bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advances and current challenges in non‐invasive wearable sensors and wearable biosensors—A mini‐review
Authors: dos Santos Caio Carvalho , Lucena Guilherme N. , Pinto Gabriel C. , Júnior Miguel J. , Marques Rodigo F.C. 
Published: October 2020

AbstractFlexible wearable sensors and wearable biosensors have attracted considerable interest in the scientific community. They have shown relevant potential for continuous monitoring of physiological functions in real‐time and non‐invasively using biofluids. Recent nanotechnology advances in sensor miniaturization and lower costs have driven the development of new flexible sensors. These new materials make sensors and biosensors promising and will cause a substantial impact on society by providing an improvement in the quality of life, as well as in a faster diagnosis and early treatment. However, considerable challenges still need to be overcome for these sensors to reach their totality, as such as improving available power supplies, low power data transmission mode, problems with device deformation and contaminated, continuous wear, understanding the correlations between analytes in biofluids and blood to validate results, and issues of security and privacy. Overcoming these challenges will allow, through the diffusion of this technology, to modify how the disease can be monitored in the future. Due to this, systematic studies should be conducted to elucidate and enhance the understanding of the current challenges for the development and implementation of wearable sensors (WS) and wearable biosensors (WBS). In this mini‐review, we discuss the state of the art of these devices, critically addressing the advances by debating the current gaps and the challenges that need to overcome this science area.
Tiny‐RainNet: a deep convolutional neural network with bi‐directional long short‐term memory model for short‐term rainfall prediction
Authors: Zhang Chang‐Jiang , Wang Hui‐Yuan , Zeng Jing , Ma Lei‐Ming , Guan Li 
Published: October 2020

AbstractRainfall is not only related to current and previous meteorological conditions but also to meteorological conditions of the current location and surrounding regions. Existing short‐term rainfall prediction methods mainly focus on radar echo extrapolation to predict the future radar echo maps, and then retrieve rainfall based on the predicted radar echo maps. These methods obtain rainfall through two separate steps usually leading to large accumulated errors. However, Tiny‐RainNet is proposed by combining convolutional neural networks (CNNs) with bi‐directional long short‐term memory (BiLSTM) to directly predict future rainfall based on sequential radar echo maps. The structure of Tiny‐RainNet is simpler than existing rainfall prediction models combining CNNs with LSTM. In order to further reduce computational complexity of the Tiny‐RainNet and obtain good rainfall prediction results, 10 × 10, not the original 101 × 101, sequential radar maps are used as inputs of the Tiny‐RainNet after making many tests considering temporal–spatial meteorological conditions. The proposed model takes into account the influence of temporal–spatial meteorological conditions on rainfall prediction. This avoids the accumulated error caused by multi‐step prediction methods. The overall performance of the Tiny‐RainNet model performs better than fully connected LSTM, LSTM and convolutional LSTM.
Design of high‐efficiency continuous resistive‐reactive class‐J power amplifier
Authors: Liu Guohua , Zhao Zhong , Cheng Zhiqun , Li Sudong 
Published: October 2020

AbstractThis paper presents an ultra‐wideband, high‐efficiency continuous resistive‐reactive class‐J power amplifier. The design space is extended by controlling the second harmonic with impedance component and multiple harmonics of a continuous class‐J PA, enabling it to achieve efficient output in multiple octave bandwidths. Based on this theory, a GaN HEMT transistor CGH40010F is used to achieve a 0.6 to 3.2 GHz, average efficiency of 65%, ultra‐wideband PA with output power greater than 40 dBm. The simulation results are consistence with the measurement results and respond to the expectations.
Chemical shift encoding using asymmetric readout waveforms
Authors: Rydén Henric , Norbeck Ola , Avventi Enrico , Skorpil Mikael , van Niekerk Adam , Skare Stefan , Berglund Johan 
Published: October 2020

