609 research outputs found
The impact of COVID-19 on Italian accommodation: A supply-perspective
No full textPurpose: The current COVID-19 pandemic has created an extremely dynamic and uncertain environment in which businesses find it very difficult to operate, particularly those in the hospitality industry. It is therefore very important to understand which actions hospitality businesses think the private and public sectors should adopt in order to cope with the pandemic and its impact. To facilitate this, this research adopted chaos theory to investigate Italian small and medium enterprises (SMEs) in the hospitality sector.
Methods: A mixed method approach, based on a convergent parallel design data validation variant, was adopted. A survey with open and closed questions was developed and sent to a sample of businesses. 1,040 completed questionnaires were collected and analysed through descriptive statistics; in addition to these usable surveys, 361 open-ended answers were analysed thematically.
Results: The results showed that Italian entrepreneurs and managers were over-relying on interventions from the public sector and that there was a lack of business actions being made, thus evidencing a deficit in terms of long-term strategic thinking and the innovation required during such turbulent times.
Implications: Although these results cannot be generalised to the whole of the hospitality industry, they shed light on important elements that industry associations should take into account
Music and tourism: hitting high notes in economics and marketing of opera houses and destinations
No full textOpera houses are surviving in a very competitive scenario, where entertainment substitutes are continually growing. Governance of opera houses and administrations of destinations are promoting their mission for music and opera. Marketing and fundraising are as essential as social media.
Main objective of this research is to investigate how much tourism is affecting economics of opera houses and destinations.
Using a k-means cluster analysis of 2015 economic performances, and considering a tourism ratio, explaining different tourists’ motivations and attractiveness of destinations, this paper will segment a sample of opera houses in big and small American towns
Destination branding through storytelling: the role of entrepreneurs in the development of industrial tourism
No full textOrganization of the G protein-coupled receptors rhodopsin and opsin in native membranes
No full textG protein-coupled receptors (GPCRs), which constitute the largest and structurally best conserved family of signaling molecules, are involved in virtually all physiological processes. Crystal structures are available only for the detergent-solubilized light receptor rhodopsin. In addition, this receptor is the only GPCR for which the presumed higher order oligomeric state in native membranes has been demonstrated (Fotiadis, D., Liang, Y., Filipek, S., Saperstein, D. A., Engel, A., and Palczewski, K. (2003) Nature 421, 127-128). Here, we have determined by atomic force microscopy the organization of rhodopsin in native membranes obtained from wild-type mouse photoreceptors and opsin isolated from photoreceptors of Rpe65-/- mutant mice, which do not produce the chromophore 11-cis-retinal. The higher order organization of rhodopsin was present irrespective of the support on which the membranes were adsorbed for imaging. Rhodopsin and opsin form structural dimers that are organized in paracrystalline arrays. The intradimeric contact is likely to involve helices IV and V, whereas contacts mainly between helices I and II and the cytoplasmic loop connecting helices V and VI facilitate the formation of rhodopsin dimer rows. Contacts between rows are on the extracellular side and involve helix I. This is the first semi-empirical model of a higher order structure of a GPCR in native membranes, and it has profound implications for the understanding of how this receptor interacts with partner proteins
Utilizing incremental learning for the prediction of disease outcomes across distributed clinical data: a framework and a case study
No full textPD-Manager: An mHealth platform for Parkinson's disease patient management
No full textPD-Manager is a mobile health platform designed to cover most of the aspects regarding the management of Parkinson's disease (PD) in a holistic approach. Patients are unobtrusively monitored using commercial wrist and insole sensors paired with a smartphone, to automatically estimate the severity of most of the PD motor symptoms. Besides motor symptoms monitoring, the patient's mobile application also provides various non-motor self-evaluation tests for assessing cognition, mood and nutrition to motivate them in becoming more active in managing their disease. All data from the mobile application and the sensors is transferred to a cloud infrastructure to allow easy access for clinicians and further processing. Clinicians can access this information using a separate mobile application that is specifically designed for their respective needs to provide faster and more accurate assessment of PD symptoms that facilitate patient evaluation. Machine learning techniques are used to estimate symptoms and disease progression trends to further enhance the provided information. The platform is also complemented with a decision support system (DSS) that notifies clinicians for the detection of new symptoms or the worsening of existing ones. As patient's symptoms are progressing, the DSS can also provide specific suggestions regarding appropriate medication changes
