A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios

CT derived hounsfield unit: An easy way to determine osteoporosis and radiation related fracture risk in irradiated patients

Background: We aimed to evaluate osteoporosis, bone mineral density, and fracture risk in irradiated patients by computerized tomography derived Hounsfield Units (HUs) calculated from radiation treatment planning system. Methods: Fifty-seven patients operated for gastric adenocarcinoma who received adjuvant abdominal radiotherapy were included in the study group. Thirty-four patients who were not irradiated after surgery comprised the control group. HUs of T12, L1, L2 vertebral bodies were measured from the computerized tomographies imported to the treatment planning system for all the patients. While the measurements were obtained just after surgery and 1 year later after surgery in the control group, the same measurements were obtained just before irradiation and 1 year after radiotherapy in the study group. Percent change in HU values (1%HU) was determined for each group. Vertebral compression fractures, which are the consequence of radiation induced osteoporosis and bone toxicity were assessed during follow-up. Results: There was no statistical significant difference in HU values measured for all the vertebrae between the study and the control group at the onset of the study. While HU values decreased significantly in the study group, there was no significant reduction in HU values in the control group after 1 year. significant correlation was found between 1%HU and the radiation dose received by each vertebra. Insufficiency fractures (IFs) were observed only in the irradiated patients (4 out of 57 patients) with the cumulative incidence of 7%. Conclusions: HU values are very valuable in determining bone mineral density and fracture risk. Radiation treatment planning system can be utilized to determine HU values. IFs are common after abdominal radiotherapy in patients with low vertebral HU values detected during radiation treatment planning. Radiation dose to the vertebral bones with low HU values should be limited below 20 Gy to prevent late radiation related bone toxicit

Neuromorphic computing with multi-memristive synapses

Neuromorphic computing has emerged as a promising avenue towards building the next generation of intelligent computing systems. It has been proposed that memristive devices, which exhibit history-dependent conductivity modulation, could efficiently represent the synaptic weights in artificial neural networks. However, precise modulation of the device conductance over a wide dynamic range, necessary to maintain high network accuracy, is proving to be challenging. To address this, we present a multi-memristive synaptic architecture with an efficient global counter-based arbitration scheme. We focus on phase change memory devices, develop a comprehensive model and demonstrate via simulations the effectiveness of the concept for both spiking and non-spiking neural networks. Moreover, we present experimental results involving over a million phase change memory devices for unsupervised learning of temporal correlations using a spiking neural network. The work presents a significant step towards the realization of large-scale and energy-efficient neuromorphic computing systems.</p

Accurate deep neural network inference using computational phase-change memory

In-memory computing using resistive memory devices is a promising non-von Neumann approach for making energy-efficient deep learning inference hardware. However, due to device variability and noise, the network needs to be trained in a specific way so that transferring the digitally trained weights to the analog resistive memory devices will not result in significant loss of accuracy. Here, we introduce a methodology to train ResNet-type convolutional neural networks that results in no appreciable accuracy loss when transferring weights to phase-change memory (PCM) devices. We also propose a compensation technique that exploits the batch normalization parameters to improve the accuracy retention over time. We achieve a classification accuracy of 93.7% on CIFAR-10 and a top-1 accuracy of 71.6% on ImageNet benchmarks after mapping the trained weights to PCM. Our hardware results on CIFAR-10 with ResNet-32 demonstrate an accuracy above 93.5% retained over a one-day period, where each of the 361,722 synaptic weights is programmed on just two PCM devices organized in a differential configuration.</p

Mechanisms of amyloid-β34 generation indicate a pivotal role for BACE1 in amyloid homeostasis

The beta‑site amyloid precursor protein (APP) cleaving enzyme (BACE1) was discovered due to its “amyloidogenic” activity which contributes to the production of amyloid-beta (Aβ) peptides. However, BACE1 also possesses an “amyloidolytic” activity, whereby it degrades longer Aβ peptides into a non‑toxic Aβ34 intermediate. Here, we examine conditions that shift the equilibrium between BACE1 amyloidogenic and amyloidolytic activities by altering BACE1/APP ratios. In Alzheimer disease brain tissue, we found an association between elevated levels of BACE1 and Aβ34. In mice, the deletion of one BACE1 gene copy reduced BACE1 amyloidolytic activity by ~ 50%. In cells, a stepwise increase of BACE1 but not APP expression promoted amyloidolytic cleavage resulting in dose-dependently increased Aβ34 levels. At the cellular level, a mislocalization of surplus BACE1 caused a reduction in Aβ34 levels. To align the role of γ-secretase in this pathway, we silenced Presenilin (PS) expression and identified PS2-γ-secretase as the main γ-secretase that generates Aβ40 and Aβ42 peptides serving as substrates for BACE1’s amyloidolytic cleavage to generate Aβ34

