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Understanding human activity and behavior, particularly real-time understanding in video feeds, is one of the most active areas of research in Computer Vision (CV) and Artificial Intelligence (AI) nowadays. To advance the topic of integrating learning engagement research with university teaching practice, accurate and efficient assessment, and analysis of students’ classroom learning behavior engagement is very important. The recently proposed classroom behavior recognition algorithms have some limitations, such as the inability to quickly and accurately identify students’ classroom behaviors because they do not consider the motion information of students between consecutive frames. In recent years, action recognition algorithms based on Convolutional Neural Networks (CNN) have improved significantly. To address the limitations of existing algorithms, in this study, a 3D-CNN is selected as a network model for classroom student behavior recognition, which increases information multisourcing and classroom student localization with high accuracy and robustness. For better analysis of human behavior in videos, the 3D convolution extends the 2D convolution to the spatial–temporal domain. In the proposed system, first of all, a real-time picture stream of each student is obtained by combining real-time target detection and tracking. Then, a deep spatiotemporal residual CNN is used to learn the spatiotemporal features of each student’s behavior, so, as to achieve real-time recognition of classroom behaviors for multistudent targets in classroom teaching scenarios. To verify the effectiveness of the proposed model, different experiments are conducted using the labeled classroom behavior dataset. The experimental results demonstrate that the proposed model exhibits better performance in classroom behavior recognition. The accurate recognition of classroom behaviors can assist the teachers and students to understand the classroom learning situation and help to promote the development of smart classroom.

Zigbee is a very popular technology for Internet of things (IoT) networks mainly because of its low power consumption and low-cost features. It shares the unlicensed 2.4 GHz Industrial, Scientific, and Medical (ISM) radio band with other wireless networks such as Wi-Fi. Usually, Zigbee and Wi-Fi networks coexist in indoor environments for their respective applications. Hence, the coexistence introduces interference for both types of networks lowering the performance of the networks, but Zigbee suffers more significant performance losses because of its lower transmission power than Wi-Fi. Since the number of IoT devices is increasing at an unprecedented rate due to numerous emerging applications and thus making the indoor environments very populous, the peaceful coexistence between Zigbee and Wi-Fi networks in proximity becomes an important research study. For this purpose, this paper presents a comprehensive performance study of a Zigbee network in the presence of a Wi-Fi interference network in a real-life apartment-based indoor environment where Wi-Fi access points of dense neighbors exist. The experiments were done in a XBee module-based Zigbee network for measuring the received signal strength indicator (RSSI), packet drop rate (PDR), and loopback throughput with and without nearby Wi-Fi traffic introduced on purpose. Various networking parameters such as the operating channels, the distances between Zigbee devices and Wi-Fi devices, the transmit timeout of Zigbee packets, and the transmission power of the Zigbee transmitter have been used in the experiments to study the network performance. Our results show that in the deployment of IoT networks in a smart home, radio interference from neighboring homes would not be an important factor, but serious considerations may need to be taken inside the same home. The experimental observations of this paper can serve as a good reference study for Zigbee network deployments in real indoor environments, particularly when interference sources are present in proximity.

It is a challenge to maintain a safe and efficient tracking for multiple high-speed trains under the moving block operational mode. In this paper, a novel cooperative tracking control based on a consensus algorithm and artificial potential field theory is proposed to realize the train tracking within a distance range. A tunable artificial potential function is first designed to dynamically adjust the distance between adjacent high-speed trains with real-time train states. By regulating the parameters of the artificial potential function, the safety distance can be adjusted according to the required tolerance deviation of the actual distance. Under the proposed strategy, each high-speed train operates with the desired speed and tracks the preceding one with an adjustable distance range. Numerical train operational cases are investigated to illustrate the effectiveness of the proposed methods.

