Tumour depth of invasion is a well-known histological risk factor in oral cavity squamous cell carcinoma. With the advent of the eighth edition of the American Joint Committee on Cancer in 2017, a consensus has been established on the point from which to measure the depth of tumour invasion. All of this has led to changes in the T category of the TNM classification, leading to an increase in staging and possible adjustments in the management of adjuvant treatments. The main objective of this research is to assess the prognosis, according to the depth of invasion in patients with clinical early stages of oral tongue squamous cell carcinoma, to evaluate the influence of the depth of invasion in the latest TNM classification as well as in the global staging system, and to analyse its relation to other histological risk factors.p values below 0.05. Results: Sixty-one patients were included. The average follow-up time was 47.42 months. Fifteen patients presented a loco-regional relapse (24.59%) and five developed distant disease (8.19%). Twelve patients died (19.67%). Statistically significant differences were observed, with respect to disease-free survival (p = 0.043), but not with respect to overall survival (p = 0.139). A total of 49.1% of the sample upstaged their T category and 29.5% underwent modifications of their global stage. The analysis of the relationship between DOI with other histological variables showed a significant association with the presence of pathological cervical nodes (p = 0.012), perineural invasion (p = 0.004) and tumour differentiation grade (p = 0.034). Multivariate analysis showed association between depth of invasion and perineural invasion. Conclusions: Depth of invasion is a histological risk factor in early clinical stages of oral tongue squamous cell carcinoma. Depth of invasion impacts negatively on patient prognosis, is capable per se of modifying the T category and the global tumour staging, and is associated with the presence of cervical metastatic disease, perineural invasion and tumoural differentiation grade.Background: The American Joint Committee on Cancer (AJCC), in its 8th edition, introduces modifications to the previous TNM classification, incorporating tumour depth of invasion (DOI). The aim of this research is to analyse the prognosis  of clinical early stage (I and II) squamous cell carcinomas of the oral tongue according to the DOI levels established by the AJCC in its latest TNM classification to assess changes to the T category and global staging system and to evaluate the association between DOI and other histological risk factors. Methods: A retrospective longitudinal observational study of a series of cases was designed. All patients were treated with upfront surgery at our institution between 2010 and 2019. The variables of interest were defined and classified into four groups: demographic, clinical, histological and evolutive control. Univariate and multivariate analyses were carried out and survival functions were calculated using the Kaplan–Meier method. Statistical significance was established for  Lip and oral cavity carcinomas account for 2% of the incidence and 1.8% of cancer mortality worldwide .The initial clinical stages (I and II) of SCC of the tongue are represented by those tumours classified as T1 or T2 and N0. In the treatment of this disease, there is a large consensus that the tumour should be extensively excised with wide margins  while thTumour depth of invasion is a widely documented and reported histological risk factor in oral cavity carcinomas, so the deeper a tumour is, the more likely it is that the disease will spread to the lymph nodes in the neck region ,16,17,18The American Joint Committee on Cancer (AJCC), in its eighth edition and subsequent update, introduces modifications with respect to the previous TNM classification, based on the scientific evidence described in the literature ,20. EsseThe starting point of the research project is based on tumour depth of invasion.The working hypothesis is as follows: “Depth of invasion, divided into 3 groups according to the 8th edition AJCC classification, worsens the prognosis of patients with initial clinical stages of oral tongue squamous cell carcinoma”.The main aim is to determine the prognosis of early stages (I and II) oral tongue SCC according to DOI levels established by the AJCC in its latest TNM classification.Secondary objectives are to analyse the clinical-pathological discrepancy of the T category according to DOI, to describe how DOI influences changes in tumoural staging system within the 7th and 8th editions of the AJCC and to assess the association between DOI and the presence of other pathological risk factors such as positive cervical lymph nodes, perineural invasion (PNI), lymphovascular invasion and tumoural differentiation grade.A retrospective longitudinal observational study of a series of cases was designed, with the population of people who attended the Oral and Maxillofacial Surgery Department of the Gregorio Marañón University Hospital, as the framework for analysis. This research study is endorsed by the ethics committee of the institution. The time period of this study was between January 2010 and December 2019. The variables of interest were defined by grouping them into 4 groups: demographic, clinical, histological and evolutive control. Information on these variables is collected from the archives of the surgical reports of the Oral and Maxillofacial Surgery Department, the clinical patients files and the archives of histological samples of the hospital’s Pathology Department.-Patients had initial clinical stages of oral tongue SCC  according to the eighth edition of the AJCC.-Patients had undergone surgery at the Oral and Maxillofacial Surgery Department of the Gregorio Marañón University Hospital.-Patients’ surgical procedures consisted of extensive tumour removal and elective neck dissection.-The tumour margins of the surgical resection were negative.-Patients were over the age of 18.Patients who were enrolled in this study had to meet all of the following inclusion criteria:-Disease that extended beyond the anterior two thirds of the tongue, therefore affecting the oropharynx.-Patients, in whose medical records, variables of interest were not identified.-Patients who were previously treated for carcinoma of the oral cavity .To be included in the research, NONE of the following criteria could be met:After establishing the inclusion and exclusion criteria and reviewing the radiological tests and histological data, a final sample size of 61 patients was obtained .2) and Fisher’s exact test. To analyse the influence of the histopathological marker DOI on overall survival, disease-free survival and recurrences (measured from the date of surgery to the occurrence of events), survival analyses were performed using Kaplan–Meier (KM) survival functions, as well as the graphical representation of the KM curves. The difference between pathological T stages according to DOI was determined using the log-rank test of the curves. In the analytical statistical phase, we worked with a two-tailed type-1 error, establishing statistical significance for p-values lower than 0.05. Statistical analysis was performed with SPSS software version 25.0.A descriptive analysis of the different variables grouped into demographic, clinical, histological and evolutive control was performed. The results were presented as the frequency and percentage of each analysis group for qualitative variables and as mean ± standard deviation of the mean for quantitative variables. Normality distribution analysis was performed using the Kolmogorov–Smirnov test. The analysis of frequency distribution between the different groups of interest was carried out using chi-squared (χn = 61).In general , the proFrom a clinical point of view , it is nAll but one of the patients were studied with Computed Tomography scan (CT scan) and only in the 23% of them a Magnetic Resonance (MR) was obtained, which is probably related to the celerity with which CT scan versus MR is acquired. Interestingly, the radiological size of the tumour could not be assessed in approximately 39% due to the presence of amalgams and dental artefacts or the superficiality of certain tumours.Almost half of the patients were reconstructed in a simple way with direct closure. Whether unilateral or bilateral neck dissection was performed depended on the location of the tumour. More than half of the sample underwent adjuvant radiotherapy and only two patients were treated with chemotherapy.A total of 72% of patients had a moderate tumour differentiation grade, with PNI present in 40% of the sample and lymphovascular invasion in only five patients . About 3A relevant fact is the difference in the T category between the pathological T in the seventh and eighth editions of the AJCC. As can be seen in In the histological neck variable, there is no N2a category in the seventh edition as there were no patients with lymph nodes between 3 and 6 cm in size. However, one patient was included in this category in the eighth edition because he had a pathological lymph node with extracapsular involvement (ENE+) and a size of less than 3 cm. The pN3b category is also not represented in the seventh edition, while two patients can be included in the eighth edition because they have more than one positive cervical lymph node with at least one of them having ENE.In the staging variable according to the seventh edition, there are no categories of IVb and IVc, as there were no patients with N3 or metastatic disease (M1). However, according to the eighth edition, category IVb is included as there were two pN3b patients.It is worth noting  that loc-n = 17): DOI ≤ 5 mm.Subgroup pT1 according to DOI (-n = 24): DOI between 5 and 10 mm.Subgroup pT2 according to DOI (-n = 20): DOI > 10 mm.Subgroup pT3 according to DOI  and the different categories of the following clinical variables : clinicaConcerning tumour size, about 50% of the tumours categorised as T2 became pT3 when DOI was analysed, while this percentage was only about 15% in the T1 category. Overall, about 50% of patients increased their pT when considering