852 resultados para Formative assessment framework. Assessment tools. Ames
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According to the Water Framework Directive (WFD) transitional waters should be differentiated according to type and, in some cases, divided into different water bodies. This raises a dilemma in trying to define parts of a continuum. In the sequence of WFD several indices have been proposed including the Estuarine Fish Assessment Index, which can be applied taking an estuary as a whole (EFAI - without water bodies division) or divided in water bodies (EFAI(WB)). The purpose of this work is to analyze the robustness of the Estuarine Fish Assessment Index, based on three different ways of dividing Portuguese estuaries into water bodies according to different criteria (criterion 1 - distance to the estuary mouth, criterion 2 - salinity and criterion 3 - morphology, salinity and human dimension as pressure and state). In this study we evaluated at which degree these three criteria could influence the ecological quality ratio (EQR) results, when the index was applied to water body level (EFAI(WB)). Also, for each estuary, the EQR(WB) results for each criterion of EFAI(WB) were combined and weighted according to the water bodies areas (EFAI overall weighted - EFAI(Ow)). Finally, it was compared if the results obtained for each criterion with the EFAI(OW) were similar to the results of the index application taking the estuary as a whole (EFAI without water bodies division). No significant differences were found in both cases, which indicated that this index is a robust method regarding the division of the estuaries in different water bodies, which is an important element of a fish-based multimetric tool for assessing estuarine ecological quality. However, in some cases, different ecological quality statuses were achieved when applying the EFAI(Ow) or the EFAI. This work addressed several aspects regarding the possible division of water bodies at the WFD context. (C) 2012 Elsevier Ltd. All rights reserved.
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The molecular profiling system was developed using directed terminal-restriction fragment length polymorphism (dT-RFLP) to characterize soil nematode assemblages by relative abundance of feeding guilds and validation by comparison to traditional morphological method. The good performance of these molecular tools applied to soil nematodes assemblages create an opportunity to develop a novel approach for rapid assessment of the biodiversity changes of benthic nematodes assemblages of marine and estuarine sediments. The main aim of this research is to combine morphological and molecular analysis of estuarine nematodes assemblages, to establish a tool for fast assessment of the biodiversity changes within habitat recovery of Zostera noltii seagrass beds; and validate the dT-RFLP as a high-throughput tool to assess the system recovery. It was also proposed to develop a database of sequences related to individuals identified at species level to develop a new taxonomic reference system. A molecular phylogenetic analysis of the estuarine nematodes has being performed. After morphological identification, barcoding of 18S rDNA are being determined for each nematode species and the results have shown a good degree of concordance between traditional morphology-based identification and DNA sequences. The digest strategy developed for soil nematodes is not suitable for marine nematodes. Then five samples were cloned and sequenced and the sequence data was used to design a new dT-RFLP strategy to adapt this tool to marine assemblages. Several solutions were presented by DRAT and tested empirically to select the solution that cuts most efficiently, separating the different clusters. The results of quantitative PCR showed differences in nematode density between two sampling stations according the abundance of the nematode density obtained by the traditional methods. These results suggest that qPCR could be a robust tool for enumeration of nematode abundance, saving time.
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The intersection of Artificial Intelligence and The Law stands for a multifaceted matter, and its effects set the advances on culture, organization, as well as the social matters, when the emergent information technologies are taken into consideration. From this point of view, the weight of formal and informal Conflict Resolution settings should be highlighted, and the use of defective data, information or knowledge must be emphasized. Indeed, it is hard to do it with traditional problem solving methodologies. Therefore, in this work the focus is on the development of decision support systems, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks. It is intended to evaluate the Quality-of-Judgments and the respective Degree-of-Confidence that one has on such happenings.
