bluuebunny/crossref_metadata_2025 huggingface dataset:
Unveiling the Hidden Burden: A Systematic Review on the Prevalence and Clinical Implications of Calcified Brain Metastases
Authors: Garaba Alexandru , Panciani Pier Paolo , Da’ana Aida , Ius Tamara , Tel Alessandro , Fontanella Marco Maria , Zeppieri Marco , Ortolani Fulvia , Agosti Edoardo
Published: December 2024

Background: Brain calcifications, found in various conditions, may be incidental or crucial for diagnosis. They occur in physiological changes, infections, genetic diseases, neurodegenerative conditions, vascular syndromes, metabolic disorders, endocrine disorders, and primary tumors like oligodendroglioma. While often incidental, their presence can be vital for accurate diagnosis. Brain metastases are the most common neoplastic lesions in adults, with their incidence increasing due to improved diagnostic tools and overall oncologic patient survival. Calcifications within brain metastases are uncommon, mostly seen in patients treated with radiation therapy (RT). Although cases of calcified brain metastasis (CBM) are reported, large recent studies are scarce and the real incidence remains unclear. This lack of data raises the risk of underestimating CBM in the differential diagnosis of brain calcifications, potentially leading to misdiagnosis and delayed treatment, particularly when calcifications are observed without prior RT. Aim: This systematic review sought to assess the incidence of CBM in patients with identified primary tumors who underwent brain chemotherapy (CT) for staging. Additionally, the study aimed to explore the primary tumor types more frequently linked to CBM and determine whether CBM manifested initially or post-RT. Methods: A comprehensive search was performed across prominent medical databases (PubMed, Cochrane Library, and Embase) until 20 January 2024. The employed search method incorporated pertinent Medical Subject Headings (MeSH) and keywords such as “calcification”, “brain metastasis”, and “CT scan”. Studies included in this review were publications focusing on CBM in patients with identified primary tumors who underwent brain CT for staging. Results: In a systematic review of 39 studies on CBM in patients with identified primary tumors, 98 papers were initially identified, with 52 chosen for full-text analysis. Among them, 39 were deemed eligible after excluding 13 for various reasons. The study investigates brain calcifications in 1115 patients with metastatic disease, revealing that 7.89% had brain metastases, with 25% showing calcifications ab initio. These calcifications were more common than previously reported, emphasizing the need for attention to intraparenchymal brain calcifications in oncologic patients. Most CBM originated from lung and breast adenocarcinomas, and their correlation with primary tumor calcifications was inconclusive. Conclusions: The study highlights the significance of identifying evolving lesions in oncologic patients, calling for increased awareness among neuroradiologists and shedding light on the prevalence and characteristics of CBM.
Predictive Modeling of Hospital Readmission of Schizophrenic Patients in a Spanish Region Combining Particle Swarm Optimization and Machine Learning Algorithms
Authors: Góngora Alonso Susel , Herrera Montano Isabel , De la Torre Díez Isabel , Franco-Martín Manuel , Amoon Mohammed , Román-Gallego Jesús-Angel , Pérez-Delgado María-Luisa
Published: December 2024

Readmissions are an indicator of hospital care quality; a high readmission rate is associated with adverse outcomes. This leads to an increase in healthcare costs and quality of life for patients. Developing predictive models for hospital readmissions provides opportunities to select treatments and implement preventive measures. The aim of this study is to develop predictive models for the readmission risk of patients with schizophrenia, combining the particle swarm optimization (PSO) algorithm with machine learning classification algorithms. The database used in the study includes a total of 6089 readmission records of patients with schizophrenia. These records were collected from 11 public hospitals in Castilla and León, Spain, in the period 2005–2015. The results of the study show that the Random Forest algorithm combined with PSO achieved the best results across the evaluated performance metrics: AUC = 0.860, recall = 0.959, accuracy = 0.844, and F1-score = 0.907. The development of these new models contributes to -improving patient care. Additionally, they enable preventive measures to reduce costs in healthcare systems.
Caterpillar-Inspired Multi-Gait Generation Method for Series-Parallel Hybrid Segmented Robot
Authors: Dou Mingyuan , He Ning , Yang Jianhua , He Lile , Chen Jiaxuan , Zhang Yaojiumin
Published: December 2024

The body structures and motion stability of worm-like and snake-like robots have garnered significant research interest. Recently, innovative serial–parallel hybrid segmented robots have emerged as a fundamental platform for a wide range of motion modes. To address the hyper-redundancy characteristics of these hybrid structures, we propose a novel caterpillar-inspired Stable Segment Update (SSU) gait generation approach, establishing a unified framework for multi-segment robot gait generation. Drawing inspiration from the locomotion of natural caterpillars, the segments are modeled as rigid bodies with six degrees of freedom (DOF). The SSU gait generation method is specifically designed to parameterize caterpillar-like gaits. An inverse kinematics solution is derived by analyzing the forward kinematics and identifying the minimum lifting segment, framing the problem as a single-segment end-effector tracking task. Three distinct parameter sets are introduced within the SSU method to account for the stability of robot motion. These parameters, represented as discrete hump waves, are intended to improve motion efficiency during locomotion. Furthermore, the trajectories for each swinging segment are determined through kinematic analysis. Experimental results validate the effectiveness of the proposed SSU multi-gait generation method, demonstrating the successful traversal of gaps and rough terrain.
A Scoping Review on Neighborhood Social Processes and Child Maltreatment
Authors: Seon Jisuk
Published: December 2024

