Miracle-dz/UniFAR-FTUs huggingface dataset:
Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation

Gene expression profiles can be used to infer previously unknown transcriptional regulatory interaction among thousands of genes, via systems biology ‘reverse engineering’ approaches. We ‘reverse engineered’ an embryonic stem (ES)-specific transcriptional network from 171 gene expression profiles, measured in ES cells, to identify master regulators of gene expression (‘hubs’). We discovered that E130012A19Rik (E13), highly expressed in mouse ES cells as compared with differentiated cells, was a central ‘hub’ of the network. We demonstrated that E13 is a protein-coding gene implicated in regulating the commitment towards the different neuronal subtypes and glia cells. The overexpression and knock-down of E13 in ES cell lines, undergoing differentiation into neurons and glia cells, caused a strong up-regulation of the glutamatergic neurons marker Vglut2 and a strong down-regulation of the GABAergic neurons marker GAD65 and of the radial glia marker Blbp. We confirmed E13 expression in the cerebral cortex of adult mice and during development. By immuno-based affinity purification, we characterized protein partners of E13, involved in the Polycomb complex. Our results suggest a role of E13 in regulating the division between glutamatergic projection neurons and GABAergic interneurons and glia cells possibly by epigenetic-mediated transcriptional regulation.
Wireless Camera Nodes on a Cyber-Physical System

This paper describes the configuration of a networked control system with multiple distributed cameras as edge nodes of a cyber-physical system. The proposed architecture deploys multiple distributed on computer vision edge nodes capturing the motion of mobile robots to interact with people on the environment. The camera nodes, network devices and mobile robots are considered part of the same control loop. Our approach provides a flexible scalable architecture that balances accuracy and reliability of the cyber-physical system, taking advantage of video processing on intermediate networked nodes and providing new functions and capabilities with minor changes. Main contribution of this paper is to configure the computer vision nodes considering the networked control loop with an adjustable sampling period to achieve the desired performance controlling the trajectory of multiple robots. Different tests have been done on a smart space as an end application framework.
Similarity Shape Based on Skeleton Graph Matching

Using graphs to match two feature sets through embedded high-order relations points has many possible applications in criminal justice, security, and high technology. In this paper, we analyze the method of using the random walk framework to establish correspondence between two skeleton graphs and ﬁnd out matching points be-tween two shapes. The graphs are matched using a skeleton graph with the descriptors of the relationship between the two edges of the end-nodes ranked on an association graph. Through adopting individual jumps with a reweighting scheme, the new proposed approach eﬀectively reﬂects the one-to-one matching constraints during the random walk process. Experiments on several benchmark data sets show that the proposed approach clearly out-performs existing algorithms, especially in the presence of noise and outliers.
Gestörter Wortabruf im kognitiven Modell und im Gehirn – eine Therapiestudie mit 3 Einzelfällen

In the present therapy study, we have for the first time combined cognitive and neural methods of examination in a model-oriented treatment setting for 3 subjects with aphasic word retrieval deficits. Based on a computer-assisted determination of the cognitive lesion in the Dell model, we applied lesion-specific and -unspecific therapies to compare their differential effectiveness. We used a picture/word interference fMRI-paradigm before and after therapy in order to assess therapy-induced changes in brain activation, the functioning of linguistic steps of processing and cognitive control, and the response to priming. As a result, all 3 subjects presented with a lexical-semantic lesion in the Dell model. In 2 subjects, the effectiveness of the lesion-specific semantic therapy was significantly stronger than that of the more unspecific phonological therapy. Due to therapy, brain activations were focused on language regions of the left or both hemispheres. Moreover, all patients recruited parts of the neural network that we had previously found in healthy speakers using the fMRI-paradigm (Abel et al., 2009, NeuroImage). A neural correlate of phonological processing was consistently located in the left superior temporal gyrus. In accordance with the cognitive lesion type, the neural correlate of semantic processing was less pronounced. Furthermore, we detected neural priming for phonological word distractors in all subjects and an additional decrease of cognitive control (monitoring) in 2 subjects. Over and above cognitive-linguistic observations, the individual pattern of brain activations therefore has the potential to indicate the type of disorder, the response to treatment techniques and the optimal therapy procedures.
Novel Covert Data Channel in Wireless Sensor Networks Using Compressive Sensing

