bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overview of Vacuum Technology
Authors: Gessert Timothy A. 
Published: December 2021

Overview of Vacuum Technology provides the reader a broad treatment of typical systems and components used in the critical field of vacuum technology. It demonstrates where and why certain vacuum components are used in this rapidly evolving area of science. It develops the reader's understanding of how to effectively establish vacuum equipment that will meet both their present and near-future needs. This important reference offers guidance on “costs of ownership” concerns for initial purchase and other less-understood costs related to operation and maintenance. This foundation will allow technologists and researchers to acquire vacuum equipment capable of producing a required level of reproducibility, as well as maintain the vacuum equipment within the research and production budgets.
This important book:Provides definitions and use cases, principles and key applications, procedures, and data evaluationDiscusses the development of gas laws, the transport of gas molecules, and vacuum chamber outgassingPresents descriptions and selection advice for critical components such as gauges, pumps, valves, chambers, feedthroughs, and flangesScientists, engineers, and technologists in semiconductor electronics, photovoltaics, energy, and materials science will find this an invaluable reference. Educators and researchers interested in vacuum technology will also find this book a useful resource.
Place cells may simply be memory cells: Memory compression leads to spatial tuning and history dependence
Authors: Benna Marcus K. , Fusi Stefano 
Published: December 2021

Significance
Numerous studies on primates revealed the importance of the hippocampus in memory formation. The rodent literature instead focused on the spatial representations that are observed in navigation experiments. Here, we propose a simple model of the hippocampus that reconciles the main findings of the primate and rodent studies. The model assumes that the hippocampus is a memory system that generates compressed representations of sensory experiences using previously acquired knowledge about the statistics of the world. These experiences can then be memorized more efficiently. The sensory experiences during the exploration of an environment, when compressed by the hippocampus, lead naturally to spatial representations similar to those observed in rodent studies and to the emergence of place cells.
Decoupling between Shockley partials and stacking faults strengthens multiprincipal element alloys
Authors: Pei Zongrui , Zhang Siyuan , Lei Yinkai , Zhang Fan , Chen Mingwei 
Published: December 2021

Significance
Alloys play crucial roles in the civilization history of human beings. Recently, a group of novel alloys without principal elements—i.e., multiprincipal element alloys—have been extensively studied due to their excellent mechanical performance. Although we know many multiprincipal element alloys have high-yield stresses, the underlying mechanistic origins remain elusive. Assisted by state-of-the-art theoretical and experimental methods, we show that the excellent mechanical properties have diverse origins. The strengthening effects through Shockley partials and stacking faults can change in different directions in these alloys, breaking the conventional wisdom. These insights generalize the physical picture for the strengthening mechanisms that can coexist in the multiprincipal element alloys and provide a pathway to design high-performance alloys.
A halogen budget of the bulk silicate Earth points to a history of early halogen degassing followed by net regassing
Authors: Guo Meng , Korenaga Jun 
Published: December 2021

Significance
Halogens play a critical role in biochemistry and are useful to understand how planets formed and evolved. As we found that the traditional way of constraining the halogen budget within Earth is unreliable, we developed a method that better utilizes relevant geochemical data and estimated halogen abundances in various silicate reservoirs of Earth. Our halogen budget indicates that the majority of halogens are more concentrated in the mantle than in the surface and suggests that halogens have likely experienced early degassing and subsequent net regassing. This study also provides an important key to deciphering the geological history of ocean chemistry.
Label-free detection of single nanoparticles with disordered nanoisland surface plasmon sensor
Authors: Lee Hongki , Berk Joel , Webster Aaron , Kim Donghyun , Foreman Matthew R 
Published: December 2021

Abstract
We report sensing of single nanoparticles using disordered metallic nanoisland substrates supporting surface plasmon polaritons (SPPs). Speckle patterns arising from leakage radiation of elastically scattered SPPs provide a unique fingerprint of the scattering microstructure at the sensor surface. Experimental measurements of the speckle decorrelation are presented and shown to enable detection of sorption of individual gold nanoparticles and polystyrene beads. Our approach is verified through bright-field and fluorescence imaging of particles adhering to the nanoisland substrate.
PET respiratory motion correction: quo vadis?
Authors: Lamare F , Bousse A , Thielemans K , Liu C , Merlin T , Fayad H , Visvikis D 
Published: December 2021

