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With the explosive increase in traffic volume in fifth-generation (5G) mobile wireless networks, an ultra-dense network (UDN) architecture, composed of highly concentrated millimeter-wave base stations within the fourth-generation (4G) system, has been developed. User equipment (UE) may encounter more frequent handover opportunities when moving in a UDN. Conventional handover schemes are too simple to adapt to the diverse handover scenarios encountered in 5G UDNs because they consider only UE signal strength. Unnecessary handovers aggravate the ping-pong effect and degrade the quality of service of cellular networks. Fuzzy logic (FL) is considered the best technique to unravel the handover problem in a high-density scenario of small cells for 4G/5G networks. In this paper, we propose an FL-based handover scheme to dynamically adjust the values of two handover parameters, namely handover margin (HOM) and time to trigger (TTT), with respect to each UE. The proposed scheme, abbreviated as FLDHDT, has dynamic adjustment of TTT in addition to HOM by using the signal to interference plus noise ratio and horizontal moving speed of the UE as inputs to the FL controller. To demonstrate the effectiveness and superiority of FLDHDT, we perform simulations using the well-known ns-3 simulator. The performance measures include the number of handovers, overall system throughput, and ping-pong ratio. The simulation results demonstrate that FLDHDT improves the handover performance of 5G UDNs in terms of the number of handovers, ping-pong ratio, and overall system throughput compared to a conventional handover scheme, namely Event A3, and an FL-based handover scheme with dynamic adjustment of only HOM.

Software defined networking (SDN) is an emerging networking architecture that separates the control plane from the data plane and moves network management to a central point, called the controller. The controller is responsible for preparing the flow tables of each switch in the data plane. Although dynamic routing can perform rerouting in case of congestion by periodically monitoring the status of each data flow, problems concerning a suitable monitoring period duration and lack of learning ability from past experiences to avoid similar but ineffective route decisions remain unsolved. This paper presents an artificial intelligence enabled routing (AIER) mechanism with congestion avoidance in SDN, which can not only alleviate the impact of monitoring periods with dynamic routing, but also provide learning ability and superior route decisions by introducing artificial intelligence (AI) technology. We evaluate the performance of the proposed AIER mechanism on the Mininet simulator by installing three additional modules, namely, topology discovery, monitoring period, and an artificial neural network, in the control plane. The effectiveness and superiority of our proposed AIER mechanism are demonstrated by performance metrics, including average throughput, packet loss ratio, and packet delay versus data rate for different monitoring periods in the system.

The main objective was to devise an endotracheal intubation formula based on pediatric patients' strongly correlated growth parameters. The secondary objective was to compare the accuracy of the new formula to the age-based formula from Advanced Pediatric Life Support Course (APLS formula) and the middle finger length-based formula (MFL-based formula). A prospective, observational study. Operation. 111 subjects age 4–12 years old undergoing elective surgeries with general orotracheal anesthesia. Growth parameters, including age, gender, height, weight, BMI, middle finger length, nasal-tragus length, and sternum length, were measured before surgeries. Tracheal length and the optimal endotracheal intubation depth (D) were measured and calculated by Disposcope. Regression analysis were used to establish a new formula for predicting the intubation depth. A self-controlled paired design was used to compare the accuracy of the intubation depth between the new formula, APLS formula, and MFL-based formula. Height (R = 0.897, P < 0.001) was strongly correlated to tracheal length and the endotracheal intubation depth in pediatric patients. New formulae basing on height were established, including new formula 1: D (cm) = 4 + 0.1 × Height (cm) and new formula 2: D (cm) = 3 + 0.1 × Height (cm). Via Bland-Altman analysis, the mean differences for new formula 1, new formula 2, APLS formula and MFL-based formula were − 0.354 cm (95% LOA, −1.289 to 1.998 cm), 1.354 cm (95% LOA, −0.289 to 2.998 cm), 1.154 cm (95% LOA, −1.002 to 3.311 cm), −0.619 cm (95% LOA, −2.960 to 1.723 cm), respectively. The rate of optimal intubation for new formula 1 (84.69%) was higher than for new formula 2 (55.86%), APLS formula (61.26%), and MFL-based formula. (69.37%). The prediction accuracy for intubation depth of the new formula 1 was higher than the other formulae. The new formula based on height: D (cm) = 4 + 0.1 × Height (cm) was preferable to APLS formula and MFL-based formula with a high incidence of appropriate endotracheal tube position. •Endotracheal intubation depth was individualized in pediatric patients.•Body height was strongly correlated with endotracheal intubation depth.•The adoption of the height-based formula decreased the incidence of endotracheal tube malposition.•The new formula based on height provided a rapid and convenient method to predict intubation depth.