Wireless sensor networks (WSN) is a novel data centered self-organizing network that can be used in acquiring and processing information. With the limited energy of sensor nodes and the increasing requirement of secure data transmission, how to save nodes energy as well as realize a transmission of sensitive information in WSN effectively is becoming an interesting research problem recently. In this paper, we present a novel scheme to transmit sensitive information in the pattern of energy efficient way by utilizing compressive sensing (CS) which is an emerging technology in recent years. In this method, sensor nodes need not to do complex computing but simple linear operations which can save the energy extensively, and thus extend the life time of the wireless sensor networks. Theory analysis and detail simulation results demonstrate the effective of our method, and the sensitive information can be accurately reconstructed even when the communication channel is lossy.
SUMOylation target sites at the C terminus protect Axin from ubiquitination and confer protein stability

Axin is a scaffold protein for the β‐catenin destruction complex, and a negative regulator of canonical Wnt signaling. Previous studies implicated the six C‐terminal amino acids (C6 motif) in the ability of Axin to activate c‐Jun N‐terminal kinase, and identified them as a SUMOylation target. Deletion of the C6 motif of mouse Axin in vivo reduced the steady‐state protein level, which caused embryonic lethality. Here, we report that this deletion (Axin‐AC6) causes a reduced half‐life in mouse embryonic fibroblasts and an increased susceptibility to ubiquitination in HEK 293T cells. We confirmed the C6 motif as a SUMOylation target in vitro, and found that mutating the C‐terminal SUMOylation target residues increased the susceptibility of Axin to polyubiquitination and reduced its steadystate level. Heterologous SUMOylation target sites could replace C6 in providing this protective effect. These findings suggest that SUMOylation of the C6 motif may prevent polyubiquitination, thus increasing the stability of Axin. Although C6 deletion also caused increased association of Axin with Dvl‐1, this interaction was not altered by mutating the lysine residues in C6, nor could heterologous SUMOylation motifs replace the C6 motif in this assay. Therefore, some other specific property of the C6 motif seems to reduce the interaction of Axin with Dvl‐1. — Kim, M. J., Chia, I. V. , Costantini, F. SUMOylation target sites at the C terminus protect Axin from ubiquitination and confer protein stability. FASEB J. 22, 3785–3794 (2008)
How to Declare Access Control Policies for XML Structured Information Objects using OASIS' eXtensible Access Control Markup Language (XACML)

Web Services, as the new building blocks of today's Internet provide the power to access distributed and heterogeneous information objects, which is the base for more advanced use like in electronic commerce. But, the access to these information objects is not always unrestricted. The owner of the information objects may control access due to different reasons. This paper introduces a novel approach for declaring information object related access restrictions, based on a valid XML encoding. The paper shows, how the access restrictions can be declared using XACML and Xpath. Based on the specified 'fine grained' policies, multiple policies can be applicable. If these policies declare positive and negative permissions for the same subject, policy inconsistencies exist. The paper also focuses on specifying the ground of policy inconsistencies and how to solve them.
Strategies of Islamist Extremism in Europe

Abstract This paper explains various strategies of contemporary Islamists extremism in Europe. The author identifies the most important variants of Islamist extremism and deals with their goals and with strategic approaches how to achieve these goals. Quasi-legalist strategies as well as violent forms of interest-empowerment are described. The author uses sources from various Islamist organizations and analyses these materials within the framework of modern insurgency. A comprehensive outlook and threat assessment of Islamist extremist strategies are included in this article.
A structural approach to the automatic adjudication of word sense disagreements

