Relative Trajectory Research Articles

Underwater DVL Optimization Network (UDON): A Learning-Based DVL Velocity Optimizing Method for Underwater Navigation

As the exploration of marine resources continues to deepen, the utilization of Autonomous Underwater Vehicles (AUVs) for conducting marine resource surveys and underwater environmental mapping has become a common practice. In order to successfully accomplish exploration missions, AUVs require high-precision underwater navigation information as support. A Strapdown Inertial Navigation System (SINS) can provide AUVs with accurate attitude and heading information, while a Doppler Velocity Log (DVL) is capable of measuring the velocity vector of the AUVs. Therefore, the integrated SINS/DVL navigation system can furnish the necessary navigational information required by an AUV. In response to the issue of DVL being susceptible to external environmental interference, leading to reduced measurement accuracy, this paper proposes an end-to-end deep-learning approach to enhance the accuracy of DVL velocity vector measurements. The utilization of the raw measurement data from an Inertial Measurement Unit (IMU), which includes gyroscopes and accelerometers, to assist the DVL in velocity vector estimation and to refine it towards the Global Positioning System (GPS) velocity vector, compensates for the external environmental interference affecting the DVL, therefore enhancing the navigation accuracy. To evaluate the proposed method, we conducted lake experiments using SINS and DVL equipment, from which the collected data were organized into a dataset for training and assessing the model. The research results show that the DVL vector predicted by our model can achieve a maximum improvement of 69.26% in terms of root mean square error and a maximum improvement of 78.62% in terms of relative trajectory error.

Legal issues in the property, use, preservation, and management of agricultural lands in Bulgaria

This article reviews the subject of ‘agricultural lands’ in Bulgaria from a legal aspect, for the period 1878-2023. It analyses the normative acts, legal consequences and the most important legal changes that the land reforms in the country derive from. There is a review of the processes of restitution, land-settlement, and limitations of property; the initiation of cadastral maps and other events and initiatives related to them; legal actions of the administrative and judicial organs; and decisions related to the judicial and constitutional control, related to the owners and users of agricultural lands. There is some detailing of how the latter perform their legal rights to the land in certain cases. The study is provisionally divided into three sub-periods: the first presents legislation in Bulgaria related to agricultural lands in the period after the establishment of the Third Bulgarian State. It gives explanation to some important moments, deriving from the historical participation of the country in the political events related to the Balkan Peninsula and the First World War, as well as to the policies of land-settlement, organisation and cooperation of the agricultural subjects; establishment of the first administrative bodies; and the administration of the processes related to the property and in particular to the agricultural land. The second period reflects on the legislation defined by the collectivisation and expropriation of the private property, the limitation of the economic relations in regard to the agricultural lands, and the following redefining of the legal institutes related to the property of agricultural land. In a sense the first two parts of the article give answers to the reasons and the need for the last land reform performed after 1989. A milestone in the article is the process of restitution as well as the problems of the legal doctrine of the last period from 1989 until 2023. Apart from identifying the most important problems of the management of the legal aspect of the restitution processes, the article provides a short review of the new course and the ‘curve’ of the legislation regarding agricultural land. The newest changes in the trajectory of the public relations and the legal challenges deriving from the legal order in the European Union are presented, including: legal contradictions of the Bulgarian legislation with the law of the EU; reflection of the structural funds over the legal processes related to the agricultural lands; and the ‘green’ payments and consolidation of the property in agricultural lands. At the end there are some suggestions for the improvement of the legal framework regarding the agricultural lands in the country. The article uses several legal methods, including legal-historical, positive legal analysis, and a normative approach in explaining the offers suitable for the change of the legal framework regarding agricultural lands.

The Evolution of Relations Between Kosovo and Montenegro: From Historic Animosity to Good Neighbourly Relations

This article covers the trajectory of relations between Kosovo and Montenegro from the beginning of the dissolution of the Socialist Federal Republic of Yugoslavia until the present, underlining the interplay of external and internal factors and dynamics. We argue that the adoption of a Euro-Atlantic agenda as the major paradigm in the policymaking of both countries has been the driving force behind the positive evolution of relations between them. This analysis foregrounds the sensitive issue of border demarcation between Kosovo and Montenegro as the most serious test of the impact of their Euro-Atlantic aspirations on their developing relations.

