The Predation of Artemia Nauplii by the Larvae of the Amazon River Prawn, Macrobrachium amazonicum (Heller, 1862), is Affected by Prey Density, Time of Day, and Ontogenetic Development

The present study analyzed the effects of prey density, the time of day, and ontogenetic development on the predation of Artemia nauplii by the larvae of the Amazon river prawn, Macrobrachium amazonicum, as well as possible synergy among these factors. Larvae were raised in 120-L tanks with biological filter systems, and fed on recently hatched Artemia nauplii, using two feeding management protocols: (a) fed once per day at 2000 h (high density HD) and (b) half of the ration provided at 2000 h, complemented at 0800 h the following day by a replacement of the nauplii consumed up to a maximum of the full ration (low density with replacement LDWR). Each treatment consisted of six replicates. The consumption of nauplii was estimated prior to the feeding times. Consumption varied according to time of day, ontogenetic development, and feeding protocol. The larvae ingested more nauplii during the daytime at most developmental stages. Ingestion rates were similar during the day under both treatments, but at night the higher density of prey in the HD treatment caused a higher encounter rate and increased ingestion of nauplii by the larvae. Among the performance indicators only survival was greater in HD in comparison with LDWR; productivity and dry weight were similar. The results indicate a circadian trophic rhythm in M. amazonicum, with the encounter rate being an important mechanism for the capture of prey during the night. A second mechanism probably the visual system aids the perception of prey during the daytime. Based on these results, we suggest that feeding captive Amazon river prawn larvae only once a day would be appropriate and economically beneficial. Further work is necessary to determine the most effective time that this single feed should be applied.

Development of a new wine tasting method based on emotional responses

Mestrado Vinifera Euromaster - Instituto Superior de Agronomia - UL

Ampliação de movimentos na dança circular com pessoas com deficiência visual

This paper aims at studying how circular dance can afford to sight-disabled peoples movement and how they can learn to cope with the deep movement of relation, consciousness, appropriation and communion with the world. Inside circular dance, a cosmic metaphor, is inscribed the movement of the world, which tells and changes amorously the human history. In the works of Paulo Freire and Maurice Merleau-Ponty one can find the necessary support to discuss, as long as possible, movement and existence. Research-action is used as a methodological approach whose empirical center is placed on the Institute of Education and Rehabilitation of Blind, in Natal, which shelters eight sightdisabled adults. The research s data reveal that the practice of circular dance concurs to enlarge the movement of the research s subjects, to develop a more accurate perception of their selves and of their own capacities, as well as improve the relations Me/Others, Me/World, which require a context of differences. The study has revealed that the practice of dance develops a better perception of the limits and surpasses as a human condition and, in consequence, the discovery of one s own body and the other s body as a resource of lessons and representations of the self and of the world. It lets out the development of a new way of thinking and coping with discrimination surrounding the disabled persons. In movement, in circular dance, the barrier between sight disablement and vision loses force.

DEVELOPMENT OF ION EXCHANGE MODELS FOR WATER TREATMENT AND APPLICATION TO THE INTERNATIONAL SPACE STATION WATER PROCESSOR

The International Space Station (ISS) requires a substantial amount of potable water for use by the crew. The economic and logistic limitations of transporting the vast amount of water required onboard the ISS necessitate onboard recovery and reuse of the aqueous waste streams. Various treatment technologies are employed within the ISS water processor to render the waste water potable, including filtration, ion exchange, adsorption, and catalytic wet oxidation. The ion exchange resins and adsorption media are combined in multifiltration beds for removal of ionic and organic compounds. A mathematical model (MFBMODEL™) designed to predict the performance of a multifiltration (MF) bed was developed. MFBMODEL consists of ion exchange models for describing the behavior of the different resin types in a MF bed (e.g., mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins) and an adsorption model capable of predicting the performance of the adsorbents in a MF bed. Multicomponent ion exchange ii equilibrium models that incorporate the water formation reaction, electroneutrality condition, and degree of ionization of weak acids and bases for mixed bed, strong acid cation, strong base anion, and weak base anion exchange resins were developed and verified. The equilibrium models developed use a tanks-inseries approach that allows for consideration of variable influent concentrations. The adsorption modeling approach was developed in related studies and application within the MFBMODEL framework was demonstrated in the Appendix to this study. MFBMODEL consists of a graphical user interface programmed in Visual Basic and Fortran computational routines. This dissertation shows MF bed modeling results in which the model is verified for a surrogate of the ISS waste shower and handwash stream. In addition, a multicomponent ion exchange model that incorporates mass transfer effects was developed, which is capable of describing the performance of strong acid cation (SAC) and strong base anion (SBA) exchange resins, but not including reaction effects. This dissertation presents results showing the mass transfer model's capability to predict the performance of binary and multicomponent column data for SAC and SBA exchange resins. The ion exchange equilibrium and mass transfer models developed in this study are also applicable to terrestrial water treatment systems. They could be applied for removal of cations and anions from groundwater (e.g., hardness, nitrate, perchlorate) and from industrial process waters (e.g. boiler water, ultrapure water in the semiconductor industry).