PurposeTo describe a new method for encoding chemical shift using asymmetric readout waveforms that enables more SNR‐efficient fat/water imaging.MethodsChemical shift was encoded using asymmetric readout waveforms, rather than conventional shifted trapezoid readouts. Two asymmetric waveforms are described: a triangle and a spline. The concept was applied to a fat/water separated RARE sequence to increase sampling efficiency. The benefits were investigated through comparisons to shifted trapezoid readouts. Using asymmetric readout waveforms, the scan time was either shortened or maintained to increase SNR. A matched in‐phase waveform is also described that aims to improve the SNR transfer function of the fat and water estimates. The sequence was demonstrated for cervical spine, musculoskeletal (MSK), and optic nerve applications at 3T and compared with conventional shifted readouts.ResultsBy removing sequence dead times, scan times were shortened by 30% with maintained SNR. The shorter echo spacing also reduced
blurring. Maintaining the scan times and using asymmetric readout waveforms achieved an SNR improvement in agreement with the prolonged sampling duration.ConclusionsAsymmetric readout waveforms offer an additional degree of freedom in pulse sequence designs where chemical shift encoding is desired. This can be used to significantly shorten scan times or to increase SNR with maintained scan time.
On solution of a class of nonlinear variable order fractional reaction–diffusion equation with Mittag–Leffler kernel
Authors: Pandey Prashant , Gómez‐Aguilar José Francisco 
Published: October 2020

AbstractIn this article, an efficient variable‐order Chebyshev collocation method which is based on shifted fifth‐kind Chebyshev polynomials is applied to solve a nonlinear variable‐order fractional reaction–diffusion equation with Mittag–Leffler kernel. The operational matrix of shifted fifth‐kind Chebyshev polynomials is derived for variable‐order ABC derivatives. The Chebyshev operational matrix together with the collocation method are applied to concerned nonlinear physical model with Mittag–Leffler kernel which is converted into a system of nonlinear algebraic equations, this system can be solved by using Newton method. The main focus of this paper is finding the convergence analysis of the approximation and high convergence order for small grid approximation. Few test examples with a comparison of maximum absolute error between the obtained numerical solution and existing known solution are being reported to show the accuracy and stability of the scheme. The physical presentation of the absolute errors for considered nonlinear variable‐order reaction–diffusion equations involving the Mittag–Leffler kernel with their exact solutions shows that the method is good for finding the solution of these kind of problems.
A stabilizer free weak Galerkin finite element method with supercloseness of order two
Authors: Al‐Taweel Ahmed , Wang Xiaoshen , Ye Xiu , Zhang Shangyou 
Published: October 2020

AbstractThe weak Galerkin (WG) finite element method is an effective and flexible general numerical technique for solving partial differential equations. A simple WG finite element method is introduced for second‐order elliptic problems. First we have proved that stabilizers are no longer needed for this WG element. Then we have proved the supercloseness of order two for the WG finite element solution. The numerical results confirm the theory.
Assessment of nutritional status in children with cancer: Significance of arm anthropometry and serum visceral proteins
Authors: Yaprak Deniz Sül , Yalçın Bilgehan , Pınar Aslı Akhun , Büyükpamukçu Münevver 
Published: October 2020

AbstractBackgroundArm anthropometry is a better indicator of nutritional status in children with cancer. The value of serum albumin and prealbumin in nutritional assesment is debatable. We investigated the nutritional status of children with cancer and their serum albumin and prealbumin levels.Patients and MethodsAt diagnosis and following induction therapies, weight, height, body mass index (BMI), mid‐upper arm circumference (MUAC), and triceps skin‐fold thickness (TSFT) were measured; serum albumin and prealbumin levels were determined. Prevalences of malnutrition defined by anthropometric indices were calculated. Correlations of anthropometric indices with each other, with serum albumin/prealbumin levels, and clinicopathological parameters were analyzed.ResultsIn 81 patients, median age was 7.5 years (males/females = 50/31), tumors were located mostly in the abdomen, and abdominal tumors were more common under 5 years. Prevalence of malnutrition according to weight for age, BMI, MUAC, TSFT z scores were 14.8%, 23.5%, 27.2%, 21%, respectively. Defined by combined BMI/MUAC/TSFT measurements, 33/81 cases (40.7%) had malnutrition (z scores < −1, 23 mild; z scores < −2, 10 moderate). Malnutrition was more prevalent under 5 years (P = .03), also in abdominal tumors (P = .03) and advanced disease (P < .001). Younger age and advanced disease were risk factors for malnutrition. At diagnosis, prevalences of low serum albumin and prealbumin levels were 7.4% and 54%, respectively. Cases with malnutrition had significantly lower survival rates.ConclusionsNutritional status is assessed best by MUAC and TSFT measurements. Serum prealbumin levels can be used to identify patients at risk of undernutrition. Presence of malnutrition is a significant poor prognostic factor. All children with cancer should undergo nutritional evaluation and active nutritional support.
Personality and emerging adults' friend selection on social networking sites: A social network analysis perspective
Authors: Zhou Yixin , Zhang Zheng , Wang Kexin , Chen Shuang , Zhou Mingjie , Zhang Jianxin 
Published: October 2020

