Virtual Mobility and Learning for PhD students of six European Countries: students’ programme evaluation

In this paper, the authors, as teachers of the Virtual Mobility and Learning ERASMUS Intensive Programme (VML–IP), put forward an analysis of the student’s final evaluation of the Programme as to the most important competences they have developed. In terms of methodology, this study has an exploratory and descriptive nature; hence, being based on empiric evidence. Thus, in the last face-to-face session, students were asked by the Programme’s coordination to present an overall evaluation of their experience in the VML–IP. Data were collected in loco, i.e. through the posters created by each group, as well as the video of the students’ oral presentations. They were later analysed using content analysis as data analysis technique. The results unveil that, although the main goal was fulfilled – i.e. to be able to design and implement a course on a ‘Virtual Mobility and Learning’ topic underpinned by solid theoretical background in the area –, the fact is that every group also pointed out several soft competences as a very important part of their experiences, and crucial for their development as students and future professionals.

Awareness and Learning in Participatory Noise Sensing

The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.

High glucose mediates prooxidant and antioxidant enzyme activities in coronary endothelial cells

Objective: Excess levels of free radicals such as nitric oxide (NO) and superoxide anion (O2-)are associated with the pathogenesis of endothelial cell dysfunction in diabetes mellitus. This study was designed to investigate the underlying causes of oxidative stress in coronary microvascular endothelial cells (CMEC) exposed to hyperglycaemia. Methods: CMEC were cultured under normal (5.5 mmol/L) or high glucose (22 mmol/L)concentrations for 7 days. The activity and expression (protein level) of eNOS, iNOS, NAD(P)H oxidase and antioxidant enzymes, namely, superoxide dismutase (SOD), catalase and glutahione peroxidase (GPx) were investigated by specific activity assays and Western analyses,respectively while the effects of hyperglycaemia on nitrite and O2 - generation were investigated by Griess reaction and cytochrome C reduction assay, respectively. Results: Hyperglycaemia did not alter eNOS or iNOS protein expressions and overall nitrite generation, an index of NO production. However, it significantly reduced the levels of intracellular antioxidant glutathione by 50% (p<0.05) and increased the protein expressions and/or activities of p22-phox, a membrane-bound component of pro-oxidant NAD(P)H oxidase and antioxidant enzymes (p<0.05). Free radical-scavengers, namely, Tiron and MPG (0.1-1 mol/L) reduced hyperglycaemia-induced antioxidant enzyme activity and increased glutathione and nitrite generation to the levels observed in CMEC cultured in normoglycaemic medium (p<0.01). The differences in enzyme activity and expressions were independent of the increased osmolarity generated by high glucose levels as investigated by using equimolar concentrations of mannitol in parallel experiments. Conclusions: These results suggest that hyperglycaemia-induced oxidative stress may arise in CMEC as a result of enhanced prooxidant enzyme activity and diminished generation of 3 antioxidant glutathione. By increasing the antioxidant enzyme capacity CMEC may protect themselves against free radical-induced cell damage in diabetic conditions. The definitive version is available at http://www.blackwell-synergy.com

