SkyNet: Memristor-based 3D IC for Artificial Neural Networks

Hardware implementations of artificial neural networks (ANNs) have become feasible due to the advent of persistent 2-terminal devices such as memristor, phase change memory, MTJs, etc. Hybrid memristor crossbar/CMOS systems have been studied extensively and demonstrated experimentally. In these circuits, memristors located at each cross point in a crossbar are, however, stacked on top of CMOS circuits using back end of line processing (BOEL), limiting scaling. Each neuron’s functionality is spread across layers of CMOS and memristor crossbar and thus cannot support the required connectivity to implement large-scale multi-layered ANNs. This work proposes a new fine-grained 3D integrated circuit technology for ANNs that is one of the first IC technologies for this purpose. Synaptic weights implemented with devices are incorporated in a uniform vertical nanowire template co-locating the memory and computation requirements of ANNs within each neuron. Novel 3D routing features are used for interconnections in all three dimensions between the devices enabling high connectivity without the need for special pins or metal vias. To demonstrate the proof of concept of this fabric, classification of binary images using a perceptron-based feed forward neural network is shown. Bottom-up evaluations for the proposed fabric considering 3D implementation of fabric components reveal up to 19x density, 1.2x power benefits when compared to 16nm hybrid memristor/CMOS technology

5-year experience with vulval lesions in a tertiary care hospital: series of 115 cases

Background: Wide range of vulval lesions have been described with similar modes of presentation. Benign and inflammatory lesions form the major chunk. Squamous cell carcinoma is the most reported malignant entity. Aim was to review the vulval lesions received in our departmentMethods: We studied the data from the archives of the Department of Pathology for a period of 5 years from January 2014 to December 2018 for vulval biopsies and specimens sent for histopathological examination. The final diagnoses were divided into non-neoplastic, neoplastic and non- specific.Results: Age of women ranged from 22 to 86 years (mean 54.3±3.6) with the maximum number of patients between 50 to 60 years of age. Most common form of clinical presentation was an itchy white elevated lesion on the vulva (72 cases, 62.6%). The most common site for the lesions was labia minora (90 cases, 78.2%). Non neoplastic lesions were seen in 53 cases and neoplastic lesions were seen in 52 cases. There were 28 (53.8%) benign lesions while 24 cases (46.1%) were malignant. Squamous cell carcinoma was the most frequently diagnosed form accounting for 20 cases (83.3%). Rare tumours like Malignant melanoma, Merkel cell carcinoma and Neuroendocrine carcinoma formed 16.6% (n=4). Seven cases were premalignant. Two cases had non-specific histologic diagnosis showing mild chronic inflammation.Conclusions: Previous studies have reported that non-neoplastic lesions form around 70% of cases. However, in our study we found that the non-neoplastic and neoplastic lesions form equal number of cases (46%) which may be attributed to increased awareness or geographical variation

Design and Evolution of Deep Convolutional Neural Networks in Image Classification – A Review

Convolutional Neural Network(CNN) is a well-known computer vision approach successfully applied for various classification and recognition problems. It has an outstanding power to identify patterns in 1D and 2D data. Though invented in 80's, it became hugely successful after LeCun's work on digit identification. Several CNN based models have been developed to record splendid performance on ImageNet and other databases. Ability of the CNN in learning complex features at different hierarchy from the data had made it the most successful among deep learning algorithms. Innovative architectural designs and hyperaparameter optimization have greatly improved the efficiency of CNN in pattern recognition. This review majorly focuses on the evolution and history of CNN models. Landmark CNN architectures are discussed with their categorization depending on various parameters. In addition, this also explores the architectural details of different layers, activation function, optimizers and other hyperparameters used by CNN. Review concludes by shedding the light on the applications and observations to be considered while designing the network

Design and Evolution of Deep Convolutional Neural Networks in Image Classification – A Review

Convolutional Neural Network(CNN) is a well-known computer vision approach successfully applied for various classification and recognition problems. It has an outstanding power to identify patterns in 1D and 2D data. Though invented in 80's, it became hugely successful after LeCun's work on digit identification. Several CNN based models have been developed to record splendid performance on ImageNet and other databases. Ability of the CNN in learning complex features at different hierarchy from the data had made it the most successful among deep learning algorithms. Innovative architectural designs and hyperaparameter optimization have greatly improved the efficiency of CNN in pattern recognition. This review majorly focuses on the evolution and history of CNN models. Landmark CNN architectures are discussed with their categorization depending on various parameters. In addition, this also explores the architectural details of different layers, activation function, optimizers and other hyperparameters used by CNN. Review concludes by shedding the light on the applications and observations to be considered while designing the network

Evaluation of COVID-19 Vaccination Websites Using DISCERN and Quality Evaluation Scoring (QUEST) Tools

