Parcel3D: Shape Reconstruction from Single RGB Images for Applications in Transportation Logistics

We focus on enabling damage and tampering detection in logistics and tackle the problem of 3D shape reconstruction of potentially damaged parcels. As input we utilize single RGB images, which corresponds to use-cases where only simple handheld devices are available, e.g. for postmen during delivery or clients on delivery. We present a novel synthetic dataset, named Parcel3D, that is based on the Google Scanned Objects (GSO) dataset and consists of more than 13,000 images of parcels with full 3D annotations. The dataset contains intact, i.e. cuboid-shaped, parcels and damaged parcels, which were generated in simulations. We work towards detecting mishandling of parcels by presenting a novel architecture called CubeRefine R-CNN, which combines estimating a 3D bounding box with an iterative mesh refinement. We benchmark our approach on Parcel3D and an existing dataset of cuboid-shaped parcels in real-world scenarios. Our results show, that while training on Parcel3D enables transfer to the real world, enabling reliable deployment in real-world scenarios is still challenging. CubeRefine R-CNN yields competitive performance in terms of Mesh AP and is the only model that directly enables deformation assessment by 3D mesh comparison and tampering detection by comparing viewpoint invariant parcel side surface representations. Dataset and code are available at https://a-nau.github.io/parcel3d.Comment: Accepted at CVPR workshop on Vision-based InduStrial InspectiON (VISION) 2023, see https://vision-based-industrial-inspection.github.io/cvpr-2023

Predictive value of CA 125 and CA 72-4 in ovarian borderline tumors

Background: The aim of this study was to assess the prognostic value of cancer antigen (CA) 125 and CA 72-4 in patients with ovarian borderline tumor (BOT). Methods: All women diagnosed and treated for BOT at our institution between 1981 and 2008 were included into this retrospective study (n=101). Preoperatively collected serum samples were analyzed for CA 125 (Architect, Abbott and Elecsys, Roche) and CA 724 (Elecsys, Roche) with reference to clinical data and compared to healthy women (n=109) and ovarian cancer patients (n=130). Results: With a median of 34.7 U/mL (range 18.1-385.0 U/mL) for CA 125 and 2.3 U/mL (range 0.2-277.0 U/mL) for CA 72-4, serum tumor markers in BOT patients were significantly elevated as compared to healthy women with a median CA 125 of 13.5 U/mL (range 4.0-49.7 U/mL) and median CA 72-4 of 0.8 U/mL (range 0.2-20.6 U/mL). In addition, there was a significant difference compared with ovarian cancer patients who showed a median CA 125 of 401.5 U/mL (range 12.5-35,813 U/mL), but no difference was observed for CA 72-4 (median 3.9 U/mL, range 0.3-10,068 U/mL). Patients with a pT1a tumor stage had significantly lower values of CA 125 but not of CA 72-4 compared with individuals with higher tumor stages (median CA 125 29.9 U/mL for pT1a vs. 50.9 U/mL for) pT1a; p=0.014). There was a trend for increased concentrations of CA 125 but not of CA 72-4 in the presence of ascites, endometriosis or peritoneal implants at primary diagnosis. With respect to the prognostic value of CA 125 or CA 72-4, CA 125 was significantly higher at primary diagnosis in patients who later developed recurrence (251.0 U/mL vs. 34.65 U/mL, p=0.012). Conclusions: Serum CA 125 and CA 72-4 concentrations in BOT patients differ from healthy controls and patients with ovarian cancer. CA 125, but not CA 724, at primary diagnosis correlates with tumor stage and tends to be increased in the presence of ascites, endometriosis or peritoneal implants. Moreover, CA 125 at primary diagnosis appears to have prognostic value for recurrence. Clin Chem Lab Med 2009; 47:537-42

Scrape, Cut, Paste and Learn: Automated Dataset Generation Applied to Parcel Logistics

State-of-the-art approaches in computer vision heavily rely on sufficiently large training datasets. For real-world applications, obtaining such a dataset is usually a tedious task. In this paper, we present a fully automated pipeline to generate a synthetic dataset for instance segmentation in four steps. In contrast to existing work, our pipeline covers every step from data acquisition to the final dataset. We first scrape images for the objects of interest from popular image search engines and since we rely only on text-based queries the resulting data comprises a wide variety of images. Hence, image selection is necessary as a second step. This approach of image scraping and selection relaxes the need for a real-world domain-specific dataset that must be either publicly available or created for this purpose. We employ an object-agnostic background removal model and compare three different methods for image selection: Object-agnostic pre-processing, manual image selection and CNN-based image selection. In the third step, we generate random arrangements of the object of interest and distractors on arbitrary backgrounds. Finally, the composition of the images is done by pasting the objects using four different blending methods. We present a case study for our dataset generation approach by considering parcel segmentation. For the evaluation we created a dataset of parcel photos that were annotated automatically. We find that (1) our dataset generation pipeline allows a successful transfer to real test images (Mask AP 86.2), (2) a very accurate image selection process - in contrast to human intuition - is not crucial and a broader category definition can help to bridge the domain gap, (3) the usage of blending methods is beneficial compared to simple copy-and-paste. We made our full code for scraping, image composition and training publicly available at https://a-nau.github.io/parcel2d.Comment: Accepted at ICMLA 202

