Miracle-dz/UniFAR-FTUs huggingface dataset:
A Reconfigurable Pipelined Architecture for Convolutional Neural Network Acceleration

The convolutional neural network (CNN) has become widely used in a variety of vision recognition applications, and the hardware acceleration of CNN is in urgent need as increasingly more computations are required in the state-of-the-art CNN networks. In this paper, we propose a pipelined architecture for CNN acceleration. The probability of both inner-layer and inter-layer pipeline for typical CNN networks is analyzed. And two types of data re-ordering methods, the filter-first (FF) flow and the image-first (IF) flow, are proposed for different kinds of layers. Then, a pipelined CNN accelerator for AlexNet is implemented, the dataflow of which can be reconfigurably selected for different layer processing. Simulation results show that the proposed pipelined architecture achieves 43% performance improvement compared with the non-pipelined ones. The AlexNet accelerator is implemented in 65nm CMOS technology working at 200MHz, with 350mW power consumption and 24GFLOPS peak performance.
Identifying health policy and systems research priorities on multisectoral collaboration for health in low-income and middle-income countries

Introduction While efforts to achieve Universal Health Coverage (UHC) and the Sustainable Development Goals (SDGs) have reinvigorated interest in multisectoral collaborations (MSCs) among the global health and development community, there remains a plethora of questions about how best to conceptualise, plan, implement, evaluate and sustain MSCs. The objective of this paper is to present research priorities on MSC for health from researchers and policymakers around the globe, with an emphasis on low-income and middle-income countries. Methods The authors identified 30 priority research questions from two sources: (1) 38 review articles on MSC for health, and (2) interviews and focus groups with a total of 81 policymakers, including government officials (largely from ministries of health and state/provincial departments of health, but also offices of planning, public service, social development, the prime minister and others), large multilateral or bilateral organisations, and non-governmental organisations. In a third phase, questions were refined and ranked by a diverse group of researchers from around the globe using an online voting platform. Results The top-ranked questions focused predominantly on pragmatic questions, such as how best to structure, implement and sustain MSCs, as well as how to build stakeholder capacity and community partnerships. Despite substantial variation between review articles, policymakers’ reflections and online ranking by researchers, two topics emerged as research priorities for all three: (1) leadership, partnership and governance structures for MSCs; and (2) MSC implementation strategies and mechanisms. The review articles underscored the need for more guidance on appropriate study designs and methods for investigating MSCs, which may be a prerequisite for other identified research priorities. Conclusion These findings could inform efforts within and beyond the health sector to better align research objectives and funding with the evidence needs of policymakers grappling with questions about how best to leverage MSCs to achieve UHC and the SDGs.
Detection of Polycyclic Aromatic Hydrocarbons in Water Samples by Annular Platform-Supported Ionic Liquid-Based Headspace Liquid-Phase Microextraction

In this paper, a new method of annular platform-supported headspace liquid-phase microextraction (LPME) was designed using ionic liquid as an extraction solvent, wherein extraction stability and efficiency were improved by adding an annular platform inside the extraction bottle. The ionic liquid 1-silicyl-3-benzylimidazolehexafluorophosphate was first synthesized and proved to be an excellent extraction solvent. Coupled with liquid chromatography, the proposed method was employed to analysis of polycyclic aromatic hydrocarbons (PAHs) in water and optimized in aspects of extraction temperature, extraction solvent volume, extraction time, pH, stirring rate, and salt effect of solution. The results indicated that this method showed good linearity (R2 > 0.995) within 0.5 µg·L−1 to 1000 µg·L−1 for PAHs. The method was more suitable for extraction of volatile PAHs, with recoveries from 65.0% to 102% and quantification limits from 0.01 to 0.05 µg·L−1. It has been successfully applied for detection of PAHs in seawater samples.
Smart Pet Clothing for Monitoring of Health and Mood

