Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytokine Response Patterns in Severe Pandemic 2009 H1N1 and Seasonal Influenza among Hospitalized Adults

Background Studying cytokine/chemokine responses in severe influenza infections caused by different virus subtypes may improve understanding on pathogenesis. Methods Adults hospitalized for laboratory-confirmed seasonal and pandemic 2009 A/H1N1 (pH1N1) influenza were studied. Plasma concentrations of 13 cytokines/chemokines were measured at presentation and then serially, using cytometric-bead-array with flow-cytometry and ELISA. PBMCs from influenza patients were studied for cytokine/chemokine expression using ex-vivo culture (Whole Blood Assay,±PHA/LPS stimulation). Clinical variables were prospectively recorded and analyzed. Results 63 pH1N1 and 53 seasonal influenza patients were studied. pH1N1 patients were younger (mean±S.D. 42.8±19.2 vs 70.5±16.7 years), and fewer had comorbidities. Respiratory/cardiovascular complications were common in both groups (71.4% vs 81.1%), although severe pneumonia with hypoxemia (54.0% vs 28.3%) and ICU admissions (25.4% vs 1.9%) were more frequent with pH1N1. Hyperactivation of the proinflammatory cytokines IL-6, CXCL8/IL-8, CCL2/MCP-1 and sTNFR-1 was found in pH1N1 pneumonia (2–15 times normal) and in complicated seasonal influenza, but not in milder pH1N1 infections. The adaptive-immunity (Th1/Th17)-related CXCL10/IP-10, CXCL9/MIG and IL-17A however, were markedly suppressed in severe pH1N1 pneumonia (2–27 times lower than seasonal influenza; P−values<0.01). This pattern was further confirmed with serial measurements. Hypercytokinemia tended to be sustained in pH1N1 pneumonia, associated with a slower viral clearance [PCR-negativity: day 3–4, 55% vs 85%; day 6–7, 67% vs 100%]. Elevated proinflammatory cytokines, particularly IL-6, predicted ICU admission (adjusted OR 12.6, 95%CI 2.6–61.5, per log10unit increase; P = 0.002), and correlated with fever, tachypnoea, deoxygenation, and length-of-stay (Spearman's rho, P-values<0.01) in influenza infections. PBMCs in seasonal influenza patients were activated and expressed cytokines ex vivo (e.g. IL-6, CXCL8/IL-8, CCL2/MCP-1, CXCL10/IP-10, CXCL9/MIG); their ‘responsiveness’ to stimuli was shown to change dynamically during the illness course. Conclusions A hyperactivated proinflammatory, but suppressed adaptive-immunity (Th1/Th17)-related cytokine response pattern was found in severe pH1N1 pneumonia, different from seasonal influenza. Cytokine/immune-dysregulation may be important in its pathogenesis.
Trickle-Down Effects of Positive and Negative Supervisor Behaviors on Service Performance: The Roles of Employee Emotional Labor and Perceived Supervisor Power

ABSTRACT Based on the trickle-down model, the present study simultaneously examined how transformational leadership and abusive supervision influence employees’ proactive customer service performance and service sabotage through employees’ emotional labor strategies toward customers. Moreover, this study examines whether perceived supervisor power can activate or inhibit the aforementioned trickle-down processes. The present study collected data from 186 service employees–supervisor pairs at different times. The results of structural equation modeling indicate that transformational leadership positively predicted employees’ proactive customer service performance via deep acting, whereas abusive supervision was positively associated with employees’ service sabotage through surface acting. Furthermore, being perceived as a powerful supervisor is an important factor to maximize the benefits of transformational leadership. The theoretical and practical implications are further discussed.
A framework for a recommendation system based on collaborative filtering and demographics

Recommendation systems attempt to predict the preference or rating that a user would give to an item. Knowledge discovery techniques can be applied to the problem of making personalized recommendations about items or information during a user's visit to a website. Collaborative Filtering algorithms give recommendations to a user based on the ratings of other users in the system. Traditional collaborative filtering algorithms face issues such as scalability, sparsity and cold start. In the proposed framework, prediction using item based collaborative filtering is combined with prediction using demographics based user clusters in an adaptive weighted scheme. The proposed solution will be scalable while addressing user cold start.
CRUISE TOURISM AS FACTOR OF SOCIAL EXCLUSION ON COZUMEL ISLAND´S RESIDENTS’ PERCEPTION

