Miracle-dz/UniFAR-FTUs huggingface dataset:
Pattern synthesis from singular solutions in the Debye limit: helical waves and twisted toroidal scroll structures

Applying the Debye limit to a suitable superposition of singular solutions of the linear two-component reaction-diffusion equations in three dimensions leads to helical and twisted toroidal scroll waves of constant concentration. An integral representation of the solutions of the Helmholtz equation in toroidal coordinates establishes a connection between helical and toroidal waves.
Rich goal types in agent programming

Goals are central to the design and implementation of intelligent software agents. Much of the literature on goals and reasoning about goals in agent programming frameworks only deals with a limited set of goal types, typically achievement goals, and sometimes maintenance goals. In this paper we extend a previously proposed unifying framework for goals with additional richer goal types that are explicitly represented as Linear Temporal Logic (LTL) formulae. We show that these goal types can be modelled as a combination of achieve and maintain goals. This is done by providing an operationalization of these new goal types, and showing that the operationalization generates computation traces that satisfy the temporal formula.
Collective competence as an ability to make sense

Many contemporary organisations takes on the character of distributed knowledge systems (Tsoukas 1996). Within such systems, knowledge and action may be co-ordinated by means of project work. A project can be understood in terms of a time-limited and collective task demanding and incorporating knowledge and competencies from a number of people with different knowledge bases. The success of interdisciplinary project teams is dependent upon their ability to co-ordinate different knowledge bases, which, I suggest, can be described as an ability to reach a state of collective competence. As shown by Dougherty, this is not an easy undertaking since there are often fundamental differences in knowledge and perspectives among different parts of the organisation (Dougherty 1992). A number of empirical studies using the conceptual lenses of ‘collective competence’ have been presented, see e.g. (Weick 1993), (Weick and Roberts 1993) and (Hansson 1998). However, these studies are undertaken in contexts with characteristics that differ in important aspects from the characteristics of a project context. Therefore, this paper focus on how we are able to understand collective competence in a project context, i.e. on how co-ordination between different knowledge bases could be achieved in situations that are less characterised by repeated and close co-operation. This paper is based on an empirical study of a development project where a number of different knowledge bases had to be co-ordinated. As it turned out, different project members had different interpretations of the target as well as different opinions on how it should be reached and how each one should play out his / her role in order to contribute to its fulfilment. In order to reach the target, project members had to make sense of the situation to be able to co-ordinate their different perspectives. Using this as a point of departure the paper elaborates on the significance of the ‘meeting’ as an arena for the co-ordination of their activities and as an arena for the constitution of collective competence in a project context.
BIST enhancement for detecting bit/byte write enable faults in SOC SRAMs

The continued increase of the integration density of systems on chip (SoCs) and the number of embedded memory blocks in them, together with the continued technology scaling, increases their sensitivity to a variety of potential manufacturing (new) defects. Standard march tests are usually used to achieve a good fault/defect coverage. This paper presents an experiment in diagnosing defects in the circuitry responsible for the realization of bit, byte or group write enable in memories. First defects in such circuitry are analyzed, and fault models together with an appropriate test algorithm are presented. Subsequently, the test is added to an existing BIST engine to target the bit/byte write enable faults. The preliminary silicon results of two experiments are presented. They validate some of the targeted fault models and show the importance of considering bit/byte write enable faults for high outgoing product quality.
Towards Understanding Social Influence in On-Line Social Networks

On-line social network sites provide an excellent platform for studying social influence among on-line friends. One of the crucial factors in analyzing social influence is conformity. Conformity can be defined as the act of matching attitudes, beliefs, and behaviors to group norms. This paper analyzed the level of conformity of 175 Facebook users, mostly college students, through an experimental study using the Facebook Graph API protocol and a follow-up user survey. The study was designed as an exploratory-based research relying on factor analysis. We discovered that a high level of posting activity on Facebook is positively related to the subject conformity.
The Role of Schizotypy in the Study of the Etiology of Schizophrenia Spectrum Disorders

