Instructional effectiveness of a computer-supported program for teaching reading comprehension strategies

This article examines the effectiveness of a computer-based instructional program (e-PELS) aimed at direct instruction in a collection of reading comprehension strategies. In e-PELS, students learn to highlight and outline expository passages based on various types of text structures (such as comparison or cause-and-effect) as well as to paraphrase, self-question, and summarize. The study involved 1041 fourth-grade elementary students from 21 schools distributed in three regions in central Chile. Participant teachers integrated this program into the Spanish language curriculum, instructing their students during thirty sessions of 90 min each during one school semester. Pretest-to-posttest gains in reading comprehension scores were significantly greater for students instructed with this program than for students who received traditional instruction (d = .5), with particularly strong effects for lower-achieving students (d = .7). The findings support the efficacy of direct instruction in specific learning strategies in a computer-based environment.     

Personalization in cultural heritage: the road travelled and the one ahead

Over the last 20?years, cultural heritage has been a favored domain for personalization research. For years, researchers have experimented with the cutting edge technology of the day; now, with the convergence of internet and wireless technology, and the increasing adoption of the Web as a platform for the publication of information, the visitor is able to exploit cultural heritage material before, during and after the visit, having different goals and requirements in each phase. However, cultural heritage sites have a huge amount of information to present, which must be filtered and personalized in order to enable the individual user to easily access it. Personalization of cultural heritage information requires a system that is able to model the user (e.g., interest, knowledge and other personal characteristics), as well as contextual aspects, select the most appropriate content, and deliver it in the most suitable way. It should be noted that achieving this result is extremely challenging in the case of first-time users, such as tourists who visit a cultural heritage site for the first time (and maybe the only time in their life). In addition, as tourism is a social activity, adapting to the individual is not enough because groups and communities have to be modeled and supported as well, taking into account their mutual interests, previous mutual experience, and requirements. How to model and represent the user(s) and the context of the visit and how to reason with regard to the information that is available are the challenges faced by researchers in personalization of cultural heritage. Notwithstanding the effort invested so far, a definite solution is far from being reached, mainly because new technology and new aspects of personalization are constantly being introduced. This article surveys the research in this area. Starting from the earlier systems, which presented cultural heritage information in kiosks, it summarizes the evolution of personalization techniques in museum web sites, virtual collections and mobile guides, until recent extension of cultural heritage toward the semantic and social web. The paper concludes with current challenges and points out areas where future research is needed.     

A mobility constraint model to infer sensor behaviour in forest fire risk monitoring

Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.     

Editorial

International Journal of Computer Vision -     

Hierarchies of parallel rewriting P systems — A survey

The paper is about some families of rewriting P systems, where the application of evolution rules is extended from the classical sequential rewriting to the parallel one (as, for instance, in Lindenmayer systems). As a result, consistency problems for the communication of strings may arise. Three variants of parallel rewriting P systems (already present in the literature) are considered here, together with the strategies they use to face the communication problem, and some parallelism methods for string rewriting are defined. We give a survey of all known results about each variant and we state some relations among the three variants, thus establishing hierarchies of parallel rewriting P systems. Various open problems related to the subject are also presented. Danicla Besozzi: She is assistant professor at the University of Milano. She received her M.S. in Mathematics (2000) from the University of Como and Ph.D. in Computer Science (2004) from the University of Milano. Her research interests cover topics in Formal Language Theory, Molecular Computing, Systems Biology. She is member of EATCS (European Association for Theoretical Computer Science) and EMCC (European Molecular Computing Consortium). Giancarlo Mauri: He is full professor of Computer Science at the University of Milano-Bicocca. His research interests are mainly in the area of theoretical computer science, and include: formal languages and automata, computational complexity, computational learning theory, soft computing techniques, cellular automata, bioinformatics and molecular computing. On these subjects, he published more than 150 scientific papers in international journals, contributed volumes and conference proceedings. Claudio Zandron: He received Ph.D. in Computer Science at the University of Milan, Italy, in 2001. Since 2002 he is assistant professor at the University of Milano-Bicocca, Italy. He is member of the EATCS (European Association for Theoretical Computer Science) and of EMCC (European Molecular Computing Consortium). His research interests are Molecular Computing (DNA and Membrane Computing) and Formal Languages.     

