A next application prediction service using the BaranC framework

Predicting user behaviour enables user assistant services provide personalized services to the users. This requires a comprehensive user model that can be created by monitoring user interactions and activities. BaranC is a framework that performs user interface (UI) monitoring (and collects all associated context data), builds a user model, and supports services that make use of the user model. A prediction service, Next-App, is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts, based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic, reflecting the current context, and is also dynamic in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.

Increasing the value of household appliances by adding a heat pump system

Historically, domestic tasks such as preparing food and washing and drying clothes and dishes were done by hand. In a modern home many of these chores are taken care of by machines such as washing machines, dishwashers and tumble dryers. When the first such machines came on the market customers were happy that they worked at all! Today, the costs of electricity and customers’ environmental awareness are high, so features such as low electricity, water and detergent use strongly influence which household machine the customer will buy. One way to achieve lower electricity usage for the tumble dryer and the dishwasher is to add a heat pump system. The function of a heat pump system is to extract heat from a lower temperature source (heat source) and reject it to a higher temperature sink (heat sink) at a higher temperature level. Heat pump systems have been used for a long time in refrigerators and freezers, and that industry has driven the development of small, high quality, low price heat pump components. The low price of good quality heat pump components, along with an increased willingness to pay extra for lower electricity usage and environmental impact, make it possible to introduce heat pump systems in other household products. However, there is a high risk of failure with new features. A number of household manufacturers no longer exist because they introduced poorly implemented new features, which resulted in low quality and product performance. A manufacturer must predict whether the future value of a feature is high enough for the customer chain to pay for it. The challenge for the manufacturer is to develop and produce a high-performance heat pump feature in a household product with high quality, predict future willingness to pay for it, and launch it at the right moment in order to succeed. Tumble dryers with heat pump systems have been on the market since 2000. Paper I reports on the development of a transient simulation model of a commercial heat pump tumble dryer. The measured and simulated results were compared with good similarity. The influence of the size of the compressor and the condenser was investigated using the validated simulation model. The results from the simulation model show that increasing the cylinder volume of the compressor by 50% decreases the drying time by 14% without using more electricity.  Paper II is a concept study of adding a heat pump system to a dishwasher in order to decrease the total electricity usage. The dishwasher, dishware and water are heated by the condenser, and the evaporator absorbs the heat from a water tank. The majority of the heat transfer to the evaporator occurs when ice is generated in the water tank. An experimental setup and a transient simulation model of a heat pump dishwasher were developed. The simulation results show a 24% reduction in electricity use compared to a conventional dishwasher heated with an electric element. The simulation model was based on an experimental setup that was not optimised. During the study it became apparent that it is possible to decrease electricity usage even more with the next experimental setup.

Searching for novel targets to control wheat Head Blight Disease-I-Protein identification, 3D modeling and virtual screening.

2016

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.

Methylmercury and polycyclic aromatic hydrocarbons in Mediterranean seafood: a molecular anthropological perspective

Seafood carries several contaminants, among which mercury and polycyclic aromatic hydrocarbons are those that cause major concern. Evidence exists that human populations are exposed to these environmental chemicals since ancient times, which may have driven the positive selection of specific genetic polymorphisms related to chemicals toxicokinetic. Both mercury and polycyclic aromatic hydrocarbons are able to cause DNA methylation changes in humans. Some Mediterranean populations may be particularly exposed to these contaminants, being the Mediterranean Sea at a high-risk for contamination by toxic compounds, and because of their traditionally high consumption of locally caught seafood. Starting from these premises the present thesis aims to contribute to the understanding of the molecular impact of seafood consumption on the biology of the Mediterranean population. To this end the work has been divided into four main parts: (1) the development and meta-analysis of a georeferenced database on polycyclic aromatic hydrocarbons in Mediterranean seafood aimed at identifying geographical patterns of contamination and trends that could be related to the biology of the marine organisms, to the physico-chemical properties of each hydrocarbon and to the oceanographic characteristic of the Mediterranean; (2) the development and validation of a food frequency questionnaire to estimate the intake of mercury through seafood consumption among a population living in a geographic area that is usually considered a contamination hotspot; (3) the creation of a biobank made of biological samples from members of several Italian communities together with information on their dietary habits, lifestyle and general health; (4) a review of the literature on the genetic component of individual susceptibility to methylmercury and polycyclic aromatic hydrocarbons exposure in humans, to the effects that these pollutants have on human DNA methylation, and to the evidence that Mediterranean coastal communities represent an informative case study to investigate the potential molecular impact of these chemicals.

