Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a system for visualizing Alberta's cemeteries

As archaeologists, historians, and other researchers interpret spatial patterns within and between cemetery sites, they can benefit from access to both relevant data and tools to visualize those data. Unfortunately, the current (and not uncommon) situation within Alberta (Canada) has disconnected data sets located throughout the province, which makes it impossible to produce many potentially insightful visualizations. In this paper, we describe the current state of a collaborative project between academics, government, and several community organizations as we work to create a centralized system for aggregating and visualizing these cemetery data. We present an overview of the architecture, prototypes of the visualization, and our vision for the complete system.
Nonomuraea wenchangensis sp. nov., isolated from mangrove rhizosphere soil.

Strain 210417(T), which forms highly branched substrate and aerial mycelia, is a Gram-positive, aerobic and non-motile actinomycete isolated from mangrove rhizosphere soil. 16S rRNA gene sequence analysis showed that the strain should be classified in the genus Nonomuraea, being most closely related to the type strains of Nonomuraea coxensis (99.6 %) and Nonomuraea bangladeshensis (99.3 %). Chemotaxonomic properties [madurose as the major sugar in the cell wall; meso-diaminopimelic acid and N-acetylmuramic acid in the peptidoglycan; MK-9(H(4)) as the major menaquinone; iso-C(16 : 0) (24.1 %) as major fatty acid; and phospholipid pattern type IV] are consistent with the assignment of strain 210417(T) to the genus Nonomuraea. Strain 210417(T) could be differentiated from the closely related species N. coxensis and N. bangladeshensis by morphological, physiological, biochemical and chemotaxonomic properties, 16S rRNA gene sequence analysis and DNA-DNA hybridization results. It is therefore proposed that strain 210417(T) represents a novel species of the genus Nonomuraea, for which the name Nonomuraea wenchangensis sp. nov. is given; the type strain is 210417(T) ( = CGMCC 4.5598(T) = DSM 45477(T)).
Hot Transcriptomics

DNA microarray technology allows for a quick and easy comparison of complete transcriptomes, resulting in improved molecular insight in fluctuations of gene expression. After emergence of the microarray technology about a decade ago, the technique has now matured and has become routine in many molecular biology laboratories. Numerous studies have been performed that have provided global transcription patterns of many organisms under a wide range of conditions. Initially, implementation of this high-throughput technology has lead to high expectations for ground breaking discoveries. Here an evaluation is performed of the insight that transcriptome analysis has brought about in the field of hyperthermophilic archaea. The examples that will be discussed have been selected on the basis of their impact, in terms of either biological insight or technological progress.
Effect of temperature on the mechanical properties of 3D-printed PLA tensile specimens

Purpose Recent advancements of 3D printing technology have brought forward the interest for this technique in many engineering fields. This study aims to focus on mechanical properties of the polylactic acid (PLA) feeding material under different thermal conditions for a typical fusion deposition of 3D printer system. Design/methodology/approach Specimens were tested under static loading within the range 20ºC to 60ºC considering different infill orientations. The combined effect of temperature and filament orientation is investigated in terms of constitutive material parameters and final failure mechanisms. The difference between feeding system before and post-3D printing was also assessed by mechanical test on feeding filament to verify the thermal profile during the deposition phase. Findings The results in terms of Young’s modulus, ultimate tensile strength (UTS), strain at failure (εf) and stress at failure (σf) are presented and discussed to study the influence of process settings over the final deposited material. Fracture surfaces have been investigated using an optical microscope to link the phenomenological interpretation of the failure with the micro-mechanical behaviour. Experimental results show a strong correlation between stiffness and strength with the infill orientation and the temperature values. Moreover, a relevant effect is related to deformed geometry of the filament approaching glass transition region of the polymer according to the deposition orientation. Research limitations/implications The developed method can be applied to optimise the stiffness and strength of any 3D-printed composite according to the infill orientation. Practical implications To avoid the failure of specimens outside the gauge length, a previously proposed modification to the geometry was adopted. The geometry has a parabolic profile with a curvature of 1,000 mm tangent to the middle part of the specimen. Originality/value Several authors have reported the stiffness and strength of 3D-printed parts under static and ambient temperature for different build parameters. However, there is a lack of literature on the combination of the latter with the temperature effects on the mechanical properties which this paper covers.
Self-Esteem, Internalizing Symptoms, and Theory of Mind in Youth With Autism Spectrum Disorder

