Miracle-dz/UniFAR-FTUs huggingface dataset:
A benchmark set extension and comparative study for the HyFlex framework

In this work we conduct a comparative study of several publicly available, state-of-the-art hyper-heuristics for HyFlex in order to assess their generality across domains. To this purpose we extend the HyFlex benchmark set with 3 new problem domains: The 0-1 Knap Sack, Quadratic Assignment and Max-Cut Problem. To our knowledge, this is the first public extension of the benchmark since the CHeSC 2011 competition. In addition, this is the first study testing the Fair-Share Iterated Local Search (FS-ILS) method, designed in prior research, using a semi-automated design approach, on new unseen problem domains. We show that, of the methods compared, Adap-HH (CHeSC 2011 winner) clearly perfoms the most consistently, overall. In addition, we identify a weakness of, as well as a way to further simplify the FS-ILS method. Finally, we found that, overall, the state-of-the-art methods compared, generalized much better than a naive baseline.
Ultrastructural analysis of autophagosome organization using mammalian autophagy-deficient cells

ABSTRACT Autophagy is mediated by a unique organelle, the autophagosome. Autophagosome formation involves a number of autophagy-related (ATG) proteins and complicated membrane dynamics. Although the hierarchical relationships of ATG proteins have been investigated, how individual ATG proteins or their complexes contribute to the organization of the autophagic membrane remains largely unknown. Here, systematic ultrastructural analysis of mouse embryonic fibroblasts (MEFs) and HeLa cells deficient in various ATG proteins reveals that the emergence of the isolation membrane (phagophore) requires FIP200 (also known as RB1CC1), ATG9A and phosphatidylinositol (PtdIns) 3-kinase activity. By contrast, small premature isolation-membrane-like and autophagosome-like structures were generated in cells lacking VMP1 and both ATG2A and ATG2B, respectively. The isolation membranes could elongate in cells lacking ATG5, but did not mature into autophagosomes. We also found that ferritin clusters accumulated at the autophagosome formation site together with p62 (also known as SQSTM1) in autophagy-deficient cells. These results reveal the specific functions of these representative ATG proteins in autophagic membrane organization and ATG-independent recruitment of ferritin to the site of autophagosome formation.
Extracting process graphs from medical text data

In this work a natural language processing workflow to extract sequential activities from large collections of medical text documents is developed. The approach utilizes graph structures to process, link and assess activities found in the documents. * Contact: aniekler@informatik.uni-leipzig.de relation extraction, natural language processing, graph processing,
Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets

We propose Impatient Deep Neural Networks (DNNs) which deal with dynamic time budgets during application. They allow for individual budgets given a priori for each test example and for anytime prediction, i.e., a possible interruption at multiple stages during inference while still providing output estimates. Our approach can therefore tackle the computational costs and energy demands of DNNs in an adaptive manner, a property essential for real-time applications. Our Impatient DNNs are based on a new general framework of learning dynamic budget predictors using risk minimization, which can be applied to current DNN architectures by adding early prediction and additional loss layers. A key aspect of our method is that all of the intermediate predictors are learned jointly. In experiments, we evaluate our approach for different budget distributions, architectures, and datasets. Our results show a significant gain in expected accuracy compared to common baselines.
Text joins for data cleansing and integration in an RDBMS

An organization's data records are often noisy because of transcription errors, incomplete information, lack of standard formats for textual data or combinations thereof. A fundamental task in a data cleaning system is matching textual attributes that refer to the same entity (e.g., organization name or address). This matching is effectively performed via the cosine similarity metric from the information retrieval field. For robustness and scalability, these "text joins" are best done inside an RDBMS, which is where the data is likely to reside. Unfortunately, computing an exact answer to a text join can be expensive. We propose an approximate, sampling-based text join execution strategy that can be robustly executed in a standard, unmodified RDBMS.
Local and Group Interaction in Prisoners''Dilemma Experiments-Imitate Locally

