bluuebunny/crossref_metadata_2025 huggingface dataset:
Future Directions: Analyzing Health Disparities Related to Maternal Hypertensive Disorders
Authors: Harris Margaret , Henke Colette , Hearst Mary , Campbell Katherine
Published: August 2020

Hypertensive disorders of pregnancy complicate up to 10% of pregnancies worldwide, constituting one of the most significant causes of maternal morbidity and mortality. Hypertensive disorders, specifically gestational hypertension, chronic hypertension, and preeclampsia, throughout pregnancy are contributors to the top causes of maternal mortality in the United States. Diagnosis of hypertensive disorders throughout pregnancy is challenging, with many disorders often remaining unrecognized or poorly managed during and after pregnancy. Moreover, the research has identified a strong link between the prevalence of maternal hypertensive disorders and racial and ethnic disparities. Factors that influence the prevalence of maternal hypertensive disorders among racially and ethnically diverse women include maternal age, level of education, United States-born status, nonmetropolitan residence, prepregnancy obesity, excess weight gain during pregnancy, and gestational diabetes. Examination of the factors that increase the risk for maternal hypertensive disorders along with the current interventions utilized to manage hypertensive disorders will assist in the identification of gaps in prevention and treatment strategies and implications for future practice. Specific focus will be placed on disparities among racially and ethnically diverse women that increase the risk for maternal hypertensive disorders. This review will serve to promote the development of interventions and strategies that better address and prevent hypertensive disorders throughout a pregnant woman’s continuum of care.
Effect of Prehospital Epinephrine on Outcomes of Out-of-Hospital Cardiac Arrest: A Bayesian Network Approach
Authors: Kim Joonghee , Kim Yu Jin , Han Sangsoo , Choi Han Joo , Moon Hyungjun , Kim Giwoon
Published: August 2020

Background. The benefit of prehospital epinephrine in out-of-hospital cardiac arrest (OHCA) was shown in a recent large placebo-controlled trial. However, placebo-controlled studies cannot identify the nonpharmacologic influences on concurrent or downstream events that might modify the main effect positively or negatively. We sought to identify the real-world effect of epinephrine from a clinical registry using Bayesian network with time-sequence constraints. Methods. We analyzed a prospective regional registry of OHCA where a prehospital advanced life support (ALS) protocol named “Smart ALS (SALS)” was gradually implemented from July 2015 to December 2016. Using Bayesian network, a causal structure was estimated. The effect of epinephrine and SALS program was modelled based on the structure using extended Cox-regression and logistic regression, respectively. Results. Among 4324 patients, SALS was applied to 2351 (54.4%) and epinephrine was administered in 1644 (38.0%). Epinephrine was associated with faster ROSC rate in nonshockable rhythm (HR: 2.02, 6.94, and 7.43; 95% CI: 1.08–3.78, 4.15–11.61, and 2.92–18.91, respectively, for 1–10, 11–20, and >20 minutes) while it was associated with slower rate up to 20 minutes in shockable rhythm (HR: 0.40, 0.50, and 2.20; 95% CI: 0.21–0.76, 0.32–0.77, and 0.76–6.33). SALS was associated with increased prehospital ROSC and neurologic recovery in noncardiac etiology (HR: 5.36 and 2.05; 95% CI: 3.48–8.24 and 1.40–3.01, respectively, for nonshockable and shockable rhythm). Conclusions. Epinephrine was associated with faster ROSC rate in nonshockable rhythm but slower rate in shockable rhythm up to 20 minutes. SALS was associated with improved prehospital ROSC and neurologic recovery in noncardiac etiology.
A Novel Hydrogel Based on Renewable Materials for Agricultural Application
Authors: Durpekova Silvie , Filatova Kateryna , Cisar Jaroslav , Ronzova Alena , Kutalkova Erika , Sedlarik Vladimir
Published: August 2020

This study details the design and characterization of a new, biodegradable, and renewable whey/cellulose-based hydrogel (i.e., agricultural hydrogel). This was formulated from cellulose derivatives (carboxymethylcellulose (CMC) and hydroxyethylcellulose (HEC)) and acid whey cross-linked with citric acid, with the aim to obtain an agricultural product with a high swelling capacity to uphold the quality of soil and conserve water resources. With regard to the swelling behaviour of the prepared hydrogels, the authors initially assessed the swelling ratio and capacity for water uptake. Evaluating the chemical structure of the hydrogel and its thermal and viscoelastic properties involved performing Fourier transform infrared spectroscopy, differential scanning colorimetry, thermal gravimetric analysis, and rheological measurement of the hydrogel films. According to preliminary results, sufficient swelling capacity and stiffness were observed in a hydrogel prepared with 3% CMC and HEC, cross-linked with 5% citric acid. Moreover, the kinetics of water uptake revealed a promising capacity that was sustainable after 5 drying and swelling cycles. The results confirmed that the stability of the hydrogel was enhanced by the presence of the citric acid. As a consequence, it is necessary to utilize an appropriate cross-linking concentration and abide by certain conditions to ensure the swelling properties of the prepared hydrogel are sufficient. Further investigation of the topic, especially in relation to applications in soil, could confirm if the whey-cellulose-based hydrogel is actually suitable for agricultural use, thereby contributing to the advancement of sustainable arable farming.
Plasma and Cellular Forms of Fibronectin as Prognostic Markers in Sepsis
Authors: Lemańska-Perek Anna , Krzyżanowska-Gołąb Dorota , Skalec Tomasz , Adamik Barbara
Published: August 2020

