bluuebunny/crossref_metadata_2025 huggingface dataset:
The medaka fish Tol2 transposable element is in an early stage of decay: identification of a nonautonomous copy
Authors: Hayashi Sakura , Tsukiyama Takuji , Iida Atsuo , Kinoshita Masato , Koga Akihiko
Published: September 2021

The majority of DNA-based transposable elements comprise autonomous and nonautonomous copies, or only nonautonomous copies, where the autonomous copy contains an intact gene for a transposase protein and the nonautonomous copy does not. Even if autonomous copies coexist, they are generally less frequent. The Tol2 element of medaka fish is one of the few elements for which a nonautonomous copy has not yet been found. Here, we report the presence of a nonautonomous Tol2 copy that was identified by surveying the medaka genome sequence database. This copy contained three local sequence alterations that affected the deduced amino acid sequence of the transposase: a deletion of 15 nucleotides resulting in a deletion of 5 amino acids, a base substitution causing a single amino acid change, and another base substitution giving rise to a stop codon. Transposition assays using cultured human cells revealed that transposase activity was reduced by the 15-nucleotide deletion and abolished by the nonsense mutation. This is the first example of a nonautonomous Tol2 copy. Thus, Tol2 is in an early stage of decay in the medaka genome, and is therefore a unique element to observe an almost complete decay process that progresses in natural populations.
Non-Rindler horizons and radiating black holes
Authors: Wasnik Vaibhav
Published: September 2021

In this work we construct metrics corresponding to radiating black holes whose near horizon regions cannot be approximated by Rindler space–time. We first construct infinite parameter coordinate transformations from Minkowski coordinates, such that an observer using these coordinates to describe space–time events measures the Minkowski vacuum to be Planckian. Utilizing these results, we construct a family of black holes that radiate at spatial infinity. As an illustration, we study a subset of the black hole solutions and show that they satisfy the null energy condition.
Enhancing the Interpretability of Deep Models in Healthcare Through Attention: Application to Glucose Forecasting for Diabetic People
Authors: De Bois Maxime , El Yacoubi Mounîm A. , Ammi Mehdi
Published: September 2021

The adoption of deep learning in healthcare is hindered by their “black box” nature. In this paper, we explore the RETAIN architecture for the task of glucose forecasting for diabetic people. By using a two-level attention mechanism, the recurrent-neural-network-based RETAIN model is interpretable. We evaluate the RETAIN model on the type-2 IDIAB and the type-1 OhioT1DM datasets by comparing its statistical and clinical performances against two deep models and three models based on decision trees. We show that the RETAIN model offers a very good compromise between accuracy and interpretability, being almost as accurate as the LSTM and FCN models while remaining interpretable. We show the usefulness of its interpretable nature by analyzing the contribution of each variable to the final prediction. It revealed that signal values older than 1[Formula: see text]h are not used by the RETAIN model for 30[Formula: see text]min ahead of time prediction of glucose. Also, we show how the RETAIN model changes its behavior upon the arrival of an event such as carbohydrate intakes or insulin infusions. In particular, it showed that the patient’s state before the event is particularly important for the prediction. Overall the RETAIN model, thanks to its interpretability, seems to be a very promising model for regression or classification tasks in healthcare.
An Accurate Real-Time License Plate Detection Method Based On Deep Learning Approaches
Authors: Khazaee Saeed , Tourani Ali , Soroori Sajjad , Shahbahrami Asadollah , Suen Ching Yee
Published: September 2021

In vision-driven Intelligent Transportation Systems (ITS) where cameras play a vital role, accurate detection and re-identification of vehicles are fundamental demands. Hence, recent approaches have employed a wide range of algorithms to provide the best possible accuracy. These methods commonly generate a vehicle detection model based on its visual appearance features such as license plate, headlights, or some other distinguishable specifications. Among different object detection approaches, Deep Neural Networks (DNNs) have the advantage of magnificent detection accuracy in case a huge amount of training data is provided. In this paper, a robust approach for license plate detection (LPD) based on YOLO v.3 is proposed which takes advantage of high detection accuracy and real-time performance. The mentioned approach can detect the license plate location of vehicles as a general representation of vehicle presence in images. To train the model, a dataset of vehicle images with Iranian license plates has been generated by the authors and augmented to provide a wider range of data for test and train purposes. It should be mentioned that the proposed method can detect the license plate area as an indicator of vehicle presence with no Optical Character Recognition (OCR) algorithm to distinguish characters inside the license plate. Experimental results have shown the high performance of the system with a precision 0.979 and recall 0.972.
THE EFFECT OF NOISE AND NONLINEAR NOISE REDUCTION METHODS ON THE FRACTAL DIMENSION OF CHAOTIC TIME SERIES
Authors: ZANDI-MEHRAN NAZANIN , JAFARI SAJAD , GOLPAYEGANI SEYED MOHAMMAD REZA HASHEMI , NAMAZI HAMIDREZA
Published: September 2021