Spectral Frame Analysis and Learning through Graph Structure

This dissertation investigates the connection between spectral analysis and frame theory. When considering the spectral properties of a frame, we present a few novel results relating to the spectral decomposition. We first show that scalable frames have the property that the inner product of the scaling coefficients and the eigenvectors must equal the inverse eigenvalues. From this, we prove a similar result when an approximate scaling is obtained. We then focus on the optimization problems inherent to the scalable frames by first showing that there is an equivalence between scaling a frame and optimization problems with a non-restrictive objective function. Various objective functions are considered, and an analysis of the solution type is presented. For linear objectives, we can encourage sparse scalings, and with barrier objective functions, we force dense solutions. We further consider frames in high dimensions, and derive various solution techniques. From here, we restrict ourselves to various frame classes, to add more specificity to the results. Using frames generated from distributions allows for the placement of probabilistic bounds on scalability. For discrete distributions (Bernoulli and Rademacher), we bound the probability of encountering an ONB, and for continuous symmetric distributions (Uniform and Gaussian), we show that symmetry is retained in the transformed domain. We also prove several hyperplane-separation results. With the theory developed, we discuss graph applications of the scalability framework. We make a connection with graph conditioning, and show the in-feasibility of the problem in the general case. After a modification, we show that any complete graph can be conditioned. We then present a modification of standard PCA (robust PCA) developed by Cand\`es, and give some background into Electron Energy-Loss Spectroscopy (EELS). We design a novel scheme for the processing of EELS through robust PCA and least-squares regression, and test this scheme on biological samples. Finally, we take the idea of robust PCA and apply the technique of kernel PCA to perform robust manifold learning. We derive the problem and present an algorithm for its solution. There is also discussion of the differences with RPCA that make theoretical guarantees difficult.

Harpalycin 2 inhibits the enzymatic and platelet aggregation activities of PrTX-III, a D49 phospholipase A(2) from Bothrops pirajai venom

Background: Harpalycin 2 (HP-2) is an isoflavone isolated from the leaves of Harpalyce brasiliana Benth., a snakeroot found in northeast region of Brazil and used in folk medicine to treat snakebite. Its leaves are said to be anti-inflammatory. Secretory phospholipases A(2) are important toxins found in snake venom and are structurally related to those found in inflammatory conditions in mammals, as in arthritis and atherosclerosis, and for this reason can be valuable tools for searching new anti-phospholipase A(2) drugs.Methods: HP-2 and piratoxin-III (PrTX-III) were purified through chromatographic techniques. The effect of HP-2 in the enzymatic activity of PrTX-III was carried out using 4-nitro-3-octanoyloxy-benzoic acid as the substrate. PrTX-III induced platelet aggregation was inhibited by HP-2 when compared to aristolochic acid and p-bromophenacyl bromide (p-BPB). In an attempt to elucidate how HP-2 interacts with PrTX-III, mass spectrometry, circular dichroism and intrinsic fluorescence analysis were performed. Docking scores of the ligands (HP-2, aristolochic acid and p-BPB) using PrTX-III as target were also calculated.Results: HP-2 inhibited the enzymatic activity of PrTX-III (IC50 11.34 +/- 0.28 mu g/mL) although it did not form a stable chemical complex in the active site, since mass spectrometry measurements showed no difference between native (13,837.34 Da) and HP-2 treated PrTX-III (13,856.12 Da). A structural analysis of PrTX-III after treatment with HP-2 showed a decrease in dimerization and a slight protein unfolding. In the platelet aggregation assay, HP-2 previously incubated with PrTX-III inhibited the aggregation when compared with untreated protein. PrTX-III chemical treated with aristolochic acid and p-BPB, two standard PLA(2) inhibitors, showed low inhibitory effects when compared with the HP-2 treatment. Docking scores corroborated these results, showing higher affinity of HP-2 for the PrTX-III target (PDB code: 1GMZ) than aristolochic acid and p-BPB. HP-2 previous incubated with the platelets inhibits the aggregation induced by untreated PrTX-III as well as arachidonic acid.Conclusion: HP-2 changes the structure of PrTX-III, inhibiting the enzymatic activity of this enzyme. In addition, PrTX-III platelet aggregant activity was inhibited by treatment with HP-2, p-BPB and aristolochic acid, and these results were corroborated by docking scores.

