Number Of Nodes Research Articles

The Learning Curve for Robotic Lateral Pelvic Lymph Node Dissection for Rectal Cancer: A View from the West.

Lateral pelvic lymph-node dissection is performed for selected patients with rectal cancer with persistent lateral nodal disease after neoadjuvant therapy. This technique has been slow to be adopted in the West due to concerns regarding technical difficulty. This is the first report on the learning curve for lateral pelvic lymph node dissection in the US or Europe. The aim of this study was to analyze the learning curve associated with robotic lateral pelvic lymph node dissection. Retrospective observational cohort. Tertiary academic cancer center. Consecutive patients from 2012 to 2021. All patients underwent robotic lateral pelvic lymph node dissection. The primary endpoints were the learning curves for maximum number of nodes retrieved and urinary retention which was evaluated with simple cumulative-sum and two-sided Bernoulli cumulative-sum charts. Fifty-four procedures were included. A single-surgeon (n = 35) and an institutional learning curve are presented in the analysis. In the single-surgeon learning curve, a turning point marking the end of a learning phase was detected at the 12th procedure for the number of retrieved nodes and at the 20th for urinary retention. In the institutional learning curve analysis, two turning points were identified at the 13th and 26th procedures indicating progressive improvements for the number of retrieved nodes and at the 27th for urinary retention. No sustained alarm signals were detected at any time point. The retrospective nature, small sample size and the referral center nature of the reporting institution that may limit generalizability. In a setting of institutional experience with robotic colorectal surgery including beyond TME resections, the learning curve for robotic lateral pelvic lymph node dissection is acceptably short. Our results demonstrate feasibility of acquisition of this technique in a controlled setting, with sufficient case volume and proctoring can optimize the learning curve. See Video Abstract.

Prevalence and quantity of lymph nodes at mediastinal stations in patients with lung cancer: lessons from 181 bilateral mediastinal lymphadenectomies

BackgroundThis study evaluated the prevalence and quantity of lymph nodes at particular stations of the mediastinum in patients with lung cancer. These data are important to radiologists, pathologists, and thoracic surgeons because they can serve as a benchmark when assessing the completeness of lymph node dissection. However, relevant data in the literature are scarce.MethodsData regarding the number of lymph nodes derived from two randomised trials of bilateral mediastinal lymph node dissection, the BML-1 and BML-2 study, were included in this analysis. Detectable nodes at particular stations of the mediastinum and the number of nodes at these stations were analysed.ResultsThe mean number of removed nodes was 28.67 (range, 4–88). Detectable lymph nodes were present at stations 2R, 4R, and 7 in 93%, 98%, and 99% of patients, respectively. Nodes were rarely present at stations 9 L (33%), and 3 (35%). The largest number of nodes was observed at stations 7 and 4R (mean, 5 nodes).ConclusionThe number of mediastinal lymph nodes in patients with lung cancer may be greater than that in healthy individuals. Lymph nodes were observed at stations 2R, 4R, and 7 in more than 90% of patients with lung cancer. The largest number of nodes was observed at stations 4R and 7. Detectable nodes were rarely observed at stations 3 and 9 L.Trial registrationISRCTN 86,637,908.

Effect of carbon nanoparticle suspension injection versus indocyanine green tracer in guiding lymph node dissection during radical gastrectomy (FUTURE-01): a randomized clinical trial.

Carbon nanoparticle suspension injection (CNSI) and indocyanine green (ICG) have both been applied intraoperatively to facilitate lymphatic mapping and postoperatively to sort lymph nodes (LNs) in gastric cancer patients. However, no study has compared the two tracers in gastric cancer patients. This prospective randomized controlled trial was conducted from January 2022 to March 2023. Patients with potentially resectable gastric cancer (cT1-4a N0/+ M0) were randomized to the CNSI or ICG group. This study enrolled 96 patients. Ninety patients were in the modified intention-to-treat population, including 46 patients (32 males and 14 females; mean [SD] age, 57.4 [9.4] years) in the CNSI group and 44 patients (31 males and 13 females; mean [SD] age, 60.8 [8.8] years) in the ICG group. The mean (SD) number of retrieved LNs was 69.8 (21.9) and 53.6 (17.2) in the CNSI and ICG groups, respectively (P<0.001). The mean (SD) number of retrieved micro-LNs was 19.9 (13.3) and 11.6 (9.9) in the CNSI and ICG groups, respectively (P=0.001). The mean (SD) number of metastatic LNs was 8.1 (11.9) and 5.2 (9.2) in the CNSI and ICG groups, respectively (P=0.19). Compared with ICG, CNSI can increase the number of LNs detected, especially micro-LNs. Both tracers have high diagnostic value for detecting metastatic LNs. CNSI-guided lymphography may be a superior method for improving the accuracy of LN dissection.

