and the severity of disease, we test the hypothesis that increased patent protection results in greater drug development effort. We find that patent protection in wealthy countries is associated with increases in R&D effort. However, the introduction of patents in developing countries has not been followed by greater R&D investment in the diseases that are most prevalent there.
Managing Use of Self for Masterful Professional Practice

Throughout the development of the OD field “use of self” or “self as instrument” has always been talked about or taught as important for the role of the change agent. Emphases ranged from self-awareness and personal growth to developing better skills in aspects of consulting. Interpretations spanned simply knowing more about your “self” to deeper recognitions of consciousness, choice, shadows, agency, behavior patterns, developmental theories, and intentionality. The National Training Laboratory’s T-group movement during the 1950s and 1960s brought considerable attention to self-awareness, feedback, and interpersonal and group dynamics, helping to solidify use of self in understanding one’s behavior and impact. While many education programs have pursued the theme or actual course work, our conceptual grounding and literature on this topic has remained sparse. Consequently, the idea of use of self has often been ambiguous, vague, and difficult to convert into action; and has mostly been a mentored skill or shared tips and techniques to aid understanding and behavior.
LIDAR Obstacle Warning and Avoidance System for Unmanned Aircraft

The availability of powerful eye-safe laser sources and the recent advancements in electro-optical and mechanical beam-steering components have allowed laser-based Light Detection and Ranging (LIDAR) to become a promising technology for obstacle warning and avoidance in a variety of manned and unmanned aircraft applications. LIDAR outstanding angular resolution and accuracy characteristics are coupled to its good detection performance in a wide range of incidence angles and weather conditions, providing an ideal obstacle avoidance solution, which is especially attractive in low-level flying platforms such as helicopters and small-to-medium size Unmanned Aircraft (UA). The Laser Obstacle Avoidance Marconi (LOAM) system is one of such systems, which was jointly developed and tested by SELEX-ES and the Italian Air Force Research and Flight Test Centre. The system was originally conceived for military rotorcraft platforms and, in this paper, we briefly review the previous work and discuss in more details some of the key development activities required for integration of LOAM on UA platforms. The main hardware and software design features of this LOAM variant are presented, including a brief description of the system interfaces and sensor characteristics, together with the system performance models and data processing algorithms for obstacle detection, classification and avoidance. In particular, the paper focuses on the algorithm proposed for optimal avoidance trajectory generation in UA applications.
A critical case study of peer mediation at an alternative high school

At the crossroad of peer mediation and alternative education, discursive and structural tensions emerge. Through critical discourse analysis of student discourse at one alternative school, the examination of the practice of peer mediation within the context of alternative schooling is centralized. Students’ discourses are juxtaposed with school officials’ discourse, case description, and participant/observation. There are three major findings that surface as a result of this study. First, there is a discourse and practice disjuncture between the positive comments from the students and faculty about peer mediation and the minimal use of the program. Second, there is a lack of structural support for the program on all levels. Third, the peer mediation program does little to transform the power relations and structural components of alternative schooling. In its current format, peer mediation at this alternative school serves the White elites as a public relations program that works to enhance the school’s public image rather than transform the students’ lives through experiential learning, improved decision-making, and the creation of new opportunities for students to resolve conflict in a more peaceful and productive manner. To my family Thank you for everything
TOR Complex 1 Includes a Novel Component, Tco89p (YPL180w), and Cooperates with Ssd1p to Maintain Cellular Integrity in Saccharomyces cerevisiae*

The Tor1p and Tor2p kinases, targets of the therapeutically important antibiotic rapamycin, function as components of two distinct protein complexes in yeast, termed TOR complex 1 (TORC1) and TORC2. TORC1 is responsible for a wide range of rapamycin-sensitive cellular activities and contains, in addition to Tor1p or Tor2p, two highly conserved proteins, Lst8p and Kog1p. By identifying proteins that co-purify with Tor1p, Tor2p, Lst8p, and Kog1p, we have characterized a comprehensive set of protein-protein interactions that define further the composition of TORC1 as well as TORC2. In particular, we have identified Tco89p (YPL180w) and Bit61p (YJL058c) as novel components of TORC1 and TORC2, respectively. Deletion of TOR1 or TCO89 results in two specific and distinct phenotypes, (i) rapamycin-hypersensitivity and (ii) decreased cellular integrity, both of which correlate with the presence of SSD1-d, an allele of SSD1 previously associated with defects in cellular integrity. Furthermore, we link Ssd1p to Tap42p, a component of the TOR pathway that is believed to act uniquely downstream of TORC1. Together, these results define a novel connection between TORC1 and Ssd1p-mediated maintenance of cellular integrity.
The TopX DB&IR engine