Earthquakes are one of the most frequent and inevitable natural disasters that occur on Earth. The most important seismic isolation device used in the isolation technology is the isolation bearing, but the limited structure of the isolation bearing is not suitable for the seismic isolation and shock absorption of smart transportation buildings. Therefore, it is very important to improve the new generation of seismic isolation structures with good seismic isolation effect, stable performance, and economical performance. It is very important to study the structural composition of the isolation bearing and the rigidity of the isolation structure. Isolation bearings are designed to resist and absorb the energy of seismic shocks by installing substructures in the structure. Active control involves installing sensors on the structure and its foundation to determine how the structure responds to seismic action. In this paper, based on the intelligent transportation of the sensor network, the reticulated shell structure of the isolation bearing is analyzed. By introducing the architecture and network layout of the sensor network, it is beneficial to obtain more accurate seismic data in complex and difficult terrain. This paper analyzes the technical principle of seismic isolation technology, which can effectively avoid the upward transmission of ground vibration by increasing the flexibility and proper damping of the system. From the experimental data of the seismic response of the ground-isolated structure to the near-field pulsation and far-field vibration, the total energy of the ground-isolated structure under the near-field pulsed ground motion is the largest. The seismic isolation effect of the reticulated shell structure of the seismic isolation bearing prevents more than 80% of the seismic energy from being transmitted to the superstructure.

Student classroom behavior performance is an important part of classroom teaching evaluation, and conducting student classroom behavior recognition is important for classroom teaching evaluation. The article proposes a deep learning-based student classroom behavior recognition method, which extracts the key information of the human skeleton from student behavior images and combines a 10-layer deep convolutional neural network (CNN-10) to recognize students’ classroom behavior. To verify the effectiveness of this method, the paper conducts a comparison experiment on the student classroom behavior dataset using CNN-10 and the student classroom behavior recognition method. The experimental results show that the student classroom behavior recognition method can effectively exclude the interference of irrelevant information such as students’ physique, dress, and classroom background, highlight the key effective information, and have higher recognition accuracy and generalization ability. Using the human skeleton and a deep learning-based student classroom behavior detection approach to identify students’ typical classroom behaviors might improve intelligent classroom teaching by reflecting students’ learning status in a timely and effective manner.

In recent years, the studies on fine-grained sedimentation mainly focus on the rock type, sedimentary environment, sedimentation, and sequence stratigraphy, while those on the relationship between sedimentary environment and lithofacies development are rare. However, a clear understanding on the relationship is of great significance to the muddy shale oil and gas exploration. This paper studied the muddy shale of semideep and deep lacustrine facies in the lower submember of Member 3 of Shahejie Formation in FY-1 Well, Dongying Sag, Bohai Bay Basin, East China. Based on geochemical data, the sedimentary environment media conditions and vertical changes of this submember were analyzed by means of core description, thin section authentication, X-ray diffraction (XRD), and other technologies, and the relationship between sedimentary environment and lithofacies development was discussed. The results show that this environment underwent three stages and is featured by cyclicity. From the bottom up, it experienced the semideep, deep, and deep/semideep waters under the relatively dry-cold/relatively warm-wet, warm-wet, and warm-wet/relatively warm-wet paleoclimates, respectively. Correspondingly, the paleoredox transited three stages from reducibility to high reducibility to high reducibility/reducibility; the paleosalinity changed from saline water to brackish water to brackish/saline water. Paleoproductivity was low/relatively high at the beginning, then became high, and finally relatively high. In this submember, the lithofacies primarily includes organic-rich mudstone, organic-rich lime mudstone, organic-rich lime-bearing mudstone, and organic-contained argillaceous limestone/lime mudstone. The sedimentary environment controls the mineral composition and content in the lithofacies and thus determines the lithofacies types. Meanwhile, the cyclicity of environmental change not only leads to that of the lithofacies development but also affects the positions of the lithofacies and its assemblages in sequence stratigraphic framework.