Neighborhood contexts, such as structures and social processes, have been explored to understand the etiology of child maltreatment, through the application of an ecological framework in child maltreatment research. While two comprehensive reviews on the relationship between neighborhood structural characteristics and child maltreatment were conducted in the 2000s, no prior study has synthesized the impacts of neighborhood social processes on child maltreatment. This study critically reviews extant literature on the role of neighborhood social processes in child maltreatment by employing the scoping review method, in accordance with the PRISMA-ScR reporting guidelines. The final review included 41 studies between the 1970s and 2022. Findings from the 41 studies were mixed by types of social processes measures, analytic approaches, and types of maltreatment. Future research directions are discussed based on the summary of the key findings.
Experimental Investigation of Concrete Crack Depth Detection Using a Novel Piezoelectric Transducer and Improved AIC Algorithm
Authors: Li Weijie , Zhu Jintao , Mu Kaicheng , Yang Wenwei , Zhang Xue , Zhao Xuefeng
Published: December 2024

Ultrasonic pulse velocity (UPV) has shown effectiveness in determining the depth of surface-open cracks in concrete structures. The type of transducer and the algorithm for extracting the arrival time of the ultrasonic signal significantly impact the accuracy of crack depth detection. To reduce the energy loss in piezoceramic-based sensors, a high-performance piezoceramic-enabled smart aggregate (SA) was employed as the ultrasonic transducer. For the extraction of ultrasonic signal arrival time in concrete, a novel characteristic equation was proposed, utilizing the slope of the signal within a shifting window. This equation was subsequently applied to modify Maeda’s function, with the arrival time of ultrasonic waves defined as the moment corresponding to the minimum Akaike information criterion (AIC) value. Six plain concrete specimens with artificial cracks were prepared and one reinforced concrete beam with a load-induced crack was used for validation. The average deviation of the testing of 492 points on 12 human-made cracks was around 5%. The detection results of 11 measurement points of a crack in a reinforced concrete beam show that three measurement points have a deviation of about 17%. The experimental results demonstrated that the novel piezoelectric transducer and improved AIC algorithm exhibit high accuracy in detecting the depth of concrete cracks.
A Unified Deflection Theory Model for Multi-Tower Self-Anchored Suspension Bridges with Different Tower–Girder and Cable–Girder Connections
Authors: Guan Shiyu , Liao Dinghui , Zhang Yi , Shi Jun , Liu Shuang , Cao Hongyou
Published: December 2024

This study presents a unified analytical model for multi-tower self-anchored suspension bridges integrating tower–girder connections (TGCs) and cable–girder connections (CGCs) within the framework of deflection theory. The connections are modeled as horizontal springs, and governing equations are derived based on force equilibrium and compatibility conditions. A comparison with a nonlinear finite element analysis under various live load scenarios confirms the accuracy of the proposed model. A parametric analysis reveals that increasing the CGC stiffness reduces girder deflection, decreasing the maximum vertical deflection by nearly 42.3% when the stiffness is increased from 0 to infinity and moving the maximum displacement from the mid-span section to the mid-tower section. Additionally, CGCs modify the load distribution between the main cable and the girder, limiting the longitudinal displacement of the tower in which the mid-tower displacement is reduced by 45.50%. Tower–girder connections improve the anchoring of the side cable to the tower. When connection stiffness is low, side- and middle-tower stiffness significantly reduce girder deflection, though this effect decreases with increasing stiffness. Enhancing mid-tower stiffness similarly reduces its longitudinal displacement regardless of the tower–girder connection. In longitudinal floating systems, mid-tower displacement rises with increasing side-tower stiffness. Establishing a unified analysis model reveals the key parameters in the structural analysis of suspension bridges, enabling an easier and faster analysis of multi-tower self-anchored suspension bridges.
Research on Fusion Model Method for Corrosion Damage Detection of Switch Sliding Baseplate
Authors: Gao Ruipeng , Shang Wenjie , Zhao Yan , Liu Mengmeng
Published: December 2024

As the core component of railways, the switch sliding baseplate has a bad operating environment, and its surface is prone to corrosion. Existing methods, including traditional methods, ultrasonic detection, and image processing, have difficulty in extracting corrosion features and being applied in practice. To solve the above problems, the Residual Neural Network 50 (ResNet50) model, a deep learning model, is introduced in this paper. To solve the problems of gradient explosion and weak corrosion in the model, a new fusion model, VGG-ResNet50-corrosion (VGGRES50_Corrosion), is proposed in this paper. First of all, for the problem that there is no public dataset, this study conducts a neutral salt spray corrosion test and collects the image features and corrosion depth parameters of skateboard corrosion in different time periods as the dataset to test the performance of the model. Then, corrosion thickness is introduced as a modified variable in the ResNet50 network, and a new network, VGGRES50_Corrosion, is introduced by blending the improved model with the Visual Geometry Group-16 (VGG16) network through a model fusion strategy. Finally, a model test and ultrasonic contrast test are designed to verify the performance of the model. In the model test, the recognition accuracy of the fusion model is 98.98% higher than that of other models, which effectively solves the shortcoming of the gradient explosion’s weak generalization ability under a small sample model. In the ultrasonic comparison experiment, the mean relative errors of this method and ultrasonic detection method are 4.08% and 46.41%, respectively, and the mean square errors are 1.86 h and 15.01 h, respectively. The prediction result of deep learning is better than that of ultrasonic piecewise linear fitting. It has been proved that VGGRES50_Corrosion can identify the degree of corrosion of slip switches more effectively, and it has great significance in improving the corrosion detection efficiency of slip switches.
Immersive Spatial Computing: How Technology Can Improve Science Content Reading and Vocabulary in Elementary Schools
Authors: Annetta Leonard , Johnson Ashley , Newton Mark H. , Franco Yvonne
Published: December 2024