Proteins as biomarkers of oxidative/nitrosative stress in diseases: the contribution of redox proteomics

Reactive oxygen species (ROS) and reactive nitrogen species (RNS) contribute to the pathogenesis and/or progression of several human diseases. Proteins are important molecular signposts of oxidative/nitrosative damage. However, it is generally unresolved whether the presence of oxidatively/nitrosatively modified proteins has a causal role or simply reflects secondary epiphenomena. Only direct identification and characterization of the modified protein(s) in a given pathophysiological condition can decipher the potential roles played by ROS/RNS-induced protein modifications. During the last few years, mass spectrometry (MS)-based technologies have contributed in a significant way to foster a better understanding of disease processes. The study of oxidative/nitrosative modifications, investigated by redox proteomics, is contributing to establish a relationship between pathological hallmarks of disease and protein structural and functional abnormalities. MS-based technologies promise a contribution in a new era of molecular medicine, especially in the discovery of diagnostic biomarkers of oxidative/nitrosative stress, enabling early detection of diseases. Indeed, identification and characterization of oxidatively/nitrosatively modified proteins in human diseases has just begun.     

Sodium Alginate—Natural Microencapsulation Material of Polymeric Microparticles

From the multitude of materials currently available on the market that can be used in the development of microparticles, sodium alginate has become one of the most studied natural anionic polymers that can be included in controlled-release pharmaceutical systems alongside other polymers due to its low cost, low toxicity, biocompatibility, biodegradability and gelatinous die-forming capacity in the presence of Ca²⁺ ions. In this review, we have shown that through coacervation, the particulate systems for the dispensing of drugs consisting of natural polymers are nontoxic, allowing the repeated administration of medicinal substances and the protection of better the medicinal substances from degradation, which can increase the capture capacity of the drug and extend its release from the pharmaceutical form.     

A Comprehensive Assessment of Qualitative and Quantitative Prodromal Parkinsonian Features in Carriers of Gaucher Disease—Identifying Those at the Greatest Risk

Carriers of GBA1 gene variants have a significant risk of developing Parkinson’s disease (PD). A cohort study of GBA carriers between 40–75 years of age was initiated to study the presence of prodromal PD features. Participants underwent non-invasive tests to assess different domains of PD. Ninety-eight unrelated GBA carriers were enrolled (43 males) at a median age (range) of 51 (40–74) years; 71 carried the N370S variant (c.1226A > G) and 25 had a positive family history of PD. The Montreal Cognitive Assessment (MoCA) was the most frequently abnormal (23.7%, 95% CI 15.7–33.4%), followed by the ultrasound hyperechogenicity (22%, 95% CI 14–32%), Unified Parkinson’s Disease Rating Scale part III (UPDRS-III) (17.2%, 95% CI 10.2–26.4%), smell assessment (12.4%, 95% CI 6.6–20.6%) and abnormalities in sleep questionnaires (11%, 95% CI 5.7–19.4%). Significant correlations were found between tests from different domains. To define the risk for PD, we assessed the bottom 10th percentile of each prodromal test, defining this level as “abnormal”. Then we calculated the percentage of “abnormal” tests for each subject; the median (range) was 4.55 (0–43.5%). Twenty-two subjects had more than 15% “abnormal” tests. The limitations of the study included ascertainment bias of individuals with GBA-related PD in relatives, some incomplete data due to technical issues, and a lack of well-characterized normal value ranges in some tests. We plan to enroll additional participants and conduct longitudinal follow-up assessments to build a model for identifying individuals at risk for PD and investigate interventions aiming to delay the onset or perhaps to prevent full-blown PD.