Natural Trajectories Research Articles

LEVIOSA: Natural Language-Based Uncrewed Aerial Vehicle Trajectory Generation

This paper presents LEVIOSA, a novel framework for text- and speech-based uncrewed aerial vehicle (UAV) trajectory generation. By leveraging multimodal large language models (LLMs) to interpret natural language commands, the system converts text and audio inputs into executable flight paths for UAV swarms. The approach aims to simplify the complex task of multi-UAV trajectory generation, which has significant applications in fields such as search and rescue, agriculture, infrastructure inspection, and entertainment. The framework involves two key innovations: a multi-critic consensus mechanism to evaluate trajectory quality and a hierarchical prompt structuring for improved task execution. The innovations ensure fidelity to user goals. The framework integrates several multimodal LLMs for high-level planning, converting natural language inputs into 3D waypoints that guide UAV movements and per-UAV low-level controllers to control each UAV in executing its assigned 3D waypoint path based on the high-level plan. The methodology was tested on various trajectory types with promising accuracy, synchronization, and collision avoidance results. The findings pave the way for more intuitive human–robot interactions and advanced multi-UAV coordination.

Dynamic strategies and optimal control analysis for hepatitis C management: non-invasive liver fibrosis diagnosis

This study proposes a novel model employing nonlinear ordinary differential equations to dissect HCV dynamics. Six distinct population groups are delineated: Susceptible, Treatment, Responder, Non-Responder, Cured, and Fibrosis. A detailed numerical analysis of this model was conducted, tracking the predicted trends over a span of 20 years. The primary objective of this analysis is to assess and confirm the model’s predictive accuracy and its potential to supplant invasive diagnostic methods in monitoring the progression of liver fibrosis. By incorporating various control parameters, namely u 1 ( t ) , u 2 ( t ) , and u 3 ( t ) , the model offers a nuanced perspective on disease progression and treatment outcomes. Parameter u 1 ( t ) modulates treatment-induced fibrosis progression, providing a crucial lever for mitigating treatment-related side effects. u 2 ( t ) reflects treatment effectiveness, capturing the proportion of responders within the treatment cohort. Meanwhile, u 3 ( t ) governs fibrosis progression in non-responders, shedding light on the disease’s natural trajectory without effective treatment.

Gut microbiota wellbeing index predicts overall health in a cohort of 1000 infants

The human gut microbiota is central in regulating all facets of host physiology, and in early life it is thought to influence the host’s immune system and metabolism, affecting long-term health. However, longitudinally monitored cohorts with parallel analysis of faecal samples and health data are scarce. In our observational study we describe the gut microbiota development in the first 2 years of life and create a gut microbiota wellbeing index based on the microbiota development and health data in a cohort of nearly 1000 infants using clustering and trajectory modelling. We show that infants’ gut microbiota development is highly predictable, following one of five trajectories, dependent on infant exposures, and predictive of later health outcomes. We characterise the natural healthy gut microbiota trajectory and several different dysbiotic trajectories associated with different health outcomes. Bifidobacterium and Bacteroides appear as early keystone organisms, directing microbiota development and consistently predicting positive health outcomes. A microbiota wellbeing index, based on the healthy development trajectory, is predictive of general health over the first 5 years. The results indicate that gut microbiota succession is part of infant physiological development, predictable, and malleable. This information can be utilised to improve the predictions of individual health risks.

