bluuebunny/crossref_metadata_2025 huggingface dataset:
Curved space equilibration versus flat space thermalization: A short review
Authors: Akhmedov E. T.
Published: July 2021

We discuss equilibration process in expanding Universes as compared to the thermalization process in Minkowski spacetime. The final goal is to answer the following question: Is the equilibrium reached before the rapid expansion stops and quantum effects have a negligible effect on the background geometry or stress–energy fluxes in a highly curved early Universe have strong effects on the expansion rate and the equilibrium is reached only after the drastic decrease of the spacetime curvature? We argue that consideration of more generic non-invariant states in theories with invariant actions is a necessary ingredient to understand quantum field dynamics in strongly curved backgrounds. We are talking about such states in which correlation functions are not functions of such isometry invariants as geodesic distances, while having correct UV behavior. The reason to consider such states is the presence of IR secular memory effects for generic time-dependent backgrounds, which are totally absent in equilibrium. These effects strongly affect the destiny of observables in highly curved spacetimes.
An Expensive Multi-Objective Optimization Algorithm Based on Decision Space Compression
Authors: Liu Haosen , Gu Fangqing , Cheung Yiu-Ming
Published: July 2021

Numerous surrogate-assisted expensive multi-objective optimization algorithms were proposed to deal with expensive multi-objective optimization problems in the past few years. The accuracy of the surrogate models degrades as the number of decision variables increases. In this paper, we propose a surrogate-assisted expensive multi-objective optimization algorithm based on decision space compression. Several surrogate models are built in the lower dimensional compressed space. The promising points are generated and selected in the lower compressed decision space and decoded to the original decision space for evaluation. Experimental studies show that the proposed algorithm achieves a good performance in handling expensive multi-objective optimization problems with high-dimensional decision space.
A Parallel Partial Enhancement Method for License Plate Localization in Low-Quality Images
Authors: Xiao Sainan , Yang Wangdong , Cao Buwen , Zhou Honglie , He Chenjun
Published: July 2021

Finding an effective license plate localization (LPL) method is challenging owing to different conditions during the image acquisition phase. Most existing methods do not consider various low-quality image conditions that exist in real-world situations. Low-quality image conditions mean that an image can have low resolution, plate imperfection effects, variable illumination environments or background objects similar to the license plate (LP). To improve the anti-interference ability and the speed performance of algorithm, this study aims to develop a parallel partial enhancement method based on color differences that demonstrates improved localization performance for blue–white LP images under low-quality conditions. A novel color difference model is exploited to enhance LP areas and filter non-LP areas. Blue–white color ratio and projection analysis are performed to select the exact LP area from the candidates. Moreover, this study develops a parallel version based on a multicore CPU for real-time processing for industrial applications. An image database including 395 low-quality car images captured from various scenes under different conditions is tested for the performance evaluation. The extensive experiments show the effectiveness and efficiency of the proposed approach.
A combinatorial description of the knot concordance invariant epsilon
Authors: Dey Subhankar , Doğa Hakan
Published: July 2021

In this paper, we give a combinatorial description of the concordance invariant [Formula: see text] defined by Hom, prove some properties of this invariant using grid homology techniques. We compute the value of [Formula: see text] for [Formula: see text] torus knots and prove that [Formula: see text] if [Formula: see text] is a grid diagram for a positive braid. Furthermore, we show how [Formula: see text] behaves under [Formula: see text]-cabling of negative torus knots.
Inference and Decision in Credal Occupancy Grids: Use Case on Trajectory Planning
Authors: Masson Marie-Hélène , Destercke Sébastien , Cherfaoui Véronique
Published: July 2021

Occupancy grids are common tools used in robotics to represent the robot environment, and that may be used to plan trajectories, select additional measurements to acquire, etc. However, deriving information about those occupancy grids from sensor measurements often induce a lot of uncertainty, especially for grid elements that correspond to occluded or far away area from the robot. This means that occupancy information may be quite uncertain and imprecise at some places, while being very accurate at others. Modelling finely this occupancy information is essential to decide the optimal action the robot should take, but a refined modelling of uncertainty often implies a higher computational cost, a prohibitive feature for real-time applications. In this paper, we introduce the notion of credal occupancy grids, using the very general theory of imprecise probabilities to model occupancy uncertainty. We also show how one can perform efficient, real-time inferences with such a model, and show a use-case applying the model to an autonomous vehicle trajectory planning problem.
High energy storage density with ultra-high efficiency and fast charging–discharging capability of sodium bismuth niobate lead-free ceramics
Authors: Manan Abdul , Rehman Maqbool Ur , Ullah Atta , Ahmad Arbab Safeer , Iqbal Yaseen , Qazi Ibrahim , Khan Murad Ali , Shah Hidayat Ullah , Wazir Arshad Hussain
Published: July 2021

