Mixed-valence complexes featuring lanthanide-lanthanide bonding have recently been shown to act as single-molecule magnets with unprecedented operating temperatures and magnetic coercivities. Here, we present the synthesis and detailed examination of the electronic structure, bonding, and magnetic properties of mixed-valence trinuclear clusters (C5iPr5)3Ln3H3I2 (Ln = Tb, Dy, Ho, Er, and Tm). Near-infrared and X-ray absorption spectra, together with computational results, confirm these clusters possess a three-center, one-electron σ bond. This metal-metal bonding leads to strong intermetal exchange coupling, resulting in magnetic behaviors that starkly contrast with typical multinuclear lanthanide complexes. Notably, structural, spectroscopic, and computational studies of the thulium cluster reveal valence delocalization through a bonding orbital of 5d-parentage between the three Tm centers. This observation represents the first example of a nontraditional electronic structure for thulium involving 5d rather than 4f orbitals. Magnetic analysis reveals a complex interplay between single-ion magnetic anisotropy and ferromagnetic exchange, governing the overall magnetic anisotropy of these clusters. Magnetic susceptibility measurements for Ln = Tb-Er indicate thermally well-isolated high-moment ground states arising from strong magnetic coupling, although the maximum values are lower than those expected for complete parallel alignment of the σ and 4f electrons. Computational analyses suggest that collinear alignment of the local anisotropy axes results in out-of-plane anisotropy for Ln = Er and Tm, whereas noncollinear alignment induces in-plane anisotropy for Ln = Tb, Dy, leading to distinct magnetic relaxation properties. Together, the results highlight the diverse magnetic behaviors that can be realized through lanthanide-lanthanide bonding and outline a synthetic path forward toward maximizing the magnetic anisotropy in f-element clusters.

The Replication Protein A (RPA) is a highly conserved heterotrimeric complex that binds single-stranded DNA and interacts with multiple proteins, playing essential roles in DNA replication, repair, and homologous recombination, thereby maintaining genome stability and supporting normal development. However, the specific members and functions of the RPA gene family remain uncharacterized in maize. In this study, 13 ZmRPA members in maize were identified, which exhibited a wide range of protein lengths, from 86 to 876 amino acids. A phylogenetic analysis of these ZmRPA genes revealed their classification into three distinct subgroups: RPA1, RPA2, and RPA3. Notably, within each subgroup, the motifs of ZmRPA proteins were similar, although variations were observed among different subfamilies. An analysis of gene duplication events suggests that RPA genes have remained highly conserved in maize. Furthermore, the analysis of cis-elements indicated that RPA genes are associated with light-responsive, as well as plant growth and development. RNA-seq analysis revealed that some ZmRPA genes exhibited pronounced expression changes under cold and drought stresses, while the results of tissue-specific expression analysis showed that most ZmRPA genes were highly expressed in the actively dividing meristems and reproductive primordia. Protein interaction and yeast two-hybrid assays revealed that ZmRPA family members interact with each other to perform their biological functions. Collectively, these findings suggest that ZmRPA family subunits may play important roles in plant growth and development, as well as stress responses, by forming various types of heteromeric complexes through protein interactions. This study provides a comprehensive understanding of the RPA gene family in maize and will facilitate further effective characterization of the RPA genes.

Fractionalization of the electron charge e is one of the most striking phenomena arising from strong electron-electron interactions. A celebrated example is the emergence of anyons with fractional charges in fractional quantum Hall effect (FQHE) states1-13. Recently, zero-field fractional Chern insulators (FCIs)14-19, lattice analogues of the FQHE states that form without Landau levels, have been realized20,21. FCIs provide a unique platform to investigate anyons, yet their detection remains a challenge. Here we report the observation of anyon-trions, a new type of excitonic complex formed by binding a trion with a fractional charge in twisted MoTe2 bilayers. Photoluminescence spectroscopy of quantum-confined excitons reveals emergent peaks that appear only within slightly doped FCI states. The new spectral features are red-shifted relative to the trions in undoped FCIs, but share the same electric field, temperature and magnetic field dependence. These observations suggest their origin as trions binding with elementary quasi-particles, that is, anyon-trions. Crucially, the ratio of binding energies between the anyon-trions in the -2/3 and -3/5 FCI states matches the expected fractional charge ratio of e/3 to e/5. This provides strong evidence for fractional charges in FCI-an essential property of anyons. Our results address a fundamental question in FCI physics and establish trion spectroscopy as a powerful probe of fractionally charged excitations, complementary to transport- and tunnelling-based approaches.

