A LITERATURE REVIEW OF SUSTAINABLE TOURISM (1990-2016): DEVELOPMENT TRAJECTORY AND FRAMEWORK

Purpose of the study—Tourism is one of the largest and fastest growing industries in the world. Just like an enterprise today, sustainability is the long-term objective pursued by tourism industry. However, little effort has been made to systematically provide sufficient information to academicians and practitioners who have great research interests in sustainable tourism. Therefore, this paper aims to figure out the knowledge mapping of sustainable tourism and to indicate its research hot spots and trends for future research. Methodology—This paper surveys the development trajectory of sustainable tourism using a literature review and classification of articles retrieved from 5 online databases with solo keyword “sustainable tourism” from 1900 to 2016. Main findings—Based on the scope of 641 articles, this study reveals that the number of publication on sustainable tourism has significantly increased since 2006. In addition, these articles are scattered across 125 journals and mostly published in 23 academic journals. The majority of targeted countries/regions for sustainable tourism focus on Asia, Europe and America. Limitation—Restricted to limited knowledge, we make a brief literature survey on sustainable tourism from 1990-2016 to explore how sustainable tourism and its applications have developed in this period. Originality/value—In fact, sustainable tourism is a belief and an overall concept in every tourism activities. Though this research has done lots, it still has rooms to make more complete. Finally, we present a conceptual framework integrating 13 classifications criteria derived from our analysis with 3247 keywords. Most interestingly, we further present a conceptual framework with a visual effect to operationalize the coverage of sustainable tourism. Based on our analysis, any researcher can easily find the popular and right journal to get into it, if he/she is in need, he/she also can roughly know its applications so far and completely get a whole picture of sustainable tourism quickly

PERCEPTION FIELD FOR A MOBILE DEVICE TO PROVIDE REAL-TIME DEPTH ESTIMATION FOR DETECTED OBJECTS

A mobile computing device (e.g., a mobile phone, camera, tablet computer, wearable and/or headset device) may include an integrated display device (e.g., a presence-sensitive screen) at which a user interface is presented to provide perception field functionality, which enables real-time depth estimation for static or moving objects that are detected by the mobile computing device based on sensory input from an onboard camera. In various examples, this functionality may be embodied in a portable and flexible library (e.g. Android library) that is installed on the mobile computing device. The purpose of perception field monitoring is to provide fast and efficient algorithms for spatial object mapping to enable real-time distance estimation of static and moving objects on a mobile computing device. The implementation of these algorithms may provide spatial location information of targeted objects, as well as distance information associated with objects that are detected by the device. In certain cases, mobile applications executing on the device may utilize such information to provide assistance to visually impaired users by creating audible alerts

Metabolic labelling of cholesteryl glucosides in Helicobacter pylori reveals how the uptake of human lipids enhances bacterial virulence.

Helicobacter pylori infects approximately half of the human population and is the main cause of various gastric diseases. This pathogen is auxotrophic for cholesterol, which it converts upon uptake to various cholesteryl α-glucoside derivatives, including cholesteryl 6'-acyl and 6'-phosphatidyl α-glucosides (CAGs and CPGs). Owing to a lack of sensitive analytical methods, it is not known if CAGs and CPGs play distinct physiological roles or how the acyl chain component affects function. Herein we established a metabolite-labelling method for characterising these derivatives qualitatively and quantitatively with a femtomolar detection limit. The development generated an MS/MS database of CGds, allowing for profiling of all the cholesterol-derived metabolites. The subsequent analysis led to the unprecedented information that these bacteria acquire phospholipids from the membrane of epithelial cells for CAG biosynthesis. The resulting increase in longer or/and unsaturated CAG acyl chains helps to promote lipid raft formation and thus delivery of the virulence factor CagA into the host cell, supporting the idea that the host/pathogen interplay enhances bacterial virulence. These findings demonstrate an important connection between the chain length of CAGs and the bacterial pathogenicity

False Data Injection Attack on Atmospheric Electric Field in Thunderstorm Warning

Thunderstorm warning plays an important role in lightning prevention and disaster mitigation. In practical applications, thunderstorm warning system is also vulnerable to attacks, such as False Data Injection Attack (FDIA). However, there is a lack of research on False Data Injection Attack for thunderstorm warning. Therefore, this paper put forwards a FDIA method based on principal component analysis (PCA) for atmospheric electric field (AEF), which is usually used for thunderstorm warning. In the FDIA scenario, the AEF-based thunderstorm warning algorithm is also introduced with electric field differential index (EFDI). Finally, experiments are conducted based on AEF data collected by an atmospheric electric field meter (AEFM) about the real thunderstorm. The experimental results show that FDIA seriously interferes with the results of the AEF-based thunderstorm warning

