Miracle-dz/UniFAR-FTUs huggingface dataset:
Assurance on XBRL‐Related Documents: The Case of United Technologies Corporation

ABSTRACT: The eXtensible Business Reporting Language (XBRL) was developed to provide financial information users with a standardized method to prepare, publish, and exchange business information in digital format. XBRL is being used around the world for financial reporting and government e‐filings. Although there has been growing awareness about assurance issues related to the use of XBRL, current audit practices and standards fall short of providing the needed guidance for the provision of assurance on XBRL‐Related Documents. In this paper, we report on a mock assurance engagement that we conducted on the XBRL‐Related Documents of United Technologies Corporation's 10‐Q for the third quarter of 2005 and repeated on its 10‐Q for the third quarter of 2008 to identify the issues that companies and auditors might encounter if they are requested to provide assurance on XBRL‐Related Documents. We describe the assurance framework applied in the mock assurance engagement, present the findings from the examination.
Accounting Software Assets: A Valuation Model for Software

Enterprise Information Technology Systems are major corporate assets upon which corporate management and operations are heavily dependent. Current accounting standards for the treatment of these assets have not kept pace with advances in technology, such as models for creating and evolving IT. Capitalizable costs according to the standards are principally primary development costs and exclude system evolution. This weakness of the standards creates a disproportionate downward bias in the book value of software and in current earnings, as costs incurred for on‐going systems evolution is five to twenty times the costs incurred for first release. We present a quantitative valuation model for IT systems based upon engineering measurements of software that allow the fair value of software to be based on all costs incurred by the system. Costs are collected by an automatic tool and stored in an inventory system of enterprise software assets. To total costs is added the effect of each individual module's relativ.
Multi-scaled Spatial Analytics on Discovering Latent Social Events for Smart Urban Services

The goal of this paper is to discover latent social events from social media for sensitively understanding social opinions that appeared within a city. The latent social event indicates a regional and inconspicuous social event which is mostly buried under macroscopic trends or issues. To detect the latent social event, we propose three methods: i) discovering areas-ofinterest (AOIs), ii) allocating social texts to the AOIs, and iii) detecting social events in each AOI. The AOIs can be composed by grouping social texts which are topically and spatially homogeneous. To make the AOIs dynamic and incremental, we use windows for allocating a social text to an adequate AOI. Lastly, the latent social events are detected from the AOI on the basis of keywords and temporal distribution of the social texts. Although, in this study, we limited the proposed method into analyzing social media, it could be extended to detecting events among agents/things/sensors.
On the use of numerical model reduction techniques in chemically reacting flows

Simulation of detailed multicomponent reactive flow processes becomes quite expensive and, despite the advent and advancement of digital computers, still engulfs an inconceivably large amount of time. Chemistry-based model reduction aims at breaking down the dimensionality of an underlying combustion model such that its simulation ideally takes considerably less time. In this thesis we examine a few practical model reduction approaches which bear the potential to be used in the context of chemically reacting flows. This examination serves also as a fairly broad overview of numerical methods needed for efficient model reduction approaches. Furthermore, we propose a novel, heuristic model reduction procedure that hinges less on iterative features and thus is less affected by convergence issues. For the nonlinear scenarios considered in this thesis, the running times obtained with the new method in conjunction with the reduced problems are quite promising when compared to the simulation costs of the respective full models. The qualitative studies carried out here shed light on the direction in which future model reductions for chemically reacting flows may proceed. We expect the novel method to become a viable alternative in the field of reduced combustion simulation. Zusammenfassung Die Simulation detaillierter reaktiver Strömungsprozesse ist trotz des Einsatzes modernster Computertechnik äußerst aufwendig. Chemie-basierte Modellreduktion hat das Ziel, die Dimension eines gegebenen Verbrennungsmodells herunterzubrechen, so dass seine Simulation weit weniger Zeit in Anspruch nimmt. Daher untersuchen wir praktische Methoden der Modellreduktion, welche das Potential besitzen, im Zusammenhang mit reaktiven Strömungen eingesetzt zu werden. Dies beschert uns ebenfalls einen hinreichend guten Überblick über numerische Methoden, welche in diesem Zusammenhang Verwendung finden. In dieser Arbeit wird ein neuartiges, heuristisches Modellreduktionsverfahren vorgestellt, welches weniger auf iterativen Eigenschaften beruht und damit auch weniger von etwaigen schlechten Konvergenzeigenschaften beeinflusst wird. Es werden nichtlineare Szenarien studiert und es wird experimentell gezeigt, dass die Laufzeit bezüglich des reduzierten Modells besser ist als jene des vollen Modells. Diese Studien weisen auch mögliche Richtungen auf, in welche sich eine zukünftige Modellreduktion für reaktive Strömungen entwickeln könnte, und wir sehen in der neuen Methode eine brauchbare Alternative zu bestehenden Konzepten der Modellreduktion.
Wait wait, don't tell me: Handedness questionnaires do not predict hand preference for grasping

