Robustor3D: robust multimodal 3D object detector for autonomous driving by vision-language knowledge blending

Multimodal 3D object detection for autonomous driving, a task for real-world application, poses substantial challenges in maintaining robust performance under various perturbations and complex environmental conditions. However, most existing approaches primarily focus on performance optimization under relatively ideal scenarios or focus on one or few disturbing conditions (interference or adverse conditions), lacking systematic exploration of robustness against real-world factors, including high class imbalance, adverse weather conditions, sensor jitter and failures, and significant scene variations. To address this issue, we propose a robust multimodal 3D detector, termed RobusTor3D, which integrates robustness at both the structural and supervisory levels by blending the knowledge from Vision-Language Models(VLMs). Structurally, textual descriptions are incorporated to enhance the semantic richness and diversity of rare classes. This novel semantic injection operation compensates for the inherent class imbalance and modality weakness in conventional visual features. Furthermore, semantic alignment capability and robust representation by Vision-Language Knowledge Extraction (V-LKE) serve as semantic priors to complement modality-specific representations, significantly improving model adaptability. At the supervisory level, we propose a Scene-level Multimodal Consistency Learning (SMCL) strategy, which jointly enforces global semantic constraints across modalities, encouraging the learning of stable and abundant semantic representations. This special design specifically reduces the impact of spatial alignment, while notably enabling semantic compensation under modality-loss conditions. Extensive robustness experiments conducted on KITTI, KITTIC, and CADC benchmarks evaluate five robustness aspects, including long-tail problem, adverse weather (rain, snow, fog, strong sunlight), sensor spatial misalignment and motion blur, modality loss, and cross-domain scenarios. The results show that the proposed RobusTor3D demonstrates superior robustness across all five evaluated aspects. It consistently outperforms the state-of-the-art methods under various challenging conditions

The double life of a Palestinian translator: A bridge between wounds and words

Dit betoog beschouwt het vertalen van Gazaanse verhalen als een vorm van getuigenis afleggen over een wereld die dreigt te verdwijnen, waarbij taal zowel een overlevingsmiddel als een strijdtoneel wordt. In het licht van voortdurende pogingen tot het monddood maken en uitroeien van het Palestijne volk, bevindt de Palestijnse vertaler zich in een tussenpositie waarin hij/zij het verdriet van dat huidige moment, zoals geuit in alle intensiteit van het Arabisch, dient te vertalen naar een taal die zaken vaak onpersoonlijk, emotieloos en gecensureerd uitdrukt, en wellicht nooit is ontworpen om dergelijke mate van verwoesting te kunnen omvatten. Dit betoog reflecteert op de ethische kant van het vertalen van verhalen die zijn geboren temidden van het puin, van getuigenissen die zijn gevormd tussen luchtaanvallen, tussen herinneringen en de dreiging van stilte. Elk te vertalen woord moet een terrein doorkruisen dat vol ligt met machtsrelaties, taalkundige verhullingen of verbloemingen, en onverschilligheid. Dit dwingt de vertaler om de dunne lijn te bewandelen tussen enerzijds het afzwakken van menselijk verdriet ten behoeve van de leesbaarheid van de vertaling, en anderzijds het behouden van de urgentie ervan in een taal die in de regel menselijk lijden op geneutraliseerde wijze communiceert. Uitgaande van de Palestijnse ervaring, stelt dit betoog dat vertalen niet langer slechts een linguïstische oefening betreft, maar een politieke en morele taak, beladen met de verantwoordelijkheid om normalisering van gewelddadige bezetting en volksuitroeiing tegen te gaan, alsmede het scheppen van ruimte voor stemmen van hen die misschien niet meer leven als hun zinnen zijn uitgesproken. Tijdens het vertalen van Palestijnse bronnen draagt de vertaler niet alleen betekenis over, maar probeert tegelijkertijd ook Palestijns leven, autonomie en erfgoed te behouden in een wereld die daar vaak pas aandacht voor heeft als een te laat is

Hierarchical human activity recognition with fusion of audio and multiple inertial sensor modalities

In everyday life, individuals engage in a multitude of activities, and recent technological advancements have facilitated the development of Artificial Intelligence systems that analyse these activities through data in various contexts. Human activity recognition, an essential Artificial Intelligence application in healthcare, detects deviations from normal activities, such as falls, which may indicate health issues. The widespread adoption of mobile and wearable technology enables the development of personalized activity recognition solutions. Given the critical importance of these Artificial Intelligence applications in healthcare, designing systems with high recognition accuracy is imperative. Moreover, these systems must be lightweight to ensure they operate seamlessly on end-user devices like smartphones without compromising their primary functions. Our research introduces innovative input representations and advanced methods in data fusion and multimodal learning that surpass previous methods in recognition accuracy while reducing computational and memory demands. We propose a streamlined neural network model that creatively integrates inertial and audio sensor data to generate color-coded image representations. This implemented Artificial Intelligence system was tested using a complex, publicly available activity recognition dataset organized hierarchically. Compared to earlier studies, our solution demonstrates significant performance enhancements, achieving a 91% balanced accuracy rate in activity recognition and offering substantial improvements in Central Processing Unit and memory efficiency

Sampling for non-destructive spectroscopy with a particular focus on agriculture, food and feed

