Miracle-dz/UniFAR-FTUs huggingface dataset:
A new path to platelet production through matrix sensing

Megakaryocytes (MK) in the bone marrow (BM) are immersed in a network of extracellular matrix components that regulates platelet release into the circulation. Combining biological and bioengineering approaches, we found that the activation of transient receptor potential cation channel subfamily V member 4 (TRPV4), a mechano-sensitive ion channel, is induced upon MK adhesion on softer matrices. This response promoted platelet production by triggering a cascade of events that lead to calcium influx, β1 integrin activation and internalization, and Akt phosphorylation, responses not found on stiffer matrices. Lysyl oxidase (LOX) is a physiological modulator of BM matrix stiffness via collagen crosslinking. In vivo inhibition of LOX and consequent matrix softening lead to TRPV4 activation cascade and increased platelet levels. At the same time, in vitro proplatelet formation was reduced on a recombinant enzyme-mediated stiffer collagen. These results suggest a novel mechanism by which MKs, through TRPV4, sense extracellular matrix environmental rigidity and release platelets accordingly.
Dynamic dewetting of surfactant solutions

Wetting and dewetting play a significant role in many natural processes as well as in many technical applications like in printing or cleaning procedures. To optimize these kind of processes the understanding of the dewetting behaviour of surfactant solutions is important. Previous investigations showed, that an addition of surfactant to a solution changes the dewetting behaviour. Those studies revealed, that the dewetting behaviour is depending on the surfactant concentration, even if the concentration is below the critical micelle concentration (CMC). Nevertheless the effects due to the presence of surfactants are not well understood. Therefore, I investigated in this work, how surfactants influence the dewetting behaviour on smooth and structured surfaces. The dewetting behaviour of various surfactant solutions (non-ionic, cationic and anionic) on a smooth polystyrene surface were compared at different concentrations well below the CMC. All surfactants show the same tendency, independent of their charge: the higher the surfactant concentration, the lower the receding contact angle as well as the film formation velocity. Scaling with the CMC leads almost to a master curve. The change in contact angle can be interpreted by local surface gradients, e.g. Marangoni stresses. At velocities > 10 mm/s the experimental results can be described by the hydrodynamic theory. Additionally to the wetting behaviour on smooth surfaces, the influence of a structured surface in the presence of surfactant was studied. A custom made printing plate with different structured areas was used as model surface. The dewetting behaviour is comparable to dewetting on smooth surfaces, the higher the surfactant concentration the lower the contact angle as well as the critical film formation velocity. The influence of the structured surface decreases with increasing concentration. The decreasing influence of the structured surface is due to the fact, that with increasing concentration the Marangoni stress towards the three phase contact line increases. These Marangoni stresses dominate the stress due to pinning on the structured surface. Since a direct measurement of the Marangoni stresses is not easily possible, I measured instead the flow profile on a microscopic lenght scale close to the contact line. A newly developed setup is able to image of a moving contact line over a long time period. The measurement of the flow profile showed that at a distance smaller than 30 μm the flow from surfactant solution differs from the one of pure water. This is in agreement with the model of the Marangoni force towards the contact line, which results in the decrease of the contact angle macroscopically.
Patterns of Cognitive and Fine Motor Deficits in a Case of Dandy-Walker Continuum

Cerebellar vermian hypoplasia in the context of Dandy-Walker complex is a relatively common disorder associated with a variety of cognitive and behavioral deficits in addition to impairment in motor control. Few studies, however, have examined the neuropsychological profiles of children with isolated hypoplasias of the cerebellum. Herein, we report a 6-year-old girl with Dandy-Walker continuum presenting with mild mental retardation and an inability to produce intelligible speech, despite adequate comprehension of single items and simple instructions. She was able to articulate vowels but not consonants, and fine motor function was deficient. Visual memory was intact for single items but not for multiple items, and visuospatial perception was impaired. An inability to form intelligible speech is not typically reported in cases of isolated vermian hypoplasia. The case extends our knowledge of the phenotypes associated with cerebellar hypoplasia and its relation to fine motor and articulatory control.
Dynamic Revenue Maximization: A Continuous Time Approach

