bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fall predictors beyond fall risk assessment tool items for acute hospitalized older adults: a matched case–control study
Authors: Noh Hye-Mi , Song Hong Ji , Park Yong Soon , Han Junhee , Roh Yong Kyun 
Published: January 2021

AbstractWe investigated whether clinical factors including comorbidities, medications, and laboratory results predict inpatient fall risk in older adults. The participants in this case–control study included hospitalized older adults with acute conditions who had falls during their hospital stay (case group) and 410 hospitalized older adults who did not experience falls (control group). Data on medical history, fall risk assessment (Morse Fall Scale; MFS), medications, and laboratory results were obtained. Conditional logistic regression analysis was performed to estimate the association between clinical factors and falls. Receiver operating characteristic curves and area under the curve (AUC) were used to determine whether clinical factors could discriminate between fallers and controls. We evaluated three models: (M1) MFS, (M2) M1 plus age, sex, ward, and polypharmacy, and (M3) M2 plus clinical factors. Patients with diabetes mellitus or MFS scores ≥ 45 had the highest risk of falls. Calcium channel blockers, diuretics, anticonvulsants, and benzodiazepines were associated with high fall risk. The AUC of the three models was 0.615, 0.646, and 0.725, respectively (M1 vs. M2, P = 0.042 and M2 vs. M3, P < .001). Examining clinical factors led to significant improvements in fall prediction beyond that of the MFS in hospitalized older adults.
Summer weather conditions influence winter survival of honey bees (Apis mellifera) in the northeastern United States
Authors: Calovi Martina , Grozinger Christina M. , Miller Douglas A. , Goslee Sarah C. 
Published: January 2021

AbstractHoney bees are crucial pollinators for agricultural and natural ecosystems, but are experiencing heavy mortality in North America and Europe due to a complex suite of factors. Understanding the relative importance of each factor would enable beekeepers to make more informed decisions and improve assessment of local and regional habitat suitability. We used 3 years of Pennsylvania beekeepers’ survey data to assess the importance of weather, topography, land use, and management factors on overwintering mortality at both apiary and colony levels, and to predict survival given current weather conditions and projected climate changes. Random Forest, a tree-based machine learning approach suited to describing complex nonlinear relationships among factors, was used. A Random Forest model predicted overwintering survival with 73.3% accuracy for colonies and 65.7% for apiaries where Varroa mite populations were managed. Growing degree days and precipitation of the warmest quarter of the preceding year were the most important predictors at both levels. A weather-only model was used to predict colony survival probability, and to create a composite map of survival for 1981–2019. Although 3 years data were likely not enough to adequately capture the range of possible climatic conditions, the model performed well within its constraints.
Histamine H1 receptor antagonists selectively kill cisplatin-resistant human cancer cells
Authors: Matsumoto Nobuki , Ebihara Miku , Oishi Shiori , Fujimoto Yuku , Okada Tomoko , Imamura Toru 
Published: January 2021

AbstractCancer therapy is often hampered by the disease’s development of resistance to anticancer drugs. We previously showed that the autonomously upregulated product of fibroblast growth factor 13 gene (FGF13; also known as FGF homologous factor 2 (FHF2)) is responsible for the cisplatin resistance of HeLa cisR cells and that it is likely responsible for the poor prognosis of cervical cancer patients treated with cisplatin. Here we show that cloperastine and two other histamine H1 receptor antagonists selectively kill HeLa cisR cells at concentrations that little affect parental HeLa S cells. The sensitivity of HeLa cisR cells to cloperastine was abolished by knocking down FGF13 expression. Cisplatin-resistant A549 cisR cells were similarly susceptible to cloperastine. H2, H3, and H4 receptor antagonists showed less or no cytotoxicity toward HeLa cisR or A549 cisR cells. These results indicate that histamine H1 receptor antagonists selectively kill cisplatin-resistant human cancer cells and suggest that this effect is exerted through a molecular mechanism involving autocrine histamine activity and high-level expression of FGF13. We think this represents a potential opportunity to utilize H1 receptor antagonists in combination with anticancer agents to treat cancers in which emergent drug-resistance is preventing effective treatment.
Thermal transformation of polar into less-polar ginsenosides through demalonylation and deglycosylation in extracts from ginseng pulp
Authors: Yao Fan , Li Xiang , Sun Jing , Cao Xinxin , Liu Mengmeng , Li Yuanhang , Liu Yujun 
Published: January 2021

