Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying 2D ML iterative reconstruction methods with resolution recovery to 3D PET data: evaluation of rebinning effects

The applicability of OSEM reconstruction algorithms with space dependent resolution recovery to clinical FDG-PET studies is verified. The performance of the 2D algorithm is improved by means of a low resolution initialization and by a infra-iteration Metz filtering. Effects of different rebinning algorithms on 3D data are assessed, concluding that they do not alter the transaxial plane blurring parameters, thus permitting a straightforward application of 2D OSEM reconstruction after rebinning, with the same system matrix. Finally axial degradation was also quantified, finding that FORE is the best rebinning method to be combined with the 2D OSEM reconstruction.
The epilepsy, the protease inhibitor and the dodecamer: progressive myoclonus epilepsy, cystatin b and a 12-mer repeat expansion

Progressive myoclonus epilepsy 1 (EPM1) or Unverricht-Lundborg disease is a human autosomal recessive neurodegenerative disorder caused by mutations in cystatin B (CSTB). The CSTB gene maps to human chromosome 21 and encodes an inhibitor of lysosomal cysteine proteases. Five point mutations have been found, two of which are seen in numerous unrelated patients. However, the main CSTB mutation in EPM1, even among patients of different ethnic origins, is an expansion of a dodecamer repeat (CCCCGCCCCGCG) in the 5′ flanking area of CSTB. Most normal alleles contain either two or three repeats, while rarer normal alleles that are highly unstable contain between 12 and 17 repeats. Mutant expanded alleles have been reported to contain between 30 and 80 copies and are also highly unstable, particularly via parental transmission. There is no apparent correlation between mutant repeat length and disease phenotype. While the repeat expansion is outside the CSTB transcriptional unit, it results in a marked decrease in CSTB expression, at least in certain cell types in vitro. Cstb homozygous knockout mice show some parallels to the phenotype of human EPM1 including myoclonic seizures, development of ataxia and neuropathological changes associated with cell loss via apoptosis. Loss of CSTB function due to mutations is consistent with the observed neurodegenerative pathology and phenotype, but the functional link to the epileptic phenotype of EPM1 remains largely unknown.
Building customer retention in on-line transportation

Customer retention emphasizes on the marketer’s activities to retain customers. Customer retention is the form of loyalty related to the behavior measured on the consumer purchase behavior indicated by the high frequency of buying a service, so that the company which wants to know the level of customer retention must see the customer behavior in using its service. This study describes the results of survey on on-line transportation service, namely Gojek, Grab, and Uber in Jakarta, Bandung and Medan. The research methodology uses a survey on 400 users of on-line transportation service and refers to customer retention modelling. The essence of this research is that customer behavioral intention on the on-line transportation service will determine whether they are retained or not based on the customer characteristics and the perception of service employee’s orientation to customer. Furthermore, the findings in this research indicate that consumer’s behavioral intention becomes necessary to be studied by business players in on-line transportation.
A light-weight summarizer based on language model with relative entropy

A new method for sentence extraction on the basis of language model with relative entropy is presented in this paper. The proposed technique first builds a sentence language model and document cluster language model respectively for the sentence and the documents. The sentences are then ranked according to the relative entropies of the estimated document language model with respect to the estimated sentence language model. The overall results on DUC and MSE corpus demonstrate that the proposed approach outperforms some of the best reported results for generic multi-document summarization.
Knowledge retention in ERP implementations: the context of UK SMEs

Abstract Knowledge retention (k-retention) is vital for various enterprise resource planning (ERP) implementations in small and medium-sized enterprises (SMEs), though it is a highly demanding and challenging task. The aim of this paper is to investigate different types of approaches to k-retention and factors influencing k-retention in SMEs. Our study adopts a grounded theory approach with cases based on 12 ERP implementations in UK SMEs. We analyze our data using thematic analysis. The findings reveal specific elements that support the k-retention of ERP package knowledge and business process knowledge. These elements are: k-retention tools, documentation, human capital and the understanding of k-retention challenges. In addition to insights from these aspects, our study reveals two additional factors (project management and organizational culture) that influence ERP package k-retention and business process k-retention. Based on these findings, we develop an ERP k-retention (EKR) framework that can be utilized by SMEs which are considering implementing ERP systems, to facilitate knowledge retention during implementation.
A Fingerprint Forensic Tool for Criminal Investigations

