Synthesis and investigation of new cholesteryl carbamate-based liquid crystals

Journal of Materials Science: Materials in Electronics - Cholesteryl chloroformate which is known liquid crystal material was modified to give the new molecules a long-lasting LC phases with the...     

Porous 3D printed concrete beams show an environmental promise: a cradle-to-grave comparative life cycle assessment

3D Concrete Printing (3DCP) is a rapidly expanding area in the field of architecture, engineering, and construction, but very limited research has quantitatively investigated its environmental impact. The existing Life Cycle Assessment (LCA) studies on 3DCP lack clearly defined functional units of comparison, especially considering load-bearing structures. This paper investigates the potential environmental benefits of 3DCP over conventional concrete construction for structural beams based on a cradle-to-grave comparative LCA. Unlike existing studies, this paper employs a recarbonation model to account for the carbon offsetting from the use-stage of 3DP concrete, which shows significant results. The assessment includes three-beam designs, each analyzed for both prefabrication and on-site construction scenarios. While currently, 3DCP has a generally higher environmental impact due to the larger quantity of cement employed in the process, the reduction of material through infill optimization for printed beams is a promising design principle to positively offset the environmental impacts in the construction sector. The paper draws recommendations for future research on material- and recarbonation-efficient 3DCP design for load-bearing structures, as well as on material development, e.g. integration of larger aggregates and low-clinker cement.

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Stock Price Prediction Using Predictive Error Compensation Wavelet Neural Networks

Machine Learning (ML) algorithms have been widely used for financial time series prediction and trading through bots. In this work, we propose a Predictive Error Compensated Wavelet Neural Network (PEC-WNN) ML model that improves the prediction of next day closing prices. In the proposed model we use multiple neural networks where the first one uses the closing stock prices from multiple-scale time-domain inputs. An additional network is used for error estimation to compensate and reduce the prediction error of the main network instead of using recurrence. The performance of the proposed model is evaluated using six different stock data samples in the New York stock exchange. The results have demonstrated significant improvement in forecasting accuracy in all cases when the second network is used in accordance with the first one by adding the outputs. The RMSE error is 33% improved when the proposed PEC-WNN model is used compared to the Long Short-Term Memory (LSTM) model. Furthermore, through the analysis of training mechanisms, we found that using the updated training the performance of the proposed model is improved. The contribution of this study is the applicability of simultaneously different time frames as inputs. Cascading the predictive error compensation not only reduces the error rate but also helps in avoiding overfitting problems.     

Trans-differentiation of human adipose-derived mesenchymal stem cells into cardiomyocyte-like cells on decellularized bovine myocardial extracellular matrix-based films

In this study, we aimed at fabricating decellularized bovine myocardial extracellular matrix-based films (dMEbF) for cardiac tissue engineering (CTE). The decellularization process was carried out utilizing four consecutive stages including hypotonic treatment, detergent treatment, enzymatic digestion and decontamination, respectively. In order to fabricate the dMEbF, dBM were digested with pepsin and gelation process was conducted. dMEbF were then crosslinked with N-hydroxysuccinimide/1-Ethyl-3-(3-dimethylaminopropyl)-carbodiimide (NHS/EDC) to increase their durability. Nuclear contents of native BM and decellularized BM (dBM) tissues were determined with DNA content analysis and agarose-gel electrophoresis. Cell viability on dMEbF for 3rd, 7th, and 14th days was assessed by MTT assay. Cell attachment on dMEbF was also studied by scanning electron microscopy. Trans-differentiation capacity of human adipose-derived mesenchymal stem cells (hAMSCs) into cardiomyocyte-like cells on dMEbF were also evaluated by histochemical and immunohistochemical analyses. DNA contents for native and dBM were, respectively, found as 886.11?±?164.85 and 47.66?±?0.09?ng/mg dry weight, indicating a successful decellularization process. The results of glycosaminoglycan and hydroxyproline assay, and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), performed in order to characterize the extracellular matrix (ECM) composition of native and dBM tissue, showed that the BM matrix was not damaged during the proposed method. Lastly, regarding the histological study, dMEbF not only mimics native ECM, but also induces the stem cells into cardiomyocyte-like cells phenotype which brings it the potential of use in CTE.     

Atmospheric pressure chemical vapor infiltration (CVI) for the preparation of biomorphic SiC ceramics derived from paper

Chemical Vapor Infiltration of biological structures such as paper is used here to produce biomorphic SiC ceramics with high temperature resistance. The biological substrate materials are infiltrated with tetramethylsilane (TMS) at atmospheric pressure and elevated temperatures of 790 degrees C. A simple tube furnace (hot-wall reactor) is used for the infiltration process. As result, porous SiC-ceramics are grown which are around 20% smaller and 70% lighter than the initial substrates. This can be explained by the pyrolytic reaction of the substrates while heating them up to 790 degrees C, which is necessary for the infiltration process. Nevertheless, besides the shrinking of the substrates the geometrical form remains nearly unchanged. The resulting materials were heated up to 1000 degrees C in oxygen atmosphere in order to analyze their resistance against oxidation. After this treatment, all of them were still mechanically stable and of unchanged shape while a further mass loss was observed. This confirms the high temperature stability of the prepared materials.     

Effects of porosity and related interstitial phase morphology difference on the grindability of clinkers

The effects of regional clinker porosity and interstitial phase morphology differences on grindability of clinkers have been investigated within the scope of this study. Porosity and phase characteristics of two clinkers from different furnaces which are using the same raw materials were determined by the application of image processing techniques on SEM images of polished surfaces. Comparison of interstitial phase compositions of two clinkers showed that, clinkers with similar phase compositions may have different grindability due to the porosity and phase morphology differences. Porous clinkers usually exhibit a dendritic interstitial phase morphology with an improved grindability. Increasing porosity also leads to greater incidence of the dendritic morphology in porous regions and lower incidence of alkali in the aluminate in dendritic regions.     

Transition to a JIT production system through ERP implementation: a case from the automotive industry

ERP systems provide important benefits to institutions, such as improved processes, improved data, supplier–customer integration, better planning and control, as well as real-time insight and just-in-time (JIT) management that can put a business organisation in front of the competition. In this study, the change and transformation experienced by establishing an ERP system are explained for an automotive supplier that was not using an integrated ERP system for a real-world problem. The pre-implementation situation, the problems of the existing system, the necessary reasons for such an application, the determined deficiencies of the installed system and the post-implementation situation are explained in detail. Thanks to the real-time information and integrated data generated by the reports, along with a more sophisticated business understanding, the risk to employees was lowered. As a result of a changeover to real-time Materials Requirement Planning, the decrease in inventory levels, stabilisation in delivery time and efficiency of control over the production processes were increased in addition to real-time tracking and reporting advantages. As a result of this work, the production processes were transformed into JIT. The inventory level was reduced to zero and a formerly used warehouse was no longer required.     

Parallel machine scheduling with tool loading: a constraint programming approach

This paper presents constraint programming models that aim to solve scheduling and tool assignment problems in parallel machine environments. There are a number of jobs to be processed on parallel machines. Each job requires a set of tools, but limited number of tools are available in the system due to economic restrictions. The problem is to assign the jobs and the required tools to machines and to determine the schedule so that the makespan is minimised. Three constraint programming models are developed and compared with existing methods described in the literature.