Advancing Open Science

Complete mitochondrial genomes (mitogenomes) are widely utilized molecular resources for phylogenetic studies. Although research on Spariformes mitogenomes has advanced significantly, there is still relatively little information regarding the molecular data and taxonomic placement of the families Nemipteridae and Lethrinidae. We report and annotate the first complete mitogenomes of Pentapodus caninus (16,866 bp; Nemipteridae) and Lethrinus olivaceus (16,792 bp; Lethrinidae), thereby expanding mitogenomic coverage in two families with limited available genomic data. Both assembled mitogenomes display the canonical vertebrate architecture, comprising 37 functional genes (13 protein-coding genes, 22 tRNAs, and 2 rRNAs) and a control region, with conserved synteny and strand asymmetry (only ND6 and eight tRNAs are light-strand encoded). While ATG serves as the primary initiation codon for most PCGs, COX1 employs an alternative GTG start codon. Structural analysis of tRNAs revealed that most sequences adopt the standard cloverleaf conformation, with the exception of tRNA-Ser^AGY, which lacks the dihydrouridine (DHU) arm. A rare tandem duplication of tRNA-Val in Lethrinus species highlights the structural variability of spariform mitochondrial genomes. Furthermore, phylogenomic reconstruction using the concatenated 13 protein-coding gene dataset recovered Nemipteridae and Sparidae as sister taxa. In this topology, Lethrinidae was identified as the earliest diverging lineage, basal to the Nemipteridae–Sparidae grouping. Our results not only advance our understanding of the origin and evolution of Spariformes, but also provide valuable information for the molecular phylogeny and taxonomy of teleostean species.

Deep learning for fine-grained radar mode recognition faces a major bottleneck—its heavy reliance on expensively labeled data. To address this, we propose a novel semi-supervised framework that effectively leverages unlabeled data. Through an end-to-end, triple-branch framework that integrates a dual contrastive learning mechanism with tailored strategies for pulse distortions, our model achieves high accuracy with minimal labels. Experimental results on two challenging datasets demonstrate that the proposed framework boosts accuracy by 17% to 34% using only 10% of the labeled data, establishing a new state-of-the-art performance.

A 15-year-old female developed refractory Complex Regional Pain Syndrome (CRPS) Type I of the left hand following metacarpal fixation. Conservative therapy and hand rehabilitation failed, resulting in persistent allodynia and functional loss. She was admitted for multimodal analgesia combining subanesthetic ketamine infusion, gabapentin, and a tunneled supraclavicular continuous nerve catheter delivering ropivacaine. Pain decreased from 7/10 at rest to 0/10 within 48 h. Allodynia has resolved, and motor function has fully recovered. The catheter was removed nine days later without complication, and pain remission persisted. This case demonstrates a safe and effective multimodal strategy for adolescent CRPS integrating central and peripheral desensitization mechanisms.

Background/Objectives: This systematic review aimed to evaluate and summarize the available evidence on the effects of light-based applications, including laser irradiation on fibroblast responses to zirconia surfaces. Methods: A comprehensive electronic search was performed in PubMed, Scopus, Web of Science, Embase, and WorldCat databases. After duplicate removal and eligibility screening, 17 studies met the inclusion criteria. Only in vitro and animal studies assessing fibroblast behavior on zirconia after light- or laser-based surface irradiation were included. Due to heterogeneity in study designs and parameters, data were qualitatively synthesized. Results: All included studies confirmed the biocompatibility of laser-modified zirconia surfaces. Various laser systems—including Er:YAG, Er,Cr:YSGG, Nd:YAG, diode, excimer, and femtosecond lasers—were investigated. Most studies reported enhanced fibroblast adhesion, proliferation, and cytoskeletal organization compared with untreated controls. Two of the included studies demonstrated an antibacterial effect of erbium lasers treatment on zirconia surfaces. However, outcomes varied depending on the laser parameters, irradiation energy, and zirconia type used. Conclusions: Laser-based surface modification of zirconia appears safe and biocompatible, with evidence indicating favorable effects on fibroblast adhesion, proliferation, and organization. While these findings are promising for optimizing soft-tissue integration around zirconia implant abutments, further standardized and long-term studies are necessary to determine optimal laser settings and confirm clinical applicability.