ABSTRACT Handedness questionnaires are a common screening tool in psychology and neuroscience, used whenever a participant's performance on a given task may conceivably be affected by their laterality. Two widely-used examples of such questionnaires are the Edinburgh Handedness Inventory and the Waterloo Handedness Questionnaire. Both instruments ask respondents to report their hand preference for performing a variety of common tasks (e.g., throwing a ball, or opening a drawer). Here we combined questions from the two instruments (E-WHQ; 22 questions total) and asked participants to report their preferred hand for each via a five-point scale. The purpose of this study was to determine whether responses on the E-WHQ are accurate, reliable, and/or predictive of hand-preference for a simple grasp-to-construct task. Regarding accuracy, handedness scores were 5% lower when participants used a scrambled response key versus a consistent one. Test-retest reliability of the questionnaire was weak, with any given inventory item eliciting a different response from 34% of respondents upon retesting. Neither was the E-WHQ predictively useful—although both left- and right-handers preferred their dominant hands, E-WHQ score did not correlate with overall percentage of dominant-hand grasps in either group. We conclude that the E-WHQ is unsuited for predicting hand preference for grasping.
Classification of breast lesions in ultrasonography using sparse logistic regression and morphology‐based texture features

PURPOSE This work proposes a new reliable computer-aided diagnostic (CAD) system for the diagnosis of breast cancer from breast ultrasound (BUS) images. The system can be useful to reduce the number of biopsies and pathological tests, which are invasive, costly, and often unnecessary. METHODS The proposed CAD system classifies breast tumors into benign and malignant classes using morphological and textural features extracted from breast ultrasound (BUS) images. The images are first preprocessed to enhance the edges and filter the speckles. The tumor is then segmented semiautomatically using the watershed method. Having the tumor contour, a set of 855 features including 21 shape-based, 810 contour-based, and 24 textural features are extracted from each tumor. Then, a Bayesian Automatic Relevance Detection (ARD) mechanism is used for computing the discrimination power of different features and dimensionality reduction. Finally, a logistic regression classifier computed the posterior probabilities of malignant vs benign tumors using the reduced set of features. RESULTS A dataset of 104 BUS images of breast tumors, including 72 benign and 32 malignant tumors, was used for evaluation using an eightfold cross-validation. The algorithm outperformed six state-of-the-art methods for BUS image classification with large margins by achieving 97.12% accuracy, 93.75% sensitivity, and 98.61% specificity rates. CONCLUSIONS Using ARD, the proposed CAD system selects five new features for breast tumor classification and outperforms state-of-the-art, making a reliable and complementary tool to help clinicians diagnose breast cancer.
The Effects Of Model Selection On The Guarantees On Target Volatility Funds