R-AFNIO: Redundant IMU fusion with attention mechanism for neural inertial odometry

Inertial Navigation Systems (INS) play an increasing role in automotive electronics and aerospace applications, particularly in autonomous vehicles, due to their low computational load, swift response, and high autonomy. However, the substantial error accumulation poses a significant challenge for an INS, especially when employing the low-cost Inertial Measurement Units (IMUs). This study proposed R-AFNIO, a convolutional and attention-based deep learning network, which is developed to decrease the issues of error accumulation and the fusion of IMU array data. Firstly, we introduce a self-supervised learning model to learn the prior knowledge from IMU observation by masking redundant IMU data and reconstructing it, thereby reducing the noise of IMU data. Furthermore, we present an intelligent framework and employ an attention-based soft-weighting algorithm to mine the latent information within redundant IMUs. This approach effectively enhances fusion precision and strengthens robustness against error observations. Notably, it is the first approach that utilizes deep learning to solve the information fusion problem of redundant IMUs (IMU arrays). Lastly, we propose a state-augmented tight integration algorithm to improve the local accuracy and robustness of the navigation system. We comprehensively validate the proposed R-AFNIO using both a publicly available dataset and a dataset collected by our team. Experiment results demonstrated that R-AFNIO performs accurate and robust results on most indicators. Compared to several current studies, the absolute trajectory error shows reductions ranging from 20.2% to 97.7%, while the relative trajectory error exhibited reductions ranging from 18.5% to 98.7%. The ablation experiment further highlights the potency of R-AFNIO’s self-supervised and redundant weighting modules.

Understanding Early Risk Factors of Preschool Disruptive Behaviors in a Population-Based Birth Cohort: Why Does Comorbidity Matter?

Research on early risk factors for disruptive behaviors (DBs: hyperactivity-impulsivity/HI, non-compliance/NC, or physical aggression/PA) has predominantly focused on individual DBs in silos (i.e., HI, NC, or PA) or the broader category of externalizing, reporting mostly common risk factors among them. However, studies addressing DB comorbidity, i.e., the simultaneous occurrence of more than one DB, showed differences in risk factors among DB comorbid profiles. Aiming to clarify this discrepancy, the present study compared the early risk factors associated with different longitudinal patterns (i.e., trajectories) of single-DBs (HI, NC, PA) with risk factors associated with monomorbid (HIonly, NConly, PAonly) and comorbid (HI + NC, NC + PA, HI + NC + PA) joint-DBs trajectories during the preschool period. In a population-based birth cohort (N = 2045), parents' pre-conception characteristics, pregnancy and perinatal conditions, and age 5 months child and family characteristics were used to compare children following single-DB and joint-DBs high trajectories to children following low or moderate trajectories. The DB trajectories were derived from mother ratings at ages 1½, 2½, 3½, 4½, and 5 years. More risk factors were identified for single-DB high trajectories than for joint-DBs high trajectories. On average, children on a single-DB high trajectory shared only 44.2% of their risk factors with children on a related joint-DBs high trajectory. Moreover, high trajectories of single-DBs shared a larger proportion of their risk factors than did high trajectories of joint-DBs. The findings show that categories of DBs include different subgroups of children based on their comorbidity patterns across DBs, which are differentially linked to early risk factors. Addressing comorbidity when investigating early risk factors of preschool DBs may improve our understanding of the etiological processes leading to these distinct but related behaviors and increase our ability to intervene upstream to prevent the earliest forms of potentially life-altering psychopathological conditions.

Transactional development of science and mathematics knowledge and reading proficiency for multilingual students across languages of instruction.

