Evolving Spiking Neural Networks to Mimic PID Control for Autonomous Blimps

In recent years, Artificial Neural Networks (ANN) have become a standard in robotic control. However, a significant drawback of large-scale ANNs is their increased power consumption. This becomes a critical concern when designing autonomous aerial vehicles, given the stringent constraints on power and weight. Especially in the case of blimps, known for their extended endurance, power-efficient control methods are essential. Spiking neural networks (SNN) can provide a solution, facilitating energy-efficient and asynchronous event-driven processing. In this paper, we have evolved SNNs for accurate altitude control of a non-neutrally buoyant indoor blimp, relying solely on onboard sensing and processing power. The blimp's altitude tracking performance significantly improved compared to prior research, showing reduced oscillations and a minimal steady-state error. The parameters of the SNNs were optimized via an evolutionary algorithm, using a Proportional-Derivative-Integral (PID) controller as the target signal. We developed two complementary SNN controllers while examining various hidden layer structures. The first controller responds swiftly to control errors, mitigating overshooting and oscillations, while the second minimizes steady-state errors due to non-neutral buoyancy-induced drift. Despite the blimp's drivetrain limitations, our SNN controllers ensured stable altitude control, employing only 160 spiking neurons

Evaluatie van de huidige screening van adoptieouders uitgevoerd door diensten voor maatschappelijk onderzoek van de CAW's in het kader van de geschiktheidsprocedure voor interlandelijke adoptie gevoerd voor de jeugdrechtbank

nrpages: 241status: publishe

How to Modulate Tumor Hypoxia for Preclinical In Vivo Imaging Research

Tumor hypoxia is related with tumor aggressiveness, chemo- and radiotherapy resistance, and thus a poor clinical outcome. Therefore, over the past decades, every effort has been made to develop strategies to battle the negative prognostic influence of tumor hypoxia. For appropriate patient selection and follow-up, noninvasive imaging biomarkers such as positron emission tomography (PET) radiolabeled ligands are unprecedentedly needed. Importantly, before being able to implement these new therapies and potential biomarkers into the clinical setting, preclinical in vivo validation in adequate animal models is indispensable. In this review, we provide an overview of the different attempts that have been made to create differential hypoxic in vivo cancer models with a particular focus on their applicability in PET imaging studies

Usefulness of splenic scintigraphy in differentiating splenosis and malignancy on gallium 68 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid-NaI3-octreotide

Somatostatin receptor (SSTR) imaging with gallium 68 (Ga-68) 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA)-peptide positron emission tomography/computed tomography (PET/CT) has been introduced in clinical routine for the diagnosis and staging of neuroendocrine tumors (NETs) with high SSTR expression. Although it has high sensitivity for NETs, there are some known diagnostic pitfalls one should be aware of. We present a case of suspected NET where Ga-68 DOTA-NaI3-octreotide (NOC) PET/CT showed several abdominal lesions with high SSTR expression suggesting malignancy. On magnetic resonance imaging, the differential diagnosis of the lesions also included splenosis. Subsequent splenic scintigraphy with technetium-99m phytate showed uptake in all suspicious lesions, and biopsy confirmed the diagnosis of splenosis. Splenic scintigraphy with single-photon emission computed tomography/CT can be a helpful noninvasive diagnostic tool when splenosis is suspected on Ga-68 DOTA-peptide PET/CT