Target Volatility Funds are becoming a more and more popular asset class amongst Variable Annuity product designers. After the recent global crisis these funds provided a decent way to assure the guarantees that investors find so attractive. However, pricing of these guarantees highly depends on the modelling assumptions we use. Although this is an exciting and demanding problem, not much attention has been shed on this topic in the academic literature. In my work I extend some of the existing results to the Barndorff-Nielsen–Shephard model and to a Lévy-process with stochastic time.
Compassion and Loving-Kindness Meditation: An Overview and Prospects for the Application in Clinical Samples

Objectives This article presents a brief overview of the empirical evidence of well-established mindfulness interventions and an in-depth review of less-established compassion-based interventions (CBIs) and loving-kindness meditation (LKM). Definitions, cognitive and physiological mechanisms, and methods of assessment are discussed. Method A literature review using the databases Google Scholar, PsycINFO, and PubMed was conducted. Results Whereas the efficacy of mindfulness-based stress reduction and mindfulness-based cognitive therapy has been documented in many trials, only seven randomized, controlled trials have been completed on CBIs and LKM. In these trials, CBIs were effective in treating psychotic disorders, affective disorders with psychotic features, major depressive disorder, eating disorders, and patients with suicide attempts in the past year; LKM was effective in treating chronic pain; and a combination of both was effective for borderline personality disorder. A larger number of nonrandomized studies indicate that CBIs and LKM may be effective in treating a wide range of clinical conditions, including depression, anxiety disorders, chronic pain, and posttraumatic stress disorder. Conclusions Further studies are needed to confirm the promising effects of CBIs and LKM. Preliminary evidence suggests that both approaches might be beneficial across various clinical populations. Future studies need to clarify whether these approaches might be options as stand-alone treatments or as adjuncts or augmentation of evidence-based methods in psychotherapy.
High-Performance Limiting Current Oxygen Sensor Comprised of Highly Active La0.75Sr0.25Cr0.5Mn0.5O3 Electrode

Zirconia-based limiting current oxygen sensor gains considerable attention, due to its high-performance in improving the combustion efficiency of fossil fuels and reducing the emission of exhaust gases. Nevertheless, the Pt electrode is frequently used in the oxygen sensor, therefore, it restrains the broader application due to the high cost. Quite recently, La0.75Sr0. 25Cr0.5Mn0. 5O3 (LSCM) has been reported to be highly active to catalyze oxygen reduction. Herein, with the intention of replacing the frequently used Pt, we studied the practicability of adapting the LSCM to zirconia-based limiting current oxygen sensor. Through comparing the electrocatalytic activity of LSCM and Pt, it is confirmed that LSCM gave analogous oxygen reactivity with that of the Pt. Then, limiting the current oxygen sensors comprised of LSCM or Pt are fabricated and their sensing behavior to oxygen in the range of 2–25% is evaluated. Conclusively, quick response/recovery rate (within 7s), linear relationship, and high selectivity (against 5% CO2 and H2O) in sensing oxygen are observed for the sensors, regardless of the sensing materials (LSCM or Pt) that are used in the sensor. Particularly, identical sensing characteristics are observed for the sensors consisting of LSCM or Pt, indicating the practicability of replacing the Pt electrode by adapting the LSCM electrode to future zirconia-based oxygen sensors.
Extended thromboprophylaxis with betrixaban: a new standard for acute medically ill patients

