Miracle-dz/UniFAR-FTUs huggingface dataset:
A method for developing agent-based models of socio-technical systems

Agent-based modeling is one of the popular tools for analyzing complex socio-technical systems. Because of the complex nature of such systems a systematic methodology is required to guide the modeling process. By studying the existing methodologies in MAS we distinguished four major differences between MAS and ABM regarding goals, system scale and diversity, level of system understanding and verification and validation concerns. In this paper we take these differences into account and based on more than 25 case studies, we present a methodological framework for developing agent-based models that consists of five general iterative phases. These phases namely: system analysis, model design, detailed design, implementation and evaluation further consists of smaller step that are also addressed in this paper. This methodology provides a tool independent template while respecting the specific requirements for ABM.
Analyzing small data sets using Bayesian estimation: the case of posttraumatic stress symptoms following mechanical ventilation in burn survivors

Background The analysis of small data sets in longitudinal studies can lead to power issues and often suffers from biased parameter values. These issues can be solved by using Bayesian estimation in conjunction with informative prior distributions. By means of a simulation study and an empirical example concerning posttraumatic stress symptoms (PTSS) following mechanical ventilation in burn survivors, we demonstrate the advantages and potential pitfalls of using Bayesian estimation. Methods First, we show how to specify prior distributions and by means of a sensitivity analysis we demonstrate how to check the exact influence of the prior (mis-) specification. Thereafter, we show by means of a simulation the situations in which the Bayesian approach outperforms the default, maximum likelihood and approach. Finally, we re-analyze empirical data on burn survivors which provided preliminary evidence of an aversive influence of a period of mechanical ventilation on the course of PTSS following burns. Results Not suprisingly, maximum likelihood estimation showed insufficient coverage as well as power with very small samples. Only when Bayesian analysis, in conjunction with informative priors, was used power increased to acceptable levels. As expected, we showed that the smaller the sample size the more the results rely on the prior specification. Conclusion We show that two issues often encountered during analysis of small samples, power and biased parameters, can be solved by including prior information into Bayesian analysis. We argue that the use of informative priors should always be reported together with a sensitivity analysis.
Sex and secrecy: How HIV-status disclosure affects safe sex among HIV-positive adolescents

HIV-positive adolescents who engage in unsafe sex are at heightened risk for transmitting or re-acquiring HIV. Disclosure of HIV-status to sexual partners may impact on condom use, but no study has explored the effects of (i) adolescent knowledge of one's HIV-status, (ii) knowledge of partner status and (iii) disclosure to partners, on safer sex behaviour. This study aimed to identify whether knowledge of HIV-status by HIV-positive adolescents and partners was associated with safer sex. Eight fifty eight HIV-positive adolescents (10–19 years old, 52% female, 68.1% vertically infected) who had ever initiated antiretroviral treatment in 41 health facilities in the Eastern Cape, South Africa, were interviewed using standardised questionnaires. Quantitative analyses used multivariate logistic regressions, controlling for confounders. Qualitative research included interviews, focus group discussions and observations with 43 HIV-positive teenagers and their healthcare workers. N = 128 (14.9%) of the total sample had ever had sex, while N = 109 (85.1%) of sexually active adolescents had boy/girlfriend. In total, 68.1% of the sample knew their status, 41.5% of those who were sexually active and in relationships knew their partner's status, and 35.5% had disclosed to their partners. For adolescents, knowing one's status was associated with safer sex (OR = 4.355, CI 1.085–17.474, p = .038). Neither knowing their partner's status, nor disclosing one's HIV-status to a partner, were associated with safer sex. HIV-positive adolescents feared rejection, stigma and public exposure if disclosing to sexual and romantic partners. Counselling by healthcare workers for HIV-positive adolescents focused on benefits of disclosure, but did not address the fears and risks associated with disclosure. These findings challenge assumptions that disclosure is automatically protective in sexual and romantic relationships for HIV-positive adolescents, who may be ill-equipped to negotiate safer sex. There is a pressing need for effective interventions that mitigate the risks of disclosure and provide HIV-positive adolescents with skills to engage in safe sex.
LOOKING THROUGH KNOWLEDGE GLASSES : A NEW READING OF OPERATIONS MANAGEMENT-THE DILEMMA OF PROCESS FORMALIZATION . INITIAL OUTCOMES OF A FIELD STUDY -

