Miracle-dz/UniFAR-FTUs huggingface dataset:
De bodemgesteldheid van het Oudland van Veurne Ambacht

Belgian holocene marine deposits, similar to those in Zeeland, were surveyed. The formation of this area in south-west Belgium was associated with the Atlantic (Old Marine Deposits) and Subatlantic marine transgressions (Duinkerken I-III); in the Subatlantic Period sands and clays were deposited on the surface peat (dating from the Subboreal). The same distinction of the coastal area as in the south-west of the Netherlands could be made along the Belgian coast: Old Land, Middle Land and New Land soil landscapes, each with their own sedimentary and geographical history. Soils were classified according to this sedimentary history (physiography and morphology system), Soil formation in this area was closely correlated with hydrology, which governed decalcification. The relation between soils and crop production was studied (mainly field crops), using a method developed by Belgian soil scientists. The position of the settlements in relation to agricultural problems was described and measures to improve agriculture (manuring, treatment, drainage) were recommended.
The Polarity Protein Pals1 Regulates Radial Sorting of Axons

Myelin is essential for rapid and efficient action potential propagation in vertebrates. However, the molecular mechanisms regulating myelination remain incompletely characterized. For example, even before myelination begins in the PNS, Schwann cells must radially sort axons to form 1:1 associations. Schwann cells then ensheathe and wrap axons, and establish polarized, subcellular domains, including apical and basolateral domains, paranodes, and Schmidt-Lanterman incisures. Intriguingly, polarity proteins, such as Pals1/Mpp5, are highly enriched in some of these domains, suggesting that they may regulate the polarity of Schwann cells and myelination. To test this, we generated mice with Schwann cells and oligodendrocytes that lack Pals1. During early development of the PNS, Pals1-deficient mice had impaired radial sorting of axons, delayed myelination, and reduced nerve conduction velocities. Although myelination and conduction velocities eventually recovered, polyaxonal myelination remained a prominent feature of adult Pals1-deficient nerves. Despite the enrichment of Pals1 at paranodes and incisures of control mice, nodes of Ranvier and paranodes were unaffected in Pals1-deficient mice, although we measured a significant increase in the number of incisures. As in other polarized cells, we found that Pals1 interacts with Par3 and loss of Pals1 reduced levels of Par3 in Schwann cells. In the CNS, loss of Pals1 affected neither myelination nor the establishment of polarized membrane domains. These results demonstrate that Schwann cells and oligodendrocytes use distinct mechanisms to control their polarity, and that radial sorting in the PNS is a key polarization event that requires Pals1. SIGNIFICANCE STATEMENT This paper reveals the role of the canonical polarity protein Pals1 in radial sorting of axons by Schwann cells. Radial sorting is essential for efficient and proper myelination and is disrupted in some types of congenital muscular dystrophy.
Study of oil palm root architecture with variation of crop stage and soil type vulnerable to drought

Root arhitecture is affected by watertable level, characteristic of soil, organic matter and also the crop stages. Root architecture spread horizontally and vertically which each consist of primary, secondary, tertiary and quaternary downward root. The oil palm root observation with variation of crop stage and soil type showed that the root of oil palm plant year 2008 on spodosols soil spread along 650 cm horizontally from the trunk and penetrate downward in range of 9-28 cm vertically. Planted in the same type of soil, the root of oil palm plant year 2004 spread along 650 cm horizontally and reached to downward in a larger range from 3 to 57 cm vertically. As a comparison, the root architecture of oil palm on inceptisols soil established the range much greater vertically than the previous. The root of oil palm plant year 2008 spread along 640 cm horizontally and penetrate downward in range of 52-90 cm vertically. With the variation of crop age, the root of oil palm plant year 2003 spread along 650 cm horizontally and reached to downward in a larger range from 150 to 200 cm vertically. Based on this study, root architecture of oil palm was varied and need to be detailed. The precise root architecture of oil palm allows a better understanding on hydrological properties of oil palm root particularly which is cultivated on soil type vulnerable to drought. Referring to this root architecture, it was enable to develop the study on early drought detection of oil palm to optimise production and towards oil palm sustainability.
Maximal Structuring of Acyclic Process Models