DOI, highlighting its importance for correctly classifying the T category.Regarding the type of elective neck dissection, of the 28 patients who received bilateral lymphadenectomy, 82% were clinically T2, and it is remarkable that 60% of the patients who received a bilateral dissection were classified into the pT3 group, while only 9% of those who underwent unilateral lymphadenectomy were designated to this same subgroup.A total of 50% of the patients reconstructed with direct closure were subclassified in the pT1 group while 72% of microsurgical techniques were employed in pT3 patients.It is very relevant that 62% of the patients who received postoperative radiotherapy (PORT) were pT3 while about 44% of those who were not irradiated were classified as pT1.When analysing histological variables , statistAbout 66% of the well-differentiated lesions were observed in the pT1 subgroup, while the vast majority of moderately (77%) and poorly (100%) differentiated carcinomas were associated with the pT2 and pT3 subgroups, suggesting that the more undifferentiated tumours were associated with a depth greater than 5 mm.Out of the 40% of patients with perineural invasion, more than 50% were associated with pT3 tumours, showing that the higher the DOI, the more likely it is to be associated with PNI.A total of 50% of pT1 patients by tumour size were also pT1 by DOI, while more than half of the patients with a pT2 neoplasm by size were upstaged to pT3 when DOI was measured. Thus, there is a considerable increase in the T category when DOI is measured (50% in pT1 and about 54% in pT2 measured by size).When analysing the overall pathological T according to the 7th and 8th editions of the AJCC, it can be seen that according to the 7th edition (only measured by size), there would be three patients (5%) with pT3 tumours; whereas, when taking into account the 8th edition (measured by size and DOI), a total of 21 patients would be reclassified as pT3.Approximately one third of the sample analysed had lymph node metastases. Of the 21 patients with positive necks, 14% corresponded to the pT1 subgroup and 57% to pT3, with a higher probability of lymph node involvement associated with deeper tumours. Four patients developed diseases in both side of the necks and three of them were in the pT3 subgroup (DOI > 10 mm).When the staging systems of the seventh and eighth editions of the AJCC are evaluated, it can be appreciated that in the early stages I and II (T1N0 and T2N0), DOI is very relevant. The percentages of patients in stages I and II, according to the seventh edition, are 41% and 24%, respectively, while in the eighth edition, they are 21% and 31%. The decrease in patients in pT1 and the increase in pT2 can only be explained by tumoural DOI, as the neck is negative (pN0) in both stages. There are three patients with ENE, which implies that, according to the 8th edition, they should be classified as pN2a and pN3 and, therefore, upgrade to stage Iva (one patient) and Ivb (two patients). According to the 7th edition, no patient would be stage IV as it does not consider ENE as a staging criterion.Concerning the analysis of the evolutive follow-up variables , no signDespite the marked differences in total recurrence between groups pT1 and pT3, statistical significance was not found. This is probably related to the limited sample size. In terms of mortality, half of the deaths occurred in the pT3 group.p = 0.039).The regression used for the multivariate analysis of all variables that were significant revealed a crucial association between the DOI and PNI . Among these thirty-two people, two were downgraded to T1 and thirty were upgraded to either T2 or T3. In summary, 30 patients (49.2%) in the sample increased their T category as outlined in When analysing the discrepancy between clinical tumour size  and pathological T according to DOI, a total of thirty-four patients (55.73%) changed their “T” category, of which thirty where upstaged and four downstaged . Considering the overall TNM classification for the T category (size and DOI) of the eighth edition of the AJCC, finally, 32 patients modified their “T” category , which means that, although there are possible changes in the T category caused by DOI, these may not be reflected in the final staging due to the N category. For example, a patient with a 4 mm DOI lesion (pT1) and a positive lymph node (N1) would have the same tumour stage as another with a 12 mm DOI lesion (pT3) and a positive lymph node (N1). Both lesions would be stage III.p = 0.012) between the presence of positive lymph nodes and the subgroups of pathological T according to DOI, such that the deeper the tumour (pT3 group), the greater the probability of presenting neck disease. The analysis of the results reveals that there are significant differences (p = 0.004) such that patients with tumours (pT1) have a significantly lower incidence of PNI than those with more invasive lesions (pT3).The relation of PNI to pathological T according to DOI  shows stp = 0.334). This is probably due to the fact that only five patients presented this histological risk factor.The analysis of results of the relation between lymphovascular infiltration and pathological T according to DOI divided by subgroups does not reach statistical significance (p = 0.034) between both variables in such a way that there are few patients with well-differentiated tumours in the pT3 subgroup and no patients with a poor differentiated tumour in the pT1 subgroup. Most of the tumours were moderately differentiated.The results of the analysis of the relation between the tumour differentiation grade (DG) and pathological T according to DOI  divided The treatment options for patients with early stages of oral cavity squamous cell carcinoma  are focused on the management of the primary tumour and the N0 neck. For the primary neoplasm, the two treatment options are surgery (extensive tumour resection and immediate reconstruction) ,22,23,24Depth of invasion, as a histological risk factor, has been extensively studied in different tumours of the organism such as melanoma, breast cancer or cervical carcinoma . Moore, Until recently, there was no clear consensus on how to measure DOI. Some authors measure it according to the structures that infiltrate the tumour in depth ,33, otheWith the advent of the latest AJCC classification ,20, critAmong all the parameters that conform the TNM classification, the maximum surface diameter of tumours  is the most controversial of all for several reasons : tumour The inclusion of DOI and the modification of the variable “primary tumour or T” in the TNM classification overcomes a part of this problem by providing value to the fact that a deep tumour can be more aggressive than a superficial lesion regardless of its size in the mucosa. The starting point of this research is the definition of DOI and its grouping into three subcategories, according to the latest AJCC classification, in such a way that those neoplasms with a tumour infiltration of less than or equal to 5 mm are considered pT1, those between 5 and 10 mm are pT2 and those with a tumour infiltration larger than 10 mm are grouped in pT3. Therefore, DOI, per se, can modify the T category of the TNM classification of oral cavity SCC.The main aim of this study is to analyse the prognosis in terms of disease-free survival and overall survival of patients with early clinical stages  of SCC of the oral tongue, according to the depth of tumour invasion indicated by the TNM classification of the eighth edition of the AJCC. Ebrahimi et al.  conducteThe sample analysed in our research reveals a significant association of the three DOI categories (grouped according to the AJCC 8th edition TNM classification) and disease-free survival, but not with overall survival. The fact that overall survival is not influenced by DOI is probably due to the sample size.In terms of changes in the T category and global staging, when comparing the seventh and eighth editions of the AJCC, different papers report modifications in the T category, ranging from 32.5% to 50%, and in global staging, ranging from 30% to 37% ,44,45,46The association of DOI with the presence of positive neck nodes is widely described in the scientific literature. ,16,17,18PNI is the capability of certain tumour cells to invade nerve structures present in the same or nearby tissue where the carcinoma proliferates. It constitutes a pathway for tumour dissemination since the nerve provides a route for the spread of the neoplasm. Some authors ,53 evaluLymphovascular infiltration is defined as the presence of tumour cells in the walls or lumen of blood or lymphatic vessels in the tissue where the primary tumour is located. There are papers ,57 that The histological differentiation grade of a tumour refers to the similarity between the tumour cells and those of the invaded tissue. Broders  classifiThe main strength of this research is the homogeneity of the sample and the accuracy of the statistical analysis, and its major limitation is that it is retrospective, losing the benefits of prospective monitoring and significantly limiting the control over possible sources of bias.p < 0.05) disease free survival but not overall survival. In addition, DOI is related to other risk factors such as positive lymph nodes, perineural invasion and tumour differentiation grade.Depth of invasion is a histological risk factor in patients diagnosed at early stages of squamous cell carcinoma of the oral cavity. The development of deeper tumours, taking into account the measures specified in the eighth edition of the AJCC, clearly worsens (With regard to tumour staging, it has been found that DOI has a strong influence on the “T” category of the TNM classification but not on the overall staging of the disease, which tends to equalise between the seventh and eighth editions of the AJCC due to the N category.For all of the previous considerations, it is advisable to always keep in mind the depth of invasion as one of the histological risk factors to be evaluated in order to decide on the best adjuvant treatment for patients, as well as to determine the time intervals for their evolutionary follow-up.