Abstract The semantic annotation of texts with senses from a computational lexicon is a complex and often subjective task. As a matter of fact, the fine granularity of the WordNet sense inventory [Fellbaum, Christiane (ed.). 1998. WordNet: An Electronic Lexical Database MIT Press], a de facto standard within the research community, is one of the main causes of a low inter-tagger agreement ranging between 70% and 80% and the disappointing performance of automated fine-grained disambiguation systems (around 65% state of the art in the Senseval-3 English all-words task). In order to improve the performance of both manual and automated sense taggers, either we change the sense inventory (e.g. adopting a new dictionary or clustering WordNet senses) or we aim at resolving the disagreements between annotators by dealing with the fineness of sense distinctions. The former approach is not viable in the short term, as wide-coverage resources are not publicly available and no large-scale reliable clustering of WordNet senses has been released to date. The latter approach requires the ability to distinguish between subtle or misleading sense distinctions. In this paper, we propose the use of structural semantic interconnections – a specific kind of lexical chains – for the adjudication of disagreed sense assignments to words in context. The approach relies on the exploitation of the lexicon structure as a support to smooth possible divergencies between sense annotators and foster coherent choices. We perform a twofold experimental evaluation of the approach applied to manual annotations from the SemCor corpus, and automatic annotations from the Senseval-3 English all-words competition. Both sets of experiments and results are entirely novel: structural adjudication allows to improve the state-of-the-art performance in all-words disambiguation by 3.3 points (achieving a 68.5% F1-score) and attains figures around 80% precision and 60% recall in the adjudication of disagreements from human annotators.
The Mre11 Complex Mediates the S-Phase Checkpoint through an Interaction with Replication Protein A

ABSTRACT The Mre11/Rad50/Nbs1 complex (MRN) plays an essential role in the S-phase checkpoint. Cells derived from patients with Nijmegen breakage syndrome and ataxia telangiectasia-like disorder undergo radioresistant DNA synthesis (RDS), failing to suppress DNA replication in response to ionizing radiation (IR). How MRN affects DNA replication to control the S-phase checkpoint, however, remains unclear. We demonstrate that MRN directly interacts with replication protein A (RPA) in unperturbed cells and that the interaction is regulated by cyclin-dependent kinases. We also show that this interaction is needed for MRN to correctly localize to replication centers. Abolishing the interaction of Mre11 with RPA leads to pronounced RDS without affecting phosphorylation of Nbs1 or SMC1 following IR. Moreover, MRN is recruited to sites at or adjacent to replication origins by RPA and acts there to inhibit new origin firing upon IR. These studies suggest a direct role of MRN at origin-proximal sites to control DNA replication initiation in response to DNA damage, thereby providing an important mechanism underlying the intra-S-phase checkpoint in mammalian cells.
Unsupervised Head--Modifier Detection in Search Queries

Interpreting the user intent in search queries is a key task in query understanding. Query intent classification has been widely studied. In this article, we go one step further to understand the query from the view of head--modifier analysis. For example, given the query “popular iphone 5 smart cover,” instead of using coarse-grained semantic classes (e.g., find electronic product), we interpret that “smart cover” is the head or the intent of the query and “iphone 5” is its modifier. Query head--modifier detection can help search engines to obtain particularly relevant content, which is also important for applications such as ads matching and query recommendation. We introduce an unsupervised semantic approach for query head--modifier detection. First, we mine a large number of instance level head--modifier pairs from search log. Then, we develop a conceptualization mechanism to generalize the instance level pairs to concept level. Finally, we derive weighted concept patterns that are concise, accurate, and have strong generalization power in head--modifier detection. The developed mechanism has been used in production for search relevance and ads matching. We use extensive experiment results to demonstrate the effectiveness of our approach.
Fast Routing in Location-Based Social Networks Leveraging Check-in Data

