Search

As the heartbeat detection from ballistocardiogram (BCG) signals using force sensors is interfered by respiratory effort and artifact motion, advanced signal processing algorithms are required to detect the J-peak of each BCG signal so that beat-to-beat interval can be identified. However, existing methods generally rely on rule-based detection of a fixed size, without considering the rhythm features in a large time scale covering multiple BCG signals. Methods. This paper develops a deep learning framework based on ResNet and bidirectional long short-term memory (BiLSTM) to conduct beat-to-beat detection of BCG signals. Unlike the existing methods, the proposed network takes multiscale features of BCG signals as the input and, thus, can enjoy the complementary advantages of both morphological features of one BCG signal and rhythm features of multiple BCG signals. Different time scales of multiscale features for the proposed model are validated and analyzed through experiments. Results. The BCG signals recorded from 21 healthy subjects are conducted to verify the performance of the proposed heartbeat detection scheme using leave-one-out cross-validation. The impact of different time scales on the detection performance and the performance of the proposed model for different sleep postures are examined. Numerical results demonstrate that the proposed multiscale model performs robust to sleep postures and achieves an averaged absolute error E abs and an averaged relative error E rel of the heartbeat interval relative to the R-R interval of 9.92 ms and 2.67 ms, respectively, which are superior to those of the state-of-the-art detection protocol. Conclusion. In this work, a multiscale deep-learning model for heartbeat detection using BCG signals is designed. We demonstrate through the experiment that the detection with multiscale features of BCG signals can provide a superior performance to the existing works. Further study will examine the ultimate performance of the multiscale model in practical scenarios, i.e., detection for patients suffering from cardiovascular disorders with night-sleep monitoring.

Cell-specific aptamers offer a powerful tool to study membrane receptors at the single-molecule level. Most target receptors of aptamers are highly expressed on the cell surface, but difficult to analyze in situ because of dense distribution and fast velocity. Therefore, we herein propose a random sampling-based analysis strategy termed ligand dilution analysis (LDA) for easily implemented aptamer-based receptor study. Receptor density on the cell surface can be calculated based on a regression model. By using a synergistic ligand dilution design, colocalization and differentiation of aptamer and monoclonal antibody (mAb) binding on a single receptor can be realized. Once this is accomplished, precise binding site and detailed aptamer-receptor binding mode can be further determined using molecular docking and molecular dynamics simulation. The ligand dilution strategy also sets the stage for an aptamer-based dynamics analysis of two- and three-dimensional motion and fluctuation of highly expressed receptors on the live cell membrane.

In retrospect, the experience of work on the physical development of people with disabilities and people with disabilities is considered

Natural cells (NCs) can automatically and continuously respond to fluctuant external information and distinguish meaningful stimuli from weak noise depending on their powerful genetic and protein networks. We herein report a network topology–directed design of dynamic molecular processing system (DMPS) as a molecular central processing unit that powers an artificial cell (AC) able to process fluctuant information in its immediate environment similar to NCs. By constructing a mixed cell community, ACs and NCs have synchronous response to fluctuant extracellular stimuli under physiological condition and in a blood vessel–mimic circulation system. We also show that fluctuant bioinformation released by NCs can be received and processed by ACs. The molecular design of DMPS-powered AC is expected to allow a profound understanding of biological systems, advance the construction of intelligent molecular systems, and promote more elegant bioengineering applications.

In order to maintain tissue homeostasis, cells communicate with the outside environment by receiving molecular signals, transmitting them, and responding accordingly with signaling pathways. Thus, one key challenge in engineering molecular signaling systems involves the design and construction of different modules into a rationally integrated system that mimics the cascade of molecular events. Herein, we rationally design a DNA-based artificial molecular signaling system that uses the confined microenvironment of a giant vesicle, derived from a living cell. This system consists of two main components. First, we build an adenosine triphosphate (ATP)-driven DNA nanogatekeeper. Second, we encapsulate a signaling network in the biomimetic vesicle, consisting of distinct modules, able to sequentially initiate a series of downstream reactions playing the roles of reception, transduction and response. Operationally, in the presence of ATP, nanogatekeeper switches from the closed to open state. The open state then triggers the sequential activation of confined downstream signaling modules., Cells communicate with the outside world to maintain homeostasis. Here the authors design a synthetic biology DNA-based signalling system AMSsys that responds to the presence of ATP.