The fractal dimension (FD) of a signal is a useful measure for characterizing its complexity. The real signals are contaminated with noise, which leads to reduced efficiency of the fractal analysis. This paper investigates the effect of noise on the FD computation and the compares the fractal dimensions obtained from noise-reduced signals. To this aim, the FD of different continuous and discrete chaotic time series is computed in the case of noise-free and noisy signals, using Katz, Higuchi, and Leibovich and Toth algorithms. Also for further investigations, the result of Lyapunov and Hurst analysis is presented. It is observed that in the continuous-time systems, the fractal dimensions obtained from all algorithms have significant changes in the presence of noise. While for the discrete-time signals, the Katz and the Higuchi dimensions have more robustness to noise. Furthermore, the Lyapunov exponent is decreased, and the Hurst exponent is increased. Then, the noisy signals are filtered with four nonlinear noise-reduction methods. The fractal dimensions are calculated from each denoised signal, and the performances of the noise-reduction methods are compared. The results show that the Katz and the Higuchi methods have less percentage change in calculating the dimension of original and filtered signals than the Leibovich and Toth method. The analysis is also done on the real heart rate signals to expand the results to real processes.
Porphyrazines with annulated diazepine rings. 6. Synthesis and properties of the alkyl substituted derivative - MgII complex of tetrakis-2,3-(5,7-di-tert-butyl-6H-1,4-diazepino)porphyrazine
Authors: Tarakanova Ekaterina N. , Tarakanov Pavel A. , Kumeev Roman S. , Nefedov Sergey E. , Stuzhin Pavel A.
Published: September 2021

Novel MgII porphyrazine 3 bearing four appended seven-membered tert-butyl substituted 1,4-diazepine rings was prepared via Linstead macrocyclization of 5,7-di-tert-butyl-6[Formula: see text]-1,4-diazepine-2,3-dicarbonitrile 2, obtained by condensation of diaminomaleonitrile and 2,2,6,6-tetramethylheptanedione-3,5 (1) in anhydrous ethanol in the presence of P2O5. The structure of the dinitrile precursor 2 was established by single crystal X-ray work. 1H NMR study revealed that the 1,4-diazepine ring is present in the 6[Formula: see text] tautomeric form both in the dinitrile precursor 2 and the MgII complex 3. The inversion of the tert-butyl substituted diazepine ring occurs more easily than in the case of aryl and alkenyl substituted species. Although porphyrazine 3exhibit some tendency to aggregation in low-polar solvents the presence of bulky tert-butyl substituents stabilizes the monomeric form and hinders formation of H-bonded dimers characteristic for aryl and styryl substituted analogues.
A ruthenium phthalocyanine functionalized with a folic acid unit as a photosensitizer for photodynamic therapy: Synthesis, characterization andin vitroevaluation
Authors: Ferreira Joana T. , Pina João , Ribeiro Carlos A. F. , Fernandes Rosa , Tomé João P. C. , Torres Tomás , Rodríguez-Morgade M. Salomé
Published: September 2021

A folate-targeted ruthenium(II) phthalocyanine (Ru(FA-Py)(DMSO)(PEG)[Formula: see text]Pc), endowed with a pyridyl ligand functionalized with one folic acid unit (FA-Py) at one of the two axial coordination sites, and a dimethylsulfoxide (DMSO) ligand coordinated to the other axial position, respectively, is described. In order to enhance its biocompatibility, the RuPc is donated with eight PEG chains attached at the peripheral positions. The observed singlet oxygen quantum yields of the PS measured in DMSO and in water are of 0.74 and 0.36, respectively, in line with those observed for other RuPcs bearing comparable axial and peripheral substitution. In vitro PDT activity of the compound has been evaluated in HT-1376 human bladder cancer cell line. Ru(FA-Py)(DMSO)(PEG)[Formula: see text]Pc revealed a slightly higher cellular uptake than those observed for the corresponding carbohydrate-substituted PSs and a better photodynamic activity compared to the glucose-functionalized RuPc.
Post Quantum Secure Command and Control of Mobile Agents Inserting Quantum-Resistant Encryption Schemes in the Secure Robot Operating System
Authors: Varma Richa , Melville Chris , Pinello Claudio , Sahai Tuhin
Published: September 2021

The secure command & control (C&C) of mobile agents arises in various settings including unmanned aerial vehicles, single pilot operations in commercial settings, and mobile robots to name a few. As more and more of these applications get integrated into aerospace and defense use cases, the security of the communication channel between the ground station and the mobile agent is of increasing importance. The development of quantum computing devices poses a unique threat to secure communications due to the vulnerability of asymmetric ciphers to Shor’s algorithm. Given the active development of new quantum resistant encryption techniques, we report the first integration of post-quantum secure encryption schemes with robotic operating system (ROS) and C&C of mobile agents, in general. We integrate these schemes in the application and network layers and study the performance of these methods by comparing them to present-day security schemes such as the widely used RSA algorithm.
Parametric and Implicit Features-Based UAV–UGVs Time-Varying Formation Tracking: Dynamic Approach
Authors: Allam Ahmed , Nemra Abdelkrim , Tadjine Mohamed
Published: September 2021