espanolCozumel es una isla que se ha desarrollado como destino turistico, durante los ultimos 15 anos se ha orientado al turismo de cruceros y hoy esta actividad es el motor de su economia. A la isla arriban la mayoria de las lineas navieras que ofrecen este servicio turistico y por ello es un caso muy representativo de la forma en la que se desarrolla e integra la comunidad con la accion local. No obstante, se evidencian hoy datos de que no obstante el desarrollo acelerado de este mercado y de su movimiento internacional, muy poco beneficia en general a las sociedades locales, probablemente incluso impulsa la exclusion social. Se analiza la percepcion de los residentes locales respecto a la forma en la que el turismo de cruceros impulsa la exclusion social, entendida en el marco desarrollado por Levitas y colaboradores (2007), mediante un estudio del caso de Cozumel en Mexico, mediante un diseno metodologico mixto, cuantitativo y cualitativo en dos etapas. Los hallazgos conducen a corroborar que el turismo de cruceros, al menos en este caso ejemplar, conduce a la percepcion de un incremento de los factores que impulsan la generacion de exclusion social. Se presentan los principales hallazgos y lineas futuras de investigacion. EnglishCozumel is an island that has been developed as a tourist destination and during the last 15 years tourism activity has been oriented to cruise tourism, which is the main driver of the island economy. Most of the cruise lines with operations in the Caribbean have arrivals to the island, and therefore it is a case that highly represents the way how community develops and integrates with the local action. Nevertheless there is evidence that, even though the rapid development and the international flow, cruise tourism brings little benefit to local communities in general and it might even promote social exclusion. The paper analyzes Cozumel residents’ perception about the way cruise tourism is a driver of social exclusion, understood from the conceptual frame developed by Levitas et. al. (2007) through a case study at Cozumel, Mexico, which was carried out using a two-stage mixed method design (quantitative and qualitative). Findings lead to confirm that, at least for the case study, cruise tourism produces the perception of an increase on the factors that drive social exclusion. Main findings and future research lines are presented.
Long-Term Behavioural Change Detection through Pervasive Sensing

The paper proposes an information generation and summarisation algorithm to detect behavioural change in applications such as long-term monitoring of vulnerable people. The algorithm learns the monitored subject's behaviour autonomously post-deployment and provides time-suppressed summaries of the activity types engaged with by the subject over the course of their day to day life. It transmits updates to external observers only when the summary changes by more than a defined threshold. This technique substantially reduces the number of transmission required by a wearable monitoring system, both through summarisation of the raw data into useful information and by preventing transmission of duplicated or predictable data and information. Based on evaluation using simulated activity data, the proposed algorithm results in an average of one transmission per month following an initial convergence period (reaching less than 1 transmission per day after only three days) and detects a change in behaviour after an average of 1.1 days.
Automatic detection of red lesions in Diabetic Retinopathy using Shape based extraction technique in fundus image

The paper proposes an automatic image processing algorithm based on shape features for the detection of red lesions. In Diabetic Retinopathy Micro-aneurysms and hemorrhages comes under the category of red lesions, which is the most common eye disease caused in diabetic patients and also leads to blindness. This paper describes an effective methodology to study any computer-aided fundus image that can be utilized as a tool for diagnosis and detection of red lesions. A Shape based extraction technique using three parameters i.e. Perimeter Area and Eccentricity is used to segment out the red lesions from rest of the image. Since the algorithm consider shape features for detection of red lesion which makes it efficient and independent of image quality. The results that are experimentally obtained by applying this algorithm has been compared with those of the ophthalmologist and the comparison of these results have been highly accurate. In addition to the accuracy of the obtained results, the proposed method is fast and having very low computational time.
The Genetic Analysis of an Acinetobacter johnsonii Clinical Strain Evidenced the Presence of Horizontal Genetic Transfer

Acinetobacter johnsonii rarely causes human infections. While most A. johnsonii isolates are susceptible to virtually all antibiotics, strains harboring a variety of β-lactamases have recently been described. An A. johnsonii Aj2199 clinical strain recovered from a hospital in Buenos Aires produces PER-2 and OXA-58. We decided to delve into its genome by obtaining the whole genome sequence of the Aj2199 strain. Genome comparison studies on Aj2199 revealed 240 unique genes and a close relation to strain WJ10621, isolated from the urine of a patient in China. Genomic analysis showed evidence of horizontal genetic transfer (HGT) events. Forty-five insertion sequences and two intact prophages were found in addition to several resistance determinants such as blaPER-2, blaOXA-58, blaTEM-1, strA, strB, ereA, sul1, aacC2 and a new variant of blaOXA-211, called blaOXA-498. In particular, blaPER-2 and blaTEM-1 are present within the typical contexts previously described in the Enterobacteriaceae family. These results suggest that A. johnsonii actively acquires exogenous DNA from other bacterial species and concomitantly becomes a reservoir of resistance genes.
Asymptotics Problems for Laser-Matter Modeling; Quantum and Classical Models