Elementary school curricular standards in the United States emphasize mathematics and literacy, while social studies and science are often left behind. Integrating science instruction with either mathematics or literacy is a strategy some teachers use to teach skills and concepts in both disciplines. Understanding science at a young age is reliant on grasping vocabulary that is new to the learner. Integrating visual imagery into reading instruction improves students’ comprehension, enhances retrieval, and increases retention. The media-based reading enhancement of text through spatial computing has begun to show promise for the integration of science vocabulary and reading comprehension, especially for low-proficiency readers. This paper provides a literary rationale for technology-enhanced intervention, provides examples of a study conducted to test the efficacy of such an intervention, presents the implications of the study’s findings, and discusses future avenues for how spatial computing might be used in science and literacy instruction in the future.
A Significant Wave Height Prediction Method Based on Improved Temporal Convolutional Network and Attention Mechanism
Authors: Han Ying , Tang Jiaxin , Jia Hongyun , Dong Changming , Zhao Ruihan
Published: December 2024

Wave prediction is crucial for ensuring the safety and disaster mitigation of coastal areas, helping to support marine economic activities. Currently, many deep learning models, such as the temporal convolutional network (TCN), have been applied to wave prediction. In this study, a prediction model based on improved TCN-Attention (ITCN-A) is proposed. This model incorporates improvements in two aspects. Firstly, to address the difficulty of calibrating hyperparameters in traditional TCN models, a whale optimization algorithm (WOA) has been introduced to achieve global optimization of hyperparameters. Secondly, we integrate dynamic ReLU to implement an adaptive activation function. The improved TCN is then combined with the attention mechanism to further enhance the extraction of long-term features of wave height. We conducted experiments using data from three buoy stations with varying water depths and geographical locations, covering prediction lead times ranging from 1 h to 24 h. The results demonstrate that the proposed integrated model reduces the RMSE of prediction by 12.1% and MAE by an 18.6% compared with the long short-term memory (LSTM) model. Consequently, this model effectively improves the accuracy of wave height predictions at different stations, verifying its effectiveness and general applicability.
Detect Insider Threat with Associated Session Graph
Authors: Ding Junmei , Qian Peng , Ma Jing , Wang Zhiqiang , Lu Yueming , Xie Xiaqing
Published: December 2024

Insider threats pose significant risks to organizational security, often leading to severe data breaches and operational disruptions. While foundational, traditional detection methods suffer from limitations such as labor-intensive rule creation, lack of scalability, and vulnerability to evasion by sophisticated attackers. Recent advancements in graph-based approaches have shown promise by leveraging behavior analysis for threat detection. However, existing methods frequently oversimplify session behaviors and fail to extract fine-grained features, which are critical for identifying subtle malicious activities. In this paper, we propose a novel approach that integrates session graphs to capture multi-level fine-grained behavioral features. First, seven heuristic rules are defined to transform user activities across different hosts and sessions into an associated session graph while extracting features at both the activity and session levels. Furthermore, to highlight critical nodes in the associated session graph, we introduce a graph node elimination technique to normalize the graph. Finally, a graph convolutional network is employed to extract features from the normalized graph and generate behavior detection results. Extensive experiments on the CERT insider threat dataset demonstrate the superiority of our approach, achieving an accuracy of 99% and an F1-score of 99%, significantly outperforming state-of-the-art models. The ASG method also reduces false positive rates and enhances the detection of subtle malicious behaviors, addressing key limitations of existing graph-based methods. These findings highlight the potential of ASG for real-world applications such as enterprise network monitoring and anomaly detection, and suggest avenues for future research into adaptive learning mechanisms and real-time detection capabilities.
Optimal Implementation of Tapped Delay Line Time-to-Digital Converters in 20 nm Xilinx UltraScale FPGAs
Authors: Morabito Mattia , Lusardi Nicola , Garzetti Fabio , Fiumicelli Gabriele , Bonanno Gabriele , Ronconi Enrico , Costa Andrea , Geraci Angelo
Published: December 2024

