Terms Of Optimal Timing Research Articles

The Role of Radiotherapy in the Management of Vaginal Melanoma: A Literature Review with a Focus on the Potential Synergistic Role of Immunotherapy.

Among the mucosal melanomas, vaginal melanomas are very rare tumors, accounting for less than 20% of melanomas arising from the female genital tract. They occur most frequently in women in post-menopausal age, but younger patients may also experience this neoplasm, mainly located in the lower third of the vagina or the anterior wall. The optimal management of this tumor remains controversial, with surgery reported as the most frequently adopted approach. However, a clear benefit of surgical treatment in terms of survival has not yet been demonstrated. Conversely, radiotherapy may represent an attractive non-invasive alternative, and there are several favorable reports of the role of radiation therapy, either delivered with photons, brachytherapy, or hadrontherapy. A wide range of techniques and fractionation regimens are reported with substantially good tolerance to the treatment, and acute G3 or higher toxicities are reported only in the case of concurrent immunotherapy. Of note, due to the rarity of the disease, there is a lack of high-level evidence for the optimal therapeutic option. In this scenario, recent studies theorize the possibility of developing combinatorial approaches of radiotherapy with immunotherapy based on cutaneous melanomas reports. In this review, we aim to summarize the evidence available in the literature supporting the role of definitive radiotherapy for vaginal melanomas, with a focus on the combination of RT with immunotherapy, in terms of optimal timing and biological rationale.

Vestibular schwannoma associated with neurofibromatosis type 2: Clinical course following stereotactic radiosurgery.

ObjectiveA lack of understanding of the clinical course of neurofibromatosis type 2 (NF2)-associated vestibular schwannoma (VS) often complicates the decision-making in terms of optimal timing and mode of treatment. We investigated the outcomes of stereotactic radiosurgery (SRS) in this population.MethodsWe retrospectively analyzed NF2 patients treated with Gamma-Knife SRS for VS in our tertiary referral center. A total of 41 treated lesions from 33 patients were collected with a follow-up period of 69.1 (45.0-104.8) months. We reviewed the treatment history, hearing function, and other treatment-related morbidities in individual cases. We also analyzed pre- and post-treatment tumor volumes via imaging studies. Longitudinal volumetric analyses were conducted for the tumor volume response of the 41 treated lesions following SRS. The growth pattern of 22 unirradiated lesions during an observation period of 83.4 (61.1-120.4) months was separately evaluated.ResultsMost treated lesions showed effective tumor control up to 85% at 60 months after SRS, whereas unirradiated lesions progressed with a relative volume increase of 14.0% (7.8-27.0) per year during the observation period. Twelve (29%) cases showed pseudoprogression with significant volume expansion in the early follow-up period, which practically reduced the rate of tumor control to 57% at 24 months. Among the patients with serviceable hearing, two (20%) cases lost the hearing function on the treated side during the early follow-up period within 24 months.ConclusionsProgressive NF2-associated VS can be adequately controlled by SRS but the short-term effects of this treatment are not highly advantageous in terms of preserving hearing function. SRS treatment candidates should therefore be carefully selected.

Integrated multi-stage and multi-zone distribution network expansion planning with renewable energy sources and hydrogen refuelling stations for fuel cell vehicles

In line with the growing pressures on implementing zero-carbon emission policies and the implementation of hydrogen in the transport sector, energy markets are experiencing inevitable transformation and interactions. Since fuel cell electric vehicles have been attracting considerable attention, the production and supply of renewable hydrogen through hydrogen refuelling stations (HRSs) are of great importance. The growing energy demand, inappropriate siting and sizing of HRSs, and high penetration of distributed renewable energy sources (RESs) make power distribution network planning very challenging. This paper proposes an integrated multi-stage and multi-zone expansion planning framework to coordinate the investment and scheduling of HRSs, wind and solar energy sources, and the distribution network. To model the green HRSs, water electrolysers powered by renewable electricity and storage tanks to locally produce and store hydrogen are suggested. The objective of the proposed problem is to minimise the investment, operation, emissions, and maintenance costs of network’s assets, RESs, and HRSs. The RESs expansion scheme comprises the installation of two different groups; the former pertains to distributed renewable sources installed over the network while the latter is integrated into HRSs. Case studies are conducted on 6-node and real Australian 100-node distribution networks. The results show the effectiveness of the proposed model in terms of optimal timing, sizing, location, and operational schedules of HRSs, RESs, and distribution network’s assets.