A smart pet clothing with full hardware and software support for internet of things is proposed. The hardware comprises three parts: a special pet sensor, an analog front-end circuit for detecting electrocardiogram (ECG) and breath signals, and a micro printed circuit board with signal communication. The software also consists of three parts: an algorithm for biosignal processing, an application (app) as graphical user interface (GUI), and a web server for healthcare. The algorithm is used to calculate the heart rate (HR), HR variability (HRV), high-to-low-frequency ratio determined by HRV analysis, breath rate, and basic emotion analysis. The app is developed for building a user-friendly GUI and communication platform between the hardware device and the cloud server. The web server not only provides detailed information to the veterinarian and the pet owner but also runs a convolutional neural network algorithm on big data to identify abnormal ECG signals. The analog front-end circuits with ECG and breath detectors, an ARM Cortex M0 MCU, and Bluetooth and power modules are integrated into a device with the size of a coin that can be placed in an approximately 32 mm χ 32 mm × 24 mm box. The mechanism can be easily worn on clothing for monitoring pet health and mood.
Portable photoacoustic system for noninvasive blood temperature measurement

A miniaturized sensing system for noninvasive measurement of blood temperature with relatively deeper penetration has being long pursued with limited success. Here, we develop a novel photoacoustics based portable sensor for noninvasive monitoring of blood temperature with high accuracy, deep penetration depth and real time capability. Optical module (laser diode with collimation lens) and acoustic module (ring ultrasound transducer with an optical/acoustic transparent Polydimethylsiloxane coupling layer) of the system is integrated to a compact sensor head with a size similar to a human thumb. Main body is battery-powered to provide the laser driver, data acquisition and also signal processing. The overall system size is around 14 cm×8 cm×3 cm. Temperature calibration and measurement is demonstrated both on phantom and animal to achieve a high accuracy of 0.2 and 0.5 degree respectively, with a fast refreshing speed of 80 Hz. In the future, such developed photoacoustic temperature sensing device can potentially become a wearable patch sensor with further miniaturization of laser diode and use of MEMS-based piezoelectric micro-machined ultrasonic transducers (PMUT).
The Neural Basis of Individual Differences in Directional Sense

Individuals differ greatly in their ability to learn and navigate through environments. One potential source of this variation is “directional sense” or the ability to identify, maintain, and compare allocentric headings. Allocentric headings are facing directions that are fixed to the external environment, such as cardinal directions. Measures of the ability to identify and compare allocentric headings, using photographs of familiar environments, have shown significant individual and strategy differences; however, the neural basis of these differences is unclear. Forty-five college students, who were highly familiar with a campus environment and ranged in self-reported sense-of-direction, underwent fMRI scans while they completed the Relative Heading task, in which they had to indicate the direction of a series of photographs of recognizable campus buildings (i.e., “target headings”) with respect to initial “orienting headings. ” Large individual differences were found in accuracy and correct decision latencies, with gender, self-reported sense-of-direction, and familiarity with campus buildings all predicting task performance. Using linear mixed models, the directional relationships between headings and the experiment location also impacted performance. Structural scans revealed that lateral orbitofrontal and superior parietal volume were related to task accuracy and decision latency, respectively. Bilateral hippocampus and right presubiculum volume were related to self-reported sense-of-direction. Meanwhile, functional results revealed clusters within the superior parietal lobule, supramarginal gyrus, superior frontal gyrus, lateral orbitofrontal cortex, and caudate among others in which the intensity of activation matched the linear magnitude of the difference between the orienting and target headings. While the retrosplenial cortex and hippocampus have previously been implicated in the coding of allocentric headings, this work revealed that comparing those headings additionally involved frontal and parietal regions. These results provide insights into the neural bases of the variation within human orientation abilities, and ultimately, human navigation.
Efficient Fixed/Floating-Point Merged Mixed-Precision Multiply-Accumulate Unit for Deep Learning Processors

