Miracle-dz/UniFAR-FTUs huggingface dataset:
in ancient heritable bacterial of fungi

Bacterial endosymbionts are critical to the existence of many eukaryotes. Among them, vertically transmitted endobacteria are uniquely typified by reduced genomes and molecular evolution rate acceleration relative to free ‐ living taxa. These patterns are attributable to genetic drift ‐ dominated degenerative processes associated with reproductive dependence on the host. The degenerative evolution scenario is well supported in endobacteria with strict vertical transmission, such as essential mutualists of insects. In contrast, heritable endosymbionts that are nonessential to their hosts and engage occasionally in horizontal transmission are expected to display deviations from the degenerative evolution model. To explore evolution patterns in such nonessential endobacteria, we focused on Candidatus Glomeribacter gigasporarum ancient heritable mutualists of fungi. Using a collection of genomes, we estimated in Glomeribacter mutation rate at 2.03×10 ‐ 9 substitutions per site per year and effective population size at 1.44×108. Both fall within the range of values observed in free ‐ living bacteria. To assess the ability of Glomeribacter to purge slightly deleterious mutations, we examined genome ‐ wide dN/dS values and distribution patterns. We found that these dN/dS profiles cluster Glomeribacter with free ‐ living bacteria as well as with other nonessential endosymbionts, while distinguishing it from essential heritable mutualists of insects. Finally, our evolutionary simulations revealed that the molecular evolution rate acceleration in Glomeribacter is caused by limited recombination in a largely clonal population rather than by increased fixation of slightly deleterious mutations. Based on these patterns, we propose that genome evolution in Glomeribacter is nondegenerative and exemplifies a departure from the model of degenerative evolution in heritable endosymbionts. a significant acceleration of the molecular evolution rate relative to free ‐ living Burkholderia, based nucleotide substitution patterns rRNA gene sequences To explore the role of genetic drift versus selection in the evolution of Glomeribacter, we estimated in these endobacteria the neutral mutation rate, μ , and effective population size, Ne. We also examined purifying selection against slightly deleterious mutations as well as diversifying selection in the Glomeribacter population. Finally, we modeled evolutionary processes under different mutation and recombination conditions in a population. We found that in Glomeribacter, μ and Ne fall within the range of values observed in free ‐ living bacteria. We also established that these endobacteria appear to be as effective at purging slightly deleterious mutations as free ‐ living bacteria. Our evolutionary simulations revealed that the evolutionary rate acceleration apparent in Glomeribacter may be independent of the nucleotide substitution rate and attributed to infrequent recombination in a predominantly clonal population. Overall, our findings indicate that genome evolution in Glomeribacter is driven by selection rather than by genetic drift.
SIMURG: Performance-based Model for the Assessment of Sustainability: Synthesis of the Paradigmatic and Frame Models

Today decision-making processes of public authorities, who have the responsibility of developing sustainable policies for their built environment entities, do not support transparency, accountability, and consistency of their decisions. What societies require is a human-centric vision, a consistent philosophical/paradigmatic model that supports this vision, and the tools that increase the legitimacy of the whole decision-making process. The problem is the lack of these visions and tools that allow the citizens to meet their priorities in their lives with the identities of built environment entities and public authorities to accept/propose suitable pr ojects by using “layers” such as historical/smart/ green/slow/safe, etc. Most of the studies in the literature deal with the sustainability assessment problem at only one environmental dimension of sustainability without considering interactions among the dimensions of 3D Cartesian system and their levels. A paradigmatic model and frame model, which will be used as a guide for developing further conceptual and practical models must be developed from scratch. The conceptual and practical models can only be developed in an iterative process by considering the interactions among these components. In this study, a bottom-up approach in an iterative process was adopted and practiced in the development process of the relationships among the components to propose the above-stated parts of the model of the research. (a) the citizens to meet their priorities in life with the identities of built environment entities, (b) public authorities and entrepreneurs to accept/propose suitable projects that have consistent identities by using “concepts/layers/labels” such as historical/smart/green/slow/ safe, etc., that are presented by specific KPIs and associated weights, for the built environment entities at all hierarchical levels. A comprehensive model can be used for the assessment of the entities' sustainability on the built environment dimension by considering the impacts of the other two dimensions, i.e., economic and social dimensions, on the built environment dimension of sustainability. There are numerous related studies and models in the literature;
Evaluating the Effect of Alzheimer’s Disease Status on Co-Registration Accuracy of PET and MRI Brain Scans ∗

