Miracle-dz/UniFAR-FTUs huggingface dataset:
Weighted atlas auto-context with application to multiple organ segmentation

Difficulties can arise from the segmentation of three-dimensional objects formed by multiple non-rigid parts represented in two-dimensional images. Problems involving parts whose spatial arrangement is subject to weak restrictions, and whose appearance and form change across images, can be particularly challenging. Segmentation methods that take into account spatial context information have addressed these types of problem, which often involve image data of a multi-modal nature. An attractive feature of the auto-context (AC) technique is that a prior "atlas", typically obtained by averaging multiple label maps created by experts, can be used as an initial source of contextual data. However, a prior obtained in this way is likely to hide the inherent multi-modality of the data. We propose a modification of AC in which a probabilistic atlas of part locations is iteratively improved and made available as an additional source of information. We illustrate this technique with the problem of segmenting individual organs in images of pig offal, reporting statistically significant improvements in relation to both conventional AC and a state-of-the-art technique based on conditional random fields.
Linear Coherent Bi-Clustering via Beam Searching and Sample Set Clustering

We propose a new bi-clustering algorithm, LinCoh, for finding linear coherent bi-clusters in gene expression microarray data. Our method exploits a robust technique for identifying conditionally correlated genes, combined with an efficient density-based search for clustering sample sets. Experimental results on both synthetic and real datasets demonstrated that LinCoh consistently finds more accurate and higher quality bi-clusters than existing bi-clustering algorithms.
Hyperspectral target detection via locality-constrained group sparse representation

Target detection is an important task in hyper-spectral image processing. Traditional methods usually impose a stringent assumption on the spectrum distribution of the background and targets, which cannot hold for all the practical situations. This problem can be avoided by sparsity-based method in which each test pixel is represented by a linear combination of a few samples from an overcomplete dictionary. However, classical sparsity model ignores the dictionary structure and cannot guarantee an accurate sparse representation for the test pixel. Motivated by this point, this paper proposes a locality-constrained group sparse representation for target detection. It makes full use of the dictionary structure and preserves the manifold of the original data at the same time, not only ensuring that the correlated training samples belonging to the correct class are used to express the test pixel but also guaranteeing that similar spectrums of HSI pixels will have similar codes. Experimental results on real hyperspectral imagery suggest that the proposed method is more effective than conventional sparsity-based algorithm and the statistics-based methods.
Correlating the Visual Representation of User Interfaces with their Internal Structures and Metadata

Pixel-based methods emerge to be a new and promising way for developing new interaction techniques on top of existing user interfaces. However, in order to maintain platform independence, other available low-level information about GUI widgets, such as accessibility metadata, was neglected intentionally. In this paper, we present a hybrid framework, PAX, which correlates the visual representation of user interfaces (i.e. the pixels) and their internal hierarchical metadata (i.e. the content, role, and value). We identify challenges to build such a framework. We also develop and evaluate two new algorithms for detecting text at arbitrary places on the screen, and for segmenting a text image into individual word blobs. Finally, we validate our framework in implementations of three applications. We enhance an existing pixel-based system, Sikuli Script, and preserve the readability of its script code at the same time. Further, we create two novel applications, Screen Search and Screen Copy, to demonstrate how PAX can be applied to developing desktop-level interactive systems.
Global and regional variability in marine surface temperatures

The temperature variability simulated by climate models is generally consistent with that observed in instrumental records at the scale of global averages, but further insight can also be obtained from regional analysis of the marine temperature record. A protocol is developed for comparing model simulations to observations that account for observational noise and missing data. General consistency between Coupled Model Intercomparison Project Phase 5 model simulations and regional sea surface temperature variability is demonstrated at interannual timescales. At interdecadal timescales, however, the variability diagnosed from observations is significantly greater. Discrepancies are greatest at low latitudes, with none of the 41 models showing equal or greater interdecadal variability. The pattern of suppressed variability at longer timescales and smaller spatial scales appears consistent with models generally being too diffusive. Suppressed variability of low‐latitude marine temperatures points to underestimation of intrinsic variability and may help explain why few models reproduce the observed temperature trends during the last 15 years.
True color image segmentation by an optimized multilevel activation function

A novel neuro-fuzzy-genetic approach is presented in this article to segment a true color image into different color levels. A MUSIG activation function induces multiscaling capabilities in a parallel self organizing neural network (PSONN) architecture. The function however resorts to equal and fixed class responses, assuming the homogeneity of image information content. In the proposed approach, genetic algorithm has been used to generate optimized class responses of the MUSIG activation function. Subsequently, the color images are segmented by applying the resultant optimized multilevel sigmoidal (OptiMUSIG) activation function. Comparative results of segmentation of two real life true color images indicate better segmentation efficiency of the OptiMUSIG activation function over the standard MUSIG activation function.
The effect of pure state structure on nonequilibrium dynamics

