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The swimming start, which involves interactions with both water and air, has predominantly been studied primarily in terms of spatio-temporal parameters, while its motor control aspects have received limited attention. This study aims to investigate and compare the coordination patterns between the arm and trunk, as well as the thigh and trunk, in S9, S10, and S12 Paralympic swimmers using the continuous relative phase. The study included twenty-one Paralympic swimmers, and the results showed significant differences (p < 0.05) from spm1d (ANOVA) in both arm-trunk and thigh-trunk CRP among the three classes of swimmers. Significant differences were observed in the arm-trunk CRP during the initial (0–8% of time) and end (30–41% of time) parts of the block phase. Both of these two differences are from the comparison of S10 and S12. The thigh-trunk CRP also showed significant differences at the end of the block phase (35–41% of time) and during the flight phase before entry (58–61% of time). Significant differences were observed in post hoc tests between S9 and S10 and between S12 and S10 for the first significant difference. The second significant difference was found between S12 and S10. The results indicate that Paralympic swimmers classified as S9, S10, and S12 tend to exhibit distinct inter-segmental coordination patterns during the dive start. By recognizing different patterns of motor coordination, coaches and trainers can develop individualized training methods to optimize the start performance for swimmers with different impairments (different classifications) and maximize their competitive potential.

Felines have significant advantages in terms of sports energy efficiency and flexibility compared with other animals, especially in terms of jumping and landing. The biomechanical characteristics of a feline (cat) landing from different heights can provide new insights into bionic robot design based on research results and the needs of bionic engineering. The purpose of this work was to investigate the adaptive motion adjustment strategy of the cat landing using a machine learning algorithm and finite element analysis (FEA). In a bionic robot, there are considerations in the design of the mechanical legs. (1) The coordination mechanism of each joint should be adjusted intelligently according to the force at the bottom of each mechanical leg. Specifically, with the increase in force at the bottom of the mechanical leg, the main joint bearing the impact load gradually shifts from the distal joint to the proximal joint; (2) the hardness of the materials located around the center of each joint of the bionic mechanical leg should be strengthened to increase service life; (3) the center of gravity of the robot should be lowered and the robot posture should be kept forward as far as possible to reduce machine wear and improve robot operational accuracy.

The information dissemination index system is an effective way to measure the dissemination of public opinion events in social networks. Due to the complexity, variability, and asymmetry of information, the construction of traditional information dissemination index systems demands excessive reliance on manual intervention, has large deviations, and is applied in a limited range. Such shortcomings cannot meet the requirements of constructing an objective, comprehensive, and highly credible index system. Therefore, we propose a method of constructing a multilevel and multigranular information dissemination index system with complex perspectives. In addition, we use the deep learning method of the convolutional neural network to extract the rich convolution features of public opinion events in the information dissemination process. Then, we train the weight, and it forms the corresponding weight of the information dissemination index systems. The experimental results prove that the method we use is superior to other methods and has better performance on the data set of a specific field.

Eukaryotic topoisomerase 1 (TOP1) regulates DNA topology to ensure efficient DNA replication and transcription. Here, the authors reveal insights into the molecular resolution of topoisomerase 1-DNA adducts by TEX264, p97 and SPRTN.

Summary: Inhibitors of Mek1/2 and Gsk3β, known as 2i, and, together with leukemia inhibitory factor, enhance the derivation of embryonic stem cells (ESCs) and promote ground-state pluripotency (2i/L-ESCs). However, recent reports show that prolonged Mek1/2 suppression impairs developmental potential of ESCs, and is rescued by serum (S/L-ESCs). Here, we show that culturing ESCs in Activin A and BMP4, and in the absence of MEK1/2 inhibitor (ABC/L medium), establishes advanced stem cells derived from ESCs (esASCs). We demonstrate that esASCs contributed to germline lineages, full-term chimeras and generated esASC-derived mice by tetraploid complementation. We show that, in contrast to 2i/L-ESCs, esASCs display distinct molecular signatures and a stable hypermethylated epigenome, which is reversible and similar to serum-cultured ESCs. Importantly, we also derived novel ASCs (blASCs) from blastocysts in ABC/L medium. Our results provide insights into the derivation of novel ESCs with DNA hypermethylation from blastocysts in chemically defined medium. : In this article, Bao and colleagues show that ASCs cultured in Activin A and BMP4, and in the absence of MEK1/2 inhibitor, possess reversible epigenetic changes that extend their developmental potency, distinct transcriptome pattern, and a stable hypermethylated epigenome. Importantly, they also derived novel hypermethylated ASCs from blastocysts in ABC/L medium. Keywords: mouse, embryonic stem cells, epigenetics, hypermethylation, development, chemically defined, genomic imprinting, blastocyst, pluripotency, implantation

