A Thermo-Electric Energy Storage (TEES) system is proposed to provide peak-load support (1–2 daily hours of operation) for distributed users using small/medium-size photovoltaic systems (4 to 50 kWe). The purpose is to complement the PV with a reliable storage system that cancompensate the produc tivity/load mismatch, aiming at off-grid operation. The proposed TEES applies sensible heat storage, using insulated warm-water reservoirs at 120/160 °C, and cold storage at −10/−20 °C (water and ethylene glycol). The power cycle is a trans-critical CO₂ unit including recuperation; in the storage mode, a supercritical heat pump restores heat to the hot reservoir, while a cooling cycle cools the cold reservoir; both the heat pump and cooling cycle operate on photovoltaic (PV) energy, and benefit from solar heat integration at low–medium temperatures (80–120 °C). This allows the achievement of a marginal round-trip efficiency (electric-to-electric) in the range of 50% (not considering solar heat integration).The TEES system is analysed with different resource conditions and parameters settings (hot storage temperature, pressure levels for all cycles, ambient temperature, etc.), making reference to standard days of each month of the year; exergy and exergo-economic analyses are performed to identify the critical items in the complete system and the cost of stored electricity. Full article

This paper presents design details adopting open embedded systems (OES) as real-time controllers in industrial distributed control systems. OES minimize development cost and enhance portability while addressing widely known shortcomings of their proprietary counterparts. These shortcomings include the black box method of distribution which hinders integration to more complex systems. However, OES are highly dependent on the compatibility of each software components and essential benchmarking is required to ensure that the system can satisfy hard real-time constraints. To address these issues and the notion that OES will find broader distributed control applications, we provide detailed procedures in realizing OES based on an open source real-time operating system on various low-cost open embedded platforms. Their performance was evaluated and compared in terms of periodicity and schedulability, task synchronization, and interrupt response time, which are crucial metrics to determine stability and reliability of real-time controllers. Practical implementations, including the modernization of a multi-axis industrial robot controller, are described clearly to serve as a comprehensive reference on the integration of OES in industrial distributed control systems. Full article

Coumarins and essential oils are the major components of the Apiaceae family and the Zosima genus. The present study reports anticholinesterase and antioxidant activities of extracts and essential oils from aerial parts, roots, flowers, fruits and coumarins—bergapten (1); imperatorin (2), pimpinellin (3) and umbelliferone (4)—isolated of the roots from Zosima absinthifolia. The investigation by light and scanning electron microscopy of the structures of secretory canals found different chemical compositions in the various types of secretory canals which present in the aerial parts, fruits and flowers. The canals, present in the aerial parts, are characterized by terpene hydrocarbons, while the secretory canals of roots, flowers and fruits include esters. Novel data of a comparative study on essential oils constituents of aerial parts, roots, flowers and fruits of Z. absinthfolia has been presented. The roots and fruits extract showed a high content of total phenolics and antioxidant activity. The GC-FID and GC-MS analysis revealed that the main components of the aerial parts, roots, flowers and fruits extracts were octanol (8.8%), octyl octanoate (7.6%), octyl acetate (7.3%); trans-pinocarvyl acetate (26.7%), β-pinene (8.9%); octyl acetate (19.9%), trans-p-menth-2-en-1-ol (4.6%); octyl acetate (81.6%), and (Z)-4-octenyl acetate (5.1%). The dichloromethane fraction of fruit and flower essential oil was characterized by the highest phenolics level and antioxidant activity. The dichloromethane fraction of fruit had the best inhibition against butyrylcholinesterase enzyme (82.27 ± 1.97%) which was higher then acetylcholinesterase inhibition (61.09 ± 4.46%) of umbelliferone. This study shows that the flowers and fruit of Z. absinthifolia can be a new potential resource of natural antioxidant and anticholinesterase compounds. Full article

