Dendritic cells (DCs) are professional antigen-presenting cells (APCs) that play a critical role to activate immune response. They may be targeted for immunomodulation by microbes, including probiotics. In this study, chicken bone marrow dendrite cells (chi-BMDCs) were stimulated with lipopolysachride (LPS), Saccharomyces boulardii (Sb), Bacillus subtilis B10 (Bs), co-culture of Sb + Bs and phosphate buffer saline (PBS) as a control group (Ctr) at 3, 6, and 12 h intervals. Results revealed that treatment groups modulated the phenotype and biological functions of chi-BMDCs. Scan electron microscopy showed attachment of probiotics on the surface of chi-BMDCs. Additionally transmission electron microscopy (TEM) revealed efficiently engulfing and degradation of probiotics. Gene expression levels of MHC-II, CD40, CD80 and CD86 up-regulated in stimulated groups. Furthermore, toll-like receptors TLR1, TLR2, TLR4, and chicken specific TLR15 expressions were improved and downstream associated factors MyD88, TRAF6, TAB1, and NFκ-B mRNA levels increased in all treatment groups as compared to control. Surprisingly, NFκ-B response was noted significant higher in LPS treatment among all groups. Moreover, IL-1β, IL-17, IL-4, TGF-β, and IL-10 production levels were found higher, and lower concentration of INF-γ and IL-8 were observed in Sb, Bs, and Sb + Bs treatment groups. In contrast, LPS groups showed prominent increase in IL-12, INF-γ, and IL-8 concentration levels as compared to control group. Altogether, these results emphasize a potentially important role of Saccharomyces boulardii and Bacillus subtilis B10 in modulating immunological functions of chi-BMDCs by targeting specific toll like receptors (TLRs) and associated factors. The role of probiotics on chi-BMDCs functionality in a non-mammalian species have been presented for the first time.

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Car crashes are among the top ten leading causes of death; they could mainly be attributed to distracted drivers. An advanced driver-assistance technique (ADAT) is a procedure that can notify the driver about a dangerous scenario, reduce traffic crashes, and improve road safety. The main contribution of this work involved utilizing the driver’s attention to build an efficient ADAT. To obtain this “attention value”, the gaze tracking method is proposed. The gaze direction of the driver is critical toward understanding/discerning fatal distractions, pertaining to when it is obligatory to notify the driver about the risks on the road. A real-time gaze tracking system is proposed in this paper for the development of an ADAT that obtains and communicates the gaze information of the driver. The developed ADAT system detects various head poses of the driver and estimates eye gaze directions, which play important roles in assisting the driver and avoiding any unwanted circumstances. The first (and more significant) task in this research work involved the development of a benchmark image dataset consisting of head poses and horizontal and vertical direction gazes of the driver’s eyes. To detect the driver’s face accurately and efficiently, the You Only Look Once (YOLO-V4) face detector was used by modifying it with the Inception-v3 CNN model for robust feature learning and improved face detection. Finally, transfer learning in the InceptionResNet-v2 CNN model was performed, where the CNN was used as a classification model for head pose detection and eye gaze angle estimation; a regression layer to the InceptionResNet-v2 CNN was added instead of SoftMax and the classification output layer. The proposed model detects and estimates head pose directions and eye directions with higher accuracy. The average accuracy achieved by the head pose detection system was 91%; the model achieved a RMSE of 2.68 for vertical and 3.61 for horizontal eye gaze estimations.

Flying Ad-hoc Network (FANET) is a new class of Mobile Ad-hoc Network in which the nodes move in three-dimensional (3-D) ways in the air simultaneously. These nodes are known as Unmanned Aerial Vehicles (UAVs) that are operated live remotely or by the predefined mechanism which involves no human personnel. Due to the high mobility of nodes and dynamic topology, link stability is a research challenge in FANET. From this viewpoint, recent research has focused on link stability with the highest threshold value by maximizing Packet Delivery Ratio and minimizing End-to-End Delay. In this paper, a hybrid scheme named Delay and Link Stability Aware (DLSA) routing scheme has been proposed with the contrast of Distributed Priority Tree-based Routing and Link Stability Estimationbased Routing FANET's existing routing schemes. Unlike existing schemes, the proposed scheme possesses the features of collaborative data forwarding and link stability. The simulation results have shown the improved performance of the proposed DLSA routing protocol in contrast to the selected existing ones DPTR and LEPR in terms of E2ED, PDR, Network Lifetime, and Transmission Loss. The Average E2ED in milliseconds of DLSA was measured 0.457 while DPTR was 1.492 and LEPR was 1.006. Similarly, the Average PDR in %age of DLSA measured 3.106 while DPTR was 2.303 and LEPR was 0.682. The average Network Lifetime of DLSA measured 62.141 while DPTR was 23.026 and LEPR was 27.298. At finally, the Average Transmission Loss in dBm of DLSA measured 0.975 while DPTR was 1.053 and LEPR was 1.227.