Antimicrobial effects of chlorhexidine, matrica drop mouthwash (chamomile extract), and normal saline on hospitalized patients with endotracheal tubes

Background: The functions and use of mouthwashes are variable depending on their type. Oral care in patients with endotracheal tubes is important to prevent side effects such as pneumonia. The aim of this study was to determine the antimicrobial effects of chlorhexidine, drop of Matrica mouthwash (chamomile extract), and normal saline on hospitalized patients with endotracheal tube in an intensive care unit (ICU). Materials and Methods: In this clinical trial, 39 patients admitted to the ICU were selected by convenience sampling, were matched based on age and sex, and randomly assigned to three groups (chlorhexidine, Matrica, saline). Mouth washing was performed every 8 to 48 hours. The samples were taken at time zero (before the intervention) and 48 hours after the intervention for bacterial culture. Antibacterial activity of each mouthwash on microorganisms was measured based on the growth of Staphylococcus aureus, Pneumococcal, Enterococcus, Pseudomonas, and Escherichia coli. The obtained data were then analyzed using Chi-square and Fisher's exact tests with the Statistical Package for the Social Sciences Package version 18. Results: Chlorhexidine mouthwash was more effective in preventing colonization of bacteria in the mouth (point probability = 0.06) in comparison with chamomile and saline mouthwashes. Nevertheless, none of the tested mouthwashes were able to remove pathogens, including Staphylococcus aureus, Pseudomonas, Klebsiella, and Acinetobacter. Conclusions: 0.2% chlorhexidine mouthwash has a significant effect on the bacterial colonization rate in comparison with Matrica and normal saline mouthwashes in ICU hospitalized patients with endotracheal tube

Pulse and quench induced dynamical phase transition in a chiral multiferroic spin chain

Quantum dynamics of magnetic order in a chiral multiferroic chain is studied. We consider two different scenarios: Ultrashort terahertz (THz) excitations or a sudden electric field quench. Performing analytical and numerical exact diagonalization calculations we trace the pulse induced spin dynamics and extract quantities that are relevant to quantum information processing. In particular, we analyze the dynamics of the system chirality, the von Neumann entropy, the pairwise and the many body entanglement. If the characteristic frequencies of the generated states are non-commensurate then a partial loss of pair concurrence occurs. Increasing the system size this effect becomes even more pronounced. Many particle entanglement and chirality are robust and persist in the incommensurate phase. To analyze the dynamical quantum transitions for the quenched and pulsed dynamics we combined the Weierstrass factorization technique for entire functions and Lanczos exact diagonalization method. For a small system we obtained analytical results including the rate function of Loschmidt echo. Exact numerical calculations for a system up to 40 spins confirm phase transition. Quench- induced dynamical transitions have been extensively studied recently. Here we show that related dynamical transitions can be achieved and controlled by appropriate electric field pulses.Comment: 13 pages, 10 figures, submitted in PR

FireNN: Neural Networks Reliability Evaluation on Hybrid Platforms

The growth of neural networks complexity has led to adopt of hardware-accelerators to cope with the computational power required by the new architectures. The possibility to adapt the network for different platforms enhanced the interests of safety-critical applications. The reliability evaluation of neural networks are still premature and requires platforms to measure the safety standards required by mission-critical applications. For this reason, the interest in studying the reliability of neural networks is growing. We propose a new approach for evaluating the resiliency of neural networks by using hybrid platforms. The approach relies on the reconfigurable hardware for emulating the target hardware platform and performing the fault injection process. The main advantage of the proposed approach is to involve the on-hardware execution of the neural network in the reliability analysis without any intrusiveness into the network algorithm and addressing specific fault models. The implementation of FireNN, the platform based on the proposed approach, is described in the paper. Experimental analyses are performed using fault injection on AlexNet. The analyses are carried out using the FireNN platform and the results are compared with the outcome of traditional software-level evaluations. Results are discussed considering the insight into the hardware level achieved using FireNN

On the Analysis of Radiation-induced Failures in the AXI Interconnect Module

Due to the increasing demand for high performance in embedded systems, devices such as SRAM-based programmable devices are becoming an appealing solution to reach high performance with limited costs. However, SRAM-based programmable devices are subjected to various sources of radiation-induced faults that affect their reliability, such as ionizing radiation and particles, even at sea-level. In this paper, we evaluate the reliability of the interconnection module, implemented on the programmable hardware, against radiation-induced faults in the configuration layer. To do so, we performed a fault injection campaign in order to emulate the radiation-induced effects impacting the configuration memory of AP-SoC Zynq 7000, specifically targeting the configuration memory section programming the interconnection module implemented on the programmable logic. This interconnection module is a crucial element for a wide range of applications and mitigation techniques such as hardware-accelerated designs, Dynamic Partial Reconfiguration, or Triple Modular Redundancy; especially if they are adopted to achieve high performance, high bandwidth and high reliability. The fault injection results have been analyzed and classified accordingly with the effect observed on the processor-system side in terms of availability and fault model affecting data computed by cores implemented on the programmable logic side