Schizotypy provides a useful construct for understanding the development of schizophrenia spectrum disorders. As research on the epidemiology of psychotic symptoms and clinical risk for psychosis has expanded, conceptual challenges have emerged to comprehend the nature and borders of the space comprised between personality variation and psychosis. Schizotypy is considered in light of these more recent constructs. It is suggested that rather than being superseded by them due to their higher specificity and predictive power for transition to psychosis, schizotypy integrates them as it constitutes a dynamic continuum ranging from personality to psychosis. The advantages of schizotypy for studying schizophrenia etiology are discussed (eg, it facilitates a developmental approach and the identification of causal, resilience, and compensating factors and offers a multidimensional structure that captures etiological heterogeneity). An overview of putative genetic, biological, and psychosocial risk factors is presented, focusing on communalities and differences between schizotypy and schizophrenia spectrum disorders. The found notable overlap supports etiological continuity, and, simultaneously, differential findings appear that are critical to understanding resilience to schizophrenia. For example, discrepant findings in genetic studies might be interpreted as suggestive of sets of independent genetic factors playing a differential role in schizotypy and schizophrenia: some would influence variation specifically on schizotypy dimensions (ie, high vs low schizotypy, thereby increasing proneness to psychosis), some would confer unspecific liability to disease by impacting neural properties and susceptibility to environmental factors (ie, high vs low resilience to disorder) and some might contribute to disease–specific characteristics. Finally, schizotypy’s promise for studying gene-environment interactions is considered.
Understanding the Usage of Content in a Mental Health Intervention for Depression: An Analysis of Log Data

Background Web-based interventions for the early treatment of depressive symptoms can be considered effective in reducing mental complaints. However, there is a limited understanding of which elements in an intervention contribute to effectiveness. For efficiency and effectiveness of interventions, insight is needed into the use of content and persuasive features. Objective The aims of this study were (1) to illustrate how log data can be used to understand the uptake of the content of a Web-based intervention that is based on the acceptance and commitment therapy (ACT) and (2) to discover how log data can be of value for improving the incorporation of content in Web-based interventions. Methods Data from 206 participants (out of the 239) who started the first nine lessons of the Web-based intervention, Living to the Full, were used for a secondary analysis of a subset of the log data of the parent study about adherence to the intervention. The log files used in this study were per lesson: login, start mindfulness, download mindfulness, view success story, view feedback message, start multimedia, turn on text-message coach, turn off text-message coach, and view text message. Differences in usage between lessons were explored with repeated measures ANOVAs (analysis of variance). Differences between groups were explored with one-way ANOVAs. To explore the possible predictive value of the login per lesson quartiles on the outcome measures, four linear regressions were used with login quartiles as predictor and with the outcome measures (Center for Epidemiologic Studies—Depression [CES-D] and the Hospital Anxiety and Depression Scale—Anxiety [HADS-A] on post-intervention and follow-up) as dependent variables. Results A significant decrease in logins and in the use of content and persuasive features over time was observed. The usage of features varied significantly during the treatment process. The usage of persuasive features increased during the third part of the ACT (commitment to value-based living), which might indicate that at that stage motivational support was relevant. Higher logins over time (9 weeks) corresponded with a higher usage of features (in most cases significant); when predicting depressive symptoms at post-intervention, the linear regression yielded a significant model with login quartile as a significant predictor (explained variance is 2.7%). Conclusions A better integration of content and persuasive features in the design of the intervention and a better intra-usability of features within the system are needed to identify which combination of features works best for whom. Pattern recognition can be used to tailor the intervention based on usage patterns from the earlier lessons and to support the uptake of content essential for therapy. An adaptable interface for a modular composition of therapy features supposes a dynamic approach for Web-based treatment; not a predefined path for all, but a flexible way to go through all features that have to be used.
3D positioning algorithm for low cost mobile robots

A new 3D positioning algorithm for low cost robots is proposed. The algorithm is based on a Finite State Machine to estimate the position and orientation of the robot. The system sets dynamically the parameters of the algorithm and makes it independent of the noise in the sensors. The algorithm has been tested for differential wheel drive robots, however it can be used with different types of robots in a simple way. To improve the accuracy of the system, a new reference system based on the accelerometer of the robot is presented which reduces the accumulative error that the odometry produces.
Pulling Together or Apart: Factors Influencing a School's Ability To Learn.

This paper focuses on a case study of an alternative school for young offenders. It describes the efforts of organizational members to bring about improvement by facilitating organizational learning. The case study builds on current research related to organizational learning and team leadership in educational settings and attempts to answer the following questions: (1) What processes and factors influence organizational learning? and (2) How does a leadership approach influence organizational learning? The paper reports the findings of a 2-year case study of an alternative school that houses 30-35 students between the ages of 12-16 years. Data sources consist of interviews, surveys, document analysis, field notes, and feedback from members of a leadership team. Results point out several factors that facilitate organizational learning, the strongest of which is the existence of an organizational learning leadership (OLL) team whose primary function is to promote organizational learning. The research also demonstrates the difficulty of changing the existing culture of leadership at the school. The alternative school learned through positive factors such as the OLL team, action research, individual learning, and distributed leadership. (Contains 38 references.) (DFR) Reproductions supplied by EDRS are the best that can be made from the original document. Pulling Together or Apart: Factors Influencing a School's Ability to Learn
CSF Biomarkers