Natural logarithm particle swarm optimization for loss reduction in an island power system

In an island power system, optimizing energy management is fundamental since there are renewable sources with their limitations. This management includes the allocation and capacity of energy sources to supply the loads. In this context, optimizing losses in the system contributes to improve the efficiency of this management. This paper proposes the losses optimization and energy management in the island power system. The authors propose the Natural Logarithm Particle Swarm Optimization to solve the problem and compare it with the Attractor Point Algorithm and Evolutionary Particle Swarm Optimization. And with that, we also propose a particle initialization for the studied particle-based algorithms to guarantee convergence in radial power systems. This is because the system configuration influences the response of the algorithm convergence. These techniques were applied to the IEEE-34 unbalanced radial island system.•Natural Logarithm Particle Swarm Optimization differs from classical PSO in that it does not calculate the velocity of the particles. Therefore, the method considers a cloud of particles with a natural logarithmic trajectory to solve the reduction of losses in a power system with a radial topology.•Natural Logarithmic Particle Swarm Optimization uses an initialization equation to minimize the initial estimation process, which is relevant to the convergence process.

Fish size structures in lakes of the Lower Mississippi River floodplain

Abstract The Lower Mississippi River has a floodplain that includes >1350 perennial lakes carved by shifts in river courses and other hydro‐fluvial processes over eons. Notwithstanding their similar provenances, these waterbodies exhibit an immense variety of morphologies and successional stages that illustrate their natural trajectory from aquatic to forested wetlands. A result of this geographical, morphological and temporal diversity is dynamic and varied fish communities. We examined how size structures of fish communities in these floodplain lakes were associated with key in‐lake and off‐lake environmental drivers. Fish lengths were collected with standardised procedures in a sample of 30 of these lakes to construct a lake‐by‐length group matrix. Likewise, in‐lake and off‐lake environmental descriptors were collected to construct a lake‐by‐covariate matrix. Distance‐based linear models were used to assess associations between fish size structure and environmental descriptors. Smaller fish were typically associated with increasing levels of turbidity, chlorophyll‐a, phycocyanin and surrounding agriculture. Shallow, hypereutrophic floodplain lakes associated with agricultural landscapes and reduced connectivity experience harsh physicochemical environments. These conditions appeared to hinder the formation of sustained fish communities but may confer a survival advantage to juveniles or small short‐lived species. Conversely, larger fish were associated with increasing lake depth, water clarity, connectivity, and extent of surrounding forests‐wetlands. Enhanced stability and size structure were observed in communities residing in deeper and clearer lakes, suggesting that these conditions facilitated the development of longer‐lived species spanning multiple age groups. The enhanced connectivity that facilitated this increased stability also permitted the presence of larger itinerant species. Size‐structure assessments can serve as a valuable ecological and biodiversity indicator in floodplain lakes. Size‐structure assessments could supplement and, depending on objectives, even supplant conventional taxonomic analyses, and enhance surveillance of this vast and important natural resource.

Clinical phenotypes and outcomes of patients with left ventricular thrombus: an unsupervised cluster analysis

BackgroundLeft ventricular thrombus (LVT) can develop in a diverse group of patients with various underlying causes, resulting in divergent natural histories and trajectories with treatment. Our aim was to use cluster analysis to identify unique clinical profiles among patients with LVT and then compare their clinical characteristics, treatment strategies, and outcomes. MethodsWe conducted a retrospective study involving 472 patients with LVT whose data were extracted from a tertiary center's echocardiography database, from March 2011 to January 2021. We used the TwoStep cluster analysis method, examining 19 variables. ResultsOur analysis of the 472 patients with LVT revealed two distinct patient clusters. Cluster 1, comprising 247 individuals (52.3%), was characterized by younger patients with a lower incidence of traditional cardiovascular risk factors and relatively fewer comorbidities compared with Cluster 2. Most patients had LVT attributed to an underlying ischemic condition, with a larger proportion being due to post-acute myocardial infarction in Cluster 1 (68.8%), and due to ischemic cardiomyopathy in Cluster 2 (57.8%). Notably, patients in Cluster 2 exhibited a reduced likelihood of LVT resolution (hazard ratio [HR] 0.58, 95% confidence interval [CI] 0.44–0.77, p < 0.001) and a higher risk of all-cause mortality (HR 2.27, 95% CI 1.43–3.60, p = 0.001). These associations persisted even after adjusting for variables such as anticoagulation treatment, the presence of left ventricular aneurysms, and specific LVT characteristics such as mobility, protrusion, and size. ConclusionThrough TwoStep cluster analysis, we identified two distinct clinical phenotypes among patients with LVT, each distinguished by unique baseline clinical attributes and varying prognoses.