This study investigated implementation strategies to optimize the precision of Tapped Delay Line (TDL) Time-to-Digital Converters (TDCs) designed for Xilinx 20 nm UltraScale Field-Programmable Gate Arrays (FPGAs). This optimization process aims to bridge the performance gap between FPGA-based TDCs, which are more flexible and suitable for fast prototyping, and the better-performing Application-Specific Integrated Circuit (ASIC) solutions, making FPGA-based TDCs viable for cutting-edge applications. Our key areas of focus included the optimal design of the decoder, the degree of sub-interpolation, and the placement of TDLs, with particular emphasis on the clocking distribution scheme within the Configurable Logic Block (CLB) to minimize the effects of Bubble Errors (BEs) and quantization error. The research led to the development and comparison of multiple TDL TDC solutions implemented on a Kintex UltraScale device (i.e., XCKU040-2FFVA1156E) housed on a KCU105 general-purpose Evaluation Board (EVB). From these, two main solutions emerged: one with high precision and one with low area. The first one was characterized by a Single-Shot Precision (SSP) of 2.64 ps r.m.s., and by Differential and Integral Non-Linearity (DNL/INL) Errors of 0.523 ps and 16.939 ps, respectively, occupying 883 CLBs and 126 kb of Block RAM (BRAM). The second one had an SSP of 3.75 ps r.m.s., a DNL of 0.599 ps, and an INL of 7.151 ps, and it occupies only 259 CLBs and 72 kb of BRAM.
Acdim: A Cardiovascular Disease Risk Prediction Model Based on TabNet and AdaBoost for Smart Aging
Authors: Zhou Feng , Hu Shijing , Du Xiaozheng , Lu Zhihui , Zhou Tongming , Zhao Yanni , Zhu Huaizhong
Published: December 2024

Cardiovascular disease is a typical chronic disease. The incidence of cardiovascular disease in the elderly population has grown to exceed 50%. The further aging of the current population has brought additional pressure on public health services. Therefore, to reduce the service pressure of medical institutions, accurate prediction of cardiovascular disease risk has become an essential task in intelligent elderly care. In order to achieve accurate prediction of cardiovascular disease risk, we propose a cardiovascular disease risk prediction model Acdim (a cardiovascular disease risk prediction model) based on ResNet (Residual Network), zebra optimization algorithm (ZOA), TabNet (Attentive Interpretable Tabular Learning), and AdaBoost (Adaptive Boosting) algorithms. In training the Acdim model, we used the dat set of the World Health Organization (WHO) Behavioral Risk Factor Monitoring System records. In the experiment, the Acdim model achieved an accuracy of 96%, a precision of 94%, a recall of 93%, a specificity of 95%, an F1 score of 91%, and an AUC of 95%. The experimental results show that the proposed Acdim model can enable elderly care institutions to accurately predict the risk of cardiovascular disease in the absence of doctors.
Cross-Project Software Defect Prediction Using Differential Perception Combined with Inheritance Federated Learning
Authors: Wang Aili , Feng Yanxiang , Yang Mingji , Wu Haibin , Iwahori Yuji , Chen Haisong
Published: December 2024

Cross-project software defect prediction (CPDP) refers to the construction of defect prediction models by collecting multi-source project data, but the heterogeneity of data among projects and the modern problem of “data islands” hinder its development. In response to these challenges, we propose a CPDP algorithm based on differential perception combined with inheritance federated learning (FedDPI). Firstly, we design an efficient data preprocessing scheme, which lays a reliable data foundation for federated learning by integrating oversampling and optimal feature selection methods. Secondly, a two-stage collaborative optimization mechanism is proposed in the federated learning framework: the inheritance private model (IPM) is introduced in the local training stage, and the differential perception algorithm is used in the global aggregation stage to dynamically allocate aggregation weights, forming positive feedback for training to overcome the negative impact of data heterogeneity. In addition, we utilize the Ranger optimization algorithm to improve the convergence speed and privacy security of the model through its irreversible mixed optimization operation. The experimental results show that FedDPI significantly improves predictive performance in various defect item data combination experiments. Compared with different deep learning and federated learning algorithms, the average improvement in AUC and G-mean indicators is 0.2783 and 0.2673, respectively, verifying the practicality and effectiveness of federated learning and two-stage collaborative optimization mechanisms in the field of CPDP.
Forests and Their Related Ecosystem Services: Visitors’ Perceptions in the Urban and Peri-Urban Spaces of Timișoara, Romania
Authors: Crețan Remus , Chasciar David , Dragan Alexandru
Published: December 2024

Urban and peri-urban forests serve as significant drivers, conferring benefits to humans through engagement with their ecosystems. These benefits encompass recreation, cognitive development, introspection, the acquisition of knowledge systems, social relations, and aesthetic values. The aim of this study is to examine the urban and peri-urban ecosystem services by offering new insights into visitors’ perspectives on the recreational, aesthetic, and spiritual values of forests in the city of Timișoara and its peri-urban area. The study focuses on two forests: Padurea Verde, the largest forest in Timișoara, and the Giroc Forest, one of the most frequently visited forest areas in the peri-urban zone of Timișoara. Thirty-six in-depth interviews were conducted with visitors to the two selected forests in September 2024. The findings indicate that visitors derive benefits from the ecosystem values of these forests, including recreational, aesthetic, and cultural values. However, there are also feelings of disappointment related to the lack of cleanliness and the presence of an excessive number of stray dogs in the forests. The findings also indicate a necessity for the implementation of organized activities, such as sports competitions and more children-oriented events, while discouraging the organization of festivals and the excessive use of noise in forests. Furthermore, they suggest that forests should be maintained in a relatively undisturbed state. These findings could prove beneficial as future perspectives for local practitioners, enabling the continued provision of complex ecosystem services and recreational values by urban and peri-urban forests.
Magnetically Induced Anisotropic Microstructures on Polyethylene Glycol Hydrogel Facilitate BMSC Alignment and Osteogenic Differentiation
Authors: Zhang Hua , Luo Yang , Xu Rong , Cao Xu , Li Guanrong , Chen Shang
Published: December 2024

