bluuebunny/crossref_metadata_2025 huggingface dataset:
Examination of the association between state tobacco control spending and the demand for electronic cigarettes by high school students
Authors: Tauras John , Diaz Megan C , Schillo Barbara , Vallone Donna
Published: December 2021

Background

While much is known about the influence of tobacco control spending on the demand for conventional cigarettes, little is known about the effects of tobacco control spending on the demand for electronic cigarettes (e-cigarettes). This study provides the first evidence on the association between state tobacco control spending and high school student vaping in the USA.

Methods

We used data from the 2015 through 2019 National Youth Risk Behavior Surveys to estimate vaping prevalence and vaping intensity demand equations. We employed logistic regressions to estimate the vaping prevalence equations and generalised linear models with log-link and gamma distribution to estimate the vaping intensity equations.

Results

We found evidence that funding for state tobacco control programmes had a significant negative association with both vaping prevalence and vaping intensity among high school students in the USA. Our results indicate that a 50% increase in state spending on tobacco control during the time of the surveys would have been associated with a 7.46% lower high school student vaping prevalence rate than what was observed.

Conclusions

There has been a dramatic increase in e-cigarette use by adolescents and young adults in the USA. The rapid rise in e-cigarette use has been a significant source of public policy concern for many states. The results of this study strongly suggest that increased spending on tobacco control programmes will reduce the number of high school students who vape and will decrease the number of days vaping products are used by high school students. These findings should be extremely valuable to policymakers interested in curbing the youth vaping epidemic in the USA.
Two-year optical site characterization for the Pacific Ocean Neutrino Experiment (P-ONE) in the Cascadia Basin
Authors: Bailly Nicolai , Bedard Jeannette , Böhmer Michael , Bosma Jeff , Brussow Dirk , Cheng Jonathan , Clark Ken , Croteau Beckey , Danninger Matthias , De Leo Fabio , Deis Nathan , Ens Matthew , Fox Rowan , Fruck Christian , Gärtner Andreas , Gernhäuser Roman , Ghuman Dilraj , Grant Darren , He Helen , Henningsen Felix , Holzapfel Kilian , Hotte Ryan , Jenkyns Reyna , Johnson Hamish , Katil Akanksha , Kopper Claudio , Krauss Carsten B. , Kulin Ian , Leismüller Klaus , Leys Sally , Lin Tony , Macoun Paul , Man Matthew , McElroy Thomas , Meighen-Berger Stephan , Michel Jan , Moore Roger , Morley Mike , Papp Laszlo , Pirenne Benoit , Qiu Tom , Rankin Mark , Rea Immacolata Carmen , Resconi Elisa , Round Adrian , Ruskey Albert , Rutley Ryan , Spannfellner Christian , Stacho Jakub , Timmerman Ross , Tomlin Meghan , Tradewell Matt , Traxler Michael , Uganecz Matt , Wagner Seann , Yañez Juan Pablo , Zheng Yinsong
Published: December 2021

The STRings for Absorption length in Water (STRAW) are the first in a series of pathfinders for the Pacific Ocean Neutrino Experiment (P-ONE), a future large-scale neutrino telescope in the north-eastern Pacific Ocean. STRAW consists of two $$150\,\mathrm {m}$$

150

m

long mooring lines instrumented with optical emitters and detectors. The pathfinder is designed to measure the attenuation length of the water and perform a long-term assessment of the optical background at the future P-ONE site. After 2 years of continuous operation, measurements from STRAW show an optical attenuation length of about 28 m at $$450\,\mathrm {nm}$$

450

nm

. Additionally, the data allow a study of the ambient undersea background. The overall optical environment reported here is comparable to other deep-water neutrino telescopes and qualifies the site for the deployment of P-ONE.
Challenging problems of particle physics and astrophysics. The preface
Authors: Khlopov Maxim Yu.
Published: December 2021

The preface to the special issue of IJMPD “Challenging Problems of Particle physics and Astrophysics” briefly reviews some new ideas in the development of modern Astrophysics, Cosmology, Particle and Astroparticle physics inspired by discussions at the Fifth International Conference on Particle Physics and Astrophysics (ICPPA2020).
Reconstruction of Phase Space and Eigenvalue Decomposition from a Biological Time Series: A Malayalam Speech Signal Case Study
Authors: Muraleedharan K. M. , Bibish Kumar K. T. , Kumar Sunil , John R. K. Sunil
Published: December 2021

Our objective is to describe the speech production system from a non-linear physiological system perspective and reconstruct the attractor from the experimental speech data. Mutual information method is utilized to find out the time delay for embedding. The False Nearest Neighbour (FNN) method and Principal Component Analysis (PCA) method are used for optimizing the embedding dimension of time series. The time series obtained from the typical non-linear systems, Lorenz system and Rössler system, is used to standardize the methods and the Malayalam speech vowel time series of both genders of different age groups, sampled at three sampling frequencies (16[Formula: see text]kHz, 32[Formula: see text]kHz, 44.1[Formula: see text]kHz), are taken for analysis. It was observed that time delay varies from sample to sample and, it ought to be better to figure out the time delay with the embedding dimension analysis. The embedding dimension is shown to be independent of gender, age and sampling frequency and can be projected as five. Hence a five-dimensional hyperspace will probably be adequate for reconstructing attractor of speech time series.
Adaptive Deep Incremental Learning — Assisted Missing Data Imputation for Streaming Data
Authors: Syavasya C. V. S. R. , Lakshmi M. A.
Published: December 2021