This paper is devoted to the asymptotic analysis of both quantum and classical models which describe the evolution of electrons subject to the potential of an atomic crystal perturbed by the highly oscillating potential of external electro-magnetic waves. We derive either Einstein rate equations or diusion equations with respect to the energy variable, depending on whether the initial model is quantum or classical. We point out the analogies and dierences in the treatment of the two models, considering successively the cases of (quasi-)periodic perturbations or random ones. We point out the dierent role of the relaxation eects according to the nature of the perturbation.
Experimenting with Comics Making as Inquiry

Abstract:I illustrate my comics making approach for the extension of multimodal analysis (MMA) in ethnographic education research. Comics making impacted how I designed my study, generated multimodal data, conducted analysis, and share work to broader academic audiences. I present two examples drawn from my ethnography of an image-based lab's graduate course to show how comics making (1) foregrounded corporeal responsiveness over time; (2) unified the visual and textual with body-sensory perception; (3) emphasized movement, affect, and empathy; and (4) enabled the use of multimodal data generated by research participants and myself. I also provide resources for scholars who are interested in making comics for their research.
Fine-Tuning and the Stability of Recurrent Neural Networks

A central criticism of standard theoretical approaches to constructing stable, recurrent model networks is that the synaptic connection weights need to be finely-tuned. This criticism is severe because proposed rules for learning these weights have been shown to have various limitations to their biological plausibility. Hence it is unlikely that such rules are used to continuously fine-tune the network in vivo. We describe a learning rule that is able to tune synaptic weights in a biologically plausible manner. We demonstrate and test this rule in the context of the oculomotor integrator, showing that only known neural signals are needed to tune the weights. We demonstrate that the rule appropriately accounts for a wide variety of experimental results, and is robust under several kinds of perturbation. Furthermore, we show that the rule is able to achieve stability as good as or better than that provided by the linearly optimal weights often used in recurrent models of the integrator. Finally, we discuss how this rule can be generalized to tune a wide variety of recurrent attractor networks, such as those found in head direction and path integration systems, suggesting that it may be used to tune a wide variety of stable neural systems.
Congestion Driven Clock Tree Routing with Via Minimization

Physical routability constraints such as legal location checking and excessive number of vias are usually ignored in most of the clock tree algorithms. These Constraints could make an abstract clock tree difficult to route in practice and cause important manufacturability and reliability challenges. Therefore the final clock tree layout specifications can be seriously deviated from the expected ones. Vias have major impact on circuit reliability and manufacturing yield. The variability in via resistance is becoming an increasing concern in nanotechnologies. In this thesis a practical frame work is proposed to construct the clock tree network under via constraint. We propose an algorithm that minimizes the number of bends that is closely related to the number of vias. The proposed algorithm is able to construct a zero skew clock tree with at most one bend branch merging. By performing simultaneous wire sizing and clock tree construction, the algorithm effectively reduces the number of bends at the expense of a small increase in capacitance. Furthermore, the number of vias is also controlled by considering a pre-specified pattern to route the internal clock tree edges. The impact of the pattern routing is taken into account in the early clock distribution design phase. We introduce a probabilistic routing demand estimation method to integrate the expected routing demand of the clock net with other clock tree optimization metrics. A new demand driven cost function is exploited in network topology generation as well as branch point embedding stages of a zero skew clock tree algorithm to reduce the number of vias. Our experiments show considerable improvements in the total number of vias. 28% reduction in the number of vias is obtained while the total clock tree wire length is reduced by an average of 8%. The post-routing induced clock skew is also controlled efficiently.
The Lotka‐Volterra Predator‐Prey Model with Foraging–Predation Risk Trade‐Offs

This article studies the effects of adaptive changes in predator and/or prey activities on the Lotka‐Volterra predator‐prey population dynamics. The model assumes the classical foraging–predation risk trade‐offs: increased activity increases population growth rate, but it also increases mortality rate. The model considers three scenarios: prey only are adaptive, predators only are adaptive, and both species are adaptive. Under all these scenarios, the neutral stability of the classical Lotka‐Volterra model is partially lost because the amplitude of maximum oscillation in species numbers is bounded, and the bound is independent of the initial population numbers. Moreover, if both prey and predators behave adaptively, the neutral stability can be completely lost, and a globally stable equilibrium would appear. This is because prey and/or predator switching leads to a piecewise constant prey (predator) isocline with a vertical (horizontal) part that limits the amplitude of oscillations in prey and predator numbers, exactly as suggested by Rosenzweig and MacArthur in their seminal work on graphical stability analysis of predator‐prey systems. Prey and predator activities in a long‐term run are calculated explicitly. This article shows that predictions based on short‐term behavioral experiments may not correspond to long‐term predictions when population dynamics are considered.
Adaptive Multipath Routing for Congestion Control in InfiniBand Networks

