ExCeL : Combined Extreme and Collective Logit Information for Enhancing Out-of-Distribution Detection

Deep learning models often exhibit overconfidence in predicting out-of-distribution (OOD) data, underscoring the crucial role of OOD detection in ensuring reliability in predictions. Among various OOD detection approaches, post-hoc detectors have gained significant popularity, primarily due to their ease of use and implementation. However, the effectiveness of most post-hoc OOD detectors has been constrained as they rely solely either on extreme information, such as the maximum logit, or on the collective information (i.e., information spanned across classes or training samples) embedded within the output layer. In this paper, we propose ExCeL that combines both extreme and collective information within the output layer for enhanced accuracy in OOD detection. We leverage the logit of the top predicted class as the extreme information (i.e., the maximum logit), while the collective information is derived in a novel approach that involves assessing the likelihood of other classes appearing in subsequent ranks across various training samples. Our idea is motivated by the observation that, for in-distribution (ID) data, the ranking of classes beyond the predicted class is more deterministic compared to that in OOD data. Experiments conducted on CIFAR100 and ImageNet-200 datasets demonstrate that ExCeL consistently is among the five top-performing methods out of twenty-one existing post-hoc baselines when the joint performance on near-OOD and far-OOD is considered (i.e., in terms of AUROC and FPR95). Furthermore, ExCeL shows the best overall performance across both datasets, unlike other baselines that work best on one dataset but has a performance drop in the other

Unguided bronchoscopic biopsy: Does yield increase with operator experience

BackgroundBronchoscopic Forceps biopsy (Endobronchial Biopsy (EBB) and Trans Bronchial Lung Biopsy (TBLB)) are commonly performed for diagnosis in patients with endobronchial abnormalities or diffuse parenchymal involvement. As the operator gains experience his yield of various diagnostic bronchoscopic biopsies is expected to increase, however, no studies on the subject are available in literature.AimsTo determine the effect of on- job experience on the yield of unguided bronchoscopic biopsies.Methods A total of 244 bronchoscopies were performed between Oct 2013 and Oct 2016. A retrospective analysis of all these bronchoscopies was undertaken. All patients who underwent biopsy were included in the study. Patients were divided into two groups with first group (Group A) comprising of biopsies done between Oct 2013 to Apr 2015 and second group comprising biopsies done between May 2015 to Oct 2016 (Group B). The diagnostic yield in two groups was compared.Results Total 71 bronchoscopic biopsies were performed during Oct 2013 to Oct 2016. 36 patients were included in group A and 35 patients were included in group B. The groups were matched in demographic profile, clinical diagnosis, bronchoscopic findings and type of biopsy undertaken. The biopsy was diagnostic in 31 patient (43.6 per cent) and non-diagnostic in 33 patients (46.4 per cent). There were 15 diagnostic biopsies in group A and 16 diagnostic biopsies in group B. The difference in the diagnostic biopsies between the two groups was not significant.ConclusionThere was no significant impact of on job experience on diagnostic yield of biopsies. This may be due to adequate exposure during training leading to a diagnostic plateau being reached

Using a simple open-source automated machine learning algorithm to forecast COVID-19 spread: A modelling study

Introduction: Machine learning algorithms have been used to develop prediction models in various infectious and non-infectious settings including interpretation of images in predicting the outcome of diseases. We demonstrate the application of one such simple automated machine learning algorithm to a dataset obtained about COVID-19 spread in South Korea to better understand the disease dynamics.Material and methods: Data from 20th January 2020 (when the first case of COVID-19 was detected in South Korea) to 4th March 2020 was accessed from Korea’s centre for disease control (KCDC). A future time-series of specified length (taken as 7 days in our study) starting from 5th March 2020 to 11th March 2020 was generated and fed to the model to generate predictions with upper and lower trend bounds of 95% confidence intervals. The model was assessed for its ability to reliably forecast using mean absolute percentage error (MAPE) as the metric.Results: As on 4th March 2020, 145,541 patients were tested for COVID-19 (in 45 days) in South Korea of which 5166 patients tested positive. The predicted values approximated well with the actual numbers. The difference between predicted and observed values ranged from 4.08% to 12.77% . On average, our predictions differed from actual values by 7.42% (MAPE) over the same period.Conclusion: Open source and automated machine learning tools like Prophet can be applied and are effective in the context of COVID-19 for forecasting spread in naïve communities. It may help countries to efficiently allocate healthcare resources to contain this pandemic

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Origin and evolution of the bread wheat D genome

Bread wheat (Triticum aestivum) is a globally dominant crop and major source of calories and proteins for the human diet. Compared with its wild ancestors, modern bread wheat shows lower genetic diversity, caused by polyploidisation, domestication and breeding bottlenecks. Wild wheat relatives represent genetic reservoirs, and harbour diversity and beneficial alleles that have not been incorporated into bread wheat. Here we establish and analyse extensive genome resources for Tausch’s goatgrass (Aegilops tauschii), the donor of the bread wheat D genome. Our analysis of 46 Ae. tauschii genomes enabled us to clone a disease resistance gene and perform haplotype analysis across a complex disease resistance locus, allowing us to discern alleles from paralogous gene copies. We also reveal the complex genetic composition and history of the bread wheat D genome, which involves contributions from genetically and geographically discrete Ae. tauschii subpopulations. Together, our results reveal the complex history of the bread wheat D genome and demonstrate the potential of wild relatives in crop improvement