Multidrug resistance (MDR) is a critical reason for cancer chemotherapy failure. Babaodan (BBD) is a famous traditional Chinese patent medicine reported to have antigastric cancer activity. However, the roles and molecular mechanisms of the reversal of MDR of gastric cancer by BBD have not been well described until now. Therefore, the purpose of this study was to elucidate further the role of BBD in reversing the MDR of gastric cancer cells and its specific regulatory mechanism via in vitro experiments. To verify our results, MTT, Doxorubicin (DOX) staining, Rhodamin123 (Rho123) staining, DAPI staining, Annexin V-FITC, propidium iodide (PI), Cyto-ID, and western blot assays were performed. To determine whether BBD triggers apoptosis and autophagy through the PI3K/AKT/mTOR signaling, we also applied 3-methyladenine (3-MA), chloroquine (CQ), and 740Y-P (an activator of PI3K). The results showed that BBD reversed the MDR and induced apoptosis and autophagy of SGC7901/DDP cells. Pathway analyses suggested BBD inhibits PI3K/AKT/mTOR pathway activity and subsequent apoptosis-autophagy induction. Inhibition of autophagy with 3-MA and chloroquine (CQ) was performed to confirm that BBD promoted autophagy. PI3K agonist, 740Y-P, further verified BBD inhibition of PI3K/AKT/mTOR pathway activation. In conclusion, BBD may reverse the MDR of gastric cancer cells, induce apoptosis, and promote autophagy via inactivation of the PI3K/AKT/mTOR signaling pathway.

Aims. Blood clots play the primary role in neurological deficits after germinal matrix hemorrhage (GMH). Previous studies have shown a beneficial effect in blood clot clearance after hemorrhagic stroke. The purpose of this study is to investigate interleukin-19’s role in hematoma clearance after GMH and its underlying mechanism of IL-20R1/ERK/Nrf2 signaling pathway. Methods. A total of 240 Sprague-Dawley P7 rat pups were used. GMH was induced by intraparenchymal injection of bacterial collagenase. rIL-19 was administered intranasally 1 hour post-GMH. IL-20R1 CRISPR was administered intracerebroventricularly, or Nrf2 antagonist ML385 was administered intraperitoneally 48 hours and 1 hour before GMH induction, respectively. Neurobehavior, Western blot, immunohistochemistry, histology, and hemoglobin assay were used to evaluate treatment regiments in the short- and long-term. Results. Endogenous IL-19, IL-20R1, IL-20R2, and scavenger receptor CD163 were increased after GMH. rIL-19 treatment improved neurological deficits, reduced hematoma volume and hemoglobin content, reduced ventriculomegaly, and attenuated cortical thickness loss. Additionally, treatment increased ERK, Nrf2, and CD163 expression, whereas IL-20R1 CRISPR-knockdown plasmid and ML385 inhibited the effects of rIL-19 on CD163 expression. Conclusion. rIL-19 treatment improved hematoma clearance and attenuated neurological deficits induced by GMH, which was mediated through the upregulation of the IL-20R1/ERK/Nrf2 pathways. rIL-19 treatment may provide a promising therapeutic strategy for the GMH patient population.

Organic matter is the material basis for shales to generate hydrocarbon, as well as the main reservoir space and seepage channel for shale gas. When the thermal evolution degree is consistent, the organic carbon content in present shales is subject to the abundance of primitive sedimentary organic matter. Deep geofluids significantly influence the sedimentary organic matter’s enrichment, but the mechanism remains unclear. This paper is aimed at determining how hydrothermal and volcanic activities affected the enrichment of sedimentary organic matter by studying lower Cambrian shales in the lower Yangtze region and upper Ordovician-lower Silurian shales. Oxidation-reduction and biological productivity are used as indicators in the study. The result shows that hydrothermal or volcanic activities affected the enrichment of sedimentary organic matter by influencing climate changes and the nutrients’ sources on the waterbody’s surface and reducing water at the bottom. In the lower Cambrian shales of the Wangyinpu Formation in the lower Yangtze region, hydrothermal origin caused excess silicon. During the sedimentary period of the lower and middle-upper Wangyinpu Formation, vigorous hydrothermal activities increased the biological productivity on the waterbody’s surface and intensified the reducibility at the bottom of the waterbody, which enabled the rich sedimentary organic matter to be well preserved. During the sedimentary period of the lower upper Ordovician Wufeng Formation and the lower Silurian Longmaxi Formation in the upper Yangtze region, frequent volcanic activities caused high biological productivity on the waterbody surface and strong reducibility at the bottom of the waterbody. As a result, the abundant organic matter deposited from the water surface can be well preserved. During the sedimentary period of the upper Longmaxi Formation, volcanic activities died down gradually then disappeared, causing the biological productivity on the water surface to decrease. Besides, the small amount of organic matter deposited from the water surface was destroyed due to oxidation.

