Stress and Strain Distributions during Machining of Ti-6Al-4V at Ambient and Cryogenic Temperatures

Dry and liquid nitrogen pre-cooled Ti-6Al-4V samples were machined at a cutting speed of 43.2 m/min and at low (0.1 mm/rev) to high (0.4 mm/rev) feed rates for understanding the effects of temperature and strain rate on chip microstructures. During cryogenic machining, it was observed that between feed rates of 0.10 and 0.30 mm/rev, a 25% pressure reduction on tool occurred. Smaller number of chips and low tool/chip contact time and temperature were observed (compared to dry machining under ambient conditions). An in-situ set-up that consisted of a microscope and a lathe was constructed and helped to propose a novel serrated chip formation mechanism when microstructures (strain localization) and surface roughness were considered. Dimpled fracture surfaces observed in high-speed-machined chips were formed due to stable crack propagation that was also recorded during in-situ machining. An instability criterion was developed that showed easier strain localization within the 0.10-0.30mm/rev feed rate range

Invariant Scattering Transform for Medical Imaging

Invariant scattering transform introduces new area of research that merges the signal processing with deep learning for computer vision. Nowadays, Deep Learning algorithms are able to solve a variety of problems in medical sector. Medical images are used to detect diseases brain cancer or tumor, Alzheimer's disease, breast cancer, Parkinson's disease and many others. During pandemic back in 2020, machine learning and deep learning has played a critical role to detect COVID-19 which included mutation analysis, prediction, diagnosis and decision making. Medical images like X-ray, MRI known as magnetic resonance imaging, CT scans are used for detecting diseases. There is another method in deep learning for medical imaging which is scattering transform. It builds useful signal representation for image classification. It is a wavelet technique; which is impactful for medical image classification problems. This research article discusses scattering transform as the efficient system for medical image analysis where it's figured by scattering the signal information implemented in a deep convolutional network. A step by step case study is manifested at this research work.Comment: 11 pages, 8 figures and 1 tabl

Rethinking Watermark: Providing Proof of IP Ownership in Modern SoCs

Intellectual property (IP) cores are essential to creating modern system-on-chips (SoCs). Protecting the IPs deployed in modern SoCs has become more difficult as the IP houses have been established across the globe over the past three decades. The threat posed by IP piracy and overuse has been a topic of research for the past decade or so and has led to creation of a field called watermarking. IP watermarking aims of detecting unauthorized IP usage by embedding excess, nonfunctional circuitry into the SoC. Unfortunately, prior work has been built upon assumptions that cannot be met within the modern SoC design and verification processes. In this paper, we first provide an extensive overview of the current state-of-the-art IP watermarking. Then, we challenge these dated assumptions and propose a new path for future effective IP watermarking approaches suitable for today\u27s complex SoCs in which IPs are deeply embedded

ToSHI - Towards Secure Heterogeneous Integration: Security Risks, Threat Assessment, and Assurance

The semiconductor industry is entering a new age in which device scaling and cost reduction will no longer follow the decades-long pattern. Packing more transistors on a monolithic IC at each node becomes more difficult and expensive. Companies in the semiconductor industry are increasingly seeking technological solutions to close the gap and enhance cost-performance while providing more functionality through integration. Putting all of the operations on a single chip (known as a system on a chip, or SoC) presents several issues, including increased prices and greater design complexity. Heterogeneous integration (HI), which uses advanced packaging technology to merge components that might be designed and manufactured independently using the best process technology, is an attractive alternative. However, although the industry is motivated to move towards HI, many design and security challenges must be addressed. This paper presents a three-tier security approach for secure heterogeneous integration by investigating supply chain security risks, threats, and vulnerabilities at the chiplet, interposer, and system-in-package levels. Furthermore, various possible trust validation methods and attack mitigation were proposed for every level of heterogeneous integration. Finally, we shared our vision as a roadmap toward developing security solutions for a secure heterogeneous integration

Quantifiable Assurance: From IPs to Platforms

Hardware vulnerabilities are generally considered more difficult to fix than software ones because they are persistent after fabrication. Thus, it is crucial to assess the security and fix the vulnerabilities at earlier design phases, such as Register Transfer Level (RTL) and gate level. The focus of the existing security assessment techniques is mainly twofold. First, they check the security of Intellectual Property (IP) blocks separately. Second, they aim to assess the security against individual threats considering the threats are orthogonal. We argue that IP-level security assessment is not sufficient. Eventually, the IPs are placed in a platform, such as a system-on-chip (SoC), where each IP is surrounded by other IPs connected through glue logic and shared/private buses. Hence, we must develop a methodology to assess the platform-level security by considering both the IP-level security and the impact of the additional parameters introduced during platform integration. Another important factor to consider is that the threats are not always orthogonal. Improving security against one threat may affect the security against other threats. Hence, to build a secure platform, we must first answer the following questions: What additional parameters are introduced during the platform integration? How do we define and characterize the impact of these parameters on security? How do the mitigation techniques of one threat impact others? This paper aims to answer these important questions and proposes techniques for quantifiable assurance by quantitatively estimating and measuring the security of a platform at the pre-silicon stages. We also touch upon the term security optimization and present the challenges for future research directions