Flexible and robust Time-Varying Formation (TVF) tracking of Unmanned Ground Vehicles (UGVs) guided by an Unmanned Aerial Vehicle (UAV) is considered in this paper. The UAV–UGVs system control model is based on leader-follower approach, where the control scheme consists of two consecutive tasks, namely, deployment task and TVF tracking. Accordingly, two novel nonlinear controllers are proposed for controlling the UGVs formation. First, unlike the classical frameworks on UGVs formation tracking, for which only particular shapes are handled (e.g. circle, square, ellipse), we propose a UGVs deployment-controller ensuring to reach free-formation shapes. The key feature is in using the estimated implicit representation of the desired formation shape as a potential function to generate the UGVs reference trajectory. Second, in the TVF tracking task, a robust cascaded velocity/torque controller for UGVs is proposed based on kinematic and dynamic models. Differently from the classical backstepping framework, the key idea is in introducing an auxiliary control input, in such a way that the overall UGV dynamics is converted into a simpler and modular control structure. As such, the auxiliary input is used to control indirectly the actual UGVs velocity vector. A signum term is added to the torque-input to compensate for the unknown external disturbances and unmodeled dynamics. Numerical simulation shows the effectiveness of the proposed formation controllers compared with the case when the perfect velocity-tracking assumption holds. Experimental results are further provided using three festos Robtino robots to show the validity of the proposed TVF tracking velocity-control scheme.
Two Birds With One Stone: Boosting Both Search and Write Performance for Tree Indices on Persistent Memory
Authors: Luo Yongping , Jin Peiquan , Zhang Zhou , Zhang Junchen , Cheng Bin , Zhang Qinglin
Published: September 2021

The advance of byte-addressable persistent memory (PM) makes it a hot topic to revisit traditional tree indices such as B+-tree and radix tree, and a few new persistent memory-friendly tree indices have been proposed. However, due to the special features of persistent memory compared to DRAM and the limitations of B+-tree-like indices, it is much harder to optimize both search and write performance for tree indices on persistent memory. As a result, most existing indices for persistent memory, e.g., WB-tree, proposed to improve write performance while sacrificing search performance. Aiming to optimize both write and search performance for tree indices on persistent memory, in this paper, we first propose a novel Two-Layer Architecture (TLA) for constructing tree indices on persistent memory. The key idea, of TLA is to organize the index with a search-optimized top layer and a write-optimized bottom layer, letting the top layer optimize search performance and the bottom layer improve write performance. By adopting efficient structures for the two layers, TLA can boost both write and search performance for tree indices on persistent memory. Following the TLA architecture, we present a new index called TLBtree (Two-Layer B+-tree) offering high search and write performance for persistent memory. Moreover, we develop a concurrent TLBtree to support non-blocking read operations in multi-core environment. We evaluate our proposals under a server equipped with real Intel Optane persistent memory. The results show that TLBtree outperforms the state-of-the-art tree indices, including WB-tree, Fast&Fair, and FPTree, in both search and write performance. Also, the concurrent TLBtree can achieve up to 3.7x speedup than its competitors under the multi-core environment.
SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks
Authors: Krishnan Gokul , Mandal Sumit K. , Pannala Manvitha , Chakrabarti Chaitali , Seo Jae-Sun , Ogras Umit Y. , Cao Yu
Published: September 2021

In-memory computing (IMC) on a monolithic chip for deep learning faces dramatic challenges on area, yield, and on-chip interconnection cost due to the ever-increasing model sizes. 2.5D integration or chiplet-based architectures interconnect multiple small chips (i.e., chiplets) to form a large computing system, presenting a feasible solution beyond a monolithic IMC architecture to accelerate large deep learning models. This paper presents a new benchmarking simulator, SIAM, to evaluate the performance of chiplet-based IMC architectures and explore the potential of such a paradigm shift in IMC architecture design. SIAM integrates device, circuit, architecture, network-on-chip (NoC), network-on-package (NoP), and DRAM access models to realize an end-to-end system. SIAM is scalable in its support of a wide range of deep neural networks (DNNs), customizable to various network structures and configurations, and capable of efficient design space exploration. We demonstrate the flexibility, scalability, and simulation speed of SIAM by benchmarking different state-of-the-art DNNs with CIFAR-10, CIFAR-100, and ImageNet datasets. We further calibrate the simulation results with a published silicon result, SIMBA. The chiplet-based IMC architecture obtained through SIAM shows 130and 72improvement in energy-efficiency for ResNet-50 on the ImageNet dataset compared to Nvidia V100 and T4 GPUs.
Regime Inference for Sound Floating-Point Optimizations
Authors: Rabe Robert , Izycheva Anastasiia , Darulova Eva
Published: September 2021

Efficient numerical programs are required for proper functioning of many systems. Today’s tools offer a variety of optimizations to generate efficient floating-point implementations that are specific to a program’s input domain. However, sound optimizations are of an “all or nothing” fashion with respect to this input domain—if an optimizer cannot improve a program on the specified input domain, it will conclude that no optimization is possible. In general, though, different parts of the input domain exhibit different rounding errors and thus have different optimization potential. We present the first regime inference technique for
sound
optimizations that automatically infers an effective subdivision of a program’s input domain such that individual sub-domains can be optimized more aggressively. Our algorithm is general; we have instantiated it with mixed-precision tuning and rewriting optimizations to improve performance and accuracy, respectively. Our evaluation on a standard benchmark set shows that with our inferred regimes, we can, on average, improve performance by 65% and accuracy by 54% with respect to whole-domain optimizations.
Battery-Free Game Boy
Authors: de Winkel Jasper , Kortbeek Vito , Hester Josiah , Pawełczak Przemysław
Published: September 2021

Any future mobile electronic device with which a user interacts (smartphone, hand-held game console) should not pollute our planet. Consequently, designers need to rethink how to build mobile devices with fewer components that negatively impact the environment (by replacing batteries with energy harvesting sources) while not compromising the user experience quality. This article addresses the challenges of battery-free mobile interaction and presents the first battery-free, personal mobile gaming device powered by energy harvested from gamer actions and sunlight. Our design implements a power failure resilient Nintendo Game Boy emulator that can run off-the-shelf classic Game Boy games like Tetris or Super Mario Land. Beyond a fun toy, our design represents the first battery-free system design for continuous user attention despite frequent power failures caused by intermittent energy harvesting.
Plant Cell Identity in the Era of Single-Cell Transcriptomics
Authors: Ryu Kook Hui , Zhu Yan , Schiefelbein John
Published: September 2021

High-throughput single-cell transcriptomic approaches have revolutionized our view of gene expression at the level of individual cells, providing new insights into their heterogeneity, identities, and functions. Recently, technical challenges to the application of single-cell transcriptomics to plants have been overcome, and many plant organs and tissues have now been subjected to analyses at single-cell resolution. In this review, we describe these studies and their impact on our understanding of the diversity, differentiation, and activities of plant cells. We particularly highlight their impact on plant cell identity, including unprecedented views of cell transitions and definitions of rare and novel cell types. We also point out current challenges and future opportunities for the application and analyses of single-cell transcriptomics in plants.
Repetitive spikes of glucose and lipid induce senescence-like phenotypes of bone marrow stem cells through H3K27me3 demethylase-mediated epigenetic regulation
Authors: Horitani Keita , Iwasaki Masayoshi , Kishimoto Hiroshi , Wada Kensaku , Nakano Miyuki , Park Haengnam , Adachi Yasushi , Motooka Daisuke , Okuzaki Daisuke , Shiojima Ichiro
Published: September 2021

Combination of hyperglycemia and hypertriglyceridemia is associated with increased risk of atherosclerotic cardiovascular disease. We found that 1) hypertriglyceridemia may enhance the negative impact of hyperglycemia on circulating EPC number in humans and 2) metabolic stress induced by glucose + triglyceride spikes in mice results in senescence-like phenotypes of bone marrow stem/progenitor cells via H3K27me3 demethylase-mediated epigenetic regulation. These findings have important implications for understanding the pathogenesis of atherosclerotic cardiovascular disease in patients with T2DM.
A Hybrid Association Rule-Based Method to Detect and Classify Botnets
Authors: Huang Yuanyuan , Jiazhong Lu , Tang Haozhe , Liu Xiaolei
Published: September 2021

Nowadays, botnet has become a threat in the area of cybersecurity, and, worse still, it is difficult to be detected in complex network environments. Thus, traffic analysis is adopted to detect the botnet since this kind of method is practical and effective; however, the false rate is very high. The reason is that normal traffic and botnet traffic are quite close to the border, making it so difficult to be recognized. In this paper, we propose an algorithm based on a hybrid association rule to detect and classify the botnets, which can calculate botnets’ boundary traffic features and receive effects in the identification between normal and botnet traffic ideally. First, after collecting the data of different botnets in a laboratory, we analyze botnets traffic features by processing a data mining on it. The suspicious botnet traffic is filtered through DNS protocol, black and white list, and real-time feature filtering methods. Second, we analyze the correlation between domain names and IP addresses. Combining with the advantages of the existing time-based detection methods, we do a global correlation analysis on the characteristics of botnets, to judge whether the detection objects can be botnets according to these indicators. Then, we calculate these parameters, including the support, trust, and membership functions for association rules, to determine which type of botnet it belongs to. Finally, we process the test by using the public dataset and it turns out that the accuracy of our algorithm is higher.
Influence of Mine Earthquake Disturbance on the Principal Stress of the Main Roadway near the Goaf and Its Prevention and Control Measures
Authors: Guo Penghui , Li Jiazhuo , Hao Xiqing , Cui Heng , Tian Lihua , Xie Wenhao , Chu Jiaqi
Published: September 2021

With the reduction and depletion of shallow energy, the mining depth of coal around the world is increasing year by year, and the mining depth of some coal mines in China has reached kilometers. The main roadway near the goaf with the deep high static stress is very easy to be damaged after being disturbed by the mine earthquake. Taking the main roadway in the no. 1 mining area of Gaojiapu coal mine in Binchang mining area, Shaanxi Province, China, as the engineering background, the high-energy mine earthquake monitored by the on-site microseism is equivalently simulated through the dynamic module of FLAC3D, and the spatial-temporal rotation characteristics of the principal stress of roadway surrounding rock under the disturbance of mine earthquake are studied and analyzed and put forward corresponding prevention and control measures. Research shows early stage of mine earthquake disturbance, roadway roof is first affected, and the principal stress of the roof has the trend of deflection to the side of the goaf. In the middle stage of mine earthquake disturbance, the main body of roof principal stress deflects to the side of goaf, and the deflection range is large. In the later stage of mine earthquake disturbance, the principal stress directions in the surrounding rock reverse rotation, and the reverse rotation angle of the principal stress direction in the roof is the largest. Finally, the asymmetric distribution characteristics of principal stress rotation are verified by using the asymmetric deformation phenomenon on both sides of roadway surrounding rock. Based on the rotation characteristics of principal stress under the dual influence of mine earthquake disturbance and goaf, optimize the layout scheme and blasting parameters of blasting pressure relief holes. The transmission direction of principal stress can be changed by blasting pressure relief method; meanwhile, the transmission of principal stress can be blocked; through the comparison of microseismic activity law before and after pressure relief, pressure relief effect is good. The research results can provide a certain reference basis for coal mine roadway pressure relief and reducing disaster conditions.
Prestroke Metformin Use on the 1‐Year Prognosis of Intracerebral Hemorrhage Patients with Type 2 Diabetes
Authors: Tu Wen-Jun , Zeng Qingjia , Wang Kai , Wang Yu , Sun Bao-Liang , Zeng Xianwei , Liu Qiang
Published: September 2021