In this chapter, the authors describe the software module developed in the context of a joint research work between the Department of Electrical and Electronic Engineering of the University of Cagliari, and Raggruppamento Carabinieri Investigazioni Scientifiche (Scientific Investigation Office) of the “Arma dei Carabinieri”, that is the militia maintained by the Italian government for police duties. Aim of the joint research work has been the study of state of the art on methods and algorithms for automatic analysis of latent fingerprint images and for fake fingerprints identification. The result of this research has been the development of a prototype software tool, whose aim is to help the human expert in analyzing latent fingerprints collected during investigations. This software exhibits several features which are not present in standard AFIS tools. Advanced modules for fingerprint image processing, comparison among fingerprints, and, finally, a module for discriminating fake latent fingerprints from “live” ones, characterize this tool. With the term “fake latent fingerprints”, we mean latent fingerprint images released on the crime scene by a “stamp” reproducing a certain true fingerprint. DOI: 10.4018/978-1-60566-836-9.ch002
Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures

A novel database search algorithm is presented for the qualitative identification of proteins over a wide dynamic range, both in simple and complex biological samples. The algorithm has been designed for the analysis of data originating from data independent acquisitions, whereby multiple precursor ions are fragmented simultaneously. Measurements used by the algorithm include retention time, ion intensities, charge state, and accurate masses on both precursor and product ions from LC‐MS data. The search algorithm uses an iterative process whereby each iteration incrementally increases the selectivity, specificity, and sensitivity of the overall strategy. Increased specificity is obtained by utilizing a subset database search approach, whereby for each subsequent stage of the search, only those peptides from securely identified proteins are queried. Tentative peptide and protein identifications are ranked and scored by their relative correlation to a number of models of known and empirically derived physicochemical attributes of proteins and peptides. In addition, the algorithm utilizes decoy database techniques for automatically determining the false positive identification rates. The search algorithm has been tested by comparing the search results from a four‐protein mixture, the same four‐protein mixture spiked into a complex biological background, and a variety of other “system” type protein digest mixtures. The method was validated independently by data dependent methods, while concurrently relying on replication and selectivity. Comparisons were also performed with other commercially and publicly available peptide fragmentation search algorithms. The presented results demonstrate the ability to correctly identify peptides and proteins from data independent acquisition strategies with high sensitivity and specificity. They also illustrate a more comprehensive analysis of the samples studied; providing approximately 20% more protein identifications, compared to a more conventional data directed approach using the same identification criteria, with a concurrent increase in both sequence coverage and the number of modified peptides.
MoG-VQE: Multiobjective genetic variational quantum eigensolver

Variational quantum eigensolver (VQE) emerged as a first practical algorithm for near-term quantum computers. Its success largely relies on the chosen variational ansatz, corresponding to a quantum circuit that prepares an approximate ground state of a Hamiltonian. Typically, it either aims to achieve high representation accuracy (at the expense of circuit depth), or uses a shallow circuit sacrificing the convergence to the exact ground state energy. Here, we propose the approach which can combine both low depth and improved precision, capitalizing on a genetically-improved ansatz for hardware-efficient VQE. Our solution, the multiobjective genetic variational quantum eigensolver (MoG-VQE), relies on multiobjective Pareto optimization, where topology of the variational ansatz is optimized using the non-dominated sorting genetic algorithm (NSGA-II). For each circuit topology, we optimize angles of single-qubit rotations using covariance matrix adaptation evolution strategy (CMA-ES) -- a derivative-free approach known to perform well for noisy black-box optimization. Our protocol allows preparing circuits that simultaneously offer high performance in terms of obtained energy precision and the number of two-qubit gates, thus trying to reach Pareto-optimal solutions. Tested for various molecules (H$_2$, H$_4$, H$_6$, BeH$_2$, LiH), we observe nearly ten-fold reduction in the two-qubit gate counts as compared to the standard hardware-efficient ansatz. For 12-qubit LiH Hamiltonian this allows reaching chemical precision already at 12 CNOTs. Consequently, the algorithm shall lead to significant growth of the ground state fidelity for near-term devices.
Activation of Self-Knowledge Reduces Conflict During Occupational Choice: An ERP Study

We investigated whether the activation of self-knowledge reduces conflict during occupational choice, which can elicit many correct answers. Conflict was measured via event-related brain potentials (ERPs). Results of this study showed that activation of self-knowledge reduces conflict during occupational choice. Our results suggest that, in a situation in which two or more possible correct answers exist, people use self-knowledge as a benchmark to reduce conflict by biasing either choice of behavior.
Distributed Spectrum Sensing with Two-Stage Detection for Cognitive Radio

In this paper we investigate spectrum sensing for cognitive radio (CR) by using multiple spectrum sensors. We explore sensing schemes based on soft information combining, hard information combining and a two-stage detection scheme that uses both soft information combining and hard information combining. The two-stage detection scheme is shown to provide improved performance compared to sensing based on either hard information combining or soft information combining alone with a trade-off of sensing time. Computer simulation results are provided to validate the concept. Index Terms—Cognitive radio, spectrum sensor, two-stage de- tection, hard information combining, soft information combining
Soft magnetic properties of Ni81Fe19 film with different substrates used for micro-fluxgate