Background. There is a pressing need for specific prognostic markers that could be used to monitor the severity of sepsis. The aims of our study were to investigate changes in the expression of different molecular forms of fibronectin in sepsis and to assess their relationship to the clinical severity and mortality of patients.Material and Methods. Forms of fibronectin: plasma (pFN), cellular (EDA-FN), FN-fibrin complexes, and fibronectin fragments were analyzed in 71 sepsis patients (survivors and nonsurvivors) and in the control by ELISA and immunoblotting.Results. The baseline pFN concentration of patients with sepsis was significantly lower than in the control (133.0 mg/L vs. 231.2 mg/L) (P<0.001), and in nonsurvivors, it was lower than in survivors (106.0 mg/L vs. 152.8 mg/L) (P=0.004). The baseline EDA-FN was significantly elevated in both sepsis groups (survivors: 6.7 mg/L; nonsurvivors: 9.4 mg/L) compared to the control (1.4 mg/L) (P<0.001). It should be noted that among patients with more severe sepsis, the EDA-FN level was higher in nonsurvivors than in survivors. Furthermore, molecular FN-fibrin complexes as well as FN fragments occurred much more frequently in nonsurvivors than in survivors.Conclusion. The study showed that in sepsis, changes in plasmatic and cellular form of fibronectin were associated with the severity of sepsis and may be useful predictors of outcome.
Superhydrophobic Hair-Like Nanowire Membrane for the Highly Efficient Separation of Oil/Water Mixtures
Authors: Fang Xinzuo , Liu Yufan , Lei Sheng , Ou Junfei
Published: August 2020

Water pollution caused by oil leakage and oily wastewater has become a serious environmental problem. Therefore, it is important to develop an efficient material to remove oil from water. Given the cost and efficiency, the membrane with superhydrophobicity is the most used material for the separation of oil/water mixtures. However, many works have been done through modification with a fluorinated reagent, causing high cost and damage to the environment. In this work, a simple and fast two-step method is employed to achieve a superhydrophobic hair-like nanowire membrane. Through the alkali-assisted oxidation process and modification with nonfluorinated low surface energy chemical, the so-obtained membrane (denoted as SHM), with the water contact angle of about 164°, exhibits excellent separation efficiency for binary mixtures of water and oils (toluene, hexane, gasoline, and so on). Meantime, this membrane also exhibits excellent durability and reusability in the long-term separation process, indicating its great potential for practical application in the future.
Design and Development of a Flexible, Plug-and-Play, Cost-Effective Tool for on-Field Evaluation of Gas Sensors
Authors: Suriano Domenico , Cassano Gennaro , Penza Michele
Published: August 2020

Atmospheric pollution is one of the biggest concerns for public health. Air quality monitoring is currently performed by expensive and cumbersome monitoring stations. For this reason, they are sparse, and therefore, inadequate to provide enough accurate information on the personal exposure to pollutant gases. The current worldwide trend to address this issue consists in the use of low-cost small gas sensors, already available on the market, with a wide range of costs and performances. However, the performance of these sensors is heavily affected by the environmental conditions of the specific location used for their deployment. For this reason, it is of fundamental importance to test them in real-world scenarios. Field evaluation of sensor performance could be a challenging task because, on the one hand, they have heterogeneous output signals, and on the other hand, there is no widely shared evaluation protocol. The SentinAir system has been designed and developed to facilitate this task. It can carry out performance evaluations for any type of sensor thanks to its configurable and adaptable sensing capability, multiple wireless sensor network compatibility, flexibility, and usability. In order to evaluate SentinAir capabilities and functionalities, the performances of CO2, NO2, and O3 sensors were tested in real-world scenarios against reference instruments. To the best of our knowledge, there is no previous study providing information about the performance of SP-61 (O3 sensor), IRC-A1 (CO2 sensor), and TDS5008 (CO2 sensor) achieved during on-field tests. On the contrary, results obtained by OXB431 (O3 sensor) and NO2B43F (NO2 sensor) are consistent with the ones shown in previous studies carried out in similar conditions. During validation tests, we have found R2=0.507 for the best performing NO2 sensor, and R2=0.668 for the best O3 sensor. Concerning the indoor experiment, the best CO2 sensor performance showed an excellent R2=0.995. In conclusion, the effectiveness of this tool in evaluating the performance of heterogeneous gas sensors in different real-world scenarios has been demonstrated. Therefore, we anticipate that the use of SentinAir will facilitate researchers to carry out these challenging tasks.
Neuroprotective Effects of the Sonic Hedgehog Signaling Pathway in Ischemic Injury through Promotion of Synaptic and Neuronal Health
Authors: Yin Sen , Bai Xuemei , Xin Danqing , Li Tingting , Chu Xili , Ke Hongfei , Han Min , Chen Wenqiang , Li Xingang , Wang Zhen
Published: August 2020

