Miracle-dz/UniFAR-FTUs huggingface dataset:
Electricity Pricing and Its Role in Modern Smart Energy System Design: A Review

Energy is the foundation for human survival and socio-economic development, and electricity is a key form of energy. Electricity prices are a key factor affecting the interests of various stakeholders in the electricity market, playing a significant role in the sustainable development of energy and the environment. As the number of distributed energy resources (DERs) increases, today’s power systems no longer rely on a vertical market model and fixed electricity pricing scheme but instead depend on power dispatch and dynamic pricing to match supply and demand. This can help prevent significant fluctuations in supply–load imbalance and maintain system stability. Modern power grids have evolved by integrating information, communication, and intelligent control technologies with traditional power systems, giving rise to the concept of smart electric grids. Choosing an appropriate pricing scheme to manage large-scale DERs and controllable loads in today’s power grid become very important. However, the existing literature lacks a comprehensive review of electricity pricing in power systems and its transformative impact on shaping the energy landscape. To fill this void, this paper provides a survey on the developments, methods, and frameworks related to electricity pricing and energy trading. The review mainly considers the development of pricing in a centralized power grid, peer-to-peer (P2P) and microgrid-to-microgrid (M2M) energy trading and sharing, and various pricing methods. The review will cover the pricing schemes in modern power systems, particularly with respect to renewable energy sources (RESs) and batteries, as well as controllable load applications, and the impact of pricing schemes based on demand-side ancillary services (DSAS) for grid frequency support. Lastly, this review article describes the current frameworks and limitations of electricity pricing in the current energy market, as well as future research directions. This review should offer a great overview and deep insights into today’s electricity market and how pricing methods will drive and facilitate the future establishment of smart energy systems.
In Silico Study to Evaluate the Inhibitory Activity of a Few Phenylethanoid Glycosides on GSK3-β Protein for Faster Diabetic Wound Healing

: Chronic wound resulting from diabetes mellitus is a signiﬁcant cause of amputation world-wide. Secondary infections, lowering of nitric oxide synthase level, reduction of glucose-6-phosphate dehydrogenase levels, improper extracellular matrix remodelling, neuropathy, abnormality of endothelial cell function, and vasculopathy impedes the normal wound healing cycle during diabetes. Multiple studies have concluded that Ser9 phosphorylation causes inhibition of the glycogen synthase kinase-3 β (GSK3-β ) protein, which is essential for faster diabetic wound healing. Hence this protein could be a potential target for molecular interactions with prospective wound-healing molecules. Verbascoside, martynoside, echinacoside, crenatoside, and salidroside are a few phenylethanoid glycosides that have potential wound-healing ability by increasing extracellular matrix synthesis, angiogenesis, keratinocyte migration, and the functioning of macrophages and neutrophils. Thus, the ﬁve glycosides were subjected to molecular docking with GSK3-β protein (PDB ID: 1I09). This study revealed strong binding interactions with GSK3-β (between − 10.2 and − 7.3 kcal/mol) and inhibition constants (between 0.032 and 4.397 µ M) which suggested potent inhibition of the target protein even at lower concentrations of these compounds. Further, the docked complexes were visualized to ﬁnd the interaction of the ligands with the amino acid residues. However, further in vivo and in vitro studies are required to validate the activity of these phenylpropanoid glycosides in diabetic wound healing.
Production of Polyhydroxybutyrate by Genetically Modified Pseudomonas sp. phDV1: A Comparative Study of Utilizing Wine Industry Waste as a Carbon Source

