IOT-5G USER TRACKING IN A 5G NETWORK USING 60 GHZ MM-WAVES BASED ON AN ABF-ED ALGORITHMS FOR A CLUTTERED INDOOR ENVIRONMENT

This paper presents a user tracking algorithm in an IoT-5G Network (or IoT-5GN). Hereby, we aim at studying and evaluating the sensing performances of the IoT-5G Access Point (or IoT-5G AP) primary signal by the IoT-5G user in a cluttered indoor environment using an energy detector (or ED) algorithm and an Alpha-&-Beta Filter (ABF or α-β-F) estimator. The 5G primary signal (or 5G-PS) frequency that we would like to detect is: 60 GHz. As a result, the 5G-PS sensing via the proposed ABF-ED algorithm, enabled us to track the IoT-5G user inside of the IoT-5G AP coverage area. The performances of the proposed ABF-ED algorithm in this paper work is evaluated by the probability of total detection error (or PTDE) measure. Through different scenarios simulations, the performances and robustness of the proffered algorithm are demonstrated.

Endothelial Cell Morphogenesis and Capillary-like Network Induced by Soluble and Bound VEGF in a Definite Biogel Composed of Collagen and Fibronectin

In vitro culture of endothelial cells to form capillary-like networks is essential in tissue engineering. Vascular endothelial growth factor (VEGF) is one of the primary signal proteins stimulating blood vessel formation. This growth factor can be soluble in the medium or protein-bound to the substrate. However, less attention has been paid to distinguishing the specific stimulations by soluble and bound VEGF. We conducted a series of experiments to explore the respective effects of these two VEGF forms. An in-house synthesized biogel comprising a definite concentration of collagen and fibronectin was designed to cultivate human umbilical vein endothelial cells to form the capillary-like network. Collagen served as the primary substrate for cell attachment. Fibronectin provided the surface to bind soluble VEGF in the culture medium to create the bound VEGF. The experiment of adding VEGF-blocking-peptide was conducted to prevent the formation of VEGF bound to the fibronectin domains, to distinguish the respective effects of the soluble and bound VEGF. With the in-house biogel of definite components, we were able to clarify the different roles of soluble and bound VEGF. The results indicated that the soluble VEGF promptly induced the cells to change from round to elongated shape, which contributed to forming network cords. Simultaneously, the bound VEGF provided long-term stimulation, causing the cells to migrate and differentiate into the final capillary-like network.

Primary Signal Phase Suppression Technique Based On Mutual Information Improved Variational Mode Decomposition

Specific emitter identification (SEI) identifies targets mainly by unintentional modulation of the signal. However, due to the high energy of the primary signal, once the primary signal changes, the recognition becomes less effective or even impossible using a feature database that is not updated. In this paper, we propose to use a mutual information improved variable mode decomposition (VMD) algorithm to suppress the primary signal phase of the transmitter. Furthermore, we simulate the feature extraction of the unintentional phase modulation of the transmitter signal and use support vector machine (SVM) for individual identification. The simulation results show that the algorithm improves the recognition rate by about 6% (0 dB) compared to the retained primary signal. The results demonstrate that our proposed phase suppression technique improves the adaptability and accuracy of individual identification of transmitters.

Transcriptional Profiles of Diploid Mutant Apis mellifera Embryos after Knockout of csd by CRISPR/Cas9

In honey bees, complementary sex determiner (csd) is the primary signal of sex determination. Its allelic composition is heterozygous in females, and hemizygous or homozygous in males. To explore the transcriptome differences after sex differentiation between males and females, with genetic differences excluded, csd in fertilized embryos was knocked out by CRISPR/Cas9. The diploid mutant males at 24 h, 48 h, 72 h, and 96 h after egg laying (AEL) and the mock-treated females derived from the same fertilized queen were investigated through RNA-seq. Mutations were detected in the target sequence in diploid mutants. The diploid mutant drones had typical male morphological characteristics and gonads. Transcriptome analysis showed that several female-biased genes, such as worker-enriched antennal (Wat), vitellogenin (Vg), and some venom-related genes, were down-regulated in the diploid mutant males. In contrast, some male-biased genes, such as takeout and apolipophorin-III-like protein (A4), had higher expressions in the diploid mutant males. Weighted gene co-expression network analysis (WGCNA) indicated that there might be interactions between csd and fruitless (fru), feminizer (fem) and hexamerin 70c (hex70c), transformer-2 (tra2) and troponin T (TpnT). The information provided by this study will benefit further research on the sex dimorphism and development of honey bees and other insects in Hymenoptera.