We characterize the profit-maximizing mechanism for repeatedly selling a non-durable good in continuous time. The valuation of each agent is private information and changes over time. At the time of contracting every agent privately observes his initial type which influences the evolution of his valuation process. In the profit-maximizing mechanism the allocation is distorted in favor of agents with high initial types. We derive the optimal mechanism in closed form, which enables us to compare the distortion in various examples. The case where the valuation of the agents follows an arithmetic/geometric Brownian motion, Ornstein-Uhlenbeck process, or is derived from a Bayesian learning model are discussed. We show that depending on the nature of the private information and the valuation process the distortion might increase or decrease over time.
Model of storage of ERP protocols in EEG/ERP portal

The EEG/ERP (Electroencephalography/Even-Related Potentials) Portal serves for storage and management of ERP experiments. The protocols describing these experiments are designed and implemented using various software applications and/or hardware devices. Some protocols are kept in XML files and stored in the EEG/ERP portal database as LOB (Large Object) data types. Since it is important for researchers to directly find details about design of the ERP protocols in the related XML files and it is also hard to use LOB data for generating the semantic web output, storage types provided by the Oracle 11g database system were investigated and compared. Therefore a new model of storage of ERP protocols is introduced. This model is finally simplified after analysis of results of performance tests.
Toward a Unified Framework for Tracking Cognitive Processes

In this paper we present an initial specification of a general, robust, and efficient computational framework for tracking cognitive processes — that is, inferring a persons’ thoughts from their actions. Our framework, which we call the mind-tracking architecture, centers on two core processes: generating predicted cognitive and action sequences using computational cognitive models, and tracking observed actions through robust matching with predicted actions. In essence, the mind-tracking architecture “thinks along” with the person in predicting a set of possible thoughts and actions, and then matches these to the person’s observed actions to infer their most likely thoughts. In the paper we provide a background of related work (e.g., for intelligent tutoring systems), outline the basic components of the architecture, and demonstrate its usefulness for a sample real-world application — real-time inference of driver intentions.
Properties of an adaptive archiving algorithm for storing nondominated vectors

Search algorithms for Pareto optimization are designed to obtain multiple solutions, each offering a different trade-off of the problem objectives. To make the different solutions available at the end of an algorithm run, procedures are needed for storing them, one by one, as they are found. In a simple case, this may be achieved by placing each point that is found into an "archive" which maintains only nondominated points and discards all others. However, even a set of mutually nondominated points is potentially very large, necessitating a bound on the archive's capacity. But with such a bound in place, it is no longer obvious which points should be maintained and which discarded; we would like the archive to maintain a representative and well-distributed subset of the points generated by the search algorithm, and also that this set converges. To achieve these objectives, we propose an adaptive archiving algorithm, suitable for use with any Pareto optimization algorithm, which has various useful properties as follows. It maintains an archive of bounded size, encourages an even distribution of points across the Pareto front, is computationally efficient, and we are able to prove a form of convergence. The method proposed here maintains evenness, efficiency, and cardinality, and provably converges under certain conditions but not all. Finally, the notions underlying our convergence proofs support a new way to rigorously define what is meant by "good spread of points" across a Pareto front, in the context of grid-based archiving schemes. This leads to proofs and conjectures applicable to archive sizing and grid sizing in any Pareto optimization algorithm maintaining a grid-based archive.
Multichannel Wiener filtering via multichannel decorrelation

