bluuebunny/crossref_metadata_2025_split huggingface dataset:
Frontoparietal network resilience is associated with protection against cognitive decline in Parkinson’s disease
Authors: Cascone Arianna D. , Langella Stephanie , Sklerov Miriam , Dayan Eran 
Published: September 2021

AbstractThough Parkinson’s disease is primarily defined as a movement disorder, it is also characterized by a range of non-motor symptoms, including cognitive decline. The onset and progression of cognitive decline in individuals with Parkinson’s disease is variable, and the neurobiological mechanisms that contribute to, or protect against, cognitive decline in Parkinson’s disease are poorly understood. Using resting-state functional magnetic resonance imaging data collected from individuals with Parkinson’s disease with and without cognitive decline, we examined the relationship between topological brain-network resilience and cognition in Parkinson’s disease. By leveraging network attack analyses, we demonstrate that relative to individuals with Parkinson’s disease experiencing cognitive decline, the frontoparietal network in cognitively stable individuals with Parkinson’s disease is significantly more resilient to network perturbation. Our findings suggest that the topological robustness of the frontoparietal network is associated with the absence of cognitive decline in individuals with Parkinson’s disease.
Heimdallarchaea encodes profilin with eukaryotic-like actin regulation and polyproline binding
Authors: Survery Sabeen , Hurtig Fredrik , Haq Syed Razaul , Eriksson Jens , Guy Lionel , Rosengren K. Johan , Lindås Ann-Christin , Chi Celestine N. 
Published: September 2021

AbstractIt is now widely accepted that the first eukaryotic cell emerged from a merger of an archaeal host cell and an alphaproteobacterium. However, the exact sequence of events and the nature of the cellular biology of both partner cells is still contentious. Recently the structures of profilins from some members of the newly discovered Asgard superphylum were determined. In addition, it was found that these profilins inhibit eukaryotic rabbit actin polymerization and that this reaction is regulated by phospholipids. However, the interaction with polyproline repeats which are known to be crucial for the regulation of profilin:actin polymerization was found to be absent for these profilins and was thus suggested to have evolved later in the eukaryotic lineage. Here, we show that Heimdallarchaeota LC3, a candidate phylum within the Asgard superphylum, encodes a putative profilin (heimProfilin) that interacts with PIP2 and its binding is regulated by polyproline motifs, suggesting an origin predating the rise of the eukaryotes. More precisely, we determined the 3D-structure of Heimdallarchaeota LC3 profilin and show that this profilin is able to: i) inhibit eukaryotic actin polymerization in vitro; ii) bind to phospholipids; iii) bind to polyproline repeats from enabled/vasodilator‐stimulated phosphoprotein; iv) inhibit actin from Heimdallarchaeota from polymerizing into filaments. Our results therefore provide hints of the existence of a complex cytoskeleton already in last eukaryotic common ancestor.
Flexible and high precision thermal metasurface
Authors: Wang Jiyao , Qin Ling , Xu Wei 
Published: September 2021

AbstractThermal metamaterials are artificial materials used to manipulate heat flow in many applications, such as thermal protection, thermal camouflage, and precise temperature control. Most of the existing thermal metamaterials are mainly based on metal, which makes their fabrication complex and time-consuming, and limits their flexibility. Here, we show a strategy to simplify the fabrication process, improve machining accuracy, and realize flexibility in thermal metasurfaces. Our proposed thermal metasurface is fabricated by laser engraving of copper-graphene coating surface, utilizing graphene coating with high thermal conductivity instead of the traditional filling materials of low thermal conductivity. It maintains the integrity of copper substrate, giving the metasurface a good heat dispersion. Controlled temperature gradient patterns are established, and the metasurface can be bent without changing its features, except for a slight variation in its thermal gradient. Finally, its cloaking ability is demonstrated by camouflaging the same heat source in the shape of different objects. Our designed metasurface mitigates the limitations in design and fabrication of existing thermal metamaterials, and can be used in applications requiring large flexibility, thermal illusion, and large thermal gradients on small scales.
Enterobacter aerogenes ZDY01 inhibits choline-induced atherosclerosis through CDCA-FXR-FGF15 axis
Authors: Tang Jinghui , Qin Manman , Tang Le , Shan Dan , Zhang Cheng , Zhang Yifeng , Wei Hua , Qiu Liang , Yu Jun 
Published: September 2021