This longitudinal study explored the reciprocal relations between students' domain-specific knowledge (science and mathematics) and reading proficiency from kindergarten to Grade 5. We compared these relational trajectories across both domains in the overall sample and examined the domain specificity of these relations within a multilingual subsample with varying language instruction backgrounds. Using latent curve modeling with structured residuals on a nationally representative data set, we identified two key patterns. In the overall sample, higher reading proficiency at kindergarten was associated with greater growth in science and mathematics knowledge, with a particularly pronounced effect in science. The predictive power of science knowledge on reading proficiency strengthened significantly from Grades 2 to 5, while reciprocal relations in mathematics intensified over time. For multilingual students, outcomes varied by the language of instruction. Those receiving English-only instruction showed early correlations between science and mathematics knowledge and reading proficiency; however, initial science and mathematics knowledge did not predict long-term growth in reading proficiency. Conversely, multilingual students who received instruction in their native language showed no immediate correlations at kindergarten. Nonetheless, their early science and mathematics knowledge significantly predicted later growth in reading proficiency. The findings underscore the critical role of native-language instruction in providing an accessible, vital cognitive and linguistic foundation that supports deeper domain knowledge building, highlighting the enduring benefits of native-language scaffolding. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Safe Guidance Scheme for Proximity Operations Forced Motion

Autonomous spacecraft proximity operations represent a key enabler for future mission architectures such as in-orbit servicing, active debris removal, object inspection, and in-orbit assembly. This work addresses safety concepts for the relative trajectory guidance design applicable to challenging proximity operations in the close-range domain. The relative orbital element framework is used to formulate safety checks that improve the trajectory’s robustness in case of chaser’s malfunctions or loss of control. Particularly, concepts of passive abort safety and active collision safety are applied to the trajectory design to maintain the chaser outside keep-out zones. These definitions are included within a guidance algorithm that exploits sequential convex programming to efficiently solve the fixed final time safety-constrained close-range rendezvous problem. Test cases of reconfiguration between stable relative orbits and synchronization to a rotating hold point are presented, highlighting the advantages in using these new safety concepts in terms of safety, trajectory insight, and formulation efficiency.

São Luiz do Paraitinga: o rio e os cenários pós-enchentes

The city of São Luiz do Paraitinga has had a unique trajectory in relation to the context of cities in the Paraíba Valley region, in São Paulo, Brazil. Since the foundation of its settlement and the planning of its layout in the 18th century by Morgado de Mateus, the town has remained on the fringes of regional development, playing a less important role in the coffeeproduction circuit, which has allowed certain local traditions to remain, such as the caipira culture, the rural way of life and the religious festivities that are still local attractions today. In 2010, an unprecedented floodswept through its historic center. Buildings made of wattle and daub were unable to withstand the water and collapsed, with partial and total damage remaining. The reconstruction of the city, as well as the landmarks listed at state and federal level, represent a unique case among similar Brazilian cases, which justified a more in-depth study. The 1982 Conselho de Defesa do Patrimônio Histórico, Arqueológico, Artístico e Turístico do Estado and 2010 Instituto do Patrimônio Histórico e Artístico Nacional registrations reiterated the importance of the city center, its architectural ensemble and its landscape, as it was one of the first planned foundations. However, the social, cultural and economic contrasts between the Historic Center and other neighborhoods in the city raise the question of the effectiveness of landmarks and their management as a Historic and Landscape Heritage. In 2022, the cycle restarted and a flood again caused damage to at least 120 buildings. Faced with this fact, the question arises of how to preserve a landscape that is permanently at risk.

Influence of Ocean Current Features on the Performance of Machine Learning and Dynamic Tracking Methods in Predicting Marine Drifter Trajectories