The application of graph convolutional neural networks for traffic prediction is a standard procedure; however, this approach is rarely used under the assumption that the exact city plan is unknown and the prediction area is a city-sized region. This paper fills this gap by proposing and evaluating the Sample and Aggregate-Voronoi method (SAGE-Voronoi), which utilizes the novel concept of Voronoi Neighborhood Weighted Graph-based convolutional networks to predict car traffic in cities. It demonstrates the usefulness of this method for short-term predictions using real sensor data from the moderate-sized town of Darmstadt. The results obtained are compared with those of other neural network algorithms, namely pure Long Short-Term Memory, SAGE, Diffusion Convolutional Gated Recurrent Unit (DCGRU), and Spatio-Temporal Graph Convolutional Neural Network (STGCN). SAGE-Voronoi obtained significantly better results than the state-of-the-art approaches. The SAGE-Voronoi graph neural network enables the reliable prediction of varying car traffic among network nodes. The proposed approach is not limited to spatiotemporal traffic data and can be utilized in other similar domains. The source code and dataset used in our experiments are available for download, enabling full reproducibility of the results.

To address the challenges of low automatic leveling efficiency and insufficient control precision for small tracked operation chassis navigating uneven terrain in hilly and mountainous areas, this study proposes a leveling control system that integrates a dual-layer threshold strategy with a BP neural network algorithm. The system is developed based on a four-point lifting leveling mechanism. Building upon this foundation, the conventional single-threshold angle error compensation control strategy was optimized to meet the specific leveling demands of chassis operating in such complex environments. A co-simulation platform was established using Matlab/Simulink-AMEsim for subsequent simulation and comparative analysis. Simulation results demonstrate that the proposed method achieves a 15.6% improvement in leveling response speed and a 21.3% enhancement in leveling accuracy compared to the classical single-threshold PID control algorithm. Static test results reveal a smooth leveling process devoid of significant overshoot or hysteresis, with the leveling error consistently maintained within 0.5°. Field tests further indicate that at a travel speed of 3 km/h under a 50 kg load, the platform stabilization time is reduced by an average of 1.3 s, while the leveling angle error remains within 0.5°. The proposed system not only improves leveling response speed and precision but also effectively enhances the overall leveling efficiency of the tracked chassis system.

The extraction of antioxidant compounds from brown macroalgae is of growing industrial interest; however, the weak correlation often observed between polyphenol content and antioxidant activity challenges the conventional strategy of optimizing only extraction yield. This study introduces, for the first time in brown macroalgae, a functionality-driven optimization approach in which ultrasound-assisted extraction (UAE) conditions are optimized based on antioxidant activity as the primary response variable, rather than compound concentration. A green UAE process was developed and optimized for four edible brown algae (Himanthalia elongata, Eisenia bicyclis, Sargassum fusiforme, and Laminaria ochroleuca), considering algae amount, solvent type and concentration, extraction time, ultrasound power, and temperature. The optimized extracts achieved 69.17–94.68% DPPH inhibition, together with high antioxidant capacity supported by ORAC (18.63–491.30 μmol TE g⁻¹ DW) and FRAP (1.24–87.65 µmol Fe⁺² g⁻¹ DW) values, identifying E. bicyclis and H. elongata as the most promising species. Chromatographic analyses confirmed the presence of phlorotannins and carotenoid pigments such as fucoxanthin as the main contributors to antioxidant activity. Overall, this work validates a functionality-driven UAE optimization strategy for efficiently maximizing antioxidant activity in brown algal extracts.

In recent years, Polish producers have been increasingly interested in organic fruit production. In this cultivation system, it is very important to choose cultivars that are less susceptible to diseases and pests. In research conducted in the years 2009–2019 in central Poland, the suitability of four sour cherry cultivars (‘Kelleris 16’, ‘Oblacinska’, ‘Debreceni Bötermö’, ‘Pandy 103’) for organic cultivation was assessed. The trees grew in two separate experimental quarters: conventional and organic, about 1 km apart. It was proved that organic sour cherry cultivation is possible, but there are many challenges. In the organic cultivation system, trees were more sensitive to low temperatures and grew and yielded less than those grown using conventional methods. The weaker growth and lower yields were mainly due to the ineffective protection against cherry leaf spot and brown rot. The fruit quality was closely dependent on the weather conditions. The fruit harvested in the organic orchard had a lower weight but tended to be firmer than that harvested in the conventional one. The smallest, but most abundant in soluble solids, were the fruits of the ‘Oblacinska’ cultivar. Unfortunately, they were infested by larvae of cherry fruit flies. Occasionally, the pest larvae lived in organic sour cherries of the ‘Pandy 103’ and ‘Debreceni Bötermö’ cultivars. In years with high rainfall, 20 to 35% of the fruit in the organic quarter was affected by fungal diseases.