Object Detection as Probabilistic Set Prediction

Accurate uncertainty estimates are essential for deploying deep object detectors in safety-critical systems. The development and evaluation of probabilistic object detectors have been hindered by shortcomings in existing performance measures, which tend to involve arbitrary thresholds or limit the detector’s choice of distributions. In this work, we propose to view object detection as a set prediction task where detectors predict the distribution over the set of objects. Using the negative log-likelihood for random finite sets, we present a proper scoring rule for evaluating and training probabilistic object detectors. The proposed method can be applied to existing probabilistic detectors, is free from thresholds, and enables fair comparison between architectures. Three different types of detectors are evaluated on the COCO dataset. Our results indicate that the training of existing detectors is optimized toward non-probabilistic metrics. We hope to encourage the development of new object detectors that can accurately estimate their own uncertainty. Code at\ua0https://github.com/georghess/pmb-nll

Renate Maschwitz, Christoph F. Müller, Hans-Peter Waldhoff (Hrsg.): Die Kunst der Mehrstimmigkeit – Gruppenanalyse als Modell für die Zivilisierung von Konflikten: Psychosozial-Verlag, Giessen, 2009

Buchbesprechun

Prospective long-term evaluation of incomplete distal renal tubular acidosis in idiopathic calcium nephrolithiasis diagnosed by low-dose NH4CL loading - gender prevalences and impact of alkali treatment

Purpose: Prospective evaluation of the prevalence of incomplete distal renal tubular acidosis (idRTA) in idiopathic calcium stone formers (ICSF) diagnosed by half-dose ammonium chloride loading (NH4Cl, 0.05 g/kg body weight/day) and impact of alkali treatment of idRTA. Methods: Evaluation of 386 consecutive idiopathic calcium stone formers (ICSF) (280 males, 106 females) for idRTA. If screening fasting urine pH was > 5.80, 1-day NH4Cl loading was performed without severe adverse effects. Normally, urine pH falls below 5.45. Results: Sixty-four idiopathic calcium stone formers exhibited idRTA, one complete dRTA. Prevalence was higher in women (25.4%) than in men (13.6%). Thus, for more equilibrated comparisons, we formed pairs of 62 idiopathic calcium stone formers (ICSF) with and 62 without idRTA, matched for gender, age, BMI and serum creatinine. Idiopathic calcium stone formers with idRTA more often had hypercalciuria (p < 0.025) and urine citrate < 2 mmol/d (p < 0.05), formed calcium phosphate stones more frequently, exhibited higher numbers of stones/year (1.4 ± 1.5 vs. 0.9 ± 0.8, p = 0.034) and 2.5 times more intrarenal calcifications (4.6 ± 5.9 vs. 1.8 ± 3.6, p = 0.002). All idiopathic calcium stone formers with idRTA were recommended chronic alkali therapy. After 4-15 years of follow-up, stone events /years follow-up (stone passage or urologic intervention) were higher in patients non-adherent to alkali therapy (0.61 ± 0.92) than in patients adherent to treatment (0.11 ± 0.21, p = 0.006). Conclusion: Incomplete distal renal tubular acidosis is 1.8-fold more prevalent among female idiopathic calcium stone formers, predicts more stone recurrences, predisposes to calcium phosphate stones and is associated with 2.5 times more intrarenal calcifications vs. non-idRTA patients. Chronic alkali treatment reduces clinical stone recurrences by 5.5 times. Keywords: Effects of alkali treatment; Gender prevalences; Incomplete distal renal tubular acidosis in idiopathic calcium nephrolithiasis; Intrarenal calcifications; Nephrocalcinosis

Совершенствование конструкции подвижной рамы стартового устройства геохода

Рассмотрено новое решение подвижной рамы стартовой установки геохода. Спроектирован подвижный упор для элементов противовращения. Приведен результат прочностного расчета подвижного упора.A new solution of the mobile frame of the starting installation of the geodatabase is considered. A movable stop for anti-rotation elements has been designed. The result of the strength calculation of the movable stop is given

LidarCLIP or: How I Learned to Talk to Point Clouds

Research connecting text and images has recently seen several breakthroughs, with models like CLIP, DALL-E 2, and Stable Diffusion. However, the connection between text and other visual modalities, such as lidar data, has received less attention, prohibited by the lack of text-lidar datasets. In this work, we propose LidarCLIP, a mapping from automotive point clouds to a pre-existing CLIP embedding space. Using image-lidar pairs, we supervise a point cloud encoder with the image CLIP embeddings, effectively relating text and lidar data with the image domain as an intermediary. We show the effectiveness of LidarCLIP by demonstrating that lidar-based retrieval is generally on par with image-based retrieval, but with complementary strengths and weaknesses. By combining image and lidar features, we improve upon both single-modality methods and enable a targeted search for challenging detection scenarios under adverse sensor conditions. We also explore zero-shot classification and show that LidarCLIP outperforms existing attempts to use CLIP for point clouds by a large margin. Finally, we leverage our compatibility with CLIP to explore a range of applications, such as point cloud captioning and lidar-to-image generation, without any additional training. Code and pre-trained models are available at https://github.com/atonderski/lidarclip

A phase I/II trial to evaluate the safety, feasibility and activity of salvage therapy consisting of the mTOR inhibitor Temsirolimus added to standard therapy of Rituximab and DHAP for the treatment of patients with relapsed or refractory diffuse large cell B-Cell lymphoma - the STORM trial