With the rapid explosion of the data streams from the applications, ensuring accurate data analysis is essential for effective real-time decision making. Nowadays, data stream applications often confront the missing values that affect the performance of the classification models. Several imputation models have adopted the deep learning algorithms for estimating the missing values; however, the lack of parameter and structure tuning in classification, degrade the performance for data imputation. This work presents the missing data imputation model using the adaptive deep incremental learning algorithm for streaming applications. The proposed approach incorporates two main processes: enhancing the deep incremental learning algorithm and enhancing deep incremental learning-based imputation. Initially, the proposed approach focuses on tuning the learning rate with both the Adaptive Moment Estimation (Adam) along with Stochastic Gradient Descent (SGD) optimizers and tuning the hidden neurons. Secondly, the proposed approach applies the enhanced deep incremental learning algorithm to estimate the imputed values in two steps: (i) imputation process to predict the missing values based on the temporal-proximity and (ii) generation of complete IoT dataset by imputing the missing values from both the predicted values. The experimental outcomes illustrate that the proposed imputation model effectively transforms the incomplete dataset into a complete dataset with minimal error.
Improvement of Association Algorithm and Its Application in Audit Data Mining
Authors: Lu Haitao , Sivaparthipan C. B. , Antonidoss A.
Published: December 2021

Data mining has become a relatively modern platform for information retrieval. The efficient data mining techniques can increase the reliability and accuracy of internal auditing for the various community even while lowering audit risk. Existing audit data mining approaches lack significant identification of hidden connections and interactions in bid data platforms. Hence, this study extends the literature survey on the signification of audit data mining in multiple applications. This survey identifies the scope of improved association algorithms in audit data mining, a rule-based machine learning approach to determine the exciting relationship among variables in large audit datasets. Therefore, a Conceptual Framework of Improved Association Algorithm (CFiAA) and its application in audit data mining is proposed. This study examines the strengths and weaknesses of the proposed CFiAA in audit mining. The proposed model has been trained using an audit data set and validates with various audit datasets. Finally, this paper presents the comparative analysis of the proposal to show its highest performance related to existing models. Thus, CFiAA scores the performance ratio of 94.5%, accuracy ratio of 92.4%, an efficiency ratio of 92.5%, F1 measure of 91.8%, error rate 32.5%, prediction ratio of 93.7%, and the precision ratio of 92.5% compared to existing models.
Stability and Modal Conversion Phenomenon of Pipe-In-Pipe Structures with Arbitrary Boundary Conditions by Means of Green’s Functions
Authors: Chang Xueping , Fan Jinming , Han Duzheng , Chen Bo , Li Yinghui
Published: December 2021

In this paper, a closed-form frequency equation of the pipe-in-pipe (PIP) structure with arbitrary boundaries is obtained. The frequency equation is derived from Green’s function of the transverse forced vibration of the PIP structure and takes into account the effects of internal two-phase flow and axial pressure. The reliability of the method in this paper is proved by comparison with the published literature. In the numerical discussion part, the PIP structures with clamped-clamped, clamped-free, and elastic boundary conditions are used as examples to discuss. The effects of equivalent stiffness coefficient, internal flow velocity, and gas volume fraction on the stability of PIP structure are studied. The results show that the stability of the PIP structure is better than that of the single-pipe structure, and the greater the equivalent stiffness coefficient of the elastic layer, the higher the critical flow velocity of the structure. In addition, a modal conversion phenomenon existing in the PIP structure is discovered. There are different forms of modal conversion for different boundary conditions, and the modal conversion makes the order of instability of the PIP structure different from that of a single-pipe. The conclusion of this paper has positive significance for the dynamic research of PIP structure.
Yamabe and gradient Yamabe solitons on real hypersurfaces in the complex quadric
Authors: Chaubey Sudhakar K. , Lee Hyunjin , Suh Young Jin
Published: December 2021

In this paper, we give a complete classification of Yamabe solitons and gradient Yamabe solitons on real hypersurfaces in the complex quadric [Formula: see text]. In the following, as an application, we show a complete classification of quasi-Yamabe and gradient quasi-Yamabe solitons on Hopf real hypersurfaces in the complex quadric [Formula: see text].
International Norms, Policy Transfers and Energy Transition: Implications for Taiwan’s Development
Authors: CHENG FANG-TING
Published: December 2021

The development of renewable energy policies in Taiwan has been thoroughly discussed from political, economic, social, industrial and environmental perspectives. Energy policies, particularly those adopted by the United Nations (UN) and other international organizations, have influenced both (1) the decision-making process of energy policies such as action plans, programs and (2) the transition to renewable energies. This paper argues that the transfer of global environmental and energy policies serves as the mechanism behind Taiwan’s efforts to expand renewable energy production. These global policies have so far been practiced by international organizations through agreements designed to combat climate change, achieve sustainable development goals (SDGs), and reduce fossil fuel subsidies. This paper examines renewable energy policies and legislation in Taiwan through the lens of policy transfers, an area which has not been fully explored in previous research.
The long-time behavior of a stochastic SIR epidemic model with distributed delay and multidimensional Lévy jumps
Authors: Kiouach Driss , Sabbar Yassine
Published: December 2021