The main advantage of understanding aetiological risks for any condition is that their recognition allows early targeted intervention in the form of preventive therapies, which ultimately reduce the burden of disease. This is particularly true for venous thromboembolism (VTE), the most significant preventable cause of morbidity and mortality in hospitalized patients. It has long been recognized that hospitalization for surgical and medical conditions is associated with 50% of the total burden of VTE, and half of this burden (23% of the total burden of VTE) occurs in the 3 months following admission to hospital for an acute medical illnesses. These figures are based on the presentation of symptomatic disease, and they significantly underestimate the attributable risk for VTE-related mortality. Studies have shown 70% of hospital-associated VTErelated mortality occurs in the acutely ill medical population. Prior to the APEX study with betrixaban, there were no United States Food and Drug Administration (FDA)approved therapies for extended VTE prophylaxis in acute medically ill patients at risk of VTE. Betrixaban was recognized as having unique properties that would suit the prevention of VTE in acute medically ill patients, and hence, the APEX study was undertaken with this drug. The results are clinically significant with a 36% relative risk reduction in symptomatic VTE in the overall APEX study population (P1⁄4 0.04), and therefore we the have the potential to reduce the overall burden of VTE by 10%. In the EU and USA, applying the APEX risk reductions to the epidemiological data means this has the potential to result in 30 000 fewer VTE-related deaths (18 000 and 12 000, respectively) and 50 000 fewer non-fatal symptomatic VTEs (30 000 and 20 000, respectively). In addition, based on the APEX data, extended-duration thromboprophylaxis with betrixaban may prevent one death for every 223 acute medically ill patients treated. In this supplement, we present the background of hospital-acquired thrombosis, the unmet need related to preventing VTE with extended thromboprophylaxis, and the pharmacology of betrixaban and its properties that suit the indication for extended VTE prophylaxis from hospitalization through post-discharge, as approved by the FDA. Finally, the primary results of the APEX study as well as post hoc analyses are reviewed.
Software Package For The Active Queue Management Module Model Verification

Self-oscillation modes in control systems of data transmission networks negatively affect the characteristics of these networks. To investigate the self-oscillation mode for systems with a control module, the analytical model of the active queue management module was developed. The problem of verification of the obtained theoretical results arises in the study. Previously, a software system was developed for software emulation of the router. However, its use has caused some difficulties. Alternatively, the simulation model of network with active queue management module was developed. The paper describes a software package for verifying theoretical calculations based on the NS-2 simulation system. For illustration, a numerical example is given. INTRODUCTION When modeling technical systems, there is often a question of verification of results. Either there is no access to data on the functioning of such systems, or the acquisition of data is associated with large resource and time costs. But some simulation experiments can be seen as a solution to this problem. The problem of the occurrence of self-oscillatory regime in systems with control is considered (see Lautenschlaeger and Francini (2015)). In particular, the active queue management modules with RED-like algorithms were studied. Based on the theoretical model (see Misra et al. (1999); Kulyabov et al. (2018)) of the functioning of the RED module, the parameters of self-oscillating regimes were investigated. However, for completeness of the study, the verification of the results is necessary. We have developed the installation for a full-scale experiment on the basis of emulation of images of network equipment (see Velieva et al. (2015)). However, this approach required some extra resources, which were not at authors disposal. So, as a substitute, it was suggested to use the simulation model. In this paper, the simulation model based on the NS-2 network protocol simulation tool is described. This approach proved to be more flexible in comparison with the full-scale experiment on the basis of emulation of network operating systems. RED ADAPTIVE CONGESTION CONTROL MECHANISM The RED algorithm (see Adams (2013); Kushwaha and Shwer (2013); Kushwaha and Gupta (2014)) uses a weighted queue length as a factor determining the probability of packets drop. As the average queue length grows, the probability of Proceedings 32nd European Conference on Modelling and Simulation ©ECMS Lars Nolle, Alexandra Burger, Christoph Tholen, Jens Werner, Jens Wellhausen (Editors) ISBN: 978-0-9932440-6-3/ ISBN: 978-0-9932440-7-0 (CD)
Integrating Cyber-Physical Systems in a Component-Based Approach for Smart Homes

Integration of different cyber-physical systems involves a development process that takes into account some solutions for intercommunicating and interoperating heterogeneous devices. Each device can be managed as a thing within the Internet-of-Things concept by using web technologies. In addition, a “thing” can be managed as an encapsulated component by applying component-based software engineering principles. Based on this context, we propose a solution for integrating heterogeneous systems using a specific component-based technology. Specifically, we focus on enabling the connection of different types of subsystems present in smart home solutions. This technology enables interoperability by applying a homogeneous component representation that provides communication features through web sockets, and by implementing gateways in proprietary network connections. Furthermore, our solution eases the extension of these systems by means of abstract representations of the architectures and devices that form part of them. The approach is validated through an example scenario with different subsystems of a smart home solution.
Pain-Associated Transcriptome Changes in Synovium of Knee Osteoarthritis Patients