Global interactions between fire and vegetation, human activities and climate

Doutoramento em Engenharia Florestal - Instituto Superior de Agronomia - UL

Developing and Improving EFL Writing Skills

Learning a foreign language is a process that entails the development of four basic skills: Listening, Speaking, Reading, and Writing. According to the Common European Framework, such skills can be grouped into productive and receptive. Reading and Listening are categorized as receptive skills, while speaking and writing are productive skills. Students’ and teachers’ experience along with research findings suggest that most learners of English as a foreign language (EFL) find productive skills more difficult to develop than receptive skill, and writing skills the hardest to acquire and improve. Learning to write is a complex process that calls for a wide range of cognitive and linguistic strategies to be used, most of which EFL students are not fully aware of. The purpose of this talk is to help EFL college majors become aware of the factors that make EFL discourse sound stilted and foreign. Good writing results from rational thinking, logical organization, and appropriate use of language. Sample texts will be looked at identify the strengths and weaknesses in each case.

Antipyretic, analgesic and anti-inflammatory activities of methanol extract of root bark of Acacia jacquemontii Benth (Fabaceae) in experimental animals

Purpose: To investigate the ethnomedicinal claims regarding the use of Acacia jacquemontii Benth. (Fabaceae) in fever, pain and inflammation. Methods: The methanol root bark extract (AJRBM) of the plant was used in the studies. Preliminary phytochemical screening of the extract was carried out according to established methods. Analgesic, anti-inflammatory and antipyretic activities were evaluated using acetic acid-induced writhing, carrageennan-induced rat paw edema and Brewer’s yeast-induced pyrexia models, respectively. The extract was administered at doses of 50 and 100 mg/kg. Aspirin (300 mg/kg, p.o.) was used as a reference drug in all models. Normal saline (10 mL/kg p.o.) was used as negative control. Results: Phytochemical screening results indicate the presence of cardioactive glycosides, tannins, flavonoids and saponins. In the acetic acid-induced writhing model, the methanol extract exhibited significant (p < 0.05) analgesic effect with 58.98 % reduction in writhing response at a dose of 100 mg/kg, compared with untreated control group. The extract significantly (p < 0.05) reduced carrageenan-induced edema at doses of 50 and 100 mg/kg to 36.84 and 47.36 %, respectively, after 1 h of extract administration. The extract exhibited predominantly dose-dependent antipyretic effect in Brewer’s yeast-induced pyrexia model. Maximum reduction in body temperature to 37.07 and 38.29 ºC at doses of 50 and 100 mg/kg, respectively, was observed, compared with untreated group (38.90 ºC) after 1 h, but this was not significant (p < 0.05). Conclusion: The plant extract exerts inhibitory effect on peripheral pain stimuli, edema and dosedependent anti-pyrexia, and thus justifies the ethnomedicinal use of Acacia jacquemontii Benth. in the management of pain, fever and inflammation.

Phytochemical profile and some biological activities of three Centaurea species from Turkey

Purpose: To characterise the phytochemical profile of whole plants of Centaurea balsamita, C. depressa and C. lycopifolia with LC-ESI-MS/MS, and as well as their antioxidant, anticholinesterase and antimicrobial activities. Methods: Organic and aqueous extracts of the three Centaurea species were evaluated for DPPH free radical, ABTS cation radical scavenging and cupric reducing antioxidant capacity (CUPRAC). Acetyland butyryl-cholinesterase enzyme inhibition abilities of the extracts using petroleum ether, acetone, methanol and water were studied to determine anticholinesterase activity, while antimicrobial activity was determined by disc diffusion method using appropriate antimicrobial standards and organisms. The phytochemical components of the methanol extracts were assessed by LC-MS/MS. Results: The methanol extract of C. balsamita exhibited much higher DPPH free and ABTS cation radicals scavenging activities (with IC50 of 62.65 ± 0.97 and 24.21 ± 0.70 mg/ml, respectively) than the other extracts. The petroleum ether extracts of the plant species exhibited moderate inhibitory activity against butyrylcholinesterase enzymes while the acetone extract of C. balsamita showed good antifungal activity against Candida albicans. Quinic acid (17513 ± 813 μg/g, 63874 ± 3066 μg/g and 108234 ± 5195 μg/g) was the major compound found in the methanol extracts of C. balsamita, C. depressa and C. Lycopifolia, respectively. Conclusion: These results indicate quinic acid is the major compound in the three plant species and that Centaurea balsamita has significant antioxidant, anticholinesterase and antimicrobial properties. Further studies to identify the compounds in the extracts responsible for the activities are required.

