Miracle-dz/UniFAR-FTUs huggingface dataset:
Bidirectional Associations Between Self-Perceptions of Aging and Processing Speed Across 3 Years

Background: Previous studies point to a potential relationship between self-perceptions of aging (SPA) and cognitive performance. However, most of these studies are limited by their experimental design. Previous longitudinal studies looked solely at memory as an outcome variable without examining the directionality of effects. The present study examines the direction of effects between two domains of SPA (personal growth and physical losses) and processing speed (PS). Methods: The sample consists of 8,198 participants of the German Ageing Survey (DEAS), aged between 40 and 93 years. A cross-lagged path model was estimated to examine directions of relationships across 3 years via chi-squared difference tests for each domain of SPA. Results: In the unconstrained models, the effect of SPA domain personal growth in 2008 on PS in 2011 and vice versa were marginally significant. For SPA domain physical losses, the effect of SPA on PS was significant, whereas the other direction of the effect did not reach significance. However, the cross-lagged paths of both domains of SPA on PS and vice versa could be set equal without a significant loss of model fit. The resulting associations indicate a significant bidirectional relationship between both domains of SPA and PS. Discussion and conclusion: This study provides initial evidence that SPA can influence trajectories of cognitive decline and vice versa. The results emphasize the detrimental and beneficial effects that stereotypes can have on individuals and add further evidence to the theory of stereotype embodiment.
Human detection using image fusion of thermal and visible image with new joint bilateral filter

We propose a novel human detection system with thermal and visible image sensors using a new joint bilateral filter. There is a limitation to the performance of devices which attempt to detect humans by using only one sensor. Therefore, we use two sensors: an infrared sensor and a color image sensor. To fuse the best features of both types of sensor in order to achieve superior performance in human detection, we use low-level image fusion. To carry out this image fusion process, we propose a new joint bilateral filter which is useful for fusion of the edge information in the visible image and the white region in the thermal image. This image fusion process effectively removes the regions of human shadow which is trouble of background subtraction. To achieve this effect, results from different pairs of fused images that are taken sequentially are subtracted to detect the human effectively. Experimental results show that effective and easy human detection can be achieved by the proposed algorithm.
Half-integrality, LP-branching, and FPT Algorithms

A recent trend in parameterized algorithms is the application of polytope tools (specifically, LP-branching) to FPT algorithms (e.g., Cygan et al., 2011; Narayanaswamy et al., 2012). Though the list of work in this direction is short, the results are already interesting, yielding significant speedups for a range of important problems. However, the existing approaches require the underlying polytope to have very restrictive properties, including half-integrality and Nemhauser-Trotter-style persistence properties. To date, these properties are essentially known to hold only for two classes of polytopes, covering the cases of Vertex Cover (Nemhauser and Trotter, 1975) and Node Multiway Cut (Garg et al., 1994). Taking a slightly different approach, we view half-integrality as a discrete relaxation of a problem, e.g., a relaxation of the search space from {0, 1}V to {0, 1/2, 1}V such that the new problem admits a polynomial-time exact solution. Using tools from CSP (in particular Thapper and Zivný, 2012) to study the existence of such relaxations, we are able to provide a much broader class of half-integral polytopes with the required properties. Our results unify and significantly extend the previously known cases. In addition to the new insight into problems with half-integral relaxations, our results yield a range of new and improved FPT algorithms, including an O*(|Σ|2k)-time algorithm for node-deletion Unique Label Cover with label set Σ (improving the previous bound of O*(|Σ|O(k2 log k) due to Chitnis et al., 2012) and an O*(4k)-time algorithm for Group Feedback Vertex Set, including the setting where the group is only given by oracle access (improving on the previous bound of O*(2O(k log k)) due to Cygan et al., 2012). The latter bound is optimal under the Exponential Time Hypothesis. The latter result also implies the first single-exponential time FPT algorithm for Subset Feedback Vertex Set, answering an open question of Cygan et al. (2012). Interestingly, despite the half-integrality, our result do not imply any approximation results (as may be expected, given the Unique Games-hardness of the covered problems).
Linear discriminant analysis based on Zp-norm maximization

