Miracle-dz/UniFAR-FTUs huggingface dataset:
In silico two‐hybrid system for the selection of physically interacting protein pairs

Deciphering the interaction links between proteins has become one of the main tasks of experimental and bioinformatic methodologies. Reconstruction of complex networks of interactions in simple cellular systems by integrating predicted interaction networks with available experimental data is becoming one of the most demanding needs in the postgenomic era. On the basis of the study of correlated mutations in multiple sequence alignments, we propose a new method (in silico two‐hybrid, i2h) that directly addresses the detection of physically interacting protein pairs and identifies the most likely sequence regions involved in the interactions. We have applied the system to several test sets, showing that it can discriminate between true and false interactions in a significant number of cases. We have also analyzed a large collection of E. coli protein pairs as a first step toward the virtual reconstruction of its complete interaction network. Proteins 2002;47:219–227. © 2002 Wiley‐Liss, Inc.
Versatile biocompatible polymer hydrogels: scaffolds for cell growth.

A three-dimensional, biocompatible hydrogel (see picture) was generated by combining two cationic polymers, chitosan and poly(ethylenimine). The hydrogels were stable under cell-culture conditions and facilitated cell proliferation, yet prevented dedifferentiation of primary human skeletal cells into fibroblasts. A variety of materials such as DNA, proteins, and peptides can be stably incorporated into the gel network
The neural basis of monitoring goal progress

The neural basis of progress monitoring has received relatively little attention compared to other sub-processes that are involved in goal directed behavior such as motor control and response inhibition. Studies of error-monitoring have identified the dorsal anterior cingulate cortex (dACC) as a structure that is sensitive to conflict detection, and triggers corrective action. However, monitoring goal progress involves monitoring correct as well as erroneous events over a period of time. In the present research, 20 healthy participants underwent functional magnetic resonance imagining (fMRI) while playing a game that involved monitoring progress toward either a numerical or a visuo-spatial target. The findings confirmed the role of the dACC in detecting situations in which the current state may conflict with the desired state, but also revealed activations in the frontal and parietal regions, pointing to the involvement of processes such as attention and working memory (WM) in monitoring progress over time. In addition, activation of the cuneus was associated with monitoring progress toward a specific target presented in the visual modality. This is the first time that activation in this region has been linked to higher-order processing of goal-relevant information, rather than low-level anticipation of visual stimuli. Taken together, these findings identify the neural substrates involved in monitoring progress over time, and how these extend beyond activations observed in conflict and error monitoring.
The synergism of MCL1 and glycolysis on pediatric acute lymphoblastic leukemia cell survival and prednisolone resistance

In vitro and in vivo resistance to prednisolone are predictive for an adverse prognosis in pediatric precursor B-acute lymphoblastic leukemia. Causes of resistance are still poorly understood. In this study, we observed that prednisolone exposure of prednisolone-sensitive patients’ leukemic cells decreased anti-apoptotic MCL1 protein levels by 2.9-fold, while MCL1 protein expression in prednisolone-resistant leukemic patients’ cells was unaffected (P<0.01). Locked nucleic acid oligonucleotides directed against MCL1 reduced MCL1 protein levels by 82±16% (P<0.05) in leukemic cells, decreased proliferation by 9-fold and sensitized to prednisolone up to 80.8-fold, compared to a non-silencing-control locked nucleic acid (P<0.05). Remarkably, we discovered that MCL1-silencing up-regulated the glucose consumption of leukemic cells by 2.5-fold (P<0.05), suggesting a potential rescue mechanism mediated by glycolysis. Targeting glycolysis by 2-deoxyglucose synergistically inhibited leukemic survival by 23.2-fold in MCL1-silenced cells (P<0.05). Moreover, 2-deoxyglucose and MCL1 locked nucleic acid concomitantly sensitized leukemic cells to prednisolone compared to MCL1 locked nucleic acid or 2-deoxyglucose alone (P<0.05). In conclusion, these results indicate the need to target both MCL1 and glycolysis simultaneously to inhibit leukemic survival and sensitize acute leukemia patients towards prednisolone.
Some constraints on positive entropy automorphisms of smooth threefolds

Suppose that $X$ is a smooth, projective threefold over $\mathbb C$ and that $\phi : X \to X$ is an automorphism of positive entropy. We show that one of the following must hold, after replacing $\phi$ by an iterate: i) the canonical class of $X$ is numerically trivial; ii) $\phi$ is imprimitive; iii) $\phi$ is not dynamically minimal. As a consequence, we show that if a smooth threefold $M$ does not admit a primitive automorphism of positive entropy, then no variety constructed by a sequence of smooth blow-ups of $M$ can admit a primitive automorphism of positive entropy. In explaining why the method does not apply to threefolds with terminal singularities, we exhibit a non-uniruled, terminal threefold $X$ with infinitely many $K_X$-negative extremal rays on $NE(X)$.
Personalisation in a System Combining Pervasiveness and Social Networking

