Normalized Solutions to the Fractional Schrödinger Equation with Potential

This paper is concerned with the existence of normalized solutions to a class of Schrödinger equations driven by a fractional operator with a parametric potential term. We obtain minimization of energy functional associated with that equations assuming basic conditions for the potential. Our work offers a partial extension of previous results to the non-local case

On The Impact of Passive Voice Requirements on Domain Modelling

Context: The requirements specification is a central arte- fact in the software engineering (SE) process, and its quality (might) influence downstream activities like implementation or testing. One quality defect that is often mentioned in standards is the use of passive voice. However, the con- sequences of this defect are still unclear. Goal: We need to understand whether the use of passive voice in requirements has an influence on other activities in SE. In this work we focus on domain modelling. Method: We designed an experiment, in which we ask students to draw a domain model from a given set of requirements written in active or passive voice. We compared the completeness of the resulting domain model by counting the number of missing actors, domain objects and their associations with respect to a specified solution. Results: While we could not see a difference in the number of missing actors and objects, participants which received passive sentences missed almost twice the associations. Conclusion: Our experiment indicates that, against common knowledge, actors and objects in a requirement can often be understood from the context. However, the study also shows that passive sentences complicate understanding how certain domain concepts are interconnected

A Recommender System for Telecom Users: Experimental Evaluation of Recommendation Algorithms

The increasing flourish of available services in telecom domain offers more choices to the end user. On the other hand, such wide offer cannot be completely evaluated by the user, and some services may pass unobserved even if useful. To face this issue, the usage of recommendation systems in telecom domain is growing, to directly notify the user about the presence of services which may meet user interests. Recommendation can be seen as an advanced form of personalization, because user preferences are used to predict the interests of users for a new service. In this paper we propose a recommender system for users of telecom services, based on different collaborative filtering algorithms applied to a complex data-set of telecom users. Experiments on the recommendation performance and accuracy are conducted to test the different effects of different algorithms on a data set coming from the telecom domain

The Invisible Power of Fairness. How Machine Learning Shapes Democracy

Many machine learning systems make extensive use of large amounts of data regarding human behaviors. Several researchers have found various discriminatory practices related to the use of human-related machine learning systems, for example in the field of criminal justice, credit scoring and advertising. Fair machine learning is therefore emerging as a new field of study to mitigate biases that are inadvertently incorporated into algorithms. Data scientists and computer engineers are making various efforts to provide definitions of fairness. In this paper, we provide an overview of the most widespread definitions of fairness in the field of machine learning, arguing that the ideas highlighting each formalization are closely related to different ideas of justice and to different interpretations of democracy embedded in our culture. This work intends to analyze the definitions of fairness that have been proposed to date to interpret the underlying criteria and to relate them to different ideas of democracy

An MPEG-7 scheme for semantic content modelling and filtering of digital video

Abstract Part 5 of the MPEG-7 standard specifies Multimedia Description Schemes (MDS); that is, the format multimedia content models should conform to in order to ensure interoperability across multiple platforms and applications. However, the standard does not specify how the content or the associated model may be filtered. This paper proposes an MPEG-7 scheme which can be deployed for digital video content modelling and filtering. The proposed scheme, COSMOS-7, produces rich and multi-faceted semantic content models and supports a content-based filtering approach that only analyses content relating directly to the preferred content requirements of the user. We present details of the scheme, front-end systems used for content modelling and filtering and experiences with a number of users

Analysis of frame-compatible subsampling structures for efficient 3DTV broadcast

The evolution of the television market is led by 3DTV technology, and this tendency can accelerate during the next years according to expert forecasts. However, 3DTV delivery by broadcast networks is not currently developed enough, and acts as a bottleneck for the complete deployment of the technology. Thus, increasing interest is dedicated to ste-reo 3DTV formats compatible with current HDTV video equipment and infrastructure, as they may greatly encourage 3D acceptance. In this paper, different subsampling schemes for HDTV compatible transmission of both progressive and interlaced stereo 3DTV are studied and compared. The frequency characteristics and preserved frequency content of each scheme are analyzed, and a simple interpolation filter is specially designed. Finally, the advantages and disadvantages of the different schemes and filters are evaluated through quality testing on several progressive and interlaced video sequences

Exploring functional pairing between surface glycoconjugates and human galectins using programmable glycodendrimersomes

Precise translation of glycan-encoded information into cellular activity depends critically on highly specific functional pairing between glycans and their human lectin counter receptors. Sulfoglycolipids, such as sulfatides, are important glycolipid components of the biological membranes found in the nervous and immune systems. The optimal molecular and spatial design aspects of sulfated and nonsulfated glycans with high specificity for lectin-mediated bridging are unknown. To elucidate how different molecular and spatial aspects combine to ensure the high specificity of lectin-mediated bridging, a bottom-up toolbox is devised. To this end, negatively surface-charged glycodendrimersomes (GDSs), of different nanoscale dimensions, containing sulfo-lactose groups are self-assembled in buffer from a synthetic sulfatide mimic: Janus glycodendrimer (JGD) containing a 3′-O-sulfo-lactose headgroup. Also prepared for comparative analysis are GDSs with nonsulfated lactose, a common epitope of human membranes. These self-assembled GDSs are employed in aggregation assays with 15 galectins, comprising disease-related human galectins, and other natural and engineered variants from four families, having homodimeric, heterodimeric, and chimera architectures. There are pronounced differences in aggregation capacity between human homodimeric and heterodimeric galectins, and also with respect to their responsiveness to the charge of carbohydrate-derived ligand. Assays reveal strong differential impact of ligand surface charge and density, as well as lectin concentration and structure, on the extent of surface cross-linking. These findings demonstrate how synthetic JGD-headgroup tailoring teamed with protein engineering and network assays can help explain how molecular matchmaking operates in the cellular context of glycan and lectin complexity

Dactinomycin induces complete remission associated with nucleolar stress response in relapsed/refractory NPM1-mutated AML

Acute myeloid leukemia (AML) with mutated NPM1 accounts for one-third of newly diagnosed AML. Despite recent advances, treatment of relapsed/refractory NPM1-mutated AML remains challenging, with the majority of patients eventually dying due to disease progression. Moreover, the prognosis is particularly poor in elderly and unfit patients, mainly because they cannot receive intensive treatment. Therefore, alternative treatment strategies are needed. Dactinomycin is a low-cost chemotherapeutic agent, which has been anecdotally reported to induce remission in NPM1-mutated patients, although its mechanism of action remains unclear. Here, we describe the results of a single-center phase 2 pilot study investigating the safety and efficacy of single-agent dactinomycin in relapsed/refractory NPM1-mutated adult AML patients, demonstrating that this drug can induce complete responses and is relatively well tolerated. We also provide evidence that the activity of dactinomycin associates with nucleolar stress both in vitro and in vivo in patients. Finally, we show that low-dose dactinomycin generates more efficient stress response in cells expressing NPM1 mutant compared to wild-type cells, suggesting that NPM1-mutated AML may be more sensitive to nucleolar stress. In conclusion, we establish that dactinomycin is a potential therapeutic alternative in relapsed/refractory NPM1-mutated AML that deserves further investigation in larger clinical studies