Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of Förster Resonance Energy Transfer (FRET) and Competition of Fluorescent Dyes on DNA Microparticles

Fluorescent labeling is widely used to investigate the structural stability and changes to DNA nano- and microstructures. Despite this, the conventional method for observing DNA structures has several limitations in terms of cost-efficiency. This paper introduces a DNA spherical particle stained with DNA intercalating dyes (SYBR Green and SYTOX Orange) as tracers and reports the interaction between multiple dyes. The interference between the dyes was analyzed in terms of Förster resonance energy transfer (FRET) and competition. The changes in the fluorescence intensity by FRET were uniform, regardless of the sequence. The competition effect could occur when several dyes were added simultaneously. These properties are expected to help in the design of multicolor tracers in bioimaging and environmental applications.
Agency at work: two beginning science teachers’ stories in a context of curriculum reform in China

ABSTRACT In this study, a sociocultural perspective was adopted to understand the interplay between identity and agency in a context of science education reform in China. The manifestation of agency and the interaction between identity and agency were examined with two beginning science teachers teaching with practical work in high school. As part of this study, the identity formation of beginning science teachers was conceived as a site for locating and investigating teacher agency. Based on multiple data sources, we identified six spaces in which the two participants’ agency manifested: (1) personal characteristics; (2) personal beliefs; (3) interactions with students; (4) interactions with colleagues; (5) curriculum materials; and (6) high-stakes examinations. In each space, the two participants’ agency contrasted in terms of perspectives and actions: one was passive, less confident and negative, whereas the other active, more confident and positive. Moreover, it was found that their contrary actions were the result of different perspectives. Based on the findings, a model of the interplay between the identity and agency of an individual science teacher is proposed in a context of curriculum reform. The implications of this model for future research and science teacher development are discussed.
Optimized Schwarz Methods for Domains with an Arbitrary Interface

Optimized Schwarz methods form a class of domain decomposition methods for the solution of partial differential equations. Optimized Schwarz methods employ a first or higher order boundary condition along the artificial interface to accelerate its convergence. In the literature, analysis of optimized Schwarz methods rely on Fourier analysis and so the domains are restricted to be regular (rectangle or disk). By expressing the interface operator in terms of Poincare–Steklov operators, we are able to derive upper bounds of the spectral radius of the operator for Poisson-like problems for two essentially arbitrary subdomains. For a first order (Robin) boundary operator, an optimal choice of the parameter in the boundary operator leads to an upper bound of 1 − O(h) of the spectral radius, where h is the discretization parameter. For a certain higher order boundary operator, a clever choice of the two parameters in the boundary operator leads to an upper bound of 1 − O(h ) of the spectral radius. These agree with the predicted rates for rectangular subdomains available in the literature and are also the observed rates in numerical simulations. This contribution summarizes the author’s work in [11, 12]. Let Ω be a bounded domain in IR with a smooth boundary. Suppose Ω is composed of two nonoverlapping open subdomains, that is, Ω = Ω 1 ∪ Ω2 with Ω1 ∩Ω2 = ∅. Assume that the artificial boundary Γ = Ω 1 ∩Ω2 is non-trivial (nonzero measure in RN−1) and is a smooth curve. We shall always assume that ∂Ωi \Γ is non-trivial for both i = 1, 2. Recall the trace space
Telomere Protection Mechanisms Change during Neurogenesis and Neuronal Maturation: Newly Generated Neurons Are Hypersensitive to Telomere and DNA Damage