Edge computing is a research hotspot that extends cloud computing to the edge of the network. Due to the recent developments in computation, storage and network technology for end devices, edge networks have become more powerful, making it possible to integrate locator/identity separation protocol (LISP) into these networks. Accordingly, in this paper, we introduce LISP into edge routers at the edge network, focusing primarily on the delay problem of mapping resolution and cache updating in LISP with the help of edge computing. To solve this delay problem, we first analyze the communication process of the locator/identity separation network and consider using the prediction method to underpin this research. In order to achieve a good prediction result, we propose and implement a Fixed Identity Mapping Prediction Algorithm (FIMPA) based on collaborative filtering, and further verify the effectiveness of the proposed algorithm through experiments on real-world data.

It is essential for patients with hypertension to effectively reduce and maintain appropriate blood pressure levels. As one of the non-pharmacological and invasive methods, physical exercise seems to improve blood pressure of the patients with hypertension. However, different volumes and intensities of physical exercise on the improvement of hypertension are different. To understand the effects of the type of exercise training on blood pressure and the other health status of patients with hypertension, a network meta-analysis was used to compare the mixed effects of different types of exercise training. This systematic review includes all eligible randomized controlled trials of PubMed, Medline, Cochrane Library, and CINAHL. Twelve studies met the inclusion criteria (n = 846 participants at the end of the study). The results show that a medium-intensity training (MIT) is best in improving the blood pressure of patients with hypertension, while a high-volume high-intensity interval training (HVHIIT) is better in reducing body mass and resting heart rate. In addition, the analysis of the exercise capacity shows that HVHIIT has a better effect on the improvement of patients with hypertension. Noticeably, long-term high-volume and appropriate intensity exercise can effectively improve the health status of patients with hypertension. In short, for patients with high blood pressure, MIT seems to be better at lowering blood pressure, while HVHIIT can better improve exercise ability and physical fitness. However, larger randomized controlled trials with a longer duration than those included in this meta-analysis are needed to confirm these results.

The therapeutic benefit of high heel shoes (HHS) for plantar fasciitis treatment is controversial. It has been suggested that plantar fascia strain can be decreased by heel elevation of shoes which helps in body weight redistribution throughout the length of the foot. Yet it is a fact that the repetitive tension caused by HHS wearing resulting in plantar fasciitis is a high-risk disease in HHS individuals who suffer heel and plantar pain. To explore the biomechanical function on plantar fascia under HHS conditions, in this study, musculoskeletal modeling (MsM) and finite element method (FEM) were used to investigate the effect of heel height on strain distribution of plantar fascia. Three-dimensional (3D) and one-dimensional (1D) finite element models of plantar fascia were generated to analyze the computed strain variation in 3-, 5-, and 7-cm heel heights. For validation, the computed foot contact pressure was compared with experimental measurement, and the strain value on 1D fascia was compared with previous studies. Results showed that the peak strain of plantar fascia was progressively increased on both 3D and 1D plantar fascia as heel elevated from 3 to 7 cm, and the maximum strain of plantar fascia occurs near the heel pain site at second peak stance. The 3D fascia model predicted a higher strain magnitude than that of 1D and provided a more reliable strain distribution on the plantar fascia. It is concluded that HHS with narrow heel support could pose a high risk on plantar fasciitis development, rather than reducing symptoms. Therefore, the heel elevation as a treatment recommendation for plantar fasciitis is questionable. Further studies of different heel support structures of shoes to quantify the effectiveness of heel elevation on the load-bearing mechanism of plantar fascia are recommended.