Abstract
Positron emission tomography (PET) respiratory motion correction has been a subject of great interest for the last twenty years, prompted mainly by the development of multimodality imaging devices such as PET/computed tomography (CT) and PET/magnetic resonance imaging (MRI). PET respiratory motion correction involves a number of steps including acquisition synchronization, motion estimation and finally motion correction. The synchronization steps include the use of different external device systems or data driven approaches which have been gaining ground over the last few years. Patient specific or generic motion models using the respiratory synchronized datasets can be subsequently derived and used for correction either in the image space or within the image reconstruction process. Similar overall approaches can be considered and have been proposed for both PET/CT and PET/MRI devices. Certain variations in the case of PET/MRI include the use of MRI specific sequences for the registration of respiratory motion information. The proposed review includes a comprehensive coverage of all these areas of development in field of PET respiratory motion for different multimodality imaging devices and approaches in terms of synchronization, estimation and subsequent motion correction. Finally, a section on perspectives including the potential clinical usage of these approaches is included.
Pre- and post-treatment image-based dosimetry in 90Y-microsphere radioembolization using the TOPAS Monte Carlo toolkit
Authors: Bertolet Alejandro , Wehrenberg-Klee Eric , Bobić Mislav , Grassberger Clemens , Perl Joseph , Paganetti Harald , Schuemann Jan 
Published: December 2021

Abstract

Objective. To evaluate the pre-treatment and post-treatment imaging-based dosimetry of patients treated with 90Y-microspheres, including accurate estimations of dose to tumor, healthy liver and lung. To do so, the Monte Carlo (MC) TOPAS platform is in this work extended towards its utilization in radionuclide therapy. Approach. Five patients treated at the Massachusetts General Hospital were selected for this study. All patients had data for both pre-treatment SPECT-CT imaging using 99mTc-MAA as a surrogate of the 90Y-microspheres treatment and SPECT-CT imaging immediately after the 90Y activity administration. Pre- and post-treatment doses were computed with TOPAS using the SPECT images to localize the source positions and the CT images to account for tissue inhomoegeneities. We compared our results with analytical calculations following the voxel-based MIRD scheme. Main results. TOPAS results largely agreed with the MIRD-based calculations in soft tissue regions: the average difference in mean dose to the liver was 0.14 Gy GBq−1 (2.6%). However, dose distributions in the lung differed considerably: absolute differences in mean doses to the lung ranged from 1.2 to 6.3 Gy GBq−1 and relative differences from 153% to 231%. We also found large differences in the intra-hepatic dose distributions between pre- and post-treatment imaging, but only limited differences in the pulmonary dose. Significance. Doses to lung were found to be higher using TOPAS with respect to analytical calculations which may significantly underestimate dose to the lung, suggesting the use of MC methods for 90Y dosimetry. According to our results, pre-treatment imaging may still be representative of dose to lung in these treatments.
Comparison of the electrical and impedance properties of Au/(ZnOMn:PVP)/n-Si (MPS) type Schottky-diodes (SDs) before and after gamma-irradiation
Authors: Altındal Şemsettin , Barkhordari Ali , Pirgholi-Givi Gholamreza , Ulusoy Murat , Mashayekhi Hamidreza , Özçelik Süleyman , Azizian-Kalandaragh Yashar 
Published: December 2021

Abstract
The effect of 60Co-iradiation) on the electrical parameters in the Au/(ZnOMn:PVP)/n-Si SDs have been investigated using the current-voltage (I–V) and capacitance/conductance-voltage (C/G–V) measurements. Firstly, the values of reverse-saturation-current (Io), ideality-factor (n), barrier-height (BH), shunt/series resistances (Rsh, Rs), and rectifying-rate (RR) were extracted from the I–V data before and after gamma-irradiation (5 and 60 kGy) using thermionic-emission (TE), Norde, and Cheung methods. The surface-states (Nss) versus energy (Ec–Ess) profile was extracted from I–V data considering voltage-dependent of n and BH using Card-Rhoderick method. Secondly, the doping-donor atoms (Nd), Fermi-energy (EF), BH, maximum electric-field (Em), and depletion-layer width (Wd) were extracted from the linear-part of reverse-bias C−2–V plot for 100 kHz before and after irradiation. Finally, the voltage-dependent profiles of Rs and radiation-induced of Nss were extracted from the C/G–V plots by using Nicollian-Brews and the difference between C–V plots before and after irradiation, respectively. The peak behavior in the Nss–V plots and shifts in its position was attributed to special-distribution of Nss at (ZnOMn:PVP)/n-Si interface and restructure/reordering of them under radiation and electric field. Experimental results show that gamma-irradiation is more effective both on the I–V and C/G–V plots or electrical parameters, and hence the fabricated Au/(ZnOMn:PVP)/n-Si SDs can be used as a radiation-sensor.
An ARDS Severity Recognition Model based on XGBoost
Authors: Zhang Huimin , Ding Renshuang , Zhang Qi , Fang Mingxing , Zhang Guanghua , Yu Naiwen 
Published: December 2021