Extracting a target source signal from multiple noisy observations is an essential task in many applications of signal processing such as digital communications or speech and audio processing. The multi-channel Wiener filter is able to solve this task in a minimum-mean-square-error (MMSE) optimal way by applying a spatial filter succeeded by a spectral postfilter. Its direct implementation, however, is difficult due to requiring the statistics of the unobservable source and noise signals. In this paper, we apply the signal-separation-based technique of multichannel decorrelation and reveal its relation to the Wiener post-filtering component. On this basis, we present a numerically robust and efficient adaptive algorithm to find an estimate of the MMSE-optimal postfilter based on the statistics of the observable signals alone. Experimental evaluation demonstrates the validity of the proposed approach and confirms the convergence of the adaptive algorithm to the MMSE-optimal postfilter solution.
Prognostic Significance of the Deleted in Colorectal Cancer Gene Protein Expression in High-Risk Resected Gastric Carcinoma

The deleted in colorectal cancer (DCC) gene is a candidate tumor suppressor gene that may be associated with differentiation and proliferation of normal cells. Loss of heterozygosity (LOH) of 18q, where the gene is located, and absence of DCC protein expression have been associated with worse prognosis in certain subgroups of patients with colorectal adenocarcinoma. We studied the prognostic significance of loss-of-protein expression in 66 patients with resected gastric cancer with a high probability of relapse (T3, T4, N+). The DCC protein was detected with immunohistochemistry using an anti-DCC monoclonal antibody on paraffin-embedded sections. The DCC protein expression was present in 51 cases (77.3%) and absent in 15 cases (22.7%). Poorly differentiated and signet ring carcinomas had significantly lower expression than more differentiated tumors(p<0.05) as did diffuse-type tumors compared to intestinal and mixed(p<0.01). There was no correlation with proliferation rate, estimated immunohistochemically using an anti-proliferating cell nuclear antigen (PCNA) monoclonal antibody. Absence of DCC protein was an independent favorable prognostic factor (median survival 57 months vs. 18 months,p=0.0176). The DCC protein expression was correlated with relapse site: all patients with distant metastases were positive for DCC staining, while one-third of patients with local/peritoneal relapse were negative(p<0.01). In conclusion, DCC protein expression seems to be a significant prognostic factor in high-risk resected gastric cancer. Our results support previous data associating the DCC gene with differentiation and indicate that this gene may play a role in the metastatic potential of these tumors. These findings need to be confirmed by future larger studies.
Novel multiple bypass bins scheme for low-power UHD video processing HEVC binary arithmetic encoder architecture

The HEVC is one of the most recent video coding standards, developed in order to face upcoming challenges, due to higher video quality and resolution. One of the HEVC components is the entropy encoder, which consists only of the Context Adaptive Binary Arithmetic Coding (CABAC) algorithm. The CABAC algorithm imposes some severe difficulties in order to achieve increasing throughput, due to the high data dependency among each processing element. Along with throughput, low-power consumption is a sought-after goal for video processing hardware architecture. This work proposes a novel multiplier-less scheme for multiple bypass bins processing focusing in increasing bin per cycle throughput focusing in low-power design for CABAC critical submodule Binary Arithmetic Encoder (BAE), with negligible degradation in frequency. The present work also accomplishes the insertion of low-power techniques, based on the average proportion of bins for video test sequences. Results show that the proposed work is able to process 8K UHD videos at 6.2 high tier with the minimum frequency among the works in the literature, which decreases the power dissipation of the block. The average power savings achieved by the insertion of low-power technique were, on average, 14.26%.
Cost-Sensitive Boosting Networks for Data Defect Prediction

: Software Defect prediction which classify the software modules into defect prone and not defect prone category and plays an important role in reducing the coast of software development and maintaining high quality software system. Existing defect prediction model face two challenges 1)Class Imbalance 2)High Dimensionality. In this paper a new cost sensitive boosting networks for data defect prediction is proposed. Cost sensitive learning is a method to solve class imbalance problem. Cost sensitive learning takes costs such as the misclassification coast into consideration. High dimensionality can be handled by using feature selection methods. For feature selection purpose three cost sensitive feature selection algorithms are used namely Cost-Sensitive Variance Score (CSVS), Cost-Sensitive Laplacian Score (CSLS), and Cost-Sensitive Constraint Score. The proposed techniques are evaluated on the data set taken from NASA MDP data set . The experiments shows that cost sensitive feature selection methods are more efficient than traditional one in reducing the total cost. The accuracy and class imbalance problem can be better solved by using the method like swarm and bagging techniques.
Joint Web-Feature (JFEAT): A Novel Web Page Classification Framework

