Switched capacitor, self referencing sensing scheme for high density magneto-resistive memories

Magneto-resistive elements have possible applications in memories and sensors. Recently considerable effort has been directed towards the development of high density magneto-resistive memories. This research includes work in many areas such as obtaining cells with higher signal levels, densification of storage cells and the development of an appropriate sensing scheme. This dissertation deals with the development of latter stages of a multi stage sensing scheme for a large magneto-resistive memory. In this sensing scheme the signal of a actual element is compared against the signal from a dummy element. The resulting signal is stored and again is compared against a signal of opposite polarity which is generated from the same element. This process is called self referencing and is done to minimize offset problems. The special features of this sensing scheme are: the balanced sensing where the signal from the actual and the dummy elements are balanced to have identical time constants, a two stage switched capacitor auto-zero scheme where the DC offsets between the two elements due to mismatch is removed while generating very little noise and self referencing which is done by a sample and compare circuit. This self referencing process increases the bit density by 50% and the two stage auto-zero significantly reduces read access time. The memory is nonvolatile, radiation hard and is designed to have a read access time of 800ns

A low-noise small signal sensing scheme in voltage mode for high density magnetoresistive memories

Magnetoresistive memory (MRAM) technology which successfully combines integrated circuit and magnetic thin film processes to achieve non-volatile, radiation hard, random access read/write memories, has shown rapid development in the past few years. A considerable amount of research effort is directed towards improving the bit density, which involves the design of denser cells with improved signal levels, and development of suitable sensing schemes. This dissertation presents work done in developing the low noise front end of a multistage small signal sensing scheme, designed for high density MRAMs. The design scheme uses a new sensing mode called \u27voltage mode\u27, instead of \u27current mode\u27 which is presently in use. An analysis of both current mode and voltage mode sensing has been carried out to show that voltage mode has superior performance. This scheme uses self referencing to reduce the memory cell area. All critical deterrant factors that affect this technique have been analyzed and suitable strategies have been developed to minimize their effect. This scheme senses a nominal signal of 0.4 mV in the presence of large voltage offsets which are 100 mV in the worst case. The memory cell area has been reduced to 25 square microns per bit and the read access time is 800 ns

Novel Software Defined Power Supply Utilizing Power Supply on Chip -Power supply which outputs the regulated output voltage by only connecting the load-

In this paper, we propose a novel software defined power supply using the general purpose DSP (Digital Signal Processor) and its control algorithm based on power supply on chip. The proposed power supply can regulate the output voltage only loading a program into the DSP without adjusting the parameters and changing the external parts. Also, it can change the output voltage according to the state of the load by executive instruction from the load. The simulation results show that the transient response depends on the inductance, the capacitance and the internal resistance, and expects sub-μ s. at switching frequency of 30 MHz.21st European Conference on Power Electronics and Applications (EPE \u2719 ECCE Europe), September 2-6, 2019, Genova, Ital

Evaluating the Effect of Non-cellular Bioactive Glass-Containing Scaffolds on Osteogenesis and Angiogenesis in in vivo Animal Bone Defect Models

The use of bone scaffolds to replace injured or diseased bone has many advantages over the currently used autologous and allogeneic options in clinical practice. This systematic review evaluates the current evidence for non-cellular scaffolds containing bioactive glass on osteogenesis and angiogenesis in animal bone defect models. Studies that reported results of osteogenesis via micro-CT and results of angiogenesis via Microfil perfusion or immunohistochemistry were included in the review. A literature search of PubMed, EMBASE and Scopus was carried out in November 2019 from which nine studies met the inclusion and exclusion criteria. Despite the significant heterogeneity in the composition of the scaffolds used in each study, it could be concluded that scaffolds containing bioactive glass improve bone regeneration in these models, both by osteogenic and angiogenic measures. Incorporation of additional elements into the glass network, using additives, and using biochemical factors generally had a beneficial effect. Comparing the different compositions of non-cellular bioactive glass containing scaffolds is however difficult due to the heterogeneity in bioactive glass compositions, fabrication methods and biochemical additives used

Antiferromagnetic CuMnAs multi-level memory cell with microelectronic compatibility