Evolution of the regional innovation system in terms of the Covid-19 pandemic, financial and economic crisis: The long term perspective from Central European region

Research background: The evolution of the innovation system is not easy to explore due to the small number or selective nature of the international research about it. The natural trajectory is well known in a long time period but differs between regions and countries — more or less developed. If the impact of the external shocks on regional innovation system (RIS) is added here, the situation is even more complicated. The answer for the crises depends on the development level of a country and region, the maturity of the relationships between actors of the Triple Helix (entrepreneurship, science, government) — their strength and stability over time, some endogenous conditions specific to it. The knowledge about the evolution of the innovation system is crucial to understand how the system works, where it was, is and will be at the evolution trajectory. Purpose of the article: Therefore, the purpose of this paper is to identify the evolution of the RIS in the one of Central Europe’s regions (Lower Silesian in Poland) including the impact of the global financial crisis and the Covid-19 pandemic on the innovation technology there. Methods: Using microdata collected by the authors and the stepwise logit modelling, industrial enterprises were analysed in three time periods: 2004–2006, 2010–2012 and 2019–2021. Total 1649 questionnaires forms were collected. The research was made in the one of Poland's well advanced regional innovation systems — the Lower Silesian. The matrix of success and fail was used as long as the AUC curve and some statistical indicators to prove the usefulness of models. The dependent variables were the new technology pushed by R&amp;D and the investment in new machinery and equipment. Findings &amp; value added: The nature of RIS evolution in the one of the regions in Central Europe in a catching-up country in the context of financial crises and Covid-19 was examined. The analyses identified two alternative groups of conditions — high or low resilience to various market shocks. To the first group belongs: R&amp;D and equipment interactions (the growing competence effect) and a cooperation along the supply chain in the industry. The low resilience is observed in the other categories, as follows: the cooperation with science institutes and business support organizations (the isolation effect), the lack of external sources of funding (the sinking effect), the short time reaction of entrepreneurs (the adaptation effect). As was pointed above in the catching-up country, some elements of the Triple Helix are more sensitive to external shocks, while others are not. The crisis situation can radically slow down an evolutionary development or change its direction. Knowing them will allow the local authority to react on time or with a low delay to reduce negative consequences of it to the regional economy. Authors have shown a new approach to the evolution process of regional innovation system. It could be useful to learn how, where and when the system is going to.

Scenarios for the long-term efficacy of amyloid-targeting therapies in the context of the natural history of Alzheimer's disease.

Recent clinical trials of amyloid beta (Aβ)-targeting therapies in Alzheimer's disease (AD) have demonstrated a clinical benefit over 18 months, but their long-term impact on disease trajectory is not yet understood. We propose a framework for evaluating realistic long-term scenarios. Results from recent phase 3 trials of Aβ-targeting antibodies were integrated with an estimate of the long-term patient-level natural history trajectory of the Clinical Dementia Rating-Sum of Boxes (CDR-SB) score to explore realistic long-term efficacy scenarios. Three distinct long-term efficacy scenarios were examined, ranging from conservative to optimistic. These extrapolations of positive phase 3 trials suggested treatments delayed onset of severe dementia by 0.3 to 0.6 years (conservative), 1.1 to 1.9 years (intermediate), and 2.0 to 4.2 years (optimistic). Our study provides a common language for long-term impact of disease-modifying treatments. Our work calls for studies with longer follow-up and results from early intervention trials to provide a comprehensive assessment of these therapies' true long-term impact. We present long-term scenarios of the efficacy of AD therapies. In this framework, scenarios are defined relative to the natural history of AD. Long-term projections with different levels of optimism can be compared. It provides a common language for expressing beliefs about long-term efficacy.