Telomeres are DNA–protein complexes at the ends of eukaryotic chromosomes that play an important role in maintaining the integrity of the genome. In proliferative stem cells and cancer cells, telomere length is maintained by telomerase, and telomere structure and functions are regulated by telomere-associated proteins. We find that telomerase levels are high in embryonic cortical neural progenitor cells (NPCs) and low in newly generated neurons (NGNs) and mature neurons (MNs). In contrast, telomere repeat-binding factor 2 (TRF2) expression is undetectable in early brain development in vivo and in cultured NPCs and is expressed at progressively higher levels as NPCs cease proliferation and differentiate into postmitotic neurons. The telomere-disrupting agent telomestatin induces a DNA damage response and apoptosis in NGNs (which have low levels of TRF2 and telomerase), whereas NPCs (which have high levels of telomerase) and MNs (which have high levels of TRF2) are resistant to telomere damage. Overexpression of TRF2 in NGNs protects them against death induced by telomestatin and other DNA-damaging agents. Knockdown of TRF2 expression in MNs and knock-out of telomerase reverse transcriptase in NPCs increased their sensitivity to telomere- and DNA-damaging agents but did not affect the vulnerability of NGNs. These findings suggest that TRF2 and telomerase function as distinct telomere protection mechanisms during the processes of neurogenesis and neuronal maturation and that hypersensitivity of NGNs to telomere damage results from relative deficiencies of both telomerase and TRF2.
Community Association Map - Processing Inter-community Relationships

The use of modern communication technology like the Internet brings a new perspective for the study of society. Following this paradigm shift, this paper presents a process to help in the analysis of social media available on the Internet, specially the analysis focused in the online community’s content. The process goal is to reveal the interests of users through a map of associated communities. The user membership is utilized to establish the relationship among communities. This map shows the interests of members in other communities. An example illustrates the application of the process. A discussion about the opportunities and drawbacks of the process usage is also presented.
Differences in the Serum Nonesterified Fatty Acid Profile of Young Women Associated with a Recent History of Gestational Diabetes and Overweight/Obesity

Background Nonesterified fatty acids (NEFA) play pathophysiological roles in metabolic syndrome and type 2 diabetes (T2D). In this study, we analyzed the fasting NEFA profiles of normoglycemic individuals at risk for T2D (women with a recent history of gestational diabetes (GDM)) in comparison to controls (women after a normoglycemic pregnancy). We also examined the associations of NEFA species with overweight/obesity, body fat distribution and insulin sensitivity. Subjects and Methods Using LC-MS/MS, we analyzed 41 NEFA species in the fasting sera of 111 women (62 post-GDM, 49 controls). Clinical characterization included a five-point oral glucose tolerance test (OGTT), biomarkers and anthropometrics, magnetic resonance imaging (n = 62) and a food frequency questionnaire. Nonparametric tests with Bonferroni correction, binary logistic regression analyses and rank correlations were used for statistical analysis. Results Women after GDM had a lower molar percentage of total saturated fatty acids (SFA; 38.55% vs. 40.32%, p = 0.0002) than controls. At an explorative level of significance several NEFA species were associated with post-GDM status (with and without adjustment for body mass index (BMI) and HbA1c): The molar percentages of 14:0, 16:0, 18:0 and 18:4 were reduced, whereas those of 18:1, 18:2, 20:2, 24:4, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA) and total n-6 NEFA were increased. BMI and the amount of body fat correlated inversely with several SFA and MUFA and positively with various PUFA species over the whole study cohort (abs(ρ)≥0.3 for all). 14:0 was inversely and BMI-independently associated with abdominal visceral adiposity. We saw no correlations of NEFA species with insulin sensitivity and the total NEFA concentration was similar in the post-GDM and the control group. Conclusion In conclusion, we found alterations in the fasting NEFA profile associated with a recent history of gestational diabetes, a risk marker for T2D. NEFA composition also varied with overweight/obesity and with body fat distribution, but not with insulin sensitivity.
Effect of Intravenous Glucose Tolerance Test on Bone Turnover Markers in Adults with Normal Glucose Tolerance

