Random Scheduling Research Articles

Mesenchymal stromal cells plus basiliximab improve the response of steroid-refractory acute graft-versus-host disease as a second-line therapy: a multicentre, randomized, controlled trial

BackgroundFor patients with steroid-refractory acute graft-versus-host disease (SR-aGVHD), effective second-line regimens are urgently needed. Mesenchymal stromal cells (MSCs) have been used as salvage regimens for SR-aGVHD in the past. However, clinical trials and an overall understanding of the molecular mechanisms of MSCs combined with basiliximab for SR-aGVHD are limited, especially in haploidentical haemopoietic stem cell transplantation (HID HSCT).MethodsThe primary endpoint of this multicentre, randomized, controlled trial was the 4-week complete response (CR) rate of SR-aGVHD. A total of 130 patients with SR-aGVHD were assigned in a 1:1 randomization schedule to the MSC group (receiving basiliximab plus MSCs) or control group (receiving basiliximab alone) (NCT04738981).ResultsMost enrolled patients (96.2%) received HID HSCT. The 4-week CR rate of SR-aGVHD in the MSC group was obviously better than that in the control group (83.1% vs. 55.4%, P = 0.001). However, for the overall response rates at week 4, the two groups were comparable. More patients in the control group used ≥ 6 doses of basiliximab (4.6% vs. 20%, P = 0.008). We collected blood samples from 19 consecutive patients and evaluated MSC-derived immunosuppressive cytokines, including HO1, GAL1, GAL9, TNFIA6, PGE2, PDL1, TGF-β and HGF. Compared to the levels before MSC infusion, the HO1 (P = 0.0072) and TGF-β (P = 0.0243) levels increased significantly 1 day after MSC infusion. At 7 days after MSC infusion, the levels of HO1, GAL1, TNFIA6 and TGF-β tended to increase; however, the differences were not statistically significant. Although the 52-week cumulative incidence of cGVHD in the MSC group was comparable to that in the control group, fewer patients in the MSC group developed cGVHD involving ≥3 organs (14.3% vs. 43.6%, P = 0.006). MSCs were well tolerated, no infusion-related adverse events (AEs) occurred and other AEs were also comparable between the two groups. However, patients with malignant haematological diseases in the MSC group had a higher 52-week disease-free survival rate than those in the control group (84.8% vs. 65.9%, P = 0.031).ConclusionsFor SR-aGVHD after allo-HSCT, especially HID HSCT, the combination of MSCs and basiliximab as the second-line therapy led to significantly better 4-week CR rates than basiliximab alone. The addition of MSCs not only did not increase toxicity but also provided a survival benefit.

A Dynamic Task Scheduling Algorithm for Airborne Device Clouds

The rapid development of mobile Internet has promoted the rapid rise of cloud computing technology. Mobile terminal devices have greatly expanded the service capacity of mobile terminals by migrating complex computing tasks to run in the cloud. However, in the process of data exchange between mobile terminals and cloud computing centers, on the one hand, it consumes the limited power of mobile terminals, and on the other hand, it results in longer communication time, which negatively affects user QoE. Mobile cloud can effectively improve user QoE by shortening the data transmission distance, reducing the power consumption, and shortening the communication time at the same time. In this paper, we utilize the property that genetic algorithm can perform global search seeking the global optimal solution and construct a dynamic task scheduling model by combining the device-cloud link. The task scheduling model based on genetic algorithm and random scheduling algorithm is compared through comparison experiments, which show that the assignment time of the task scheduling model based on genetic algorithm is shortened by 11.82% to 48.51% and the energy consumption is reduced by 22.28% to 47.52% under different load conditions.

Safety, tolerability and immunogenicity of PRV-101, a multivalent vaccine targeting coxsackie B viruses (CVBs) associated with type 1 diabetes: a double-blind randomised placebo-controlled Phase I trial