Self-esteem is a potent indicator of mental health in typically developing (TYP) individuals. It is surprising that there have been few comprehensive investigations of self-esteem in children and adolescents with autism spectrum disorder (ASD), given that they are at high risk for comorbid mental health problems, such as depression and anxiety. The objectives of the current study were to assess how youth with ASD rate their self-esteem compared to age-matched TYP youth and to examine how self-esteem relates to internalizing psychopathology and theory of mind in the two groups. Seventy-three children and adolescents, ages 9 to 17, were administered a battery of questionnaires assessing self-esteem and internalizing symptoms, as well as tasks designed to measure theory of mind. Results indicated that youth with ASD rated their self-esteem significantly lower than did TYP youth. Self-esteem was strongly related to depression in both groups but was negatively related to theory of mind only for youth with ASD. These results may provide important insights into how individuals with ASD form evaluations of their own self-worth and illustrate how increasing self-awareness in individuals with ASD is not without risks.
Synthesis and Properties of Highly Conducting Natural Flake Graphite/Phenolic Resin Composite Bipolar Plates for Pem Fuel Cells

Electrically conductive composite bipolar plates consisting of resole-typed phenol formaldehyde resin and natural flake graphite (NFG) have been fabricated by compression molding technique at room temperature. The aim of this study is to investigate the effects of NFG content, molding pressure, and nano-sized carbon black (NCB) on the properties of composite bipolar plates. The NFG/resin composite plates have been studied for various properties including electrical, mechanical, and thermal properties. It has been observed that the composite plates prepared at NFG content of 45 wt%, NCB content of 4.5 wt%, and molding pressure of 15 MPa have optimum properties. Under optimal conditions, bipolar plates showed better properties at bulk density 1.79 g/cc, electrical conductivity 358 S/cm, flexural strength 29.3 MPa, compressive strength 43.6 MPa, water absorption 0.34% and surface microhardness 72.6 HV. Additionally, the plates were thermally stable up to 300°C. Hence, NFG/resin composites successfully fulfil the DOE-2015 requirements for bipolar plates in PEM fuel cells.
Six Visions for the Future of Personality Psychology

This is an exciting time to be a personality psychologist. A few years ago a distinguished colleague described the field as “coming out of a tailspin. ” He was right, but things are much better now. Personality psychology’s important contributions are having an increasing impact as creative researchers push forward with programs on topics as diverse as the molecular biology of genetics and the psychological dynamics of people who have been socialized in more than one culture. Personality is the most important topic in psychology because it is where all the other areas come together. Cognitive psychology describes how people think and perceive. Developmental psychology traces the course of a person’s psychological construction and change from infancy throughout life. Biological psychology explains the underpinnings of behavior in anatomy, physiology, genetics, and evolutionary history. And social psychology concerns how people respond to and affect the behavior of others. All of these subdisciplines serve personality psychology, the only field with the selfassigned mission of explaining whole people. It does this by focusing on individual differences, for the most part, but this is only natural. People are different from each other, and an understanding of how and why they differ necessarily entails a complementary understanding of the ways in which they are the same. So it is a bit surprising, in retrospect, what a difficult time personality has sometimes had in gaining the attention and even respect of the rest of psychology, not to mention the world at large. I can identify at least three historic reasons for this difficulty. First, personality psychology has long been identified in the minds of many people with the first (and perhaps only) course in the subject that they took in college. Too often, this was (and sometimes still is) the classic “tour of the graveyard” that focuses on brilliant but long-deceased theorists and leads students to end the semester thinking the burning concern of the field is the disagreement between Freud and Jung (see Laura King’s contribution later in this chapter). I actually defend the inclusion of Freud and Jung in modern personality courses, in measured doses, but a course that is restricted to theorists like these is an unforgivable misrepresentation of the field, a failure in one’s duty to educate students, and a slap in the face to every contemporary personality researcher. A second source of personality’s difficulty is, of course, Mischel’s (1968) critique and the ensuing decades of arguments, rebuttals, and obfuscations. The controversy resulted in some hard-won enlightenment (Kenrick & Funder, 1988) but also left behind damage that included decimated or disestablished graduate programs, careers that ended prematurely or never even began, and a lingering image in the minds of a surprising number of smart psychologists outside the field that “personality” is a quaint,
A Parallel Algorithm for the Constrained Multiple Sequence Alignment Problem Designed for GPUs

Multiple sequence alignment (MSA) is one of the most important problems in computational biology. As availability of genomic and proteomic data constantly increases, new tools for processing this data in reasonable time are needed. One method of addressing this issue is parallelization. Nowadays, graphical processing units offer much more computational power than central processors, hence GPUs become more and more popular in computational-intensive tasks, including sequence alignment. We investigate the constrained multiple sequence alignment problem (CMSA) which allows some prior knowledge to be introduced to a final alignment. As a result we propose a GPU-parallel version of the Center Star algorithm which overtakes vastly its CPU-serial equivalent as well as the parallel version run on the quad-core processor. The speedups over CPU-serial algorithm were from 30 to 110 in the case of synthetic sets and from 55 to 75 for the real sequences obtained from the Pfam database.
Identification of subject specific and functional consistent ROIs using semi-supervised learning