Joint pain causes significant morbidity in osteoarthritis (OA). The aetiology of joint pain in OA is not well understood. The synovial membrane as an innervated joint structure represents a potential source of peripheral pain in OA. Here we analyse, using a hypothesis-free next generation RNA sequencing, the differences in protein-coding and non-coding transcriptomes in knee synovial tissues from OA patients with high knee pain (n = 5) compared with OA patients with low knee pain (n = 5), as evaluated by visual analogue scale (VAS). We conduct Gene Ontology and pathway analyses on differentially expressed mRNA genes. We identify new protein-coding, long non-coding RNA and microRNA candidates that can be associated with OA joint pain. Top enriched genes in painful OA knees encode neuronal proteins that are known to promote neuronal survival under cellular stress or participate in calcium-dependent synaptic exocytosis and modulation of GABA(γ-aminobutyric acid)ergic activity. Our study uncovers transcriptome changes associated with pain in synovial microenvironment of OA knees. This sets a firm ground for future mechanistic studies and drug discovery to alleviate joint pain in OA.
Evaluation of the immune response against Trypanosoma cruzi cytosolic tryparedoxin peroxidase in human natural infection

Trypanosoma cruzi, the aetiological agent of Chagas disease, has a highly efficient detoxification system to deal with the oxidative burst imposed by its host. One of the antioxidant enzymes involved is the cytosolic tryparedoxin peroxidase (c‐TXNPx), which catalyses the reduction to hydrogen peroxide, small‐chain organic hydroperoxides and peroxynitrite. This enzyme is present in all parasite stages, and its overexpression renders parasites more resistant to the oxidative defences of macrophages, favouring parasite survival. This work addressed the study of the specific humoral and cellular immune response triggered by c‐TXNPx in human natural infection. Thus, sera and peripheral blood mononuclear cells (PBMC) were collected from chronically infected asymptomatic and cardiac patients, and non‐infected individuals. Results showed that levels of IgG antibodies against c‐TXNPx were low in sera from individuals across all groups. B‐cell epitope prediction limited immunogenicity to a few, small regions on the c‐TXNPx sequence. At a cellular level, PBMC from asymptomatic and cardiac patients proliferated and secreted interferon‐γ after c‐TXNPx stimulation, compared with mock control. However, only proliferation was higher in asymptomatic patients compared with cardiac and non‐infected individuals. Furthermore, asymptomatic patients showed an enhanced frequency of CD19+ CD69+ cells upon exposure to c‐TXNPx. Overall, our results show that c‐TXNPx fails to induce a strong immune response in natural infection, being measurable only in those patients without any clinical symptoms. The low impact of c‐TXNPx in the human immune response could be strategic for parasite survival, as it keeps this crucial antioxidant enzyme activity safe from the mechanisms of adaptive immune response.
Hidden Policy Attribute-Based Data Sharing with Direct Revocation and Keyword Search in Cloud Computing

Attribute-based encryption can be used to realize fine-grained data sharing in open networks. However, in practical applications, we have to address further challenging issues, such as attribute revocation and data search. How do data users search for the data they need in massive amounts of data? When users leave the system, they lose the right to decrypt the shared data. In this case, how do we ensure that revoked users cannot decrypt shared data? In this paper, we successfully address these issues by proposing a hidden policy attribute-based data sharing scheme with direct revocation and keyword search. In the proposed scheme, the direct revocation of attributes does not need to update the private key of non-revoked users during revocation. In addition, a keyword search is realized in our scheme, and the search time is constant with the increase in attributes. In particular, the policy is hidden in our scheme, and hence, users’ privacy is protected. Our security and performance analyses show that the proposed scheme can tackle the security and efficiency concerns in cloud computing.