The possibility of expliciting practice has been and still is a controversial issue that has been the central focus of theoretical papers, dissertations and practical models within the knowledge management field. Although most of these discrepancies are of a theoretical nature, they have nonetheless a great impact on the practical domain that goes far beyond just the knowledge management field. This paper aims to shed light on some aspects related to the possibility of expliciting knowledge. The Operations Management field will provide us the opportunity to address this issue. In this field, process documentation is a well-established practice that aims to capture the business practice in process representations like blueprintings and flowcharts. These explicit documents play a key role in process management, design and improvement. But, to what extent do they reflect practice? This is the dilemma of process formalisation that we will tackle through a theoretical analysis and through a case study of a Spanish service company immersed in making their practice explicit.
Multi-person location and tracking method based on BP neural network

This paper focuses on the study of multi-person location and tracking in a complex scene created by 3ds max. To establish the complicated relationship between the 2D-image information that is obtained through the three-camera system and the 3D information of the target, an artificial neural network is proposed. In order to overcome the shortcomings of traditional BP algorithm as being slow to converge and easy to reach extreme minimum value, the model adopts LM (Levenberg-Marquardt) algorithm to achieve a higher speed and a lower error rate. Experiment results verify that the BP neural network improves the efficiency, accuracy and robustness of the method comparing with traditional binocular location (TBL) methods.
Visualizing Variance with Percent Change Threshold

This report proposes a standard method to characterize variability and sensitivity of functional neuroimaging experiments. Most functional neuroimaging analyses result in statistic images of signal-to-noise. However, it is essential to examine both signal and noise individually, to characterize sensitivity and to identify artifacts. Confidence intervals simultaneous convey signal and noise but are poorly suited to imaging. We describe an image which conveys the same information as a confidence interval when used with an image of estimated signal. This image is the half-length of a two-sided confidence interval, and is most easily seen as the minimum change required to obtain a significant activation at level (either corrected or uncorrected). If the estimated signal has units of percent change, then we call this image a level percent change threshold (PCT). We demonstrate the method on two fMRI datasets, showing that PCT can vary by an order of magnitude across the brain.
Galaxy Luminosity Function in Groups

We compute the luminosity function (LF) of galaxies in groups. The data consist of groups of galaxies selected in distance and redshift space in two samples comprising a total number of 66 groups. The assignment of galaxies to the groups was derived from the Edinburgh-Durham Southern Galaxy Catalog, considering a limiting apparent magnitude mlim = 19.4. We find a flat faint end of the mean galaxy LF in groups, which is in contrast to the mean galaxy LF in clusters where a large relative number of faint galaxies is present. We find that a Schechter function with parameters M* ≃ -19.6 ± 0.2, α ≃ -1.0 ± 0.2 provides a satisfactory fit to the galaxy LF of our total sample of groups in the range of absolute magnitudes -22 < M < -16.
Downlink cross-tier interference pricing and power control in OFDMA HetNets

Deploying smallcell networks achieves great spatial reuse at the cost of severe cross-tier interference from concurrent transmission. This paper addresses the downlink cross-tier interference pricing and power control for orthogonal frequency division multiple access (OFDMA) heterogeneous Networks (HetNets), where a macrocell underlaid with several femtocells.We assume that the macrocell protects its transmission by pricing the interference on each orthogonal subchannel and each femtocell base station (FBS) determines the power allocation strategy accordingly.Then, a Stackelberg game is used to formulate the mentioned model. Existence and uniqueness of the Stackelberg equilibrium (SE) are analyzed. In addition, a distributed interference pricing and power update algorithm (DIPPU) with guaranteed convergency is proposed to achieve the SE. Simulation results validate the proposed algorithm and show its fast convergence. Due to the non-cooperative manner, the proposed scheme can approach the cooperative scheme in terms of capacity of femtocells with reduced communication overhead effectively.
CONSIM(Conflict Simulator): Risk, cost and benefit in political simulations

