Miracle-dz/UniFAR-FTUs huggingface dataset:
Outcomes and costs of treating chronic obstructive pulmonary disease with inhaled fixed combinations: the Italian perspective of the PATHOS study

Purpose Fixed-dose combinations of inhaled corticosteroids and long-acting β2-agonists have proven to prevent and reduce chronic obstructive pulmonary disease (COPD) exacerbations. The aim of this analysis was to explore the clinical consequences and direct health care costs of applying the findings of the PATHOS (An Investigation of the Past 10 Years Health Care for Primary Care Patients with Chronic Obstructive Pulmonary Disease) study to the Italian context. Patients and methods Effectiveness data from the PATHOS study, a population-based, retrospective, observational registry study conducted in Sweden, in terms of reduction in COPD and pneumonia-related hospitalizations, were considered, in order to estimate the differences in resource consumption between patients treated with budesonide/formoterol and fluticasone/salmeterol. The base case considers the average dosages of the two drugs reported in the PATHOS study and the actual public price in charges to the Italian National Health Service, while the difference in hospitalization rates reported in the PATHOS study was costed based on Italian real-world data. Results The PATHOS study demonstrated a significant reduction in COPD hospitalizations and pneumonia-related hospitalizations in patients treated with budesonide/formoterol versus fluticasone/salmeterol (−29.1% and −42%, respectively). In the base case, the treatment of a patient for 1 year with budesonide/formoterol led to a saving of €499.90 (€195.10 for drugs, €193.10 for COPD hospitalizations, and €111.70 for pneumonia hospitalizations) corresponding to a −27.6% difference compared with fluticasone/salmeterol treatment. Conclusion Treatment of COPD with budesonide/formoterol compared with fluticasone/salmeterol could lead to a reduction in direct health care costs, with relevant improvement in clinical outcomes.
Region of attraction estimates for LPV-gain scheduled control systems

Recent methods for gain scheduling controller design based on linear parameter-varying (LPV) systems offer a systematic way to obtain a nonlinear controller that covers different operating conditions. However, despite that the LPV synthesis part of the process of obtaining a gain scheduled controller is theoretically straight forward, the nonlinear closed loop system may be unstable for some operating conditions. This property is illustrated by a simple second order autonomous nonlinear system, the well known Van der Pol equation. Furthermore, a region of attraction estimate based on the LPV analysis for the nonlinear system is given.
Towards a heterogeneous simulation kernel for system-level models: a SystemC kernel for synchronous data flow models

As SystemC gains popularity as a modeling language of choice for system-on-chip (SoC) designs, heterogeneous modeling in SystemC and efficient simulation become increasingly important. However, in the current reference implementation, all SystemC models are simulated through a nondeterministic discrete-event (DE) simulation kernel that schedules events at run time mimicking other models of computation (MoCs) using DE, which may get cumbersome. This sometimes results in too many delta cycles hindering the simulation performance of the model. SystemC also uses this simulation kernel as the target simulation engine. This makes it difficult to express different MoCs naturally in SystemC. In an SoC model, different components may need to be naturally expressible in different MoCs. These components may be amenable to static scheduling-based simulation or other presimulation optimization techniques. The goal is to create a simulation framework for heterogeneous SystemC models and to gain efficiency and ease of use within the framework of SystemC reference implementation. In this paper, a synchronous data flow (SDF) kernel extension for SystemC is introduced. Experimental results showing improvement in simulation time are also presented.
Applying Evolutionary Thinking to the Study of Emotion

This paper argues for invoking evolutionary, functional thinking in analyzing emotions. It suggests that the fitness needs of normal individuals be kept in mind when trying to understand emotional behavior. This point of view is elaborated in sections addressing these topics: defining emotion; applying comparative analysis to the study of emotions; focusing on the elicitors and resulting motivated behaviors mediated by the various affects; recognizing that not all emotions have prominent, distinct facial expressions; acknowledging all of the basic emotions and not just some exemplars; crediting the more sensible Cannon-Bard theory over James-Lange; recognizing the more ancient, fundamental role of the limbic system in emotion compared with that of the neocortex; and analyzing socio-emotional interactions as they occur naturally, not just individual emotional behavior studied under artificial conditions. Describing the various facets and neuroendocrine mechanisms of each basic emotion can provide a framework for understanding the normal and pathological development of each emotion. Such an inventory, or ethogram, would provide a comprehensive list of all of the observable behavioral tendencies of our species.
People Searched by People: Context-Based Selectiveness in Online Search