Antiferromagnets offer a unique combination of properties including the radiation and magnetic field hardness, the absence of stray magnetic fields, and the spin-dynamics frequency scale in terahertz. Recent experiments have demonstrated that relativistic spin-orbit torques can provide the means for an efficient electric control of antiferromagnetic moments. Here we show that elementary-shape memory cells fabricated from a single-layer antiferromagnet CuMnAs deposited on a III–V or Si substrate have deterministic multi-level switching characteristics. They allow for counting and recording thousands of input pulses and responding to pulses of lengths downscaled to hundreds of picoseconds. To demonstrate the compatibility with common microelectronic circuitry, we implemented the antiferromagnetic bit cell in a standard printed circuit board managed and powered at ambient conditions by a computer via a USB interface. Our results open a path towards specialized embedded memory-logic applications and ultra-fast components based on antiferromagnets

Quantitative analysis of the ACL and PCL using T1rho and T2 relaxation time mapping: an exploratory, cross-sectional comparison between OA and healthy control knees.

BACKGROUND: Quantitative magnetic resonance imaging (MRI) methods such as T1rho and T2 mapping are sensitive to changes in tissue composition, however their use in cruciate ligament assessment has been limited to studies of asymptomatic populations or patients with posterior cruciate ligament tears only. The aim of this preliminary study was to compare T1rho and T2 relaxation times of the anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) between subjects with mild-to-moderate knee osteoarthritis (OA) and healthy controls. METHODS: A single knee of 15 patients with mild-to-moderate knee OA (Kellgren-Lawrence grades 2-3) and of 6 age-matched controls was imaged using a 3.0 T MRI. Three-dimensional (3D) fat-saturated spoiled gradient recalled-echo images were acquired for morphological assessment and T1ρ- and T2-prepared pseudo-steady-state 3D fast spin echo images for compositional assessment of the cruciate ligaments. Manual segmentation of whole ACL and PCL, as well as proximal / middle / distal thirds of both ligaments was carried out by two readers using ITK-SNAP and mean relaxation times were recorded. Variation between thirds of the ligament were assessed using repeated measures ANOVAs and differences in these variations between groups using a Kruskal-Wallis test. Inter- and intra-rater reliability were assessed using intraclass correlation coefficients (ICCs). RESULTS: In OA knees, both T1rho and T2 values were significantly higher in the distal ACL when compared to the rest of the ligament with the greatest differences in T1rho (e.g. distal mean = 54.5 ms, proximal = 47.0 ms, p < 0.001). The variation of T2 values within the PCL was lower in OA knees (OA: distal vs middle vs proximal mean = 28.5 ms vs 29.1 ms vs 28.7 ms, p = 0.748; Control: distal vs middle vs proximal mean = 26.4 ms vs 32.7 ms vs 33.3 ms, p = 0.009). ICCs were excellent for the majority of variables. CONCLUSION: T1rho and T2 mapping of the cruciate ligaments is feasible and reliable. Changes within ligaments associated with OA may not be homogeneous. This study is an important step forward in developing a non-invasive, radiological biomarker to assess the ligaments in diseased human populations in-vivo.Declarations Ethics approval and consent to participate This study was approved by the East of England Cambridge Central Research Ethics Committee and written informed consent was given by all subjects included in the study. All methods were carried out in accordance with relevant guidelines and regulations. Consent for publication Not Applicable Availability of data and materials The datasets generated and analysed during the current study are not publicly available due to unattained permission from participants and research ethics committee but could be made available from JWM (email: [email protected]). Competing interests JWM, DAK and JDK acknowledge funding support from GlaxoSmithKline for their studentships and fellowships, respectively. JWM is an employee of AstraZeneca. CDSR, VAC and SMM have no competing interests to declare. Acknowledgements The Addenbrooke's Hospital Magnetic Resonance Imaging and Spectroscopy (MRIS) staff are thanked for their help with arranging and conducting the study MRI examinations. We also acknowledge the support of the Addenbrooke's Charitable Trust and the National Institute for Health Research Cambridge Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Funding The study was funded by an Experimental Medicine Initiative PhD studentship from the University of Cambridge [grant number RG81329] and by GlaxoSmithKline [grant number RG87552]. Authors' contributions Writing of original draft manuscript: CDSR. Study design and coordination: CDSR, JWM, JDK and SMM. Data acquisition: JWM and JDK. Data curation, analysis and interpretation: CDSR, JWM, VAC, JDK, DAK and SMM. Statistical analysis: CDSR and JWM. Review and editing of manuscript: JWM, VAC, JDK, DAK and SMM. All authors read and approved the final manuscript

