A new monitoring design for uni-variate statistical quality control charts

In this research, an iterative approach is employed to analyze and classify the states of uni-variate quality control systems. To do this, a measure (called the belief that process is in-control) is first defined and then an equation is developed to update the belief recursively by taking new observations on the quality characteristic under consideration. Finally, the upper and the lower control limits on the belief are derived such that when the updated belief falls outside the control limits an out-of-control alarm is received. In order to understand the proposed methodology and to evaluate its performance, some numerical examples are provided by means of simulation. In these examples, the in and out-of-control average run lengths (ARL) of the proposed method are compared to the corresponding ARL’s of the optimal EWMA, Shewhart EWMA, GEWMA, GLR, and CUSUM[11] methods within different scenarios of the process mean shifts. The simulation results show that the proposed methodology performs better than other charts for all of the examined shift scenarios. In addition, for an autocorrelated AR(1) process, the performance of the proposed control chart compared to the other existing residual-based control charts turns out to be promising.     

Form-birefringence structure fabrication in GaAs by use of SU-8 as a dry-etching mask

A thin layer of a SU-8 submicrometer pattern produced by holographic lithography was directly used as the dry-etching mask in a chemically assisted ion-beam-etching system. With optimized etching parameters, etching selectivity of 7:1 was achieved together with a smooth vertical profile. As an application, a half-wavelength retardation plate for a 1.55-microm wavelength was produced and evaluated.     

Nanoscale Optoregulation of Neural Stem Cell Differentiation by Intracellular Alteration of Redox Balance

Regulation of stem cell (SC) fate, a decision between self‐renewal and differentiation, is of immense importance in regenerative medicine and has been proven to be a powerful stimulus regulating many cell functions influencing the SC fate. This study uses triphenylphosphonium‐functionalized gold nanoparticles (TPP‐AuNPs) to explore the interplay of intracellular electromagnetic (EM) exposure and the SC fate. Localized EM waves are generated inside neural stem cells (NSCs) to stimulate TPP‐AuNPs (AuNPs), targeting the mitochondria through inducing reactive oxygen species and differentiating these cells into neurons. Following laser irradiation of TPP‐AuNPs‐transfected NSCs, their differentiation to neurons is monitored by tracing the relevant markers both at the genetic and protein levels. The electrophysiology technique is further used to examine the functionality of neurons. The results confirm that TPP‐AuNPs subjected to electromotive forces have the potential to regulate cellular fate, although further investigations are still required to shed light on the mechanisms underlying the interaction of EM‐stimulated TPP‐AuNPs on cellular fate to design highly adjustable cell differentiation and reprogramming methods.     

ProcessAtlas: A scalable and extensible platform for business process analytics

In today's knowledge‐, service‐, and cloud‐based economy, an overwhelming amount of business‐related data are being generated at a fast rate daily from a wide range of sources. These data increasingly show all the typical properties of big data: wide physical distribution, diversity of formats, nonstandard data models, and independently managed and heterogeneous semantics. In this context, there is a need for new scalable and process‐aware services for querying, exploration, and analysis of process data in the enterprise because (1) process data analysis services should be capable of processing and querying large amount of data effectively and efficiently and, therefore, have to be able to scale well with the infrastructure's scale and (2) the querying services need to enable users to express their data analysis and querying needs using process‐aware abstractions rather than other lower‐level abstractions. In this paper, we introduce ProcessAtlas, ie, an extensible large‐scale process data querying and analysis platform for analyzing process data in the enterprise. The ProcessAtlas platform offers an extensible architecture by adopting a service‐based model so that new analytical services can be plugged into the platform. In ProcessAtlas, we present a domain‐specific model for representing process knowledge, ie, process‐level entities, abstractions, and the relationships among them modeled as graphs. We provide services for discovering, extracting, and analyzing process data. We provide efficient mapping and execution of process‐level queries into graph‐level queries by using scalable process query services to deal with the process data size growth and with the infrastructure's scale. We have implemented ProcessAtlas as a MapReduce‐based prototype and report on experiments performed on both synthetic and real‐world datasets.     

