A Fast Frequency Sweep – Green’s Function Based Analysis of Substrate Integrated Waveguide

In this paper, a fast frequency sweep technique is applied to the analysis of Substrate Integrated Waveguides performed with a Green’s function technique. The well-known Asymptotic Waveform Evaluation technique is used to extract the Padè approximation of the frequency response of Substrate Integrated Waveguides devices. The analysis is extended to a large frequency range by adopting the Complex Frequency Hopping algorithm. It is shown that, with this technique, CPU time can be reduced of almost one order of magnitude with respect to a point by point computation

Neural correlates of hyperalgesia in the monosodium iodoacetate model of osteoarthritis pain

Background: The mechanisms driving osteoarthritic pain remain poorly understood, but there is increasing evidence for a role of the central nervous system in the chronification of pain.We used functional magnetic resonance imaging to investigate the influence of a model of unilateral knee osteoarthritis on nociceptive processing. Results: Four to five weeks post intra-articular injection of monosodium iodoacetate (MIA, 1 mg) into the left knee, Sprague Dawley rats were anesthetized for functional magnetic resonance imaging studies to characterize the neural response to a noxious stimulus (intra-articular capsaicin injection). In a two-arm cross-over design, 5 mM/50 ml capsaicin was injected into either the left knee (n¼8, CAPS-MIA) or right control knee (n¼8, CAPS-CON), preceded by contralateral vehicle (SAL) injection. To assess neural correlates of mechanical hyperalgesia, hindpaws were stimulated with von Frey hairs (8 g: MIA; 15 g: control knee, based on behavioral withdrawal responses). The CAPS-MIA group exhibited significant activation of the periaqueductal gray, unilateral thalamus and bilateral mensencephalon, superior-colliculus, and hippocampus, with no significant activation in the other groups/conditions. Capsaicin injection increased functional connectivity in the mid-brain network and mediodorsal thalamic nucleus, hippocampus, and globus pallidus, which was significantly stronger in CAPS-MIA compared to CAPS-CON groups. Mechanical stimulation of the hyperalgesic (ipsilateral to MIA knee) and normalgesic (contralateral) hindpaws evoked qualitatively different brain activation with more widespread brainstem and anterior cingulate (ACC) activation when stimulating the hyperalgesic paw, and clearer frontal sensory activation from the normalgesic paw. Conclusions: We provide evidence for modulation of nociceptive processing in a chronic knee osteoarthritis pain model with stronger brain activation and alteration of brain networks induced by the pro-nociceptive stimulus. We also report a shift to a medial pain activation pattern following stimulation of the hyperalgesic hindpaw. Taken together, our data support altered neural pain processing as a result of peripheral and central pain sensitization in this model

Preclinical PET and MR Evaluation of 89Zr- and 68Ga-Labeled Nanodiamonds in Mice over Different Time Scales

Nanodiamonds (NDs) have high potential as a drug carrier and in combination with nitrogen vacancies (NV centers) for highly sensitive MR-imaging after hyperpolarization. However, little remains known about their physiological properties in vivo. PET imaging allows further evaluation due to its quantitative properties and high sensitivity. Thus, we aimed to create a preclinical platform for PET and MR evaluation of surface-modified NDs by radiolabeling with both short- and long-lived radiotracers. Serum albumin coated NDs, functionalized with PEG groups and the chelator deferoxamine, were labeled either with zirconium-89 or gallium-68. Their biodistribution was assessed in two different mouse strains. PET scans were performed at various time points up to 7 d after i.v. injection. Anatomical correlation was provided by additional MRI in a subset of animals. PET results were validated by ex vivo quantification of the excised organs using a gamma counter. Radiolabeled NDs accumulated rapidly in the liver and spleen with a slight increase over time, while rapid washout from the blood pool was observed. Significant differences between the investigated radionuclides were only observed for the spleen (1 h). In summary, we successfully created a preclinical PET and MR imaging platform for the evaluation of the biodistribution of NDs over different time scales

A hybrid type-2 fuzzy logic system and extreme learning machine for low-cost INS/GPS in high-speed vehicular navigation system

Due to the combined navigation system consisting of both Inertial Navigation System (INS) and Global Positioning System (GPS) in a complementary mode which assure a reliable, accurate, and continuous navigation system, we use a GPS/INS navigation system in our research. Because of the conditions of navigation system such as low-cost MEMS-based inertial sensors with considerable uncertainty in INS sensors, a highly noisy real data, and a long term outage of GPS signals during our flight tests, we enhance the positioning speed and accuracy by an Extreme Learning Machine (ELM) with the features of excellent generalization performance and fast learning speed. However, the generalization capability of ELM usually destabilizes with uncertainty existing in the dataset. In order to fix this limitation, first, a Type-2 Fuzzy Logic System (T2-FLS) handles the uncertainties in GPS/INS data, and then the final output ends up to the ELM to train and predict INS positioning error. We verify the efficiency of the suggested method in the estimation of speed and accuracy in INS sensors error during GPS satellites outage, particularly in real-time applications with a high-speed vehicle. Then, to evaluate the overall performance of the proposed method, the achieved results are discussed and compared to other methods like Extended Kalman Filter (EKF), wavelet-ELM, and Adaptive Neuro-Fuzzy Inference System (ANFIS). The results present considerable achievement and open the door to the application of T2-FLS and ELM in GPS/INS integration even in severe conditions

A Hybrid Multi-Criteria Decision Model (HMCDM) based on AHP and TOPSIS analysis to evaluate Maintenance Strategy

The aim of the present paper concerns a Hybrid Multi-Criteria Decision Model (HMCDM) to evaluate Maintenance Strategy. In order to improve production performance, in particular system availability and to reduce cost organization, in particular maintenance cost an integrated MCDM approach is proposed. The aim of the proposed method is to suggest the best maintenance solution for industrial systems. The new hybrid model is able to overcame the shortcomings of literature methods, matching Analytic Hierarchy Process (AHP) with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for the evaluation of maintenance policy. The proposed model has been applied in a real case study in a water bottling company. Different maintenance alternatives were considered and different criteria and sub-criteria were evaluated using Reliability, Availability, Maintainability, Safety (RAMS) and production parameters. The outputs suggested the best maintenance solution for all machines in the analyzed company. The results highlight a Maintenance Cost reduction and a System Availability increase of analyzed water bottling company

Metabolomics reveals biomarkers of opioid use disorder

Opioid use disorder (OUD) is diagnosed using the qualitative criteria defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Diagnostic biomarkers for OUD do not currently exist. Our study focused on developing objective biological markers to differentiate chronic opiate users with OUD from chronic opiate users without OUD. Using biospecimens from the Golestan Cohort Study, we compared the metabolomics profiles of high opium users who were diagnosed as OUD positive with high opium users who were diagnosed as OUD negative. High opium use was defined as maximum weekly opium usage greater than or equal to the median usage (2.4 g per week), and OUD was defined as having 2 or more DSM-5 criteria in any 12-month period. Among the 218 high opium users in this study, 80 were diagnosed as OUD negative, while 138 were diagnosed as OUD positive. Seven hundred and twelve peaks differentiated high opium users diagnosed as OUD positive from high opium users diagnosed as OUD negative. Stepwise logistic regression modeling of subject characteristics data together with the 712 differentiating peaks revealed a signature that is 95 predictive of an OUD positive diagnosis, a significant (p < 0.0001) improvement over a 63 accurate prediction based on subject characteristic data for these samples. These results suggest that a metabolic profile can be used to predict an OUD positive diagnosis. © 2021, The Author(s)