Plasma membranes are the fundamental mediators through which cells communicate with their surrounding environment. The techniques to monitor or synthetically manipulate the cell membranes are attractive tools to engineer the functions of cells as well as their local microenvironment. Current advances of biomolecular science enable the insertion of functional compounds onto cell-surface via external integration or genetic engineering to manipulate cell membrane function. Recently, the DNA nanotechnology made it possible to use synthetic DNA as an emerging and promising molecular toolkit for anchoring and exploring cell-surface. In this review, the latest advances of DNA nanotechnology on cell-surface are summarized. We first give an overview of commonly used strategies for installing DNA nanodevices onto cell-surface including amphiphilic interaction, covalent modification, and affinity labeling. Then the biological applications of DNA nanodevices on cell membranes are reviewed. By integrating functional nucleic acids as recognition elements, DNA sensors are fabricated to monitor the cellular microenvironment and membrane activities. In addition, the programmable behaviors of DNA on cell-surface are also discussed, which include biomimicry and the regulation of membrane functions. Finally, we analyze the current challenges in the development of DNA nanotechnology on cell-surface as well as their prospects in bioimaging and cancer therapy.

As the smallest unit of life, cells attract interest due to their structural complexity and functional reliability. Protocells assembled by inanimate components are created as an artificial entity to mimic the structure and some essential properties of a natural cell, and artificial reaction networks are used to program the functions of protocells. Although the bottom-up construction of a protocell that can be considered truly ‘alive’ is still an ambitious goal, these man-made constructs with a certain degree of ‘liveness’ can offer effective tools to understand fundamental processes of cellular life, and have paved the new way for bionic applications. In this review, we highlight both the milestones and recent progress of protocells programmed by artificial reaction networks, including genetic circuits, enzyme-assisted non-genetic circuits, prebiotic mimicking reaction networks, and DNA dynamic circuits. Challenges and opportunities have also been discussed., In this review, the milestones and recent progress of protocells programmed by various types of artificial reaction networks are highlighted.

A combustion oscillation experiment showed combustion oscillation frequencies of around 350 Hz when only natural gas was used as fuel and approximately 200 and 400 Hz when a hydrogen–natural gas mixture was used. To analyze the resonant frequency, two- and four-region models considering unburned and burned regions of the combustor were developed. The experimental frequencies of the 100% natural gas condition were successfully predicted. Conversely, the experimentally observed frequencies under the hydrogen–natural gas condition were not accurately predicted. A swirler-combustor model was then constructed to get closer to the actual configuration and shape of the experimental setup. However, the model could not reproduce the experimental value under the hydrogen–natural gas condition. A whole piping model was then developed by adding a casing and an air supply pipe to the combustor. The resonant frequencies under both the 100% natural gas and hydrogen–natural gas conditions were successfully calculated. The model reproduced the range and change tendency of the experimentally measured oscillation frequency.

Afterglow luminescence is an internal luminescence pathway that occurs after photo-excitation, holds great promise for non-background molecular imaging in vivo, but suffer from poor quantitative ability owing to luminescent attenuation over time. Moreover, the inert structure and insufficient reactive sites of current afterglow materials make it hard to design activatable afterglow probes for specific detection. Here, we report a ratiometric afterglow luminescent nanoplatform to customize various activatable afterglow probes for reliable quantification and molecular imaging of specific analytes, such as NO, ONOO− or pH. Notably, these afterglow probes can not only address the attenuation of afterglow intensity and eliminate the interference of factors (e.g., laser power, irradiation time, and exposure time), but also significantly improve the imaging reliability in vivo and signal-to-background ratios (~1200-fold), both of which enable more reliable quantitative analysis in biological systems. Moreover, as a proof-of-concept, we successfully design an NO-responsive ratiometric afterglow nanoprobe, RAN1. This nanoprobe can monitor the fluctuations of intratumoral NO, as a biomarker of macrophage polarization, making it possible to real-time dynamically evaluate the degree cancer immunotherapy, which provides a reliable parameter to predict the immunotherapeutic effect.

Summary Using spherically directed reduction of metal ions, a facile and universal method for in situ crosslinking of DNA micelles is described. By incorporating a series of specific template domains into lipid-DNA monomers, copper-, silver-, and gold-crosslinked DNA micelles are formed. By combining characterization results and simulation algorithms, accurate structural profiling of DNA micelles is achieved for the first time. The prepared metal-crosslinked DNA micelles show obvious merits, including one-step formation of core structure and ligand corona, facile size tunability, monodispersity, stability against salt-induced aggregation, high utilization of DNA ligand, mild synthesis conditions, and less time consumption and better internalization. Based on our spherically directed synthesis, metal-crosslinked DNA micelle flares were further prepared for effective intracellular imaging by integrating an aptamer-toehold strategy. In addition, we extended the strategy to cholesterol-based double-stranded DNA micelles, giving strong evidence that our method is not only universal but also flexible.