With the extensive use of sensor-embedded smart phones, Location-Based Social Networks (LBSN) become more and more popular among online social networks in recent years. In social networks, constructing the shortest path with minimum cost between any two nodes efficiently is vital for both graph analysis and implementation of applications. This is well known as the routing problem in social networks. However, existing approaches of routing in social networks all fail in the scenario of LBSN which are large and dynamic. In this paper, we work out a fast routing system in LBSN leveraging check-in data to tackle this challenging problem. To be specific, firstly, we demonstrate the existence of the small world phenomenon in LBSN. Secondly, we reveal the friendship-inverse-geography property in LBSN. Thirdly, we design a Location-Based Fast Routing System LBFRS which can accomplish fast routing in LBSN leveraging geographical knowledge predicted from check-in data. Experiments on two real Location-Based Social Networks Go Walla and Bright kite have shown that LBFRS performs much more accurate prediction in geography than the baseline method and accomplishes dozens of times faster routing than Dijkstra in average.
On the Construction, Maintenance and Analysis of Case-Based Strategies in Computer Poker

The state-of-the-art within Artificial Intelligence has directly benefited from research conducted within the computer poker domain. One such success has been the the advancement of bottom up equilibrium finding algorithms via computational game theory. On the other hand, alternative top down approaches, that attempt to generalise decisions observed within a collection of data, have not received as much attention. In this thesis we examine top down approaches that use Case-Based Reasoning in order to construct strategies within the domain of computer poker. Our analysis begins with the development of frameworks to produce static strategies that do not change during game play. We trace the evolution of our case-based architecture and evaluate the effect that modifications have on strategy performance. The end result of our experimentation is a coherent framework for producing strong case-based strategies based on the observation and generalisation of expert decisions. Next, we introduce three augmentation procedures that extend the initial frameworks in order to produce case-based strategies that are able to adapt to changing game conditions and exploit weaknesses of their opponents. Two of the augmentation procedures introduce different forms of opponent modelling into the case-based strategies produced. A further extension investigates the use of transfer learning in order to leverage information between separate poker sub-domains. For each poker domain investigated, we present results obtained from the Annual Computer Poker Competition, where the best poker agents in the world are challenged against each other. We also present results against a range of human opponents. The presented results indicate that the top down case-based strategies produced are competitive against both human opposition, as well as state-of-the-art, bottom up equilibrium finding algorithms. Furthermore, comparative evaluations between augmented and non-augmented frameworks show that strategies which have been augmented with either transfer learning or opponent modelling capabilities are typically able to outperform their non-augmented counterparts.
BioTAM: a technology acceptance model for biometric authentication systems

The increasing demand on biometric authentication systems (BASs) has brought the need of secure and privacy-preserving solutions accepted by a wider community of users. The decision makers pay a great attention to how people react to BASs and their opinions about the features and procedures of the system. In this work, a generic Biometric Technology Acceptance Model (BioTAM) is proposed. BioTAM encounters trust as an objective measure of privacy-security tradeoff, public willingness and user confidence. BioTAM takes into account social and human factors which prominently affect the wider dissemination and easy penetration of BASs. To scrutinise people's behavioural intention to use a BAS, BioTAM melds traditional Technology Acceptance Model constructs and the trust model offered as a new construct. In order to inspire stakeholders on how BioTAM can be used to assess a BAS, a sample case study is investigated.
Cytotoxic Helix-Rich Oligomer Formation by Melittin and Pancreatic Polypeptide