Background It is well known that enteral nutrients result in acute suppression of bone turnover markers (BTMs), and incretin hormones are believed to play a significant role in this physiological skeletal response. However, there is limited research exploring the impact of parenteral nutrients on BTMs. Our aim was to assess the influence of intravenous glucose on BTMs in adults with normal glucose tolerance (NGT). Material/Methods We conducted 1-h intravenous glucose tolerance test (IVGTT) in 24 subjects with NGT. Blood samples were collected before and 5, 10, 15, 20, 30, 60 min after administration of glucose, then serum levels of bone formation marker procollagen type I N-terminal propeptide (P1NP) and resorption marker C-terminal cross-linking telopeptides of collagen type I (CTX) were measured. Results During IVGTT, the fasting CTX level fell gradually and reached a nadir of 80.4% of the basal value at 60 min. Conversely, the fasting P1NP level decreased mildly and reached a nadir of 90.6% of the basal value at 15 min, then gradually increased and reached 96.6% at 60 min. The CTX-to-P1NP ratio increased slightly and reached a peak of 104.3% of the basal value at 10 min, then fell gradually and reached a nadir of 83% at 60 min. Conclusions Our study indicates that intravenous glucose results in an acute suppression of BTMs in the absence of incretin hormones. The mechanism responsible for this needs further investigation.
When majority voting fails: Comparing quality assurance methods for noisy human computation environment

Quality assurance remains a key topic in human computation research. Prior work indicates that majority voting is effective for low difficulty tas ks, but has limitations for harder tasks. This paper explores two methods of addressing this problem: tournament selection and elimination selection, which exploit 2-, 3- and 4-way comparisons between different answers to human computation tasks. Our experimental results and statistical analyses show that both methods produce the correct answer in noisy human computation environment more often than majority voting. Furthermore, we find that the use of 4-way comparisons can significantly reduce the cost of quality assurance relative to the use of 2-way comparisons.
Fitness function evaluations: A fair stopping condition?

It has become acceptable practice to use only a limit on the number of fitness function evaluations (FEs) as a stopping condition when comparing population-based optimization algorithms, irrespective of the initial number of candidate solutions. This practice has been advocated in a number of competitions to compare the performance of population-based algorithms, and has been used in many articles that contain empirical comparisons of algorithms. This paper advocates the opinion that this practice does not result in fair comparisons, and provides an abundance of empirical evidence to support this claim. Empirical results are obtained from application of a standard global best particle swarm optimization (PSO) algorithm with different swarm sizes under the same FE computational limit, on a large benchmark suite.
Selected papers from the DCW data quality project

This paper reviews three readily available cartographical databases (DBs), the Digital Chart of the World (DCW), the World Vector Shoreline (WVS) and 30 Arc-Second DCW Digital Elevation Models (DEM) all originating from the US Defense Mapping Agency (DMA). These are presumed strong candidates as cartographical data sources for strategic needs at several Consultative Group of International Agricultural Research (CGIAR) centres. While most cartographical themes found within these DBs are of acceptable quality, some themes definitively needs improvement. No known substitutes to these are known to the author. An approach is being suggested to overcome these inadequacies. Furthermore, the data quality part of the US Spatial Data Transfer Standard (SDTS) is being briefly summarised with the aim to stress the importance of data quality reporting within the UNEP/CGIAR project when data sets are created. Introduction, definitions and scope I will in this presentation briefly summarise information on some GIS databases (DBs) that originates from the US Defense Mapping Agency, are currently available, are potentially suited for strategic needs of several CGIAR centres and have been recommended to be used as such at the first CGIAR/UNEP workshop ( Arendal I ). Strategic needs was at Arendal I defined as requirements related to studies covering a large geographical area, for example in characterisation and classification to be used in strategic research planning (anon. 1992). I will limit this presentation to cartographical DBs. By cartographical DB is meant a structured collection of digital GIS datasets digitised from topographical (or equivalent) paper maps or created for the purpose of making topographic type paper maps. Commonly, the following themes are included in cartographical DBs: (i) Coastline, (ii) International boundaries, (iii) National administrative boundaries, (iv) Transport infrastructure, (v) Cities, (vi) Hypsography or Digital Elevation Models and (vii) Hydrography. In this presentation International and Sub-national Boundaries are excluded. These will be presented by Deichman and Fox later. Besides the value of this kind of GIS data for cartographical purposes, they are also of great value in GIS modelling. The use of administrative boundaries to derive statistics is a most prominent example. I will not examine sources for GIS cartographical data for operational needs. Operational needs was defined at Arendal I to be related to much more detailed data
Smart manual landmarking of organs