Bio-QA-GNN: Reasoning with Language Models and Knowledge Graphs for Interpretable Biomedical Question Answering

Nowadays the idea of injecting world or domain-specific structured knowledge into pre-trained language models (PLMs) is becoming an increasingly popular approach for solving problems such as biases, hallucinations, huge architectural sizes, and explainability lack—critical for real-world natural language processing applications in sensitive fields like bioinformatics. One recent work that has garnered much attention in Neuro-symbolic AI is QA-GNN, an end-to-end model for multiple-choice open-domain question answering (MCOQA) tasks via interpretable text-graph reasoning. Unlike previous publications, QA-GNN mutually informs PLMs and graph neural networks (GNNs) on top of relevant facts retrieved from knowledge graphs (KGs). However, taking a more holistic view, existing PLM+KG contributions mainly consider commonsense benchmarks and ignore or shallowly analyze performances on biomedical datasets. This thesis start from a propose of a deep investigation of QA-GNN for biomedicine, comparing existing or brand-new PLMs, KGs, edge-aware GNNs, preprocessing techniques, and initialization strategies. By combining the insights emerged in DISI's research, we introduce Bio-QA-GNN that include a KG. Working with this part has led to an improvement in state-of-the-art of MCOQA model on biomedical/clinical text, largely outperforming the original one (+3.63\% accuracy on MedQA). Our findings also contribute to a better understanding of the explanation degree allowed by joint text-graph reasoning architectures and their effectiveness on different medical subjects and reasoning types. Codes, models, datasets, and demos to reproduce the results are freely available at: \url{https://github.com/disi-unibo-nlp/bio-qagnn}.

Survival and quality of life of patients with oral and oropharyngeal cancer at 1-year follow-up of tumor resection

OBJECTIVE: This study aimed to assess the survival and life quality evolution of patients subjected to surgical excision of oral and oropharyngeal squamous cell carcinoma. MATERIAL AND METHODS: Forty-seven patients treated at a Brazilian healthcare unit specialized in head and neck surgery between 2006 and 2007 were enrolled in the study. The gathering of data comprised reviewing hospital files and applying the University of Washington Quality of Life (UW-QOL) questionnaire previously and 1 year after the surgery. Comparative analysis used Poisson regression to assess factors associated with survival and a paired t-test to compare preoperative and 1-year postoperative QOL ratings. RESULTS: 1 year after surgery, 7 patients were not found (dropout of the cohort); 15 had died and 25 fulfilled the UW-QOL again. The risk of death was associated with having regional metastasis previously to surgery (relative risk=2.18; 95% confidence interval=1.09-5.17) and tumor size T3 or T4 (RR=2.30; 95%CI=1.05-5.04). Survivors presented significantly (p<0.05) poorer overall and domain-specific ratings of quality of life. Chewing presented the largest reduction: from 74.0 before surgery to 34.0 one year later. Anxiety was the only domain whose average rating increased (from 36.0 to 70.7). CONCLUSIONS: The prospective assessment of survival and quality of life may contribute to anticipate interventions aimed at reducing the incidence of functional limitations in patients with oral and oropharyngeal cancer.