With an ever growing population of aged individuals who are at risk of developing Alzheimer’s disease (AD), there is an urgent need for a sensitive, specific and preferably non-invasive diagnostic standard of disease progression. Diagnosis of AD is still largely based on exclusion criteria of secondary causes and other forms of dementia with similar clinical pictures, than the diagnostic accuracy of AD is low. Recent research focused the attention to biochemical diagnostic markers (biomarkers) as they are very important indicators of normal and abnormal biological processes. Molecular aberrations in the AD brain are reflected in the cerebrospinal fluid (CSF) where three candidate biomarkers have recently been identified: total tau protein, amyloid -protein 1-42 and tau protein phosphorylated at AD-specific epitopes. The sensitivity and specificity of these data are able for discrimination of AD patients from controls. Here, we review the recent literature on biochemical biomarkers and discuss their predictive value as indicative for disease vulnerability to detect individuals at risk for AD and to determine the clinical efficacy of novel, disease-modifying strategies. According to the literature analysis reported in the present review, we can conclude that the combination of the CSF biomarkers and their ratios may significantly increase the specificity and the accuracy of AD diagnosis.
Estimation of distributions, moments and quantiles in deconvolution problems

When using the bootstrap in the presence of measurement error, we must first estimate the target distribution function; we cannot directly resample, since we do not have a sample from the target. These and other considerations motivate the development of estimators of distributions, and of related quantities such as moments and quantiles, in errors-in-variables settings. We show that such estimators have curious and unexpected properties. For example, if the distributions of the variable of interest, W. say, and of the observation error are both centered at zero, then the rate of convergence of an estimator of the distribution function of W can be slower at the origin than away from the origin. This is an intrinsic characteristic of the problem, not a quirk of particular estimators; the property holds true for optimal estimators.
A Survey of Cyclical Effects in Credit Risk Measurement Models

We survey both academic and proprietary models to examine how macroeconomic and systematic risk effects are incorporated into measures of credit risk exposure. Many models consider the correlation between the probability of default (PD) and cyclical factors. Few models adjust loss rates (loss given default) to reflect cyclical effects. We find that the possibility of systematic correlation between PD and LGD is also neglected in currently available models.
FLD-based detection of re-compressed speech signals

Prior works on re-quantization detection were mainly focused on still images and videos, implying that the involved quantization is uniform. In this paper, we examine non-uniform re-quantization, and then investigate the automatic detection of re-compressed speech signals. Based on Fisher Linear Discriminant (FLD), two detection algorithms are described in the time-domain and in the DFT-domain respectively. Comparative experiments indicate that both detection algorithms produce reliable results with AUC values higher than 0.9744 for a set of different experimental setups. In general, time-domain detection performs slightly better than DFT-domain detection. However, the latter is superior in the less dimensionality of input vectors.
THE EXTRACTION OF COASTLINE USING OBIA AND GIS

The aim of the paper was to test the possibility of using object based image analyses of Landsat satellite data for worldwide assessment of sea coast changes over time. The coastline in this project was defined as the seaward margin of dunes or land vegetation. The proposed method uses Red and IRed channels of Landsat images for segmentation. The rule based classification of segmented objects is supported by DEM and wind fetch data modeled in GIS. The coastline extraction from polygons classified as sedimentary beaches are done by designed GIS tool.The results are used to discuss the usefulness of proposed method and to present some coastline changes in the southern Baltic along the polish coast.
Investigation and Comparison of the Preprocessing Algorithms for Microarray Analysis for Robust Gene Expression Calculation and Performance Analysis of Technical Replicates

Preprocessing of microarray data involves the necessary steps of background correction, normalization and summarization of the raw intensity data obtained from cDNA or oligo-arrays before statistical analysis. Several algorithms, namely RMA, dChip, and MAS5 exist for the preprocessing of Affymetrix microarray data. Previous studies have identified RMA as one of most accurate algorithms while MAS5 was characterized with lower accuracy and sensitivity levels. In this study, performance of different preprocessing algorithms have been compared in terms of ROC characteristics of pairwise intensity differences of microarray replicates. Our findings indicated that all three algorithms predicted in similar order the quality of the technical replicates obtained from a selected set of latin square experiments. On the other hand, RMA exhibited higher performance in terms of accuracy by maximizing the area under the receiver operating curve. The proposed method also is useful for detection of global and/or local artifacts associated within the technical replicas of a microarray experiment. Therefore this study is unique in the sense that it provides an extensive investigation and comparison of preprocessing algorithms and proposes a novel method for the detection and identification of fine technical replicate pair
Contribution of Impaired Mitochondrial Autophagy to Cardiac Aging: Mechanisms and Therapeutic Opportunities