Pseudomonas sp. phDV1 is a polyhydroxyalkanoate (PHA) producer. The presence of the endogenous PHA depolymerase (phaZ) responsible for the degradation of the intracellular PHA is one of the main shortages in the bacterial production of PHA. Further, the production of PHA can be affected by the regulatory protein phaR, which is important in accumulating different PHA-associated proteins. PHA depolymerase phaZ and phaR knockout mutants of Pseudomonas sp. phDV1 were successfully constructed. We investigate the PHA production from 4.25 mM phenol and grape pomace of the mutants and the wild type. The production was screened by fluorescence microscopy, and the PHA production was quantified by HPLC chromatography. The PHA is composed of Polydroxybutyrate (PHB), as confirmed by 1H-nuclear magnetic resonance analysis. The wildtype strain produces approximately 280 μg PHB after 48 h in grape pomace, while the phaZ knockout mutant produces 310 μg PHB after 72 h in the presence of phenol per gram of cells, respectively. The ability of the phaZ mutant to synthesize high levels of PHB in the presence of monocyclic aromatic compounds may open the possibility of reducing the costs of industrial PHB production.
A Hierarchical Control Scheme for Adaptive Cruise Control System Based on Model Predictive Control

An adaptive cruise control (ACC) system can improve safety and comfort during driving by taking over longitudinal control of the vehicle. It requires the coordination between the upper-layer controller and the lower-layer actuators. In this paper, a hierarchical anti-disturbance cruise control architecture based on electronic stability control (ESC) system is proposed. The upper-layer controller outputs the desired longitudinal acceleration or deceleration to the lower-layer actuators. In order to improve the accuracy of model prediction and achieve the coordinated control of multiple objectives, an upper-layer model prediction cruise controller is established based on feedback control and disturbance compensation. In addition, based on the hydraulic control unit (HCU) model and the vehicle longitudinal dynamics model, a lower-layer nonlinear model predictive deceleration controller is proposed in order to solve the problems of pressure fluctuations and the low accuracy of small decelerations when ESC is used as the actuator for the ACC system. Finally, the simulation and experimental tests were carried out. The results show that the proposed control architecture can improve the stability and comfort of the cruise control process. Moreover, compared with the traditional PID deceleration controller, it effectively improves the deceleration control accuracy.
Axion term in topological insulators with broken time reversal and parity

The main subject of this work is the axion term in the effective electromagnetic action of topological insulators, which is responsible for the special electromagnetic properties of these materials. The axion term is characterized by a parameter θ, which can only take the values of 0, for regular insulators, or π, for topological insulators, respecting at least one of the time reversal or parity symmetries. A non zero axion term leads to a variety of measurable phenomena, generally referred to as the magneto-electric effects. We focus our interest on the value the parameter θ takes for a topological insulator, when both time reversal and parity are broken. In this case θ no longer must be quantized to 0 or π. We use a lattice model for a topological insulator, and introduce a symmetry breaking term in the Hamiltonian. We numerically find the value of θ in this case using calculations of the magnitude of various magneto-electric effects. The results are compared to the theoretical prediction. We find that θ is no longer quantized when a specific symmetry breaking term is introduced.
Segmentation of 4D Flow MRI: Comparison between 3D Deep Learning and Velocity-Based Level Sets

A thoracic aortic aneurysm is an abnormal dilatation of the aorta that can progress and lead to rupture. The decision to conduct surgery is made by considering the maximum diameter, but it is now well known that this metric alone is not completely reliable. The advent of 4D flow magnetic resonance imaging has allowed for the calculation of new biomarkers for the study of aortic diseases, such as wall shear stress. However, the calculation of these biomarkers requires the precise segmentation of the aorta during all phases of the cardiac cycle. The objective of this work was to compare two different methods for automatically segmenting the thoracic aorta in the systolic phase using 4D flow MRI. The first method is based on a level set framework and uses the velocity field in addition to 3D phase contrast magnetic resonance imaging. The second method is a U-Net-like approach that is only applied to magnitude images from 4D flow MRI. The used dataset was composed of 36 exams from different patients, with ground truth data for the systolic phase of the cardiac cycle. The comparison was performed based on selected metrics, such as the Dice similarity coefficient (DSC) and Hausdorf distance (HD), for the whole aorta and also three aortic regions. Wall shear stress was also assessed and the maximum wall shear stress values were used for comparison. The U-Net-based approach provided statistically better results for the 3D segmentation of the aorta, with a DSC of 0.92 ± 0.02 vs. 0.86 ± 0.5 and an HD of 21.49 ± 24.8 mm vs. 35.79 ± 31.33 mm for the whole aorta. The absolute difference between the wall shear stress and ground truth slightly favored the level set method, but not significantly (0.754 ± 1.07 Pa vs. 0.737 ± 0.79 Pa). The results showed that the deep learning-based method should be considered for the segmentation of all time steps in order to evaluate biomarkers based on 4D flow MRI.
The Introduction of Detergents in Thermal Proteome Profiling Requires Lowering the Applied Temperatures for Efficient Target Protein Identification