—Does the clinical status of patients with either Alzheimer’s disease or mild cognitive impairment when compared with the normal healthy status of control subjects have an effect on the co-registration accuracy of the participants PET and MRI brain scans? An initial evaluation reveals that a statistically signiﬁcant difference may exist in co-registration accuracy with some popular algorithms for the different groups of participants’ brain scans. These differences suggest that investigators should use appropriate caution when reviewing fusion studies of co-registered PET and MRI brain scans.
Dose Planning and Dose Delivery in Radiation Therapy

A method has been developed for calibration of CT-numbers to volumetric electron density distributions using tissue substitutes of known elemental composition and experimentally determined electron density. This information have been used in a dose calculation method based on photon and electron interaction processes. The method utilizes a convolution integral between the photon fiuence matrix and dose distribution kernels. Inhomogeneous media are accounted for using the theorems of Fano and O'Connor for scaling dose distribution kernels in proportion to electron density. For clinical application of a calculated dose plan, a method for prediction of accelerator output have been developed. The method gives the number of monitor units that has to be given to obtain a certain absorbed dose to a point inside an iiregular, inhomogeneous object. The method for verification of dose distributions outlined in this study makesit possible to exclude the treatment related variance contributions, making an objective evaluation of dose calculations with experiments feasible. The methods for electron density determination, dose calculation and prediction of accelerator output discussed in this study will all contribute to an increased accuracy in the mean absorbed dose to the target volume. However, a substantial gain in the accuracy for the spatial absorbed dose distribution will also follow, especially using CT for mapping of electron density together with the dose calculation algorithm.
Metacognitive Attitude and Knowledge of Biology Teacher Candidates

Metacognitive knowledge becomes a target on Indonesian curriculum to improve the accomplishment of Indonesian students’ higher order thinking skill. The study aimed to discover the metacognitive attitudes and knowledge of Biology teacher candidates. The study was conducted with the participation of 90 biology teacher candidates from two state universities in Jakarta. The results revealed that most teacher candidates have moderate metacognitive attitudes and low
Green Synthesis of Silver Nanoparticles Using Stem Bark Extract of Prosopis africana and Their Antimicrobial Activity

--------------------------------------------------------------------------------------------------------------------------------------ABSTRACT Silver nanoparticles (AgNPs) were synthesized using aqueous stem bark extract of Prosopis africana. The synthesis was done using 1mM silver nitrate solution and aqueous extract derived from the stem bark of Prosopis africana at 60°C.The AgNPs were characterized using UV-Visible spectroscopy, FT-IR, SEM, XRF and XRD analyses. The combination of pale yellow to dark brown coloration and the characteristics peak at 445nm from the UV-Visible spectroscopic analysis confirmed the formation of the silver nanoparticles.The XRD analysis confirmed the crystalline nature of the synthesized AgNPs and the crystallite size was 10nm approximately. The FTIR spectrum revealed the possible biomolecules that served as reducing and as well as stabilizing agents. The SEM images showed multiple shapes with spiky and spherical shapes dominant. The XRF analysis confirmed the existence of silver in the AgNPs and its quantification. The antimicrobial sensitivity of the AgNPs was also tested against Staphyloccus aureus, Bacislus subtilis, Escherichia coli and Proteus vulgarcus. The AgNPs was effective against Staphyloccus aureus and Bacislus subtilis and non-effective against Escherichia coli and Proteus vulgarcus. The minimum inhibitory concentrations (MIC) were 0. 5µg/ml, 0. 25µg/ml for Staphyloccus aureus and Bacislus subtilis respectively.
Minimum+1 (s, t)-cuts and Dual-edge Sensitivity Oracle