Motivated by short-range Ising spin glasses, we review some rigorous results and their consequences for the relation between the number/nature of equilibrium pure states and nonequilibrium dynamics. Two of the consequences for spin glass dynamics following an instantaneous deep quench to a temperature with broken spin flip symmetry are: (1) almost all initial configurations lie on the boundary between the basins of attraction of multiple pure states; (2) unless there are uncountably many pure states with almost all pairs having zero overlap, there can be no equilibration to a pure state as time . We discuss the relevance of these results to the difficulty of equilibration of spin glasses. We also review some results concerning the ‘nature versus nurture’ problem of whether the large-t behavior of both ferromagnets and spin glasses following a deep quench is determined more by the initial configuration (nature) or by the dynamics realization (nurture).
Particle positioning system for ad-hoc wireless networks

Geometric routing, data collection, node deployment and node tracking in wireless ad-hoc networks often require a form of position-awareness by the nodes. There exist several location sensing algorithms that use network topology (connectivity) to infer spatial information. Most of these rely on either centralised computation method, several well known anchor nodes/points or expensive message exchange between the nodes. We propose a particle positioning system (PPS) that uses node connectivity information collected by routing protocol to map node positions and hence avoid some of the aforementioned restrictions. PPS mainly uses a combination of particle and spring physics to simulate a system that calculates increasingly accurate relative positions with increased topology knowledge. If combined with angle of arrival information (AoA) or anchor nodes, PPS can map its relative coordinates to the real world positions. In this paper we show that PPS generates positions accurate to between 6-33% of the node's transmission range, while competitive location estimate techniques manage a 20% accuracy only in best-case scenarios.
Dynamic application-aware resource management using Software-Defined Networking: Implementation prospects and challenges

Today's Internet does not provide an exchange of information between applications and networks, which may result in poor application performance. Concepts such as application-aware networking or network-aware application programming try to overcome these limitations. The introduction of Software-Defined Networking (SDN) opens a path towards the realization of an enhanced interaction between networks and applications. Hence, a more dynamic and demand-based allocation of network resources to heterogeneous applications can be realized. The implementation of the resource management action, however, may have an impact on the data transport and application quality. This paper summarizes resource management mechanisms provided by current SDN approaches based on OpenFlow and exemplary evaluates implementation prospects and challenges.
A Cysteine Protease Inhibitor of Plasmodium berghei Is Essential for Exo-erythrocytic Development

Plasmodium parasites express a potent inhibitor of cysteine proteases (ICP) throughout their life cycle. To analyze the role of ICP in different life cycle stages, we generated a stage-specific knockout of the Plasmodium berghei ICP (PbICP). Excision of the pbicb gene occurred in infective sporozoites and resulted in impaired sporozoite invasion of hepatocytes, despite residual PbICP protein being detectable in sporozoites. The vast majority of these parasites invading a cultured hepatocyte cell line did not develop to mature liver stages, but the few that successfully developed hepatic merozoites were able to initiate a blood stage infection in mice. These blood stage parasites, now completely lacking PbICP, exhibited an attenuated phenotype but were able to infect mosquitoes and develop to the oocyst stage. However, PbICP-negative sporozoites liberated from oocysts exhibited defective motility and invaded mosquito salivary glands in low numbers. They were also unable to invade hepatocytes, confirming that control of cysteine protease activity is of critical importance for sporozoites. Importantly, transfection of PbICP-knockout parasites with a pbicp-gfp construct fully reversed these defects. Taken together, in P. berghei this inhibitor of the ICP family is essential for sporozoite motility but also appears to play a role during parasite development in hepatocytes and erythrocytes.
Text Tokenization for Knowledge-free Automatic Extraction of Lexical Similarities

Previous studies on automatic extraction of lexical similarities have considered as semantic unit of text the word. However, the theory of contextual lexical semantics implies that larger segments of text, namely non-compositional multiwords, are more appropriate for this role. We experimentally tested the applicability of this notion applying automatic collocation extraction to identify and merge such multiwords prior to the similarity estimation process. Employing an automatic WordNet-based comparative evaluation scheme along with a manual evaluation procedure, we ascertain improvement of the extracted similarity relations.
Feature oriented sentiment analysis in social networking sites to track malicious campaigners

Social networking websites are considered as major sources of opinions and views of the public on the prevalent social issues at a given point in time. Websites like the Twitter1 reflect the public views through its millions of messages posted by its users world wide, whenever a controversial issue arises in the society. It is during this time that we observe significant amount of malicious, violent contents going viral over the internet. In this paper we propose a technique that applies sentiment analysis on data from Twitter and measures the sentiments of posts in order to identify the origin of malicious contents. This is achieved by taking into account the influence of the posts on the public as well. The prominent feature of our work is the technique that is used for feature-oriented sentiment analysis. This involves an algorithm that parses a given tweet and builds a Dependency tree of each sentence in order to effectively identify the sentiment of the tweet. The working and the scope of our techniques are illustrated with a case study and associated results.
Geminin Is Required for the Maintenance of Pluripotency

Pluripotency requires the expression of the three core transcriptions factors Oct4, Sox2 and Nanog, as well as further, complementary proteins. The geminin protein is part of this network, and was shown to play a role in the regulation of DNA replication, the control of the cell cycle, and the acquisition of neural fate. It is highly expressed in the early embryo, in particular the epiblast and the early neural ectoderm, and also in pluripotent embryonic stem cells. The genetic inactivation of geminin resulted in lethality after the first few cell divisions, and thus prohibited the outgrowth of pluripotent cells. We established embryonic stem cells allowing the deletion of the geminin gene by induction of of Cre-recombinase with tamoxifen. Here, we show that geminin deficiency quickly leads to a loss of pluripotency, and to differentiation into the mesendodermal direction with high Oct4/low Sox2 levels. Simultaneous loss of geminin and induction of the neural lineage resulted in immediate apoptosis. These results suggested that in early development geminin functions via the co-expressed Sox2 gene. We found that the stem cell enhancer SRR2 of Sox2 is occupied by the activating esBAF complex in the presence of geminin, but becomes epigenetically repressed in its absence by the Polycomb repressive complex PRC2. The importance of geminin for Sox2 expression also explains the absolute requirement for geminin during the induction of pluripotency by OSKM viruses. In summary, geminin is required for Sox2 expression, and thus for the maintenance of totipotency, pluripotency and the early neural lineage.
Extended Quantum XOR Gate in Terms of Two-Spin Interactions

Considerations of feasibility of quantum computing lead to the study of multispin quantum gates in which the input and output two-state systems (spins) are not identical. We provide a general discussion of this approach and then propose an explicit two-spin interaction Hamiltonian which accomplishes the quantum XOR gate function for a system of three spins: two input and one output.
Three Puzzles in Hierarchical Evolution1

Abstract The maximum degree of hierarchical structure of organisms has risen over the history of life, notably in three transitions: the origin of the eukaryotic cell from symbiotic associations of prokaryotes; the emergence of the first multicellular individuals from clones of eukaryotic cells; and the origin of the first individuated colonies from associations of multicellular organisms. The trend is obvious in the fossil record, but documenting it using a high-resolution hierarchy scale reveals three puzzles: 1) the rate of origin of new levels accelerates, at least until the early Phanerozoic; 2) after that, the trend may slow or even stop; and 3) levels may sometimes arise out of order. The three puzzles and their implications are discussed; a possible explanation is offered for the first.
Sonication, Vacuum Infiltration and Thiol Compounds Enhance the Agrobacterium-Mediated Transformation Frequency of Withania somnifera (L.) Dunal

In the present study, we have established a stable transformation protocol via Agrobacterium tumafacines for the pharmaceutically important Withania somnifera. Six day-old nodal explants were used for 3 day co-cultivation with Agrobacterium tumefaciens strain LBA4404 harbouring the vector pCAMIBA2301. Among the different injury treatments, sonication, vacuum infiltration and their combination treatments tested, a vacuum infiltration for 10 min followed by sonication for 10 sec with A. tumefaciens led to a higher transient GUS expression (84% explants expressing GUS at regenerating sites). In order to improve gene integration, thiol compounds were added to co-cultivation medium. A combined treatment of L-Cys at 100 mg/l, STS at 125 mg/l, DTT at 75 mg/l resulted in a higher GUS expression (90%) in the nodal explants. After 3 days of co-cultivation, the explants were subjected to three selection cycles with increasing concentrations of kanamycin [100 to 115 mg/l]. The integration and expression of gusA gene in T0 and T1 transgenic plants were confirmed by polymerase chain reaction (PCR), and Southern blott analysis. These transformed plants (T0 and T1) were fertile and morphologically normal. From the present investigation, we have achieved a higher transformation efficiency of (10%). Withanolides (withanolide A, withanolide B, withanone and withaferin A) contents of transformed plants (T0 and T1) were marginally higher than control plants.
Perfromance evaluation of two signatures' codes linear decorrelator detector for CDMA systems in Nakagami fading channel