This paper reports novel theoretical and analytical results for a perturbed version of a SIR model with Gamma-distributed delay. Notably, our epidemic model is represented by Itô–Lévy stochastic differential equations in order to simulate sudden and unexpected external phenomena. By using some new and ameliorated mathematical approaches, we study the long-run characteristics of the perturbed delayed model. Within this scope, we give sufficient conditions for two interesting asymptotic properties: extinction and persistence of the epidemic. One of the most interesting results is that the dynamics of the stochastic model are closely related to the intensities of white noises and Lévy jumps, which can give us a good insight into the evolution of the epidemic in some unexpected situations. Our work complements the results of some previous investigations and provides a new approach to predict and analyze the dynamic behavior of epidemics with distributed delay. For illustrative purposes, numerical examples are presented for checking the theoretical study.
The Impact of Terrestrial Radiation on FPGAs in Data Centers
Authors: Keller Andrew M. , Wirthlin Michael J.
Published: December 2021

Field programmable gate arrays (FPGAs) are used in large numbers in data centers around the world. They are used for cloud computing and computer networking. The most common type of FPGA used in data centers are re-programmable SRAM-based FPGAs. These devices offer potential performance and power consumption savings. A single device also carries a small susceptibility to radiation-induced soft errors, which can lead to unexpected behavior. This article examines the impact of terrestrial radiation on FPGAs in data centers. Results from artificial fault injection and accelerated radiation testing on several data-center-like FPGA applications are compared. A new fault injection scheme provides results that are more similar to radiation testing. Silent data corruption (SDC) is the most commonly observed failure mode followed by FPGA unavailable and host unresponsive. A hypothetical deployment of 100,000 FPGAs in Denver, Colorado, will experience upsets in configuration memory every half-hour on average and SDC failures every 0.5–11 days on average.
ReuseTracker
: Fast Yet Accurate Multicore Reuse Distance Analyzer
Authors: Sasongko Muhammad Aditya , Chabbi Milind , Marzijarani Mandana Bagheri , Unat Didem
Published: December 2021

One widely used metric that measures data locality is
reuse distance
—the number of unique memory locations that are accessed between two consecutive accesses to a particular memory location. State-of-the-art techniques that measure reuse distance in parallel applications rely on simulators or binary instrumentation tools that incur large performance and memory overheads. Moreover, the existing sampling-based tools are limited to measuring reuse distances of a single thread and discard interactions among threads in multi-threaded programs. In this work, we propose
ReuseTracker
—a fast and accurate reuse distance analyzer that leverages existing hardware features in commodity CPUs.
ReuseTracker
is designed for multi-threaded programs and takes cache-coherence effects into account. By utilizing hardware features like performance monitoring units and debug registers,
ReuseTracker
can accurately profile reuse distance in parallel applications with much lower overheads than existing tools. It introduces only 2.9× runtime and 2.8× memory overheads. Our tool achieves 92% accuracy when verified against a newly developed configurable benchmark that can generate a variety of different reuse distance patterns. We demonstrate the tool’s functionality with two use-case scenarios using PARSEC, Rodinia, and Synchrobench benchmark suites where
ReuseTracker
guides code refactoring in these benchmarks by detecting spatial reuses in shared caches that are also false sharing and successfully predicts whether some benchmarks in these suites can benefit from adjacent cache line prefetch optimization.
Practical Frequency-Hiding Order-Preserving Encryption with Improved Update
Authors: Yang JiHye , Kim Kee Sung
Published: December 2021

Order-preserving encryption (OPE) that preserves the numerical ordering of plaintexts is one of the promising solutions of cloud security. In 2013, an ideally secure OPE, which reveals no additional information except for the order of underlying plaintexts, was proposed, along with the notion (mutable encryption) that ciphertexts can be changed. Unfortunately, even the ideally secure OPE can be vulnerable by inferring the underlying frequency of repeated plaintexts. To solve this problem, in 2015, Kerschbaum designed a frequency-hiding OPE (FH-OPE) scheme based on the notion of a randomized order under the strengthened security model. Later, Maffei et al. has shown that Kerschbaum’s model is imprecise, which means no such OPE scheme can exist. Moreover, they provided a new FH-OPE scheme under the corrected security model. However, their scheme requires the order information of all the encrypted plaintexts as an input; therefore, it causes relatively high overhead during encryption. In this work, we propose a more efficient FH-OPE based on Maffei et al.’ s security model and also present an improved update algorithm suitable for duplicate plaintexts.
Benchmark Problems for the Numerical Discretization of the Cahn–Hilliard Equation with a Source Term
Authors: Yoon Sungha , Lee Hyun Geun , Li Yibao , Lee Chaeyoung , Park Jintae , Kim Sangkwon , Kim Hyundong , Kim Junseok
Published: December 2021