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On the one hand, pesticides may be absorbed into the body orally, dermally, ocularly and by inhalation and the human exposure may be dietary, recreational and/or occupational where toxicity could be acute or chronic. On the other hand, the environmental fate and toxicity of the pesticide is contingent on the physico-chemical characteristics of pesticide, the soil composition and adsorption. Human toxicity is also dependent on the exposure time and individual’s susceptibility. Therefore, this work will focus on the development of an Artificial Intelligence based diagnosis support system to assess the pesticide toxicological risk to humanoid, built under a formal framework based on Logic Programming to knowledge representation and reasoning, complemented with an approach to computing grounded on Artificial Neural Networks. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting.
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Plants of genus Schinus are native South America and introduced in Mediterranean countries, a long time ago. Some Schinus species have been used in folk medicine, and Essential Oils of Schinus spp. (EOs) have been reported as having antimicrobial, anti-tumoural and anti-inflammatory properties. Such assets are related with the EOs chemical composition that depends largely on the species, the geographic and climatic region, and on the part of the plants used. Considering the difficulty to infer the pharmacological properties of EOs of Schinus species without a hard experimental setting, this work will focus on the development of an Artificial Intelligence grounded Decision Support System to predict pharmacological properties of Schinus EOs. The computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters to the handling of incomplete, unknown, or even self-contradictory information. New clustering methods centered on an analysis of attribute’s similarities were used to distinguish and aggregate historical data according to the context under which it was added to the Case Base, therefore enhancing the prediction process.
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It is well known that human resources play a valuable role in a sustainable organizational development. Indeed, this work will focus on the development of a decision support system to assess workers’ satisfaction based on factors related to human resources management practices. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data or knowledge in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process.
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This paper focus on the development of an algorithm using Matlab to generate Typical Meteorological Years from weather data of eight locations in the Madeira Island and to predict the energy generation of photovoltaic systems based on solar cells modelling. Solar cells model includes the effect of ambient temperature and wind speed. The analysis of the PV system performance is carried out through the Weather Corrected Performance Ratio and the PV system yield for the entire island is estimated using spatial interpolation tools.
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Background The evaluation of the elderly’s ability to manage medication through the use of a validated tool can be a significant step in identifying inabilities and needs, with the objective of increasing their self-care skills, and promoting successful aging. Aim of the review To identify studies assessing the elderly’s functional ability to manage their own medication. Method For the search strategy, the PICO method was used: P—Population(elderly), I—Instruments (tools for assessing medication management ability), C—Context (community) and O—Outcomes (functional ability to manage medication). Thefinal search query was run in MEDLINE/PubMed,CINAHL Plus, ISI Web of Science and Scopus. The whole process was developed according to the PRISMA statement. Results The search retrieved 8051 records. In each screening stage, the selection criteria were applied to eliminate records where at least one of the exclusion criteria was verified. At the end of this selection, we obtained a total of 18 papers (17 studies). The results allow the conclusion to be drawn that studies use several different instruments, most of them not validated. The authors agree that medication management abilities decrease as cognitive impairment increases, even if a lot of studies assess only the physical dimension. DRUGS was the instrument most often used. Conclusion Older adults’ ability to manage their medication should be assessed using tools specifically built and validate for the purpose. DRUGS (which uses the real regimen taken by the elderly) was the most widely used assessment instrument in the screened studies.