Aims/hypothesisInfection with coxsackie B viruses (CVBs) can cause diseases ranging from mild common cold-type symptoms to severe life-threatening conditions. CVB infections are considered to be prime candidates for environmental triggers of type 1 diabetes. This, together with the significant disease burden of acute CVB infections and their association with chronic diseases other than diabetes, has prompted the development of human CVB vaccines. The current study evaluated the safety and immunogenicity of the first human vaccine designed against CVBs associated with type 1 diabetes in a double-blind randomised placebo-controlled Phase I trial.MethodsThe main eligibility criteria for participants were good general health, age between 18 and 45 years, provision of written informed consent and willingness to comply with all trial procedures. Treatment allocation (PRV-101 or placebo) was based on a computer-generated randomisation schedule and people assessing the outcomes were masked to group assignment. In total, 32 participants (17 men, 15 women) aged 18–44 years were randomised to receive a low (n=12) or high (n=12) dose of a multivalent, formalin-inactivated vaccine including CVB serotypes 1–5 (PRV-101), or placebo (n=8), given by intramuscular injections at weeks 0, 4 and 8 at a single study site in Finland. The participants were followed for another 24 weeks. Safety and tolerability were the primary endpoints. Anti-CVB IgG and virus-neutralising titres were analysed using an ELISA and neutralising plaque reduction assays, respectively.ResultsAmong the 32 participants (low dose, n=12; high dose, n=12; placebo, n=8) no serious adverse events or adverse events leading to study treatment discontinuation were observed. Treatment-emergent adverse events considered to be related to the study drug occurred in 37.5% of the participants in the placebo group and 62.5% in the PRV-101 group (injection site pain, headache, injection site discomfort and injection site pruritus being most common). PRV-101 induced dose-dependent neutralising antibody responses against all five CVB serotypes included in the vaccine in both the high- and low-dose groups. Protective titres ≥8 against all five serotypes were seen in >90% of participants over the entire follow-up period.Conclusions/interpretationThe results indicate that the tested multivalent CVB vaccine is well tolerated and immunogenic, supporting its further clinical development.Trial registrationClinicalTrials.gov NCT04690426.FundingThis trial was funded by Provention Bio, a Sanofi company.Graphical

Lifetime maximization of wireless sensor networks while ensuring intruder detection

Wireless sensor networks (WSN) have a wide variety of application areas and one of these areas is border crossing security. Unauthorized crossing of border areas, unauthorized arms and drug trafficking can be avoided at a lower cost and easier than conventional methods by monitoring the borders with the help of a WSN. In this study, we offer a mathematical model that guarantees the detection of possible intruders by scheduling the activities of the sensors whatever the route the intruder follows throughout the border zone or whatever the time the intruder enters to the route. To achieve the highest possible WSN management efficiency, we integrate coverage, routing, data routing, and sensor scheduling WSN design issues into the mathematical model. We first demonstrate the effectiveness of scheduling the sensors by the help of the offered mathematical model by comparing it against a random activity schedule of the sensors with respect to network lifetime and intruder detection ratio performance measures. We also develop a Lagrangean heuristic strategy to solve realistic sized instances of the proposed problem. We produce several random border zone instances with varying sizes and test the proposed solution strategy to illustrate the effectiveness of the offered solution strategy by comparing its performance against the performance of a commercial mixed-integer linear programming (MILP) solver.

On differential privacy for federated learning in wireless systems with multiple base stations

AbstractIn this work, we consider a federated learning model in a wireless system with multiple base stations and inter‐cell interference. We apply a differentially private scheme to transmit information from users to their corresponding base station during the learning phase. We show the convergence behavior of the learning process by deriving an upper bound on its optimality gap. Furthermore, we define an optimization problem to reduce this upper bound and the total privacy leakage. To find the locally optimal solutions of this problem, we first propose an algorithm that schedules the resource blocks and users. We then extend this scheme to reduce the total privacy leakage by optimizing the differential privacy artificial noise. We apply the solutions of these two procedures as parameters of a federated learning system where each user is equipped with a classifier and communication cells have mostly fewer resource blocks than numbers of users. The simulation results show that our proposed scheduler improves the average accuracy of the predictions compared with a random scheduler. In particular, the results show an improvement of over 6%. Furthermore, its extended version with noise optimizer significantly reduces the amount of privacy leakage.

Demonstration of the collusion risk mitigation effect of random tie-breaking and dynamic scheduling

We study the “groups of three” tournament format which was planned to be implemented in the 2026 FIFA World Cup. Finally, FIFA resigned from the format because its implementation is highly likely to lead to collusion (match-fixing). In our paper, we show that some modifications to this format may significantly reduce the risk of collusion. Such a reduction can be achieved by the following two innovative changes: random tie-breaking based on the goal-difference along with dynamic scheduling. Our Monte Carlo simulations show that the expected number of matches with high risk of collusion is reduced from 5.5 in the FIFA's initial proposal to 0.26 in our proposed design.