The development and use of CONSIM (Conflict Simulator), a computer program designed to heurististically simulate decision making, is described. A typical example is used to evaluate and analyze the methodology of CONSIM. The simulation model is designed for two political opponents, each possessing any finite number of alternatives. The model is constructed utilizing techniques frequently employed in game theory. Probabilities are assigned, using a Bayesian Approach, to sets of alternatives available to the United States and China. Incorporated into the model is the capability of varying the probabilities as the Vietnam Conflict evolves and the re-evaluation of risks, costs, and benefits occurs. CONSIM is easy to use and applicable wherever probabilities may be assigned to each alternative in a mutually exclusive and exhaustive set of alternatives in a dynamic situation.
Hand posture estimation by combining 2-D appearance-based and 3-D model-based approaches

This paper proposes a method for the rapid and precise estimation of human hand postures by combining 2D appearance matching and 3D model-based fitting. First a rough posture estimate is obtained by image indexing. Each possible hand appearance generated from a given 3D shape model is labeled by an index obtained by PCA compression and registered with its 3D model parameters in advance. By retrieving the index of the input image, the method can obtain the matched appearance image and its 3D parameters rapidly. Then, starting from the obtained rough estimate, it estimates the posture and moreover refines the given initial 3D model by model-fitting. The sequential activation of the two processes in every frame gives the precise posture estimate rapidly. The effectiveness of the method is shown by experimental results.
A controlled trial of population management: diabetes mellitus: putting evidence into practice (DM-PEP).

OBJECTIVE Population-level strategies to organize and deliver care may improve diabetes management. We conducted a multiclinic controlled trial of population management in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS We created diabetic patient registries (n = 3,079) for four primary care clinics within a single academic health center. In the intervention clinic (n = 898), a nurse practitioner used novel clinical software (PopMan) to identify patients on a weekly basis with outlying values for visit and testing intervals and last measured levels of HbA1c, LDL cholesterol, and blood pressure. For these patients, the nurse practitioner e-mailed a concise patient-specific summary of evidence-based management suggestions directly to primary care providers (PCPs). Population changes in risk factor testing, medication prescription, and risk factor levels from baseline (1 January 2000 to 31 August 2001) to follow-up (1 December 2001 to 31 July 2003) were compared with the three usual-care control clinics (n = 2,181). RESULTS Patients had a mean age of 65 years, were mostly white (81%), and the majority were insured by Medicare/Medicaid (62%). From baseline to follow-up, the increase in proportion of patients tested for HbA1c (P = 0.004) and LDL cholesterol (P < 0.001) was greater in the intervention than control sites. Improvements in diabetes-related medication prescription and levels of HbA1c, LDL cholesterol, and blood pressure in the intervention clinic were balanced by similar improvements in the control sites. CONCLUSIONS Population-level clinical registries combined with summarized recommendations to PCPs had a modest effect on management. The intervention was limited by good overall quality of care at baseline and temporal improvements in all control clinics. It is unknown whether this intervention would have had greater impact in clinical settings with lower overall quality. Further research into more effective methods of translating population registry information into action is required.
An Analysis of a Mandarin-English Code-switching Speech Corpus : SEAME