The role of parenteral nutrition in paediatric critical care, and its consequences on recovery

: The goal of nutritional support during critical illness is to provide the appropriate amount of nutrition accounting for the acute, stable and recovery phase in order to accelerate recovery and to improve short-term and long-term outcomes. Although the preferred route to provide nutritional support during paediatric critical illness is via enteral route, reaching target intakes is often difficult due to (perceived) feeding intolerance, fluid restriction, and interruptions around procedures. Because undernourishment in these children has been associated with impaired outcome, parenteral nutrition (PN) has therefore been viewed as an optimal alternative for reaching early and high nutritional targets. However, PN recommendations regarding timing, dose and composition varied widely and were based on studies using intermediate or surrogate endpoints and observational studies. It was not until the paediatric early versus late PN in critically ill children (PEPaNIC) randomized controlled trial (RCT) that the advice to reach high and early macronutrient goals via PN was challenged. The PEPaNIC study showed that omitting supplemental PN during the first week of paediatric intensive care unit (PICU) admission as compared with early initiation of PN (<24 hours) reduced new acquired infections and accelerated recovery. The provision of amino acids in particular was negatively associated with short-term outcomes, probably explained by the suppression of the activation of autophagy. Autophagy is an evolutionary conserved intracellular degradation process and it is crucial for maintaining cellular integrity and function, which becomes even more important during acute stress. Results of the long-term PEPaNIC follow-up study showed that withholding early PN did not negatively affect anthropometrics and health status but improved neurocognitive and psychosocial development 2 and 4 years later. Current guidelines therefore advise to consider withholding parenteral macronutrients for the first week of PICU admission, while providing micronutrients. Although parenteral restriction during the first week of critical illness has been found beneficial, further research beyond the acute phase is warranted to determine the best role of PN in terms of optimal timing, dose and composition in order to improve short-term recovery and long-term developmental outcomes.

Efficient design optimization of complex system through an integrated interface using symbolic computation

A complex system is composed of several subsystems and numerous lower level components. It is inefficient to design the complex system at the system level by using high-fidelity models. A system level approach using a language-based model is required to design such a highly complex system before implementing a detailed design. However, as commercial process integration and design optimization software packages focus on detailed design, which uses the high-fidelity models, it is difficult to perform the design optimization of a highly complex system, such as a combat vehicle. Moreover, as commercial optimization software packages use numerical computation, the gradient calculation cost can increase, and the matrix computation process can be inefficient in terms of optimization time. Therefore, in this study, an integrated interface for efficient design optimization was developed to focus on concept design using a MODELICA language-based model. Additionally, the design variable screening by using analysis of variance, surrogate modeling through sequential design of experiments, and symbolic computation were used to solve the aforementioned problems. These were applied to the design optimization of the combat vehicle system to demonstrate the effectiveness of the integrated interface and symbolic computation. In conclusion, a concept design utilizing a MODELICA language-based model was achieved, and the optimization time achieved by symbolic computation was largely reduced in comparison to the optimization time achieved by numerical computation.

A General Framework for Accelerating Swarm Intelligence Algorithms on FPGAs, GPUs and Multi-Core CPUs

Swarm intelligence algorithms (SIAs) have demonstrated excellent performance when solving optimization problems including many real-world problems. However, because of their expensive computational cost for some complex problems, SIAs need to be accelerated effectively for better performance. This paper presents a high-performance general framework to accelerate SIAs (FASI). Different from the previous work which accelerates SIAs through enhancing the parallelization only, FASI considers both the memory architectures of hardware platforms and the dataflow of SIAs, and it reschedules the framework of SIAs as a converged dataflow to improve the memory access efficiency. FASI achieves higher acceleration ability by matching the algorithm framework to the hardware architectures. We also design deep optimized structures of the parallelization and convergence of FASI based on the characteristics of specific hardware platforms. We take the quantum behaved particle swarm optimization algorithm as a case to evaluate FASI. The results show that FASI improves the throughput of SIAs and provides better performance through optimizing the hardware implementations. In our experiments, FASI achieves a maximum of 290.7 Mb/s throughput which is higher than several existing systems, and FASI on FPGAs achieves a better speedup than that on GPUs and multi-core CPUs. FASI is up to 123 times and not less than 1.45 times faster in terms of optimization time on Xilinx Kintex Ultrascale xcku040 when compares to Intel Core i7-6700 CPU/NVIDIA GTX1080 GPU. Finally, we compare the differences of deploying FASI on hardware platforms and provide some guidelines for promoting the acceleration performance according to the hardware architectures.