Let G be a directed multi-graph on n vertices and m edges with a designated source vertex s and a designated sink vertex t. We study the (s,t)-cuts of capacity minimum+1 and as an important application of them, we give a solution to the dual-edge sensitivity for (s,t)-mincuts—reporting an (s,t)-mincut upon failure or insertion of any pair of edges. Picard and Queyranne [Mathematical Programming Studies, 13(1): 8–16 (1980)] showed that there exists a directed acyclic graph (DAG) that compactly stores all minimum (s,t)-cuts of G. This structure also acts as an oracle for the single-edge sensitivity of minimum (s,t)-cut. For undirected multi-graphs, Dinitz and Nutov [STOC, 509–518 (1995)] showed that there exists an 𝒪(n) size 2-level Cactus model that stores all global cuts of capacity minimum+1. However, for minimum+1 (s,t)-cuts, no such compact structure exists till date. We present the following structural and algorithmic results on minimum+1 (s,t)-cuts. (1) Structure: There is an 𝒪(m) size 2-level DAG structure that stores all minimum+1 (s,t)-cuts of G such that each minimum+1 (s,t)-cut appears as 3-transversal cut—it intersects any path in this structure at most thrice. We also show that there is an 𝒪(mn) size structure for storing and characterizing all minimum+1 (s,t)-cuts in terms of 1-transversal cuts. (2) Data structure: There exists an 𝒪(n2) size data structure that, given a pair of vertices {u,v} that are not separated by an (s,t)-mincut, can determine in 𝒪(1) time if there exists a minimum+1 (s,t)-cut, say (A,B), such that s,u ∊ A and v,t∊ B; the corresponding cut can be reported in 𝒪(|B|) time. (3) Sensitivity oracle: There exists an 𝒪(n2) size data structure that solves the dual-edge sensitivity problem for (s,t)-mincuts. It takes 𝒪(1) time to report the capacity of a resulting (s,t)-mincut (A,B) and 𝒪(|B|) time to report the cut. (4) Lower bounds: For the data structure problems addressed in results (2) and (3) above, we also provide a matching conditional lower bound. We establish a close relationship among three seemingly unrelated problems—all-pairs directed reachability problem, the dual-edge sensitivity problem for (s,t)-mincuts, and the problem of reporting the capacity of ({x,y}, {u,v})-mincut for any four vertices x,y,u,v in G. Assuming the Directed Reachability Hypothesis by Patrascu [SIAM J. Computing, 827–847 (2011)] and Goldstein et al. [WADS, 421–436 (2017)], this leads to \(\tilde{\Omega }(n^2)\) lower bounds on the space for the latter two problems.
DLCR: Efficient Indexing for Label-Constrained Reachability Queries on Large Dynamic Graphs

Many real-world graphs, e.g., social networks, biological networks, knowledge graphs, naturally come with edge-labels, with different labels representing different relationships between nodes. On such edge-labeled graphs, an important query is the label-constrained reachability (LCR) query, where we are given a source s , a target t , a label set ψ, and the goal is to check if there exists any path P from s to t such that labels of edges on P all belong to ψ. Existing indexing schemes for LCR queries still focus on static graphs, despite the fact that many edge-labeled graphs are dynamic in nature. Motivated by the limitations of existing solutions, we present a study on how to effectively maintain the indexing scheme on dynamic graphs. Our proposed approach is based on the state-of-the-art 2-hop index for LCR queries. In this paper, we present efficient algorithms for updating the index structure in response to dynamic edge insertions/deletions and demonstrate the correctness of our update algorithms. Following that, we present that adopting a query-friendly but update-unfriendly indexing scheme results in surprisingly superb query/update efficiency and outperforms those update-friendly ones. We analyze and demonstrate that the query-friendly indexing scheme actually achieves the same time complexity as those of update-friendly ones. Finally, we present the batched update algorithms where the updates may include multiple edge insertions/deletions. Extensive experiments show the effectiveness of the proposed update algorithms, query-friendly indexing scheme, and batched update algorithms.
Query Strategies for Directed Graphical Models and their Application to Adaptive Testing

of “Query Strategies for Directed Graphical Models and their Application to Adaptive Testing” by Sam Saarinen, Ph.D., Brown University, May 2021. Educational assessments are crucial for both instructors and education researchers to measure learning, troubleshoot student problems, evaluate pedagogy, and improve education. Unfortunately, creating and administering reliable assessments is a labor-intensive process. This dissertation frames assessment creation from a pool of assessment items as a machine learning problem and tackles this problem by learning directed graphical models of topic prerequisite relationships. It is shown on a variety of real datasets that these models can be learned in a computationallyand dataefficient manner from records of student responses, can be queried efficiently, and produce accurate predictions about student knowledge. This technique is used to develop and administer novel computer science assessments of instructor-defined specificity using student-authored questions. Query Strategies for Directed Graphical Models and their Application to Adaptive Testing by Sam Saarinen B. Sc. , University of Kentucky, 2016 Sc. M. , Brown University, 2018 A dissertation submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in the Department of Computer Science at Brown University Providence, Rhode Island May 2021 © Copyright 2021 by Sam Saarinen This dissertation by Sam Saarinen is accepted in its present form by the Department of Computer Science as satisfying the dissertation requirement for the degree of Doctor of Philosophy. Date Michael L. Littman, Director Recommended to the Graduate Council Date Stephen Bach, Reader Date Shriram Krishnamurthi, Reader Approved by the Graduate Council Date Andrew G. Campbell Dean of the Graduate School
From Pixels to Layers: Joint Motion Estimation and Segmentation