In the age of the internet, the ability to fully control online information about oneself is no longer possible; once information is online, it is easily disseminated and quickly becomes part of the internet archive. In this paper, we explore data from a set of in-person questionnaires and contextual interviews with both searchers and searched individuals and an additional data set from an online survey of internet users to identify strategies for vetting, managing, and interpreting content online. We see a desire for agency, a contextualization of information based on social context and temporal context, and a desire to constrain the exploration of online content to a relevant subset of information when searching others, i.e. a desire for selectiveness. We offer an evocative design sketch to highlight these issues and foster a discussion of emerging socio-cultural norms around online search behavior.
Evolutionary Dynamics of Intratumor Heterogeneity

Intraneoplastic diversity in human tumors is a widespread phenomenon of critical importance for tumor progression and the response to therapeutic intervention. Insights into the evolutionary events that control tumor heterogeneity would be a major breakthrough in our comprehension of cancer development and could lead to more effective prevention methods and therapies. In this paper, we design an evolutionary mathematical framework to study the dynamics of heterogeneity over time. We consider specific situations arising during tumorigenesis, such as the emergence of positively selected mutations (“drivers”) and the accumulation of neutral variation (“passengers”). We perform exact computer simulations of the emergence of diverse tumor cell clones over time, and derive analytical estimates for the extent of heterogeneity within a population of cancer cells. Our methods contribute to a quantitative understanding of tumor heterogeneity and the impact of heritable alterations on this tumor trait.
Optimal controller initialization for switching between stabilizing controllers

An important class of switched systems consists of those systems built as the feedback interconnection of a plant to be controlled, together with a multicontroller whose dynamics switch. When designing this type of switching controllers, one is faced with the questions of how to select controller realizations and how to initialize the state of the controllers as they are switched into the feedback loop. This paper deals with these questions for the problem of switching between linear time- invariant controllers. We show that significant improvements in closed-loop performance can be attained by optimally choosing the initial state of a controller, as this controller is switched into the feedback loop. By including appropriate constraints on the optimizations used to select controller initializations, we show that the resulting switched closed-loop can be made uniformly input-to-state stable for arbitrary switching. Simulations illustrate the benefits of our approach with respect to others previously suggested in the literature.
Trends in adsorption characteristics of benzene on transition metal surfaces: Role of surface chemistry and van der Waals interactions

: The accurate description of interface characteristics between organic molecules and metal surfaces has long been debated in theoretical studies. A well-founded description of interface geometry and adsorption energy is highly desirable for these hybrid inorganic/organic interfaces. Using first principles calculations with the inclusion of five van der Waals functionals (vdW-DF family), benzene (C6H6) adsorption on seven transition metal surfaces is studied to explore the performance of these vdW functionals under varying surface chemistry. Our results reveal that vdW interactions are crucial for an accurate description of bonding on transition metal substrates. We find that vdW interactions increase adsorption energy on coinage metal surfaces (Au, Ag, Cu) by about 0.7 eV, while they lead to even larger increases in the adsorption energies on the reactive transition metal surfaces (Pd, Pt, Rh, Ni). Our calculations also reveal that changes in adsorption energies stemming from vdW functionals show significant variation, and can be grouped. We find the adsorption energies and heights on the reactive transition metal surfaces obtained using vdW-DF and vdW-DF2 functionals to differ significantly from those of the opt-type functionals, revealing the intrinsic strong repulsion character at short ranges for the former functionals. A simple comparison between experimentally determined adsorption energies (averaged) and those of computed suggests that optPBE and optB88 functionals show systematically good agreement. The information acquired from our analysis on the performance of these functionals can be used as a basis for further refinement of these functionals for the adsorption Abstract The accurate description of interface characteristics between organic molecules and metal surfaces has long been debated in theoretical studies. All proposed methods revealed the importance of van der Waals interactions. Using first principles calculations with the inclusion of five van der Waals functionals, Benzene (C 6 H 6 ) adsorption on coinage and transition metal surfaces are studied to explore the performance of these functionals under varying surface chemistries. Our results reveal that van der Waals interactions are crucial for an accurate description of bonding not only for coinage, but also for transition metal substrates. Moreover, adsorption energy results stemming from these five functionals show significant variation, with a trend that allows a grouping based on the calculated adsorption strengths. A simple comparison between the averaged experimentally determined adsorption energies and those computed suggests that optPBE and optB88 functionals show systematically good agreements. The information acquired from our comprehensive analysis on the performance of these functionals is of broad interest, and in particular, can be used as a basis for further refinement of these functionals for varying surface chemistry.
Uporaba emotivno pogojenega računalništva v priporočilnih sistemih