Robotic Pancreatoduodenectomy: Increasing Complexity and Decreasing Complications with Experience: Single-Center Results from 150 Consecutive Patients.

This report describes the authors' experience with 150 consecutive robotic pancreatoduodenectomies. The study enrolled 150 consecutive patients who underwent robotic pancreatoduodenectomy between 2018 and 2023. Pre- and intraoperative variables such as age, gender, indication, operation time, diagnosis, and tumor size were analyzed. The patients were divided into two groups. Group 1 comprised the first 75 patients, and group 2 comprised the last 75 cases. The median age of the patients was 62.4 years and did not differ between the two groups. Morbidity was lower in group 2. The mortality rate was 0.7% at 30 days and 1.3% at 90 days, and there was no difference between the groups. There was a significant reduction (p < 0.05) in operative time, resection time, reconstruction time, and conversion to open surgery in group 2. Partial resection of the portal vein was performed in 17 patients and more common in group 2 (p < 0.01). The number of resected lymph nodes was higher in group 2. The indication for pancreatoduodenectomy did not differ between the two groups. There was no difference in tumor size or clinical characteristics of the patients. The robotic platform is useful for pancreatoduodenectomy, facilitates adequate lymphadenectomy, and is helpful for digestive tract reconstruction after resection. Robotic pancreatoduodenectomy is safe and feasible for selected patients. It should be performed in specialized centers by surgeons experienced in open and minimally invasive pancreatic surgery.

Total RAMIE with three-field lymph node dissection by a simultaneous two-team approach using a new docking method for esophageal cancer.

Thoracic esophageal cancer surgery using robotic approaches for the thoracic and abdominal parts has recently been reported as total robot-assisted minimally invasive esophagectomy (RAMIE). We herein present the first report of a new technique for esophageal cancer: total RAMIE with three-field lymph node dissection (3FLND) by a simultaneous two-team approach using a new docking method. We reviewed 20 patients who underwent total RAMIE with 3FLND by a simultaneous two-team approach at the National Cancer Center East Hospital from March 2023 to September 2023. Short-term surgical outcomes and the safety and efficacy of this technique were analyzed. The mean operative time for abdominal surgery with this new docking technique was 135 ± 19.6min. The total operative time was 488 ± 42.9min, and the time from the end of abdominal manipulation to the end of surgery was 80.1 ± 15.6min. The intraoperative blood loss was 116.7 ± 64.4mL. The incidence of anastomotic leakage, postoperative vocal cord paralysis, and postoperative pneumonia was 10%, 5%, and 10%, respectively. The median postoperative hospital stay was 14days (range 11-63days). No in-hospital deaths occurred, and R0 resection was possible in all cases. The average number of lymph nodes dissected was 87.7. These results demonstrate that total RAMIE with a simultaneous two-team approach using the new docking method can be safely introduced. The simultaneous cervical and abdominal manipulation with the new docking method allowed total RAMIE without prolonging the operating time, suggesting that it may be a valuable approach for esophageal cancer surgery.

Robot-assisted minimally invasive oesophagectomy versus thoracoscopic approach: multi-institutional study on short-term outcomes.