Sampling plays a pivotal role in the analytical process, particularly when employing non-destructive spectroscopic sensors (NDSS). This review bridges Theory of Sampling (ToS) and Design of Experiments (DoE) to address sampling challenges in NDSS agri-food applications. Sampling quality is the primary driver of overall uncertainty, often significantly surpassing laboratory and instrumental errors. Non-destructive spectroscopic setups inherently sample through their optical configurations. We highlight the importance of replication methods to determine sources of variance, particularly in physical sampling procedures, and provide practical guidelines for achieving representative sampling. Additionally, the review briefly discusses computational augmentation and resampling techniques. Practical considerations and case studies from food and feed applications illustrate the constraints and solutions for effective sampling, providing insights for researchers and industry aiming to optimize NDSS measurements.</p

Quantifying inter- and intramolecular interactions in liquids with correlated vibrational spectroscopy: case study of CCl₄ and CH₃CN

Correlated vibrational spectroscopy (CVS) is a hyper-Raman-based vibrational spectroscopy that retrieves separate spectra of individual (self-correlated, SC) and interacting (cross-correlated, CC) molecules. The spectra are recorded in the &gt;40 cm–1 THz/mid-IR frequency range and contain modes that are IR and/or Raman active. Here, we further develop CVS and apply it to investigate intra- and intermolecular interactions using room temperature liquid carbon tetrachloride (CCl4), a nonpolar liquid, and acetonitrile (CH3CN), a polar liquid, as case studies. CVS spectra of CCl4 display no intermolecular coupling, confirming the isotropy and short-range nature of the molecular interactions. Strong intramolecular coupling is observed on the Fermi resonance, and the relative phase between the participating modes is determined based on the intensities in the experimental spectra. CVS spectra of acetonitrile display intermolecular coupling of the C≡N mode vibrations, whose cross-correlated out-of-phase signature is evidence for near-perpendicular pair arrangements. Performing a theoretical analysis of the CVS response, an equation for the effective average orientational angle between C≡N groups of adjacent liquid molecules is developed and solved. The effective average orientational angle between adjacent acetonitrile dipoles is ∼102° ± 2°, which is close to a head-to-tail arrangement

The expression of compassion in leadership in intercultural organizational situations: the case of Japanese leaders in India

In this paper, we examine the role played by compassion in leadership in intercultural situations. Focusing on the growing and important economic context of Indo-Japanese business, we develop a model that identifies contingent factors that affect Japanese leaders' expressions of compassion in intercultural organizational contexts. We engage with the spiritual capital construct and analyse leaders' lived experiences leading to a novel extension of the well-established Nested Spheres Model of Culture. By adopting an inductivist and social constructivist approach, semistructured interviews with Japanese business leaders operating in India are employed to generate data. The empirical data show how changes in time and place cause deeply embedded cultural values (such as compassion) to surface and become more explicit in leadership. The study also underlines the need to explore the wider spatial, temporal, and economic contingencies that affect both the dynamics of compassion in “intercultural” business situations and spiritual leadership in intercultural contexts.<br/

Anglophone political song in eighteenth-century Ireland: the evidence of print

Among the earliest-printed songs in Ireland are the political songs of Dublin’s prosperous English-speaking population—politicians, lawyers, clergy, tradespeople, and gentry. With the political campaigns and controversies which arise across the eighteenth century—particularly the Wood’s halfpence affair (1722–1725), the candidacy of Charles Lucas for a parliamentary seat (1748–1749), and the Volunteer movement (1779–1784)—the printing of partisan song becomes a marked feature of Dublin print culture and, increasingly, that of Irish regions: Belfast, Cork, and Downpatrick, for example. These three political controversies of the eighteenth century can be seen to inaugurate the strong traditions in which print culture bolsters the dissemination of political song, which would proliferate in the revolutionary years of the 1790s and beyond.<br/

Scarring and selection in the Great Irish Famine

How do famines shape the health of survivors? We examine the long-term impact of the Great Irish Famine (1845–1852) on human stature, distinguishing between adverse scarring effects and the apparent resilience of survivors due to selection. Using anthropometric data from over 14,500 individuals born before, during, and after this famine, we find that selection effects were most pronounced in areas with the highest mortality rates. Individuals born in severely affected regions exhibited no evidence of stunted growth, indicating that the Famine disproportionately eliminated the most vulnerable. In contrast, stunting is observed only in areas with lower excess mortality, where selective pressures were weaker. These findings contribute to debates on the biological consequences of extreme catastrophic risks, demonstrating how selection effects can obscure long-term health deterioration. More broadly, our study provides a methodological framework for assessing selection in historical anthropometric research

Epidemic Oracle: an approach to boost security and performance of delay tolerant networks

Delay Tolerant Networks (DTNs) play a vital role in disaster response to address intermittent connectivity, in particular when Unmanned Aerial Vehicles (UAVs) are deployed to relay critical information. However, most existing DTN protocols are highly susceptible to Denial-of-Service (DoS)attacks because their flooding-based or simplistic routing decisions can be exploited by malicious nodes to quickly saturate buffers, exhausting network resources and disrupting legitimate traffic. This paper presents an Epidemic Oracle (EO) implementation, to mitigate DoS threats by intelligently removing delivered messages from all buffers, thus reducing overhead and freeing network resources. Through extensive simulation in the ONE environment, EO is evaluated against three established encounter-based DTN protocols-Epidemic, Spray and Wait, and Spray and Wait Binary-under varying buffer sizes, transmission speeds, and both aggressive and stealthy DoS attacks. The findings indicate that EO substantially increases delivery ratios while curtailing buffer congestion, even under severe adversarial conditions. These improvements highlight the potential of oracle-based interventions to bolster performance in UAV-assisted disaster scenarios, paving the way for more resilient and efficient DTNs in emergency communications