Auto-TransRL: Autonomous Composition of Vision Pipelines for Robotic Perception

Creating a vision pipeline for different datasets to solve a computer vision task is a complex and time consuming process. Currently, these pipelines are developed with the help of domain experts. Moreover, there is no systematic structure to construct a vision pipeline apart from relying on experience, trial and error or using template-based approaches. As the search space for choosing suitable algorithms for achieving a particular vision task is large, human exploration for finding a good solution requires time and effort. To address the following issues, we propose a dynamic and data-driven way to identify an appropriate set of algorithms that would be fit for building the vision pipeline in order to achieve the goal task. We introduce a Transformer Architecture complemented with Deep Reinforcement Learning to recommend algorithms that can be incorporated at different stages of the vision workflow. This system is both robust and adaptive to dynamic changes in the environment. Experimental results further show that our method also generalizes well to recommend algorithms that have not been used while training and hence alleviates the need of retraining the system on a new set of algorithms introduced during test time.Comment: Presented at the IEEE ICRA 2022 Workshop in Robotic Perception and Mapping: Emerging Technique

Residence time estimates for asymmetric simple exclusion dynamics on stripes

The target of our study is to approximate numerically and, in some particular physically relevant cases, also analytically, the residence time of particles undergoing an asymmetric simple exclusion dynamics on a stripe. The source of asymmetry is twofold: (i) the choice of boundary conditions (different reservoir levels) and (ii) the strong anisotropy from a nonlinear drift with prescribed directionality. We focus on the effect of the choice of anisotropy in the flux on the asymptotic behavior of the residence time with respect to the length of the stripe. The topic is relevant for situations occurring in pedestrian flows or biological transport in crowded environments, where lateral displacements of the particles occur predominantly affecting therefore in an essentially way the efficiency of the overall transport mechanism

Epidemiological Study of Thoracolumbar Pott’s Spine at a Tertiary Care Hospital in North India

The vertebral column is involved in less than 1% of all the cases of tuberculosis. It can associated with major neurological deficits due to compression of adjacent neural structures with significant deformity of spinal column. Therefore, early diagnosis and management of spinal TB has special importance in preventing these serious complications. In order to extract current trends in diagnosis and medical or surgical treatment of spinal TB we performed a review with patients admitted to our hospital between 2016 and 2017. Although the development of more accurate imaging modalities such as magnetic resonance imaging and advanced surgical techniques have made the early diagnosis and management of spinal TB much easier, these are still very challenging topics. In this review we aim to discuss the diagnosis and management of spinal TB based on studies with acceptable design, clearly explained results and justifiable conclusions

Concept-based Anomaly Detection in Retail Stores for Automatic Correction using Mobile Robots

Tracking of inventory and rearrangement of misplaced items are some of the most labor-intensive tasks in a retail environment. While there have been attempts at using vision-based techniques for these tasks, they mostly use planogram compliance for detection of any anomalies, a technique that has been found lacking in robustness and scalability. Moreover, existing systems rely on human intervention to perform corrective actions after detection. In this paper, we present Co-AD, a Concept-based Anomaly Detection approach using a Vision Transformer (ViT) that is able to flag misplaced objects without using a prior knowledge base such as a planogram. It uses an auto-encoder architecture followed by outlier detection in the latent space. Co-AD has a peak success rate of 89.90% on anomaly detection image sets of retail objects drawn from the RP2K dataset, compared to 80.81% on the best-performing baseline of a standard ViT auto-encoder. To demonstrate its utility, we describe a robotic mobile manipulation pipeline to autonomously correct the anomalies flagged by Co-AD. This work is ultimately aimed towards developing autonomous mobile robot solutions that reduce the need for human intervention in retail store management.Comment: 8 pages, 9 figures, 2 tables, IEEE Transactions on Systems, Man and Cybernetic

The challenge of catalyst prediction

New insights and successful use of computational catalysis are highlighted. This is within the context of remaining issues that prevent theoretical catalysis to be fully predictive of catalyst performance. A major challenge is to include in modelling studies the transient initiation as well as deactivation processes of the catalyst. We will illustrate this using as an example for solid acid catalysis, the alkylation process, and for transition metal catalysis, the Fischer-Tropsch reaction. For the alkylation reaction of isobutane and alkene, an important reaction for high octane gasoline, we will present a deactivation model. For the Fischer-Tropsch reaction, which converts synthesis gas into gasoline grade molecules, we discuss structural reorganization of the catalyst induced by reaction