This study investigates experimentally the effects of locality on learning and strategic behaviour in a repeated prisoners’ dilemma. We compare a simple situation that models space (players interact only with their neighbours) with one that does not (players interact with all members of the population). Within this context different information conditions are studied. We find that imitation, while assumed to be a driving force in many models of spatial evolution, is a negligible factor in the experiment. Behaviour is driven by reinforcement learning and, under specific conditions, strategic behaviour.
GLUT4 and Transferrin Receptor Are Differentially Sorted Along the Endocytic Pathway in CHO Cells

The trafficking of GLUT4, a facilitative glucose transporter, is examined in transfected CHO cells. In previous work, we expressed GLUT4 in neuroendocrine cells and fibroblasts and found that it was targeted to a population of small vesicles slightly larger than synaptic vesicles (Herman, G.A, F. Bonzelius, A.M. Cieutat, and R.B. Kelly. 1994. Proc. Natl. Acad. Sci. USA. 91: 12750–12754.). In this study, we demonstrate that at 37°C, GLUT4-containing small vesicles (GSVs) are detected after cell surface radiolabeling of GLUT4 whereas uptake of radioiodinated human transferrin does not show appreciable accumulation within these small vesicles. Immunofluorescence microscopy experiments show that at 37°C, cell surface–labeled GLUT4 as well as transferrin is internalized into peripheral and perinuclear structures. At 15°C, endocytosis of GLUT4 continues to occur at a slowed rate, but whereas fluorescently labeled GLUT4 is seen to accumulate within large peripheral endosomes, no perinuclear structures are labeled, and no radiolabeled GSVs are detectable. Shifting cells to 37°C after accumulating labeled GLUT4 at 15°C results in the reappearance of GLUT4 in perinuclear structures and GSV reformation. Cytosol acidification or treatment with hypertonic media containing sucrose prevents the exit of GLUT4 from peripheral endosomes as well as GSV formation, suggesting that coat proteins may be involved in the endocytic trafficking of GLUT4. In contrast, at 15°C, transferrin continues to traffic to perinuclear structures and overall labels structures similar in distribution to those observed at 37°C. Furthermore, treatment with hypertonic media has no apparent effect on transferrin trafficking from peripheral endosomes. Double-labeling experiments after the internalization of both transferrin and surface-labeled GLUT4 show that GLUT4 accumulates within peripheral compartments that exclude the transferrin receptor (TfR) at both 15° and 37°C. Thus, GLUT4 is sorted differently from the transferrin receptor as evidenced by the targeting of each protein to distinct early endosomal compartments and by the formation of GSVs. These results suggest that the sorting of GLUT4 from TfR may occur primarily at the level of the plasma membrane into distinct endosomes and that the organization of the endocytic system in CHO cells more closely resembles that of neuroendocrine cells than previously appreciated.
Airway Surface Dehydration Aggravates Cigarette Smoke-Induced Hallmarks of COPD in Mice

Introduction Airway surface dehydration, caused by an imbalance between secretion and absorption of ions and fluid across the epithelium and/or increased epithelial mucin secretion, impairs mucociliary clearance. Recent evidence suggests that this mechanism may be implicated in chronic obstructive pulmonary disease (COPD). However, the role of airway surface dehydration in the pathogenesis of cigarette smoke (CS)-induced COPD remains unknown. Objective We aimed to investigate in vivo the effect of airway surface dehydration on several CS-induced hallmarks of COPD in mice with airway-specific overexpression of the β-subunit of the epithelial Na+ channel (βENaC). Methods βENaC-Tg mice and wild-type (WT) littermates were exposed to air or CS for 4 or 8 weeks. Pathological hallmarks of COPD, including goblet cell metaplasia, mucin expression, pulmonary inflammation, lymphoid follicles, emphysema and airway wall remodelling were determined and lung function was measured. Results Airway surface dehydration in βENaC-Tg mice aggravated CS-induced airway inflammation, mucin expression and destruction of alveolar walls and accelerated the formation of pulmonary lymphoid follicles. Moreover, lung function measurements demonstrated an increased compliance and total lung capacity and a lower resistance and hysteresis in βENaC-Tg mice, compared to WT mice. CS exposure further altered lung function measurements. Conclusions We conclude that airway surface dehydration is a risk factor that aggravates CS-induced hallmarks of COPD.
A Structural Explanation of the Effects of Dissociated Glucocorticoids on Glucocorticoid Receptor Transactivation