Early microRNA and metabolite changes after anterior cruciate ligament reconstruction surgery

ObjectivesAnterior cruciate ligament (ACL) reconstruction after injury does not prevent post-traumatic osteoarthritis (PTOA). Circulating microRNA (miRNA) and metabolite changes emerging shortly after ACL injury and reconstruction remain insufficiently defined, potentially harbouring early cues contributing to PTOA evolution. Moreover, their differential expression between females and males also may influence PTOA’s natural trajectory. This study aims to determine alterations in plasma miRNA and metabolite levels in the early stages following ACL reconstruction and between females and males. MethodsA cohort of 43 ACL reconstruction patients was examined. Plasma was obtained at baseline, 2-weeks, and 6-weeks post-surgery (129 biospecimens in total). High throughput miRNA sequencing and metabolomics were conducted. Differentially expressed miRNAs and metabolites were identified using negative binomial and linear regression models, respectively. Associations between miRNAs and metabolites were explored using time and sex as co-variants, (pre- versus 2- and 6-weeks post-surgery). Using computational biology, miRNA-metabolite-gene interaction and pathway analyses were performed. ResultsLevels of 46 miRNAs were increased at 2-weeks post-surgery compared to pre-surgery (baseline) using miRNA sequencing. Levels of 13 metabolites were significantly increased while levels of 6 metabolites were significantly decreased at 2-weeks compared to baseline using metabolomics. Hsa-miR-145-5p levels were increased in female subjects at both 2-weeks (log2-fold-change 0.71, 95%CI 0.22,1.20) and 6-weeks (log2-fold-change 0.75, 95%CI 0.07,1.43) post-surgery compared to males. In addition, hsa-miR-497-5p showed increased levels in females at 2-weeks (log2-fold-change 0.77, 95%CI 0.06,1.48) and hsa-miR-143-5p at 6-weeks (log2-fold-change 0.83, 95%CI 0.07,1.59). Five metabolites were decreased at 2-weeks post-surgery in females compared to males: L-leucine (-1.44, 95%CI -1.75,-1.13), g-guanidinobutyrate (-1.27, 95%CI 1.54,-0.99), creatinine (-1.17, 95%CI -1.44,-0.90), 2-methylbutyrylcarnitine (-1.76, 95%CI -2.17,-1.35), and leu-pro (-1.13, 95%CI -1.44,-0.83). MiRNA-metabolite-gene interaction analysis revealed key signalling pathways based on post-surgical time-point and in females versus males. ConclusionMiRNA and metabolite profiles were modified by time and by sex early after ACL reconstruction surgery, which could influence surgical response and ultimately risk of developing PTOA.

Unveiling the dance of evolution: Pla-mediated cleavage of Ymt modulates the virulence dynamics of Yersinia pestis.

The emergence of Y. pestis as a highly lethal pathogen is driven by extensive gene pseudogenization and acquisition of exogenous plasmids pPCP1 and pMT1. However, the interplay between these two plasmids during evolution remains largely unexplored. Our study reveals intricate interactions between Ymt and Pla, two crucial virulence determinants encoded on these plasmids. Pla-mediated cleavage of Ymt significantly decreases Y. pestis survival in mouse blood and enhances its virulence in mice. The prevalent Pla-I259T variant in modern strains displays reduced Ymt cleavage, thereby extending the survival of infected animals and potentially increasing strain transmissibility. Our findings shed light on the nuanced evolution of Y. pestis, wherein reduced cleavage efficiency is a positive selection force, shaping the pathogen's natural trajectory.

Problematic Internet use among adults: A longitudinal European study.