Two-dimensional (2D) nanomaterials are attracting increasing research interest because of their unique properties and promising applications. Here, we report a facile method to manipulate the assembly of nanoparticles (NPs) to fabricate free-standing 2D quasi-nanosheets. The as-generated 2D products are composed of few-layer NPs; that is, their thicknesses are only tens of nanometers but lateral dimensions could be up to several micrometers. Therefore, the novel structure was denoted as 2D “quasi-nanosheets (QNS)”. Specifically, several types of building blocks could be assembled into 2D unary, binary, ternary, and even quaternary QNS by a universal procedure. The entire assembly process is carried out in solution and mediated simply by tuning the concentration of ligands surrounding the NPs. In contrast to traditional assembly techniques, even without any substrate or template, these QNS showed exceptionally high stability. They can remain intact for several days without any disassembly regardless of the solvent environment (e.g., water, ethanol, methanol, and hexane). In general, our method has effectively tackled several limitations associated with traditional assembly techniques and allows more freedom in manipulating assembly of NPs, which may hold great potential for future fabrication of 2D devices with rich functionalities.

Novel materials from self-assembled nanocrystals hold great promise for applications ranging from inorganic catalysis to bio-imaging. However, because of the inherent anisotropic properties, it is challenging to assemble one-dimensional (1D) nanorods into higher-order structures (e.g. 2D sheets or 3D networks) without any support. Here, we have developed a facile strategy for the direct self-assembly of 1D nanorods into free-standing 2D nanorafts with lateral dimensions up to several micrometers. As a general approach, 2D nanorafts with diverse compositions, e.g. MgF(2), WO(2), CdS, ZnS, and ZnSe nanorafts, have been fabricated from the assembly of their 1D building blocks. More importantly, these nanorafts show high stability even when dispersed in different solvents, making them suitable for various applications. Because of their high porosity and strong adsorption capability, MgF(2) nanorafts were investigated to illustrate the collective advantages generated from the assembly platform. Moreover, flexibility in the composition and structure of the building blocks demonstrated in this work will lead to next generation materials with rich functionalities.

Cell membrane-targeted bioimaging is a prerequisite for studying the roles of membrane-associated biomolecules in various physiological and pathological processes. However, long-term in situ bioimaging on the cell membrane with conventional fluorescent probes leads to diffusion into cells from the membrane surface. Therefore, we herein proposed a de novo strategy to construct an antidiffusion probe by integrating a fluorochrome characterized by strong hydrophobicity and low lipophilicity, with an enzyme substrate to meet this challenge. This precipitating fluorochrome HYPQ was designed by conjugating the traditionally strong hydrophobic solid-state fluorochrome 6-chloro-2-(2-hydroxyphenyl) quinazolin-4(3H)-one (HPQ) with a 2-(2-methyl-4H-chromen-4-ylidene) malononitrile group to obtain closer stacking to lower lipophilicity and elongate emission to the far-red to near-infrared wavelength. As proof-of-concept, the membrane-associated enzyme γ-glutamyltranspeptidase (GGT) was selected as a model enzyme to design the antidiffusion probe HYPQG. Then, benefiting from the precipitating and stable signal properties of HYPQ, in situ imaging of GGT on the membrane was successfully realized. Moreover, after HYPQG was activated by GGT, the fluorescence signal on the cell membrane remained unchanged, with incubation time even extending to 6 h, which is significant for in situ monitoring of enzymatic activity. In vivo testing subsequently showed that the tumor region could be accurately defined by this probe after long-term in situ imaging of tumor-bearing mice. The excellent performance of HYPQ indicates that it may be an ideal alternative for constructing universal antidiffusion fluorescent probes, potentially providing an efficient tool for accurate imaging-guided surgery in the future.