There is a therapeutic need for glucocorticoid receptor (GR) ligands that distinguish between the transrepression and transactivation activity of the GR, the later thought to be responsible for side effects. These ligands are known as “dissociated glucocorticoids” (dGCs). The first published dGCs, RU24782 (9α-fluoro-11β-hydroxy-16α-methylpregna-21-thiomethyl-1,4-diene-3,20-dione) and RU24858 (9α-fluoro-11β-hydroxy-16α-methylpregna-21-cyanide-1,4-diene-3,20-dione), do not have the 17α-hydroxyl group that characterizes dexamethasone (Dex; 9α-fluoro-11β,17α,21-trihydroxy-16α-methylpregna-1,4-diene-3,20-dione), and they differ from one another by having C21-thiomethyl and C21-cyanide moieties, respectively. Our aim was therefore to establish the structural basis of their activity. Both RU24782 and RU24858 induced a transactivation activity highly dependent on the GR expression level but always lower than dexamethasone. They also display less ability than dexamethasone to trigger steroid receptor coactivator 1 (SRC-1) recruitment and histone H3 acetylation. Docking studies, validated by mutagenesis experiments, revealed that dGCs are not anchored by Gln642, in contrast to Dex, which is hydrogen bonded to this residue via its 17α-hydroxyl group. This contact is essential for SRC-1 recruitment and subsequent dexamethasone-induced GR transactivation, but not transrepression. The ability of dGCs to make contacts with Ile747, for both RU24858 and RU24782 and with Asn564 for RU24858 are not strong enough to maintain GR in a conformation able to efficiently recruit SRC-1, unless SRC-1 is overexpressed. Overall, our findings provide some structural guidelines for the synthesis of potential new dissociated glucocorticoids with a better therapeutic ratio.
A multiclass classification model for stock news based on structured data

Stock news plays an important role on market considering the timely dissemination of news will likely to affect a stock's price changes. Classifying stock news is very helpful for investors to make investment decisions. In this paper, we design and implement a structured data based classification model, which could be effectively applied to the field of stock news classification problem. The model firstly calculates the news correlation by using structured data, and then makes use of the parameter fitting method along with the output value of softmax regression model, after that, the final probability sequence is presented. The multi-label classification is realized by the method of selecting multi-labels. Finally, we compare the novel algorithm with a general algorithm, verifying the availability and accuracy of our classification method.
Novel Immunomodulators from Hard Ticks Selectively Reprogramme Human Dendritic Cell Responses

Hard ticks subvert the immune responses of their vertebrate hosts in order to feed for much longer periods than other blood-feeding ectoparasites; this may be one reason why they transmit perhaps the greatest diversity of pathogens of any arthropod vector. Tick-induced immunomodulation is mediated by salivary components, some of which neutralise elements of innate immunity or inhibit the development of adaptive immunity. As dendritic cells (DC) trigger and help to regulate adaptive immunity, they are an ideal target for immunomodulation. However, previously described immunoactive components of tick saliva are either highly promiscuous in their cellular and molecular targets or have limited effects on DC. Here we address the question of whether the largest and globally most important group of ticks (the ixodid metastriates) produce salivary molecules that specifically modulate DC activity. We used chromatography to isolate a salivary gland protein (Japanin) from Rhipicephalus appendiculatus ticks. Japanin was cloned, and recombinant protein was produced in a baculoviral expression system. We found that Japanin specifically reprogrammes DC responses to a wide variety of stimuli in vitro, radically altering their expression of co-stimulatory and co-inhibitory transmembrane molecules (measured by flow cytometry) and their secretion of pro-inflammatory, anti-inflammatory and T cell polarising cytokines (assessed by Luminex multiplex assays); it also inhibits the differentiation of DC from monocytes. Sequence alignments and enzymatic deglycosylation revealed Japanin to be a 17.7 kDa, N-glycosylated lipocalin. Using molecular cloning and database searches, we have identified a group of homologous proteins in R. appendiculatus and related species, three of which we have expressed and shown to possess DC-modulatory activity. All data were obtained using DC generated from at least four human blood donors, with rigorous statistical analysis. Our results suggest a previously unknown mechanism for parasite-induced subversion of adaptive immunity, one which may also facilitate pathogen transmission.
On the accuracy of short-term quality models for long-term quality prediction