Background: The objective of this paper was to evaluate the COVID-19 vaccine registration website across UN-recognized member states for their portal quality, reliability, Ease Use and help to the general population in informed decision making.Methods: 12 UN member states (Countries) were selected based on the inclusion and exclusion criteria mentioned in the methodology section of this paper. PPS technique was used for sampling and selection of 12 countries from 193 UN member states. Post selection of UN member states the study used 2 step evaluation techniques, Step 1 The DISCERN checklist consists of 16 questions in three sections and is aimed to assess the reliability of information and quality of information; Step 2 The QUEST tool consists of 6 items with a subitem, Authorship, Attribution, Conflict of Interest, Complementarity, Currency, Tone. The authors developed a standard set of instructions for evaluating Vaccination Portals to bring uniformity in understanding and context setting.Results: DISCERN tool overall reliability score on the Likert scale of 0 to 5 was 4 (SD ± 1.28). On Quality of information regarding treatment choices, the average score was 3.4 (SD ± 1.67). The QUEST tool on ease of use, concision, and comprehensiveness demonstrated an average score of 18.1 (SD ± 8.3) out of 28.The vaccine registration portal of the Czech Republic was found to be most informative and was able to provide a piece of scientifically valid information on safety, efficacy, long-term short effects, choice of vaccine with attributable authors details. India, Bangladesh, Nigeria, South Africa scored relatively low to missing critical information on the website. The United Arab Emirates, Republic of South Korea, Indonesia, Australia, and Argentina had minor elements missing.Conclusions: COVID-19 vaccination portals vary in the quality of information, and many were found unable to provide critical information for decision making on getting vaccinated

CT-guided gastrostomy tube placement—a single center case series

PURPOSEThe role of computed tomography (CT)-guided gastrostomy tube placement is still evolving. It is a valuable alternative to guide gastrostomy tube placement in a few selected patients, who are not candidates for the established endoscopy- or fluoroscopy-guided gastrostomy tube placement. Our objective was to describe our institutional experience placing gastrostomy tubes using CT guidance and to conduct a review of literature for similar studies to provide the best current evidence on success rates and complications.METHODSWe identified gastrostomy tubes placed under CT guidance at our institution using a comprehensive case log. We also identified studies in the literature, through a systematic search of PubMed. In both the local and literature analyses, we recorded success and complication rates.RESULTSA total of 31 patients underwent 33 attempted CT-guided gastrostomy tube placements at our institution, with 32 successful procedures yielding a success rate of 97%. The overall rate of successful gastrostomy tube placement using CT-guidance was 94.9% (634/668), as reported in the existing literature.CONCLUSIONCT-guidance is an effective method for gastrostomy tube placement and may play an important role in patients for whom endoscopic or fluoroscopic gastrostomy tube placement is not feasible

CT-guided cryoablation for post-thoracotomy pain syndrome: a retrospective analysis

PURPOSEPost-thoracotomy pain syndrome is a common condition affecting up to 50% of post-thoracotomy patients. However, percutaneous computed tomography (CT)-guided intercostal nerve cryoablation may provide symptomatic benefit in chronic and/or refractory cases.METHODSA retrospective review of our institution’s comprehensive case log from October 2017 to September 2018 for patients who underwent cryoablation was analyzed. Thirteen patients with post-thoracotomy pain syndrome, refractory to medical management, were treated with CT-guided intercostal nerve cryoablation. Most patients had treatment of the intercostal nerve at the level of their thoracotomy scar, two levels above and below. The safety and technical success of this technique and the clinical outcomes of the study population were then retrospectively reviewed.RESULTSOf the patients, 69% experienced significant improvement in their pain symptoms with a median pain improvement score of 3 points (range, -1 to 8 points) over a median follow-up of 11 months (range, 2–18.6 months). Complications included pneumothorax in 8% and pseudohernia in 23% of patients.CONCLUSIONCT-guided intercostal nerve cryoablation may be an effective technique in the treatment of post-thoracotomy pain syndrome and requires further study

Role of non-coding RNA networks in leukemia progression, metastasis and drug resistance.

Early-stage detection of leukemia is a critical determinant for successful treatment of the disease and can increase the survival rate of leukemia patients. The factors limiting the current screening approaches to leukemia include low sensitivity and specificity, high costs, and a low participation rate. An approach based on novel and innovative biomarkers with high accuracy from peripheral blood offers a comfortable and appealing alternative to patients, potentially leading to a higher participation rate.Recently, non-coding RNAs due to their involvement in vital oncogenic processes such as differentiation, proliferation, migration, angiogenesis and apoptosis have attracted much attention as potential diagnostic and prognostic biomarkers in leukemia. Emerging lines of evidence have shown that the mutational spectrum and dysregulated expression of non-coding RNA genes are closely associated with the development and progression of various cancers, including leukemia. In this review, we highlight the expression and functional roles of different types of non-coding RNAs in leukemia and discuss their potential clinical applications as diagnostic or prognostic biomarkers and therapeutic targets

The future of care work: towards a radical politics of care in CSCW research and practice

Computer-Supported Cooperative Work (CSCW) and Human- Computer Interaction (HCI) have long studied how technology can support material and relational aspects of care work, typically in clinical healthcare settings. More recently, we see increasing recognition of care work such as informal healthcare provision, child and elderly care, organizing and advocacy, domestic work, and service work. However, the COVID-19 pandemic has underscored long-present tensions between the deep necessity and simultaneous devaluation of our care infrastructures. This highlights the need to attend to the broader social, political, and economic systems that shape care work and the emerging technologies being used in care work. This leads us to ask several critical questions: What counts as care work and why? How is care work (de)valued, (un)supported, or coerced under capitalism and to what end? What narratives drive the push for technology in care work and whom does it benefit? How does care work resist or build resilience against and within oppressive systems? And how can we as researchers advocate for and with care and caregivers? In this one-day workshop, we will bring together researchers from academia, industry, and community-based organizations to reflect on these questions and extend conversations on the future of technology for care work