Abstract
Landslide is a hazard that threaten the people who lives in the mountain area, it comes active especially rainy seasons and causes a large number of casualties every year. The movement of the slope is an indicator of activity of the landslide, it is helpful to capture the precursor of the activity, the monitoring of the movement of the slope is very important. However it is a difficult problem due to complex topography, cloudy and rainy weather for optical sensors, In this paper we will show the capability of up-to-date Advanced Land Observing Satellite-2 (ALOS-2) Synthetic Aperture Radar (SAR) data in monitoring the movement of the landslide which located in south China, which can capture the fast and slow movement with different spatial and temporal baseline combination, the results shows that the L-band SAR data has its advantage in monitoring the movement of the landslides especially in the low latitude, cloudy and rainy area.

Abstract
This paper shows by examples how the Theory of Programming can be taught to first-year CS undergraduates. The only prerequisite is their High School acquaintance with algebra, geometry, and propositional calculus. The main purpose of teaching the subject is to support practical programming assignments and projects throughout the degree course. The aims would be to increase the student’s enjoyment of programming, reduce the workload, and increase the prospect of success. © 2019, Springer Nature Switzerland AG.

Abstract
Resumo A ana´lise de sinais biome´dicos desempenha, atualmente, um papel fundamental no auxi´lio ao diagno´stico cli´nico. Os avanc¸os cienti´ficos multiplicam-se a um ritmo frene´tico numa sociedade cada vez mais consciente e desejosa de soluc¸o~es para os problemas de sau´de. Este trabalho pretende dar uma perspetiva histo´rica dos avanc¸os no estudo dos sinais biome´dicos e refletir a sua importa^ncia na sociedade.Palavras-chave: Sinais Biome´dicos; diagno´stico cli´nico; avanc¸os Abstract Currently the biomedical signal analysis plays a fundamental role in helping clinical diagnosis. Scientific advances multiply at a frenetic pace in a society that is increasingly aware of and desirous of solutions to health problems. The need for constant updating of the means of clinical diagnosis is necessary to meet the demands of the world today. This work intends to give a historical perspective of advances in the biomedical signal study and to reflect its importance in society. Keywords: Biomedical Signal analysis, clinical diagnosis, scientific advances

Abstract
Objectives: This study sought to evaluate whether velocity of naturally occurring myocardial shear waves (SW) could relate to myocardial stiffness (MS) in vivo. Background: Cardiac SW imaging has been proposed as a noninvasive tool to assess MS. SWs occur after mechanical excitation of the myocardium (e.g., mitral valve closure [MVC] and aortic valve closure [AVC]), and their propagation velocity is theoretically related to MS, thus providing an opportunity to assess stiffness at end-diastole (ED) and end-systole. However, given that SW propagation in vivo is complex, it remains unclear whether natural SW velocity effectively relates to MS. Methods: This study prospectively enrolled 50 healthy volunteers (HV) (43.7 ± 17.1 years of age) and 18 patients with cardiac amyloidosis (CA) (68.0 ± 9.8 years of age). HV were divided into 3 age groups: group I, 20 to 39 years of age (n = 24); group II, 40 to 59 years of age (n = 11); and group III, 60 to 80 years of age (n = 15). Parasternal long-axis views were acquired using an experimental scanner. Tissue (Doppler) acceleration maps were extracted from an anatomical M-mode along the midline of the left ventricular septum. Results: SW propagation velocity was significantly higher in CA patients than in HV after both MVC (3.54 ± 0.93 m/s vs. 6.33 ± 1.63 m/s, respectively; p < 0.001) and AVC (3.75 ± 0.76 m/s vs. 5.63 ± 1.13 m/s, respectively; p < 0.001). Similarly, SW propagation velocity differed significantly among age groups in HV, with a significantly higher value for group III than for group I, both occurring after MVC (p < 0.001) and AVC (p < 0.01). Moreover, SW propagation velocity after MVC was found to be significantly higher in patients with an increasing grade of diastolic dysfunction (p < 0.001). Finally, positive correlation was found between SW velocities after MVC and mitral inflow-to-mitral relaxation velocity ratio (E/E') (r = 0.74; p = 0.002). Conclusions: End-diastole SW velocities were significantly higher in patients with CA, patients with a higher grade of diastolic dysfunction, and elderly volunteers. These findings thus suggest that the speed of naturally induced SWs may be related to MS. © 2019 American College of Cardiology Foundation

Abstract
Colloids and suspensions are part of our daily routines. Even the blood is considered a "naturally" occurring colloid. However, the majority of colloids are complex and composed by a diversity of nano to microparticles. The characterization of both synthetic and physiological fluids in terms of particulate types, size and surface characteristics plays a vital role in products formulation, and in the early diagnosis through the identification of abnormal scatterers in physiological fluids, respectively. Several methods have been proposed for characterizing suspensions, including imaging, electrical sensing counters, hydrodynamic or field flow fractionation. However, the Dynamic Light Scattering (DLS) has evolved as the most convenient method from these. Based also on the scattering signal, we propose a novel, simple and fast method able to determine the number of different scatterers type present in a suspension, without any previous information about its composition (in terms of particle classes). This is achieved by collecting features from a 980 nm laser back-scattered signal acquired through a polymeric lensed optical fiber tip dipped into the solution. Unlike DLS, this technique allows the trapping of particles whose diameter >= 1 mu m. For smaller particles, despite not guaranteeing their immobilization, it is also able to determine the number of different nanoparticles classes in an ensemble. The number of particle types was correctly determined for suspensions of synthetic particles and yeasts; different bacteria; and 100 nm nanoparticles types, using both Principal Component Analysis and K-means algorithms. This method could be a valuable alternative to complex and time-consuming methods for particles separation, such as field flow fractionation.

Abstract
Social media are essentially changing the way firms communicate, create and collaborate in and for innovation. In this special issue introductory article, we take stock of the robust multi-faceted nature of research and practice at the intersection of social media (SM) and innovation. We introduce the nine papers included in this special issue and highlight the rich variety of their contribution with reference to our organising framework. Diagnosing from a strategic perspective, we position SM strategy in and for innovation as an overlapping interaction between dynamic capabilities (sensing, seizing, reconfiguration) and the level of stakeholder engagement (macro, meso, micro). We explain how each interaction holds distinctive synergy in an open and collaborative innovation process. This organising framework shows how the malleable nature of SM creates opportunities for firms to engage widely distributed knowledge sources, enhance innovation capabilities and empower internal human resources towards an open and collaborative culture. Yet, we warn that all is not as rosy as it seems and a purposeful and coherent strategy that delivers distinctive ‘co-ownership’ experiences is quintessential ingredient to realise profits from SM use in innovation.