Reservoir pore space assessment is of great significance for petroleum exploration and production. However, it is difficult to describe the pore characteristics of deep-buried dolomite reservoirs with the traditional linear method because these rocks have undergone strong modification by tectonic activity and diagenesis and show significant pore space heterogeneity. In this study, 38 dolostone samples from 4 Cambrian formations of Tarim Basin in NW China were collected and 135 thin section images were analyzed. Multifractal theory was used for evaluation of pore space heterogeneity in deep-buried dolostone based on thin section image analysis. The physical parameters, pore structure parameters, and multifractal characteristic parameters were obtained from the digital images. Then, the relationships between lithology and these parameters were discussed. In addition, the pore structure was classified into four categories using K-means clustering analysis based on multifractal parameters. The results show that the multifractal phenomenon generally exists in the pore space of deep-buried dolomite and that multifractal analysis can be used to characterize the heterogeneity of pore space in deep-buried dolomite. For these samples, multifractal parameters, such as αmin, αmax, ΔαL, ΔαR, Δf, and AI, correlate strongly with porosity but only slightly with permeability. However, the parameter Δα, which is usually used to reveal heterogeneity, does not show an obvious link with petrophysical properties. Of dolomites with different fabrics, fine crystalline dolomite and medium crystalline dolomite show the best petrophysical properties and show significant differences in multifractal parameters compared to other dolomites. More accurate porosity estimations were obtained with the multifractal generalized fractal dimension, which provides a new method for porosity prediction. The various categories derived from the K-means clustering analysis of multifractal parameters show distinct differences in petrophysical properties. This proves that reservoir evaluation and pore structure classification can be accurately performed with the K-means clustering analysis method based on multifractal parameters of pore space in deep-buried dolomite reservoirs.

The abundance of organic matter in shales, which has a direct effect on the hydrocarbon generation potential of shales, is an important organic geochemical parameter for evaluating shale gas reservoirs. The total organic carbon content (TOC content) in shale is controlled by the abundance of original sedimentary organic matter. Therefore, it is very important to study the mechanism of organic matter enrichment in shale. In this paper, the Lower Cambrian marine shales from the Lower Yangtze region are selected as the research subject, most of which originate from a typical area well called Well JXY1. The degree of pyritization (DOP) is used to characterize the redox environment of the water body, while the P/Al ratio is used to analyze the biological productivity of paleoseawater. The paleosalinity of seawater is calculated via carbon and oxygen isotope analysis. In addition, the early Cambrian hydrothermal activities were studied by using core description; Si, Al, Fe, and Mn elemental analysis; and oxygen isotope calculations. The results show that during the early Cambrian Wangyinpu sedimentary period, the seawater was an anaerobic water body with H2S, and the oxygen concentration was approximately 0 mL/L. In the middle stages of the Wangyinpu sedimentary period, the water body had the strongest reducibility and the highest biological productivity. Moreover, the paleoocean in this period between the Yangtze plate and the Cathaysian plate was greatly affected by hydrothermal activities, with temperatures ranging from 90°C to 120°C. Active hydrothermal activities promoted high biological productivity and an anaerobic environment, both of which were conducive to the preservation and enrichment of organic matter, resulting in extremely high TOC content in the Wangyinpu shales (from 6.5% to approximately 16%).