Ceramics-based capacitors with excellent energy storage characteristics, fast charging/discharge rate, and high efficiency have received significant attention. In this work, [Formula: see text][Formula: see text]NbO3(NBN) ceramics were processed through solid-state sintering route. The investigated ceramics were crystallized in a single perovskite phase. Dense microstructure, with small average grain size ([Formula: see text]0.92 [Formula: see text]m) is obtained for the investigated ceramics. A high dielectric constant [Formula: see text]1000 accompanied by a low dielectric loss was achieved for these ceramics at ambient temperature. A recoverable energy density [Formula: see text]0.92 J/cm3and ultra-high efficiency of 96.33% at 138 kV/cm were obtained at room temperature. Furthermore, a lower discharging time of 0.14 [Formula: see text]s was also achieved. This material is a suitable candidate for power pulsed applications.
Kīlauea–Leilani 2018 lava flow delineation using Sentinel2 and Landsat8 images
Authors: Musacchio Massimo , Silvestri Malvina , Rabuffi Federico , Buongiorno Maria Fabrizia , Falcone Sergio
Published: July 2021

Kīlauea is a broad shield volcano built against the southeastern slope of Mauna Loa. The summit presently has a caldera that is roughly 4 km by 3.2 km wide, and walls between 0 and 120 m high. In late April 2018, an eruption involving both the summit crater and the lower East Rift Zone occurred. In this work a quasi-real-time estimation of the evolution of radiant lava flow extension starting from May 2018 for Kīlauea–Leilani eruption using satellite image data is presented. The active lava flow evolution was obtained using Copernicus Sentinel2 (S2) and USGS-Landsat8 (L8) polar satellites acquiring medium/high-spatial-resolution images (20 × 20 m and 30 × 30 m, respectively) in the vis–SWIR–TIR (Short wave infrared-thermal infra red) spectral range. Because of the Kīlauea eruption extension and duration, a multisensor approach was used in order to improve the timing of the information derived by high-spatial-resolution remote-sensed data merging two missions with different revisit times. The 2018 eruptions at Hawaii's Kīlauea Volcano developed rapidly after the initial activity centred on the Pu‘u ‘Ō‘o crater floor on 1 May followed by draining of the lava lake at Halemáumáu Overlook Crater in the following days. During the magma extrusion from the summit, earthquake swarms and ground cracking hit the Leilani Estates neighbourhood on 2 May. With the S2 and L8 sensors we followed the lava flow from 5 May up to mid August, considering also that the activity started to decline from the beginning of August. At the end of the activity, Kīlauea Volcano had experienced its largest lower East Rift Zone eruption and caldera collapse in at least 200 years.
HyperBench
Authors: Fischl Wolfgang , Gottlob Georg , Longo Davide Mario , Pichler Reinhard
Published: July 2021

To cope with the intractability of answering Conjunctive Queries (CQs) and solving Constraint Satisfaction Problems (CSPs), several notions of hypergraph decompositions have been proposed—giving rise to different notions of width, noticeably, plain, generalized, and fractional hypertree width (hw, ghw, and fhw). Given the increasing interest in using such decomposition methods in practice, a publicly accessible repository of decomposition software, as well as a large set of benchmarks, and a web-accessible workbench for inserting, analyzing, and retrieving hypergraphs are called for.

We address this need by providing (i) concrete implementations of hypergraph decompositions (including new practical algorithms), (ii) a new, comprehensive benchmark of hypergraphs stemming from disparate CQ and CSP collections, and (iii) HyperBench, our new web-interface for accessing the benchmark and the results of our analyses. In addition, we describe a number of actual experiments we carried out with this new infrastructure.
Improving Power of DSP and CNN Hardware Accelerators Using Approximate Floating-point Multipliers
Authors: Leon Vasileios , Paparouni Theodora , Petrongonas Evangelos , Soudris Dimitrios , Pekmestzi Kiamal
Published: July 2021

Approximate computing has emerged as a promising design alternative for delivering power-efficient systems and circuits by exploiting the inherent error resiliency of numerous applications. The current article aims to tackle the increased hardware cost of floating-point multiplication units, which prohibits their usage in embedded computing. We introduce AFMU (Approximate Floating-point MUltiplier), an area/power-efficient family of multipliers, which apply two approximation techniques in the resource-hungry mantissa multiplication and can be seamlessly extended to support dynamic configuration of the approximation levels via gating signals. AFMU offers large accuracy configuration margins, provides negligible logic overhead for dynamic configuration, and detects unexpected results that may arise due to the approximations. Our evaluation shows that AFMU delivers energy gains in the range 3.6%–53.5% for half-precision and 37.2%–82.4% for single-precision, in exchange for mean relative error around 0.05%–3.33% and 0.01%–2.20%, respectively. In comparison with state-of-the-art multipliers, AFMU exhibits up to 4–6× smaller error on average while delivering more energy-efficient computing. The evaluation in image processing shows that AFMU provides sufficient quality of service, i.e., more than 50
db
PSNR and near 1 SSIM values, and up to 57.4% power reduction. When used in floating-point CNNs, the accuracy loss is small (or zero), i.e., up to 5.4% for MNIST and CIFAR-10, in exchange for up to 63.8% power gain.
Practical Wavelet Tree Construction
Authors: Dinklage Patrick , Ellert Jonas , Fischer Johannes , Kurpicz Florian , Löbel Marvin
Published: July 2021

We present new sequential and parallel algorithms for wavelet tree construction based on a new
bottom-up
technique. This technique makes use of the structure of the wavelet trees—refining the characters represented in a node of the tree with increasing depth—in an opposite way, by first computing the leaves (most refined), and then propagating this information upwards to the root of the tree. We first describe new sequential algorithms, both in RAM and external memory. Based on these results, we adapt these algorithms to parallel computers, where we address both shared memory and distributed memory settings.