Sparse CNN and Deep Reinforcement Learning-Based D2D Scheduling in UAV-Assisted Industrial IoT Networks

Unmanned aerial vehicles (UAVs) have been widely applied in wireless communications because of its high flexibility and line-of-sight transmission. In this study, we develop low-complexity and robust device-to-device (D2D) link scheduling in UAV-assisted industrial Internet of Things (IIoT) networks. First, we propose a sparse convolutional neural network (SCNN) model that uses the geographical map of transmission links as input. The model consists of three main blocks: generic feature filtering, speed–accuracy balancing, and deep feature processing. Unlike other state-of-the-art methods, the proposed SCNN directly processes the geographical map collected using a connected UAV. Second, we propose a deep deterministic policy gradient-based reinforcement learning model that processes the output feature map from the SCNN to optimize the D2D scheduling decision and maximize the achievable system rate in the long run. Extensive simulations revealed that the proposed scheme significantly improved the achievable rate over other benchmark comparison schemes, such as transmitters and receivers (T&R) density-based deep learning (DL), ResNet-based DL, VGGNet-based DL, random scheduling, and all-active schemes, respectively. The simulations also demonstrated that the proposed scheme reduces computational complexity. With reduced complexity and nearly optimal performance, the proposed solution can be more efficiently applied to large-scale and dense IIoT networks.

Contextual Interference Effect in Learning of Simulated Laparoscopic Tasks

Laparoscopy, a minimally invasive surgical technique involving fine motor movements of the hands and fingers, has proven to be an invaluable tool in surgical care. Expediting the learning process of surgeons to reach proficiency in this surgical technique directly impacts patient outcomes, recovery times, and time management in hospitals [1]. Within motor learning, blocked and random practice has been identified as having correspondingly low or high levels of contextual interference, with different effects on learning and retention of motor skills. Contextual interference can be described as the level of mental interference created during the practice of motor skills. So far, research has been equivocal in identifying the best practice schedule for optimizing the acquisition and retention of fine and gross motor skills. This study examines the role of contextual interference in the acquisition, short-term retention (10-minute), and long-term retention (10-day) of three variations of a simulated laparoscopic task in 60 adults aged 18-65, 30 males and 30 females. The index of performance was represented by the total time taken to complete each task using curved laparoscopic graspers. Results showed that both blocked and random practice groups significantly improved acquisition performance over 54 acquisition trials. Participants undergoing a blocked practice schedule improved their pattern time-to-completion by 46%, retaining most of their performance in the 10-minute retest while maintaining their skill as well after 10 days. The random practice group improved acquisition performance by 38%, maintaining most of their performance in the short-term retention test, with only a slight decrease in speed in the long-term retention test. No statistically significant differences in the efficiency of blocked versus random practice schedules were found for both acquisition and retention, suggesting that both practice schedules can be viable options for learning and retention of simulated laparoscopic surgical tasks. We suggest tailoring training programs to individual skill levels to provide each learner with the optimal amount of contextual interference to reach their optimal challenge point according to subjective task difficulty experienced.

Safety and immunogenicity of shorter interval schedules of the novel oral poliovirus vaccine type 2 in infants: a phase 3, randomised, controlled, non-inferiority study in the Dominican Republic

The novel oral poliovirus vaccine type 2 (nOPV2) is now authorised by a WHO emergency use listing and widely distributed to interrupt outbreaks of circulating vaccine-derived poliovirus type 2. As protection of vulnerable populations, particularly young infants, could be facilitated by shorter intervals between the two recommended doses, we aimed to assess safety and non-inferiority of immunogenicity of nOPV2 in 1-week, 2-week, and 4-week schedules. In this phase 3, open-label, randomised trial, healthy, full-term, infants aged 6-8 weeks from a hospital or a clinic in the Dominican Republic were randomly allocated (1:1:1 ratio) using a pre-prepared, computer-generated randomisation schedule to three groups to receive two doses of nOPV2 immunisations with a 1-week interval (group A), 2-week interval (group B), or 4-week interval (group C). The nOPV2 vaccine was given at a 0·1 mL dose and contained at least 105 50% cell culture infective dose. Neutralising antibodies against poliovirus types 1, 2, and 3 were measured before each immunisation and 4 weeks after the second dose. The primary outcome was the type 2 seroconversion rate 28 days after the second dose, and the non-inferiority margin was defined as a lower bound 95% CI of greater than -10%. Safety and reactogenicity were assessed through diary cards completed by the parent or guardian. The trial is registered with ClinicalTrials.gov, NCT05033561. We enrolled 905 infants between Dec 16, 2021, and March 28, 2022. 872 infants were included in the per-protocol analyses: 289 in group A, 293 in group B, and 290 in group C. Type 2 seroconversion rates were 87·5% (95% CI 83·2 to 91·1) in group A (253 of 289 participants), 91·8% (88·1 to 94·7) in group B (269 of 293 participants), and 95·5% (92·5 to 97·6) in group C (277 of 290 participants). Non-inferiority was shown for group B compared with group C (difference in rates -3·7; 95% CI -7·9 to 0·3), but not for group A compared with group C (-8·0; -12·7 to -3·6). 4 weeks after the second nOPV2 dose, type 2 neutralising antibodies increased in all three groups such that over 95% of each group was seroprotected against polio type 2, although final geometric mean titres tended to be highest with longer intervals between doses. Immunisation with nOPV2 was well tolerated with no causal association to vaccination of any severe or serious adverse event; one death from septic shock during the study was unrelated to the vaccine. Two nOPV2 doses administered 1 week or 2 weeks apart from age 6 weeks to 8 weeks were safe and immunogenic. Immune responses after a 2-week interval were non-inferior to those after the standard 4-week interval, but marked responses after a 1-week interval suggest that schedules with an over 1-week interval can be used to provide flexibility to campaigns to improve coverage and hasten protection during circulating vaccine-derived poliovirus type 2 outbreaks. Bill & Melinda Gates Foundation.