ZDY01 utilized TMA and reduced TMAO level, increased abundance of gut microbiota, accelerated resorption of bile acids into blood by upregulating Asbt and Ostα/β expression, and inactivated FXR-FGF15 axis resulting in increased CYP7A1 expression.
Nuclear atypia grading in breast cancer histopathological images based on CNN feature extraction and LSTM classification
Authors: Karimi Jafarbigloo Sanaz , Danyali Habibollah 
Published: September 2021

AbstractEarly diagnosis of breast cancer, the most common disease among women around the world, increases the chance of treatment and is highly important. Nuclear atypia grading in histopathological images plays an important role in the final diagnosis and grading of breast cancer. Grading images by pathologists is a time consuming and subjective task. Therefore, the existence of a computer‐aided system for nuclear atypia grading is very useful and necessary. In this study, two automatic systems for grading nuclear atypia in breast cancer histopathological images based on deep learning methods are proposed. A patch‐based approach is introduced due to the large size of the histopathological images and restriction of the training data. In the proposed system I, the most important patches in the image are detected first and then a three‐hidden‐layer convolutional neural network (CNN) is designed and trained for feature extraction and to classify the patches individually. The proposed system II is based on a combination of the CNN for feature extraction and a two‐layer Long short‐term memory (LSTM) network for classification. The LSTM network is utilised to consider all patches of an image simultaneously for image grading. The simulation results show the efficiency of the proposed systems for automatic nuclear atypia grading and outperform the current related studies in the literature.
Capturing semantic features to improve Chinese event detection
Authors: Ma Xiaobo , Liu Yongbin , Ouyang Chunping 
Published: September 2021

AbstractCurrent Chinese event detection methods commonly use word embedding to capture semantic representation, but these methods find it difficult to capture the dependence relationship between the trigger words and other words in the same sentence. Based on the simple evaluation, it is known that a dependency parser can effectively capture dependency relationships and improve the accuracy of event categorisation. This study proposes a novel architecture that models a hybrid representation to summarise semantic and structural information from both characters and words. This model can capture rich semantic features for the event detection task by incorporating the semantic representation generated from the dependency parser. The authors evaluate different models on kbp 2017 corpus. The experimental results show that the proposed method can significantly improve performance in Chinese event detection.
HCISNet: Higher‐capacity invisible image steganographic network
Authors: Li Yafeng , Liu Ju , Liu Xiaoxi , Wang Xuejing , Gao Xuesong , Zhang Yuyi 
Published: September 2021

AbstractInformation hiding as a crucial method for multimedia security and privacy protection, has received a substantial amount of attention. However, the most existing methods focus on the resistance of steganalysis and the robustness of information, resulting in low capacity. In this paper, to further increase the capacity of information hiding, a high‐capacity adversarial image steganography model with end‐to‐end manner, termed as HCISNet is proposed. First, an enhanced Dense Atrous Spatial Pyramid Pooling module is presented to learn more semantic information in cover image, which can adaptively embed more message in redundant regions with rich textures. Then, a modified discriminator network with lightweight residual block is employed to assist the encoder network with optimal high‐capacity solution. Meanwhile, the multiple objective function with the perceptual loss and several training tricks are developed, which can improve the visual and perceptual consistency of the original and the steganographic image, further enhancing the capacity. Finally, experiments and analysis are conducted on three public datasets, where this model has better imperceptibility, higher security and greater capacity. Under same experimental conditions, the cover image can embed 5.68 bits per pixel (BPP), far exceeding the previous highest value of 4.4 BPP in state‐of‐the‐art methods in the authors' knowledge.
An unbiased NOEMA 2.6 to 4 mm survey of the GG Tau ring: First detection of CCS in a protoplanetary disk
Authors: Phuong N. T. , Dutrey A. , Chapillon E. , Guilloteau S. , Bary J. , Beck T. L. , Coutens A. , Denis-Alpizar O. , Di Folco E. , Diep P. N. , Majumdar L. , Melisse J.-P. , Lee C.-W. , Pietu V. , Stoecklin T. , Tang Y.-W. 
Published: September 2021