AbstractThe present study was conducted to qualitatively and quantitatively elucidate dynamic changes of ginsenosides in ginseng pulp steamed under different temperatures (100 or 120 °C) for different durations (1–6 h) through UPLC-QTOF-MS/MS and HPLC with the aid of as numerous as 18 authentic standards of ginsenosides. Results show that levels of eight polar ginsenosides (i.e., Rg1, Re, Rb1, Rc, Rb2, Rb3, F1, and Rd) declined but those of 10 less-polar ginsenosides [i.e., Rf, Rg2, 20(S)-Rh1, 20(R)-Rg2, F4, 20(S)-Rg3, 20(R)-Rg3, PPT, Rg5, and 20(R)-Rh2] elevated with increases of both steaming temperature and duration; the optimum steaming conditions for achieving the highest total ginsenosides were 100 °C for 1 h. Particular, 20(R)-Rg3, a representative less-polar ginsenoside with high bioactivity such as potent anti-cancer effect, increased sharply but Re, the most abundant polar ginsenoside in fresh ginseng pulp, decreased dramatically. More importantly, ginsenoside species enhanced from 18 to 42 after steaming, mainly due to transformation of polar into less-polar ginsenosides. Furthermore, four malonyl-ginsenosides were detected in fresh ginseng pulps and ten acetyl-ginsenosides were formed during steaming, demonstrating that demalonylation and acetylation of ginsenosides were the dominant underling mechanisms for transformation of polar into less-polar ginsenosides.
CROP: a CRISPR/Cas9 guide selection program based on mapping guide variants
Authors: Aprilyanto Victor , Aditama Redi , Tanjung Zulfikar Achmad , Utomo Condro , Liwang Tony 
Published: January 2021

AbstractThe off-target effect, in which DNA cleavage was conducted outside the targeted region, is a major problem which limits the applications of CRISPR/Cas9 genome editing system. CRISPR Off-target Predictor (CROP) is standalone program developed to address this problem by predicting off-target propensity of guide RNAs and thereby allowing the user to select the optimum guides. The approach used by CROP involves generating substitution, deletion and insertion combinations which are then mapped into the reference genome. Based on these mapped variants, scoring and alignment are conducted and then reported as a table comprising the off-target propensity of all guide RNAs from a given gene sequence. The Python script for this program is freely available from: https://github.com/vaprilyanto/crop.
Auto‐calibration Kalman filters for non‐linear systems with direct feedthrough
Authors: Cui Yi , Wang Zhihua 
Published: January 2021

AbstractThe problem of state estimation for non‐linear systems with unknown inputs is discussed. The objective is to construct a non‐linear filter where the unknown input affects both the state equation and measurement equation. An auto‐calibration Kalman filter is proposed with three stages, where the first and second stages are the extension of the two‐stage Kalman filter in non‐linear system cases, and the third stage is the extended Kalman filter with correlated noise. Compared with the two‐stage extended Kalman filter, the presented algorithm conducts a more reasonable linearization of the measurement equation in the third stage. As a result, auto‐calibration is realized and more accurate and more stable state estimation can be obtained. Simulative and practical examples both demonstrate the validity and superiority of the presented auto‐calibration Kalman filter. Furthermore, positioning experiments illustrate that the auto‐calibration Kalman filter can obtain an accurate long‐term heading estimation in pedestrian navigation and is easy to apply in engineering applications.
Stability and stabilisation for switched impulsive positive systems
Authors: Du Shengli , Dong Jiangtao , Wang Yuee 
Published: January 2021