In practice, all our algorithms outperform previous ones in both time and memory efficiency, because we can compute all auxiliary information solely based on the information we obtained from computing the leaves. Most of our algorithms are also adapted to the wavelet
matrix
, a variant that is particularly suited for large alphabets.
Testing a Quantum Annealer as a Quantum Thermal Sampler
Authors: Izquierdo Zoe Gonzalez , Hen Itay , Albash Tameem
Published: July 2021

Motivated by recent experiments in which specific thermal properties of complex many-body systems were successfully reproduced on a commercially available quantum annealer, we examine the extent to which quantum annealing hardware can reliably sample from the thermal state in a specific basis associated with a target quantum Hamiltonian. We address this question by studying the diagonal thermal properties of the canonical one-dimensional transverse-field Ising model on a D-Wave 2000Q quantum annealing processor. We find that the quantum processor fails to produce the correct expectation values predicted by Quantum Monte Carlo. Comparing to master equation simulations, we find that this discrepancy is best explained by how the measurements at finite transverse fields are enacted on the device. Specifically, measurements at finite transverse field require the system to be quenched from the target Hamiltonian to a Hamiltonian with negligible transverse field, and this quench is too slow. The limitations imposed by such hardware make it an unlikely candidate for thermal sampling, and it remains an open question what thermal expectation values can be robustly estimated in general for arbitrary quantum many-body systems.
Conversation and Culture
Authors: Floyd Simeon
Published: July 2021

Conversation analysis is a method for the systematic study of interaction in terms of a sequential turn-taking system. Research in conversation analysis has traditionally focused on speakers of English, and it is still unclear to what extent the system observed in that research applies to conversation more generally around the world. However, as this method is now being applied to conversation in a broader range of languages, it is increasingly possible to address questions about the nature of interactional diversity across different speech communities. The approach of pragmatic typology first applies sequential analysis to conversation from different speech communities and then compares interactional patterns in ways analogous to how traditional linguistic typology compares morphosyntax. This article discusses contemporary literature in pragmatic typology, including single-language studies and multilanguage comparisons reflecting both qualitative and quantitative methods. This research finds that microanalysis of face-to-face interaction can identify both universal trends and culture-specific interactional tendencies.
A Description of Handgrip Strength in the Very Older Adult People Living in Rural Vietnam and Its Association with Daily Functions
Authors: Nguyen Nga Thi Thuy , Nguyen Thanh Xuan , Nguyen Anh Trung , Nguyen Thu Thi Hoai , Nguyen Tam Ngoc , Nguyen Huong Thi Thu , Nguyen Huong Thi Thanh , Pham Thang , Vu Huyen Thi Thanh
Published: July 2021

Objective. To describe handgrip strength (HGS) and identify associated factors in community‐dwelling older adults in rural Vietnam. Methods. A cross‐sectional study was conducted in community‐dwelling older adults 80 years and over in five rural communities in Hanoi, Vietnam. Age‐gender‐BMI stratified HGS values were reported as means and standard deviations. Demographic characteristics, malnutrition, risk of fall, basic activities of daily living (ADL), and instrumental activities of daily living (IADL) were investigated. Multivariate linear regression explored the association between HGS and these factors. Results. In 308 participants, mean age was 85.4 ± 4.2 years. Mean HGS was 21.6 ± 6.1 kg for males and 15.3 ± 4.3 kg for females. HGS in our sample was generally lower than that in other European countries and Asian threshold. Low HGS was correlated with older age (β = −0.196, p < 0.001), female (β = −0.443, p < 0.001), low education (β = −0.130, p < 0.05), risk of falls (β = −0.114, p < 0.05), and lower IADL (β = 0.153, p = 0.001). Conclusions. The age‐gender‐BMI stratified HGS values of 80 years and over community‐dwellers in rural Vietnam were described. HGS decreased with advanced age, female, low education, high risk of falls, and impaired IADLs. The results could provide useful reference data for further investigations and measures in clinical practice.
The Analysis of Internet Commercial Judicial Based on Big Data Alliance and Mining Service Process Model
Authors: Zhonglong Zhao , Hongliang Wang
Published: July 2021

At present, a series of economic structural changes created by the network economy have brought challenges to the entire economy and society. Traditional social commerce has also suffered severe tests under the background of network economy and global integration, and the rise and development of network commercial activities lack legal constraints. Based on the Big Data technology, in view of the characteristics of data mining services, this paper expands and changes the traditional model and proposes the Big Data alliance data mining service process model. Moreover, this paper uses intelligent decision‐making theory and knowledge reasoning methods to construct a fast‐responding, service‐reusable, and intelligent service model to realize the scalability of data mining services. In addition, this paper constructs system function modules according to the requirements of Internet commercial judicial data mining and verifies the performance of the system constructed in this paper through experimental analysis. The research results show that the system constructed in this paper has certain practical effects.
Equestrian Sports Posture Information Detection and Information Service Resource Aggregation System Based on Mobile Edge Computing
Authors: Wu Zhong , Zhou Chuan
Published: July 2021

