Modeling and Verification of Agent based Adaptive Traffic Signal using Symbolic Model Verifier

This paper addresses the issue of modeling and verification of a Multi Agent System (MAS) scenario. We have considered an agent based adaptive traffic signal system. The system monitors the smooth flow of traffic at intersection of two road segment. After describing how the adaptive traffic signal system can efficiently be used and showing its advantages over traffic signals with predetermined periods, we have shown how we can transform this scenario into Finite State Machine (FSM). Once the system is transformed into a FSM, we have verified the specifications specified in Computational Tree Logic(CTL) using NuSMV as a model checking tool. Simulation results obtained from NuSMV showed us whether the system satisfied the specifications or not. It has also showed us the state where the system specification does not hold. Using which we traced back our system to find the source, leading to the specification violation. Finally, we again verified the modified system with NuSMV for its specifications.Comment: 13 pages, 6 figures, Submitted to International Journal of Computer Application (IJCA

Redefining Super-Resolution: Fine-mesh PDE predictions without classical simulations

In Computational Fluid Dynamics (CFD), coarse mesh simulations offer computational efficiency but often lack precision. Applying conventional super-resolution to these simulations poses a significant challenge due to the fundamental contrast between downsampling high-resolution images and authentically emulating low-resolution physics. The former method conserves more of the underlying physics, surpassing the usual constraints of real-world scenarios. We propose a novel definition of super-resolution tailored for PDE-based problems. Instead of simply downsampling from a high-resolution dataset, we use coarse-grid simulated data as our input and predict fine-grid simulated outcomes. Employing a physics-infused UNet upscaling method, we demonstrate its efficacy across various 2D-CFD problems such as discontinuity detection in Burger's equation, Methane combustion, and fouling in Industrial heat exchangers. Our method enables the generation of fine-mesh solutions bypassing traditional simulation, ensuring considerable computational saving and fidelity to the original ground truth outcomes. Through diverse boundary conditions during training, we further establish the robustness of our method, paving the way for its broad applications in engineering and scientific CFD solvers.Comment: Accepted at Machine Learning and the Physical Sciences Workshop, NeurIPS 202

Intra-operative point-of-procedure delineation of oral cancer margins using optical coherence tomography.

ObjectivesSurgical margin status is a significant determinant of treatment outcome in oral cancer. Negative surgical margins can decrease the loco-regional recurrence by five-fold. The current standard of care of intraoperative clinical examination supplemented by histological frozen section, can result in a risk of positive margins from 5 to 17 percent. In this study, we attempted to assess the utility of intraoperative optical coherence tomography (OCT) imaging with automated diagnostic algorithm to improve on the current method of clinical evaluation of surgical margin in oral cancer.Materials and methodsWe have used a modified handheld OCT device with automated algorithm based diagnostic platform for imaging. Intraoperatively, images of 125 sites were captured from multiple zones around the tumor of oral cancer patients (n = 14) and compared with the clinical and pathologic diagnosis.ResultsOCT showed sensitivity and specificity of 100%, equivalent to histological diagnosis (kappa, ĸ = 0.922), in detection of malignancy within tumor and tumor margin areas. In comparison, for dysplastic lesions, OCT-based detection showed a sensitivity of 92.5% and specificity of 68.8% and a moderate concordance with histopathology diagnosis (ĸ = 0.59). Additionally, the OCT scores could significantly differentiate squamous cell carcinoma (SCC) from dysplastic lesions (mild/moderate/severe; p ≤ 0.005) as well as the latter from the non-dysplastic lesions (p ≤ 0.05).ConclusionThe current challenges associated with clinical examination-based margin assessment could be improved with intra-operative OCT imaging. OCT is capable of identifying microscopic tumor at the surgical margins and demonstrated the feasibility of mapping of field cancerization around the tumor

Life Cycle Cost Methodology for Mixers based on MTTF Life Cycle Cost Model

Abstract: Most of the manufacture and mixer users have confusion about selecting the life cycle cost model or life cycle costing of mixers. This paper presents the life cycle costing of mixers based on the MTTF life cycle cost model from the various life cycle cost models. This method or model can also be applied to the static as well as dynamic mixers. This model has five components and these components will be easily collected by the manufacturer data and field data from the end users of the mixers. MTTF life cycle cost model has benefitted to manufacturer and also users to calculating the total life cycle cost of their products