Cerebral ischemia is a common cerebrovascular condition which often induces neuronal apoptosis, leading to brain damage. The sonic hedgehog (Shh) signaling pathway has been reported to be involved in ischemic stroke, but the underlying mechanisms have not been fully elucidated. In the present study, we demonstrated that expressions of Shh, Ptch, and Gli-1 were significantly downregulated at 24 h following oxygen-glucose deprivation (OGD) injury in neurons in vitro, effects which were associated with increasing numbers of apoptotic cells and reactive oxygen species generation. In addition, expressions of synaptic proteins (neuroligin and neurexin) were significantly downregulated at 8 h following OGD, also associated with concomitant neuronal apoptosis. Treatment with purmorphamine, a Shh agonist, increased Gli-1 in the nucleus of neurons and protected against OGD injury, whereas the Shh inhibitor, cyclopamine, produced the opposite effects. Activation of Shh signals promoted CREB and Akt phosphorylation; upregulated the expressions of BDNF, neuroligin, and neurexin; and decreased NF-κB phosphorylation following OGD. Notably, this activation of Shh signals was accompanied by improved neurobehavioral responses along with attenuations in edema and apoptosis at 48 h postischemic insult in rats. Taken together, these results demonstrate that activation of the Shh signaling pathway played a neuroprotective role in response to ischemic exposure via promotion of synaptic and neuronal health.
A Fissile Ripple Spreading Algorithm to Solve Time-Dependent Vehicle Routing Problem via Coevolutionary Path Optimization
Authors: Xu Wen , Li JiaJun
Published: August 2020

The time-dependent vehicle routing problems have lately received great attention for logistics companies due to their crucial roles in reducing the time and economic costs, as well as fuel consumption and carbon emissions. However, the dynamic routing environment and traffic congestions have made it challenging to make the actual travelling trajectory optimal during the delivery process. To overcome this challenge, this study proposed an unconventional path optimization approach, fissile ripple spreading algorithm (FRSA), which is based on the advanced structure of coevolutionary path optimization (CEPO). The objective of the proposed model is to minimize the travelling time and path length of the vehicle, which are the popular indicators in path optimization. Some significant factors usually ignored in other research are considered in this study, such as congestion evolution, routing environment dynamics, signal control, and the complicated correlation between delivery sequence and the shortest path. The effectiveness of the proposed approach was demonstrated well in two sets of simulated experiments. The results prove that the proposed FRSA can scientifically find out the optimal delivery trajectory in a single run via global research, effectively avoid traffic congestion, and decrease the total delivery costs. This finding paves a new way to explore a promising methodology for addressing the delivery sequence and the shortest path problems at the same time. This study can provide theoretical support for the practical application in logistics delivery.
Physarum-Inspired Autonomous Optimized Routing Protocol for Coal Mine MANET
Authors: Jiang Haifeng , Liu Xiaoxiao , Xiao Shuo , Tang Chaogang , Chen Wei
Published: August 2020

Mobile Ad Hoc Network (MANET) is suitable for complex environment communication in coal mine. The processes of nutrient flux transfer and path choice in Physarum networks are similar to data transmission and routing decision in MANET. In this paper, we use a Physarum optimization model to design Physarum-inspired autonomous optimized routing (PIAOR) protocol to adapt to the dynamic network topology in underground mine. PIAOR introduces the status of MANET into the Poisson equation in the Physarum model, selects reasonable parameters to represent the transmission performance of the network, and uses the differential evolution equation of the Physarum model to evolve the parameters. PIAOR has achieved the distributed routing decision by automatically reconstructing the optimal routing path, which has reduced the algorithm complexity. Based on NS2, simulation experiments are performed to evaluate the performance of PIAOR, and the results are compared with GPSR, PIMAR, and P-IRP routing algorithms. The experimental results show that the routing path selected by PIAOR is better than that selected by the other three protocols in the performance of average end-to-end delay, delivery ratio, and throughput. The balance of energy consumption and network load is reached, and the network lifetime is effectively prolonged when using the PIAOR protocol.
A New Image Classification Approach via Improved MobileNet Models with Local Receptive Field Expansion in Shallow Layers
Authors: Wang Wei , Hu Yiyang , Zou Ting , Liu Hongmei , Wang Jin , Wang Xin
Published: August 2020

Because deep neural networks (DNNs) are both memory-intensive and computation-intensive, they are difficult to apply to embedded systems with limited hardware resources. Therefore, DNN models need to be compressed and accelerated. By applying depthwise separable convolutions, MobileNet can decrease the number of parameters and computational complexity with less loss of classification precision. Based on MobileNet, 3 improved MobileNet models with local receptive field expansion in shallow layers, also called Dilated-MobileNet (Dilated Convolution MobileNet) models, are proposed, in which dilated convolutions are introduced into a specific convolutional layer of the MobileNet model. Without increasing the number of parameters, dilated convolutions are used to increase the receptive field of the convolution filters to obtain better classification accuracy. The experiments were performed on the Caltech-101, Caltech-256, and Tubingen animals with attribute datasets, respectively. The results show that Dilated-MobileNets can obtain up to 2% higher classification accuracy than MobileNet.
Light: An Alternative Method for Physical Control of Postharvest Rotting Caused by Fungi of Citrus Fruit
Authors: Kahramanoğlu İbrahim , Nisar Muhammad Farrukh , Chen Chuying , Usanmaz Serhat , Chen Jinyin , Wan Chunpeng
Published: August 2020

