A Novel Placement Technique of S2 Screw (from S2 to Promontorium) and Double Screwing from S2

Since pseudoarthrosis or screw loosening is frequently seen in lumbosacral stabilizations ending in S1, S2 screws are used more frequently to support S1 screws. This study aims to describe a new screw placement technique and location from S2. Revision surgery was applied to the patient who had previously undergone surgery with the rigid instrumentation system and encountered pseudoarthrosis during the follow-up period. Instrumentation was performed from S2 to the promontorium. The patient’s chronic low back pain arising due to pseudoarthrosis was reduced and a strong lumbosacral dynamic instrumentation was performed to the patient. Dual screw placement from S2 and/or screw placement in the S2-promontorium direction is a new alternative to provide a powerful instrumentation.

An Automated Approach of Detection of Memory Leaks for Remote Server Controllers

Memory leaks are a major concern to the long running applications like servers which make the working set to grow with the program. This eventually leads to system crashing. This paper discusses a staged approach to detect leaks in firmware of remote server controller. Remote server controller monitors the server remotely with many processes running in the background. Any memory leak in the long running applications pose a threat to the performance of the system. The approach adopted here filters the processes running in the system with leaks based on time threshold in the first stage. These processes with leaks are passed to the next stage where precise memory leak detection is done using the open source dynamic instrumentation tool Valgrind. The system leverages an automated leak detection approach that invokes the leak detection process on encountering any severity in the system and generates a consolidated leak report. The proposed approach has less impact on the performance of the system and is faster compared to many available systems as there is no need to modify or re-compile the program. In addition, the automated approach offers an effective technique for detecting possible leakages in early software development phases.

Firmware code instrumentation technology for internet of things-based services

With the rapid development of electronic and information technology, Internet of Things (IoT) devices have become extensively utilised in various fields. Increasing attention has been paid to the performance and security analysis of IoT-based services. Dynamic instrumentation is a common process in software analysis for acquiring runtime information. However, due to the limited software and hardware resources in IoT devices, most dynamic instrumentation tools do not support IoT-based services. In this paper, we provide an analysis tool, IoTDIT, to solve the current problem of runtime detection in IoT-based services. IoTDIT employs static analysis and ptrace system calls to obtain dynamic firmware information, which can aid in firmware performance analysis and security detection. We perform experiments to verify the performance and effectiveness of the proposed instrumentation tool.

Two Anatomists Are Better than One—Dual-Level Android Malware Detection

The openness of the Android operating system and its immense penetration into the market makes it a hot target for malware writers. This work introduces Androtomist, a novel tool capable of symmetrically applying static and dynamic analysis of applications on the Android platform. Unlike similar hybrid solutions, Androtomist capitalizes on a wealth of features stemming from static analysis along with rigorous dynamic instrumentation to dissect applications and decide if they are benign or not. The focus is on anomaly detection using machine learning, but the system is able to autonomously conduct signature-based detection as well. Furthermore, Androtomist is publicly available as open source software and can be straightforwardly installed as a web application. The application itself is dual mode, that is, fully automated for the novice user and configurable for the expert one. As a proof-of-concept, we meticulously assess the detection accuracy of Androtomist against three different popular malware datasets and a handful of machine learning classifiers. We particularly concentrate on the classification performance achieved when the results of static analysis are combined with dynamic instrumentation vis-à-vis static analysis only. Our study also introduces an ensemble approach by averaging the output of all base classification models per malware instance separately, and provides a deeper insight on the most influencing features regarding the classification process. Depending on the employed dataset, for hybrid analysis, we report notably promising to excellent results in terms of the accuracy, F1, and AUC metrics.

Biomechanical In Vitro Test of a Novel Dynamic Spinal Stabilization System Incorporating Polycarbonate Urethane Material Under Physiological Conditions

Posterior dynamic stabilization systems (PDSS) were developed to provide stabilization to pathologic or hypermobile spinal segments while maintaining the healthy biomechanics of the spine. Numerous novel dynamic devices incorporate the temperature and moisture dependent material polycarbonate urethane (PCU) due to its mechanical properties and biocompatibility. In this study, standardized pure moment in vitro tests were carried out on human lumbar spines to evaluate the performance of a device containing PCU. An environmental chamber with controlled moisture and temperature was included in the setup to meet the requirements of testing under physiological conditions. Three test conditions were compared: (1) native spine, (2) dynamic instrumentation, and (3) dynamic instrumentation with decompression. The ranges of motion, centers of rotation, and relative pedicle screw motions were evaluated. The device displayed significant stiffening in flexion–extension, lateral bending, and axial rotation load directions. A reduction of the native range of motion diminished the stiffening effect along the spinal column and has the potential to reduce the risk of the onset of degeneration of an adjacent segment. In combination with decompression, the implant decreased the native range of motion for flexion–extension and skew bending, but not for lateral bending and axial rotation. Curve fittings using the sigmoid function were performed to parameterize all load-deflection curves in order to enhance accurate numerical model calibrations and comparisons. The device caused a shift of the center of rotation (COR) in the posterior and caudal direction during flexion–extension loading.