One of the key objectives of a pervasive computing system is to provide appropriate support to enable the user to manage the increasingly complex environment surrounding her. This includes managing the ever-increasing number of devices which can be accessed wirelessly as well as the vast range of services at her disposal. The aim of the Persist project was to develop a pervasive system that would bridge the gap between fixed smart spaces (e.g. smart homes) and systems created for mobile users. Using the concept of Personal Smart Spaces the Persist project has built a prototype system to demonstrate some of the capabilities that this can provide. The Societies project is currently building on these ideas to develop a new type of system that combines pervasive with social networking functionality. Personalisation is an essential feature of any pervasive system and plays a key role in the prototype implemented in Persist. This will also play a key role in the new platform being developed in the Societies project. This paper describes how personalisation is handled within the Persist system and some ideas for the new platform.
Distance Estimation for Very Large Networks using MapReduce and Network Structure Indices

Distance calculation is key to many network mining applications such as centrality and clustering. As the size of available networks increases to millions of nodes and edges, distance calculation becomes a bottleneck for such applications. One way to overcome such bottlenecks is to use the MapReduce parallel processing framework, though increasing resources linearly does not scale well for many network mining applications. Hence, instead of calculating the exact distance, efficiently and accurately estimating distance may scale better for very large networks. In this paper, we propose a network structure index(NSI) on the MapReduce framework by extending the basic breadth-first search algorithm to accurately estimate shortest distance using MapReduce. We demonstrate the accuracy of our method for distance estimation on synthetic and real networks. We use distance estimation along with progressive sampling to achieve two specific applications for very large networks: closeness centrality and betweenness centrality. We first evaluate our distance estimation method on relatively small networks, then we report our observations about the most central nodes of a Twitter network with more than 40 million nodes.
Age, dyslexia subtype and comorbidity modulate rapid auditory processing in developmental dyslexia

The nature of Rapid Auditory Processing (RAP) deficits in dyslexia remains debated, together with the specificity of the problem to certain types of stimuli and/or restricted subgroups of individuals. Following the hypothesis that the heterogeneity of the dyslexic population may have led to contrasting results, the aim of the study was to define the effect of age, dyslexia subtype and comorbidity on the discrimination and reproduction of non-verbal tone sequences. Participants were 46 children aged 8–14 (26 with dyslexia, subdivided according to age, presence of a previous language delay, and type of dyslexia). Experimental tasks were a Temporal Order Judgment (TOJ) (manipulating tone length, ISI and sequence length), and a Pattern Discrimination Task. Dyslexic children showed general RAP deficits. Tone length and ISI influenced dyslexic and control children's performance in a similar way, but dyslexic children were more affected by an increase from 2 to 5 sounds. As to age, older dyslexic children's difficulty in reproducing sequences of 4 and 5 tones was similar to that of normally reading younger (but not older) children. In the analysis of subgroup profiles, the crucial variable appears to be the advantage, or lack thereof, in processing long vs. short sounds. Dyslexic children with a previous language delay obtained the lowest scores in RAP measures, but they performed worse with shorter stimuli, similar to control children, while dyslexic-only children showed no advantage for longer stimuli. As to dyslexia subtype, only surface dyslexics improved their performance with longer stimuli, while phonological dyslexics did not. Differential scores for short vs. long tones and for long vs. short ISIs predict non-word and word reading, respectively, and the former correlate with phonemic awareness. In conclusion, the relationship between non-verbal RAP, phonemic skills and reading abilities appears to be characterized by complex interactions with subgroup characteristics.
Gaussian Process Time Series Model for Life Prognosis of Metallic Structures

Al 2024-T351 fatigue specimens have been modeled using a kernel-based multi-variate Gaussian Process approach. The Gaussian Process model projects fatigue affecting input variables to output crack growth by probabilistically inferring the underlying nonlinear relationship between input and output. The Gaussian Process approach not only explicitly models the uncertainty due to scatter in material microstructure parameter but it also implicitly models the loading sequence effect due to variable loading. The loading sequence effect is modeled through the Gaussian Process optimal hyperparameters by using the crack length data observed over the entire domain of spectrum loading. The performance in the crack growth prediction is evaluated for two covariance functions, a radial basis-based, anisotropic, covariance function and a neural network-based isotropic covariance function. Furthermore, the performance of different types of scaling, used to scale the input—output data space, is tested. It is found that for the radial basis-based anisotropic covariance function with normalized scaling, the prediction error is consistently lower compared to other combinations. In addition, the Gaussian Process model allows determination of the collapse load condition, which is a desirable feature for the online health monitoring and prognosis.
Towards an intelligent robotic walker for assisted living using multimodal sensorial data

