Correction to: Two New Co(II) Complexes of Picolinate: Synthesis,Crystal Structure,Spectral Characterization, α-Glucosidase İnhibition and TD/DFT Study

Journal of Inorganic and Organometallic Polymers and Materials -     

A haar wavelet approximation for two-dimensional time fractional reaction–subdiffusion equation

Engineering with Computers - In this study, we established a wavelet method, based on Haar wavelets and finite difference scheme for two-dimensional time fractional reaction–subdiffusion...     

Combining Electricity and Fuel Supply: Operational Strategies for Biogas Plants

The operational consequences resulting from the combination of a flexibly operated combined heat and power unit (CHP) and an off‐grid biomethane filling station at one biogas plant were investigated. Four different operating scenarios were compared to evaluate the storage capacity needed to balance biogas demand fluctuations and biogas production. The scenario in which fuel production was given priority and electricity was produced within the remaining hours proved to cause the lowest additional costs since it does not require additional installation of biogas storage capacity and causes minor opportunity cost in electricity marketing. Giving fuel demand the priority reduces the necessary biogas storage capacity by 75 % compared to parallel optimization of the electricity and fuel demands.     

Tunable Fano-Resonant Metasurfaces on a Disposable Plastic-Template for Multimodal and Multiplex Biosensing

Metasurfaces are engineered nanostructured interfaces that extend the photonic behavior of natural materials, and they spur many breakthroughs in multiple fields, including quantum optics, optoelectronics, and biosensing. Recent advances in metasurface nanofabrication enable precise manipulation of light–matter interactions at subwavelength scales. However, current fabrication methods are costly and time-consuming and have a small active area with low reproducibility due to limitations in lithography, where sensing nanosized rare biotargets requires a wide active surface area for efficient binding and detection. Here, a plastic-templated tunable metasurface with a large active area and periodic metal–dielectric layers to excite plasmonic Fano resonance transitions providing multimodal and multiplex sensing of small biotargets, such as proteins and viruses, is introduced. The tunable Fano resonance feature of the metasurface is enabled via chemical etching steps to manage nanoperiodicity of the plastic template decorated with plasmonic layers and surrounding dielectric medium. This metasurface integrated with microfluidics further enhances the light–matter interactions over a wide sensing area, extending data collection from 3D to 4D by tracking real-time biomolecular binding events. Overall, this work resolves cost- and complexity-related large-scale fabrication challenges and improves multilayer sensitivity of detection in biosensing applications.     

Feature selection and fault‐severity classification–based machine health assessment methodology for point machine sliding‐chair degradation

In this paper, we propose an offline and online machine health assessment (MHA) methodology composed of feature extraction and selection, segmentation‐based fault severity evaluation, and classification steps. In the offline phase, the best representative feature of degradation is selected by a new filter‐based feature selection approach. The selected feature is further segmented by utilizing the bottom‐up time series segmentation to discriminate machine health states, ie, degradation levels. Then, the health state fault severity is extracted by a proposed segment evaluation approach based on within segment rate‐of‐change (RoC) and coefficient of variation (CV) statistics. To train supervised classifiers, a priori knowledge about the availability of the labeled data set is needed. To overcome this limitation, the health state fault‐severity information is used to label (eg, healthy, minor, medium, and severe) unlabeled raw condition monitoring (CM) data. In the online phase, the fault‐severity classification is carried out by kernel‐based support vector machine (SVM) classifier. Next to SVM, the k‐nearest neighbor (KNN) is also used in comparative analysis on the fault severity classification problem. Supervised classifiers are trained in the offline phase and tested in the online phase. Unlike to traditional supervised approaches, this proposed method does not require any a priori knowledge about the availability of the labeled data set. The proposed methodology is validated on infield point machine sliding‐chair degradation data to illustrate its effectiveness and applicability. The results show that the time series segmentation‐based failure severity detection and SVM‐based classification are promising.     

Simultaneous detection of surface coverage and structure of krypton films on gold by helium atom diffraction and quartz crystal microbalance techniques

We describe a quartz crystal microbalance setup that can be operated at low temperatures in ultra high vacuum with gold electrode surfaces acting as substrate surface for helium diffraction measurements. By simultaneous measurement of helium specular reflection intensity from the electrode surface and resonance frequency shift of the crystal during film adsorption, helium diffraction data can be correlated to film thickness. In addition, effects of interfacial viscosity on the helium diffraction pattern could be observed. To this end, first, flat gold films on AT cut quartz crystals were prepared which yield high enough helium specular reflection intensity. Then the crystals were mounted in the helium diffractometer sample holder and driven by means of a frequency modulation driving setup. Different crystal geometries were tested to obtain the best quality factor and preliminary measurements were performed on Kr films on gold surfaces. While the crystal structure and coverage of krypton films as a function of substrate temperature could successfully be determined, no depinning effects could be observed.     

Towards providing optimal energy‐efficiency and throughput for IEEE 802.11 WLANs

IEEE 802.11 wireless network standard has become one of the most used wireless networking technologies for smart devices as it offers mobility support and low cost deployment. However, these devices deeply rely on the energy provided by their batteries, which results in limited running time. IEEE 802.11 network standard provides stations with carrier sense multiple access with collision avoidance for the medium access. Yet it results in stations to consume an important amount of power. Therefore, minimizing WiFi‐based energy consumption in smart devices has been received substantial attention in both academia and industry. Accordingly, this paper * proposes a novel beacon‐based energy‐efficient collision‐free medium access control protocol for any type of IEEE 802.11 stations, regardless of being stationary or mobile, or having different amount of traffic flow, transmission rates, or traffic types. The proposed scheme is valid for all types of low or wide bandwidth, single or multiuser multiple‐input multiple‐output WLAN channels, such as IEEE 802.11a\b\g\n\ac. In the proposed scheme, energy saving is achieved, enabling stations to transmit on the right time and maintaining stations in the doze state during a predetermined sleep_time interval after each successful frame transmission, by making use of modified control and management frames of the standard IEEE 802.11 protocol. The proposed scheme reduces the probability of collisions and may allow stations to enter the collision‐free state, regardless of the number of stations on the channel and their traffic types. Widespread simulations have been executed to validate the efficiency of the proposed method. The results demonstrate that the proposed method significantly increases overall throughput and reduces power consumption of stations over IEEE 802.11 WLANs.