Out‐of‐Plane 3D‐Printed Microfibers Improve the Shear Properties of Hydrogel Composites

One challenge in biofabrication is to fabricate a matrix that is soft enough to elicit optimal cell behavior while possessing the strength required to withstand the mechanical load that the matrix is subjected to once implanted in the body. Here, melt electrowriting (MEW) is used to direct‐write poly(ε‐caprolactone) fibers “out‐of‐plane” by design. These out‐of‐plane fibers are specifically intended to stabilize an existing structure and subsequently improve the shear modulus of hydrogel–fiber composites. The stabilizing fibers (diameter = 13.3 ± 0.3 µm) are sinusoidally direct‐written over an existing MEW wall‐like structure (330 µm height). The printed constructs are embedded in different hydrogels (5, 10, and 15 wt% polyacrylamide; 65% poly(2‐hydroxyethyl methacrylate) (pHEMA)) and a frequency sweep test (0.05–500 rad s^?1, 0.01% strain, n = 5) is performed to measure the complex shear modulus. For the rheological measurements, stabilizing fibers are deposited with a radial‐architecture prior to embedding to correspond to the direction of the stabilizing fibers with the loading of the rheometer. Stabilizing fibers increase the complex shear modulus irrespective of the percentage of gel or crosslinking density. The capacity of MEW to produce well‐defined out‐of‐plane fibers and the ability to increase the shear properties of fiber‐reinforced hydrogel composites are highlighted.     

Bat4CEP: a bat algorithm for mining of complex event processing rules

Complex Event Processing (CEP) is a modern software technology for the dynamic analysis of continuous data streams. CEP is able of searching extremely large data streams in real time for the presence of event patterns. So far, specifying event patterns of CEP rules is still a manual task based on the expertise of domain experts. This paper presents a novel bat-inspired swarm algorithm for automatically mining CEP rule patterns that express the relevant causal and temporal relations hidden in data streams. The basic suitability and performance of the approach is proven by extensive evaluation with both synthetically generated data and real data from the traffic domain.

     

ErgoVSM: A Tool for Integrating Value Stream Mapping and Ergonomics in Manufacturing

Value stream mapping (VSM) is a lean tool aiming at waste reduction. Previous research suggests that the use of VSM may result in work intensification and thus an increased risk for the workers of developing work‐related musculoskeletal disorders (MSD). In the current study, VSM was developed to also consider physical exposure in the analyzed production system (ErgoVSM). As the VSM, ErgoVSM is based on a participatory approach. ErgoVSM was tested in a Swedish manufacturing company. The results suggest that ErgoVSM catalyzes change processes to include intervention proposals emphasizing ergonomics in addition to waste reduction. Thus, ErgoVSM appeared useful for the investigated target group of production engineers and experienced operators. The performance improvements suggested when using the ordinary VSM seemed not to be hampered by adding the ergonomics complement. However, the use of ErgoVSM was somewhat more time consuming than the use of VSM. In conclusion, ErgoVSM is suggested as a feasible tool to be used by production engineers and experienced operators for including ergonomics considerations in the rationalization process.     

A decision support system for improved resource planning and truck routing at logistic nodes

In this paper, we present an innovative decision support system that simultaneously provides predictive analytics to logistic nodes as well as to collaborating truck companies. Logistic nodes, such as container terminals, container depots or container loading facilities, face heavy workloads through a large number of truck arrivals during peak times. At the same time, truck companies suffer from augmented waiting times. The proposed system provides forecasted truck arrival rates to the nodes and predicted truck gate waiting times at the nodes to the truck companies based on historical data, economic and environmental impact factors. Based on the expected workloads, the node personnel and machinery can be planned more efficiently. Truck companies can adjust their route planning in order to minimize waiting times. Consequently, both sides benefit from reduced truck waiting times while reducing traffic congestion and air pollution. We suggest a flexible cloud based service that incorporates an advanced forecasting engine based on artificial intelligence capable of providing individual predictions for users on all planning levels. In a case study we report forecasting results obtained for the truck waiting times at an empty container depot using artificial neural networks.     