Deep learning is getting more and more attentions in recent years. Many hardware architectures have been proposed for efficient implementation of deep neural network. The arithmetic unit, as a core processing part of the hardware architecture, can determine the functionality of the whole architecture. In this paper, an efficient fixed/floating-point merged multiply-accumulate unit for deep learning processor is proposed. The proposed architecture supports 16-bit half-precision floating-point multiplication with 32-bit single-precision accumulation for training operations of deep learning algorithm. In addition, within the same hardware, the proposed architecture also supports two parallel 8-bit fixed-point multiplications and accumulating the products to 32-bit fixed-point number. This will enable higher throughput for inference operations of deep learning algorithms. Compared to a half-precision multiply-accumulate unit (accumulating to single-precision), the proposed architecture has only 4.6% area overhead. With the proposed multiply-accumulate unit, the deep learning processor can support both training and high-throughput inference.
Sparse functional link adaptive filter using an ℓ1-norm regularization

Linear-in-the-parameters nonlinear adaptive filters often show some sparse behavior due to the fact that not all the coefficients are equally useful for the modeling of any nonlinearity. Recently, proportionate algorithms have been proposed to leverage sparsity behaviors in nonlinear filtering. In this paper, we deal with this problem by introducing a proportionate adaptive algorithm based on an ℓ1-norm penalty of the cost function, which regularizes the solution, to be used for a class of nonlinear filters based on functional links. The proposed algorithm stresses the difference between useful and useless functional links for the purpose of nonlinear modeling. Experimental results clearly show faster convergence performance with respect to the standard (i.e., non-regularized) version of the algorithm.
A 2-GHz Direct Digital Frequency Synthesizer Based on LUT and Rotation

This paper proposes a direct digital frequency synthesizer (DDFS) based on Lookup-Table-Rotation (LUT-ROT) architecture. The DDFS takes the advantages of coarse-fine LUT and pipelined rotation units to achieve both high-speed and high-resolution. Based on the analysis of approximation error, the trade-off between accuracy and memory usage is achieved, which leads to the lowest amplitude of noise and the smallest size of LUT. Experimental results show that the DDFS achieves 11.7mW/GHz power consumption and 96dBc SFDR in 2-GHz clock frequency.
Cerebrovascular Pathology in Hypertriglyceridemic APOB-100 Transgenic Mice

Hypertriglyceridemia is not only a serious risk factor in the development of cardiovascular diseases, but it is linked to neurodegeneration, too. Previously, we generated transgenic mice overexpressing the human APOB-100 protein, a mouse model of human atherosclerosis. In this model we observed high plasma levels of triglycerides, oxidative stress, tau hyperphosphorylation, synaptic dysfunction, cognitive impairment, increased neural apoptosis and neurodegeneration. Neurovascular dysfunction is recognized as a key factor in the development of neurodegenerative diseases, but the cellular and molecular events linking cerebrovascular pathology and neurodegeneration are not fully understood. Our aim was to study cerebrovascular changes in APOB-100 transgenic mice. We described the kinetics of the development of chronic hypertriglyceridemia in the transgenic animals. Increased blood-brain barrier permeability was found in the hippocampus of APOB-100 transgenic mice which was accompanied by structural changes. Using transmission electron microscopy, we detected changes in the brain capillary endothelial tight junction structure and edematous swelling of astrocyte endfeet. In brain microvessels isolated from APOB-100 transgenic animals increased Lox-1, Aqp4, and decreased Meox-2, Mfsd2a, Abcb1a, Lrp2, Glut-1, Nos2, Nos3, Vim, and in transgenic brains reduced Cdh2 and Gfap-σ gene expressions were measured using quantitative real-time PCR. We confirmed the decreased P-glycoprotein (ABCB1) and vimentin expression related to the neurovascular unit by immunostaining in transgenic brain sections using confocal microscopy. We conclude that in chronic hypertriglyceridemic APOB-100 transgenic mice both functional and morphological cerebrovascular pathology can be observed, and this animal model could be a useful tool to study the link between cerebrovascular pathology and neurodegeneration.
Do Focal Chondral Defects of the Knee Increase the Risk for Progression to Osteoarthritis? A Review of the Literature