Equestrianism is a special sport. Equestrian sports have become popular in people’s lives and have also developed rapidly in our country, becoming a trend. This paper aims to study the equestrian sports posture information detection and information service resource aggregation system based on mobile edge computing. The research of equestrian sports can greatly promote future development. For this reason, we use the power of science and technology to study the equestrian sports posture and make an equestrian sports posture information detection system. The system is designed to feed back the riding posture in real time and can provide equestrian athletes with a more scientific and healthier equestrian training posture. In order to fully verify the practicability of the system, at the end of the forum, the performance of the entire monitoring platform was tested, and three tests were designed, respectively: packet loss rate test, driving test, and riding test. The driving test proves the validity of data transmission, and the riding test proves the practicability of the monitoring platform’s functions. The test results show that the maximum data packet loss rate is 0.6%, which can fully confirm that the monitoring platform has sufficient technical practicability, no problems have been found in practical applications, and it has good market and application prospects.
Probiotics Fermentation Technology, a Novel Kefir Product, Ameliorates Cognitive Impairment in Streptozotocin‐Induced Sporadic Alzheimer’s Disease in Mice
Authors: El Sayed Nesrine S. , Kandil Esraa A. , Ghoneum Mamdooh H.
Published: July 2021

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by cognitive impairment. Gut microbiota dysfunction (dysbiosis) is implicated in the pathology of AD and is associated with several detrimental consequences, including neurotransmitter depletion, oxidative stress, inflammation, apoptosis, and insulin resistance, which all contribute to the onset of AD. The objective of this study was to assess the effectiveness of Probiotics Fermentation Technology (PFT), a kefir product, in alleviating AD symptoms via regulation of the gut microbiota using a streptozotocin‐ (STZ‐) induced AD mouse model and to compare its activity with simvastatin, which has been proven to effectively treat AD. Mice received one intracerebroventricular injection of STZ (3 mg/kg). PFT (100, 300, 600 mg/kg) and simvastatin (20 mg/kg) were administered orally for 3 weeks. PFT supplementation mitigated STZ‐induced neuronal degeneration in the cortex and hippocampus, restored hippocampal acetylcholine levels, and improved cognition in a dose‐dependent manner. These effects were accompanied by reductions in oxidative damage, proinflammatory cytokine expression, apoptosis, and tau hyperphosphorylation. Moreover, PFT hindered amyloid plaque accumulation via the enhancement of insulin‐degrading enzyme. These beneficial effects were comparable to those produced by simvastatin. The results suggest that PFT can alleviate AD symptoms by regulating the gut microbiota and by inhibiting AD‐related pathological events.
Application of Ensemble Learning Using Weight Voting Protocol in the Prediction of Pile Bearing Capacity
Authors: Pham Tuan Anh , Vu Huong-Lan Thi
Published: July 2021

Accurate prediction of pile bearing capacity is an important part of foundation engineering. Notably, the determination of pile bearing capacity through an in situ load test is costly and time-consuming. Therefore, this study focused on developing a machine learning algorithm, namely, Ensemble Learning (EL), using weight voting protocol of three base machine learning algorithms, gradient boosting (GB), random forest (RF), and classic linear regression (LR), to predict the bearing capacity of the pile. Data includes 108 pile load tests under different conditions used for model training and testing. Performance evaluation indicators such as R-square (R2), root mean square error (RMSE), and MAE (mean absolute error) were used to evaluate the performance of models showing the efficiency of predicting pile bearing capacity with outstanding performance compared to other models. The results also showed that the EL model with a weight combination of

w

1

 = 0.482,

w

2

 = 0.338, and

w

3

 = 0.18 corresponding to the models GB, RF, and LR gave the best performance and achieved the best balance on all data sets. In addition, the global sensitivity analysis technique was used to detect the most important input features in determining the bearing capacity of the pile. This study provides an effective tool to predict pile load capacity with expert performance.
Analysis of Seepage and Displacement Field Evolutionary Characteristics in Water Inrush Disaster Process of Karst Tunnel
Authors: Lai Yongbiao , Li Shuo , Guo Jiaqi , Zhu Zhengguo , Huang Xin
Published: July 2021

Water inrush of tunnel is one of the most common geological disasters in the karst strata in China. Aiming at the rock mass with a quasi-masonry structure in the water-resistant strata between karst cavity with high pressure water and tunnel and the shortcomings of theoretical analysis, traditional numerical simulation, and physics model test for describing and reflecting this special structure of rock mass, a Discrete Element Method considering the fluid-solid coupling effect and structural characteristics of rock mass is employed to study the disaster process of water inrush and the evolutionary characteristics of catastrophe information like seepage pressure and displacement under condition of different karst water pressure, tunnel depth, and lateral pressure coefficient. Research results show the following: (1) the seepage pressure and displacement increase with the increase of kart water pressure. The seepage pressure demonstrates a decreasing state from top to bottom in water-resistant strata, and the time of arrival to a stable value for the seepage pressure shows the time effect. (2) The larger the tunnel depth, the greater the coalescence and distribution scope of fracture and the more likely the water inrush to occur in a short time. The stability of water-resistant strata decreases on the whole with the growth of tunnel depth. (3) The increase of lateral pressure coefficient can restrain the fracture development and strengthen stability. The fracture state is significantly influenced by a lateral pressure coefficient. The results of numerical simulation are consistent with those obtained by a model test. Research and analysis based on energy are a promising train of thought for studying the disaster process of water inrush in a karst tunnel.
Extreme-Point Symmetric Mode Decomposition to Define the Turbulence Characteristics of a Flume Flow
Authors: Shi Zhi-Peng , He Ting-Ting , Zhang Gen-Guang
Published: July 2021