Target Vessel and Mid-term Outcomes after Endovascular Repair of Complex Abdominal and Type IV Thoracoabdominal Aortic Aneurysms Using TAMBE vs t-Branch Devices

Introduction. This article is devoted to the study of psychological problems in communication and communication in addicted youth. The introduction presents the main manifestations and etiological principles of the emergence of preconditions for the formation of addictive behavior. The tendency to actualize the study of deviant behavior as a marker of the most complex types of psychological aspects related to adaptation in society and search for oneself is analyzed. The data obtained can form a psychotechnological form of solving communication problems. Furthermore, the research model conducted research can become a reliable type of screening research of predictors of the manifestation of addiction in young people. Objective. Find the main predictors of psychological problems in communication in addicted youth. Methods and Research. As a study, the objective of the investigation was 15 people: girls and men aged 18-35 years, living in the territory of the Ural Federal District, staying in the Center for Social Adaptation of the Sverdlovsk region. To realize the purpose of the study, such methods as "The questionnaire of dysfunctional beliefs in borderline personality disorder PBQ-BPD" and "IAF autonomous functioning index" were applied. As a statistical processing of data, Pearson's χ2 criterion of difference between two or more relative indices was used. Results. Differences in indicators were found, which confirms a high degree of distrust and defense in young people. The indicators of dependence did not reveal the degree of relevance, while high levels of authorship, interest, and susceptibility to control may be indicators of problems in communication and the manifestation of dependent behavior as a consequence of forms of communication. Discussion. The results obtained allow us to highlight the main causes of psychological problems in addicted youth. Programs operating in the centers of social adaptation lose their effectiveness, which is worth considering, focusing on the erroneous, distorted representation of adaptation for young people.

Dairy products contain complex types and contents of proteins, lipids, and lactose. The Maillard reaction (MR) occurs between proteins and reducing sugars during the processing and storage of dairy products. Maillard reaction products (MRPs) have garnered attention for their potential antioxidant activity. MRPs include melanoidins, reductones, and volatile heterocyclic compounds, which affect flavor and color. Relevant literature was identified through a structured search of PubMed and Web of Science; studies were included if they investigated MRPs in dairy products and reported antioxidant-related outcomes. This review offers a comprehensive overview of the MR in dairy products, systematically investigating the influence of protein, reducing sugars, and their ratios, as well as reaction conditions (process technology, temperature, time, pH, and water activity) on the formation and antioxidant activity of MRPs. The review also covers current applications and the future potential of MRPs as natural antioxidants in dairy products. Although MRPs effectively delay lipid oxidation and enhance stability in dairy products, research on their molecular structure and antioxidant mechanisms remains insufficient. Future research should focus on understanding the multifactorial synergistic effects within the complex dairy matrix, elucidating the molecular structure and extraction of antioxidant substances, and developing regulatory techniques to balance the antioxidant properties of MRPs with the safety concerns of potential harmful byproducts.