The ultra-short pulsed laser annealing process enhances the performance of MoS₂ thin film transistors (TFTs) without thermal damage on plastic substrates. However, there has been insufficient investigation into how much improvement can be brought about by the laser process. In this paper, we observed how the parameters of TFTs, i.e., mobility, subthreshold swing, I_on/I_off ratio, and V_th, changed as the TFTs’ contacts were (1) not annealed, (2) annealed on one side, or (3) annealed on both sides. The results showed that the linear effective mobility (μ_{eff_lin}) increased from 13.14 [cm²/Vs] (not annealed) to 18.84 (one side annealed) to 24.91 (both sides annealed). Also, I_on/I_off ratio increased from $2.27\times {10}^5$ (not annealed) to $3.14\times {10}^5$ (one side annealed) to $4.81\times {10}^5$(both sides annealed), with V_th shifting to negative direction. Analyzing the main reason for the improvement through the Y function method (YFM), we found that both the contact resistance (R_c) and the channel interface resistance (R_ch) improves after the pulsed laser annealings under different conditions. Moreover, the R_c enhances more dramatically than the R_ch does. In conclusion, our picosecond laser annealing improves the performance of TFTs (especially, the R_c) in direct proportion to the number of annealings applied. The results will contribute to the investigation about correlations between the laser annealing process and the performance of devices. Full article

The aim of this study is to investigate the corrosion behavior of steel reinforcement embedded in mortar specimens in which both the aggregate and cement are partially replaced by ladle furnace slag (LFS) and different percentages of chloride ions by weight of cement are introduced into the mix at the time of kneading. The corrosion behavior was studied by using electrochemical techniques in order to evaluate the corrosion rate and the symptoms produced in steels of specimens with and without slag LFS. From the analysis of the results, it is concluded that the use of LFS in a partial replacement of aggregate and cement in mortar specimens does not compromise the behavior of the mortar with regard to corrosion of the steel reinforcement; consequently, partial replacement by LFS is fully feasible from this standpoint. Full article

This proposal suggests a novel nonlinear position-stabilizing controller for magnetic levitation (MAGLEV) applications. The proposed scheme is devised by combining the active damping injection technique and disturbance observers (DOBs), considering the inherent nonlinear dynamics, as well as parameter and load variations. The convergence and performance recovery properties are obtained by analyzing the closed-loop dynamics, which is the main contribution. The numerical verification confirms a considerable closed-loop robustness improvement, compared with the cascade-type feedback-linearization controller. Full article

The subsurface target classification of ground penetrating radar (GPR) is a popular topic in the field of geophysics. Among the existing classification methods, geometrical features and polarimetric attributes of targets are primarily used. As polarimetric attributes contain more information of targets, polarimetric decomposition methods, such as H-Alpha decomposition, have been developed for target classification of GPR in recent years. However, the classification template used in H-Alpha classification is preset depending on the experience of synthetic aperture radar (SAR); therefore, it may not be suitable for GPR. Moreover, many existing classification methods require excessive human operation, particularly when outliers exist in the sample (the data set containing the features of targets); therefore, they are not efficient or intelligent. We herein propose a new machine learning method based on sample centers, i.e., particle center supported plane (PCSP). The sample center is defined as the point with the smallest sum of distances from all points in the same sample, which is considered as a better representation of the sample without significant effect of the outliers. In this proposed method, particle swarm optimization (PSO) is performed to obtain the sample centers; the new criterion for subsurface target classification is achieved. We applied this algorithm to full polarimetric GPR data measured in the laboratory and outdoors. The results indicate that, comparing with support vector machine (SVM) and classical H-Alpha classification, this new method is more efficient and the accuracy is relatively high. Full article

In recent years, there has been an increasing need for materials that are environmentally friendly and have functional properties. Polylactic acid (PLA) is a biomass-based polymer, which has attracted research attention as an eco-friendly material. Various studies have been conducted on functionality imparting and performance improvement to extend the field of application of PLA. Particularly, research on natural fiber-reinforced composites have been conducted to simultaneously improve their environmental friendliness and mechanical strength. Research interest in hybrid composites using two or more fillers to realize multiple functions are also increasing. Phase change materials (PCMs) absorb and emit energy through phase transition and can be used as a micro encapsulated structure. In this study, we fabricated hybrid composites using microcapsulated PCM (MPCM) and the natural fibrous filler, kenaf. We aimed to fabricate a composite material with improved endothermic characteristics, mechanical performance, and environmental friendliness. We analyzed the endothermic properties of MPCM and the structural characteristics of two fillers and finally produced an eco-friendly composite material. The PCM and kenaf contents were varied to observe changes in the performance of the hybrid composites. The endothermic properties were determined through differential scanning calorimetry, whereas changes in the physical properties of the hybrid composite were determined by measuring the mechanical properties. Full article