AbstractThe current study is dedicated to addressing the stability and weighted ‐gain performance analysis of switched impulsive positive systems (SIPSs). Firstly, by designing a novel multiple piecewise‐continuous copositive linear Lyapunov function and using the mode‐dependent average dwell time (MDADT) switching method, improved stability conditions that are able to achieve a tighter dwell time bound are developed. It is shown that the system under study is stable and possesses an attenuation property under the designed switching signals. Secondly, with the above stability conditions, a more effective controller design strategy has been proposed. The solved controllers are both quasi‐time dependent and mode‐dependent. Moreover, the constraint on the rank of the controller and the computation burden caused by iteration algorithm used in literature are relaxed. Finally, the feasibility and superiority of the proposed strategies are verified by some simulations.
L4Net: An anchor‐free generic object detector with attention mechanism for autonomous driving
Authors: Wu Yanan , Feng Songhe , Huang Xiankai , Wu Zizhang 
Published: January 2021

AbstractGeneric object detection is a crucial task for autonomous driving. To devise a safe and efficient object detector, the following aspects are required to be considered: high accuracy, real‐time inference speed and small model size. Herein, a simple yet effective anchor‐free object detector named L4Net is proposed, which incorporates a keypoint detection backbone and a co‐attention scheme into a unified framework, and achieves lower computation cost with higher detection accuracy than prior art across a wide spectrum of resource constrains. Specifically, the backbone utilizes Multi‐scale Receptive‐fields Enhancement module (MRE) to capture context‐wise information, where the features of object scale and shape invariance are simultaneously considered. The co‐attention scheme integrates the strength of both Class‐agnostic Attention (CA) and Semantic Attention (SA), and explores the valuable features from low‐level to high‐level to generate more accurate prediction boxes. Compared with previous feature fusion strategy, multi‐scale features are selectively integrated by fully exploiting the different characteristics of low‐level and high‐level features, which leads to a small model size and faster inference speed. Extensive experiments on four well‐known datasets demonstrate the effectiveness of our method. For instance, L4Net achieves 71.68% mAP on KITTI test set, with 13.7 M model size at the speed of 149 FPS on NVIDIA TX and 30.7 FPS on Qualcomm‐based device, respectively, which is 4x smaller and 2x faster than baseline model.
A non‐uniform NSAF‐SF adaptive algorithm
Authors: Xavier P. P. S. , Petraglia M. R. , Haddad D. B. 
Published: January 2021

AbstractSpeech enhancement and acoustic noise reduction are two important tasks where adaptive filtering algorithms emerge as a competitive solution. Unfortunately, in such applications the convergence rate of the system identification is hampered when the excitation data is highly correlated. Subband adaptive algorithms have been developed to address such issue. A recently proposed low‐complexity subband adaptive structure with sparse subfilters is generalised, in order to permit a non‐uniform filter bank structure. This generalisation brings additional flexibility to the resulting critically decimated adaptive structure, which allows one to adapt it to the idiosyncrasies of the application of interest without losing the perfect‐reconstruction property. A closed‐form solution for the optimal values that the adaptive coefficient should assume in order to accurately emulate a given impulse response is derived. Simulations reveal that the resulting algorithm may outperform recently published subband adaptive filtering algorithms, thereby requiring even less computational effort.
A high‐linearity high‐gain up‐conversion mixer for 24 GHz automotive radar applications
Authors: Siddique A. , Delwar T. S. , Ryu J. Y. 
Published: January 2021

AbstractThis paper presents a high conversion gain and highly linearised up‐conversion mixer designed in 65 nm CMOS process, which translates intermediate frequency of 2.4 GHz and local oscillator frequency of 21.6–24 GHz in radio frequency. In the proposed mixer, the tranconductance stage consists of a common source route with neutralisation technique and dual capacitive cross coupled‐common gate route to achieve high linearity and stability. In addition, it also includes dual negative resistance switches with improved inter‐stage matching network to enhance the conversion gain and to decrease the noise figure. The mixer achieves the conversion gain of 4.7 dB, the measured output 1‐dB compression point of 0.41 dBm and noise figure of 3.8 dB at 24 GHz. In an automotive radar application, the proposed mixer showed a high conversion gain, an excellent output 1‐dB and a low noise figure with power consumption of approximately 5.2 mW at a 1.2 V supply.
Maximising robustness and diversity for improving the deep neural network safety
Authors: Esmaeili Bardia , Akhavanpour Alireza , Sabokrou Mohammad 
Published: January 2021