AbstractPersonality affects how emerging adults select friends and how they are selected on social networking sites (SNSs). Big Five personality traits and frequency of contacts on SNSs were collected from 160 college freshmen (M = 18 years) under a round‐robin design over 2 months. Using social network analyses, we examined how personality and dyadic similarity affect online friend selections among new acquaintances. Our results show that people with high extraversion, neuroticism, and agreeableness and low openness selected more friends, verifying both the social enhancement hypothesis and the social compensation hypothesis. People with low extraversion, conscientiousness, and neuroticism and high openness were selected as online friends more often. Only openness dissimilarity had a salutary effect. We discuss the role of personality in social networking friend selection.
Bioactivity improvement via display of the hydrophobic core of HYD1 in a cyclic β‐hairpin‐like scaffold, MTI‐101
Authors: Jain Priyesh , Badger David B. , Liang Yi , Gebhard Anthony W. , Santiago Daniel , Murray Philip , Kaulagari Sridhar R. , Gauthier Ted J. , Nair Rajesh , Kumar MohanRaja , Guida Wayne C. , Hazlehurst Lori A. , McLaughlin Mark L. 
Published: October 2020

AbstractHYD1 is an all D‐amino acid linear 10‐mer peptide that was discovered by one‐bead‐one‐compound screening. HYD1 has five hydrophobic amino acids flanked by polar amino acids. Alanine scanning studies showed that alternating hydrophobic amino acid residues and N‐ and C‐terminal lysine side chains were contributors to the biological activity of the linear 10‐mer analogs. This observation led us to hypothesize that display of the hydrophobic pentapeptide sequence of HYD1 in a cyclic beta‐hairpin‐like scaffold could lead to better bioavailability and biological activity. An amphipathic pentapeptide sequence was used to form an antiparallel strand and those strands were linked via dipeptide‐like sequences selected to promote β‐turns. Early cyclic analogs were more active but otherwise mimicked the biological activity of the linear HYD1 peptide. The cyclic peptidomimetics were synthesized using standard Fmoc solid phase synthesis to form linear peptides, followed by solution phase or on‐resin cyclization. SAR studies were carried out with an aim to increase the potency of these drug candidates for the killing of multiple myeloma cells in vitro. The solution structures of 1, 5, and 10 were elucidated using NMR spectroscopy. 1H NMR and 2D TOCSY studies of these peptides revealed a downfield Hα proton chemical shift and 2D NOE spectral analysis consistent with a β‐hairpin‐like structure.
A user‐friendly, Python‐based quantum mechanics/Gromacs interface: gmx2qmmm
Authors: Götze Jan P. , Pi Yuan‐Wei , Petry Simon , Langkabel Fabian , Witte Jan Felix , Lemke Oliver 
Published: October 2020

AbstractWe introduce a Python 2.7 software called gmx2qmmm, which provides an interface between the Gaussian and Gromacs software packages in an additive quantum mechanics/molecular mechanics (QM/MM) scheme. Other QM packages will be added in future releases. The main advantage of gmx2qmmm is its simplicity in terms of input setup and configuration as it maintains the Gromacs file formats, as well as input conventions. It is also designed such that users do not need to reconfigure or recompile any of the interfaced programs. While our main goal was to provide a simplified transition from Gromacs to QM/MM using Gromacs directly as the basis for the MM part, we considered alternative ways to treat the QM/MM boundary. Our software was also developed to test a previously considered way to account for the presence of link atoms, which we term here link atom correction functions (LCFs). We show that LCFs can be good candidates to improve the forces at the QM/MM junction; however, from our data, it is also apparent that LCFs will not necessarily improve energy barriers, likely due to them being tailored to improve the situation close to potential minima. LCFs are, however, trivial to set up and can be used in the future to support the accuracy of QM/MM optimizations and dynamics. We present data on how our interface compares to a full QM description of small polypeptides; furthermore, we investigate the UV/vis spectroscopy of chlorophyll‐containing proteins depending on the employed potentials and geometries.
Binding properties of cucurbit[7]uril to neutral and protonated amino acids: A theoretical study
Authors: Ma Fenfen , Zheng Xiaoyan , Xie Jing , Li Zesheng 
Published: October 2020

