Collaborative SLAM with Convolutional Neural Network-based Descriptor for Inter-Map Loop Closure Detection

This paper introduces a novel Collaborative Si-multaneous Localization and Mapping (CSLAM) framework, enhanced with a Histogram of Oriented Gradients (HOG) de-scriptor, to improve Inter-Map Loop Closure Detection. Our framework stands out by integrating a convolutional neural network-based loop closure detection, employing the HOG de-scriptor for enhanced illumination robustness, and utilizing collaborative mapping from multiple robotic agents for refined pose estimations and mapping precision. Tested in diverse real-world fields, particularly for landmine detection, the framework demonstrates superior robustness and accuracy, outperforming the existing CCM-SLAM model. Additionally, it incorporates a transformation matrix from visual SLAM for LiDAR Point Clouds correction, showcasing its efficacy in 3D mapping and localization in GNSS-denied settings. Our results indicate that incorporating the CALC descriptor within a CSLAM system significantly enhances loop closure detection and mapping precision, marking a significant step forward in autonomous cooperative navigation and mapping in challenging environment

MNCs’ Intermediate Units and Their Choice of Control Mechanisms

This paper analyzes how MNCs’ intermediate units—those that exercise authority over other subsidiaries—apply specific control mechanisms: centralization, formalization, outcome control, and socialization. We combine agency and network theory to explain how intermediate units’ dual agency role—as both principal and agent— and their network embeddedness form the choice of control mechanisms. More specifically, we propose hypotheses on how the intermediate units’ internal and external relationships determine their choice of control mechanism. We study this issue in the context of Spanish intermediate units —owned by European MNCs— that exercise authority over subsidiaries in Latin America

Can toll prices changes affect the housing market? The case of the Severn crossing toll removal

Purpose Since 1966, the Severn crossing has been connecting England and Wales. In January 2018, its ownership returned to the UK Government, and this marked the start of a toll-free journey across the two countries and made commuting between the regions more affordable. In this paper, we examine the impact of the toll removal on the property market. Design/methodology/approach We employ property-level data from the Land Registry and a difference-in-differences (DiD) empirical model for the periods 2016–2018 and 2019–2021 to capture the pre- and post-toll removal dynamics. The DiD estimation allows us to examine the causal relationship between policy changes and property prices. Findings Our findings suggest that property prices in Newport and Monmouthshire (South East Wales) are positively affected by the policy, which results in a statistically significant increase of 5.8% more than those located in the South West England (Bristol and South Gloucestershire) region in the period 2019–2021. The impact can reach up to 13.1% for properties located in a 10 km radius of the bridge. The results indicate that the toll removal enables the ripple effect across the two markets by reducing commuting costs. Originality/value This is the first paper that examines the Severn Crossing case study. Its contribution is significant since we provide empirical evidence on how reduced transportation costs increase property prices in the lowest income region and have the opposite effect on the area with higher incomes and economic activity levels

Three Approaches for Winning the Platform Competition

The notion of platforms isn't novel, yet digital platforms have become the dominant business models across various industries. Today, many of the world's most valuable companies are platform-based, deriving their success from disrupting conventional businesses and innovating new products and services in emerging areas. Digital platforms are not exclusive to tech giants or digital startups. Companies in established sectors, such as banking, automotive, pharmaceuticals, airlines, and retail, are increasingly leveraging digital platforms to transform their operations and industries, with many already delivering remarkable results. Digital platforms are fundamentally reshaping strategy and competition. Unlike traditional manufacturing or product-centric organizations, the unique attributes of platforms, like network effects and winner-takes-all market dynamics, create a fiercely competitive environment, making it particularly challenging when competing against platform leaders with formidable capabilities and resources and dominant market positions. This study delves into critical questions: What are the main strategies used by platforms to gain market dominance? How do emerging platforms challenge and overtake established ones? Under what conditions are these strategies successful? Addressing these questions is essential for business leaders, entrepreneurs, and policymakers, and they constitute the central focus of this research

Health-related quality of life among adult patients with cancer in Uganda – a cross-sectional study