N6-methyladenosine (m⁶A) has been identified in various biological processes and plays important regulatory functions in diverse cells. However, there is still no visualization database for exploring global m⁶A patterns across cell lines. Here we collected all available MeRIP-Seq and m⁶A-CLIP-Seq datasets from public databases and identified 340,950 and 179,201 m⁶A peaks dependent on 23 human and eight mouse cell lines respectively. Those m⁶A peaks were further classified into mRNA and lncRNA groups. To better understand the potential function of m⁶A, we then mapped m⁶A peaks in different subcellular components and gene regions. Among those human m⁶A modification, 190,050 and 150,900 peaks were identified in cancer and non-cancer cells, respectively. Finally, all results were integrated and imported into a visualized cell-dependent m⁶A database CVm6A. We believe the specificity of CVm6A could significantly contribute to the research for the function and regulation of cell-dependent m⁶A modification in disease and development. Full article

With the development of continuous casting technology, there has been an increase in the stringent requirements for the cleanliness and quality of steel being produced. The flow state of molten steel in tundish is the key to: Optimizing the residence time of molten steel in the tundish; homogenizing the temperature of molten steel; and removing inclusions by floatation. Hence, from theoretical and practical aspects, it is imperative to examine and analyze the flow field of molten steel in the tundish in order to ensure the desired molten steel flow. In this study, a two-strand tundish with 650 mm × 180 mm slab casting is considered as the subject for this research. According to the similarity theory, combined with the geometrical shape and dimension of the prototype tundish, a tundish model with a geometric similarity ratio of 2:3 is established in the laboratory. Digital particle image velocimetry (PIV) is employed to measure and examine the flow fields at different casting speeds for a tundish containing different flow control devices. The flow in the tundish is typically turbulent and also consists of a vortex motion; it exhibits both random and ordered characteristics. Results reveal that the presence of baffles with 15° holes can cause an upward-directed flow in the outlet section and give rise to a large circulation. When the casting speed is doubled, the overall velocity of the flow field and turbulent intensity increase, leading to an increase in the molten steel surface velocity. Full article

This article provides a detailed comparative analysis of five orientational, two degrees of freedom (DOF) mechanisms whose envisioned application is the wrist of the iCub humanoid robot. Firstly, the current iCub mk.2 wrist implementation is presented, and the desired design objectives are proposed. Prominent architectures from literature such as the spherical five-bar linkage and spherical six-bar linkage, the OmniWrist-III and the Quaternion joint mechanisms are modeled and analyzed for the said application. Finally, a detailed comparison of their workspace features is presented. The Quaternion joint mechanism emerges as a promising candidate from this study. Full article

Traditional plant breeding evaluation methods are time-consuming, labor-intensive, and costly. Accurate and rapid phenotypic trait data acquisition and analysis can improve genomic selection and accelerate cultivar development. In this work, a technique for data acquisition and image processing was developed utilizing small unmanned aerial vehicles (UAVs), multispectral imaging, and deep learning convolutional neural networks to evaluate phenotypic characteristics on citrus crops. This low-cost and automated high-throughput phenotyping technique utilizes artificial intelligence (AI) and machine learning (ML) to: (i) detect, count, and geolocate trees and tree gaps; (ii) categorize trees based on their canopy size; (iii) develop individual tree health indices; and (iv) evaluate citrus varieties and rootstocks. The proposed remote sensing technique was able to detect and count citrus trees in a grove of 4,931 trees, with precision and recall of 99.9% and 99.7%, respectively, estimate their canopy size with overall accuracy of 85.5%, and detect, count, and geolocate tree gaps with a precision and recall of 100% and 94.6%, respectively. This UAV-based technique provides a consistent, more direct, cost-effective, and rapid method to evaluate phenotypic characteristics of citrus varieties and rootstocks. Full article