Robot-assisted minimally invasive oesophagectomy and conventional minimally invasive oesophagectomy are superior to open techniques. However, few studies have directly compared the outcomes of the two minimally invasive approaches. A retrospective study of patients from six medical centres with oesophageal squamous cell carcinoma who underwent minimally invasive oesophagectomy between 2015 and 2022. Perioperative outcomes were compared after applying inverse probability of treatment weighting. The study included 577 patients (robot-assisted minimally invasive oesophagectomy: 206; conventional minimally invasive oesophagectomy: 371). After applying inverse probability of treatment weighting, robot-assisted minimally invasive oesophagectomy was found to yield a higher number of mediastinal nodes compared with conventional minimally invasive oesophagectomy (14.86 versus 12.66, P = 0.017). Robot-assisted minimally invasive oesophagectomy was notably effective in retrieving upper mediastinal left recurrent laryngeal nerve nodes, averaging 1.97 nodes versus 1.14 nodes harvested by conventional minimally invasive oesophagectomy (P < 0.001). This was coupled by a significant decrease in nerve palsy rates (13.9% versus 22.8%, P = 0.020). A significantly larger percentage of patients in the robot-assisted minimally invasive oesophagectomy group had an uncomplicated postoperative course (51.8% versus 34%, P < 0.001). Robot-assisted minimally invasive oesophagectomy also led to a reduction in pneumonia rates (8.6% versus 15.2%, P = 0.041) and was linked to a shorter length of stay (length of stay; 16.64 versus 21.14 days, P = 0.007). The advantage of robot-assisted minimally invasive oesophagectomy in reducing the length of stay was especially pronounced in patients with a high Charlson co-morbidity index (≥2, mean difference 8.46 days; P = 0.0069) and those who underwent neoadjuvant therapy (mean difference 5.63 days; P < 0.001). In oesophageal squamous cell carcinoma, the use of robot-assisted minimally invasive oesophagectomy led to fewer cases of pneumonia and faster recovery compared with conventional minimally invasive oesophagectomy. Additionally, robot-assisted minimally invasive oesophagectomy significantly improved the feasibility and safety of performing lymph node dissection along the recurrent laryngeal nerve.

Para-aortic lymph node dissection with or without nerve-sparing in gynecological malignancies.

Para-aortic lymph node dissection (PALND) is a widely used treatment that causes many complications. This study is to evaluate the efficacy and safety of nerve-sparing para-aortic lymph node dissection (NSPALND) by comparing it with conventional PALND in gynecological malignancies and to prove whether locating the superior hypogastric plexus (SHP) can help reveal the para-aortic nerves. This is a retrospective study of the patients who underwent para-aortic lymphadenectomy from January 2020 to December 2022 at Zhejiang Cancer Hospital. All of them were divided into NSPALND and PALND groups according to whether or not nerve-sparing was performed. The surgical, functional and oncological outcomes were evaluated. There were 43 patients enrolled, of which, 20 patients underwent NSPALND and 23 patients underwent PALND. The para-aortic nerves were successfully revealed by locating the SHP in all 20 cases of NSPALND. The post-operative anal exhaust time in the NSPALND group was significantly shorter than that in the PALND group (2.5 vs. 4 days, p=0.006), and the incidence of acute intestinal obstruction in the NSPALND group was significantly lower than that in the PALND group (10% vs. 39%, p=0.029). There was no difference between the two groups in terms of catheterization duration, urinary retention, dysuria, as well as the number of lymph nodes removed and the para-aortic recurrence rate. NSPALND can significantly reduce the rate of acute intestinal obstruction and improve post-operative intestinal function. Locating the SHP and using it as an anatomical landmark to reveal the para-aortic nerves is feasible. Its exact clinical value needs to be further studied.

Immunological mechanism of Ermiao Powder improving inflammation in rats with collagen-induced arthritis through α7nAChR-JAK2/STAT3 pathway