DEVELOPMENT AND VALIDATION OF THE ANTERIOR CRUCIATE LIGAMENT INJURY-RISK-ESTIMATION QUIZ (ACL-IQ)

Over 2 million Anterior Cruciate Ligament (ACL) injuries occur annually worldwide resulting in considerable economic and health burdens (e.g., suffering, surgery, loss of function, risk for re-injury, and osteoarthritis). Current screening methods are effective but they generally rely on expensive and time-consuming biomechanical movement analysis, and thus are impractical solutions. In this dissertation, I report on a series of studies that begins to investigate one potentially efficient alternative to biomechanical screening, namely skilled observational risk assessment (e.g., having experts estimate risk based on observations of athletes movements). Specifically, in Study 1 I discovered that ACL injury risk can be accurately and reliably estimated with nearly instantaneous visual inspection when observed by skilled and knowledgeable professionals. Modern psychometric optimization techniques were then used to develop a robust and efficient 5-item test of ACL injury risk prediction skill—i.e., the ACL Injury-Risk-Estimation Quiz or ACL-IQ. Study 2 cross-validated the results from Study 1 in a larger representative sample of both skilled (Exercise Science/Sports Medicine) and un-skilled (General Population) groups. In accord with research on human expertise, quantitative structural and process modeling of risk estimation indicated that superior performance was largely mediated by specific strategies and skills (e.g., ignoring irrelevant information), independent of domain general cognitive abilities (e.g., metal rotation, general decision skill). These cognitive models suggest that ACL-IQ is a trainable skill, providing a foundation for future research and applications in training, decision support, and ultimately clinical screening investigations. Overall, I present the first evidence that observational ACL injury risk prediction is possible including a robust technology for fast, accurate and reliable measurement—i.e., the ACL-IQ. Discussion focuses on applications and outreach including a web platform that was developed to house the test, provide a repository for further data collection, and increase public and professional awareness and outreach (www.ACL-IQ.org). Future directions and general applications of the skilled movement analysis approach are also discussed.

Development of Safety Performance Functions for SafetyAnalyst Applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency’s safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.

Development of an activity disease score in patients with uveitis (UVEDAI)

To develop a disease activity index for patients with uveitis (UVEDAI) encompassing the relevant domains of disease activity considered important among experts in this field. The steps for designing UVEDAI were: (a) Defining the construct and establishing the domains through a formal judgment of experts, (b) A two-round Delphi study with a panel of 15 experts to determine the relevant items, (c) Selection of items: A logistic regression model was developed that set ocular inflammatory activity as the dependent variable. The construct “uveitis inflammatory activity” was defined as any intraocular inflammation that included external structures (cornea) in addition to uvea. Seven domains and 15 items were identified: best-corrected visual acuity, inflammation of the anterior chamber (anterior chamber cells, hypopyon, the presence of fibrin, active posterior keratic precipitates and iris nodules), intraocular pressure, inflammation of the vitreous cavity (vitreous haze, snowballs and snowbanks), central macular edema, inflammation of the posterior pole (the presence and number of choroidal/retinal lesions, vascular inflammation and papillitis), and global assessment from both (patient and physician). From all the variables studied in the multivariate model, anterior chamber cell grade, vitreous haze, central macular edema, inflammatory vessel sheathing, papillitis, choroidal/retinal lesions and patient evaluation were included in UVEDAI. UVEDAI is an index designed to assess the global ocular inflammatory activity in patients with uveitis. It might prove worthwhile to motorize the activity of this extraarticular manifestation of some rheumatic diseases.

The Effects of Visual Discriminability and Rotation Angle on 30-Month-Olds’ Search Performance in Spatial Rotation Tasks

Tracking objects that are hidden and then moved is a crucial ability related to object permanence, which develops across several stages in early childhood. In spatial rotation tasks, children observe a target object that is hidden in one of two or more containers before the containers are rotated around a fixed axis. Usually, 30-month-olds fail to find the hidden object after it was rotated by 180°. We examined whether visual discriminability of the containers improves 30-month-olds’ success in this task and whether children perform better after 90° than after 180° rotations. Two potential hiding containers with same or different colors were placed on a board that was rotated by 90° or 180° in a within-subjects design. Children (N D 29) performed above chance level in all four conditions. Their overall success in finding the object did not improve by differently colored containers. However, different colors prevented children from showing an inhibition bias in 90° rotations, that is, choosing the empty container more often when it was located close to them than when it was farther away: This bias emerged in the same colors condition but not in the different colors condition. Results are discussed in view of particular challenges that might facilitate or deteriorate spatial rotation tasks for young children.