The new 130-cm optical telescope at Devasthal, Nainital

A modern Ritchey-Chretien Cassegrain 130-cm diameter optical telescope has been successfully installed at Devasthal, Nainital in the central Himalayan region. This location was chosen after carrying out extensive site surveys. The first images obtained with the telescope indicate that atmospheric seeing and sky darkness at Devasthal are nearly at values as measured during the site survey. The values of seeing and sky darkness are comparable to some of the best astronomical sites in the world. The 130-cm telescope is functional and observations can be carried out from the control centre at Devasthal or from the Manora Peak in Nainital. This telescope has started providing valuable data for a number of research projects and is expected to help meet part of the national requirement in optical observational astronomy from small-aperture ground-based telescopes

Alkaline phosphatase variation during carfilzomib treatment is associated with best response in multiple myeloma patients

The ubiquitin–proteasome pathway regulates bone formation through osteoblast differentiation. We analyzed variation alkaline phosphatase (ALP) during carfilzomib treatment. Data from 38 patients enrolled in the PX‐171‐003 and 29 patients in PX‐171‐004 studies, for patients with relapsed/refractory myeloma, were analyzed. All patients received 20 mg/m 2 of carfilzomib on Days 1, 2, 8, 9, 15, and 16 of a 28‐day cycle. Sixty‐seven patients from ALP data were evaluable. In PX‐171‐003, the ORR (>PR) was 18% and the clinical benefit response (CBR; >MR) was 26%, while in PX‐171‐004, the ORR was 35.5% overall and 57% in bortezomib‐naive patients. ALP increment from baseline was statistically different in patients who achieved ≥VGPR compared with all others on Days 1 ( P  = 0.0049) and 8 ( P  = 0.006) of Cycle 2. In patients achieving a VGPR or better, ALP increased more than 15 units per liter at Cycle 2 Day 1 over baseline. An ALP increase over the same period of time was seen in 26%, 13% and 11% of patients achieving PR, MR, and SD, respectively. This retrospective analysis of patients with relapsed or refractory myeloma treated with single‐agent carfilzomib indicates that early elevation in ALP is associated with subsequent myeloma response.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86807/1/j.1600-0609.2011.01602.x.pd

An evaluation of large group cognitive behaviour therapy with mindfulness (CBTm) classes

Abstract Background Ensuring equitable and timely access to Cognitive Behaviour Therapy (CBT) is challenging within Canada’s service delivery model. The current study aims to determine acceptability and effectiveness of 4-session, large, Cognitive Behaviour Therapy with Mindfulness (CBTm) classes. Methods A retrospective chart review of adult outpatients (n = 523) who attended CBTm classes from 2015 to 2016. Classes were administered in a tertiary mental health clinic in Winnipeg, Canada and averaged 24 clients per session. Primary outcomes were (a) acceptability of the classes and retention rates and (b) changes in anxiety and depressive symptoms using Generalized Anxiety Disorder 7-item (GAD-7) and Patient Health Questionnaire 9-item (PHQ-9) scales. Results Clients found classes useful and > 90% expressed a desire to attend future sessions. The dropout rate was 37.5%. A mixed-effects linear regression demonstrated classes improved anxiety symptoms (GAD-7 score change per class = − 0.52 [95%CI, − 0.74 to − 0.30], P < 0.001) and depressive symptoms (PHQ-9 score change per class = − 0.65 [95%CI, − 0.89 to − 0.40], P < 0.001). Secondary analysis found reduction in scores between baseline and follow-up to be 2.40 and 1.98 for the GAD-7 and PHQ-9, respectively. Effect sizes were small for all analyses. Conclusions This study offers preliminary evidence suggesting CBTm classes are an acceptable strategy to facilitate access and to engage and maintain clients’ interest in pursuing CBT. Clients attending CBTm classes experienced improvements in anxiety and depressive symptoms. Symptom improvement was not clinically significant. Study limitations, such as a lack of control group, should be addressed in future research.https://deepblue.lib.umich.edu/bitstream/2027.42/148879/1/12888_2019_Article_2124.pd

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts