Mechanism for etching of exfoliated graphene on substrates by low-energy electron irradiation from helium plasma electron sources

Article investigating the mechanism for etching of exfoliated graphene multilayers on SiO₂ by low-energy (50 eV) electron irradiation using He plasma systems for electron sources

Cloud scheduling with discrete charging units

We consider a scheduling problem for running jobs on machines rented from the cloud. Cloud service providers such as Amazon EC2 and Google Cloud offer machines to rent on demand, and charge the rental usage by a specific interval of time, say at an hourly rate. This pricing model creates an interesting optimization problem called Interval Scheduling with Discrete Charging Units (ISDCU) which assigns jobs to run on the machines with the objective of minimizing the rental cost. In this paper, we study the problem of ISDCU where each machine can process a maximum of g jobs simultaneously. We focus on interval jobs where each job must be assigned to a machine upon its arrival and run for a required processing length. We show that ISDCU is NP-hard even for the case of g = 1. We also show that no deterministic online algorithm can achieve a competitive ratio better than max{2, g} in the non-clairvoyant setting, and better than max{3/2, g} in the clairvoyant setting. Lastly, we develop and analyze several online algorithms, most of which achieve a competitive ratio of O(g).Ministry of Education (MOE)Accepted versionThis work is supported by Singapore Ministry of Education Academic Research Fund Tier 1 under Grant 2018-T1-002-063. The authors would like to thank anonymous reviewers for their valuable suggestions to improve this paper

Competitiveness of Dynamic Bin Packing for Online Cloud Server Allocation

Cloud-based systems often face the problem of dispatching a stream of jobs to run on cloud servers in an online manner. Each job has a size that defines the resource demand for running the job. Each job is assigned to run on a cloud server upon its arrival and the job departs after it completes. The departure time of a job, however, is not known at the time of its arrival. Each cloud server has a fixed resource capacity and the total resource demand of all the jobs running on a server cannot exceed its capacity at all times. The objective of job dispatching is to minimize the total cost of the servers used, where the cost of renting each cloud server is proportional to its running hours by “pay-as-you-go” billing. The above job dispatching problem can be modeled as a variant of the dynamic bin packing (DBP) problem known as MinUsageTime DBP. In this paper, we study the competitiveness bounds of MinUsageTime DBP. We establish an improved lower bound on the competitive ratio of Any Fit family of packing algorithms, and a new upper bound of μ + 3 on the competitive ratio of the commonly used First Fit packing algorithm, where μ is the max/min job duration ratio. Our result significantly reduces the gap between the upper and lower bounds for the MinUsageTime DBP problem to a constant value independent of μ, and shows that First Fit packing is near optimal for MinUsageTime DBP.NRF (Natl Research Foundation, S’pore)MOE (Min. of Education, S’pore

Interval job scheduling with machine launch cost

We study an interval job scheduling problem in distributed systems. We are given a set of interval jobs, with each job specified by a size, an arrival time and a processing length. Once a job arrives, it must be placed on a machine immediately and run for a period of its processing length without interruption. The homogeneous machines to run jobs have the same capacity limits such that at any time, the total size of the jobs running on any machine cannot exceed its capacity. Launching each machine incurs a fixed cost. After launch, a machine is charged a constant cost per time unit until it is terminated. The problem targets to minimize the total cost incurred by the machines for processing the given set of interval jobs. We focus on the algorithmic aspects of the problem in this article. For the special case where all the jobs have a unit size equal to the machine capacity, we propose an optimal offline algorithm and an optimal 2-competitive online algorithm. For the general case where jobs can have arbitrary sizes, we establish a non-trivial lower bound on the optimal solution. Based on this lower bound, we propose a 5-approximation algorithm in the offline setting. In the non-clairvoyant online setting, we design a O(μ)-competitive Modified First-Fit algorithm which is near optimal (μ is the max/min job processing length ratio). In the clairvoyant online setting, we propose an asymptotically optimal O(logμ)-competitive algorithm based on our Modified First-Fit strategy.Ministry of Education (MOE)This work was supported by the Singapore Ministry of Education Academic Research Fund Tier 1 under Grant 2019-T1002-042, by the NationalNatural Science Foundation of China under Grant 61902063, and by the Provincial Natural Science Foundation of Jiangsu, China under Grant BK20190342

Inhibition of MYC suppresses programmed cell death ligand-1 expression and enhances immunotherapy in triple-negative breast cancer

Abstract. Background:. Cancer immunotherapy has emerged as a promising strategy against triple-negative breast cancer (TNBC). One of the immunosuppressive pathways involves programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1), but many patients derived little benefit from PD-1/PD-L1 checkpoint blockades treatment. Prior research has shown that MYC, a master transcription amplifier highly expressed in TNBC cells, can regulate the tumor immune microenvironment and constrain the efficacy of immunotherapy. This study aims to investigate the regulatory relationship between MYC and PD-L1, and whether a cyclin-dependent kinase (CDK) inhibitor that inhibits MYC expression in combination with anti-PD-L1 antibodies can enhance the response to immunotherapy. Methods:. Public databases and TNBC tissue microarrays were used to study the correlation between MYC and PD-L1. The expression of MYC and PD-L1 in TNBCs was examined by quantitative real-time polymerase chain reaction and Western blotting. A patient-derived tumor xenograft (PDTX) model was used to evaluate the influence of a CDK7 inhibitor THZ1 on PD-L1 expression. Cell proliferation and migration were detected by 5-ethynyl-2′-deoxyuridine (EdU) cell proliferation and cell migration assays. Tumor xenograft models were established for in vivo verification. Results:. A high MYC expression level was associated with a poor prognosis and could alter the proportion of tumor-infiltrating immune cells (TIICs). The positive correlation between MYC and PD-L1 was confirmed by immunostaining samples from 165 TNBC patients. Suppression of MYC in TNBC caused a reduction in the levels of both PD-L1 messenger RNA and protein. In addition, antitumor immune response was enhanced in the TNBC cancer xenograft mouse model with suppression of MYC by CDK7 inhibitor THZ1. Conclusions:. The combined therapy of CDK7 inhibitor THZ1 and anti-PD-L1 antibody appeared to have a synergistic effect, which might offer new insight for enhancing immunotherapy in TNBC