Introducing dual excitation and tunable dual emission in ZnO through selective lanthanide (Er3+/Ho3+) doping

We have introduced dual excitation properties in the multifunctional semiconductor ZnO by controlled solid state diffusion of dopant lanthanide ions like Er3+ and Ho3+ into the lattice at 500 degrees C. So far light emission from doped ZnO has been explored either under UV or IR excitation. Our results show that the emission colour can be tuned from cyan to red under UV (band edge, 377 nm) excitation and from green to red under IR (980 nm) excitation in ZnO through selected doping of lanthanide ions. Doping lanthanide ions in ZnO changes its morphology and emission characteristics. Whereas down conversion emission under UV excitation is due to across band gap excitation and subsequent donor-acceptor pair recombination, the dependence of up conversion emission yield on pump laser power indicates that two to three photon processes may be more effective in ZnO hosts for frequency upconversion

Plasmonic enhancement of dual mode fluorescence in a silver nano-antenna-ZnO:Er3+ hybrid nanostructure

Tuning of surface plasmon resonance (SPR) of silver nanoparticles (Ag NPs) through shape tailoring make them frequency tunable multipolar optical nano antennas that can be harnessed for optical enhancements in a fluorophore placed in optimal proximity. Such SPR tuning has been achieved with Ag nano-hexagons in which enhancements in both down (under UV excitation) and up (under IR excitation) conversion fluorescence from rare earth Er3+-doped ZnO nanoparticles are realised. The near field generated by the pure Ag NPs and their hybrids under UV and IR incident light is simulated using a finite difference time domain method, and a direct correlation with the observed fluorescence enhancement is established

JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS

Dual excitation properties have been introduced in ZnO nanoparticles (similar to 10 nm) through lanthanide (Er3+/Ho3+) doping by inclusive co precipitation at room temperature. Monophasic hexagonal ZnO nanoparticles form hierarchical micro flowers as a consequence of lanthanide doping. The Stokes and anti Stokes emissions were investigated under UV (399 nm) and IR (980 nm) excitation. The down-conversion emission under band edge excitation is in the blue region and the up-conversion (UC) emission of lanthanide doped ZnO nanocrystals exhibit strong green and red fluorescence bands for ZnO:Er3+ and only green band for ZnO:Ho3+. Post synthesis annealing further improves luminescence properties in ZnO:Er3+ that exhibits triple mode excitation of fluorescence under UV as well as IR wavelengths 980 and 1550 nm, also confirmed by confocal fluorescence mapping. The measured dependence of pump power on UC emission suggest that lanthanide doping in ZnO leads to frequency up-conversion emission via two to three photon absorption processes

Role of urine cytology in bladder neoplasm – Cytopathological correlation and review of literature

Background: Urinary bladder tumors are the second most common tumors affecting males. The aim of the study was to evaluate the various histopathological findings in various bladder tumors and their correlation with exfoliative urine cytology. Design: This is an observational study carried out over a period of 7 years at a tertiary care hospital between January 2010 and January 2017. Materials and Methods: Tumors were divided into invasive and noninvasive urothelial carcinoma and were further classified into high-grade or low-grade urothelial cancer. Urine cytology smears from all these patients were also were studied. Cytological findings were correlated with histopathological findings. Result showed that bladder tumors were commonly seen in males with average age of presentation being the sixth decade. The most common type of carcinoma seen was low-grade urothelial carcinoma-noninvasive type. Urine cytology was positive in 47.46% patients. Sample Size: In our study, 113 cystoscopic biopsies were included over a period of 7 years (85 males and 28 females). Conclusion: Accuracy of diagnosing malignancy in urine cytology varies, and it depends on the presence of diagnostic yield in the urine cytology, processing of the sample, and experience of the cytopathologist. Urine cytology should be reported in a background of detailed clinical information and should always be followed by histopathological examination

Triple excitation with dual emission in paramagnetic ZnO:Er3+ nanocrystals

ZnO nanocrystals have been made excitable under UV as well as near and far infrared (IR) wavelengths (980 nm, 1550 nm) through doping of rare earth ion Er3+ thus making it a triple excitation nanophosphor. Whereas the visible emission under UV is broad due to intrinsic donor acceptor pair recombination, the sharp green and red emission peaks under IR are characteristic of f-f transitions of the Er3+ ion. Thus both down and upconversion fluorescence in ZnO could be realised through doping of rare earth ion Er3+ that also makes ZnO: Er3+ nanocrystals paramagnetic. To the best of our knowledge we are reporting upconversion at 1550 nm in ZnO: Er3+ for the first time