Network Synchronization among Femtocells

Abstract-To successfully deploy femtocells overlaying the Macrocell as a two-tier that had been shown greatly benefiting communications quality in various manners, it requires to mitigate cross-tier interference between the Macrocell and femtocells, as well as intra-tier interference among femtocells. For this purpose, solutions for interference mitigation have been proposed for femtocells in literatures. However, an essential assumption of these solutions is that all femtocells and the Macrocell shall be synchronized. Such a (network) synchronization of the Macrocells and user deployed femtocells create diverse challenges from conventional synchronization among Macrocells. Existing solutions therefore leverage the global positioning system (GPS) or the wired backhaul (IEEE 1588) to synchronize the Macrocell and all femtocells, however, they are infeasible for LTEAdvanced femtocells suffering a severe penetration loss of GPS signals and a severe jitter on the backhaul with heterogeneous protocols. As a consequence, each femtocell achieving a timing consensus by leveraging synchronization signals broadcasted by the Macrocell or by the neighboring femtocells turns out to be the possible solution. In this paper, we propose a network synchronization algorithm for femtocells. By only utilizing existing synchronization signals, the proposed network synchronization algorithm achieves the timing consensus among femtocells with and without the present of the Macrocell. Yielding an extremely low computational complexity, the proposed algorithm achieves the essential assumption of interference mitigation solutions in literatures and thus enabling the femtocell technology

A Low Power Fully Integrated Analog Baseband Circuit with Variable Bandwidth for 802.11 a/b/g WLAN

Abstract: This paper presents experimental results of an analog baseband circuit with variable bandwidth for WLAN direct conversion receiver in UMC 0.18um CMOS process. A seventh order chebyshev lowpass filter with triple bandwidth is used in the analog baseband circuit. The bandwidth is selectable from 7.56MHz, 19.5MHz, or 26.5MHz. The circuit adopts the servo loop for dc offset cancellation. It also has a gain range from 20dB to 60 dB with 10 dB steps while only dissipating 22.248mW. In addition, an automatic frequency tuning loop (ATL) is reported to achieve the bandwidth accuracy of the filter

Ultra high-resolution fMRI and electrophysiology of the rat primary somatosensory cortex

High-resolution functional-magnetic-resonance-imaging (fMRI) has been used to study brain functions at increasingly finer scale, but whether fMRI can accurately reflect layer-specific neuronal activities is less well understood. The present study investigated layer-specific cerebral-blood-volume (CBV) fMRI and electrophysiological responses in the rat cortex. CBV fMRI at 40×40 µm in-plane resolution was performed on an 11.7-T scanner. Electrophysiology used a 32-channel electrode array that spanned the entire cortical depth. Graded electrical stimulation was used to study activations in different cortical layers, exploiting the notion that most of the sensory-specific neurons are in layers II–V and most of the nociceptive-specific neurons are in layers V–VI. CBV response was strongest in layer IV of all stimulus amplitudes. Current source density analysis showed strong sink currents at cortical layers IV and VI. Multi-unit activities mainly appeared at layers IV–VI and peaked at layer V. Although our measures showed scaled activation profiles during modulation of stimulus amplitude and failed to detect specific recruitment at layers V and VI during noxious electrical stimuli, there appears to be discordance between CBV fMRI and electrophysiological peak responses, suggesting neurovascular uncoupling at laminar resolution. The technique implemented in the present study offers a means to investigate intracortical neurovascular function in the normal and diseased animal models at laminar resolution

Muscle 4EBP1 activation modifies the structure and function of the neuromuscular junction in mice

Dysregulation of mTOR complex 1 (mTORC1) activity drives neuromuscular junction (NMJ) structural instability during aging; however, downstream targets mediating this effect have not been elucidated. Here, we investigate the roles of two mTORC1 phosphorylation targets for mRNA translation, ribosome protein S6 kinase 1 (S6K1) and eukaryotic translation initiation factor 4E-binding protein 1 (4EBP1), in regulating NMJ structural instability induced by aging and sustained mTORC1 activation. While myofiber-specific deletion of S6k1 has no effect on NMJ structural integrity, 4EBP1 activation in murine muscle induces drastic morphological remodeling of the NMJ with enhancement of synaptic transmission. Mechanistically, structural modification of the NMJ is attributed to increased satellite cell activation and enhanced post-synaptic acetylcholine receptor (AChR) turnover upon 4EBP1 activation. Considering that loss of post-synaptic myonuclei and reduced NMJ turnover are features of aging, targeting 4EBP1 activation could induce NMJ renewal by expanding the pool of post-synaptic myonuclei as an alternative intervention to mitigate sarcopenia

Caries and Restoration Detection Using Bitewing Film Based on Transfer Learning with CNNs

Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early; the treatment will be relatively easy; which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However; the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of professionals. In addition to the use of Gaussian high-pass filter and Otsu’s threshold image enhancement technology; this research solves the problem that the original cutting technology cannot extract certain single teeth; and it proposes a caries and lesions area analysis model based on convolutional neural networks (CNN); which can identify caries and restorations from the bitewing images. Moreover; it provides dentists with more accurate objective judgment data to achieve the purpose of automatic diagnosis and treatment planning as a technology for assisting precision medicine. A standardized database established following a defined set of steps is also proposed in this study. There are three main steps to generate the image of a single tooth from a bitewing image; which can increase the accuracy of the analysis model. The steps include (1) preprocessing of the dental image to obtain a high-quality binarization; (2) a dental image cropping procedure to obtain individually separated tooth samples; and (3) a dental image masking step which masks the fine broken teeth from the sample and enhances the quality of the training. Among the current four common neural networks; namely; AlexNet; GoogleNet; Vgg19; and ResNet50; experimental results show that the proposed AlexNet model in this study for restoration and caries judgments has an accuracy as high as 95.56% and 90.30%; respectively. These are promising results that lead to the possibility of developing an automatic judgment method of bitewing film