Classical Out-of-Distribution Detection Methods Benchmark in Text Classification Tasks

State-of-the-art models can perform well in controlled environments, but they often struggle when presented with out-of-distribution (OOD) examples, making OOD detection a critical component of NLP systems. In this paper, we focus on highlighting the limitations of existing approaches to OOD detection in NLP. Specifically, we evaluated eight OOD detection methods that are easily integrable into existing NLP systems and require no additional OOD data or model modifications. One of our contributions is providing a well-structured research environment that allows for full reproducibility of the results. Additionally, our analysis shows that existing OOD detection methods for NLP tasks are not yet sufficiently sensitive to capture all samples characterized by various types of distributional shifts. Particularly challenging testing scenarios arise in cases of background shift and randomly shuffled word order within in domain texts. This highlights the need for future work to develop more effective OOD detection approaches for the NLP problems, and our work provides a well-defined foundation for further research in this area.Comment: 11 pages, 3 figures, Association for Computational Linguistic

MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation

NeRF is a popular model that efficiently represents 3D objects from 2D images. However, vanilla NeRF has some important limitations. NeRF must be trained on each object separately. The training time is long since we encode the object's shape and color in neural network weights. Moreover, NeRF does not generalize well to unseen data. In this paper, we present MultiPlaneNeRF -- a model that simultaneously solves the above problems. Our model works directly on 2D images. We project 3D points on 2D images to produce non-trainable representations. The projection step is not parametrized and a very shallow decoder can efficiently process the representation. Furthermore, we can train MultiPlaneNeRF on a large data set and force our implicit decoder to generalize across many objects. Consequently, we can only replace the 2D images (without additional training) to produce a NeRF representation of the new object. In the experimental section, we demonstrate that MultiPlaneNeRF achieves results comparable to state-of-the-art models for synthesizing new views and has generalization properties. Additionally, MultiPlane decoder can be used as a component in large generative models like GANs

Is there a bad time for intravenous thrombolysis? The experience of Polish stroke centers

Background and purpose The outcome in acute stroke strongly depends on patient-related issues, as well as on the availability of human and diagnostic resources. Our aim was to evaluate safety and effectiveness of intravenous alteplase for stroke according to the time of admission to the hospital. Materials and methods We analyzed the data of all acute stroke patients treated with alteplase between October 2003 and December 2010, contributed to the Safe Implementation of Thrombolysis for Stroke registry from 27 Polish stroke centers. According to the time of admission we distinguished between: (1) non-working days (Friday 14:30–Monday 08:00 plus national holidays); (2) out-of-office hours (non-working days plus 14:30–08:00 during working days); and (3) night hours (time from 23:00 to 06:00). Patients admitted during regular working hours (Monday 08:00–Friday 14:30, excluding national holidays) were used as the reference. Results Of 1330 patients, 448 (32.5%) were admitted on non-working days, 868 (65.3%) at out-of-office hours, and 105 (7.9%) during night hours. In multivariate logistic regression, none of the evaluated periods showed association with symptomatic intracranial hemorrhage, 7-day mortality, and neurological improvement ≥4 points in the National Institutes of Health Stroke Scale score at day 7. Patients admitted during night hours had lower odds (OR 0.53, 95% CI: 0.29–0.95, p=0.032) for achieving favorable outcome (modified Rankin Scale score 0–2). Conclusions There is no bad time for thrombolysis. Stroke centers should feel confident about the treatment outside regular working hours, irrespective of equipment and staff availability. However, it may be reasonable to pay additional attention during nighttime

Predicting neutropenia dynamics after radiation therapy in multiple myeloma patients receiving first-line bortezomib-based chemotherapy – a pilot study

Introduction. Radiation therapy (RT) is a useful modality for achieving local control and symptom relief in patients with multiple myeloma (MM), but its use can result in adverse effects such as neutropenia, which may be aggravated by prior chemotherapy. Material and methods. In this retrospective study, we analyzed 530 complete blood count results of 32 MM patients who underwent RT for symptomatic bone pain between cycles or after completing first-line bortezomib-based chemotherapy (VCD). To evaluate the dynamics of neutrophil count (ANC) changes, we developed a generalized additive model (GAM) using initial ANC, dosage (BED10), and treatment volume (PTV) as predictors. Results. Our GAM model demonstrated that ANC nadir after RT can be expected approximately 16 days after treatment initiation. The delivery of 8 Gy in 1 fraction resulted in the lowest ANC nadir, while a dose of 30 Gy in 10–15 fractions was deemed the safest. For PTV = 1000cm3, an initial ANC level of at least 1.42 × 103/µl was associated with no incidence of severe neutropenia irrespective of the fractionation scheme. Longer courses allowed for treatment delivery without significant neutropenia even with an initial ANC of 1.23 × 103/µl on the day of RT initiation. Conclusions. Our model could aid in optimizing treatment strategies for MM patients receiving RT and chemotherapy. Further research is needed to validate our findings and evaluate the feasibility of implementing this model in clinical practice