Designing a Hydrological Real-Time System for Surface Water and Groundwater in Denmark with Engagement of Stakeholders

Increasing attention on extreme hydrological events has created considerable demand for real-time information on surface water, groundwater and the unsaturated zone. In the present study, we describe how to convert a national water resources model (DK-model) covering the entire freshwater cycle in Denmark to real-time application. We have engaged stakeholders in the process of designing a hydrological real-time system. The participatory approach has been supported by a web-based questionnaire survey and a participatory workshop. A system prototype presented to the stakeholders simulates groundwater levels, streamflow and water content in the root zone with a lead time of 48 h. The active engagement of stakeholders has provided very valuable insights and feedbacks regarding how model and data should be combined in a real-time to best supporting water resources management.     

Physical performances of alkali‐activated portland cement‐glass‐limestone blends

The potential of calcium aluminosilicate (CAS) glasses as supplementary cementitious materials is studied in terms of the development of compressive strength for mortars containing a mixture of portland cement, CAS glass, and limestone. In addition, the impact of internal and external alkali activation of the cementitious systems on the mortar performances is investigated. Internal alkali activation is obtained by adding alkali oxides to the CAS glass system, whereas external alkali activation is realized by hydration of the blended cements containing alkali‐free CAS glasses using alkaline solutions. For the internally alkali‐activated systems and the alkali‐free mortars, higher strengths are achieved in comparison to the reference mortar prepared from plain ordinary portland cement. In contrast, the externally alkali‐activated mortars exhibit lower compressive strengths, implying the importance of both the immediate availability of alkali ions in the cementitious system and the increased dissolution rate of the glass particles caused by the network depolymerization. The glasses are also studied by thermal analysis and the results are used to calculate the theoretical CO₂ emissions. The lowest embodied CO₂ emission is estimated for the blends containing alkali‐activated CAS glasses.     

Electromechanical properties of CaZrO3 modified (K,Na)NbO3‐based lead‐free piezoceramics under uniaxial stress conditions

Piezoelectric actuators are typically preloaded with a modest mechanical compressive stress during actuation to reduce cracking and allow for operation in the dynamic range. In addition, actuators are required to carry out mechanical work during operation, resulting in a nonlinear relationship between stress and actuation voltage. In fact, mechanical loading can significantly impact the electromechanical performance of lead‐free piezoelectrics. Herein, we report the dependence of electromechanical properties of CaZrO₃ modified (K,Na)NbO₃‐based lead‐free piezoceramics on uniaxial compressive stress, comparing to their lead‐based counterparts. It is demonstrated that increased non‐180° domain switching enhances the strain output at a moderate stress of approximately ?50 MPa from room temperature to 150°C. Larger uniaxial stress, however, is found to suppress ferroelectric domain switching, resulting in the continuous strain and polarization decrease.     

New Fluorescent Nanoparticles for Ultrasensitive Detection of Nucleic Acids by Optical Methods

For decades the detection of nucleic acids and their interactions at low abundances has been a challenging task that has thus far been solved by enzymatic target amplification. In this work we aimed at developing efficient tools for amplification‐free nucleic acid detection, which resulted in the synthesis of new fluorescent nanoparticles. Here, the fluorescent nanoparticles were made by simple and inexpensive radical emulsion polymerization of butyl acrylate in the presence of fluorescent dyes and additional functionalization reagents. This provided ultra‐bright macrofluorophores of 9–84 nm mean diameter, modified with additional alkyne and amino groups for bioconjugation. By using click and NHS chemistries, the new nanoparticles were attached to target‐specific DNA probes that were used in fluorimetry and fluorescence microscopy. Overall, these fluorescent nanoparticles and their oligonucleotide derivatives have higher photostability, brighter fluorescence and hence dramatically lower limits of target detection than the individual organic dyes. These properties make them useful in approaches directed towards ultrasensitive detection of nucleic acids, in particular for imaging and in vitro diagnostics of DNA.