In this paper, we present benchmark problems for the numerical discretization of the Cahn–Hilliard equation with a source term. If the source term includes an isotropic growth term, then initially circular and spherical shapes should grow with their original shapes. However, there is numerical anisotropic error and this error results in anisotropic evolutions. Therefore, it is essential to use isotropic space discretization in the simulation of growth phenomenon such as tumor growth. To test numerical discretization, we present two benchmark problems: one is the growth of a disk or a sphere and the other is the growth of a rotated ellipse or a rotated ellipsoid. The computational results show that the standard discrete Laplace operator has severe grid orientation dependence. However, the isotropic discrete Laplace operator generates good results.
Artificial Intelligence-Based Echocardiographic Left Atrial Volume Measurement with Pulmonary Vein Comparison
Authors: Zhu Mengyun , Fan Ximin , Liu Weijing , Shen Jianying , Chen Wei , Xu Yawei , Yu Xuejing
Published: December 2021

This paper combines echocardiographic signal processing and artificial intelligence technology to propose a deep neural network model adapted to echocardiographic signals to achieve left atrial volume measurement and automatic assessment of pulmonary veins efficiently and quickly. Based on the echocardiographic signal generation mechanism and detection method, an experimental scheme for the echocardiographic signal acquisition was designed. The echocardiographic signal data of healthy subjects were measured in four different experimental states, and a database of left atrial volume measurements and pulmonary veins was constructed. Combining the correspondence between ECG signals and echocardiographic signals in the time domain, a series of preprocessing such as denoising, feature point localization, and segmentation of the cardiac cycle was realized by wavelet transform and threshold method to complete the data collection. This paper proposes a comparative model based on artificial intelligence, adapts to the characteristics of one-dimensional time-series echocardiographic signals, automatically extracts the deep features of echocardiographic signals, effectively reduces the subjective influence of manual feature selection, and realizes the automatic classification and evaluation of human left atrial volume measurement and pulmonary veins under different states. The experimental results show that the proposed BP neural network model has good adaptability and classification performance in the tasks of LV volume measurement and pulmonary vein automatic classification evaluation and achieves an average test accuracy of over 96.58%. The average root-mean-square error percentage of signal compression is only 0.65% by extracting the coding features of the original echocardiographic signal through the convolutional autoencoder, which completes the signal compression with low loss. Comparing the training time and classification accuracy of the LSTM network with the original signal and encoded features, the experimental results show that the AI model can greatly reduce the model training time cost and achieve an average accuracy of 97.97% in the test set and increase the real-time performance of the left atrial volume measurement and pulmonary vein evaluation as well as the security of the data transmission process, which is very important for the comparison of left atrial volume measurement and pulmonary vein. It is of great practical importance to compare left atrial volume measurements with pulmonary veins.
Exercise Behavior Prediction and Injury Assessment Based on Swarm Intelligence Algorithm
Authors: Ding Ding , Jiang Jianqiong , Liu Changya
Published: December 2021

The biggest view of the whole world on science and technology and sports is that science and technology and sports both represent national strength. At present, the integration of sports and science and technology has not reached a certain height, especially in the prediction of sports behavior and injury assessment, and the investment in science and technology is still lacking. This leads to a high number of injuries caused by sports every year. However, swarm intelligence algorithm has made few breakthrough achievements in the past few years, and the combination of sports behavior and swarm intelligence algorithm can just solve this problem. It is very important to choose the algorithm for predicting and assessing sports behavior. We should choose an efficient algorithm with high stability, high convergence speed, and optimization ability. In this paper, the IPSGWO algorithm is proposed to realize this application. IPSGWO algorithm is based on the GWO algorithm, with appropriate strategies and ideas, to maximize the improvement. In this paper, the convergence curve of PSO, GWO, and IPSGWO is tested to determine whether the IPSGWO algorithm has more stable and higher performance, and the simulation experiment is used to determine whether the IPSGWO algorithm is suitable for prediction and injury assessment compared with the other two. From the experimental results, the IPSGWO algorithm does have higher performance; because of this, it is more accurate for prediction and injury assessment.
High-Capacity Real-Time Face Retrieval Recognition Algorithm Based on Task Scheduling Model for the Treatment Area of Hospital
Authors: Zhou Yi , Xia Weili
Published: December 2021