Affordances and Language: How the Level of Object Familiarity modulates the Manipulation and Categorization of Objects across Development

According to much evidence, observing objects activates two types of information: structural properties, i.e., the visual information about the structural features of objects, and function knowledge, i.e., the conceptual information about their skilful use. Many studies so far have focused on the role played by these two kinds of information during object recognition and on their neural underpinnings. However, to the best of our knowledge no study so far has focused on the different activation of this information (structural vs. function) during object manipulation and conceptualization, depending on the age of participants and on the level of object familiarity (familiar vs. non-familiar). Therefore, the main aim of this dissertation was to investigate how actions and concepts related to familiar and non-familiar objects may vary across development. To pursue this aim, four studies were carried out. A first study led to the creation of the Familiar and Non-Familiar Stimuli Database, a set of everyday objects classified by Italian pre-schoolers, schoolers, and adults, useful to verify how object knowledge is modulated by age and frequency of use. A parallel study demonstrated that factors such as sociocultural dynamics may affect the perception of objects. Specifically, data for familiarity, naming, function, using and frequency of use of the objects used to create the Familiar And Non-Familiar Stimuli Database were collected with Dutch and Croatian children and adults. The last two studies on object interaction and language provide further evidence in support of the literature on affordances and on the link between affordances and the cognitive process of language from a developmental point of view, supporting the perspective of a situated cognition and emphasizing the crucial role of human experience.

Development of an innovative strategy to enhance the efficacy of gene therapy for CDKL5 deficiency disorder

CDKL5 (cyclin-dependent kinase-like 5) deficiency disorder (CDD) is a severe X-linked neurodevelopmental disease caused by mutations in the CDKL5 gene, characterized by early-onset epileptic seizures, intellectual disability, motor and visual impairment and respiratory dysregulation. Although pharmacological treatments are used to control seizures, there is currently no cure to ameliorate symptoms for CDD. Albeit delivery of a wild-type copy of the mutated gene to cells represents the most curative approach for a monogenic disease, proof-of-concept studies highlight significant efficacy caveats for brain gene therapy. The major one regards the low efficiency of gene delivery to the CNS by viral vectors. We used a secretable Igk-TATk-CDKL5 protein to enhance the efficiency of a gene therapy for CDD. In view of the properties of the Igk-chain leader sequence, the TATk-CDKL5 protein produced by infected cells is secreted via constitutive secretory pathways. Importantly, due to the transduction property of the TATk peptide, the secreted CDKL5 protein is internalized by cells. We compared the effects of a CDKL5 gene therapy with an IgK-TATk-CDKL5 gene therapy in a Cdkl5 KO mouse model to validate whether the Igk-TATk-CDKL5 approach significantly improve the therapeutic efficacy. We found that, although AAVPHP.B_Igk-TATk-CDKL5 and AAVPHP.B_CDKL5 vectors had similar brain infection efficiency, the AAVPHP.B_Igk-TATk-CDKL5 vector led to a higher CDKL5 protein replacement and Cdkl5 KO mice treated with the AAVPHP.B_Igk-TATk-CDKL5 vector showed a behavioral and neuroanatomical improvement in comparison with Cdkl5 KO mice treated with the AAVPHP.B_CDKL5 vector.

Alpha oscillations index the functionality and the plastic changes of the visual system

Alpha oscillations are linked to visual awareness and to the periodical sampling of visual information, suggesting that alpha rhythm reflect an index of the functionality of the posterior cortices, and hence of the visual system. Therefore, the present work described a series of studies investigating alpha oscillations as a biomarker of the functionality and the plastic modifications of the visual system in response to lesions to the visual cortices or to external stimulations. The studies presented in chapter 5 and 6 showed that posterior lesions alter alpha oscillations in hemianopic patients, with reduced alpha reactivity at the eyes opening and decreased alpha functional connectivity, especially in right-lesioned hemianopics, with concurrent dysfunctions in the theta range, suggesting a specialization of the right hemisphere in orchestrating alpha oscillations and coordinating complex interplays among different brain rhythms. The study presented in chapter 7 investigated a mechanism of rhythmical attentional sampling of visual information in healthy participants, showing that perceptual performance is influenced by a rhythmical mechanism of attentional allocation, occurring at lower-alpha frequencies (i.e., 7 Hz), when a single spatial location is monitored, and at lower frequencies (i.e., 5 Hz), when attention is allocated to two spatial locations. Moreover, the right hemisphere seemed to have a dominance in this rhythmical attentional sampling, distributing attentional resources to the entire visual field. Finally, the study presented in chapter 8 showed that prolonged visual entrainment induce long-term modulations of resting-state alpha activity in healthy participants, suggesting that persistent modifications in the functionality of the visual system are possible. Altogheter, these findings show that functional processes and plastic changes of the visual system are reflected in alpha oscillatory patterns. Therefore, investigating and promoting alpha oscillations may contribute to the development of rehabilitative protocols to ameliorate the functionality of the visual system, in brain lesioned patients.

