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In order to solve the problems of low tensile strength of composite mortar prone to cracking when reinforced concrete beams are strengthened by traditional methods, this paper proposes a new polyurethane concrete–prestressing wire (PUC–PSW) reinforcement method using polyurethane concrete (PUC) as the wire embedding material. Twelve reinforced concrete T-beams were tested for PUC–PSW flexural reinforcement. These consisted of one unreinforced beam, four PSW-reinforced beams and seven PUC–PSW-reinforced beams. The wire embedding material, wire anchorage form, PUC material depth, amount of wire and loading type were used as variables. The test results show that PUC–PSW reinforcement can significantly increase the yield load and ultimate load of the reinforced beams by 24.1% and 44.6%, respectively, compared with PSW reinforcement. When the load reached 90 kN, the crack widths of PSW-reinforced beam A2 and PUC–PSW-reinforced beam A8 were 0.17 mm and 0.1 mm, respectively. The ability of PUC–PSW reinforcement to limit crack development is better than that of PSW reinforcement, especially after the main beam steel yield. The strength, stiffness and crack-limiting ability of the reinforced beam increase with the PUC thickness of the reinforced layer.

Atomic scale computer simulations based on density functional theory (DFT) are used to calculate the formation energies and structures associated with phases in the U–N, Pu–N, U–C and Pu–C systems. Stable phases across the compositional spaces, from the metal to the nitrogen gas or graphite end members, are identified using convex hull analysis. Many predicted phases correspond to those known from experimental phase diagrams (e.g. UN, U 2 N 3 ; PuN; UC, U 2 C 3 ; Pu 2 C 3 ). However, many phases only sit on the convex hull upon inclusion of a suitably characterised Hubbard parameter (i.e. DFT + U). A nonstoichiometric composition of UN 2−x is identified on the U–N convex hull but others, including stoichiometric UN 2 , are close to the line. A stoichiometric structure for Pu 3 C 2 with symmetry is identified, alongside which a nonstoichiometric PuC 1−x phase has a similar energy.

In this study, a novel comparison between single phase 7-Level Packed U—Cell (PUC) inverter and single phase 9-Level Cross Switches Cell (CSC) inverter with Model Predictive Controller (MPC) for solar grid-tied applications is presented. Our innovation introduces a unique approach by integrating PV solar panels in PUC and CSC inverters in their two DC links rather than just one which increases power density of the system. Another key benefit for the proposed models lies in their simplified design, offering improved power quality and reduced complexity relative to traditional configurations. Moreover, both models feature streamlined control architectures that eliminate the need for additional controllers such as PI controllers for grid reference current extraction. Furthermore, the implementation of Maximum Power Point Tracking (MPPT) technology directly optimizes power output from the PV panels, negating the necessity for a DC-DC booster converter during integration. To validate the proposed concept’s performance for both inverters, extensive simulations were conducted using MATLAB/Simulink, assessing both inverters under steady-state conditions as well as various disturbances to evaluate its robustness and dynamic response. Both inverters exhibit robustness against variations in grid voltage, phase shift, and irradiation. By comparing both inverters, results demonstrate that the CSC inverter exhibits superior performance due to its booster feature which relies on generating voltage level greater than the DC input source. This primary advantage makes CSC a booster inverter.

The tuning of weighting factor has been considered as the most challenging task in the implementation of multi-objective model predictive control (MPC) techniques. Thus, this paper proposes an artificial intelligence (AI)-based weighting factor autotuning in the design of a finite control set MPC (FCS-MPC) applied to a grid-tied seven-level packed U-cell (PUC7) multilevel inverter (MLI). The studied topology is capable of producing a seven-level output voltage waveform and inject sinusoidal current to the grid with high power quality while using a reduced number of components. The proposed cost function optimization algorithm ensures auto-adjustment of the weighting factor to guarantee low injected grid current total harmonic distortion (THD) at different power ratings while balancing the capacitor voltage. The optimal weighting factor value is selected at each sampling time to guarantee a stable operation of the PUC inverter with high power quality. The weighting factor selection is performed using an artificial neural network (ANN) based on the measured injected grid current. Simulation and experimental results are presented to show the high performance of the proposed strategy in handling multi-objective control problems.

The mechanisms and consequences of gene regulation by Hfq on trans-encoded small RNAs (sRNAs) have been well studied and documented. Recent employment of Genomic SELEX to search for Hfq-binding motifs has indicated that Hfq might frequently regulate gene expression controlled by cis-antisense RNAs. Here, we use the classic ColE1 plasmid antisense RNA-based regulation model (i.e., RNA I) to study the role of Hfq in controlling antisense regulatory functions. We show that Hfq exhibits a high binding affinity for RNA I and that binding limits RNase E cleavage, thereby stabilizing RNA I and reducing the plasmid copy number. Full-length RNA I displays a binding affinity for Hfq in the sub-micromolar range. In vivo overexpression of Hfq prolongs RNA I stability and reduces the ColE1 plasmid copy number, whereas deletion of hfq reduces RNA I stability and increases the plasmid copy number. RNA I predominantly binds to the proximal face of Hfq and exhibits competitive ability against a chromosome-borne proximal face-bound sRNA (DsrA) for Hfq binding. Through its strong promoter and high gene dosage features, plasmid-encoded antisense RNA I results in high RNA I expression, so it may antagonize the effects of trans-encoded RNAs in controlling target gene expression.