There are few cross-cultural studies utilizing longitudinal analysis to explore problematic internet use (PIU), and almost none among adults. The present follow-up study compared three waves across 12-month period every six months and observed the natural course and trajectory of PIU in a European multi-country sample of adults from 11 countries (Finland, Germany, Italy, Spain, France, Switzerland, Hungary, Poland, UK, Norway, Belgium). A total of 139 participants (45.5% females) provided data across all three waves with an average age of 26.14 years (SD = 5.92). There were longitudinal effects in PIU, with statistical differences between at-risk users compared to healthy users in Waves 1 and 2, and Waves 1 and 3. The analyses of variance showed a longitudinal effect of waves on the PIU symptoms. PIU was significantly affected by time and type of user, with those classed as at-risk having higher scores than healthy users, although PIU decreased over time. In addition, the type of PIU detected in adults contained mild addictive symptoms. In conclusion, this study demonstrated that PIU was generally low among European adult population and tended to decrease over the one-year period, what contrasts with adolescent population findings.

Analysis of Cerebrospinal Fluid, Plasma β-Amyloid Biomarkers, and Cognition from a 2-Year Phase 2 Trial Evaluating Oral ALZ-801/Valiltramiprosate in APOE4 Carriers with Early Alzheimer's Disease Using Quantitative Systems Pharmacology Model.

ALZ-801/valiltramiprosate is an oral, small-molecule inhibitor of beta-amyloid (Aβ) aggregation and oligomer formation in late-stage development as a disease-modifying therapy for early Alzheimer's disease (AD). The present investigation provides a quantitative systems pharmacology (QSP) analysis of amyloid fluid biomarkers and cognitive results from a 2-year ALZ-801 Phase 2 trial in APOE4 carriers with early AD. The single-arm, open-label phase 2 study evaluated effects of ALZ-801 265 mg two times daily (BID) on cerebrospinal fluid (CSF) and plasma amyloid fluid biomarkers over 104 weeks in APOE4 carriers with early AD [Mini-Mental State Examination (MMSE) ≥ 22]. Subjects with positive CSF biomarkers for amyloid (Aβ42/Aβ40) and tau pathology (p-tau181) were enrolled, with serial CSF and plasma levels of Aβ42 and Aβ40 measured over 104 weeks. Longitudinal changes of CSF Aβ42, plasma Aβ42/Aβ40 ratio, and cognitive Rey Auditory Verbal Learning Test (RAVLT) were compared with the established natural disease trajectories in AD using a QSP approach. The natural disease trajectory data for amyloid biomarkers and RAVLT were extracted from a QSP model and an Alzheimer's disease neuroimaging initiative population model, respectively. Analyses were stratified by disease severity and sex. A total of 84 subjects were enrolled. Excluding one subject who withdrew at the early stage of the trial, data from 83 subjects were used for this analysis. The ALZ-801 treatment arrested the progressive decline in CSF Aβ42 level and plasma Aβ42/Aβ40 ratio, and stabilized RAVLT over 104 weeks. Both sexes showed comparable responses to ALZ-801, whereas mild cognitive impairment (MCI) subjects (MMSE ≥ 27) exhibited a larger biomarker response compared with more advanced mild AD subjects (MMSE 22-26). In this genetically defined and biomarker-enriched early AD population, the QSP analysis demonstrated a positive therapeutic effect of oral ALZ-801 265 mg BID by arresting the natural decline of monomeric CSF and plasma amyloid biomarkers, consistent with the target engagement to prevent their aggregation into soluble neurotoxic oligomers and subsequently into insoluble fibrils and plaques over 104 weeks. Accompanying the amyloid biomarker changes, ALZ-801 also stabilized the natural trajectory decline of the RAVLT memory test, suggesting that the clinical benefits are consistent with its mechanism of action. This sequential effect arresting the disease progression on biomarkers and cognitive decline was more pronounced in the earlier symptomatic stages of AD. The QSP analysis provides fluid biomarker and clinical evidence for ALZ-801 as a first-in-class, oral small-molecule anti-Aβ oligomer agent with disease modification potential in AD. https://clinicaltrials.gov/study/NCT04693520.