Solar light has fundamental roles in vast chemical, biochemical, and physical process in biosphere and hence been declared as “source of life.” Solar light is further classified into a broad range of electromagnetic waves, and each region in the solar spectrum bears its unique actions in the universe or biosphere. Since centuries, solar light is believed as a potent source of killing pathogens causing postharvest losses on food products as well as human skin diseases. Citrus fruit crops are widely produced and consumed across the world, but due to their higher juicy contents, Penicillium italicum (blue mold) and Penicillium digitatum (green mold) make their entry to decay fruits and cause approximately 80% and 30% fruit losses, respectively. Agrochemicals or synthetic fungicides are highly efficient to control these postharvest fungal pathogens but have certain health concerns due to toxic environmental residues. Therefore, the scientific community is ever looking for some physical ways to eradicate such postharvest fungal pathogens and reduce the yield losses along with maintaining the public health concerns. This review article presents and discusses existing available information about the positive and negative impacts of different spectrums of solar light exposure on the postharvest storage of citrus fruits, especially to check citrus postharvest rotting caused by Penicillium italicum (blue mold) and Penicillium digitatum (green mold). Moreover, a special focus shall be paid to blue light (390–500 nm), which efficiently reduces the decay of fruits, while keeping the host tissues/cells healthy with no known cytotoxicity, killing the fungal pathogen probably by ferroptosis, but indepth knowledge is scanty. The study defines how to develop commercial applications of light in the postharvest citrus industry.
Fault Diagnosis of High-Power Tractor Engine Based on Competitive Multiswarm Cooperative Particle Swarm Optimizer Algorithm
Authors: Xiao Maohua , Wang Weichen , Wang Kaixin , Zhang Wei , Zhang Hengtong
Published: August 2020

With the rapid development of high-power tractor, the fault diagnosis of high-power tractor has become more and more important for ensuring the operating safety and efficiency. PSO is an iterative optimization evolutionary algorithm, which can iterate through different particles to find the optimal solution. However, there is only one population in the standard PSO algorithm, and the information exchange between the populations is relatively single, which can easily lead to the stagnation of the development of the population. In this paper, due to high-power tractor diesel engine fault complexity, fault correlation, and multifault concurrency, a multigroup coevolution particle swarm optimization BP neural network for diesel engine fault diagnosis method was proposed. First, the USB-CAN device was used to collect data of 8 items of the diesel engine under five different working conditions, and the data was parsed through the SAE J1939 protocol; then, the BP neural network was reconstructed, and a competitive multiswarm cooperative particle swarm optimizer algorithm (COM-MCPSO) was used to optimize its structure and weights. Finally, the data of optimized neural network under five different fault conditions show that, compared with BP neural network and PSO optimized BP neural network, the fault diagnosis of COM-MCPSO optimized BP neural network not only improves the network training speed, but also enhances generalization ability and improves recognition accuracy.
A Decoupling and Bidirectional Resampling Method for Multilabel Classification of Imbalanced Data with Label Concurrence
Authors: Zhou Shuyue , Li Xiaobo , Dong Yihong , Xu Hao
Published: August 2020

Label imbalance is one of the characteristics of multilabel data, and imbalanced data seriously affects the performance of the classifiers. In multilabel classification, resampling methods are mostly used to deal with imbalanced problems. Existing resampling methods balance the data by either undersampling or oversampling, which causes overfitting and information loss. Resampling has a significant impact on the minority labels. Furthermore, the high concurrency of majority labels and minority labels in many instances also affects the performance of classification. In this study, we proposed a bidirectional resampling method to decouple multilabel datasets. On one hand, the concurrency of labels can be reduced by setting termination conditions for decoupling, and on the other hand, the loss of instance information and overfitting can be alleviated by combining oversampling and undersampling. By measuring the minority labels of the instances, the instances that have less impact on minority labels are selected to resample. The number of resampling is limited to keep the original distribution of the data during the resampling phase. The experiments on seven benchmark multilabel datasets have proved the effectiveness of the algorithm, especially on datasets with high concurrency of majority labels and minority labels.
A Bandwidth Statistical Multiplexing and Control Method for Satellite Broadcasting
Authors: Wang Yingqiang , Nian Zhaohua , Liu Chang , Han Wei , Lin Maowei
Published: August 2020

In the field of satellite data broadcasting, the management quality of data broadcasting bandwidth is directly related to the throughput of the broadcasting system and plays an important role in the performance of satellites. In this paper, for the sun-synchronous orbit meteorological satellite broadcasting which has the conventional product files and emergency information, a broadcast bandwidth statistical multiplexing and control method is designed for bandwidth management. It can be used for the management of broadcasting between regular products and emergency information, as well as internal broadcasting among regular products. This paper is the first to apply common multiplexing of PID and channel mode (CMPCM) to satellite broadcasting. The test verified that the broadcast channel of the parameters and the broadcast schedule management channel resources achieved statistical multiplexing of bandwidth, ratio of channel management functions, and data broadcast control. Broadcasting occupation ratio (BOR) and broadcasting file error ratio (BER) improved significantly. This is significant for improving the efficiency of satellite uplink broadcasting.
Hearing Phenotypes of Patients with Hearing Loss Homozygous for the GJB2 c.235delc Mutation
Authors: Guo Chang , Huang Sha-Sha , Yuan Yong-Yi , Zhou Ying , Wang Ning , Kang Dong-Yang , Yang Su-Yan , Zhang Xin , Gao Xue , Dai Pu
Published: August 2020