AbstractThis article proposes a novel yet efficient defence method against adversarial attack(er)s aimed to improve the safety of deep neural networks. Removing the adversarial noise by refining adversarial samples as a defence strategy is widely investigated in previous works. Such methods are simply broken if an attacker has access to both main and refiner networks. To cope with this weakness, the authors propose to refine the input samples relying on a set of encoder–decoders, which are trained in such a way to reconstruct the samples on completely different feature spaces. To this end, the authors learn several encoder–decoder networks and force their latent spaces to have a maximum diversion. In this way, if attacker gets access to one of the refiner networks, other ones can play as a defence network. The evaluation of the proposed method confirms its performance against adversarial samples.
Design and analysis of a novel topology for slotless brushless DC (BLDC) motors with enhanced torque and efficiency
Authors: Mousavi‐aghdam Seyed Reza 
Published: January 2021

AbstractA novel high‐torque slotless brushless DC (BLDC) motor is proposed. The proposed topology has a unique concentrated winding structure and accordingly the motor design is effectively modified with its dual‐rotor structure. The rotor structure of the proposed motor may be modified itself and form three different topologies. First, the basic structures of the new slotless BLDC motor and its operation principle are described. Then, design methodology of the proposed motor is explained. Initial analysis of the motor is subsequently conducted using 2D finite element (FE) simulations. Next, design parameters of the proposed motor are further optimized using Salp algorithm. The proposed topologies are compared with the conventional single and dual‐rotor structures. Finally, experimental prototype is built for verification. The simulation and experimental results exhibit that the proposed slotless BLDC motor has high torque and efficiency in comparison with the conventional structures and may be a good candidate for small‐sized BLDC motors. Moreover, the results show that the proposed BLDC motor has nearly ideal back‐EMF which makes sensorless methods more efficient for the proposed motor.
Improvement of the slotless tubular permanent magnet linear motor with lighter mover mass for punching applications
Authors: Luo Ciyong , Long Xing , Zhu Ziang 
Published: January 2021

AbstractThe slotless tubular permanent magnet linear motor (STPMLM) offers obvious advantages when it is applied to the punching system, such as space saving and controllable impact strength. Herein, the mechanical and electromagnetic coupled differential equations were established to present a comprehensive analysis of the relationship between mover mass and motor performance in the punching system. The travel time of the punching movement was expressed analytically under the condition of the mover obtaining the same impact kinetic energy, and the relationship between the mover mass and the resistive energy consumption in one punching process was also deduced under the same condition. Then the analytical results were validated by a numerical model. The studies show that a lighter mover mass can contribute to less resistive energy consumption and faster dynamic response in the punching applications. Based on that, a STPMLM with special‐shaped yoke was designed for lighter mover mass. Moreover, prototype experiments including static thrust characteristic and dynamic performance were conducted. The experimental results proved that the proposed permanent magnet linear motor with special‐shaped yoke can improve the dynamic performance and reduce resistive energy consumption while ensuring that the electromagnetic performance is not affected.
Online non‐invasive evaluation of arcing time for condition assessment of high‐voltage gas circuit breakers
Authors: Mohammadhosein Milad , Niayesh Kaveh , Shayegani Akmal Amir Abbas , Mohseni Hossein 
Published: January 2021

AbstractOnline non‐invasive methods to assess circuit breaker condition have been under consideration in recent years. The combination of the arcing time and the short‐circuit current recorded by protective relays can be utilized to assess the degrading impact of current interruption on arcing contacts. In many previous investigations, an integral over arcing time of different functions of current and voltage has been proposed to predict the erosion rate of arcing contacts. Although the arcing time is a crucial parameter for these indices, no easily adaptable method to online condition assessment is available. This paper proposes a method for online determination of arcing time based on the measurement of the switching time of the auxiliary contacts. Several experiments have been performed under no‐load conditions as well as during short‐circuit current interruption, on two circuit breakers with different trip coil excitations (AC and DC). The results show that the delay time between the contact separation instant of the arcing contacts and the switching time of the auxiliary contacts has a very low jitter. This enables precise determination of the arcing time by measurement of the switching time of the auxiliary contacts, which is accessible during the online operation of circuit breakers.
An efficient framework for deep learning‐based light‐defect image enhancement
Authors: Ma Chengxu , Li Daihui , Zeng Shangyou , Zhao Junbo , Chen Hongyang 
Published: January 2021

