The Role of the Human Hypothalamus in Food Intake Networks: An MRI Perspective

Hypothalamus (HT), this small structure often perceived through the prism of neuroimaging as morphologically and functionally homogeneous, plays a key role in the primitive act of feeding. The current paper aims at reviewing the contribution of magnetic resonance imaging (MRI) in the study of the role of the HT in food intake regulation. It focuses on the different MRI techniques that have been used to describe structurally and functionally the Human HT. The latest advances in HT parcellation as well as perspectives in this field are presented. The value of MRI in the study of eating disorders such as anorexia nervosa (AN) and obesity are also highlighted.

Research on Characteristics of Broadband Acoustic Sensor Based on Silicon-Based Grooved Microring Resonator

In order to meet the requirements of having a small structure, a wide frequency band, and high sensitivity for acoustic signal measurement, an acoustic sensor based on a silicon-based grooved microring resonator is proposed. In this paper, the effective refractive index method and the finite element method are used to analyze the optical characteristics of a grooved microring resonator, and the size of the sensor is optimized. The theoretical analysis results show that, when the bending radius reaches 10 μm, the theoretical quality factor is about 106, the sensitivity is 3.14 mV/Pa, and the 3 dB bandwidth is 430 MHz, which is three orders of magnitude larger based on the sensitivity of the silicon-based cascaded resonator acoustic sensor. The sensor exhibits high sensitivity and can be used in hydrophones. The small size of the sensor also shows its potential application in the field of array integration.

A simple and novel control strategy for semi-active vibration suppression by a magnetorheological damper

Conventional skyhook-based ON–OFF control switches the damping force on a vibration suppression target according to the sign of the product of the target and relative velocities (which is called the condition function). Here, we propose a control strategy that uses a novel condition function for improved performance. The proposed strategy is formulated based on the theory of forced vibration with base excitation. Its effect upon semi-active vibration performance is investigated via numerical simulations and experimental tests of the vibration suppression of a small structure equipped with a magnetorheological (MR) damper. In the simulations, the proposed control strategy can offer high-performance semi-active vibration suppression, even in the presence of force delays in the damper. The experiments show that the displacement response with the proposed control is lower than that with the conventional skyhook-based control over the entire frequency range; furthermore, the desired performance can be achieved when the proposed condition function is used with velocity-proportional control. The simplicity and high performance demonstrated by the proposed control strategy make it applicable to semi-active vibration suppression of practical systems, even in the presence of unavoidable force delays in controllable dampers.

A Multi-Objective Evolutionary Approach Based on Graph-in-Graph for Neural Architecture Search of Convolutional Neural Networks

With the development of deep learning, the design of an appropriate network structure becomes fundamental. In recent years, the successful practice of Neural Architecture Search (NAS) has indicated that an automated design of the network structure can efficiently replace the design performed by human experts. Most NAS algorithms make the assumption that the overall structure of the network is linear and focus solely on accuracy to assess the performance of candidate networks. This paper introduces a novel NAS algorithm based on a multi-objective modeling of the network design problem to design accurate Convolutional Neural Networks (CNNs) with a small structure. The proposed algorithm makes use of a graph-based representation of the solutions which enables a high flexibility in the automatic design. Furthermore, the proposed algorithm includes novel ad-hoc crossover and mutation operators. We also propose a mechanism to accelerate the evaluation of the candidate solutions. Experimental results demonstrate that the proposed NAS approach can design accurate neural networks with limited size.

Morphological Analysis of Several Bamboo Species with Potential Structural Applications

Bamboo constitutes a family of plants that are very promising and interesting as renewable materials for both large and small structure construction. To be used as an alternative to traditional materials; the understanding of its morphology and mechanical behavior is of crucial importance. As the distribution of fibers and vascular bundles differs for each type of bamboo; several bamboo types have been characterized: Phyllostachys aurea (PA), Arundinaria amabilis (AA) and Dendrocalamus strictus (DS). Morphological analysis has been performed by optical (OM) and scanning electron microscopy (SEM). Differences in density; surface morphology and wall thickness have been found. In fact; PA and AA have shown a great morphological regularity; while DS presents the greatest thickness; to the point that it can be considered full culm. The plant’s own ducts constitute a very important factor for future impregnations and the optimization of mechanical properties for structure construction.

Development of the First Aliphatic 18F-Labeled Tetrazine Suitable for Pretargeted PET Imaging – Expanding the Bioorthogonal Tool Box

<p>Pretargeting imaging of nanomedicines have attracted considerable interest in nuclear medicine since it has the potential to increase imaging contrast while simultaneously reducing radiation burden to healthy tissue. Currently, the tetrazine ligation is the fastest bioorthogonal reaction available for this strategy and consequently, the state-of-art choice for <i>in vivo</i>chemistry. We have recently identified key properties for tetrazines to be applied in pretargeting. We have also developed a method to ¹⁸F-label highly reactive tetrazines using an aliphatic nucleophilic substitution strategy.<a> In this study, we combined this knowledge and developed an ¹⁸F-labeled tetrazine for pretargeted imaging. In order to develop this ligand, a small structure-property study was carried out. The most promising compound - with respect to reactivity, hydrophilicity and <i>ex vivo</i> blocking effect - was selected for labeling and subsequent PET <i>in vivo</i> imaging. Radiolabeling was achieved in satisfying radiochemical yields, molar activities as well as in high radiochemical purities. The tracer </a><a>displayed favorable pharmacokinetics and remarkable target-to-background ratios in pretargeted experiments - already one hour post injection.</a> We believe that the developed pretargeting imaging agent is a promising candidate for translation into clinical studies.</p>