Multimodal Detection of Unknown Objects on Roads for Autonomous Driving

Tremendous progress in deep learning over the last years has led towards a future with autonomous vehicles on our roads. Nevertheless, the performance of their perception systems is strongly dependent on the quality of the utilized training data. As these usually only cover a fraction of all object classes an autonomous driving system will face, such systems struggle with handling the unexpected. In order to safely operate on public roads, the identification of objects from unknown classes remains a crucial task. In this paper, we propose a novel pipeline to detect unknown objects. Instead of focusing on a single sensor modality, we make use of lidar and camera data by combining state-of-the art detection models in a sequential manner. We evaluate our approach on the Waymo Open Perception Dataset and point out current research gaps in anomaly detection

Multimodal Detection of Unknown Objects on Roads for Autonomous Driving

Tremendous progress in deep learning over the last years has led towards a future with autonomous vehicles on our roads. Nevertheless, the performance of their perception systems is strongly dependent on the quality of the utilized training data. As these usually only cover a fraction of all object classes an autonomous driving system will face, such systems struggle with handling the unexpected. In order to safely operate on public roads, the identification of objects from unknown classes remains a crucial task. In this paper, we propose a novel pipeline to detect unknown objects. Instead of focusing on a single sensor modality, we make use of lidar and camera data by combining state-of-the art detection models in a sequential manner. We evaluate our approach on the Waymo Open Perception Dataset and point out current research gaps in anomaly detection.Comment: Daniel Bogdoll, Enrico Eisen, Maximilian Nitsche, and Christin Scheib contributed equally. Accepted for publication at SMC 202

IgE Recognition Patterns of Profilin, PR-10, and Tropomyosin Panallergens Tested in 3,113 Allergic Patients by Allergen Microarray-Based Technology

BACKGROUND: IgE recognition of panallergens having highly conserved sequence regions, structure, and function and shared by inhalant and food allergen sources is often observed. METHODS: We evaluated the IgE recognition profile of profilins (Bet v 2, Cyn d 12, Hel a 2, Hev b 8, Mer a 1, Ole e 2, Par j 3, Phl p 12, Pho d 2), PR-10 proteins (Aln g 1, Api g 1, Bet v 1.0101, Bet v 1.0401, Cor a 1, Dau c 1 and Mal d 1.0108) and tropomyosins (Ani s 3, Der p 10, Hel as 1, Pen i 1, Pen m 1, Per a 7) using the Immuno-Solid phase Allergen Chip (ISAC) microarray system. The three panallergen groups were well represented among the allergenic molecules immobilized on the ISAC. Moreover, they are distributed in several taxonomical allergenic sources, either close or distant, and have a route of exposure being either inhalation or ingestion. RESULTS: 3,113 individuals (49.9% female) were selected on the basis of their reactivity to profilins, PR-10 or tropomyosins. 1,521 (48.8%) patients were reactive to profilins (77.6% Mer a 1 IgE(+)), 1,420 (45.6%) to PR-10 (92.5% Bet v 1 IgE(+)) and 632 (20.3%) to tropomyosins (68% Der p 10 IgE(+)). A significant direct relationship between different representative molecules within each group of panallergens was found. 2,688 patients (86.4%) recognized only one out of the three distinct groups of molecules as confirmed also by hierarchical clustering analysis. CONCLUSIONS: Unless exposed to most of the allergens in the same or related allergenic sources, a preferential IgE response to distinct panallergens has been recorded. Allergen microarray IgE testing increases our knowledge of the IgE immune response and related epidemiological features within and between homologous molecules better describing the patients' immunological phenotypes

Eliciting the Demand for Long Term Care Coverage: A Discrete Choice Modelling Analysis

We evaluate the demand for long term care (LTC) insurance prospects in a stated preference context, by means of the results of a choice experiment carried out on a representative sample of the Emilia-Romagna population. Choice modelling techniques have not been used yet for studying the demand for LTC services. In this paper these methods are first of all used in order to assess the relative importance of the characteristics which define some hypothetical insurance programmes and to elicit the willingness to pay for some LTC coverage prospects. Moreover, thanks to the application of a nested logit specification with partial degeneracy, we are able to model the determinants of the preference for status quo situations where no systematic cover for LTC exists. On the basis of this empirical model, we test for the effects of a series of socio-demographic variables as well as personal and household health state indicators

Sadness at the Rainbow: Unraveling the Unheard Sentiments of Non-Binary Students

The number of individuals identifying as non-binary or genderqueer has significantly increased over time. This group experiences their gender identity as neither entirely male nor exclusively female; instead, they perceive it as a combination or a complete absence of binary gender identification that may evolve or remain consistent over time. Nevertheless, there is a limited amount of research focusing on the experiences of non-binary students, leading to common misunderstandings within their community. Consequently, this study sought to delve into the physical, mental, interpersonal, emotional, and spiritual experiences of non-binary students. To analyze the collected data, a qualitative approach, specifically a narrative research design, was employed. Three students from the Philippine Science High School - Ilocos Region Campus were chosen through snowball sampling to share their personal experiences as non-binary students. Based on the gathered information, it can be concluded that non-binary students in the PSHS-IRC community undergo a range of experiences that significantly affect their physical, mental, interpersonal, emotional, and spiritual well-being. It was observed that they struggle to form a positive self-image due to their dissatisfaction with their physical appearance. Additionally, their body dysmorphia, stemming from a dislike for their bodies perceived as too masculine or feminine, negatively impacts their mental health. Moreover, homophobia continues to disrupt their interpersonal relationships, as they often endure physical, mental, emotional, and spiritual abuse. Nonetheless, they still have support networks that provide ongoing assistance. Lastly, the results also indicate that their faith in Christianity has waned due to relentless verbal attacks from conservative individuals

A Comparative Effectiveness Trial of Depression Collaborative Care: Subanalysis of Comorbid Anxiety

The purpose of this exploratory subanalysis was to compare the effects of two depression quality improvement approaches on clinical outcomes and service utilization for individuals with comorbid depression/anxiety. This study used data from Community Partners in Care (CPIC), a cluster-randomized comparative effectiveness trial (N = 1,018; depression = 360; comorbid depression/anxiety = 658). Each intervention arm received the same quality improvement materials, plus either technical support (Resources for Services, RS) or support for collaborative implementation planning (Community Engagement and Planning, CEP). For the comorbid depression/anxiety subgroup, the collaborative planning arm was superior at improving mental health-related quality of life and mental wellness, as well as decreasing behavioral hospitalizations and homelessness risk at 6 months. The effects were not significant at 12 months. A collaborative planning process versus technical support for depression quality improvement can have short-term effects on mental wellness and social determinants of health among those with comorbid depression/anxiety