Monitoring of mental workload levels during an everyday life office-work scenario

Personal and ubiquitous healthcare applications offer new opportunities to prevent long-term health damage due to increased mental workload by continuously monitoring physiological signs related to prolonged high workload and providing just-in-time feedback. In order to achieve a quantification of mental load, different load levels that occur during a workday have to be discriminated. In this work, we present how mental workload levels in everyday life scenarios can be discriminated with data from a mobile ECG logger by incorporating individual calibration measures. We present an experiment design to induce three different levels of mental workload in calibration sessions and to monitor mental workload levels in everyday life scenarios of seven healthy male subjects. Besides the recording of ECG data, we collect subjective ratings of the perceived workload with the NASA Task Load Index (TLX), whereas objective measures are assessed by collecting salivary cortisol. According to the subjective ratings, we show that all participants perceived the induced load levels as intended from the experiment design. The heart rate variability (HRV) features under investigation can be classified into two distinct groups. Features in the first group, representing markers associated with parasympathetic nervous system activity, show a decrease in their values with increased workload. Features in the second group, representing markers associated with sympathetic nervous system activity or predominance, show an increase in their values with increased workload. We employ multiple regression analysis to model the relationship between relevant HRV features and the subjective ratings of NASA-TLX in order to predict the mental workload levels during office-work. The resulting predictions were correct for six out of the seven subjects. In addition, we compare the performance of three classification methods to identify the mental workload level during office-work. The best results were obtained with linear discriminant analysis (LDA) that yielded a correct classification for six out of the seven subjects. The k-nearest neighbor algorithm (k-NN) and the support vector machine (SVM) resulted in a correct classification of the mental workload level during office-work for five out of the seven subjects.     

2,6-Bis-benzimidazolylpyridines as new catalyst in copper-based ATRP

The ligands, 2,6-bis(NH-benzimidazol-2-yl)pyridine (L1) and 2,6-bis(N-methyl-benzimidazol-2-yl)pyridine (L2), were synthesized by a one-step reaction of 2,6-pyridinedicarboxylic acid with a diamine (o-phenylenediamine or N-methyl-1,2-phenylenediamine), respectively, in syrupy phosphoric acid at ca. 200 °C. Their efficiency as a catalyst in Cu-based atom transfer radical polymerizations (ATRP) of methylmethacrylate (MMA) was investigated. The linear first-order kinetic plots were observed; indicating that the number of active species is constant during the polymerization and termination reactions are limited. The apparent rate constant values of ATRP of MMA with CuCl/L1 catalyst system at 90 °C in acetonitrile were found to be between 3.83 × 10^?5 and 1.33 × 10^?4 s^?1, while they were between 1.86 × 10^?4 and 4.40 × 10^?4 s^?1 in the case of CuCl/L2 catalyst, indicating the presence of lower radical concentration throughout the polymerization of MMA using CuCl/L1 catalyst system. In both the cases, low apparent rate constant values are obtained. This indicates that ATRP proceeded at reasonable rates and a good control over ATRP in general. Apparent rate constant vs [ligand]/[catalyst] ratio plots showed a maximum at the [ligand]/[catalyst] ratio of two. M _n,GPC values increased slightly linearly with conversion and molecular weight values were closer to M _n,th in the case of ATRP of MMA using CuCl/L2 catalyst complex. Cyclic voltammetry measurements confirmed that CuCl/L1 and CuCl/L2 complexes in acetonitrile give reversible redox couples and copper(I) centers in CuCl/L1 and CuCl/L2 catalyst complexes that are readily oxidized and they potentially suit to facile ATRP.     

Semi-automated model matching using version difference

Interoperability of software is a critical requirement in the architecture, engineering, and construction (AEC) industry, where a number of data exchange standards have been created to enable data exchange among different software packages. To be able to comply with existing data exchange standards, the software developers need to match their internal data schemas to the schema defined in a standard and vice versa. The process of matching two large scale data models is time consuming and cumbersome when performed manually, and becomes even more challenging when a source and/or a target model is being updated frequently to meet the ever expanding real world requirements. While several prior studies discussed the need for approaches toward automated or semi-automated schema matching, an approach that builds on existing matches between two models has rarely been studied. In this paper, we present a semi-automated approach for model matching. This approach leverages a given set of existing matching between two models and upgrades those matching when a new version of a target model is released. The paper describes in detail a list of upgrade patterns generated and validated through a prototype by matching a domain-specific data model to several recent releases of the industry foundation classes.     