Balancing of flexible rotors based on evolutionary algorithms

An unbalance in a rotating flexible rotor causes excessive vibration and elastic deformations with subsequent malfunction and failure. In spite of different techniques deployed to reduce or eliminate rotor unbalance, it is impossible to remove the unbalance completely. The unbalance will only be reduced to a residual level. Hence, any other method that can reduce this residual level further can be considered as an alternative. In this article, Differential Evolution (DE) and Genetic Algorithm (GA) were successfully applied as optimization techniques to balance rotating flexible rotors. The unbalancing challenge is formulated as an optimization problem with an objective function of minimizing the rotor unbalance by identifying the optimum correction parameters. Modeling and response analyses were performed in ANSYS while optimizations were conducted in MATLAB. The results of four balancing cases show that the approaches are robust at both balancing speed and beyond. Also, the results obtained show that GA performs slightly better than DE in terms of optimization time and effective reduction of vibration amplitude.

Enhanced Precision Analysis for Accuracy-Aware Bit-Width Optimization Using Affine Arithmetic

Bit-width allocation has a crucial impact on hardware efficiency and accuracy of fixed-point arithmetic circuits. This paper introduces a new accuracy-guaranteed word-length optimization approach for feed-forward fixed-point designs. This method uses affine arithmetic, which is a well-known analytical technique, for both range and precision analyses. This paper introduces an acceleration technique and two new semianalytical algorithms for precision analysis. While the first algorithm follows a progressive search strategy, the second one uses a tree-shaped search method for fractional width optimization. The algorithms offer two different time-complexity/cost efficiency tradeoffs. The first algorithm has polynomial complexity and achieves comparable results with existing heuristic approaches. The second algorithm has exponential complexity, but it achieves near-optimal results compared to the exhaustive search method. A commonly used set of case studies is used to evaluate the efficiency of the proposed techniques and algorithms in terms of optimization time and hardware cost. The first and second algorithms achieve 10.9% and 13.1% improvements in area, respectively, over uniform fractional width allocation. The proposed acceleration technique reduces the complexity of the fractional width selection problem by an average of 20.3%.

A hardware accelerator for Particle Swarm Optimization

The Particle Swarm Optimization or PSO is a heuristic based on a population of individuals, in which the candidates for a solution of the problem at hand evolve through a simulation process of a social adaptation simplified model. Combining robustness, efficiency and simplicity, PSO has gained great popularity as many successful applications are reported. The algorithm has proven to have several advantages over other algorithms that based on swarm intelligence principles. The use of PSO solving problems that involve computationally demanding functions often results in low performance. In order to accelerate the process, one can proceed with the parallelization of the algorithm and/or map it directly onto hardware. This paper presents a novel massively parallel coprocessor for PSO implemented using reconfigurable hardware. The implementation results show that the proposed architecture is up to 135× and not less than 20× faster in terms of optimization time when compared to the direct software execution of the algorithm. Both the accelerator and the processor used to run the software version are mapped into FPGA reconfigurable hardware.

Clinical experience transitioning from IMRT to VMAT for head and neck cancer

To quantify clinical differences for volumetric modulated arc therapy (VMAT) versus intensity modulated radiation therapy (IMRT) in terms of dosimetric endpoints and planning and delivery time, twenty head and neck cancer patients have been considered for VMAT using Nucletron Oncentra MasterPlan delivered via an Elekta linear accelerator. Differences in planning time between IMRT and VMAT were estimated accounting for both optimization and calculation. The average delivery time per patient was obtained retrospectively using the record and verify software. For the dosimetric comparison, all contoured organs at risk (OARs) and planning target volumes (PTVs) were evaluated. Of the 20 cases considered, 14 had VMAT plans approved. Six VMAT plans were rejected due to unacceptable dose to OARs. In terms of optimization time, there was minimal difference between the two modalities. The dose calculation time was significantly longer for VMAT, 4 minutes per 358 degree arc versus 2 minutes for an entire IMRT plan. The overall delivery time was reduced by 9.2 ± 3.9 minutes for VMAT (51.4 ± 15.6%). For the dosimetric comparison of the 14 clinically acceptable plans, there was almost no statistical difference between the VMAT and IMRT. There was also a reduction in monitor units of approximately 32% from IMRT to VMAT with both modalities demonstrating comparable quality assurance results. VMAT provides comparable coverage of target volumes while sparing OARs for the majority of head and neck cases. In cases where high dose modulation was required for OARs, a clinically acceptable plan was only achievable with IMRT. Due to the long calculation times, VMAT plans can cause delays during planning but marked improvements in delivery time reduce patient treatment times and the risk of intra-fraction motion.