Application of gaming robot based on gait recognition algorithm in sports training and assistance system

At present, game sports robots have become a new type of sports assistance technology, which can achieve more natural and smooth motion trajectory analysis under continuous training, and provide a gamified user experience for sports training. This article analyzes the application of game motion robots based on gait recognition algorithms in sports training and motion assistance systems, which can more accurately obtain information data of the athlete during the movement process and has good results in preventing sports injuries. We combine gait recognition algorithms with video feature aggregation to integrate high-level and low-level network features, achieving effective extraction of multi-level image features. Finally, complete action recognition, review, and analysis. Through experimental comparison, it can be seen that the feature aggregation modules designed in this article at different levels are very effective, and combined with gait recognition algorithms, they can effectively improve the accuracy of motion recognition and have excellent robustness. The motion assistance system designed in this article can automatically determine the movements during exercise, allowing athletes to self-evaluate their movements and correct incorrect movements without the need for professional guidance, achieving healthy and effective exercise results.

Counting your chickens before they hatch: improvements in an untreated chronic pain population, beyond regression to the mean and the placebo effect.

Isolating the effect of an intervention from the natural course and fluctuations of a condition is a challenge in any clinical trial, particularly in the field of pain. Regression to the mean (RTM) may explain some of these observed fluctuations. In this paper, we describe and quantify the natural trajectory of questionnaire scores over time, based on initial scores. Twenty-seven untreated chronic low back pain patients and 25 healthy controls took part in this observational study, wherein they were asked to complete an array of questionnaires commonly used in pain studies during each of 3 visits (V1, V2, V3) at the 2-month interval. Scores at V1 were classified into 3 subgroups (extremely high, normal, and extremely low), based on z-scores. The average delta (∆ = V2 - V1) was calculated for each subgroup, for each questionnaire, to describe the evolution of scores over time based on initial scores. This analysis was repeated with the data for V2 and V3. Our results show that high initial scores were widely followed by more average scores, while low initial scores tended to be followed by similar (low) scores. These trajectories cannot be attributable to RTM alone because of their asymmetry, nor to the placebo effect as they occurred in the absence of any intervention. However, they could be the result of an Effect of Care, wherein participants had meaningful improvements simply from taking part in a study. The improvement observed in patients with high initial scores should be carefully taken into account when interpreting results from clinical trials.

Trajectory Planning Research Based on Rapidly-exploring Random Trees (RRT) Algorithm and Modified Forms

With the rapid advancement of computer technology, robots have become indispensable in various fields. Trajectory planning plays a crucial role in optimizing robot performance by enhancing work efficiency and reducing operational costs. While the widely used Rapidly-exploring Random Trees (RRT) algorithm is effective in path planning, it often generates non-optimal paths with poor smoothness. By incorporating elements from RRT-Connect and reverse optimization, the algorithm can efficiently navigate through intricate and dynamic surroundings. Furthermore, the utilization of cubic polynomial interpolation in optimizing path curves adds a layer of sophistication to the trajectory planning process. This interpolation technique allows for the creation of smoother and more natural path trajectories, reducing jerky movements and enhancing overall motion control precision. The paths produced by the enhanced RRT algorithm demonstrate increased continuity and visual attractiveness, crucial for tasks necessitating accurate and elegant robotic motions. The improved algorithm showcases reduced path length and time consumption, as well as enhanced path smoothness. Particularly, relative to the traditional RRT approach, the time consumption has dropped by 69.15% and the median duration of the paths has fallen by 21.11%. These improvements signify a substantial advancement in trajectory planning for robots, offering more efficient and smoother paths for robotic operations across various applications.

Iron deficiency in new onset heart failure: association with clinical factors and quality of life.