Many tissues exhibit structural anisotropy, which imparts orientation-specific properties and functions. However, recapitulating the cellular patterns found in anisotropic tissues presents a remarkable challenge, particularly when using soft and wet hydrogels. Herein, we develop self-assembled anisotropic magnetic Fe3O4 micropatterns on polyethylene glycol hydrogels utilizing dipole–dipole interactions. Under the influence of a static magnetic field, Fe3O4 nanoparticles align into highly ordered structures with a height of 400–600 nm and a width of 8–10 μm. Furthermore, our layer-by-layer assembly technique enables the creation of oriented micropatterns with varying densities and heights, which can be further manipulated to form three-dimensional structures by adjusting the angle of the magnetic field. These anisotropic magnetic Fe3O4 micropatterns can be applied to various substrates, including treated glass slides, standard glass slides, silicon wafers, and polydimethylsiloxane. The patterned Fe3O4 scaffolds, modified with gold coating, effectively enhance cellular adhesion, orientation, and osteogenic differentiation of bone marrow-derived stem cells, which is crucial for effective tissue repair. Overall, this study presents an efficient strategy for constructing anisotropic Fe3O4 micropattern hydrogels, providing a bioactive platform that significantly enhances cellular functions.
RNA-Seq Analysis Uncovered Transcriptomic Changes in Poncirus trifoliata Roots Under Long-Term Soil Drought Conditions
Authors: Song Chuncao , Zeng Xingying , Zheng Lin , Huang Qin , Zhong Lingshan , Zhou Yong , Yin Hengfu , Peng Yanjie
Published: December 2024

Drought is one of the most serious abiotic stresses in citrus plantations. It is thus imperative to fully understand the drought-resistant mechanisms in these plants. Here, RNA-seq was used to analyze the transcriptomic changes in the roots of Poncirus trifoliata, a widely used rootstock in citrus plantations, under a 72-day soil drought and a 7-day recovery stage. Our results showed that the genes upregulated under drought were only enriched in the galactose metabolism and protein processing in endoplasmic reticulum pathways. In the galactose metabolism pathway, four genes related to the synthesis of raffinose family oligosaccharides, which act as osmoprotectants and ROS scavengers, were significantly upregulated under long-term drought. Several heat-shock protein (HSP) family genes were significantly upregulated under drought, leading to increased levels of HSPs to alleviate the endoplasmic reticulum-associated degradation of misfolded proteins induced by drought stress. Some other upregulated genes under drought, like late embryogenesis-abundant family genes and lipid transfer protein family genes, might also be crucial to the drought resistance of P. trifoliata roots. MSYJ196370 (heat-shock factor family gene) was the top hub gene in the protein–protein interaction analysis of upregulated genes under drought. These findings supplement the transcriptomic response of P. trifoliata root under long-term drought stress.
Research on Evolutionary Game of Adopting Blockchain-Based Automotive Traceability
Authors: Tang Xiaoyu , Li Shouwei , Li Jingwei , Zhang Yonghong
Published: December 2024

To adopt the blockchain-based automobile traceability system (BCATS) and increase the transparency of the Chinese auto market, this study constructs a tripartite evolutionary game model of manufacturers, regulators, and consumers, discusses the evolutionary stabilization strategy (ESS) under different cases, and analyzes the influencing factors on the tripartite ESS through numerical simulation. The study finds that there exists an ESS of blockchain adoption and tripartite cooperation, and it is influenced by different factors including blockchain construction cost, traceability service price, and government subsidy. Lowering the blockchain construction cost, and increasing the traceability service price and government subsidy can all have a positive impact on accomplishing the ideal ESS, but the latter two can also have a negative impact when they are beyond the scope of effectiveness. The study results provide practical recommendations for adopting blockchain in the auto traceability, which can help to promote blockchain in the Chinese auto market.
Effects of Ti and Sn Substitutions on Magnetic and Transport Properties of the TiFe2Sn Full Heusler Compound
Authors: Popescu Bogdan , Assahsahi Ilhame , Galatanu Magdalena , Galatanu Andrei
Published: December 2024

The synthesis of polycrystalline TiFe2Sn samples by a route including arc melting and spark plasma sintering with Hf, Y, and In substitutions at the Ti and Sn sites is investigated. For a reduced amount of substitution, around 2 at%, the samples are single phase, while for increased amounts, secondary phases segregate. As is characteristic of these compounds, the Fe-Ti atomic disorder generates a weak ferromagnetic ordering, which is also influenced by the type of substitutional atoms and the secondary phases in the samples with a higher Hf content. The Seebeck coefficient values show an increase for Ti0.98Hf0.02Fe2Sn and for samples with an adjusted Sn content, resulting in slightly increased power factor values. These values reach a maximum for Ti0.98Hf0.02Fe2Sn at approximately 300 K and for TiFe2Sn1.05 at approximately 325 K, namely, 2.69 × 10⁻4 Wm−1K−2 and 2.52 × 10⁻4 Wm−1K−2, respectively. The thermal conductivity of all the samples with substitutions increases with respect to the pristine sample. The highest figure of merit value of 0.016 is also obtained for Ti0.98Hf0.02Fe2Sn at 325 K.
Functions of Insulin-like Peptide Genes (CsILP1 and CsILP2) in Female Reproduction of the Predatory Ladybird Coccinella septempunctata (Coleoptera: Coccinellidae)
Authors: Feng Shanshan , Wang Da , Qin Qiuju , Chen Ke , Zhang Wenjing , He Yunzhuan
Published: December 2024