A scalable modified deep reinforcement learning algorithm for serverless IoT microservice composition infrastructure in fog layer

Nowadays many modern and Artificial Intelligence (AI) enabled Internet of Things (IoT) applications consist of chains connecting microservices distributed across the fog and cloud layers to achieve a certain functionality. These microservices should be assigned to the available processing instances placed on the things, fog and cloud layers while considering the resource utilization, Quality of Service (QoS) parameters and requirements of the user. Despite several existing optimization approaches, IoT microservice composition remains a challenge in serverless computing architecture due to the large-scale environment, its dynamic nature and the heterogeneous nodes with limited capacity. To address these challenges, a novel IoT microservice composition based on serverless architecture is proposed in the fog layer. Serverless computing is a new paradigm which offers the ability to build scalable applications without worrying about back-end management making this paradigm particularly effective in IoT environment. We specifically propose a modified Deep Reinforcement Learning (DRL)-based Microservice Chaining at Fog Layer (DRLMCF) algorithm to improve the distributed chained microservice placement in order to minimize resource utilization and delay in a fog based serverless architecture. Unlike existing methods, the proposed DRLMCF is built on realistic assumptions and does not require expert tuning or a large amount of labeled data to make optimal decisions. Furthermore, our method is not entirely dependent on a central controller and fog nodes take part in the decision making thus making the algorithm scalable in IoT environment. Compared to state-of-the art methods including load balance, shortest path and random schedule algorithms, evaluation by simulating several real-world scenarios demonstrates the proposed DRLMCF improves end to end delay up to 57.3% and the number of successfully chained microservices by up to 84%.

Accelerated versus standard epirubicin followed by cyclophosphamide, methotrexate, and fluorouracil or capecitabine as adjuvant therapy for breast cancer (UK TACT2; CRUK/05/19): quality of life results from a multicentre, phase 3, open-label, randomised, controlled trial