In recent years, live webcast classes have been increasingly used in China as an approach to alleviating educational poverty through equal access to high-quality education. Many schools in impoverished areas have managed to increase their proportions of students entering college by introducing the new model. While celebrating improved learning outcomes of a small percentage of students, educators should also be concerned about the overall academic wellbeing and sustainable development of less successful students. In the present study, academic wellbeing was conceptualized as a multidimensional construct covering seven dimensions, namely Empathy, Support, Responsiveness, Reliability, Tangibility, Self-efficacy and Buoyancy. Data were collected from 136 twelfth-grade students who had studied in live webcast classes. The results show that the overall academic wellbeing in live webcast classes was consistent among students of different academic performance levels, but the specific dimensions of academic wellbeing that they think mostly need improvement varied among different student groups. The findings of this study suggest that learner wellbeing and sustainability can be enhanced by closer collaboration between live webcast instructors and local teachers in instructional materials design, exercise and test questions&rsquo, compilation, as well as students&rsquo, self-study facilitation. The degree to which a local teacher should be involved in classroom teaching depends on the students&rsquo, academic level and learning needs.

The organization of nanoparticles (NPs) with controlled chemical composition and size distribution into well-defined sheets will find many practical applications, but the chemistry remains problematic. Therefore, we report a facile method to assemble NPs to free-floating two-dimensional (2D) nanosheets with a superlattice and thicknesses reaching 22.8 nm. The ligand oleic acid is critical in the formation of nanosheets. As assembled, these free-floating 2D nanosheets remain intact in both polar and nonpolar solvents, e.g., deionized water, ethanol, N,N-dimethylformamide, dimethyl sulfoxide, toluene, hexane, and chloroform, without any disassembly. Compared to Fe(3)O(4) NP building blocks, these 2D nanosheets show more favorable catalytic properties and enhanced catalytic reactivity, which can be exploited to mimic natural enzymes. Our work is expected to open up a new avenue for synthesizing free-floating 2D supersheets by NP assembly, leading to a new generation of materials with enriched functions and broader applications.

A power and area efficient two-step hybrid voltage–time ADC achieves a 4-GS/s conversion speed and 39.9-dB SNDR in 28-nm CMOS. Two pipelined time-based converters (TBCs) with a thermometer capacitive DAC (CDAC) in the ADC lead to a high-speed and low-power operation. The pipelined architecture splits the full ADC resolution, thus relaxing the TBC complexity. The TBC consists of a voltage-domain comparator, a current-source-based voltage-to-time converter (VTC), and a ring oscillator (RO)-based time-to-digital converter (TDC) with feedforward and 2 $\times $ interpolation that achieves high conversion speed and good linearity simultaneously. The prototype ADC is fabricated in a standard 28-nm CMOS process with an active area of only 0.017mm2. The measured SNDR and SFDR are 39.9 and 47.8 dB with a Nyquist input at 4 GS/s. The FoMW and FoMS are 39.3 fJ/conv-step and 152.2 dB, respectively.

This paper presents a reconfigurable BW 2nd-order noise-shaping (NS) hybrid voltage-time ADC based on the two-step ADC structure. Composed by a SAR ADC in the 1st stage and a time-based-converter (TBC) in the 2nd stage, with a reconfigurable passive filter, it realizes a 2nd-order NS while simultaneously maintaining a simple and high-speed operation. Due to the delay introduced by the inter-stage residue amplifier (RA), one NS order is inherently provided by the pipelined architecture. Fabricated in 28 nm CMOS, the prototype chip operates at 1 GS/s while consuming 2.3 mW at 1 V. At an OSR of 4, the SNDR is 63.58 dB leading to a 170.9 dB FoM S . Thanks to the reconfigurable filter, the ADC is able to achieve 163.5 dB and 171.6 dB FoM s at OSR of 2 and 6, respectively.

BackgroundMedical staff fighting the COVID-19 pandemic are experiencing stress from high occupational risk, panic in the community and the extreme workload. Maintaining the psychological health of a medical team is essential for efficient functioning, but psychological intervention models for emergency medical teams are rare.AimsTo design a systematic, full-coverage psychological health support scheme for medical teams serving large-scale emergent situations, and demonstrate its effectiveness in a real-world study in Leishenshan Hospital during the COVID-19 epidemic in Wuhan, China.MethodsThe scheme integrates onsite and online mental health resources and features team-based psychosocial support and evidence-based interventions. It contained five modules, including a daily measurement of mood, a daily mood broadcast that promotes positive affirmation, a daily online peer-group activity with themes based on the challenges reported by the team, Balint groups and an after-work support team. The daily mood measurement provides information to the other modules. The scheme also respects the special psychological characteristics of medical staff by promoting their strengths.ResultsThe scheme economically supported a special medical team of 156 members with only one onsite psychiatrist. Our data reflected that the entire medical team maintained an overall positive outlook (7–9 out of 10 in a Daily Mood Index, DMI) for nearly 6 weeks of continuous working. Since the scheme promoted self-strengths and positive self-affirmation, the number of self-reports of life-related gains were high and played a significant effect on the DMI. Our follow-up investigations also revealed that multiple modules of the scheme received high attention and evaluation levels.ConclusionOur quantitative data from Leishenshan hospital, Wuhan, China, show that the programme is adequate to support the continuous high workload of medical teams. This scheme could be applied to medical teams dealing with emergent situations.

