Compact Markov-modulated models for multiclass trace fitting

Markov-modulated Poisson processes (MMPPs) are stochastic models for fitting empirical traces for simulation, workload characterization and queueing analysis purposes. In this paper, we develop the first counting process fitting algorithm for the marked MMPP (M3PP), a generalization of the MMPP for modeling traces with events of multiple types. We initially explain how to fit two-state M3PPs to empirical traces of counts. We then propose a novel form of composition, called interposition, which enables the approximate superposition of several two-state M3PPs without incurring into state space explosion. Compared to exact superposition, where the state space grows exponentially in the number of composed processes, in interposition the state space grows linearly in the number of composed M3PPs. Experimental results indicate that the proposed interposition methodology provides accurate results against artificial and real-world traces, with a significantly smaller state space than superposed processes

Cognitive distance and research output in computing education:a case-study

Contribution: This paper quantifies the phenomenon of more versus better research output in computing research education and elaborates on how the organizational variable known as cognitive distance plays a fundamental role in mediating such more versus better research output relation. Background: To improve the current educational system, investigation and quantification is needed of the 'silos.' Cognitive distance - a measure of the differences in background, culture, and expertise between collaborators - may be a factor influencing the lack of quality and variety in research outputs. Addressing this is a key enabler for fruitful collaboration. Research Question: Does collaboration with similarly expert researchers yield better research? Methodology: A quantitative survey provides baseline data for cognitive distance while publication data allowed creation of a co-authorship network between 123 researchers in a European computing research department. The network was analyzed through quantitative and qualitative research methods. Findings: Increased expertise overlaps across sub-fields of computing is a strong predictor for further collaboration (quantity), but research impact (quality) decreases with larger overlaps. This reveals an educational silo effect in doctoral computing education and, consequently, a flaw in the connected research output. The lack of a single, agreed way to evaluate research impact across sub-fields further hinders cross-departmental collaboration among doctoral students. Conclusion: Three recommendations emerge for policy makers and educational leaders: 1) departments should be cross-functional and focused on societal interests; 2) communities of practice should be created at the level of doctoral education and upward; and 3) departments should hold matchmaking and speed-meeting events regularly within and across institutions.</p

Is depression a real risk factor for acute myocardial infarction mortality? A retrospective cohort study

Background: Depression has been associated with a higher risk of cardiovascular events and a higher mortality in patients with one or more comorbidities. This study investigated whether continuative use of antidepressants (ADs), considered as a proxy of a state of depression, prior to acute myocardial infarction (AMI) is associated with a higher mortality afterwards. The outcome to assess was mortality by AD use. Methods: A retrospective cohort study was conducted in the Veneto Region on hospital discharge records with a primary diagnosis of AMI in 2002-2015. Subsequent deaths were ascertained from mortality records. Drug purchases were used to identify AD users. A descriptive analysis was conducted on patients' demographics and clinical data. Survival after discharge was assessed with a Kaplan-Meier survival analysis and Cox's multiple regression model. Results: Among 3985 hospital discharge records considered, 349 (8.8%) patients were classified as AD users'. The mean AMI-related hospitalization rate was 164.8/100,000 population/year, and declined significantly from 204.9 in 2002 to 130.0 in 2015, but only for AD users (-40.4%). The mean overall follow-up was 4.64.1years. Overall, 523 patients (13.1%) died within 30days of their AMI. The remainder survived a mean 5.3 +/- 4.0years. After adjusting for potential confounders, use of antidepressants was independently associated with mortality (adj OR=1.75, 95% CI: 1.40-2.19). Conclusions: Our findings show that AD users hospitalized for AMI have a worse prognosis in terms of mortality. The use of routinely-available records can prove an efficient way to monitor trends in the state of health of specific subpopulations, enabling the early identification of AMI survivors with a history of antidepressant use

Geocoding health data with Geographic Information Systems: a pilot study in northeast Italy for developing a standardized data-acquiring format

Introduction. Geographic Information Systems (GIS) have become an innovative and somewhat crucial tool for analyzing relationships between public health data and environment. This study, though focusing on a Local Health Unit of northeastern Italy, could be taken as a benchmark for developing a standardized national data-acquiring format, providing a step-by-step instructions on the manipulation of address elements specific for Italian language and traditions. Methods. Geocoding analysis was carried out on a health database comprising 268,517 records of the Local Health Unit of Rovigo in the Veneto region, covering a period of 10 years, starting from 2001 up to 2010. The Map Service provided by the Environmental Research System Institute (ESRI, Redlands, CA), and ArcMap 10.0 by ESRI\uae were, respectively, the reference data and the GIS software, employed in the geocoding process. Results. The first attempt of geocoding produced a poor quality result, having about 40% of the addresses matched. A procedure of manual standardization was performed in order to enhance the quality of the results, consequently a set of guiding principle were expounded which should be pursued for geocoding health data. High-level geocoding detail will provide a more precise geographic representation of health related events. Conclusions. The main achievement of this study was to outline some of the difficulties encountered during the geocoding of health data and to put forward a set of guidelines, which could be useful to facilitate the process and enhance the quality of the results. Public health informatics represents an emerging specialty that highlights on the application of information science and technology to public health practice and research. Therefore, this study could draw the attention of the National Health Service to the underestimated problem of geocoding accuracy in health related data for environmental risk assessment