Regions of interests (ROIs) for defining nodes of brain network are of great importance in brain network analysis of fMRI data. The ROIs are typically identified using prior anatomical information, seed region based correlation analysis, clustering analysis, region growing or ICA based methods. In this paper, we propose a novel method to identify subject specific and functional consistent ROIs for brain network analysis using semi-supervised learning. Specifically, a graph theory based semi-supervised learning method is adopted to optimize ROIs defined using prior knowledge with a constraint of local and global functional consistency, yielding subject specific ROIs with enhanced functional connectivity. Experiments using simulated fMRI data have demonstrated that functional consistent ROIs can be identified effectively from data with different signal to noise ratios (SNRs). Experiments using resting state fMRI data of 25 normal subjects for identifying ROIs of the default mode network have demonstrated that the proposed method is capable of identifying subject specific ROIs with stronger functional connectivity and higher consistency across subjects than existing alternative techniques, indicating that the proposed method can better identify brain network ROIs with intrinsic functional connectivity.
Improved short-term load forecasting based on EEMD, Guassian disturbance firefly algorithm and support vector machine

Accurate short-term load forecasting plays a crucial role in electricity industry and market. In this study, a novel forecasting method based on Support Vector Machine (SVM) and Firefly Algorithm (FA) has been created to realize accurate and reliable load prediction. The performance of SVM highly depends on the selection of parameters, and Gaussian disturbance Firefly Algorithm (GDFA) proposed in this study can satisfy the necessary. Ensemble Empirical Mode Decomposition (EEMD) is employed to decompose the load data into sub-series with different frequency. This paper extracts daily maximum temperature, daily minimum temperature, wind speed, rainfall, day type, and the load one week before the forecasting day as input variables. Two cases are taken to verify the effective performance of GDFA compared with FA, as well as the superiority of EEMD-GDFA-SVM over other forecasting techniques in short-term load forecasting.
The Economic Design of the MSE Control Chart

In this article, an economic design model of the MSE control chart is proposed. The formulated cost function includes the cost incurred in production process and the loss borne by customers because of the shift of means and the drift of variation. The economic bounds where the process is shut down if the search indicates the presence of an assignable cause are also being considered. A program written in Matlab 7.0 is used to determine the optimum parameters including the sample size n, the sample interval h and the width of the control limits k. Finally, an example is given to illustrate the proposed economic design and sensitivity analysis is carried out.
HIF1α Protein Stability Is Increased by Acetylation at Lysine 709*

Background: HIF1α and p300 are key components of HIF-1 transcription complex. Results: Lysine 709 of HIF1α is acetylated by p300, which increases protein stability and HIF-1 activity. Conclusion: p300 has a novel function in stabilizing HIF1α by Lys-709 acetylation. Significance: New insights in how HIF1α is post-translationally regulated by its cofactor to ensure HIF-1 activity. Lysine acetylation regulates protein stability and function. p300 is a component of the HIF-1 transcriptional complex and positively regulates the transactivation of HIF-1. Here, we show a novel molecular mechanism by which p300 facilitates HIF-1 activity. p300 increases HIF-1α (HIF1α) protein acetylation and stability. The regulation can be opposed by HDAC1, but not by HDAC3, and is abrogated by disrupting HIF1α-p300 interaction. Mechanistically, p300 specifically acetylates HIF1α at Lys-709, which increases the protein stability and decreases polyubiquitination in both normoxia and hypoxia. Compared with the wild-type protein, a HIF1α K709A mutant protein is more stable, less polyubiquitinated, and less dependent on p300. Overexpression of the HIF1α wild-type or K709A mutant in cancer cells lacking the endogenous HIF1α shows that the K709A mutant is transcriptionally more active toward the HIF-1 reporter and some endogenous target genes. Cancer cells containing the K709A mutant are less sensitive to hypoxia-induced growth arrest than the cells containing the HIF1α wild-type. Taken together, these data demonstrate a novel biological consequence upon HIF1α-p300 interaction, in which HIF1α can be stabilized by p300 via Lys-709 acetylation.
Models for thrombin generation and risk of disease

Computational models can offer an integrated view of blood clotting dynamics and may ultimately be instructive regarding an individual's risk of bleeding or clotting. Appropriately, developed and validated models could allow clinicians to simulate the outcomes of therapeutics and estimate risk of disease. Computational models that describe the dynamics of thrombin generation have been developed and have been used in combination with empirical studies to understand thrombin dynamics on a mechanistic basis. The translation of an individual's specific coagulation factor composition data using these models into an integrated assessment of hemostatic status may provide a route for advancing the long‐term goal of individualized medicine. This review details the integrated approaches to understanding: (i) What is normal thrombin generation in individuals? (ii) What is the effect of normal range plasma composition variation on thrombin generation in pathologic states? (iii) Can disease progression or anticoagulation be followed by understanding the boundaries of normal thrombin generation defined by plasma composition? (iv) What are the controversies and limitations of current computational approaches? Progress in these areas can bring us closer to developing models that can be used to aid in identifying hemostatic risk.
Chapter 5 TRIO:ASYSTEMFORDATA,UNCERTAINTY,AND LINEAGE