Turbulence is a key feature of solid-liquid two-phase flows, and the pulsating velocity is the basis for calculating turbulence characteristics. In general, the method of mathematical expectation is used to calculate pulsating velocity. However, this method does not reflect the fluctuating state of the instantaneous velocity. Therefore, the method of extreme-point symmetric mode decomposition (ESMD) is adopted to calculate pulsating velocity and turbulence characteristics. The ESMD involves two stages, namely, modal decomposition and time-frequency analysis. The optimal adaptive global mean (AGM), which is the result of modal decomposition, can accurately reflect the fluctuation state of the instantaneous velocity, and the theory of the pulsating velocity defined on this basis is reasonable. Moreover, the flow pattern and turbulence behaviour of a two-phase flow can be predicted using the calculated turbulence characteristics. The method is used to analyse the pulsating velocity of the flume, and its rationality in theoretically predicting the turbulence behaviour of flume flows is demonstrated.
Cross-Individual Gesture Recognition Based on Long Short-Term Memory Networks
Authors: Min Huasong , Chen Ziming , Fang Bin , Xia Ziwei , Song Yixu , Wang Zongtao , Zhou Quan , Sun Fuchun , Liu Chunfang
Published: July 2021

Gestures recognition based on surface electromyography (sEMG) has been widely used for human-computer interaction. However, there are few research studies on overcoming the influence of physiological factors among different individuals. In this paper, a cross-individual gesture recognition method based on long short-term memory (LSTM) networks is proposed, named cross-individual LSTM (CI-LSTM). CI-LSTM has a dual-network structure, including a gesture recognition module and an individual recognition module. By designing the loss function, the individual information recognition module assists the gesture recognition module to train, which tends to orthogonalize the gesture features and individual features to minimize the impact of individual information differences on gesture recognition. Through cross-individual gesture recognition experiments, it is verified that compared with other selected algorithm models, the recognition accuracy obtained by using the CI-LSTM model can be improved by an average of 9.15%. Compared with other models, CI-LSTM can overcome the influence of individual characteristics and complete the task of cross-individual hand gestures recognition. Based on the proposed model, online control of the prosthetic hand is realized.
Flexural Fatigue Behaviors of Silicon Carbide Recycled Concrete in Corrosive Environments
Authors: Zhou Jinzhi , Fu Tiantian , Zhong Chuheng , Peng Kun , Shuang Ziyang
Published: July 2021

An experimental study on the flexural fatigue behaviors of recycled concrete (RC) and silicon carbide recycled concrete (SiCRC) was conducted. The immersion time was 0 d, 30 d, 60 d, and 90 d in 5% NaCl solution for these two kinds of recycled concrete specimens, respectively, and then, four‐point flexural fatigue tests were performed by MTS fatigue testing machine. The fatigue life for varying stress levels ranging from 0.9 to 0.6 was obtained. The fatigue life was given considering the failure probability according to the fatigue life and stress level of the specimen via the logarithmic normal distribution and Weibull distribution, respectively. The relationship between fatigue life and failure probability was also obtained. The fatigue life with failure probability of 1% and 50% was further predicted. The results showed that the fatigue life of RC and SiCRC increased in corrosive environments. The fatigue life of SiCRC is higher than that of RC, and the incorporation of SiCRC can improve the fatigue life of recycled concrete.
Astrocytes in the Ventromedial Hypothalamus Involve Chronic Stress-Induced Anxiety and Bone Loss in Mice
Authors: Liu Yunhui , Shao Jie , Gao Dashuang , Zhang Lu , Yang Fan
Published: July 2021

Chronic stress is one of the main risk factors of bone loss. While the neurons and neural circuits of the ventromedial hypothalamus (VMH) mediate bone loss induced by chronic stress, the detailed intrinsic mechanisms within the VMH nucleus still need to be explored. Astrocytes in brain regions play important roles in the regulation of metabolism and anxiety-like behavior through interactions with surrounding neurons. However, whether astrocytes in the VMH affect neuronal activity and therefore regulate chronic stress-induced anxiety and bone loss remain elusive. In this study, we found that VMH astrocytes were activated during chronic stress-induced anxiety and bone loss. Pharmacogenetic activation of the Gi and Gq pathways in VMH astrocytes reduced and increased the levels of anxiety and bone loss, respectively. Furthermore, activation of VMH astrocytes by optogenetics induced depolarization in neighboring steroidogenic factor-1 (SF-1) neurons, which was diminished by administration of N-methyl-D-aspartic acid (NMDA) receptor blocker but not by alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor blocker. These results suggest that there may be a functional “glial-neuron microcircuit” in VMH nuclei that mediates anxiety and bone loss induced by chronic stress. This study not only advances our understanding of glial cell function but also provides a potential intervention target for chronic stress-induced anxiety and bone loss therapy.
Iterative Construction of Fixed Points for Operators Endowed with Condition

E

in Metric Spaces
Authors: Ahmad Junaid , Ullah Kifayat , Işik Hüseyin , Arshad Muhammad , de la Sen Manuel
Published: July 2021