We aim at developing an intelligent robotic platform that provides cognitive assistance and natural support in indoor environments to the elderly society and to individuals with moderate to mild walking impairment. Towards this end, we process data from audiovisual sensors and laser range scanners, acquired in experiments with patients in real life scenarios. We present the main concepts of an automatic system for user intent and action recognition that will integrate multiple modalities. We demonstrate promising preliminary results, firstly on action recognition based on the visual modality, i.e. color and depth cues, and secondly on the detection of gait cycle patterns that exploit the laser range data. For action recognition we are based on local interest points, 3D Gabor filters and dominant energy analysis, feeding a support vector machine. Then the recognized actions can trigger the gait cycle detection that detect walking patterns by exploiting the laser range data, modeled by hidden Markov models. In this way, we shall acquire the overall patient's state and the robot shall autonomously reason on how to provide support.
EARLY BUD-BREAK 1 (EBB1) is a regulator of release from seasonal dormancy in poplar trees

Significance Timing of vegetative bud dormancy is an environmentally and economically important trait whose importance will grow due to rapid climate changes. However, the underpinning regulatory mechanisms are still poorly understood. We report the identification and characterization of the Early Bud-Break 1 (EBB1) gene in poplar that regulates the timing of bud-break. EBB1 plays a major and integrative role in the reactivation of the shoot apical meristem after winter dormancy. The knowledge about EBB1 function can enable novel approaches for population management, molecular breeding, and genetic engineering of dormancy-associated traits. Trees from temperate latitudes transition between growth and dormancy to survive dehydration and freezing stress during winter months. We used activation tagging to isolate a dominant mutation affecting release from dormancy and identified the corresponding gene EARLY BUD-BREAK 1 (EBB1). We demonstrate through positioning of the tag, expression analysis, and retransformation experiments that EBB1 encodes a putative APETALA2/Ethylene responsive factor transcription factor. Transgenic up-regulation of the gene caused early bud-flush, whereas down-regulation delayed bud-break. Native EBB1 expression was highest in actively growing apices, undetectable during the dormancy period, but rapidly increased before bud-break. The EBB1 transcript was localized in the L1/L2 layers of the shoot meristem and leaf primordia. EBB1-overexpressing transgenic plants displayed enlarged shoot meristems, open and poorly differentiated buds, and a higher rate of cell division in the apex. Transcriptome analyses of the EBB1 transgenics identified 971 differentially expressed genes whose expression correlated with the EBB1 expression changes in the transgenic plants. Promoter analysis among the differentially expressed genes for the presence of a canonical EBB1-binding site identified 65 putative target genes, indicative of a broad regulatory context of EBB1 function. Our results suggest that EBB1 has a major and integrative role in reactivation of meristem activity after winter dormancy.
Social media analysis for Indonesian language: case study flood in Jakarta

Social media had become worldwide phenomena. More than 80% of Internet's users are social media's users. When a disaster occurred, information needs will rise. Twitter is one of popular information resource especially in Indonesia. Because of that, twitter's information extraction system was needed. This research proposes a system that can detect topic in social media twitter by representing its content as a complex network graph using the implementation of natural language processing, graph concept, and complex network analysis. This system consists of 3 subsystems which are crawler, graph converter, and application for graph visualization. From testing result, we reach 89% success rate of keyword extraction using RIDF term weighting method and collecting messages by certain category. General topic about governor election and 13 subtopics was successfully extracted from set data flood in Jakarta.
Negotiation Support Systems and Software Agents in E-Business Negotiations

Experiments with negotiation software agents’ in frictionless commerce indicate potential for destructive behaviour. Most of the agents are capable of engaging in auctions and have no ability to conduct complex business negotiations. Recognizing that people and software agents operate in different although overlapping spheres we propose an environment in which negotiation and decision support systems work together with software agents in electronic negotiations. Based on our experiences with the Inspire system we constructed an environment comprising software agents, and negotiation and decision support systems. One agent monitors the process, facilitates the use of Inspire, interprets the negotiators’ activities and provides methodological advice. The architecture of this environment is based on the separation of user support functions from the autonomous software activities, separation of the support for individuals from facilitation and mediation; and scalability and the ability to provide linkages with the existing software.
Level influence of spatial pyramid matching in object classification

