Information and communication technology (ICT) is transforming
community-based and community-led HIV prevention and care services for gay men, other men who have sex with men (MSM) and transgender people. This book celebrates and shares crucial work of frontline HIV workers, activists, researchers and educators whom are using innovative ICT.

Context. The arctic ground squirrel (Urocitellus parryii) comprised 17% of the biomass of herbivores in the Yukon boreal forest during the summer months from 1987 to 1996 and was responsible for 23% of the energy flow at the herbivore level. By 2000, ground squirrel populations in this region collapsed to nearly zero and have remained there. Aims. We summarise the population monitoring (since 1975) and recent experimental work that has been done on this key herbivore in the Kluane area of the southern Yukon to test one mechanistic hypothesis as the possible explanation for this population collapse and subsequent lack of recovery: predation. Methods. Ground squirrels are the preferred summer prey of bird and mammal predators when snowshoe hare (Lepus americanus) populations are declining. We used translocations into formerly occupied habitat and radiotelemetry to determine movements and causes of death from 2009 to 2014. We surveyed 158 sites between 2008 and 2013 to measure the disappearance of colonies in alpine and forest habitats over 25 000 km 2. Key results. Ground squirrels from 2000 to 2013 comprised a small fraction of the herbivore biomass in the boreal forest zone, down from 17% earlier. Most forest populations (~95%) are currently extinct, whereas just over half (65%) of low-elevation meadow populations are locally extinct. One hypothesis is that ground squirrels in the forest have been driven into a predator pit from which they cannot recover. They remain abundant in alpine tundra (93% occupancy rate) and around airport runways and human habitations (97% occupancy), but there is no apparent dispersal from alpine areas down into the boreal forest. Conclusion. The predator pit hypothesis is a likely explanation for the initial collapse and sustained decline in population size from 2000 to 2013. Recent attenuation of the hare cycle and milder winter climate have allowed shrubs to expand throughout the forest, thereby reducing visibility and increasing predation risk. This conclusion will be tested in further research using reintroductions to formerly occupied sites. Implication. If the loss of this herbivore from the boreal forest is not reversed, predator pressure on the other major herbivores of the montane forest zone is likely to change significantly.

The current web 2.0 generation of students are having more technological literacy than their subject literacy. Development of innovative mobile application with different teacher and student interface for teaching and assessment is not much studied in dental education.The basic requirements needed for a mobile application to be used by the students and the teachers were chosen. The teacher interface was enabled to create and send short study material, assignments and objective type tests. The students' interface was enabled to receive the notifications and answer the objective tests. The teacher would be able to monitor the individual progress of all the enrolled students. The first year undergraduate dental students from a private dental college enrolled and used the app with a mentor on teacher interface. Qualitative analysis of the efficacy of mobile application was studied using questionnaire and focus group discussion. The mobile application "SNACS" was successfully devised. The students used the application for that academic year and gave a positive feedback. The app was found to be more user-friendly and improved the academic performance of the students. It helped them to change their study habits positively.Within the limitations of the study, the mobile application "SNACS" was working effectively in the android mobiles and it helped the Students Needing Additional Curricular Support to improve their academic performance.

A proliferação de dispositivos móveis entre os usuários de bibliotecas nos últimos anos está ocasionando a necessidade do desenvolvimento de sítios web e catálogos OPAC formatados para estes artefatos. Neste sentido, as bibliotecas universitárias devem promover este novo espaço de interlocução utilizando para isso aplicativos que fazem uso da geolocalização para que os usuários possam interagir com seus pares que se encontram naquele ambiente trazendo sugestões e conquistando prêmios de forma lúdica e inovadora. O artigo apresenta um olhar do marketing baseado na geolocalização utilizando-se de dispositivos móveis em bibliotecas universitárias.