Statistical shape models play a very important role in most modern medical segmentation frameworks. In this work we propose an extension to an existing approach for statistical shape model generation based on manual mesh deformation. Since the manual acquisition of ground truth segmentation data is a prerequisite for shape model creation, we developed a method that integrates a solution to the landmark correspondence problem in this particular step. This is done by coupling a user guided mesh adaptation for ground truth segmentation with a simultaneous real time optimization of the mesh in order to preserve point correspondences. First, a reference model with evenly distributed points is created that is taken as the basis of manual deformation. Afterwards the user adapts the model to the data set using a 3D Gaussian deformation of varying stiffness. The resulting meshes can be directly used for shape model construction. Furthermore, our approach allows the creation of shape models of arbitrary topology. We evaluate our method on CT data sets of the kidney and 4D MRI time series images of the cardiac left ventricle. A comparison with standard ICP-based and population-based optimization based correspondence algorithms showed better results both in terms of generalization capability and specificity for the model generated by our approach. The proposed method can therefore be used to considerably speed up and ease the process of shape model generation as well as remove potential error sources of landmark and correspondence optimization algorithms needed so far.
Cell-free reconstitution of vacuole membrane fragmentation reveals regulation of vacuole size and number by TORC1

The size and copy number of an organelle depend on an equilibrium of membrane fusion and fission. In vitro reconstitution of yeast vacuole fission and fusion shows that TORC1 selectively stimulates fission but does not change fusion activity. This explains the morphological transitions of yeast vacuoles in response to nutrient availability.
Aortic Input Impedance Increases With Age in Healthy Men and Women

Aortic input impedance represents the hydraulic load presented by the systemic circulation to the left ventricle of the heart and is increased in patients with cardiovascular disease. Aging is a strong independent risk factor for cardiovascular disease and could exert this effect partly through an increase in modulus of aortic input impedance. We used a novel noninvasive technique to determine aortic input impedance in 71 healthy men and women aged 20 to 69 years. We found that the aortic input impedance spectrum was shifted rightward with advancing age, characterized by a 37% increase in the frequency of the minimum modulus between the third and seventh decade (P<0.0001). The frequency of the minimum modulus correlated with age in all subjects (r=0.48; P<0.0001), in men (r=0.43; P<0.005), and in women (r=0.53; P=0.001). Although several physical characteristics were associated with the frequency of the minimum modulus (bivariate correlation), a regression model that included age and these physical characteristics showed that age was the only independent predictor of the frequency of the minimum modulus. We conclude that aortic input impedance increases with advancing age in healthy men and women. This increase in aortic input impedance may be an important mechanism by which age increases the risk of cardiovascular disease in humans.
An iterative semi-supervised approach to software fault prediction

Background: Many statistical and machine learning techniques have been implemented to build predictive fault models. Traditional methods are based on supervised learning. Software metrics for a module and corresponding fault information, available from previous projects, are used to train a fault prediction model. This approach calls for a large size of training data set and enables the development of effective fault prediction models. In practice, data collection costs, the lack of data from earlier projects or product versions may make large fault prediction training data set unattainable. Small size of the training set that may be available from the current project is known to deteriorate the performance of the fault predictive model. In semi-supervised learning approaches, software modules with known or unknown fault content can be used for training. Aims: To implement and evaluate a semi-supervised learning approach in software fault prediction. Methods: We investigate an iterative semi-supervised approach to software quality prediction in which a base supervised learner is used within a semi-supervised application. Results: We varied the size of labeled software modules from 2% to 50% of all the modules in the project. After tracking the performance of each iteration in the semi-supervised algorithm, we observe that semi-supervised learning improves fault prediction if the number of initially labeled software modules exceeds 5%. Conclusion: The semi-supervised approach outperforms the corresponding supervised learning approach when both use random forest as base classification algorithm.
Enhancing Wireless Sensor Networks with Acoustic Sensing Technology: Use Cases, Applications &amp; Experiments

