bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlation of internet search enquiries, incidence of ophthalmological diseases and corneal, cataract and refractive surgical procedures
Authors: Ghaly Mohamed , Jaber Diana , Matthaei Mario , Cursiefen Claus , Händel Alexander , Köberlein-Neu Juliane , Hörster Robert , Siebelmann Sebastian 
Published: December 2022

AbstractAnalysis of internet search queries (ISQ) could be useful to study public interest and medical need for corneal, cataract, and refractive surgery. To date, there are preliminary data on seasonal trends in ophthalmic conditions, but only few studies correlate these data with real data from healthcare systems. The aim of this study is to analyze ISQ and correlate it with real healthcare system data. Data were retrieved from the KBV registry of patients who underwent outpatient ophthalmic surgery in Germany from 2017 to 2019 and from Statista GmbH from 2010 to 2020 for corneal refractive surgery. Time Series analysis of ISQ was analyzed from 2004 to 2020 and correlated with healthcare system data using bivariate correlation analysis. ISQ correlated significantly with the incidence of ophthalmic procedures such as corneal transplantations (r = 0.69, p < 0.05), cataract- (r = 0.59, p < 0.05) and refractive laser surgery (r = 0.83, p < 0.05) in Germany. In addition, specific trends were observed with respect to individual surgical procedures. The correlation between search intensities and surgical procedures varied significantly. Thus, interests in surgical procedures can be tracked by observing changes in ISQ over time. These data correlate with real healthcare data and could be used in the future for now-casting or even forecasting.
Intestinal bacterial community composition of juvenile Chinese mitten crab Eriocheir sinensis under different feeding times in lab conditions
Authors: Xu Yingkai , Huang Ziwei , Zhang Baoli , Yu Changyue , Li Lisong , Li Xiaodong , Li Yingdong 
Published: December 2022

AbstractFeeding time is an important factor affecting the physiological activity and feeding rhythm of crustaceans. However, little is known about the factors and mechanisms contributing to variations in feeding time in aquatic species or their impacts. Moreover, the gut microbiome largely affects host physiology and is associated with diet. To investigate the effects of different feeding times on the composition of intestinal bacterial communities, high-throughput 16S rRNA sequencing was used to monitor the gut bacteria of the Chinese mitten crab Eriocheir sinensis over a 10-day period under different feeding times: 06:00 h, 12:00 h, 18:00 h, and 24:00 h. Weight gain of the day-fed groups was significantly higher than that of the night-fed groups. Two probiotics, Akkermansia muciniphila and Faecalibacterium prausnitzii, were detected in the intestines of crabs in the 12:00 group. In addition, the diversity and richness of the flora in the 12:00 group were slightly higher than those in the other treatment groups. These results collectively indicate that different feeding times change the intestinal flora composition of Chinese mitten crabs, and further identified specific feeding times associated with a more significant weight gain effect. Our findings provide important insights into improving farming strategies for Chinese mitten crabs.
Using high-throughput sequencing to investigate the dietary composition of the Korean water deer (Hydropotes inermis argyropus): a spatiotemporal comparison
Authors: Lee Seung-Kyung , Woo Cheolwoon , Lee Eun Ju , Yamamoto Naomichi 
Published: December 2022

AbstractThe Korean water deer (Hydropotes inermis argyropus) is considered a vermin in Korea because it damages crops, but also listed as a vulnerable species on the IUCN’s red list. Therefore, it is indispensable to manage them appropriately by understanding the ecology such as food habits. Here, we aimed to apply high-throughput sequencing (HTS), a sensitive and objective method, to investigate the dietary composition of the Korean water deer inhabiting the lowland and forest areas in summer and winter. We targeted the internal transcribed spacer 2 (ITS2) region for plant identification. From a total of 40 fecal samples analyzed, 63 plant genera were identified, withMorusbeing the most abundant, and some of the plant taxa identified by HTS were detected for the first time as the diets of Korean water deer. By type, woody plants (68.6%) were the most predominant, followed by forbs (7.0%) and graminoids (0.7%). We found that the deer in the forest area ate more woody plants (84.6%) than those in the lowland area (52.7%). It was also found that the type of woody plants that the deer ate changed by season. Overall, our results indicate that the Korean water deer is a browser that is seasonally adaptable and feeds on a wide variety of woody plants. We expect that the results and genetics methods reported here, by parallelly investigating their habitat range and reproductive behavior in the future, will help the management and conservation of the Korean water deer, which is in contradictory situations.
Geometry-aware view reconstruction network for light field image compression
Authors: Zhang Youzhi , Wan Lifei , Mao Yifan , Huang Xinpeng , Liu Deyang 
Published: December 2022