Adjuvant chemotherapy for patients with early breast cancer improves outcomes but its toxicity affects patients' quality of life (QOL). The UK TACT2 trial investigated whether accelerated epirubicin improves time to recurrence and if oral capecitabine is non-inferior to cyclophosphamide, methotrexate, and fluorouracil (CMF) for efficacy with less toxicity. Results showed no benefit for accelerated epirubicin and capecitabine was non-inferior. As part of the QOL substudy, we aimed to assess the effect of chemotherapies on psychological distress, physical symptoms, and functional domains. TACT2 was a multicentre, phase 3, open-label, parallel-group, randomised, controlled trial done in 129 UK centres. Participants were aged 18 years or older with histologically confirmed node-positive or high-risk node-negative invasive primary breast cancer, who had undergone complete excision, and due to receive adjuvant chemotherapy. Patients were randomly assigned (1:1:1:1) to four cycles of 100 mg/m2 epirubicin either every 3 weeks (standard epirubicin) or every 2 weeks with 6 mg pegfilgrastim on day 2 of each cycle (accelerated epirubicin), followed by four 4-week cycles of either CMF (600 mg/m2 cyclophosphamide intravenously on days 1 and 8 or 100 mg/m2 orally on days 1-14; 40 mg/m2 methotrexate intravenously on days 1 and 8; and 600 mg/m2 fluorouracil intravenously on days 1 and 8 of each cycle) or four 3-week cycles of 2500 mg/m2 capecitabine (1250 mg/m2 given twice daily on days 1-14 of each cycle). The randomisation schedule was computer generated in random permuted blocks, stratified by centre, number of nodes involved (none vs 1-3 vs ≥4), age (≤50 years vs >50 years), and planned endocrine treatment (yes vs no). QOL was one of the secondary outcomes and is reported here. All patients from a subset of 44 centres were invited to complete QOL questionnaires (Hospital Anxiety and Depression Scale [HADS] and European Organisation for Research and Treatment of Cancer [EORTC] Quality of Life Questionnaire 30-item core module [QLQ-C30] and Quality of Life Questionnaire breast module [QLQ-BR23]) at baseline, end of standard or accelerated epirubicin, end of CMF or capecitabine, and at 12 and 24 months after randomisation. The QOL substudy prespecified two coprimary QOL outcomes assessed in the intention-to-treat population: overall QOL (reported elsewhere) and HADS total score. Prespecified secondary QOL outcomes were EORTC QLQ-C30 subscales of physical function, role function, and fatigue and EORTC QLQ-BR23 subscales of sexual function and systemic therapy side-effects. This trial is registered with ISRCTN, ISRCTN68068041, and ClinicalTrials.gov, NCT00301925. From Dec 16, 2005, to Dec 5, 2008, 4391 patients (20 [0·5%] of whom were male) were enrolled in TACT2; 1281 (85·8%) of 1493 eligible patients were included in the QOL substudy. Eight (0·6%) participants in the QOL substudy were male and 1273 (99·4%) were female. Median follow-up was 85·6 months (IQR 80·6-95·9). Analysis was performed on the complete QOL dataset (as of Sept 15, 2011) when all participants had passed the 24-month timepoint. Prerandomisation questionnaires were completed by 1172 (91·5%) patients and 1179 (92·0%) completed at least one postrandomisation questionnaire. End-of-treatment HADS depression score (p=0·0048) and HADS total change score (p=0·0093) were worse for CMF versus capecitabine. Accelerated epirubicin led to worse physical function (p=0·0065), role function (p<0·0001), fatigue (p=0·0002), and systemic side-effects (p=0·0001), but not sexual function (p=0·36), compared with standard epirubicin during treatment, but the effect did not persist. Worse physical function (p=0·0048), sexual function (p=0·0053), fatigue (p<0·0001), and systemic side-effects (p<0·0001), but not role functioning (p=0·013), were seen for CMF versus capecitabine at end of treatment; these differences persisted at 12 months and 24 months. Accelerated epirubicin was associated with worse QOL than was standard epirubicin but only during treatment. These findings will help patients and clinicians make an informed choice about accelerated chemotherapy. CMF had worse QOL effects than did capecitabine, which were persistent for 24 months. The favourable capecitabine QOL compared with CMF supports its use as an adjuvant option after neoadjuvant chemotherapy in patients with triple-negative breast cancer. Cancer Research UK, Amgen, Pfizer, and Roche.

A Measurement Scheduling Method for Multi-vehicle Cooperative Localization Considering State Correlation

Accurate and robust localization is a fundamental requirement for safe autonomous driving. Currently, most vehicles rely on single-vehicle localization (SVL) using the global navigation satellite system (GNSS) for obtaining the position data. However, in urban canyons or areas with signal interruptions, the GNSS signals may be unreliable, thus leading to accumulated errors in SVL. In contrast, cooperative localization provides the advantages of superior accuracy, good fault tolerance, and high flexibility by leveraging multi-source data from self-sensors and neighboring vehicles. Nevertheless, establishing communication links with all surrounding vehicles can introduce a severe communication burden and thus impact real-time data processing performance. To address these challenges, this paper proposes a cooperative localization method with loosely-coupled communication that considers the state correlation. In this study, the communication process is divided into two topologies to ensure filter consistency, and an approximate variable substitutions technique enables suboptimal estimation of a cross-covariance matrix. Furthermore, a dynamic period measurement scheduling (DPMS) method is proposed. The DPMS optimally selects vehicles for cooperative localization based on the covariance matrix trace values, considering three factors of location uncertainty and employing a weight function for period adjustment. Finally, the proposed method is evaluated through multiple simulations and field tests, assessing the algorithm convergence, localization accuracy, execution time, and communication burden. The results demonstrate that compared to the sequential greedy algorithm, the proposed method can significantly reduce communication and computation burden while achieving higher localization accuracy than the random measurement scheduling method and the measurement scheduling method based on a deep neural network.