Although the use of detergents in thermal proteome profiling (TPP) has become a common practice to identify membrane protein targets in complex biological samples, surprisingly, there is no proteome-wide investigation into the impacts of detergent introduction on the target identification performance of TPP. In this study, we assessed the target identification performance of TPP in the presence of a commonly used non-ionic detergent or a zwitterionic detergent using a pan-kinase inhibitor staurosporine, our results showed that the addition of either of these detergents significantly impaired the identification performance of TPP at the optimal temperature for soluble target protein identification. Further investigation showed that detergents destabilized the proteome and increased protein precipitation. By lowering the applied temperature point, the target identification performance of TPP with detergents is significantly improved and is comparable to that in the absence of detergents. Our findings provide valuable insight into how to select the appropriate temperature range when detergents are used in TPP. In addition, our results also suggest that the combination of detergent and heat may serve as a novel precipitation-inducing force that can be applied for target protein identification.
Chromosomal Aberration t(14;17)(q32;q21) Simultaneously Activates HOXB5 and miR10a in Triple-Hit B-Cell Lymphoma

BCL2, BCL6 and MYC are major oncogenes in B-cell lymphoma. Their aberrant activation frequently occurs via chromosomal translocations which juxtapose light or heavy chain immunoglobulin (IG) genes to BCL2 and MYC or fuse diverse partner genes with BCL6. So-called double-hit lymphomas usually carry BCL2 and MYC rearrangements, while triple-hit lymphomas additionally bear BCL6-fusions. All these translocations are of diagnostic relevance and usually denote poor prognosis. Here, we genomically characterized classic follicular lymphoma (FL) cell line SC-1, thereby identifying t(14;18)(q32;q21) juxtaposing IGH and BCL2, t(8;14)(q24;q32) juxtaposing IGH and MYC, and t(3;3)(q25;q27) fusing MBNL1 to BCL6. In addition, we found that SC-1 carries a novel chromosomal rearrangement, t(14;17)(q32;q21), which, though present at establishment, has remained unreported until now. We further show that t(14;17)(q32;q21) juxtaposes IGH with the HOXB gene cluster at 17q21 and affect the oncogenic activation of both homeobox gene HOXB5 and neighboring micro-RNA gene miR10a. Moreover, we detected aberrant overexpression of HOXB5 in subsets of Burkitt lymphoma, FL, and multiple myeloma patients, confirming the clinical relevance of its deregulation. In SC-1, HOXB5 activation was additionally supported by co-expression of hematopoietic stem cell factor ZNF521, indicating an aberrant impact in cell differentiation. Functional investigations showed that HOXB5 represses the apoptotic driver BCL2L11 and promotes survival in the presence of etoposide, and that miR10a inhibits BCL6 and may thus play an oncogenic role in later stages of lymphomagenesis. Collectively, we characterize triple-hit B-cell line SC-1 and identify the aberrant expression of HOXB5 and miR10a, both novel oncogenes in B-cell lymphoma.
High Buffering Potential of Winter Wheat Composite Cross Populations to Rapidly Changing Environmental Conditions