Search for cytotoxic agents in multiple Laurencia complex seaweed species (Ceramiales, Rhodophyta) harvested from the Atlantic Ocean with emphasis on the Brazilian State of Espírito Santo

The development of new anti-cancer drugs of algal origin represents one of the least explored frontiers in medicinal chemistry. In this regard, the diversity of micro- and macroalgae found in Brazilian coastal waters can be viewed as a largely untapped natural resource. In this report, we describe a comparative study on the cytotoxic properties of extracts obtained from the Laurencia complex: Laurencia aldingensis, L. catarinensis, L. dendroidea, L. intricata, L. translucida, L. sp, and Palisada flagellifera. All of these species were collected in the coastal waters of the State of Espírito Santo, Brazil. Four out of the twelve samples initially investigated were found to show significant levels of toxicity towards a model tumor cell line (human uterine sarcoma, MES-SA). The highest levels of cytotoxicity were typically associated with non-polar (hexane) algal extracts, while the lowest levels of cytotoxicity were found with the corresponding polar (methanol) extracts. In this report, we also describe a biological model currently in development that will not only facilitate the search for new anti-cancer drug candidates of algal origin, but also permit the identification of compounds capable of inducing the destruction of multi-drug resistant tumors with greater efficiency than the pharmaceuticals currently in clinical use.

Plasma Kallikrein and Angiotensin I-converting enzyme N- and C-terminal domain activities are modulated by the insertion/deletion polymorphism

Angiotensin I-converting enzyme (ACE) is recognized as one of the main effector molecules involved in blood pressure regulation. In the last few years some polymorphisms of ACE such as the insertion/deletion (I/D) polymorphism have been described, but their physiologic relevance is poorly understood. In addition, few studies investigated if the specific activity of ACE domain is related to the I/D polymorphism and if it can affect other systems. The aim of this study was to establish a biochemical and functional characterization of the I/D polymorphism and correlate this with the corresponding ACE activity. For this purpose, 119 male brazilian army recruits were genotyped and their ACE plasma activities evaluated from the C- and N-terminal catalytic domains using fluorescence resonance energy transfer (FRET) peptides, specific for the C-domain (Abz-LFK(Dnp)OH), N-domain (Abz-SDK(Dnp)P-OH) and both C- and N-domains (Abz-FRK(Dnp)P-OH). Plasma kallikrein activity was measured using Z-Phe-Arg-AMC as substrate and inhibited by selective plasma kallikrein inhibitor (PKSI). Some physiological parameters previously described related to the I/D polymorphism such as handgrip strength, blood pressure, heart rate and BMI were also evaluated. The genotype distribution was II n = 27, ID n = 64 and DD n = 28. Total plasma ACE activity of both domains in II individuals was significantly lower in comparison to ID and DD. This pattern was also observed for C- and N-domain activities. Difference between ID and DD subjects was observed only with the N-domain specific substrate. Blood pressure, heart rate, handgrip strength and BMI were similar among the genotypes. This polymorphism also affected the plasma kallikrein activity and DD group presents high activity level. Thus, our data demonstrate that the I/D ACE polymorphism affects differently both ACE domains without effects on handgrip strength. Moreover, this polymorphism influences the kallikrein-kinin system of normotensive individuals. (C) 2009 Elsevier Ltd. All rights reserved.

PROPOSAL OF A PERFORMANCE MEASURING SYSTEM APPLIED TO AGRICULTURAL MECHANIZATION

The leaders` organizations of several different sectors have as characteristic to measure their own performance in a systematic way. However, this concept is still unusual in agricultural enterprises, including the mechanization sector. Mechanization has an important role on the production costs and to know its performance is a key factor for the agricultural enterprise success. This work was generated by the importance that measurement of performance has for the management and the mechanization impact on the production costs. Its aim is to propose an integrated performance measurement system to give support to agricultural management. The methodology was divided in two steps: adjustment of a conceptual model based on Balanced Score Card - BSC; application of the model in a study case at sugar cane mill. The adjustment and the application of the conceptual model allowed to obtain the performance index in a systematic way, that are associated to: costs and deadline ( traditionally used); control and improvement on the quality of operations and support process; environmental preservation; safety; health; employees satisfaction; development of information systems. The adjusted model helped the development of the performance measurement system for the mechanized management systems and the index allows an integrated view of the enterprise, related to its strategic objectives.