This paper presents an in-depth study of face detection, face feature extraction, and face classification from three important components of a high-capacity face recognition system for the treatment area of hospital and a study of a high-capacity real-time face retrieval and recognition algorithm for the treatment area of hospital based on a task scheduling model. Considering the real-time nature of our system, our face feature extraction network is modeled by DeepID, and the network is slightly improved by introducing a central loss verification signal to train a DeepID-like network model using central loss and use it to extract face features. To further investigate and optimize the schedulability analysis problem of the directed graph real-time task model, this paper proposes a rigorous and approximate response time analysis method for the directed graph real-time task model with an arbitrary time frame. Based on the theoretical results of the greatly additive algebra, it is shown that the coherent qualifying function is linearly periodic, i.e., the function can be represented by a finite nonperiodic part and an infinitely repeated periodic part, thus calculating the coherent qualifying function independent of the magnitude of the interval time. The algorithm for high-capacity real-time face retrieval and recognition in the treatment area of hospital based on the task scheduling model is further investigated, and a face database is established by using the PCA dimensionality reduction technique. Based on the internal architecture of the processor, image preprocessing and IP core packaging are implemented, and the hardware engineering of the high-capacity real-time face recognition system for hospital visits is built using the IP-based design concept. The performance tests of the face detection model and feature extraction network show that the face detection model has a significant reduction in false-positive rate, better fitting of border regression, and improved time performance. The face feature extraction network has no overfitting, and the features are highly discriminative with small feature extraction time consumption. The high-capacity real-time face recognition system for the treatment area of hospital combined with the optimized directed graph task scheduling model can approach 25 fps, which meets the real-time requirements, and the face recognition rate surpasses that of real people. It realizes the intelligence, self-help, and autonomy of medical services and satisfies the medical needs of users in all aspects.
A Review of Infectious Diseases Associated with Religious and Nonreligious Rituals
Authors: Gajurel Kiran , Deresinski Stan
Published: December 2021

Rituals are an integral part of human life but a wide range of rituals (both religious and non-religious), from self-flagellation to blood brotherhood to ritual sprinkling of holy water, have been associated with transmission of infections. These infections include angiostrongyliasis, anthrax, brucellosis, cholera, COVID-19, cutaneous larva migrans, Ebola, hepatitis viruses, herpes simplex virus, HIV, human T-cell leukemia virus (HTLV), kuru, Mycobacterium bovis, Naegleria fowleri meningoencephalitis, orf, rift valley fever, and sporotrichosis. Education and community engagement are important cornerstones in mitigating infectious risks associated with rituals.
[Retracted] Wireless Network Sensing of Urban Surface Water Environment Based on Clustering Algorithm
Authors: Zhao Qichao , Yang Xiufeng , Dong Xuxin , Li Huairui
Published: December 2021

To improve the wireless sensing image extraction technology of urban surface water environment, a regional FCM clustering method combined with water index was proposed in this paper. The normalized water index (NDWI) was obtained by calculating the fusion multispectral wireless sensing image. Through the combination with normalized water index, fuzzy clustering results were obtained by RFCM algorithm proposed in this paper. The optimal threshold was selected to defuzzify the fuzzy clustering results, and finally, the extraction results of urban surface water were obtained. The accuracy of the proposed algorithm was compared with that of the traditional surface water extraction algorithm. The experimental results showed that the size of different neighborhood regions affected the water extraction accuracy. In W city, the kappa coefficient of MFCM16 was 0.41% higher than that of MFCM8, and the overall classification accuracy of MFCM16 was 1.33% higher than that of MFCM. In G city area, the kappa coefficient of MFCM16 was 1.81% higher than that of MFCM8, and the overall classification accuracy of MFCM16 was 1.7% higher than that of MFCM. Comparing the RFCM algorithm with other algorithms, the RFCM algorithm obtained the best experimental results, to reduce the “salt‐and‐pepper phenomenon” effect.
[Retracted] Research on the Difficulties and Countermeasures of the Practical Teaching of Ideological and Political Theory Courses in Colleges and Universities Based on Wireless Communication and Artificial Intelligence Decision Support
Authors: Tang Chaozhen
Published: December 2021

The rapid development of wireless communication technology has caused the computing speed and performance of information terminals to increase exponentially. Artificial intelligence technology emerged in this context. As an efficient work system, artificial intelligence has been introduced into many areas of social life. Especially in the field of education, it has made outstanding contributions. At this stage, the conflict between Eastern and Western civilizations is intensifying. As the most active ideological group, college students have not yet formed a scientific understanding of the pros and cons of Eastern and Western civilizations, and it is easy for them to fall into confusion in this kind of ideological turmoil. This requires that the ideological and political education in our country’s colleges and universities effectively play a role, strengthen ideological guidance, and create a new system of practical teaching of college ideological and political theory courses under the background of wireless communication. Ideological and political education, as one of the courses with outstanding characteristics in our country’s university education courses, has a guiding role that cannot be ignored for university students. This paper uses a questionnaire survey method to conduct an online survey of 500 college students from 6 universities in Shanghai to obtain first‐hand information on the current ideological and political practice courses of Chinese universities and then sort out the emergence of artificial intelligence‐based decision support systems in China. The practical class encountered difficulties and explored strategies to alleviate this dilemma, hoping to provide a useful reference for the development of ideological and political teaching in China in the future.
Pectoralis Muscle Mass on Chest CT at Admission Predicts Prognosis in Patients with Pneumonia
Authors: Yokosuka Ryohsuke , Imai Ryosuke , Ro Shosei , Murakami Manabu , Okafuji Kohei , Kitamura Atsushi , Tomishima Yutaka , Jinta Torahiko , Nishimura Naoki , Tamura Tomohide , Takahashi Osamu
Published: December 2021