This article addresses the transformation of a process model with an arbitrary topology into an equivalent structured process model. In particular, this article studies the subclass of process models that have no equivalent well-structured representation but which, nevertheless, can be partially structured into their maximally-structured representation. The transformations are performed under a behavioral equivalence notion that preserves the observed concurrency of tasks in equivalent process models. The article gives a full characterization of the subclass of acyclic process models that have no equivalent well-structured representation, but do have an equivalent maximally-structured one, as well as proposes a complete structuring method. Together with our previous results, this article completes the solution of the process model structuring problem for the class of acyclic process models.
Multivariate analyses in microbial ecology

Environmental microbiology is undergoing a dramatic revolution due to the increasing accumulation of biological information and contextual environmental parameters. This will not only enable a better identification of diversity patterns, but will also shed more light on the associated environmental conditions, spatial locations, and seasonal fluctuations, which could explain such patterns. Complex ecological questions may now be addressed using multivariate statistical analyses, which represent a vast potential of techniques that are still underexploited. Here, well-established exploratory and hypothesis-driven approaches are reviewed, so as to foster their addition to the microbial ecologist toolbox. Because such tools aim at reducing data set complexity, at identifying major patterns and putative causal factors, they will certainly find many applications in microbial ecology.
Authentication and Key Agreement Protocols Preserving Anonymity

Anonymity is a very important security feature in addition to authentication and key agreement features in communication protocols. In this paper, we propose two authentication and key agreement (AKA) protocols: the AKA protocol with user anonymity (UAP) and the AKA protocol with user and server anonymity (USAP). The proposed protocols have the following advantages: first of all, they preserve anonymity, which is a security feature that was ignored in most of the previously proposed AKA protocols; secondly, they exploit the difference in capabilities between resource constrained clients and highly resourceful servers and thus are suitable for wireless applications; thirdly, they resist known attacks; and finally, they perform better in terms of the number of messages and bits exchanged and computing time as compared to the previously proposed AKA protocols. For example, USAP preserves user and server anonymity, exchanges 3 messages with 1920 bits in total, and requires only 280 msec of processing time on the user side when implemented on Mitsubishis M16C microprocessor. Similarly, the UAP is scalable, preserves user anonymity, requires 440 msec, and exchanges 2560 bits.
S1P1 receptor directs the release of immature B cells from bone marrow into blood

S1P1 receptor expression is required for the egress of newly formed T cells from the thymus and exit of mature T and B cells from secondary lymphoid organs. In this study, we deleted the expression of the S1P1 receptor gene (S1pr1) in developing B cells in the bone marrow. Although B cell maturation within the bone marrow was largely normal in the B cell–specific S1pr1 knockout (B-S1pr1KO) mice, their newly generated immature B cells appeared in the blood at abnormally low numbers as compared with control mice. In the bone marrow of B-S1pr1KO mice, immature B cells in contact with the vascular compartment displayed increased apoptosis as compared with control mice. Forced expression of CD69, a negative regulator of S1P1 receptor expression, in developing bone marrow B cells also reduced the number of immature B cells in the blood. Attenuation of CXCR4 signaling, which is required for the proper retention of developing B cells in bone marrow, did not release immature B cells into the blood of B-S1pr1KO mice as effectively as in control mice. Our results indicate that the S1P1 receptor provides a signal necessary for the efficient transfer of newly generated immature B cells from the bone marrow to the blood.
Relation between baseline and on-treatment lipid parameters and first acute major coronary events in the Air Force/Texas Coronary Atherosclerosis Prevention Study (AFCAPS/TexCAPS).