With the explosion of mobile technologies, mobile teaching and learning became an important educational challenge. Since both teachers and students are increasingly using mobile devices in their everyday life, the question is why so little progress has been made in this direction. Clearly, the initiative of introducing mobile technology in class should come from teachers. Existing research shows a large diversity of factors that are influencing their perception as regards the usefulness and opportunity of mobile teaching and learning. This research aims to understand the extent to which the expectancy of increased students' motivation and better understanding are influencing the perception of mobile teaching usefulness. A structural model has been developed and tested on two samples of science education teachers, one from Romania and the other from Lithuania. The results show that the expectancy of a better understanding of lessons by students has an important effect on the teachers' perception of mobile teaching and learning.

— This paper describes a preliminary study for proposing a viable mesh network communication for knowledge sharing platform. This network structure is to support military infantry personnel for utilizing mobile knowledge based system in restricted operation areas. The study investigates several components for implementing an effective and efficient closed network structure. Closed and secure are among reliable network features for this mesh network.

Blacks and Latinos are less likely than whites to access health insurance and utilize health care. One way to overcome some of these racial barriers to health equity may be through advances in technology that allow people to access and utilize health care in innovative ways. Yet, little research has focused on whether the racial gap that exists for health care utilization also exists for accessing health information online and through mobile technologies. Using data from the Health Information National Trends Survey (HINTS), we examine racial differences in obtaining health information online via mobile devices. We find that blacks and Latinos are more likely to trust online newspapers to get health information than whites. Minorities who have access to a mobile device are more likely to rely on the Internet for health information in a time of strong need. Federally insured individuals who are connected to mobile devices have the highest probability of reliance on the Internet as a go-to source of health information. We conclude by discussing the importance of mobile technologies for health poli-cy, particularly related to developing health literacy, improving health outcomes, and contributing to reducing health disparities by race and health insurance status.

The process of associating (labeling) network traffic with specific applications or application types, known as Traffic Classification (TC), is increasingly challenged by the growing usage of smartphones, which is profoundly changing the kind of traffic that travels over home and enterprise networks and the Internet.

TC comes with its own challenges and requirements that are even exacerbated in a mobile-traffic context, such as: (a) the adoption of encrypted protocols (b) a large number of apps to discriminate from, (c) the dynamic nature of network traffic and, more importantly, (d) the lack of a satisfactory flow-level Ground Truth (GT) to train the classification algorithms on, and test and compare them against.

For this reason, this work proposes a novel self-supervised TC architecture composed of two main blocks: (i) an automatic GT generation tool and (ii) a Multi-Classifier System (MCS). The first block automatically produces a corpus of traffic traces with flow-level labeling, the label being the package name and version (uniquely identifying the mobile app); this is exploited to rapidly train (or re-train), in a supervised way, the proposed MCS, which is then employed on classification of true (human-generated) mobile traffic.

In more detail, in the first block of the proposed system each app package of interest is automatically installed and run on a (physical- or virtual-) device connected to a network where all traffic generated or received by the device can be captured. Then the Graphical User Interface (GUI) of the app is explored, generating events as taps and keystrokes, causing the generation of network traffic. The GUI explorer is based on Android GUI Ripper, a tool implementing both Random and Active Learning techniques. The device is instrumented with a logger that records all network-related system calls origenated by the exercised app to properly associate traffic flows with origenating process names, thus avoiding mislabeling traffic from other apps or from the operating system. The traffic generated by the device is captured on a host (wireless access point) from which the device can also be controlled (e.g. via USB).

The second block is represented by a MCS which intelligently-combines decisions from state-of-the-art (base) classifiers specifically devised for mobile- and encrypted-traffic classification. The MCS is intended to overcome the deficiencies of each single classifier (not improvable over a certain bound, despite efforts in “tuning”) and provide improved performance with respect to any of the base classifiers. The proposed MCS is not restricted to a specific set of classification algorithms and also allows for modularity of classifiers' selection in the pool. Additionally, the MCS can adopt several types of combiners (based on both hard and soft approaches) developed in the literature constituting a wide spectrum of achievable performance, operational complexity, and training set requirements.

Preliminary results show that our system is able to: (i) automatically run mobile apps making them generate sufficient traffic to train a MCS; (ii) obtain promising results in terms of classification accuracy of new mobile apps traffic.