FY2010 Annual Report Research, Intelligent Transportation Systems, and Technology Transfer Activities, October 18, 2011

Transportation research makes a difference for Iowans and the nation. Implementation of cost effective research projects contributes to a transportation network that is safer, more efficient, and longer lasting. Working in cooperation with our partners from universities, industry, other states, and FHWA, as well as participation in the Transportation Research Board (TRB), provides benefits for every facet of the DOT. This allows us to serve our communities and the traveling public more effectively. Pooled fund projects allow leveraging of funds for higher returns on investments. In 2010, Iowa led fifteen active pooled fund studies, participated in twenty-two others, and was wrapping-up, reconciling, and closing out an additional 6 Iowa Led pooled fund studies. In addition, non-pooled fund SPR projects included approximately 20 continued, 9 new, and over a dozen reoccurring initiatives such as the technical transfer/training program. Additional research is managed and conducted by the Office of Traffic and Safety and other departments in the Iowa DOT.

Variational and learning models for image and time series inverse problems

Inverse problems are at the core of many challenging applications. Variational and learning models provide estimated solutions of inverse problems as the outcome of specific reconstruction maps. In the variational approach, the result of the reconstruction map is the solution of a regularized minimization problem encoding information on the acquisition process and prior knowledge on the solution. In the learning approach, the reconstruction map is a parametric function whose parameters are identified by solving a minimization problem depending on a large set of data. In this thesis, we go beyond this apparent dichotomy between variational and learning models and we show they can be harmoniously merged in unified hybrid frameworks preserving their main advantages. We develop several highly efficient methods based on both these model-driven and data-driven strategies, for which we provide a detailed convergence analysis. The arising algorithms are applied to solve inverse problems involving images and time series. For each task, we show the proposed schemes improve the performances of many other existing methods in terms of both computational burden and quality of the solution. In the first part, we focus on gradient-based regularized variational models which are shown to be effective for segmentation purposes and thermal and medical image enhancement. We consider gradient sparsity-promoting regularized models for which we develop different strategies to estimate the regularization strength. Furthermore, we introduce a novel gradient-based Plug-and-Play convergent scheme considering a deep learning based denoiser trained on the gradient domain. In the second part, we address the tasks of natural image deblurring, image and video super resolution microscopy and positioning time series prediction, through deep learning based methods. We boost the performances of supervised, such as trained convolutional and recurrent networks, and unsupervised deep learning strategies, such as Deep Image Prior, by penalizing the losses with handcrafted regularization terms.

Integrated communication and learning towards autonomous mobile radio networks

The integration of distributed and ubiquitous intelligence has emerged over the last years as the mainspring of transformative advancements in mobile radio networks. As we approach the era of “mobile for intelligence”, next-generation wireless networks are poised to undergo significant and profound changes. Notably, the overarching challenge that lies ahead is the development and implementation of integrated communication and learning mechanisms that will enable the realization of autonomous mobile radio networks. The ultimate pursuit of eliminating human-in-the-loop constitutes an ambitious challenge, necessitating a meticulous delineation of the fundamental characteristics that artificial intelligence (AI) should possess to effectively achieve this objective. This challenge represents a paradigm shift in the design, deployment, and operation of wireless networks, where conventional, static configurations give way to dynamic, adaptive, and AI-native systems capable of self-optimization, self-sustainment, and learning. This thesis aims to provide a comprehensive exploration of the fundamental principles and practical approaches required to create autonomous mobile radio networks that seamlessly integrate communication and learning components. The first chapter of this thesis introduces the notion of Predictive Quality of Service (PQoS) and adaptive optimization and expands upon the challenge to achieve adaptable, reliable, and robust network performance in dynamic and ever-changing environments. The subsequent chapter delves into the revolutionary role of generative AI in shaping next-generation autonomous networks. This chapter emphasizes achieving trustworthy uncertainty-aware generation processes with the use of approximate Bayesian methods and aims to show how generative AI can improve generalization while reducing data communication costs. Finally, the thesis embarks on the topic of distributed learning over wireless networks. Distributed learning and its declinations, including multi-agent reinforcement learning systems and federated learning, have the potential to meet the scalability demands of modern data-driven applications, enabling efficient and collaborative model training across dynamic scenarios while ensuring data privacy and reducing communication overhead.