In this paper, linear discriminant analysis (LDA) based on Lp-norm (LDA-Lp) optimization method is proposed. The objective function utilizing the Lp-norm with arbitrary p value is studied. By maximizing the Lp-norm-based ratio between the between-class scatter and the within-class scatter, LDA-Lp can construct a set of local optimal projection vectors. Moreover, the optimal projection vectors can be obtained by the gradient ascent method. Experimental results on the two synthetic and fourteen benchmark datasets demonstrate that the better performance of LDA-Lp can be achieved by choosing the optimal value of p.
Isoform-Specific Toxicity of Mecp2 in Postmitotic Neurons: Suppression of Neurotoxicity by FoxG1

The methyl-CpG binding protein 2 (MeCP2) is a widely expressed protein, the mutations of which cause Rett syndrome. The level of MeCP2 is highest in the brain where it is expressed selectively in mature neurons. Its functions in postmitotic neurons are not known. The MeCP2 gene is alternatively spliced to generate two proteins with different N termini, designated as MeCP2-e1 and MeCP2-e2. The physiological significance of these two isoforms has not been elucidated, and it is generally assumed they are functionally equivalent. We report that in cultured cerebellar granule neurons induced to die by low potassium treatment and in Aβ-treated cortical neurons, Mecp2-e2 expression is upregulated whereas expression of the Mecp2-e1 isoform is downregulated. Knockdown of Mecp2-e2 protects neurons from death, whereas knockdown of the e1 isoform has no effect. Forced expression of MeCP2-e2, but not MeCP2-e1, promotes apoptosis in otherwise healthy neurons. We find that MeCP2-e2 interacts with the forkhead protein FoxG1, mutations of which also cause Rett syndrome. FoxG1 has been shown to promote neuronal survival and its downregulation leads to neuronal death. We find that elevated FoxG1 expression inhibits MeCP2-e2 neurotoxicity. MeCP2-e2 neurotoxicity is also inhibited by IGF-1, which prevents the neuronal death-associated downregulation of FoxG1 expression, and by Akt, the activation of which is necessary for FoxG1-mediated neuroprotection. Finally, MeCP2-e2 neurotoxicity is enhanced if FoxG1 expression is suppressed or in neurons cultured from FoxG1-haplodeficient mice. Our results indicate that Mecp2-e2 promotes neuronal death and that this activity is normally inhibited by FoxG1. Reduced FoxG1expression frees MecP2-e2 to promote neuronal death.
Refactoring Erlang programs

This paper presents the model, the design principles and the prototype of a refactoring toolset for Erlang programs. With this toolset one can incrementally carry out programmer-guided meaning-preserving program transformations. Erlang is a mostly dynamically typed language, and many of its semantical rules are also dynamic. Therefore the main challenge in this research is to ensure the safety of (the statically performed) refactoring steps. The paper analyses the language constructs of Erlang with respect to refactoring. A novelty of the presented approach is that programs are represented, stored and manipulated in a relational database. This feature makes it possible to express refactoring steps in a fairly compact and comprehensible way. The proposed software development environment with the integrated refactoring tool provides multiple editing modes. These editing modes support changes ranging from fully controlled (allowing only meaning-preserving transformations) to uncontrolled (editing program text freely). Transformations are performed more safely and efficiently in an editing mode with higher control.
Development of a low-cost ultra-tiny line laser range sensor