Accurately and rapidly predicting marine drifter trajectories under conditions of information scarcity is critical for addressing maritime emergencies and conducting marine surveys with resource-limited unmanned vessels. Machine learning-based tracking methods, such as Long Short-Term Memory networks (LSTM), offer a promising approach for trajectory prediction in such scenarios. This study combines satellite observations and idealized simulations to compare the predictive performance of LSTM with a resource-dependent dynamic tracking method (DT). The results indicate that when driven solely by historical drifter paths, LSTM achieves better trajectory predictions when trained and tested on relative trajectory intervals rather than the absolute positions of individual trajectory points. In general, LSTM provides a more accurate geometric pattern of trajectories at the initial stages of forecasting, while DT offers superior accuracy in predicting specific trajectory positions. The velocity and curvature of ocean currents jointly influence the prediction quality of both methods. In regions characterized by active sub-mesoscale dynamics, such as the fast-flowing and meandering Kuroshio Current and Kuroshio Current Extension, DT predicts more reliable trajectory patterns but lacks precision in detailed position estimates compared to LSTM. However, in areas dominated by the fast but relatively straight North Equatorial Current, the performance of the two methods reverses. The two methods also demonstrate different tolerances for noise and sampling intervals. This study establishes a baseline for selecting machine learning methods for marine drifter prediction and highlights the limitations of AI-based predictions under data-scarce and resource-constrained conditions.

Relative Trajectories of Contaminated, Spherical Drops in a Temperature Gradient and Gravity at Finite Stokes Numbers

Relative Trajectories of Contaminated, Spherical Drops in a Temperature Gradient and Gravity at Finite Stokes Numbers

Chinese investment in Central and Eastern Europe: Studying the evolution of industrial relations after the takeover of a Slovenian company

The article studies the approach Chinese investors apply to industrial relations at the company level in Central and Eastern Europe. The takeover of a home appliances producer in Slovenia by a Chinese state-owned enterprise and the trajectory of company-level industrial relations are analysed. Adopting a political economy approach, we examine the role played by market-related factors (especially FDI motivation), institutional context, trade union power resources and the Chinese state as an investor. The study contributes in two ways. First, it shows the inadequacy of market-based explanations as host institutions and actors modify transfer outcomes, blurring the ideal types, such as the ‘latecomer’ model and its apparent CEE counterpart. Second, the strategic interests of Chinese SOEs may unwillingly empower local actors struggling to influence transfer outcomes.

Associations of serial negative income shock and all-cause mortality: a longitudinal study in China

IntroductionWith a precarious economic outlook and increasing income volatility in current times, understanding the association between negative income shock and health is crucial. However, few studies have examined such associations...

Intention inference for space targets using deep convolutional neural network

Intention inference for space targets is crucial for space situational awareness. This paper introduces a rapid and precise method for recognizing the intentions of non-cooperative space targets using a deep convolutional neural network (CNN). By employing a relative orbital dynamics model, an analysis of relative motion was performed, resulting in the identification of 11 distinct motion intentions for space targets. This study also describes how to generate relative motion trajectory images to create a training set for intention inference, effectively converting the problem into one of image recognition and classification. Extensive simulations were carried out to fine-tune the network hyperparameters, and the results highlight the exceptional performance of the proposed CNN-based method, which achieved an accuracy of 99.682%. This method significantly enhances recognition accuracy over other neural network-based methods for space objects and offers considerable potential for applications like spacecraft collision avoidance and strategic maneuvers among space targets.

VSLAM based on deep learning in low-textured scenes

Abstract Traditional Visual Simultaneous Localization and Mapping (VSLAM) algorithms often suffer from the low positioning accuracy and robustness of the traditional feature extraction methods. These methods typically require environments with clear features, perform poorly or even fail in low-textured scenes. To solve this problem, we propose an RGB-D VSLAM algorithm that integrates a deep learning feature extraction network. First, to solve the problem in which sufficient feature points cannot be extracted, the proposed algorithm uses the R2D2 feature extraction network to extract keypoints and generate descriptors. We also perform lightweight optimization on the R2D2 network, ensuring accuracy while doubling the inference speed. Subsequently, we employ the L2 distance to measure the distance between descriptors, thereby enhancing the accuracy of keypoint matching. Ultimately, we add a dense mapping thread to obtain a dense 3D point map generated by the RGB-D information and poses of the keyframes. The experimental results on the TUM dataset show that the average absolute trajectory error is reduced by 59% and the relative trajectory error is reduced by 56%. The results demonstrate that our algorithm significantly improves localization accuracy and system robustness in low-textured environments.