The Pearl River Estuary (PRE), China, where riverine and marine factors alternate in strength and weakness, is one of the most important fishing grounds in the South China Sea. The spatial–temporal distribution of fish larvae directly affects the stock density in the area. This study revealed the relationship between fish larvae and marine environmental factors in the PRE, through multisensor satellite remote sensing and fishing surveys, based on the Habitat Suitability Index (HSI) model. The spatial–temporal distribution of fish larvae has unique distribution characteristics under different seasons and has high consistency with the changes of monsoon and flow field, etc. The findings of this study can help researchers gain a good understanding of the movement of fish larvae in the PRE and promote better habitat conservation under a changing climate.The spawning grounds are important areas for the survival and reproduction of aquatic organisms and play an important role in the replenishment of fishery resources. The density of fish larvae in the Pearl River Estuary (PRE) was analyzed to establish Habitat Suitability Index (HSI) based on marine environmental factors. Survey data and satellite remote sensing data, including sea surface temperature, sea surface salinity and chlorophyll a concentration, from 2014 to 2017 during April–September were analyzed. Results showed that the accuracy of the HSI model based on the larval density and environmental factors was more than 60%, and the distribution trend of HSI was consistent with the distribution trend of larval density. The HSI models constructed based on Arithmetic Mean Model (AMM), Geometric Mean Model (GMM) and Minimum Model (MINM) methods can better predict the spatial–temporal distribution of larvae in the PRE. Among them, the accuracy of the HSI model constructed by the AMM and GMM methods was the highest in April (71%) and September (93%); the accuracy of the HSI model constructed by the MINM method was the highest in June (70%), July (84%) and August (64%). In general, the areas with high HSI values are mainly distributed in the offshore waters of the PRE. The spatial–temporal distribution of larvae in the PRE was influenced by monsoon, Pearl River runoff, Guangdong coastal currents and the invasion of high-salinity seawater from the outer sea. The Pearl River Estuary (PRE) is a subtropical, high productive estuary in the northern South China Sea (SCS). The Pearl River is the largest river in southern China. It is an important fishery production base and a gene bank of aquatic biological resources, with more than 380 species of fish . The runThunnus obesus in the Indian Ocean [Sthenoteuthis oualaniensis and sea surface temperature, sea surface height anomalies in the SCS [Larimichthys polyactis and environmental factors in Haizhou Bay [The Habitat Suitability Index (HSI) can be used to simulate the response of organisms to environmental conditions. The model has the advantages of a straightforward evaluation approach, clear expression of species’ optimal environmental circumstances and being easy to understand ,22. It ian Ocean , the rel the SCS  and the zhou Bay . Previouzhou Bay ,30,31. TIn this study, the spatial and temporal distribution of larvae in the PRE was analyzed based on the HSI model, and the effects of environmental changes on the distribution of larvae were analyzed to predict the location and abundance of larvae in the PRE. The findings of the study will help to clarify the status of fishery resources replenishment in the area and provide scientific reference for the restoration and conservation of offshore spawning grounds in the SCS.−3; N is the number of larvae, in ind and V is the volume of filtered water, in (10 m)−3.The larval data were obtained from surveys of spawning grounds in the PRE conducted between 2014 and 2018 . The research area was at 113–115° E, 21–23° N . The samhttp://oceancolor.gsfc.nasa.gov; accessed on: 20 May 2021) with a temporal resolution of 1 day and a spatial resolution of 4 km. SSS data were from the Global Ocean Physical Reanalysis Product of the Copernicus Marine Environment Management Service  with a temporal resolution of 1 month and a spatial resolution of 1/12°. R v.4.0.0  software was used to eliminate invalid values, month-by-month average, and data fuse for SST, SSS and Chl-a. ArcGIS 10.3  was used to map the geographically overlaid distribution of environmental parameters and larval density [Satellite data include sea surface temperature (SST), sea surface salinity (SSS) and sea surface chlorophyll a concentration (Chl-a). SST and Chl-a data were obtained from MODIS Aqua products  models were established using the larval density with SST, SSS and Chl-a, respectively. In this study, the area with the highest density of larvae is assumed to be the most suitable area for larvae, with an HSI of 1. The area with no larval density is unsuitable for larvae, with an HSI of 0. Among them, 80% of the larval density data were used to develop the model via random sampling, and the remaining 20% of the data were used for model validation. The single-factor habitat index SI was calculated as :(2)SIi=YThe relationship between SI and SST and SSS and Chl-a was modeled by the simple nonlinear regression . The equHSI was calculated based on the single-factor SI using Maximum Model (MAXM), Minimum Model (MINM), Arithmetic Mean Model (AMM) and Geometric Mean Model (GMM), respectively, with the following equations ,39:(4)HSThe remaining 20% of investigation data were taken into each of the 4 equations for validation. The forecast was considered accurate if the error between theoretical value and actual value was less than 0.4, otherwise, the forecast is considered inaccurate . ArcGIS p < 0.05) indicated that each model was accurate.The SI for each environmental factor and larval density were obtained for different months , based oThe three factors SST, SSS and Chl-a were fitted separately, and the actual values of larval density were plotted against the fitted results . ResultsFor SST, the optimum SST for April larvae was 23.2 °C, for June larvae was 29.6 °C, for July larvae was 29.0 °C, for August larvae was 29.2 °C and for September larvae was 28.7 °C , Table 2For SSS, the optimum SSS for April larvae was 29.0, for June larvae was 30.2, for July larvae was 27.9, for August larvae was 29.6 and for September larvae was 24.4 , Table 23, for June larvae was 1.9 mg/m3, for July larvae was 4.1 mg/m3, for August larvae was 3.7 mg/m3 and for September larvae was 2.4 mg/m3 , and the MAXM and MINM methods had the lowest accuracy (57%). In June, the MINM method had the highest accuracy rate (70%), and the MAXM method had the lowest accuracy rate (41%). In July, the MINM method had the highest accuracy rate (84%), and the MAXM method had the lowest accuracy rate (46%). In August, the MINM method had the highest accuracy (64%), and the AMM, GMM and MAXM methods had the lowest accuracy (36%). In September, the AMM and GMM methods had the highest accuracy (93%), and the MAXM method had the lowest accuracy (60%).−3) and a higher HSI (>0.8) predicted for this area based on the AMM and GMM methods. In the offshore waters of the PRE , the larval density was low (0–10 ind(10 m)−3). The HSI in this area predicted by AMM and GMM was also low (<0.2), and the predicted results were consistent with the actual values. The results predicted by MAXM overestimated the low-value area of larval density, which was inconsistent with the actual situation. MINM did not identify the high-value area on the east side of the PRE, and the predicted results were slightly worse than those of AMM and GMM. In June, the MINM predictions were the most accurate, the spatial distribution predicted by AMM was more similar to the actual distribution of larval density, and both GMM and MINM predictions gave a conservative estimate of larval density, resulting in some high-value areas not being detected. MAXM accurately predicted the high-value area of larval density, but it also overestimated areas of low larval density as well, which was not consistent with the actual situation. In July, the spatial distributions predicted by AMM, GMM and MINM were similar and consistent with the actual larval density distribution. Higher-density areas  had higher HSIs (>0.8) predicted by the three models, and lower-density areas had lower HSIs. In August, the predicted HSI distribution based on AMM, GMM and MINM was consistent with the actual distribution trends of larval density. Among them, the predicted results of AMM were more optimistic and those of MINM were more conservative. The predicted results of MAXM were too optimistic and did not match the actual situation. In September, predicted results of AMM, GMM, MAXM and MINM showed similar trends. The HSI results obtained from AMM, GMM and MINM for the near-shore waters on the west side of the PRE  were higher (>0.8), and the density of larvae was relatively high (>20 ind(10 m)−3) at most survey stations in this area, and the predicted results were consistent with the actual values. However, the MAXM prediction made a higher estimate for the waters within the PRE, which was not consistent with the actual situation.The spatial–temporal distributions of HSI and larval density in the PRE indicated that the predicted results of the HSI model were similar to the actual larval density distribution trends . In ApriMAXM, MINM, AMM and GMM are widely used in the construction of the HSI model ,39. The −3. From June to September, larvae in the PRE were mainly distributed in the waters with SST of 28–30 °C, and the suitable SST for larvae was 28.7–29.6 °C according to the SI model, and the density of juvenile fish was 0–700 ind(10 m)−3 (Water temperature plays a key role in fish maturation and egg development . Seasona(10 m)−3 . High vaSalinity is considered to be the key factor controlling the distribution and composition of estuarine fish . Due to 3, and the optimum Chl-a for larvae in April, June, July, August and September was 2–4 mg/m3 based on the SI model. The higher Chl-a area did not result in a high distribution of larva density (Chl-a reflects the amount of phytoplankton in the area and is the primary food supply for zooplankton and some marine creatures ,50. Ther density , partly The ecological environment of the PRE is complex and variable. Studies showed that the monsoons in the PRE played the most important role in the surface shape and extension of the plume ,56. The In this study, the HSI model for the distribution of larvae in the PRE was constructed and the larvae habitat was predicted, based on satellite remote sensing and in situ observations. In June–August, the model constructed by MINM has the highest accuracy. In April and September, the model constructed by AMM and GMM has the highest accuracy. The interaction effects between environmental factors and the importance of the influencing factors will be considered, and the impact of daily environmental changes in the PRE on larvae will be discussed in future research, with a view to provide a more accurate scientific reference for the assessment and prediction of fishery resources in the PRE.