To enable robotic sensing for tasks with requirements on weight, size, and cost, we develop an ultra-tiny line laser range sensor based on the Time-of-Flight (TOF) principle. With delicate circuit design and optical attachments, we create a sensor as small as 35[mm] × 27[mm] × 30[mm] and as light as 20[g]. The line sensor samples 272 pixels (256 effective pixels) uniformly distributed within the measurement field of view customizable using different laser lenses. The optimal measurement range of the sensor is 0.05[m] ~ 2[m]. Higher sampling rates can be achieved with a shorter range. The sensor can also extend its range to 3[m] with reduced accuracy. We model the overall errors of the sensor and formulate calibration methods, achieving repeatable accuracy and measurement bias both within 2[cm] with our tested ambient lighting conditions and measurement ranges. The sensor is applicable to range sensing tasks including humanoid hand-eye measurement, UAV safe landing, tiny robot range sensing, and object detection.
Dopamine D 2 Receptor-Mediated Regulation of Pancreatic b Cell Mass

Cell Mass Author(s) Sakano, Daisuke; Choi, Sungik; Kataoka, Masateru; Shiraki, Nobuaki; Uesugi, Motonari; Kume, Kazuhiko; Kume, Shoen Citation Stem cell reports (2016), 7(1): 95-109 Issue Date 2016-07-12 URL http://hdl.handle. net/2433/216336 Right © 2016 The Author(s). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Type Journal Article Textversion publisher
Hybrid active contours in multiphase level set framework for images segmentation

A major problem with image segmentation is the building of model that is able to deal with all kind of image. This is due to the diversity of the image sources. However, the aim is to widen, as much as possible, the capability of the model to segment several image modalities. Hybridization between some models seems a good alternative to achieve that. In this paper, functional that incorporate several kinds of image information is used: edge detector function, local means and variances, and global means. Such choice allows getting successful segmentation results as it will be shown in the experimental section.
On the performance of transceiver techniques for the K-user MIMO IFC with LTE-A turbo coding

The design of transceiver techniques for optimizing the performance of the K-user multiple-input multiple-output (MIMO) interference channel (IFC) is of great importance and has been the subject of many recent research papers. However, the vast majority of the existing comparative studies for the various techniques capitalizes on their ergodic sum-rate performance and does not quantify their achievable performance with practical error correction coding. In this paper we investigate the achievable performance of different transceiver techniques for the K-user MIMO IFC with the long term evolution advanced (LTE-A) turbo coding scheme. Techniques achieving interference alignment (IA) at the interference-limited regime as well as a technique that reconfigures to the interference conditions are considered. It is shown that, for most of the tested 3-user MIMO IFCs where each transmitter may send more than one data streams, the iterative transceiver techniques result in superior achievable spectral efficiency than conventional IA.
Adaptive granularity memory systems: A tradeoff between storage efficiency and throughput

We propose adaptive granularity to combine the best of fine-grained and coarse-grained memory accesses. We augment virtual memory to allow each page to specify its preferred granularity of access based on spatial locality and error-tolerance tradeoffs. We use sector caches and sub-ranked memory systems to implement adaptive granularity. We also show how to incorporate adaptive granularity into memory access scheduling. We evaluate our architecture with and without ECC using memory intensive benchmarks from the SPEC, Olden, PARSEC, SPLASH2, and HPCS benchmark suites and micro-benchmarks. The evaluation shows that performance is improved by 61% without ECC and 44% with ECC in memory-intensive applications, while the reduction in memory power consumption (29% without ECC and 14% with ECC) and traffic (78% without ECC and 66% with ECC) is significant.
Using interactive domain overviews to develop deep understanding in a complex reasoning task

Representations in the form of concept maps have been shown to be a benefit to leaners. However, previous research examined the influence of these representations in learning in well-structured environments. Additionally, previous research suggests that increasing the activity of students in learning environments has also been shown to yield gains in learning, called the generation effect. The current study extends the literature by examining the influence generative activities and concept map representations have on an ill-structured reasoning process, namely “thinking like a lawyer. ” Preand posttests targeting factual knowledge, recall, and transfer were used to assess learning, while verbal protocols were implemented to examine learning processes used by participants. Results were mixed. Representation and activity had no effect on factual knowledge, recall, and near transfer measures. Verbal protocol results showed that students who studied with the concept map representation condition produced a higher proportion of deep utterances during problem solving when using static representations compared to those that generated their representation. The opposite was true for students in the text list condition. Those who generated their text list representation during study produced a higher proportion of deep utterances in problem solving when compared to those who studied with a static list. Thus, a careful consideration of topical materials and learning environments is necessary to determine whether or not concept maps and generation effects will encourage deeper comprehension in learners.
Memory Updating and Mental Arithmetic