HFE gene mutations in patients with primary iron overload: Is there a significant improvement in molecular diagnosis yield with HFE sequencing?

Rare HFE variants have been shown to be associated with hereditary hemochromatosis (HH), an iron overload disease. The low frequency of the HFE p.C282Y mutation in HH-affected Brazilian patients may suggest that other HFE-related mutations may also be implicated in the pathogenesis of HH in this population. The main aim was to screen for new HFE mutations in Brazilian individuals with primary iron overload and to investigate their relationship with HH. Fifty Brazilian patients with primary iron overload (transferrin saturation >50% in females and 60% in males) were selected. Subsequent bidirectional sequencing for each HFE exon was performed. The effect of HFE mutations on protein structure were analyzed by molecular dynamics simulation and free binding energy calculations. p.C282Y in homozygosis or in heterozygosis with p.H63D were the most frequent genotypic combinations associated with HH in our sample population (present in 17 individuals, 34%). Thirty-six (72.0%) out of the 50 individuals presented at least one HFE mutation. The most frequent genotype associated with HH was the homozygous p.C282Y mutation (n = 11, 22.0%). One novel mutation (p.V256I) was indentified in heterozygosis with the p.H63D mutation. In silico modeling analysis of protein behavior indicated that the p.V256I mutation does not reduce the binding affinity between HFE and beta 2-microglobulin ((beta 2M) in the same way the p.C282Y mutation does compared with the native HFE protein. In conclusion, screening of HFE through direct sequencing, as compared to p.C282Y/p.H63D genotyping, was not able to increase the molecular diagnosis yield of HH. The novel p.V256I mutation could not be implicated in the molecular basis of the HH phenotype, although its role cannot be completely excluded in HH-phenotype development. Our molecular modeling analysis can help in the analysis of novel, previously undescribed, HFE mutations. (C) 2010 Elsevier Inc. All rights reserved.

The Coefficient of Variance as an index of L2 lexical processing skill

The Coefficient of Variance (mean standard deviation/mean Response time) is a measure of response time variability that corrects for differences in mean Response time (RT) (Segalowitz & Segalowitz, 1993). A positive correlation between decreasing mean RTs and CVs (rCV-RT) has been proposed as an indicator of L2 automaticity and more generally as an index of processing efficiency. The current study evaluates this claim by examining lexical decision performance by individuals from three levels of English proficiency (Intermediate ESL, Advanced ESL and L1 controls) on stimuli from four levels of item familiarity, as defined by frequency of occurrence. A three-phase model of skill development defined by changing rCV-RT.values was tested. Results showed that RTs and CVs systematically decreased as a function of increasing proficiency and frequency levels, with the rCV-RT serving as a stable indicator of individual differences in lexical decision performance. The rCV-RT and automaticity/restructuring account is discussed in light of the findings. The CV is also evaluated as a more general quantitative index of processing efficiency in the L2.

An investigation of the interrelationship between manipulative therapy-induced hypoalgesia and sympathoexcitation