From the start of the pandemic, several aspects of healthcare policies changed, not least the clinical trials management from recruiting capabilities to the protocol compliance in terms of schedule of procedures, follow-up visits, staff constraints and monitoring. This study aims to assess the impact of the COronaVIrusDisease-2019 (COVID-19) pandemic in the conduction of clinical trials at the site of clinical oncology, Ancona , to identify the strengths and weaknesses upfront the past emergency, and to select better strategies for future similar situations.Data from February to July of the years 2019, 2020 and 2021 were collected and three practical parameters of the trial unit were investigated: milestones, performance, and impact.The trials mean numbers were 18, 24, and 23, in 2019, 2020, and 2021 respectively. The pre-Site Initiation Visit (PRE-SIV) rate grew from 66.6% in 2019 to 95.5% in 2021 with a deflection in 2020. Protocol deviations were 40 in the period February-July 2019, in the same period of 2020 the number of deviations increased due to COVID related ones, then there was a significant total decrease in February-July 2021. In 2020 and 2021, all the investigator meetings were online.The growing number of remote Site Initiation Visit (SIV) and meetings over the last 3 years suggests the feasibility of the on-line processes. The significant reduction in protocol deviations during 2021 is probably due to an under check of data during a pandemic. But that is also a possible key indicator of the coping strategy made out by clinical oncology to guarantee the continuity of care in clinical trials and to offer new opportunities of cancer care in a bad scenario such as a pandemic one. Clinical trials are the highest contribution to improve knowledge and progress in various settings of medicine. In addition, they add great opportunities for cancer care offering new treatments and benefiting from advances in scientific research .COronaVIrusDisease-2019 (COVID-19) globally spread from February 2020, becoming pandemic and leading to a new scenario with the reorganization of medical assistance and medical research too  have drawn up guidelines in order to reorganize clinical trials and to respect the standards of good clinical practice , 12.The main national and international scientific societies, as the Italian Association of Medical Oncology (AIOM), the European Society for Medical Oncology (ESMO) and the American Society of Clinical Oncology (ASCO) contributed to the draft of the guidelines –15.Guidelines address aspects of clinical trial management, such as protocol modification, communications with the institutional review board/ethics committee, investigational product distribution, remote site monitoring, informed consent process and the importance of maintaining data integrity and the audit trail .The aims of this study were to evaluate the impact of the COVID-19 pandemic in the interventional clinical trials at the clinical oncology of the University Hospital of Marche, in Ancona  and to identify the strengths and the weaknesses adopted upfront the past emergency.All data concerning interventional and active trials (profit and non-profit) were collected, from phase I to phase III, conducted from February to July of the years 2019, 2020 and 2021.The following areas were identified:(1).Milestones.(2).Performance.(3).Impact.The milestones data included:(1).Number of recruiting trial.(2).Number of pre-Site initiation visit (PRE-SIV), Site Initiation Visit (SIV), Close Out Visit (COV) of the site.(3).Monitoring visit.(4).Investigator meeting.(5).First patient in/last.For each trial, the following information was collected:(1).State of the trial (active/suspended/closed).(2).Protocol acronym, sponsor and phase.(3).Setting of disease.(4).Setting of population.(5).Treatment arms.(6).PRE-SIV date.(7).SIV date.(8).Monitoring visit date and number.(9).COV date.(10).Investigator’s meeting date and number.(11).List of patients enrolled in each trial with the date of screening, eligibility of the patient (enrolled or screening failure), status of the patient in relation to the treatment of the study .The performance key indicators included:(1).Enrollment rate in active trials.(2).Compliance with the schedule visits.(3).Patient safety based on the number of protocol deviations. A protocol deviation is any change from the study design under the investigator’s control and not approved by the ethics board. While, COVID-19 related protocol deviation is a protocol deviation due to the pandemic impact on the organization, management, patient safety or other.The source documents used to collect all the above information were:(1).Follow-up letters of the monitoring visits sent to the site by the contract research associate (CRA).(2).Annual report (follow up form) sent to the ethics committee by the site for each trial.(3).Case report form (CRF).(4).Paper medical records.(5).Protocols and patients database.(6).Software human including work agenda and visit planning.About the semesters of the three considered years, the following data related to the trial enrollment status were taken into consideration:(1).Enrollment suspended: study temporarily interrupted and then restarted.(2).Enrollment withdrawn: study permanently suspended and not restarted.(3).Enrollment terminated: study concluded for the achievement of target/study objective.All data was collected and processed with the Microsoft Excel program (version 2019 16.0.6742.2048).All interventional recruiting studies in the considered periods were included.The average number of interventional recruiting studies was 18 studies in 2019, 24 in 2020 and 23 in 2021. The maximum number of recruiting studies was 21 in July 2019, 28 in February of 2020 and to 25 in July of 2021.Table 1 and In the 2019 the rate of PRE-SIV remotely conducted were 66.6%, while 33.3% were on site, in the 2020 the rate of remote were 89.5% remotely and 10.5% on site, in the 2021 almost all the PRE-SIV were conducted remotely (Table 1 and In the 2019 the rate of SIV remotely performed was one (7.7%), while 12 (92.3%) were on site, in the 2020 half of them were on site and half were remote, in the 2021, the rate of remote were 6 (42.8%), the remnant 8 (57.2%) were on site (Table 1).In 2019 all the monitoring visits carried out were on site (83). In the 2020 the rate of monitoring visits remotely conducted were 60.3% (35), while 39.7% (23) on site, in the 2021 the rate remotely was 30.9% (21) remotely and 69.1% (47) on site (Table 1).In March and April 2019, the monitoring visits were on site for a total number of 12 and 16 respectively, in March and April 2020 were all remotely and 8 and 6, respectively (Table 1 and In the 2019 the rate of investigator meetings remotely conducted were 17 (81%) and 4 (19%) were on site, in the 2020 and in the 2021 all investigator meetings were remote (14 and 23 respectively) .In the considered period during 2019, the enrolled patients were 13, in 2020, they were 38 and in 2021, the total was 27 (Table 2 and In July 2019 there was the maximum number of patient visits (63 visits each months), while during 2020 the maximum number was in February and April (57 visits each months), in 2021 it was during March (51 visits each months) .In 2020, the active studies were 24, whereas the suspended trials were eleven and terminated trials were 6. In the 2021, the active trials were 23, while there was no suspended trial and the terminated ones were 6 (The pandemic has a global impact on cancer care and clinical trials have been one of the most affected areas .Results of a systematic review by Sathian et al.  showed hLooking at the data, it’s evident how the pandemic led to a modification of study site selection and to the conduction of clinical trials, also. A major limitation of this study stands in the comparison of data from 2019 to 2021, not considering useful previous data due to an internal reorganization during 2018.The number of PRE-SIVs shows an increase rate over time despite the pandemic, but the performance has changed. In fact, the percentage of PRE-SIV remotely conducted grew from 66.6% in 2019 to 95.5% in 2021.In the meanwhile, there was a clear reduction in the number of SIVs during 2020 compared to 2019 and 2021. This decrease occurred during March and April 2020. Literature data confirmed similar results in other countries in which 85% of the trial sites postpone SIV during pandemic .The number of remote SIV growth over the last 3 years from 7.8% to 42.8%, suggesting the feasibility of the telematics process. Literature data confirms that over 70% of sites organized SIV and monitoring visits on-line, reducing on site visits for sponsors and promoting easier approval process and improving the cost effectiveness of clinical trials .In 2020, the participating investigator meetings were less than those conducted in 2019, and in the 2020 and 2021 the meetings were 100% remotely, bringing a huge change.Despite the reduction in milestones in 2020 due to the suspended trials, data showed that COVID-19 has brought a new work modality at site. In fact, Webex became a reality at work in 2020, they were confirmed in 2021 and they are still in use now.According to literature data, after a sharp early decline, the enrollment of new participants and ongoing study visits recovered during the COVID-19 pandemic. This recovery was accompanied by the increased use of electronic tools and new approaches such as remote visits and telemedicine .So, even if there were a reduction in the number of PRE-SIV, SIV, monitoring visits, the fewer of those have been carried out with a new modality taking advantage of the technologies.Regulators issued guidance published on statistical mitigation approaches, while sponsors applied telemedicine and remote patients to avoid limited data gaps and protocol deviations .An important number of deviations due to the pandemic were highlighted in Ancona. These findings are consistent with other studies conducted in other countries in which about 50–60% of the protocol deviations were COVID-19 related .Interestingly, in 2021 the protocol deviations were fewer, but this was probably due to the reduction of monitoring visits, and because the source data checks were not carried out properly. But a probable improvement of trial performance was also due to the site capabilities of coping with pandemic impact, even if there were a high number of active trials.Performance items showed an increase in patient enrollment in 2020 compared to 2019. This finding is site specific and justifiable by the fact that during 2019, there were more PRE-SIV and SIV leading to the opportunity of a high number of active studies in 2020, while in 2021 there are fewer enrolled patients due to the reduction of PRE-SIV and SIV during 2020.ClinicalTrials.gov, only 14% of institutions continued with active enrollment during the pandemic and the oncology clinic in Ancona was one of those. There was an increase in enrollment during 2020, despite the restrictions related to the pandemic and becoming one of the clinical sites that have been able to face pandemic maintaining the performance [By the analysis of the contract research organization IQVIA and by the interrogation of formance .In conclusion, during the pandemic the oncology clinic was able to guarantee the continuity of care of clinical trials patients and to offer new experimental opportunities carrying out the prevention of SARS-CoV2 infections.