Utility of Plerixafor In Addition to Chemotherapy and G-CSF Mobilization Regimens

AbstractAbstract 4443 Introduction:Various chemotherapeutic agents particularly cyclophosphamide (CY) are utilized in combination with growth factors in an attempt to increase the number of stem cells available for collection in the peripheral blood. Plerixafor (P) is a reversible antagonist of CXCR4 and interrupts its interaction with SDF-1. This results in a rapid release of hematopoietic stem cells from the marrow to the circulation. Recent pivotal phase III trial data has established the efficacy of P in combination with G-CSF (G) in patients who had failed prior attempts at stem cell collection. However, there is limited data about the utility of plerixafor in patients who are being mobilized with chemotherapy and G. Method:In this single institution study of uniformly treated patients we describe our experience with the use of P as a salvage option in patients who fail to optimally mobilize CD34+ cells (>5 × 106 CD34+ cells/kg). Patients received CY (3-4 g/m2) followed by GCSF (10 mcg/kg) from day 1 to day 10. Thirteen patients (6 NHL, 4 MM, 2 Hodgkin lymphoma, 1 Ewings sarcoma) received salvage P from 2008–2010. Their outcomes were compared with 10 matched, historic controls mobilized with (CY n=8; CY + etoposide n=1; CY + topotecan n=1) plus G-CSF (10mcg/kg/d) identified from our institutional database. Data was collected on mobilization and transplant outcomes and analyzed utilizing SPSS version 13.0. Patients receiving P were closely matched to historic controls (CY+G). Result:Both groups were similar with regards to age, gender, disease type, prior therapies and performance status (p>0.05 for all). Patients in the P arm received a median of 2.5 doses (range 1–8). The mean CD34+ count was 21.5cells/ul in the P arm and 32.5 cells/ul in the CY+G arm (p=0.2). Similarly, no significant difference was observed in the average number of apheresis sessions in the P vs. CY+G arms (4.2 vs. 4.4, p=0.8) or the total number of CD34+ stem cells collected (4.0×106/kg vs. 3.9×106/kg, p=0.9). However, 7 out of the 13 patients who received P did have an increase of >10 CD34+ cells/ul in their peripheral blood. Utilizing a cut-off of 5×106 CD34+/kg, 3 (23%) patients in the P arm and 3 (30%) patients in the CY+G arm had a successful harvest. Three NHL patients required >4 doses of P, but all eventually collected >2 × 106 CD34+ cells/kg. Neutrophil and platelet engraftment dynamics were similar in both groups of patients. Median time to neutrophil engraftment was 10 days for both groups, p=0.8, and to platelet engraftment was 22 days vs. 20.5 days, p=0.1, respectively for P vs. CY+G. Conclusion:Our limited single-center retrospective case-controlled outcomes data, suggests that when compared with CY+G, the addition of P as a salvage agent does not significantly improve mobilization outcomes. Further evaluation is needed to combine P with CY+G in terms of optimal timing and potentially dosing of chemotherapy agents utilized. We suggest that the combination P+G would provide better potential outcomes such as improved collection and less hospitalization and reduce the use of chemo-mobilization prior to an Autologous Hematopoietic Stem Cell Transplant. Disclosures:No relevant conflicts of interest to declare.

Intelligent path planning of two cooperating robots based on fuzzy logic

This paper proposes an intelligent path planning scheme for two cooperating robots (TCRs) using fuzzy logic. The proposed scheme requires knowledge of the robots' dynamics, which in turn depends upon the characteristics of the payload carried by the TCRs. However, the dynamic properties of the payload are not known exactly, so that the dynamics of the robots, and hence the required joint torque, must be calculated for nominal set of the payload characteristics. The force of the TCRs is an important factor in carrying the payload (object). It is divided into external force and internal force. In general, effects of the internal force of the TCRs are not considered in performing the load distribution in terms of optimal time, but they are essential in optimal trajectory planning; if they are not taken into consideration, the optimal scheme is no longer feasible. To alleviate this deficiency, we present an algorithm for finding the internal-force factors for the TCRs in terms of the optimal time and for constructing an optimal trajectory. The effectiveness of the proposed system is demonstrated by computer simulations using two three-joint planner robot manipulators.