The prevalence of cardiovascular disease increases with advancing age. Although long-term exposure to cardiovascular risk factors plays a major role in the etiopathogenesis of cardiovascular disease, intrinsic cardiac aging enhances the susceptibility to developing heart pathologies in late life. The progressive decline of cardiomyocyte mitochondrial function is considered a major mechanism underlying heart senescence. Damaged mitochondria not only produce less ATP but also generate increased amounts of reactive oxygen species and display a greater propensity to trigger apoptosis. Given the postmitotic nature of cardiomyocytes, the efficient removal of dysfunctional mitochondria is critical for the maintenance of cell homeostasis, because damaged organelles cannot be diluted by cell proliferation. The only known mechanism whereby mitochondria are turned over is through macroautophagy. The efficiency of this process declines with advancing age, which may play a critical role in heart senescence and age-related cardiovascular disease. The present review illustrates the putative mechanisms whereby alterations in the autophagic removal of damaged mitochondria intervene in the process of cardiac aging and in the pathogenesis of specific heart diseases that are especially prevalent in late life (eg, left ventricular hypertrophy, ischemic heart disease, heart failure, and diabetic cardiomyopathy). Interventions proposed to counteract cardiac aging through improvements in macroautophagy (eg, calorie restriction and calorie restriction mimetics) are also presented.
Two-body transients in coupled atomic-molecular bose-einstein condensates.

We discuss the dynamics of an atomic Bose-Einstein condensate when pairs of atoms are converted into molecules by single-color photoassociation. Three main regimes are found, and it is shown that they can be understood on the basis of time-dependent two-body theory. In particular, the so-called rogue dissociation regime [Phys. Rev. Lett. 88, 090403 (2002)10.1103/PhysRevLett.88. 090403], which has a density-dependent limit on the photoassociation rate, is identified with a transient regime of the two-atom dynamics exhibiting universal properties. Finally, we illustrate how these regimes could be explored by photoassociating condensates of alkaline-earth atoms.
Novel Use of Proton Magnetic Resonance Spectroscopy (1HMRS) to Non-Invasively Assess Placental Metabolism

Background Placental insufficiency is a major cause of antepartum stillbirth and fetal growth restriction (FGR). In affected pregnancies, delivery is expedited when the risks of ongoing pregnancy outweigh those of prematurity. Current tests are unable to assess placental function and determine optimal timing for delivery. An accurate, non-invasive test that clearly defines the failing placenta would address a major unmet clinical need. Proton magnetic resonance spectroscopy (1H MRS) can be used to assess the metabolic profile of tissue in-vivo. In FGR pregnancies, a reduction in N-acetylaspartate (NAA)/choline ratio and detection of lactate methyl are emerging as biomarkers of impaired neuronal metabolism and fetal hypoxia, respectively. However, fetal brain hypoxia is a late and sometimes fatal event in placental compromise, limiting clinical utility of brain 1H MRS to prevent stillbirth. We hypothesised that abnormal placental 1H MRS may be an earlier biomarker of intrauterine hypoxia, affording the opportunity to optimise timing of delivery in at-risk fetuses. Methods and Findings We recruited three women with severe placental insufficiency/FGR and three matched controls. Using a 3T MR system and a combination of phased-array coils, a 20×20×40 mm1H MRS voxel was selected along the ‘long-axis’ of the placenta with saturation bands placed around the voxel to prevent contaminant signals. A significant choline peak (choline/lipid ratio 1.35–1.79) was detected in all healthy placentae. In contrast, in pregnancies complicated by FGR, the choline/lipid ratio was ≤0.02 in all placentae, despite preservation of the lipid peak (p<0.001). Conclusions This novel proof-of-concept study suggests that in severe placental insufficiency/FGR, the observed 60-fold reduction in the choline/lipid ratio by 1H MRS may represent an early biomarker of critical placental insufficiency. Further studies will determine performance of this test and the potential role of 1H-MRS in the in-vivo assessment of placental function to inform timing of delivery.
A review of an information extraction technique approach for automatic short answer grading

The requirement for automatic short answer grading (ASAG) system brings researchers to discover more knowledge about this field. Many techniques have been developed to reach the highest accuration. It can be processed by following stages: creating data set, pre-processing, model building, grading, and model evaluation. One of the techniques which commonly used is information extraction technique. Information extraction is a technique that employing finding fact on the student answers as patterns and then matches these to the teacher answer. The accuration is pointed out in computer and human raters agreement. The goal of this paper is to present a review of several ASAG research which using information extraction technique. However, this paper does not conclude the best method which can be used for general cases.