Morphological and radiographic studies on the Manus region in the Arabian one-humped camel (Camelus dromedaries).

The study aims to analyse the normal anatomical and radiographical features of the Manus of the southern Aswanian-adapted Arabian one-humped camel, providing crucial data for diagnosing and treating various ailments. Our study was applied to 10 cadaver forelimbs of adult male one-humped camels (4-5 years old) for an explanation of the gross anatomy of the bones of the Manus region from under the carpal bones by using traditional techniques, including the gross anatomical, radiographic and x-ray (at the dorsopalmar and lateral planes) of the preparation of Manus bones. Our results showed that the large fused (third and fourth) metacarpal bones, in which the fusion extended along the entire length of the bone except at the distal end, diverged to form separate articulations with cross-ponding digits. As described in all ruminant species, especially the camel, there were two digits, and each digit consisted of three phalanges and two proximal sesamoid bones. Our radiographic x-ray data revealed that the complete radiopaque septum that completely divided the medullary cavity into two separate parts was clear from the dorsopalmar view, while the lateral view showed the proximal sesamoid bones that were placed over each other and located palmar to the head of the large metacarpal bone. In conclusion, our study reveals the adaptations of the Arabian one-humped camel to Egyptian conditions, aiding in the early diagnosis of lameness and digit problems and enabling veterinarians and camel owners to better address these issues, thereby improving the overall health and well-being of these animals.

In silico design of CMV promoter binding oligonucleotides and their impact on inhibition of gene expression in Chinese hamster ovary cells.

Modulation of expression levels of endogenous or recombinant genes can be of great interest for diverse applications, such as the study of genotype-phenotype relationships for a gene of interest, or fine-tuning of transcription to determine physiologically relevant effects of gene expression levels. During the last decades, several synthetic biology tools were established to control gene expression in mammalian cells such as Chinese hamster ovary (CHO) cells, one of the most important cell systems for basic research as well as the production of biopharmaceuticals. Here we describe the use of triplex forming oligos (TFOs), short RNA or ssDNA molecules that can bind to the major grove of their target duplex with great specificity, to control transgene expression in CHO cells. For proof of concept, a panel of TFOs with a size of 10-20 nts were designed with the help of the on-line tool Triplexator targeting the viral cytomegalovirus (CMV) promoter/enhancer region controlling the downstream reporter gene hCD4. The effect of TFOs was tested as ssDNA oligos pre-annealed to the promoter/enhancer region in vitro as well as upon endogenous transcription of the TFO as an RNA molecule binding to their target duplex in vivo. Results showed that not only binding of the TFO, but the exact location of triplex formation within the promoter/enhancer is paramount for transcription inhibition. After relieving a binding conflict by introducing a point mutation within the CMV promoter, longer TFOs (26-30 nts) could be designed and analysed. Selected TFOs achieved a reduction in recombinant hCD4 expression of up to 85% in CHO-K1 cells.

Efficient UAV-based mobile edge computing using differential evolution and ant colony optimization.

Internet of Things (IoT) tasks are offloaded to servers located at the edge network for improving the power consumption of IoT devices and the execution times of tasks. However, deploying edge servers could be difficult or even impossible in hostile terrain or emergency areas where the network is down. Therefore, edge servers are mounted on unmanned aerial vehicles (UAVs) to support task offloading in such scenarios. However, the challenge is that the UAV has limited energy, and IoT tasks are delay-sensitive. In this paper, a UAV-based offloading strategy is proposed where first, the IoT devices are dynamically clustered considering the limited energy of UAVs, and task delays, and second, the UAV hovers over each cluster head to process the offloaded tasks. The optimization problem of dynamically determining the optimal number of clusters, specifying the member tasks of each cluster, is modeled as a mixed-integer, nonlinear constraint optimization. A discrete differential evolution (DDE) algorithm with new mutation and crossover operators is proposed for the formulated optimization problem, and compared with the particle swarm optimization (PSO) and genetic algorithm (GA) meta-heuristics. Further, the ant colony optimization (ACO) algorithm is employed to identify the shortest path over the cluster heads for the UAV to traverse. The simulation results validate the effectiveness of the proposed offloading strategy in terms of tasks delays and UAV energy consumption.

High-performance simplification of triangular surfaces using a GPU.

Due to advances in high-performance computing technologies, computer graphics techniques-especially those related to mesh simplification-have been noticeably improved. These techniques, which have a strong impact on many applications, such as geometric modeling and visualization, have been well studied for more than two decades. Recent advances in GPUs have led to significant improvements in terms of speed and interactivity. In this paper, we present a mesh simplification algorithm that benefits from the parallel framework provided by recent GPUs. We customize the halfedge data structure for adaption with the dynamic memory restrictions of CUDA. The proposed algorithm is fully parallelized by employing a lock-free skip priority queue and a set of disjoint regions of the mesh. The proposed technique accelerates the simplification process while preserving the topological properties of the mesh. Some results and comparisons are provided to verify the efficiency of the proposed algorithm.