Preparation and characterization of zeolite beta–polyurethane composite membranes

Incorporation of zeolite into polyurethane (PU) membranes was investigated by using as‐synthesized and calcined zeolite beta particles at two different loading contents (0.1 and 1 wt %). The chemical interaction between the zeolite beta crystals and PU was observed by ATR‐FTIR spectroscopy. The SEM results suggested that the calcined zeolite beta crystals were more homogeneously dispersed in the composite membranes than the as‐synthesized zeolite beta crystals. DMA results demonstrated that all composite membranes had higher storage modulus in the rubbery state and higher stability towards thermal and mechanical degradation with respect to the control groups. Tensile testing results also showed increased tensile strength and elongation at break for all composite membranes. This study suggests that incorporating zeolite beta in its as‐synthesized or calcined forms and at different amounts can be applied as an alternative method for tailoring the mechanical properties of PU membranes without changing its structural characteristics. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007     

Framework for Providing Customized Data Representations for Effective and Efficient Interaction with Mobile Computing Solutions on Construction Sites

Conceptual representations of information contained in product and process models are often difficult to use for accessing data when performing engineering tasks. This is especially true if project-management information contained in product and process models needs to be made accessible on a mobile computer on construction sites. To make this information accessible, customized conceptual and visual information representations are needed. For the project-management tasks of progress monitoring and creating and administering punch lists, existing approaches that provide access to relevant project information are ineffective and inefficient in transforming information from product and process models into usable representations. As a result, these applications do not always provide information representations that are of the required structure, granularity, and type. In this paper, we describe a navigational model framework, which is an approach that effectively and efficiently creates and manages different views of information contained in product and process models. We validated this framework by implementing a prototype system and testing it through a designed set of experiments. The use cases for these experiments were established in an extensive study on the information and data collection needs on construction sites.     

Lysozyme-loaded lipid-polymer hybrid nanoparticles: preparation,characterization and colloidal stability evaluation

Context: Lipid-polymer hybrid nanoparticles (LPNPs) are polymeric nanoparticles enveloped by lipid layers, which have emerged as a potent therapeutic nanocarrier alternative to liposomes and polymeric nanoparticles.

Objective: The aim of this work was to develop, characterize and evaluate LPNPs to deliver a model protein, lysozyme.

Materials and methods: Lysozyme-loaded LPNPs were prepared by using the modified w/o/w double-emulsion-solvent-evaporation method. Poly-?-caprolactone (PCL) was used as polymeric core material and tripalmitin:lechitin mixture was used to form a lipid shell around the LPNPs. LPNPs were evaluated for particle size distribution, zeta potential, morphology, encapsulation efficiency, in vitro drug release, stability and cytotoxicity.

Results: The DLS measurement results showed that the particle size of LPNPs ranged from 58.04?±?1.95?nm to 2009.00?±?0.52?nm. The AFM and TEM images of LPNPs demonstrate that LPNPs are spherical in shape. The protein-loading capacity of LPNPs ranged from 5.81% to 60.32%, depending on the formulation parameters. LPNPs displayed a biphasic drug release pattern with a burst release within 1?h, followed by sustained release afterward. Colloidal stability results of LPNPs in different media showed that particle size and zeta potential values of particles did not change significantly in all media except of FBS 100% for 120?h. Finally, the results of a cellular uptake study showed that LPNPs were significantly taken up by 83.3% in L929 cells.

Conclusion: We concluded that the LPNPs prepared with PCL as polymeric core material and tripalmitin:lechitin mixture as lipid shell should be a promising choice for protein delivery.     

Electrocoagulation of simulated reactive dyebath effluent with aluminum and stainless steel electrodes