Recognising Skin Cancer in Primary Care

Abstract: Skin cancer, including melanoma, basal cell carcinoma and cutaneous squamous cell carcinoma, has one of the highest global incidences of any form of cancer. In 2016 more than 16,000 people were diagnosed with melanoma in the UK. Over the last decade the incidence of melanoma has increased by 50% in the UK, and about one in ten melanomas are diagnosed at a late stage. Among the keratinocyte carcinomas (previously known as non-melanoma skin cancers), basal cell carcinoma is the most common cancer amongst Caucasian populations. The main risk factor for all skin cancer is exposure to ultraviolet radiation—more than 80% are considered preventable. Primary care clinicians have a vital role to play in detecting and managing patients with skin lesions suspected to be skin cancer, as timely diagnosis and treatment can improve patient outcomes, particularly for melanoma. However, detecting skin cancer can be challenging, as common non-malignant skin lesions such as seborrhoeic keratoses share features with less common skin cancers. Given that more than 80% of skin cancers are attributed to ultraviolet (UV) exposure, primary care clinicians can also play an important role in skin cancer prevention. This article is one of a series discussing cancer prevention and detection in primary care. Here we focus on the most common types of skin cancer: melanoma, squamous cell carcinoma and basal cell carcinoma. We describe the main risk factors and prevention advice. We summarise key guidance on the symptoms and signs of skin cancers and their management, including their initial assessment and referral. In addition, we review emerging technologies and diagnostic aids which may become available for use in primary care in the near future, to aid the triage of suspicious skin lesions

Recognising Skin Cancer in Primary Care

Abstract: Skin cancer, including melanoma, basal cell carcinoma and cutaneous squamous cell carcinoma, has one of the highest global incidences of any form of cancer. In 2016 more than 16,000 people were diagnosed with melanoma in the UK. Over the last decade the incidence of melanoma has increased by 50% in the UK, and about one in ten melanomas are diagnosed at a late stage. Among the keratinocyte carcinomas (previously known as non-melanoma skin cancers), basal cell carcinoma is the most common cancer amongst Caucasian populations. The main risk factor for all skin cancer is exposure to ultraviolet radiation—more than 80% are considered preventable. Primary care clinicians have a vital role to play in detecting and managing patients with skin lesions suspected to be skin cancer, as timely diagnosis and treatment can improve patient outcomes, particularly for melanoma. However, detecting skin cancer can be challenging, as common non-malignant skin lesions such as seborrhoeic keratoses share features with less common skin cancers. Given that more than 80% of skin cancers are attributed to ultraviolet (UV) exposure, primary care clinicians can also play an important role in skin cancer prevention. This article is one of a series discussing cancer prevention and detection in primary care. Here we focus on the most common types of skin cancer: melanoma, squamous cell carcinoma and basal cell carcinoma. We describe the main risk factors and prevention advice. We summarise key guidance on the symptoms and signs of skin cancers and their management, including their initial assessment and referral. In addition, we review emerging technologies and diagnostic aids which may become available for use in primary care in the near future, to aid the triage of suspicious skin lesions

Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings : a systematic review

Acknowledgments This systematic review was funded by the National Institute for Health Research Policy Research Programme, conducted through the Policy Research Unit in Cancer Awareness, Screening, and Early Diagnosis (PR-PRU-1217–21601). The views expressed in this publication are those of the authors and not necessarily those of the National Health Service, the NIHR or the Department of Health and Social Care. The first author (OTJ) was also supported by the CanTest Collaborative funded by Cancer Research UK (C8640/A23385), of which FMW is Director, JE is an Associate Director, and NC is Research Fellow. During protocol development, this Review benefited from the advice of an international expert panel from the CanTest collaborative, including Willie Hamilton (University of Exeter, Exeter, UK), Greg Rubin (University of Newcastle, Newcastle, UK), Hardeep Singh (Baylor College of Medicine, Houston, TX, USA), and Niek de Wit (University Medical Center Utrecht, Utrecht, Netherlands). The research was also supported by a Cancer Research UK Cambridge Centre Clinical Research Fellowship for OTJ, and a National Health and Medical Research Council Investigator Fellowship (APP1195302) for JE. The funding sources had no role in the study design, data collection, data analysis, data interpretation, writing of the report, or in the decision to submit for publication. The authors would like to thank Isla Kuhn (Reader Services Librarian, University of Cambridge Medical Library, Cambridge, UK) for her help in developing the search strategy. We also thank Smiji Saji, who assisted with the early stages of the Review, Haruyuki Yanaoka, who assisted with the translation and assessment of papers that were written in Korean, and Steve Morris who assisted with the analysis of the data.Peer reviewedPublisher PD