The study aims to investigate the effects of the alcohol extract of Coreopsis tinctoria Nutt (AC) on diabetic nephropathy (DN) mice. A total of 30 db/db (DN) mice were divided into 3 groups, which were treated with AC (300 mg/kg/day), metformin (180 mg/kg/day), or saline by gavage for 10 weeks. Ten db/m mice treated with saline were used as normal control (NC group). Body weight (BW) and fasting blood glucose (FBG), HbA1c, 24 h urinary albumin excretion (UAE), and renal pathological fibrosis were analyzed. Expression of miR-192, miR-200b, and proteins in the PTEN/PI3K/AKT pathway was analyzed by qPCR or western blot. The DN mice had significantly higher BW, FBG, and 24 h UAE, as well as more severe pathological fibrosis when compared with NC. Treatment of AC could decrease BW, FBG, and 24 h UAE and alleviated kidney damage. Compared with the NC group, expressions of miR-192 and miR-200b were increased, whereas their target proteins (ZEB2 and PTEN) were reduced in the kidneys of DN mice, which further modulated the expression of their downstream proteins PI3K p85α, P-AKT, P-smad3, and COL4 α1; these proteins were increased in the kidneys of DN mice. In contrast, AC treatment reversed the expression changes of these proteins. These findings demonstrate that AC may protect the kidneys of DN mice by decreasing miR-192 and miR-200b, which could further regulate their target gene expression and modulate the activity of the PTEN/PI3K/AKT pathway to reduce the degree of renal fibrosis.

A tunnel passing below a metro station is taken as the object of our study, and a two-dimensional plane model is established to study the effects of their dynamic interaction to seismic excitation. Comparative analysis is used to obtain the influence law between the underground structures and on the soil. The results show that (1) the influence of the underground structure on the soil response is related to structure depth. The range of influence of the station structure on the surface is approximately five times the width of the station, and the surface response is obviously significant within this range. (2) The existence of the tunnel is conducive to reducing the acceleration of the column in the station. It increases the displacement difference between the stations, but the impact on the internal force of the station is not significant. (3) The influence of the station on the dynamic response of the tunnel is consistent with regard to tunnel acceleration, difference in displacement between the top and bottom of the tunnel, and internal force. The presence of the station will reduce the dynamic response of the tunnel.

Background. Qing Guang An Granule (QGAG), a Chinese patent medicine, has been used clinically to treat glaucoma for more than 20 years. Objective. To explore the possible mechanism of treatment of QGAG in glaucoma by using network pharmacology and molecular docking in this study. Methods. Active compounds and targets of each herb in QGAG were retrieved via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Glaucoma-related targets were acquired from OMIM and DisGeNET database. Key targets of QGAG against glaucoma were acquired by overlapping the above targets via the Venn diagram. Using the DAVID, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the key targets were performed. The docking process was performed using the AutoDock 4.2.6 and AutoDock Vina 1.1.2. Results. The 55 active compounds and 173 targets were obtained and constructed a compound-target network. The 20 key targets of QGAG in treating glaucoma were acquired, and these targets are involved in the apoptotic process, cellular response to hypoxia, negative regulation of cell growth, and ovarian follicle development. The main pathways are p53, HIF-1, PI3K-Akt, and neurotrophin signaling pathway. Conclusion. QGAG may exert a protective effect by acting on the optic nerve at a molecular and systemic level. This study can provide a certain basis for future researches on exploring the QGAG in treating glaucoma and provide new ideas for developing new drugs.

Mobile-edge cloud computing, an emerging and prospective computing paradigm, can facilitate the complex application execution on resource-constrained mobile devices by offloading computation-intensive tasks to the mobile-edge cloud server, which is usually deployed in close proximity to the wireless access point. However, in the multichannel wireless interference environment, the competition of mobile users for communication resources is not conducive to the energy efficiency of task offloading. Therefore, how to make the offloading decision for each mobile user and select its suitable channel become critical issues. In this paper, the problem of the offloading decision is formulated as a 0-1 nonlinear integer programming problem under the constraints of channel interference threshold and the time deadline. Through the classification and priority determination for the mobile devices, a reverse auction-based offloading method is proposed to solve this optimization problem for energy efficiency improvement. The proposed algorithm not only achieves the task offloading decision but also gives the facility of resource allocation. In the energy efficiency performance aspects, simulation results show the superiority of the proposed scheme.