Malware has become a major threat to cyberspace security, not only because of the increasing complexity of malware itself, but also because of the continuously created and produced malicious code. In this paper, we propose two novel methods to solve the malware identification problem. One is to solve to malware classification. Different from traditional machine learning, our method introduces the ensemble models to solve the malware classification problem. The other is to solve malware family clustering. Different from the classic malware family clustering algorithm, our method introduces the t-SNE algorithm to visualize the feature data and then determines the number of malware families. The two proposed novel methods have been extensively tested on a large number of real-world malware samples. The results show that the first one is far superior to the existed individual models and the second one has a good adaptation ability. Our methods can be used for malicious code classification and family clustering, also with higher accuracy.

Abstract Background Tracheomalacia (TM), caused by anterior mediastinal tumorectomy, most likely to deteriorate condition of patient life. Case presentation A 63-year-old patient felt serious dyspnea diagnosis as TM caused by the recurrent cervical schwannoma. The narrowest diameter of the TM was only 0.446 cm and the length of malacic segment was 7.47 cm. Here we designed a novel tracheal suspension technique by using autogenous rib cartilage graft to treat severe TM. The obvious effect was observed that the inner diameter increased from 0.446 cm to 1.390 cm,and the airway symptom was alleviated. Conclusion The autogenous rib cartilage graft used for suspending the malacic trachea was safe and effective.

The explosive data growth in smart city is making domain big data a hot topic for knowledge extraction. Non-taxonomic relations refer to any relations between concept pairs except the is-a relation, which is an important part of Knowledge Graph. In this paper, toward big data in smart city, we present a multi-phase correlation search framework to automatically extract non-taxonomic relations from domain documents. Different kinds of semantic information are used to improve the performance of the system. First, inspired by the works of network representation; we propose a Semantic Graph-Based method to combine structure information of semantic graph and context information of terms together for nontaxonomic relationships identification. Second, different semantic types of verb sets are extracted based on the dependency syntactic information, which are ranked to act as non-taxonomic relationship labels. Extensive experiments demonstrate the efficiency of the proposed framework. The F1 value reaches 81.4% for identification of non-taxonomic relationships. The total precision of the non-taxonomic relationship labels extraction is 73.4%, and 87.8% non-taxonomic relations can be provided with “good”labels. We hope this article can provide a useful way for domain big data knowledge extraction in smart city.

Kinematics data are primary biomechanical parameters. A principal component analysis (PCA) of waveforms is a statistical approach used to explore patterns of variability in biomechanical curve datasets. Differences in experienced and recreational runners’ kinematic variables are still unclear. The purpose of the present study was to compare any differences in kinematics parameters for competitive runners and recreational runners using principal component analysis in the sagittal plane, frontal plane and transverse plane. Forty male runners were divided into two groups: twenty competitive runners and twenty recreational runners. A Vicon Motion System (Vicon Metrics Ltd., Oxford, UK) captured three-dimensional kinematics data during running at 3.3 m/s. The principal component analysis was used to determine the dominating variation in this model. Then, the principal component scores retained the first three principal components and were analyzed using independent t-tests. The recreational runners were found to have a smaller dorsiflexion angle, initial dorsiflexion contact angle, ankle inversion, knee adduction, range motion in the frontal knee plane and hip frontal plane. The running kinematics data were influenced by running experience. The findings from the study provide a better understanding of the kinematics variables for competitive and recreational runners. Thus, these findings might have implications for reducing running injury and improving running performance.