Abstract
Given the subjectivity and non-real-time of disease scoring system and invasive parameters in evaluating the development of acute respiratory distress syndrome (ARDS), combined with noninvasive parameters, this paper proposed an ARDS severity recognition model based on extreme gradient boosting (XGBoost). Firstly, the physiological parameters of patients were extracted based on the MIMIC-III database for statistical analysis, and the outliers and unbalanced samples were processed by the interquartile range and synthetic minority oversampling technique. Then, Pearson correlation coefficient and random forest were used as hybrid feature selection to score the noninvasive parameters comprehensively, and essential parameters for identifying diseases were obtained. Finally, XGBoost combined with grid search cross-validation to determine the best hyper-parameters of the model to realize the accurate classification of disease degree. The experimental results show that the model’s area under the curve (AUC) is as high as 0.98, and the accuracy is 0.90; the total score of blood oxygen saturation (SpO2) is 0.625, which could be used as an essential parameter to evaluate the severity of ARDS. Compared with traditional methods, this model has excellent advantages in real-time and accuracy and could provide more accurate diagnosis and treatment suggestions for medical staff.
Research on Strawberry Maturity Detection Technology Based on Improved YOLOv4
Authors: Cui Ming , Jiang Qiyou , Li Na , Xue Xiaosong 
Published: December 2021

Abstract
Strawberry maturity detection is a key technology for automated strawberry picking and intelligent information monitoring. This paper studies strawberry maturity detection technology, and proposes an improved YOLOv4 convolutional neural network detection method. In view of great amount of network parameters, this paper uses MobileNetv3 backbone feature extraction network and depthwise separable convolution for lightweight improvement of the YOLOv4 network. In order to increase the model training accuracy, this paper uses the Kmeans++ clustering algorithm to calculate the prior bounding box size, and uses transfer learning and staged training methods to improve the training efficiency of the built network model. The experimental results show that the mean average precision (mAP) of the test dataset in this paper is 96.78%; the precision of mature strawberry detection is 98.72%, with recall rate 91.67% and average precision (AP) 99.56%; the precision of immature strawberry detection is 90.76%, with recall rate 83.92% and AP 94.00%. Single image detection time is 56ms, which can meet the demand for real-time high-precision detection of strawberries.
Outlier Detection Method for Flash Flood Disaster Monitoring Data based on Information Entropy
Authors: Chen Yongzhi , Xu Ziao , Niu Chaoqun 
Published: December 2021

Abstract
In the research of flash flood disaster monitoring and early warning, the Internet of Things is widely used in real-time information collection. There are abnormal situations such as noise, repetition and errors in a large amount of data collected by sensors, which will lead to false alarm, lower prediction accuracy and other problems. Aiming at the characteristic that outliers flow of sensors will cause obvious fluctuation of information entropy, this paper proposes a local outlier detection method based on information entropy and optimized by sliding window and LOF (Local Outlier Factor). This method can be used to improve the data quality, thus improving the accuracy of disaster prediction. The method is applied to data stream processing of water sensor, and the experimental results show that the method can accurately detect outliers. Compared with the existing detection methods that only use data distance to determine, the test positive rate is improved and the false positive rate is reduced.
Meta-Analysis of the Correlation between TCM Syndromes of Lung Cancer and CT through Data Mining and Computer Software
Authors: Su Yifan , Li Dehui , Fan Huanfang 
Published: December 2021

Abstract
To systematically evaluate the correlation between the traditional Chinese medicine (TCM) syndromes of lung cancer and the imaging manifestations of CT. Computer search of CNKI, Cochrane Library, PubMed, Springer, CBM, VIP, Wanfang database, Baidu library and other major databases. Collect the relevant literature on the TCM syndromes of lung cancer and CT imaging manifestation since the database was built until September 1, 2021. Two researchers collected literature and evaluated the quality of the literature, conducted data mining on the literature, and used the computer Revman 5.3 software to conduct a Meta-analysis of the included literature. The results showed that the phlegm dampness type lobular sign was higher than the burr sign, and there was no significant difference between vacuole sign and cavity sign; In Qi-Yin deficiency type, lobular sign was higher than burr sign, vacuole sign was higher than cavity sign; In Qi stagnation blood stasis type, lobular sign is higher than burr sign. The CT lobular sign of lung cancer are mainly phlegm dampness type, Qi-Yin deficiency type and Qi stagnation blood stasis type. Vacuole sign is mainly Qi-Yin deficiency type. Burr sign and cavity sign are less in the above three types. In this study, the combination of computer and meta-analysis technology has promoted the development of lung cancer micro-differentiation theory and assisted in improving the treatment level of lung cancer clinical syndrome differentiation.
Research and Analysis on Technical Problems of New Energy Vehicles in China Based on Big Data and Artificial Intelligence Algorithm
Authors: Gong Kunyao 
Published: December 2021