Objectives The study aimed to investigate the prevalence and factors associated with poor health-related quality of life in adults with cancer in Uganda. Methods This cross-sectional study surveyed 385 adult patients (95% response rate) with various cancers at a specialised oncology facility in Uganda. Health-related quality of life was measured using the EORTC QLQ-C30 in the Luganda and English languages. Predetermined validated clinical thresholds were applied to the instrument in order to identify patients with poor health-related quality of life, that is, functional impairments or symptoms warranting concern. Multivariable logistic regression was used to identify factors associated with poor health-related quality of life in six subscales: Physical Function, Role Function, Emotional Function, Social Function, Pain and Fatigue. Results The mean age of the patients was 48 years. The majority self-reported poor functioning ranging between 61% (Emotional Function) to 79% (Physical Function) and symptoms (Fatigue 63%, Pain 80%) at clinically concerning levels. These patients were more likely to be older, without formal education and not currently working. Being an inpatient at the facility and being diagnosed with cervical cancer or leukaemia was a predictor of poor health-related quality of life. Conclusion Improvement of cancer care in East Africa requires a comprehensive and integrated approach that addresses various challenges specific to the region. Such strategies include investment in healthcare infrastructure, for example, clinical guidelines to improve pain management, and patient education and support services

He Said, She Said: Gender Differences in the Disclosure of Positive and Negative Information

Research on gender differences in (self-)disclosure has produced mixed results, and, where differences have emerged, they may be an artifact of the measures employed. The present paper explores whether gender – defined as self-identified membership in one’s sociocultural group – can indeed account for differences in the desire and propensity to divulge information to others. We additionally identify a possible moderator for such differences. In three studies employing two distinct research approaches – a free recall task for the extreme desire to disclose (Study 1, N = 195) and scaled responses to scenarios that manipulate valence experimentally in an exploratory study (Study 2, N = 547) and a preregistered replication (Study 3, N = 405) – we provide evidence of a robust interaction between gender and information valence. Male participants appear similar to female participants in their desire and likelihood to disclose positive information but are less likely than women to want to share negative information with others, and less likely to ultimately act on that desire. Men are reportedly more motivated than women to disclose as a means of self-enhancement, and self-reports reveal that women perceive their sharing behavior to be relatively normative, while men believe themselves to be more withholding than what is optimal. Information disclosure is increasingly pervasive and permanent in the digital age, and is accompanied by an array of social and psychological consequences. Given their disparate disclosing behaviors, men and women may thus be differentially advantaged by, or susceptible to, the positive and negative consequences of information sharing

MIM-OOD: Generative Masked Image Modelling for Out-of-Distribution Detection in Medical Images

Unsupervised Out-of-Distribution (OOD) detection consists in identifying anomalous regions in images leveraging only models trained on images of healthy anatomy. An established approach is to tokenize images and model the distribution of tokens with Auto-Regressive (AR) models. AR models are used to 1) identify anomalous tokens and 2) in-paint anomalous representations with in-distribution tokens. However, AR models are slow at inference time and prone to error accumulation issues which negatively affect OOD detection performance. Our novel method, MIM-OOD, overcomes both speed and error accumulation issues by replacing the AR model with two task-specific networks: 1) a transformer optimized to identify anomalous tokens and 2) a transformer optimized to in-paint anomalous tokens using masked image modelling (MIM). Our experiments with brain MRI anomalies show that MIM-OOD substantially outperforms AR models (DICE 0.458 vs 0.301) while achieving a nearly 25x speedup (9.5 s vs 244 s)

Surface gravity wave-induced drift of floating objects in the diffraction regime

Floating objects will drift due to the action of surface gravity waves. This drift will depart from that of a perfect Lagrangian tracer due to both viscous effects (non-potential flow) and wave–body interaction (potential flow). We examine the drift of freely floating objects in regular (non-breaking) deep-water wave fields for object sizes that are large enough to cause significant diffraction. Systematic numerical simulations are performed using a hybrid numerical solver, qaleFOAM, which deals with both viscosity and wave–body interaction. For very small objects, the model predicts a wave-induced drift equal to the Stokes drift. For larger objects, the drift is generally greater and increases with object size (we examine object sizes up to 10% of the wavelength). The effects of different shapes, sizes and submergence depths and steepnesses are examined. Furthermore, we derive a ‘diffraction-modified Stokes drift’ akin to Stokes (Trans. Camb. Phil. Soc., vol. 8, 1847, pp. 411–455), but based on the combination of incident, diffracted and radiated wave fields, which are based on potential-flow theory and obtained using the boundary element method. This diffraction-modified Stokes drift explains both qualitatively and quantitatively the increase in drift. Generally, round objects do not diffract the wave field significantly and do not experience a significant drift enhancement as a result. For box-shape objects, drift enhancement is greater for larger objects with greater submergence depths (we report an increase of 92% for simulations without viscosity and 113% with viscosity for a round-cornered box whose size is 10% of the wavelength). We identify the specific standing wave pattern that arises near the object because of diffraction as the main cause of the enhanced drift. Viscosity plays a small positive role in the enhanced drift behaviour of large objects, increasing the drift further by approximately 20%