Multiple enzymatic approaches to hydrolysis of fungal beta-glucans by the soil bacterium Chitinophaga pinensis

The genome of the soil Bacteroidota Chitinophaga pinensis encodes a large number of glycoside hydrolases (GHs) with noteworthy features and potentially novel functions. Several are predicted to be active on polysaccharide components of fungal and oomycete cell walls, such as chitin, beta-1,3-glucan and beta-1,6-glucan. While several fungal beta-1,6-glucanase enzymes are known, relatively few bacterial examples have been characterised to date. We have previously demonstrated that C. pinensis shows strong growth using beta-1,6-glucan as the sole carbon source, with the efficient release of oligosaccharides from the polymer. We here characterise the capacity of the C. pinensis secretome to hydrolyse the beta-1,6-glucan pustulan and describe three distinct enzymes encoded by its genome, all of which show different levels of beta-1,6-glucanase activity and which are classified into different GH families. Our data show that C. pinensis has multiple tools to deconstruct pustulan, allowing the species' broad utility of this substrate, with potential implications for bacterial biocontrol of pathogens via cell wall disruption. Oligosaccharides derived from fungal beta-1,6-glucans are valuable in biomedical research and drug synthesis, and these enzymes could be useful tools for releasing such molecules from microbial biomass, an underexploited source of complex carbohydrates

Mechanisms of amyloid-β34 generation indicate a pivotal role for BACE1 in amyloid homeostasis

The beta‑site amyloid precursor protein (APP) cleaving enzyme (BACE1) was discovered due to its "amyloidogenic" activity which contributes to the production of amyloid-beta (Aβ) peptides. However, BACE1 also possesses an "amyloidolytic" activity, whereby it degrades longer Aβ peptides into a non‑toxic Aβ34 intermediate. Here, we examine conditions that shift the equilibrium between BACE1 amyloidogenic and amyloidolytic activities by altering BACE1/APP ratios. In Alzheimer disease brain tissue, we found an association between elevated levels of BACE1 and Aβ34. In mice, the deletion of one BACE1 gene copy reduced BACE1 amyloidolytic activity by ~ 50%. In cells, a stepwise increase of BACE1 but not APP expression promoted amyloidolytic cleavage resulting in dose-dependently increased Aβ34 levels. At the cellular level, a mislocalization of surplus BACE1 caused a reduction in Aβ34 levels. To align the role of γ-secretase in this pathway, we silenced Presenilin (PS) expression and identified PS2-γ-secretase as the main γ-secretase that generates Aβ40 and Aβ42 peptides serving as substrates for BACE1's amyloidolytic cleavage to generate Aβ34

Prediction Of Problematic Internet Use By Attachment In University Students

Aim of this research is to examine the predictive power of attachment style on problematic internet use among university students. Participants of study consist of 481 university students (230 girls). Results indicate that there is a negative correlation between secure attachment style and social benefit/social comfort and there is a positive correlation between preoccupied attachment style and social benefit/social comfort which is a sub-dimension of problematic internet use. Considering predictive power of attachment on problematic internet use, results show that preoccupied, secure and dismissing attachment styles are significant predictors of social benefit/social comfort. Results and comments for the future studies on problematic internet use and attachment were discussed in general

During early stages of cancer, neutrophils initiate anti-tumor immune responses in tumor-draining lymph nodes

Tumor-draining lymph nodes (LNs) play a crucial role during cancer spread and in initiation of anti-cancer adaptive immunity. Neutrophils form a substantial population of cells in LNs with poorly understood functions. Here, we demonstrate that, during head and neck cancer (HNC) progression, tumor-associated neutrophils transmigrate to LNs and shape anti-tumor responses in a stage-dependent manner. In metastasis-free stages (N0), neutrophils develop an antigen-presenting phenotype (HLA-DR+CD80+CD86+ICAM1+PD-L1-) and stimulate T cells (CD27+Ki67highPD-1-). LN metastases release GM-CSF and via STAT3 trigger development of PD-L1+ immunosuppressive neutrophils, which repress T cell responses. The accumulation of neutrophils in T cell-rich zones of LNs in N0 constitutes a positive predictor for 5-year survival, while increased numbers of neutrophils in LNs of N1-3 stages predict poor prognosis in HNC. These results suggest a dual role of neutrophils as essential regulators of anti-cancer immunity in LNs and argue for approaches fostering immunostimulatory activity of these cells during cancer therapy