This paper proposes a demo of the TopX search engine, an extensive framework for unified indexing, querying, and ranking of large collections of unstructured, semistructured, and structured data. TopX integrates efficient algorithms for top-k-style ranked retrieval with powerful scoring models for text and XML documents, as well as dynamic and self-tuning query expansion based on background ontologies.
Fine-grained Patient Similarity Measuring using Deep Metric Learning

Patient similarity measuring plays a significant role in many healthcare applications, such as cohort study and treatment comparative effectiveness research. Existing methods mainly rely on supervised metric learning method to study patient similarity from Electronic Health Records (EHRs), facing the challenge of differentiating patients with a large number of fine-grained disease categories. Deep metric learning has gained noticeable success in fine-grained image categorization problem, however, it cannot be directly applied to classification of patients with hierarchical disease labels. In this paper, we present a novel three layer patient similarity deep metric learning framework (PSDML) by optimizing quadruple loss improved from triplet loss, to learn an embedding distance for disease classification among the patients. The context semantic relation of multi diagnosis labels encoding by ICD-10 is taken into account to compute the supervised distance of patients. To solve the diagnosis class imbalance, patient tuples that violate deep metric learning framework loss constraints are chosen prior as samples to accelerate the convergence of the neural network. We conducted KNN multi label classification experiment using the learned similarity metric on the real EHRs about stroke disease collected by Chinese Stroke Data Center. The results demonstrate substantial improvement over the baselines.
Dynamic Aspects of Macrophage Polarization during Atherosclerosis Progression and Regression

It is well recognized that macrophages in many contexts in vitro and in vivo display a spectrum of inflammatory features and functional properties. A convenient system to group together different subsets of macrophages has been the M1 (inflammatory)/M2 (anti-inflammatory) classification. In addition to other sites of inflammation, it is now established that atherosclerotic plaques contain both M1 and M2 macrophages. We review results made possible by a number of recent mouse models of atherosclerotic regression that, taken with other literature, have shown the M1/M2 balance in plaques to be dynamic, with M1 predominating in disease progression and M2 in regression. The regulation of the macrophage phenotype in plaques and the functional consequences of the M1 and M2 states in atherosclerosis will also be discussed.
Sound source tracking based on updating histogram

In this paper, a method for a single sound source tracking using a sequential updating histogram based on a speech sparseness by two microphones is proposed. The sound source localization based on the sequential updating histogram can estimate the direction-of-arrival even when a talker moves rapidly. In this paper, such a method is attempted to apply for the sound source tracking problem which the talker moves continuously. Several experiments were conducted in a noisy environment room to evaluate the effectiveness of the proposed method.
MSK-type signals in the presence of adjacent channel interference and white noise

In this letter, the problem of adjacent channel interference (ACI) caused by the close packing of constant envelope MSK-type users in a given frequency band is considered. An optimal receiver filter, based on the theory of matched filtering, is found, and it serves as an upper bound on the signal-to-interference ratio. The intersymbol interference (ISI) caused by the time response of the matched filter is eliminated by a decision feedback equalizer (DFE) which, however, degrades performance. It was found that the matched-filter upper bound allows about 3-15 dB more ACI than the performance of a classical correlation detector (for additive white Gaussian noise only), depending on the frequency separation between channels. The DFE performance is only a little bit worse than that of the matched filter.
A new context for Deese/Roediger-McDermott false memory

False recognition in the Deese/Roediger-McDermott (DRM) paradigm was assessed following manipulation of encoding context. Undergraduate students at Simon Fraser University participated. Experiment 1 replicates the DRM effect using 5-item lists; Experiment 2 demonstrates that a false recognition effect also occurs for 3-item lists specifically developed to later bias the encoding context of DRM lists used in Experiment 1. Experiment 3 investigates false memory upon manipulation of list context; participants studied 8-item lists, in which either the first or last 3 items (bias items) of the list were in a different context than the remaining 5 DRM items. Findings revealed no differences in false recognition due to encoding context. Two accounts of the DRM effect are discussed: the associative activation account, and the discrepancy-attribution hypothesis.