Insulin-like peptides (ILPs) are important peptide hormones in insects, particularly involved in regulating physiological processes such as growth, development, and reproduction. However, the specific roles of ILPs in the reproduction of natural enemy insects remain unknown. In this study, two ILP genes, CsILP1 and CsILP2, were cloned and their functions were analyzed in female Coccinella septempunctata L. (Coleoptera: Coccinellidae). The open reading frames (ORFs) of CsILP1 and CsILP2 were 384 bp and 357 bp, respectively. The expression of CsILP1 increased on the 6th day after eclosion, reaching its peak on the 12th day, while CsILP2 levels showed a significant increase on the 6th day and then stabilized. In different tissues, CsILP1 was highly expressed in ovaries, while CsILP2 predominated in elytra. Injection of dsRNA targeting CsILP1 and CsILP2 resulted in the down-regulation of insulin pathway genes. The relative expression of ovarian development-related genes Vasa, G2/M, and Vg was reduced by 82.50%, 89.55%. and 96.98% in dsCsILP1-treated females, and by 42.55%, 91.36%, and 55.63% in dsCsILP2-treated females. Furthermore, substantial decreases in 14-day fecundity were observed, with reductions of 89.99% for dsCsILP1 and 83.45% for dsCsILP2. These results confirm the regulatory functions of CsILP1 and CsILP2 in female C. septempunctata reproduction.
Bumblebee Abundance in Species-Rich Grasslands in Southern Sweden Decreases with Increasing Amount of Arable Land at a Landscape Level
Authors: Milberg Per , Bergman Karl-Olof , Fjellander Gabriella , Tälle Malin , Westerberg Lars
Published: December 2024

Conservation of bumblebee populations is essential because of their role as pollinators. Declines in bumblebee abundance have been documented in recent decades, mostly attributed to agricultural intensification, landscape simplification and loss of semi-natural grasslands. In this study, we investigated the effects of landscape composition on bumblebee abundance at different spatial scales in 476 semi-natural grassland sites in southern Sweden. The area of arable land had a negative effect on total bumblebee abundance at all scales. This was most pronounced for short-tongued bumblebees, species typical of forested landscapes, and species with medium to large colony sizes and early queen emergence. The area of semi-natural grassland had a clear negative effect up to 1 km, affecting short-tongued bumblebees in both forested and agricultural landscapes and species with medium colony sizes and early queen emergence. The negative effect of arable land on bumblebees calls for action to adapt farming practices to ensure their conservation, e.g., by reducing pesticide use, improving crop diversity and promoting the presence of floral resources and alternative bumblebee habitats, such as species-rich field margins.
Effect of Anesthetic Modality on Decision-to-Delivery Interval and Maternal–Neonatal Outcomes in Category 2 and 3 Cesarean Deliveries
Authors: Pečlin Polona , Pavlica Maja , Druškovič Mirjam , Kavšek Gorazd , Verdenik Ivan , Pintarič Tatjana Stopar
Published: December 2024

Background/Objectives: The optimal anesthetic technique for category 2 and 3 cesarean deliveries remains debated, with concerns about impacts on decision-to-delivery interval (DDI) and perinatal outcomes. This study examined the influence of epidural, spinal, and general anesthesia on DDI, surgical and postoperative complications, and neonatal outcomes. Methods: This prospective cohort study at a tertiary perinatology center enrolled parturient women undergoing category 2 and 3 cesarean deliveries. Three DDI phases were assessed for each anesthetic modality: transfer time (decision for cesarean section to admission in the operation room), anesthetic time (admission to incision), and delivery time (incision to delivery of the neonate). The surgical procedure time (incision to closure), neonatal (5 min Apgar score, umbilical artery pH/base excess, neonatal intensive care unit (NICU) admission) and maternal (blood loss, surgical and postoperative complications) outcomes were also analyzed for each group. Results: There were 215 women (122 category 2 and 93 category 3) included. The use of epidural and general anesthesia was associated with significantly shortened DDI compared to spinal anesthesia (p < 0.001). This difference was due prolonged transfer (p < 0.05) and anesthetic times (p < 0.001), respectively. No cases of umbilical artery pH below 7 were observed in any group. No significant differences were observed in the incidence of umbilical artery pH between 7 and 7.10 or in base excess below −12 nmol/L (p = 0.416 and p = 0.865, respectively). NICU admission was higher with both general and spinal anesthesia (p = 0.021), but mainly due to a higher proportion of preterm births, both before the 32nd week (p = 0.033) and between the 32nd and 37th week of pregnancy (p < 0.001). General anesthesia was associated with higher maternal blood loss (p = 0.026) and a higher rate of postoperative complications (p = 0.006). Conclusions: In category 2 and 3 cesarean deliveries, general and epidural anesthesia were associated with shorter DDI compared to spinal anesthesia with no differences in neonatal outcomes. General anesthesia was associated with a higher risk of maternal complications compared to neuraxial anesthetic techniques.
Endometriosis Coinciding with Uterus Didelphys and Renal Agenesis: A Literature Review
Authors: Dayan Davut , Ebner Florian , Janni Wolfgang , Hancke Katharina , Adiyaman Duygu , Huener Beate , Hensel Michelle , Hartkopf Andreas Daniel , Schmid Marinus , Lukac Stefan
Published: December 2024