Predicting neutropenia dynamics after radiation therapy in multiple myeloma patients receiving first-line bortezomib-based chemotherapy – a pilot study

Introduction.Radiation therapy (RT) is a useful modality for achieving local control and symptom relief in patients with multiple myeloma (MM), but its use can result in adverse effects such as neutropenia, which may be aggravated by prior chemotherapy. Material and methods.In this retrospective study, we analyzed 530 complete blood count results of 32 MM patients who underwent RT for symptomatic bone pain between cycles or after completing first-line bortezomib-based che­motherapy (VCD). To evaluate the dynamics of neutrophil count (ANC) changes, we developed a generalized additive model (GAM) using initial ANC, dosage (BED10), and treatment volume (PTV) as predictors. Results.Our GAM model demonstrated that ANC nadir after RT can be expected approximately 16 days after treatment initiation. The delivery of 8 Gy in 1 fraction resulted in the lowest ANC nadir, while a dose of 30 Gy in 10–15 fractions was deemed the safest. For PTV = 1000 cm3, an initial ANC level of at least 1.42 × 103/μl was associated with no incidence of severe neutropenia irrespective of the fractionation scheme. Longer courses allowed for treatment delivery without significant neutropenia even with an initial ANC of 1.23 × 103/μl on the day of RT initiation. Conclusions.Our model could aid in optimizing treatment strategies for MM patients receiving RT and chemotherapy. Further research is needed to validate our findings and evaluate the feasibility of implementing this model in clinical practice.

The microbial production of polyhydroxyalkanoates from waste polystyrene fragments attained using oxidative degradation

© 2018 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/polym10090957Excessive levels of plastic waste in our oceans and landfills indicate that there is an abundance of potential carbon sources with huge economic value being neglected. These waste plastics, through biological fermentation, could offer alternatives to traditional petrol-based plastics. Polyhydroxyalkanoates (PHAs) are a group of plastics produced by some strains of bacteria that could be part of a new generation of polyester materials that are biodegradable, biocompatible, and, most importantly, non-toxic if discarded. This study introduces the use of prodegraded high impact and general polystyrene (PS0). Polystyrene is commonly used in disposable cutlery, CD cases, trays, and packaging. Despite these applications, some forms of polystyrene PS remain financially and environmentally expensive to send to landfills. The prodegraded PS0 waste plastics used were broken down at varied high temperatures while exposed to ozone. These variables produced PS flakes (PS1–3) and a powder (PS4) with individual acid numbers. Consequently, after fermentation, different PHAs and amounts of biomass were produced. The bacterial strain, Cupriavidus necator H16, was selected for this study due to its well-documented genetic profile, stability, robustness, and ability to produce PHAs at relatively low temperatures. The accumulation of PHAs varied from 39% for prodegraded PS0 in nitrogen rich media to 48% (w/w) of dry biomass with the treated PS. The polymers extracted from biomass were analyzed using nuclear magnetic resonance (NMR) and electrospray ionization tandem mass spectrometry (ESI-MS/MS) to assess their molecular structure and properties. In conclusion, the PS0–3 specimens were shown to be the most promising carbon sources for PHA biosynthesis; with 3-hydroxybutyrate and up to 12 mol % of 3-hydroxyvalerate and 3-hydroxyhexanoate co-monomeric units generated

Mass spectrometry reveals molecular structure of polyhydroxyalkanoates attained by bioconversion of oxidized polypropylene waste fragments

This study investigated the molecular structure of the polyhydroxyalkanoate (PHA) produced via a microbiological shake flask experiment utilizing oxidized polypropylene (PP) waste as an additional carbon source. The bacterial strain Cupriavidus necator H16 was selected as it is non-pathogenic, genetically stable, robust, and one of the best known producers of PHA. Making use of PHA oligomers, formed by controlled moderate-temperature degradation induced by carboxylate moieties, by examination of both the parent and fragmentation ions, the ESI-MS/MS analysis revealed the 3-hydroxybutyrate and randomly distributed 3-hydroxyvalerate as well as 3-hydroxyhexanoate repeat units. Thus, the bioconversion of PP solid waste to a value-added product such as PHA tert-polymer was demonstrated.This research was funded by the Research Investment Fund, University of Wolverhampton, Faculty of Science and Engineering, UK. This work was also partially supported the European Regional Development Fund Project EnTRESS No 01R16P00718 and the PELARGODONT Project UM0-2016/22/Z/STS/00692 financed under the M-ERA.NET 2 Program of Horizon 2020.Published onlin

Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data

Aim Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert-based information is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert-based information with detailed empirical evidence. Here, we compared expert-based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS-tracking data of 1,498 individuals from 49 mammal species. Location Worldwide. Time period 1998-2021. Major taxa studied Forty-nine terrestrial mammal species. Methods Using GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types. Results IUCN habitat suitability data were in accordance with the GPS data (> 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a > 50% probability of agreement based on proportional habitat use and selection ratios, respectively. Main conclusions We show how GPS-tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, we show that GPS-tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data