of “From Pixels to Layers: Joint Motion Estimation and Segmentation” by Deqing Sun, Brown University, May 2013 Estimating image motion, or optical flow, in scenes with multiple moving objects and segmenting the individual moving objects are two fundamental problems in computer vision and have applications in many fields, including medical imaging, image processing, graphics, and robotics. Motion estimation and scene segmentation are particularly challenging because of lighting changes, motion boundaries, occlusions, and indiscriminative appearances. Despite decades of extensive research effort, current methods still tend to produce large optical flow errors near motion boundaries and in occlusion regions and falsely merge foreground objects with the background. A key feature of optical flow methods is an energy term, or prior, that prefers spatially smooth flow fields. In this dissertation, we show that image-dependent and non-local prior models can better preserve motion boundaries than the widely used pairwise Markov Random Field (MRF) models. We also demonstrate that joint motion estimation and segmentation can achieve more accurate results than the separate treatment of each problem. First, we formulate fully learnable low-level models of optical flow and learn the models from training data. Our results show that image-dependent, steerable models outperform standard MRF models, especially in recovering motion boundaries. Second, to understand what makes optical flow accurate, we perform a quantitative analysis of recent practices in optical flow estimation. Median filtering of the flow field is one of the key features of the most accurate methods and we formalize this as a non-local smoothness term that integrates information over a large spatial neighborhood. We further define a weighted non-local smoothness term that uses both image and motion cues to preserve motion boundaries. Third, inspired by recent successes in static image segmentation we develop a layered model to segment moving objects (layers) using image-dependent, continuous support functions. The method orders each layer in depth and explicitly models the occlusions between layers and the temporal consistency of layers. In an attempt to avoid being trapped in poor local optima, we define a discrete formulation of our objective function and extend graph cuts optimization methods to obtain good initial values for the continuous formulation. The mixed continuous-discrete optimizer can automatically infer the number of layers and their depth ordering for a given scene. Experimental results on benchmark datasets demonstrate the benefits of joint motion estimation and segmentation: the layered approach achieves more accurate motion estimates in motion boundary and occlusion regions and better segments the foreground from the background when compared with solving each problem separately.
Improved Scientific Analysis through Domain Driven Visualization and Support for Analytic Deliberation

of “Improved Scientific Analysis through Domain Driven Visualization and Support for Analytic Deliberation” by Radu Jianu, Ph.D., Brown University, May 2012. This dissertation introduces and evaluates novel visualization methods that enable researchers to derive and test hypotheses from available scientific data faster and more accurately than before. Following the traditional visualization approach, we introduce novel ways of visualizing and interacting with scientific data that support and accelerate researchers’ data analysis workflows. Following the visual analytics path, which advocates for supporting the reasoning process itself, we quantify the degree to which interface design elements can be used to unobtrusively guide researchers towards applying verified and established analysis techniques in their research. We first present novel visualization methods that were developed in response to analytic needs indentified through collaborative efforts in three concrete application areas. In neuroscience we enable faster interaction with diffusion tensor imaging (DTI) datasets by creating planar representations of the inherently 3D data. In proteomics we facilitate the visual collation of experimental data and existing protein interaction information and accelerate the discovery process by uncovering and supporting elements of the proteomic analysis workflow. In genomics we increase the accessibility of analyzable visualizations of microarray data and eliminate the overhead of creating visualizations and learning new systems by implementing and evaluating a novel data distribution method. Finally, we use the concepts of persuasive technology and “choice architecture” which state that a user of a system can be unobtrusively guided towards behavioral patterns that are more efficient, in terms of self-assumed goals, by slight alterations in the system interface. We provide quantitative experimental support for the hypothesis that we can use subtle changes in the interfaces of visual analysis systems to influence users’ analytic behavior and thus unobtrusively guide them towards improved analytic strategies. We posit that this approach may facilitate the use of visual analytics expertise to correct biases and heuristics documented in the cognitive science community. Improved Scientific Analysis through Domain Driven Visualization and Support for Analytic Deliberation by Radu Jianu B. S. , Polytechnic University of Timisoara, 2005 Sc. M. Brown University, 2007 A dissertation submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in the Department of Computer Science at Brown University Providence, Rhode Island May 2012 c © Copyright 2012 by Radu Jianu This dissertation by Radu Jianu is accepted in its present form by the Department of Computer Science as satisfying the dissertation requirement for the degree of Doctor of Philosophy. Date David H. Laidlaw, Director Recommended to the Graduate Council Date Odest Chadwicke Jenkins, Reader Date Ben J. Raphael, Reader Approved by the Graduate Council