With the increasing amount of web pages over the internet, it has been a major concern to obtain information on the internet accurately at a reasonable cost with decent performance. A potential solution is through the classification of web pages into meaningful categories. An effective classification of web pages is of benefit to various applications such as web mining and search engines. Unlike text documents, the nature of web pages limits the performance of successful traditional pure-text classification methods. Noises exist in the form of HTML tags, multimedia contents, dynamic contents and the network structure of web pages which requires a deeper look into effective feature selection of web pages. Often, these features are filtered out relying on the displayed texts of the web page for classification. This paper proposed a framework where web page features are taken into consideration during classification of the web page due to the potential valuable information that might be stored within each of the features. For this reason, this paper explores the potential of the universal Resource Locator (URL), web page title as well as the metadata for information to be used in classification with various categories defined by the users. The framework then explores suitable machine learning algorithms for individual classification of each web feature. The results would then be used for weighted voting to obtain the classification of that webpage. This approach showed improvements over pure-text as well as virtual-webpage classification approaches.
A comparative study of cluster based outlier detection, distance based outlier detection and density based outlier detection techniques

As there is an increasing demand of data, outlier detection is coming across as a popular field of research. Outlier is stated as an observation which is dissimilar from the other observations present in the data set. It is advantageous in the fields like medical industry, crime detection, fraudulent transaction, public safety etc. Outlier can be learnt in different fields like big data, time series data, high dimension data, biological data, uncertain data and many more. Most of the time 10% of the whole sample data set is incorrect, not accessible or missing sometimes. This paper studies and compares the popular outlier detection algorithms namely, Cluster based outlier detection, Distance based outlier detection and Density based outlier detection. Comparative study of these outlier detection techniques is performed to find out most efficient outlier detection method for calculation of the outlier.
Crystal Structure of Hypothetical Fructose-Specific EIIB from Escherichia coli

We have solved the crystal structure of a predicted fructose-specific enzyme IIBfruc from Escherichia coli (EcEIIBfruc) involved in the phosphoenolpyruvate-carbohydrate phosphotransferase system transferring carbohydrates across the cytoplasmic membrane. EcEIIBfruc belongs to a sequence family with more than 5,000 sequence homologues with 25–99% amino-acid sequence identity. It reveals a conventional Rossmann-like α-β-α sandwich fold with a unique β-sheet topology. Its C-terminus is longer than its closest relatives and forms an additional β-strand whereas the shorter C-terminus is random coil in the relatives. Interestingly, its core structure is similar to that of enzyme IIBcellobiose from E. coli (EcIIBcel) transferring a phosphate moiety. In the active site of the closest EcEIIBfruc homologues, a unique motif CXXGXAHT comprising a P-loop like architecture including a histidine residue is found. The conserved cysteine on this loop may be deprotonated to act as a nucleophile similar to that of EcIIBcel. The conserved histidine residue is presumed to bind the negatively charged phosphate. Therefore, we propose that the catalytic mechanism of EcEIIBfruc is similar to that of EcIIBcel transferring phosphoryl moiety to a specific carbohydrate.
Outcomes of children with BCR-ABL1–like acute lymphoblastic leukemia treated with risk-directed therapy based on the levels of minimal residual disease.