The Walrus Optimization (WO) algorithm, a metaheuristic inspired by walrus behavior, is known for its competitive convergence speed and effectiveness in solving high-dimensional and practical engineering optimization problems. However, it suffers from a tendency to converge to local optima and exhibits instability during the iterative process. To overcome these limitations, this study proposes an improved WO (IMWO) algorithm based on the integration of Differential Evolution/best/1 (DE/best/1) mutation, Logistics-Sine-Cosine (LSC) Mapping, and the Beta Opposition-Based Learning (Beta-OBL) strategy. These strategies work synergistically to enhance the algorithm's global exploration capability, improve its search stability, and accelerate convergence with higher precision. The performance of the IMWO algorithm was comprehensively evaluated using the CEC2017 and CEC2022 benchmark test suites, where it was compared against the original WO algorithm and six other state-of-the-art metaheuristics. Experimental data revealed that the IMWO algorithm achieved average fitness rankings of 1.66 and 1.33 in the two test suites, ranking first among all compared algorithms. The WSN coverage optimization problem aims to maximize the monitored area while reducing perception blind spots under limited node resources and energy constraints, which is a typical complex optimization problem with multiple constraints. In a practical application addressing the coverage optimization problem in Wireless Sensor Networks (WSNs), the IMWO algorithm attained average coverage rates of 95.86% and 96.48% in two sets of coverage experiments, outperforming both the original WO and other compared algorithms. These results confirm the practical utility and robustness of the IMWO algorithm in solving complex real-world engineering problems.

Cotton is an important economic crop, and its weed management directly affects yield and quality. In actual cotton fields, detection accuracy still faces challenges due to the complex types of weeds, variable morphologies, and environmental factors. Most existing models rely on the attention mechanism to improve performance, but channel attention tends to ignore spatial information, while full spatial attention brings high computational costs. Therefore, this paper proposes a grouped enhanced fusion attention mechanism (GEFA), which combines grouped convolution and local spatial attention to reduce complexity and parameter quantity while effectively enhancing feature expression ability. The GEFAY detection model constructed based on GEFA achieves good balance in efficiency, accuracy, and complexity on the CottonWeedDet12, VOC, and COCO datasets. Compared with classic attention methods, this model has the smallest increase in parameters and computational costs while significantly improving accuracy. It is more suitable for deployment on edge devices. The further designed end-to-end intelligent weed detection system and edge device deployment can achieve image detection on local maps and real-time cameras, with good practicality and scalability, providing effective technical support for intelligent visual applications in precision agriculture.

With the widespread adoption of the Internet of Things (IoT) and smart devices, the volume of data generated in sensor networks has increased dramatically, with diverse and structurally complex types that pose growing security risks. Anomaly detection in sensor networks has become a key technology for ensuring system stability and secure operation. This paper proposes a sensor anomaly detection model, termed RESTADM, which integrates a Transformer and a Radial Basis Function (RBF) neural network. The model first employs the Transformer to effectively capture the temporal dependencies in sensor data and then uses the RBF neural network to accurately identify anomalies. Experimental results on two public benchmark datasets, SMD and PSM, demonstrate the state-of-the-art performance of RESTADM. Our model achieves impressive F1-scores of 98.56% on SMD and 97.70% on PSM. This represents a statistically significant improvement compared to a range of baseline algorithms, including traditional models like CNN and LSTM, as well as the standard Transformer model. This validates the effectiveness of our proposed Transformer-RBF fusion, confirming the model’s high accuracy and robustness and offering an efficient security solution for intelligent sensing systems.

The pursuit of functional chalcoarsenates is of great significance for potential electrocatalytic oxygen evolution applications. Herein, two transition-metal polythioarsenate complexes {TM(tptz)[As2S2(μ2-S)(μ2-S2)]} [TM = Mn2+ (1a) and Cd2+ (1b), tptz = 2,4,6-tris-2-pyridyl-1,3,5-triazine] have been afforded by the solvothermal method. 1a and 1b contain a hitherto-unknown acentric cyclic [As2S2(μ2-S)(μ2-S2)]2- moiety that is built from two AsS subunits bridged by S2- and S22-. This [As2S2(μ2-S)(μ2-S2)]2- moiety serves as a bidentate chelating ligand to unsaturated complexes [TM(tptz)]2+, resulting in the rare TM polythioarsenate complexes. The energy gaps achieved from the UV-visible absorption spectrum are 1.33 eV for 1a and 1.31 eV for 1b, and 1a and 1b exhibit a remarkable photocurrent response under visible-light irradiation. 1a and 1b are utilized for the fabrication of the electrodes Ni/1a/NF and Ni/1b/NF (NF = porous Ni foam) as the electrocatalysts, which exhibit excellent oxygen evolution reaction (OER) activity with low overpotentials of 214 mV for Ni/1a/NF and 208 mV for Ni/1b/NF to achieve a current density of 10 mA·cm-2. This study not only enriches the structural type of chalcoarsenate complexes but also offers the only case of polythioarsenate complexes as OER electrocatalysts.