AbstractWe systematically investigate the binding nature of cucurbit[7] (CB[7]) toward 20 amino acids in both neutral (AAs) and protonated (AAs+) states using quantum chemistry methods. The result indicates that, among AAs, Arg and Asn show the largest binding strength to CB[7], and for AAs+, Gln+ and Asn+ bind to CB[7] the strongest. The binding strength of protonated CB[7]/AA+ is much stronger than that of neutral CB[7]/AA counterpart due to the introduction of ion‐dipole interaction and the increase in number and strength of hydrogen bonds. Energy decomposition analysis indicates that electrostatic interactions play major roles in both CB[7]/AAs and CB[7]/AAs+ complexes. Moreover, we analyzed the dependence of binding strength on single AA volume and dipole moment. This study is beneficial for providing valuable information in predicting the recognition sites for a sequence‐based peptide or protein by CB[7] and rationally designing a synthetic host molecule for specific peptide or protein recognition.
Robust stability analysis for linear systems with distributed delays: A time‐domain approach
Authors: Juárez Luis , Alexandrova Irina V. , Mondié Sabine 
Published: October 2020

SummaryThis work is devoted to the robust stability analysis of linear systems with distributed delays. The approach is based on recent results in the Lyapunov‐Krasovskii framework, where a Lyapunov‐Krasovskii functional with prescribed negative definite derivative is applied. The stability conditions obtained in this work, are simple inequalities which depend on the so‐called delay Lyapunov matrix. The cases of matrix parameters and delays uncertainties are addressed, accurately detecting exact stability bounds when applied in an iterative manner. Our method is used successfully to tackle the challenging problem of robust predictor‐based stabilization of systems with state and input delays.
Nontracking type iterative learning control based on economic model predictive control
Authors: Long Yushen , Xie Lihua , Liu Shuai 
Published: October 2020

SummaryMost existing iterative learning control algorithms are designed to improve tracking performance with respect to a given trajectory over a fixed time period. In this article, we design two iterative learning‐based economic model predictive controllers for repetitive tasks where no target trajectory is available. The controller is able to search for suboptimal trajectories with good performance by exploiting information from previous experience. Compared with existing works, the objective function is not assumed to be positive definite so it is not limited to the tracking problem but can represent more general economic performance index. The controller can learn from the previous closed‐loop trajectory, resulting in a performance which is guaranteed to be no worse than the previous one. Under some standard assumptions in model predictive control, the recursive feasibility of the algorithms is ensured. We show that the fixed operation time algorithm can guarantee that the performance is no worse than the previous iteration even without the dissipative assumption. By allowing the operation time to vary, the flexible operation time algorithm can balance the operation time and the system performance if dissipative assumption is satisfied. For both algorithms, each iteration is guaranteed to be completed within a uniformly bounded time duration.
Preparation of a Sulfonic‐Acid‐Type Ordered Mesoporous Carbon Solid Acid via Hydrothermal Synthesis for the Transesterification of Waste Frying Oil
Authors: Ma Xiuhua , Huang Zhihang , Yuan Hong , Ke Yihu 
Published: October 2020

AbstractHydrothermal carbonisation was used to synthesise hydrothermally ordered mesoporous carbon (HOMC), employing sucrose as the carbon source, a P123 block copolymer as the surfactant and tetraethyl orthosilicate as the silicon source. A high‐density sulfonic‐acid‐based solid acid catalyst (HOMC‐SO3H) was subsequently prepared via low‐temperature sulfonation of the HOMC with concentrated sulfuric acid. Transmission electron microscopy and small‐angle X‐ray diffraction analyses showed that both the HOMC and HOMC‐SO3H exhibited an ordered mesoporous structure. The N2 Brunauer‐Emmett‐Teller surface areas of the HOMC and HOMC‐SO3H were determined to be 112 and 87 m2/g, respectively, and the average pore sizes were 11.0 and 15.1 nm, respectively. X‐ray photoelectron spectroscopy data confirmed that −SO3H groups were successfully introduced onto the HOMC surface by the sulfonation process, and a surface acid concentration of 5.9 mmol/g HOMC‐SO3H was determined by acid‐base titration. The HOMC‐SO3H was applied to the transesterification of waste frying oil with methanol and a fatty acid methyl ester yield of 95 % was obtained after a 5 h reaction at 180 °C.
Pyrolysis of Deep Eutectic Solvents for the Preparation of Supported Copper Electrocatalysts
Authors: Iwanow Melanie , Vieira Luciana , Rud Igor , Seidler Johannes , Kaiser Manuela , Van Opdenbosch Daniel , Zollfrank Cordt , Richter Michael , Gärtner Tobias , König Burkhard , Sieber Volker 
Published: October 2020