InfiniBand networks are aimed to fulfill increasing communication demand of parallel applications in High Performance Clusters. However, the dynamic behavior of communication load may cause bottlenecked link(s) which lead to message congestion. Congestion spreading increases latency and reduces network throughput causing important performance degradation. In this paper, we propose a congestion control technique for InfiniBand networks. Our proposal is based on an adaptive routing algorithm that performs a communication load balancing over several alternative paths. Congestion is controlled by avoiding sending communication-load excess through network congested area, while maintaining injection rate. Proposed mechanism uses the management model defined in InfiniBand specs, thus full compatibility is provided meanwhile congestion control is addressed.
Tracking and Surveillance in Wide-Area Spatial Environments Using the Abstract Hidden Markov Model

In this paper, we consider the problem of tracking an object and predicting the object's future trajectory in a wide-area environment, with complex spatial layout and the use of multiple sensors/cameras. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. We employ the Abstract Hidden Markov Models (AHMM), an extension of teh well-known Hidden Markov Model (HMM) and a special type of Dynamic Probabilistic Network (DPN), as our underlying representation framework. The AHMM allows us to explicitly encode the hierarchy of connected spatial locations, making it scalable to the size of the environment being modeled. We describe an application for tracking human movement in an office-like spatial layout where the AHMM is used to track and predict the evolution of object trajectories at different levels of detail.
Quality and Social Responsibility: A view to continuous improvement and excellence in Portuguese Higher Education Institutions, the perspective of the students integrated in mobility programmes

The Total Quality Management (TQM) is increasingly a need for organizations. The growing social concerns have led organizations to think evolutionarily in quality, especially those wishing to make an approach towards excellence. TQM can be used as a determinant of the development of a corporate culture ethically sensitive. Models such as the European Quality Award and European Foundation for Quality Management incorporate an element of social responsibility and management practices compatible with the defender of the ideals of Corporate Social Responsibility (Ghobadian and Woo, 1996 and Martin-Castilla, 2002, cited by Ghobadian et al., 2007). Institutions of higher education are among the group of institutions that demand excellence. The quality and social responsibility are factors that begin to be part of their strategies. Students from Higher Education Institutions (HEI) integrated in mobility programs, increasingly important stakeholders for these institutions, will have their own perspective on these matters which is important on the evaluation of HEI.
Joint Phase Tracking and Channel Decoding for OFDM Physical-Layer Network Coding

This paper investigates the problem of joint phase tracking and channel decoding in OFDM based Physical-layer Network Coding (PNC) systems. OFDM signaling can obviate the need for tight time synchronization among multiple simultaneous transmissions in the uplink of PNC systems. However, OFDM PNC systems are susceptible to phase drifts caused by residual carrier frequency offsets (CFOs). In the traditional OFDM system in which a receiver receives from only one transmitter, pilot tones are employed to aid phase tracking. In OFDM PNC systems, multiple transmitters transmit to a receiver, and these pilot tones must be shared among the multiple transmitters. This reduces the number of pilots that can be used by each transmitting node. Phase tracking in OFDM PNC is more challenging as a result. To overcome the degradation due to the reduced number of per-node pilots, this work supplements the pilots with the channel information contained in the data. In particular, we propose to solve the problems of phase tracking and channel decoding jointly. Our solution consists of the use of the expectation-maximization (EM) algorithm for phase tracking and the use of the belief propagation (BP) algorithm for channel decoding. The two problems are solved jointly through iterative processing between the EM and BP algorithms. Simulations and real experiments based on software-defined radio show that the proposed method can improve phase tracking as well as channel decoding performance.
Towards a policy-driven framework for adaptive Web services composition

The variation of contexts in which a Web service could be used and the resulting variation in functional and quality of service (QoS) requirements motivates further research to extend Web services platforms to cater for differentiated service offerings and dynamic adaptability. Adaptability is an important requirement in the context of Web services to cater for the need of diverse set of client applications requesting customized view of consumed Web services to fit their own contexts and preferences. This paper presents an ongoing project to devise a novel service composition framework, named AdaptiveBPEL that leverages aspect-oriented software development (AOSD) techniques to open up the service composition for dynamic change in order to provide a greater degree of configurability and dynamic adaptability of Web services. This framework can: 1) easily adapt to changes in business rules, and collaboration policies governing service interactions; 2) provide different levels of functional and QoS offerings. The adaptation process is policy-driven to declaratively define the adaptive service behavior through dynamic injection of functional and non-functional extensions into a core service composition to allow on-demand and per-instance service adaptability.