This chapter covers the Trio database management system. Trio is a robust prototype that supports uncertain data and data lineage, along with the standard features of a relational DBMS. Trio’s new ULDB data model is an extension to the relational model capturing various types of uncertainty along with data lineage, and its TriQL query language extends SQL with a new semantics for uncertain data and new constructs for querying uncertainty and lineage. Trio’s data model and query language are implemented as a translation-based layer on top of a conventional relational DBMS, with some stored procedures for functionality and increased efficiency. Trio provides both an API and a full-featured graphical user interface. Acknowledgments. Contributors to the Trio project over the years include (alphabetically) Parag Agrawal, Omar Benjelloun, Ashok Chandra, Julien Chaumond, Anish Das Sarma, Alon Halevy, Chris Hayworth, Ander de Keijzer, Raghotham Murthy, Michi Mutsuzaki, Tomoe Sugihara, Martin Theobald, and Jeffrey Ullman. Funding has been provided by the National Science Foundation and the Boeing and Hewlett-Packard Corporations.
Experimental and numerical study on short eccentric columns strengthened by textile-reinforced concrete under sustaining load

For the eccentric compression structures which cannot be strengthened by wrap method, this paper presents an experimental and numerical study on flexural strengthening by applying textile reinforced concrete at the tensile face. Seven short columns were constructed and tested under eccentric load. One of the columns did not receive any strengthening and was used as the control column, whereas the rest six were externally upgraded by textile-reinforced concrete layers. The main parameters taken into account covered: (a) type of mortar, (b) preload level, and (c) number of textile-reinforced concrete layers. Besides the experimental program, a numerical investigation utilizing non-linear finite element analysis was carried out and a good agreement was obtained between the experimental and numerical results. Further, the numerical analysis was extended to additional cases to deepen the understanding of flexural-enhancing mechanism . It is concluded that textile-reinforced concrete substantially increases the flexural capacity of the eccentric compression columns; the more the textile layer, the greater the gain. However, the preload has an apparently adverse influence on the strengthening effectiveness, as it causes the strain loss of the textile; the bigger the preload level, the more the loss.
Dynamic network configuration: Hotspot identification for Virtual Small Cells

One of the envisaged candidates technologies to be used in next generation mobile networks is the integration of a large number of antennas at the Base Station (BS), known as Massive Multiple-Input Multiple-Output (MIMO). Massive MIMO can focus the energy on a user or group of users to improve their throughput and the network capacity. An approach of this technology focuses on the creation of coverage areas with the size of a pico-cell, called Virtual Small Cells (VSCs). Their main advantage is that they allow increasing the network capacity while avoiding the deployment cost of new small BSs. Identifying the dense traffic areas in real time and serving them in a responsive way is a key challenge to be address. Our work focuses on dynamically identifying the dense traffic areas so that the VSCs can be implemented and adjust their coverage. To conduct this research we use the K-means method and propose an algorithm that dynamically determines the hotspot parameters for VSCs, i.e., center and radius in order to optimize the overall capacity of the mobile network. Note that this algorithm could be used to identify any group of users.
Structure of Factor H-binding Protein B (FhbB) of the Periopathogen, Treponema denticola

Background: The Treponema denticola FhbB protein binds FH, a complement regulator. Results: The structure of FhbB was solved, and its interaction with FH was further defined. Conclusion: The structurally unique FhbB protein interacts with CCP7 of FH through electrostatic interactions. Significance: The T. denticola/FH interaction may perturb complement regulation resulting in conditions that favor the development of periodontal disease. Periodontitis is the most common disease of microbial etiology in humans. Periopathogen survival is dependent upon evasion of complement-mediated destruction. Treponema denticola, an important contributor to periodontitis, evades killing by the alternative complement cascade by binding factor H (FH) to its surface. Bound FH is rapidly cleaved by the T. denticola protease, dentilisin. In this report, the structure of the T. denticola FH-binding protein, FhbB, was solved to 1.7 Å resolution. FhbB possesses a unique fold that imparts high thermostability. The kinetics of the FH/FhbB interaction were assessed using surface plasmon resonance. A KD value in the micromolar range (low affinity) was demonstrated, and rapid off kinetics were observed. Site-directed mutagenesis and sucrose octasulfate competition assays collectively indicate that the negatively charged face of FhbB binds within FH complement control protein module 7. This study provides significant new insight into the molecular basis of FH/FhbB interaction and advances our understanding of the role that T. denticola plays in the development and progression of periodontal disease.