Context. Molecular line surveys are among the main tools to probe the structure and physical conditions in protoplanetary disks (PPDs), the birthplace of planets. The large radial and vertical temperature as well as density gradients in these PPDs lead to a complex chemical composition, making chemistry an important step to understand the variety of planetary systems.
Aims. We aimed to study the chemical content of the protoplanetary disk surrounding GG Tau A, a well-known triple T Tauri system.
Methods. We used NOEMA with the new correlator PolyFix to observe rotational lines at ∼2.6 to 4 mm from a few dozen molecules. We analysed the data with a radiative transfer code to derive molecular densities and the abundance relative to 13CO, which we compare to those of the TMC1 cloud and LkCa 15 disk.
Results. We report the first detection of CCS in PPDs. We also marginally detect OCS and find 16 other molecules in the GG Tauri outer disk. Ten of them had been found previously, while seven others (13CN, N2H+, HNC, DNC, HC3N, CCS, and C34S) are new detections in this disk.
Conclusions. The analysis confirms that sulphur chemistry is not yet properly understood. The D/H ratio, derived from DCO+/HCO+, DCN/HCN, and DNC/HNC ratios, points towards a low temperature chemistry. The detection of the rare species CCS confirms that GG Tau is a good laboratory to study the protoplanetary disk chemistry, thanks to its large disk size and mass.
Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine
Authors: Guo Lin Lawrence , Pfohl Stephen R. , Fries Jason , Posada Jose , Fleming Scott Lanyon , Aftandilian Catherine , Shah Nigam , Sung Lillian 
Published: September 2021

Abstract
Objective The change in performance of machine learning models over time as a result of temporal dataset shift is a barrier to machine learning-derived models facilitating decision-making in clinical practice. Our aim was to describe technical procedures used to preserve the performance of machine learning models in the presence of temporal dataset shifts.
Methods Studies were included if they were fully published articles that used machine learning and implemented a procedure to mitigate the effects of temporal dataset shift in a clinical setting. We described how dataset shift was measured, the procedures used to preserve model performance, and their effects.
Results Of 4,457 potentially relevant publications identified, 15 were included. The impact of temporal dataset shift was primarily quantified using changes, usually deterioration, in calibration or discrimination. Calibration deterioration was more common (n = 11) than discrimination deterioration (n = 3). Mitigation strategies were categorized as model level or feature level. Model-level approaches (n = 15) were more common than feature-level approaches (n = 2), with the most common approaches being model refitting (n = 12), probability calibration (n = 7), model updating (n = 6), and model selection (n = 6). In general, all mitigation strategies were successful at preserving calibration but not uniformly successful in preserving discrimination.
Conclusion There was limited research in preserving the performance of machine learning models in the presence of temporal dataset shift in clinical medicine. Future research could focus on the impact of dataset shift on clinical decision making, benchmark the mitigation strategies on a wider range of datasets and tasks, and identify optimal strategies for specific settings.
Study on discharge mode and transition mechanism of atmospheric pressure Ar/Zn pulsed microwave plasma jet
Authors: Zhang Sanyang , Chen Zhaoquan , Yang Jie , Chen Sile , Feng Deren , Zhou Yuming , Wang Bing , Lu Xinpei 
Published: September 2021