The burgeoning complexity of space missions has amplified the research focus on robots that are capable of assisting astronauts in accomplishing tasks within space stations. Nevertheless, these robots grapple with substantial mobility challenges in a weightless environment. This study proposed an omnidirectional continuous movement method for a dual-arm robot, inspired by the movement patterns of astronauts within space stations. On the basis of determining the configuration of the dual-arm robot, the kinematics and dynamics model of the robot during contact and flight phases were established. Thereafter, several constraints are determined, including obstacle constraints, prohibited contact area constraints, and performance constraints. An optimization algorithm based on the artificial bee colony algorithm was proposed to optimize the trunk motion law, contact point positions between the manipulators and the inner wall, as well as the driving torques. Through the real-time control of the two manipulators, the robot is capable of achieving omnidirectional continuous movement across various inner walls with complex structures while maintaining optimal comprehensive performance. Simulation results demonstrate the correctness of this method. The method proposed in this paper provides a theoretical basis for the application of mobile robots within space stations. As human space exploration continues to advance, space robots capable of performing various operational tasks within a space station have emerged as a significant field of research ,2. MobilNumerous researchers have investigated ground mobile robots, focusing on common mobility modes such as wheel-type ,5,6,7, tNumerous space robots are equipped with two manipulators to complete a variety of operational tasks ,24. For Researchers continue to explore the use of robots within space stations. However, achieving continuous movement in a weightless environment remains a formidable challenge. Moreover, the complex structure of the space station’s inner walls and the high-performance demands placed on the robots further complicate the analysis. This paper introduces an omnidirectional continuous movement method and has the following key contributions.(1)The paper proposes a movement method for a dual-arm robot that simulates the way astronauts use their arms to interact with the inner walls for locomotion. This approach allows the robot to transition between different inner walls. The two manipulators function as both operational and mobile systems, reducing the structural complexity;(2)Based on the kinematic and dynamic models of the dual-arm robot in both contact and flight phases, this study proposes not only the contact points between manipulators and the inner wall, but also the trunk movement law and the driving torques, as optimization variables. It aids in enhancing the robot’s overall performance;(3)This research presents multiple constraints, including obstacle constraints, prohibited contact area constraints, and performance constraints. To improve optimization efficiency under these constraints, an optimization algorithm based on the artificial bee colony algorithm (OA-ABC) is introduced.The findings of this study provide a theoretical foundation for the practical application of robots within space stations.The remainder of the paper is structured as follows. In a space station, traditional movement modes, such as wheel-type and leg-type, are not applicable due to the low friction and complex surface structures of the inner wall. Astronauts often achieve efficient movement by using the reaction force between their arms or legs and the inner wall, thereby offering inspiration for the efficient movement of robots in a space station. As a solution, this paper proposes a dual-arm space robot, with each manipulator having six degrees of freedom (DOFs) and the capability to complete collaborative tasks. The robot can move through the interaction between the manipulators and the inner wall, as seen in The research objectives of this paper are as follows.(1)The robot should achieve omnidirectional continuous movement in a space station using the manipulators. This means it should not have to stop and adjust its posture after each motion cycle ;(2)The robot should be capable of moving along an expected trajectory in a complex environment with obstacles, steps, and prohibited contact areas;(3)The robot should possess superior comprehensive performance, including excellent dynamic stability, low energy consumption, and smooth motion laws.F1F2 represents the trunk of the robot. O1O2 and O2O3 depict the potential trajectories of the trunk during the contact phase . These trajectories may be straight lines or curves. O2 is the ideal nearest point, but it may change according to actual circumstances. The coordinate origin of the fixed coordinate system O0–X0Y0Z0 coincides with the projection point of O2. The directions of the coordinate axes are demonstrated in pO–pYpZpX coincides with the geometric center of the trunk. The coordinate system of the i-th joint is denoted as iO–iYiZiX. The contact points P1 and P2 between the two manipulators and the space station’s inner wall may not be in the same plane, assuming P1 and P2 are fixed in a fixed coordinate system. Moreover, there may be obstacles on the inner wall. When the two manipulators of the robot detach from the inner walls of the space station, the robot enters the flight phase.O1O2 and O2O3 can be formulated ast1 and t2 represent the times in the r-th phases of approaching the inner wall (O1O2 phase) and moving away from the inner wall (O2O3 phase), respectively. asr, bsr, and csr represent the polynomial coefficients. os1 represents the coordinate of the point O1, which is a known value. os2 represents the coordinate of the point O2. While os2 is on the trajectory O1O2, its position remains uncertain. It can be expressed as a function of position change Δosy2, which is the distance between the ideal closest point and the actual closest point in the Y0 direction. The function can be written asFirstly, the kinematics of the robot is analyzed. The trajectory equations for O2O3 is variable and lies on the line between the optimized point O2 and the predetermined position point O1 for the subsequent cycle. By optimizing the polynomial coefficients and the position of os2, the trajectory of the robot’s trunk can be determined. The velocity of the trunk can be obtained by deriving Equation (1).The trajectory asr, bsr, and csr not being independent. The known value Usr can be expressed asOP1 is the position of the trunk at point O1. v1, v2 and v3 are the velocities of the trunk at point O1, O2 and O3, respectively. By incorporating the aforementioned known values as boundary conditions into the position and velocity equations, the polynomial coefficients bsr and csr can be expressed as functions of as2 and Δosy2.Given that the robot needs to meet the expected movement, some values are known during the robot’s continuous movement, which results in aΘ, bΘ, and cΘ represent the polynomial coefficients that can be determined through optimization in the r-th phases (O1O2 phase or O2O3 phase).  is the initial posture of the trunk. The angular velocity of the trunk can be obtained by deriving Equation (4).The change in the trunk posture can be expressed asaΘ, bΘ, and cΘ in Equation (4) are not independent. The known value UrΘ can be expressed as1 and Θ2 are the postures of the trunk at points O1 and O2, respectively. O1, O2, and O3, respectively. By introducing the known values as boundary conditions into the posture and angular velocity equations, the variables only consist of axΘ2, ayΘ2, and azΘ2.Similarly, due to the presence of boundary conditions, the polynomial coefficients pO–pYpZpX relative to the fixed coordinate system can be expressed asi-th coordinate system relative to (i − 1)-th coordinate system. The kinematics modeling of each manipulator involves six unknown joint angles iθ , which can be determined once the position and posture of the trunk are known. The joint angles, angular velocities, and angular accelerations can be formulated asTp refers to the trunk parameters, including the position, velocity (angular velocity), and acceleration (angular acceleration) of the trunk. Pi represents the position of the contact points between the manipulators and the inner wall.Moreover, the kinematics modeling of the manipulators is established based on the analysis of the trunk parameters. The homogeneous transformation matrix of the trunk coordinate system i − 1)-th link relative to the i-th link, and The angular velocity and angular acceleration of the link can be expressed asi-th moving coordinate system for the j-th manipulator and the acceleration i-th link can be expressed asi-th coordinate system relative to the origin of the (i − 1)-th coordinate system, and i-th link in the i-th coordinate system. i-th coordinate system, which can be written asi-th link in the i-th coordinate system. Following this, the Newton–Euler method can be employed to calculate the mutual forces and torques between the links and the joint driving torques. For the i-th link, the equation can be written asi − 1)-th link to the i-th link in the i-th coordinate system, respectively. The manipulators possess a total of 12 DOFs and require 12 drives for the two manipulators. When two manipulators come into contact with the inner wall simultaneously, the trunk has 6 DOFs, resulting in redundant actuation. The robot has 11 components, with a total of 66 equations and 72 unknowns. Optimization is necessary to find the optimal solution. To simplify the calculation, three joints for each manipulator are selected, and the driving torque variation is modeled as a polynomial.Mira, Mirb, and Mirc are the polynomial coefficients in the r-th phase. By optimizing these coefficients, the driving torques of three selected joints for each manipulator can be obtained, and the driving torques of other joints can be obtained by solving Equation (12).The acceleration O3, the posture of the trunk at point O1 in the next cycle, and the duration of the flight phase. The duration lkt can be expressed asOvk3 represents the velocity of the robot when it is at point O3 in the k-th cycle, and Ok3 and point Ok+1)1(. The angular velocity of the trunk can be written asOk3 in the previous cycle and the posture vector Ok+1)11The continuous movement of a robot is governed by various constraints, including obstacle constraints, prohibited contact area constraints, and performance constraints.qsd between capsules, while the minimum distance qD between capsules and each plane of the cuboid is calculated to identify potential collisions with obstacles. The minimum distances qsd and qD should meet the following conditions:qr and sr are the radii of the capsules, and Δd is the safe distance.Obstacle constraints: The two manipulators may not only collide with obstacles, but may also readily collide with each other, leading to joint–joint, joint–link, and link–link collisions. Collision detection is executed by simplifying the joints and links of the robot into capsules and obstacles into cuboids, followed by calculating the minimum distance between them. The self-collision detection is performed by calculating the minimum distance (2)Prohibited contact area constraints: Within the space station, certain regions of the inner wall may be vulnerable and require protection from potential damage caused by contact with the robot. Therefore, it is necessary to avoid contact with such areas, which can be expressed asAkxS and AkyS represent the length and width of a rectangular prohibited contact area, respectively, and Ar is the radius of the circular contact surface at the end of the manipulator.