The adoption of Autonomous Mobile Robots (AMRs) for internal logistics is accelerating, with most solutions emphasizing decentralized, onboard intelligence. While AMRs in indoor environments like factories can be supported by infrastructure, involving external sensors and computational resources, such systems remain underexplored in the literature. This paper presents a comprehensive overview of infrastructure-based AMR systems, outlining key opportunities and challenges. To support this, we introduce a reference architecture combining infrastructure-based sensing, on-premise cloud computing, and onboard autonomy. Based on the architecture, we review core technologies for localization, perception, and planning. We demonstrate the approach in a real-world deployment in a heavy-vehicle manufacturing environment and summarize findings from a user experience (UX) evaluation. Our aim is to provide a holistic foundation for future development of scalable, robust, and human-compatible AMR systems in complex industrial environments.
In this note we generalize the results of the recent work by Tom Bohman and Jakob Hofstad on the independence number in G(n,p) to the case of the random k-uniform hypergraph. The weak independence number is concentrated on two values for p>n−(k−1)kk+1+ε. This bound is roughly optimal, as such concentration is generally not observed when p=o(n−(k−1)kk+1log2k+1n).
In this paper we consider C1 diffeomorphisms on compact Riemannian manifolds admitting a dominated splitting Ecs⊕Ecu. First, we prove that the smallest Lyapunov exponent along Ecu, computed with respect to the Lebesgue measure, is computable using observable measures. Then we show that if the Lyapunov exponents along Ecu are positive Lebesgue almost everywhere and Ecu admits a finest 1-dominated splitting on the support of an ergodic observable measure then f is non-uniformly expanding along Ecu. As a byproduct, every C1+α diffeomorphism exhibiting a dominated splitting Es⊕Ecu where Ecu fulfills the previous assumptions admits an SRB measure.
Introduction: Anal squamous cell carcinoma (ASCC) is rare, and optimal treatment for patients unsuitable for definitive chemoradiotherapy remains undefined. This study describes PACTUS (Palliative Anal Cancer Treatment Uppsala Style), a two-week radiotherapy regimen designed for symptom relief and potentially durable local control. Methods: We retrospectively reviewed consecutive patients with ASCC treated with palliative-intent radiotherapy at Uppsala University Hospital (2017-2025). The principal cohort received PACTUS (40 Gy in 10 fractions). Patients treated with Short-course or Quad Shot were included as contextual case series. Treatment selection was based on patient fitness, anticipated tolerance, prognosis, logistics, and patient preference. Overall survival (OS) was measured from radiotherapy initiation. Clinical response, symptom outcomes, and adverse effects were summarized using evaluable denominators. Results: Of 735 patients treated for ASCC, 35 (4.7%) received palliative-intent radiotherapy: 28 received PACTUS, 4 Short-course, and 3 Quad Shot. The median age was 80 years (range, 60-97), 25 (71%) were women, and 30 (86%) had an ECOG performance status >= 3. Elective nodal irradiation was delivered to 24/28 patients in PACTUS. The median OS in PACTUS cohort was 30 months. At the data cut-off (April 2, 2026), 20 patients had died: 14/28 (50%) in PACTUS, 4/4 (100%) in Short-course, and 2/3 (67%) in Quad Shot. Median follow-up among surviving patients was 20 months (range, 4-71 months). Clinical response was evaluable in 15/35 (43%) patients and symptom outcomes in 13/35 (37%); therefore, these findings were not considered representative of the full cohort. Toxicity was not collected systematically or graded prospectively. Conclusions: PACTUS was feasible in this selected cohort of predominantly elderly and comorbid patients and warrants prospective evaluation. However, because treatment selection was guided by patient fitness and anticipated treatment tolerance, comparisons between the alternative regimens are descriptive only and cannot establish comparative effectiveness or a survival benefit.
This chapter examines the contemporary Russian writer Maria Stepanova’s autobiographical prose work In Memory of Memory ( Pamiati pamiati , 2017). Stepanova’s hybrid text depicts the author’s search for information about her family history over the course of the long twentieth century. The chapter considers three levels within the text: 1) documentary material, 2) literary narrative about the documentary project, and 3) meta-commentary on memory and the documentary process. The analysis applies insights from cognitive theory, arguing that In Memory of Memory builds a documentary mode into the reading process.