Objective: To investigate a proposed model in which manipulative therapy produces a treatment-specific initial hypoalgesic and sympathoexcitatory effect by activating a descending pain inhibitory system. The a priori hypothesis tested was that manipulative therapy produces mechanical hypoalgesia and sympatho-excitation beyond that produced by placebo or control. Furthermore, these effects would be correlated, thus supporting the proposed model. Design: A randomized, double-blind, placebo-controlled, repeated-measures study of the initial effect of treatment. Setting: Clinical neurophysiology laboratory. Subjects: Twenty-four subjects (13 women and 11 men; mean age, 49 yr) with chronic lateral epicondylalgia (average duration, 6.2 months). Intervention: Cervical spine lateral glide oscillatory manipulation, placebo and control. Outcome Measures: Pressure pain threshold, thermal pain threshold, pain-free grip strength test, upper limb tension test 2b, skin conductance, pileous and glabrous skin temperature and blood flux. Results: Treatment produced hypoalgesic and sympathoexcitatory changes significantly grater than those of placebo and control (p < .03). Confirmatory factor-analysis modeling, which was performed on the pain-related measures and the indicators of sympathetic nervous system function, demonstrated a significant correlation (r = .82) between the latencies of manipulation-induced hypoalgesia and sympathoexcitation. The Lagrange Multiplier test and Wald test indicated that the two latent factors parsimoniously and appropriately represented their observed variables. Conclusions: Manual therapy produces a treatment-specific initial hypoalgesic and sympathoexcitatory effect beyond that of placebo or control. The strong correlation between hypoalgesic and sympathoexcitatory effects suggests that a central control mechanism might be activated by manipulative therapy.

Solute transport by surface runoff from low-angle slopes: theory and application

The removal of chemicals in solution by overland how from agricultural land has the potential to be a significant source of chemical loss where chemicals are applied to the soil surface, as in zero tillage and surface-mulched farming systems. Currently, we lack detailed understanding of the transfer mechanism between the soil solution and overland flow, particularly under field conditions. A model of solute transfer from soil solution to overland flow was developed. The model is based on the hypothesis that a solute is initially distributed uniformly throughout the soil pore space in a thin layer at the soil surface. A fundamental assumption of the model is that at the time runoff commences, any solute at the soil surface that could be transported into the soil with the infiltrating water will already have been convected away from the area of potential exchange. Solute remaining at the soil surface is therefore not subject to further infiltration and may be approximated as a layer of tracer on a plane impermeable surface. The model fitted experimental data very well in all but one trial. The model in its present form focuses on the exchange of solute between the soil solution and surface water after the commencement of runoff. Future model development requires the relationship between the mass transfer parameters of the model and the time to runoff: to be defined. This would enable the model to be used for extrapolation beyond the specific experimental results of this study. The close agreement between experimental results and model simulations shows that the simple transfer equation proposed in this study has promise for estimating solute loss to surface runoff. Copyright (C) 2000 John Wiley & Sons, Ltd.

Adolescents' perceptions of social status: Development and evaluation of a new indicator

Objective. Eliminating health disparities, including those that are a result of socioeconomic status (SES), is one of the overarching goals of Healthy People 2010. This article reports on the development of a new, adolescent-specific measure of subjective social status (SSS) and on initial exploratory analyses of the relationship of SSS to adolescents' physical and psychological health. Methods. A cross-sectional study of 10 843 adolescents and a subsample of 166 paired adolescent/mother dyads who participated in the Growing Up Today Study was conducted. The newly developed MacArthur Scale of Subjective Social Status (10-point scale) was used to measure SSS. Paternal education was the measure of SES. Indicators of psychological and physical health included depressive symptoms and obesity, respectively. Linear regression analyses determined the association of SSS to depressive symptoms, and logistic regression determined the association of SSS to overweight and obesity, controlling for sociodemographic factors and SES. Results. Mean society ladder ranking, a subjective measure of SES, was 7.2 ± 1.3. Mean community ladder ranking, a measure of perceived placement in the school community, was 7.6 ± 1.7. Reliability of the instrument was excellent: the intraclass correlation coefficient was 0.73 for the society ladder and 0.79 for the community ladder. Adolescents had higher society ladder rankings than their mothers (µteen = 7.2 ± 1.3 vs µmom = 6.8 ± 1.2; P = .002). Older adolescents' perceptions of familial placement in society were more closely correlated with maternal subjective perceptions of placement than those of younger adolescents (Spearman's rhoteens