Background and Objectives. The concept of sarcopenia has been attracting attention in recent years, but its association with in-hospital mortality of patients with pneumonia is still unclear. Therefore, we investigated the relationship between pectoralis muscle mass on chest computed tomography (CT) and in-hospital mortality in patients with pneumonia. Methods. A retrospective cohort study was performed in patients aged 18 years or older with pneumonia who underwent chest CT within 24 hours of admission between April 2014 and March 2019. We measured the thickness, area, and volume of the pectoralis major and minor muscles at the level of the aortic arch. Factors associated with mortality were examined using logistic regression analysis. Results. A total of 483 patients (mean age 77 ± 14 years, 300 men (62%)) were included, and fifty-one patients (11%) died during admission. In univariate analysis, decreased thickness, area, and volume of the pectoralis major and minor muscles were associated with higher in-hospital mortality. Multivariate analysis with adjustment for age, gender, serum albumin, and A-DROP revealed that thinner pectoralis major and minor muscles were independent factors of poor prognosis (odds ratio: 0.878, 95% confidence interval (CI): 0.783–0.985,P=0.026and odds ratio: 0.842, 95% CI: 0.733–0.968,P=0.016, respectively). Approximately 25% of the patients died when the pectoralis minor muscle thickness was 5 mm or less, and no patients died when it was 15 mm or more. Conclusion. The pectoralis muscle mass may be an independent prognostic factor in hospitalized patients with pneumonia.
The Transmutation Logic of China University Science and Technology Innovation System since the Founding of the Communist Party of China One Hundred Years Ago: Three-Chain Perspectives Led by Party-Building
Authors: Liu Hongda , Yu Zhen , Zhang Jijian , Yao Pinbo
Published: December 2021

The university science and technology innovation system is an essential bridge between higher education and national innovation development. Since the founding of the Communist Party of China, the scientific and technological innovation system of Chinese universities has intermingled with the historical environment and internal and external factors and has gone through several stages of development from weak to strong and from fragile to solid. In this process, the Communist Party of China has always been firmly based on the central concept of people-oriented, using a forward-looking vision to develop the macro deployment of the university science and technology innovation system and finally using the combination of ideology and politics, the three-wide education throughout the sustainable development, and optimization of the system, returning to the “university” nature of the university science and technology innovation system, to achieve the fusion of the system and the Party-building development. To this end, the university science and technology system in the new era must continue to uphold the leadership of the Communist Party of China, draw on the power of the three chains led by the Party, inductively form contemporary inspiration from the logic of construction over the past century, and adapt to the complex and changing world situation of the future.
Analytical Solution of Composite Curved I-Beam considering Tangential Slip under Uniform Distributed Load
Authors: Qin Xu-Xi , Chen He-Ping , Wang Shu-Juan
Published: December 2021

An analytical solution of composite curved I-beam considering the partial interaction in tangential direction under uniform distributed load is obtained. Based on the Vlasov curved beam theory, the global balance condition of the problem has been obtained by means of the principle of virtual work; integrating this by parts, the governing system of differential equations and corresponding boundary conditions have been determined. Analytical expressions for the composite beam considering the partial interaction have been developed. In order to verify the validity and the accuracy of this study, the analytical solutions are presented and compared with other three FEM results using the space beam element and the shell element. The deflection and the tangential slip of the composite curved I-beam are investigated.
Analysis of Hydrogeochemical Characteristics of Tunnel Groundwater Based on Multivariate Statistical Technology
Authors: Peng Chen , Liu Yuanming , Chen Huiyu , Yuan Qiaowei , Chen Qingzhi , Mei Shilong , Wu Zhonghu
Published: December 2021

Following tunnel excavation, which is influenced by hydraulic fracturing and geological structure, a series of hydrochemical reactions occur in the karst aquifer, which has a significant impact on groundwater hydrology and the earth process. Based on five sets of 38 samples collected in the Tongzi Tunnel in 2020 and 2021, the main geochemical processes and water quality conditions of the karst aquifer system during tunnel construction were revealed by multivariate statistical analysis and graphical methods. The results showed that water-rock action is the main mechanism controlling groundwater chemistry in the study area; HCO3-, Ca2+, and Mg2+ are associated with the widely distributed carbonate rocks in the study area. SO42- is derived from gypsum and sulfate rocks and special strata, which are another important source of Ca2+. Sodium-containing silicates and reverse cation exchange as the causal mechanisms of Na+ whereas F- is derived from fluorite. According to the mineral saturation index calculations, the dissolution and precipitation of minerals such as alum, gypsum, calcite, dolomite, and salt rock have an important influence on the main chemical components in water. The 38 samples were subjected to cluster analysis, and the results could be classified into seven categories. The representative clusters 1, 3, and 5 were selected for principal component analysis. Clusters 1 and 5 of groundwater represent weathering, dissolution, and ion exchange of carbonate and sulfate rocks and are closely related to the lithologic limestone, limestone intercalated with carbonaceous mudstone, carbonaceous mudstone, and coal-measure strata in the aquifer. Cluster 3 is dominated by upper surface river water and characterizes the geochemistry in natural water bodies dominated by the dissolution of carbonate, sulfate, and salt rocks. Finally, groundwater quality is mostly found in Class IV, with NO3- and F- being the main contaminants in the water.
Volatile-Olfactory Profiles of cv. Arbequina Olive Oils Extracted without/with Olive Leaves Addition and Their Discrimination Using an Electronic Nose
Authors: Marx Ítala M. G. , Rodrigues Nuno , Veloso Ana C. A. , Casal Susana , Pereira José A. , Peres António M.
Published: December 2021

