Curved Space-Time at the Planck Scale

This paper presents a physically plausible and somewhat illuminating first step in extending the fundamental principles of mechanical stress and strain to space-time. Here the geometry of space-time, encoded in the metric tensor, is considered to be made up of a dynamic lattice of extremely small, localized fields that form a perfectly elastic Lorentz symmetric space-time at the global (macroscopic) scale. This theoretical model of space-time at the Planck scale leads to a somewhat surprising result in which matter waves in curved space-time radiate thermal gravitational energy, as well as an equally intriguing relationship for the anomalous dispersion of light in a gravitational field.

Asbestos Exposure during Gasket Removal from Aircraft Engine

We have previously evaluated asbestos exposure associated with various maintenance procedures on light aircraft. The purpose of this study was to evaluate asbestos exposure during engine maintenance on light aircraft. This test was designed to evaluate the potential for asbestos exposure to mechanics and others who remove asbestos-containing engine gaskets from reciprocating style aircraft engines. Utilized in this test was an air cooled, horizontally opposed, aviation gasoline burning engine, assembled during 1986 and operated intermittently up into 2015, having accumulated 1680 hours run time. Nearly 75% of the asbestos-containing gaskets installed during 1986 were still in place at the time of testing. Chrysotile asbestos contents of such gaskets ranged from 55% to 60% by area, for those of sheet style and 5% by area, for the spiral wound metal/asbestos style. Despite the levels of effort required to effect gasket removals, the professional aircraft mechanic was not exposed to airborne asbestos fibers at the lower limits of sampling and analytical detection achieved;all of which were substantially less than the current Occupational Safety and Health Administration Permissible Exposure Limits for asbestos. The results of this testing indicate an absence of gasket related asbestos exposure risk to mechanics who work with light aircraft engines, including those having asbestos-containing gaskets. These results are consistent with the findings of Mlyarek and Van Orden who studied the asbestos exposure risk occasioned during overhaul of larger radial style reciprocating aircraft engines [1].

The Brain-Gut Axis in Alzheimer’s Disease

There is a vast colony of microbes in the human gut that not only maintains intestinal function but also has intricate links to the brain via the “microbiota-gut-brain” (MGB) axis. The axis now has been demonstrated to have implications for the treatment of several neuro-psychological illnesses, including Alzheimer’s Disease (AD), a condition that affects a person’s ability to connect socially and communicate effectively. Previously thought to be a rare disorder, it is now thought to affect 1 in 9 individuals in the United States. Unfortunately, there is not FDA-approved drug for the primary symptoms of AD, and the current cognitive-behavioral therapy procedures for the condition are time-consuming and expensive. Scientists are currently investigating the MGB axis to identify potential treatment targets to reduce AD symptoms. This review aims to highlight the functioning of the MGB axis;research into this dysfunction may effectively demonstrate the need of innovative AD treatment approaches, ranging from probiotics and dietary changes to more contemporary techniques like fecal transplants, vagal nerve stimulation, and gene therapy. Not simply behavioral intervention therapy, but also microbes, may hold the key to curing AD.

Cardiac CT Image Segmentation for Deep Learning-Based Coronary Calcium Detection Using K-Means Clustering and Grabcut Algorithm

Specific medical data has limitations in that there are not many numbers and it is not standardized.to solve these limitations,it is necessary to study how to efficiently process these limited amounts of data.In this paper,deep learning methods for automatically determining cardiovascular diseases are described,and an effective preprocessing method for CT images that can be applied to improve the performance of deep learning was conducted.The cardiac CT images include several parts of the body such as the heart,lungs,spine,and ribs.The preprocessing step proposed in this paper divided CT image data into regions of interest and other regions using K-means clustering and the Grabcut algorithm.We compared the deep learning performance results of original data,data using only K-means clustering,and data using both K-means clustering and the Grabcut algorithm.All data used in this paper were collected at Soonchunhyang University Cheonan Hospital in Korea and the experimental test proceeded with IRB approval.The training was conducted using Resnet 50,VGG,and Inception resnet V2 models,and Resnet 50 had the best accuracy in validation and testing.Through the preprocessing process proposed in this paper,the accuracy of deep learning models was significantly improved by at least 10%and up to 40%.