Background: Focal chondral defects (FCDs) of the knee are believed to contribute to the development of osteoarthritis (OA), resulting in pain and dysfunction. Purpose: To investigate whether untreated FCDs of the knee progress to radiographically evident OA over time. Study Design: Systematic review; Level of evidence, 3. Methods: A literature review was performed by searching the PubMed, Embase, and Cochrane Library databases to locate studies evaluating clinical and/or radiological outcomes of patients with FCDs that were diagnosed by arthroscopic surgery or magnetic resonance imaging (MRI) and were left untreated with a minimum 2-year follow-up. Additionally, studies were included if there was a radiographic assessment of OA. Search terms used were “knee,” “focal,” “isolated,” “chondral,” “cartilage,” and “osteoarthritis. ” Studies were evaluated based on clinical/radiological outcomes and OA risk factors. The study methodology was assessed using the modified Coleman Methodology Score. Results: Eight studies comprising 1425 knees met the inclusion criteria. All studies were of level 3 evidence. The risk of incident cartilage damage (enlargement of original FCDs or incidence of additional FCDs) at latest follow-up was assessed in 3 studies, while 1 study only reported the incidence of cartilage damage at follow-up. All 4 studies noted an increased progression of cartilage damage at follow-up. The progression of cartilage damage was most commonly seen in the patellofemoral joint and medial femoral condyle but was not associated with the development of knee OA based on the Kellgren-Lawrence grade. MRI of the FCDs revealed increased water content, cartilage deterioration, and proteoglycan loss within the medial and lateral compartments. Conclusion: Patients with untreated FCDs of the knee joint are more likely to experience a progression of cartilage damage, although the studies included in this review did not demonstrate the development of radiographically evident OA within 2 years of follow-up.
Investigation on the Gate Bias Voltage of BigFET in Power-rail ESD Clamp Circuit for Enhanced Transient Noise Immunity

This paper investigates the bigFET gate bias voltage in power-rail electrostatic discharge (ESD) clamp circuit for enhanced transient noise immunity. Based on a timed shutoff circuit, a resistor pair is employed to bias the bigFET gate voltage to different ratios of VDD. Through detailed investigations, an optimized bigFET gate bias scheme is proposed. With the optimized scheme, enhanced transient noise immunity of the investigated circuit is achieved. Besides, the optimized scheme can induce the channel and parasitic bipolar junction transistor parallel shunt paths in ESD events, which result in a lower on-resistance. Moreover, the optimized scheme is also validated in the high-threshold-voltage bigFET samples.
The EcoChip: A Wireless Multi-Sensor Platform for Comprehensive Environmental Monitoring

This paper presents the EcoChip, a new system based on the state-of-the-art electro-chemical impedance (EIS) technologies allowing the growth of single strain organisms isolated from northern habitats. This portable system is a complete and autonomous wireless platform designed to monitor and cultivate microorganisms directly sampled from their natural environment, particularly from harsh northern environments. Using 96-well plates, the EcoChip can be used in the field for real-time monitoring of bacterial growth. Manufactured with high-quality electronic components, this new EIS monitoring system is designed to function at a low excitation voltage signal to avoid damaging the cultured cells. The high-precision calibration network leads to high-precision results, even in the most limiting contexts. Luminosity, humidity, and temperature can also be monitored with the addition of appropriate sensors. Access to robust data storage systems and power supplies is an obvious limitation for northern research. That is why the EcoChip is equipped with a flash memory that can store data over long periods of time. To resolve the power issue, a low-power micro-controller and a power management unit control and supply all electronic building blocks. Data stored in the EcoChip's flash memory can be transmitted through a transceiver whenever a receiver is located within the functional transmission range. In this paper, we present the measured performance of the system, along with results from laboratory tests in vitro and from two field tests. The EcoChip has been utilized to collect bio-environemental data in the field from the northern soils and ecosystems of Kuujjuarapik and Puvirnituq, during two expeditions, in 2017 and 2018, respectively. We show that the EcoChip can effectively carry out EIS analyses over an excitation frequency ranging from 750 Hz to 10 kHz with an accuracy of 2.35%. The overall power consumption of the system was 140.4 mW in normal operating mode and 81 μW in sleep mode. The proper development of the isolated bacteria was confirmed through deoxyribonucleic acid sequencing, indicating that bacteria thrive in the EcoChip's culture wells while the growing conditions are successfully gathered and stored.
An Iterative Reweighted Minimax Algorithm for the Design of FRM-based Two-channel QMF Banks