Munchausen syndrome is a complex type of abuse, which is offen underdiagnosed or misdiagnosed in clinical practice, and has harmful consequences for children. Its relationship with child abuse, of which it is a vanety, must be recognized in clinical and forensic practice. The authors report herein two observed of different types of Munchausen syndrome by proxy (MSbP). The first, the most severe form of MSbP, with induced, true illness and related pathological symptoms into victim. The second case is moderate form, much more complex to detect, in which a perpetrator parent simulates and aggravates the child's illness. Adequate training of health professionals and investigators is essential in revealing cases of MSbP. Diagnosis must be based on the study of the different forms of "abuse" and the knowledge of clinical protocols used to validate any suspected behaviour which could be potentially harmful to the child. Moreover, a lack of training may lead to misleading interpretations of medical history interpretation and fallacious conclusions. Our study aims to review the features that are to be considered in a suspected of MSbP, in accordance with recently updated consensus statement by the Committee on Child Abuse and Neglect from the American Academy of Pediatrics.

Background/Objectives: Fragility fractures of the pelvis (FFPs) are a significant concern in the elderly population, often leading to severe morbidity and mortality. This study aims to evaluate the diagnostic challenges, clinical outcomes, and mortality rates associated with FFPs in patients referred to multiple hospitals. Methods: A total of 99 patients with suspected pelvic fragility fractures were enrolled between January 2023 and June 2025. Initial diagnoses were made using plain X-rays, with computed tomography (CT) utilized to assess posterior ring fractures. Data on demographics, fracture types according to the Fragility Fracture of the Pelvis (FFP) Classification, hemoglobin levels, and mortality rates were collected and analyzed. Results: The findings revealed that while plain X-rays identified only anterior pelvic ring fractures, CT scans detected posterior ring fractures in 60.6% of cases. Patients with Nakatani II and III pelvic ramus fractures exhibited the most significant decreases in hemoglobin levels. The overall mortality rate was found to be 13.13%, with the highest rates observed in FFP I (13.5%) and FFP II (11.9%) groups. Conclusions: The findings of this study underscore the importance of CT imaging in the diagnosis of FFPs and highlight the need for close monitoring of hemoglobin levels in affected patients. This study also emphasizes the increased mortality risk associated with more complex fracture types. Future research should focus on evaluating functional independence and treatment outcomes to guide clinical decision-making in managing fragility fractures of the pelvis.

8-Hydroxyquinoline-based tetracoordinate boron complexes have been observed to exhibit pronounced luminescence and light-activated reactive oxygen species (ROS) generation, while their copper(II) analogs demonstrate significant cytotoxic effects in cancer cells. Nevertheless, both types of complexes are hindered by their inherent hydrophilicity, thereby limiting their efficacy in biological applications. Thus, we developed heavy-metal-free photosensitizers (PSs) based on 8-quinolinolato boron complexes, which exhibit light-activated fluorescence emission and ROS generation upon aggregation. The PSs effectively localize within lipid droplets and exhibit immediate and sustained ROS production upon exposure to light, even under hypoxic conditions, leading to lipid droplet-specific peroxidation, which is in accordance with the intracellular location, leading to ferroptosis-like cell death. Moreover, their fluorescence emission is quenched in the presence of Cu2+ ions, and the produced complexes enhance cytotoxicity instead. The photophysical properties of the complexes were comprehensively studied by a combination of experimental measurements, quantum mechanical (QM) and hybrid QM/molecular mechanics (MM) simulations. Thus, this investigation offers insights into new molecular design approaches for multifunctional probes with potential applications in photodynamic therapy and chemotherapy for cancer treatment.

The Pathfinder Algorithm (PFA) is a bionic swarm intelligence optimization algorithm inspired by simulating the cooperative movement of animal groups in nature to search for prey. Based on fitness, the algorithm classifies search individuals into leaders and followers. However, PFA fails to effectively balance the optimization capabilities of leaders and followers, leading to problems such as insufficient population diversity and slow convergence speed in the original algorithm. To address these issues, this paper proposes an enhanced pathfinder algorithm based on multi-strategy (EODE-PFA). Through the synergistic effects of multiple improved strategies, it effectively solves the balance problem between global exploration and local optimization of the algorithm. To verify the performance of EODE-PFA, this paper applies it to CEC2022 benchmark functions, three types of complex engineering optimization problems, and six sets of feature selection problems, respectively, and compares it with eight mature optimization algorithms. Experimental results show that in three different scenarios, EODE-PFA has significant advantages and competitiveness in both convergence speed and solution accuracy, fully verifying its engineering practicality and scenario universality. To highlight the synergistic effects and overall gains of multiple improved strategies, ablation experiments are conducted on key strategies. To further verify the statistical significance of the experimental results, the Wilcoxon signed-rank test is performed in this study. In addition, for feature selection problems, this study selects UCI real datasets with different real-world scenarios and dimensions, and the results show that the algorithm can still effectively balance exploration and exploitation capabilities in discrete scenarios.

ABSTRACTThis article presents a series of cases involving hepatic lenticular degeneration (Wilson's disease) complicated by renal tumors. It details the clinical manifestations, diagnostic procedures, treatment strategies, pathological features and outcomes of these patients. We found that this type of patient has an early‐onset disease, complex tumor pathological types, and may have a relatively poor prognosis. Through the analysis of these cases, we aim to enhance the understanding of this complex condition and provide valuable references for clinical practice.

Background:Lateral meniscal posterior root tears (LMPRTs) affect knee stability and load distribution. LMPRT repair with anterior cruciate ligament reconstruction (ACLR) demonstrated favorable functional outcomes and a high meniscal healing rate. However, most studies have reported only short-term follow-up results.Purpose:To evaluate the long-term clinical and radiologic outcomes of LMPRT repairs with ACLR.Study Design:Case series; Level of evidence, 4.Methods:Inclusion criteria consisted of patients who underwent LMPRT repair and hamstring ACLR from 2005 to 2019. Exclusion criteria were patients without postoperative magnetic resonance imaging (MRI), patients followed for <4 years, and patients who had reinjury. Healing of the repaired LMPRT was evaluated, and extrusion of the midbody of the lateral meniscus was measured by MRI. Joint space width (JSW) of the lateral compartment on the Rosenberg view was measured and compared preoperatively and at follow-up. Lysholm score and Tegner activity scale were compared between preoperative and follow-up periods.Results:Thirty-four patients were included, with a mean follow-up period of 96.8 ± 45.9 months (range, 48-200 months). Tear patterns of the LMPRT were classified into oblique (n = 22) and complex (n = 12) types. Follow-up MRI showed complete healing in 27, partial in 4, and none in 3. Follow-up extrusion was not significantly different from preoperative extrusion (1.31 ± 1.35 mm vs 1.46 ± 1.41 mm, P = .646). Preoperative lateral JSW did not show a significant decrease compared to follow-up lateral JSW (6.2 ± 1.1 mm vs 5.9 ± 0.8 mm, P = .18). Preoperative Lysholm score and Tegner activity scale improved significantly at follow-up (P < .001 and P < .001, respectively).Conclusion:At a mean 8-year follow-up, LMPRT repair with ACLR led to significant functional improvement and 91.1% complete or partial healing.