Implementation of Random Search Algorithm with FSSRS (Fixed Step Size Random Search) for Applicating the Patrol System Based on Mobile Computing

Environmental security is very influential for the sustainability of human life. In order for environmental security to remain in a safe condition, a system is needed that can control the environment, such as patrolling at every point to ensure that the environmental conditions are safe. However, it is felt that this is not enough if the patrol system is not assisted by tools or systems that are digitalized and integrated with community service officers, such as firefighters, ambulances, and police, and are easy for officers to use when conducting patrols. So, it is necessary to schedule patrols to several points with different routes for each activity so that it is not easily read by unwanted parties in terms of crime. In order for the system to obtain patrol scheduling in a timely and efficient manner, an appropriate and efficient algorithm is needed, the algorithm is random search with FSSRS (Fixed Step Size Random Search) which can suggest random and precise patrol scheduling. From the results of training using four iterations, namely 50, 100, 150, and 200, the best value was produced in the 200th iteration. Data was taken from the results of a case study survey with eight patrol points using coordinates at each point. So, it can be concluded that the FSSRS algorithm is effectively used to randomize patrol points and can be implemented in the application patrol system.

Replay attack detection and mitigation for cyber–physical systems via RADIR algorithm with encryption scheduling

This paper investigates the security state estimation issue facing replay attacks in confidential cyber–physical systems. Smart sensor equipped with a power harvester transmits critical measurements to the remote estimator over wireless networks, in which the transmission modes include encrypted and normal. In order to complete the persistent threats, the adversary launches multi-stage discontinuous replay attacks to compromise the estimation process. In virtue of the designed label detection scheme, we transform attack detection into encryption scheduling optimization under the constraint of sensor energy harvesting and acquire a rigorous relationship between detection probability, attack duration, and encryption ratio. Different from most existing studies only focusing on attack detection, the localization of replay interval measured by detection immediacy is also analyzed. Subsequently, the optimal periodic encryption scheduling strategy is given to maximally determine the attack interval by adopting an optimization-based approach. Further, a complete algorithm of replay attack detection, isolation, and recovery (RADIR) is designed to minimize deterioration from multi-stage attacks, which can guarantee the estimated performance of the system as much as possible. Finally, the unmanned ground vehicle system is applied to validate the theoretical results, where the dataset of replay attacks is obtained by capturing the normal operation data of a moving vehicle. Also, we compare the optimal encryption strategy designed in this paper with general centralized and random scheduling strategies.

Comparison of the efficacy of thulium fiber laser and holmium laser lithotripsy in the treatment of upper urinary tract stones

Objective: To compare the efficacy of thulium fiber laser (TFL) and holmium laser (HL) in the treatment of upper urinary tract stones. Methods: A total of 76 patients diagnosed with upper urinary tract stones by radiographic examination and who required ureteroscopy lithotripsy or retrograde intrarenal stone surgery were prospectively enrolled from the Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine between January 2022 and June 2022. Patients were divided into TFL group (n=38) and HL group (n=38) in a 1∶1 ratio according to the randomization schedule. The perioperative outcomes and stone-free rate of two groups were recorded and compared. Results: Finally, the clinical data of 71 patients were completely collected, including 55 males and 16 females, with a mean age of (45.7±14.1) years old. There were 36 patients in TFL group and 35 patients in HL group, and there was no significant difference in age, body mass index, gender, Charlson comorbidity index, stone site, stone location, stone size and stone density between two groups (all P>0.05). All the surgeries were successfully performed with no intraoperative complications. There were no significant differences between the two groups in terms of operation time, stone displacement during lithotripsy, visual field clarity, changes in hemoglobin, leukocyte, and C-reactive protein, and length of postoperative hospital stay (all P>0.05), but the laser action time[M (Q1,Q3)] in the TFL group was 30.0 (20.0, 48.8)s, which was significantly shorter than that in the HL group [90.0 (50.0, 120.0)s, P<0.001]. The stone-free rates of TFL group and HL group were 97.2% (35/36) and 88.6% (31/35), and there was no significant difference (P=0.337). The postoperative complication incidences of TFL group and HL group were 36.1% (13/36)and 22.9% (8/35), respectively, and the difference was not significant either (P=0.221). For ureter stones, the laser action time in TFL group was 22.5 (20.0, 43.8)s, which was significantly shorter than that in HL group [80.0 (50.0, 120.0)s, P<0.001]. For stones with maximum diameter≤10 mm, the laser action time in TFL group was 20.0 (10.0, 25.0)s, which was significantly shorter than that in HL group [50.0 (40.0, 80.0)s, P<0.001]. For stones with maximum diameter>10 mm, the laser action time in TFL group was 60.0(42.5, 180.0)s, which was significantly shorter than that in HL group [180.0(120.0, 210.0)s, P=0.035]. For stones with density≤1 000 CT, the laser action time in TFL group was 30.0 (20.0, 45.0)s, which was significantly shorter than that in HL group [95.0 (47.5, 120.0), P=0.001]. For stones with density>1 000 CT, the laser action time in TFL group was 30.0 (20.0, 90.0)s, which was significantly shorter than that in HL group [80.0 (55.0, 180.0)s, P=0.033]. Conclusion: TFL lithotripsy is an effective and safe surgical procedure for the treatment of upper urinary tract stones, with similar clinical efficacy but shorter laser action time compared to HL lithotripsy.