Background/Objectives: Endometriosis and urogenital malformation with uterus didelphys and renal agenesis might occur concomitantly, and the question arises whether both entities are associated with each other. Methods: A literature search was conducted in PubMed and Web of Science, using the following search terms: “endometriosis and uterine malformation, endometriosis and Herlyn–Werner–Wunderlich syndrome”, “endometriosis and OHVIRA (Obstructed Hemivagina and Ipsilateral Renal Anomaly) syndrome” and “uterus didelphys, renal agenesis and endometriosis”. Results: We identified and examined 36 studies, comprising a total of 563 cases with coinciding endometriosis and OHVIRA. The most prevalent symptoms were dysmenorrhea and lower abdominal pain. Renal agenesis occurred more frequently on the right side. In the majority of cases, vaginal septum resection was performed to alleviate hematometrocolpos. Among the 97 cases necessitating abdominal exploration, endometriosis was identified in 61 patients (62.9%), although this figure is most likely an overestimation. However, a significantly heightened risk of endometriosis was evident. Conclusions: This literature review highlights the importance of considering the potential for urogenital malformation and endometriosis in cases of dysmenorrhea during adolescence. Ultrasound examination has proven to be a valuable diagnostic tool for identifying uterine abnormalities and guiding subsequent diagnostic and, if necessary, surgical interventions. Thorough assessment and appropriate management are imperative to mitigating the long-term consequences associated with deep infiltrating endometriosis.
Contemporary Issues in Postmastectomy Radiotherapy: A Brief Review
Authors: Grace Caroline A. , McKay Michael J.
Published: December 2024

Breast cancer is the one of the most common cancers and causes a significant disease burden. Currently, postmastectomy radiotherapy (PMRT) is indicated for breast cancer patients with higher risk of recurrence, such as those with positive surgical margins or high-risk breast cancer (T3 with positive lymph nodes, ≥4 positive lymph nodes or T4 disease). Whether PMRT should be used in intermediate-risk breast cancer (T3 with no positive lymph nodes or T1-2 with 1-3 positive lymph nodes) is contentious. Rates of breast reconstruction postmastectomy are increasing in countries like Australia, and PMRT usage in such settings is another area of active research. Ongoing trials are also assessing the safety and efficacy of hypofractionated PMRT, a clinical scenario now widely accepted for early-stage breast cancer. This brief review is unique in that it aims to examine three current and controversial aspects of the PMRT field (PMRT in intermediate-risk breast cancer, PMRT in conjunction with breast reconstruction and its hypofractionation). To achieve this aim, we discuss available and emerging literature and guidelines to offer insights important to the PMRT field. Current literature suggests that PMRT could play a role in improving the overall survival rate and in reducing locoregional recurrence in intermediate-risk breast cancer. In terms of recommending a timing or type of breast reconstruction best suited to the setting of PMRT, we found that individual patient preferences and circumstances need to be considered alongside a multidisciplinary approach. Research into PMRT hypofractionation safety and efficacy is ongoing and its place remains to be elucidated.
Epidemiology of Latent Tuberculosis in Rheumatic Immune-Mediated Inflammatory Diseases—Study of 1117 Patients and Descriptive Literature Review
Authors: Osorio-Chávez Joy Selene , Martínez-López David , Álvarez-Reguera Carmen , Portilla Virginia , Cifrián José Manuel , Castañeda Santos , Ferraz-Amaro Iván , Blanco Ricardo
Published: December 2024

Background/Objectives: Patients with rheumatic immune-mediated diseases (rheumatic-IMID) and latent tuberculosis (LTBI) are at an increased risk of developing active tuberculosis (TB); therefore, screening is recommended before starting biological treatment. The aims of this study were as follows: (i) to assess the prevalence of LTBI, (ii) to determine the importance of using a booster test in TST-negative patients, (iii) to compare the tuberculin skin test (TST) with the interferon-gamma release assay (IGRA), (iv) to perform a review of the prevalence of LTBI. Methods: A cross-sectional hospital study was performed, including patients diagnosed with rheumatic-IMID who underwent a TST and/or IGRA during the period 2016–2020. If the first TST was negative, a new TST (booster) was performed. Results: A total of 1117 patients were included. The overall prevalence of LTBI was estimated to be 31.7% (95% confidence interval, 29.74–33.66). The LTBI prevalence ranged from 38.5% for vasculitis to 14% for sarcoidosis. The booster test was positive in 22.9% of 817 patients with a negative or indeterminate IGRA. The IGRA was positive in 3.8% of 793 patients with a negative booster.The adjusted Cohen’s kappa coefficient between TST (+booster) and IGRA was 0.62. Conclusions: LTBI is frequent in patients with rheumatic-IMID. IGRA and TST (+booster) show a moderate, fair grade of agreement. Therefore, performing both tests before biological therapy should be highly recommended.
Regulatory Role of Vacuolar Calcium Transport Proteins in Growth, Calcium Signaling, and Cellulase Production in Trichoderma reesei
Authors: Oshiquiri Letícia Harumi , Pereira Lucas Matheus Soares , Maués David Batista , Milani Elizabete Rosa , Silva Alinne Costa , Jesus Luiz Felipe de Morais Costa de , Silva-Neto Julio Alves , Veras Flávio Protásio , de Paula Renato Graciano , Silva Roberto Nascimento
Published: December 2024

