The advent of deep learning has completely reshaped our world. Now, our daily life is fulfilled with many well-known applications that adopt deep learning techniques, such as self-driving cars and face recognition. Furthermore, robotics developed more forms of technology which share the same principle with face recognition, such as hand pose recognition and fingerprint recognition. Image recognition technology requires a huge database and various learning algorithms, such as convolutional neural network and recurrent neural network, that requires lots of computational power, such as CPUs and GPUs. Thus, clients could not be satisfied with the computational resource of the local machine. The cloud resource platform emerged at a historic moment. Docker containers play a significant role of microservices-based applications in the next generation. However, it could not guarantee the quality of service. From clients’ perspective, they have to balance the budget and quality of experiences (e.g. response time). The budget leans on individual business owners and the required Quality of Experience (QoE) depends on usage scenarios of different applications, for instance, an autonomous vehicle requires real-time response, but, unlocking your smartphone can tolerate delays. Plenty of on-going projects developed user-oriented optimization resource allocation to improve the quality of the service. Considering the users’ specifications, including accelerating the training process and specifying the quality of experience, this thesis proposes two differentiate containers scheduling for deep learning applications: TRADL and DQoES .

Expansins (EXPs) which are the essential components of plant cell wall function as relaxation factors to directly promote turgor-driven expansion of cell wall and control plant growth and development and diverse environmental stress responses. A lot of EXPs genes have been widely identified and characterized in numerous plant species, but not in sweetpotato. In the present study, a total of 59 EXPs genes that unevenly distributed onto 14 of 15 chromosomes were identified from sweetpotato genome, and segmental and tandem duplications were exhibited to act as dominant functions in IbEXPs diversity. Phylogenetic analysis exhibited that IbEXPs members were clustered into four subfamilies according to EXPs in Arabidopsis and rice and the regularity of motif, domain and gene structures was in accordance with the subfamily classification. The collinearity analysis between IbEXPs and related homologous sequences in 9 plants provided the phylogenetic insights of EXPs gene family. Cis-element analysis futhrer revealed the potential roles of IbEXPs in sweetpotato development and stress responses. Evidence from RNA-seq and qRT-PCR analysis of eight selected IbEXPs genes displayed their various tissue specificity in different tissues, and their transcripts were varyingly induced or suppressed under multiple hormone treatments (ABA, SA, JA and ACC) and abiotic stresses (low and high temperature). These results supply worthy foundations to further comprehensively investigate the exact functions of IbEXPs genes, and multiple members may function as promising regulators to control plant development and enhance the stress resistance of transgenic plants.

Definitive surgical resection is the preferred treatment for early-stage non-small-cell lung cancer (NSCLC). Research into genetic alterations, including epidermal growth factor receptor (EGFR) mutation, in early stage NSCLC remains insufficient. Here, we investigated the prevalence of genetic alterations in early-stage NSCLC and the association between EGFR mutation and recurrence after complete resection. Between January 2019 and December 2021, 659 patients with NSCLC who underwent curative surgical resection at a single regional cancer center were recruited. We compared the clinical and pathological data between the recurrence and non-recurrence groups. Multivariate logistic regression was used to predict the risk factors for recurrence. Among the 659 enrolled cases, the most common histology was adenocarcinoma (74.5%), followed by squamous cell carcinoma (21.7%). The prevalence of EGFR mutation was 43% (194/451). Among them, L858R point mutation and exon 19 deletion was 52.3% and 42%, respectively. ALK rearrangement was found at 5.7% (26/453), and ROS1 fusion was found at 1.6% (7/441). The recurrence rate of the entire population was 19.7%. In multivariate analysis, the presence of EGFR mutation, stage II or III (vs. stage I), and pathologic subtype (presence of solid type) were associated with recurrence. Among the recurred group, 86.5% of the patients with EGFR mutation experienced distant recurrence compared to only 66.7% of wild-type (p = 0.016), with no significant difference in median disease-free survival (p = 0.983). In conclusion, the prevalence of EGFR mutation, ALK rearrangement, and ROS1 fusion was 43.0%, 5.7%, and 1.6%, respectively in patients with early-stage NSCLC who underwent curative resection. Along with stage II/III and solid pathologic subtype, EGFR mutation was an independent risk factor for recurrence. In the recurrence group, the rate of distant metastasis was higher in patients with EGFR mutation than in those with wild-type.