This study investigated the immunological mechanisms of Ermiao powder in the treatment of rheumatoid arthritis rats through the alpha 7 nicotinic acetylcholine receptor(α7nAChR)-Janus kinases 2(JAK2)/signal transducer and activator of transcription 3(STAT3) signaling pathway. A total of 56 female Wistar rats were randomly divided into the normal group(HG, n=8), collagen-induced arthritis(CIA) model group(CM, n=8), vagotomy group(VA, n=8), sham group(SH, n=8), Ermiao Powder treatment model group(EM, n=8), Ermiao Powder treatment for vagotomy group(EV, n=8) and Ermiao Powder treatment for sham group(ES, n=8). Following the establishment of CIA models in all groups except the HG group, the rats underwent unilateral vagotomy and sham operation(only the vagus nerve was separated). Drug treatment was started 7 days after surgery and continued for 35 days. The body weight and joints of rats were recorded, the pathological changes of the spleen of rats were observed, the contents of interleukin-6(IL-6), interleukin-1β(IL-1β) and tumor necrosis factor-α(TNF-α) in serum were detected by enzyme-linked immunosorbent assay(ELISA), and the mRNA and protein expression of α7nAChR-JAK2/STAT3 pathway core genes in spleen were detected by qRT-PCR, Western blot and immunohistochemistry. RESULTS:: showed that CM group(compared with HG group) and VA group(compared with CM group and SH group) had significantly decreased body weight(P&lt;0.05, P&lt;0.01), increased arthritis score(P&lt;0.05, P&lt;0.01), swollen ankle joints with deformity, and increased and enlarged lymph nodes in the spleen. There were also notable increases in the serum levels of IL-6, IL-1β and TNF-α(P&lt;0.05, P&lt;0.01), and in the mRNA expressions of JAK2 and STAT3 in the spleen(P&lt;0.05, P&lt;0.01). The protein levels of phosphorylated JAK2(p-JAK2)/JAK2 and phospho-STAT3(p-STAT3)/STAT3 were significantly increased(P&lt;0.05, P&lt;0.01), and the number of JAK2, p-JAK2, STAT3 and p-STAT3 cells increased(P&lt;0.05, P&lt;0.01). EM group(compared with CM group) and ES group(compared with SH group) exhibited significantly increased body weight(P&lt;0.01), decreased arthritis scores(P&lt;0.05, P&lt;0.01), reduced swelling of ankle joint, and decreased number and volume of lymph nodes in the spleen. Furthermore, serum levels of IL-6, IL-1β, and TNF-α decreased(P&lt;0.05, P&lt;0.01), the mRNA expression of JAK2 and STAT3 in spleen decreased(P&lt;0.05, P&lt;0.01), the protein levels of p-JAK2/JAK2 and p-STAT3/STAT3 decreased(P&lt;0.05, P&lt;0.01), and the number of JAK2, p-JAK2, STAT3 and p-STAT3 cells decreased(P&lt;0.05, P&lt;0.01), whereas the mRNA and protein expressions of α7nAChR were significantly increased(P&lt;0.01). Compared with the VA group, there was no significant differences in weight gain and arthritis scores in the EV group. The number of lymph nodes in the spleen was not significantly reduced and the volume was still large, suggesting the inflammation was not significantly improved. The serum levels of IL-6, IL-1β and TNF-α were not significantly different, and there were no significant differences in α7nAChR, JAK2, and STAT3 mRNA expression in the spleen. The protein expression levels of p-JAK2/JAK2 and α7nAChR in spleen were lower(P&lt;0.05, P&lt;0.01), while p-STAT3/STAT3 protein expression was not significantly different. Besides, the two groups had no significant difference in the number of JAK2, p-JAK2, STAT3, and p-STAT3 cells. The results suggested that unilateral vagotomy promoted the increase of phosphorylated JAK2 and STAT3 expressions and exacerbated inflammation. In contrast, Ermiao Powder alleviated the inflammation in rheumatoid arthritis rats by activating the α7nAChR-mediated JAK2/STAT3 pathway through the vagus nerve, suggesting that the α7nAchR-JAK2/STAT3 pathway may be a potential target for the treatment of rheumatoid arthritis.

Emergent scale-free networks.

Many complex systems-from the Internet to social, biological, and communication networks-are thought to exhibit scale-free structure. However, prevailing explanations require that networks grow over time, an assumption that fails in some real-world settings. Here, we explain how scale-free structure can emerge without growth through network self-organization. Beginning with an arbitrary network, we allow connections to detach from random nodes and then reconnect under a mixture of preferential and random attachment. While the numbers of nodes and edges remain fixed, the degree distribution evolves toward a power-law with an exponent that depends only on the proportion p of preferential (rather than random) attachment. Applying our model to several real networks, we infer p directly from data and predict the relationship between network size and degree heterogeneity. Together, these results establish how scale-free structure can arise in networks of constant size and density, with broad implications for the structure and function of complex systems.