Povzetek. V članku predstavljamo rezultate treh raziskav, vezanih na izboljšanje delovanja multimedijskih priporočilnih sistemov s pomočjo metod emotivno pogojenega računalništva (ang. affective computing). Vsebinski priporočilni sistem smo izboljšali s pomočjo metapodatkov, ki opisujejo emotivne odzive uporabnikov. Pri skupinskem priporočilnem sistemu smo dosegli značilno izboljšanje v območju hladnega zagona z uvedbo nove mere podobnosti, ki temelji na osebnostnem modelu velikih pet (ang. five factor model). Razvili smo tudi sistem za neinvazivno označevanje vsebin z emotivnimi parametri, ki pa še ni zrel za uporabo v priporočilnih sistemih.
Reinforcement Learning of POMDPs using Spectral Methods

Author(s): Azizzadenesheli, Kamyar; Lazaric, Alessandro; Anandkumar, Animashree | Abstract: We propose a new reinforcement learning algorithm for partially observable Markov decision processes (POMDP) based on spectral decomposition methods. While spectral methods have been previously employed for consistent learning of (passive) latent variable models such as hidden Markov models, POMDPs are more challenging since the learner interacts with the environment and possibly changes the future observations in the process. We devise a learning algorithm running through episodes, in each episode we employ spectral techniques to learn the POMDP parameters from a trajectory generated by a fixed policy. At the end of the episode, an optimization oracle returns the optimal memoryless planning policy which maximizes the expected reward based on the estimated POMDP model. We prove an order-optimal regret bound with respect to the optimal memoryless policy and efficient scaling with respect to the dimensionality of observation and action spaces.
Current Account Imbalances and Structural Adjustment in the Euro Area: How to Rebalance Competitiveness

Low international competitiveness of a set of euro area countries, which have become evident by large current account deficits and rising risk premiums on government bonds, is one of the most challenging economic policy issues for Europe. We analyse the role of private restructuring and public structural reforms for the urgently needed readjustment of intra-euro area imbalances. A panel regression reveals a significant impact of private restructuring and public structural reforms on intra-euro area competitiveness. This implies that private restructuring and public reforms are rather than public transfers the best way to preserve long-term economic stability in Europe.
Searchable Keyword-Based Encryption

To solve the problem of searching on encrypted data, many keyword search schemes have been proposed in recent years. The goal of such schemes is to enable a user to give an untrusted storage server the ability only to test whether an encrypted document contains a few keywords without learning anything else about the document. In this paper, we are concerned with decrypting the searched results as well as searching for desired documents. In the previously proposed schemes, except for the work by Waters et al. [26], a user decrypts searched documents using his private key, Apriv, or a symmetric key. Our another goal is to enable a user to give a proxy the ability to decrypt only the ciphertexts containing desired keywords, but not other ciphertexts. We propose a new mechanism, Searchable Keyword-Based Encryption (SKBE) which satisfles both the above goals. As a result of adding the delegation of decryption ability, our mechanism works more securely and e‐ciently in several applications, such as email gateways, secure audit logs, and decryption key delegation systems, than any of the previously proposed schemes. We formalize this mechanism, deflne its security model and propose an e‐cient construction whose security is proved in a random oracle model under the Bilinear Di‐e-Hellman Inversion assumption. The scheme is constructed based on the Public Key Encryption with Conjunctive Field Keyword Search scheme in [21] by using a hybrid encryption technique.
Case Studies: Memory Behavior of Multithreaded Multimedia and AI Applications

Memory performance becomes a dominant factor for today’s microprocessor applications. In this paper, we study memory reference behavior of emerging multimedia and AI applications. We compare memory performance for sequential and multithreaded versions of the applications on multithreaded processors. The methodology we used including workload selection and parallelization, benchmarking and measurement, memory trace collection and verification, and tracedriven memory performance simulations. The results from the case studies show that opposite reference behavior, either constructive or disruptive, could be a result for different programs. Care must be taken to make sure the disruptive memory references will not outweigh the benefit of parallelization.
Distributed MAC Protocol for Cognitive Radio Networks: Design, Analysis, and Optimization

In this paper, we investigate the joint optimal sensing and distributed Medium Access Control (MAC) protocol design problem for cognitive radio (CR) networks. We consider both scenarios with single and multiple channels. For each scenario, we design a synchronized MAC protocol for dynamic spectrum sharing among multiple secondary users (SUs), which incorporates spectrum sensing for protecting active primary users (PUs). We perform saturation throughput analysis for the corresponding proposed MAC protocols that explicitly capture the spectrum-sensing performance. Then, we find their optimal configuration by formulating throughput maximization problems subject to detection probability constraints for PUs. In particular, the optimal solution of the optimization problem returns the required sensing time for PUs' protection and optimal contention window to maximize the total throughput of the secondary network. Finally, numerical results are presented to illustrate developed theoretical findings in this paper and significant performance gains of the optimal sensing and protocol configuration.
White Paper: Mobile Knowledge Management