The diagnostic accuracy of two human epididymis protein 4 (HE4) testing systems in combination with CA125 in the differential diagnosis of ovarian masses

Background: Cancer antigen 125 (CA125) is the best known single tumor marker for ovarian cancer (OC). We investigated whether the additional information of the human epididymis protein 4 (HE4) improves diagnostic accuracy. Methods: We retrospectively analyzed preoperative sera of 109 healthy women, 285 patients with benign ovarian masses (cystadenoma: n = 78, leimyoma: n = 66, endometriosis: n = 52, functional ovarian cysts: n = 79, other: n = 10), 16 low malignant potential (LMP) ovarian tumors and 125 OC (stage 1: 22, II: 15, III: 78, IV: 10). CA 125 was analyzed using the ARCHITECT system, HE4 using the ARCHITECT(a) system and EIA(e) technology additionally. Results: The lowest concentrations of CA125 and HE4 were observed in healthy individuals, followed by patients with benign adnexal masses and patients with LMP tumors and OC. The area under the curve (AUC) for the differential diagnosis of adnexal masses of CA 125 alone was not significantly different to HE4 alone in premenopausal (CA 125: 86.7, HE4(a): 82.6, HE4(e): 81.6% p > 0.05) but significantly different in postmenopausal {[}CA125: 93.4 vs. HE4(a): 88.3 p = 0.023 and vs. HE4(e): 87.8% p=0.012] patients. For stage I OC, HE4 as a single marker was superior to CA 125, which was the best single marker in stage H-IV. The combination of CA 125 and HE4 using risk of malignancy algorithm (ROMA) gained the highest sensitivity at 95% specificity for the differential diagnosis of adnexal masses {[}CA 125: 70.9, HE4(a): 67.4, HE4(e): 66.0, ROMA(a): 76.6 and ROMA(e): 74.5%], especially in stage I OC {[}CA 125: 27.3, HE4(a): 40.9, HE4(e): 40.9, ROMA(a): 45.5 and ROMA(e): 45.5%]. Conclusions: CA 125 is still the best single marker in the diagnosis of OC. HE4 alone and even more the combined analysis of CA 125 and HE4 using ROMA improve the diagnostic accuracy of adnexal masses, especially in early OC

Heterogeneous Graph-based Trajectory Prediction using Local Map Context and Social Interactions

Precisely predicting the future trajectories of surrounding traffic participants is a crucial but challenging problem in autonomous driving, due to complex interactions between traffic agents, map context and traffic rules. Vector-based approaches have recently shown to achieve among the best performances on trajectory prediction benchmarks. These methods model simple interactions between traffic agents but don't distinguish between relation-type and attributes like their distance along the road. Furthermore, they represent lanes only by sequences of vectors representing center lines and ignore context information like lane dividers and other road elements. We present a novel approach for vector-based trajectory prediction that addresses these shortcomings by leveraging three crucial sources of information: First, we model interactions between traffic agents by a semantic scene graph, that accounts for the nature and important features of their relation. Second, we extract agent-centric image-based map features to model the local map context. Finally, we generate anchor paths to enforce the policy in multi-modal prediction to permitted trajectories only. Each of these three enhancements shows advantages over the baseline model HoliGraph.Comment: Accepted on IEEE ITSC 202

Coexistence of adenomyosis uteri and endometrial cancer is associated with an improved prognosis compared with endometrial cancer only

The present study aimed to identify differences in protein expression in cases of endometrioid endometrial cancer (EEC) with and without coexisting adenomyosis uteri (AM), and to evaluate the histopathological and prognostic distinctions. The total cohort included 22 patients in Group A (patients with concomitant AM and EEC) and 35 patients in Group B (patients affected only by EEC). Evaluation of the following factors was performed: Tumour grade, International Federation of Gynaecology and Obstetrics (FIGO) stage, survival, and expression of estrogen receptor beta (ER beta), glycodelin and inhibin beta B. Group A (AM and EEC) was associated with a lower tumour grade (G1, 90.9 vs. 45.7%;P=0.001) and a lower FIGO stage (FIGO stage I, 100 vs. 80%;P=0.002) compared with Group B (EEC only). In the survival analysis, Group A was associated with a significantly higher 5-year survival rate (95 vs. 82%;P=0.024) than Group B. In addition, the expression of ER beta in Group A was significantly higher (P<0.001), whereas the expression of glycodelin is significantly lower (P=0.028), compared with Group B. The results of the present study indicate that the presence of AM in cases of EEC may be a positive prognostic factor

IκBβ acts to inhibit and activate gene expression during the inflammatory response

