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Nowadays, due to the advances in mobile and wireless communication, mobile devices are widely used in our daily life. Meanwhile, in the mobile devices, there exits diverse applications which are developed to satisfy the various requirements of mobile users. Correspondingly, a large number of services are produced by the mobile devices. Since the mobile devices have limitations on the battery capacity, physical size, etc., they can hardly complete all the services. To relieve this problem, driven by edge computing, the central units (CUs) in fifth-generation wireless systems (5G) could be enhanced into edge nodes (ENs) for processing. However, during the transmission of edge services, the privacy leakage may occur, and the overall performance of the networks needs to be taken into consideration. In this paper, an optimization problem is defined to improve the resource utilization and load balance for all the ENs while protecting the privacy information and satisfying the time requirement. Then, a balanced service offloading method, abbreviated BSOM, is proposed. Finally, abundant experiments and evaluations are conducted to validate our proposed method is both effective and feasible. [ABSTRACT FROM AUTHOR]

Nowadays, with the development of wireless communication, people are relying on mobile devices heavily due to various application deployment and plentiful service experience of customers in wireless metropolitan area network (WMAN). The computing resources of the mobile devices are limited as they are restricted with physical size, battery capacity, etc. In order to release the resource limitation, cloudlet, an effective paradigm, is introduced to host the computing tasks offloaded from the mobile devices. Compared with the cloud computing, the cloudlets are deployed closer to provide customers with fewer task offloading delay. Currently, the offloaded task scale is increasing, which generates large quantities of energy exposure for task implementation among cloudlets. Taking advantage of live virtual machine (VM) migration technology, the energy consumption of cloudlets could be definitely reduced. But such migration across cloudlets also decreases the implementation performance of the tasks. Therefore, it is still a challenge to jointly optimize the execution performance and the energy consumption for cloudlet management in WMAN. In this paper, a novel virtual machine (VM) scheduling method is proposed to balance the implantation time and the energy consumption to cope with the above challenge. Specifically, a collection of available migration polices are obtained through heuristically searching of destination cloudlets for the running computing tasks. Then, simple additive weighting (SAW) and multiple criteria decision making (MCDM) techniques are leveraged to select the optimal VM scheduling strategy across cloudlets in WMAN. Finally, experimental results and evaluations validate our proposed method is both effective and feasible. [ABSTRACT FROM AUTHOR]

Apricot kernel meal is an understudied and underutilized by-product of the apricot industry. In this study, apricot kernel protein (AKP) was obtained from apricot kernel meal by a simple one-step salting-in method, exhibiting high yield (38.4 g AKP/100 g defatted meal), high protein content (91.4%), and high solubility (92.5% at neutral pHs). The possibility and kinetics of AKP fibrillization were further investigated. It was found that apricot kernel protein amyloid fibrils (AKPFs) with twisted nanofibrillar structures were readily formed by heating at pH 2.0 and 90 °C. SDS-PAGE analysis indicated that these AKPFs contained peptide fragments with the molecular weight of around 6.5 kDa. Atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FTIR), circular dichroism spectroscopy (CD) and intrinsic fluorescence spectroscopy revealed that the structure, morphology and properties of AKPFs were analogous to other food protein-derived amyloid fibrils. Importantly, AKPF has upgraded foaming characteristics, e.g., AKPF-18h (AKPF formed at 18 h) has 31.7% higher foaming capacity and 30.2% higher foam stability relative to AKP. This is attributed to the formation of a homogeneous interfacial film at the air/water interface of the foam. The DPPH radical scavenging activity of AKPF-18h was also improved, reaching 53.0%, about twice that of AKP (28.4%). In addition, the developed AKP and AKPFs were not cytotoxic in vitro. All these findings suggest that AKPFs have great potential for future food applications. [Display omitted] • Apricot kernel protein (AKP) was prepared with high yield, purity and solubility. • AKP amyloid fibrils (AKPFs) were readily formed under conventional conditions. • The foaming capacity and foam stability of AKPFs were significantly improved. • Antioxidant activity of AKPFs were also significantly enhanced. • AKP and AKPF were not cytotoxic in vitro. [ABSTRACT FROM AUTHOR]

A good grasp of the relations between rapid economic development of China and stable energy supply is an important means to achieve coordinated development among energy, economy and society. This paper uses cointegration test, Granger causality test and vector error correction model, and other empirical method to analyze the relationship between the total amount of energy consumption and energy trade from 2000 to 2013, reveals that energy has a high degree of dependence on imported trade. The results showed that energy consumption has relatively strong positive impact on the energy business in the short term, then a weak negative effect in the long term. The impact of energy trading on the energy consumption is not significant in the short or long term. [ABSTRACT FROM AUTHOR]

Over the past years, with the development of hardware and software, the intelligent sensors, which are deployed in the wearable devices, smart phones, and etc., are leveraged to collect the data around us. The data collected by the sensors is analyzed, and the corresponding measures will be implemented. However, due to the limited computing resources of the sensors, the overload resource usage may occur. In order to satisfy the requirements for strong computing power, edge computing, which emerges as a novel paradigm, provides computing resources at the edge of networks. In edge computing, the computing tasks could be offloaded from the sensors to the other sensors for processing. Despite the advantages of edge computing, during the offloading process of computing tasks between sensors, private data, including identity information and address, may be leaked, which threatens personal security. Hence, it is important to avoid privacy leakage in edge computing. In addition, the time consumption of offloading computing tasks affects the using experience of customers, and low time consumption makes contributions to the development of applications which are strict with time. To satisfy the above requirements, a time-efficient offloading method (TEO) with privacy preservation for intelligent sensors in edge computing is proposed. Technically, the time consumption and the offloading of privacy data are analyzed in a formalized way. Then, an improved of Strength Pareto Evolutionary Algorithm (SPEA2) is leveraged to optimize the average time consumption and average privacy entropy jointly. At last, abundant experimental evaluations are conducted to verify efficiency and reliability of our method. [ABSTRACT FROM AUTHOR]