PurposeThe global population of the aged is escalating. The need of transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) in patients older than 80 years is on the rise. The aim of this study was to retrospectively evaluate the safety and the prognosis of TACE in octogenarians with HCC.Materials and MethodsFrom January 2007 to January 2018, 86 octogenarians with HCC initially treated with TACE, who were treatment naïve or had a recurrence after surgery and/or radiofrequency ablation, were enrolled in this study. The adverse events were evaluated. The overall survival (OS) after TACE and causes of death were investigated. The prognostic factors for OS were analyzed using Cox proportional hazard models.ResultsGrade 4 adverse events (according to the Common Terminology Criteria for Adverse Event version 4.0) of AST, ALT and tumor rupture were found in 8, 4 and 1 patients, respectively. There were no treatment-related deaths. The 1-, 3- and 5-year overall survival rates were 84.1%, 61.1% and 27.6%, respectively. The overall median survival time was 38.3 months (HR 2.854, 95% CI 32.7–43.8). 56.9% causes of death were HCC or liver dysfunction. Multivariate analysis revealed that performance status (ECOG: 0) was an independent prognostic significant factor (95% CI 1.103–4.573; P = .026).ConclusionsTACE is safe and could improve survival of octogenarians with HCC. Performance status is an important prognosis factor predicting the OS.

PurposeTo evaluate the effectiveness and safety of prophylactic intraoperative uterine artery embolization (UAE) performed immediately after fetal delivery during planned cesarean section or cesarean hysterectomy in patients with placenta accreta spectrum disorder or placenta previa.MethodsA systematic search was conducted on Ovid MEDLINE and Embase, PubMed, Web of Science, and Cochrane databases. Studies were selected using the Population/Intervention/Comparison/Outcomes (PICO) strategy. The intraoperative blood loss and the rate of emergent peripartum hysterectomy (EPH) were the primary outcomes, whereas the length of hospital stay and volume of blood transfused were the secondary outcomes. A random-effects model was employed to pool each effect size. The cumulative values of the primary outcomes were calculated using the generic inverse variance method.ResultsEleven retrospective cohort studies and five case series were included, recruiting 421 women who underwent prophylactic intraoperative UAE (UAE group) and 374 women who did not (control group). Compared with the control group, the UAE group had significantly reduced intraoperative blood loss (p = 0.020) during cesarean section or cesarean hysterectomy. Furthermore, the EPH rate was also significantly decreased (p = 0.020; cumulative rate: 19.65%), but not the length of hospital stay (p = 0.850) and volume of pRBC transfused (p = 0.140), after cesarean section in the UAE group. The incidence of major complications was low (3.33%), despite two patients with uterine necrosis.ConclusionThe currently available data provides encouraging evidence that prophylactic intraoperative UAE may contribute to hemorrhage control and fertility preservation in women with abnormal placentation.RegistrationPROSPERO registration code: CRD42021230581. https://clinicaltrials.gov/ct2/show/CRD42021230581Level of EvidenceLevel 2a, systematic review of retrospective cohort studies.

Network function virtualization (NFV) is an emerging technology that is gaining popularity for network function migration. NFV converts a network function from a dedicated hardware device into a virtual network function (VNF), thereby improving the agility of network services and reducing management costs. A complex network service can be expressed as a service function chain (SFC) request, which consists of an ordered sequence of VNFs. Given the inherent heterogeneity and dynamic nature of network services, effective SFC deployment encounters significant unpredictable challenges. Machine learning-based methods offer the flexibility to predict and select the optimal next action based on existing data models. In this paper, we propose a deep reinforcement learning-based approach for bandwidth-aware service function chaining (DRL-BSFC). Aiming to simultaneously improve the acceptance ratio of SFC requests and maximize the total revenue for Internet service providers, DRL-BSFC integrates a graph convolutional network (GCN) for feature extraction of the underlying physical network, a sequence-to-sequence (Seq2Seq) model for capturing the order information of an SFC request, and a modified A3C (Asynchronous Advantage Actor–Critic) algorithm of deep reinforcement learning. To ensure efficient resource utilization and a higher acceptance ratio of SFC requests, the bandwidth cost for deploying an SFC is explicitly incorporated into the A3C’s reward function. The effectiveness and superiority of DRL-BSFC compared to the existing DRL-SFCP scheme are demonstrated via simulations. The performance measures include the acceptance ratio of SFC requests, the average bandwidth cost, the average remaining link bandwidth, and the average revenue-to-cost ratio under different SFC request arrival rates.