Using Family Systems Theory in Counseling Mixed-Faith Latter-Day Saint Couples After a Religious Disaffiliation

Increasingly, marriages in The Church of Jesus Christ of Latter-day Saints transition from a same-faith to “mixed-faith” status as one spouse religiously disaffiliates. Due to unique beliefs and expectations in sharing beliefs, increased risks of conflict and dissolution are identified. Theorizing the phenomenon through Family Systems Theory, this article assists providers in employing a systemic diagnosis to navigate conflicting triangulations between spouses, while assisting couples in choosing a relational trajectory, deconstructing prior patterns, and creating new patterns centered on shared values. Interventions will be illustrated with a case study; limitations and implications will be discussed.

Narrating lives across 16 years: Developmental trajectories of coherence and relations to well-being in a lifespan sample.

The ability to narrate a life coherently develops first in adolescence, but little is known about its course across adulthood and into old age. Also, the potential association of life narrative coherence with well-being has never been studied. Our aim was to investigate lifespan development of coherence and associations with well-being using data from the longitudinal MainLife study. A total of 172 urban Germans (8-80 years; 87 females) narrated their lives up to six times across 16 years (N = 803 brief entire life narratives). Most were highly educated, and the proportion of a migration background was typical for the local population. Life narratives were rated for three types of global coherence (temporal, causal-motivational, and thematic) and coded for two types of autobiographical arguments (stability maintaining and change engendering). Multilevel models were used to investigate their lifespan development and relations to well-being. While most life narrative measures increased up to emerging adulthood and then remained stable, thematic coherence continued to increase into middle adulthood. Only change-engendering autobiographical arguments slowly decreased from midlife onward. Unexpectedly, neither autobiographical arguments nor global coherence correlated significantly with well-being. Data exploration suggested an association between thematic coherence and self-continuity. We conclude that life narrative coherence may only be related to well-being if samples include cases with more extreme noncoherence (e,g., clinical disorders). Our findings add to understanding the development of the life story across the lifespan, especially in older age, and suggest studying relations of coherence, self-continuity, and well-being specifically in life crises and in clinical samples. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Neoliberalism by stealth? Labour reforms and institutional discontinuity in worker representation in France

This article analyses the 2017 reforms to worker representation in France, focusing on the transition and implementation phases. The authors conducted 160 interviews with managers, union and employee representatives in seven large French companies across retail, finance, energy and pharmaceuticals. The article introduces the notion of institutional discontinuity to describe the path taken through the 2017 reforms, where a change to the formal institutional structures is expected to bring about a change in the functioning of representative institutions. The findings contribute to debates on the trajectories of employment relations in France. The authors argue that institutional discontinuity has opened a wider path towards more discretion-enhancing representative institutions, reflecting a clearer neoliberal path in employment relations. Yet, recognising that changing institutional form does not necessarily, nor automatically result in institutions functioning differently, the authors also analyse how actors play a role in shaping the process, whether they try to facilitate the change or to limit its effects.

Distributed control of spacecraft formation under [formula omitted] perturbation in the port-Hamiltonian framework

To control the relative position and relative velocity of spacecraft formation, a time-varying nonlinear relative motion model under J2 perturbation in an elliptical orbit is established in the port-Hamiltonian (PH) framework, and a distributed control law for spacecraft formation is developed using the consensus algorithm for parameter estimation and the passivity-based control (PBC) method based on the state-error interconnection and damping assignment (IDA) technique. First, the influence of J2 perturbation on the potential energy and orbit parameters in the model is considered when the relative motion model is built in the PH frame, and the expression of the relative motion acceleration under J2 perturbation is given. Second, to solve the problem that the state of the chief spacecraft cannot be directly obtained from the deputy spacecraft under distributed communication, a consensus-based parameter estimation method is introduced, the estimated parameter of the chief spacecraft is applied to the relative motion model in the PH frame, and a state error model with the estimated parameters derived from the consistency algorithm is established. Then, after the stability analysis is conducted on the desired PH system containing the estimated parameter values, the desired Hamiltonian energy function with the estimated parameters is designed according to the time-varying errors of the relative equilibrium states of the deputy spacecraft and the errors between deputy spacecraft, and the distributed control law of spacecraft formation is derived based on the state-error IDA-PBC method. Finally, the expected relative motion trajectory designed based on the TH equation is used to simulate a spacecraft formation under J2 perturbation, and the results indicate that the spacecraft can quickly converge to the expected formation under the influence of the control law.