Deactivation Kinetics of the Catalytic Alkylation Reaction

A kinetics theory of catalyst deactivation is presented of the solid acid-catalyzed alkylation reaction of isobutane with propylene or butene that gives alkylate, a high octane fuel, as product. The intimate relation between the kinetics network of the reaction, catalyst deactivation kinetics, and residence time distribution is analyzed. The question is addressed why the deactivation of the alkylation reaction in a continuously stirred tank reactor (CSTR) is slow compared to that in a tubular plug flow reactor (PFR). Conditions are derived where such differences will be minimum and maximum. In the reaction regime of high alkylate selectivity, linear and quadratic power law kinetics equations in propylene concentration can be deduced from microkinetics. They are used to derive analytical expressions of deactivation times for CSTR and PFR. The theoretical power law kinetics equations can be related to previously established empirical rate equations of catalyst deactivation. We show that, in the CSTR, the self-alkylation reaction path contributes substantially to the deactivation time. In the self-alkylation reaction, alkylate is formed by reaction of the isobutene reaction intermediate and isobutane. Catalysts of high proton strength can benefit catalyst deactivation times by suppressing the carbenium ion deprotonation reaction that produces alkenes as isobutene. In the PFR, selective alkylate formation occurs only when the reaction occurs in a reaction zone of the catalyst bed. Deactivation is faster than in CSTR because of the reactant profile in the reaction zone. This reaction zone has restricted mobility due to the fast deactivation of reactive protons located behind the reaction zone by alkenes formed by nonselective reactions in the reaction zone. In PFR, as long as the reaction is limited to an immobile reaction zone, deactivation time is independent of reaction site density and contact time. Contact time dependence arises when the reaction zone is mobile. Overall deactivation time then depends strongly on the degree of deactivation of the protons behind the reaction zone

Experimental and clinical data analysis for identification of COVID-19 resistant ACE2 mutations.

The high magnitude zoonotic event has caused by Severe Acute Respitarory Syndrome CoronaVirus-2 (SARS-CoV-2) is Coronavirus Disease-2019 (COVID-19) epidemics. This disease has high rate of spreading than mortality in humans. The human receptor, Angiotensin-Converting Enzyme 2 (ACE2), is the leading target site for viral Spike-protein (S-protein) that function as binding ligands and are responsible for their entry in humans. The patients infected with COVID-19 with comorbidities, particularly cancer patients, have a severe effect or high mortality rate because of the suppressed immune system. Nevertheless, there might be a chance wherein cancer patients cannot be infected with SARS-CoV-2 because of mutations in the ACE2, which may be resistant to the spillover between species. This study aimed to determine the mutations in the sequence of the human ACE2 protein and its dissociation with SARS-CoV-2 that might be rejecting viral transmission. The in silico approaches were performed to identify the impact of SARS-CoV-2 S-protein with ACE2 mutations, validated experimentally, occurred in the patient, and reported in cell lines. The identified changes significantly affect SARS-CoV-2 S-protein interaction with ACE2, demonstrating the reduction in the binding affinity compared to SARS-CoV. The data presented in this study suggest ACE2 mutants have a higher and lower affinity with SARS-Cov-2 S-protein to the wild-type human ACE2 receptor. This study would likely be used to report SARS-CoV-2 resistant ACE2 mutations and can be used to design active peptide development to inactivate the viral spread of SARS-CoV-2 in humans

Pfannenstiel vs. midline incision for urinary diversion, following minimally invasive radical cystectomy: single center experience

Aim: The present study is to assess the morbidity on comparing Pfannenstiel vs. midline incision following minimally invasive radical cystectomy.Methods: This is a retrospective comparative study from February 2004 to February 2017 and the number of patients studied was 116. Patients were divided into group A (Pfannenstiel incision) and group B (midline incision). The parameters analyzed were age, gender, co-morbidity, tobacco exposure, occupation, presentation, computed tomography findings, hydronephrosis, transurethral resection of bladder tumor report, duration of surgery (in minutes), hemoglobin drop (in gram per deciliter), need for blood transfusion (number of units), hospital stay (in days), epidural analgesia, analgesic requirement, pain score on first three postoperative days (on visual analogue scale), complications, and lymph node yield (numbers). Standard steps included cystectomy with bilateral pelvic lymph-adenectomy done either through the laparoscopic or robotic approach and specimen retrieval along with diversion through either Pfannenstiel or midline incision.Results: Primary end points, post operative pain score (P = 0.0001), analgesic requirement (P = 0.0003), post operative wound complication (P = 0.002), length of hospital stay (P = 0.0003) all were less (statistically significant P < 0.05) for group A as compared to group B and secondary end points, duration of surgery (P = 0.0002), post operative paralytic ileus duration (P = 0.0006) were less (statistically significant P < 0.05) for group A as compared to group B. Other secondary end points, post operative hemoglobin drop (P = 0.08), the number of units of blood transfused (P = 0.189) and lymph node yield (P = 0.533) were comparable in either group (statistically insignificant P ≥ 0.05).Conclusion: Minimally invasive (laparoscopic or robotic) radical cystectomy with an extra-corporeal diversion through Pfannenstiel incision offers an advantage of less morbidity than midline incision