(3)Performance constraints: The performance indices of the robot include motion feasibility, zero moment point (ZMP), total inertia moment, and energy consumption.O1O2 and O2O3 of the trunk should lie within the workspace when two manipulators come into contact with the inner wall. These constraints can be expressed astP represents the set of discrete points of the position of the center of mass of the trunk, and tC denotes the workspace.Motion feasibility: The motion feasibility constraint involves two aspects: firstly, the rotation angles of the joints of both manipulators and the trunk should be within the predefined ranges; secondly, the trajectories i-th link. P1P2. The distance can be expressed asA, B, and C are the coefficients of the linear equation.ZMP. To ensure the motion stability of the robot, ZMP is introduced as a performance index. When the gravity acceleration is not considered, ZMP can be expressed asi-th link of the j-th manipulator and the trunk, respectively. i-th link of the j-th manipulator and the trunk in the fixed coordinate system, respectively. 0MIt are the inertia moments. The total inertia moment should be constrained from three aspects: mean, variance, and the total inertia moment at the moment of detachment from the inner wall. The mean value should also be within a reasonable range and not too large. It can be expressed asmean(GM) represents the mean of the total inertia moment and Total inertia moment. The robot may exhibit large velocities and acceleration during continuous movement. Moreover, due to the frequent changes in the motion direction of the robot and its zero velocity at the point closest to the inner wall, the amplitude of velocity and acceleration can be substantial. This can result in significant changes in inertia torque. Excessive inertia torque and large amplitude can make the dynamic performance of the robot challenging to control. Therefore, changes in total inertia moment should stay within a reasonable range. The total inertia moment can be expressed asijP denotes the instantaneous power of the i-th joint of the j-th leg, Energy consumption. Energy consumption is another critical performance index for robots operating in a space station, where energy resources are limited. Therefore, it is essential to minimize energy consumption. The total energy consumption can be expressed as(1)sa2 in Equation (1), polynomial coefficients Θax2, Θay2, and Θaz2 in Equation (4), and Δosy2 in Equation (2). Furthermore, the optimization variables also include the motion time t1 and t2 of the robot in the O1O2 and O2O3 phases.Trunk movement law: Given the trajectory is not unique and the posture is not constant, the optimization variables include polynomial coefficient (2)P1 =  and P2 =  of the two contact points are also optimized.Contact points: The coordinates (3)Mpa, Mpb, and Mpc in Equation (13), which represent the driving torques, are also considered optimization parameters.Driving torques: The polynomial coefficients The optimization variables primarily consist of the trunk movement law, the contact points between manipulators and the inner wall, and the driving torques. G1 and G2 symbolize the mean and variance of the discrete points corresponding to ZMPd. G3 and G4 represent the variance of the discrete points corresponding to the total inertia moment and the total inertia moment at the moment of detachment from the inner wall, respectively. G5 represents the energy consumption of the robot. nq is the weight coefficient. For the driving torques, the main optimization objective is energy consumption, represented by G5 in Equation (27).The optimization objective function for the continuous movement of the robot can be expressed asIn the continuous movement process, a multitude of optimization parameters are involved. To enhance the optimization efficiency, an optimization algorithm based on an artificial bee colony algorithm is proposed, and the optimization flowchart is shown in Z0 =  and the initial constraint range FQ =  for the objective functions. Values from Z0 are randomly selected to ascertain if the initial dataset has been filtered. If it has not, the values of each objective function are calculated. During this calculation process, the precision and efficiency of the inverse kinematics of the manipulator are linked to the given initial values. The ranges of the two contact points are divided into equidistant grids. When the trunk of the robot is at point O1, the joint angles of the two manipulators, which correspond to the end of the manipulators at each grid point, are calculated. This process establishes the initial joint angle dataset, JD. To solve inverse kinematics, joint angles corresponding to the coordinates of the contact points closest to the target contact points can be selected from the dataset as the initial values. This significantly enhances the efficiency of the solving process. After solving the inverse kinematics, the constraint yQ is assessed to determine whether it is satisfied. If yQ is not met, the value is re-evaluated from Z0, and the inverse kinematics is re-solved. If yQ is satisfied, each objective function value and its corresponding argument parameters are stored. Subsequently, high-quality data are selected from the initial values to form the optimized initial value dataset YD, after which 0Z and FQ are updated.The optimization process begins by defining the initial range of optimization parameters YD is then input into the artificial bee colony algorithm cB for further optimization. In the three stages of leading bee, following bee, and investigating bee, the solved objective function values are evaluated against the objective function range constraint FQ. If FQ is not met, the corresponding date set is discarded. If FQ is satisfied, it is updated, and the optimization process continues. At each generation of the artificial bee colony algorithm, the minimum multi-objective function value iG is compared with the current optimal solution iG is superior to SR, SR is not met, the optimization process continues; otherwise, the current optimal solution is regarded as the global optimal solution. This optimization method can also be applied to optimize the driving torques.The filtered dataset To demonstrate the effectiveness of the proposed method, an example is presented. The structural parameters of two identical manipulators are shown in O1 during the four cycles are , ,  and , respectively. The given parameters are shown in vi1, vi2, and vi3 are the velocities of the trunk at points Ok1, Ok2, and Ok3, respectively, while Ok1 and Ok2, respectively. Moreover, ωk1 and ωk2 are the angular velocity of the trunk at points Ok1 and Ok2. For the given constraints, Δd in Equation (19) is 0.15 m, while qr = sr = 0.30 m. AkxS and AkzS in Equation (20) are 1.25 m and 2.48 m, respectively, and Ar is 200 mm. The rotation angle range for the four joints at jA, jB, jC, and jF is . The rotation angle range for the two joints at D1 and E2 and the rotation angle range for the two joints at D2 and E1 are  and , respectively. Moreover, the range of posture angles of the trunk around both the X0-axis and Y0-axis in a fixed coordinate system is , while the range around the Z0-axis is . The range for the mean of the total inertia moment is . For the OA-ABC, the number of honey sources, as well as the leading bees and following bees, is 100, with the maximum number of iterations being 100. The expansion coefficient for the honey source search range is 1. The threshold value for the leading bee to become an investigating bee is set at 55. The range of the two contact points are {, } and {, }, respectively. The above range is divided into a 71 × 151 grid, with each unit being 10 mm. The machine spec used is as follows: the CPU model is EPYC 7742, with 64 physical cores and 128 GB of RAM (Random Access Memory). Based on the method proposed in this paper, the optimization results of motion parameters are shown in Suppose the space station model is a cuboid with dimensions of 32.5 m × 23.7 m × 18.6 m, and the fixed coordinate system of the robot during its first cycle as a reference. As depicted in The motion trajectory of the center of mass of the robot’s trunk in the space station is shown in iA, iB, iC, and iF is , the maximum angle range for the two joints at D1 and E2 is , and the maximum angle range for the two joints at D2 and E1 is . The rotation angles remain within the permissible range. During the flight phase, as shown in The variations in the joint angles of the two manipulators are shown in X0, Y0, and Z0 axes are 9.58°, 7.00°, and 22.26°, respectively. If the robot’s trunk posture remains unchanged, it results in a significant increase in the calculated mean and variance of ZMPd, the variance of the total inertia moment and the total inertia moment at the moment of detachment from the inner wall, and the energy consumption of the robot, thereby leading to a decrease in overall performance.The variations in the angle and angular velocity of the trunk are presented in ZMPd is shown in ZMPd fluctuates within a minimal range, reaching maximum values of 0.43, 0.42, 0.40, and 0 during the four cycles, respectively. Notably, the sudden variation in ZMPd during the transition from the O1O2 phase to the O2O3 phase can be attributed to the change in acceleration direction, but this does not compromise the robot’s dynamic stability. By controlling the trajectory and posture of the trunk, ZMPd remains at zero during the fourth cycle. The change in total inertia moment is shown in O1O2 phase to the O2O3 phase due to the high acceleration when the direction of movement changes. The mean values of the total inertia moment for the four cycles are 33.22 Nm, 33.97 Nm, 50.70 Nm, and 16.47 Nm, respectively, while the variances are 331.45 Nm, 407.66 Nm, 238.43 Nm, and 10.78 Nm, all within small ranges. At the moment of detachment from the inner wall, the total inertia moments are 12.29 Nm,13.84 Nm, and 28.40 