Oils from cv. Arbequina were industrially extracted together with olive leaves of cv. Arbequina or Santulhana (1%, w/w), and their olfactory and volatile profiles were compared to those extracted without leaves addition (control). The leaves incorporation resulted in green fruity oils with fresh herbs and cabbage olfactory notes, while control oils showed a ripe fruity sensation with banana, apple, and dry hay grass notes. In all oils, total volatile contents varied from 57.5 to 65.5 mg/kg (internal standard equivalents), being aldehydes followed by esters, hydrocarbons, and alcohols the most abundant classes. No differences in the number of volatiles were observed. The incorporation of cv. Arbequina or Santulhana leaves significantly reduced the total content of alcohols and esters (minus 37–56% and 10–13%, respectively). Contrary, cv. Arbequina leaves did not influence the total content of aldehydes or hydrocarbons, while cv. Santulhana leaves promoted a significant increase (plus 49 and 10%, respectively). Thus, a leaf-cultivar dependency was observed, tentatively attributed to enzymatic differences related to the lipoxygenase pathway. Olfactory or volatile profiles allowed the successful unsupervised differentiation of the three types of studied cv. Arbequina oils. Finally, a lab-made electronic nose was applied to allow the nondestructive discrimination of cv. Arbequina oils extracted with or without the incorporation of olive leaves (100% and 99 ± 5% of correct classifications for leave-one-out and repeated K-fold cross-validation variants), being a practical tool for ensuring the label correctness if future commercialization is envisaged. Moreover, this finding also strengthened that olive oils extracted with or without olive leaves incorporation possessed quite different olfactory patterns, which also depended on the cultivar of the olive leaves.
LASP1 Induces Epithelial-Mesenchymal Transition in Lung Cancer through the TGF-β1/Smad/Snail Pathway
Authors: Xue Qingming , Jiang Hong , Wang Jinjie , Wei Dongshan
Published: December 2021

Background. LIM and SH3 domain protein 1 (LASP1), highly expressed in a variety of tumors, is considered as a novel tumor metastasis biomarker. However, it is unknown which signaling pathway works and how the signal transduces into cell nucleus to drive tumor progression by LASP1. The aim of this study is to explore the essential role of LASP1 in TGF-β1-induced epithelial-mesenchymal transition (EMT) in lung cancer cells. Methods. The gene and protein levels of LASP-1 were successfully silenced or overexpressed by LASP-1 shRNA lentivirus or pcDNA in TGF-β1-treated lung cancer cell lines, respectively. Then, the cells were developed EMT by TGF-β1. The cell abilities of invasion, migration, and proliferation were measured using Transwell invasion assay, wound healing assay, and MTT assay, respectively. Western blotting was used to observe the protein levels of EMT-associated molecules, including N-cadherin, vimentin, and E-cadherin, and the key molecules in the TGF-β1/Smad/Snail signaling pathway, including pSmad2 and Smad2, pSmad3 and Smad3, and Smad7 in cell lysates, as well as Snail1, pSmad2, and pSmad3 in the nucleus. Results. TGF-β1 induced higher LASP1 expression. LASP1 silence and overexpression blunted or promoted cell invasion, migration, and proliferation upon TGF-β1 stimulation. LASP1 also regulated the expression of vimentin, N-cadherin, and E-cadherin in TGF-β1-treated cells. Activity of key Smad proteins (pSmad2 and pSmad3) and protein level of Smad7 were markedly regulated through LASP1. Furthermore, LASP1 affected the nuclear localizations of pSmad2, pSmad3, and Snail1. Conclusion. This study reveals that LASP1 regulates the TGF-β1/Smad/Snail signaling pathway and EMT markers and features, involving in key signal molecules and their nuclear levels. Therefore, LASP1 might be a drug target in lung cancer.
Shikonin Alleviates Endothelial Cell Injury Induced by ox-LDL via AMPK/Nrf2/HO-1 Signaling Pathway
Authors: Liu Shuang , Yan Wen , Hu Yanbing , Wu Huiying
Published: December 2021