AbstractLight Field (LF) imaging empowers many attractive applications by simultaneously recording spatial and angular information of light rays. In order to meet the challenges of LF storage and transmission, many view reconstruction-based LF compression methods are put forward. However, occlusion issue and under-exploitation of LF rich structure information limit the view reconstruction qualities, which further influence LF compression efficiency. In order to alleviate these problems, in this paper, we propose a geometry-aware view reconstruction network for LF compression. In our method, only sparsely-sampled LF views are encoded, which are further used as priors to reconstruct the un-sampled LF views at the decoder side. The proposed reconstruction process contains two stages including geometry-aware reconstruction and texture refinement. The geometry-aware reconstruction stage utilizes a multi-stream framework, which can fully explore LF spatial-angular, location and geometry information. The texture refinement stage can adequately fuse such rich LF information to further improve LF reconstruction quality. Comprehensive experimental results validate the superiority of the proposed method. The rate-distortion performance and the perceptual quality of reconstructed views further demonstrate that the proposed method can save more bitrate while increasing LF reconstruction quality.
Thermal spiral inductor using 3D printed shape memory kirigami
Authors: Kim Yelim , Phon Ratanak , Jeong Heijun , Kim Yeonju , Lim Sungjoon 
Published: December 2022

AbstractSpiral inductors are required to realise high inductance in radio frequency (RF) circuits. Although their fabrication by using micro-electrical–mechanical systems, thin films, actuators, etc., has received considerable research attention, current approaches are both complex and expensive. In this study, we designed and fabricated a thermal spiral inductor by using a three-dimensional (3D) printed shape-memory polymer (SMP). The proposed inductor was inspired by kirigami geometry whereby a two-dimensional (2D) planar geometric shape could be transformed into a 3D spiral one to change the inductance by heating and manually transform. Mechanical and electromagnetic analyses of the spiral inductor design was conducted. Hence, in contrast with the current processes used to manufacture spiral inductors, ours can be realised via a single facile fabrication step.
Nucleophagy delays aging and preserves germline immortality
Authors: Papandreou Margarita-Elena , Konstantinidis Georgios , Tavernarakis Nektarios 
Published: December 2022

AbstractMarked alterations in nuclear ultrastructure are a universal hallmark of aging, progeroid syndromes and other age-related pathologies. Here we show that autophagy of nuclear proteins is an important determinant of fertility and aging. Impairment of nucleophagy diminishes stress resistance, germline immortality and longevity. We found that the nematode Caenorhabditis elegans nuclear envelope anchor protein, nuclear anchorage protein 1 (ANC-1) and its mammalian ortholog nesprin-2 are cleared out by autophagy and restrict nucleolar size, a biomarker of aging. We further uncovered a germline immortality assurance mechanism, which involves nucleolar degradation at the most proximal oocyte by ANC-1 and key autophagic components. Perturbation of this clearance pathway causes tumor-like structures in C. elegans, and genetic ablation of nesprin-2 causes ovarian carcinomas in mice. Thus, autophagic recycling of nuclear components is a conserved soma longevity and germline immortality mechanism that promotes youthfulness and delays aging under conditions of stress.
Utilizing biocatalysis and a sulfolane-mediated reductive acetal opening to access nemtabrutinib from cyrene
Authors: Kuhl Nadine , Turnbull Ben W. H. , Ji Yining , Larson Reed T. , Shevlin Michael , Prier Christopher K. , Chung Cheol K. , Desmond Richard , Guetschow Erik , He Cyndi Qixin , Itoh Tetsuji , Kuethe Jeffrey T. , Newman Justin A. , Reibarkh Mikhail , Rivera Nelo R. , Shang Gao , Wang Zhixun , Zewge Daniel , Thaisrivongs David A. 
Published: December 2022

