Towards More Data-Aware Application Integration (extended version)

Although most business application data is stored in relational databases, programming languages and wire formats in integration middleware systems are not table-centric. Due to costly format conversions, data-shipments and faster computation, the trend is to "push-down" the integration operations closer to the storage representation. We address the alternative case of defining declarative, table-centric integration semantics within standard integration systems. For that, we replace the current operator implementations for the well-known Enterprise Integration Patterns by equivalent "in-memory" table processing, and show a practical realization in a conventional integration system for a non-reliable, "data-intensive" messaging example. The results of the runtime analysis show that table-centric processing is promising already in standard, "single-record" message routing and transformations, and can potentially excel the message throughput for "multi-record" table messages.Comment: 18 Pages, extended version of the contribution to British International Conference on Databases (BICOD), 2015, Edinburgh, Scotlan

Responsible Composition and Optimization of Integration Processes under Correctness Preserving Guarantees

Enterprise Application Integration deals with the problem of connecting heterogeneous applications, and is the centerpiece of current on-premise, cloud and device integration scenarios. For integration scenarios, structurally correct composition of patterns into processes and improvements of integration processes are crucial. In order to achieve this, we formalize compositions of integration patterns based on their characteristics, and describe optimization strategies that help to reduce the model complexity, and improve the process execution efficiency using design time techniques. Using the formalism of timed DB-nets - a refinement of Petri nets - we model integration logic features such as control- and data flow, transactional data storage, compensation and exception handling, and time aspects that are present in reoccurring solutions as separate integration patterns. We then propose a realization of optimization strategies using graph rewriting, and prove that the optimizations we consider preserve both structural and functional correctness. We evaluate the improvements on a real-world catalog of pattern compositions, containing over 900 integration processes, and illustrate the correctness properties in case studies based on two of these processes.Comment: 37 page

Δ\Delta-scaling and heat capacity in relativistic ion collisions

The $\Delta$-scaling method has been applied to the total multiplicity distribution of the relativistic ion collisions of p+p, C+C and Pb+Pb which were simulated by a Monte Carlo package, LUCIAE 3.0. It is found that the $\Delta$-scaling parameter decreases with the increasing of the system size. Moreover, the heat capacities of different mesons and baryons have been extracted from the event-by-event temperature fluctuation in the region of low transverse mass and they show the dropping trend with the increasing of impact parameter.Comment: version 2: major change: 4 pages, 3 figures; Proceeding of International Conference on "Strangeness in Quark Matter" (SQM2004), Cape Town, South Africa, Spet. 2004 (Submitted to J. Phys. G.

Simultaneous bilateral hip replacement reveals superior outcome and fewer complications than two-stage procedures: a prospective study including 1819 patients and 5801 follow-ups from a total joint replacement registry

<p>Abstract</p> <p>Background</p> <p>Total joint replacements represent a considerable part of day-to-day orthopaedic routine and a substantial proportion of patients undergoing unilateral total hip arthroplasty require a contralateral treatment after the first operation. This report compares complications and functional outcome of simultaneous versus early and delayed two-stage bilateral THA over a five-year follow-up period.</p> <p>Methods</p> <p>The study is a post hoc analysis of prospectively collected data in the framework of the European IDES hip registry. The database query resulted in 1819 patients with 5801 follow-ups treated with bilateral THA between 1965 and 2002. According to the timing of the two operations the sample was divided into three groups: I) 247 patients with simultaneous bilateral THA, II) 737 patients with two-stage bilateral THA within six months, III) 835 patients with two-stage bilateral THA between six months and five years.</p> <p>Results</p> <p>Whereas postoperative hip pain and flexion did not differ between the groups, the best walking capacity was observed in group I and the worst in group III. The rate of intraoperative complications in the first group was comparable to that of the second. The frequency of postoperative local and systemic complication in group I was the lowest of the three groups. The highest rate of complications was observed in group III.</p> <p>Conclusions</p> <p>From the point of view of possible intra- and postoperative complications, one-stage bilateral THA is equally safe or safer than two-stage interventions. Additionally, from an outcome perspective the one-stage procedure can be considered to be advantageous.</p

Are Soft Prompts Good Zero-shot Learners for Speech Recognition?

Large self-supervised pre-trained speech models require computationally expensive fine-tuning for downstream tasks. Soft prompt tuning offers a simple parameter-efficient alternative by utilizing minimal soft prompt guidance, enhancing portability while also maintaining competitive performance. However, not many people understand how and why this is so. In this study, we aim to deepen our understanding of this emerging method by investigating the role of soft prompts in automatic speech recognition (ASR). Our findings highlight their role as zero-shot learners in improving ASR performance but also make them vulnerable to malicious modifications. Soft prompts aid generalization but are not obligatory for inference. We also identify two primary roles of soft prompts: content refinement and noise information enhancement, which enhances robustness against background noise. Additionally, we propose an effective modification on noise prompts to show that they are capable of zero-shot learning on adapting to out-of-distribution noise environments