Guided ultrasound wave propagation in intact and healing long bones
No full textUltrasonic evaluation of bone fracture healing has been traditionally based on the measurement of the propagation velocity of the first arriving signal (FAS). However, the FAS in general corresponds to a lateral wave that propagates along the bone's subsurface. In this work, we study guided ultrasound propagation in intact and healing bones. We developed a 2-D model of a bone-mimicking plate in which the healing process was simulated as a 7-stage process, and we also carried out ex vivo experiments on an intact tibia. Guided waves were represented in the time-frequency (t-f) domain of the signal by incorporating the Lamb wave theory. Three t-f distribution functions were examined, namely the reassigned Spectrogram, the smoothed-pseudo Wigner-Ville, and the reassigned version of it. For the intact plate case, we found that the S2, A3 Lamb modes were the dominant waves for a broadband 1-MHz excitation, and the S2, S0 for a 500-kHz excitation. During the simulated healing process, the mechanical and geometrical callus properties affected the theoretically anticipated Lamb modes. The propagation of guided waves throughout the thickness of the cortical bone and their sensitivity to both the mechanical and structural changes during healing can supplement velocity measurements so as to enhance the monitoring capabilities of ultrasonic evaluation. Nevertheless, the applicability of the Lamb wave theory to real bones has several limitations mostly associated with neglecting the inhomogeneity, anisotropy and irregular geometry of bone. (E-mail: [email protected]) (c) 2006 World Federation for Ultrasound in Medicine & Biology
Does tourist’s engagement influence destination loyalty? An analysis of Turismo do Centro de Portugal
No full textNowadays, the tourism market is facing several challenges and becoming an even more competitive environment. Destination competitiveness is flourishing not only because of the impact on destinations due to the tourism growth but also due to COVID -19 restrictions. The need to have a distinctive factor for destinations is now more critical than ever, and destinations should aim to create a relationship with tourists to ensure the experience is memorable and that tourists repeat the visit and make positive recommendations about the destination to others. This need suggests the usefulness of tourist engagement to achieve their goals ultimately. So, this study aims to understand how the engagement between tourists and the tourism destination can influence tourists’ destination loyalty, namely their willingness to recommend the destination to friends and family and their intention to repeat the visit. This research explores Centro de Portugal (a relevant destination in Portugal) as the loyal destination.info:eu-repo/semantics/publishedVersio
Colorspace based methodology for segmentation of leaves
No full textDigital image processing continues to be in high demand for research purposes. Research in this field encompasses various components such as color, texture, and pattern analysis. One specific area of focus is the segmentation process of plant leaves. Plant leaves have distinctive patterns and features that make them an interesting subject for study. This research specifically targets the segmentation of plant leaves, aiming to group them into different classes. The dataset used in this study consists of a collection of plant leaves, totaling 477 samples, which are divided into training and testing data. The segmentation process plays a crucial role in achieving accurate results prior to the classification phase. To accomplish this, a proposed segmentation method utilizing the K-Means algorithm as a pre-processing step is employed. The K-Means algorithm separates the leaf object from the background based on two color features represented by values 0 and 1. The pre-processing results are displayed using the color feature with a value of 1, representing the RGB (Red, Green, Blue) values of the leaf object. Subsequently, the RGB values are transformed into the Hue, Saturation, and Value (HSV) color space for feature extraction. This HSV color feature extraction method is proposed to enhance classification accuracy. For the testing phase, we consider various methods such as neural networks, SVMs etc, all utilizing K-Fold Cross Validation. The test results indicate that both Naive Bayes without K-Fold Cross Validation and SVM with K-Fold Cross Validation achieve a high accuracy rate of 91%. In conclusion, the segmentation method employing K-Means and HSV demonstrates its effectiveness in achieving high accuracy in the testing process for plant leaf segmentation
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