Background. Although recent studies have focused on the use of metformin in treating ischemic stroke, there is little literature to support whether it can treat intracerebral hemorrhage (ICH). Therefore, this study is aimed at evaluating the possible effects of prestroke metformin (MET) on ICH patients with type 2 diabetes. Methods. From January 2010 to December 2019, all first‐ever ICH patients with type 2 diabetes from our hospitals were included. All discharged patients would receive a one‐time follow‐up at 1 year after admission. Death, disability, and recurrence events were recorded. Results. We included 730 patients for analysis (the median age: 65 [IQR, 56‐72] years and 57.7% was men). Of those patients, 281 (38.5%) had received MET before ICH (MET+), whereas 449 (61.5%) had not (MET−). MET (+) patients had a lower median baseline hematoma volume than did MET (‐) patients (9.6 ml [IQR, 5.3‐22.4 ml] vs. 14.7 ml [IQR, 7.9‐28.6 ml]; P < 0.001). The inhospital mortality events were not significantly reduced in the MET (+) group compared with the MET (‐) group (6.4% vs 8.9%, respectively; absolute difference, −2.5% [95% CI, −3.9% to −0.7%]; OR, 0.70 [95% CI, 0.39 to 1.27]; P = 0.22). The 1‐year mortality events were not significantly reduced in the MET (+) group compared with the MET (‐) group (14.1% vs 17.4%, respectively; absolute difference, −3.3% [95% CI, −5.1% to −1.8%]; OR, 0.73 [95% CI, 0.47 to 1.14]; P = 0.16). The 1‐year disability events were not significantly reduced in the MET (+) group compared with the MET (‐) group (28.4% vs 34.1%, respectively; absolute difference, −5.7% [95% CI, −8.2% to −3.3%]; OR, 0.77 [95% CI, 0.52 to 1.13]; P = 0.18). Finally, the recurrence rates in those two groups were not significantly different (MET [+] vs. MET [‐]: 6.4% vs. 5.9%; absolute difference, 0.5% [95% CI, 0.2% to 1.3%]; OR, 1.08 [95% CI, 0.51 to 2.28]; P = 0.84). Conclusions. Pre‐ICH metformin use was not associated with inhospital mortality and 1‐year prognosis in diabetic ICH patients.
The Construction of Basketball Training System Based on Motion Capture Technology
Authors: Nie Shangqi , Li Yuanqing , Ma Biao , Zhang Yufeng , Song Jeho
Published: September 2021

Motion capture is a cross-cutting application field developed in recent years, which comprises electronics, communications, control, computer graphics, ergonomics, navigation, and other disciplines. The accurate application of basketball technical movements in the basketball game is very important. Therefore, it is of great significance to capture and standardize athletes’ movements and improve their training. Unfortunately, there are numerous issues in traditional classroom teaching that largely helps to train the athletes. To solve the issues of traditional basketball classroom teaching, a virtual simulation system for students’ sports training is designed in this paper. Firstly, the information of basketball dribbling movement is captured and simulated in three dimensions. Secondly, we compare it with the standard database to judge the irregularities of athletes’ movements, and carry out digital processing on athletes’ movements and skill improvements statistics in combination with system functions. Thirdly, we set up a gradual training cycle. Finally, the Kinect-based capture technology is adopted to obtain the activity information of different joints of the human body. Through processing the motion data, relevant motion analysis data are fed to the established motion model, to realize the comparative analysis of motion pictures. In our experiments, we observed better training of the physical education.
PD-1/PD-L1 Inhibitors versus Chemotherapy for Previously Treated Advanced Gastroesophageal Cancer: A Meta-Analysis of Randomized Controlled Trials
Authors: Maoxi Zhong , Jinmin Xue , Xiaozhu Zeng , Yubing Yue , Yuxi Zhu
Published: September 2021

Patients with advanced gastroesophageal cancer refractory to the previous regimen of chemotherapy suffered from poor prognosis without many effective treatment options. Immune checkpoint inhibitors (ICIs) provide promising efficacy, but the relevant clinical trials have offered controversial data. We performed this meta-analysis to compare the efficacy and safety of inhibitors against programmed cell death receptor 1 (PD-1) and its ligand PD-L1 versus chemotherapy as second or third-line therapy in patients with advanced gastroesophageal cancer. Six randomized controlled trials (RCTs) including 2,648 patients were included. The meta-analysis results indicated that both ORR (RR = 1.39, 95% CI: 0.85∼2.25,

P

 = 0.188) and PFS (HR = 1.14, 95% CI: 0.88∼1.46,

P

 = 0.316) were not significantly improved by ICIs compared with chemotherapy. However, the OS was significantly prolonged (HR = 0.85, 95% CI: 0.75–0.97,