Assessment of Asbestos Exposure Associated with a Brake Grinder

The wear patterns for drum-style automotive brakes tend to enlarge internal drum diameters. Such enlargement is most profound when used brake drums are machined to restore the metal friction surfaces. Specialized arc grinding machinery has been used to match replacement shoe-style brake friction materials to enlarged drums. The process of arc grinding removes friction material, thereby producing dust. When organic-style friction materials contained asbestos, use of arc grinding machinery posed an asbestos fiber exposure risk to operators and proximate personnel. The manufacturers of arc grinding machinery have incorporated local exhaust ventilation systems designed to capture and remove this dust at the point of grinding contact and propel this dust into collection bags or other systems. This research was designed to evaluate the dust capture and retention characteristics of a specific arc grinder product, when used to custom grind asbestos-containing brake friction materials. A Bear Model 1420 automotive brake shoe arc grinder was the subject of this study. During two separate but consecutive test sessions, newly relined sets of shoe-style automobile brake friction materials were precision ground. Both area and personal air samples were collected throughout each testing session. This work took place within a closed and unventilated metal building, with total interior volume of 2500 m3. Collected air samples were analyzed using phase contrast microscopy (PCM) and transmission electron microscopy (TEM). The results of analysis using PCM for personal samples (n = 6) ranged from <0.044 to 0.055 fibers per cc (f/cc) (mean 0.05). Follow-up analysis of these personal samples using TEM indicated asbestos-adjusted PCM exposures ranging from <0.0074 to 0.055 f/cc (mean ≤ 0.041). Area air samples, taken at distances ranging from 1.5 to 9 meters from the arc grinder (n = 12), showed asbestos-adjusted PCM concentrations ranging from <0.0075 to 0.041 f/cc (mean ≤ 0.017). The process of custom arc grinding shoe-style, asbestos-containing brake friction materials can cause exposure to airborne asbestos fibers. However, when done using properly equipped arc grinding machines, such exposures are not expected to exceed the current occupational exposure limits for asbestos of 0.1 f/cc 8-hour time-weighted average (TWA) or 1.0 f/cc 30-minute average.

3-Multi ranked encryption with enhanced security in cloud computing

Searchable Encryption(SE)enables data owners to search remotely stored ciphertexts selectively.A practical model that is closest to real life should be able to handle search queries with multiple keywords and multiple data owners/users,and even return the top-k most relevant search results when requested.We refer to a model that satisfies all of the conditions a 3-multi ranked search model.However,SE schemes that have been proposed to date use fully trusted trapdoor generation centers,and several methods assume a secure connection between the data users and a trapdoor generation center.That is,they assume the trapdoor generation center is the only entity that can learn the information regarding queried keywords,but it will never attempt to use it in any other manner than that requested,which is impractical in real life.In this study,to enhance the security,we propose a new 3-multi ranked SE scheme that satisfies all conditions without these security assumptions.The proposed scheme uses randomized keywords to protect the interested keywords of users from both outside adversaries and the honest-but-curious trapdoor generation center,thereby preventing attackers from determining whether two different queries include the same keyword.Moreover,we develop a method for managing multiple encrypted keywords from every data owner,each encrypted with a different key.Our evaluation demonstrates that,despite the trade-off overhead that results from the weaker security assumption,the proposed scheme achieves reasonable performance compared to extant schemes,which implies that our scheme is practical and closest to real life.

