Tension of knotted surgical sutures shows tissue specific rapid loss in a rodent model

<p>Abstract</p> <p>Background</p> <p>Every surgical suture compresses the enclosed tissue with a tension that depends from the knotting force and the resistance of the tissue. The aim of this study was to identify the dynamic change of applied suture tension with regard to the tissue specific cutting reaction.</p> <p>Methods</p> <p>In rabbits we placed single polypropylene sutures (3/0) in skin, muscle, liver, stomach and small intestine. Six measurements for each single organ were determined by tension sensors for 60 minutes. We collected tissue specimens to analyse the connective tissue stability by measuring the collagen/protein content.</p> <p>Results</p> <p>We identified three phases in the process of suture loosening. The initial rapid loss of the first phase lasts only one minute. It can be regarded as cutting through damage of the tissue. The percentage of lost tension is closely related to the collagen content of the tissue (r = -0.424; p = 0.016). The second phase is characterized by a slower decrease of suture tension, reflecting a tissue specific plastic deformation. Phase 3 is characterized by a plateau representing the remaining structural stability of the tissue. The ratio of remaining tension to initial tension of phase 1 is closely related to the collagen content of the tissue (r = 0.392; p = 0.026).</p> <p>Conclusions</p> <p>Knotted non-elastic monofilament sutures rapidly loose tension. The initial phase of high tension may be narrowed by reduction of the surgeons' initial force of the sutures' elasticity to those of the tissue. Further studies have to confirm, whether reduced tissue compression and less local damage permits improved wound healing.</p

Fast and Energy-Efficient State Checkpointing for Intermittent Computing

Intermittently powered embedded devices ensure forward progress of programs through state checkpointing in non-volatile memory. Checkpointing is, however, expensive in energy and adds to the execution times. To minimize this overhead, we present DICE, a system that renders differential checkpointing profitable on these devices. DICE is unique because it is a software-only technique and efficient because it only operates in volatile main memory to evaluate the differential. DICE may be integrated with reactive (Hibernus) or proactive (MementOS, HarvOS) checkpointing systems, and arbitrary code can be enabled with DICE using automatic code-instrumentation requiring no additional programmer effort. By reducing the cost of checkpoints, DICE cuts the peak energy demand of these devices, allowing operation with energy buffers that are one-eighth of the size originally required, thus leading to benefits such as smaller device footprints and faster recharging to operational voltage level. The impact on final performance is striking: with DICE, Hibernus requires one order of magnitude fewer checkpoints and one order of magnitude shorter time to complete a workload in real-world settings

Demystifying Energy Consumption Dynamics in Transiently powered Computers

Transiently powered computers (TPCs) form the foundation of the battery-less Internet of Things, using energy harvesting and small capacitors to power their operation. This kind of power supply is characterized by extreme variations in supply voltage, as capacitors charge when harvesting energy and discharge when computing. We experimentally find that these variations cause marked fluctuations in clock speed and power consumption. Such a deceptively minor observation is overlooked in existing literature. Systems are thus designed and parameterized in overly conservative ways, missing on a number of optimizations. We rather demonstrate that it is possible to accurately model and concretely capitalize on these fluctuations. We derive an energy model as a function of supply voltage and prove its use in two settings. First, we develop EPIC, a compile-time energy analysis tool. We use it to substitute for the constant power assumption in existing analysis techniques, giving programmers accurate information on worst-case energy consumption of programs. When using EPIC with existing TPC system support, run-time energy efficiency drastically improves, eventually leading up to a 350% speedup in the time to complete a fixed workload. Further, when using EPIC with existing debugging tools, it avoids unnecessary program changes that hurt energy efficiency. Next, we extend the MSPsim emulator and explore its use in parameterizing a different TPC system support. The improvements in energy efficiency yield up to more than 1000% time speedup to complete a fixed workload