The present study aimed to explore the effects of shikonin (SKN) on the damage of human venous endothelial cells (HUVECs) induced by ox-LDL and the underlying molecular mechanism. The HUVECs were randomly divided into six groups: control, ox-LDL, SKN + ox-LDL, SKN + ox-LDL + compound C, SKN + ox-LDL + si-Nrf2, and SKN + ox-LDL + si-HO-1. The MTT method was used to detect cell viability, flow cytometry was used to detect cell apoptosis and reactive oxygen species (ROS) levels, and Western blot was used to detect protein levels. Compared to the control group, the cell viability of the ox-LDL group decreased, the apoptosis rate increased, the level of cleaved caspase-3 was upregulated, and the level of Bcl-2 protein was downregulated. The level of TNF-α, IL-1β, IL-6, vascular cell adhesion molecule-1 (VCAM1), intercellular adhesion molecule-1 (ICAM1), and E-selectin (E-sel) was increased, ROS levels increased, and superoxide dismutase (SOD) level decreased. Moreover, the protein levels of p-AMPK, Nrf2, and HO-1 were decreased. Compared to the ox-LDL group, SKN treatment improves cell viability, alleviates cell apoptosis and oxidative stress injury, and upregulates the protein levels of p-AMPK, Nrf2, and HO-1. Compound C, si-Nrf2, and si-HO-1 administration inhibits the AMPK/Nrf2/HO-1 signaling pathway, increases ROS generation, and inhibits the antagonistic effect of SKN on ox-LDL-induced HUVECs damage. In summary, SKN suppressed ox-LDL-induced ROS production and improved cell viability and cell apoptosis via the AMPK/Nrf2/HO-1 pathway.
Safety of Five Tuina Manipulations in Rats with Deep Vein Thrombosis
Authors: Zhou Ying , Zhang Yumo , Zhang Xiaoyan , Chen Zhuo , Dong Jian , Yang Chao , Lv Taotao , Yu Tianyuan , Lu Mengqian
Published: December 2021

Objective. To study the effects of five tuina manipulations in rats with deep vein thrombosis (DVT) and to explore how to safely perform tuina in the treatment of thrombotic diseases. Methods. Seventy-two male Sprague-Dawley (SD) rats were randomly divided into the model, pointing manipulation, plucking manipulation, kneading manipulation, pushing manipulation, and pulling manipulation groups (n = 12). DVT model was established by incomplete ligation. The tuina intervention was started on the next day after modeling and applied once a day 10 times by the manipulation simulators. On the 3rd and 10th days after intervention, respectively, the effects of tuina on thrombosis were evaluated based on thrombus elasticity, blood coagulation, fibrinolytic function and blood rheology with the ultrasound elastography, four coagulation tests, enzyme linked immunosorbent assay (ELISA), and hemorheology tests. Results. In the pointing manipulation group, the strain rate ratio, 6-ketoprostaglandin F1α (6-Keto-PGF1α), and high shear rate were decreased, and the thromboxane B2 (TXB2) content was increased (

P
<
0.05

). In the plucking manipulation group, the D-dimer and 6-Keto-PGF1α contents were increased, prothrombin time (PT) was shortened, and activated partial thromboplastin time (APTT) was activated, and the high shear rate and plasma viscosity were decreased (

P
<
0.05

). In the kneading manipulation group, APTT was shortened, and 6-Keto-PGF1α, high shear rate, and plasma viscosity were decreased (

P
<
0.05

). In the pushing manipulation group, the strain rate ratio, low shear rate, and high shear rate were all decreased (

P
<
0.05

). In the pulling manipulation group, both the strain rate ratio and the low shear rate were decreased (

P
<
0.05

). The 6-Keto-PGF1α changes on the 3rd and 10th days after intervention were opposite in the pushing manipulation group and the pulling manipulation group (

P
<
0.05

). Conclusion. The pointing, pushing, and pulling manipulations seem to be safe in the early period of thrombosis, but the risk is likely to be elevated as the treatment course of intervention increases. The plucking and kneading manipulations potentially have certain risks in the treatment of DVT in rats.
A Study of Cloud-Based Remote Clinical Care Technology
Authors: Lin Bo , Huang Wei
Published: December 2021

This paper uses cloud computing to build and design remote clinical care technology, and the study refines the evaluation approach for the elements and builds an evaluation prototype for the strategy, uses service design theory to improve the design of the service part of the assistive system, summarizes the list of requirements based on system design and service design, and designs a service design prototype. Through design practice, the detailed design of the software interaction interface and the auxiliary product of the care assistance system based on the prototype are investigated. Based on the user perspective, the strategy of meeting user expectations and improving user information literacy is proposed; based on the social network perspective, the strategy of establishing a long-term mechanism for smart medical operation and improving the information interaction network environment is proposed; and based on the system service perspective, the strategy of optimizing the system function design and innovating the service model is proposed. Compared with the traditional written patient handover, the application of MNIS under cloud computing can significantly shorten the handover time of surgical patients, improve the standardized rate of surgical safety verification execution and the qualified rate of nursing documents, while the rate of standardized application of prophylactic antibiotics is also significantly higher than that of the control group. The questionnaire survey of nursing staff in the operating room showed that clinical nursing staff was generally satisfied with the clinical application of MNIS under cloud computing, with an average satisfaction score of 64.5 to 11.3, and an average score of 3.58 to 0.54 for each item. Among them, pre-application training of MNIS, departmental support for MNIS, and its ease of verification in surgical patients were the three main factors favoring the clinical application of MNIS in the operating room with cloud computing, while barriers to wireless network connectivity, inconvenient PDA input, and small screen size were the three main drawbacks affecting its application. The determined clinical evaluation index system of MNIS in the operating room is innovative, which not only includes clinical care indicators but also covers general hardware and software indicators, which can effectively reflect the practical application capability of mobile terminal clinical and user experience feelings, and the evaluation index system is comprehensive.