Abstract
In recent years, with the increasing problems of environmental pollution and energy security, energy-saving emission reduction and green low-carbon have become the focus of public opinion. Meanwhile, the New Energy Vehicles (NEVs) industry is beginning to rise gradually. Although NEV technology has made significant progress in some key technologies in China, there are still some technical bottlenecks restricting the popularization of NEVs. In order to understand the research hotspots and trends in the technology area of NEV quickly, objectively and intuitively, this paper studies the published literature on technical direction of NEVS in CNKI Database for the past ten years, which is from 2011 to 2020. According to the method of keyword analysis of the bibliometric, all the keywords in the literature are statistically classified as the research object, research method and research hotspot. Therefore, considering the development and the bottleneck of the NEVs industry in China, this paper sums up the hotspots and difficult points on technical problems of NEVs in China for the past ten years, and then establishes the problem method database of the NEV technology in China. It could provide a basis for the development of the NEV technology disciplines, and then contribute to facilitating the solution of the core technology in the field of NEVs. With the advent of intelligent and networked vehicles, artificial intelligence algorithm is applied to the energy management and control system of energy vehicles, so as to make common progress in the industrial production technology of new energy vehicles and artificial intelligence production technology. Big data has brought new challenges and opportunities to automobile Internet marketing. Using the big data system, Internet companies can accurately lock users, timely formulate and adjust refined marketing strategies according to the in-depth mining of big data, and timely quantitatively evaluate each effect. Big data provides technical basic support for Internet precision marketing in the automotive industry. With the big data system, brand marketing and effect marketing can be more accurate, and the tracking of effects can be more specific, so as to greatly reduce cost waste and improve user conversion rate.
Third-order ladder operators, generalized Okamoto and exceptional orthogonal polynomials
Authors: Hussin V , Marquette I , Zelaya K 
Published: December 2021

Abstract
We extend and generalize the construction of Sturm–Liouville problems for a family of Hamiltonians constrained to fulfill a third-order shape-invariance condition and focusing on the ‘−2x/3’ hierarchy of solutions to the fourth Painlevé transcendent. Such a construction has been previously addressed in the literature for some particular cases but we realize it here in the most general case. The corresponding potential in the Hamiltonian operator is a rationally extended oscillator defined in terms of the conventional Okamoto polynomials, from which we identify three different zero-modes constructed in terms of the generalized Okamoto polynomials. The third-order ladder operators of the system reveal that the complete set of eigenfunctions is decomposed as a union of three disjoint sequences of solutions, generated from a set of three-term recurrence relations. We also identify a link between the eigenfunctions of the Hamiltonian operator and a special family of exceptional Hermite polynomial.
Direct ink write multi-material printing of PDMS-BTO composites with MWCNT electrodes for flexible force sensors
Authors: Renteria Anabel , Balcorta Victor H , Marquez Cory , Rodriguez Aaron A , Renteria-Marquez Ivan , Regis Jaime , Wilburn Bethany , Patterson Steven , Espalin David , Tseng Tzu-Liang (Bill) , Lin Yirong 
Published: December 2021

Abstract
With recent advances of additive manufacturing technology, direct ink write (DIW) printing has allowed to incorporate multi-material printing of various materials with freedom of design and complex geometric shapes to complete functional sensors in a one-step fabrication. This paper introduces the use of DIW 3D printing of polydimethylsiloxane (PDMS) with barium titanate (BTO) filler as stretchable composites with tunable piezoelectric properties that can be used for force sensors applications. To improve the bonding between stretchable piezoelectric composites and electrodes, multi-walled carbon nanotubes was included in the fabrication of electrodes at a fixed ratio of 11 wt. %. The alignment of the BTO dipoles was achieved through corona poling method, which applies an electric charge on the surface layer of the functional material, aligning the dipoles in the desired direction and thus gaining the piezoelectricity. Different BTO mixing ratios (10–50 wt. %) were evaluated in order to obtain tunable piezoelectric properties and compare the sensitivity with respect their elastic properties. Tensile testing and piezoelectric testing were carried out to characterize mechanical and piezoelectric properties. Results showed that fabricated PDMS with 50 wt. % BTO gave the highest piezoelectric coefficient (d
33) of 11.5 pC N−1 and with an output voltage of 385 mV under compression loading of >200 lbF. This demonstrates feasibility of using multi-material DIW printing to fabricate piezoelectric force sensors with integrated electrodes in one-step without compromising the flexibility of the material.