AbstractThe enhancement of light‐defect images such as extremely low‐light, low‐light and dim‐light has always been a research hotspot. Most of the existing methods are excellent in specific illuminations, and there is much room for improvement in processing light‐defect images with different illuminations. Therefore, this study proposes an efficient framework based on deep learning to enhance various light‐defect images. The proposed framework estimates the reflectance component and illumination component. Next, we propose a generator guided by an attention mechanism in the reflectance part to repair the light‐defect in the dark. In addition, we design a colour loss function for the problem of colour distortion in the enhanced images. Finally, the illumination map of the light‐defect images is adjusted adaptively. Extensive experiments are conducted to demonstrate that our method can not only deal with the images with different illuminations but also enhance the images with clearer details and richer colours. At the same time, we prove its superiority by comparing it with state‐of‐the‐art methods under both visual quality comparison and quantitative comparison of various datasets and real‐world images.
Design and research of single‐sided slotted waveguide antenna with a large beam declination
Authors: Zhao Chengwei , Li Xiaoping , Sun Chao , Tian Lishan , Huang He 
Published: January 2021

AbstractThe slot of the conventional longitudinal slot antenna is alternately opened on both sides of the broadside. A novel single‐sided slot array with a large‐declination (biased towards the load) is proposed, in which the slots are only biased to the same side of the waveguide broadside. The main beam declination of a single‐sided slot antenna is only biased towards the load direction and is only related to the broad‐side of the waveguide. To verify the theoretical analysis, a single‐sided slot array with 10‐slot was simulated, fabricated, and measured. According to the measured results, the antenna achieved a beam declination of 25° and a sidelobe level below −22 dB, which is in good agreement with the theoretical analysis. Furthermore, the main beam declination of the single‐sided slot and the traditional double‐sided slot array has been thoroughly studied and compared. When the main beam has a large declination angle (>30°) to the load, a single‐sided slot array is the only choice.
Dielectric‐loaded substrate integrated waveguide H‐plane horn antenna with embedded air cavity
Authors: Huang Sheng , Chan King Yuk , Fu Yunhao , Ramer Rodica 
Published: January 2021

AbstractA new type of dielectric‐loaded substrate integrated waveguide H‐plane horn antenna with an embedded air cavity is proposed aiming to improve E‐plane performance on a thin substrate. Comparing with recent works, this design attracts superior radiation performance only requiring drilling process to embed a rectangular air cavity in the extended dielectric loading. The measurement results show that at 24.15 GHz, the proposed antenna provides a gain of 13 dBi and 27.7 dB front‐to‐back ratio with narrow 34.3° and 27.3° half‐power beamwidths in E‐ and H‐plane. From 22 to 27 GHz, the side lobe level in E‐plane is reduced below −10 dB. The entire proposed antenna size is 59 × 16 × 3.175 mm.
High scaling ratio line width reduction and fabrication method with electrohydrodynamic jet printing
Authors: E Cheng  , Zhang Tianxiao , Cheng Yu , Li Jinnan , Zhang Zhengyan 
Published: January 2021

AbstractElectrohydrodynamic (EHD) printing has great potential to be used in the field of electronic industry, precision optics and biological engineering. However, it is still a challenge to achieve a high scaling ratio for line patterns production by EHD jet printing technique, which can effectively prevent the needles to be blocked. In this paper, the influence of the key process parameters on the line width of EHD jet printing was investigated. The printing needle with the inner diameter of 890 μm was used, and the line with width of 3.02 μm was printed by optimizing the parameters. The scaling ratio between the needle inner diameter and the printed line width was up to 295 times. At the same time, the function model between the flow rate and printed line width of PVP/PEO composite was deduced. The error was found to be less than 1% by the verification of experiments. By utilizing this model, the printed line width can be predicted by controlling the flow rate, which will greatly improve the work efficiency. By controlling the flow rate, the goal of printing on demand can be realized. The proposed method and model can provide support for the fabrication of micro‐nano scale structure.