This paper presents research carried out within the EU FP7 EAR-IT project, which is working on the challenges of bringing acoustic sensing intelligence to large-scale indoor and outdoor wireless sensor networks, i.e. into two existing test beds out of the EU FP7 FIRE projects SmartSantander and Hobnet. Besides the benefits by integrating machine-learning based acoustic sensing technology, the general deployment approach of the so-called Acoustic Processing Unit, an embedded device whose capabilities go beyond state-of-the-art IoT sensors, as well as the EAR-IT indoor and outdoor use cases are described. This includes hardware qualification for the applications such as energy efficiency of buildings, traffic monitoring and emergency vehicle detection and tracking outdoor as well as acoustic emergency detection for indoor environments and further, a detailed description of the individual Acoustic Processing Unit software components. Latest efforts and simulation results for acoustic source localization using audio sensing technology for wireless sensor networks are presented, indicating that a more intelligent usage of the audio modality enables a wide range of applications and services with high social and technological value.
Affordance discovery based on intrinsic motivation in robots

Affordance research is a new biology-inspired approach to promote the cognitive capabilities of robots. Affordances could capture the relationships between the robot and environment in terms of actions that the robot is able to perform. Intrinsic motivation is the fundamental factor that drives an organism to learn even without external reward, and it is also the reason why an infant organism keeps interacting with the world and developing the knowledge. To search an object is the prerequisite to perceive later affordances such as graspable and pushable, and it is also the instinct action of an infant before 5 months. In this paper, we propose an intrinsic motivation based method to discover the searchable affordance for a robot equipped with limited perceptual and behavioral capabilities. The experiment is carried out in both simulation and real environments, where the NAO humanoid robot could construct the searchable relationships and make the target object be the center of its vision.
Environmental versus geographical effects on genomic variation in wild soybean (Glycine soja) across its native range in northeast Asia

Abstract A fundamental goal in evolutionary biology is to understand how various evolutionary factors interact to affect the population structure of diverse species, especially those of ecological and/or agricultural importance such as wild soybean (Glycine soja). G. soja, from which domesticated soybeans (Glycine max) were derived, is widely distributed throughout diverse habitats in East Asia (Russia, Japan, Korea, and China). Here, we utilize over 39,000 single nucleotide polymorphisms genotyped in 99 ecotypes of wild soybean sampled across their native geographic range in northeast Asia, to understand population structure and the relative contribution of environment versus geography to population differentiation in this species. A STRUCTURE analysis identified four genetic groups that largely corresponded to the geographic regions of central China, northern China, Korea, and Japan, with high levels of admixture between genetic groups. A canonical correlation and redundancy analysis showed that environmental factors contributed 23.6% to population differentiation, much more than that for geographic factors (6.6%). Precipitation variables largely explained divergence of the groups along longitudinal axes, whereas temperature variables contributed more to latitudinal divergence. This study provides a foundation for further understanding of the genetic basis of climatic adaptation in this ecologically and agriculturally important species.
The Vertica Query Optimizer: The case for specialized query optimizers

The Vertica SQL Query Optimizer was written from the ground up for the Vertica Analytic Database. Its design and the tradeoffs we encountered during its implementation argue that the full power of novel database systems can only be realized with a carefully crafted custom Query Optimizer written specifically for the system in which it operates.