AbstractElectrochemical CO2 reduction on Cu‐based catalysts can form a variety of products including hydrocarbons, alcohols and formate, besides carbon monoxide and hydrogen. Compared to other electroactive metals, copper has a rather low cost and low toxicity.We have developed a novel method for catalyst preparation using deep eutectic solvents (DES), where the pyrolysis of a metal‐containing DES leads to a material consisting of a metal embedded in a carbon support rich in oxygen and nitrogen functional groups (CNO). We focus on the preparation of copper‐based materials as catalysts for the electrochemical CO2 reduction. Depending on the nature of DES, the properties of the carbon support can be changed. The electrochemical activity of the materials was correlated with the preparation parameters such as variation of DESs, copper precursor and/or pyrolysis temperature. These Cu/CNO copper catalysts showed formate formation rates up to 85.5 μmol h−1 cm−2 at 1.5 V vs. Ag/AgCl.
High‐Capacity, Dendrite‐Free, and Ultrahigh‐Rate Lithium‐Metal Anodes Based on Monodisperse N‐Doped Hollow Carbon Nanospheres
Authors: Liu Yuping , Zhen Yanzhong , Li Taoran , Bettels Frederik , He Tao , Peng Manhua , Liang Yucang , Ding Fei , Zhang Lin 
Published: October 2020

AbstractTo unlock the great potential of lithium metal anodes for high‐performance batteries, a number of critical challenges must be addressed. The uncontrolled dendrite growth and volume changes during cycling (especially, at high rates) will lead to short lifespan, low Coulombic efficiency (CE), and security risks of the batteries. Here it is reported that Li metal anodes, employing the monodisperse, lithiophilic, robust, and large‐cavity N‐doped hollow carbon nanospheres (NHCNSs) as the host, show remarkable performances—high areal capacity (10 mAh cm−2), high CE (up to 99.25% over 500 cycles), complete suppression of dendrite growth, dense packing of Li anode, and an extremely smooth electrode surface during repeated Li plating/stripping. In symmetric cells, a highly stable voltage hysteresis over a long cycling life >1200 h is achieved, and a low and stable voltage hysteresis can be realized even at an ultrahigh current density of 64 mA cm−2. Furthermore, the NHCNSs‐based anodes, when paired with a LiFePO4 (LFP) cathode in full cells, give rise to highly improved rate capability (104 mAh g−1 at 10 C) and cycling stability (91.4% capacity retention for 200 cycles), enabling a promising candidate for the next‐generation high energy/power density batteries.
Vertical 0D‐Perovskite/2D‐MoS2 van der Waals Heterojunction Phototransistor for Emulating Photoelectric‐Synergistically Classical Pavlovian Conditioning and Neural Coding Dynamics
Authors: Cheng Yongchao , Li Huangjinwei , Liu Biao , Jiang Leyong , Liu Min , Huang Han , Yang Junliang , He Jun , Jiang Jie 
Published: October 2020

AbstractOptoelectronic‐neuromorphic transistors are vital for next‐generation nanoscale brain‐like computational systems. However, the hardware implementation of optoelectronic‐neuromorphic devices, which are based on conventional transistor architecture, faces serious challenges with respect to the synchronous processing of photoelectric information. This is because mono‐semiconductor material cannot absorb adequate light to ensure efficient light–matter interactions. In this work, a novel neuromorphic‐photoelectric device of vertical van der Waals heterojunction phototransistors based on a colloidal 0D‐CsPbBr3‐quantum‐dots/2D‐MoS2 heterojunction channel is proposed using a polymer ion gel electrolyte as the gate dielectric. A highly efficient photocarrier transport interface is established by introducing colloidal perovskite quantum dots with excellent light absorption capabilities on the 2D‐layered MoS2 semiconductor with strong carrier transport abilities. The device exhibits not only high photoresponsivity but also fundamental synaptic characteristics, such as excitatory postsynaptic current, paired‐pulse facilitation, dynamic temporal filter, and light‐tunable synaptic plasticity. More importantly, efficiency‐adjustable photoelectronic Pavlovian conditioning and photoelectronic hybrid neuronal coding behaviors can be successfully implemented using the optical and electrical synergy approach. The results suggest that the proposed device has potential for applications associated with next‐generation brain‐like photoelectronic human–computer interactions and cognitive systems.