Hybrid Mobile Cloud Computing Architecture with Load Balancing for Healthcare Systems

Healthcare is a fundamental part of every individual’s life.The healthcare industry is developing very rapidly with the help of advanced technologies.Many researchers are trying to build cloud-based healthcare applications that can be accessed by healthcare professionals from their premises,as well as by patients from their mobile devices through communication interfaces.These systems promote reliable and remote interactions between patients and healthcare professionals.However,there are several limitations to these innovative cloud computing-based systems,namely network availability,latency,battery life and resource availability.We propose a hybrid mobile cloud computing(HMCC)architecture to address these challenges.Furthermore,we also evaluate the performance of heuristic and dynamic machine learning based task scheduling and load balancing algorithms on our proposed architecture.We compare them,to identify the strengths and weaknesses of each algorithm;and provide their comparative results,to show latency and energy consumption performance.Challenging issues for cloudbased healthcare systems are discussed in detail.

无线传感器网络中公钥机制研究综述

物联网是当前学术界和产业界的研究热点,作为物联网主要构成部分之一的无线传感器网络(Wireless Sensor Networks,WSNs),其安全与人们的生活安全及隐私息息相关.过去近二十年来WSNs安全得到了广泛深入的研究,其中公钥机制从最初的不可行认知到现今的广泛研究应用,在WSNs中的可行性正逐渐被认可.然而公钥机制是否可以在WSNs中全面展开、其被引入到WSNs后会带来哪些问题、还有哪些尚未解决,这些都有待进一步探究.本文梳理了WSNs中公钥机制研究的高质量文献并将其归结为原语类、密钥管理类、认证与访问控制类、其他应用类,对比分析了各类文献中的经典研究工作,总结了WSNs中引入公钥机制的必要性、可行性及相关问题与挑战,针对这些挑战分析了其现有解决情况,最后对研究方向及可能的解决方案进行了展望.

基于信用等级划分的医疗数据安全共识算法

在基于区块链的医疗数据共享系统中为防御恶意节点攻击并且提高共识效率,该文提出基于信用等级划分的医疗数据安全共识算法(SCA_MD)。首先,在SCA_MD中,考虑由数据节点、共识节点和监管节点组成的医疗区块共识模型,提出相应的节点身份验证机制,实现快速验证。其次,提出基于海洋掠食者的自我优化信用等级划分算法(SCRD),以限制恶意节点共识权力。最后改进代表节点选举机制和共识机制,提高共识的效率。实验结果表明:不管恶意节点数量如何变化,SCA_MD都能提高交易吞吐量,降低平均交易时延和平均节点通信开销。

PCRAM损耗均衡研究综述

随着半导体工艺的高速发展,计算机系统中处理器与主存之间性能差距的不断增大,传统存储器件的集成度已接近极限,能耗问题也日益突出,当前传统的主存技术面临挑战.相变随机存储器(PCRAM)具有集成度高、功耗低、非易失、字节级编址等优良特性,是最有发展潜力的、最有可能完全取代DRAM主存的非易失性存储器之一.首先介绍了PCRAM的发展与应用现状,指出T型结构是当前学术界和产业界广泛采用的器件结构,目前已经有PCRAM产品逐步开始量产并投入商业应用.然后,介绍了PCRAM当前面临的挑战,指出PCRAM面临的写耐久性局限是限制期发展与应用的主要障碍之一,分布不均匀的写操作会使PCRAM快速失效.接着,从硬件辅助和软件辅助两个角度分别介绍了当前研究人员所提出的一些具有代表性的PCRAM损耗均衡技术,在分析和归纳当前研究现状的基础上,指出了现有方案的优点和亟待完善之处.最后,展望了未来PCRAM损耗均衡技术的研究方向,为该领域今后的发展提供参考.

A systematic literature review of blockchain cyber security

Since the publication of Satoshi Nakamoto's white paper on Bitcoin in 2008,blockchain has(slowly)become one of the most frequently discussed methods for securing data storage and transfer through decentralized,trustless,peer-to-peer systems.This research identifies peer-reviewed literature that seeks to utilize blockchain for cyber security purposes and presents a systematic analysis of the most frequently adopted blockchain security applications.Our findings show that the Internet of Things(IoT)lends itself well to novel blockchain applications,as do networks and machine visualization,public-key cryptography,web applications,certification schemes and the secure storage of Personally Identifiable Information(PII).This timely systematic review also sheds light on future directions of research,education and practices in the blockchain and cyber security space,such as security of blockchain in IoT,security of blockchain for AI data,and sidechain security.