Purpose. To investigate the characteristics of blood in nonsyndromic retinitis pigmentosa (RP) and reveal the pathogenesis of blood cells involved in blood stasis in RP.Design. This is a retrospective observational study.Methods. We collected vein blood from 101 cases of patients with nonsyndromic RP and 120 cases of normal individuals according to a single-blind study and used routine clinical examination to detect the indicators of blood. All the subjects were mainly from the central south of China. Data were analyzed statistically between the RP group and normal control.Results. The indicator of platelet distribution width (PDW) in patients with RP was higher than that in the normal group; the indicators of red blood cell (RBCs), hemoglobin (HGB), hematocrit (HCT), basophils (BASs), platelets (PLTs), and plateletcrit (PCT) in the RP group were lower than those in the normal control. The differences were statistically very significant between the RP group and normal group (p<0.01). There were no statistical differences in the other indicators between the RP and normal group.Conclusions. The changes in RBCs and PLTs in patients with RP implied that RP induces RBC aggregation and platelet activation, leading to blood stasis which in turn initiates more apoptosis.

Retinitis pigmentosa (RP) represents a clinically and genetically heterogeneous disease characterized by progressive photoreceptor loss. In recent years, research has been rarely made in blood flow affected in RP. The specific mechanism of blood flow affected in RP is not completely clear. A number of studies indicated that the decreased blood flow was related to RP. According to clinical observation and treatment experience, Chinese medicine considered that blood stasis runs throughout the RP disease progression, and the blood stasis corresponding to Chinese herbal medicine has a positive effect on the clinical treatment of RP. Therefore, we proposed that the decreased blood flow may participate in the lesion. In this article, we will review the findings on the decreased blood flow affected in RP from the perspective of modern medicine and Chinese medicine.

We propose a novel fault-tolerant cooperative control strategy for multiagent systems. A set of unknown input observers for each agent are constructed for fault detection. Then a real-time adaptive extremum seeking algorithm is utilized for adaptive approximation of fault parameter. We prove that the consensus can be still reached by regulating the interconnection weights and changing the connection topology of the fault agent. A numerical simulation example is given to illustrate the feasibility and effectiveness of the proposed method.

Qingxuan Jiangya Decoction (QXJYD) is a traditional Chinese medicine commonly used in the clinical treatment of hypertension. Earlier studies had shown that QXJYD could inhibit the elevation of blood pressure in spontaneously hypertensive rats (SHRs) and prevent remodeling of arterial vessels. This study examines the therapeutic efficacy of QXJYD against elevated blood pressure using the SHR model, as well as the mechanisms behind its antihypertensive activity and protection against renal fibrosis. The results showed that QXJYD significantly attenuated the increase in blood pressure in SHRs and mitigated the development of renal interstitial fibrosis. In addition, QXJYD also robustly decreased the excess accumulation of extracellular matrix and attenuated the elevated expression of MMPs. The antihypertensive effects and renal protection of QXJYD were determined to be strongly associated with inhibition of TGF-β1/Smad signaling pathway.

Image-based visual servoing for nonholonomic mobile robots using epipolar geometry is an efficient technology for visual servoing problem. An improved visual servoing strategy, namely, three-step epipolar-based visual servoing, is developed for the nonholonomic robot in this paper. The proposed strategy can keep the robot meeting FOV constraint without any 3D reconstruction. Moreover, the trajectory planned by this strategy is shorter than the existing strategies. The mobile robot can reach the desired configuration with exponential converge. The control scheme in this paper is divided into three steps. Firstly, by using the difference of epipoles as feedback, the robot rotates to make the current configuration and desired configuration in the same orientation. Then, by using a linear input-output feedback, the epipoles are zeroed so as to align the robot with the goal. Finally, by using the difference of feature points, the robot reaches the desired configuration. Simulation results and experimental results are given to illustrate the effectiveness of the proposed control scheme.