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In Europe, the concerns with the status of marine ecosystems have increased, and the Marine Directive has as main goal the achievement of Good Environmental Status (GES) of EU marine waters by 2020. Molecular tools are seen as promising and emerging approaches to improve ecosystem monitoring, and have led ecology into a new era, representing perhaps the most source of innovation in marine monitoring techniques. Benthic nematodes are considered ideal organisms to be used as biological indicator of natural and anthropogenic disturbances in aquatic ecosystems underpinning monitoring programmes on the ecological quality of marine ecosystems, very useful to assess the GES of the marine environment. dT-RFLP (directed Terminal-Restriction Fragment Length Polymorphism) allows to assess the diversity of nematode communities, but also allows studying the functioning of the ecosystem, and combined with relative real-time PCR (qPCR), provides a high-throughput semi-quantitative characterization of nematode communities. These characteristics make the two molecular tools good descriptors for the good environmental status assessment. The main aim of this study is to develop and optimize the dT-RFLP and qPCR in Mira estuary (SW coast, Portugal). A molecular phylogenetic analysis of marine and estuarine nematodes is being performed combining morphological and molecular analysis to evaluate the diversity of free-living marine nematodes in Mira estuary. After morphological identification, barcoding of 18S rDNA and COI genes are being determined for each nematode species morphologically identified. So far we generated 40 new sequences belonging to 32 different genus and 17 families, and the study has shown a good degree of concordance between traditional morphology-based identification and DNA sequences. These results will improve the assessment of marine nematode diversity and contribute to a more robust nematode taxonomy. The DNA sequences are being used to develop the dT-RFLP with the ability to easily process large sample numbers (hundreds and thousands), rather than typical of classical taxonomic or low throughput molecular analyses. A preliminary study showed that the digest enzymes used in dT-RFLP for terrestrial assemblages separated poorly the marine nematodes at taxonomic level for functional group analysis. A new digest combination was designed using the software tool DRAT (Directed Terminal Restriction Analysis Tool) to distinguished marine nematode taxa. Several solutions were provided by DRAT and tested empirically to select the solution that cuts most efficiently. A combination of three enzymes and a single digest showed to be the best solution to separate the different clusters. Parallel to this, another tool is being developed to estimate the population size (qPCR). An improvement in qPCR estimation of gene copy number using an artificial reference is being performed for marine nematodes communities to quantify the abundance. Once developed, it is proposed to validate both methodologies by determining the spatial and temporal variability of benthic nematodes assemblages across different environments. The application of these high-throughput molecular approaches for benthic nematodes will improve sample throughput and their implementation more efficient and faster as indicator of ecological status of marine ecosystems.
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A link between patterns of pelvic growth and human life history is supported by the finding that, cross-culturally, variation in maturation rates of female pelvis are correlated with variation in ages of menarche and first reproduction, i.e., it is well known that the human dimensions of the pelvic bones depend on the gender and vary with the age. Indeed, one feature in which humans appear to be unique is the prolonged growth of the pelvis after the age of sexual maturity. Both the total superoinferior length and mediolateral breadth of the pelvis continues to grow markedly after puberty, and do not reach adult proportions until the late teens years. This continuation of growth is accomplished by relatively late fusion of the separate centers of ossification that form the bones of the pelvis. Hence, in this work we will focus on the development of an intelligent decision support system to predict individual’s age based on a pelvis' dimensions criteria. Some basic image processing techniques were applied in order to extract the relevant features from pelvic X-rays, being the computational framework built on top of a Logic Programming approach to Knowledge Representation and Reasoning that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.
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The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestations. This autoimmune hypercoagulable state, usually known as Hughes syndrome, has severe consequences for the patients, being one of the main causes of thrombotic disorders and death. Therefore, it is required to be preventive; being aware of how probable is to have that kind of syndrome. Despite the updated of antiphospholipid syndrome classification, the diagnosis remains difficult to establish. Additional research on clinically relevant antibodies and standardization of their quantification are required in order to improve the antiphospholipid syndrome risk assessment. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model allows for improving the diagnosis, classifying properly the patients that really presented this pathology (sensitivity higher than 85%), as well as classifying the absence of APS (specificity close to 95%).
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The porpoise of this study was to implement research methodologies and assess the effectiveness and impact of management tools to promote best practices for the long term conservation of the endangered African wild dog (Lycaon pictus). Different methods were included in the project framework to investigate and expand the applicability of these methodologies to free-ranging African wild dogs in the southern African region: ethology, behavioural endocrinology and ecology field methodologies were tested and implemented. Additionally, research was performed to test the effectiveness and implication of a contraceptive implant (Suprenolin) as a management tool for the species of a subpopulation hosted in fenced areas. Attention was especially given to social structure and survival of treated packs. This research provides useful tools and advances the applicability of these methods for field studies, standardizing and improving research instruments in the field of conservation biology and behavioural endocrinology. Results reported here provide effective methodologies to expand the applicability of non-invasive endocrine assessment to previously prohibited fields, and validation of sampling methods for faecal hormone analysis. The final aim was to fill a knowledge gap on behaviours of the species and provide a common ground for future researchers to apply non-invasive methods to this species research and to test the effectiveness of the contraception on a managed metapopulation.