An optimal scheduling algorithm considering the transactions worst-case delay for multi-channel hyperledger fabric network

As the most popular consortium blockchain platform, Hyperledger Fabric (Fabric for short) has released multiple versions that support different consensus protocols to address the risks faced in current and future network transactions. For example, Fabric v1.4 and v2.0 use Kafka and Raft mechanisms to complete consensus and ensure that the system can withstand failures such as crashes, network partitions, or network shutdowns. In a multi-channel Fabric network architecture, the system structure cannot guarantee the behavior of malicious nodes. Complex cooperation between peer groups on different channels can greatly affect the security and efficiency of the entire network architecture, which is challenging to estimate and optimize.To address this challenge, we designed a Drift Plus Penalty Algorithm (DPPA) and a Transaction Worst-case Delay Algorithm (TWDA) based on peer node random scheduling using the Lyapunov optimization framework. The DPPA ensures the stability of the system and provides the maximum transaction processing rate under the minimum safety probability. The numerical results show that this algorithm can achieve a good balance between system security probability and queue accumulation. The TWDA considers discarding transactions with excessively long delay time by setting a worst-case transaction delay threshold. When considering both the security probability and queue accumulation of the Fabric system, the optimal scheduling of peer nodes is given. Numerical simulations were conducted on two types of algorithms, and the results showed that the security of the TWDA was slightly worse than that of the DPPA, but the system queue accumulation was significantly smaller. Therefore, the simulation results not only validate the effectiveness of the two types of algorithms but also provide operators with operational strategies that consider different factors.

Distributed Data Flow Scheduling Optimization in Industrial Internet of Things Based on Optimal Transport Theory

The development of industrial internet of things (IIoT) has completely changed the traditional manufacturing industry. The data exchange between controllers and actuators needs to achieve extremely low delay in IIoT. Due to the limited communication resources, it is necessary to reasonably schedule data flow to reduce delay. Although the studies of data flow scheduling exist in IIoT, they have not considered the impact of time-varying environmental factors and most of them adopted centralized scheduling schemes, which increase computation and communication cost rapidly in large-scale network scenarios. In this paper, the consensus-based distributed optimal transport (OT) algorithm is proposed to optimize data flow scheduling for IIoT networks. Specifically, a data flow scheduling optimization mechanism based on time-varying environmental factors is proposed and an online distributed data flow scheduling optimization algorithm is designed. Compared with the random data flow scheduling algorithm, numerical results show that the proposed algorithm can maximally reduce the average delay by 87%, increase the transmission rate and the spectral efficiency by 157% and 98%, respectively.

Optimizing generating unit maintenance with the league championship method: A reliability-based approach

The electrical power industry has experienced an unprecedented pace of digital transformation as a prevailing economic trend in recent years. This shift towards digitalization has resulted in an increasing interest in the collection of real-time equipment condition data, which provides opportunities for implementing sensor-driven condition-based repair. As a result, there is a growing need for the development of generator maintenance scheduling to consider probabilistic equipment behavior, which requires significant computational efforts. To address this issue, the research proposes the use of a meta-heuristic league championship method (LCM) for generator maintenance scheduling, considering random generation profiles based on generation adequacy criteria. The experimental part of the study compares this approach and its modifications to widely used meta-heuristics, such as differential evolution and particle swarm methods. The identification and demonstration of optimal method settings for the generation maintenance scheduling problem are presented. Subsequently, it is illustrated that employing random league scheduling expedience can reduce the variance of objective function values in resulting plans by over three times, with values of 0.632 MWh and 0.205 MWh for conventional and proposed techniques respectively. In addition, three approaches are compared to assess generation adequacy corresponding to different schedules. The study emphasizes the efficacy of employing the LCM approach in scheduling generator maintenance. Specifically, it showcases that among all the methods examined, the LCM approach exhibits the lowest variance in objective function values, with values of 38.81 and 39.90 MWh for LCM and its closest rival, the modified particle swarm method (MPSM), respectively.