P

 = 0.018) in the ICIs group compared with chemotherapy. Subgroup analysis showed that ICIs provide statistically significant OS benefits over chemotherapy in PD-L1-positive, squamous cell carcinoma, Asia origin, esophageal cancer, second-line treatment, male, and aged 65 or older patients. Compared with chemotherapy, the TRAEs risk of ICIs was reduced by 33% (RR = 0.67, 95% CI: 0.62–0.73,

P

 ≤ 0.001). And the risk of grades 3–5 of TRAEs was reduced by 60% (RR = 0.40, 95% CI: 0.33–0.49,

P

 ≤ 0.001). Compared to chemotherapy, ICIs appeared to improve OS and were better tolerated in previously treated patients with advanced esophageal cancer. We recommend PD-1/PD-L1 inhibitors as an optimal treatment option for positive PD-L1 expression, squamous cell carcinoma, Asia origin, esophageal cancer, second-line treatment, male, and ≥65 years of age patients.
Curcumin Alleviated Dextran Sulfate Sodium-Induced Colitis by Regulating M1/M2 Macrophage Polarization and TLRs Signaling Pathway
Authors: Kang Zeng-Ping , Wang Meng-Xue , Wu Tian-Tian , Liu Duan-Yong , Wang Hai-Yan , Long Jian , Zhao Hai-Mei , Zhong You-Bao
Published: September 2021

Curcumin has shown good efficacy in mice with experimental colitis and in patients with ulcerative colitis, but the mechanism of action through the regulation of M1/M2 macrophage polarization has not been elaborated. The ulcerative colitis was modeled by dextran sulfate sodium; colitis mice were orally administrated with curcumin (10 mg/kg/day) or 5-ASA (300 mg/kg/day) for 14 consecutive days. After curcumin treatment, the body weight, colon weight and length, colonic weight index, and histopathological damage in colitis mice were effectively improved. The concentrations of proinflammatory cytokines IL-1β, IL-6, and CCL-2 in the colonic tissues of colitis mice decreased significantly, while anti-inflammatory cytokines IL-33 and IL-10 increased significantly. Importantly, macrophage activation was suppressed and M1/M2 macrophage polarization was regulated in colitis mice, and the percentage of CD11b+F4/80+ and CD11b+F4/80+TIM-1+ and CD11b+F4/80+iNOS+ decreased significantly and CD11b+F4/80+CD206+ and CD11b+F4/80+CD163+ increased significantly. Additionally, curcumin significantly downregulated CD11b+F4/80+TLR4+ macrophages and the protein levels of TLR2, TLR4, MyD88, NF-κBp65, p38MAPK, and AP-1 in colitis mice. Our study suggested that curcumin exerted therapeutic effects in colitis mice by regulating the balance of M1/M2 macrophage polarization and TLRs signaling pathway.
Design of an Improved Hybrid FTC for Faults in Aero-Engine Closed-Loop Control System
Authors: Liu Xiaofeng , Luo Chenshuang , Xiong Liuqi
Published: September 2021

Due to the aero-engines in a high temperature, pressure, and spool speed environment, the concurrent faults in actuator/sensor combined with degradation of the aero-engine could arise the problem of closed-loop instability during the flight. For this purpose, an improved hybrid fault-tolerant control (FTC) technique has been studied in this paper to deal with simultaneous failure of actuators and sensors associated with health parameters of the typical components’ degradation in aero-engines. The improved hybrid FTC structure combined with the nonlinear thermodynamic component-level (NCL) model-based estimation method merges fault estimation of actuators/sensors and typical components’ degradation estimation process into the FTC process. A robust

H

∞

state feedback controller under the disturbance of simultaneous actuator and sensor faults is designed in the proposed method, together with the switching algorithm serving for the fault estimation and improved hybrid FTC channels. In order to show the feasibility of the proposed method, several semiphysical experiments are engaged to illustrate that the improved hybrid FTC structure can save the tolerant-control time and improve performance of the control system.
Synthesis and Application of Iron Oxide Nanoparticles in Bone Tissue Repair
Authors: Lu Da , Wu Xueqing , Wang Wei , Ma Chenghao , Pei Baoqing , Wu Shuqin
Published: September 2021

Nanoparticles play a vital role in bone tissue repair engineering, especially iron oxide nanoparticles (IONPs), which have magnetic properties, semiconductor properties, and nontoxicity at the same time, and their applications in biomedicine have received widespread attention. This review summarizes the excellent performance of IONPs in enhancing scaffold functions, promoting stem cell differentiation, and labeling positioning, in order to understand the research progress and future development trends of IONPs in bone tissue repair engineering, as well as the security issues. Firstly, IONPs can affect the expression of genes and proteins to accelerate the process of biomineralization under a magnetic field. Then, the composite of IONPs and polymers can synthesize a scaffold which can promote the attachment, proliferation, and bone differentiation of stem cells. Furthermore, IONPs can also mark the location of drugs in the body to follow up the process of bone repair. Therefore, extensive research on the manufacturing and application range of IONPs is of great significance to bone tissue repair engineering.
Construction of a Hierarchical Neural Network Power Source Model for Human Capital Technology Innovation and Benefit Distribution with Big Data Analysis
Authors: Liu Yang , Tsai Sang-Bing
Published: September 2021