BACKGROUND The Air Force/Texas Coronary Atherosclerosis Prevention Study (AFCAPS/TexCAPS) is the first primary-prevention study in a cohort with average total cholesterol (TC) and LDL cholesterol (LDL-C) and below-average HDL cholesterol (HDL-C). Treatment with lovastatin (20 to 40 mg/d) resulted in a 25% reduction in LDL-C and a 6% increase in HDL-C, as well as a 37% reduction in risk for first acute major coronary event (AMCE), defined as fatal or nonfatal myocardial infarction, unstable angina, or sudden cardiac death. This article describes the relation between baseline and on-treatment lipid and apolipoprotein (apo) parameters and subsequent risk for AMCEs. METHODS AND RESULTS With all available data from the entire 6605-patient cohort, a prespecified Cox backward stepwise regression model identified outcome predictors, and logistic regression models examined the relation between lipid variables and AMCE risk. Baseline LDL-C, HDL-C, and apoB were significant predictors of AMCE; only on-treatment apoB and the ratio of apoB to apoAI were predictive of subsequent risk; on-treatment LDL-C was not. When event rates were examined across tertiles of baseline lipids, a consistent benefit of treatment with lovastatin was observed. CONCLUSIONS Persons with average TC and LDL-C levels and below-average HDL-C may obtain significant clinical benefit from primary-prevention lipid modification. On-treatment apoB, especially when combined with apoAI to form the apoB/AI ratio, may be a more accurate predictor than LDL-C of risk for first AMCE.
Inactivation of various proteinase inhibitors and the complement system in human plasma by the 56-kilodalton proteinase from Serratia marcescens

The interaction of the 56-kilodalton (kDa) proteinase from Serratia marcescens with human plasma activated C1 (C1) inhibitor, alpha 2-antiplasmin, and antithrombin III was investigated. The 56-kDa proteinase was not affected by these inhibitors; on the contrary, all the inhibitors were inactivated by the 56-kDa proteinase within 2 to 6 h. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis indicated that all three inhibitors showed decreases in molecular weight of approximately 8,000 to 10,000 as a result of proteolytic cleavage by the 56-kDa proteinase. The 56-kDa proteinase also inactivated serum complement within 2 to 6 h. The loss of inhibitory activity caused by the 56-kDa proteinase, together with the effects of endogenous serine proteinases, may facilitate tissue destruction and inflammation.
Real-time emotions recognition system

This paper presents the experimental setup and methodology for a real-time emotions recognition system, based on the recent Intel RealSense 3D sensor, to identify six emotions: happiness, sadness, anger, surprise, fear, and neutral. The process includes the database construction, with 43 participants, based on facial features extraction and a multiclass Support Vector Machine classifier. The system was first tested offline using Linear kernel and Radial Basis Function (RBF) kernel. In the offline evaluation, the system performance was quantified in terms of confusion matrix, accuracy, sensitivity, specificity, Area Under the Curve, and Mathews Correlation Coefficient metrics. The RBF kernel achieved the best performance, with an average accuracy of 93.6%. Then, the real-time system was evaluated in a laboratorial setup, achieving an overall accuracy of 88%. The time required for the system to perform facial expression recognition efficiently is 1–3ms. The results, obtained by simulation and experimentally, point out that the present system can recognize facial expressions accurately.
Supporting developers with natural language queries

The feature list of modern IDEs is steadily growing and mastering these tools becomes more and more demanding, especially for novice programmers. Despite their remarkable capabilities, IDEs often still cannot directly answer the questions that arise during program comprehension tasks. Instead developers have to map their questions to multiple concrete queries that can be answered only by combining several tools and examining the output of each of them manually to distill an appropriate answer. Existing approaches have in common that they are either limited to a set of predefined, hardcoded questions, or that they require to learn a specific query language only suitable for that limited purpose. We present a framework to query for information about a software system using guided-input natural language resembling plain English. For that, we model data extracted by classical software analysis tools with an OWL ontology and use knowledge processing technologies from the Semantic Web to query it. We use a case study to demonstrate how our framework can be used to answer queries about static source code information for program comprehension purposes.
Respiration-Averaged CT for Attenuation Correction of PET Images – Impact on PET Texture Features in Non-Small Cell Lung Cancer Patients