High-heeled shoes increase the difficulty of maintaining balance. The aim of this study was to evaluate the dynamic posture control when wearing high-heeled shoes using star excursion balance test (SEBT) in combination of plantar pressure measurement. 20 healthy young females volunteered to participate in the test. Participants completed the modified three directions including anterior, posteromedial, and posterolateral in the SEBT. Three different types of shoes were used: Flat (0.8 cm), Low (4.0 cm), High (6.6 cm). A Novel Pedar insole system was used to measure peak pressure, contact area and pressure-time integral of the stance limb. Results showed that normalized excursion distance decreased significantly as heel height increased. The changes of plantar pressure in the SEBT as heel height increased were more obvious in MF, MM, MR and ML areas. Plantar loading of stance limb shifted to medial forefoot to reduce posture instability. Knowledge of this study identified dynamic posture control deficits when wearing high-heeled shoes and the critical role of medial forefoot in posture control, providing a basis for further research of improving the ability of dynamic balance.

Purpose: The aim of this study was to analyze plantar pressure during the open stance forehand (OSF) in female tennis players. Methods: Seven female players executed the tennis forehand technique with open stance in the biomechanical laboratory. A portable pressure insole system was adopted to collect mean pressure (MP), peak pressure (PP), force (F), pressure-time integral (PTI) and contact area (CA) in 7 regions of the feet. Independent sample T-test was used to analyze the difference among these parameters. Results: F, PP in the first phalangeal region (BT) and the remaining four toe regions (OT) of the right foot (RF) were both larger than the left foot (LF); F in the fourth and fifth metatarsophalangeal joint (M4-5), the middle foot region (MF), hind foot region（HF）and PP in M4-5 of LF were significantly greater than the same region in RF; MP in BT and OT of RF showed significantly higher pressure than LF. While MP among areas of M4-5 and HF of LF was significantly greater than RF; PTI, CA in OT, M4-5 and MF of RF were significantly higher than LF while M1, M2-3, M4-5 and MF of LF showed significant smaller. Conclusion: RF role was to generate the power and LF role was to stabilize the balance of the body during the OFS. However, long-term and repeated open stance was likely to lead to the overuse injuries in the regions of M1 and HF of both feet.

Most of the previous studies have been focused on the upper limb biomechanical characteristic in the clear stroke among different level badminton players, but research on the lower limb is limited. The aim of this study is to explore the lower limb kinematics and foot pressure in the backcourt forehand clear stroke among badminton players to give theoretical reference in teaching and answer the questions occurring in the process of learning the actions. Ten professional badminton players (PP) and ten amateur players (AP) were recruited in this study. Plantar pressure analyses indicated that both the PP and the AP were in contact with the ground over the forefoot without the midfoot and heel. The work suggests that when designing professional badminton sports shoes, the designers should focus on strengthening footwear resistance in the metatarsal and forefoot area, especially the first metatarsal area, to meet the requirement of the movement demand and take the badminton movement characteristics in different regions of the design. The peak ankle dorsiflexion, eversion, and internal rotation angle levels of the AP are lower than those of the PP. It is important for the AP group to enhance their ankle strength to prevent injury and improve performance.

Collective behavior, from murmurations to synchronized beating of heart cells, governs some of the most beautiful and important aspects of nature. Likewise, cooperation—the act of sacrificing personal benefits for the common good—is one of the pillars of social evolution, and it is the basis for the emergence of collective organized actions from single-cell organisms to modern human societies. Here we merge these two phenomena into a single model, considering an ensemble of networked oscillators, where each oscillator can be either a cooperator or a defector, and with only cooperators contributing to synchrony. At the same time, the value of the order parameter in the neighborhood of each oscillator is considered as an effective local temperature which determines the strategy updating procedure in the evolutionary game. The emergence of cooperation is thus intertwined with that of synchronization, producing a novel and fascinating dynamics which includes a double explosive transition.