A simple parametric representation of the Hodgkin-Huxley model

The Hodgkin-Huxley model, decades after its first presentation, is still a reference model in neuroscience as it has successfully reproduced the electrophysiological activity of many organisms. The primary signal in the model represents the membrane potential of a neuron. A simple representation of this signal is presented in this paper. The new proposal is an adapted Frequency Modulated Möbius multicomponent model defined as a signal plus error model in which the signal is decomposed as a sum of waves. The main strengths of the method are the simple parametric formulation, the interpretability and flexibility of the parameters that describe and discriminate the waveforms, the estimators’ identifiability and accuracy, and the robustness against noise. The approach is validated with a broad simulation experiment of Hodgkin-Huxley signals and real data from squid giant axons. Interesting differences between simulated and real data emerge from the comparison of the parameter configurations. Furthermore, the potential of the FMM parameters to predict Hodgkin-Huxley model parameters is shown using different Machine Learning methods. Finally, promising contributions of the approach in Spike Sorting and cell-type classification are detailed.

A Compact Muon Tracker for Dynamic Tomography of Density Based on a Thin Time Projection Chamber with Micromegas Readout

Tomography based on cosmic muon absorption is a rising technique because of its versatility and its consolidation as a geophysics tool over the past decade. It allows us to address major societal issues such as long-term stability of natural and man-made large infrastructures or sustainable underwater management. Traditionally, muon trackers consist of hodoscopes or multilayer detectors. For applications with challenging available volumes or the wide field of view required, a thin time projection chamber (TPC) associated with a Micromegas readout plane can provide a good tradeoff between compactness and performance. This paper details the design of such a TPC aiming at maximizing primary signal and minimizing track reconstruction artifacts. The results of the measurements performed during a case study addressing the aforementioned applications are discussed. The current works lines and perspectives of the project are also presented.

Distinct Processing of Sensory Prediction Error and Task Error during Motor Learning

While sensory-prediction error (SPE), the difference between predicted and actual sensory feedback, is recognized as the primary signal that drives implicit motor recalibration, recent studies have shown that task error (TE), the difference between sensory feedback and the movement goal, also plays a modulatory role. To systematically examine how SPE and TE collectively shape implicit recalibration, we performed a series of visuomotor learning experiments, introducing perturbations that varied the size of TE using a popular target displacement method and the size of SPE using a clamped visual feedback method. In Experiments 1 & 2, we observed robust sign-dependent changes in hand angle in response to perturbations with both SPE and TE but failed to observe changes in hand angle in response to TE-only perturbations. Yet in Experiments 3 & 4, the magnitude of TE modulated implicit recalibration in the presence of a fixed SPE. Taken together, these results underscore that implicit recalibration is driven by both SPE and TE (Kim, Parvin, & Ivry, 2019), while specifying unappreciated interactions between these two error-based processes. First, TE only impacts implicit calibration when SPE is present. Second, transient changes occurring when the target is displaced to manipulate TE has an attenuating effect on implicit recalibration, perhaps due to attention being directed away from the sensory feedback.

Mechanism of insulin resistance in obesity: a role of ATP

Obesity increases the risk of type 2 diabetes through the induction of insulin resistance. The mechanism of insulin resistance has been extensively investigated for more than 60 years, but the essential pathogenic signal remains missing. Existing hypotheses include inflammation, mitochondrial dysfunction, hyperinsulinemia, hyperglucagonemia, glucotoxicity, and lipotoxicity. Drug discoveries based on these hypotheses are unsuccessful in the development of new medicines. In this review, multidisciplinary literature is integrated to evaluate ATP as a primary signal for insulin resistance. The ATP production is elevated in insulin-sensitive cells under obese conditions independent of energy demand, which we have named “mitochondrial overheating.” Overheating occurs because of substrate oversupply to mitochondria, leading to extra ATP production. The ATP overproduction contributes to the systemic insulin resistance through several mechanisms, such as inhibition of AMPK, induction of mTOR, hyperinsulinemia, hyperglucagonemia, and mitochondrial dysfunction. Insulin resistance represents a feedback regulation of energy oversupply in cells to control mitochondrial overloading by substrates. Insulin resistance cuts down the substrate uptake to attenuate mitochondrial overloading. The downregulation of the mitochondrial overloading by medicines, bypass surgeries, calorie restriction, and physical exercise leads to insulin sensitization in patients. Therefore, ATP may represent the primary signal of insulin resistance in the cellular protective response to the substrate oversupply. The prevention of ATP overproduction represents a key strategy for insulin sensitization.

A Compact Muon Tracker for Dynamic Tomography of Density Based on a Thin Time Projection Chamber with Micromegas Readout

Tomography based on cosmic muon absorption is a rising technique because of its versatility and its consolidation as geophysics tool over the past decade. It allows to address major societal issues such as long-term stability of natural and man-made large infrastructures or sustainable underwater management. Traditionally, muon trackers consist of hodoscopes or multilayer detectors. For applications with challenging available volumes or wide field of view required, a thin time projection chamber (TPC) associated with a Micromegas readout plane can provide a good tradeoff between compactness and performance. This paper details the design of such a TPC aiming at maximizing primary signal and minimizing track reconstruction artifacts. The results of the measurements performed during a case study addressing the aforementioned applications are discussed. The current works lines and perspectives of the project are also presented.