In this paper, a hierarchical neural network power source model is used to conduct an in-depth analysis and research on human capital technology innovation and revenue distribution. A hierarchical neural network analysis method was chosen to evaluate the human capital value of professional degree master students, and the applicability of the index system was confirmed through errors; moreover, the significance of the output results was analyzed according to the weight assignments of the input, implicit, and output layers. The analysis found that there was a large disagreement in the assessment of their human capital value, which led to the lack of practical utility of human capital. Knowledge-skilled talents have a wealth of theoretical knowledge and can use theories to guide related work. Compared with technically skilled high-skilled talents, their educational level is higher, and they can summarize past intuitive experience into theoretical guidance. Therefore, the hierarchical neural network method we constructed is theoretically effective in assessing the value of the human capital of professional master’s students and the role of the main constituents. Based on the assessment results, we can provide policy-informed suggestions for improving the quality of school education. To quickly verify whether the model can converge during the training process, a simple dataset with only two sequences and the elements in the sequences being real numbers rather than vectors are constructed to speed up the computation; meanwhile, the length of the sequences in this dataset is adjustable to initially verify the model’s ability to alleviate the long-time dependence problem.
Deep Integration of Physical Health Education Based on Intelligent Communication Technology
Authors: Liu Min , Bu Jianjun
Published: September 2021

In recent years, intelligent medical communication technology has developed rapidly, and the advancement of hardware technology has accelerated the development of software technology. Physical exercise breaks the limits of all aspects of the human body and requires scientific and reliable information. Industrial cameras realize collection and high-resolution image processing functions and use artificial intelligence to create conditions for collecting scientific data. With the powerful driving force of artificial intelligence, it is believed that physical education will develop to a new height. The intellectualization of physical education makes people expect that it will also bring some inevitable problems, but as long as we continue to overcome and improve, we believe that artificial intelligence will better serve physical education and benefit mankind. Artificial intelligence is the current trend of social development. This paper takes physical education as a breakthrough point to discuss the application of artificial intelligence in physical education. This paper uses the grey GM prediction model and questionnaire survey method to build an online education platform and develop an effective education model, which can integrate the country’s best educational resources and reduce time and space constraints. Providing a relaxing learning environment for education, one can learn anytime, anywhere. In a typical physical education system, the average self-efficacy score is converted from 20.48 points to 68.37 points, and the average self-score of physical education in the integrated artificial intelligence environment is converted from 30.25 points to 75.54 points. The data show that the quality of education has greatly improved.
A Decade of Research on Coffee as an Anticarcinogenic Beverage
Authors: Nigra Ayelén D. , Teodoro Anderson J. , Gil Germán A.
Published: September 2021

Coffee consumption has been investigated as a protective factor against cancer. Coffee is a complex beverage that contains more than 1000 described phytochemicals, which are responsible for its pleasant taste, aroma, and health‐promoting properties. Many of these compounds have a potential therapeutic effect due to their antioxidant, anti‐inflammatory, antifibrotic, and anticancer properties. The roasting process affects the phytochemical content, and undesirable compounds may be formed. In recent years, there have been contradictory publications regarding the effect of coffee drinking and cancer. Therefore, this study is aimed at evaluating the association of coffee consumption with the development of cancer. In PubMed, until July 2021, the terms “Coffee and cancer” resulted in about 2150 publications, and almost 50% of them have been published in the last 10 years. In general, studies published in recent years have shown negative associations between coffee consumption and the risk or development of different types of cancer, including breast, prostate, oral, oral and pharyngeal, melanoma, skin and skin nonmelanoma, kidney, gastric, colorectal, endometrial, liver, leukemic and hepatocellular carcinoma, brain, and thyroid cancer, among others. In contrast, only a few publications demonstrated a double association between coffee consumption and bladder, pancreatic, and lung cancer. In this review, we summarize the in vitro and in vivo studies that accumulate epidemiological evidence showing a consistent inverse association between coffee consumption and cancer.
The Analysis of Using Spatial Smoothing for DOA Estimation of Coherent Signals in Sparse Arrays
Authors: Xu Haiyun , Cui Weijia , Du Yuxi , Mei Fengtong , Ba Bin
Published: September 2021

When there is coexistence of uncorrelated and coherent signals in sparse arrays, the conventional algorithms for direction-of-arrival (DOA) estimation using difference coarray fail. In order to solve the problems, this paper analyzes the feasibility of using spatial smoothing in sparse arrays. Firstly, we summarize the two types of sparse arrays, one consisting of identical sparse subarrays and the other consisting of several uniform linear subarrays. Then, we give the feasibility analysis and the processes of applying spatial smoothing. At last, we discuss the performance of the number of detectable coherent signals in different sparse arrays. Numerical experiments prove the conclusions proposed by the paper.
[Retracted] Improvement of English Teaching Model Based on Computer Network
Authors: Du Yining
Published: September 2021