Recently, Li et al. proposed a novel smart card and dynamic ID-based remote user authentication scheme for multi-server environments. They claimed that their scheme can resist several types of attacks. However, through careful analysis, we find that Li et al.'s scheme is vulnerable to stolen smart card and off-line dictionary attacks, replay attacks, impersonation attacks and server spoofing attacks. By analyzing other similar schemes, we find that a certain type of dynamic ID-based multi-server authentication scheme in which only hash functions are used and whereby no registration center participates in the authentication and session key agreement phase faces difficulties in providing perfectly efficient and secure authentication. To compensate for these shortcomings, we propose a novel dynamic ID-based remote user authentication scheme for multi-server environments based on pairing and self-certified public keys. Security and performance analyses show that the proposed scheme is secure against various attacks and has many excellent features.

In recent years, the industrial use of the internet of things (IoT) has been constantly growing and is now widespread. Wireless sensor networks (WSNs) are a fundamental technology that has enabled such prevalent adoption of IoT in industry. WSNs can connect IoT sensors and monitor the working conditions of such sensors and of the overall environment, as well as detect unexpected system events in a timely and accurate manner. Monitoring large amounts of unstructured data generated by IoT devices and collected by the big-data analytics systems is a challenging task. Furthermore, detecting anomalies within the vast amount of data collected in real time by a centralized monitoring system is an even bigger challenge. In the context of the industrial use of the IoT, solutions for monitoring anomalies in distributed data flow need to be explored. In this paper, a low-power distributed data flow anomaly-monitoring model (LP-DDAM) is proposed to mitigate the communication overhead problem. As the data flow monitoring system is only interested in anomalies, which are rare, and the relationship among objects in terms of the size of their attribute values remains stable within any specific period of time, LP-DDAM integrates multiple objects as a complete set for processing, makes full use of the relationship among the objects, selects only one “representative” object for continuous monitoring, establishes certain constraints to ensure correctness, and reduces communication overheads by maintaining the overheads of constraints in exchange for a reduction in the number of monitored objects. Experiments on real data sets show that LP-DDAM can reduce communication overheads by approximately 70% when compared to an equivalent method that continuously monitors all objects under the same conditions.

Interdependent networks (IN) are collections of non-trivially interrelated graphs that are not physically connected, and provide a more realistic representation of real-world networked systems as compared to traditional isolated networks. In particular, they are an efficient tool to study the evolution of cooperative behavior from the viewpoint of statistical physics. Here, we consider a prisoner dilemma game taking place in IN, and introduce a simple rule for the calculation of fitness that incorporates individual popularity, which in its turn is represented by one parameter α . We show that interdependence between agents in different networks influences the cooperative behavior trait. Namely, intermediate α values guarantee an optimal environment for the evolution of cooperation, while too high or excessively low α values impede cooperation. These results originate from an enhanced synchronization of strategies in different networks, which is beneficial for the formation of giant cooperative clusters wherein cooperators are protected from exploitation by defectors.

The big data security problems during the process of data production,storage,use,transmission,sharing and destruction have been explored.Firstly,the development strategies of big data security worldwide were summarized.Second,from the perspective of the whole life cycle management,the current technical research and the progress of big data security protection were introduced by focusing on its collection,storage,transport,use and open sharing,destruction and management strategy.Finally,some new problems that need to be solved in the future research of big data security were discussed.

Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted) immunization and layer node-based random (targeted) immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER) random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF) networks.

In network security, how to use efficient response methods against cascading failures of complex networks is very important. In this paper, concerned with the highest-load attack (HL) and random attack (RA) on one edge, we define five kinds of weighting strategies to assign the external resources for recovering the edges from cascading failures in heterogeneous scale-free (SF) networks. The influence of external resources, the tolerance parameter, and the different weighting strategies on SF networks against cascading failures is investigated carefully. We find that, under HL attack, the fourth kind of weighting method can more effectively improve the integral robustness of SF networks, simultaneously control the spreading velocity, and control the outburst of cascading failures in SF networks than other methods. Moreover, the third method is optimal if we only knew the local structure of SF networks and the uniform assignment is the worst. The simulations of the real-world autonomous system in, Internet have also supported our findings. The results are useful for using efficient response strategy against the emergent accidents and controlling the cascading failures in the real-world networks.