Hereditary hearing loss is characterized by remarkable phenotypic heterogeneity. Patients with the same pathogenic mutations may exhibit various hearing loss phenotypes. In the Chinese population, the c.235delC mutation is the most common pathogenic mutation of GJB2 and is closely related to hereditary recessive hearing loss. Here, we investigated the hearing phenotypes of patients with hearing loss associated with the homozygous c.235delC mutation, paying special attention to asymmetric interaural hearing loss. A total of 244 patients with the GJB2 c.235delC homozygous mutation encountered from 2007 to 2015 were enrolled. The severity of hearing loss was scaled with the American Speech-Language-Hearing Association (ASHA). Auditory phenotypes were analyzed, and three types of interaural asymmetry were defined based on audiograms: Type A (asymmetry of hearing loss severity), Type B (asymmetry of audiogram shape), and Type C (Type A plus Type B). Of the 488 ears (244 cases) examined, 71.93% (351) presented with profound hearing loss, 14.34% (70) with severe hearing loss, and 9.43% (46) with moderate to severe hearing loss. The most common audiogram shapes were descending (31.15%) and flat (24.18%). A total of 156 (63.93%) of the 244 patients exhibited asymmetric interaural hearing loss in terms of severity and/or audiogram shape. Type A was evident in 14 of these cases, Type B in 106, and Type C in 36. In addition, 211 of 312 ears (67.63%) in the interaural hearing asymmetry group showed profound hearing loss, and 59 (18.91%) exhibited severe hearing loss, with the most common audiogram shapes being flat (27.88%) and descending (22.12%). By contrast, in the interaural hearing symmetry group, profound hearing loss was observed in 140 ears (79.55%), and the most common audiograms were descending (46.59%) and residual (21.59%). Hearing loss associated with the GJB2 c.235delC homozygous mutation shows diverse phenotypes, and a considerable proportion of patients show bilateral hearing loss asymmetry.
Modified Decision Tree Technique for Ransomware Detection at Runtime through API Calls
Authors: Ullah Faizan , Javaid Qaisar , Salam Abdu , Ahmad Masood , Sarwar Nadeem , Shah Dilawar , Abrar Muhammad
Published: August 2020

Ransomware (RW) is a distinctive variety of malware that encrypts the files or locks the user’s system by keeping and taking their files hostage, which leads to huge financial losses to users. In this article, we propose a new model that extracts the novel features from the RW dataset and performs classification of the RW and benign files. The proposed model can detect a large number of RW from various families at runtime and scan the network, registry activities, and file system throughout the execution. API-call series was reutilized to represent the behavior-based features of RW. The technique extracts fourteen-feature vector at runtime and analyzes it by applying online machine learning algorithms to predict the RW. To validate the effectiveness and scalability, we test 78550 recent malign and benign RW and compare with the random forest and AdaBoost, and the testing accuracy is extended at 99.56%.
Food Safety Risk Assessment of γ-Butyrolactone Transformation into Dangerous γ-Hydroxybutyric Acid in Beverages by Quantitative 13C-NMR Technique
Authors: Jin Shaoming , Ning Xiao , Cao Jin , Wang Yaonan
Published: August 2020

Food safety remains a matter of great concern in most countries and the composition in food is crucial to food safety. It is very important to make sense of the quality and change of food ingredients. In this research, the change of γ-butyrolactone (GBL), one kind of food additive in beverage, had been evaluated by nuclear magnetic resonance (NMR) technique. The 1H-NMR results of seven beverages covering various kinds with spiked GBL indicated that GBL was transformed into dangerous γ-hydroxybutyric acid (GHB) in six popular beverages under certain conditions which could happen during transportation and storage. Further results of quantitative 13C-NMR showed that pH and temperature were two key factors affecting the transforming degree of GBL to GHB. Lower pH and higher temperature will increase the degree of transformation. GHB was a neurotransmitter on the chemical control list, which was absolutely forbidden to be added to food. This nondestructive NMR detecting technology which did not need the complex pretreatment method to directly determine food ingredients can be useful for identifying the risk of food safety from the changes of food composition during transport and storage.
Structural Optimization of the Aircraft NACA Inlet Based on BP Neural Networks and Genetic Algorithms
Authors: Li Zhimao , Chen Changdong , Pei Houju , Kong Benben
Published: August 2020