In this paper we propose to effectively consider the shape and size variations for object classification. Specifically, a novel image matching method is proposed to incorporate the image segmentation with Spatial Pyramid Matching (SPM), and test our method on flower classification. A Level Influence Factor (LIF) is introduced to represent weights of different pyramid levels based on the statistical information of each segmented image. Then the images are classified based on the LIF weighted spatial pyramid bag-of-visual-words feature, and some levels with weight values zeros are not needed to be compared further. Also, in SPM matching stage, the block in one image is compared with not only its corresponding block in another image, but also the spatially neighboring blocks of the corresponding blocks to find the best match. This fuzzy matching method can incorporate some translation of objects. Experiments are performed on a flower dataset containing 1360 images from 17 different categories. And experimental results demonstrate that our proposed method has better time efficiency than traditional SPM and outperforms the state-of-art flower classification methods.
Neural Integration of Risk and Effort Costs by the Frontal Pole: Only upon Request

Rewards in real life are rarely received without incurring costs and successful reward harvesting often involves weighing and minimizing different types of costs. In the natural environment, such costs often include the physical effort required to obtain rewards and potential risks attached to them. Costs may also include potential risks. In this study, we applied fMRI to explore the neural coding of physical effort costs as opposed to costs associated with risky rewards. Using an incentive-compatible valuation mechanism, we separately measured the subjective costs associated with effortful and risky options. As expected, subjective costs of options increased with both increasing effort and increasing risk. Despite the similar nature of behavioral discounting of effort and risk, distinct regions of the brain coded these two cost types separately, with anterior insula primarily processing risk costs and midcingulate and supplementary motor area (SMA) processing effort costs. To investigate integration of the two cost types, we also presented participants with options that combined effortful and risky elements. We found that the frontal pole integrates effort and risk costs through functional coupling with the SMA and insula. The degree to which the latter two regions influenced frontal pole activity correlated with participant-specific behavioral sensitivity to effort and risk costs. These data support the notion that, although physical effort costs may appear to be behaviorally similar to other types of costs, such as risk, they are treated separately at the neural level and are integrated only if there is a need to do so.
On testing the equality of sofic systems

In this paper we study three classes of finite automata satisfying the properties that every biinfinite word is the label of at most one, at least one and exactly one bi-infinite path. In particular, we investigate the algorithmic complexity of testing if a given finite automaton has one of these properties. Also, when restricted to the first class above, we give a polynomial time algorithm deciding whether for two automata, the languages of bi-infinite words obtained as labels of bi-infinite paths are equal. In terms of sofic systems, the result provides a polynomial time algorithm to test the equality of two subshifts of finite type, given their representations as local automata.
A new image correction method for live cell atomic force microscopy

During live cell imaging via atomic force microscopy (AFM), the interactions between the AFM probe and the membrane yield distorted cell images. In this work, an image correction method was developed based on the force–distance curve and the modified Hertzian model. The normal loading and lateral forces exerted on the cell membrane by the AFM tip were both accounted for during the scanning. Two assumptions were made in modelling based on the experimental measurements: (1) the lateral force on the endothelial cells was linear to the height; (2) the cell membrane Young's modulus could be derived from the displacement measurement of a normal force curve. Results have shown that the model could be used to recover up to 30% of the actual cell height depending on the loading force. The accuracy of the model was also investigated with respect to the loading force and mechanical property of the cell membrane.
Fair Procedures: Evidence from Games Involving Lotteries

Procedural fairness plays a prominent role in the social discourse concerning the marketplace in particular, and social institutions in general. Random procedures are a simple case, and they have found application in several important social allocation decisions. We investigate random procedures in the laboratory. We find that an unbiased random procedure is an acceptable substitute for an unbiased allocation: similar patterns of acceptance and rejection result when either is inserted as a feasible proposal in a sequential battle-of-the-sexes. We also find that unbiasedness, known to be a crucial characteristic of allocation fairness, is important to procedural fairness: in the context of a random offer game, a biased outcome is more readily accepted when chosen by an unbiased random draw than by one that is biased. Procedural fairness is conceptually different than allocation fairness or attribution-based behavior, and none of the current models of fairness and reciprocity captures our results. Post hoc extension of one of these models (ERC) suggests that a deeper understanding of procedural fairness requires further investigation of competing fairness norms.
Interacting noise sources shape patterns of arm movement 6 variability in 3 D space

8 Authors: 9 Gregory A. Apker, Timothy K. Darling, Christopher A. Buneo 10 11 School of Biological and Health Systems Engineering 12 Arizona State University 13 P.O. Box 879709 14 Tempe, AZ 85287-9709 15 USA 16 17 Running Head: Sources of reaching variability 18 19 Corresponding Author: C. A. Buneo, School of Biological and Health Systems Engineering, 20 Arizona State University, P.O. Box 879709, Tempe, AZ 85287-9709, U.S.A. E-mail: 21 cbuneo@asu.edu 22 23 24 25 26 27 Articles in PresS. J Neurophysiol (September 15, 2010). doi:10.1152/jn.00590. 2010