Homotopy types of Hom complexes of graph homomorphisms whose codomains are square-free

Abstract The urban constant-pressure water supply system is a typical nonlinear complex system. For such systems, conventional PID control often fails to adapt to multiple operating conditions, and the standard Particle Swarm Optimization (PSO) algorithm is susceptible to local optima when tuning PID parameters. To address these issues, a multi-strategy integrated improved Particle Swarm Optimization (MSIPSO) algorithm is proposed. The MSIPSO algorithm enhances population diversity via Kent chaotic mapping, incorporates a nonlinear adaptive inertia weight to balance global exploration and local exploitation capabilities, and employs the Levy flight strategy to prevent premature convergence. Experimental results on the CEC2005 benchmark functions demonstrate that the MSIPSO algorithm outperforms several comparative algorithms in both convergence accuracy and stability. Subsequently, the MSIPSO algorithm was applied for PID parameter tuning in the constant-pressure water supply system. The results indicate that the proposed MSIPSO-PID controller effectively reduces the overshoot, shortens the settling time, and consequently enhances the system's dynamic performance. This study thereby offers a viable solution for the optimal control of complex industrial processes.

This research analyzes the attraction mechanisms of large Chinese commercial complexes, explaining why this type of complex remains resilient in the digital shopping era. This paper begins with research on three mechanisms of spatial structure, atmospheric experience, and composite functions from both international and Chinese perspectives. This review shows that although these studies focus on similar points, existing research fails to form a unified explanation framework, due to the different country backgrounds and analytical views. To address this gap, this study introduces theories of behavioral economics and consumer psychology to understand how these three mechanisms operate. Building on this analysis, this research constructs an attraction model based on Stimulus, Organism, Response framework. Spatial structure, atmospheric cues, and composite functions work as environmental stimuli. They influence internal states such as pleasure, satisfaction, and loyalty, and then shape consumer behavior including dwell, exploration, and consumption tendency. This model provides a structured way to understand how Chinese commercial complexes guide consumer reactions. This research contributes to offer an integrated theoretical perspective by connecting fragmented findings into a unified framework. This provides a starting point for future empirical research that may examine mechanism strength, moderation effects, and regional differences. Therefore, this study pays a foundation for understanding the unique consumption logic in Chinese commercial complexes.

Purpose This study aims to enhance the classification of construction accident reports by addressing challenges including limited high-quality datasets, class imbalance and constraints of traditional machine learning models. A novel framework integrating ensemble learning with lightweight large language models (l-LLMs) is proposed to improve the accuracy, robustness and practical utility of safety management in the construction industry. Design/methodology/approach A dataset of 10,994 Occupational Safety and Health Administration (OSHA) construction accident reports was manually labeled using the Occupational Injury and Illness Classification System (OIICS). To address class imbalance, random oversampling and Synthetic Minority Oversampling Technique (SMOTE) were applied and compared. Five l-LLMs (TinyBERT, MobileBERT, ELECTRA, DistilBERT and ALBERT) were fine-tuned for classification, and three ensemble methods (soft voting, hard voting and stacking) were evaluated. Findings Random oversampling substantially improved performance, whereas SMOTE decreased effectiveness. Ensemble classifiers consistently outperformed individual large language models (LLMs), with the soft-voting ensemble achieving the highest F1 score (0.9261 ± 0.0063), surpassing baseline models support vector machine (SVM), Naïve Bayes (NB) and long short-term memory (LSTM) network. The results demonstrate the framework’s ability to accurately classify rare and complex accident types, supporting early hazard detection, targeted safety training and risk mitigation strategies. Originality/value The study advances construction safety analytics by integrating ensemble learning with l-LLMs, offering a robust solution for imbalanced textual datasets. It highlights practical applications, including enhanced safety management, decision support and accident prevention, with potential adaptation to other datasets and international contexts. By linking technical innovation to tangible societal and economic benefits, the framework contributes to safer, more efficient construction practices and promotes a culture of safety.