SEAME (South East Asia Mandarin-English) is a 30 hours spontaneous Mandarin-English code-switching speech corpus recorded from Singapore and Malaysia speakers. In this paper, we report a series of analyses on the recording, processing time and voice activity rate (VAR) of the speech recording, transcription, validation and language boundaries labeling processes. In addition, the duration of the monolingual segment in the code-switching utterance and the analysis of the speakers‟ behavior in language switching during conversation are also described. The results of the analysis show that 80% and 72% monolingual segments of English and Mandarin in the code-switching utterance are shorter than one second. In over 80% of the cases, speakers directly switch language without any short pause and discourse particle between two adjacent different languages.
Towards a Prediction and Data Driven Computational Process Model of Emotion

Starting from the assumption that computational models of emotion (CME) should produce tangible and useful results, I focus on their potential role in developing theoretical predictions and comparative testing of different theories. Concretely, I suggest a specific type of CME for this purpose, the prediction and data driven computational process (PDCP) model of emotion, as based on largely shared assumptions about the emotion process and the underlying components. After providing an overview of the wide variety of emotion theories and their suitability for computational modeling, the current version of the component process model (CPM) of emotion is described, including the specific predictions amenable to modeling. I then review the empirical data confirming many of these predictions and thus providing a solid basis for the development of CMEs. On this basis, I outline the skeleton of a realistic PDCP model that should allow testing competing theories and models. Specifically, I propose an incremental approach to concrete static and dynamic modeling efforts using recently developed advanced experimental procedures and assessment instruments as well as expert systems.
A soluble form of the urokinase plasminogen activator receptor (suPAR) can bind to hematopoietic cells

The receptor for urokinase plasminogen activator (uPAR; CD87) is a 50‐ to 65‐kDa glycosylphosphatidylinositol (GPI)‐anchored glycoprotein expressed by leukocytes and tumor cells where it facilitates uPA‐dependent, plasmin‐mediated pericellular proteolysis during cellular invasion. Because uPAR is inducibly shed into culture supernatants and human body fluids, we tested the hypothesis that soluble uPAR (suPAR) can bind to the plasma membrane of hematopoietic cells where it might modulate their invasive phenotype. As measured by flow cytometry, recombinant biotinylated‐suPAR (B‐suPAR) bound in a specific fashion to THP‐1 leukemia cells and blood PMNs and monocytes (but not to lymphocytes). B‐suPAR also demonstrated specific binding to a variety of leukemic lines, including cells that are positive or negative for membrane uPAR expression. Binding of B‐suPAR to THP‐1 cells was enhanced four‐ to sevenfold by 24‐h exposure of cells to PMA or by coincubation with uPA ligand (but not its isolated catalytic and binding fragments). Conversely, binding of B‐suPAR to PMNs was unaffected by brief exposure to fMLP, and was inhibited by coincubation with uPA. B‐suPAR binding to PMA‐differentiated THP‐1 cells in the presence of uPA was further enhanced by acid washing (removing endogenous uPA) but was partially inhibited by treatment of cells with trypsin. Pretreatment of PMA‐differentiated THP‐1 cells and unstimulated PMNs with soluble sugars, calcium chelators, and antibodies specific for integrins or extracellular matrix proteins failed to consistently block the binding of B‐suPAR. Whereas the binding of suPAR did not measurably affect cell‐associated plasmin activation, suPAR did competitively inhibit the binding of exogenous uPA to membrane‐associated uPAR. These observations support the hypothesis that suPAR can bind specifically to trypsin‐sensitive receptors expressed by certain normal and neoplastic hematopoietic cells where its binding is variably influenced by uPA ligand. J. Leukoc. Biol. 64: 203–213; 1998.
The X-Ray Forest: A New Prediction of Hierarchical Structure Formation Models