ATOM: model-driven autoscaling for microservices

Microservices based architectures are increasinglywidespread in the cloud software industry. Still, there is ashortage of auto-scaling methods designed to leverage the uniquefeatures of these architectures, such as the ability to indepen-dently scale a subset of microservices, as well as the ease ofmonitoring their state and reciprocal calls.We propose to address this shortage with ATOM, a model-driven autoscaling controller for microservices. ATOM instanti-ates and solves at run-time a layered queueing network model ofthe application. Computational optimization is used to dynami-cally control the number of replicas for each microservice and itsassociated container CPU share, overall achieving a fine-grainedcontrol of the application capacity at run-time.Experimental results indicate that for heavy workloads ATOMoffers around 30%-37% higher throughput than baseline model-agnostic controllers based on simple static rules. We also find thatmodel-driven reasoning reduces the number of actions needed toscale the system as it reduces the number of bottleneck shiftsthat we observe with model-agnostic controllers

Tri nove vrste i jedan novi rod ultraspecijaliziranih špiljskih leptodirina iz Hrvatske (Coleoptera, Cholevidae)

Croatodirus casalei Giachino & Jalžić, new species from N Velebit, Lubenovac, Slovačka jama pothole, and C. ozimeci Casale, Giachino & Jalžić new species, from Lokve, Lokvarka špilja cave, are described. The morphological features of the new taxa are compared with those of the type species of the genus (C. bozicevici Casale, Giachino & Jalžić, 2000). The genus is confirmed as a homogeneous, well characterized and monophyletic unit, and is attributed to the phyletic lineage of Anthroherpon. Velebitodromus, new genus, smidai new species, is described from N Velebit, Lubenovac, Mali kuk, Slovačka jama pothole. Owing to both external features and structures of male and female genitalia, the genus is attributed to the phyletic lineage of Anthroherpon, and is recognized as related to the genera Anthroherpon Reitter, 1889, and Paranthrophilon Reitter, 1889.U radu su opisane Croatodirus casalei Giachino & Jalžić, nova vrsta sa Sjevernog Velebita (Lubenovac, Mali kuk, Slovačka jama) i C. ozimeci Casale, Giachino & Jalžić, nova vrsta iz Lokava (špilja Lokvarka). Njihova morfološka svojstva uspoređuju se s onima tipske vrste ovog roda (C. bozicevici Casale, Giachino & Jalžić, 2000). Rod se potvrđuje kao homogen, jasno raspoznatljiv i monofiletički, te je pridodan filetičkoj liniji Anthroherpon. Novi rod Velebitodromus s novom vrstom smidai opisan je također sa Sjevernog Velebita (Lubenovac, Slovačka jama). Zbog vanjskih osobina i zbog građe muških i ženskih genitalija, rod je pridodan filetičkoj liniji Anthroherpon, i prepoznaje se kao srodan rodovima Anthroherpon Reitter, 1889 i Paranthrophilon Reitter, 1889

Flora and Fauna in East Asian Art

Flora and Fauna in East Asian Art is the fourth annual exhibition curated by students enrolled in the Art History Methods course. This exhibition highlights the academic achievements of six student curators: Samantha Frisoli ’18, Daniella Snyder ’18, Gabriella Bucci ’19, Melissa Casale ’19, Keira Koch ’19, and Paige Deschapelles ’20. The selection of artworks in this exhibition considers how East Asian artists portrayed similar subjects of flora and fauna in different media including painting, prints, embroidery, jade, and porcelain. This exhibition intends to reveal the hidden meanings behind various representations of flora and fauna in East Asian art by examining the iconography, cultural context, aesthetic and function of each object.https://cupola.gettysburg.edu/artcatalogs/1025/thumbnail.jp

QMLE: a methodology for statistical inference of service demands from queueing data

Estimating the demands placed by services on physical resources is an essential step for the definition of performance models. For example, scalability analysis relies on these parameters to predict queueing delays under increasing loads. In this paper, we investigate maximum likelihood (ML) estimators for demands at load-independent and load-dependent resources in systems with parallelism constraints. We define a likelihood function based on state measurements and derive necessary conditions for its maximization. We then obtain novel estimators that accurately and inexpensively obtain service demands using only aggregate state data. With our approach, and also thanks to approximation methods for computing marginal and joint distributions for the load-dependent case, confidence intervals can be rigorously derived, explicitly taking into account both topology and concurrency levels of the services. Our estimators and their confidence intervals are validated against simulations and real system measurements for two multi-tier applications, showing high accuracy also in the presence of load-dependent resources