The volatile aroma compounds in wines produced from Chinese wild/hybrid species were investigated in comparison to wines from European grapes. Volatiles were extracted by headspace solid‐phase micro‐extraction and identified by gas‐chromatography/mass‐spectrometry. The identification of analyte was performed by a combination of the linear retention index approach with the comparison of the obtained mass spectra. A total of 98 peaks were tentatively assigned as wine aroma components, and 15 odorants can be found at concentrations above their odor threshold among the odor activity values (OAVs) of 46 compounds evaluated in all of the wines. The "OAVs' aroma wheels" showed that the classes of aromatic series are first fruity, next herbaceous and roasty and no spicy and caramelized notes. Via principal component analysis, all the grape germplasm studied could be divided into four groups: "Jingsheng‐1," "Cabernet Gernischt," "Beibinghong," and others, which exhibited distinctive aroma features, respectively. Practical applications Chinese wild grape species have many desirable properties for wine grape breeding such as possessing strong resistant genes to fungal diseases and cold condition, especially after hybridization with European grapes. As an emerging wine country, wines from Chinese wild/hybrid species have achieved much success in the last few years. The chemical content and biological properties have been studied extensively in many but there are a few studies in our knowledge about the wine tastes of these species. In this paper, the key odorants in wines produced from the Chinese grape species of V. amurensis Rupr., V. davidii Foex., and V. quinquangularis Rehd. and its hybrids were characterized in comparison to wines produced from European grapes (V. vinifera). The findings will help to the further understanding of the key aroma components in the different Chinese grapevine germplasm, and make further efforts to enrich the wine types in the marketplace. [ABSTRACT FROM AUTHOR]

The article comments on exercise-induced neuroplasticity and the central mechanism of exercise therapy for chronic low back pain. Possible mechanisms of induced neuroplasticity in the treatment of low back pain include activation of the endogenous pain regulation mechanism, increased functional activity of sensorimotor brain areas, and increased concentration of brain-derived neurotrophic factor. Also noted is the positive impact of exercise therapy on central nervous system plasticity.

In recent years, the prevalence of cardiovascular diseases has been growing geometrically, especially among the elderly. Real-time heart rate monitoring becomes an effective measure for preventing cardiovascular diseases. Traditional contact-based real-time heart rate measurement methods require long-term wearing of contact electrodes, which can cause inconvenience to the elderly population. In this study, a wide spectrum full color night vision elderly face video heart rate automatic measurement and early warning system was designed and developed by combining imaging photoplethysmography (IPPG), video acquisition equipment based on starlight wide spectrum camera and high-speed face recognition signal processing algorithm based on deep learning. By constructing a software and hardware platform, a comprehensive evaluation of the system's application in elderly facial video heart rate measurement experiments was conducted. [ABSTRACT FROM AUTHOR]

Objective: This study is aimed to design wearable care equipment based on the narrow-band Internet of Things (NB-IoT) to assist in applying health-related big data and gain the optimum treatment time for patients with fractures. Methods: A wearable care equipment based on the NB-IoT technique (namely, a brace) was designed by combining sensors with embedded systems, man–machine interaction technique, and so on. Also, the exercise heart rate, the surface temperature of disease location, and the data on oxyhemoglobin saturation of patients were acquired using sensors. Next, these data were sent to an application (APP) on a cell phone after transmission to a single-chip machine for processing. Finally, the data on heart rate, body temperature, blood oxygen, and their variation curves were displayed on the APP. Results: The wearable care equipment could provide a normal average recovery curve for patients with fractures, which was instrumental for patients and doctors to fully grasp the rehabilitation condition. If the key indicators were abnormal and exceeded the threshold value, the wearable equipment generated an early warning signal to alert patients to seek medical attention in time. Conclusions: The test results indicated that the wearable care equipment based on the NB-IoT technique could realize the acquisition, storage, and analysis of the physiological parameters of patients. The wearable equipment had a series of characteristics, including low cost, low power dissipation, stable signal connection, and strong practicability, having a certain practical significance for the consistency of enhancing the health service and assisting the health-related big data development. [ABSTRACT FROM AUTHOR]

Workflow is one of the most typical applications in distributed computing, which makes a variety of complex computing work orderly. However, assigning workflow tasks to nodes in the process of multi-node collaboration is still a challenge, because there are some unpredictable emergencies, i.e., uncertainty, in the process of workflow scheduling. The paper proposes a blockchain-powered resource provisioning (BPRP) method to solve the above problems. Technically, we use the directed acyclic graph in the graph theory to represent the workflow task and optimize the workflow scheduling strategy in the presence of uncertainty. The processing time and energy consumption of workflow tasks are also optimized by using non-dominated sorting genetic algorithm III (NSGA-III). Finally, we carry out experimental simulations to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]