The increase in the number of colleges and universities has brought great pressure to college English teaching. How to improve the teaching efficiency of English mode is an urgent problem to be solved. This article mainly studies the improvement of English teaching mode based on computer image assistance. In the preexperiment test, a unified English final test paper was selected, and the scores of 40 students were entered into the computer. The experimental group chose the English teaching mode of computer‐assisted teaching. The control group still used traditional teaching methods to learn. At the end of the experiment, the students in the experimental group and the control group were given a posttest of writing in their respective classrooms, and the teachers gave their scores according to the scoring standard of the college entrance examination. SPSS 17.0 software is used to analyze the students’ scores, and the experimental results are obtained by comparing the changes of students’ scores before and after the test. In groups, tasks are done together, but it also helps students develop a correct sense of collective responsibility and fair play. Students can evaluate team members from the aspects of activity enthusiasm and learning participation. Students’ self‐assessment can be evaluated objectively by observing their preclass learning level, chapter task completion, class attendance, group cooperation participation, and so on. In terms of learning motivation, the average value of students’ online learning initiative consciousness (3.04) and the average value of learning interest (3.05) are slightly higher than 3. The results show that computer image‐assisted teaching can maximize the use of classrooms to improve students’ opportunities to use language and fully reflect students’ role as the main body of practice in English learning.
Plant Natural Compounds in the Treatment of Adrenocortical Tumors
Authors: Manso Jacopo , Sharifi-Rad Javad , Zam Wissam , Tsouh Fokou Patrick Valere , Martorell Miquel , Pezzani Raffaele
Published: September 2021

Plant natural products are a plethora of diverse and complex molecules produced by the plant secondary metabolism. Among these, many can reserve beneficial or curative properties when employed to treat human diseases. Even in cancer, they can be successfully used and indeed numerous phytochemicals exert antineoplastic activity. The most common molecules derived from plants and used in the fight against cancer are polyphenols, i.e., quercetin, genistein, resveratrol, curcumin, etc. Despite valuable data especially in preclinical models on such compounds, few of them are currently used in the medical practice. Also, in adrenocortical tumors (ACT), phytochemicals are scarcely or not at all used. This work summarizes the available research on phytochemicals used against ACT and adrenocortical cancer, a very rare disease with poor prognosis and high metastatic potential, and wants to contribute to stimulate preclinical and clinical research to find new therapeutic strategies among the overabundance of biomolecules produced by the plant kingdom.
Simultaneous and Rapid Determination of Six Tyrosine Kinase Inhibitors in Patients with Non-Small Cell Lung Cancer Using HPLC-MS/MS
Authors: Liu Yanping , Liu Hua , Xia Zhewei , Wang Zhipeng , Yun Yunlei , Zhang Guanying , Huang Lifeng , Gao Shouhong , Chen Wansheng
Published: September 2021

Objective. To develop a new method for quantitatively analyzing six tyrosine kinase inhibitors (gefitinib, erlotinib, icotinib, afatinib, osimertinib, and crizotinib) used in the treatment of non-small cell lung cancer (NSCLC) by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Methods. The analytes were detected in the selected reaction monitoring mode on a triple quadrupole mass spectrometer with the positive ionization mode. Carbamazepine was utilized as the internal standard. The pretreatment of the plasma sample was completed based on protein precipitation with acetonitrile, and the analytes were separated on an Agilent Zorbax SB-C18 reversed-phase column (2.1 mm × 100 mm, 3.5 μm, Agilent, USA) using gradient elution. The mobile phase consisted of 0.1% formic acid in water (phase A) and 0.1% formic acid in acetonitrile (phase B). The flow rate was 0.3 mL/min, and the injection volume was 5 μL. The column temperature was set and maintained at 35°C. Results. The calibration curves were linear over the range from 5.0 to 1000.0 ng/mL for gefitinib, crizotinib, and osimertinib; from 50.0 to 4000.0 ng/mL for icotinib and erlotinib; and from 5.0 to 400.0 ng/mL for afatinib. Linear correlation coefficients were >0.990 for all regression curves. The intra- and interday accuracy and precision of the method were within ±15.0% and not more than 15.0%, respectively. The mean recovery of all the analytes ranged from 70.18% to 110.76%, the matrix effect was from 88.85% to 127.58%, and stability was within ±15.0%. Conclusion. This newly developed method was sensitive, simple, and robust and could be used in therapeutic drug monitoring of six tyrosine kinase inhibitors in NSCLC patients.
Experimental Study of a Deep-Learning RGB-D Tracker for Virtual Remote Human Model Reconstruction
Authors: Payandeh Shahram , Wael Jeffrey
Published: September 2021

Tracking movements of the body in a natural living environment of a person is a challenging undertaking. Such tracking information can be used as a part of detecting any onsets of anomalies in movement patterns or as a part of a remote monitoring environment. The tracking information can be mapped and visualized using a virtual avatar model of the tracked person. This paper presents an initial novel experimental study of using a commercially available deep-learning body tracking system based on an RGB-D sensor for virtual human model reconstruction. We carried out our study in an indoor environment under natural conditions. To study the performance of the tracker, we experimentally study the output of the tracker which is in the form of a skeleton (stick-figure) data structure under several conditions in order to observe its robustness and identify its drawbacks. In addition, we show and study how the generic model can be mapped for virtual human model reconstruction. It was found that the deep-learning tracking approach using an RGB-D sensor is susceptible to various environmental factors which result in the absence and presence of noise in estimating the resulting locations of skeleton joints. This as a result introduces challenges for further virtual model reconstruction. We present an initial approach for compensating for such noise resulting in a better temporal variation of the joint coordinates in the captured skeleton data. We explored how the extracted joint position information of the skeleton data can be used as a part of the virtual human model reconstruction.