The microwave plasma jet has the advantage of high plasma density and abundant active particles but fails to produce large-scale microwave plasmas in ambient air which hinders the application of microwave plasma ignition and combustion. We have applied a surface wave resonator (including a Zn-coated iron wire trigger) to produce a large-scale Ar/Zn pulsed microwave plasma jet. The discharge experiment shows that the plasma jet generally presents three discharge modes, namely, filamentous argon discharge (P &lt; 120 W), bright argon plasma filaments covered by Ar/Zn thin plasma layers (120 W ≤ P ≤ 150 W), and bright thick Ar/Zn plasma columns (P ≥ 155 W). The optical emission spectrum indicates that the electron temperature is ∼4000–5000 K, the electron density is on the order of 1015 cm−3, and the plasma has the characteristic of local thermodynamic equilibrium. According to the transient discharge photos and the simulated electric fields, the mechanism of the three discharge modes and their transformations could be attributed to the combined interactions (the mutual resonance enhancement between the surface wave and the plasma jet, the propagation of the ionization wave, and the different particle states in the Ar/Zn pulsed microwave plasma). The results have suggested that the large-scale Ar/Zn pulsed microwave plasma jet can be generated by adding Zn vapor into the Ar microwave plasma jet and the proposed Ar/Zn pulsed microwave plasma jet is suitable for the application of plasma ignition and combustion.
Design of a large-radius high impedance intense current diode based on gradient magnetic field
Authors: Chen Yinghao , Ju Jinchuan , Zhou Yunxiao , Zhang Jun , Zhang Wei , Zhang Faning 
Published: September 2021

In order to reduce the size of high impedance diodes and magnetic energy consumptions, a high impedance intense current diode is designed in this paper. By reducing the center radius of the cathode and utilizing the gradient magnetic field, the electron beam is emitted in the cathode with a small radius and transmitted in the drift tube with a large radius. The influence of magnetic field distribution on the electron beam transmission is analyzed by particle-in-cell simulation. When the diode voltage is 680 kV, the impedance is 77 Ω, and the cathode radius is 60 mm, the anode radius of the traditional diode is 116 mm and the cathode–anode axial gap is 57 mm. At the same voltage and impedance, the cathode radius of the novel diode is 38 mm, the anode radius is reduced to 80 mm, and the cathode–anode axial gap is shortened to 36 mm. Further application of the novel diode to a relativistic triaxial klystron amplifier device shows that the output power of the novel diode is the same as that of the traditional diode. Through simple quantitative analysis, it is found that the magnetic energy consumption of the novel diode is less than that of the traditional diode. To sum up, the novel diode can achieve good performances in a smaller volume than the traditional diodes.
Obligate movements of an active site–linked surface domain control RNA polymerase elongation and pausing via a Phe pocket anchor
Authors: Bao Yu , Landick Robert 
Published: September 2021

Significance
RNA synthesis by cellular RNA polymerases depends on an active-site component called the trigger loop that oscillates between an unstructured loop that admits NTP substrates and a helical hairpin that positions the NTP in every round of nucleotide addition. In most bacteria, the trigger loop contains a large, surface-exposed insertion module that occupies different positions in different transcription complexes but whose function during active transcription is unknown. By developing and using a disulfide reporter system, we find the insertion module must also alternate between in and out positions for every nucleotide addition, must swivel to a paused position to support regulation, and in enterobacteria, evolved a “Phe pocket” that captures a key phenylalanine in the out and swivel positions.
Location of freight warehouses facilities: A GIS-based multi-criteria decision analysis
Authors: Wazer Zaina B , Moutaz Noor 
Published: September 2021

AbstractFreight transportation is of high importance and is used to determine the region’s economy. Typically, effective freight transportation systems are related to decreasing the costs of moving goods from and to the logistics facilities. The city of Baghdad suffers from many problems with the land transport system, especially the transportation of goods, and among the important things to reduce the current burden on the network is to find the most suitable sites for the establishment of warehouses distributed over each city of Baghdad. Understanding the assembly pattern of the truck’s trip ends can help improve the location of these facilities on space. This paper explores the best places for unloading (warehouses), using 4 criteria that affect taking the most appropriate location for warehouses to improve logistical facilities, which are (land use, population, current warehouses, road network). The weight of criteria was collected from the questionnaire using the Google form and obtain answers from Decision-makers to include them in the AHP hierarchical analysis process to obtain the weights for each criterion. Multi-criteria decision analysis is performed to create a suitable surface to identify potential locations where new logistical facilities can be established. The ArcGIS 10.7 software and its extensions (i.e. spatial analysis and network analysis) are used extensively in analysis for modelling site allocation. The results indicate that the most suitable sites from the group of sites that appeared in the analysis are (near the entrance to the Diyala Bridge and the entrance to the people on the outskirts of the city of Baghdad).
Comparison of the winglet aerodynamic performance in unmanned aerial vehicle at low Reynolds number
Authors: Putro S H S , Pitoyo B J , Pambudiyatno N , Sutardi  , Widodo W A 
Published: September 2021