Conversion of amyloid fibrils by many peptides/proteins involves cytotoxic helix-rich oligomers. However, their toxicity and biophysical studies remain largely unknown due to their highly dynamic nature. To address this, we chose two helical peptides (melittin, Mel and pancreatic polypeptide, PP) and studied their aggregation and toxicity. Mel converted its random coil structure to oligomeric helical structure upon binding to heparin; however, PP remained as helix after oligomerization. Interestingly, similar to Parkinson’s associated α-synuclein (AS) oligomers, Mel and PP also showed tinctorial properties, higher hydrophobic surface exposure, cellular toxicity and membrane pore formation after oligomerization in the presence of heparin. We suggest that helix-rich oligomers with exposed hydrophobic surface are highly cytotoxic to cells irrespective of their disease association. Moreover as Mel and PP (in the presence of heparin) instantly self-assemble into stable helix-rich amyloidogenic oligomers; they could be represented as models for understanding the biophysical and cytotoxic properties of helix-rich intermediates in detail.
Incremental Conductance MPPT TechniqueFOR PV System

Nowadays solar energy has great importance. Because it is easily available resource for energy generation. But the only problem is efficiency of solar system. And to increase its efficiency many MPPT techniques are used. Large number of papers were published on Maximum Power Point techniques (MPPT). And therefore many techniques are available for use. These techniques differs in many aspects. Incremental conductance is one of the important technique in this system and because of its higher steady-state accuracy and environmental adaptability it is widely implemented tracked control strategy. This paper presents details of Incremental Conductance algorithm with simulation results obtained using MATLAB and SIMULINK.
OCCAMS -- An Optimal Combinatorial Covering Algorithm for Multi-document Summarization

OCCAMS is a new algorithm for the Multi-Document Summarization (MDS) problem. We use Latent Semantic Analysis (LSA) to produce term weights which identify the main theme(s) of a set of documents. These are used by our heuristic for extractive sentence selection which borrows techniques from combinatorial optimization to select a set of sentences such that the combined weight of the terms covered is maximized while redundancy is minimized. OCCAMS outperforms CLASSY11 on DUC/TAC data for nearly all years since 2005, where CLASSY11 is the best human-rated system of TAC 2011. OCCAMS also delivers higher ROUGE scores than all human-generated summaries for TAC 2011. We show that if the combinatorial component of OCCAMS, which computes the extractive summary, is given true weights of terms, then the quality of the summaries generated outperforms all human generated summaries for all years using ROUGE-2, ROUGE-SU4, and a coverage metric. We introduce this new metric based on term coverage and demonstrate that a simple bi-gram instantiation achieves a statistically significant higher Pearson correlation with overall responsiveness than ROUGE on the TAC data.
Geochemical properties of rocks and soils in Gusev Crater, Mars: Results of the Alpha Particle X-Ray Spectrometer from Cumberland Ridge to Home Plate

[1] Geochemical diversity of rocks and soils has been discovered by the Alpha Particle X-Ray Spectrometer (APXS) during Spirit's journey over Husband Hill and down into the Inner Basin from sol 470 to 1368. The APXS continues to operate nominally with no changes in calibration or spectral degradation over the course of the mission. Germanium has been added to the Spirit APXS data set with the confirmation that it occurs at elevated levels in many rocks and soils around Home Plate. Twelve new rock classes and two new soil classes have been identified at the Spirit landing site since sol 470 on the basis of the diversity in APXS geochemistry. The new rock classes are Irvine (alkaline basalt), Independence (low Fe outcrop), Descartes (outcrop similar to Independence with higher Fe and Mn), Algonquin (mafic-ultramafic igneous sequence), Barnhill (volcaniclastic sediments enriched in Zn, Cl, and Ge), Fuzzy Smith (high Si and Ti rock), Elizabeth Mahon (high Si, Ni, and Zn outcrop and rock), Halley (hematite-rich outcrop and rock), Montalva (high K, hematite-rich rock), Everett (high Mg, magnetite-rich rock), Good Question (high Si, low Mn rock), and Torquas (high K, Zn, and Ni magnetite-rich rock). New soil classes are Gertrude Weise (very high Si soil) and Eileen Dean (high Mg, magnetite-rich soil). Aqueous processes have played a major role in the formation and alteration of rocks and soils on Husband Hill and in the Inner Basin.