Mobile Knowledge Management (mKM) systems try to incorporate the technical progresses in the field of Mobile Computing, such as mobile networks and mobile and personal devices, into IT-solutions supporting Knowledge Management in organisations. This report intends to identify the challenges of mKM and establish the conceptual definitions in this regard within mummy. After providing a shared understanding of the relevant terms, we introduce the mummy definition of mKM and discuss the problems and requirements in this field. Consequently, we first discuss the abstract use cases for mKM systems and then introduce the key concepts in mummy for resolving selected problems and meeting the related requirements. Finally, we summarise the concepts by providing a reference model.
Pregabalin in Neuropathic Pain: Evidences and Possible Mechanisms

Pregabalin is an antagonist of voltage gated Ca2+ channels and specifically binds to alpha-2-delta subunit to produce antiepileptic and analgesic actions. It successfully alleviates the symptoms of various types of neuropathic pain and presents itself as a first line therapeutic agent with remarkable safety and efficacy. Preclinical studies in various animal models of neuropathic pain have shown its effectiveness in treating the symptoms like allodynia and hyperalgesia. Clinical studies in different age groups and in different types of neuropathic pain (peripheral diabetic neuropathy, fibromyalgia, post-herpetic neuralgia, cancer chemotherapy-induced neuropathic pain) have projected it as the most effective agent either as monotherapy or in combined regimens in terms of cost effectiveness, tolerability and overall improvement in neuropathic pain states. Preclinical studies employing pregabalin in different neuropathic pain models have explored various molecular targets and the signaling systems including Ca2+ channel-mediated neurotransmitter release, activation of excitatory amino acid transporters (EAATs), potassium channels and inhibition of pathways involving inflammatory mediators. The present review summarizes the important aspects of pregabalin as analgesic in preclinical and clinical studies as well as focuses on the possible mechanisms.
The Role of Intellectual Property Rights in Technology Transfer and Economic Growth: Theory and Evidence

Following the conclusion of the TRIPS Agreement much has been written on the potential costs and benefits of stronger Intellectual Property Rights (IPRs) protection in terms of growth and technology transfer, particularly for developing countries. This paper reviews this literature and provides new evidence linking protection of IPRs to economic growth, innovation and technology diffusion. Results suggest that while stronger IPR protection can ultimately reap rewards in terms of greater domestic innovation and increased technology diffusion in developing countries with sufficient capacity to innovate, it has little impact on innovation and diffusion in those without such capacity and may impose additional costs, especially for the least developed countries that will be precluded from using imitation as a means to develop innovative capacity. There is a considerable incentive, therefore, for countries at different stages of development to use the flexibilities in the TRIPS Agreement to maximise its net benefits for their development. + We would like to thank Olga Memedovic and David Greenaway for useful comments, and Michael Bailey for proofreading the final document. * Professor of International Economics, Leverhulme Centre for Research on Globalisation and Economic Policy, School of Economics, The University of Nottingham, University Park, Nottingham, NG7 2RD, UK. Email: rod.falvey@nottingham.ac. uk † Assistant Professor of Economics, Department of Economics, The University of Vienna, Hohenstaufengasse 9, Vienna, A-1010, Austria. Email: neil.foster@univie.ac. at
PiRAT: Pivot Routing for Alarm Transmission in wireless sensor networks

Wireless sensor networks are increasingly used for remote monitoring, fire detection, emergency response. Such networks are equipped with small devices powered by batteries and designed to be operated for years. They are often based on the ZigBee standard which defines low power and low data rate protocols. As network size and data rates increase, congestion arises as a problem in these networks, especially when an emergency situation generates alarm messages in a specific area in the network. Indeed, congestion occurs as the alarms converge to a specific destination, which results into packet losses and higher delays. In this paper, we propose a solution for congested links, called the PiRAT (Pivot Routing for Alarm Transmission) protocol. It is based on multi-path routing in order to add some diversity in routing the alarms. PiRAT uses intermediate nodes as pivots to reach the destination. Simulation results show that PiRAT has better performance than previous protocols in terms of packet loss, end-to-end delay, congestion and node overload.
Recent advances in the understanding of immune-mediated nephrotic syndrome: diagnostic and prognostic implications

Glomerular diseases with severe defects in glomerular permeability give rise to heavy proteinuria and can present as nephrotic syndrome. There are many different causes of the nephrotic syndrome and a renal biopsy is nearly always needed to elucidate the underlying disease. During the last decade, substantial advances have occurred in the understanding of the pathophysiological mechanisms involved in immune-mediated glomerular diseases. Here, we review the diagnostic and prognostic implications of recent progress on the understanding of membranous nephropathy, minimal change disease, focal segmental glomerulosclerosis, amyloidosis, IgA nephropathy and membranoproliferative glomerulonephritis.