Tau proteins are proteins that stabilize micro-tubules, but their hyperphosphorylation can result in the formation of protein aggregates and, over time, neuro-degeneration. This phenomenon, termed tauopathy, is pathologically involved in several neurodegenerative disorders. DNA aptamers are single-stranded oligonucleotides capable of specific binding to target molecules. Using tau epitopes predisposed for phosphorylation, we identified six distinct aptamers that bind to tau at two phosphorylatable epitopes (Thr-231 and Ser-202) and to full-length Tau441 proteins with nanomolar affinity. In addition, several of these aptamers also inhibit tau phosphorylation (IT4, IT5, IT6) and tau oligomerization (IT3, IT4, IT5, IT6). This is the first report to identify tau epitope-specific aptamers. Such tau aptamers can be used to detect tau in biofluids and uncover the mechanism of tauopathy. They can be further developed into novel therapeutic agents in mitigating tauopathy-associated neurodegenerative disorders.

The organization of nanoparticles (NPs) with controlled chemical composition and size distribution into well-defined sheets will find many practical applications, but the chemistry remains problema...

The specific binding ability of DNA-lipid micelles (DLMs) can be increased by the introduction of an aptamer. However, supramolecular micellar structures based on self-assemblies of amphiphilic DLMs are expected to demonstrate low stability when interacting with cell membranes under certain conditions, which could lead to a reduction in selectivity for targeting cancer cells. We herein report a straightforward cross-linking strategy that relies on a methacrylamide branch to link aptamer and lipid segments. By an efficient photoinduced polymerization process, covalently linked aptamer-lipid units help stabilize the micelle structure and enhance aptamer probe stability, further improving the targeting ability of the resulting nanoassembly. Besides the development of a facile cross-linking method, this study clarifies the relationship between aptamer-lipid concentration and the corresponding binding ability.

A comprehensive nonlinear regression model for dissociation equilibria of cell-specific aptamers is proposed by considering the effect of receptor expression level. Benefiting from the global regression of simultaneous equations, the fitted parameters reach a very significant level, indicating the statistical validity of this updated model. According to the fitting results, we found that dissociation constants fitted using the previous model are obviously larger than the updated values, which can be explained by the effect of receptor number on curve fitting. In addition, equivalent receptor density can be estimated using the updated model, which may lead to some new judgments about reported results of cell-SELEX.

This letter presents a single-channel high-speed hybrid voltage–time two-step analog to digital converter (ADC). Two time-based converters (TBCs) are pipelined by a capacitive DAC (CDAC) and a residue amplifier (RA). The proposed hybrid architecture minimizes the impact of the TBCs nonlinearity while maintaining a low-power consumption for a high sample rate. A unipolar voltage to time converter (VTC) and a ring oscillator (RO)-based time to digital converter (TDC) with feed-forward and $2\times $ interpolation is used as TBC which ensures high-speed and low-power operation. The prototype ADC is fabricated in 28-nm CMOS. At 4-GS/s and a Nyquist input frequency, it achieves 39.9-dB SNDR and 47.8-dB SFDR for a power consumption of 11.7 mW. The FOM W and FOM S are 36.2 fJ/conv-step and 152.2 dB, respectively.

Inspired by this elegant system of cellular adaptivity, we herein report the rational design of a dynamic artificial adaptive system able to sense and respond to environmental stresses in a unique sense-and-respond mode. Utilizing DNA nanotechnology, we constructed an artificial signal feedback network and anchored it to the surface membrane of a model giant membrane vesicle (GMV) protocell. Such a system would need to both senses incoming stimuli and emit a feedback response to eliminate the stimuli. To accomplish this mechanistically, our DNA-based artificial signal system, hereinafter termed DASsys, was equipped with a DNA trigger-induced DNA polymer formation and dissociation machinery. Thus, through a sequential cascade of stimulus-induced DNA strand displacement, DASsys could effectively sense and respond to incoming stimuli. Then, by eliminating the stimulus, the membrane surface would return to its initial state, realizing the formation of a cyclical feedback mechanism. Overall, our strategy opens up a route to the construction of artificial signaling system capable of maintaining homeostasis in the cellular micromilieu, and addresses important emerging challenges in bioinspired engineering.