Background: The current standard treatment of patients with relapsed or refractory diffuse large cell B-Cell lymphoma (DLBCL) primarily consists of intensified salvage therapy and, if the disease is chemo-sensitive, high dose therapy followed with autologous stem cell transplantation. In the rituximab era however, this treatment approach has shown only limited benefit. In particular, patients relapsing after rituximab-containing primary treatment have an adverse prognosis, especially if this occurs within the first year after therapy or if the disease is primarily refractory. Therefore there is an ultimate need for improved salvage treatment approaches. Methods/design: The STORM study is a prospective, multicentre phase I/II study to evaluate the safety, feasibility and activity of salvage therapy consisting of the mTOR inhibitor temsirolimus added to the standard therapy rituximab and DHAP for the treatment of patients with relapsed or refractory DLBCL. The primary objective of the phase I of the trial is to establish the maximum tolerated dose (MTD) of temsirolimus in combination with rituximab and DHAP. The secondary objective is to demonstrate that stem cells can be mobilized during this regimen in patients scheduled to proceed to high dose therapy. In phase II, the previously established maximum tolerated dose of temsirolimus will be used. The primary objective is to evaluate the overall response rate (ORR) in patients with relapsed DLBCL. The secondary objective is to evaluate progression free survival (PFS), overall survival (OS) and toxicity. The study will be accompanied by an analysis of lymphoma subtypes determined by gene expression analysis (GEP). Discussion: The STORM trial evaluates the safety, feasibility and activity of salvage therapy consisting of the mTOR inhibitor temsirolimus added to standard therapy of rituximab and DHAP for the treatment of patients with relapsed or refractory DLBCL. It also might identify predictive markers for this treatment modality

Biocomputational prediction of non-coding RNAs in model cyanobacteria

<p>Abstract</p> <p>Background</p> <p>In bacteria, non-coding RNAs (ncRNA) are crucial regulators of gene expression, controlling various stress responses, virulence, and motility. Previous work revealed a relatively high number of ncRNAs in some marine cyanobacteria. However, for efficient genetic and biochemical analysis it would be desirable to identify a set of ncRNA candidate genes in model cyanobacteria that are easy to manipulate and for which extended mutant, transcriptomic and proteomic data sets are available.</p> <p>Results</p> <p>Here we have used comparative genome analysis for the biocomputational prediction of ncRNA genes and other sequence/structure-conserved elements in intergenic regions of the three unicellular model cyanobacteria <it>Synechocystis </it>PCC6803, <it>Synechococcus elongatus </it>PCC6301 and <it>Thermosynechococcus elongatus </it>BP1 plus the toxic <it>Microcystis aeruginosa </it>NIES843. The unfiltered numbers of predicted elements in these strains is 383, 168, 168, and 809, respectively, combined into 443 sequence clusters, whereas the numbers of individual elements with high support are 94, 56, 64, and 406, respectively. Removing also transposon-associated repeats, finally 78, 53, 42 and 168 sequences, respectively, are left belonging to 109 different clusters in the data set. Experimental analysis of selected ncRNA candidates in <it>Synechocystis </it>PCC6803 validated new ncRNAs originating from the <it>fabF-hoxH </it>and <it>apcC-prmA </it>intergenic spacers and three highly expressed ncRNAs belonging to the Yfr2 family of ncRNAs. Yfr2a promoter-<it>luxAB </it>fusions confirmed a very strong activity of this promoter and indicated a stimulation of expression if the cultures were exposed to elevated light intensities.</p> <p>Conclusion</p> <p>Comparison to entries in Rfam and experimental testing of selected ncRNA candidates in <it>Synechocystis </it>PCC6803 indicate a high reliability of the current prediction, despite some contamination by the high number of repetitive sequences in some of these species. In particular, we identified in the four species altogether 8 new ncRNA homologs belonging to the Yfr2 family of ncRNAs. Modelling of RNA secondary structures indicated two conserved single-stranded sequence motifs that might be involved in RNA-protein interactions or in the recognition of target RNAs. Since our analysis has been restricted to find ncRNA candidates with a reasonable high degree of conservation among these four cyanobacteria, there might be many more, requiring direct experimental approaches for their identification.</p

Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning

Multitarget Tracking (MTT) is the problem of tracking the states of an unknown number of objects using noisy measurements, with important applications to autonomous driving, surveillance, robotics, and others. In the model-based Bayesian setting, there are conjugate priors that enable us to express the multi-object posterior in closed form, which could theoretically provide Bayes-optimal estimates. However, the posterior involves a super-exponential growth of the number of hypotheses over time, forcing state-of-the-art methods to resort to approximations for remaining tractable, which can impact their performance in complex scenarios. Model-free methods based on deep-learning provide an attractive alternative, as they can, in principle, learn the optimal filter from data, but to the best of our knowledge were never compared to current state-of-the-art Bayesian filters, specially not in contexts where accurate models are available. In this paper, we propose a high-performing deep-learning method for MTT based on the Transformer architecture and compare it to two state-of-the-art Bayesian filters, in a setting where we assume the correct model is provided. Although this gives an edge to the model-based filters, it also allows us to generate unlimited training data. We show that the proposed model outperforms state-of-the-art Bayesian filters in complex scenarios, while matching their performance in simpler cases, which validates the applicability of deep-learning also in the model-based regime. The code for all our implementations is made available at https://github.com/JulianoLagana/MT3 .Comment: 8 pages, 4 figure