The activation of pro-inflammatory gene programs by nuclear factor-κB (NF-κB) is primarily regulated through cytoplasmic sequestration of NF-κB by the inhibitor of κB (IκB) family of proteins1. IκBβ, a major isoform of IκB, can sequester NF-κB in the cytoplasm2, although its biological role remains unclear. Although cells lacking IκBβ have been reported3, 4, in vivo studies have been limited and suggested redundancy between IκBα and IκBβ5. Like IκBα, IκBβ is also inducibly degraded; however, upon stimulation by lipopolysaccharide (LPS), it is degraded slowly and re-synthesized as a hypophosphorylated form that can be detected in the nucleus6, 7, 8, 9, 10, 11. The crystal structure of IκBβ bound to p65 suggested this complex might bind DNA12. In vitro, hypophosphorylated IκBβ can bind DNA with p65 and c-Rel, and the DNA-bound NF-κB:IκBβ complexes are resistant to IκBα, suggesting hypophosphorylated, nuclear IκBβ may prolong the expression of certain genes9, 10, 11. Here we report that in vivo IκBβ serves both to inhibit and facilitate the inflammatory response. IκBβ degradation releases NF-κB dimers which upregulate pro-inflammatory target genes such as tumour necrosis factor-α (TNF-α). Surprisingly, absence of IκBβ results in a dramatic reduction of TNF-α in response to LPS even though activation of NF-κB is normal. The inhibition of TNF-α messenger RNA (mRNA) expression correlates with the absence of nuclear, hypophosphorylated-IκBβ bound to p65:c-Rel heterodimers at a specific κB site on the TNF-α promoter. Therefore IκBβ acts through p65:c-Rel dimers to maintain prolonged expression of TNF-α. As a result, IκBβ^(−/−) mice are resistant to LPS-induced septic shock and collagen-induced arthritis. Blocking IκBβ might be a promising new strategy for selectively inhibiting the chronic phase of TNF-α production during the inflammatory response

Induced Pluripotent Stem Cell-Derived Brain Endothelial Cells as a Cellular Model to Study Neisseria meningitidis Infection

Meningococcal meningitis is a severe central nervous system infection that occurs when Neisseria meningitidis (Nm) penetrates brain endothelial cells (BECs) of the meningeal blood-cerebrospinal fluid barrier. As a human-specific pathogen, in vivo models are greatly limited and pose a significant challenge. In vitro cell models have been developed, however, most lack critical BEC phenotypes limiting their usefulness. Human BECs generated from induced pluripotent stem cells (iPSCs) retain BEC properties and offer the prospect of modeling the human-specific Nm interaction with BECs. Here, we exploit iPSC-BECs as a novel cellular model to study Nm host-pathogen interactions, and provide an overview of host responses to Nm infection. Using iPSC-BECs, we first confirmed that multiple Nm strains and mutants follow similar phenotypes to previously described models. The recruitment of the recently published pilus adhesin receptor CD147 underneath meningococcal microcolonies could be verified in iPSC-BECs. Nm was also observed to significantly increase the expression of pro-inflammatory and neutrophil-specific chemokines IL6, CXCL1, CXCL2, CXCL8, and CCL20, and the secretion of IFN-γ and RANTES. For the first time, we directly observe that Nm disrupts the three tight junction proteins ZO-1, Occludin, and Claudin-5, which become frayed and/or discontinuous in BECs upon Nm challenge. In accordance with tight junction loss, a sharp loss in trans-endothelial electrical resistance, and an increase in sodium fluorescein permeability and in bacterial transmigration, was observed. Finally, we established RNA-Seq of sorted, infected iPSC-BECs, providing expression data of Nm-responsive host genes. Altogether, this model provides novel insights into Nm pathogenesis, including an impact of Nm on barrier properties and tight junction complexes, and suggests that the paracellular route may contribute to Nm traversal of BECs

Self-oscillating geometric pump in a dissipative atom-cavity system

Pumps are transport mechanisms in which direct currents result from a cycling evolution of the potential. As Thouless has shown, the pumping process can have topological origins, when considering the motion of quantum particles in spatially and temporally periodic potentials. However, the periodic evolution that drives these pumps has always been assumed to be imparted from outside, as was the case in the experimental systems studied so far. Here we report on an emergent mechanism for geometric pumping in a quantum gas coupled to an optical resonator, where we observe a particle current without applying a periodic drive. The pumping potential experienced by the atoms is formed by the self-consistent cavity field interfering with the static laser field driving the atoms. Due to dissipation, the cavity field evolves between its two quadratures, each corresponding to a different centrosymmetric crystal configuration. This self-oscillation results in a time periodic potential analogous to that in a Rice-Mele pump. In the experiment, we directly follow the evolution by measuring the phase winding of the cavity field with respect to the driving field and observing the atomic motion in-situ. The discovered mechanism combines the dynamics of topological and open systems.Comment: 10 pages, 7 figure