Emerging 5G communication systems require ADCs to directly digitize wide bandwidth (BW) signals with high spectral purity at low power consumption. Current state-of-the-art solutions include mainly time-interleaved (TI) pipelined [1–4] or pipelined-SAR [5] architectures, enhanced by digital calibration. To ensure a sufficiently high input BW, all these designs employ a static front-end buffer. This buffer often dissipates more power than the ADC itself, significantly deteriorates the linearity and noise performance, and severely limits the available swing, unless over-voltage or multiple supplies are used [1–5].

Biomimetic giant membrane vesicles, with size and lipid compositions comparable to cells, have been recognized as an attractive experimental alternative to living systems. Due to the similarity of their membrane structure to that of body cells, cell-derived giant plasma membrane vesicles have been used as a membrane model for studying lipid/protein behavior of plasma membranes. However, further application of biomimetic giant membrane vesicles has been hampered by the side-effects of chemical vesiculants and the utilization of osmotic buffer. We herein develop a facile strategy to derive giant membrane vesicles (GMVs) from mammalian cells in biofriendly medium with high yields. These GMVs preserve membrane properties and adaptability for surface modification and encapsulation of exogenous molecules, which would facilitate their potential biological applications. Moreover, by loading GMVs with therapeutic drugs, GMVs could be employed for drug transport to tumor cells, which represents another step forward in the biomedical application of giant membrane vesicles. This study highlights biocompatible GMVs with biomimicking membrane surface properties and adaptability as an ideal platform for drug delivery strategies with potential clinical applications.

Automatic anomaly detection in real-world video surveillance is still challenging. In this paper, we propose an autoencoder architecture based on a stacked convolutional LSTM framework that highlights both spatial and temporal aspects in detecting anomalies of surveillance videos. The spatial component(i.e. spatial encoder/decoder) uses Convolutional Neural Network (CNN) and carries information about scenes and objects. The temporal component(i.e. temporal encoder/decoder) uses stacked convolutional LSTM and conveys object movement. Specifically, we integrate CNN and the stacked convolutional LSTM to learn normal patterns from the training data, which contains only normal events. With the integrated approach, our method can better model spatio-temporal information than many others. We train our models in an unsupervised manner, and labels are required only in the testing phase. Our method is evaluated on the datasets of Avenue, UCSD and ShanghaiTech Campus. The results show that the accuracy of our method rivals state-of-the-art methods with a faster detection speed.

Detecting and understanding changes in cell conditions on the molecular level is of great importance for the accurate diagnosis and timely therapy of diseases. Cell-based SELEX (Systematic Evolution of Ligands by EXponential enrichment), a foundational technology used to generate highly-specific, cell-targeting aptamers, has been increasingly employed in studies of molecular medicine, including biomarker discovery and early diagnosis/targeting therapy of cancer. In this review, we begin with a mechanical description of the cell-SELEX process, covering aptamer selection, identification and identification, and aptamer characterization; following this introduction is a comprehensive discussion of the potential for aptamers as targeting moieties in the construction of various nanotheranostics. Challenges and prospects for cell-SELEX and aptamer-based nanotheranostic are also discussed.

A highly efficient nanozyme system, termed hollow multipod Cu(OH)2 superstructure (HMPS), has been developed via direct conversion from irregular nanoparticles. The HMPS displayed a body size around 150 nm and branch lengths in the range of 150–250 nm. Based on the excellent catalytic properties of HMPS, we developed a simple and highly sensitive colorimetric assay to detect urine glucose, and the results are in good agreement with hospital examination reports.

© The Institution of Engineering and Technology 2017. A new power-efficient dynamic residue amplifier for pipelined successive-approximation-register (SAR) ADCs is presented. A complementary input pair and a reference level detection technique are proposed to improve the performance of the dynamic amplifier. At a 400 MS/s sampling rate, the proposed amplifier achieves a gain of 16. The input referred noise is 57.2 μV and the total harmonic distortion is –57.1 dB. The power consumption of the proposed amplifier is 55.6 μW in 28 nm CMOS technology. ispartof: Electronics Letters vol:53 issue:23 pages:1510-1511 status: published