Ufmylation is a recently identified small ubiquitin-like modification, whose biological function and relevant cellular targets are poorly understood. Here we present evidence of a neuroprotective role for Ufmylation involving Autophagy-related gene 9 (Atg9) during Drosophila aging. The Ufm1 system ensures the health of aged neurons via Atg9 by coordinating autophagy and mTORC1, and maintaining mitochondrial homeostasis and JNK (c-Jun N-terminal kinase) activity. Neuron-specific expression of Atg9 suppresses the age-associated movement defect and lethality caused by loss of Ufmylation. Furthermore, Atg9 is identified as a conserved target of Ufm1 conjugation mediated by Ddrgk1, a critical regulator of Ufmylation. Mammalian Ddrgk1 was shown to be indispensable for the stability of endogenous Atg9A protein in mouse embryonic fibroblast (MEF) cells. Taken together, our findings might have important implications for neurodegenerative diseases in mammals.

In order to improve the seismic performance of reinforced concrete (RC) columns, a reinforcement technology using prestressed steel wire ropes embedded in polyurethane cement composite material is proposed. Four concrete columns reinforced with different materials were subjected to a combination of axial compression and horizontally repeated loading tests (one of which was not reinforced, while the remaining three were reinforced with prestressed steel wire rope, polyurethane cement composite material, and prestressed steel wire ropes embedded in polyurethane cement composite material). The experimental results show that the ductility and energy dissipation capacity of reinforced concrete columns after reinforcement are significantly improved. After strengthening with prestressed steel wire ropes embedded in polyurethane cement composite material, the ultimate horizontal displacement and energy dissipation capacity of reinforced concrete columns were significantly improved, which were 69% and 3.2 times higher than those of unreinforced columns, respectively.

Since multicarrier based modulation techniques are simple to implement and can be used to control inverters at any level, they are frequently employed in modern multilevel inverters in high or medium power applications. When considering the many multi-carrier modulation techniques available, level-shifted pulse-width modulation (LSPWM) is often chosen for its superior harmonic performance. However, this traditional LSPWM method is not suitable for controlling newly proposed reduced switch count (RSC) MLI topologies. The research work in this paper seeks to elucidate the reasons why conventional LSPWM is ineffective in controlling RSC MLI topologies, and proposes a generalized LSPWM system based on logical expressions. The proposed method can be utilized with symmetrical and asymmetrical RSC MLIs, and can be extended to an arbitrary number of levels. The merit of the proposed method for controlling any RSC configuration with satisfactory line-voltage THD (≈1.8%) performance (identical to conventional LSPWM) was evaluated using multiple 13-level asymmetrical RSC-MLI topologies. A MATLAB model was developed and then subjected to simulation and real-world testing to prove the effectiveness of the proposed modulation strategy.

Multi-parent advanced generation inter-cross (MAGIC) populations facilitate the genetic dissection of complex quantitative traits in plants and are valuable breeding materials. We report the development of the first eggplant MAGIC population (S3 Magic EGGplant InCanum, S3MEGGIC; 8-way), constituted by the 420 S3 individuals developed from the intercrossing of seven cultivated eggplant ( Solanum melongena ) and one wild relative ( S. incanum ) parents. The S3MEGGIC recombinant population was genotyped with the eggplant 5k probes SPET platform and phenotyped for anthocyanin presence in vegetative plant tissues (PA) and fruit epidermis (FA), and for the light-insensitive anthocyanic pigmentation under the calyx (PUC). The 7,724 filtered high-confidence single-nucleotide polymorphisms (SNPs) confirmed a low residual heterozygosity (6.87%), a lack of genetic structure in the S3MEGGIC population, and no differentiation among subpopulations carrying a cultivated or wild cytoplasm. Inference of haplotype blocks of the nuclear genome revealed an unbalanced representation of the founder genomes, suggesting a cryptic selection in favour or against specific parental genomes. Genome-wide association study (GWAS) analysis for PA, FA, and PUC detected strong associations with two myeloblastosis (MYB) genes similar to MYB113 involved in the anthocyanin biosynthesis pathway, and with a COP1 gene which encodes for a photo-regulatory protein and may be responsible for the PUC trait. Evidence was found of a duplication of an ancestral MYB113 gene with a translocation from chromosome 10 to chromosome 1 compared with the tomato genome. Parental genotypes for the three genes were in agreement with the identification of the candidate genes performed in the S3MEGGIC population. Our new eggplant MAGIC population is the largest recombinant population in eggplant and is a powerful tool for eggplant genetics and breeding studies.

Changing hydrological conditions due to climate, land use and infrastructure pose significant ongoing challenges to the hydrological research and water management communities. While, traditionally, hydrological models have assumed stationary conditions, there has been much progress since 2005 on model parameter estimation under unknown or changed conditions and on techniques for modelling in those conditions. There is an analogy between extrapolation in space (termed Prediction in Ungauged Basins, PUB), and extrapolation in time (termed Prediction in Ungauged Climates, PUC) that can be exploited for estimating model parameters. Methods for modelling changing hydrological conditions need to progress beyond the current scenario approach, which is reliant upon precalibrated models. Top-down methods and analysis of spatial gradients of a variable of interest, instead of temporal gradients (a method termed ‘Trading space for time’) show much promise for validating more complex model projections. Understanding hydrological processes and how they respond to change, along with quantification of parameter estimation and modelling process uncertainty will continue to be active areas of research within hydrology. Contributions from these areas will not only help inform future climate change impact studies about what will change and by how much, but also provide insight into why any changes may occur, what changes we are able to predict in a realistic manner, and what changes are beyond the current predictability of hydrological systems.