With video services such as HTTP-based adaptive streaming, network congestion may result in quality fluctuations over several minutes. There is therefore a need for estimating the quality of long audiovisual sequences. This can be achieved by using short-term audiovisual quality models, which output quality scores for short periods of time, for instance 10 s. Temporal pooling such as averaging is typically applied on the short-term quality estimates for providing a quality score for a longer time period, for instance three minutes. With this modeling strategy, the performance of the overall quality model can be increased by improving both the short-term quality model and the temporal pooling strategy. However, depending on the temporal pooling strategy, and possibly the targeted test data obtained for long sequences, a small improvement of the short-term quality model may eventually not have any significant impact on the long-term quality estimates. This paper investigates this aspect by comparing the performance results of the combination of six short-term quality models with six different pooling strategies. Results show that the performance of well performing short term models is a good indicator of the performance of the long-term quality models, independently of the pooling strategy.
Character gazetteer for Named Entity Recognition with linear matching complexity

A large amount of unstructured data is produced daily through numerous media around us. Despite that computer systems are becoming more powerful, even the commodity hardware, processing of such data and gaining useful information in time efficient manner remains a problem. One of the domains in unstructured data processing is Natural Language Processing (NLP). NLP covers areas like information extraction, machine translation, word sense disambiguation, automated question answering, etc. All of these areas require fast and precise Named Entity Recognition (NER), which is not a trivial task because of the processed data size and heterogeneity. Our effort in this research area is to provide fast tokenization and precise NER with linear complexity. In this paper, we present a character gazetteer with linear tokenization as well as NER and compare its two tree data structure representations; i.e. multiway tree implemented by hash maps and first child-next sibling binary tree. Our measurements shows that one outperforms the other in processing time, while the other outperforms it in memory consumption efficiency.
Karyotypic change between diagnosis and relapse as a predictor of salvage therapy outcome in AML patients

Background Only a few patients who experience AML relapse derive lasting benefit from re-induction therapy. The utility of reassessing the disease karyotype at relapse is unclear. The main goals of this study were to identify prognostic factors for AML relapse and to determine the prognostic utility of karyotypic change between diagnosis and relapse as a variable for predicting response to salvage therapy for relapsed AML. Methods This retrospective study included 58 patients with relapsed AML treated at the Yonsei University College of Medicine between 2005 and 2010. Karyotypes at both diagnosis and relapse were available for 45 patients (77%). A change in karyotype at relapse was observed in 17 of 45 cases (37%), and no change was noted in 28 of 45 cases (62%). Results Karyotypic changes between diagnosis and relapse were associated with the response rate (RR) to salvage therapy (P=0.016). Overall survival (OS) and event-free survival (EFS) in the group with karyotypic changes between diagnosis and relapse were significantly different from those with no karyotypic changes (P=0.004 and P=0.010, respectively). We applied multiple multivariate Cox regression analyses to identify independent prognostic factors for overall response (OR), OS, and EFS. A change in karyotype between diagnosis and relapse was significantly associated with OS (P=0.023; RR=2.655) and EFS (P=0.033; RR=2.831). Conclusion Karyotypic changes between the diagnosis and relapse of AML could be used to predict outcomes and tailor clinical and biological therapeutic strategies for relapsed AML patients.
Structured Adaptive Regularization of Weight Vectors for a Robust Grapheme-to-Phoneme Conversion Model

