Towards an integrated neonatal brain and cardiac examination capability at 7 T: electromagnetic field simulations and early phantom experiments using an 8-channel dipole array

Objective

Neonatal brain and cardiac imaging would benefit from the increased signal-to-noise ratio levels at 7 T compared to lower field. Optimal performance might be achieved using purpose designed RF coil arrays. In this study, we introduce an 8-channel dipole array and investigate, using simulations, its RF performances for neonatal applications at 7 T.

Methods

The 8-channel dipole array was designed and evaluated for neonatal brain/cardiac configurations in terms of SAR efficiency (ratio between transmit-field and maximum specific-absorption-rate level) using adjusted dielectric properties for neonate. A birdcage coil operating in circularly polarized mode was simulated for comparison. Validation of the simulation model was performed on phantom for the coil array.

Results

The 8-channel dipole array demonstrated up to 46% higher SAR efficiency levels compared to the birdcage coil in neonatal configurations, as the specific-absorption-rate levels were alleviated. An averaged normalized root-mean-square-error of 6.7% was found between measured and simulated transmit field maps on phantom.

Conclusion

The 8-channel dipole array design integrated for neonatal brain and cardiac MR was successfully demonstrated, in simulation with coverage of the baby and increased SAR efficiency levels compared to the birdcage. We conclude that the 8Tx-dipole array promises safe operating procedures for MR imaging of neonatal brain and heart at 7 T.

     

Use of Pleurotus albidus mycoprotein flour to produce cookies: Evaluation of nutritional enrichment and biological activity

The demand for healthy and quality food has aroused interest in innovative ingredients, such as mycoprotein, that can enrich its chemical composition and bioactivity. The objective of this study was to prepare chocolate cookies using Pleurotus albidus mycoprotein flour to replace wheat flour. Nutritional composition, biological activity (antioxidant activity and α-glycosidase inhibition capacity) and physical properties of the cookies were evaluated. When compared to control cookie, the total replacement of wheat flour (80 g) by mycoprotein flour significantly enhanced cookies protein content (67%), total dietary fibre (336%), phenolic content (81%), antioxidant activity (159% DPPH; 73% ABTS) and capacity to inhibit α-glycosidase activity in vitro by 75%. Also, the use of P. albidus mycoprotein flour increased the hardness (112.4 N) and altered the colour parameters of the cookies, reducing the luminosity and the yellowish colour. In conclusion, use of P. albidus mycoprotein flour can aggregate nutritional and biological value in backery products.     

Improved resolution of the multiple inverse method by eliminating erroneous solutions

The multiple inverse method is a numerical technique designed to separate stresses from heterogeneous fault–slip data. The method is one of the resampling methods based on the pattern recognition. Plotting solutions determined from k-fault subset into the parameter space, we have clusters representing significant stresses for the dataset. This paper presents a technique to improve the resolution of stress for the method. The regularity/singularity test of the subsets taken from the fault–slip data is the key for this purpose. The resolution and accuracy of the method are improved by eliminating erroneous stresses or artifacts that were yielded by the method. The performances of the method are demonstrated with a variety of artificial datasets.     

Incremental Composition in Distributional Semantics

Journal of Logic, Language and Information - Despite the incremental nature of Dynamic Syntax (DS), the semantic grounding of it remains that of predicate logic, itself grounded in set theory, so...     

QM/MM investigation of the reaction rates of substrates of 2,3-dimethylmalate lyase: A catabolic protein isolated from Aspergillus niger

Aspergillus niger is an industrially important microorganism used in the production of citric acid. It is a common cause of food spoilage and represents a health issue for patients with compromised immune systems. Recent studies on Aspergillus niger have revealed details on the isocitrate lyase (ICL) superfamily and its role in catabolism, including (2R, 3S)-dimethylmalate lyase (DMML). Members of this and related lyase super families are of considerable interest as potential treatments for bacterial and fungal infections, including Tuberculosis. In our efforts to better understand this class of protein, we investigate the catalytic mechanism of DMML, studying five different substrates and two different active site metals configurations using molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. We show that the predicted barriers to reaction for the substrates show good agreement with the experimental k_cat values. This results help to confirm the validity of the proposed mechanism and open up the possibility of developing novel mechanism based inhibitors specifically for this target.     

