Seven-Level Symmetrical Series/Parallel Multilevel Inverter with PWM Technique Using Digital Logic

This paper attempts to come up with a proposed configuration of Multilevel inverters with a lesser number of switches that are smaller in size, lesser in cost and with a higher efficiency. Designing an inverter topology with a lesser number of switches and proper control technique is the major challenge. cascaded H-Bridge (CHB) topology are more popular among the existing configurations of multilevel inverters (MLI). Even though it can produce more levels, it needs to accommodate a huge number of switches for higher levels. The focus of this paper is to reduce the number of components for the same voltage level of cascaded H- Bridge configuration. In addition to that, generating the gating pulses for the switches is difficult when there is an asymmetry in the switches. A new symmetrical series/parallel configuration is proposed with reduced switch count and the pulse width modulation (PWM) technique is implemented with digital logic to generate the required gating pulses for the switches. The total harmonic distortion (THDI) of the output current is reduced with this PWM technique. The simulation has been carried out in MATLAB/Simulink software for both R (resistive) and R-L (resistive -inductive) loads

Using Whole Slide Image Representations from Self-Supervised Contrastive Learning for Melanoma Concordance Regression

Although melanoma occurs more rarely than several other skin cancers, patients' long term survival rate is extremely low if the diagnosis is missed. Diagnosis is complicated by a high discordance rate among pathologists when distinguishing between melanoma and benign melanocytic lesions. A tool that provides potential concordance information to healthcare providers could help inform diagnostic, prognostic, and therapeutic decision-making for challenging melanoma cases. We present a melanoma concordance regression deep learning model capable of predicting the concordance rate of invasive melanoma or melanoma in-situ from digitized Whole Slide Images (WSIs). The salient features corresponding to melanoma concordance were learned in a self-supervised manner with the contrastive learning method, SimCLR. We trained a SimCLR feature extractor with 83,356 WSI tiles randomly sampled from 10,895 specimens originating from four distinct pathology labs. We trained a separate melanoma concordance regression model on 990 specimens with available concordance ground truth annotations from three pathology labs and tested the model on 211 specimens. We achieved a Root Mean Squared Error (RMSE) of 0.28 +/- 0.01 on the test set. We also investigated the performance of using the predicted concordance rate as a malignancy classifier, and achieved a precision and recall of 0.85 +/- 0.05 and 0.61 +/- 0.06, respectively, on the test set. These results are an important first step for building an artificial intelligence (AI) system capable of predicting the results of consulting a panel of experts and delivering a score based on the degree to which the experts would agree on a particular diagnosis. Such a system could be used to suggest additional testing or other action such as ordering additional stains or genetic tests.Comment: Accepted at ECCV 2022 AIMIA Workshop. arXiv admin note: text overlap with arXiv:2109.0755

Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload.

Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin & eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning system which classifies digitized dermatopathology slides into 4 categories. The system is developed using 5,070 images from a single lab, and tested on an uncurated set of 13,537 images from 3 test labs, using whole slide scanners manufactured by 3 different vendors. The system\u27s use of deep-learning-based confidence scoring as a criterion to consider the result as accurate yields an accuracy of up to 98%, and makes it adoptable in a real-world setting. Without confidence scoring, the system achieved an accuracy of 78%. We anticipate that our deep learning system will serve as a foundation enabling faster diagnosis of skin cancer, identification of cases for specialist review, and targeted diagnostic classifications

TERT and TERT promoter in melanocytic neoplasms: Current concepts in pathogenesis, diagnosis, and prognosis

Background and objectiveLocated on chromosome locus 5p15.33, telomerase reverse transcriptase (TERT or hTERT) encodes the catalytic subunit of telomerase which permits lengthening and preservation of telomeres following mitosis. Mutations in TERT promoter (TERT‐p) upregulate expression of TERT, allowing survival of malignant cells and tumor progression in wide variety of malignancies including melanoma. The objective of this review is to examine the roles of TERT and TERT‐p in the pathogenesis, diagnosis, and prognostication of cutaneous melanoma.MethodsAll studies of TERT or TERT‐p in cutaneous melanocytic neoplasms with the following inclusion criteria were reviewed: publication date between 2010 and 2019, English language, and series of ≥3 cases were reviewed for evidence supporting the role of TERT in pathogenesis, diagnosis, and prognosis. Studies with <3 cases or focused primarily on mucosal or uveal melanocytic tumors were excluded.Results and conclusionTERT‐p mutations are frequent in chronic and non‐chronic sun damage melanoma and correlate with adverse prognosis, inform pathogenesis, and may provide diagnostic support. While TERT‐p mutations are uncommon in acral melanoma, TERT copy number gains and gene amplification predict reduced survival. Among atypical spitzoid neoplasms, TERT‐p mutations identify biologically aggressive tumors and support the diagnosis of spitzoid melanoma. TERT‐p methylation may have prognostic value in pediatric conventional melanoma and drive tumorigenesis in melanoma arising within congenital nevi. Finally, TERT‐p mutations may aid in the differentiation of recurrent nevi from recurrent melanoma.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156143/2/cup13691.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156143/1/cup13691_am.pd

Enzyme-linked immunosorbent assay as a helpful diagnostic tool for pemphigus erythematosus with equivocal histologic and immunofluorescent findings

Enzyme-linked immunosorbent assay is a sensitive and specific method for the detection of circulating autoantibodies in pemphigus vulgaris and foliaceus. Herein, pemphigus erythematosus with equivocal immunofluorescence and non-diagnostic histology, but confirmed by enzyme-linked immunosorbent assay, is described. As a non-invasive, sensitive, and specific assay with additional utility for monitoring disease activity, this case adds to growing evidence supporting ELISA as the diagnostic method of choice for common and less common variants of pemphigus

Enzyme-linked immunosorbent assay as a helpful diagnostic tool for pemphigus erythematosus with equivocal histologic and immunofluorescent findings

Enzyme-linked immunosorbent assay is a sensitive and specific method for the detection of circulating autoantibodies in pemphigus vulgaris and foliaceus. Herein, pemphigus erythematosus with equivocal immunofluorescence and non-diagnostic histology, but confirmed by enzyme-linked immunosorbent assay, is described. As a non-invasive, sensitive, and specific assay with additional utility for monitoring disease activity, this case adds to growing evidence supporting ELISA as the diagnostic method of choice for common and less common variants of pemphigus

Vesiculobullous Diseases

A diverse range of inflammatory dermatoses are characterized by vesicles or bullae [...