PURPOSE BCR-ABL1–like acute lymphoblastic leukemia (ALL) is a recently identified B-cell ALL (B-ALL)subtype with poor outcome that exhibits a gene expression profile similar to BCR-ABL1-positive ALL but lacks the BCR-ABL1 fusion protein. We examined the outcome of children with BCR-ABL1–like ALL treated with risk-directed therapy based on minimal residual disease (MRD) levels during remission induction. PATIENTS AND METHODS Among 422 patients with B-ALL enrolled onto the Total Therapy XV study between 2000 and 2007, 344 had adequate samples for gene expression profiling. Next-generation sequencing and/or analysis of genes known to be altered in B-ALL were performed in patients with BCR-ABL1–likeALL who had available material. Outcome was compared between patients with and those without BCR-ABL1–like ALL. RESULTS Forty (11.6%) of the 344 patients had BCR-ABL1–like ALL. They were significantly more likely to be male, have Down syndrome, and have higher MRD levels on day 19 and at the end of induction than did other patients with B-ALL. Among 25 patients comprehensively studied for genetic abnormalities, 11 harbored a genomic rearrangement of CRLF2, six had fusion transcripts responsive to ABL tyrosine kinase inhibitors or JAK inhibitors, and seven had mutations involving the Ras signaling pathway. There were no significant differences in event-free survival (90.0% +/- 4.7% [SE] v. 88.4% +/- .9% at 5 years; P = .41or in overall survival (92.5% +/- 4.2% v. 95.1% +/- 1.3% at 5 years; P = .41) between patients with and without BCR-ABL1–like ALL. CONCLUSION Patients who have BCR-ABL1–like ALL with poor initial treatment response can be salvaged with MRD-based risk-directed therapy and may benefit from identification of kinase-activating lesions for targeted therapies.
Knowledge Security Risk Management in Contemporary Companies -- Toward a Proactive Approach

Although emerging organizational knowledge systems, such as social media, are widely researched, related knowledge security risks have received less attention. Traditional information security management models tend to concentrate on the technological viewpoint to secure existing information assets. However, the use of contemporary approaches for knowledge creation and sharing offer new important possibilities for making use of internal and external knowledge. Simultaneously, their implementation involves changes in technologies, as well as a change in work processes and communications. Hence, knowledge security risk management should be developed from the current focus on relatively static containers and information assets toward more proactive management of the potential future risks of knowledge sharing. This paper introduces a proactive process for managing knowledge security risks and reports experiences of its use by professionals with experience in various topics of information and knowledge security.
Clustering microarray data using fuzzy clustering with viewpoints

This paper studies the application of fuzzy clustering with viewpoints in order to cluster cell samples according to their gene expression profile. This method combines fuzzy clustering with external domain knowledge represented by the so-called viewpoints. The viewpoints that we employ are obtained from previously available expression data. The method was compared to the clustering algorithms of k-means, fuzzy c-means, affinity propagation, as well as a method of clustering microarray data that is based on prior biological knowledge, and has shown comparable/improved results over them.
East African origins for Madagascan chickens as indicated by mitochondrial DNA

The colonization of Madagascar by Austronesian-speaking people during AD 50–500 represents the most westerly point of the greatest diaspora in prehistory. A range of economically important plants and animals may have accompanied the Austronesians. Domestic chickens (Gallus gallus) are found in Madagascar, but it is unclear how they arrived there. Did they accompany the initial Austronesian-speaking populations that reached Madagascar via the Indian Ocean or were they late arrivals with Arabian and African sea-farers? To address this question, we investigated the mitochondrial DNA control region diversity of modern chickens sampled from around the Indian Ocean rim (Southeast Asia, South Asia, the Arabian Peninsula, East Africa and Madagascar). In contrast to the linguistic and human genetic evidence indicating dual African and Southeast Asian ancestry of the Malagasy people, we find that chickens in Madagascar only share a common ancestor with East Africa, which together are genetically closer to South Asian chickens than to those in Southeast Asia. This suggests that the earliest expansion of Austronesian-speaking people across the Indian Ocean did not successfully introduce chickens to Madagascar. Our results further demonstrate the complexity of the translocation history of introduced domesticates in Madagascar.