Development of unsupervised learning methods with applications to life sciences data

Machine Learning makes computers capable of performing tasks typically requiring human intelligence. A domain where it is having a considerable impact is the life sciences, allowing to devise new biological analysis protocols, develop patients’ treatments efficiently and faster, and reduce healthcare costs. This Thesis work presents new Machine Learning methods and pipelines for the life sciences focusing on the unsupervised field. At a methodological level, two methods are presented. The first is an “Ab Initio Local Principal Path” and it is a revised and improved version of a pre-existing algorithm in the manifold learning realm. The second contribution is an improvement over the Import Vector Domain Description (one-class learning) through the Kullback-Leibler divergence. It hybridizes kernel methods to Deep Learning obtaining a scalable solution, an improved probabilistic model, and state-of-the-art performances. Both methods are tested through several experiments, with a central focus on their relevance in life sciences. Results show that they improve the performances achieved by their previous versions. At the applicative level, two pipelines are presented. The first one is for the analysis of RNA-Seq datasets, both transcriptomic and single-cell data, and is aimed at identifying genes that may be involved in biological processes (e.g., the transition of tissues from normal to cancer). In this project, an R package is released on CRAN to make the pipeline accessible to the bioinformatic Community through high-level APIs. The second pipeline is in the drug discovery domain and is useful for identifying druggable pockets, namely regions of a protein with a high probability of accepting a small molecule (a drug). Both these pipelines achieve remarkable results. Lastly, a detour application is developed to identify the strengths/limitations of the “Principal Path” algorithm by analyzing Convolutional Neural Networks induced vector spaces. This application is conducted in the music and visual arts domains.

Mind the gaps: cognitive-inspired AI for high-level visual sensemaking. Towards abstract concept image classification

The abundance of visual data and the push for robust AI are driving the need for automated visual sensemaking. Computer Vision (CV) faces growing demand for models that can discern not only what images "represent," but also what they "evoke." This is a demand for tools mimicking human perception at a high semantic level, categorizing images based on concepts like freedom, danger, or safety. However, automating this process is challenging due to entropy, scarcity, subjectivity, and ethical considerations. These challenges not only impact performance but also underscore the critical need for interoperability. This dissertation focuses on abstract concept-based (AC) image classification, guided by three technical principles: situated grounding, performance enhancement, and interpretability. We introduce ART-stract, a novel dataset of cultural images annotated with ACs, serving as the foundation for a series of experiments across four key domains: assessing the effectiveness of the end-to-end DL paradigm, exploring cognitive-inspired semantic intermediaries, incorporating cultural and commonsense aspects, and neuro-symbolic integration of sensory-perceptual data with cognitive-based knowledge. Our results demonstrate that integrating CV approaches with semantic technologies yields methods that surpass the current state of the art in AC image classification, outperforming the end-to-end deep vision paradigm. The results emphasize the role semantic technologies can play in developing both effective and interpretable systems, through the capturing, situating, and reasoning over knowledge related to visual data. Furthermore, this dissertation explores the complex interplay between technical and socio-technical factors. By merging technical expertise with an understanding of human and societal aspects, we advocate for responsible labeling and training practices in visual media. These insights and techniques not only advance efforts in CV and explainable artificial intelligence but also propel us toward an era of AI development that harmonizes technical prowess with deep awareness of its human and societal implications.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

[the Use Of Fish On Buccal Smear To Investigate Mosaicism With A 45,x Cell Line: Study On Healthy Men And Patients With Disorders Of Sex Development].

To verify whether fluorescence in situ hybridization (FISH) of cells from the buccal epithelium could be employed to detect cryptomosaicism with a 45,X lineage in 46,XY patients. Samples of nineteen 46,XY healthy young men and five patients with disorders of sex development (DSD), four 45,X/46,XY and one 46,XY were used. FISH analysis with X and Y specific probes on interphase nuclei from blood lymphocytes and buccal epithelium were analyzed to investigate the proportion of nuclei containing only the signal of the X chromosome. The frequency of nuclei containing only the X signal in the two tissues of healthy men did not differ (p = 0.69). In all patients with DSD this frequency was significantly higher, and there was no difference between the two tissues (p = 0.38), either. Investigation of mosaicism with a 45,X cell line in patients with 46,XY DSD or sterility can be done by FISH directly using cells from the buccal epithelium.