The optimal design of two-channel FIR quadrature mirror filter (QMF) banks based on the Frequency-Response-Masking (FRM) technique is studied in this paper. An iterative algorithm is proposed to design a prototype filter. In each iteration of the algorithm, the prototype filter is optimized in the constrained weighted minimax sense with the weighting function being updated for reducing the reconstruction error of the filter banks. Further, we give an alternating variable approach to solving these constrained weighted minimax design problems of FRM filters. Specifically, it converts the nonlinear best approximation problem into a series of linear best approximation subproblems and solves each one using an efficient Goldfarb-Idnani based algorithm. The proposed filter banks have lower overall arithmetic complexity compared with the conventional ones. An example is presented and the simulation results show the proposed method performs better than an existing method.
Obstetric antiphospholipid syndrome

The present clinical and laboratory classification criteria for antiphospholipid syndrome (APS) were established in Sydney, Australia, in 2006. In this review, we focus on the obstetric subset of APS (OAPS), defined by persistent positivity for antiphospholipid antibodies together with either early recurrent pregnancy loss, early fetal death, stillbirth or premature birth <34 gestational weeks due to pre-eclampsia, eclampsia and placental insufficiency. It is important to diagnose these cases since most women suffering from OAPS can, when given appropriate treatment, have successful pregnancies. Furthermore, patients with OAPS may, depending on the antibody profile, be at enhanced risk of thrombotic events later in life. We present an update on the present knowledge of possible underlying pathogenesis, risk factors and risk estimations for adverse pregnancy outcomes before and during pregnancy, current treatment concepts, and long-term outcomes for women with OAPS and their children.
Village Health Sanitation and Nutrition Committees: reflections on strengthening community health governance at scale in India

India’s National Health Mission constituted Village Health Sanitation and Nutrition Committees (VHSNCs) as a key mechanism for community health governance. Health committees provide citizens with the opportunity to shape health systems and policies. Yet much remains to be learnt on how best to sustain health committees as vehicles for community health governance at scale. This paper reflects on the authors’ experiences of introducing revised guidelines and an institutional support package for VHSNCs in two pilot settings in India and outlines lessons we learnt for sustaining community health governance at geographic scale. We describe the importance of ensuring norms for equitable participation, aligning committee rules with existing forms of decentralised government and providing key supports in terms of engaging NGOs as key implementation facilitators. Integration with rigid and unresponsive government administrative structures however remains a persistent challenge for scaling up health committees. With sustained financial support and strategic deployment of key personnel, VHSNCs could pave the way for more equitable and effective community participation in health governance at scale.
Folded Cascode OTA with 5540 MHzpF/mA FoM

A micropower single-stage folded cascode amplifier able to drive a wide range of capacitive loads is presented. It features class AB operation and includes power-efficient adaptive biasing techniques, which provide enhanced dynamic output current boosting and gain-bandwidth product (GBW). Phase lead compensation is used to improve phase margin and settling performance for low capacitive loads. Measurement results for a 0.5 μm CMOS process show a FoM of 5540 MHz pF/mA, the highest one reported to date for a folded cascode amplifier to the authors' knowledge.