: A winter wheat composite cross population (CCP), created in the UK in 2001, has been grown in Germany, Hungary, and the UK since 2005 (F 5 generation). In 2008/09 (F 8 ), a cycling pattern for the populations was developed between partners to test the effects of rapidly changing environments on agronomic performance and morphological characteristics. One CCP was grown by eight partners for one year and subsequently sent to the next partner, creating “cycling CCPs” with different histories. In 2013, all eight cycling CCPs and the three non-cycling CCPs (from Germany, Hungary, and the UK) were included in a two-year experiment in Germany with three line varieties as references. Differing seed weights of the F 13 at sowing affected some agronomic parameters under drought conditions in 2014/15 but not under less stressful conditions in 2013/14. In both experimental years, the CCPs were comparable to the line varieties in terms of agronomic performance, with some CCPs yielding more than the varieties under the drought conditions of 2015. The results highlight the potential of CCPs to compete with line varieties, while the overall similarity of the CCPs based on their origin and cycling history for agronomic traits indicates a high buffering potential under highly variable environmental conditions.
RSSI and Device Pose Fusion for Fingerprinting-Based Indoor Smartphone Localization Systems

: Complementing RSSI measurements at anchors with onboard smartphone accelerometer measurements is a popular research direction to improve the accuracy of indoor localization systems. This can be performed at different levels; for example, many studies have used pedestrian dead reckoning (PDR) and a ﬁltering method at the algorithm level for sensor fusion. In this study, a novel conceptual framework was developed and applied at the data level that ﬁrst utilizes accelerometer measurements to classify the smartphone’s device pose and then combines this with RSSI measurements. The framework was explored using neural networks with room-scale experimental data obtained from a Bluetooth low-energy (BLE) setup. Consistent accuracy improvement was obtained for the output localization classes (zones), with an average overall accuracy improvement of 10.7 percentage points for the RSSI-and-device-pose framework over that of RSSI-only localization.
Experimental Investigation and Modeling of Force-Induced Surface Errors for the Robot-Assisted Milling Process

A series of experiments were performed aiming at controlling milling force-induced surface errors in the robot-assisted milling process, for the sub-area of the multi-stiffener reinforced inner wall of complex cylindrical thin-walled casting parts, to investigate the relationship between surface errors, milling forces, and robot-assisted milling parameters. Firstly, based on the design of experiments (DoE) method, milling forces and surface errors were investigated based on a series of experiments with different groups of milling parameters. Secondly, the modeling of milling forces, surface errors, and milling parameters was realized by means of response surface methodology (RSM), then the parametric expression was obtained of the robot-assisted milling process. Finally, the parameters of the milling process toward the surface error were obtained based on an evolutionary algorithm. The results show that the surface errors are different for the different milling styles of down milling and up milling. In up milling processes, the surface errors are positive, and the actual material removal amounts are generally higher than the nominal ones, while negative in down milling processes. The surface errors induced by milling forces can be effectively controlled and reduced using process optimization in the robot-assisted milling process, while maintaining relatively high milling forces and high machining efficiency. This provides theoretical support for industry applications.
Estimating the Impact of Consecutive Blood Meals on Vector Competence of Aedes albopictus for Chikungunya Virus

The continuous expansion of Aedes albopictus in Europe and the increases in autochthonous arboviruses transmissions in the region urge a better understanding of the virus transmission dynamic. Recent work described enhanced chikungunya virus (CHIKV) dissemination in Aedes aegypti mosquitoes exposed to a virus-free blood meal three days after their infection with CHIKV. Our study investigated the impact of a second blood meal on the vector competence of Ae. albopictus from southern Switzerland infected with CHIKV. Seven-day-old Ae. albopictus females were exposed to CHIKV-spiked blood and incubated at constant (27 °C) and fluctuating (14–28 °C) temperatures. Four days post-infection (dpi), some of these females were re-fed with a non-infectious blood meal. Virus infectivity, dissemination, transmission rate, and efficiency were investigated at seven and ten dpi. No enhanced dissemination rate was observed among females fed a second time; however, re-fed females have shown higher transmission efficiency than those fed only once after seven days post-infection and incubated under a fluctuating temperature regime. Vector competence for CHIKV was confirmed in Ae. albopictus from southern Switzerland. We did not observe an increase in dissemination rates among mosquitoes fed a second time (second blood meal), regardless of the temperature regime.
Latent Regression Analysis Considering Student, Teacher, and Parent Variables and Their Relationship with Academic Performance in Primary School Students in Chile