Nm, which are close to zero. These results demonstrate that the robot possesses good dynamic stability. The changes in energy consumption are shown in The change in X0-axis and Z0-axis, respectively. The positions of the centers of the three rectangles in the moving coordinate system for the third cycle are , , and . Without considering the prohibited contact areas, the optimized positions of the two contact points are  and , respectively. However, these contact points fall within the prohibited contact areas. Thus, the contact position is optimized twice, resulting in new contact points at  and , respectively. Analysis shows that the modified contact point positions have not significantly impacted the overall performance of the robot.The results from the above analysis demonstrate that the method proposed in this paper enables the robot to achieve continuous movement among the various complex inner walls of the space station while maintaining good comprehensive performance. This provides a theoretical basis for the control of robots within a space station.To further substantiate the feasibility of the method proposed in this paper, a simulation is conducted. Software Webots is employed to simulate the examples discussed in −3 m/s and 0 m/s, respectively. Moreover, the ratio of the maximum difference to the maximum motion velocity of the robot is merely 0.01. The motion process of the robot within the space station is shown in The aforementioned analysis indicates that the simulation results of the robot align closely with the theoretical calculation results, supporting the feasibility of the method proposed in this paper.The strengths of the algorithm proposed in this paper are primarily evident in the following areas.(1)Traditional artificial bee colony algorithms randomly select honey sources within the range of independent variables. For our algorithm, we create an initial dataset prior to optimization. This means that the randomly obtained honey sources are screened based on the values of each objective function, leading to enhanced computational efficiency;(2)The range of contact points between the manipulators and the inner wall is meshed, and a joint angle dataset is established. Using the joint angles corresponding to the mesh points closest to the actual contact points as the initial values effectively addresses the problem of low efficiency in solving the inverse kinematics of the manipulators;(3)A single objective function range constraint is introduced in the three stages of leading bee, following bee, and investigating bee. This strategy allows for the elimination of some solutions that evidently do not meet the requirements even before calculating and comparing the normalized multi-objective function values;(4)Throughout the optimization process, the range of independent variables in the initial dataset and the constraint range of each objective function are dynamically updated to improve the convergence speed of the algorithm.To further underscore the superiority of OA-ABC introduced in this paper, we compare it with the traditional artificial bee colony algorithm (ABC) and the genetic algorithm (GA) ,46,47. FThe comparison of the omnidirectional mobile robot proposed in this paper with existing space mobile robots is shown in In order to facilitate efficient robot movement within a space station, this paper proposed an omnidirectional continuous movement method for a dual-arm robot. This method emulates the way astronauts use the reaction forces from their hands or feet and the inner walls to move around. (1) After determining the configuration of the robot’s two manipulators, mathematical models for both the contact and flight phases were established. These models clarified the relationship between motion parameters and dynamic performance, underscoring the significance of the robot’s motion mode in achieving continuous movement. (2) Several constraints were proposed, including obstacle constraints, prohibited contact area constraints, and performance constraints. After determining the optimization parameters, an optimization algorithm based on the artificial bee colony algorithm (OA-ABC) was proposed to enhance computational efficiency through the stepwise screening of variables and objective function values. (3) An example was provided of a robot achieving omnidirectional continuous movement within a space station model measuring 32.5 m × 23.7 m × 18.6 m. The robot achieves continuous movement between different inner walls over more than three cycles, covering a total distance of 60.32 m. During the flight phase, the maximum rotation angle and angular velocity of the robot’s trunk were 189° and 0.23 rad/s, respectively. In long-distance movement, the error between the theoretically calculated results and the simulation results fell within a reasonable range, and the robot demonstrated good comprehensive performance. These findings validate the feasibility of the method proposed in this paper. The method proposed in this paper provides a theoretical reference for controlling the motion of robots in a space station.


Based on the change in the color of the solution and the formation of a precipitate, the occurrence of thermal-oxidative degradation of the MEA solution with the formation of destruction products, including insoluble ones, was confirmed. The electrokinetic activity of the resulting degradation products, including insoluble ones, was studied during the electrodialysis purification of an aged MEA solution. To understand the influence of degradation products on the ion-exchange membrane properties, a package of samples of MK-40 and MA-41 ion-exchange membranes was exposed to a degraded MEA solution for 6 months. A comparison of the efficiency of the electrodialysis treatment of a model absorption solution of MEA before and after long-time contact with degraded MEA showed that the depth of desalination was reduced by 34%, while the magnitude of the current in the ED apparatus was reduced by 25%. For the first time, the regeneration of ion-exchange membranes from MEA degradation products was carried out, which made it possible to restore the depth of desalting in the ED process by 90%.The thermal-oxidative degradation of aqueous solutions of carbonized monoethanolamine (MEA, 30% wt., 0.25 mol MEA/mol CO One of 2 .2 to form carbamate according to In the absorber, MEA reacts with COHowever, in some cases, MEA-carbamate by the cyclization reaction  forms oxazalidone .On the other side, MEA-carbamate can react with MEA to form N,N′-di(hydroxyethyl)urea .In turn, 2-hydroxyzolidone can also react with MEA to form 1-(2-hydroxyethyl)-2-imidazolidone (HEIA) according to the reaction .HEIA, as a result of the hydrolysis reaction, can form N-(2-hydroxy)-ethylenediamine (HEEDA) .These four substances  and their further degradation products, including MEA dimers, trimers, and tetramers, as well as their cyclization, polymerization, and oxidation products, constitute the main group of degradation products ,7. The e2 [2 emissions of 49 kg/s), the loss of absorbent (30% MEA solution) will be 120 tons per year of operation, which is about 10% from the initial content of MEA in solution. As a result, technologies aimed at removing degradation products of alkanolamines are relevant. The main technologies are ion exchange, thermal distillation, and electrodialysis [The contribution of HSS to the total losses of MEA during the absorption–desorption cycle can reach 80 g of a 30% MEA solution per ton of absorbed COdialysis ,14. Membdialysis ,18,19,202)/mol (MEA) −25.9 MJ/kg (absorbent), taking into account the energy consumption for additional desorption solution. The efficiency of the HSS isolation process using electrodialysis can be increased by adding an equimolar alkali. For the first time, the scheme with the introduction of a neutralization unit was proposed by the ElectroSep company, which currently presents it on the market for alkanolamine purification technologies under the ElectroSep® brand. In [In recent years, researchers have been interested in approaches to optimizing the process of HSS electrodialysis recovery from the point of view of reducing alkanolamine losses and reducing energy costs. Thus, a two-stage scheme for the electrodialysis isolation of TSS was proposed in order to reduce the losses of the amine. This approach makes it possible to reduce MEA losses by 30% . In the rand. In , devotedrand. In  also shorand. In , it was rand. In ,25 proporand. In ,27. Howerand. In , there iAnother problem characteristic of the electromembrane desalination technology is the degradation of the surface material of ion-exchange membranes. One of the main reasons for the electrochemical degradation of an anion-exchange polymer is the nucleophilic attack of quaternary amines by hydroxyl ions , which aAn analysis of the literature data on these processes indicates that the separation capacity of ion-exchange membranes (productivity and selectivity) depends on the conditions of the electrodialysis process and the impact of various degradation products of amines on them. In this regard, the purpose of this work was an experimental study of the process of thermal degradation of MEA solutions and the effect of the products of this process on the separating properties of ion-exchange membranes (performance and selectivity) on the efficiency of their electrodialysis purification. The aim of this study was to assess the prospects for the electrodialysis process from the point of view of the performance of cation- and anion-exchange membranes under conditions of prolonged contact with a working solution containing MEA thermal-oxidative degradation products. Moreover, in this work, for the first time, an approach to the regeneration of ion-exchange membranes during electrodialysis was experimentally tested.2-loading.For the preparation of model absorbent solution, the following chemicals were used: monoethanolamine , carbone dioxide , formic acid , gladical acetic acid , oxalic acid dehydrated , nitric acid , sulfuric acid , distilled water. A 30% wt. solution of MEA in water was prepared gravimetrically; then, carbon dioxide was introduced to achieve the required COIon-exchange membranes MA-41 and MK-40  have the characteristics presented in The aging of the carbonized MEA solutions was carried out using a sealed stainless steel vessel (5 L). The vessel, half-filled with a solution of carbonized MEA, was placed in a thermostat, and exposure was carried out for 336 h (two weeks) at 120 °C. Sampling from a vessel (preliminarily cooled to room temperature) to assess the degree of degradation of the MEA solution was carried out after 7, 13, 45, 75, 155, 215, and 336 h using the spectrophotometer PE-5400UF . The measurements were carried out in a wide range of wavelengths: from 200 to 1000 nm. After filtering the solution through a UFFK-1 microfilter , the color was eliminated, and the sediment content was 20 g/L.To ensure the identity of the resulting aged solution in real conditions of the carbonization process (and it takes place in the presence of oxygen contained in the flue gas), before experiments with ion-exchange membranes, MEA oxidation products were added to the filtered solution—thermostable salts (TSS) of such acids as, mg/L: formic 800, oxalic 330, acetic 70, nitrogen 460, sulfuric 670, and hydrochloric 70.First of all, ion-exchange membranes were kept in distilled water for 24 h. Then, the membranes were placed in a degraded MEA solution (336 h) and kept in continuous contact with it for 6 months (4392 h). The choice of a solution corresponding to 336 h of degradation is determined by the degree of its degradation . Such a solution makes it possible to clearly demonstrate the effect of soluble degradation products on the transfer of ions through membranes during electrodialysis purification.2/mol MEA using fresh MK-40 and MA-41 membranes and the same membranes after 6 months of contact with a pre-degraded MEA solution. The flow scheme of the electrodialysis lab set-up is represented in 2 was equipped with commercial cation-exchange membranes MK-40 and anion-exchange membranes MA-41 . The alternation of membranes led to the formation of 10 circulated desalting cells and 9 flowing concentrating cells. Both electrodes were made of platinized titanium. The rinse of electrode compartments was 30% wt. of MEA in water. Model MEA solution was poured into container V1 in the amount of 1 l and into the containers of anolyte (V2) and catholyte (V3). The concentrate tank (V4) was filled with distilled water, which made it possible to create the maximum difference in the electrical conductivity of the solution in the desalination and concentration chambers. This technique led to the intensification of the process of electrodialysis isolation of the target components. Pumps P1-P4 provided continuous circulation of liquid in the hydraulic paths at a given speed. The average linear velocity of solutions in the sections of the electrodialyzer was 0.35 cm/s (Re ≈ 10). Electrodialysis was carried out in the controlled potential mode at 30 V voltage. The DC Power Supply HY5005E-2  power supply unit supplies the electrodialyzer with direct current. The current flowing through the machine was detected by a DC source. The intensity of the electrodialysis process was estimated from the change in the electrical conductivity of the diluate solution and its temperature .To assess the electrokinetic activity of MEA degradation products, a comparison was made of the electrodialysis treatment of a model 30% wt. carbonized aqueous MEA solution with a residual carbon dioxide content of 0.2 mol COQs, kJ/g(HSS)) for the ED process was calculated based on experimentally obtained data according to Formula (1):U (V) is the voltage applied to the electrodes, I (A) is the average current over a period of time t (h) and m (HSS) (g) is the HSS mass removed over a period of time t (h).The specific energy consumption (2/mol MEA) the dependence of electrical conductivity on CO2 concentration is linear, the calculation of the desalination depth can be carried out using the electrical conductivity values according to Formula (2):SEC—electrical conductivity; 0, 60 min is the duration of the electrodialysis experiment.The depth of desalination (release of carbon dioxide) was estimated from the values of the specific electrical conductivity (SEC) of solutions and the dependence of the SEC of a carbonized MEA solution on the degree of saturation with carbon dioxide . Since iI is the current supplied to the apparatus, A; cellN is the number of elementary cells in the membrane package of the electrodialysis apparatus; n is the amount of obtained carbonate ions, mol-eq; τ is the time elapsed since the beginning of the experiment, s; F is Faraday’s constant, 96,485 A s/mol.The current efficiency of carbonate ions η in the electrodialysis apparatus was calculated using Formula (3):The elemental composition of the precipitate in degraded MEA was analyzed using wavelength-dispersive X-ray fluorescence analysis, carried out on an ARL PERFORM’X  sequential X-ray fluorescence spectrometer using a rhodium tube . Up to 7To study the electrokinetic activity of degradation products, this work was divided into two parts: (1) obtaining a degraded amine solution; (2) comparison of the efficiency of electrodialysis treatment of a carbonized amine solution before and after contact of ion-exchange membranes with a degraded solution. The article also considers the approach of regeneration of ion-exchange membranes from degradation products.The appearance of a rich brown color and turbidity of the MEA solution during its thermal exposure at a temperature of 120 °C is direct evidence of the thermal aging processes of MEA. The detection of iron and nickel cations in the filtered sediment  is obvioThe graphical dependence of the increase in the concentration of insoluble iron and nickel compounds, built on the basis of the data in 2 from a real flue gas in which oxygen is present are presented, while in the experiments of this work, model solutions of carbonized MEA were used, which were not saturated with oxygen. According to the data given in [A significant excess of the concentration of iron in the oxidation products is understandable since nickel is initially an additive in the composition of stainless steel. It should be noted that the nature of the dependences obtained correlates with the data  obtainedgiven in , iron ioAnalysis of the change in the optical density of the MEA solution during degradation  demonstrThe data in The course of the electrodialysis process was assessed by the change in the electrical conductivity of the diluate solution and its temperature, which were recorded according to the readings of the conductometer “C”,  every 10Desalting depth for MA-41 and MK-40 membranes after exposure to the degraded MEA solution decreased to 1.6 mS/cm compared to 4.4 mS/cm for fresh membranes . It shouThis decrease in productivity is due to clogging of the membrane with amine degradation products. It should be noted that the deposition of degradation and corrosion products on the surface of ion-exchange membranes leads to a change in their color .It can be seen that corrosion and MEA degradation products are deposited on the membrane surface. Obviously, the amine compaction products adsorbed on the membrane surface have low electrokinetic activity . This ha+. In this case, a highly alkaline environment contributes to the washing off of deposits from the membrane surface. Thus, one can expect a decrease in the resistance of the membrane and an increase in its conductivity.In this work, for the first time for ion-exchange membranes MK-40 and MA-41, alkaline regeneration was carried out from corrosion products and degradation of the MEA absorbent during electrodialysis. Since the products of MEA compaction in aqueous solutions are cationic in nature, they preferentially settle on cation-exchange membranes during electrodialysis. The sediment accumulation on the ion-exchange membrane leads to an increase in its resistance and, as a result, to a decrease in the module amperage (which we observed on membranes that were in contact with the degraded solution for 6 months). In order to assess the contribution of the effect of alkanolamine compaction products on the operation of ion-exchange membranes, a 4-fold regeneration of membranes with an alkali solution (with a concentration of 5 g/L NaOH) was carried out for the first time in the electrodialysis mode. The choice of such a regenerating agent is due to the fact that cation-exchange membranes are supplied in the Na-form, that is, the counterion of the polyelectrolyte in the membrane is NaElectrodialysis of an alkaline solution of 5 g/L NaOH was carried out for 1 h. An aqueous solution with an alkali content of 5 g/L NaOH was supplied to the desalination chambers, and distilled water was supplied to the concentration chambers. At each repetition, the hydraulic circuits for desalting and concentrating were filled with fresh alkali solution and distilled water. The electrode chambers were filled with a sodium sulfate solution, which ensured high conductivity in the electrode chambers. The kinetics of changes in electrical conductivity for membranes before and after regeneration is shown in It can be seen that after 6 months of exposure, the resistance of ion-exchange membranes increases. Clogging of the membrane surface with groups with low electrokinetic activity leads to a decrease in the transfer of carbonate ions through the membranes. This behavior persists during repeated electrodialysis treatments of the MEA absorbent on clogged membranes. A single regeneration of the membranes with a NaOH solution made it possible to reduce the gap between fresh and clogged membranes in terms of the depth of desalination. However, 4-fold electrodialysis treatment of an alkaline solution (5 g NaOH/L) allows for increasing the transfer through the membranes . Apparen2 extraction depth to 10%. It should be noted that the current after 4-fold alkaline regeneration reached 1.5 A; however, the transfer of carbonate ions remained higher than in the case of clogged membranes. This is also confirmed by the dependence of the current output on the time of electrodialysis . This allows us to state that the clogging of ion-exchange membranes occurs mainly by products of thermal degradation of MEA.A study of the thermal degradation of a carbonized 30% wt. solution of monoethanolamine (MEA) for 336 h at 120 °C was made. Based on the change in color of the solution and the formation of a precipitate, the thermal degradation of the MEA solution was confirmed. As part of the study of the thermal degradation of an MEA solution, the electrokinetic activity of the tarry products of densification of the amine in the degraded solution was studied. To determine the electrokinetic activity of the amine compaction products, a package of MK-40 and MA-41 ion-exchange membranes was exposed to a degraded solution for 6 months. A comparison of the electrodialysis treatment of a model MEA absorption solution before and after exposure showed that the relative depth of desalination is reduced by 34%, while the magnitude of the current flowing through the apparatus is reduced by 25%. For the first time, the alkaline regeneration of ion-exchange membranes was carried out in the mode of electrodialysis from MEA degradation products, which made it possible to restore the relative depth of desalting to 90% and relative current efficiency to 96%. It has been shown that to optimize the process of electrodialysis regeneration of the MEA solution, it should be started simultaneously with the start of the carbon dioxide absorption process.