Abstract
The Aerodynamic performance of an object is very dependent on the flow of fluid through it and the geometric shape of the object. The use of Unmanned Aerial Vehicle (UAV) demands high aerodynamic performance because it strongly supports the cruising range and fuel or battery used. By reducing drag and increasing the lift optimally, the resulting lift to drag ratio will get maximum results. This study compares the use of winglets in UAVs at low Reynolds numbers. This is very important because generally UAVs are used at low Reynolds numbers. The freestream used is Re = 2.34 x 104 on several low to high angle of attack. The type of airfoil used is Eppler 562 which is equipped with a winglet. Winglets used are simple winglets, blended winglets, and wingtip fence. The geometry was analyzed using numerical simulations namely computational fluid dynamic (CFD). The turbulent model used in this study is K-ω SST on Ansys 19.1. From this study it was found that the use of a wingtip fence produced the best aerodynamic performance compared to other configurations. In addition, the use of a wingtip fence can delay stall and separation better than simple and blended winglets.
Structure from Motion (SfM) method to characterize fluvial sedimentology in Way Semaka river in Lampung province, Indonesia
Authors: Wibowo R C , Mulyatno B S , Dewanto O , Sarkowi M 
Published: September 2021

Abstract
Structure from motion (SfM) has been applied recently in fluvial sedimentology. This application is due to the availability of many low-cost unmanned aerial vehicles/drones, which can help overcome challenging terrain, provide efficient and reproducible and high-accuracy topographic images and data. The current study describes the application of SfM to build a geomorphological model and estimate the surface water velocity of the Way Semaka River in the Bandar Negeri Suoh (BNS) region in the West Lampung area. Way Semaka is a river type with an extensive meandering system and stable extension tectonic regime relatively. River morphology approximately 96.62 m width and 4 m depth in straight (relatively) area, whereas in channel area approximately 171.22 m width and 5 m depth. The velocity range between 0.39 – 1.56 m/s based on image analysis proven by current meter measurements onsite with an RMS error of 0.25. Manual geomorphic unit level 2 analysis revealed that 9% of the coverage consisted of basins for the channel’s zone, 35% of the coverage consisted of convexity, 9% consisted of planar features, and 37% of the coverage consisted of the transition zone.
Synthesis and characterization exopolysaccharide from algae Spirulina sp. using technique sol-gel as adsorbent Pb(II) ion
Authors: Kausar R A , Buhani  , Suharso  , Setiawan A 
Published: September 2021

Abstract
In this study, a modification of exopolysaccharide (EPS) from Spirulina sp. algae biomass with silica (HES) and exopolysaccharide from Spirulina sp. algae biomass with silica coated by magnetite particles (HESM) has been done successfully. A series of experiments with the batch method were conducted to test the ability of HESM adsorption of Pb(II) ions in solution. Identification of functional groups of HESM adsorbents was studied using infrared spectrometer (IR) while surface morphological analysis and composition of the constituent elements of HESM were performed using scanning electron microscope-energy (SEM). Concentration of Pb(II) ion in the adsorption process were analysed by inductively coupled plasma-atomic emission spectrometry (ICP-AES Adsorption of Pb(II) ions with HES and HESM is optimum at pH 7 and concentration at 25 ppm with the adsorption capacity on HES at 3.85 mg g−1 while on HESM at 272.63 mg g−1, contact time of 15 min and it tends to follow second orde pseudo kinetic model and Langmuir adsorption isotherm model.