On the evaluation of SEU effects on AXI interconnect within AP-SoCs

G-Programmable System-on-Chips offering the union of a processor system with a programmable hardware gave rise to applications that choose hardware acceleration to offload and parallelize computationally demanding tasks. Due to flexibility and performance they provide at low cost, these devices are also appealing for several applications in avionics, aerospace and automotive sectors, where reliability is the main concern. In particular, the interconnection architecture, and especially the AXI Interconnection for FPGA-accelerated applications, plays a critical role in these systems. This paper presents a reliability analysis of the AXI Interconnect IP Core implemented on Zynq-7000 AP-SoC against SEUs in the configuration memory of the programmable logic. The analysis has been conducted performing a fault injection campaign on the specific section of the configuration memory implementing the IP Core under test, which has been implemented within a benchmark design. The results are analyzed and classified, highlighting the criticality of the AXI Interconnect IP Core as a point of failure, especially for SEU-hardened hardware accelerator relying on mitigation techniques based on fine-grained and coarse-grained replication

بررسی میزان انواع خشونت خانگی و عوامل مرتبط با آن در مادران باردار منطقه کلاله

یافته‌ها: 312 نفر معادل 78 درصد از مادران باردار به اشکال مختلف مورد خشونت قرار گرفته بودند. شایع‌ترین نوع خشونت علیه مادران باردار، عاطفی بود و 78 نفر از زنان از خشونت جسمی و 53 نفر از خشونت جنسی شکایت داشتند. همچنین با افزایش تحصیلات خشونت علیه مادران کاهش پیدا کرد. بین خشونت خانگی و مصرف سیگار و عدم اشتغال همسر رابطه معناداری مشاهده شد Introduction: Violence against women is a universal phenomenon which has negative impact on the mental health of the family and society, and the consequences such as increased health care costs, reduced productivity and labor force of women are another results of this health and social cultural problem. So, this study was performed with aim to determine types of domestic violence and its related factors in pregnant women. Methods: This descriptive-analytic study was performed on 368 pregnant mothers in area of Kalaleh in 2014. Data were collected by simple sampling and using a questionnaire. Data was analyzed with SPSS software (version 19) and descriptive statistics and Fisher's exact test, Chi-square, independent t-test, and Pearson correlation test. Results: 312 pregnant women (84.78%) had been exposed to different types of violence. The most common type of violence against pregnant women was emotional with 181 cases (49.18%) and 78 (21.20%) complained of physical violence and 53 (14.40%) of sexual violence. Increased education reduced violence against women. There was a significant relationship between domestic violence, smoking and lack of husband's employment (P <0.05). Conclusion: According to high rate of domestic violence, it is recommended to screen violence in the all health and therapy centers. Also, life skills training and counseling culture among couples is important

Analysis and Mitigation of Soft-Errors on High Performance Embedded GPUs

Multiprocessor system-on-chip such as embedded GPUs are becoming very popular in safety-critical applications, such as autonomous and semi-autonomous vehicles. However, these devices can suffer from the effects of soft-errors, such as those produced by radiation effects. These effects are able to generate unpredictable misbehaviors. Fault tolerance oriented to multi-threaded software introduces severe performance degradations due to the redundancy, voting and correction threads operations. In this paper, we propose a new fault injection environment for NVIDIA GPGPU devices and a fault tolerance approach based on error detection and correction threads executed during data transfer operations on embedded GPUs. The fault injection environment is capable of automatically injecting faults into the instructions at SASS level by instrumenting the CUDA binary executable file. The mitigation approach is based on concurrent error detection threads running simultaneously with the memory stream device to host data transfer operations. With several benchmark applications, we evaluate the impact of softerrors classifying Silent Data Corruption, Detection, Unrecoverable Error and Hang. Finally, the proposed mitigation approach has been validated by soft-error fault injection campaigns on an NVIDIA Pascal Architecture GPU controlled by Quad-Core A57 ARM processor (JETSON TX2) demonstrating an advantage of more than 37% with respect to state of the art solution