With the development of the increasing demand for cooling air in cabin and electronic components on aircraft, it urges to present an energy-efficient optimum method for the ram air inlet system. A ram air performance evaluation method is proposed, and the main structural parameters can be extended to a certain type of aircraft. The influence of structural parameters on the ram air performance is studied, and a database for the performance is generated. A new method of integrating the BP neural networks and genetic algorithm is used for structure optimization and is proven effective. Moreover, the optimum result of the structure of the NACA ram air inlet system is deduced. Results show that (1) the optimization algorithm is efficient with less prediction error of the mass flow rate and fuel penalty. The average relative error of the mass flow rate is 1.37%, and the average relative error of the fuel penalty is 1.41% in the full samples. (2) Predicted deviation analysis shows very little difference between optimized and unoptimized design. The relative error of the mass flow rate is 0.080% while that of the fuel penalty is 0.083%. The accuracy of the proposed optimization method is proven. (3) The mass flow rate after optimization is increased to 2.506 kg/s, and the fuel penalty is decreased by 74.595 Et kg. The BP neural networks and genetic algorithms are studied to optimize the design of the ram air inlet system. It is proven to be a novel approach, and the efficiency can be highly improved.
Impact of Node Density on the QoS Parameters of Routing Protocols in Opportunistic Networks for Smart Spaces
Authors: Garg Puneet , Dixit Ashutosh , Sethi Preeti , Pinheiro Plácido Rogerio
Published: August 2020

The need and importance of Smart Spaces have been potentially realized by the researchers due to its applicability in the current lifestyle. Opportunistic network, a successor of mobile ad hoc networks and a budding technology of network, is a best-suited technology for implementing Smart Spaces due to its wide range of applications in real-life scenarios ranging from building smart cities to interplanetary communication. There are numerous routing protocols which are available in opportunistic network, each having their pros and cons; however, no research till the time of listing has been done which can quantitatively demonstrate the maximum performance of these protocols and standardize the comparison of opportunistic routing protocols which has been a major cause of ambiguous performance evaluation studies. The work here presents a categorical view of the opportunistic routing protocol family and thereby compares and contrasts the various simulators suited for their simulation. Thereafter, the most popular protocols (selecting at least one protocol from each category) are compared based on node density on as many as 8 standard performance metrics using ONE simulator to observe their scalability, realism, and comparability. The work concludes by presenting the merits and demerits of each of the protocols discussed as well as specifying the best routing protocol among all the available protocols for Smart Spaces with maximum output. It is believed that the results achieved by the implemented methodology will help future researchers to choose appropriate routing protocol to delve into their research under different scenarios.
Evaluation of Salt-Induced Damage to Aged Wood of Historical Wooden Buildings
Authors: Mi Xiaochen , Li Tieying , Wang Jinping , Hu Yongfeng
Published: August 2020

Salt is a common cause of damage to building materials used in cultural and historical buildings. The damage to aged wood in historical wooden buildings has not been extensively studied, resulting in the need for a more detailed analysis. In this work, Yingxian Wooden Pagoda, a typical historical wooden structure, was taken as the research object. Multichemical analyses were conducted to evaluate and understand the salt-induced damage to the aged wood using a scanning electron microscope equipped with an energy-dispersive X-ray spectrometer, sulphur K-edge X-ray absorption near-edge structure spectroscopy, X-ray fluorescence spectroscopy, X-ray powder diffraction, and attenuated total reflectance fourier transformed infrared spectroscopy. The results showed the presence of invasive salt crystallisations and ions in the aged samples. The source of these invasive elements was deduced by identifying the type, amount, and valency of the elements; they were found to be derived from environmental factors such as acid rain and atmospheric pollutant. The unique damage mechanism and route induced by salt in historical buildings made of wood were summarised; the damage was attributed to the accumulation of sulphate salt causing hydrolysis of the carbohydrates and salt crystallisation resulting in mechanical damage. This interdisciplinary study is significant for decision making in studies related to the preservation and evaluation of historical wooden buildings.
Evolutionary Game Models on Multiagent Collaborative Mechanism in Responsible Innovation
Authors: Yang Kun , Wang Wan , Hu Bin
Published: August 2020

Innovation is a game process; in particular, the behavior among multiple agents in responsible innovation is susceptible to the influence of benefits, risks, responsibilities, and other factors, resulting in unstable collaborative relationships. Therefore, this paper constructs a tripartite evolutionary game model including the government, enterprises, and the public, combined with system dynamics modeling to simulate and analyze the tripartite behavior strategy and sensitivity to relevant exogenous variables. The study shows that the tripartite game eventually converges to a stable state of the government active supervision, enterprises making responsible innovation, and the public’s positive participation. The positive participation of the public drives rapidly the game to a steady state, while the behavioral strategies of enterprises are more susceptible to the behavior of the government. Supervision cost, penalty amount, and value compensation are the most critical factors influencing the change of the corresponding agents’ behavior strategy, and the final strategic stability of tripartite is affected by multiple exogenous variables.
The Regenerative Potential of Facial Nerve Motoneurons following Chronic Axotomy in Rats
Authors: Ni Yusu , Chen Diyan , Jiang Yi , Qiu Danhong , Li Wen , Li Huawei
Published: August 2020