We use numerical simulations of structure formation in a cold dark matter model to predict the absorption lines in the soft X-rays produced by heavy elements in the shock-heated intergalactic medium at low redshift. The simulation incorporates a model for heavy-element production in galaxies and the subsequent dispersion of the metals to the intergalactic medium. We analyze in particular absorption lines produced by oxygen and calculate the ionization stage, taking into account the observed X-ray background at the present time. We find that oxygen is fully ionized by the X-ray background in low-density voids and is mostly in the form of O VII and O VIII in the sheets and filamentary regions. Strong absorption lines of O VII and O VIII with equivalent widths W ~ 100 km s-1 are produced in filamentary regions of overdensities of ~100 and temperatures of ~106 K, located in the outskirts of groups and clusters of galaxies. The O VII line at E = 574 eV is generally the strongest one in these systems. Our model predicts that any X-ray source (such as a quasar) should typically show about one O VII absorption line with W > 100 km s-1 in the interval from z = 0 to z = 0.3. These lines could be detected with the upcoming generation of X-ray telescopes, and their origin in intervening systems could be confirmed by the association with groups of galaxies and X-ray-emitting halos near the line of sight at the same redshift. The hot intergalactic medium may be one of the main reservoirs of baryons in the present universe, and the heavy-element X-ray absorption lines offer a promising possibility of detecting this new component in the near future.
Strategies for the Identification of Novel Brain Specific Genes Affected in Alzheimer Disease

ABSTRACT: The pathological changes that occur in Alzheimer disease (AD) brain lead to a large loss of various classes of neurons and the production of novel proteinaceous elements such as neuritic plaques and neurofibrillary tangles. For the neuronal loss to occur and these elements to arise, there must be a disturbance in the expression or regulation of genes that code for proteins required for normal cell maintenance, or perhaps even for the expression of genes unique to AD. We describe the construction of a cDNA library from the human substantia innominata and strategies for isolating genes that are expressed differentially between brain regions and which may be affected by AD. Some of the results obtained using these strategies and a preliminary description of a novel brain specific mRNA of 15.5kb, whose expression is increased in AD affected temporal cortex, are presented.
Design and implementation of real-time distributed systems with the ASSERT Virtual Machine

This paper describes how the ASSERT Virtual Machine, a dedicated execution platform that guarantees a predictable real-time behaviour, can be used to develop real-time embedded distributed systems with high-integrity requirements. The concept of virtual machine-level software components is developed, and sample programming patterns are provided. Components are used in the framework of the ASSERT development process, and are based on the Ravenscar Computational Model, a concurrent tasking model which can be statically analysed for a correct real-time behaviour. The current architecture of the ASSERT virtual machine is described in detail, and experience gained with its use in the last few years is provided.
Comprehensive Structural and Functional Characterization of the Human Kinome by Protein Structure Modeling and Ligand Virtual Screening

The growing interest in the identification of kinase inhibitors, promising therapeutics in the treatment of many diseases, has created a demand for the structural characterization of the entire human kinome. At the outset of the drug development process, the lead-finding stage, approaches that enrich the screening library with bioactive compounds are needed. Here, protein structure based methods can play an important role, but despite structural genomics efforts, it is unlikely that the three-dimensional structures of the entire kinome will be available soon. Therefore, at the proteome level, structure-based approaches must rely on predicted models, with a key issue being their utility in virtual ligand screening. In this study, we employ the recently developed FINDSITE/Q-Dock ligand homology modeling approach, which is well-suited for proteome-scale applications using predicted structures, to provide extensive structural and functional characterization of the human kinome. Specifically, we construct structure models for the human kinome; these are subsequently subject to virtual screening against a library of more than 2 million compounds. To rank the compounds, we employ a hierarchical approach that combines ligand- and structure-based filters. Modeling accuracy is carefully validated using available experimental data with particularly encouraging results found for the ability to identify, without prior knowledge, specific kinase inhibitors. More generally, the modeling procedure results in a large number of predicted molecular interactions between kinases and small ligands that should be of practical use in the development of novel inhibitors. The data set is freely available to the academic community via a user-friendly Web interface at http://cssb.biology. gatech.edu/kinomelhm/ as well as at the ZINC Web site ( http://zinc.docking.org/applications/2010Apr/Brylinski-2010.tar.gz ).