The development of a protecting group-free, 2-step synthesis of 5-amino-2-hydroxymethyltetrahydropyran 1a from biorenewable Cyrene™ is described which renders access to BTK-inhibitor nemtabrutinib (2) more efficient and sustainable.
High level Petri nets‐based proposal of an integrated intrusion detection and prevention mechanism in network controlled systems
Authors: Farah Khamsa , Chabir Karim , Abdelkrim Mohamed Naceur 
Published: December 2022

AbstractThe authors’ work deals with modelling with coloured Petri nets (CPN) of network controlled systems (NCS) and exposes a proposal of a sensor fault detection and prevention mechanism. In NCS, the network must be viewed as part of the system and not just a means of communication. For this, two issues must be considered. The first consists of adapting the control and diagnostic laws to the performance of the network. The second is to guarantee the performance of the system. Each control loop containing a network is vulnerable to faults and cyber attacks and malicious users can intercept and listen to data during transmission. For that reason, it is essential to protect transmitted data against unauthorized access and modification and to diagnose components. In this paper, the authors presented a model with CPN of a NCS, the authors proposed a sensor fault detection and correction mechanism, then the authors injected a sensor fault and the authors tested the effectiveness of the proposed mechanism in detecting that fault and correcting its influence. Simulation results proved the success of the preventive mechanism in overcoming the influence of the fault and returning to normal behaviour.
An online intelligent robust adaptive LSQR estimation method for LTI state space model
Authors: Hosseini Shahram , Navabi M. , Hajarian Masoud 
Published: December 2022

AbstractRegarding the low accuracy and instability of common online methods for estimating dynamic models in the time domain, in the presence of uncertainty in system dynamics, sensor noise and environmental disturbances, this area is still open for further research. In this paper, a new estimation method is proposed based on a new online robust meta‐heuristic adaptive LSQR (ORALSQR) for simultaneous estimation of a multi input/output linear dynamic model and system state variables. This new adaptive LSQR algorithm is used to solve the output matrix equations of the least squares error problem. The presented algorithm, based on its iterative nature, searches the answer subspace by using a new meta‐heuristic logic. In addition, the algorithm solving steps and the search domain size in each iteration are intelligently determined by the method. In an identification maneuver, this method estimates the state variables using an estimated model in the Kalman filter, then estimates the model online for the next iteration using the state variables. In addition the stability proof of this method is presented. Numerical results show more accuracy and robustness of this method compared to the other methods mentioned in this paper which contain LS and RLS based estimation methods.
Stochastic expansion planning of transmission system and energy hubs in the presence of correlated uncertain variables
Authors: Allahvirdizadeh Yousef , Shayanfar Heidarali , Moghaddam Mohsen Parsa 
Published: December 2022