Effect of stress sensitivity on displacement efficiency in CO_2 flooding for fractured low permeability reservoirs

Carbon dioxide flooding is an effective means of enhanced oil recovery for low permeability reservoirs. If fractures are present in the reservoir, CO2 may flow along the fractures, resulting in low gas displacement efficiency. Reservoir pore pressure will fluctuate to some extent during a CO2 flood, causing a change in effective confining pressure. The result is rock deformation and a reduction in permeability with the reduction in fracture permeability, causing increased flow resistance in the fracture space. Simultaneously, gas cross flowing along the fractures is partially restrained. In this work, the effect of stress changes on permeability was studied through a series of flow experiments. The change in the flowrate distribution in a matrix block and contained fracture with an increase in effective pressure were analyzed. The results lead to an implicit comparison which shows that permeability of fractured core decreases sharply with an increase in effective confining pressure. The fracture flowrate ratio declines and the matrix flowrate ratio increases. Fracture flow will partially divert to the matrix block with the increase in effective confining pressure, improving gas displacement efficiency.

Pericardial decompression syndrome: A comprehensive review

Pericardial decompression syndrome(PDS)is an infrequent,life-threatening complication following pericardial drainage for cardiac tamponade physiology.PDS usually develops after initial clinical improvement following pericardiocentesis and is significantly underreported and may be overlooked in the clinical practice.Although the precise mechanisms resulting in PDS are not well understood,this seems to be highly associated with patients who have some underlying ventricular dysfunction.Physicians performing pericardial drainage should be mindful of the risk factors associated with the procedure including the rare potential for the development of PDS.

Detection of Fronts from Ocean Colour Monitor Images Using Entropic Technique: A Case Study of Meso- and Micro-Scale Chlorophyll Mapping in Bay of Bengal, India

This paper discusses a robust technique using entropy-based detection for delineating edges in ocean colour images. The detection process relies on Jhensen-Shannon divergence based image segmentation, which has been found to be the most suitable for noisy ocean colour images. In the attempted technique, partial removal of the noise in the images is performed and the edges are detected using entropic method. In our approach, Jhensen-Shannon divergence for the images is calculated, and the divergence image is arrived at after applying an appropriate threshold and filter to estimate the gradients. An attempted case study on retrieving chlorophyll front edges using this technique indicates that entropic method is far superior to conventional edge-enhancement tools, in terms of its insensitivity to impulsive noises and, capability in detecting meso- and micro-scale changes. This procedure would largely decrease the ambiguities associated with the ocean colour edges and hence has promising application potential in targeting fishing zones, sediment dispersion modeling and climate related studies.

Complex Limb Salvage with Placental-Based Allografts: A Pilot Study

Background: Commercially available human placental amnion/chorion tissue allografts have been successfully used as protective treatment barriers for wounds and diabetic ulcers. Burn and traumatic limb injuries with exposed bone or tendon generally require surgical flaps or amputations for healing. The purpose of this study was to determine if dehydrated human amnion/ chorion membrane allografts (dHACM) with decellularized human collagen matrix (dHCM) could be used to salvage injured human extremities. Methods and Materials: dHACM/dHCM was topically applied to the wounds after debridement. Negative Pressure Wound Therapy (NPWT) was concurrently initiated, primarily to bolster the tissue with moisture and contamination control. Approximately every seven days, wounds were re-evaluated for granulation tissue growth response. As needed, patients received dHACM/ dHCM and NPWT in the outpatient or home care settings after discharge. Results: Fifteen males and two females (26 extremities) were treated for fourteen burn and three Necrotizing Soft Tissue Infections (NSTI) injuries. Closure was observed in patients after two to five dHACM/dHCM applications. The dHACM/dHCM treatment was initiated: (median) 17-days after injury;NPWT for 17-days;autograft or primary closure after 21-days;discharge 25-days after the first application. Conclusion: Treatment with human placental-derived allografts provided a protective covering that enabled the healing cascade to generate granulation tissue formation in extremity wounds with exposed tendon and/or bone. In select limb salvage cases, dHACM/dHCM treatment may be a promising alternative to amputations, tissue rearrangements, free tissue flaps or other techniques for resolution of extremity wounds with bone and tendon exposure.