Purpose We compared attenuation correction of PET images with helical CT (PET/HCT) and respiration-averaged CT (PET/ACT) in patients with non-small-cell lung cancer (NSCLC) with the goal of investigating the impact of respiration-averaged CT on 18F FDG PET texture parameters. Materials and Methods A total of 56 patients were enrolled. Tumors were segmented on pretreatment PET images using the adaptive threshold. Twelve different texture parameters were computed: standard uptake value (SUV) entropy, uniformity, entropy, dissimilarity, homogeneity, coarseness, busyness, contrast, complexity, grey-level nonuniformity, zone-size nonuniformity, and high grey-level large zone emphasis. Comparisons of PET/HCT and PET/ACT were performed using Wilcoxon signed-rank tests, intraclass correlation coefficients, and Bland-Altman analysis. Receiver operating characteristic (ROC) curves as well as univariate and multivariate Cox regression analyses were used to identify the parameters significantly associated with disease-specific survival (DSS). A fixed threshold at 45% of the maximum SUV (T45) was used for validation. Results SUV maximum and total lesion glycolysis (TLG) were significantly higher in PET/ACT. However, texture parameters obtained with PET/ACT and PET/HCT showed a high degree of agreement. The lowest levels of variation between the two modalities were observed for SUV entropy (9.7%) and entropy (9.8%). SUV entropy, entropy, and coarseness from both PET/ACT and PET/HCT were significantly associated with DSS. Validation analyses using T45 confirmed the usefulness of SUV entropy and entropy in both PET/HCT and PET/ACT for the prediction of DSS, but only coarseness from PET/ACT achieved the statistical significance threshold. Conclusions Our results indicate that 1) texture parameters from PET/ACT are clinically useful in the prediction of survival in NSCLC patients and 2) SUV entropy and entropy are robust to attenuation correction methods.
Experimentally validated repetitive-predictive control of a robot arm with constraints

A multivariable predictive-repetitive controller has recently been reported that uses a frequency response decomposition technique to detect the dominant frequency components in the reference signal for each output and embeds these in the controller. This paper addresses issues concerning the implementation of operational constraints on control signal amplitudes, their increments and on the plant outputs. The major contribution is an on-line solution developed using quadratic programming via identification of active constraints. Supporting experimental results from application to a 2D robotic system are also given.
Generation of graphical representations of student tracking data in course management systems

An approach of employing information visualisation to develop systems that facilitate instructors in Web-based distance learning is presented here. The paper describes a tool, called CourseVis, that uses multidimensional student tracking data collected by CMS and generates graphical representations that can be used by instructors to gain an understanding of what is happening in distance learning classes. The work followed a systematic approach that started from collecting the instructors' needs, produced some appropriate graphical representations of student tracking data, and evaluated the effectiveness, efficiency and usefulness of the proposed representations. The evaluation has shown that with CourseVis the instructors can identify tendencies in their classes, quickly discover individuals that need special attention, and are able to provide better support to their students.
ZINC 15 – Ligand Discovery for Everyone

Many questions about the biological activity and availability of small molecules remain inaccessible to investigators who could most benefit from their answers. To narrow the gap between chemoinformatics and biology, we have developed a suite of ligand annotation, purchasability, target, and biology association tools, incorporated into ZINC and meant for investigators who are not computer specialists. The new version contains over 120 million purchasable “drug-like” compounds – effectively all organic molecules that are for sale – a quarter of which are available for immediate delivery. ZINC connects purchasable compounds to high-value ones such as metabolites, drugs, natural products, and annotated compounds from the literature. Compounds may be accessed by the genes for which they are annotated as well as the major and minor target classes to which those genes belong. It offers new analysis tools that are easy for nonspecialists yet with few limitations for experts. ZINC retains its original 3D roots – all molecules are available in biologically relevant, ready-to-dock formats. ZINC is freely available at http://zinc15.docking. org.
A novel electric design for electromagnetic stimulation-the Slinky coil