AbstractEnergy hubs (EHs), with interconnecting different energy carriers, technologies, and sectors, improve energy efficiency and enhance the flexibility of energy management. EHs can be an alternative to the upgradation of the transmission system infrastructures. Then, it is necessary to evaluate accurately the impact of integrating EHs across the power system on the expansion planning of the transmission system. This paper proposes an expansion planning of the transmission system and integrated EHs across the power system in deterministic and stochastic environments. In addition, the correlation among the uncertain variables may affect the expansion planning and scheduling decisions as well as the resulting costs. Therefore, the stochastic modelling of the proposed planning approach is developed considering the correlation among the uncertain variables. The uncertainties related to the generation of the renewable energy sources (RESs), energy demands, and electrical/thermal/cooling/gas price are addressed with a stochastic scenario‐based scheme. For this purpose, numerous scenarios are generated by implementing the well‐known Monte Carlo simulation (MCS) technique. Then the Cholesky decomposition technique combined with Nataf transformation is used to make the samples correlated. Next, the k‐means method as an efficient scheme of data clustering is used to reduce the initial scenarios to some limited ones.
Effect of organophilic group of coupling agent on the electrical performance of Boron Nitride/meta‐aramid composite paper
Authors: Ruan Haoou , Xie Qing , Song Jingxuan , Wang Shenghui , Chang Xiaobin , Xu Yuqin , Lü Fangcheng 
Published: December 2022

AbstractOrganophilic groups of coupling agents can be the key factor for the electrical performance of Boron Nitride (BN)/meta‐aramid composite paper. In this article, four types of triethoxy‐silane coupling agents with different organophilic groups, including mercapto‐propyl (MP), glycidylether‐propyl (GP), amino‐propyl (AP) and trideca‐fluoro‐octyl (TFO) were studied. The structural and electrical properties of modified papers were compared, and the molecular simulation was conducted to reveal the interface interaction of modified BN and aramid. The results show that AP, GP and MP follow the same mechanism, improving the electrical performance by modifying the interface stability and paper structure, and the ranks of improving effects are AP, MP and GP. While, TFO mainly relies on the fluorine components to implement the electrical reinforcement, which compensates for the shortcoming in the paper structure. By choosing TFO and filler content of 15 wt%, the optimal breakdown strength of the paper can be increased to 28.17 kV/mm, 1.8 times that of the paper doped with the hydroxylated BN.
Gesture recognition algorithm based on multi‐scale feature fusion in RGB‐D images
Authors: Sun Ying , Weng Yaoqing , Luo Bowen , Li Gongfa , Tao Bo , Jiang Du , Chen Disi 
Published: December 2022

AbstractWith the rapid development of sensor technology and artificial intelligence, the video gesture recognition technology under the background of big data makes human‐computer interaction more natural and flexible, bringing richer interactive experience to teaching, on‐board control, electronic games, etc. In order to perform robust recognition under the conditions of illumination change, background clutter, rapid movement, partial occlusion, an algorithm based on multi‐level feature fusion of two‐stream convolutional neural network is proposed, which includes three main steps. Firstly, the Kinect sensor obtains RGB‐D images to establish a gesture database. At the same time, data enhancement is performed on training and test sets. Then, a model of multi‐level feature fusion of two‐stream convolutional neural network is established and trained. Experiments result show that the proposed network model can robustly track and recognize gestures, and compared with the single‐channel model, the average detection accuracy is improved by 1.08%, and mean average precision (mAP) is improved by 3.56%. The average recognition rate of gestures under occlusion and different light intensity was 93.98%. Finally, in the ASL dataset, LaRED dataset, and 1‐miohand dataset, recognition accuracy shows satisfactory performances compared to the other method.
Integrated approaches to COVID-19 emergency response in fragile, conflict-affected and vulnerable settings: a public health policy brief
Authors: Olu Olushayo Oluseun , Waya Joy Luba Lomole , Bankss Sandra , Maleghemi Sylvester , Guyo Argata Guracha 
Published: December 2022

AbstractIn the absence of fully effective measures to prevent and treat COVID-19, the limited access to and hesitancy about vaccines, the prolongation of the on-going pandemic is likely. This underscores the need to continue to respond and maintain preparedness, preferably using a more sustainable approach. A sustainable management is particularly important in fragile, conflict-affected and vulnerable countries of sub-Saharan Africa given several peculiar challenges. This Viewpoint proposes policy options to guide transitioning from current COVID-19 emergency response interventions to longer-term and more sustainable responses in such settings. In the long term, a shift in policy from a vertical to a more effective approach should integrate response coordination, surveillance, case management, risk communication and operational support, among other elements, for better results. We call on public health policymakers, partners and donors to support full implementation of these policy options in a holistic manner to encompass all emerging public health threats.
Ultra-sensitive terahertz sensing based on Rayleigh anomaly in hyperbolic metamaterial gratings
Authors: Li Guangyuan , Yang Xiuhua 
Published: December 2022

