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Use of biological or synthetic mesh might improve outcomes of immediate implant-based breast reconstruction—breast reconstruction with implants or expanders at the time of mastectomy—but there is a lack of high-quality evidence to support the safety or effectiveness of the technique. We aimed to establish the short-term safety of immediate implant-based breast reconstruction performed with and without mesh, to inform the feasibility of undertaking a future randomised clinical trial comparing different breast reconstruction techniques. In this prospective, multicentre cohort study, we consecutively recruited women aged 16 years or older who had any type of immediate implant-based breast reconstruction for malignancy or risk reduction, with any technique, at 81 participating breast and plastic surgical units in the UK. Data about patient demographics and operative, oncological, and complication details were collected before and after surgery. Outcomes of interest were implant loss (defined as unplanned removal of the expander or implant), infection requiring treatment with antibiotics or surgery, unplanned return to theatre, and unplanned re-admission to hospital for complications of reconstructive surgery, up to 3 months after reconstruction and assessed by clinical review or patient self-report. Follow-up is complete. The study is registered with the ISRCTN Registry, number ISRCTN37664281. Between Feb 1, 2014, and June 30, 2016, 2108 patients had 2655 mastectomies with immediate implant-based breast reconstruction at 81 units across the UK. 1650 (78%) patients had planned single-stage reconstructions (including 12 patients who had a different technique per breast). 1376 (65%) patients had reconstruction with biological (1133 [54%]) or synthetic (243 [12%]) mesh, 181 (9%) had non-mesh submuscular or subfascial implants, 440 (21%) had dermal sling implants, 42 (2%) had pre-pectoral implants, and 79 (4%) had other or a combination of implants. 3-month outcome data were available for 2081 (99%) patients. Of these patients, 182 (9%, 95% CI 8–10) experienced implant loss, 372 (18%, 16–20) required re-admission to hospital, and 370 (18%, 16–20) required return to theatre for complications within 3 months of their initial surgery. 522 (25%, 95% CI 23–27) patients required treatment for an infection. The rates of all of these complications are higher than those in the National Quality Standards (<5% for re-operation, re-admission, and implant loss, and <10% for infection). Complications after immediate implant-based breast reconstruction are higher than recommended by national standards. A randomised clinical trial is needed to establish the optimal approach to immediate implant-based breast reconstruction. National Institute for Health Research, Association of Breast Surgery, and British Association of Plastic, Reconstructive and Aesthetic Surgeons.

Hierarchical link sharing addresses the demand for fine-grain traffic control at multiple levels of aggregation.Currently deployed scheduling algorithms for hierarchical link sharing are effective with upholding rate guarantees to classes, but perform poorly when distributing excess capacity to classes in need of additional capacity.This leads to counterintuitive allocations and leaves the allocation of capacity vulnerable to manipulation, whereby classes in one branch of the hierarchy can obtain bandwidth at the cost of classes in another branch. We present HLS, a strategy-proof scheduler for hierarchical link sharing, which ensures rate guarantees and provides isolation between classes in the hierarchy.HLS is designed to satisfy a hierarchical version of max-min fairness.We evaluate our implementation of HLS in the Linux kernel with respect to rate allocation and overhead, and compare the results obtained for the CBQ and HTB Linux qdiscs.

This study explores institutional complexity in Thai State-Owned Enterprises (SOEs). In doing so, a qualitative approach has been employed in this study in order to identify institutional logics in the field of Thai SOEs and to understand organisational and individual perceptions of institutional complexity in the implementation of performance measurement systems (PMS) and how they respond to the complexity. To achieve this goal, two Thai SOEs were studied, both of which faced challenges in the implementation of Economic Value Management (EVM) and Balance Scorecard (BSC) as well as difficulties in linking their individual BSC and incentive systems. The qualitative data were collected from semi-structured interviews and document reviews. The empirical aspects of this study reveal that the institutional logics in the field of Thai SOEs are the logic of bureaucracy, commercial operations, social activities, seniority and unity. Regarding the multiple institutional logics embedded, SOEs experienced the institutional complexity in the implementation of PMS. The results suggest that the organisations have decoupled the EVM and loosely coupled the BSC from organisational practices to cope with institutional complexity and conflict institutional demands. Also, the evidence shows that the institutional logics influence SOEs’ actions towards resisting changes incentive systems and the relationship between individual BSC and incentives.

Hierarchical link sharing addresses the demand for fine-grain traffic control at multiple levels of aggregation. At present, packet schedulers that can support hierarchical link sharing are not suitable for an implementation at line rates, and deployed schedulers perform poorly when distributing excess capacity to classes that need additional bandwidth. We present HLS, a packet scheduler that ensures a hierarchical max-min fair allocation of the link bandwidth. HLS supports minimum rate guarantees and isolation between classes. Since it is realized as a non-hierarchical round robin scheduler, it is suitable to operate at high rates. We implement HLS in the Linux kernel and evaluate it with respect to achieved rate allocations and overhead. We compare the results with those obtained for CBQ and HTB, the existing scheduling algorithms in Linux for hierarchical link sharing. We show that the overhead of HLS is comparable to that of other classful packet schedulers.

Models for the dynamics of congestion control generally involve systems of coupled differential equations. Universally, these models assume that traffic sources saturate the maximum transmissions allowed by the congestion control method. This is not suitable for studying congestion control of intermittent but bursty traffic sources. In this paper, we present a characterization of congestion control for arbitrary time-varying traffic that applies to rate-based as well as window-based congestion control. We leverage the capability of network calculus to precisely describe the input-output relationship at network elements for arbitrary source traffic. We show that our characterization can closely track the dynamics of even complex congestion control algorithms.

Traffic from distributed training of machine learning (ML) models makes up a large and growing fraction of the traffic mix in enterprise data centers. While work on distributed ML abounds, the network traffic generated by distributed ML has received little attention. Using measurements on a testbed network, we investigate the traffic characteristics generated by the training of the ResNet-50 neural network with an emphasis on studying its short-term burstiness. For the latter we propose metrics that quantify traffic burstiness at different time scales. Our analysis reveals that distributed ML traffic exhibits a very high degree of burstiness on short time scales, exceeding a 60:1 peak-to-mean ratio on time intervals as long as 5~ms. We observe that training software orchestrates transmissions in such a way that burst transmissions from different sources within the same application do not result in congestion and packet losses. An extrapolation of the measurement data to multiple applications underscores the challenges of distributed ML traffic for congestion and flow control algorithms.