Grapheme-to-phoneme (g2p) conversion, used to estimate the pronunciations of out-of-vocabulary (OOV) words, is a highly important part of recognition systems, as well as text-to-speech systems. The current state-of-the-art approach in g2p conversion is structured learning based on the Margin Infused Relaxed Algorithm (MIRA), which is an online discriminative training method for multiclass classification. However, it is known that the aggressive weight update method of MIRA is prone to overfitting, even if the current example is an outlier or noisy. Adaptive Regularization of Weight Vectors (AROW) has been proposed to resolve this problem for binary classification. In addition, AROW’s update rule is simpler and more efficient than that of MIRA, allowing for more efficient training. Although AROW has these advantages, it has not been applied to g2p conversion yet. In this paper, we first apply AROW on g2p conversion task which is structured learning problem. In an evaluation that employed a dataset generated from the collective knowledge on the Web, our proposed approach achieves a 6.8% error reduction rate compared to MIRA in terms of phoneme error rate. Also the learning time of our proposed approach was shorter than that of MIRA in almost datasets. key words: g2p conversion, out-of-vocabulary word, online discriminative training, structured learning, AROW
The integrin cytoplasmic domain-associated protein ICAP-1 binds and regulates Rho family GTPases during cell spreading

Using two-hybrid screening, we isolated the integrin cytoplasmic domain-associated protein (ICAP-1), an interactor for the COOH terminal region of the β1A integrin cytoplasmic domain. To investigate the role of ICAP-1 in integrin-mediated adhesive function, we expressed the full-length molecule in NIH3T3 cells. ICAP-1 expression strongly prevents NIH3T3 cell spreading on extracellular matrix. This inhibition is transient and can be counteracted by coexpression of a constitutively activated mutant of Cdc42, suggesting that ICAP-1 acts upstream of this GTPase. In addition, we found that ICAP-1 binds both to Cdc42 and Rac1 in vitro, and its expression markedly inhibits activation of these GTPases during integrin-mediated cell adhesion to fibronectin as detected by PAK binding assay. In the attempt to define the molecular mechanism of this inhibition, we show that ICAP-1 reduces both the intrinsic and the exchange factor–induced dissociation of GDP from Cdc42; moreover, purified ICAP-1 displaces this GTPase from cellular membranes. Together, these data show for the first time that ICAP-1 regulates Rho family GTPases during integrin-mediated cell matrix adhesion, acting as guanine dissociation inhibitor.
Sex-Prediction from Periocular Images Across Multiple Sensors and Spectra

In this paper, we provide a comprehensive analysis of periocular-based sex-prediction (commonly referred to as gender classification) using state-of-the-art machine learning techniques. In order to reflect a more challenging scenario where periocular images are likely to be obtained from an unknown source, i.e. sensor, convolutional neural networks are trained on fused sets composed of several near-infrared (NIR) and visible wavelength (VW) image databases. In a cross-sensor scenario within each spectrum an average classification accuracy of approximately 85% is achieved. When sex-prediction is performed across spectra an average classification accuracy of about 82% is obtained. Finally, a multi-spectral sex-prediction yields a classification accuracy of 83% on average. Compared to proposed works, obtained results provide a more realistic estimation of the feasibility to predict a subject's sex from the periocular region.
Level locomotion in wood ants: evidence for grounded running

In order to better understand the strategies of locomotion in small insects, we have studied continuous level locomotion of the wood ant species Formica polyctena. We determined the three-dimensional centre of mass kinematics during the gait cycle and recorded the ground reaction forces of single legs utilising a self-developed test site. Our findings show that the animals used the same gait dynamics across a wide speed range without dissolving the tripodal stride pattern. To achieve higher velocities, the ants proportionally increased stride length and stepping frequency. The centre of mass energetics indicated a bouncing gait, in which horizontal kinetic and gravitational potential energy fluctuated in close phase. We determined a high degree of compliance especially in the front legs, as the effective leg length was nearly halved during the contact phase. This leads to only small vertical oscillations of the body, which are important in maintaining ground contact. Bouncing gaits without aerial phases seem to be a common strategy in small runners and can be sufficiently described by the bipedal spring-loaded inverted pendulum model. Thus, with our results, we provide evidence that wood ants perform ‘grounded running’.