Reinforcement learning-based charging cluster determination algorithm for optimal charger placement in wireless rechargeable sensor networks

Wireless power transfer (WPT) provides a promising technology for energy replenishment of wireless rechargeable sensor networks (WRSNs), where wireless chargers can be deployed at fixed locations for charging nodes simultaneously within their effective charging range. Optimal charger placement (OCP) for sustainable operations of WRSN with cheaper charging cost is a challenging and difficult problem due to its NP-completeness in nature. This paper proposes a novel reinforcement learning (RL) based approach for OCP, where the problem is firstly formulated as a charging cluster determination problem with a fixed clustering radius and then tackled by the reinforcement learning-based charging cluster determination (RL-CCD) algorithm. Specifically, nodes are coarsely clustered by the K-Means++ algorithm, with chargers placed at the cluster center. Meanwhile, RL is applied to explore the potential locations of the cluster centers to adjust the center locations and reduce the number of clusters, using the number of nodes in the cluster and the summation of distances between the cluster center and nodes as the reward. Moreover, an experience-strengthening mechanism is introduced to learn the current optimal charging experience. Extensive simulations show that RL-CCD significantly outperforms existing algorithms.

Stepwise reconstruction of higher-order networks from dynamics.

Higher-order networks present great promise in network modeling, analysis, and control. However, reconstructing higher-order interactions remains an open problem. A significant challenge is the exponential growth in the number of potential interactions that need to be modeled as the maximum possible node number in an interaction increases, making the reconstruction exceedingly difficult. For higher-order networks, where higher-order interactions exhibit properties of lower-order dependency and weaker or fewer higher-order connections, we develop a reconstruction scheme integrating a stepwise strategy and an optimization technique to infer higher-order networks from time series. This approach significantly reduces the potential search space for higher-order interactions. Simulation experiments on a wide range of networks and dynamical systems demonstrate the effectiveness and robustness of our method.

Safety and perioperative outcomes of uniportal versus multiportal video-assisted thoracoscopic surgery.

Uniportal video-assisted thoracoscopic surgery (U-VATS) has recently become an alternative approach for many minimally invasive thoracic procedures, but although its surgical effectiveness has been proven, still its feasibility and safety are debated and unclear. the objective of this study was to compare the safety and perioperative outcomes of U-VATS versus multiportal VATS (M-VATS). This was a comparative follow-up randomised controlled clinical trial, carried out on 36 randomly selected eligible patients, and fulfilling the inclusion and exclusion criteria for VATS, they were assigned randomly into two groups: Study Group I including 18 patients undergoing U-VATS with conventional treatment using standard chest tube drainage and Control Group II including 18 patients undergoing M-VATS) with the same conventional treatment using standard chest tube drainage and served as a comparable control group. Patients in the U-VATS Group 1 had faster operation time, and with reduced blood loss, pleural drainage and post-operative hospitalisation, they also experienced lower average post-operative pain score on comparison with those in M-VATS Group II (P < 0.001), respectively. For either group, there were no hospital deaths or infections. There was no noticeable difference between the two groups in terms of the number of resected lymph nodes or the rates of intraoperative or post-operative complications (P > 0.05). U-VATS is feasible and safe in eligible selected patients with favourable short-term perioperative outcomes (operative time, duration of pleural drainage, post-operative pain, early ambulation, duration of hospital stay as well as the risk of perioperative complications), and it can be considered the preferred approach in minimally invasive thoracic procedures that open up for the possibility of fast-track thoracic surgeries.

Lymph node metastasis burden identifies head and neck squamous cell carcinoma patients benefiting from adjuvant chemoradiation: a propensity score-matching

IntroductionTo examine the influence of adjuvant chemoradiation therapy (CRT) on survival, stratified by varying numbers and level involved of metastatic lymph nodes in patients with head and neck squamous cell carcinoma (HNSCC). MethodsPatients who underwent surgery for metastatic, negative margin HNSCC without extranodal extension were retrospectively enrolled and divided into two groups based on adjuvant therapy received: radiotherapy (RT) and CRT. The impact of RT versus CRT, stratified by the number of positive lymph nodes and the level involved, on Disease-Free Survival (DFS) and Overall Survival (OS) was analyzed. ResultsFollowing propensity score matching, a total of 580 patients were included. The burden and level of lymph node metastasis were independent predictors of poorer survival. Among patients with no more than two positive lymph nodes or involvement of levels I-III, the addition of chemotherapy to RT did not demonstrate a significant improvement in prognosis. However, in patients with three or more positive lymph nodes, CRT showed improved DFS and OS compared to RT. In patients with involvement of levels IV-V, the addition of chemotherapy to RT resulted in a significant 24% reduction in the risk of recurrence and a 20% decrease in the risk of death. ConclusionIncorporation of adjuvant chemoradiation can lead to a favorable prognosis in patients with metastatic HNSCC. This impact was notable in cases where there were three or more positive lymph nodes or involvement of levels IV-V.