Is domain-general memory updating ability predictive of calculation skills or are such skills better predicted by the capacity for updating specifically numerical information? Here, we used multidigit mental multiplication (MMM) as a measure for calculating skill as this operation requires the accurate maintenance and updating of information in addition to skills needed for arithmetic more generally. In Experiment 1, we found that only individual differences with regard to a task updating numerical information following addition (MUcalc) could predict the performance of MMM, perhaps owing to common elements between the task and MMM. In Experiment 2, new updating tasks were designed to clarify this: a spatial updating task with no numbers, a numerical task with no calculation, and a word task. The results showed that both MUcalc and the spatial task were able to predict the performance of MMM but only with the more difficult problems, while other updating tasks did not predict performance. It is concluded that relevant processes involved in updating the contents of working memory support mental arithmetic in adults.
Dynamin-Related Protein-1 Controls Fusion Pore Dynamics During Platelet Granule Exocytosis

Objective—Platelet granule exocytosis serves a central role in hemostasis and thrombosis. Recently, single-cell amperometry has shown that platelet membrane fusion during granule exocytosis results in the formation of a fusion pore that subsequently expands to enable the extrusion of granule contents. However, the molecular mechanisms that control platelet fusion pore expansion and collapse are not known. Methods and Results—We identified dynamin-related protein-1 (Drp1) in platelets and found that an inhibitor of Drp1, mdivi-1, blocked exocytosis of both platelet dense and &agr;-granules. We used single-cell amperometry to monitor serotonin release from individual dense granules and, thereby, measured the effect of Drp1 inhibition on fusion pore dynamics. Inhibition of Drp1 increased spike width and decreased prespike foot events, indicating that Drp1 influences fusion pore formation and expansion. Platelet-mediated thrombus formation in vivo after laser-induced injury of mouse cremaster arterioles was impaired after infusion of mdivi-1. Conclusion—These results demonstrate that inhibition of Drp1 disrupts platelet fusion pore dynamics and indicate that Drp1 can be targeted to control thrombus formation in vivo.
Inactivation of DNA-Binding Response Regulator Sak189 Abrogates β-Antigen Expression and Affects Virulence of Streptococcus agalactiae

Background Streptococcus agalactiae is able to colonize numerous tissues employing different mechanisms of gene regulation, particularly via two-component regulatory systems. These systems sense the environmental stimuli and regulate expression of the genes including virulence genes. Recently, the novel two-component regulatory system Sak188/Sak189 was identified. In S. agalactiae genome, it was adjacent to the bac gene encoding for β-antigen, an important virulence factor. Methodology/Principal Findings In this study, the sak188 and sak189 genes were inactivated, and the functional role of Sak188/Sak189 two-component system in regulation of the β-antigen expression was investigated. It was demonstrated that both transcription of bac gene and expression of encoded β-antigen were controlled by Sak189 response regulator, but not Sak188 histidine kinase. It was also found that the regulation occurred at transcriptional level. Finally, insertional inactivation of sak189 gene, but not sak188 gene, significantly affected virulent properties of S. agalactiae. Conclusions/Significance Sak189 response regulator is necessary for activation of bac gene transcription. It also controls the virulent properties of S. agalactiae. Given that the primary functional role of Sak188/Sak189 two-component systems is a control of bac gene transcription, this system can be annotated as BgrR/S (bac gene regulatory system).
1 Data Modeling and Functional Modeling – Which Comes First ?