The traditional Chinese medicine formula Pien Tze Huang (PZH) has long been used as a folk remedy for cancer. To elucidate the mode of action of PZH against cancer, in the present study we used a 5-FU resistant human colorectal carcinoma cell line (HCT-8/5-FU) to evaluate the effects of PZH on multidrug resistance (MDR) and epithelial-mesenchymal transition (EMT) as well as the activation of TGF-βpathway. We found that PZH dose-dependently inhibited the viability of HCT-8/5-FU cells which were insensitive to treatment of 5-FU and ADM, demonstrating the ability of PZH to overcome chemoresistance. Furthermore, PZH increased the intercellular accumulation of Rhodamine-123 and downregulated the expression of ABCG2 in HCT-8/5-FU cells. In addition, drug resistance induced the process of EMT in HCT-8 cells as evidenced by EMT-related morphological changes and alteration in the expression of EMT-regulatory factors, which however was neutralized by PZH treatment. Moreover, PZH inhibited MDR/EMT-enhanced migration and invasion capabilities of HCT-8 cells in a dose-dependent manner and suppressed MDR-induced activation of TGF-βsignaling in HCT-8/5-FU cells. Taken together, our study suggests that PZH can effectively overcome MDR and inhibit EMT in human colorectal carcinoma cells via suppression of the TGF-βpathway.

Objective. To determine the risks of induced term delivery to the mother and neonate at different gestational ages in the absence of obstetric indications. Study Design. All deliveries in New South Wales (NSW) between 1998 and 2008 were reviewed from the MDC. Uncomplicated pregnancies which were induced for non-obstetric reasons after 37 completed weeks were reviewed. This was a retrospective, historical cohort study, and both maternal and neonatal outcomes were analysed and compared between different gestational age groups. Results. An analysis of the data shows that induction of labour after 37 completed weeks exposes the fetus and mother to different levels of risk at different gestations. Conclusion. In an uncomplicated pregnancy, induction of labour is associated with the highest rate of neonatal complication at 37 weeks as compared with rates at later gestations. With each ensuing week, the neonatal outcome improves. At 40 weeks the likelihood of neonatal intensive care admission, low Apgar scores, and perinatal death rate is at its lowest, and then there is a slight but not significant rise after 41 weeks. The likelihood of caesarean section is the lowest when inductions are carried out at 39 weeks and is the highest at 41 weeks and over.

In order to investigate how the amino acids on the surface of myoglobin molecule influence myoglobin's structure and function, a variety of spectroscopy techniques were applied in the study of the interaction between Fe(III) and myoglobin (wild type and its mutants, D44K, D60K, and K56D). The results demonstrate that Fe(III) can quench the fluorescence of wild type and mutants of myoglobin, and the quenching mechanisms are static quenching. It is found that the binding distance between Fe(III) and myoglobin mutants gets smaller, the binding capacity increases by the values of binding constant and the bimolecular quenching constant as well as the binding distance. Those data also indicate that the metal ion Fe(III) can interact strongly with myoglobin mutants. The three-dimensional conformation change after surface amino acids are replaced is detected by the UV absorption spectroscopy and fluorescence spectroscopy, which make mutants become more dynamic and change its function and interaction with Fe(III) strongly.

As tremendous mobile devices access to the Internet in the future, the cells which can provide high data rate and more capacity are expected to be deployed. Specifically, in the next generation of mobile communication 5G, cloud computing is supposed to be applied to radio access network. In cloud radio access network (Cloud-RAN), the traditional base station is divided into two parts, that is, remote radio heads (RRHs) and base band units (BBUs). RRHs are geographically distributed and densely deployed, so as to achieve high data rate and low latency. However, the ultradense deployment inevitably deteriorates spectrum efficiency due to the severer intercell interference among RRHs. In this paper, the downlink spectrum efficiency can be improved through the cooperative transmission based on forming the coalitions of RRHs. We formulate the problem as a coalition formation game in partition form. In the process of coalition formation, each RRH can join or leave one coalition to maximize its own individual utility while taking into account the coalition utility at the same time. Moreover, the convergence and stability of the resulting coalition structure are studied. The numeric simulation result demonstrates that the proposed approach based on coalition formation game is superior to the noncooperative method in terms of the aggregate coalition utility.