Reactive dyebath effluents are ideal candidates for electrocoagulation due to their intensive color, medium strength, recalcitrant COD and high electrolyte (NaCl) content. The present study focused on the treatability of simulated reactive dyebath effluent (COD(o)=300 mg/L; color in terms of absorbance values A(o,436)=0.532 cm(-1), A(o,525)=0.693 cm(-1) and A(o,620)=0.808 cm(-1)) employing electrocoagulation with aluminum and stainless steel electrodes. Optimization of critical operating parameters such as initial pH (pH(o) 3-11), applied current density (J(c)=22-87 mA/cm(2)) and electrolyte type (NaCl or Na(2)SO(4)) improved the overall treatment efficiencies resulting in effective decolorization (99% using stainless steel electrodes after 60 min, 95% using aluminum electrodes after 90 min electrocoagulation) and COD abatement (93% with stainless steel electrodes after 60 min, 86% with aluminum electrodes after 90 min of reaction time). Optimum electrocoagulation conditions were established as pH(o) 5 and J(c)=22 mA/cm(2) for both electrode materials. The COD and color removal efficiencies also depended on the electrolyte type. No in situ, surplus adsorbable organically bound halogens (AOX) formation associated with the use of NaCl as the electrolyte during electrocoagulation was detected. An economical evaluation was also carried out within the frame of the study. It was demonstrated that electrocoagulation of reactive dyebath effluent with aluminum and stainless steel electrodes was a considerably less electrical energy-intensive, alternative treatment method as compared with advanced chemical oxidation techniques.     

Application of Different Molecular Techniques for Characterization of Catalase‐Positive Cocci Isolated from Sucuk

This study was carried out for the characterization and discrimination of the indigenous Gram positive, catalase‐positive cocci (GCC) population in sucuk, a traditional Turkish dry‐fermented sausage. Sucuk samples, produced by the traditional method without starter culture were collected from 8 local producers in Kayseri/Turkey and a total of 116 GCC isolates were identified by using different molecular techniques. Two different molecular fingerprinting methods; namely, randomly amplified polymorphic DNA‐PCR (RAPD‐PCR) and repetitive extragenic palindrome‐PCR (rep‐PCR), were used for the clustering of isolates and identification at species level was carried out by full length sequencing of 16S rDNA. Combining the results obtained from molecular fingerprinting and 16S rDNA sequencing showed that the dominant GCC species isolated from the sucuk samples was Staphylococcus saprophyticus followed by Staphylococcus succinus and Staphylococcus equorum belonging to the Staphylococcus genus. Real‐time PCR DNA melting curve analysis and high‐resolution melting (HRM) analysis targeting the V1 + V3 regions of 16S rDNA were also applied for the discrimination of isolates belonging to different species. It was observed statistically different Tm values and species‐specific HRM profiles for all except 2 species (S. saprophyticus and Staphylococcus xylosus) that have high 16S rDNA sequence similarity. The combination of rep‐PCR and/or PCR‐RAPD with 16S rRNA gene sequencing was an efficient approach for the characterization and identification of the GCC population in spontaneously fermented sucuk. On the other hand, intercalating dye assays were found to be a simple and very promising technique for the differentiation of the GCC population at species level.     

Nano-engineering of high-performance PA6.6 nanocomposites by the integration of CVD-grown carbon fiber on graphene as a bicomponent reinforcement by melt-compounding

In this study, long carbon nanofibers (CNFs) were grown on graphene nanoplatelets (GNPs) by chemical vapor deposition (CVD) technique to develop three-dimensional (3D) bicomponent nanostructures. The structure and properties of graphene before and after CVD process were investigated in details. X-ray photoelectron analysis depicted the formation of Fe-C bonds by the deposition of carbon atoms on the catalyst surface of Fe₂O₃. This hybrid additive was firstly used as a reinforcing agent in melt compounding to fabricate PA6.6-based nanocomposites with enhanced mechanical and thermal properties. Both GNP and CNF-GNP have enough surface oxygen functional groups to improve the interfacial interactions with polyamide matrix and thus provide good wettability. Also, both neat GNP and its bicomponent additive with CNF also acted as a nucleating agent and allowed the crystal growth in nanocomposite structure. Homogeneous dispersion of nanoparticles was achieved by using thermokinetic mixer during compounding by applying high shear rates. Mechanical results showed that 23 and 34% improvement in flexural and tensile modulus values, respectively, was attained by the addition of 0.5 wt % CNF-GNP hybrid additive. The heat distortion temperature and Vicat softening temperature of the resulting PA6.6 nanocomposites were improved compared to neat PA6.6 material indicating performance enhancement at higher service temperature conditions. CNF was successfully grown on Fe-loaded GNP by CVD method and this hybrid additive was compounded with PA6.6 by melt-mixing process. Mechanical results showed that 34% improvement in tensile modulus value was attained by the addition of 0.5 wt % CNF-GNP hybrid additive because it acted as a nucleating agent and allowed the crystal growth in the nanocomposite structure. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48347.