In the analysis phase of the information system development (ISD), the users' requirements are studied and defined. In most ISD methodologies, the requirements are defined by two models: a conceptual data model in form of e.g. an entity-relationship (ER) diagram or a class diagram; and a functional model in form of e.g. data flow diagrams (DFD) or use cases. Different ISD methodologies prescribe different orders of carrying out these modeling activities but there is no commonly agreed order for performing them. In order to find out whether the order of analysis activities makes any difference, and which order leads to better results, we have conducted two independent comparative experiments in laboratory settings. The subjects in the two experiments were asked to create data models and functional models of a certain system while working in the two opposite orders. In each experiment we used a different ISD methodology and different subjects, but assigned the same modeling tasks. The main results of the experiments are that the data models are of better quality when created as the first modeling task, and that analysts prefer to first create the data model and then the functional model. The results of the two experiments have been reported in Shoval & Kabeli (2005) and in Shoval et al. (2009). This paper provides an overview of the two studies.
Summary a ) Finding and evaluating community structure in networks

In an age of social media, source control management is evolving to take on a more collaborative flair. Communities like GitHub, SourceForge, BitBucket and Redmine are all examples of online communities centered around collaborative coding. These systems typically include expected features such as version control, branching, and merging, and also incorporate social media features such as commenting, followers and groups. We want to explore the nature of communities and collaboration in one of the largest and most popular websites, GitHub, to see if it has lived up to its promise of ”social coding”.
Vegetation Productivity in Natural vs. Cultivated Systems along Water Availability Gradients in the Dry Subtropics

The dry subtropics are subject to a rapid expansion of crops and pastures over vast areas of natural woodlands and savannas. In this paper, we explored the effect of this transformation on vegetation productivity (magnitude, and seasonal and long-term variability) along aridity gradients which span from semiarid to subhumid conditions, considering exclusively those areas with summer rains (>66%). Vegetation productivity was characterized with the proxy metric “Enhanced Vegetation Index” (EVI) (2000 to 2012 period), on 6186 natural and cultivated sampling points on five continents, and combined with a global climatology database by means of additive models for quantile regressions. Globally and regionally, cultivation amplified the seasonal and inter-annual variability of EVI without affecting its magnitude. Natural and cultivated systems maintained a similar and continuous increase of EVI with increasing water availability, yet achieved through contrasting ways. In natural systems, the productivity peak and the growing season length displayed concurrent steady increases with water availability, while in cultivated systems the productivity peak increased from semiarid to dry-subhumid conditions, and stabilized thereafter giving place to an increase in the growing season length towards wetter conditions. Our results help to understand and predict the ecological impacts of deforestation on vegetation productivity, a key ecosystem process linked to a broad range of services.
SEÇMECE : Optimizing Lifetime of Federated Sensor Networks by Exploiting Data and Model Redundancy

Next generation sensor network deployments are foreseen to be large infrastructures, with multiple concurrent tasks running on the same set of hardware. Applications will need standardized methods to access and integrate data from such heterogeneous sensor networks. Hence, a Federated Sensor Network (FSN) model can significantly simplify the development of multi-network applications by presenting a unified system view, hiding the heterogeneity, and performing optimizations. The optimizations are possible due to redundancies in the system. First, a given task can be accomplished by multiple alternative ways (i.e. models), each of which incorporates different types of sources (model redundancy). Second, sensor readings about the same physical phenomenon at some well-defined spatial locations are correlated (spatial data redundancy), and third, sensor observations do not lose their utility immediately but only over time (temporal data redundancy). Seçmece optimizer makes use of these redundancies to select which models to run, using which sources at which rate, aiming to achieve the required quality with the minimum cost. We first show that even this optimization problem is strongly NP-Hard, and then extend the problem to maximize the system lifetime, the time the system can continue answering the given queries with enough quality. Finally, we study our solution approaches, and possible modifications, to demonstrate performance gains in both real world scenarios and random generated setups.