The prevalence of iron deficiency (ID) in newly diagnosed heart failure (HF) and the progression of ID in patients after initiation of HF therapy are unknown. We aimed to describe the natural trajectory of ID in patients with new onset HF during the first year after HF diagnosis, assessing associations between ID, clinical factors, and quality of life (QoL). A prospective cohort of patients with new onset HF in hospitals or outpatient clinics at five major hospitals in Stockholm, Sweden, during 2015-2018 were analysed with clinical assessment, electrocardiogram, blood samples including iron levels, Minnesota living with heart failure questionnaire (MLHFQ), and echocardiogram at baseline and after 12months. Of 547 patients with new-onset HF, 482 (88%) had complete iron data at baseline. Median age was 70years (interquartile range 61-77) and 311 (65%) were men; 55% of patients had ejection fraction (EF)≤40%, 19% had EF 41-49%, and 26% had HF with preserved EF (HFpEF) [Correction added on 26 June 2024, after first online publication: The 'Mean age was 70 years' has been corrected to 'Median age was 70 years' in this version.]. At baseline, 163 patients (34%) had ID defined as ferritin <100μg/L or ferritin 100-299μg/L and transferrin saturation <20%. After 12months of follow-up, 119 (32%) had ID of the 368 patients who had complete iron data both at baseline and after 12months and did not receive intravenous (i.v.) iron during follow-up. During the first year after HF diagnosis, 19% had persistent ID, 13% developed ID, 11% resolved ID, and 57% never had ID, consequently 24% changed their classification. Anaemia at baseline was the strongest independent predictor of ID 1year after diagnosis [odds ratio (OR) 3.91, 95% confidence interval (CI) 1.88-8.13, P<0.001], followed by HF hospitalization (OR 2.21, 95% CI 1.24-3.95, P<0.01), female sex (OR 2.04, 95% CI 1.25-3.32, P<0.01), HFpEF (OR 1.96, 95% CI 1.13-3.39, P<0.05), and diabetes mellitus (OR 1.92, 95% CI 1.06-3.48, P<0.05). ID was associated with low QoL at baseline (MLHFQ score mean difference 7.4 points, 95% CI 3.1-11.7, P<0.001), but not at follow-up. About one third of patients with new onset HF had ID both at the time of HF diagnosis and after 1year, though a quarter of the patients changed their ID status. Patients with anaemia, HF hospitalization, female gender, HFpEF, or diabetes mellitus at baseline were more likely to have ID after 1year implying that these should be carefully screened for ID to find those in need of i.v. iron treatment.

Seamless multi‐mode switching controller of four‐switch buck–boost converter based on integrated natural trajectory method

SummaryWith the characteristics of high efficiency and high power density, the four switch buck–boost (FSBB) converter is widely used in electric vehicles, direct current microgrids, and so forth. However, how to achieve smooth switching between different modes of FSBB has always been a hot issue in the theoretical and engineering fields. In this paper, considering the dynamic performance and output voltage or inductance current deviation, a control algorithm with integrated natural trajectory method is designed to realize the switching of different modes of FSBB converter. The proposed control algorithm is based on the theory of large signal natural locus and average natural locus. The normalized phase locus of inductance current and output voltage divides the phase plane into five regions and performs large signal or average switching operations in different regions. Theoretical analysis shows that the proposed control algorithm can achieve the balance between the dynamic performance and output voltage or inductance current deviation of FSBB converter in different mode switching. Finally, the performance of the proposed control algorithm is verified by experiments results.

VNOTES retroperitoneal sentinel lymph node dissection for endometrial cancer staging: First multicenter, prospective case series.