A novel coil design for inductive electromagnetic stimulation of neural cells has been simulated and experimentally tested. This coil improves the focal effect of a magnetic stimulator, and it reduces its inductance, hence the efficiency of the system is improved. The basic structure of the device is derived from the popular "Slinky" toy. The actual device is formed by winding different numbers of loops forming a helical coil on a half torus. The loops are bunched at the axis of the torus. The coil, due to its geometry, generates a unique distribution of eddy currents in nearby tissues which is favorable compared to a solenoid type stimulator. This renders the Slinky coil more selective than conventional coils used for magnetic stimulation. The distribution of eddy currents was analyzed using Matlab, following Faraday's Law of Induction. Improved focality permits the current through the coil to be reduced for the same effect. In addition, the reduced inductance of the Slinky coil decreases the power requirement; thus, the improved efficiency of the system may allow the generation of bursts of pulses, and expand the utilization of the system to possible functional activation of certain neuro-muscular structures when peripheral nerves are stimulated. <<ETX>>
Projective geometry and feedback stabilization

The goal of this paper is to provide a geometric study of the well-posedness and stability concepts associated to the feedback control loops. The usefulness of Kleinian-view of geometry is emphasized and tools from matrix projective geometry are applied. It will be shown that Mobius transforms play a central role to arrive to the group structures that characterize the well posed and stable feedback connections of dynamic systems. The well-known Youla parametrization is obtained as a special case of this group of transforms.
Analysis of Bug Triage using Data Preprocessing (Reduction) Techniques

In the bug triage we have an unavoidable step of fixing the bugs which helps in correctly assigning a developer to a new bug. Text classification and binary classification techniques are applied to decrease the time cost in manual work and to enhance the working of automatic bug triage. We address the problem of data reduction and hence we combine the instance selection and the feature selection algorithms to simultaneously reduce the data scale and enhance the accuracy of the bug reports in the bug triage. We determine a predictive model to perform the algorithms which adds on to prioritize the developer to a new bug by extracting attributes and the bug data set from the historical table. By leveraging data mining techniques, mining software repositories can uncover interesting information in software repositories and solve realworld software problem like Eclipse, Mozilla and GNOME.
The Thing We Tried That Worked : Utile Distinctions for Relational Reinforcement Learning

This paper introduces a relational function approximation technique based on McCallum’s UTree algorithm (McCallum, 1995). We have extended the original approach to handle relational observations using an attribute graph of observable objects and relationships (McGovern et al., 2003). Furthermore, we address the inherent challenges that arise with a relational representation. We use stochastic sampling to manage the search space (Srinivasan, 1999), and sampling to address issues of autocorrelation (Jensen and Neville, 2002). We prevent the algorithm from growing an overly large and complex tree by incorporating Iterative Tree Induction’s approach (Utgoff, 1995). We compare Relational UTree’s performance with similar relational learning methods (Finney et al., 2002) (Driessens et al., 2001).
Measurement Bias from Address Aliasing

In this paper, we identify address aliasing as an important underlying mechanism causing measurement bias on modern Intel microarchitectures. By analyzing hardware performance counters, we show how bias arises from two external factors:size of environment variables, and characteristics of dynamically linked heap allocators. We demonstrate ways to deal with this type of bias, through runtime detection and correction of aliasing conditions. For heap allocators, we show that common implementations tend to give worst case alignment by default, favoring page alignment for large allocations. The performance impact of aliased memory accesses can be significant, causing up to a 2x performance degradation in already optimized code. Our results can enable new optimization strategies to account for this phenomenon.