Software Composition of Different Security Level Components

In this paper the authors show how software component design can affect security properties through different composition operators. The authors define software composition as the result of aggregating and/or associating a component to a software system. The component itself may be informational or functional and carry a certain level of security attribute. The authors first show that the security attributes or properties form a lattice structure when combined with the appropriate least upper bound and greatest lower bound type of operators. Three composition operators, named C l, C2 and C3 are developed. The system＇s security properties resulting from these compositions are then studied. The authors discuss how different composition operators maintain, relax and restrict the security properties. Finally, the authors show that C1 and C2 composition operators are order-sensitive and that C3 is order-insensitive.

Software Defect Prediction Harnessing on Multi 1-Dimensional Convolutional Neural Network Structure

Developing successful software with no defects is one of the main goals of software projects.In order to provide a software project with the anticipated software quality,the prediction of software defects plays a vital role.Machine learning,and particularly deep learning,have been advocated for predicting software defects,however both suffer from inadequate accuracy,overfitting,and complicated structure.In this paper,we aim to address such issues in predicting software defects.We propose a novel structure of 1-Dimensional Convolutional Neural Network(1D-CNN),a deep learning architecture to extract useful knowledge,identifying and modelling the knowledge in the data sequence,reduce overfitting,and finally,predict whether the units of code are defects prone.We design large-scale empirical studies to reveal the proposed model’s effectiveness by comparing four established traditional machine learning baseline models and four state-of-the-art baselines in software defect prediction based on the NASA datasets.The experimental results demonstrate that in terms of f-measure,an optimal and modest 1DCNN with a dropout layer outperforms baseline and state-of-the-art models by 66.79%and 23.88%,respectively,in ways that minimize overfitting and improving prediction performance for software defects.According to the results,1D-CNN seems to be successful in predicting software defects and may be applied and adopted for a practical problem in software engineering.This,in turn,could lead to saving software development resources and producing more reliable software.

Experimental and Numerical Study of Structural Identification Using Non-Linear Resonant Decay Method

One of the practical approaches in identifying structures is the non-linear resonant decay method which identifies a non-linear dynamic system utilizing a model based on linear modal space containing the underlying linear system and a small number of extra terms that exhibit the non-linear effects.In this paper,the method is illustrated in a simulated system and an experimental structure.The main objective of the non-linear resonant decay method is to identify the non-linear dynamic systems based on the use of a multi-shaker excitation using appropriated excitation which is obtained from the force appropriation approach.The experimental application of the method is indicated to provide suitable estimates of modal parameters for the identification of non-linear models of structures.

浅析“一带一路”跨界文化传播对经济发展的促进

本文简要概述了"一带一路"沿线国对"一带一路"的认识现状,提出要利用各种渠道客观传播我国"一带一路"合作倡仪的文化内涵,以开放包容理念传播、学习和吸收沿途国优秀文化,以文化交流夯实民意基础,实施跨界文化管理,促进"一带一路"沿途国经济合作,实现"共羸"发展。

Study on Countermeasures of Language Exchange and Cultural Communication along “the Belt and Road”

This paper introduces the language and cultural status along"the Belt and Road", points out the importance of language and cultural communication to realize the"the Belt and Road"initiative, and put forward that our country should use various channels to spread the cultural connotation of"the Belt and Road"initiative, spread, study and absorb excellent culture of countries along"the Belt and Road"in spirits of open and inclusive, and enhance public support by cultural communication to promote economic cooperation, cultural prosperity and innovation of countries along the"the Belt and Road ".