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At the beginning, this Ph.D. project led to an overview of the most common and emerging types of fraud and possible countermeasures in the olive oil sector. Furthermore, possible weaknesses in the current conformity check system for olive oil were highlighted. Among those, despite the organoleptic assessment is a fundamental tool for establishing the virgin olive oils (VOOs) quality grade, the scientific community has evidenced some drawbacks in it. In particular, the application of instrumental screening methods to support the panel test could reduce the work of sensory panels and the cost of this analysis (e.g. for industries, distributors, public and private control laboratories), permitting the increase in the number and the efficiency of the controls. On this basis, a research line called “Quantitative Panel Test” is one of the main expected outcomes of the OLEUM project that is also partially discussed in this doctoral dissertation. In this framework, analytical activities were carried out, within this PhD project, aimed to develop and validate analytical protocols for the study of the profiles in volatile compounds (VOCs) of the VOOs headspace. Specifically, two chromatographic approaches, one targeted and one semi-targeted, to determine VOCs were investigated in this doctoral thesis. The obtained results, will allow the possible establishment of concentration limits and ranges of selected volatile markers, as related to fruitiness and defects, with the aim to support the panel test in the commercial categorization of VOOs. In parallel, a rapid instrumental screening method based on the analysis of VOCs has been investigated to assist the panel test through a fast pre-classification of VOOs samples based on a known level of probability, thus increasing the efficiency of quality control.
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Nowadays, information security is a very important topic. In particular, wireless networks are experiencing an ongoing widespread diffusion, also thanks the increasing number of Internet Of Things devices, which generate and transmit a lot of data: protecting wireless communications is of fundamental importance, possibly through an easy but secure method. Physical Layer Security is an umbrella of techniques that leverages the characteristic of the wireless channel to generate security for the transmission. In particular, the Physical Layer based-Key generation aims at allowing two users to generate a random symmetric keys in an autonomous way, hence without the aid of a trusted third entity. Physical Layer based-Key generation relies on observations of the wireless channel, from which harvesting entropy: however, an attacker might possesses a channel simulator, for example a Ray Tracing simulator, to replicate the channel between the legitimate users, in order to guess the secret key and break the security of the communication. This thesis work is focused on the possibility to carry out a so called Ray Tracing attack: the method utilized for the assessment consist of a set of channel measurements, in different channel conditions, that are then compared with the simulated channel from the ray tracing, to compute the mutual information between the measurements and simulations. Furthermore, it is also presented the possibility of using the Ray Tracing as a tool to evaluate the impact of channel parameters (e.g. the bandwidth or the directivity of the antenna) on the Physical Layer based-Key generation. The measurements have been carried out at the Barkhausen Institut gGmbH in Dresden (GE), in the framework of the existing cooperation agreement between BI and the Dept. of Electrical, Electronics and Information Engineering "G. Marconi" (DEI) at the University of Bologna.
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In 2014, the Bloomsbury Learning Environment (BLE) Consortium initiated a wide-ranging, two-year-long research and dissemination project focusing on the use of technology in assessment and feedback. Our aim was to understand and improve processes, practices, opportunities and tools available to the institutional members of the BLE Consortium. From the project, we produced three research papers investigating current practice and 21 case studies describing both technology-enabled pedagogy and technical development. Now presented as a free ebook, co-edited by Leo Havemann and Sarah Sherman, we offer the flavour of the variety and breadth of the BLE’s activities relating to the project theme as a contribution to the education sector’s widening conversation about the interplay of assessment, feedback, pedagogy and technology.