Background. The precise mechanisms of nerve regeneration remain unclear. The potential of facial nerve regeneration and probable mechanisms involved following chronic facial nerve injury should be further studied. Methods. Adult male Wistar rats were used to model either (i) facial nerve injury (axotomy) or (ii) reinjury (chronic axotomy followed by a second axotomy within 5 months). The rats were housed in the animal facility of the Eye and ENT Hospital of Shanghai Medical School, Fudan University (Shanghai, China). Expression of Shh (sonic hedgehog) and growth-associated protein 43 (GAP43, a neuronal marker) was detected in bilateral facial nuclei using reverse transcriptase PCR, western blotting analysis, and immunohistochemistry. The number of surviving motoneurons was quantified, and facial nerve regeneration was examined using transmission electron microscopy. Results. Reinjury of the facial nerve 12 weeks after the first axotomy resulted in upregulation of GAP43 mRNA and protein expression in neurons ipsilateral to the axotomy; immunohistochemistry revealed that Shh expression was higher compared with control side facial nuclei at the same time point. GAP43 expression subsequently decreased. Conclusion. The greatest regeneration potential of the facial nerve occurred within 5 months following chronic axotomy in rats, and regeneration may involve the Shh signaling pathway.
Developing a Data Model of Indoor Points of Interest to Support Location-Based Services
Authors: Claridades Alexis Richard C. , Lee Jiyeong
Published: August 2020

Focus on indoor spatial applications has been rising with the growing interest in indoor spaces. Along with the widespread use of mobile devices and the internet, it has increased demands for indoor location-based services (LBS), demanding more efficient representation and management of indoor spatial data. Indoor points of interest (Indoor POI) data, representing both spaces and facilities located indoors, provide the infrastructure for these services. These datasets are vital in delivering timely and accurate information to users, such as in cases of managing indoor facilities. However, even though there are studies that explore its use across applications and efforts exerted towards the standardization of the data model, most POI development studies have focused on the outdoors and remain underdeveloped in the indoors. In this paper, we propose a spatial-temporal Indoor POI data model to provide direction for the establishment of indoor POI data and to address limitations in currently available data specifications. By exploring how different Indoor POIs are from its outdoor counterparts, particularly on extending its outdoor counterparts’ functions on searching, sharing, and labeling, we describe the data model and its components using the Unified Modeling Language (UML). We perform an SQL-based query experiment to demonstrate the potential use of the data model using sample data.
Impact Factors on Posterior Modified Transfacet Debridement for Thoracic Spinal Tuberculosis Basing on Regression and Classification Analysis
Authors: Chen Xiaoping , Lin Jiamin , Huang Han , Huang Yunpeng
Published: August 2020

Posterior transfacet approach has been proved to be a safe and effective access to treat thoracic disc herniation. However, the influencing factors of posterior modified transarticular debridement for thoracic tuberculosis have not been reported in the clinical literature. From 2009 to 2014, 37 patients with TST underwent a posterior modified transfacet debridement, interbody fusion following posterior instrumentation, under the cover of 18 months of antituberculosis chemotherapy. The patients were evaluated preoperatively and postoperatively in terms of Frankel Grade, visual analog scale (VAS) pain score, kyphotic Cobb angle, and bone fusion. Blood loss (positive correlation) and focal debridement (positive correlation) could affect operative time. Operative time (positive correlation) could affect blood loss. While, age (positive correlation), PostE (negative correlation), and T_FocalDebridement (positive correlation) could affect bone fusion. The accuracy of naive bayes classifier model is 86.11%. Our preliminary results show that blood loss and focal debridement could affect operative time; operative time could affect blood loss; age, PostE, and T_FocalDebridement could affect bone fusion; the naive Bayes classifier model can predict the KirkaldyWillis accurately.
Medications for Hypertension Change the Secretome Profile from Marrow Stromal Cells and Peripheral Blood Monocytes
Authors: Satani Nikunj , Giridhar Kaavya , Cai Chunyan , Wewior Natalia , Norris Dominique D. , Aronowski Jaroslaw , Savitz Sean I.
Published: August 2020

Marrow stromal cells (MSCs) are in different stages of clinical trials for stroke patients. MSCs are proposed to promote recovery through the release of secretomes that modulate the function of beneficial immune cells. The majority of stroke patients have comorbidities including hypertension, for which they are prescribed antihypertensive medications that might affect the function of MSCs, when they are administered in stroke patients. Here, we studied the effects of common antihypertensive medications on the secretomes of human MSCs and their modulation of human monocytes (Mo) derived from stroke patients. MTT assay was used to assess the proliferation of MSCs after they were exposed to increased levels of antihypertensive medications. MSCs were exposed to the following medications: atenolol, captopril, and losartan. Monocytes were isolated from stroke patients with NIHSS ranging from 11 to 20 and from healthy controls. MSC-Mo cocultures were established, and a secretome profile was analyzed using the Magpix Multiplex cytokine array from Luminex technology. The linear mixed-effect model was used for statistical analysis. All analyses were performed using SAS 9.4, and p values less than 0.05 were considered significant. At clinically relevant levels, there was no change in MSC proliferation after exposure to atenolol, captopril, or losartan. Atenolol increased IL-1RA in stroke-Mo and decreased IL-8 secretion from MSCs indicating an anti-inflammatory effect of atenolol on secretomes of these cells. Captopril increased IL-8 from stroke-Mo and increased IL-6, IL-8, and MCP-1 secretions from MSCs. Captopril also increased IL-6 secretion from cocultures of stroke-Mo and MSCs indicating a strong proinflammatory effect on MSCs and their interaction with Mo. Atenolol increased the secretion of IL-8 and MCP-1 while captopril increased the secretion of IL-6 and MCP-1 from MSCs. Losartan decreased the release of IL-6 from MSCs. Losartan reduced MCP-1 and TNF-α from stroke-Mo and reduced IL-8 from cocultures of stroke-Mo and MSCs. Our results show that antihypertensive medications such as atenolol, captopril, and losartan, at concentrations comparable to doses prescribed for patients hospitalized for acute stroke, modulate the secretome profile of MSCs and their modulatory effects on target immune cells. Our results suggest that stroke trials involving the use of intravenous MSCs should consider the effect of these antihypertensive drugs administered to stroke patients.
Guardian Map Approach to Feasible Range of Static Stability Margin of Hypersonic Flight Vehicles with Input Saturation
Authors: Lei Hao , Chen Boyi , Liu Yanbin , Lu Yuping
Published: August 2020