The impact of flavonoids on spatial memory in rodents: from behaviour to underlying hippocampal mechanisms

Emerging evidence suggests that a group of dietary-derived phytochemicals known as flavonoids are able to induce improvements in memory, learning and cognition. Flavonoids have been shown to modulate critical neuronal signalling pathways involved in processes of memory, and therefore are likely to affect synaptic plasticity and long-term potentiation mechanisms, widely considered to provide a basis for memory. Animal dietary supplementation studies have further shown that flavonoid-rich foods are able to reverse age-related spatial memory and spatial learning impairments. A more accurate understanding of how a particular spatial memory task works and of which aspects of memory and learning can be assessed in each case, are necessary for a correct interpretation of data relating to diet-cognition experiments. Further understanding of how specific behavioural tasks relate to the functioning of hippocampal circuitry during learning processes might be also elucidative of the specific observed memory improvements. The overall goal of this review is to give an overview of how the hippocampal circuitry operates as a memory system during behavioural tasks, which we believe will provide a new insight into the underlying mechanisms of the action of flavonoids on cognition.

Child Aggression in a Post-Communist Country: Race and Gender Aspects in a Cross-Cultural Comparison

Gypsies represent approximately 2.5% of the Czech population, but are considerably over-represented among the unemployed, prisoners, schooldropouts, neglected children, etc. Together with racist attitudes on the part of the majority, this causes strong inter-ethnic tension and obviouseconomic, moral and political problems. This research studied the way in which this situation is reflected in peer relations between Gypsy andmajority children in schools. Six samples of children (totalling 2974 children aged 7-15, of whom 15% were Gypsies) were studied through peernomination, teacher assessment and self-reporting. Gypsy/non-Gypsy and gender dichotomies were correlated with measures of aggression,victimisation and acceptance/rejection. The results showed that Gypsy children, both boys and girls, were more likely to nominate their Gypsy peers as aggressors than they nominatemajority children, implying that they tend to direct their rejection toward their own kind. The number of Gypsy children in a class was also animportant factor with Gypsies being more likely to be accepted and less likely to appear aggressive when they were only one or two in a class, thanin a class where there was a greater number of Gypsy pupils. When whole classes were taken as the unit of analysis, Gypsy children were seen asmore likely to behave aggressively in class by their Gypsy and non-Gypsy counterparts as well as by their teachers. At the same time they aremuch less likely to become victims of aggression than are non-Gypsy children, both boys and girls. Mr. Rican also found that the acceptance/rejection patterns of Gypsy children betray their unsatisfactory socialisation. Among their peers, Gypsyor non-Gypsy, they tend to prefer aggressors or children who teachers describe as showing little discipline or effort to succeed at school. Partialcorrelation to assess the influence of seniority on aggressiveness provided a warning that the recent lengthening of compulsory school attendance islikely to bring an increase in aggressiveness. He believes that Gypsy ethnic identity has lost many of its important positive aspects, making itsnegative aspects more prominent and more dangerous. He does however find some possible ways for teachers to reinforce the positive aspects ofGypsy children's identities in order to support their socialisation at schools.