We consider the class of mappings endowed with the condition

E

in a nonlinear domain called 2-uniformly convex hyperbolic space. We provide some strong and

Δ

-convergence theorems for this class of mappings under the Agarwal iterative process. In order to support the main outcome, we procure an example of mappings endowed with the condition

E

and prove that its Agarwal iterative process is more effective than Mann and Ishikawa iterative processes. Simultaneously, our results hold in uniformly convex Banach, CAT(0), and some CAT(

κ

) spaces. This approach essentially provides a new setting for researchers who are working on the iterative procedures in fixed point theory and applications.
GT-Bidding: Group Trust Model of P2P Network Based on Bidding
Authors: Zhang Lin , Wei Xinyan , Huang Yanwen , Huang Haiping , Fu Xiong , Wang Ruchuan
Published: July 2021

Due to the lack of trusted third parties as guarantees in peer-to-peer (P2P) networks, how to ensure trusted transactions between peers has become a research hotspot. However, the open and distributed characteristics of P2P networks have brought challenges to network security, and there are problems such as node fraud and unavailability of services in the network. To solve the problem of how to select trusted transaction peers in P2P groups, a new trust model, GT-Bidding, is proposed in this paper. This model follows the bidding process of human society. First, each service peer applies for a group of guarantee peers and carries out credit mortgages for this service. Second, based on the entropy and TOPSIS method (Technology for Order Preference by Similarity to an Ideal Solution) approaching the ideal solution, a set of ideal trading sequences is selected. Then, the transaction impact function is used to assign weights to the selected guarantee peers and service nodes, respectively; thus, the comprehensive trust of each service node can be calculated. Finally, the service peer is verified using feedback based on the specific confidence level, which encourages the reputation of the service and its guarantee peers to update. Experiments show that GT-Bidding improves the successful transaction rate and resists complex attacks.
Artemisinin-Based Combination Therapy Synergized with Medicinal Plants to Induce Musculotoxic Effects
Authors: Daubrey-Potey Thérèse , Adjogoua Valéry , Kamagaté Mamadou , Aoussi Serges , Dosso Mireille
Published: July 2021

Introduction. Multivisceral, neurological, hepatic, and renal damage has been witnessed following the use of artemisinin-based combination therapy (ACT) and herbal medicine. These multiple organ damages make us think of muscle damage. The objective was to study the myotoxicity of the combination of ACTs with medicinal plants. Materials and Methods. Muscle cells (RD cells) were brought into contact with preparations of antimalarial drugs and/or antimalarial herbs. The following drugs were used: artesunate 100 mg/amodiaquine 270 mg (ASAQ) and artemether 80 mg/lumefantrine 480 mg (AL); plant Sida acuta (PSA) and plant Enantia polycarpa (PEP) at 10 µg/ml. After 5 days of incubation, the cells were counted by using a hemocytometer with trypan blue solution. Results. Artesunate/amodiaquine caused a significant drop in the number of muscle cells, compared to the control, between D2 and D4 (

p

 < 0.001). There was also a significant difference between the control and artemether/lumefantrine between D2 (

p

 < 0.01) and D4 (

p

 < 0.001) and between the control and the Sida acuta plant, on D2 (

p

 < 0.001), D4 (

p

 < 0.001), and D5 (

p

 < 0.05). In tubes treated with ASAQ and Sida acuta, cell mortality was over 30%. Finally, statistically significant cell destruction in the tubes treated with the combination of antimalarial drugs and traditional plants compared to those of the control was observed from D2 (

p

 < 0.001). Conclusion. Artemisinin-based combination therapy remains effective and well tolerated. But its combination with medicinal plants induced myotoxic effects. This toxicity would appear to be of the additive type. Further studies should be able to better elucidate the mechanism of this toxicity.
POI Recommendation Method Using Deep Learning in Location‐Based Social Networks
Authors: Liu Yang , Wu An-bo
Published: July 2021

To solve the problems of large data sparsity and lack of negative samples in most point of interest (POI) recommendation methods, a POI recommendation method based on deep learning in location‐based social networks is proposed. Firstly, a bidirectional long‐short‐term memory (Bi‐LSTM) attention mechanism is designed to give different weights to different parts of the current sequence according to users’ long‐term and short‐term preferences. Then, the POI recommendation model is constructed, the sequence state data of the encoder is input into Bi‐LSTM‐Attention to get the attention representation of the current POI check‐in sequence, and the Top‐N recommendation list is generated after the decoder processing. Finally, a negative sampling method is proposed to obtain an effective negative sample set, which is used to improve the calculation of the Bayesian personalized ranking loss function. The proposed method is demonstrated experimentally on Foursquare and Gowalla datasets. The experimental results show that the proposed method has better accuracy, recall, and F1 value than other comparison methods.
Extracorporeal Shockwave Therapy Modulates the Expressions of Proinflammatory Cytokines IL33 and IL17A, and Their Receptors ST2 and IL17RA, within the Articular Cartilage in Early Avascular Necrosis of the Femoral Head in a Rat Model
Authors: Cheng Jai-Hong , Jhan Shun-Wun , Hsu Chieh-Cheng , Chiu Hung-Wen , Hsu Shan-Ling
Published: July 2021