Static stability margin is a critical parameter in flight control design. The feasible range of it must cover the uncertainty through the flight. To reasonably identify the feasible range of static stability margin in advance, an approach based on guardian maps is proposed for flight control of hypersonic flight vehicles with input saturation. First, the model of hypersonic flight vehicle (HFV) is established as a parametric plant. Then, flying quality requirements for the closed-loop system are formulated as inequality constraints using guardian maps. Moreover, by using linear matrix inequality, the saturation of elevators is taken into account in the integrated control of attitude control. The prescribed minimum of static stability margin that ensures the flying quality of hypersonic flight vehicles with input saturation is obtained. Furthermore, from the prospective of integrated control, it is shown that the feasible range of static stability margin can be enlarged by changing aerodynamic characteristics. The effectiveness of the proposed approach is validated by numerical simulation.
Association of Serum FAM19A5 with Cognitive Impairment in Vascular Dementia
Authors: Li Juan , Li Shoulin , Song Yihong , Zhou Wei , Zhu Xiaohao , Xu Suo , Ma Yihong , Zhu Chunlin
Published: August 2020

Objective. Family with sequence similarity 19 member A5 (FAM19A5), a novel chemokine-like peptide, is a secreted protein mainly expressed in the brain. FAM19A5 was recently found to be involved in a variety of neurological diseases; however, its correlation with vascular dementia (VaD) remains unclear. The aim of the study is to explore the association between serum FAM19A5 and cognitive impairment in subjects with VaD. Method. 136 VaD subjects and 81 normal controls were recruited in the study. Their demographic and clinical baseline data were collected on admission. All subjects received Mini-Mental State Examination (MMSE) evaluation, which was used to test their cognitive functions. A sandwich enzyme-linked immunosorbent assay (ELISA) was applied to detect the serum levels of FAM19A5. Results. No significant differences were found between the two groups regarding the demographic and clinical baseline data (p>0.05). The serum FAM19A5 levels were significantly higher compared to normal controls (p<0.001). The Spearman correlation analysis indicated that serum FAM19A5 levels and MMSE scores have a significant negative correlation in VaD patients (r=−0.414, <0.001). Further multiple regression analysis indicated that serum FAM19A5 levels were independent risk predictors for cognitive functions in VaD (β=0.419, p=0.031). Conclusion. The serum FAM19A5 level of VaD patients is significantly increased, which may serve as a biomarker to predict cognitive function of VaD.
Estimation of Disease Transmission in Multimodal Transportation Networks
Authors: Zheng Yu
Published: August 2020

Mathematical models are important methods in estimating epidemiological patterns of diseases and predicting the consequences of the spread of diseases. Investigation of risk factors of transportation modes and control of transportation exposures will help prevent disease transmission in the transportation system and protect people’s health. In this paper, a multimodal traffic distribution model is established to estimate the spreading of virus. The analysis is based on the empirical evidence learned from the real transportation network which connects Wuhan with other cities. We consider five mainstream travel modes, namely, auto mode, high-speed railway mode, common railway mode, coach mode, and flight mode. Logit model of economics is used to predict the distribution of trips and the corresponding diseases. The effectiveness of the model is verified with big data of the distribution of COVID-19 virus. We also conduct model-based tests to analyze the role of lockdown on different travel modes. Furthermore, sensitivity analysis is implemented, the results of which assist in policy-making for containing infection transmission through traffic.
Mobile Users’ Self-Disclosure Behaviour on WeChat: Application of Social Cognitive Theory
Authors: Ma Liang , Ding Xiaoyan , Zhang Xin , Zhang Ge
Published: August 2020

One of the most challenging issues confronting social media operators is how to increase users’ activity and self-disclosure behaviour. However, more and more users are lowering their disclosures on social media, such as WeChat in China. Using social cognitive theory as a starting point while utilizing mobile instant messaging software WeChat as an example, this paper studies the dynamics that influence users’ self-disclosure behaviour on WeChat from two aspects: individual factors and environment factors. A structural equation model is used to verify a conceptual model. The results show that, firstly, mobile users’ self-disclosure behaviour on WeChat can be affected by both individual factors and environment factors. Specifically, individual factors, such as privacy concerns, negatively affect users’ self-disclosure behaviour, while environmental factors, such as social influences, positively affect users’ self-disclosure behaviour. More importantly, the research points to significant differences in self-disclosure behaviour between mobile users of different genders and ages. As such, the conclusions of this paper should provide key information for optimized operation of WeChat and other mobile information systems.