A coherence maximisation process for solving normative inconsistencies

Norms can be used in multi-agent systems for defining patterns of behaviour in terms of permissions, prohibitions and obligations that are addressed to agents playing a specific role. Agents may play different roles during their execution and they may even play different roles simultaneously. As a consequence, agents may be affected by inconsistent norms; e.g., an agent may be simultaneously obliged and forbidden to reach a given state of affairs. Dealing with this type of inconsistency is one of the main challenges of normative reasoning. Existing approaches tackle this problem by using a static and predefined order that determines which norm should prevail in the case where two norms are inconsistent. One main drawback of these proposals is that they allow only pairwise comparison of norms; it is not clear how agents may use the predefined order to select a subset of norms to abide by from a set of norms containing multiple inconsistencies. Furthermore, in dynamic and non-deterministic environments it can be difficult or even impossible to specify an order that resolves inconsistencies satisfactorily in all potential situations. In response to these two problems, we propose a mechanism with which an agent can dynamically compute a preference order over subsets of its competing norms by considering the coherence of its cognitive and normative elements. Our approach allows flexible resolution of normative inconsistencies, tailored to the current circumstances of the agent. Moreover, our solution can be used to determine norm prevalence among a set of norms containing multiple inconsistencies.     

Structure based virtual screening-driven identification of monastrol as a potent urease inhibitor

Virtual screening uses computer based methods to discover new ligands on the basis of biological structures. Among all virtual screening methods structure based docking has received considerable attention. In an attempt to identify new ligands as urease inhibitors, structure-based virtual screening (SBVS) of an in-house database of 10,000 organic compounds was carried out. The X-ray crystallographic structure of Bacillus pasteurii (BP) in complex with acetohydroxamic acid (PDB Code 4UBP) was used as a protein structure. As a starting point, ~10,000 compounds of our in-house database were analyzed to check redundancy and the compounds found repeated were removed from the database. Finally 6993 compounds were docked into the active site of BP urease using GOLD and MOE-Dock software. A remarkable feature of this study was the identification of monastrol, a well-known KSP inhibitor already in clinical trials, as a novel urease inhibitor. The hits identified were further evaluated by molecular docking and on examination of the affinity predictions, twenty-seven analogs of monastrol were synthesized by a multicomponent Biginelli reaction followed by their in vitro screening as urease inhibitors. Finally twelve compounds were identified as new urease inhibitors. The excellent in vitro activity suggested that these compounds may serve as viable lead compounds for the treatment of urease related problems.     

Health information technologies for patients with diabetes

Patients with chronic illnesses, such as diabetes, need daily care and follow-up beyond occasional visits to healthcare providers. Research has shown that overcoming a multifaceted illness, such as diabetes, requires patients to be engaged in the monitoring and management of their own health. Health information technology (HIT) has been shown to empower chronically-ill patients to take charge of their healthcare, and alleviate their daily frustrations while they strive to lead a normal life. In this paper, we surveyed 31 patients with diabetes to identify the major frustrations they experience daily, examine the role of HIT in their current treatment, and identify gaps in their current care and education that, if addressed, could improve their quality of life. Themes identified in our survey results include a lack of interaction with healthcare providers, difficulties in scheduling appointments, a lack of timely communication with healthcare providers, and challenges in managing the complex care of diabetes. The contributions of this paper include a detailed set of recommendations on how HIT can be utilized to help chronically-ill patients live a better life despite their illnesses, with a particular emphasis on diabetes care and management.     

Robust guaranteed cost control of uncertain fuzzy systems under time-varying sampling

In practice, the system is often modeled as a continuous-time fuzzy system, while the control input is applied only at discrete instants. This system is called a sampled-data control system. In this paper, robust guaranteed cost control for uncertain sampled-data fuzzy systems is discussed. A guaranteed cost control where a quadratic cost function is bounded by a certain scalar, not only stabilizes a system but also considers a control performance. A typical sampled-data control is the zero-order input, which can be represented as a piecewise-continuous delay. Here we take a delay system approach to the sampled-data guaranteed cost control problem. The closed-loop system with a sampled-data state feedback controller becomes a system with time-varying delay. First, guaranteed cost control performance conditions for the closed-loop system are given in terms of linear matrix inequalities (LMIs). Such conditions are derived by using Leibniz–Newton formula and free weighting matrix method for fuzzy systems under the assumption that sampling time is not greater than some prescribed scalar. Then, a design method of robust guaranteed cost state feedback controller for uncertain sampled-data fuzzy systems is proposed. Examples are given to illustrate our robust sampled-data guaranteed cost control design.