Landscape design of urban culture transmission based on the regional information security of Internet of Things

In the context of the rapid development of Internet of Things technology, urban cultural communication and information security have become a new focus in the field of landscape design. This paper innovatively discusses the landscape design of urban cultural communication based on Internet of Things regional information security, aiming at building a safe and culturally rich urban landscape environment. Taking the unique regional culture of Zhangjiajie as an example, this study evaluated the cultural communication effect of landscape design under information security guarantee through in-depth case analysis and field investigation, combined with Internet of Things information security technology. The results show that the cluster head node strategy has significant advantages in resisting physical capture attacks, especially when the number of sensor nodes captured is less than 2000, the information loss rate is less than 0.1. This discovery not only improves the level of information security in the Internet of Things environment, but also provides technical support for the effective dissemination of urban culture. In addition, through the detailed analysis and evaluation of landscape, this study further reveals the important role of landscape design in regional cultural inheritance. To sum up, this study not only provides a new perspective for urban landscape design, but also provides practical guidance for the protection and dissemination of urban culture in the era of Internet of Things.

Stability prediction of roadway surrounding rock using INGO-RF

In order to more accurately classify the stability of roadway surrounding rock and identify dangerous areas in a timely manner to prevent roadway collapse and other disasters, an INGO-RF roadway surrounding rock stability prediction model is proposed. This model combines the improved Northern Gok algorithm (INGO) and Random Forest (RF) based on the analysis of influencing factors of roadway surrounding rock stability. First, three strategies were employed to enhance the Northern Gob algorithm (NGO): Logistic chaotic mapping, refraction reverse learning, and improved sine and cosine. Subsequently, INGO was utilized to optimize the number of decision trees and the minimum number of leaf nodes for RF species in order to improve the prediction accuracy of RF. Secondly, a data set consisting of 34 groups of roadway surrounding rock data is selected. The input indexes of the model include roof strength, two-wall strength, floor strength, burial depth, roadway pillar width, ratio of direct roof thickness to mining height, and surrounding rock integrity. Meanwhile, surrounding rock stability is considered as the output index. Particle swarm optimization backpropagation neural network (PSO-BPNN), genetic algorithm optimization support vector machine (GA-SVM), Sparrow search algorithm optimization RF (SSA-RF) models were introduced to compare the prediction results with the INGO-RF model, and the results showed that: INGO-RF model has the best performance in the comparison of various performance indicators. Compared with other models, the accuracy rate (Ac) in the test set has increased by 0.12∼0.4, the accuracy rate (Pr) has increased by 0.07∼0.65, and the recall rate (Re) has increased by 0.08∼0.37. The harmonic mean (F1-Score) of the recall rate increased by 0.08∼0.52, the mean absolute error (MAE) decreased by 0.1428∼0.4285, the mean absolute percentage error (MAPE) decreased by 7.15%∼28.57%, and the root mean square error (RMSE) decreased by 0.1565∼0.3779. Finally, the data on surrounding rock conditions of roadways in multiple mining areas in Shanxi Province were collected to test the INGO-RF model. The results indicate that the predicted outcomes closely align with the actual results, demonstrating a certain level of reliability and stability. It shows that it can better meet the practical needs of engineering and avoid the occurrence of mine disasters.

Spontaneous recovery in random hypergraphs.

In many real-world phenomena, such as the reconstruction of disaster areas after an earthquake or the stock market's recovery after an economic crisis, damaged networks are spontaneously active after receiving assistance. To reveal how the recovery process, the research of dynamic network recovery has become a hot topic in the field of network science. Previous studies on network recovery have been limited to simple networks with pairwise interactions. However, real-world systems are usually networks with higher-order interactions that are composed of multiple units. To better understand the recovery phenomenon on complex networks in the real world, we propose a novel spontaneous recovery model applied to hypergraphs. The model considers two types of recovery, internal recovery and fast recovery, where inactive nodes in the network can either recover internally with independent probabilities or receive sufficient resources from the hyperedge for fast recovery. We find that the number of active nodes in the system shows a phase change from continuous to discontinuous as the fast recovery condition is relaxed. Moreover, under the influence of higher-order interactions, increasing both average hyperedge cardinality and network heterogeneity contribute to increasing the network resilience. These findings help us understand the recovery mechanisms of complex networks and provide essential insights into designing highly resilient systems.