Individual differences in developmental trajectories of affective attention and relations with competence and social reticence with peers.

This study examined individual differences in affective attention trajectories in infancy and relations with competence and social reticence at 24 months. Data collection spanned 2017 to 2021. Infants (N = 297, 53% White, 49% reported as assigned male at birth) recruited in South Central and Central Pennsylvania and Northern New Jersey provided eye-tracking data at five assessments. Caregivers self-reported anxiety symptoms, infant temperamental negative affect, and infant competence at the final assessment. A subgroup of infants participated in a peer social dyad at the final assessment. Using group-based trajectory modeling, we found three groups of infants with different affective attention trajectories: affective attention increasers (n = 73), affective attention shifters (n = 156), and affective attention decreasers (n = 50). Affective attention increasers exhibited low intercepts with steep attention increases, particularly to angry facial configurations. Affective attention shifters exhibited middle intercepts with attention decreases to facial configurations but an attention increase to angry facial configurations. Affective attention decreasers exhibited high intercepts with steep attention decreases. Infants in the affective attention increasers group exhibited more competence when accounting for caregiver anxiety symptoms and infant temperamental negative affect. Group membership was not related to social reticence during the peer social dyad. Infants higher in temperamental negative affect exhibited more social reticence, particularly as the social dyad continued. Our results provide evidence for individual differences in developmental trajectories of affective attention and relations with toddler social behavior. Our results are primarily generalizable to rural and urban populations in the Midatlantic United States. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Effect of the cone-beam CT acquisition trajectory on image quality in spine surgery: experimental cadaver study

BACKGROUNDIntraoperative 3D imaging with cone-beam CT (CBCT) improves assessment of implant position and reduces complications in spine surgery. It is also used for image-guided surgical techniques, resulting in improved quality of care. However, in some cases, metal artifacts can reduce image quality and make it difficult to assess pedicle screw position and reduction. PURPOSEThe objective of this study was to investigate whether a change in CBCT acquisition trajectory in relation to pedicle screw position during dorsal instrumentation can reduce metal artifacts and consequently improve image quality and clinical assessability. STUDY DESIGNExperimental cadaver study. METHODSA human cadaver was instrumented with pedicle screws in the thoracic and lumbar spine region (Th11 to L5). Then, the acquisition trajectory of the CBCT (Cios Spin, Siemens, Germany) to the pedicle screws was systematically changed in 5° steps in angulation (−30° to +30°) and swivel (−25° to +25°). Subsequently, radiological evaluation was performed by 3 blinded, qualified raters on image quality using 9 questions (including anatomical structures, implant position, appearance of artifacts) with a score (1–5 points). For statistical evaluation, the image quality of the different acquisition trajectories was compared to the standard acquisition trajectory and checked for significant differences. RESULTSThe angulated acquisition trajectory significantly increased the score for subjective image quality (p<.001) as well as the clinical assessability of pedicle screw position (p<.001) with particularly strong effects on subjective image quality in the vertebral pedicle region (d=1.61). Swivel of the acquisition trajectory significantly improved all queried domains of subjective image quality (p<.001) as well as clinical assessability of pedicle screw position (p<.001). CONCLUSIONSIn this cadaver study, the angulation as well as the swivel of the acquisition trajectory led to a significantly improved image quality in intraoperative 3D imaging (CBCT) with a constant isocenter. The data show that maximizing the angulation/swivel angle towards 30°/25° provides the best tested subjective image quality and enhances clinical assessability. Therefore, a correct adjustment of the acquisition trajectory can help to make intraoperative revision decisions more reliably. CLINICAL SIGNIFICANCEThe knowledge of enhanced image quality by changing the acquisition trajectory in intraoperative 3D imaging can be used for the assessment of critical screw positions in spine surgery. The implementation of this knowledge requires only a minor change of the current intraoperative imaging workflow without additional technical equipment and could further reduce the need for revision surgery.