In linear time invariant channel model, the systems that are designed based on CDMA are suffering from multiple access interference (MAI) and noise problems. In time varying channel model, the CDMA systems suffer from complex time varying channel's gains plus MAI and noise. A lot of CDMA detectors are designed to overcome the MAI problem. But these detectors have complex structures and their performances are affected by the presence of time varying channel's gains. This paper gives proposal for new linear CDMA detector that has the same MAI cancellation capability as CDMA decorrelator detector but with simpler structure. The operation of the new detector is based on the symmetry property of the cross-correlation matrix of CDMA signatures' codes. The structure complexity of this new detector is as simple as matched filter detector structure. The performance of this new detector is evaluated in the presence of Nakagami time varying channel's complex gains. Closed forms of probability of error for the proposed detector and decorrelator detector are represented for flat and multipath Nakagami fading models. Channel phase estimation error effect is included in the probability of error formulas. Different channel estimators are used with the proposed detector to overcome the fading phenomenon.
Heterogeneity of Developmental Dyscalculia: Cases with Different Deficit Profiles

Developmental Dyscalculia (DD) has long been thought to be a monolithic learning disorder that can be attributed to a specific neurocognitive dysfunction. However, recent research has increasingly recognized the heterogeneity of DD, where DD can be differentiated into subtypes in which the underlying cognitive deficits and neural dysfunctions may differ. The aim was to further understand the heterogeneity of developmental dyscalculia (DD) from a cognitive psychological perspective. Utilizing four children (8–9 year-old) we administered a comprehensive cognitive test battery that shed light on the cognitive-behavioral profile of each child. The children were compared against norm groups of aged-matched peers. Performance was then contrasted against predominant hypotheses of DD, which would also give insight into candidate neurocognitive correlates. Despite showing similar mathematical deficits, these children showed remarkable interindividual variability regarding cognitive profile and deficits. Two cases were consistent with the approximate number system deficit account and also the general magnitude-processing deficit account. These cases showed indications of having domain-general deficits as well. One case had an access deficit in combination with a general cognitive deficit. One case suffered from general cognitive deficits only. The results showed that DD cannot be attributed to a single explanatory factor. These findings support a multiple deficits account of DD and suggest that some cases have multiple deficits, whereas other cases have a single deficit. We discuss a previously proposed distinction between primary DD and secondary DD, and suggest hypotheses of dysfunctional neurocognitive correlates responsible for the displayed deficits.
Improving the user experience on mobile apps through data mining

With the advance of mobile applications market, there is an increasing concern about the challenges when developing products that meet the many types of users and to harmonize each product with the various usage environments, thus, providing a good user experience. This situation leads to the need to develop a framework that makes applications become aware of the context and provides a self-learning of the user navigation. This article presents a theoretical framework and the TURAP operation process, a framework for Android applications that helps to tackle these challenges.
COMPLEX AGENT-BASED MODELS: APPLICATION OF A CONSTRUCTIVISM IN THE ECONOMIC RESEARCH

Economies constitute complex and dynamic systems, which have been studied from multiple perspectives and with various tools, techniques and methods. They encompass behavioural patterns, interaction among particular subjects, or several functional principles [34]. There are two dominating issues related to modelling of economic systems. Firstly, study of economic systems is traditionally based on analytical and econometric tools, which have been the main arbiters of the veracity or plausibility of assumptions and hypotheses in economics. Theoretical models are usually developed for analytical tractability and offer internal consistency within prescribed conditions and assumptions [28]. This approach is highly suitable for theory development. However, in practice the pace of change and existing uncertainty about the way in which markets will evolve has made it increasingly important for companies to be aware of modelling techniques, which would enable support of decision-making processes. Due to this necessity various modelling tools, methods, or techniques have already been applied in the business realm, ranging from standardised tools and techniques such as Unified Modelling Language (UML) or Petri nets [30], to non-standardised “fun diagrams” helping managers to capture mental models and ideas [5]. Moreover, the pool of applied techniques comprises both models grounded in exact mathematical representation of reality, which can be further simulated (e.g. Markov chains), and more or less vague models helping only to express significant elements and relations in the studied business domain (e.g. flow charts, or causal-loop diagrams). Secondly, majority of these approaches and techniques usually fail when coping with one particular attribute of real economic systems – complexity [6]. These two gaps might be bridged with the help of new modelling paradigms that have been established only recently. Application of agent-based modelling in the realm of economic systems is labelled as Agent-based Computational Economics (ACE). Current ACE research divides into four streams distinguished by objectives [34]: 1) Empirical understanding. 2) Normative understanding. 3) Qualitative insight and theory generation. 4) Methodological advancement.