Interference Aware Resource Control for 6G-Enabled Expanded IoT Networks

Emerging consumer devices rely on the next generation IoT for connected support to undergo the much-needed digital transformation. The main challenge for next-generation IoT is to fulfil the requirements of robust connectivity, uniform coverage and scalability to reap the benefits of automation, integration and personalization. Next generation mobile networks, including beyond 5G and 6G technology, play an important role in delivering intelligent coordination and functionality among the consumer nodes. This paper presents a 6G-enabled scalable cell-free IoT network that guarantees uniform quality-of-service (QoS) to the proliferating wireless nodes or consumer devices. By enabling the optimal association of nodes with the APs, it offers efficient resource management. A scheduling algorithm is proposed for the cell-free model such that the interference caused by the neighbouring nodes and neighbouring APs is minimised. The mathematical formulations are obtained to carry out the performance analysis with different precoding schemes. Further, the allocation of pilots for obtaining the association with minimum interference is managed using different pilot lengths. It is observed that the proposed algorithm offers an improvement of 18.9% in achieved spectral efficiency using partial regularized zero-forcing (PRZF) precoding scheme at pilot length τp=10. In the end, the performance comparison with two other models incorporating random scheduling and no scheduling at all is carried out. As compared to random scheduling, the proposed scheduling shows improvement of 10.9% in obtained spectral efficiency by 95% of the user nodes.

(024) A Randomized Trial on the Sexual Effectiveness and Impact on the Vaginal Microbiome of Reformulated Personal Water Lubricants with Lowered Osmolality and pH in Premenopausal and Postmenopausal Women

Abstract Introduction Vaginal dryness may be associated with postmenopausal women; however, it may also occur due to chronic medical conditions and as a direct side effect from medications. Personal lubricants can address sexual complaints and symptomatology associated with vaginal dryness, although clinically published data supporting their efficacy remains limited. Age-associated vaginal-physiological changes due to hypoestrogenic milieux include increased pH, decreased natural lubrication, reduced endothelial rugae and altered vaginal microbiome. While personal lubricants may alleviate symptoms, their definitive effects on the vaginal microbiome remain understudied and underappreciated. Objective This study examined reformulated water-based lubricants (lowered osmolalities and pH,) and their effect on female sexual function compared to their counterparts (higher osmolalities/increased pH). A secondary analysis examined if these reformulated lubricants influenced the vaginal microbiome of women from different age groups. Methods An open-label, parallel-design study was performed in heterosexual women in stable monogamous relationships, aged 18–65 years with mild-to-moderate vaginal dryness and dyspareunia. The study population (n=174) included an approximate 50:50 ratio of premenopausal to postmenopausal women. The randomization schedule was stratified by menopausal status. Subjects were randomized to use one of five water-based lubricants and instructed to use their lubricant during vaginal intercourse at least once a week over a 4-week period. The Female Sexual Function Index (FSFI) measured sexual functioning after 4 weeks of use as an indicator of lubricant performance. More than a 4-point increase in total FSFI is deemed clinically important. From the study-enrolled subjects, 50 females were randomized to one of five lubricant treatment groups for secondary microbiome analysis. To this end, four vaginal swabs per participant were sampled during pre- (“baseline”) and post- (“2 hours”, “24 hours” and “4 weeks”) lubricant application to assess bacterial diversity via 16S sequencing. Additionally, vaginal moisture and pH measurements were collected at baseline, 2 hours, and 24 hours post-lubricant application and correlated with microbiome diversity and richness using non-parametric tests and linear mixed models. Results An increase in FSFI total score of &amp;gt;4 points was found for all lubricants in the total population and for 4/5 lubricants in the premenopausal subgroup, as indicated by the mean differences to baseline. The number of subjects in sexual function (total FSFI &amp;gt;26.55) after treatment was significantly greater than the number in sexual function before treatment for both subgroups (premenopausal 19.3% to 78.4%; postmenopausal 22.3% to 75.3%; p&amp;lt;0.0001 for both). Lactobacillus species and Gardnerella vaginalis were the predominant taxa across all participants. Repeated lubricant applications did not alter the vaginal microbiome for up to 4 weeks post-product applications. Microbial diversity and relative abundance differed significantly between age groups but remained unaffected during product applications. Relative abundance of Lactobacilli spp. negatively correlated with vaginal pH while that of Gardnerella spp. showed a positive correlation with vaginal pH across all age groups. Conclusions These reformulated lubricants can be used not only to relieve symptomatology of vaginal dryness and dyspareunia, but to enhance overall sexual satisfaction regardless of menopausal status. These study lubricants demonstrated no significant impact on vaginal microbiome. Further studies with larger samples are warranted. Disclosure Yes, this is sponsored by industry/sponsor: Reckitt Benckiser Health. Clarification: Industry funding only - investigator initiated and executed study. Any of the authors act as a consultant, employee or shareholder of an industry for: Reckitt Benckiser Health.