The soft magnetic properties of Ni81Fe19 films respectively with Ti, Ta and Cr substrates used for micro-fluxgate have been studied in this paper. The films were characterized using transmission electron microscope (TEM), X-ray diffraction (XRD) and vibrating sample magnetometer (VSM). The testing results showed that Ta substrate film, due to its ladder rising hysteresis loop, is more appropriate for fluxgate core in these four kinds of Ni81Fe19 films, film with no substrate and film with Ti substrate take the second place and the Cr substrate film would not be suitable as fluxgate core because of its bad soft magnetic properties.
Is the prediction of pKa values by constant‐pH molecular dynamics being hindered by inherited problems?

In this study, we investigate two factors that can hinder the performance of constant‐pH molecular dynamics methods in predicting protein pKa values, using hen egg white lysozyme as a test system. The first factor is related to the molecular definition and pKa value of model compounds in the Poisson‐Boltzmann framework. We address this by defining the model compound as a molecular fragment with an associated pKa value that is calibrated against experimental data, which results in a decrease of 0.12 units in pKa errors. The second addressed factor is the possibility that detrimental structural distortions are being introduced in the simulations by the underlying molecular mechanics force field. This issue is investigated by analyzing how the gradual structural rearrangements affect the predicted pKa values. The two GROMOS force fields studied here (43A1 and 53A6) yield good pKa predictions, although a time‐dependent performance is observed: 43A1 performs better after a few nanoseconds of structural reorganization (pKa errors of ∼0.45), while 53A6 gives the best prediction right at the first nanosecond (pKa errors of 0.42). These results suggest that the good performance of constant‐pH molecular dynamics methods could be further improved if these force field limitations were overcome. Proteins 2011;. © 2011 Wiley‐Liss, Inc.
Epstein-Barr Virus-Associated Smooth Muscle Tumors Are Distinctive Mesenchymal Tumors Reflecting Multiple Infection Events: A Clinicopathologic and Molecular Analysis of 29 Tumors From 19 Patients

Epstein-Barr virus-associated smooth muscle tumors (EBV-SMT) are rare lesions that occur in immunocompromised patients. Because they have not been fully characterized pathologically or at the molecular level, we have studied 29 tumors from 19 patients, the largest series to date. Cases coded as EBV-SMT were identified in 19 patients from consultation files and from the renal transplant database at Singapore General Hospital. EBV-SMT occurred in adults (mean age 39 years; range, 21-57 years) and predominantly affected males (12 male, 7 female). Causes of immunocompromise were renal transplantation (10), AIDS (8), and steroid therapy (1). Tumors were located in soft tissue (5), lung (5), liver (4), and miscellaneous sites (15). In 13 patients (68%), the tumors were multiple. Infection with EBV was confirmed in all cases by in situ hybridization for EBV early RNAs (EBER). EBV-SMT were typically well-differentiated smooth muscle tumors with little atypia and usually a low level of mitotic activity. Unlike classic leiomyosarcomas, they lacked significant pleomorphism but frequently displayed primitive round cell areas and prominent intratumoral T lymphocytes. No consistent relationship between histologic features and clinical outcome was noted. All expressed actin (29 of 29) and less frequently desmin (14 of 26). Multiple tumors in a given patient were clonally distinct as assessed by the long terminal repeat region of the virus, supporting the view that multifocal tumors arise from multiple infection events rather than from metastasis. Strain typing by analysis of the EBNA-3C gene confirmed the presence of EBV type 2. Two of four tumors assessed were positive for a 30-bp deletion in the LMP1 gene. EBV copy number per cell ranged greatly between patients and between tumors from the same patient. Follow-up information was available in 18 of 19 patients (mean, 25 months; range, 1-105 months). Fifteen patients were alive: 11 with disease and 4 without. Three patients died, 1 due to disease. We conclude that EBV-SMT are histologically distinct from classic soft tissue smooth muscle tumors, are not readily evaluated by means of conventional histologic criteria, and in the case of multifocal tumors are the result of multiple infection events rather than metastasis. EBV-2 can transform smooth muscle cells, independent of the presence of the LMP1 deletion associated with greater virulence.
Early Mobilization After Stroke: Early Adoption but Limited Evidence

