49 research outputs found
Process Safety Academy (PSA) for first line supervisors
PresentationThe intent of Process Safety Academy is to provide all operations day shift, shift Supervisors including new supervisors, a list of activities and behaviors considered proved practices that will help enhance their process safety leadership attributes and accelerate their assimilation into their jobs from the process safety perspective. These process safety specific behaviors that are not only aligned with but also complementary to the key EHSS leadership behaviors developed to help achieve EHSS excellence. Key principles that are to be embedded in the supervisors approach to process safety. Process safety, the key element in SHEMS, OIMS, RCMS is the way, SABIC runs its Manufacturing Business. As operations leaders, it is critical that all supervisors show their process safety leadership. • It is not only about the words we use, it is about the quality time the supervisors spend on process safety and the way they act with regard to process safety as a core value. The organization will mirror what management thinks of process safety, so that these supervisors will place their energy on the areas they think are important to Kemya. The management’s job is to make sure that what is important to SABIC, process safety in this case, matches what the supervisors perceive is important to SABIC management
Myelin repair in vivo is increased by targeting oligodendrocyte precursor cells with nanoparticles encapsulating leukaemia inhibitory factor (LIF)
AbstractMultiple sclerosis (MS) is a progressive demyelinating disease of the central nervous system (CNS). Many nerve axons are insulated by a myelin sheath and their demyelination not only prevents saltatory electrical signal conduction along the axons but also removes their metabolic support leading to irreversible neurodegeneration, which currently is untreatable. There is much interest in potential therapeutics that promote remyelination and here we explore use of leukaemia inhibitory factor (LIF), a cytokine known to play a key regulatory role in self-tolerant immunity and recently identified as a pro-myelination factor. In this study, we tested a nanoparticle-based strategy for targeted delivery of LIF to oligodendrocyte precursor cells (OPC) to promote their differentiation into mature oligodendrocytes able to repair myelin. Poly(lactic-co-glycolic acid)-based nanoparticles of ∼120 nm diameter were constructed with LIF as cargo (LIF-NP) with surface antibodies against NG-2 chondroitin sulfate proteoglycan, expressed on OPC. In vitro, NG2-targeted LIF-NP bound to OPCs, activated pSTAT-3 signalling and induced OPC differentiation into mature oligodendrocytes. In vivo, using a model of focal CNS demyelination, we show that NG2-targeted LIF-NP increased myelin repair, both at the level of increased number of myelinated axons, and increased thickness of myelin per axon. Potency was high: a single NP dose delivering picomolar quantities of LIF is sufficient to increase remyelination.Impact statementNanotherapy-based delivery of leukaemia inhibitory factor (LIF) directly to OPCs proved to be highly potent in promoting myelin repair in vivo: this delivery strategy introduces a novel approach to delivering drugs or biologics targeted to myelin repair in diseases such as MS
Paclitaxel and etoposide co-loaded polymeric nanoparticles for the effective combination therapy against human osteosarcoma
RRH Clustering Using Affinity Propagation Algorithm with Adaptive Thresholding and Greedy Merging in Cloud Radio Access Network
Affinity propagation (AP) clustering with low complexity and high performance is suitable for radio remote head (RRH) clustering for real-time joint transmission in the cloud radio access network. The existing AP algorithms for joint transmission have the limitation of high computational complexities owing to re-sweeping preferences (diagonal components of the similarity matrix) to determine the optimal number of clusters as system parameters such as network topology. To overcome this limitation, we propose a new approach in which preferences are fixed, where the threshold changes in response to the variations in system parameters. In AP clustering, each diagonal value of a final converged matrix is mapped to the position (x,y coordinates) of a corresponding RRH to form two-dimensional image. Furthermore, an environment-adaptive threshold value is determined by adopting Otsu’s method, which uses the gray-scale histogram of the image to make a statistical decision. Additionally, a simple greedy merging algorithm is proposed to resolve the problem of inter-cluster interference owing to the adjacent RRHs selected as exemplars (cluster centers). For a realistic performance assessment, both grid and uniform network topologies are considered, including exterior interference and various transmitting power levels of an RRH. It is demonstrated that with similar normalized execution times, the proposed algorithm provides better spectral and energy efficiencies than those of the existing algorithms