Firefly Interval Selection Combined With Extreme Learning Machine for Spectral Quantification of Complex Samples

ABSTRACTFirefly algorithm (FA) combined with extreme learning machine (ELM) is developed for spectral interval selection and quantitative analysis of complex samples. The method firstly segments the spectra into a certain number of intervals. Vectors with 1 and 0, which represent the interval selected or not, are used as the inputs of the FA. The RMSEP value predicted by ELM model is used as the fitness function of the FA. The activation function and number of hidden layer nodes of ELM, number of spectral intervals, population number, environmental absorbance, and constant of FA are optimized. The predictive performance of FA‐ELM is compared with full‐spectrum PLS, ELM, genetic algorithm‐ELM (GA‐ELM), and particle swarm optimization‐ELM (PSO‐ELM) by one ultraviolet (UV) spectrum dataset of gasoil and three near‐infrared (NIR) spectral datasets of corn, wheat, and tablet samples. The results show that FA‐ELM has a better performance compared with its competitors in predicting monoaromatics, water, wheat kernel texture, and active pharmaceutical ingredients (APIs) in gasoil, corn, wheat, and tablet samples.

Inferring Phylogenetic Networks from Multifurcating Trees via Cherry Picking and Machine Learning

The Hybridization problem asks to reconcile a set of conflicting phylogenetic trees into a single phylogenetic network with the smallest possible number of reticulation nodes. This problem is computationally hard and previous solutions are restricted to small and/or severely restricted data sets, for example, a set of binary trees with the same taxon set or only two non-binary trees with non-equal taxon sets. Building on our previous work on binary trees, we present FHyNCH, the first algorithmic framework to heuristically solve the Hybridization problem for large sets of multifurcating trees whose sets of taxa may differ. Our heuristics combine the cherry-picking technique, recently proposed to solve the same problem for binary trees, with two carefully designed machine-learning models. We demonstrate that our methods are practical and produce qualitatively good solutions through experiments on both synthetic and real data sets.

3D network-on-chip data acquisition system mapping based on reinforcement learning and improved attention mechanism

The three-dimensional Network-on-Chip (NoC) data acquisition system is designed to create a time-interleaved data acquisition system using NoC technology. In the design of NoC application systems, optimizing the mapping algorithm can effectively reduce network communication latency. Aiming at the mapping challenge of a large number of functional IP nodes in 3D NoC data acquisition system, the reinforcement learning and improved attention mechanism mapping algorithm (RA-Map) is proposed. The RA-Map mapping algorithm employs node function encoding and node position encoding to express the properties of an IP node in the task graph preprocessing. The local attention mechanism is used in the mapping network encoder, and the fusion of dynamic key node information is proposed in the decoder. The mapping result evaluation network achieves unsupervised training of the mapping network. These targeted improvements improve the quality of the mapping. Experimental results show that the RA-Map mapping algorithm can effectively model the IP core mapping. Compared with the DPSO algorithm and SA algorithm, the average communication cost of RA-Map mapping algorithm is reduced by 6.5 % and 8.5 %, respectively.

Acceleration of particle-in-cell simulations using sparse grid algorithms. II. Application to partially magnetized low temperature plasmas

In Paper I [Garrigues et al., Phys. Plasmas 31, 073907 (2024)], we have extended the sparse PIC approach already used in the literature with the offset scheme to reduce the grid-based error. In this study, we demonstrate the ability of the offset sparse PIC algorithm to model partially magnetized low-temperature plasmas by reducing the grid-based error. In the context of multi-cusp magnetic field configurations, the offset scheme reduces the error of the current collected at the walls to less than 5% for more of the plasma conditions encountered in ion source applications. The formation of a double layer in the sheath region is also captured. In the context of the electron drift instability that occurs in the Hall thruster, the plasma properties as well as the ion velocity distribution function can be retrieved with a high enough precision without considering an initial regular grid with a smaller mesh resolution. The results also highlight the advantage of combining the electric potential at the nodes of the regular grid instead of directly combining the electric field from the component grids. Compared to the regular PIC algorithm, the typical speed-up factor is about three for a number of mesh nodes of 2562 and five for 5122.