Avascular necrosis (AVN) of the femoral head (AVNFH) is a disease caused by injury to the blood supply of the femoral head, resulting in a collapse with osteonecrosis and damage to the articular cartilage. Extracorporeal shockwave therapy (ESWT) has been demonstrated to improve AVNFH owing to its anti-inflammation activity, angiogenesis effect, and tissue regeneration in clinical treatment. However, there are still so many pieces of the jigsaw that need to be fit into place in order to ascertain the mechanism of ESWT for the treatment of AVNFH. The study demonstrated that ESWT significantly protected the trabecular bone volume fraction BV/TV (

P
<
0.01

) and the trabecular thickness (

P
<
0.001

), while in contrast, the trabecular number and trabecular separation were not significantly different after treatment as compared with AVNFH. ESWT protected the articular cartilage in animal model of AVNFH. The levels of IL1-β and IL33 were significantly induced in the AVNFH group (

P
<
0.001

) as compared with Sham and ESWT groups and reduced in ESWT group (

P
<
0.001

) as compared with AVNFH group. In addition, the expression of the receptor of IL33, ST2, was reduced in AVNFH and induced after ESWT (

P
<
0.001

). The expression of IL17A was induced in the AVNFH group (

P
<
0.001

) and reduced in the ESWT group (

P
<
0.001

). Further, the expression of the receptor of IL17A, IL17RA, was reduced in the AVNFH group (

P
<
0.001

) and improved to a normal level in the ESWT group as compared with Sham group (

P
<
0.001

). Taken together, the results of the study indicated that ESWT modulated the expression of IL1-β, pro-inflammatory cytokines IL33 and IL17A, and their receptors ST2 and IL17RA, to protect against loss of the extracellular matrix in the articular cartilage of early AVNFH.
[Retracted] Effects of Aspirin on Myocardial Ischemia‐Reperfusion Injury in Rats through STAT3 Signaling Pathway
Authors: Wu Zhenjun , Li Xuewen , Li Xiuyue , Yu Lihua
Published: July 2021

Objective. To investigate the role and mechanism of aspirin in myocardial injury induced by myocardial ischemia‐reperfusion in rats through STAT3 signaling pathway. Methods. Sixty rats were randomly divided into three groups: the sham operation group, MI/R group, and MI/R+aspirin group (aspirin group). The rats in the sham operation group did not ligate the LAD coronary artery, while the aspirin group ligated the LAD coronary artery, which caused the suture to be loosened after 30 minutes ischemia, and 60 mg/kg aspirin was injected into the tail vein 10 minutes before reperfusion. After three hours of reperfusion, the ultrasound system was used to collect hemodynamic parameters, including ejection fraction (EF%), shortening fraction (FS%), and left ventricular end‐systolic pressure (LVESP%) and left ventricular end‐diastolic pressure (LVEDP%). Finally, the rats were euthanized; then, blood samples were taken for biochemical examination, myocardial tissue was collected, and the left ventricle was used for subsequent experiments. The gene expression levels of Bax and Bcl‐2 were detected by PCR. The protein expression levels of Bcl‐2, Bax, p‐JAK2, total JAK2, p‐STAT3, and total STAT3 were detected by Western blot. Results. Compared with the sham operation group and the aspirin group, the area of myocardial infarction in the MI/R was significantly increased (p < 0.05). In terms of hemodynamic parameters, LVEDP was significantly elevated in the MI/R group. The results of PCR showed that compared with the MI/R group, the mRNA expression of Bax in the aspirin group was significantly decreased, while that of Bcl‐2 was significantly increased (p < 0.05). Western blot analysis showed that compared with the MI/R group, aspirin pretreatment significantly increased the expression levels of p‐STAT3 and p‐JAK2 (p < 0.05). Conclusion. The mechanism of aspirin preconditioning to protect the heart from MI/R injury appears to be related to JAK2/STAT3 and related to the activation of the signaling pathway.
Investigations on Internal Ballistic Characteristics of Pasty Propellant Rocket Engine
Authors: Shan Xinyou , Li Yingkun , Chen Xiong , Wu Yan , He Yong , Li Weixuan
Published: July 2021

Pasty rocket engines have broad application prospects in the aerospace field. To study the internal ballistic characteristics of the pasty propellant rocket engine, the burning surface change model of pasty propellant was built. The calculation program was developed to calculate the pressure evolution in the combustion chamber, and the experiment was carried out based on a pasty propellant rocket test system. The data calculated by the program are in good agreement with the experiment, the error of the initial pressure peak is only 4.02%, and the internal ballistic characteristics of the rocket engine at each stage were analyzed detailly. The effects of ignition delay time, transport pipeline structure, free volume of the combustion chamber, mass flow rate, and flow velocity of the pasty propellant on internal ballistic characteristics of the pasty propellant rocket engine are investigated. The results indicate that when the ignition delay time increases, the pressure rises faster and the initial pressure peak increases obviously. The transport pipe diameter changes from 11.3 mm to 7.4 mm, and the initial combustion time and residual propellant combustion time decreased by 41.3% and 36.0%. The reduction of the free volume of the combustion chamber can reduce the initial pressure peak and the time to reach the equilibrium pressure. The initial pressure spike and equilibrium pressure rise with the increase of the pasty propellant flow velocity. While the ignition transient decreased with the increase of the pasty propellant flow velocity. The internal ballistic properties can be improved by reducing the ignition delay time, the diameter of the transport pipeline, and the free volume of the combustion chamber, or by increasing the mass flow rate of the pasty propellant rocket engine.
Analysis of the Contribution of Intellectual Capital to Economic Growth Based on an Empirical Analysis of Prefecture-Level Cities in Guangxi
Authors: Zeng Qun , Tan ZhenHai , Liu Chunnian
Published: July 2021