Abstract
Terahertz sensors are promising for biomedical, environmental and security applications. Challenges in terahertz sensing have been the limited sensitivity and small figure of merit (FOM). Here we propose an ultra-sensitive terahertz sensing platform based on the Rayleigh anomaly (RA) in hyperbolic metamaterial gratings, which are composed of periodic slits patterned in paired metal-dielectric multilayers. Simulation results show that, under normal incidence with transverse-magnetic polarization and designed with proper parameters, the proposed structure has a super-high quality factor of 516, an ultra-high sensitivity of 1.56 THz RIU−1 (or

9.06
×

10
4

nm RIU−1), and extremely large FOM of 355 RIU−1 at frequency of 2.272 THz, corresponding to a large normalized sensitivity of 0.69 RIU−1. By comparing with other multilayered gratings, we attribute this exceptionally high sensing performance to the strong local field enhancement over an extremely large area in the sensing region at the RA frequency, which is found to be unique for hyperbolic metamaterial gratings. We further show that the resonance frequency decreases linearly with the grating period, following the RA equation, whereas the large normalized sensitivity keeps constant. We expect this work provides a novel strategy to design extremely sensitive sensors in terahertz as well as other frequency regimes.
A potential well model for host-guest chemistry in double-network hydrogels toward mechanochemical coupling and toughening
Authors: Xing Ziyu , Lu Haibao , Lau Denvid , Fu Yong-Qing 
Published: December 2022

Abstract
Different from conventional single-network hydrogels, double-network (DN) hydrogels have attracted great research interest due to their ultra-high toughness; however, the working principles behind their complex mechanochemical coupling have not been fully understood. In this study, an extended potential well model is formulated to investigate the host-guest chemistry and the free-energy trap effect, coupled in DN hydrogels undergoing mechanochemical toughening. According to the Morse potential and mean field model, the newly established potential well model can describe the coupled binding of the host brittle network and guest ductile network in the DN hydrogels. A free-energy equation is further proposed to describe the working principles of the mechanochemical coupling and toughening mechanisms using the depth, width, and trap number of potential wells, which determine the barrier energy of the host brittle network, the mesh size of guest ductile network, and the mechanochemical host-guest interactions of these two networks, respectively. Finally, the effectiveness of the proposed model is verified using finite-element analysis (FEA) and experimental results of various DN hydrogels reported in the literature. Using the potential well model, which has host-guest chemistry from both brittle and ductile networks, this study clarifies the linking of mechanochemical coupling and toughening mechanisms in DN hyrdogels.
Guided ultrasonic waves propagation imaging: a review
Authors: Chia Chen Ciang , Lee Shi Yn , Harmin Mohammad Yazdi , Choi Yunshil , Lee Jung-Ryul 
Published: December 2022

Abstract
This article presents a comprehensive review of the laser-based guided ultrasonic waves propagation imaging (G-UPI) system and respective signal/data processing methods related to the nondestructive testing and evaluation of thin-walled structures. The primary goal of this study is to review and recognize various processing methods, explain the working principles of the most influential methods, and highlight outstanding capabilities. In addition, the suitability of the methods for multiple types of damage and defect in various materials and structures are presented. At the same time, success stories of difficult-to-inspect cases are highlighted. Its secondary goal is to compare and discuss the merits and demerits of the laser-scanning part of the system for ultrasound generation and acquisition to provide a guideline for scanning scheme or hardware selection. Finally, the potential challenges and prospects of the G-UPI are discussed. It is expected that this review would serve as an entrance key for newcomers and a reference point for researchers to explore the opportunities for further improvement in the laser ultrasound-based evaluation of critical engineering structures.