The current standard treatment for endometrial cancer is a laparoscopic hysterectomy with adnexectomies and bilateral sentinel node resection. A retroperitoneal vNOTES sentinel node resection has several theoretical potential advantages. These include being less invasive, leaving no visible scars, operating without Trendelenburg, and therefore offering the anesthetic advantage of easier ventilation in obese patients and following the natural lymph node trajectory from caudally to cranially and therefore a lower risk of missing the sentinel node. The aim of this study is to determine the feasibility of a retroperitoneal vNOTES approach to sentinel lymph node dissection for staging of endometrial cancer. A prospective multicenter case series was performed in four hospitals. A total of 64 women with early-stage endometrial carcinoma suitable for surgical staging with sentinel lymph node removal were operated via a transvaginal retroperitoneal vNOTES approach. The paravesical space was entered through a vaginal incision after injecting the cervix with indocyanine green. A vNOTES port was placed into this space and insufflation of the retroperitoneum was performed. Sentinel lymph nodes were identified bilaterally using near-infrared light followed by endoscopic removal of these nodes. A total of 64 women with early-stage endometrial cancer underwent sentinel lymph node removal by retroperitoneal vNOTES technique. All patients also underwent subsequent vNOTES hysterectomy and bilateral salpingo-oophorectomy. The median age was 69.5 years, median total operative time was 126 min and the median estimated blood loss was 80 mL. In 97% of the cases bilateral sentinel nodes could be identified. A total of 60 patients had negative sentinel nodes, three had isolated tumor cells and one had macroscopically positive sentinel nodes. No complications with sequel occurred. This prospective multicenter case series demonstrates the feasibility of the vNOTES approach for identifying and removing sentinel lymph nodes in women with endometrial carcinoma successfully and safely. vNOTES allows sole transvaginal access with exposure of the entire retroperitoneal space, following the natural lymph trajectory caudally to cranially, and without the need for a Trendelenburg position.

Intersegmental coordination in human slip perturbation responses

Intersegmental coordination (ISC) of lower limbs and planar covariation law (PCL) are important phenomena observed in biomechanics of human walking and other activities. Gait perturbations tend to cause deviation from the expected ISC pattern thus violating PCL. We used a data set of seven subjects, who experienced unexpected slips, to investigate and characterize the evolution of ISC during slip recoveries and falls. We have analyzed and presented the development of ISC patterns, encompassing the step preceding the slip initiation and duration of slip until it stops. The results show that the ISC patterns during slip recovery deviate considerably from the normal walking patterns. A newly proposed Euclidian distance-based metric (EDM) was used to quantify the deviation from the normal walking ISC pattern during four slip recoveries and three falls evaluated at gait events such as slip start, foot strike, and peak height of the swing foot. The timing of gait events after slip, pattern of EDM, placement of the feet after slip and temporal patterns of each limb angle have been presented. This initial investigation provides insight into the ISC during slip recovery which highlights the human natural recovery trajectories during such perturbations. The observed patterns of the ISC trajectories during slip can be used for the design of human-inspired controllers for exoskeleton devices that can provide external assistance to human subjects during balance recovery.

Cardioid oscillator-based pattern generator for imitating the time-ratio-asymmetrical behavior of the lower limb exoskeleton.

Periodicity, self-excitation, and time ratio asymmetry are the fundamental characteristics of the human gait. In order to imitate these mentioned characteristics, a pattern generator with four degrees of freedom is proposed based on cardioid oscillators developed by the authors. The proposed pattern generator is composed of four coupled cardioid oscillators, which are self-excited and have asymmetric time ratios. These oscillators are connected with other oscillators through coupled factors. The dynamic behaviors of the proposed oscillators, such as phase locking, time ratio, and self-excitation, are analyzed via simulations by employing the harmonic balance method. Moreover, for comparison, the simulated trajectories are compared with the natural joint trajectories measured in experiments. Simulation and experimental results show that the behaviors of the proposed pattern generator are similar to those of the natural lower limb. It means the simulated trajectories from the generator are self-excited without any additional inputs and have asymmetric time ratios. Their phases are locked with others. Moreover, the proposed pattern generator can be applied as the reference model for the lower limb exoskeleton controlling algorithm to produce self-adjusted reference trajectories.