Recent research has revealed the calcium signaling significance in the production of cellulases in Trichoderma reesei. While vacuoles serve as the primary calcium storage within cells, the function of vacuolar calcium transporter proteins in this process remains unclear. In this study, we conducted a functional characterization of four vacuolar calcium transport proteins in T. reesei. This was accomplished by the construction of the four mutant strains ∆trpmc1, ∆tryvc1, ∆tryvc3, and ∆tryvc4. These mutants displayed enhanced growth when subjected to arabinose, xylitol, and xylose. Furthermore, the mutants ∆trpmc1, ∆tryvc1, and ∆tryvc4 showed a reduction in growth under conditions of 100 mM MnCl2, implying their role in manganese resistance. Our enzymatic activity assays revealed a lack of the expected augmentation in cellulolytic activity that is typically seen in the parental strain following the introduction of calcium. This was mirrored in the expression patterns of the cellulase genes. The vacuolar calcium transport genes were also found to play a role in the expression of genes involved with the biosynthesis of secondary metabolites. In summary, our research highlights the crucial role of the vacuolar calcium transporters and, therefore, of the calcium signaling in orchestrating cellulase and hemicellulase expression, sugar utilization, and stress resistance in T. reesei.
Heart Disease and Pectus Excavatum: An Underestimated Issue—Single Center Experience and Literature Review
Authors: Ravasin Alice , Viggiano Domenico , Tombelli Simone , Checchi Luca , Stefàno Pierluigi , Voltolini Luca , Gonfiotti Alessandro
Published: December 2024

Pectus excavatum (PE) can be associated with either congenital or acquired heart disease. This study highlights the importance of PE surgical repair in cases of severe chest depression on the heart in underlying cardiac diseases exacerbating cardiopulmonary impairment. From January 2023 to March 2024, four male patients underwent PE repair, having heart disease including pericarditis, mitral valve prolapse, ventricular fibrillation arrest and type 1 second-degree atrioventricular block. PE severity was determined by the Haller index (HI). Preoperative assessment included a pulmonary function test, chest computed tomography and cardiac evaluation. The Nuss procedure was performed in three patients, whereas, in one patient, it was performed in combination with a modified Ravitch procedure. The median HI was five. The median time of chest tube removal was 6.5 days. Postoperative complications were prolonged air leak, atrial fibrillation and atelectasis. The median length of hospital stay was 19.5 days, and no 30-day postoperative mortality was recorded. In all patients, surgical repair helped to resolve the underlying cardiological issues, and surgical follow-ups were deemed regular. PE is generally an isolated congenital chest wall abnormality, and, when associated with a heart disease, it can have severe life-threatening hemodynamic consequences due to mechanical compression on the heart for which surgical corrections should be considered.
Effect of Hot Water Bottle and Cloth Blanket on Rectal Temperature During Magnetic Resonance Imaging of the Head in Cats Under General Anesthesia
Authors: Pavel Ruxandra , Fernoagă Cristina , Neagu Alexandru Gabriel , Costea Ruxandra
Published: December 2024

Maintaining an animal’s body temperature during magnetic resonance imaging (MRI) poses great challenges, as many temperature measuring devices and warming systems are incompatible with the MRI machine. The aim of this study was to examine body temperature changes and evaluate the impact of using a hot water bottle and a cloth blanket on rectal temperature during magnetic resonance imaging in cats. We included in this study 30 cats from different breeds that underwent magnetic resonance imaging for 60 min that were randomly divided into a passively insulated group (G1) covered with a blanket (n = 15) and a positively heated group (G2) using a silicone hot water bottle under the abdomen and the same cloth blanket over the cat (n = 15). The body temperature was measured before premedication, before induction of anesthesia, and after the MRI examination. Body temperature decreased slightly but significantly (p < 0.05) after premedication. At the end of the MRI, body temperature had decreased more in G1 than G2 (p = 0.033) to 37.0 (36.5–37.5) °C and 38 (37.9–38.2) °C, respectively. This study provides clinical evidence that cats needing magnetic resonance imaging of the head can be protected from hypothermia by using a hot water bottle placed underneath their abdomen and a cloth blanket covering their full body.
A PDE-ODE Coupled Model for Biofilm Growth in Porous Media That Accounts for Longitudinal Diffusion and Its Effect on Substrate Degradation
Authors: Bottomley Emma , Eberl Hermann J.
Published: December 2024

We derive a one-dimensional macroscopic model for biofilm formation in a porous medium reactor to investigate the role of longitudinal diffusion of substrate and suspended bacteria on reactor performance. By comparing an existing base model—one without longitudinal diffusion, which was the point of departure for our work, to the new model—we noticed significant changes in system dynamics. Our results suggest that neglecting it can lead to underestimation of quenching length and biofilm accumulation downstream, even in the advection-dominated regime. The effects of attachment and detachment of suspended bacteria on biofilm formation and substrate degradation were also examined. In the one-dimensional model, it was found that attachment has a stronger influence on substrate depletion, which becomes more pronounced as diffusion in the pore space increases.