In the last decade, increasing attention has been paid to understanding the components of care that might contribute to the stroke unit effect. Early mobilization, in its many guises, is one component of care proposed to contribute to the survival and recovery benefits of stroke unit care.1 This topical review provides an overview of the current evidence, research, and practice recommendations for early mobilization after stroke. As a term, early mobilization is problematic. There is no common understanding of the meaning of early (eg, hours, days, weeks, months) or mobilization (movement of, eg, cells, joints, limbs, people). A recurring theme in this review, inadequate definition currently limits our ability to synthesize information on the topic. For example, in some clinical trials of mobility interventions started soon after stroke, mobilization is used to describe a program of task-specific standing and walking retraining (rehabilitation) delivered by therapists or nurses and continued throughout the acute hospital stay.2,3 In other cases, mobilization refers simply to moving a patients’ limbs in bed or sitting them out of bed. The timing of commencement of activity is also highly variable and often hard to determine. As both what we do (intervention type, intensity, frequency, amount), and when we do it, may confer benefit or harm, we highlight variations in definition where relevant. We have focused our review on out-of-bed interventions commencing in the first 24 to 72 hours after stroke, as this is the period of greatest clinical uncertainty. Early mobilization was first discussed at a Swedish consensus conference on stroke care in the mid-1980s (Bo Norving and Bent Indredavik, personal communication, 2014) with several local guidelines in Norway and Sweden recommending the practice. Early mobilization became more prominent in the literature in the early 1990s when Indredavik and colleagues reported their clinical …
Computational music remixing with EarSketch (abstract only)

Our work has focused on how to create a learning experience that is highly personally motivating for students, has a low barrier of entry for creation an artistic computational artifact, and is scalable for use in formal and informal education settings at the national level. We have created a learning environment called EarSketch that addresses student engagement through a STEAM learning experience that provides authentic learning in both the technical (i.e. computing) and artistic domains (i.e. music remixing). EarSketch is an integrated curriculum, software toolset, audio loop library, and social sharing site that teaches computing principles through digital music composition and remixing. Attendees will use Python to place audio clips, create rhythms, and add and control effects to a multi-track digital audio workstation (DAW) while learning computing concepts such as variables, iteration, conditionals, strings, lists, and functions. Participants write code to make music, with a focus on popular genres such as hip hop. The agenda outlines the pedagogy of connecting musical expression to computation. EarSketch has been used in introductory computing summer camps, secondary school classes, and is currently working towards integration with CS Principles pilot programs. All participants will need a laptop for running the EarSketch software. EarSketch will run on OSX and Windows laptops. Participants will also need headphones for listening to projects created using EarSketch. It is highly suggested that participants download the EarSketch installer at http://earsketch.gatech. edu/downloads and install the software prior to the workshop.
Requirements of a Model-Driven Methodology and Tool-Chain for the Design and Verification of Hierarchical Controllers of an Autonomic Network

Model-driven approaches to design, simulation, verification, validation and testing of complex systems are increasingly required in every domain of systems and software engineering where the systems are complex. The domain of autonomic network engineering is one such new area calling for such model-driven approaches. In this paper we provide the requirements of a model-driven methodology and Tool-Chain for the design and verification of hierarchical controllers of an autonomic network. The requirements are classified as behavioral, structural and stability requirements. Based on these requirements, we propose a hybrid approach that combines design techniques from modern control theory, conventional protocol design and model-driven systems engineering for the design of hierarchical controllers that meet the stability, structural and behavioral requirements of their autonomic network architectures. The methodology addresses the problems of behavior conflicts, stability, response time problems and operating regions conflicts of hierarchical controllers. A Tool-Chain to realize the proposed methodology is also presented.
Ethical Conflict in Nurse Practitioners and Physician Assistants in Managed Care

Background: More patients are receiving healthcare services from nurse practitioners (NPs) and physician assistants (PAs). These providers are likely to be confronted with a variety of ethical issues as they balance quality care with their patients' rising cost concerns. However, very little is known about the ethical conflicts and causes of these conflicts experienced by these clinicians in their daily practice. Objective: To identify ethical concerns and conflicts NPs and PAs encounter related to managed care in the delivery of primary care to patients and the factors that influence ethical conflict. Methods: A cross-sectional self-administered mailed questionnaire was sent to 3,900 NPs and PAs randomly selected from primary care and primary care subspecialties in the United States (adjusted response rate, 50.6%). Respondents were surveyed on ethical issues and concerns, ethics preparedness, and ethical conflict. Bivariate and multiple linear regression analyses were used to evaluate predictors of ethical conflict. Results: Insurance constraints were reported to have interfered with the ability to provide quality patient care by 72% of respondents, with 55.3% reporting daily to weekly interferences. Nearly half of respondents (47%) have been asked by a patient to mislead insurers to assist them in receiving care. A perceived obligation to advocate for patients, even if it means exaggerating the severity of a patient's condition, was the single most significant predictor of ethical conflict, explaining 25% of the variance. Discussion: NPs and PAs are experiencing ethical conflict often associated with their perceived professional obligations to advocate for patients. Being well-prepared in ethics and having sufficient professional independence help clinicians balance the ethical complexities and demands of meeting patients' needs within a constrained healthcare system.