Software-defined networking (SDN) is an emerging networking technology with a central point, called the controller, on the control plane. This controller communicates with the application and data planes. In fifth-generation (5G) mobile wireless networks and beyond, specific levels of service quality are defined for different traffic types. Ultra-reliable low-latency communication (URLLC) is one of the key services in 5G. This paper presents a fuzzy logic (FL)-based dynamic routing (FLDR) mechanism with congestion avoidance for URLLC on SDN-based 5G networks. By periodically monitoring the network status and making forwarding decisions on the basis of fuzzy inference rules, the FLDR mechanism not only can reroute in real time, but also can cope with network status uncertainty owing to FL’s fault tolerance capabilities. Three input parameters, normalized throughput, packet delay, and link utilization, were employed as crisp inputs to the FL control system because they had a more accurate correlation with the network performance measures we studied. The crisp output of the FL control system, i.e., path weight, and a predefined threshold of packet loss ratio on a path were applied to make routing decisions. We evaluated the performance of the proposed FLDR mechanism on the Mininet simulator by installing three additional modules, topology discovery, monitoring, and rerouting with FL, on the traditional control plane of SDN. The superiority of the proposed FLDR over the other existing FL-based routing schemes was demonstrated using three performance measures, system throughput, packet loss rate, and packet delay versus traffic load in the system.

In the 802.11 protocol, the fundamental medium access mechanism is called Distributed Coordination Function (DCF). In DCF, before making any transmission attempt, the nodes count down a timer with a value randomly selected from the Contention Window (CW) size. If the transmitted packet is involved in a collision, the node increases the CW size in an attempt to reduce the collision rate. Conversely, if the packet is transmitted successfully, the node reduces the CW size in order to increase the frequency of the transmission attempts. The growth or reduction in the CW size has a critical effect on the network performance. Several backoff algorithms have been proposed to improve the system throughput. However, none of these methods enable the system to approach the theoretical maximum throughput possible under DCF. Accordingly, this study proposes the Rapidly Adaptive Collision Backoff (RACB) algorithm, in which the CW size is adjusted dynamically based on the collision rate, as analyzed by a mathematical model. Notably, RACB requires no knowledge of the number of nodes in the wireless network and is applicable to both lightly loaded and heavily loaded networks. The numerical results show that, by adjusting the CW size such that the collision rate is maintained at a value close to 0.1, RACB enables the system throughput to approach the maximum DCF throughput in wireless environments containing any number of nodes.

Wearable electromagnetic interference (EMI) shielding fabrics with excellent electromagnetic shielding performance, oxidation resistance, and structural stability are highly demanded for the rapid development of electronic devices and wireless communication. MXenes are metallic conductive materials with exceptional EMI shielding properties, but they are prone to oxidation in air and have poor structural stability and durability on fabric substrates. Herein, we present a one-step assembly method to fabricate fabrics coated with MXenes and polymeric sodium alginate (SA) composite (MXene-SA). SA protects MXenes from oxidation and forms a stable interlayer structure by bonding to MXenes. The MXene-SA coated fabrics are breathable and flexible, and have a low sheet resistance of 2.12 ± 0.08 Ω/sq and a high EMI shielding performance of 37.05 dB at X-band, which is comparable to the best 42.31 dB. Moreover, the MXene-SA coated fabrics exhibit high structural stability and oxidation resistance under various conditions of sonication disintegration, mechanical abuse, chemical corrosion, and humidity, compared to pure MXenes coated fabrics. We believe that the wearable and high-performance MXene-SA fabrics have great potential for the next generation of ultra-portable and wearable EMI shielding products.

Introduction Tissue adhesives, such as 2-octyl cyanoacrylate, are widely used for tissue approximation and protection of surgical wounds during total knee arthroplasty (TKA). However, drying time for tissue adhesives can increase overall operating time and impede efficiency. Various methods may reduce the drying time of tissue adhesives. However, there is currently no clinical or in vivo data to support these findings. This study aims to investigate whether preheated 2-octyl cyanoacrylate (Dermabond™, Ethicon, Inc., Somerville, NJ, US) shortens drying time in robotic-assisted TKA. Methods This randomized pilot study included 40 patients undergoing TKA, and they were randomized into two groups: the intervention group received Dermabond™ preheated in a solution warmer device, while the control group received Dermabond™ at ambient temperature. Incision size, preparation, and drying times were recorded and compared. Comparison of drying time, preparation time, incision size, BMI, weight, height, age, surgery time, and gender between the preheated and control groups was conducted using the t-test, Levene's test, and the chi-squared test. Results Data from 39 patients were analyzed, as one intervention failed due to premature Dermabond™ drying in the preheated group. The drying time was reduced by an average of 26.8 seconds in the preheated group compared to the control group (p < 0.05). No significant differences were observed in preparation time or incision size between the groups. Conclusion Preheating Dermabond™ reduces drying time; however, the reduction does not provide substantial time savings to alter the current TKA workflow. Improvements in intraoperative efficiency may be better achieved by optimizing other aspects of the procedure.