As an important part of intelligent transportation systems, path planning algorithms have been extensively studied in the literature. Most of existing studies are focused on the global optimization of paths to find the optimal path between Origin-Destination (OD) pairs. However, in urban road networks, the optimal path may not be always available when some unknown emergent events occur on the path. Thus a more practical method is to calculate several suboptimal paths instead of finding only one optimal path. In this paper, a cooperativeQ-learning path planning algorithm is proposed to seek a suboptimal multipath set for OD pairs in urban road networks. The road model is abstracted to the form thatQ-learning can be applied firstly. Then the gray prediction algorithm is combined intoQ-learning to find the suboptimal paths with reliable constraints. Simulation results are provided to show the effectiveness of the proposed algorithm.

Hypoxia-induced angiogenesis plays an important role in the development and metastasis of solid tumors and is highly regulated by HIF-1α/VEGF-A pathway. Therefore, inhibiting tumor angiogenesis via suppression of HIF-1α/VEGF-A signaling represents a promising strategy for anticancer treatment. As a traditional Chinese medicine formula, Pien Tze Huang (PZH) has long been used as a folk remedy for cancer in China and Southeast Asia. Previously, we reported that PZH inhibits colorectal cancer (CRC) growth both in vivo and in vitro. To elucidate the antitumor mechanisms of PZH, in the present study we used human umbilical vein endothelial cells (HUVEC) and colorectal carcinoma HCT-8 cells to evaluate the effects of PZH on hypoxia-induced angiogenesis and investigated the underlying molecular mechanisms. We found that PZH could inhibit hypoxia-induced migration and tube formation of HUVEC cells in a dose-dependent manner, although the low concentrations of PZH had no effect on HUVEC viability. Moreover, PZH inhibited hypoxia-induced activation of HIF-1αsignaling and the expression of VEGF-A and/or VEGFR2 in both HCT-8 and HUVEC cells. Collectively, our findings suggest that PZH can inhibit hypoxia-induced tumor angiogenesis via suppression of HIF-1α/VEGF-A pathway.

Microcontroller based maximum power point tracking (MPPT) has been the most popular MPPT approach in photovoltaic systems due to its high flexibility and efficiency in different photovoltaic systems. It is well known that PV systems typically operate under a range of uncertain environmental parameters and disturbances, which implies that MPPT controllers generally suffer from some unknown stochastic perturbations. To address this issue, a novel Newton-based stochastic extremum seeking MPPT method is proposed. Treating stochastic perturbations as excitation signals, the proposed MPPT controller has a good tolerance of stochastic perturbations in nature. Different from conventional gradient-based extremum seeking MPPT algorithm, the convergence rate of the proposed controller can be totally user-assignable rather than determined by unknown power map. The stability and convergence of the proposed controller are rigorously proved. We further discuss the effects of partial shading and PV module ageing on the proposed controller. Numerical simulations and experiments are conducted to show the effectiveness of the proposed MPPT algorithm.

Multiple layers of suppressive components including regulatory T (TReg) cells, suppressive antigen-presenting cells, and inhibitory cytokines form suppressive networks in the ovarian cancer microenvironment. It has been demonstrated that as a major suppressive element, TRegcells infiltrate tumor, interact with several types of immune cells, and mediate immune suppression through different molecular and cellular mechanisms. In this paper, we focus on human ovarian cancer and will discuss the nature of TRegcells including their subsets, trafficking, expansion, and function. We will briefly review the development of manipulation of TRegcells in preclinical and clinical settings.

Using an integral equation associated with generalized backward Kolmogorov's equation for the transition probability density function, recurrence relations are derived for the moments of the time of first exit of jump-diffusions with Markovian switching. The results are used to find the expectation of first passage time of some financial models.