Academic performance in primary students is fundamental to future school success; however, simultaneous analysis of different key individual, family, and teaching factors must be considered to improve understanding and benefit the development of students’ potential. This article presents a latent regression analysis model that examines the relationship between the latent variables (self-efficacy, interest in reading, bullying, parental expectations, and discrimination/exclusion, and teacher violence/aggression) and the academic performance of first-cycle primary students. The model investigates the impact of the latent variables on the standardized endogenous variables of SIMCE Mathematics and Language test scores using a quantitative, non-experimental, correlational, and cross-sectional design. The study involved 70,778 students (53.4% female), with an average age of 9.5 years (SD = 0.6), from Chilean public (33.6%) and subsidized (66.4%) schools. The results indicate that the model accounted for 49.8% and 47.7% of the mean variability in SIMCE Mathematics and Language test scores, respectively. The goodness-of-fit indices demonstrated satisfactory fits for both models. In both tests, student self-efficacy emerged as the most significant factor explaining test score variability, followed by parental expectations. Bullying was identified as a relevant factor in reducing mean performance on both tests. The findings suggest that education decision makers should address these issues to improve student outcomes.
Antagonistic Interactions of Lactic Acid Bacteria from Human Oral Microbiome against Streptococcus mutans and Candida albicans

Oral probiotic lactic acid bacteria can exhibit antagonistic activities against pathogens associated with diseases in the oral cavity. Therefore, twelve previously isolated oral strains were assessed for antagonistic evaluation against selected oral test microorganisms Streptococcus mutans and Candida albicans. Two separate co-culturing analyses were performed, where all tested strains showed the presence of antagonistic activity and four strains, Limosilactobacillus fermentum N 2, TC 3-11, and NA 2-2, and Weissella confusa NN 1, significantly inhibited Streptococcus mutans by 3–5 logs. The strains showed antagonistic activity against Candida albicans, and all exhibited pathogen inhibition by up to 2 logs. Co-aggregation capability was assessed, showing co-aggregative properties with the selected pathogens. Biofilm formation and antibiofilm activity of the tested strains against the oral pathogens were assayed, where the strains showed specificity in self-biofilm formation and well-expressed antibiofilm properties by most of them above 79% and 50% against Streptococcus mutans and Candida albicans, respectively. The tested LAB strains were assayed by a KMnO4 antioxidant bioassay, where most of the native cell-free supernatants exhibited total antioxidant capacity. These results show that five tested strains are promising candidates to be included in new functional probiotic products for oral healthcare.
F2 Laser-Induced Micro-Reticulated Structural Changes of Amorphous Carbon Thin Films

Micro/nanoprocessing of materials using lasers is currently an active research topic. In that research, the choice of the laser to be used is critical, but the F2 laser, which has the shortest wavelength (157 nm) among commercially available lasers, has few research compared to its potential. In this paper, we discovered a new photochemical processing by using an F2 laser to irradiate an amorphous carbon thin film. The short wavelength and high photon energy of the F2 laser can photoexcite the surface of the thin film at high density and generate active oxygen atoms O(1D) by photodecomposition of atmospheric oxygen molecules. As a result, the optical change of the amorphous carbon thin film was induced without thickness reduction, and a micron-sized network-like, reticulated structural change was formed in the thin film surface after one month at the latest. The formed micron-sized reticulated structure was relatively swollen, and a graphitization occurred in the structure, observed by Raman spectroscopy. However, the structure was not observed when the laser irradiated area became smaller. This work has made it possible to form a micron-sized reticulated structure including carbon nanocrystals in an amorphous carbon, which is expected to further expand the applications of carbon materials.