Multiple Protective Roles of Nanoliposome-Incorporated Baicalein against Alpha-Synuclein Aggregates

Nanoparticles are useful for increasing drug stability, solubility, and availability. The small molecule baicalein inhibits fibrillation, and detoxifies aggregates of α-synuclein (αSN) associated with Parkinson's disease (PD), but it suffers from instability, low solubility and consequent low availability. Here it is demonstrated that incorporation of baicalein into zwitterionic nanoliposomes (NLP-Ba) addresses these problems. NLP-Ba inhibits αSN fibril initiation, elongation, secondary nucleation, and also depolymerizes mature fibrils more effectively than free baicalein and prevents soluble αSN aggregates from seeding new fibrils. Importantly, NLP-Ba perturbs oligomers’ capacity to permeabilize the membrane. The interaction between NLP-Ba and αSN is confirmed by different biophysical techniques. This nanosystem crosses the blood-brain barrier in vitro and is effective against rotenone neurotoxicity in vivo. The effect of NLP-Ba on αSN fibrillation/cytotoxicity is attributed to a combination of free baicalein and empty NLPs. The results indicate a neuroprotective role for NLP-Ba in decreasing αSN pathogenicity in PD and highlight the use of nanoliposomes to mobilize poorly soluble hydrophobic drugs.     

Improvement of heavy oil recovery and role of nanoparticles of clay in the surfactant flooding process

Increasing demand and dwindling supply of crude oil have spurred efforts toward enhancing heavy oil recovery. Recently, applications of nanoparticles (NPs) for heavy oil recovery have been reported. In this study, the use of clay NPs is investigated for enhanced oil recovery. Surfactant solutions and newly developed nanosurfactant solutions with 1600–2000 ppm SDS were tested. The crude oil had a viscosity of 1320 mPa.sec at test conditions. In this study, the role of NPs in the adsorption of surfactant onto solid surfaces of reservoir core is studied. The core flooding experiments showed high potential of using nanoclay for enhancing heavy oil recovery, where 52% of surfactant flooded heavy oil was recovered after injecting the NPs solvent. Moreover, nanoclay has generally better performance in enhancing the oil recovery at surfactant solution, near CMC conditions. The nanoclay surfactant solutions improved oil recovery. The nanoclay, however, showed improved performance in comparison with clay.     

Characterisation of spray‐dried microparticles containing iron coated by pectin/resistant starch

Iron is one of three major minerals in human body. However, the iron deficiency is a medical problem in developed and underdeveloped countries due to its poor oral absorption or insufficient iron intake. Encapsulation could solve problems associated with oral iron consumption. Various advantages including low cost, biodegradability, biocompatibility and large‐scale production have been included in the current study. In a modified encapsulation method, iron microparticles were prepared using low methoxy pectin and resistant starch during spray drying. Covalent and hydrogen bonds were formed between iron and pectin and between polymers, respectively. Particles sized 3.5 ± 1.14 μm and showed spherical shapes. The yield of particles was 72.07%, and solubility and loading efficiency were 33.64% ± 0.88 and 34.79%, respectively. In conclusion, using iron as a cross‐linker of pectin molecules resulted in microparticles with appropriate properties of lowering organoleptic changes and a better bioavailability especially in dairy‐based products for food fortification.     

Multi-Hop WiMAX Networks: A New Opportunistic Algorithm Using AMC and PUSC Mode for Different Mobility Users

Resource allocation algorithms play the main role in provisioning high throughput in broad band wireless communications. The previous studies in WiMAX networks have considered either AMC or PUSC techniques for the resource allocation algorithms. In this way, AMC based algorithms have presented high throughput for low speed users. Conversely, PUSC based algorithms have not been affected by users’ speed, whilst the throughput is low. To date, the importance of presenting proportional fair and maintaining the network throughput for the users with different speeds has not been acknowledged yet. This paper presents a novel opportunistic algorithm which is suitable for the users with different mobility speeds. The new algorithm uses two modes of AMC and PUSC simultaneously. The simulation results reveal that in comparison to similar algorithms, the proposed algorithm presents more proportional fair throughput when there are both high and low speed users.     

A heuristic threshold policy for fault detection and diagnosis in multivariate statistical quality control environments

In this paper, a heuristic threshold policy is developed to detect and classify the states of a multivariate quality control system. In this approach, a probability measure called belief is first assigned to the quality characteristics and then the posterior belief of out-of-control characteristics is updated by taking new observations and using a Bayesian rule. If the posterior belief is more than a decision threshold, called minimum acceptable belief determined using a heuristic threshold policy, then the corresponding quality characteristic is classified out-of-control. Besides using a different approach, the main difference between the current research and previous works is that the current work develops a novel heuristic threshold policy, in which in order to save sampling cost and time or when these factors are constrained, the number of the data gathering stages is assumed limited. A numerical example along with some simulation experiments is given at the end to demonstrate the application of the proposed methodology and to evaluate its performances in different scenarios of mean shifts.