The purpose of this paper is to explore the reasons for the differences in intellectual capital between regions and put forward reasonable suggestions for regional economic development through the use of an intellectual capital measurement model. Based on a sample of 14 cities in Guangxi in 2017, this work builds a set of indicator systems to evaluate intellectual capital contributions. First, the comprehensive intellectual capital score of each region is calculated, and the principal component analysis is used to analyze three elements. Second, a regression equation model between the regional intellectual capital and the regional economic status indicator—GDP—is established, and a descriptive statistical test, a correlation test, and a robustness test are carried out on the model. This work finds that the three major factors of regional intellectual capital have positive effects on the level of regional economic development, among which the contribution of regional structural capital to economic development is the largest, reaching more than 50%, followed by human capital, and, finally, relational capital. The unbalanced characteristics of intellectual capital between cities are quite prominent, and thus, the alleviation of the unbalanced development of cities has become a problem that must be urgently addressed. Structural capital has the highest impact on GDP of all types of capital, with government income from structural capital accounting for more than half of total incomes.
PPARα Agonist Fenofibrate Enhances Cancer Vaccine Efficacy
Authors: Chekaoui Arezki , Ertl Hildegund C.J.
Published: July 2021

Reducing metabolic stress within the tumor microenvironment (TME) could be essential for improving the efficacy of cancer immunotherapy. Using a mouse model of melanoma, we show here that appropriately timed treatment with the PPARα agonist fenofibrate improves the ability of a T cell–inducing cancer vaccine to delay tumor progression. Fenofibrate reduced the use of glucose by tumor and stromal cells in the TME and promoted the use of fatty acids for their metabolic needs. The glucose within the TME was in turn available for use by vaccine-induced tumor-infiltrating CD8+ T cells, which improved their ability to slow tumor progression. Early fenofibrate treatment 3 days after vaccination improved functions of circulating CD8+ T cells but failed to significantly affect tumor-infiltrating lymphocyte (TIL) metabolism or decrease tumor progression. In contrast, delaying treatment until day 5 after vaccination modified TIL metabolism and augmented the vaccine's ability to slow tumor progression. In summary, our findings reveal that a PPARα agonist can increase the efficacy of a cancer vaccine by reprogramming cells within tumors to increase fatty acid metabolism, providing T cells access to glucose in the TME.

Significance:

These findings suggest that metabolic manipulations using already approved drugs may offer an easy pathway to increase the efficacy of vaccines against solid tumors.
Change in Blood and Benign Breast Biomarkers in Women Undergoing a Weight-Loss Intervention Randomized to High-Dose ω-3 Fatty Acids versus Placebo
Authors: Fabian Carol J. , Befort Christie A. , Phillips Teresa A. , Nydegger Jennifer L. , Kreutzjans Amy L. , Powers Kandy R. , Metheny Trina , Klemp Jennifer R. , Carlson Susan E. , Sullivan Debra K. , Zalles Carola M. , Giles Erin D. , Hursting Stephen D. , Hu Jinxiang , Kimler Bruce F.
Published: July 2021

The inflammation-resolving and insulin-sensitizing properties of eicosapentaenoic (EPA) and docosahexaenoic (DHA) fatty acids have potential to augment effects of weight loss on breast cancer risk. In a feasibility study, 46 peri/postmenopausal women at increased risk for breast cancer with a body mass index (BMI) of 28 kg/m2 or greater were randomized to 3.25 g/day combined EPA and DHA (ω-3-FA) or placebo concomitantly with initiation of a weight-loss intervention. Forty-five women started the intervention. Study discontinuation for women randomized to ω-3-FA and initiating the weight-loss intervention was 9% at 6 months and thus satisfied our main endpoint, which was feasibility. Between baseline and 6 months significant change (P < 0.05) was observed in 12 of 25 serum metabolic markers associated with breast cancer risk for women randomized to ω-3-FA, but only four for those randomized to placebo. Weight loss (median of 10% for trial initiators and 12% for the 42 completing 6 months) had a significant impact on biomarker modulation. Median loss was similar for placebo (−11%) and ω-3-FA (−13%). No significant change between ω-3-FA and placebo was observed for individual biomarkers, likely due to sample size and effect of weight loss. Women randomized to ω-3-FA exhibiting more than 10% weight loss at 6 months showed greatest biomarker improvement including 6- and 12-month serum adiponectin, insulin, omentin, and C-reactive protein (CRP), and 12-month tissue adiponectin. Given the importance of a favorable adipokine profile in countering the prooncogenic effects of obesity, further evaluation of high-dose ω-3-FA during a weight-loss intervention in obese high-risk women should be considered.

Prevention Relevance:

This study examines biomarkers of response that may be modulated by omega-3 fatty acids when combined with a weight-loss intervention. While focused on obese, postmenopausal women at high risk for development of breast cancer, the findings are applicable to other cancers studied in clinical prevention trials.