Knowledge, Attitude and Practices Towards Dengue Fever Among Slum Dwellers: A Case Study in Dhaka City, Bangladesh

Objectives: This study intends to evaluate Dhaka city slum dwellers’ responses to Dengue fever (DF).Methods: 745 individuals participated in a KAP survey that was pre-tested. Face-to-face interviews were performed to obtain data. Python with RStudio was used for data management and analysis. The multiple regression models were applied when applicable.Results: 50% of respondents were aware of the deadly effects of DF, its common symptoms, and its infectious nature. However, many were unaware that DF could be asymptomatic, a previously infected person could have DF again, and the virus could be passed to a fetus. Individuals agreed that their families, communities, and authorities should monitor and maintain their environment to prevent Aedes mosquito breeding. However, overall 60% of the study group had inadequate preventative measures. Many participants lacked necessary practices such as taking additional measures (cleaning and covering the water storage) and monitoring potential breeding places. Education and types of media for DF information were shown to promote DF prevention practices.Conclusion: Slum dwellers lack awareness and preventative activities that put them at risk for DF. Authorities must improve dengue surveillance. The findings suggest efficient knowledge distribution, community stimulation, and ongoing monitoring of preventative efforts to reduce DF. A multidisciplinary approach is needed to alter dwellers’ behavior since DF control can be done by raising the population’s level of life. People and communities must perform competently to eliminate vector breeding sites

Conductive textiles for signal sensing and technical applications

Conductive textiles have found notable applications as electrodes and sensors capable of detecting biosignals like the electrocardiogram (ECG), electrogastrogram (EGG), electroencephalogram (EEG), and electromyogram (EMG), etc; other applications include electromagnetic shielding, supercapacitors, and soft robotics. There are several classes of materials that impart conductivity, including polymers, metals, and non-metals. The most significant materials are Polypyrrole (PPy), Polyaniline (PANI), Poly(3,4-ethylenedioxythiophene) (PEDOT), carbon, and metallic nanoparticles. The processes of making conductive textiles include various deposition methods, polymerization, coating, and printing. The parameters, such as conductivity and electromagnetic shielding, are prerequisites that set the benchmark for the performance of conductive textile materials. This review paper focuses on the raw materials that are used for conductive textiles, various approaches that impart conductivity, the fabrication of conductive materials, testing methods of electrical parameters, and key technical applications, challenges, and future potential

Performance and emissions of diesel engine with circulation nonsurfactant emulsion fuel system

Diesel engine is known for its durable operation and capability of utilizing various type of fuels, however, dangerous exhaust emissions are emitted from diesel engines. Nonsurfactant emulsion fuel is a potential fuel for diesel engine to reduce for Nitrogen oxides (NOx) and Particulate matter (PM) emission compare to conventional diesel fuel in a diesel engine. In this study, emulsion fuel was prepared using a mixer known as Circulation Non-Surfactant Emulsion Fuel System. The study carried out with different water percentages in the emulsion fuel given as follows: 3%, 6%, and 9% and at a different engine load condition from 1-4 kW with a constant speed of 3200 rpm. Results show that, 6% emulsion fuel shows average 4.38% reduction in NOx emission and 1.10% reduction in fuel consumption. 9% emulsion fuel show higher amount of CO emission compare to Diesel while it reduces CO2 emission. Overall, 6% when prepared are recommended for the formation of non-surfactant emulsion fuel

COVID-19 among staff and their family members of a healthcare research institution in Bangladesh between March 2020 and April 2021 : a test-negative case–control study

Objective To identify factors associated with COVID- 19 positivity among staff and their family members of icddr,b, a health research institute located in Bangladesh. Setting Dhaka, Bangladesh. Participants A total of 4295 symptomatic people were tested for SARS-CoV-2 by reverse-transcription PCR between 19 March 2020 and 15 April 2021. Multivariable logistic regression was done to identify the factors associated with COVID- 19 positivity by contrasting test positives with test negatives. Result Forty-three per cent of the participants were tested positive for SARS-CoV-2. The median age was high in positive cases (37 years vs 34 years). Among the positive cases, 97% were recovered, 2.1% had reinfections, 24 died and 41 were active cases as of 15 April 2021. Multivariable regression analysis showed that age more than 60 years (adjusted OR (aOR)=2.1, 95% CI 1.3 to 3.3; pwere tested negative. Conclusions The study findings suggest that older age, fever, cough and anosmia were associated with COVID- 19 among the study participants.publishedVersionPeer reviewe

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries